Bioresource Technology 171 (2014) 452–460

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Simulation of water removal process and optimization of aeration strategy in sewage sludge composting Hai-Bin Zhou, Tong-Bin Chen, Ding Gao ⇑, Guo-Di Zheng, Jun Chen, Tian-Hao Pan, Hong-Tao Liu, Run-Yao Gu Center for Environmental Remediation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 11A Datun Road, Beijing 100101, PR China

h i g h l i g h t s  A mathematical model for composting process was developed and verified.  Water removal was enhanced with higher aeration rate and on/off time ratio.  The optimization of aeration strategy was discussed.

a r t i c l e

i n f o

Article history: Received 9 May 2014 Received in revised form 30 June 2014 Accepted 1 July 2014 Available online 8 July 2014 Keywords: Aeration strategy Water removal Sewage sludge Mathematical model

a b s t r a c t Reducing moisture in sewage sludge is one of the main goals of sewage sludge composting and biodrying. A mathematical model was used to simulate the performance of water removal under different aeration strategies. Additionally, the correlations between temperature, moisture content (MC), volatile solids (VS), oxygen content (OC), and ambient air temperature and aeration strategies were predicted. The mathematical model was verified based on coefficients of correlation between the measured and predicted results of over 0.80 for OC, MC, and VS, and 0.72 for temperature. The results of the simulation showed that water reduction was enhanced when the average aeration rate (AR) increased to 15.37 m3 min1 (6/34 min/min, AR: 102.46 m3 min1), above which no further increase was observed. Furthermore, more water was removed under a higher on/off time of 7/33 (min/min, AR: 87.34 m3 min1), and when ambient air temperature was higher. Ó 2014 Elsevier Ltd. All rights reserved.

1. Introduction The high moisture content (MC) of dewatered sewage sludge causes problems in terms of sludge treatment and disposal; therefore, it is important to reduce sludge moisture to reduce the overall sludge volume and quantity (Cai et al., 2012; Zhao et al., 2010). Indeed, water removal is important to the reduction of sludge volume and quantity (Cai et al., 2012) during sewage sludge biodrying and composting processes, during which time the moisture content can be reduced to below 40% from 60–70%. Moisture content is a critical parameter involved in bio-drying and composting that influences the complex biochemical reactions associated with microbial growth and the associated biodegradation of organic matter (Ryckeboer et al., 2003). A sufficient MC ensures microbial activity (Hamoda et al., 1998), but a MC that is too high leads to a low biodegradation rate and generation of foul odor

⇑ Corresponding author. Tel./fax: +86 10 64889303. E-mail address: [email protected] (D. Gao). http://dx.doi.org/10.1016/j.biortech.2014.07.006 0960-8524/Ó 2014 Elsevier Ltd. All rights reserved.

(Haug, 1993). The MC of different composting materials is usually reduced to approximately 50–70% following the addition of bulking agents (Richard et al., 2002). If the MC is too high, the oxygen diffusion is impeded owing to a poor void structure in the pile, which leads to anaerobic conditions, failure of self-heating, and poor processing (Miller, 1989). Haug (1993) suggested that the optimum MC was 60%. During processing of other composting materials such as livestock and poultry manure, the moisture content often decreases too rapidly to complete the innoxious disposal, resulting in the need to add water in the middle of the composting processes. The main drying mechanism in bio-drying is convective evaporation through mechanically controlled aeration, which uses heat produced from the biodegradation of organic matter (NavaeeArdeh et al., 2006; Zhou et al., 2014). The primary functions of aeration are oxygen supplementation, water removal, and controlling the pile temperature. Water removal and maintenance of high temperature are two contrasting aspects. Specifically, a larger aeration rate and longer aeration time can improve water evaporation, but can also carry heat generated during organic matter

