孟加拉国中部土地利用和人口暴露于PM2.5的气候决定因素

Md. Shareful Hassan, Reeju F. L. Gomes, M. A. H. Bhuiyan, M. T. Rahman
{"title":"孟加拉国中部土地利用和人口暴露于PM2.5的气候决定因素","authors":"Md. Shareful Hassan, Reeju F. L. Gomes, M. A. H. Bhuiyan, M. T. Rahman","doi":"10.3390/pollutants3030026","DOIUrl":null,"url":null,"abstract":"The major industrial cities of Bangladesh are experiencing significant air-pollution-related problems due to the increased trend of particulate matter (PM2.5) and other pollutants. This paper aimed to investigate and understand the relationship between PM2.5 and land use and climatic variables to identify the riskiest areas and population groups using a geographic information system and regression analysis. The results show that about 41% of PM2.5 concentration (μg/m3) increased within 19 years (2002–2021) in the study area, while the highest concentration of PM2.5 was found from 2012 to 2021. The concentrations of PM2.5 were higher over barren lands, forests, croplands, and urban areas. From 2002–2021, the concentration increased by about 64%, 62.7%, 57%, and 55% (μg/m3) annually over barren lands, forests, cropland, and urban regions. The highest concentration level of PM2.5 (84 μg/m3) among other land use classes was found in urban areas in 2021. The regression analysis shows that air pressure (hPa) (r2 = −0.26), evaporation (kg m−2) (r2 = −0.01), humidity (kg m−2) (r2 = −0.22), rainfall (mm/h) (r2 = −0.20), and water vapor (kg m−2) (r2 = −0.03) were negatively correlated with PM2.5. On the other hand, air temperature (k) (r2 = 0.24), ground heat (W m−2) (r2 = 0.60), and wind speed (m s−1) (r2 = 0.34) were positively correlated with PM2.5. More than 60 Upazilas were included in the most polluted areas, with a total population of 11,260,162 in the high-risk/hotspot zone (1,948,029 aged 0–5, 485,407 aged 50–69). Governmental departments along with policymakers, stainable development practitioners, academicians, and others may use the main results of the paper for integrated air pollution mitigation and management in Bangladesh as well as in other geographical settings worldwide.","PeriodicalId":20301,"journal":{"name":"Pollutants","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Land Use and the Climatic Determinants of Population Exposure to PM2.5 in Central Bangladesh\",\"authors\":\"Md. Shareful Hassan, Reeju F. L. Gomes, M. A. H. Bhuiyan, M. T. Rahman\",\"doi\":\"10.3390/pollutants3030026\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The major industrial cities of Bangladesh are experiencing significant air-pollution-related problems due to the increased trend of particulate matter (PM2.5) and other pollutants. This paper aimed to investigate and understand the relationship between PM2.5 and land use and climatic variables to identify the riskiest areas and population groups using a geographic information system and regression analysis. The results show that about 41% of PM2.5 concentration (μg/m3) increased within 19 years (2002–2021) in the study area, while the highest concentration of PM2.5 was found from 2012 to 2021. The concentrations of PM2.5 were higher over barren lands, forests, croplands, and urban areas. From 2002–2021, the concentration increased by about 64%, 62.7%, 57%, and 55% (μg/m3) annually over barren lands, forests, cropland, and urban regions. The highest concentration level of PM2.5 (84 μg/m3) among other land use classes was found in urban areas in 2021. The regression analysis shows that air pressure (hPa) (r2 = −0.26), evaporation (kg m−2) (r2 = −0.01), humidity (kg m−2) (r2 = −0.22), rainfall (mm/h) (r2 = −0.20), and water vapor (kg m−2) (r2 = −0.03) were negatively correlated with PM2.5. On the other