Estimated long-term outdoor air pollution concentrations in a cohort study

被引:99
作者
Beelen, Rob
Hoek, Gerard
Fischer, Paul
van den Brandt, Piet A.
Brunekreef, Bert
机构
[1] Univ Utrecht, Inst Risk Assessment Sci, Div Environm Epidemiol, NL-3508 TD Utrecht, Netherlands
[2] Natl Inst Publ Hlth & Environm, Ctr Environm Hlth Res, NL-3720 BA Bilthoven, Netherlands
[3] Maastricht Univ, Dept Epidemiol, NL-6200 MD Maastricht, Netherlands
[4] Univ Utrecht, Med Ctr, Julius Ctr Hlth Sci & Primary Care, NL-3508 GA Utrecht, Netherlands
关键词
long term; exposure; air pollution; geographic information system; traffic; cohort;
D O I
10.1016/j.atmosenv.2006.10.020
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Several recent studies associated long-term exposure to air pollution with increased mortality. An ongoing cohort study, the Netherlands Cohort Study on Diet and Cancer (NLCS), was used to study the association between long-term exposure to traffic-related air pollution and mortality. Following on a previous exposure assessment study in the NLCS, we improved the exposure assessment methods. Long-term exposure to nitrogen dioxide (NO2) nitrogen oxide (NO), black smoke (BS), and sulphur dioxide (SO2) was estimated. Exposure at each home address (N = 21868) was considered as a function of a regional, an urban and a local component. The regional component was estimated using inverse distance weighed interpolation of measurement data from regional background sites in a national monitoring network. Regression models with urban concentrations as dependent variables, and number of inhabitants in different buffers and land use variables, derived with a Geographic Information System (GIS), as predictor variables were used to estimate the urban component. The local component was assessed using a GIS and a digital road network with linked traffic intensities. Traffic intensity on the nearest road and on the nearest major road, and the sum of traffic intensity in a buffer of 100m around each home address were assessed. Further. a quantitative estimate of the local component was estimated. The regression models to estimate the urban component explained 67%, 46%, 49% and 35% of the variances of NO2, NO, BS. and SO2 concentrations, respectively. Overall regression models which incorporated the regional, urban and local component explained 84%, 44%. 59% and 56% of the variability in concentrations for NO2, NO, BS and SO2, respectively. We were able to develop an exposure assessment model using GIS methods and traffic intensities that explained a large part of the variations in outdoor air pollution concentrations. (c) 2006 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1343 / 1358
页数:16
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