# This YAML file holds some of the content of the website, for convenience. # Learn YAML, it's worth it: http://sweetohm.net/article/introduction-yaml.html # /!. IF YOU BREAK THIS FILE YOU BREAK THE WEBSITE. TREAD CAREFULLY. # Metadata about this website meta: title: Travel Carbon Footprint Calculator description: A travel carbon footprint calculator for researchers. authors: - name: Didier Barret email: dbarret@irap.omp.eu role: Principal Investigator - name: Antoine Goutenoir email: antoine@goutenoir.com role: Software Ninja - name: Jean-Michel Glorian email: Jean-Michel.Glorian@irap.omp.eu role: Benevolent Wizard # Aka. Laws models: - name: Atmosfair (RFI=3 for altitude > 9 km) # Slugged version of the display name above # Only lowercase alphanumeric, starting with a letter, using - as liaison # In other words, MUST match ^[a-z]([a-z0-9-]*[a-z0-9])?$ eg: icao-with-rfi # MUST be unique, two models MUST NOT have the same slug. slug: atmosfair-rfi # There MUST exist a python file named like this in `flaskr/laws` # And it MUST contain a class named EmissionModel # Please keep this lowercased, letters-only (or I will breathe fire) file: travel_emission_lerp_fit # Color MUST be in the hex form, without alpha color: "#9933ff" # Whether this model is selected by default in the list. selected: true # The configuration that will be fed to the model. # May be anything, really. Go bonkers! config: plane_emission_linear_fit: # A coefficient applied to the distance connecting_flights_scale: 1.05 # Radiative Forcing Index # Multiplier after scaling rfi: 1.0 # Flat scalar to add before scaling with laws offset_before: 0 # Flat scalar to multiply before scaling with laws scale_before: 1 # The travel_emission_lerp_fit uses points instead of intervals # List of (distance in km, footprint in kg) points: - [ 0.0, 0.0 ] - [ 299.9, 0.0 ] - [ 300.0, 100.771075677223 ] - [ 3999.9, 866.237395584634 ] - [ 4000.0, 844.203401814933 ] - [ 19999.9, 5606.129335551792 ] - [ 25000.0, 7094.270252762378 ] - name: MyClimate (RFI=2) # Slugged version of the display name above # Only lowercase alphanumeric, starting with a letter, using - as liaison # In other words, MUST match ^[a-z]([a-z0-9-]*[a-z0-9])?$ eg: icao-with-rfi # MUST be unique, two models MUST NOT have the same slug. slug: my-climate-rfi # There MUST exist a python file named like this in `flaskr/laws` # And it MUST contain a class named EmissionModel # Please keep this lowercased, letters-only (or I will breathe fire) file: travel_emission_lerp_fit # Color MUST be in the hex form, without alpha color: "#99ff33" # Whether this model is selected by default in the list. selected: true # The configuration that will be fed to the model. # May be anything, really. Go bonkers! config: plane_emission_linear_fit: # A coefficient applied to the distance connecting_flights_scale: 1.05 # Radiative Forcing Index # Multiplier after scaling # DEPRECATED rfi: 1.0 # Flat scalar to add before scaling with laws offset_before: 95 # Flat scalar to multiply before scaling with laws scale_before: 1 # The travel_emission_lerp_fit uses points instead of intervals # List of (distance in km, footprint in kg) points: - [0.0, 0.0 ] - [299.9, 0.0 ] - [300.0, 120.42928309599999 ] - [1499.9, 278.86980907246215 ] - [1500.0, 278.8830135500002 ] - [2499.9, 438.3026953954595 ] - [2500, 438.3186389580005 ] - [19999.9, 3335.611941663665 ] - [25000.0, 4163.431314509144 ] - name: ADEME (RFI=1.9) # Slugged version of the display name above # Only lowercase alphanumeric, starting with a letter, using - as liaison # In other words, MUST match ^[a-z]([a-z0-9-]*[a-z0-9])?$ eg: icao-with-rfi # MUST be unique, two models MUST NOT have the same slug. slug: ademe-rfi # There MUST exist a python file named like this in `flaskr/laws` # And it MUST contain a class named EmissionModel # Please keep this lowercased, letters-only (or I will breathe fire) file: travel_emission_lerp_fit # Color MUST be in the hex form, without alpha color: "#33ff99" # Whether this model is selected by default in the list. selected: true # The configuration that will be fed to the model. # May be anything, really. Go bonkers! config: plane_emission_linear_fit: # A coefficient applied to the distance connecting_flights_scale: 1.05 # Radiative Forcing Index # Multiplier after scaling # DEPRECATED rfi: 1.0 # Flat scalar to add before scaling with laws offset_before: 0 # Flat scalar to