We hope you'll find answers to your questions here! Please also check out the extensive tooltips spread throughout this site (for helpful info, just hover your mouse pointer over any "i" in a circle).
The application of data filters is limited by the number of data points. Have you investigated the use of normalization techniques so that the entire data set can be utilized to provide a more “apples to apples” comparison?
Yes, as of October 2022 the LBT now accepts non-US buildings and currencies. At the launch of the internationalized tool in October 2022 the peer group database is still comprised only of US buildings, but you are now able to compare your lab buildings with the peer group regardless of where your facility is located. As more international facilities are entered into the database, you’ll be able to compare with facilities around the world.
As of October 2022, the LBT uses 2020 EGRID factors for electricity for US buildings, using the average values by state. For international buildings, the tool uses values from Our World in Data. For natural gas, fueld oil, district hot water, and chilled water we use the Energy Star 2022 conversion factors with a modification for CHW to scale by the electricity GHG emissions factor for the building’s location. This approach is based on the assumption that the majority of district HW is generated through natural gas combustion, and the majority of district chilled water is generated using electric chillers.
As of October 2022, the LBT is using ASHRAE Standard 169-2021 to determine climate zones for buildings. The closest listed climate zone location to the entered address is used to assign the climate zone for each building. Note that the climate zone designation for many global zones was updated versus previous years, so some buildings’ calculated climate zones have changed. Also note: buildings have the same climate zone for all entered years of data in the LBT.
Exchange rates for 1 September 2022 were used (taken from currencyfreaks.com); these are not “live” values, but they may be updated periodically.
Regional factors are currently only available for the US: as of October 2022, the LBT uses state-by-state average GHG emissions factors from EGRID. For non-US countries, only national averages are used at present but this may be updated in future. We do not currently offer users the option to enter custom GHG factors for their campus central plants or to reflect specific power purchasing arrangements, but this may also be accommodated in future.
Site-to-source conversion factors are not readily available for all countries and so these were not included in the international expansion. For US buildings, the LBT uses Energy Star 2018 national average conversion factors. The industry is moving towards using GHG intensity in place of Source EUI, and so our recommendation is to use GHG intensity where a metric of primary energy consumption comparison is needed.
The metric or SI system of units is the world's most widely used system of measurement. Common metric units used in the building energy industry include kWh for all types of energy, square meters for areas, and kilograms for CO2 emissions.
Imperial or US units are used chiefly in the US, but are also sometimes used alongside metric units in some other countries. Common US units used in the building energy industry include Btus for many energy quantities, square feet for areas, and lbs for CO2 emissions.
Use the dropdown menu marked with a globe icon (top right of each page) to switch between Imperial/US and Metric/SI options. The page will reload when you change the unit selection. If you are logged in, your units preference will be saved to your LBT account profile.
The OP module goes beyond energy benchmarking to allow you to compare the operational practices and policies at your buildings with those of your peers. The module includes 23 questions, such as 'Does this building have an energy manager?' and 'Are filtering fume hoods in use?' The pie charts on the Operational Practices page let you see how your answers to these questions compare to those of your peers.
The Operational Practices tab works in the same way as the Benchmark Analysis tab. Select a question to which you'd like to see the answers, and then use the filters at the right to select buildings that are similar to yours. Only buildings that meet the filter conditions AND have an answer to the selected question will appear on the pie charts. Mouse over the pie charts to see percentages and other info. Your own buildings are identified by name in the table underneath the pie chart (click on the down arrows on the right of the rows to expand). For your own buildings, please answer the Operational Practices fields via the Your Buildings tab of the LBT. The OP fields are labeled with a blue 'OP' symbol on the Edit/Add building pages. If you provided data via the OP Survey prior to the launch of the OP Module, your data has been transferred into Your Buildings and can be accessed from there.
A set of 23 priority fields can be viewed via the pie charts. Please click on the dropdown menu labeled 'Select Property to Plot' to see the list and select a field of interest to you.We hope to expand the number of database fields viewable via the OP interface in future.
