Characteristics and formation of typical winter haze in Handan, one of the most polluted cities in China

Exploring efficient strategies for air quality improvement in China based on its regional characteristics and interannual evolution of PM2.5 pollution

Fine particulate matter (PM2.5) harms human health and hinders normal human life. Considering the serious complexity and obvious regional characteristics of PM2.5 pollution, it is urgent to fill in the comprehensive overview of regional characteristics and interannual evolution of PM2.5. This review studied the PM2.5 pollution in six typical areas between 2014 and 2022 based on the data published by the Chinese government and nearly 120 relevant literature. We analyzed and compared the characteristics of interannual and quarterly changes of PM2.5 concentration. The Beijing-Tianjin-Hebei region (BTH), Yangtze River Delta (YRD) and Pearl River Delta (PRD) made remarkable progress in improving PM2.5 pollution, while Fenwei Plain (FWP), Sichuan Basin (SCB) and Northeast Plain (NEP) were slightly inferior mainly due to the relatively lower level of economic development. It was found that the annual average PM2.5 concentration change versus year curves in the three areas with better pollution control conditions can be merged into a smooth curve. Importantly, this can be fitted for the accurate evaluation of each area and provide reliable prediction of its future evolution. In addition, we analyzed the factors affecting the PM2.5 in each area and summarize the causes of air pollution in China. They included primary emission, secondary generation, regional transmission, as well as unfavorable air dispersion conditions. We also suggested that the PM2.5 pollution control should target specific industries and periods, and further research need to be carried out on the process of secondary production. The results provided useful assistance such as effect prediction and strategy guidance for PM2.5 pollution control in Chinese backward areas.

Chemical characteristics and formation mechanism of secondary inorganic aerosols: The decisive role of aerosol acidity and meteorological conditions

In recent years, there has been a growing concern about air pollution and its impact on the air quality and human health, especially for fine particulate matter (PM2.5) and its associated secondary aerosols in urban areas. This study conducted a year-long field campaign to collect PM2.5 samples day and night in an urban area of central Taiwan. Higher PM2.5 mass concentrations were observed in winter (27.7 ± 9.7 μg/m3), followed by autumn (22.5 ± 8.3 μg/m3), spring (19.2 ± 6.4 μg/m3), and summer (11.0 ± 3.1 μg/m3). The dominant formation mechanism of secondary inorganic aerosols was heterogeneous reactions of NO3- at night and homogeneous reactions of SO42- during the day. Additionally, significant correlations were observed between aerosol liquid water content (ALWC) and NO3- during nighttime, indicating the importance of aqueous-phase NO3- formation. The role of aerosol acidity was explored and a unique alkaline condition was found in spring and summer, which showed lower PM2.5 concentrations than the neutralized condition. Under the neutralized condition, higher PM2.5 concentrations were commonly found when combining the ammonium-rich regime with molar ratios of [NO3-]/[SO42-] exceeding 1.6, suggesting the importance of reducing both NH3 and NOx. Furthermore, the results showed that reducing NH3 should be prioritized under high temperature conditions, while reducing NOx became important under low temperature conditions. Clustering of backward trajectories showed that long-range transport could enhance the formation of secondary aerosols, but local emissions emerged as the main factor driving high PM2.5 concentrations. This study provides insights for policymakers to improve air quality, suggesting that different mitigation strategies should be formulated based on meteorological variables and that using clean energy for vehicles and electricity generation is important to alleviate air pollution.

Aqueous-phase formation of N-containing secondary organic compounds affected by the ionic strength

The reaction of carbonyl-to-imine/hemiaminal conversion in the atmospheric aqueous phase is a critical pathway to produce the light-absorbing N-containing secondary organic compounds (SOC). The formation mechanism of these compounds has been wildly investigated in bulk solutions with a low ionic strength. However, the ionic strength in the aqueous phase of the polluted atmosphere may be higher. It is still unclear whether and to what extent the inorganic ions can affect the SOC formation. Here we prepared the bulk solution with certain ionic strength, in which glyoxal and ammonium were mixed to mimic the aqueous-phase reaction. Molecular characterization by High-resolution Mass Spectrometry was performed to identify the N-containing products, and the light absorption of the mixtures was measured by ultraviolet-visible spectroscopy. Thirty-nine N-containing compounds were identified and divided into four categories (N-heterocyclic chromophores, high-molecular-weight compounds with N-heterocycle, aliphatic imines/hemiaminals, and the unclassified). It was observed that the longer reaction time and higher ionic strength led to the formation of more N-heterocyclic chromophores and the increasing of the light-absorbance of the mixture. The added inorganic ions were proposed to make the aqueous phase somewhat viscous so that the molecules were prone to undergo consecutive and intramolecular reactions to form the heterocycles. In general, this study revealed that the enhanced ionic strength and prolonged reaction time had the promotion effect on the light-absorbing SOC formation. It implies that the aldehyde-derived aqueous-phase SOC would contribute more light-absorbing particulate matter in the industrial or populated area where inorganic ions are abundant.

Effects of Air Pollution Exposure during Preconception and Pregnancy on Gestational Diabetes Mellitus

This study aimed to investigate the association between air pollution and gestational diabetes mellitus (GDM) in small- and medium-sized cities, identify sensitive periods and major pollutants, and explore the effects of air pollution on different populations. A total of 9820 women who delivered in Handan Maternal and Child Health Hospital in the Hebei Province from February 2018 to July 2020 were included in the study. Logistic regression and principal component logistic regression models were used to assess the effects of air pollution exposure during preconception and pregnancy on GDM risk and the differences in the effects across populations. The results suggested that each 20 μg/m3 increase in PM2.5 and PM10 exposure during preconception and pregnancy significantly increased the risk of GDM, and a 10 μg/m3 increase in NO2 exposure during pregnancy was also associated with the risk of GDM. In a subgroup analysis, pregnant women aged 30-35 years, nulliparous women, and those with less than a bachelor's education were the most sensitive groups. This study provides evidence for an association between air pollution and the prevalence of GDM, with PM2.5, PM10, and NO2 as risk factors for GDM.