multiply before scaling with laws scale_before: 1 # The travel_emission_lerp_fit uses points instead of intervals # List of (distance in km, footprint in kg) points: - [0.0, 0.0 ] - [299.9, 0.0 ] - [300.0, 195.74749999999995 ] - [999.9, 301.13494249999997 ] - [1000.0, 301.15000000000003 ] - [1999.9, 475.61588499999993 ] - [2000, 475.63333333333316 ] - [2999.9, 573.7901833333333 ] - [3000, 573.8000000000008 ] - [3999.9, 851.1722600000007 ] - [4000, 851.2000000000004 ] - [4999.9, 1116.223495 ] - [5000, 1116.2499999999998 ] - [5999.9, 1157.0959149999994 ] - [6000, 1157.1000000000004 ] - [6999.9, 1196.99601 ] - [7000, 1196.9999999999998 ] - [7999.9, 1367.9828999999993 ] - [8000, 1368.0000000000005 ] - [8999.9, 1444.9423050000007 ] - [9000, 1444.9499999999994 ] - [9999.9, 1643.4801449999993 ] - [10000, 1643.5000000000007 ] - [10999.9, 1975.016844999998 ] - [11000, 1968.2100000000028 ] - [19999.9, 3570.462197000003 ] - [25000.0, 4460.630000000003 ] - name: DEFRA (RFI=1.9) # Slugged version of the display name above # Only lowercase alphanumeric, starting with a letter, using - as liaison # In other words, MUST match ^[a-z]([a-z0-9-]*[a-z0-9])?$ eg: icao-with-rfi # MUST be unique, two models MUST NOT have the same slug. slug: defra-rfi # There MUST exist a python file named like this in `flaskr/laws` # And it MUST contain a class named EmissionModel # Please keep this lowercased, letters-only (or I will breathe fire) file: travel_emission_lerp_fit # Color MUST be in the hex form, without alpha color: "#3399ff" # Whether this model is selected by default in the list. selected: true # The configuration that will be fed to the model. # May be anything, really. Go bonkers! config: plane_emission_linear_fit: # A coefficient applied to the distance connecting_flights_scale: 1.05 # Radiative Forcing Index # Multiplier after scaling # DEPRECATED rfi: 1.0 # Flat scalar to add before scaling with laws offset_before: 0 # Flat scalar to multiply before scaling with laws scale_before: 1 # The travel_emission_lerp_fit uses points instead of intervals # List of (distance in km, footprint in kg) points: - [0.0, 0.0 ] - [299.9, 0.0 ] - [300.0, 47.496000000000016 ] - [499.9, 79.14416800000002 ] - [500.0, 78.03232675954409 ] - [3699.9, 576.0667775328388 ] - [3700.0, 541.2334271596557 ] - [19999.9, 2878.9047733493503 ] - [25000.0, 3596.0006143105275 ] - name: KLM data (no RF, not recommended) # Slugged version of the display name above # Only lowercase alphanumeric, starting with a letter, using - as liaison # In other words, MUST match ^[a-z]([a-z0-9-]*[a-z0-9])?$ eg: icao-with-rfi # MUST be unique, two models MUST NOT have the same slug. slug: klm-data-no-rfi # There MUST exist a python file named like this in `flaskr/laws` # And it MUST contain a class named EmissionModel # Please keep this lowercased, letters-only (or I will breathe fire) file: travel_emission_lerp_fit # Color MUST be in the hex form, without alpha color: "#ff3399" # Whether this model is selected by default in the list. selected: false # The configuration that will be fed to the model. # May be anything, really. Go bonkers! config: plane_emission_linear_fit: # A coefficient applied to the distance connecting_flights_scale: 1.05 # Radiative Forcing Index # Multiplier after scaling # DEPRECATED rfi: 1.0 # Flat scalar to add before scaling with laws offset_before: 0 # Flat scalar to multiply before scaling with laws scale_before: 1 # The travel_emission_lerp_fit uses points instead of intervals # List of (distance in km, footprint in kg) points: - [0.0, 0.0 ] - [299.9, 0.0 ] - [300.0, 41.883578628476144 ] - [2499.9, 214.70184186944394 ] - [2500.0, 261.6807087092951 ] - [14999.9, 962.2587735768744 ] - [25000.0, 1522.7313138757793 ] - name: ICAO (no RF, not recommended) # Slugged version of the display name above # Only lowercase alphanumeric, starting with a letter, using - as liaison # In other words, MUST match ^[a-z]([a-z0-9-]*[a-z0-9])?