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Jin MY, Gallagher J, Li XB, Lu KF, Peng ZR, He HD. Characterizing the distribution pattern of traffic-related air pollutants in near-road neighborhoods. ENVIRONMENTAL MONITORING AND ASSESSMENT 2024; 196:767. [PMID: 39073498 DOI: 10.1007/s10661-024-12917-3] [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: 02/03/2024] [Accepted: 07/11/2024] [Indexed: 07/30/2024]
Abstract
In near-road neighborhoods, residents are more frequently exposed to traffic-related air pollution (TRAP), and they are increasingly aware of pollution levels. Given this consideration, this study adopted portable air pollutant sensors to conduct a mobile monitoring campaign in two near-road neighborhoods, one in an urban area and one in a suburban area of Shanghai, China. The campaign characterized spatiotemporal distributions of fine particulate matter (PM2.5) and black carbon (BC) to help identify appropriate mitigation measures in these near-road micro-environments. The study identified higher mean TRAP concentrations (up to 4.7-fold and 1.7-fold higher for PM2.5 and BC, respectively), lower spatial variability, and a stronger inter-pollutant correlation in winter compared to summer. The temporal variations of TRAP between peak hour and off-peak hour were also investigated. It was identified that district-level PM2.5 increments occurred from off-peak to peak hours, with BC concentrations attributed more to traffic emissions. In addition, the spatiotemporal distribution of TRAP inside neighborhoods revealed that PM2.5 concentrations presented great temporal variability but almost remained invariant in space, while the BC concentrations showed notable spatiotemporal variability. These findings provide valuable insights into the unique spatiotemporal distributions of TRAP in different near-road neighborhoods, highlighting the important role of hyperlocal monitoring in urban micro-environments to support tailored designing and implementing appropriate mitigation measures.
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Affiliation(s)
- Meng-Yi Jin
- Center for Intelligent Transportation Systems and Unmanned Aerial Systems Applications Research, School of Naval Architecture, Ocean and Civil Engineering, State Key Laboratory of Ocean Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
- Department of Civil, Structural & Environmental Engineering, Trinity College Dublin, The University of Dublin, Dublin, D02 PN40, Ireland
| | - John Gallagher
- Department of Civil, Structural & Environmental Engineering, Trinity College Dublin, The University of Dublin, Dublin, D02 PN40, Ireland
| | - Xiao-Bing Li
- Institute for Environmental and Climate Research, Jinan University, Guangzhou, 510632, China
| | - Kai-Fa Lu
- iAdapt: International Center for Adaptation Planning and Design, College of Design, Construction and Planning, University of Florida, Gainesville, FL, 32611-5706, USA
| | - Zhong-Ren Peng
- iAdapt: International Center for Adaptation Planning and Design, College of Design, Construction and Planning, University of Florida, Gainesville, FL, 32611-5706, USA.
- Healthy Building Research Center, Ajman University, Ajman, United Arab Emirates.
| | - Hong-Di He
- Center for Intelligent Transportation Systems and Unmanned Aerial Systems Applications Research, School of Naval Architecture, Ocean and Civil Engineering, State Key Laboratory of Ocean Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China.
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Ouma YO, Keitsile A, Lottering L, Nkwae B, Odirile P. Spatiotemporal empirical analysis of particulate matter PM 2.5 pollution and air quality index (AQI) trends in Africa using MERRA-2 reanalysis datasets (1980-2021). THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 912:169027. [PMID: 38056664 DOI: 10.1016/j.scitotenv.2023.169027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Revised: 11/27/2023] [Accepted: 11/29/2023] [Indexed: 12/08/2023]
Abstract
In this study, the spatial-temporal trends of PM2.5 pollution were analyzed for subregions in Africa and the entire continent from 1980 to 2021. The distributions and trends of PM2.5 were derived from the monthly concentrations of the aerosol species from MERRA-2 reanalysis datasets comprising of sulphates (SO4), organic carbon (OC), black carbon (BC), Dust2.5 and Sea Salt (SS2.5). The resulting PM2.5 trends were compared with the climate factors, socio-economic indicators, and terrain characteristics. Using the Mann-Kendall (M-K) test, the continent and its subregions showed positive trends in PM2.5 concentrations, except for western and central Africa which exhibited marginal negative trends. The M-K trends also determined Dust2.5 as the dominant contributing aerosol factor responsible for the high PM2.5 concentrations in the northern, western and central regions of Africa, while SO4 and OC were respectively the most significant contributors to PM2.5 in the eastern and southern Africa regions. For the climate factors, the PM2.5 trends were determined to be positively correlated with the wind speed trends, while precipitation and temperature trends exhibited low and sometimes negative correlations with PM2.5. Socio-economically, highly populated, and bare/sparse vegetated areas showed higher PM2.5 concentrations, while vegetated areas tended to have lower PM2.5 concentrations. Topographically, low laying regions were observed to retain the deposited PM2.5 especially in the northern and western regions of Africa. The Air Quality Index (AQI) results showed that 94 % of the continent had an average PM2.5 of 12-35 μg/m3 hence classified as "Moderate" AQI, and the rest of the continent's PM2.5 levels was between 35 and 55 μg/m3 implying AQI classification of "Unhealthy for Sensitive People". Northern and western Africa regions had the highest AQI, while southern Africa had the lowest AQI. The approach and findings in this study can be used to complement the evaluation and management of air quality in Africa.
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Affiliation(s)
- Yashon O Ouma
- Department of Civil Engineering, University of Botswana, Private Bag UB 0061, Gaborone, Botswana.
| | - Amantle Keitsile
- Department of Civil Engineering, University of Botswana, Private Bag UB 0061, Gaborone, Botswana
| | - Lone Lottering
- Department of Civil Engineering, University of Botswana, Private Bag UB 0061, Gaborone, Botswana
| | - Boipuso Nkwae
- Department of Civil Engineering, University of Botswana, Private Bag UB 0061, Gaborone, Botswana
| | - Phillimon Odirile
- Department of Civil Engineering, University of Botswana, Private Bag UB 0061, Gaborone, Botswana
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