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Data Assimilation as a Tool to Improve Chemical Transport Models Performance in Developing Countries

Book Chapter (2021)
Author(s)

Santiago Lopez Restrepo (Universidad EAFIT, TU Delft - Mathematical Physics, SimpleSpace)

A. Yarce Botero (TU Delft - Mathematical Physics, Universidad EAFIT, SimpleSpace)

O.L. Quintero Montoya (TU Delft - Mathematical Physics)

N. Pinel Pelaez (TU Delft - Mathematical Physics, Universidad EAFIT)

J.E. Hinestroza Ramirez (Universidad EAFIT)

Elias David Nino-Ruiz (Universidad del Norte)

Jimmy Anderson Flórez (Centro Tecnologico Aeroespacial para la Defensa CETAD)

Angela Maíra Rendón (Universidad de Antioquia)

Monica Lucia Alvarez-Laínez (Universidad EAFIT)

A.W. Heemink (TU Delft - Mathematical Physics)

More authors (External organisation)

Research Group
Mathematical Physics
Copyright
© 2021 S. Lopez Restrepo, A. Yarce Botero, O.L. Quintero Montoya, N. Pinel Pelaez, J.E. Hinestroza Ramirez, Elias David Nino-Ruiz, Jimmy Anderson Flórez, Angela Maíra Rendón, Monica Lucia Alvarez-Laínez, A.W. Heemink, More Authors
DOI related publication
https://doi.org/10.5772/intechopen.97503
More Info
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Publication Year
2021
Language
English
Copyright
© 2021 S. Lopez Restrepo, A. Yarce Botero, O.L. Quintero Montoya, N. Pinel Pelaez, J.E. Hinestroza Ramirez, Elias David Nino-Ruiz, Jimmy Anderson Flórez, Angela Maíra Rendón, Monica Lucia Alvarez-Laínez, A.W. Heemink, More Authors
Research Group
Mathematical Physics
ISBN (print)
['978-1-83968-786-0', '978-1-83968-785-3']
ISBN (electronic)
978-1-83968-787-7
Reuse Rights

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Abstract

Particulate matter (PM) is one of the most problematic pollutants in urban air. The effects of PM on human health, associated especially with PM of ≤2.5μm in diameter, include asthma, lung cancer and cardiovascular disease. Consequently, major urban centers commonly monitor PM2.5 as part of their air quality management strategies. The Chemical Transport models allow for a permanent monitoring and prediction of pollutant behavior for all the regions of interest, different to the sensor network where the concentration is just available in specific points. In this chapter a data assimilation system for the LOTOS-EUROS chemical transport model has been implemented to improve the simulation and forecast of Particulate Matter in a densely populated urban valley of the tropical Andes. The Aburrá Valley in Colombia was used as a case study, given data availability and current environmental issues related to population expansion. Using different experiments and observations sources, we shown how the Data Assimilation can improve the model representation of pollutants.