Faecal Pollution in Laucala Bay

Transcription

Postgraduate Research in Environmental Sciences
A Benthic and Pelagic Analysis
ALVIN CHANDRA
DEPARTMENT OF ENVIRONMENTAL SCIENCES
UNIVERSITY OF THE SOUTH PACIFIC (USP)
SUVA 2005
…the sea is more than an
amenity. It is a treasure. It
offers a necessity of life that
must be rationed among those
who have power over it.
-Oliver Wendell Holmes, 1931
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ABSTRACT
Faecal coliform bacteria are commonly used as enteric pathogen indicators. The increase in faecal
coliform bacteria has attracted much interest in view of its public health significance in Laucala Bay,
Suva, Fiji Islands. In this research, pelagic and benthic faecal coliform, water quality and nutrient
levels were analysed from twenty independent stations on a fortnightly basis, across Laucala Bay
form the 9th of March to the 6th of April, 2005. It was spatially explicit that high contamination of
water and well as the sediments, exists near land mass and stepwise multiple regression indicates
that distance measure is a strong influence on faecal coliform levels in the bay. Comparison of data
set with other historic data sets suggests an increase in faecal contamination over the years. In
conclusion, this research recommends integrated monitoring schemes to reduce not only faecal
pollution but other sources of contamination.
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TABLE OF CONTENTS
1.0
2.0
3.0
4.0
INTRODUCTION
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1.1 Background and scope….
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1.2 Research objectives
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1.3 Path diagram
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METHODOLOGY
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2.1 Sample collection, preparation and processing
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2.2 Faecal coliform analysis of water samples ….
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2.3 Faecal coliform analysis of sediment samples
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2.4 Confirmation of faecal coliform in sediment samples ….
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2.5 Nitrate analysis
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2.6 Statistical analysis of water quality data
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RESULT AND ANALYSIS
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3.1 Effect of salinity
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3.2 Effect of water temperature
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3.3 Effect of dissolved oxygen
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3.4 Effect of turbity
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3.5 Pelagic and benthic faecal coliform levels ….
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3.6 Correlation of distance form coastline with faecal coliform levels
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DISCUSSION
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4.1 The general water quality of Laucala Bay lagoon
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4.2 Faecal coliform contamination
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4.3 Implications of faecal coliform contamination
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4.4 Research limitations
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5.0
INTEGRATED POLLUTION MANAGEMNT PLAN….
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6.0
CONCLUSION AND RECOMMENDATIONS…
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7.0
BIBLIOGRAPHY….
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APPENDICES
Appendix A: Data set form field sampling
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Appendix C: Figure 2-Frequency distribution graph of measured variables
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Appendix B: Research sampling station locations
Appendix D: Table1-Tables showing highest, lowest and mean values of variables
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Appendix E: Figure 3-Spatial maps of tested parameters in Laucala Bay ….
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Appendix F: Figure 4-Scatter plots showing correlations of environmental variables
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Appendix G: Correlations of pelagic faecal coliform levels with distance ….
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Appendix H: Correlations of benthic faecal coliform levels with distance….
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Chapter 1:
Introduction and Background
1.1 Background and Scope of Study
Faecal pollution decreases water quality in many marine and freshwater ecosystems. This pollution can
originate form point sources, such as industrial and municipal effluents, or form non-point sources, such as
land runoff and septic tank seepage that disperse over wide areas (Parveen et al., 1997)
The Laucala Bay is a unique lagoonal environment to study both point sources and non-point sources of faecal
pollution. Located in southeast Viti Levu, the major island of the Fiji group, at about 180.10S and 1700.30 E in
the capital city of Suva, it represents one of the major commercial centres of the small island territories in the
South Pacific (Corless, 1995).
Laucala Bay lies between the Suva Peninsula on the west and the Rewa River delta on the east. The bay is
harboured by unique system of coral reefs to the south and is connected on its west side to Suva Harbour. The
ecosystem consists of reefs, mangrove and mudflat habitats, most of which are submerged by a shallow layer
of seawater that enters the bay twice daily around high tide (Seeto, 1999). Consequently, the reefs restrict
water exchange between Suva Harbour and the open ocean thus inhibiting the dispersal of pollutants.
The main source of freshwater into Laucala Bay is the Vunidawa River, which is a distributary of the Rewa River.
Other freshwater sources come from the Vatuwaqa, Nasinu and Samabula Rivers. Laucala Bay at high tide has a
surface area of 4500 ha and a low tide area of 3900 ha (Cladwell Connell Engineers, 1982).
The rapid increase in population, together with the associated expansion of industrial sites, port activity and
waste disposal have led to considerable problems of management of the nearby coastal zone. Both the Kinoya
and Raiwaqa plant effluents ultimately move into Laucala Bay and greater Suva shores. Others sources rural
non-point sources of pollution is also discharged into the river course and coastal waters without treatment.
The sewage effluent is discharged through 0.6 meters diameter fibreglasses on extending about 800m into
Laucala Bay and terminates in a 9m long diffuse section (Seeto;, 1999). Concern over the environmental effects
of continued shoreline discharge of milliscreened and untreated sewage into the Laucala Bay waters has
become a major environmental and political issue over the years.
Many of the previous investigations in Laucala Bay lagoon involve the study of the effect of sewage on water
chemistry and biology of the bay water. However, less attention has been paid to contaminating elements in
the sediments as a consequence of the sewage input form the Kinoya outfall and catchment rivers. This
research attempts to study the various factors which influence the faecal pollution in pelagic water and benthic
sediments, and aims to identify potential variables causing the pollution. At large, scientific data is of no use if
it is not communicated or utilised. Therefore, an integrated pollution management plan is also proposed in the
research to monitor and combat faecal pollution in the Laucala Bay.
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1.2 Objectives of the Research
The aim of this study is to analyse the factors causing faecal contamination in the Laucala Bay lagoon. To
develop a critical understanding of the factors causing the contamination, this research has the following two
objectives:
1.
To investigate relationship between distance to Kinoya sewage treatment plant outfall, distance form
nearest rivers, distance form coastline, physical water characteristics and faecal coliform concentration in
Laucala Bay pelagic waters from 9th March to 6th April 2005 on a fortnightly basis.
2.
To correlate pelagic faecal coliform concentrations, distance to Kinoya Sewage Treatment Plant Outfall,
distance form nearest rivers, distance form coastline, and with their relative levels in benthic sediment
accumulations.
1.3 Path Diagram
In the path diagram Figure 1, the environmental variables are being illustrated. The positive and negative signs
indicate the possible effects each of the variables poses on the other. The single-headed arrow denotes
causality between the environmental variables.
Figure 1: Path diagram for the environmental factors causing faecal contamination and relationships between
them of in the Laucala Bay.
PHYSICAL WATER
CHARACTERISTICS
DISTANCE FROM OUTFALL
Distance form Coastline
Salinity, Temperature, Dissolved
Oxygen, Nutrient (Nitrate), Turbity
+/WEEKS
Distance form Major Rivers
+/+/-
Pelagic Faecal coliform
concentration
(Water)
+/+/-
BENTHIC FAECAL
COLIFORM
CONCENTRATIONS
(SEDIMENT)
The environmental variables used in Figure 1 are used in the research to explore the plausible sets of casual
relations between them. This research thus analyses the correlations between the observed variables to obtain
estimates of the path coefficients. The research also uses the environmental variables in the path analysis to
perform statistical tests to find out whether the coefficients of the different variables are significantly different.
