Long-term trends and health impact of PM2.5 and O3 in Tehran, Iran, 2006-2015

Evaluating the health impact of air pollution control strategies and synergies among PM2.5 and O3 pollution in Beijing-Tianjin-Hebei region, China

Since 2013, China has implemented a series of strict Air Pollution Control Strategies (APCS) to mitigate environmental and health risks associated with ambient fine particulate matter (PM2.5). However, while APCS sets clear targets for PM2.5 concentration, it lacks quantitative control over O3 levels. Most existing studies have focused on nation-wide health assessments. Therefore, by conducting a coupled framework using health assessment and decomposition method, the spatiotemporal variation in deaths attributable to PM2.5 pollution, as well as the role of APCS and the synergies between PM2.5 and O3 on PM2.5 concentration and health impacts in the Beijing-Tianjin-Hebei (BTH) region have been explored. The result showed that: (1) PM2.5 concentration in the BTH region decreased by 68.2%, with a reduction of 45,833 (95% Confidence Interval [CI]: 33,808, 50,069) deaths over the period. However, both concentrations and mortality remained high, indicating a need for faster reductions. (2) End-of-pipe control contributed the most to reducing PM2.5 concentrations and deaths, though the gaps between source control and end-of-pipe control is narrowing. (3) The synergistic effects of O3 and PM2.5 in reducing concentration and mortality have increased, becoming a significant driver of PM2.5-related health impacts. Our study emphasizes the future importance of implementing refined, diverse emission reduction measures and coordinating efforts to reduce both O3 and PM2.5 emissions, which are crucial for achieving the Sustainable Development Goals (SDGs) and advancing the "Beautiful China" and "Healthy China" initiatives.

Intercomparison of health impacts from nationwide PM2.5 pollution using observations and modeling: A case study of the worst event in recent decades

This study investigated the temporal and spatial characteristics of PM2.5 and the related human health impacts in various environmental areas of South Korea during high-concentration days in winter (February 15-March 15, 2019). These analyses were performed using PM2.5 observations and numerical modeling, which included the Community Multi-scale Air Quality model (CMAQ v5.3.2) and the Environmental Benefits Mapping and Analysis Program-Community Edition (BenMAP-CE v1.5.0.4). The mean PM2.5 concentrations observed on high-concentration days (50.1 μg m-3 in the southeastern area to 65.2 μg m-3 in the southwestern area) were 2.1-2.7 times higher than those observed on non-high-concentration days (18.4 μg m-3 in the southeastern area to 27.0 μg m-3 in the northwestern area). In addition, many premature deaths and high premature death rates from respiratory and cardiovascular diseases attributable to high PM2.5 levels were mostly distributed in the western regions of South Korea. These regional differences may be due to a combination of local meteorology and emissions and/or the long-range transport of pollutants. However, the magnitude of these premature deaths varied across areas, genders, and age groups due to differences in PM2.5 concentrations and mortality rates. The number of premature deaths from cardiovascular diseases due to increased PM2.5 levels was slightly higher than that from respiratory diseases, owing to the higher mortality rates. The health impact of cardiovascular diseases was estimated to be more severe in women than in men, and vice versa for respiratory diseases.

Assessing the burden of diseases attributed to exposure to ambient particulate matter by air quality modeling

This study aimed to assess PM2.5 exposure levels in Ahvaz, Iran, and quantify the associated burden of disease attributable to particulate pollution. To quantify uncertainty mortality and morbidity, the exposure response function model for probabilistic risk assessment was used. The analysis of aerosol variations by the Aerosol Optical Thickness indicated a decline in PM2.5 concentrations during pandemic. During the study period, the annual mean of PM2.5 concentrations exceeded the annual limit value established by the World Health Organization. Cause-specific mortality, including trachea bronchus lung cancer, stroke, and acute lower respiratory infections, also decreased by 14-28% in 2020. Restricted activity days and work days lost decreased by 11.8% and 13.8%, respectively, correlating with lower PM2.5 concentrations. Years lived with disability dropped from 242.7 to 170.4 years per 105 capita in 2020 during the pandemic. Mitigation strategies, including green infrastructure, industrial regulation, and improved urban planning, are needed to reduce health risks in this highly polluted region.

Assessment of disease burden and mortality attributable to air pollutants in northwestern Iran using the AirQ+ software

It is well known that one of the main causes of mortality and reduced life expectancy is air pollution, which carries the highest burden of diseases attributed to environmental factors. The poor air quality in Iranian cities leads to a wide range of acute and chronic health effects. This study estimates the natural deaths, ALRI, COPD, lung cancer, IHD, and strokes caused by air pollutants in Bukan, a southern city in West Azerbaijan Province, from 2011 to 2019. Population data was obtained from government organizations, and pollutant data for 2011-2019 was collected from the Bukan Environmental Protection Organization. Analyses were performed using Excel, and the data was subsequently entered into the WHO's AirQ+ model to extract the results. The study found that long-term exposure to PM10, PM2.5, NO2, and O3 resulted in an estimated 316, 241, 14, and 52 deaths, respectively. By comparing the air quality over the 8-year period, it was determined that the air quality in Bukan city is not in good condition, with particulate matter levels exceeding relevant standards. Given the increasing trend of air pollution and associated health impacts, it is essential to implement effective control policies to improve the city's air quality. This information provides a crucial step for city managers, policymakers, and health officials to mitigate the health effects caused by air pollution.

The economic burden of premature mortality attributable to ambient PM2.5 in Iran, a national analysis, 2001-2016

This study aimed to estimate the years of potential productive life lost (YPPLL) and the cost of lost productivity due to premature mortality attributable to ambient PM2.5 in Iran from 2000 to 2016. To quantify the burden of air pollution-related premature mortality: the number of deaths, YPPLL, and the economic costs of productivity losses were used. The human capital approach was used to estimate productivity losses. During the study period, deaths related to ambient PM2.5 resulted in a total of 3,792,968 YPPLL, of which 2,470,632 (68%) were in males.. The total productivity losses due to deaths related to ambient PM2.5 were $5,621,702,120 for the 2001-2016 period. The productivity losses increased from $119,084,207 in 2001 to $491,328,522 in 2016. In the 2001 - 2016 period, ambient PM2.5 induced a significant economic burden in the form of productivity losses in Iran, which is expected to increase. Policymakers should consider these findings when formulating public health policies to reduce air pollution and its negative consequences.

Long-term perspectives on land-use changes and air pollution policies in Iran: A comparative analysis of regional and global patterns in atmospheric PM2.5

Fine particulate matter (PM2.5) pollution is a major environmental challenge across the Middle East, including Iran. However, a substantial lack of knowledge exists regarding the linkage between aerosol trends, specific compounds, and their interrelation with emissions, mitigation strategies, and land changes. This research comprehensively evaluates the spatiotemporal trends of PM2.5 and its main precursors (SO2 and BC) concentrations in relation to LULC (Land-Use and Land-Cover) changes and mitigation policies in Iran during 1980-2023. Surface PM2.5 concentrations were estimated using five monthly MERRA-2 simulation datasets, including sea salt2.5, dust2.5, BC, OC, and SO4. The Evaluation of MERRA-2 PM2.5 against ground-based measurements confirmed that the MERRA-2 reanalysis data is ideal for monitoring PM2.5 patterns in Iran. Our trend analysis showed that dust dominates high PM2.5 concentrations in southwestern and southeastern Iran during summer, while anthropogenic aerosols (SO2 and BC) are the most significant contributors to PM2.5 in urban areas like Tehran in winter. Overall, a significant rise in aerosol occurred over Iran during 1980-2023, which reversed to a decreasing trend in PM2.5, BC and SO2 around 2006-2010. At the regional scale, aerosols variations were influenced by land-use changes, while urban and agricultural LULC changes being the primary contributors in dust-dominant regions, accounting for 38.1% and 26.4% of the variation, respectively. Our findings indicate that, although land-use changes initially influenced air pollution trends, recent clean-air policies have been essential in reducing emissions across major urban centers. Additionally, these trends in Iran align with or diverge from global patterns, reflecting the rise in industrial emissions across South Asia and contrasting with policy-driven decreases in developed regions such as Europe and North America, highlighting the urgent need for effective policies and land management to mitigate urban air pollution from diverse aerosol sources.

Short-term exposure to PM2.5 pollution in Iran and related burden diseases

The objective of this study was to estimate the health effects attributed to PM2.5 exposure in southwest of Iran. In order to estimate HA-CVD, HA-RD, LC-M, I-As in children, RAD, and WDL, the exposure-response function method was used. The annual mean of PM2.5 regularly exceeded 5.26-8.5 times from 2021 annual limit value established by the WHO. The dominance of PM2.5 in PM2.5/PM10 ratio decreased -34.6% from 2015 to 2020.  The results showed that the risks of HA-CVD (- 51. 9), HA-RD (- 68.7%), LC-M (- 43.6%), I-As (- 52.1%), RAD (- 56.8%), and WDL (- 58.7%) declined per 105 inhabitants between 2018 and 2020 . Reducing the particulate emissions from industries and road traffic led to lower exposure to PM2.5, which will be effective in decrease of mortality rate.

