A Comparison of Different Approaches to Estimate Small-Scale Spatial Variation in Outdoor NO ₂ Concentrations

Abstract

BackgroundIn 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.ObjectiveIn 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.MethodsTwo 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 conclusionThe 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.

Assessing the Suitability of Multiple Dispersion and Land Use Regression Models for Urban Traffic-Related Ultrafine Particles

“…In previous studies of model performance, predictions of NO 2 and tracers (i.e., sulfur hexafluoride) have been within a factor of two of observations with reasonable agreement among models (e.g., CALINE4, AERMOD, R-LINE, QUIC, CAR, Urban, and regression). 31–39 We found that our tested models generally underestimated PNC relative to measurements, consistent with previous studies that reported underestimation of traffic-related air pollution by dispersion models for conditions of atmospheric instability, wind direction perpendicular to the highway, or low concentrations. 11,36,37,45 However, our results were different from studies that reported overestimation of traffic-related air pollution during stable or parallel wind conditions, and when concentrations were relatively high.…”

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

“…This is likely because the LUR model was developed for the whole of the Netherlands and lacking specific local information for the Rijnmond area. A study in Amsterdam (NL) by Dijkema et al (2011) compared NO 2 concentrations estimated by 2 LUR models (regional and city specific) against the Dutch CAR dispersion model. All models explained between 50 and 60% of the variance, although CAR overestimated at background and underestimated at traffic monitoring sites.…”

“…Chemical Transport Models have also been used to model short-and long-term exposure periods (Hennig et al, 2014). Few studies to date have conducted comparisons between LUR and DMs for their performance in estimating exposures (Beelen et al, 2010;Cyrys et al, 2005;Dijkema et al, 2011;Gulliver et al, 2011;Marshall et al, 2008;Sellier et al, 2014). These studies included different models, spatial resolution, pollutants and study areas, factors likely to have contributed to inconsistent findings within individual studies.…”

Predictors of intra-community variation in air quality

“…For example, Zhu et al (2002) showed that carbon monoxide, particle number, and black carbon were substantially higher near a busy interstate freeway in southern California, with levels dropping sharply within a few hundred meters from the roadway during daytime hours. Levels of NO 2 have also been shown to be highest near a busy road and declining gradually with increasing distance (Gilbert et al, 2003; Beckerman et al, 2008; Dijkema et al, 2010; Skene et al, 2010). Most studies of intra-community air quality have been based on extensive monitoring in a single city (Hoek et al, 2008) or on a few monitors in each of many cities (Hart et al, 2009).…”