PM10 Concentrations Research Articles

Elemental Characteristics of Particulate Matter (PM₁₀ and PM₂.₅) from Peat Swamp Area in Kuala Pahang

Particulate matter (PM) is normally being divided into two common groups known as: the coarse fraction particle with a range of sizing from 2.5 to 10 UM (PM10–PM2.5), and the fine fraction particles with a dimension smaller than 2.5 µm (PM2.5). It is also can be defined as a sum of solid and liquid particles which suspended in the air. The contribution of particulate matter towards the air pollution from peat swamp area in Kuala Pahang can be generated from various sources such as unpaved road, vehicle, open burning and uncover soil. In fact, monsoon season also play an important role where PM can be conveyed by wind from one location to another. Air pollution has become a matter of concern over Malaysia. The objective of this survey is to determine the particular matters in the air by using Aeroqual AQM 65 which is located in Kuala Pahang, Pekan. Air Pollution Index (API) is the reading to determine the quality of air whether it suitable and safe for human being. The data is obtained from the Aeroqual AQM 65 machine starting for April 2019 till March 2020. The survey will last for 12 months to generate a reliable result. From the API gain, the government can work out with some ideal on improving the surrounding air quality in the meantime to generate different strategy to overcome the problems. According to Aeroqual AQM 65, the reading of concentration of PM10 and PM2.5 are almost the same yet the concentration of PM10 is still slightly higher than PM2.5. According to the analysis, there is a rapid increase of concentration of PM form June to September and a sharp drop from September to March due to the happening of monsoon season. When the direction of monsoon season changes, the graph tends drop because the wind tends to convey the PM away. Therefore, the reading of API of PM2.5 is higher than PM10 and the highest reading for both particular matter API is on September yet the lowest reading of API for both particular matters is on November.

Chemical speciation and oxidative potential of PM10 in different residential microenvironments: Bedroom, living room and kitchen

Exposure to particulate matter (PM) and its chemical constituents in residential microenvironments has become a major health concern worldwide. The oxidative potential (OP) has been proposed as a metric for estimating the PM capacity to induce oxidative stress and, consequently, health effects. In the present study, PM10 was daily monitored simultaneously in the bedroom, living room and kitchen of three dwellings for one week in a small town of Portugal, to perform a detailed characterisation of its organic and inorganic constituents and the determination of the OP. Bedrooms (B) were found to be a hotspot of PM10 concentrations (B1 = 22.7 μg m−3; B2 = 19.5 μg m−3; B3 = 68.1 μg m−3). PM10-bound elements varied significantly between microenvironments in all dwellings. Lower molecular weight polycyclic aromatic hydrocarbons (PAHs) were found to be between 14 and 72 times higher than high molecular weight PAHs in bedrooms. The mean volume-normalised OP determined by the dithiothreitol and ascorbic acid assays varied within the 0.01–0.38 nmol min−1 m−3 and 0.03–0.53 nmol min−1 m−3 ranges, respectively. Quinones, oxy-aromatic, aromatic and alkyl-aromatic compounds stood out in bedrooms. Strong and significantly positive relationship between OP and black carbon, Cu and Br were observed, indicating common redox active species mainly associated with traffic emissions. Sr, Fe, Zn and Zr presented higher concentrations in dwelling 3, exhibiting excellent positive correlation with OP, indicating that the Sahara dust intrusion recorded in that house may have contributed to the formation of more redox active species thought to drive antioxidant depletion responses.

The Seasonality of PM and NO2 Concentrations in Slovakia and a Comparison with Chemical-Transport Model

The air quality (AQ) of a given location depends mostly on two factors: emissions and meteorological conditions. For most places on Earth, the meteorology of an area changes seasonally. For central Europe, winters are associated with poor dispersion conditions, which, in combination with high emissions from local heating systems, lead to significantly higher concentrations than during summer. In this study, the seasonality of AQ is analysed using hourly measurements from 44 monitoring stations in Slovakia for the years 2007–2023 for NO2, PM10 and PM2.5. Two factors are used to evaluate the seasonality—the difference and ratio of the winter and summer mean concentrations. It was found that the seasonal difference has been gradually decreasing for all pollutants since 2017. In the case of PM2.5, the seasonal ratio drops from a value of around 2.5 in 2018 to approximately 1.7 in 2023. While in the past, the seasonal ratio was the highest for PM2.5, in the last three years it is the highest for NO2 with values larger than 2. Our results imply that summer sources of PM emissions start to play a more important role for the AQ than in the past. The observed seasonality was compared with two full-year chemical-transport model simulations.

