Application of Algal Turf Scrubber Technique to remove nutrient from

Transcription

International Summer Water Resources Research School
Dept. of Water Resources Engineering, Lund University
Application of Algal Turf Scrubber Technique to
remove nutrient from a eutrophic reservoir in the
Jiulong River watershed, Southeast China
By
Charlotta Dixner
2013
Charlotta Dixner
2013-07-20
VVRF05
Abstract
The increasing demand for low-cost technologies can be managed by ecological engineering
that imply controlled ecosystems designed specific for water treatment. The method called
Algal Turf Scrubber (ATS) Technique lowers the nutrient concentration and increases the
dissolved oxygen concentration in the water at a high rate. Moreover, the nutrients that has
been removed from the water body and stored in the biomass of the algae can be collected to
produce biofuels.
This report will assess the potential for improving water quality and to control algae
production in and around Jiulong River, Fujian. The project will provide preliminary
quantification of growth rates, chemical and biochemical composition of the algae.
The result shows that the phosphorous removal rate in this experiment is high and furthermore
the comparison with Chesapeake Bay confirms this, because of their lower values. The high
values of nitrate and ammonium indicates that the Jiulong River is very nutrient rich. In both
cases the phytoplankton Melosira is the dominant species, which furthermore validates these
conditions. The water quality has been improved, which can be confirmed by the increased
dissolved oxygen (DO) and pH in the outflow water. The phytoplankton varies between
March and June/July and between the different cycles, which mainly depends on the amount
of total phosphorous available.
The ATS technology is recommended for large scale nutrient removal. However, more
experiments are needed in the future to find the optimal conditions for ATS to get a high
removal rate.
Keywords: Algal turf scrubber, Algae, Nitrogen, Phosphorus, Jiulong River
Charlotta Dixner
2013-07-20
VVRF05
Table of Contents
1.
Introduction ........................................................................................................................ 1
2.
Algal Turf Scrubber Technique.......................................................................................... 2
2.1
Algal Turf Scrubber ..................................................................................................... 2
2.2 Biofuels potential of ATS ................................................................................................ 2
2.3
2.4
3.
Major challenges of ATS technique application ...................................................... 3
Previous experiments ................................................................................................... 3
Materials and methods ....................................................................................................... 4
3.1
Study site ..................................................................................................................... 4
3.2
Experiment design ....................................................................................................... 5
3.2.1
4.
Materials ............................................................................................................... 5
3.3
Sampling ...................................................................................................................... 5
3.4
Lab analysis ................................................................................................................. 6
Result and discussion ......................................................................................................... 7
4.1 Algae samples .................................................................................................................. 7
4.2 Water samples .................................................................................................................. 9
4.3 Phytoplankton................................................................................................................. 11
4.3.1 March 2013 ............................................................................................................. 11
4.3.2 June/July 2013 ......................................................................................................... 13
5.
Conclusions ...................................................................................................................... 15
6.
Acknowledgements .......................................................................................................... 15
7.
References ........................................................................................................................ 16
Charlotta Dixner
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1. Introduction
Human activities has contributed to a substantially degradation of aquatic ecosystems.
Eutrophication and harmful algal blooms (HABs) occur more frequently in rivers and coastal
areas and an increase in agriculture and industry has resulted in increased nutrients (nitrogen,
N and phosphorus, P) (Chen & Hong, 2012). One of the major water quality problems of
environmental concern reported from aquaculture is high concentration of nitrogen (N) and
phosphorus (P) in effluent discharge (Valeta & Verdegem, 2012). The export of these
nutrients to coastal waters can result in negative consequences like higher phytoplankton and
more severe hypoxia and increased nutrients can furthermore have indirect effects. To
improve and restore aquatic ecosystems a markedly reduced nutrient input is needed as well
as an appropriate management (Chen & Hong, 2012).
