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Biofilm growth kinetics and nutrient (N/P) adsorption in an urban lake using reclaimed water: A quantitative baseline for ecological health assessment

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Reclaimed wastewater reuse represents an effective method for partial resolution of increasing urban water shortages; however, reclaimed water may be characterized by significant contaminant loading, potentially affecting receiving ecosystem (and potentially human) health. The current study examined biofilm growth and nutrient adsorption in Olympic Lake (Beijing), the largest artificial urban lake in the world supplied exclusively by reclaimed wastewater. Findings indicate that solid particulate, extracellular polymeric substance (EPS) and metal oxide (Al, Fe, Mn) constituent masses adhere to a bacterial growth curve during biofilm formation and growth. Peak values were observed after ≈30 days, arrived at dynamic stability after ≈50 days and were affected by growth matrix surface roughness. These findings may be used to inform biofilm cultivation times for future biomonitoring. Increased growth matrix surface roughness (10.0 μm) was associated with more rapid biofilm growth and therefore an increased sensitivity to ecological variation in reclaimed water. Reclaimed water was found to significantly inhibit biofilm nutrient adsorption when compared with a “natural water” background, with elevated levels of metal oxides (Al, Fe, and Mn) and EPS representing the key substances actively influencing biofilm nutrient adsorption in reclaimed water. Results from the current study may be used to provide a quantitative baseline for future studies seeking to assess ecosystem health via monitoring of biofilms in the presence of reclaimed water through an improved quantitative understanding of biofilm kinetics in these conditions.
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Manuscript Number: ECOLIND-6466R1
Title: Biofilm Growth Kinetics and Nutrient (N/P) Adsorption in an Urban
Lake using Reclaimed Water: A Quantitative Baseline for Ecological Health
Assessment
Article Type: Research paper
Keywords: Biofilms; Reclaimed water; Lake; Growth kinetics; Nutrient
Adsorption, Eutrophication, Ecological Health Assessment
Corresponding Author: Dr. Paul Hynds,
Corresponding Author's Institution: Dublin Institute of Technology
First Author: Tianzhi Wang
Order of Authors: Tianzhi Wang; Zhenci Xu; Yunkai Li; Mingchao Liang;
Zenhua Wang; Paul Hynds
Abstract: Reclaimed wastewater reuse represents an effective method for
partial resolution of increasing urban water shortages; however,
reclaimed water may be characterized by significant contaminant loading,
potentially affecting receiving ecosystem (and potentially human) health.
The current study examined biofilm growth and nutrient adsorption in
Olympic Lake (Beijing), the largest artificial urban lake in the world
supplied exclusively by reclaimed wastewater. Findings indicate that
solid particulate, extracellular polymeric substance (EPS) and metal
oxide (Al, Fe, Mn) constituent masses adhere to a bacterial growth curve
during biofilm formation and growth. Peak values were observed after ≈30
days, arrived at dynamic stability after ≈50 days and were affected by
growth matrix surface roughness. These findings may be used to inform
biofilm cultivation times for future biomonitoring. Increased growth
matrix surface roughness (10.0μm) was associated with more rapid biofilm
growth and therefore an increased sensitivity to ecological variation in
reclaimed water. Reclaimed water was found to significantly inhibit
biofilm nutrient adsorption when compared with a "natural water"
background, with elevated levels of metal oxides (Al, Fe, and Mn) and EPS
representing the key substances actively influencing biofilm nutrient
adsorption in reclaimed water. Results from the current study may be used
to provide a quantitative baseline for future studies seeking to assess
ecosystem health via monitoring of biofilms in the presence of reclaimed
water through an improved quantitative understanding of biofilm kinetics
in these conditions.
Response to Reviewers: The authors are very grateful to the reviewers for
improving our manuscript. All author responses are included in the author
response document
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ECOLIND-6466
Reviewer Comments & Author Responses
Reviewer 1, Comment: You correctly started by stating that freshwater resources are increasingly
falling behind ever-increasing consumption which is fuelled by rapid urbanization, economic growth
etc. At this point, you may like to give some descriptive statistics regarding freshwater consumption
and freshwater capacity in China and/or in Beijing region.
Author Response: The authors agree that the recommended addition would be helpful for the
audience to place the current work in a national and global context. Accordingly, the following
paragraph has been added to the manuscript:
Recent studies have specifically highlighted Beijing as an urban area characterised by sever
water resource pressures (Zhang et al., 2011; Gao et al., 2014). For example, Jenerette et al. (2006)
estimate that while Beijing requires approximately 3064 ML/day, locally available resources account
for only a fraction of this, necessitating significant water imports from neighbouring Hebei.
Moreover, calculations indicate a total annual water footprint of approximately 47 x 108 m3/annum,
equating to an individual water footprint of 648 m3/annum, which is significantly higher to the
national mean of 391 m3/annum (Zhao et al., 2009; Ge et al., 2011). During the 4-year period 2011-
2014, freshwater consumption in Beijing outstripped local freshwater resources by 39.3% (Beijing
Water Authority, 2015).
Reviewer 1, Comment: if the article is accepted and printed in black and white, some of your
Figures (i.e. Figures 1,2,3) will become untrackable. You may like to redraw the lines with different
markers and line types so as to differentiate different series.
Author Response: The authors agreed that Figures 1-3 (now Figures 2-4 due to addition of
supplementary Figure 1) would not be readable in grayscale. Accordingly, we have followed the
reviewers recommendation by amending these figures to black/white/grayscale. We have chosen not
to amend Figure 5 (Previously Figure 4), as this figure is readable in its current format when viewed
in grayscale.
Response to Reviewers
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Reviewer 2, Comment: While the very sophisticated mathematical and statistical approach employed
is in my opinion completely correct and sound, I think that it is not clearly explained to the common
reader. This section could be more clearly presented, the variables and equations perhaps presented in
boxes or tables, and not directly "embedded" along the text. Otherwise, its okay. All information
required is presented.
Author Response: The authors agree that the overall mathematical/statistical approach used
required additional presentation. We have chosen to leave equations embedded within the text in
order that more mathematically minded reader have adequate detail for study replication. However,
we have developed and added a new Figure 1, as follows to help simplify the overall modelling
approach for readers. All other figure numbers and titles have been amended accordingly.
Figure 1. Schematic outlining the employed biofilm growth kinetic model
Reviewer 2, Comment: There are two references in the list cited in the text as "Wang et al, 2013a"
and "Wang et al, 2013b) that are properly quoted. However, twice the quotation "Wang et al, 2013" is
present in the text. This should be fixed.
Author Response: Thank you for pointing this mistake out. Accordingly, we have corrected the
error; both are now Wang et al., 2013a
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Reviewer 2, Comment: The reference "Wang et al, 2010" was quoted in the text but not listed.
