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Prepared for Bioresource Technology

Life Cycle Analysis on Biodiesel Production from Microalgae: Water Footprint and Nutrients Balance

Jia Yang¹, Ming Xu², Xuezhi Zhang³, Qiang Hu³, Milton Sommerfeld³, Yongsheng Chen^1*

¹School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332-0355

²Brook Byers Institute for Sustainable Systems, Georgia Institute of Technology, Atlanta, GA 30332-0595

³Department of Applied Sciences and Mathematics, Arizona State University at the Polytechnic Campus, Mesa, AZ 85212

^ Corresponding author. Tel.: +01 404 894 3089

E-mail addresses: yongsheng.chen@ce.gatech.edu

Table of Content

1. Data 3

1.1 Temperature 3

1.2 Evaporation 3

1.3 Radiation 3

1.4 Algal growth Rate 3

2 Calculations for water footprint 4

2.1 Water Usage 4

2.1.1 Culture 4

2.1.2 Harvest 4

2.1.3 Drying 5

2.1.4 Extract and Esterification 5

2.1.5 Summary 5

2.2 Nutrients Usage 6

3 Sensitivity Analysis 6

4 Comparison among different species 6

5. Comparison among different locations 7

6. Policy implications 7

References 7

Supporting figures and tables

Figure.S1. A rough sensitivity analysis of eight parameters 8

Figure.S2. A rough sensitivity analysis of eight parameters 9

Figure.S3. Relative water footprints of biodiesel production using different microalgae species as compared with Chlorella vulgaris 10

Figure.S4. Water footprint (kg-water/kg-biodiesel) of Chlorella vulgaris-based biodiesel production in different states. 11

Table S1 Solid contents and recovery rates of common harvest methods 12

Table S2 Biomass fraction of different composition in microalgae 13

Table S3 Inorganic matter fraction of microalgae 14

Table S4 Nutrients concentration (SE Medium) in pond 15

Table S5 Variation ranges of parameters for the biodiesel production based on Chlorella vurlgaris 16

Table S6 Water footprints among different microalgae species 17

Table S7 Climatic conditions in states and the corresponding water footprint of microalgae Chlorella vulgaris 18

Table S8 Average climatic condition in the United States and the corresponding growth rate of microalgae Chlorella vulgaris 19

Table S9 Freshwater usage of each state 20

Table S10 Current usages and cost of nitrogen and phosphate 22

1. Data

1.1 Temperature

The temperature (T) in this study stands for the average annual temperature, and the data were got from the Report of NREL (1994), where thirty years of data (1961~1990) of each state was available. In the part 4.2 of spatial variation, the specific temperature for each state used in this study was taken from the atlas of the average annual temperature in the United States.

1.2 Evaporation

The lake evaporation rates (LER) were used to calculate the daily water loss caused by evaporation from open pond surfaces for each state, and the calculation was by the following formula (Derecki, 1980):

Eq. S1

PER stands for the pan evaporation rate, and the data comes from the Report from NOAA (Farnsworth, 1982), which records fourteen years (1956-1970) data of monthly, seasonal, and annual averages of estimated pan evaporation based on observation from Class A pans and on meteorological measurements by the National Weather Service (NWS) and cooperating agencies. The specific PER for one state was consider as an average value of all the PER observed in the state.

1.3 Radiation

Radiation is related to the photosynthesis and the growth rate of microalgae. At certain ranges of latitudes, the fraction of total solar energy available for algae to use in photosynthesis could be considered the same (Clarens, 2010). Therefore, the growth rate of microalgae in each state can be calculated based on the state’s average radiation.
The data of radiation can be downloaded from the National Solar Radiation Database (NSRDB) (1994), which provides thirty years of data (1961‐1990) at each state. The specific data for each state used in this study were taken from the ‘atlas for the solar radiation data manual for flat-plate and concentrating collectors’ provided by NSRDB.

1.4 Algal growth Rate

Generally, algal growth rate is considered positively linear relate to total radiation (TR) (Clarens, 2010) and temperature (Sheehan, 1998), which can be expressed as following:

AGR= k*TR*T Eq. S3

In particular, the coefficient k varies between microalgae species. For example, for Chlorella vulgaris, this coefficient k can be derived from literature reports of field-scale algae cultivation in open ponds by Weissman & Goebel (1986) in south California (Sheehan, 1998). Through calculation, the value of k of Chlorella vulgaris is at 0.23±0.022 g/kWh/°C.

