In recent times, the brick kiln contributes to air pollution is one of the most emerging issues worldwide. In this research work, the Peshawar city, ambient air quality was measured, using a fixed air monitoring station to evaluate the impact of gaseous emission from brick kilns on ground level. In this study, the portable gas analyzer (PG-250) was used to quantify brick-based emitting carbon monoxide (CO), sulfur dioxide (SO2) and nitrogen oxide (NOx) from 3 brick kilns in the city of Peshawar. It was noticed that the average concentration of SO2 and NOx exceeds the National Environmental Quality Standards (NEQS) of Pakistan specifically, in terms of air quality. The brick kilns in District Peshawar have shown negative effects on the environment. It is necessary to take various measures to monitor the brick kiln embosom regularly before it becomes a significant risk for individuals. In conclusion, the impact of air pollution on physical activity and sedentary behavior at a specific time may be different.

The present research analyzes air quality in Ahvaz, a city in the south of Iran, paying special attention to sulfur dioxide (SO2). In order to prepare the average data in the city, measurements have been carried out between 2009 and 2010 in two different locations. Relations between sulfur dioxide and some meteorological parameters have been calculated statistically, using the daily average data. The wind data (velocity, direction), relative humidity, temperature, sunshine periods, evaporation and rainfall have been considered as independent variables. The RMSE Test showed that among different prediction models, the stepwise one is the best option. The average concentrations have been calculated for every 24 hours, during each month and each season. Results show that the highest concentration of sulfur dioxide occurs generally in the morning while the lowest concentration is found before the sunshine. In case of the monthly concentrations of sulfur dioxide, the highest value belongs to January, while the lowest one occurs in October. And as for the seasonal concentrations, it has been shown that the highest amounts belong to winter. Results show that quantities of SO2 in different seasons as well as the entire year can be estimated by climate parameters. Results also indicate that the relations between the SO2 and meteorological parameters are stronger than the entire year during the seasons.

For the first time, sulfur dioxide concentration was monitored between 2005 and 2016 over Iran which is among the countries with a high SO2 emission rate in the world. To that end, SO2 column concentration at Planetary Boundary Layer (PBL) from Ozone Monitoring Instrument (OMI) was analyzed. OMI is a sensor onboard the Aura satellite which can measure daily SO2 concentration on the global scale. From OMI maps, 19 notable SO2 hotspots were detected over Iran. The results indicate that the most elevated level of SO2 among these 19 hotspots belong to Khark Island and Asaluye in Bushehr province, southwest of Iran. Annual trend analysis shows that SO2 concentration has been slightly augmented during 2005-2016 over this country. Distribution analysis of SO2 concentration over Iran showed that the most polluted provinces are Bushehr, Khuzestan and Ilam lied in the southwest of Iran. On the contrary, the lowest level of SO2 has observed over northwest of Iran at West and East Azerbaijan and Ardabil provinces. The correlation coefficient between total energy production in Iran and SO2 concentration from 2005 to 2016 is as high as ~0.7. Hence, it can be derived that energy production, most notably production of crude oil, plays a pivotal role in SO2 concentration over Iran.

peer reviewed | In the global COVID-19 epidemic, humans are faced with a new challenge. The concept of quarantine as a preventive measure has changed human activities in all aspects of life. This challenge has led to changes in the environment as well. The air quality index is one of the immediate concrete parameters. In this study, the actual potential of quarantine effects on the air quality index and related variables in Tehran, the capital of Iran, is assessed, where, first, the data on the pollutant reference concentration for all measuring stations in Tehran, from February 19 to April 19, from 2017 to 2020, are monitored and evaluated. This study investigated the hourly concentrations of six particulate matters (PM), including PM2.5, PM10, and air contaminants such as nitrogen dioxide (NO2), sulfur dioxide (SO2), ozone (O3), and carbon monoxide (CO). Changes in pollution rate during the study period can be due to reduced urban traffic, small industrial activities, and dust mites of urban and industrial origins. Although pollution has declined in most regions during the COVID-19 quarantine period, the PM2.5 rate has not decreased significantly, which might be of natural origins such as dust. Next, the air quality index for the stations is calculated, and then, the interpolation is made by evaluating the root mean square (RMS) of different models. The local and global Moran index indicates that the changes and the air quality index in the study area are clustered and have a high spatial autocorrelation. The results indicate that although the bad air quality is reduced due to quarantine, major changes are needed in urban management to provide favorable conditions. Contaminants can play a role in transmitting COVID-19 as a carrier of the virus. It is suggested that due to the rise in COVID-19 and temperature in Iran, in future studies, the effect of increased temperature on COVID-19 can be assessed.