Author Response: This was a mistake on the authors part; thank you for pointing it out. We have
amended it to Wang et al., 2013a
Reviewer 2, Comment: The reference "Oliveira et al, 2014" was quoted in the text also but not listed
(Mistyping? Olivieri et al, 2014?)
Author Response: Yes, the reviewer is absolutely correct, this was a mis-spelling. We have amended
to read Olivieri et al, 2014
Reviewer 2, Comment: Two different algorithms were mentioned, LM and ME. I figured this as
typing error. If this is not the case, this point should be made clear in the text. In the other hand,
calibration results were very good.
Author Response: Yes, the reviewer is correct, only one iterative algorithm was used, namely the
Levenberg-Marquardt (LM) algorithm; accordingly, the text has been amended from ME to LM
Reviewer 2, Comment: As indicated by the authors along the text, biofilms are formed by complex
inorganic/organic mixtures of substances from different origins and having different properties.
Thinking about the measurements of biofilms properties presented in this work, and with the
background measurements presented in the reservoir water (Table 1), no conclusion can be drawn
about the "health" of an artificial ecosystem at least as I can guess what this health could mean: the
capacity of this closed or semi-closed system to support different forms of life, to support some form
of food production, or to provide water resources for human use.
In my opinion the authors would benefit from being less emphatic in their conclusions and by
pointing out the limitations of this kind of study on ecosystem health evaluation. From this aspect, I
think they are very far off the mark.
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Author Response: The authors agree that the original manuscript was perhaps too emphatic with
respect to the discussion and conclusions section, and that the presented study, while useful and
novel, did not provide sufficient data to make definite conclusions with respect to the use of biofilms
as effective ecological monitors. Accordingly, the authors have made the following manuscript
amendments:
Methods Section: The following sentence has been added:
According to Gan & Bai (2010), both treatment plants achieve ≈ 6-log virus and bacteria removal, 3-
log turbidity removal, 91% removal of linear alkylbenzene sulfonates (LAS), and ≥98% removal of
volatile phenols.
Discussion Section: Overall, we have tempered the language throughout the discussion to correctly
reflect the study findings and not overemphasize or overstate the conclusions which may confidently
be drawn from the collated data. Additionally, the following paragraph have been added:
It is important to note that, within the context of ecosystem health assessment, the current study
comprised some inherent limitations, instead focusing on biofilm growth kinetics in a reclaimed
wastewater background. The current study did not include eco-toxicological analyses, and thus only
indicative conclusions pertaining to ecological health may be made. Future work should concentrate
on biofilm growth kinetics and responses to the presence of ecologically harmful compounds, in
addition to human toxins and pathogens including heavy metals, PAHs, urban pesticides, and
endocrine disruptors.
Conclusions Section: The following paragraph has been added:
Accordingly, it is concluded that biofilms may be effective indicators of ecological health in aquatic
ecosystems characterized by the presence of reclaimed water i.e. indicators of system capacity to
support food production and/or provide water resources for human use. However, significant further
work is required to elucidate the association between biofilm presence and associated growth
kinetics, and the human health related contaminants of primary concern e.g. PAHs, urban pesticides,
endocrine disruptors, enteric pathogens, etc.
1
Biofilm Growth Kinetics and Nutrient (N/P) Adsorption in 1
an Urban Lake using Reclaimed Water: A Quantitative 2
Baseline for Ecological Health Assessment 3
Wang Tianzhi1, Xu Zhenci1, Li Yunkai1,*, Liang Mingchao1, Wang Zhenhua2, Paul 4
Hynds3
5
6
1 College of Water Resources and Civil Engineering, China Agricultural University, Beijing 7
100083, China 8
2 College of Water and Architectural Engineering, Shihezi University, Shihezi City 832000, 9
Xinjiang, China 10
3 School of Civil and Structural Engineering, Dublin Institute of Technology, Bolton St., 11
Dublin 7, Republic of Ireland 12
Abstract: 13
Reclaimed wastewater reuse represents an effective method for partial resolution of 14
increasing urban water shortages; however, reclaimed water may be characterized by significant 15
contaminant loading, potentially affecting receiving ecosystem (and potentially human) health. 16
The current study examined biofilm growth and nutrient adsorption in Olympic Lake (Beijing), 17
the largest artificial urban lake in the world supplied exclusively by reclaimed wastewater. 18
Findings indicate that solid particulate, extracellular polymeric substance (EPS) and metal oxide 19
(Al, Fe, Mn) constituent masses adhere to a bacterial growth curve during biofilm formation and 20
growth. Peak values were observed after 30 days, arrived at dynamic stability after 50 days and 21
were affected by growth matrix surface roughness. These findings may be used to inform biofilm 22
* Corresponding author Yunkai Li
Tel: 86-10-62738485; Fax: 86-10-62738485; E-mail address: liyunkai@126.com
*Manuscript
Click here to view linked References
2
cultivation times for future biomonitoring. Increased growth matrix surface roughness (10.0μm) 23
was associated with more rapid biofilm growth and therefore an increased sensitivity to ecological 24
variation in reclaimed water. Reclaimed water was found to significantly inhibit biofilm nutrient 25
adsorption when compared with a “natural water” background, with elevated levels of metal 26
oxides (Al, Fe, and Mn) and EPS representing the key substances actively influencing biofilm 27
nutrient adsorption in reclaimed water. Results from the current study may be used to provide a 28
quantitative baseline for future studies seeking to assess ecosystem health via monitoring of 29
biofilms in the presence of reclaimed water through an improved quantitative understanding of 30
biofilm kinetics in these conditions. 31
32
Keywords: Biofilms; Reclaimed water; Lake; Growth kinetics; Nutrient Adsorption, 33
Eutrophication, Ecological Health Assessment 34
35
1. Introduction 36
Increasing socioeconomic development, urbanization and wastewater 37
production, in concurrence with the predicted effects of climate change will have far 38
reaching consequences for global aquatic ecosystems, particularly those situated 39
within urban and peri-urban areas. Presently, an estimated 80% of global wastewater 40
remains untreated and as such, is not reclaimed or reused; effective wastewater reuse 41
serves the dual purpose of diversion from the aquatic environment and supplementary 42
resource provision (Beaudequin et al., 2015) and is therefore particularly beneficial in 43
regions characterized by water scarcity and/or significant aquatic contamination. 44
3
Recent studies have specifically highlighted Beijing as an urban area characterized by 45
sever water resource pressures (Gao & Hu, 2011; Zhang & Anadon, 2014). For 46
