Shen, Y; de Hoogh, K; Schmitz, O; Gulliver, J; Vienneau, D; Vermeulen, R; Hoek, G; Karssenberg, D
(2024)
Europe-wide high-spatial resolution air pollution models are improved by including traffic flow estimates on all roads.
ATMOSPHERIC ENVIRONMENT, 335.
p. 120719.
ISSN 1352-2310
https://doi.org/10.1016/j.atmosenv.2024.120719
SGUL Authors: Gulliver, John
Abstract
Road traffic is an important source of noise and air pollution. Modelling of air pollution and noise therefore requires detailed information on annual average daily traffic (AADT) flows on all roads. Europe-wide estimates on traffic intensity are however not publicly available. This has hampered previous Europe-wide air pollution and noise modelling, used extensively in Europe-wide epidemiological studies of morbidity and mortality. We aim to estimate Europe-wide AADT and quantify potential improvements of previous Europe-wide air pollution models.
We built separate random forests (RF) models for different road types in OpenStreetMap (highway, primary, secondary and tertiary, and residential roads). We collected observations on annual average daily traffic (AADT) from six European countries. We evaluated our AADT models using 5-fold cross-validation (CV) and by comparison of our Europe-wide traffic flow estimates with national traffic model estimates for Switzerland and the Netherlands. We evaluated whether adding our estimated AADT as predictors for Europe-wide air pollution models trained by more than 2000 routine monitoring sites improved the performance of the models based upon major road length in different buffer sizes.
The 5-fold cross-validation result showed our estimates overall captured variations in AADT between road types (R2 = 0.82). Our result showed variability in AADT within and between road types, documenting the benefit of our model framework at a continental scale. Our AADT estimates modestly improved model performance of previous Europe-wide air pollution models for NO2, PM10, PM2.5, and O3, especially for NO2 (3% improvement of geographically-weighted regression model). Improvement of model performance was larger in urban areas (5% and 8% increases in R2 for NO2 and O3). Importantly, more detailed intra-city near-road variations were captured for traffic-related air pollution. The resulting AADT estimates of all roads across Europe will be useful for further improving air pollution modelling and facilitating harmonized road traffic noise modelling in Europe.
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