Source apportionment of PM2.5 across China using LOTOS-EUROS. (September 2017)

• Record Type: Journal Article
• Authors: Timmermans, R.; Kranenburg, R.; Manders, A.; Hendriks, C.; Segers, A.; Dammers, E.; Zhang, Q.; Wang, L.; Liu, Z.; Zeng, L.; Denier van der Gon, H.; Schaap, M.
• Is Part Of: Atmospheric environment. Volume 164(2017)
• Page Start: 370
• Page End: 386
• Publication Date: 2017-09
• Subjects: PM2.5 -- Beijing -- Shanghai -- Chemistry transport model -- Model evaluation; Air -- Pollution -- Periodicals; Air -- Pollution -- Meteorological aspects -- Periodicals; 551.51
• DOI: 10.1016/j.atmosenv.2017.06.003
• Languages: English
• ISSNs: 1352-2310

Abstract

Abstract: China's population is exposed to high levels of particulate matter (PM) due to its strong economic growth and associated urbanization and industrialization. To support policy makers to develop cost effective mitigation strategies it is of crucial importance to understand the emission sources as well as formation routes responsible for high pollution levels. In this study we applied the LOTOS-EUROS model with its module to track the contributions of predefined source sectors to China for the year 2013 using the MEIC emission inventory. It is the first application of the model system to a region outside Europe. The source attribution was aimed to provide insight in the sector and area of origin of PM2.5 for the cities of Beijing and Shanghai. The source attribution shows that on average about half of the PM2.5 pollution in both cities originates from the municipality itself. About a quarter of the PM2.5 comes from the neighbouring provinces, whereas the remaining quarter is attributed to long range transport from anthropogenic and natural components. Residential combustion, transport, and industry are identified as the main sources with comparable contributions allocated to these sectors. The importance of the sectors varies throughout the year and differs slightly between the cities. During winter, urban contributions from residential combustion are dominant, whereas industrial and traffic contributions with a larger share of regional transport are more important during summer. The evaluation of the model results against satellite and in-situ observations shows the ability of the LOTOS-EUROS model to capture many features of the variability in particulate matter and its precursors in China. The model shows a systematic underestimation of particulate matter concentrations, especially in winter. This illustrates that modelling particulate matter remains challenging as it comes to components like secondary organic aerosol and suspended dust as well as emissions and formation of PM during winter time haze situations. All in all, the LOTOS-EUROS system proves to be a powerful tool for policy support applications outside Europe as the intermediate complexity of the model allows the assessment of the area and sector of origin over decadal time periods. Highlights: The regional LOTOS-EUROS model has been successfully applied to China. Modelled particulate matter concentrations agree well with observations. About half of modelled PM2.5 in Beijing and Shanghai derives from the city itself. The main source sectors are residential combustion, transport and industry.