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Source: EIA, Energy Assessor Experiment in the 2012 Commercial Buildings Energy Consumption Survey. The 2012 CBECS microdata files now contain additional variables for energy consumption and expenditures, in total, by energy source, and by end use. EIA continues to work on end use modeling to complete the processing of the consumption and expenditures data. The remaining building characteristics tables (Tables B15 through B46) have just been released.
The first fourteen building characteristics Detailed Tables, an accompanying report, and survey methodology information - How was the 2012 CBECS buildings survey conducted?
EIA is concluding the second and final phase of CBECS data collection, the Energy Supplier Survey (ESS).
The next release will be the Building Characteristics Detailed Tables; the tables will be similar to those published for the 2003 CBECS. The next release will be the Building Characteristics Detailed Tables, which will be similar to those published for the 2003 CBECS.
The first stage of CBECS data processing is almost complete and EIA expects to release preliminary building characteristics estimates by early June. Westat has been transmitting cases to EIA every few weeks since May, and the data editing phase here at EIA is making good progress. The CBECS interviewers have been in the field for 3 months now, and they have already collected data for about 4,500 buildings all across the country.
Folders with materials for each building case assignment being put together.The start of the 2012 CBECS field period is just over a month away, and there is a lot of activity occurring right now in preparation! The CBECS interviewers will be trained in-depth to ensure that high quality data are collected. Meanwhile, back at Westat's home office in Rockville, MD, staff are working hard to make sure the behind-the-scenes logistics are in place. After reviewing 400+ suggestions from stakeholders, the proposed 2012 CBECS questionnaire is currently under review by the Office of Management and Budget (OMB). The field listers' hard work and attention to detail will ensure that the sample frame is accurate and complete. The 2007 round of CBECS was the first time in the 30 year history of CBECS that commercial buildings were surveyed about water consumption and characteristics.
Though most of the data collected as part of the CBECS 2007 cycle could not be released, EIA has been able to produce data on energy characteristics found in large hospitals in 2007. EIA and the CBECS survey contractor (Westat) are working hard right now to create the CBECS sampling "frame," which is the list from which buildings will be randomly selected to be interviewed.
The last steps before the questionnaire is finalized are to (1) write all the new questions according to best practices for survey design and then (2) program them into the CBECS survey instrument. We are hard at work reviewing all the great feedback on the 2012 questionnaire that we've received to date. Following the suspension of the 2011 Commercial Buildings Energy Consumption Survey (CBECS) given insurmountable funding constraints in FY 2011, EIA has resumed preparations to conduct the next Commercial Buildings Energy Consumption Survey (CBECS). EIA previously reported that the CBECS 2007 data do not meet EIA standards for quality, credible energy information. For further information, please contact Joelle Michaels, CBECS Survey Manager, or by phone at 202-586-8952; or Tom Leckey. The San Francisco Public Utilities Commission (SFPUC) today released a report that details the energy performance of 305 of San Francisco’s municipal facilities during calendar year 2011, including more than 37 million square feet of building area. In 2011, the 305 buildings analyzed used just under 3.5 million MMBtu of energy (electricity, natural gas and steam combined) and were responsible for 91,454 tons of CO2 equivalent emissions. As expected, some building types are bigger energy users per square foot than others, for example hospitals and museums (higher energy intensity) versus fire stations and libraries (lower energy intensity). San Francisco’s public buildings receive greenhouse-gas-free electricity from the Hetch Hetchy Power system. Tracking energy usage through benchmarking reveals which facilities are performing well, and helps agencies understand which should be prioritized for improvements.
San Francisco’s ordinance is unique among many green-building initiatives in that it provides owners with actual energy performance information on their buildings year-to-year, not modeled or hypothetical scenarios.
San Francisco is one of six cities and two states with building energy benchmarking ordinances, including Seattle, New York City, Austin, District of Columbia, Philadelphia and California and Washington State. How much of this Saved Energy was electricity related, and how much was Increased natural gas energy efficiency related.
Now that we’ve started benchmarking building for their energy use, how much longer before we start assessing the healthfulness of their indoor environments? Energy Manager Today is a leading energy management news and industry analysis resource, featuring daily trade publication news to keep corporate executives fully informed.
Energy management news, policy and industry analysis by Business Sector Media, LLC - Copyright ©2016, all rights reserved. The CBECS climate zones are groups of climate divisions, as defined by the National Oceanic and Atmospheric Administration (NOAA), which are regions within a state that are as climatically homogeneous as possible. A HDD is a measure of how cold a location was over a period of time, relative to a base temperature (in CBECS, 65 degrees Fahrenheit).