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degradation, lowering the temperature, which can decrease the water removal rate. In a typical composting process, the range of aeration rate is large. Ekinci (2001) studied sludge and woodchip composting under different airflow rates of 0.1615–1.131 m3 h1 kg1 dry matter and found that heat production was insensitive to air flow, except under the lowest flow. Many researchers have investigated the influence of changing aeration strategies to maintain a set temperature (Adani et al., 2002; Sole-Mauri et al., 2007; Wang et al., 2013). Adani et al. (2002) controlled the temperature at 70, 60 and 45 °C for as long as possible and found that moisture contents were reduced to 40.9%, 66.5%, and 66.7%, respectively, but no further experiments under higher aeration rates were performed. Similar results were observed by MacGregor et al. (1981), but opposite results were obtained by Nakasaki et al. (1987), who suggested that 60 °C was the most suitable temperature when both the water removal rate and the degradation rate were high. When compared with traditional composting, biodrying employs a higher aeration rate to strengthen water removal (Epstein, 1996), during which time the temperature was lower. When the aeration rate increased to a specific value (about 0.0455 m3 h1 kg1), higher aeration rate did not exert a significant effect, and water removal increased by only 2.86% (Zhao et al., 2010). Furthermore, the highest temperature was only 55 °C owing to the high aeration rate and turning frequency. The moisture and temperature of inlet air can influence the biodrying and composting process. Air enters the composting pile from the bottom, and then gets wet and saturated as it travels through the pile, resulting in an inability to remove water molecules from the upper layers (Sugni et al., 2005). As a result, compost piles dry from the bottom up (Wang et al., 2013; Zhao et al., 2010). The influence of air temperature is particularly strong in cold weather, necessitating control of aeration using specially designed processes. Wang et al. (2013) found that aeration at 1200 m3d1 prevented the pile from warming. Moreover, if ambient temperature is too low, the influence of aeration rate on water removal was minor. However, the author did not provide a detailed description of the aeration strategy in their publication. Numerical simulation shows high efficiency, low cost and easy control relative to field tests. Numbers of numerical equations established on the basis of the energy and mass balance during composting have been shown to describe and predict the temperature, moisture levels and organics degradation in the pile well under normal temperatures (Haug, 1993; Keener et al., 1993; Mason, 2006; Sole-Mauri et al., 2007). However, few have defined the optimal on/off time of the aeration strategy during composting processes. Moreover, water removal during winter has not been thoroughly discussed. Therefore, in the present study, a mathematical model was established and used to optimize the aeration strategy during composting and biodrying. The specific objectives were to: (1) simulate the process of sewage sludge composting using CTB (control technology for bio-drying) process; (2) simulate different aeration operations, including the influence of on/off time ratio during the process, and (3) compare composting performance during winter and summer to identify an optimized aeration strategy for biodrying and composting facilities.

The characteristics of the raw materials are listed in Table 1. A total of 120 tons of SS, 20 tons of SD, and 60 tons of RP were uniformly mixed and composted in a static aeration pile. The cuboid pile was 33 m long, 5 m wide and 1.8 m high. The characteristics of the initial materials are shown in Table 1. The initial MC of the mixed material was about 65% and the volatile solid (VS) was about 83.5%. 2.2. Numerical models 2.2.1. Organic matter biodegradation kinetics A first order kinetic expression was used to describe VS degradation (Eq. 1) (Haug, 1993):

dmVS ¼ k  mVS ; dt

ð1Þ

k ¼ kT  kMC  kO2  kFAS ;

ð2Þ

where mvs is the mass of volatile solid in the pile, kg; t is time, min; k is the coefficient of the biodegradation of volatile solid; kT, kO2 , kFAS and kMC are the factors to adjust the rate constant for the effect of temperature, O2, free air space (FAS), and MC (dimensionless), respectively. The expression Eq. (3) developed by Haug (1993) can properly explain the simulation results and has a wide range of use. However, it cannot reflect the influence of microbial succession because it does not consider mesophilic bacteria. Additionally, the function value appears to be negative when the temperature is too high, which does not conform to the fact that microbes would be inactivated.

kT ¼ k20 ½1:066ðT20Þ  1:21ðTT ref Þ :

ð3Þ

Therefore, the equation was modified as follows to rectify these disadvantages. In this study, microbes were divided into mesophilic and thermophilic bacteria, while organic materials were divided into rapid and slow degraders, the percentages of which were gf and gs respectively. The degradation rate of rapidly degrading organic matter (OM) kT fast is related to both mesophilic and thermophilic microbes, while kT slow is assumed to only be affected by thermophilic microbes:

kT fast ¼ k20fast ½fðTÞmesophilic þ fðTÞthermophilic ;

ð4Þ

kT slow ¼ k20slow  fðTÞthermophilic :

