Spatial and temporal variation of particulate matter and gaseous pollutants in 26 cities in China

Ambient ozone and ovarian reserve in Chinese women of reproductive age: Identifying susceptible exposure windows

Little is known about the association of ambient ozone with ovarian reserve. Based on a retrospective cohort study of 6008 women who attended a fertility center in Hubei, China, during 2018-2021, we estimated ozone exposure levels by calculating averages during the development of follicles (2-month [W1], 4-month [W2], 6-month [W3]) and 1-year before measurement (W4) according to Tracking Air Pollution in China database. We used multivariate logistic regression and linear regression models to investigate association of ozone exposure with anti-müllerian hormone (AMH), the preferred indicator of ovarian reserve. Each 10 μg/m3 increases in ozone were associated with 2.34% (0.68%, 3.97%), 2.08% (0.10%, 4.01%), 4.20% (1.67%, 6.67%), and 8.91% (5.79%, 11.93%) decreased AMH levels during W1-W4; AMH levels decreased by 15.85%, 11.90%, 16.92% in the fourth quartile during W1, W3, and W4 when comparing the extreme quartile, with significant exposure-response relationships during W4 (P < 0.05). Ozone exposure during W1 was positively associated with low AMH. Additionally, we detected significant effect modification by age, body mass index, and temperature in ozone-associated decreased AMH levels. Our findings highlight the potential adverse impact of ozone pollution on female ovarian reserve, especially during the secondary to small antral follicle stage and 1-year before measurement.

Fine particulate matter and its constituent on ovarian reserve: Identifying susceptible windows of exposure

BACKGROUND

Little is known about the associations of exposure to fine particulate matter (PM2.5) and its constituents with ovarian reserve, and the potential susceptible window of exposure remains unclear.

METHODS

We performed a retrospective cohort study of 5189 women who attended a fertility center in Hubei, China, during 2019-2022, and estimated concentrations of PM2.5 and its major constituents during the development of follicles (4th-6th month [W1], 0-4th month [W2], 0-6th month [W3]) and 1-year before measurement (W4) based on Tracking Air Pollution in China database. We used multivariable linear regression and logistic regression models to examine the associations of PM2.5 and its constituent exposures with anti-Müllerian hormone (AMH), the preferred indicator of ovarian reserve.

RESULTS

We observed significantly decreased AMH levels associated with increasing PM2.5 concentrations, with the percent changes (95 % confidence intervals [CIs]) of 1.99 % (0.24 %-3.71 %) during W1 and 3.99 % (0.74 %-7.15 %) during W4 for per 10 μg/m3 increases in PM2.5.When PM2.5 exposure levels were equal to 50th percentile (32.6-42.3 μg/m3) or more, monotonically decreased AMH levels and increased risks of low AMH were seen with increasing PM2.5 concentrations during W1 and W4 (P < 0.05). Black carbon (BC), ammonium (NH4+), nitrate (NO3-), and organic matter (OM) during W1, and NH4+, NO3-, as well as sulfate (SO42-) during W4 were significantly associated with decreased AMH. Moreover, PM2.5 and SO42- exposures during W4 were positively associated with low AMH. Additionally, the associations were stronger among women aged <35 years, lived in urban regions, or measured AMH in cold-season (P for interaction <0.05).

CONCLUSION

PM2.5 and specific chemical components (particularly NH4+, NO3-, and SO42-) exposure during the secondary to antral follicle stage and 1-year before measurement were associated with diminished ovarian reserve (DOR), indicating the adverse impact of PM2.5 and its constituent exposures on female reproductive potential.

Rural-Urban Disparities in Multimorbidity Associated With Climate Change and Air Pollution: A Longitudinal Analysis Among Chinese Adults Aged 45

Background and Objectives

Chronic conditions and multimorbidity are increasing worldwide. Yet, understanding the relationship between climate change, air pollution, and longitudinal changes in multimorbidity is limited. Here, we examined the effects of sociodemographic and environmental risk factors in multimorbidity among adults aged 45+ and compared the rural-urban disparities in multimorbidity.

Research Design and Methods

Data on the number of chronic conditions (up to 14), sociodemographic, and environmental factors were collected in 4 waves of the China Health and Retirement Longitudinal Study (2011-2018), linked with the full-coverage particulate matter 2.5 (PM2.5) concentration data set (2000-2018) and temperature records (2000-2018). Air pollution was assessed by the moving average of PM2.5 concentrations in 1, 2, 3, 4, and 5 years; temperature was measured by 1-, 2-, 3-, 4-, and 5-year moving average and their corresponding coefficients of variation. We used the growth curve modeling approach to examine the relationship between climate change, air pollution, and multimorbidity, and conducted a set of stratified analyses to study the rural-urban disparities in multimorbidity related to temperature and PM2.5 exposure.

Results

We found the higher PM2.5 concentrations and rising temperature were associated with higher multimorbidity, especially in the longer period. Stratified analyses further show the rural-urban disparity in multimorbidity: Rural respondents have a higher prevalence of multimorbidity related to rising temperature, whereas PM2.5-related multimorbidity is more severe among urban ones. We also found temperature is more harmful to multimorbidity than PM2.5 exposure, but PM2.5 exposure or temperature is not associated with the rate of multimorbidity increase with age.

Discussion and Implications

Our findings indicate that there is a significant relationship between climate change, air pollution, and multimorbidity, but this relationship is not equally distributed in the rural-urban settings in China. The findings highlight the importance of planning interventions and policies to deal with rising temperature and air pollution, especially for rural individuals.

Effects of shared governance and cost redistribution on air pollution control: a study of game theory-based cooperation

This study seeks cost-effective strategies for PM2.5 reduction to generate insights into minimizing pollution abatement costs subject to different scenarios. This study theorizes that the cooperation of PM2.5 abatement has potential gains for participants and develop an empirical way to compare the costs and efficiency of PM2.5 abatement involving the variation of environmental conditions. This study revises the cooperative game model in the context of threshold effects using data obtained from the Beijing-Tianjin-Hebei metropolitan cluster in China. In general, the results support the key assertion that cooperation in the metropolitan cluster plays a vital role in optimizing the efficiency and costs of PM2.5 abatement. In addition to extending the application of the revised model, this study provides a way to estimate the costs and the mitigation benefits of meeting the pollution targets for each coparticipant and take the scenario of multiparty cooperation into account as well as the scenarios involving other types of pollutants. The empirical findings have important policy implications for regional shared governance, decentralization, and resource reallocation. Economic incentive-based shared governance and cost reallocation work better than traditional regulations.

Effects of anthropogenic precursor emissions and meteorological conditions on PM2.5 concentrations over the "2+26" cities of northern China

Elucidating the characteristics and influencing mechanisms of PM_2.5 concentrations is the premise and key to the precise prevention and control of air pollution. However, the temporal and spatial heterogeneity of PM_2.5 concentrations and its driving mechanism are complex and need to be further analyzed. We analyzed the temporal and spatial variations of PM_2.5 concentrations in the "2 + 26" cities from 2015 to 2021, and quantified the influence of meteorological factors and anthropogenic emissions and their interactions on PM_2.5 concentrations based on geographic detector model. We find the inter-annual and inter-season PM_2.5 concentrations show downward trend from 2015 to 2021, and the inter-month PM_2.5 concentrations present a U-shaped distribution. The PM_2.5 concentrations in the "2 + 26" cities manifest a spatial distribution pattern of high in the south and low in the north, and high in the middle and low in the surroundings. Meteorological conditions have stronger effects on PM_2.5 concentrations than anthropogenic emissions, and planetary boundary layer height and temperature are the two main driving factors at the annual scale. On the seasonal scale, sunshine duration is the dominant factor of PM_2.5 concentrations in summer and autumn, and planetary boundary layer height is the dominant factor of PM_2.5 concentrations in winter. The effect of anthropogenic emissions on PM_2.5 concentration is higher in winter and spring than in summer and autumn, and ammonia and ozone have stronger effects on PM_2.5 concentrations than other anthropogenic emissions. Interactions between the factors significantly enhance the PM_2.5 concentrations. The interactions between planetary boundary layer height and other impacting factors play dominant roles on PM_2.5 concentrations at annual scale and in winter. Our results not only provide crucial information for further developing air quality policies of the "2 + 26" cities, but also bear out several important implications for clean air policies in China and other regions of the world.

Association and interaction of O3 and NO2 with emergency room visits for respiratory diseases in Beijing, China: a time-series study

BACKGROUND

Ozone (O₃) and nitrogen dioxide (NO₂) are the two main gaseous pollutants in the atmosphere that act as oxidants. Their short-term effects and interaction on emergency room visits (ERVs) for respiratory diseases remain unclear.

METHODS

We conducted a time-series study based on 144,326 ERVs for respiratory diseases of Peking University Third Hospital from 2014 to 2019 in Beijing, China. Generalized additive models with quasi-Poisson regression were performed to analyze the association of O₃, NO₂ and their composite indicators (O_x and O_x^wt) with ERVs for respiratory diseases. An interaction model was further performed to evaluate the interaction between O₃ and NO₂.

RESULTS

Exposure to O₃, NO₂, O_x and O_x^wt was positively associated with ERVs for total respiratory diseases and acute upper respiratory infection (AURI). For instance, a 10 μg/m³ increase in O₃ and NO₂ were associated with 0.93% (95%CI: 0.05%, 1.81%) and 5.87% (95%CI: 3.92%, 7.85%) increase in AURI at lag0-5 days, respectively. Significant linear exposure-response relationships were observed in O_x and O_x^wt over the entire concentration range. In stratification analysis, stronger associations were observed in the group aged < 18 years for both O₃ and NO₂, in the warm season for O₃, but in the cold season for NO₂. In interaction analysis, the effect of O₃ on total respiratory emergency room visits and AURI visits was the strongest at high levels (> 75% quantile) of NO₂ in the < 18 years group.

CONCLUSIONS

Short-term exposure to O₃ and NO₂ was positively associated with ERVs for respiratory diseases, particularly in younger people (< 18 years). This study for the first time demonstrated the synergistic effect of O₃ and NO₂ on respiratory ERVs, and O_x and O_x^wt may be potential proxies.

