Impacts of meteorological conditions on wintertime PM2.5 pollution in Taiyuan, North China

Negative association of atmospheric pollutants with semen quality: A cross-sectional study in Taiyuan, China

BACKGROUND

In recent decades, the quality of male semen has decreased worldwide. Air pollution has been linked to lower semen quality in several studies. However, the effects of atmospheric pollutants on different semen characteristics have not always been consistent. The aim of this study was to investigate the association between the Air Quality Index (AQI) and six atmospheric pollutants (PM2.5, PM10, SO2, NO2, CO, and O3), semen quality, and their key exposure window periods.

METHODS

This study included 1711 semen samples collected at the reproductive clinics of the First Affiliated Hospital of Shanxi Medical University in Taiyuan, Shanxi, China, from October 10, 2021, to September 30, 2022. We evaluated the association of AQI and six atmospheric pollutants with semen quality parameters throughout sperm development and three key exposure windows in men using single-pollutant models, double-pollutant models, and subgroup analyses of semen quality-eligible groups.

RESULTS

Both the single-pollutant model and subgroup analyses showed that PM, CO, and O3 levels were negatively correlated with total and progressive motility. At 70-90 d before semen collection, CO exposure and semen volume (β =-1.341, 95 % CI: -1.805, -0.877, P <0.001), total motility (β =-2.593, 95 % CI: -3.425, -1.761, P <0.001), and progressive motility (β =-4.658, 95 % CI: -5.556, -3.760, P <0.001) were negatively correlated. At 0-9 days before semen collection, CO was negatively correlated with normal morphology (β =-3.403, 95 % CI: -5.099, -1.708, P <0.001). Additionally, the AQI was adversely associated with total and progressive motility in subgroup analyses of the semen quality-eligible groups.

CONCLUSIONS

During the entire sperm development process, multiple air pollutants were determined to have an adverse correlation with semen quality parameters. AQI was significant marker for the combined effects of various atmospheric pollutants on male reproductive health.

Multi-Scale Meteorological Impact on PM2.5 Pollution in Tangshan, Northern China

Tangshan, a major industrial and agricultural center in northern China, frequently experiences significant PM2.5 pollution events during winter, impacting its large population. These pollution episodes are influenced by multi-scale meteorological processes, though the complex mechanisms remain not fully understood. This study integrates surface PM2.5 concentration data, ground-based and upper-air meteorological observations, and ERA5 reanalysis data from 2015 to 2019 to explore the interactions between local planetary boundary layer (PBL) structures and large-scale atmospheric processes driving PM2.5 pollution in Tangshan. The results indicate that seasonal variations in PM2.5 pollution levels are closely linked to changes in PBL thermal stability. During winter, day-to-day increases in PM2.5 concentrations are often tied to atmospheric warming above 1500 m, as enhanced thermal inversions and reduced PBL heights lead to pollutant accumulation. Regionally, this aloft warming is driven by a high-pressure system at 850 hPa over the southern North China Plain, accompanied by prevailing southwesterly winds. Additionally, southwesterly winds within the PBL can transport pollutants from the adjacent Beijing-Tianjin-Hebei region to Tangshan, worsening pollution. Simulations from the chemical transport model indicate that regional pollutant transport can contribute to approximately half of the near-surface PM2.5 concentration under the unfavorable synoptic conditions. These findings underscore the importance of multi-scale meteorology in predicting and mitigating severe wintertime PM2.5 pollution in Tangshan and surrounding regions.

PM2.5 exposure contributes to anxiety and depression-like behaviors via phenyl-containing compounds interfering with dopamine receptor

As a global problem, fine particulate matter (PM2.5) really needs local fixes. Considering the increasing epidemiological relevance to anxiety and depression but inconsistent toxicological results, the most important question is to clarify whether and how PM2.5 causally contributes to these mental disorders and which components are the most dangerous for crucial mitigation in a particular place. In the present study, we chronically subjected male mice to a real-world PM2.5 exposure system throughout the winter heating period in a coal combustion area and revealed that PM2.5 caused anxiety and depression-like behaviors in adults such as restricted activity, diminished exploratory interest, enhanced repetitive stereotypy, and elevated acquired immobility, through behavioral tests including open field, elevated plus maze, marble-burying, and forced swimming tests. Importantly, we found that dopamine signaling was perturbed using mRNA transcriptional profile and bioinformatics analysis, with Drd1 as a potential target. Subsequently, we developed the Drd1 expression-directed multifraction isolating and nontarget identifying framework and identified a total of 209 compounds in PM2.5 organic extracts capable of reducing Drd1 expression. Furthermore, by applying hierarchical characteristic fragment analysis and molecular docking and dynamics simulation, we clarified that phenyl-containing compounds competitively bound to DRD1 and interfered with dopamine signaling, thereby contributing to mental disorders. Taken together, this work provides experimental evidence for researchers and clinicians to identify hazardous factors in PM2.5 and prevent adverse health outcomes and for local governments and municipalities to control source emissions for diminishing specific disease burdens.

