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European Biosolids and Organic Resources Conference 15-16 November, Edinburgh, Scotland

OPTIMISING THE PERFORMANCE AND STABILITY OF CONVENTIONAL MESOPHILIC ANAEROBIC DIGESTION OF SEWAGE SLUDGE

Giacalone, S.1,2, Winter, P.1, Smith S.R.2

1Thames Water, 2Imperial College London, UKCorresponding Author Email: [email protected]

Abstract

Anaerobic digestion (AD) is the most widely adopted sewage sludge treatment in the UK, but uncertainties remain on best operational practice. The interactive effects of three critical process control parameters on the conventional mesophilic AD of sewage sludge have been tested using an automated digestion apparatus to simulate the operational process and determine optimal treatment conditions. The first parameter chosen was the ratio of primary to surplus activated sludge (PS: SAS). Because of the difference in origin, the physico-chemical characteristics and anaerobic biodegradability of the two types of sludge were evaluated. The second control parameter was the dry solids concentration of the feed sludge, which impacts the rate of addition of substrate into the reactor, and determines the organic loading rate (OLR). The third parameter was temperature, which fundamentally impacts rate of physico-chemical and biological reactions. Results indicate that PS: SAS has the largest impact on biogas yield and OLR impacts reactor alkalinity. Significant interactive effects have been determined for PS: SAS and OLR, on ammoniacal nitrogen levels, and PS: SAS and temperature, influencing pathogens reduction potential.

Keywords

Anaerobic Digestion, Operational Parameters, Process Optimisation

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Introduction

General context

Anaerobic digestion (AD) provides an environmentally sound technology for the treatment of sewage sludge. It allows the treatment of the polluted biodegradable waste, the production of a stable stream of organic matter with high fertilizer value and the recovery of a fraction of the organic carbon in the form of methane (CH4) gas. The success of this process for the treatment of sewage sludge is demonstrated by its extensive utilisation, which in the UK represents approximately 80% of the 1.5 Mt/year of sewage sludge produced (DEFRA, 2011). The AD process has the benefit of low operational cost, and it is a net energy producer. One of the main constraints to the AD process is the high capital cost of the reactors, due to the large capacity required to accommodate the relatively long process retention times due to the relatively slow rate of anaerobic microbiological reactions. Therefore wastewater utilities are interested in maximising the throughput capability of existing assets, by increasing the AD treatment rate. Under the current UK legislation, optimising the performance of AD bio-reactors is of particular significance due to the value of the Renewable Obligation Certificates (ROCs) (House of Parliament, 2011), which include energy produced with bio-methane, and the potential de-regulation of the sludge market currently discussed by OFWAT, the UK water regulator. It is therefore of primary importance for the utilities to understand the limits of performance of the existing assets, to correctly evaluate future strategies.

Project aim and literature review

This research aims to optimise AD at large scale municipal sewage treatment works (STW). A large number of variables influence the digestion process, however, the major factors under operational control and which impact the process include: temperature, organic loading rate (OLR) and primary: surplus activated sludge ratio (PS: SAS). Therefore, these parameters were selected for investigation based on operational experience of water companies, previously reported research (Gonzalez, 2012; Perez et al., 2013) and other published literature (Appels et al., 2008).

Temperature is a critical control variable in all bio-chemical processes. The hydrolysis rate of substrate in AD can be increased by increasing temperature and approximately doubles with incremental 20oC step rise, following the Arrhenius relationship (Ge et al., 2011). Ge et al. (2011) showed that the other various major microbial groups (acidogens, acetogens and methanogens) are not impacted in the same way. This implies that hydrolysis rate can be enhanced by increasing temperature, and because in AD acid production is much faster than acid consumption (Parkin and Owen, 1987; Gerardi, 2003; Appels et al., 2008), care should be taken to avoid reactions unbalances, which could lead to reactor acidification. Temperature also affects the dissociation point of ionic species and the solubility of gases (Batstone & Jensen, 2011). For instance, these have considerable impact on the carbonate and ammoniacal nitrogen (Amm-N) systems, which are of crucial importance for digester stability. Operational aspects of managing the digester temperature also include changes in the absolute humidity of gas and the thermal self-sustainability of AD process.

