phosphate release involving paos activity during anaerobic fermentation of ebpr sludge and the...

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Phosphate release involving PAOs activity during anaerobic

fermentation of EBPR sludge and the extension of ADM1

Ruyi Wang, Yongmei Li ⇑, Wenling Chen, Jinte Zou, Yinguang Chen

State Key Laboratory of Pollution Control and Resource Reuse, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China

h i g h l i g h t s

Adding acetate facilitates PHAsynthesis, which accelerates sludge

disintegration.

A new model for anaerobic

fermentation of EBPR sludge based on

ADM1 is established.

PAOs decay rate is determined, and

the model contains PHA storages on 4

VFA species.

Fractions of VFA species from PHA

lysis vary with initial acetate

concentration.

Phosphorus release and precipitation

processes are included in the new

model.

g r a p h i c a l a b s t r a c t

0

1

2

3

4

5

6

7

0 1 2 3 4 5 6 7

l n ( R t ) ( g P m - 3 h - 1 )

Time(d)

ADM1 extension

bPAO

= 0.35 d-1

PAOs

PO4

HAc, HPr, HBu, HVa

PHA

PP

Precipitation

NH4

Mg

K

Composite particulates

Carbohydrates, Proteins,

Lipids

Disintegration

Hydrolysis

Acidogenesis

Acetogenesis

a r t i c l e i n f o

Article history:

Received 24 January 2015

Received in revised form 7 October 2015

Accepted 27 October 2015

Available online 7 November 2015

Keywords:

Phosphate release

Enhanced biological phosphorus removal

Sludge fermentation

Modification of ADM1

Polyhydroxyalkanoate

a b s t r a c t

Anaerobic fermentation of the enhanced biological phosphorus removal (EBPR) sludge was investigated

in terms of phosphate release and volatile fatty acids (VFAs) production regarding polyphosphate accu-

mulating organisms (PAOs) activity. PAOs decay rate during fermentation was determined as

0.35 ± 0.03 d1. Sludge lysis was enhanced with an increase in polyhydroxyalkanoate (PHA) content.

Moreover, the phosphate release profiles and the VFAs production as well as the individual VFA fractions

varied with different acetate concentrations added initially. Based on these observations, anaerobic

digestion model No. 1 was extended and modified by introducing: (1) processes that PAOs store 4 VFA

species as PHA, which can be degraded into varied fractions of individual VFA in dependence on PHA

composition, (2) the effect of PHA content on disintegration rate, and (3) phosphorus precipitation.

The proposed model adequately fitted a multi-experiment, multi-variable data set, indicating that it plays

an important role in predicting phosphate and VFAs variations during EBPR sludge fermentation.

2015 Elsevier B.V. All rights reserved.

1. Introduction

Phosphorus (P) removal from wastewater is a crucial procedure

to limit the growth of aquatic plants and algae, and thus to control

eutrophication. On the other hand, phosphorus is a non-renewable,

non-interchangeable finite resource. It is predicted that the mined

phosphate rocks will be exhausted within 90 years [1]. Fortunately,

waste streams offer a compelling opportunity to recover phospho-

rus, and this could theoretically satisfy 15–20% of world demand

for phosphate rock [2].

Enhanced biological phosphorus removal (EBPR) process has

become a well-established process and is currently applied in

many full-scale wastewater treatment plants (WWTPs) [3]. In the

EBPR process, polyphosphate accumulating organisms (PAOs) cap-

able of storing phosphate as intracellular polyphosphate are lar-

gely responsible for transfer of phosphorus from the liquid phase

to the sludge phase. The process inevitably produces a great deal

http://dx.doi.org/10.1016/j.cej.2015.10.110

1385-8947/ 2015 Elsevier B.V. All rights reserved.

⇑ Corresponding author. Tel.: +86 021 65982692; fax: +86 021 65986313.

E-mail address: [email protected] (Y. Li).

Chemical Engineering Journal 287 (2016) 436–447

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of excess sludge, which is not only a perfect resource to produce

biogas or soluble carbon source but also rich in phosphorus, nor-

mally 0.06–0.15 mg P mg VSS1 [4].

One of the options to recover phosphorus from EBPR sludge is to

get magnesium ammonium phosphate (struvite) from fermented/

digested sludge liquor through chemical precipitation [2,5]. During

anaerobic treatment of EBPR sludge, most of the phosphorus stored

as polyphosphate and part of the phosphorus present in theorganic matter are released. It was reported that more than 80%

of the total biologically-bound phosphorus that had been removed

previously during EBPR treatment was released during anaerobic

digestion [6]. In most cases, a complete release of the stored

polyphosphate was found [7,8]. Studies revealed that the observed

phosphorus release that occurred during anaerobic sludge diges-

tion was determined by such factors as the total phosphorus con-

tent in sludge, the local wastewater conditions, and the complex

chemistry [6,9–11]. One of the complications is in-reactor repre-

cipitation of phosphorus, which could limit phosphorus availability

in the liquid phase and also lead to blockages in pipes and pumps

of sludge treatment facilities [2]. In order to limit undesirable in-

reactor precipitation and to enhance phosphorus recovery, it is

important to investigate phosphate release during anaerobic treat-

ment of EBPR sludge. However, to our best knowledge, phosphate

release during fermentation of EBPR sludge is still lack of under-

standing, especially the phosphate release behavior regarding the

activity of PAOs.

