Airborne Aluminum as an Underestimated Source of Human Exposure: Quantification of Aluminum in 24 Human Tissue Types Reveals High Aluminum Concentrations in Lung and Hilar Lymph Node Tissues.

Aluminum (Al) is the most abundant metal in the earth's crust, and humans are exposed to Al through sources like food, cosmetics, and medication. So far, no comprehensive data on the Al distribution between and within human tissues were reported. We measured Al concentrations in 24 different tissue types of 8 autopsied patients using ICP-MS/MS (inductively coupled plasma-tandem mass spectrometry) under cleanroom conditions and found surprisingly high concentrations in both the upper and inferior lobes of the lung and hilar lymph nodes. Al/Si ratios in lung and hilar lymph node samples of 12 additional patients were similar to the ratios reported in urban fine dust. Histological analyses using lumogallion staining showed Al in lung erythrocytes and macrophages, indicating the uptake of airborne Al in the bloodstream. Furthermore, Al was continuously found in PM2.5 and PM10 fine dust particles over 7 years in Upper Austria, Austria. According to our findings, air pollution needs to be reconsidered as a major Al source for humans and the environment.

Effects of long-term exposure to outdoor air pollution on COVID-19 incidence: A population-based cohort study accounting for SARS-CoV-2 exposure levels in the Netherlands.

Several studies have linked air pollution to COVID-19 morbidity and severity. However, these studies do not account for exposure levels to SARS-CoV-2, nor for different sources of air pollution. We analyzed individual-level data for 8.3 million adults in the Netherlands to assess associations between long-term exposure to ambient air pollution and SARS-CoV-2 infection (i.e., positive test) and COVID-19 hospitalisation risks, accounting for spatiotemporal variation in SARS-CoV-2 exposure levels during the first two major epidemic waves (February 2020-February 2021). We estimated average annual concentrations of PM10, PM2.5 and NO2 at residential addresses, overall and by PM source (road traffic, industry, livestock, other agricultural sources, foreign sources, other Dutch sources), at 1 × 1 km resolution, and weekly SARS-CoV-2 exposure at municipal level. Using generalized additive models, we performed interval-censored survival analyses to assess associations between individuals' average exposure to PM10, PM2.5 and NO2 in the three years before the pandemic (2017-2019) and COVID-19-outcomes, adjusting for SARS-CoV-2 exposure, individual and area-specific confounders. In single-pollutant models, per interquartile (IQR) increase in exposure, PM10 was associated with 7% increased infection risk and 16% increased hospitalisation risk, PM2.5 with 8% increased infection risk and 18% increased hospitalisation risk, and NO2 with 3% increased infection risk and 11% increased hospitalisation risk. Bi-pollutant models suggested that effects were mainly driven by PM. Associations for PM were confirmed when stratifying by urbanization degree, epidemic wave and testing policy. All emission sources of PM, except industry, showed adverse effects on both outcomes. Livestock showed the most detrimental effects per unit exposure, whereas road traffic affected severity (hospitalisation) more than infection risk. This study shows that long-term exposure to air pollution increases both SARS-CoV-2 infection and COVID-19 hospitalisation risks, even after controlling for SARS-CoV-2 exposure levels, and that PM may have differential effects on these COVID-19 outcomes depending on the emission source.

Air concentrations of trace elements in a municipality under the influence of Tarragona petrochemical complex: Human health risks.

One of the largest petrochemical complexes of southern Europe is located in Tarragona County (Catalonia, Spain). Despite environmental monitoring is routinely conducted in the area, the long-term occurrence of airborne trace elements has been poorly investigated. In the present study, the concentrations of arsenic (As), cadmium (Cd), chromium (Cr), nickel (Ni), lead (Pb) and vanadium (V) were analysed in air samples collected in El Morell, a town potentially impacted by the petrochemical. Air samples were simultaneously collected in the town of Cambrils, as a background site. Meteorological data and retro trajectories analysis were used to evaluate the impact of the petrochemical industry on the levels of trace elements in air. Subsequently, human health risks due to inhalation exposure to the trace elements were also assessed. Except for V, air concentrations were significantly higher near the oil refinery than the background levels. Human health risks were also estimated to be higher in the vicinity of the petrochemical complex. In turn, air inhalation of Pb and V was higher than their dietary intakes. The present data should be considered only as preliminary, since the sampling was taken during only three weeks, which is an insufficient period to extract reliable conclusions. Further long-term studies should be focused on assessing the influence of temporary variables, such as meteorological conditions and fugitive or sporadic emissions.

