2019
DOI: 10.1016/j.atmosenv.2019.116878
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Analysis of exposure to fine particulate matter using passive data from public transport

Abstract: The city of Santiago experiences extreme pollution events during winter due to particulate matter and the associated health impact depends on the exposure to this pollutant, particularly to PM 2.5 . We present and apply a method that estimates the exposure of users of the public transport system of Santiago by combining smart card mobility data with measured surface concentrations from the monitoring network of Santiago and simulated concentrations by the CHIMERE model. The method was applied between July 20th… Show more

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Cited by 9 publications
(5 citation statements)
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References 39 publications
(45 reference statements)
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“…Understanding and modeling urban mobility correctly is a crucial issue for the development of Smart Cities (Mamei et al 2019). The object of the modeling can be displacements (Mamei et al 2019), congestion levels (Del Vecchio et al 2019), and exposure to pollution factors (Trewhela et al 2019). The type of model varies according to the type of relationship between the variables to be theorized.…”
Section: Results From Camentioning
confidence: 99%
“…Understanding and modeling urban mobility correctly is a crucial issue for the development of Smart Cities (Mamei et al 2019). The object of the modeling can be displacements (Mamei et al 2019), congestion levels (Del Vecchio et al 2019), and exposure to pollution factors (Trewhela et al 2019). The type of model varies according to the type of relationship between the variables to be theorized.…”
Section: Results From Camentioning
confidence: 99%
“…It simulates the physical–chemical processes of the different atmospheric pollutants based on emissions from the main anthropogenic sectors: residential, transportation, industry, and energy. This modeling system has been successfully applied to simulate the dispersion of atmospheric pollutants in central and southern Chile as well as the exposure to particulate matter of public transport users [ 27 , 28 , 29 ].…”
Section: Methodsmentioning
confidence: 99%
“…Later on, a module for the simulation of particulate matter (Pun and Seigneur, 2007;Bessagnet et al, 2008) was added to the model. The model is currently used extensively in air quality monitoring and forecasts for both research and operative purposes at regional and hemispheric levels (Cholakian et al, 2019b;Lachatre et al, 2019;Trewhela et al, 2019;Lapere et al, 2020). It has also been used in many model intercomparison studies, as well as model-observation comparisons within multi-model experiments, for example to investigate European particulate matter trends (Ciarelli et al, 2019).…”
Section: The Chimere Chemistry Transport Modelmentioning
confidence: 99%