Simultaneous comparison of the chemical composition and attributable source of PM2.5 during 2014–2018 in major metropolitan cities in South Korea: impacts of policy interventions

Abstract Ambient fine particulate matter (PM2.5) is one of the most concerning pollutants, characterized by its diverse chemical composition. Although various studies have revealed PM2.5 chemical components, there is limited knowledge on how to reduce PM2.5 concentrations through administrative policies focusing on source management. We compared PM2.5 compositional characteristics and performed source apportionment using the positive matrix factorization in four metropolitan cities (Seoul, Daejeon, Gwangju, and Ulsan) in South Korea from 2014 to 2018. The annual average of PM2.5 concentrations exceeded the annual national ambient air quality standard of 15 μg m−3 in all areas while secondary inorganic aerosols constituted the largest fraction of PM2.5. This implies that secondary formation from gaseous precursors in the atmosphere was the main factor contributing to ambient PM2.5. However, the concentrations of PM2.5 constituents varied significantly across cities, suggesting that PM2.5 is a heterogeneous pollutant considerably influenced by region-specific conditions. In line with the chemical composition, secondary nitrate, secondary sulfate, and mobile-related sources were found to be significant contributors of PM2.5. Additionally, the extent of contribution from each source varied across the study regions. We also evaluated the impacts of policy interventions by comparing the PM2.5 composition and source apportionment before and after the policies for improving air quality. Intensive programs focused on the vehicle sector in Seoul led to a considerable decrease in the concentrations of carbonaceous compounds and mobile-related sources. In addition, strengthened regulations on coal-fired power plants (CFPPs) since 2016 have influenced the contributions of coal combustion sources in two cities adjacent to the west coastal area, where approximately half of the CFPPs of the country are densely distributed. Overall, the study’s findings indicate that region-specific PM2.5 chemical constituents and source contributions should be considered for establishing PM2.5-related policies, considering the high heterogeneity of PM2.5.

Ozone-Induced Lung Injury are Mediated Via PPAR-Mediated Ferroptosis in Mice.

In recent years, the concentration of PM2.5 in China has decreased, while the concentration of ozone remains rising. Exposure to ozone contributes to respiratory illnesses; however, little is known about the underlying molecular mechanisms. The present study established an ozone-induced lung injury mice model to investigate potential molecular biomarkers and toxic mechanisms. Collected and analyzed the ozone pollution data in Xinxiang city from 2015 to 2022. At the same time, 24 male C57BL/6 mice were randomly assigned to control group and ozone exposure group. The ozone exposure concentration is 1ppm, with 4h of daily exposure for 33 consecutive days. HE staining was used to assess lung histological alterations and lung injury. High-throughput sequencing performed on the lung tissues of mice was used to analyze the differential expressed genes and signal transduction pathways. Xinxiang city is suffering from ozone pollution, especially in summer. HE staining showed that the ozone exposure could induce obvious inflammatory cell infiltration, alveolar wall thickening, or fracture. Transcriptome data revealed that there is a 145 differentially expressed genes between two groups and the genes enriched in PPAR signaling pathway, ferroptosis. The pivotal genes in the PPAR pathway including Adipoq, Lpl, Pck1, and Plin1 expression were significantly reduced. Additionally, the expression of Acsl6 and Scl7a11, which are close to PPAR pathway and ferroptosis has decreased. Ozone exposure could disrupt the lipid metabolism balance via downregulating lipid peroxidation-related genes through the PPAR signaling pathway, which further induced lung cell ferroptosis and aggravated lung injury in mice.

