Average Concentrations Of PM2 Research Articles

Particulate matter – a cancerous threat to our health?

Introduction: Particulate matter (PM) as a part of outdoor air pollutants are classified as human carcinogens. They are formed majorly as a result of combustion process by industry, power plants and engines. PM can be divided by the size of their particles into PM2.5 and PM10, where PM2.5 are small enough to penetrate into the alveoli sacs in the lung reaching the bloodstream, whereas PM10 affect mostly oral cavity, nose and the throat.
 Aim of the study: This study aims to investigate the impact of PM2.5 and PM10 particle concentrations in the EU NUTS 2 subregions on the death rates due to the most common malignant neoplasms.
 Results: There is a positive moderate correlation (r = 0.421; p < 0.001) between the annual mean concentration of PM2.5 and deaths due to malignant tumors. The strongest correlation was observed for malignant neoplasms of larynx, which is a positive correlation with a strong effect (r = 0.641; p < 0.001); and malignant neoplasm of bladder (r = 0.523; p < 0.001). For PM10, there is a moderately weak positive correlation (r = 0,195; p = 0.008) between the annual average concentration of PM10 and deaths due to malignant tumors. The strongest correlation was observed for malignant neoplasms of larynx, which is a positive correlation with a strong effect (r = 0,551; p < 0.001).
 Conclusion: The effect of PM impact on the malignant neoplasms is strong to moderate. The most affected neoplasm site are the ones the PMs intake occurs, being in the respiratory system. However other sites, where PMs can accumulate can be impacted as well. Further studies about the population with the highest risk due to the PMs exposure may be beneficial as other non-air quality-connected predictors may be found.

A comprehensive attribution analysis of PM2.5 in typical industrial cities during the winter of 2016–2018: Effect of meteorology and emission reduction

The frequent occurrence of air pollution in winter has aroused widespread concern. Identifying the detailed source composition of PM2.5 and assessing the reduction effects of different emission sources are crucial steps in improving pollution levels. In this study, we conducted a comprehensive evaluation of emission source reductions, encompassing ten local and ten regional sources. Furthermore, we analyzed the influence of meteorological changes on the abatement of PM2.5 in Tangshan, Shijiazhuang, Xingtai, and Handan during the winter period from 2016 to 2018. Our findings indicate that, in comparison to the winter of 2016, there were significant decreases in the average concentrations of PM2.5 during the winter of 2017. These decreases were attributed to favorable meteorological conditions and emission reductions. However, during the winter of 2018, there was a rebound in PM2.5 concentrations for all four cities. This rebound was primarily caused by adverse meteorological diffusion conditions. Throughout the entire research period spanning from the winter of 2016 to 2018, emission reduction played a significant role in PM2.5 abatement, contributing to 68% in Tangshan, 87% in Shijiazhuang, 93% in Xingtai, and 96% in Handan, respectively. The source apportionment analysis revealed that industrial and residential sources were the dominant contributors to PM2.5 concentrations in the cities. These findings not only confirm the effectiveness of existing industrial and residential pollution control policies but also highlight the imperative need for implementing non-point source control and joint control measures for regional elevated sources in the future.

Elucidating Best Geospatial Estimation Method Applied to Environmental Sciences

The aim of this study is to assess and identify the most suitable geospatial interpolation algorithm for environmental sciences. The research focuses on evaluating six different interpolation methods using annual average PM10 concentrations as a reference dataset. The dataset includes measurements obtained from a target air quality network (scenery 1) and a sub-dataset derived from a partitive clustering technique (scenery 2). By comparing the performance of each interpolation algorithm using various indicators, the study aims to determine the most reliable method. The findings reveal that the kriging method demonstrates the highest performance within environmental sciences, with a spatial similarity of approximately 70% between the two scenery datasets. The performance indicators for the kriging method, including RMSE (root mean square error), MAE (mean absolute error), and MAPE (mean absolute percentage error), are measured at 3.2 µg/m3, 10.2 µg/m3, and 7.3%, respectively.This study addresses the existing gap in scientific knowledge regarding the comparison of geospatial interpolation techniques. The findings provide valuable insights for environmental managers and decision-makers, enabling them to implement effective control and mitigation strategies based on reliable geospatial information and data. In summary, this research evaluates and identifies the most suitable geospatial interpolation algorithm for environmental sciences, with the kriging method emerging as the most reliable option. The study’s findings contribute to the advancement of knowledge in the field and offer practical implications for environmental management and planning.