The organic loading rate (OLR) is a mathematical expression, and is a function of the feed sludge dry solids (DS), volatile solids (VS) and hydraulic retention time (HRT). Previous studies (Hill, 1982; Gianico et al., 2013; Gou et al., 2013) demonstrate that the substrate feed rate to the digester impacts the absolute and specific CH4 production rate. The relationship between CH4 productivity and OLR is non-linear (Husain, 1998), which may be explained due to biological stress and substrate inhibition. Limits on maximum OLR are also dictated by processing capabilities. Digestion asset managers aim to maximise the OLR to intensify the use of assets, and this can be achieved either by increasing the sludge concentration within the reactor or minimising the retention time. The impact of HRT on AD processes has been widely studied (Parkin and Owen, 1987; Miron et al., 1999; Gerardi, 2003; Appels et al., 2008). The lower limit of HRT depends on the rate limiting step, which can either be hydrolysis in the case of low temperature and slowly biodegradable material, or methanogenesis for soluble,




rapidly degradable feedstock (Miron et al., 1999). Increasing the HRT over 20 days appears to have little impact on biogas yield, and the high capital cost of increasing digester volume to accommodate the longer retention time suggests that techno-economics become unfavourable (Parkin and Owen, 1987).

The PS: SAS defines the proportion of sludge received for AD from the primary sedimentation process and secondary biological treatment. The anaerobic digestibility of these sludge types varies greatly. Primary sludge (PS) is a highly degradable material, constituted from a varying proportion of proteins, oil and grease, carbohydrates, fibres (mainly cellulose from toilet paper) and grit. Various authors reported the macro-constituents and elemental composition of PS, and average values are reported in Table 1. The anaerobic biodegradability of PS varies in the range of 50-70% VS, and the theoretical biogas yield depends on the composition, but is estimated in range of 900-1000 NLbiogas/kgVSdestroyed

(Parkin and Owen, 1987; Barber, 2014). A large concentration of pathogens is found in PS (Mininni et al., 2004) and their reduction or elimination is necessary if the sludge is applied to land for restoration or agricultural use (Water UK, 2006). Surplus activated sludge (SAS) is composed of microbial cells, extracellular polymeric substance (EPS), soluble microbial products (Shana et al., 2013) and suspended solids carried over from the primary sedimentation process. Because SAS arises from a biological reactor, its composition is more stable compared to PS. Proteins generated from the assimilation of soluble nitrogen (N) in wastewater comprise the largest fraction of VS in SAS. Typical values reported for SAS composition are listed in Table 1. Activated sludge is highly recalcitrant under anaerobic conditions, and only a small fraction, in the range of 20-44%VS, is accessible during the AD process (Winter and Pearce, 2010; Shana, 2013; Barber, 2014). Solids retention time (sludge age) in the activated sludge process has a strong impact on the biodegradability of SAS, and increasing age correspondingly reduces degradability (Bolzonella et al., 2005; Batstone & Jensen, 2011). Theoretical gas yields for SAS range between 800-900 NLbiogas/kgVSdestroyed (Parkin and Owen, 1987; Barber, 2014). Pathogens are commonly found in SAS, thus also this sludge stream requires pathogens stabilisation in order to be safely applied on land for agricultural use (Smith, 2014a). On the other hand, because nutrients, such as N and phosphorus (P) are concentrated in SAS (Mininni et al., 2004), its fertiliser value is high, and the AD process can be exploited to mineralise a fraction of these nutrients.

Table 1: Reported organic constituents for sewage sludge. Values indicate average and standard deviation.

Constituent PS SASProteins (%DS) 22% ± 4% 46% ± 5%Fibres (%DS) 21% ± 1% 2% ± 2%

Carbohydrates (%DS) 23% ± n/a 25% ± 3%Lipids (%DS) 14% ± 4% 4% ± 3%Ash (%DS) 26% ± 7% 23% ± 8%

Literature(Barber, 2014; Smith 2014b; Gonzalez, 2006; O’Rourke,

1986)

(Barber, 2014; Smith 2014; Gonzalez, 2006)

The overall aim of the research is to quantify the impact and interaction between the main operational control variables of temperature, OLR and PS: SAS on sewage sludge AD processes. The objectives are to measure the effects of these parameters, under accurately controlled conditions, on gas yield, specific gas production, VS destruction, reactor physico-chemical conditions and pathogen reduction. Efforts are made to minimise the intrinsic variability of sludge characteristics and parameters which are closely related to operational practice are selected as control variable, to highlight trends which might be valuable to AD practitioners and operators.




