Cause of PM2.5 pollution during the 2016-2017 heating season in Beijing, Tianjin, and Langfang, China

Effects of short- and long-term exposures to multiple air pollutants on depression among the labor force: A nationwide longitudinal study in China

BACKGROUND

Depression prevalence has surged within the labor force population in recent years. While links between air pollutants and depression were explored, there was a notable scarcity of research focusing on the workforce.

METHODS

This nationwide longitudinal study analyzed 27,457 workers aged 15-64. We estimated monthly mean concentrations of fine particulate matter (PM2.5), its primary components, and Ozone (O3) at participants' residences using spatiotemporal models. To assess the relationship between short- (1 to 3 months) and long-term (1 to 2 years) exposure to various air pollutants and depressive levels and occurrences, we employed linear mixed-effects models and mixed-effects logistic regression. We considered potential occupational moderators, such as labor contracts, overtime compensation, and total annual income.

RESULTS

We found significant increases in depression risks within the workforce linked to both short- and long-term air pollution exposure. A 10 μg/m3 rise in 2-year average PM2.5, black carbon (BC), and O3 concentrations correlated with increments in depressive scores of 0.009, 0.173, and 0.010, and a higher likelihood of depression prevalence by 0.5 %, 12.6 %, and 0.7 %. The impacts of air pollutants and depression were more prominent in people without labor contracts, overtime compensation, and lower total incomes.

CONCLUSION

Exposures to air pollutants could increase the risk of depression in the labor force population. The mitigating effects of higher income, benefits, and job security against depression underscore the need for focused mental health interventions.

Assessing emission-driven changes in health risk of source-specific PM2.5-bound heavy metals by adjusting meteorological covariates

Heavy metals (HMs) in PM2.5 gain much attention for their toxicity and carcinogenic risk. This study evaluates the health risks of PM2.5-bound HMs, focusing on how meteorological conditions affect these risks against the backdrop of PM2.5 reduction trends in China. By applying a receptor model with a meteorological normalization technique, followed by health risk assessment, this work reveals emission-driven changes in health risk of source-specific HMs in the outskirt of Tianjin during the implementation of China' second Clean Air Action (2018-2020). Sources of PM2.5-bound HMs were identified, with significant contributions from vehicular emissions (on average, 33.4 %), coal combustion (26.3 %), biomass burning (14.1 %), dust (11.7 %), industrial boilers (9.7 %), and shipping emission and sea salt (4.7 %). The source-specific emission-driven health risk can be enlarged or dwarfed by the changing meteorological conditions over time, demonstrating that the actual risks from these source emissions for a given time period may be higher or smaller than those estimated by traditional assessments. Meteorology contributed on average 56.1 % to the interannual changes in source-specific carcinogenic risk of HMs from 2018 to 2019, and 5.6 % from 2019 to 2020. For the source-specific noncarcinogenic risk changes, the contributions were 38.3 % and 46.4 % for the respective periods. Meteorology exerts a more profound impact on daily risk (short-term trends) than on annual risk (long-term trends). Such meteorological impacts differ among emission sources in both sign and magnitude. Reduced health risks of HMs were largely from targeted regulatory measures on sources. Therefore, the meteorological covariates should be considered to better evaluate the health benefits attributable to pollution control measures in health risk assessment frameworks.

Aerosol liquid water in PM2.5 and its roles in secondary aerosol formation at a regional site of Yangtze River Delta

Aerosol liquid water content (ALWC) plays an important role in secondary aerosol formation. In this study, a whole year field campaign was conducted at Shanxi in north Zhejiang Province during 2021. ALWC estimated by ISORROPIA-II was then investigated to explore its characteristics and relationship with secondary aerosols. ALWC exhibited a highest value in spring (66.38 µg/m3), followed by winter (45.08 µg/m3), summer (41.64 µg/m3), and autumn (35.01 µg/m3), respectively. It was supposed that the secondary inorganic aerosols (SIA) were facilitated under higher ALWC conditions (RH > 80%), while the secondary organic species tended to form under lower ALWC levels. Higher RH (> 80%) promoted the NO3- formation via gas-particle partitioning, while SO42- was generated at a relative lower RH (> 50%). The ALWC was more sensitive to NO3- (R = 0.94) than SO42- (R = 0.90). Thus, the self-amplifying processes between the ALWC and SIA enhanced the particle mass growth. The sensitivity of ALWC and OX (NO2 + O3) to secondary organic carbon (SOC) varied in different seasons at Shanxi, more sensitive to aqueous-phase reactions (daytime R = 0.84; nighttime R = 0.54) than photochemical oxidation (daytime R = 0.23; nighttime R = 0.41) in wintertime with a high level of OX (daytime: 130-140 µg/m3; nighttime: 100-140 µg/m3). The self-amplifying process of ALWC and SIA and the aqueous-phase formation of SOC will enhance aerosol formation, contributing to air pollution and reduction of visibility.