This study investigates changes in air quality conditions during the restricted COVID-19 lockdown period in 2020 across 21 metropolitan areas in the Middle East and how these relate to surface urban heat island (SUHI) characteristics. Based on satellite observations of atmospheric gases from Sentinel-5, results indicate significant reductions in the levels of atmospheric pollutants, particularly nitrogen dioxide (NO₂), sulfur dioxide (SO₂), and carbon monoxide (CO). Air quality improved significantly during the middle phases of the lockdown (April and May), especially in small metropolitan cities like Amman, Beirut, and Jeddah, while it was less significant in “mega” cities like Cairo, Tehran, and Istanbul. For example, the concentrations of NO₂ in Amman, Beirut, and Jeddah decreased by −56.6%, −43.4%, and −32.3%, respectively, during April 2020, compared to April 2019. Rather, there was a small decrease in NO₂ levels in megacities like Tehran (−0.9%) and Cairo (−3.1%). Notably, during the lockdown period, there was a decrease in the mean intensity of nighttime SUHI, while the mean intensity of daytime SUHI experienced either an increase or a slight decrease across these locations. Together with the Gulf metropolitans (e.g. Kuwait, Dubai, and Muscat), the megacities (e.g. Tehran, Ankara, and Istanbul) exhibited anomalous increases in the intensity of daytime SUHI, which may exceed 2 °C. Statistical relationships were established to explore the association between changes in the mean intensity and the hotspot area in each metropolitan location during the lockdown. The findings indicate that the mean intensity of SUHI and the spatial extension of hotspot areas within each metropolitan had a statistically significant negative relationship, with Pearson's r values generally exceeding - 0.55, especially for daytime SUHI. This negative dependency was evident for both daytime and nighttime SUHI during all months of the lockdown. Our findings demonstrate that the decrease in primary pollutant levels during the lockdown contributed to the decrease in the intensity of nighttime SUHIs in the Middle East, especially in April and May. Changes in the characteristics of SUHIs during the lockdown period should be interpreted in the context of long-term climate change, rather than just the consequence of restrictive measures. This is simply because short-term air quality improvements were insufficient to generate meaningful changes in the region's urban climate.

Stillbirth has a great impact on contemporary and future generations. Increasing evidence show that ambient air pollution exposure is associated with stillbirth. However, previous studies showed inconsistent findings. To clarify the effect of maternal air pollution exposure on stillbirth, we searched for studies examining the associations between air pollutants, including particulate matter (diameter ≤ 2.5 μm [PM₂.₅] and ≤10 μm [PM₁₀]) and gaseous pollutants (sulfur dioxide [SO₂], nitrogen dioxide [NO₂], carbon monoxide [CO] and ozone [O₃]), and stillbirth published in PubMed, Web of Science, Embase and Cochrane Library until December 11, 2020. The pooled effect estimates and 95% confidence intervals (CI) were calculated, and the heterogeneity was evaluated using Cochran’s Q test and I² statistic. Publication bias was assessed using funnel plots and Egger’s tests. Of 7546 records, 15 eligible studies were included in this review. Results of long-term exposure showed that maternal third trimester PM₂.₅ and CO exposure (per 10 μg/m³ increment) increased the odds of stillbirth, with estimated odds ratios (ORs) of 1.094 (95% CI: 1.008–1.180) and 1.0009 (95% CI: 1.0001–1.0017), respectively. Entire pregnancy exposure to PM₂.₅ was also associated with stillbirth (OR: 1.103, 95% CI: 1.074–1.131). A 10 μg/m³ increment in O₃ in the first trimester was associated with stillbirth, and the estimated OR was 1.028 (95% CI: 1.001–1.055). Short-term exposure (on lag day 4) to O₃ was also associated with stillbirth (OR: 1.002, 95% CI: 1.001–1.004). PM₁₀, SO₂ and NO₂ exposure had no significant effects on the incidence of stillbirth. Additional well-designed cohort studies and investigations regarding potential biological mechanisms are warranted to elaborate the suggestive association that may help improve intergenerational inequality.

The increase of gaseous ammonia (NH₃) concentration in the atmosphere significantly impacts the regional air quality, human health, and the nitrogen cycle of ecosystems. This study aims to verify the reanalyzed product of IASI NH₃ (the ANNI-NH₃-v2.1R-I, hereafter referred to as IASI_NH₃_R) and to analyze the spatial and temporal characteristics of atmospheric NH₃ during 2008–2016 and its underlying influencing factors. Our results show a good agreement between spatial pattern and temporal (annual and monthly) trend of the satellite-derived surface NH₃ concentrations and the measured near-ground NH₃ measurements over different land covers in Eastern China, suggesting the IASI_NH₃_R product can be used to investigate spatial and temporal trends of atmospheric NH₃ concentration. The annual mean NH₃ column concentrations peaked in the North China Plain (averaged 12 × 10¹⁵ mol cm⁻² yr⁻¹) and showed a significant increasing trend at a rate of 0.6 × 10¹⁵ mol cm⁻² yr⁻¹ during the entire period, which can be ascribed to densely populated, intensive agricultural activities and substantial reduction of SO₂ and NO₂ emissions since 2011. The NH₃ column concentrations show a slight increase in winter in most regions of China, probably due to less precipitation amount and increased uncertainty for lower NH₃ columns and the thermal contrast (TC). A large seasonal variation of NH₃ column concentrations was observed, with the highest values in summer and the lowest in autumn. Such seasonal variation is mainly affected by seasonal differences in NH₃ emissions and meteorological conditions. Our results suggest that the current control measures effectively decreased SO₂ and NO₂ pollution but are not yet apparent in the mitigation of atmospheric NH₃ pollution, which also merits more attention considering that no effective measures are being implemented for NH₃ emission control at a regional or national scale in China.

