The effects of COVID-19 pandemic on the air pollutants concentration during the lockdown in Tehran, Iran

Aghashariatmadari, Zahra

doi:10.1016/j.uclim.2021.100882

Cited by 12 publications

(6 citation statements)

References 24 publications

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“…The O 3 levels increased in March–April in Iran ( Naqvi et al, 2021 ), then decreased in last days April 2020. In Tehran (Iran), the O 3 levels increased by 53.7% in 2020 compared to averaged 5-years ago at Aghdasieh station ( Aghashariatmadari, 2021 ), and by 28.8% at Sharif-University station compared to the same period in 2019 ( Broomandi et al, 2020 ). In Ardabil the monthly changes during lockdown increased O 3 levels by 51% compared to two months before COVID-19 lockdown ( Rad et al, 2021 ).…”

Section: Resultsmentioning

confidence: 97%

Increased tropospheric ozone levels as a public health issue during COVID-19 lockdown and estimation the related pulmonary diseases

Anbari

Khaniabadi

Sicard

et al. 2022

Atmospheric Pollution Research

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Section: Resultsmentioning

confidence: 97%

Increased tropospheric ozone levels as a public health issue during COVID-19 lockdown and estimation the related pulmonary diseases

Anbari

Khaniabadi

Sicard

et al. 2022

Atmospheric Pollution Research

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“…Although the lockdowns reduced the PM 10 levels in Tehran between 20 and 30 percent [ 105 ], this short-term drop did not diminish the citywide long-term detrimental consequences of PM 10 . Indeed, the industrial plants surrounding the city increased their production of detergents and hygiene products during the COVID-19 pandemic, which account for the continued city pollution [ 106 ]. In addition, the predominant wind direction in Tehran is from the west and south, which may carry PM 10 and other pollutants from their sources (e.g., industrial sources, construction sites, landfills, and desert areas in the south of the city) [ 107 ].…”

Section: Discussionmentioning

confidence: 99%

“…Over 75% of Tehran’s residents use non-standard fuel-powered automobiles, which account for 40% of the city’s air pollution, including NO 2 [ 105 , 109 , 110 ]. Except for the northern portion of the city, bus terminals are another source of NO 2 across the city [ 106 ]. The long-term exposure of Tehran’s residents to air pollution has resulted in a considerable increase in the mortality rate from respiratory disorders, according to earlier research [ 105 ] and we can now see how this has exacerbated the COVID-19 situation.…”

Section: Discussionmentioning

confidence: 99%

The COVID-19 Mortality Rate Is Associated with Illiteracy, Age, and Air Pollution in Urban Neighborhoods: A Spatiotemporal Cross-Sectional Analysis

et al. 2023

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There are different area-based factors affecting the COVID-19 mortality rate in urban areas. This research aims to examine COVID-19 mortality rates and their geographical association with various socioeconomic and ecological determinants in 350 of Tehran’s neighborhoods as a big city. All deaths related to COVID-19 are included from December 2019 to July 2021. Spatial techniques, such as Kulldorff's SatScan, geographically weighted regression (GWR), and multi-scale GWR (MGWR), were used to investigate the spatially varying correlations between COVID-19 mortality rates and predictors, including air pollutant factors, socioeconomic status, built environment factors, and public transportation infrastructure. The city's downtown and northern areas were found to be significantly clustered in terms of spatial and temporal high-risk areas for COVID-19 mortality. The MGWR regression model outperformed the OLS and GWR regression models with an adjusted R2 of 0.67. Furthermore, the mortality rate was found to be associated with air quality (e.g., NO2, PM10, and O3); as air pollution increased, so did mortality. Additionally, the aging and illiteracy rates of urban neighborhoods were positively associated with COVID-19 mortality rates. Our approach in this study could be implemented to study potential associations of area-based factors with other emerging infectious diseases worldwide.

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“…In recent years, AP has become a leading cause of death in both developing and developed countries [7]. In this regard, the amount of air pollutants in many cities in Iran has reached dangerous levels, including in Tehran, Mashhad, Isfahan, Tabriz, Shiraz, Karaj, Arak and Ahvaz [8][9][10][11]. Among the various sectors that pollute the air in Iran, the transportation and industry sectors both generate the most pollution; the transportation sector alone emits 63.3% of the total nitrogen oxide emissions, 29.3% of sulfur dioxide emissions, 27.5% of carbon dioxide emissions, 24.8% of sulfur trioxide emissions, 98.6% of carbon monoxide emissions, 96.3% of carbon hydride emissions, and 79.2% of suspended particles.…”

Section: Introductionmentioning

confidence: 99%

Monitoring Trends of CO, NO2, SO2, and O3 Pollutants Using Time-Series Sentinel-5 Images Based on Google Earth Engine

et al. 2023

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Air pollution (AP) is a significant risk factor for public health, and its impact is becoming increasingly concerning in developing countries where it is causing a growing number of health issues. It is therefore essential to map and monitor AP sources in order to facilitate local action against them. This study aims at assessing the suitability of Sentinel-5 AP products based on Google Earth Engine (GEE) to monitor air pollutants, including CO, NO2, SO2, and O3 in Arak city, Iran from 2018 to 2019. Our process involved feeding satellite images to a cloud-free GEE platform that identified pollutant-affected areas monthly, seasonally, and annually. By coding in the JavaScript language in the GEE, four pollution parameters of Sentinel-5 satellite images were obtained. Following that, images with clouds were filtered by defining cloud filters, and average maps were extracted by defining average filters for both years. The employed model, which solely used Sentinel-5 AP products, was tested and assessed using ground data collected from the Environmental Organization of Central Province. Our findings revealed that annual CO, NO2, SO2, and O3 were estimated with RMSE of 0.13, 2.58, 4.62, and 2.36, respectively, for the year 2018. The annual CO, NO2, SO2, and O3 for the year 2019 were also calculated with RMSE of 0.17, 2.41, 4.31, and 4.6, respectively. The results demonstrated that seasonal AP was estimated with RMSE of 0.09, 5.39, 0.70, and 7.81 for CO, NO2, SO2, and O3, respectively, for the year 2018. Seasonal AP was also estimated with RMSE of 0.12, 4.99, 1.33, and 1.27 for CO, NO2, SO2, and O3, respectively, for the year 2019. The results of this study revealed that Sentinel-5 data combined with automated-based approaches, such as GEE, can perform better than traditional approaches (e.g., pollution measuring stations) for AP mapping and monitoring since they are capable of providing spatially distributed data that is sufficiently accurate.

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The effects of COVID-19 pandemic on the air pollutants concentration during the lockdown in Tehran, Iran

Cited by 12 publications

References 24 publications

Increased tropospheric ozone levels as a public health issue during COVID-19 lockdown and estimation the related pulmonary diseases

Increased tropospheric ozone levels as a public health issue during COVID-19 lockdown and estimation the related pulmonary diseases

The COVID-19 Mortality Rate Is Associated with Illiteracy, Age, and Air Pollution in Urban Neighborhoods: A Spatiotemporal Cross-Sectional Analysis

Monitoring Trends of CO, NO2, SO2, and O3 Pollutants Using Time-Series Sentinel-5 Images Based on Google Earth Engine

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