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Supporting Information Mass balance and life cycle assessment of biodiesel from microalgae incorporated with nutrient recycling options and technology uncertainties List of Authors: Juhong Yuana, Alissa Kendallb, Yizhen Zhanga a. Institute of Transportation Studies, University of California, Davis, 1605 Tilia Street, Suite #100, Davis, CA 95616, USA. Email: [email protected]. b. Corresponding author. Department of Civil and Environmental Engineering, University of California, Davis, 1 Shields Avenue, Davis, CA, 95616, USA. Email: [email protected], Phone: +1-530-7525722, Fax: +1-530-752-7872. S-1 Section S1. Nutrients and carbon requirement and optimal N-P ratio There exist complex interactions between nutrients, especially N and P, in mass culturing of algae, as observed by many researchers (Ahlgren, 1977, Kunikane & Kaneko, 1984, Kunikane et al., 1984, Smith, 1982). S. dimorphus typically has protein content of 8% to 18% of the total biomass, though protein content can reach 35% under certain culture conditions (Demirbas & Demirbas, 2011, Wang et al., 2012). In the model developed here a C:N:P composition of 100:9:1 and 100:3:1 is used for normal N conditions and low N conditions, respectively. These ratios are similar to a few recent studies that assumed normal-N conditions, for example a C:N:P ratio of 100:11:1 (Chisti, 2007) and 103:10:1 (Frank et al., 2011). N deprivation has been a common strategy to stimulate high lipid content in algae. Previous studies have shown that lipid content can be doubled when the algae culture is subject to N deficient conditions, though biomass growth is also slowed (Rodolfi et al., 2009; Chen et al., 2011) {Chen, 2011 #291}. Section S2. Ammonia volatilization and denitrification To date, all the studies identified in the literature that focus on quantifying ammonia volatilization rates from open raceway ponds (ORPs) are based on algae grown in wastewater or artificial wastewater, in which the concentration of free ammonia varies. The data for freshwater-grown algae with synthetic nutrients is still lacking. Because there are no data for freshwater ORPs with synthetic nitrogen fertilizers, the literature on wastewater systems is reviewed instead. The ammonia volatilization rate from ORPs is highly variable, and depends on the free ammonia concentration in pond water, fertilizer compound used, temperature, and pH value. Previous studies found that N losses due to ammonia volatilization ranged from 1% to 46% of the total N input. Some researchers have found that ammonia volatilization is the main contributor to N loss, accounting for 46% of the total N input (Rockne & Brezonik, 2006), or 37.5% to 41% of the total dissolved N (Nunez et al., 2001). Pano and Middlebrooks (1982) also claim that ammonia volatilization is the major process for ammonia removal in wastewater stabilization ponds, especially if the pH is above 10. S-2 Unfortunately there is no consensus in the literature on the main pathway for N losses from ORPs. Some researchers conclude that nitrification and denitrification processes are more important contributors to N removal from algal ponds and ammonia volatilization does not seem significant, such as Ferrara and Avci (1982). More recently, Zimmo et al. (2003) also found that the ammonia volatilization rate did not exceed 1.5% of the total N removal from ponds and then in following year found that ammonia volatilization was lower than 1.1% of the total N influent (Zimmo et al., 2004). Similarly, Woertz et al. (2009) found that volatilization was lower than 7% of the input N even when the pH is as high as 10.3. The literature on this topic shows significant variability in estimates for ammonia volatilization, a key driver for testing the importance of this rate in a sensitivity analysis. In this study, 4% of the total N influent is volatilized as ammonia; this rate is used because the pH condition is nearly optimal in a mature algae ORP cultivation system, which avoids high volatilization rates. The optimal pH value of culture media for cell growth of S. dimorphus was found to be around 7 (Bassi et al., 1990, Shen et al., 2009). Due to uncertainty in these estimates the ammonia volatilization rate is tested over a range from 1% to 7% in the sensitivity analysis. Estimates for N2O emissions from the ORP were adapted from Fagerstone et al. (2011). In their study, the total N2O-N produced from algal cultivation in a well-mixed ORP was calculated to be 0.002% of the total N input based on experimental data collection, which was substantially lower than the 1% to 3% range for terrestrial crops estimated by the Intergovernmental Panel on Climate Change (Buendia et al., 2006). Section S3. Biogas yield rate Many previous studies have shown a production rate of between 0.1 to 0.4 L CH4/g VS (Frank et al., 2011). For example, in the literature on whole-algae digestion Ras et al. (2011) reported a yield of 0.24 L CH4/g VS for anaerobic digestion of Chlorella vulgaris based on a hydraulic retention time (HRT) of 28 days. A yield of 0.292 L CH4/g VS was adopted by Collet et al. (2011) for anaerobic digestion performance of Chlorella vulgaris, with a CH4 