Methods, limitations, and data sources for Sustain.Life’s carbon calculators.
Updated: November 2023
Purchased steam, heat and cooling
Upstream and downstream transportation and distribution
Fuel and energy-related activities
Without contractual instrument: If a user purchases electricity without contractual instruments (typically through the local utility at standard rates), we calculate location-based emissions by multiplying reported grid electricity consumption by a local grid emission factor. In the U.S., we select the emissions factor based on the eGrid subregion. Outside the U.S., we use provincial or country-level factors. Our emission factors account for renewable energy in the local grid mix.
With contractual instruments: If a user purchases electricity through contractual instruments, we calculate location-based emissions
To calculate market-based emissions, we multiply contractual electricity supply purchases by source-specific factors. These factors include custom emissions factors, if provided by the user, supplier-specific emission factors, and residual mix factors. If none of these factors are available, we apply the default grid factor. We use an emission factor of 0 for offsite renewable energy such as RECs and renewable PPAs. We use the Greenhouse Gas Protocol’s market-based emission factor hierarchy to apply these factors. Any remaining electricity that is delivered via the grid without any contractual instrument is categorized as Regular grid electricity, emissions for this electricity are calculated using the same hierarchy.
Direct line microgrid: If the user also purchases electricity from a direct-line source (i.e., not from the grid), we recommend users obtain a source-specific emission factor from their supplier. Without this, we multiply reported consumption by the same local grid factor as a proxy (consistent with the Greenhouse Gas Protocol). Both location- and market-based emissions from direct-line microgrid electricity use are calculated by multiplying either the custom supplier-specific or local grid factor by the electricity use.
Onsite generation: Onsite renewable energy installations have no associated scope 2 emissions, and onsite fossil fuel electricity generation only has associated emissions in scope 1. We ask for electricity generated from these sources to provide users with a complete picture of their electricity use, though the values have no bearing on the emissions calculation.
We assume that for any offsite renewables the user purchases that any associated energy attributes are transferred to the user or retired on behalf of the user. If this is not the case, users should not claim it as offsite renewables. For onsite renewable generation, we assume the user does not generate certificates or retains them if they are generated.
Although it is recommended by the Greenhouse Gas Protocol, residual mix emission factors are not available in many parts of the world, reducing the accuracy of market-based emissions calculations. We recommend that users obtain supplier-specific factors whenever possible.
Methodology Sources
U.S. Energy Information Administration, Commercial Buildings Energy Consumption Survey (CBECS)
Greenhouse Gas Protocol Corporate Standard
Energy Benchmarking Report, IOTA
Emission Factor Sources
Australian National Greenhouse Accounts Factors
Entwicklung der spezifischen KohlendioxidEmissionen des deutschen Strommix in den Jahren 1990 – 2020
Canada National Inventory Report (NIR)
Sustainable Energy Authority of Ireland – Conversion Factors
DBEIS Greenhouse gas reporting: conversion factors
When users provide equipment wattage, we calculate emissions based on the country-level emission factor matching the user's currently selected location. We select country-level since remote workers may not be located in the same region as the offices they report to. In the absence of equipment wattage, we make assumptions about typical equipment used and its wattage. We estimate other work-related home energy use (heating, cooling) by using an average annual U.S. household member consumption value to prorate work-from-home energy use and applying a country-specific emission factor. We arrived at MT CO2e per household member by applying an emission factor for each fuel (electricity, natural gas, fuel oil, propane) and adjusting the result based on total national consumption of each fuel.
We assume that, on average, remote employees use one laptop (60W), one monitor (10W), and one task light (20W) to perform work activities for 8 hours per day and 261 days per year. We also assume that one third of a household member's energy use is attributable to work-from-home activities, such as space heating and cooling, overhead lighting, preparing food and beverages during the workday and water use-related energy. If there is not a selected country for the given location, then average annual U.S. household consumption values are applied.