Long-Term Air Pollution Characteristics and Multi-scale Meteorological Factor Variability Analysis of Mega-mountain Cities in the Chengdu-Chongqing Economic Circle

Currently, air quality has become central to global environmental policymaking. As a typical mountain megacity in the Cheng-Yu region, the air pollution in Chongqing is unique and sensitive. This study aims to comprehensively investigate the long-term annual, seasonal, and monthly variation characteristics of six major pollutants and seven meteorological parameters. The emission distribution of major pollutants is also discussed. The relationship between pollutants and the multi-scale meteorological conditions was explored. The results indicate that particulate matter (PM), SO2 and NO2 showed a "U-shaped" variation, while O3 showed an "inverted U-shaped" seasonal variation. Industrial emissions accounted for 81.84%, 58% and 80.10% of the total SO2, NOx and dust pollution emissions, respectively. The correlation between PM2.5 and PM10 was strong (R = 0.98). In addition, PM only showed a significant negative correlation with O3. On the contrary, PM showed a significant positive correlation with other gaseous pollutants (SO2, NO2, CO). O3 is only negatively correlated with relative humidity and atmospheric pressure. These findings provide an accurate and effective countermeasure for the coordinated management of air pollution in Cheng-Yu region and the formulation of the regional carbon peaking roadmap. Furthermore, it can improve the prediction accuracy of air pollution under multi-scale meteorological factors, promote effective emission reduction paths and policies in the region, and provide references for related epidemiological research.

Graphical abstract

Supplementary Information

The online version contains supplementary material available at 10.1007/s11270-023-06279-8.

The association between air pollution, meteorological factors, and daily outpatient visits for urticaria in Shijiazhuang, Hebei Province, China: a time series analysis

The associations of air pollution and meteorological factors with the outpatient visits of urticaria remain poorly studied. This study aimed to assess the association between air pollution, meteorological factors, and daily outpatient visits for urticaria in Shijiazhuang, China, during 2014-2019. Daily recordings of air pollutant concentrations, meteorological data, and outpatient visits data for urticaria were collected during the 6 years. Descriptive research methods were used to describe the distribution characteristics and demographic features of urticaria. A combination of the generalized linear regression model (GLM) and distribution lag nonlinear model (DLNM) was used to evaluate the lag association between environmental factors and daily outpatient visits for urticaria. Stratified analyses by gender (male; female) and age (< 18 years; 18-39 years; > 39 years) were further conducted. The dose-response relationship between daily urticaria visits and CO, NO₂, O₃, temperature, and relative humidity was nonlinear. High concentrations of CO, NO₂, O₃, and high temperatures increased the risk of urticaria outpatient visits. The maximum cumulative association of high concentrations of CO, NO₂, and O₃ was lag 0-14 days (CO: RR = 1.10, 95%CI: 1.06, 1.31; NO₂: RR = 1.09, 95%CI: 1.01, 1.08; O₃: RR = 1.16, 95%CI: 1.08, 1.25), and high temperatures was lag 0-7 days (RR = 1.27, 95%CI: 1.14, 1.41). Low concentrations of NO₂, O₃, and high humidity, on the other hand, act as protective factors for urticaria outpatient. The maximum cumulative association of low concentrations of NO₂ was the 0-day lag (RR = 0.97, 95%CI: 0.95, 0.99), O₃ was lag 0-5 days (RR = 0.94, 95%CI: 0.88, 0.99), and high humidity was lag 0-10 days (RR = 0.93, 95%CI: 0.89, 0.98). Stratified analyses showed that the risk of urticaria outpatient visits was higher for the males and in the < 18 years age group. In conclusion, we found that the development of urticaria in Shijiazhuang has a distinct seasonal and cyclical nature. Air pollutants and meteorological factors had varying degrees of influence on the risk of urticaria outpatient visits. This study provides indirect evidence for a link between air pollution, meteorological factors, and urticaria outpatient visits.

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

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

Machine learning combined with the PMF model reveal the synergistic effects of sources and meteorological factors on PM2.5 pollution

PM_2.5 pollution is a complex process mainly affected by emission sources and meteorological conditions. However, it is hard to accurately assess the effects of emission sources and meteorological conditions on the variation of PM_2.5 concentrations in the complex atmospheric environment. In this study, the Random Forest model with Shapley Additive exPlanations (RF-SHAP) and Partial Dependence Plot (RF-PDP) was combined with Positive Matrix Factorization (PMF) to evaluate the impacts of various factors on PM_2.5 pollution. The results show that anthropogenic emissions and meteorological conditions contributed about 67% (40.5 μg/m³) and 33% (19.7 μg/m³) to variation in PM_2.5 concentrations, respectively. Specifically, secondary nitrate (SN) had the greatest impact among all sources (about 45%). Hence, we further explore the impacts of the primary sources and meteorological conditions on SN formation. Coal combustion and vehicle emissions significantly contribute to the formation of SN by providing a large number of precursor NO_X. Additionally, the RF-PDP method was further employed to estimate the synergistic effects of primary sources and meteorological conditions on SN formation. The results help reveal strategies to simultaneously reduce SN by controlling primary emissions under suitable meteorological conditions. This work also suggests that the machine learning model can utilize online datasets well and provide a reliable approach for analyzing the causes of PM_2.5 pollution.

Spatiotemporal variations and sources of PM2.5 in the Central Plains Urban Agglomeration, China

The Central Plains Urban Agglomeration (CPUA) is the largest region in central China and suffers from serious air pollution. To reveal the spatiotemporal variations and the sources of fine particulate matter (PM_2.5, with an aerodynamic diameter of smaller than 2.5 μm) concentrations of CPUA, multiple and transdisciplinary methods were used to analyse the collected millions of PM_2.5 concentration data. The results showed that during 2017 ~ 2020, the yearly mean concentrations of PM_2.5 for CPUA were 68.3, 61.5, 58.7, and 51.5 μg/m³, respectively. The empirical orthogonal function (EOF) analysis suggested that high PM_2.5 pollution mainly occurred in winter (100.8 μg/m³, 4-year average). The diurnal change in PM_2.5 concentrations varied slightly over the season. The centroid of the PM_2.5 concentration moved towards the west over time. The spatial autocorrelation analysis indicated that PM_2.5 concentrations exhibited a positive spatial autocorrelation in CPUA. The most polluted cities distributed in the northern CPUA (Handan was the centre) formed a high-high agglomeration, and the cities located in the southern CPUA (Xinyang was the centre) formed a low-low agglomeration. The backward trajectory model and potential source contribution function were employed to discuss the regional transportation of PM_2.5. The results demonstrated that internal-region and cross-regional transport of anthropogenic emissions were all important to PM_2.5 pollution of CPUA. Our study suggests that joint efforts across cities and regions are necessary.