Methods and materials

Sludge source

Sewage sludge samples were collected at weekly intervals from Reading STW, which receives municipal wastewater from a population equivalent of approximately 220,000 people. Primary sludge was collected after lamella sedimentation, and it comprised indigenous sludge only. Surplus activated sludge was collected after belt thickening. The activated sludge plant comprises a series of anaerobic, anoxic and aerobic zones, and the average solids retention time was 20 days. In this research SAS refers only to activated sludge arising from suspended growth processes. A representative indication of the sludge composition is given in Figure 1.

Figure 1: Content of major organic constituents and ash in sewage sludge samples collected at Reading STW. Tot Carbo includes fibres, starch and sugar as sucrose. (Average values, n=10)

Experimental apparatus

Sludge thickening

A sludge thickening device was designed and constructed using woven drainage bags to increase control over the sludge DS concentration (Figure 2).Primary sludge, was collected from the desludging lines of the lamellae primary settlement tank at approximately 1.5% DS and was stored in an industrial bulk container. The sludge was pumped through a static mixer, dosed with polymer electrolyte, and transferred into the draining bags, to retain the solids and remove free water. The collected sludge had a DS concentration in the range 10-13%. In the case of SAS, the sludge was collected after the thickening belt at approximately 6% DS, and was pumped into draining bags to increase the DS content to approximately 9%.




Figure 2: Sludge thickening system for raw primary sludge

Anaerobic reactors

Autodigesters with 50 L working volume were used for this experimental programme (Figure 3). These are a development of an original design from Glamorgan University. The reactors were fully automated, completely stirred digesters and were supplied with sludge semi-continuously. The sludge feed was supplied from a refrigerated and stirred feed tank, which was cleaned and supplied with fresh sludge every week. The recirculation of sludge in the feed tank and the feeding and withdrawal of sludge in the reactor was performed using peristaltic pumps. The bio-reactor was equipped with a heating jacket, pH and temperature probes and a level sensor to control the active volume. The waste tank was located on a digital load cell and the mass of sludge withdrawn at every cycle was measured. Sludge was fed in batches at a frequency of 3 times per day. The biogas was conditioned through a copper sulphate catchpot to strip hydrogen sulphide (H2S) and silica gel to dry the gas. Gas was continuously monitored for CH4 and carbon dioxide (CO2) fractions and flowrate. The values expressed here refer to dry gas, normalised at 25oC and 1 Atm. The performance was measured as gas yield (m3/t dry solids fed (DSfed)) and specific gas production (m3/t volatile solids destroyed (VSdes)).




Figure 3: Image and schematic for autodigester apparatus

Sampling and physico-chemical analysis

The collected and prepared sludge was subsampled and the DS and VS content was measured each day. A range of other stability indicators (Table 2) were also measured on both feed and digested sludges at a frequency of twice per week. Microbiological enumeration of the indicator bacteria, Escherichia Coli, occurred at a frequency of once per week.

Table 2: Routine physico-chemical analysis performed on sewage sludge

Stability indicatorsAnalysis Method

pH ProbeAlkalinity Titration and Colorimetry

Volatile Fatty Acids Gas chromatographyAmmoniacal nitrogen Steam distillation and titration




Experimental design and treatments conditions discussed

General experimental design

The control variables selected as experimental treatments were temperature, OLR and PS: SAS. The range and rationale for the experimental conditions are indicated in Table 3.

Table 3: Range and rationale for experimental control variables

Parameter Minimum Median Maximum Reason for selected rangePS:SAS

(DS basis) 20:80 50:50 80:20Wide range of scenarios given by different plant configurations.

OLR (KgVS/m3/d) 1.5 2.75 4Current dry solids range achievable by conventional thickening units.

Temperature (oC) 37 41 45 Insufficient literature regarding upper mesophilic range.

Hydraulic retention time is kept constant at 16 days in all the treatment combinations.

The experimental design to quantify the interactive effects of the treatment parameters was constructed using the Box-Behnken method (Myers and Montgomery, 2009), a surface response statistical method, which optimises the selection of treatment conditions to minimize the standard error of regression coefficients. This statistical strategy requires treatment combinations at the midpoints of the range of experimental conditions and therefore provides the greatest statistical confidence around the centre of the experimental combination cube. The Box-Behnken simulation was completed using the Minitab statistical package and indicated that 12 experiments performed in duplicate would be necessary within the specified parameter range, as well as a six replicate experiment at the centre of the experimental cube. Each treatment combination was carried out as a pseudo-replicate based on multiple hydraulic retention times.

