Exposure to air pollutants has been associated with respiratory and cardiovascular mortality, but the underlying molecular mechanisms remain inadequately understood. We aimed to examine molecular-level inflammatory and oxidative stress responses to personal air pollutant exposure. Fifty-three healthy adults aged 22–52 were measured three times for their blood inflammatory cytokines and urinary malondialdehyde (MDA, an oxidative stress biomarker) within 2 consecutive months. Pollutant concentrations monitored indoors and outdoors were combined with the time-activity data to calculate personal O₃, PM₂.₅, NO₂, and SO₂ exposures averaged over 12 h, 24 h, 1 week, and 2 weeks, respectively, prior to biospecimen collection. Inflammatory cytokines and MDA were associated with pollutant exposures using linear mixed-effects models controlling for various covariates. After adjusting for a co-pollutant, we found that concentrations of proinflammatory cytokines were significantly and negatively associated with 12-h O₃ exposures and significantly but positively associated with 2-week O₃ exposures. We also found significant and positive associations of proinflammatory cytokines with 12-h and 24-h NO₂ exposures, respectively. However, we did not find clear associations of PM₂.₅ and SO₂ exposure with proinflammatory cytokines and with MDA. The removal of an O₃-generating electrostatic precipitator in the mechanical ventilation systems of the offices and residences of the subjects was associated with significant decreases in IL-1β, IL-2, IL-6, IL-8, IL-17A, and TNF-α. These findings suggest that exposure to O₃ for different time durations may affect systemic inflammatory responses in different ways.

To investigate chemical characteristics, abatement mechanisms and regional transport of atmospheric pollutants during the COVID-19 outbreak control period in the Yangtze River Delta (YRD) region, China, the measurements of air pollutants including fine particulate matter (PM₂.₅) and volatile organic compounds (VOCs) on non-control period (NCP, 24 December 2019–23 January 2020) and control period (CP, 24 January–23 February 2020) were analyzed at the urban Pudong Supersite (PD) and the regional Dianshan Lake Supersite (DSL). Due to the stricter outbreak control, the levels of PM₂.₅ and VOCs, and the occurrence frequencies of haze-fog episodes decreased substantially from NCP to CP, with average reduction rates of 31.6%, 38.9% and 35.1% at PD, and 34.5%, 50.7% and 37.9% at DSL, respectively. The major source for PM₂.₅ was secondary sulfate & nitrate in both periods, and the emission control of primary sources such as coal burning and vehicle exhaust decreased the levels of precursors gas sulfur dioxide and nitrogen oxide, which highly contributed to the abatement of PM₂.₅ from NCP to CP. The higher levels of ozone at both PD and DSL on CP might be due to the weak nitrogen monoxide titration, low relative humidity and high visibility compared with NCP. Vehicle exhaust and fugitive emission from petrochemical industry were the major contributors of ambient VOCs and their decreasing activities mainly accounted for VOCs abatement. Moreover, the high frequency of haze-fog events was closely impacted by medium-scale regional transport within Anhui and Jiangsu provinces. Therefore, the decreasing regional transported air pollutants coincided with the emission control of local sources to cause the abatement of haze-fog events in YRD region on CP. This study could improve the understanding of the change of atmospheric pollutants during the outbreak control period, and provide scientific base for haze-fog pollution control in YRD region, China.

Soluble iron (FeS) in aerosols contributes to free oxygen radical generation with implications for human health, and potentially catalyzes sulfur dioxide oxidation. It is also an important external source of micronutrients for ocean ecosystems. However, factors controlling FeS concentration and its contribution to total iron (FeT) in aerosols remain poorly understand. Here, FeS and FeT in PM₂.₅ was studied at four urban sites in eastern China from 21 to 31 December, 2017. Average FeT (869–1490 ng m⁻³) and FeS (24–68 ng m⁻³) concentrations were higher in northern than southern China cities, but Fe solubility (%FeS, 2.7–5.0%) showed no spatial pattern. Correlation analyses suggested %FeS was strongly correlated with FeS and PM₂.₅ instead of FeT concentrations. Individual particle observations confirmed that more than 65% of nano-sized Fe-containing particles were internally mixed with sulfates and nitrates. Furthermore, there was a high correlation between sulfates or nitrates/FeT molar ratio and %FeS. We also found that the sulfates/nitrates had weaker effects on %FeS at RH < 50% than at RH > 50%, suggesting RH as indirect factor can influence %FeS in PM₂.₅. These results suggest an important role of chemical processing in enhancing %FeS in the polluted atmosphere.