Many of the OP fields are new as of 2020 and so only a fraction of building owners have so far entered data for them. Much of the data used to pre-populate the fields prior to launch came from a limited number of owners, each with relatively large numbers of buildings. Some of the OP fields were already open and collecting data prior to release of the new module, but as optional (non-mandatory) fields, fewer users tend to fill them out when they add their building data to the LBT. You can help to increase the population of buildings in the OP Module by answering the OP questions for your own buildings (via the Your Buildings tab)!
All of the Operational Practices questions are included in the data entry forms in the Your Buildings tab. The OP fields are marked with a blue 'OP' sign. One important thing to note for answering yes/no OP questions is that you should only leave the field unanswered if you do not know the answer to the question. If the answer is no, please select N. Unanswered questions are ignored by the pie charts and are not taken to mean 'no.'
If you don't know the answer, just leave that field blank or unanswered -- no problem.
Yes. Please note that you still need to add a data year to indicate for which year your answers are valid. You may see a warning about low energy usage, but you should be able to save your data and to use the OP Module with no trouble.
The responses to OP questions are stored in the same place as the responses to the other LBT questions: in the LBNL Building Performance Database (BPD).
Yes. In this case you will see only one pie chart (the peer group chart). If you do own or manage buildings, we encourage you to enter your buildings' data via the Your Buildings tab. This will allow you to compare your practices more directly with those of your peers, and will also help us to build the anonymized peer group database for others to compare to.
There are a few different ways to do this, but they all happen on the Utility Usage tab of an LBT building, once you’ve set up a link between your LBT and Portfolio Manager accounts and a link between each building and its corresponding Portfolio Manager facility. Please see the Setup Instructions page for a step-by-step guide.
Setting up the connection is simple and involves just a few steps. Please see the Setup Instructions page for a step-by-step guide.
Once you’ve linked your Portfolio Manager and LBT accounts, linking individual buildings is simple and involves just a few more steps. Please see the Setup Instructions page for a step-by-step guide.
Yes, just follow the same linking procedure for each Portfolio Manager account.
No, you can only connect each Portfolio Manager account to one LBT account.
No, LBT will not backfill past years. LBT will try to download any data with Data Year equal to the current calendar year, and will then download data following the end of each future data year. The LBT’s Portfolio Manager Connection module will never automatically overwrite any data you manually entered for your buildings. For any other years, you can backfill data manually by adding a data year via the Your Buildings tab and importing energy usage data from the Utility Usage tab for the data year. See also below for some examples of data import timing.
Yes. Your data will never be automatically overwritten by the LBT, and you can always enter your own utility usage data or overwrite data imported from Portfolio Manager.
If you create a new building from a Pending Building in the Portfolio Manager tab, a few other data fields will be imported. These include building name, address, and gross floor area. This is the only case in which data other than annual utility usage is imported from Portfolio Manager.
Fuel types not included in the LBT list are imported from PM (in kBtu) and summed. These then appear in the Other Fuels LBT data field (in MMBtu).
Fuel oil usage in Portfolio Manager is summed across grades (all in kBtu) and imported into the Fuel Oil LBT data field. Fuel oil in LBT can be displayed in MMBtu or gallons (using a conversion factor of 0.138 MMBtu/gal, typical for Fuel Oil #2), but is always saved in MMBtu. For this reason the specific MMbtu/gal factor does not affect the PM data import.
You can only import annual data at this time, but note that you can choose the End Month that works with your accounting system (if you don’t use calendar years).
LBT will start trying to import data following the end of each data year, i.e. immediately following the end of the End Month you entered for the building. If Portfolio Manager does not yet contain a full year of data for that year, no data will be imported and LBT will continue trying (once per day) to import data. Note: where data years are split across calendar years, the Data Year is taken to be the year containing more months.
Two examples of auto data import timing are given below:
No. At this time, data transfer is only from Portfolio Manager to LBT.
Other than energy data, there’s just not that much overlap in fields collected by these two tools. Most of the other fields in Portfolio Manager are not particularly helpful for benchmarking lab facilities against each other, so there’s little point in importing them to LBT. And most of the fields that LBT needs in order for you to meaningfully benchmark lab buildings (e.g. number of fume hoods, types of lab space) aren’t fields that are currently collected by Portfolio Manager. Note: If you create a new building from a Pending Building in the Portfolio Manager tab, a few other data fields will be imported. These include building name, address, and gross floor area. This is the only case in which data other than annual utility usage is imported from Portfolio Manager.
