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Li L, Bi X, Wang X, Song L, Dai Q, Liu B, Wu J, Zhang Y, Feng Y. High aerosol loading over the Bohai Sea: Long-term trend, potential sources, and impacts on surrounding cities. ENVIRONMENT INTERNATIONAL 2024; 183:108387. [PMID: 38141490 DOI: 10.1016/j.envint.2023.108387] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Revised: 12/11/2023] [Accepted: 12/12/2023] [Indexed: 12/25/2023]
Abstract
Air pollution over the oceans has received less attention compared to densely populated urban areas of continents. The Bohai Sea, a semi-enclosed sea in northern China, is surrounded by thirteen industrial cities that have experienced significant improvements in air quality over the past decade. However, the changes in air pollution over the Bohai Sea and its impacts on surrounding cities remain poorly understood. To address this, this study investigated the evolution of air pollution and its chemical composition in the Bohai Sea over four decades, utilizing satellite remote sensing data, reanalysis datasets, emissions inventories, and statistical modeling. Historically, the region has suffered from severe air pollution, resulting from a combination of continental emissions and marine inputs (e.g., sea salt, ports and maritime vessel activities). The aerosol optical depth (AOD) over the sea was higher than the mean levels observed in its surrounding coastal cities. Statistically, 45% of the air masses reaching the Bohai Sea are associated with natural sources (dust- and marine-rich), while the remainder carry anthropogenic pollutants from continental regions. With the exception of Cangzhou city, these coastal cities suffer from air pollutants originating from the Bohai Sea. Cities in the northern region of the sea, spanning from Tianjin to Yingkou, are particularly impacted. The majority of the surrounding cities are affected by a large proportion of anthropogenic aerosol types transported through air masses from the Bohai Sea, including those from biomass burning and industrial activities. These findings emphasize the considerable influence of human-induced sources in the Bohai Sea on neighboring urban areas. Furthermore, being a maritime region, natural sources like sea salt and dust from the sea may also exert a discernible impact on the neighboring environment.
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Affiliation(s)
- Linxuan Li
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; China Meteorological Administration-Nankai University (CMA-NKU) Cooperative Laboratory for Atmospheric Environment-Health Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Xiaohui Bi
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; China Meteorological Administration-Nankai University (CMA-NKU) Cooperative Laboratory for Atmospheric Environment-Health Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Xuehan Wang
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; China Meteorological Administration-Nankai University (CMA-NKU) Cooperative Laboratory for Atmospheric Environment-Health Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Lilai Song
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; China Meteorological Administration-Nankai University (CMA-NKU) Cooperative Laboratory for Atmospheric Environment-Health Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Qili Dai
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; China Meteorological Administration-Nankai University (CMA-NKU) Cooperative Laboratory for Atmospheric Environment-Health Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Baoshuang Liu
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; China Meteorological Administration-Nankai University (CMA-NKU) Cooperative Laboratory for Atmospheric Environment-Health Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Jianhui Wu
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; China Meteorological Administration-Nankai University (CMA-NKU) Cooperative Laboratory for Atmospheric Environment-Health Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Yufen Zhang
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; China Meteorological Administration-Nankai University (CMA-NKU) Cooperative Laboratory for Atmospheric Environment-Health Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Yinchang Feng
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; China Meteorological Administration-Nankai University (CMA-NKU) Cooperative Laboratory for Atmospheric Environment-Health Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China.
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Li C, van Donkelaar A, Hammer MS, McDuffie EE, Burnett RT, Spadaro JV, Chatterjee D, Cohen AJ, Apte JS, Southerland VA, Anenberg SC, Brauer M, Martin RV. Reversal of trends in global fine particulate matter air pollution. Nat Commun 2023; 14:5349. [PMID: 37660164 PMCID: PMC10475088 DOI: 10.1038/s41467-023-41086-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Accepted: 08/21/2023] [Indexed: 09/04/2023] Open
Abstract
Ambient fine particulate matter (PM2.5) is the world's leading environmental health risk factor. Quantification is needed of regional contributions to changes in global PM2.5 exposure. Here we interpret satellite-derived PM2.5 estimates over 1998-2019 and find a reversal of previous growth in global PM2.5 air pollution, which is quantitatively attributed to contributions from 13 regions. Global population-weighted (PW) PM2.5 exposure, related to both pollution levels and population size, increased from 1998 (28.3 μg/m3) to a peak in 2011 (38.9 μg/m3) and decreased steadily afterwards (34.7 μg/m3 in 2019). Post-2011 change was related to exposure reduction in China and slowed exposure growth in other regions (especially South Asia, the Middle East and Africa). The post-2011 exposure reduction contributes to stagnation of growth in global PM2.5-attributable mortality and increasing health benefits per µg/m3 marginal reduction in exposure, implying increasing urgency and benefits of PM2.5 mitigation with aging population and cleaner air.