Particulate matters (PM2.5, PM10) and the risk of depression among middle-aged and older population: analysis of the Korean Longitudinal Study of Aging (KLoSA), 2016-2020 in South Korea.

BACKGROUND: There is a growing concern that particulate matter (PM) such as PM2.5 and PM10 has contributed to exacerbating psychological disorders, particularly depression. However, little is known about the roles of these air pollutants on depression in elderly. Therefore, this study aimed to examine the association between PM2.5 and PM10, and depression in the elderly population in South Korea. METHODS: We used panel survey data, the Korean Longitudinal Study of Aging (KLoSA), administered by the Labor Institute during the study period of 2016, 2018, and 2020 covering 217 districts in South Korea (n = 7674). Annual district-specific PM2.5 and PM10 concentrations were calculated for the study period from the monthly prediction concentrations produced by a machine-learning-based ensemble model (cross-validated R2: 0.87), then linked to the people matching with year and their residential district. We constructed a generalized estimating equation (GEE) model with a logit link to identify the associations between each of the long-term PM2.5 and PM10 exposures and depression (CES-D 10) after adjusting for individual and regional factors as confounders. RESULTS: In single-pollutant models, we found that long-term 10 [Formula: see text] increments in PM2.5 (OR 1.36, 95% CI 1.20-1.56) and PM10 (OR 1.19, 95% CI 1.10-1.29) were associated with an increased risk of depression in the elderly. Associations were consistent after adjusting for other air pollutants (NO2 and O3) in two-pollutant models. In addition, the impacts substantially differed by regions grouped by the tertile of the population density, for which the risks of particulate matters on depression were substantial in the middle- or high-population-density areas in contrast to the low-population-density areas. CONCLUSIONS: Long-term exposure to PM2.5 and PM10 was associated with a higher risk of developing depression in elderly people. The impact was modified by the population density level of the region where they reside.

Human health impacts attributable to inhalation exposure of particulate matter (PM10 and PM2.5) during the Holi festival.

OBJECTIVE: The present study focuses on residential areas of Delhi to identify the elevated levels of ambient PM10 and PM2.5 due to biomass burning followed by the coloring activity in the Holi festival celebrated at the end of the winter season. This study also focuses on the health risk assessment and mortality among different age groups due to the change in particulate matter levels during the Holi festival in Delhi, India. MATERIALS AND METHODS: Secondary data of particulate matters have been procured from the Central Pollution Control Board (CPCB), Delhi Pollution Control Committee (DPCC), and Indian Institute of Tropical Meteorology (IITM), Pune for the period of the pre-, during, and post-Holi period for the year 2018-2020 at four selected residential locations in Delhi, India. The health impacts of particle inhalation were quantified using the AirQ + models. RESULTS: The results indicated the levels of PM10 and PM2.5 rise about 3-4 times higher during the Holi festival than on normal days, resulting in health risks and causing an excess number of mortality and Asthma cases in Delhi. Such cases were also found to be higher in 2018, followed by 2019 and 2020 at all the selected locations in Delhi. CONCLUSIONS: The study linked the increasing particulate levels in the Holi festival with the increased health risk through short-term exposure of the population. The excess number of cases (ENCs) of mortality, all causes of mortality among adults (age > 30 years) associated with short-term exposure to particulate were also identified.

Early-life exposure to ambient air pollutants and kidney function in adolescents: a cohort study based on the 'Children of 1997' Hong Kong birth cohort.

OBJECTIVES: Air pollution is increasingly linked to impaired kidney function in adults. However, little is known about how early-life exposure to air pollutants affects kidney function in adolescents. STUDY DESIGN: Cohort study. METHODS: We leveraged data from the 'Children of 1997' Hong Kong population-representative birth cohort (N = 8327). Residential exposure to average ambient levels of four air pollutants, including inhalable particle (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), and nitrogen monoxide (NO), during in utero, infancy, and childhood periods was estimated using the inverse distance weighting. Kidney function was assessed using estimated glomerular filtration rate (eGFR) calculated from age-adjusted equations for adolescents. Generalized linear regression was used to examine the association of air pollutant exposure in each period with kidney function at 17.6 years. Two-pollutant models tested the robustness of the association. RESULTS: Of the 3350 participants included, 51.4% were boys. Exposure to PM10 was associated with poorer kidney function. Each interquartile range increment in PM10 was inversely associated with eGFR (ß: -2.933, 95% confidence interval -4.677 to -1.189) in utero, -2.362 (-3.992 to -0.732) infancy, -2.708 (-4.370 to -1.047) childhood, and -2.828 (-4.409 to -1.247) overall. Exposure to PM10 and SO2in utero had a stronger inverse association with kidney function in males. The associations were robust to PM10 exposure in two-pollutant models. CONCLUSIONS: Our findings suggest that early-life exposure to ambient PM10 and SO2 is associated with reduced kidney function in adolescents, especially exposure in utero.

