TY - JOUR
T1 - Suitability modeling and sensitivity analysis for biomass energy facilities in Turkey
AU - Guler, Dogus
AU - Charisoulis, Georgios
AU - Buttenfield, Barbara P.
AU - Yomralioglu, Tahsin
N1 - Publisher Copyright:
© 2021, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.
PY - 2021/9
Y1 - 2021/9
N2 - Nowadays, problems relating to the inadequacy of energy resources are emerging, due to fast population growth and inevitable urban sprawl. Renewable energy resources are of vital importance in order to overcome these problems that endanger countries in terms of economic, social, and environmental factors. The determination of suitable facility locations is a key matter to solve, in order to effectively exploit biomass energy potential. This paper proposes an approach to biomass facility location that integrates open-source geographic information systems (GIS), fuzzy logic, and a best worst method (BWM) solution, which is a newly developed multi-criteria decision-making (MCDM) method to address optimal facility location. Suitable locations take different criteria into consideration, including potential biomass amount (e.g., agricultural and animal wastes), slope, and distances to roads and water bodies. By utilizing MCDM, the most critical criterion can be determined. Moreover, the paper demonstrates that fuzzy logic allows intermediate values for suitability criteria and is preferable to Boolean logic. The proposed approach is illustrated using all cities of Turkey as an empirical case study. Four specific regions that greatly have highly suitable areas are presented. Sensitivity analysis shows that different agendas such as economic cost and social impact might change the suitability results, specifically in areas of the highly suitable class. These results are most strongly affected by potential biomass amount, population density, and distances to roads and settlements. Graphic abstract: [Figure not available: see fulltext.].
AB - Nowadays, problems relating to the inadequacy of energy resources are emerging, due to fast population growth and inevitable urban sprawl. Renewable energy resources are of vital importance in order to overcome these problems that endanger countries in terms of economic, social, and environmental factors. The determination of suitable facility locations is a key matter to solve, in order to effectively exploit biomass energy potential. This paper proposes an approach to biomass facility location that integrates open-source geographic information systems (GIS), fuzzy logic, and a best worst method (BWM) solution, which is a newly developed multi-criteria decision-making (MCDM) method to address optimal facility location. Suitable locations take different criteria into consideration, including potential biomass amount (e.g., agricultural and animal wastes), slope, and distances to roads and water bodies. By utilizing MCDM, the most critical criterion can be determined. Moreover, the paper demonstrates that fuzzy logic allows intermediate values for suitability criteria and is preferable to Boolean logic. The proposed approach is illustrated using all cities of Turkey as an empirical case study. Four specific regions that greatly have highly suitable areas are presented. Sensitivity analysis shows that different agendas such as economic cost and social impact might change the suitability results, specifically in areas of the highly suitable class. These results are most strongly affected by potential biomass amount, population density, and distances to roads and settlements. Graphic abstract: [Figure not available: see fulltext.].
KW - Best worst method (BWM)
KW - Biomass energy
KW - Fuzzy logic
KW - Open-source geographic information systems (GIS)
KW - Suitability modeling
KW - Turkey
UR - http://www.scopus.com/inward/record.url?scp=85107405755&partnerID=8YFLogxK
U2 - 10.1007/s10098-021-02126-8
DO - 10.1007/s10098-021-02126-8
M3 - Article
AN - SCOPUS:85107405755
SN - 1618-954X
VL - 23
SP - 2183
EP - 2199
JO - Clean Technologies and Environmental Policy
JF - Clean Technologies and Environmental Policy
IS - 7
ER -