Associations of PM2.5 intensity and duration with cognitive impairment: A longitudinal analysis of middle-aged and older adults in China

Long-term exposure to air pollution is associated with a higher risk of cognitive impairment; however, the understanding of this association is incomplete. We aimed to explore the relationship between fine particulate matter (PM_2.5) exposure and cognitive function using a prospective cohort of ageing adults, including 19,389 respondents in four waves of the China Health and Retirement Longitudinal Study (CHARLS, 2011-2018) linked with the historical PM_2.5 concentrations (2000-2018) in China. By extending the measurement of PM_2.5 exposure from exposure intensity (averaged PM_2.5 concentrations) to exposure duration (the number of months with higher PM_2.5 concentrations), we employed two linear models, the fixed-effect and mixed-effect linear models, to estimate the associations between PM_2.5 exposure and cognitive impairment, with adjustments for individual and regional covariates. Our findings show that the higher PM_2.5 intensity was associated with worse cognitive function, but the associations were only statistically significant in a longer exposure period (more than one year), especially in the 10-year exposure (Coefficient: -0.13; 95% Confidence Interval: -0.22, -0.04). Similar patterns were seen for fully adjusted models of PM_2.5 duration: a longer duration in PM_2.5 exposure was associated with lower cognitive scores, and the duration with higher cut-off points had stronger effects on cognitive function except for the duration at 75 μg/m³, suggesting a possible coincidence of increasing air pollution and economic development. The stronger exposure to PM_2.5 was associated with poorer cognitive function among Chinese adults, while more work is necessary to explore the causal effect of air pollution, independent of individual and contextual background characteristics.

Spatial and temporal characteristics of air pollutants and their health effects in China during 2019-2020

This work presents the temporal and spatial characteristics of the major air pollutants and their associated health risks in China from 2019 to 2020, by using the monitoring data from 367 cities. The annual average PM_2.5, PM₁₀, NO₂, SO₂, CO, and O₃ concentrations decreased by 10.9%, 13.2%, 9.3%, 10.1%, 9.4%, and 5.5% from 2019 to 2020. National average PM_2.5 concentration in 2020 met the standard of 35 μg/m³, and that of O₃ decreased from 2019. COVID-19 lockdown affected NO₂ level dramatically, yet influences on PM_2.5 and O₃ were less clear-cut. Positive correlations between PM_2.5 and O₃ were found, even in winter in all five key regions, e.g., Jing-Jin-Ji (JJJ), FenWei Plain (FWP), Yangtze River Delta (YRD), Pearl River Delta (PRD) and Chengdu-Chongqing Region (CCR), indicating importance of secondary production for both PM_2.5 and O₃. Large seasonal variability of PM_2.5-SO₂ correlation indicates a varying role of SO₂ to PM_2.5 pollution in different seasons; and generally weak correlations in winter between PM_2.5 and NO₂ or SO₂ reveal the complexity of secondary formation processes to PM_2.5 pollution in winter. Multilinear regression analysis between PM_2.5 and SO₂, NO₂ and CO demonstrates that PM_2.5 is more sensitive to the change of NO₂ than SO₂ in JJJ, FWP, PRD and CCR, suggesting a priority of NO_x emission control for future PM_2.5 reduction. Furthermore, the new World Health Organization Air Quality Guidelines (WHO AQG2021) were adopted to calculate the excess health risks (ER) as well as the health-risk based air quality index (HAQI_WHO) of the pollutants. Such assessment points out the severity of air pollution associated health risks under strict standards: 40.0% of days had HAQI_WHO>100, while only 14.4% days had AQI>100. PM_2.5 ER was generally larger than O₃ ER, but O₃ ER in low PM_2.5 region (PRD) and during summer became more serious. Notably, NO₂ ER became even more important than PM_2.5 due to its strict limit of WHO AQG2021. Overall, our results highlight the increasing importance of O₃ in both air quality evaluation and health risk assessment, and the importance of coordinated mitigation of multiple pollutants (mainly PM_2.5, O₃ and NO₂) in protecting the public health.

Restricted Anthropogenic Activities and Improved Urban Air Quality in China: Evidence from Real-Time and Remotely Sensed Datasets Using Air Quality Zonal Modeling

The study aims to examine the major atmospheric air pollutants such as NO2, CO, O3, PM2.5, PM10, and SO2 to assess the overall air quality using air quality zonal modeling of 15 major cities of China before and after the COVID-19 pandemic period. The spatio-temporal changes in NO2 and other atmospheric pollutants exhibited enormous reduction due to the imposition of a nationwide lockdown. The present study used a 10-day as well as 60-day tropospheric column time-average map of NO2 with spatial resolution 0.25 × 0.25° obtained from the Global Modeling and Assimilation Office, NASA. The air quality zonal model was employed to assess the total NO2 load and its change during the pandemic period for each specific region. Ground surface monitoring data for CO, NO2, O3, PM10, PM2.5, and SO2 including Air Quality Index (AQI) were collected from the Ministry of Environmental Protection of China (MEPC). The results from both datasets demonstrated that NO2 has drastically dropped in all the major cities across China. The concentration of CO, PM10, PM2.5, and SO2 demonstrated a decreasing trend whereas the concentration of O3 increased substantially in all cities after the lockdown effect as observed from real-time monitoring data. Because of the complete shutdown of all industrial activities and vehicular movements, the atmosphere experienced a lower concentration of major pollutants that improves the overall air quality. The regulation of anthropogenic activities due to the COVID-19 pandemic has not only contained the spread of the virus but also facilitated the improvement of the overall air quality. Guangzhou (43%), Harbin (42%), Jinan (33%), and Chengdu (32%) have experienced maximum air quality improving rates, whereas Anshan (7%), Lanzhou (17%), and Xian (25%) exhibited less improved AQI among 15 cities of China during the study period. The government needs to establish an environmental policy framework involving central, provincial, and local governments with stringent laws for environmental protection.

Ambient gaseous pollutants and emergency ambulance calls for all-cause and cause-specific diseases in China: a multicity time-series study

Much attention has been paid to the health effects of ambient particulate matter pollution; the effects of gaseous air pollutants have not been well studied. Emergency ambulance calls (EACs) may provide a better indicator of the acute health effects than the widely used health indicators, such as mortality and hospital admission. We estimated the short-term associations between gaseous air pollutants [nitrogen dioxide (NO₂), sulfur dioxide (SO₂), and ozone (O₃)] and EACs for all-cause, cardiovascular, and respiratory diseases in seven Chinese cities from 2014 to 2019. We used generalized additive models and random-effects meta-analysis to examine the city-specific and pooled associations. Stratified analyses were conducted by age, sex, and season. A total of 1,626,017 EACs were observed for all-cause EACs, including 230,537 from cardiovascular diseases, and 96,483 from respiratory diseases. Statistically significant associations were observed between NO₂ and EACs for all-cause diseases, while the effects of SO₂ were positive, but not statistically significant in most models. No significant relationship was found between O₃ and EACs. Specifically, each 10 μg/m³ increase in the 2-day moving average concentration of NO₂ was associated with a 1.07% [95% confidence interval (CI): 0.40%, 1.76%], 0.76% (95% CI: 0.19%, 1.34%) and 0.06% (95% CI: -1.57%, 1.73%) increase in EACs due to all-cause, cardiovascular and respiratory diseases, respectively. Stratified analysis showed a larger effect of NO₂ on all-cause EACs in the cold season [excess relative risk (ERR): 0.33% (95% CI: 0.05%, 0.60%) for warm season, ERR: 0.77% (95% CI: 0.31%, 1.23%) for cold season]. Our study indicates that acute exposures to NO₂ might be an important trigger of the emergent occurrence of all-cause, cardiovascular and respiratory diseases, and this effect should be of particular concern in the cold season. Further policy development for controlling gaseous air pollution is warranted to reduce the emergent occurrence of cardiopulmonary diseases.

Spatio-Temporal Characteristics of Air Quality Index (AQI) over Northwest China

In recent years, air pollution has become a serious threat, causing adverse health effects and millions of premature deaths in China. This study examines the spatial-temporal characteristics of ambient air quality in five provinces (Shaanxi (SN), Xinjiang (XJ), Gansu (GS), Ningxia (NX), and Qinghai (QH)) of northwest China (NWC) from January 2015 to December 2018. For this purpose, surface-level aerosol pollutants, including particulate matter (PMx, x = 2.5 and 10) and gaseous pollutants (sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), and ozone (O3)) were obtained from China National Environmental Monitoring Center (CNEMC). The results showed that fine particulate matter (PM2.5), coarse particulate matter (PM10), SO2, NO2, and CO decreased by 28.2%, 32.7%, 41.9%, 6.2%, and 27.3%, respectively, while O3 increased by 3.96% in NWC during 2018 as compared with 2015. The particulate matter (PM2.5 and PM10) levels exceeded the Chinese Ambient Air Quality Standards (CAAQS) Grade II standards as well as the WHO recommended Air Quality Guidelines, while SO2 and NO2 complied with the CAAQS Grade II standards in NWC. In addition, the average air quality index (AQI), calculated from ground-based data, improved by 21.3%, the proportion of air quality Class I (0–50) improved by 114.1%, and the number of pollution days decreased by 61.8% in NWC. All the pollutants’ (except ozone) AQI and PM2.5/PM10 ratios showed the highest pollution levels in winter and lowest in summer. AQI was strongly positively correlated with PM2.5, PM10, SO2, NO2, and CO, while negatively correlated with O3. PM10 was the primary pollutant, followed by O3, PM2.5, NO2, CO, and SO2, with different spatial and temporal variations. The proportion of days with PM2.5, PM10, SO2, and CO as the primary pollutants decreased but increased for NO2 and O3. This study provides useful information and a valuable reference for future research on air quality in northwest China.

Effect of ambient air pollutants on in vitro fertilization-embryo transfer pregnancy outcome in Zhengzhou, China

With the acceleration of China's urbanization and industrialization, air pollution has become a major environmental problem. Retrospective data analysis of 6564 patients who underwent IVF-ET in the center for reproductive medicine of the First Affiliated Hospital of Zhengzhou University from 2015 to 2020. Different stages were selected from 90 days before oocyte retrieval to 35 days after transfer and divided into five exposure periods. Multivariate logistic regression was used to analyze the relationship between six ambient air pollutants (PM_2.5, PM₁₀, NO₂, SO₂, CO and O₃) and the IVF-ET pregnancy outcome. The results showed that air pollutants can significantly affect the IVF pregnancy outcome. The harmful effects of ambient air pollutants are more obvious in the patients aged < 35 years, single embryo transfer and cleavage stage embryo transfer.