Application of the Lasso regularisation technique in mitigating overfitting in air quality prediction models

As a significant global concern, air pollution triggers enormous challenges in public health and ecological sustainability, necessitating the development of precise algorithms to forecast and mitigate its impacts, which has led to the development of many machine learning (ML)-based models for predicting air quality. Meanwhile, overfitting is a prevalent issue with ML algorithms that decreases their efficacy and generalizability. The present investigation, using an extensive collection of data from 16 sensors in Tehran, Iran, from 2013 to 2023, focuses on applying the Least Absolute Shrinkage and Selection Operator (Lasso) regularisation technique to enhance the forecasting precision of ambient air pollutants concentration models, including particulate matter (PM2.5 and PM10), CO, NO2, SO2, and O3 while decreasing overfitting. The outputs were compared using the R-squared (R2), mean absolute error (MAE), mean square error (MSE), root mean square error (RMSE), and normalised mean square error (NMSE) indices. Despite the preliminary findings revealing that Lasso dramatically enhances model reliability by decreasing overfitting and determining key attributes, the model's performance in predicting gaseous pollutants against PM remained unsatisfactory (R2PM2.5 = 0.80, R2PM10 = 0.75, R2CO = 0.45, R2NO2 = 0.55, R2SO2 = 0.65, and R2O3 = 0.35). The minimal degree of missing data presumably explained the strong performance of the PM model, while the high dynamism of gases and their chemical interactions, in conjunction with the inherent characteristics of the model, were the primary factors contributing to the poor performance of the model. Simultaneously, the successful implementation of the Lasso regularisation approach in mitigating overfitting and selecting more important features makes it highly suggested for application in air quality forecasting models.

Hidden health effects and economic burden of stroke and coronary heart disease attributed to ambient air pollution (PM2.5) in Tehran, Iran: Evidence from an assessment and forecast up to 2030

Air pollution is one of the main causes of global disease burden, especially in low-income and middle-income countries. Estimation of the current situation and prediction of the future health effects of death and incidence of stroke and coronary heart disease (CHD) attributed to PM2.5 were done using BenMAP-CE software. Estimating and forecasting the economic burden of these diseases were done in 4 scenarios: Stability of the current PM2.5 concentration, annual 10 % reduction of PM2.5 concentration, reduction to 5 µg/m3, and reduction to 12 µg/m3, with three approaches for calculating the economic burden in mortality costs, including the human capital(HC), years of life lost(YLL) and value of statistical life(VSL) was performed. With the stability of the PM2.5 concentration, the economic burden of stroke attributed to PM2.5 with the approach of calculating the cost of death with the HC, the YLL, and VSL will reach from 64, 82 and 172 million USD in 2020-849, 1120 and 2703 million USD in 2030 and these costs for CHD in the mentioned approaches of calculating the cost of death will reach respectively from 499, 568 and 898 million USD in 2020-7096, 8088, and 13,621 million USD in 2030. We find that the morbidity economic burden (including direct, indirect, and intangible costs) of stroke compared to the cost of death with the HC, and YLL approaches are 67.58 times, 3.15 times respectively, and in the VSL approach is 47.32 % of stroke death cost. Also, the costs of CHD morbidity economic burden compared to the cost of death in the method of calculating the cost of death with the HC, YLL, and VSL approaches are 42.09, 7.25, and 1.16 times, respectively. This study provides comprehensive baseline information for health policymakers to understand the benefits of air pollution control policies globally, especially in LMICs.

Air quality in different urban hotspots in a metropolitan city in India and the environmental implication

This research study investigates hourly data on concentrations of five major air pollutants such as particulate matter (PM10, PM2.5) and gaseous pollutants (SO2, NO2, CO) measured during 2022 at four hotspot sites (industrial site, traffic site, commercial site, harbour, and one residential site) in Chennai, India. The analysis encompasses temporal variations spanning annual, seasonal, and diurnal variations in the pollutants. Notably, PM10 and CO emerge as the predominant pollutants, with the highest concentrations at industrial and traffic sites (PM10: 67.64 ± 40.77 µg/m3, CO: 1.41 ± 0.84 mg/m3; traffic site: PM10: 58.67 ± 20.05 µg/m3, CO: 0.99 ± 0.57 mg/m3). Seasonal dynamics reveal prominent winter spikes in particulate matter (PM10, PM2.5) and carbon monoxide (CO) concentrations, while nitrogen dioxide (NO2) and sulphur dioxide (SO2) levels peak during the summer season, particularly in the harbour area. The proximity to roadways exerts a discernible influence on diurnal patterns, with traffic sites showcasing broader rush hour peaks compared to sharper spikes observed at other sites. Furthermore, distinct bimodal patterns are evident for PM10 and PM2.5 concentrations in residential and harbour areas. A common lognormal distribution pattern is identified across the studied sites, suggesting consistent air quality trends despite contrasting locations. The conditional probability function (CPF) is used in conjunction with local meteorological conditions for identifying key pollution sources in each location. The implementation of polar plots emphasizes industries as principal local sources of pollution, at industrial sites significantly contributing to PM10, SO2, and NO2 concentrations under specific wind conditions. The main objective of the present study is to facilitate a good understanding of pollutant dynamics, pollution sources, and their intricate interplay with meteorological factors, thereby contributing to the formulation and implementation of effective air pollution control and mitigation strategies.

Estimating the burden of diseases attributed to PM2.5 using the AirQ + software in Mashhad during 2016-2021

The study used the AirQ + software developed by the World Health Organization (WHO) to evaluate the health impacts associated with long-term exposure to PM2.5 in Mashhad, Iran. For this purpose, we analyzed the daily average concentrations of PM2.5 (with a diameter of 2.5 micrometers or less) registered by the air quality monitoring stations from 2016 to 2021. The levels of PM2.5 surpassed the Air Quality Guidelines (AQG) limit value of 5 µg/m3 (annual value) established by WHO. The findings revealed that the burden of mortality (from all-natural causes) at people above 30 years old associated with PM2.5 exposures was 2093 [95% confidence interval [CI]: 1627-2314] deaths in 2016 and 2750 [95% CI: 2139-3038] deaths in 2021. In general, the attributable mortality from specific causes of deaths (e.g., COPD (chronic obstructive pulmonary diseases), IHD (ischemic heart diseases) and stroke) in people above 25 years old increased between the years, but the mortality from lung cancer was stable at 46 [95% CI: 33-59] deaths in 2016 and 48 [95% CI: 34-61] deaths in 2021. The attributable mortality from ALRI (Acute Lower Respiratory Infection) in children below 5 years old increased between the years. We also found differences in mortality cases from IHD and stroke among the age groups and between the years 2016 and 2021. It was concluded that burden of disease methodologies are suitable tools for regional and national policymakers, who must take decisions to prevent and to control air pollution and to analyze the cost-effectiveness of interventions.

Ambient Air Pollution and Incident Cardiovascular Disease in People With Type 2 Diabetes Mellitus: A Cohort Study

OBJECTIVES

We aimed to assess the effect of air pollution on incident cardiovascular disease (CVD) in people with type 2 diabetes mellitus (T2DM).

METHODS

We tracked 486 T2DM patients from 2012 to 2021. Cox regression models were applied to assess the hazard of exposure to particulate matter, carbon monoxide (CO), ozone, nitrogen dioxide, and sulfur dioxide (SO 2 ) on incident CVD, revealing hazard ratios (HRs).

RESULTS

CVD incidents occurred in 73 individuals. Among men, each 1-ppm increase in CO levels raised the risk of CVD (HR: 2.66, 95% CI: 1.30-5.44). For women, a 5-ppb rise in SO 2 increased CVD risk (HR: 1.60, 95% CI: 1.11-2.30). No notable impact of particulate pollutants was found.

CONCLUSIONS

Persistent exposure to gaseous air pollutants, specifically CO and SO 2 , is linked to the development of CVD in men and women with T2DM.

Unveiling the potential of a novel portable air quality platform for assessment of fine and coarse particulate matter: in-field testing, calibration, and machine learning insights

Although low-cost air quality sensors facilitate the implementation of denser air quality monitoring networks, enabling a more realistic assessment of individual exposure to airborne pollutants, their sensitivity to multifaceted field conditions is often overlooked in laboratory testing. This gap was addressed by introducing an in-field calibration and validation of three PAQMON 1.0 mobile sensing low-cost platforms developed at the Mining and Metallurgy Institute in Bor, Republic of Serbia. A configuration tailored for monitoring PM2.5 and PM10 mass concentrations along with meteorological parameters was employed for outdoor measurement campaigns in Bor, spanning heating (HS) and non-heating (NHS) seasons. A statistically significant positive linear correlation between raw PM2.5 and PM10 measurements during both campaigns (R > 0.90, p ≤ 0.001) was observed. Measurements obtained from the uncalibrated NOVA SDS011 sensors integrated into the PAQMON 1.0 platforms exhibited a substantial and statistically significant correlation with the GRIMM EDM180 monitor (R > 0.60, p ≤ 0.001). The calibration models based on linear and Random Forest (RF) regression were compared. RF models provided more accurate descriptions of air quality, with average adjR2 values for air quality variables in the range of 0.70 to 0.80 and average NRMSE values between 0.35 and 0.77. RF-calibrated PAQMON 1.0 platforms displayed divergent levels of accuracy across different pollutant concentration ranges, achieving a data quality objective of 50% during both measurement campaigns. For PM2.5, uncertainty ( U r ) was below 50% for concentrations between 9.06 and 34.99 μg/m3 in HS and 5.75 and 17.58 μg/m3 in NHS, while for PM10, it stayed below 50% from 19.11 to 51.13 μg/m3 in HS and 11.72 to 38.86 μg/m3 in NHS.

Synergistic PM2.5 and O3 control to address the emerging global PM2.5-O3 compound pollution challenges

In recent years, the issue of PM2.5-O3 compound pollution has become a significant global environmental concern. This study examines the spatial and temporal patterns of global PM2.5-O3 compound pollution and exposure risks, firstly at the global and urban scale, using spatial statistical regression, exposure risk assessment, and trend analyses based on the datasets of daily PM2.5 and surface O3 concentrations monitored in 120 cities around the world from 2019 to 2022. Additionally, on the basis of the common emission sources, spatial heterogeneity, interacting chemical mechanisms, and synergistic exposure risk levels between PM2.5 and O3 pollution, we proposed a synergistic PM2.5-O3 control framework for the joint control of PM2.5 and O3. The results indicated that: (1) Nearly 50% of cities worldwide were affected by PM2.5-O3 compound pollution, with China, South Korea, Japan, and India being the global hotspots for PM2.5-O3 compound pollution; (2) Cities with PM2.5-O3 compound pollution have exposure risk levels dominated by ST + ST (Stabilization) and ST + HR (High Risk). Exposure risk levels of compound pollution in developing countries are significantly higher than those in developed countries, with unequal exposure characteristics; (3) The selected cities showed significant positive spatial correlations between PM2.5 and O3 concentrations, which were consistent with the spatial distribution of the precursors NOx and VOCs; (4) During the study period, 52.5% of cities worldwide achieved synergistic reductions in annual average PM2.5 and O3 concentrations. The average PM2.5 concentration in these cities decreased by 13.97%, while the average O3 concentration decreased by 19.18%. This new solution offers the opportunity to construct intelligent and healthy cities in the upcoming low-carbon transition.

Two Decades of Air Pollution Health Risk Assessment: Insights From the Use of WHO's AirQ and AirQ+ Tools

Objectives

We evaluated studies that used the World Health Organization's (WHO) AirQ and AirQ+ tools for air pollution (AP) health risk assessment (HRA) and provided best practice suggestions for future assessments.

Methods

We performed a comprehensive review of studies using WHO's AirQ and AirQ+ tools, searching several databases for relevant articles, reports, and theses from inception to Dec 31, 2022.

Results

We identified 286 studies that met our criteria. The studies were conducted in 69 countries, with most (57%) in Iran, followed by Italy and India (∼8% each). We found that many studies inadequately report air pollution exposure data, its quality, and validity. The decisions concerning the analysed population size, health outcomes of interest, baseline incidence, concentration-response functions, relative risk values, and counterfactual values are often not justified, sufficiently. Many studies lack an uncertainty assessment.

Conclusion

Our review found a number of common shortcomings in the published assessments. We suggest better practices and urge future studies to focus on the quality of input data, its reporting, and associated uncertainties.

Estimating the health impacts of exposure to Air pollutants and the evaluation of changes in their concentration using a linear model in Iran

In big and industrial cities of developing countries, illness and mortality from long-term exposure to air pollutants have become a serious issue. This research was carried out in 2019-2020 to estimate the health impacts of PM10, NO2 and O3 pollutants by using AirQ+ and R statistical programming software in Arak, Isfahan, Tabriz, Shiraz, Karaj, and Mashhad. Mortality statistics, number of people in required age groups, and amount of pollutants were gathered respectively from different agencies like Statistics and Information Technology of the Ministry of Health, Statistical Center, and Department of Environment and by using Excel, the average 24-hour and 1-hour concentration and maximum 8-hour concentration for PM10, NO2 and O3 pollutants were gathered. We used linear mixed impacts model to account for the longitudinal observations and heterogeneity of the cities. The results of the study showed high number of deaths due to chronic bronchitis in adults, premature death of infants, and respiratory diseases in Mashhad. This research highlights the importance of estimation of health impacts from exposure to air pollutants on residents of the studied cities.

Associations between long-term exposure to air pollution, diabetes, and hypertension in metropolitan Iran: an ecologic study

Epidemiological studies on air pollution, diabetes, and hypertension conflict. This study examined air pollution, diabetes, and hypertension in adults in 11 metropolitan areas of Iran (2012-2016). Local environment departments and the Tehran Air Quality Control Company provided air quality data. The VIZIT website and Stepwise Approach to Chronic Disease Risk Factor Surveillance study delivered chronic disease data. Multiple logistic regression and generalized estimating equations evaluated air pollution-related diabetes and hypertension. In Isfahan, Ahvaz, and Tehran, PM2.5 was linked to diabetes. In all cities except Urmia, Yasuj, and Yazd, PM2.5 was statistically related to hypertension. O3 was connected to hypertension in Ahvaz, Tehran, and Shiraz, whereas NO2 was not. BMI and gender predict hypertension and diabetes. Diabetes, SBP, and total cholesterol were correlated. Iran's largest cities' poor air quality may promote diabetes and hypertension. PM2.5 impacts many cities' outcomes. Therefore, politicians and specialists have to control air pollution.

Temporal characteristics and health effects related to NO2, O3, and SO2 in an urban area of Iran

This study reports on temporal variations of NO2, O3, and SO2 pollutants and their related health effects in urban air of Khorramabad, Iran using AirQ 2.2.3 software. Based on data between 2015 and 2021, hourly NO2, O3, and SO2 concentrations increase starting at 6:00 a.m. local time until 9:00 p.m., 3:00 p.m., and 7:00 p.m. local time, respectively, before gradually decreasing. The highest monthly NO2, O3, and SO2 concentrations are observed in October, August, and September, respectively. Annual median NO2, O3, and SO2 concentrations range between 17 ppb and 38.8 ppb, 17.5 ppb-36.6 ppb, and ∼14 ppb-30.8 ppb, respectively. Two to 93 days and 17-156 days between 2015 and 2021 exhibit daily concentrations of NO2 and SO2 ≤ WHO AQGs, respectively, while 187-294 days have 8-h maximum O3 concentrations ≤ WHO AQGs. The mean excess mortality ascribed to respiratory mortality, cardiovascular mortality, hospital admissions for COPD, and acute myocardial infraction are 121, 603, 39, and 145 during 2015-2021, respectively. O3 is found to exert more significant health effects compared to SO2 and NO2, resulting in higher cardiovascular mortality. The gradual increase in NO2 and possibly O3 over the study period is suspected to be due to economic sanctions, while SO2 decreased due to regulatory activity. Sustainable control strategies such as improving fuel quality, promoting public transportation and vehicle retirement, applying subsidies for purchase of electric vehicles, and application of European emission standards on automobiles can help decrease target pollutant levels in ambient air of cities in developing countries.

Evaluating the mortality and health rate caused by the PM2.5 pollutant in the air of several important Iranian cities and evaluating the effect of variables with a linear time series model

All over the world, the level of special air pollutants that have the potential to cause diseases is increasing. Although the relationship between exposure to air pollutants and mortality has been proven, the health risk assessment and prediction of these pollutants have a therapeutic role in protecting public health, and need more research. The purpose of this research is to evaluate the ill-health caused by PM2.5 pollution using AirQ + software and to evaluate the different effects on PM2.5 with time series linear modeling by R software version 4.1.3 in the cities of Arak, Esfahan, Ahvaz, Tabriz, Shiraz, Karaj and Mashhad during 2019-2020. The pollutant hours, meteorology, population and mortality information were calculated by the Environmental Protection Organization, Meteorological Organization, Statistics Organization and Statistics and Information Technology Center of the Ministry of Health, Treatment and Medical Education for 24 h of PM2.5 pollution with Excel software. In addition, having 24 h of PM2.5 pollutants and meteorology is used to the effect of variables on PM2.5 concentration. The results showed that the highest and lowest number of deaths due to natural deaths, ischemic heart disease (IHD), lung cancer (LC), chronic obstructive pulmonary disease (COPD), acute lower respiratory infection (ALRI) and stroke in The effect of disease with PM2.5 pollutant in Ahvaz and Arak cities was 7.39-12.32%, 14.6-17.29%, 16.48-8.39%, 10.43-18.91%, 12.21-22.79% and 14.6-18.54 % respectively. Another result of this research was the high mortality of the disease compared to the mortality of the nose. The analysis of the results showed that by reducing the pollutants in the cities of Karaj and Shiraz, there is a significant reduction in mortality and linear modeling provides a suitable method for air management planning.

Association Between Air Pollution and Coronary Heart Disease Hospitalizations in Lanzhou City, 2013-2020: a Time Series Analysis

Coronary heart disease (CHD) is one of the most serious public health problems. However, few studies have focused on the effects of exposure to particulate matter and gaseous air pollutants on CHD. This study aimed to explore the relationship between air pollutants and the number of hospitalized patients with CHD in Lanzhou, and we collected daily data on the number of hospitalized patients with CHD, daily air pollutants, and meteorological factors from 2013 to 2020. A distributed lag nonlinear model (DLNM) combined with a quasi-Poisson regression model was applied to evaluate the relationship between air pollutants and the number of hospitalized patients with CHD. The results indicated that the hysteresis effect of all pollutants except O38h reached its maximum at lag3, and the relative risk of coronary heart disease admission was 1.0014 (95%CI: 1.0004, 1.0023), 1.0003 (95%CI: 1.0000, 1.0006), 1.0020 (95%CI: 1.0004, 1.0035), and 1.0053 (95%CI: 1.0026, 1.0080) when PM2.5, PM10, NO2, and SO2 concentrations were increased by 10 μg/m3, respectively. Each 1 mg/m3 increase in CO concentration was associated with a relative risk of coronary heart disease; hospitalization risk was 1.1076 (95%CI: 1.0530, 1.1650). We observed a relative risk of 0.9991 (95%CI: 0.9986, 0.9999) for each 10 μg/m3 increase in O38h for coronary heart disease admission at lag1. Women and elderly were more susceptible to the impact of air pollution, and the impact was greater during cold seasons. Our results indicate that air pollution increased the risk of hospitalization for CHD in a short term. The research findings can provide strategic insights into the impact of current and future air pollution on CHD.