A single factor ANOVA analysis, with 95% confidence interval, was performed to compare the statistical significance of the treatment conditions.

Specific treatment conditions for variable for PS: SAS and temperature at constant OLR

The experiments considered in this section aim at showing the interactive effects of PS: SAS and temperature, at a constant loading rate of 2.75 kgVS/m3/d (6% DS concentration and 16 d HRT). The conditions of the experiments are summarised in table 4.

Table 4: Treatment conditions considered (Variable PS: SAS and temperature at constant OLR=2.75 kgVS/m3/d)

Conditions PS:SAS (%DS) Temperature (oC)

High PS 80:20 3780:20 45

High SAS 20:80 3720:80 45

Specific treatment conditions for variable OLR and temperature at constant PS: SAS

In this section results for constant PS: SAS=50:50 are considered. This sludge feed ratio is fairly typical for large STW with activated sludge plant. In this case only two experiments are considered, as indicated in table 5.




Table 5: Treatment conditions considered (Variable OLR and temperature at constant PS: SAS=50:50)

Temperature (oC) OLR (kgVS/m3/d)37 1.541 2.75

Results and Discussion

Variable PS: SAS and temperature at constant OLR

Gas performance and solids reduction

Figure 4 shows the time series for the high PS experiment, and Figure 5 for the high SAS experiment. It is evident from the figures that when the feed sludge contained a large proportion of PS, the variability of gas production was higher than when a high SAS fraction was used as feed. This was probably linked to the variable nature of the PS, which composition is largely influenced by the network and sedimentation efficiency of the lamellae. In the case of SAS, the sludge was more homogeneous and the gas production rate more predictable.

The statistical analysis of data indicated that for high PS there was no statistically significant difference between the two temperature regimes (table 5). A statistically significant difference was found for the specific gas production, with higher average value for the 45 oC treatment. When considering the values for VS destruction (VSD), it was found that a higher solids removal was obtained for the lower temperature. This was a further indication of the variability of the physico-chemical properties of the PS. This could imply that the temperature effects for high PS were negligible compared to the variability in sludge feed composition, even for a highly controlled pilot scale scenario. In the case of the high SAS treatment, the gas yield and VSD increased in the higher temperature condition, however no change in specific gas production was detected (Table 5). This suggested that the rate of hydrolysis increased with temperature and that a larger fraction of the solids was transformed into gas for an equivalent retention time.

The difference in gas yield and VSD observed between the high PS and high SAS treatments may be explained due to the different accessibility of substrates in the two sludge types. In the case of PS, substrates were apparently more readily available and quickly hydrolysable, compared to SAS which contains organic compounds that are less accessible to hydrolysis reactions (Pavlostathis and Giraldo-Gomez, 1991). The higher specific gas production rate for PS compared to SAS may also be explained by the higher fraction of fats in PS (Figure 1). Activated sludge is also a source of lipids, but this forms part of the cell wall and membrane (Milo and Phillips, 2015.) and is difficult to access during the AD process.




Figure 4: Effect of temperature on biogas yield (m3/tDSfed) [square markers] and specific biogas production (m3/tVSdes) [triangle markers] for anaerobic digestion of sludge feed containing 80 % primary sludge (PS) and 20% surplus activated sludge (SAS) (DS basis) at an organic loading rate of 2.75 kgVS/m3/d. Markers indicate daily average and lines represent 7 day rolling average.

Figure 5: Effect of temperature on biogas yield (m3/tDSfed) [square markers] and specific biogas production (m3/tVSdes) [triangle markers] for anaerobic digestion of sludge feed containing 20 % primary sludge (PS) and 80% surplus activated sludge (SAS) (DS basis) at an organic loading rate of 2.75 kgVS/m3/d. Markers indicate daily average and lines represent 7 day rolling average.




Table 5: Statistical analysis for biogas yield (m3/tDSfed), biogas production (m3/tVSdes) and VSD (%) for variable PS: SAS and temperature at constant OLR of 2.75 kgVS/m3/d. Values indicate average and relative standard deviation.