The impact of air pollutants on spontaneous abortion: a case-control study in Tongchuan City.

OBJECTIVES: Studies related to air pollutants and spontaneous abortion in urban northwestern China are scarce, and the main exposure windows of pollutants acting on pregnant women are unclear. STUDY DESIGN: Case-control study. METHODS: Data were collected from pregnant women in Tongchuan City from 2018 to 2019. A total of 289 cases of spontaneous abortion and 1156 cases of full-term labor were included and analyzed using a case-control study. Logistic regression models were developed to explore the relationship between air pollutants and spontaneous abortion after Chi square analysis and Air pollutant description. RESULTS: O3 (odds ratio [OR] = 1.028) is a risk factor for spontaneous abortion throughout pregnancy. PM2.5 (OR = 1.015), PM10 (OR = 1.010), SO2 (OR = 1.026), and NO2 (OR = 1.028) are risk factors for spontaneous abortion in the 30 days before the last menstrual period. PM2.5 (OR = 1.015), PM10 (OR = 1.013), SO2 (OR = 1.036), and NO2 (OR = 1.033) are risk factors for spontaneous abortion in the 30-60 days before the last menstrual period. PM2.5 (OR = 1.028), PM10 (OR = 1.013), SO2 (OR = 1.035), and NO2 (OR = 1.059) are risk factors for spontaneous abortion in the 60-90 days before the last menstrual period. CONCLUSION: Exposure to high levels of air pollutants may be a cause of increased risk of spontaneous abortion, especially in the first trimester of the last menstrual period.

Indication Variability of the Particulate Matter Sensors Dependent on Their Location.

Particulate matter (PM) suspended in the air significantly impacts human health. Those of anthropogenic origin are particularly hazardous. Poland is one of the countries where the air quality during the heating season is the worst in Europe. Air quality in small towns and villages far from state monitoring stations is often much worse than in larger cities where they are located. Their residents inhale the air containing smoke produced mainly by coal-fired stoves. In the frame of this project, an air quality monitoring network was built. It comprises low-cost PMS7003 PM sensors and ESP8266 microcontrollers with integrated Wi-Fi communication modules. This article presents research results on the influence of the PM sensor location on their indications. It has been shown that the indications from sensors several dozen meters away from each other can differ by up to tenfold, depending on weather conditions and the source of smoke. Therefore, measurements performed by a network of sensors, even of worse quality, are much more representative than those conducted in one spot. The results also indicated the method of detecting a sudden increase in air pollutants. In the case of smokiness, the difference between the mean and median indications of the PM sensor increases even up to 400 µg/m3 over a 5 min time window. Information from this comparison suggests a sudden deterioration in air quality and can allow for quick intervention to protect people's health. This method can be used in protection systems where fast detection of anomalies is necessary.

Performance Assessment of Two Low-Cost PM2.5 and PM10 Monitoring Networks in the Padana Plain (Italy).

Two low-cost (LC) monitoring networks, PurpleAir (instrumented by Plantower PMS5003 sensors) and AirQino (Novasense SDS011), were assessed in monitoring PM2.5 and PM10 daily concentrations in the Padana Plain (Northern Italy). A total of 19 LC stations for PM2.5 and 20 for PM10 concentrations were compared vs. regulatory-grade stations during a full "heating season" (15 October 2022-15 April 2023). Both LC sensor networks showed higher accuracy in fitting the magnitude of PM10 than PM2.5 reference observations, while lower accuracy was shown in terms of RMSE, MAE and R2. AirQino stations under-estimated both PM2.5 and PM10 reference concentrations (MB = -4.8 and -2.9 µg/m3, respectively), while PurpleAir stations over-estimated PM2.5 concentrations (MB = +5.4 µg/m3) and slightly under-estimated PM10 concentrations (MB = -0.4 µg/m3). PurpleAir stations were finer than AirQino at capturing the time variation of both PM2.5 and PM10 daily concentrations (R2 = 0.68-0.75 vs. 0.59-0.61). LC sensors from both monitoring networks failed to capture the magnitude and dynamics of the PM2.5/PM10 ratio, confirming their well-known issues in correctly discriminating the size of individual particles. These findings suggest the need for further efforts in the implementation of mass conversion algorithms within LC units to improve the tuning of PM2.5 vs. PM10 outputs.

