Collaborative Optimization of Emissions and Abatement Costs for Air Pollutants and Greenhouse Gases from the Perspective of Energy Structure: An Empirical Analysis in Tianjin
Xiaran Zhang,
Xiaoxia Rong,
Meng Cai and
Qingchun Meng
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Xiaran Zhang: School of Management, Shandong University, Jinan 250100, China
Xiaoxia Rong: School of Mathematics, Shandong University, Jinan 250100, China
Meng Cai: School of Management, Shandong University, Jinan 250100, China
Qingchun Meng: School of Management, Shandong University, Jinan 250100, China
Sustainability, 2019, vol. 11, issue 14, 1-18
Abstract:
Both air pollution and greenhouse effect have become important issues with regard to environmental protection both in China and across the world. Consumption of energy derived from coal, oil, and natural gas forms the main source of China’s major air pollutants, SO 2 and NO X , as well as the major greenhouse gas CO 2 . The energy structure adjustment approach provides a sensible way, not only to achieve climate change mitigation and air pollutant reduction, but also to reduce abatement costs. In this paper, a multi-objective optimization method was adopted in order to analyze the collaborative optimization of emissions and abatement costs for both air pollutants and greenhouse gases. As a typical industrial city and economic center with fossil fuels as its main energy source, Tianjin of China is used as the research sample to prove that this method can mitigate air pollutants and greenhouse gas emissions and reduce abatement costs. Through demonstration, the results show that the optimization method proposed can reduce SO 2 , NO X , and CO 2 emissions by 27,000 tons, 33,000 tons, and 29,000 tons, respectively, and the abatement costs will be reduced by 620 million yuan by adjusting the energy structure of Tianjin. The proposed method also suggests that China can achieve reductions of abatement cost and greenhouse gas and air pollutant emissions under the proposed energy structure. The results indicate that collaborative optimization would help China and other countries cope with climate change while improving domestic air quality.
Keywords: collaborative optimization; emission reduction; abatement cost; energy structure; multi-objective optimization (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:11:y:2019:i:14:p:3872-:d:248941
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