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Environ Int. 2014 Dec;73:382-92. doi: 10.1016/j.envint.2014.08.011. Epub 2014 Sep 16.

Comparing land use regression and dispersion modelling to assess residential exposure to ambient air pollution for epidemiological studies.

Author information

1
Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland; MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, Imperial College London, London, United Kingdom. Electronic address: c.dehoogh@unibas.ch.
2
MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, Imperial College London, London, United Kingdom.
3
Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland.
4
Netherlands Organization for Applied Research, Utrecht, The Netherlands.
5
Finnish Meteorological Institute, Helsinki, Finland.
6
Center for Research in Environmental Epidemiology (CREAL), Barcelona, Spain; IMIM (Hospital del Mar Research Institute), Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Spain.
7
Epidemiology Department, Lazio Regional Health Service, Rome, Italy.
8
Institute for Risk Assessment Sciences, Utrecht University, P.O. Box 80178, 3508 TD Utrecht, The Netherlands.
9
Environmental Protection Agency, Lazio Region, Italy.
10
Helmholtz Zentrum München, German Research Center for Environmental Health, Institutes of Epidemiology I and II, Neuherberg, Germany; University of Augsburg, Environmental Science Center, Augsburg, Germany.
11
Laboratory of Heat Transfer and Environmental Engineering, Aristotle University of Thessaloniki, Aristotle University, Thessaloniki, Greece.
12
Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland; Institute for Risk Assessment Sciences, Utrecht University, P.O. Box 80178, 3508 TD Utrecht, The Netherlands.
13
Department of Public Health and Clinical Medicine, Occupational and Environmental Medicine, Umeå University, Sweden.
14
IUF Leibniz Research Institute for Environmental Medicine, University of Düsseldorf, Düsseldorf, Germany.
15
Department of Hygiene, Epidemiology and Medical Statistics University of Athens, Medical School, Athens, Greece.
16
MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, Imperial College London, London, United Kingdom; Directorate of Public Health and Primary Care, Imperial College Healthcare NHS Trust, London, UK.
17
IUF Leibniz Research Institute for Environmental Medicine, University of Düsseldorf, Düsseldorf, Germany; Medical Faculty, Heinrich-Heine University of Düsseldorf, Düsseldorf, Germany.
18
Department of Applied Environmental Science, Stockholm University, Stockholm, Sweden.
19
Department of Hygiene, Epidemiology and Medical Statistics University of Athens, Medical School, Athens, Greece; Department of Primary Care & Public Health Sciences and Environmental Research Group, King's College London, United Kingdom.
20
Department of Environmental Health, National Institute for Health and Welfare (THL), Kuopio, Finland.
21
Rhenish Institute for Environmental Research (RIU), Köln, Germany.
22
Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.
23
Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland; IUF Leibniz Research Institute for Environmental Medicine, University of Düsseldorf, Düsseldorf, Germany.
24
Energy and Air quality Department, Barcelona Regional, Barcelona, Spain.
25
Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland; Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA, United States.
26
Institute for Risk Assessment Sciences, Utrecht University, P.O. Box 80178, 3508 TD Utrecht, The Netherlands; Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands.
27
Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden; Centre for Occupational and Environmental Medicine, Stockholm County Council, Stockholm, Sweden.

Abstract

BACKGROUND:

Land-use regression (LUR) and dispersion models (DM) are commonly used for estimating individual air pollution exposure in population studies. Few comparisons have however been made of the performance of these methods.

OBJECTIVES:

Within the European Study of Cohorts for Air Pollution Effects (ESCAPE) we explored the differences between LUR and DM estimates for NO2, PM10 and PM2.5.

METHODS:

The ESCAPE study developed LUR models for outdoor air pollution levels based on a harmonised monitoring campaign. In thirteen ESCAPE study areas we further applied dispersion models. We compared LUR and DM estimates at the residential addresses of participants in 13 cohorts for NO2; 7 for PM10 and 4 for PM2.5. Additionally, we compared the DM estimates with measured concentrations at the 20-40 ESCAPE monitoring sites in each area.

RESULTS:

The median Pearson R (range) correlation coefficients between LUR and DM estimates for the annual average concentrations of NO2, PM10 and PM2.5 were 0.75 (0.19-0.89), 0.39 (0.23-0.66) and 0.29 (0.22-0.81) for 112,971 (13 study areas), 69,591 (7) and 28,519 (4) addresses respectively. The median Pearson R correlation coefficients (range) between DM estimates and ESCAPE measurements were of 0.74 (0.09-0.86) for NO2; 0.58 (0.36-0.88) for PM10 and 0.58 (0.39-0.66) for PM2.5.

CONCLUSIONS:

LUR and dispersion model estimates correlated on average well for NO2 but only moderately for PM10 and PM2.5, with large variability across areas. DM predicted a moderate to large proportion of the measured variation for NO2 but less for PM10 and PM2.5.

KEYWORDS:

Air pollution; Cohort; Dispersion modelling; Exposure; Land use regression

PMID:
25233102
DOI:
10.1016/j.envint.2014.08.011
[Indexed for MEDLINE]

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