THE POTENTIAL FOR CO-DIGESTION OF ORGANICS USING THERMAL HYDROLYSIS AT BLUE PLAINS ADVANCED WASTEWATER TREATMENT WORKS

Bill Barber1, Chris Peot2, Matt Higgins3, Bo Bodniewicz1, Jim Marx1, Walter Bailey2, Bernhard Wett, Saul Kinter2, Ahmed Al-Omari2, Sudhir Murthy2 1. AECOM, 2. DC Water, 3. Bucknell University ABSTRACT The District of Columbia Water and Sewer Authority (DC Water) have recently installed a state of the art biosolids processing facility at its Blue Plains wastewater treatment works. The facility, the first of its kind in North America, will generate approximately 10 MW electricity by thermally hydrolyzing and digesting site-generated sewage sludge. In addition, it will produce Class A biosolids cake which further reduces DC Water’s carbon and environmental footprint. In order to optimize the use of this facility, DC Water are investigating the impact of co-digesting other organic materials to further increase renewable energy and provide financial benefits for its rate-payers. Tests looking specifically at food-waste show it to be a good candidate for co- digestion. When compared to two control reactors in a laboratory study, a digester supplemented thermally hydrolyzed food-waste to similarly processed sludge, as an increase in COD loading, resulted in an increase in biogas consistent with the loading rate and improved biodegradability of the food-waste fraction. This increased the total COD destruction and volatile solids destruction (by mass balance) compared to the controls. Due to high degradability, the solids yield produced from the food-waste was much lower than that from sludge. As the food-waste had a higher carbon:nitrogen ratio, its addition resulted in a statistically significant drop in pH which helped reduce free ammonia levels, known to limit the process, although not found to be inhibitory in the trials. It was determined that up to 600 m3 of the food- waste could be added daily prior to the need for a major infrastructure upgrade.

INTRODUCTION The District of Columbia Water and Sewer Authority (DC Water) operates the Blue Plains Wastewater Treatment Plant (Blue Plains), which is the largest advanced wastewater treatment plant (AWTP) in the country, with a design capacity of 370 million gallons per day (mgd) and a peak capacity of 1.076 billion gallons per day. The plant is located in the District of Columbia between Interstate 295 and the Potomac River, occupying approximately 150 acres. The existing wastewater treatment processes at the Blue Plains AWTP consists of preliminary treatment, secondary treatment, nitrification / denitrification, effluent filtration, chlorination / dechlorination and post-aeration. DC Water has recently undergone a major overhaul of its sludge processing capability. This has resulted in a move away from Class B lime stabilization producing 1,200 wet tons biosolids/day, to the installation of anaerobic digestion preceded by thermal hydrolysis plant – based on Cambi™ technology (Figure 1) – as a conclusion of a previously completed Biosolids Master Plan. The benefits associated with the overhaul are: production of renewable energy in the form of biogas, generation of Class A biosolids and ease of operation. The production of energy, reduction in biosolids production (by approximately 50%), improvement in dewaterability, reduced transport requirements, and the fact that lime is no longer required, all combine to help reduce DC Water’s carbon footprint by 40% and assist in the attainment of energy neutrality. In addition, it is expected that the new infrastructure will reduce operational expenditure by approximately $20 million annually. While the current wastewater configuration at Blue Plains consumes 26 MW of electricity, the new facility is expected to generate approximately 10 MW of power. Based on the expected flows and loads from 330 mgd, energy generated from biogas is expected to be in the order of 0.20 kWhr/m3 influent added. This compares with energy requirements of Blue Plains Advanced Wastewater Treatment works of 0.53 kWhr/m3 published previously. As part of a wider initiative, DC Water is pro-actively pursuing ways to minimize its energy demand and associated environmental impact. This is being achieved by deployment of a multi-faceted approach involving, reduction of aeration demand during nutrient removal by use of deammonification, renewable energy from solar, and anaerobic digestion of sludge produced on site to generate renewable energy through turbines as mentioned above. The production of renewable energy in this way can be further enhanced by exploiting the spare capacity of the anaerobic digestion plant and associated ancillary infrastructure by the addition of external energy sources in the form of waste organics by co-digestion.