Urban and suburban decadal variations in air pollution of Beijing and its meteorological drivers

Air pollution is a major threat to human health and ecosystems. Using 10-year (2013-2022) multi-source observations for the Beijing, China, we showed that clean-air actions have significantly reduced PM2.5, PM10, CO, NO2, and SO2 pollution, with an increase in the surface maximum daily 8-h average ozone (MDA8O3) concentrations during autumn and winter, leading to a rapid diminishment of the urban-suburban gap in air pollution. Secondary sources and vehicle emissions were enhanced in both urban and suburban areas in all seasons except summer from 2013 to 2022. By combining statistical analysis with the convergent cross-mapping model, the varying relationships between air pollution and meteorological conditions in the urban and suburban areas were delineated. The results suggested that boundary layer height and relative humidity exerted strong and stable influences on all air pollutants, except for MDA8O3, whose key meteorological driver was temperature. This study showed that increasing O3 trends in autumn and winter and aggravated O3 formation in summer in urban areas in Beijing became non-negligible from 2013 to 2022, despite the declining levels of air pollutants. Meteorological observations suggested that weather patterns in Beijing, characterized by higher temperatures, sunshine hours, and boundary layer height and lower relative humidity, have become more favorable for O3 formation in autumn and winter. Future mitigation efforts should focus on reducing VOC and NOx emissions to avoid further deterioration of O3 pollution under the frequent adverse meteorological conditions predicted under the background of global warming.

The influence of PM2.5 exposure duration and concentration on outpatient visits of urban hospital in a typical heavy industrial city

To explain the duration and dose effects of pollutant exposure on public health and provide scientific data for air pollution prevention and control and disease prevention by examining the influence of PM2.5 concentration and exposure duration on daily outpatient visits among patients with cardiovascular, cerebrovascular, and respiratory diseases in a typical heavy industrial city in China. Daily outpatient data on cardiovascular, cerebrovascular, and respiratory diseases and regional PM2.5 exposure duration and concentration were collected from a provincial hospital in Taiyuan, China, from 2016 to 2021. The correlations of numeric variables were analyzed using the Pearson correlation method. A generalized additive model (GAMs) was also established to investigate the effects of PM2.5 concentration and exposure duration on outpatient visits. Correlation analysis showed that the outpatient visits in Taiyuan was significantly correlated with the PM2.5 concentration and exposure duration. The longer the exposure time of PM2.5 pollution, the stronger the correlation of PM2.5 with outpatient visits showed. Cardiovascular outpatient visits were extremely significant related with medium to long-term exposure of PM2.5 (exposure with more than 30 days) (p < 0.001). In addition, outpatient visits of cerebrovascular and respiratory disease were extremely significant correlated with PM2.5 (exposures within 0-360 days) (p < 0.001). The results of GAMs showed the linear or the nonlinear relationships between outpatient visits and exposure of PM2.5. Among the linear relationships, when average concentration of PM2.5 (exposure within less than 15 days) increased by 1 mg/m3, the cardiovascular outpatient visits increased most dramatically (by about 440 people). For nonlinear relationships, when the average PM2.5 concentration (exposure with over 30 days or more) increased by 1 mg/m3, the most dramatic increase occurred in cardiovascular outpatient visits (with a maximum increase of 7000), followed by cerebrovascular outpatient visits (with a maximum increase of 1200), and respiratory outpatient visits (with a maximum increase of 250). The GAMs also revealed a dose effect in the relationship between outpatient visits and PM2.5 exposure. In moderately polluted air (based on air quality standards of China, GB3095-2012), when the average concentration of PM2.5 increased by 1 mg/m3, the cardiovascular outpatient visits increased the most (by 1200 people), followed by cerebrovascular outpatient visits (by 200 people) and respiratory outpatient visits (by 20 people). We concluded that outpatient visits in cardiovascular, cerebrovascular, and respiratory disease are closely correlated with the concentration and exposure duration of air pollution. There is a linear relationship between short-term air pollution exposure (exposure within less than 15 days) and outpatient visits. As PM2.5 concentration increases, cardiovascular outpatient visits increase gradually, with its growth trend exceeding that of cerebrovascular and respiratory disease. There is a nonlinear relationship between medium and long-term air pollution exposure (exposure with more than 30 days) and outpatient visits, with cardiovascular and cerebrovascular outpatient visits showed a nonlinear but overall upward trend when the atmosphere is moderately polluted.