ð5Þ

Mesophilic and thermophilic bacteria were assumed to be inactivated when the temperature was higher than 45.5 and 75 °C, respectively. F(T)mesophilic and f(T)thermophilic were as follows:

(

fðTÞmesophilic ¼

1:066ðT20Þ  1:21ðTT refm Þ

if T 6 ð1:5T refm  10Þ

0

if T > ð1:5T refm  10Þ

;

ð6Þ ( fðTÞthermophilic ¼

1:066ðT20Þ  1:21ðTT reft Þ

if T 6 ð1:5T reft  10Þ

0

if T > ð1:5T reft  10Þ

;

ð7Þ 2. Methods 2.1. Composting devices Sewage sludge (SS) was collected from a municipal sewage treatment plant (Shanghai, China) with a disposal capacity of 1.28  105 tons d1. Sawdust (SD, diameter 0–2 cm, mixture of sawdust and wood shavings) was bought from a furniture plant. And returned product (RP) after the treatment of sludge was used.

Table 1 Properties of raw materials.

Sewage sludge Sawdust Returned Product Mixed material

MC (%)

VS (%)

Density (kg m3)

80.2 14.5 43.8 65.4

62.1 94.6 75.3 83.5

1032 102 305 654

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where Trefm and Treft are the reference temperatures in °C. Eqs. 8–11 describe the effects of O2, FAS and MC on the rate constant coefficient during aeration composting:

kO2 ¼

100V O2 ; 100V O2 þ 2

ð8Þ

where V O2 is the volume percentage of oxygen in air, %:

kFAS ¼

1 e½26:375ðFASÞþ3:4945

þ1

FAS ¼ 1  qb where qs ¼

þ

qw

VS

1

1VS ;

qVS þ qASH

qs

 ;

km ¼ ð10Þ

e is the porosity of the matrix (dimension-

less); qb is the wet bulk density of substrates (kg m3); qs is the particle density of dry matter in composting materials (kg m3); qw is the density of water (kg m3); qVS is the density of VS (kg m3); and qASH is the density of ash (kg m3).

kMC ¼

1 e½17:684ð1MCÞþ7:0622 þ 1

:

ð11Þ

2.2.2. Heat balance equations Heat balance components in the composting model include sensible heating of the composting materials (QM), sensible heat of input and output dry air (QH), conductive/convective/radiative heat losses (QD, QU), latent heat of water evaporation (QC), and biological heat production (QR). The overall heat transfer coefficient (U) incorporates the combined effects of conduction, convection and radiation through the wall boundaries. The heat balance equation, configured for sensible heat accumulation as the dependent variable, is presented below:

Q M ¼ Q R þ DQ C þ DQ H þ DQ D þ DQ U :

Q M ¼ ms  ½ð1  MCÞ  C S þ MC  C W   T;

ð13Þ

where ms is the mass of the pile, kg; Cs is the specific heat capacity of solid, kJ K1 kg1; and Cw is the specific heat capacity of water, kJ K1 kg1. The heat generation can then be calculated as follows:

Q R ¼ ðHrx Þ  DmBVS ;

ð15Þ

where Hrx is the coefficient of heat production of biodegradable 1 organic matter, and H25 ; Ca is the sperx is the value at 25 °C, kJ kg cific heat capacity of dry air, kJ K1 kg1; yair=BVS and yH2 O=BVS are the coefficients of air consumption and water generation, kg kg1. Sensible heat of dry air:

Q C ¼ C a  ma  T:

ð16Þ

Latent and sensible heat change in air:

Q H ¼ C v  ma  HS  T þ ma  hLV  HS ;

ð19Þ

ð20Þ

where ki ¼ 0:1538 þ 0:5114  MCi (i = 1, 2), which is related to the MC of the composting pile (Ekinci, 2001). Since every two piles of compost in the Shanghai composting plant are only separated by a wall, the heat loss through the conductivity between the material and wall was neglected in this simulation. The coefficients used in this simulation are shown in Table 2. 2.2.3. Water and air mass balance equation During the composting process, water molecules were generated or emitted when the material collapsed, after which they diffused to the air phase and were carried out of the pile, which led to changes in MC. The air was assumed to be saturated through the pile at every level. Specifically, O2 was blown into the pile and consumed during OM degradation and the convection and diffusion was considered. The mass balance equations of dry air, water, and oxygen are provided in Eqs. 21–23:

