The tool estimates the carbon footprint of a single or for multiple hotel rooms nights and meeting spaces across the world. This information can be used to calculate a company’s business travel hotel stay carbon footprint for Scope 3 reporting and offsetting or provide information for clients on whose behalf you are booking or offsetting travel. The data is aggregated to show the median carbon footprint in particular geographical locations, with the choice of hotel class by number of stars. The tool calculates the carbon footprint using the Hotel Carbon Measurement Initiative (HCMI) methodology; ideal for corporate reporting and calculating the amount that is required for carbon offsetting.

HCMI is the industry accepted way to measure and compare scope 1 and 2 GHG 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 source data are taken from the Cornell Hotel Sustainability Benchmarking Tool (CHSB) 2019 data set, with over 15,000 hotels in over 500 geographies, which nearly doubles in size every year.
Data for the countries where actual figures 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 2019 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 extrapolation is a broad and high-level figure, we believe that it is better than other existing hotel footprinting methods currently available. 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 with a guidance document outlining the methodology are freely available online through the Cornell University Center for Hospitality Research or here.

a. Actual Data
Indicates figures were available from the source data received from the Cornell Hotel Sustainability Benchmarking Tool (CHSB) 2019 data set.
b. Extrapolated Data
Proxy country/group of countries used to estimate the figure using the extrapolation methodology explained above (2) for countries with lack of minimum number of properties to display actual figures.

a. Average of 2 Stars and 4 Stars
The average of 2 Stars and 4 Stars measure were calculated and used as proxy to fill in the gaps in 3 stars measure for a specific country.
b. Average of 3 Stars and 5 Stars
The average of 3 Stars and 5 Stars measure were calculated and used as proxy to fill in the gaps in 4 stars measure for a specific country.
c. Climate Grouping Extrapolation
Countries from the same climate zone are grouped together and used as proxy to fill in the gaps among countries based on measure generated from the grouping.
d. Country Grouping Extrapolation
Countries from the same location are grouped together and estimated based on measure generated from the grouping.
e. Global Extrapolation
Countries that lack of minimum number of properties to display figures or lack of solid proxy estimated based on the measure generated from the whole list of countries that have actual data.
f. Partial Data Extrapolation
Countries that lack of minimum number of properties to display figures for some of the stars (i.e., data not available for 3 stars and 4 stars) estimated based on the measure generated from the data partially available.
g. Sub-National Province Level Extrapolation
Provinces that lack of minimum number of properties to display figures are grouped together and used as proxy to fill in the gaps among provinces within the same country.
h. Sub-National State Level Extrapolation
States that lack of minimum number of properties to display figures are grouped together and used as 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 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 2019 participation includes 21,432 hotels from 26 international hotel chains: AINA Hospitality, Centara Hotels & Resorts, Chatham Lodging Trust, CPG Hospitality, DiamondRock Hospitality Company, EVENT Hospitality & Entertainment, Hilton Worldwide, Hong Kong & Shanghai Hotels, Horwath HTL Asia Pacific, Hyatt Hotels Corporation, Intercontinental Hotels Group, Mandarin Oriental Hotel Group, Marriott International, MGM Resorts International, Park Hotel Group, Park Hotels & Resorts, Pebblebrook Hotel Trust, Playa Hotels & Resorts, Pro-Invest Group, Radisson Hotel Group, RLJ Lodging Trust, Ryman Hospitality Properties, Six Senses Hotels Resorts Spas, Sudima Hotels, Wyndham Hotels & Resorts, Xenia Hotels & Resorts.

Data sets are updated annually. The next update will be available in the first quarter of 2023 with 2021 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 2022.

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.