A panel model for predicting the diversity of internal temperatures from English dwellings

Using panel methods, a model for predicting daily mean internal temperature demand across a heterogeneous domestic building stock is developed. The model offers an important link that connects building stock models to human behaviour. It represents the first time a panel model has been used to estimate the dynamics of internal temperature demand from the natural daily fluctuations of external temperature combined with important behavioural, socio-demographic and building efficiency variables. The model is able to predict internal temperatures across a heterogeneous building stock to within ~0.71°C at 95% confidence and explain 45% of the variance of internal temperature between dwellings. The model confirms hypothesis from sociology and psychology that habitual behaviours are important drivers of home energy consumption. In addition, the model offers the possibility to quantify take-back (direct rebound effect) owing to increased internal temperatures from the installation of energy efficiency measures. The presence of thermostats or thermostatic radiator valves (TRV) are shown to reduce average internal temperatures, however, the use of an automatic timer is statistically insignificant. The number of occupants, household income and occupant age are all important factors that explain a proportion of internal temperature demand. Households with children or retired occupants are shown to have higher average internal temperatures than households who do not. As expected, building typology, building age, roof insulation thickness, wall U-value and the proportion of double glazing all have positive and statistically significant effects on daily mean internal temperature. In summary, the model can be used as a tool to predict internal temperatures or for making statistical inferences. However, its primary contribution offers the ability to calibrate existing building stock models to account for behaviour and socio-demographic effects making it possible to back-out more accurate predictions of domestic energy demand

The Energy Costs of Historic Preservation

We explore the impact of historical preservation policies on domestic energy consumption. Using panel data for England from 2006 to 2013 and employing a fixed effects strategy, we document that (i) rising national energy prices induce an increase in home energy efficiency installations and a corresponding reduction in energy consumption and (ii) this energy saving effect is significantly less pronounced in Conservation Areas and in places with high concentrations of Listed Buildings, where the adoption of energy efficiency instal lations is typically more costly and sometimes legally prevented altogether. The energy costs of preservation are substantial

Thermal and Lighting Consumption Savings in Classrooms Retrofitted with Shading Devices in a Hot Climate

Most educational buildings in southern Spain do not meet current energy requirements as weak thermal envelopes and the lack of cooling systems lead to severe discomfort in classrooms, especially when temperatures are above 30 °C. Given that global warming is expected to worsen this situation in coming decades, one of the first steps to be taken is to protect window openings from high levels of solar radiation by adding shading devices to reduce indoor temperatures and improve visual comfort. The aim of this research is to evaluate the reduction in thermal and lighting consumption in a classroom where a solar protection system in the form of an egg-crate shading device was installed. Two classrooms—one with an egg-crate device and another with no shading system—were monitored and compared for a whole year. The use of an egg-crate device in these classrooms reduced indoor operative temperatures during warmer periods while also improving indoor natural illuminance levels. Moreover, annual electric air conditioning consumption decreased by approximately 20%, with a 50% reduction in electric lighting consumption. These savings in electricity were largely conditioned by the use patterns observed in these ambient systems.Spanish government BIA2014-53949-RMinistry of Economy and Competitiveness, Spanish GovernmentEuropean Regional Development Fun

Potential Climatic Impacts and Reliability of Very Large-Scale Wind Farms

Abstract and PDF report are also available on the MIT Joint Program on the Science and Policy of Global Change website (http://globalchange.mit.edu/).Meeting future world energy needs while addressing climate change requires large-scale deployment of low or zero greenhouse gas (GHG) emission technologies such as wind energy. The widespread availability of wind power has fueled legitimate interest in this renewable energy source as one of the needed technologies. For very large-scale utilization of this resource, there are however potential environmental impacts, and also problems arising from its inherent intermittency, in addition to the present need to lower unit costs. To explore some of these issues, we use a threedimensional climate model to simulate the potential climate effects associated with installation of wind-powered generators over vast areas of land or coastal ocean. Using windmills to meet 10% or more of global energy demand in 2100, could cause surface warming exceeding 1oC over land installations. In contrast, surface cooling exceeding 1oC is computed over ocean installations, but the validity of simulating the impacts of windmills by simply increasing the ocean surface drag needs further study. Significant warming or cooling remote from both the land and ocean installations, and alterations of the global distributions of rainfall and clouds also occur. These results are influenced by the competing effects of increases in roughness and decreases in wind speed on near-surface turbulent heat fluxes, the differing nature of land and ocean surface friction, and the dimensions of the installations parallel and perpendicular to the prevailing winds. These results are also dependent on the accuracy of the model used, and the realism of the methods applied to simulate windmills. Additional theory and new field observations will be required for their ultimate validation. Intermittency of wind power on daily, monthly and longer time scales as computed in these simulations and inferred from meteorological observations, poses a demand for one or more options to ensure reliability, including backup generation capacity, very long distance power transmission lines, and onsite energy storage, each with specific economic and/or technological challenges.This study received support from the MIT Joint Program on the Science and Policy of Global Change, which is funded by a consortium of government, industry and foundation sponsors

Developing LCA-based benchmarks for sustainable consumption - for and with users

This article presents the development process of a consumer-oriented, illustrative benchmarking tool enabling consumers to use the results of environmental life cycle assessment (LCA) to make informed decisions. Active and environmentally conscious consumers and environmental communicators were identified as key target groups for this type of information. A brochure presenting the benchmarking tool was developed as an participatory, iterative process involving consumer focus groups, stakeholder workshops and questionnaire-based feedback. In addition to learning what works and what does not, detailed suggestions on improved wording and figures were obtained, as well as a wealth of ideas for future applications

The drivers of Chinese CO2 emissions from 1980 to 2030

China's energy consumption doubled within the first 25 years of economic reforms initiated at the end of the 1970s, and doubled again in the past 5 years. It has resulted of a threefold CO2 emissions increase since early of 1980s. China's heavy reliance on coal will make it the largest emitter of CO2 in the world. By combining structural decomposition and input–output analysis we seek to assess the driving forces of China's CO2 emissions from 1980 to 2030. In our reference scenario, production-related CO2 emissions will increase another three times by 2030. Household consumption, capital investment and growth in exports will largely drive the increase in CO2 emissions. Efficiency gains will be partially offset the projected increases in consumption, but our scenarios show that this will not be sufficient if China's consumption patterns converge to current US levels. Relying on efficiency improvements alone will not stabilize China's future emissions. Our scenarios show that even extremely optimistic assumptions of widespread installation of carbon dioxide capture and storage will only slow the increase in CO2 emissions