Characteristics of PM2.5 Chemical Compositions and Their Effect on Atmospheric Visibility in Urban Beijing, China during the Heating Season

Health risk assessment of PM2.5 heavy metals in county units of northern China based on Monte Carlo simulation and APCS-MLR

The key areas of China's urbanization process have gradually shifted from urban areas to county-level units. Correspondingly, air pollution in county towns may be heavier than in urban areas, which has led to a lack of understanding of the pollution situation in such areas. In view of this, 236 PM_2.5 filter samples were collected in Pingyao, north of the Fen-Wei Plain, one of the most polluted areas in China. Monte Carlo simulation was used to solve the serious uncertainties of traditional HRA, and the coupling technology of absolute principal component score-multiple linear regression (APCS-MLR) and health risk assessment (HRA) is used to quantitatively analyze the health risks of pollution sources. The results showed that PM_2.5 concentration was highest in autumn, 3.73 times the 24 h guideline recommended by the World Health Organization (WHO). Children were more susceptible to heavy metals in the county-level unit, with high hazard quotient (HQ) values of Pb being the dominant factor leading to an increased non-carcinogenic risk. A significant carcinogenic risk was observed for all groups in autumn in Pingyao, with exposure to Ni in the outdoor environment being the main cause. Vehicle emissions and coal combustion were identified as two major sources of health threats. In short, China's county-level population, about one-tenth of the world's population, faces far more health risks than expected.

Inhalation Bioaccessibility and Risk Assessment of Metals in PM2.5 Based on a Multiple-Path Particle Dosimetry Model in the Smelting District of Northeast China

PM2.5 can deposit and partially dissolve in the pulmonary region. In order to be consistent with the reality of the pulmonary region and avoid overestimating the inhalation human health risk, the bioaccessibility of PM2.5 heavy metals and the deposition fraction (DF) urgently needs to be considered. This paper simulates the bioaccessibility of PM2.5 heavy metals in acidic intracellular and neutral extracellular deposition environments by simulating lung fluid. The multipath particle dosimetry model was used to simulate DF of PM2.5. According to the exposure assessment method of the U.S. Environmental Protection Agency, the inhalation exposure dose threshold was calculated, and the human health risk with different inhalation exposure doses was compared. The bioaccessibility of heavy metals is 12.1−36.2%. The total DF of PM2.5 in adults was higher than that in children, and children were higher than adults in the pulmonary region, and gradually decreased with age. The inhalation exposure dose threshold is 0.04−14.2 mg·kg−1·day−1 for the non-carcinogenic exposure dose and 0.007−0.043 mg·kg−1·day−1 for the carcinogenic exposure dose. Cd and Pb in PM2.5 in the study area have a non-carcinogenic risk to human health (hazard index < 1), and Cd has no or a potential carcinogenic risk to human health. A revised inhalation health risk assessment may avoid overestimation.

Current challenges of improving visibility due to increasing nitrate fraction in PM2.5 during the haze days in Beijing, China

The annual mean PM_2.5 mass concentration has decreased because of the stringent emission controls implemented in Beijing, China in recent years, whereas the nitrate NO₃^- mass fraction in PM_2.5 increases gradually. Low-visibility events occur frequently even though PM_2.5 pollution has been mitigated significantly, with the daily mean PM_2.5 mass concentration mostly less than 75 μg/m³. In this study, the non-linear relationship was analyzed between atmospheric visibility and PM_2.5 based on chemical composition from a two-year field observation. Our results showed that NO₃^- became the main constituent of PM_2.5, especially during the haze pollution episodes. A localized parameterization scheme was proposed between the atmospheric extinction coefficient (σ_ext) and major chemical constituents of PM_2.5 by multiple linear regression (MLR). The contribution of NO₃^- to σ_ext increased with increasing air pollution, and NO₃^- became the most important contributor for PM_2.5 above 75 μg/m³. The visibility decreased with increasing NO₃^- mass fraction for the same PM_2.5 mass concentration when PM_2.5 was above 20 μg/m³. The hygroscopicity of PM_2.5 increased with increasing mass fraction of hygroscopic NO₃^-. These results stressed the importance of reducing particulate NO₃^- and its precursors (for instance, NH₃) through effective emission control measures as well as the tightening of PM_2.5 standards to further improve air quality and visibility in Beijing.