Insights into PM2.5 pollution of four small and medium-sized cities in Chinese representative regions: Chemical compositions, sources and health risks

Fine particles (PM2.5) pollution is still a severe issue in some cities in China, where the chemical characteristics of PM2.5 remain unclear due to limited studies there. Herein, we focused on PM2.5 pollution in small and medium-sized cities in key urban agglomerations and conducted a comprehensive study on the PM2.5 chemical characteristics, sources, and health risks. In the autumn and winter of 2019-2020, PM2.5 samples were collected simultaneously in four small and medium-sized cities in four key regions: Dingzhou (Beijing-Tianjin-Hebei region), Weinan (Fenwei Plain region), Fukang (Northern Slope of the Tianshan Mountain region), and Bozhou (Yangtze River Delta region). The results showed that secondary inorganic ions (43.1 %-67.0 %) and organic matter (OM, 8.6 %-36.4 %) were the main components of PM2.5 in all the cities. Specifically, Fukang with the most severe PM2.5 pollution had the highest proportion of SO42- (31.2 %), while the dominant components in other cities were NO3- and OM. The Multilinear Engine 2 (ME2) analysis identified five sources of PM2.5 in these cities. Coal combustion contributed most to PM2.5 in Fukang, but secondary sources in other cities. Combined with chemical characteristics and ME2 analysis, it was preliminarily determined that the primary emission of coal combustion had an important contribution to high SO42- in Fukang. Potential source contribution function (PSCF) analysis results showed that regional transport played an important role in PM2.5 in Dingzhou, Weinan and Bozhou, while PM2.5 in Fukang was mainly affected by short-range transport from surrounding areas. Finally, the health risk assessment indicated Mn was the dominant contributor to the total non-carcinogenic risks and Cr had higher carcinogenic risks in all cities. The findings provide a scientific basis for formulating more effective abatement strategies for PM2.5 pollution.

Quantifying the scale-dependent relationships of PM2.5 and O3 on meteorological factors and their influencing factors in the Beijing-Tianjin-Hebei region and surrounding areas

To investigate the variations of PM2.5 and O3 and their synergistic effects with influencing factors at different time scales, we employed Bayesian estimator of abrupt seasonal and trend change to analyze the nonlinear variation process of PM2.5 and O3. Wavelet coherence and multiple wavelet coherence were utilized to quantify the coupling oscillation relationships of PM2.5 and O3 on single/multiple meteorological factors in the time-frequency domain. Furthermore, we combined this analysis with the partial wavelet coherence to quantitatively evaluate the influence of atmospheric teleconnection factors on the response relationships. The results obtained from this comprehensive analysis are as follows: (1) The seasonal component of PM2.5 exhibited a change point, which was most likely to occur in January 2017. The trend component showed a discontinuous decline and had a change point, which was most likely to appear in February 2017. The seasonal component of O3 did not exhibit a change point, while the trend component showed a discontinuous rise with two change points, which were most likely to occur in July 2018 and May 2017. (2) The phase and coherence relationships of PM2.5 and O3 on meteorological factors varied across different time scales. Stable phase relationships were observed on both small- and large-time scales, whereas no stable phase relationship was formed on medium scales. On all-time scales, sunshine duration was the best single variable for explaining PM2.5 variations and precipitation was the best single variable explaining O3 variations. When compared to single meteorological factors, the combination of multiple meteorological factors significantly improved the ability to explain variations in PM2.5 and O3 on small-time scales. (3) Atmospheric teleconnection factors were important driving factors affecting the response relationships of PM2.5 and O3 on meteorological factors and they had greater impact on the relationship at medium-time scales compared to small- and large-time scales.

Spatiotemporal characteristics of air pollutants and their associated health risks in '2+26' cities in China during 2016-2020 heating seasons

To understand characteristics of air pollutants and their associated health risks in recent heating seasons in China, ambient monitoring data of six air pollutants in '2 + 26' cities in Beijing-Tianjin-Hebei and its surrounding areas (known as the BTH2+26 cities) during 2016-2020 heating seasons was analyzed. Results show that daily average concentrations of PM2.5, PM10, SO2, NO2, and CO dropped significantly in BTH2+26 cities from the 2016-2017 heating season to 2019-2020 heating season, while 8h O3 increased markedly. During 2016-2020 heating seasons, annual average values of total excess risks (ERtotal) were 2.3% mainly contributed by PM2.5 (54.4%) and PM10 (36.1%). With PM2.5 pollution worsening, PM10 and NO2 were the important contribution factors of the enhanced ERtotal. Higher health-risk based air quality index (HAQI) values were mainly concentrated in the western Hebei and northern Henan. HAQI showed spatial agglomeration effect in four heating seasons. Impact factors of HAQI varied in different heating seasons. These findings can provide useful insights for China to further propose effective control strategies to alleviate air pollution in the future.