Air pollution after acute bronchiolitis is a risk factor for preschool asthma: a nested case-control study

BackgroundAcute bronchiolitis and air pollution are both risk factor of pediatric asthma. This study aimed to assess subsequent exposure to air pollutants related to the inception of preschool asthma in infants with acute bronchiolitis. This study aimed to assess subsequent exposure to air pollutants related to the inception of preschool asthma in infants with acute bronchiolitis.MethodsA nested case-control retrospective study was performed at the Kaohsiung Medical University Hospital systems between 2009 and 2019. The average concentration of PM10, PM2.5, SO2, NO, NO2, and NOX was collected for three, six, and twelve months after the first infected episode. Adjusted regression models were employed to evaluate the association between asthma and air pollution exposure after bronchiolitis.ResultsTwo thousand six hundred thirty-seven children with acute bronchiolitis were included. Exposure to PM10, PM2.5, SO2, NO, NO2, and NOX in the three, six, and twelve months following an episode of bronchiolitis was found to significantly increase the risk of preschool asthma in infants with a history of bronchiolitis.(OR, 95%CI: PM10 = 1.517-1.559, 1.354–1.744; PM2.5 = 2.510-2.603, 2.148–3.061; SO2 = 1.970-2.040, 1.724–2.342; ; NO = 1.915-1.950, 1.647–2.272; NO2 = 1.915-1.950, 1.647–2.272; NOX = 1.752-1.970, 1.508–2.252) In a sensitive analysis of hospitalized infants, only PM10, PM2.5, SO2, and NO were found to have significant effects during all time periods. (OR, 95%CI: PM10 = 1.613-1.650, 1.240–2.140; PM2.5 = 2.208-2.286, 1.568–3.061; SO2 = 1.679-1.622, 1.197–2.292; NO = 1.525-1.557, 1.094–2.181)ConclusionThe presence of ambient PM10, PM2.5, SO2 and NO in the three, six, and twelve months following an episode of acute bronchiolitis has been linked to the development of preschool asthma in infants with a history of acute bronchiolitis.

Ambient Air Quality Monitoring with Reference to Particulate Matter (PM10) in Kolhapur City

Air is an important medium for all living beings and is essential for the well-being of all. Monitoring of air is important to know the quality of air. The air quality monitoring was carried out in Kolhapur City under the National Air Monitoring Program. The present study involves the assessment of PM10 as described in the National Ambient Air Quality Standards (NAAQS). The source apportionment study related to particulate matter was carried out in Kolhapur City. The study also determined the average PM10 concentration in the city as it will be useful for preparing an action plan to reduce PM10 concentration. PM10 concentration was calculated as per the standard method adopted by CPCB. Sampling was carried out for 8 hours in three shifts twice a week at each sampling site for three consecutive years. Mahadwar Road (MR) and Dabholkar Corner (DC) were selected per the surrounding residential area, population density, and traffic conjunction. The third site Shivaji University (SUK), was selected as a control site. The results indicated that the PM10 level has risen above the prescribed standards of NAAQS. The reason for the rise in PM10 may be due to fossil fuel burning, construction activity, vehicles, and unpaved roads. The Analysis of Variance (ANOVA) technique is used to check the equality of the mean concentration of PM10 at these three locations and found a significant difference between mean concentrations of PM10, suggesting increased particulate matter.

An analysis of air pollution associated with the 2023 sand and dust storms over China: Aerosol properties and PM10 variability