Temporal and spatial variations of air pollution across China from 2015 to 2018

This study investigated concentrations of PM_2.5, PM₁₀, SO₂, NO₂, CO and O₃, and air quality index (AQI) values across 368 cities in mainland China during 2015-2018. The study further examined relationships of air pollution status with local industrial capacities and vehicle possessions. Strong correlations were found between industrial capacities (coal, pig iron, crude steel and rolled steel) and air pollution levels. Although statistical and significant reductions of PM_2.5, PM₁₀, SO₂, NO₂, CO and AQI values were observed in response to various laws and regulations in industrial sectors, both particle and gaseous pollutants still had annual average concentrations above recommended limits. In order to further reduce air pollution, more efforts can be done to control traffic emissions caused by minicars and heavy trucks, which was revealed after investigating 16 vehicle types. This was also consistent with the apparent air quality improvement during the COVID-19 lockdown period in China in 2020, despite industrial operations being still active at full capacities.

Seasonal Disparity in the Effect of Meteorological Conditions on Air Quality in China Based on Artificial Intelligence

Air contamination is identified with individuals’ wellbeing and furthermore affects the sustainable development of economy and society. This paper gathered the time series data of seven meteorological conditions variables of Beijing city from 1 November 2013 to 31 October 2017 and utilized the generalized regression neural network optimized by the particle swarm optimization algorithm (PSO-GRNN) to explore seasonal disparity in the impacts of mean atmospheric humidity, maximum wind velocity, insolation duration, mean wind velocity and rain precipitation on air quality index (AQI). The results showed that in general, the most significant impacting factor on air quality in Beijing is insolation duration, mean atmospheric humidity, and maximum wind velocity. In spring and autumn, the meteorological diffusion conditions represented by insolation duration and mean atmospheric humidity had a significant effect on air quality. In summer, temperature and wind are the most significant variables influencing air quality in Beijing; the most important reason for air contamination in Beijing in winter is the increase in air humidity and the deterioration of air diffusion condition. This study investigates the seasonal effects of meteorological conditions on air contamination and suggests a new research method for air quality research. In future studies, the impacts of different variables other than meteorological conditions on air quality should be assessed.

Three-Year Variations in Criteria Atmospheric Pollutants and Their Relationship with Rainwater Chemistry in Karst Urban Region, Southwest China

Air pollutants have been investigated in many studies, but the variations of atmospheric pollutants and their relationship with rainwater chemistry are not well studied. In the present study, the criteria atmospheric pollutants in nine monitoring stations and rainwater chemistry were analyzed in karst Guiyang city, since the time when the Chinese Ambient Air Quality Standards (CAAQS, third revision) were published. Based on the three-year daily concentration dataset of SO2, NO2, CO, PM10 and PM2.5, although most of air pollutant concentrations were within the limit of CAAQS III-Grade II standard, the significant spatial variations and relatively heavy pollution were found in downtown Guiyang. Temporally, the average concentrations of almost all air pollutants (except for CO) decreased during three years at all stations. Ratios of PM2.5/PM10 in non- and episode days reflected the different contributions of fine and coarse particles on particulate matter in Guiyang, which was influenced by the potential meteorological factors and source variations. According to the individual air quality index (IAQI), the seasonal variations of air quality level were observed, that is, IAQI values of air pollutants were higher in winter (worst air quality) and lower in summer (best air quality) due to seasonal variations in emission sources. The unique IAQI variations were found during the Chinese Spring Festival. Air pollutant concentrations are also influenced by meteorological parameters, in particular, the rainfall amount. The air pollutants are well scoured by the rainfall process and can significantly affect rainwater chemistry, such as SO42−, NO3−, Mg2+, and Ca2+, which further alters the acidification/alkalization trend of rainwater. The equivalent ratios of rainwater SO42−/NO3− and Mg2+/Ca2+ indicated the significant contribution of fixed emission sources (e.g., coal combustion) and carbonate weathering-influenced particulate matter on rainwater chemistry. These findings provide scientific support for air pollution management and rainwater chemistry-related environmental issues.

Spatial characteristics of the PM2.5/PM10 ratio and its indicative significance regarding air pollution in Hebei Province, China

Particulate matter (PM) is the primary air pollutant in northern China. The PM_2.5/PM₁₀ ratio has been used increasingly as an indicator to reflect anthropogenic PM pollution, but its advantages compared with individual PM_2.5 or PM₁₀ concentrations have not been proven sufficiently by experimental data. By dividing Hebei Province (China) into seven natural ecological regions, this study investigated the spatial characteristics of the PM_2.5/PM₁₀ ratio and its relationships with PM_2.5, PM₁₀, economic density, and wind speed. Results showed that the PM_2.5/PM₁₀ ratio decreased from east to west and from south to north, with an annual average value in 2019 of 0.439-0.559. The characteristics of the spatial variation of the PM_2.5/PM₁₀ ratio were different to those of either PM_2.5 or PM₁₀ concentration, indicating that PM pollution reflected by the PM_2.5/PM₁₀ ratio is not entirely consistent with that by PM_2.5 and PM₁₀ concentrations. In comparison with PM_2.5 or PM₁₀ concentration, the PM_2.5/PM₁₀ ratio had higher (lower) correlation with economic density (wind speed), indicating that the PM_2.5/PM₁₀ ratio is a better indicator used to reflect the intensity of anthropogenic emissions of PM pollutants. According to the characteristics of the spatial variations of the PM_2.5/PM₁₀ ratio and the PM_2.5 and PM₁₀ concentrations, the seven ecological regions of Hebei Province were categorized into four different types of atmospheric PM pollution: "three low regions," "three high regions," "one high and two low regions," and "one low and two high regions." This reflects the comprehensive effect of the intensity of anthropogenic PM emissions and the atmospheric diffusion conditions.

PM1 chemical composition and light absorption properties in urban and rural areas within Sichuan Basin, southwest China

Sichuan Basin is encircled by high mountains and plateaus with the heights ranging from 1 km to 3 km, and is one of the most polluted regions in China. However, the dominant chemical species and light absorption properties of aerosol particles is still not clear in rural areas. Chemical composition in PM₁ (airborne particulate matter with an aerodynamic diameter less than 1 μm) and light-absorbing properties were determined in Chengdu (urban) and Sanbacun (rural) in western Sichuan Basin (WSB), Southwest China. Carbonaceous aerosols and secondary inorganic ions (NH₄⁺, NO₃^- and SO₄^2-) dominate PM₁ pollution, contributing more than 85% to PM₁ mass at WSB. The mean concentrations of organic and elemental carbon (OC, EC), K⁺ and Cl^- are 19.69 μg m^-3, 8.00 μg m^-3, 1.32 μg m^-3, 1.16 μg m^-3 at the rural site, which are 26.2%, 65.3%, 34.7% and 48.7% higher than those at the urban site, respectively. BrC (brown carbon) light absorption coefficient at 405 nm is 63.90 ± 27.81 M m^-1 at the rural site, contributing more than half of total absorption, which is about five times higher than that at urban site (10.43 ± 4.74 M m^-1). Compared with secondary OC, rural BrC light absorption more depends on primary OC from biomass and coal burning. The rural MAE_BrC (BrC mass absorption efficiency) at 405 nm ranges from 0.6 to 5.1 m² g^-1 with mean value of 3.5 ± 0.8 m² g^-1, which is about three times higher than the urban site.

Occurrence, spatial distribution, seasonal variations, potential sources, and inhalation-based health risk assessment of organic/inorganic pollutants in ambient air of Tehran

The present study evaluated the concentrations, spatial distribution, seasonal variations, potential sources, and risk assessment of organic/inorganic pollutants in ambient air of Tehran city. Totally, 180 air samples were taken from 9 sampling stations from March 2018 to March 2019 and were analyzed to determine the concentrations of organic pollutants (BTEX compounds and PM_2.5-bound PAHs) plus inorganic pollutants (PM_2.5-bound metals and asbestos fibers). The results revealed that the mean concentrations of ∑ PAHs, BTEX, ∑ heavy metals, and asbestos fibers were 5.34 ng/m³, 60.55 µg/m³, 8585.12 ng/m³, and 4.13 fiber/ml in the cold season, respectively, and 3.88 ng/m³, 33.86 µg/m³, 5682.61 ng/m³, and 3.21 fiber/ml in the warm season, respectively. Source apportionment of emission of the air pollutants showed that PAHs are emitted from diesel vehicles and industrial activities. BTEX and asbestos are also released mainly by vehicles. The results of the inhalation-based risk assessment indicated that the carcinogenic risk of PAHs, BTEX, and asbestos exceeded the recommended limit by The US environmental protection agency (US EPA) and WHO (1 × 10^-4). The risk of carcinogenesis of heavy metal of lead and chromium also exceeded the recommended limit. Thus, proper management strategies are required to control the concentration of these pollutants in Tehran's ambient air in order to maintain the health of Tehran's citizens.

Air pollution in Germany: Spatio-temporal variations and their driving factors based on continuous data from 2008 to 2018

This study analyzed long-term observational data of particulate matter (PM_2.5, PM₁₀) variability, gaseous pollutants (CO, NO₂, NO_X, SO₂, and O₃), and meteorological factors in 412 fixed monitoring stations from January 2008 to December 2018 in Germany. Based on Hurst index analysis, the trend of atmospheric pollutants in Germany was stable during the research period. The relative correlations of gaseous pollutants and meteorological factors on PM_2.5 and PM₁₀ concentrations were analyzed by Back Propagation Neural Network model, showing that CO and temperature had the greater correlations with PM_2.5 and PM₁₀. Following that, PM_2.5 and PM₁₀ show a strong positive correlation (R² = 0.96, p < 0.01), suggesting that the reduction of PM_2.5 is essential for reducing PM pollution and enhancing air quality in Germany. Based on typical PM₁₀/CO ratios obtained under ideal weather conditions, it is conducive to roughly estimate the contribution of natural sources. In winter, the earth's crust contributed about 20.1% to PM₁₀. Taken together, exploring the prediction methods and analyzing the characteristic variation of pollutants will contribute an essential implication for air quality control in Germany.