Visit the Your Buildings tab in LBT. Buildings with a Portfolio Manager link have an additional "Edit Settings" button at the right of the table. Alternatively, visit the Portfolio Manager tab of the LBT, where linked buildings are listed under the Connected Properties sub-tab.
From the Connected Properties tab on the Portfolio Manager page, click the Unlink Property button. Any building data previously imported from Portfolio Manager will remain in the LBT, but the connection will be broken.
The link to Portfolio Manager will also be broken.
If you cancel the connection via Portfolio Manager, the link will disappear from LBT too. If you don’t immediately see the link disappear from the Your Buildings tab, please visit the Portfolio Manager tab of the LBT. This will cause the data to update and you should then see the link disappear from the Your Buildings tab too.
Deleting a linked building from Portfolio Manager has the same effect as cancelling the connection from Portfolio Manager: the link will disappear from LBT. If you don’t immediately see the link disappear from the Your Buildings tab, please visit the Portfolio Manager tab of the LBT. This will cause the data to update and you should then see the link disappear from the Your Buildings tab too.
To get the most out of the Actionable Insights module, you should enter as much data as possible on your buildings via the Your Buildings tab. You can also edit building data from within the Actionable Insights module. Fill out as many of the fields as possible on your building, including HVAC systems, fume hoods, and control strategies. If you haven't entered enough data to generate useful insights in a given area, the module will generate an Insight that advises you to enter more data on that topic. Note: the Actionable Insights module only looks at the most recent year of data associated with each building.
Yes! Here are three examples:
No problem. You need to have an account with associated buildings in order to obtain Actionable Insights, but you can create a hypothetical "Test Data" building that has the properties you're interested in. Insights will be generated for the test building just as they would for a real one. Just make sure to select "Test Data" under "Building Status" so we know not to add the test building to the peer group dataset!
The Actionable Insights module was sponsored by Siemens Smart Infrastructure and was developed by I2SL and kW Engineering. The development team thanks members of the I2SL Laboratory Benchmarking Working Group for their valuable contributions to the design and testing of the AI Module.
The Labs21 Benchmarking tool has been retired from service and the old web address now redirects here. The dataset behind the Labs21 tool has been incorporated into an extension to the Building Performance Database and it's now available through the LBT instead.
Your data and your user account have been migrated from the old database at Lawrence Berkeley National Laboratory (LBNL) to the Building Performance Database (also hosted by LBNL). You should be able to view all your data via the LBT now. Your username for logging into the LBT will be the email address (not the username) you used for the Labs21 tool. To access your account, click on "Login" and use the "Forgot Password?" link to choose a new password for your account. You should then have access to any building data you entered in the Labs21 tool.
Your account has been migrated over from the old Labs21 tool into the new LBT, but you'll need to choose a new password. Your username for logging into the LBT will be the email address (not the username) you used for the Labs21 tool. To access your account, click on "Login" and use the "Forgot Password?" link to choose a new password for your account. You should then have access to any building data you entered in the Labs21 tool.
Registered users can log in to enter and save data on their own buildings, which will then appear alongside peer-group buildings on the benchmarking charts. Registration is free! If you don't own buildings, or would prefer to explore the peer-group database on its own, you may view the data as a guest.
Benchmarking means a number of different things in different contexts, even within the energy efficiency world! The LBT is an example of whole-building energy benchmarking. The tool allows comparison of energy use intensity between buildings with nominally similar functional requirements.
Functional requirements are the services a building must provide for its occupants. Examples of functional requirements include location, lab type, lab square footage, hours of occupancy, and number of fume hoods. When comparing building energy intensity, it makes sense to compare buildings with similar functional requirements. Some buildings meet these requirements more efficiently than others. Examples of building properties that are not functional requirements include HVAC system type, use of exhaust air heat recovery, and fume hood control strategy. Note that it can still be very interesting to compare buildings with similar system types.