Optimization study on the application of induced dust suppression cover in primary crushing station of open-pit mine

Aiming at the problems of large dust production, high dust removal cost and poor dust suppression effect of primary crushing station in open-pit mine, the new type dry device-dust suppression cover was put forward, which induced dust to complete the circular clean movement with closed loop eddy current inside the enclosure by means of pressure balance and closed loop flow. After field application, it was found that the dust suppression effect of the device was not ideal and it was seriously affected by wind. By means of fluid dynamics simulation, the structure of the device was optimized for design and engineering application. The simulation results showed that the optimized device enhanced the overall upward movement trend of the internal air flow, weakened the transverse movement trend of air flow, and blocked the interference of ambient wind, which can effectively inhibit the driving effect of overdraft on dust dispersion. The monitoring results showed that the dust concentration around the optimized device was significantly lower than that before optimization, and the lowest concentration can reach 0.33 mg/m³, which met the requirements of environmental protection emission.

Variations of the urban PM2.5 chemical components and corresponding light extinction for three heating seasons in the Guanzhong Plain, China

In order to investigate the variations of PM_2.5 (particulate matter with an aerodynamic diameter less than 2.5 μm) chemical components responding to the pollution control strategy and their effect on light extinction (b_ext) in the Guanzhong Plain (GZP), the comparisons of urban atmospheric chemical components during the heating seasons were extensively conducted for three years. The average concentration of PM_2.5 decreased significantly from 117.9 ± 57.3 μg m^-3 in the heating season 1 (HS1) to 53.5 ± 31.3 μg m^-3 in the heating season 3 (HS3), which implied that the effective strategies were implemented in recent years. The greatest contribution to PM_2.5 (∼30%) was from Organic matter (OM). The heightened contributions of the secondary inorganic ions (SNA, including NO₃^-, SO₄^2-, and NH₄⁺) to PM_2.5 were observed with the values of 34% (HS1), 41% (HS2), and 42% (HS3), respectively. The increased percentages of NO₃^- contributions indicated that the emission of NOx should be received special attention in the GZP. The comparison of PM_2.5 chemical compositions and implications across major regions of China and the globe were investigated. NH₄NO₃ was the most important contributor to b_ext in three heating seasons. The average b_ext was decreased from 694.3 ± 399.1 Mm^-1 (HS1) to 359.3 ± 202.3 Mm^-1 (HS3). PM_2.5 had a threshold concentration of 75 μg m^-3, 64 μg m^-3, and 57 μg m^-3 corresponding to the visual range (VR) < 10 km in HS1, HS2, and HS3, respectively. The enhanced impacts of the oxidant on PM_2.5 and O₃ were observed based on the long-term variations in PM_2.5 and OX (Oxidant, the sum of O₃ and NO₂ mixing ratios) over the five heating seasons and PM_2.5 and O₃ over six summers from 2016 to 2021. The importance of coordinated control of PM_2.5 and O₃ was also investigated in the GZP.

Exposure to fine particulate matter constituents and cognitive function performance, potential mediation by sleep quality: A multicenter study among Chinese adults aged 40-89 years

Although exposure to fine particulate matter (PM_2.5) has been associated with cognitive decline, little is known about which PM_2.5 constituents are more harmful. Recent study on the association between PM_2.5 and sleep quality prompted us to propose that sleep quality may mediate the adverse effects of PM_2.5 components on cognitive decline. Understanding the association between PM_2.5 constituents and cognitive function, as well as the mediating role of sleep quality provides a future intervention target for improving cognitive function. Using data involving 1834 participants from a multicenter cross-sectional study in nine cities of the Beijing-Tianjin-Hebei (BTH) region in China, we undertook multivariable linear regression analyses to quantify the association of annual moving-average PM_2.5 and its chemical constituents with cognitive function and to assess the modifying role of exposure characteristic in this association. Besides, we examined the extent to which this association of PM_2.5 constituents with cognitive function was mediated via sleep quality by a mediation analysis. We observed significantly negative associations between an increase of one interquartile range increase in PM_2.5 [-0.876 (95 % CI: -1.205, -0.548)], organic carbon [-0.481 (95 % CI: -0.744, -0.219)], potassium [-0.344 (95 % CI: -0.530, -0.157)], iron [-0.468 (95 % CI: -0.646, -0.291)], and ammonium ion [-0.125 (95 % CI: -0.197, -0.052)] and cognitive decline. However, we didn't find any individual components more harmful than PM_2.5. Poor sleep quality partially mediated the estimated associations, which were explained ranging from 2.28 % to 11.99 %. Stratification analyses showed that people living in areas with lower greenspace were more susceptible to specific PM_2.5 components. Our study suggests that the adverse effect of suffering from PM_2.5 components is more pronounced among individuals with poor sleep quality, amplifying environmental inequalities in health. Besides reducing environmental pollution, improving sleep quality may be another measure worth considering to improve cognition if our research is confirmed in the future.