Spatiotemporal heterogeneity of the relationships between PM2.5 concentrations and their drivers in China's coastal ports

PM2.5 is one of the primary air pollutants that affect air quality and threat human health in the port areas. To prevent and control air pollution, it is essential to understand the spatiotemporal distributions of PM2.5 concentrations and their key drivers in ports. 19 coastal ports of China are selected to examine the spatiotemporal distributions of PM2.5 concentrations during 2013-2020. The annual average PM2.5 concentration decreases from 61.03 μg/m3 to 30.17 μg/m3, with an average decrease rate of 51.57%. Significant spatial autocorrelation exists among PM2.5 concentrations of ports. The result of the geographically and temporally weighted regression (GTWR) model shows significant spatiotemporal heterogeneity in the effects of meteorological and socioeconomic factors on PM2.5 concentrations. The effects of boundary layer height on PM2.5 concentrations are found to be negative in most ports, with a stronger effect found in the Pearl River Delta, Yangtze River Delta and some ports of the Bohai Rim Area. The total precipitation shows negative effects on PM2.5 concentrations, with the strongest effect found in ports of the Southeast Coast. The effects of surface pressure on PM2.5 concentrations are positive, with stronger effects found in Beibu Gulf Port and Zhanjiang Port. The effects of wind speed on PM2.5 concentrations generally increase from south to north. Cargo throughput shows strong and positive effects on PM2.5 concentrations in ports of Bohai Rim Area; the positive effects found in Beibu Gulf Port increased from 2013 to 2018 and decreased since 2019. The positive effects of GDP and nighttime light on PM2.5 concentrations gradually decrease and turn negative from south to north. Understandings obtained from this study can potentially support the prevention and control of air pollution in China's coastal ports.

The effect of natural and socioeconomic factors on haze pollution from global and local perspectives in China

Analyzing the factors that cause haze and the regional differences in the influence of factors on haze is the premise and critical to precise prevention and control of haze pollution. This paper explores the global effects of haze pollution drivers and the spatial heterogeneity of factors on haze pollution using global and local regression models. The results show that, from a global perspective, a 1 μg/m³ increase in the average PM_2.5 concentration of a city's neighbors will increase the city's PM_2.5 concentration by 0.965 μg/m³. Temperature, atmospheric pressure, population density, and green coverage of built-up areas are positively associated with haze, while GDP per capita is the opposite. From a local perspective, each factor has different influencing scales on haze pollution. Specifically, technical support is on a global scale, and for every 1 unit increase in technical support level, the PM_2.5 concentration will decrease by 0.106-0.102 μg/m³. The influencing scales of other drivers are local. In southern China, the concentration of PM_2.5 decreases by 0.001-0.075 μg/m³ for every 1 °C increase in temperature, while in northern China, the concentration of PM_2.5 increases by 0.001-0.889 μg/m³. In the region around the Bohai Sea in eastern China, the concentration of PM_2.5 will decrease by 0.001-0.889 μg/m³ for every 1 m/s increase in wind speed. Population density positively impacts haze pollution, and the impact intensity gradually increases from 0.097 to 1.140 from south to north. For every 1% increase in the proportion of the secondary industry in southwest China, the PM_2.5 concentration will increase by 0.001-0.284 μg/m³. For cities in northeast China, for every 1% increase in the urbanization rate, the PM_2.5 concentration will decrease by 0.001-0.203 μg/m³. These findings help policymakers develop targeted joint prevention and control policies for haze pollution, considering regional differences.

Association between maternal exposure to air pollution and gestational diabetes mellitus in Taiyuan, North China

BACKGROUND

The effect of air pollution on human health has been a major concern, especially the association between air pollution and gestational diabetes mellitus (GDM).

METHODS

In this study, we conducted a retrospective cohort study in Taiyuan, a typical energy production base in China. This study included 28,977 pairs of mothers and infants between January 2018 and December 2020. To screen for GDM, oral glucose tolerance test (OGTT) was performed in pregnant women at 24-28 weeks of gestation. Logistic regression was used to assess the trimester-specific association between 5 common air pollutants (PM₁₀, PM_2.5, NO₂, SO₂, and O₃) and GDM, and the weekly-based association was also assessed using distributed lag non-linear models (DLNMs). Odds ratios (ORs) with 95 % confidence intervals (CIs) were calculated for the association between GDM and each air pollutant.