Monitoring Rainwater Properties and Outdoor Particulate Matter in a Former Steel Manufacturing City in Romania

Wet deposition is influencing air quality because air pollutants are washed away from the surrounding air. Consequently, particulate matter and associated compounds are transported in the rainwater and enter into soil, surface waters, and groundwater. Nonpoint sources of heavy metals from stormwater runoff have increased in urban areas due to industrialization and the increasing impervious surfaces. In this work, we present an assessment of the rainwater composition regarding the nutrients and other physicochemical characteristics measured in three locations selected in Targoviste city, Romania, a city that had a specialized steel factory and important metallurgical facilities. The rainwater was collected using three PALMEX rain samplers and then was transferred to high-density polyethylene bottles and analyzed using ICP-MS. PM2.5 concentrations were also monitored continuously using optical monitors calibrated using a gravimetric sampler. A detailed analysis of the heavy metals content in rainwater and PM was presented for the pollution episodes occurring in October and November 2019. Backward trajectories were computed using the HYSPLIT model for these periods. The results showed that the PM2.5 ranged from 11.1 to 24.1 μg/m3 in 2019, while the heavy metals in collected rainwater were (µg L−1): 0.25 (Cd) − CV = 26.5%, 0.10 (Co) − CV = 58.1%, 1.77 (Cr) − CV = 24.3%, 377.37 (Ni) − CV = 27.9%, 0.67 (Pb) − CV = 74.3%, and 846.5 (Zn) − CV = 20.6%. Overall, Ni, Pb, Cr, and V had significant correlations between the concentrations from rainwater and PM. Negative associations were found between precipitation events and heavy metals both from rainwater and PM, but only a few showed statistical significance. However, this could explain the “washing” effect of the rain on the heavy metals from PM2.5. The potential sources of nitrogen in the rainwater collected in Targoviste could be from burning fossil fuels and the soils, including both biological processes and fertilization resulting from the intensive agriculture in the piedmont plain in which the city is located. Based on the results, rainwater monitoring can constitute a reliable method for air quality characterization. Additional research is required to better understand seasonality and sources of heterogeneity regarding the associations between PM and rainwater composition.

Wintertime chemical characteristics of aerosol and their role in light extinction during clear and polluted days in rural Indo Gangetic plain

This paper reports the chemical and light extinction characteristics of fine aerosol (PM_2.5) during the winter period (2017-18) at Lumbini, Nepal, a rural site on the Indo Gangetic Plains. A modified IMPROVE algorithm was employed to reconstruct light extinction by chemical constituents of aerosol. The fine aerosol levels impacted visibility adversely during daytime, but during nighttime visibility was controlled by fog droplets rather than by aerosols. The PM_2.5 chemical constituents showed varying characteristics during clear and polluted days. The average NO₃^-/SO₄^2- concentration ratio was 0.57 during clear and 1.36 and polluted days, signifying a change in secondary inorganics and formation processes mainly due to decreasing photochemical production and due to increased partitioning of nitrate particles at a lower temperature. The increased secondary organics contribution and the higher OM/OC ratio (2.2) during polluted days showed the vital role of aqueous processing and biomass burning emissions in determining the concentration of organics. Total light extinction was 2.3 times higher on polluted days compared to clear days, while the PM_2.5 mass concentration was 1.5 times higher. This variation in mass and extinction order signifies that various chemical components in fine particles have a more considerable impact on light extinction. On clear days we found that carbonaceous particles (OM and EC) made a major contribution to light extinction. In contrast, the extinction contribution by secondary inorganic (especially NH₄NO₃) increased significantly during polluted days, with hygroscopic growth and enhanced scattering efficiency at higher RH conditions playing a major role. The comparison between clear and polluted days altogether suggests that regulating the nitrate sources can help significantly in improving the visibility levels and restrict fog haze development during wintertime in rural IGP.