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Chapter 2:
Methodology
2.1
Sample collection, preparation and processing
Sampling was conducted across twenty independent stations (sites 1-20)on a fortnightly basis across Laucala
Bay exhibiting different degrees of pollution from the 9th of March to the 6th of April, 2005 (Appendix A: Figures
1a, 1b and 1c). All water sampling was carried during the outgoing tides.
Water samples for faecal coliform and nitrate analysis were collected in Niskin bottles from the sub-surface of
water at a constant depth of 50cm. Water samples for faecal coliform analysis were transferred and stored in
autoclaved glass bottles, while water samples for nitrate analysis were stored in acid washed polythene bottles.
To test for water quality parameters, water sample from each station was poured from the Niskin bottle into a
beaker, and the dissolved oxygen, salinity and temperature were measured using the YSI 85 electronic meter.
The water samples were then transferred into eskies packed with ice in field, to minimise the potential for
volatisation or biodegradation.
Turbity of the water for each station was measured by lowering a secchi disk in the water column and the
length at which the disk disappeared was measured.
th
Sediment samples were collected on the 9 of March 2005, using a sediment grab form nineteen stations
across the Laucala Bay. Depth at station 13 exceeded the length of sediment grab, therefore a sediment grab
could not be used. Sediments were transferred into sterile polythene bags and the samples were frozen at 40
5 C for analysis.
Water samples for faecal coliform analysis was processed within 4 hours of collection. 1ml of the original
seawater samples were transferred using 1ml autoclaved pipettes into 99ml of demineralised/distilled water
-2
sterile Duran Schott bottles (which was pre-autoclaved), forming a dilution of 10 . The diluted volumes were
then filtered through 0.45µm membrane filters in autoclaved membrane filter assembly. Nitrate analyte were
0
first filtered through bitman filters, then preserved with 2ml concentrated sulphuric acid and stored at 4 C for
analysis.
2.2
Faecal coliform analysis of water samples
Faecal coliform analysis of water samples were carried out using Membrane Filtration Method, in accordance
to standards of the United States Environment Protection Agency and World Health Organisation (WHO 2003).
The Membrane Filtration Method is a rapid, economical and more precise method for a research of this nature.
2.21
Preparation of M-FC agar media
52 grams of M-FC agar was dissolved into 1litre of distilled water and the mixture was heated in microwave
oven to dissolve completely. After heating, 10ml of 1% solution of Rosolic Acid in 0.2% of NaOH was added to
the M-FC agar solution. The mixture was then heated for another ten minutes with frequent stirring. Later the
0
mixture was cooled to 50 C using a water bath. The prepared M-FC media was then poured into twenty four
Petri dishes in a Laminar Flow Chamber (to reduce any bacterial contamination).
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2.22
Enumeration of water samples
Standard microbiology laboratory procedures were followed to enumerate bacterial water samples (see
APHA/AWWA/WPCF 1999) . Inside the Laminar Flow Chamber, the working bench was wiped with ethanol.
Using sterilised tweezers, in flame heated environment, the filtered 0.45µm membrane filter papers were
enumerated onto M-FC agar media. The enumerated media was then packaged into a sterile plastic bag and
0
incubated for 24 hours into heat oven at 39 C.
Peptone and yeast extract in M-FC agar serve as nutritious source and bile salts were added to inhibit growth of
Gram-positive flora. Lactose in the media was fermented by faecal coliforms at the temperature to form blue
colonies in the medium (agar base plus rosolic acid). The blue colonies were identified as Escherichia coli
colonies, which were counted after 24 hours of incubation.
2.3
Faecal coliform analysis of benthic sediment samples
The sediment samples were analysed using the Most Probable Number (MPN) technique, which is more timeconsuming but efficient then the Membrane Filtration (MF) Method.
2.31
Preparation of sediment dilutions
Due to the large amount of sediment samples, it was necessary to prepare sediment dilutions in order to
achieve more precise results. 1gram of the sediment samples were weighed and transferred using sterilised
spatula into pre-autoclaved 99ml of demineralised/distilled water contained into sterile Duran Schott bottles.
2.32
Preparation of double and single strength MacConkey’s broth
39.9 grams of the MacConkey- Bouillon granules was weighed and transferred into 570ml of distilled water.
The constituents were mixed well in distilled water, till all of the MacConkey- Bouillon granules were diluted.
This mixture represented double strength formula of the MacConkey broth. 10mls of these were transferred
into 57 sterile McCartney bottles using sterile 10ml pipettes.
The above steps were further repeated but this time with 39.9 grams of MacConkey- Bouillon granules was
dissolved into 1140ml of distilled water. This mixture represented double strength formula of the MacConkey
broth. 10ml of this single strength solution was transferred into one hundred and fourteen McCartney bottles
using sterile 10ml pipettes.
Thus for each of the nineteen sediment samples, three double strength 10ml and six single strength 10ml
MacConkey’s broth was packaged into sterile McCartney bottles. Later, each of the one hundred and seventyone McCartney bottles (containing MacConkey’s broth) was packaged with single Dhruhm tubes (fermentation
tubes).
The McCartney bottles (containing MacConkey’s broth), together with 10ml, 1ml and 0.1ml pipettes were
autoclaved for half an hour at 1210C.
2.33
Enumeration of sediment dilutions into MacConkey’s broth
Each of the sediment dilutions was enumerated into the sterile MacConkey’s broth in the Laminar Flow
Chamber, near to Bunsen flame to maintain sterility. Firstly, 10ml of the sediment dilutions for each of the
stations were transferred using sterile 10ml pipettes into three double-strength sterile MacConkey’s broth.
Then 1ml of each of the sediment dilutions were transferred into three single-strength sterile MacConkey’s
broth using sterile 1ml pipettes. Similarly, 0.1ml sediment dilutions were enumerated into three single-strength
sterile MacConkey’s broth using sterile 0.1ml pipettes. Therefore for each sediment dilution from each of the
nineteen stations, three 10ml double strength enumerations and three 1ml and three 0.1ml single strength
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0
enumerations were prepared. The one hundred and seventy-one enumerates were then incubated at 37 C for
twenty four to forty-eight hours, and were checked for gas production in the fermentation tubes periodically
after 24 hours of incubation (Babinchak et al., 1977; Hata, 2005: pers. comm.).
2.34
Checking for MPN values
MPN values as indicated in the MPN chart confirm the number of positive gas producers in each of the bottles.
The numbers reflect the coliform levels in the sediment samples. Thus, the number of positive gas producers
for each of the bottles were recorded and compared with the MPN chard to produce the MPN index for each
sediment sample.
2.4
Confirmation of faecal coliform in sediment samples
To confirm that the sediment samples which showed positive gas production in the MacConkey’s broth, had
faecal coliform content, tests were carried out with Brila broth (Brilliant-Green Bile Lactose broth). Should
there be a colour change form brilliant green to light green of the enumerated positive gas producers in
MacConkey’s broth, then indication of faecal coliform was confirmed in the sediment samples.
2.41
Preparation of Brila Broth (Brilliant-Green Bile Lactose broth)
Since one hundred bottles showed positive gas production in double and single strength MacConkey’s broth
media, a total of one hundred bottles of Brila broth was prepared.
40grams of Brilliant-Green Bile Lactose broth granules was suspended into 1 litre of distilled water. 10mls of
the Brila broth was transferred consecutively into one hundred McCartney bottles using sterile 10ml pipettes.
Each of the McCartney bottles was fitted with fermentation tubes and autoclaved for half an hour at 1210C.
