Emissions and Efficiencies of Rural Wood

Transcription

Emissions of Rural Wood-Burning
Cooking Devices
Grant Ballard-Tremeer
A thesis submitted to the Faculty of Engineering, University of the
Witwatersrand, Johannesburg, in fulfilment of the requirements for the
degree of Doctor of Philosophy.
Johannesburg, 1997
Declaration
This thesis is my own work. It is being submitted for the degree of Doctor of Philosophy in
the University of the Witwatersrand, Johannesburg. It has not been submitted before for
any degree or examination in any other University.
Grant Ballard-Tremeer
9th day of April 1997
Declaration
i
Abstract
Approximately 2500 million people are exposed daily to emissions from biofuel-burning
cooking sites. Respiratory disease, which is the main cause of death in developing
communities, is linked to these emissions. This thesis is an attempt to expand the
knowledge of emission testing of cooking devices used by the rural poor so that testing
guidelines may be developed.
Emissions of a number of cooking devices were measured directly in this study during
typical cooking cycles. Carbon monoxide, sulphur dioxide and total suspended particulate
concentrations were measured by placing the cooking devices under an extraction hood
with controlled extraction characteristics.
Four contributions towards the development of emission testing guidelines were made.
1) There was a measurable but small influence of the test rig on carbon monoxide
emissions. No effect of extraction could be detected at 95 % confidence for sulphur dioxide
and suspended particulates. There was no detectable interaction between stove type and
extraction level (at 95 % confidence). An extraction hood can therefore be used with
confidence to compare emissions from different stoves provided the extraction level is
unchanged between tests. 2) Stove performance was independent of the quantity of water
used and wood type. Stove type, the use of lids, and wood size had a significant effect on
emissions at 95 % confidence. It is therefore important when testing emissions that these
parameters be specified precisely. 3) It was found that the ratio between carbon monoxide,
sulphur dioxide and particulates varied during a test and was dependant on stove type.
The prediction of one pollutant from concentrations of another is therefore impossible –
each pollutant of interest should be measured separately. 4) The validity of assuming
constant emission rate in the indirect ‘chamber’ method favoured by many researchers
was tested by simulating numerically the pollutant concentrations which would have been
recorded in a chamber using the real time data collected in this study. Chamber method
accuracy, it was found, could be improved by regular stove refuelling, and an alternative
calculation method. Even so, results were biased (at 95 % confidence) and hence the
method cannot be recommended for cooking device comparisons.
Abstract
ii
Acknowledgements
I would like to thank Dr HH Jawurek for his tireless help and enthusiasm. He has inspired
and challenged me over the years and I have grown through his mentoring. I am greatly
indebted to him.
Dr DI Banks has provided many useful insights at crucial stages. I thank him for his
friendship and invaluable advice.
Professor H Annegarn and Mrs M Kneen of Annegarn Environmental Research helped
with the calibration of the smoke meter.
Dr G Helas of the Max Planck Institute for Chemistry, Mainz, Germany introduced the
world of atmospheric biogeochemistry to me.
Dr K Krishna Prasad and Professor Kirk R Smith gave clarifying comments many of
which have been incorporated into this version.
The Instituut Voor Milieuvraagstukken of the Vrije Universiteit, Amsterdam generously
made their computer and printing facilities available to me.
The Foundation for Research Development (FRD) and the University of the
Witwatersrand assisted financially.
Acknowledgements
iii
Contents
DECLARATION
i
ABSTRACT
ii
ACKNOWLEDGEMENTS
iii
CONTENTS
iv
FIGURES
ix
TABLES
xii
SYMBOLS
xiv
1 OVERVIEW
1.1 The extent of the problem
1
2
1.1.1 The health impact of combustion emissions
2
1.1.2 World-wide exposure to biofuel combustion products
3
1.1.3 Lack of alternatives
3
1.2 The gap in stove testing methods
4
1.2.1 The need for stove emission measurement
4
1.2.2 The difficulty of measuring emissions from stoves used by the rural poor
5
1.2.3 Historic focus on efficiency not emissions
5
1.2.4 The existing methods of emission measurement
7
1.2.5 Issues considered in this study
9
1.3 Summary
11
1.4 Thesis organisation
11
2 APPARATUS
13
2.1 Extraction booth
14
2.2 Extraction control
15
2.3 Orifice flow meter
15
2.4 Obscuration meters
17
2.5 Gas analysis
20
2.6 Weighing platform
21
Contents
iv
2.6.1 Separation of wood and char
22
2.6.2 Measurement of fuel burn rate and water evaporated
23
2.7 Water temperature
23
2.8 Fire temperature
24
2.9 Data acquisition
25
2.10 Summary
26
3 THE EFFECT OF AN EXTRACTION HOOD
27
3.1 Background and aims
27
3.2 Experimental design
28
3.2.1 Variables and hypotheses
28
3.2.2 Levels
29
3.2.3 Significance
31
3.2.4 Treatment combinations, repetition and randomisation
32
3.2.5 Other variables
32
3.3 Results and discussion
39
3.3.1 Fire temperature, power and efficiency
39
3.3.2 Emissions
43
3.4 Summary and conclusions
4 THE SCREENING OF EXPERIMENTAL VARIABLES
50
52
52
4.1.1 Stove type
53
4.1.2 Amount of water
54
4.1.3 Pot lids
54
4.1.4 Wood type
55
4.1.5 Wood size
55
56
56
4.2.2 Levels
56
4.2.3 Significance
60
60
60
60
4.3.1 Stove type
60
62
Contents
v
4.3.3 Pot lids
64
4.3.4 Wood type
66
4.3.5 Wood size
67
4.3.6 First order interactions
68
68
5 REAL-TIME EMISSION PATTERNS
70
70
5.1.1 The definition of the problem and the method of solution
70
5.1.2 Previous studies
71
73
75
5.3.1 The open fires
77
5.3.2 The enclosed stoves
82
5.3.3 Extraction analysis of variance
89
5.3.4 Variable screening analysis of variance
89
6 THE SIMULATION OF A DILUTION CHAMBER
89
91
91
94
97
6.3.1 The effect of cooking task on chamber method accuracy
99
6.3.2 The effect of air exchange rate on chamber method accuracy
109
6.3.3 The effect of cooking device type on chamber method accuracy
111
113
7 SUMMARY AND CONCLUSIONS
115
7.1 The need for this work
115
7.2 The aim of this work
115
7.3 The approach
116
7.4 The effect of the extraction hood on emission measurements
116
7.5 The study of the effect of five experimental variables
117
7.6 The relationship between CO, SO2 and TSP
118
7.7 The validity of assuming constant emission rate in chamber tests
118
7.8 The significance of this work
119
Contents
vi
7.9 Areas for further work
APPENDIX A EXPERIMENTAL RESULTS
120
121
A.1 Included on the diskette
121
A.2 Installing and removing the program
121
A.3 What the analysis program does
122
A.3.1 Emissions
123
A.3.2 Efficiency
128
A.3.3 Smoke and specific optical density and TSP
132
APPENDIX B REQUIREMENTS OF A TESTING METHOD
133
B.1 International standards versus testing guidelines
133
B.2 Absolute versus comparative measurements
135
B.3 Integral versus real time measurements
137
B.4 Indirect versus direct measurements
137
B.5 Water boiling test versus other methodologies
140
B.6 Recommendations
143
APPENDIX C FACTORIAL ANALYSIS
144
C.1 Identifying variables and defining hypotheses
144
C.2 Selection of levels
145
C.3 Level of significance
145
C.4 Treatment combinations, repetition and randomisation
146
C.5 Calculation methods
146
APPENDIX D WOOD COMBUSTION
148
D.1 Oxidant
149
D.2 Fuel
149
D.2.1 Moisture
150
D.2.2 Inorganic Materials (Ash)
150
D.2.3 Organic Materials
151
D.2.4 Direct combustion
151
D.3 Pyrolysis
152
D.3.1 Ratio of volatiles to char
152
D.3.2 Initiation reactions
152
D.3.3 Pyrolysis reactions
152
D.3.4 Volatiles
154
Contents
vii
D.3.5 Char
D.4 Combustion
155
155
D.4.1 Reaction Rate
155
D.4.2 Combustion of Activated Carbon
156
D.4.3 Combustion of Volatiles
157
D.4.4 Sulphur Dioxide
157
APPENDIX E CASE STUDY: COOKING DEVICES COMPARED
159
REFERENCES
177
Contents
viii
Figures
Figure 2.1 Schematic arrangement of apparatus
13
Figure 2.2 Extraction booth
14
Figure 2.3 Extraction control and emission measurement devices
15
Figure 2.4 Orifice plate calibration equipment
16
Figure 2.5 Orifice plate calibration curve
17
Figure 2.6 Light obscuration smoke meters
18
Figure 2.7 Optical smoke density calibration curve
20
Figure 2.8 Thermocouple arrangement for measuring the fire temperature
24
Figure 2.9 Computer data acquisition process
25
Figure 3.1 Three extraction levels
31
Figure 3.2 Average fire temperature and extraction level
40
Figure 3.3 CO mass and extraction level
45
Figure 3.4 CO emission factor and extraction level
46
Figure 3.5 SO2 emission factor and extraction level
48
Figure 3.6 TSP emission mass and extraction level
49
Figure 3.7 TSP emission factor and extraction level
50
Figure 4.1 Fire temperature for 1 and 2 litres of water heated
62
Figure 4.2 CO emission mass for 1 and 2 litres of water heated
63
Figure 4.3 CO emission factor for 1 and 2 litres of water heated
63
Figure 4.4 Fire temperatures with and without pot lids in place
64
Figure 4.5 TSP emission mass with and without pot lids
65
Figure 4.6 TSP emission factor with and without pot lids
65
Figure 4.7 Fire powers for eucalyptus and pine
66
Figure 4.8 CO emission mass for eucalyptus and pine
66
Figure 4.9 TSP emission mass for large and small pieces of wood
67
Figure 5.1 Fuel and evaporated water mass
76
Figure 5.2 Fuel mass, evaporated water mass and water temperature
77
Figure 5.3 CO, SO2 and TSP for the open fire
79
Figure 5.4 Burn rate for the open fire
79
Figure 5.5 CO, SO2 and TSP for the improved open fire
81
Figure 5.6 Burn rate for the improved open fire
81
Figure 5.7 CO, SO2 and TSP for the one pot metal stove
84
Figures
ix
Figure 5.8 Burn rate for the one pot metal stove
84
Figure 5.9 CO, SO2 and TSP for the two pot metal stove
86
Figure 5.10 Burn rate for the two pot metal stove
86
Figure 5.11 CO, SO2 and TSP for the two pot ceramic stove
88
Figure 5.12 Burn rate for the two pot ceramic stove
88
Figure 6.1 ‘Chamber’ mass rate balance
92
Figure 6.2 ‘Chamber’ mass rate balance with stove extinguished
93
Figure 6.3 Room CO concentration for constant E & F
94
Figure 6.4 Fuel mass and burn rate of the one pot metal stove for the
chamber simulation, single charge
99
Figure 6.5 CO emission rate for the one pot metal stove, single charge,
EF =0.011 g/s
100
Figure 6.6 CO, Csimulated(t) for a 16 m3 room, S=5, one pot metal stove, single
charge
100
Figure 6.7 CO, Csimulated(t) and C(t) using constant E simulated calculated using
the least squares regression of Ahuja et al (1987) and the simple mean of
E(t) proposed in this thesis, one pot metal stove, single charge
101
Figure 6.8 CO, Csimulated(t) and C(t) using constant E simulated (for t=1000s), one
pot metal stove, single charge
102
Figure 6.9 Fuel mass and burn rate of the improved open fire for the
chamber simulation, single charge
103
Figure 6.10 CO emission rate for the improved open fire, single charge,
EF =4.8 10-3 g/s
104
Figure 6.11 CO, Csimulated(t) and C(t) using constant E measured , improved open
fire, single charge
104
Figure 6.12 CO emission rate for the one pot metal stove, refuelled,
EF =1.1 10-2 g/s
106
Figure 6.13 CO, Csimulated(t) and C(t) using constant E measured , one pot metal
stove, refuelled
106
Figure 6.14 CO emission rate for the improved open fire, refuelled,
EF =4.9 10-3 g/s, refuelled
108
Figure 6.15 CO, Csimulated(t) and C(t) using constant E measured , improved open
fire, refuelled
Figures
108
x
Figure A1 Emission measurement parameters compared graphically
128
Figure A2 Temperature variations in the Water Boiling Test
131
Figure C1 Selection of variable levels in a factorial design
145
Figure D1 Simple wood combustion model
149
Figures
xi
Tables
Table 2.1 Gas analyser specifications
21
Table 3.1 Influence of extraction hood on emissions: variables and
hypotheses
29
Table 3.2 Three cooking devices used in the extraction tests
29
Table 3.3 Three extraction levels
30
Table 3.4 Properties of Eucalyptus grandis
32
Table 3.5 Summary of experimental variables
38
Table 3.6 Fire power (kW) and extraction level
41
Table 3.7 Efficiency (%) and extraction level
42
Table 3.8 Confidence limits for extraction and stove
44
Table 3.9 F factors for CO mass
46
Table 3.10 F factors for CO emission factor
47
Table 3.11 F factors for SO2 emission factor
48
Table 3.12 Summary of results for the influence of the test rig on emissions
at the 95 % confidence limit
51
Table 4.1 Five variables and hypothesis
56
Table 4.2 Two cooking devices used in the variable screening tests
57
Table 4.3 Properties of Pinus patula
59
Table 4.4 Sieve sizes for the selection of wood
59
Table 4.5 Performance characteristics of the two stoves
61
Table 4.6 Emission characteristics of the two stoves
61
Table 5.1 Two additional cooking devices used in the real-time emission
comparisons
74
Table 5.2 Comparison of average correlation coefficients for the open fires
(showing standard deviation in brackets)
78
Table 5.3 Pollutant correlations for the open fire
78
Table 5.4 Pollutant correlations for the improved open fire
80
Table 5.5 Comparison of average correlation coefficients for the three
stoves (showing standard deviation in brackets)
82
Table 5.6 Pollutant correlations for the one pot metal stove
83
Table 5.7 Pollutant correlations for the two pot metal stove
85
Table 5.8 Pollutant correlations for the two pot ceramic stove
87
Tables
xii
Table 6.1 Performance characteristics of the one pot metal stove for the
chamber simulation
98
Table 6.2 Performance characteristics of the improved open fire for the
chamber simulation
98
Table 6.3 Measured and simulated emission factors for the one pot metal
stove, single charge
102
Table 6.4 Measured and simulated emission factors for the improved open
fire, single charge
105
Table 6.5 Measured and simulated emission factors for the one pot metal
stove, refuelled
107
Table 6.6 Measured and simulated emission factors for the improved open
fire, refuelled
109
Table 6.7 Percentage error at different air exchange rates
110
Table 6.8 Percentage error for different cooking devices
111
Table A1 Summary of experimental variables recorded every 10 seconds
123
Table A2 Time intervals for fixed-time emission concentration
measurements
126
Table A3 Quantity of water and temperature change to transfer 251 kJ of
energy
127
Table B1 International standards versus testing guidelines
135
Table B2 Absolute versus comparative measurements
136
Table B3 Integral versus real time measurements
137
Table B4 Indirect versus direct measurements
140
Table B5 Water boiling test versus other methodologies
142
Table C1 The calculation of a two factor analysis of variance
147
Table D1 Proximate analysis of wood (Shafizadeh 1981:106)
150
Table D2 Ultimate analysis of wood (Cheremisinoff 1992:8)
150
Table D3 Pyrolysis reactions at different temperatures
153
Table D4 Yield of volatile gases at different temperatures (Speight 1993:57) 154
Tables
xiii
Symbols
ΔT
Rise in water temperature
K
ΔTi
Rise in water temperature for heating stage i
K
η
Efficiency
%
σ2
Sample variance
C
Spatial average concentration of the pollutant in the chamber
kg/m³
C
Average pollutant emission rate
kg/s
C&
Rate of change of concentration of the pollutant
kg/m³s
CM
Pollutant concentration at time t
kg/m³
cp
Specific thermal capacity of water
kJ/kgK
Dx
Optical smoke density
/m
E
Pollutant source strength
kg/kg
Emeasured
Mean emission factor calculated using the real time data collected
with the hood
kg/kg
Esimulated
Mean emission factor calculated using the solution to the simulated
dilution chamber
kg/kg
e
Number of levels of the factor E - factorial experiment
F
Snedecor's F distribution - test for statistical significance
F
Fuel burn rate
kg/s
H
Height of the open side above the process covered by a hood
m
h
Step size in Runge-Kutta solution to an ordinary differential
equation
hco
Enthalpy of combustion of the char at the reference temperature
Symbols
kJ/kg
xiv
h fo
Enthalpy of combustion of the fuel at the reference temperature
kJ/kg
h fg
Enthalpy of vaporisation of water
kJ/kg
i
Heating stage number
K
Total number of pots
k
Constant in Runge-Kutta solution to an ordinary differential
equation, chapter 6
k
Pot number, chapter 3 & Appendix A
ME
Mass of pollutant emitted
kg
M Etotal
Total mass of pollutant emitted
kg
&
M
Etotal
Average pollutant emission rate
kg/s
M Etask
Total pollutant mass emitted during the desired task
kg/task
MS
Statistical mean square
Mwater
Mass of moisture in a sample of wood
kg
M wood
Mass of oven dried wood
kg
m
Mass of water in the main pot at the start of the experiment
kg
$
m
Mass of water evaporated
kg
&a
m
Rate of pollutant mass accumulation in the chamber
kg/s
mc
Mass of char remaining at the end of the phase
kg
mf
Mass of fuel used during the phase
kg
& in
m
Instantaneous mass flow rate of pollutant into the chamber
kg/s
mk
Average mass of water in each pot
kg
Symbols
xv
$k
m
Mass of water evaporated from each pot
kg
& out
m
Mass flow rate of pollutant leaving the chamber
kg/s
m pot1
Mass of pot 1
kg
m pot 2
Mass of pot 2
kg
mstove
Mass of stove
kg
& stove
m
Mass rate of pollutant emission from the stove
kg/s
mwood
Mass of wood
kg
n
Final heating stage number, Appendix A
n
Number of sample readings, Appendix C
n...N
Counter used in Runge-Kutta solution to an ordinary differential
equation
OSD
Specific Optical Smoke Density
m−1
P
Average fire power
kW
PHU
Percentage Heat Utilised
%
Q
Volumetric extraction flow rate through a hood
m³/s
r
Linear correlation coefficient
S
Air exchange rate in the chamber
s −1
Sx
Percentage obscuration
%
SFC
Specific Fuel Consumed
kg/kg
SS
Statistical sum of squares
s
Number of levels of the factor S - factorial experiment
T
Test duration
Symbols
s
xvi
TSP
Total Suspended Particulate concentration
mg/m³
t
Time
s
t task
Time taken to achieve the desired task
s
V
Capture velocity at the process surface under a hood, chapter 3
m/s
V
Volume of the chamber, chapter 6
m³
v& flue
Flue extraction rate
m³/s
W
Width of the open side of a hood
m
x
Wood moisture content
%
x1 , x2 ,K, xn
Observations 1 to n
x path
Optical path length
Symbols
m
xvii
1
Overview
Development organisations attempting to promote improved stoves in rural areas often
recognise the need for reduced smoke and other emissions from these stoves. In a survey
of improved cookstove programmes (Smith & Ramakrishna 1991:219-241; Ramakrishna
1992:135-146) a significant number of organisations (67%) indicated that smoke reduction
was one of their most important objectives. Many stove dissemination programmes have
found that users derived the greatest satisfaction from reduction in smoke levels (Karekezi
1992:93; WHO 1992:29). Furthermore, recent research has demonstrated a relationship
between air pollution from the combustion of biomass fuel and poor health (WHO 1992:626). Only by measuring the emissions of new stoves and comparing them with those of
earlier cooking devices can improvements be assessed and emission levels reduced.
There are, however, no accepted guidelines for testing emissions from biomass cookstoves
(WHO 1992:28). Objective measurements of stove emissions currently require expensive
equipment, as well as significant expertise, and therefore these tests are restricted to
large-scale national programmes (Smith & Ramakrishna 1991:227). Current knowledge of
emissions from stoves and how to gauge emission levels is severely limited and requires
considerably more research (Joseph 1991:154). In this thesis an attempt is made to expand
the knowledge of emission testing methods of biofuel cookstoves † .
There are two compelling reasons for focusing on emission testing methods – each of these
is considered below. The impact of biomass combustion pollution on people is discussed in
Section 1.1. We will see from this discussion that improvements in emission levels will
have a profound effect on many people. Section 1.2 covers the lack of accepted guidelines
for testing emissions and the problems associated with making progress in developing
them.
†
The terms ‘cookstove’ and ‘stove’ are used loosely here to refer to some type of domestic
cooking device used predominantly by the rural poor in less developed countries. This
includes the most basic of cooking devices, the open fire – a ‘three stone fire’ built on the
ground with a pot supported above it. The term ‘biofuel’ or ‘biomass’ is used although this
thesis focuses on wood combustion. Biofuels are any fuels from living sources: wood,
charcoal, dung and crop residues.
1
Overview
1
1.1
The extent of the problem
The health risk associated with exposure to smoke and other products of combustion and
the number of people at risk world-wide should be considered. For many rural dwellers
there is no possibility of changing to fuels other than wood.
1.1.1 The health impact of combustion emissions
In developing countries respiratory disease is the chief cause of death (Krugmann
1989:129; WHO 1992:11). Acute respiratory infections are one of the leading causes of
death in black South African children (von Schirnding et al 1991:81). The link between
these respiratory problems and emissions from cooking with biofuels however has only
recently been made. Below are listed a number of the findings of studies into the long term
effects of exposure – specific details lie beyond the scope of this work – more detail can be
found in the references given below:
•
Biomass combustion products are believed to be a major cause of respiratory disease,
particularly in young children (Hong 1992:75; Morris et al 1990:105; Pierson et al
1989:341).
•
Polyaromatic hydrocarbons found in wood smoke are known to cause bladder and lung
problems (Calle & Zeighami 1984:44).
•
Lung cancer can occur many years after exposure as a result of the carcinogens in
biomass fuels (Sobue 1990:63,64; Karekezi 1992:97; Morris et al 1990:105; Kossove
1982:624; Hong 1992:54). Many polyaromatic hydrocarbons found in wood smoke are
known carcinogens (Calle & Zeighami 1984:41 list fifteen strong carcinogens). The
quantity of one of these carcinogens, benzo(H)pyrene, that a rural woman is exposed
to in a day would be equivalent to that from smoking 450 non-filter cigarettes (Sims &
Kjellström 1992:151; see Smith 1990:453,454 for a comparison of smoking and rural
smoke exposure).
•
The effects of nitrogen oxides on the immune system may increase the chance of
contracting tuberculosis in children exposed to a tuberculous adult (Achmadi 1992:8;
Kossove 1982:623).
1
Overview
2
•
Adverse effects of exposure on pregnant women and on the birth weight of children
have been found (WHO 1992:11). Smoke exposure frequently causes eye infections
(WHO 1992:20).
1.1.2 World-wide exposure to biofuel combustion products
More than half the world’s population uses biofuels every day for cooking – about 2500
million people (WHO 1992:1,10). In Africa firewood accounts for over 70% of the total
energy used (Ellegård 1992:30). In South Africa approximately 60% of the population
depend on coal or wood for cooking and heating (Makhudu et al 1994:1).
Women, frequently with young children carried on their backs, spend between 1 and 6
hours each day cooking (Vasudevan 1991:203; Sims & Kjellström 1992:151). In some areas
exposure is longer because wood fires are used for heat during the night and the winter
months (see Achmadi 1992:3-5).
1.1.3 Lack of alternatives
There is a pressing need for alternative fuels. Fuel substitution is essential for a number
of reasons including (Eberhard 1990; WHO 1992:31; Barnes 1990):
•
the scarcity of wood in some areas,
•
health problems associated with the combustion of wood,
•
woodland loss through poor agricultural practices resulting in the irreversible loss of
topsoil, and,
•
the relationship between energy use and economic growth and development.
The scarcity of firewood often leads to substitutes which have higher emission levels than
wood, for example crop residues and dung (Crewe 1992:20; Joshi et al 1989). In the
vicinity of the South African coal fields, coal is often substituted for wood because of its
low cost (Lennon & Turner 1991:5). Emission levels from coal, even ‘smokeless’ coal, are
frequently higher than from wood, and therefore the associated health problems may be
increased (Lennon & Turner 1991:5; Hong 1992:74,75).
For hundreds of millions of people alternative fuels are unavailable owing to cost and
supply problems (WHO 1992:1). Although a transition to electricity or gas would be the
1
Overview
3
most healthy solution “the likelihood of a complete transition from biofuels to electricity
in the poorer urban and rural communities in the near future is minimal” (Nel et al
1994:5).
The large scale use of biofuels, principally wood, will be unavoidable in developing
countries in the foreseeable future.
1.2
The gap in stove testing methods
Historically research organisations have used efficiency and cost as the primary criteria
for rating rural stove suitability. This has provided little incentive to study the emissions
from biofuel combustion. Technical difficulties in measuring rural stove emissions have
also contributed to this information scarcity.
1.2.1 The need for stove emission measurement
The need for the development of emission testing methods is frequently stressed in the
literature (WHO 1992:28,36,42; Shukla 1991:179; Smith et al 1992:Section 4D). In a study
of the priorities of improved cookstove programmes from around the world, decreasing
smokiness scored almost as high as increasing household fuel efficiency (67% as against
70%) (Ramakrishna 1992:138).
It has sometimes been assumed that efficiency is a sufficient measure for gauging
emissions – that improving efficiency will naturally lead to reduced emissions. A number
of studies have shown that this clearly is not the case (Smith 1992:173,182; Ahuja et al
1987:267; Nangale 1992:18). In fact it has been recognised that a conflict exists between
high efficiency and low emissions (Shelton 1982:874). The reason for this is simple to
understand – efficiency is influenced by two largely independent factors: combustion
efficiency, and heat transfer efficiency. Combustion efficiency, a measure of how well the
fuel is burnt, relates directly to emissions. Poor combustion efficiency means that the fuel
is not completely burnt and therefore the products of incomplete combustion are emitted
from the stove. However, heat transfer efficiency (how well the energy released from the
wood is transferred to the pot) can be improved while, at the same time, decreasing
combustion efficiency. This often yields an improved overall efficiency but increased
emissions (See Smith 1992:173,182; and Ahuja et al 1987:267). It is therefore vital to
measure stove emissions and not to assume that a high efficiency stove will have low
emissions.
1
Overview
4
1.2.2 The difficulty of measuring emissions from stoves used by the rural poor
Emissions from the type of biofuel stove frequently used by the rural poor are difficult to
measure for a number of reasons (see Ahuja et al 1987:249):
•
Since stoves used in underdeveloped countries often do not have chimneys there is no
easy place to measure emission concentrations. Care must be taken to ensure adequate
mixing of the combustion gases and accurate measurement of dilution factors.
•
Biofuels do not burn evenly and the resulting fire is transient and largely
unrepeatable.
•
Preparing meals on a stove involves a number of different operations. Measurements
of emissions need to be made over a range of processes to ensure that results indicate
emissions representative of actual usage.
1.2.3 Historic focus on efficiency not emissions
During the 1940s and 50s stove development work focused on the four-fold problem of
health, cleanliness, fuel economy and forest economy (Kristoferson & Bokalders 1991;
Karekezi 1992:91). Smoke removal from the kitchen was often the primary concern for
development organisations (Ahuja et al 1987:248). This focus led to the development of
large-mass, mud stoves with chimneys. These were assumed to be fuel-efficient, but often
used more fuel than open fires (Baldwin 1987).
In the 1970s development workers became acutely aware of the global fuelwood crisis
(Aprovecho Institute 1984). Studies by Dr Sam Baldwin in West Africa, published in Vita
News (1984) set the direction for much of the stove development work in subsequent
years. He described a number of ideas which at the time were revolutionary. The largemass mud stoves promoted by many development organisations increased fuel
consumption, were time-consuming to build, and were easily broken. Low mass, metal or
ceramic chimney-less stoves on the other hand were low in cost, fuel-efficient, and allowed
for rapid production (Baldwin 1984; Ouedraogo et al 1983:1-3). Efficiency soon became the
principal concern of development organisations (Bialy 1991:3; Joseph 1991:145) – thus
technical and scientific issues relating to efficiency became the focus of intensive research
(Karekezi 1992:91).
1
Overview
5
Many researchers emphasised the need for standard methods of measuring efficiency and
attempted to make suggestions (Joseph & Shanahan 1980; De Lepeleire 1981; Aprovecho
Institute 1984; Baldwin 1987). International standards were agreed upon by a number of
key stove development workers and were published in 1982. The revised edition
(VITA 1985) received fairly wide acceptance (Stewart 1987). A discussion of the
advantages and disadvantages of these methods can be found in Appendix B * .
It is often assumed that deforestation and the collection of firewood are directly linked. It
is also frequently assumed that improved stoves can have a profound effect on slowing
deforestation. These assumptions, which formed the foundation for the development of
fuel-efficient stoves, have however been questioned. The following arguments have been
confirmed by the author through personal experience in rural areas:
Clearing woodland for agriculture and the use of wood for building are, in many areas,
•
the main contributors to deforestation rather than the use of wood for fuel (Krugmann
1989; Kristoferson & Bokalders 1991; Barnes 1990; Liengme 1983). In many areas a
progression can be seen: initially fuelwood gathering is confined to dead wood. Rural
overcrowding leads to a large demand for wood and a diminishing supply because of
the clearance of fields and the cutting of live trees for building. Wood gatherers are
soon forced to use wood from the remaining live trees which reduces supplies even
further. Commenting on the disappearance of forests in southern Natal, South Africa,
Gandar writes: “It is wrong to lay all the blame on the firewood crisis but the chances
are that it was the last nail in the forest’s coffin.” (Gandar 1987). Wood used as fuel is
therefore not the sole contributor to deforestation.
With large population growth rates, savings from more efficient fuel usage are
•
overtaken in a very short time (Baldwin 1984).
The introduction of improved stoves in rural areas leads to changes in cooking
•
operations and quantities of food prepared and therefore does not directly decrease fuel
consumption (Bialy 1991:17; Smith & Ramakrishna 1991:231-232). A stove which is
enjoyable to use will usually be used more frequently and for longer periods. This may
*
Appendix A describes the use of the computer software (provided on the accompanying
diskette) for accessing the experimental data and results.
1
Overview
6
lead to better hygiene and nutrition, but seldom decreases overall fuel consumption.
An example of the difficulty in predicting the reaction of a population to energy related
changes is that in South Africa 75% of coal-using households continue to use coal after
having been provided with electricity (Sithole et al 1991:2).
The ‘discovery’ of the poor link between deforestation and the use of wood for fuel has led
to a re-assessment of the aims of improved stove programmes. Current work in improved
stoves is concerned with both socio-economic and technical or scientific factors (Karekezi
1992:91). This broad base is reflected in recent studies which cover subjects as diverse as
welfare issues, the need for land redistribution, women’s time, and the effect of smoke –
all in relation to rural fuel usage (see Eberhard 1992:20-24). This ‘renewed’ social angle
comprises a focus on ‘the consumer not the commodity’ (Viljoen 1991:19). It is emphasised
that rural people can recognise and prioritise their own needs (Karekezi 1992:93; WHO
1992:29).
1.2.4 The existing methods of emission measurement
A few studies have been undertaken in an attempt to propose methods of emission
measurement of stoves used by the rural poor. In contrast, many studies have been carried
out on wood-burning stoves used for heating in the homes of the more affluent (these are
occasionally referenced in this thesis where findings are relevant). The methods can be
divided into two broad categories depending on whether they involve the direct or the
indirect measurement of the pollutants. ‡
a) Direct measurement
Direct measurement of stove emissions involves measurement at the source – the stove. A
hood placed over the stove to capture the emissions is frequently used. Butcher et al
(1984) attempted to design a low cost simple measurement system for determining
simultaneously the emissions and efficiency of stoves. The method involved the direct
‡
A third category, receptor or exposure measurements involve the study of exposure levels
experienced by people within the environment. They are particularly useful in medical
studies where health risks can be accurately assessed. Emission levels measured in these
types of test are complex functions of person, environment, and stove.
