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The need for an improved control strategy for the operation of a wind-powered refrigeration system for the storage of apples was investigated. The results are applicable to other systems which employ intermittently available power sources, battery and thermal storage, and an auxiliary, direct current power supply. Tests were conducted on the wind-powered refrigeration system at the Virginia Polytechnic Institute and State University Horticulture Research Farm in Blacksburg, Virginia. Tests were conducted on the individual components of the system. In situ windmill performance were also conducted. The results of these tests have been presented. An improved control strategy was developed to improve the utilization of available wind energy and to reduce the need for electrical energy from an external source while maintaining an adequate apple storage environment. Ph. D.

Oligotrophic catchments with short spatey streams, upland lakes and peaty soils characterise northwest European Atlantic coastal regions. These catchments are important biodiversity refuges, particularly for sensitive diadromous fish populations but are subject to changes in land use and land management practices associated with afforestation, agriculture and rural development. Quantification of the degree of catchment degradation resulting from such anthropogenic impacts is often limited by a lack of long-term baseline data in what are generally relatively isolated, poorly studied catchments. This research uses a combination of palaeolimnological (radiometrically-dated variations in sedimentary geochemical elements, pollen, diatoms and remains of cladocera), census, and instrumental data, along with hindcast estimates to quantify environmental changes and their aquatic impacts since the late 19th century. The most likely drivers of any change are also identified. Results confirm an aquatic biotic response (phyto- and zooplankton) to soil erosion and nutrient enrichment associated with the onset of commercial conifer afforestation, effects that were subsequently enhanced as a result of increased overgrazing in the catchment and, possibly, climate warming. The implications for the health of aquatic resources in the catchment are discussed Environmental Protection Agency in Ireland (ILLUMINATE 2005-W-MS-40, P.McGinnity was supported by the Beaufort Marine Research Award in Fish Population Genetics funded by the Irish Government under the Sea Change Programme.

In the pursuit of creating efficient CdTe p-n homojunctions, we developed iodine (I) n-type doped CdTe using Cadmium Iodide (CdI2) as a dopant in varying concentrations (1018 cm-3, 1019 cm-3 and 1020 atoms·cm-3 target concentrations) in CdTe. Iodide doped crystals were grown using a Modified Vertical Bridgman furnace (MVB). Single crystals were characterized using XRD (X-Ray Diffraction), Hall effect, IR (Infrared) Microscopy, UV-VIS-NIR (Ultraviolet-Visible-Near infrared Spectroscopy) and FTIR (Fourier Transform Infrared Spectroscopy). Partners at the National Renewable Energy Laboratory (NREL) also provided data for Hall Effect and Two Photon Excitation Time Resolved Photoluminescence (2PE TRPL) of wafers and films. Photoluminescence mapping (PL mapping) was obtained from Klar scientific, and glow discharge mass spectrometry (GDMS) for purity and final doping concentration was obtained from the National Research Council Canada. Due to poor carrier properties in the crystals as-grown, two annealing treatments were explored, in either tellurium or cadmium vapor. Homojunctions were made at NREL by depositing n-type films from these crystals on p-type single crystals, CdTe:P grown and WSU. The n-type films were created using the close-space sublimation epitaxy (CSSE) process. Herein is reported the results of the grown CdTe:I crystals and, to a lesser extent, the properties of the CdTe:I thin films formed by CSSE.

The SmartBay NIAP fund was made available in 2012 through Dublin City University over a two year period to enable researchers to access the SmartBay Ireland National Test and Demonstration Facility in Galway Bay. Research proposals were invited for funding under a number of activity types that are in line with the objectives of the SmartBay PRTLI Cycle 5 programme. This fund provided small awards (typically €2-25K) to research teams through a national competitive process, which was open to all higher education institutions on the island of Ireland. There were both open and biannual calls. The SmartBay NIAP fund was established to enable researchers in academia and industry to access the SmartBay Ireland national test and demonstration infrastructure. Proposals to access the infrastructure were brief and required information on the researcher(s), a description of the proposed research and its potential impact to the research team arising from the access to SmartBay Ireland. Marine Institute

