carbon footprint for nerds

Our carbon footprint calculation is based on a scientific background. On this page you can find more information about it!

The carbon footprint is the amount of carbon dioxide (CO²) released into the atmosphere because of the activities of an individual, organization or community. By releasing greenhouse gases into the atmosphere, we have an impact on the environment, causing climate change. CO² is related to the emissions of all greenhouse gases we produce. For example, production, transport, heating and of course making energy from fossil fuels. Global warming is one of the consequences attributed to the increasing amount of CO² emissions. Our climate is changing, and this is a threat to humans and nature.

‘Carbon dioxide’ is the main greenhouse gas that is expelled by the tourism industry. Global tourism produces about 8% of global greenhouse gas emissions. This includes the entire supply chain of tourism: transportation, accommodation, food and beverages, souvenirs, clothing, cosmetics, and other goods. With the fast-growing travel sector, we need to bring the emissions down to a much lower level.

We have calculated that each overnight stay in a certified hotel will reduce the carbon footprint with 2 kilos per guest night in comparison to staying in a non-certified hotel.  Although the vast part of the emissions derives from transport by air to destinations, each step forward is one! We believe that ultimately real change will come from implementing regulations and incentives together with all stakeholders to encourage low-carbon operations and undertake action.

The source of the carbon footprint method in

The carbon footprint is calculated by means of a mathematical formula. This formula was developed by the Breda University of Applied Sciences (BUAS) in cooperation with and the Dutch tourism sector as a part of the ‘Carbon management for tour operators’ (CARMATOP) project. We have integrated this model in our dataset to automatically calculate the carbon footprint of all the accommodations we have in our database. Each year the algorithm will be reviewed by an external party, to guarantee the level of accuracy.

Carbon footprint calculation method

The means of every accommodation carbon footprint calculation in our database is based on the carbon footprint algorithm model we developed. We perform three steps of calculation: 1) calculate the mean and average of accommodation’s direct energy use and present them in the guest-night and the room-night unit, 2) conduct a regression analysis of the attributes of accommodations to get the energy-influential variable, 3) adjust with climate factor per countries where the accommodation is located.

We worked with the data based on scope 1 of the Corporate Accounting and Reporting Standard of the Greenhouse Gas Protocol: direct greenhouse gas emissions occur from sources that are owned or controlled by the company. Our carbon footprint calculation is taking into account two types of real data: the real output of accommodation’s direct energy use and the attribute of the accommodations. The real output of direct energy use of a significant number of accommodations is calculated per accommodation per guest night and room night. In addition to this, regression analyses are conducted on the attributes of the accommodations, to find out if there is a correlation of these attributes within the accommodations with the direct energy use. We found there is a direct correlation for several attributes, calculated to what extent it correlates, and incorporated the energy-influential variables to the algorithm model. Furthermore, within the algorithm, we have integrated the greenhouse gas emissions specific factors of every country in the world. We put the algorithm model in our system to calculate all the accommodation in our database automatically. Each part of the accommodations’ unique value (direct energy use of accommodation, influential accommodation attribute, and countries’ climate factor) part is multiplied to each other in order to get the accommodation carbon footprint score. We are right now developing the third iteration of the algorithm to bring the carbon footprint formula towards HCMI compliance, the most used methodology in the tourism sector.

The reliability and shortcoming of the carbon footprint figures

The accommodation carbon footprint measurement is still in development. The generated numbers are an outcome of a statistical formula and therefore an estimate, but still an accurate one. There is a standard deviation of 5% minus and 5% plus on this estimate. The probability that an accommodation with a very high carbon footprint has a very low carbon footprint (or vice versa) is low.

Based on the accommodation energy data we use for our carbon footprint measurement at the moment, we cannot comply with all scopes of GHG Protocol on the Corporate Accounting and Reporting Standard. Out of three scopes, we currently only able to meet the scope 1 of GHG Protocol on the Corporate Accounting and Reporting Standard. This may lead to the partial representation of the greenhouse gas emission that exists along the tourism value chain, especially within the accommodation.

Our ultimate goal is to work with the actual figures of the carbon footprint of all accommodations. Therefore, we supply all interested parties with tools to calculate their carbon footprint based on the Hotel Carbon Measurement Initiative (HCMI) methodology. Of course, we make sure we perform an assessment of the data delivered to guarantee accuracy and validity. HCMI is a methodology and tool which enables hotels to measure and report on carbon emissions in a consistent way. It was developed by the International Tourism Partnership and the World Travel & Tourism Council in partnership with KPMG and 23 global hotel companies. HCMI can be used by any hotel anywhere in the world, from small guesthouses to 5-star resorts. Over 24,000 hotels globally are using HCMI.

Carbon footprint figures presentation

We use a green foot for all accommodations that score lower than 15 kg carbon per guest night, as this is the calculated average output of a hotel based on the sample. The accommodations that have a higher output than 15 kg per guest night will receive a green foot. Validated real data is always of higher value than an algorithm. If we have enough data it will result in a higher ranking within the search results and with a distinctive icon.



The accommodations with a higher output than 15 kg per guest night receive the grey foot icon. Validated actual emissions of hotels are always of higher value than the results of the algorithm. We have already set ourselves the goal of collecting the actual CO² emissions in cooperation with the ecolabels. In the future, we will assign this validated and actual data a higher ranking within the search results and indicate them with a distinctive icon.

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