To date, the processes of phosphate release during anaerobic

treatment of P-rich sludge have been considered only in a few

models despite that a dynamic model can help to apprehend the

complexity of the processes and to indentify optimal working

strategies. BNRM1 and its extension BNRM2, which include biolog-

ical C, N, and P removal processes and simplified anaerobic sludge

treatment processes, were proposed to simulate a whole WWTP

[12,13]. An extension of UCTADM1 model was proposed by includ-

ing phosphate systems during anaerobic digestion of high P con-

tent sludge [14]. Processes of phosphate release and precipitation

are included in the anaerobic digestion model in Biowin software.However, processes such as phosphate release with respect to

PAOs activity, and production of volatile fatty acids (VFAs) from

polyhydroxyalkanoate (PHA) lysis are not considered in these

models. Furthermore, biological processes in these models are sim-

plified compared with anaerobic digestion model No. 1 (ADM1)

developed by Batstone et al. [15]. The most well established

ADM1 is a unified base for modeling of anaerobic processes. Some

adjustments and extensions based on ADM1 have been made to

deal with different situations [16,17]. Surprisingly, no modification

of ADM1 can be found to model phosphate variation since phos-

phorus is not included in ADM1.

The aim of this study is to investigate phosphate release and

variations of VFAs regarding PAOs activity. A model was estab-

lished for EBPR sludge fermentation by incorporating phosphatevariation processes into ADM1 based on experimental results.

The simulation results of the extended ADM1 were compared to

experimental data obtained in a set of batch experiments for EBPR

sludge fermentation with the addition of acetate. The new model is

a reliable tool for better understanding and optimization of EBPR

sludge treatment to enhance phosphorus recovery.

2. Materials and methods

2.1. Operation of EBPR system

Two sequencing batch reactors (SBR) with a working volume of

16 L were applied to culture P-rich EBPR sludge. They were contin-uously operated under alternating anaerobic/aerobic conditions,

on the basis of a 6-h operation cycle. The operation of the SBRs

was described in the Supplementary Information.

After more than 3 months, the reactors were running in a steady

state with MLSS concentrations of 2833 ± 167 g m 3. Phosphorus

removal was relatively stable (97 ± 3%), and the phosphorus con-

tent of sludge was 0.12 ± 0.01 g P g VSS1. Performance of the SBR

systems in terms of PO4-P and acetate variations during a working

cycle is shown in Fig. S1 in the Supplementary Information. Thetypical profiles of PO4-P and acetate concentrations were consis-

tent with the expected behavior of enriched PAOs, implying that

the EBPR activated sludge was cultured well.

2.2. Measurement of VFAs uptake parameters

Sludge was taken at the end of the aerobic phase of the SBR sys-

tems and centrifuged. The supernatant was discarded and the

solids were resuspended in a solution that had the same composi-

tion as the SBR feed, except that it did not contain C and P sources.

220 mL of the resuspended solids were placed in a 250 mL serum

bottle that was mixed by a magnetic stirrer. Then, different VFA

sources (acetate, propionate, butyrate, and valerate) were added

into different bottles. The temperature of the reactors were main-tained at 35 ± 2 C, and the pH were controlled at 7 by adding

NaOH or HCl. Samples were frequently taken for the determination

of VFAs and PO4-P during the anaerobic experiments. The batch

experiments were performed in triplicate, and their averages are

reported.

2.3. Experiment for PAOs activity decay during anaerobic fermentation

The sludge was withdrawn from the SBR systems (at the end of

the aerobic phase) and had been concentrated by gravity for 12 h

before use. The experiment was conducted in 250 mL serum bot-

tles which were placed in a shaker (35 ± 1 C, 160 rpm). Each bottle

contained 220 mL concentrated sludge. Anaerobic conditions were

achieved by purging with nitrogen gas for 20 s. During the anaero-bic fermentation, pH was controlled at 7 by adding NaOH.

The decay rate of PAOs during anaerobic fermentation was cal-

culated on the basis of measuring the maximal phosphate release

rate (PRR). The interval of 0, 1, 2, 3, 5, and 7 days were selected

to measure the maximal PRR. In order to ensure sufficient

polyphosphate for phosphate release under anaerobic conditions

and avoid limiting the measured anaerobic rates, sludge sample

in one bottle at each interval was exposed to one cycle of aerobic

and subsequent anaerobic conditions according to the method of

[18]. Samples during the anaerobic condition were collected fre-

quently for analysis of soluble phosphate. The experiment was

repeated three times, their averages are reported.

The decay rate of PAOs was calculated based on the following

equation [19].

b ¼ ln Rt R0

1

t dð1Þ

where, b is the decay rate of PAOs, R0 is PRR before fermentation, Rt is PRR at fermentation time t d.

2.4. Anaerobic fermentation of EBPR sludge

The experiment was conducted in identical serum bottles with

a volume of 600 mL maintained in a shaker (35 ± 1 C, 160 rpm).

