Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China; Key Laboratory of Meteorological Disaster, Ministry of Education (KLME), Joint International Research Laboratory of Climate and Environment Change (ILCEC), Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing 210044, China.
Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China.
Sci Total Environ. 2020 Nov 20;744:140837. doi: 10.1016/j.scitotenv.2020.140837. Epub 2020 Jul 13.
Stringent clean air actions have been implemented to improve air quality in China since 2013. In addition to anthropogenic emission abatements, the changes in air quality may be modulated also by meteorology. In this study, we developed multiple linear regression models to quantify meteorological influences on the trends in fine particulate matter (PM) and ozone (O) concentrations and associated health burden over three polluted regions of China, i.e., North China Plain, Yangtze River Delta, and Fen-wei Plain during 2014-2018, with a novel focus on the contributions of the most influential meteorological factors to PM and O trends as well as the meteorological contributions to PM- and O-related mortality trends. The meteorology-driven PM (O) trends for the three regions were -0.5-2.0 (+0.7+0.8) μg m yr, contributing 10- 26% (12- 18%) of the observed five-year decreasing PM (increasing O) trends. The decreased relative humidity (increased daytime planetary boundary layer height) was identified to be the most influential meteorological factor and explained 55% (42%) of the largest meteorology-driven PM (O) trend among all regions and seasons. The meteorology-driven decreases in PM (increases in O) concentrations led to overall decreases in PM-related (increases in O-related) mortalities with trends of -2.2-7.4 (+0.5+0.9) thousand yr for the three regions, accounting for 10- 26% (15- 31%) of the total decreasing (increasing) trends in PM-related (O-related) mortalities. The results emphasize the important role of meteorology in PM and O air quality and associated health burden over China, and have important implications for China's air quality planning. In particular, more efforts in emission control should be taken to offset the adverse effects on ozone caused by meteorology.
自 2013 年以来,中国已实施严格的清洁空气行动以改善空气质量。除了人为减排之外,空气质量的变化也可能受到气象条件的调节。在这项研究中,我们开发了多元线性回归模型,以量化气象因素对中国三个污染地区(华北平原、长三角和汾渭平原)细颗粒物(PM)和臭氧(O)浓度趋势及其相关健康负担的影响,特别关注最具影响力的气象因素对 PM 和 O 趋势的贡献,以及气象因素对 PM 和 O 相关死亡率趋势的贡献。这三个地区的气象驱动的 PM(O)趋势分别为-0.5-2.0(+0.7+0.8)μg m yr,占观察到的五年 PM(O)下降(O 增加)趋势的 10-26%(12-18%)。相对湿度降低(白天行星边界层高度增加)被确定为最具影响力的气象因素,解释了所有地区和季节中最大的气象驱动 PM(O)趋势的 55%(42%)。PM 浓度的气象驱动下降(O 浓度的增加)导致 PM 相关死亡率的总体下降(O 相关死亡率的增加),三个地区的趋势分别为-2.2-7.4(+0.5+0.9)千 yr,占 PM 相关死亡率(O 相关死亡率)总下降(增加)趋势的 10-26%(15-31%)。研究结果强调了气象在中国 PM 和 O 空气质量及其相关健康负担中的重要作用,这对中国的空气质量规划具有重要意义。特别是,应加大减排力度,以抵消气象条件对臭氧造成的不利影响。