Please use this identifier to cite or link to this item: http://hdl.handle.net/10071/35819
Author(s): Juma, A.
Elvas, L. B.
Ferreira, J. C.
Nunes, L.
Date: 2025
Title: Mobility effect on city pollution: A case study
Journal title: Journal of Ambient Intelligence and Smart Environments
Volume: N/A
Reference: Juma, A., Elvas, L. B., Ferreira, J. C., & Nunes, L. (2025). Mobility effect on city pollution: A case study. Journal of Ambient Intelligence and Smart Environments. https://doi.org/10.1177/18761364251396640
ISSN: 1876-1364
DOI (Digital Object Identifier): 10.1177/18761364251396640
Keywords: Urban mobility
Air quality
Covid-19
Data mining
Data analytics
Machine learning
Pollution
Abstract: The present work reports the impacts on urban mobility and air quality in Lisbon, Portugal, of the imposed restrictions to curb the transmission of SARS-CoV-2 virus, which causes COVID-19 disease. We performed a data-driven approach over Lisbon Smart cities data, collected from several sources, such as traffic and pollution. During the first Portuguese emergency period (18-03-2020 to 03-05-2020) the sharp reductions in anthropogenic activities, most importantly road traffic, resulted in generally reduced criteria air pollutant concentration compared to an homologous baseline from 2013–2019 measured in the six air quality monitoring stations throughout the city. The most negatively impacted air pollutants were NO2, with a reduction of 54.35% in traffic stations and 28.62% in background stations. Google mobility indicator for local commerce was found to be the main anthropogenic activity indicator for Lisbon, with a moderate and positive correlation with NO2 concentration (r=+0.54). A regressor ML pipeline was trained to predict NO2 concentration with the available anthropogenic activity, weather, and air pollutant inputs from March/2020 to March/2021, achieving R2 = 0.925 on the test set.
Peerreviewed: yes
Access type: Open Access
Appears in Collections:ISTAR-RI - Artigos em revistas científicas internacionais com arbitragem científica

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