Mechanisms of PM10 Disruption of the Nrf2 Pathway in Cornea.

We have previously shown that PM10 exposure causes oxidative stress and reduces Nrf2 protein levels, and SKQ1 pre-treatment protects against this damage in human corneal epithelial cells (HCE-2). The current study focuses on uncovering the mechanisms underlying acute PM10 toxicity and SKQ1-mediated protection. HCE-2 were pre-treated with SKQ1 and then exposed to 100 µg/mL PM10. Cell viability, oxidative stress markers, programmed cell death, DNA damage, senescence markers, and pro-inflammatory cytokines were analyzed. Nrf2 cellular location and its transcriptional activity were determined. Effects of the Nrf2 inhibitor ML385 were similarly evaluated. Data showed that PM10 decreased cell viability, Nrf2 transcriptional activity, and mRNA levels of antioxidant enzymes, but increased p-PI3K, p-NFκB, COX-2, and iNOS proteins levels. Additionally, PM10 exposure significantly increased DNA damage, phosphor-p53, p16 and p21 protein levels, and ß-galactosidase (ß-gal) staining, which confirmed the senescence. SKQ1 pre-treatment reversed these effects. ML385 lowered the Nrf2 protein levels and mRNA levels of its downstream targets. ML385 also abrogated the protective effects of SKQ1 against PM10 toxicity by preventing the restoration of cell viability and reduced oxidative stress. In conclusion, PM10 induces inflammation, reduces Nrf2 transcriptional activity, and causes DNA damage, leading to a senescence-like phenotype, which is prevented by SKQ1.

Mobility, bacterial hosts, and risks of antibiotic resistome in submicron bioaerosols from a full-scale wastewater treatment plant.

Antibiotic resistome could be loaded by bioaerosols and escape from wastewater or sludge to atmosphere environments. However, until recently, their profile, mobility, bacterial hosts, and risks in submicron bioaerosols (PM1.0) remain unclear. Here, metagenomic sequencing and assembly were employed to conduct an investigation of antibiotic resistome associated with PM1.0 within and around a full-scale wastewater treatment plant (WWTP). More subtypes of antibiotic resistant genes (ARGs) with higher total abundance were found along the upwind-downwind-WWTP transect. ARGs in WWTP-PM1.0 were mainly mediated by plasmids and transposases were the most prevalent mobile genetic elements (MGEs) co-occurring with ARGs. A contig-based analysis indicated that very small proportions (15.32%-19.74%) of ARGs in WWTP-PM1.0 were flanked by MGEs. Proteobacteria was the most dominant host of ARGs. A total of 28 kinds of potential pathogens, such as Pseudomonas aeruginosa and Escherichia coli, carried multiple ARG types. Compared to upwind, WWTP and corresponding downwind were characterized by higher PM1.0 resistome risk. This study emphasizes the vital role of WWTPs in discharging PM1.0-loaded ARGs and antibiotic resistant pathogens to air, and indicates the need for active safeguard procedures, such as that employees wear masks and work clothes, covering the main emission sites, and collecting and destroying of bioaerosols.

Green space modified the association between air pollutants and hypertension in China.

Evidence regarding the combined effects of green space and air pollutants on hypertension remains limited and complex. This study aims to investigate the varying effects of greenness under different air pollution levels in China, using data from the wave 2018 China Health and Retirement Longitudinal Study (CHARLS) involving 17 468 adults (aged ≥ 45 years). As a result, the prevalence rate of hypertension was 42.04%. Logistic regression analyses revealed the positive associations between air pollution concentrations at the city level and prevalent hypertension and the negative associations between NDVI and prevalent hypertension, all of which were more prominent in the populations of the eastern and rural regions. Notably, the negative effect of green space was greater at the lowest quartiles of each air pollutant (OR for PM2.5 quartiles = 0.724, 0.792, 0.740, and 0.931) . Improving air quality and greenness could potentially reduce hypertension risk, and minimizing air pollution might optimize the protective effects of greenness.