2.42
Enumeration of positive MacConkey’s broth into Brila Broth
Using a sterile enumerating loop, each of the positive MacConkey’s broth samples were enumerated into the
sterile Brila broth samples. The enumerated Brila samples were then incubated at 370C for twenty four hours
and checked for gas production.
2.5
Nitrate analysis of palegic water samples
The nitrate content of the water samples were analysed by the Flow Injection Analysis (FIA) as detailed by
Diamond (1999), Lachat Instruments, Wisconsin.
2.51
Preparation of reagents
Reagent 1-Ammonium chloride buffer: In a fume hood, 500 ml of deionised water was added to a 1 litre
volumetric flask, together with 105ml of concentrated hydrochloric acid (HCl) and 95ml ammonium hydroxide
(NH4OH) solution. 1g of disodium ethylenediamine tetra-acetic acid dehydrate (Na2EDTA.2H2O) was added to
the flask and the solutes were diluted to the mark and inverted to mix. The pH was adjusted to 8.5 with
hydrochloric acid solution and the reagent was later frozen till later use.
Reagent 2- Sulfanilamide colour reagent: To a 1 litre volumetric flask, 60ml of deionised water was added.
Then, 100ml of 85% of phosphoric acid (H3PO4), 40g of sulphanilamide and 1.0g of N-(1-napthyl)ethylenediamine dihydrocholride (NED) was added. The mixture was shook to wet and was then stirred for
thirty minutes to dissolve. The mixture was diluted to mark with distilled water and inverted to mix. The
reagent was stored in a dark bottle and frozen until its use in the Flow Injection Analysis (FIA).
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2.52
Preparation of standards
The standards and the working standard solutions were prepared on the day the samples were to be analysed
in FIA machine.
Standard 1: Stock Standard 5.00mM: In a 250ml volumetric flask, 0.126 grams of potassium nitrate (KNO3)
0
dried at 60 C for 1 hour was diluted in 200ml of deionised water. The solution was diluted to mark and inverted
to mix.
Standard 2: Working Stock Standard 50µM: In a 100ml volumetric flask, 1ml of the Stock Standard (Standard 1)
was transferred and diluted to mark with deionised water. The flask was inverted to mix.
In addition 50µM working standard, the following working standards were prepared using standard 2 solutions:
Working Standard (Prepared Daily)
Concentartion (µM)
Volume (ml) of working stock standard 2
diluted to 250 ml with deionised water
2.53
A
B
C
D
E
0.00
5.00
10.00
15.00
20.00
0
25
50
75
100
Analysing water samples using the Flow Injection Analysis (FIA)
The manifold of the machine was setup and data system with the parameters was entered. Deionised water
was pumped through all the reagent lines for a good half an hour and the FIA machine was checked for leaks
and smooth flow. The machine was switched to reagents and the system was allowed to equilibrate until a
stable baseline was achieved.
The standards and samples were placed in test-tubes in the auto sampler. Information on correlation of sample
codes to the test-tube rack codes, concentration (“known” for standards and “unknown” for samples) and
replicates was entered into the data system.
The FIA machine was then calibrated by injecting the standards. Thus the data system was able to associate the
concentrations with the instrument responses for each standard. The entire 40 (replicate for each station)
samples were run in the instrument and nitrate concentrations for each of the stations were printed out from
the computer in mg/L.
2.6
Statistical analysis of water quality data
FC counts of pelagic and benthic stations were log-transformed to achieve normal distribution. Data were
analysed for mean, range and standard deviation by plotting frequency distribution graphs for each variable.
The relationship between faecal coliform and other environmental variables were analysed by linear
regressions (Aslan-Yilmaz et al., 2004). To deduce significance and effect of each parameter in relation to
pelagic and benthic sediment faecal coliform levels, stepwise multiple linear regressions were carried out
(Linton, 2005: pers. com.).
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Chapter 3:
Result and Analysis
The raw data collected over the three consecutive fortnightly water sampling period was recorded and
tabulated into relevant columns (Appendix B).
Seeto (1992) identifies the Raiwaqa and Kinoya Sewage Treatment Plants and septic tank seepage form Suva as
the major contributors of faecal pollution in Laucala Bay and Suva Harbour. In addition to the anthropogenic
factors, natural factors such as temperature, salinity, nutrient levels, dissolved oxygen and turbity have all been
reported to be the primary factors affecting the numbers of coliform bacteria in the marine environment (Solic
and Krstulovic, 1992). Therefore was critical to examine the effects of each parameter with the pelagic faecal
coliform concentrations to determine the most probable factor faecal pollution.
3.1
Effect of salinity
A higher frequency of salinity occurred between 25ppt-30ppt (Figure 2.1 and Table 1.1). By plotting the salinity
levels over the three sampling periods, it is obvious that relative salinity levels are higher offshore than in the
coastal area of the bay (Figure 3.1). The scatter plot shows that an inverse relationship between faecal coliform
2
2
and salinity exists (R =0.004) (Figure 4.2). However the low R value depicts that data is insufficient to depict a
more significant relationship. A multiple linear regression shows that no significant correlation exists and
during the course of study, salinity had no effect on pelagic faecal coliform levels over the three fortnightly
sampling (p=0.649; p>0.05).
3.2
Effect of water temperature
0
0
Water temperature of sub-surface (pelagic) waters ranged between 28.2 C and 30.95 C (Table 1.2). The
temperature range of the Laucala Bay waters showed a normal distribution, depicting very low changes in the
2
bay waters (Figure 2.2). An increasing exponential relationship exists between water temperatures (R =0.012)
(Figure 4.3). A multiple linear regression of temperature and pelagic faecal coliform levels depicts a nonsignificant effect of temperature on pelagic faecal coliform levels (p=0.403; p>0.05).
3.3
Effect of dissolved oxygen
Frequency of dissolved oxygen levels ranged form 4.17mg/L to 32.1mg/L (Figure 2.3 and Table 1.3). It was
obvious form the field data of dissolved oxygen levels that such a high variation in values in one sampling event
th
(6 April, 2005) is unrealistic and they reflect the poor calibration of the YSI 85 electronic meter, which was
th
used to measure the dissolved oxygen levels. Therefore field data for 6 April, 2005 was excluded from the
statistical analysis.
Dissolved oxygen levels in the water were higher in value as moved away from the coastal waters (Figure 3.3).
It is also obvious form the plot of dissolved oxygen levels that higher up in the bay, near the Kinoya STP,
dissolved oxygen levels are comparatively lower to other stations (i.e. dissolved oxygen levels decreases as
th
moved towards the stations located near to Kinoya STP). A scatter plot of the first two sampling events (9 and
rd
23 March, 2005) illustrates an inverse relationship between the dissolved oxygen and pelagic faecal coliform
2
levels (Figure 4.4). The low R value shows the limited sampling events and data to produce such a correlation
2
(R = 0.079). The correlation was insignificant and dissolved oxygen did not affect the pelagic faecal coliform
levels greatly, during the sampling events (p=0.719; p>0.05).
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3.4
Effect of turbity
Turbity levels ranged form 0.3 m to 2.9 m (Figure 2.4 and Table 1.4). Turbity of the water column increased as
moved form coastal waters to offshore waters (Figure 3.4). This shows that water was less turbid and clearer in
the offshore waters. With a mean of 1.73m, a normal distribution of turbity was observed over the three
sampling events (SD= 0.73). Correlation between turbity and pelagic faecal coliform levels (Figure 4.5) shows a
2
direct relationship, however data being insufficient to reflect such a correlation (R = 0.031). No significant
effect of turbity on pelagic faecal coliform levels were attributed by multiple linear correlation (p= 0.179;
p>0.05).