Each serum bottle contained 380 mL of the concentrated sludge

taken from the SBR systems (at the end of the aerobic phase). Acet-

ate was added to make the initial calculated acetate concentration

of 100, 300, 500, and 1000 g COD m3

, and labeled as Ac-100,Ac-300, Ac-500, and Ac-1000, respectively. The bottle without

R. Wang et al. / Chemical Engineering Journal 287 (2016) 436–447 437

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addition of acetate was labeled as Control. Anaerobic conditions

were achieved by purging with nitrogen gas for 20 s. The pH value

in each bottle was controlled at 7 by adding NaOH after samples

were taken for analysis. Samples from the bottles were immedi-

ately filtered through a Whatmann GF/C glass microfiber filter.

The filtrate was analyzed for chemical oxygen demand (COD),

VFAs, PO4-P, NH4-N, and metal ions. The filter residue was assayed

for volatile suspended solids (VSS) and PHA. Sludge samples beforefermentation and after 7 days operation were taken for testing

viable and dead cells. The batch experiments were performed in

triplicate, and their averages are reported.

2.5. Analytical methods

VFAs were measured by gas chromatography (6890N, Agilent,

USA) [20]. The analyses of COD, PO4-P, NH4-N, and VSS were

conducted according to standard methods [21]. Metal ions were

determined by inductively coupled plasma emission spectrometry

(ICP 720ES, Agilent, USA). The analyses of poly-3-hydroxybutyrate

(PHB), poly-3-hydroxyvalerate (PHV), and poly-3-hydroxy-2-

methylvalerate (PH2MV) were conducted by gas chromatography

(Trace GC Ultra, Thermo Fisher, USA) according to the method of [22]. The total PHA was calculated as the sum of measured PHB,

PHV, and PH2MV.

The LIVE/DEAD Bac lightTM bacterial viability kit (L7012) was

used to discriminate between viable and dead cells. With an appro-

priate mixture of the SYTO 9 and propidium iodide stains, bacteria

with intact cell membranes stain fluorescent green, whereas bacte-

ria with damaged membranes stain fluorescent red. The sludge

samples were examined visually by fluorescence microscopy

(Nikon Eclipse 80i, Japan), and photos were taken. Then the ratios

of green fluorescence to total fluorescence (red + green fluores-

cence) were determined, which are equivalent to the ratio of viable

cells to total cells [23].

2.6. Modeling approach

Modeling and simulation were carried out using the WEST soft-

ware (Mikebydhi.com). Most initial substrate concentrations were

directly obtained from the experimental measurements. The initial

values that could not be measured directly were calculated from

the available values based on the COD, phosphorus and nitrogen

balance, and were determined by fitting to the curves of measured

variables. Except for the measured differences, the same initial

concentrations were applied in every batch test simulation. The

goodness-of-fit between experimental and simulated values for a

variable was quantified by calculating Theil’s inequality coefficient

(TIC), shown as Eq. (2) [24].

TIC jk ¼

ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ffiffiffiffiffiffiffiffiffi1

N data jk

PN data jki¼1

ð yijk ^ yijkÞ2

q ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi

1

N data jk

PN data jki¼1

ð yijkÞ2

q þ

ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ffiffiffi1

N data jk

PN data jki¼1

ð^ yijkÞ2

q ð2Þ

where TIC jk is the goodness-of-fit between experimental and simu-

lated values for variable j in bottle k , y ijk represents the measured

value of variable j, in bottle k, at time i, and ^ yijk is the corresponding

simulated value. Variable j from bottle k has N data jk measured values

at successive different times i. TIC allows judging whether there is a

considerable difference between simulated and measured results. A

value of the TIC less than 0.3 indicates a good agreement with mea-

sured data.

Confidence intervals of the estimated parameters were calcu-

lated through a method based on the Fisher Information Matrix(FIM) considering a confidence level of 95% [25,26].

3. Results and discussion

3.1. Activity decay of PAOs during anaerobic fermentation

The activity of PAOs during anaerobic fermentation decreased

steadily (Fig. 1). The average decay rate of PAOs was determined

as 0.35 ± 0.03 d1. Such rate was higher than the default value of

0.2 d

1

in activated sludge model No. 2D (ASM2D) [27] and0.18 d1 obtained by Hao et al. [19]. The difference may be caused

by the different operation conditions of decay experiments. The

decay experiment in the present study was carried out under

anaerobic condition at 35 ± 1 C, while their decay rates were

obtained under aerobic condition at around 20 C. Lopez-Vazquez

et al. [28] found that anaerobic maintenance coefficient of PAOs

continuously increased with a rise of temperature, leading to

increased energy consumption. This implies that the decay rate

of PAOs increases as the temperature rises. Therefore, the higher

decay rate was mainly caused by the higher temperature, although

the absence of oxygen might slightly reduce the decay rate [29]. It

is known that PAOs eventually die under anaerobic condition since

they require aerobic condition to supply a terminal electron accep-

tor for their growth. However, PAOs can derive their maintenance

energy from degradation of cellular materials. As a result, PAOs are

able to withstand anaerobic condition over a period of time. The

determined decay rate in this study indicates that PAOs are still

active over a few days after entering the anaerobic fermentation

reactor, and capable of following the same P-release mechanisms

as in the anaerobic reactor in EBPR system.

