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

Paolo Maranzano, Alessandro Fassò, Matteo Pelagatti and Manfred Mudelsee
Additional contact information
Paolo Maranzano: Department of Statistics and Quantitative Methods (DISMEQ), University of Milano-Bicocca, 20126 Milano, Italy
Alessandro Fassò: Department of Management, Information and Production Engineering (DIGIP), University of Bergamo, 24044 Dalmine, Italy
Manfred Mudelsee: Climate Risk Analysis, 37581 Heckenbeck, Germany

IJERPH, 2020, vol. 17, issue 3, 1-22

Abstract: 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 x ) and nitrogen dioxide (NO 2 ), 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 x and NO 2 . Instead, in one of the most central monitoring stations, a significant negative impact is found.

Keywords: air pollution; oxides; traffic; state space; milan; area b; cross validation; policy intervention analysis; counter-factual; unobservable components (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1660-4601/17/3/1088/pdf (application/pdf)
https://www.mdpi.com/1660-4601/17/3/1088/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jijerp:v:17:y:2020:i:3:p:1088-:d:318308

Access Statistics for this article

IJERPH is currently edited by Ms. Jenna Liu

More articles in IJERPH from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().