Dramatic changes in aerosol composition during the 2016-2020 heating seasons in Beijing-Tianjin-Hebei region and its surrounding areas: The role of primary pollutants and secondary aerosol formation

With the implementation of a series of air pollution mitigation strategies during the past decade, great air quality improvements have been observed in the BTH region. Despite of significant decreases in gaseous pollutants, such as SO₂ and NO₂, the enhancement of secondary aerosol formation was observed. NO₃^- has surpassed SO₄^2- and OM to become the dominant PM_2.5 component. We find that the reduction of POC mainly dominated the decreasing trend of OC. As for secondary inorganic components, the key processes or factors controlling the spatial-temporal variation characteristics were different. The areas with large SO₄^2- concentrations corresponded well to those with high SO₂ concentrations, while the synchronized NO₃^- better followed spatial patterns in O₃ than NO₂. From 2016 to 2020, the response of SO₄^2- to SO₂ was close to a linear function, while the reaction of NO₃^- to the decrease of NO₂ displayed nonlinear behavior. Such different relationships indicated that SO₄^2- was predominantly controlled by SO₂, while NO₃^- was not only related to NO₂ but also determined by the secondary conversion process. The ratios of SO₄^2-, NO₃^-, NH₄⁺, and OC to EC between 2016 and 2020 were generally higher than 1 in typical BTH cities, and the ratio of NO₃^- to EC was exceptionally high, with a range reaching up to 200 %. Besides, this ratio coincided well with the enhancement of O_x, indicating the potential role of O_x to secondary NO₃^- formation. The diurnal cycle of NO₃^-, O₃, and NO₂ concentration change rate indicated that the relative increase of O₃ during nighttime may offset the effectiveness of NO_X emission reduction. This study provided observational evidence of enhanced secondary NO₃^- formation with the rising trend of atmospheric oxidation and emphasized the importance of nighttime chemistry for NO₃^- formation in the BTH region.

Significant decline in aerosols in the mixing layer in Beijing from 2015 to 2020: Effects of regional coordinated air pollution control

Beijing's air quality has improved significantly since the implementation of the Air Pollution Prevention and Control Action Plan in 2013, but the local and regional contributions to this improvement have rarely been studied. Here, the vertical profile of the atmospheric backscattering coefficient (ABC) was measured by a ceilometer in Beijing from 2015 to 2020. The results show that the ABC in Beijing decreased the most at ground level from 2015 to 2020, decreasing 51.4%. Interannual variability decreased with height, and no noticeable change was found in the height range above 600 m. The most apparent declines occurred in autumn and winter, with decreases greater than 55.0%, and the minimum decrease occurred in summer, with a reduction of only 20.0%. To analyze the reasons for the autumn and winter declines, we divided the whole day into four periods according to the evolution characteristics of the atmospheric boundary layer. The significant decrease in the backscattering coefficient near the ground during the daytime confirms the effect of local emission reductions. In contrast, the considerable decreases in the backscattering coefficient measured at different heights in the midday mixing layer demonstrate the contribution of regional transport reduction. The above research results confirm the importance of regional coordinated air pollution control.

Decade-long trends in chemical component properties of PM2.5 in Beijing, China (2011-2020)

A 10-year-long measurement of water-soluble inorganic ions in PM_2.5 was made in Beijing from June 2011 to December 2020, to investigate the interannual trends of chemical characteristics of PM_2.5 and to provide insights into the future prevention and control of PM_2.5 pollution. From 2011 to 2020, with the implementation of strict air pollution control strategies, significant changes of PM_2.5 have been observed in Beijing, with NO₃^-, SO₄^2- and NH₄⁺ decreasing at rates of 5.10, 8.80 and 7.64% yr^-1 respectively. The percentages of NO₃^- and SO₄^2- under elevated pollution levels were investigated. When PM_2.5 values fell in the range of 0-400 μg m^-3, NO₃^-/ SO₄^2- values were mostly higher than 1 and showed upward trends from 2011 to 2020. However, under extremely heavy haze conditions, SO₄^2- dominated PM_2.5 formation. This result was closely related to the change characteristics of the oxidation ratio of sulfate (SOR), the oxidation ratio of nitrate (NOR) and gaseous precursors under different pollution levels. The change characteristics of NOR and SOR under elevated PM_2.5 levels indicated that the aqueous phase oxidation was the key process driving SO₄^2- formation; while as for NO₃^-, in addition to the availability of NH₄⁺, the atmospheric oxidation capacity made crucial roles. The analysis of typical haze episodes during the past decade indicated that the emission reduction of gaseous pollutants, especially SO₂, made great contributions to the improved PM_2.5 air quality in Beijing. We highlighted that future efforts should focus on enhanced reduction of NO₂ emission and control of atmospheric oxidation capacity to further reduce particulate nitrate formation.