The current air pollution by SO₂ due to anthropogenic pressure in Poland was assessed based on sulfur concentrations in pine needles (Pinus sylvestris L.). On 308 monitoring sample plots located in pine stands distributed across Poland, measurements were conducted in mineral soil layers (0–10 cm, 10–40 cm, 40–100 cm) and in the soil organic layer (+5–0 cm). Samples of Scots pine foliage (current-year needles) were then collected, and the sulfur concentration in these needles was determined. Based on these data, a map of the spatial variability of sulfur concentrations in pine needles was drawn. The mean sulfur concentration in the pine needles was 854.8 mg kg⁻¹ in dry mass. Higher SO₂ emissions were noted in regions influenced by industry, such as the Upper Silesia and regions under strong urban pressure. Sulfur concentrations in Scots pine needles were related to the stands' degrees of defoliation. A comparison of the current sulfur concentrations in pine needles from biomonitoring in 2015–2016 with those from previous biomonitoring (in 1983–1985, by Dmuchowski and Bytnerowicz (1995) showed that air quality has improved and SO₂ emissions have decreased.

Air pollution is one of the most important branches of environmental science as it affects human health, climate and ecosystems. Emissions of air pollutants from transport (vehicles and ships) in port cities strongly affect air quality at local scales, warranting for a combination of theoretical and experimental studies to identify pollution hotspots. The purpose of this paper is to provide a methodology for developing a hybrid emission inventory from transport sector for two port cities located respectively on the Northern Aegean islands of Chios and Lesvos. Emission inventories were constructed for the year 2014 based on top-down and bottom-up approaches. Official data from local authorities and survey results were used for the calculation of emissions. Traffic emissions were spatially allocated to the road network based on population data and hourly traffic counts, and distributed over time (on an hourly basis) with the use of local temporal coefficients.Regarding carbon monoxide road emissions, the highest quantities are mainly emitted by Passenger Cars (43%,32% in Chios and Lesvos respectively) while for PM₁₀ emissions, trucks have the largest share (66% in Chios and 86% in Lesvos). The pollutants that are emitted in greater quantities from the ships at the ports of Mytilene and Chios are NOₓ, followed by SO₂ and CO. Most of the ship emissions in the ports occur by the ships at berth, as they remain berthed for hours whereas maneuvering lasts 15–20 min. As for the daily contribution of the two transport sources to the pollution profile of Mytilene, road emissions are higher for almost all pollutants. However, the contribution of ship emissions is not negligible, especially during the touristic period when marine traffic increases and emissions close to the port area become more important than those from road transport.

Ozone has become a major atmospheric pollutant in China as the pattern of urban energy usage has changed and the number of motor vehicles has grown rapidly. The Beijing-Tianjin-Hebei Urban Agglomeration, also known as the Jing-Jin-Ji Urban Agglomeration (hereafter, JJJUA), with a precarious balance between protecting the ecological environment and sustaining economic development, is challenged by high levels of ozone pollution. Based on ozone observation data from 13 cities in the JJJUA from 2014 to 2017, the spatio-temporal trends in the evolution of ozone pollution and its associated influencing factors were analyzed using Moran’s I Index, hot-spot analysis, and Geodetector using ArcGIS and SPSS software. Five key results were obtained. 1) There was an increase in the annual average ozone concentration, for the period 2014–2017. Comparing the 13 prefecture-level cities, ozone pollution in Chengde and Hengshui decreased, while it worsened in the remaining 11 cities. 2) Ozone pollution was worse in spring and summer than in autumn and winter; the peak ozone pollution season was from May to September; the average ozone concentration on workdays was higher than that on non-workdays, showing a counter-weekend effect. 3) Annual average concentrations were high in the central and southern parts of the study region but low in the north. 4) Prominent positive spatial correlations were observed in ozone concentration, with the best correlations shown in summer and autumn; concentrations were high in Baoding and Xingtai but low in Beijing and Chengde. 5) Concentrations of PM10, NO2, CO, SO2, and PM2.5, as well as average wind speed, sunshine duration, evaporation, precipitation, and temperature, all had significant effects on ozone pollution, and interactions between these influencing factors increased it.

The increase of gaseous ammonia (NH₃) concentration in the atmosphere significantly impacts the regional air quality, human health, and the nitrogen cycle of ecosystems. This study aims to verify the reanalyzed product of IASI NH₃ (the ANNI-NH₃-v2.1R-I, hereafter referred to as IASI_NH₃_R) and to analyze the spatial and temporal characteristics of atmospheric NH₃ during 2008–2016 and its underlying influencing factors. Our results show a good agreement between spatial pattern and temporal (annual and monthly) trend of the satellite-derived surface NH₃ concentrations and the measured near-ground NH₃ measurements over different land covers in Eastern China, suggesting the IASI_NH₃_R product can be used to investigate spatial and temporal trends of atmospheric NH₃ concentration. The annual mean NH₃ column concentrations peaked in the North China Plain (averaged 12 × 10¹⁵ mol cm⁻² yr⁻¹) and showed a significant increasing trend at a rate of 0.6 × 10¹⁵ mol cm⁻² yr⁻¹ during the entire period, which can be ascribed to densely populated, intensive agricultural activities and substantial reduction of SO₂ and NO₂ emissions since 2011. The NH₃ column concentrations show a slight increase in winter in most regions of China, probably due to less precipitation amount and increased uncertainty for lower NH₃ columns and the thermal contrast (TC). A large seasonal variation of NH₃ column concentrations was observed, with the highest values in summer and the lowest in autumn. Such seasonal variation is mainly affected by seasonal differences in NH₃ emissions and meteorological conditions. Our results suggest that the current control measures effectively decreased SO₂ and NO₂ pollution but are not yet apparent in the mitigation of atmospheric NH₃ pollution, which also merits more attention considering that no effective measures are being implemented for NH₃ emission control at a regional or national scale in China.

