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Socio-Economic Class and Exposure to NO2 Air Pollution in the Netherlands

Panis, Luc Int*†; Beckx, Carolien*; Wets, Geert

doi: 10.1097/01.ede.0000362234.56425.2c
Abstracts: ISEE 21st Annual Conference, Dublin, Ireland, August 25–29, 2009: Oral Presentations

*VITO, Mol, Flanders, Belgium; and †University if Hasselt, Hasselt, Flanders, Belgium.

Abstracts published in Epidemiology have been reviewed by the organizations of Epidemiology. Affliate Societies at whose meetings the abstracts have been accepted for presentation. These abstracts have not undergone review by the Editorial Board of Epidemiology.


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Background and Objective:

Many studies on air pollution ignore the spatial and temporal variation in population density. Newly developed activity-based transport models have the ability to retain demographic and socio-economic data about the people making trips and performing activities in different locations throughout the day. In this way exposure analysis can be disaggregated by subgroups in the population.

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The activity-based model Albatross was used to model activities and trips for all individuals in The Netherlands for 4000 population zones. Air quality was modeled with AURORA, a 3-dimensional Eulerian model, at a resolution of 3 × 3 km. Resulting hourly concentration data were combined with hourly population data derived from the activity-based model to provide detailed dynamic exposure assessments. We focus on specific differences in NO2 exposure due to different time-activity patterns in different income groups.

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People belonging to the lowest socio-economic group (income <average) appear to be exposed to slightly higher concentrations of NO2 throughout the day compared to the highest socio-economic group (income more than double of average), but there is a large variation within the day. Differences of up to 3% in the early morning are statistically significant. This effect is caused by concentration differences between the residential areas of both groups. The opposite effect was found during the morning rush hour. People belonging to the highest income group have a higher exposure at that time, because they are more likely to be driving to work, exposing themselves to higher concentrations in traffic. This offsets most of the difference between both groups and hence the overall (24h) difference between both socio-economic groups is small (0.84%) and not significant.

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Low income groups are more likely to suffer higher residential exposure to traffic related air pollution, however this effect is offset by lower exposure during morning trips.

© 2009 Lippincott Williams & Wilkins, Inc.