ARPA-E

About: ARPA-E is a government organization based out in Washington D.C., District of Columbia, United States. It is known for research contribution in the topics: Population & Climate change. The organization has 1161 authors who have published 1267 publications receiving 30049 citations. The organization is also known as: Advanced Research Projects Agency - Energy.

Regional climate models downscaling in the Alpine area with multimodel superensemble

Abstract: . The climatic scenarios show a strong signal of warming in the Alpine area already for the mid-XXI century. The climate simulations, however, even when obtained with regional climate models (RCMs), are affected by strong errors when compared with observations, due both to their difficulties in representing the complex orography of the Alps and to limitations in their physical parametrization. Therefore, the aim of this work is to reduce these model biases by using a specific post processing statistic technique, in order to obtain a more suitable projection of climate change scenarios in the Alpine area. For our purposes we used a selection of regional climate models (RCMs) runs which were developed in the framework of the ENSEMBLES project. They were carefully chosen with the aim to maximise the variety of leading global climate models and of the RCMs themselves, calculated on the SRES scenario A1B. The reference observations for the greater Alpine area were extracted from the European dataset E-OBS (produced by the ENSEMBLES project), which have an available resolution of 25 km. For the study area of Piedmont daily temperature and precipitation observations (covering the period from 1957 to the present) were carefully gridded on a 14 km grid over Piedmont region through the use of an optimal interpolation technique. Hence, we applied the multimodel superensemble technique to temperature fields, reducing the high biases of RCMs temperature field compared to observations in the control period. We also proposed the application of a brand new probabilistic multimodel superensemble dressing technique, already applied to weather forecast models successfully, to RCMS: the aim was to estimate precipitation fields, with careful description of precipitation probability density functions conditioned to the model outputs. This technique allowed for reducing the strong precipitation overestimation, arising from the use of RCMs, over the Alpine chain and to reproduce well the monthly behaviour of precipitation in the control period.

Geochemical Model of Mud Volcanoes from Reviewed Worldwide Data

Abstract: Geochemical data from mud volcanic fluids obtained from various geological environments have been reviewed and reprocessed. The chemical and isotopic components of the liquid and gas phases have been studied. Notwithstanding the geographical distance between the mud volcanic areas and the differences between the geological environments, a common originating fluid derived from seawater has been recognized. Diagenetic processes due to sediment compaction can be considered to be responsible for the evolutionary patterns observed in the liquid phase and in the associated gas-emissions. Geochemical data fit the currently available physical models.

A comprehensive approach to the investigation of atmospheric particulate PM2.5: Preliminary results

Abstract: Understanding the health effects induced in humans by the inhalation of air particulate matter requires first that airborne particles be characterized in detail. Aiming at elucidating some prominent mechanisms and processes involved in the atmospheric environment - human organism interaction, a comprehensive approach was adopted to thoroughly investigate PM 2.5 from a mineralogical, chemical and chemical-physical point of view. In the present study, two summer and winter samplings collected from the Rome urban area were investigated by different techniques (SEM-EDS, XRD, ICP-MS, ICP-OES, TGA-DTA). Mineralogical and physical characterization gave important information on the prevalent phases (oxides, sulphates, silicates, carbonates, and abundant carbonaceous particles hosting metals) contained into the material under study. The bulk chemical composition evidenced the presence of heavy metals, in particular As, Cd, Cu, Cr, Fe, Pb, Ni, and Zn. Consequently, in order to verify the potential mobility of such heavy metals, batch kinetic leaching tests were carried out by using a physiological solution mimicking the lung environment and samples were collected from the solution at different times of treatment. Among the metals contained into the particulate, a leaching trend was observed mainly for Pb, Cd and Cu, with Cd resulting the most mobile metal, whereas no Fe release was observed. The leaching solution mimicking the human intrapulmonary fluid will be exploited for future toxicological tests in cellular models, in order to assess the potentially harmful role of the above metals in biological systems .