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Metro systems play a crucial role in public transportation worldwide. Given that metro stations are unique built environments with a significant volume of daily commuters, ensuring a satisfactory air quality in these spaces becomes paramount. This study involved measurements of indoor air quality (IAQ), staff satisfaction, particulate matter (PM) chemical composition, and heavy metal health risks at a typical metro station in Tianjin over two seasons. Although the air exchange rate was sufficient to maintain a CO2 concentration less than 1000 ppm, the proportion of staff reporting no sick-building symptoms decreased from 83 % in spring to 25 % in winter. An average mass concentration of PM with an aerodynamic diameter smaller than 2.5 µm (PM2.5) of 68.0 ± 42.2 µg/m3 and an average PM1 mass concentration of 51.8 ± 33.3 µg/m3 were observed on the platform in winter. PM2.5 contained more metal in winter than in spring. PM2.5 in winter contained more metal in winter than in spring. With a lower relative humidity in winter, the coefficient of friction between railway wheels and rails increased, thus increasing particle emission. The carcinogenic risk of Cr on the platform was unacceptable. Moreover, the health risks induced by Ba should be investigated. The findings indicate that PM control at metro stationss, particularly on platforms in winter, should be emphasized.

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The complex interaction between emissions, meteorology, and atmospheric chemistry makes accurate predictions of particulate pollution difficult. Advanced data mining techniques can reveal potential laws, providing new possibilities for understanding the evolution and causes of air pollution. Based on the Granger method and block modeling analysis, this paper explored the intercity spillover effects of hourly PM2.5 in Hubei Province, China, to determine the specific role (i.e., overflow, limited overflow, bilateral, inflow, and limited inflow) of each city on regional pollution formation. Furthermore, a dynamic Apriori algorithm considering time-lag effects was used to mine the spatio-temporal associations of extreme PM2.5 pollution events among different cities. Results suggest that the northern and central cities with high-level PM2.5 concentration in Hubei have a significant spillover effect, whereas the eastern and southern cities generally play a role as the sink of pollutants. Based on the association rules of extreme PM2.5 pollution, four main pollutant transport channels were excavated and well matched with the trajectories extracted by the atmospheric model. This paper provides new insights for exploring the interaction of intercity particulate pollution, which is a supplement and cross-validation of the model results.

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Air pollution risk factor on human health was surpassed only by high blood pressure, tobacco use and poor diet. Total number of deaths due to air pollution worldwide was estimated to 6.67 million people in 2019. In the European Union, 97% of the urban population is exposed to levels of fine particulate matter above the latest guideline levels set by the World Health Organization. Air pollution accounts for 20% of newborn deaths worldwide, most related to complications of low birth weight and preterm birth. Low birth weight and preterm birth are responsible for 1.8 million deaths worldwide. Bucharest is the capital city of Romania and one of the most polluted cities in Europe, ranking in the 9th position out of 96 of the top cities from Europe and in the 4th position out of 32 of the top cities in Eastern Europe, data from June 2022. The aim of this study was to measure the real time level of indoor particulate pollution levels in different indoor environments from Bucharest, during the pandemic period. The PM2.5/PM10 ratio and its rate of change were also determined for the measured data. The PM2.5/PM10 ratio and its rate of change were also calculated based on the measurement data. The PM2.5/PM10 ratio showed an upward trend on weekends compared to weekdays, suggesting a relationship with outdoor PM where leisure activities and traffic infiltrated the indoors. The fluctuation range of the PM2.5/PM10 ratio was 0.44~0.95, and low measured values were detected on weekdays. Of the seasons, the proportion of particulate in autumn and its rate of change tended to be higher than in summer. It was suggested that outdoor air may have permeated the room. In addition, the relationship was considered, such as it is a holiday period, there are few rainy days, the concentration of coarse particles is high, and the number of residents in the city decreases. When it comes to indoor air quality, the higher this ratio, the more serious the air pollution. PM10 concentrations decreased by 29.1% in the absence of human activity and increased by 35.1% in the presence of humans. PM2.5 concentration decreased by 30.3% without human activity and increased by 3.1% with the presence of humans. Certain trends were suggested for the resumption of human activity and an increase in PM2.5 concentrations. The average relative difference between October 2021, a pandemic period, and October 2022, a post pandemic period, was 64% for PM10 and 47% for PM2.5. The pandemic period brought a significantly better indoor air quality from the particulate pollution point of view.

