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.

Resolving Regional Discrimination Problems: Some Case Histories

Abstract: Developing the capability to identify, with high confidence, small events in areas of low seismicity and sparse station distribution remains as a major challenge to effective monitoring of a Comprehensive Test Ban Treaty (CTBT). Recent research in seismic discrimination has produced a number of potentially useful methodologies, particularly at regional distance ranges, for identifying seismic events in a CTBT monitoring system. Much optimism in the ability of such a system to automatically and reliably discriminate seismic events worldwide has been engendered by these recent results and by the availability of ever increasing volumes of seismic data from expanding global seismic networks. However, this optimism needs to be tempered by the fact that there are many problems and complexities associated with discrimination of small seismic events using regional seismic data. Moreover, an understanding of these problems leads to a number of conceivable scenarios by which a determined evader might be able to test clandestinely, taking advantage of gaps in knowledge of regional signal characteristics in particular regions and the shear quantity of data that the CTBT system must process.

Evaluation of Climate Driven Simulations of Po River Flow from 1971 to 2000 Through Flow-Duration Curve Indices: Preliminary Results

Abstract: Climate shows a natural variability that influences the dynamics of river discharges. In particular, intense precipitations would cause floods, while prolonged dry periods are associated to droughts phenomena. In the Mediterranean area, climate change is expected to increase the frequency of these phenomena due to variations in the precipitation partitioning in both space and time. To evaluate the impacts of these changes on the Po river daily discharges, we have developed a modelling chain that includes both climate and hydrological models. The performances of the chain are currently under testing through different simulations over the period 1971-2000. These simulations are driven by precipitation and temperature from a high resolution observed climate dataset and from the regional climate model COSMO-CLM, driven by perfect boundary conditions given by ERA40 Reanalysis and by suboptimal boundary conditions, using the global climate model CMCC-CM. The aim of these simulations is to investigate the uncertainties introduced by the components of the modelling chain and their effects on simulated discharges: the first simulation is used as reference simulation, the second one aims to evaluate how the uncertainties, introduced by the RCM, COSMO-CLM, propagate to the simulated discharges; and the last one is designed to evaluate the joint effects of the GCM, CMCC-CM, and the RCM on the simulation outputs. The results of such analysis will be used to qualify the XXI century climate projections and to correctly interpret climate change impacts on hydrological cycle in the future. The simulations performances are evaluated by comparing the precipitation and discharge seasonality and through five indices based on the flow-duration curve, that is representative of the probability distribution function of the river flow. To improve the simulation results a quantile-quantile correction is applied to simulated discharges using 1972-1990 data as calibration period and validating the results on 1991-2000. The quantile-quantile corrected simulations better resemble discharge seasonality and flow-duration curve. Results show how probabilistic bias correction helps in reducing the overall uncertainty.

Integration of Multi-sensor A-DInSAR Data for Landslide Inventory Update

Abstract: A systematic and reproducible methodology to analyze multi-sensors advanced satellite radar differential interferometry (A-DInSAR) data for identifying ground motion areas and for updating landsides inventories is proposed. We apply the methodology in a wide area of north-western Italy, corresponding to Piedmont region that is affected by different landslides. We use satellites images acquired, in ascending and descending acquisition geometry, by C-band (ERS ½ and ENVISAT, RADARSAT) and X-band (COSMO-SkyMed) sensors and processed using SqueeSAR™, PSInSAR™ and PSP-IfSAR techniques. Landslides characterized by linear and non-linear behavior were recognized.

Carbon monoxide concentrations evaluated by traffic noise data in urban areas

Abstract: (ricevuto il 21 Febbraio 1997; revisionato il 28 Luglio 1997; approvato il 18 Agosto 1997) Summary. — It is shown that variations in carbon monoxide concentrations can be evaluated by measuring environmental noise, wind velocity and vertical thermal stability. The results can be justified on the basis of the theory of the street canyon effect. The methodology proposed was verified in two Italian cities with different characteristics: Milan and Ravenna. PACS 92.60 ‐ Air quality and air pollution. Processes of urbanisation produce drastic modifications in the atmosphere and terrain, bringing about the transformation of radiative and thermal properties and in the features of aerodynamics and humidity. For example, building materials increase the thermal capacity of the system and cause the surface to become more impermeable. The geometry of buildings produce multireflectivity which leads to an entrapment of solar radiation. The heat and water generated by human activity combine with natural sources of heat and water of the urban system, with the result that, during daytime, the urban area absorbs more heat than the surrounding area and therefore, at night, especially in conditions of weak wind, the city air is warmer than that in the surrounding rural suburbs. The physical structure of the city also exerts a strong influence on the wind field whose speed is generally reduced due to the friction with the surfaces (urban buildings oppose a greater resistance to the wind flux compared to those in rural areas), while the street system forces its direction. Up to now, considerable difficulties have been encountered in describing pollutant dispersion in urban atmospheres by means of mathematical models. The basic reason lies in the complexity of topography in the urban environment, comprising streets lined with buildings, squares where several streets meet, green areas, large-scale trunk roads and areas of dense traffic. To this, we must add any natural complexities in cases where towns are located in the hills, mountains or along the coast.

Sensing properties of MWCNTs layers electrodecorated with metal nanoparticles for detection of aromatic hydrocarbon compounds

Abstract: An electrophoretic process is proposed to deposit electrochemically-preformed Au or Pd NPs, with controlled size, directly on MWCNTs-based chemiresistors to improve the detection of aromatic pollutants, compared to pristine ones. The sensing properties of pristine and functionalized MWCNTs were evaluated at an operating temperature of 40°C towards various concentrations of one aromatic pollutant, belonging to the dangerous BTEX class of compounds, m-Xylene. The sensing performance was related to the metal used in the functionalization process. Metal-doped MWCNTs sensors exhibited a very high gas sensitivity to m-Xylene even at low (80 ppb) concentration at low operating temperature (40°C), good reversibility and repeatability, with the sensing properties controlled by the type of deposited metal catalyst. The results indicate that Metal-modified MWCNT-based chemiresistive gas sensors has good potential in practical applications, due to its remarkable performance, low power consumption, and facile synthesized methods.