http://hdl.handle.net/20.500.11765/10165 Mon, 13 Apr 2026 08:52:38 GMT 2026-04-13T08:52:38Z http://hdl.handle.net/20.500.11765/15942 Título : Air pollution and meteorological variables’ effects on COVID-19 first and second waves in Spain Autor : Bañuelos Gimeno, Jorge; Blanco, Alejandro; Díaz, Julio; Linares Gil, Cristina; López Bueno, José Antonio; Navas-Martín, Miguel Ángel; Sánchez Martínez, Gerardo; Luna Rico, Yolanda; Hervella, Beatriz; Belda Esplugues, Fernando; Culqui Lévano, Dante R. Resumen : The aim of this research is to study the infuence of atmospheric pollutants and meteorological variables on the incidence rate of COVID-19 and the rate of hospital admissions due to COVID-19 during the frst and second waves in nine Spanish provinces. Numerous studies analyze the efect of environmental and pollution variables separately, but few that include them in the same analysis together, and even fewer that compare their efects between the frst and second waves of the virus. This study was conducted in nine of 52 Spanish provinces, using generalized linear models with Poisson link between levels of PM10, NO2 and O3 (independent variables) and maximum temperature and absolute humidity and the rates of incidence and hospital admissions of COVID-19 (dependent variables), establishing a series of signifcant lags. Using the estimators obtained from the signifcant multivariate models, the relative risks associated with these variables were calculated for increases of 10 µg/m3 for pollutants, 1 °C for temperature and 1 g/m3 for humidity. The results suggest that NO2 has a greater association than the other air pollution variables and the meteorological variables. There was a greater association with O3 in the frst wave and with NO2 in the second. Pollutants showed a homogeneous distribution across the country. We conclude that, compared to other air pollutants and meteorological variables, NO2 is a protagonist that may modulate the incidence and severity of COVID-19, though preventive public health measures such as masking and hand washing are still very important. Sat, 01 Jan 2022 00:00:00 GMT http://hdl.handle.net/20.500.11765/15942 2022-01-01T00:00:00Z http://hdl.handle.net/20.500.11765/15941 Título : Short-term infuence of environmental factors and social variables COVID-19 disease in Spain during first wave (Feb–May 2020) Autor : Culqui Lévano, Dante R.; Díaz, Julio; Blanco, Alejandro; Navas-Martín, Miguel Ángel; Sánchez Martínez, Gerardo; Luna Rico, Yolanda; Hervella, Beatriz; Belda Esplugues, Fernando; Linares Gil, Cristina Resumen : This study aims to identify the combined role of environmental pollutants and atmospheric variables at short term on the rate of incidence (TIC) and on the hospital admission rate (TIHC) due to COVID-19 disease in Spain. This study used information from 41 of the 52 provinces of Spain (from Feb. 1, 2021 to May 31, 2021). Using TIC and TIHC as dependent variables, and average daily concentrations of PM10 and NO2 as independent variables. Meteorological variables included maximum daily temperature (Tmax) and average daily absolute humidity (HA). Generalized linear models (GLM) with Poisson link were carried out for each provinces The GLM model controlled for trend, seasonalities, and the autoregressive character of the series. Days with lags were established. The relative risk (RR) was calculated by increases of 10 μg/m3 in PM10 and NO2 and by 1 °C in the case of Tmax and 1 g/m3 in the case of HA. Later, a linear regression was carried out that included the social determinants of health. Statistically signifcant associations were found between PM10, NO2, and the rate of COVID19 incidence. NO2 was the variable that showed greater association, both for TIC as well as for TIHC in the majority of provinces. Temperature and HA do not seem to have played an important role. The geographic distribution of RR in the studied provinces was very much heterogeneous. Some of the health determinants considered, including income per capita, presence of airports, average number of diesel cars per inhabitant, average number of nursing personnel, and homes under 30 m2 could explain the diferential geographic behavior. As fndings indicates, environmental factors only could modulate the incidence and severity of COVID-19. Moreover, the social determinants and public health measures could explain some patterns of geographically distribution founded. Descripción : A correction to this article was published on 26 March 2022. Sat, 01 Jan 2022 00:00:00 GMT http://hdl.handle.net/20.500.11765/15941 2022-01-01T00:00:00Z http://hdl.handle.net/20.500.11765/15387 Título : Characterization of OCO-2 and ACOS-GOSAT biases and errors for CO2 flux estimates [Discussion paper] Autor : Kulawik, Susan; Crowell, Sean; Baker, David