1. 2nd International Conference on Algal Biorefinery, DTU, Lyngby, Denmark
27th – 29th August 2014
Microalgae as a protein rich livestock feed ingredient in The Netherlands: an environmental sustainability analysis
Sue Ellen Taelman(a),
Steven De Meester(a), Wim Van Dijk(b), Vamilson da Silva(c), Jo Dewulf (a)
(a) Department of Sustainable Organic Chemistry and Technology, Ghent University, Coupure Links 653, B-9000 Ghent, Belgium
(b) Application Center for Renewable Resources, Wageningen University and Research Centre, P.O. Box, 8200 AK, Lelystad, The Netherlands.
(c) Departamento de Engenharia Sanitária e Ambiental, Universidade Federal de Santa Catarina, Caixa Postal 476. CEP Florianópolis, Brazil

2. What is the most sustainable protein rich alternative?
Introduction (1)
Demand for vegetable protein feed sources increases
Import of proteins in the EU: soybean crops, mainly from Brazil
Deforestation, fossil fuel use, ..  Sustainable?
Alternative : algae as renewable protein source
Potential:
Up to 50% proteins
Considered to be highly productive
Cultivation on marginal land possible …
What is the most sustainable protein rich alternative?

3. Introduction (2)
EnAlgae: INTERREG IVB North West Strategic Initiative (03/2011 – 06/2015)
9 pilot scale algae cultivation sites (micro- and macroalgae)
-> one of these located in Lelystad, The Netherlands
-> Integrated microalgal biorefinery
Goal of this study:
(1) Determining the natural resource footprint of protein rich algal meal for livestock feed applications in The Netherlands
(2) Comparison with soybean crop production in Brazil and transport to The Netherlands

4. Env. Sustainability Analysis
Life Cycle Assessment (LCA), ISO standards & 14044
Functional unit: basket of products
System boundaries: cradle-to-gate
Foreground: 95% gathered at the site
Background: database ecoinvent v2.2
Resource consumption (CEENE)
Dewulf et al. 2007

5. 10.2% DW
500 m²
3241 kg
DW.ha-1.y-1

6. LCA (cradle-to-gate)
System expansion based on functionalities to avoid allocation

7. LCA results (CEENE method)
MJex/functionalities
Abiotic Renewables
Fossil
fuels
Nuclear
resources
Metal ores
Minerals
Water
Land use
Atmospheric
TOTAL
Relative contribution (%)
Digestion
2.64E+01
6.86E+02
6.66E+01
5.51E-01
9.04E-01
4.64E+01
1.41E+03
0.00E+00
2.21E+03
72.74
CHP process
6.35E+00
1.48E+02
1.53E+01
7.40E-02
3.68E-02
1.17E+01
4.23E+00
1.86E+02
6.14
Condensation
3.01E+00
7.08E+01
7.30E+00
1.57E-02
1.51E-02
5.58E+00
1.99E+00
8.87E+01
2.93
Inoculum production
1.76E+00
2.67E+01
5.51E+00
3.22E-02
2.50E-02
8.62E+00
9.40E-01
4.36E+01
1.44
Algae cultivation T2
7.12E+00
1.68E+02
1.74E+01
8.16E-02
5.12E-02
2.30E+01
7.60E+00
2.24E+02
7.37
Algae cultivation T1
7.10E+00
1.73E+01
8.18E-02
5.33E-02
7.59E+00
2.23E+02
7.35
Dewatering T2
1.00E+00
2.35E+01
2.42E+00
7.18E-03
5.79E-03
1.85E+00
6.65E-01
2.94E+01
0.97
Dewatering T1
Drying
7.69E-03
2.79E+00
1.39E-02
1.95E-04
2.92E-04
5.54E-03
2.54E-03
2.82E+00
0.09
Crushing
2.06E-03
1.32E-01
5.07E-03
1.29E-05
2.35E-05
4.34E-03
2.10E-03
1.46E-01
0.00
5.38E+01
1.32E+03
1.34E+02
8.51E-01
1.10E+00
1.22E+02
1.43E+03
3.03E+03
1.77
43.44
4.43
0.03
0.04
4.02
47.16

8. LCA (cradle-to-gate)
A basket of products delivered by the linear (soybean based) economy and (algae based) biorefinery
Prudêncio da Silva et al. 2010

9. LCA results (CEENE method)
MJex/functionalities
Abiotic Renewables
Fossil
fuels
Nuclear
resources
Metal ores
Minerals
Water
Land use
Atmospheric
TOTAL
Relative contribution (%)
LINEAR ECONOMY
Soybean cultivation
1.18E-02
2.69E-01
2.79E-02
7.15E-04
6.91E-04
2.57E-02
4.81E+00
0.00E+00
5.15E+00
91.47
Drying
6.97E-04
2.33E-03
9.15E-04
2.03E-05
3.92E-05
1.76E-04
1.75E-01
1.80E-01
3.19
Crushing
1.45E-02
7.76E-02
1.68E-03
1.26E-05
2.23E-05
1.28E-03
3.52E-03
9.86E-02
1.75
Export to The Netherlands
2.96E-03
1.74E-01
1.04E-02
1.46E-04
7.32E-04
4.65E-03
9.29E-03
2.02E-01
3.58
2.99E-02
5.23E-01
4.08E-02
8.94E-04
1.48E-03
3.18E-02
5.00E+00
5.63E+00
0.53
9.29
0.73
0.02
0.03
0.56
88.85
0.00
BIOREFINERY
Algae cultivation
2.04E+01
4.68E+02
5.10E+01
2.20E-01
1.53E-01
6.29E+01
1.91E+01
6.22E+02
99.53
7.69E-03
2.79E+00
1.39E-02
1.95E-04
2.92E-04
5.54E-03
2.54E-03
2.82E+00
0.45
1.84E-03
1.18E-01
4.51E-03
1.15E-05
2.09E-05
3.86E-03
1.87E-03
1.30E-01
2.05E+01
4.72E+02
5.11E+01
1.54E-01
6.30E+01
6.25E+02
3.28
75.50
8.18
0.04
10.08
3.06
Factor 100 difference could be expected:
mature large scale technology (soybean) versus young small scale technology (algae)

10. Conclusion
Improvements in terms of energy efficiency necessary to become competitive with protein rich soy meal
Modified sensitivity test (electricity based on wind energy, lower working hours for blowers and mixing devices, more energy efficient blower, higher harvested fraction and algal productivity) reveals promising results!
Further research:
Process optimization (e.g. recycling of centrates, digestate or livestock manure as nutrients for algae, …)
Protein digestibility
LCA: emission footprint

11. Thank you!
+32 (0)