To improve the water quality in degraded aquatic ecosystems there is an increasing demand
for low-cost technologies. This problem can be managed by ecological engineering that imply
controlled ecosystems designed specific for water treatment (Adey et al, 2011). Another issue is
the continued use of fossil fuels which have put much attention to renewable biofuels. The use
of oil crops and waste oils to produce biofuels cannot meet the existing demand for fuel any
longer, so in recent year’s microalgae appear to be a more promising alternative (Christenson
& Sims, 2011). Furthermore, aquatic algae are capable of using solar energy to enable nutrient
removal of nitrogen, phosphorus and carbon dioxide and have besides greater photosynthetic
potential than higher-trophic-level plants (Adey et al, 2011).
Algae based treatment can, compared to physical and chemical treatment processes,
potentially achieve nutrient removal in a less expensive and ecologically safer way with the
added benefits of resource recovery and recycling (Christenson & Sims, 2011). One method
called Algal Turf Scrubber (ATS) Technique lowers the nutrient concentration and increases
the dissolved oxygen concentration in the water at a high rate. Moreover, the nutrients that has
been removed from the water body and stored in the biomass of the algae is collected to
produce biofuels (Adey et al, 2011). The aim of this report is to apply the Algal Turf Scrubber
technique and evaluate the algal flora and water sources in the Jiulong River. This is a first
step towards the goal of large-scale application to improve water quality and production of
algal biofuels with ecologically engineered technologies.
The research questions in this paper are:


Will the water quality be improved?
How efficient is the removal capacity of nutrients?
This report will assess the potential for improving water quality and to control algae
production in and around Jiulong River, Fujian. The project will provide preliminary
quantification of growth rates, chemical and biochemical composition of the algae.
Recommendations concerning development of large scale nutrient removal in the Jiulong
River will be made based on the data gathered during the proposed research.
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2. Algal Turf Scrubber Technique
2.1 Algal Turf Scrubber
ATS was invented by scientist Walter Adey in the 1980s at the Smithsonian Institution. The
purpose of this tool was to control water quality in highly diverse model ecosystems. The
ATS system produces multiple environmental and social benefits and result in clean, healthy
water, as well as restored waterways and has in addition large potential for valuable
byproducts (Adey & Bannon, 2008).
The system of the ATS technique consists of an attached algal community that takes the form
of a “turf” growing on screens in a shallow trough or basin (raceway) (Adey et al, 2011). The
turfs can be efficient scrubbers of carbon dioxide, nutrients and different pollutants found in natural or
waste water (The Smithsonian Institution, 1982). Algal Turfs are biodiverse communities of
unicellular to filamentous algae of all major algae (Adey & Bannon, 2008). The water is
pumped through the raceway and the algal community takes up inorganic compounds and
release dissolved oxygen through photosynthesis and provides water treatment. The algae
remove the nutrients through biological uptake and produce oxygen as the water flows down
the raceway. When the water is released back into the water at the end of the raceway it has a
lower nutrient concentration and a higher dissolved oxygen concentration than when it was
pumped onto the raceway. The biomass of the algae growing on the screen stores the nutrients
that have been removed from the water and the algae are collected. To obtain high growth
rates it is important to collect the algae since it rejuvenates the community and it also prevents
or reduces the potential effects of invertebrate micrograzers. The technology removes
nutrients and produces oxygen at a high rate and is among the highest of any recorded values
due to the fast growth rate of algae on ATS. Different design properties of ATS include the
flow rate of water, the slope of the raceway, the loading rate of nutrients in the water, and the
type of screen used to grow algae (Adey et al, 2011).
2.2 Biofuels potential of ATS
There is a large potential for valuable byproduct use and reuse in addition to the
environmental benefits of ATS systems and this would create new economic opportunities
(Adey & Bannon, 2008). Microalgae exhibit enormous potential for biotechnological
industries, since they are the principal primary producers of oxygen in the world. The
microalgae biomass can be used for the production of pigments, lipids, foods, and renewable
energy. An important application of microalgae is biodiesel production that is possible
because of the large amount of lipids that microalgae contain. Proteins, carbohydrates, lipids,
and minerals compose 90-95% of the microalgae dry biomass. Furthermore, after hydrolysis,
the residual biomass can potentially be used for bioethanol production (Schneider et al, 2012).
