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This study comprehensively investigated the impact of dust storms (DSs) on downstream cities, by selecting representative DS events. In this paper, we discussed the characteristics of meteorological conditions, air pollutants, PM2.5 components, and their influence on sulfate formation mechanisms. During DSs, strong winds, reaching speeds of up to 10 m/s, led to significant increases in PM10 and PM2.5, with maximum concentrations of 2684.5 and 429 µg/m3, respectively. Primary gaseous pollutants experienced substantial reductions, with decline rates of 48.1, 34.9, 36.8, and 9.0 % for SO2, NO2, NH3, and CO, respectively. Despite a notable increase in PM2.5 concentrations, only 7.6 % of the total mass of PM2.5 was attributed to ionic and carbonaceous components, a much lower value than observed before the DSs (77.3 %). Concentrations of Fe, Ti, and Mn exhibited increases by factors of 6.5-14.1, 10.4-17.0, and 1.6-4.7, respectively. In contrast to the significant decrease of >76.2 % in nitrogen oxidation ratio (NOR), sulfur oxidation ratio (SOR) remained at a relatively high level, displaying a strong positive correlation with high concentrations of Fe, Mn, and Ti. Quantitative analysis revealed an average increase of 0.187 and 0.045 µg/m3 in sulfate from natural sources and heterogeneous generation, respectively. The heterogeneous reaction on mineral dust was closely linked to atmospheric humidity, radiation intensity, the form of metal existence, and concentrations of it. High concentrations of titanium dioxide and iron­manganese oxides in mineral dust promoted heterogeneous oxidation of SO2 through photocatalysis during the daytime and metal ion catalysis during the nighttime. This study establishes that the metal components in mineral dust promote heterogeneous sulfate formation, quantifies the yield of sulfate generated as a result, and provides possible mechanisms for heterogeneous sulfate formation.

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Fine particulate matter (PM2.5) chemical composition has strong and diverse impacts on the planetary environment, climate, and health. These effects are still not well understood due to limited surface observations and uncertainties in chemical model simulations. We developed a four-dimensional spatiotemporal deep forest (4D-STDF) model to estimate daily PM2.5 chemical composition at a spatial resolution of 1 km in China since 2000 by integrating measurements of PM2.5 species from a high-density observation network, satellite PM2.5 retrievals, atmospheric reanalyses, and model simulations. Cross-validation results illustrate the reliability of sulfate (SO42-), nitrate (NO3-), ammonium (NH4+), and chloride (Cl-) estimates, with high coefficients of determination (CV-R2) with ground-based observations of 0.74, 0.75, 0.71, and 0.66, and average root-mean-square errors (RMSE) of 6.0, 6.6, 4.3, and 2.3 µg/m3, respectively. The three components of secondary inorganic aerosols (SIAs) account for 21% (SO42-), 20% (NO3-), and 14% (NH4+) of the total PM2.5 mass in eastern China; we observed significant reductions in the mass of inorganic components by 40-43% between 2013 and 2020, slowing down since 2018. Comparatively, the ratio of SIA to PM2.5 increased by 7% across eastern China except in Beijing and nearby areas, accelerating in recent years. SO42- has been the dominant SIA component in eastern China, although it was surpassed by NO3- in some areas, e.g., Beijing-Tianjin-Hebei region since 2016. SIA, accounting for nearly half (∼46%) of the PM2.5 mass, drove the explosive formation of winter haze episodes in the North China Plain. A sharp decline in SIA concentrations and an increase in SIA-to-PM2.5 ratios during the COVID-19 lockdown were also revealed, reflecting the enhanced atmospheric oxidation capacity and formation of secondary particles.

