Street-scale dispersion modelling framework of road-traffic derived air pollution in Hanoi, Vietnam.

Autor: Ngo KQ; Cranfield Environment Centre, School of Water, Energy and Environment, Cranfield University, College Road, Cranfield, Bedfordshire, MK43 0AL, United Kingdom. Electronic address: khoi.lucas.ngo@cranfield.ac.uk., Hoang LA; Faculty of Environmental Sciences, University of Science, Vietnam National University, 334 Nguyen Trai, Thanh Xuan, Hanoi, Viet Nam., Ho BQ; Institute for Environment & Resources (IER), 142 to Hien Thanh., District 10, Ho Chi Minh City, Viet Nam., Harris NRP; Cranfield Environment Centre, School of Water, Energy and Environment, Cranfield University, College Road, Cranfield, Bedfordshire, MK43 0AL, United Kingdom., Drew GH; Cranfield Environment Centre, School of Water, Energy and Environment, Cranfield University, College Road, Cranfield, Bedfordshire, MK43 0AL, United Kingdom., Mead MI; MRC Centre for Environment and Health, Environmental Research Group, Imperial College London, United Kingdom.
Jazyk: angličtina
Zdroj: Environmental research [Environ Res] 2023 Sep 15; Vol. 233, pp. 116497. Date of Electronic Publication: 2023 Jun 24.
DOI: 10.1016/j.envres.2023.116497
Abstrakt: Traffic is an important source of air pollution in Vietnamese cities. The spatio-temporal variation of air pollution derived from traffic is poorly understood. Application of dispersion modelling can help but is hindered by the local scarcity of suitable input data. This study fills the data gap, by establishing a framework employing open-access global data to model emission from traffic activities in Hanoi. The outlined methodology explicitly defines road sources, calculates their emission, and employs background pollution profiles from Copernicus Atmospheric Monitoring Service (CAMS) to produce street-scale distribution maps for CO, PM 10 and PM 2.5 . Pollution hotspots are found near major traffic flows with the highest hourly average CO, PM 10 and PM 2.5 concentrations at 1206, 87.5 and 61.5 μgm -3 , respectively. The relationship between concentrations and properties of the road network is assessed. Motorcycles are the main emitters of the traffic sector. Emission from Heavy Good Vehicles dominate during the night, with contribution percentages increase as it gets further away from the city core. Modelled concentrations are underestimated mainly due to low vehicular emission factor. Adjusting emission factors according to vehicle quality in Vietnam greatly improves agreement. The presence of non-traffic emission sources contributes to the model underestimation. Results for comparisons of daily averaged PM values are broadly in agreement between models and observations; however, diurnal patters are skewed. This results partly from the uncertainties linked with background pollution levels from CAMS, and partly from non-traffic sources which are not accounted for here. Further work is needed to assess the use of CAMS's concentrations in Vietnam. Meteorological input contributes to the temporal disagreement between the model and observations. The impact is most noticeable with CO concentrations during morning traffic rush hours. This study recommends approaches to improve input for future model iterations and encourage applications of dispersion modelling studies in similar economic settings.
Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)
Databáze: MEDLINE
Externí odkaz: