ALBERT

Description: Intercomparison of two meteorological limited area models for quantitative precipitation forecast verification Natural Hazards and Earth System Science, 12, 591-606, 2012 Author(s): E. Oberto, M. Milelli, F. Pasi, and B. Gozzini The demand for verification of numerical models is still very high, especially for what concerns the operational Quantitative Precipitation Forecast (QPF) used, among others, for evaluating the issuing of warnings to the population. In this study, a comparative verification of the QPF, predicted by two operational Limited Area Models (LAMs) for the Italian territory is presented: COSMO-I7 (developed in the framework of the COSMO Consortium) and WRF-NMM (developed at NOAA-NCEP). The observational dataset is the precipitation recorded by the high-resolution non-GTS rain gauges network of the National Civil Protection Department (NCPD) over two years (2007–2008). Observed and forecasted precipitation have been treated as areal quantity (areal average of the values accumulated in 6 and 24 h periods) over the 102 "warning areas", defined by the NCPD both for administrative and hydrological purposes. Statistics are presented through a series of conventional indices (BIAS, POD and POFD) and, in addition, the Extreme Dependency Score (EDS) and the Base Rate (BS or 1-BS) have been used for keeping into account the vanishing of the indices as the events become rare. Results for long-period verification (the whole 2 yr) with increasing thresholds, seasonal trend (3 months period), diurnal error cycle and error maps, are presented. Results indicate that WRF has a general tendency of QPF overestimation for low thresholds and underestimation for higher ones, while COSMO-I7 tends to overestimate for all thresholds. Both models show a seasonal trend, with a bigger overestimation during summer and spring, while during autumn and winter the models tend to be more accurate.

Description: Publication year: 2011 Source: Procedia Environmental Sciences, Volume 6 Sarah Cornell, Cat Downy ESS2010 was the first Open Science Conference of the international collaborative initiative AIMES, and was convened and organized by QUEST, the UK's directed research programme for Earth System science. The conference showcased advances in Earth system modelling, deploying observations and process understanding to develop more quantitative and predictive understanding of the interactions of the climate system, the biosphere and the anthroposphere. These tools extend understanding of the system dynamics of biogeochemical cycles, and give perspectives on the relationships between climate, ecosystems and human needs. As Earth system science is a global research endeavour, and its remit has important societal and policy implications, a recurrent theme in the conference was the responsibility of scientists working on knowledge integration in the global environmental change context.

Description: Publication year: 2011 Source: Procedia Environmental Sciences, Volume 4 Ma Chun, Ju Mei-ting, Zhang Xiao-chun, Li Hong-yuan Analyses of energy consumption and carbon emissions in Tianjin are ways to understand the dynamics of developing cities in China. Using carbon emission calculation methodology recommended by IPCC, the amount of energy consumption and carbon emissions in Tianjin were calculated from 1995 to 2007. The results showed that the energy consumption structure in Tianjin relied on coal. Annual carbon emission was 26.37 million tons with growth of 4.48% per year; Sc (carbon emission per GDP) reduced year by year, and Se (carbon emission per energy consumption) decreased overall. We also proposed countermeasures to reduce carbon emissions from energy consumption.

Description: Publication year: 2011 Source: Procedia Environmental Sciences, Volume 10, Part B Yanhong Yan, Zhining Jia, Yulin Yang The polytetrafluroethylene (PTFE) polymer-based nanocomposites filled with nanoscale lamellar structure expanded graphite (nano-EG) and reinforced with different nanoparticles, such as nano-Al 2 O 3 , nano-copper, nano-SiO 2 and nano-TiO 2 , were prepared by using cold briquetting and hot-press sintering technologies. The quasi-static tensile experiments and dynamic mechanical thermal analysis (DTMA) were carried out. The results showed that the mechanical properties of these nanocomposites stronger depend on the variety of nanoparticles. Stress-displacement and stress relaxation curves indicate that theses composites are typical viscoelastic materials. However, due to the addition of nano-EG and other nano-particles, some composites showed relatively brittle to some extent. These research findings are believed to be helpful for providing practical guide in harsh environments.

Description: Publication year: 2011 Source: Procedia Environmental Sciences, Volume 11, Part C Liu Hongmin Crew's health and productivity is strongly affected by cabins’ thermal environment. This paper focuses on the numerical simulation of the indoor thermal environment in air-conditioned vessel cabins. The original airconditioning system of the cabin was analyzed. Three modified air-conditioning systems with different air-supply outlet locations and under-supply air-conditioning system were put forward for optimization. Air temperature, air velocity and PMV distribution were discussed under Airpak simulation. The results show that under-supply airconditioning system has good performance with little eddies and can contribute to energy saving. Indoor air temperature with under-supply air-conditioning system was 2∼4 lower than that °C with original air-conditioning system, leading to lower predicted mean vote (PMV).

Description: Publication year: 2011 Source: Procedia Environmental Sciences, Volume 8 Parvinder Singh Sandhu

Description: Publication year: 2011 Source: Procedia Environmental Sciences, Volume 10, Part C Xin Zhou, Ziru Lian, Jiangtao Wang, Liju Tan, Zhichao Zhao Estrogens (estrone, estradiol and estriol) and synthetic compound (ethynyl estradiol) in the water and sediment of Licun River-Jiaozhou Bay area in Qingdao were monitored. Estrogens in waters were concentrated using modified C- 18 SPE cartridges, and estrogens in sediments were extracted by liquid-solid extraction. Silane derivatives of the extracted and concentrated estrogens were analyzed by GC-MS. The concentration of estrogens ranged from ND (below the detection limit) to 180 ng/L in waters and ND to 10.8 colong/kg (dry weight) in sediment. The concentrations of estrogen in river water were higher than those in seawater during the monitoring periods. The distribution of estrogen concentration along Licun river suggested that estrogens were different with distance from the respective effluent sites. The highest concentrations were detected at station 5 which directly receives huge quantities of pollutants from adjacent rivers containing large amounts of farming and industrial wastewater.

Description: Publication year: 2011 Source: Procedia Environmental Sciences, Volume 9 Jean-Christophe Lata, Sébastien Barot, Gérard Lacroix The International Congress “Ecological Engineering; from concepts to applications”, Paris, was held on 2-4 December, 2009 [3]. These three days were dedicated to the exploration of new breakthroughs in ecological engineering and reflections on the way to develop the field and ground it on sound ecological and conceptual bases

Description: Publication year: 2011 Source: Procedia Environmental Sciences, Volume 6 Cat Downy, Sarah Cornell

Description: Publication year: 2011 Source: Procedia Environmental Sciences, Volume 11, Part B Shuzhou Wang, Bo Meng Neural networks with good nonlinear mapping abilities can be applied to build simulation model of helicopter. But they have some difficulties such as hardness of selecting network structure, slow convergence speed, local minimum, and over-fitting. To avoid above problems, a modeling method for dynamic nonlinear system based on support vector machine was proposed. This method was applied to build simulation model of helicopter. Compared with neural network model, SVM model possess some advantages such as simple structure, fast convergence speed and high generalization ability.