Potential health risks due to in-car aerosol exposure across ten global cities

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dc.contributor.author Kumar, Prashant
dc.contributor.author Hama, Sarkawt
dc.contributor.author Abbass, Rana
dc.contributor.author Nogueira, Thiago
dc.contributor.author Brand, Veronika
dc.contributor.author Abhijith, k.v
dc.contributor.author Andrade, Maria
dc.contributor.author Asfaw, Araya
dc.contributor.author Hama Aziz, , Kosar
dc.contributor.author Cao a, Shi-Jieg , A
dc.contributor.author El-Gendy, , Ahmed
dc.contributor.author Khare, , Mukesh
dc.contributor.author Muula, Adamson
dc.contributor.author Nagendra k, , S.M. Shiva
dc.contributor.author Ngowi, Aiwerasia
dc.contributor.author Omer, Khalid
dc.contributor.author Salam, Abdus
dc.date.accessioned 2023-08-10T11:09:32Z
dc.date.available 2023-08-10T11:09:32Z
dc.date.issued 2021-06-15
dc.identifier.citation Kumar, P., Hama, S., Abbass, R.A., Nogueira, T., Brand, V.S., Abhijith, K.V., de Fatima Andrade, M., Asfaw, A., Aziz, K.H., Cao, S.J. and El-Gendy, A., 2021. Potential health risks due to in-car aerosol exposure across ten global cities. Environment international, 155, p.106688. en_US
dc.identifier.uri http://dspace.muhas.ac.tz:8080/xmlui/handle/123456789/3398
dc.description.abstract Car microenvironments significantly contribute to the daily pollution exposure of commuters, yet health and so cioeconomic studies focused on in-car exposure are rare. This study aims to assess the relationship between air pollution levels and socioeconomic indicators (fuel prices, city-specific GDP, road density, the value of statistical life (VSL), health burden and economic losses resulting from exposure to fine particulate matter ≤2.5 µm; PM2.5) during car journeys in ten cities: Dhaka (Bangladesh); Chennai (India); Guangzhou (China); Medellín (Colombia); S˜ ao Paulo (Brazil); Cairo (Egypt); Sulaymaniyah (Iraq); Addis Ababa (Ethiopia); Blantyre (Malawi); and Dar-es-Salaam (Tanzania). Data collected by portable laser particle counters were used to develop a proxy of car-user exposure profiles. Hotspots on all city routes displayed higher PM2.5 concentrations and disproportionately high inhaled doses. For instance, the time spent at the hotspots in Guangzhou and Addis Ababa was 26% and 28% of total trip time, but corresponded to 54% and 56%, respectively, of the total PM2.5 inhaled dose. With the exception of Guangzhou, all the cities showed a decrease in per cent length of hotspots with an increase in GDP and VSL. Exposure levels were in dependent of fuel prices in most cities. The largest health burden related to in-car PM2.5 exposure was estimated for Dar-es-Salam (81.6 ± 39.3 μg m− 3 ), Blantyre (82.9 ± 44.0) and Dhaka (62.3 ± 32.0) with deaths per 100,000 of the car commuting population per year of 2.46 (2.28–2.63), 1.11 (0.97–1.26) and 1.10 (1.05–1.15), respectively. However, the modest health burden of 0.07 (0.06–0.08), 0.10 (0.09–0.12) and 0.02 (0.02–0.03) deaths per 100,000 of the car commuting population per year were estimated for Medellin (23 ± 13.7 μg m− 3 ), Sa˜o Paulo (25.6 ± 11.7) and Sulaymaniyah (22.4 ± 15.0), respectively. Lower GDP was found to be associated with higher economic losses due to health burdens caused by air pollution in most cities, indicating a socioeconomic discrepancy. This assessment of health and socioeconomic parameters associated with in-car PM2.5 exposure highlights the importance of imple menting plausible solutions to make a positive impact on peoples’ lives in these cities en_US
dc.language.iso en en_US
dc.publisher Elsevier en_US
dc.relation.ispartofseries Elservier;,155,p.106688
dc.title Potential health risks due to in-car aerosol exposure across ten global cities en_US
dc.type Article en_US


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