Impact of deep basin terrain on PM2.5 distribution and its seasonality over the Sichuan Basin, Southwest China

The terrain effect on atmospheric environment is poorly understood in particular for the polluted region with underlying complex topography. Therefore, this study targeted the Sichuan Basin (SCB), a deep basin with severe PM_2.5 pollution enclosed by the eastern Tibetan Plateau (TP), Yunnan-Guizhou Plateaus (YGP) and mountains over Southwest China, and we investigated the terrain effect on seasonal PM_2.5 distribution and the meteorological mechanism based on the WRF-Chem simulation with stuffing the basin topography. It is characterized that the three-dimensional distribution of topography-induced PM_2.5 concentrations over the SCB with the seasonal shift of regional PM_2.5 averages from approximately 30 μg m^-3 in summer to 90 μg m^-3 in winter at surface layer and from summertime 10 μg m^-3 to wintertime 30 μg m^-3 in the lower free troposphere. Such basin-forced PM_2.5 changes presented the vertically monotonical declines concentrated within the lower troposphere below 3.6 km in spring, 2.3 km in summer, 2.6 km in autumn and 4.8 km in winter. Impacts of deep basin aggravated PM_2.5 accumulation within the SCB and transport toward the surrounding plateaus contributing approximately 50-90% to PM_2.5 levels over the regions of eastern TP and northern YGP. In the SCB, atmospheric thermal structure in the lower troposphere could build a vertical convergence layer between the boundary layer and free troposphere, acting as a lid inhibiting air diffusion, which was regulated by the terrain effects on interactions of westerlies and Asian monsoons, especially the wintertime strong warm lid deteriorating air pollution in the SCB. Furthermore, warm and humid air conditions within the basin prompted sulfur oxidation ratio by +0.02 and nitrogen oxidation ratio by +0.22 effectively producing the secondary PM_2.5 in atmospheric environment.

Cross-boundary transport and source apportionment for PM2.5 in a typical industrial city in the Hebei Province, China: A modeling study

Cross-boundary transport of air pollution is a difficult issue in pollution control for the North China Plain. In this study, an industrial district (Shahe City) with a large glass manufacturing sector was investigated to clarify the relative contribution of fine particulate matter (PM_2.5) to the city's high levels of pollution. The Nest Air Quality Prediction Model System (NAQPMS), paired with Weather Research and Forecasting (WRF), was adopted and applied with a spatial resolution of 5 km. During the study period, the mean mass concentrations of PM_2.5, SO₂, and NO₂ were observed to be 132.0, 76.1, and 55.5 μg/m³, respectively. The model reproduced the variations in pollutant concentrations in Shahe at an acceptable level. The simulation of online source-tagging revealed that pollutants emitted within a 50-km radius of downtown Shahe contributed 63.4% of the city's total PM_2.5 concentration. This contribution increased to 73.9±21.2% when unfavorable meteorological conditions (high relative humidity, weak wind, and low planetary boundary layer height) were present; such conditions are more frequently associated with severe pollution (PM_2.5 ≥ 250 μg/m³). The contribution from Shahe was 52.3±21.6%. The source apportionment results showed that industry (47%), transportation (10%), power (17%), and residential (26%) sectors were the most important sources of PM_2.5 in Shahe. The glass factories (where chimney stack heights were normally < 70 m) in Shahe contributed 32.1% of the total PM_2.5 concentration in Shahe. With an increase in PM_2.5 concentration, the emissions from glass factories accumulated vertically and narrowed horizontally. At times when pollution levels were severe, the horizontally influenced area mainly covered Shahe. Furthermore, sensitivity tests indicated that reducing emissions by 20%, 40%, and 60% could lead to a decrease in the mass concentration of PM_2.5 of of 12.0%, 23.8%, and 35.5%, respectively.

Effects of temperature and PM2.5 on the incidence of hand, foot, and mouth in a heavily polluted area, Shijiazhuang, China

The influence of weather and air pollution factors on hand, foot, and mouth disease (HFMD) has received widespread attention. However, most of the existing studies came from lightly polluted areas and the results were inconsistent. There was a lack of relevant evidence of heavily polluted areas. This study aims to quantify the relationship between weather factors and air pollution with HFMD in heavily polluted areas. We collected the daily number of hand, foot, and mouth disease in Shijiazhuang, China from 2014 to 2018, as well as meteorological and air pollutant data over the same period. The generalized linear model combined with the distributed lag model was used to study the effect of meteorological factors and air pollutants on the daily cases of HFMD and its hysteresis effect. We found that the dose-response relationship between temperature, PM_2.5, and the risk of hand-foot-mouth disease was non-linear. Both low temperature and high temperature increased the risk of hand-foot-mouth disease. The cumulative effect of high temperature reached the maximum at 0-10 lag days, and the cumulative effect of low temperature reached the maximum at 0-3 lag days. The concentration of PM_2.5 between 76 and 200 μg/m³ has a certain risk of the onset of hand, foot, and mouth disease, but the extreme PM_2.5 concentration has a certain protective effect. In addition, low humidity, low wind speed, and low-O₃ can increase the risk of HFMD. Risks of humidity and low concentration of O₃ increased as lag days extended. In conclusion, our study found that climate factors and air pollutants exert varying degrees of impact on HFMD. Our research provided the scientific basis for establishing an early warning system so that medical staff and parents can take corresponding measures to prevent HFMD.

