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Validation of PM 10 and PM 2.5 early alert in Bogotá, Colombia, through the modeling software WRF-CHEM
Air quality data from Bogotá, Colombia, show high levels of particulate matter (PM), which often generate respiratory problems to the population and a high economic cost to the government. Since 2016, air quality in the city of Bogotá has been measured through the Bogota Air Quality Index (IBOCA) wh...
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Published in: | Environmental science and pollution research international 2020-03 |
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Main Authors: | , , , , , , |
Format: | Article |
Language: | English |
Online Access: | Get full text |
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Summary: | Air quality data from Bogotá, Colombia, show high levels of particulate matter (PM), which often generate respiratory problems to the population and a high economic cost to the government. Since 2016, air quality in the city of Bogotá has been measured through the Bogota Air Quality Index (IBOCA) which works as an indicator of environmental risk due to air pollution. However, available technological tools in Bogotá are not enough to generate early alerts due to PM
and PM
. Currently, alerts are only announced once the measured PM values exceed a certain standard (e.g., 37 μ g/m
), but not with enough anticipation to efficiently protect the population. It is necessary to develop an early air quality alert in Bogotá, in order to provide information that improves risk management protocols in the capital district. The purpose of this investigation is to validate the correctivealert presented on the 14th and 15th of February of 2019, through the WRF-Chem model under different weather conditions, using three different setups of the model to simulate PM
and PM
concentrations during two different climatic seasons and different resolutions. The results of this article generate a validation of two configurations of the model that can be used for the Environmental Secretary of the District (SDA) forecasts in Bogotá, Colombia, in order to contribute to the prediction of pollution events produced by PM
and PM
as a tool for an early alert system (EAS) at least 24 h in advance. |
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ISSN: | 1614-7499 |