Analysis of pollution status and influencing factors of polybrominated diphenyl ethers in household dust in five cities in northern China

Objective: To investigate the pollution levels and influencing factors of polybrominated diphenyl ethers (PBDEs) in household dust in five cities in northern China. Methods: Based on the "Chinese Indoor Environment and Health Surveillance" project carried out by the National Institute of Environmental Health, Chinese Center for Disease Control and Prevention in 2018-2019, during the warm season (April 2018 to September 2018) and the cold season (November 2018 to March 2019), Lanzhou in Northwest China, Shijiazhuang in North China, Panjin in Northeast China, Luoyang in Central China, and Qingdao in East China were selected as the research sites. A total of 87 families were recruited to study residences in real-life scenarios. At the same time, dust samples were collected to detect the concentration of PBDEs. The level of household environmental indicators was measured, and the residential building characteristics and family behavior habits were collected through questionnaires. A total of 142 valid dust samples and 140 valid questionnaires were obtained. The differences in PBDE concentrations across seasons, wind zones, residential building characteristics, and family habits were analyzed. The exploratory factor analysis was performed to investigate the possible sources of PBDEs, and multivariate linear regression was used to explore the factors influencing PBDEs in household dust. Results: The M (Q1, Q3) of total PBDE concentrations in 142 household dust samples in five cities was 144.51 (106.61, 222.65) ng/g in the warm season and 145.10 (98.57, 180.65) ng/g in the cold season, respectively. There were seasonal differences in the concentration of ∑12PBDEs in Luoyang and Shijiazhuang (P<0.01). The concentration of BDE-71 was highest among PBDE homologues, followed by BDE-66 and BDE-47. Three factors were extracted by exploratory factor analysis in the warm season, and the cumulative variance contribution rate was 67.90%. The multivariate linear regression showed that the house completion less than ten years [β (95%CI): 0.186 (0.013, 0.359)], infrequent home cooking [β (95%CI):-0.342 (-0.570, -0.114)], and increased residential PM10 concentration [β (95%CI): 0.001 (0.000, 0.002)] during the warm season, as well as the house far from driveway [β (95%CI): 0.093 (0.013, 0.172)], house area less than 90 m2 [β (95%CI):-0.138 (-0.264, -0.013)], and lower residential xylene concentration [β (95%CI):-0.006 (-0.011, -0.001)] during the cold season might be related to the elevated concentrations of ∑12PBDEs in household dust. Conclusion: The pollution of PBDEs in household dust in five northern cities is at a medium to high level. Years of house completion, frequency of cooking at home, residential PM10 concentration, distance from house to driveway, house area, and residential xylene concentration may influence household PBDE concentrations.

Selection and evaluation of commercial low-cost devices for indoor air quality monitoring in schools

The use of low-cost sensors for monitoring Indoor Air Quality (IAQ) in schools has shown promising results, with the commercialisation of these devices increasing worldwide. This study aims to identify an effective, commercially available low-cost device for IAQ monitoring in schools.Four low-cost devices (AirVisual Pro, PocketLab Air, PurpleAir PA-II-SD and uRAD Monitor A3) were selected for both qualitative and performance evaluations. Field tests were conducted in six indoor microenvironments within a nursery and a primary school. The low-cost devices were co-located with research-grade instruments to obtain reference concentrations of PM1, PM2.5, PM10, CO2, VOC, formaldehyde and O3.The qualitative evaluation revealed limitations, including data loss, negative or erratic values, inconsistent timestamps, and connectivity issues. PM low-cost devices exhibited better performance during non-occupancy periods but faced challenges during periods of occupancy. All devices tended to underestimate measurements compared to reference data, although AirVisual Pro performed better for PM2.5 during occupancy. Furthermore, CO2 concentrations were slightly overestimated, showing improved accuracy during occupancy periods. While formaldehyde peaks were detected by the low-cost device, overall performance was weak for both formaldehyde and O3.The results indicated that AirVisual Pro demonstrated the best overall performance, and presents itself as a promising tool for IAQ monitoring in schools. However, performance evaluations should be tailored to specific microenvironments and occupancy periods. Despite some acceptable performance results, real-context use of the selected low-cost device should be preceded by a proper calibration. Additionally, long-term performance evaluation should be considered in future studies.

