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Estimation of daily PM10 concentrations in Italy (2006-2012) using finely resolved satellite data, land use variables and meteorology

Stafoggia, Massimo and Schwartz, Joel and Badaloni, Chiara and Bellander, Tom and Alessandrini, Ester and Cattani, Giorgio and De' Donato, Francesca and Gaeta, Alessandra and Leone, Gianluca and Lyapustin, Alexei and Sorek-Hamer, Meytar and de Hoogh, Kees and Di, Qian and Forastiere, Francesco and Kloog, Itai. (2017) Estimation of daily PM10 concentrations in Italy (2006-2012) using finely resolved satellite data, land use variables and meteorology. Environment international, 99. pp. 234-244.

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Official URL: http://edoc.unibas.ch/54443/

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Abstract

Health effects of air pollution, especially particulate matter (PM), have been widely investigated. However, most of the studies rely on few monitors located in urban areas for short-term assessments, or land use/dispersion modelling for long-term evaluations, again mostly in cities. Recently, the availability of finely resolved satellite data provides an opportunity to estimate daily concentrations of air pollutants over wide spatio-temporal domains. Italy lacks a robust and validated high resolution spatio-temporally resolved model of particulate matter. The complex topography and the air mixture from both natural and anthropogenic sources are great challenges difficult to be addressed. We combined finely resolved data on Aerosol Optical Depth (AOD) from the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm, ground-level PM10 measurements, land-use variables and meteorological parameters into a four-stage mixed model framework to derive estimates of daily PM10 concentrations at 1-km2 grid over Italy, for the years 2006-2012. We checked performance of our models by applying 10-fold cross-validation (CV) for each year. Our models displayed good fitting, with mean CV-R2=0.65 and little bias (average slope of predicted VS observed PM10=0.99). Out-of-sample predictions were more accurate in Northern Italy (Po valley) and large conurbations (e.g. Rome), for background monitoring stations, and in the winter season. Resulting concentration maps showed highest average PM10 levels in specific areas (Po river valley, main industrial and metropolitan areas) with decreasing trends over time. Our daily predictions of PM10 concentrations across the whole Italy will allow, for the first time, estimation of long-term and short-term effects of air pollution nationwide, even in areas lacking monitoring data.
Faculties and Departments:09 Associated Institutions > Swiss Tropical and Public Health Institute (Swiss TPH)
09 Associated Institutions > Swiss Tropical and Public Health Institute (Swiss TPH) > Department of Epidemiology and Public Health (EPH) > Environmental Exposures and Health > Physical Hazards and Health (Röösli)
UniBasel Contributors:de Hoogh, Kees
Item Type:Article, refereed
Article Subtype:Research Article
Publisher:Elsevier
ISSN:0160-4120
Note:Publication type according to Uni Basel Research Database: Journal article
Identification Number:
Last Modified:12 Sep 2018 14:05
Deposited On:25 Apr 2017 07:18

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