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Title: Fire-Pollutant-Atmosphere Components and Its Impact on Mortality in Portugal During Wildfire Seasons
Authors: Duarte, Ediclê de Souza Fernandes
Salgueiro, Vanda
Costa, Maria João
Lucio, Paulo Sérgio
Potes, Miguel
Bortoli, Daniele
Salgado, Rui
Keywords: Pollutants
Issue Date: Oct-2023
Publisher: AGU
Citation: Duarte, E., V. Salgueiro, M. J. Costa, P. S. Lucio, M. Potes, D. Bortoli, R. Salgado: (2023). Fire-pollutant-atmosphere components and its impact on mortality in Portugal during wildfire seasons. GeoHealth, 7, e2023GH000802.
Abstract: This study analyzed fire-pollutant-meteorological variables and their impact on cardio-respiratory mortality in Portugal during wildfire season. Data of burned area, particulate matter with a diameter of 10 or 2.5 μm (μm) or less (PM10, PM2.5), carbon monoxide (CO), nitrogen dioxide (NO2), ozone (O3), temperature, relative humidity, wind speed, aerosol optical depth and mortality rates of Circulatory System Disease (CSD), Respiratory System Disease (RSD), Pneumonia (PNEU), Chronic Obstructive Pulmonary Disease, and Asthma (ASMA), were used. Only the months of 2011–2020 wildfire season (June–July–August–September-October) with a burned area greater than 1,000 ha were considered. Principal component analysis was used on fire-pollutant-meteorological variables to create two indices called Pollutant-Burning Interaction (PBI) and Atmospheric-Pollutant Interaction (API). PBI was strongly correlated with the air pollutants and burned area while API was strongly correlated with temperature and relative humidity, and O3. Cluster analysis applied to PBI-API divided the data into two Clusters. Cluster 1 included colder and wetter months and higher NO2 concentration. Cluster 2 included warmer and dried months, and higher PM10, PM2.5, CO, and O3 concentrations. The clusters were subjected to Principal Component Linear Regression to better understand the relationship between mortality and PBI-API indices. Cluster 1 showed statistically significant (p-value < 0.05) correlation (r) between RSDxPBI (rRSD = 0.58) and PNEUxPBI (rPNEU = 0.67). Cluster 2 showed statistically significant correlations between RSDxPBI (rRSD = 0.48), PNEUxPBI (rPNEU = 0.47), COPDxPBI (rCOPD = 0.45), CSDxAPI (rCSD = 0.70), RSDxAPI (rCSD = 0.71), PNEUxAPI (rPNEU = 0.49), and COPDxAPI (rPNEU = 0.62). Cluster 2 analysis indicates that the warmest, driest, and most polluted months of the wildfire season were associated with cardio-respiratory mortality.
Type: article
Appears in Collections:FIS - Publicações - Artigos em Revistas Internacionais Com Arbitragem Científica
CGE - Publicações - Artigos em Revistas Internacionais Com Arbitragem Científica

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