Every spring, a large part of China is confronted with sand and dust storms (SDS) – mainly originating in the Gobi (including Chinese and Mongolian Gobi) and Taklamakan deserts. In March-April 2023, most of northern, northwestern and northeastern China was struck by three sandstorms that affected an area with more than 500 million people. In this study, aerosol optical, microphysical and radiative properties were studied during these SDS events using an integrated approach that combines satellite, terrestrial and re-analysis data. The results showed that dusty conditions were observed in most areas north of the Yangtze River (Chang Jiang) with daily average PM10 concentrations exceeding 1000 µg/m3 in many cities. VIIRS aerosol optical depth (AOD) at 550 nm during three SDS events exceeded a value of 1 throughout nearly the entire northern part of the country. The AERONET data obtained from the AOE_Baotou site showed a significant increase in total AOD and a corresponding decrease in AE during the SDS. The single scattering albedo (SSA), asymmetry parameter (ASY), real refractive index (RRI) and imaginary refractive index (IRI) values indicate an abundance of scattering coarse-mode particles. Aerosol radiative forcing (ARF) at top of the atmosphere and at the earth's surface was nearly always negative during the period and ranged from −48.5 to +2.7 Wm−2 and from −180.8 to −66.6 Wm−2, resulting in high positive ARF values at ATM (from +63.8 to +132.3 Wm−2). Each of these affects the heating of the atmosphere and cooling on the earth's surface. The atmospheric heating rates ranged from 1.8 to 3.7 K day−1. The formation of these SDS mainly resulted from the passage of cold fronts associated with low pressure systems in the Gobi and Taklamakan deserts, creating conditions for dust to rise into the atmosphere and move further downwind.

Health risk assessment of workers' exposure to BTEX and PM during refueling in an urban fuel station.

The proximity of fuel stations to the roads and the activities inside the station can contribute to PM and VOCs and impose health risks on station workers. The study presents the exposure and health risk assessment of the fuel station personnel to total volatile organic compounds (TVOCs) and particulate matter (PM) during refueling operations. TVOCs and PM monitoring were carried out at a fuel station in Chennai, India, for 1 week in March 2021, covering both weekdays and weekends. The health risks were assessed using EPA's health impact assessment methodology. Exposure to TVOCs (3177.39 ± 5450.32 μg/m3) exceeded the EPA standard of 5 μg/m3, by more than 500 times, peaking during refueling operations. The average concentrations of PM10, PM2.5, and PM1 were 76.55 ± 23.08 μg/m3, 41.81 ± 9 μg/m3, and 30.38 ± 7.56 μg/m3, respectively. The concentrations were observed to be high during morning and evening hours due to the increased traffic on the adjacent road and inside the fuel station. The synergistic health risks linked with long-term exposure to high concentrations of BTEX and PM were also estimated. At the fuel station, a significant contribution to the SOA formation potential was shown by toluene, followed by m-xylene, p-xylene, o-xylene, ethylbenzene, and benzene. Furthermore, the deposition of airborne particles in the workers' respiratory tract was calculated using the Multiple Path Particle Dosimetry model while considering the daily average exposure duration of 12 h. The results showed that 59% of PM10 particles were deposited in the head region, whereas 11% and 10% of PM2.5 and PM1 particles were deposited in the pulmonary region. Hence, the health risk assessment indicated no non-cancer risk of exposure to PM (hazard quotient = 0.13) to station personnel exposed regularly for 1 year. However, prolonged exposure to VOCs for more than 1 year can result in both carcinogenic and non-carcinogenic risk (hazard quotient = 0.045 and cancer risk > 10-6) in workers.

Using particle dimensionality-based modeling to estimate lung carcinogenicity of 3D printer emissions.

The use of 3D printing technologies by industry and consumers is expanding. However, the approaches to assess the risk of lung carcinogenesis from the emissions of 3D printers have not yet been developed. The objective of the study was to demonstrate a methodology for modeling lung cancer risk related to specific exposure levels as derived from an experimental study of 3D printer emissions for various types of filaments (ABS, PLA, and PETG). The emissions of 15 filaments were assessed at varying extrusion temperatures for a total of 23 conditions in a Class 1,000 cleanroom following procedures described by ANSI/CAN/UL 2904. Three approaches were utilized for cancer risk estimation: (a) calculation based on PM2.5 and PM10 concentrations, (b) a proximity assessment based on the pulmonary deposition fraction, and (c) modeling based on the mass-weighted aerodynamic diameter of particles. The combined distribution of emitted particles had the mass median aerodynamic diameter (MMAD) of 0.35 μm, GSD 2.25. The average concentration of PM2.5 was 25.21 μg/m3 . The spline-based function of aerodynamic diameter allowed us to reconstruct the carcinogenic potential of seven types of fine and ultrafine particles (crystalline silica, fine TiO2 , ultrafine TiO2 , ambient PM2.5 and PM10, diesel particulates, and carbon nanotubes) with a correlation of 0.999, P < 0.00001. The central tendency estimation of lung cancer risk for 3D printer emissions was found at the level of 14.74 cases per 10,000 workers in a typical exposure scenario (average cumulative exposure of 0.3 mg/m3 - years), with the lowest risks for PLA filaments, and the highest for PETG type.

