Identifying and quantifying the major sources of atmospheric particulate matter (PM) is essential for the development of pollution mitigation strategies to protect public health. However, urban PM is affected by local primary emissions, transport, and secondary formation; therefore, advanced methods are needed to elucidate the complex sources and transport patterns. Here, an improved source apportionment method was developed by incorporating the receptor model, Lagrangian simulation, and emissions inventories to quantify PM2.5 sources for an industrial city in China. PM2.5 data including ions, metals, organic carbon, and elemental carbon were obtained by analyzing 1 year of sampling results at urban and rural sites. This method identified coal combustion (30.64%), fugitive dust (13.25%), and vehicles (12.51%) as major primary sources. Secondary sources, including sulfate, nitrate, and secondary organic aerosols also contributed strongly (25.28%–30.76% in total) over urban and rural areas. Hebei Province was the major regional source contributor (43.05%–57.51%) except for fugitive dust, on which Inner Mongolia had a greater impact (43.51%). The megacities of Beijing and Tianjin exerted strong regional impacts on the secondary nitrate and secondary organic aerosols factors, contributing 11.32% and 15.65%, respectively. Pollution events were driven largely by secondary inorganic aerosols, highlighting the importance of reducing precursor emissions at the regional scale, particularly in the Beijing–Tianjin–Hebei region. Overall, our results demonstrate that this novel method offers good flexibility and efficiency for quantifying PM2.5 sources and regional contributions, and that it can be extended to other cities.

Firework/firecracker (FF) burning can significantly deteriorate air quality, whereas little is known about its influences on the elemental composition and associated health risks. Fine particles (PM2.5) and trace elements were characterized based on a multi-site campaign at Chifeng, China around 2016 Chinese Spring Festival (SF). Severe pollution levels average of 57.70 μg m−3 were observed during the SF with maximum to 471.00 μg m−3 shortly after the intensive FF activities. Largely enhanced PM2.5-bound metals were found in both urban and rural sites especially for K (8.27±5.36 μg m−3) and Al (2.36±1.41 μg m−3). Ba and Sr as the tracer of fireworks also increased more than 20-fold compared to non-SF period. Accordingly, FF burning factor identified via PMF model contributed significantly to the total elemental mass (71.34±24.94%) during the SF. Its major impacts on both crustal elements as Al, Ca, K and heavy metals as Cr, Cu and Pb were both identified. Elevated non-cancer risks (0.76 to children, 0.11 to adults) and cancer risks (3.96 × 10−6) were assessed during the SF, with As, Cd, Pb exerted the most adverse threats. The FF burning contributed the second largest share of the health threats after coal combustion, accounted for 28.35% and 12.64% of non-cancer risks for children and adults, respectively, and 10.03% of cancer risks, respectively. This study provided scientific evidences for stricter firework/firecracker regulations to protect public health.

Trace metals in atmospheric particulate matter (PM) are a serious threat to public health. Although pollution from toxic metals has been investigated in many Chinese cities, the spatial and temporal patterns in PM2.5 remain largely unknown. Long-term PM2.5 field sampling in 11 cities, combined with a systemic literature survey covering 51 cities, provides the first comprehensive database of 21 PM2.5-bound trace metals in China. Our results revealed that PM2.5 elemental compositions varied greatly, with generally higher levels in North China, especially for crustal elements. Pollution with Cr, As, and Cd was most serious, with 61, 38, and 16 sites, respectively, surpassing national standards, including some in rural areas. Local emissions, particularly from metallurgical industries, were the dominant factors driving the distribution in polluted cities such as Hengyang, Yuncheng, and Baiyin, which are mainly in North and Central China. Elevated As, Cd, and Cr levels in Yunnan, Guizhou Province within Southwest China were attributed to the high metal content of local coal. Diverse temporal trends of various elements that differed among regions indicated the complexity of emission patterns across the country. The results demonstrated high non-carcinogenic risks for those exposed to trace metals, especially for children and residents of heavily cities highly polluted with As, Pb, or Mn. The estimated carcinogenic risks ranged from 6.61 × 10−6 to 1.92 × 10−4 throughout China, with As being the highest priority element for control, followed by Cr and Cd. Regional diversity in major toxic metals was also revealed, highlighting the need for regional mitigation policies to protect vulnerable populations.

In order to evaluate the volatile organic compounds (VOCs) pollution characteristics in Chengdu and to identify their sources, ambient air sample collection and measurement were conducted at 28 sampling sites covering all districts/counties of Chengdu from May 2016 to January 2017. Meanwhile, a county-level anthropogenic speciated VOCs emission inventory was established by “bottom-up” method for 2016. Then, a comparison was made between the VOCs emissions, spatial variations, and source structures derived from the measurement and emission inventory. Ambient measurements showed that the annual average mixing ratios of VOCs in Chengdu were 57.54 ppbv (12.36 to 456.04 ppbv), of which mainly dominated by alkanes (38.8%) and OVOCs (22.0%). The ambient VOCs in Chengdu have distinct spatiotemporal characteristics, with a high concentration in January at the middle-northern part of the city and a low concentration in September at the southwestern part. The spatial distribution of VOCs estimated by the emission inventory was in good agreement with ambient measurements. Comparison of individual VOCs emissions indicated that the emissions of non-methane hydrocarbon species agreed within ±100% between the two methods. Both positive matrix factorization (PMF) model results and emission inventory showed that vehicle emissions were the major contributor of anthropogenic VOCs in Chengdu (31% and 37%), followed by solvent utilization (26% and 27%) and industrial processes (23% and 30%). The large discrepancies were found between the relative contribution of combustion sources, and the PMF resolved more contributions (20%) than the emission inventory (6%). Overall, this study demonstrates that measurement results and emission inventory were in a good agreement. However, to improve the reliability of the emission inventory, we suggest significant revision on source profiles of oxygenated volatile organic compounds (OVOCs) and halocarbons, as well as more detailed investigation should be made in terms of energy consumption in household.

This paper compiled a new speciated NMVOCs emission inventory for the industrial sources at the county-level by using a bottom-up approach in 2016, as well as estimated the ozone formation potential (OFP) and investigated its spatial characteristics in China. Results indicated that the total NMVOCs emissions from industrial sources estimated as 21.04 Tg in 2016. The five major source categories including “production of VOCs”, “storage and transportation”, “industrial processes using VOCs as raw material”, “processes using VOCs-containing products”, and “industrial fossil fuel combustion processes” generated 1.92 Tg, 0.94 Tg, 6.54 Tg, 10.04 Tg, and 1.60 Tg VOCs, respectively, in 2016. According to our estimates, aromatics were the largest contributor of industrial NMVOCs emissions in 2016, accounting for 36% of total NMVOCs, followed by Alkanes (29%), OVOCs (22%), Alkenes (7%), Halocarbons (4%), and Alkynes (2%). Styrene, m/p-xylene, ethylbenzene, toluene, and ethyl acetate were the top five VOC species from industrial sources in terms of abundance in 2016. Aromatics have a high potential for ozone formation, and accounted for 70% of total OFP, followed by Alkenes (14%), Alkanes (10%), and OVOCs (6%). Styrene, p-xylene, toluene, ethylbenzene, 1,3-butadiene were the five species that had the largest potential to form ozone, and plastic industry, coke industry, household appliances industry, and architectural decoration were the key contributing sectors. The emissions displayed distinct spatial characteristics, with significantly higher emissions and OFPs in coastal regions than in other inland areas of China.