Evaluating ecosystem service trade-offs with wind electricity production in Switzerland

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• 作者：Thomas Egli^a ; ^b ; Janine Bolliger^a ; Felix Kienast^a ; ^{felix.kienast@wsl.ch" class="auth_mail" title="E-mail the corresponding author}
• 关键词：Marxan ; Trade-offs ; Ecosystem services ; Wind turbines ; Land-use change ; Land-use conflict
• 刊名：Renewable and Sustainable Energy Reviews
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：67
• 期：Complete
• 页码：863-875
• 全文大小：1769 K

文摘

In Switzerland, different types of land use, including electricity production, compete directly for little available space. The Swiss energy strategy relies heavily on incorporating renewable sources of electricity, including wind. In order to ensure long term efficient, socially acceptable and sustainable electricity production, land-use conflicts should be addressed and properly managed through a comprehensive and balanced process. We propose a method to apply the ecosystem service (ES) approach combined with an optimisation tool to tackle the complex problems posed by wind electricity development in a topographically challenging landscape. Marxan was used as optimisation software to evaluate, assess, and quantify the trade-offs between ES provisioning and wind electricity production. Expressing different ES in comparable units and evaluating the costs to the system when these are lost versus the benefits gained from wind electricity production generated an output of possible solutions. When compared to similar studies modelling wind electricity output that avoid negative interaction with ES throughout Switzerland, the current results using the optimisation tool Marxan suggest a solution requiring 13.5% fewer turbines (1903 in an average solution) in order to produce 12 TWh/yr of wind generated electricity and 18% fewer turbines (842 on average) to produce 5 TWh/yr. Thus, using optimisation software can lead to more efficient spatial planning solutions. Our methodology can be applied toward cost-effective renewable energy development that minimises opportunity cost in terms of foregone ES provisioning.