Figure 1. Section of the Cambi ® thermal hydrolysis process installed at Blue Plains

Although co-digestion of waste materials poses challenges, on the whole, it is viewed as highly beneficial, from both a financial and environmental aspect. A recent study by WERF (2010) identified numerous benefits of co-digestion sub-divided into three areas of: technical; economic, and environmental benefits. Local authorities in the US, as well as European Governments see co-digestion as a means to increase production of renewable energy to assist with State targets, reduce reliance on landfill which is not considered sustainable, and reduce carbon impact helping to meet emissions reductions targets. In addition, co-digestion of waste organics at a municipal wastewater treatment works can provide tangible financial benefits which can be used to off-set costs and ultimately passed on to rate payers. A recent study by the EPA (2014) highlighted six success stories where co-digestion has been employed with potential pay-back times from just under 3 to 12 years. The stand-out success story was based on experience at East Bay Municipal Utilities District (EBMUD) which calculates annual benefits of $11M (EPA, 2014), of which over 70% come from tipping fees which range from 3 cents/gallon to $30/ton solid waste. To determine the viability of co-digestion at Blue Plains, a laboratory study was conducted in conjunction with Bucknell University looking specifically at pre-processed food-waste from a Waste Management site in California. The aim of which was to quantify the influence of adding food-waste to thermally hydrolyzed sludge so that the economic and environmental impacts could be determined.

Co-digestion of food-waste According to the U.S. Environmental Protection Agency (EPA), food waste represents 14.5% of (MSW), and most of what’s generated is wasted. Of the 251 million tons of MSW Americans generated in 2012, food waste comprised 36.43 million tons, of which only 1.74 million tons (4.8%) was recovered. An estimated 216 wastewater treatment facilities located in the U.S. haul in food waste (primarily FOG) for co-digestion with sewage sludge. This accounts for approximately 17% of all municipal plants which use anaerobic digestion (EPA, 2014). A great deal of work has been conducted on the anaerobic digestion of food-waste, both as a mono- and co-substrate and with various inocula (Tampio, et al., 2014; Mata-Alvarez, et al., 2014; Spargiminio et al. 2014; Rajagopalan et al., 2014; Kangle et al., 2012, Iacovidou, et al., 2012; Banks, and Zhang, 2010). Table 1 summarizes the main findings. Food-waste co-digestion influences performance of anaerobic digestion in various obvious and not so obvious ways. Being more biodegradable and having inherently higher energy content than sludge, it is clear that addition of food-waste can significantly increase biogas production compared to a case where the food-waste is absent. As food waste has a much higher carbon to nitrogen ratio than sludge, its addition to alter the bulk carbon to nitrogen ratio within a digester has been shown to provide success with improving the digestion process itself (Mata-Alvarez, et al., 2014). However, as food-waste also contains nitrogen compounds which originate from protein, addition of food has been found to increase ammonia levels during anaerobic digestion (Banks and Zhang, 2010). In studying the influence of pre-processed food-waste on standard mesophilic digestion, Kuo- Dahab and co-workers (2014) studied the impact of varying loading rate on digester performance. They added food-waste in proportions of 10, 20, 50 and 100% comparing performance to digesters not fed any food-waste. In terms of loading rates, the addition of 50% food-waste was equivalent to 4.19 kg VS/m3.d. The study concluded that the optimal dosage rate was 50%, however, closer look at the data reveals that improvements in gas production starts to tail-off prior to that addition rate. This may be due to the continued addition of ammonia which may accumulate (Banks and Zhang, 2010) and cause inhibition (Rajagopal et al., 2013) or wash out of trace nutrients required for biogas production (Banks and Zhang, 2010).

