Pub Date : 2024-04-16DOI: 10.1007/s10874-024-09457-y
A.T.M. Mustafa Kamal, Md. Safiqul Islam, Shahid Uz Zaman, Md. Jalil Miah, Tanvir Ahmed, Sirajul Hoque, Abdus Salam
Five atmospheric trace gases were measured in Dhaka, Bangladesh, using an automated direct sensing gas monitoring system. The average concentrations of CO, NO, NO2, TVOC, and O3 were 2603.6 ± 1216.4, 281.5 ± 158.0, 182.7 ± 69.4, 10,068.2 ± 5296.1 and 36.6 ± 23.6 µg/m3. The measured trace gas concentrations demonstrated significant seasonal and monthly fluctuations, with NO and CO concentrations being the highest in winter, O3 and TVOC concentrations being the highest during the monsoon season, and NO2 concentrations being the highest during the pre-monsoon season. Air mass trajectories and wind rose plots during the monsoon were compared to the winter. It showed that air masses from the southeast and south had an impact on the quantity of most of the trace gases whilst they traveled over the Bay of Bengal throughout the monsoon period. In contrast, air masses from the northwestern region, north, and the west had a bigger effect on the rising amount of trace gases across the Indo Gangetic Plain (IGP) during the winter season. NO2 (182.7 µg/m3) had the maximum concentration of the gases measured and crossed the World Health Organization’s (WHO) annual recommended value. The source characteristics of NOx, TVCO, and O3 gases were determined using the positive matrix factorization (PMF 5.0) model. The combustion of fossil fuels and aerosols were found to be the major sources of NOx and O3, with aerosol formation being the primary source of TVOC concentration.
{"title":"Quantification and source apportionment of atmospheric trace gases over Dhaka, Bangladesh","authors":"A.T.M. Mustafa Kamal, Md. Safiqul Islam, Shahid Uz Zaman, Md. Jalil Miah, Tanvir Ahmed, Sirajul Hoque, Abdus Salam","doi":"10.1007/s10874-024-09457-y","DOIUrl":"10.1007/s10874-024-09457-y","url":null,"abstract":"<div><p>Five atmospheric trace gases were measured in Dhaka, Bangladesh, using an automated direct sensing gas monitoring system. The average concentrations of CO, NO, NO<sub>2</sub>, TVOC, and O<sub>3</sub> were 2603.6 ± 1216.4, 281.5 ± 158.0, 182.7 ± 69.4, 10,068.2 ± 5296.1 and 36.6 ± 23.6 µg/m<sup>3</sup>. The measured trace gas concentrations demonstrated significant seasonal and monthly fluctuations, with NO and CO concentrations being the highest in winter, O<sub>3</sub> and TVOC concentrations being the highest during the monsoon season, and NO<sub>2</sub> concentrations being the highest during the pre-monsoon season. Air mass trajectories and wind rose plots during the monsoon were compared to the winter. It showed that air masses from the southeast and south had an impact on the quantity of most of the trace gases whilst they traveled over the Bay of Bengal throughout the monsoon period. In contrast, air masses from the northwestern region, north, and the west had a bigger effect on the rising amount of trace gases across the Indo Gangetic Plain (IGP) during the winter season. NO<sub>2</sub> (182.7 µg/m<sup>3</sup>) had the maximum concentration of the gases measured and crossed the World Health Organization’s (WHO) annual recommended value. The source characteristics of NOx, TVCO, and O<sub>3</sub> gases were determined using the positive matrix factorization (PMF 5.0) model. The combustion of fossil fuels and aerosols were found to be the major sources of NOx and O<sub>3</sub>, with aerosol formation being the primary source of TVOC concentration.</p></div>","PeriodicalId":611,"journal":{"name":"Journal of Atmospheric Chemistry","volume":"81 1","pages":""},"PeriodicalIF":3.0,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140592009","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-22DOI: 10.1007/s10874-023-09454-7
Roholah Malekei, Mohammad Hossein Sayadi, Reza Dahmardeh Behrooz, Dimitris G. Kaskaoutis
This study investigates the concentrations and spatial distribution of toxic heavy metals (Cd, Cu, Pb and Zn) through chemical analysis of rainwater samples collected in Tehran, Iran during winter and spring of 2022, characterized by different land use, emission sources, traffic conditions and population density. The average concentrations of the examined heavy metals at the five sampling sites were 52.9, 11.8, 14.6 and 0.93 μg l−1 for Zn, Pb, Cu and Cd, respectively. The concentrations of all heavy metals were significantly higher (p < 0.05) at the sampling points in central and south Tehran compared to sites in the west and north, due to different urban characteristics, higher pollution emission rates from the traffic and domestic sectors, and local wind patterns developed within the city. High traffic load in the central part of Tehran also escalates the heavy metal concentrations in this region. The significant correlations between the examined heavy metals at the five sites indicate common, local anthropogenic sources. The heavy metal concentrations were higher for rain samples collected in spring than in winter, likely associated with dilution processes in winter and the restriction measures due to COVID-19 pandemic. During the lockdown period, a drastic decrease in traffic load was observed in Tehran, confirming that motor vehicles is the main regulatory factor for air pollution and potential toxic elements in the city.
