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doi:10.3808/jei.202100458
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Development of An Integrated Method (MGCMs-SCA-FER) for Assessing the Impacts of Climate Change – A Case Study of Jing-Jin-Ji Region

H. Mei1,2, Y. P. Li1,3 *, J. Lv4, X. J. Chen3, C. Lu3, C. Suo4, and Y. Ma1

  1. Environment and Energy Systems Engineering Research Center, School of Environment, Beijing Normal University, Beijing 100875, China
  2. Shenzhen Academy of Environmental Sciences, Shenzhen 518001, China
  3. Institute for Energy, Environment and Sustainable Communities, University of Regina, Regina, SK S4S 0A2, Canada
  4. Sino-Canada Energy and Environmental Research Academy, North China Electric Power University, Beijing 102206, China

*Corresponding author. Tel.: +86 10 58800156; fax: +86 10 58800156. E-mail address: yongping.li@iseis.org (Y. P. Li).

Abstract


In this study, an integrated method (abbreviated as MGCMs-SCA-FER) is developed for assessing the impacts of climate change, which incorporates multiple global climate models (MGCMs), stepwise cluster analysis (SCA), and fixed-effects regression (FER) within a general framework. MGCMs-SCA-FER is capable of (i) dealing with the uncertainty in climate change projection caused by heterogeneity of structures and parameters of GCM; (ii) capturing nonlinear relationship between input variables and outputs without assumption of their functions; (iii) identifying interaction of different units and quantifying the effects of climate change on electricity demand. MGCMs-SCA-FER is then applied to Jing-Jin-Ji for assessing the impacts of climate change on single-city and entire-region electricity demands. Results demonstrated that climate change projections and electricity demand predictions varied significantly across different GCMs and RCPs. Results disclose that (i) Jing-Jin-Ji region would experience a warmer climate in the next 80 years of 2021 ~ 2100 (For every decade, temperatures would increase by [0.17, 0.23] °C under RCP4.5 and [0.35, 0.54] °C under RCP8.5); (ii) For 1 °C increase in temperature, annual electricity demand would rise by 4.5%; (iii) electricity intensity has the most significant impact on electricity demand for Jing-Jin-Ji region; (iv) electricity demand would increase under all scenarios, and the electricity demand under RCP8.5 would be higher than that under RCP4.5. From a long-term perspective, analyzing the climate change impacts on electricity demand and making adaptive management strategy are important for the regional sustainability

Keywords: climate change, electricity demand, fixed-effects regression, impact assessment, multi-GCMs, stepwise cluster analysis


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