Table 1. Observations specific to food-waste co-digestion Observation Reference Food-waste is more biodegradable than sludge Rajagopalan et al., 2014; Banks and Zhang, 2010 Food-waste produces a higher gas yield than sludge Banks and Zhang, 2010

Food-waste adversely influences dewatering Fü, et al., 2015 Rajagopalan et al., 2014 Increases sodium and potassium concentration in Rajagopalan et al., 2014 digestate

Increases system ammonia Banks and Zhang, 2010; Iacovidou, et al., 2012 Substrate diversification and better nutritional Mata-Alvarez, et al., 2014; balance can lead to a more versatile and robust Rajagopalan et al., 2014; Rajagopal, microbial community 2013; Goberna et al., 2010 Has an optimal loading rate 50% for standard Kuo-Dahab, et al., 2014; mesophilic digestion

Improves degradation of propionate Banks and Zhang, 2010

Is more suited to standard digestion than autoclaving Tampio, et al., 2014; Spargiminio et al., 2014 Can improve digestion by altering carbon:nitrogen Mata-Alvarez, et al., 2014; Kangle et ratio. Ideal ratio for anaerobic digestion between 16 al., 2012; Iacovidou, et al., 2012; and 35 Banks and Zhang, 2010 Massé et al., 2003; Kayhanian, 1999

Increases sludge production, however by less than Kuo-Dahab, et al., 2014 would be expected by mass balance

May accumulate heavy metals at full-scale, not Iacovidou, et al., 2012; Pahl et al. generally observed at laboratory or pilot-scale 2008 especially Zn, Pb and Ni

May wash out nutrients, especially Se, and Co. Banks and Zhang, 2010 Evidence to suggest washout of Mo and W, also considered important for acetoclastic methanogenesis.

As well as increasing biogas production, the addition of food-waste may have adverse impacts on dewatering. Food-waste co-digestion appears to result in the release of mono-valent cations, especially sodium and potassium and this is thought to interfere with bridging potential during dewatering which results in deterioration (Rajagopalan et al., 2014). In addition, the provision of a readily biodegradable substrate will increase kinetic rates of faster growing organisms, which, by default, will increase the production of growth related extracellular byproducts (Barker and Stuckey, 1999). A link has been found between the production of these materials and deterioration in dewatering performance, specifically related to food-waste co-digestion (Fü, et al., 2015). In that study, food-waste substrate was added in a ratio of inoculum to substrate of 4:1 on a volatile solids basis which the authors found to be the optimized loading rate. They concluded that food-waste fed digesters produced digestate which exhibited similar dewatering characteristics as and was strongly influenced by the production of protein rich extracellular polymer substances. They also found that digestates from restaurant food waste were inferior with respect to dewaterability compared to those generated from co-digestion of household kitchen waste. However, the inferior dewatering characteristics may be partially positively offset by a reduction in biosolids production. Whereas the biosolids yield from standard mesophilic digestion can be approximately 0.60 to 0.65 kg solids out/kg solids in, figures determined for studies where food- waste is co-digested have shown lower results, due in part to the higher digestibility of the material being added. Spargiminio’s group (2014) found sludge yields ranging from 0.2 to 0.3 for food-waste fed digesters, and low yields were also observed in the work of Rajagopalan et al., (2014) based on bench-scale studies of Californian based pre-processed food-waste. MATERIALS AND METHODS Pre-processed food-waste was supplied by Waste Management from a site in California for this study. The food waste was a homogenized material and stored in a freezer until use. The food- waste was approximately 13% dry solids of which 80% was volatile and had a COD concentration ranging up to approximately 200,000 mg/l. In order to determine the impact of food-waste co-digestion a number of 10 liter lab-scale anaerobic digestion chemostats (Figure 2) were set-up. Details of the experimental set-up are described elsewhere (Xiao et al., 2014). The reactors were fed a blend of thermally hydrolyzed sludge and food-waste once a day at the same time. The following were measured: TS/VS (Influent and Effluent) TCOD, sCOD (Influent and Effluent) Headspace Gas (CH4, CO2, H2, MT, DMS) total gas volume and gas production rates, + pH, and alkalinity, viscosity, NH4 , other cations, VFA concentration and speciation. In addition, carbon, hydrogen and nitrogen measurements were made for sludge and food-waste. A control reactor fed only thermally hydrolyzed sludge was configured at 18 days hydraulic retention time (HRT), which corresponded to a daily feeding rate of 0.56 l/d. A test reactor was set-up whereby food-waste was added at approximately 25% by load COD (corresponding to 0.11 l/d of food- waste – total daily flow of 0.67 l/d), and this reduced the retention time to 15 days. For completeness a second control reactor was used for comparison which was run at 15 days with no food-waste. Going forward, the three digesters will be referred to as: 18 day HRT, 15 day HRT (food) and 15 day HRT. The inputs to the digesters are given in Table 2. In order to determine the impacts of co-digestion, the results were analyzed in two different ways. In the first, correlations were sought on a basis of material coming into, and exiting a particular digester. For example, if 1 kg COD enters the digester, how much exits in the biogas, and how much in the effluent. This type of analysis was conducted to determine the actual influence of the food-waste. The second way the results were analyzed was to compare digesters against one another in terms of performance. In order to determine any statistical significance in the experimental findings, 2-tailed T-tests were conducted at 95% confidence based on the methodology proposed by Gossett (Student, 1908). For purposes of comparison, all results across the entire experimental period were used.