RESULTS

The overall incidence of GDM was 3.29 %. PM_2.5 was positively associated with GDM over the second trimester (OR [95 % CI], 1.105 [1.021, 1.196]). O₃ was positively associated with GDM in the preconception period (OR [95 % CI], 1.125 [1.024, 1.236]), the first trimester (OR [95 % CI], 1.088 [1.019, 1.161]) and the 1st + 2nd trimester (OR [95 % CI], 1.643 [1.387, 1.945]). For the weekly-based association, PM_2.5 was positively associated with GDM at 19-24 weeks of gestation, with the strongest association at week 24 (OR [95 % CI], 1.044 [1.021, 1.067]). PM₁₀ was positively associated with GDM at 18-24 weeks of gestation, with the strongest association at week 24 (OR [95 % CI], 1.016 [1.003, 1.030]). O₃ was positively associated with GDM during the 3rd week before conception to the 8th gestational week, with the strongest association at week 3 of gestation (OR [95 % CI], 1.054 [1.032, 1.077]).

CONCLUSION

The findings are important for the development of effective air quality policies and the optimization of preventive strategies for preconception and prenatal care.

Chemical composition, oxidative potential and identifying the sources of outdoor PM2.5 after the improvement of air quality in Beijing

Air pollution poses a serious threat to human health. The implementation of air pollution prevention and control policies has gradually reduced the level of atmospheric fine particles in Beijing. Exploring the latest characteristics of PM_2.5 has become the key to further improving pollution reduction measures. In the current study, outdoor PM_2.5 samples were collected in the spring and summer of Beijing, and the chemical species, oxidative potential (OP), and sources of PM_2.5 were characterized. The mean PM_2.5 concentration during the entire study period was 41.6 ± 30.9 μg m^-3. Although the PM_2.5 level in summer was lower, its OP level was significantly higher than that in spring. SO₄^2-, NH₄⁺, EC, NO^3-, and OC correlated well with volume-normalized OP (OP_v). Strong positive correlations were found between OP_v and the following elements: Cu, Pb, Zn, Ni, As, Cr, Sn, Cd, Al, and Mn. Seven sources of PM_2.5 were identified, including traffic, soil dust, secondary sulfate, coal and biomass burning, oil combustion, secondary nitrate, and industry. Multiple regression analysis indicated that coal and biomass combustion, industry, and traffic were the main contributors to the OP_v in spring, while secondary sulfate, oil combustion, and industry played a leading role in summer. The source region analysis revealed that different pollution sources were related to specific geographic distributions. In addition to local emission reduction policies, multi-provincial cooperation is necessary to further improve Beijing's air quality and reduce the adverse health effects of PM_2.5.

Prediction of the Impact of Meteorological Conditions on Air Quality during the 2022 Beijing Winter Olympics

The issue of air pollution has attracted more and more attention. Understanding how to predict air quality based on weather conditions has strong practical significance. For the first time, this paper combines weather circulation with climate prediction models to explore long-term air quality predictions. Using the T-mode (time realizations in columns) objective circulation classification method, we classified the weather circulation affecting Beijing, China, according to nine categories of predominant weather conditions. PM2.5, NO2, SO2, and CO concentration distributions for these nine circulation patterns were also determined. When the Beijing area was controlled by northwestern low pressure, a high-pressure rear, or a weak pressure field, the PM2.5 concentrations were higher, while high-pressure systems and a high-pressure rear were mostly associated with relatively high NO2, SO2, and CO concentrations. The concentrations of these pollutants under high-pressure fronts and northwestern high-pressure settings were low. Using the FLEXPART-WRF model to simulate the 48 h backward trajectory of the highest PM2.5 concentration under the nine circulation patterns from 2015 to 2021, we obtained the trap time of pollutants per unit concentration (imprint analysis) and determined the particle trap area under each circulation pattern. When using the EC-Earth climate prediction model, the daily circulation field during the Beijing Winter Olympics was forecasted, and the nine circulation patterns were compared. The corresponding circulation pattern in Beijing during the 2022 Winter Olympics should be conducive to the diffusion of pollutants and, therefore, the air quality is expected to be good.