F.; Liu, Junjie; McKain, Kathryn; Sweeney, Colm; Biraud, Sebastien C.; Wofsy, Steven C.; O’Dell, Christopher W.; Wennberg, Paul O.; Wunch, Debra; Roehl, Coleen M.; Deutscher, Nicholas Michael; Kiel, Matthaeus; Griffith, David W. T.; Velazco, Voltaire A.; Notholt, Justus; Warneke, Thorsten; Petri, Christof; De Mazière, Martine; Sha, Mahesh Kumar; Sussmann, Ralf; Rettinger, Markus; Pollard, David F.; Morino, Isamu; Uchino, Osamu; Hase, Frank; Feist, Dietrich G.; Roche, Sébastien; Strong, Kimberly; Kivi, Rigel; Iraci, Laura; Shiomi, Kei; Dubey, Manvendra K.; Sepúlveda Hernández, Eliezer; García Rodríguez, Omaira Elena; Te, Yao; Jeseck, Pascal; Heikkinen, Pauli; Dlugokencky, Edward J.; Gunson, Michael R.; Eldering, Annmarie; Crisp, David; Fisher, Brendan; Osterman, Gregory Resumen : We characterize the magnitude of seasonally and spatially varying biases in the National Aeronautics and Space Administration (NASA) Orbiting Carbon Observatory-2 (OCO-2) Version 8 (v8) and the Atmospheric CO2 Observations from Space (ACOS) Greenhouse Gas Observing SATellite (GOSAT) version 7.3 (v7.3) satellite CO2 retrievals by comparisons to measurements collected by the Total Carbon Column Observing Network (TCCON), Atmospheric Tomography (ATom) experiment, and National Oceanic and Atmospheric Administration (NOAA) Earth System Research Laboratory (ESRL) and 50 U. S. Department of Energy (DOE) aircraft, and surface stations. Although the ACOS-GOSAT estimates of the column averaged carbon dioxide (CO2) dry air mole fraction (XCO2) have larger random errors than the OCO-2 XCO2 estimates, and the space-based estimates over land have larger random errors than those over ocean, the systematic errors are similar across both satellites and surface types, 0.6 ± 0.1 ppm. We find similar estimates of systematic error whether dynamic versus geometric coincidences or ESRL/DOE aircraft versus TCCON are used for validation (over land), once validation and co55 location errors are accounted for. We also find that areas with sparse throughput of good quality data (due to quality flags and preprocessor selection) over land have ~double the error of regions of high-throughput of good quality data. We characterize both raw and bias-corrected results, finding that bias correction improves systematic errors by a factor of 2 for land observations and improves errors by ~0.2 ppm for ocean. Tue, 01 Jan 2019 00:00:00 GMT http://hdl.handle.net/20.500.11765/15387 2019-01-01T00:00:00Z http://hdl.handle.net/20.500.11765/15164 Título : Analysis of the October 2014 subtropical cyclone using the WRF and the HARMONIE-AROME numerical models: Assessment against observations Autor : Quitián Hernández, Lara; Bolgiani, Pedro; Santos Muñoz, Daniel; Sastre, Mariano; Díaz Fernández, Javier; González-Alemán, Juan Jesús; Farrán Martín, José Ignacio; López Campano, Laura; Valero, Francisco; Martín, María Luisa Resumen : Subtropical cyclones (STCs) are low-pressure systems characterized by having a thermal hybrid structure and sharing tropical and extratropical characteristics. These cyclones are widely studied due to their harmful impacts, in some cases, similar to those caused by hurricanes or tropical storms. From a numerical modeling point of view, they are considered a challenge on account of their rapid intensification. That is the reason why this paper analyzes the simulations of the STC that occurred in October 2014 near the Canary Islands through two highresolution numerical models: Weather Research and Forecasting (WRF) and HARMONIE-AROME. In this study, the simulations obtained with both models of this STC are analyzed versus different observational data. METAR data are used to validate some surface simulated variables throughout the STC life while soundings are chosen to study the tropospheric behavior. Finally, MSG-SEVIRI satellite brightness temperature is used to be compared to those brightness temperatures simulated by both models to give information of the cloud top spatial structure of this atmospheric system. The 2 m temperature, 2 m dew-point temperature, and 10 m wind speed variables do not show significant deviations when carrying out the validation of both models against the available METAR data. It is outstanding the good results found for the HARMONIE-AROME model when analyzing the temperature sounding for both analyzed dates. Additionally, regarding the wind speed sounding, better results are presented in general by the HARMONIE-AROME model, being the WRF model slightly better during the pre-STC stage. Moreover, the skillfulness of the HARMONIE-AROME model is highlighted when simulating the infrared brightness temperature and cloud distribution compared to the WRF model. Fri, 01 Jan 2021 00:00:00 GMT http://hdl.handle.net/20.500.11765/15164 2021-01-01T00:00:00Z