3.2. Variation of PHA content and its influence on sludge lysis

PHA content increased slowly within the first day when there

was no additional acetate (Fig. 2a), and the synthesized PHA

amount remarkably increased in 2 h with the increase of initial

acetate concentration (Fig. 2b–e). The more acetate added initially,

the quicker PHA reached the peak value, and the greater the peakvalue was. Obviously, PO4-P concentrations increased during the

first day, and the more acetate initially added the faster phosphate

concentration increased (Fig. 2). On the contrary, acetate concen-

trations in the bottles with high initial acetate concentrations

decreased sharply to a very low level in 2 h (Fig. 3). The quick

release of phosphate in the bottles with high acetate concentration

resulted from the P-release mechanisms, i.e. PAOs took up VFAs

and stored them as PHA, and meanwhile polyphosphate was

decomposed to generate the energy for these biotransformations.

It was reported that microbial cells became extremely fragile

after accumulation of large amount of PHA inside the cell [30].

y = -0.35 x + 5.59

R² = 0.97

0

1

2

3

4

5

6

7

0 1 2 3 4 5 6 7 8

l n ( R t ) ( g P m - 3 h - 1 )

Time (d)

Fig. 1. Decreasing trend in the activity of PAOs during anaerobic fermentation of EBPR sludge.

438 R. Wang et al. / Chemical Engineering Journal 287 (2016) 436–447


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Wang et al. [31] also pointed out that increase of sludge PHA was

beneficial to cell disruption. Due to decay in this study, both the

VSS concentrations and the fractions of viable cells (shown in

Fig. 4) decreased after 7 days of EBPR sludge fermentation com-

pared with those before fermentation (VSS: 11.2 ± 0.4 kg m3

, frac-tion of viable cells: 93 ± 1%). It is obvious that both the VSS

concentration and the fraction of viable cells decreased with the

increase of initial acetate concentration (Fig. 4 and Supplementary

Information – Fig. S2). It also should be noticed that on the final

day, soluble COD (SCOD) excluding the amount of acetate initially

added increased with the increase of initial acetate concentration.

For example, the observed SCOD increased from

4.16 ± 0.18 kg COD m3 for Control to 6.22 ± 0.29 kg COD m3 for

Ac-1000 on the final day (Supplementary Information – Fig. S3).

Therefore, it can be demonstrated that the increased PHA content

accelerates sludge disintegration and the following lysis, resulting

in the increased fraction of bacteria with damaged membranes and

the reduced VSS concentration after 7 days of EBPR sludge fermen-

tation, which thereby caused an increase in SCOD excluding theamount of acetate initially added.

3.3. Model development

To handle EBPR sludge fermentation, a new model was devel-

oped in the framework of ADM1, applying the same structure,

nomenclature, and units [15]. Table 1 presents the componentsintroduced into ADM1. Stoichiometric matrix and kinetic rate

equations for the proposed and modified processes are shown

respectively in Tables 2 and 3. Parameters corresponding to these

processes are defined in Table 4.

In the proposed model, PAOs are still active after entering into

the anaerobic environment and able to take up VFAs and store

them as PHA by utilizing the energy from the hydrolysis of

polyphosphate. PAOs and their storage products (PHA and

polyphosphate) are subject to separate decay processes. It should

be emphasized that anaerobic uptake of VFAs by PAOs in this

model has been specified into 4 different processes based on 4

VFA species (acetate, propionate, butyrate, valerate). The uptake

rates of different VFAs are differed by introducing separate param-

eters, and different parameters were also introduced for the ratiosof PO4-P release to PHA storage on different VFAs. The proposed

0

0.05

0.1

0.15

0.2

0.25

0.3

0

0.2

0.4

0.6

0.8

1

1.2

0 1 2 3 4 5 6 7 8

P H A ( k g C

O D k g S S - 1 )

P O 4 - P

( k g P m - 3 )

Time (d)

PO -P TIC=0.02

Measured PO -P

PHA TIC=0.03

Meausred PHA

0

0.05

0.1

0.15

0.2

0.25

0.3

0

0.2

0.4

0.6

0.8

1

1.2

0 1 2 3 4 5 6 7 8

P H A ( k g C O D k g S S - 1 )

P O 4 - P

( k g P m - 3 )

Time (d)

PO -P TIC=0.03

Measured PO -P

PHA TIC=0.03Measured PHA

0

0.05

0.1

0.15

0.2

0.25

0.3

0

0.2

0.4

0.6

0.8

1

1.2

0 1 2 3 4 5 6 7 8

P H A ( k g C O D k g S S - 1 )

P O 4 - P ( k g P m - 3 )

Time (d)

PO -P TIC=0.02

Measured PO -P

PHA TIC=0.03

Measured PHA

0

0.05

0.1

0.15

0.2

0.25

0.3

0

0.2

0.4

0.6

0.8

1

1.2

0 1 2 3 4 5 6 7 8

P H A ( k g C O D k g S S - 1 )

P O 4 - P ( k g P m - 3 )

Time (d)

PO -P TIC=0.04

Measured PO -P

PHA TIC=0.04

Measured PHA

0

0.05

0.1

0.15

0.2

0.25

0.3

0

0.2

0.4

0.6

0.8

1

1.2

0 1 2 3 4 5 6 7 8

P H A ( k g C O D k g S S - 1 )

P O 4 - P ( k g P m - 3 )

Time (d)

PO -P TIC=0.04

Measured PO -P

PHA TIC=0.04

Measured PHA

(a) Control (b) Ac-100

(c) Ac-300 (d) Ac-500

(e) Ac-1000

Fig. 2. Experimental and simulated variations of PO4-P concentration and PHA content in the batch fermentation tests at different initial acetate concentrations. TIC

coefficients for model fitting are indicated in every plot.