Effects of Ambient O3 on Respiratory Mortality, Especially the Combined Effects of PM2.5 and O3

BACKGROUND

In China, the increasing concentration of ozone (O3) has emerged as a significant air pollution issue, leading to adverse effects on public health, particularly the respiratory system. Despite the progress made in managing air pollution in China, it is crucial to address the problem of environmental O3 pollution at present.

METHODS

The connection between O3 exposure and respiratory mortality in Shenyang, China, from 2014 to 2018 was analyzed by a time-series generalized additive regression model (GAM) with quasi-Poisson regression. Additionally, the potential combined effects of fine particulate matter (PM2.5) and O3 were investigated using the synergy index (SI).

RESULTS

Our findings indicate that each 10 μg/m3 increase in O3 at lag 2 days was associated with a maximum relative risk (RR) of 1.0150 (95% CI: 1.0098-1.0202) for respiratory mortality in the total population. For individuals aged ≥55 years, unmarried individuals, those engaged in indoor occupations, and those with low educational attainment, each 10 μg/m3 increase in O3 at lag 07 days was linked to RR values of 1.0301 (95% CI: 1.0187-1.0417), 1.0437 (95% CI: 1.0266-1.0610), 1.0317 (95% CI: 1.0186-1.0450), and 1.0346 (95% CI: 1.0222-1.0471), respectively. Importantly, we discovered a synergistic effect of PM2.5 and O3, resulting in an SI of 2.372 on the occurrence of respiratory mortality.

CONCLUSIONS

This study confirmed a positive association between O3 exposure and respiratory mortality. Furthermore, it highlighted the interaction between O3 and PM2.5 in exacerbating respiratory deaths.

Characterization of microplastics in the atmosphere of megacity Tehran (Iran)

In this study, the characteristics of ambient airborne microplastics were investigated in Tehran to obtain insights into their origins. For this purpose, sampling operations took place at locations with different backgrounds in summer and autumn by using TSP and PM10 high-volume samplers. As a result of microscopic analysis and Raman spectroscopy, the color, shape, number, size, and type of microplastic particles were investigated. Seven types of chemical structures were identified in the particles, among which polypropylene (18.7%) in summer and polystyrene (20%) in autumn had the dominant share. The average number of particles collected using the TSP and PM10 samplers were 1165 ± 147.64 and 1006.5 ± 147.64, respectively. The size of microplastic particles in different stations varied between 4 and 3094 μm. In the seasonal examination of the identified colors, black (38-43%), red (17-19%), gold (13-14%), brown (12% in both seasons), blue (7-10%), yellow (3-5%), and green (2-5%) had the largest proportions, respectively. The examined microplastics were in three forms: fiber, bead, and fragment, among which the predominant form was fiber, and the most infrequent particles were fragments. Statistical comparisons showed that the sampling location does not have a significant effect on the number and size of particles (p value > 0.05). The season was not identified as a determining parameter for particle size (p value > 0.05). On the other hand, seasonal changes can have a tremendous effect on the microplastic particle number (p value < 0.05). Lastly, to obtain more detailed information about the origin of these particles, continuous and long-term monitoring near known industries and suspected sources of plastic materials and source apportionment studies were suggested.

Regional joint PM2.5-O3 control policy benefits further air quality improvement and human health protection in Beijing-Tianjin-Hebei and its surrounding areas

Beijing-Tianjin-Hebei and its surrounding areas (hereinafter referred to as "2+26" cities) are one of the most severe air pollution areas in China. The fine particulate matter (PM_2.5) and surface ozone (O₃) pollution have aroused a significant concern on the national scale. In this study, we analyzed the pollution characteristics of PM_2.5 and O₃ in "2+26" cities, and then estimated the health burden and economic loss before and after the implementation of the joint PM_2.5-O₃ control policy. During 2017-2019, PM_2.5 concentration reduced by 19% while the maximum daily 8 hr average (MDA8) O₃ stayed stable in "2+26" cities. Spatially, PM_2.5 pollution in the south-central area and O₃ pollution in the central region were more severe than anywhere else. With the reduction in PM_2.5 concentration, premature deaths from PM_2.5 decreased by 18% from 2017 to 2019. In contrast, premature deaths from O₃ increased by 5%. Noticeably, the huge potential health benefits can be gained after the implementation of a joint PM_2.5-O₃ control policy. The premature deaths attributed to PM_2.5 and O₃ would be reduced by 91.6% and 89.1%, and the avoidable economic loss would be 60.8 billion Chinese Yuan (CNY), and 68.4 billion CNY in 2035 compared with that in 2019, respectively. Therefore, it is of significance to implement the joint PM_2.5-O₃ control policy for improving public health and economic development.

Assessing the health impacts of PM2.5 and ozone pollution and their comprehensive correlation in Chinese cities based on extended correlation coefficient

The coordinated control of PM_2.5 and ozone pollution is becoming more and more important in the current and next stage of Chinese environmental pollution control. Existing studies are unable to provide sufficient quantitative assessments of the correlation of PM_2.5 and ozone pollution to support the coordinated control of the two air pollutants. This study develops a systematic method to comprehensively assess the correlation between PM_2.5 and ozone pollution, including the evaluation of the impact of two air pollutants on human health and the extended correlation coefficient (ECC) for assessing the bivariate correlation index of PM_2.5-ozone pollution in Chinese cities. According to the latest studies on epidemiology conducted in China, we take cardiovascular and cerebrovascular diseases and respiratory diseases as the ozone pollution's health burden when evaluating the health impact of ozone pollution. The results show that the health impact of PM_2.5 in China decreases by 25.9 % from 2015 to 2021, while the health impact of ozone increases by 11.8 %. The ECC of 335 cities in China shows an increasing-decreasing trend but has generally increased from 2015 to 2021. The study provides important support for an in-depth understanding of the correlation and development trend of Chinese PM_2.5 and ozone pollution by classifying the comprehensive PM_2.5-ozone correlation performances of Chinese cities into four types. China or other countries will get better environmental benefits by implementing different coordinated management approaches for different correlative types of regions based on the assessment method in this study.

Comparative review of ambient air PM2.5 source apportioning studies in Tehran

Rapid urbanization and consuming lifestyles have intensified air pollution in urban areas. Air pollution in megacities has imposed severe environmental damages to human health. Proper management of the issue necessitates identification of the share of emission sources. Therefore, numerous research works have studied the apportionment of the total emissions and observed concentrations among different emissions sources. In this research, a comprehensive review is conducted to compare the source apportioning results for ambient air PM2.5 in the megacity of Tehran, the capital of Iran. One hundred seventy-seven pieces of scientific literatures, published between 2005 and 2021, were reviewed. The reviewed research are categorized according to the source apportioning methods: emission inventory (EI), source apportionment (SA), and sensitivity analysis of the concentration to the emission sources (SNA). The possible reasons for inconsistency among the results are discussed according to the scope of the studies and the implemented methods. Although 85% of the reviewed original estimates identify that mobile sources contribute to more thant 60% of Tehran air pollution, the distribution of vehicle types and modes are clearly inconsistent among the EI studies. Our review suggests that consistent results in the SA studies in different locations in central Tehran may indicate the reliability of this method for the identification of the type and share of the emission sources. In contrast, differences among the geographical and sectoral coverage of the EI studies and the disparities among the emission factors and activity data have caused significant deviations among the reviewed EI studies. Also, it is shown that the results of the SNA studies are highly dependent on the categorization type, model capabilities and EI presumptions and data input to the pollutant dispersion modelings. As a result, integrated source apportioning in which the three methods complement each other's results is necessary for consistent air pollution management in megacities.

Supplementary information

The online version contains supplementary material available at 10.1007/s40201-023-00855-0.

Mortality and morbidity assessment attributed to short- and long-term exposure to fine particles in ambient air of Agadir city, Morocco: The AirQ model approach

It is well established that respiratory mortality and morbidity are associated with high concentrations of fine particles such as PM2.5. The aim of this study was to evaluate the long- and short-term impacts of PM2.5 on the population of Agadir, Morocco, using AirQ 2.1.1 software. The mean PM2.5 values were obtained from data collected at three sites. Baseline incidence data were obtained from the literature, and relative risk (RR) values were referenced from the World Health Organization. This study quantified long-term total mortality (LT-TM), lung cancer mortality (LT-LC), morbidity from acute lower respiratory tract infections (LT-ALRI), and morbidity from chronic obstructive pulmonary disease (LT-COPD), as well as short-term total mortality (ST-TM). The attributable proportions (AP) of LT-TM and LT-LC were estimated to 14.19% and 18.42%, respectively. Their excess deaths were estimated to 279 and 11 persons, respectively, and their RRs to 1.16 (95% CI: 1.10-1.22) and 1.23 (95% CI: 1.12-1.37), respectively. Furthermore, the AP of LT-ALRI and LT-COPD were estimated to 14.36% and 15.68%, respectively, their excess deaths to 33 and 4, and their RRs to 1.17 (95% CI: 1.11-1.31) and 1.19 (95% CI: 1.00-1.02), respectively. In comparison, the AP of ST-TM was estimated to 1.27%, with a 25-person excess death rate. This study was conducted to inform decision-making and to promote local policies on ambient air quality.

