论文标题
部分可观测时空混沌系统的无模型预测
Coarse particulate matter air quality in East Asia: implications for fine particulate nitrate
论文作者
论文摘要
粗颗粒物（PM）是东亚的严重空气污染问题。对南部平原和首尔都市地区空气质量网络观测的分析表明，它主要是人为的，在2015 - 2019年期间已下降21％。这种人为粗糙的PM通常不包括在空气质量模型中，而是清除硝酸来抑制细颗粒的形成（PM2.5）硝酸盐，这是PM2.5污染的主要贡献者。在GEOS-CHEM模型中包括IT会降低模拟的PM2.5硝酸盐，以提高与观测的一致性。在2015 - 2019年间，人为粗糙的PM降低直接增加了夏季的PM2.5硝酸盐，抵消了其他排放控制的作用，而在冬季，它增加了PM2.5硝酸盐对氨和二氧化硫排放的敏感性。我们的工作意味着需要更强大的氨和氮氧化物发射控制，以提高PM2.5空气质量，因为粗pm继续降低。
Coarse particulate matter (PM) is a serious air pollution problem in East Asia. Analysis of air quality network observations in the North China Plain and the Seoul Metropolitan Area shows that it is mainly anthropogenic and has decreased by 21% over 2015-2019. This anthropogenic coarse PM is generally not included in air quality models but scavenges nitric acid to suppress the formation of fine particulate (PM2.5) nitrate, a major contributor to PM2.5 pollution. Including it in the GEOS-Chem model decreases simulated PM2.5 nitrate to improve agreement with observations. Decreasing anthropogenic coarse PM over 2015-2019 directly increases PM2.5 nitrate in summer, offsetting the effect of other emission controls, while in winter it increases the sensitivity of PM2.5 nitrate to ammonia and sulfur dioxide emissions. Our work implies the need for stronger ammonia and nitrogen oxides emission controls to improve PM2.5 air quality as coarse PM continues to decrease.