2 Calculations for water footprint

2.1 Water Usage

The calculation of water footprint was based on the microalgae biodiesel production in the pond which is continuously chemostat, and thus the growth rate of microalgae and the nutrients concentration in pond could be considered as constant. To simplify calculation, microalgae density in pond is also assumed constant. The value of microalgae density is considered as 1g/L, or 0.1% as microalgae percentage. (DOE, 2009).

2.1.1 Culture

All the water usages during culture are assumed to be consumed by evaporation. The results are calculated based on evaporation of water, with the following formula:

F_Cul(kg/day)=S(m²)*LER(m/day)*1000 Eq. S4

Where F_Cul stands for the water loss by the evaporation everyday (kg/day), Sstands for the area of pond.
LER stands for the lake evaporation rate. Considering the average evaporation rate in the U.S. ranged from 0.15 cm/day to 0.5 cm/day, thus an average value of 0.27 cm/day was used in Equation S4.

2.1.2 Harvest

Harvest is the process of collecting small microalgal cells from the dilute suspension of a growing culture. The low concentration of algal suspension and small cell size (1 to 30 μm) make harvest become the bottlenecks in microalgal culture (Wang, 2008). Normally, the microalgae in pond is at the mass percentage of only about 0.1%, and the percentage can increase to 1%-3% after harvest (DOE, 2009). The mass ratio of microalgae to water after harvest is called solid content after harvest (SCH), which is an important parameter to estimate the harvest method. Another important parameter of harvest method is the recovery rate of harvest (RRH), which referred to the percentage of microalgae collected for drying over all the harvested ones. Table S1 summarized the solid contents and recovery rates of common harvest methods (Sim et al., 1988).
After harvest, parts of water are discharged directly to the wastewater system, while others are recycling to the pond. The water loss during harvest process is the water discharged to wastewater system, and it can be calculated by the following formula:

F_har(kg/day)=[A1(kg/day)/0.1%-A1(kg/day)/SCH(%)]*(1-RR) Eq. S5

where Sstands for the area of pond. Hstands for the depth of pond, A1 stands for the daily mass of microalgae harvested from the pond, and the value equals to the production of S and GR. A1 divided by 0.1% refers to the water discharged when harvesting microalgae. SCH stands for the solid content after harvest, the range of it can be got from Table S1, RR stands for the recycle rate, which equals to the mass ratio of recycling water to the all the harvest water.

2.1.3 Drying

The algae paste collected after harvest unit are then sent for further drying. Normally, the classic drying device, such as drum dryer or belt dryer can dry the algal paste to the solid content of 90% (DOE, 2009; Hassebrauck, 1996). And thus the water lost during drying could be computed by following formulas:

F_dry= A1(kg/day)/SCH(%) – A1(kg/day)*SRR(%)/SCD(%) Eq. S6

Where A1 stands for the daily microalgae harvested from the pond, and the value of it equals to the production of S and GR. SCH stands for the solid content after harvest, the range of it can be got from Table S1. RRH stands for the recovery rate after harvest, and the range of it can be got from Table S1. SCD stands for the solid content after drying.

2.1.4 Extract and Esterification

It have been reported that the algae oil extraction is very similar to soybean extraction with solid content of 90% (Laurent et al., 2009). And the average of water cost for extraction and esterification is about 2-10 liter water per liter biodiesel (Dominguez-Faus et al., 2009). So the water usage during extract and esterification can be computed as following:

F_ee= B*W_ee Eq. S7

Where W_ee stands for the water usage for extraction and esterification, and its variation range can got from ref (Dominguez-Faus et al., 2009), B stands for the microalgal biofuel production based on the volume of pond, the value of B equals to the following formula:

B= A1(kg/day)* RRH(%) * YR(%) * LC(%) Eq. S8

Where A1 stands for the microalgae harvested from the pond, and the value of it equals to the production of S and GR. RRH stands for the recovery rate, and the range of it can be got from Table S1. YR stands for the yield rate from biomass to biofuel through extraction and esterification. The YR equals to the production of yield rate of extract (YRE) and the yield rate of esterfication (YREs). The variation of YRE can got from the work of Kim, and the range of YREs can taken from work of Antolin (1980); LC is algal lipid content.

