Título :	Toward an early warning system for health issues related to particulate matter exposure in Brazil : the feasibility of using global PM2.5 concentration forecast products
Autor :	Roux, Emmanuel Ignotti, Eliane Bègue, Nelson Bencherif, Hassan Catry, Thibault Dessay, Nadine Gracie, Renata Gurgel, Helen da Costa Hacon, Sandra de Sousa Magalhães, Mônica de A. F. M. Monteiro, Antônio Miguel Vieira Revillion, Christophe Villela, Daniel Antunes Maciel Xavier, Diego Barcellos, Christovam
metadata.dc.identifier.orcid:	https://orcid.org/ 0000-0003-2266-8207 https://orcid.org/ 0000-0002-9743-1856 https://orcid.org/ 0000-0003-1815-0667 https://orcid.org/ 0000-0001-9514-1751 https://orcid.org/ 0000-0003-0526-3531 https://orcid.org/ 0000-0003-0225-3696 https://orcid.org/ 0000-0002-4250-6742 https://orcid.org/ 0000-0002-8222-0992 https://orcid.org/ 0000-0002-6595-8274 https://orcid.org/ 0000-0002-6595-8274 https://orcid.org/ 0000-0002-3896-2083 https://orcid.org/ 0000-0001-8371-2959 https://orcid.org/ 0000-0001-5259-7732 https://orcid.org/ 0000-0002-1161-2753
Assunto::	Previsões de material particulado - Brasil Doenças respiratórias agudas graves Sistema de alerta antecipado Sensoriamento remoto
Fecha de publicación :	12-dic-2020
Editorial :	MDPI
Citación :	ROUX, Emmanuel et al. Toward an early warning system for health issues related to particulate matter exposure in Brazil: the feasibility of using global PM2.5 concentration forecast products. Remote Sensing, v. 12, n. 24, 4074, 2020. DOI: https://doi.org/10.3390/rs12244074. Disponível em: https://www.mdpi.com/2072-4292/12/24/4074. Acesso em: 4 dez. 2021.
Abstract:	: PM2.5 severely affects human health. Remotely sensed (RS) data can be used to estimate PM2.5 concentrations and population exposure, and therefore to explain acute respiratory disorders. However, available global PM2.5 concentration forecast products derived from models assimilating RS data have not yet been exploited to generate early alerts for respiratory problems in Brazil. We investigated the feasibility of building such an early warning system. For this, PM2.5 concentrations on a 4-day horizon forecast were provided by the Copernicus Atmosphere Monitoring Service (CAMS) and compared with the number of severe acute respiratory disease (SARD) cases. Confounding effects of the meteorological conditions were considered by selecting the best linear regression models in terms of Akaike Information Criterion (AIC), with meteorological features and their two-way interactions as explanatory variables and PM2.5 concentrations and SARD cases, taken separately, as response variables. Pearson and Spearman correlation coefficients were then computed between the residuals of the models for PM2.5 concentration and SARD cases. The results show a clear tendency to positive correlations between PM2.5 and SARD in all regions of Brazil but the South one, with Spearman’s correlation coefficient reaching 0.52 (p < 0.01). Positive significant correlations were also found in the South region by previously correcting the effects of viral infections on the SARD case dynamics. The possibility of using CAMS global PM2.5 concentration forecast products to build an early warning system for pollution-related effects on human health in Brazil was therefore established. Further investigations should be performed to determine alert threshold(s) and possibly build combined risk indicators involving other risk factors for human respiratory diseases. This is of particular interest in Brazil, where the COVID-19 pandemic and biomass burning are occurring concomitantly, to help minimize the effects of PM emissions and implement mitigation actions within populations.
Licença::	© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
DOI:	https://doi.org/10.3390/rs12244074
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