Cardiovascular, respiratory and all-cause (natural) health endpoint estimation using a spatial approach in Malaysia

In 2016, the World Health Organization (WHO) estimated that approximately 4.2 million premature deaths worldwide were attributable to exposure to particulate matter 2.5 μm (PM_2.5). This study assessed the environmental burden of disease attributable to PM_2.5 at the national level in Malaysia. We estimated the population-weighted exposure level (PWEL) of PM10 concentrations in Malaysia for 2000, 2008, and 2013 using aerosol optical density (AOD) data from publicly available remote sensing satellite data (MODIS Terra). The PWEL was then converted to PM_2.5 using Malaysia's WHO ambient air conversion factor. We used AirQ+ 2.0 software to calculate all-cause (natural), ischemic heart disease (IHD), stroke, chronic obstructive pulmonary disease (COPD), lung cancer (LC), and acute lower respiratory infection (ALRI) excess deaths from the National Burden of Disease data for 2000, 2008 and 2013. The average PWELs for annual PM_2.5 for 2000, 2008, and 2013 were 22 μg m-3, 18 μg m-3 and 24 μg m-3, respectively. Using the WHO 2005 Air Quality Guideline cut-off point of PM_2.5 of 10 μg m-3, the estimated excess deaths for 2000, 2008, and 2013 from all-cause (natural) mortality were between 5893 and 9781 (95 % CI: 3347-12,791), COPD was between 164 and 957 (95 % CI: 95-1411), lung cancer was between 109 and 307 (95 % CI: 63-437), IHD was between 3 and 163 deaths, according to age groups (95 % CI: 2-394) and stroke was between 6 and 155 deaths, according to age groups (95 % CI: 3-261). An increase in estimated health endpoints was associated with increased estimated PWEL PM_2.5 for 2013 compared to 2000 and 2008. Adhering the ambient PM_2.5 level to the Malaysian Air Quality Standard IT-2 would reduce the national health endpoints mortality.

Effect of urban form on PM2.5 concentrations in urban agglomerations of China: Insights from different urbanization levels and seasons

Planned urban form has become an important strategy to improve air quality in urban agglomerations (UAs), especially pollution due to PM_2.5, but the influencing mechanisms are not yet clear. This study explores the relationship between four metrics of urban form (size, fragmentation, shape, and dispersion) as determined by analysis of remotely sensed images at 30-m resolution and PM_2.5 concentrations in 19 Chinese UAs. The influence of level of urban development and season is examined. Five control variables, including population density, temperature, precipitation, wind speed, and the normalized difference vegetation index (NDVI) are selected for use in multiple linear regression models. Size, fragmentation, and shape of urban form, but not dispersion, were found to have significant effects on PM_2.5 concentrations of different urbanization-level UAs. Urban size and fragmentation have stronger impacts on PM_2.5 concentrations in UAs with lower urbanization levels while urban shape has a greater impact in higher-level UAs. In terms of seasonal variation in all UAs, urban form is more pronouncedly associated with PM_2.5 concentrations during spring and autumn than summer and winter. Urban size and fragmentation are positively associated with PM_2.5 concentrations whereas urban shape and dispersion are on the contrary. The relationships between urban form and PM_2.5 uncovered here underscore the importance of urban planning as a tool to minimize PM_2.5 pollution. Specifically, local government should encourage polycentric urban form with lower fragmentation in urban agglomerations. UAs with lower urbanization levels should control the disordered expansion of construction land and higher-level UAs should promote the mix of green land and construction land. Moreover, measures to control air pollution from anthropogenic activities in spring, autumn and winter are likely to be more effective in decreasing PM_2.5 concentrations in UAs.

Assessment of indoor air quality and their inter-association in hospitals of northern India-a cross-sectional study

This study was commenced to evaluate the indoor and outdoor air quality concentrations of PM_2.5, sub-micron particles (PM_>2.5, PM_1.0-2.5, PM_{0.50 -1.0}, PM_0.25-0.50, and PM_<0.25), heavy metals, and microbial contaminants along with their identification in three different hospitals of Lucknow City. The study was conducted from February 2022 to April 2022 in hospitals situated in the commercial, residential, and industrial belts of the city. The indoor concentration trend of particulate matter as observed during the study suggested that most of the highest concentrations belonged to the hospital situated in an industrial area. The highest obtained indoor and outdoor concentrations for PM_1.0-2.5, PM_0.50-1.0, PM_0.25-0.50, and PM_<0.25 are 40.44 µg/m³, 56.08 µg/m³, 67.20 µg/m³, 74.50 µg/m³, 61.9 µg/m³, 79.3 µg/m³, 82.0 µg/m³, and 93.9 µg/m³, respectively, which belonged to hospital C situated in the industrial belt. However, for PM_>2.5, the highest indoor concentration obtained belonged to hospital B, i.e., 30.7 µg/m³, which is situated in the residential belt of the city. Regarding PM_2.5, the highest indoor and outdoor concentrations obtained are 149.41 µg/m³ and 227.45 µg/m³, which were recorded at hospital A and hospital C, respectively. The present study also observed that a high bacterial load of 1389.21 CFU/m³ is recorded in hospital B, and the fungi load was highest in hospital C with 786.34 CFU/m³. Henceforth, the present study offers thorough information on the various air pollutants in a crucial indoor setting, which will further aid the researchers in the field to identify and mitigate the same more precisely.

Ambient PM2.5 and O3 pollution and health impacts in Iranian megacity

The main objectives of this study were to (i) assess variation within fine particles (PM_2.5) and tropospheric ozone (O₃) time series in Khorramabad (Iran) between 2019 (before) and 2020 (during COVID-19 pandemic); (ii) assess relationship between PM_2.5 and O₃, the PM_2.5/O₃ ratio, and energy consumption; and (iii) estimate the health effects of exposure to ambient PM_2.5 and O₃. From hourly PM_2.5 and O₃ concentrations, we applied both linear-log and integrated exposure-response functions, city-specific relative risk, and baseline incidence values to estimate the health effects over time. A significant correlation was found between PM_2.5 and O₃ (r =-0.46 in 2019, r =-0.55 in 2020, p < 0.05). The number of premature deaths for all non-accidental causes (27.5 and 24.6), ischemic heart disease (7.3 and 6.3), chronic obstructive pulmonary disease (17 and 19.2), and lung cancer (9.2 and 6.25) attributed to ambient PM_2.5 exposure and for respiratory diseases (4.7 and 5.4) for exposure to O₃ above 10 µg m^-3 for people older than 30-year-old were obtained in 2019 and 2020. The number of years of life lost declined by 11.6% in 2020 and exposure to PM_2.5 reduced the life expectancy by 0.58 and 0.45 years, respectively in 2019 and 2020. Compared to 2019, the restrictive measures associated to COVID-19 pandemic led to reduction in PM_2.5 (-25.5%) and an increase of O₃ concentration (+ 8.0%) in Khorramabad.

Characteristics of Air Pollutants Emission and Its Impacts on Public Health of Chengdu, Western China

Pollution caused by PM_2.5 and O₃ are common environmental problems which can easily affect human health. Chengdu is a major central city in Western China, and there is little research on the regional emissions and health effects of air pollution in Chengdu. According to the Multi-resolution Emissions Inventory of the Chinese Model, 2017 (MEIC v1.3), this study compiled the air pollutant emission inventory of Chengdu. The results show that the pollutant emission of Chengdu is generally higher in winter than in summer. The southeast area of Chengdu is the key area where emissions of residential and industrial sectors are dominant. Through air quality simulation with a Weather Research and Forecasting model, coupled with the Community Multiscale Air Quality (WRF-CMAQ), the health effects of PM_2.5 and O₃ in winter and summer in Chengdu of 2017 were investigated. The primary pollutant in winter is PM_2.5 and O₃ in summer. PM_2.5 pollution accounted for 351 deaths in January and July 2017, and O₃ pollution accounted for 328 deaths in the same period. There were 276 deaths in rural areas and 413 in urban areas. In January and July 2017, the health economic loss caused by PM_2.5 accounted for 0.0974% of the gross regional product (GDP) of Chengdu in 2017, and the health economic loss caused by O₃ accounted for 0.0910%.

Tracking short-term health impacts attributed to ambient PM2.5 and ozone pollution in Chinese cities: an assessment integrates daily population

Joint and synergistic control of PM_2.5 and ozone pollution is an urgent need in China and a global-widely concerned issue. Health impact assessment could provide a comprehensive perspective for PM_2.5-ozone coordinated control strategies. For a detailed understanding of the seasonality and regionality of the health impacts attributed to PM_2.5 and ozone in China, this study extended the classic health impact function by daily population and assessed the short-term (daily) health impacts in 335 Chinese cities in 2021. Population migration indexes from Baidu were introduced to estimate the cities' daily population. Using this method, we quantitatively investigated the influence of population on short-term health impact assessment and identified which was significant in the Pearl River Delta (PRD) region and other populous cities. Although the annual sums of PM_2.5- and ozone-related daily health impacts were close for all Chinese cities, the PM_2.5-related health impact was equivalent to 333.96% and 32.07% of that ozone-related, during the cold and warm periods. The correlation and local spatial association analysis found significant city-specific and city-cluster associations of daily health impacts during the warm period and in Beijing-Tianjin-Hebei and surrounding regions (BTHS) and the Yangtze River Delta (YRD). Policymakers could promote period- and pollutant-targeted control actions for the major city groups, especially the BTHS, YRD, and PRD. Our methods and findings investigated the various influences of the population on short-term health impact assessment and proposed the PM_2.5-ozone collaborative control idea for key regions and city groups.

