Informacja

Drogi użytkowniku, aplikacja do prawidłowego działania wymaga obsługi JavaScript. Proszę włącz obsługę JavaScript w Twojej przeglądarce.

Tytuł pozycji:

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

Tytuł:
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
Autorzy:
Emmanuel Roux
Eliane Ignotti
Nelson Bègue
Hassan Bencherif
Thibault Catry
Nadine Dessay
Renata Gracie
Helen Gurgel
Sandra de Sousa Hacon
Mônica de A. F. M. Magalhães
Antônio Miguel Vieira Monteiro
Christophe Revillion
Daniel Antunes Maciel Villela
Diego Xavier
Christovam Barcellos
Temat:
particulate matter forecasts
severe acute respiratory diseases
Brazil
early warning system
remotely sensed observation assimilation
Science
Źródło:
Remote Sensing, Vol 12, Iss 24, p 4074 (2020)
Wydawca:
MDPI AG, 2020.
Rok publikacji:
2020
Kolekcja:
LCC:Science
Typ dokumentu:
article
Opis pliku:
electronic resource
Język:
English
ISSN:
12244074
2072-4292
Relacje:
https://www.mdpi.com/2072-4292/12/24/4074; https://doaj.org/toc/2072-4292
DOI:
10.3390/rs12244074
Dostęp URL:
https://doaj.org/article/468b63f7c47145c5b99476bb08c737e1  Link otwiera się w nowym oknie
Numer akcesji:
edsdoj.468b63f7c47145c5b99476bb08c737e1
Czasopismo naukowe
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.
Zaloguj się, aby uzyskać dostęp do pełnego tekstu.

Ta witryna wykorzystuje pliki cookies do przechowywania informacji na Twoim komputerze. Pliki cookies stosujemy w celu świadczenia usług na najwyższym poziomie, w tym w sposób dostosowany do indywidualnych potrzeb. Korzystanie z witryny bez zmiany ustawień dotyczących cookies oznacza, że będą one zamieszczane w Twoim komputerze. W każdym momencie możesz dokonać zmiany ustawień dotyczących cookies