The LBT is designed to be used by a wide range of professionals, including facility owners, energy managers, consultants, and design engineers. It can be used to benchmark labs from any industry sector, including commercial, academic, government, and healthcare sectors.
There are a number of good reasons to benchmark building energy usage. These include, but are not limited to:
The 2030 Commitment is an excellent use for benchmarking data. The guidance for using the old Labs21 tool for LEED O&M is applicable to the 2030 Commitment. As described in that document, we recommend applying filtering criteria in a progressive manner until either a) all relevant criteria are selected or b) a minimum sample size (at least 12 comparables) is reached. It is important to maintain a minimum dataset for the data to be relevant; benchmarking against a small sample risks distorting the baseline. For obvious reasons, we recommend excluding estimated data. This is particularly important for the 2030 Commitment, a program that requires comparison to a statistical average of measured building performance data.
For very specialized projects with unusually energy-intensive performance criteria that the tool does not currently capture (e.g. cleanroom-dominated buildings), firms sometimes use engineering judgements based on their energy models rather than using tool data. We recommend contacting the AIA 2030 Commitment administrators for additional guidance in these rare cases.
Yes. Please see this document for guidance on how to use the tool for LEED O&M certification. Please note that although the document was written some time ago for the old Labs21 tool, the procedure described is still valid. Guidance documentation specific to the LBT will be added in the coming months.
Just obtain a username and password via the link on the homepage, and then start entering your building’s data on the Your Buildings tab!
The LBT includes a large number of data fields on each building. Some of these fields are mandatory. Please provide as many of the optional fields as you can! Please see this document for a full list of all LBT data fields.
Some of the data fields are optional and are not required to complete your submission. Others are mandatory. If it turns out you don’t have everything needed, you can save your data (with draft entries for mandatory fields) and return later when you have the rest. If you’ve saved incomplete or placeholder data, it would be good to select “Test Data” as your entry in the Building Status field. Don’t forget to change this field to “Existing Building” once the data submission is complete!
It is acceptable to enter fiscal year data. At present, the benchmarking tool does not attempt to correct for weather variations between sites or years. It is therefore not critical to provide data by calendar year.
In addition to entering building total energy consumption, you can enter individual end use energy consumption on the Utility Usage tab for each of your buildings. Please enter end use data if you measure it -- we'd love to have more of this kind of data in the database!
If the building is supplied by district energy sources (e.g. steam or chilled water), you should enter the amount of each district utility consumed by each building. Do not correct for the efficiency of the plant serving the building. The tool uses standard conversion factors to convert district utility usage to primary (source) energy usage. While this approach does not account for the efficiency of each specific plant, it permits a more equitable comparison between buildings connected to different plants (or with dedicated primary equipment located at the building).
If the renewable energy sources are on-site (e.g. roof-mounted photovoltaic panels), you can enter the amount of energy generated on the Utility Usage tab for your building. Note that this should only include renewables that reduce electric consumption recorded by the main electric meter for the building. To keep the LBT focused on the performance of lab buildings themselves, we are not collecting data on off-site renewable sources or on purchased emissions offsets.
Your data entries are saved once you submit them. You can log out and then return to edit them at any time.
To share data entry responsibilities, we recommend creating a single login for team members to share. Building data cannot at present be shared between different user accounts.
There is currently no bulk data upload option, but we'd like to add one in future.
For the purposes of the tool, the lab area is the area requiring 100 percent outside (“once-through”) air for ventilation. It typically includes lab spaces and lab support spaces. It also includes physics/engineering labs and clean rooms that don't necessarily use 100 percent outside air. It does not include office spaces, conference rooms, lobbies, breakout spaces, mechanical rooms, restrooms, corridors, stairways, etc. Importantly, lab area also typically does not include language, computer, or music “labs”, or “living lab” showcase buildings (except any lab spaces as defined above).
Gross floor area (also known as gross square footage) is the total floor area of the building, excluding open spaces such as parking garages and guard shacks. Net floor area includes net assignable space only, i.e. it excludes circulation spaces, restrooms, mechanical rooms, etc. Net floor area is always smaller than gross floor area. Note that gross floor area is a required data entry in the LBT, while net floor area is optional.