All algal cells have phospholipid membranes and a small amount of oil that can be converted
to biodiesel. Diatoms tend to have higher oil content, since they store food in oils. Oils from
ATS algae could be converted into biodiesel, but the concentrations of fatty acids in the ATS
are relatively low.
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Algae biofuels from fermentation processes is therefore preferred than from oil extraction
and has moreover a relatively higher economic value that might come from conversion of
algal oils into nutraceuticals, such as omega-3 fatty acids (Adey et al, 2011). After the
extraction of the oil, by-products such as proteins and the residual biomass can be used as
fertilizer or it can be fermented to produce bioethanol and biomethane. The biomass can also
be burned to produce energy (Schneider et al, 2012).
2.3 Major challenges of ATS technique application
The planet suffers an enormous burden due to the population growth, modernization and
globalization among others which have led to an environmental challenge. Even though
sustainable solutions are approached, all of those today involve methodologies that will have
serious impacts on the atmosphere, water quality and biodiversity. The solutions must have
multiple benefits; they must be economically competitive and biological in nature, but
ultimately lead to environmental restoration (Adey & Bannon, 2008). The algal turf scrubber
technique is one method that benefits of cost-effective algae production and harvesting to both
wastewater treatment and the production of biofuels and other bioproducts. However, there
are major challenges to the implementation of an integrated algae system. One is the large
scale production of algae that includes the nutrient supply and recycling, gas transfer and
exchange, culture integrity and environment control. Secondly, one challenge is the
harvesting of algae in a way that allows for downstream processing to produce biofuels and
other bioproducts of value. Economically it can also be costly if the algae growth requires the
availability of primary nutrients and micronutrients and they need to be added in great
amounts (Christenson & Sims, 2011).
2.4
Previous experiments
Previous experiments have been done and one experiment was in Chesapeake Bay, Maryland,
United States in the years 2007/2008. The total phosphorous removal rates are compared and
discussed with the result from the experiment in this report, see section 4 below. Data can be
found in table 1 below.
Table 1. Data from an experiment in the Chesapeake Bay, Maryland, United States in 2007/2008.
River
Total nitrogen (TN)
removal rates (m−2 day−1)
The Bush
River
The
Patapsco
River
The Patuxent
River
Period
85mgTN
Total phosphorus (TP)
removal rates (m−2
day−1)
10mgTP
<10mgTN
150mgTN
<1mgTP
18mgTP
July to September 2007
mid-October to late-November 2007
45mgTN
250mgTN
4mgTP
45mgTP
November 15, 2007 to mid-April 2008
May to October
16mgTN
3mg TP
December 2007 to February 2008
May to June 2007
Source: Mulbury et al, 2010
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3. Materials and methods
3.1 Study site
Jiulong River is situated in Xiamen, in southeast of China, and is the second largest river in
Fujian Province. It is 285 km long and has an area of 14740 km2. The confluence of two
major tributaries, North Jiulong tributary and West Jiulong tributary has mainly formed the
Jiulong River. The river discharges about 12.4 billion m3/year of water into the Xiamen Bay
through the estuary. A population of 3.5 million residents, in six counties and two cities,
constitute the environmental pressure for the Jiulong River Basin. Only 13.4 percent of land
area are covered by the Jiulong River Basin and Xiamen area, but contributes more than 25
percent of the GDP of Fujian Province. Xiamen Bay receives wastewaters from both the
Jiulong River Basin and its adjacent coastal areas due to the hydrographical setting (Chen et
al, 2013). Due to extensive soil erosion and nutrient discharges from intensive agricultural
activities and animal feeding there is increasing impact on water quality in this area (Chen et
al, 2008).