The proportion of asthma patients with mild to moderate exacerbations is far greater than the number who experience episodes that are severe enough to require emergency room visits or hospital admission. However the routinely collected data from hospitals is absent in the past.To evaluate associations between short-term exposures to air pollutants and hospital outpatient visits for asthma in China.We obtained data for 143,057 asthma outpatient visits from the largest hospitals in 17 Chinese cities, between Jan 01 2013 and Dec 31 2015. We used daily concentrations of air pollutants measured by the China National Environmental Monitoring Centre. We used a time-stratified case-crossover design, and fitted conditional logistic regression models to determine the associations.Particulate matter ≤10μm in diameter (PM10) and nitrogen dioxide (NO2) were associated with increased risks of hospital outpatient visits for asthma on the same day, while the effects were delayed for particulate matter ≤2.5μm in diameter (PM2.5) and sulphur dioxide (SO2). For the cumulative effect model at lag05 days, 10 μg/m3 increase in air pollutants concentrations were correlated with hospital outpatient visits for asthma with odds ratios (ORs) and 95% confidence intervals 1.004 (1.000-1.008) for PM2.5, 1.005 (1.002-1.008) for PM10, 1.030 (1.021-1.040) for NO2, and 1.015 (1.008-1.021) for SO2. Almost one in nine (10.9%; 7.7, 13.9%) hospital outpatient visits for asthma were attributable to NO2.Short-term exposures to PM2.5, PM10, NO2 and SO2 were associated with hospital outpatient visits for asthma in China.

Fine particulate matter (PM₂.₅) pollution has become a worldwide environmental concern because of its adverse impacts on human health. This study aimed to explore the spatiotemporal variations and influencing factors of PM₂.₅ concentrations in Beijing during the 2013–2018 period, and further analyzed the impacts of environmental protection policies implemented in recent years. Notably, this study employed various statistical methods, i.e., ordinary Kriging interpolation, spatial autocorrelation analysis, time-series analysis and the Bonferroni test, to evaluate the regional and seasonal differences of PM₂.₅ concentrations based on long-term monitoring data. The results illustrated that PM₂.₅ concentrations decreased on a yearly basis, demonstrating that air pollution control policies have achieved initial success. Furthermore, PM₂.₅ concentrations were higher in the winter and in the southern regions. Diurnal variation presented a bimodal distribution, which varied slightly with the season. Relative humidity and wind speed were the principal meteorological factors affecting the distribution of PM₂.₅ concentrations, while precipitation had essentially no effect. A high positive correlation between PM₂.₅ and gaseous pollutants (SO₂, NO₂, and CO) indirectly reflected the contribution of automobile exhaust and coal-fired emissions. Generally, PM₂.₅ concentrations demonstrated strong spatiotemporal variations, and meteorological factors and pollutant emissions played an important role in this.

PM₂.₅ pollution is caused by multiple factors and determining how these factors affect PM₂.₅ pollution is important for haze control. In this study, we modified the geographically weighted regression (GWR) model and investigated the relationships between PM₂.₅ and its influencing factors. Experiments covering 368 cities and 9 urban agglomerations were conducted in China in 2015 and more than 20 factors were considered. The modified GWR coefficients (MGCs) were calculated for six variables, including two emission factors (SO₂ and NO₂ concentrations), two meteorological factors (relative humidity and lifted index), and two topographical factors (woodland percentage and elevation). Then the spatial distribution of MGCs was analyzed at city, cluster, and region scales. Results showed that the relationships between PM₂.₅ and the different factors varied with location. SO₂ emission positively affected PM₂.₅, and the impact was the strongest in the Beijing–Tianjin–Hebei (BTH) region. The impact of NO₂ was generally smaller than that of SO₂ and could be important in coastal areas. The impact of meteorological factors on PM₂.₅ was complicated in terms of spatial variations, with relative humidity and lifted index exerting a strong positive impact on PM₂.₅ in Pearl River Delta and Central China, respectively. Woodland percentage mainly influenced PM₂.₅ in regions of or near deserts, and elevation was important in BTH and Sichuan. The findings of this study can improve our understanding of haze formation and provide useful information for policy-making.