3.5
Pelagic and benthic faecal coliform levels
Pelagic Faecal coliform levels ranged from 600-12,200 colonies/100ml (Figure 2.5 and Table 1.5). Coastal
waters had higher faecal coliform levels and the levels decreased as moved towards offshore waters (Figure
3.5). It was also noticed that FC levels were generally higher in stations closer to the Kinoya STP.
The Brila Broth confirmatory test indicated that 95% of the sediment samples form the nineteen different
stations contained faecal coliform enteric bacteria. A similar trend was also noticed in the sediment FC levelssediment FC levels were higher in coastal waters and stations closer to Kinoya STP (Figure 3.6)). Sediment FC
levels ranged from 400-110,000 MPN/100ml (Figure 2.6 and Table 1.6). In general, the numbers of faecal
coliform at all the sampling sites were lower for seawater than their relative sediment samples.
3.6
Correlation of distances from coastline on pelagic and benthic faecal coliform levels
A correlation between pelagic faecal coliform levels to distance form Kinoya sewage treatment plant (Figure
5.3) and nearest influencing rivers showed no relationship (Figure 5.2), while correlation with distance form
coastline showed an inverse relationship (Figure 5.1). The low R2 values (however greater than other parameter
correlations) reflect the insufficient data generated through limited sampling events to produce a stronger
correlation (R2= 0.166, R2=0.017 and R2=0.119 respectively). Consequently correlation of benthic faecal
coliform levels with pelagic faecal coliform levels and distances variables, showed a direct relationship of
benthic faecal coliform levels with distances and no relationship with relative pelagic faecal coliform levels.
A stepwise linear regression of pelagic faecal coliform levels and the various distances showed that distances
form the coastline was a more significant parameter influencing faecal contamination in Laucala Bay (p=0.001,
p<0.005).
Similarly a stepwise correlation of likely influencing variables with benthic faecal coliform levels; pelagic faecal
coliform levels and distance variables (Figure 6), showed that distances form coastline and Kinoya STP, were
significant factors influencing relative benthic faecal coliform levels in sediments (p=0.005, p=0.001, where
p<0.005).
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Chapter 4:
Discussion
4.1
The general water quality of Laucala Bay
The water quality in the Laucala Bay had been greatly affected by large amounts of domestic discharges as well
as industrial inputs for decades. An ever increasing population, together with an associated increase in
industrial development, port activity and waste disposal problems have led to considerable problems.
As indicated by the water quality results, coastal areas have low dissolved oxygen, high turbity and high pelagic
and benthic sediment faecal coliform levels. Consequently, nitrate levels were seen to be generally higher in
the offshore waters then near the coastal waters. The high turbity levels indicate the high sediment load of the
coastal waters (thus low water clarity). “The clarity of water in Laucala Bay is affected by clay and fine silt
discharged naturally by the Rewa and Vatuwaqa Rivers. Deforestation and agriculture in land also contribute to
a heavier silt load. Wave actions on fine sediments in shallow waters contribute to high turbity as well” (Seeto,
1999). High turbity however restricts phytoplankton growth in the coastal waters (Mallin et. al., 1999). Clearer
water is found in deep water and so the reef side of the bay seems to be clearer. The low dissolved oxygen
content of the coastal waters is indicative of the high biological oxygen demand and organic matter
degradation (where waters were generally more turbit) (Seeto, 1999).
Nitrate levels were the highest in stations 14 and 10. This may be particularly due to the influence from the
Rewa River, which continuously brings materials as well as leached fertilisers form anthropogenic activities in
the upper river. The gradual increase in nitrate levels in stations closer to Kinoya STP and Vatuwaqa and
Samabula Rivers indicate a possible effect of them on the nitrate levels.
It can be deduced from the correlation between pelagic and benthic sediment faecal coliform levels, that the
microbial relation between seawater and sediments of Laucala Bay is possibly established by a continuous
process of precipitation and resuspention of microorganisms. However, a lack of significant correlation
between the microorganisms in both environments is explained by their different survival and accumulation
rate capabilities and need for longer term seasonal data
The significant correlations of the distance variables with the pelagic and benthic sediment faecal coliform
levels (Table 5.1 and Table 6.1) are indicative of the presence of both point source and non-point source of
pollution. From the existing limited data, it is impossible to separate out the effect of distance from rivers,
coastlines and Kinoya Sewage Treatment Plant, and thus conclude the most significant distance measure
affecting the pollution source. However, no other parameters are as significant as the distances. It is therefore
evident that distance form coastline and nearest influencing rivers are the most significant parameters
affecting faecal coliform pollution in Laucala Bay.
As indicated by Seeto (1999), possible sources of faecal pollution in Laucala Bay include the present Kinoya
outfall, Kinoya creek, Vatuwaqa and Samabula Rivers. Uluituni Creek, a minor tributary of Laucala Bay, have
also shown high level of faecal coliform in the past (Cladwell Connell Engineers, 1984). Land runoff may be an
additional source of faecal contamination in Laucala Bay; form urban storm water, rural run off and Kinoya
Village (unsewered). Consequently, an investigation into upper Vatuwaqa River showed evidence of raw
sewage being pumped into the river seasonally forms the Raiwaqa Sewage Treatment Plant.
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4.2
Faecal coliform contamination
In general, the numbers of faecal coliform at all the sampling sites were lower for seawater than their relative
sediment samples. The mean levels of faecal contamination of Laucala Bay lagoon, in comparison with the
World Health Organisation Guidelines for Safe Recreational Water Environments, falls within a very poor
sanitary risk inspection category. According to the World Health Organisation guidelines (Nadiu 1991, WHO
2003), less than 350 colonies/100ml, are considered safe for marine bathing and shellfish harvesting waters.
The mean faecal coliform levels over the three sampling periods for pelagic water are 5915 colonies/100ml
(Range: 600-10,000 E. coli colonies/100ml), while that for sediments are 19,742 MPN/100ml. During week one
of pelagic faecal coliform sampling, 95% of all the stations exceeded the criteria. Consequently during the
second and third sampling spans, all the stations (100%) exceeded the criteria. Consequently, it was no surprise
that 100% of the stations analysed for sediment faecal coliform levels, exceeded the WHO marine bathing
waters criteria. Watling and Chape (1992) say faecal coliform levels are thousands of times above acceptable
levels.
Several cases of faecal pollution have been reported by researches in Laucala Bay. Caldwell Connell Engineers
(1982) reported a pelagic faecal coliform geometric mean of 200,000 colonies/100ml (Range: 30,000-1.7
Million). Barry (1988) recorded a range of 2-10,000 E.coli /100ml while Nadiu et. al (1991) reported a range of
0-5100 E.coli /100ml . Thus it is clear form the current levels that whilst the level of faecal colifom has
significantly decreased since 1982, it has increased from 1988. This can be significantly due to increased
population, greater pressure on the existing sewage treatment plants and elevated coastal activity. The Wailea
squatter settlement field visit in the upper Vatuwaqa River catchment is evident of this fact, where present
demand for human sewage disposal far exceeds the capacity of STPs to accommodate supply. Thus regular
excessive sewage buildup in the treatment plant, results in seasonal outflows and dumping into the Vatuwaqa
River tributaries.
4.3
Implications of the faecal pollution
Suva Point and Laucala Bay are significant recreational areas for Suva residents. As documented by this
research faecal coliform Escherichia coli form an important biological component of sewage sludge, and the
recreational and coastal waters as well as the sediments of Laucala Bay contain this pathogen in high numbers.