Can Green Technological Innovation Reduce Hazardous Air Pollutants?—An Empirical Test Based on 283 Cities in China

Based on the panel data of 283 cities in China from 2009 to 2018, this paper analyzes the effect of urban green scientific and technological innovation enhancement on hazardous air pollutants using the GS2SLS method, which simultaneously controls for model endogeneity and spatial spillover effects and reveals the transmission mechanism of urban green scientific and technological innovation level. It was found that (1) There is a significant spatial spillover effect of hazardous air pollutants between regions, both in China as a whole and in the eastern, central, and western parts of the country, and the spatial spillover effect of hazardous air pollutants is significantly greater in the eastern and central parts of China than in the western parts. (2) Green technological innovation has a significant inhibitory effect on hazardous air pollutants in cities in eastern and central China. An extended study found that the improvement in green technology levels in innovative cities has a better effect on controlling hazardous air pollutants than in non-innovative cities. (3) The energy- saving and green economy effects have a mediating influence on the effect of green technological innovation on hazardous air pollutants in cities, and the simultaneous occurrence of these two effects in green technological innovation serves to enhance the transmission of hazardous air pollutants in order to facilitate the long-term management of haze.

Persistent pollution episodes, transport pathways, and potential sources of air pollution during the heating season of 2016-2017 in Lanzhou, China

As one of the most important industrial cities in Northwest China, Lanzhou currently suffers from serious air pollution. This study analyzed the formation mechanism and potential source areas of persistent air pollution in Lanzhou during the heating period from November 1, 2016 to March 31, 2017 based on the air pollutant concentrations and relevant meteorological data. Our findings indicate that particulate pollution was extremely severe during the study period. The daily PM_2.5 and PM₁₀ concentrations had significantly negative correlations with daily temperature, wind speed, maximum daily boundary layer height, while the daily PM_2.5 and PM₁₀ concentrations showed significantly positive correlations with daily relative humidity. Five persistent pollution episodes were identified and classified as either stagnant accumulation or explosive growth types according to the mechanism of pollution formation and evolution. The PM_2.5 and PM₁₀ concentrations and PM_2.5/PM₁₀ ratio followed a growing "saw-tooth cycle" pattern during the stagnant accumulation type event. Dust storms caused abrupt peaks in PM₁₀ and a sharp decrease in the PM_2.5/PM₁₀ ratio in explosive growth type events. The potential sources of PM₁₀ were mainly distributed in the Kumtag Desert in Xinjiang Uygur Autonomous Region, the Qaidam Basin and Hehuang Valley in Qinghai Province, and the western and eastern Hexi Corridor in Gansu Province. The contributions to PM₁₀ were more than 120 μg/m³. The important potential sources of PM_2.5 were located in Hehuang Valley in Qinghai and Linxia Hui Autonomous Prefecture in Gansu; the concentrations of PM_2.5 were more than 60 μg/m³.

Evolution of secondary inorganic aerosols amidst improving PM2.5 air quality in the North China plain

The Clean Air Action implemented by the Chinese government in 2013 has greatly improved air quality in the North China Plain (NCP). In this work, we report changes in the chemical components of atmospheric fine particulate matter (PM_2.5) at four NCP sampling sites from 2012/2013 to 2017 to investigate the impacts and drivers of the Clean Air Action on aerosol chemistry, especially for secondary inorganic aerosols (SIA). During the observation period, the concentrations of PM_2.5 and its chemical components (especially SIA, organic carbon (OC), and elemental carbon (EC)) and the frequency of polluted days (daily PM_2.5 concentration ≥ 75 μg m^-3) in the NCP, declined significantly at all four sites. Asynchronized reduction in SIA components (large decreases in SO₄^2- with stable or even increased NO₃^- and NH₄⁺) was observed in urban Beijing, revealing a shift of the primary form of SIA, which suggested the fractions of NO₃^- increased more rapidly than SO₄^2- during PM_2.5 pollution episodes, especially in 2016 and 2017. In addition, unexpected increases in the sulfur oxidation ratio (SOR) and the nitrogen oxidation ratio (NOR) were observed among sites and across years in the substantially decreased PM_2.5 levels. They were largely determined by secondary aerosol precursors (i.e. decreased SO₂ and NO₂), photochemical oxidants (e.g. increased O₃), temperature, and relative humidity via gas-phase and heterogeneous reactions. Our results not only highlight the effectiveness of the Action Plan for improving air quality in the NCP, but also suggest an increasing importance of SIA in determining PM_2.5 concentration and composition.

Impacts of primary emissions and secondary aerosol formation on air pollution in an urban area of China during the COVID-19 lockdown

Restrictions on human activities were implemented in China to cope with the outbreak of the Coronavirus Disease 2019 (COVID-19), providing an opportunity to investigate the impacts of anthropogenic emissions on air quality. Intensive real-time measurements were made to compare primary emissions and secondary aerosol formation in Xi'an, China before and during the COVID-19 lockdown. Decreases in mass concentrations of particulate matter (PM) and its components were observed during the lockdown with reductions of 32-51%. The dominant contributor of PM was organic aerosol (OA), and results of a hybrid environmental receptor model indicated OA was composed of four primary OA (POA) factors (hydrocarbon-like OA (HOA), cooking OA (COA), biomass burning OA (BBOA), and coal combustion OA (CCOA)) and two oxygenated OA (OOA) factors (less-oxidized OOA (LO-OOA) and more-oxidized OOA (MO-OOA)). The mass concentrations of OA factors decreased from before to during the lockdown over a range of 17% to 58%, and they were affected by control measures and secondary processes. Correlations of secondary aerosols/ΔCO with Ox (NO2 + O3) and aerosol liquid water content indicated that photochemical oxidation had a greater effect on the formation of nitrate and two OOAs than sulfate; however, aqueous-phase reaction presented a more complex effect on secondary aerosols formation at different relative humidity condition. The formation efficiencies of secondary aerosols were enhanced during the lockdown as the increase of atmospheric oxidation capacity. Analyses of pollution episodes highlighted the importance of OA, especially the LO-OOA, for air pollution during the lockdown.

