An intensive sampling of PM_2.5 was conducted at a rural site (Gucheng) in the North China Plain from 22 October to 23 November 2016. A total of 25 elements (Al, Na, Cl, Mg, P, S, K, Ca, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Se, Br, Sr, Cd, Ba, Pb, and Sb) from PM_2.5 filter samples collected daily were measured using a wavelength dispersive X-ray fluorescence spectrometer. Cl, S, and K were the most abundant elements, with average concentrations of 2077.66 ng m⁻³ (range 118.88–4638.96 ng m⁻³), 1748.78 ng m⁻³ (range 276.67–4335.59 ng m⁻³), and 1287.07 ng m⁻³ (range 254.90–2748.63 ng m⁻³), respectively. Among noncrustal trace metal elements, the concentration of Zn was the highest, with an average of 397.74 ng m⁻³ (range 36.45–1602.96 ng m⁻³), followed by Sb and Pb, on average, of 299.20 ng m⁻³ and 184.52 ng m⁻³, respectively. The morphologies of PM_2.5 samples were observed using scanning electron microscopy. The shape of the particles was predominantly spherical, chain-like, and irregular. Positive matrix factorization analysis revealed that soil dust, following by industry, secondary formation, vehicle emissions, biomass and waste burning, and coal combustion, were the main sources of PM_2.5. The results of cluster, potential source contribution function, and concentration weighted trajectory analyses suggested that local emissions from Hebei Province, as well as regional transport from Beijing, Tianjin, Shandong, and Shanxi Province, and long-range transport from Inner Mongolia, were the main contributors to PM_2.5 pollution.

For many years, Beijing has suffered from severe air pollution. At present, fine particulate matter (PM_2.5) pollution in the winter and ozone (O₃) pollution in the summer constitute serious environmental problems. In this study, the combination of a comprehensive air quality model with particulate matter source apportionment technology (CAMx-PAST) and monitoring data was used for the high-spatial resolution source apportionment of secondary inorganic components (SNA: SO₄²⁻, NO₃⁻, and NH₄⁺) in PM_2.5; their corresponding precursor gases (SO₂, NO₂, and NH₃); and O₃ in the winter and summer over Beijing. Emissions from residents, industry, traffic, agriculture, and power accounted for 54%, 25%, 14%, 5%, and 2% of PM_2.5 in the winter, respectively. In the summer, the emissions from industry, traffic, residents, agriculture, and power accounted for 42%, 24%, 20%, 10%, and 4% of PM_2.5, respectively. The monthly transport ratio of PM_2.5 was 27% and 46% in the winter and summer, respectively. The regional transport of residential and industrial emissions accounted for the highest proportion of PM_2.5. The regional transport of emissions had a significant effect on the SO₄²⁻ and NO₃⁻ concentrations, whereas SO₂ and NO₂ pollution were mainly affected by local emissions, and NH₄⁺ and NH₃ were mainly attributed to agricultural emissions. Industrial and traffic sources were two major emission sectors that contributed to O₃ pollution in Beijing. The monthly transport ratios of O₃ were 31% and 65% in the winter and summer, respectively. The high-spatial resolution regional source apportionment results showed that emissions from Langfang, Baoding, and Tangshan had the greatest impact on Beijing’s air pollution. This work’s methods and results will provide scientific guidance to support the government in its decision-making processes to manage the PM_2.5 and O₃ pollution issues.

With the implementation of air pollution control measures, the concentration of air pollutants in the North China Plain has exhibited a downward trend, but severe fine particulate matter (PM_2.5) pollution remains. PM_2.5 is harmful to human health, and the exploration of its source characteristics and potential hazards has become the key to mitigating PM_2.5 pollution. In this study, PM_2.5 samples were collected in Beijing and Gucheng during the summer of 2019. PM_2.5 components, its oxidative potential (OP), and health risks were characterized. The average PM_2.5 concentrations in Beijing and Gucheng during the sampling period were 34.0 ± 6.1 μg/m³ and 37.1 ± 6.9 μg/m³, respectively. The principal component analysis (PCA) results indicated that the main sources of PM_2.5 in Beijing were vehicle exhaust and secondary components and that the main sources in Gucheng were industrial emissions, dust and biomass combustion. The OP values were 91.6 ± 42.1 and 82.2 ± 47.1 pmol/(min·m³), respectively, at these two sites. The correlation between the chemical components and the OP values varied with the PM_2.5 sources at these two locations. The health risk assessment results demonstrated that Cr and As were potentially carcinogenic to all populations at both sites, and Cd posed a potential carcinogenic risk for adults in Gucheng. Regional cooperation regarding air pollution control must be strengthened to further reduce PM_2.5 pollution and its adverse health effects.

The Beijing-Tianjin-Hebei (BTH) region experienced heavy air pollution in December 2015, which provided a good opportunity to explore the aerosol-radiation interaction (ARI) effects of different particulate matter (PM) components (sulfate, nitrate, and black carbon (BC)). In this study, five tests were conducted by the Weather Research and Forecasting—Chemistry (WRF-Chem) model. The tests included scenario 1 simulation with ARI turned on, scenario 2 simulation with ARI turned off, scenario3 simulation without NO_x/NO₃⁻ emissions and with ARI turned on, scenario 4 simulation without SO₂/SO₄²⁻ emissions and with ARI turned on, and scenario 5 simulation without BC emissions and with ARI turned on. The ARI decreased the downward shortwave radiation (SWDOWN) and the temperature at 2 m (T2), reduced the planetary boundary layer (PBL) height (PBLH), and increased the relative humidity (RH) at 2 m in the region. These factors also contribute to pollution accumulation. The results revealed that BC aerosols have a stronger effect on the reduction in SWDOWN than sulfate (SO₄²⁻) and nitrate (NO₃⁻). BC aerosols produce both cooling and heating effects, while SO₄²⁻ aerosols produce only cooling effects. The PBL decreased and RH2 increased due to the aerosol feedback effect of sulfate, nitrate, and BC. The ARI effect on meteorological factors during the nonheavy pollution period was much smaller than that during the pollution period.