Resuspension of inhalable particles from clothing: A manikin-based chamber study

Clothing plays a significant role in facilitating inhalation exposure to particulate matter (PM). Nevertheless, there is a lack of studies investigating PM resuspension from clothing. This study aims to quantify size-resolved PM resuspension rate (RR) from clothing while exploring the effects of factors influencing this process. In a controlled chamber, we deposited Arizona Test Dust on a seated and clothed thermal manikin. The seated manikin was then placed in a resuspension chamber to perform arm movements using a consistent test mechanism. We evaluated the size-resolved resuspension rates in the diameter range 0.3–10 μm as a function of long-sleeve clothing type (cotton shirts vs. polyacrylic sweaters), relative humidity (RH) (35 vs. 70 %), dust loading (204 vs. 321 mg/m2), and movement intensity (0.25, 0.5, and 0.75 Hz). The short-term PM10 concentration in the breathing zone was 1.25 times higher than in the bulk air during resuspension. The size-dependent RR varied between 0.01 h−1 and 0.06 h−1. Higher RR was associated with higher movement intensity and dust loading on clothing, while a small dependence was found on clothing type and RH. The results offer a valuable dataset for enhancing current inhalation exposure models related to indoor aerosols and for developing targeted interventions to reduce exposure to particles associated with clothing.

Variations of black carbon, particulate matter and nitrogen oxides mass concentrations in urban environment with respect to winter heating period and meteorological conditions

The atmospheric concentrations of particulate pollution are of great scientific concern due to their impact on both human health and environment. This study aimed to investigate the concentration of black carbon (BC), particulate matter with an aerodynamic diameter of less than 10 micrometres (PM10) and nitrogen oxides (NOx) at an urban background environment throughout the year, and understand the impact of winter heating and meteorology on its concentration level. The campaign covered heating and non-heating periods, from 1 June 2021 to 31 May 2022. During the heating period, the mass concentrations of BC, PM10 and NOx were 1.17, 24.9 and 19.4 µg m–3, respectively. The analysis revealed that the mass concentrations of BC and NOx were 1.9 and 1.4 times greater during the heating period, respectively, compared to the non-heating period. In contrast, PM10 remained almost constant during the heating (19.4 µg m–3) and non-heating periods (20.0 µg m–3). Throughout the year, the BC mass concentration was dominated by BCFF (71.2%) originating from fossil fuel combustion with a maximum (8.43 µg m–3) during the heating period. Moreover, wind speed presented a weak negative correlation with BC (r = –0.40), PM10 (r = –0.19) and NOx (r = –0.40) during the heating period.

Mobile monitoring of air pollutant concentration in the park of Urumqi, China

The concentrations of PM2.5, PM10, O3 and NO2 in Urumqi People's Park were monitored by mobile monitoring in July and October 2023, and the temporal and spatial changes of pollutant concentrations in urban parks and their influencing factors were analyzed. The results show that park can effectively reduce PM and NO2 concentration, increase O3 concentration. PM concentration in the park was higher in the morning than the noon. O3 and NO2 concentration is lower in the morning than the noon. The concentration within the park was lower than that outside the park. The mitigative effect of pollutants in the park was better in summer than in autumn. The concentration of PM in the park showed a high value aggregation, and PM2.5 and PM10 showed the same spatial distribution in the high value cluster, and the pollution of both showed homology in summer. O3 and NO2 concentrations tend to accumulate at low value cluster. Pollutants are affected by the local environment. PM2.5 concentration is greatly affected by wind speed and distance from water, O3 concentration is greatly affected by temperature and average distance from road. The closer to the road, the higher the concentration of NO2. Attention should be paid to the landscape design of the buffer zone of 30–50 m with the high pollution area. This study can provide reference for park planning and design.