Long-term exposure to particulate matter was associated with increased dementia risk using both traditional approaches and novel machine learning methods

Air pollution exposure has been linked to various diseases, including dementia. However, a novel method for investigating the associations between air pollution exposure and disease is lacking. The objective of this study was to investigate whether long-term exposure to ambient particulate air pollution increases dementia risk using both the traditional Cox model approach and a novel machine learning (ML) with random forest (RF) method. We used health data from a national population-based cohort in Taiwan from 2000 to 2017. We collected the following ambient air pollution data from the Taiwan Environmental Protection Administration (EPA): fine particulate matter (PM_2.5) and gaseous pollutants, including sulfur dioxide (SO₂), carbon monoxide (CO), ozone (O₃), nitrogen oxide (NO_x), nitric oxide (NO), and nitrogen dioxide (NO₂). Spatiotemporal-estimated air quality data calculated based on a geostatistical approach, namely, the Bayesian maximum entropy method, were collected. Each subject's residential county and township were reviewed monthly and linked to air quality data based on the corresponding township and month of the year for each subject. The Cox model approach and the ML with RF method were used. Increasing the concentration of PM_2.5 by one interquartile range (IQR) increased the risk of dementia by approximately 5% (HR = 1.05 with 95% CI = 1.04-1.05). The comparison of the performance of the extended Cox model approach with the RF method showed that the prediction accuracy was approximately 0.7 by the RF method, but the AUC was lower than that of the Cox model approach. This national cohort study over an 18-year period provides supporting evidence that long-term particulate air pollution exposure is associated with increased dementia risk in Taiwan. The ML with RF method appears to be an acceptable approach for exploring associations between air pollutant exposure and disease.

Health and economic impacts of ambient air particulate matter (PM2.5) in Karaj city from 2012 to 2019 using BenMAP-CE

The present study aims to estimate the effects of PM_2.5 on the health and economy of Karaj city from 2012 to 2019. In this study, mortality attributed to long-term exposure to PM_2.5 and its spatial distribution in Karaj over the 2012-2019 period were estimated using the Global Exposure Mortality Model (GEMM) concentration-response function and BenMAP software. PM_2.5 hourly concentration data of air quality monitoring stations were used to estimate PM_2.5 for the whole city of Karaj. The economic effects of this pollutant were also assessed using the value of statistical life (VSL) method. The results showed that the annual average PM_2.5 concentration during the studied time increased and was higher than the air quality guideline levels recommended by the World Health Organization. Also, the annual number of deaths attributed to PM_2.5 in adults (older than 25 years) was estimated to be about 1200. The highest to lowest proportions of PM_2.5-related deaths were non-accidental mortality, ischemic heart attack, stroke, acute respiratory tract infection, chronic obstructive pulmonary disease (COPD), and lung cancer, in the order of their appearance. The results showed that the economic loss attributed to this pollutant was estimated at 380 to 504 million USD per year. Due to the effects of PM_2.5 on health and the economy in this city, we suggest conducting special planning to control and reduce the concentration of ambient air particulate matter by improving the public transportation system and updating industrial processes.

Tropospheric Ozone in Tehran, Iran, during the last 20 years

Air pollution and its effects on human health and the environment are one of the main concerns in urban areas. This study focuses on the distribution and changes in the concentrations of ozone and its precursors (i.e., NO, NO2 and CO) in Tehran for the 20-year period from 2001 to 2020. The effects of precursors and meteorological conditions (temperature, wind speed, dew point, humidity and rainfall) on ozone were investigated using data from 22 stations of the Air Quality Control Company (AQCC) and meteorological stations. Regression models were applied to evaluate the dependence of ozone concentration on its precursors and meteorological parameters based on monthly average values. Finally, the monthly and annual levels of surface ozone and total column ozone were compared during the study period. The results show that the average ozone concentration in Tehran varied substantially between 2001 and 2008, and decreased after 2008 when stringent air quality control measures were implemented. The highest average concentration of ozone occurred in the southwest of Tehran. Although mobile and resident sources play an important role in the release of precursors, the results also indicate a significant effect of meteorological conditions on the changes in ozone concentration. This study is an effective step toward a better understanding of ozone changes in Tehran under the changing influence of precursors and meteorological conditions.

Detection of urban trees sensitivity to air pollution using physiological and biochemical leaf traits in Tehran, Iran

The increased population in megacities has recently exacerbated the need to combat air pollution. This study examined the concept that the sensitivity and tolerance of urban plant species to air pollution might be used to determine Tehran, Iran's air quality and obtain suitable urban greening. The air pollution tolerance index (APTI) was derived using the total chlorophyll, relative water content, pH, and ascorbic acid content of leaf extract from Morus alba, Ailanthus altissima, and Salix babylonica trees as an indicator of the sensitivity and tolerance of urban plant species. A. altissima and S. babylonica, with APTI values of 11.15 and 11.08, respectively, were sensitive to air pollution and can be employed as bioindicators, whereas M. alba, with an APTI value of 14.08, exhibited moderate resistance to air pollution and is therefore recommended for urban planting. Furthermore, the content of enzymatic and non-enzymatic parameters (carotenoid, phenol, and flavonoids) and proline concentration in the polluted seasons and sites (3 and 4) have been increased in M. alba. Collectively, we expect our findings to contribute to the rapidly growing body of research aiming to find a suitable urban greening for a wide range of polluted megacities.

Effect of portable air purifier on indoor air quality: reduced exposure to particulate matter and health risk assessment

We sought to investigate the impact of air purifiers in the removal of particular matter (PM)₁₀, PM_2.5, PM_1, and particle number concentration (PNC) in the indoor air of dormitories located at Iran's largest medical university, Tehran University of Medical Sciences. Twelve rooms were selected and randomly assigned to two rooms: sham air purifier system deployed room (SR) and true air purifier system deployed room (TR). All study samples were drawn simultaneously from assigned rooms using portable GRIMM dust monitors for 24 h. The PM monitors of air were positioned in the middle of each room next to the air purifier at the height of the breathing zone (1.5 m in height). The mean PM₁₀, PM_2.5, PM₁, and PNC removal efficiency in rooms with and without a smoker were measured to be 40.7 vs 83.8%, 31.2 vs 78.4%, 29.9 vs 72.3%, and 44.3 vs 75.6%, respectively. The results showed that smoking is an important influencing factor on the indoor air quality; smoking lowered the removal efficiency of PM₁₀, PM_2.5, PM₁, and PNC by 43%, 47%, 43%, and 31%, respectively. An air purifier could decline the PM₁₀ and PM_2.5 even lower than the WHO 24-h guideline level in non-smoker rooms. This study revealed that using household air purifiers in rooms with smokers and non-smokers significantly reduces the non-carcinogenic risks of exposure to PM₁₀ and PM_2.5.

Time series analysis of the air pollution around Ploiesti oil refining complex, one of the most polluted regions in Romania

Refineries and petrochemical industries are known to be the principal sources of emissions for a number of air pollutants, such as Volatile Organic Compounds (VOCs), greenhouse gases and particulate matter, which negatively affect the air quality. The primary goal of this research was the time series analysis of PM_2.5, PM₁₀, As, Cd, Ni, Pb, benzene, toluene, ethylbenzene, o-xylene, m-xylene, p-xylene, CO, NO, NO₂, NO_x, SO₂ and O₃ over an eleven-year period (2009-2019) and the connection between air pollution and meteorological parameters (air temperature, precipitation quantity and relative humidity). Regarding the pollution level of the major pollutants, the minimum pollution levels, except SO₂ and O₃, were recorded during warmer periods, meanwhile increased levels, were detected during the cold period (in winter). The air pollutants' concentration and distribution are affected by meteorological parameters, such as wind speed and direction, rainfall or even relative humidity. Therefore, the highest concentrations in the winter season were 1.25 times higher than in autumn, 1.3 times higher than the average annual value, 1.57 times higher than in spring and 1.79 times higher than in summer. Monthly variation of O₃ showed lower concentration during winter (27.62 µg/m³) and higher in summer (46.42 µg/m³). Based on the statistical analysis, a significant Spearman correlation was detected between the studied air pollutants and meteorological parameters, and according to the Principal Component Analysis (PCA) and cluster analysis, some common sources were also detected.

Air pollution exposure and mammographic breast density in Tehran, Iran: a cross-sectional study

BACKGROUND

Air pollution is one of the major public health challenges in many parts of the world possibly has an association with breast cancer. However, the mechanism is still unclear. This study aimed to find an association between exposure to six criteria ambient air pollutants (PM_2.5, PM₁₀, SO₂, NO₂, O₃, and CO) and mammographic breast density (MBD), as one of the strongest predictors for developing breast cancer, in women living in Tehran, Iran.

METHODS

Participants were selected from women attending two university hospitals for screening mammography from 2019 to 2021. Breast density was rated by two expert radiologists. Individual exposures to 3-year ambient air pollution levels at the residence were estimated.

RESULTS

The final analysis in 791 eligible women showed that low and high breast density was detected in 34.8 and 62.2 of participants, respectively. Logistic regression analysis after considering all possible confounding factors represented that an increase in each unit of NO₂ (ppb) exposure was associated with an increased risk of breast density with an OR equal to 1.04 (95CI: 1.01 to 1.07). Furthermore, CO level was associated with a decreasing breast density (OR = 0.40, 95CI = 0.19 to 0.86). None of the other pollutants were associated with breast density.

CONCLUSION

Higher MBD was associated with an increased level of NO₂, as a marker of traffic-related air pollution. Furthermore, CO concentration was associated with a lower MBD, while other criteria air pollutants were not related to MBD. Further studies are needed to evaluate the association between ambient air pollutants with MBD.

