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In Xi'an, a city that frequently experiences serious PM pollution in northern China, 1476 PM10 and 1464 PM2.5 valid daily filter samples were collected at six sites from December 2014 to November 2015 and analyzed for 29 species. The annual mean PM10 and PM2.5 concentrations were 149.4 ± 93.1, 108.0 ± 70.9 μg/m3, respectively. Organic carbon (OC) is the predominant PM2.5 component while crustal material predominated in PM10. Sulfate concentrations, which was the largest component in Xi'an PM in previous studies, were lower than nitrate. Winter sulfate, OC, and elemental carbon (EC) have decreased since 2003, while nitrate remained constant in recent years and the ratio of NO3−/SO42− increased from 0.4 in 2006 to 1.3 in 2014. This result suggests that the motor vehicle contribution to PM has increased relative to coal-fired power plant emissions over the past decade. The mass fractions of crustal material, sulfate, and EC in PM2.5 decreased as the PM2.5 concentrations increased from “clean” days (

Potential health benefits from improved ambient air quality during the COVID-19 shutdown have been recently reported and discussed. Despite the shutdown measures being in place, northern China still suffered severe haze episodes (HE) that are not yet fully understood, particularly how the source emissions changed. Thus, the meteorological conditions and source emissions in processing five HEs occurred in Beijing-Tianjin-Hebei area were investigated by analyzing a comprehensive real-time measurement dataset including air quality data, particle physics, optical properties, chemistry, aerosol lidar remote sensing, and meteorology. Three HEs recorded before the shutdown began were related to accumulated primary pollutants and secondary aerosol formation under unfavorable dispersion conditions. The common "business as usual" emissions from local primary sources in this highly polluted area exceeded the wintertime atmospheric diffusive capacity to disperse them. Thus, an intensive haze formed under these adverse meteorological conditions such as in the first HE, with coal combustion to be the predominant source. Positive responses to the shutdown measures were demonstrated by reduced contributions from traffic and dust during the final two HEs that overlapped the Spring and Lantern Festivals, respectively. Local meteorological dispersion during the Spring Festival was the poorest among the five HEs. Increased residential burning plus fireworks emissions contributed to the elevated PM2.5 with the potential of enhancing the HEs. Our results highlight that reductions from shutdown measures alone do not prevent the occurrence of HEs. To further reduce air pollution and thus improve public health, abatement strategies with an emphasis on residential burning are needed.

In recent years, China has experienced severe and persistent air pollution associated with rapid urbanization and climate change. Three years' time series (January 2014 to December 2016) concentrations data of air pollutants including particulate matter (PM2.5 and PM10) and gaseous pollutants (SO2, NO2, CO, and O3) from over 1300 national air quality monitoring sites were studied to understand the severity of China's air pollution. In 2014 (2015, 2016), annual population-weighted-average (PWA) values in China were 65.8 (55.0, 50.7) μg m−3 for PM2.5, 107.8 (91.1, 85.7) μg m−3 for PM10, 54.8 (56.2, 57.2) μg m−3 for O3_8 h, 39.6 (33.3, 33.4) μg m−3 for NO2, 34.1 (26, 21.9) μg m−3 for SO2, 1.2 (1.1, 1.1) mg m−3 for CO, and 0.60 (0.59, 0.58) for PM2.5/PM10, respectively. In 2014 (2015, 2016), 7% (14%, 19%), 17% (27%, 34%), 51% (67%, 70%) and 88% (97%, 98%) of the population in China lived in areas that meet the level of annual PM2.5, PM10, NO2, and SO2 standard metrics from Chinese Ambient Air Quality Standards-Grade II. The annual PWA concentrations of PM2.5, PM10, O3_8 h, NO2, SO2, CO in the Northern China are about 40.4%, 58.9%, 5.9%, 24.6%, 96.7%, and 38.1% higher than those in Southern China, respectively. Though the air quality has been improving recent years, PM2.5 pollution in wintertime is worsening, especially in the Northern China. The complex air pollution caused by PM and O3 (the third frequent major pollutant) is an emerging problem that threatens the public health, especially in Chinese mega-city clusters. NOx controls were more beneficial than SO2 controls for improvement of annual PM air quality in the northern China, central, and southwest regions. Future epidemiologic studies are urgently required to estimate the health impacts associated with multi-pollutants exposure, and revise more scientific air quality index standards.