Pollution Characteristics, Chemical Compositions, and Population Health Risks during the 2018 Winter Haze Episode in Jianghan Plain, Central China

To determine the pollution characteristics, chemical compositions, and population health risks of PM2.5 at different pollution levels, PM2.5 samples were intensively collected during the long-lasting winter haze episode from 13–23 January 2018 in Xiantao in Jianghan Plain (JHP), central China. The higher PM2.5 levels during the severe pollution period were dominated by the WNW-NNE air-masses, whereas the lower PM2.5 concentrations during other pollution periods were mainly affected by the NE, S, and NW air-masses. The NO3−/SO42− and OC/EC ratios indicated a mixed contribution of intensive vehicle exhaust and secondary formation. The enrichment factor and geo-accumulation index for assessing the PM2.5-bound metal(loid)s contamination levels were positively correlated. Ingestion is the dominant exposure pathway of PM2.5-bound metal(loid)s for children and adults, followed by inhalation and dermal contact. As, Cr, and Pb may pose carcinogenic and non-carcinogenic risks, whereas Sb and V may only pose non-carcinogenic risks for children and adults. The population health risks may not depend on the pollution levels but depend on the PM2.5-bound metal(loid)s concentrations. PM2.5-bound metal(loid)s may pose much higher population health risks for adults compared to children. More attentions should be paid to the population health risks of PM2.5-bound metal(loid)s during a long-lasting winter haze episode in JHP.

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

To investigate the cause of fine particulate matter (particles with an aerodynamic diameter less than 2.5 µm, PM_2.5) pollution in the heating season in the North China Plain (specifically Beijing, Tianjin, and Langfang), water-soluble ions and carbonaceous components in PM_2.5 were simultaneously measured by online instruments with 1-hr resolution, from November 15, 2016 to March 15, 2017. The results showed extreme severity of PM_2.5 pollution on a regional scale. Secondary inorganic ions (SNA, i.e., NO₃^-+SO₄²+ NH₄⁺) dominated the water-soluble ions, accounting for 30%-40% of PM_2.5, while the total carbon (TC, i.e., OC + EC) contributed to 26.5%-30.1% of PM_2.5 in the three cities. SNA were mainly responsible for the increasing PM_2.5 pollution compared with organic matter (OM). NO₃^- was the most abundant species among water-soluble ions, but SO₄^2- played a much more important role in driving the elevated PM_2.5 concentrations. The relative humidity (RH) and its precursor SO₂ were the key factors affecting the formation of sulfate. Homogeneous reactions dominated the formation of nitrate which was mainly limited by HNO₃ in ammonia-rich conditions. Secondary formation and regional transport from the heavily polluted region promoted the growth of PM_2.5 concentrations in the formation stage of PM_2.5 pollution in Beijing and Langfang. Regional transport or local emissions, along with secondary formation, made great contributions to the PM_2.5 pollution in the evolution stage of PM_2.5 pollution in Beijing and Langfang. The favourable meteorological conditions and regional transport from a relatively clean region both favored the diffusion of pollutants in all three cities.

PM2.5-inducible long non-coding RNA (NONHSAT247851.1) is a positive regulator of inflammation through its interaction with raf-1 in HUVECs

Several studies have demonstrated that PM_2.5 inhalation is associated with an increased risk of cerebrovascular disease (CVD), in which inflammation plays an important role. The mechanisms of this disease are not fully understood to date. Long non-coding RNAs (lncRNAs) are involved in many pathophysiological processes, such as immune responses; however, their functions associated with inflammation are largely unexplored. High-throughput sequencing assay and obtained numerous lncRNAs that altered the expression in response to PM_2.5 treatment in HUVECs. NONHSAT247851.1 was also identified, which was significantly up-regulated to control the expression of immune response genes. Mechanistically, the results indicated that NONHSAT247851.1 knockdown reduced the expression of IL1β. In study, we investigated NONHSAT247851.1 as a promoter in regulating immune response genes via binding with raf-1 to regulate the phosphorylation level of p65 protein in HUVECs. The data collected suggests that NONHSAT247851.1 regulates inflammation via interaction with raf-1 to control the inflammatory expression in PM_2.5 exposure.

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.

Mixed and intensive haze pollution during the transition period between autumn and winter in Beijing, China

In the Northern China Plain (NCP), extreme haze events with high concentrations of fine particles occur frequently during the winter but rarely occur in autumn. In this study, we present a synthetic analysis of particulate constituents during the historically polluted transition period of autumn-winter in 2018, revealing that mixed-type haze episodes are the result of regional transport, homogeneous/heterogeneous conversion, and sandstorm influences. The hydrolysis process of N₂O₅ at higher relative humidity levels (>70%), which feature an enhanced nitrate oxidation ratio (0.30-0.70) and NO₃^- concentration (>60 μg m^-3), was the driving factor for high PM_2.5 mass concentrations during the observation periods. The long-distance transport of sandstorms, characterized by decreasing PM_2.5/PM₁₀ ratios (<30%) from the north/northwest, is the most important factor for the explosive growth of PM₁₀ concentration. These results can help us gain a comprehensive understanding of haze formation and highlight the importance of nitrate chemistry in the aqueous phase. The results suggest that persistent NO_x emission reduction measures must be made to better achieve air quality standards in Beijing and the NCP region.

Source, contribution and microbial N-cycle of N-compounds in China fresh snow

The importance and contribution of nitrogen compounds and the related microbial nitrogen cycling processes in fresh snow are not well understood under the current research background. We collected fresh snow samples from 21 cities that 80% are from China during 2016 and 2017. Principal component analysis showed that SO₄^2- were in the first principal component, and N-compounds were the second. Furthermore, the main pollutant ions SO₄^2- and NO₃^- were from anthropogenic sources, and SO₄^2- contributed (61%) more to the pollution load than NO₃^- (29%), which were confirmed through a series of precipitation mechanism analysis. We selected five N-cycle processes (consist of oxidation and reduction processes) for molecular biology experiments, including Ammonia-oxidation process, Nitrite-oxidation process, Denitrification process, Anaerobic-ammoxidation process (Anammox) and Dissimilatory nitrate reduction to ammonium process (DNRA). Except ammonia-oxidizing archaeal (AOA) and bacterial (AOB) amoA genes (above 10⁷ copies g^-1), molecular assays of key functional genes in various nitrogen conversion processes showed a belowed detection limit number, and AOB abundance was always higher than AOA. The determination of the microbial transformation rate using the ¹⁵N-isotope tracer technique showed that the potential rate of five N-conversion processes was very low, which is basically consistent with the results from molecular biology studies. Taken together, our results illustrated that microbial nitrogen cycle processes are not the primary biological processes causing the pollution in China fresh snow.

