The tool estimates the carbon footprint of a single or multiple hotel room nights and meeting spaces across the world. Companies can use this information to calculate the carbon footprint of hotel stays during business travels for Scope 3 reporting and offsetting, or to provide clients with information when booking hotels or offsetting carbon on their behalf.
The tool outputs the median carbon footprint in particular geographical locations, and users can look for the carbon footprint of hotels by the number of Expedia Stars. It calculates the carbon footprint using the Hotel Carbon Measurement Initiative (HCMI) methodology; ideal for corporate reporting and calculating the amount of carbon to offset.

HCMI is the industry-accepted way to measure and compare scope 1 and 2 greenhouse gas emissions of hotels. It includes emissions related to fuels burnt on site (e.g. in gas boilers and company vehicles) and electricity used on site. It also accounts for emissions related to any outsourced laundry and refrigerants (e.g. used in air conditioning). For more information, please visit the Sustainable Hospitality Alliance.

The data is taken from the Cornell Hotel Sustainability Benchmarking Tool (CHSB) 2023 data set (based on 2021 data), with over 25,000 hotels in over 600 geographies, which nearly doubles in size every year.
Data for the countries where actual median figures are not available from the raw data received are extrapolated using the following methodology: (1) the average HCMI figure; (2) the average rooms to meeting space ratio; and (3) average CO2e per kWh of electricity for the entire data set were weighted against the International Energy Agency (IEA) CO2 Emissions from Fuel Combustion 2021 country average output of CO2 per kWh of electricity, proportionate to the ratio of difference for each country compared to the global average. A rule-of-thumb of 75% of a hotel’s energy usage being derived from electricity was applied, and that figure was multiplied by the respective ratio of each country’s CO2 per kWh compared to the global average, then adding in the remaining 25% of CO2 from energy usage using the same average and applying the average room floor area to meeting space floor area to generate mean HCMI figures for the remaining countries.
For more information on the data set and the extrapolation methodology, please contact us at info@greenview.sg.
While we understand that global extrapolations are broad and high-level figures, we believe that it is better than other existing hotel footprinting methods because of the CHSB source data. Furthermore, as the CHSB data set grows in reach and depth over time, we will be able to reduce extrapolation, while making improvements in the remaining countries that still require it for footprinting exercises.
The CHSB data set, along with the accompanying guidance document outlining the methodology, are freely available online through the Cornell University Center for Hospitality Research or here.

a. Actual Data
Indicates that figures were available in the source data received from the Cornell Hotel Sustainability Benchmarking Tool (CHSB) 2023 data set (2021 data).
b. Extrapolated Data
Proxy country/group of countries were used to estimate the figure using the extrapolation methodology explained above in Section 2 (What is the Hotel Carbon Measurement Initiative) for countries that lack the minimum number of properties to generate a median figure.

a. Average of 2 Stars and 4 Stars
The average of 2 Stars and 4 Stars coefficients was calculated and used as a proxy to fill in the gap in the 3 Stars coefficient for a specific country.
b. Average of 3 Stars and 5 Stars
The average of 3 Stars and 5 Stars coefficients was calculated and used as a proxy to fill in the gap in the 4 Stars coefficient for a specific country.
c. Climate Grouping Extrapolation
Countries from the same climate zone are grouped together and used as a proxy to fill in the gaps among countries based on the coefficient generated from the grouping.
d. Country Grouping Extrapolation
Countries from the same location are grouped together and estimated based on the coefficient generated from the grouping.
e. Global Extrapolation
For countries that lack the minimum number of properties to generate a median figure or good proxy, its coefficient was estimated based on the coefficient generated from the whole list of countries that have actual data.
f. Partial Data Extrapolation
For countries that lack the minimum number of properties to generate a median figure for some of the Expedia Stars (i.e., data not available for 3 stars and 4 stars), its coefficient was estimated based on the coefficient generated from partially available data.
g. Sub-National Province Level Extrapolation
Provinces that lack the minimum number of properties to generate a median figure are grouped together and its coefficient is used as a proxy to fill in the gaps among provinces within the same country.
h. Sub-National State Level Extrapolation
States that lack the minimum number of properties to generate a median figure are grouped together and its coefficient is used as a proxy to fill in the gaps among states within the same country.

Under GET THE RESULT section, below the text “Rooms Footprint” and “Meeting Footprint”, the following text displayed to state the data status:
a. Available data: Singapore (Actual) all hotels
b. Available data: Ireland (Climate Grouping Extrapolation). all hotels

The publishing cycle for the Cornell Hotel Sustainability Benchmarking Tool (CHSB) takes up to two years, which includes collection of data from major hotel chains (generally available in the third quarter of the following calendar year), data aggregation, rigorous validity testing and analysis, data verification, and finally drafting and publishing of the report.

The benchmarking data for CHSB2023 (2021 data) includes 25,576 hotels from 31 international hotel chains: ACCOR S.A., AINA Hospitality, Centara Hotels & Resorts, Chatham Lodging Trust, CPG Hospitality, DiamondRock Hospitality Company, Four Seasons Hotels and Resorts, Hilton Worldwide, Hong Kong & Shanghai Hotels, Horwath HTL Asia Pacific, Hyatt Hotels Corporation, Intercontinental Hotels Group, KHP Capital Partners, KSL Capital Partners, Mandarin Oriental Hotel Group, Marriott International, MGM Resorts International, Pacific Beachcomber, Park Hotel Group, Park Hotels & Resorts, Pebblebrook Hotel Trust, Playa Hotels & Resorts, Radisson Hotel Group, RLJ Lodging Trust, Rosewood Hotel Group, Ryman Hospitality Properties, Six Senses Hotels Resorts Spas, Sunstone Hotel Investors, The Ascott Limited, Wyndham Hotels & Resorts, Xenia Hotels & Resorts.

Data sets are updated annually. The next update will be available in the first quarter of 2024 with the 2022 calendar year dataset.

If a country does not have granular level data (e.g. by metropolitan statistical areas (MSAs)), a default value for the entire country is provided.

Please use the following citation for Footprinting:
a. Hotel Footprinting Tool, V[version number]. HCMI values obtained using [indicate hotel class] hotel class and [statistic] statistic, www.hotelfootprints.org, retrieved [date].
b. Example: Hotel Footprinting Tool, V3.0. HCMI values obtained using all hotel class and median, www.hotelfootprints.org, retrieved 10 March 2023.

Please email us at info@greenview.sg and we will send a template for you to fill in the data.

Please email us at info@greenview.sg and we will be happy to receive your feedback to help us improve the tool.