{"title":"Toxic heavy metals in rainwater samples of Tehran","authors":"Roholah Malekei, Mohammad Hossein Sayadi, Reza Dahmardeh Behrooz, Dimitris G. Kaskaoutis","doi":"10.1007/s10874-023-09454-7","DOIUrl":"10.1007/s10874-023-09454-7","url":null,"abstract":"<div><p>This study investigates the concentrations and spatial distribution of toxic heavy metals (Cd, Cu, Pb and Zn) through chemical analysis of rainwater samples collected in Tehran, Iran during winter and spring of 2022, characterized by different land use, emission sources, traffic conditions and population density. The average concentrations of the examined heavy metals at the five sampling sites were 52.9, 11.8, 14.6 and 0.93 μg l<sup>−1</sup> for Zn, Pb, Cu and Cd, respectively. The concentrations of all heavy metals were significantly higher (<i>p</i> < 0.05) at the sampling points in central and south Tehran compared to sites in the west and north, due to different urban characteristics, higher pollution emission rates from the traffic and domestic sectors, and local wind patterns developed within the city. High traffic load in the central part of Tehran also escalates the heavy metal concentrations in this region. The significant correlations between the examined heavy metals at the five sites indicate common, local anthropogenic sources. The heavy metal concentrations were higher for rain samples collected in spring than in winter, likely associated with dilution processes in winter and the restriction measures due to COVID-19 pandemic. During the lockdown period, a drastic decrease in traffic load was observed in Tehran, confirming that motor vehicles is the main regulatory factor for air pollution and potential toxic elements in the city.</p></div>","PeriodicalId":611,"journal":{"name":"Journal of Atmospheric Chemistry","volume":"81 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2023-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138947659","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-17DOI: 10.1007/s10874-023-09455-6
Abdelfettah Benchrif, Mounia Tahri, Benjamin Guinot, El Mahjoub Chakir, Fatiha Zahry, Bouamar Bagdhad, Moussa Bounakhla, Hélène Cachier
This study investigates the sources and characteristics of PM10 pollution in Tetouan city, Morocco, by employing a combination of chemical mass closure, source-receptor modelling (namely positive matrix factorization, PMF), and air mass trajectory statistical analyses (concentration weighted trajectory, CWT). It provides compelling evidence that using such a combination is a powerful approach for studying the composition and sources of PM10 in the Tetouan region. The PMF analysis identifies four PM10 sources, namely Vehicle Exhaust, Secondary Aerosols, Nitrate + Biomass Burning, and Fresh Sea Salt, with distinct seasonal contributions. CWT analysis reveals the Mediterranean Basin as the primary source region, with influences from populated areas in northern Morocco, southern Europe, and marine emissions. PM10 mass closure highlights the abundance of Dust, Particulate Organic Matter (POM), and Water-Soluble Inorganic Ions (WSI), accounting for the majority of the mass. The low OC/EC ratio advocates that carbonaceous aerosols primarily originate from local traffic emissions. Diagnostic of WSI ratios shows that the [NH4+]/[SO42−] ratio indicated an ammonium-poor environment and suggested an acidic nature of the PM10 aerosols, while the [SO42−]/[NO3−] ratio reflects the combined influence of stationary and mobile sources, with a partial contribution from industrial activities throughout the year. These findings are expected to shed light on the chemical composition, origin of emission sources, and transport pathways of PM10 in the region, contributing to the understanding of air pollution in the south western Mediterranean.