content in the biogas of 70%. High yields were found in S-3 Abdou’s experiments, in which whole algae biomass is pretreated with microwave pretreatment, as 0.525 L CH4/g VS (Hamani Abdou, 2012). At least two studies have examined lipid-extracted algae biomass, the type of biomass considered in the mass balance model described in this article. Ehimen et al. (2011) conducted a study with residual biomass (after oil extraction) of C. vulgaris, and reported a yield of 0.3 L CH4/g VS when hydraulic retention time (HRT), temperature and substrate C:N ratio are optimal, and CH4 content in biogas of about 69.2%. Zhao et al. (2012) evaluated AD performance of five different algal species for both whole algal biomass and lipid-extracted biomass, and found that the yield of CH4 from lipid-extracted biomass ranged from 0.304 to 0.399 L CH4/g VS for five algal species, and the yield from whole biomass ranged from 0.337 to 0.557 L CH4/g VS. The mass balance model assumes a yield similar to these lipid-extracted values; 0.32 L CH4/g VS for the Low N cultivation condition and 0.36 L CH4/g VS for the Normal N cultivation condition. Section S4. Nutrients Recovery from Anaerobic Digestion N Recovery A few previous LCA studies on algal biofuels have examined recycling nutrients, primarily N, from digester effluent, and there exists a great deal of variability in recycling potential. For example, Xu et al. (2011) assumes that about 15% of N can be recycled and the recycling of P can be ignored; Frank et al. (2011) use a baseline scenario that assumes 80% of N is retained as ammonium in the liquid fraction of the digestate, and thus can be recycled for algal biomass cultivation. They also assume a 50:50 split for P in liquid and solid fractions. Similarly, in their techno-economic assessment of algae production for biomethane production, Zamalloa et al. (2011) assume that 70% of N and 50% of P entering the AD reactor can be recovered and recycled. The composition of anaerobic digestate effluent depends highly on the type of feedstock and the conditions of the AD reactor. N mineralization rate varies from 30% to 68% in previous studies due to S-4 differences in loading rates, hydraulic retention time (HRT), composition of AD feedstock, etc. Research efforts have been made by previous researchers to measure N mineralization rate and the amount of N in organic and inorganic forms for effluent from AD of non-extracted algal biomass, manure and other wastes. Unfortunately, results are different based on different experimental conditions including loading rates, HRT, composition of the AD feedstock, etc. The N mineralization rate varies from 30% to 68% in previous studies (González-Fernández et al., 2013). González-Fernández et al. (2013), Sialve et al. (2009) and Ras et al. (2011) all concluded that long retention time correlated with higher mineralization efficiency. The mineralization rate of C. vulgaris increased from 19% to 68% as HRT increased from 16 to 28 days (Ras et al., 2011). Similar rates have been reported in other studies. For example, N mineralization rates for anaerobic digestate from animal waste have shown that 51% (swine and cattle manure) to 75% (poultry manure) of the total N was found in the form of ammonium in the digestate (Kirchmann & Witter, 1992). Similary, a study by Morken et al. (2013) assumed that 60% of the N entering AD was mineralized to ammonia in the liquid fraction of the digestate, with the balance retained in the solid fraction. The mineralization rate of 60% was equal to the VS reduction rate in their model. The mass balance model assumes 65% of N can be recovered in the liquid fraction of the digestate and, due to uncertainty in this value; a range of 50-80% is tested in the sensitivity analysis. P Recovery Field et al. (1984) separated phosphorus, potassium, calcium, and magnesium into extractable and total fractions in anaerobically digested swine manure. Nearly 100% of total phosphorus, potassium, calcium and magnesium were recovered in digested effluent, indicating nutrient conservation during digestion. The solid fraction contained 59.6% to 85.8% of the total effluent P. In other words, 14% to 40% of the total P was found to be in the liquid fraction and could be recycled to provide nutrients for algal growth. In research analyzing the fate of nutrients during digestion with swine manure, Massé et al. (2007) found 74.5% of total phosphate recovered in the effluent from anaerobic digestion of swine manure and 25.5% retained in S-5 the bioreactors. For the phosphate recovered in the effluent, 62.3% is settled in the sludge section. Assuming that all the P in the supernatant fraction could be recycled, this leads to 28% of P in the liquid fraction of AD effluent. In contrast, some low P mineralization rates have been found. It was found that the dissolved P in the effluent of dairy manure digestate accounted for 7% of the total P using data from six on-farm anaerobic digesters (Güngör & Karthikeyan, 2008). Similarly, Wahal (2010) reported that less than 5% of P in digested dairy waste was in the dissolved/liquid fraction from the average measurements from five samples. These low rates may indicate significant uncertainty in