1
Overview
7
measurement of carbon monoxide and total suspended particulates passing through a
hood at a measured flow rate. Nangale (1992) repeated this work and included an
indicator of hydrocarbon activity by passing the sampling stream through cold water and
measuring the change in acidity of the water.
b) Indirect measurement
Indirect methods measure the influence of the stove on a dilution chamber (a room
simulating a rural dwelling). The emission source strength is calculated by performing a
mass balance for the pollutant in the chamber.
The majority of emission measurement studies relating directly to rural development focus
on indirect measurements using the ‘chamber method’:
•
Initially methods for evaluating rural stoves in terms of emissions for design
improvement and development purposes were explored (Ahuja et al 1987). A stove is
taken through a combustion cycle in an enclosure (designed to simulate a rural
dwelling), and carbon monoxide concentration some distance away from the stove is
recorded. Mass balance calculations are used to determine the average air exchange
rate in the room and hence emission source strength is calculated.
•
Joshi et al (1989) studied the performance of a few unvented metal stoves as affected
by three different fuels: wood, dung, and crop residues using the chamber method
proposed by Ahuja et al (1987).
•
The effects of common defects in construction and operation of large-mass stoves with
chimneys were studied by Joshi et al (1991) using the chamber method.
The chamber method has found favour with the Intermediate Technology Development
Group in the UK (see Young 1992) and is strongly recommended as the direction for
future emission testing work (personal communication: Professor Kirk Smith,
Environmental & Health Sciences; Warren Hall; University of California; Berkeley, USA
94720-7360). Indoor pollutant concentrations and exposures were measured in a World
Health Organisation (WHO) study into air quality in rural kitchens in Ethiopia, and field
workers were trained in chamber method calculations (Usinger 1994).
1
Overview
8
The method is however not used in this study for the reasons discussed below. Some
advantages and disadvantages of direct and indirect methods, from the point of view of
development organisations, are contrasted in Appendix B.
1.2.5 Issues considered in this study
In this study we will place the cooking device to be tested under an extraction hood with
measured extraction characteristics. This direct method allows the assessment of a
number of the fundamental issues related to testing which an indirect method would not
facilitate. Emissions and efficiencies will be measured simultaneously, and the cooking
devices will be operated in ways closely reflecting rural usage; as far as possible fires or
stoves will be refuelled when required. Water will be brought to the boil as rapidly as
possible during the heating up phase (commonly called the ‘high power’ phase) and will
then be maintained within 5°C of boiling for 30 minutes during the simmering phase
(called the ‘low power’ phase). This task is the same as that defined by the Water Boiling
Test (VITA 1985). The selection of these parameters are discussed in Appendix B with
particular reference to the needs of development organisations.
Four issues are considered in this study (detailed background and aims are to be found
within the chapter dealing with each issue):
a) The effect of an extraction hood (chapter 3)
The direct measurement of the emissions using a hood is not the preferred method for
testing stove emissions (Nangale 1992). One of the reasons for this is “the potential for the
mechanically induced air flow to change the combustion characteristics of the stove”
(Ahuja et al 1987:250). In this study the effect of the air flow on stove emissions is
examined.
b) The screening of experimental variables (chapter 4)
It is vital that stoves are tested in ways that reflect actual usage, because both efficiency
(see Baldwin 1987:262,263) and emissions (it is conjectured) are highly dependent on stove
operation. It is therefore essential to assess the importance of a number of variables that
are suspected to be influencing factors in emission tests.
1
Overview
9
An example from personal experience § : pot lids are generally used in the Mpumalanga
Province. The determination of efficiency is complicated by the use of lids because the
amount of water evaporated when lids are used is partly dependent on how well the lid
fits, and partly dependent on the fire power. Simmering efficiency (the efficiency of a stove
while simmering water), in particular, becomes a function of the ‘goodness-of-fit’ of the lid
and the skill of the operator. The effect of pot lids on stove emissions is unknown – it
seems likely that pot lids would reduce total exposure if cooking time or fire power were
reduced.
The effect of five variables (stove type, wood type, wood size, the use of lids, and the
quantity of water heated) on efficiency and emissions are considered in this study. It is
hoped that this will contribute to the formulation of emission testing guidelines.
c) Real-time emission patterns (chapter 5)
In some studies complicated and costly experiments using gas chromatography are used to
quantify individual hydrocarbons in the particulates (see for example, Cooke et al 1982,
McCrillis et al 1992, and Smith et al 1993). In simplified tests carbon monoxide (CO) and
Total Suspended Particulates (TSP) are measured, CO being an indicator of acute hazard
and TSP of chronic hazard (see for example Butcher et al 1984, Ahuja et al 1987, Joshi et
al 1989, and Nangale 1992). It is commonly accepted that equipment for measuring even
these pollutants is excessively expensive. If it were possible to measure only one pollutant
and from this measurement infer the others, great reductions in experimental costs could
be achieved.
In this study we assess whether this simplification is valid.
d) The simulation of a dilution chamber (chapter 6)
The determination of emission source strength using the chamber method requires the
solution of a first order differential equation which is formulated from a mass balance
§
All field-work was carried out in the Mhala district of Mpumalanga Province (formerly
the Eastern Transvaal) where the University has a rural facility. The School of Mechanical
Engineering has been involved in stove design and dissemination projects in this area
since 1990.
1
Overview
10
within the chamber (Ahuja 1987:257,258). In order to solve the differential equation it is
necessary to assume, among other things, that fuel burn rate and emission source
strength are kept constant. To ensure that they are constant it has been suggested by
Ahuja et al (1987) that the stove be operated in a specific way (without refuelling, by
bringing water to the boil and keeping it boiling for 15 minutes, and by tending the fire in
such a way as to ensure a steady flame) which differs substantially from operation during
a real cooking cycle. Even so, it is questionable whether it is possible to operate the stove
in such a way as to ensure constant burn rate, and whether a constant burn rate implies a
constant emission rate.
In this study, since we can measure directly the burn rate and the emission rate, we can
calculate the average room concentrations for any combination of room volume and air
exchange rate. In this way it will be possible to check the validity of the assumptions that
are made in the chamber method.
1.3
Summary
In this chapter we have considered the background to this study. The formulation of
emission testing methods that are suited to the needs of development organisations is
important for two reasons: the number of people affected by exposure to combustion
products is very large; and there is clearly a gap in accessible methods for the
measurement of emissions. Four specific needs are considered in this thesis:
• The effect of an extraction hood on stove emissions and operation;
• the selection of experimental variables;
• the comparison of real-time emission patterns; and
• the validity of assuming constant burn rate and emission rate in the chamber method.
1.4
Thesis organisation
Chapter 2 describes the experimental apparatus. The four chapters which follow this
contain the four contributions made by the thesis. Each of these chapters has four
subsections: background and aims, experimental design, results and discussion, summary
and conclusions. Mathematical methods are introduced and discussed where they are used
in the text. Chapter 7 summarises the thesis and provides conclusions for the entire work.
1
Overview
11
The appendices cover subjects which may be useful to the reader, but which interrupt the
flow of the body of the thesis. The reader is referred to the relevant appendix in the text.
1
Overview
12
2
Apparatus
The experimental apparatus used to measure the direct emissions from a number of stoves
is described below. It allows the simultaneous real-time measurement of efficiency and
emissions. The relationships of the various parts can be seen in Figure 2.1 below.
Centrifugal fan
Extraction control
Damper
Light obscuration meters
Gas Analysis Probe
Orifice flow
meter
Extraction hood
Thermocouples
Pot
Not to scale
Stove
Weighing
Platform
Figure 2.1 Schematic arrangement of apparatus
2
Apparatus
13
2.1
Extraction booth
The entire stove, the pots, and the scale were enclosed in a three sided extraction booth.
Booths such as this one are typically used for the extraction of fumes where a low capture
velocity is sufficient – typically of the order of 0.5 m/s (Committee on Industrial
Ventilation 1982:4-5).
Extraction duct
Dimensions in mm
800
Figure 2.2 Extraction booth
2
Apparatus
14
2.2
Extraction control
Flue gases are removed from the hood through a duct of 200mm diameter. The duct is
connected to a centrifugal fan and a three phase motor. Flow rate is controlled by means
of a butterfly damper. The emission measurement devices are supported in the straight
section below the fan and their position can be seen in Figure 2.3 below.
Centrifugal fan
200 OD
Damper
Access door
Smoke meters
Gas analysis probe
d pressure tapping
Orifice
Dimensions in mm
Figure 2.3 Extraction control and emission measurement devices
2.3
Orifice flow meter
The flow rate of the flue gas was measured with a calibrated 130 mm diameter orifice plate
and an electronic micro-manometer (Air Neotronics MP6KS with a DC output of
1 mV/count). The pressure drop was converted to a digital signal for computer processing.
The orifice plate was fitted to the inlet within the extraction hood, making it an ‘infinityto-pipe-diameter’ type. It was fitted with a d/2 pressure tapping (a tapping half a diameter
from the orifice plate).
2
Apparatus
15
Calibration over the full working range against a standard orifice (BS 1042:1981) was
carried out at the beginning, three times during and again at the end of the testing
programme. The total change in response was less than 0.1 % over the entire range and
was therefore considered to have remained constant for the duration of the tests.
The calibration wind tunnel is shown in Figure 2.4 below. The orifice to be calibrated was
connected to the inlet of the wind tunnel so as to emulate the ‘infinity-to-pipe-diameter’
arrangement of the extraction hood. Flow direction is shown by the arrow.
Test section
130 mm orifice ½d tapping
BS Orifice 101.59 mm
corner tappings
Variable speed
centrifugal fan
Figure 2.4 Orifice plate calibration equipment
The measured data had a linear regression correlation coefficient of 1.0000 to the
measured accuracy. The incoming pressure drop from the micro-manometer was
converted into a standard pressure drop with a look up table. Calculated mass and volume
flow rates were corrected for flue temperature using the correction equations given in
BS 1042 (1981). Figure 2.5 shows the orifice calibration curve measured at 25°C.
2
Apparatus
16
450
Standard orifice BS1042 (Pa)
400
350
300
250
200
150
100
50
0
0
50
100
150
200
Non-standard orifice (Pa)
Figure 2.5 Orifice plate calibration curve
2.4
Obscuration meters
Since the particulates emitted by wood fires are essentially all in the respirable size range
(Butcher et al 1984; Calle & Zeighami 1984) it is appropriate to measure total suspended
particulates (TSP). TSP were measured by means of a light obscuration (or an
attenuation) meter.
Two different light obscuration smoke meters were designed and built and are shown in
Figure 2.6. The first meter – which was used for most of the experimental work – operated
in the visible light spectrum and used a high intensity red Light Emitting Diode (LED)
and light dependent resistor. A second meter was built because it was suspected that the
condensation of volatiles on optical surfaces (‘window contamination’) led to drift and
unreliable results. A 180° slit was cut into the tube to allow a small amount of clean air to
pass in front of the lens to keep it clean. The whole tube was enclosed in a sheath to
ensure that no outside light entered through this slit. The second meter used a high
intensity infrared LED and a photo-transistor operated in the linear regime. An
operational amplifier was used to convert the gain reading to volts and to ensure that the
load on the transistor remained constant. Tests showed that the meters gave almost
identical results (±5 % deviation). A number of stove tests from those already completed
using only the first obscuration meter were repeated using both smoke meters. Drift of the
earlier instrument was indeed present but much smaller than was originally suspected (of
2
Apparatus
17
the order of 1 % over the entire burn cycle – that is, the older smoke meter indicated 1 %
at the end of a test after the fire had been extinguished). The new instrument had a drift
of less than 0.1 %.
The effect of steam was not visible on obscuration plots when the water was boiling
vigorously – the approximately 1m distance between the pot and smoke meters appears to
be sufficient for the vaporisation of the visible steam leaving the surface.
The voltage drop across the light detectors was converted into a digital signal for computer
processing.
Lens
path length 200
Infra-red LED
Photo-transistor
Slit to generate
air curtain
path length 180
Red LED
LDR
Dimensions in mm
Figure 2.6 Light obscuration smoke meters
The British Standard Specification for Smoke Density Indicators and Recorders
(BS 2811:1969) defines the optical density of a medium as
100
100 − S x
where S x is the percentage obscuration, and
D x is the optical density (dimensionless) over a path length x
D x = log 10
Optical density is proportional to the length of the path between transmitter and receiver.
A specific optical smoke density (OSD) can be defined as the optical density divided by the
path length.
2
Apparatus
18
It is pointed out in BS 2811 (1969:7) that the logarithmic absorption law (called Lambert’s
law) which is the basis of the above equation is followed by all but very dense smoke.
Additionally the relationship does not hold if the light source is not monochromatic, the
smoke is of varying colours, or the particles of varying sizes (Nader 1976: 608-611).
The science of the formation and structure of smoke is complex and the reader is referred
to Bartok and Sarofim (1991) for a general introduction to the field. The aerosol particles
from the burning of biofuels (and fossil fuels) have, however, been shown to possess a
fairly narrow size distribution (Haynes 1991:293; Nader 1976:608).
There is a valid linear correlation (better than 97%) between the optical density and mass
concentration, and light obscuration equipment can therefore be calibrated in terms of
mass concentration (BS 2811:1969:15; Nader 1976:608).
The calibration of the smoke meters was carried out by collecting particulate samples on
acid etched 47 mm diameter membrane filters and measuring the change in mass.
Fine particles range in size from 0.01 μm to 1 μm – particles from fuel combustion sources
smaller than 0.01 μm rapidly coagulate and grow; it has been found, however, that they do
not grow larger than about 1 μm (Godish 1991:56). These particles, therefore, are in the
respirable range (Nader 1976:608). Coarse particles emitted from a fire, in contrast, are
predominantly produced by mechanical processes, and are larger then 2 μm (Godish
1991:56).
An 8 μm pore size Nuclepore membrane filter formed the first collection stage and was
used to remove the coarse particles. This filter size has roughly a 50% collection efficiency
at 2.5 μm aerodynamic diameter (Lippmann & Harman 1989:193). The second stage was a
0.4 μm pore size Nuclepore membrane which collects essentially all the fine particles that
pass through the first filter (those with an aerodynamic diameter less than 2.5 μm). A
0.4 μm pore size Nuclepore filter has roughly a 50 % collection efficiency at 0.01 μm
(Lippmann & Harman 1989:193).
The two stages were connected in series in open face Stacked Filter Units mounted in the
middle of the airstream 0.1 m above the beam of the higher smoke meter. Sampling rates
varied between 5 and 20 litres per minute, and therefore sampling was not strictly
isokinetic: sampling speed was marginally lower than extraction speed and consequently a
small overestimation can be expected due to impaction on the first stage of the filter unit.
The filters clogged rapidly (within 1 to 5 minutes) and were therefore changed regularly.
2
Apparatus
19
Most of the particulates were collected on the 0.4 μm filter (10 times the mass collected on
the 8 μm filter). This confirmed the narrow size distribution of the particulates and the
fact that most wood smoke is in the respirable range (see Nader 1976:608). In addition it
demonstrates the small error due to the non-isokinetic sampling. An air volume (dry gas)
meter with a 0.0001 m3 resolution was used to record the total volume which had passed
through the filter in the specified time.
The particulate mass figures were related to the integral of the OSD over the sample time
(the time mean OSD). From this a conversion factor for OSD to mass concentration could
be determined. The calibration curve (with a correlation coefficient, r, of 0.98 and a slope
of 9.4) is given in Figure 2.7 below.
Particulate mass concentration (mg m -3)
60
50
40
30
20
10
0
0
1
2
3
4
5
6
Time mean optical smoke density (s m -1)
Figure 2.7 Optical smoke density calibration curve
2.5
Gas analysis
An electrochemical flue gas analyser manufactured by Industrielle Mess- und
Regelsysteme für Umwelttechnologie, Heilbronn, Germany, the IMR 3000P, was used to
measure carbon monoxide (CO) and sulphur dioxide (SO2). The analyser carries out
automatic corrections for the cross sensitivity of the cells and is specifically calibrated for
the measurement of flue gases. Room temperature and gas temperature are also measured
2
Apparatus
20
by this device. During a test gas concentrations and temperatures were downloaded to a
computer via a serial RS232 interface and were recorded every 10 seconds.
The analyser performs automatic zero calibration. Calibration against reference gases was
carried out at the beginning, middle and end of the testing programme. Total change in
response was less than 2 % during the entire test period and was therefore taken to have
remained constant during the tests
Table 2.1 Gas analyser specifications
Variable
Principle
Range
Resolution
Accuracy
CO
electrochemical
0 – 6000 ppm
1 ppm
±2%
SO2
electrochemical
0 – 4000 ppm
1 ppm
±2%
Room T
PTC resistance
-20 – 99 °C
1 °C
±1%
Gas T
Ni/Cr-Ni thermocouple
0 – 1200 °C
1 °C
±2%
2.6
Weighing platform
In this study efficiency was determined by carrying out the Water Boiling Test (WBT)
recommended by VITA (1985). Efficiency of a cooking device is defined as the ratio of
energy entering the pot to the energy content of the fuel consumed. In this study separate
efficiencies were determined for the heating up and the simmering phase. The
determination of such efficiencies requires that the masses of wood and char be separately
known at the beginning and end of each phase. Furthermore, the burn rate was to be
determined continuously. These measurements were determined by weighing as outlined
below.
A digital battery-operated scale (single loadcell type) with a 100 kg range and 0.01 kg
resolution supported the entire stove, fuel and pots. Mass readings were downloaded
regularly to a computer via an RS232 serial interface and were recorded every 10 seconds.
The measurement of stove efficiency presents two particular problems. The first is a
problem caused by the nature of the fuel – the separate burning of volatiles (pyrolysis
2
Apparatus
21
products of the wood) and char. The second is a problem caused by the stove – the fuel is
contained within the stove making the measurement of amount burned difficult. These
problems are discussed in Section 2.6.1 below. In addition, fuel mass is difficult to measure
because of the superimposed change in the mass of water being heated (as a result of
evaporation). This difficulty is discussed in Section 2.6.2.
2.6.1 Separation of wood and char
Upon heating, biofuels are converted into a mixture of volatiles and carbonaceous char
which burn with entirely different characteristics. The volatile products mix with air and
burn with flames (this is called wood pyrolysis); the carbonaceous char glows as it burns
(this is called char combustion). These two modes of combustion have entirely different
chemical mechanisms and kinetics (Shafizadeh 1981:103,104).
Within a stove, during burning, the proportions of wood, pyrolising solid, and char are
unknown. Efficiency can only be determined by separating the wood and char and by
measuring the proportions of each, and hence calculating the energy released. To do this
without disturbing the fire is impossible.
The second problem involved in measuring the efficiency of biofuel stoves is caused by the
stove. Since all the fuel is inside the stove it is usually required that the fuel be removed
from the firebox, measured and replaced. Combined with the added problem of separating
the unburned wood and the char this presents major practical problems.
A common solution is to place the entire stove on a scale (Baldwin 1987:83). Any wood in
the firebox is removed, the stove is weighed with the charcoal, and then the wood
returned. In this study this approach has been followed for the open fire and the improved
open fire. (These fires were fed radially, following traditional practice. The char can thus
be broken off from the unburned wood without drastic disturbance of the fire.) For
enclosed stoves it is impractical to remove unburned wood. To get a good indication of the
energy released from the fuel it is better to operate the stove in such a way that only char
remains at the end of an experiment (or heating phase). This means operating the stove in
a way that does not entirely reflect rural practice. The equivalent mass of fuel burned, on
an energy basis (with reference to the unburned wood), can then be calculated in the
following manner:
2
Apparatus
22
Taking,
m f as the mass of fuel used during the phase (kg),
m c as the mass of char remaining at the end of the phase (kg),
hco as the enthalpy of combustion of char at the reference temperature (kJ / kg), and
h fo as the enthalpy of combustion of the fuel at the reference temperature (kJ / kg).
*
we have m f h fo = energy released by the wood if it were burned completely
m c hco = energy released by the remaining char if it were burned completely
∴ energy released = m f h fo − m c hco
Dividing by h fo we obtain m f − m c
hco
h fo
that is, the effective fuel burned.
2.6.2 Measurement of fuel burn rate and water evaporated
Fuel burn rate is usually calculated as an overall figure during the heating up phase and
the simmering phase. Having the stove resting on the scale suggests that burn rate can be
measured continuously.
The difficulty is that both the water mass in the pots and fuel mass are decreasing at
different rates, neither of which is constant. Since the mass of the stove and pots are
known, lifting the pot from the fire for a fraction of a second (until the scale has become
stable) makes it possible to calculate the interim fuel and water masses. A few tests
conducted with the pots lifted in this manner at 2 minute intervals (more frequently near
the boiling point) showed that the evaporation rate was essentially constant (but of
different value) for each phase. For most of the tests the pots were lifted at the beginning
and end of each phase only. In these cases burn rate was estimated on the assumption of a
constant evaporation rate for the phase in question. More detail is given in Chapter 5.
2.7
Water temperature
Water temperature in the pots was measured continuously using type J unsheathed
thermocouples suspended in the centre of each pot 10 mm from the bottom. A computer
*
For all practical purposes h o may be taken as the (lower) calorific value as determined by
means of a bomb calorimeter.
2
Apparatus
23
with a thermocouple card was used to record the water temperatures every 10 seconds
throughout the test.
2.8 Fire temperature
The measurement of the temperature of a fire is not easy. A fire is typically very transient
and temperatures are unevenly distributed across its area as well as its height. An
indication of fire temperature is at best approximate – it is commonly recognised that
there is no complete solution, and that the “indicated temperature is probably not the
temperature of anything except the thermocouple hot junction, but is a compromise value
related to fire temperatures in a potentially useful manner” (Gilchrist 1963:135).
For the present purpose it is useful to have an indication of the temperature to which the
saucepan or pot is exposed, and at the same time to obtain some measure of the evenness
of the fire temperature below the pot.
Three type K sheathed thermocouples (310 stainless steel sheaths) were placed 10 mm
below the base of the pot – well below the boundary layer of the gases and flames passing
across the base and around the pot (this was verified visually). The thermocouple
junctions were positioned on a 100 mm diameter spaced at 120° as shown in the following
diagram.
Pot diameter 250
Base of pot
Thermocouple
Side view
Bottom view
Dimensions in mm
Figure 2.8 Thermocouple arrangement for measuring the fire temperature
2
Apparatus
24
2.9 Data acquisition
A 386 SX computer was used to monitor the experiment and gather and store data for
later analysis.
The interface equipment consisted of a PC-30 A/D converter, a PC-73 thermocouple card
with cold junction compensation (both Eagle Electric, Cape Town, South Africa), and two
RS232C interfaces.
The control and data acquisition process was as follows:
1 Initialisation
- thermocouples
- A/D converters
- RS232 interfaces
2 Calibration
- smoke meters
- gas analyser
- micromanometer
3 Set up test
- pot masses
- initial water masses
- initial wood masses
4 Read equipment
- thermocouples
2 water temperatures
3 fire temperatures
1 scale temperature
- A/D converter
1 micromanometer
2 smoke meters
- scale mass
stable or unstable
combined water & wood mass
- gas analyser
room temperature
flue gas temperature
CO, SO2
5 Display and record data
end? YES
6 Respond to user actions
- add more wood to the fire
- separate fuel and water
- separate char & unburned wood
- change experimental phase
- add a comment to the data
end? NO
Figure 2.9 Computer data acquisition process
2
Apparatus
25
2.10 Summary
The experimental apparatus has been described.
The direct source emissions of unvented cooking devices were measured by placing the
stove under an extraction hood. A calibrated orifice plate was used to measure extraction
rates continuously during a test. Carbon monoxide and sulphur dioxide were measured
with an electrochemical gas analyser and a calibrated light obscuration meter was used to
measure total suspended particulates.
The stove was placed on a digital weighing platform which was used to measure fuel
burned and water evaporated during a test. Thermocouples measured average fire
temperature and water temperatures. A computer was used to record the experimental
variables at 10 second intervals.
2
Apparatus
26
3
The effect of an extraction hood
One of the problems with placing a stove under a hood is “the potential for the
mechanically induced air flow to change the combustion characteristics of the stove”
(Ahuja et al 1987:250). This issue must be investigated before an extraction hood can be
used with any degree of confidence.
3.1
Background and aims
In 1984 Butcher et al proposed and tested a method for measuring the direct emissions
from rural stoves. Since most rural stoves do not have chimneys (Ahuja et al 1987:249) it
is not possible to measure the pollutant concentrations in the flue and it is therefore
necessary to place the stove under a hood into which all the flue gases are drawn.
Butcher’s study determined the emissions of rural stoves for the first time.
The chamber method, where the effect of the stove concentrations are measured in a
dilution chamber and the source emissions are calculated (Ahuja et al 1987), was
developed in response to perceived difficulties with the hood method. These difficulties
are:
1. The measurement of air flow rates is costly and prone to errors.
2. The method is limited to the laboratory setting.
3. The hood could interfere with the tending of the fire.
4. The forced extraction of the emissions through the hood could change the combustion
characteristics of the stove.
There have never been any investigations into the validity of these objections. It is not the
intention of this thesis to investigate the first three in any detail. It is argued however in
Appendix B, that absolute measurements of air flow rates may in fact be unnecessary. If
this is true, the cost of the experimental equipment would be greatly reduced.
Furthermore, there seems no reason to assume that suspending a hood over a stove
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27
requires laboratory facilities. A portable extraction hood could easily be designed † . Such a
system could potentially be used to measure both indoor and outdoor emissions. It is
important to design the hood carefully so that it does not interfere with tending the fire –
this however is not an insurmountable problem.
The presence of a hood could change stove emission measurements in the following ways:
1. The extraction may change the wood combustion characteristics – independent of the
type of stove (all stoves are influenced in the same way).
2. The extraction may interact with the stove type. The design – particularly the type of
air inlet – may respond to the forced extraction in different ways.
In this chapter we aim to investigate and quantify the influence of a hood on stove
performance (in terms of fire power, fire temperatures, and efficiencies) and stove
emissions.
3.2
Experimental design
The experimental design takes the form of an Analysis of Variance (ANOVA) with two
factors each at three levels. The mathematical methods as well as some definitions
relating to an analysis of variance (such as factors, levels, and null hypotheses) are covered
briefly in Appendix C.
Two variables are considered: stove type and extraction rate. The interaction of stove type
and extraction rate is particularly important since the presence of this interaction would
make stove comparisons impossible – it would not be known whether the influence of an
†
The design of a portable hood forms part of an ongoing undergraduate project. Initial
results show that the hood method can be extended to a field setting. The Max-Planck
Institute for Chemistry has conducted field tests in Zimbabwe successfully using an
extraction hood in an attempt to characterise rural biofuel combustion in terms of global
warming potential (personal communication: Dr Günter Helas, Max-Planck Institute for
Chemistry; Biogeochemistry Department; PO Box 3060; D-55020 Mainz; Germany).
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28
extraction hood (if any) was consistent between any stove. The variables and hypotheses
are given in Table 3.1 below.
Table 3.1 Influence of extraction hood on emissions: variables and hypotheses
Variable
Null hypothesis
Stove type
Emissions are independent of stove type.
Extraction rate
Emissions are independent of extraction rate.
Interaction
There is no interaction between stove type and extraction rate – all
stoves are influenced equally by extraction.
3.2.2 Levels
a) Stove type
Three types of cooking device were selected for these tests. The selection was based
primarily on the need for having a range of common stoves which could be expected to be
influenced by the mechanically induced air flow in different ways. Thus stoves with
different air inlet characteristics were selected.
The improved open fire, an open fire raised on a grate, has the least restricted access to
outside air and, as such, could be expected to be the most susceptible to the influence of
the forced air flow. Raising a fire allows primary air to reach the fuel bed from below.
The one pot metal stove has a small air inlet with a sliding door. The two pot ceramic
stove is the most enclosed, having fixed primary and secondary air inlets.
Table 3.2 Three cooking devices used in the extraction tests
Improved open fire: An improved ‘three stone fire’ – with a 10 mm square
grate supported 10 mm above the ground; the pot is supported 100 mm above
the grate. The fire is built on the grid. The grate area (the maximum fuel bed
area) is approximately half the pot floor area.
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29
One pot metal: One pot ‘Mbaula’ – A one pot metal stove manufactured in
Malawi, with ceramic insulation. The stove is top fed (the pot must be
removed to add fuel), and has an adjustable damper to control air inlet. The
diameter of the firebox is 200 mm
Two pot ceramic: A two pot stove designed at the University and
manufactured by a rural potter in Mpumalanga (Ballard-Tremeer &
Trickett 1991; Ballard-Tremeer et al 1992). The stove is top fed. A tunnel
connects the two pot holders and combustion gases escape from around the
second pot. The diameter of the firebox is 250 mm.
b) Extraction rate
Three levels of extraction rate are considered. Extracting at an insufficient rate to remove
the emission gases is impractical since gases would then escape around the sides of the
hood. With the stove removed a lit match was held 50 mm above the experimental
platform – the position of the centre of the fire within a stove – and the extraction rate
was adjusted to one of three levels as shown in Table 3.3 and Figure 3.1.
Table 3.3 Three extraction levels
Mass flow rate (kg/s)
Volume flow rate (m3/s)
[average during tests]
[average during tests]
0.056
0.049
Clearly discernible effect.
0.076
0.065
Setting midway between the
0.065
0.056
Extraction level
No noticeable effect on
flames, but sufficient to
capture all emissions.
above two extraction rates.
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30
0.08
0.07
Mass flow rate (kg/s)
Volume flow rate (m³/s)
Flow rate
0.06
0.05
0.04
0.03
0.02
0.01
0
No noticeable
effect on flames
Midway
Clearly
discernible effect
Figure 3.1 Three extraction levels
An empirical hood design equation was used to calculate the air ‘capture’ velocities at the
stove (Committee on Industrial Ventilation 1982:5.101) which correspond to the above
extraction rates. Calculations are made according to the formula Q = WHV where:
Q is the volumetric extraction flow rate (m3/s),
W is the width of the open side, in this case 800 mm,
H is the height of the open side above the process surface, in this case 600 mm, and
V is the capture velocity at the process surface (m/s).
In this experiment Q is measured, and therefore V can be calculated: V = 2.083Q. Capture
velocities for the three extraction levels used ranged from 0.10 to 0.12 m/s. These capture
velocities are lower than typical air currents in a closed room which are usually taken to
be 0.25 m/s (Committee on Industrial Ventilation 1982:4.5).
3.2.3 Significance
A level of significance of 10 % (a 90 % confidence that the null hypothesis is true) is
common for experiments of this nature (Baldwin 1987:206,207). The level of significance
chosen for this study is 5 % (a 95 % confidence level) because of the importance of these
investigations in the early stages of developing stove emission testing guidelines.
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31
A 3x3 factorial design with 2 repetitions per treatment was used. This meant that 18 tests
were conducted. The tests were fully randomised. Please refer to Appendix C for a brief
discussion on the importance of these parameters.
a) Fuel
Type, ash content, burning characteristics. The wood, Eucalyptus grandis, which is
used in these tests is an exotic wood indigenous to Australia, and is grown extensively in
South Africa on a commercial basis. Amid considerable controversy, Eucalypts have been
introduced in Africa more widely than any other species: They grow quickly, but
consequently have high water consumption. Many of the negative ecological effects that
have been blamed on Eucalyptus are however increasingly being attributed to poor
management systems (Munslow and Katerere 1988:162,163). Relevant properties of
Eucalyptus grandis are listed below (CSIR, Forestek departmental database; Eberhard
1990:21, chemical analysis of a number of samples was carried out to determine the
sulphur content):
Table 3.4 Properties of Eucalyptus grandis
Botanical name:
Eucalyptus grandis
Hardwood / Softwood:
Hardwood
Trade name:
Saligna
Original distribution:
Eastern Australia
Texture:
Course and even
Grain:
Straight
Average density at 10% moisture content:
615 (500-800) kg/m3
Gross lower calorific value:
19.76 MJ/kg
average
sapwood 19.82 MJ/kg
heartwood 19.69 MJ/kg
3
Calorific value by volume
11700 MJ/m3
Percentage sulphur content, S2 by mass
0.04 ± 0.01 %
32
Calorific value by volume has been included here since calorific value in itself is not a good
indicator of usefulness for fuel – studies have indicated that a volume basis may give a
better indicator of rural user preference (See Eberhard & Poynton 1986:28.5,6).
