Life cycle evaluation of microalgae based biorefinery supply network: A sustainable multi-criteria approach
Algal Research, ISSN: 2211-9264, Vol: 66, Page: 102816
2022
- 6Citations
- 33Captures
- 1Mentions
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Article Description
Due to enjoying such features as ability to produce high volumes of oil and reducing and eliminating environment carbon dioxide, microalgae is a promising solution for producing biofuels. In order to help the commercialization of this emerging industry, the present study offers a sustainable mixed integer linear programming model (MILP) for designing and planning microalgae biofuel production and distribution network. As objective functions, this model considers minimizing the total cost of the network and maximizing greenhouse gas emission saving simultaneously. In order to design microalgae biofuel sustainable production and distribution network, a two-stage approach is developed. In order to reduce computational complexity, at first place, data envelopment analysis approach (DEA) and Combinative Distance-Based Assessment (CODAS) approach as well as best worst method (BWM) are developed respectively for determining the location of suitable candidates for establishing microalgae production facilities and constructing biorefinery based on economic, social and environmental criteria. In the second stage, the environmental effects of microalgae biofuel supply chain network are measured using one of the newest and most effective methods that is based upon environmental life cycle assessment as well as OpenLCA software and then followed by formulizing a bi-objective linear programming model. For solving the offered model, augmented epsilon constraint method is used. Finally, a realistic case study conducted at national level concerning microalgae biofuel supply chain. The results indicate that based on the offered model by replacing fossil fuels with biofuel we can achieve greenhouse gases emission saving by 99 %.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S2211926422001874; http://dx.doi.org/10.1016/j.algal.2022.102816; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85136485793&origin=inward; https://linkinghub.elsevier.com/retrieve/pii/S2211926422001874; https://dx.doi.org/10.1016/j.algal.2022.102816
Elsevier BV
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