Conditions PS:SAS=80:20 PS:SAS=20:80

Gas yield (m3/tDSfed)

Specific gas production (m3/tVSdes)

VSD (%) Gas yield (m3/tDSfed)


VSD (%)

37 oC 459 ± 21% 1269 ± 20% 47.6 ± 14% 280 ± 13% 1084 ± 18% 34.5 ± 15%45 oC 453 ± 15% 1346 ± 16% 44.3 ± 8% 305 ± 16% 1117 ± 17% 36.7 ± 9%

p-value 0.605 0.045 0.001 0.000 0.144 0.011Reactor physico-chemical conditions

The stability conditions in the bio-reactor were determined from alkalinity and Amm-N, as these indicate the buffering capacity of the reactor and the potential inhibition from free ammonia (NH3), respectively; data are shown in Figure 6 and 7 for high PS and high SAS, respectively.

Figure 6: Effect of temperature on alkalinity (mg/L) [triangle markers] and ammoniacal nitrogen (Amm-N) (mg/L) [circle markers] for anaerobic digestion of sludge feed containing 80 % primary sludge (PS) and 20% surplus activated sludge (SAS) (DS basis) at an organic loading rate of 2.75 kgVS/m3/d. Markers indicate samples result and lines represent 7 day rolling average.




Figure 7: Effect of temperature on alkalinity (mg/L) [triangle markers] and ammoniacal nitrogen (Amm-N) (mg/L) [circle markers] for anaerobic digestion of sludge feed containing 20 % primary sludge (PS) and 80% surplus activated sludge (SAS) (DS basis) at an organic loading rate of 2.75 kgVS/m3/d. Markers indicate samples result and lines represent 7 day rolling average.

Raising the digestion temperature to 45oC increased the rate of VSD, consistent with the greater hydrolysis of organic substrates compared to cooler condition. The hydrolysis of the proteinaceous fraction is also increased under these conditions and, consequently, more Amm-N may potentially be produced. Ammoniacal-N generates bicarbonate and therefore contributes to total alkalinity of the reactor (Sotemann, 2005), therefore the amount of Amm-N produced by different feedstock materials has a major influence on process alkalinity. Thus, in the high PS treatment both alkalinity and Amm-N were raised by increasing the digestion temperature. Alkalinity was also significantly raised and to a greater extent relative to the high PS in the high SAS treatment at 45oC compared to 37oC. The increased production of Amm-N in the high SAS treatment compared to PS was probably explained because proteins constitute approximately 45% of SAS (Figure 1), compared to about 20% in PS, thus their breakdown generates a larger amount of Amm-N (Figure 6 and 7). However, no effect of temperature on the Amm-N concentration was detected when the proportion of SAS in the feed sludge was increased (Table 6). A possible explanation for this behaviour could be related to the equilibrium status of Amm-N, since at higher temperatures more NH3 is formed, as illustrated in Figure 9 (Hansen et al., 1997). Free NH3 is highly volatile (Vahlberg et al., 2013), and therefore volatilisation losses as gas from the system may increase.

Table 6: Statistical analysis for alkalinity (mg/L) and ammoniacal nitrogen (Amm-N) (mg/L) for variable PS: SAS and temperature at constant OLR of 2.75 kgVS/m3/d. Values indicate average and relative standard deviation.


Alkalinity (mg/L) Amm-N (mg/L) Alkalinity (mg/L) Amm-N (mg/L)

37 oC 5864 ± 8% 936 ± 8% 7382 ± 7% 1678 ± 10%45 oC 6545 ± 6% 1201 ± 29% 8718 ± 6% 1716 ± 18%

p-value 0.000 0.004 0.000 0.655




Figure 8: Fraction of free ammonia as function of temperature for typical anaerobic digestion conditions (Hansen et al., 1997)

Pathogen reduction

Pathogens were measured in both feed and digested sludge, and the results are summarised in Figure 9 and 10, for an influent sludge of 80% PS and 80% SAS, respectively. Values below the limit of detection (2.4 log10/gDS) are set to zero.

Figure 9: Effect of temperature on indicator pathogen (E.Coli) number (log10/gDS) in feed sludge [triangle markers] and digested sludge [circle markers] for anaerobic digestion of sludge feed containing 80 % primary sludge (PS) and 20% surplus activated sludge (SAS) (DS basis) at an organic loading rate of 2.75 kgVS/m3/d. Markers indicate samples result and lines represent 7 day rolling average.