2.1.5 Summary

For freshwater as input water or culture medium, the whole freshwater usage during the whole process can be computed as the following:

WFa (FW)=F_cul+F_har+F_dry+F_eeEq. S9

If using sea-/wastewater as culture medium, the freshwater is consumed only during the process of culture by evaporation and refining by extraction and esterification. Thus, the freshwater usage during the whole process can be computed as the following:

WFa (SW/WW)=F_cul +F_eeEq. S10

And the water footprint of microalgae biofuel production can be computed as the following:

WFa=F/B Eq. S11

2.2 Nutrients Usage

The nutrients consumption of algae is calculated by the biomass fraction of Chlorella vulgaris. The biomass fraction of Chlorella vulgaris is from ref (Lardon et al., 2009), and the relative content is from ref (Demirba, 2009; Chisti^{, 2008}; Li et al., 2008), which shown in Table S2. Based on S5, biomass fraction of microalgae can be calculated, and the results are as in Table S3, and the microalgae molecular formula can be written as C_17.1H_31.2O_3.4N_0.6. Thus the nitrogen mass fraction of microalgae can be calculated, and the value is 2.7%.
Assuming all the nitrogen was consumed for biosynthesis, it is possible to estimate nitrogen requirements. The consumption is based on the following equation:

N_consumption =Mass_algae* MF_nitrogen Eq. S12

Where,

Mass_algae =Growth rate* Growth Cycle* Pond Size/Biodiesel production;

MF_nitrogen is the mass fraction of nitrogen;

The nitrogen in input water can be calculated by following equations:

N_input=N_consumptNon+N_discharge Eq. S13

Where,

N_discharge=N_Pond*(1-Recycle rate) Eq. S14
The nitrogen in pond is based on the medium. In this paper, the medium is SE medium, and the composition is shown in Table S4. Other basic nutrients (phosphorus, potassium, magnesium and sulfur) are treated as proportional to nitrogen (Lardon et al., 2009), and the results are showed in Figure 4.

3 Sensitivity Analysis

From table S5, there are eight parameters affect water footprint, which can be roughly represents as Figure S2. However, considering the narrow range of yield of extraction and yield of esterification, only 6 parameters are taken into account for a directly sensitivity analysis, as Figure 3(a), and 4 of the 6 are used for a furthermore sensitivity analysis by combining their input parameter values (Figure 3(b)).

4 Comparison among different species

All the microalgae are chosen from the reports of Aquatic Species Program (Sheehan et al., 1998), and their growth rates are taken from the similar reports. Since a lack of relative lipid content with these microalgae in the ASP report, the lipid content of microalgae were taken from the review by Chisti (2008). Based on the data, the water footprints of microalgae are computed (assuming culture condition are similar to that in California), and the results are shown in Table S6 and Figure S2.

5. Comparison among different locations

Microalgae show different water footprints in different locations. The temperatures and total radiations of selected states are summarized in Table S7. Assuming the microalgae is Chlorella vulgaris, thus its growth rate can be calculated by equation S3, and the value of k can be got form Table S1. Based on the climatic condition in each state, and the water footprint of it can be calculated, which is also shown in Table S7.

6. Policy implications

The average water and nutrient of the United States are computed based on the average annual temperature, radiation, and evaporation rate in the United States, which is shown in Table S8. And the microalgae strain is considered as Chlorella vulgaris, thus the corresponding growth rate can be computed, and the result is also shown in Table S8. The climatic condition and corresponding growth rate of microalgae Chlorella vulgaris in each state can be got from Table S10.
Current freshwater usages in the whole nation and different sates can be get from the report of USGS (2009), and the results listed as Table S9.
Current usages and cost of nitrogen, phosphate are taken from the report of UDSA (2010), and the values of them are listed in Table S10.

References

Antolin, G., Tinaut, F.V., Briceno, Y., Castano, V., Perez, C., Ramirez, A.I., 2002. Optimisation of biodiesel production by sunflower oil transesterification. Bioresource Technol. 83, 111–114.

