Li Gen, Zhang Runsen, Masui Toshihiko
Center for Social and Environmental Systems Research, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba 3058506, Japan.
Graduate School of Advanced Science and Engineering, Hiroshima University, 1-5-1 Kagamiyama, Higashihiroshima 7398529, Japan.
Sci Total Environ. 2021 Mar 20;761:143264. doi: 10.1016/j.scitotenv.2020.143264. Epub 2020 Nov 12.
This research involved constructing a computable general equilibrium (CGE) model for assessing China's latest environmental tax policies. Most environmental CGE models link pollutant emissions to the standard CGE model only by pollution coefficients per unit of sectoral output, and the emission reduction process is not included within production structures. We constructed separate pollution treatment sectors for solid waste management, wastewater management, and waste gas management to describe the pollution treatment processes and identify how policies affect production activities. We compiled the satellite accounts of 18 pollutants from the China Environmentally Extended Input-Output (CEEIO) dataset covering primary gas, water, and solid pollutants and disaggregated the electricity sector into six different production technologies: hydroelectricity, coal power, gas electricity, oil electricity, nuclear power, and renewable energies. We drew two primary conclusions from the simulation results. First, the environmental policies examined could help reduce the emissions of most kinds of pollutants, but also negatively affect GDP. GDP loss by 2030 would be 0.03% in the low environmental tax scenario (LowET), 0.06% in the high environmental tax scenario (HighET), 0.16% in the low environmental tax and low carbon tax scenario (LowETC), and 0.34% in the high environmental tax and high carbon tax scenario (HighETC). SO emissions would decrease by 17.4%, 21.0%, 19.3% and 24.5%, respectively, and CO emissions would reduce by 0.9%, 1.7%, 5.8% and 11.0%. Second, despite the minor changes in the economic impacts, the effectiveness in pollution treatment of environmental tax policies is underestimated if the pollution treatment sectors are disaggregated in the CGE model. Take the SO for an example. The calculated SO reductions will increase from 8.95% to 24.46% after disaggregating the pollution treatment sectors in HighETC scenarios.
本研究构建了一个可计算一般均衡（CGE）模型，用于评估中国最新的环境税收政策。大多数环境CGE模型仅通过单位部门产出的污染系数将污染物排放与标准CGE模型联系起来，而减排过程并未纳入生产结构之中。我们针对固体废物管理、废水管理和废气管理构建了单独的污染治理部门，以描述污染治理过程，并确定政策如何影响生产活动。我们根据涵盖主要气体、水和固体污染物的中国环境扩展投入产出（CEEIO）数据集编制了18种污染物的卫星账户，并将电力部门细分为六种不同的生产技术：水力发电、煤炭发电、天然气发电、石油发电、核能发电和可再生能源。我们从模拟结果中得出了两个主要结论。首先，所考察的环境政策有助于减少大多数种类污染物的排放，但也会对国内生产总值产生负面影响。在低环境税情景（LowET）下，到2030年国内生产总值损失将为0.03%；在高环境税情景（HighET）下为0.06%；在低环境税和低碳税情景（LowETC）下为0.16%；在高环境税和高碳税情景（HighETC）下为0.34%。二氧化硫排放量将分别减少17.4%、21.0%、19.3%和24.5%，一氧化碳排放量将分别减少0.9%、1.7%、5.8%和11.0%。其次，尽管经济影响的变化较小，但如果在CGE模型中对污染治理部门进行细分，环境税收政策在污染治理方面的有效性会被低估。以二氧化硫为例。在HighETC情景下对污染治理部门进行细分后，计算得出的二氧化硫减排量将从8.95%增至24.46%。
Zotero 插件