我国省域CO2-PM2.5-O3时空关联效应与协同管控对策

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摘要首先分析了2015~2019年我国省域CO₂排放量和大气PM_2.5、O₃污染浓度的时空特征及三者变化量之间的关联效果.而后利用排放因子法编制2011~2019年各省CO₂和PM_2.5、O₃前体物的排放清单,结合STIRPAT模型分情景预测了CO₂和PM_2.5、O₃前体物的协同效应,并建立评级体系识别重点管控区域并对其开展分部门的协同效应解析,最后提出分级协同管控对策.研究结果表明,53%的省份CO₂减排与PM_2.5浓度下降之间不存在关联效果,87%的省份CO₂减排与O₃浓度下降之间不存在关联效果.2012~2014年我国CO₂与PM_2.5具有协同效应,而2015~2019年则不具有该效应,另多数研究年份CO₂与O₃前体物具有协同效应,但并未出现减污降碳协同效应.基于协同效应系数分析,低碳情景下达到协同效应的省份多于基准情景.根据评级体系将所研究的省份分为4级管控区域,“Ⅰ级管控区域”各部门应优先考虑CO₂和PM_2.5的协同减排,“Ⅱ级管控区域”各部门应优先考虑CO₂和O₃的协同减排,建议各部门参照低碳情景发展,“Ⅰ、Ⅱ级管控区域”需合理调控人口和城镇化率,优化能源结构等.

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	李飞
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	周媛媛
	欧昌宏

关键词 ：减污降碳, 协同效应, 时空特征, STIRPAT模型, 分级管控, PM_2.5, O₃

Abstract：Spatio-temporal characteristics and correlation effects of CO₂ emissions and PM_2.5 and O₃ pollution concentrations in Chinese provinces from 2015 to 2019 were firstly analyzed. Then, the emission factor method was used to compile the emission inventories of CO₂, PM_2.5 and O₃ precursors in each province from 2011 to 2019, and combined the STIRPAT model the synergistic effects of CO₂, PM_2.5 and O₃ precursors were predicted under different scenarios. Moreover, a rating system was established to identify key control areas with their synergistic effects analyzed by sectors, and finally the targeted synergistic control measures were proposed. The results showed that there was no correlation between CO₂ emission reduction and PM_2.5 concentration reduction in 53% of the provinces, and that between CO₂ emission reduction and O₃ concentration reduction in 87% of the provinces. There was a synergistic effect between CO₂ and PM_2.5 in China from 2012 to 2014, while no synergistic effect from 2015 to 2019. Further, there was a synergistic effect between CO₂ and O₃ precursors in China in the most years, but there was no general synergistic effect between pollution reduction and carbon reduction. Based on the analysis of the obtained coefficient of synergy effect, more provinces achieved the synergistic effect in the low carbon scenario than that in the baseline scenario. Further, according to the developed rating system, the studied provinces were divided into four levels of control areas. The sectors in the "Class I Control Area" should give priority to the synergistic emission reduction of CO₂ and PM_2.5, while that in the "Class II Control Area" the synergistic emission reduction of CO₂ and O₃. It was recommended that each sector should take into account the low-carbon scenario, and the "I and II Control Area" should reasonably regulate the population and urbanization rate, and optimize the energy structure, etc.

Key words： pollution and carbon reduction synergistic effect spatio-temporal characteristics STIRPAT model hierarchical control PM_2.5 O₃

收稿日期: 2023-04-24

PACS:

X51

基金资助:国家社会科学基金资助项目(19CGL042);中央高校基本科研业务费专项资金资助项目(2722023EZ009;2722023EJ013)

通讯作者: 李飞,教授,lifei@zuel.edu.cn E-mail: lifei@zuel.edu.cn

作者简介: 李飞(1986-),男,河南新乡人,教授,博士,主要研究方向为环境监测、环境健康风险管理、环境与健康大数据、环境修复技术.发表论文100余篇.lifei@zuel.edu.cn.

引用本文:

李飞, 董珑, 孔少杰, 屈志光, 郭锦媛, 周媛媛, 欧昌宏. 我国省域CO₂-PM_2.5-O₃时空关联效应与协同管控对策[J]. 中国环境科学, 2023, 43(12): 6246-6260. LI Fei, DONG Long, KONG Shao-jie, QU Zhi-guang, GUO Jin-yuan, ZHOU Yuan-yuan, OU Chang-hong. Spatial-temporal correlation effects of CO₂-PM_2.5-O₃ and synergistic control countermeasures in China's provincial area. CHINA ENVIRONMENTAL SCIENCECE, 2023, 43(12): 6246-6260.

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