{"title":"Aerosols in Northern Morocco (Part 3): the application of three complementary approaches towards a better understanding of PM10 sources","authors":"Abdelfettah Benchrif, Mounia Tahri, Benjamin Guinot, El Mahjoub Chakir, Fatiha Zahry, Bouamar Bagdhad, Moussa Bounakhla, Hélène Cachier","doi":"10.1007/s10874-023-09455-6","DOIUrl":"10.1007/s10874-023-09455-6","url":null,"abstract":"<div><p>This study investigates the sources and characteristics of PM<sub>10</sub> pollution in Tetouan city, Morocco, by employing a combination of chemical mass closure, source-receptor modelling (namely positive matrix factorization, PMF), and air mass trajectory statistical analyses (concentration weighted trajectory, CWT). It provides compelling evidence that using such a combination is a powerful approach for studying the composition and sources of PM<sub>10</sub> in the Tetouan region. The PMF analysis identifies four PM<sub>10</sub> sources, namely Vehicle Exhaust, Secondary Aerosols, Nitrate + Biomass Burning, and Fresh Sea Salt, with distinct seasonal contributions. CWT analysis reveals the Mediterranean Basin as the primary source region, with influences from populated areas in northern Morocco, southern Europe, and marine emissions. PM<sub>10</sub> mass closure highlights the abundance of Dust, Particulate Organic Matter (POM), and Water-Soluble Inorganic Ions (WSI), accounting for the majority of the mass. The low OC/EC ratio advocates that carbonaceous aerosols primarily originate from local traffic emissions. Diagnostic of WSI ratios shows that the [NH<sub>4</sub><sup>+</sup>]/[SO<sub>4</sub><sup>2−</sup>] ratio indicated an ammonium-poor environment and suggested an acidic nature of the PM<sub>10</sub> aerosols, while the [SO<sub>4</sub><sup>2−</sup>]/[NO<sub>3</sub><sup>−</sup>] ratio reflects the combined influence of stationary and mobile sources, with a partial contribution from industrial activities throughout the year. These findings are expected to shed light on the chemical composition, origin of emission sources, and transport pathways of PM<sub>10</sub> in the region, contributing to the understanding of air pollution in the south western Mediterranean.</p></div>","PeriodicalId":611,"journal":{"name":"Journal of Atmospheric Chemistry","volume":"81 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2023-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138714346","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study addresses the spatio-temporal variability and plausible sources of criteria air pollutants in the Western Indian city-Ahmedabad. The air pollutants PM10, PM2.5, O3, NO2, SO2, and CO have been analyzed at ten locations in Ahmedabad from 2017 to 2019. The seasonal variability indicates that the air pollutant concentration is highest during winter, followed by pre-monsoon, post-monsoon, and monsoon seasons. The concentration of PM2.5 (59.52 ± 16.68–89.72 ± 20.68) and PM10 (107.25 ± 30.43–176.04 ± 38.34) crosses the National Ambient Air Quality Standards (NAAQS) in all seasons. However, the seasonal difference from winter to pre-monsoon is not highly significant (p > 0.05), indicating that the pollution remains fairly similar during these two seasons. The spatial variability of air pollutants over Ahmedabad indicates that the concentration is highest in the south and central region of Ahmedabad and lowest at the east location. The Ventilation Coefficient (VC) has been used to understand the dispersion of air pollutants. The K-means clustering was performed to assess the locations within Ahmedabad with similar air pollutants sources followed by source identification using Principal Component Analysis-Multiple Linear Regression method (PCA-MLR) of 5 clusters. The different locations identified were industrial, residential, and traffic which mainly contribute to the air pollutants in Ahmedabad city. The health risk assessment indicates PMs are the leading pollutant and causing excess risk (ER > 1) at all the locations. With the help of the different statistical techniques, it helps in ascertaining the hotspots of air pollution in a region which will be beneficial in studying health exposure and for policymakers to adopt mitigation strategies.
