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Comparison of Land-Use Regression Modeling with Dispersion and Chemistry Transport Modeling to Assign Air Pollution Concentrations within the Ruhr Area

Authors :
Frauke Hennig
Dorothea Sugiri
Lilian Tzivian
Kateryna Fuks
Susanne Moebus
Karl-Heinz Jöckel
Danielle Vienneau
Thomas A.J. Kuhlbusch
Kees de Hoogh
Michael Memmesheimer
Hermann Jakobs
Ulrich Quass
Barbara Hoffmann
Source :
Atmosphere, Vol 7, Iss 3, p 48 (2016)
Publication Year :
2016
Publisher :
MDPI AG, 2016.

Abstract

Two commonly used models to assess air pollution concentration for investigating health effects of air pollution in epidemiological studies are Land Use Regression (LUR) models and Dispersion and Chemistry Transport Models (DCTM). Both modeling approaches have been applied in the Ruhr area, Germany, a location where multiple cohort studies are being conducted. Application of these different modelling approaches leads to differences in exposure estimation and interpretation due to the specific characteristics of each model. We aimed to compare both model approaches by means of their respective aims, modeling characteristics, validation, temporal and spatial resolution, and agreement of residential exposure estimation, referring to the air pollutants PM2.5, PM10, and NO2. Residential exposure referred to air pollution exposure at residences of participants of the Heinz Nixdorf Recall Study, located in the Ruhr area. The point-specific ESCAPE (European Study of Cohorts on Air Pollution Effects)-LUR aims to temporally estimate stable long-term exposure to local, mostly traffic-related air pollution with respect to very small-scale spatial variations (≤100 m). In contrast, the EURAD (European Air Pollution Dispersion)-CTM aims to estimate a time-varying average air pollutant concentration in a small area (i.e., 1 km2), taking into account a range of major sources, e.g., traffic, industry, meteorological conditions, and transport. Overall agreement between EURAD-CTM and ESCAPE-LUR was weak to moderate on a residential basis. Restricting EURAD-CTM to sources of local traffic only, respective agreement was good. The possibility of combining the strengths of both applications will be the next step to enhance exposure assessment.

Details

Language :
English
ISSN :
20734433
Volume :
7
Issue :
3
Database :
Directory of Open Access Journals
Journal :
Atmosphere
Publication Type :
Academic Journal
Accession number :
edsdoj.8e8d6a2307514964bfa5ef39180f1521
Document Type :
article
Full Text :
https://doi.org/10.3390/atmos7030048