$ eg: icao-with-rfi # MUST be unique, two models MUST NOT have the same slug. slug: icao-no-rfi # There MUST exist a python file named like this in `flaskr/laws` # And it MUST contain a class named EmissionModel # Please keep this lowercased, letters-only (or I will breathe fire) file: travel_emission_lerp_fit # Color MUST be in the hex form, without alpha color: "#ff9933" # Whether this model is selected by default in the list. selected: false # The configuration that will be fed to the model. # May be anything, really. Go bonkers! config: plane_emission_linear_fit: # A coefficient applied to the distance connecting_flights_scale: 1.05 # Radiative Forcing Index # Multiplier after scaling # DEPRECATED rfi: 1.0 # Flat scalar to add before scaling with laws offset_before: 0 # Flat scalar to multiply before scaling with laws scale_before: 1 # The travel_emission_lerp_fit uses points instead of intervals # List of (distance in km, footprint in kg) points: - [0.0, 0.0 ] - [299.9, 0.0 ] - [300.0, 67.00585705041823 ] - [2499.9, 211.09825928042045 ] - [2500.0, 206.528816915788 ] - [14999.9, 663.8204584246745 ] - [25000.0, 1029.6603566841018 ] # The grouped barchart displayed on the home page. laws_plot: distances: - 350.0 - 500.0 - 1000.0 - 1500.0 - 2500.0 - 3000.0 - 4500.0 - 5000.0 - 8000.0 - 10000.0 - 12000.0 # The content is Markdown. HTML is also allowed. # If you also want Markdown in the titles, just ask. home: # The hero block (aka. jumbotron) is the top-level, salient block # It's like a welcoming mat :) hero: title: Estimate your travel carbon footprint # Using a pipe (|) allows you to set multiline content # Careful, indentation matters. description: | Travel footpint calculator provided by Didier Barret
CNRS, [IRAP](http://www.irap.omp.eu), [@DidierBarret](https://twitter.com/DidierBarret), [didier.barret@gmail.com](mailto:didier.barret@gmail.com) # Three blocks per section. # sections: # You can also use columns. columns: - blocks: - title: What does the tool do? content: | The tool computes the carbon footprint associated with round trip flights. It does so for a set of trips from a given city of origin to a set of destinations. Similarly, the tool allows to compute the carbon footprint of a larger set of trips, corresponding to a conference, a meeting and so on. For this, the city of departure for each participant to the conference has first to be provided. If multiple destination cities are provided, the tool ranks those cities according to the associated carbon footprint. While online calculators enable to compute the footprint of a limited number of trips, this tool enables to compute the footprint of a larger number of trips in an automated way. Furthermore, it provides an estimate based on data from six different methods, whose estimates can differ significantly. If more than one method is selected by the user, the tool returns the mean of the estimates of all selected method. - title: How does the tool work? content: | A round trip is defined by a city pair. The two cities are geolocated and from their longitude and latitude, the great circle distance is computed. This is the shortest path a plane can follow. Some methods thus consider uplift correction factors in computing the carbon dioxide emission of a flight. In addition, two cities may not be connected by a direct flight. This is accounted for by increasing by 5% the great circle distance. Each method provides the carbon dioxide emission in kg as a function of the flight distance in km. Thus from the increased great circle distance, the carbon dioxide emission of a flight associated with a trip between a city pair is computed and multiplied by two to account for a round trip. - title: Which methods are used? content: | The tool incorporates six different methods, among the most widely used, and for which the methodology used is documented. Providing more than one method enables to get a mean value, while illustrating the significant differences in their estimates. In alphabetic order, the data considered are from ADEME: the French Environment & Energy Management Agency, atmosfair: a German carbon offsetting company, DEFRA: the UK Department for Environment, Food & Rural Affairs, ICAO: International Civil Aviation Organization, from the KLM carbon compensation service data and finally from myclimate. _This list is obviously not exhaustive but represents a variety of estimates from lower to higher values._ - title: How are the different methods built? content: | What is needed for each method is a function giving the carbon dioxide emission as a function of the flight distance. ADEME and DEFRA provide mean emission factors, as a function of flight distance. Myclimate provides an analytical formula. For ICAO and atmosfair, the on-line calculators have been run for a wide range of flights of varying distances (~100 flights spanning