The study site for this experiment was located at southeast of the Jiulong River (N 24° 31’
13.63”, E 117° 47’ 10.72”) and can be seen in figure 1 below.
Fig 1. Map over the experiment site, located at southeast of the Jiulong River
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3.2 Experiment design
The project was started up at the 25th of June 2013.
The system was operated over a one month period in
order to quantify algal growth potential. The
experimental system was constructed of a wooden
bed with a plastic turf. The water passes through the
test bed, with flow generated by a small electric
pump. Algae will be grown, as periphyton, attached
to the turf that is placed in the bottom of the test bed.
Bricks are used to support the turf and to distribute
the water flow more evenly.
The equipment used in the experiment can be seen in
figure 2 to the right. The dimensions of the ATS were
9m (length) * 0.5m (width) = 4.5m2.
Fig 2. ATS equipment used in the experiment
3.2.1 Materials
The first part of the experiment was to start up the project and to go sampling the algae and
water samples. First in section 3.4, the lab analysis, more advanced instruments where
needed. The instruments used in this experiment can be found in the text below. And
equipment used in the lab can be seen in table 2.
Table 2. Instrument and their model used throughout experiments
Instrument
Scale
Model
BS 210 S
Multi 3430 SET G (S9403, FD0925-3, TC925-3)
SX2-4-10
Muffle furnace
HY-5A
Oscillator
Universal 320
Centrifuge
plus
SAN++ SYSTEM
SKALAR SAN analyzer
Ultra violet spectrophotometer GEAESYS 10uv, Thermo
WTW
Usage
Determine the dry weight
biomass
Determine Twater, pH, DO
Make to ash
Mixing
Separation
Analyze
Determine DRP
3.3 Sampling
3.3.1 Monitor the environmental parameters
The WTW was used to determine the water temperature, pH, dissolved oxygen (DO) of both
the inflow and outflow water. A filter syringe was used to get the inflow water samples that
were used to determine the nutrients (ammonium, nitrate and orto phosphate).
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3.3.2 Filter the water
The pump was turned off so that the water could be drained away (approximately 15-30 min).
3.3.3 Phytoplankton samples
Phytoplankton samples were collected in a bottle at both the inflow and outflow area. The
species and community structure of the phytoplankton were decided in the lab by another
team.
3.3.4 Algae harvesting and pretreatment
The algal mud was collected through brushing the algae from the turf and gathered in a
bucket. 1000 mL of all the algal mud existing in the bed was then collected and brought back
to the lab.
3.4 Lab analysis
3.4.1 Algal mud treatment and analysis
1) The algal mud was put onto a tray and dried in a ventilated and shade place, a fan was
used to speed up the drying.
2) After air-drying the algal mud was put into an oven (70 ℃) until constant weight
(approximately 24h).
3) A scale with the accuracy one over ten thousand was used to determine the dry weight
(biomass).
4) The growth rate of the algae A (g per m2 per day) was calculated with the equation:
A = dry weight (g) / ATS area (m2) / cultivation days
The final units in grams oven dry-weight/m2/day for productivity.
3.4.2 Chemical analysis
1) The content of C, N, P (carbon, nitrogen, phosphorous) will be determined. The CN
analyzer is used to determine the concentration of TN and TOC of 1g dried algal mud
samples, but during the time for this experiment this instrument wasn’t available.
After grinding, 250mg dry algal mud sample was ashed for 2h in a muffle furnace
(550 °C) using a crucible. 50 ml was removed to a centrifugal tube and 10 ml 1 mol/L
concentrated hydrochloric acid was added. The sample was oscillated for 18h and then
centrifuged for 10 min (4000 rpm).
2) The liquid supernatant was diluted 100 times, the content of DRP was determined by
using the ultra violet spectrophotometer. The concentration of nutrients (NO3-N, NO2N, NH4-N, DRP, DSi) was determined using SKALAR as well.