Similarly, a CDD is a measure of how hot a location was over a period of time, relative to a base temperature (65 degrees Fahrenheit).
Each building in the CBECS is assigned a CBECS climate zone based on the 30-year average (1971-2000) HDD and CDD (base 65 degrees Fahrenheit) for the NOAA climate division in which the weather station closest to the sampled building is located.
This study investigated the current energy use perceptions and practices of staff and students within five buildings at the University of Sheffield, UK. The UK Climate Change Act (2008) set legally binding targets for a national 34% reduction in greenhouse gas (GHG) emissions by 2020 (compared with 1990 levels). For the UoS, the abovementioned HEFCE target equates to a decrease in CO2 emissions from around 35,000 tonnes of CO2 (2005 level) to 19,000 tonnes of CO2 by 2020 [1]. The prominence of encouraging behaviour change within this report adds impetus to a number of schemes currently in operation at the UoS that are aimed at reducing energy consumption.
The present study sought to investigate the current energy use practices of staff and students within five buildings across the UoS campus using a focus group protocol (detailed below). The five buildings included within the investigation were the Crookesmoor Building (CB), the Graduate Research Centre (GRC), Regent Court (RC), Northgate House (NH) and the Humanities Research Institute (HRI) [2].
These five buildings were selected on the basis of the UoS’s on-going “Low Carbon Estates” project undertaken with BEAU (Building Environments Analysis Unit) in the school of Architecture (Altan, Douglas and Kim, in press) and represented a mix of building styles, ages and uses. Five qualitative focus groups were held with staff and post-graduate students within the selected buildings (one group per building).
These topics were selected as the basis for the discussion as they are known to influence energy use in shared building environments. Following the focus group discussions, a questionnaire was used to acquire basic demographic information from participants. Participants were asked to consider to what extent occupants are aware of the impact of their usage on the building’s consumption.
Across all groups it was felt that their awareness of energy usage was limited due to a lack of information from the University. This general lack of awareness of energy use appeared to be also motivated by a perceived lack of responsibility and ownership over energy consumption. The perceived lack of responsibility also appeared to be tied to the perception of others’ levels of concern with energy conservation. Participants were asked to consider how much control building occupants had over the energy they used within the building. This ‘sub-optimal’ energy use behaviour was seen as justifiable on the grounds that it was perceived to be the only direct means of regulating their thermal comfort.
It was felt the University should be doing more to lead conservation efforts and that energy conservation should be a more visible priority for the University. Participants also suggested that incentivising departments across campus to reduce their usage, either through offering an opportunity for them to spend any financial savings from energy conservation activities on new equipment for the department or by encouraging energy saving competitions between buildings (again with some kind of reward), could promote behaviour change. It was felt that technological change, such as installation of movement sensors for lighting or the replacement of inefficient electrical equipment, should come before (or at least at the same time) as behaviour change efforts. A priority technological issue that participants wished to be resolved was that of space heating and, more specifically, their desire for greater control over the heating. This study used focus groups to investigate the current energy use practices of staff and postgraduate students inhabiting five ‘under-performing’ buildings at the University of Sheffield (UoS). Several factors were found to relate to people’s intentions to conserve energy in University buildings. Desire for control:  The occupants in general felt they had very little control over how much energy they consumed in their buildings, particularly due to the automation of the heating system and the necessity of certain electrical equipment.
The multiple occupancy nature of the buildings further added to the feeling of little control.
Prioritise technological change: Priorities for the reduction of energy use initially centred on technological changes, to make equipment as efficient as possible and to increase the occupants’ ability to moderate the building temperature.
Many of the concepts raised by participants for not taking action would appear to mirror those within the Theory of Planned Behaviour (TPB, Ajzen, 1985); a general model used to link behavioural intentions with subsequent behaviour, as well as the more specific, heuristic model of environmentally relevant behaviour proposed by Matthies (2005).
