Nonlinear and lagged meteorological effects on daily levels of ambient PM2.5 and O3: Evidence from 284 Chinese cities

Abstract

Numerous studies have linked the dispersion and deposition of atmospheric pollutants to meteorology. However, the lag structure of the effects lacks investigation. A two-stage analysis was used to assess the effects of meteorological factors on daily levels of particulate matter with an atmospheric diameter of less than 2.5 μg (PM2.5) and ozone (O3) in 284 major Chinese cities during 2015–2018. A quantile regression model combined with a distributed lag nonlinear model was first used to estimate the city-specific nonlinear and delayed effects of meteorology on air pollutants. Then, a multivariate meta-analysis was utilized to pool the city-specific effect estimates across China. In general, the meteorological effects were nonlinear. The wind speed, temperature, and rainfall were observed to be the primary meteorological factors influencing PM2.5 concentration, while temperature, relative humidity, and sunshine duration played crucial roles in influencing O3 concentration. Additionally, diverse meteorological lag pattern effects were also noted. For PM2.5, the effects of rainfall and wind were delayed and lasted for 2–4 d, while the effects of relative humidity, temperature, and sunshine duration peaked in real time and then quickly became negative or vanished after 1 d. For O3, the effects of relative humidity and sunshine duration were limited to 5 d, and rainfall and temperature only exerted significant impacts on the current day. This large-scale study thoroughly investigated the delayed and nonlinear association between meteorology and air pollution, and it presented important implications for the development of air pollution forecasts and control strategies from the meteorological perspective.