Differences in cellular and molecular processes in exposure to PM2.5 and O3

Epidemiological and toxicological studies have shown that PM2.5 and O3 could pose significant risks to human health, such as an increased incidence of respiratory and cardiovascular diseases. Usually, the adverse health outcomes induced by PM2.5 and O3 exposure are similar. However, PM2.5 and O3 have distinct physical and chemical properties, with PM2.5 being a solid–liquid mixture and O3 being a strongly oxidizing gaseous pollutant. Therefore, we speculated that there are some differences in biological processes induced by PM2.5 and O3 exposure. In the present study, we investigated the differences induced by PM2.5 and O3 exposure from the perspective of cellular and molecular processes. Firstly, the pulmonary epithelial cells (BEAS-2B) were exposed to different concentrations of PM2.5 or O3 at different durations. Then, we chose experimental models with the concentrations and duration at which the cell survival rate was 50 % after exposure to PM2.5 and O3, which were 100 μg/mL for 24 h for PM2.5, and 200 ppb for 4 h for O3. Our findings indicate that PM2.5 infiltrates cells via endocytosis without causing significant damage to cell membranes, while O3 induces lipid peroxidation at the cell surface. Moreover, the detection of mitochondrial function showed that the content of ATP was significantly reduced after exposure to both PM2.5 and O3. However, we found a significant difference in mtDNA copy number. PM2.5 exposure increased the mtDNA copy number by up-regulating the expression of fission genes (Fis1, Mff, Dnm1). O3 exposure decreased it by up-regulating the expression of fusion gene (Mfn1, Mfn2) and down-regulating the expression of fission gene (Fis1, Dnm1). These results indicate that although both PM2.5 and O3 exposure induced almost exactly similar adverse health outcomes, significant differences do exist in cellular and molecular processes.

Investigating the trend of the vertical distribution of ambient air pollutants (PM2.5, PM10, NOX, and NO2); A systematic review

BackgroundNumerous investigations have explored variations in vertical air pollutant concentrations, yielding diverse findings. So, we have conducted this systematic review to gain a more comprehensive understanding of the vertical distribution of air pollutant concentrations (PM2.5, PM10, NOX, and NO2) and the influencing factors. MethodsRelevant studies were identified by searching the three central electronic databases, PubMed, Web of Science, and Scopus, from the beginning of 2000 to the end of 2023. This study included original articles published in English that examine the pollutant concentration variations below 500 m. FindingOf 3614 articles, 57 studies met our criteria. Our findings showed a decline in PM2.5 and NOX concentrations as altitude increased, while NO2 concentrations exhibited an increase. Conversely, no statistically significant relationship was identified between altitude and PM10 concentrations. The regression analysis yielded coefficients for the relationship between concentration and altitude (0-500 m) as follows: PM2.5 (-0.11), PM2.5/PM10 (0.0008), NOX (-0.11), and NO2 (0.13). Conducting additional research on this topic and investigating the impact of meteorological parameters on pollutant concentrations at different altitudes enhances our understanding of the vertical distribution of pollutant concentrations.

Pinpointing sources of pollution using citizen science and hyperlocal low-cost mobile source apportionment

Currently, methodologies for the identification and apportionment of air pollution sources are not widely applied due to their high cost. We present a new approach, combining mobile measurements from multiple sensors collected from the daily walks of citizen scientists, in a high population density area of Birmingham, UK. The methodology successfully pinpoints the different sources affecting the local air quality in the area using only a handful of measurements. It was found that regional sources of pollution were mostly responsible for the PM2.5 and PM1 concentrations. In contrast, PM10 was mostly associated with local sources. The total particle number and the lung deposited surface area of PM were almost solely associated with traffic, while black carbon was associated with both the sources from the urban background and local traffic. Our analysis showed that while the effect of the hyperlocal sources, such as emissions from construction works or traffic, do not exceed the distance of a couple of hundred meters, they can influence the health of thousands of people in densely populated areas. Thus, using this novel approach we illustrate the limitations of the present measurement network paradigm and offer an alternative and versatile approach to understanding the hyperlocal factors that affect urban air quality. Mobile monitoring by citizen scientists is shown to have huge potential to enhance spatiotemporal resolution of air quality data without the need of extensive and expensive campaigns.

Individual and joint exposure to air pollutants and patterns of multiple chronic conditions.