@ðe  qa Þ @q @q ¼ u  a  yair=BVS  BVS ; @t @z @t

ð21Þ

  @ðqs MC Þ @HS @q e @ 2 ðqa HS Þ ¼ u  qa  þ H S  a þ 2  Dw  @t @z2 @z @z b þ yH2 O=BVS 

@ qBVS ; @t

ð22Þ

@ðe  qa  C O2 Þ @C O2 @q e ¼ u  ðqa  þ C O2  a Þ þ 2  DO2 @z @z @t b 

@ 2 ðqa C O2 Þ @q þ yO2 =BVS  BVS : @t @z2

ð23Þ

where e is the porosity in the composting pile, m3 m3; qa is the density of dry air, kg m3; z is the height of the pile, m; u is the

ð14Þ

where Hrx is the coefficient of heat generation by OM degradation, which is a function of temperature:

Hrx ¼ H25 rx þ ðyair=BVS  C a þ yH2 O=BVS  C W Þ  ðT  25Þ;

DT ; Dz

2k21 ; k1 þ k2

ð12Þ

The sensible heat of the pile can be calculated by the following equation:

ð18Þ

The heat conduction between adjacent layers is calculated using the conductivity coefficient and the temperature gradient:

ð9Þ

;

1  Mw

hLV ¼ 2465:4  2:3771  T:

Q D ¼ km  AS 

FAS can be calculated using the following equation:

 Mw

1993), which is related to air temperature, and can be calculated using Eq. 18:

ð17Þ

where HS is the saturated absolute humidity of air, kg kg1; Cv is the specific heat capacity of water vapor, kJ K1 kg1; ma is the mass of dry air, kg; and hLV is the latent heat of water vapor, kJ kg1. Heat conductivity can be calculated from the coefficient of heat conduction. HLV is the evaporative latent heat of water (Haug,

Table 2 Coefficients used in the simulation. Coefficients

Value

Units

References

Ca Cs Cw Cv hLV Hrx kBVS k20fast k20slow Mair Mwater yair/BVS yH2 O=BVS

1.004 1.046 4.184 1.841 2465.4 22097 0.2 0.04 0.015 28.96 18.015 0.2836 0.7164

kJ kg1°C1 kJ kg1°C1 kJ kg1°C1 kJ kg1°C1 kJ kg1 kJ kg1 kg kg1 d1 d1 g mol1 g mol1 kg kg1 kg kg1

Ekinci (2001) Ekinci (2001) Ekinci (2001) Ekinci (2001) Mason (2006) Haug (1993) Estimated Haug (1993) Haug (1993) Constant Constant C10H19O3N C10H19O3N

yO2 =BVS

1.18

kg kg1

Ekinci (2001)

qa qs qw gf gs

1.18 1.06  103 1.0  103 0.4 0.6

kg m3 kg m3 kg m3 kg kg1 kg kg1

Constant Tested Constant Haug (1993) Haug (1993)

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H.-B. Zhou et al. / Bioresource Technology 171 (2014) 452–460

velocity of the air flow, m s1; qBVS is the density of the BVS, kg m3; DO2 and Dw are the confidents of the O2 and water transfer, which are 105 and 104 m2 s1, respectively; and C O2 is the concentration of oxygen, %. The density of dry air was calculated in Eq. 24.

qa ðtÞ ¼

P  M air ; R  ½T a þ 273:15

ð24Þ

where P is the standard atmospheric pressure, kN m2; Mair is the molar mass of air, g mol1; Mwater is the molar mass of water, g mol1; R is the universal gas constant, N m mol1 K1. Hs is the saturated moisture of air (kg H2O kg1 dry air): 2238