Adsorption and oxidation of SO2 on the surface of TiO2 nanoparticles: the role of terminal hydroxyl and oxygen vacancy–Ti3+ states

The absorption and oxidation reactions of SO₂ on TiO₂ nanoparticles were investigated by using a flow chamber, synchrotron X-ray absorption near-edge structure and high resolution synchrotron X-ray photoelectron spectroscopy techniques.

Characteristics and formation mechanisms of winter haze in Changzhou, a highly polluted industrial city in the Yangtze River Delta, China

Changzhou, an industrial city in the Yangtze River Delta, has been experiencing serious haze pollution, particularly in winter. However, studies pertaining to the haze in Changzhou are very limited, which makes it difficult to understand the characteristics and formation of winter haze in this area, and develop effective control measures. In this study, we carried out continuous online observation of particulate matter, chemical components, and meteorology in Changzhou in February 2017. Our results showed that haze pollution occurred frequently in Changzhou winter and exhibited two patterns: dry haze with low relative humidity (RH) and wet haze with high RH. Water-soluble inorganic ions (SO₄^2-, NO₃^-, and NH₄⁺) accounted for ∼52.2% of the PM_2.5 mass, of which sulfate was dominant in wet haze periods while nitrate was dominant in other periods. With the deterioration of haze pollution, the proportion of nitrate in PM_2.5 increased, while sulfate proportion increased under wet haze and decreased under dry haze. Dry haze and wet haze appeared under slow north wind and south wind, respectively, and strong north wind or sea breeze scavenged pollution. We found that formation of nitrate occurred rapidly in daytime with high concentrations of odd oxygen (O_x = O₃ + NO₂), whereas formation of sulfate occurred rapidly during nighttime with high RH, indicating that photochemistry and heterogeneous reaction were the major formation mechanisms for nitrate and sulfate, respectively. Through the cluster analysis of 36-h backward trajectories, five sources of air masses from three directions were identified. High PM_2.5 concentrations (84.1 μg m^-3 on average) usually occurred under the influence of two clusters (46%) from the northwest, indicating that regional transport from northern China aggravated the winter haze pollution in Changzhou. Emission reduction, particularly the mobile sources, and regional joint prevention and control can help to mitigate the winter haze in Changzhou.

Biotoxicity of water-soluble species in PM2.5 using Chlorella

China has been faced with severe haze pollution, which is hazardous to human health. Among the air pollutants, PM_2.5 (particles with an aerodynamic diameter ≤ 2.5 μm) is the most dangerous because of its toxicity and impact on human health and ecosystems. However, there has been limited research on PM_2.5 particle toxicity. In the present study, we collected daily PM_2.5 samples from January 1 to March 31, 2018 and selected samples to extract water-soluble species, including SO₄^2-, NO₃^-, WSOC, and NH₄⁺. These samples represented clean, good, slight, moderate, and heavy pollution days. After extraction using an ultrasonic method, PM_2.5 solutions were obtained. We used Chlorella as the test algae and studied the content of chlorophyll a, as well as the variation in fluorescence when they were placed into the PM_2.5 extraction solution, and their submicroscopic structure was analyzed using transmission electron microscopy (TEM). The results showed that when the air quality was relatively clean and good (PM_2.5 concentration ≤ 75 μg m^-3), the PM_2.5 extraction solutions had no inhibiting effects on Chlorella, whereas when the air quality was polluted (PM_2.5 concentration > 75 μg m^-3) and heavily polluted (PM_2.5 concentration > 150 μg m^-3), with increasing PM_2.5 concentrations and exposure time, the chlorophyll a content in Chlorella decreased. Moreover, the maximum photochemical quantum yield (F_v/F_m) of Chlorella obviously decreased, indicating chlorophyll inhibition during polluted days with increasing PM_2.5 concentrations. The effects on the chlorophyll fluorescence parameters were also obvious, leading to an increase of energy dissipated per unit reaction center (DI_o/RC), suggesting that Chlorella could survive when exposed to PM_2.5 solutions, whereas the physiological activities were significantly inhibited. The TEM analysis showed that there were few effects on Chlorella cell microstructure during clean days, whereas plasmolysis occurred during light- and medium-polluted days. With increasing pollution levels, plasmolysis became more and more apparent, until the organelles inside the cells were thoroughly destroyed and most of the parts could not be recognized.

Association between chemical components of PM2.5 and children's primary care night-time visits due to asthma attacks: A case-crossover study

BACKGROUND

Few papers have examined the association between the chemical components of PM_2.5 and health effects. The existence of an association is now under discussion.

METHODS

This case-crossover study aimed to examine the association between the chemical components of PM_2.5 and night-time primary care visits (PCVs) due to asthma attacks. The subjects were 1251 children aged 0-14 years who received medical care for asthma at a municipal emergency clinic. We measured daily average concentrations of hydrogen ion, sulfate ion, nitrate ion and water-soluble organic compounds (WSOCs), which are components of PM_2.5. We estimated the odds ratios (ORs) of PCVs per unit increment (inter quartile ranges) in each chemical component of PM_2.5 for the subgroups of warmer months and colder months separately.