Impact of SARS-CoV-2 on Ambient Air Quality in Northwest China (NWC)

SARS-CoV-2 was discovered in Wuhan (Hubei) in late 2019 and covered the globe by March 2020. To prevent the spread of the SARS-CoV-2 outbreak, China imposed a countrywide lockdown that significantly improved the air quality. To investigate the collective effect of SARS-CoV-2 on air quality, we analyzed the ambient air quality in five provinces of northwest China (NWC): Shaanxi (SN), Xinjiang (XJ), Gansu (GS), Ningxia (NX) and Qinghai (QH), from January 2019 to December 2020. For this purpose, fine particulate matter (PM2.5), coarse particulate matter (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), and ozone (O3) were obtained from the China National Environmental Monitoring Center (CNEMC). In 2020, PM2.5, PM10, SO2, NO2, CO, and O3 improved by 2.72%, 5.31%, 7.93%, 8.40%, 8.47%, and 2.15%, respectively, as compared with 2019. The PM2.5 failed to comply in SN and XJ; PM10 failed to comply in SN, XJ, and NX with CAAQS Grade II standards (35 µg/m3, 70 µg/m3, annual mean). In a seasonal variation, all the pollutants experienced significant spatial and temporal distribution, e.g., highest in winter and lowest in summer, except O3. Moreover, the average air quality index (AQI) improved by 4.70%, with the highest improvement in SN followed by QH, GS, XJ, and NX. AQI improved in all seasons; significant improvement occurred in winter (December to February) and spring (March to May) when lockdowns, industrial closure etc. were at their peak. The proportion of air quality Class I improved by 32.14%, and the number of days with PM2.5, SO2, and NO2 as primary pollutants decreased while they increased for PM10, CO, and O3 in 2020. This study indicates a significant association between air quality improvement and the prevalence of SARS-CoV-2 in 2020.

Analysis of Spatio-Temporal Variation Characteristics of Main Air Pollutants in Shijiazhuang City

Air pollution has become one of the important concerns of environmental pollution in the Beijing–Tianjin–Hebei region. As an important city in Beijing–Tianjin–Hebei, Shijiazhuang has long been ranked in the bottom ten in terms of air quality in the country. In order to effectively grasp the influencing factors and current distribution of air pollution in Shijiazhuang City, this paper collects data on the top air pollutants in Shijiazhuang from 2017 to 2019, analyzes the characteristics of time changes in the region, and uses the Kriging interpolation method to affect the air pollutants in this area. The spatial distribution characteristics are studied. The results show (1) From 2017 to 2019, the environmental quality of Shijiazhuang City showed a decreasing trend except for O3. (2) Seasonal changes show that NO2, PM2.5, and CO show as winter > autumn > spring > summer, PM10, SO2 show as winter > spring > autumn > summer, and O3 concentration changes as summer > spring > autumn > winter. (3) The daily change trends of NO2, SO2, PM10 and PM2.5 are similar, while the change trends of O3 and NO2 are opposite. (4) The correlations between air quality index (AQI) and concentrations suggest that PM10, PM2.5, and CO contribute the most to undesirable pollution levels in this area, while NO2, SO2, and O3 contribute less to undesirable pollution. We have concluded that the particulate pollution in Shijiazhuang City has been effectively controlled, thanks to the relevant measures introduced by the government, but the O3-based compound pollution is gradually increasing, so particulate pollution and O3 pollution need to be treated together. The research results of this article have important practical significance for urban or regional air environment monitoring and prevention.

Impact of weather and emission changes on NO2 concentrations in China during 2014-2019

Nitrogen dioxide (NO₂) is one of the most important air pollutants that highly affect the formation of secondary fine particles and tropospheric ozone. In this study based on hourly NO₂ observations from June 2014 to May 2019 and a regional air quality model (WRF-CMAQ), we comprehensively analyzed the spatiotemporal variations of NO₂ concentrations throughout China and in 12 urban agglomerations (UAs) and quantitatively showed the anthropogenic and meteorological factors controlling the interannual variations (IAVs). The ground observations and tropospheric columns show that high NO₂ concentrations are predominantly concentrated in UAs such as Beijing-Tianjin-Hebei (BTH), the Shandong Peninsula (SP), the Central Plain (CP), Central Shaanxi (CS), and the Yangtze River Delta (YRD). For different UAs, the NO₂ IAVs are different. The NO₂ increased first and then decreased in 2016 or 2017 in BTH, YRD, CS, and Cheng-Yu, and decreased from 2014 to 2019 in Harbin-Changchun, CP, SP, Northern Slope of Tianshan Mountain, and Beibu-Gulf, while increased slightly in the Pearl River Delta (PRD) and Hohhot-Baotou-Erdos-Yulin (HBEY). The NO₂ IAVs were primarily dominated by emission changes. The net wintertime decreases of NO₂ in BTH, Yangtze River Middle-Reach, and PRD were mostly contributed by emission reductions from 2014 to 2018, and the significant increase in the wintertime in HBEY was also dominated by emission changes (93%). Weather conditions also have an important effect on the NO₂ IAVS. In BTH and HBEY, the increases of NO₂ in winter of 2016 are mainly attributed to the unfavorable weather conditions and for the significant decreases in the winter of 2017, the favorable weather conditions also play a very important role. This study provides a basic understanding on the current situation of NO₂ pollution and are helpful for policymakers as well as those interested in the study of tropospheric ozone changes in China and downwind areas.

Spatio-temporal characteristics of air pollutants over Xinjiang, northwestern China

To understand the characteristics of particulate matter (PM) and other air pollutants in Xinjiang, a region with one of the largest sand-shifting deserts in the world and significant natural dust emissions, the concentrations of six air pollutants monitored in 16 cities were analyzed for the period January 2013-June 2019. The annual mean PM_2.5, PM₁₀, SO₂, NO₂, CO, and O₃ concentrations ranged from 51.44 to 59.54 μg m^-3, 128.43-155.28 μg m^-3, 10.99-17.99 μg m^-3, 26.27-31.71 μg m^-3, 1.04-1.32 mg m^-3, and 55.27-65.26 μg m^-3, respectively. The highest PM concentrations were recorded in cities surrounding the Taklimakan Desert during the spring season and caused by higher amounts of wind-blown dust from the desert. Coarse PM (PM_10-2.5) was predominant, particularly during the spring and summer seasons. The highest PM_2.5/PM₁₀ ratio was recorded in most cities during the winter months, indicating the influence of anthropogenic emissions in winters. The annual mean PM_2.5 (PM₁₀) concentrations in the study area exceeded the annual mean guidelines recommended by the World Health Organization (WHO) by a factor of ca. ∼5-6 (∼7-8). Very high ambient PM concentrations were recorded during March 19-22, 2019, that gradually influenced the air quality across four different cities, with daily mean PM_2.5 (PM₁₀) concentrations ∼8-54 (∼26-115) times higher than the WHO guidelines for daily mean concentrations, and the daily mean coarse PM concentration reaching 4.4 mg m^-3. Such high PM_2.5 and PM₁₀ concentrations pose a significant risk to public health. These findings call for the formulation of various policies and action plans, including controlling the land degradation and desertification and reducing the concentrations of PM and other air pollutants in the region.

Air pollution characteristics, health risks, and source analysis in Shanxi Province, China

China is confronting an unprecedented air pollution problem. This study discussed the characteristics of air pollution and its risks on human health and conducted source analysis combined with local development in Shanxi Province in 2016 and 2017. Results demonstrated that the air pollution situation in Shanxi was deteriorating, with Taiyuan, Yangquan, Changzhi, Jincheng, Jinzhong, and Linfen being heavily polluted districts. Particulate matter (PM) was considered the major pollutant, but nitrogen dioxide and ozone showed a dominant trend recently. Furthermore, the health risks evaluated on the basis of a comprehensive air quality index (AAQI) and an aggregated risk index revealed a relatively high-risk level in Shanxi. Among the pollutants, the largest contributor was PM, followed by sulfur dioxide and ozone. Southern Shanxi had the largest pollution level and health risks, whereas Datong was the least polluted region. Source analysis suggested that the main driving forces of air pollution, besides natural factors, were urbanization, population size, civil vehicles, coal-based heavy industries, and high-energy consumption. Therefore, strengthening urban greening, vigorously adjusting and optimizing the industrial structure, and formulating a multi-domain cooperative control regime on air pollution, especially PM and ozone, should be promoted.

The Effects of Fireworks Discharge on Atmospheric PM2.5 Concentration in the Chinese Lunar New Year

Discharging fireworks during the Chinese Lunar New Year celebrations is a deep-rooted custom in China. In this paper, we analyze the effect of this cultural activity on PM2.5 concentration using both ground observations and satellite data. By combining remote sensing data, the problem of uneven spatial distribution of ground monitoring has been compensated, and the research time span has been expanded. The results show that the extensive firework displays on New Year's Eve lead to a remarkable increase in nationwide PM2.5 concentration, which were 159~223% of the average level, indicating the instantaneous effect far exceeds that of any other factor over the whole year. However, the averaged PM2.5 concentrations of the celebration period were 0.99~16.32 μg/m3 lower compared to the average values of the corresponding pre-celebration period and post-celebration period, indicating the sustained effect is not very significant. The implementation of firework prohibition policies can greatly reduce the instantaneous PM2.5 increase, but no obvious air quality improvement is observed over the entire celebration period. Combining these findings and the cultural significance of this activity, we recommend that this custom is actively maintained, using new technologies and scientific governance programs to minimize the negative effects.

Source apportionment of particulate matter based on numerical simulation during a severe pollution period in Tangshan, North China

Facing serious air pollution problems, the Chinese government has taken numerous measures to prevent and control air pollution. Understanding the sources of pollutants is crucial to the prevention of air pollution. Using numerical simulation method, this study analysed the contributions of the total local emissions and local emissions from different sectors (such as industrial, traffic, resident, agricultural, and power plant emissions) to PM_2.5 concentration, backward trajectory, and potential source regions in Tangshan, a typical heavy industrial city in north China. The impact of multi-scale meteorological conditions on source apportionment was investigated. From October 2016 to March 2017, total local emissions accounted for 46.0% of the near-surface PM_2.5 concentration. In terms of emissions from different sectors, local industrial emissions which accounted for 23.1% of the near-surface PM_2.5 concentration in Tangshan, were the most important pollutant source. Agricultural emissions were the second most important source, accounting for 10.3% of the near-surface PM_2.5 concentration. The contributions of emissions from power plants, traffic, residential sources were 2.0%, 3.0%, and 7.2%, respectively. The contributions of total local emissions and emissions from different sectors depended on multi-scale meteorological conditions, and static weather significantly enhanced the contribution of regional transport to the near-surface PM_2.5 concentration. Eight cluster backward trajectories were identified for Tangshan. The PM_2.5 concentration for the 8 cluster trajectories significantly differed. The near-surface PM_2.5 in urban Tangshan (receptor point) was mainly from the local emissions, and another important potential source region was Tianjin. The results of the source apportionment suggested the importance of joint prevention and control of air pollution in some areas where cities or industrial regions are densely distributed.