Public health decisions concerning the safety of marine waters for recreational use or for the harvesting of
shellfish continue to be based primarily upon faecal coliform enumerations. The most likely adverse health
outcome associated with exposure to faecally contaminated recreational water would be enteric illness, such
as self-limiting gastroenteritis, which may often be of short duration. “Transmission of pathogens that can
cause gastroenteritis is biologically plausible and is analogous to waterborne disease transmission in drinkingwater” (Guidelines for Safe Recreational Water Environments,).
Marine sediments of recent origin (clay and silt) act as reservoirs of pollutant bacteria and viruses entering the
marine ecosystem. Generally a large number of microorganisms discharged into marine environments settle in
the sediment bottom layer, “where a higher concentration of indicators of faecal pollution and pathogens, such
as E.coli, Salmonella and viruses, occur in comparison with the numbers of those microorganisms in
surrounding seawater” (Chen et al, 1979).
The enteric viruses tend to become associated with particulate matter and “accumulate in the upper layers of
marine sediments, thereby becoming concentrated in numbers significantly higher than in the overlaying water
column” (Wait and Sobsey, 1983). These microorganisms (bacteria and viruses) survive longer in sediments
than in the water column (Smith et al.1978). According to Goyal et al. (1956), adsorption and sedimentation
tend to remove enteric microorganisms from suspension and concentrate them in layers of sediment, where
they continue metabolically and physiologically active, thus posing a hazard to human health.
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Shellfish are filter feeders and accumulate microorganisms in the gut from surrounding water and sediments.
Ingested microorganisms are not necessarily digested or killed and may remain viable within the shellfish gut.
Growth of shellfish in polluted waters may lead to the buildup of bacteria and viruses (pathogenic to humans)
in them (Rowse and Fleet, 1982).
The importance of the study of contamination of marine sediments in swimming and shellfish-harvesting areas
of Laucala Bay is based on the fact that the microorganisms associated with the sediments may be resuspended
both by several natural processes (currents, rainwater runoff, storms and changes in salinity and organic
matter) or by man made activities (dredging or boat traffic) affecting the microbial quality of seawater and
shellfish consequently (Grimes, 1975). Continued consumption of shellfish with high coliform contents may
result in bacterial and viral diseases such as typhoid and paratyphoid infections caused by Salmonella as well as
amoebic dysentery, type A hepatitis and poliomyelitis (Seeto, 1999). Resuspension of sediment-associated
viruses by various natural and human activities may increase the risk of virus exposure form ingestion of
contaminated water or shellfish.
The concentration and persistence of enteric virus in marine sediments, including those underlying shellfishharvesting and bathing waters, indicate the need for a reliable method to isolate and quantify enteric viruses in
sediments in Laucala Bay. Sited references that evaluated the effectiveness of indicator microorganisms as
‘predators of the sanitary quality of shellfish breeding’, suggest that sediment samples may provide a more
valid, longer-term assessment of the microbiological quality of Laucala Bay lagoon than water samples (which
provide data of more ephemeral nature) (Labelle et al., 1980, El-Sayed, 1982, Martinez-Manzanares, et al,
1992).
From the palegic water contamination levels, it is possible that bacterial accumulation and enhanced survival
rates may also persist within the coral surfaces surrounding the Laucala Bay lagoonal reefs, where the
overlaying water column conditions may promote habitat of bacteria and viruses from wastewater discharges
(Lipp et al., 2002). Study conducted within corals of the Florida Keys in USA, reveals that the surface microlayer
of coral heads (mucus) accumulates microbial indicators present in wastewater (Lipp et al., 2002). Enteric
viruses were found to be concentrated in coral surface microlayers (CSM). Symbiotic association also exists
between microbes and corals and thus it is possible for native microbial community to be displaced from their
coral microhabitats due to accumulation of enteric bacteria on CSM (Lipp et al., 2002). Thus, apart from human
health risks, faecal pollution also poses threats to the health of Laucala Bay offshore coral reefs. A detailed
study on this can only reveal more direct evidence for enteric bacteria impacts on local reefs.
4.4
Research limitations
This research was limited to a short term monitoring within the research limits of postgraduate research and
thus could not be extended for a detailed longer-term monitoring of the water and sediments. Water quality
monitoring requires data form a longer time scale to analyse for any trends and validate a source of pollution.
The limited time scale restricted the number of independent stations and replicates in the field. Thus it was
also difficult with the limited data to separate the different effects of distances.
Failure of the Flow Injection Autoanalyser and its limited excess prevented accurate and timely analysis of
nitrates in water samples. A better calibration for the first field samples however allowed analysis of nitrates in
the first field sampling.
Seasonal data are needed to understand the dynamics of benthic and pelagic microbial processes in Laucala
Bay and are essential when assessing the potential biological effects of an ocean outfall discharge. Tidal
variation can also be included as one of the parameters for analysis. Concentration and dilution of suspended
coliform bacteria with changing water levels may also be operative in the Bay. A possible cause could be the
falling tide, which could transport contaminated headwater from stream and feeder creek to downstream
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sampling locations (Mallin et al., 1999). In addition, faecal coliforms which had previously settled out and had
been concentrated in sediments are probably resuspended with tidal stirring.
There are also avenues to add more probable parameters to research model (Figure 1) for separating different
factors causing pollution and its source. As mentioned earlier, the limited time constrained the number of
independent environmental parameters used in this study.
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Chapter 5:
Integrated Pollution Management Plan
Effective management of Laucala Bay marine ecosystem is a concern for Suva residents, and the proposed
management plan aims to reduce not only faecal pollution, but other forms of contamination that exists in the
bay. As indicated by the research, there are both point source and non-point source of pollution and thus an
integrated approach is needed to reduce pollution through this proposed water management and monitoring
scheme (Figure 2).
Figure 2: Integrated Pollution management and monitoring plan for Laucala Bay. Control Points represent
quality control status reports
Control Point 1
International Waters
Programme (IWP)-Ministry
of Environment
Public Works Department
Ministry of Health
Health & Sanitation SectionSuva City Council
Identified
Pollution
Problem
Control Point 2
STAGE 1
Identifying
problems and
integrating
stakeholders
If problem not
resolved
STAGE 4
Draw up Memorandum of
Understanding
Public Education
Campaign
Control Point 3
STAGE 2
Evaluation and Analysis
of problem. & seeking
stakeholder participation
Monitoring
Mitigation
STAGE 3
Collaboration by various
parties to resolve pollution
problem-solutions provided
to stakeholders
Involvement of Consultant and Executing Agency (s)
Management of Laucala Bay lagoon requires the integration of scientific monitoring techniques, integration of
community stakeholders, pollution awareness and improved long-term surveillance, both scientifically and
through legislation. The proposed management plan should proceed through four stages, “stimulating physical,
biological and chemical parameters over the well-defined annual seasonal cycle and inter-annual variation for
long-term trends.
5.1
Stage 1: Establishment of Laucala Bay Integrated Marine Pollution Management Network (Duration
0-2 months)
At stage one, it is vital that all stakeholders (industries, private and public enterprises) and community of
Laucala Bay come together, to discuss the priority problems affecting the lagoon and specific recommendations
for actions to improve the marine ecosystem. It is also recommended that the plan of action and the necessary
participation of the different stakeholders be discussed by the implementing sectors.
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5.2
Stage 2: Baseline monitoring and survey (Duration: 3 years)
Baseline information to assess pollution status, implement a monitoring plan, compare water quality data and
project validation is necessary (Prandle, 1991). Therefore in stage two of the plan, it is recommended that a
baseline water quality monitoring survey be carried out in Laucala Bay sampling stations through the
implementation of an appropriate sampling design. Previous studies carried out should also be considered.
