The Interannual Variation of Transboundary Contributions from Chinese Emissions of PM2.5 to South Korea

Abstract

In recent years, several studies pointed out that anthropogenic emission sources in China which significantly contribute to the PM 2.5 mass burden was an important cause of particulate pollution in South Korea. However, most studies generally focused upon a single pollution event. It is rare to see comprehensive research that captures those features prone to interannual variations concerning the transboundary pollutant contribution in South Korea using a unified method. In this paper, we establish the emission inventories covering East Asia in 2010, 2015, and 2017, and then conduct the source apportionment by applying a coupled regional air quality model called the Integrated Source Apportionment Module (ISAM). Comparison of simulated and observed PM 2.5 mass concentration at 165 CNEMC (China National Environmental Monitoring Center) sites suggests that the PM 2.5 concentrations are well represented by the modeling system. The model is used to quantitatively investigate the contribution from emission sources in China to PM 2.5 concentrations over South Korea and those features found to be prone to interannual variations are then discussed. The results show that the average annual contribution of PM 2.5 has dropped significantly from 28.0% in 2010 to 15.7% in 2017, which strongly suggests that China has achieved remarkable results in the treatment of atmospheric particulates.

Comment on acp-2022-368

“…However, the long-range transport among those city clusters has not been well studied. In fact, PM2.5 pollution is not restricted to surrounding influence, which requires joint controls with multi-regional policy implementation across the whole country (Zhang et al, 2017;Han and Zhang, 2021). Therefore, quantification of both inner regional and long-range transport on 60 PM2.5 pollution across China is prerequisite for designing an effective multiple-regional joint control strategy.…”

Multi-scale three-dimensional variational data assimilation for high-resolution aerosol observations: Methodology and application

“…Although significant progress in multi-scale DA methods has been made in the fields of meteorological and oceanographic DA, its application in aerosol data assimilation is still not explored. The aerosol distribution is inherently multi-spatial and small-scale by nature (Xu et al, 2005) due to complex factors such as multi-scale weather systems (Zhang, 2005;Zhu et al, 2013;Liu et al, 2015;Huang et al, 2017), localized emission sources, and small-scale photochemical processes Chen S Y et al, 2017, Han andZhang, 2021). On the other hand, the horizontal spatial resolution of the monitoring network has reached up to 10 km in a number of cities and surrounding areas in eastern China and thus could provide observational information on multi scales.…”