The consecutive disparity of precipitation in conterminous Spain

Precipitation irregularity constitutes a constraint for natural systems and socio-economic activities, particularly in water-scarce environments. Standard variability statistics such as the standard deviation, variance, and coefficient of variation do not consider the chronological order of these values. In Climatology, however, the temporal order of meteorological events is a relevant factor that can affect natural and socio-economic systems. In order to evaluate the disparity between consecutive values in precipitation series, we applied the Consecutive Disparity Index (D) to the monthly grid with the highest spatial resolution (10×10 km) existing in Peninsular Spain for the period December 1915–November 2015. Monthly, seasonal, and annual D values show an increase from north to southwest, especially in July and August. The D values for the month-to-month correlative series and for monthly mean precipitation reveal a relatively similar pattern. In the latter case, however, the low values are recorded towards southern Spain, following some mountain ranges in the Centre-East of the territory. Monthly, seasonal, and annual precipitation values are also negatively correlated with the corresponding D values.

Effects of air quality on the health of Mediterranean forests

<p>The climate change has turned out to be a determining factor in the development of forest in Spain. Production systems have emitted polluting gases and other particles into the atmosphere, for which some plants have not yet developed adaptation systems. Among the most harmful pollutants for the environment are gases such as nitrous oxides, ozone, particulate matter.</p><p>However, this condition is not the same in Peninsular Spain, and the Balearic Islands since the plant compositions differ in the territory and the bioclimatic, topographic, and anthropic characteristics. Monitoring the vegetation with sufficient spatial and temporal resolution, studying variables conditioning plant health is a challenge from the nature of the variables and the amount of data to be handled. </p><p>The Mediterranean forest is one of the most ecosystem affected by climate change because of usually experimented long periods of drought that, in combination with increased temperatures, can drastically reduce the photosynthetic activity of trees and therefore the biomass of forests.</p><p>That is why the application of environmental technologies based on Remote Sensing (which provide plant health indices from passive sensors on satellite platforms and other variables of interest), Geographic Information Systems (to integrate, process, analyze spatial and temporal data) and machine learning models (which facilitate the extraction of relationships between variables, conditioning factors and predict patterns). </p><p>In this regard, this work's objective is to evaluate the possible effect that different pollutants have on the health of the vegetation, measured from the annual values of the Normalized Difference Vegetation Index (NDVI), in the Mediterranean forests of Peninsular Spain. To achieve this, we are used machine learning techniques using the Random Forest algorithm. The study has also been done with various climatic, topographic, and anthropic variables that characterize the forest to carry it out. </p><p>The results showed that certain variables such as the aridity index had generated the NDVI values and therefore plant development, while others are limiting factors such as the concentration of certain pollutants and the direct relationship between them particulates and NOx. This study can verify how the Random Forest algorithm offers reliable results, even when working with heterogeneous variables. </p>

First sampling of microplastics in streams and rivers of peninsular Spain

Durante 2019 y 2020 se llevó a cabo una campaña de muestreo para la identificación de microplásticos en 157 arroyos y ríos de la España peninsular. El muestreo se realizó aplicando una metodología desarrollada por HyT (Asociación Hombre y Territorio) en el marco del Proyecto LIBERA y, en concurrencia con una campaña de análisis de contaminantes en IBA (Áreas Importantes para la Conservación de las Aves y la Biodiversidad) llevada a cabo por SEO/BirdLife. Las muestras fueron procesadas inicialmente para la detección de microplásticos bajo lupa y posteriormente fueron sometidas a análisis de espectroscopía infrarroja FTIR (Espectrofotómetro de transformada de Fourier) por el Servicio de Microanálisis de la Universidad de Sevilla. Los resultados de este muestreo, el primero de estas características que se realiza en España para la detección de estos contaminantes, reflejan que más de un 70% de las muestras tienen presencia de microplásticos, con una mayor presencia de fibras, fragmentos y films. Entre las muestras analizadas con FTIR se han identificado un total de 33 polímeros diferentes. El trabajo ofrece, por tanto, datos relevantes acerca de este problema en ríos y arroyos de España.

Assessment of High-Speed Rail Service Coverage in Municipalities of Peninsular Spain

The Spanish transportation and housing infrastructure plan has planned that in 2024 all provincial capitals in peninsular Spain are to be connected by high-speed rail lines. Nowadays, 35 stations are already operational. These stations and the roads to access them are very important, as these are the only access points for travelers to benefit from the high railway speed. The goal of this study is to evaluate the railway coverage of high-speed services in Spanish peninsular municipalities in 2018 and planned for 2024. A methodology and research tools related to accessibility from municipalities to stations have been used, based on Geographic information Systems. An interaction model was used based on the floating catchment area in three steps. The resulting thematic maps and the analysis of the number of municipalities and the resident population is based on the degree of coverage in 2018. Likewise, in 2024 almost all of the municipalities are planned to have high high-speed railway coverage, these being the most densely populated. The analysis allowed us to present a detailed view of the problem; a methodology and a specific application framework are offered to make the high-speed rail services in Spain more equitable.

Epidemiology of multiple sclerosis and vitamin D levels in Lanzarote, Canary Islands, Spain

Background Low levels of 25-hydroxyvitamin D (25(OH)D) have been described as one of the possible environmental factors involved in multiple sclerosis (MS) etiopathogenesis. Objectives To study epidemiology of MS and 25(OH)D serum levels of patients in Lanzarote (29°02′06″N), a region with high ultraviolet radiation values during the whole year which is located far apart from Iberian Peninsula (36°–43°N), but without genetic/ethnic differences with it. Methods Incidence in Lanzarote was assessed according to McDonald 2005 criteria between January 2008 and December 2015 and prevalence date was 12/31/15. For 25(OH)D serum levels analyses, samples from 60 MS patients and 60 healthy donors (HD) were collected monthly in a one-year prospective study. Results The prevalence of MS in Lanzarote was 50.0/100,000 and the incidence per year was 2.5/100,000. Median 25(OH)D levels values were 29.1 ng/ml for MS patients (maximum = 36.1 ng/ml, minimum = 22.5 ng/ml) and 27.1 ng/ml for HD (maximum = 34.8 ng/ml, minimum = 22.8 ng/ml). There were no significant differences between 25(OH)D serum levels between MS patients and HD. Conclusions Lanzarote possesses lower prevalence and incidence values than peninsular Spain. Moreover, 25(OH)D serum levels do not differ between MS patients and HD.

Remote sensing and ecosystem modeling to simulate terrestrial carbon fluxes

<p>The main goal of this thesis is the establishment of a framework to analyze the forest ecosystems in peninsular Spain in terms of their role in the carbon cycle. In particular, the carbon fluxes that they exchange with atmosphere are modeled to evaluate their potential as carbon sinks and biomass reservoirs. The assessment of gross and net carbon fluxes is performed at 1-km spatial scale and on a daily basis using two different ecosystem models, Monteith and BIOME-BGC, respectively. These models are driven by a combination of satellite and ground data, part of the latter being also employed as a complementary data source and in the validation process.</p>