hand, air temperature (k) (r2 = 0.24), ground heat (W m−2) (r2 = 0.60), and wind speed (m s−1) (r2 = 0.34) were positively correlated with PM2.5. More than 60 Upazilas were included in the most polluted areas, with a total population of 11,260,162 in the high-risk/hotspot zone (1,948,029 aged 0–5, 485,407 aged 50–69). Governmental departments along with policymakers, stainable development practitioners, academicians, and others may use the main results of the paper for integrated air pollution mitigation and management in Bangladesh as well as in other geographical settings worldwide.\",\"PeriodicalId\":20301,\"journal\":{\"name\":\"Pollutants\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-08-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Pollutants\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3390/pollutants3030026\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Pollutants","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/pollutants3030026","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

由于颗粒物质(PM2.5)和其他污染物的增加趋势,孟加拉国的主要工业城市正在经历严重的空气污染相关问题。本文旨在通过地理信息系统和回归分析,研究和了解PM2.5与土地利用和气候变量的关系,以确定最危险的地区和人群。结果表明:研究区PM2.5浓度(μg/m3)在2002-2021年的19年间增加了约41%,其中2012 - 2021年是PM2.5浓度最高的年份;在荒地、森林、农田和城市地区,PM2.5浓度较高。2002-2021年,荒地、森林、农田和城市地区的浓度分别以每年64%、62.7%、57%和55% (μg/m3)递增。在其他土地利用类别中,2021年城市地区的PM2.5浓度最高(84 μg/m3)。回归分析表明,大气压力(hPa) (r2 =−0.26)、蒸发量(kg m−2)(r2 =−0.01)、湿度(kg m−2)(r2 =−0.22)、降雨量(mm/h) (r2 =−0.20)和水蒸气(kg m−2)(r2 =−0.03)与PM2.5呈负相关。另一方面,气温(k) (r2 = 0.24)、地热(W m−2)(r2 = 0.60)和风速(m s−1)(r2 = 0.34)与PM2.5呈正相关。60多个乌帕兹拉被列入污染最严重的地区,高风险/热点地区的总人口为11,260,162人(0-5岁的1,948,029人,50-69岁的485,407人)。政府部门以及政策制定者、可持续发展从业人员、学者和其他人可将该文件的主要成果用于孟加拉国以及世界其他地理环境的综合空气污染缓解和管理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Land Use and the Climatic Determinants of Population Exposure to PM2.5 in Central Bangladesh
The major industrial cities of Bangladesh are experiencing significant air-pollution-related problems due to the increased trend of particulate matter (PM2.5) and other pollutants. This paper aimed to investigate and understand the relationship between PM2.5 and land use and climatic variables to identify the riskiest areas and population groups using a geographic information system and regression analysis. The results show that about 41% of PM2.5 concentration (μg/m3) increased within 19 years (2002–2021) in the study area, while the highest concentration of PM2.5 was found from 2012 to 2021. The concentrations of PM2.5 were higher over barren lands, forests, croplands, and urban areas. From 2002–2021, the concentration increased by about 64%, 62.7%, 57%, and 55% (μg/m3) annually over barren lands, forests, cropland, and urban regions. The highest concentration level of PM2.5 (84 μg/m3) among other land use classes was found in urban areas in 2021. The regression analysis shows that air pressure (hPa) (r2 = −0.26), evaporation (kg m−2) (r2 = −0.01), humidity (kg m−2) (r2 = −0.22), rainfall (mm/h) (r2 = −0.20), and water vapor (kg m−2) (r2 = −0.03) were negatively correlated with PM2.5. On the other hand, air temperature (k) (r2 = 0.24), ground heat (W m−2) (r2 = 0.60), and wind speed (m s−1) (r2 = 0.34) were positively correlated with PM2.5. More than 60 Upazilas were included in the most polluted areas, with a total population of 11,260,162 in the high-risk/hotspot zone (1,948,029 aged 0–5, 485,407 aged 50–69). Governmental departments along with policymakers, stainable development practitioners, academicians, and others may use the main results of the paper for integrated air pollution mitigation and management in Bangladesh as well as in other geographical settings worldwide.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信