Existing research on the detrimental effects of air pollution and its mixture on multiple chronic conditions (MCC) is not yet fully recognized. Our objective was to examine if individual and joint exposure to air pollution is associated with the incidence and patterns of MCC. Totally 10,231 CHARLS 2015 participants aged over 45 years and 1,938 without MCC were followed up in 2018 and 2020. Residential-levelcumulative personal exposure concentrations of PM1, PM10, PM2.5, CO, O3, NO2, SO2, NO3-, Cl-, NH4+, and SO42- at the residential level were determined utilizing a spatio-temporal random forest model with a spatial resolution of 0.1° × 0.1°. In the cross-sectional and longitudinal research, logistic regression, cox regression analysis, and quantile g-computation were utilized to estimate the single and joint effect with MCC and its patterns, respectively. Interaction analyses and stratified analyses were also performed. A correlation was observed between the prevalence of cardiovascular illnesses and the presence of all 11 major air pollutants. PM2.5, PM10, NH4+, NO3-, CO, and SO42- are associated with an increased frequency of respiratory disorders. An increase of PM2.5, PM1, PM10, NO2, and SO2 (a 10µg/m3 rise), CO (a 0.1mg/m3 rise), and PMCs (Cl-, NH4+, NO3-, and SO42-) (a 1µg/m3 rise) corresponded to the HRs (95% CI) for developing MCC of 1.194 (95% CI: 1.043, 1.367), 1.362 (95% CI: 1.073, 1.728), 1.115 (95% CI: 1.026, 1.212), 1.443 (95% CI: 1.151, 1.808), 3.175 (95% CI: 2.291, 4.401), 1.272 (95% CI: 1.149,1.410), 1.382 (95% CI: 1.011, 1.888), 1.107 (95% CI: 1.003, 1.222), 1.035 (95% CI: 0.984, 1.088), and 1.122 (95% CI: 1.086, 1.160), respectively. SO2 was the predominant contributor to the combined effect (HR: 2.083, 95% CI: 1.659-2.508). Gender, age, drinking, and health status could modify the effects of air pollutants on MCC patterns. Long-term exposure to air pollution is correlated to the incidence and patterns of MCC in middle-aged and elderly Chinese individuals. Preventive methods are essential to safeguarding those susceptible to MCC.

Annual Variations of PM10, PM2.5 and PM1.0 Fraction at an Urban Site in Ansan, Korea

This study examines particulate matter (PM) concentrations, specifically PM10, PM2.5, and PM1.0, at an urban site in Ansan, South Korea. Three BAM-1020 continuous monitors measured PM10, PM2.5, and PM1.0 hourly from January to December 2021, with data acquisition rates of 97.1%, 97.3%, and 93.4%, respectively. Average annual concentrations were 45.7±48.4 µg/m³ (PM10), 26.4±22.7 µg/m³ (PM2.5), and 18.5±14.5 µg/m³ (PM1.0). PM10 was 91% of the annual air quality standard, while PM2.5 exceeded this standard by 176%, indicating severe pollution. Statistical analyses using probability density function (PDF) and cumulative distribution function (CDF) showed 98.5% of data converged at 150 µg/m³ (PM10), 75 µg/m³ (PM2.5), and 50 µg/m³ (PM1.0), with the remaining 1.5% corresponding to approximately 131 hours, annually. In 2021, all six observed yellow dust events occurred in spring (March to May). PM10, PM2.5, and PM1.0 concentrations increased from January to March, peaked in March, decreased until September, and rose again. The coarse fraction ratio increased stepwise from February to May, likely due to yellow dust and episodes of high PM concentration in the spring. The PM1.0 concentration was higher in summer and fall compared with that in spring and winter. The PM1.0/PM2.5 ratio was highest in summer and fall even though the annual PM1.0concentration was lowest, suggesting a higher secondary formation rate of fine particles during these periods. This underscores the need for further scientific investigation on PM1.0. The study provides insights into the simultaneous observation and distribution characteristics of PM10, PM2.5, and PM1.0, highlighting the mass concentration, distribution, and ratio of PM1.0. These findings are crucial for understanding PM distribution in Ansan, an industrial complex, and can serve as essential data for chemical composition comparisons, data validation, public health strategies, and cost-benefit analyses for regional PM improvement.