This calculator follows GHG Protocol recommendation of establishing a baseline of employee home emissions to calculate work-related emissions. If the user does not enter specific wattage, we default to our assumptions which do not account for specialized equipment. The calculator applies a country-level factor and doesn’t consider the regional distribution of employees. This calculator can only be used for home office emissions estimates in one country at a time. The error introduced by these equipment and regional limitations is typically small. However, if this is a large, material source of emissions for your organization, we recommend using our home office emissions workbook on the Downloads page to perform per- employee calculations that will apply regional emission factors and consider variables like heating fuel type, floor space of the working area, and presence of other household members.
Methodology Sources
EPA Power Management for Computers and Monitors
2015 Residential Energy Consumption Survey: Energy Consumption and Expenditures Tables
Emission Factor Sources
DBEIS Greenhouse gas reporting: conversion factors
ADEME Bilans GES Carbon Database
Sustainable Energy Authority of Ireland – Conversion Factors
Australian Government, National Greenhouse Accounts Factors
Entwicklung der spezifischen KohlendioxidEmissionen des deutschen Strommix in den Jahren 1990 – 2020
Canada National Inventory Report (NIR)
If the energy source for heat generation is provided, we apply the appropriate EPA emissions factor, assuming default thermal efficiency of 80%. If the energy source is unknown, we use the EPA-recommended default factor which assumes natural gas for steam generation. For purchased cooling, we apply the EPA factor by chiller type, if provided. If unknown or other, we default to electric-driven chiller since these are most common. CO2 emissions from biogenic heating are not directly reported since they are biogenic, which we report separately in alignment with the Greenhouse Gas Protocol.
We assume 80% thermal efficiency for heating and steam. We use natural gas as the default energy source for steam generation, hot water as the default source of heating, and electric chillers as the default chiller type in the U.S. and Canada, unless users make a chiller type selection.
The calculator does not account for variations in thermal or energy efficiency.
Methodology Sources
GHG Protocol Corporate Standard
U.S. EPA Energy Star Portfolio Manager
U.S. Department of Energy CHP Fact Sheet
Emission Factor Sources
Canada National Inventory Report (NIR)
DBEIS Greenhouse gas reporting: conversion factors
ADEME Bilans GES Carbon Database
We apply emission factors for reported quantities of fuel based on user location. If country-level factors aren't available in our dataset, we default to available country factors within proximity to the user's location. We report biogenic CO2 from landfill gas and wood products as a separate output from total CO2e in alignment with GHG Protocol guidelines. We use published heating values of fuels to convert user consumption units. This calculator aligns with the GHG Protocol guidelines for calculating scope 1 emissions from fuel combustion.
This calculator does not include all scope 1 fuel sources. If users need to account for a fuel source that is not currently available like mixed coal, petroleum coke, non-wood biomass, or other gaseous fuels, then custom sources can be entered by the user and applied to their fuel consumption. and CO2 scrubbing, and non-combustion process emissions are also excluded. We do not apply a separate oxidation factor as oxidation is already accounted for in each fuel’s emission factor.
Methodology Sources
GHG Protocol Corporate Standard
Emission Factor Sources
Australian Government, National Greenhouse Accounts Factors
Entwicklung der spezifischen KohlendioxidEmissionen des deutschen Strommix in den Jahren 1990 – 2020
Canada National Inventory Report (NIR)
Sustainable Energy Authority of Ireland – Conversion Factors
DBEIS Greenhouse gas reporting: conversion factors
ADEME Bilans GES Carbon Database
We calculate emissions from vehicles in one of four ways, depending on the data the user provides:
1. Fuel- and -distance-based (most accurate)
2. Fuel-based
3. Distance-based
4. Spend-based (least accurate)
We choose the most accurate method based on the data the user has entered.
If a user is tracking by vehicle and enters both fuel use and distance travelled, we use the fuel to calculate CO2 emissions by multiplying by an emission factor for the fuel and we use the distance to calculate the CH4 and N2O emissions by multiplying by distance-based emission factors. This approach of using both fuel and distance is the most accurate for calculating mobile combustion emissions.