Figure 2. Typical lab-scale anaerobic digester used in test

Table 2. Input data for lab-scale co-digestion experiments Data 18d HRT 15d HRT (food) 15d HRT Input DS Average [%] 12.31 11.42 10.40 95% confidence ±0.03 (145) ±0.16 (102) ±0.03 (145) Input VS Average [%] 9.69 9.14 8.20 95% confidence ±0.04 (145) ±0.12 (102) ±0.04 (145) Input total COD load Average [mg/d] 94007 111303 95301 95% confidence ±1536 (40) ±5256 (26) ±1766 (39) Input soluble COD load Average [mg/d] 21667 27217 21927 95% confidence ±918 (34) ±1775 (26) ±717 (33) Input VS load Average [mg/d] 53186 60302 53407 95% confidence ±868 (145) ±1338 (101) ±1132 (145) Input ammonia load Average [mg/d] 324 314 323 95% confidence ±55 (33) ±34 (26) ±49 (33)  Numbers in parentheses refer to sample size

As can be seen from Table 2, the test digester was fed approximately 20% more total COD than either of the other two digesters, and circa 14% more material on a volatile solids basis. These figures relate to loading rates of 9.2 kg COD/m3.d and 5.4 kg VS/m3.d for the control digesters, compared to 11.0 kg COD/m3.d and 6.1 kg VS/m3.d rates for the test digester. RESULTS Performance and biogas Table 3 summarizes the main performance results of the three digesters. Table 3. Summary of performance of co-digestion experiments Data 18d HRT 15d HRT (food) 15d HRT Gas Production Average [mls/d] 30130 36728 31942 95% confidence ±609 (244)  ±745 (177) ±505 (245) t-test (2 tailed at 95% sig) Food reactor Food reactor 22% higher 18% higher Total COD destruction Average [%] 52.6 58.3 53.1 95% confidence ±1.2 (38) ±1.1 (30) ±1.3 (38) t-test (2 tailed at 95% sig) Food reactor Food reactor 11% higher 10% higher Soluble COD destruction Average [%] N/A 50.7 43.8 95% confidence N/A ±2.4 (26) ±3.6 (34) t-test (2 tailed at 95% sig) Food reactor N/A 16% higher Volatile Solids destruction (MB) Average [%] 52.7 56.4 52.7 95% confidence ±0.8 (107) ±0.6 (76) ±0.5 (107) t-test (2 tailed at 95% sig) Food reactor 7% Food reactor 7% higher higher Volatile Solids destruction (VK) Average [%] 54.2 55.7 54.9 95% confidence ±0.9 (105) ±1.1 (72) ±0.9 (106) t-test (2 tailed at 95% sig) No significance No significance  Numbers in parentheses refer to sample size  Student t-test conducted to determine statistical difference between non-food and food fed reactors. Text refers to level of significance. No significance implies that data sets for both non-food and food fed reactor are statistically equivalent.