5.3
Stage 3: Execution of water quality monitoring scheme (Duration: five years)
The objective of stage three of the scheme is to reduce the concentration of the pollutants by evaluating the
success of strategies agreed by the different stakeholders through regular water monitoring, using the baseline
experimental design.
The point source pollutants monitoring must be carried out on four months basis for a period of four years.
Therefore identified environmental variables must be sampled every four months, analysed and evaluated. The
trends of scientific data must also be represented on a four-month time scale, and compared with the baseline
survey. Decreasing levels in a variable would indicate improvement of water quality of an area.
At this stage, effective collaboration between the consultancy and the network of stakeholders is
recommended. Should a source still persist to show no improvement in physical, chemical and biological
quality of its immediate aquatic environment and persisting high contamination levels of pollutants, more
effective effluent discharge strategies and options should be provided to the residing stakeholder and/or
stakeholders. Problems and solutions must be mitigated within two years to complement low contamination
levels of pollutants and improved water quality.
5.4
Stage 5: Execution of water quality surveillance scheme (Duration 2 years)
At the end of stage three, strategies to reduce contaminates into water must be effectively placed. Therefore
the focus should now shift to improving the environmental health of the Laucala Bay. Thus the long-term,
standardised measurement and observation of the aquatic environment through the Laucala Bay Water Quality
Monitoring Scheme should aim to reduce contaminants within acceptable and standard levels.
Environmental and pollution parameters must be sampled every six months, and compared with standard
levels for contaminants. Yearly trends can be viewed, with average data plotted against standard values (Figure
3).
Figure 3: Example of possible statistical representations of monitoring parameters to view yearly
trends of changes
Source: Murray, A. and Portmann J.E., 1982
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A Memorandum of Understanding (MOU) could also be established between the legislators and stakeholders
on measures for treating, reducing and seeking alternatives to effluent discharges into coastal waters.
Emphasis should also be placed on community education programmes for managing Laucala Bay aquatic
environment and refining legislations covering the disposal of wastes into water.
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Chapter 6:
Conclusion and Recommendations
In this exploratory study, it has been illustrated that the discharges from coastal areas and polluted river waters
affect the microbial quality of water and sediments. Sediment is the most stable environment and allows the
survival of microorganisms, thus acting as a reservoir of pathogens. This study detailed that in the Laucala Bay
marine environment benthic faecal coliform E.coli (enteric microorganisms) levels are at significantly elevated
levels relative to the overlaying water column.
There is no single evidence through this research that there is just one source of pollution; faecal pollution is
more localized in the Bay or coastline area. It is spatially explicit that high pollution of palegic water and the
sediments, exists near land mass and stepwise regression indicates that distance measures influences faecal
coliform levels most in Laucala Bay. The coastal areas in Laucala Bay is most polluted showing the highest
pelagic and benthic sediment faecal coliform levels and lower dissolved oxygen and water turbity, thus
portraying a poor water quality in the coastal waters. This study is not intended to cause havoc in community.
It is purely designed to illustrate that anthropogenic effects are having a negative environmental impact in the
Laucala Bay marine ecosystem, which not only pauses threats to biota, but local residents. The stepwise
regression in this research indicates that the distance measure is a strong influence on the pelagic and benthic
faecal coliform levels. As distance of sampling stations from the coast and Kinoya Outfall are measuring very
similar things, “one should not increase, beyond what is necessary and not make more assumptions than the
minimum needed to explain the phenomena” (Principle of Occam’s Razor). Thus the perception should purely
be that faecal pollution does exist, and community collaboration is required to further explore its causes.
Public health decisions concerning the safety of marine ecosystem waters for recreational use or for the
harvesting of shellfish continue to be based primarily upon faecal coliform enumerations. Although the validity
of the faecal coliform indicator system continues to be questioned, a suitable alternative has yet to be
accepted. According to Anderson and others (1983), selection of a reliable indicator requires a good deal of
information concerning the fate of the potential indicator in aquatic systems. Despite this fact, it is evident that
the discharge of domestic sewage effluent bearing pathogenic enteric viruses into coastal waters is a potential
risk to public health, particularly to those who bathe or consume shellfish from the coastal waters. Till a viable
means of pollution management is sought, this research recommends that recreational bathing and shellfish
harvesting from coastal areas of Laucala Bay, especially those immediate to downstream rivers and the sewage
outfall is limited.
An integrated approach to reducing pollution in Laucala Bay is critical as both point and non-point source of
contamination persists. Understanding of the natural background variability in benthic microbial populations is
critical for designing an appropriate and cost effective long-term monitoring programme that is sensitive to