Figure 10: Effect of temperature on indicator pathogen (E.Coli) number (log10/gDS) in feed sludge [triangle markers] and digested sludge [circle markers] for anaerobic digestion of sludge feed containing 20 % primary sludge (PS) and 80% surplus activated sludge (SAS) (DS basis) at an organic loading rate of 2.75 kgVS/m3/d. Markers indicate samples result and lines represent 7 day rolling average.

Digestion temperature had a significant effect on the E.Coli removal rate (Table 7), which increased at 45oC compared to 37oC. Furthermore, the sludge feed regime also influenced the removal rate and numbers in the high PS were consistently below limit of detection in the warmer digestion conditions. By contrast, numbers declined below the limit of detection after approximately 80 days in the high SAS treatment. A possible explanation for this behaviour is the presence of EPS in SAS, which may potentially retain and protect pathogenic organisms within the floc structure, reducing exposure to inhibitory processes and maintaining a less competitive environment for pathogen survival.

For both feed types, the reduction in pathogens level for the 45oC regime was higher than 3 log or 99.9%, which indicated that secondary digestion is not required to achieve a compliant product at a conventional AD site (99% minimum pathogen reduction), for the current UK legislation (Water UK, 2006).

Table 7: Statistical analysis for indicator pathogen (E.Coli) number (log10/gDS) for variable PS:SAS and temperature at constant OLR of 2.75 kgVS/m3/d. Values indicate average and relative standard deviation.


Pathogens in feed (log10/gDS)

Pathogens in digestate

(log10/gDS)

Pathogens in feed (log10/gDS)

Pathogens in digestate

(log10/gDS)37 oC 6.06 ± 14% 5.04 ± 14% 6.43 ± 6% 4.89 ± 12%45 oC 5.7 ± 23% <2.4 ± n/a 6.49 ± 6% 3.03 ± 10%

p-value n/a 0.000 n/a 0.000




Variable OLR and temperature at constant PS: SAS

Gas performance and solids reduction

The gas performance time series for the two treatments are indicated in figure 11.

Figure 11: Effect of temperature and OLR on biogas yield (m3/tDSfed) [square markers] and specific biogas production (m3/tVSdes) [triangle markers] for anaerobic digestion of sludge feed containing 50 % primary sludge (PS) and 50% surplus activated sludge (SAS) (DS basis). Markers indicate daily average and lines represent 7 day rolling average.

Typical gas yield reported in literature for a PS: SAS sludge feed regime equivalent to 50:50 is typically equivalent to approximately 350-380 m3/tDSfed (Wilson et al., 2011). The results presented here show that the gas yield rate was increased above this value and was in the range 380-400 m3/tDSfed (Table 9). This response may be explained because fresh indigenous PS was used in the experiments reported, as PS age and storage can increase gas losses and imported sludge may contain fractions of undetermined treatability (Giacalone et al., 2014). The statistical analysis of data showed that there was a significant increase in gas yield when the OLR and temperature were increased (Table 9). The VSD calculated by mass balance was increased for the lower temperature treatment, although VSD was similar for both digestion temperature conditions using the Van Kleeck (VK) calculation method (Switzenbaum et al., 2003). Consequently, the specific biogas production was apparently greater with the higher loading rate and temperature treatment based on the overall mean performance for the duration of the experimental period. However, the daily monitoring data (Figure 11) showed that the specific biogas production approached generally similar values for both experimental conditions after approximately 45 days. This may also suggest a degree of biomass adaptation over multiple hydraulic retention times.




Table 8: Statistical analysis for biogas yield (m3/tDSfed), biogas production (m3/tVSdes) volatile solids destruction (VSD) (%) and Van Kleeck VSD (%) for variable OLR and temperature for AD of sludge feed containing 50 % primary sludge (PS) and 50% surplus activated sludge (SAS) (DS basis). Values indicate average and relative standard deviation.

Conditions PS:SAS=50:50

Gas yield (m3/tDSfed)


VSD (%) VSD VK (%)

37 oC, 1.5 kgVS/m3/d 384 ± 7% 1033 ± 12% 46.2 ± 8% 44.9 ± 15%41 oC, 2.75 kgVS/m3/d 403 ± 9% 1195 ± 16% 44.2 ± 10% 44.8 ± 14%

p-value 0.006 0.000 0.036 0.915

Reactor physico-chemical conditions

The chemical conditions for the two treatments are indicated in figure 12.

