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| Sartini, Ludovica; Pisoni, E.; Thunis, P.. |
| This study investigates the dispersion of atmospheric pollutants over a coastal region of north-western Italy by means of modelling techniques. A series of annual air quality model simulations corresponding to different emission reduction scenarios has been performed with a three-dimensional chemical transport modelling chain running at 3 km resolution. The emission reduction scenarios were used to develop bottom-up (locally produced) source-receptor relationships to perform a local source allocation analysis of the main atmospheric pollutants in a few polluted cities within the domain of interest. Results were compared with default top-down (EU-wide) source-receptor relationships, at roughly 7 km resolution. The results show the benefit of using the two... |
| Tipo: Text |
Palavras-chave: Source allocation; Air quality models; CHIMERE; Inventory emissions; SHERPA methodology. |
| Ano: 2020 |
URL: https://archimer.ifremer.fr/doc/00644/75649/76515.pdf |
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| Mentaschi, Lorenzo; Vousdoukas, Michalis; Voukouvalas, Evangelos; Sartini, Ludovica; Feyen, Luc; Besio, Giovanni; Alfieri, Lorenzo. |
| Statistical approaches to study extreme events require, by definition, long time series of data. In many scientific disciplines, these series are often subject to variations at different temporal scales that affect the frequency and intensity of their extremes. Therefore, the assumption of stationarity is violated and alternative methods to conventional stationary extreme value analysis (EVA) must be adopted. Using the example of environmental variables subject to climate change, in this study we introduce the transformed-stationary (TS) methodology for non-stationary EVA. This approach consists of (i) transforming a non-stationary time series into a stationary one, to which the stationary EVA theory can be applied, and (ii) reverse transforming the result... |
| Tipo: Text |
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| Ano: 2016 |
URL: http://archimer.ifremer.fr/doc/00354/46490/46266.pdf |
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