Ban, K., Hama, S., Nishizuka, K., Kaieda, M., Matsumoto, T., Kondo, A., Noda, H., Fukuda, H., 2002. Repeated use of whole-cell biocatalysts immobilized within biomass support particles for biodiesel fuel production. J. Mol. Catal. B. Enzym.17, 157–165

Chisti Y., 2008. Biodiesel from microalgae beats bioethanol. Trends Biotechnol. 26, 126-131.

Chisti, Y., 2007. Biodiesel from microalgae. Biotechnol Adv. 25, 294-306.

Clarens, A.F., Resurreccion E.P., White M.A., Colosi L. M., 2010. Environmental Life Cycle Comparison of Algae to Other Bioenergy Feedstocks. Environ Sci Technol. 44, 1813-1819.

Demirba, A., 2009. Production of Biodiesel from Algae Oils. Energy Sources. 31, 163-168.

Derecki, J.A.,1980. Evaporation from Lake Superior. Ann Arbor, Mich.: U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, Environmental Research Laboratories, Great Lakes Environmental Research Laboratory

Dominguez-Faus, R., Powers, S.E., Burken, J.G., Alvarez, P.J., 2009. The Water Footprint of Biofuels: A Drink or Drive Issue? Environ. Sci. Technol. 43, 3005-3010.

Energy Independence and Security Act of 2007 (EISA) H. R. 6; 110th United States Congress. ^{http://thomas.loc.gov/cgi-bin/ bdquery/z?d110:h.r.00006, (accessed February 10, 2008).}

Farnsworth^{, R.K., Thompson, E.S., 1982. Mean monthly, seasonal, and annual pan evaporation for the United States. NOAA technical Report NWS 34. U.S. Department of Commerce.}

Hassebrauck, M., Ermel, G., 1996. Two examples of thermal drying of sewage sludge. Water Sci. Technol 33, 235–242.

Hu, Q., Sommerfeld, M.; Jarvis, E., Ghirardi, M., Posewitz, M, Seibert, M., Darzins, A., 2008. Microalgal Triacylglycerols as Feedstocks for Biofuel Production: Perspectives and Advances, Plant J. 54, 621-639.

Kenny, J.F., Barber, N.L., Hutson, S.S., Linsey, K.S., Lovelace, J.K., and Maupin, M.A., 2009. Estimated use of water in the United States in 2005: U.S. Geological Survey Circular 1344, 52 p.

Lardon, L., Helias, A., Sialve, B., Steyer, J.P., Bernard, O., 2009. Life-Cycle Assessment of Biodiesel Production from Microalgae. Environ. Sci. Technol. 43, 6475-6481.

Lee, J., Yoo, C., Jun, S.Y., Ahn, C.Y., Oh, H.M., 2010. Comparison of several methods for effective lipid extraction from microalgae. Bioresource Techno., 101, S75–S77.

Li, Q., Du, W., Liu, D.H., 2008. Perspective of microbioal oils for biodiesel production. Appl. Microbiol. Biotechnol. 80, 749-756

NREL, National Solar Radiation Database (1961‐1990), 1994. In National Renewable Energy Laboratory.

Sheehan, J.; Dunahay, T., Benemann J., Roessler P., 1998. A look back at the U.S. Department of Energy's Aquatic Species Program-Biodiesel from Algae. Retrieved June 29, 2007, from www.nrel.gov/docs/fy04osti/34796.pdf.

Sim, T.S.; Goh, A.; Becker, E.W. Comparison of Centrifugation, Dissolved Air Flotation and Drum Filtration Techniques for Harvesting Sewage-grown Algae. Biomass. 1988, 16(1), 51-62.

U.S. department of energy, National algal biofuels technology roadmap, 2009. https://e-center.doe.gov/iips/faopor.nsf/UNID/79E3ABCACC9AC14A852575CA00799D99/$file/AlgalBiofuels_Roadmap_7.pdf

United States Department of Agriculture (USDA), 2010. U.S. fertilizer use and price. http://www.ers.usda.gov/Data/FertilizerUse/

Wakeley, H.L., Hendrickson, C.T., Griffin, W. M., Matthews H. S., 2009. Economic and Environmental Transportation Effects of Large-Scale Ethanol Production and Distribution in the United States. Environ. Sc. Technol. 43, 2228-2233.