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Affiliation(s)
- Chi Li
- Department of Energy, Environmental & Chemical Engineering, Washington University in St. Louis, St. Louis, MO, USA.
| | - Aaron van Donkelaar
- Department of Energy, Environmental & Chemical Engineering, Washington University in St. Louis, St. Louis, MO, USA
| | - Melanie S Hammer
- Department of Energy, Environmental & Chemical Engineering, Washington University in St. Louis, St. Louis, MO, USA
| | - Erin E McDuffie
- Department of Energy, Environmental & Chemical Engineering, Washington University in St. Louis, St. Louis, MO, USA
- Office of Atmospheric Protection, Climate Change Division, U.S. Environmental Protection Agency, Washington, D.C., USA
| | - Richard T Burnett
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
- Population Studies Division, Health Canada, Ottawa, ON, Canada
| | - Joseph V Spadaro
- Spadaro Environmental Research Consultants (SERC), Philadelphia, PA, USA
- European Centre for Environment and Health, World Health Organization (Consultant), Bonn, North Rhine-Westphalia, Germany
| | - Deepangsu Chatterjee
- Department of Energy, Environmental & Chemical Engineering, Washington University in St. Louis, St. Louis, MO, USA
| | - Aaron J Cohen
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
- Health Effects Institute, Boston, MA, USA
| | - Joshua S Apte
- Department of Civil and Environmental Engineering, University of California, Berkeley, CA, USA
- School of Public Health, University of California, Berkeley, Berkeley, CA, USA
| | - Veronica A Southerland
- Milken Institute School of Public Health, George Washington University, Washington, DC, USA
| | - Susan C Anenberg
- Milken Institute School of Public Health, George Washington University, Washington, DC, USA
| | - Michael Brauer
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
- School of Population and Public Health, University of British Columbia, Vancouver, BC, Canada
| | - Randall V Martin
- Department of Energy, Environmental & Chemical Engineering, Washington University in St. Louis, St. Louis, MO, USA
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Yousefi R, Shaheen A, Wang F, Ge Q, Wu R, Lelieveld J, Wang J, Su X. Fine particulate matter (PM2.5) trends from land surface changes and air pollution policies in China during 1980-2020. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2023; 326:116847. [PMID: 36436250 DOI: 10.1016/j.jenvman.2022.116847] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Revised: 11/11/2022] [Accepted: 11/20/2022] [Indexed: 06/16/2023]
Abstract
High levels of fine particulate matter (PM2.5) pose a severe air pollution challenge in China. Both land use changes and anthropogenic emissions can affect PM2.5 concentrations. Only a few studies have addressed the long-term impact of land surface changes on PM2.5 in China. We conducted a comprehensive analysis of PM2.5 trends over China using the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) during 1980-2020. The monthly mean PM2.5 concentrations of MERRA-2 were evaluated across mainland China against independent surface measurements from 2013 to 2020, showing a good agreement. For the trend analysis, China was subdivided into six regions based on land use and ambient aerosols types. Our results indicate an overall significant PM2.5 increase over China during 1980-2020 with major changes in-between. Notwithstanding continued urbanization and associated anthropogenic activities, the PM2.5 reversed to a downward trend around 2007 over most regions except for the part of China that is most affected by desert dust. Statistical analysis suggests that PM2.5 trends during 1980-2010 were associated with urban expansion and deforestation over eastern and southern China. The trend reversal around 2007 is mainly attributed to Chinese air pollution control measures. A multiple linear regression analysis reveals that PM2.5 variability is linked to soil moisture and vegetation. Our results suggest that land use and land cover changes as well as pollution controls strongly influenced PM2.5 trends and that drought conditions affect PM2.5 particularly over desert and forest regions of China. This work contributes to a better understanding of the changes in PM2.5 over China.