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pathway of anaerobic PHA synthesis and degradation shows that

the type of VFA taken up by PAOs determines the composition of

PHA stored, which subsequently affects the VFA species produced

from PHA degradation (Supplementary Information – Fig. S4).

PHB is degraded to acetate and butyrate, while PHV is mainly bio-

converted to acetate, propionate, and valerate. Generally, in this

model PHA is degraded into VFAs, and the fraction of individual

VFA generated from PHA lysis varies with the change of PHA com-

position. This variation can be expressed by adjusting values of the

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

2.2

0 1 2 3 4 5 6 7 8

V F A s ( k g C O D m - 3 )

Time (d)

Sac TIC=0.08 Sva TIC=0.07

Measured Sac Measured Sva

0

0.2

0.4

0.6

0.81

1.2

1.4

1.6

1.8

2

2.2

0 1 2 3 4 5 6 7 8

V F A s ( k

g C O D m - 3 )

Time (d)



0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

2.2

0 1 2 3 4 5 6 7 8

V F A s ( k

g C O D m - 3 )

Time (d)



0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

2.2

0 1 2 3 4 5 6 7 8

V F A s ( k

g C O D m - 3 )

Time (d)



0

0.2

0.4

0.6

0.81

1.2

1.4

1.6

1.8

2

2.2

0 1 2 3 4 5 6 7 8

V F A s ( k g C O D m - 3 )

Time (d)

Sac TIC=0.06

Sva TIC=0.04

Measured Sac

Measured Sva

(a) Control (b) Ac-l00

005-cA(d)003-cA(c)

(e) Ac-l000

Fig. 3. Experimental and simulated variations of acetate (S ac) and valerate (S va) in the batch fermentation tests at different initial acetate concentrations. TIC coefficients for

model fitting are indicated in every plot.

0.45

0.55

0.65

0.75

0.85

0.95

6.5

7.0

7.5

8.0

8.5

9.0

9.5

10.0

10.5

Control Ac-100 Ac-300 Ac-500 Ac-1000

F r a c t i o n o f v i a b l e c e l l s ( % )

V S S ( k g m - 3 )

VSS Fract ions of viable cells

Fig. 4. VSS concentrations and fractions of viable cells after 7 days of EBPR sludge

fermentation at different initial acetate concentrations.

Table 1

Dynamic state variables introduced into the extended ADM1.

Name Description Unit

S po4 Soluble phosphate kg P m3

S Mg Magnesium ion kmol m3

S K Potassium ion kmol m3

X PAO Polyphosphate accumulating organisms kg COD m3

X PP Polyphosphate kg P m3

X PHA Polyhydroxyalkanoates kg COD m3

X Str Magnesium ammonium phosphate kg m3

X KStr Magnesium potassium phosphate kg m3


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Table 2

Stoichiometry for the extended and modified processes.

Process 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

S su S fa S ac S pro S bu S va X c S I X ch X pr X li X I S IN S IC S po4 X PP X PH

1 Disintegration 1 f si,xc f ch,xc f pr,xc f li,xc f xi,xc P

i¼712N iv i;1 P

i¼112;1723C iv i;1 P

i¼712P iv i;1

2 Hydrolysis of X ch 1 1 P

i¼112;1723C iv i;2 P Xch

3 Hydrolysis of X li 1 f fa,li f fa,li 1 P

i¼112;1723C iv i;3 P Xli

4 Lysis of X PP 1 1

5 Storage of X PHA on S ac 1 P

i¼112;1723C iv i;5 Y PO4,ac Y PO4,ac 1

6 Storage of X PHA on S pro 1 Pi¼112;1723C iv i;6 Y PO4,pro Y PO4,pro 1 7 Storage of X PHA on S bu 1

Pi¼112;1723C iv i;7 Y PO4,bu Y PO4,bu 1

8 Storage of X PHA on S va 1 P

i¼112;1723C iv i;8 Y PO4,va Y PO4,va 1

9 Lysis of X PHA Y PHA,ac Y PHA,pro Y PHA,bu Y PHA,va P

i¼112;1723C iv i;9 1

10 Decay of X PAO 1 N Xbiom N Xc P

i¼112;1723C iv i;10 PXbiom-PXc

11 Organism growth P

i¼112N iv i;11-Y xN X biom P

i¼112;1723C iv i11 P

i¼112P iv i;11 Y xP X biom

12 Decay of organism 1 NXbiom- N Xc P

i¼112;1723C iv i;12 P X biom P X c

13 Formation of

MgNH4PO4

1 31

14 Formation of

MgKPO4

31

Note: organism growth includes different processes carried out by different groups of organisms, and in these processes the stoichiometric coefficients for substrates suggested


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stoichiometric parameters: Y PHA,ac, Y PHA,pro, Y PHA,bu, and Y PHA,va, and

the sum of the 4 parameters should be 1 based on COD balance.