When a user enters fuel consumption in bulk (“Tracking by fuel”) we multiply the fuel use by the appropriate emission factors for the given fuel for the gases CO2, CH4, and N2O. When a user enters fuel usage for a specific vehicle, we multiply the fuel use by emission factors for that fuel and for the type of vehicle.
If a user has entered vehicle information with the fuel efficiency of the vehicle and only enters distance in Measure, then we estimate the amount of fuel consumed using the distance travelled and the fuel efficiency. We then multiply the amount of fuel by the appropriate CO2 factor for the fuel and we multiply the distance by appropriate factors for CH4 and N2O.
We currently only support spend-based calculations in some areas and only for gasoline/petrol. If supported, when a user enters a spend amount for a vehicle, we retrieve the most recent average price of gasoline/petrol for that location. We use this price to estimate the amount of fuel purchased. We then multiply the fuel by the appropriate emissions factor for the fuel and vehicle class.
The fuel- and distance-based method along with the fuel-based method are the preferred methods for calculating emissions. Emissions calculated using distance only or spend only should be considered estimates.
In the absence of the vehicle class when tracking by fuel, we use a generic emission factor representative of all vehicle classes which may differ by a small amount (<1%) from tracking by vehicle classes. Where practical, we recommend tracking vehicle classes but it is not required for accurate emissions calculations.
Methodology Sources
U.S. EPA Fuel Efficiency Database
NREL: Experience with Bi-Fuel LPG Pickups in Texas
NREL: 100,000-Mile Evaluation of Transit Buses Operated on Biodiesel Blends (B20)
NREL: SunLine Transit Agency American Fuel Cell Bus Progress Report
University of Michigan: On-road fuel economy of vehicles in the United States: 1923-2015
H2 Tools: Lower and higher heating values of fuels
The Engineering ToolBox: Fuels – Higher and lower calorific values
Neste Renewable Diesel Handbook
U.S. Energy Information Administration Regular Gasoline All Areas Average Retail Price Monthly
U.S. Energy Information Administration Diesel Fuel Average Price Monthly
Emission Factor Sources
GHG Protocol Emission Factors from Cross-Sector Tools
We calculate emissions by multiplying the reported amount of refrigerant by its global warming potential (GWP). We separate outputs into Kyoto Protocol greenhouse gases that must be included in scope 1 emissions inventories, and greenhouse gases that fall outside of the Kyoto Protocol, such as HCFCs. Excluded refrigerants may have been banned under the Montreal Protocol, but remain in use, for instance to deplete existing stock or through permitted reclamation and reuse. These emissions are reported separately from scope 1 emissions to provide a complete account of organizational impacts.
Where recent GWP values are not available, we assume that previously published values (e.g., IPCC AR4) are still accurate. We assume that user data covers releases from all activities surrounding refrigeration equipment management (installation, use, maintenance, decommissioning).
While we list the most common and several less common refrigerants, our list is not exhaustive. If users enter a value for externally calculated emissions that are neither PFCs nor HFCs in the "Other" field, we will surface them as emissions outside of scope 1. We provide an option to enter externally calculated emission factors as custom sources. To calculate emissions from refrigerants not listed, we recommend that users contact their suppliers to obtain the 100-year global warming potential of the refrigerant, multiply this value by kilograms released during the reporting period, and convert the result to metric tons.
Methodology Sources
Refrigerant liquid-to-weight conversion
U.S. EPA Fugitive Emissions – Greenhouse Gas Inventory Guidance
GHG Protocol, Corporate Standard
Emission Factor Sources
CA Air resources Board: High-GWP Refrigerants
The Climate Registry, Appendix A: Global Warming Potentials
We calculate emissions by multiplying the reported amount of fire suppression chemicals by their global warming potential (GWP) value. We divide outputs into Kyoto Protocol greenhouse gases that must be included in scope 1 emissions inventories, and greenhouse gases that fall outside of the Kyoto Protocol, such as halons and ketones. Some fire suppressants have been banned under the Montreal Protocol, but are still in use, for instance to deplete existing stock or through permitted reclamation and reuse. These emissions can be reported separately from scope 1 emissions to provide a complete account of organizational impacts.