The association between indoor air quality and respiratory health symptoms among preschool children in Penang, Malaysia.

A cross-sectional study was conducted among 126 preschool children aged 4-6 years in traffic, industrial, and suburban areas of Penang, Malaysia, to determine their exposure to indoor air pollutants and their associations with respiratory symptoms. A standardised and validated questionnaire was used to collect data on respiratory health symptoms among respondents. An indoor air quality assessment was conducted in selected preschools that included temperature, relative humidity, air velocity, volatile organic compounds (VOCs), and particulate matter (PM2.5, and PM10). There were significant differences in median concentrations of PM2.5, PM10 and relative humidity among study groups. Statistical analysis showed significant associations between air pollutants in preschool with respiratory symptoms. Factors that influenced the increased likelihood of cough and phlegm were linked to the increase in PM2.5 exposure. This study suggests regular classroom cleaning and routine maintenance of air conditioners to be done inside the preschools.

Investigation of the relationship between air pollution and gestational diabetes.

BACKGROUND: Gestational diabetes mellitus (GDM) can have negative effects on both the pregnancy and perinatal outcomes, as well as the long-term health of the mother and the child. It has been suggested that exposure to air pollution may increase the risk of developing GDM. This study investigated the relationship between exposure to air pollutants with gestational diabetes. METHODS: The present study is a retrospective cohort study. We used data from a randomised community trial conducted between September 2016 and January 2019 in Iran. During this period, data on air pollutant levels of five cities investigated in the original study, including 6090 pregnant women, were available. Concentrations of ozone (O3), nitric oxide (NO), nitrogen dioxide (NO2), nitrogen oxides (NOx), sulphur dioxide (SO2), carbon monoxide (CO), particulate matter < 2.5 (PM2.5) or <10 µm (PM10) were obtained from air pollution monitoring stations. Exposure to air pollutants during the three months preceding pregnancy and the first, second and third trimesters of pregnancy for each participant was estimated. The odds ratio was calculated based on logistic regression in three adjusted models considering different confounders. Only results that had a p < .05 were considered statistically significant. RESULTS: None of the logistic regression models showed any statistically significant relationship between the exposure to any of the pollutants and GDM at different time points (before pregnancy, in the first, second and third trimesters of pregnancy and 12 months in total) (p > .05). Also, none of the adjusted logistic regression models showed any significant association between PM10 exposure and GDM risk at all different time points after adjusting for various confounders (p > .05). CONCLUSIONS: This study found no association between GDM risk and exposure to various air pollutants before and during the different trimesters of pregnancy. This result should be interpreted cautiously due to the lack of considering all of the potential confounders.

The health of pregnant women and their children can be impacted by gestational diabetes mellitus (GDM), one of the prevalent pregnancy complications. Some of studies showed that the incidence of gestational diabetes can be influenced by genetic or environmental factors. Air pollution is an environmental stimulus that may predispose pregnant women to GDM. This research explored whether air pollution could increase the risk of developing gestational diabetes. Over 6000 pregnant women in five cities of Iran participated in the study and were screened for gestational diabetes. Their exposure to the various air pollutants during the three months preceding pregnancy and total pregnancy period was measured. In this study, we found no clear association between air pollution and gestational diabetes. However, this finding needs to be interpreted cautiously since all the influential factors were not assessed.

Interactions between aerosols and surface ozone in arid and semi-arid regions of China.

Atmospheric aerosols affect surface ozone concentrations by influencing radiation, but the mechanism and dominant factors are unclear. Therefore, this paper analyses the changes in aerosol-radiative-surface ozone in China's arid and semi-arid regions with the help of the Atmospheric Radiative Transfer (SBDART) model. The results suggest that Aerosol Optical Depth (AOD) and coarse Particulate Matter (PM10) have the same trend, with high values in spring and winter and low values in summer and autumn. Surface ozone is high in spring and summer and low in autumn and winter. Surface ozone is higher in spring and summer and lower in autumn and winter. In winter, mainly secondary pollutants are dominated by high pollution levels. In the rest of the seasons, a mixture of dust, motor vehicle exhaust, and soot is dominated by low pollution levels. Surface ozone is positively correlated with fine particles and negatively correlated with coarse particles. Temperature is positively correlated with surface ozone in all seasons and negatively correlated with PM10 in summer, autumn, and winter. Precipitation negatively correlates with PM10 each season and surface ozone in winter and spring. Analysis of surface ozone and PM10 sources in the more polluted city of Hohhot based on the back-line trajectory model showed that airflow trajectories mainly transported surface ozone and PM10 pollution from northwestern Inner Mongolia and western Mongolia. During dusty solid weather, the decrease in radiation reaching the Earth's surface and the cooling effect of aerosols lead to lower temperatures, which slows down the rate of chemical reactions of precursors of surface ozone, resulting in lower ozone concentrations at the surface. This study can provide a theoretical reference for aerosol and surface ozone control in arid and semi-arid areas of China.