Concentrations of Four Major Air Pollutants among Ecological Functional Zones in Shenyang, Northeast China

Air pollution is a critical urban environmental issue in China; however, the relationships between air pollutants and ecological functional zones in urban areas are poorly understood. Therefore, we analyzed the spatiotemporal characteristics of four major air pollutants (particulate matter less than or equal to 2.5 µm (PM2.5) and 10 µm (PM10) in diameter, SO2, and NO2) concentrations over five ecological functional zones in Shenyang, Liaoning Province, at hourly, seasonal, and annual scales using data collected from 11 monitoring stations over 2 years. We further assessed the relationships between these pollutants and meteorological conditions and land-use types at the local scale. Peaks in PM, SO2, and NO2 concentrations occurred at 08:00–09:00 and 23:00 in all five zones. Daytime PM concentrations were highest in the industrial zone, and those of SO2 and NO2 were highest in residential areas. All four air pollutants reached their highest concentrations in winter and lowest in summer. The highest mean seasonal PM concentrations were found in the industrial zone, and the highest SO2 and NO2 concentrations were found in residential areas. The mean annual PM and SO2 concentrations decreased in 2017 in all zones, while that of NO2 increased in all zones excluding the cultural zone. The natural reserve zone had the lowest concentrations of all pollutants at all temporal scales. Pollutant concentrations of PM2.5, PM10, SO2, and NO2 were correlated with visibility, and their correlation coefficients are 0.675, 0.579, 0.475, and 0.477. Land coverage with buildings and natural vegetation negatively and positively influence air pollutant concentrations, respectively.

PM2.5 and O3 pollution during 2015-2019 over 367 Chinese cities: Spatiotemporal variations, meteorological and topographical impacts

The strict Clean Air Action Plan has been in place by central and local government in China since 2013 to alleviate haze pollution. In response to implementation of the Plan, daytime PM_2.5 (particulate matter with aerodynamic diameter less than 2.5 μm) showed significant downward trends from 2015 to 2019, with the largest reduction during spring and winter in the North China Plain. Unlike PM_2.5, O₃ (ozone) showed a general increasing trend, reaching 29.7 μg m^-3 on summer afternoons. Increased O₃ and reduced PM_2.5 simultaneously occurred in more than half of Chinese cities, increasing to approximately three-fourths in summer. Declining trends in both PM_2.5 and O₃ occurred in only a few cities, varying from 19.1% of cities in summer to 33.7% in fall. Meteorological variables helped to decrease PM_2.5 and O₃ in some cities and increase PM_2.5 and O₃ in others, which is closely related to terrain. High wind speed and 24 h changing pressure favored PM_2.5 dispersion and dilution, especially in winter in southern China. However, O₃ was mainly affected by 24 h maximum temperature over most cities. Soil temperature was found to be a key factor modulating air pollution. Its impact on PM_2.5 concentrations depended largely on soil depth and seasons; spring and fall soil temperature at 80 cm below the surface had largely negative impacts. Compared with PM_2.5, O₃ was more significantly affected by soil temperature, with the largest impact at 20 cm below the surface and with less seasonal variation.

Time series analysis of meteorological factors and air pollutants and their association with hospital admissions for acute myocardial infarction in Korea

BACKGROUND

We assessed the association between multiple meteorological factors and air pollutants and the number of acute myocardial infarction (AMI) cases using a multi-step process.

METHODS

Daily AMI hospitalizations matched with 16 meteorological factors and air pollutants in 7 metropolitan provinces of the Republic of Korea from 2002 to 2017 were analyzed. We chose the best fit model after conducting the Granger causality (GC) test and examined the daily lag time effect on the orthogonalized impulse response functions. To define dose-response relationships, we performed a time series analysis using multiple generalized additive lag models based on seasons.

RESULTS

A total of 196,762 cases of AMI in patients older than 20 years admitted for hospitalization were identified. The distribution of meteorological factors and air pollutants showed characteristics of a temperate climate. The GC test revealed a complex interaction between meteorological factors, including air pollutants, and AMI. The final selected factors were NO₂ and temperature; these increased the incidence of AMI on lag day 4 during summer (NO₂: population-attributable fraction [PAF], 3.9%; 95% confidence interval [CI], 3.6-4.0; mean temperature: PAF, 3.3%; 95% CI, 2.7-3.9).

CONCLUSIONS

This multi-step time series analysis found that average temperature and NO₂ are the most important factors impacting AMI hospitalizations, specifically during summer. Based on the model, we were able to visualize the effect-time association of meteorological factors and air pollutants and AMI.

Ambient Gaseous Pollutants in an Urban Area in South Africa: Levels and Potential Human Health Risk

Urban air pollution from gaseous pollutants is a growing public health problem in many countries including South Africa. Examining the levels, trends and health risk of exposure to ambient gaseous pollutants will assist in understanding the effectiveness of existing control measures and plan for suitable management strategies. This study determined the concentration levels and non-cancer risk of CO, SO2, NO2, and O3 at an industrial area in Pretoria West, South Africa. We utilised a set of secondary data for CO, NO2, SO2, and O3 that was obtained from a monitoring station. Analysis of the hourly monitored data was done. Their non-cancer risk (HQ) was determined using the human health risk assessment model for different age categories. The annual levels of NO2 (39.442 µg/m3), SO2 (22.464 µg/m3), CO (722.003 µg/m3) and the 8-hour concentration of CO (649.902 µg/m3) and O3 (33.556 µg/m3) did not exceed the South African National Ambient Air Quality Standards for each pollutant. The HQ for each pollutant across exposed groups (except children) was less than 1. This indicates that the recorded levels could not pose non-cancer risk to susceptible individuals.

Severe air pollution events not avoided by reduced anthropogenic activities during COVID-19 outbreak

Due to the pandemic of coronavirus disease 2019 in China, almost all avoidable activities in China are prohibited since Wuhan announced lockdown on January 23, 2020. With reduced activities, severe air pollution events still occurred in the North China Plain, causing discussions regarding why severe air pollution was not avoided. The Community Multi-scale Air Quality model was applied during January 01 to February 12, 2020 to study PM_2.5 changes under emission reduction scenarios. The estimated emission reduction case (Case 3) better reproduced PM_2.5. Compared with the case without emission change (Case 1), Case 3 predicted that PM_2.5 concentrations decreased by up to 20% with absolute decreases of 5.35, 6.37, 9.23, 10.25, 10.30, 12.14, 12.75, 14.41, 18.00 and 30.79 μg/m³ in Guangzhou, Shanghai, Beijing, Shijiazhuang, Tianjin, Jinan, Taiyuan, Xi'an, Zhengzhou, Wuhan, respectively. In high-pollution days with PM_2.5 greater than 75 μg/m³, the reductions of PM_2.5 in Case 3 were 7.78, 9.51, 11.38, 13.42, 13.64, 14.15, 14.42, 16.95 and 22.08 μg/m³ in Shanghai, Jinan, Shijiazhuang, Beijing, Taiyuan, Xi'an, Tianjin, Zhengzhou and Wuhan, respectively. The reductions in emissions of PM_2.5 precursors were ~2 times of that in concentrations, indicating that meteorology was unfavorable during simulation episode. A further analysis shows that benefits of emission reductions were overwhelmed by adverse meteorology and severe air pollution events were not avoided. This study highlights that large emissions reduction in transportation and slight reduction in industrial would not help avoid severe air pollution in China, especially when meteorology is unfavorable. More efforts should be made to completely avoid severe air pollution.

Influence of meteorological conditions on PM2.5 concentrations across China: A review of methodology and mechanism

Air pollution over China has attracted wide interest from public and academic community. PM_2.5 is the primary air pollutant across China. Quantifying interactions between meteorological conditions and PM_2.5 concentrations are essential to understand the variability of PM_2.5 and seek methods to control PM_2.5. Since 2013, the measurement of PM_2.5 has been widely made at 1436 stations across the country and more than 300 papers focusing on PM_2.5-meteorology interactions have been published. This article is a comprehensive review on the meteorological impact on PM_2.5 concentrations_. We start with an introduction of general meteorological conditions and PM_2.5 concentrations across China, and then seasonal and spatial variations of meteorological influences on PM_2.5 concentrations. Next, major methods used to quantify meteorological influences on PM_2.5 concentrations are checked and compared. We find that causality analysis methods are more suitable for extracting the influence of individual meteorological factors whilst statistical models are good at quantifying the overall effect of multiple meteorological factors on PM_2.5 concentrations. Chemical Transport Models (CTMs) have the potential to provide dynamic estimation of PM_2.5 concentrations by considering anthropogenic emissions and the transport and evolution of pollutants. We then comprehensively examine the mechanisms how major meteorological factors may impact the PM_2.5 concentrations, including the dispersion, growth, chemical production, photolysis, and deposition of PM_2.5. The feedback effects of PM_2.5 concentrations on meteorological factors are also carefully examined. Based on this review, suggestions on future research and major meteorological approaches for mitigating PM_2.5 pollution are made finally.

Ambient Air Pollution Exposure Association with Anaemia Prevalence and Haemoglobin Levels in Chinese Older Adults

BACKGROUND

Health effects of air pollution on anaemia have been scarcely studied worldwide. We aimed to explore the associations of long-term exposure to ambient air pollutants with anaemia prevalence and haemoglobin levels in Chinese older adults.

METHODS

We used two-level linear regression models and modified Poisson regression with robust error variance to examine the associations of particulate matter (PM) and nitrogen dioxide (NO₂) on haemoglobin concentrations and the prevalence of anaemia, respectively, among 10,611 older Chinese adults enrolled in World Health Organization (WHO) Study on global AGEing and adult health (SAGE) China. The average community exposure to ambient air pollutants (PM with an aerodynamic diameter of 10 μm or less (PM₁₀), 2.5 μm or less (PM_2.5), 1 μm or less (PM₁) and nitrogen dioxide (NO₂)) for each participant was estimated using a satellite-based spatial statistical model. Haemoglobin levels were measured for participants from dried blood spots. The models were controlled for confounders.