We assume that user data covers releases from all activities surrounding refrigeration equipment management (installation, use, maintenance, decommissioning).
Wetting agents and other fire suppression formulations protected as trade secrets are excluded because global warming potential is unavailable. We list common fire suppressants, but our list is not exhaustive. We provide an option to enter externally calculated emission factors as custom sources. To calculate emissions from fire suppressants not listed, we recommend that clients contact their suppliers to obtain a global warming potential value. Multiply this value by the weight of fire suppressant releases in kilograms and then convert it to metric tons.
Methodology Sources
U.S. EPA Fugitive Emissions – Greenhouse Gas Inventory Guidance
GHG Protocol, Corporate Standard
Emission Factor Sources
U.S. EPA GHG Emissions Factors Hub
Novec 1230 Environmental Properties
This calculator uses the GHG Protocol's average data method for aggregated waste streams (e.g., single-stream recycling) and the waste-type-specific method for material-specific waste streams (e.g., paper recycling). We calculate emissions by multiplying reported waste material weights by emission factors for each disposal method. When users report volume of waste, we use U.S. EPA conversion factors to obtain weight estimates. If users are unable to break out landfilled and incinerated waste, we use a blended factor. To estimate biogenic CO2 emissions that occur during composting, incineration, and waste-to-energy generation, we use data from the IPCC to estimate the biogenic carbon in each waste stream based on user practices and convert this into CO2. When users do not know how their trash is treated, we use a blended landfill-incineration emission factor that reflects the relative shares of landfilling and incineration for trash treatment in the U.S.
Following IPCC 2006 Guidelines, we assume that dry matter content, total carbon, and share of fossil carbon in waste materials follows Table 2.4 (Volume 5 Chapter 2). For biogenic CO2 emissions from composting, we assume 12% of total dry weight is degradable carbon based on an U.S. EPA estimate. We assume the user’s municipal solid waste (MSW) stream resembles the breakdown in U.S. EPA’s characterization studies to estimate. Although specific to the U.S., this data is generally representative of global commercial MSW. When a user does not know if their waste goes to landfill or for combustion, we calculate a blended emissions factor using a landfill: combustion ratio of 4.2:1 based on 2018 U.S. EPA data. We assume that materials not listed in the calculator are a part of the waste stream that goes to landfill, incineration, or waste-to-energy.
Volume-to-weight conversions of waste increase the level of uncertainty in outputs. We recommend that users obtain tonnage reports from their waste management providers or weigh their waste for accuracy. This calculator is not designed for waste streams from highly specialized operations or processes, if this applies to you contact us directly.
Methodology Sources
GHG Protocol Waste Generated in Operations
EPA Advancing Sustainable Materials Management: 2018 Fact Sheet
EPA Volume to Weight Conversion Factors
IEA Methodology for Allocating Municipal Solid Waste to Biogenic and Non-Biogenic Energy
Emission Factors Sources
DBEIS Greenhouse gas reporting: conversion factors
ADEME Bilans GES Carbon Database
Australia National Greenhouse Accounts Factors
When users provide distance data, we use the GHG Protocol's distance-based method, applying emissions factors by mode.
We assume average commute distances for each mode according to the sources listed below. We assume that each employee makes a single round trip using the same mode each day.
Methodology Sources
GHG Protocol Employee Commuting Chapter 7
U.S. Department of Transportation, Transportation Statistics Annual Report 2020
US Census Report : Commuting by Public Transportation in the United States: 2019
NY MTA The Climate Registry Report 2017
Statistics Canada Results from the 2016 Census: Long commutes to work by car
Moovit Insights: Public Transit Index
Ireland National Travel Survey 2016
UK National Travel Survey 2019 - Table NTS0901
Australia Household Travel Survey 2019/20
Singapore General Household Survey 2015
Singapore Land Transport Authority 2014
Emission Factor Sources
IEA 2017 Fuel Economy in Major Car Markets
DBEIS Greenhouse gas reporting: conversion factors
We use the GHG Protocol's distance-based method by mode, using DEFRA emissions factors which include radiative forcing and distance uplift.
