Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Assessment of the Road Traffic Air Pollution in Urban Contexts: A Statistical Approach

Version 1 : Received: 29 October 2021 / Approved: 1 November 2021 / Online: 1 November 2021 (12:51:36 CET)

How to cite: Marino, C.; Nucara, A.; Panzera, M.F.; Pietrafesa, M. Assessment of the Road Traffic Air Pollution in Urban Contexts: A Statistical Approach. Preprints 2021, 2021110016 (doi: 10.20944/preprints202111.0016.v1). Marino, C.; Nucara, A.; Panzera, M.F.; Pietrafesa, M. Assessment of the Road Traffic Air Pollution in Urban Contexts: A Statistical Approach. Preprints 2021, 2021110016 (doi: 10.20944/preprints202111.0016.v1).

Abstract

In the article a statistical approach to the assessment of the emission rates discharged by the road traffic in a spatial context is proposed. It exploits an indicator, the Yearly Average Vehicle, representing the pollutant emission rate of the average vehicle belonging to a specific category, and considers the statistical variability of most of the involved traffic parameters: vehicle speed and mileage travelled in the considered time period. Finally, indicators, assessing both the most probable value among the possible emission rates and the extent of their variability range, are proposed. They may also be used to underpin decision making-processes, when the effects of different policies addressing air pollution issues, are to be evaluated. Therefore, they are suitable for the analysis supporting urban planning activities, with a view to addressing and mitigating the effects and the consequences of pollution due to the transportation sector of the urban context.

Keywords

Road Traffic; Air Pollution Assessment; Emission factors; Statistical Approach; Transport Policy

Subject

ENGINEERING, Other

Comments (0)

We encourage comments and feedback from a broad range of readers. See criteria for comments and our diversity statement.

Leave a public comment
Send a private comment to the author(s)
Views 0
Downloads 0
Comments 0
Metrics 0


×
Alerts
Notify me about updates to this article or when a peer-reviewed version is published.
We use cookies on our website to ensure you get the best experience.
Read more about our cookies here.