Hs ðT a Þ ¼

M water 108:896T a þ273 ; M air 760  108:896T a2238 þ273

ð25Þ

where Ta is the temperature of air or the gas phase, °C. The evaporated water was calculated using the mass of water carried by the air when going out of the pile. As in many simulations (Das and Keener, 1997; Ekinci, 2001; Wang et al., 2013), when the MC is higher than 50%, the moisture of outlet air can be assumed to be saturated (Bach et al., 1987); accordingly, the water carried by the outlet air is much higher than that carried by inlet air, especially when the temperature difference between inlet and outlet air is greater than 20 °C. However, when the temperature of inlet air was low, the influence could not be ignored because it will lead to failed heating of the composting piles (Wang et al., 2013). The operation becomes difficult in winter, especially in cold regions. 2.3. Simulations design The initial parameters of the models in Experiment 1–4 are shown in Table 3, and treatments in each experiment are defined. First, verification between the modeling system and the experimental composting system was processed using the CTB composting system, which was controlled using Compsoft v3.0 (GreenTech Environmental Engineering Ltd., Beijing, China) (Chen et al., 2001) in a sewage sludge treatment plant in Shanghai (Experiment 1). In Experiment 2, the blower time was set as 4, 6, and 8 min in an aeration cycle for three treatments while the average aeration rates were set at 10.25, 15.37, and 20.49 m3 min1, respectively, to investigate the influence of changes in aeration rate on composting. The effects of aeration on/off ratio were investigated in Experiment 3 using a set average aeration rate of about 15.37 m3 min1, and the on/off time was set as 7/33, 6/34, and 5/35 min/min while the aeration rate was calculated and fixed, correspondingly. In Experiment 4, ambient air temperatures were set at 10 °C and 25 °C to simulate the different performances of the composting plant during winter and summer at an aeration rate of 102.46 m3 min1, while the initial temperatures were set at 20 °C and 40 °C, respectively. Mathematical operations of the composting models were conducted using Mat. Lab 2009.

2.4. Sampling and analysis During the composting process of Experiment 1, fresh samples were collected at random from top to bottom of the pile in different positions every 2 days. Samples were then analyzed for moisture content (MC) and organic matter content (OM). Three electronic thermometers and O2 sensors (Alphasense, UK) were inserted into the upper, middle and bottom layers of the pile and CompsoftÒ3.0 automatically recorded the data daily. And the average temperature and O2 content was calculated. The ambient temperature was monitored by a portable weather station (Metpak II, UK). The MC was determined from the weight loss upon drying at 105 °C for 5 h in a hot-air oven, and the VS was taken as the weight loss after 4 h at 550 °C in a muffle furnace. All samples were analyzed in triplicate.

3. Results and discussion 3.1. Experiment 1: verification of simulation system Comparison of the temperature, O2 content (OC), MC and VS predicted for 12 days (Fig 1) with experimental data revealed acceptable differences. The temperature of the pile increased quickly in the first 2 days, and then remained at above 50 °C for the following 5 days, which met the requirement of remaining above 50 °C for more than 5–7 days during the experiment according to US EPA 40 CFR Part 503 Regulations (Zhou et al., 2014). The OC showed periodic alterations because of the intermittent ventilation strategy. Over the course of an aeration cycle, the OC increased when the blower started to work, reached a peak when the aeration rate equaled oxygen consumption or when OC reached the maximum concentration (OCmax), then decreased rapidly owing to microbial activity when the blower stopped (Fig. 2). The OCmax decreased in the first 2 days because the microbial activity increased as the pile temperature increased. Additionally, the minimum OC (OCmin) decreased to about 0, which indicated that anaerobic conditions formed because of OM degradation. When the temperature decreased owing to the reduction of easily degradable organic matters, OCmin also increased to about 20%, indicating that the microbial activity decreased and the composting pile was stabilized. The VS also decreased from 83.5% to about 80% in 12 days. MC provides direct evidence of the water removal process. In the present study, dry air was blown into the reactor from the bottom, resulting in removal of heat and water molecules from the composting pile as the air temperature increased throughout the pile. MC decreased from 65% to about 42% in 12 days via water removal by dry air passing through the pile. Sewage sludge primarily contains bound water such as vicinal water, and water of hydration after mechanical dewatering (Vesilind, 1994), which cannot be easily removed by forced air or convection. Microbial activity has been shown to increase notably during the mesophilic phase when temperature increases (Hassen et al., 2001), generating more met-

Table 3 Initialization of the parameter for the models. Parameters

Ambient temperature (Ta, °C) Original pile temperature (°C) Aeration rate (Q, m3 min1) On/off time of blower (min/min) Average aeration rate (m3 min1) Starting moisture of the mixture (%)