Taurine reduction associated with heart dysfunction after real-world PM2.5 exposure in aged mice

Ambient PM_2.5 has been proved to be an independent risk factor for cardiovascular diseases; however, little information is available on the age-dependent effects of PM_2.5 on the cardiovascular system and the underlying mechanisms following chronic exposure. In this study, multi-aged mice were exposed to PM_2.5 via the newly developed real-ambient PM_2.5 exposure system to investigate age-related effects on the heart after long-term exposure. First, the chemical and physical properties of PM_2.5 used in the exposure system were analyzed. The heart rate of conscious mice was recorded, and results showed that exposure of aged mice to PM_2.5 for 26 weeks significantly increased heart rate. Histological analysis and ELISA assays indicated that aged mice were more sensitive to PM_2.5 exposure in terms of inducing cardiac oxidative stress and inflammation. Furthermore, untargeted metabolomics revealed that taurine was involved with the PM_2.5-induced cardiac dysfunction. The reduced taurine concentration in the heart was examined by LC-MS and imaging mass spectrometry; it may be due to the increased p53 expression level, ROS and inflammatory cytokines. These results emphasize the age-dependent effects of PM_2.5 on the cardiovascular system and suggest that taurine may be the novel cardiac effect target for PM_2.5-induced heart dysfunction in the aged.

Proteomic characteristics of PM2.5 -induced differentially expressed proteins in human renal tubular epithelial cells

Human renal epithelial (HK-2) cells were treated with PM_2.5 (50 μg/mL) from Shenzhen and Taiyuan, proteomics and bioinformatics were used to screen the differentially expressed proteins (DEPs). A total of 577 DEPs were screened after HK-2 cells exposed to Shenzhen PM_2.5, of which 426 were up-regulated and 151 were down-regulated. A total of 1250 DEPs were screened in HK-2 cells after exposure to Taiyuan PM_2.5, of which 488 were up-regulated and 185 were down-regulated. The top 10 proteins with the highest number of nodes were screened using the interaction network map of DEPs. HK-2 cells exposed to Shenzhen PM_2.5 contained CYR61, CTGF, and THBS1 proteins, while HK-2 cells exposed to Taiyuan PM_2.5 contained ALB, FN1, and CYR61 proteins. Additionally, PM_2.5 components were detected, PM_2.5 samples from Shenzhen and Taiyuan induced obvious changes in DEPs expression, the difference in DEPs between the two cities was probably associated with the different PM_2.5 components.

Seasonal characteristics of boundary layer over a high-altitude rural site in Western India: implications on dispersal of particulate matter

The temporal variability of the planetary boundary layer height (PBLH) over Mahabaleshwar was studied for a period of 1 year from 1 December 2015 to 30 November 2016 using microwave radiometer (MWR) observations. The PBLH over Mahabaleshwar was found to be the highest during the pre-monsoon (March-May) season and lowest during the winter (December-February) season. The seasonal mean of PBLH was estimated to be 339±88 m during winter, 485±70 m during pre-monsoon, 99±153 m during monsoon, and 438±24 m during post-monsoon season. Frequency distribution analysis of PBLH during pre-monsoon season revealed that the formation of turbulence internal boundary layer (TIBL) is evident. In contrast, cold and moist air mass during the monsoon season enhances the wind shear with lower buoyancy term which results in lowering of PBLH. The comparison of PBLH between MWR and radiosonde observations shows a good correlation (r² = 0.66, p=0.001). The growth rate was observed to be 388 m/h during pre-monsoon, 206 m/h during winter, 57 m/h during monsoon, and 167 m/h during post-monsoon season. The seasonal mean concentration of PM_2.5 was found to be 42.3±4.6 μg/m³during winter, 33.4±8.7 μg/m³ during pre-monsoon, 6.6±2.2 μg/m³ during monsoon, and 26.1±1.7 μg/m³during post-monsoon season. The effect of higher loading of scattering-type aerosol (dust particle) was also investigated as a case study. The analysis reveals the inverse relationship between the PBL height variability and the particulate loading indicating the importance of aerosol direct effect. Analysis of the ventilation coefficient (Vc) revealed that the dissipation potential was higher (1736 m²/s) during pre-monsoon season as compared to (1191 m²/s, 455m²/s, and 1580 m²/s) winter, monsoon, and post-monsoon seasons.

Coupled Air Quality and Boundary-Layer Meteorology in Western U.S. Basins during Winter: Design and Rationale for a Comprehensive Study

Wintertime episodes of high aerosol concentrations occur frequently in urban and agricultural basins and valleys worldwide. These episodes often arise following development of persistent cold-air pools (PCAPs) that limit mixing and modify chemistry. While field campaigns targeting either basin meteorology or wintertime pollution chemistry have been conducted, coupling between interconnected chemical and meteorological processes remains an insufficiently studied research area. Gaps in understanding the coupled chemical-meteorological interactions that drive high pollution events make identification of the most effective air-basin specific emission control strategies challenging. To address this, a September 2019 workshop occurred with the goal of planning a future research campaign to investigate air quality in Western U.S. basins. Approximately 120 people participated, representing 50 institutions and 5 countries. Workshop participants outlined the rationale and design for a comprehensive wintertime study that would couple atmospheric chemistry and boundary-layer and complex-terrain meteorology within western U.S. basins. Participants concluded the study should focus on two regions with contrasting aerosol chemistry: three populated valleys within Utah (Salt Lake, Utah, and Cache Valleys) and the San Joaquin Valley in California. This paper describes the scientific rationale for a campaign that will acquire chemical and meteorological datasets using airborne platforms with extensive range, coupled to surface-based measurements focusing on sampling within the near-surface boundary layer, and transport and mixing processes within this layer, with high vertical resolution at a number of representative sites. No prior wintertime basin-focused campaign has provided the breadth of observations necessary to characterize the meteorological-chemical linkages outlined here, nor to validate complex processes within coupled atmosphere-chemistry models.