RESULTS

All the studied pollutants were significantly associated with increased anaemia prevalence in single pollutant model (e.g., the prevalence ratios associated with an increase in inter quartile range in three years moving average PM₁₀ (1.05; 95% CI: 1.02-1.09), PM_2.5 (1.11; 95% CI: 1.06-1.16), PM₁ (1.13; 95% CI: 1.06-1.20) and NO₂ (1.42; 95% CI: 1.34-1.49), respectively. These air pollutants were also associated with lower concentrations of haemoglobin: PM₁₀ (-0.53; 95% CI: -0.67, -0.38); PM_2.5 (-0.52; 95% CI: -0.71, -0.33); PM₁ (-0.55; 95% CI: -0.69, -0.41); NO₂ (-1.71; 95% CI: -1.85, -1.57) respectively.

CONCLUSIONS

Air pollution exposure was significantly associated with increased prevalence of anaemia and decreased haemoglobin levels in a cohort of older Chinese adults.

Investigating air pollutant concentrations, impact factors, and emission control strategies in western China by using a regional climate-chemistry model

In this study, in situ observations were conducted for six criteria air pollutants (PM_2.5, PM₁₀, SO₂, NO₂, CO, and O₃) at 23 sites in western China for 1 year. Subsequently, the detailed Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) results for the pollutants were determined. The WRF-Chem model provided a clear perspective on the spatiotemporal distribution of air pollutants. High pollutant concentrations were mainly observed over highly populated mega-city regions, such as Sichuan and Guanzhong basins, whereas low concentration levels were observed over the Tibetan Plateau (TP). The TP also showed an increased concentration of O₃. Seasonally, all six pollutants except O₃ exhibited high concentration values during winter and low values during summer. O₃ concentrations exhibited an opposite seasonal variation in low-altitude regions. Unlike other pollutants that exhibited gradually decreasing concentrations with an increase in altitude, O₃ concentrations revealed an increasing trend. Furthermore, NO₂ concentrations gradually increased in the upper atmosphere possibly due to lighting and stratospheric transmission. Atmospheric pollution is closely related to emissions and meteorological variations in western China. Meteorological conditions in the summer are conducive to pollutant dispersion and wet scavenging; however, unfavourable weather conditions (high pressure as well as a low planetary boundary layer height and precipitation level) in the winter can further worsen air pollution. Atmospheric pollutants from various emission sectors generally exhibited varying monthly profiles. In six typical cities, pollutants were positively correlated with multiple emission sources except for industrial emissions. Further sensitivity simulations indicated that eliminating residential emissions resulted in the largest decrease (up to 70%) in PM_2.5 and PM₁₀ concentrations. The most significant reductions in the concentrations of SO₂ and NO₂ were achieved by eliminating industrial and transportation emissions, respectively. The outcomes of this study could be helpful for future studies on pollution formation mechanisms as well as environmental and health risk assessments in western China.

The Effect of Socioeconomic Factors on Spatiotemporal Patterns of PM2.5 Concentration in Beijing-Tianjin-Hebei Region and Surrounding Areas

The study investigated the spatiotemporal evolution of PM2.5 concentration in the Beijing-Tianjin-Hebei region and surrounding areas during 2015-2017, and then analyzed its socioeconomic determinants. First, an estimation model considering spatiotemporal heterogeneous relationships was developed to accurately estimate the spatial distribution of PM2.5 concentration. Additionally, socioeconomic determinants of PM2.5 concentration were analyzed using a spatial panel Dubin model, which aimed to improve the robustness of the model estimation. The results demonstrated that: (1) The proposed model significantly increased the estimation accuracy of PM2.5 concentration. The mean absolute error and root-mean-square error were 9.21 μg/m3 and 13.10 μg/m3, respectively. (2) PM2.5 concentration in the study area exhibited significant spatiotemporal changes. Although the PM2.5 concentration has declined year by year, it still exceeded national environmental air quality standards. (3) The per capita GDP, urbanization rate and number of industrial enterprises above the designated size were the key factors affecting the spatiotemporal distribution of PM2.5 concentration. This study provided scientific references for comprehensive PM2.5 pollution control in the study area.

Spatio-temporal patterns of air pollution in China from 2015 to 2018 and implications for health risks

China has been seriously affected by particulate matter (PM) and gaseous pollutants in the atmosphere. In this study, we systematically analyse the spatio-temporal patterns of PM_2.5, PM₁₀, SO₂, CO, NO₂, and O₃ and the associated health risks, using data collected from 1498 national air quality monitoring sites. An analysis of the averaged data from all the sites indicated that, from 2015 to 2018, annual mean concentrations of PM_2.5, PM₁₀, SO₂ and CO declined by 3.2 μg m^-3, 3.7 μg m^-3, 3.9 μg m^-3, and 0.1 mg m^-3, respectively. In contrast, those of NO₂ and O₃ increased at rates of 0.4 and 3.1 μg m^-3, respectively. Except for O₃, the annual mean concentrations of all pollutants were generally the highest in North China and lowest in the Tibetan Plateau. The concentrations were generally higher in the north of the country than in the south. In all regions of China, the pollutant concentrations were the highest in winter and lowest in summer, except for O₃, which showed an opposite seasonal pattern. Overall, the seasonal mean concentrations of all the pollutants (except for O₃) significantly decreased between the same seasons in 2018 and 2015, whereas the seasonal mean O₃ concentrations generally significantly increased, and/or remained at stable levels in all four seasons except for winter. Diurnal variations of all pollutants (except for O₃) exhibited a bimodal pattern with peaks between 8:00 and 11:00 a.m. and 9:00 and 12:00 p.m., whereas O₃ exhibited a unimodal pattern with maximum values between 5:00 and 7:00 p.m. No significant differences in the daily mean concentrations of all pollutants were found between weekdays and weekends in all regions, except for PM_2.5 and PM₁₀ in Northeast China. In Northwest China and Southeast China, PM_2.5 showed stronger correlations with NO₂ relative to SO₂, suggesting that NO_x emission control may be more effective than SO₂ emission control for alleviating PM_2.5 formation. Compared with 2015, the total PM_2.5-attributable mortality, number of respiratory and cardiovascular diseases, and incidence of chronic bronchitis decreased overall by 23.4%-26.9% in 2018. In contrast, for O₃-attributable deaths, there was an increase of 18.9%. Our study not only improves the understanding of the spatial and temporal patterns of air pollutants in China, but also highlights that synchronous control of PM_2.5 and O₃ pollution should be implemented to achieve dual benefits in protecting human health.

Unexpected rise of ozone in urban and rural areas, and sulfur dioxide in rural areas during the coronavirus city lockdown in Hangzhou, China: implications for air quality

The outbreak of coronavirus named COVID-19, initially identified in Wuhan, China in December 2019, has spread rapidly at the global scale. Most countries have rapidly stopped almost all activities including industry, services and transportation of goods and people, thus decreasing air pollution in an unprecedented way, and providing a unique opportunity to study air pollutants. While satellite data have provided visual evidence for the global reduction in air pollution such as nitrogen dioxide (NO₂) worldwide, precise and quantitative information is missing at the local scale. Here we studied changes in particulate matter (PM_2.5, PM₁₀), carbon monoxide (CO), NO₂, sulfur dioxide (SO₂) and ozone (O₃) at 10 urban sites in Hangzhou, a city of 7.03 million inhabitants, and at 1 rural site, before city lockdown, January 1-23, during city lockdown, January 24-February 15, and during resumption, February 16-28, in 2020. Results show that city lockdown induced a sharp decrease in PM_2.5, PM₁₀, CO, and NO₂ concentrations at both urban and rural sites. The NO₂ decrease is explained by reduction in traffic emissions in the urban areas, and by lower regional transport in rural areas during lockdown, as expected. SO₂ concentrations decreased from 6.3 to 5.3 μg m^-3 in the city, but increased surprisingly from 4.7 to 5.8 μg m^-3 at the rural site: this increase is attributed both to higher coal consumption for heating and emissions from traditional fireworks of the Spring Eve and Lantern Festivals during lockdown. Unexpectedly, O₃ concentrations increased by 145% from 24.6 to 60.6 μg m^-3 in the urban area, and from 42.0 to 62.9 μg m^-3 in the rural area during the lockdown. This finding is explained by the weakening of chemical titration of O₃ by NO due to reductions of NO_x fresh emissions during the non-photochemical reaction period from 20:00 PM to 9:00 AM (local time). During the lockdown, compared to the same period in 2019, the daily average concentrations in the city decreased by 42.7% for PM_2.5, 47.9% for PM₁₀, 28.6% for SO₂, 22.3% for CO and 58.4% for NO₂, which is obviously explained by the absence of city activities. Overall, we observed not only the expected reduction in some atmospheric pollutants (PM, SO₂, CO, NO₂), but also unexpected increases in SO₂ in the rural areas and of ozone (O₃) in both urban and rural areas, the latter being paradoxically due to the reduction in nitrogen oxide levels. In other words, the city lockdown has improved air quality by reducing PM_2.5, PM₁₀, CO, and NO₂, but has also decreased air quality by augmenting O₃ and SO₂.

Spatiotemporal Variations of Particulate and Gaseous Pollutants and Their Relations to Meteorological Parameters: The Case of Xiangyang, China

High air pollution levels have become a nationwide problem in China, but limited attention has been paid to prefecture-level cities. Furthermore, different time resolutions between air pollutant level data and meteorological parameters used in many previous studies can lead to biased results. Supported by synchronous measurements of air pollutants and meteorological parameters, including PM_2.5, PM₁₀, total suspended particles (TSP), CO, NO₂, O₃, SO₂, temperature, relative humidity, wind speed and direction, at 16 urban sites in Xiangyang, China, from 1 March 2018 to 28 February 2019, this paper: (1) analyzes the overall air quality using an air quality index (AQI); (2) captures spatial dynamics of air pollutants with pollution point source data; (3) characterizes pollution variations at seasonal, day-of-week and diurnal timescales; (4) detects weekend effects and holiday (Chinese New Year and National Day holidays) effects from a statistical point of view; (5) establishes relationships between air pollutants and meteorological parameters. The principal results are as follows: (1) PM_2.5 and PM₁₀ act as primary pollutants all year round and O₃ loses its primary pollutant position after November; (2) automobile manufacture contributes to more particulate pollutants while chemical plants produce more gaseous pollutants. TSP concentration is related to on-going construction and road sprinkler operations help alleviate it; (3) an unclear weekend effect for all air pollutants is confirmed; (4) celebration activities for the Chinese New Year bring distinctly increased concentrations of SO₂ and thereby enhance secondary particulate pollutants; (5) relative humidity and wind speed, respectively, have strong negative correlations with coarse particles and fine particles. Temperature positively correlates with O₃.