from 300 km to 12000 km) and the estimates have been fitted with linear functions, covering adjacent distance intervals. For its carbon compensation service, KLM provides on its web site a table of emissions for a large range of flights. The KLM data have been also been fitted with linear functions. - title: What about radiative forcing? slug: rfi content: | Radiative forcing accounts for the fact that aviation contributes to climate change more than just with the emission of carbon dioxide from burning fuels, by releasing gases and particles directly into the upper troposphere and lower stratosphere where they have an impact on atmospheric composition. These gases and particles include carbon dioxide (CO2), ozone (O3), and methane (CH4); trigger formation of condensation trails (contrails); and may increase cirrus cloudiness; all of which contribute to climate change. A Radiative Forcing Index (RFI) of 1.9–2 is used by DEFRA, myclimate and recommended by ADEME (see discussion in [Jungbluth, N. & Meili, C. Int J Life Cycle Assess (2019) 24: 404](https://doi.org/10.1007/s11367-018-1556-3).). ATMOSFAIR considers a multiplier of 3, for all emissions above 9 km, accounting for the profile of the flight. ICAO, on the other hand does not include a multiplier, arguing that the scientific community has not settle on a value! KLM data does not seem to account for radiative forcing either, as the estimates they provide are close, although a little higher, than the ones of ICAO. Therefore, the methods based on ICAO and KLM data are not recommended, but given as methods providing the lowest emissions. [![Models used](static/img/recap_scaling_laws.jpg)](static/img/recap_scaling_laws.jpg) - title: Seating category content: | The tool assumes economy seats in computing the carbon dioxide emission. For indication, DEFRA provides mean emission factors for different seat classes considering international flights. Related to the area occupied by the seat in the plane, for Premium economy, the emission would be 1.6 times larger than flying an economy seat. It would be 2.9 and 4 times higher from flying Business class and First class respectively. - title: Accounting for train emission content: | The minimum distance for flying is an input to be provided by the user (it is set to 300 km by default). Below the minimum distance for flying, it is assumed that train is used. The tool then computes the travel footprint associated with train. The French emission factors provided by ADEME are 3.37 and 5.11 grams of carbon dioxide equivalent per km per passenger for high speed trains and normal trains respectively. This low value is due to the fact that electricity is provided by nuclear plants. It is larger by some factors across Europe. The tool thus assumes the mean of the emission factors of national and international rails, as provided by DEFRA (i.e. 23 grams per passenger km). This makes the carbon dioxide emission of trains, typically one tenth (1/10) of the one of aircrafts. - blocks: - title: Input and output data content: | The inputs are provided in US English for the city and country names, without diacritics. On each line, the city and country names must be separated by a comma. Pasting a csv file in the form is possible, provided that a comma separates the city and country names. A round trip is defined by a city pair. If the user enters cityA as the origin city, and twice cityB as destinations, the tool returns the cumulative emission and distance from two round trips involving cityA and cityB, and indicates that 2 round trips were involved. The same happens if the user enters twice cityA as the city of origin and cityB as the sole destination. Three types of inputs can be considered depending on whether the user wants an “individual” estimate or an estimate for a conference, meeting and so on. In the former case, the “origin” city is unique and the “destination” cities may be multiple. The tool returns the carbon dioxide equivalent emission for each city of destination. In the later case, the “origin” cities are multiple (i.e. the cities from which the participants to the conference depart from), and the “destination” city may be a single host city or multiple host cities if the user wants to compare their associated footprint. If there is one destination, the tool returns the carbon dioxide equivalent for each city of origin. If multiple destinations