Ash is composed mainly of compounds of alkali metals and alkali earths. Mineral content
varies considerably according to the species, locality and soil contamination (Shafizadeh
1981:106). Bark in general contains more ash than wood so all wood was debarked before
use. The wood did not contain any blue stain or rot.
Eucalyptus grandis is considered a ‘good’ fuelwood (for barbecuing, for example). It is,
however, not used extensively in rural areas of Southern Africa because it is seldom grown
outside commercial plantations (see Eberhard & Poynton 1986:28.6-8 for commonly used
wood species).
Fuel size. Large pieces of wood burn more slowly than small pieces (Joseph & Shanahan
1980:11). The use of ‘sieves’ for the size selection of coal for the testing of domestic
cooking appliances is described in SABS 1111 (1976). The method is based on BS 1016
(1979:part 17). The selection of wood ‘diameter’ used in this study is based on the same
principle. Three rings with internal diameters of 60 mm, 30 mm and 15 mm were used to
sort the split wood pieces. Pieces greater than 60 mm were split further. Pieces smaller
than 15 mm were used as kindling in the ignition process. Pieces which were greater than
30 and less than 60 mm were used for these tests, while those between 15 and 30 mm were
rejected. The selected wood was cut to 100 mm lengths.
Moisture content. Moisture in the wood acts as a heat sink and lowers combustion
efficiency and hence increases emissions (Shafizadeh 1981:105). The moisture content of
the batches of wood was measured daily. A randomly chosen piece of each size was
weighed, heated at 105 °C for 24 hours, and re-weighed. Moisture content can then be
calculated as described in Baldwin (1987:56) or VITA (1985:30):
Moisture content x =
Mwater mass of moisture in sample
Mwood mass of oven dry wood sample
Measured moisture content was 11% ± 1% over the entire testing period.
Consistency. The combustion properties of wood vary with the part of the plant used
(Cline-Cole 1990:79). One of the reasons however for the popularity of Eucalyptus grandis
in South Africa is its consistency (Green Heritage Committee 1978:7). Although this refers
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33
specifically to the commercial timber and paper industries it is a good indicator of
combustion consistency too. Batches of 20 kg were prepared using sieves as described
above. Each batch was then thoroughly mixed to give each piece an equal chance of being
selected.
b) Stove
Control. The only stove which has an air inlet control is the one pot metal stove. The
stove was lit with the vent completely open and it remained open during the high power
phase. The inlet opening was set at 25 % during the low power phase.
c) Process / task
Amount of water. In the VITA standards (1985:2) it is recommend that the pots be filled
to two thirds capacity. The pots used in this study have a capacity of 5.5 litres; two thirds
would therefore be 3.67 litres. The South African Bureau of Standards (1403: 1986) use
one litre of water. The amount of water is directly related to the time to reach boiling
point. Two litres were used as a convenient amount (just over one third capacity) which
would prevent excessively long boiling times (in the range 15-25 minutes depending on the
stove type). The effect of different amounts of water is considered in Chapter 4.
Purity of water. Municipal tap water was used. It was assumed that this was consistent
throughout the experiment.
Cooking duration. The WBT entails bringing the water in the main pot to boil and then
simmering it for 30 minutes (VITA 1985:2,3).
Power levels required. The power levels used during a cooking task are mainly operatordependent and partly dependent on stove and wood type. The VITA standards specify that
during the ‘high power’ phase the operator should “control the fire with the means
commonly used locally to bring the first pot to a boil as rapidly as possible”, and, during
the ‘low power’ phase, “maintain the fire at a level just sufficient to keep the water
simmering. Use the least amount of wood possible and avoid vigorous boiling.” (1985:2,3).
With traditional open fires, power level or wood burning rate is frequently controlled by
manoeuvring sticks of wood arranged in a star shape around the fire. Particularly high
powers are obtained by adding small chips of wood, accompanied by vigorous blowing. The
following comments on this method can be made:
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34
•
very precise control of the fire temperature is possible – when using an enclosed stove
without air dampers control is more difficult.
•
pre-heating of wood – with stoves the fire is often quenched when new wood is added
and hence fire temperature initially decreases before the wood starts to burn.
•
wood size is usually adjusted to suit power requirements – the VITA standards state
that the wood should be “preferably pieces of uniform size” (1985:1). For these tests
the wood size was specified as described above (sub-section a) and therefore the fire
temperature had to be controlled in other ways.
The fuel feed rate (dependent on when wood is added and how much is added) is
particularly important in the control of fire temperature, and hence of power levels. It has
also been found that the quantity of wood added to a fire greatly effects emissions (Cooke
et al 1982:147). Different procedures for wood addition were followed during the heating
up phase and the simmering phase.
During the heating up phase wood was added only once, 5 to 6 minutes after ignition. At
this time the firebox of the enclosed stoves was filled to capacity. Wood was placed on the
grate of the improved open fire in such a way as to maintain the ‘star’ shape – not all the
fuel in the open fire was thus exposed to flames immediately and pre-heating of the wood
occurred.
One piece of wood at a time was added during the simmering phase as and when required.
To maintain the water temperature one piece was added to the enclosed stoves soon after
the flames died down (all the volatiles were consumed) – the water temperature can be
maintained in the stoves with glowing char alone, but new wood cools the fire appreciably.
To maintain the water temperature using the improved open fire, however, flames are
continuously required. Wood was added before the flames died and in such a way that the
fire was not quenched. As the flames eventually died down, this new piece of wood could
be manoeuvred into the fire until it started to burn with flames at one end. Since it was
required that only char was present when boiling point was reached (so that efficiency
could be determined, see section 2.6) a piece of wood was always required at the start of
the simmering phase.
Fuel feed rate, even using the above guidelines, is a subjective process (see sub-section e
below). With a randomised factorial design small variations can be ignored since they have
a random influence evenly distributed across the tests.
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35
d) Pots
Type and size. Two aluminium saucepans 250 mm in diameter and 120 mm high, 1 mm
thick were used (capacity 5.5 litres). These pots are typical of those used by rural dwellers
in Mpumalanga (Kennedy 1990:53), although this is not a specific requirement for this
study.
Heat transfer characteristics. The same two pots were used throughout the testing
programme. The pots were cleaned thoroughly after each test to ensure that heat transfer
rates to the water remained consistent.
Pot lids. No pot lids were used during these tests to avoid errors associated with the
goodness of fit of the lids and with lid orientation in (generally) non-circular pot rims (see
also VITA 1985:1). The use of pot lids is an important part of efficient cooking practice,
and is practised by many different cultures – the effect of lids is considered in Chapter 4.
e) Operator
Ignition method. A 420 x 580 mm sheet of newsprint was crumpled to form the kindling.
Further kindling, 0.03 kg exactly, was placed in a ‘wigwam’ arrangement evenly around
the paper. The test wood (sized as described in sub-section a above) was then added to
make a combined mass of approximately 0.15 kg. The paper was lit in two places (on
opposite sides of the fire).
Skill, stacking of wood. A number of trial runs were conducted with each stove until
effective methods of stacking, adding wood and operating the stove were discovered. These
were then kept the same during the tests. Wood was added in such a way as to maintain
the basic ‘wigwam’ shape and to keep the fire evenly distributed in the firebox.
Fire attendance. Variations in fire attendance can make a big difference in stove
performance (up to 100%) (Joseph & Shanahan 1980:7). Two precautions were taken:
using a consistent method, and careful recording of each intervention (what was done and
when it was done). During the rapid heating phase from room temperature greater
intervention from the tester is required than during the simmering phase.
Fuel feed rate. The fuel feed rate has been described above under the section power
levels required (sub-section c).
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36
Definition of ‘boiling’. A thermocouple was suspended at the centre of the saucepan
15 mm from the bottom. The water in the pot was considered to be boiling when the
thermocouple indicated 94.4 °C (the boiling point at the local altitude) for at least 10
seconds.
Definition of ‘simmering’. Water was kept simmering for 30 minutes once boiling point
had been reached. The fire was maintained at a level sufficient to keep the water bubbling
gently – within 5 °C of boiling point. The water did not boil vigorously at any time during
the simmering phase.
Definition of ‘end of test’. In accordance with the VITA test definition the test was
ended 30 minutes after the start of the simmering phase (1985:3).
f) Environmental
Wind speed. Even small amounts of wind can affect stove performance significantly
(Baldwin 1987:85). Since the testing rig was situated indoors and each stove was shielded
from room winds on three sides the only effect of ‘wind’ would be caused by the extraction
hood, which is an experimental variable.
Temperature. Room temperature was recorded throughout the experiment.
Relative humidity. Variations in humidity were ignored. Wood moisture content which
varies with relative humidity and wood species (VITA 1985:30) was measured daily. It did
not vary by more than 1 % during the whole test period (more than a year).
Atmospheric pressure. The atmospheric pressure during the tests was not measured.
The influence of changing atmospheric pressure on boiling temperature was considered to
be negligible.
Altitude. Johannesburg, where all the tests were carried out, is at an altitude of about
1700 metres above sea level. Baldwin (1985:85) points out that high altitudes will have a
small effect on efficiency as determined by the Water Boiling Test and a large effect on
field test efficiencies due to longer cooking times at lower boiling temperatures. McCrillis
and Burnet (1990:100) found a decrease in unburned hydrocarbons (specifically
polynuclear aromatic hydrocarbons at a 90% confidence level) with a 735 m increase in
altitude.
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37
g) Experimental
Influence of enclosure on stove operation. The enclosure (a hood plus three walls) will
effect the fire in two ways: Air flow patterns will be more constrained than from those in
an open area; and the reflection from the test rig walls of radiation from the stove will
increase the fire temperature slightly. Reflection from the test rig walls was ignored.
Influence of ‘ease of access’ on skill. The arrangement of the testing rig means that
only one side of the fire is easily accessible. This has an unmeasured effect on the way the
fire is arranged and controlled – and hence on stove performance.
Experimental variables can be divided into those that can be controlled and those that
cannot. Uncontrolled variables are either measurable or immeasurable. Variables which
cannot be measured remain unknown (Wilson 1952:38). The following table summarises
the experimental variables and indicates whether they are controlled, measured or are
believed to be insignificant (and are thus ignored). Note that variables which are believed
to be insignificant may in fact be important – a fully randomised design, as used here,
largely avoids this problem (see Appendix C). In addition to the variables mentioned here
there are an infinite number of other variables (Wilson 1952:38; Fisher 1951:18,19)
considered to be irrelevant.
Table 3.5 Summary of experimental variables
Parameter
Approach
Fuel type
Controlled. One type of fuel used, mixed and randomly selected.
Fuel size
Controlled. Two diameters used, 100 mm lengths, randomly selected.
Fuel moisture content
Measured. Random samples collected and measured on a daily basis.
Fuel consistency
Ignored. Fully randomised design.
Stove control
Controlled. Damper on one pot metal stove fully open during heating up, 25 %
open during simmering phase.
Task, Quantity of water
Controlled. 2 litres used.
Task, Purity of water
Cooking duration
Measured and Controlled. Time to boil measured, simmered for 30 minutes.
Power levels required
Measured and Controlled. Cooking devices operated consistently and at the same
time with respect for traditional subjective practices, all interventions recorded.
Pots, type and size
Controlled. 5.5 litre capacity aluminium saucepans.
Heat transfer
characteristics
Controlled and Ignored. Pots thoroughly cleaned after each test, fully
randomised design minimises the effect of pot deterioration.
Pot lids
Controlled. No pot lids used.
Operator, ignition method
Controlled. 420 x 580 mm sheet of newsprint, 0.03 kg of kindling, and 0.11 kg of
larger pieces arranged in wigwam, fire lit at two places.
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38
Fire operation skill
Controlled. Trial runs to learn consistency.
Fire attendance
Controlled and Ignored. Consistent approach, with a fully randomised design.
Definition of boiling
Controlled. Thermocouple indicates 94.4 °C for at least 10 seconds.
Definition of simmering
Controlled. 30 minutes, gentle bubbling within 5 °C of 94.4 °C.
Wind speed
Controlled. Ensured the absence of wind.
Temperature
Measured. Room temperature measured continuously during test.
Relative humidity
Ignored. Randomised design and daily measurement of wood moisture content.
Atmospheric pressure
Altitude
Controlled and Measured. All tests conducted in Johannesburg at 1700 m above
sea level.
Effect of hood
Measured. Experimental variable.
Effect of enclosure
Effect of ‘ease of access’ on
skill
Controlled. Access to the stoves remained consistent.
3.3
Results and discussion
3.3.1 Fire temperature, power and efficiency
For both fire temperature and fire power, the effect of extraction level cannot be detected
at the 95 % confidence limit. This is true for the heating up phase as well as the
simmering and overall figures – during any phase the three stoves operate at different
temperatures and powers.
Figure 3.2 shows the average overall fire temperature for the three stoves at the different
extraction levels. The one pot metal stove reaches the highest temperatures and the
improved open fire the lowest. The enclosed firebox of the one pot stove ‘focuses’ and
contains the fire thus leading to higher fire temperatures. The two pot ceramic stove has a
greater thermal inertia than the one pot stove due to its large mass (18 kg) and therefore
it takes longer to heat up.
It is clear that extraction level does not have an effect on the fire temperature. The fire
temperatures for the heating up phase as well as the simmering phase follow similar
trends.
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39
540
550
470
600
510
Fire temperature (°C)
520
410
500
450
400
380
300
370
200
High
100
0
Medium
1 pot
stove
2 pot
ceramic
stove
Stove type
Low
Extraction level
Improved
open fire
Figure 3.2 Average fire temperature and extraction level
The fire power (the ratio of the energy content of the fuel consumed during a test or phase
to the duration of the test or phase) follows similar patterns to fire temperature. The fire
power of the two pot ceramic stove is relatively high. A large proportion of this energy goes
into raising the temperature of the stove itself.
P=
m f h fo − m c hco
T
where
P is the average fire power (kW)
m f is the mass of fuel (kg)
h fo is the enthalpy of combustion of the fuel (kJ / kg)
m c is the mass of char remaining (kg)
hco is the enthalpy of combustion of char (kJ / kg)
T is the test duration (s)
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40
Table 3.6 Fire power (kW) and extraction level
Low
Medium
High
1 pot metal stove
3.9
3.8
4.3
2 pot ceramic stove
4.2
3.9
3.8
Improved open fire
3.4
3.5
3.3
Stove efficiency (calculated according to the following equation) is defined as the ratio of
energy entering the pot to the energy content of the fuel consumed. The energy entering
the pot produces two measurable effects: raising the temperature of the water and
evaporating water. For the one pot cooking devices the stove efficiencies are for all
practical purposes identical to the widely used ‘Percentage Heat Utilised’ (Baldwin 1987).
Baldwin uses initial rather than average mass of water in the first term of the numerator.
A correction relating to temperature dips during the simmering phase is recommended,
but in fact not applied by Baldwin (1987); the correction is retained in this study but its
effect is very minor. For the two pot stoves the energy absorbed by the second pot is
included in the efficiency calculation. Baldwin (1987) recommends that the second pot be
ignored since “The additional heat recuperated... is ineffective in actually cooking food
because it is too low in temperature and because it cannot be easily controlled”. From the
author’s personal experience in the field this has not been the case: the second pot is
frequently used effectively on the stoves tested here.
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41
$k⎤
⎡ c p m k ( ΔT ) k + h fg m
⎥
⎥⎦
k =1 ⎢
⎣
where
η is the efficiency
k is the pot number
K is the number of pots
c p is the specific thermal capacity of water (kJ / kgK)
K
η = ∑⎢
m k is the average mass of water in each pot (kg)
ΔT is the rise in water temperature (K), with correction (see Appendix A.3.2(d))
h fg is the enthalpy of vaporisation of water (kJ / kg)
$ k is the mass of water evaporated from each pot (kg)
m
m f is the mass of fuel used during the phase (kg)
h fo is the enthalpy of fuel combustion at the reference temperature (kJ / kg)
m c is the mass of char remaining at the end of the phase (kg)
hco is the enthalpy of char combustion at the reference temperature (kJ / kg)
Table 3.7 Efficiency (%) and extraction level
Low
Medium
High
1 pot metal stove
22
22
18
2 pot ceramic stove
23
26
24
Improved open fire
21
20
22
The efficiency of the two pot ceramic stove was greater than that of the improved open fire
and the one pot stove but the means were not separable at the 90% confidence level
(calculated using Student’s t test).
At the 95 % confidence limit no interaction between stove type and extraction level can be
detected for fire temperature, fire power or efficiency. This indicates that to the desired
level of significance the different stove types did not react in different ways to the three
extraction rates.
The fact that the forced extraction had no detectable effect on the stove fire temperature,
fire power and efficiency indicates that extraction did not alter the stove operation
appreciably.
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3.3.2 Emissions
The total emission mass and the emission factors for the three pollutants, CO, SO2 and
TSP are discussed below. Emission masses per test or cooking task relate directly to
human exposure. They are calculated using the following equation:
⎡T
⎤
M E = ⎢ C M v& flue dt ⎥
⎢⎣ t = 0
⎥⎦
where
M E is the mass of pollutant (g)
∫
C M is the pollutant concentration at time t (g / m 3 )
v& flue is the flue extraction rate (m 3 / s)
Pollutant levels are usually quoted in the literature as emission factors. The pollutant
emission factor is defined as the ratio of the mass of pollutant to the mass of fuel burned ‡ .
Since the denominator of emission factor is the mass of fuel burned a stove which is
inefficient, but releases a similar mass of pollutant to another, will have a reduced
emission factor. Emission factors therefore include the effects of efficiency and thus favour
the less efficient stove. Emission factors are useful in environmental studies, where the
total emissions in a community are to be calculated, or in source apportionment studies
(for example Smith et al 1992 and 1993). In a study where stoves are being compared the
total emission mass seems a more useful indicator of potential hazard. Ahuja et al
(1987:260) suggest that to compare stoves a ‘standard task’ should be defined and then
emission masses can be compared (the standard task was defined as the raising of 3.5 kg of
water by 60°C – the transfer of 879 kJ to the pot). Here the task is the raising of 2 kg of
‡
Note that emission factor E =
ME
m f − m c (used, for example, by Macumber & Jaasma,
1982) is not exactly the same as the emission factor used by some researchers (Ahuja et al
1987, Joshi et al 1989, Joshi et al 1991) where the denominator m f −
hco
h fo
m c is used. To
relate the emission of a pollutant to the ‘equivalent wood consumed’ defined according to
the enthalpy of combustion of the fuel and char is deceptive from a mass balance
perspective and would lead to higher factors (generally about 25%) than those reported
here.
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43
water by approximately 70 °C for the heating up phase followed by 30 minutes simmering.
During the heating up phase this represents 585.7 kJ transferred to the water.
Snedecor’s F factor, which is used as an indication of the confidence limit for the rejection
of the null hypothesis in the analysis of variance, is given below in Table 3.8 (df1 and df2
are the degrees of freedom of the source and error terms respectively). F factors higher
than those tabulated indicate that the null hypothesis is rejected. The greater the F factor
the greater the degree of confidence in the rejection of the null hypothesis * . F factors
depend on the number of degrees of freedom in the terms being assessed.
Table 3.8 Confidence limits for extraction and stove
Applies to...
Extraction level
or Stove type
Interaction
Snedecor’s F distribution
Snedecor’s F distribution
95 % confidence limit
90 % confidence limit
9
F = 4.26
F = 3.01
9
F = 3.63
F = 2.69
df1
df2
2
4
Each factor with a rejected null hypothesis at 95 % confidence (5 % significance level) has
been shaded in the tables below.
Wood combustion is complex and emission levels are dependant on numerous factors. The
reader is referred to Appendix D for an introduction to this subject. Here we merely point
out the basic processes:
•
CO is a product of incomplete combustion which forms where there is insufficient
oxygen or where the temperature is high. At lower temperatures and in the presence of
sufficient oxygen the formation of CO2 dominates (see Shafizadeh 1981:123). We
therefore would expect CO to increase with increasing burn rate and fire temperature.
*
The null hypothesis states that the factor in question has no detectable effect. For
example, that emissions are independent of stove type.
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44
•
SO2 on the other hand is usually considered a product of complete combustion. We
therefore expect SO2 to decrease as CO increases. If burn rate increases substantially
however, SO2 and CO may both increase, the smaller variations being masked. Organic
or inorganic sulphur in the wood is either emitted as SO2, is emitted in the particulates
as sulphates, or remains in the ash also in the form of sulphates (Myers et al 1973:6).
•
TSP are products of incomplete combustion and are made up predominantly of
complex unburned organic compounds or elemental carbon (soot). At high
temperatures, and in the presence of insufficient oxygen, carbon monoxide may react
to form carbon dioxide and elemental carbon. We would expect, in general though, that
TSP will increase with burn rate and fire temperature.
a)
Carbon monoxide
The effect of the extraction on the emission mass can be clearly seen, although this effect
is smaller than the changes in emission levels between stove types.
51
50
CO mass (g)
34
45
60
21
40
28
30
34
10
20
12
10
0
High
15
1 pot
stove
2 pot
ceramic
stove
Stove type
Medium
Low
Extraction level
Improved
open fire
Figure 3.3 CO mass and extraction level
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45
The F factor for the extraction level was much smaller than the F factor for the three
stoves. Thus extraction has a much smaller effect on CO emissions than does stove type.
Table 3.9 F factors for CO mass
Source
F
Extraction
7.5
Stove
56.3
Extraction x Stove
.76
71
80
CO emission factor (g/kg)
47
78
70
31
60
41
50
40
17
43
30
20
17
High
10
24
0
1 pot
stove
2 pot
ceramic
stove
Stove type
Medium
Low
Extraction level
Improved
open fire
Figure 3.4 CO emission factor and extraction level
The effect of the forced extraction can be clearly seen for the CO emission factor, with the
general trend of a decreasing emission factor for increasing extraction rate.
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46
Table 3.10 F factors for CO emission factor
Source
F
Extraction
23.6
Stove
169.3
Extraction x Stove
5.8
Interaction of extraction and stove type could be detected for the emission factor at 98 %
confidence – this indicated that different stoves were affected by the extraction to different
degrees.
b)
Sulphur dioxide
Typical results for sulphur dioxide are shown in the figure and table below. The effect of
the forced extraction cannot be detected at the 95 % confidence limit and the differences
between the three stoves are particularly clear.
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47
0.94
1.35
SO2 emission factor
(g/kg)
1.4
1.01
1.2
1
0.25
0.8
0.6
0.33
0.13
0.4
0.2
High
0.33
0.09
0
Medium
0.15
1 pot
stove
2 pot
ceramic
stove
Stove type
Low
Extraction level
Improved
open fire
Figure 3.5 SO2 emission factor and extraction level
Table 3.11 F factors for SO2 emission factor
Source
F
Extraction
2.2
Stove
152.1
Extraction x Stove
0.6
Stove type strongly affected SO2 emissions but there was no detectable effect of extraction
at 95 % confidence. The extraction did not change the SO2 emission characteristics.
SO2 is usually considered a product of complete combustion but here the stove with the
highest levels of CO (a product of incomplete combustion) also had the highest levels of
SO2. The reason for this is not known although there is a relationship between the
formation of SO2 and fire temperature (see Figure 3.2). It is further possible that burn
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48
rate is the dominating factor in the SO2 emission levels – the one pot stove has the highest
burn rate of the three stoves tested. Chemical analysis of the wood, char and the ash
showed that sulphur remained in each of these – all the sulphur in the wood is not
converted to SO2 during combustion (percentage sulphur, S2, by mass, 0.04 ±.01 % in the
wood, 0.09 ±.01 % in the char, and 0.23 ±.01 % in the ash present as sulphates).
c)
Total suspended particulates
TSP mass is shown in Figure 3.6 below. There is no systematic decrease in TSP mass with
an increase extraction level. A medium extraction level yielded the lowest TSP readings.
The reason for this is not known and would need further investigation.
1.17
1.2
0.97
TSP mass (g)
1
0.79
0.57
0.53
0.8
0.6
0.56
0.4
0.34
0.43
0.61
0.2
High
0
Medium
1 pot
stove
2 pot
ceramic
stove
Stove type
Low
Extraction level
Improved
open fire
Figure 3.6 TSP emission mass and extraction level
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49
1.6
TSP emission factor (g/kg)
1.6
1.5
1.2
0.83
1.4
0.85
1.2
1
0.8
0.5
0.6
0.98
0.72
0.62
0.4
High
0.2
0
Medium
1 pot
stove
2 pot
ceramic
stove
Stove type
Low
Extraction level
Improved
open fire
Figure 3.7 TSP emission factor and extraction level
The effect of stove type on the TSP emission factor can be detected at 99 % confidence.
The effect of extraction on TSP emissions was not significant at 95 % confidence.
3.4
Summary and conclusions
In this chapter we have discussed the results of the first set of tests which involved the
measurement of the influence of the test rig on the stove operation and on the
measurement apparatus.
A summary of the findings for the 95 % confidence limit are shown below in Table 3.12.
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50
Table 3.12 Summary of results for the influence of the test rig on emissions at
the 95 % confidence limit
Parameter
Significant effect of
extraction level
stove
stove and extraction
level interaction
NO
YES
NO
Efficiency
NO
YES
NO
CO emissions
YES
YES
NO
SO2 emissions
NO
YES
NO
TSP emissions
NO
YES
NO
Power and fire
temperature
Fire power, fire temperature and efficiency are not affected by the rate of extraction used
in these tests.
SO2 and TSP show no significant effect of extraction; although there is a measurable
influence of extraction on CO emissions it is considerably smaller than the effect of the
stove. There is however the potential for the forced extraction to influence these emission
measurements. Care must obviously be taken to extract the combustion gases at the
lowest rate possible to capture all emissions.
There is no detectable interaction between stove type and extraction level (at 95 %
confidence). This indicates that the influence of the extraction is independent of the type
of stove. If measurements are influenced by the extraction they are all affected to an equal
extent. An extraction hood can therefore be used with confidence to compare emissions
from different stoves provided the extraction level does not change between tests.
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51
4
The screening of experimental variables
The five experimental variables examined in this study are believed to be important
parameters in emissions tests and therefore must be carefully specified when such tests
are carried out. The variables are screened to find out if they influence emissions.
4.1
Background and aims
The VITA efficiency testing ‘standards’ (1985), which were intended to allow international
comparisons of stoves, have been questioned on a number of levels (Bialy 1991:5):
1. The tests may not be sufficient for the right choices to be made;
2. The methods are not as widely used as intended (see variations in Baldwin 1987:84;
Stewart 1987; Butcher et al 1984:3; Jayaraman et al 1989:121; Joshi 1989:764; and
Ahuja et al 1987:249,254); and
3. As a basis for international comparison they are lacking because they do not specify
some important parameters. A method intended to allow comparison between different
stove programmes around the world would need to be far more specific than that given
in the VITA standards.
There is no one perfect stove for all areas (Kristoferson & Bokalders 1991). A successful
stove in one area may be a disaster in another since stove performance is a function of
many variables (Bialy 1991:9). Internationally standard tests are of no use to development
organisations attempting to find the most “effective and desirable stoves for a specific
social and economic context” (VITA 1985:vii).
In the design of tests for emissions a similar tension exists between methods which allow
inter-programme comparisons and methods which are specific to a local context. “It makes
little sense to establish stove efficiency and emission rates based on fuel types and burning
rates that have little if any relationship to the fuel and burn rates normally used.”
(Sanborn & Blanchet 1982:198)
It seems clear that recommendations or guidelines for stove emission measurement are
required rather than strict ‘standards’. The purpose of these recommendations would be
to ensure that any results were consistent (giving the same results each time under the
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52
same local conditions) and representative (giving some indication as to what can be
expected in the field, that is, within a specific context).
The variables to be examined are listed below:
1. The type of stove (included for the purpose of studying the interaction between it and
the other four variables),
2. The amount of water used in the pot,
3. The use of pot lids,
4. The type of wood, and
5. The size of wood.
4.1.1 Stove type
A number of studies have been carried out in which different stoves are compared in terms
of their emission characteristics. Here we are concerned more with the interaction
between the type of stove and the four other variables; the reader is referred to
Appendix E for a detailed comparison of all 5 cooking devices mentioned in this work.
Brief mention is made below of studies in which low-cost cooking devices intended for use
in underdeveloped countries have been compared:
Butcher et al (1984) compared the emissions from three stoves using an extraction hood.
They do not, however, provide any details of the individual emission characteristics of
these stoves.
Joshi et al (1989) compared four metal stoves fuelled with wood, crop residue or dung. It
was found that increasing stove power level led to reduced efficiencies. They measured
increasing CO and TSP emission factors with increasing efficiency, but no correlation was
found with emission mass per task.
Nangale (1992) compared a traditional ‘three stone fire’ and an ‘improved’ metal stove.
Emissions for the stove were greater than those from the traditional open fire by factors of
about 5 for carbon monoxide and total suspended particulates and 2.2 for hydrocarbon
acidity.
Two stoves are compared in this section, an improved open fire and a one pot metal stove,
but the differences between the emission characteristics of the stoves are not of primary
importance here – they are considered in Chapter 5. The variable has been included here
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53
because a knowledge of the interaction between the stove and the other four experimental
variables could be important in the validity of comparative tests.
In the VITA standards (1985:2) it is recommend that the pots are filled to 2/3 capacity.
The South African Bureau of Standards (Number 1403 – 1986) use 1 litre of water. No
references could be found in the literature to studies into the effect of different quantities
of water on efficiency or emissions.
It seems probable that, during the heating up phase, heating more water will increase
total emission mass because of the longer time to reach boiling point, and leave the
emission factor unchanged. During the simmering phase (which lasts for 30 minutes
irrespective of the quantity of water heated) emissions would not be expected to change.
4.1.3 Pot lids
All emission studies reported in the literature have been conducted using lids on pots but
efficiency studies are usually conducted without pot lids.
The use of pot lids in efficiency measurements has been the subject of considerable debate.
Initially the VITA standards recommended the use of lids (December 1982 first edition). It
is recommended that lids are not used in the revised edition (VITA 1985). The reasons
(suggested by Baldwin 1987:262,263) are that “lids proved to be cumbersome in practice
and additionally did not reduce the scatter in the data but rather increased it.”
The amount of water evaporated when pot lids are used is partially dependent on how well
lids fit, and partially dependent on the fire power. If the water temperature during the
simmering phase is below boiling very little water vapour will escape, but if the water boils
the lid will be pushed open. The Specific Fuel Consumed (SFC), the ‘standard’ measure of
efficiency, which is defined as fuel used during a test divided by the mass of water
evaporated (VITA 1985:7) is extremely sensitive to the use of lids. The VITA standards,
however, erroneously allow the use of lids “if they are needed to reduce the effect of drafts
on evaporation rate” (1985:4).
Baldwin points out that “by not using a lid, evaporation rates are higher and the stove
must be run at a somewhat higher power to maintain the temperature than is the case
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54
with a lid.” (1987:263). This means that without a lid low power is not really achieved
during the simmering phase.
Lids are, however, used by a large proportion of the rural cooks in Mpumalanga, South
Africa where the author has conducted field studies.
4.1.4 Wood type
Emissions from different fuel types in rural stoves have been compared in two studies, but
very little work has been done in this field:
Butcher et al (1984) compared emissions from 9 different fuel types – six tropical tree
species, cow dung, coconut husks and charcoal. He does not, however, give any details of
the different emissions characteristics of the fuels.
Joshi et al (1989) compared emissions from three different fuels: wood, dung and crop
residues. Dung and crop residues gave far higher emissions than the wood.