detect any future perturbations or changes directly attributable to the construction and operation of a new
outfall.
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Exposed In-situ in Membrane Diffusion Chambers Containing Filtered and Non-Filtered Estuarine
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Mallin, M. A., E. C. Esham, K. E. Williams and J. E. Nearhoof. (1999). Tidal Stage Variability of Fecal
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APPENDIX A
DATA SET FROM FIELD SAMPLING
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APPENDIX B
RESEARCH SAMPLING STATION LOCATIONS
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APPENDIX C
FIGURE 2: FREQUENCY DISTRIBUTION GRAPH OF VARIABLES MEASURED IN
LAUCALA BAY FORM 9TH MARCH TO 6TH APRIL, 2005
Figure 2.1: Frequency Distribution graph of Salinity levels
S A L IN I T Y
L E V E L S
IN
L A U C A L A
B A Y
30
2 5
Frequency
2 0
1 5
1 0
5
M e a n = 2 5 .5 3
S td . D e v . = 6 . 3 9 3 9 1
N = 6 0
0
1 0 .0 0
1 5.0 0
20 .0 0
2 5 .0 0
3 0 .0 0
S a lin ity ( p p t)
Figure 2.2: Frequency Distribution graph of Temperature
T E M P E R A T U R E L E V E L S IN L A U C A L A B A Y
14
12
Frequency
10
8
6
4
M e a n = 2 9 .6 2 7 5
S td . D e v . = 0 . 8 8 3
N = 60
2
0
2 8 .0 0
2 9 .0 0
3 0 .0 0
3 1 .0 0
3 2 .0 0
T e m p e ra ture
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Figure 2.3: Frequency Distribution graph of Dissolved Oxygen levels
D I S S O L V E D O X Y G E N L E V E L S IN L A U C A L A B A Y
30
25
Frequency
20
15
10
5
M e an = 9 .98 0 2
S td . D e v . = 9 . 4 3 9 1 9
N = 60
0
5 .0 0
1 0 .0 0
1 5 .0 0
2 0.0 0
2 5 .00
3 0 .0 0
D is s o lv e d O x y g e n ( m g /L )
Figure 2.4: Frequency Distribution graph of Turbity levels
T U R B IT Y L E V E L S I N L A U C A L A B A Y
14
12
Frequency
10
8
6
4
M e an = 1 .73 8 2
S td . D e v . = 0 . 7 2 9 5 6
N = 60
2
0
0 .0 0
1 .0 0
2 .0 0
3 .0 0
4 .0 0
T u rb it y ( m )
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Figure 2.5: Frequency Distribution graph of Pelagic Faecal coliform levels
F A E C A L C O L IF O R M L E V E L S IN L A U C A L A B A Y
60
50
Frequency
40
30
20
10
M e a n = 5 9 1 5 .2 5
S td . D e v . =
1 4 1 40 .9 26
N = 59
0
0
20000
40000
60000
80000
100000
F C L e v e ls ( c o lo n ie s /1 0 0 m l)
Figure 2.6: Frequency Distribution graph of Benthic Sediment Faecal coliform levels
B E N T H IC S E D IM E N T L E V E L S I N L A U C A L A B A Y L A G O O N
20
Frequency
15
10
5
M e a n = 1 9 7 4 2 .1 1
S td . D e v . =
3 2 28 2 .95 6
N = 19
0
0
2 0 0 00
40000
6 00 0 0
80000
100000
120000
B e n t h ic S e d im e n t L e v e ls
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APPENDIX D
TABLE 1: TABLES SHOWING HIGHEST, LOWEST AND MEAN VALUES OF VARIABLES
EXAMINED IN THE DIFFERENT SAMPLING WEEKS
Table 1.1: Table showing highest, lowest and mean Salinity levels in the different sampling weeks
Week
Highest Salinity
Value (ppt)
Station
Lowest Salinity
Value (ppt)
Mean Salinity (ppt)
Station
1 (09.03.05)
26.85
6
9.2
7
18.51
3 (23.03.05)
31.9
18
25.3
14
28.5
5 (06.04.05)
31.55
18
27.9
12
29.58
Table 1.2: Table showing highest, lowest and mean Temperature levels in the different sampling
weeks
Week
Highest Temperature
0
Value ( C)
Station
Lowest Temperature
0
Value ( C)
Mean Temperature
(0C)
Station
1 (09.03.05)
29.55
20
28.4
1
28.88
3 (23.03.05)
30.95
12
29.6
3
30.65
5 (06.04.05)
30.15
10
28.2
4
27.88
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Table1.3: Table showing highest, lowest and mean Dissolved Oxygen levels in the different sampling
weeks
Highest Dissolved
Oxygen
Week
Value
(mg/L)
Station
Lowest Dissolved Oxygen
Value
(mg/L)
Mean Dissolved
Oxygen (mg/L)
Station
1 (09.03.05)
7.985
3
4.63
18
6.68
3 (23.03.05)
6.99
14
3.77
11
5.49
5 (06.04.05)
32.1
2
4.17
19
17.77
Table 1.4: Table showing highest, lowest and mean Turbity levels in the different sampling weeks
Week
Highest Turbity (m)
Value (m)
Station
Lowest Turbity (m)
Value (m)
Mean Turbity (m)
Station
1 (09.03.05)
1.75
19
0.7
11
1.59
3 (23.03.05)
4
3
0.7
18
1.95
5 (06.04.05)
2.9
9
0.3
4
1.68
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Table 1.5: Table showing highest, lowest and mean Pelagic Faecal coliform levels in the different
sampling weeks
Week
Highest
Mean
(colonies/100ml)
Lowest
Value
(colonies/100
ml)
Station
Value
(colonies/1
00ml)
1 (09.03.05)
9600
3
600
12
5765
3 (23.03.05)
12200
15
6000
20
3715
5 (06.04.05)
10000
14
800
5
3650
Station
Table 1.6: Table showing highest, lowest and mean Benthic Sediment levels in the different sampling
weeks
Highest
Value
(CFU/100ml)
110000
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Lowest (MPN/100ml)
Stations
11,15, 19
Value
(MPN/100ml)
400
Mean (MPN/100ml)
Station
3
19742
Page 31 of 41
APPENDIX E
FIGURE 3: SPATIAL MAPS OF TESTED PARAMETERS IN LAUCALA BAY
Figure 3.1: Plot of Nitrate Levels measured on the 9th of March, 2005 in Laucala Bay
85
21
47
37
28
48
31
14
29
29
22
36
50
9
6
44
3
20
Coastline
7
23
Figure 3.2: Plot of Salinity Levels measured in Laucala Bay
25
28 28
Week 1
32
Week 3
Week 5
28
30
31
32
15
23
17
15
11
32
24
23
18
14
9
31
24
30
32
2827
29
31
23
27
19
29
26
28
31
28
27
29
28
30
27
29
29
29
29
30
30
29
29
30
29
9
9
30
20
28
28
28
29
29
12
Figure 3.3: Plot of Dissolved Oxygen Levels measured in Laucala Bay
Alvin Chandra
Page 32 of 41
7.3 7.5
5.2
7.0
Week 1
Week 3
Week 5
30.3
6.8
6.3
6.8
5.8
6.3
5.6
3.9
7.8
4.1
5.5
3.8
31.0
31.5
31.3
6.4
8.0
5.3
29.4
4.3
6.8
4.9
5.0
4.6
4.9
6.56.6
5.7
6.5
7.5
7.4
6.0
4.2
5.2
5.5
4.9
7.1
6.9
6.3
4.6
4.5
4.5
31.9
6.5
29.9
6.8
3.6
28.8
4.7
4.3
7.4
7.4
31.4
5.9
32.1
5.0
Figure 3.4: Plot of Turbity Levels measured in Laucala Bay
1.6 2.0
3.1
Week 1
2.2
Week 3
Week 5
2.2
2.2
1.8
1.2
1.8
1.4
1.2
1.6
1.2
0.7
1.4
1.6
1.6
1.5
0.7
2.3
2.7
1.6
1.2
1.6
1.9
1.72.1
1.5
1.8
1.2
1.8
0.8
1.3
Alvin Chandra
2.2
0.8
3.0
0.5
1.5
1.8
2.9
2.5
0.9
0.9
1.5
1.9
0.7
2.5
4.0
3.1
1.4
1.7
1.3
2.7
2.2
2.1
2.4
2.5