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BACKGROUND: Coronary heart disease (CHD), the leading cause of death globally, might be developed or exacerbated by air pollution, resulting high burden to patients. To date, limited studies have estimated the relations between short-term exposure to air pollution and CHD disease burden in China, with inconsistent results. Hence, we aimed to estimate the short-term impact and burden of ambient PM pollutants on hospitalizations of CHD and specific CHD. METHODS: PM10 and PM2.5 were measured at 82 monitoring stations in 9 cities in Sichuan Province, China during 2017-2018. Based on the time-stratified case-crossover design, the effects of short-term exposure to particle matter (PM) pollution on coronary heart disease (CHD) hospital admissions were estimated. Meanwhile, the linked burden of CHD owing to ambient PM pollution were estimated. RESULTS: A total of 104,779 CHD records were derived from 153 hospitals from these 9 cities. There were significant effects of PM pollution on hospital admissions (HAs) for CHD and specific CHD in Sichuan Province. A 10 µg/m3 increase of PM10 and PM2.5 was linked with a 0.46% (95% CI: 0.08, 0.84%), and 0.57% (95% CI: 0.05, 1.09%) increments in HAs for CHD at lag7, respectively. The health effects of air pollutants were comparable modified by age, season and gender, showing old (≥ 65 years) and in cold season being more vulnerable to the effects of ambient air pollution, while gender-specific effects is positive but not conclusive. Involving the WHO's air quality guidelines as the reference, 1784 and 2847 total cases of HAs for CHD could be attributable to PM10 and PM2.5, separately. The total medical cost that could be attributable to exceeding PM10 and PM2.5 were 42.04 and 67.25 million CNY from 2017 to 2018, respectively. CONCLUSIONS: This study suggested that the short-term exposure to air pollutants were associated with increased HAs for CHD in Sichuan Province, which could be implications for local environment improvement and policy reference.

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The San Joaquin Valley (SJV) of California has suffered persistent particulate matter (PM) pollution despite many years of control efforts. To further understand the chemical drivers of this problem and to support the development of State Implementation Plan for PM, a time-of-flight aerosol chemical speciation monitor (ToF-ACSM) outfitted with a PM2.5 lens and a capture vaporizer has been deployed at the Fresno-Garland air monitoring site of the California Air Resource Board (CARB) since Oct. 2018. The instrument measured non-refractory species in PM2.5 continuously at 10-min resolution. In this study, the data acquired from Oct. 2018 to May 2019 were analyzed to investigate the chemical characteristics, sources and atmospheric processes of PM2.5 in the SJV. Comparisons of the ToF-ACSM measurement with various co-located aerosol instruments show good agreements. The inter-comparisons indicated that PM2.5 in Fresno was dominated by submicron particles during the winter whereas refractory species accounted for a major fraction of PM2.5 mass during the autumn associated with elevated PM10 loadings. A rolling window positive matrix factorization analysis was applied to the organic aerosol (OA) mass spectra using the Multilinear Engine (ME-2) algorithm. Three distinct OA sources were identified, including vehicle emissions, local and regional biomass burning, and formation of oxygenated species. There were significant seasonal variations in PM2.5 composition and sources. During the winter, residential wood burning and oxidation of nitrogen oxides were major contributors to the occurrence of haze episodes with PM2.5 dominated by biomass burning OA and nitrate. In autumn, agricultural activities and wildfires were found to be the main cause of PM pollution. PM2.5 concentrations decreased significantly after spring and were dominated by oxygenated OA during March to May. Our results highlight the importance of using seasonally dependent control strategies to mitigate PM pollution in the SJV.

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Studies on the variation in the particulate matter (PM) content, Saturation Isothermal Remanent Magnetization (SIRM), and particle grain-size distribution at a high spatial resolution are helpful in evaluating the important role of urban forests in PM removal. In this study, the trees located in dense urban forests (T0) retained more PM than trees located in open spaces (T1-T4); the SIRM and PM weight of T0 were 1.54-2.53 and 1.04-1.47 times more than those of T1-T4, respectively. In addition, the SIRM and PM weight decreased with increasing distance to the road, suggesting that distance from pollution sources plays a key role in reducing the air concentration of PM. The different grain-size components were determined from frequency curve plots using a laser particle-size analyzer. A unimodal spectrum with a major peak of approximately 20 µm and a minor peak between 0.1 and 1 µm was observed, indicating that a large proportion of fine air PM was retained by the needles of the study trees. Additionally, more <2.5 µm size fraction particles were observed at the sampling site near the traffic source but, compared to a tree in a row of trees, the percentage of the >10 µm size fraction for the tree in the dense urban forest was higher, indicating that the particles deposited on the needle surface originating from traffic sources were finer than those from natural atmospheric dust. The exploration of the variation in the PM weight, SIRM, and grain size of the particles deposited on the needle surface facilitates monitoring the removal of PM by urban forests under different environmental conditions (e.g., in closed dense urban forests and in open roadside spaces), different distances to roads, and different sampling heights above the ground.