example, Jenerette et al. (2006) estimate that while Beijing requires approximately 47
3064 ML/day, locally available resources account for only a fraction of this, 48
necessitating significant water imports from neighboring Hebei. Moreover, 49
calculations indicate a total annual water footprint of approximately 47 x 108 50
m3/annum, equating to an individual water footprint of 648 m3/annum, which is 51
significantly higher to the national mean of 391 m3/annum (Zhao et al., 2009; Ge et 52
al., 2011). During the 4-year period 2011-2014, freshwater consumption in Beijing 53
outstripped local freshwater resources by 39.3% (Beijing Water Authority, 2015). 54
Numerous studies have reported high levels of support for water reuse among the 55
general public, however, these studies have also shown that support decreases in line 56
with increasing levels of human contact, leading to underutilization of reclaimed 57
water for recreation and consumption (i.e. aquifer recharge) (Friedler et al., 2006). 58
This has been further exacerbated by public health concerns resulting from the 59
difficulties associated with pathogen detection and identification in reclaimed 60
wastewater (Graczyk & Lucy, 2007; Olivieri et al., 2014). 61
Biofilms are composite systems primarily composed of photoautotrophic (algae) 62
and heterotrophic (bacteria, fungi and protozoa) microorganisms, inorganic minerals 63
and organic polymers which form semi-stable dynamic systems (Rao, 1997). These 64
systems adhere to living or inanimate surfaces in multiple settings and are embedded 65
within a self-produced matrix of extracellular polymeric substances (EPS), 66
4
a polymeric conglomeration comprising proteins, polysaccharides, nucleic acids, 67
uronic acids, lipids, humic acids and amino acids, of which proteins and extracellular 68
polysaccharides comprise 7080% of the total (Hong & Herbert 2002; Hall-Stoodley 69
et al., 2004; Lear & Lewis, 2012). The formation, growth and response of aquatic 70
biofilms is closely connected with several physical, chemical and biological factors 71
including water current, substrate type, growth surface, light, temperature, organic 72
and inorganic chemical constituents (i.e. nutritional cues) and microbial composition 73
(Lear & Lewis, 2012). 74
Ecological health assessment is a process by which the nature and effects of 75
anthropogenic activities on the local environment are monitored and quantified for the 76
purposes of future management and control (Porsbring, 2007). Monitoring may be 77
undertaken via physical, chemical or biological techniques, with Porsbring (2007) 78
maintaining that biological techniques via the use of naturally occurring native 79
organisms (biomonitors) represent the most direct and effective monitoring approach 80
within aquatic systems. Changes in aquatic biological communities often directly 81
reflect physical, chemical and/or biological factors, in addition to the overall health of 82
the ecosystem. Lear & Lewis (2009) have previously employed bacterial DNA 83
fingerprint data from surface water streams to assess the impact of catchment landuse 84
i.e. increasing urban development. Similarly, Rotter et al. (2013) report that 85
periphyton levels in the River Elbe (a mixture of algae, cyanobacteria, heterotrophic 86
microbes and detritus attached to aquatically submerged surfaces) may be used to 87
provide an ecologically relevant assessment of pesticide effects under field conditions 88
5
for successful implementation of the EU Water Framework Directive (WFD). 89
Biofilms have been shown to both accurately and quickly reflect environmental 90
variation, leading to their use as biomonitors and/or indices for aquatic ecosystem 91
health evaluation (Eppley, 1977; Burns & Ryder, 2001; Guasch et al., 2003; Lawrence 92
et al., 2004; Porsbring, 2007, Ancion et al., 2014). Yan et al. (2014) investigated the 93
responses of freshwater biofilms to pollutants and overall ecosystem health in 94
Baiyangdian Lake, China. Biofilm biomass production, chlorophyll production, 95
extracellular enzyme activity and polysaccharide content were all measured in the 96
context of pollutant exposure. Results indicate that biofilms provide salient 97
information pertaining to contamination detection and ecological health assessment; 98
biofilms associated with artificial substrata were recommended for future 99
bio-monitoring at the site. Burns & Ryder (2001) and Lawrence et al. (2004) have 100
previously shown the efficacy of using biofilms as bio-monitors in riverine systems. 101
Due to the aforementioned lack of sustainable water supply in some regions and 102
increasing global rates of urbanization, the utilization of reclaimed wastewater to 103
supplement inland waterbodies represents an effective method for alleviation of urban 104
water shortages. The inherently high levels of nitrogen, phosphorous and 105
microorganisms present in reclaimed water frequently result in diverse and in some 106
cases unique biofilm communities. 107
To date, few studies have focused on biofilm growth kinetics or contaminant 108
absorption within aquatic environments supplied partly or wholly by reclaimed water. 109
Those which have been undertaken indicate that the presence of biofilm is associated 110
6
with measureable levels of both nitrogen and phosphorus adsorption (Liang et al., 111
2013; Wang et al., 2013a). In order to establish the potential efficacy of biofilms as 112
effective indicators of ecological health in aquatic ecosystems fed by reclaimed water, 113
it is critical that these processes are appropriately quantified. 114
The current study applied in-situ sample cultivation and laboratory analyses to 115
investigate biofilm growth kinetics and nutrient (nitrogen and phosphorus) adsorption 116
processes in Olympic Lake, Beijing. A growth model has been developed to elucidate 117
the growth kinetics of biofilms associated with an aquatic environment dominated by 118
reclaimed water. Dynamic variations of organic (EPS) and inorganic (Al, Fe, Mn) 119
biofilm constituents have been quantified, in addition to the solid particulate fraction. 120
Finally, three isotherm equations have been used to model the N and P adsorption 121
processes. 122
123
2. Materials and Methods 124
2.1 Study Site 125
Olympic Lake is located in the Chaoyang district of Beijing and was constructed 126
in 2007 as the primary aquatic sports venue for the 29th Olympic Games. It has an 127
area of 165,000 m2, a depth range of 0.61.1 m and a total volume of 159,000 m³ 128
(Wang et al. 2013a), thus making it the largest constructed aquatic system in the 129
world supplied entirely by reclaimed water. The lake is currently employed as an 130
urban artificial ecological water system, with two primary reclaimed water sources 131
employed, namely, the Qinghe Reclaimed Water Treatment Plant (80,000 m³/d, 132
7
ANANOX (Anaerobic-Anoxic-OXic Process)) and the Beixiaohe Reclaimed Water 133
Treatment Plant (60,000 m³/d, Membrane Bioreactor + Reverse Osmosis). Based 134
upon the current Chinese Environmental Quality Standards for Surface Water (GB 135
3838-2002), background water quality in the Olympic Green’s central and northern 136
areas are categorized as Levels III and IV, respectively. According to Gan & Bai 137
