A model based on the known high correlation between photosynthetically active radiation (PAR) and global horizontal irradiance (GHI) was implemented to estimate PAR from GHI measurements in this present study. The model has been developed using satellite-derived GHI and PAR estimations. Both variables can be estimated using Kato bands, provided by Satellite Application Facility on Climate Monitoring (CM-SAF), and its ratio may be used as the variable of interest in order to obtain the model. The study area, which was located in mainland Spain, has been split by cluster analysis into regions with similar behavior, according to this ratio. In each of these regions, a regression model estimating PAR from GHI has been developed. According to the analysis, two regions are distinguished in the study area. These regions belong to the two climates dominating the territory: an Oceanic climate on the northern edge; and a Mediterranean climate with hot summer in the rest of the study area. The models obtained for each region have been checked against the ground measurements, providing correlograms with determination coefficients higher than 0.99.
Frame and daughters directives for evaluating the ambient air quality have been adopted by the EU as a part of the new strategies for pollution prevention and control and environmental management. Therefore, the prediction of ozone concentration and the identification of episodes by modeling are fundamental for protecting and preventing the population and environment against the harmful effects of this species. Under this approach, ambient air quality (immission) data in three zones: A Guarda, Corrubedo and Verín (two coastal and one interior) of Galicia (NW Spain), were collected and evaluated using statistical tools. Punctual and functional background and standard levels of ozone and NOx in the three zones have been determined for detecting abnormal situations and identifying possible emission sources. With this aim, threshold values were established by defining confidence levels. Finally, ozone concentration has been forecasted by time series modeling. Descriptive and predictive models of ozone involving different parameters depending of the area considered have been developed. Satisfactory estimation of ozone concentration was obtained in the three cases with proved efficiency, since predictive values did not exceed the 95% confidence level.
Gridded chemical transport models are often used for the assessment of air quality. For European continental scale the EMEP emissions inventory with a low 50x50 km 2 resolution is yearly available. However, current air quality models are usually applied with higher spatial resolution, in order to obtain representative results, especially in regional domains; therefore, a simple topdown approach based in the spatial interpolation of EMEP emissions is not appropriate. On the other hand, a bottom-up approach requires a huge amount of data to estimate the emissions source-by-source, which are not always justified for all the sources.The aim of this work is the development and application of a mixed top-down and bottom-up methodology for high resolution emissions inventories, based on EMEP emission data and other emissions data source (PRTR, UNFCCC and LRTAP). The emissions of the main industrial and road traffic sources (>50000 inhabitants cities, motorways) were obtained by a bottom-up approach, with industrial emissions considered from point sources. Other emissions from sparse sources are estimated following a top-down approach, based on the EMEP inventory, following a spatial segregation methodology which considers different geographical parameters, which are dependent on the source type.Data processing was performed using ArcMap GIS, following the CORINAIR structure [3]. Therefore, results are easily updatable and they can be analysed jointly to the geographical parameters, in order to check the inventory coherence before its application to an air quality model.
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