{"title":"Spatio-temporal variability and possible source identification of criteria pollutants from Ahmedabad-a megacity of Western India","authors":"Shahana Bano, Vrinda Anand, Ritesh Kalbande, Gufran Beig, Devendra Singh Rathore","doi":"10.1007/s10874-023-09456-5","DOIUrl":"10.1007/s10874-023-09456-5","url":null,"abstract":"<div><p>This study addresses the spatio-temporal variability and plausible sources of criteria air pollutants in the Western Indian city-Ahmedabad. The air pollutants PM<sub>10</sub>, PM<sub>2.5</sub>, O<sub>3</sub>, NO<sub>2</sub>, SO<sub>2,</sub> and CO have been analyzed at ten locations in Ahmedabad from 2017 to 2019. The seasonal variability indicates that the air pollutant concentration is highest during winter, followed by pre-monsoon, post-monsoon, and monsoon seasons. The concentration of PM<sub>2.5</sub> (59.52 ± 16.68–89.72 ± 20.68) and PM<sub>10</sub> (107.25 ± 30.43–176.04 ± 38.34) crosses the National Ambient Air Quality Standards (NAAQS) in all seasons. However, the seasonal difference from winter to pre-monsoon is not highly significant (p > 0.05), indicating that the pollution remains fairly similar during these two seasons. The spatial variability of air pollutants over Ahmedabad indicates that the concentration is highest in the south and central region of Ahmedabad and lowest at the east location. The Ventilation Coefficient (VC) has been used to understand the dispersion of air pollutants. The K-means clustering was performed to assess the locations within Ahmedabad with similar air pollutants sources followed by source identification using Principal Component Analysis-Multiple Linear Regression method (PCA-MLR) of 5 clusters. The different locations identified were industrial, residential, and traffic which mainly contribute to the air pollutants in Ahmedabad city. The health risk assessment indicates PMs are the leading pollutant and causing excess risk (ER > 1) at all the locations. With the help of the different statistical techniques, it helps in ascertaining the hotspots of air pollution in a region which will be beneficial in studying health exposure and for policymakers to adopt mitigation strategies.</p></div>","PeriodicalId":611,"journal":{"name":"Journal of Atmospheric Chemistry","volume":"81 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138631151","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-03DOI: 10.1007/s10874-023-09453-8
Sunaina S., U. C. Kulshrestha
Precipitation is one of the significant phenomena for deposition of nitrogen, carbon and metal fractions. In the current study, Total Nitrogen (TN), Dissolved Organic Carbon (DOC) and metal concentrations were measured at two sites having distinct land use patterns in Delhi National Capital Region during different seasons in 2018 and 2019 to find out their potential sources. The TN mean concentration was found to be 16.0 mg/l and 7.0 mg/l at DG and JN site respectively. Whereas the DOC mean concentration was found to be 3.8 mg/l and 2.5 mg/l at DG and JN site respectively. The sequence for the metal concentrations was recorded as Ca > Na > Mg >K> Al > Cu > Fe > Mn > Zn > As for DG site whereas at JN site we recorded different sequence i.e., Ca > Al > Na > K > Mg > Fe > Mn > Zn > Cu > As. Different sources can be attributed to the influence of anthropogenic activities (agriculture, animal husbandry) on nitrogenous species, and biomass burning on dissolved organic carbon species. The wind rose plots indicated that the local and regional sources located in the south-eastern and north-western direction from the sites influenced the wet deposition of the species. Air-mass back trajectory analysis implied the influence of air masses originating from the Bay of Bengal during monsoon season while that of air masses originating from Haryana, Punjab and further north-west during winter season. Presently, very limited information is available on TN and DOC linking with heavy metals. The current study will be filling such gaps to further help nitrogen and carbon budgeting and linking nitrogen with climate change. The study has policy implications as well for north-central India especially for identifying and controlling local, trans-boundary and distance emission sources. The findings facilitate us to understand a holistic view of chemical composition of precipitation so that effective mitigation measures can be taken accordingly.