Since disintegration is the first step of organism lysis, it is

assumed that PHA content mainly influences the sludge disintegra-

tion step. Its rate is modified by introducing a mathematical

expression, eð f dis X PHA= X CÞ. Because the dead PAOs turn to the complex

particulate pool ( X C) in the model, the ratio X PHA= X C is applied in

eð f dis X PHA= X C Þ to describe the impact of PHA content. The expression

Table 3

Kinetic rate equations for the extended and modified processes.

Process Process rate equation q j

1 Disintegration kdise f dis X PHA= X Cð Þ X C

4 Lysis of X PP bPP X PP5 Storage of X PHA on S ac qPHA;ac

S acK S;PHA ac þS ac

S acS ac þS pro þS buþS va

X PP= X PAOK PP þ X PP= X PAO

1 X PHA= X PAO f

maxPHA

a X PAO

6 Storage of X PHA on S pro qPHA;proS pro

K S;PHA pro þS pro

S proS ac þS pro þS buþS va


1 X PHA= X PAO f

maxPHA

a

X PAO7 Storage of X PHA on S bu qPHA;bu

S buK S;PHA buþS bu

S buS ac þS pro þS bu þS va


1 X PHA= X PAO f

maxPHA

a X PAO

8 Storage of X PHA on S va qPHA;vaS va

K S;PHA v a þS vaS va

S ac þS pro þS buþS va


1 X PHA= X PAO f

maxPHA

a X PAO

9 Lysis of X PHA bPHA X PHA10 D ec ay of X PAO bPAO X PAO13 Formation of MgNH4PO4

kr;MgNH4 PO4 S 13

MgS 13

NHþ4S

13

PO34 K

13

SP;MgNH4 PO4

3

14 Formation of MgKPO4kr;MgKPO4 S

13

MgS 13

KS 13

PO34 K

13

SP;MgKPO4

3

Note: only the extended and modified rate equations are presented, the others are the same with those suggested by Batstone et al. [15]; S NHþ4is the molar concentration of

NHþ4 ; S PO34is the molar concentration of PO34 .

Table 4

Measured and estimated parameter values for the proposed model.

Parameter Value Unit Description LBd UBe Literature value

qPHA,ac 4.3a d1 Rate constant for PHA storage on S ac 1.6 5.0 3 (20 C)

f

qPHA,pro 6.7a d1 Rate constant for PHA storage on S pro 2.5 7.8 -

qPHA, bu 1.6a d1 Rate constant for PHA storage on S bu 0.6 1.9 –

qPHA,va 1.4a d1 Rate constant for PHA storage on S va 0.5 1.6 –

bPHA 0.39 d1 Rate constant for lysis of X PHA 0.1 0.6 0.2 (20 C)

f

bPP 0.55 d1 Rate constant for lysis of X PP 0.1 0.6 0.2 (20 C)

f

f maxPHA

0.7 kg COD kg COD1 Maximum ratio of PHA to active biomass 0.2 2 0.2–8.3 Cmol/Cmolg

a 2 – Exponent of PHA inhibition term 1 3 1–8.6g

kdis 0.1 d1 Disintegration rate 0.1 0.5 0.4–1h

f dis 1.7 – Factor of PHA effect on disintegration 1 2 –

K SP,MgNH4PO4 1.3 1012 – Solubility product of MgNH4PO4 6.9 10

14 2 1012 6.9 1014–1.1 1010i

Y PHA,ac Table 5 kg COD kg COD1 Fraction of S ac from PHA lysis 0 1 –

Y PHA,pro Table 5 kg COD kg COD1 Fraction of S pro from PHA lysis 0 1 –

Y PHA,bu Table 5 kg COD kg COD1 Fraction of S bu from PHA lysis 0 1 –

Y PHA,va Table 5 kg COD kg COD1 Fraction of S va from PHA lysis 0 1 –

Y PO4,ac 0.49 b

kg P kg COD1

PO4 release per PHA stored on S ac – – 0.4f

Y PO4,pro 0.36b kg P kg COD1 PO4 release per PHA stored on S pro – – –

Y PO4,bu 0.31b kg P kg COD1 PO4 release per PHA stored on S bu – – –

Y PO4,va 0.17b kg P kg COD1 PO4 release per PHA stored on S va – – –

bPAO 0.35b d1 Rate constant for decay of X PAO – – 0.2 (20 C)

f

K PP 0.01 kg P kg COD1 Saturation coefficient for polyphosphate – – 0.01f

K s,PHA_ac 0.004 kg COD m3 Saturation coefficient for S ac – – 0.004

f

K s,PHA_pro 0.004 kg COD m3 Saturation coefficient for S pro – – –

K s,PHA_bu 0.004 kg COD m3 Saturation coefficient for S bu – – –

K s,PHA_va 0.004 kg COD m3 Saturation coefficient for S va – – –

kr,MgNH4PO4 300 d1 Rate constant for MgNH4PO4formation – – 300

i

kr,MgKPO4 300 d1 Rate constant for MgKPO4 formation – – –

K SP,MgKPO4 2.4 1011 – Solubility product of MgKPO4 – – 2.4 10

11 j

P Xc 0.006 kg P kg COD1 Phosphorus content of X C – – –

P Xch 0.008 kg P kg COD1 Phosphorus content of X ch – – 0.008

k

P Xli 0.003 kg P kg COD1 Phosphorus content of Xli – – 0.003

k

P Xbiom 0.019 kg P kg COD1 Phosphorus content of Xbiom – – 0.02

f , 0.019k

P XI 0.011 kg P kg COD1 Phosphorus content of XI – – 0.01

f

P SI 0.011c kg P kg COD1 Phosphorus content of SI – – 0f

a Estimated based on measurement.b Measured in this study.c Similar to X I.d LB = lower bound.e UB = upper bound.f ASM2D [27].

g Refs. [37] and [38].h ADM1 [15].i Ref. [34].

j Ref. [46].k Refs. [32] and [33].



