Impact of energy flow optimization on the mitigation of environmental consequences and costs in greenhouse cucumber prod
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RESEARCH ARTICLE
Impact of energy flow optimization on the mitigation of environmental consequences and costs in greenhouse cucumber production Farshad Soheilifard 1 & Morteza Taki 1
&
Rosalie van Zelm 2
Received: 13 May 2020 / Accepted: 11 October 2020 # Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract Cucumber, as a major cultivated plant in Iran, takes up more than 80% of greenhouse production. So, improving the production efficiency can save energy, reduce the environmental consequences and production costs, and also create a lot of job opportunities. The present study aimed to investigate the impact of energy flow optimization on the environmental impacts and costs in greenhouse cucumber production by data envelopment analysis (DEA) and life cycle assessment (LCA) methods. For environmental assessment, human health damage, ecosystem damage, and resource scarcity were considered and analyzed in the form of 8, 12, and 2 impact categories, respectively, using the ReCiPe2016 (H) method on endpoint level. Required data were collected through questionnaire from 30 cucumber growers. The results of the current status of environmental impacts showed the major contribution of fuels (natural gas and diesel) in all three main impact categories. Based on DEA analysis, 19 greenhouses (63%) were identified as inefficient units with a mean efficiency score of 0.70 (TE = 0.7). The highest inefficiency was related to the manure (72%), electricity (71.7%), and fuel (59%), respectively. Electricity and manure showed the highest saving potential, while the highest contribution to total energy saving was related to fuel (87%). Environmental analysis of optimized greenhouses showed that efficient use of inputs can reduce all environmental impacts between 7 and 80%, which highlights the importance of efficient resource management in this study. Also, production costs were decreased by about 67 $ tonne−1 (196 to 129 $) after the optimization of the units. Keywords Data envelopment analysis . Life cycle assessment . Energy efficiency . Energy flow . Optimization
Nomenclature GHG Greenhouse gas LCA Life cycle assessment DEA Data envelopment analysis DMU Decision-making unit LCI Life cycle inventory LCIA Life cycle impact assessment
FU DALY CCR BCC VRS CRS TE PTE
Functional unit Disability-adjusted life years Charnes, Cooper, and Rhodes Banker, Charnes, and Cooper Variable returns to scale Constant returns to scale Technical efficiency Pure technical efficiency
Responsible Editor: Philippe Loubet * Morteza Taki [email protected]; [email protected] 1
Department of Agricultural Machinery and Mechanization, Faculty of Agricultural Engineering and Rural Development, Agricultural Sciences and Natural Resources University of Khuzestan, P.O. Box: 6341773637, Mollasani, Iran
2
Department of Environmental Science, Institute for Water and Wetland Research, Radboud University Nijmegen, Nijmegen, Netherlands
Introduction The agricultural sector is one of the major contributors to greenhouse gases (GHGs) emissio
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