In China, over 1.3 billion people have high health risks associated with exposure to ambient fine particulate matter (PM2.5) that exceeds the World Health Organization (WHO) Air Quality Guidelines (AQG). The PM2.5 mass concentrations from 1382 national air quality monitoring stations in 367 cities, between January 2014 and December 2016, were analyzed to estimate the health burden attributable to ambient PM2.5 across China. The integrated exposure-response model was applied to estimate the relative risks of disease-specific mortality. Disease-specific mortality baselines in province-level administrative units were adjusted by the national mortality baseline to better reveal the spatial inequality of the health burden associated with PM2.5. Our study suggested that PM2.5 in 2015 contributed as much as 40.3% to total stroke deaths, 33.1% to acute lower respiratory infection (ALRI

Samples of ambient PM2.5 were collected in the Qingdao harbor area between 21 March and May 25, 2016, and analyzed to investigate the compositions and sources of PM2.5 and to assess source-specific selected toxic element health risks to workers via a combination of positive matrix factorization (PMF) and health risk (HR) assessment models. The mean concentration of PM2.5 in harbor area was 48 μg m−3 with organic matter (OM) dominating its mass. Zn and V concentrations were significantly higher than the other selected toxic elements. The hazard index (HI) and cancer risk (Ri) of all selected toxic elements were lower than the United States Environmental Protection Agency (USEPA) limits. There were no non-cancer and cancer risks for workers in harbor area. The contributions from industrial emissions (IE), ship emissions (SE), vehicle emissions (VE), and crustal dust and coal combustion (CDCC) to selected toxic elements were 39.0%, 12.8%, 24.0%, and 23.0%, respectively. The HI values of selected toxic elements from IE, CDCC, SE, and VE were 1.85 × 10−1, 7.08 × 10−2, 6.36 × 10−2, and 3.37 × 10−2, respectively; these are lower than the USEPA limits. The total cancer risk (Rt) value from selected toxic elements in CDCC was 2.04 × 10−7, followed by IE (6.40 × 10−8), SE (2.26 × 10−8), and VE (2.18 × 10−8). CDCC and IE were the likely sources of cancer risk in harbor area. The Bo Sea and coast were identified as the likely source areas for health risks from IE via potential source contribution function (PSCF) analysis based on the results of PMF-HR modelling. Although the source-specific health risks were below the recommended limit values, this work illustrates how toxic species in PM2.5 health risks can be associated with sources such that control measures could be undertaken if the risks warranted it.

The chemical species in PM2.5 and air pollutant concentration data with 1-hr resolution were monitored synchronously between 15 November 2018 and 20 January 2019 in Linfen, China, which were analysed for multiple temporal patterns, and PM2.5 source apportionment using positive matrix factorisation (PMF) modelling coupled with online chemical species data was conducted to obtain the apportionment results of distinct temporal patterns. The mean concentration of PM2.5 was 124 μg/m3 during the heating period, and NO3− and organic carbon (OC) were the dominant species. The concentrations and percentages of NO3−, SO42−, and OC increased notably during the growth periods of haze events, thereby indicating secondary particle formation. Six factors were identified by the PMF model during the heating period, including vehicular emissions (VE: 26.5%), secondary nitrate (SN: 16.5%), coal combustion and industrial emissions (CC&IE: 25.7%), secondary sulfate and secondary organic carbon (SS&SOC: 24.4%), biomass burning (BB: 1.0%), and crustal dust (CD: 5.9%). The primary sources of PM2.5 on clean days were CD (33.3%), VE (23.1%), and SS&SOC (20.6%), while they were CC&IE (32.9%) and SS&SOC (28.3%) during the haze events. The contributions of secondary sources and CC&IE increased rapidly during the growth periods of haze events, while that of CD increased during the dissipation period. Diurnal variations in the contribution of secondary sources were mainly related to the accumulation and transformation of corresponding gaseous precursors. In comparison, contributions of CC&IE and VE varied as a function of the domestic heating load and peak levels occurred during the morning and evening rush hours. High contributions of major sources (CC&IE and SS&SOC) during haze events originated mainly from the north and south, while high contribution of a major source (CD) on clean days was from the northwest.