The Heuristic model of environmentally relevant behaviour also considers norms as motivators of behaviour, both Personal Environmental norms (personal ideas about how one should act) and again, Social norms, as well as Other motives, which covers broader influences on an individual’s behaviour. Diffusion of responsibility and social loafing literatures could also provide some insight into the apparent inaction within these buildings. Importantly, by relating social psychological theories such as the TPB to the findings of this research, it becomes possible to speculate over how to implement changes that should stand to promote attitude consistent behaviour. Schemes such as the NUS ‘Green Impact’ were suggested as a potentially good vehicle for taking action by our participants. As highlighted in the present study, and argued by Fischer (2008) and Matthies (2005), the conscious decision process and subsequent re-evaluation of norms requires individuals to be provided with information and feedback so that they know the nature of the problem, the existing options and their respective consequences and impacts. The present research provides insight into the socio-technical reasons as to why University buildings, in this case at the University of Sheffield, might ‘underperform’ in terms of their energy consumption. The research indicates that participation in schemes like the NUS’ ‘Green Impact’ scheme and the provision of granular energy-use information to building occupants could stand to promote personal responsibility for taking action and make energy conservation normative, in turn encouraging both individual and collective action. The Journal of Sustainability Education (JSE) serves as a forum for academics and practitioners to share, critique, and promote research, practices, and initiatives that foster the integration of economic, ecological, and social-cultural dimensions of sustainability within formal and non-formal educational contexts. About the AuthorsColin Whittle: Combining a broad psychology background with his interest in the reduction of energy consumption and sustainable living, Colin Whittle's research is focused on the role of citizens in sustainable, future cities.
The Heart of Sustainability: Big Ideas from the field of Environmental Education and their Relationship to Sustainability Education or What’s love got to do with it? Left to right: Rex Britter, Carlo Ratti, and Prudence Robinson of urban studies and planning and the SENSEable City Laboratory used existing infrastructure in two MIT buildings to detect mismatches between human occupancy and consumption of electricity, chilled water, and steam.
Much energy is wasted heating and cooling indoor spaces when no one or almost no one is present.
In the search for energy-saving opportunities, commercial buildings are a good place to look. One challenge in commercial buildings is providing the “right” amount of heating and cooling. Past studies have examined the relationship between energy use and occupancy, but they have focused on single buildings and yielded inconclusive results. Three years ago, Ratti realized that the needed technology is already in place on the MIT campus.
For their initial study, the MIT team focused on the Sloan Building (E52) and the Ronald M. The curves below show data on energy use in the two buildings during eight days in winter 2006.


Hourly energy use for chilled water (for air conditioning), steam (for heat), and electricity during eight days in winter 2006 shows distinctly different profiles in two MIT buildings: the Sloan Building, E52 (left), and the Ronald M. Analysis of comparable data from spring, summer, and autumn shows little seasonal variation in patterns of electricity use in the two buildings. The next step was to examine the relationship between those energy-use patterns and variations in occupancy, using WiFi connections as a proxy.
Results of an analysis of the correlation between electricity consumption and occupancy based on the full two weeks of data from which the hourly energy consumption curves (previous image) were extracted.
Energy Information Administration, Commercial Buildings Energy Consumption Survey 2012, March 4, 2015.
The 2012 CBECS consumption and expenditures detailed tables are comprised of tables C1-C38, which cover overall electricity, natural gas, fuel oil and district heat consumption, and tables E1-E11, which disaggregate the same energy sources by end use (heating, cooling, lighting, etc.). These files contain untabulated records for 6,720 buildings so that data users can create custom tables that are not available through the pretabulated detailed tables.
The tables present electricity, natural gas, fuel oil and district heat consumption in total, per building, per square foot and by end use.
These files contain untabulated records for individual buildings so that data users can create custom tables that are not available through the pretabulated Detailed Tables. The data file is no longer split up into groups, so one download will provide users with all the CBECS variables.
The Energy Supplier Survey (ESS) was conducted between March and October 2014, collecting data from energy providers of buildings in the CBECS for which energy usage data was not obtained from the building respondent. The Energy Supplier Survey (ESS) was conducted between March and October 2014, collecting data from energy providers of buildings in the CBECS for which energy usage data was not obtained from the building respondent. Since March, EIA has been collecting data from energy providers of buildings in the CBECS for which energy usage data was not obtained from the building respondent. This preliminary data release includes building counts and total square footage by building activity, Census region and division, and building size category, and year of construction. We have evaluated the work remaining to ensure high data quality and adjusted the projected schedule of data releases as shown below. This preliminary data release includes building counts and total square footage by building activity, Census region and division, and building size category, and year of construction. In the last stage of building characteristics data release, the raw data files will be made available for public use. EIA is collecting data from energy providers of buildings in the CBECS for which energy usage data was not obtained from the building respondent. This preliminary data release will include building counts and total square footage by categories such as building activity, Census region, and building size category. In the next month, home office staff at Westat (the CBECS survey contractor) will continue to work on open cases via telephone interviews. The information collected in these interviews has already passed through and cleared two levels of automated data checks. In this follow-up survey, we will request energy use and cost data directly from the energy suppliers of electricity, natural gas, fuel oil, or district energy.