As one would expect, the test reactor produces more biogas than either control tests, and being more biodegradable, increases the weighted average destruction of total and soluble COD and volatile solids based on Mass Balance. Interestingly, no statistical influence was observed in performance when volatile solids destruction based on Van Kleek was compared. Although a significant increase in biogas was observed in the test reactor, it was similar to the increase in total COD fed to the reactor. In order to better understand the gas data, yields were determined based on a variety of input variables. These are shown in Table 4. Table 4. Summary of gas yield results Data 18d HRT 15d HRT 15d HRT (food) Yield per total COD fed Average [ml biogas/mg tCODfed] 0.32 0.34 0.34 95% confidence ±0.02 (39) ±0.03 (26) ±0.02 (39) t-test (2 tailed at 95% significance) No No significance significance Yield per soluble COD fed Average [ml biogas/mg sCODfed] 1.45 1.40 1.50 95% confidence ±0.10 (34) ±0.12 (26) ±0.07 (33) t-test (2 tailed at 95% significance) No No significance significance Yield per VS fed Average [ml biogas/mg VSfed] 0.57 0.62 0.59 95% confidence ±0.01 (138) ±0.02 (100) ±0.01 (142) t-test (2 tailed at 95% significance) Food digester No 8% higher significance Yield per total COD destroyed Average [ml biogas/mg tCODdestroyed] 0.61 0.58 0.60 95% confidence ±0.03 (40) ±0.05 (26) 0.03 (39) t-test (2 tailed at 95% significance) Non-food No digester 6% significance higher Yield per soluble COD destroyed Average [ml biogas/mg sCODdestroyed] N/A 2.83 N/A 95% confidence N/A ±0.29 (26) N/A t-test (2 tailed at 95% significance) N/A N/A Yield per VS destroyed Average [ml biogas/mg VSdestroyed] 1.08 1.12 1.11 95% confidence ±0.06 (106) ±0.03 (77) ±0.05 (109) t-test (2 tailed at 95% significance) No No significance significance  Numbers in parentheses refer to sample size  Student t-test conducted to determine statistical difference between non-food and food fed reactor. Text refers to level of significance. No significance implies that data sets for both non-food and food fed reactor are statistically equivalent.

As can be seen from Table 4, the addition of food-waste did not appear to influence the yield of biogas, regardless of the unit of measure. Based on the loading rates of the experiments described herein, these results did not show that the addition of food-waste had synergistic impacts on biogas production or improved overall sludge digestability. This was further supported by data showing release of ammonia – which increases with increasingly good performance – which showed no statistical significance between test and either control digester (discussed later). Data was also determined from analysis of the carbon, hydrogen and nitrogen content of the food-waste and sludge. Unfortunately, no measurements were made on either Oxygen or Sulfur. It was therefore assumed that the measured data comprised of 95% of the volatile fraction. Based on the measured data, a variety of specific determinants were calculated from theory. These are shown in Table 5 Table 5. Specific parameters for sludge and food-waste used in this study Data Sludge Food Waste Molecular formula C9.8H18O3.8N C19H36O5.3N C/N ratio 8.4 16.3 COD equivalence 1.771 2.169 3 Biogas Yield [Nm /kg CODeq destroyed] 0.889 1.084 3  Biogas Yield [m /kg CODeq destroyed] 1.016 1.237 Biogas Methane Content [% CH4] 70 70 Calorific Value [kJ/kg LOI]  25,250 30,430  Adjusted to digester temperature  LOI refers to Loss On Ignition