The determination of nitrate is based on the cadmium reduction method; after dialysis, the
sample is buffered at around pH 8.2 and is passed through a column containing granulated
copper-cadmium to reduce the nitrate to nitrite. The nitrite (originally present plus reduced
nitrate) is determined by diazotizing with sulfanilamide and coupling with N-(1-naphthyl)
ethylenediamine dihydrochloride to form a highly coloured azo dye which is measured at 540
nm.
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The determination of ortho Phosphate is based on the reaction; ammonium heptamolybdate
and potassium antimony(III) oxide tartrate react in an acidic medium with diluted solutions of
phosphate to form an antimony-phospho-molybdate complex. This complex is reduced to an
intensely blue-coloured complex by L(+)ascorbic acid. The complex is measured at 880 nm.
The determination of Ammonia is based on the modified Berthelot reaction; ammonia is
chlorinated to monochloramine which reacts with phenol. After oxidation and oxidative
coupling a green coloured complex is formed. The reaction is catalysed by nitroprusside,
sodium hypochlorite is used for chlorine donation. The absorption of the formed complex is
measured at 630 nm.
4. Result and discussion
The project will provide preliminary quantification of growth rates and chemical and
biochemical composition of the algae. These data will include algal species, measurements of
growth rates and of chemical compositions of source waters and of the algal biomass.
Recommendations concerning development of large scale nutrient removal and commercialscale production of algal biofuels in the Jiulong River will be made based on these data
gathered during the proposed research.
4.1 Algae samples
First data from the algae samples are processed and the result from both March and June/July
2013 can be found in table 3 below. The algal productivity, the total phosphorous and the total
phosphorous removal rate can be seen in figure 3, 4 and 5 below.
Table 3. Various data from sampling and lab analysis. Data is from three cycles in both March
and June/July 2013. Data sources from March are from the research project and June/July
from this experiment.
Sample
Date
Volume of
Algal mud(L)
Biomass
(g/L)
Algal Productivity
(g/m2/day)
TP (mg/g
Biomass)
Total phosphorus
(TP) removal rates
(mg/ m2 / day)
DRP (mg P
/ L)
Algae
Algae
Algae
Algae
Algae
Algae
2013-03-13
2013-03-17
2013-03-20
2013-07-01
2013-07-10
2013-07-13
6
19,6
12
10
15,6
14,4
30,290
23,561
31,089
63,951
53,105
20,392
13,462
25,656
27,635
23,686
30,683
21,751
2,600
2,722
2,010
1,368
1,978
2,490
35,003
69,841
55,536
32,408
60,701
54,156
26,001
27,223
20,096
13,683
19,783
24,898
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Algal productivity
Algal productivity (g/m2/day)
35
30
25
20
March 2013
15
June/July 2013
10
5
0
Experiment 1
Experiment 2
Experiment 3
Fig 3. Graph over the algal productivity (g/m2/day). The purple staple shows values from
March and the green staple from June/July.
As can be seen in figure 3 above, the algal productivity is the least at experiment one. This is
due to the absence of algae on the turf scrubber. In the second and third experiment traces of
algae is remaining on the turf scrubber which contribute to an increased algal productivity. In
June/July in experiment 3, the algal productivity is even lower than in the first experiment.
This might be due to a lower number of cultivating days.
Total phosphorous
3
TP (mg/g biomass)
2,5
2
March
1,5
June/July
1
0,5
0
Experiment 1
Experiment 2
Experiment 3
Fig 4. Graph over total phosphorus (mg/g biomass). The purple staple shows values from
March and the green from June/July.
The total phosphorous differs between March and June/July. This is probably due to the algae
species, see section 4.2, because of the connection between TP and the kind of species.
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Total phosphorous removal rate
TP removal raet (g/m2/day)
80
70
60
50
40
March 2013
30
June/July 2013
20
10
0
Experiment 1
Experiment 2
Experiment 3
Fig 5. Graph over the total phosphorous removal rate (g/m2/day). The purple staple shows
values from March and the green from June/July.