After working on the 2003 and the 2007 CBECS, this particular experienced interviewer was happy to be back: "This is my favorite project! They will begin their training with distance learning modules to acclimate them with the CBECS and energy concepts before they travel to the in-person training. Materials for each case assignment are carefully being put together, including maps and other forms that will allow the interviewer to find the sampled buildings. The survey is administered using a computerized survey instrument, but we've provided a paper representation of the questionnaire (240 pages) and a summary of the major changes (7 pages) here. For the details of how the CBECS sampling frame is constructed, see: How Will Buildings Be Selected for the 2012 CBECS? Green Building Council for hosting an informative 2012 CBECS Stakeholder Meeting on May 15, 2012.
The CBECS is administered by a trained interviewer using a laptop and a structured survey instrument.
As a result, EIA will not publish complete data tables from CBECS 2007 or release a public use file.
This translates into approximately $1 million less in energy costs in 2011 than the previous year. The Energy Star label has not yet created ratings categories for most other public building types. This benchmarking effort is part of the SFPUC’s larger energy efficiency and green building program. It also provides a national energy score so owners can see if their buildings are over or under-performing compared to similar buildings.
San Francisco is the first city on the West Coast to release municipal building energy use information following New York City and Washington D.C.
Each NOAA climate division is placed into one of five CBECS climate zones based on its 30-year average heating degree-days (HDD) and cooling degree-days (CDD) for the period 1971 through 2000.
The heating degree-day is the difference between that day's average temperature and 65 degrees if the daily average is less than 65; it is zero if the daily average temperature is greater than or equal to 65. The cooling degree-day is the difference between that day's average temperature and 65 degrees if the daily average is greater than 65; it is zero if the daily average temperature is less than or equal to 65. A series of focus groups with staff and post-graduate representatives from these buildings explored occupant awareness of energy consumption, perceived level of control over energy use, priorities for reduction and the perceived facilitators and barriers to reduction. UK Universities and other centres of Higher Education represent a sector where large reductions in carbon emissions are possible. To help meet this challenge, the UoS recently commissioned a carbon reduction report in order to identify where savings could be made.
Being a large, research-led University comprising a range of modern and more dated buildings, it is felt that issues raised by occupants within these buildings will to some extent reflect similar issues within similar Universities in theUK. The locations of these buildings on the UoS campus can be seen in Figure 1 and details of the building characteristics are presented in Table 1. The project had previously collected detailed data on the gas and electricity usage or each building and compared these with the CIBSE (2004, 2008) “good” and “typical” usage benchmarks for the type of workspaces present in each building.
Electricity Consumption of five University buildings against “Good” and “Typical” benchmarks. Participants were invited to participate via email and each received a gift voucher worth ?5.00 (approx. For example, it is often argued that building occupants need to first have an awareness of their energy use before efforts to increase efficiency and prevent wastage will be made (Zimmerman, 2008; Driedger, 2011).