Analysis of Air Pollutants and Their Potential Sources in Eastern Xinjiang, Northwestern Inland China, from 2018 to 2022

Air pollution in the developed regions of eastern China has been intensively investigated in the past decade. However, there is a relative dearth of air pollution studies on the northwest of inland China (e.g., Xinjiang). In this work, hourly measurement data of six criteria air pollutants (PM2.5, PM10, CO, NO2, O3, and SO2) for the past five years (2018–2022) from Hami and Turpan cities of eastern Xinjiang were analyzed to reveal air pollution characteristics and the distribution of potential sources. Hami and Turpan had the highest AQI values in winter due to increased coal combustion for domestic heating and unfavorable meteorological conditions. The slight elevations of AQI values in spring were caused by frequent dust storms. PM10 was the most frequent main pollutant in both Hami (63.1%) and Turpan (74.1%), followed by PM2.5 and O3. Except for O3, PM2.5, PM10, SO2, NO2, and CO exhibited a generally decreasing pattern in annual average values. But the annual average concentrations of PM10 in Hami (83.5 μg·m−3) and Turpan (139 μg·m−3) in 2022 were still higher than those in eastern China. Diurnal and monthly variations of the six criteria pollutants were influenced by a combination of emission sources and meteorological conditions. The air masses in eastern Xinjiang mainly originated from the west and north and were affected by both inter-regional and intra-regional transport. Analysis of the distribution of potential sources showed that local emissions strongly impacted particulate matter pollution in winter, while regional transport played a dominant role in other seasons. O3 showed a broad distribution of potential sources across all four seasons. Considering that the trend that O3 pollution increased year by year, eastern Xinjiang might face a similar pollution situation as eastern China, i.e., the combined pollution of particulate matter and O3.

Spatial and Temporal Variations in PM1 Concentration and its Correlation with AOD in China from 2014 to 2017

Based on the PM1 mass concentration data from all the air quality monitoring stations in China from 2014 to 2017, the temporal and spatial distribution characteristics of PM1 concentration were studied using the time series statistical and spatial hierarchical clustering methods, and the PM1 spatiotemporal evolution characteristics were revealed. Combined with AOD data of the MODIS remote-sensing satellite, the temporal and spatial variation in PM1-AOD correlation was analyzed on a fine scale. The results showed that, from 2014 to 2017, the annual average PM1 concentration in China decreased yearly, the seasonal PM1 concentration showed the characteristics of "high in winter and low in summer," and the monthly average PM1 concentration showed a "U"-shaped variation. An "M"-shaped PM1 variation pattern was presented before and after the holidays. Weekly variation showed that high PM1 values occurred on Mondays and Fridays, and low ones occurred on Sundays. Based on the spatial clustering method, the national average annual PM1 concentration in China was divided into seven categories, and the overall spatial distribution pattern was "high in the east and low in the west and high in the north and low in the south." The highest and the lowest values of average PM1 concentration occurred in central China(54.59 μg·m-3) and in Xinjiang-Qinghai-Xizang(11.37 μg·m-3), respectively. The PM1-AOD relationship was positively correlated as a whole, the highest correlation coefficient was 0.55 in central China, and the lowest value was 0.36 in central and southern China.

Variability of ambient particulate matter loading at Henties Bay, Namibia

The Namibian coast is one of the areas of international interest for aerosol studies. This is due to the region’s importance for the global radiation budget because of the presence of a semi-permanent stratocumulus cloud along the coast. Aerosol particles may scatter/absorb radiation and directly influence how long clouds last by modifying their properties. This is all dependent on the particles’ chemical and physical properties because of the sources they were emitted from. In this study, we identified and investigated episodes of high (HAE) and low (LAE) PM concentrations and the meteorology that may favour their occurrence. Here, we investigated PM2.5 (particles with an aerodynamic diameter of 2.5 µm or less) and PM10 (particles with an aerodynamic diameter of 10 µm or less) at Henties Bay, Namibia. Daily aerosol measurements were taken with E-samplers between 15 and 29 July 2019. The Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model was used to investigate the long-range atmospheric transport of air masses that reached Henties Bay. The study found that during HAEs, the average PM2.5 concentration was 28.40 ± 18.10 µg/m3 and the average PM10 concentration was 68.20 ± 44.3 µg/m3. In contrast, during LAEs, the average PM2.5 concentration was 13.3 ± 9.52 µg/m3 and the average PM10 concentration was 30.00 ± 23.00 µg/m3. In both fractions, there was an observed dominant contribution from marine sources.