RESULTS

No association was seen between PCVs and PM_2.5 mass concentrations the day before the PCVs in either warmer or colder months. In the warmer months, an association was seen with the concentrations of WSOCs and hydrogen ion the day before the PCVs (OR = 1.33; 95% CI: 1.00-1.76, OR = 1.18; 95% CI: 1.02-1.36, respectively). Furthermore, a negative association was seen between sulfate ion and PCVs (OR = 0.85; 95%CI: 0.74-0.98). No associations were observed in the colder months.

CONCLUSIONS

We observed a positive association between PCVs and certain concentrations of WSOCs and hydrogen ions in warmer months. In contrast, sulfate ion showed a negative association.

Assessment of satellite-estimated near-surface sulfate and nitrate concentrations and their precursor emissions over China from 2006 to 2014

China is the largest anthropogenic aerosol-generating country worldwide; however, few studies have analyzed the PM_2.5 chemical components and their underlying precursor emissions over long periods and across the national domain. First, global 3-D tropospheric chemistry and transport model (GEOS-Chem)-integrated satellite-retrieved aerosol optical depth (AOD) and vertical profiles were used to estimate near-surface sulfate and nitrate levels at 10-km resolution over China from 2006 to 2014. Ground measurement validation of our satellite model yielded correlation coefficients (r) of 0.7 and 0.73 and normalized mean bias (NMB) values of -37.96% and - 32.73% for sulfate and nitrate, respectively. Second, analyses of the spatiotemporal distributions of sulfate and nitrate as well as the vertical density Ozone Monitoring Instrument (OMI)-measured SO₂ (PBL_SO₂) and NO₂ (TVCD_NO₂) indicated that the highest nitrate and sulfate levels occurred in the North China Plain (~25 μg/m³) and Sichuan Basin (SCB) (~30 μg/m³), respectively. The long-term variations in the estimated components and precursor gases indicated that the large sulfate decline was positively correlated with the SO₂ emission reduction due to the mandatory desulfurization implemented in 2007. The annual growth rate of sulfate relative to the national mean was -6.19%/yr, and the concentration decreased by 17.10% from 2011 to 2014. Energy consumption increases and a lack of control measures for NO₂ resulted in persistent increases in NO₂ emissions and nitrate concentrations from 2006 to 2010, particularly in the SCB. With energy consumption structure advancements, reductions in NO₂ emissions and corresponding nitrate levels over three typical regions were prominent after 2012. Third, the estimated national-scale uncertainties of satellite datasets at 0.1° × 0.1° were 26.88% for sulfate and 25.55% for nitrate. Differences in the spatial distributions and temporal trends between our estimated components and precursor gases were mainly attributed to the dataset accuracy, the data pre-processing strategy, inconsistent column density and near-surface mass concentration, meteorological variables and complex chemical reactions.

Acute effect of ambient air pollution on hospitalization in patients with hypertension: A time-series study in Shijiazhuang, China

Although numerous studies have investigated the association between air pollution and hospitalization, few studies have focused on the health effect of air pollution on populations with hypertension. In this study, we conducted a time-series study to investigate the acute adverse effect of six criteria ambient air pollutants (fine particulate matter [PM_2.5], inhalable particulate matter [PM₁₀], nitrogen dioxide [NO₂], sulfur dioxide [SO₂], ozone [O₃], and carbon monoxide [CO]) on hospitalization of patients for hypertension in Shijiazhuang, China, from 2013 to 2016. An over-dispersed Poisson generalized addictive model adjusting for weather conditions, day of the week, and long-term and seasonal trends was used. In addition, we evaluated the effect of modification by season, sex, and age. A total of 650,550 hospitalization records were retrieved during the study period. A 10 μg/m³ increase of PM_2.5 (lag06), PM₁₀ (lag06), NO₂ (lag03), O₃ (lag6), and CO (lag04) corresponded to 0.56% (95% confidence interval [CI]: 0.28-0.83%), 0.31% (95% CI: 0.12-0.50%), 1.18% (95% CI: 0.49-1.87%), 0.40% (95% CI: 0.09-0.71%), and 0.03% (95% CI: 0.01-0.05%) increments in hospitalization of patients for hypertension, respectively. We observed statistically significant associations with PM_2.5, PM₁₀, NO₂, O₃, and CO, while positive but insignificant associations with SO₂. The effects of PM_2.5, PM₁₀, NO₂, O₃, and CO were robust when adjusted for co-pollutants. We found stronger associations in the cool season than in the warm season. Moreover, there were non-significant differences in the associations between air pollution and sex or age group. This study suggests that patients with hypertension had an increased risk of hospital admission when exposed to air pollution.

Haze Influencing Factors: A Data Envelopment Analysis Approach

This paper investigates the meteorological factors and human activities that influence PM_2.5 pollution by employing the data envelopment analysis (DEA) approach to a chance constrained stochastic optimization problem. This approach has the two advantages of admitting random input and output, and allowing the evaluation unit to exceed the front edge under the given probability constraint. Furthermore, by utilizing the meteorological observation data incorporated with the economic and social data for Jiangsu Province, the chance constrained stochastic DEA model was solved to explore the relationship between the meteorological elements and human activities and PM_2.5 pollution. The results are summarized by the following: (1) Among all five primary indexes, social progress, energy use and transportation are the most significant for PM_2.5 pollution. (2) Among our selected 14 secondary indexes, coal consumption, population density and civil car ownership account for a major portion of PM_2.5 pollution. (3) Human activities are the main factor producing PM_2.5 pollution. While some meteorological elements generate PM_2.5 pollution, some act as influencing factors on the migration of PM_2.5 pollution. These findings can provide a reference for the government to formulate appropriate policies to reduce PM_2.5 emissions and for the communities to develop effective strategies to eliminate PM_2.5 pollution.