Figure 12: Effect of OLR and temperature on alkalinity (mg/L) [square markers] and ammoniacal nitrogen (Amm-N) (mg/L) [triangle markers] for anaerobic digestion of sludge feed containing 50 % primary sludge (PS) and 50% surplus activated sludge (SAS) (DS basis). Markers indicate samples result and lines represent 7 day rolling average.

It is evident from the data that the change in treatment conditions led to a significant change in reactor physico-chemical properties (Table 10). In this case the increase in alkalinity and amm-N were attributable to the increase in organic loading rate, which was varied by increasing influent solids concentration. No sign of inhibition were found for the measured level of amm-N.




Table 9: Statistical analysis for alkalinity (mg/L) and ammoniacal nitrogen (Amm-N) (mg/L) for variable OLR and temperature for anaerobic digestion of sludge feed containing 50 % primary sludge (PS) and 50% surplus activated sludge (SAS) (DS basis). Values indicate average and relative standard deviation

Conditions PS:SAS=50:50

Alkalinity (mg/L) Amm-N (mg/L)

37 oC, 1.5 kgVS/m3/d 3229 ± 4% 635 ± 5%41 oC, 2.75 kgVS/m3/d 7360 ± 5% 1452 ± 2%

p-value 0.000 0.000

Pathogen reduction

Pathogens level in feed sludge and digestate were measured and are indicated in figure 13.

Figure 13: Effect of OLR and temperature on indicator pathogen (E.Coli) number (log10/gDS) in feed sludge [square markers] and digested sludge [triangle markers] for anaerobic digestion of sludge feed containing 50 % primary sludge (PS) and 50% surplus activated sludge (SAS) (DS basis). Markers indicate samples result and lines represent 7 day rolling average.

Although the data are scarce for the low temperature and low load treatment, it is evident that an increase in temperature to 41oC did not bring benefits to the pathogen reduction potential. Table 11 summarises the average values, and this reduction level is in line with what reported in literature for mesophilic AD (Smith et al., 2005).

Table 101: Statistical analysis for pathogen levels (Variable OLR and temperature at constant PS: SAS)

Conditions PS:SAS=50:50Pathogens in feed

(log10/gDS)Pathogens in digestate

(log10/gDS)37 oC, 1.5 kgVS/m3/d 6.0 ± 18% 4.7 ± n/a

41 oC, 2.75 kgVS/m3/d 6.7 ± 6% 5.1 ± 15%p-value n/a 0.546




Conclusions

Interactive effects of temperature and PS: SAS ratio have been detected on AD gas production rate and solids destruction.

Increasing the digestion temperature improved the gas yield for high SAS treatments, by increasing the hydrolysis rate and VS destruction.

However, temperature has no significant effect on the average gas yield for high PS feed, due to the larger variability of composition, high biodegradability and hydrolysis rate of this substrate type.

The parameters having the greatest impact on alkalinity, from greatest to lowest, were OLR, PS: SAS and temperature.

The pathogen reduction potential of AD depended upon the process temperature and PS: SAS ratio.

Increasing the temperature from 37 to 41 oC had no significant effect on pathogen reduction and the overall mean removal rate was 97.5%.

However, increasing the digestion temperature to 45oC increased the rate of pathogen reduction to 99.9%, for both high PS and high SAS. This implies that for this temperature regime secondary digesters would not be required to achieve a compliant product at a conventional AD site.

For a standard treatment at PS:SAS=50:50, increasing the temperature and load from 37 to 41oC, and 1.5 to 2.75 kgVS/m3/d. respectively, brought minor benefits in terms of gas yield, but significantly improved reactor alkalinity and thus digestion stability.

Acknowledgements

This work was carried out as part of the Thames Water Utilities Innovation Programme and the requirements for the EngD STREAM Programme in the Department of Civil and Environmental Engineering, Imperial College London. The views expressed in the paper are those of the authors and not necessarily those of Thames Water.

The authors thank all the people who contributed to the various aspects of this project, especially the members of the steering group Pete Pearce, Paul Fountain, Achame Shana, Nick Mills, Peter Vale, Dave Auty, Aurelien Perrault and Ester Rus. The author is also grateful to the people who helped with the experimental work Franziska Wiedecke, Johanna Bobbio, Sam Jarvis and Dejene Tilahun.

This project was sponsored by Thames Water, Anglian Water, Severn Trent Water and the Engineering and Physical Sciences Research Council.




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