Multi-source observations on the effect of atmospheric blocking on air quality in Istanbul: a study case.

Air pollution is affected by the atmospheric dynamics. This study aims to determine that air pollution concentration values in Istanbul increased significantly and reached peak values due to atmospheric blocking between the 30th of December 2022 and the 5th of January 2023. In this study, hourly pollutant data was obtained from 16 air quality monitoring stations (AQMS), the exact reanalysis data was extracted from ERA5 database, and inversion levels and meteorological and synoptic analyses were used to determine the effects of atmospheric blocking on air pollution. Also, cloud base heights and vertical visibility measurements were taken with a ceilometer. Statistical calculations and data visualizations were performed using the R and Grads program. Omega-type blocking, which started in Istanbul on December 30, 2022, had a significant impact on the 1st and 2nd of January 2023, and PM10 and PM2.5 concentration values reached their peak values at 572.8 and 254.20 µg/m3, respectively. In addition, it was found that the average concentration values in the examined period in almost all stations were higher than the averages for January and February. As a result, air quality in Istanbul was determined as "poor" between these calendar dates. It was found that the blocking did not affect the ozone (µg/m3) concentration. It was also found that the concentrations of particulate matter (PM) 10 µm or less in diameter (PM10) and PM 2.5 µm or less in diameter (PM2.5) were increased by the blocking effect in the Istanbul area. Finally, according to the data obtained using the ceilometer, cloud base heights decreased to 30 m and vertical visibility to 10 m.

Chemical characteristics, morphology and source apportionment of PM10 over National Capital Region (NCR) of India.

The present study frames the physico-chemical characteristics and the source apportionment of PM10 over National Capital Region (NCR) of India using the receptor model's Positive Matrix Factorization (PMF) and Principal Momponent Mnalysis/Absolute Principal Component Score-Multilinear Regression (PCA/APCS-MLR). The annual average mass concentration of PM10 over the urban site of Faridabad, IGDTUW-Delhi and CSIR-NPL of NCR-Delhi were observed to be 195 ± 121, 275 ± 141 and 209 ± 81 µg m-3, respectively. Carbonaceous species (organic carbon (OC), elemental carbon (EC) and water-soluble organic carbon (WSOC)), elemental constituents (Al, Ti, Na, Mg, Cr, Mn, Fe, Cu, Zn, Br, Ba, Mo Pb) and water-soluble ionic components (F-, Cl-, SO42-, NO3-, NH4+, Na+, K+, Mg2+, Ca2+) of PM10 were entrenched to the receptor models to comprehend the possible sources of PM10. The PMF assorted sources over Faridabad were soil dust (SD 15%), industrial emission (IE 14%), vehicular emission (VE 19%), secondary aerosol (SA 23%) and sodium magnesium salt (SMS 17%). For IGDTUW-Delhi, the sources were SD (16%), VE (19%), SMS (18%), IE (11%), SA (27%) and VE + IE (9%). Emission sources like SD (24%), IE (8%), SMS (20%), VE + IE (12%), VE (15%) and SA + BB (21%) were extracted over CSIR-NPL, New Delhi, which are quite obvious towards the sites. PCA/APCS-MLR quantified the similar sources with varied percentage contribution. Additionally, catalogue the Conditional Bivariate Probability Function (CBPF) for directionality of the local source regions and morphology as spherical, flocculent and irregular were imaged using a Field Emission-Scanning Electron Microscope (FE-SEM).

Temporal variation of the PM2.5/PM10 ratio and its association with meteorological factors in a South American megacity: Metropolitan Area of Lima-Callao, Peru.