Conditionally Background Level of Aerosol Pollution of Near-Surface Air in Moscow and One of Its Suburbs: Seasonal Variations

The data of continuous observations of aerosol composition in the near-surface atmosphere in Moscow (in the city center) and in Moscow region (near Zvenigorod, Moscow region) for three years, from autumn 2019 to the end of 2022, are analyzed. The obtained data were compared with the results of observations on the Moscow network stations “Mosecomonitoring”. The concept of conditionally background aerosol pollution of the atmosphere in Moscow is introduced for those days when the average daily concentration of PM10 is less than the MPC value (60 µg/m3). Previously, the authors found that all episodes of increased aerosol pollution in Moscow with daily average PM10 concentration higher than the MPC value, are associated either with the presence of a close local source in the city itself, or with the long-range transport of fire aerosols and/or dust from other territories to the Moscow region. The average daily PM2.5 concentration in the city and the suburb is lower than the MPC (35 µg/m3) all year round. The days corresponding to the introduced conditional background make up more than 91% over three years in the center of Moscow. Such a conditional background is formed by both natural and anthropogenic sources of aerosols, and not only of local, but also of remote origin. It implicitly takes into account the influence of meteorological conditions on sources and sinks of aerosols, as well as advective air mass transport of aerosol to and from the city. Seasonal variations in mass concentration of PM10, PM2.5 particles and individual chemical elements, as well as in the distribution of chemical elements by the size of aerosol particles in near-surface atmosphere under conditionally background pollution are analyzed. The emphasis is placed on the similarity and difference in the conditionally background near-surface aerosol for the city and the suburb in different seasons.

The influence of PM2.5 exposure duration and concentration on outpatient visits of urban hospital in a typical heavy industrial city.

To explain the duration and dose effects of pollutant exposure on public health and provide scientific data for air pollution prevention and control and disease prevention by examining the influence of PM2.5 concentration and exposure duration on daily outpatient visits among patients with cardiovascular, cerebrovascular, and respiratory diseases in a typical heavy industrial city in China. Daily outpatient data on cardiovascular, cerebrovascular, and respiratory diseases and regional PM2.5 exposure duration and concentration were collected from a provincial hospital in Taiyuan, China, from 2016 to 2021. The correlations of numeric variables were analyzed using the Pearson correlation method. A generalized additive model (GAMs) was also established to investigate the effects of PM2.5 concentration and exposure duration on outpatient visits. Correlation analysis showed that the outpatient visits in Taiyuan was significantly correlated with the PM2.5 concentration and exposure duration. The longer the exposure time of PM2.5 pollution, the stronger the correlation of PM2.5 with outpatient visits showed. Cardiovascular outpatient visits were extremely significant related with medium to long-term exposure of PM2.5 (exposure with more than 30days) (p < 0.001). In addition, outpatient visits of cerebrovascular and respiratory disease were extremely significant correlated with PM2.5 (exposures within 0-360days) (p < 0.001). The results of GAMs showed the linear or the nonlinear relationships between outpatient visits and exposure of PM2.5. Among the linear relationships, when average concentration of PM2.5 (exposure within less than 15days) increased by 1mg/m3, the cardiovascular outpatient visits increased most dramatically (by about 440 people). For nonlinear relationships, when the average PM2.5 concentration (exposure with over 30days or more) increased by 1mg/m3, the most dramatic increase occurred in cardiovascular outpatient visits (with a maximum increase of 7000), followed by cerebrovascular outpatient visits (with a maximum increase of 1200), and respiratory outpatient visits (with a maximum increase of 250). The GAMs also revealed a dose effect in the relationship between outpatient visits and PM2.5 exposure. In moderately polluted air (based on air quality standards of China, GB3095-2012), when the average concentration of PM2.5 increased by 1mg/m3, the cardiovascular outpatient visits increased the most (by 1200 people), followed by cerebrovascular outpatient visits (by 200 people) and respiratory outpatient visits (by 20 people). We concluded that outpatient visits in cardiovascular, cerebrovascular, and respiratory disease are closely correlated with the concentration and exposure duration of air pollution. There is a linear relationship between short-term air pollution exposure (exposure within less than 15days) and outpatient visits. As PM2.5 concentration increases, cardiovascular outpatient visits increase gradually, with its growth trend exceeding that of cerebrovascular and respiratory disease. There is a nonlinear relationship between medium and long-term air pollution exposure (exposure with more than 30days) and outpatient visits, with cardiovascular and cerebrovascular outpatient visits showed a nonlinear but overall upward trend when the atmosphere is moderately polluted.