Most of the results appear consistent with previous work from the literature. However, the calorific value for the food-waste is 20 – 25% higher than measured elsewhere (Banks and Zhang; 2014). The stoichiometric data calculated in Table 5 was used to check the mass balance results for the test digester to enable calculation of biogas production from food-waste and sludge independently. In order to do this, it was assumed that COD from the sludge fraction in the test digester digested no differently to the non-test digesters, i.e. approximately 53%. Based on this assumption, COD destruction for the food fraction was back-calculated as 77% to enable the weighted average to be consistent with that measured for the test digester of 58%. According to these findings, a theoretical biogas production for the sludge fraction of 28,368 ml/d was determined from stoichiometry compared to 30,130 ml/d measured result for 18 day HRT digester with no food. Subsequently, a separate biogas production of 7,480 ml/d was determined for the food fraction. This gave a total theoretical biogas production of 35,848 ml/d for the test digester, compared to 36,728 ml/d giving a 97% fit. The closeness in the theoretical and measured data, suggest that the assumption that the sludge digested similarly regardless of the presence of food-waste appeared valid, and also strengthened the data which showed no synergistic impacts of the food-waste. This may be partially due to the fact that primary sludge, which digests well to begin with, makes up a large proportion of the sludge entering the anaerobic digestion system at Blue Plains. The results suggest that an increase in biogas production based on addition of food-waste is directly related to the additional total COD load added combined with the fact that the COD added has a higher COD destruction rate attached to it. A Sankey diagram showing the split of COD between influent, biogas and effluent is shown in Figure 3 based on these calculations.

Figure 3. Sankey diagram showing breakdown of influent COD into biogas and digestate. Calculated based on comparing food fed digester with 18d HRT digester

Solids Production The additional solids produced from co-digestion may play a major role in understanding the economics of co-digestion. Whilst interviewed utilities admitted to additional biosolids production for a survey by the EPA, none would reveal how much of the solids were due to the addition of co-digestates (EPA, 2014). Previous work on pre-processed food waste has shown that the solids generated from co-digestion are much lower than would be expected based on mass balance by volatile solids destruction (Rajagopalan et al., 2104; Spargiminio et al., 2014). Based on standard mesophilic digestion, a typical biosolids production of around 0.6 kg output/kg fed can be expected, based on a volatile solids content of 75% and typical volatile solids destruction. In this study, both control reactors exhibited similar biosolids production rates of 0.60 ± 0.06 for 15 days HRT and 0.60 ± 0.05 for 18 days HRT respectively at 95% confidence. The digester to which food-waste was added had a weighted average biosolids yield of 0.57 ± 0.05 at 95% confidence. Assuming that the sludge portion of the feed generated a similar yield in the test digester – consistent with previous assumptions – then, for the weighted average data to match 0.57 kg/kg, the biosolids yield from the food-waste fraction independently is equivalent to 0.45 kg/kg. This number is higher than data recorded elsewhere (Spargiminio et al., 2014), and could be a consequence of previous work which showed higher gas yields (i.e. better performance) for food-waste co-digestion in absence of autoclaving compared to digesters fed the same material which had not been pre-processed (Tampio et al., 2014). pH and ammonia

It is well understood that (mainly) free unionized ammonia controls the upper pH limits of anaerobic digestion. Increasing pH and temperature both shift the equilibrium position away + from ammonium (NH4 ) to its unionized form (NH3). Having no charge enables the unionized molecule to diffuse more rapidly through the cell membrane and this may cause a proton imbalance or a potassium deficiency. Conversely charged ammonium may inhibit the methane synthesizing enzymes directly (Chen et al., 2014). Ammonia is released from the catabolism of proteins, and therefore increases significantly with increasing sludge content and improving performance of digestion. As both of these are relevant to digestion systems employing thermal hydrolysis, it is important to find ways to alleviate toxicity of ammonia, especially the unionized fraction.