For metal heating stoves in developed countries a difference in emission factor between
species of wood has been recorded although this difference is not statistically significant
(Smith 1987:269). Emission differences between hardwoods and softwoods do not appear
to be large and as Smith points out “the variation of emissions with combustion conditions
is much larger than that due to differences in the fuel contaminants of most biofuel”
(1987:268).
4.1.5 Wood size
No research into the effect of wood size on emissions from rural stoves could be found in
the literature. In a study into the effect of size on emissions of metal heating stoves
however, it was found that the smallest pieces of wood had the highest emission factors
and the largest pieces had the lowest emissions (Cooke et al 1982:151). The reason
suggested for this was that smaller pieces have a shorter distance for the pyrolysis
products to diffuse, a larger surface area to mass ratio, and a reduction in the time
required to heat the entire piece of wood. This finding is also reported by
Smith (1987:288). Smaller pieces of wood also burn faster than large pieces (Joseph &
Shanahan 1980:11).
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55
In a study on the amount of wood loaded into the combustion chamber it was found that,
at the same burning rate, emissions increased with increasing quantity (Cooke et al
1982:147). The reason given is that an increased quantity of wood is then subject to preburning pyrolysis. We would expect the same to apply to the use of smaller pieces of wood
which increase the surface area of fuel directly exposed to the heat.
4.2
Experimental design
Five variables are considered: stove type, amount of water heated, whether pot lids are
used or not, wood type, and wood size. Each variable with its null hypothesis is stated in
the table below:
Table 4.1 Five variables and hypothesis
Variable
Null hypothesis
Stove type
Emissions are independent of stove type.
Amount of water
Emissions are independent of the amount of water in the pot.
Pot lid
Emissions are independent of whether a pot lid is used or not.
Wood type
Emissions are independent of the type of wood used.
Wood size
Emissions are independent of the size of the wood used.
In addition to the effects of the single variables listed above the factorial design indicates
the ten first order interactions. Second and higher order interactions are grouped and
used as an indication of error.
4.2.2 Levels
Each of the variables are set at two levels as described below.
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56
a) Stove type
Two types of stove were selected. The selection was based on the need for two significantly
different stoves principally in terms of emissions.
Table 4.2 Two cooking devices used in the variable screening tests
Improved open fire: A metal tripod frame 100 mm high with a 10 mm square
grid supported 10 mm above the ground.
One pot metal stove: One pot ‘Mbaula’ – A one pot metal stove manufactured
in Malawi (with ceramic insulation). The stove is top fed (the pot must be
removed to add fuel), and has an adjustable damper to control air inlet.
b) Amount of water
Two levels of water were used – 1 litre and 2 litres. These quantities may appear to be
small for a pot capacity of 5 litres, but in order to keep the heating up phase under 25
minutes the volume had to be less than 3 litres.
c) Pot lids
Here, the question of pot lids is once again investigated. Emissions and efficiencies were
measured using pots with lids and without. A small hole (4 mm) was drilled in the lid of
the pots through which the thermocouple could be fitted.
d) Wood type
Wood is commonly divided into two main groups: softwoods and hardwoods. These names
do not refer to strength or density of the wood as is commonly assumed. Softwood trees
produce naked seeds borne on cone scales; and their leaves are usually needle-like.
Hardwood trees, on the other hand, produce seed in ovaries, bear fruit and have broad
leaves (CSIR 1993:13.3).
Not all types of wood are good fuel woods. In rural areas wood selected for cooking is based
on a number of important criteria. Those particularly important to stove evaluation are
(Cline-Cole 1990:77):
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57
•
Equilibrium moisture content
•
Drying rate
•
Smoke quality – agreeable or foul smelling
•
Smoke quantity
•
Combustion speed
•
Combustion character – steady or requiring continuous attention
•
Ignitability
•
Calorific value
•
Ash production
•
Ease of splitting
•
Ease of felling
•
Strength – hard or soft
•
Density
•
Charcoal production – the amount of char produced
Fuelwood species are selected by the user according to the specific purpose to which they
will be put (Eberhard & Poynton 1986:28.6).
It is not the intention of this study to provide culturally relevant information on particular
stoves, but rather to explore emission testing methods. The wood types were therefore not
chosen for their local Southern African relevance. Wood types which represent broad
categories according to their burning properties and which were freely available were
selected. For the measurement of the influence of the test rig on the emissions only one
type of wood was needed.
Two wood types selected for this study were Eucalyptus grandis, as used in the previous
chapter, and Pinus patula.
Relevant properties of Eucalyptus grandis have been given in Table 3.4.
Pinus patula is one of the eight most important pine species in South Africa. It was first
introduced from Mexico in 1907.
Pines are evergreens and are softwood trees that grow in summer rainfall areas – mainly
in north eastern areas of South Africa. Pine is not a preferred fuelwood in rural areas
(because it burns too quickly and does not make good coals) even though, as a softwood, it
has a slightly higher gross calorific value than most hardwoods (but a lower calorific value
by volume) (Eberhard & Poynton 1986:28.5).
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58
Properties of Pinus patula are listed below (CSIR, Forestek departmental database;
Eberhard 1990:22):
Table 4.3 Properties of Pinus patula
Botanical name:
Pinus patula
Hardwood / Softwood:
Softwood
Trade name:
SA Pine
Original distribution:
Central Mexico
Texture:
Fine, clearly visible growth rings
Grain:
Straight
Average density at 10% moisture content:
450 (350-610) kg/m3
Gross lower calorific value:
20.42 MJ/kg
average
sapwood 19.94 MJ/kg
heartwood 20.90 MJ/kg
Calorific value by volume
8633 MJ/m3
Baldwin (1987:178) gives typical gross calorific values of average hardwood (19.734±0.981
MJ/kg) and average softwood (20.817±1.479 MJ/kg).
e) Wood size
Wood of two sizes was sorted using sieves as described for coal sizing in Analysis and
testing of coal and coke: Size analysis of coal (BS 1016:Part 17:1979). Three rings with
internal diameters of 60 mm, 30 mm and 15 mm were used to sort the split wood pieces.
Table 4.4 Sieve sizes for the selection of wood
Size (diameter of sieve)
Use
d > 60 mm
Split into smaller pieces
d < 15 mm
Kindling used during ignition
15 to 30 mm
The smaller pieces
30 to 60 mm
The larger pieces
The selected wood was cut to 100 mm lengths.
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59
4.2.3 Significance
A level of significance of 5 % was chosen as described in Section 3.2.3.
Five variables each at two levels, gives 32 treatments. No treatment repetitions were
performed. The design was once again fully randomised.
A detailed description of each of the additional variables has been given in Section 3.2.5
above and they remain the same for this section.
4.3
Snedecor’s F factors greater than 4.49 indicate the rejection of the null hypothesis at 95 %
confidence. Note that each result presented is a mean for that variable over 16 tests.
4.3.1 Stove type
The performance characteristics of the two stoves are given in Table 4.5 below. More
precise control of the one pot metal stove than of the improved open fire was possible as
can be seen in the ‘turn down’ ratio from heating up to simmering phase for fire power
(turn down is the ratio of heating up power to simmering power; 1.5 for the improved open
fire and 2.6 for the one pot metal stove). The fire temperature of the one pot metal stove
did not decrease from heating up to simmering phases – the stove had become hot by the
start of the simmering phase and retained this heat during simmering. The difference
between the two cooking devices for overall and heating up efficiencies was not
statistically significant at 95 % confidence, however, simmering phase differences were
significant.
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60
Table 4.5 Performance characteristics of the two stoves
Improved open fire
One pot metal stove
Heating up
Simmering
Overall
Heating up
Simmering
Overall
Efficiency (%)
20.9
17.2
19.6
20.6
31.0
22.6
Power (kW)
3.5
2.4
2.7
4.4
1.7
2.5
‘Fire temperature’ (°C)
440
260
350
480
470
470
Time to reach boil (min)
12:30
12:00
The one pot metal stove emitted much higher levels of CO and SO2 than the improved
open fire but statistically equal quantities of TSP at 95 % confidence. These characteristics
are shown in Table 4.6. The TSP mass for the improved open fire increased during the
simmering phase whereas those of the one pot stove decreased (the emission rate
remained roughly constant – the simmering phase was approximately 4 times as long as
the heating up phase). It is suspected that this has to do with the uniform temperatures
which developed in the one pot metal stove during the simmering phase. In contrast, in
the improved open fire some wood smouldered and some burned with flames throughout
the simmering phase. In the one pot metal stove the simmering phase was predominantly
the burning of the char without flames. This ‘glowing combustion’ was not hot enough in
the open fire to keep the water simmering – flaming combustion was necessary (see
Appendix D for an introductory discussion of combustion principles).
Table 4.6 Emission characteristics of the two stoves
Improved open fire
One pot metal stove
Heating up
Simmering
Overall
Heating up
Simmering
Overall
Total CO (g)
3.6
6.5
10.1
15.1
11.9
26.9
17.3
41.2
26.2
62.5
103.2
71.6
Total SO2 (g)
0.03
0.006
0.04
0.16
0.11
0.27
Total TSP (g)
0.14
0.41
0.55
0.23
0.13
0.36
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61
In general the one pot metal stove had higher emissions than the improved open fire. The
primary reason is the restricted air supply to the one pot metal stove. It has also been
found that emissions can be reduced by the operator adding small quantities of wood more
frequently (Cooke et al 1982:149,150). The open fire arrangement favours this type of
combustion whereas the one pot metal stove encourages the user to add as much fuel as
possible at one time and then control the fire with the damper.
It can be seen from Figure 4.1 that, to a large extent, changing the amount of water used
in the pot had a very small effect on the overall operation of the stove in terms of fire
temperature. Fire power and efficiency behaved in a similar way. Only a fractionally
higher average fire temperature for 2 litres was reached during heating up phase than for
1 litre. This would mean that the time to reach boiling point would be almost double for
double the quantity of water, but we would expect there to be very little effect on the stove
emissions.
470
500
450
440
410
370
Fire Temperature (°C)
400
410
360
350
300
250
200
150
1 litre
2 litres
100
50
0
Heating up
Simmering
Overall
Phase
Figure 4.1 Fire temperature for 1 and 2 litres of water heated
The CO, SO2 and TSP emission factors were statistically independent of the amount of
water used. The heating up phase CO, SO2 and TSP mass demonstrated the effect of the
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62
increased time needed to bring twice the quantity of water to the boil. A comparison for
CO is shown in Figure 4.2 and Figure 4.3.
19.3
20
1 litre of water
18
2 litres of water
16
CO emission mass (g)
17.7
14
12
10
10.6
9.64
8.06
8.74
8
6
4
2
0
Heating up
Simmering
Overall
Phase
Figure 4.2 CO emission mass for 1 and 2 litres of water heated
80
70
1 litre of water
70.3
74.1
2 litres of water
60
48.2
50
40
39.5
49.6
40.3
30
20
10
0
Heating up
Simmering
Overall
Phase
Figure 4.3 CO emission factor for 1 and 2 litres of water heated
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63
4.3.3 Pot lids
It was found that pot lids reduced simmering and overall stove efficiencies (overall
efficiencies of 23.9 % without lids, 18.3 % with lids). This result, which appears to run
contrary to common sense, serves to illustrate the problem with the usual method used to
calculate efficiency. The evaporation of water, in the numerator of the efficiency equation,
is not the real aim of cooking: lids reduced evaporation which made a significant
contribution to the calculated simmering efficiency. It should be stressed that the fires
were tended sensibly and thus differently with and without lids as is evident from the fire
temperature data.
A pot lid had the greatest effect on fire temperature operation during the simmering phase
(illustrated in Figure 4.4). It is clear from this graph that to maintain simmering requires
a much lower fire temperature when pot lids are used.
500
460
450
460
450
450
Fire Temperature (°C)
400
360
350
280
300
250
200
No pot lids
Pot lids
150
100
50
0
Heating up
Simmering
Overall
Phase
Figure 4.4 Fire temperatures with and without pot lids in place
The lower fire temperature required when simmering with pot lids in place means that
stove emission masses were reduced during the simmering phase, and for the overall mass.
An example of the effect of the pot lids for TSP is given in Figure 4.5.
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64
0.58
0.6
Pot lids not used
TSP emission mass (g)
0.5
Pot lids used
0.4
0.35
0.34
0.3
0.22
0.2
0.19
0.15
0.1
0
Heating up
Simmering
Overall
Phase
Figure 4.5 TSP emission mass with and without pot lids
The CO, SO2 and TSP emission factors increased with the use of pot lids during the
simmering phase. The reason is that very little wood was needed to keep the water
simmering when lids are used (the fuel burn rate was 0.12 g/s without lids as against
0.04 g/s with lids during the simmering phase). TSP emission factors are shown in
Figure 4.6.
TSP emission factor (g/kg)
2
1.86
1.8
Pot lids not used
1.6
Pot lids used
1.46
1.4
1.19
1.2
1
0.8
0.87
1.17
0.78
0.6
0.4
0.2
0
Heating up
Simmering
Overall
Phase
Figure 4.6 TSP emission factor with and without pot lids
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65
4.3.4 Wood type
The two types of wood could not be statistically separated for fire power, fire temperature
or any of the emission parameters (CO, SO2 and TSP emission masses and emission
factors). To all intents and purposes they were the same. Figure 4.7 and Figure 4.8 show
this graphically.
3.99
3.99
4
Eucalyptus
3.5
Pine
Power(kW)
3
2.62
2.5
2.07
2.57
2.01
2
1.5
1
0.5
0
Heating up
Simmering
Overall
Phase
Figure 4.7 Fire powers for eucalyptus and pine
18.8
20
Pine
16
CO emission mass (g)
18.2
Eucalyptus
18
14
12
10
9.59
9.04
9.24
9.14
8
6
4
2
0
Heating up
Simmering
Overall
Phase
Figure 4.8 CO emission mass for eucalyptus and pine
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66
The reason for the similarity between the woods, especially in terms of emissions, is
unknown. The consistency of this finding is particularly remarkable. The factorial design
ensures that the experimental basis for findings is broad – here we have 16 repetitions at
each level under four different conditions.
The two wood types are appreciably different, one being a hardwood and one being a
softwood. Are fuel woods basically the same with respect to emissions and efficiency? This
question cannot be adequately answered from this study, but indications are that the type
of wood used is not critical provided the wood is recognised as a ‘usable’ fuelwood. This is
consistent with the findings described by Smith (1987:269).
4.3.5 Wood size
Figure 4.9 shows a typical example of the effect of using larger pieces of wood in the
stoves. Larger pieces of wood reduced CO, SO2 and TSP emission mass and emission
factors. These reductions were significant at the 95 % confidence level for the heating up
phase and at 85 % for the overall result. This finding has been reported in urban wood
combustion studies (Cooke et al 1982:151) – where it is suggested that smaller pieces have
a shorter distance for the pyrolysis products to diffuse, a large surface area to mass, and a
reduction in the time required to heat the entire piece of wood.
0.6
0.53
TSP emission mass (g)
0.49
Small pieces of wood
0.5
Large pieces of wood
0.4
0.3
0.3
0.24
0.23
0.2
0.15
0.1
0
Heating up
Simmering
Overall
Phase
Figure 4.9 TSP emission mass for large and small pieces of wood
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67
4.3.6 First order interactions
There is a strong interaction between the size of wood used and the stove type for power,
fire temperatures, and heating up phase CO and SO2 emissions (but not for efficiency). It
is probable that a particular type of stove has an optimum fuel size – this would relate to
the firebox size.
There is a very strong interaction between the use of a lid and the stove type for the
simmering phase and overall CO and SO2 emission mass and emission rate, but not for the
emission factor. The reason for this is not known.
Since both of these interactions involve stove type it is important to specify the size of the
wood to be used and whether to use pot lids, as far as possible, according to local practice.
Where possible an analysis of variance should be used to determine the best combination
of variables for a particular stove.
4.4
In this chapter we have considered 5 experimental variables. The findings have been
considered in detail in Sections 4.3.1 to 4.3.6. The findings are:
1. The two stoves had similar efficiencies but very different emission characteristics. CO
and SO2 were emitted at much higher quantities for the enclosed stove. TSP was
statistically equal at 95 % confidence. It is suspected that the reason for this is the
tendency of the improved open fire to smoulder almost continuously.
2. Stove performance was independent of the amount of water used in the pots.
3. Pot lids reduced overall efficiency by reducing water evaporation in the calculation of
simmering efficiency. The use of a pot lid reduced total emission masses, but increased
emission factors – emission factors are highly dependent on the quantity of fuel
consumed, and lids reduced the fuel consumed during simmering by a factor of three.
4. Eucalyptus grandis and Pinus patula were virtually identical with respect to power,
efficiency and emissions.
5. Larger pieces of wood reduced emissions.
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68
Stove performance was independent of the quantity of water used and the wood type.
Further work should be conducted in order to compare other hardwood-softwood
combinations as well as other biofuels such as dung and crop residues.
The other factors (stove type, the use of lids, and wood size) had a significant effect on
emissions at 95 % confidence for either part or all of the test. It is therefore important in
designing an emissions testing method that these parameters are specified precisely.
Comparisons between cooking devices cannot usefully be made where these parameters
are not kept constant.
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69
5
Real-time emission patterns
The overall aim of stove testing is to “identify the most effective and desirable stoves for a
specific social and economic context” (VITA 1985:vii). When testing a number of stoves for
emissions the tester would want to be able to rank the stoves in order of hazard. Of high
priority in the development of emission testing guidelines is to “specify which pollutants
need to be measured” (WHO 1992:36). Three pollutants have been measured in this study.
This chapter attempts to answer the question: “Is it sufficient to measure only one
pollutant rather than all three and still rank the stoves correctly in order of hazard?”
5.1
Background and aims
On the surface it would appear that the above question is easily answered. In Figure 3.4
the worst stove in terms of CO emission factor is the one pot metal stove, it is also the
worst stove in terms of SO2 emission factor (Figure 3.5) and TSP emission factor
(Figure 3.7). The other two stoves (the improved open fire and the two pot ceramic stove)
are ranked in the same order according to CO and SO2, but the TSP emission factors are
roughly equal (not statistically different at the 95 % confidence level).
5.1.1 The definition of the problem and the method of solution
In order to simplify the following discussion the hypothesis that it is sufficient to measure
only one of the pollutants is defined.
We can state that the hypothesis is true for the CO and SO2 emission factors of the three
stoves considered in Chapter 3. We could consider the hypothesis to be substantially true
for TSP (according to the needs of development organisations). It does therefore seem to
be sufficient to measure only one of the pollutants rather than all three and still rank the
stoves in order of hazard.
These observations have not however answered the question sufficiently for the finding to
be generalised. The reason for this is as follows. The task defined within the water boiling
test (bring to the boil and simmer for 30 minutes) simulates common cooking practice.
Within different contexts different tasks may reflect common practice more closely. For
example, in Mpumalanga, during field work, simmering times frequently lasting over an
hour were observed. The WBT is still a good general basis for testing and it is not being
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70
argued here that it should have been changed in this study (although the WBT should be
adapted for local conditions as argued in Appendix B). We recognise however that in
attempting to reach a general conclusion from a specific example we must be extremely
careful not to make erroneous conclusions. For the hypothesis to be generally true it must
be true for any task.
We can test the hypothesis for different tasks by subdividing the task which has been used
here. For the hypothesis to be generally true in stove comparisons it must be true for each
stove in any subdivision of the testing cycle. For example CO and SO2 should be well
correlated for each stove over the whole test cycle.
The hypothesis is therefore tested in the following way: We calculate the correlation of the
pollutants for every moment through the test. If the pollutants are well correlated for all
the stoves under consideration then the hypothesis is true for any task.
The most simple pollutant formation model – that emission factor is a constant during a
test – would imply that emissions are directly proportional to fuel burn rate. If this were
true then each pollutant would follow exactly the same trend as burn rate. The hypothesis
would then be generally true. If emission factor varies then the hypothesis can still be
generally true as long as the emission factor varies equally for each pollutant. Even if the
emission factors varied independently the pollutants could still be predominantly
influenced by burn rate, provided it varied very much more than the emission factors, and
the hypothesis could then still be true for the general case.
5.1.2 Previous studies
In rural cookstove emission tests it is common to measure carbon monoxide (CO) and total
suspended particulates (TSP). The reason for choosing these pollutants is medical: Carbon
monoxide is acknowledged as a good indicator of acute (short term) hazard and TSP of
chronic (long term) hazard. No studies aiming to determine which pollutants should be
measured from a pollutant emission point of view have been conducted on rural stoves.
In an attempt to produce testing methods which do not require costly equipment it has
been suggested that it is necessary to measure only one pollutant and from this
measurement infer the others (Young 1992). Results from a few rural studies suggest that
this inference is valid – Butcher et al (1984) found that stoves with a high CO emission
factor had a high TSP emission factor; Nangale (1992) found that high CO emissions
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71
implied high TSP emissions and high hydrocarbon acidity. Ahuja et al (1987), however, did
not find a consistent correlation between CO and TSP.
There is a world-wide interest in emission contributions to global warming and a number
of studies on biofuel emissions have been conducted. Lobert et al (1991) studied carbon
and nitrogen compounds emitted from biomass combustion on an inclined burning table.
These fires were intended to emulate large scale biomass fires, and to measure emission
ratios between compounds for use in emission predictions (for example, the CO/CO2 molar
ratio measured from a savannah fire flyover is used to predict CH4 emissions for that fire
from a knowledge of the laboratory CH4/CO2 ratios. CO/CO2 ratios are determined from
grab samples during flyovers (Helas et al 1995:230)). Ratios for two distinct combustion
stages were measured: flaming and smouldering combustion (these terms are defined in
Appendix D) – a sudden transition between flaming and smouldering combustion was
encouraged so that mixed combustion was not present (Lobert et al 1991:294). CO2 and
SO2 were found to relate closely to fire temperature and were emitted mostly during the
flaming stage – they are substances in a comparatively high oxidation state. CO and
unburned hydrocarbons were emitted predominantly during the smouldering stage – they
are products of incomplete combustion (Lobert et al 1991:294,295).
A number of studies into emissions from enclosed heating stoves (usually intended for use
in more affluent communities) in which more than one pollutant has been measured have
been conducted – some of the findings are listed below since the general chemical makeup
of the wood smoke can be expected to be similar to that from the cooking devices examined
in this work:
The ratios of hydrocarbons (CH4, C2’s such as C2H4 and hydrocarbons >C3’s) vary
depending on temperature although there is a general trend to lower concentrations of
unburned hydrocarbons with higher temperatures (Thornton & Malte 1982:861-864).
The formation of polyaromatic hydrocarbons (PAHs) peaks at about 790 °C (Cooke et al
1982:144,145). Temperatures above 900 °C act to reduce both PAHs and total organic
emissions, while low temperature combustion between 280 °C and 600 °C yield high total
organic emissions while producing only limited amounts of the PAHs (Cooke et al
1982:141).
Emissions were found to be inversely proportional to burn rate – a high burn rate leads to
low emission rate and emission factor (Peters et al 1982:208).
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72
In real time SO2, CO and NOx comparisons for a hand fired residential stove, SO2 and CO
were found to follow the same general trends (both increased soon after refuelling), but
NOx did not (Macumber & Jaasma 1982:328,329,331).
Although the overall correlation between pollutants for different stoves (total emission
factor or emission mass per task) is important, it is essential to look at the real time
variations of these pollutants and the real time correlations for a number of different
stoves (as has been argued in Section 5.1.1. The aim of this chapter is to determine for CO,
SO2 and TSP whether it is sufficient to measure only one pollutant rather than all three
and still rank the stoves in order of hazard for any task.
5.2
Experimental design
Data from the 18 tests described in Chapter 3 and the 32 tests described in Chapter 4 was
analysed in terms of the correlation between the three pollutants which were measured.
Two additional sets of experiments were also conducted to broaden the range of type of
stove considered. A two pot metal stove with a chimney, and a traditional open fire were
added to the stoves tested. They are described in Table 5.1 below.
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73
Table 5.1 Two additional cooking devices used in the real-time emission
comparisons
The two pot metal stove had galvanised steel inner and outer walls,
ceramic insulation, a removable heavy-gauge steel cooking plate, a
stainless steel firebox and a chimney. The stove was 350 mm wide at the
firebox end, 650 mm long and 200 mm deep. Five tests were conducted on
this stove. The starting mass of wood was far greater than that used for
the other stoves because of the much larger fire box (1 kg of wood was
used, and the stove was not refuelled before boiling point was reached).
The extraction rate of 0.056 m3/s was constant for all five tests † .
Emissions and efficiencies of a traditional open fire were also measured
using the same fuelling techniques as used for the improved open fire
(described in Chapter 3) and an extraction rate of 0.056 m3/s. Six tests
were carried out. The open fire was built on a sand base 50 mm thick,
with the pot supported on a metal tripod 100 mm above the base. The
side lengths of the triangular frame were 250 mm.
The correlations between the real time curves of burn rate, CO, SO2, and TSP were
calculated. This involved six combinations: CO to burn rate; SO2 to burn rate, TSP to burn
rate, CO to SO2, CO to TSP, and SO2 to TSP. The linear correlation coefficient, r is given
by:
n
∑ (x
i
− x )( yi − y)
i =1
n
∑
i =1
( xi − x) 2
n
∑(y
i
− y) 2
i =1
where
x is the mean of the x co - ordinates
y is the mean of the y co - ordinates
n is the number of data points
†
These tests were conducted with the assistance of Mr D. Evans, a final year BSc student.
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74
The correlation coefficient always lies between +1 and -1. If r = 0 there is no relationship
between x and y. A correlation of +1 is a perfect positive correlation; all points lie on a
straight line and x increases as y increases. A coefficient of -1 is a perfect negative
correlation; a straight line joins all the points, but the slope of the line is negative; x
increases as y decreases (or visa versa).
The average correlation is calculated by averaging the correlation coefficients for each
test. This value indicates whether, for a particular stove, the correlation coefficients are
consistent.
In addition, it is possible to calculate the overall correlation coefficient by combining all
data pairs for all the tests on a particular stove. This coefficient indicates whether the
curve fitted to the data for the individual tests has a consistent slope – it indicates whether
there is a simple conversion factor from the concentration reading of one pollutant to that
of the other.
The correlation results for the 18 extraction test, and the 32 five factor tests were
processed using the analysis of variance techniques already described in Chapter 3 and
Chapter 4. From this analysis the effects of these factors on the correlations can be
assessed.
5.3
The sum of fuel mass and water mass was measured continuously. A plot of fuel mass and
water evaporated for a test of the one pot metal stove is shown in Figure 5.1. The
evaporated water mass shown in the figure was measured by briefly lifting the pot from
the stove at regular intervals throughout the test (every 2 to 3 minutes). The curve
‘unsmoothed fuel mass’ has been corrected for the evaporated water mass but has not
been smoothed. The discontinuities were removed as shown in the curve ‘smoothed fuel
mass’ by combining all wood additions made at intervals through the test with the
preceding fuel masses.
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75
Fuel & evaporated water mass (kg)
0.8
Unsmoothed fuel mass
Smoothed fuel mass
Evaporated water mass
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
0
500
1000
1500
2000
2500
Time (seconds)
Figure 5.1 Fuel and evaporated water mass
It can be seen from Figure 5.2 that the water evaporated from the pot during the heating
up phase and during the simmering phase was approximately linear even though the
water temperature did not remain steady. It was therefore considered sufficient to
measure the water evaporated only at two points – when boiling point was reached and at
the end of the simmering phase in the tests described below. It was assumed that the
evaporation was linear for the calculations of burn rate given in the sections below. Burn
rate is the same as the rate of change of fuel mass but it is always positive.
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100
0.7
Mass of fuel in stove
Evaporated water mass
Water temperature
0.6
0.5
90
80
70
60
50
0.4
40
0.3
30
0.2
Water temperature (°C)
Fuel & evaporated water mass (kg)
0.8
20
0.1
10
0
0
0
500
1000
1500
2000
2500
Time (seconds)
Figure 5.2 Fuel mass, evaporated water mass and water temperature
It was found that the open fires and the enclosed stoves had fundamentally different
emission characteristics and correlations. The discussion below commences by examining
the open fires (Section 5.3.1); the enclosed stoves are examined in Section 5.3.2. In Section
5.3.3 and Section 5.3.4 we look briefly at the analysis of variance conducted on the
correlation data.
5.3.1 The open fires
The improved open fire and the traditional open fire showed remarkable similarity. In
particular TSP followed the trend of increasing emission throughout the test. The
correlations between TSP and burn rate, and between SO2 and TSP were reversals of the
trends for the stoves.
Table 5.2 shows the average correlations for the open fires (each calculated over 6 tests).
The number in brackets following the coefficient is the standard deviation of the
parameter for all the tests conducted on that stove.
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77
Table 5.2 Comparison of average correlation coefficients for the open fires
Correlation...
CO:burn rate
SO2:burn rate
TSP:burn rate
CO:SO2
CO:TSP
SO2:TSP
Open fire
0.2 (0.2)
0.3 (0.2)
-0.01 (0.1)
0.5 (0.3)
0.02 (0.4)
-0.6 (0.1)
Improved
0.1 (0.2)
0.6 (0.2)
-0.09 (0.1)
0.3 (0.4)
0.5 (0.4)
-0.4 (0.1)
open fire
a) Traditional open fire
The open fire had the worst correlations between the four parameters. Burn rate was not
correlated to the three pollutants and there was a poor correlation between the pollutants.
The overall correlation coefficients were similar to the average coefficients and indicated
generally poor correlations.
Table 5.3 Pollutant correlations for the open fire
Correlation...
CO:burn rate
SO2:burn rate
TSP:burn rate
CO:SO2
CO:TSP
SO2:TSP
Test shown in
0.1
0.1
0.1
0.0
0.4
-0.6
0.2
0.3
-0.01
0.5
0.02
-0.6
0.2
0.2
0.1
0.3
0.4
0.1
0.4
0.3
-0.01
0.7
-0.3
0.2
Figure 5.3 &
Figure 5.4
Average over 6
tests
Standard
deviation
Overall
(combined)
The fuel burn rate showed that the same effect of radial feeding of the fire was evident for
the improved open fire. The peaks visible in the burn rate graphs for the other three
stoves did not occur for the fires.
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78
9
250
8
7
6
150
5
4
100
3
Carbon monoxide
50
SO2 (ppm); TSP (g/m³)
CO concentration (ppm)
200
2
Sulphur dioxide
0
1
0
0
500
1000
1500
2000
2500
3000
3500
3000
3500
Time (seconds)
Figure 5.3 CO, SO2 and TSP for the open fire
8E-4
7E-4
Burn rate (kg/s)
6E-4
5E-4
4E-4
3E-4
2E-4
1E-4
0E+0
0
500
1000
1500
2000
2500
Time (seconds)
Figure 5.4 Burn rate for the open fire
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79
b) Improved open fire
The improved open fire had fairly poor correlations between the 4 parameters. The
correlation coefficients for the improved open fire are listed in Table 5.4. SO2 however
correlated well with burn rate and CO with TSP. Carbon monoxide and TSP increased
gradually during the whole test, whereas SO2 returned to approximately zero as burn rate
decreased to zero. It can be seen from Figure 5.5 that CO and SO2 were well correlated up
until the last 15 minutes when CO continued to climb whereas SO2 decreased. There was a
recognisable negative correlation between SO2 and TSP, that is, as SO2 increased, TSP
decreased. Standard deviations in the pollutant correlations were high which indicated
high variability in the correlations.
Table 5.4 Pollutant correlations for the improved open fire
Correlation...
CO:burn rate
SO2:burn rate
TSP:burn rate
CO:SO2
CO:TSP
SO2:TSP
Test shown in
0.2
0.7
-0.06
0.5
0.7
-0.1
0.1
0.6
-0.09
0.3
0.5
-0.4
0.2
0.2
0.1
0.4
0.4
0.1
-0.2
-0.4
-0.1
-0.1
-0.03
-0.1
Figure 5.5 &
Figure 5.6
Average over 6
tests
Standard
deviation
Overall
(combined)
Fuel burn rate decreased to zero when fresh wood was added. The open fires were fed
radially and therefore ‘new’ wood started to burn gradually throughout the test.
