Estimation and Spatiotemporal Analysis of NO 2 Pollution in East Asia During 2001–2016

• Published in: Journal of geophysical research. Atmospheres 2022-01, Vol.127 (2)
• Main Authors: Hu, Mingyun, Chen, Yiang, Yuan, Dehao, Yu, Rui, Lu, Xingcheng, Fung, Jimmy C. H., Chen, Wanying, Huang, Yeqi, Lau, Alexis K. H.
• Format: Article
• Language: English
• ISSN: 2169-897X; 2169-8996
• DOI: 10.1029/2021JD035129

Ambient nitrogen dioxide (NO 2 ) not only has adverse health effects on humans but also contributes to the production of two major secondary atmospheric pollutants, ozone (O 3 ) and fine particulate matter (PM 2.5 ). In this study, surface NO 2 concentrations in East Asia from 2001 to 2016 were estimated by combining an ensemble backpropagation neural network method, satellite NO 2 column data, and reanalysis data. The estimated monthly and annual mean NO 2 concentrations were well‐correlated with the observations, with R (correlation coefficient) values of 0.89 and 0.91, respectively. Our results indicate that the NO 2 concentrations in most areas of East Asia peaked during 2011–2013. The NO 2 concentrations in autumn and winter, especially in the eastern and northern parts of China, were much higher than those in summer. In terms of population NO 2 exposure, over 25 million South Korea residents (∼45% of the population) were exposed to NO 2 concentrations higher than the 2005 World Health Organization's annual standard (40 μg/m 3 , ∼22 ppbv at 25°C) in 2015. In contrast, the entire populations of some developing countries, such as Vietnam, Cambodia, Myanmar, the Philippines, and Lao PDR, were exposed to NO 2 concentrations less than 14 ppbv. Based on the estimation, NO 2 ‐related asthma cases in East Asia increased by 1.37% annually from 2001 to 2015, reaching 139,000 cases (95% confidence interval: 37,400–263,400) in 2015. NO x emission inventories vary from country to country in East Asia; thus, more targeted NO x emission‐control policies are urgently required. As one of the major atmospheric pollutants, NO 2 contributes to the formation of several secondary atmospheric pollutants and the development of respiratory diseases. Satellite NO 2 data and meteorological factors are commonly used to retrieve surface NO 2 concentrations. Several regression methods have been adopted to construct models to estimate NO 2 pollution concentrations; however, limitations such as low resolution and relatively large bias hinder the performance of these simulations. In this study, we applied a machine learning method to estimate surface NO 2 concentrations over East Asia, improving the estimation accuracy and resolution compared with previous models. The spatial distribution pattern revealed that NO 2 concentrations were relatively high in most territories in South Korea and the North China Plain. Based on the estimated NO 2 concentrations, population NO 2 exposure and