Health impact assessment of air pollution using a dynamic exposure profile: Implications for exposure and health impact estimates

Dhondt, Stijn; Beckx, Carolien; Degraeuwe, Bart; Lefebvre, Wouter; Kochan, Bruno; Bellemans, Tom; Panis, Luc Int; Macharis, Cathy; Putman, Koen

doi:10.1016/j.eiar.2012.03.004

Cited by 71 publications

(50 citation statements)

References 65 publications

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“…Several studies have compared population exposure estimates based on static populations with spatially and temporally dynamic populations, emphasizing the need to account for population dynamics to reduce bias in population exposure estimates [21,[23][24][25][26][36][37][38][39]45,46,[63][64][65][66][67][68][69][70][71][72][73][74][75][76]. Thus, appropriate population exposure estimates in urban areas require the consideration of individual's activities, which have a large degree of spatial and temporal dynamics.…”

Section: Dynamic Population Modelingmentioning

confidence: 99%

Integrating Modes of Transport in a Dynamic Modelling Approach to Evaluate Population Exposure to Ambient NO2 and PM2.5 Pollution in Urban Areas

Ramacher

Karl

2020

IJERPH

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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 NO2 and 19% more to PM2.5 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 NO2 and PM2.5, 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 NO2 and 15% for PM2.5). Results for population-weighted exposure revealed exposure to PM2.5 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 NO2 and PM2.5. 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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Section: Dynamic Population Modelingmentioning

confidence: 99%

Integrating Modes of Transport in a Dynamic Modelling Approach to Evaluate Population Exposure to Ambient NO2 and PM2.5 Pollution in Urban Areas

Ramacher

Karl

2020

IJERPH

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“…Since that day, billions of vehicles have been sold all around the world, with heavy results on human health [2], [3] and corrosive effects on monuments and historical masterpieces [4, [5]. In a city like Firenze, Italy, UNESCO site since 1982 with a high population density, it is mandatory to reduce pollutant in order to preserve people and monuments' health.…”

Section: Introductionmentioning

confidence: 99%

Introducing wireless charging facilities for electric vehicles: the case study of Firenze

Campatelli

Benesperi

Barbieri

et al. 2014

2014 IEEE International Electric Vehicle Conference (IEVC)

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In a World with an increasing population and related mobility needs, a traditional internal combustion engine based mobility paradigm cannot be considered the only possible solution. This is particularly true for cities full of masterpieces and historical buildings as Firenze, used as case study. Specifically it combines very high mobility needs for tourists and inhabitants with a very high sensitivity to air pollution problems for its artistic heritage. However, the autonomy of the available vehicles is still an issue to be exceeded for a large electric mobility implementation [1]. Within this paper, a structured method to implement static and dynamic wireless charging systems in urban mobility will be presented. The parametric nature of the model is a fundamental feature of the methodology, because makes it easy to be used as a framework for feasibility analysis: the developed analysis could be easily applied also to other cities because the required input are quite easy to be obtained.

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“…Air pollution is elevated in urban areas, which is mainly due to emissions from traffic (fossil fuel-driven vehicles and ships), industry, and residential heating [16,20]. Therefore, high concentrations can be expected near big roads, as well as harbor and industry areas [21]. Pollutants range from larger particles such as particulate matter (PM) to gases such as ozone, NO x , CO, etc.…”

Section: Modeling Environmentmentioning

confidence: 99%

“…A dynamic individual exposure model that is able to evolve as the individual moves would lay the basis for an assessment of the exposure level by providing reliable and standardized information on the exposed objects across a vast range of human activities [21]. In this paper, we conducted a thorough literature review on different types of exposure models, their characters and advantages, and both their spatial and socioeconomic dimensions.…”

Section: Dynamics Of Environment Exposurementioning

confidence: 99%

An Agent-Based Modeling Framework for Simulating Human Exposure to Environmental Stresses in Urban Areas

et al. 2018

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Several approaches have been used to assess potential human exposure to environmental stresses and achieve optimal results under various conditions, such as for example, for different scales, groups of people, or points in time. A thorough literature review in this paper identifies the research gap regarding modeling approaches for assessing human exposure to environment stressors, and it indicates that microsimulation tools are becoming increasingly important in human exposure assessments of urban environments, in which each person is simulated individually and continuously. The paper further describes an agent-based model (ABM) framework that can dynamically simulate human exposure levels, along with their daily activities, in urban areas that are characterized by environmental stresses such as air pollution and heat stress. Within the framework, decision-making processes can be included for each individual based on rule-based behavior in order to achieve goals under changing environmental conditions. The ideas described in this paper are implemented in a free and open source NetLogo platform. A basic modeling scenario of the ABM framework in Hamburg, Germany, demonstrates its utility in various urban environments and individual activity patterns, as well as its portability to other models, programs, and frameworks. The prototype model can potentially be extended to support environmental incidence management through exploring the daily routines of different groups of citizens, and comparing the effectiveness of different strategies. Further research is needed to fully develop an operational version of the model.

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Health impact assessment of air pollution using a dynamic exposure profile: Implications for exposure and health impact estimates

Cited by 71 publications

References 65 publications

Integrating Modes of Transport in a Dynamic Modelling Approach to Evaluate Population Exposure to Ambient NO2 and PM2.5 Pollution in Urban Areas

Integrating Modes of Transport in a Dynamic Modelling Approach to Evaluate Population Exposure to Ambient NO2 and PM2.5 Pollution in Urban Areas

Introducing wireless charging facilities for electric vehicles: the case study of Firenze

An Agent-Based Modeling Framework for Simulating Human Exposure to Environmental Stresses in Urban Areas

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