Experiment 1

Experiment 2

Prediction

T1

10 20 102.46 6/34 15.37 65%

10 20 102.46 4/36 10.25 65%

T2

6/34 15.37

Experiment 3 T3

8/32 20.49

T1 10 20 87.34 7/33 15.30 65%

T2

102.46 6/34 15.37

Experiment 4 T3

122.95 5/35 15.37

T1

T2

10 20 102.46 6/34 15.37 65%

25 40

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H.-B. Zhou et al. / Bioresource Technology 171 (2014) 452–460

a

b

40

60

Oxygen Concentration (%)

55

o

Temperature ( C)

50 45 40 35 30

Measured Predicted

25 20

Predicted, OCmax Predicted, OCmin Measured, OCmax Measured, OCmin

30

20

10

0

0

2

4

6

8

10

0

12

2

4

6

10

12

d 0.90

80 75 70 65 60 55 50 45 40 35 30 25 20

Measured Predicted

Measured Predicted

0.85

VS (%)

Moisture Content (%)

c

8

Time (d)

Time (d)

0.80 0.75 0.70 0.65

0

2

4

6

8

10

12

Time (d)

-2

0

2

4

6

8

10

12

Time (d)

Fig. 1. Predicted and measured pile temperature (a), OC (b), MC (c), and VS change (d) during composting process.

Fig. 2. Typical changes in oxygen concentration of the compost pile over the course of one aeration cycle. The blower started at time = 0, and the dotted vertical line indicates the time at which the blower stopped.

abolic water. Additionally, the vicinal water boundary water layers in bio-drying material were destroyed, increasing the effectiveness of sludge dewatering during the thermophilic phase (Vesilind, 1994). The air temperature is known to increase through the composting pile, increasing the saturation vapor pressure and removing a large quantity of vapor from the liquid water in the pile (Wang et al., 2011). Moreover, the abundant heat produced by the microbial metabolism and forced aeration facilitate water evaporation, leading to efficient removal of moisture from the bulk in the thermophilic phase. Fig. 1 and Table 4 summarize the performance of the mathematical model. The coefficient of correlation (CC) (Devore and Peck, 2007) was calculated using the Eq. (26) to measure the degree of linear correlation between the measured and predicted results. A good prediction effect is confirmed when CC is above 0.80.

Pn CC; r ¼

i¼1 ½y1 ðxi Þ

 hy1 i½y2 ðxi Þ  hy2 i nry1 ry2

ð26Þ

where y1(xi) is the measured values; y2(xi) was the predicted values; was the average of the measured values; was the average of the predicted values; ry1, ry2 were the standard deviation of the measured and predicted values, respectively; and n was the number of samples. The MC and VS showed a good fit between experimental and predicted data, with differences of only 2.5 and 0.19% being observed on day 12, respectively. The predicted OCmax was higher than that observed in the experiment, while the OCmin after day 8 was lower than in the experiment. This was likely because the predicted OM biodegradation was slower in the simulated system, which would lead to a slower temperature increase in the mesophilic phase and slower decrease after the peak temperature occurred. The peak temperature was reached about 2 days later, and the highest temperature was predicted to be 2 °C lower than the measured data, and the predicted temperature was higher than the measured data after day 3. The coefficient CC of the temperature, OC, MC and VS between the measured and predicted values were calculated (Table 4). The results showed that the OC, MC, and VS were well predicted, with CCs of 0.88, 1.00, and 1.00, respectively, while the temperature was acceptably predicted, with a CC of 0.72. The temperature CC was likely influenced by temperature variations during day and night. Overall, the performance of the prediction was acceptable; indicating that, under the same simulation conditions, the results of the following simulations could be useful for guiding large scale composting processes of sewage sludge. 3.2. Experiment 2: influence of average aeration rate The main function of aeration includes oxygen supply, system temperature control, and material drying, which provides suitable ecological conditions for microbes during composting (Cai et al., 2013; de Guardia et al., 2008). In the present study, the aeration time was too short to provide sufficient oxygen to the pile in T1 (Treatment 1, defined in Table 3), which led to a slower temperature