Wang, B., Li, Y., Wu N., Lan C.Q., 2008. CO2 bio-mitigation using microalgae. Appl. Microbiol. Biot. 79, 707-718.

Figure Captions
Fig. S1. The life cycle of microalgae biodiesel production.
Fig. S2. Roughly sensitivity analysis of all the parameters.
Fig. S3. Relative water footprints of biodiesel production using different microalgae species as compared with Chlorella vulgaris.
Fig. S4. Water footprint (kg-water/kg-biodiesel) of Chlorella vulgaris-based biodiesel production in different states.

Fig. S1. The life cycle of microalgae biodiesel production.

Fig. S2.Roughly sensitivity analysis of all the parameters

Fig. S3. Relative water footprints of biodiesel production using different microalgae species as compared with Chlorella vulgaris.

Fig S4. Water footprint (kg-water/kg-biodiesel) of Chlorella vulgaris-based biodiesel production in different states.

Table S1

Solid contents and recovery rates of common harvesting methods.

Solid Content after Harvest

(SCH, %)

Recovery Rate after harvest

(RRH, %)

Flocculation

95-98^a

Filtration

1.5-3

Table S2

Fraction of different composition in microalgae

Composition	Molecular Formula	Content	Reference
Protein	C_4.43H₇O_1.44N_1.16^b	51-58%^a	^a(Demirba, 2009); ^b( Lardon et al., 2009)
Carbohydrate	C₆H₁₂O₆^b	12-17%^a	^a(Demirba, 2009); ^b(Lardon et al., 2009)
Lipid	C₄₀H₇₄O₅^b	14-40%^a	^a(Demirba, 2009; Chisti, 2007; Li et al., 2008); ^b( Lardon et al., 2009)

Table S3

Composition of C,H,O,N in microalgae

Inorganic matter	C	H	O	N
Molar composition	17.1	31.2	3.4	0.6

Table S4

Nutrients concentration (SE Medium) in pond (mg/L)

Component	concentration	Component	concentration
NaNO₃	250	H₃BO₃	2.86
K₂HPO₄·H₂O	75	MnCl₂·4H₂O	1.81
MgSO₄·H₂O	75	ZnSO₄·7H₂O	0.22
CaCl₂·2H₂O	25	CuSO₄·5H₂O	0.079
KH₂PO₄	175	(NH₄)₆Mo₇O₂₄·4H₂O	0.039
NaCl	25	Na₂EDTA	10
HCl（0.1N）	0.5mL·L^-1	FeCl₃·6H₂O	0.81

Table S5

Variation ranges of parameters for the biodiesel production based on Chlorella vurlgaris

Parameter	Value used in the case	Variation Range	Reference
Lake Evaporation Rate	2.7	2-5 cm /day	(Farnsworth et al., 1982)
Total Radiation	5 kwh/m²/day
Temperature	30 ℃
Algal Growth Rate	35^[a] g/m²/day	10-50g/m²/day	(Demirba, 2009);(Li et al,, 2008)
Algal Lipid Content (m/m)	35%	25-45 %	(Hu et al., 2008); (Chisti, 2008)
Solid Content after Harvest (v/v)	1.5%	1%-3 %	(Sim et al., 1988)
Recovery Rate after Harvest (v/v)	85%	80-98 %	(Sim et al., 1988)
Solid Content after Drying (v/v)	90%	80-95 %	(DOE, 2009); (Hassebrauck et al., 1996)
Yield Rate after Extraction (m/m)	85%	67-90 %	(Lee et al, 2010)
Yield Rate after Esterification(m/m)	96%	94%-98 %	(Ban et al., 2002); (Antolin et al., 2002)

[a] this value is calculated from LER and TR by Eq. S3.
Table S6

Water footprints among different microalgae species

		Algal growth rate (g/m²/d)	Lipid Content	Water Footprint	Normalized, compare Chlorella vulgaris
1	Dunaliella primolecta	12	27±5 %	1818.5±339	3.07±0.57
2	Phaeodactylum tricornutum	22	20±3 %	1456±205	2.46±0.35
3	Monallanthus salina	28.1	21±6 %	1230±380	2.08±0.64
4	Tetraselmis sueica:	25	19±6 %	1440±427	2.43±0.72
5	Nannochloris	31.9	28±11 %	863±331	1.46±0.56
6	Isochrysis galbana	28.1	28±6 %	911±256	1.54±0.43
7	Cyclotella cryptica	30	30±2 %	758±62	1.28±0.15
8	Botryococcus braunii	3.4	52±33 %	3595±2245	6.08±3.80
9	Nanocloropsis sp	20.4	49±19 %	721±376	1.22±0.64
10	Chlorella vulgaris	35	37±11 %	591±170	1.00±0.29
11	Chaetoceros gracilis	40	30±14 %	708±331	1.20±0.56

