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Integrating Modes of Transport in a Dynamic Modelling Approach to Evaluate Population Exposure to Ambient NO(2) and PM(2.5) Pollution in Urban Areas

To evaluate the effectiveness of alternative policies and measures to reduce air pollution effects on urban citizen’s health, population exposure assessments are needed. Due to road traffic emissions being a major source of emissions and exposure in European cities, it is necessary to account for di...

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Autores principales: Ramacher, Martin Otto Paul, Karl, Matthias
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7142857/
https://www.ncbi.nlm.nih.gov/pubmed/32235712
http://dx.doi.org/10.3390/ijerph17062099
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author Ramacher, Martin Otto Paul
Karl, Matthias
author_facet Ramacher, Martin Otto Paul
Karl, Matthias
author_sort Ramacher, Martin Otto Paul
collection PubMed
description To evaluate the effectiveness of alternative policies and measures to reduce air pollution effects on urban citizen’s health, population exposure assessments are needed. Due to road traffic emissions being a major source of emissions and exposure in European cities, it is necessary to account for differentiated transport environments in population dynamics for exposure studies. In this study, we applied a modelling system to evaluate population exposure in the urban area of Hamburg in 2016. The modeling system consists of an urban-scale chemistry transport model to account for ambient air pollutant concentrations and a dynamic time-microenvironment-activity (TMA) approach, which accounts for population dynamics in different environments as well as for infiltration of outdoor to indoor air pollution. We integrated different modes of transport in the TMA approach to improve population exposure assessments in transport environments. The newly developed approach reports 12% more total exposure to NO(2) and 19% more to PM(2.5) compared with exposure estimates based on residential addresses. During the time people spend in different transport environments, the in-car environment contributes with 40% and 33% to the annual sum of exposure to NO(2) and PM(2.5), in the walking environment with 26% and 30%, in the cycling environment with 15% and 17% and other environments (buses, subway, suburban, and regional trains) with less than 10% respectively. The relative contribution of road traffic emissions to population exposure is highest in the in-car environment (57% for NO(2) and 15% for PM(2.5)). Results for population-weighted exposure revealed exposure to PM(2.5) concentrations above the WHO AQG limit value in the cycling environment. Uncertainties for the exposure contributions arising from emissions and infiltration from outdoor to indoor pollutant concentrations range from −12% to +7% for NO(2) and PM(2.5). The developed “dynamic transport approach” is integrated in a computationally efficient exposure model, which is generally applicable in European urban areas. The presented methodology is promoted for use in urban mobility planning, e.g., to investigate on policy-driven changes in modal split and their combined effect on emissions, population activity and population exposure.
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spelling pubmed-71428572020-04-14 Integrating Modes of Transport in a Dynamic Modelling Approach to Evaluate Population Exposure to Ambient NO(2) and PM(2.5) Pollution in Urban Areas Ramacher, Martin Otto Paul Karl, Matthias Int J Environ Res Public Health Article To evaluate the effectiveness of alternative policies and measures to reduce air pollution effects on urban citizen’s health, population exposure assessments are needed. Due to road traffic emissions being a major source of emissions and exposure in European cities, it is necessary to account for differentiated transport environments in population dynamics for exposure studies. In this study, we applied a modelling system to evaluate population exposure in the urban area of Hamburg in 2016. The modeling system consists of an urban-scale chemistry transport model to account for ambient air pollutant concentrations and a dynamic time-microenvironment-activity (TMA) approach, which accounts for population dynamics in different environments as well as for infiltration of outdoor to indoor air pollution. We integrated different modes of transport in the TMA approach to improve population exposure assessments in transport environments. The newly developed approach reports 12% more total exposure to NO(2) and 19% more to PM(2.5) compared with exposure estimates based on residential addresses. During the time people spend in different transport environments, the in-car environment contributes with 40% and 33% to the annual sum of exposure to NO(2) and PM(2.5), in the walking environment with 26% and 30%, in the cycling environment with 15% and 17% and other environments (buses, subway, suburban, and regional trains) with less than 10% respectively. The relative contribution of road traffic emissions to population exposure is highest in the in-car environment (57% for NO(2) and 15% for PM(2.5)). Results for population-weighted exposure revealed exposure to PM(2.5) concentrations above the WHO AQG limit value in the cycling environment. Uncertainties for the exposure contributions arising from emissions and infiltration from outdoor to indoor pollutant concentrations range from −12% to +7% for NO(2) and PM(2.5). The developed “dynamic transport approach” is integrated in a computationally efficient exposure model, which is generally applicable in European urban areas. The presented methodology is promoted for use in urban mobility planning, e.g., to investigate on policy-driven changes in modal split and their combined effect on emissions, population activity and population exposure. MDPI 2020-03-22 2020-03 /pmc/articles/PMC7142857/ /pubmed/32235712 http://dx.doi.org/10.3390/ijerph17062099 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Ramacher, Martin Otto Paul
Karl, Matthias
Integrating Modes of Transport in a Dynamic Modelling Approach to Evaluate Population Exposure to Ambient NO(2) and PM(2.5) Pollution in Urban Areas
title Integrating Modes of Transport in a Dynamic Modelling Approach to Evaluate Population Exposure to Ambient NO(2) and PM(2.5) Pollution in Urban Areas
title_full Integrating Modes of Transport in a Dynamic Modelling Approach to Evaluate Population Exposure to Ambient NO(2) and PM(2.5) Pollution in Urban Areas
title_fullStr Integrating Modes of Transport in a Dynamic Modelling Approach to Evaluate Population Exposure to Ambient NO(2) and PM(2.5) Pollution in Urban Areas
title_full_unstemmed Integrating Modes of Transport in a Dynamic Modelling Approach to Evaluate Population Exposure to Ambient NO(2) and PM(2.5) Pollution in Urban Areas
title_short Integrating Modes of Transport in a Dynamic Modelling Approach to Evaluate Population Exposure to Ambient NO(2) and PM(2.5) Pollution in Urban Areas
title_sort integrating modes of transport in a dynamic modelling approach to evaluate population exposure to ambient no(2) and pm(2.5) pollution in urban areas
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7142857/
https://www.ncbi.nlm.nih.gov/pubmed/32235712
http://dx.doi.org/10.3390/ijerph17062099
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