沉淀是氮、碳和金属组分沉积的重要现象之一。在目前的研究中,在2018年和2019年的不同季节,在德里国家首都地区两个土地利用模式不同的地点测量了总氮(TN)、溶解有机碳(DOC)和金属浓度,以找出它们的潜在来源。DG和JN位点TN平均浓度分别为16.0 mg/l和7.0 mg/l。DG和JN位点的DOC平均浓度分别为3.8 mg/l和2.5 mg/l。金属浓度序列记录为Ca > Na > Mg >K> Al > Cu > Fe > Mn > Zn > DG位点,我们记录了不同的序列,即Ca > Al > Na >K> Mg > Fe > Mn > Zn > Cu > as。不同的来源可归因于人为活动(农业、畜牧业)对含氮物种的影响,以及生物质燃烧对溶解有机碳物种的影响。风玫瑰样地表明,位于站点东南和西北方向的局地源和区域源影响了该物种的湿沉积。气团的反轨迹分析表明,季风季节来自孟加拉湾的气团对大气的影响最大,而冬季来自哈里亚纳邦、旁遮普邦和更西北方向的气团对大气的影响最大。目前,有关TN和DOC与重金属联系的信息非常有限。目前的研究将填补这些空白,进一步帮助氮和碳预算,并将氮与气候变化联系起来。这项研究对印度中北部也有政策意义,特别是在确定和控制当地、跨界和远距离排放源方面。这些发现有助于我们全面了解降水的化学成分,从而采取有效的减缓措施。
{"title":"Wet deposition of total nitrogen, dissolved organic carbon and heavy metals investigating role of long-range transport at two sites in Delhi","authors":"Sunaina S., U. C. Kulshrestha","doi":"10.1007/s10874-023-09453-8","DOIUrl":"10.1007/s10874-023-09453-8","url":null,"abstract":"<div><p>Precipitation is one of the significant phenomena for deposition of nitrogen, carbon and metal fractions. In the current study, Total Nitrogen (TN), Dissolved Organic Carbon (DOC) and metal concentrations were measured at two sites having distinct land use patterns in Delhi National Capital Region during different seasons in 2018 and 2019 to find out their potential sources. The TN mean concentration was found to be 16.0 mg/l and 7.0 mg/l at DG and JN site respectively. Whereas the DOC mean concentration was found to be 3.8 mg/l and 2.5 mg/l at DG and JN site respectively. The sequence for the metal concentrations was recorded as Ca > Na > Mg >K> Al > Cu > Fe > Mn > Zn > As for DG site whereas at JN site we recorded different sequence i.e., Ca > Al > Na > K > Mg > Fe > Mn > Zn > Cu > As. Different sources can be attributed to the influence of anthropogenic activities (agriculture, animal husbandry) on nitrogenous species, and biomass burning on dissolved organic carbon species. The wind rose plots indicated that the local and regional sources located in the south-eastern and north-western direction from the sites influenced the wet deposition of the species. Air-mass back trajectory analysis implied the influence of air masses originating from the Bay of Bengal during monsoon season while that of air masses originating from Haryana, Punjab and further north-west during winter season. Presently, very limited information is available on TN and DOC linking with heavy metals. The current study will be filling such gaps to further help nitrogen and carbon budgeting and linking nitrogen with climate change. The study has policy implications as well for north-central India especially for identifying and controlling local, trans-boundary and distance emission sources. The findings facilitate us to understand a holistic view of chemical composition of precipitation so that effective mitigation measures can be taken accordingly.</p></div>","PeriodicalId":611,"journal":{"name":"Journal of Atmospheric Chemistry","volume":"80 4","pages":"291 - 307"},"PeriodicalIF":2.0,"publicationDate":"2023-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10874-023-09453-8.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135868289","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-02DOI: 10.1007/s10874-023-09451-w
Ankit Kumar, Priya Saxena, Abdul Atiq Siddiqui, Sreekanth Bojjagani, Altaf Husain Khan, Ganesh Chandra Kisku
Lucknow is one of the most polluted metro-city in India with increasing vehicular density and fuel consumption in the last three decades. The study was conducted during years 2019–2021 for measurement of fine particulate matter (PM2.5), nitrogen dioxide (NO2), sulphur dioxide (SO2), respirable particulate matter (PM10), and noise levels at nine selected sites; 4 residential, 4 commercial, and 1 industrial, encompassing prior-to-lockdown, during-lockdown, and after-lockdown periods. Values of PM10 for prior-to-lockdown, during-lockdown, and after-lockdown period ranged from 133.2 to 197.4, 77.0 to 135.0, and 91.4 to 148.0 µg/m3, respectively while values of PM2.5 were 66.5 to 93.6, 41.9 to 67.5 and 49.5 to 98.6 µg/m3, respectively. Corresponding values of SO2 ranged from 8.7 to 12.8, 5.5 to 7.6, and 11.4 to 17.6 µg/m3, respectively while values of NO2 were 24.6 to 57.0, 20.5 to 32.8, and 26.1 to 43.8 µg/m3, respectively. Order of the trace metals associated with PM2.5 is Co < Cd < As < Cr < Ni < Cu < Pb < Mn < K < Zn, Co < Cd < As < Cr < Cu < Ni < Pb < Mn < Zn < K and Cd < Co < As < Cr < Cu < Ni < Pb < Mn < K < Zn in the same periods. Statistical data evidenced that the air quality of the city witnessed drastic improvement during the COVID-19 pandemic. WHO AIRQ + was utilized to calculate attributable health risk and post-neonatal disease burden; showing 1447 ± 768 estimated number of cases attributable to ambient PM10 per lakh of population. Regulatory authorities need to establish new benchmarks for the prevention and management of public health risks for urban resilience and environmental management for episodic events in the near future.