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has an extreme value of 1 when no PHA exits. Its value increases

with the increase of PHA content. The impact of PHA content on

sludge disintegration rate varies with many factors, such as sludge

characteristics, which are highly variable for different EBPR sys-

tems, and operating conditions of anaerobic fermentation systems.

Therefore, f dis is used to account for various situations. Since the

value of f dis is difficult to be measured directly, it can be obtained

by mainly fitting to the curves of measured concentrations of SCODand VFAs in experiments with different PHA contents. As the oper-

ating conditions may be different between lab scale and full scale

fermentations, the value obtained from the lab scale simulation

should be adjusted when the full scale anaerobic fermentation is

simulated.

Phosphorus is assumed to be a constituent element of organic

compounds (organisms, carbohydrates, lipids, particulate and sol-

uble organic inerts) [32,33]. Therefore, the phosphate release and

requirement for the processes like the hydrolysis of carbohydrates

and lipids, and decay and growth of organisms are considered

(Table 2).

As phosphate counter ions, K+ and Mg2+ are released together

with the release of phosphate from the cleavage of polyphosphate.

It was reported that struvite can be formed during anaerobic diges-

tion, whereas newberyite significantly precipitates only at low pH

(


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MgNH4PO4, rather than MgKPO4. Since molar ratio of Mg:NH4:PO4and pH value play important roles in struvite precipitation [1],

struvite formation was limited during the first day due to thelow NH4-N concentrations and pH (Supplementary Information –

Figs. S5 and S6). NH4-N concentrations increased gradually because

of the hydrolysis of nitrogenous organic substances, and they were

higher than 0.1 kg N m3 one day later. Meanwhile, the PO4-P and

Mg2+ concentrations were also in high levels, thus the condition

became suitable for the formation of MgNH4PO4. As a result, the

precipitation got more notable when the pH was corrected (pH val-

ues dropped in between the manual pH corrections due to acidifi-

cation). This manifests that long time operation of EBPR sludge

fermentation (resulting in high NH4-N concentration) can raise

the possibility of phosphorus precipitation and diminish phospho-

rus availability in the liquid phase for the subsequent phosphorus

recovery. These variations were well simulated by introducing pre-

cipitation processes. Batstone et al. [42] pointed out that physico-chemical processes commonly occur in biochemical systems and

have an impact on biochemical processes. The precipitation mod-

ule in this study needs further study to improve the simulation

of phosphate, Mg2+

, and K+

, because the probable dissolution pro-cesses and other species likely to precipitate [13,43,44] are not

considered.

3.5.2. Variations of soluble COD and VFAs

PHA degradation, hydrolysis, acetogenesis, and acidogenesis

contributed to the gradual increase of SCOD and VFAs concentra-

tions (Supplementary Information – Fig. S3, and Figs. 3 and 5).

On the final day of fermentation, the concentrations of both SCOD

and total VFAs excluding the amount of acetate initially added

increased with the increase of initial acetate concentration. The

simulated SCOD and VFAs concentrations fitted the measurements

well, thanks to the expression eð f dis X PHA= X C Þ introduced into the disin-

tegration kinetics. The estimated value of kdis, which is highly

dependent on digestion condition and has large variability, was0.1 d1 obtained in this study. It is lower than the default value

0

0.3

0.6

0.9

1.2

1.5

1.8

0 1 2 3 4 5 6 7 8

V F A s ( k g C O D m - 3 )

Time (d)

Spro TIC=0.06 SbuTIC=0.08

Measured Spro Measured Sbu

0

0.3

0.6

0.9

1.2

1.5

1.8

0 1 2 3 4 5 6 7 8

V F A s ( k g C O D m - 3 )

Time (d)

Spro TIC=0.05 Sbu TIC=0.09


0

0.3

0.6

0.9

1.2

1.5

1.8

0 1 2 3 4 5 6 7 8

V F A s ( k g C O D m - 3 )

Time (d)



0

0.3

0.6

0.9

1.2

1.5

1.8

0 1 2 3 4 5 6 7 8

V F A s ( k g C O D m - 3 )

Time (d)



0

0.3

0.6

0.9

1.2

1.5

1.8

0 1 2 3 4 5 6 7 8

V F A s ( k g C

O D m - 3 )

Time (d)

Spro TIC=0.03

Sbu TIC=0.06

Measured Spro

Measured Sbu

(b) Ac-l00(a) Control

(c) Ac-300 (d) Ac-500

(e) Ac-l000

Fig. 5. Experimental and simulated variations of propionate (S pro) and butyrate (S bu) in the batch fermentation tests at different initial acetate concentrations. TIC coefficients

for model fitting are indicated in every plot.


http://-/?-http://-/?-http://-/?-http://-/?-http://-/?-http://-/?-


10/12

(0.4–1.0 d1) suggested by Batstone et al. [15]. Nevertheless, the

value of k diseð f dis X PHA= X CÞ during the first 2 days was higher than 0.1

due to the existence of PHA, and it got higher when more acetate

was initially added. As the PHA was quickly degraded, this value

became close to 0.1.