The proportion of asthma patients with mild to moderate exacerbations is far greater than the number who experience episodes that are severe enough to require emergency room visits or hospital admission. However the routinely collected data from hospitals is absent in the past.To evaluate associations between short-term exposures to air pollutants and hospital outpatient visits for asthma in China.We obtained data for 143,057 asthma outpatient visits from the largest hospitals in 17 Chinese cities, between Jan 01 2013 and Dec 31 2015. We used daily concentrations of air pollutants measured by the China National Environmental Monitoring Centre. We used a time-stratified case-crossover design, and fitted conditional logistic regression models to determine the associations.Particulate matter ≤10μm in diameter (PM10) and nitrogen dioxide (NO2) were associated with increased risks of hospital outpatient visits for asthma on the same day, while the effects were delayed for particulate matter ≤2.5μm in diameter (PM2.5) and sulphur dioxide (SO2). For the cumulative effect model at lag05 days, 10 μg/m3 increase in air pollutants concentrations were correlated with hospital outpatient visits for asthma with odds ratios (ORs) and 95% confidence intervals 1.004 (1.000-1.008) for PM2.5, 1.005 (1.002-1.008) for PM10, 1.030 (1.021-1.040) for NO2, and 1.015 (1.008-1.021) for SO2. Almost one in nine (10.9%; 7.7, 13.9%) hospital outpatient visits for asthma were attributable to NO2.Short-term exposures to PM2.5, PM10, NO2 and SO2 were associated with hospital outpatient visits for asthma in China.

The townships of Puchuncaví and Quintero, on the coast of central Chile, have soils contaminated by atmospheric deposition of sulfur dioxide and trace elements from the nearby Ventanas Industrial Complex. The purpose of this study was to evaluate potential human health and ecological risks, by determining the spatial distribution of soil total concentrations arsenic (As), copper (Cu), lead (Pb), and zinc (Zn) in these townships. Total concentrations of these elements were determined in 245 topsoil samples, used to generate continuous distribution maps. The background concentrations of Cu, As, Pb, and Zn in the studied soils were 100, 16, 35, and 122 mg kg⁻¹, respectively. The concentrations of Cu, As, and Pb were positively correlated with each other, suggesting that their source is the Ventanas copper smelter. On the other hand, correlations for Zn were weaker than for other trace elements, suggesting low impact of the Ventanas copper smelter on spatial distribution of Zn. Indeed, only 6% of the study area exhibited Zn concentrations above the background level. In contrast, 77, 32 and 35% of the study area presented Cu, As, and Pb concentrations, respectively, above the background level. The carcinogenic risk due to exposure to As was above the threshold value of 10⁻⁰⁴ in the population of young children (1–5 years old) on 27% of the study area. These risk values are classified as unacceptable, which require specific intervention by the Chilean government. Based on the estimated concentrations of exchangeable Cu, 10, 15, and 75% of the study area exhibited high, medium, and low phytotoxicity risk, respectively.

PM₂.₅ pollution is caused by multiple factors and determining how these factors affect PM₂.₅ pollution is important for haze control. In this study, we modified the geographically weighted regression (GWR) model and investigated the relationships between PM₂.₅ and its influencing factors. Experiments covering 368 cities and 9 urban agglomerations were conducted in China in 2015 and more than 20 factors were considered. The modified GWR coefficients (MGCs) were calculated for six variables, including two emission factors (SO₂ and NO₂ concentrations), two meteorological factors (relative humidity and lifted index), and two topographical factors (woodland percentage and elevation). Then the spatial distribution of MGCs was analyzed at city, cluster, and region scales. Results showed that the relationships between PM₂.₅ and the different factors varied with location. SO₂ emission positively affected PM₂.₅, and the impact was the strongest in the Beijing–Tianjin–Hebei (BTH) region. The impact of NO₂ was generally smaller than that of SO₂ and could be important in coastal areas. The impact of meteorological factors on PM₂.₅ was complicated in terms of spatial variations, with relative humidity and lifted index exerting a strong positive impact on PM₂.₅ in Pearl River Delta and Central China, respectively. Woodland percentage mainly influenced PM₂.₅ in regions of or near deserts, and elevation was important in BTH and Sichuan. The findings of this study can improve our understanding of haze formation and provide useful information for policy-making.