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Affiliation(s)
- Robabeh Yousefi
- Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
| | - Abdallah Shaheen
- Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
| | - Fang Wang
- Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China.
| | - Quansheng Ge
- Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
| | - Renguang Wu
- School of Earth Sciences, Zhejiang University, Hangzhou, China
| | - Jos Lelieveld
- Department of Atmospheric Chemistry, Max Planck Institute for Chemistry, Mainz, Germany; Climate and Atmosphere Research Center, The Cyprus Institute, Nicosia, Cyprus
| | - Jun Wang
- Department of Chemical and Biochemical Engineering, Iowa Technology Institute, Center for Global and Regional Environmental Research, University of Iowa, Iowa City, IA, USA
| | - Xiaokang Su
- College of Resource Environment and Tourism, Capital Normal University, Beijing, China
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Ali MA, Bilal M, Wang Y, Qiu Z, Nichol JE, Mhawish A, de Leeuw G, Zhang Y, Shahid S, Almazroui M, Islam MN, Rahman MA, Mondol SK, Tiwari P, Khedher KM. Spatiotemporal changes in aerosols over Bangladesh using 18 years of MODIS and reanalysis data. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2022; 315:115097. [PMID: 35504182 DOI: 10.1016/j.jenvman.2022.115097] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/25/2021] [Revised: 04/13/2022] [Accepted: 04/16/2022] [Indexed: 06/14/2023]
Abstract
In this study, combined Dark Target and Deep Blue (DTB) aerosol optical depth at 550 nm (AOD550 nm) data the Moderate Resolution Imaging Spectroradiometer (MODIS) flying on the Terra and Aqua satellites during the years 2003-2020 are used as a reference to assess the performance of the Copernicus Atmosphere Monitoring Services (CAMS) and the second version of Modern-Era Retrospective analysis for Research and Applications (MERRA-2) AOD over Bangladesh. The study also investigates long-term spatiotemporal variations and trends in AOD, and determines the relative contributions from different aerosol species (black carbon: BC, dust, organic carbon: OC, sea salt: SS, and sulfate) and anthropogenic emissions to the total AOD. As the evaluations suggest higher accuracy for CAMS than for MERRA-2, CAMS is used for further analysis of AOD over Bangladesh. The annual mean AOD from both CAMS and MODIS DTB is high (>0.60) over most parts of Bangladesh except for the eastern areas of Chattogram and Sylhet. Higher AOD is observed in spring and winter than in summer and autumn, which is mainly due to higher local anthropogenic emissions during the winter to spring season. Annual trends from 2003-2020 show a significant increase in AOD (by 0.006-0.014 year-1) over Bangladesh, and this increase in AOD was more evident in winter and spring than in summer and autumn. The increasing total AOD is caused by rising anthropogenic emissions and accompanied by changes in aerosol species (with increased OC, sulfate, and BC). Overall, this study improves understanding of aerosol pollution in Bangladesh and can be considered as a supportive document for Bangladesh to improve air quality by reducing anthropogenic emissions.
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Affiliation(s)
- Md Arfan Ali
- Lab of Environmental Remote Sensing (LERS), School of Marine Sciences (SMS), Nanjing University of Information Science and Technology (NUIST), Nanjing, 210044, China
| | - Muhammad Bilal
- Lab of Environmental Remote Sensing (LERS), School of Marine Sciences (SMS), Nanjing University of Information Science and Technology (NUIST), Nanjing, 210044, China
| | - Yu Wang
- Lab of Environmental Remote Sensing (LERS), School of Marine Sciences (SMS), Nanjing University of Information Science and Technology (NUIST), Nanjing, 210044, China
| | - Zhongfeng Qiu
- Lab of Environmental Remote Sensing (LERS), School of Marine Sciences (SMS), Nanjing University of Information Science and Technology (NUIST), Nanjing, 210044, China.
| | - Janet E Nichol
- Department of Geography, School of Global Studies, University of Sussex, Brighton, BN19RH, UK
| | - Alaa Mhawish
- Lab of Environmental Remote Sensing (LERS), School of Marine Sciences (SMS), Nanjing University of Information Science and Technology (NUIST), Nanjing, 210044, China
| | - Gerrit de Leeuw
- Royal Netherlands Meteorological Institute (KNMI), R & D Satellite Observations, 3730AE De Bilt, the Netherlands; Aerospace Information Research Institute, Chinese Academy of Sciences (AirCAS), No.20 Datun Road, Chaoyang District, Beijing, 100101, China; School of Atmospheric Physics, Nanjing University of Information Science and Technology (NUIST), Nanjing, 210044, China; School of Environment Science and Spatial Informatics, University of Mining and Technology, Xuzhou, Jiangsu, 221116, China
| | - Yuanzhi Zhang
- Lab of Environmental Remote Sensing (LERS), School of Marine Sciences (SMS), Nanjing University of Information Science and Technology (NUIST), Nanjing, 210044, China
| | - Shamsuddin Shahid
- Department of Hydraulics & Hydrology, University Technology Malaysia, Malaysia
| | - Mansour Almazroui
- Center of Excellence for Climate Change Research/Department of Meteorology, King Abdulaziz University, Jeddah, 21589, Saudi Arabia; Climatic Research Unit, School of Environmental Sciences, University of East Anglia, Norwich, UK
| | - M Nazrul Islam
- Center of Excellence for Climate Change Research/Department of Meteorology, King Abdulaziz University, Jeddah, 21589, Saudi Arabia.