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H.-B. Zhou et al. / Bioresource Technology 171 (2014) 452–460

increase. As the aeration rate increased, the temperature increased much more rapidly in T2 and T3 (Treatment 2 and 3, defined in Table 3), but the high temperature lasted for less time. The thermophilic phase in T3 only lasted for about 4 days when the temperature was above 50 °C, and the temperature in T2 was higher. A lower temperature meant lower microbial activity and oxygen consumption (Fig 3b). The OCmax in T1 decreased on day 1, and was maintained at 11% for about 4 days, then increased when the

degradable OM decreased, while the temperature decreased. The OCmin in T1 increased since about day 5, and reached 16% on day 12. The water evaporation rate is usually higher at high temperature, which increases the absolute humidity of the output air and improves the heat transfer rate on the pile surface. As a result, the MC and VS in T1 only decreased to 51.73 and 82.08%, respectively. T2 and T3 showed similar MC and VS reductions, which were both higher than that of T1. Water evaporation was not significantly

Table 4 Temperature, moisture, oxygen, and VS validation performance of composting models. Parameters

Difference between model and data

Coefficient of correlation (CC)

Items

Predicted

Measured

Temperature

Highest temperature Time to reach Length of thermophilic phase

56 °C 2.5 d 10 d

58 °C 2d 7d

0.72

Moisture content

Average MC

42.99%

41.84%

1.00

Oxygen content

Max on day 2 Min on day 2

21% 0%

18% 0%

0.88 0.97

VS

Average VS

81.18%

81.34%

1.00

T1: 4/36 T2: 6/34 T3: 8/32

0

Moisture Content (%)

c

2

4

6

8

10

0

T1: 4/36, OCmin T2: 6/34, OCmin T3: 8/32, OCmin

T1: 4/36, OCmax T2: 6/34, OCmax T3: 8/32, OCmax

2

8

4

T1: 4/36 T2: 6/34 T3: 8/32

70

60 50

40

6

10

12

Time (d)

d

80

T1: 4/36 T2: 6/34 T3: 8/32

85

80

75

0

Water Removal Rate (kg/(kg d))

34 32 30 28 26 24 22 20 18 16 14 12 10 8 6 4 2 0 -2

12

Time (d)

30

e

Oxygen Concentration (%)

b

80 75 70 65 60 55 50 45 40 35 30 25 20

Volatile Solid (%)

o

Temperature ( C)

a

2

4

6

8

10

12

0

2

4

6

8

10

12

Time (d)

Time (d) 0.05

T1: 4/36 T2: 6/34 T3: 8/32

0.04 0.03 0.02 0.01 0.00 -0.01 -0.02 0

2

4

6

8

10

12

Time (d) Fig. 3. Predicted effect of on/off time (4/36, 6/34, 8/32 min/min) on pile temperature (a), OC (b), MC (c), VS content in sludge (d), and water removal rate (e).

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H.-B. Zhou et al. / Bioresource Technology 171 (2014) 452–460

T1: 87.34, 7/33 T2: 102.46, 6/34 T3: 122.95, 5/35

Moisture Content (%)

2

4

6

8

10

T1: 87.34, 7/33, OCmin T2: 102.46, 6/34, OCmin T3: 122.95, 5/35, OCmin T1: 87.34, 7/33, OCmax T2: 102.46, 6/34, OCmax T3: 122.95, 5/35, OCmax

35 30 25 20 15 10 5

12

Time (d) T1: 87.34, 7/33 T2: 102.46, 6/34 T3: 122.95, 5/35

70

0

d

80

60 50

40

2

4

6

8

10

12

Time (d) 85

T1: 87.34, 7/33 T2: 102.46, 6/34 T3: 122.95, 5/35

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81 80

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Time (d)

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Oxygen Concentration (%)

b

80 75 70 65 60 55 50 45 40 35 30 25 20

Volatile Solid (%)

o

Temperature ( C)

a

T1: 87.34, 7/33 T2: 102.46, 6/34 T3: 122.95, 5/35

0.03

0.02

0.01

0.00 0

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Time (d) Fig. 4. Predicted effect of aeration rate (87.34, 102.46, 122.95 m3 min1) and on/off time (7/33, 6/34, 5/35 min/min) under the same average aeration rate on pile temperature (a), OC (b), MC (c), VS content in sludge (d), and water removal rate (e).

