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.

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.

Health Risk Assessment of Exposure to Air Pollutants Exceeding the New WHO Air Quality Guidelines (AQGs) in São Paulo, Brazil

We applied the AirQ+ model to analyze the 2021 data within our study period (15 December 2020 to 17 June 2022) to quantitatively estimate the number of specific health outcomes from long- and short-term exposure to atmospheric pollutants that could be avoided by adopting the new World Health Organization Air Quality Guidelines (WHO AQGs) in São Paulo, Southeastern Brazil. Based on temporal variations, PM_2.5, PM₁₀, NO₂, and O₃ exceeded the 2021 WHO AQGs on up to 54.4% of the days during sampling, mainly in wintertime (June to September 2021). Reducing PM_2.5 values in São Paulo, as recommended by the WHO, could prevent 113 and 24 deaths from lung cancer (LC) and chronic obstructive pulmonary disease (COPD) annually, respectively. Moreover, it could avoid 258 and 163 hospitalizations caused by respiratory (RD) and cardiovascular diseases (CVD) due to PM_2.5 exposure. The results for excess deaths by RD and CVD due to O₃ were 443 and 228, respectively, and 90 RD hospitalizations due to NO₂. Therefore, AirQ+ is a useful tool that enables further elaboration and implementation of air pollution control strategies to reduce and prevent hospital admissions, mortality, and economic costs due to exposure to PM_2.5, O₃, and NO₂ in São Paulo.

Spatial patterns and temporal variations of traffic-related air pollutants and estimating its health effects in Isfahan city, Iran

Isfahan as an important industrial city has faced with air pollution recently. Thus, we assessed the spatial and temporal trends of ambient PM_2.5, CO, SO₂, and O₃ and for estimating their health effect on Isfahan citizens between March 2018 and March 2019 through the AirQ+ software. Our results showed that citizens of Isfahan in almost 240, 167, and 134 of the days in the year has exposure to PM_2.5, SO₂, and O₃ higher than the WHO daily guideline, respectively. Daily variations of PM_2.5, CO, and SO₂ concentration showed the increasing trend of pollutants in the morning to evening. The maximum concentrations of O₃ were observed in the noonday. Also, the concentrations of these pollutants on Friday due to the holiday effect were higher than the weekdays. Except for O₃, the PM_2.5, CO, and SO₂ concentrations in the cold months and cold seasons was higher compared with the hot months and hot seasons. The total number of deaths because of lung cancer, natural mortality, ischemic heart disease, chronic obstructive pulmonary disease,, stroke associated with ambient PM_2.5 with the attributable proportion (AP) 11.43%, 11.63%, 15.96%, 15.15%, and 13.1% (95% CI) were 683, 19, 2, 202, and 55 cases, respectively. Therefore, the present study provides additional data for the provincial managers and politicians useful in planning proper strategies of air pollution control to decrease exposure and attributable mortalities.

Concentrations and mortality due to short- and long-term exposure to PM2.5 in a megacity of Iran (2014-2019)

The present study aimed to survey the spatial and temporal trends of ambient concentration of PM_2.5 and to estimate mortality attributed to short- and long-term exposure to PM_2.5 in Isfahan from March 2014 to March 2019 using the AirQ⁺ software. The hourly concentrations of PM_2.5 were obtained from the Isfahan Department of Environment and Isfahan Air Quality Monitoring Center. Then, the 24-h mean concentration of PM_2.5 for each station was calculated using the Excel software. According to the results, the annual mean concentration of PM_2.5 in 2014-2019 was 29.9-50.9 μg/m³, approximately 3-5 times higher than the WHO guideline (10 μg/m³). The data showed that people of Isfahan in almost 58% to 96% of the days of a year were exposed to PM_2.5 higher than the WHO daily guideline. The concentrations of PM_2.5 in cold months such as October, November, December and January were higher than those in the other months. The zoning of the annual concentrations of PM_2.5 in urban areas showed that the highest PM_2.5 concentrations were related to the northern, northwestern, southern and central areas of the city. On average, from 2014 to 2019, the number of deaths due to natural mortality, lung cancer (LC), chronic obstructive pulmonary disease (COPD), ischemic heart disease (IHD) and stroke associated with ambient PM_2.5 were 948, 16, 18, 281 and 60, respectively. The present study estimated that on average, 14.29% of the total mortality, 17.2% of lung cancer (LC), 15.54% of chronic obstructive pulmonary disease (COPD), 17.12% of ischemic heart disease (IHD) and 14.94% of stroke mortalities were related to long-term exposure to ambient PM_2.5. So provincial managers and politicians must adopt appropriate strategies to control air pollution and reduce the attributable health effects and economic losses.