The total phosphorous removal rate in figure 5 above is lower for the first experiment; this is
due to that it is connected to the algal productivity. The increase in algae leads to a higher
uptake of nutrients and a higher TP removal rate.
4.2 Water samples
Secondly, data from the water samples are processed and the result from both March and
June/July 2013 can be found in table 4 below. The dissolved oxygen (DO) can be seen in
figure 6, also below.
Table 4. Various data from sampling and lab analysis. DRP is the dissolved reactive
phosphorus, the form directly taken up by plant cells. Data is from three cycles in both March
and June/July 2013. Data sources from March are from the research project and June/July
from this experiment.
Sample
Date
Water
Water
Water
Water
Water
Water
2013-03-13
2013-03-17
2013-03-20
2013-07-01
2013-07-10
2013-07-13
pH
Water temp(℃)
Inflow
21,0
20,4
22,4
29,5
29,1
28,5
Outflow
20,9
20,5
22,4
29,6
29,6
28,0
Inflow
7,300
7,280
7,078
6,77
6,81
6,89
DO(mg/L)
Outflow
7,950
7,362
7,732
7,8
7,08
7,34
Inflow
10,26
7,88
6,63
7,2
6,74
6,78
NO3+NO2-N
(mg N/L)
Outflow
9,68
9,38
9,55
9,74
7,39
7,51
NH4+-N
(mg N/L)
2,695
0,096
1,906
1,547
1,451
0,262
0,313
0,260
DRP
(mg P/L)
0,001
0,002
0,002
0,094
0,080
0,051
As can be seen in table 4 above, the concentrations of nitrate and ammonium is rather high.
This indicates that the Jiulong River is a very nutrient rich river. The values for DRP are
ordinary, but they are a bit lower for March. This can be explained by the algal bloom that
occurred during March and the phosphorous was depleted because of the high quantity of
algae.
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Dissolved oxygen, DO (mg/L) was measured in both March and June/July 2013, see figure 6
below. The values were measured for three cycles and for both the inflow and outflow water.
Dissolved oxygen,
June/July 2013
12
10
8
6
4
2
0
Inflow
Outflow
DO (mg/L)
DO (mg/L)
Dissolved oxygen,
March 2013
12
10
8
6
4
2
0
Inflow
Outflow
Fig 6. Graph over the dissolved oxygen, DO (mg/L) in the water. The left graph shows DO in
March; the light green staples show the inflow water and the green staples the outflow water.
The right graph shows the DO in June/July; the light blue staples show the inflow water and
the dark blue staples the outflow water.
If comparing the dissolved oxygen (DO) and the pH in the inflow water with the outflow
water is has increased, see table 4 (and figure 6 for DO). Growing algae remove carbon
dioxide from the water during photosynthesis and releases oxygen, this result in both
increased DO levels and in an increase in pH levels. The DO in the first experiment in March
is higher than the other experiments and this is due to an algal bloom that occurred during this
time. The algal bloom outside the ATS produces oxygen which contributes to a higher value
for the inflow water.
June-July Water Tempereture (℃)
The water temperature varies
with the seasons and data for
June/July can be seen in figure 7
to the right. The June/July
experiment lasted from 2013-0625 to 2013-07-13.
40
35
Experiment start
restart
First sample
Second sample
Third sample
30
25
20
15
10
5
0
6/24 6/26 6/28 6/30 7/2
7/4
7/6
7/8 7/10 7/12 7/14
Date (Year 2013)
Fig 7. The graph shows the variation of the water
temperature. The graph shows the variations for
June/July 2013.
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The water temperature varied during the experiment as can be seen in figure 7 above, but it is
an ordinary variation. These variations might influence the algal productivity and as can be
seen in figure 3, the algal productivity is higher for June/July than March. This seems
reasonable, since the temperature in March is lower.