Effect of urban underlying surface on PM2.5 vertical distribution based on UAV in Xi'an, China

Fine particulate matter (PM_2.5) has become a significant issue of ecological environment. However, few studies have explored the vertical distribution of PM_2.5 in cities. The objectives of this paper are to reveal the vertical distribution regular pattern of PM_2.5 over urban underlying surfaces near the ground with a hexacopter-type unmanned aerial vehicle (UAV) in winter. Results showed that the maximum vertical gradient of PM_2.5 near the ground was typically the greatest in the morning as the stable atmospheric conditions. Moreover, regression model illustrated that relative humidity had the greatest impact on the vertical profile of PM_2.5 compared to air temperature and altitude as hygroscopic of PM_2.5 aerosols. Curve model shown that vertical profile of PM_2.5 over the surfaces of water and green space first increased slowly and then declined, besides, the highest concentration inflection of PM_2.5 above the water body (23.7 m) is higher than the green space (14.3 m). Thus, suggesting residents living vertical of 10-30 m from the ground around large water bodies and green spaces should not open windows for ventilation in the morning. Therefore, this study provides insights into the vertical distributions of PM_2.5 over different underlying surfaces and should be of reference value to urban planners for designing urban spaces to optimize atmosphere environment to provide a healthy living environment.

Proteomic characteristics and identification of PM2.5-induced differentially expressed proteins in hepatocytes and c-Myc silenced hepatocytes

Proteomics and bioinformatics were applied to explore PM_2.5-induced differentially expressed proteins (DEPs) in hepatocytes (L02 cells) and c-Myc-silenced hepatocytes. L02 cells and c-Myc-silenced hepatocytes were treated with PM_2.5 for 24 h. Fifty-two DEPs were screened in L02 hepatocytes, of which 28 were upregulated and 24 were downregulated. Forty-one DEPs were screened in the c-Myc-silenced hepatocytes, of which 31 were upregulated and 10 were downregulated. GO analysis showed that DEPs in L02 cells were mainly concentrated in the cytosol and were involved in biological processes such as the response to metal ions. DEPs in c-Myc-silenced cells were mainly enriched in the extracellular space and were involved in lipoprotein metabolism. KEGG analysis showed that DEPs in L02 cells were mainly involved in arachidonic acid metabolism and mineral absorption. DEPs in c-Myc-silenced cells were mainly enriched in pathways involving nerve absorption, complement and coagulation cascades, and other pathways. Twenty key proteins, including Metallothionein-2A (MT2A), Metallothionein-1X (MT1X), zinc transporter ZIP10 (SLC39A10) and Serine protease 23 (PRSS23) were screened in two groups through analysis of protein-protein interactions. Based on the identification of the selected DEPs, PRSS23 and SLC39A10 might be the potential biomarker of PM_2.5-induced carcinogenesis, which provide the scientific basis for further research into the carcinogenic mechanisms of PM_2.5.

Impact of city lockdown on the air quality of COVID-19-hit of Wuhan city

A series of strict lockdown measures were implemented in the areas of China worst affected by coronavirus disease 19, including Wuhan, to prevent the disease spreading. The lockdown had a substantial environmental impact, because traffic pollution and industrial emissions are important factors affecting air quality and public health in the region. After the lockdown, the average monthly air quality index (AQI) in Wuhan was 59.7, which is 33.9% lower than that before the lockdown (January 23, 2020) and 47.5% lower than that during the corresponding period (113.6) from 2015 to 2019. Compared with the conditions before the lockdown, fine particulate matter (PM_2.5) decreased by 36.9% and remained the main pollutant. Nitrogen dioxide (NO₂) showed the largest decrease of approximately 53.3%, and ozone (O₃) increased by 116.6%. The proportions of fixed-source emissions and transported external-source emissions in this area increased. After the lockdown, O₃ pollution was highly negatively correlated with the NO₂ concentration, and the radiation increase caused by the PM_2.5 reduction was not the main reason for the increase in O₃. This indicates that the generation of secondary pollutants is influenced by multiple factors and is not only governed by emission reduction.