5
80
250
9
Carbon monoxide
Sulphur dioxide
8
7
6
150
5
4
100
3
200
2
50
1
0
0
0
500
1000
1500
2000
2500
3000
2500
3000
Time (seconds)
Figure 5.5 CO, SO2 and TSP for the improved open fire
6E-4
Burn rate (kg/s)
5E-4
4E-4
3E-4
2E-4
1E-4
0E+0
0
500
1000
1500
2000
Time (seconds)
Figure 5.6 Burn rate for the improved open fire
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81
5.3.2 The enclosed stoves
The one pot metal stove and the two pot ceramic stove were very similar in their
correlation patterns. All the enclosed stoves had an excellent correlation between CO and
SO2 over each test. This finding is unexpected since these gases are predominantly formed
during different combustion phases – CO and SO2 have been found to be poorly correlated
in fires emulating large scale biomass burning (an open physical geometry similar to an
open fire) (Lobert et al 1991:295). In contrast, experiments on an enclosed stove showed
good real time CO and SO2 correlations (Macumber & Jaasma 1982:328,329,331) as has
been found here.
Table 5.5 shows the correlations for the three stoves. The number in brackets following
the coefficient is the standard deviation of the parameter for all the tests conducted on
that stove.
Table 5.5 Comparison of average correlation coefficients for the three stoves
Correlation...
CO:burn rate
SO2:burn rate
TSP:burn rate
CO:SO2
CO:TSP
SO2:TSP
One pot metal
0.8 (0.1)
0.9 (0.1)
0.7 (0.3)
1.0 (0.01)
0.8 (0.2)
0.8 (0.2)
0.6 (0.1)
0.8 (0.1)
0.5 (0.1)
0.8 (0.1)
0.8 (0.2)
0.6 (0.2)
0.3 (0.2)
0.3 (0.2)
0.1 (0.3)
1.0 (0.01)
0.5 (0.2)
0.5 (0.2)
stove
Two pot
ceramic stove
Two pot metal
stove
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82
a) One pot metal stove
The one pot metal stove had very high correlations (individual and overall) between all 4
parameters for all the tests. The correlations between the pollutants and burn rate which
can be seen in Table 5.6 indicates that the emission factors were roughly constant. For
this stove measuring only one of the pollutants would be a sufficient indicator of the
others.
Table 5.6 Pollutant correlations for the one pot metal stove
Correlation...
CO:burn rate
SO2:burn rate
TSP:burn rate
CO:SO2
CO:TSP
SO2:TSP
Test shown in
0.9
0.9
0.8
1.0
0.9
0.9
0.8
0.9
0.7
1.0
0.8
0.8
0.1
0.1
0.3
0.01
0.2
0.2
0.8
0.7
0.7
1.0
0.8
0.7
Figure 5.7 &
Figure 5.8
Average over 6
tests
Standard
deviation
Overall
(combined)
Fuel burn rate (shown in Figure 5.8) had two peaks which corresponded to the stove
refuelling. These peaks were reflected in the pollutant emissions.
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600
35
Carbon monoxide
Sulphur dioxide
30
25
400
20
300
15
200
10
100
500
5
0
0
0
500
1000
1500
2000
2500
3000
Time (seconds)
Figure 5.7 CO, SO2 and TSP for the one pot metal stove
8E-4
7E-4
Burn rate (kg/s)
6E-4
5E-4
4E-4
3E-4
2E-4
1E-4
0E+0
0
500
1000
1500
2000
2500
3000
Time (seconds)
Figure 5.8 Burn rate for the one pot metal stove
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84
b) Two pot metal stove
The two pot metal stove had low correlations between burn rate and the three pollutants,
a very good correlation between CO and SO2, and a fair correlation between TSP and CO
or SO2. The low correlation with burn rate indicates that the emission factors are not
constants for the tests, although, since the pollutants vary together, the emission factors
vary together. The correlations are given in Table 5.7 below. The overall correlation
coefficients were strikingly different from the average coefficients in that, on an overall
basis, the pollutants were not correlated. This indicates that, while, for example CO and
SO2 follow the same patterns within a test, the relationship between them across different
tests changes. For this stove therefore it is not possible to infer one pollutant from another
even though they follow similar emission patterns.
Table 5.7 Pollutant correlations for the two pot metal stove
Correlation...
CO: burn rate
SO2:burn rate
TSP:burn rate
CO:SO2
CO:TSP
SO2:TSP
Test shown in
0.3
0.4
0.3
1.0
0.5
0.5
0.3
0.3
0.1
1.0
0.5
0.5
0.2
0.2
0.3
0.01
0.2
0.2
-0.2
-0.1
-0.1
-0.08
-0.2
-0.2
Figure 5.9 &
Figure 5.10
Average over 5
tests
Standard
deviation
Overall
(combined)
5
85
300
14
Carbon monoxide
Sulphur dioxide
12
250
10
200
8
150
6
100
4
50
2
0
0
500
1000
1500
2000
2500
3000
3500
350
0
4000
Time (seconds)
Figure 5.9 CO, SO2 and TSP for the two pot metal stove
2.5E-03
Burn rate (kg/s)
2.0E-03
1.5E-03
1.0E-03
5.0E-04
0.0E+00
0
500
1000
1500
2000
2500
3000
3500
4000
Time (seconds)
Figure 5.10 Burn rate for the two pot metal stove
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86
c) Two pot ceramic stove
The two pot ceramic stove had good average and overall correlations between the 4
parameters, but the correlations were not as high as for the one pot metal stove. The
correlation between TSP and burn rate was the weakest – TSP increased gradually during
the duration of the test as it did for the open fires. CO also gradually increased during the
test although the peaks are greater than for TSP. CO and SO2 were generally well
correlated except for the start and end of tests where SO2 decreased to zero and CO
remained high. These effects are shown graphically in Figure 5.11.
Table 5.8 Pollutant correlations for the two pot ceramic stove
Correlation...
CO:burn rate
SO2:burn rate
TSP:burn rate
CO:SO2
CO:TSP
SO2:TSP
Test shown in
0.7
0.9
0.5
0.9
0.8
0.7
0.6
0.8
0.5
0.8
0.8
0.6
0.1
0.1
0.1
0.1
0.2
0.2
0.8
0.6
0.5
0.9
0.6
0.7
Figure 5.11 &
Figure 5.12
Average over 6
tests
Standard
deviation
Overall
(combined)
Peaks corresponding to fuel additions were clearly visible for the two pot ceramic stove as
can be seen in Figure 5.12.
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87
Carbon monoxide
300
12
Sulphur dioxide
250
10
200
8
150
6
100
4
50
2
0
0
0
500
1000
1500
2000
2500
3000
Time (seconds)
Figure 5.11 CO, SO2 and TSP for the two pot ceramic stove
6E-4
Burn rate (kg/s)
5E-4
4E-4
3E-4
2E-4
1E-4
0E+0
0
500
1000
1500
2000
2500
3000
Time (seconds)
Figure 5.12 Burn rate for the two pot ceramic stove
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88
5.3.3 Extraction analysis of variance
The analysis of variance performed on the correlation data for the three sets of six tests
confirmed that the ‘goodness’ of correlation was strongly stove dependant (frequently the
confidence level was better than 99%). There was no effect of the forced extraction, nor
were there any interactions between stove type and extraction level.
5.3.4 Variable screening analysis of variance
The stove type strongly affected all the six combinations of correlation that were
considered for the five factor analysis of variance. The correlations of CO and SO2 to each
other and to burn rate were also strongly influenced by the fuel size. There was a
significant interaction between the size of the wood and the type of stove. The reason for
these correlations is unknown although it is suspected that the rate of diffusion of
pyrolysis products, and the differences in surface area to mass, account for the differences
in emission of the three pollutants. The ratios of combustion products depend strongly on
reaction temperature (Shafizadeh 1981:107; Speight 1993:57; Thornton & Malte 1982:861864). The enclosed stoves have higher average fire temperatures than the open fires
(537 °C compared to 390 °C). The combination of these two effects could be responsible for
these correlation trends.
The presence of the pot lid had an effect on the correlation of TSP to burn rate and TSP to
CO and SO2. There were occasionally significant interactions (better than 90 %
confidence) between lid and stove, and lid and size.
5.4
The correlations between CO, SO2, TSP and fuel burn rate were calculated for five
different types of cooking device.
Particular cooking devices were found to have specific correlation characteristics. The
cooking devices can be divided into two categories according to these correlations: the open
fires and the enclosed stoves.
The open fires had generally poor correlations between the four parameters. TSP
increased gradually throughout the test and had a negative correlation to SO2. TSP and
burn rate for the fires did not correlate.
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89
The stoves had particularly good correlations between CO and SO2 and good correlations
between all the combinations of pollutants and burn rate. The two pot metal stove is a
notable exception in that, although the pollutants follow similar trends within a test, the
relationship between the pollutants is not constant across tests.
The correlation between the three pollutants measured in this study is dependent on the
type of stove. It is therefore necessary to measure each pollutant separately.
5
90
6
The simulation of a dilution chamber
The measurement of stove emissions using a dilution chamber is known as the chamber
method. In this method it is necessary to assume that the emission rate is constant
throughout a test. The aim of this chapter is to compare the emission factors calculated by
assuming constant emission rate with the numerical solution using the emission rate
measured in this study and thereby to assess the validity of the chamber method.
6.1
Background and aims
The chamber method for measuring unvented cookstove emissions was first proposed by
Ahuja et al (1987). The method was developed in an attempt to reduce the cost and
complexity of measuring emissions, and avoid some of the errors assumed to have been
caused by suspending an extraction hood above a stove. There are two parts to the
chamber method. Firstly the stove is operated according to a pre-defined task in a dilution
chamber, and concentrations of the pollutants in this chamber are measured. The air in
the room is mixed by means of fans to avoid stratification of the gases or smoke. Before
the stove emission factor can be calculated the air exchange rate in the chamber must be
measured – this constitutes the second part of the method. The fire is removed from the
room and the gas or smoke concentrations continue to be measured. The air exchange rate
is calculated from the measurements of the pollutant concentration decay.
The mathematical basis for the method is shown below.
An ordinary differential equation can be derived from a mass balance for the volume. If
the emission factor (E, kg/kg) and the fuel burn rate (F, kg/s) are assumed to be constant,
this equation can be solved algebraically.
The differential equation is derived as follows. Consider a chamber of volume V (m3). We
perform a mass balance of the pollutant over the control volume. We assume that no
& in = 0 where
pollutant enters the room from the outside (that is, m in = 0 , and therefore m
& in is the instantaneous mass flow rate of pollutant into the room.) In Figure 6.1, at any
m
& a is the rate of pollutant mass accumulation in the chamber, m
& stove is the mass
time t, m
& out is the mass flow rate of pollutant
rate of pollutant emission from the stove, and m
leaving the chamber (all these units are in kg/s).
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91
Figure 6.1 ‘Chamber’ mass rate balance
Since mass is conserved, and assuming that none of the particular pollutant condenses, we
have:
Rate of mass accumulation = Mass flow rate of pollutant into the chamber
+ mass rate of pollutant generation in the chamber
− mass flow rate of pollutant out of the chamber
&a =m
& in + generated − m
& out = m
& generated − m
& out
m
& a = F ( t) E( t) − m a S
∴m
or, by dividing through by the volume, we get
F ( t) E( t)
C& ( t) =
− C( t) S
V
where, at time t
(6.1)
m a is the mass of pollutant in the volume V (kg)
& a is the rate of change of mass accumulated in the chamber (kg / s)
m
F is the fuel burn rate (kg / s)
E is the source strength (kg pollutant / kg fuel )
V is the chamber volume (m 3 )
S is the air exchange rate in the chamber (exchanges / s)
C is the concentration of the pollutant in the chamber (kg / m 3 )
C& is the rate of change of concentration of the pollutant (kg / m 3 s).
The solution to this first order ordinary differential equation, when F, E, and S are
constant, is:
C( t ) =
FE(1 − e − St )
VS
(6.2)
C( t)VS
F (1 − e − St )
(6.3)
or
E=
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92
To determine the air extraction rate, the stove is extinguished and removed from the room
after it has been operating for some while (at the end of the test period). The mass balance
& stove = 0 becomes:
when m
Figure 6.2 ‘Chamber’ mass rate balance with stove extinguished
Rate of mass accumulation
&a
m
&a
∴m
or C& ( t)
= − Rate change of mass leaving the chamber
& out
= −m
= −ma S
= − C( t) S
The variables of this first order ordinary differential equation are easily separable. For
constant S the solution becomes:
C(t) = K e − St
For two known concentrations, C1 and C2, (measured at times t1 and t2) we can calculate
the air exchange rate S:
S=
ln C1 (t1 ) − ln C2 (t2 )
t2 − t1
For typical constant E and F, a room volume of 16 m3 and an air extraction rate of 5
exchanges per hour, equation 6.2 predicts room concentrations as shown in Figure 6.3.
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93
1
CO room concentration (g/m³)
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
0
500
1000
1500
2000
Time (seconds)
Figure 6.3 Room CO concentration for constant E & F
Using the procedure described below it is possible to calculate the error introduced by
assuming E and F to be constant – the aim of this chapter is to examine the validity of
these assumptions.
6.2
Experimental design
Experiments on the one pot metal stove and the improved open fire were conducted under
the hood using the stove operating conditions of Ahuja et al (1987). “Three and a half
kilograms of water were boiled in a covered, flat bottomed, aluminium vessel of 5 litres
capacity with a thermometer (0.5 °C accuracy) inserted through a rubber stopper in the
lid. Just enough wood was used in each experiment to bring this water to the boil and to
keep it boiling for about 15 minutes” (Ahuja et al 1987:254). In an attempt to “minimise
variations in emission characteristics” a single charge of fuel was used (Ahuja et al
1987:254). The fire was tended only to ensure a steady flame.
In addition to these tests using a single charge of fuel, chamber pollutant concentrations
were simulated for the one pot metal stove and the improved open fire operated in a way
which related closer to rural practice. The method was the same as that described in
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94
Chapter 3 (where the stove was refuelled during the test and 2 litres of water was heated
and simmered for 30 minutes, no pot lids were used).
Ahuja et al (1987) measured carbon monoxide continuously and determined the constant
mean emission factor using a least squares optimisation procedure to fit the room
concentration curve. The ratio of this mean to the equilibrium room CO concentration
curve was applied to the mean particulate concentration since TSP was not measured
continuously. This, it should be noted, could lead to errors since CO and TSP correlate
differently for different cooking devices as was demonstrated in Chapter 5. (Additionally
the two pollutants interact differently with their surroundings (personal communication:
Professor Kirk Smith, Environmental & Health Sciences; Warren Hall; University of
California; Berkeley USA 94720-7360)). The least squares optimisation procedure entailed
calculating z(t)
1 e St for all t and doing a linear regression of C(t) and z(t) forcing the
intercept to zero (personal communication: Professor Chandra Venkataraman; Centre for
Environmental Science & Engineering; Indian Institute of Technology; Powai; Bombay
400 076; India). The slope gave the equilibrium concentration Ce from which E simulated can
be calculated ( C e
FE simulated VS ).
A somewhat simpler method than the least squares one for determining the mean
emission factor could however be used. Considering equation 6.3 we know C(t), t, V, S, and
F, and therefore E(t) can be calculated for each C(t). The mean emission factor is then
simply the mean of E(t).
For comparison in the following simulation we will use three estimation methods: the least
squares regression used by Ahuja et al (1987), referred to here as the ‘least squares
method’; the calculation of the mean of E(t) as described in the previous paragraph,
referred to as the ‘simple mean method’; and the pollutant room concentration C(t) at
1000, 1500 and 2000 seconds after the start of the fire substituted into equation 6.3,
referred to as the ‘substitution method’.
The chamber volume V used by Ahuja et al (1987) was 16 m3 and the average air exchange
rate S calculated over a number of tests was approximately 5 exchanges per hour (when
mixing fans were used), which is equivalent to 80 m3 per hour. These figures were used in
the chamber simulation described below.
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95
The simulation involves the following:
1. Using F(t) and E(t) measured in this study (which vary over time) we can find a
F ( t) E( t)
− C( t) S (equation 6.1) which we will call
numerical solution to C& ( t) =
V
Csimulated(t). We calculate this room pollutant concentration at regular intervals (every 10
seconds) throughout the experiment. The curve of simulated concentration against time
which can then be plotted is equivalent to that which would have been measured if the
stove had been operated in a chamber with perfect mixing and a constant air exchange
rate.
2. The room pollutant concentrations Csimulated(t) calculated in 1 above can be used to
determine the mean stove emission factor according to the least squares method, the
simple mean method, or the substitution method described above where F and E are
assumed to be constant. We will call this emission factor E simulated . It is an average
emission factor for the test.
3. The emission factor E simulated is compared to E measured the average emission factor
calculated by integrating the product of the pollutant concentrations ( C M ) and the flue
extraction rate ( v& flue ) measured with the hood over time t, and dividing by the total
T
mass of fuel burned, E measured =
∫C
& flue dt
Mv
( m f − m c ) (as described in more detail in
t=0
Section 3.3.2 and Appendix A.3.1(a)).
It may be pointed out that in this process the hood measurements are the basis for
E simulated and E measured and therefore errors in these measurements are carried through to
both results. This however is not problematic since the simulation only aims to allow the
assessment of deviations of the emission rate from constant and the impact of these on the
accuracy of the chamber method. It is however assumed that the emission rate variations
measured using the hood reflect the ‘real life’ emission rate variations.
F ( t) E( t)
− C( t) S , when E(t) and F(t) are not
The ordinary differential equation C& ( t) =
V
constant must be solved numerically. The fourth order Runge-Kutta method, a single-step
method for the solution of the initial value problem y ′ = f ( x, y), y( x 0 ) = y 0 at equidistant
points, was used. The algorithm is as follows (see Kreyszig 1988:1068-1072):
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96
for n = 0,1,L , N − 1
we define
k1 = hf ( x n , y n )
k2 = hf ( x n + 12 h, y n + 12 k1 )
k3 = hf ( x n + 12 h, y n + 12 k2 )
k4 = hf ( x n + h, y n + k3 ), and
x n +1 = x n + h
the solution is then
y n+1 = y n + 16 (k1 + 2 k2 + 2 k3 + k4 )
where h is the step size
In summary: we operate the stove under the hood, measure E(t) and F(t) throughout the
test, and calculate the room pollutant concentrations which we would have measured had
we operated the stove in a chamber of known volume and air exchange rate. We use this
simulated room pollutant concentration to calculate the stove emission factor E simulated
according to three methods. We then compare these simulated emission factors to the
emission factor E measured calculated from the hood test.
6.3
For the tests conducted using the stove operating conditions of Ahuja et al (1987) the one
pot metal stove required 0.6 kg of wood to complete the task whereas the improved open
fire required 0.5 kg. The performance characteristics for these tests are given in Table 6.1
and Table 6.2.
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97
Table 6.1 Performance characteristics of the one pot metal stove for the
chamber simulation
Heating up
Boiling
Overall
Power, kW
4.8
1.2
3.3
Efficiency, %
20
42
23
Average fire temperature, °C
520
450
490
Burn rate, g/minute
14.7
3.6
10.0
Duration, minutes
21:45
15:47
37:32
Table 6.2 Performance characteristics of the improved open fire for the
chamber simulation
Heating up
Boiling
Overall
Power, kW
3.6
3.4
3.6
Efficiency, %
21
18
20
Average fire temperature, °C
410
340
370
Burn rate, g/minute
11.1
10.3
10.8
Duration, minutes
24:54
15:07
40:01
Section 6.3.1 describes the dilution chamber simulation results for the one pot metal stove,
the improved open fire operated with a single charge of fuel and for the same two cooking
devices operated according to the VITA water boiling test (1985) as was described in
Chapter 3. From this discussion it will be possible to assess the impact of the cooking task
on the accuracy of the chamber results. In section 6.3.2 we will consider the impact of the
air exchange rate on the accuracy of the chamber results, and in section 6.3.3 the
discussions will focus on the accuracy of the chamber method with reference to the type of
cooking device being tested.
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98
6.3.1 The effect of cooking task on chamber method accuracy
Figure 6.4 shows the fuel mass and the burn rate for the one pot metal stove operated
with a single charge of fuel. Burn rate reached a peak after 500 seconds. The emission rate
(equivalent to EF, the emission factor multiplied by the fuel burn rate) is shown in Figure
6.5. It can be seen, as we would expect, that the emission rate was far from constant.
Averaged over the whole test the emission rate was 0.011 g/s (this is the mean emission
T
rate, EF =
∫
EFdt
T
). The emission factor E measured was 56 g/kg.
t=0
The simulated room CO concentration Csimulated(t) is shown in Figure 6.6. It is clear from
this figure that the CO concentration in the room did not tend to an equilibrium value.
The emission factors calculated using fixed times for C(t) in equation 6.3 (the substitution
method) can be expected to vary depending on the time t at which Csimulated(t) is calculated.
0.5
-600.0E-6
0.45
Fuel mass
Fuel mass (kg)
0.35
-500.0E-6
-400.0E-6
0.3
0.25
-300.0E-6
0.2
-200.0E-6
0.15
0.1
d(fuel)/dt (kg/s)
Burn rate
0.4
-100.0E-6
0.05
000.0E+0
0
0
500
1000
1500
2000
Time (seconds)
Figure 6.4 Fuel mass and burn rate of the one pot metal stove for the chamber
simulation, single charge
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99
0.05
0.045
CO emission rate (g/s)
0.04
0.035
0.03
0.025
0.02
0.015
0.01
0.005
0
0
500
1000
1500
2000
Time (seconds)
Figure 6.5 CO emission rate for the one pot metal stove, single charge,
EF =0.011 g/s
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
0
500
1000
1500
2000
Time (seconds)
Figure 6.6 CO, Csimulated(t) for a 16 m3 room, S=5, one pot metal stove, single
charge
The results for the simulation are shown in Figure 6.7 and Figure 6.8 below. A constant
E simulated calculated according to each of the 3 methods has been substituted into equation
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100
6.2 to generate the exponential curves of C(t) (least squares), C(t) (simple mean) and C(t)
(substitution t=1000s). Table 6.3 summarises the results for these methods and indicates
the percentage error of the simulated emission factors compared to the measured emission
factor.
0.9
C simulated (t)
0.8
0.7
C(t) (least squares)
0.6
0.7
C(t) (simple mean)
0.5
0.6
0.5
0.4
0.4
0.3
0.3
0.2
0.2
0.1
0.1
0
0
0
500
1000
1500
2000
Time (seconds)
Figure 6.7 CO, Csimulated(t) and C(t) using constant E simulated calculated using the
least squares regression of Ahuja et al (1987) and the simple mean of E(t)
proposed in this thesis, one pot metal stove, single charge
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101
1
0.9
0.8
C(t) (substitution t=1000s)
0.7
0.6
0.5
0.4
C simulated (t)
0.3
0.2
0.1
0
0
500
1000
1500
2000
Time (seconds)
Figure 6.8 CO, Csimulated(t) and C(t) using constant E simulated (for t=1000s), one pot
metal stove, single charge
Table 6.3 Measured and simulated emission factors for the one pot metal stove,
single charge
Emission factor (g/kg) CO
Error
E measured
56
—
E simulated (least squares)
91
39 % over
E simulated (simple mean)
80
31 % over
E simulated (t=1000s)
111
98 % over
52
7 % under
28
50 % under
Turning now to the improved open fire operated with a single charge of fuel, we note that
it had a more steady burn rate and emission rate than the one pot metal stove. One of the
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102
reasons for this is that the fire could be tended more easily than that of the enclosed one
pot metal stove. The burn rate during the test can be seen in Figure 6.9 and the CO
emission rate in Figure 6.10. The CO room concentration is shown in Figure 6.11, the
curve for constant E and F follows the true curve fractionally more closely than that for
the one pot metal stove and consequently the errors in estimation of all three methods are
not as great. Note that C(t) is given for constant E measured ; the two curves intersect at a
time t which would make E measured = E simulated . Error in the result for the improved open
fire using the least squares method (28 %) was less than that for the one pot metal stove
(39 %, see Table 6.4).
-500.0E-6
0.7
-450.0E-6
0.6
-400.0E-6
-350.0E-6
-300.0E-6
0.4
-250.0E-6
0.3
-200.0E-6
d(fuel)/dt (kg/s)
Fuel mass (kg)
0.5
-150.0E-6
0.2
Fuel mass
0.1
-100.0E-6
Burn rate
-50.0E-6
0
000.0E+0
0
500
1000
1500
2000
Time (seconds)
Figure 6.9 Fuel mass and burn rate of the improved open fire for the chamber
simulation, single charge
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103
0.03
0.025
0.02
0.015
0.01
0.005
0
0
500
1000
1500
2000
Time (seconds)
Figure 6.10 CO emission rate for the improved open fire, single charge,
EF =4.8 10-3 g/s
0.35
C simulated (t)
0.3
0.25
0.2
0.15
C(t) using E measured
0.1
0.05
0
0
500
1000
1500
2000
Time (seconds)
Figure 6.11 CO, Csimulated(t) and C(t) using constant E measured , improved open fire,
single charge
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104
Table 6.4 Measured and simulated emission factors for the improved open fire,
single charge
Error
E measured
22
—
30
28 % over
30
27 % over
32
45 % over
23
5 % over
15
32 % under
Emission rates for the one pot metal stove and the improved open fire when they are
refuelled are far less transient than for a single fuel charge. We would therefore expect the
chamber method to give more accurate results under these conditions because the
assumptions of constant E and F are less erroneous.
The CO emission rate for the improved open fire is given in Figure 6.12 below and the
simulated room concentration in Figure 6.13.
The simulated emission factors are given in Table 6.5.
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105
0.035
0.03
0.025
0.02
0.015
0.01
0.005
0
0
500
1000
1500
2000
Time (seconds)
Figure 6.12 CO emission rate for the one pot metal stove, refuelled,
EF =1.1 10-2 g/s
0.7
C simulated (t)
0.6
0.5
0.4
0.3
0.2
0.1
0
0
500
1000
1500
2000
Time (seconds)
Figure 6.13 CO, Csimulated(t) and C(t) using constant E measured , one pot metal stove,
refuelled
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106
Table 6.5 Measured and simulated emission factors for the one pot metal stove,
refuelled
Error
E measured
41
—
49
16 % over
41
1 % under
53
29 % over
52
27 % over
49
20 % over
The CO emission rate for the improved open fire is given in Figure 6.14 and the simulated
CO room concentration in Figure 6.15. Estimation errors are particularly low for this
cooking device when it is refuelled (see Table 6.6). This type of fire, as has already been
noted in Chapter 5, is fed radially, new wood being added to the sides of the fire and
gradually introduced into the combustion zone.
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107
0.009
0.008
0.007
0.006
0.005
0.004
0.003
0.002
0.001
0
0
500
1000
1500
2000
Time (seconds)
Figure 6.14 CO emission rate for the improved open fire, refuelled,
EF =4.9 10-3 g/s, refuelled
0.3
0.25
0.2
0.15
0.1
C simulated (t)
0.05
0
0
500
1000
1500
2000
Time (seconds)
Figure 6.15 CO, Csimulated(t) and C(t) using constant E measured , improved open fire,
refuelled
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108
Table 6.6 Measured and simulated emission factors for the improved open fire,
refuelled
Error
E measured
23
—
23
1 % over
20
12 % under
18
22 % under
20
13 % under
24
4 % over
The importance of a carefully defined cooking task in the accuracy of the chamber method
has been illustrated through the above discussions. Operating the stoves with a single
fuelling leads to greater errors for both cooking devices considered, than operating them
with refuelling. It may be concluded from this that, as we would expect with the chamber
method, the tester is not free to operate the stove in any way desired but is constrained by
the need to achieve as constant an emission rate as possible.
Fortunately this limitation is not as serious as it may seem since a refuelled cooking
device, which generally reflects common cooking better than a single charge of fuel, has
reduced error. It logically follows that frequent, small charges of fuel will lead to greater
accuracy when using the dilution chamber method than occasional refuelling with large
quantities of fuel. The ability to assess real-life emissions accurately however may be
limited if local practice deviates significantly from this.
6.3.2 The effect of air exchange rate on chamber method accuracy
The simulation was repeated for other air exchange rates and the resulting percentage
error calculated for the least squares and simple mean methods. The results are
summarised in Table 6.7 below. For each cooking device at each air exchange rate two
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109
numbers are given – the first being the percentage error for the emission factor calculated
according to the least squares method and the second being that calculated according to
the simple mean method.
Table 6.7 Percentage error at different air exchange rates
% error least squares (simple mean)
One pot metal, single charge
Improved open fire, single charge
One pot metal, refuelled
Improved open fire, refuelled
2.5 /hr
5.0 /hr
30 /hr
39 over
36 over
56 over
(36 over)
(31 over)
(10 over)
26 over
28 over
45 over
(32 over)
(27 over)
(8 over)
14 over
16 over
26 over
(1 under)
(1 over)
(4 over)
2 under
1 over
8 over
(17 under)
(12 over)
(2 under)
Error is generally reduced at higher exchange rates according to the simple mean of E(t)
estimation method, but increases according to the least squares method. These trends
should be considered carefully by the researcher intending to use the chamber method in
the field where widely differing air exchange rates between tests may be encountered. An
example is that of the WHO (Usinger 1994:30) where air exchange rates in excess of
2000 m3/h were measured during chamber tests with a mean for 11 tests of 1204 m3/h
(compared with the 80 m3/h used here). Care should be taken not to misinterpret
comparative tests (on the same slightly modified stove, perhaps) where exchange rates
differ. Although not given here, we would expect the error when the emission factor is
determined at discrete intervals using the substitution method to be larger and vary over a
wider range.
Here it is assumed that air exchange rate is constant during each test and that the
emissions are evenly mixed, conditions which may not be realistic, especially at high air
exchange rates. Where air exchange rates are high the simple mean calculation method
should clearly be used.
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Further research should be conducted on air exchange rate issues: in particular, before the
method can be used in a field setting studies should be conducted to determine the effect
of a non-constant air exchange rate, the degree of variation encountered in different field
settings, and conditions necessary for adequate mixing of the chamber pollutants.
6.3.3 The effect of cooking device type on chamber method accuracy
The simulation has been extended to the data collected for the studies in Chapter 3, 4
and 5. From the tests of Chapters 3 and 5 we are able to compare five cooking devices each
tested six times (five times for the two pot metal stove). From Chapter 4 we have 16 tests
under varying conditions for two cooking devices. This data is included here for
comparison.
Simulation results are given in Table 6.8. Two rows for each cooking device are given; the
first lists the results for the least squares method and the second for the simple mean
method. The second column of this table shows the mean percentage error of the
simulated emission factors for the 5 stoves. Errors are usually overestimations of the true
result. The open fires have lower errors than the enclosed stoves (as we have seen in
earlier sections) because of the more steady emission rates of these devices. This is
particularly evident in the comparison of the improved open fire and the one pot metal
stove in the last two rows of the table, a result based on the mean of 16 repeated tests.
Table 6.8 Percentage error for different cooking devices
Cooking device type
(no. of tests)
Mean
error (%)
Standard
Deviation
Range (%)
Statistical
differing means at
95 % confidence
between Emeasured
Ranking
Emeasured
Ranking
Esimulated
and Esimulated
Traditional open fire (6)
Improved open fire (6)
1 pot metal stove (6)
2 pot ceramic stove (6)
Improved open fire (16)
6
6 over
2 over
1 over
10 under
13 over
3 over
20 over
11 over
11 over
3 over
7 over
6 over
27 over
16 over
4
6
2
12
7
5
6
6
5
5
6
8
8
7
-11 to -1
-11 to 6
-4 to 2
-9 to 25
-18 to 1
-6 to 7
-28 to -14
6 to 21
-22 to -8
-6 to 7
-20 to 1
-21 to 10
-44 to -18
-29 to -7
yes
no
no
no
yes
no
yes
yes
yes
no
yes
yes
yes
yes
1
1
3
1
2
2
1
1
1
4
3
3
3
3
2
111
The statistical significance of the variations is given in the 5th column. Here it can be seen
that the difference between the measured emission factors and the simulated ones are
significant, according to the least squares method, for all the cooking devices except the
improved open fire. According to the simple mean method simulated emission factors very
less from the measured emission factors that with the least squares method; only the two
pot metal stove, and the results for the improved open fire and the one pot metal stove at
the bottom of the table, have statistical differing means at 95 % confidence. Within this
column the dashed lines between entries for a cooking device indicate a statistically
significant difference at 95 % confidence between the emission factor results of each
calculation method.