Acute effect of air pollutants' peak-hour concentrations on ischemic stroke hospital admissions among hypertension patients in Beijing, China, from 2014 to 2018

Air pollutants' effect on ischemic stroke (IS) has been widely reported. But the effect of high-level concentrations during people's outdoor periods among hypertension patients was unknown. Peak-hour concentrations were defined considering air pollutants' high concentrations as well as people's outdoor periods. We conducted a time-series study and used the generalized additive model to analyze peak-hour concentrations' acute effect. A total of 315,499 IS patients comorbid with hypertension were admitted to secondary and above hospitals in Beijing from 2014 to 2018. A 10 µg/m³ (CO: 1 mg/m³) increase of the peak-hour concentrations was positively associated with IS hospital admissions among hypertension patients. The maximum effect sizes were as follows: for PM_2.5, 0.17% (95% confidence interval [CI]: 0.10-0.24%) at Lag0 and 0.22% (95% CI: 0.12-0.33%) at Lag0-5; for PM₁₀, 0.09% (95% CI: 0.05-0.13%) at Lag5 and 0.17% (95% CI: 0.09-0.26%) at Lag0-5; for SO₂, 0.87% (95% CI: 0.46-1.29%) at Lag5; for NO₂, 0.83% (95% CI: 0.62-1.04%) at Lag0 and 0.86% (95% CI: 0.59-1.13%) at Lag0-1; for CO 1.23% (95% CI: 0.66-1.80%) at Lag0 and 1.33% (95% CI: 0.33-2.35%) at Lag0-5; for O₃ 0.23% (95% CI: 0.12-0.35%) at Lag0 and 0.20% (95% CI: 0.05-0.34%) at Lag0-1. The effect sizes of PM_2.5, NO₂, and O₃ remained significant after adjusting daily mean. Larger effect sizes were observed for PM_2.5 and PM₁₀ in cool season and for O₃ in warm season. As significant exposure indicators of air pollution, peak-hour concentrations exposure increased the risk of IS hospital admissions among hypertension patients and it is worthy of consideration in relative environmental standard. It is suggested for hypertension patients to avoid outdoor activity during peak hours. More relevant searches are required to further illustrate air pollutant's effect on chronic disease population.

Heavy haze pollution during the COVID-19 lockdown in the Beijing-Tianjin-Hebei region, China

To investigate the characteristics of particulate matter with an aerodynamic diameter less than 2.5 μm (PM_2.5) and its chemical compositions in the Beijing-Tianjin-Hebei (BTH) region of China during the novel coronavirus disease (COVID-19) lockdown, the ground-based data of PM_2.5, trace gases, water-soluble inorganic ions, and organic and elemental carbon were analyzed in three typical cities (Beijing, Tianjin, and Baoding) in the BTH region of China from 5-15 February 2020. The PM_2.5 source apportionment was established by combining the weather research and forecasting model and comprehensive air quality model with extensions (WRF-CAMx). The results showed that the maximum daily PM_2.5 concentration reached the heavy pollution level (>150 μg/m³) in the above three cities. The sum concentration of SO₄^2-, NO₃^- and NH₄⁺ played a dominant position in PM_2.5 chemical compositions of Beijing, Tianjin, and Baoding; secondary transformation of gaseous pollutants contributed significantly to PM_2.5 generation, and the secondary transformation was enhanced as the increased PM_2.5 concentrations. The results of WRF-CAMx showed obviously inter-transport of PM_2.5 in the BTH region; the contribution of transportation source decreased significantly than previous reports in Beijing, Tianjin, and Baoding during the COVID-19 lockdown; but the contribution of industrial and residential emission sources increased significantly with the increase of PM_2.5 concentration, and industry emission sources contributed the most to PM_2.5 concentrations. Therefore, control policies should be devoted to reducing industrial emissions and regional joint control strategies to mitigate haze pollution.