For the purposes of the tool, a lab building is a building containing lab space as defined above. To obtain meaningful results, it is recommended that the tool is used only when the total lab area fraction (lab area as a fraction of total gross square footage) exceeds approximately 10 percent.
We hope that this site is intuitive to use! However, if you have problems with the website, or if you have a burning question that is not answered in these FAQs or in the informational tooltips spread throughout the site, please contact email@example.com.
It helps a lot! The vast majority of buildings in the database are user-submitted. The more buildings we have in the tool, and the more detailed data we have on each building, the greater chance every user has to select a large sample of peer buildings for benchmarking. Without user submissions, this tool could not exist.
Not long! If all energy usage and building area data are available, and the user is familiar with the building, we estimate a reporting burden of 15 minutes per building.
Not long! About 10 minutes to select some filters and make a couple of iterations to obtain a good sample size of peer buildings.
“Normal” depends on what kind of lab building we’re talking about – that’s one of the big reasons we need a lab benchmarking tool! Explore the dataset using the Benchmark Analysis tab to see what's normal for the type of lab building you're interested in!
No. The LBT allows users to input data on their buildings and compare them to other similar buildings in the database, using various building and system level metrics. A rating based on a multi-parameter regression analysis of the dataset (analogous to an ENERGY STAR score) may be provided in future versions of the tool.
Both Portfolio Manager and the LBT will accept and store building data (building properties and energy usage information). There are a number of differences, but the most significant one for lab building owners is that Portfolio Manager does not currently collect lab-specific information such as percent lab area, lab type, or lab purpose. For this reason, any comparison between lab buildings made via Portfolio Manager is not a true comparison between peer buildings with similar functional requirements. The LBT is the only benchmarking tool to include lab-specific functional requirements to allow selection of a peer group of lab buildings.
No. ENERGY STAR does not currently offer an ENERGY STAR ranking for lab buildings.
No. An I2SL lab efficiency score is under consideration, but further analysis is required and no score or certification is currently available.
Whole-building energy benchmarking is a high-level exercise that’s well suited to identifying good candidates for follow-up investigation.
Generally speaking, if your building has a higher energy use intensity than a peer group of similar buildings, then it may be a good candidate for a closer look at its energy consumption. Note that high energy consumption may also be a symptom of an energy-intensive functional requirement that does not appear on the list of filtering criteria in the tool – that’s why a follow-up is a good idea.
Buildings with high energy efficiency would generally be expected to have lower energy intensity than otherwise similar facilities.
Information entered by users of this tool is not used to recognize individual facilities based on their reported energy consumption. I2SL celebrates high achievement in lab sustainability via its annual Go Beyond Awards program, which includes a category for exceptional projects carried out in laboratory or other high-tech facilities.
We recognize that important actionable insights can be gained from the types of benchmaking data collected by the LBT. These insights can help to bridge the gap between benchmarking and taking real action to achieve energy savings and performance improvements. We released the LBT Actionable Insights module in late 2019.
The application of data filters is limited by the number of data points. Have you investigated the use of normalization techniques so that the entire data set can be utilized to provide a more “apples to apples” comparison?
Yes. Normalization is typically done with either a regression-based approach or simulation model-based approach.
You can filter the dataset by climate zone, but the tool does not currently “normalize” data to a typical year or to weather differences within a climate zone.
To select buildings in a similar climate zone to yours, you can filter the dataset by climate zone, but the tool does not currently “normalize” data to a typical year or to weather differences within a climate zone. You can also filter the dataset by U.S. state (via the Building Properties menu on the Benchmark Analysis tab). There's not currently any way for a group of users to share their data directly with each other.
Source energy consumption is calculated using the same factors as those used in ENERGY STAR Portfolio Manager (published by ENERGY STAR in August 2018). GHG emission calculations were updated in October 2022; please see the separate FAQ on those calculations for details.
To compare the energy usage of different buildings, it is helpful to combine energy usage data from different sources (e.g. electricity, district chilled water, natural gas) into a single building energy consumption metric. A number of metrics are in common use: site energy includes only the energy consumed at the building itself; source energy also includes the energy used to generate and transmit the energy used on site; and GHG emissions and energy cost, both typically closely related to source energy consumption, are also used frequently. No single metric is the best approach for all situations.
