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http://hdl.handle.net/10174/43
2024-03-29T02:38:33ZPollutant-meteorological factors and cardio-respiratory mortality in Portugal: Seasonal variability and associations
http://hdl.handle.net/10174/36351
Title: Pollutant-meteorological factors and cardio-respiratory mortality in Portugal: Seasonal variability and associations
Authors: Duarte, Ediclê de Souza Fernandes; Lucio, Paulo Sérgio; Costa, Maria João; Salgueiro, Vanda; Salgado, Rui; Potes, Miguel; Hoelzemann, Judith J.; Bortoli, Daniele
Abstract: Seasonal variations in cardiorespiratory diseases may be influenced by air pollution and meteorological factors. This work aims to highlight the relevance of a complete seasonal characterization of the pollutant-meteorological factors and cardio-respiratory mortality in Portugal and the relationships between health outcomes and environmental risk factors. To this end, air pollution and meteorological variables along with health outcomes were analyzed at national level and on a monthly basis for the period of 2011–2020. It was found that cardiorespiratory mortality rates during winter were 44% higher than during the summer. Furthermore, particulate matter with aerodynamic diameters of 10 and 2.5 μm (μm) or smaller (PM10 and PM2.5), carbon monoxide (CO) and nitrogen dioxide (NO2) showed a seasonal variability with the highest concentrations during winter while ozone (O3) presented higher concentrations during spring and summer. PM10, PM2.5 and NO2, showed a positive correlation between seasons, indicating similar patterns of behavior. Canonical correlation analysis (CCA) applied to pollutant-meteorological and cardiorespiratory mortality data indicates a strong linear correlation between pollutant-meteorological factors and health outcomes. The first canonical correlation was 0.889, and the second was 0.545, both statistically significant (p-value < 0.001). The CCA results suggest that there is a strong association between near-surface temperature, relative humidity, PM10, PM2.5, CO and NO2 and health outcomes. The results of this study provide important information of the seasonal variability of air pollutants and meteorological factors in Portugal and their associations with cardiorespiratory mortality.2024-01-01T00:00:00ZFire-Pollutant-Atmosphere Components and Its Impact on Mortality in Portugal During Wildfire Seasons
http://hdl.handle.net/10174/36350
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
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.2023-09-30T23:00:00ZAnalysis of sunshine duration and cloud cover trends in Lisbon for the period 1890–2018
http://hdl.handle.net/10174/36349
Title: Analysis of sunshine duration and cloud cover trends in Lisbon for the period 1890–2018
Authors: Aparicio, Alejandro; Carrasco, Victor; Montero-Martín, J.; Sanchez-Lorenzo, A.; Costa, Maria João; Antón, Manuel
Abstract: Sunshine duration (SD) represents a valuable parameter for early years when few or none measurements of surface solar radiation (SSR) are available. In the present work, daily and monthly SD records registered in Lisbon (Portugal) for the period 1890–1940 have been digitized to expand the data series available in electronic format, which starts in 1941. The resulting series for the period 1890–2018 can be considered as the earliest one in Portugal and the second one in the Iberian Peninsula. Cloud cover (CC) data for the same period have also been digitized. The SD series exhibits a weak negative trend (without statistical significance) from the 1890s to the 1910s, which is in line with the early dimming period in SSR reported in some regions. Subsequently, no trends are obtained for the period 1910s–1950s, which indicates that the early brightening is not observed in Lisbon unlike other locations in the Iberian Peninsula. After that, two strong statistically significant trends are found for the periods 1950s–1980s and 1980s–2010s in line with the well-known global dimming and brightening periods in SSR, respectively. On the other hand, the CC series presents an increase from 1890 to the 1980s, followed by a decrease up to 2018 (both being statistically significant), which may partially explain the reported SD trends. An analysis of SD under cloudless conditions proved the utility of this quantity to track long-term changes in atmospheric aerosol load. In addition, this analysis and a seasonal one pointed out that aerosols seem to play a relevant role in SD long-term variability.2023-06-30T23:00:00ZMicrowave radiometer, sun-photometer and GNSS multi-comparison of integrated water vapor in Southwestern Europe
http://hdl.handle.net/10174/36348
Title: Microwave radiometer, sun-photometer and GNSS multi-comparison of integrated water vapor in Southwestern Europe
Authors: Vaquero-Martínez, Javier; Antón, Manuel; Costa, Maria João; Bortoli, Daniele; Navas-Guzmán, Francisco; Alados-Arboledas, Lucas
Abstract: This work presents a comparison of integrated water vapor (IWV) data recorded from microwave radiometer (MWR) and sun-photometer (SP) using global navigation satellite system (GNSS) IWV as reference in five mid-latitude sites of Portugal and Spain (2003–2021). A very high correlation is obtained for both instruments (R2 between 0.94 and 0.98), although, while MWR shows a wet bias, SP exhibits a dry one. In addition, a dependence of mean bias error (MBE) and standard deviation (SD) on IWV has been observed, increasing (larger discrepancies) both indices as IWV increases. The solar zenith angle (SZA) dependence is also studied, finding slightly larger discrepancies for the MWR than for SP in comparison with GNSS for very high values of SZA. Finally, a marked seasonal dependence is observed for SP-GNSS differences, modulated by the IWV dependence explained above. In contrast, the seasonal dependence for MWR is quite weaker than it is for SP. Therefore, in spite of the excellent agreement found among the different instruments, it is recommended that: i) the dependence with IWV be studied and corrected to further increase the performance of the instruments, and ii) metadata be used to filter out situations in which the instrument cannot operate properly.2023-04-30T23:00:00Z