This included a revised New Environmental Paradigm (NEP) scale (Dunlap, van Liere, Mertig and Jones, 2000), which was used as a quantitative indicator of participants’ environmental attitudes. That is, it was recognised that a propensity to take action was likely to relate to people’s personal views on energy conservation and their environmental values and that those with less of a concern would be less aware of and less concerned with their energy use. This would appear to relate to the fact that the general heating for the buildings is controlled centrally by the University an issue that, anecdotally, is a perennial issue within a number of buildings across the UoS campus. To this end, a perceived priority for the University was to provide more detailed and accessible information about energy usage, both the levels of consumption and methods to reduce consumption. It was stressed, however, that there should be no punishment for energy wastage, only rewards for reductions. It was reasoned that technological changes could lead to immediate returns in terms of energy saving, while behavioural change efforts could take time to yield such returns. Importantly, this desire was not necessarily indicative of a more general desire for personal control over the workplace environment, as there was some willingness for certain aspects of the environment to be remotely controlled. Participants discussed their awareness of energy consumption, their perceived level of control over energy use, their priorities for energy conservation and the perceived facilitators and barriers to action to reduce energy consumption. These included the perceived actions and opinions of other building users (and University authorities), and their perceptions of control over reducing energy consumption. Participants suggested that the University’s desires to reduce energy use across campus had not been successfully communicated to them, resulting in a lack of awareness about current energy use in their buildings and a general feeling that it is not their responsibility to manage it. At one level, this finding perhaps illustrates the need for the UoS to invest in more actively in its sustainability message in order to improve general awareness and the perceived importance of this issue. The suggestion that occupants are using electric heaters to supplement their building’s heating, despite the gas usage (for space heating) exceeding “typical” benchmarks, is worrying and adds impetus to the need for a greater understanding of occupants’ behaviours so as to limit this supplementary energy use where it is not warranted. Discussion of how to then change behaviour focused on the monitoring of energy use and incentivising reductions and rewarding conservation efforts. They would further appear to relate to established psychological theories such as diffusion of responsibility (e.g. Reference to this model can provide an explanation as to why people tended not to act in accordance with their pro-environmental attitudes (see NEP scores in Table 2). However, Matthies (2005) argues that these norms are only considered when a conscious behavioural decision must be made.
Both theories indicate that in group situations people are generally less likely to take action than when alone because, for instance, they do not assume personal responsibility for taking action (anticipating that someone else will do so) or because they believe that others will not put in the effort, so do not put in (as much) effort themselves.
Such schemes are likely to be beneficial on several fronts, such as problematizing wasteful energy use, and so challenging occupants’ habits, potentially causing a re-evaluation of their behaviour and norms through conscious decision processes (Matthies, 2005). The UoS has implemented systems within some buildings that can measure and feedback information on energy use at the building level (although this information is not currently accessible to all). The findings indicate that while building occupants tend to harbour pro-environmental attitudes, they do not readily act on these; often citing a lack of awareness about the energy consumption of the building and a lack of personal control over – and responsibility for – energy conservation. The overall effectiveness of such schemes will, however, hinge to upon appropriate communication with building occupants to promote a consciousness and understanding of the need for action and how to act. Occupants from the Crookesmoor building had been relocated to the Arts Tower (AT) at the time of completing our study (see Figure 1). Particular research interests include the adoption and use of sustainable technologies, the importance of environmental literacy and environmental citizenship and citizen engagement. Stauffer, MIT Energy InitiativeThis article first appeared in the Autumn 2012 issue of Energy Futures, the magazine of the MIT Energy Initiative. According to the US Energy Information Administration, commercial buildings account for nearly 20% of US energy consumption and 12% of the nation’s greenhouse gas emissions.
With people constantly coming and going, energy use is frequently either too high or too low for the number of people present.
Performing the needed large-scale field experiments could require installing a pervasive system of sensors to collect data on building operations and occupancy—an undertaking that would be both expensive and intrusive. The Institute has a network of more than 100,000 sensors that monitor the functioning of MIT’s building automation systems across campus and in turn reveal the per-building consumption of electricity, chilled water for cooling, and high-temperature steam for heating. The curves show hourly readings for electricity (green), chilled water (blue), and steam (red). In E52, electricity use shows pronounced recurring daily cycles, peaking during the daytime and returning to baseline levels at night and on weekends.
Chilled water use in E52 is relatively flat, while that in M37 shows considerable variation, including some daytime peaks.
As shown in the figures below, electricity consumption in both buildings demonstrates a significant positive correlation with occupancy rate: WiFi connections can account for 69% of the variation in electricity levels in building E52 and for 63% in building M37. In both MIT buildings, electricity use shows a significant positive correlation with occupancy rate (as measured by WiFi connections).
For example, they are developing new ways to present their findings so that people can quickly comprehend what’s involved.
For example, grouping offices together can prevent the loss of heat from occupied, heated spaces to unoccupied, unheated ones. Rex Britter, a DUSP research scientist in the lab, notes that encouraging people to change their habits may require some creative thinking. Each table has row categories for building floorspace, principal building activity, year constructed, and Census region and division.
Also, in addition to a CSV (comma delimited) file, the data are also available as a SAS data file. It should be noted that all the tables still contain preliminary data and many of the estimates are expected to change slightly when the consumption data are released near the end of this year.
Now the ESS energy usage data is being combined and processed with the energy usage from the building respondents.