A Review of Studies Using Air Q Software for Prediction of Air Pollution Health Effects in Iran

PURPOSE OF REVIEW

Exposure to air pollutants may lead to various health effects and is a major public health issue. Concerns about these effects exist in both developed and developing countries. The Air Q software was developed to estimate the health impacts of air pollution based on reported levels of air pollutants in real world studies. In Iran several studies have been conducted to estimate human morbidity and mortality based on this software. We conducted this review to summarize articles which have predicted the effects of air pollution on human health in Iran using Air Q. We conducted a systematic search for relevant studies published until 24 April 2021 in Web of Science, PubMed, Scopus, and SID (Scientific Information Database which includes articles in Farsi language). We applied no time or language restrictions.

RECENT FINDINGS

A total of 44 studies out of 525 identified articles met our inclusion criteria. The main air pollutants under investigation were particulate matter (PM), NO₂, O₃, and SO₂. Most studies were conducted in metropolitan areas, such as Ahvaz (9 studies), Tehran (9 studies), and Shiraz (7 studies). In all studies, the levels of most air pollutants were higher than the 2005 WHO guideline levels and were predicted to be related to considerable health effects. However, it was not possible to aggregate the results and report the total number of casualties during these years, because studies were done in different cities with fluctuating levels of multiple pollutants and in different years and time frames. This systematic review showed that air pollution remains at unacceptably high levels resulting in substantial detrimental health effects in various Iranian cities. Using clean renewable energies, increasing human capital, and increasing green spaces and vegetation can help improve air pollution and decrease human casualties in Iran.

The impact of local fugitive particulate matter and emission inventories on air quality and health in dry and arid areas

The arid and semi-arid regions are facing a huge brunt of fugitive Particulate Matter (fPM) pollution, usually ascribed to the natural dust generated at the regional level (>100 km). In this study, the contribution of locally generated fPM to air pollution and it's environmental risk were assessed at a typical dry-arid area in the Middle East (i.e., State of Qatar, 200 × 200 km² domain) with the use of different emission and dispersion models. Four modelling scenarios were constructed to reflect standard practices (e.g., regional emission models and the World Health Organization's (WHO) Environmental Burden of Disease (EBD) method) and higher resolution calculations with emission models that were developed in past field campaigns. Emphasis was given to the effect on the WHO methodology beyond the typical emission estimates and ambient concentration levels. Eventually, the use of higher spatial resolution population and concentration data revealed fPM hot spots yielding up to 11.0 times higher short-term excess mortalities (an average increase of 1.8 times) compared to the baseline WHO methodology, where the whole population was exposed to a single average concentration. A difference that could be attributed to the improvement of the emission estimations for barren lands and traffic. For example, the estimated PM₁₀ emission fluxes from barren lands, within the main metropolitan area, using the improved emissions model ranged from 0.05 to 42.0 μg m^-2 s^-1, which is considerably higher than the emissions predicted using just the literature models (0.03 to 2.0 μg m^-2 s^-1). Overall, the barren lands emissions accounted for more than 90% of the fPM emissions during the study period. Consequently, this study is one of the first to quantify the significance of locally induced fPM and highlight the need for dedicated field studies and improved emissions estimation tools.

Ozone Pollution in Chinese Cities: Spatiotemporal Variations and Their Relationships with Meteorological and Other Pollution Factors (2016–2020)

With the acceleration of urbanization, ozone (O3) pollution has become increasingly serious in many Chinese cities. This study analyzes the temporal and spatial characteristics of O3 based on monitoring and meteorological data for 366 cities and national weather stations throughout China from 2016 to 2020. Least squares linear regression and Spearman’s correlation coefficient were computed to investigate the relationships of O3 with various pollution factors and meteorological conditions. Global Moran’s I and the Getis–Ord index Gi* were adopted to reveal the spatial agglomeration of O3 pollution in Chinese cities and characterize the temporal and spatial characteristics of hot and cold spots. The results show that the national proportion of cities with an annual concentration exceeding 160 μg·m−3 increased from 21.6% in 2016 to 50.9% in 2018 but dropped to 21.5% in 2020; these cities are concentrated mainly in Central China (CC) and East China (EC). Throughout most of China, the highest seasonal O3 concentrations occur in summer, while the highest values in South China (SC) and Southwest China (SWC) occur in autumn and spring, respectively. The highest monthly O3 concentration reached 200 μg·m−3 in North China (NC) in June, while the lowest value was 60 μg·m−3 in Northeast China (NEC) in December. O3 is positively correlated with the ground surface temperature (GST) and sunshine duration (SSD) and negatively correlated with pressure (PRS) and relative humidity (RHU). Wind speed (WIN) and precipitation (PRE) were positively correlated in all regions except SC. O3 concentrations are significantly differentiated in space: O3 pollution is high in CC and EC and relatively low in the western and northeastern regions. The concentration of O3 exhibits obvious agglomeration characteristics, with hot spots being concentrated mainly in NC, CC and EC.

Temporal profiles of ambient air pollutants and associated health outcomes in two polluted cities of the Middle East

Dust storms and particulate matters had been increased due to climate change in the Middle East. On the other hand, urbanization and industrialization raised levels of gaseous air pollutants in all big cities. In the current study, air pollution information collected from Environmental Protection Agency of Khuzestan and Tehran containing hourly O₃, NO₂, CO, SO₂, PM₁₀ and PM_2.5 concentrations between 2014 and 2015. This study evaluated the air quality of these two cities by Air Quality Index (AQI). As a result, mean concentrations of O₃, NO₂, PM₁₀ and PM_2.5 were higher in Ahvaz than Tehran while Tehran was more pollutant in terms of CO and SO₂. Diurnal variations of O₃ in weekend were the only trend located above weekday variations along the daytimes. Hourly variations of all pollutants changed with a wider range of concentrations in Ahvaz. Diurnal peaks of all pollutants showed their highest level on Monday as the busiest day in mega city, Tehran with the exception of SO₂. PM_2.5 was the worst and limiting pollutant for both cities. Accordingly, winter was the most polluted season by 77 and 33 μg m^-3 in Ahvaz and Tehran, respectively. Number of clean days was significantly lower in Ahvaz (no-day) than mega city, Tehran (<17 days). The number of unhealthy days was also presented significantly higher in Ahvaz (>186 days). Although, annual PM_2.5 concentrations were more in Ahvaz, the higher at-risk population in Tehran caused more health endpoints in the capital of Iran. Consequently, both cities should have their own especial pattern to control air pollution and attributed health damages.

Reduction in daily ambient PM2.5 pollution and potential life gain by attaining WHO air quality guidelines in Tehran

BACKGROUND

Fine particulate matter pollution (PM_2.5) is widely considered to be a top-ranked risk factor for premature mortality and years of life lost (YLL). However, evidence regarding the effect of daily air quality improvement on life expectancy is scarce, especially in the Middle East such as Iran. This study aimed to investigate the potential benefits in life expectancy at concentrations meeting the daily PM_2.5 standards during 2012-2016 in Tehran, Iran.

METHODS

We collected daily non-accidental mortality and data on air pollutants and weather conditions from Tehran, Iran, 2012-2016. A quasi-Poisson or Gaussian time-series regression was employed to fit the associations between ambient PM_2.5 and mortality or YLL. Potential gains in life expectancy (PGLE) and attributable fraction (AF) were estimated by assuming that daily PM_2.5 concentrations attained the World Health Organization air quality guidelines (WHO AQG) 2005 (25 μg/m³) and 2021 (15 μg/m³).

RESULTS

During the study period, a total of 221,231 non-accidental deaths were recorded in Tehran, resulting in 3.6 million YLL. The mean concentration of ambient PM_2.5 was 34.7 μg/m³ (standard deviation: 15.3 μg/m³). For a 10-μg/m³ rise in 4-day moving average (lag 03-day) in PM_2.5 concentration, non-accidental mortality and YLL increased by 1.12% (95% confidence interval: 0.60, 1.65) and 20.73 (7.08, 34.39) person years, respectively. A relatively higher effect was observed in males and young adults aged 18-64 years. We estimated that 39830 [AF = 1.1%] and 74284 [AF = 2.1%] YLL could potentially be avoided if daily PM_2.5 concentrations attained the WHO AQG 2005 and 2021, respectively, which corresponded to potential gains in life expectancy of 0.18 (0.06, 0.30) and 0.34 (0.11, 0.56) years for each deceased person. PM_2.5-associated PGLE estimates were largely robust when performing sensitivity analyses.

CONCLUSIONS

Our findings indicated that short-term exposure to PM_2.5 is associated with increased non-accidental YLL and mortality. Prolonged life expectancy could be achieved if the particulate matter air pollution level were kept under a stricter standard.

