Spatialization of Chinese R-410A emissions from the room air-conditioning sector

Pengcheng Wu, Li Zhang, Bo Yao (), Bofeng Cai (), Yifang Zhu (), Hui Liu, Pengling Wang, Lisha Liu, Yanwei Dou, Han Yan, Yijun Liu, Zixuan Xie, Lingyun Pang, Libin Cao, Yimeng Ren and Xin Bo
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Pengcheng Wu: Sun Yat-Sen University
Li Zhang: Chinese Academy of Environmental Planning
Bo Yao: Fudan University
Bofeng Cai: Chinese Academy of Environmental Planning
Yifang Zhu: University of California Los Angeles
Hui Liu: Wuhan University
Pengling Wang: National Climate Center
Lisha Liu: University of New South Wales
Yanwei Dou: China Household Electrical Appliances Association
Han Yan: Taikang Asset Management Co., LTD
Yijun Liu: Shanghai Jiao Tong University
Zixuan Xie: Washington University in St. Louis
Lingyun Pang: Chinese Academy of Environmental Planning
Libin Cao: Chinese Academy of Environmental Planning
Yimeng Ren: Renmin University of China
Xin Bo: Beijing University of Chemical Technology

Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, 2023, vol. 25, issue 6, No 19, 5263-5281

Abstract: Abstract Hydrofluorocarbons (HFCs) are strong greenhouse gases and regulated by the Montreal Protocol as substitutes of ozone depletion substances. Currently, Chinese HFC emissions keep increasing, and the inventory is only on a national or city level. A high-resolution gridded HFC emission inventory is needed to develop HFC reduction policy and phase-down schedule. We developed a method by integrating point sources with longitude and latitude information and area sources using the proxy factor to explore the distribution of R-410A [a mixture of HFC-32 (CH2F2) and HFC-125 (C2HF5)] emissions from the room air-conditioning sector on a 10 × 10 km2 grid scale. Variety of regression models (including the principal component analysis, multiple linear regressions, stepwise regressions, and linear regression), analysis scale (national level and provincial level), and data dimensions (the proxy factor and unit-area value) were tested. The gross domestic product was found as the optimal proxy factor and used to spatialize R-410A emissions at a high-resolution scale. Compared to the national-level analysis, model evaluation parameters were largely improved for the provincial-level regression analysis, including root-mean-square error (from 20.96 to 11.35), normalized mean bias (from 0.16 to − 0.01), normalized mean error (from 0.45 to 0.20), mean absolute error (from 11.27 to 4.97), correlation coefficient (from 0.91 to 0.97), and relative error (from 39% to 76%), suggesting a better performance for the provincial-level analysis. This study provides a cost-effective method to establish fine-resolution HFC inventory. Meanwhile, high-resolution emissions grid data could be further applied to implement site-specific management of low-carbon development.

Keywords: High-resolution; R-410A emissions; Hydrofluorocarbons; Room air-conditioning; Spatialization; Proxy factors (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10668-022-02264-z

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