The remaining building characteristics data releases will include two more groups of Detailed Tables and the public use microdata files. Now the ESS energy usage data will be combined and processed with the energy usage from the building respondents.
The Detailed Tables will be released in four groups; the table numbers shown below correspond to the 2003 CBECS tables.
The ESS will be completed this summer, at which point the ESS energy usage data will be combined and processed with the energy usage from the building respondents. Next will be the release of Building Characteristics Detailed Tables, which will be similar to those published for the 2003 CBECS. Now, we're checking all the open-ended responses and interviewer comments and running case-level edits that check for item consistency within questionnaires and help to verify that the energy usage data are accurate.


Many have worked on other large-scale surveys of various topics, while some are new to interviewing.
At the beginning of April, they will attend a four-day in-person training session in Los Angeles where they will learn the ins-and-outs of the CBECS interviewing process and the questionnaire. Each respondent will be provided a package of materials about the CBECS when they are first contacted. Because the computer automates all the question skip patterns, the survey is not as long or complicated as it appears! We had about 20 participants attending in-person and another 40 or 50 participants via webinar, representing a variety of industries – government, trade associations, real estate, energy consultants, advocacy groups, architects, engineers, laboratories, and equipment manufacturers. The questionnaire is programmed in-house by EIA using a survey processing language called Blaise. Green Building Council, ASHRAE, members of the Real Estate Roundtable (RER) such as Tishman Speyer, Simon Property Group, and Transwestern, the American Institute of Architects (AIA), EPA Energy Star, EPA Office of Water, National Renewable Energy Laboratory (NREL), Consortium for Energy Efficiency, Energy Performance Measurement Institute, San Diego State University, BuildingWise, Lutron Electronics, SRG Partnership, Performance Buildings Systems, Grundfos, National Trust for Historic Preservation, and Center for Environmental Innovation in Roofing.
EIA's status reports for CBECS 2012 will report on risk mitigation strategies undertaken to assure the delivery of CBECS 2012 data. The SFPUC has completed over 150 energy efficiency projects in municipal buildings, which are saving the City approximately $4.6M each year.
Audits then give owners specific direction as to which building energy systems need improving, if any, and clear analysis of the costs and benefits of making those improvements. For example, if the average temperature for a given day is 40 degrees, then the heating degree-days for that single day equal 25.
For example, if the average temperature for a given day is 80 degrees, then the cooling degree-days for that single day equal 15. Overall, personal awareness and attitudes about the need to conserve energy, the perceived actions and opinions of other users (including University authorities) and perceptions of control over the ease and opportunity to reduce energy consumption were perceived by occupants to relate to whether they would intend to conserve energy in University buildings. As such, in 2010 the Higher Education Funding Council for England (HEFCE) produced a sustainable development action plan for Higher Education (HE, 2010), setting a target for a 43% reduction on annual direct and indirect GHG emissions by 2020 (from a 2005 baseline). It was found that electricity performance in each building was lower than the ‘good’ benchmark (except in Regents Court, see Figure 2), while gas usage was higher than the ‘good’ benchmark in all buildings (except Regents Court, see Figure 3).
It is reasoned that the heat generated from these computers reduces the need for gas heating, whilst increasing the need for cooling from air conditioning units. Such user-related behaviour is a large component of the energy consumption of buildings but is difficult to account for in benchmark analysis (Hernandez, Burke and Lewis, 2008) and was not considered within Altan et al.’s (in press) benchmarking comparison. Equally, however, it has been shown that awareness alone might not translate directly into behaviour due to physical and psychological barriers to action (for a review, see Gifford, 2011). The data was second coded by an independent researcher who was not involved in the data collection.
It was also reasoned the visible introduction of more efficient technologies across campus might stand to generate awareness of the need for greater energy efficiency and more conservative use of energy. It was felt that providing information on usage would make people more aware of how much they are consuming and this may in turn lead to them to consider it to be their responsibility and promote conservation. In some cases, the NUS ‘Green Impact’ scheme was seen as a good vehicle for providing ‘regular’ building occupants with the required authority and autonomy to take more action in order to address energy use.
This preference for technological intervention could perhaps be seen as a by-product of the above issues of awareness, control and responsibility. In short, while participants did appear to have positive attitudes towards energy conservation, this attitude was accompanied by a (wrongful) perception that acting to conserve energy was not a priority for the University and could be negatively evaluated by other building users (unfavourable social norms) and a belief that that they did not have the ability or authority to facilitate any change (low perceived behavioural control). It is argued that most environmentally relevant behaviour, such as using electric heaters, is habitual and therefore repeated without consideration. There was evidence of both these view points within the focus group responses, with participants recognising that with multiple users of the building and work spaces, not everyone will feel it is their responsibility to save energy and may assume that someone else will be preventing energy waste.
