679 research outputs found

    Differentiation and dynamics of competitiveness impacts from the EU ETS

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    We summarises the main factors that differentiate impacts of the EU ETS on profitability and market share. By examining sampling a range of sectors, we present some simple metrics and indicators to help judge the nature of potential impacts. We also consider briefly the mitigation response to these impacts by sectors, and how they may evolve over time. The broad conclusion confirms the aggregate findings presented in the existing literature - most participating sectors are likely to profit under the current ETS structure out to 2012 at the cost of a modest loss of market share, but this may not hold for individual companies and regions. The period 2008-12 can assist participating sectors to build experience and financial reserves for longer term technology investments and diversification, providing the continuation and basic principles of the EU ETS post-2012 is quickly defined and incentives are in place for sectors to pursue this.Emissions trading, industrial competitiveness, spillovers, allowance allocation, perverse incentives.

    Benchmark analysis of forecasted seasonal temperature over different climatic areas

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    From a long-term perspective, an improvement of seasonal forecasting, which is often exclusively based on climatology, could provide a new capability for the management of energy resources in a time scale of just a few months. This paper regards a benchmark analysis in relation to long-term temperature forecasts over Italy in the year 2010, comparing the eni-kassandra meteo forecast (e-kmf ® ) model, the Climate Forecast System–National Centers for Environmental Prediction (CFS-NCEP) model, and the climatological reference (based on 25-year data) with observations. Statistical indexes are used to understand the reliability of the prediction of 2-m monthly air temperatures with a perspective of 12 weeks ahead. The results show how the best performance is achieved by the e-kmf ® system which improves the reliability for long-term forecasts compared to climatology and the CFS-NCEP model. By using the reliable highperformance forecast system, it is possible to optimize the natural gas portfolio and management operations, thereby obtaining a competitive advantage in the European energy market

    Effects of Model Horizontal Grid Resolution on Short- and Medium-Term Daily Temperature Forecasts for Energy Consumption Application in European Cities

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    A short-term forecast of energy consumption is affected by different factors related to the demand in residential, commercial, thermoelectric, and industrial sectors. This demand can be strongly constrained by weather variables, especially temperatures, whose forecast may be very useful to predict the balances between supply and demand, minimizing the risk of price volatility. Energy companies use the relationship between meteorological forecast output and energy request to provide an effective scheduling of national gas and power grids and reduce operational costs in critical periods. This work reports a comparison analysis for short- and medium-term daily temperature forecasts during the period 2013-2014 by using the weather model e-kmf™ (eni-kassandra meteo forecast), currently adopted in gas and power applications where meteorological output has a key role. This weather forecast system uses different models and initial data to develop probabilistic predictions from a perspective of eleven days ahead. In particular, a set of model runs with horizontal grid spacing of 5.5, 8, 13, and 18 km with the same domain size are undertaken to assess the sensitivity of temperature to horizontal resolutions. A nonlinear Kalman filter has been also applied to postprocess forecasted data in eight European cities (Milano, Roma, Torino, Napoli, Munich, Paris, Brussels, and London). Filtered forecasts over these cities have been compared to local observations taken from SYNOP (surface synoptic observations) and METAR (meteorological Aerodrome Report) stations. Skill scores of performance have been used to generally assess the forecast reliability up to day +11. In order to understand the sensitivity to the horizontal resolution, investigations have been carried out even during four specific periods of two weeks with stable and unstable weather conditions

    Quality of anticholinergic burden scales and their impact on clinical outcomes: a systematic review.

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    Older people are at risk of anticholinergic side effects due to changes affecting drug elimination and higher sensitivity to drug's side effects. Anticholinergic burden scales (ABS) were developed to quantify the anticholinergic drug burden (ADB). We aim to identify all published ABS, to compare them systematically and to evaluate their associations with clinical outcomes. We conducted a literature search in MEDLINE and EMBASE to identify all published ABS and a Web of Science citation (WoS) analysis to track validation studies implying clinical outcomes. Quality of the ABS was assessed using an adapted AGREE II tool. For the validation studies, we used the Newcastle-Ottawa Scale and the Cochrane tool Rob2.0. The validation studies were categorized into six evidence levels based on the propositions of the Oxford Center for Evidence-Based Medicine with respect to their quality. At least two researchers independently performed screening and quality assessments. Out of 1297 records, we identified 19 ABS and 104 validations studies. Despite differences in quality, all ABS were recommended for use. The anticholinergic cognitive burden (ACB) scale and the German anticholinergic burden scale (GABS) achieved the highest percentage in quality. Most ABS are validated, yet validation studies for newer scales are lacking. Only two studies compared eight ABS simultaneously. The four most investigated clinical outcomes delirium, cognition, mortality and falls showed contradicting results. There is need for good quality validation studies comparing multiple scales to define the best scale and to conduct a meta-analysis for the assessment of their clinical impact

    Effects of temperature on flood forecasting: analysis of an operative case study in Alpine basins

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    Abstract. In recent years the interest in the forecast and prevention of natural hazards related to hydro-meteorological events has increased the challenge for numerical weather modelling, in particular for limited area models, to improve the quantitative precipitation forecasts (QPF) for hydrological purposes. After the encouraging results obtained in the MAP D-PHASE Project, we decided to devote further analyses to show recent improvements in the operational use of hydro-meteorological chains, and above all to better investigate the key role played by temperature during snowy precipitation. In this study we present a reanalysis simulation of one meteorological event, which occurred in November 2008 in the Piedmont Region. The attention is focused on the key role of air temperature, which is a crucial feature in determining the partitioning of precipitation in solid and liquid phase, influencing the quantitative discharge forecast (QDF) into the Alpine region. This is linked to the basin ipsographic curve and therefore by the total contributing area related to the snow line of the event. In order to assess hydrological predictions affected by meteorological forcing, a sensitivity analysis of the model output was carried out to evaluate different simulation scenarios, considering the forecast effects which can radically modify the discharge forecast. Results show how in real-time systems hydrological forecasters have to consider also the temperature uncertainty in forecasts in order to better understand the snow dynamics and its effect on runoff during a meteorological warning with a crucial snow line over the basin. The hydrological ensemble forecasts are based on the 16 members of the meteorological ensemble system COSMO-LEPS (developed by ARPA-SIMC) based on the non-hydrostatic model COSMO, while the hydrological model used to generate the runoff simulations is the rainfall–runoff distributed FEST-WB model, developed at Politecnico di Milano
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