gcbb12229-sup-0001-DataS1

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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: juyuan@ucdavis.edu.
b. Corresponding author. Department of Civil and Environmental Engineering, University of California,
Davis, 1 Shields Avenue, Davis, CA, 95616, USA. Email: amkendall@ucdavis.edu, Phone: +1-530-7525722, Fax: +1-530-752-7872.
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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.
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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
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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
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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
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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
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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.
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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.
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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,
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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
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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.
In summary, while findings from this study suggest that low N conditions may yield environmental
benefits, previous research has been inconclusive on the feasibility and promise of low N conditions to
increase lipid production at commercial scale, and from an energy balance perspective total biomass
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productivity may be more important. Thus, the findings from this study should be interpreted in the
context of uncertainty for commercialization, and in the context of possible tradeoffs among
environmental and energy performance criteria.
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