(2010), both treatment plants achieve ≈6-log virus and bacteria removal, 3-log 138
turbidity removal, 91% removal of linear alkylbenzene sulfonates (LAS), and ≥98% 139
removal of volatile phenols. The variation in measured lake water chemistry during 140
the 58-day biofilm sampling period is presented in Table 1. 141
142
2.2 Collection and Preparation of Biofilm Samples 143
Due to the ease with which glass slides may be processed to simulate variable 144
surface matrices, the in-situ glass sampling method was employed for sample 145
collection (Yang, 2005; Dong et al., 2005; Liang et al., 2013; Wang et al., 2016). 146
Liang et al. (2013) and Wang et al. (2013a) have shown that increased natural surface 147
roughness (pebbles, gravels, aquatic plants) is associated with biofilm microbial 148
diversity. Accordingly, surfaces of several potential growth matrices in lake water 149
were simulated using glass slides (25 mm × 75 mm) with distinct roughness 150
coefficients (0.1μm, 1.0μm, 10.0μm) for biofilm cultivation. Prior to installation, 151
slides were thoroughly cleaned with deionized water, followed by immersion in a 6:1 152
H2O:HNO3 solution for 24 hours, and finally flushed with deionized water. Cleaned 153
glass slides were fixed on an organic glass shelf (48 cm × 60 cm × 7.5 cm) (Wang et 154
8
al., 2016). Overall, 450 glass slides of identical roughness were fixed on each shelf, 155
with three shelves employed (1350 slides) i.e. three shelves of 0.1μm, 1.0μm and 156
10.0μm roughness. Shelves were placed adjacently on the lakebed, 50m from the 157
shore, close to the lake centre, at a depth of 30cm below the water surface. 158
Biofilm cultivation and monitoring took place over a continuous 58-day period, 159
during June and July (Mean Ambient Air Temperature 25oC). Measured solid 160
particulate masses after 58 days of growth were approximately equal to those 161
recorded after 51 days, thus it was considered that biofilms had reached a steady state 162
and the experiment was concluded. 163
There were a total of ten sampling events during the growth period; these 164
occurred at 5-day intervals for the first 6 sample events and at 7-day intervals for the 165
remaining 4 sample events. This sample regime was designed based upon findings 166
from a recent study at Olympic Lake (Wang et al., 2016) during which rapid biofilm 167
growth was followed by significantly reduced growth rates; thus it was considered 168
preferable to include higher resolution sampling during the rapid growth phase. 169
Sample events comprised extraction of 45 slides from each shelf (n = 135), with 50% 170
of extracted slides immediately refrigerated at 4°C. Remaining slides were sonicated 171
in a cavitational ultrasonic cleaner (45 min; 40 KHz) for biofilm removal and 172
production of a suspension for analyses. 173
174
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2.3 Biofilm Constituent Analyses 175
2.3.1 Solid (Dry Mass) Particulate Mass 176
Refrigerated glass slides were dried (vacuum oven at 70°C) to a constant 177
(recorded) weight and then sonicated (45 min; 40 KHz). After washing with deionized 178
water and air-drying, slides were dried and reweighed (recorded), with the difference 179
between the two recorded weights considered to equate to the solid particulate biofilm 180
weight. Five replicates were analyzed for each sample event and roughness coefficient, 181
with mean particulates masses recorded and employed for modelling. 182
183
2.3.2. Extracellular Polymeric Substances 184
Prepared biofilm suspensions were centrifuged (x2000g, 4°C, 15 mins), followed 185
by resuspension of resulting biofilm sediments in a pH 7.0 buffer (Na3PO4 2 mmol/L, 186
NaCI 9 mmol/L, NaH2PO4 4 mmol/L, and KCl 1 mmol/L) and heated to 80°C for 1 h. 187
Subsequently, samples were centrifuged (x12,000g, 4°C, 15 mins) for EPS extraction. 188
The phenol/sulfuric acid method (Nocker et al., 2007) and the Lowry method (NaOH) 189
(Lowry et al., 1951) were used to quantify extracellular carbohydrate 190
(polysaccharides) content and extracellular protein content, respectively. Both 191
methods are frequently used due to their relative simplicity and sensitivity within 192
normal EPS content ranges. 193
194
2.3.3. Metal Oxides (Al, Fe, and Mn) 195
The content of Al, Fe, and Mn oxides were measured in solution using an 196
10
analogous method to that previously described by Dong et al. (2005). Two slides for 197
each matric roughness coefficient were selected after each of the ten sample events (n 198
= 60). Glass slides with attached biofilms were rinsed (ddH2O) and placed in 100 mm 199
glass petri dishes with 60 ml 15% HNO3 and shaken for 24h, thus permitting Al, Fe, 200
and Mn oxide solute extraction. Acidified solute extracts of Fe and Mn were analyzed 201
via flame atomic absorption spectroscopy (FAAS) (WYX-9004; Shenyang, China), 202
with Al extractions analyzed by internally coupled plasma atomic emission 203
spectroscopy (ICP-AES) (PE-1000; Shenyang, China). 204
205
2.4 Nitrogen and Phosphorous Adsorption 206
An analogous method to that employed by Liu et al. (2015) was used to quantify 207
maximum nitrogen and phosphorous adsorption in biofilm samples. Based upon 208
experimental results obtained during the current study (Figures 2, 3 and 5), 25-day 209
samples were employed for these analyses. Summarily, 28 slides representing each 210
roughness coefficient were collected and individually placed in 100 ml centrifuge 211
tubes, followed by addition of increasing NH4Cl concentrations (0, 5, 10, 15, 20, 25, 212
30 mg/l) and the same concentration gradient of KH2PO4 to a final volume of 55 ml (n 213
= 84). Samples were stored at 25°C for 24 hours, centrifuged (x2000g, 4°C, 10 mins), 214
and filtered through a 0.45μm membrane. Concentrations of ammonium nitrogen and 215
phosphate in solution were measured via ISC1500 ion chromatography. The quantity 216
of ammonium nitrogen and phosphate adsorbed by the biofilm were calculated via 217
subtraction of the relevant NH4Cl and KH2PO4 concentrations. The Linear, 218
11
Freundlich and Langmuir isotherm equations (Headley et al., 1998) were employed 219
for biofilm adsorption isotherm fitting, in addition to the analytical isotherms of 220
nitrogen and phosphorus. 221
222
2.5 Modelling Biofilm Growth Kinetics 223
The biofilm growth process is typically divided into four phases after initial 224
attachment, namely, the adaptive, growth, stable, and shedding phases, with biofilm 225
growth equal to the difference between net growth and shedding (Taylor & Jaffe, 226
1990). Accordingly, based upon previous studies, the following assumptions were 227
made: (1) biofilm net growth (
1
Y
), conformed to the logistic growth model (Richards 228
et al. 1959), (2) maximum biofilm shedding is equal to maximum growth minus the 229
final biofilm quantity (Pizarro et al., 2014) and (3) net biofilm growth exhibits a linear 230
correlation with matrix roughness (R); thus the stable biofilm volume will also exhibit 231
a linear correlation with R (Gjaltema et al., 1994). Based upon assumption (1), net 232
biofilm growth (
1
Y
), is described by (Eqn. 1): 233
234
(Eqn. 235
1) 236
237
Accordingly, biofilm shedding quantity (
2
Y
), is obtained by (Eqn. 2), 238
239
12
4
2
)
2(
31
(= )
1
max T b
bT
yy
Yb be



(Eqn. 2) 240
241
Based upon assumption (3) (net biofilm growth exhibits a linear correlation with 242