Spatial homogeneity and heterogeneity of ambient air pollutants in Tehran

To investigate spatial inequality of ambient air pollutants and comparison of their heterogeneity and homogeneity across Tehran, the following quantitative indicators were utilized: coefficient of divergence (COD), the 90^th percentile of the absolute differences between ambient air pollutant concentrations and coefficient of variation (CV). Real-time hourly concentrations of particulate matter (PM) and gaseous air pollutants (GAPs) of twenty-two air quality monitoring stations (AQMSs) were obtained from Tehran Air Quality Control Company (TAQCC) in 2017. Annual mean concentrations of PM_2.5, PM_10-2.5, and PM₁₀ (PM_X) ranged from 21.7 to 40.5, 37.3 to 75.0 and 58.0 to 110.4 μg m^-3, respectively. Annual mean PM_2.5 and PM₁₀ concentrations were higher than the World Health Organization air quality guideline (WHO AQG) and national standard levels. NO₂, O₃, SO₂ and CO annual mean concentrations ranged from 27.0 to 76.8, 15.5 to 25.1, 4.6 to 12.2 ppb, and 1.9 to 3.8 ppm over AQMSs, respectively. Our generated spatial maps exhibited that ambient PM_X concentrations increased from the north into south and south-western areas as the hotspots of ambient PM_X in Tehran. O₃ hotspots were observed in the north and south-west, while NO₂ hotspots were in the west and south. COD values of PM_X demonstrated more results lower than the 0.2 cut off compared to GAPs; indicating high to moderate spatial homogeneity for PM_X and moderate to high spatial heterogeneity for GAPs. Regarding CV approach, the spatial variabilities of air pollutants followed in the order of O₃ (87.3%) > SO₂ (65.2%) > CO (61.8%) > PM_10-2.5 (52.5%) > PM_2.5 (48.9%) > NO₂ (48.1%) > PM₁₀ (42.9%), which were mainly in agreement with COD results, except for NO₂. COD values observed a statistically (P < 0.05) positive correlation with the values of the 90^th percentile across AQMSs. Our study, for the first time, highlights spatial inequality of ambient PM_X and GAPs in Tehran in detail to better facilitate establishing new intra-urban control policies.

Spatiotemporal variation in PM2.5 concentrations and their relationship with socioeconomic factors in China's major cities

The air quality issues caused by extreme haze episodes in China have become increasingly serious in recent years. In particular, fine particulate matter (PM_2.5) has become the major component of haze with many adverse impacts and has therefore become of great concern to scientists, government, and the general public in China. This study investigates the spatiotemporal variation in PM_2.5 in 269 Chinese cities from 2015 to 2016 and its associations with socioeconomic factors to identify the possible strategies for PM_2.5 pollution mitigation. Specifically, we first quantified the spatial pattern of PM_2.5 concentrations in both 2015 and 2016, and then changes between the two years. Next, we examined the relationship between socioeconomic factors and PM_2.5 concentrations and changes. The results showed that most cities in eastern China experienced decreases in PM_2.5 concentration, although most of these cities already had high PM_2.5 pollution level. Cities with low PM_2.5 concentrations experienced increases in PM_2.5 concentrations and were mostly located in southern and southwestern China. The PM_2.5 concentration was the highest in winter, followed by in spring, autumn and summer; for changes in PM_2.5 concentrations, the highest magnitude of decrease occurred in summer, followed by the decreases in winter, autumn and spring. Cities with high PM_2.5 concentrations tended to be clustered, but the clustered characteristics were not clearly related to the changes in PM_2.5 concentrations. The relationship between PM_2.5 concentration and urban size was an inverse U-shaped curve, suggesting the existence of the Environmental Kuznets Curve for air quality in China. Population density and secondary industry share are the keys factors relating to air pollution control. In comparison to other cities, most moderately developed cities had a greater magnitude of decrease in PM_2.5 concentrations and the key factor for pollution improvement was industrial structure; however, smaller cities tended to have a greater increase in PM_2.5 concentrations and population density was the most important influencing factor. As a result, for air pollution control in China, specific regulations should be carried out according to different regions and different developmental stages based on the locations of cities.

Spatiotemporal variations of air pollutants in western China and their relationship to meteorological factors and emission sources

We have carried out a comprehensive analysis of six air pollutants (particles with an aerodynamic diameter less than 2.5 μm (PM_2.5) and less than 10 μm (PM₁₀), carbon monoxide (CO), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), and ozone (O₃)) in western China, including the spatiotemporal characteristics of air pollutants, their relationship with meteorological factors and emission sources, and the efficiency of emission control strategies for the region. Based hourly observations at 23 sites in western China from June 2016 to May 2017, concentrations of most pollutants were higher outside the Tibetan Plateau, lowest in summer and highest in winter, the exception being O₃. This was partially because meteorological conditions in winter were found to the most unfavorable to pollutant dispersion and dilution than other seasons. Pollutant concentrations at most sites were correlated with the residential emissions which were higher in winter, but anti-correlated with the industrial emissions which were lower during the winter holiday period. The Weather Research and Forecasting with Chemistry (WRF-Chem) simulations of four pollution control strategies indicated that reduction of residential emissions is crucial to alleviate PM_2.5, PM₁₀, and CO pollution in western China, although reduction of industrial and transport emissions can reduce SO₂ and NO₂, respectively. Since PM_2.5 and PM₁₀ were also found to be the species most and next frequently responsible for extremely serious pollution in western China, respectively, we recommend pollution control regulations that target residential emissions.

Spatial association between outdoor air pollution and lung cancer incidence in China

Background

Lung cancer is the most common cancer in China. Previous studies have indicated that lung cancer incidence exhibits remarkable spatial heterogeneity, and lung cancer is related to outdoor air pollution. However, the non-linear spatial association between outdoor air pollution and lung cancer incidence in China remains unclear.

Methods

In this study, the relationships between the lung cancer incidence of males and females from 207 counties in China in 2013 with annual concentrations of PM2.5, PM10, SO₂, NO₂, CO and O₃ were analysed. GeoDetector q statistic was used for examining the non-linear spatial association between outdoor air pollution and incidence of lung cancer.

Results

An apparent spatial and population gender heterogeneity was found in the spatial association between outdoor air pollution and lung cancer incidence. Among the six selected pollutants, SO₂ has the greatest influence on lung cancer (q = 0.154 in females) in north China. In the south, each selected pollutant has a significant impact on males or females, and the mean q value in the south is 0.181, which is bigger than that in the north (q = 0.154). In addition, the pollutants have evident non-linear interaction effects on lung cancer. In north China, the interaction between SO₂ and PM2.5 is the dominant interaction, with q values of 0.207 in males and 0.334 in females. In the south, the dominant interactive factors are between SO₂ and O₃ in males and between SO₂ and CO in females, with q values of 0.45, 0.232 respectively. Smoking is a substantial contributor to lung cancer among men, either in South or North China, with q value of 0.143 and 0.129 respectively, and the interaction between smoking and air pollutants increases this risk.

Conclusions

This study implies that the influence of SO₂ and PM2.5 on lung cancer should be focused on in north China, and in the south, the impact of O₃ and CO as well as their interaction with SO₂ need to be paid more attention. Smoking, particularly in men, remains a significant risk factor for lung cancer in both North and South China.

Gaseous and particulate pollutants in Lhasa, Tibet during 2013-2017: Spatial variability, temporal variations and implications

In recent decades, most big cities in China have experienced severe air pollution accompanied by rapid economic and social development. Analysis of measurements of air pollutants form a fundamental basis for understanding the characteristics of air pollution and are important references for policy-making. In this study, five-year measurements of air pollutants at 6 sites in Lhasa, a typical high altitude big city in southwestern China, were analyzed from January 2013 to December 2017. Air pollutants at all the 6 sites in Lhasa generally displayed similar patterns of both diurnal and monthly variations, indicating the mixed atmospheric environment and the overall effect of the meteorological conditions in the city. Spatially, the air pollutant concentrations at the 6 sites were generally characterized by high concentrations of SO₂, NO₂, CO, PM₁₀ and PM_2.5 at urban sites and high O₃ concentrations at suburban sites. In comparison with other provincial capital cities in China, Lhasa has low concentrations of air pollutants, except for O₃, and thus, better air quality. Although Lhasa has experienced rapid urbanization and economic development, air pollution conditions have remained rather stable and even decreased slightly in term of particular air pollutants. We suggested that the relatively isolated location, low air pollutant emissions associated with its industrial structure and renewable energy consumption, and effective air pollution control measures, collectively contributed to the synchronous improvement of the economy and air quality in Lhasa. Such "Lhasa pattern" may serve as a positive example for other regional hub cities in China and beyond that experience socioeconomic development and simultaneously seek to improve air quality.

Dynamic effect analysis of meteorological conditions on air pollution: A case study from Beijing

Air quality directly relates to human health and economic and social sustainable development. This study collected the meteorological data of Beijing from November 1, 2013 to October 31, 2017, employed vector autoregression (VAR) model, Granger causality test, impulse response function and variance decomposition to explore the dynamic effects of average humidity, extreme wind speed, sunshine duration, average wind speed and rainfall capacity on air quality index (AQI). The results indicated that the air pollution in Beijing was mainly a self-aggregation and self-diffusion process, the self-cumulative effect accounted for around 88.9318% during 5 periods, once the diffusion conditions of air pollution worsen, air pollution would be formed within 3 days. Meteorological conditions, especially extreme wind speed, sunshine duration and average humidity affected the concentration and spatial-temporal distribution of air pollutant. Extreme wind speed as atmospheric dynamic factor rather than average wind speed was the most important meteorological element influencing the AQI change in Beijing, which caused more atmospheric motion and turbulence, improving the diffusion and dilution ability of air pollutant, whose self-cumulative influence was around 7.5270% during 5 periods. Sunshine duration as atmospheric thermal factor was the secondary important meteorological element affecting AQI change in Beijing for it was associated with the formation of temperature stratification and inversion, the self-cumulative effect accounted for around 2.1402% during 4 periods. This study deepens the insights about the formation and diffusion mechanism of air pollution in Beijing, introduces nontraditional methods to review traditional issue and draw valuable conclusions. Other natural or human action factor should be further analyzed in the future research.