the recyclability of a significant portion of P in ADintegrated algae systems, but may also reflect the unique characteristics of feedstocks and AD operation that could be improved in a commercial algal oil production system. More recently, Alcántara et al. (2013) found in their experiments that as much as 89% of P could be potentially recovered from the digestates of photoautotrophically cultivated algae. This high P recovery rate might be due to the significant accumulation of polyphosphates during the cultivation of algal biomass. This recovery rate is adopted in this study because this is the only available P recycling rate for digestates of algae. Section S5. Fugitive emissions of methane Fugitive losses of biogas during production and processing are highly variable, and the quantification of fugitive losses is difficult. Previous studies have assumed a fugitive loss of 0% to 2% of the produced methane (Meyer-Aurich et al., 2012), or as high as 13.5% of the biogas for a small scale farm-based digester system (Sandars et al., 2003). Measurement of fugitive methane emissions from a Canadian biodigester into which cattle manure and other feedstock were fed to produce biogas showed an average emission rate of 3.1% of the total methane (Flesch et al., 2011). This model assumes a range of 0 to 3% in the sensitivity analysis, and the midpoint 1.5% is used in the baseline results. This range is used because this industrial S-6 scale AD system is assumed to be more effective at reducing or eliminating sources of fugitive emissions compared to the small-scale agricultural digesters which have been better studied. Section S6. CH4 concentration of biogas Biogas produced from AD processes is primarily a mixture of CH4 and CO2. Previous studies on experiments with AD of algae have reported a range of CH4 concentrations from 61% to 69% depending on algal species, temperatures, loading rates and other conditions (Ehimen et al., 2011; Golueke et al., 1957; Mussgnug et al., 2010; Yen & Brune, 2007). Golueke et al. found out that the biogas out of anaerobic digester using a mix of Scenedesmus sp. and Chlorella sp. as feedstock consisted of 30% CO2 and 62% CH4 by volume. A number of other studies have reported similar CH4 content. A CH4 content of 69% of biogas was reported by Yen and Brune, who produced biogas from AD of algae at loading rate of 4 g VS/day and 10 days HRT. The CH4 contents of biogas ranged from 61% to 67% in the results of experiments by Mussgnug et al. (2010). A CH4 concentration range from 62% to 69% was found in a more recent study by Ehimen et al. (2011) under different AD conditions including various operation temperatures and C: N ratios of the feedstock. The baseline assumption for this study uses the following biogas constituent ratios; CH4 constitutes 66% of the biogas by volume, CO2 constitutes 33%, and other substances and pollutants 1% of the biogas. No sensitivity analysis is conducted for these parameters. Section S7. Supporting Material for Results and Discussion Nutrients, water and carbon savings for two different N supply conditions Figures S1a and S1b quantify the contributions of recycling growth medium and recycling nutrients, water and carbon from digestate or from biogas combustion to fulfilling the total demand for nutrients, energy, and water. S-7 Figure S1. Nutrient (a) and water and carbon (b) requirements and savings through recycling for two different N supply conditions per kg of algal oil. Recycled N and P contribute to 66% and 90% of the total N and P requirements respectively, regardless of the N supply conditions. For growth water, recycling streams can provide 89% (or 84%) of the total requirement for Normal N (or Low N) conditions. Also, 40% (or 33%) of the C requirement can be fulfilled by recycled CO2 from biogas combustion and from unharvested biomass in growth medium for Normal N (or Low N) conditions. Because of its lower N requirement and higher lipid content, the consumption of nutrients, water and carbon for algal biomass grown in Low N condition is significantly lower than biomass grown in Normal N condition to produce 1 kg of oil. The Low N condition requires 24.06 g of N and 5.22 g of P to produce 1 kg of oil, which are 79% and 37% less than the net requirements for the case of Normal N (115.49 g of N and 5.22 g of P). The net carbon requirement is 1.58 kg of C, 30% less than its counterpart (2.28 kg of C). However the net requirement of water to produce 1 kg of algal oil for the two N supply conditions does not differ significantly, for the reasons explained below. Freshwater is needed to mostly make up the evaporation loss which is 5.96 L per m2 per day, or 373 L per kg of biomass for biomass grown under the Low N condition, which is 56% higher than evaporation losses for biomass under Normal N condition (239 L per kg of biomass). This higher evaporation loss per unit of biomass largely offsets the benefit brought by higher lipid content of biomass under Low N conditions. S-8 Sensitivity Analysis A sensitivity analysis was conducted to understand how the variation in a list of key parameters could affect the results and to identify some of the most important parameters affecting net requirements