The Metropolitan Area of Lima-Callao (MALC) is a South American megacity that has suffered a serious deterioration in air quality due to high levels of particulate matter (PM2.5 and PM10). Studies on the behavior of the PM2.5/PM10 ratio and its temporal variability in relation to meteorological parameters are still very limited. The objective of this study was to analyze the temporal trends of the PM2.5/PM10 ratio, its temporal variability, and its association with meteorological variables over a period of 5 years (2015-2019). For this, the Theil-Sen estimator, bivariate polar plots, and correlation analysis were used. The regions of highest mean concentrations of PM2.5 and PM10 were identified at eastern Lima (ATE station-41.2 µg/m3) and southern Lima (VMT station-126.7 µg/m3), respectively. The lowest concentrations were recorded in downtown Lima (CDM station-16.8 µg/m3 and 34.0 µg/m3, respectively). The highest average PM2.5/PM10 ratio was found at the CDM station (0.55) and the lowest at the VMT station (0.27), indicating a predominance of emissions from the vehicular fleet within central Lima and a greater emission of coarse particles by resuspension in southern Lima. The temporal progression of the ratio of PM2.5/PM10 showed positive and highly significant trends in northern and central Lima with values of 0.03 and 0.1 units of PM2.5/PM10 per year, respectively. In the southern region of Lima, the trend was also significant, showcasing a value of 0.02 units of PM2.5/PM10 per year. At the hourly and monthly level, the PM2.5/PM10 ratio presented a negative and significant correlation with wind speed and air temperature, and a positive and significant correlation with relative humidity. These findings offer insights into identifying the sources of PM pollution and are useful for implementing regulations to reduce air emissions considering both anthropogenic sources and meteorological dispersion patterns.

Satellite or ground-based measurements for air pollutants (PM2.5, PM10, SO2, NO2, O3) data and their health hazards: which is most accurate and why?

Air pollution is growing at alarming rates on regional and global levels, with significant consequences for human health, ecosystems, and change in climatic conditions. The present 12 weeks (4 October 2021, to 26 December 2021) study revealed the different ambient air quality parameters, i.e., PM2.5, PM10, SO2, NO2, and O3 over four different sampling stations of Delhi-NCR region (Dwarka, Knowledge park III, Sector 125, and Vivek Vihar), India, by using satellite remote sensing data (MERRA-2, OMI, and Aura Satellite) and different ground-based instruments. The ground-based observation revealed the mean concentration of PM2.5 in Dwarka, Knowledge park III, Sector 125, and Vivek Vihar as 279 µg m-3, 274 µg m-3, 294 µg m-3, and 365 µg m-3, respectively. The ground-based instrumental concentration of PM2.5 was greater than that of satellite observations, while as for SO2 and NO2, the mean concentration of satellite-based monitoring was higher as compared to other contaminants. Negative and positive correlations were observed among particulate matter, trace gases, and various meteorological parameters. The wind direction proved to be one of the prominent parameter to alter the variation of these pollutants. The current study provides a perception into an observable behavior of particulate matter, trace gases, their variation with meteorological parameters, their health hazards, and the gap between the measurements of satellite remote sensing and ground-based measurements.

Public risk perception of air pollution in the general population of Italy and Sweden during the COVID-19 pandemic: Environmental and socio-demographic drivers.

Air pollution is an important anthropogenic hazard due to its effect on human health and the environment. Understanding how the population perceives the risk associated with air pollution is a crucial aspect to inform future policies and communication strategies. The aim of this study is to examine the association between air pollution concentrations and public risk perception of air pollution, also exploring socio-demographic patterns in the general population of Italy and Sweden. To this end, we derived 3-year PM10 average concentrations from ground monitoring stations and integrated with a population-based survey carried out in August 2021 in both countries. Relative perceived likelihood and impact on the individual were considered as domains of risk perception. In addition this, information on direct experience and socio-demographic factors were included as possible determinants of risk perception. Linear regression models were performed to examine the association of PM10 average concentrations at regional level and individual level factors with risk perception domains. In both countries, respondents who live in the most densely populated regions report a higher perceived likelihood of air pollution. Direct experience is the main driver of risk perception in both countries. Being male and smokers in Italy, older age and having left/centre-left political orientation in both countries are associated with a higher perceived likelihood and impact of air pollution. These findings will inform future health and environmental studies regarding the public risk perception of air pollution highlighting individual's awareness and the socio-demographic patterns.