Investigating PM2.5 toxicity in highly polluted urban and industrial areas in the Middle East: human health risk assessment and spatial distribution

Exposure to particulate matter (PM) can be considered as a factor affecting human health. The aim of this study was to investigate the concentration of PM2.5 and heavy metals and their influence on survival of A549 human lung cells in exposure to PM2.5 breathing air of Ahvaz city. In order to assess the levels of PM2.5 and heavy metals, air samples were collected from 14 sampling stations positioned across Ahvaz city during both winter and summer seasons. The concentration of heavy metals was determined using ICP OES. Next, the MTT assay [3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide] was employed to ascertain the survival rate of A549 cells. The findings from this research demonstrated that average PM2.5 of the study period was (149.5 μg/m3). Also, the average concentration of PM2.5 in the urban area in winter and summer was (153.3- and 106.9 μg/m3) and in the industrial area this parameter was (191.6 and 158.3 μg/m3). The average concentration of metals (ng/m3) of urban areas against industrial, Al (493 vs. 485), Fe (536 vs. 612), Cu (198 vs. 212), Ni (128 vs. 129), Cr (48.5 vs. 54), Cd (118 vs. 124), Mn (120 vs. 119), As (51 vs. 67), Hg (37 vs. 50), Zn (302 vs. 332) and Pb (266 vs. 351) were obtained. The results of the MTT assay showed that the highest percentage of cell survival according to the exposure concentration was 25 > 50 > 100 > 200. Also, the lowest percentage of survival (58.8%) was observed in the winter season and in industrial areas with a concentration of 200 μg/ml. The carcinogenic risk assessment of heavy metals indicated that except for Cr, whose carcinogenicity was 1.32E−03, other metals were in the safe range (10–4–10–6) for human health. The high concentration of PM2.5 and heavy metals can increase respiratory and cardiovascular diseases and reduce the public health level of Ahvaz citizens.

Temporal profile of ionic species and n-alkanes composition of PM10 in a rural environment of Western Himalaya

The temporal profile of PM10 and its composition comprising water-soluble ionic species and n-alkanes studied over the 14 months was segregated into three seasons: winter, summer, and monsoon. The average PM10 concentration exceeds the prescribed National PM10 limits in summer and winter. The PM10 concentration was highest in summer, followed by winter, and lowest in monsoon. Water-soluble inorganic ionic species— major cations (Ca2+, Mg2+, Na+, K+, and NH4+) and anions (F−, Cl−, NO3− and SO42−) contributed an average 30.7% to PM10. The ionic species displayed significant variation, with the highest concentration in winter and the lowest in the monsoon. The secondary inorganic ions, SO42−, NO3−, and NH4+, contributed 84% to the total ionic mass. The ion balance study revealed a strong correlation between anion and cation charge equivalents, suggesting their main contribution to PM10. The neutralization of NO3− + SO42− with NH4+ suggested, NH4+ being the main neutralizing species. n-alkanes concentration in PM10 was significant and showed seasonal variation, highest in the winters and lowest in monsoon. The source profiling of PM10 components, using statistical correlation, regression, and principal component analysis (PCA), revealed solid-fuel biomass, soil dust, and brick kilns and transported materials as major sources.

Relationship Between Outdoor Air Pollutant Exposure and Premature Delivery in China- Systematic Review and Meta-Analysis.