Seasonal variation in health impacts associated with visibility in Beijing, China

Visibility has been continuously and stably observed for more than half a century, while particulate matter with an aerodynamic diameter ≤ 2.5 μm (PM_2.5) was not introduced to the national monitoring system in China until 2013. It is a scientific issue as to whether visibility can be used as an alternative to assess the health risks of air pollution in periods and areas without pollutant monitoring data. A generalized additive model (GAM) was adopted to estimate the impacts of seasonal changes in visibility on mortality in Beijing, China. Moreover, we estimated the contributions of particulate matter in the health effects of visibility by adjusting for dry extinction coefficient (β_dryext) and PM_2.5 in the model, respectively. We found that the acute health impacts of visibility varied by season, with the highest risks in winter. For respiratory mortality, the effect estimates per 1 km decrease in visibility were 0.40% (95% CI: 0.17-0.62%) in spring, 0.10% (95% CI: -0.14-0.34%) in summer, 0.27% (95% CI: 0.09-0.45%) in autumn, and 0.62% (95% CI: 0.38-0.85%) in winter. For cardiovascular mortality, the effect estimates per 1 km decrease in visibility were 0.20% (95% CI: 0.08-0.31%) in spring, 0.16% (95% CI: 0.04-0.27%) in summer, 0.25% (95% CI: 0.13-0.37%) in autumn, and 0.24% (95% CI: 0.13-0.35%) in winter. The seasonal pattern of health impacts related to visibility reflected the seasonal variations in the characteristics of air pollution emission sources and meteorological conditions that are unfavorable for pollutant dispersion. Particulate matter, particularly PM_2.5, made significant contributions to the health impacts of visibility. The results indicated that controlling pollutant emissions in winter would be of significant importance to improve air quality and mitigate the health hazard of air pollution in Beijing. Our study also provides further evidence on the feasibility of using visibility to assess the health impacts of particulate matter pollution.

Spatiotemporal variations and influencing factors of PM2.5 concentrations in Beijing, China

Fine particulate matter (PM_2.5) pollution has become a worldwide environmental concern because of its adverse impacts on human health. This study aimed to explore the spatiotemporal variations and influencing factors of PM_2.5 concentrations in Beijing during the 2013-2018 period, and further analyzed the impacts of environmental protection policies implemented in recent years. Notably, this study employed various statistical methods, i.e., ordinary Kriging interpolation, spatial autocorrelation analysis, time-series analysis and the Bonferroni test, to evaluate the regional and seasonal differences of PM_2.5 concentrations based on long-term monitoring data. The results illustrated that PM_2.5 concentrations decreased on a yearly basis, demonstrating that air pollution control policies have achieved initial success. Furthermore, PM_2.5 concentrations were higher in the winter and in the southern regions. Diurnal variation presented a bimodal distribution, which varied slightly with the season. Relative humidity and wind speed were the principal meteorological factors affecting the distribution of PM_2.5 concentrations, while precipitation had essentially no effect. A high positive correlation between PM_2.5 and gaseous pollutants (SO₂, NO₂, and CO) indirectly reflected the contribution of automobile exhaust and coal-fired emissions. Generally, PM_2.5 concentrations demonstrated strong spatiotemporal variations, and meteorological factors and pollutant emissions played an important role in this.

Characterization of aerosol chemical composition and the reconstruction of light extinction coefficients during winter in Wuhan, China

To evaluate light extinction contributions of aerosol chemical constituents and their impacts on atmospheric visibility, the PM_2.5 and its chemical components, light scattering (b_sp) and absorption (b_ap) were continuously measured in Wuhan from January to February 2018. The average of PM_2.5 concentration, b_sp and b_ap were 96.5 ± 13.7 μg m^-3, 564 ± 124 Mm^-1 and 44 ± 8 Mm^-1 during polluted days, respectively, which was about 2.0, 2.1 and 1.6 times higher than those of clean days, respectively. Compared with the clean days, the increase of the mass concentrations of SNA (SO₄^2-, NO₃^-, NH₄⁺) during polluted days was higher than those of organic (OC) and elemental (EC) carbon, indicated the increase of SNA was the main cause of air pollution. The PM_2.5 concentration threshold was 66 μg m^-3, corresponding to the visibility lower than 10 km. The revised Interagency Monitoring of Protected Visual Environments (IMPROVE) algorithm was used to reconstruct the light extinction coefficient (b_ext) in Wuhan. The sum of light extinction coefficients of (NH₄)₂SO₄, NH₄NO₃ and organic matter (OM) accounted for 70.5% and 83.9% of b_ext during clean and polluted days, respectively. The backward trajectory and potential source contribution function (PSCF) analysis revealed that regional transport accounted for 55.6% of the total airflow, which originated from south, northwest and west of Wuhan. The increases of (NH₄)₂SO₄ and NH₄NO₃ concentrations, emitted from local vehicle exhaust and coal combustion, and their hygroscopic growth in ambient were the major causes of pollution in Wuhan.