Table S7

Climatic conditions in states and the corresponding water footprint of microalgae Chlorella vulgaris

States	TR (kwh/m²/day)	T (℃)	Growth Rate (g/m²/day)	LER (cm /day)	WFa (kg water/kg biodiesel)
CA	5	15	16.58	0.34	1078
AZ	5.5	25	31.43	0.49	860
NM	5.5	15	18.24	0.39	1119
TX	4.5	20	20.46	0.46	1163
LA	4	20	18.19	0.32	927
FL	4	25	22.86	0.32	774
AR	4	18	15.87	0.27	924
MS	4	18	15.87	0.27	924
AL	4	18	15.87	0.27	924
GA	4	18	15.87	0.27	924
SC	4	18	15.87	0.27	924
NC	4	16.3	14.56	0.27	996
NV	5	10	10.37	0.29	1413
UT	5	10	10.37	0.29	1413
CO	5	7	7.35	0.24	1612
OK	4	12.5	11.10	0.39	1719
KS	4	12.5	11.10	0.39	1719
MO	4	12.5	11.10	0.24	1139
TN	3	15	9.94	0.27	1342
kY	3	12.5	8.33	0.23	1311
WV	3	13	8.33	0.22	1267
VA	3.5	15	11.60	0.24	1087
IL	3	11.5	7.35	0.22	1493
IN	3	11.5	7.35	0.22	1493
OH	3	11.5	7.35	0.22	1493
PA	3	10	6.22	0.19	1546
NY	3	5	2.45	0.17	832
HI	4	25	22.86	0.34	796

Table S8

Average climatic condition in the United States and the corresponding growth rate of microalgae Chlorella vulgar

(kwh/m²/day)

(℃)

LER

(cm/m²/day)

Growth Rate

(g/m²/day)

12.5

0.23

11.1

Table S9

Freshwater usage of each state

State	Freshwater Usage(MG/yr)
Alabama ..................	9,960
Alaska .....................	876
Arizona ....................	6,240
Arkansas ..................	11,400
California ................	32,900
Colorado ..................	13,600
Connecticut .............	854
Delaware .................	635
District of Columbia	9.7
Florida .....................	6,820
Georgia ....................	5,380
Hawaii .....................	447
Idaho .......................	19,500
Illinois .....................	15,200
Indiana .....................	9,340
Iowa .........................	3,370
Kansas .....................	3,790
Kentucky .................	4,330
Louisiana .................	11,400
Maine ......................	466
Maryland .................	1,350
Massachusetts .........	1,260
Michigan .................	11,700
Minnesota ................	4,040
Mississippi ..............	2,850
Missouri ...................	8,790
Montana ...................	10,100
Nebraska ..................	12,600
Nevada .....................	2,380
New Hampshire .......	439
New Jersey ...............	1,930
New Mexico .............	3,330
New York .................	10,300
North Carolina .........	11,300
North Dakota ............	1,340
Ohio..........................	11,500
Oklahoma .................	1,540
Oregon ......................	7,220
Pennsylvania ............	9,470
Rhode Island ............	141
South Carolina .........	7,850
South Dakota ............	500
Tennessee .................	10,800
Texas ........................	23,600
Utah ..........................	4,820
Vermont ....................	523
Virginia.....................	7,080
Washington...............	5,600
West Virginia ............	4,810
Wisconsin .................	8,600
Wyoming ..................	4,410
Puerto Rico ...............	722
U.S. Virgin Islands ...	11.4
Total	349,423

Table S10

Current usages and cost of nitrogen, phosphate

Year	Nitrogen (10³ ton)	Phosphate (10³ ton)	Cost of 30% N (Dollars per ton)	Cost of 45% P (Dollars per ton)
2007	13,194.4	4,571.7	1337	1778

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