Modeling of PM10 Particulate Matter in Ahvaz City Using Remote Sensing and Meteorological Parameters

Introduction: In recent years, remote sensing (RS) products have emerged as effective tools for monitoring air pollution. This study aims to predict the concentrations of particulate matter with a diameter smaller than 10μm (PM10) using a multivariate linear regression (MLR) model, incorporating both Aerosol Optical Depth (AOD) products and meteorological parameters. Material and Methods: In this study, data on PM10 concentrations, Aerosol Optical Depth (AOD), and meteorological parameters (wind speed, temperature, humidity, and horizontal visibility) were used. The study focused on the time 15:00 each day, as this time was identified as having significant data relevance. The methodology section also consisted of three steps: 1) pairwise correlation analysis: The relationship between meteorological parameters, AOD, and PM10 was assessed using the pairwise correlation method. 2) Model development: A MLR model was developed to predict PM10 concentrations. 3) Validation: The model was validated using a separate dataset, ensuring that 70% of the data was used for training, and 30% for testing and validation. Results: The pairwise correlation analysis revealed a strong correlation (0.86) between AOD remote sensing index and PM10. The highest correlation (0.9) was observed during the spring season. The five developed equations to estimate the PM10 index yielded correlation coefficients ranging from 0.86 to 0.90. Notably, the highest correlation was achieved when AOD data and all the meteorological parameters were u tilized simultaneously. These results highlighted the utility of remote sensing products and meteorological data in air quality monitoring and prediction. Conclusion: This study demonstrates that a MLR model incorporating AOD and meteorological parameters can effectively predict PM10 concentrations in Ahvaz City, particularly during dust storms in hot seasons. These findings can aid policymakers and public health officials in developing strategies to mitigate the adverse effects of dust storms on air quality and public health.

ENVIRONMENTAL POLLUTION IN THE CITY OF BUCHAREST

The work covers air quality monitoring tools in Bucharest, major industrial facilities impacting pollution and the city's eight air quality monitoring stations. Data on pollutant emissions from Bucharest's thermal power plants (SO2, NOx and dust) are presented. Finally, the paper graphically presents the annual average concentrations of NO2, SO2, PM10 and O3 at the monitoring stations and examines pollution peaks and daily limit exceedances from 2017 to 2022.

The mediating effect of TyG-related indicators between long-term exposure to particulate matter and cardiovascular disease: evidence from a national longitudinal cohort study

BackgroundAmbient particulate matter (PM) exposure is recognized as a risk factor for cardiovascular disease (CVD). However, the extent to which PM exposure is associated with CVD via triglyceride glucose (TyG)-related indicators remains unknown. This study examines the relationship between long-term PM exposure and CVD events, further assessing whether TyG-related indicators mediate this association.MethodsThis cohort study involved 7,532 individuals aged at least 45 years who were not diagnosed with CVD in 2011 from the China Longitudinal Study of Health and Retirement (CHARLS) and were followed up for the occurrence of CVD until 2020. The annual PM concentration data at the city level, with aerodynamic diameters ≤ 1 μm (PM1), ≤ 2.5 μm (PM2.5), and ≤ 10 μm (PM10), were obtained from the ChinaHighAirPollutants (CHAP). The average concentration of PM in the 3 years before the baseline survey in 2011 was defined as the long-term exposure level of the individual. The relationship between PM exposure and CVD incidence was examined via Cox proportional hazards models, with a focus on probing the role of TyG-related indicators through mediation analysis.ResultsA total of 1,865 individuals with CVD were diagnosed over the span of a 7.4-year follow-up period. The 3-year average concentrations before baseline were 31.29 µg/m³ for PM1, 56.03 µg/m³ for PM2.5, and 95.73 µg/m³ for PM10. In fully adjusted model, the Cox proportional hazards models revealed that an increase of 10 µg/m³ in the PM1, PM2.5, and PM10 exposure concentrations corresponded to elevated CVD risk, with HRs (95% CI) of 1.135 (1.078–1.195), 1.092 (1.062–1.123), and 1.075 (1.059–1.090), respectively. Mediation analyses further suggested that the correlation between PM exposure and CVD could be partly mediated via TyG-BMI, TyG-WC, and TyG-WHtR, with mediation proportions varying from 5.54 to 15.30%.ConclusionA significant correlation was observed between long-term PM exposure and increased CVD risk, with TyG-related indicators, such as TyG-BMI, TyG-WC, and TyG-WHtR, partially mediating this relationship.