Causes of PM2.5 pollution in an air pollution transport channel city of northern China

To develop effective mitigation policies, a comprehensive understanding of the evolution of the chemical composition, formation mechanisms, and the contribution of sources at different pollution levels is required. PM_2.5 samples were collected for 1 year from August 2016 to August 2017 at an urban site in Zibo, then chemical compositions were analyzed. Secondary inorganic aerosols (SNA), anthropogenic minerals (MIN), and organic matter (OM) were the most abundant components of PM_2.5, but only the mass fraction of SNA increased as the pollution evolved, implying that PM_2.5 pollution was caused by the formation of secondary aerosols, especially nitrate. A more intense secondary transformation was found in the heating season (from November 15, 2016, to March 14, 2017), and a faster secondary conversion of nitrate than sulfate was discovered as the pollution level increased. The formation of sulfate was dominated by heterogeneous reactions. High relative humidity (RH) in polluted periods accelerated the formation of sulfate, and high temperature in the non-heating season also promoted the formation of sulfate. Zibo city was under ammonium-rich conditions during polluted periods in both seasons; therefore, nitrate was mainly formed through homogeneous reactions. The liquid water content increased significantly as the pollution levels increased when the RH was above 80%, indicating that the hygroscopic growth of aerosol aggravated the PM_2.5 pollution. Source apportionment showed that PM_2.5 was mainly from secondary aerosol formation, road dust, coal combustion, and vehicle emissions, contributing 36.6%, 16.5%, 14.7%, and 13.1% of PM_2.5 mass, respectively. The contribution of secondary aerosol formation increased remarkably with the deterioration of air quality, especially in the heating season.

Composition and sources of particulate matter in the Beijing-Tianjin-Hebei region and its surrounding areas during the heating season

This paper aimed to analyze the composition and pollution sources of particulate matter (PM) in the Beijing-Tianjin-Hebei region and its surrounding areas (henceforth the BTH region) during the heating season to support the mitigation and control of regional air pollution. Manual monitoring data from the China National Environmental Monitoring Network for Atmospheric PM in the BTH region were collected and analyzed during the 2016 and 2018 heating seasons. The positive definite matrix factor analysis (PMF) model was used to analyze the PM sources in BTH cities during the heating season. The main PM components were organic matter (OM), nitrate (NO₃^-), sulfate (SO₄^2-) and ammonium salt (NH₄⁺). Direct emission sources have decreased since 2016, indicating the effectiveness of governmental controls on these sources; however, secondary pollution showed an increasing trend, suggesting control measures should be strengthened. Daily regional average concentrations of OM, SO₄^2-, NH₄⁺, elemental carbon (EC), chloride (Cl^-) and trace elements all showed similar trends. When air quality worsened, the concentrations of the main PM components increased, but trends of change varied among components. In 2018, concentrations of OM and chloride were highest in the Taihang Mountains, and NO₃ concentrations were highest in Anyang, Hebi, Jiaozuo and Xinxiang. The SO₄^2- concentration was highest in the southern section of the Taihang Mountains. The NH₄⁺ and EC concentrations were generally highest in the central and southern regions. The concentration of crustal substances was highest in some cities in the north and central parts of the BTH region. In the 2018 heating season, the pollution level of five transmission channels showed an increasing trend in the Northwest, Southeast, Yanshan, South and Taihang Mountain channels. These findings provide a scientific basis for the continued management of atmospheric PM pollution.

Meteorological Influences on Spatiotemporal Variation of PM2.5 Concentrations in Atmospheric Pollution Transmission Channel Cities of the Beijing–Tianjin–Hebei Region, China

Understanding the spatiotemporal characteristics of PM_2.5 concentrations and identifying their associated meteorological factors can provide useful insight for implementing air pollution interventions. In this study, we used daily air quality monitoring data for 28 air pollution transmission channel cities in the Beijing–Tianjin–Hebei region during 2014–2019 to quantify the relative contributions of meteorological factors on spatiotemporal variation in PM_2.5 concentration by combining time series and spatial perspectives. The results show that annual mean PM_2.5 concentration significantly decreased in 24 of the channel cities from 2014 to 2019, but they all still exceeded the Grade II Chinese Ambient Air Quality Standards (35 μg m⁻³) in 2019. PM_2.5 concentrations exhibited clear spatial agglomeration in the most polluted season, and their spatial pattern changed slightly over time. Meteorological variables accounted for 31.96% of the temporal variation in PM_2.5 concentration among the 28 cities during the study period, with minimum temperature and average relative humidity as the most critical factors. Spatially, atmospheric pressure and maximum temperature played a key role in the distribution of PM_2.5 concentration in spring and summer, whereas the effect of sunshine hours increased greatly in autumn and winter. These findings highlight the importance of future clean air policy making, but also provide a theoretical support for precise forecasting and prevention of PM_2.5 pollution.