| | - Muhammad Ashfaqur Rahman
- Weather and Climate Model Earth Science Technology and Policy Services Ltd. (ESTEPS), Dhaka, 1000, Bangladesh
| | - Sanjit Kumar Mondol
- School of Geographical Science, Nanjing University of Information Science and Technology, Nanjing, 210044, China
| | | | - Khaled Mohamed Khedher
- Department of Civil Engineering, College of Engineering, King Khalid University, Abha, 61421, Saudi Arabia
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Abstract
Central Asia is one of the most important sources of mineral saline dust worldwide. A comprehensive understanding of Central Asian dust transport is essential for evaluating its impacts on human health, ecological safety, weather and climate. This study first puts forward an observation-based climatology of Central Asian dust transport flux by using the 3-D dust detection of Cloud-Aerosol LiDAR with Orthogonal Polarization (CALIOP). The seasonal difference of transport flux and downstream contribution are evaluated and compared with those of the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2). Central Asian dust can be transported not only southward in summer under the effect of the South Asian summer monsoon, but also eastward in other seasons under the control of the westerly jet. Additionally, the transport of Central Asian dust across the Pamir Plateau to the Tibetan Plateau is also non-negligible, especially during spring (with a transport flux rate of 150 kg m−1 day−1). The annual CALIOP-based downstream contribution of Central Asian dust to South Asian (164.01 Tg) is 2.1 times that to East Asia (78.36 Tg). This can be attributed to the blocking effect of the higher terrain between Central and East Asia. Additionally, the downstream contributions to South and East Asia from MERRA-2 are only 0.36 and 0.84 times that of CALIOP, respectively. This difference implies the overestimation of the wet and dry depositions of the model, especially in the low latitude zone. The quantification of the Central Asian dust transport allows a better understanding of the Central Asian dust cycle, and supports the calibration/validation of aerosol-related modules of regional and global climate models.
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Long-Term Variability of Dust Events in Southwestern Iran and Its Relationship with the Drought. ATMOSPHERE 2021. [DOI: 10.3390/atmos12101350] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Dust storms represent a major environmental challenge in the Middle East. The southwest part of Iran is highly affected by dust events transported from neighboring desert regions, mostly from the Iraqi plains and Saudi Arabia, as well as from local dust storms. This study analyzes the spatio-temporal distribution of dust days at five meteorological stations located in southwestern Iran covering a period of 22 years (from 1997 to 2018). Dust codes (06, 07, 30 to 35) from meteorological observations are analyzed at each station, indicating that 84% of the dust events are not of local origin. The average number of dust days maximizes in June and July (188 and 193, respectively), while the dust activity weakens after August. The dust events exhibit large inter-annual variability, with statistically significant increasing trends in all of five stations. Spatial distributions of the aerosol optical depth (AOD), dust loading, and surface dust concentrations from a moderate resolution imaging spectroradiometer (MODIS) and Modern-Era Retrospective analysis for Research and Applications (MERRA-2) retrievals reveal high dust accumulation over southwest Iran and surrounding regions. Furthermore, the spatial distribution of the (MODIS)-AOD trend (%) over southwest Iran indicates a large spatial heterogeneity during 2000–2018 with trends ranging mostly between −9% and 9% (not statistically significant). 2009 was the most active dust year, followed by 2011 and 2008, due to prolonged drought conditions in the fertile crescent and the enhanced dust emissions in the Iraqi plains during this period. In these years, the AOD was much higher than the 19-year average (2000 to 2018), while July 2009 was the dustiest month with about 25–30 dust days in each station. The years with highest dust activity were associated with less precipitation, negative anomalies of the vegetation health index (VHI) and normalized difference vegetation index (NDVI) over the Iraqi plains and southwest Iran, and favorable meteorological dynamics triggering stronger winds.