matrix roughness), net growth quantity (
1
Y
) and shedding volume (
2
Y
) were amended 243
as follows: 244
2
15 1
()
1max bT
y
Y b R be

  
(Eqn. 245
3) 246
247
4
2
()
2 3 5 1
()
1
b
max T
bT
y n R y
Y b b R be


 

 



(Eqn. 4) 248
249
Growth quantity (
Y
) is equal to the difference between net growth and shedding 250
quantity (Eqn. 5): 251
4
22
()
1 2 5 3 5
11
( ) ( )
11
b
max T
max b T b T
y n R y
y
Y Y Y b R b b R
b e b e

   
 

   

   

(Eqn. 5) 252
253
Figure 1 presents a graphical representation of the biofilm growth kinetic model 254
employed in the current study. In Eqns 1 5,
Y
represents the unit-area of each 255
biofilm constituent;
1
Y
is net growth (unit-area) of each biofilm constituent;
2
Y
is 256
the measured shedding quantity (unit-area) of each biofilm constituent; R is the matrix 257
roughness;
max
y
is the maximum measured quantity (unit-area) of each biofilm 258
constituent;
()T
y
is the unit-area of each biofilm constituent based upon an infinite 259
13
growth period;
T
is the biofilm growth period;
1
b
,
2
b
,
3
b
, and
4
b
are equation 260
parameters;
n
, and
5
b
are roughness parameters. 261
The Levenberg-Marquardt (LM) algorithm, an iterative numeric minimization 262
algorithm for solving non-linear least squares problems, was used to fit the non-linear 263
relationship between measured solid particulate mass and biofilm growth time. The 264
optimization software package 1stOpt was use to iteratively run the LM algorithm and 265
generate statistical test parameters for all developed models (RMSE, DC, R, R2, χ2, F). 266
The generated F-statistic was used to adjudge model fitting accuracy; based upon 267
employed degrees of freedom (df = 9) and critical value tables, a critical F-statistic 268
value of 5.1 was employed. 269
270
3. Results 271
3.1 Solid Particulates and Biofilm Growth 272
Temporal variation associated with measured solid particulate mass per unit area 273
during the experimental period is presented in Figure 2; as shown, biofilm growth 274
typically adhered to a bacterial growth/kinetic curve, with the overall growth process 275
approximately divided into three phases, namely rapid growth, rapid shedding, and 276
dynamic stability. A relatively rapid and stable solid particulate mass increase 277
conforming to an exponential curve was exhibited from 030 days (growth phase) 278
among all three growth matrices (0.1µm, 1.0 µm and 10.0 µm), with maximum values 279
of 3.32, 3.54, and 4.22 mg cm-2, respectively. Thus, growth matrix surface roughness 280
was found to directly correlate with measured solid particulate mass (R2 = 0.85 - 0.96). 281
14
A logarithmic particulate mass decrease was noted during the 30-50 day period (rapid 282
shedding), with the aforementioned correlation remaining in place after 50-day 283
growth. After 50 days, all three matrices entered a stationary growth phase, during 284
which the measured biofilm mass associated with the 1.0-μm roughness matrix was 285
greatest (1.80 mg cm-2), while that of the 0.1-μm and 10-μm roughness matrices 286
exhibited a similar solid particulate mass (≈1.2 mg cm-2). 287
Growth model parameters based upon results of LM iterative modelling are 288
presented in Table 2. As shown, non-linear correlations indicate an appropriately 289
accurate model fit (R2 = 0.79 0.95), with the F-statistic significantly greater than the 290
calculated critical value (F >5.1) (i.e. appropriately accurate fitting function). 291
292
3.2 Extracellular Polymeric Substances and Biofilm Growth 293
Temporal variation associated with measured contents of extracellular proteins, 294
extracellular polysaccharides and total extracellular polymeric substances (EPS) are 295
presented in Figure 3. As shown, in all cases the measured mass of extracellular 296
protein, extracellular polysaccharide and EPS adhered to a bacterial growth/kinetic 297
curve over the duration of biofilm growth. As for solid particulates, the growth 298
process could be approximately divided into three distinct periods; rapid growth, rapid 299
shedding, and dynamic stability. During the first phase (030 days), contents of 300
extracellular proteins, extracellular polysaccharides and EPS increased quickly to 301
their maximum values on all growth matrices. Maximum values for all three 302
measured extracellular constituents were exhibited by biofilms cultivated on the 303
15
10-μm matrix (0.17 mg cm-2 extracellular proteins, 0.70 mg cm-2 extracellular 304
polysaccharides, and 0.88 mg cm-2 EPS), with lowest maximum values observed on 305
the 0.1-μm matrix (0.13 mg cm-2 extracellular proteins, 0.38 mg cm-2 extracellular 306
polysaccharides, and 0.53 mg cm-2 EPS). 307
During the shedding phase (3050 days), measured constituent volumes 308
decreased rapidly, with stabilization occurring from approximately day-50 (i.e. 309
initiation of stationary phase). During the stationary phase, measured constituent 310
volumes were greatest in biofilms grown on the 1.0-μm roughness matrix (0.05 mg 311
cm-2 extracellular proteins, 0.16 mg cm-2 extracellular polysaccharides, and 0.26 mg 312
cm-2 EPS), with lowest measured values associated with the 0.1-μm matrix (0.04 mg 313
cm-2 extracellular proteins, 0.10 mg cm-2 extracellular polysaccharides, and 0.17 mg 314
cm-2 EPS). 315
Nonlinear fitting of the relationship between measured EPS and biofilm growth 316
was undertaken using the LM algorithm. As shown (Table 3), all calculated R2 values 317
were ≥ 0.7 (0.7 0.99), with all F-values significantly greater than 5.1, thus indicating 318
a good model fit. 319
320
3.3 Metal Oxides and Biofilm Growth 321
Al, Fe, and Mn oxides followed a bacterial growth curve during biofilm growth, 322
thus exhibiting similar patterns to those of measured solid particulates and EPS 323
(Figure 5). During all phases of biofilm growth, the order of measured oxides 324
followed Fe>Al> Mn; maximum values were observed after 30 days on biofilms 325
16
associated with a surface roughness of 10μm (45.92 μg/cm2, 39.68μg/cm2, 326
3.44 μg/cm2), with minimum values observed on surfaces with a 0.1μm roughness 327
coefficient (35.84 μg/cm2, 28.56 μg/cm2, 2.43 μg/cm2). During the stationary phase, 328
oxides were highest in biofilms formed on surfaces with a roughness of 1.0μm 329
(17.40 μg/cm2, 14.00 μg/cm2, 1.38 μg/cm2), with lowest levels observed in those 330
formed on surfaces with a roughness of 10μm (12.70 μg/cm2, 11.30 μg/cm2, 331
0.87 μg/cm2). As for EPS, nonlinear fitting of the relationship between metal oxides 332
and biofilm growth was successfully achieved using the LM algorithm (Table 4); 333
calculated R2 values were 083 (0.83 0.97), with all F-values significantly greater 334
than 5.1 (F = 46 - 330). 335
336
3.3 Nutrient Adsorption Characteristics and Modelling 337
Measured biofilm N/P isotherms and unit contents of biofilm constituents after 338
25d growth are presented in Figure 5 and Table 5, respectively, with results of Linear, 339
Freundlich, and Langmuir isotherm modelling outlined in Table 6. Ammonium 340
nitrogen and phosphorus concentrations adhered to an expected trend i.e. adsorption 341
capacity increased in concurrence with increasing solution equilibrium concentration 342
(Fig. 4). Biofilm adsorption of both ammonium nitrogen and phosphorus were notably 343
