School of Economics and Management, Tongji University, Siping Road 1500, Shanghai 200092, China.
Int J Environ Res Public Health. 2018 Mar 15;15(3):529. doi: 10.3390/ijerph15030529.
The particulate matter 2.5 (PM) is a serious air-pollutant emission in China, which has caused serious risks to public health. To reduce the pollution and corresponding public mortality, this paper proposes a method by incorporating slacks-based data envelopment analysis (DEA) and an integrated exposure risk (IER) model. By identifying the relationship between the PM concentration and mortality, the potential PM concentration efficiency and mortality reduction were measured. The proposed method has been applied to China's 243 cities in 2015. Some implications are achieved. (1) There are urban disparities in estimated results around China. The geographic distribution of urban mortality reduction is consistent with that of the PM concentration efficiency, but some inconsistency also exists. (2) The pollution reduction and public health improvement should be addressed among China's cities, especially for those in northern coastal, eastern coastal, and middle Yellow River areas. The reduction experience of PM concentration in cities of the southern coastal area could be advocated in China. (3) Environmental consideration should be part of the production adjustment of urban central China. The updating of technology is suggested for specific cities and should be considered by the policymaker.
细颗粒物 2.5（PM）是中国严重的空气污染物排放，对公众健康造成严重风险。为了减少污染和相应的公众死亡率，本文提出了一种方法，结合基于松弛的数据包络分析（DEA）和综合暴露风险（IER）模型。通过识别 PM 浓度与死亡率之间的关系，测量了潜在的 PM 浓度效率和死亡率降低。该方法已应用于 2015 年中国的 243 个城市。得出了一些结论。（1）中国各地的估计结果存在城市差异。城市死亡率降低的地理分布与 PM 浓度效率的分布一致，但也存在一些不一致。（2）中国的城市应该解决污染减排和公众健康改善问题，特别是北方沿海、东部沿海和黄河中游地区的城市。应该在中国倡导南方沿海地区城市在 PM 浓度降低方面的经验。（3）环境因素应成为中国中部城市生产调整的一部分。建议对特定城市进行技术更新，并由政策制定者进行考虑。
