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基于STRIPAT-情景分析的中国浙江省PM浓度影响因素及趋势预测

Influencing factors and trend prediction of PM concentration based on STRIPAT-Scenario analysis in Zhejiang Province, China.

作者信息

Zhang Qiong, Ye Shuangshuang, Ma Tiancheng, Fang Xuejuan, Shen Yang, Ding Lei

机构信息

Research Center of Industrial Economy Around Hangzhou Bay, Ningbo Polytechnic, Ningbo, 315800 China.

Ningxia Art Vocational College, Yinchuan, 750021 China.

出版信息

Environ Dev Sustain. 2022 Sep 15:1-25. doi: 10.1007/s10668-022-02672-1.

Abstract

The government's development of eco-environmental policies can have a scientific foundation thanks to the fine particulate matter (PM) medium- and long-term change forecast. This study develops a STRIPAT-Scenario analysis framework employing panel data from 11 cities in Zhejiang Province between 2006 and 2020 to predict the changing trend of PM concentrations under five alternative scenarios. The results reveal that: (1) urbanization development (), economic development (), technological innovation investment () and environmental regulation intensity have a significant inhibitory effect on PM concentration in Zhejiang Province, while industrial structure, industrial energy consumption and the number of motor vehicles () have a significant increase on PM concentration. (2) Under any scenario, the PM concentration of 11 cities in Zhejiang Province can reach the constraint target set in the 14th Five-Year plan. The improvement in urban PM quality is most obviously impacted by the high-quality development scenario (S4). (3) Toward 2035, PM concentrations of 11 cities in Zhejiang Province can reach the National Class I level standard in most scenario models, among which Hangzhou, Jiaxing and Shaoxing are under high pressure to reduce emissions and are the key areas for PM management in Zhejiang Province. However, most cities cannot reach the 10 μg/m limit of WHO's AQG2005 version. Finally, this study makes recommendations for reducing PM in terms of enhancing industrial structure and funding science and technology innovation.

摘要

政府生态环境政策的制定得益于细颗粒物(PM)中长期变化预测,从而有了科学依据。本研究构建了一个基于2006年至2020年浙江省11个城市面板数据的STIRPAT - 情景分析框架,以预测五种替代情景下PM浓度的变化趋势。结果表明:(1)城市化发展()、经济发展()、技术创新投入()和环境规制强度对浙江省PM浓度有显著抑制作用,而产业结构、工业能源消耗和机动车保有量()对PM浓度有显著增加作用。(2)在任何情景下,浙江省11个城市的PM浓度均能达到“十四五”规划设定的约束性目标。城市PM质量改善受高质量发展情景(S4)影响最为明显。(3)到2035年,浙江省11个城市的PM浓度在多数情景模型下能达到国家一级标准水平,其中杭州、嘉兴和绍兴减排压力较大,是浙江省PM治理的重点区域。然而,多数城市无法达到世界卫生组织2005年版空气质量准则(AQG2005)10μg/m的限值。最后,本研究从优化产业结构和加大科技创新投入方面对降低PM提出了建议。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0748/9476454/aa7a804f672d/10668_2022_2672_Fig1_HTML.jpg

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