lower in background solutions of reclaimed water than ddH2O (Fig. 4). All three 344
models for ammonium nitrogen and phosphorus adsorption exhibited high levels of 345
validation (R2 0.91). Within ammonium nitrogen models, fitting parameters Kd 346
(sorption coefficient), Sm (saturated maximum adsorption capacity), and MBC 347
17
(maximum buffering capacity) were all shown to increase in concurrence with an 348
increased matrix roughness coefficient in both background solutions (reclaimed water 349
and ddH2O). In the case of deionized water, the order of 1/n (slope of adsorption 350
isotherm i.e. adsorption stability) was 1/n1.0 > 1/n0.1 > 1/n10.0, while this was 1/n0.1 > 351
1/n1.0 > 1/n10.0 for reclaimed water. Within phosphorus models, the order of Kd was 352
Kd10 > Kd0.1 > Kd1.0, while the order of Sm was Sm0.1 > Sm10.0 > Sm1.0 for both 353
background solutions. Significantly different phosphorus modelling results were 354
found between the background solutions for both 1/n and MBC; orders of 1/n1.0 > 355
1/n10.0 > 1/n0.1, and MBC0.1 > MBC 10.0 > MBC1.0 resulted from ddH2O, while these 356
were 1/n1.0 > 1/n0.1 > 1/n10.0, and MBC10.0 > MBC0.1 > MBC1.0 for reclaimed water. As 357
shown (Table 6), reclaimed water was associated with significantly lower model 358
fitting parameters (Kd, Sm, and MBC) for both ammonium nitrogen and phosphorus 359
i.e. decreased adsorption capacity. Conversely, an increased 1/n was also associated 360
with reclaimed water, irrespective of matrix roughness coefficient. 361
362
4. Discussion 363
Biofilm formation and adhesion are significantly associated with numerous 364
factors including hydrological conditions, matrix type, nutrition level, and light, with 365
growth matrix surface roughness recognized as a particularly important variable (Tang 366
et al., 2013). Results from the current study show that biofilm growth adheres to a 367
bacterial growth curve (Fig. 2), characterized by rapid growth (0 30 days), rapid 368
shedding (30 50 days), and dynamic stability (>50 days). These findings are 369
18
mirrored and substantiated by previous studies which have investigated the condition 370
and duration of biofilm formation in water supply systems and found that biofilms 371
formed a stable microbial community via an 372
attachment-growth-shedding-reattachment cycle (Wimpenny, 1996; Hall-Stoodley et 373
al., 2004). Typically, during the rapid growth phase, microbial mass and diversity rise 374
quickly, leading to increased EPS secretion, solid particulate adsorption, and 375
subsequent biofilm proliferation. Rapid shedding is characterized by inhibited nutrient 376
transfer and resultant microbial die-off; thus, EPS secretion decreases, leading to a 377
lack of adhesion and subsequent shedding. This is followed by dynamic stability 378
whereby microbial mass and diversity remain relatively constant, with the concurrent 379
processes of new biofilm attachment and mature biofilm exfoliation occurring in 380
relative equilibrium (Hall-Stoodley et al., 2004; Lear & Lewis, 2012). 381
Findings from the current study indicate that biofilm growth is represented by a 382
dynamically balanced process of growth-shedding-regrowth, which has been 383
appropriately characterized by the established model. The developed model adheres to 384
the assumption that biofilm growth is equal to the difference between net growth and 385
shedding, with this relationship summerised in terms of surface roughness (R) as 386
follows: when R = 0.1μm, n > 0 and when R 1.0μm, n 0; thus, the matrix surface 387
was conducive to biofilm shedding and impeded attachment when R = 0.1μm. 388
Maximum solid particulate contents of 3.32, 3.54, and 4.22 mg cm-2, were 389
associated with 0.1μm, 1.0μm, and 10.0μm surface roughness coefficients, 390
respectively (Fig. 2). Previous studies of biofilm attachment to aquatic plant and 391
19
artificial substrate surfaces in Chinese freshwater lakes have reported solid particulate 392
contents occurring within the range 1.5 2.9 mg/cm2 (Yang, 2005; Wang et al., 393
2013a); Yang (2005) has reported mean solid particulate contents of 2.35 mg/cm2 in 394
biofilms cultivated on glass slides similar to those used in the current study. 395
Accordingly, it may be concluded that biofilms occurring in reclaimed water are 396
associated with elevated solid particulate volumes, with findings from the current 397
study indicating that these may be as much as 50% higher, depending on the biofilm 398
growth matrix. During the active growth phase, measured biofilm constituent contents 399
were found to be greatest in biofilms grown on 10.0μm surface roughness matrices 400
(Figure 3), thus indicating elevated biofilm growth rates, as previously reported by 401
Wang et al. (2016). This occurs due to the increasing adhesive capacity of nutrients 402
and microorganisms in concurrence with an increasing effective surface area (Shafagh, 403
1986). 404
Extracellular polymeric proteins were found to represent the primary biofilm 405
constituent; this is significant as EPS composition and quantity have been shown to 406
affect biofilm porosity, diffusivity, adsorption, and microbial metabolism (Vogt et al., 407
2013). Maximum measured extracellular protein, extracellular polysaccharide and 408
total EPS contents of 0.17, 0.70, and 0.88 mg/cm2 (40, 165, and 208 mg/g as solid 409
particulates), respectively, were found in biofilms from Olympic Lake (Figure 3). 410
Zhang (2010) has previously shown that the content of extracellular polysaccharides 411
in a biofilm reactor initially increase rapidly, followed by a subsequent decrease and 412
stabilization, similar to overall trends found in the current study. Zhang (2010) also 413
20
reported maximum extracellular polysaccharides occurring within the range 100 120 414
mg/g i.e. 37-65% lower than results from the present study. Analogous experiments 415
carried out in a ddH2O background corresponded with previous studies i.e. measured 416
contents of solid particulates and EPS were significantly higher in reclaimed water. 417
This is primarily due to the significantly elevated (and complex) organic content 418
associated with reclaimed water (Table 1); higher levels of suspended particulate 419
matter and subsequently available nutrients result in proliferation of both microbial 420
mass and diversity within biofilms (Hall-Stoodley et al., 2004; Flemming & 421
Wingender, 2010). 422
Several studies have shown that the presence of metal oxides varying trophic 423
levels will significantly influence surface adsorption processes in water and soils 424
(Perret et al., 2000; Dong et al., 2005; Wei et al., 2011; Huang & Liu, 2013). 425
Accordingly, Al, Fe and Mn oxide variations during biofilm growth were investigated; 426
all three adhered to the bacterial growth curve during biofilm cultivation, with an 427
overall pattern similar to that exhibited by measured solid particulate mass (Figure 5). 428
Measured quantities of both EPS and metal oxides were positively correlated with 429
biofilm nutrient adsorption, with results also indicating that biofilm constituents 430
increase in concurrence with increasing growth surface roughness; the highest 431
experimental roughness coefficient (10.0μm) was associated with absorption of 432
significantly larger volumes of organic and inorganic charged colloids. Tsuneda et al. 433
