Data di Pubblicazione:
2019
Citazione:
Is a land use regression model capable of predicting the cleanest route to school? / L. Boniardi, E. Dons, L. Campo, M. Van Poppel, L. Int Panis, S. Fustinoni. - In: ENVIRONMENTS. - ISSN 2076-3298. - 6:8(2019 Jul 30), pp. 90.1-90.12.
Abstract:
Land Use Regression (LUR) modeling is a widely used technique to model the spatial variability of air pollutants in epidemiology. In this study, we explore whether a LUR model can predict home-to-school commuting exposure to black carbon (BC). During January and February 2019, 43 children walking to school were involved in a personal monitoring campaign measuring exposure to BC and tracking their home-to-school routes. At the same time, a previously developed LUR model for the study area was applied to estimate BC exposure on points along the route. Personal BC exposure varied widely with mean ± SD of 9003 ± 4864 ng/m3. The comparison between the two methods showed good agreement (Pearson’s r = 0.74, Lin’s Concordance Correlation Coefficient = 0.6), suggesting that LUR estimates are capable of catching differences among routes and predicting the cleanest route. However, the model tends to underestimate absolute concentrations by 29% on average. A LUR model can be useful in predicting personal exposure and can help urban planners in Milan to build a healthier city for schoolchildren by promoting less polluted home-to-school routes.
Tipologia IRIS:
01 - Articolo su periodico
Keywords:
air pollution; black carbon (BC); land use regression (LUR); active mobility; traffic pollution; schoolchildren; school streets
Elenco autori:
L. Boniardi, E. Dons, L. Campo, M. Van Poppel, L. Int Panis, S. Fustinoni
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