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Gholamnia R, Abtahi M, Dobaradaran S, Koolivand A, Jorfi S, Khaloo SS, Bagheri A, Vaziri MH, Atabaki Y, Alhouei F, Saeedi R. Spatiotemporal analysis of solar ultraviolet radiation based on Ozone Monitoring Instrument dataset in Iran, 2005-2019. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2021; 287:117643. [PMID: 34182400 DOI: 10.1016/j.envpol.2021.117643] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/21/2021] [Revised: 06/16/2021] [Accepted: 06/21/2021] [Indexed: 06/13/2023]
Abstract
The solar ultraviolet radiation (UVR) at national, provincial and county levels in Iran during 2005-2019 were determined based on Ozone Monitoring Instrument (OMI) dataset. The temporal (annual and monthly) trends and spatial distributions of the UVR in terms of erythemally weighted daily dose (EDD), erythemally weighted irradiance at local solar noon time (EDR), and UV index and the major factors influencing the spatiotemporal trends were analyzed. The population-weighted average values of EDD, EDR, and UV index in Iran were respectively 3631 J/m2, 176.3 mW/m2, 7.1 in 2005 and rose by 0.22% per year to 3744 J/m2, 181.7 mW/m2, and 7.3, respectively in 2019, but the annual trend was not statistically significant. The EDD in Iran during the study period exhibited the highest monthly average value in June (6339 J/m2) and the lowest one in December (1263 J/m2). The solar UVA/UVB ratios at the national level during 2005-2019 were considerably lower in summer. The EDD provincial average values in the study period were in the range of 2717 (Gilan) to 4424 J/m2 (Fars). The spatiotemporal variations of the solar UVR parameters were well described by the linear models as a function of cloud optical thickness (COT), ozone column amount, surface albedo, latitude, and altitude (R2 > 0.961, p value < 0.001) and the temporal changes of the solar UVR parameters were mainly caused by the COT. The results indicated that non-burning exposure to solar UVR in summer can be more efficient for vitamin D synthesis due to higher contribution of UVB in the solar UVR. The spatial distributions and temporal trends should be considered to determine the optimal duration, time and condition of exposure to the solar UVR for the public and occupational training and public health measures.
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Affiliation(s)
- Reza Gholamnia
- Workplace Health Promotion Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran; Department of Health and Safety, and Environment (HSE), School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Mehrnoosh Abtahi
- Workplace Health Promotion Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran; Department of Environmental Health Engineering, School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Sina Dobaradaran
- Systems Environmental Health and Energy Research Center, The Persian Gulf Biomedical Sciences Research Institute, Bushehr University of Medical Sciences, Bushehr, Iran; Department of Environmental Health Engineering, Faculty of Health and Nutrition, Bushehr University of Medical Sciences, Bushehr, Iran
| | - Ali Koolivand
- Department of Environmental Health Engineering, Faculty of Health, Arak University of Medical Sciences, Arak, Iran
| | - Sahand Jorfi
- Environmental Technology Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran; Department of Environmental Health Engineering, School of Public Health, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
| | - Shokooh Sadat Khaloo
- Workplace Health Promotion Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran; Department of Health and Safety, and Environment (HSE), School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Amin Bagheri
- Workplace Health Promotion Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran; Department of Health and Safety, and Environment (HSE), School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Mohammad Hossein Vaziri
- Workplace Health Promotion Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran; Department of Health and Safety, and Environment (HSE), School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Yasamin Atabaki
- Department of Occupational Health and Safety at Work, School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Farnaz Alhouei
- Department of Occupational Health and Safety at Work, School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Reza Saeedi
- Workplace Health Promotion Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran; Department of Health and Safety, and Environment (HSE), School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
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Long-Term Variation Assessment of Aerosol Load and Dominant Types over Asia for Air Quality Studies Using Multi-Sources Aerosol Datasets. REMOTE SENSING 2021. [DOI: 10.3390/rs13163116] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Long-term (2000–2019) assessment of aerosol loads and dominant aerosol types at spatiotemporal scales using multi-source datasets can provide a strong impetus to the investigation of aerosol loads and to the targeted prevention control of atmospheric pollution in densely populated regions with frequent anthropogenic activities and heavy aerosol emissions. This study uses multi-source aerosol datasets, including Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2), Moderate Resolution Imaging Spectroradiometer (MODIS), and Aerosol Robotic Network (AERONET), to conduct a long-term variation assessment of aerosol load, high aerosol load frequency, and dominant aerosol types over Asia. The results indicate that regional aerosol type information with adequate spatial resolution can be combined with aerosol optical depth (AOD) values and heavy aerosol load frequency characterization results to explore the key contributors to air pollution. During the study period, the aerosol load over the North China Plain, Central China, Yangtze River Delta, Red River Delta, Sichuan Basin, and Pearl River Delta exhibited an increasing trend from 2000–2009 due to a sharp rise in aerosol emissions with economic development and a declining trend from 2010–2019 under stricter energy conservation controls and emissions reductions. The growth of urban/industrial (UI) type and biomass burning (BB) type aerosol emissions hindered the improvement of the atmospheric environment. Therefore, in future pollution mitigation efforts, focus should be on the control of UI-type and BB-type aerosol emissions. The Indus–Ganges River Plain, Deccan Plateau, and Eastern Ghats show a continuously increasing trend; however, the aerosol load growth rate of the last decade was lower than that of the first decade, which was mainly due to the decrease in the proportion of the mixed type aerosols.