Energy schemes can also help to promote a shared sense of responsibility for taking action (provided that participation is not delegated to an individual or small team), providing focussed and targeted energy saving goals, in addition to the provision of the agency and authority required to make and enforce change.
Our findings suggest that increasing the granularity of this feedback to map to particular rooms (or even individuals), could both satisfy the desire among staff and postgraduates for more information on their energy use and illustrate how much they contribute to the University’s energy use and, in principle, how much they could help the University save, therefore enabling conscious, pro-environmental, decision making. While it is likely that awareness of this campaign will increase with time, we would argue that additional channels of communication could be established to facilitate the aims of this campaign. These perceptions would appear to be augmented by the multiple-occupancy nature of the buildings and workspaces.
The focus of this study is on the user-perceptions of energy consumption and not necessarily on explaining the buildings’ objective energy performance. Their method uses existing infrastructure, namely, connections on MIT’s wireless network as an indicator of occupancy plus energy-use data gathered by sensors that monitor building operations. Yet studies have shown that continuously monitoring and adjusting operations and implementing a small number of energy-efficiency strategies could reduce that energy use by as much as 30%.
The campus also has a means of tracking occupancy: via its ubiquitous WiFi network, which includes more than 5,000 hotspots, almost one per room and hallway. All data are converted to a standardized unit—kilowatts—and then normalized by area—watts per square meter—so the datasets for the two buildings can be compared.
Electricity use in both buildings displays steady baseline consumption superimposed by daytime peaks on weekdays. Similar cycles appear in the M37 data, but the constant background level is about three times higher than in E52, perhaps because the M37 labs contain equipment that must operate continuously and therefore need a constant supply of electricity. In E52, there are two distinct usage patterns for chilled water and steam, one in winter and spring and another in summer and fall. In contrast, the correlation between chilled water and steam use and human occupancy is weak, with WiFi connections accounting for only a small amount of the observed variation. And at times, spaces can be designed to take advantage of “thermal seepage” through internal walls.
As an example, he describes a concept he calls the “weighted thermostat.” Picture a large meeting room. Now the ESS energy usage data is being combined and processed with the energy usage from the building respondents and end use estimates (the amount of energy used for heating, cooling, lighting, etc.) are being modeled.
The public use microdata files are building-level records provided for data users to perform individualized analyses.
The Energy Suppliers Survey (ESS) data collection begins in early spring: those data will provide energy usage and cost data for about half the CBECS cases. In two recent four-day training sessions, the interviewers were thoroughly trained on all the steps necessary to complete an interview: determining if the building is in scope for the survey, making an appointment, gaining cooperation, using the computer to conduct the interview, and scanning utility bills.
The CBECS contractor, Westat, is hiring about 300 field interviewers who will visit each of these buildings to determine eligibility for the CBECS. They will get lots of practice with the survey instrument before they hit the streets as soon as they return home from training.
Among other items, this package contains worksheets to help the building respondents prepare for the interview and a list of organizations that have encouraged participation in the CBECS .
EIA presented our planned changes to the 2012 CBECS questionnaire and took comments from the audience on each questionnaire section.
However, in some of the Western states, the NOAA climate divisions (on which the CBECS climate zones are based) are defined more by drainage basins than by counties, and so sometimes there is more than one climate zone per county. Recommendations for encouraging energy conservation focus on engendering greater occupant responsibility for conservation by providing a clear conservation message, participating in energy reduction schemes and providing greater energy usage information.  Few papers have investigated occupant understanding of energy use in UK University and Higher Education buildings, despite large reduction targets in the sector. Critically, the HEFCE has made 40% of each HE institution’s capital funding dependent on their successful adherence to the CIF 2 (Capital Investment Framework 2, 2009), requiring the demonstration of clear carbon management plans and progress in line with the sector level targets. Thus, each building was underperforming in terms of either its gas or electricity consumption compared with what would be expected as ‘good’ for the building type [3]. Therefore, within the current research we investigated occupant perceptions of energy consumption in order to increase understanding of how energy is considered and consumed within these University buildings. Higher scores on the NEP items indicate a more ecocentric orientation with a greater commitment to the preservation of natural resources, whereas lower scores indicate an anthropocentric orientation, suggesting a commitment to exploitation of natural resources.