Objective: Preterm birth (PTB) is considered as a public health problem and one of the main risk factors related to the global disease burden. The purpose of this study aims to explore the influence of exposure to major air pollutants at different pregnancies on PTB. Methods: The relationship between air pollutants and PTB in China was collected from cohort studies and case-control studies published before 30 April 2022. Meta-analysis was carried out with STATA 15.0 software. Results: A total of 2,115 papers were retrieved, of which 18 papers met the inclusion criteria. The comprehensive effect of pollutant exposure and PTB were calculated. PM2.5 during entire pregnancy and O3 exposure during third trimester were positively associated with preterm birth. Every 10μg/m3 increase in the average concentration of PM2.5 during the whole pregnancy will increase the risk of premature delivery by 4%, and every 10μg/m3 increase in the average concentration of O3 in the third trimester will increase the risk of premature delivery by 1%. Conclusion: Exposure to PM2.5 entire prenatal pregnancy and O3 in third trimester is associated with an increased risk of preterm birth occurrence.

Mortality Risk and Burden From a Spectrum of Causes in Relation to Size-Fractionated Particulate Matters: Time Series Analysis.

There is limited evidence regarding the adverse impact of particulate matters (PMs) on multiple body systems from both epidemiological and mechanistic studies. The association between size-fractionated PMs and mortality risk, as well as the burden of a whole spectrum of causes of death, remains poorly characterized. We aimed to examine the wide range of susceptible diseases affected by different sizes of PMs. We also assessed the association between PMs with an aerodynamic diameter less than 1 µm (PM1), 2.5 µm (PM2.5), and 10 µm (PM10) and deaths from 36 causes in Guangzhou, China. Daily data were obtained on cause-specific mortality, PMs, and meteorology from 2014 to 2016. A time-stratified case-crossover approach was applied to estimate the risk and burden of cause-specific mortality attributable to PMs after adjusting for potential confounding variables, such as long-term trend and seasonality, relative humidity, temperature, air pressure, and public holidays. Stratification analyses were further conducted to explore the potential modification effects of season and demographic characteristics (eg, gender and age). We also assessed the reduction in mortality achieved by meeting the new air quality guidelines set by the World Health Organization (WHO). Positive and monotonic associations were generally observed between PMs and mortality. For every 10 μg/m3 increase in 4-day moving average concentrations of PM1, PM2.5, and PM10, the risk of all-cause mortality increased by 2.00% (95% CI 1.08%-2.92%), 1.54% (95% CI 0.93%-2.16%), and 1.38% (95% CI 0.95%-1.82%), respectively. Significant effects of size-fractionated PMs were observed for deaths attributed to nonaccidental causes, cardiovascular disease, respiratory disease, neoplasms, chronic rheumatic heart diseases, hypertensive diseases, cerebrovascular diseases, stroke, influenza, and pneumonia. If daily concentrations of PM1, PM2.5, and PM10 reached the WHO target levels of 10, 15, and 45 μg/m3, 7921 (95% empirical CI [eCI] 4454-11,206), 8303 (95% eCI 5063-11,248), and 8326 (95% eCI 5980-10690) deaths could be prevented, respectively. The effect estimates of PMs were relatively higher during hot months, among female individuals, and among those aged 85 years and older, although the differences between subgroups were not statistically significant. We observed positive and monotonical exposure-response curves between PMs and deaths from several diseases. The effect of PM1 was stronger on mortality than that of PM2.5 and PM10. A substantial number of premature deaths could be preventable by adhering to the WHO's new guidelines for PMs. Our findings highlight the importance of a size-based strategy in controlling PMs and managing their health impact.

Changes in Health Risks and Pollution Sources of Atmospheric PM2.5-bound Metals in a Background Site in North China