improved at higher aeration; however, the degradation of OM decreased as the temperature decreased, which was also confirmed by previous studies (Wang et al., 2013). The highest water removal rate was about 0.025 kg kg1 d1 in T3, which was slightly higher than T2. However, the water removal rate decreased to lower than T2 after about day 7 because the temperature was far lower than T2 and the saturation moisture content decreased. Overall, the total water removal from 1 kg of primary materials was 0.143, 0.207, and 0.204 kg water in T1, T2, and T3, respectively. This occurred because, although the aeration rate was higher, the increase in the quantity of water carried by the air was small. The water removal of T3 was slightly lower than that of T2 with the increase of aeration rate, which indicated that after the aeration rate increased to a certain extent, the water removal rate would not increase significantly (see Figs. 4e and 5). 3.3. Experiment 3: on/off time rate under the same average aeration rate The influence of on/off time ratio is very important to the composting water removal process. In this experiment, we set the same average aeration rate in the three treatments while using a different instantaneous aeration rate and on/off time. The higher on/off time meant a lower instantaneous average aeration rate. Additionally, using the same average aeration rate did not result in the

same water removal rate during composting. Temperature, which increased quickly in the first 2 days and reached a maximum of 57 °C, showed minor differences among the three treatments. The temperature of T1 was higher in the first 8 days relative to T2 and T3 because the aeration time was longer and the off time was shorter. The oxygen content remained above the limit of 10% that has been suggested as the minimum amount required to maintain aerobic conditions (Haug, 1993). The higher oxygen content also resulted in generation of more heat, especially during the first 6 days when the OCmin was relatively low. Because of the longer aeration time and higher temperature, the water removal rate was 2.19 and 4.53% higher in T1 than T2 and T3, respectively, while the VS degradation rate was 1.86 and 3.92% higher, respectively. Overall, the total water removal from 1 kg of primary materials was 0.212, 0.207, and 0.202 kg water. After day 9, the biodegradation in T1 decreased to a lesser degree than that in T2 and T3, which led to lower heat generation and temperature and a higher OCmin. 3.4. Experiment 4: comparison between summer and winter During summer and winter, we assumed the average ambient air temperature to be 25 and 10 °C. The influence of the temperature of air on the sensible and latent heat of dry air and the saturate moisture content has been considered in the simulation system.

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b

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Moisture Content (%)

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Time (d) Fig. 5. The predicted effect of inlet air temperature (10 °C, 25 °C) on pile temperature (a), OC (b), MC (c), VS content in sludge (d), and water removal rate (e).

The original temperature was higher in summer (40 °C) than in winter (20 °C). Specifically, the temperature increased from 40 to about 63 °C in 1.5 days, then decreased to about 50 °C on day 12 in summer. However, the average temperature increased from 20 to about 55 °C in 3 days during winter, and the maximum temperature was much lower. The low temperature led to lower water removal and VS degradation. The average MC in winter and summer decreased to 43.48 and 40.91%, respectively. The peak water removal rate occurred on days 4–5 in winter, when it was about 0.220 kg kg1 d1, while the maximum water removal rate occurred on day 3 in summer, which was about 0.023 kg kg1 d1. Additionally, the total water evaporation during 12 days was 0.229 and 0.203 kg kg1 initial materials in summer and winter, respectively. Low temperature significantly inhibited water removal during the composting process. Accordingly, the aeration strategy should be improved for processing in cold regions, especially during winter. Additionally, the initial characteristics should be adjusted to meet the demand to operate in winter, and temperature insulation measures should be taken when necessary.

4. Conclusions The water removal process was simulated to facilitate operation of large scale sewage sludge composting. The simulated results were very close to the measured, with CCs of over 0.80 for OC,

MC, and VS, and 0.72 for temperature. A better water removal showed under larger average aeration rate, but no further increase was observed when the aeration rate was higher than 15.37 m3 min1 (6/34 min/min, AR:102.46 m3 min1). A higher on/off time ratio of 7/33 min/min (AR: 87.34 m3 min1) could increase the water removal and biodegradation slightly. Low surrounding temperature prohibited temperature increases and decreased water removal.

Acknowledgements The project was financially supported by the State Environmental Protection Public Welfare Professional Program of China (No. 201209022), and the National Key Technology R&D Program of China (No. 2012BAC25B03).

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