are provided the tool returns the carbon dioxide equivalent emission summed over all cities of origin and for each city of destination. The cumulative distance to each city of destination is also provided. The result pages provides a summary plot which can be downloaded, as well as a csv and raw yaml file. The csv file lists the name of the city as in the form, the address to which it was geolocated, the carbon dioxide emission (in kg), the distance travelled, the number of trips possible by train (i.e. when the distance is less than the minimum flying distance, e.g. 300 km) and the number of trips by plane. The plot and the csv file rank the cities against the carbon dioxide emissions. - title: Trouble shooting content: | The estimation can go wrong if a city is not properly geolocated. This may happen because the name of the city is wrongly spelled or the geolocator (OSM) is confused. An error should be listed at the end of the result page. Don’t be surprised, if the name recovered by the geolocator is not exactly the one you had expected (e.g. a city is located at the address of an embassy). If nothing happens during a request, it is most likely caused by the geolocator being unavailable. In this case, try again a few minutes later. - title: Caveats content: | The numbers provided by the tool do not come with uncertainties. Therefore they must be considered as indicative of the true values. Selecting more than one method is recommended, because they may make the numbers closer to their true values. In all cases however, the numbers can be used for relative comparisons, e.g. when comparing two cities for hosting a conference. - title: Confidentiality content: | The data provided in the form will remain confidential, as will be the results. - title: Disclaimer content: | This tool is provided on a best effort basis as a service to members of the science community. The numbers provided are informative and have obviously no legal value. - title: Reference content: | Results from the tool may reference to Barret (2019, in preparation). - title: Original motivation content: | Global warming is a threat for life on our planet. Emissions of carbon dioxide by aircrafts keeps increasing, as the world economy keeps growing (it is about 3% of the anthropogenic emissions nowadays). Carrying scientific research requires traveling across the world, and thus air travel is likely to dominate the carbon footprint of most scientists and is likely to be large for developing international projects. This tool was first developed to compute the travel footprint associated with the development of the X-ray Integral Field Unit to fly on board the Athena space observatory in the early 2030s. The rather large number derived, typically one hundred ton of carbon dioxide per bi-annual consortium meeting, imposed concrete actions to reduce the footprint of the project, by re-considering the number of large meetings, implementing different ways of interacting and working collectively in a world-wide consortium. The tool was further improved to easily compute the travel footprint associated with individual traveling or with the organization of events, involving a large number of travels. Finally, by comparing different, widely used methods, providing so different estimates, I would expect to raise awareness within the scientific community (and hopefully the authorities and medias) about the lack of regulations or framework on the critical matter of estimating aircraft emissions. - title: Concluding note content: | As a personal note, I would like to stress that, as a scientist, I find it worrying or even shocking that there are no standards for computing the flight emissions, while we know that flight travels, releasing carbon dioxide at high altitudes, contribute to global warming. To take an example, the International Civil Aviation Organization (ICAO) is a United Nations specialized agency, established by States in 1944 to manage the administration and governance of the Convention on International Civil Aviation. ICAO has global responsibility for the establishment of standards, recommended practices, and guidance on various aspects of international civil aviation, including environmental protection. How can ICAO ignore radiative forcing in the results provided by its widely used on- line calculator? (which by the way is the calculator used by the travel agency