However, it was also argued that if responsibility for the ‘Green Impact’ was delegated to one person or group that this could backfire and reduce people’s perceived personal responsibility for taking action.
According to the TPB, this lack of apparent support for taking action to conserve energy and the perceptively (and in some instances actual) low ability to act would have reduced their intentions to act upon their pro-environmental attitudes.
In order for new norms to be formed, a conscious decision process must be engaged, where the individual becomes conscious of (1) that there is a problem (i.e. For instance, Lehrer and Vasudev (2011) are investigating the use of a web-based social network with a forum where staff and managers can contribute discussions of energy issues. While the low use of electricity in four of the five buildings is encouraging, this needs to be considered alongside the higher than average levels of gas used (and vice versa for Regents Court).
Analysis of 2006 data from two MIT buildings shows that two-thirds of the variation in electricity levels corresponds to changing occupancy levels. Students flood into the hall for class, and then after 90 minutes the hall is empty—but still being heated or cooled. In 2005, when the campus-wide wireless network was relatively new, Ratti and his colleagues performed iSPOTS, a project investigating how WiFi was changing the working habits of the MIT community. But in academic buildings, people are more likely to enter and exit at irregular times, occupancy can vary widely over short periods, and there may be long stretches of time when buildings are almost—but not quite—empty.
M37 is predominantly composed of laboratories, while E52 is a more typical working space with classrooms, offices, and open reception areas. The final curve (black) shows outdoor air temperatures measured at Logan International Airport in Boston.
But chilled water and steam consumption in the two buildings show differing trends, sometimes but not always correlating to changes in outdoor temperatures. In E52, steam use rises and falls frequently, sometimes correlated with outdoor temperature, but the overall range of values encompassed is far smaller than in the M37 data. In M37, similar patterns appear in steam use, but levels of chilled water consumption show no such seasonal difference. Even so, 69% of the variation in the Sloan Building (E52) and 63% of that in the McNair Building (M37) can be accounted for by changes in occupancy.
For instance, that continuously heated lecture hall can be surrounded by heavily used offices so that someone benefits from the warm air even when the lecture hall is empty. When many people are present, they can adjust the thermostat over a wide range to get the room to a comfortable temperature.
Detailed examples of how to perform these calculations can be found in an extensive User's Guide. The data are inoculated so that it is not possible to identify any individual building on the file.
Some of their previous or current other occupations include: accountants, firefighters, social workers, interior designers, caterers, military personnel, teachers, tax preparers, government workers, geological technicians, sales people, certified energy managers, dairy farmers, electrical contractors, DJs, architects, parents, and grandparents.
There are an additional 461 segments that were listed in 2003 that will also be part of the area frame.
EIA will provide regular project status reports to the public throughout the course of the project. This paper recognises the importance that staff and student engagement will have in the successful achievement of these targets and explores their insights and perceptions. And, more generally, perceptions of personal control over workplace conditions (or lack thereof) are known to influence people’s energy usage (see Maniccia, Rutledge, Rea & Morrow, 1999).
The main themes that emerged in response to each of the main questions are summarised and discussed below.
Such systems might not only help Higher Education Institutions to communicate and share ideas but could also prove effective in assessing the broader penetration and effectiveness of existing or planned campaigns.
A legacy of that project is a rich historical database on WiFi use as well as evidence that WiFi connections are a good indicator of where people are and when. Drawing on the iSPOTS project, the researchers gathered detailed data on WiFi use in those buildings in 2006. But if only a few people are present, their ability to regulate the temperature would be more restricted. And finally, the CBECS questionnaire has been annotated to be used with the public use files.
The skills that they all have in common that make them effective interviewers are the ability to talk to respondents, an eye for detail, and a talent for organization.
The MIT team suggests changes in how commercial buildings are designed and used that may help bring energy and people together in time and space.
And aided by MIT’s Department of Facilities, they obtained the 2006 energy consumption data they needed. Only if the individuals’ become conscious of these factors will they begin to (re)evaluate the norms on which they based their behaviour. In the present sample, there is a suggested lack of awareness among occupants about both the problem (i.e. Combined with a perceived lack of control (as discussed above), according to Matthies (2005), this should encourage habitual behaviours to dominate, which could help explain the reported slow the pace of pro-environmental behaviour change.



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