Nitrate dominates the chemical composition of PM2.5 during haze event in Beijing, China

Water-soluble inorganic ions (WSI), a major component of PM_2.5, often increased rapidly during the haze event in Beijing. Sulfate (SO₄^2-), Nitrate (NO₃^-), and Ammonium (NH₄⁺) are three main components of WSI. Since year 2015, sulfate concentrations in PM_2.5 has gradually decreased owing to the effective control of SO₂ emissions. However, the contribution of nitrate to PM_2.5 has significantly increased during haze events in Beijing at the same time. In this study, a highly time-resolved online analyzer (Monitor for Aerosols and Gases, MARGA) was employed to measure the WSI in PM_2.5 in Beijing from 5 February to 15 November 2017. Three typical haze events during this sampling period were investigated. During heavy pollution episodes in winter, nitrate concentrations increased from 7.5 μg/m³ to 45.6 μg/m³ (45.0% of WSI), while sulfate increased from 4.2 μg/m³ to 20.1 μg/m³ (19.8% of WSI). This indicated that nitrate is more important than sulfate as a driver for the growth of PM_2.5 during the period of heavy air pollution in winter. Nitrate also dominates the increase of WSI in the pollution episodes in autumn, with an average concentration of 52.5 μg/m³, and contributed up to 67% of WSI. The average concentration ratio of NH₄⁺ to SO₄^2- was higher in autumn (1.02) than that in summer (0.74) and close to that in winter (1.00). This is mainly because the emission control of coal combustion in Beijing and surrounding areas results in an NH₃-rich and SO₂-lean atmosphere, which promoted the formation of ammonium nitrate. Our study indicates that nitrate has become the most important component of WSI in PM_2.5 and is driving the rapid growth of PM_2.5 concentrations during heavy pollution episodes in Beijing. Therefore, more efforts shall be made to reduce the nitrogen oxide and ammonia emissions in Beijing and surrounding areas.

Global Land Surface Temperature Influenced by Vegetation Cover and PM2.5 from 2001 to 2016

Land surface temperature (LST) is an important parameter to evaluate environmental changes. In this paper, time series analysis was conducted to estimate the interannual variations in global LST from 2001 to 2016 based on moderate resolution imaging spectroradiometer (MODIS) LST, and normalized difference vegetation index (NDVI) products and fine particulate matter (PM2.5) data from the Atmospheric Composition Analysis Group. The results showed that LST, seasonally integrated normalized difference vegetation index (SINDVI), and PM2.5 increased by 0.17 K, 0.04, and 1.02 μg/m3 in the period of 2001–2016, respectively. During the past 16 years, LST showed an increasing trend in most areas, with two peaks of 1.58 K and 1.85 K at 72°N and 48°S, respectively. Marked warming also appeared in the Arctic. On the contrary, remarkable decrease in LST occurred in Antarctic. In most parts of the world, LST was affected by the variation in vegetation cover and air pollutant, which can be detected by the satellite. In the Northern Hemisphere, positive relations between SINDVI and LST were found; however, in the Southern Hemisphere, negative correlations were detected. The impact of PM2.5 on LST was more complex. On the whole, LST increased with a small increase in PM2.5 concentrations but decreased with a marked increase in PM2.5. The study provides insights on the complex relationship between vegetation cover, air pollution, and land surface temperature.