Furthermore, the increased amount of total VFAs did not lead to

equal enhancement of individual VFA. Much more acetate and

butyrate were produced at higher initial acetate concentration

(Figs. 3 and 5). The acetate and butyrate concentrations for Ac-

1000 on the final day were 2.02 ± 0.05 and 1.66 ± 0.09 kg COD m 3,

respectively, while 1.19 ± 0.08 kg COD m3 acetate and

0.88 ± 0.04 kg COD m3 butyrate were observed in the control test.

This is caused by the different composition of PHA. It is confirmed

that under anaerobic conditions, external acetate was mainly used

for PHB production. Accordingly, PHB synthesis largely contributed

to the increase of PHA content (Supplementary Information –

Fig. S7). As a consequence of that the PHB was degraded to acetate

and butyrate, the higher PHB content led to the higher fraction of

acetate and butyrate generated from PHA lysis. This is reflected

in the varied values of Y PHA,ac, Y PHA,pro, Y PHA,bu, and Y PHA,va (Table 5).

Therefore, both the introduction of PHA content effect on disinte-

gration rate and the varied values of Y PHA,ac, Y PHA,pro, Y PHA,bu, and

Y PHA,va resulted in the good simulation of VFAs productions.

Simulation results suggest that PAOs activity plays an impor-

tant role in phosphate release and VFAs production during EBPR

sludge fermentation, and that there is a need to introduce some

modification to ADM1 when dealing with anaerobic treatment of

EBPR sludge. Phosphate release rate is highly dependent on the

concentrations of the VFAs, and the extent of phosphate release

is associated with the possibility of phosphorus precipitation with

the increase of NH4-N concentration. It is notable that in the model

the introduced processes of PHA storage based on VFAs uptake

leading to phosphate release are critical, because these processes

determine not only the phosphate release rate but also the amount

and composition of PHA. High PHA content accelerates sludge dis-

integration, and different compositions of PHA result in different

fractions of individual VFA. Moreover, in our previous study [45],

it was found that high phosphate concentration inhibits anaerobic

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0 1 2 3 4 5 6 7 8

M e t a l

i o n ( k g m - 3 )

Time (d)

Mg TIC=0.04 K TIC=0.05

Measured Mg Measured K

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0 1 2 3 4 5 6 7 8

M e t a l i o

n ( k g m - 3

Time (d)



0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0 1 2 3 4 5 6 7 8

M e t a l i o n

( k g m - 3

Time (d)



0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0 1 2 3 4 5 6 7 8

M e t a l i o n ( k g m - 3

Time(d)



0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0 1 2 3 4 5 6 7 8

M e t a l i o n ( k g m - 3

Time(d)



(a) Control (b) Ac-100

(c) Ac-300 (d) Ac-500

(e) Ac-1000

)

) )

)

Fig. 6. Experimental and simulated variations of Mg2+ and K+ concentrations in the batch fermentation tests at different initial acetate concentrations. TIC coefficients for

model fitting are indicated in every plot.


http://-/?-http://-/?-http://-/?-http://-/?-http://-/?-


11/12

digestion and its concentration should be reduced before anaerobic

sludge digestion. Therefore, short-term fermentation of EBPR

sludge with additional acetate can maximize phosphate release

and minimize undesirable in-reactor precipitation, which can

improve the phosphorus recovery from the liquid phase and per-

formance of subsequent sludge treatment for biogas or VFAs pro-

duction. The proposed model is a good tool to simulate anaerobic

treatment of EBPR sludge for better understanding of the complexprocesses and optimization of sludge treatment line to enhance

phosphorus recovery. Since the results are based on a single set

of experiments, performed with a single kind of EBPR sludge, the

established model together with the proposed parameters should

be further validated.

4. Conclusions

Decay rate of PAOs during EBPR sludge fermentation was deter-

mined as 0.35 ± 0.03 d1. Increased PHA content accelerates sludge

disintegration and lysis. Based on the experimental results, ADM1

was extended and modified by including processes that PAOs are

able to store 4 VFA species in the form of PHA, the effect of PHA

content on disintegration rate, and phosphorus precipitation pro-cesses. Data from a set of anaerobic fermentation experiments

for EBPR sludge were used to test the validity of the model. Simu-

lation results reveal that the modified ADM1 can be used to predict

phosphate and VFAs variations during anaerobic fermentation of

EBPR sludge, and the model is a good tool for better understanding

the complex processes. Future work should be addressed on the

extension of precipitation module to improve the simulation of

phosphate under more complex conditions.

Acknowledgments

This work was supported by the National High Technology

Research and Development Program of China (863) (Grant No.

2011AA060902).

Appendix A. Supplementary data

Supplementary data associated with this article can be found, in

the online version, at http://dx.doi.org/10.1016/j.cej.2015.10.110.

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