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Statistical Modeling of the Early-Stage Impact of a New Traffic Policy in Milan, Italy

Most urban areas of the Po basin in the North of Italy are persistently affected by poor air quality and difficulty in disposing of airborne pollutants. In this context, the municipality of Milan started a multi-year progressive policy based on an extended limited traffic zone (Area B). Starting on...

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Autores principales: Maranzano, Paolo, Fassò, Alessandro, Pelagatti, Matteo, Mudelsee, Manfred
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7037004/
https://www.ncbi.nlm.nih.gov/pubmed/32046370
http://dx.doi.org/10.3390/ijerph17031088
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author Maranzano, Paolo
Fassò, Alessandro
Pelagatti, Matteo
Mudelsee, Manfred
author_facet Maranzano, Paolo
Fassò, Alessandro
Pelagatti, Matteo
Mudelsee, Manfred
author_sort Maranzano, Paolo
collection PubMed
description Most urban areas of the Po basin in the North of Italy are persistently affected by poor air quality and difficulty in disposing of airborne pollutants. In this context, the municipality of Milan started a multi-year progressive policy based on an extended limited traffic zone (Area B). Starting on 25 February 2019, the first phase partially restricted the circulation of some classes of highly polluting vehicles on the territory, in particular, Euro 0 petrol vehicles and Euro 0 to 3 diesel vehicles, excluding public transport. This is the early-stage of a long term policy that will restrict access to an increasing number of vehicles. The goal of this paper is to evaluate the early-stage impact of this policy on two specific vehicle-generated pollutants: total nitrogen oxides (NO [Formula: see text]) and nitrogen dioxide (NO [Formula: see text]), which are gathered by Lombardy Regional Agency for Environmental Protection (ARPA Lombardia). We use a statistical model for time series intervention analysis based on unobservable components. We use data from 2014 to 2018 for pre-policy model selection and the relatively short period up to September 2019 for early-stage policy assessment. We include weather conditions, socio-economic factors, and a counter-factual, given by the concentration of the same pollutant in other important neighbouring cities. Although the average concentrations reduced after the policy introduction, this paper argues that this could be due to other factors. Considering that the short time window may be not long enough for social adaptation to the new rules, our model does not provide statistical evidence of a positive policy effect for NO [Formula: see text] and NO [Formula: see text]. Instead, in one of the most central monitoring stations, a significant negative impact is found.
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spelling pubmed-70370042020-03-11 Statistical Modeling of the Early-Stage Impact of a New Traffic Policy in Milan, Italy Maranzano, Paolo Fassò, Alessandro Pelagatti, Matteo Mudelsee, Manfred Int J Environ Res Public Health Article Most urban areas of the Po basin in the North of Italy are persistently affected by poor air quality and difficulty in disposing of airborne pollutants. In this context, the municipality of Milan started a multi-year progressive policy based on an extended limited traffic zone (Area B). Starting on 25 February 2019, the first phase partially restricted the circulation of some classes of highly polluting vehicles on the territory, in particular, Euro 0 petrol vehicles and Euro 0 to 3 diesel vehicles, excluding public transport. This is the early-stage of a long term policy that will restrict access to an increasing number of vehicles. The goal of this paper is to evaluate the early-stage impact of this policy on two specific vehicle-generated pollutants: total nitrogen oxides (NO [Formula: see text]) and nitrogen dioxide (NO [Formula: see text]), which are gathered by Lombardy Regional Agency for Environmental Protection (ARPA Lombardia). We use a statistical model for time series intervention analysis based on unobservable components. We use data from 2014 to 2018 for pre-policy model selection and the relatively short period up to September 2019 for early-stage policy assessment. We include weather conditions, socio-economic factors, and a counter-factual, given by the concentration of the same pollutant in other important neighbouring cities. Although the average concentrations reduced after the policy introduction, this paper argues that this could be due to other factors. Considering that the short time window may be not long enough for social adaptation to the new rules, our model does not provide statistical evidence of a positive policy effect for NO [Formula: see text] and NO [Formula: see text]. Instead, in one of the most central monitoring stations, a significant negative impact is found. MDPI 2020-02-08 2020-02 /pmc/articles/PMC7037004/ /pubmed/32046370 http://dx.doi.org/10.3390/ijerph17031088 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Maranzano, Paolo
Fassò, Alessandro
Pelagatti, Matteo
Mudelsee, Manfred
Statistical Modeling of the Early-Stage Impact of a New Traffic Policy in Milan, Italy
title Statistical Modeling of the Early-Stage Impact of a New Traffic Policy in Milan, Italy
title_full Statistical Modeling of the Early-Stage Impact of a New Traffic Policy in Milan, Italy
title_fullStr Statistical Modeling of the Early-Stage Impact of a New Traffic Policy in Milan, Italy
title_full_unstemmed Statistical Modeling of the Early-Stage Impact of a New Traffic Policy in Milan, Italy
title_short Statistical Modeling of the Early-Stage Impact of a New Traffic Policy in Milan, Italy
title_sort statistical modeling of the early-stage impact of a new traffic policy in milan, italy
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7037004/
https://www.ncbi.nlm.nih.gov/pubmed/32046370
http://dx.doi.org/10.3390/ijerph17031088
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