of nutrients, water and carbon. The sensitivity analysis was done for the Normal N condition, the baseline scenario in this study. A total of twelve parameters are considered, and the lower and higher bounds for these parameters, which are chosen to reflect the pessimistic and optimistic estimates under currently viable technologies, are listed in Table S1 and Figure S2 below. The ranges used in the analysis and reasoning for their selection for some important parameters are as follows: the range of lipid content (20% to 30%) is based on data from experiments using Scenedesmus sp. grown under normal N conditions (Xin et al., 2010a, Xin et al., 2010b); the range of growth rates (20 to 30 g/m2/day) are from the review study Fernández et al. (2012); because no other data have been found for P recovery rate from anaerobic digestion of algae, a range of 83% to 95% is assumed to reflect the possible variation around the value from Alcántara et al. for P recovery from the liquid fraction of digestate. Ranges for other parameters are based on data found in literature cited previously. Table S1. Key parameters affecting nutrients, water and carbon cycles, for biomass grown in Normal N condition. Parameters Pessimistic Baseline Optimistic Algal growth rate (g/m2/d) 20 25 30 Lipid content 20% 25% 30% CO2 mass transfer efficiency 75% 83% 91% N loss due to ammonia volatilization 7% 4% 1% Water evaporation (L/m2/d) 6.96 5.96 4.96 Efficiency of harvesting and dewatering 78% 86% 95% Efficiency of oil extraction 60% 74% 87% Loss of N and P due to co-extraction 1.5% 1% 0.5% CH4 yield (L/g VS) 0.26 0.34 0.42 Fugitive CH4 loss 3% 1.5% 0% N in liquid fraction of digestate 50% 65% 80% P in liquid fraction of digestate 83% 89% 95% As shown in Figures S2a and S2b, the nutrient recovery rates from the liquid fraction of the digestate, the lipid content of the algal cell, and efficiency of oil extraction are the most important factors influencing the net nutrient requirements per 1 kg of algal oil. As shown in Figure S2c, lipid content, S-9 algal growth rate, efficiency of harvesting and dewatering, efficiency of oil extraction and water evaporation rate significantly affect the net water requirement. For the net carbon requirement for 1 kg of algal oil, the lipid content, efficiency of oil extraction, CO2 mass transfer efficiency, and CH4 yield from AD are the most important factors. Figure S2. Sensitivity analysis: net requirements of (a) nitrogen, (b) phosphorus, (c) water and (d) carbon relative to parameter change for 1 kg of algal oil produced from biomass under Normal N conditions. Discussion on low and normal N supply conditions The results show that the Low N case is clearly preferable from a mass balance perspective, as it requires much less net nutrients and carbon compared to the Normal N case on the basis of 1 kg of algal S-10 oil. The sensitivity analysis also identifies algal lipid productivity as the most important parameter. Previous studies have also shown preferable results for Low N conditions from a life cycle perspective (Lardon et al., 2009; Xu et al., 2011). The fossil energy requirement and other life cycle impacts are significantly reduced by lower nutrients requirements and higher oil yield on the basis of 1 unit of biomass for low N conditions. On the other hand, the Normal N case performs slightly better for this integrated system in terms of energy recovery from algal biomass, and the annual production of energy is significantly higher than the low N case given the same area and volume of ponds. As stated before, producing biofuel from algae biomass does not occur at an industrial scale at present; many technologies are still under development and there are many uncertainties associated with the production system. Research efforts devoted to increasing lipid productivity have observed that nutrient deprivation or limitation could lead to an increase in the overall lipid productivity and consider it as a promising strategy (Chen et al., 2010, Rodolfi et al., 2009). However, quite a few studies found that the overall productivity of oil is lower under nutrient deficiency because of the significantly lower biomass growth rate (Lyon et al., 2013, Sheehan et al., 1998); and that nitrogen stressing could negatively impact the algal health (Liu et al., 2013). Further, the nutrient stressing strategy may not be economically beneficial because growth rates are more important for large-scale operation (Liu, 2012). Stephenson et al. (2010) suggest an effective way to balance both biomass productivity and lipid accumulation using a two-stage cultivation method, where the biomass concentration level increases rapidly under the initial N-sufficient conditions and then the N supply is stopped and N is depleted naturally in the culture. However, more research is needed to optimize the laboratory conditions, and more testing in outdoor ponds is required before scaling up to a commercial operation. Therefore, the trade-off between lipid content and biomass productivity and the trade-off between environmental sustainability and economic benefits have to be considered for a commercial-scale operation. 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