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Although dust suppressants are widely applied to control road dust pollution, a consensus on their effectiveness has not been reached. To evaluate the effectiveness of dust suppressants (a calcium-magnesium complex) from health risks and health damage, spraying and sampling activities were conducted at four sites in Beijing. Using inhalation risk model and health damage assessment, health risks of PMx for three sensitive occupational groups were calculated and converted to life and economic loss. Results revealed that dust suppressants can indeed mitigate PM pollution and its accompanying health risks and health damage in road dust, but at a limited efficiency. By spraying dust suppressants, the total PM-related life loss reduced by 1.60E-02 years and 2.50E-04 years in urban and suburban areas on average, and the total willingness to pay (WTP) values decreased by 120 and 50 US$ for PM2.5 and PM10, indicating a more considerable environmental gain if dust suppressants were sprayed in additional regions when necessary. Overall, our study demonstrated that the effectiveness of dust suppressants cannot be pictured only by the variations of pollutant concentrations, and indicators with practice and economic value should be more useful for traffic-related pollution management.

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Due to the suspension of traffic mobility and industrial activities during the COVID-19, particulate matter (PM) pollution has decreased in China. However, rarely have research studies discussed the spatiotemporal pattern of this change and related influencing factors at city-scale across the nation. In this research, the clustering patterns of the decline rates of PM2.5 and PM10 during the period from 20 January to 8 April in 2020, compared with the same period of 2019, were investigated using spatial autocorrelation analysis. Four meteorological factors and two socioeconomic factors, i.e., the decline of intra-city mobility intensity (dIMI) representing the effect of traffic mobility and the decline rates of the secondary industrial output values (drSIOV), were adopted in the regression analysis. Then, multi-scale geographically weighted regression (MGWR), a model allowing the particular processing scale for each independent variable, was applied for investigating the relationship between PM pollution reductions and influencing factors. For comparison, ordinary least square (OLS) regression and the classic geographically weighted regression (GWR) were also performed. The research found that there were 16% and 20% reduction of PM2.5 and PM10 concentration across China and significant PM pollution mitigation in central, east, and south regions of China. As for the regression analysis results, MGWR outperformed the other two models, with R2 of 0.711 and 0.732 for PM2.5 and PM10, respectively. The results of MGWR revealed that the two socioeconomic factors had more significant impacts than meteorological factors. It showed that the reduction of traffic mobility caused more relative declines of PM2.5 in east China (e.g., cities in Jiangsu), while it caused more relative declines of PM10 in central China (e.g., cities in Henan). The reduction of industrial operation had a strong relationship with the PM10 drop in northeast China. The results are crucial for understanding how the decline pattern of PM pollution varied spatially during the COVID-19 outbreak, and it also provides a good reference for air pollution control in the future.

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The interpretive utility of environmental magnetic proxies for investigating airborne particulate matter (PM) pollution impact is restricted by differences in soil composition, land cover and land use. For soil magnetic applications, land use strongly influences magnetic particle distribution down the soil profile, even in homogeneous soil environments. Here, an adaptive approach is engineered to provide accurate magnetic proxy information for pollution monitoring across different land use types. In an 81-km2 area between two industrial harbours, the irregular distribution of forests, arable lands, pasture and residential areas prevented robustly relating topsoil magnetic susceptibility data to known pollution impacts. Although normalized topsoil susceptibility values showed improved potential for deriving airborne pollution impacts, optimal results were obtained by depth-integrating magnetic susceptibility logs, revealing long-term impacts of both active and decommissioned industrial facilities. Complementing soil magnetic observations, active and passive (bio)magnetic monitoring allowed discriminating short-term pollution patterns and evaluating changes in PM impact across the study area. Hereby, active PM receptors (strawberry leaves and plastic coated cardboards (PCCs)) provided promising results, yet passive receptors allowed estimating pollution impacts more efficiently. For the latter, species-independent grass leaf sampling reflected airborne PM depositional patterns most accurately, whereas wiped anthropogenic surfaces proved too sensitive to wash-off.