Numerous possible remediation techniques have been reported for the control of ammonia inhibition during anaerobic digestion. These include: struvite precipitation; Anammox, and use of zeolite and carbon fiber textiles. However, the cost of these techniques prohibits their use at large scale. Acclimation of methanogenic consortia to high ammonia levels or raising ammonia tolerance capacity has proven to be a useful and economical method for improving the anaerobic digestion of numerous waste streams (Massé et al., 2003; Kayhanian, 1999). Another way to reduce ammonia toxicity is to reduce digester pH by altering the carbon:nitrogen ratio (Chen et al., 2014; Kayhanian, 1999). It was hoped that addition of food-waste to a digestion system based on thermal hydrolysis would reduce pH, by the rapid production of volatile fatty acid intermediates, and therefore reduce toxicity potential from ammonia present which would ultimately aid with process efficiency and stability, potentially allowing an increased loading.

In this study input ammonia loads were not statistically significant at 95% confidence between the test and two control reactors and were in the range of 314 to 324 mg/d (Table 2). Although the food-waste supplemented reactor had 25% additional loading in the form of COD, elemental analysis showed that the nitrogen content was lower (3.8% of VS) than that of sludge (6.7%). Whilst ammonia concentrations for test reactor and 15 day non-food reactor were similar at 471 ± 48 (at 95% confidence) and 482 ± 72 (at 95% confidence) for test and 15 day reactors respectively, the input ammonia concentration was statistically higher for the 18 day digester at 578 ± 98 (at 95% confidence). These figures followed a similar trend with respect to digester concentrations with both reactors at 15 days (food and no food) showing levels of ammonia consistent with thermal hydrolysis at approximately 2600 mg/l. However, the 18 day digester maintained its higher concentration at over 3100 mg/l. There was no statistical significance in the release of ammonia between the 18 day digester and that processing the food-waste with approximately 6 times the load of ammonia in the effluent compared with the influent.

As previously mentioned, it was hoped that the addition of a higher carbon:nitrogen waste to the digester would reduce pH. A statistically significant drop in pH of 0.1 units from 7.78 to 7.68 was noted at 95% confidence with 298 degrees of freedom between the control digester at 18 days and the one fed the food. Subsequently, free ammonia concentration in the food-fed reactor was statistically significantly lower by 33%, with a figure of 149 ± 11 (at 95% confidence) for food-fed digester compared with 222 ± 21 (at 95% confidence) in absence of food. The influence of the pH drop of 0.1 unit on reduction of free ammonia was calculated at the average ammonia concentration at pH values of 7.68 and 7.78. The pH drop accounted for a reduction of 24% (out of the 33% observed) for free ammonia. The difference between 33 and 24% could be explained by a higher influent ammonia in the non-food-fed reactor. However, the performance data proposes that most of the COD was readily degraded, which suggested that the free ammonia levels observed in these experiments, regardless of the presence of the food, were not causing any significant inhibition. This was backed up by Ripley Ratio’s of less than 0.1 for all of the digesters tested. In addition, when output data on volatile fatty acids were converted to COD equivalents (data not shown), they contributed only 2% to 4% to the soluble COD exiting the reactor, demonstrating no inhibition of intermediate acid degradation. These findings are similar to those summarized by Rajagopal el al (2013) who reported on the anaerobic digestion of chicken manure and found no toxicity to methanogenesis up to 250 mg/l free ammonia (FA) in digesters fed at 10% dry solids. However, even this figure appears low when compared to other studies. In a review article investigating the impacts of toxicants on anaerobic digestion, Chen and co-workers (2014) described a study which concluded that a threshold for free ammonia which could be tolerated was 620 mg/l corresponding to a carbon:nitrogen ratio of approximately 4 which is approximately half of typical sewage sludge. IMPLICATIONS The biosolids facility at Blue Plains is designed such that it can accommodate peak flows of 450 tDS.d of biosolids without the need to engage in use of a back-up facility. Therefore, with average flows there is spare capacity running throughout the biosolids processing plant. Subsequently, there is potential for adding other materials such as the food-waste described in this paper. After analysis of the lab-data and calculation, the value of 1 m3 of food-waste was determined, and is summarized in Figure 4.

