Urban water demand model: the case study of Emilia Romagna (Italy)

Water is the driving force in nature. We use water for washing cars, doing laundry, cooking, taking a shower, but also to generate energy and electricity. Therefore water is a necessary product in our daily lives (USGS. Howard Perlman, 2013). The model that we created is based on the urban water demand computer model from the Pacific Institute (California). With this model we will forecast the future urban water use of Emilia Romagna up to the year of 2030. We will analyze the urban water demand in Emilia Romagna that includes the 9 provinces: Bologna, Ferrara, Forli-Cesena, Modena, Parma, Piacenza, Ravenna, Reggio Emilia and Rimini. The term urban water refers to the water used in cities and suburbs and in homes in the rural areas. This will include the residential, commercial, institutional and the industrial use. In this research, we will cover the water saving technologies that can help to save water for daily use. We will project what influence these technologies have to the urban water demand, and what it can mean for future urban water demands. The ongoing climate change can reduce the snowpack, and extreme floods or droughts in Italy. The changing climate and development patterns are expected to have a significant impact on water demand in the future. We will do this by conducting different scenario analyses, by combining different population projections, climate influence and water saving technologies. In addition, we will also conduct a sensitivity analyses. The several analyses will show us how future urban water demand is likely respond to changes in water conservation technologies, population, climate, water price and consumption. I hope the research can contribute to the insight of the reader’s thoughts and opinion.

Study of the performances of the H->ZZ*->4l analysis with the CMS phase-II upgrade

The performances of the H → ZZ* → 4l analysis are studied in the context of the High Luminosity upgrade of the LHC collider, with the CMS detector. The high luminosity (up to L = 5 × 10^34 cm−2s−1) of the accelerator poses very challenging experimental con- ditions. In particular, the number of overlapping events per bunch crossing will increase to 140. To cope with this difficult environment, the CMS detector will be upgraded in two stages: Phase-I and Phase-II. The tools used in the analysis are the CMS Full Simulation and the fast parametrized Delphes simulation. A validation of Delphes with respect to the Full Simulation is performed, using reference Phase-I detector samples. Delphes is then used to simulate the Phase-II detector response. The Phase-II configuration is compared with the Phase-I detector and the same Phase-I detector affected by aging processes, both modeled with the Full Simulation framework. Conclusions on these three scenarios are derived: the degradation in performances observed with the “aged��� scenario shows that a major upgrade of the detector is mandatory. The specific upgrade configuration studied allows to keep the same performances as in Phase-I and, in the case of the four-muons channel, even to exceed them.