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Particle size distribution and emission factors from 9 State 3-5 light-duty gasoline vehicles (LDGVs) and 15 State 3-5 heavy-duty diesel vehicles (HDDVs) were tested in this study using a constant volume sampling (CVS) system on a dynamometer. The influences of driving cycles and emission control level on the PM emission factors and particle size distribution were analyzed. The results show that the PM emission factors of the tested LDGVs and HDDVs were (4.1±4.0)×1014 and (5.7±4.3)×1015 kg-1, respectively; the HDDV PM emission factor was (14±7) times less than that of LDGVs. Regarding LDGVs, the PM emission factor under the extra high speed condition was much more than that of the other speed conditions at (5.1±5.0)×1013 km-1, 11.7, 14.1, and 7.3 times more than that under the low, medium, and high speed conditions, respectively. Regarding HDDVs, the emission factor under the high speed condition was 2.5 and 1.4 times that under the low and medium speed conditions, respectively, and was mostly of nuclei-mode particles. At the emission control level of State 3-5, the PM emission factors of LDGVs were (2.7±1.7)×1013, (2.6±1.3)×1013, and (1.6±1.2)×1013 km-1, respectively, and those of HDDVs were (2.2±1.2)×1015, 2.0×1015, and (7.1±2.1)×1014 km-1, respectively. With improvement in emission control level, the particle number emission control of LDGVs and HDDVs generally showed a good downward trend. However, the emission of PM above 110 nm from LDGVs did not improve with the emission control level. Although the quantity emission factor of HDDVs with particle size above 110 nm is relatively low, its harm to the environment cannot be ignored, which should justify necessary attention.

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Particulate matter is one of the main pollutants, causing hazy days, and it has been serious concern for public health worldwide, particularly in China recently. Quality of outdoor atmosphere with a pollutant emission of PM2.5 is hard to be controlled; but the quality of indoor air could be achieved by using fibrous membrane-based air-filtering devices. Herein, we introduce nanofiber membranes for both indoor and outdoor air protection by electrospun synthesized polyacrylonitrile:TiO2 and developed polyacrylonitrile-co-polyacrylate:TiO2 composite nanofiber membranes. In this study, we design both polyacrylonitrile:TiO2 and polyacrylonitrile-co-polyacrylate:TiO2 nanofiber membranes with controlling the nanofiber diameter and membrane thickness and enable strong particulate matter adhesion to increase the absorptive performance and by synthesizing the specific microstructure of different layers of nanofiber membranes. Our study shows that the developed polyacrylonitrile-co-polyacrylate:TiO2 nanofiber membrane achieves highly effective (99.95% removal of PM2.5) under extreme hazy air-quality conditions (PM2.5 mass concentration 1 mg/m3). Moreover, the experimental simulation of the test in 1 cm3 air storehouse shows that the polyacrylonitrile-co-polyacrylate:TiO2 nanofiber membrane (1 g/m2) has the excellent PM 2.5 removal efficiency of 99.99% in 30 min.

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To evaluate lung function responses to short-term indoor PM1 and PM2.5 concentrations, we conducted a panel study of healthy schoolchildren aged 13-14 years. The following lung function parameters FVC, FEV1, PEF, and mid expiratory flows MEF25, MEF50, and MEF75 were measured in 141 schoolchildren of the secondary school in Wroclaw, Poland in years 2009-2010. On days when spirometry tests were conducted, simultaneously, PM1 and PM2.5 samples were collected inside the school premises. Information about differentiating factors for children including smoking parents, sex, living close to busy streets, dust, mold, and pollen allergies were collected by means of questionnaires. To account for repeated measurements, the method of generalized estimating equations (GEE) was used. The GEE models for the entire group of children revealed the adverse effects (p < 0.05) of PM1 and PM2.5. Small differences in effects estimates per interquartile range (IQR) of PM1 and PM2.5 on MEF25 (5.1 and 4.8 %), MEF50 (3.7 and 3.9 %), MEF75 (3.5 and 3.6 %) and FEV1 (1.3 and 1.0 %) imply that PM1 was likely the component of PM2.5 that might have a principal health effect on these lung function parameters. However, the reduction of FVC and PEF per IQR for PM2.5 (2.1 and 5.2 %, respectively) was higher than for PM1 (1.0 and 4.4 %, respectively). Adjustment for potential confounders did not change the unadjusted analysis.

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