Air pollution and inflammation: Findings from concurrent repeated measures of systemic and reproductive tract cytokines during term pregnancy in Mexico City

BACKGROUND

Environmental exposures are associated with a number of outcomes including adverse pregnancy outcomes. Although inflammation is hypothesized to play a role, the mechanistic pathways between environmental exposures and adverse health outcomes, including associations between exposures and longitudinal measures of systemic and reproductive tract inflammation, need elucidation.

OBJECTIVES

This study was conducted to evaluate whether exposure to air pollution is associated with immunologic responses in the systemic circulation and lower reproductive tract, and to evaluate whether systemic and reproductive tract immunologic responses are similar.

METHODS

We quantified repeated measures of cytokines from cervico-vaginal exudates and serum obtained concurrently among 104 women with term pregnancies and estimated PM₁₀ and CO exposure using the monitor nearest each participant's residence. Serum and cervico-vaginal cytokines were compared using Wilcoxon signed-ranks test and Spearman rank correlations for select gestational months. We used intraclass correlation coefficients (ICCs) to quantify reproducibility of cytokine measurements, and Tobit regression to estimate associations between air pollution and cytokines.

RESULTS

Median cervico-vaginal levels of IL-6, Eotaxin, IP-10, MCP-1, MIP-1α, MIP-1β, and TNFα were higher than corresponding serum cytokines, significantly so for IL-6 and IP-10. Cervico-vaginal and serum cytokines were not correlated, but cytokines from the same fluid were correlated. ICCs for most serum cytokines were ≤0.40, while ICCs were higher in cervico-vaginal cytokines (range 0.52-0.83). IP-10 and Eotaxin had the highest ICCs for both cytokine sources. In adjusted models, PM₁₀ was positively associated with serum cytokines IL-6, IP-10, MIP-1β and Eotaxin but inversely associated with cervico-vaginal cytokine TNFα, IP-10, MIP-1β, MCP-1 and Eotaxin, controlling for false discovery rate. CO was inversely associated with cervico-vaginal TNFα, IL-6, MIP-1β, MCP-1 and Eotaxin.

CONCLUSIONS

Inflammatory processes are compartment-specific. Systemic inflammatory markers may provide information on immunologic processes and response to environmental exposures, but are not proxies for lower reproductive tract inflammation.

Air pollution characteristics and their relationship with emissions and meteorology in the Yangtze River Delta region during 2014-2016

With rapid economic growth and urbanization, the Yangtze River Delta (YRD) region in China has experienced serious air pollution challenges. In this study, we analyzed the air pollution characteristics and their relationship with emissions and meteorology in the YRD region during 2014-2016. In recent years, the concentrations of all air pollutants, except O₃, decreased. Spatially, the PM_2.5, PM₁₀, SO₂, and CO concentrations were higher in the northern YRD region, and NO₂ and O₃ were higher in the central YRD region. Based on the number of non-attainment days (i.e., days with air quality index greater than 100), PM_2.5 was the largest contributor to air pollution in the YRD region, followed by O₃, PM₁₀, and NO₂. However, particulate matter pollution has declined gradually, while O₃ pollution worsened. Meteorological conditions mainly influenced day-to-day variations in pollutant concentrations. PM_2.5 concentration was inversely related to wind speed, while O₃ concentration was positively correlated with temperature and negatively correlated with relative humidity. The air quality improvement in recent years was mainly attributed to emission reductions. During 2014-2016, PM_2.5, PM₁₀, SO₂, NO_x, CO, NH₃, and volatile organic compound (VOC) emissions in the YRD region were reduced by 26.3%, 29.2%, 32.4%, 8.1%, 15.9%, 4.5%, and 0.3%, respectively. Regional transport also contributed to the air pollution. During regional haze periods, pollutants from North China and East China aggravated the pollution in the YRD region. Our findings suggest that emission reduction and regional joint prevention and control helped to improve the air quality in the YRD region.

Health Risk and Resilience Assessment with Respect to the Main Air Pollutants in Sichuan

Rapid urbanization and industrialization in developing countries have caused an increase in air pollutant concentrations, and this has attracted public concern due to the resulting harmful effects to health. Here we present, through the spatial-temporal characteristics of six criteria air pollutants (PM_2.5, PM₁₀, SO₂, NO₂, CO, and O₃) in Sichuan, a human health risk assessment framework conducted to evaluate the health risk of different age groups caused by ambient air pollutants. Public health resilience was evaluated with respect to the risk resulting from ambient air pollutants, and a spatial inequality analysis between the risk caused by ambient air pollutants and hospital density in Sichuan was performed based on the Lorenz curve and Gini coefficient. The results indicated that high concentrations of PM_2.5 (47.7 μg m⁻³) and PM₁₀ (75.9 μg m⁻³) were observed in the Sichuan Basin; these two air pollutants posed a high risk to infants. The high risk caused by PM_2.5 was mainly distributed in Sichuan Basin (1.14) and that caused by PM₁₀ was principally distributed in Zigong (1.01). Additionally, the infants in Aba and Ganzi had high health resilience to the risk caused by PM_2.5 (3.89 and 4.79, respectively) and PM₁₀ (3.28 and 2.77, respectively), which was explained by the low risk in these two regions. These regions and Sichuan had severe spatial inequality between the infant hazard quotient caused by PM_2.5 (G = 0.518, G = 0.493, and G = 0.456, respectively) and hospital density. This spatial inequality was also caused by PM₁₀ (G = 0.525, G = 0.526, and G = 0.466, respectively), which is mainly attributed to the imbalance between hospital distribution and risk caused by PM_2.5 (PM₁₀) in these two areas. Such research could provide a basis for the formulation of medical construction and future air pollution control measures in Sichuan.

The distribution variance of airborne microorganisms in urban and rural environments

Microorganisms are ubiquitous in the atmosphere, where they can disperse for a long distance. However, it remains poorly understood how these airborne microorganisms vary and which factors influence the microbial distribution in different anthropogenic activity regions. To explore the regional differences of bacteria and fungi in airborne particles, PM_2.5 and PM₁₀ samples were collected in the urban and rural areas of Hangzhou. The bacterial and fungal communities in the urban atmosphere was more similar to each other than those in the rural atmosphere. Analyses conducted by the concentration weighted trajectory model demonstrated that the local environment contributed more to the similarity of airborne bacteria and fungi compared with the atmospheric transport. The concentrations of local air pollutants (PM_2.5, PM₁₀, NO₂, SO₂ and CO) were positively correlated with the similarity of the bacterial and fungal communities. Additionally, the concentrations of these air pollutants in the urban site were about 1.5 times than those in the rural site. This implicated that anthropogenic activity, which is the essential cause of air pollutants, influenced the similarity of airborne bacteria and fungi in the urban area. This work ascertains the outdoor bacterial and fungal distribution in the urban and the rural atmosphere and provides a prospective model for studying the contributing factors of airborne bacteria and fungi.

Spatio-temporal variations and factors of a provincial PM2.5 pollution in eastern China during 2013-2017 by geostatistics

Fine particulate matter (PM_2.5) is a typical air pollutant and has adverse health effects across the world, especially in the rapidly developing China due to significant air pollution. The PM_2.5 pollution varies with time and space, and is dominated by the locations owing to the differences in geographical conditions including topography and meteorology, the land use and the characteristics of urbanization and industrialization, all of which control the pollution formation by influencing the various sources and transport of PM_2.5. To characterize these parameters and mechanisms, the 5-year PM_2.5 pollution patterns of Jiangsu province in eastern China with high-resolution was investigated. The Kriging interpolation method of geostatistical analysis (GIS) and the HYbrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model were conducted to study the spatial and temporal distribution of air pollution at 110 sites from national air quality monitoring network covering 13 cities. The PM_2.5 pollution of the studied region was obvious, although the annual average concentration decreased from previous 72 to recent 50 μg m⁻³. Evident temporal variations showed high PM_2.5 level in winter and low in summer. Spatially, PM_2.5 level was higher in northern (inland, heavy industry) than that in eastern (costal, plain) regions. Industrial sources contributed highest to the air pollution. Backward trajectory clustering and potential source contribution factor (PSCF) analysis indicated that the typical monsoon climate played an important role in the aerosol transport. In summer, the air mass in Jiangsu was mainly affected by the updraft from near region, which accounted for about 60% of the total number of trajectories, while in winter, the long-distance transport from the northwest had a significant impact on air pollution.

Particulate matter pollution in Chinese cities: Areal-temporal variations and their relationships with meteorological conditions (2015-2017)

As the second largest economy in the world, China experiences severe particulate matter (PM) pollution in many of its cities. Meteorological factors are critical in determining both areal and temporal variations in PM pollution levels; understanding these factors and their interactions is critical for accurate forecasting, comprehensive analysis, and effective reduction of this pollution. This study analyzed areal and temporal variations in concentrations of PM_2.5, PM₁₀, and PM_coarse (PM₁₀ - PM_2.5) and PM_2.5 to PM₁₀ ratios (PM_2.5/PM₁₀) and their relationships with meteorological conditions in 366 Chinese cities from January 1, 2015 to December 31, 2017. On the national scale, PM_2.5 and PM₁₀ decreased from 48 to 42 μg m^-³ and from 88 to 84 μg m^-³, respectively, and the annual mean concentrations were 45 μg m^-³ (PM_2.5) and 84 μg m^-³ (PM₁₀) during the time period (2015-2017). In most regions, largest PM concentrations occurred in winter. However, in northern China, in spring PM_coarse concentrations were highest due to dust. The PM_2.5/PM₁₀ ratio was higher in southern than in northern China. There were large regional disparities in PM diurnal variations. Generally, PM concentrations were negatively correlated with precipitation, relative humidity, air temperature, and wind speed, but were positively correlated with surface pressure. The sunshine duration showed negative and positive impacts on PM in northern and southern cities, respectively. Meteorological factors impacted particulates of different size differently in different regions and over different periods of time.