Contributions of Traffic and Industrial Emission Reductions to the Air Quality Improvement after the Lockdown of Wuhan and Neighboring Cities Due to COVID-19

Dynamic harmonization of source-oriented and receptor models for source apportionment

Millions of premature mortalities are caused by the air pollution of fine particulate matter with aerodynamic diameters less than 2.5 μm (PM_2.5) globally per year. To effectively control the dominant emission sources and abate air pollution, source apportionment of PM_2.5 is normally conducted to quantify the contributions of various sources, but the results of different methods might be inconsistent. In this study, we dynamically harmonized the results from the two dominant source apportionment methods, the source-oriented and receptor models, by updating the emission inventories of primary PM_2.5 from the major sectors based on the Bayesian Inference. An adjoint model was developed to efficiently construct the source-receptor sensitivity matrix, which was the critical information for the updates, and depicted the response of measurements to the changes in the emissions of various sources in different regions. The harmonized method was applied to a measurement campaign in Beijing from January to February 2021. The results suggested a significant reduction of primary PM_2.5 emissions in Beijing. Compared with the baseline emission inventory of 2017, the primary PM_2.5 emissions from the local residential combustion and industry in Beijing had significantly declined by about 90 % during the investigated period of the year, and the traffic emission decreased by about 50 %. The proposed methods successfully identified the temporally dynamic changes in the emissions induced by the Spring Festival. The methods could be a promising pathway for the harmonization of source-oriented and receptor source apportionment models.

Ecological Study on Global Health Effects due to Source-Specific Ambient Fine Particulate Matter Exposure

Ambient air pollution of fine particulate matter with diameters less than 2.5 μm (PM2.5) is associated with millions of premature deaths per year, recognized as a leading global health concern. The dose-response relation between ambient PM2.5 exposure and mortality risk is the most fundamental information for assessments of the health effects of PM2.5. The existing dose-response relations were generally developed based on the assumption of equal contribution to toxicity from various sources. However, the sources of PM2.5 may significantly influence health effects. In this study, we conducted an ecological study to investigate the global long-term correlation between source-specific PM2.5 exposure and cause-specific mortality risk (SPECM) based on the regional aggregate data of the publically available official health databases from 528 regions worldwide with a total registered population of 3.2 billion. The results provided preliminary epidemiological evidence for differing chronic health effects across various sources. The relative mortality risks of lung cancer and circulatory diseases were closely correlated with the primary emissions from industrial and residential combustion sources. Chronic lower respiratory diseases were mostly associated with the mass concentration of particulate matter.