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The chemical composition of particulate material plays an important role in the atmosphere, providing cloud and ice nuclei for storm development. This study aims to evaluate and infer the sources of ions, metals, and metalloids in the fine atmospheric particulate matter (PM2.5) from triple border Paraná, Santa Catarina (Brazil), and northeastern Argentina, which is among those with the highest hail incidence in the world. Among the ions, the concentrations presented the following sequence in decreasing order: [Formula: see text]> K+> [Formula: see text]> [Formula: see text]> Ca2+> Cl-> Na+> Mg2+. Regarding the metals and metalloid concentrations, the order was of S > Si > Al > Fe > P > Ti, Cr, Cu, and Zn > Br > Mn, and Ni. The main sources, supported by positive matrix factorization results, are soil and agricultural activities, as well as vehicular emissions due to the agricultural machinery and the displacement of residents. Besides, the influence of aerosols from biomass burning and industrial activities was observed, possibly come from long-distance transport. The composition of PM2.5 presents one or more elements considered present ice nuclei (IN) activity, such as Al, Mn, Cu, Co, Ni, and V (in form of oxides), corroborating with other studies, also, with high hail incidence. However, further studies are needed to verify the role of aerosol characteristics in the formation of IN and, consequently, hail.

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The COVID-19 pandemic has raised awareness about various environmental issues, including PM2.5 pollution. Here, PM2.5 pollution during the COVID-19 lockdown was traced and analyzed to clarify the sources and factors influencing PM2.5 in Guangzhou, with an emphasis on heavy pollution. The lockdown led to large reductions in industrial and traffic emissions, which significantly reduced PM2.5 concentrations in Guangzhou. Interestingly, the trend of PM2.5 concentrations was not consistent with traffic and industrial emissions, as minimum concentrations were observed in the fourth period (3/01-3/31, 22.45 µg/m3) of the lockdown. However, the concentrations of other gaseous pollutants, e.g., SO2, NO2 and CO, were correlated with industrial and traffic emissions, and the lowest values were noticed in the second period (1/24-2/03) of the lockdown. Meteorological correlation analysis revealed that the decreased PM2.5 concentrations during COVID-19 can be mainly attributed to decreased industrial and traffic emissions rather than meteorological conditions. When meteorological factors were included in the PM2.5 composition and backward trajectory analyses, we found that long-distance transportation and secondary pollution offset the reduction of primary emissions in the second and third stages of the pandemic. Notably, industrial PM2.5 emissions from western, southern and southeastern Guangzhou play an important role in the formation of heavy pollution events. Our results not only verify the importance of controlling traffic and industrial emissions, but also provide targets for further improvements in PM2.5 pollution.

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BACKGROUND: Fine particulate matter (PM2.5) is a complex mixture of fine particulates with large spatiotemporal heterogeneities in chemical compositions. While PM2.5 has been associated with gestational diabetes mellitus (GDM), little is known about the relationship between specific chemical components of PM2.5 and GDM. We examined the associations between GDM and pregnancy exposures to PM2.5 and its compositions, including sulfate (SO42-), ammonium (NH4+), nitrate (NO3-), organic matter (OM), black carbon (BC), mineral dust (DUST), and sea-salt (SS), and to identify critical windows of exposure. METHODS: We used data from the 2005-2015 Florida Vital Statistics Birth Records. A well-validated geoscience-derived model was used to estimate women's pregnancy exposures to PM2.5 and its compositions. Distributed lag models were used to examine the associations and to identify the critical windows of exposure. RESULTS: A total of 2,078,669 women were included. In single-pollutant models, after controlling for potential confounders, positive associations between PM2.5 and GDM were observed during the second trimester of pregnancy. We found positive associations between SO42-, NH4+, NO3-, OM and BC, with largest effect sizes observed in the 21-24 weeks of pregnancy. Negative associations were observed for DUST and SS. Consistent results for NH4+, OM, DUST and SS were observed in the multi-pollutant models. CONCLUSIONS: Exposures to PM2.5 and its compositions (mainly NH4+, OM) during the second trimester are positively associated with GDM, especially for exposures during the 21-24 weeks of pregnancy. Further studies are needed to confirm the findings and examine the underlying mechanisms.