To explore the change features of PM2.5-bound metals in a background site of North China in the past ten years, 71 and 160 samples were collected from December 2011 to January 2013 (period Ⅰ) and from September 2019 to November 2021 (period Ⅱ) in Tuoji Island National Atmospheric Monitoring Station, respectively.The concentration of metals sampled was determined using ICP-MS, and the concentrations, sources, and health risks of heavy metals were compared. The results revealed that the average concentration of PM2.5 was (54.06±39.71) μg·m-3during period Ⅱ, which was 3.53 ng·m-3 lower than that during period Ⅰ. The concentrations of Zn, Mn, As, Pb, and V in stage Ⅱ decreased by 54.53, 172.63, 0.8, 79.06, and 3.81 ng·m-3, respectively, whereas the concentrations of Cr, Cu, Cd, and Ni increased by 2.01, 5.42, 3.03, and 3.55 ng·m-3, respectively. The PMF model results indicated that the biggest contributor to PM2.5-bound metal was industrial emissions (32.32%), followed by coal combustion (27.47%), vehicle emissions (23.70%), ship emissions (9.69%), and dust sources (6.83%) during period Ⅱ. The contribution ratio of dust sources and ship emissions decreased by 20.73% and 8.83%, respectively, whereas for coal combustion and industrial emissions it increased by 2.50% and 13.52%, respectively, when compared with that during period Ⅰ. The total carcinogenic risk induced by PM2.5-bound heavy metals of period Ⅱ increased, with the highest contributions by Cr and Cd. The total non-carcinogenic risk decreased, with Mn contributing the most. Therefore, in the process of air pollution control, the control of pollution sources of heavy metals such as Cr and Mn should be reinforced.

Seasonal disparity of the short-term association between air pollution and gastritis outpatient visits: A large scale hospital-based study in eastern China

Evidence on associations between outdoor air pollution and the risk of digestive diseases, especially seasonal disparity, is scarce. We aimed to compare the acute effects of air pollution on outpatient visits for gastritis between warm and cold seasons in China. We collected data on six criteria air pollutants [fine particulate matter (PM2.5), inhalable particulate matter (PM10), nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO), and ozone (O3)], daily counts of gastritis outpatient visits, and meteorological variables during 2014–2020 (2536 days) in Hefei, China. A time-series analysis with generalized additive model was used, and potential effect modifiers were explored. Totally, 106,429 outpatient visits were recorded. The average concentrations of PM2.5, PM10, CO, NO2, SO2, and O3 were 54.82, 81.95, 886.75, 39.51, 11.81, and 84.75 μg/m3, respectively, exceeding the updated WHO Air Quality Guidelines values. Short-term PM2.5, CO, and NO2 exposures significantly increased the risk of gastritis outpatient visits and the lag response effects varied at different lag days. Each 10 μg/m3 increment of PM2.5, CO, and NO2 at lag 0 day, the excess risks of gastritis outpatient visits increased by 0.50% (95% CI: 0.04%, 0.95%), 0.05% (0%, 0.10%), and 1.50% (0.54%, 2.47%), respectively. We found insignificant differences in age-, sex- or insurance-strata but significant differences in seasonal strata with stronger effects in cold seasons. Null association of exposure to O3, SO2, or PM10 was observed. This study provided first-hand data that short-term exposure to PM2.5, CO, and NO2 but not O3, SO2, or PM10 was positively associated with gastritis outpatient visits, and such association was more evident in cold seasons, further suggesting the need for underscoring the continued efforts for public health intervention and air pollution control, especially in winter.

Effects of land use patterns on PM10 concentrations in urban and suburban areas. A European scale analysis

Landscape structure, the spatial characteristic of land cover, is a key factor in air quality. In this study, we investigate the connection between different land-use category areas taken from the 2018 Urban Atlas and the European Environmental Agency's monthly average coarse particulate matter (PM10) concentrations. We identified the main PM10 emission-source land-use categories that restrict the transmission of PM10 and therefore reduce PM10 concentrations in urban and suburban areas. According to our results, water, forest and urban park areas inside differently sized buffer zones surrounding PM10 monitoring stations have an obvious clearing effect on PM10 concentrations throughout almost all seasons, while there is a positive correlation between areas of vacant land, railways and mine, dump and construction sites and monthly PM10 concentrations. In addition, the strong effect of the correlation between built-up areas, industrial areas and roads and monthly average PM10 concentrations changes seasonally. Air pollution from motor vehicles shows a significant positive statistical relationship with PM10 concentrations only in the summer, but in contrast, during the heating (cold) period, because of motor vehicle driving (secondary) winds, traffic corridors have a significant decreasing effect on PM10 concentrations. By understanding the effect of different land use/land cover patterns on PM10 concentrations and variability, we can derive precise spatial urban planning strategies that are adaptable for health care.