Inorganic ion chemistry of local particulate matter in a populated city of North China at light, medium, and severe pollution levels

Twenty-six pairs of PM_2.5 and PM₁₀ samples were collected during haze episodes in Zhengzhou (113°28' E, 34°37' N), a highly populated city in North China. The samples were used to examine the inorganic ion chemistry of particulate matter (PM) of local origin at light (PM_2.5 < 60 μg m^-3 and PM₁₀ < 135 μg m^-3), medium (PM_2.5: 60-170 μg m^-3 and PM₁₀: 135-325 μg m^-3), and severe (PM_2.5 > 170 μg m^-3 and PM₁₀ > 325 μg m^-3) pollution levels. At the light and severe pollution levels, the increase of PM₁₀ was accounted for by the increase of PM_2.5, and the variation of PM_10-2.5 was small. In contrast, the increase of PM₁₀ at the medium pollution level was caused by the increase in both PM_2.5 and PM_10-2.5. Sulfate (SO₄^2-), nitrate (NO₃^-), ammonium (NH₄⁺), and chloride in the form of ammonium chloride (Cl^-_S) accounted for 47.8% and 60.3% of the PM_2.5 mass at the light and severe levels, respectively. These values indicate a large contribution of secondary inorganic species to the PM_2.5 growth. As the pollution level changed from light to medium, the contribution of SO₄^2- to the growth of PM_2.5 decreased from 49.0% to 15.1%, while those of NO₃^- and Cl^-_S increased from 25.1% and 0.6% to 32.5% and 2.8%, respectively, indicating the substantial production of nitrate and chloride. At the severe level, the contribution of SO₄^2- was 30.1%, while those of NO₃^- and Cl^-_S were 5.9% and 0.5%, respectively, suggesting a hindering effect of sulfate on the production of nitrate and chloride. These results indicate that the production of secondary species with the increase of PM_2.5 was dominated by sulfate-associated conversions at the light and severe pollution levels and was substantially influenced by nitrate- and chloride-associated conversions at the medium pollution level. The estimation of carbonate presence in the PM indicates that part of the carbonate in coarse particles (PM_10-2.5) of crustal origin enhanced sulfate production via heterogeneous surface reactions. Quantification of the contribution of primary and secondary species to PM_2.5 showed that it was dominated by both primary and secondary particles at the light pollution level, and it was mainly composed of secondary species at the severe pollution level.

Haze formation indicator based on observation of critical carbonaceous species in the atmosphere

Organic aerosol (OA) are always the most abundant species in terms of relative proportion to PM_2.5 concentration in Beijing, while in previous studies, poor link between carbonaceous particles and their gaseous precursors were established based on field observation results. Through this study, we provided a comprehensive analysis of critical carbonaceous species in the atmosphere. The concentrations, diurnal variations, conversions, and gas-particle partitioning (F-factor) of 8 carbonaceous species, carbon dioxide (CO₂), carbon monoxide (CO), methane (CH₄), volatile organic compounds (VOCs), non-methane hydrocarbon (NMHC), organic carbon (OC), elemental carbon (EC), and water soluble organic compounds (WSOCs), in Beijing were analyzed synthetically. Carbonaceous gases (CO, CO₂, VOCs, and CH₄) and OC/EC ratios exhibited double-peak diurnal patterns with a pronounced midnight peak, especially in winter. High correlation between VOCs and OC during winter nighttime indicated that OC was formed from VOCs precursors via an unknown mechanism at relative humidity greater than 50% and 80%, thereby promoting WSOC formation in PM₁ and PM_2.5 respectively. The established F-factor method was effective to describe gas-to-particle transformation of carbonaceous species and was a good indicator for haze events since high F-factors corresponded with enhanced PM_2.5 level. Moreover, higher F-factors in winter indicated carbonaceous species were more likely to exist as particles in Beijing. These results can help gain a comprehensive understanding of carbon cycle and formation of secondary organic aerosols from gaseous precursors in the atmosphere.

Significant HONO formation by the photolysis of nitrates in the presence of humic acids

The generation of HONO and NO₂ by the photolysis of nitrates in the presence of humic acids (HA) was measured under various conditions. The photolysis experiments of HA, KNO₃ and KNO₃/HA under simulated sunlight was carried out by a flow tube reactor at ambient temperature and pressure. HONO and NO₂ were major products by the photolysis of KNO₃. By contrast, the photolysis of HA and KNO₃/HA mainly generated HONO. HA significantly enhanced the formation of HONO during the photolysis process of KNO₃. With increasing the KNO₃ mass, the HONO formation rate (R_HONO) on KNO₃/HA increased while the photolysis rate normalized by the KNO₃ mass exhibited an opposite trend. R_HONO on KNO₃/HA linearly increased with irradiation intensity (88-262 W/m²) and relative humidity (7-70%), whereas it linearly decreased with the pH (pH = 2-12). In addition, the reaction paths of the HONO formation by the photolysis of nitrates in the presence of HA were proposed according to experimental results. Finally, atmospheric implications of the enhanced HONO formation by the photolysis of nitrates in the presence of HA were discussed.

Acute effects of air pollution on type II diabetes mellitus hospitalization in Shijiazhuang, China

Air pollution has been considered as an important contributor to diabetes development. However, the evidence is fewer in developing countries where air pollution concentrations were much higher. In this study, we conduct a time-series study to investigate the acute adverse effect of six air pollutants on type II diabetes mellitus (T2DM) hospitalization in Shijiazhuang, China. An over-dispersed passion generalized addictive model adjusted for weather conditions, day of the week, and long-term and seasonal trends was used. Finally, a 10-μg/m³ increase of fine particulate matter (PM_2.5), inhalable particulate matter (PM₁₀), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), and carbon monoxide (CO) corresponded to 0.53% (95% confidence interval = 0.22-0.83), 0.32% (95% CI = 0.10-0.55), 0.55% (95% CI = 0.04-1.07), 1.27% (95% CI = 0.33-2.22), and 0.04% (95% CI = 0.02-0.06) increment of T2DM hospitalization, respectively. The effects of PM_2.5, PM₁₀, and CO were robust when adjusted for co-pollutants. The associations appeared to be a little stronger in the cool season than in the warm season. And stronger associations were found in male and elderly (≥ 65 years) than in female and younger people (35-65 years). Our results contribute to the limited data in the scientific literature on acute effects of air pollution on type II diabetes mellitus in developing countries.

MAIN FINDINGS

This is the first adverse effect evidence of air pollution on T2DM in Shijiazhuang, a severely polluted city in China. Males were more vulnerable than females in severe pollution.