外文翻译 - 碳“智能足迹”案例研究.doc
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1、外文文献及译文文献、资料题目:Carbon Brainprint Case Study文献、资料来源:https:/dspace.canfiled.ac.uk/handle/1826/7000文献、资料发表(出版)日期:院 (部):专 业:班 级:姓 名:学 号:指导教师:翻译日期:外文文献:Carbon Brainprint Case Study The Carbon Brainprint project was supported by HEFCE under its Leading Sustainable Development in Higher Education program,
2、with support for case studies from Santander Universities. Research Councils UK and the Carbon Trust were members of the steering group, and the Carbon Trust advised on best practice in carbon footprint.SummaryIt is estimated that non-domestic buildings were responsible for 18% of UK total greenhous
3、e gas emissions (582 Mt CO2e/year) in 2010. Of non-domestic building emissions, 34% (36 Mt CO2e/year) was due to lighting, office equipment and catering and 46% (49 Mt CO2e/year) was due to heating.A team consisting of researchers at the University of Reading, the Universitys Facilities Management D
4、irectorate and Newera Controls Ltd. conducted two separate investigations to measure and demonstrate the potential for two important and complementary approaches in achieving energy efficiency and greenhouse gas emission reductions in buildings. The first focused on influencing user behavior, in an
5、office building on the main campus. The second considered an interventionist approach in an accommodation block at the Henley Business School using intelligent monitoring and control systems. To date, the first investigation has demonstrated a 20% saving in lighting, office equipment and catering en
6、ergy use, largely through user awareness and behavior change. The second has indicated that savings in heating energy of the order of 24% can be achieved by enhancement of legacy Building Management Systems (BMS) using a Building Energy Management System (BEMS). There is also scope for further savin
7、gs if the BEMS system is extended to other services such as lighting.General descriptionOver the past 20 years many different buildings have been labeled as “intelligent” (Clements- Croome, 2004). Industry has many established intelligent building solutions but finds it difficult to demonstrate and
8、prove their benefits. Intelligent sustainable buildings improve business value because they take into account environmental and social needs, and occupant wellbeing, which leads to improvement in work productivity. The ideal system links the building, systems within it and the occupants so they have
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