Shen Fuzhen, Zhang Lin, Jiang Lu, Tang Mingqi, Gai Xinyu, Chen Mindong, Ge Xinlei
Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China.
Reading Academy, Nanjing University of Information Science and Technology, Nanjing 210044, China.
Environ Int. 2020 Apr;137:105556. doi: 10.1016/j.envint.2020.105556. Epub 2020 Feb 10.
Air pollution events occurred frequently in China, and tremendous efforts were devoted to the reduction of air pollution in recent years. Here, analysis of ambient monitoring data of six criteria air pollutants from 367 Chinese cities during 2015-2018, showed that PM, PM, SO and CO were reduced significantly by 22.1%, 13.5%, 46.4% and 21.5%, respectively, NO reduction was less significant (6.3%) while O level instead increased over China (13.7%). Spatial distribution, seasonal, monthly and diurnal variations of the air pollutants during 2018, implicated of effective control measures, were discussed in details, especially for the five key densely populated regions of Jing-Jin-Ji (JJJ), Fen Wei Plains (FWP), Yangtze River Delta (YRD), Sichuan Basin (SCB) and Pearl River Delta (PRD). Moreover, excess health risks (ERs) of the six pollutants were estimated for 2018, and such risks was two times higher if the World Health Organization (WHO) air quality guideline rather than Chinese guideline was adopted. PM rather than PM was the dominant contributor to ERs, and the case with both PM and PM exceeding threshold values occupied ~1/3 of total days, yet contributed ~2/3 of total ERs. For 2018, the health-risk based air quality index (HAQI) was further calculated by combining health risks from multiple pollutants, and it was found that high HAQI mostly distributed in North China Plain (NCP). ~15%, ~85% and ~95% people in YRD, FWP and JJJ were exposed to polluted air (HAQI > 100), and population-normalized HAQI further added the inequality, JJJ and a small region of SCB had much higher HAQI (>280). Investigations on HAQI with socioeconomic factors show that total population, population density and built-up area presented an inverted U-shape, suggesting existence of Environmental Kuznets Curve (EKC), while a positive relationship was found between HAQI and share of secondary industry. Multiple regression analysis suggested that built-up area was the most prominent factor to HAQI, followed by the gross domestic product (GDP). The findings here demonstrate in great details the current characteristics of air pollution and its associated health risks in China, therefore providing important implications for effective air pollution control strategies in near future for different regions of China.
空气污染事件在中国频繁发生，近年来我国在减少空气污染方面付出了巨大努力。在此，对2015 - 2018年期间中国367个城市六种空气污染物的环境监测数据进行分析，结果表明，细颗粒物（PM）、可吸入颗粒物（PM）、二氧化硫（SO）和一氧化碳（CO）分别显著下降了22.1%、13.5%、46.4%和21.5%，氮氧化物（NO）降幅较小（6.3%），而臭氧（O）水平在全国范围内反而上升了13.7%。详细讨论了2018年空气污染物的空间分布、季节、月度和日变化情况以及有效的控制措施，尤其针对京津冀（JJJ）、汾渭平原（FWP）、长江三角洲（YRD）、四川盆地（SCB）和珠江三角洲（PRD）这五个主要人口密集地区。此外，还估算了2018年这六种污染物的超额健康风险（ERs），如果采用世界卫生组织（WHO）空气质量准则而非中国准则，此类风险会高出两倍。细颗粒物（PM）而非可吸入颗粒物（PM）是超额健康风险的主要贡献者，PM和PM均超过阈值的情况占总天数的约1/3，但却贡献了约2/3的总超额健康风险。对于2018年，通过综合多种污染物的健康风险进一步计算了基于健康风险的空气质量指数（HAQI），发现高HAQI值大多分布在华北平原（NCP）。长江三角洲（YRD）、汾渭平原（FWP）和京津冀（JJJ）分别有15%、85%和95%的人口暴露于污染空气中（HAQI > 100），按人口归一化后的HAQI进一步加剧了不平等，京津冀（JJJ）和四川盆地（SCB）的一个小区域HAQI值更高（> 280）。对HAQI与社会经济因素的调查表明，总人口、人口密度和建成区面积呈现倒U形，表明存在环境库兹涅茨曲线（EKC），而HAQI与第二产业之间存在正相关关系。多元回归分析表明，建成区面积是影响HAQI的最显著因素，其次是国内生产总值（GDP）。此处的研究结果详细展示了中国目前空气污染的特征及其相关健康风险，从而为中国不同地区近期有效的空气污染控制策略提供了重要启示。
