Abstract
As the most developed city circle in northern China, allocating CO2 emission quotas at the Bohai Rim Economic Circle (BREC) city level is essential for developing specific abatement policies. Thus, with reflecting multi-principles (fairness, efficiency, sustainability, and feasibility), this paper formulates the CO2 emission quota allocation among cities in BREC in 2030 based on the multi-objective decision approach. We first propose three allocation schemes based on the principles of fairness, efficiency, and sustainability, which are conducted by entropy method, zero-sum gains data envelopment (ZSG-DEA) model, and CO2 sequestration share method, respectively. Then, the CO2 allocation satisfaction is defined and used to measure the feasibility principle which is integrated as the objective function of the multi-objective decision model together with three allocation schemes to obtain the optimal allocation results. The results show that Beijing, Tianjin, Dalian, Shijiazhuang, Yantai, Weifang, and Linyi enjoy the largest CO2 emission quotas, having 1179.94 Mt in total and accounting for 31%. Beijing has the highest quotas, and Laiwu has the lowest emission quotas. Cities with large energy consumption and less CO2 sequestration capacity, such as Tianjin, Handan, and Tangshan, experience a decrease in the emission quota shares from 2017 to 2030, indicating that these cities would undertake large emission reduction obligations. Sensitivity analysis shows that Beijing, Zibo, and Jinan are more sensitive to minimum satisfaction changes, and the total satisfaction experiences an increase first and declines thereafter. Based on the results above, cities with large pressure to reduce CO2 emissions should not only promote economic development but also improve the capacity of CO2 sequestration by enhancing environmental protection to realize emission reduction targets.
Highlights
In order to combat climate change, the Chinese government has undertaken to reduce the national carbon emission intensity by 60%-65% in 2030 compared with 2005 and reach the CO2 emissions peak before 2030
According to the interpretation of fair CO2 emission quotas allocation in previous literature, this paper uses four indicators selected from different perspectives of fairness principle to obtain the allocation scheme based on fairness, including population, GDP, historical cumulative net CO2 emissions, and historical carbon emission
This paper develops a multi-objective decision model integrating the principles of fairness, efficiency, sustainability, and feasibility to allocate the CO2 emission quotas at the city level
Summary
In order to combat climate change, the Chinese government has undertaken to reduce the national carbon emission intensity by 60%-65% in 2030 compared with 2005 and reach the CO2 emissions peak before 2030. To reduce carbon emissions intensity, China has committed to implementing the emissions trading scheme (ETS), which is an effective way to reduce CO2 emissions through the market mechanism (Han et al, 201 7; Kong et al, 2019; Hu et al.,2020). Studies have focused on CO2 emission quotas allocation at different levels, for example, country level (Benestad, 1994; Pan et al, 2014; Momeni et al, 2018), China’s provincial level (Yi et al, 2011; Kong et al, 2019; He and Zhang 2020; Zhou et al, 2021) and several provinces within specific regions (Han et al, 2016; Chang et al, 2020). Few studies and methods are focusing on the CO2 emission quotas allocation at the city level
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