If you’re only benchmarking against buildings with the same energy sources (e.g. if all buildings in the benchmarking sample are connected to the same campus central plant) then it doesn’t matter too much whether site or source energy consumption is used. Otherwise, and certainly when using the tool, source energy (or GHG emissions) is the better basis for comparison. The dataset contains buildings with many varied energy sources, and a comparison based on site energy will tend to introduce distortions because the site energy usage of some buildings includes the energy used to generate utilities (e.g. if the building contains chillers or boilers) while for others it does not (e.g. chilled water or steam received from a central plant).
The use of source energy as a metric for comparison acts to alleviate these distortions. The tool uses standard ENERGY STAR (August 2018) conversion factors between site and source energy. The use of standard factors means that the efficiencies of individual central plants are not taken into account. This approach is preferable because it provides a more equitable comparison between the lab buildings themselves and not the district energy plants to which they are connected.
No. The LBT is designed to be used with whole building energy usage data and it should not be used for individual labs within buildings.
No. You are welcome to use the publicly available (anonymized) data using the filtering tools on the site, but we cannot share the raw data.
The data in the LBT was provided by a wide range of laboratory owners and operators in the United States, including federal government agencies, universities, pharmaceutical companies, and other organizations. Identities of the buildings and organizations in the database are masked for confidentiality. The database also includes selected buildings from the U.S. Department of Energy’s Commercial Buildings Energy Consumption Survey (CBECS) dataset.
No. The dataset is the largest known collection of lab-specific building data, but it is not designed to be a statistically representative sample of the U.S. building stock.
For most buildings, the building-level energy use data is measured data from building-level utility meters. You can use the filters on the Benchmark Analysis page to select whether you want to see measured and/or estimated data on your charts. Data labeled as “estimated” is typically based on allocations made where buildings do not have dedicated utility meters. In some cases, estimated data may be based on energy modeling predictions.
Yes. All user input data is treated as confidential. The only people with access to the database are technical staff responsible for the Building Performance Database and for this website. The identities of peer group buildings in the benchmarking charts are masked. Furthermore, only normalized metrics are shown (e.g. kBtu/sf/yr); the raw data points from which metrics are calculated (e.g. building area) are not displayed on the charts. Additionally, peer group information is further anonymized by the inclusion of a small amount (±2.5 percent) of "jitter" (small, randomized changes in value) away from the underlying true building data.
LBNL staff perform reviews of all new submissions of data for inclusion in the peer benchmarking dataset. Records that are clearly incorrect (e.g. energy intensity outside of reasonable bounds) or trial entries (marked by user as test or demo data) are not included. However, no detailed auditing is performed to confirm that submitted buildings are real or that data has been entered accurately.
As of late 2022, there were approximately 950 lab buildings in the peer benchmarking dataset. In recent years, the size of the peer dataset has been growing at around 40 buildings per year.
LBNL staff review user-submitted data periodically, typically twice a year. The searchable peer group database is updated after each data review.
No. Only the most recent year of data is shown for each building in the peer group database and for users' own buildings. Viewing of “longitudinal” data (data over time) may be incorporated into future versions of the tool.
Definitely not. Although the dataset includes the Labs21 peer group, which contained data from as early as 2002, most of the entries are less than 5 years old. Many users update their building data each year, and new facilities are being added to the database at a rate of approximately 40 buildings per year.
System-level data entry is not mandatory (and wasn't in the Labs21 tool either), so a limited amount of it has been submitted. Please provide whatever system level you can, so we can improve the quality and breadth of the dataset for all users!
Most likely because users in your climate zone have not submitted much building data to the tool. Please submit yours, and encourage your neighbors to do the same!
Contact firstname.lastname@example.org with ideas or suggestions.
The database is hosted and maintained by LBNL. The LBT user interface is hosted and maintained by I2SL.
We have a long wish-list of future improvements and new modules for the LBT. Stay tuned!
Great! Please contact email@example.com. We will be very happy to hear from you!