Figure 4. Calculated impact of 1 m3 food-waste determined from laboratory data collected in this study.

Figure 4 shows that addition of 1 m3 of food-waste is expected to generate 83 Nm3 which contain approximately 36 kg of methane and 58 kg of carbon dioxide. The calorific value of the gas quantity generated from 1 m3 food-waste is circa 593 kWhr. Assuming this is burnt in an engine with electrical conversion efficiency of 37%, a quantity of 0.025 kWe would be generated from this amount of food-waste. Based on loading rates, if 150 m3 of food-waste are supplemented, biogas production would increase by 12% although the loading rate only by 8.6%, and volumetric throughput by 5.3%. Addition of material will obviously have an impact on the amount of spare capacity of the plant, until major infrastructure upgrades are required. Figure 5 shows the influence of adding increasing quantities of food-waste based on the characteristics highlighted in Figure 4 on installed capacity of the main process units, namely: the turbines; the mesophilic anaerobic digestion system (MAD); thermal hydrolysis plant (THP) and dewatering. The capacities are determined assuming a baseline sludge feed load of 280 tDS.d.

Figure 5. Influence of adding increasing quantities of food-waste on available capacity of main unit operations. The graph shows existing used capacity in absence of food-waste addition is between 50% for dewatering, and up to approximately 65% for anaerobic digestion. It is interesting to note that the rate of capacity loss is different for the unit operations with increasing food-waste addition. Initially, there is more digestion than turbine capacity. However, as the material being added is relatively concentrated and generates a high biogas yield, the impact on the digestion plant is lower than that on the co-generation facility. In terms of rate loss; turbine capacity is consumed at a rate of 5.5%/100 m3 food-waste added, compared to 3.4%/100 m3 loss for digestion; and 2.9%/100 m3 for thermal hydrolysis. Due to the low yield of biosolids generated from the food- waste, the capacity loss in dewatering is only 1.9%/100 m3. Based on the above analysis approximately 600 m3 food-waste could be added before major infrastructure is required in the form of a turbine, followed a little later by more digestion capacity and a while later by additional thermal hydrolysis. It is not expected that the dewatering plant will be rate-limiting for co-digestion unless enormous quantities of materials are supplemented to the biosolids processing facility. The addition of food-waste will have an impact on truck movements, with trucks entering the Blue Plains site to off-load the material, and additional biosolids trucks exiting the facility to accommodate the additional biosolids due to the degradation of the food-waste. Figure 6 shows the expected increase in truck movements due to co-digestion based on deliveries 5 days a week in 20m3 trucks.

Figure 6. Impact of food-waste co-digestion on additional transport movements Owing to the low biosolids generation due to co-digestion, as previously discussed, the number of trucks exiting the site due to additional biosolids production as a direct consequence of co- digestion are only between a quarter and a third of the number of trucks delivering the food- waste. Although truck movements increase, the total number of trucks based on the new biosolids facility is still significantly lower (approximately half) of the previous liming process. CONCLUSIONS This study demonstrates numerous benefits of co-digesting food-waste. These include increased biogas production, potentially improved bacterial communities which aid with digestion stability and operation, and lowering of pH causing a reduction in free ammonia concentration. It is possible that reduced free ammonia may enable higher loading rates to be accommodated, although inhibition due to ammonia was not found in this study. The biosolids produced from food-waste itself are also small compared to sludge, thereby minimizing cost increases due to additional biosolids production. Based on the current configuration of Blue Plains, it is possible to add up to 600 m3 food-waste daily, assuming similar characteristics to the one tested.

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