We apply regional intercity rail emission factors to distance data provided by the user based on the region of travel.
When users provide vehicle travel fuel, we apply standard vehicle combustion emission factors to the amount of fuel consumed. When users provide distance data, we use regional distance-based emission factors based on regional differences in vehicle fuel economy and the user-specified region of travel.
For air travel, we use the following distance categorization to determine which emission factor to apply. These categories match industry guidance:
The distance-based car travel calculations rely on broader assumptions of regional variations in fuel economy. These should be viewed as a calculation with a higher degree of uncertainty.
Methodology Sources
GHG Protocol, Corporate Standard
Emission Factor Sources
DBEIS Greenhouse gas reporting: conversion factors
IEA 2017 Fuel Economy in Major Car Markets
Fraunhofer-Institute for Systems and Innovation Research ISI
When the user has exact travel data for attendees, we pass the distances to our Business Travel calculator to calculate emissions. When the user does not have exact data, we make assumptions about the average travel distances for attendees traveling by each mode. If the user does not have an estimate of the mode share of attendees, we assume a mode share based on U.S. EPA long distance travel data.
We use the number of non-local attendees and duration of the event and apply average hotel energy use to estimate the total hotel energy consumption. We then apply the appropriate emission factors for the location of the event to calculate emissions.
We use average energy consumption data for public assembly buildings and the area of the venue to estimate the energy consumption for the event. We then apply location-specific emission factors to calculate the emissions from the venue’s energy consumption.
When the user has exact waste data, we pass these inputs to our Non-Hazardous Waste calculator to estimate emissions. This calculator uses location-specific emission factors to estimate the emissions in the region of the event.
Users specify whether the event attendees were provided beverages, snacks, and the percentage of meals which contained meat. For each food and beverage category provided, we make an assumption of the daily consumption of each by each attendee. We then calculate the total food and beverage consumed for the event and apply appropriate food and beverage emission factors.
We adjust the user’s spending for inflation and use the U.S. EPA EEIO’s dataset to estimate emissions based on the user’s spending on merchandise.
When the user does not have exact travel data, we assume the following average one-way trip distances for each mode. These assumptions are based on published US EPA data. We use a weighted average emission factor for economy, business, and first class flights and assume that all flights are medium haul.
When the user does not have an estimate for the mode share of attendees, we assume the following mode share based on US EPA data: Car: 63% Rail: 1% Air: 36%
We country-specific hotel stay emission factors from UK DEFRA data to estimate the emissions of non-local attendees for the duration of the event.
In the absence of energy consumption gathered directly from the venue, this calculator relies on average daily energy use per square meter of venue area based on US CBECS data (shown below). Consumption values, whether estimated or exact, are matched with location-specific electricity grid emission factors.
We assume that all waste is sent to landfill and that all recyclables are a mix of paper, plastic, metal, and glass.
If the event serves them, we make the following assumptions about each attendee’s daily consumption of food and beverages. Non-alcoholic beverages: three per day Alcoholic beverages: one per day Snacks: One per day Meals: Three per day.
This impact calculator performs the best when provided exact measured data for travel, energy, and waste. Estimations for venue energy consumption are based on US building data, so international users are advised to gather venue energy consumption directly.
Methodology Sources
EPA Greenhouse Gas Inventory Guidance: Indirect Emissions from Events and Conferences
Meet Green: The Environmental Footprint of an Event
Emission Factor Sources
DBEIS Greenhouse gas reporting: conversion factors
Food and Agriculture Organization of the United Nations
We calculate emissions from Purchased Goods and Services using the GHG Protocol spend-based approach. First, we convert the user's spending to 2018 USD using U.S. Bureau of Labor Statistics (BLS) data, which we update twice per year. Then we multiply this converted spending by the summary commodity emissions factor from the U.S. EPA's EEIO model, using the commodity the user has indicated via U.S. Bureau of Economic Analysis Industry Classifications. When the user does not map 100% of their spending, we extrapolate emissions from their existing spending onto unmapped categories.