In the final column of Table 6.8 the stoves are ranked according to their simulated
emission factors. The ranking is given on a scale of digits where 1 rates best (lowest
emission factor); where two (or more) devices have the same rating their differences in
emission factor are not significant at the 95 % confidence level (the ranking given in Table
1 of Appendix E is identical to the one in the second last column here, but in Appendix E it
is expressed at the 90 % confidence level). Discrepancies between measured and simulated
emission factors are clearly evident, the two pot metal stove rates (tie) first according to
E measured but third according to E simulated for both calculation methods – this is a result of
significant overestimations by the chamber method for this cooking device, in turn a result
of greatly varying emission rates. The best cooking device however, the improved open
fire, is the best according to all three emission factors – overestimations of emission factor
calculated with the least squares method was small (because of the relatively constant
emission rate pattern of this stove), and emission factor calculated according to the simple
mean method underestimated the measure emission factors by 10 %.
The ranking according to the least squares calculations is different from that for the
simple mean calculations, the later being closer to the measured emission factor ranking
than the former.
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6.4
In order to calculate the pollutant emission factor using the chamber method it is
necessary to assume that the burn rate and the emission factor do not change during the
test. The validity of this assumption has been tested by simulating the pollutant room
concentrations which would have been recorded in the chamber method using the real
time data collected using the hood method.
Simulated and measured emission factors for two cooking devices, the improved open fire
and the one pot metal stove, operated in the same way as is recommended by Ahuja et al
(1987) for the chamber method, were compared. The same cooking devices operated
according to the VITA (1985) water boiling test were also compared thus allowing an
assessment of the impact of the simulated cooking task on the accuracy of chamber tests.
The air exchange rate may also have an effect on the accuracy of these tests and this was
assessed by recalculating the simulated emission factors at 3 different air exchange rates.
Finally, the usefulness of the chamber method as a means of comparing the emissions of
various cooking devices has been assessed by comparing simulated emission factors for the
5 cooking devices considered earlier in this work.
The results may be summarised as follows:
•
There is a relationship between the cooking task used in chamber tests and the
accuracy of the results. The more constant the pollutant emission rate, the more
accurate the method. Refuelled cooking devices lead to better accuracy for that reason.
•
The air exchange rate has an influence on the accuracy of results. Of the two methods
compared for calculating emission factors from data collected in chamber tests the
accuracy of the least squares method deteriorates with increasing air exchange rate
and that of the simple mean method improves.
•
The open fires are favoured by the chamber method since emission rates are more
close to constant than for the other cooking devices considered. Differences in emission
factors between those of the simulated chamber method and the measured emission
factors are statistically significant at 95 % confidence for 6 of the 7 sets of tests for the
least squares calculation method, and 3 of the 7 for the simple mean calculation
method.
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In conclusion care should be taken in the use of the chamber method: Cooking devices
should be refuelled regularly and not operated with a single charge of fuel as was
suggested in earlier studies using the chamber method. Attention should be given to the
rate of air exchange in the test chamber: particularly at high air exchange rates the simple
mean method should be used to calculate emission factors rather than the least squares
method. Comparisons between tests conducted at differing air exchange rates is
problematic. Because the accuracy of chamber method tests depends on a constant
emission rate, and since the method tends to overestimate emission factors when emission
rates vary widely, results are biased. The simple mean method of calculating emission
factors gave better results than the least squares method and should therefore be used.
The chamber method may certainly be useful in some situations such as for determining
emission factors in climate change studies or perhaps in medical studies. Further study
and discussion appear to be necessary before the method can be recommended to
development organisations for use in comparing emissions from cooking devices.
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114
7
This thesis has attempted to contribute to the knowledge of emission testing of woodburning cooking devices used by the rural poor so that testing guidelines can be developed
from a strong technical foundation.
7.1
The need for this work
About 2500 million people in developing countries are exposed daily to biofuel combustion
emissions (WHO 1992:1,10). Respiratory disease, which is the main cause of death in
developing communities, has been linked to these combustion products (Krugmann
1989:129). For many people alternative fuels are not available (WHO 1992:1) and
consequently the development of improved biofuel cookstoves which reduce emissions is
essential (WHO 1992:28). Only by measuring the emissions of new stoves and comparing
them with those of earlier cooking devices can improvements be assessed and emission
levels reduced. Guidelines for measuring the emissions from these stoves must therefore
be developed.
7.2
The aim of this work
The aim of this thesis has been to contribute to the knowledge of emission testing so that
guidelines can be developed from a strong technical foundation. There were four specific
aims:
1. To measure the effect of an extraction hood on emission measurements.
2. To measure the effect of five experimental variables (stove type, wood type, wood size,
the use of lids, and the quantity of water heated) on stove emissions.
3. To consider the relationship between carbon monoxide (CO), sulphur dioxide (SO2) and
total suspended particulates (TSP) with a view to answering the question: “Is it
sufficient to measure only one of these pollutants?”.
4. To test the validity of assuming constant burn rate and emission rate in chamber tests.
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7.3
The approach
Each stove to be tested was placed under an extraction hood with controlled extraction
characteristics. Flow rate in the duct above the extraction hood was measured with a
calibrated orifice flow meter and controlled with a fan and damper. The velocities at the
stove were less than typical air currents in a closed room (0.10 to 0.12 m/s). An optical
smoke density meter calibrated in terms of mass density (measuring TSP) and an
electrochemical gas analyser measuring CO and SO2 were used to measure emission
concentration in the duct throughout the test.
The test entailed operating the stove as described in the VITA efficiency testing standards
(1985). Water in a pot was heated on the stove as rapidly as possible and, once boiling
point was reached, was simmered for 30 minutes.
Efficiency and other performance characteristics of the stove were calculated from fuel
mass and evaporated water mass, measured by placing the whole stove on a digital
weighing platform under the hood. The water temperature, the temperature of three
points in the fire, and the temperature of the flue gas were measured using
thermocouples.
The data was collected every 10 seconds throughout the test.
7.4
The effect of the extraction hood on emission measurements
A 3 by 3 analysis of variance was used to detect the effect of extraction on the emission
measurements. Three extraction levels were used (0.049, 0.056 and 0.065 m3/s) on three
cooking devices (an open fire built on a grate, a one pot metal stove and a two pot ceramic
stove).
It was found that fire power, fire temperature and efficiency were not affected by the rate
of extraction used.
There was a measurable influence of the test rig on the CO emissions although it was
small and sometimes not detectable. No effect of extraction could be detected at 95 %
confidence for SO2 and TSP.
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The potential therefore exists for the forced extraction to influence the stove emissions.
Care must be taken to extract the combustion gases at the lowest rate sufficient to capture
all emissions.
There was no detectable interaction between stove type and extraction level (at the 95 %
confidence limit). This indicated that the influence of the extraction was independent of
the type of stove, that is, if measurements are influenced by the extraction they are
influenced to an equal extent for any stove. An extraction hood can therefore be used with
confidence to compare emissions from different stoves provided the extraction level is not
changed between tests.
7.5
The study of the effect of five experimental variables
Five experimental variables were compared using a 5 by 2 analysis of variance. The effect
on emissions of two stoves (an open fire built on a grate, and a one pot metal stove), the
amount of water used in the pots (1 or 2 litres), the use of pot lids, the type of wood
(Eucalyptus or Pine), and the size of wood (15 to 30, and 30 to 60 mm effective diameter)
was studied. The principal findings were:
1. The two stoves had similar efficiencies but very different emission characteristics. CO
and SO2 were emitted at much higher quantities for the enclosed stove. TSP was
statistically equal at 95 % confidence.
2. Stove performance was independent of the amount of water used in the pots.
3. Pot lids reduced overall efficiency by reducing water evaporation in the calculation of
simmering efficiency. The use of a pot lid reduced total emission masses, but increased
emission factors.
4. Eucalyptus and Pine were virtually identical with respect to power, efficiency and
emissions.
5. Larger pieces of wood reduced emissions.
Stove performance was independent of the quantity of water used and the wood type. The
other factors, stove type, the use of lids, and wood size had a significant effect on
emissions at 95 % confidence for either part or all of the test. It is therefore important in
designing an emissions testing method that these parameters are specified precisely.
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Comparisons between cooking devices cannot usefully be made where these parameters
are not kept consistent unless they are included in the statistical design.
7.6
The relationship between CO, SO2 and TSP
The correlations between CO, SO2, TSP and fuel burn rate were calculated for five
different types of stove.
Particular stoves were found to have specific correlation characteristics. The cooking
devices can be divided into two categories according to these correlations: the open fires
and the enclosed stoves.
The open fires had generally poor correlations between the four parameters. The stoves
had particularly good correlations between CO and SO2 and good correlations between all
the combinations of pollutants and burn rate.
It was found that the correlation between the three pollutants measured in this study was
dependent on the type of stove. It is therefore necessary to measure each pollutant
separately.
7.7
The validity of assuming constant emission rate in chamber
tests
In order to calculate the pollutant emission factor using the chamber method it is
necessary to assume that the burn rate and the emission factor do not change during a
test. The validity of this assumption has been tested by simulating the pollutant room
concentrations which would have been recorded in the chamber method using the real
time data collected using the hood method.
The cooking task in chamber tests was found to have an effect on the accuracy of results.
In particular, it was found that cooking devices should be refuelled regularly and not
operated with a single charge of fuel.
Air exchange rate, it was found, has an important influence on accuracy and this
particularly depended on the calculation method used to determine emission factors from
the raw data of chamber tests. Dividing the concentration data C(t) by F (1 e St ) and
multiplying by VS and then simply taking the mean gave better results than the least
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118
squares method used by Ahuja et al (1987). The least squares method was particularly
inaccurate at higher air extraction rates.
The chamber method appears to be biased towards cooking devices with consistent
emission rates. This bias is statistically significant at the 95 % confidence level.
Comparisons between cooking devices can therefore not be made confidently.
In view of these problems associated with assuming constant burn rate and emission
factor for the cooking devices considered here the chamber method should be used with
care when measuring stove emission factors. The correct application of the method
however appears to lie outside the reach of development organisations attempting to
compare cooking devices. Further study and discussion is required before the method can
be recommended. Further work is also required before the method’s applicability in the
field can be assessed.
7.8
The significance of this work
“There are currently no commonly accepted guidelines for testing emissions from simple
biomass cookstoves, the most common combustion device in the world. It is therefore
necessary to establish these procedures and specify which pollutants need to be measured.
These guidelines should lead to the rating of the stove’s level of cleanliness under
laboratory and field conditions.” (WHO 1992:36)
In direct response to the above statement this thesis has attempted to contribute to the
framework for the establishment of emission testing guidelines. As a result of this work
anyone attempting to define acceptable guidelines should:
1. Realise that an extraction hood can be used in such a way that emission comparisons
can be made and should therefore not dismiss the use of a hood in emission testing.
2. Ensure that development organisations realise the part played by each experimental
variable and the importance of comparing emissions (and efficiencies) under the same
conditions. Valid comparisons can only be made where important variables such as the
use of pot lids and the size of the fuel are held constant or are varied intentionally in an
analysis of variance experiment.
3. Realise that as many pollutants should be measured as can be afforded.
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4. Recognise the problems associated with assuming constant burn rate and emission rate
in ‘chamber method’ tests and not recommend that development organisations use this
method for comparing cooking devices until further work has been done.
An example of the use of the hood in comparing five different stove models has been
included in Appendix E; this paper has been accepted for publication in Biomass and
Bioenergy, Elsevier Applied Science Publishers, Great Britain.
7.9
Areas for further work
The following areas require further study:
• The design of a portable extraction hood.
• The examination of other types of wood to determine whether, for fuel woods, emissions
are independent of wood type.
• An examination of the emission characteristics of other biofuels.
• A re-examination of the VITA international standards (1985) for measuring efficiency
in the light of the findings on emissions.
• An in-depth look at the emission characteristics of the five stoves discussed in
Chapter 5 with a view to discovering the cause of the different emission patterns. This
may lead to a better understanding of how to design low emission stoves.
• The air exchange rate is assumed to be constant in the dilution chamber method for
measuring emission factors. This assumption should be tested from a practical
perspective, particularly in a field setting under various frequently encountered
conditions.
• Standard methods for measuring emissions from biofuel cooking devices urgently need
to be developed taking into consideration the findings of this study and world-wide
experience.
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Appendix A Experimental results
The enclosed computer diskette contains the full experimental results for all tests carried
out in this work. This Appendix is a description of the data stored on the diskette,
instruction for installing and removing the analysis program from the hard disk drive, and
the methods used by the program to analyse the data.
A.1 Included on the diskette
The diskette contains:
• An installation program INSTALL.BAT which creates the necessary directories on
your fixed diskette and decompresses and copies the data and program files.
• A compressed data file TESTS.EXE. This file automatically decompresses when it is
run. It contains the experimental data files. These files are named according to the date
of the test as follows: File name: Tmmddyy.Vxx where mm is the month, dd is the day,
yy is the year, and xx is the experiment number performed on that day. The data files
are in TAB delimited ASCII format and can be loaded into any word processor of
spreadsheet. It is, however, easiest to analyse and view the data using the enclosed
analysis program.
• A compressed program file PROGRAMS.EXE. This file contains the data analysis
program ANALYSIS.EXE and a support program BRUN45.EXE which provides
modules for the main program. The program can be run (once decompressed) by typing
ANALYSIS (and pressing enter) at the DOS prompt.
A.2 Installing and removing the program
The analysis program will only work if the files are decompressed to a fixed diskette. They
occupy about 4 MB.
The installation program creates a directory on your fixed diskette called \stovephd and
decompresses and copies the program files analysis.exe and brun45.exe to this
directory. It then creates a sub-directory \stovephd\tests and decompresses and copies
the test data files to this directory.
121
The files and program may be removed by deleting the contents of the directories created
by the installation program and then removing the directories. The batch file
uninstal.bat, which can be executed by typing uninstal from within the \stovephd
directory, deletes and removes these automatically.
To execute the installation program insert the enclosed diskette into drive a (or drive b)
and from the C:\ prompt type
a:install
(or b:install if drive b is used) and press enter.
You may exit the installation program once it has started by pressing Ctrl+C. Installation
takes approximately 5 minutes.
The analysis program can be run by typing analysis in the c:\stovephd\ directory.
Operating instructions are given in the program.
A.3 What the analysis program does
• Allows the user to select a data file for analysis according to a description of the test.
• Loads the file and allows viewing of the data.
• Analyses the data according to the methods described below.
The raw data was recorded every 10 seconds in a table of experimental variables. This is
the file Tmmddyy.Vxx stored in the \stovephd\tests directory. The following variables
were recorded:
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Table A1 Summary of experimental variables recorded every 10 seconds
Time elapsed since the start of the experiment (seconds)
Mass of water and wood (kg)
Temperature of room (°C)
Temperature of flue gas (°C)
O2 (%), CO, SO2, NOx, NO2, and H2S concentration (ppm)
Temperature of pot 1 (main pot) and pot 2 (secondary pot) (°C)
Temperature of fire probe 1, 2 and 3 (°C)
Temperature of weighing platform (°C)
Output of the light obscuration smoke meters 1 and 2 (%)
Orifice pressure drop (Pa)
Comment including mass of wood added, and user comments
The analysis program smoothes the experimental data using Spencer’s 15-point
summation formula (Guest 1961:354).
Concentrations of NOx, NO2, and H2S were below the detection limit of the equipment and,
although recorded, are not displayed or analysed in the program.
A.3.1 Emissions
The analysis programme calculates emission parameters in seven different ways and
outputs them to the file stovephd\COemis.txt, stovephd\SO2emis.txt and
stovephd\TSPemis.txt for later use. During a session the emissions of all the files which
are viewed are stored one after the next in the above files. These files are overwritten each
time the program is restarted (the file names could be changed before restarting to
preserve the data). Some of the calculation methods have been used in other studies whilst
others have not been used for emission comparisons before.
The parameters can be calculated for each pollutant measured – in this case CO, SO2 and
TSP.
a) Pollutant emission factor (or source strength)
The pollutant emission factor, or the pollutant source strength, is the most commonly
used measure of emission level and has been used in both direct and indirect measurement
studies (see, Smith et al 1992; Ahuja et al 1987; and Young 1992:12 for indirect calculation
123
of source strength; and Nangale 1992; and Butcher et al 1984 for direct measurement
calculations).
Basically, determining the pollutant emission factor involves the calculation of the mass of
pollutant emitted from the source per kilogram of fuel burnt (gpollutant/kgfuel).
The test is conducted in such a way that no wood remains at the end of each phase, or that
wood and char are separated and weighed separately.
The source strength is calculated as shown below:
⎡T
⎤
⎢ C M v& flue dt ⎥
⎢⎣ t = 0
⎥⎦
E=
m f − mc
∫
where
E is the pollutant source strength (kg / kg)
C M is the pollutant concentration (kg / m 3 )
v& flue is the flue extraction rate (m 3 / s)
m f − m c is the fuel consumed (kg)
⎞
⎛T
⎛ T
⎞
Strictly speaking, the definite integral is a sum: ⎜⎜ C M v& flue dt⎟⎟ is ⎜ C M v& flue Δt⎟ since the
⎝ t=0
⎠
⎠
⎝ t =0
∫
∑
pollutant mass concentration is not continuous, but a series of discrete measurements
(every 10 seconds). The sum approximates the integral as 't tends to zero. The integral
has been used here to distinguish this sum from the simple average given in sub-section g
where the concentration every minute is used.
Numeric integration involved Romberg Integration, using the Composite Trapezoidal Rule
and Richardson h2 and h4 extrapolation (Q= h1/h2 was taken to be 0.5).
b) Total emission mass
The total emission mass per WBT standard task involves the calculation of the mass of
pollutant emitted during the heating up phase and during the simmering phase. Total
emission is used in the comparison of fuels for domestic cooking by the British Standards
Institute (BS 3841:1972). The total emission mass is directly related to the two common
124
cooking tasks simulated in the WBT, and possibly gives a better indication of exposure
than the emission factor. The emission mass is calculated as shown below.
T
M Etotal =
∫C
M v flue dt
&
t =0
where
M Etotal is the total mass of pollutant emitted (kg)
The flue extraction rate is essentially constant throughout a test and therefore the total
pollutant emitted is directly proportional to the area under the concentration – time curve.
c) Maximum concentration
The maximum concentration of the pollutant during the heating up phase and during the
simmering phase is very easily measured, and needs no calculations – complex or simple.
South African Standards (SABS 1403:1986) specifies the measurement of average and
peak levels of light obscuration in the chimney of the stove.
d) Emission rate
The emission rate, as used in British Standard PD 6434 in the measurement of smoke
reducing characteristics of domestic appliances burning solid fuel, is calculated as the total
emission mass (as calculated in sub-section b) divided by the measurement duration.
&
M
Etotal
⎡T
⎤
⎢⎣ t = 0
⎥⎦
=
T
where
&
M
Etotal is the average pollutant emission rate (kg / s)
∫
e) Measurements at fixed times
When gas samples are collected and analysed later in a laboratory decisions must be made
as to when in the burn cycle the samples should be taken. In the case of the study by
Smith et al (1993 and 1992) in Manila, three samples, which each took about two minutes
to collect, were collected for each stove “just after lighting, after ten minutes, and at the
end (at approximately thirty minutes when only char was left)”.
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In this study, ‘instantaneous’ measurements (rather than average or total emission over a
two minute ‘collection’ time) were considered. Readings immediately after lighting are
strongly dependent on many variables such as lighting method and instrumentation
reaction rate, and therefore were not considered. Four measurements were used to cover
the wood and char-burning phases:
Table A2 Time intervals for fixed-time emission concentration measurements
Time
Phase
5 minutes after ignition
Heating up
10 minutes after ignition
Heating up
5 minutes after boiling point is first reached
Simmering
10 minutes after boiling point is first
Simmering
reached
f) Emission mass per defined task
In an attempt to “compare stoves using a composite index that incorporates both
efficiency and emissions” Ahuja et al (1987:260) defined a standard task as one that raises
the temperature of 3.5 kg of water (the amount they used in their pot) by 60°C. This
means the transfer of 879 kJ of energy to the contents of the pot.
The use of a defined standard task is similar to the calculation of a total emission mass as
described in sub-section b. The definition of the task as an energy transfer, however,
would lead to very different results when different quantities of water are used in different
experiments.
Tests in this study use a maximum of 2 litres of water, and therefore a transfer of 879 kJ
would mean raising the water temperature by 105°C (and 1 litre by 210°C)! The transfer of
251 kJ, however, would be possible for both 1 and 2 litres. For a two pot stove (which
would require 4 litres of water) the total temperature change (for temperature changes in
both pots added) should be taken together as in the example below:
Pot 1: 2 litres – 15°C change; and Pot 2: 2 litres – 5°C change; this would mean that 2
litres of water have been heated by 20°C.
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Table A3 Quantity of water and temperature change to transfer 251 kJ of
energy
Quantity of water
Temperature change for 251 kJ energy transfer
1 litre
60°C
2 litres
30°C
Pollutant mass for this task defined above can obviously only be calculated for the heating
up phase, but similar tasks, possibly based on a quantity of water which evaporated during
the simmering phase, could easily be defined (but would not be easy to calculate
accurately).
M Etask
⎡T
⎤
⎢⎣ t = 0
⎥⎦
=
. t task
T
where
M Etask is the total pollutant mass emitted during the task (kg / task)
∫
t task is the time taken to achieve the desired task
or the time to heat the water in the pot
by 60 o C for 1 litre, and
by 30 o C for 2 litres.
g) Simple average
When computers are not used, and measurements are made by hand, emission
concentration cannot be recorded as frequently as every 10 seconds. The average
concentration during a particular phase could easily be calculated by adding together all
the evenly spaced readings and dividing by the total number of readings.
This case, where electronic monitoring is unavailable, can easily be simulated using the
following equation. The time interval was taken to be 1 minute, that is, every sixth
reading was used, the others ignored.
127
C =
⎡T
⎤
⎢ C M Δt ⎥
⎣ t =0
⎦
∑
T
Δt
where
C is the average pollutant emission rate (kg / s)
Δt is the time interval (s)
T
Δt is the number of time divisions
h) Comparison of emission parameters
Figure A1 shows the relationship between the different emission testing parameters which
have been described above for the heating and simmering phases.
Heating up phase
Simmering phase
300
Simmering phase
Peak concentration
250
Heating up phase
Concentration (ppm)
200
150
Average
heating up
100
Proportional to emission mass & emission rate
for simmering phase
50
0
0
500
1000
1500
2000
2500
3000
Time (seconds)
Concentration
5 and 10 minutes after ignition and boiling
Figure A1 Emission measurement parameters compared graphically
A.3.2 Efficiency
The calculation of stove efficiency has been the subject of considerable debate. Two
methods (the calculation of Specific Fuel Consumed (SFC) and the calculation of
Percentage Heat Utilised (PHU)) have been widely recommended, with most researchers
calculating both.
128
The definition of efficiency, although important, is not the focus of this study.
Nevertheless various methods of calculating stove efficiency have been compared; these
are discussed below.
a) Fire Power
VITA (1985), Stewart (1987) and Baldwin (1987) all emphasise the importance of
recording either the burn rate or the fire power for each SFC or PHU value. Fire power is
calculated as follows:
P=
T
where
P is the average fire power (kW)
b) Specific Fuel Consumed (SFC)
The Specific Fuel Consumed (SFC) for each phase as well as an overall combined figure is
frequently calculated according to the following formula (VITA 1985):
SFC =
fuel used
water evaporated
mf −
=
hco
h fo
$
m
mc
where
$ is the mass of water evaporated from the main pot (kg)
m
At times SFC is calculated using the initial mass of water (Stewart 1987:19,20) or the final
mass of water (Baldwin 1987:84) in the denominator of the above equation instead of the
mass of water evaporated.
Stoves designs fall into two broad categories – single pot stoves (ones where only 1 pot can
be heated at a time); and multipot stoves (more than one pot can be heated at a time). The
mass of water used in calculating the SFC is measured for the main pot only in a multipot
stove although water is placed in each pot.
129
c) Percentage Heat Utilised (PHU)
Baldwin (1987:84) recommends the calculation of Percentage Heat Utilised (PHU) rather
than SFC. In effect PHU is a simplified calculation of efficiency – the ratio of the output
energy to the input energy for the defined task.:
PHU =
$
c p mΔT + h fg m
.100
where
m is the mass of water in the main pot at the start of the experiment (kg)
ΔT is the rise in water temperature (K)
During the simmering phase the water temperature rise 'T is usually taken to be 5°C.
d) Improved efficiency equation
In order to make comparisons between the various calculation methods, a technically more
complete equation for the stove efficiency has been developed in the present study.
The efficiency of a cooking process is difficult to define in technical terms. Even using
simplified tasks, such as the heating of a quantity of water to boiling point as rapidly as
possible, or the simmering of a quantity of water for a period, efficiency is difficult to
define. Here we measure the ratio of the energy into the pot to the energy liberated by the
fire – similar to the PHU. This ratio is not entirely related to the task. For example, the
‘loss’ of energy by evaporation is used as a partial measure of the energy transferred to the
pot, not as ‘lost heat’. The purpose of simmering food is usually not to evaporate water,
but to maintain the food temperature until it is cooked.
There are two notable omissions in the PHU equation given by Stewart (1987):
•
the mass of water evaporated and the mass of water heated is measured for the main
pot only (the second and subsequent pot are ignored); and
•
water temperature fluctuations within each phase are ignored, that is, during the
simmering phase the water temperature tends to fluctuate as in Figure A2.
130
100
B1
80
Temperature °C
B3
B
90
B2
C
B4
70
60
Temperature drop
(exaggerated scale)
50
40
30
A
20
10
0
Time
Figure A2 Temperature variations in the Water Boiling Test
Each stage during which the temperature rises should be included in the calculation. The
change in temperature 'T during the simmering phase in the example shown above is
given by:
ΔT = ΔTB3 − B2 + ΔTC − B4
Baldwin (1987) in fact recommends the measurement of temperature fluctuations, and
makes provision for them to be included in the PHU equation.
Baldwin recommends that the second and subsequent pots should be ignored in the
calculation of efficiency. The equation he uses is that given in Section c above. He writes:
“... the additional heat recuperated by the second and subsequent pots increases the
laboratory PHU, but is ineffective in actually cooking food because it is too low in
temperature and because it cannot be easily controlled.” “... the performance of multipot
stoves in actual cooking of food is better predicted by their first pot PHU than by their
total PHU.” (Baldwin 1987:92).
The full efficiency equation, including all pots and water temperature fluctuations in each
pot, as well as average rather than initial mass of water in the first term of the numerator,
is as follows:
131
⎤
⎡
⎛ n
⎞
$k⎥
c p m k ⎜ ΔTi ⎟ + h fg m
⎢
K
⎝ i =1
⎠k
⎥
⎢
η=
⎥
⎢
o
o
m f h f − m c hc
k =1 ⎢
⎥
⎥
⎢
⎦
⎣
where
k is the pot number
K is the number of pots
∑
∑
m k is the average mass of water in each pot (kg)
ΔTi is the rise in water temperature (K)
i is the heating stage number
n is the final heating stage
$ k is the mass of water evaporated from each pot (kg)
m
m f is the mass of fuel (wood) used during phase (kg)
h fo is the enthalpy of fuel combustion at the reference temperature (kJ / kg)
m c is the mass of char remaining at the end of the phase (kg)
hco is the enthalpy of char combustion at the reference temperature (kJ / kg)
A.3.3 Smoke and specific optical density and TSP
Specific Optical Smoke Density (OSD), which is independent of optical path length can be
defined for black smokes, and monochromatic light as in the equation below.
log 10
OSD =
100
100 − S x
x path
where
OSD is the Optical Smoke Density (m -1 )
S x is the smoke obscuration (%)
x path is the optical path length (m)
Total Suspended Particulate mass concentration is calculated by multiplying the OSD by
9.4, the calibration coefficient described in Section 2.4.
132
Appendix B Requirements of a testing method
In this appendix we consider five major choices which must be made by anyone attempting
to develop emission testing guidelines. The guideline developer must decide whether to
use:
•
International standards or testing guidelines;
•
absolute or comparative measurements;
•
integral or real time measurements;
•
indirect or direct measurements; and
•
the Water Boiling Test or some other experimental method.
B.1
International standards versus testing guidelines
After many years of controversy over the definition of efficiency and test methodology the
publication of a ‘standard’ for Testing the efficiency of wood-burning cookstoves by the
Volunteers in Technical Assistance (VITA) in 1985 produced a “generally accepted ... test
procedure that can be applied universally.” (Stewart 1987). The laboratory test is known
as the Water Boiling Test (WBT).
Should international standards similar to those for efficiency be produced for emission
testing?
The VITA standards state the primary purpose of stove testing in the following way (page
vii): “Stove testing is the systematic measuring of the advantages and limitations of a
particular stove model. Its primary aim is to help identify the most effective and desirable
stoves for a specific social and economic context. With ongoing stove production, a testing
program provides essential quality control and may lead to important design
modifications.” This is similar to the purpose of testing as defined in this study: testing so
that different stove models can be compared and hence improved within a specific context.
The group involved in setting the standards felt it important to stress that “a distinction
should be made between testing done for local use only (for stove users and others) and
testing where the results are intended to be transmitted to other places.” (VITA 1985:viii).
133
They hoped that “by imposing a scientific standard in stove testing, ..., [they would] assure
a high degree of uniformity in stove test results from around the world. The widespread
use of standardised testing procedures will permit the comparison of stove designs on a
more systematic basis...”.
It seems clear that the VITA method is intended to allow comparison of stoves between
different stove programmes – an international standard.
Problems with the VITA standards are discussed by Bialy (1991:5). He questions them on
a number of levels: the tests may not be sufficient for the right choices to be made; the
methods are not as widely used as intended (see variations in Baldwin 1987:84; Stewart
1987; Butcher et al 1984:3; Jayaraman et al 1989:121; Joshi 1989:764; and Ahuja et al
1987:249,254); and, as a basis for international comparison they are lacking because they
do not specify some important parameters.
A method intended to allow comparison between different stove programmes around the
world would need to be far more specific than that given in the VITA standards.
A successful stove in one area, may be a disaster in another. Stove performance is a
function of many variables and therefore must be area specific (Bialy 1991:9). This is
demonstrated in tests which have shown that even altitude has an effect on emissions
from wood-burning stoves (McCrillis & Burnet 1990:692). There is no one perfect stove for
all areas (Kristoferson & Bokalders 1991). Internationally standard tests would be of no
use to development organisations attempting to find the most “effective and desirable
stoves for a specific social and economic context”. It seems impossible to design tests
which allow both international comparisons and provide useful data for a specific social
context.
In the design of tests for emissions a similar tension exists between methods which allow
inter-programme comparisons and methods which are only specific to a local context.
It seems clear that recommendations or guidelines for stove emission measurement are
required rather than strict ‘standards’. The purpose of these recommendations would be
to ensure that any results were consistent (giving the same results each time under the
same local conditions) and representative (giving some indication as to what can be
expected in the field, that is, within a specific context).
134
Table B1 International standards versus testing guidelines
SUMMARY OF ADVANTAGES AND DISADVANTAGES
International Standards
Testing Guidelines
Allows international comparisons
Can relate to specific socio-cultural practice
Requires very specific controlled conditions
Guidelines ensure control where it is
which limit local area applicability
necessary, but are flexible for non-critical
factors
Two objections to using guidelines rather than standards are frequently made:
•
The above discussion implies that an organisation using these guidelines to choose
between two stoves, for example, would need to test both stoves and not rely merely on
results from other testing programmes.