(2003) have shown that bacterial cells within biofilm samples are anionic due to the 434
existence of negative charge groups on their surface and elevated numbers of anionic 435
21
groups existing within EPS. Thus, in the current study, biofilms favored adsorption of 436
positively charged NH4+. Additionally, biofilms also comprise nitrifying and 437
denitrifying bacteria, resulting in both denitrification and dephosphorylation 438
(Paniagua-Michel & Garcia 2003; Wang et al., 2016). Finally, it is likely that Fe3+ and 439
Al3+ present in solution will combine with PO43- to form insoluble compounds 440
conducive to phosphorus adsorption (Olivieri et al., 2014). Modelling results (Table 6) 441
show that biofilm adsorption of ammonium nitrogen and phosphorus decreased in 442
reclaimed water as characterized by a decrease in the fitting parameters Kd, Sm and 443
MBC; thus, nutrient adsorption by biofilms are adjudged to be ecologically beneficial, 444
adding to the self-purification capacity of the waterbody. The observed increase in 445
nonlinear parameter 1/n (absorption stability) suggests greater fluctuations of the 446
adsorption curve, leading to decreased adsorption stability. This illustrates both 447
inhibition of biofilm nutrient adsorption and a reduction in the stability of the 448
adsorption process due to increased competitive adsorption. Reclaimed water 449
represents a complex mixture of myriad substances, in which elevated concentrations 450
of ions and organic materials compete for ammonium and phosphorus adsorption sites, 451
thus resulting in competitive adsorption (Wang et al., 2013b). Further studies are 452
required to further elucidate the inhibitory mechanisms associated with biofilm 453
growth and nutrient adsorption in reclaimed water. Based upon results of the current 454
study, it is concluded that glass slide cultivation of biofilms is an effective approach to 455
biomonitoring urban lakes utilizing reclaimed water, with a cultivation period of 456
approximately 50 days deemed appropriate. Moreover, biofilm growth associated with 457
22
a growth matric surface roughness of 10μm was fastest and therefore most 458
ecologically sensitive (i.e. conservative biomonitoring approach). 459
It is important to note that, within the context of ecosystem health assessment, the 460
current study comprised some inherent limitations, instead focusing on biofilm 461
growth kinetics in a reclaimed wastewater background. The current study did not 462
include eco-toxicological analyses, and thus only indicative conclusions pertaining to 463
ecological health may be made. Future work should concentrate on biofilm growth 464
kinetics and responses to the presence of ecologically harmful compounds, in addition 465
to human toxins and pathogens including heavy metals, PAHs, urban pesticides, and 466
endocrine disruptors. Additionally, future work is required to improve current 467
understanding of biofilm formation, structure and contaminant purification capacity in 468
order to make further recommendations pertaining to their use in ecological health 469
assessment. 470
5. Conclusions 471
The growth characteristics of biofilms on multiple growth matrix surfaces and 472
their effects on nutrient (NH4-N and P) adsorption were investigated. Results indicate 473
that biofilm constituent concentrations (solid particulates, metal oxides, and EPS) 474
adhere to a bacterial growth curve, thus mirroring measured biofilm growth in 475
reclaimed water. Biofilm solid particulates were significantly greater in biofilms 476
associated with reclaimed water than those cultivated in ddH2O, irrespective of 477
growth media surface roughness, while quantified biofilm constituents (Al, Mn, and 478
Fe oxides, extracellular proteins, and extracellular polysaccharides) exhibited 479
23
maximum values during the rapid growth phase. Measured biofilm constituents (EPS, 480
Metal Oxides) were significantly higher in the reclaimed water background than a 481
natural water background, thus agreeing with previous studies. Accordingly, it is 482
concluded that biofilms may be effective indicators of ecological health in aquatic 483
ecosystems characterized by the presence of reclaimed water i.e. indicators of system 484
capacity to support food production and/or provide water resources for human use. 485
However, significant further work is required to elucidate the association between 486
biofilm presence and associated kinetics, and the human health related contaminants 487
of primary concern e.g. PAHs, urban pesticides, endocrine disruptors, enteric 488
pathogens, etc. Where biofilms are used for ecological biomonitoring, a growth 489
matrix surface roughness of 10.0μm is preferable due to increased biofilm growth 490
rates and subsequently enhanced sensitivity to ecological variations. The developed 491
growth model describes key biofilm constituent kinetics, while also providing 492
information pertaining to biofilm cultivation times for future biomonitoring. Overall, 493
study results show that metal oxides and EPSs are the key substances actively 494
influencing surface adsorption of biofilms in reclaimed water. Comparative 495
experiments indicate that reclaimed water not only inhibits biofilm adsorption of 496
ammonium and phosphorus, but also reduces nitrogen and phosphorus adsorption 497
stability. 498
499
Acknowledgements 500
The authors gratefully acknowledge financial support from the National Natural 501
24
Science Fund of China (No. 51321001), the Key Project of the Beijing Eleventh-Five 502
Year Research Program (No. D090409004009004), Department of Water Resources, 503
Social Research Project (No. 201401054), and the Special Fund for Water 504
Conservancy Scientific Research in the Public Interest (No. 201001067). The authors 505
would also like to thank the anonymous reviewers whose insightful comments and 506
recommendations helped to improve the final manuscript. 507
508
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634
Figure 1. Schematic outlining the employed biofilm growth kinetic model
Figure
Figure 2. Measured and fitted (Solid particulate mass growth model) solid particulate mass per unit
area during 58-day biofilm growth
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5
5.0
0 10 20 30 40 50 60
Particulate Mass (mg/cm^2)
Growth Days
0.1μm (Measured)
0.1μm (Fitted)
1.0μm (Measured)
1.0μm (Fitted)
10.0μm (Measured)
10.0μm (Fitted)
Figure 3. Measured and fitted (growth models) (a) extracellular polysaccharide,
(b) extracellular protein, and (c) total EPS contents per unit area during 58-day biofilm growth
Figure 4. Measured and fitted (growth models) (a) Al oxide, (b) Fe oxide, and (c) Mn oxide contents
per unit area during 58-day biofilm growth
Figure 5. Biofilm adsorption isotherms and analytical isotherms of NH4-N (a) and P (b) (DW,
ddH2O; RW, reclaimed water)
Table 1. Measured lakewater chemistry during 58-day biofilm cultivation period
Table 2. Solid particulate mass growth model parameters based upon results of Levenberg-
Marquardt iterative modelling (1stOpt)
R (μm)
b1
b2
b3
b4
b5
n
R2
F
Yg
0.1
55
55
55
0.24
1.2×10-51
91
10.60
1.67
0.79
49
1.0
1.08
0.13
0.91
108
10.0
0.11
0.09
0.95
193
Note: Yg, weights of solid particulates per unit area; R, roughness; R2, decisive coefficient of fitting function.