Emission factors from the EPA EEIO dataset are developed with the following assumptions:
All suppliers of a given commodity have similar emissions.
Goods and services produced or procured outside of the U.S. have GHG footprints resembling their U.S. alternatives.
Generally, fluctuations in inflation have an insignificant impact on final GHG calculations.
Changes in inflation that occur between our inflation updates are assumed to be insignificant compared to the margin of error of the EEIO dataset and spend-based methodology.
While the spend-based approach is effective for providing an initial estimate for emissions from purchases, because it is based on general commodity emission factors, it cannot provide supplier-specific emissions estimates. For example, switching to a supplier with lower emissions will not be reflected in a spend-based analysis since the EEIO commodity factor would remain the same.
Furthermore, this approach estimates emissions based on $ spent, so only reductions in spending will show reductions in emissions. In instances where environmentally preferable products and services are more expensive than their traditional counterparts (which is common), a spend-based approach will estimate higher emissions for the environmentally preferable alternative. Lastly, because the most reliable spend-based emission factors are based on an analysis of the U.S. economy, they may provide less accurate results for spending that occurs outside of the U.S.
Despite these drawbacks, spend-based analyses still provide value in instructing organizations where to start when it comes to gathering more information or implementing policies. Results from this calculator should be used as a springboard for supplier-engagement surveys to collect specific supplier emissions data. By extrapolating mapped emissions onto unmapped categories (when the used does not map 100% of their spending), we assume that emissions of unmapped categories reflect emissions of the user’s mapped categories.
For this reason, we require the user to map a minimum of 75% of their spending so that such extrapolation does not have a large impact on overall emissions. However, in cases where the user does not map particularly GHG-intensive categories, it could reduce the accuracy of our emissions calculation. To avoid this, users should map 100% of their spending.
Methodology Sources
US Burueau of Labor Statistics - Consumer Price Index
US Bureau of Economic Analysis - Industry Classifications
Emission Factor Sources
US EPA Supply Chain Greenhouse Gas Emission Factors for US Industries and Commodities
When the user inputs shipment weight along with origin and destination information, we follow the Global Logistics Emissions Council's (GLEC) Framework for calculating logistics emissions. For transportation emissions, we multiply the emission factor by the weight of the shipment and the distance it was shipped. We calculate distance differently for each mode:
For road transport we use shortest feasible distance (SFD), the shortest road network distance between two points, and add 5% per GLEC guidance to bring the estimate closer to actual distance.
For air transport, we use great circle distance in accordance with the International Air Transport Association's RP 1678.
For sea transport, we use the Sea Distance database from Centre d'Études et de Recherches sur le Développement International (CERDI) which provides sea route distance between common ports in country pairs. We then add 15% per GLEC guidance to bring the estimate closer to the actual distance.
For rail transport, due to the lack of standardized data on global rail networks, we use the SFD approach for road distance as a proxy. For all modes, we use blended emission factors comprised of the major fuel types for that mode. When calculating warehousing emissions, we multiply the emission factor by the weight of the goods and length of storage time. When the user provides volume of goods, we convert that to weight using the "Average Goods" conversion provided by GLEC.
To categorize road and air transport distances into short-, medium-, and long-haul, we use the following bins:
Air Transport
Road Transport
We assume different truck types for each road transport trip distance. For example, for the EU we assume short haul trips are done with commercial van/small box trucks, medium haul trips are done with medium-goods vehicles, and long-haul trips are done with heavy-goods vehicles. When the user inputs spend data, we adjust for inflation and then multiply the spent amount by the EPA EEIO emission factor for the given mode.
We assume that each shipment uses a single mode of transport. Although this is not often the case, by selecting the prominent mode or selecting air (if air transport is involved), the calculator will provide a sufficient estimate. To achieve the most accurate calculation, users should separate each leg of the journey into their respective modes. We assume that the start and end of each trip is at a transshipment site, which transfers the cargo to/from the transport vehicle.