NLRP3 inflammasome activation determines the fibrogenic potential of PM2.5 air pollution particles in the lung

Airborne fine particulate matter (PM_2.5) is known to cause respiratory inflammation such as chronic obstructive pulmonary disease and lung fibrosis. NLRP3 inflammasome activation has been implicated in these diseases; however, due to the complexity in PM_2.5 compositions, it is difficult to differentiate the roles of the components in triggering this pathway. We collected eight real-life PM_2.5 samples for a comparative analysis of their effects on NLRP3 inflammasome activation and lung fibrosis. In vitro assays showed that although the PM_2.5 particles did not induce significant cytotoxicity at the dose range of 12.5 to 100 µg/mL, they induced potent TNF-α and IL-1β production in PMA differentiated THP-1 human macrophages and TGF-β1 production in BEAS-2B human bronchial epithelial cells. At the dose of 100 µg/mL, PM_2.5 induced NLRP3 inflammasome activation by inducing lysosomal damage and cathepsin B release, leading to IL-1β production. This was confirmed by using NLRP3- and ASC-deficient cells as well as a cathepsin B inhibitor, ca-074 ME. Administration of PM_2.5 via oropharyngeal aspiration at 2 mg/kg induced significant TGF-β1 production in the bronchoalveolar lavage fluid and collagen deposition in the lung at 21 days post-exposure, suggesting PM_2.5 has the potential to induce pulmonary fibrosis. The ranking of in vitro IL-1β production correlates well with the in vivo total cell count, TGF-β1 production, and collagen deposition. In summary, we demonstrate that the PM_2.5 is capable of inducing NLRP3 inflammasome activation, which triggers a series of cellular responses in the lung to induce fibrosis.

Does the "Blue Sky Defense War Policy" Paint the Sky Blue?-A Case Study of Beijing-Tianjin-Hebei Region, China

Improving air quality is an urgent task for the Beijing-Tianjin-Hebei (BTH) region in China. In 2018, utilizing 365 days' daily concentration data of six air pollutants (including PM_2.5, PM₁₀, SO₂, NO₂, CO and O₃) at 947 air quality grid monitoring points of 13 cities in the BTH region and controlling the meteorological factors, this paper takes the implementation of the Blue Sky Defense War (BSDW) policy as a quasi-natural experiment to examine the emission reduction effect of the policy in the BTH region by applying the difference-in-difference method. Results show that the policy leads to the significant reduction of the daily average concentration of PM_2.5, PM₁₀, SO₂, O₃ by -1.951 μg/m³, -3.872 μg/m³, -1.902 μg/m³, -7.882 μg/m³ and CO by -0.014 mg/m³, respectively. The results of the robustness test support the aforementioned conclusions. However, this paper finds that the concentration of NO₂ increases significantly (1.865 μg/m³). In winter heating seasons, the concentration of SO₂, CO and O₃ decrease but PM_2.5, PM₁₀ and NO₂ increase significantly. Besides, resource intensive cities, non-key environmental protection cities and cities in the north of the region have great potential for air pollutant emission reduction. Finally, policy suggestions are recommended; these include setting specific goals at the city level, incorporating more cities into the list of key environmental protection cities, refining the concrete indicators of domestic solid fuel, and encouraging and enforcing clean heating diffusion.

Estimating PM2.5 concentrations via random forest method using satellite, auxiliary, and ground-level station dataset at multiple temporal scales across China in 2017

Fine particulate matter with aerodynamic diameters less than 2.5 μm (PM_2.5) poses adverse impacts on public health and the environment. It is still a great challenge to estimate high-resolution PM_2.5 concentrations at moderate scales. The current study calibrated PM_2.5 concentrations at a 1 km resolution scale using ground-level monitoring data, Aerosol Optical Depth (AOD), meteorological data, and auxiliary data via Random Forest (RF) model across China in 2017. The three ten-folded cross-validations (CV) methods including sample-based, time-based, and spatial-based validation combined with Coefficient Square (R²), Root-Mean-Square Error (RMSE), and Mean Predictive Error (MPE) have been used for validation at different temporal scales in terms of daily, monthly, heating seasonal, and non-heating seasonal. Finally, the distribution map of PM_2.5 concentrations was illustrated based on the RF model. Some findings were achieved. The RF model performed well, with a relatively high sample-based cross-validation R² of 0.74, a low RMSE of 16.29 μg × m^-3, and a small MPE of -0.282 μg × m^-3. Meanwhile, the performance of the RF model in inferring the PM_2.5 concentrations was well at urban scales except for Chengyu (CY). North China, the CY urban agglomeration, and the northwest of China exhibited relatively high PM_2.5 pollution features, especially in the heating season. The robustness of the RF model in the present study outperformed most statistical regression models for calibrating PM_2.5 concentrations. The outcomes can supply an up-to-date scientific dataset for epidemiological and air pollutants exposure risk studies across China.