Vertical Wind Shear Modulates Particulate Matter Pollutions: A Perspective from Radar Wind Profiler Observations in Beijing, China

Vertical wind shear (VWS) is one of the key meteorological factors in modulating ground-level particulate matter with an aerodynamic diameter of 2.5 µm or less (PM2.5). Due to the lack of high-resolution vertical wind measurements, how the VWS affects ground-level PM2.5 remains highly debated. Here we employed the wind profiling observations from the fine-time-resolution radar wind profiler (RWP), together with hourly ground-level PM2.5 measurements, to explore the wind features in the planetary boundary layer (PBL) and their association with aerosols in Beijing for the period from December 1, 2018, to February 28, 2019. Overall, southerly wind anomalies almost dominated throughout the whole PBL or even beyond the PBL under polluted conditions during the course of a day, as totally opposed to the northerly wind anomalies in the PBL under clean conditions. Besides, the ground-level PM2.5 pollution exhibited a strong dependence on the VWS. A much weaker VWS was observed in the lower part of the PBL under polluted conditions, compared with that under clean conditions, which could be due to the strong ground-level PM2.5 accumulation induced by weak vertical mixing in the PBL. Notably, weak northbound transboundary PM2.5 pollution mainly appeared within the PBL, where relatively small VWS dominated. Above the PBL, strong northerlies winds also favored the long-range transport of aerosols, which in turn deteriorated the air quality in Beijing as well. This was well corroborated by the synoptic-scale circulation and backward trajectory analysis. Therefore, we argued here that not only the wind speed in the vertical but the VWS were important for the investigation of aerosol pollution formation mechanism in Beijing. Also, our findings offer wider insights into the role of VWS from RWP in modulating the variation of PM2.5, which deserves explicit consideration in the forecast of air quality in the future.

Contamination profiles and potential health risks of organophosphate flame retardants in PM2.5 from Guangzhou and Taiyuan, China

Organophosphate flame retardants (OPFRs) are emerging contaminants in recent years. They can be present in the atmospheric fine particle (PM_2.5), leading to potential adverse effects on humans. In this study, the concentrations and in vitro toxicities of OPFRs in PM_2.5 samples were investigated for one year at Guangzhou and Taiyuan in China. Eleven OPFRs, including chloro-, aryl-, and alkyl-substituted OPFRs, were detected at total concentrations ranging from 3.10 to 544 ng m^-3. Chloro-substituted OPFRs were the dominant contaminants. Based on the statistical analysis, the same contamination sources of all OPFRs were found except for tris(butoxyethyl) phosphate (TBOEP) and triethyl phosphate (TEP), which may come from traffic emission. The results of cell viability and dithiothreitol assays indicated that OPFRs and PM_2.5 could induce the death of normal lung epithelial cells and the production of reactive oxygen species (ROS), respectively. According to the redundancy analysis, the distribution of OPFRs was significantly related to the PM_2.5 concentrations and indirectly associated with ROS production induced by PM_2.5 from Taiyuan. Exposure to PM_2.5-bound OPFRs in Guangzhou and Taiyuan only posed minimum health risks to both toddlers and adults. These findings could provide important evidence to better clarify the contamination profiles and human health risks of OPFRs in atmospheric fine particles.

Synoptic pattern and planetary boundary layer structure associated with aerosol pollution during winter in Beijing, China

The day-to-day variations in the planetary boundary layer (PBL) structure and air quality are closely governed by large-scale synoptic forcings. Partly due to the lack of long-term PBL observations during the winter in Beijing, the complex relationships between the large-scale synoptic patterns, local PBL structures/processes, and PM_2.5 pollution have not been fully understood. Thus, this study systematically investigated these linkages by combining aerosol measurements, surface meteorological observations, radiosonde data, reanalysis, long-term three-dimensional meteorological simulations, and idealized meteorology-chemistry coupled simulations. Based on the validated long-term simulation results, the boundary layer height (BLH) in Beijing during two winters from 2013 to 2015 was calculated and compared with PM_2.5 measurements. A significant anti-correlation was found between the daily BLH and PM_2.5 concentration in Beijing, indicating the importance of the PBL structure on the variations in the aerosol pollution levels. Those days with low BLHs are often accompanied by a strong elevated thermal inversion layer. Based on the daily 900-hPa geopotential height fields, seven synoptic patterns were identified using an objective approach, in which two types were found to be associated with heavy PM_2.5 pollution in Beijing. One pattern was characterized by weak northwesterly prevailing winds and a strong elevated thermal inversion layer over Beijing, and the local emissions of aerosols played a decisive role in the formation of heavy pollution. The other pattern was associated with southerly prevailing winds, which could transport the pollutants emitted from southern cities to Beijing. According to the meteorology-chemistry coupled simulations, southerly regional transportation can contribute approximately 56% of the PM_2.5 in Beijing. The results of this study have important implications for understanding the crucial roles that multiscale meteorological factors play in modulating the aerosol pollution in Beijing during the winter.