0.3
2.0
0.8
Page 33 of 41
Figure 3.5: Plot of Pelagic Faecal coliform Levels measured in Laucala Bay
58000
3000
Week 1
1300
10000
Week 3
Week 5
1400
1400
300
3100
600
1700 600
8000
3500
1800
1400
8600
1100
1100
3800
12200
1900
6500
1200
6000
1600
1900 1800
2700
700
1400
2000
2500
4100
10300
4000
1300
1900
2400
1600
5900
1200
1900
800
4700
1200
1300
4500
5600
200096000
6800
4400
4200
5200
7200
6500
3700
2400
4800
Figure 3.6: Plot of Benthic Sediment Faecal coliform Levels measured in Laucala Bay
93007500
9300
7500
24000
15000
110000
9300
110000
11000
2300
4300
2300
9300
400
15000
9300
15000
4300
Alvin Chandra
Page 34 of 41
APPENDIX F
FIGURE 4: SCATTER PLOTS SHOWING CORRELATIONS OF ENVIRONMENTAL VARIABLES MEASURED
IN LAUCALA BAY LAGOON WITH PELAGIC AND BENTHIC FAECAL COLIFORM LEVELS
Figure 4.1:
levels
G r aScatter
p h o f Nplot
it r aof
t e Nitrate
L e v e l s levels
V s P eversus
l a g i c Pelagic
F e a c a l Faecal
c o l if o rcoliform
m l e v e ls
1 2 .0 0
1 1 .0 0
1 0 .0 0
ln_FC
9.0 0
8.0 0
7 .00
R S q L in e a r = 0 . 0 8 1
6.0 0
5.0 0
0 .0 00
2 0 .00 0
4 0 .0 0 0
6 0 .0 0 0
8 0 .0 0 0
1 0 0 .0 0 0
N it r a t e L e v e ls ( m g /L )
G ra
p h o fplot
Sa liofn Salinity
ity Vs Plevels
e la g ic
Fe a c
a l co lifo
rm le
v e ls levels
Figure 4.2:
Scatter
versus
Pelagic
Faecal
coliform
1 2.00
1 1.00
ln_FC
1 0.00
9.00
8.00
7.00
R Sq L inea r = 0.00 4
6.00
5.00
5.00
10 .0 0
15 .0 0
20 .0 0
25.0 0
30 .0 0
35 .0 0
Sa lin ity (p p t)
Alvin Chandra
Page 35 of 41
Figure G4.3:
plot
Temperature
levels
r a pScatter
h o f Te
m pof
e ra
tu re V s P e versus
la g ic FPelagic
e a c a l Faecal
c o l ifo rcoliform
m le v e ls
1 2 .0 0
1 1 .0 0
1 0 .0 0
ln_FC
9.0 0
8.0 0
7 .00
R S q L in e a r = 0 .01 2
6.0 0
5.0 0
2 8.0 0
29 .0 0
3 0.0 0
31 .0 0
3 2 .0 0
T e m p e r a tu r e
Figure
4.4: Scatter plot of Dissolved Oxygen Levels versus Pelagic Faecal coliform
G ra p h o f Fa e c a l co l ifo rm le v e ls V s D is s o lv e d O x y g e n L ev e ls
levels
1 2 .0 0
1 1 .0 0
ln_FC
1 0 .0 0
9.0 0
8.0 0
7 .0 0
R S q Li n e a r = 0 .0 7 9
6.0 0
5.0 0
3 .0 0
4 .0 0
5 .0 0
6 .00
7 .0 0
8 .0 0
D is s o lv e d O x y g e n (m g /L )
Alvin Chandra
Page 36 of 41
Figure 4.5:
plotTof
Turbity
Pelagic
Faecal
G Scatter
ra ph of
u rb
ity Vversus
s P e la
g ic Fe
a c acoliform
l c o lifolevels
rm le v e ls
1 2 .0 0
1 1 .0 0
1 0 .0 0
ln_FC
9.0 0
8.0 0
7 .00
R S q L in e a r = 0 .03 1
6.0 0
5.0 0
0 .0 0
1 .0 0
2 .0 0
3.0 0
4 .0 0
T u rb ity (m )
Alvin Chandra
Page 37 of 41
APPENDIX G
FIGURE 5: CORRELATIONS OF PELAGIC FAECAL COLIFORM WITH VARIOUS DISTANCE VARIABLES
Figure 5.1: Correlation of Distance form coastline with Pelagic Faecal coliform levels
Figure 5.2: Correlation
of Distance form nearest River with Pelagic Faecal coliform
G r a p h s h o w in g L n F C l e v e l s V s D i s t a n c e f o r m N e a r e s t R iv e r s
levels
1 2 .0 0
1 2 .0 0
1 1 .0 0
1 1 .0 0
1 0 .0 0
1 0 .0 0
9 .0 0
9.0 0
C o a s t l in e
ln_FC
ln_FC
G r a p h s h o w in g F C le v e ls V s D is t a n c e f o r m
8.0 0
8 .0 0
7 . 00
7 .00
R S q L in e a r = 0 . 1 1 9
R S q L in e a r = 0 . 01 7
6.0 0
6 .0 0
5.0 0
5 .0 0
0 .0 0
2 .0 0
4 .0 0
6.0 0
8 .0 0
1 0 .0 0
1 2 .0 0
0 .0 0
Alvin Chandra
2 .00
4 .0 0
6. 0 0
8. 0 0
D is t a n c e f ro m n e a re s t R iv e r s (K m )
D is t a n c e f ro m C o a s t ( K m )
Page 38 of 41
1 0 .0 0
1 2 .0 0
Table 5.1: Correlation of Independent Environmental variables with Pelagic Faecal coliform levels
Figure 5.3: Correlation of Distance form Kinoya STP with Pelagic Faecal coliform
G r a p h o f D i s t a n c e f o r m K in o y a S T P V s P e la g ic F e a c a l c o l ifo r m le v e ls
levels
1 2 .0 0
R*
2
p*
Temperature
0.012
0.403
Salinity (ppt)
0.004
0.649
Dissolved Oxygen (mg/L)
0.002
0.719
Turbity (m)
0.031
0.179
0
0.927
Distance form Kinoya STP (Km)
0.166
0.181/ 0.010
Distance form Coastline (Km)
0.119
0.07/ 0.001
Distance form Nearest Rivers (Km)
0.017
0.331/ 0.155
Independent Variables
1 1 .0 0
ln_FC
1 0 .0 0
9.0 0
8.0 0
7 .0 0
No. of Weeks
R S q Li n e a r = 0 .0 3 1
6.0 0
5.0 0
1 .0 0 0 0
2 .0 0 0 0
3 .0 00 0
4 .00 0 0
5 .0 0 0 0
6 .0 0 0 0
D is t a n c e f o rm K in o y a S T P ( K m )
7 .0 00 0
8 .0 0 0 0
*Products of multiple Linear Regressions.
Alvin Chandra
Page 39 of 41
APPENDIX H
FIGURE 6: CORRELATIONS OF BENTHIC SEDIMENT FAECAL COLIFORM WITH VARIOUS DISTANCE VARIABLES
Figure 6.2: Correlation of Distance Coastline with Benthic Faecal coliform levels
L n F C l e v e l s in S e d im e n t V s D i s t a n c e f o r m C o a s t lin e
1 2 .0 0
1 2 .0 0
1 1 .0 0
1 1 .0 0
1 0 .0 0
1 0 .0 0
Ln_Sediment
Ln_Sediment
Figure 6.1: Correlation of Distance form Kinoya STP with Benthic Faecal coliform
L n F C l e v e l s in S e d im e n t V s D i s t a n c e f o r m K in o y a S T P
levels
9 .0 0
8 .0 0
7 .00
9.0 0
8.0 0
7 .00
R S q Li n e a r = 0 .4 8 3
6.0 0
R S q L in e a r = 0 .38 1
6.0 0
5 .0 0
5.0 0
1 .0 0
2 .0 0
3 .0 0
4 .0 0
5.0 0
6 .0 0
7 .0 0
8 .0 0
0 .0 0
D is t a n c e f o rm K in o y a S T P ( K m )
Alvin Chandra
2 .0 0
4 .0 0
6 .0 0
D i s t a n c e f r o m C o a s t (K m )
Page 40 of 41
8 .00
1 0 .0 0
Figure 6.3: Correlation of Distance form nearest River with Benthic Faecal coliform
L n F C l e v el s in S e d im e n t V s D i s t a n c e f o r m N e a re s t R iv e r s
levels
Table 6.1: Correlation of Independent Environmental variables with Benthic Faecal coliform
levels
Independent Variables
R2*
p*
Pelagic Faecal coliform Levels
0.002
0.431
Distance form Kinoya STP (Km)
0.483
0.001
Distance form Coastline (Km)
0.381
0.005
Distance form Nearest Rivers (Km)
0.465
0.01
1 2 .0 0
1 1 .0 0
Ln_Sediment
1 0 .0 0
9 .0 0
8 .0 0
7 .00
R S q L in e a r = 0 .46 5
6.0 0
*Products of Stepwise Multiple Linear Regressions
5 .0 0
0 .0 0
2 .0 0
4 .0 0
6 .0 0
8 .0 0
1 0 .0 0
D is t a n c e f r o m n e a r e s t R iv e r s ( K m )
Alvin Chandra
Page 41 of 41

Faecal Pollution in Laucala Bay

Transcription

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