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This study presents the distribution characteristics and possible sources of fine particulate matter (PM2.5) and its components, as well as policy-related pollution reduction in the Chinese cities of Jinan, Shijiazhuang (SJZ), Chengdu, Wuxi, Wuhan, and Harbin (HRB). PM2.5 samples were collected using mid-volume samplers during the autumn of 2017 in all six cities. The samples were analyzed to determine the ambient PM2.5 compositions, including the concentrations of water-soluble inorganic ions (WSIIs), carbonaceous aerosols, and elements concentrations. The chemical ratios of organic carbon to elemental carbon and nitrate to sulfate as well as the enrichment factors of elements were calculated to establish the possible sources of PM2.5 in all six cities. The highest PM2.5 concentration was 152 µg/m3 in SJZ, while the lowest concentration was 47 µg/m3 in HRB. During the sampling period in these six cities, the PM2.5 concentrations exceeded the World Health Organization recommended daily average air quality guidelines by 2.4-6.1 times, and WSIIs, carbonaceous aerosols, and elements accounted for 31.8%-61.6%, 9.8%-35.1%, and 0.9%-2.5% of the PM2.5, respectively. In 2013, the Chinese government formulated the Air Pollution Prevention and Control Action Plan (APPCAP) for controlling air pollution, and effective measures have been implemented since then. Compared with previous studies conducted during 2009-2013 before the implementation of the APPCAP, the concentrations of PM2.5 and most of its components decreased to varying degrees, and large changes in the chemical ratios of PM2.5 components were observed. These results indicate that PM2.5 sources vary among these six cities and that China has improved the ambient air quality in these cities through the implementation of air pollution control policies. The APPCAP have achieved considerable results in continuously reducing pollution concentrations, although the air pollution concentrations observed in this study remain high compared with those of other countries.

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There is limited understanding of adverse health effect associations with chemical constituents of fine particulate matter (PM2.5) as well as the underlying mechanisms. We outlined a workflow to assess metrics, beyond concentration, using household and personal PM2.5 filter samples collected in India as a proof of concept for future large-scale studies. Oxidative potential, chemical composition (polycyclic aromatic hydrocarbons and elements), and bioactivity (developmental exposures in zebrafish) were determined. Significant differences were observed in all metrics between personal and household PM2.5 samples. This work established methods to characterize multiple metrics of PM2.5 to ultimately support the identification of more health-relevant metrics than concentration.

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Epidemiological studies of wildfire PM2.5 constituents are hindered by the limited information on the population exposure to ambient PM2.5 constituents during high-pollution episodes from wildfires ("smoke waves"). The chemical composition of wildfire-related PM2.5 can be affected by different ecosystems. Current literature assessing the differences in PM2.5 pollution from wildfire smoke by ecosystems often analyzes air samples collected from the smoke near the center of an individual fire, but the results might not represent the exposure of the general public living away from the fire center but affected by the smoke of the fire. We assessed the population-based exposure to wildfire-related PM2.5 species by integrating monitor measurements on 29 PM2.5 species and previous findings on smoke waves during 2004-2009 in 51 Western US counties across six ecoregions. We found that across all ecoregions, smoke waves were associated with an increase in the fraction of organic carbon of total PM2.5 by 20 percentage points (95% confidence interval (CI): 17, 23), an increase in the fraction of elemental carbon by 0.99 percentage points (95% CI: 0.43, 1.6), and decreases in fractions of sulfate and crustal species. While the PM2.5 mixtures were dominated by the same source (wildfires), compositions in North American Deserts and the Great Plains during smoke waves were distinct. Besides expanding the knowledge of wildfire PM2.5, our study has implications beyond wildfires and could aid future population-based epidemiological research on PM2.5 mixtures by source and region.

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To reduce air pollution within a 300 km radius from Hangzhou (the capital city of Zhejiang Province in East China) for the 2016 G20 summit (9/4-9/5), the 14-day (8/24-9/6) stringent pollution control measures were implemented in Shanghai. Changes in atmospheric concentrations during the same 14-day period from 2014 to 2016 were examined at two Supersites, i.e., urban Pudong site (PD) and Dianshan Lake regional site (DSL). Up to 50% reductions were found for PM2.5, with 13.1% and 9.7% reductions for SO2 and NO2, respectively. No apparent improvements were found for 8-h average O3 concentrations. Large reductions were also found for SO42- (51.4%), NO3- (68.8%), and NH4+ (84.4%), on average. Elevated coefficient of divergence values (0.52-0.56) suggested that pollutant sources differed at the two sites. Biomass burning, resuspended dust, combustion, iron and steel industry, sea salt, secondary aerosol, and vehicle exhaust were identified at the DSL site by Positive Matrix Factorization (PMF). Secondary aerosol and vehicle exhaust accounted for 45.7% of PM2.5 mass, followed 11.2%-13.7% each by industry, resuspended dust, and coal and oil combustion.