Fire-Pollutant-Atmosphere Components and Its Impact on Mortality in Portugal During Wildfire Seasons

IF 4.3 2区医学 Q2 ENVIRONMENTAL SCIENCES Geohealth Pub Date : 2023-10-06 DOI:10.1029/2023GH000802

Ediclê de Souza Fernandes Duarte, Vanda Salgueiro, Maria João Costa, Paulo Sérgio Lucio, Miguel Potes, Daniele Bortoli, Rui Salgado

{"title":"Fire-Pollutant-Atmosphere Components and Its Impact on Mortality in Portugal During Wildfire Seasons","authors":"Ediclê de Souza Fernandes Duarte, Vanda Salgueiro, Maria João Costa, Paulo Sérgio Lucio, Miguel Potes, Daniele Bortoli, Rui Salgado","doi":"10.1029/2023GH000802","DOIUrl":null,"url":null,"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.","PeriodicalId":48618,"journal":{"name":"Geohealth","volume":"7 10","pages":""},"PeriodicalIF":4.3000,"publicationDate":"2023-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/2023GH000802","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Geohealth","FirstCategoryId":"3","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1029/2023GH000802","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}

引用次数: 1

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, PM_2.5), 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, PM_2.5, 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 (r_RSD = 0.58) and PNEUxPBI (r_PNEU = 0.67). Cluster 2 showed statistically significant correlations between RSDxPBI (r_RSD = 0.48), PNEUxPBI (r_PNEU = 0.47), COPDxPBI (r_COPD = 0.45), CSDxAPI (r_CSD = 0.70), RSDxAPI (r_CSD = 0.71), PNEUxAPI (r_PNEU = 0.49), and COPDxAPI (r_PNEU = 0.62). Cluster 2 analysis indicates that the warmest, driest, and most polluted months of the wildfire season were associated with cardio-respiratory mortality.

Abstract Image

查看原文

微信好友朋友圈 QQ好友复制链接

本刊更多论文

葡萄牙野火季节火灾污染物大气成分及其对死亡率的影响。

本研究分析了葡萄牙野火季节火灾污染物气象变量及其对心肺死亡率的影响。烧伤面积、直径为10或2.5μm（μm）或更小的颗粒物（PM10、PM2.5）、一氧化碳（CO）、二氧化氮（NO2）、臭氧（O3）、温度、相对湿度、风速、气溶胶光学深度和循环系统疾病（CSD）、呼吸系统疾病（RSD）、肺炎（PNEU）、慢性阻塞性肺病和哮喘（ASMA）的死亡率数据，使用。只考虑了2011-2020年野火季节的几个月（6月至7月至8月至9月至10月），过火面积超过1000公顷。对火灾污染物气象变量进行主成分分析，建立了两个称为污染物-燃烧相互作用（PBI）和大气-污染物相互作用（API）的指数。PBI和大气污染物和燃烧面积呈强相关，而API和温度、相对湿度和O3呈强相关。应用于PBI-API的聚类分析将数据分为两个聚类。第1类包括较冷、较潮湿的月份和较高的NO2浓度。第2类包括温暖和干燥的月份，以及较高的PM10、PM2.5、CO和O3浓度。对聚类进行主成分线性回归，以更好地了解死亡率与PBI-API指数之间的关系。聚类1显示RSDxPBI（r RSD=0.58）和PNEUxPBI，和COPDxAPI（r PNEU=0.62）。聚类2分析表明，野火季节最温暖、最干燥和污染最严重的月份与心肺死亡率有关。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文去求助

来源期刊

Geohealth Environmental Science-Pollution

CiteScore

6.80

自引率

6.20%

发文量

124

审稿时长

19 weeks

期刊介绍： GeoHealth will publish original research, reviews, policy discussions, and commentaries that cover the growing science on the interface among the Earth, atmospheric, oceans and environmental sciences, ecology, and the agricultural and health sciences. The journal will cover a wide variety of global and local issues including the impacts of climate change on human, agricultural, and ecosystem health, air and water pollution, environmental persistence of herbicides and pesticides, radiation and health, geomedicine, and the health effects of disasters. Many of these topics and others are of critical importance in the developing world and all require bringing together leading research across multiple disciplines.