4.3 Phytoplankton
Phytoplankton samples were collected from both inflow and outflow. The result from March
and June/July 2013 can be seen in the graphs below. The first five graphs show algae from
March and the last six graphs show algae from June/July. Photos of some of the
phytoplankton found in the samples can be seen below in figure 13-16 below (Melosira,
Synedra, Fragilaria and Pandorina).
4.3.1 March 2013
The distribution of phytoplankton varies between the different cycles and it is also depending
on the inflow and outflow water. The percentage of different species can be seen in the figures
8-12 below. There is one graph less for March because of the lack of an inflow sample from
the first experiment (20130313).
Phytoplankton (outflow),
20130313
Melosira
44%
50%
Synedra
Pandorina
6%
Fig 8. Graph over phytoplankton
Phytoplankton (inflow), 20130317
5% 3%
20130317
4%
1%
2%
Melosira
Melosira
Synedra
Synedra
Fragilaria
Fragilaria
92%
93%
Pandorina
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20130320
1%
5%
Melosira
22%
15%
58%
0%
3%
Synedra
Melosira
Fragilaria
Synedra
Pandorina
96%
Fragilaria
Peridiniopsis
Fig 13. Melosira
Fig 14. Synedra
Fig 15. Fragilaria
Fig 16. Pandorina
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4.3.2 June/July 2013
The distribution of phytoplankton varies between the different cycles and it is also depending
on the inflow and outflow water. The percentage of different species can be seen in the figures
below.
20130701
1%
2% 4%
Melosira
10%
Melosira
Cyclotella
7%
Synedra
Fragilaria
76%
Synedra
1%
11%
Cosmarium
1%
3%
Anabeana
20130710
0%
Melosira
9%
Melosira
Cyclotella
10%
Synedra
Fragilaria
77%
Cyclotella
27%
0%
Synedra
1%
57%
15%
Cosmarium
Anabeana
0%
201307013
3%
0%
0%
Melosira
8%
Cyclotella
89%
Fragilaria
Cosmarium
Anabeana
Fragilaria
1%
62%
Cosmarium
Anabeana
Cyclotella
24%
1%
1%
1%
5%
Melosira
7%
Cyclotella
Synedra
Synedra
Fragilaria
Fragilaria
Cosmarium
86%
Anabeana
Cosmarium
Anabeana
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The phytoplankton species that occur in a sample differs depending on the season, the cycle
and if the sample is from the inflow or outflow water, see figures above. The difference
between March and June/July has to do with that different species favor different climate. The
algal bloom that occurred in March might also have contributed to different species. The
variation between the inflow and outflow water could be due to competition and that the
dominant species are taking over, as can be seen in some of the figures above. In both cases
the Melosira is the dominant species, which confirm the nutrient rich conditions in Jiulong
River, since this specie is a preference for these conditions.
The phytoplankton in the various cycles differs as well. There is a connection between species
and the total phosphorous content in the water that will be normalized by the amount of
biomass. If the TP content available varies the species will differ as well.
If the TP removal rate is compared with the experiment in Chesapeake Bay, USA, table 1 in
section 2.4, the removal rate in this experiment is high which indicates that the ability of the
algae to remove nutrients is very efficient. This could be due to different reasons like seasons,
climate and nutrients available. However, other reasons like storms, algal blooms and the
setup of the experiment should also be taken into account.
Some sources of error that was taken into account in this experiment (June/July) were that the
water to the algal turf scrubber was turned off during the second cycle which might have
affected the result. During the third cycle a typhoon set in which probably influenced the
algae growth.