Influence of urban morphological parameters on the distribution and diffusion of air pollutants: A case study in China

Air pollution has a serious fallout on human health, and the influences of the different urban morphological characteristics on air pollutants cannot be ignored. In this study, the relationship between urban morphology and air quality (wind speed, CO, and PM_2.5) in residential neighborhoods at the meso-microscale was investigated. The changes in the microclimate and pollutant diffusion distribution in the neighborhood under diverse weather conditions were simulated by Computational Fluid Dynamics (CFD). This study identified five key urban morphological parameters (Building Density, Average Building Height, Standard Deviation of Building Height, Mean Building Volume, and Degree of Enclosure) which significantly impacted the diffusion and distribution of pollutants in the neighborhood. The findings of this study suggested that three specific strategies (e.g. volume of a single building should be reduced, DE should be increased) and one comprehensive strategy (the width and height of the single building should be reduced while the number of single buildings should be increased) could be illustrated as an optimized approach of urban planning to relief the air pollution. The result of the combined effects could provide a reference for mitigating air pollution in sustainable urban environments.

Spatial Characteristics of PM2.5 Pollution among Cities and Policy Implication in the Northern Part of the North China Plain

In the recent decade, the North China Plain (NCP) has been among the region’s most heavily polluted by PM2.5 in China. For the nonattainment cities in the NCP, joint pollution control with related cities is highly needed in addition to the emission controls in their own cities. However, as the basis of decision-making, the spatial characteristics of PM2.5 among these cities are still insufficiently revealed. In this work, the spatial characteristics among all nonattainment cities in the northern part of the North China Plain (NNCP) region were revealed based on data mining technologies including clustering, coefficient of divergence (COD), network correlation model, and terrain and meteorology analysis. The results indicate that PM2.5 pollution of cities with a distance of less than 180 km exhibits homogeneity in the NCP region. Especially, the sub-region, composed of Xinxiang, Hebi, Kaifeng, Zhengzhou, and Jiaozuo, was strongly homogeneous and a strong correlation exists among them. Compared with spring and summer, much stronger correlations of PM2.5 between cities were found in autumn and winter, indicating a strong need for joint prevention and control during these periods. All nonattainment cities in this region were divided into city-clusters, depending on the seasons and pollution levels to further helping to reduce their PM2.5 concentrations effectively. Air stagnation index (ASI) analysis indicates that the strong correlations between cities in autumn were more attributed to the transport impacts than those in winter, even though there were higher PM2.5 concentrations in winter. These results provided an insight into joint prevention and control of pollution in the NCP region.

Depression and Anxiety Associated with Exposure to Fine Particulate Matter Constituents: A Cross-Sectional Study in North China

The association between fine particulate matter (PM_2.5) exposure and mental disorders is attracting increasing attention, but the roles of specific PM_2.5 chemical constituents have yet to be explored. We conducted a multicenter cross-sectional study in nine cities located in the Beijing-Tianjin-Hebei region in China to assess the effects of PM_2.5 and chemical constituents on depression and anxiety. The Patient Health Questionnaire-9 (PHQ-9) and Generalized Anxiety Disorder (GAD-7) scale were used to quantify the depression and anxiety status, atmospheric monitoring data from fixed stations was used to calculate exposure concentrations. We performed multiple logistic regression models to assess the associations of PM_2.5 chemical constituents exposure over the preceding 2 weeks with depression and anxiety. Overall, anxiety and depression were significantly associated with organic carbon (OC), elemental carbon (EC), copper (Cu), cadmium (Cd), nickel (Ni), and zinc (Zn). Subgroup analysis showed a stronger effect of PM_2.5 constituents on depression during the heating period. This study provide evidence for the possible link between PM_2.5 constituents and mental disorders among middle-aged and elderly Chinese adults, which requires further validation of the causal correlation. Our findings support the need for a stricter regulation on emissions of certain specific constituents, in addition to targeting control of total PM_2.5 emission concentration.

Ambient air pollution and respiratory bacterial infections, a troubling association: epidemiology, underlying mechanisms, and future challenges

The World Health Organization attributed more than four million premature deaths to ambient air pollution in 2016. Numerous epidemiologic studies demonstrate that acute respiratory tract infections and exacerbations of pre-existing chronic airway diseases can result from exposure to ambient (outdoor) air pollution. In this context, the atmosphere contains both chemical and microbial pollutants (bioaerosols), whose impact on human health remains unclear. Therefore, this review: summarises the findings from recent studies on the association between exposure to air pollutants-especially particulate matter and ozone-and onset or exacerbation of respiratory infections (e.g. pneumonia, cystic fibrosis lung infection, and tuberculosis); discusses the mechanisms underlying the relationship between air pollution and respiratory bacterial infections, which is necessary to define prevention and treatment strategies; demonstrates the relevance of air pollution modelling in investigating and preventing the impact of exposure to air pollutants on human health; and outlines future actions required to improve air quality and reduce morbidity and mortality related to air pollution.