Cholera epidemics have a recorded history in eastern Congo dating to 1971. A study was conducted to find out the linkage between climate variability/change and cholera outbreak and to assess the related economic cost in the management of cholera in Congo.This study integrates historical data (20 years) on temperature and rainfall with the burden of disease from cholera in South-Kivu province, eastern Congo.Analyses of precipitation and temperatures characteristics in South-Kivu provinces showed that cholera epidemics are closely associated with climatic factors variability. Peaks in Cholera new cases were in synchrony with peaks in rainfalls. Cholera infection cases declined significantly (P<0.05) with the rise in the average temperature. The monthly number of new Cholera cases oscillated between 5 and 450. For every rise of the average temperature by 0.35 °C to 0.75 °C degree Celsius, and for every change in the rainfall variability by 10-19%, it is likely cholera infection risks will increase by 17 to 25%. The medical cost of treatment of Cholera case infection was found to be of US$50 to 250 per capita. The total costs of Cholera attributable to climate change were found to fall in the range of 4 to 8% of the per capita in annual income in Bukavu town.It is likely that high rainfall favor multiplication of the bacteria and contamination of water sources by the bacteria (Vibrio cholerae). The consumption of polluted water, promiscuity, population density and lack of hygiene are determinants favoring spread and infection of the bacteria among human beings living in over-crowded environments.

Solar tracking systems increase the electricity production by about 30% relative to fixed installations. A robust design of the mechanical system requiring less material than 100kg steel per kW nominal PV module power is essential to further improve the economics of PV tracker plants. The Solar Wings approach reaches this goal by using steel cables as a mounting system for the PV modules and benefits by the long-time experience of project partner BMF using steel cables in transportation systems such as ski-lift, funicular, aerial passenger lines. Tests with the first Solar Wings prototype in Switzerland passed successfully. The first 600 kW PV plant powered by the one axis Solar Wings tracking system will put into operation in December 2008 in Southern Germany. To maximize reliability and reduce maintenance costs only one electrical three-phase asynchronous motor is used to track 100kW PV modules. A two-axis tracking Solar Wings system will be available next year. Further development targets are low optical concentration by the use of planar mirrors mounted on a parallel axis to the PV module axis. PV modules and mirrors track individually and thus an increase of the electricity production of higher than 60% relative to fixed mounted installation is expected. First results of the measured increase of performance by individual tracking of the planar mirrors and the PV modules, performed on a small scale dish model, are reported. 23rd European Photovoltaic Solar Energy Conference and Exhibition, 1-5 September 2008, Valencia, Spain; 2790-2794

