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A comparison of different approaches to estimate small-scale spatial variation in outdoor NO₂ concentrations.

Dijkema MB, Gehring U, van Strien RT, van der Zee SC, Fischer P, Hoek G, Brunekreef B - Environ. Health Perspect. (2010)

Bottom Line: Predictions from both LUR models and the calculation of air pollution from road traffic (CAR) dispersion model were compared against NO₂ measurements obtained from Amsterdam.More complete traffic information contributed more to a better model fit than did detailed land-use data.Dispersion-model estimates for NO₂ concentrations were within the range of both LUR estimates.

View Article: PubMed Central - PubMed

Affiliation: Department of Environmental Health, Municipal Health Service Amsterdam (GGD), Amsterdam, The Netherlands. mdijkema@ggd.amsterdam.nl

ABSTRACT

Background: In epidemiological studies, small-scale spatial variation in air quality is estimated using land-use regression (LUR) and dispersion models. An important issue of exposure modeling is the predictive performance of the model at unmeasured locations.

Objective: In this study, we aimed to evaluate the performance of two LUR models (large area and city specific) and a dispersion model in estimating small-scale variations in nitrogen dioxide (NO₂) concentrations.

Methods: Two LUR models were developed based on independent NO₂ monitoring campaigns performed in Amsterdam and in a larger area including Amsterdam, the Netherlands, in 2006 and 2007, respectively. The measurement data of the other campaign were used to evaluate each model. Predictions from both LUR models and the calculation of air pollution from road traffic (CAR) dispersion model were compared against NO₂ measurements obtained from Amsterdam.

Results and conclusion: The large-area and the city-specific LUR models provided good predictions of NO₂ concentrations [percentage of explained variation (R²) = 87% and 72%, respectively]. The models explained less variability of the concentrations in the other sampling campaign, probably related to differences in site selection, and illustrated the need to select sampling sites representative of the locations to which the model will be applied. More complete traffic information contributed more to a better model fit than did detailed land-use data. Dispersion-model estimates for NO₂ concentrations were within the range of both LUR estimates.

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Related in: MedlinePlus

Evaluation of large-area and city-specific LUR models for measurements sites in Amsterdam, the Netherlands: predicted NO2 concentrations from one LUR-model versus observed concentrations at measurement sites that were used to develop the other LUR model. (A) Estimations by the large-area LUR, city-specific sites. (B) Estimations by the city-specific LUR, large-area sites. The dotted line indicates where observed equals predicted concentration.
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f1-ehp-119-670: Evaluation of large-area and city-specific LUR models for measurements sites in Amsterdam, the Netherlands: predicted NO2 concentrations from one LUR-model versus observed concentrations at measurement sites that were used to develop the other LUR model. (A) Estimations by the large-area LUR, city-specific sites. (B) Estimations by the city-specific LUR, large-area sites. The dotted line indicates where observed equals predicted concentration.

Mentions: Figure 1 shows plots of the observed NO2 concentrations at sites used to develop one LUR model and predicted concentrations from the other LUR model. Both LUR models performed less well in predicting NO2 concentrations at the sites that were used to develop the other model. Applying the large-area model to sites of the city-specific campaign (n = 62) (Figure 1A) resulted in an R2 of 48%, much lower than the R2 (72%) (Table 3) of the city-specific LUR for the sites of the city-specific campaign used to develop the model and the internal cross-validation R2. Applying the city-specific model to the Amsterdam sites of the large-area campaign resulted in an R2 of 57% (n = 13) (Figure 1B), much lower than the R2 of the large-area model for the Amsterdam sites of the large-area campaign (79%) [Supplemental Material, Figure 3 (doi:10.1289/ehp.0901818)] and the internal cross-validation R2.


A comparison of different approaches to estimate small-scale spatial variation in outdoor NO₂ concentrations.

Dijkema MB, Gehring U, van Strien RT, van der Zee SC, Fischer P, Hoek G, Brunekreef B - Environ. Health Perspect. (2010)

Evaluation of large-area and city-specific LUR models for measurements sites in Amsterdam, the Netherlands: predicted NO2 concentrations from one LUR-model versus observed concentrations at measurement sites that were used to develop the other LUR model. (A) Estimations by the large-area LUR, city-specific sites. (B) Estimations by the city-specific LUR, large-area sites. The dotted line indicates where observed equals predicted concentration.
© Copyright Policy - public-domain
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3094419&req=5

f1-ehp-119-670: Evaluation of large-area and city-specific LUR models for measurements sites in Amsterdam, the Netherlands: predicted NO2 concentrations from one LUR-model versus observed concentrations at measurement sites that were used to develop the other LUR model. (A) Estimations by the large-area LUR, city-specific sites. (B) Estimations by the city-specific LUR, large-area sites. The dotted line indicates where observed equals predicted concentration.
Mentions: Figure 1 shows plots of the observed NO2 concentrations at sites used to develop one LUR model and predicted concentrations from the other LUR model. Both LUR models performed less well in predicting NO2 concentrations at the sites that were used to develop the other model. Applying the large-area model to sites of the city-specific campaign (n = 62) (Figure 1A) resulted in an R2 of 48%, much lower than the R2 (72%) (Table 3) of the city-specific LUR for the sites of the city-specific campaign used to develop the model and the internal cross-validation R2. Applying the city-specific model to the Amsterdam sites of the large-area campaign resulted in an R2 of 57% (n = 13) (Figure 1B), much lower than the R2 of the large-area model for the Amsterdam sites of the large-area campaign (79%) [Supplemental Material, Figure 3 (doi:10.1289/ehp.0901818)] and the internal cross-validation R2.

Bottom Line: Predictions from both LUR models and the calculation of air pollution from road traffic (CAR) dispersion model were compared against NO₂ measurements obtained from Amsterdam.More complete traffic information contributed more to a better model fit than did detailed land-use data.Dispersion-model estimates for NO₂ concentrations were within the range of both LUR estimates.

View Article: PubMed Central - PubMed

Affiliation: Department of Environmental Health, Municipal Health Service Amsterdam (GGD), Amsterdam, The Netherlands. mdijkema@ggd.amsterdam.nl

ABSTRACT

Background: In epidemiological studies, small-scale spatial variation in air quality is estimated using land-use regression (LUR) and dispersion models. An important issue of exposure modeling is the predictive performance of the model at unmeasured locations.

Objective: In this study, we aimed to evaluate the performance of two LUR models (large area and city specific) and a dispersion model in estimating small-scale variations in nitrogen dioxide (NO₂) concentrations.

Methods: Two LUR models were developed based on independent NO₂ monitoring campaigns performed in Amsterdam and in a larger area including Amsterdam, the Netherlands, in 2006 and 2007, respectively. The measurement data of the other campaign were used to evaluate each model. Predictions from both LUR models and the calculation of air pollution from road traffic (CAR) dispersion model were compared against NO₂ measurements obtained from Amsterdam.

Results and conclusion: The large-area and the city-specific LUR models provided good predictions of NO₂ concentrations [percentage of explained variation (R²) = 87% and 72%, respectively]. The models explained less variability of the concentrations in the other sampling campaign, probably related to differences in site selection, and illustrated the need to select sampling sites representative of the locations to which the model will be applied. More complete traffic information contributed more to a better model fit than did detailed land-use data. Dispersion-model estimates for NO₂ concentrations were within the range of both LUR estimates.

Show MeSH
Related in: MedlinePlus