{"title":"Impact of lockdown (COVID-19) and unlocking period on ambient air quality and human health in Lucknow city, India","authors":"Ankit Kumar, Priya Saxena, Abdul Atiq Siddiqui, Sreekanth Bojjagani, Altaf Husain Khan, Ganesh Chandra Kisku","doi":"10.1007/s10874-023-09451-w","DOIUrl":"10.1007/s10874-023-09451-w","url":null,"abstract":"<div><p>Lucknow is one of the most polluted metro-city in India with increasing vehicular density and fuel consumption in the last three decades. The study was conducted during years 2019–2021 for measurement of fine particulate matter (PM<sub>2.5</sub>), nitrogen dioxide (NO<sub>2</sub>), sulphur dioxide (SO<sub>2</sub>), respirable particulate matter (PM<sub>10</sub>), and noise levels at nine selected sites; 4 residential, 4 commercial, and 1 industrial, encompassing prior-to-lockdown, during-lockdown, and after-lockdown periods. Values of PM<sub>10</sub> for prior-to-lockdown, during-lockdown, and after-lockdown period ranged from 133.2 to 197.4, 77.0 to 135.0, and 91.4 to 148.0 µg/m<sup>3</sup>, respectively while values of PM<sub>2.5</sub> were 66.5 to 93.6, 41.9 to 67.5 and 49.5 to 98.6 µg/m<sup>3</sup>, respectively. Corresponding values of SO<sub>2</sub> ranged from 8.7 to 12.8, 5.5 to 7.6, and 11.4 to 17.6 µg/m<sup>3</sup>, respectively while values of NO<sub>2</sub> were 24.6 to 57.0, 20.5 to 32.8, and 26.1 to 43.8 µg/m<sup>3</sup>, respectively. Order of the trace metals associated with PM<sub>2.5</sub> is Co < Cd < As < Cr < Ni < Cu < Pb < Mn < K < Zn, Co < Cd < As < Cr < Cu < Ni < Pb < Mn < Zn < K and Cd < Co < As < Cr < Cu < Ni < Pb < Mn < K < Zn in the same periods. Statistical data evidenced that the air quality of the city witnessed drastic improvement during the COVID-19 pandemic. WHO AIRQ + was utilized to calculate attributable health risk and post-neonatal disease burden; showing 1447 ± 768 estimated number of cases attributable to ambient PM<sub>10</sub> per lakh of population. Regulatory authorities need to establish new benchmarks for the prevention and management of public health risks for urban resilience and environmental management for episodic events in the near future.</p></div>","PeriodicalId":611,"journal":{"name":"Journal of Atmospheric Chemistry","volume":"80 4","pages":"271 - 289"},"PeriodicalIF":2.0,"publicationDate":"2023-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48575086","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Particulate-bound Polycyclic Aromatic Hydrocarbons (PAHs) have been identified as pollutants of serious concern due to their severe health impacts on human and animal life. In the present work, 16 USEPA (United States Environmental Protection Agency) identified PAHs present in PM2.5 at Jorhat, India during the winter months (Jan-March, 2020) were analyzed. Apart from the temporal variability of these compounds, the impact of varying meteorological factors like temperature, wind speed, relative humidity, and planetary boundary layer height on PAHs concentration have also been studied. It has been observed that the effect of ambient air temperature and planetary boundary layer on PAHs concentration are significant compared to other meteorological parameters during the winter season. The average concentration of total PAHs during this period was 157.2 ± 127.7 ng/m3 with dominance of high molecular weight aromatics compared to the low molecular weight ones. Among all 16 PAHs studied, the contribution of benzo(b,j)fluoranthene (27.26%) to total PAHs concentration was found to be the highest followed by di-benzo(a,h)anthracene (10.37%). Source identification analysis using isomeric PAHs ratios indicated that crop residue burning, vehicular emission, coal, and wood combustion are the major emission sources of PAHs. A comparative study of PAHs emission at the present site with other northern cities of India has been performed and it is observed that vehicular emission contributing to PAHs is common to all cities but in Kolkata, wood and coal combustion were also responsible for PAHs emission. Biomass burning is also seen to be a contributor to Amritsar. Whereas in Jorhat, crop residue and coal/wood combustion are seen to be major contributors to PM2.5 bound PAHs unlike other cities.