•
It would also be difficult for a development organisation to choose the best design from
those available elsewhere. The organisation would need samples from other
programmes and would need to test them according to their own specific socioenvironment.
Both of these observations are true and should, in fact, be stressed – stoves in general are
not directly transferable to different contexts. Test results from other socio-environments
are, however, useful indicators of a stove’s strengths and weaknesses and are not
completely worthless provided the development worker considers both the origin and
destination environments carefully.
B.2
Absolute versus comparative measurements
Technical studies on stove emissions, using sophisticated equipment have been used in the
environmental (see Smith et al 1992 for work on determining greenhouse gas emissions),
medical (Calle & Zeighami 1984; van Houdt et al 1986; McCrillis, Watts & Warren 1992),
and combustion fields (Islam et al 1986; Islam & Smith 1989). The results are intended to
be general – indicating the extent of the problem, and at the same time absolute – given in
units which are internationally recognised. These complex tests usually cannot be carried
out by development organisations interested in finding the best stoves for their particular
area.
135
Tests for use within development organisations, on the other hand, are used to compare
designs in order to choose the best; to improve a design; and to measure the effect of
modifications on emission characteristics. When comparing stoves it is not necessary for
the results to be given in absolute units. Relative units (for example, one stove emits 20%
less carbon monoxide per task than another) would be sufficient for a development
organisations’ needs. Absolute units would be a nice luxury – but they are clearly not vital
for these types of measurement.
In experimental design it is often recognised that comparative measurements are better
than absolute. “It is generally advisable to make comparative observations or
measurements where this is possible, instead of relying on absolute measurements. In
most cases it is some comparison which is the real object of the experiment, and it is
usually better to make this comparison directly...” (Wilson 1952:38.) Two stoves cannot be
tested simultaneously thus allowing just one measurement to be made, but since a
universal absolute is not required, as long as measurements for each stove are made in the
same units and using a common ‘zero point’, comparisons can be made.
Table B2 Absolute versus comparative measurements
Absolute Measurements
Useful for international comparison
Comparative Measurements
Relates directly to the object of the
experiment.
Useful for international conclusions – for
Limited usefulness of data beyond local
example environmental management
context
Higher cost
Lower cost
Calibration to international standard
Internal calibration
necessary
Once again it must be stressed that the above argument implies that in order to compare
two stoves both designs must be available for testing using the same apparatus and test
procedure.
136
B.3
Integral versus real time measurements
Efficiency and emissions from fires vary greatly with time. Integral measurements
involve the measurement and recording of ONLY the sum or average of a variable over a
defined time period, usually of a long duration. Real time measurements involve the
measurement of the value of a variable at a particular time. The distinction between the
two measurement types can become confusing when samples are collected and analysed
later. The greater the sample size the ‘more integral’ the measurement.
Often sensitivity requirements of equipment are less demanding for integral
measurements since a larger sample is collected. Since exposure potential is the important
value in health risk assessment long term measurements are frequently used. These
integrate short term fluctuations and provide a time-weighted exposure indication
(Hawthorne et al, 1984:16).
Table B3 Integral versus real time measurements
Integral Measurements
Integrates short term fluctuations
Real Time Measurements
Records all fluctuations – real as well as
errors
Comparisons direct and easy
Difficulties in interpretation – requires
detailed analysis
Can loose important interactions and
Allows for detailed analysis and calculation
relationships through averages
of integral as well as real time conclusions
Less demanding sensitivity requirements
Background noise problematic
For development organisations integral measurements are better than real time
measurements provided it has been verified that the proposed method is internally
consistent.
B.4
Indirect versus direct measurements
The choice between indirect or direct emission measurement basically means choosing
between the chamber method type of experiment (as described by Ahuja et al 1987) or the
137
hood method – using a hood to capture all the emissions and measure flue concentrations
(as in Butcher et al 1984).
The chamber method (Ahuja et al 1987), involving the indirect measurement of emissions,
seems to be growing in popularity. It has, however, the following problems:
•
The emission measurement, requiring absolute real time measurement of at least one
pollutant may be costly. Real time concentrations of carbon monoxide or some
other pollutant are required even though only a single emission factor for the stove can
be calculated from the data collected.
•
The air exchange rate in the room must be constant during the test. To meet this
requirement a hut with a secondary outer wall which encloses the entire hut is built –
the cost of such a construction could be high.
•
The need for a double wall enclosure would make field usage a problem; the method
has apparently not been assessed in the field.
•
To ensure that the pollutants are uniformly mixed in the room fans must be
strategically placed between the inner and the outer wall. These fans must be carefully
placed so as not to influence the stove combustion characteristics.
•
The emission source strength is assumed to be constant. It is sometimes presumed
that this implies a constant burn rate (see Young 1992). There are three problems with
this assumption:
- emission source strength is seldom constant;
- a constant burn rate is virtually impossible to achieve; and
- a constant burn rate may not imply a constant source strength.
•
The operators must expose themselves to the pollutants while tending the stove and
recording data from the instruments. High levels of carbon monoxide from poor stoves
could be dangerous.
•
The calculations required to interpret the data are particularly complicated and prone
to error.
•
A single charge of fuel is used, and the fire is tended only to ensure a steady flame –
this limits the relevance of the results to predictions of performance by rural users.
138
This of course is not central to the method and could easily be changed. The fire would
then need to be rearranged and tended. This issue is considered in Chapter 6.
•
The amount of information yielded by the study (an integral result over the whole test)
is small compared with the effort required, and the cost involved.
The hood method, involving direct measurement of emissions, as proposed by Butcher et
al (1984) has a number of problems:
•
Pollution measurement equipment is costly. Since absolute measurements are not
really required it seems possible to simplify the equipment and to use cheaper
methods.
•
Determination of air flow is costly and complicated. Again, since absolute
measurements are not required, measurements of flow rates in the flue are
unnecessary. All that is required is some assurance that flow rate is constant during
experiments and between experiments – this would be neither costly nor complicated.
•
The induced flow in the hood could change the stove combustion characteristics. This
is potentially a major problem with the method. This issue is examined in Chapter 3.
•
The extraction system is fairly expensive in the form used by Butcher et al (1984).
Cheaper methods, for example using a hair dryer fan, and a twelve volt battery for the
gas extraction, could be designed, depending on flow rates required.
•
The method in its present form is limited to the laboratory setting. It would be
possible, however, to design a battery powered extraction system, and a simple
portable hood to enclose the stove and protect it from outside influences such as wind.
Such apparatus, if carefully designed and tested, could be used indoors or outdoors,
and in the field as well as in the laboratory.
139
Table B4 Indirect versus direct measurements
Indirect Measurements
Direct Measurements
Requires costly real time measurements, but Although real time equipment is desirable it
only gives integral results – large expense
is not required.
with a small payback.
Assumes that room air exchange rate is
Extraction may influence stove combustion
constant, and requires careful mixing of
characteristics.
room air.
Very complicated experimental method and
Although still complex the interpretation of
calculations.
results is simpler than in the chamber
method. The experimental method is
simpler than that of the chamber method.
Emission strength is assumed to be constant
Does not rely on constant emission strength
– this is clearly not the case.
or fuel burn rate.
Limited to indoor studies.
Applicable in the field and laboratory
settings, indoors or outdoors.
B.5
Water boiling test versus other methodologies
Should emission tests be based on the Water Boiling Test (WBT) used in the measurement
of efficiency? It has already been stated that the VITA methods are not as widely used as
was intended. Not one of the emission tests, described in the sections above, used the WBT
method, with the tests by Butcher et al (1984) a possible exception (perhaps using
something similar to the provisional standards of 1982).
A distinction must be made between the method recommended for the WBT and the
methods of analysis given in the VITA standards.
The WBT described in Testing of the efficiency of wood-burning cookstoves by VITA (1985)
and in two books (Stewart 1987 and Baldwin 1987) which are based on the standard
method use slightly different efficiency definitions – all three use the same experimental
method but different analytical methods. Here we are discussing whether to use the
recommended experimental method, not a particular analytical method.
140
Testing a stove in the laboratory according to the WBT involves operating the stove under
two conditions, heating and simmering, using water to simulate food. Water is brought to
the boil as rapidly as possible during the heating up phase (commonly called the high
power phase) and then maintained within 5°C of boiling for 30 minutes during the
simmering phase (commonly called the low power phase). The fuel consumed for these
tasks is then measured. The Specific Fuel Consumed (SFC) for each phase as well as an
overall combined figure is then calculated.
The heating up phase and the simmering phase are intended to mimic the two most
common cooking tasks (VITA 1985:viii), boiling and simmering.
There are a large number of different test methods which have been used in previous
studies. These are compared in the following table (spaces indicate unspecified
information):
141
Table B5 Water boiling test versus other methodologies
Reference
Ignition
VITA (1985)
As normally
done in
households of
the area
SABS 1403:Gr
10:1986
30 minute
ignition period
before test
begins
As
recommended
by appliance
manufacturer
PD 6434 (BSI)
BS 3841:1972
Ignition gas at
set rate, fire
must reach 1.17
kW in 50
minutes for
valid test.
Defined fuel
charge for
ignition
McCrillis &
Burnet (1990),
McCrillis et al
(1992)
Newspaper and
kindling,
refuelled after
10 minutes
Smith et al
(1993), Smith et
al (1992)
Butcher et al
(1984)
Small amount of
kerosene
Refuelling
As required
Control
As required
As
recommended
by appliance
manufacturer
Steady state
operation at
rated output
Refuelled when
power output
drops below a
defined level. 20
seconds before
and after
refuelling
emission
measurement is
reduced.
Refuelled as
necessary to
maintain
desired burn
rate
Single charge –
no refuelling
Three or four
refuel charges
Pre-set controls
are not adjusted
unless
manufacturer
states that
adjustments are
necessary
Preliminary
tests are used to
set controls
which then
remain
unchanged for
the duration of
the test
Fuel added
when necessary
Heating 2 litres
of water, boiling
for 15 minutes
and simmer for
30 minutes
Heat water in
pots with lids –
pollutant
monitors
started when a
steady flame
had been
established
Nangale (1992)
One charge of
fuel – no
refuelling
Islam et al
(1986), Islam &
Smith (1989)
Ahuja et al
(1987), Joshi et
al (1989), Joshi
et al (1991),
Young (1992)
Single charge
End of each
piece of wood
dipped in a
measured
amount of
kerosene
Task
Heat water 2/3
pot capacity to
boil as rapidly
as possible,
simmer for 30
minutes
6 hour heating
period
Single charge of
fuel – no
refuelling
End point
30 minutes after
boiling
Time
Predetermined
time with fire
maintained at
desired burn
rate
Heating 2 litres
of water
Dependant on
appliance and
manufacturers
advice
Power drops
below defined
level after third or
fourth radiation
peak
Test completed
after 8 hours
30 minutes
duration
Rearranged and
blown with a
blowpipe as
needed
30 minutes after
boiling
Minimal fire
tending
End point when
water
temperature
started dropping
steadily
Controls
unchanged
3½ litres of
water heated in
pots with lids,
and maintain
boiling for 15
minutes
Fire tended to
ensure a steady
flame
Fire removed
from room when
water
temperature
dropped by 0.5 °C
(about 15 minutes
after boiling)
142
In the development of emission testing guidelines it seems wise to use the WBT as the
starting point. Ignition, refuelling and stove control may need to be controlled more
carefully than in the VITA standards. A contribution to this area is made in Chapter 4.
B.6
Recommendations
Based on the above discussions five suggestions are made.
1. Testing guidelines as opposed to rigorous international standards are required.
2. Comparative measurements are sufficient for the purposes of development
organisations – equipment for absolute measurements is an unnecessary expense.
3. For development organisations integral measurements will be sufficient to allow stove
comparisons.
4. The direct measurement of emissions from the stove yields far more information than
indirect measurements. Basic assumptions made for the ‘chamber’ method (Ahuja et al
1987) which involved indirect measurement of emissions seem to be questionable and
the experimental and analytical methods are complex.
5. The WBT method as described by VITA (1985) which involves two phases: heating up
to boiling point and simmering for 30 minutes should be used as the starting point for
the development of emission testing methods.
143
Appendix C Factorial analysis
The experimental design is often the most critical area of research. This appendix briefly
describes the design of a factorial experiment.
When there is more than one independent variable, emphasis is laid in classical methods
on varying the experimental conditions only one variable at a time. Observations are
repeated under exactly the same conditions. With factorial designs replicate observations
are not carried out under exactly the same conditions, and a number of variables are
changed simultaneously (see Fisher 1951:91; Wilson 1952:48).
There are three specific advantages to using a factorial design in experimentation rather
than classical methods (see Fisher 1951:99):
1. Greater efficiency – a number of factors (or variables) are evaluated with equal
precision with a fraction of the number of observations that would otherwise be
necessary.
2. Greater comprehensiveness – in addition to the determination of the effects of
single factors, interactions of the factors are also evaluated.
3. Wider inductive basis (Fisher’s term) – conclusions based on an experiment in
which many factors have been varied have been tested under a broader range of
conditions than if only one variable had been changed at a time.
Designing a factorial experiment involves firstly identifying important variables (or
factors) which are to be studied, and formulating an hypothesis. Secondly, levels at which
the variables will be tested are selected. A level of significance should be chosen before the
data is analysed, and the treatment combinations should be fully randomised. The method
of statistical analysis especially suited to factorial experiments is called the analysis of
variance (ANOVA).
C.1 Identifying variables and defining hypotheses
Independent variables which are believed to be significant are selected for study. A null
hypothesis is written for each variable – an hypothesis stating that the factor in question
has a negligible effect. A null hypothesis is specific enough to allow it to be disproved. It is
144
important to note that a null hypothesis is never proved or established, but is possibly
disproved. As Fisher (1951:16) puts it: “Every experiment may be said to exist only in
order to give the facts a chance of disproving the null hypothesis”. If the null hypothesis is
disproved the alternative hypothesis is not in fact proved. During analysis the null
hypothesis is proved false at a certain level of significance.
C.2 Selection of levels
Since each factor is set to predetermined levels for a particular experiment the selection of
the levels must be made carefully.
When selecting levels of the experimental factors the typical range of the variable must be
considered. Levels should not be set to extreme values – using extreme values could lead to
serious misinterpretation since frequently response curves change drastically at the ends,
as can be seen in Figure C1 which illustrates a predominantly linear response to a
variable.
Figure C1 Selection of variable levels in a factorial design
C.3 Level of significance
The statistical level of significance at which the null hypothesis is accepted or rejected
should be chosen carefully (Wilson 1952:59). The choice is usually based on the cost of
misinterpreting the result, and on previous experience. At times the term ‘confidence
145
limits’ is used instead of level of significance. A confidence interval of 95 % is taken as
being equivalent to a significance level of 5 %. This is not strictly precise but for practical
purposes the term can be used in this way (Brownlee 1949:34).
C.4 Treatment combinations, repetition and randomisation
Repetition within each treatment should be considered – greater accuracy is an obvious
advantage of repetition. Variation within repeated treatments is used as a measure of
error. Without repetition high order interactions (usually 4th, 5th, and higher) are used as
an indication of experimental error.
There are an infinite number of variables in any experiment which are usually considered
to be irrelevant (Wilson 1952:38; Fisher 1951:18,19). Variables which seem to be
insignificant may in fact be important. These seemingly unimportant variables vary in
either an unknown way or with unknown effect, and their effects can never be completely
eliminated. These variables, and their effects, can however be randomised by randomising
the order of the experiments (Wilson 1952:54).
C.5 Calculation methods
Analysis of variance is based on a property of variance that if a process has a number of
factors each contributing to the final result, than the total variance is equal to the sum of
the component variances (Brownlee 1949:51). This is not the case for the standard
deviation, σ , of a set of data. The variance, σ 2 , is computed according to the following
formula (Crow et al 1960:13):
2
⎡ n
⎛ n ⎞ ⎤
1
2
⎢n x i − ⎜ x i ⎟ ⎥
σ =
n( n − 1) ⎢ i=1
⎝ i =1 ⎠ ⎥
⎣
⎦
where
2
∑
∑
σ 2 is the sample variance
n is the number of sample readings
x1 , x 2 ,..., x n are the observations
For a two factor analysis, as in the case for the measurement of the influence of the test
rig on stove emissions, an ANOVA table can be constructed as shown in Table C1.
146
Table C1 The calculation of a two factor analysis of variance
Source
Degrees of
Sum of squares
Mean square
F ratio
freedom (df)
(SS)
(MS)
Stove (S)
s-1
σ 2s+ e + nσ 2se + neσ 2s
SSS
s−1
MSS
MS Error
Extraction (E)
e-1
σ 2s+ e + nσ 2se + nsσ 2e
SS E
e −1
MS E
MS Error
Interaction (SxE)
(s-1)(e-1)
σ 2s+ e + nσ 2se
SSS + E
( s − 1)( e − 1)
MSS + E
MS Error
Error
se(n-1)
σ 2s+ e
SS Error
se( n − 1)
Total
sen-1
where
s is the number of levels of the factor S (stove type)
e is the number of levels of the factor E (extraction level)
n is the number of repetitions of each combination of factors
Snedecor's F distribution is used to test for statistical significance. The size of the F factor
relates directly to the confidence at which the null hypothesis can be rejected - the larger
the factor the greater the confidence of the statistical inference.
147
Appendix D Wood combustion
It is not sufficient merely to study the emissions from a stove without looking in some
detail at the processes which are taking place within the stove. The combustion of the
wood relates to the fuel burn rate (or the reaction rate), the combustion products (or the
emissions), the required excess air for complete combustion, and the fire temperatures.
The processes are extremely complicated, principally because the fuel has a complex
physical and chemical composition and is burnt in an uncontrolled environment. The
burning of hydrocarbons is frequently chaotic. “Above a certain temperature objects can
suddenly burst into flame, burn furiously, then when the heat produced drops off, the
flames can suddenly cease. The reaction can choose between two stable modes... chaos”
(Scott 1992:108).
To simplify things use is often made of a Simple Chemically-Reacting System (SCRS)
where all factors except oxidant, fuel, and products are removed (Spalding 1979:101). This
has led to descriptions of the combustion process which are overly simplified – usually the
combustion of carbon in oxygen. These descriptions are useful in the basic understanding
of the process, but are severely limited when one attempts to understand the formation of
the emissions from wood fires. We look at the fuel and the way it burns in some detail in
this chapter – even so, this is only a brief introduction to the subject.
A simple combustion model is given in Figure D1.
148
HEAT
OXIDANT
air
FUEL
> Moisture
> Inorganic
materials
> Organic
materials
COMBUSTION
COMBUSTION
PRODUCTS
WATER
Figure D1 Simple wood combustion model
D.1 Oxidant
Oxygen deficiency leads to incomplete combustion and the formation of many products of
incomplete combustion. Excess air cools the system. The air requirements depend on the
chemical and physical characteristics of the fuel. The efficiency of the combustion process
and the system as a whole also depends on the intake and temperature of the air which
contains approximately 21% oxygen and 78% nitrogen (Shafizadeh 1981:120).
D.2 Fuel
Both the chemical and the physical composition of the fuel are important determining
factors in the characteristics of combustion.
Wood can be analysed by breaking it down into structural components (called proximate
analysis) or into chemical elements (ultimate analysis). Below are given average results of
the two types of analyses.
149
Table D1 Proximate analysis of wood (Shafizadeh 1981:106)
Species
Ash (%)
Extractives (%)
Lignin (%)
Hemicellulose (%)
Cellulose (%)
Softwood
0.4
2
27.8
24
41
Hardwood
0.3
3.1
19.5
35
39
Table D2 Ultimate analysis of wood (Cheremisinoff 1992:8)
Carbon (%)
Hydrogen (%)
50.5
6.0
Oxygen (%)
42.4
Nitrogen (%)
0.2
Sulphur (%)
Non-combustibles
0.05
1.0
D.2.1 Moisture
Moisture in wood (and other biofuels) is stored in spaces within the dead cells and within
the cell walls. When the fuel is dried the stored moisture equilibrates with the ambient
relative humidity. Equilibrium is usually about 20% in air dried fuel (Shafizadeh
1981:105).
The moisture in the fuel acts as a heat sink, lowering the combustion efficiency. It also
promotes the formation of carbonaceous char (that is char, water and carbon dioxide)
(Shafizadeh 1981:118).
D.2.2 Inorganic Materials (Ash)
Inorganic materials in plants depend on the type of the plant and the soil contamination in
which the plant grows. On average wood contains about 0.5% ash. Insoluble compounds
act as a heat sink in the same way as moisture, lowering combustion efficiency, but soluble
ionic compounds can have a catalytic effect on the pyrolysis and combustion of the fuel
(Shafizadeh 1981:106) – more detail is given below. The presence of inorganic compounds
favours the formation of char (Shafizadeh 1981:118).
The ash is typically composed of the following compounds:
150
CaO (±50%), K2O (±20%), Na2O, MgO, SiO, Fe2O3, P2O5, and SO3 (Baldwin 1987:175). The
SO3, as reported in an ash analysis, is in the form of a sulphate (for example, CaSO4 or
K2SO4).
D.2.3 Organic Materials
The organic compounds in wood are principally in the form of cellulose, hemicellulose,
lignin. A small proportion are solvent soluble extractives (lipids and terpenes).
a) Cellulose
Cellulose is the same in all types of biofuel - except for the degree of polymerisation. It is
composed of D-glucopyranose units linked linearly with I-(1Æ4) glycosidic links.
Cellulose is the main component of wood (Shafizadeh 1982:749).
b) Hemicellulose
Acetyl-4-O-methylglucuronoxylan forms the main hemicellulose of hardwoods.
Glucomannan forms the main hemicellulose of softwoods. These carbohydrates easily
break down at the glycosidic link. They have a lower heat of combustion than cellulose
because they contain several molecules of water in their chemical composition ([C6(H2O)5]n
or [C5(H2O)4]n). Hardwoods have a greater proportion of acetyl and methoxyl groups than
do softwoods. This explains why they are used in distillation to obtain acetic acid and
methanol.
c) Lignin
Lignins have an approximate analysis of C10H11O2 for both softwoods and hardwoods
(Shafizadeh 1981:112). In addition to the same compounds as hemicellulose, hardwoods
have syringyl propane units, and softwoods contain guaiacyl propane units. On
combustion, lignin yields mainly char (Shafizadeh 1981:107) although the quantity of char
depends strongly on the burning conditions.
D.2.4 Direct combustion
Biomass fuels never burn directly: Solid biomass fuels are thermally degradable and under
the influence of a sufficiently strong energy source they break down into a mixture of
volatiles and carbonaceous char. The two modes of combustion (solid char, and gaseous
151
volatiles) have completely different chemical mechanisms and kinetics. The thermal
degradation of the fuel is called pyrolysis.
D.3 Pyrolysis
Cellulose and hemicellulose form mainly volatile products on heating due to the thermal
cleavage of the sugar units. The lignin forms mainly char since it is not readily cleaved to
lower molecular weight fragments (Shafizadeh 1981:110).
The discussions of pyrolysis below focus primarily on cellulose because it is the largest
component of the wood forming volatiles (Shafizadeh 1982:749).
D.3.1 Ratio of volatiles to char
The proportion of volatiles to char is a complex interaction of temperature, heating rate,
particle size and the effect of catalysts. Yield is highly dependent on the pyrolysis
temperature (the heat treatment temperature), the nature of the substrate, and the
presence of incombustible materials (Shafizadeh 1982:758).
Addition of an acidic catalyst or slow heating promotes the dehydration and charring
reactions. It follows that a higher temperature and smaller particle size, leading to
increased heating rates, promotes the production of volatiles, whereas lower temperatures
and larger pieces of wood promotes the formation of char (as well as water and CO2). The
presence of water, and inorganic materials also promote the formation of char because of
the ‘heat sink’ they provide.
D.3.2 Initiation reactions
Cellulose and hemicellulose initially break into compounds of lower molecular weight. This
forms an ‘activated cellulose’ which decomposes by two competitive reactions – one
forming volatiles (anhydrosugars) and the other char and gases.
D.3.3 Pyrolysis reactions
The thermal degradation of the activated cellulose and hemicellulose to form volatiles and
char can be divided into categories depending on the reaction temperature. Within a fire
all these reactions take place concurrently and consecutively. The reactions are highly
complex - they are briefly described in Table D3.
152
Table D3 Pyrolysis reactions at different temperatures
Condition
Processes
Products
Below 300°C
free radical initiation, elimination
formation of carbonyl and carboxyl,
of water and depolymerisation
evolution of CO and CO2 and
mainly a charred residue
300-450°C
breaking of glycosidic linkages of
mixture of levoglucosan,
polysaccharide by substitution
anhydrides and oligosaccharides
largely in the form of a tar fraction
Above 450°C
dehydration, rearrangement and
variety of carbonyl compounds
fission of sugar units
such as acetaldehyde, glyoxal and
acrolein which evaporate easily
Above 500°C
a mixture of all above processes
Condensation
unsaturated products condense and a highly reactive char residue
cleave to the char
a mixture of all above products
containing trapped free radicals
153
D.3.4 Volatiles
The yield of gases within two different temperature regimes is given in Table D4.
Table D4 Yield of volatile gases at different temperatures (Speight 1993:57)
<400°C
>1000°C
125
>550
CO2
30
20
CO
25
25
CH4
14
12
CnHm
4
2
H2
20
35
N2
7
6
Yield of gas (m3/ton)
Composition (vol. %)
The organic compounds in the biofuel break down and evaporate into (Shafizadeh
1981:107).
1)
2)
a gas fraction containing:
•
CO
•
CO2
•
some hydrocarbons
•
H2
a condensable fraction containing:
•
H2O
•
low molecular weight organic compounds
- aldehydes
- acids
- ketones
- alcohols
154
3)
a tar fraction containing:
•
higher molecular weight sugar residues
•
furan derivatives
•
phenolic compounds
•
airborne particles of tar and charred material which form the smoke.
Gaseous emissions are predominantly a product of pyrolitic cracking of the fuel. If flames
are present, fire temperatures are high, and more oxygen is available from thermally
induced convection. The lower temperatures of the smouldering stage results in a lower
oxygen supply from diffusion into the fuel bed – gases in this phase which leave the fuel
bed are not oxidised further (Lobert et al 1995:295).
D.3.5 Char
The char which is formed is highly reactive because of the trapped free radicals, and
porous. This means a large surface area which has a large absorptive capacity. The
properties of the char are related to the pyrolysis conditions as well as the physical and
chemical properties of the fuel. Cellulose chars are most reactive and have the greatest
surface area when formed at 550°C (Shafizadeh 1981:122).
D.4 Combustion
The pyrolysed products, volatiles and char, burn with completely different characteristics.
The burning of the active carbon (the char) to form CO2 in the presence of sufficient
oxygen and high enough temperatures is known as glowing combustion. Where
temperatures are too low, or where there is insufficient oxygen for complete combustion
smouldering occurs (characterised by smoking or emission of unoxidised pyrolysis
products). The burning of the volatiles is known as flaming combustion. Flaming
dominates at higher temperatures and smouldering at lower temperatures.
D.4.1 Reaction Rate
At lower temperatures, that is for glowing and smouldering combustion, the rate of
combustion is controlled by the pyrolysis and combustion kinetics. At higher
temperatures, for flaming combustion, the reactions take place very rapidly and heat and
mass transfer factors dominate (Shafizadeh 1981:120).
155
Determining the reaction rate of even a simple solid (such as a carbon sphere) is complex
and involves at least the following five steps (Kanury 1975:201):
1. Oxygen has to diffuse to the fuel surface,
2. Diffused oxygen has to be absorbed by the surface,
3. Absorbed oxygen has to react with the solid to form absorbed products,
4. Absorbed products have to be desorbed from the surface, and
5. Desorbed products have to diffuse away from the surface.
These steps, which must occur in order, determine the reaction rate. The slowest step,
under the reaction conditions determines the burning rate. For carbon combustion steps 2
and 4 are known to be extremely rapid. Step 3 is the slowest when the particle
temperature is low, and hence kinetic processes dominate. In this kinetic regime, the
burning rate is exponentially related to temperature.
When temperature is high step 3 is faster than steps 1 and 5 and therefore the reaction
rate is controlled by mass transfer processes. In this regime, burning rate depends weakly
on temperature and strongly on particle size.
The formation of the volatiles at temperatures greater than 400°C is a highly endothermic
process and consequently higher temperatures do not necessarily lead to greater reaction
temperatures (Shafizadeh 1982:757).
The formation of an ash layer on the char slows combustion appreciably (Baldwin
1987:183).
D.4.2 Combustion of Activated Carbon
Char is very different from pure carbon compounds like graphite. Cellulose chars have a
formula of approximately C6.7H3.3O (Shafizadeh 1982: 758). It is useful however to
consider the burning of a pure carbon particle because it can give us an indication of what
can be expected from complex compounds.
The burning of a carbon particle has been studied in some detail (See Spalding 1979:371392). Carbon can oxidise to form either carbon monoxide or carbon dioxide according to
the following two equations:
156
C + O2 Æ CO2
C + ½O2 Æ CO
At lower temperatures, and in the presence of sufficient oxygen (Shafizadeh 1981:123) the
formation of CO2 dominates. At higher temperatures CO is formed preferentially, and
either escapes or burns later, well away from the solid carbon.
The ratio of CO to CO2 is influenced by various anions and cations (Shafizadeh 1981:123).
Phosphates and borates (anions) increase the formation of CO and decrease CO2. Sodium
and potassium ions (cations) reduce CO and increase CO2 and therefore promote
smouldering combustion.
At very high temperatures no oxygen reaches the carbon and it therefore ‘burns’ in carbon
dioxide according to the following reaction equation:
C + CO2 Æ 2CO
The flame produced by this reaction is pale blue and envelopes the char particle. Oxygen
diffuses inwards, and CO or CO2 move in the opposite direction.
Outgoing pyrolysis products also react with the carbonaceous layer (Kanury 1975:200).
Frequently inert gases are absorbed on the char surface (gases such as N2 and CO2). These
reactions are rapid and reversible.
D.4.3 Combustion of Volatiles
The volatiles burn with flames. Many free radical reactions are involved in all phases of
this process. The transformations are extremely complicated and include further fission,
dehydration, and disproportionation of the sugar units (Shafizadeh 1981:121). Further
pyrolysis of the volatiles can cause char particles to form in the gas. This is the cause of
soot. Soot is also formed at temperatures of around 700°C according to the following
reaction: 2CO Ù CO2 + C.
D.4.4 Sulphur Dioxide
Whereas CO is a product of incomplete combustion, SO2 is the result of perfect combustion
(Myers et al 1973:3).
157
Sulphates are frequently emitted as particulates (Myers et al 1973:6).
Sulphur can exist in the fuel in an organic or inorganic form. In coal there is usually more
organic sulphur than inorganic (Speight 1993:6). Organic sulphur groups are usually
oxidised to sulphates (van Krevelen 1961:171) whereas inorganic sulphur is oxidised to
pyritic sulphur FeS2 (Speight 1993:147, 150).
158
Appendix E Case study: cooking devices compared
This paper was accepted subject to revision by Biomass and Bioenergy on 1 December
1995. This revised version was submitted on 21 May 1996 and was subsequently accepted
for publication. The full reference is: Ballard-Tremeer G & Jawurek H H (1996)
Comparison of Five Rural, Wood-Burning Cooking Devices: Efficiencies and Emissions,
Biomass and Bioenergy, Vol 11, No 5, pp. 419-430, Elsevier Science Ltd, Great Britain.
Comparison of Five Rural, Wood-Burning Cooking
Devices: Efficiencies and Emissions
G. Ballard-Tremeer 1 and H. H. Jawurek 2
School of Mechanical Engineering, University of the Witwatersrand, Johannesburg,
P. O.WITS 2050, South Africa
Abstract
The following cooking devices were compared: An open fire built on the ground, an ‘improved’ open
fire built on a raised grate, a one-pot metal stove, a two-pot ceramic stove and a two-pot metal stove.