Time
d
T
°C
pH
NH4+
mg/L
NO3-
mg/L
TN
mg/L
TP
mg/L
CODCr
mg/L
BOD
mg/L
DO
mg/L
Ca
mg/L
Mg
mg/L
5
25
7.22
5.4
5.92
12.3
0.02
14.2
6.3
6.74
42
26.8
10
26
7.42
7.2
4.78
13.8
0.03
30.2
6.6
7.22
40.1
27.6
15
26
7.38
12.9
3.67
17.1
0.03
29
6.2
5.78
36.5
27.9
20
26
7.29
18.2
2.27
22.8
0.01
28.6
6
4.42
34.2
27.3
25
30
7.97
0.128
0.94
6.24
0.09
12.5
6.9
6.9
41.5
29.6
30
32
7.97
0.432
1.86
6.78
0.09
17.5
2.4
6.83
39.8
29.6
37
30
8.00
0.776
0.37
5.72
0.16
16.2
3.4
6.96
40.4
27.2
44
33
8.13
0.668
1.12
8
0.06
2.1
10.1
6.92
38.3
25.2
51
33
8.20
0.372
2.19
6.63
0.12
11.7
2.4
6.82
38.3
25.2
58
29
8.19
0.608
2.74
12
0.1
8.1
1.6
7.14
40.4
25.2
P
Y
Table
Table 3. Extracellular Polymeric Substance (EPS) growth model parameters based upon results of
Levenberg-Marquardt iterative modelling (1stOpt)
R/μm
b1
b2
b3
b4
b5
n
R2
F
Ypro
0.1
15
0.13
1.1×106
10
11.80
0
0.84
57
1.0
1.37
0.33
0.80
40
10.0
0.14
0.08
0.70
22
Ypol
0.1
161
0.22
1.2×101
11
14.30
10.00
0.82
52
1.0
1.41
0.25
0.96
263
10.0
0.14
-0.12
0.99
573
YtEPS
0.1
90
0.21
0.6×101
16
12.90
10.00
0.92
98
1.0
1.33
0
0.95
167
10.0
0.123
0.08
0.96
271
Note: Ypro, weights of extracellular proteins per unit area; Ypol, weights of extracellular polysaccharides per unit area; YtEPS,
weights of total EPS per unit area; R, roughness; R2, decisive coefficient of fitting function.
Table 4. Metal oxide growth model parameters based upon results of Levenberg-Marquardt iterative
modelling (1stOpt)
R/μm
b1
b2
b3
b4
b5
n
R2
F
YAl
0.1
27
0.18
1.3×10-36
23
12.30
2.50
0.83
46
1.0
1.21
0
0.96
231
10.0
0.12
0.05
0.95
183
YMn
0.1
56
0.21
1.8×10-23
45
11.80
2.50
0.85
51
1.0
1.09
0
0.97
317
10.0
0.11
0.05
0.90
137
YFe
0.1
39
0.20
2.1×10-50
31
11.40
2.50
0.85
47
1.0
1.15
0
0.97
330
10.0
0.12
0.05
0.94
120
Note: YAl, weights of Al oxide per unit area; YMn, weights of Mn oxide per unit area; YFe, weights of Fe oxide per unit area;
R, roughness; R2, decisive coefficient of fitting function.
P
Y
P
Y
Table 5. Measured unit contents of EPS and metal oxides on day-25 (mg/g)
Al
oxide
Mn
oxide
Fe
oxide
Extracellular
proteins
Extracellular
polysaccharides
Total
EPS
0.1 µm
8.6
0.7
10.8
30.9
121.0
151.9
1.0 µm
9.3
0.8
11.2
45.7
138.8
184.5
10 µm
9.8
0.8
11.4
47.5
159.4
206.9
Table 6. Validation (Fitting) results of Linear, Freundlich, and Langmuir isotherm modelling
nitrogen and phosphorus adsorption isotherms and change rate of fitting parameters
N/P
Background
Linear
Freundlich
Langmuir
a
Kd
R2
1/n
LnK
R2
Sm
MBC
R2
NH4+
0.1 μm
DW
156.22
73.34
-24.9
0.96
0.73
36.3
5.12
0.92
2000
-16.7
172.41
-67.7
0.93
RW
-138.49
55.06
0.92
1.00
3.69
0.91
1667
55.56
0.91
1.0 m
DW
-102.79
132.91
-51.9
0.96
0.89
4.5
5.04
0.90
2500
-20.0
188.68
-57.2
0.93
RW
-68.54
63.89
0.96
0.93
4.23
0.92
2000
80.65
0.95
10 μm
DW
931.41
171.44
-39.4
0.92
0.57
36.3
6.60
0.93
5000
-33.3
769.23
-72.9
0.94
RW
124.37
103.86
0.95
0.78
5.30
0.91
3333
208.33
0.91
PO43-
0.1 μm
DW
673.86
69.57
-68.2
0.94
0.44
55.7
6.28
0.98
2000
-54.6
625
-90.9
0.96
RW
95.00
22.12
0.96
0.68
4.25
0.97
909
57.14
0.97
1.0 m
DW
-34.91
34.11
-45.7
0.95
0.92
1.1
3.62
0.96
10000
-50.1
33.22
-35.7
0.98
RW
21.34
18.509
0.99
0.93
3.18
0.99
5000
21.36
0.99
10 μm
DW
775.50
74.39
-45.6
0.92
0.52
19.2
6.17
0.96
3333
-40.0
357.14
-63.6
0.99
RW
336.68
40.47
0.96
0.62
5.22
0.99
2000
129.87
0.99
Note: DW, deionized water; RW, reclaimed
Constituent
R/μm
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