Health Endpoint of Exposure to Criteria Air Pollutants in Ambient Air of on a Populated in Ahvaz City, Iran

The presence of criteria air pollutants (CAP) in the ambient air of a populated inhalation region is one of the main serious public health concerns. The present study evaluated the number of cardiovascular mortalities (CM), hospital admissions with cardiovascular disease (HACD), and hospital admissions for respiratory disease (HARD) due to CAP exposure between 2010 and 2014. The study used the Air Q model and descriptive analysis to investigate the health endpoint attributed to the ground level of ozone (O₃), nitrogen dioxide (NO₂), sulfide dioxide (SO₂), and particle matter (PM₁₀). Baseline incidence (BI) and relative risk (RR) are the most important factors in the evaluation of health outcomes from exposure to CAP in the ambient air of a populated area according to EPA and the World Health Organization (WHO) guidelines. Our study showed that annual cases of cardiovascular mortality during the period 2010–2014 relating to particle mater were 478, 506, 469, 427, and 371; ozone was 19, 24, 43, 56, and 49; nitrogen dioxide was 18, 20, 23, 27, and 21; and sulfide dioxide was 26, 31, 37, 43 and 11, in the years 2010 to 2014, respectively. These results indicate that the number of hospital admissions for respiratory disease attributed to PM were 2054, 2277, 2675, 2042, and 1895; O₃ was 27, 35, 58, 73, and 63; NO₂ was 23, 24, 15, 25, and 18; and SO₂ was 23, 24, 25, 30, and 20, in the years from 2010 to 2014, respectively. The results also showed that the number of hospital admissions for cardiovascular disease related to particle mater was 560, 586, 529, 503, and 472; ozone was 22, 32, 38, 55, and 51; nitrogen dioxide was 19, 18, 13, 21, and 14; and sulfide dioxide was 12, 14, 16, 22, and 9, in the same period, respectively. Observations showed that most of the pollution was from outdoor air and in the human respiratory tract. Increased levels of sulfide dioxide, particle matter, nitrogen dioxide, and ozone can cause additional morbidity and mortality for exposed populations. According to the results, it is possible to help increase the level of public health. The use of these findings could also be of great help to health professionals and facilitators at regional and national levels.

Does air pollution increase child mortality? Evidence from 58 developing countries

This study aims to investigate the effects of air quality on child mortality in developing countries. We consider annual data covering the period from 2010 to 2016 of 58 countries and estimate the empirical models using recently developed panel quantile regression with the method of moments (MM-QR). It is found that outdoor air quality (measured by the concentration of PM_2.5 in the air) has a positive and significant effect on total child mortality, post-neonatal mortality, and under-five child mortality. However, its effect on neonatal mortality is not statistically significant at lower quantiles. Furthermore, Household air pollution (HAP) also has a positive and significant effect on total child mortality, neonatal mortality, and under-five child mortality. The effect of HAP on post-neonatal mortality is not significant in most cases. Overall, the adverse effect of HAP is larger than the PM_2.5. For instance, a 1% increase of PM_2.5 concentration in the outdoor causes 0.231% total child mortality due to respiratory diseases at [Formula: see text], while a 1% increase of HAP causes 0.532% total child mortality at the same quantile. In many cases, the coefficients of PM_2.5 and HAP increase at the higher quantiles, supporting asymmetric effects of pollutants on child mortality. However, per capita income, access to basic drinking water and sanitation facilities, and domestic and external health expenditures significantly reduce child mortality. On the contrary, open defecation increases mortality. Consequently, policymakers should take adequate measures to improve indoor and outdoor air quality to combat child mortality due to respiratory diseases in developing countries. They should also take initiatives to enhance per capita income, basic drinking water, and sanitation facilities, domestic and external health expenditures, and public awareness against open defecation.

Temporal variations, regional contribution, and cluster analyses of ozone and NOx in a middle eastern megacity during summertime over 2017-2019

Particulate matter is usually regarded as the dominant pollutant in Tehran megacity in Iran. However, the number of ozone exceedance days significantly increased in recent years. This study analyzes simultaneous measurements of O3 and NOx (NO+NO2) concentrations to improve our understanding of ozone evolution during the summers of 2017 to 2019. The k-means clustering technique was used to select five representative air quality monitoring sites in Tehran to capture O3 and NOx concentrations' variability. The findings show that all of the investigated sites failed to meet the ozone non-attainment criterion. The ozone weekend effect is seen in the study of weekday/weekend differences in 2017 and 2018, but not in 2019, which can be due to the shift in the ozone production regime. The summer mean variation analysis can also be used to deduce this regime change. In 2017, the O3 and NO2 summer mean variations suggest a holdback in the NO2 upward trend and a reversal in the O3 downward trend that had been in place since 2012. Air mass back trajectory clustering reveals that east and north-east air mass clusters have the most significant impact on Tehran's O3 pollution and the highest regional contribution to OX. The study of OX against NOx shows that the regional contribution to OX increased from 2017 to 2018 and then decreased in 2019; however, the local contribution is the opposite. The diurnal analysis of the regional and local contributions to OX indicated that OX in Tehran might be primarily affected by pollutants from a short distance. The findings reveal critical changes in the behavior of O3 in recent years, indicating that decision-makers in Tehran should reconsider air pollution control measures.

The oxidative and neurotoxic potentials of the ambient PM2.5 extracts: The efficient multi-solvent extraction method

The health effects of ambient air particulate matter with a diameter of ≤2.5 μm (PM_2.5) on the central nervous system are well known and the induced oxidative stress has been shown as their main neuropathologic outcome. Ambient air PM_2.5 sampling methods mostly use air sampler systems that collect PM_2.5 on filters, which is followed by a PM_2.5 extraction approach. Inefficient extraction may lead to compositional bias and unreal interpretation of the results. This study aimed to compare our proposed multi-solvent extraction (MSE) approach for PM_2.5 extraction with a conventional aqueous extraction (AqE) method using the analysis of oxidative effects and cytotoxicity in the human neuroblastoma SH-SY5Y cell line. Ambient PM_2.5 samples were collected from an urban traffic location in Tehran city, the capital of Iran, using a high-volume sampler. The developed MSE method was proved to have superior advantages over the AqE method including an increased extraction efficiency (as much as 96 against 48% for PM_ms and PM_aq, respectively), and decreased artifacts and compositional biases. Ambient PM_2.5, besides PM_ms and PM_aq were analyzed for water-soluble ions, metals, and major elements. Dithiothreitol, ascorbic acid, lipid peroxidation, and cell viability assays on SH-SY5Y cells represented the significantly higher oxidative potential for PM_ms compared to PM_aq. The increased cytotoxicity may occur because of the increased oxidative potential of PM_ms and possibly is associated with higher efficiency of the MSE over the AqE method for removal of total redox-active PM components.

Estimation of long-term and short-term health effects attributed to PM2.5 standard pollutants in the air of Ardabil (using Air Q + model)

Clean air is considered as a basic need for human health. However, air pollution is a significant threat to health in developed and developing countries. The aim of this study was to estimate the health effects attributed to PM_2.5 pollutants in the air of Ardabil in 2018 (using Air Q + model). Raw data related to particles were collected from the Department of Environment and processed in Excel software and converted into an input file of the Air Q + model, and in the final stage, by considering appropriate epidemiological parameters and combining these data with air quality data, it was possible to estimate the health effects of air pollution. The results showed that the average annual concentrations of PM_2.5 and PM₁₀ were 15.47 and 30.94 in the study year, respectively. The total number of deaths due to ALRI, COPD, lung cancer, IHD, and stroke deaths on average during the study period were estimated to be 73, 11, 7, 15, and 14 deaths, respectively, which include 14.62, 15.78, 4.9, 12.43, and 11.6% of deaths due to ALRI, COPD, lung cancer, IHD, and stroke deaths, respectively. In conditions of concentration above 5 µg/m³, attributed proportion, total number of attributed cases and number of attributed cases per 100,000 population (with moderate relative risk and confidence interval of 95%) for cardiovascular diseases have been estimated to be 0.95% 103 people and 42.19 people. Also, the attributed proportion, the total number of attributable cases, and the number of attributable cases per 100,000 population (with moderate relative risk and confidence of 95%) for the admission of respiratory diseases have been estimated at 97.1%, 68 persons and 3 persons, respectively. Our results suggest that particle exposure even at low concentrations is associated with an increased risk of overall mortality and specific cause mortality and hospital admissions for respiratory and cardiovascular diseases.

Human health risk assessment in PM10 -bound trace elements, seasonal patterns, and source apportionment study in a critically polluted coking coalfield area of India

Jharia Coalfield (JCF) has been affected by coalmine fire and subsidence problems for several years. The emission of particulate pollutants is due to the history of unscientific and unregulated coal mining in the JCF area. In the present study (conducted in the year 2019), seasonal variations, possible causes, and human health hazards of particulate matter (PM₁₀ )-bound trace metals like Cd, Cu, Fe, Cr, Ni, Mn, Co, Pb, Zn, and As were estimated. The mean concentration of PM₁₀ (418 ± 67 µg/m³ ) exceeded the limit of NAAQS (National Ambient Air Quality Standards India, 2009) by a factor of 4.18. PM₁₀ -bound trace metal concentrations were found in the order of Fe > Mn > Cu > Zn > Cr > Pb > Co > Ni > Cd > As. The maximum trace metal concentrations of all the metals studied were observed at the mining areas of JCF affected by coalmine fire. Human health carcinogenic and noncarcinogenic risks in children and adults were estimated through exposure pathways, ingestion, dermal contact, and inhalation. The cancer risk was evaluated as excess cancer risk (ECR). Noncancer risk estimates were evaluated as the hazard index (HI) and the hazard quotient (HQ). The HI and HQ values for Cr, Cu, Cd, As, and Pb at coalmine-fire-affected areas were observed to be higher than the value of safe dose (≤1), showing a possible noncarcinogenic risk to the inhabitants as a result of multielemental toxicity. The ECR values (>10-6) in JCF areas suggested a carcinogenic risk to the populace of the area, owing to inhalation of PM₁₀ -linked Cd. Active mine fire (related to mining activities), higher transportation load, and resuspended particulate matter from road transportation were identified as the possible causes of the estimated risks based on principal component analysis and Pearson correlation analyses. Integr Environ Assess Manag 2022;18:469-478. © 2021 SETAC.