14
Charlotta Dixner
2013-07-20
VVRF05
5. Conclusions
Considering all the parameters above affecting the water quality, the algae ability to remove
nutrients from the water in the Jiulong River seems to be efficient and the water quality seems
to be improved. If there is a higher amount of algae the uptake of nutrients increase and
consequently the removal rate. Furthermore, the comparison with Chesapeake Bay confirms
the high TP removal rate in this experiment. The high values of nitrate and ammonium
indicates that the Jiulong River is very nutrient rich. The improved water quality can be
confirmed by the increased dissolved oxygen (DO) and pH in the outflow water. The
phytoplankton differs between March and June/July and between the different cycles. This is
due to the climate, but mainly it depends on the amount of total phosphorous available. In
both cases the Melosira is the dominant species, which furthermore validates the nutrient rich
conditions in Jiulong River since it is a preference for these conditions.
The removal capacity in the Jiulong River is high and the technology is recommended for
large scale nutrient removal. However, more experiments are needed in the future to find out
the optimal conditions for ATS to get a high removal rate.
6. Acknowledgements
The author would like to thank Professor Nengwang Chen, who has supervised this project
and been very helpful. Thanks to the research assistants Zhuhong Chen and Yinqi Wu for
leading me through the experiment with useful comments. Thanks to Kaifang Xu (Kate), my
project coworker for a satisfying teamwork. Thanks to the University of Maryland for the
collaboration.
The author is also thankful for the cooperation between Lund University and Xiamen
University and to Linus Zhang and Rolf Larsson for organizing this. Finally, thanks to the
Swedish sponsor Sweco for the contribution to the experience at Lingfeng Summer Research
School 2013.
15
Charlotta Dixner
2013-07-20
VVRF05
7. References
Adey, W. H., Kangas, P. C., Mulbry W. (2011). Algal Turf Scrubbing: Cleaning Surface Waters
with Solar Energy while Producing a Biofuel. BioScience, Vol. 61, No. 6, pp. 434441.
Adey, W., Bannon, J. (2008). ALGAL TURF SCRUBBERS: CLEANING WATER WHILE
CAPTURING SOLAR ENERGY. Proceedings of the 3rd Environmental Physics
Conference. pp 197 – 206.
Chen, N., Hong, H. (2012). Integrated management of nutrients from the watershed to coast
in the subtropical region. SciensDirect, Vol 4, pp 233–242.
Chen, N., Hong, H., Zhang, L., Cao, W. (2008). Nitrogen sources and exports in an
agricultural watershed in Southeast China. Biogeochemistry, Vol 87, pp 169–
179. DOI 10.1007/s10533-007-9175-2
Chen, N., Peng, B., Hong, H., Turyaheebwa, N., Cui, S., Mo, X. (2013). Nutrient enrichment
and N:P ratio decline in a coastal bay-river system in southeast China: The need
for a dual nutrient (N and P) management strategy. Ocean & Coastal
Management. Vol 81, pp 7-13.
Christenson, L., Sims, R. (2011). Production and harvesting of microalgae for wastewater
treatment, biofuels, and bioproducts. Biotechnology Advances, Vol 29, pp 686–
702.
Mulbry, W., Kangas, P., Kondrad, S. (2010). Toward scrubbing the bay: Nutrient removal
using small algal turf scrubbers on Chesapeake Bay tributaries. Ecological
Engineering, VOL 36, pp 536–541.
Schneider, R., C., S., Bjerk, T., R., Gressler, P., D., Souza, M., P., Corbellini V., A., Lobo,
E., A. (2012). Potential Production of Biofuel from Microalgae Biomass
Produced in Wastewater. Biodiesel - Feedstocks, Production and Applications.
Chapter 1, pp 3-24. DOI: 10.5772/52439.
The Smithsonian Institution. Walter H. Adey, McLean, Va. Algal Turf Scrubber. United
States Patent No. 4,333,263, June 8, 1982.
Valeta, J., S., Verdegem, M., C. (2012). Nitrogen Dynamics and Removal by Algal Turf
Scrubber under High Ammonia and Organic MatterLoading in a Recirculating
Aquaculture System. World Academy of Science, Engineering and Technology,
Vol 71, pp 2095-2102.
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Application of Algal Turf Scrubber Technique to remove nutrient from

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