{"references": ["U.S. Energy Information Administration. \"How much energy is\nconsumed in residential and commercial buildings in the United States?\"\nAvailable at: http://www.eia.gov/tools/faqs/faq.cfm?id=86&t=1", "S. Darby, \"The effectiveness of feedback on energy consumption.\"\nEnvironmental Change Institute, University of Oxford, 2006. Available\nat: http://www.globalwarmingisreal.com/energyconsump-feedback.pdf.\nVisited: September 2015", "J. S. John, \"Putting energy disaggregation tech to the test,\" November,\n2013. Greentech Media. Available at:\nhttp://www.greentechmedia.com/articles/read/putting-energydisaggregation-tech-to-the-test.\nVisited: September 2015", "A. Zoha, A. Gluhak, M. A. Imran, S. Rajasegarar, \"Non-intrusive load\nmonitoring approaches for disaggregated energy sensing: a survey,\"\nSensors, vol. 12, no. 12, pp. 16838-16866, December 2012.", "G. W. Hart, \"Nonintrusive appliance load monitoring,\" in Proc. of the\nIEEE, vol. 80, pp. 1870-1891, December 1992.", "M. Baranski, J. Voss, \"Non-intrusive appliance load monitoring based\non Optical Sensor,\" IEEE Bologna PowerTech Conference, Bologna,\nItaly, June 2003. Available at:\nhttp://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1304732", "L. Farinaccio, R. Zmeureanu, \"Using a pattern recognition approach to\ndisaggregate the total electricity consumption in a house into the major\nen-uses,\" Elsevier, Energy and Buildings, vol. 30, no. 3, pp. 245-259,\nAugust 1999.", "J. M. Abreu, F. C. Pereira, P. Ferr\u00e3o, \"Using pattern recognition to\nidentify habitual behavior in residential electricity consumption,\"\nElsevier, Energy and Buildings, vol. 49, pp. 479-487, June 2012.", "C. Beckel, L. Sadamori, S. Santini, \"Automatic socio-economic\nclassification of households using electricity consumption data,\" in\nProc. of the 4th international conference on future energy systems, New\nYork, 2013, pp. 75-86.\n[10] H. Zhao, F. Magoul\u00e8s, \"A review on the prediction of building energy\nconsumption,\" Elsevier, Renewable and Sustainable Energy Reviews,\nvol. 16, no. 6, pp. 3586-3592, August 2012.\n[11] G. K. F. Tso, K. K. W. Yau, \"Predicting electricity energy consumption:\nA comparison of regression analysis, decision tree and neural networks,\"\nElsevier, Energy, vol. 32, no. 9, pp. 1761-1768, September 2007.\n[12] F. Farzan, S. A. Vaghefi, K. Mahani, M. A. Jafari, J. Gong, \"Operational\nplanning for multi-building portfolio in an uncertain energy market,\"\nElsevier, Energy and Buildings, vol. 103, pp. 271-283, September 2015."]} Energy disaggregation has been focused by many energy companies since energy efficiency can be achieved when the breakdown of energy consumption is known. Companies have been investing in technologies to come up with software and/or hardware solutions that can provide this type of information to the consumer. On the other hand, not all people can afford to have these technologies. Therefore, in this paper, we present a methodology for breaking down the aggregate consumption and identifying the highdemanding end-uses profiles. These energy profiles will be used to build the forecast model for optimal control purpose. A facility with high cooling load is used as an illustrative case study to demonstrate the results of proposed methodology. We apply a high level energy disaggregation through a pattern recognition approach in order to extract the consumption profile of its rooftop packaged units (RTUs) and present a forecast model for the energy consumption.

I derive and test predictions from the classic Mussa and Rosen (1978) second-degree price discrimination model using data from the United States clothes washer market. I find evidence consistent with price discrimination in the market response to energy efficiency policy changes. Concurrent with the effective dates of both the new 2004 and 2007 federal minimum efficiency and ENERGY STAR standards, within-model clothes washer prices dropped on average. The heterogeneous pattern of price reduction across market segments, and adjustments in the menu of products, were consistent with predictions from the price-discrimination model, and not with a perfectly competitive market.

Climate change is one of the preeminent policy issues of our day, and the social cost of carbon (SCC) is one of the foremost tools for determining the socially optimal policy response. The SCC is estimated using Integrated Assessment Models (IAMs), of which Nordhaus’ DICE is the oldest and one of the best respected. These numerical models capture the various steps in the climate and economic processes that translate a marginal unit of CO2 emissions into economic damage. While accuracy at each of these steps is necessary to precisely estimate the SCC, correct calibrating the climate damage function, which translates a temperature change into a percentage change in GDP, is critical. Calibration of the damage function determines which climate damages are included and excluded from the cost of carbon. Traditionally, Nordhaus calibrated the DICE damage function using a global damage estimate calculated by aggregating a series of region-sector specific damage estimates (Nordhaus and Boyer, 2000; Nordhaus, 2008). However, in DICE-2013, Nordhaus moved to calibrating the DICE damage function using a meta-analysis at the global scale (Nordhaus and Sztorc, 2013). This paper critiques this meta-analysis approach as it is currently applied and re-estimates the DICE-2013 damage function using up-to-date meta-analysis techniques to more accurately reflect climate damages and the uncertainty underlying them. This paper finds that DICE-2013 damage function significantly under-estimates climate damages by a factor of two to three. This is a working paper.