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Abstract
This study assessed the aerosol climatology over Iran, based on the monthly data of aerosol optical depth (AOD) derived from the reanalysis-based Modern Era Retrospective Analysis for Research and Applications (MERRA-2) and the satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS). In addition, sea level pressure, wind speed, temperature, relative humidity, precipitation, and soil moisture from the ERA5 reanalysis dataset were applied to investigate the climate-related effects on temporal AOD changes. Our analysis identified positive and negative AOD trends during 2000–2010 and 2010–2018, respectively, which are likely linked to aeolian dust changes. The dust-driven AOD trends were supported by changes in the Ångström exponent (AE) and fine mode fraction (FMF) of aerosols over Iran. During the early period (2000–2010), results of AOD-meteorology correlation analyses suggest reduced soil moisture, leading to increased dust emissions, whereas our results suggest that during the later period (2010–2018) an increase of soil moisture led to decreased AOD levels. Soil moisture appears to be a key factor in dust mobilization in the region, notably in southwestern Iran, being influenced by adjacent mineral dust sources. These phenomena were affected by large-scale sea level pressure transformations and the associated meteorology in the preceding winter seasons. Using a multiple linear regression model, AOD variability was linked to various meteorological factors in different regions. Our results suggest that climatic variations strongly affect the dust cycle, with a strong dependence on wintertime conditions in the region.
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Mahato S, Ghosh KG. Short-term exposure to ambient air quality of the most polluted Indian cities due to lockdown amid SARS-CoV-2. ENVIRONMENTAL RESEARCH 2020; 188:109835. [PMID: 32798952 PMCID: PMC7330599 DOI: 10.1016/j.envres.2020.109835] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/10/2020] [Revised: 06/13/2020] [Accepted: 06/14/2020] [Indexed: 05/17/2023]
Abstract
Air pollution has happened to be one of the mounting alarms to be concerned with in many Indian cities. COVID-19 epidemic endow with a unique opportunity to report the degree of air quality improvement due to the nationwide lockdown in 10 most polluted cities across the country. National Air Quality Index (NAQI) based on continuous monitoring records of seven criteria pollutants (i.e. common air pollutants with known health impacts e.g. PM10, PM2.5, CO, NO2, SO2, NH3 and O3) for a total of 59 stations across the cities, satellite image derived Aerosol Optical Depth (AOD) and few statistical tools are employed to derive the outcomes. NAQI results convey that 8 cities out of the 10 air quality restored to good to satisfactory category during the lockdown period. Within week+1 of the lockdown period, PM10 and PM2.5 concentrations have suppressed below the permissible limit in all cities. CO and NO2 have reduced to about -30% and -57% respectively during the lockdown period. Diurnal concentrations of PM10 and PM2.5 have dropped drastically on the very 4th day of lockdown and become consistent with minor hourly vacillation. In April 2020 the AOD amount was reduced to about 36% and 18% in contrast to April 2018 and April 2019 respectively. This add-on reporting of the possible recovery extent in air quality may help to guide alternative policy intervention in form of short term lockdown so as to testify whether this type of unconventional policy decisions may be put forward to attain a green environment. Because, despite numerous restoration plans, air pollution levels have risen unabated in these cities. However, detailed inventory needs to be focused on identifying the localized pollution hotspots (i.e. source contribution).
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Affiliation(s)
- Susanta Mahato
- Department of Geography, University of Gour Banga, Malda, West Bengal, India.
| | - Krishna Gopal Ghosh
- Department of Geography, Presidency University, Kolkata, West Bengal, India.
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