Efficiencies (ratios of energy entering the pot to the energy content of the fuel consumed) were
determined by carrying out a computer-controlled version of the standard Water Boiling Test.
Emission concentrations of smoke, carbon monoxide, and sulphur dioxide were measured by means of
a fume extraction hood, an optical smoke density meter and an electrochemical flue gas analyser.
Average emissions of smoke were lowest for the improved open fire and the two-pot ceramic stove,
with the remaining devices higher-emitting by factors of 1.5 to 3. Emissions of carbon monoxide and
sulphur dioxide were lowest for the two open fires; the stoves were higher-emitting by factors ranging
from 2 to 3 for carbon monoxide and 3 to 10 for sulphur dioxide. Average efficiencies were 14% for the
open fire, 21% for the improved open fire, and (with no statistically significant difference) 20 to 24%
for the stoves .
Key words: Stoves, woodstoves, cooking fires, efficiency, emissions, biomass.
1
Graduate student
2
To whom correspondence should be addressed e-mail: [email protected]
159
1 Background and Aims
The cooking devices to be compared in this study are: an open fire, an ‘improved’ open fire built on a
raised grate, a commercial one-pot metal stove, a prototype two-pot ceramic stove and a prototype
two-pot metal stove.
The open, wood-burning fire built on the ground with a pot supported above it − the ‘three stone fire’
− is the most basic of cooking devices, and in many rural areas of the world the most common. It is
thus a natural point of reference in a comparison of stove types. Open fires are widely held to have
low heat transfer efficiencies (ratios of energy entering the pot to that liberated by combustion) and
high levels of pollutant emission.
It is to be expected that raising an open fire onto a grate would lead to reduced heat losses to the
ground and, by supplying primary air from beneath the fuel bed, to increased completeness of
combustion. This would favour both increased efficiency and reduced emissions. Krishna Prasad1
further mentions that a grate ‘helps in defining the combustion space better, thereby promoting the
use of compact fires’ (as opposed to wastefully large ones).
The only quantitative study of open fires with and without grates appears to be that of Visser and
Verhaard of the Eindhoven Woodburning Stove Group, reported in summary form by
Gopalakrishnan2. For wood (white fir) of 10% moisture content and with the pot elevated 110 mm
above the fuel bed (both reasonable values in practice) the efficiencies were 20.5% for the open fire
and 22% for the fire on a grate. The corresponding figures for oven-dried wood were 21% and 24%.
These are not large improvements. However, the test methods that were employed differed from the
VITA (Volunteers in Technical Assistance) tests that are currently accepted as standard3,4 and this
may have biased the results; certain test methods are known to favour certain stove types5. Baldwin6,
on the other hand, in dealing with West African uninsulated metal (‘malgache’) stoves, reports that
the fitting of a grate increased their efficiency from about 18 to nearly 25%. Emissions were not
measured in either study.
Early stove work was aimed largely at increasing fuel efficiency. The last decade, however, has seen
an increasing awareness of the problem of emissions. In 1992 the World Health Organization7 stated
that emissions from rural, biomass-burning cooking sites were a health hazard affecting half the
world’s population (approximately 2500 million people). Emissions are now considered at least as
important as efficiencies.
The commercial one-pot metal stove used in this study is a typical example of current trends in stove
design. It has light-gauge steel inner and outer walls, ceramic insulation and an adjustable damper to
control the inlet air flow. The stove is chimneyless and top-fed (the pot has to be removed to add fuel).
The stove was advocated as being fuel-efficient, but there was no information on its emission
160
characteristics. Presumably many buyers − perhaps even the manufacturers − share the widely-held
view that any stove must be lower-polluting than an open fire. In fact, the opposite is more likely.
Increased efficiency (‘Percentage Heat Utilised’) is frequently achieved at the cost of reduced
completeness of combustion and thus of increased emissions8. Nangale9 in comparing a three stone
fire with an ‘improved’ metal stove obtained an increase in mean efficiency from 22.8 to 24.2% and
increases in emissions by factors of about 5 for both carbon monoxide and total suspended
particulates, and 2.2 for hydrocarbon acidity.
The two-pot ceramic stove of this study is similar in design to the TERI (TATA Energy Research
Institute, Bombay) Improved Chimneyless Woodfuel Cookstove4. It consists of two pot holders; the
first contains the firebox and is the main cooker; a tunnel connects the first to the second pot holder;
combustion gases escape from the latter around the second pot which is intended for simmering and
for maintaining food at temperature. The design respects the two-pot cooking that is practised in
many parts of the world where meals consist of a starch-based main dish and a smaller dish of
vegetables or meat. Additionally, the second pot recuperates energy from the flue gases, thus
improving efficiency. Emissions were not considered at the time of design (1990).
The two-pot metal stove represents an attempt to provide, at low cost, the features of a ‘proper’ stove
− the widely desired cast iron range. The features are: durability − the result of construction in
appropriate metals, the ability to accommodate two (or more) pots, a flat cooking surface, operation at
waist height, refuelling without removal of the pot(s), and a chimney. The two-pot metal stove of this
study has galvanised steel inner and outer walls enclosing a layer of ceramic fibre insulation, a
removable heavy-gauge steel cooking plate (hob), a stainless steel fire box, and a chimney. We are
informed (by an associate who has worked on this stove) that a stove of strikingly similar design is
widely used in Lapland.
The two-pot ceramic stove and the two-pot metal stove were developed in the School of Mechanical
Engineering in co-operation with the Wits Rural Facility (WRF), an interdisciplinary unit of our
University concerned with rural upliftment and operating in Mpumalanga (previously Eastern
Transvaal) province. The ceramic stove was designed to be manufactured by rural potters using
locally available materials and traditional techniques, and several units were successfully
manufactured in this manner. Field tests were conducted in the vicinity of the WRF, our study area.
Despite initial community enthusiasm for the stove, it failed to achieve long-term acceptance10. The
stove remains of interest, however, because it represents a recognised type of cooking device that is in
use elsewhere. The two-pot metal stove was designed after extensive consultation with the
inhabitants of our study area. The design was modified a number of times (for improved operation
and greater ease of local manufacture) and appears to have community acceptance. For purposes of
the present comparison the stove is an example of a distinct class of rural cooking device − the rangetype stove.
161
The aims of the present study are to compare the efficiencies (determined by standard VITA tests)
and the emissions of the five rural cooking devices of markedly different design discussed above.
2 Apparatus and Procedure
2.1 The cooking devices (‘stoves’)
These are shown in Figure 1. The open fire was built on a sand base 50 mm thick and beneath the
tripod shown. The tripod supported an aluminium pot of 250 mm diameter and of 5 litre capacity,
filled at the beginning of each test with 2 litres of water. The same pot size and charge was used
throughout, also as the second pot in the case of two-pot stoves. The improved open fire was of the
same dimensions as the open fire, but was fitted with a wire grate of 10 mm square pitch on which the
fire was built. The grate area (maximum fuel bed area) was approximately half the area of the bottom
of the pot. The main features of the three stoves have already been discussed. Note that the two-pot
metal stove is drawn to a smaller scale than the other cooking devices.
Ø200
Open fire
1 pot metal stove
Improved open fire
180
200
250
2 pot ceramic stove
650
2 pot metal stove
Figure 1 The cooking devices
162
2.2 Efficiency
Efficiency was determined by carrying out the Water Boiling Test (WBT) recommended by VITA3.
Stewart4 describes this as a ‘generally accepted ... test procedure that can be applied universally’.
The WBT involves operating the stove under conditions of heating up and simmering, using water to
simulate food. Water is brought to the boil as rapidly as possible during the heating-up phase
(commonly called the ‘high-power phase’) and is then maintained within 5oC of boiling for 30 minutes
during the simmering phase (called the ‘low-power phase’). In this study the efficiency of each phase
was determined (though only the overall efficiency over the entire test is reported here). In order to
determine the separate efficiencies it is necessary to know the energy content of the combustibles
remaining at the end of each phase. At the end of the simmering phase (end of test) this presented no
problem. The wood and the char (each of known calorific value) were separated and weighed. At the
end of the heating-up phase and with open fires wood and char were separated and weighed rapidly,
the fire was reassembled and the test was continued into the simmering phase. With enclosed stoves,
however, the removal of combustibles at the end of the heating-up phase proved too problematic. The
stoves were thus fuelled in such a way that char only remained at the end of the heating-up phase.
The required control of the fire was difficult to achieve with both procedures and repeatability was
inherently low, as also noted by Nangale9.
Efficiency is defined as the ratio of energy entering the pot to the energy content of the fuel
consumed. The energy entering the pot produces two measurable effects: raising the temperature of
the water to the boiling point and evaporating water. The former was measured by a thermocouple
(others measured fire temperature), the latter by a digital weighing platform on which the stove
rested. Initial mass of wood, added wood, and char (and where applicable, wood) remaining at the end
of each phase were similarly determined by weighing. Thus the energy content of the fuel consumed
could be calculated. For the one-pot cooking devices efficiency was given by
η=
c pm ΔT + hfg m fg
m f hf − mc hc
where
η is efficiency (fractional)
c p is the specific thermal capacity of water (kJ kg-1 K-1)
m 1 is the average mass of water in the pot during the heating-up phase (kg)
ΔT is the rise in water temperature for the heating up phase (K)
hfg is the enthalpy of vaporisation of water (kJ kg-1)
163
m fg is the mass of water evaporated (kg)
m f is the mass of fuel (wood) used during the test (or phase) (kg)
hf is the enthalpy of combustion (lower calorific value) of the fuel (kJ kg-1)
mc is the mass of char remaining at the end of the test (or phase) (kg)
hc is the enthalpy of combustion of the char (kJ kg-1)
The resulting efficiencies are for all practical purposes identical with the widely used ‘Percentage
Heat Utilised’ of Baldwin’s6. (He uses initial rather than average mass of water in the first term of the
numerator.) For the two-pot stoves the numerator terms − the energy absorbed − were summed over
both pots. Baldwin6 recommends that the second pot be ignored since ‘... the additional heat
recuperated ... is ineffective in actually cooking food because it is too low in temperature and because
it cannot be easily controlled’. This has not been our experience during fieldwork: we have seen the
second pot used very effectively on our stoves.
The efficiencies of cooking devices are frequently reported as a function of ‘fire power’. Fire power is
defined as the ratio of energy content of the fuel consumed during a test (or phase) to the duration of
the test (or phase).
2.3 Direct versus indirect measurement of emissions
The direct measurement of emissions involves measurement at the source − the stove − and uses an
extraction hood to capture the emissions11. Indirect methods measure the influence of the stove on a
dilution chamber (simulating a dwelling) and calculate the ‘source strength’ (emission rate) on the
assumption that it is constant12. The ‘hood method’ was used in the present study. It requires fewer
assumptions than the ‘chamber method’ and it has the potential of providing more information. The
question whether ‘the mechanically induced air flow [changes] the combustion characteristics of the
stove’12 was addressed in preliminary tests discussed below.
2.4 Extraction rate
The stove and the weighing platform were placed beneath an extraction hood fitted with a butterfly
damper and an orifice plate flow meter. The volumetric extraction rate was set at three different
levels, 0.049, 0.056 or 0.065 m3 s-1, in order to study the effect of extraction on stove performance. The
lowest of these rates was one that was sufficient to capture all smoke, but that had no visible effect on
the flame of a lit match held in the position normally occupied by the stove. The highest rate was one
that had a small, but clearly discernible effect on the flame. Statistically designed experiments
(analysis of variance) showed that extraction at the above levels had no effect (at 95% confidence) on
stove efficiency, fire power, fire temperature and the emission of all pollutants measured with the
164
exception of carbon monoxide (CO). There was a small decrease in CO emissions with increasing
extraction, but there was no interaction (at 95% confidence) between this and stove type. This means
that the CO emissions of all stoves were equally influenced by extraction. An empirical hood design
equation was used to calculate the air (‘capture’) velocities at the stove13 corresponding to the above
extraction rates. The velocities ranged from 0.10 to 0.12 ms-1. Typical air currents in a closed room are
0.25 ms-1
13
. The hood method can therefore be used with confidence, provided that the extraction
rate is appropriately low and is not changed between tests.
2.5 Pollutants measured
The pollutants measured were particulates (smoke), carbon monoxide (CO) sulphur dioxide (SO2),
oxides of nitrogen (NOx) as well as carbon dioxide (CO2). Among these CO constitutes both a short
and long term health hazard, while particulates, SO2 and NOx have long term health effects.
Hydrocarbon emissions were not measured. However, the most hazardous group of these, the
polyaromatic hydrocarbons − many of which are known carcinogens − are emitted as particulates14.
Since the particulates emitted by wood fires are predominantly in the respirable size range11,14 it is
appropriate to measure total suspended particulates (TSP). TSP were measured by means of a light
obscuration (attenuation) meter consisting of a light-emitting diode and a light-dependent resistor
operating in the linear range. The meter was mounted in the exit duct of the extraction hood.
Obscuration was expressed in terms of specific optical smoke density (OSD, m-1) which is defined as
OSD = log 10(100 / 100 - S x ) x-1
where Sx is the light obscuration (%) over the path length x (m).
The correlation between OSD and mass concentration of TSP was established by use of a standard
filter sampling system as employed in air pollution measurements. Flue samples were drawn through
two Nucleopore acid etched membrane filters in series, the first of 8 μm pore size, the second of 0.4
μm. These filters had 50% collection efficiencies for particles of 2.5 and 0.01 μm aerodynamic diameter
respectively15. Sample volume (over a sampling period of a few minutes) was measured by means of an
air volume (dry gas) meter. Particulates collected were measured by weighing the filters. (The masses
collected on the fine filters were ten times those collected on the coarse filters; this confirms the
largely respirable nature of the particulates.) Eleven such calibration data points were established at
different naturally-occurring stages of smokiness of a stove. The correlation between mass
concentration and OSD, time-averaged over each sampling period, was linear (correlation coefficient
0.98), as also found in other studies16,17.
Gas was sampled from the exit duct of the extraction hood and concentrations (above background) of
CO, SO2, NOx and CO2 were measured by means of an electrochemical flue gas analyser manufactured
165
by Industrielle Mess- und Regelsysteme für Umwelttechnologie, Heilbronn, Germany, the IMR
3000P. The emissions of NOx encountered in this study were frequently close to or below the
detection limit of the unit and are thus not reported.
2.6 Data acquisition, water evaporated, fuel burned and burn rate
The concentrations of the gaseous pollutants, light obscuration, orifice plate pressure drop and mass
(stove, fuel, pot and water, combined) were recorded digitally at 10 second intervals throughout the
test. Additionally, at the start of the test and at the end of each phase the pot was briefly lifted off the
stove. From these mass records, and with wood and char treated as discussed in Section 2.2, the
separate masses of wood supplied, char (and where applicable, wood) remaining, and water
evaporated could be determined for each phase.
In a number of tests the pot was briefly lifted off the stove every two to three minutes throughout
both phases. This provided records versus time of water mass, and hence fuel mass, and thus the burn
rate. It was found that the mass of water decreased essentially linearly with time during the
simmering phase (as expected) and nearly linearly during the heating-up phase. Furthermore, the
mass of water evaporated during the heating-up phase was a small fraction of the mass of fuel burned.
Thus for those tests in which total mass evaporated only was measured, a linear change in mass was
assumed for both phases. Thus the instantaneous burn rate could be estimated for these cases also.
2.7 Fuel and fuelling
The wood used for testing was Eucalyptus grandis, a non-indigenous plantation wood. The wood is
not used in rural areas, but is considered a good barbecue fuel by urban dwellers. It is a hardwood, as
are the types of wood preferred by rural users. Its moisture content was 10.7(±1.3)%.
The effect of type of wood on stove performance was studied in a separate set of experiments. The
improved open fire and the one-pot metal stove were used to compare Eucalyptus grandis and Pinus
patula a softwood considered too fast-burning for satisfactory cooking. There was no difference (at the
95% confidence level) in the efficiency and emissions results for the two types of wood. This would
seem to indicate that wood type is not a critical factor in this study. (The calorific values of the woods
were obtained from a database of the Forestek Division of the South African Council for Scientific and
Industrial Research; the values were 19.69 MJ kg-1 for E. grandis and 20.90 MJ kg-1 for P. patula. The
calorific value of char was taken as 28.0 MJ kg-1, the value given by Baldwin6.)
Pieces of wood chopped to a ‘diameter’ of less than 15 mm (capable of passing through a ring of 15
mm internal diameter) were used as kindling. Pieces of diameter 30 to 60 mm were used as main fuel.
All pieces were 100 mm in length. The initial fuel charge consisted of 0.03 kg of kindling and
approximately 0.12 kg of main fuel for the four smaller devices, and 0.75 kg for the larger two-pot
166
metal stove. The open fires were fed radially and semi-continuously, following traditional practice.
The stoves were fed intermittently, generally once during the heating-up phase and one to three times
during the simmering phase.
3 Results and Discussion
It was found that for the one-pot metal stove, TSP, CO, and SO2 follow similar emission patterns
during a test (see Figure 2). Thus, if the ratios of the instantaneous concentrations of TSP and of SO2
to that of CO were to be calculated they would approximate to constants. In the terminology of
atmospheric chemistry18, the emission ratios of TSP and SO2 to CO, are essentially constant over a
test. Such behaviour has been noted by Lobert et al18 and Helas (personal communication, see also19)
for TSP, CO and various hydrocarbon products of incomplete combustion emitted from real and
simulated savannah fires. This finding has important implications for the taking of ‘grab samples’ of
fire plumes and in the estimation of the emissions of trace gases affecting atmospheric chemistry and
climate19. It should therefore be noted that considerably more variable emission ratios than those for
the one-pot metal stove are exhibited by the two other stoves of this study, and that this variability is
even more marked in the case of the open fires. Figure 3 shows the emission patterns of the improved
open fire; the SO2/CO emission ratio, for example, varies with time from 0.17 to 1.2; if the emission
ratio were to be based on mean concentrations, or on cumulative masses emitted, its value would
depend on the duration of the test. Care must therefore be exercised when using emission ratios in
the study of stoves and cooking fires.
600
Carbon monoxide
35
Sulphur dioxide
30
25
400
20
300
15
200
10
100
500
5
0
0
0
500
1000
1500
2000
2500
3000
Time (seconds)
Figure 2 Instantaneous concentrations of CO, TSP and SO2, one pot stove
167
The TSP data shown in Figure 3 have the appearance of including a superimposed drift to higher
values with time. It was initially thought that this was due to condensation of volatiles on the optical
surfaces during a test. Subsequent checks, however, showed that such ‘window contamination’
amounted at most to 1% obscuration over a test. Further, the drift-like effect was absent in numerous
tests, see for example Figure 2.
250
9
Carbon monoxide
Sulphur dioxide
8
7
6
150
5
4
100
3
200
2
50
1
0
0
0
500
1000
1500
2000
2500
3000
Time (seconds)
Figure 3 Instantaneous concentrations of CO, TSP and SO2, improved open fire
The TSP emission patterns for the traditional open fire were very similar to those of the improved
open fire. These fires therefore become increasingly smoky with time. (In absolute terms, however,
they are low-smoke-emitting devices − compare the TSP concentration scales in Figures 2 and 3.) A
possible explanation for this might be the following: The fires were fed semi-continuously; they thus
always contained ‘new’ wood which means that there was always some smoke; the wood was fed
radially inwards; this caused accumulations of ash in the combustion space in the middle of the fires,
leading to the progressive reduction of air supply and thus to increased smoking. By the same
argument, CO, also a product of incomplete combustion, should display a trend to higher
concentrations with time. This trend is clearly discernible in Figure 3, superimposed over emission
peaks somewhat sharper than those for TSP. It may well be that the dying away of SO2 emissions in
the later stages of this test is attributable to the same reduction in combustion air that caused the
increased emissions of TSP and of CO. The traditional open fire displayed similar CO and SO2
emission patterns.
The above behaviour is very different from that exhibited by the one-pot metal stove (Figure 2) for
which the products of incomplete and complete combustion − CO and TSP, and SO2 − respectively,
varied ‘in phase’, as already noted. (In phase emissions of CO and SO2 have also been reported for a
168
residential coal stove20.) Figure 4 shows the burn rate of the one-pot metal stove for the same test as
that of Figure 2. The burn rate varied very sharply with time (for example by a factor of 15 between
1000 and 1500 seconds) and it seems that this masked any changes in emission factor (mass pollutant
emitted per mass fuel burned) that occurred during the test. (The three main peaks relate to the
addition of fuel, one during the heating-up phase and two during the simmering phase.) The open
fires on the other hand were operated more closely to steady state; they were thus less burn-ratedominated and this allowed the changes in emission factor discussed above to be detected. The burn
rate effect was, however, not absent; thus the simultaneous peaks in CO and SO2 at 1000 and 2000
seconds in Figure 3 correspond to peaks in burn rate.
8E-4
7E-4
Burn rate (kg/s)
6E-4
5E-4
4E-4
3E-4
2E-4
1E-4
0E+0
0
500
1000
1500
2000
2500
3000
Time (seconds)
Figure 4 Instantaneous burn rate, one pot metal stove
The presentation of the main results starts with efficiencies. Figure 5 shows overall efficiency (over
the heating-up and the simmering phases) versus fire power for the 29 tests that were conducted.
Focusing attention initially on the one-pot devices (open data points) we note a general trend to
reduced efficiencies with increasing fire power. This was also reported by Joshi et al21 in their study of
four metal stoves fuelled with wood, crop residue or dung. It would appear that for our devices and
those of Joshi et al and for the ranges of power that were studied, the higher the power of a fire, the
more of its energy is lost to the surroundings, rather than transferred to the pot. Further, some
cooking devices are inherently more prone to losses than others. The open fire is thus doubly
penalised: It has high losses to the ground, it therefore needs to be built quite large if it is to achieve
boiling and it therefore suffers the additional size-related losses. (We should like to stress that our
open fires were sensibly operated; considerably lower efficiencies could have been achieved by building
larger fires.) The improved open fire has reduced losses to the ground and can therefore be built
169
economically small. Additionally it is self-limiting in power, the grate being able to accommodate no
more than a finite amount of wood at a time. Compared with the improved open fire the one-pot
metal stove, being insulated, has reduced losses to the surroundings, but it incurs the added loss (as
do all stoves) of raising its own mass to operating temperature. The stove does not, as might perhaps
have been expected, outperform the improved open fire.
30
25
Efficiency (%)
20
15
Open fire
Improved open fire
1 pot metal
10
2 pot ceramic
2 pot metal
5
0
0
1
2
3
4
5
6
Power (kw)
Figure 5 Efficiency and fire power
Turning now to the two-pot stoves (solid data points) we note that they also obey the ‘economy of
smallness’ rule noted above. The data lie roughly parallel to those for the one-pot devices, but
displaced to slightly higher efficiency. This would appear to be due to the energy recuperation by the
second pot.
The efficiencies of the improved open fire and of our stoves are slightly higher than those of Joshi et
al21 at the same power and with wood-fuelling. However, Joshi et al extended their measurements to
powers as low as 2 kW and achieved efficiencies of 30 and 37% with their ‘TARA’ and ‘CP’ stoves
respectively. Our devices were difficult or impossible to operate at such low powers.
The averages of the efficiencies shown in Figure 5 are given in the first row of data in Table 1.
Alongside each entry and in brackets is given the standard deviation, and beneath this the range of
data for the (generally) six tests per cooking device. To the right of the dotted line in each cell is given
a rating on a scale of digits where 1 rates highest; where two (or more) devices have the same rating,
170
their differences in efficiency (or other performance data) are not statistically significant at the 90%
confidence level.
Table 1 Performance characteristics of the cooking devices
Improved open
fire (6)
1-pot metal
stove (6)
2-pot ceramic
stove (6)
2-pot metal
stove (5)
Stove type (no. of tests)
Open fire (6)
Efficiency, % (st. dev.)
14 (2.1)
11.6–16.8
2
21 (1.3)
19.7–23.1
1
20 (3.1)
16.0–24.7
1
24 (3.1)
18.1–26.2
1
22 (3.0)
18.2–25.9
1
Total CO per test, g
15 (2.1)
12.9–18.0
1
12 (2.2)
10.0–15.5
1
43 (9.8)
32.7–54.4
3
28 (6.1)
20.1–37.5
2
30 (11)
17.5–41.1
2
CO emission factor, g kg-1
19 (3.7)
13.3–23.4
1
19 (3.7)
15.4–25.0
1
66 (15.2)
43.6–80.5
3
38 (9.9)
23.4–52.8
2
22 (8.0)
12.0–31.6
1
Total SO2 per test, g
0.058 (0.025)
0.082 (0.034)
0.694 (0.114)
1
1
0.03–0.09
0.05–0.13
0.50–0.80
3
0.218 (0.062)
0.14–0.33
2
0.303 (0.113)
2
0.17–0.42
Total TSP per test, g
0.891 (0.160)
0.523 (0.198)
0.976 (0.278)
2
1
0.65–1.08
0.28–0.78
0.46–1.12
2
0.492 (0.122)
0.34–0.61
1
1.595 (0.306)
3
1.22–1.94
Time to reach boil, min
22 (3)
18–25
2
22 (3)
17–27
2
16 (2)
13–19
1
22 (2)
19–25
2
32 (5)
26–39
3
CO to CO2 mol ratio, (%)
1.30 (0.16)
1.08–1.56
1
1.02 (0.12)
0.85–1.17
1
5.25 (1.39)
3.64–7.60
3
1.83 (0.32)
1.48–2.42
2
1.00 (0.62)
0.31–1.88
1
The fire built on a grate with an efficiency of 21% is a substantial improvement on the open fire at
14% (the corresponding reduction in fuel consumption is 32%) and it competes successfully with the
one-pot metal stove at 20%. The two-pot stoves had slightly higher efficiencies, but the differences
between these figures and that for the improved open fire were not significant at 90% confidence.
In presenting results on emissions we prefer the use the total mass of pollutant emitted per test
(cooking task). This mass is directly related to human exposure. Emission factors, because of their
denominator term (mass of fuel burned) include the effects of efficiency. (Emission factors for CO are
shown in Table 1 for purpose of comparison.) Joshi et al21, 22 also prefer the use of mass emitted per
task, but generally report both it and emission factor. However, they define the task not as the
simulated cooking cycle of the WBT, but the transfer of a fixed, and much smaller, amount of energy
− 879 kJ − to the pot.
Figure 6 shows efficiency as the abscissa and total CO emissions as the ordinate for the 29 tests under
discussion. The figure is not intended as a ‘plot’ in the functional relationship sense, but as a
171
‘performance map’ on which the top left-hand corner is the region of good performance and the
bottom right hand corner the region of poor performance.
30
25
Efficiency (%)
20
15
Open fire
Improved open fire
10
1 pot metal
2 pot ceramic
5
2 pot metal
0
0
10
20
30
40
50
60
Total Emissions (g)
Figure 6 Efficiency and total CO emissions
Clearly the improved open fire is a good overall performer, with efficiencies not significantly different
from that of the stoves and emissions significantly lower, see also Table 1. Its CO emissions are also
marginally lower than those of the open fire, but not statistically so at 90% confidence. (The use of
emission factor eliminates the difference between the two fires, the less efficient device, the
traditional open fire, being unrealistically favoured.) Table 1 shows the stoves to have had CO
emissions (mass per task) higher than those of the fires by factors of 2 to 3, with the one-pot metal
stove the highest emitter. CO emission factors ranged from 19 to 66 g kg-1; this is in close agreement
with Joshi et al21 whose mean values were 17 to 62 g kg-1. Also shown in Table 1 is the CO to CO2 mol
ratio (ratio of total moles emitted during test). It is included partly because it is of interest to
atmospheric chemistry19, and partly as a further indicator of incompleteness of combustion. The ratio
is by far the highest for the one-pot metal stove. It would appear that the incompleteness of
combustion was due not to a shortage of primary air, but rather due to quenching associated with the
very narrow gap between the top of the stove and the bottom of the pot − there was a visible reduction
in smoke emissions when the pot was briefly lifted off the stove.
The SO2 emissions were lowest for the open fire and the improved open fire; the stoves were
higher-emitting than the (averaged) fires by factors of 3 to 10, with the one-pot metal stove again the
worst emitter. Emissions of TSP were lowest for the improved open fire and the two-pot ceramic
172
stove; the other devices were higher emitting by factors of 1.5 to 3. It should be noted that the health
hazard of the two-pot metal stove is reduced by the presence of the chimney which removes the
emissions from the immediate vicinity of the cooking site.
Joshi et al21 observe increasing emission factors for CO and TSP with increasing efficiency, but
observe no such correlation for emission mass per task. The correlation is also absent in the present
study (see Figure 6). The positive correlation between emission factor and efficiency would thus seem
to be due to the fact that the two quantities have denominators that are proportional to each other −
mass of fuel burned, and energy content of fuel burned. This, together with the (real) negative
correlation between efficiency and power, explains the negative correlation between emission factors
and power observed by Joshi et al21, and the absence of correlation between emission mass and power
observed in the present study.
Figure 6 shows the performance points of the open fires to be considerably less scattered than those of
the stoves. Data of the Aprovecho Institute23 similarly shows open fires to behave more consistently
than enclosed (‘Louga’) stoves. We believe that the reason for this is that open fires are tended
near-continuously, they are visible and allow immediate intervention in the event of any irregular or
undesired behaviour. Stoves are fed intermittently and operate in a highly transient manner. This
favours irregularities of combustion which, because the devices are closed, go uncorrected for
extended periods.
Taking a final and broad look at the ratings shown in Table 1 we note the following: The improved
open fire rates first, or jointly first, in all categories except time to reach boiling. The one-pot metal
stove rates first in time to reach boiling (this would endear it to users), jointly first in efficiency, and
last with respect to emissions (which, smoke excepted, are invisible). Clearly, efficiencies and
emissions need to be determined before a stove design is disseminated. The traditional open fire is not
the disaster it is generally held to be; while less efficient than the other devices it rates second in
overall emissions. The remaining two stoves rate joint first in efficiency, but are overall higheremitting than the traditional open fire.
4 Summary and Conclusions
For the one-pot metal stove the emission ratios TSP/CO and SO2/CO were approximately constant
over the duration of a test. The behaviour of the other two stoves was more variable, and for the open
fires emission ratios changed with time by factors of up to 7. Care must therefore be taken when
using emission ratios in the context of biomass-burning stoves and fires. Care is also required in
dealing with grab samples (for subsequent analysis) of the flue gases of such devices.
The one-pot metal stove exhibited very sharp variations in burn rare. It seems that these
overshadowed any changes in emission factor with time, thus leading to essentially constant emission
173
ratios. The open fires were semi-continuously fed and operated more closely to steady state; this
permitted additional factors influencing emissions to be detected.
The average emissions of TSP were lowest for the improved open fire and the two-pot ceramic stove;
the other devices were higher-emitting by factors of up to 3. The emissions of CO and SO2 were lowest
for the two open fires; the stoves were higher emitting by factors of up to 3 for CO and up to 10 for
SO2. Overall, the improved open fire was the lowest-emitting device and the commercial one-pot metal
stove the highest-emitting. It is thus important that new stove designs be tested for emissions before
being disseminated.
Mean efficiencies were 14% for the traditional open fire, 21% for the improved open fire and 20 to
24% for the stoves, with no statistically significant difference (at 90% confidence) between the latter
four devices.
Acknowledgements
The authors offer their thanks to the following: The Director and staff, particularly Mr. E-J. P.
Harvey, of the Wits Rural Facility (WRF) for their support and for facilitating field work related to
this study; Dr D. I. Banks, previously of the WRF, for design input, student supervision, friendship,
advice and criticism; Dr H. Annegarn and Mrs M. Kneen of Annegarn Environmental Research for
help with the calibration of the smoke meter; Dr G. Helas of the Max Planck Institute for Chemistry,
Mainz, Germany, for advice and helpful discussions; the Foundation for Research Development (FRD)
and the University for financial assistance.
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Emissions and Efficiencies of Rural Wood

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