Properties of particulate matter and gaseous pollutants in Shandong, China: Daily fluctuation, influencing factors, and spatiotemporal distribution

Characteristics of the spatial and temporal distribution of air pollutants may reveal the cause of air pollution, especially for large regions where the anthropogenic pollutant emission is concentrated. This study addresses this issue by focusing on Shandong province, which has the highest air pollutant emissions in China. First, the spatial and temporal variation characteristics of the observed concentrations of conventional pollutants are analyzed in detail. The most prominent indicator of the problem (PM_2.5), was selected as the key analytical object. On the spatial scale, the Multivariate Moran model was used to identify factors affecting the spatial distribution of PM_2.5. On the time scale, wavelet analysis was used to explore the fluctuation characteristics of PM_2.5 at different time periods. Results show that there are significant regional differences in pollutant concentration within Shandong province. The concentration of particulate matter and gaseous pollutants in western and northern Shandong is significantly higher than eastern Shandong. The average concentrations of PM_2.5, PM₁₀, SO₂ and NO₂ were highest in winter and lowest in summer, whereas concentration of O₃ peaked in summer. For PM_2.5, the annual mean concentration has a significant spatial correlation with SO₂ emission, GDP per capita, population density and energy consumption per unit of GDP; in addition, the correlation between different regions and various indices is different. On the time scale, the fluctuation energy of PM_2.5 concentrated in Dezhou and Liaocheng is the strongest on December 18 and 19, 2015. The inversion temperature has a strong influence on the daily variation of PM_2.5 concentration. The formation and evolution of atmospheric pollution, therefore, can be explored by combining the temporal and spatial distribution of pollutants, providing a comprehensive analytical method for atmospheric pollution in different regions.

Linkages between aerosol pollution and planetary boundary layer structure in China

China suffers from high levels of PM_2.5 pollution, which is often exacerbated by unfavorable planetary boundary layer (PBL) structures. Partly due to a lack of appropriate observations, the PBL-aerosol linkages in China are not clearly understood. Thus, we investigated these linkages from a national perspective using sounding data collected from 2014 to 2017. Correlation analyses revealed a significant anti-correlation between monthly boundary layer height (BLH) and aerosol pollution that was ubiquitous across China, indicating the important role of the PBL in regulating the seasonal variations of pollution in China. Besides, the day-to-day variations in pollution were modulated by the daily variabilities in the PBL structure. During winter, highly polluted days in most of the Chinese cities studied were associated with a low BLH, strong thermal stability, and weak PBL winds. In the North China Plain and Northeast China, the wintertime heavy pollution was often related to southerly winds and moister PBL. This study has important implications for understanding the crucial role that the PBL plays in modulating aerosol pollution in China.

Elucidating the relationship between aerosol concentration and summertime boundary layer structure in central China

Wuhan, a megacity in central China, suffers from frequent aerosol pollution and is accompanied by meteorological factors at both synoptic and local scales. Partly due to the lack of appropriate observations of planetary boundary layer (PBL), the associations between synoptic conditions, PBL, and pollution there are not yet fully understood. Thus, systematic analyses were conducted using the fine-resolution soundings, surface meteorological measurements, and aerosol observations in Wuhan during summer for the period 2013-2016, in combination with T-mode principal component analysis and simulations of backward trajectory. The results showed that the variations of boundary layer height (BLH) not only modulated the diurnal variation of PM_2.5 concentration in Wuhan, but also the daily pollution level. Five different synoptic patterns during summer in Wuhan were identified from reanalysis geopotential height fields. Among these synoptic patterns, two types characterized by northeasterly prevailing winds, were found to be associated with heavy pollution in Wuhan. Driven by the northeasterly winds, the polluted air mass from the heavily polluted regions could be easily transported to Wuhan, such as North China Plain and Yangtze River Delta. Such regional transports of pollutants must be partly responsible for the aerosol pollution in Wuhan. In addition, these two synoptic patterns were also featured by the relatively high cloud cover and low boundary layer height in Wuhan, which would favor the occurrence of pollution there. Overall, this study has important implications for understanding the important roles of meteorological factors in modulating aerosol pollution in central China.