The source, transport, deposition and direct radiative effect of mineral dust over western China: A modeling study of July 2022 with focus on the Tibetan Plateau

A Regional Air Quality Model System (RAQMS) driven by WRF was applied to explore the emission, transport, deposition, and direct radiative effect of mineral dust over western China in July 2022, with focus on the Tibetan Plateau (TP). Model validation against ground and satellite observations demonstrated the model reproduced meteorological variables, PM10 concentration, aerosol optical depth (AOD), and extinction coefficients in the vertical reasonably well. There was a dust event during 3–7 July 2022, which was originated from the Taklimakan Desert (TKD) and affected eastern and central TP under anticyclonic flows, resulting in the maximum hourly PM10 concentration exceeding 50 μg m−3 in Lhasa. Shortwave radiation was reduced considerably by dust aerosols over eastern TP, with the maximum decrease in daytime mean shortwave radiation reaching 30 W m−2 around Nyingchi on 5 July. Anthropogenic aerosols dominated PM10 mass in the capital cities of western China (54–67 %), while dust aerosols were dominant in the cities near the deserts. During this dust event, dust aerosols from TKD and Qaidam Desert (QDD) significantly influenced eastern TP, with dust contributions to PM10 mass concentration of 52 %, 76 % and 69 %, respectively, in Chamdo, Lhasa and Nyingzhi, respectively. The total dust emission in western China was about 10.6 Tg in July 2022, with the largest contribution from TKD (63.5 %), followed by Gobi Desert (GB) (26 %). The total deposition of dust was estimated to be 6.2 Tg, in which TKD and GB contributed 66 % and 22 %, respectively. During the study period, about 418 Gg dust aerosols were deposited on TP, 49 % of which was from TKD and 25 % from QDD. Foreign dust sources contributed approximately 7 % and 9 % to dust concentration and total deposition over TP, respectively. Over southern TP, the source contribution to dust deposition was estimated to be 42 %, 24 % and 21 % from TKD, foreign sources and QDD, respectively, suggesting potentially important impact of long-range transboundary dust transport on deposition, surface albedo and climate over TP.

Chemical composition, mutagenicity, and cytotoxicity of urban submicron particulate matter (PM1) in Agra, India

This study, conducted in Agra, India, examined the mass concentrations, chemical compositions, and seasonal variations of submicron particles (PM1). The concentrations of metals, water-soluble inorganic ions (WSIs) including anions (F−, Cl−, NO₃−, SO₄2−) and cations (Ca2+, K+, Mg2+, NH₄+, Na+), organic carbon (OC) and elemental carbon (EC) and polycyclic aromatic hydrocarbons (PAHs) in PM1 extract were determined using Inductively Coupled Plasma-Optical Emission Spectroscopy (ICP-OES), Ion Chromatography, Thermogravimetric Analysis and Gas Chromatography-Mass Spectrometry (GC–MS) respectively. For morphological observation of PM1 particles, Field Emission Scanning Electron Microscopy-Energy Dispersive X-ray spectrometry (FESEM-EDS) was used. The annual average concentration of PM1 was 82.9 ± 33.4 μg/m3, which exceeds the World Health Organisation's (WHO) safe limit for PM2.5 of 5 μg/m3 by a factor of 17. The PM1 mass composition included metals (31 %), WSIs (28 %), OC and EC (9.8 %), and PAHs (0.4 %). Winter recorded the highest PM1 concentration (96.1 ± 25.8 μg/m3), followed by post-monsoon, summer, and monsoon seasons. The average concentration of PAHs was 364.6 ± 226.6 ng/m3. Positive Matrix Factorization (PMF) identified traffic, emissions from biomass/coal and wood combustion, industrial/stationary sources, and secondary aerosols as potential contributors. The Ames test revealed the presence of frameshift mutations and base pair substitutions, especially in winter and post-monsoon. Additionally, PM1 exhibited cytotoxic effects on V-79 cells, with heightened toxicity during winter and prolonged exposure in other seasons. This study underscores the urgent need to address local emission sources and establish regulatory standards for PM1 in urban areas.