For sea shipments, we assume this occurs at a maritime container terminal. We assume that all sea shipments are containerized and transported via general cargo ships and that all road transport is non-refrigerated. If exact addresses are not given for origin and destination, we assume that origin/destination locations are the geographic centroids for the given cities.
This calculator will provide less accurate results for shipments that use many different modes, refrigerated shipments, or shipments with road transport carriers where a significant portion of their fleet is electrified or uses biofuel. Because our emission factor for warehousing is a global value based on EU logistic sites, it may be less accurate outside of the EU (although it is deemed sufficient by GLEC). In general, results based on spend data should be taken to be high-level estimates due to the inherent inaccuracies of spend-based analysis. Furthermore, the EPA EEIO dataset is specific to the US, therefore the spend-based approach is even less accurate for non-US transportation.
Methodology Sources
Emission Factor Sources
We calculate emissions from fuel- and energy-related activities from three sources:
Upstream emissions of purchased fuels: Emissions from the extraction, production, and transportation of fuels the user consumes
Upstream emissions of purchased energy: Emissions from the extraction, production, and transportation of fuels used to generate energy (electricity, steam, heat, and cooling) that the user purchases
Transmission & distribution (T&D) losses: Energy lost during the transmission of purchased energy to the user Emissions calculated for the above are not already included in Scope 1 or 2. We do not calculate emissions from the generation of purchased electricity sold to end users since this is generally only applicable to utility providers.
Upstream emissions of purchased fuels
To calculate the upstream emissions of purchased fuels, we apply well-to-tank fuel-specific emission factors to fuels the user has already entered in Buildings and Vehicles categories. These factors represent emissions in the supply chain for those fuels and not combustion.
Upstream emissions of purchased energy
We break this category out by purchased energy type. For electricity, we use the specific grid mix for the country or subregion (where available) and adjust for the efficiency of power generation to estimate the per kilowatt-hour fuel input for the grid region. We then apply well-to-tank fuel-specific emission factors to create a blended emission factor for each country or subregion (dataset available here). Finally, we multiply this emission factor by grid electricity the user has input into the Buildings category. For purchased heat and steam, we multiply the amount of heat and steam the user has purchased by a well-to-tank emission factor that adjusts for thermal efficiency. We assume that heat and steam is generated from a combined heat and power plant. For purchased cooling, we divide the user’s cooling consumption by an assumed efficiency (based on cooling type) and multiply by the appropriate well-to-tank emission factor.
Transmission & distribution losses
We calculate all T&D losses by multiplying the user’s consumption by lifecycle emission factors and estimated distribution losses for the region, country, or subregion.
We assume that heat and steam purchased by the user is generated from a natural gas CHP plant. We assume that direct line microgrid electricity purchased by the user is also generated by a CHP plant. We use average efficiency values for natural gas and electric chillers from U.S. DOE to estimate the fuel input for purchased cooling. Based on data from the EIA, we use average power plant generation efficiencies (or heat rates) to estimate upstream emissions from the generation of electricity. We assume a 5% transmission and distribution loss for heat and steam systems based on information from U.K. DEFRA. We assume a 3% transmission and distribution loss for purchased cooling based on information from the U.S. EPA. For electricity delivered through a direct line, we assume a T&D loss factor that matches the local grid. When the user burns wood onsite, we use an average emission factor from wood chips, wood logs, and wood pellets.
Methodology Sources
NREL Life Cycle Emission Factors for Electricity Generation
Ember Global Electricity Review 2022
US DOE Absorption Chillers for CHP Systems
US DOE Energy Efficient Water-Cooled Electric Chillers
US EPA Portfolio Manager Source Energy
ASHRAE 90.1-2004 Minimum Required Efficiencies for Water-Cooled Chillers
US EIA Average Operating Heat Rate for Selected Energy Sources
Emission Factor Sources
Réseau de Transport d'Électricité Transmission Loss Rates
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