of my institute, being a public institution). The IPCC in its 1999 report have defined the radiative forcing index to be between 2 and 4. Why ICAO is using 1? This is just an example, which clearly show the urgent need to agree on a common methodology accepted by all parties in computing flight emission. May be this tool will help to raise awareness on this issue. - title: Additional resources content: | - Offset your flight with [atmosfair](https://www.atmosfair.de/en/offset/flight) - [ADEME](https://www.ecologique-solidaire.gouv.fr/sites/default/files/Info%20GES_Guide%20m%C3%A9thodo.pdf) (French Environment & Energy Management Agency) - [DEFRA](https://www.gov.uk/government/publications/greenhouse-gas-reporting-conversion-factors-2019) emission conversion factors 2019 - [ICAO](https://www.icao.int/environmental-protection/carbonoffset/pages/default.aspx) Carbon Emissions Calculator - [KLM data](https://www.klm.com/travel/nl_en/prepare_for_travel/fly_co2_neutral/all_about_sustainable_travel/index.htm) KLM data - [MyClimate](https://www.myclimate.org) MyClimate - L. Hackel [travel footprint calculator](https://lhackel.shinyapps.io/travel_footprint/) based on DEFRA emission factors estimate: hero: title: Request an estimation description: | The results will be available (almost) immediately.
It may take from a few seconds up to a few minutes, depending on the amount of locations you provided. help: first_name: Fill these to say hello. last_name: We will never share your data with anyone. origin_addresses: | Use en_US city and country names, without diacritics.   The comma matters.
This is either a home city and a country or the cities and countries of the participants to the conference, meeting… destination_addresses: | This is either the cities and countries to travel to or the host city and country of the conference, meeting…
Please provide multiple cities and countries to compute the location of the minimum emission. # Labels accept HTML, but not markdown # Descriptions accept neither, since we use the HTML title attribute form: email: label: Email Address description: Make sure you provide a valid address or you won't receive the results! first_name: label: First Name description: Also known as given name, eg. `Didier`. placeholder: Adèle last_name: label: Last Name description: Also known as family name, eg. `Barret`. placeholder: Bellego institution: label: Institution / Enterprise description: If any? comment: label: Leave a comment description: Any input is appreciated. Everyone's a critic. use_train_below_km: label: Use train below description: We will use train emission models instead of plane fo trips below this distance. origin_addresses: label: Origin Cities description: | One address per line, in the form `City, Country`. Make sure your addresses are correctly spelled. # We MUST use the dumb CRLF pair for windows users placeholder: "Paris, France\r\nBerlin, Germany" # placeholder: | # Paris, France # Berlin, Germany destination_addresses: label: Destination Cities description: | One address per line, in the form `City, Country`. Make sure your addresses are correctly spelled. placeholder: | Washington, United States of America compute_optimal_destination: label: | Compute the destination city that will minimize emissions
(useful when setting up a meeting/conference) description: | We will only look through Cities specified in the Destination Cities. use_atmosfair_rfi: label: | Use the RFI multiplier recommended by atmosfair (i.e. 3 for all emissions above 9km)
For long flights, the multiplier may reach 2.8 or so. Otherwise, by default, 1.9 will be used. description: | We will only look through Cities specified in the Destination Cities. estimate_queue: hero: title: Please wait… description: | Your estimation is being computed. This may take several minutes.
This webpage will automatically update when it is done. estimation: hero: title: Your estimation is now available! description: | Thank you for using our service.
Bookmark this webpage, it is private and unlisted. failure: hero: title: Your estimation has failed! description: | Sorry about that. Please find the error message below.
Thank you for using our service. lolliplot: one_to_one: | The carbon dioxide equivalent emission is provided for each city of destination. Identical trips (i.e. identical destinations) are summed and the cumulative distance is provided. one_to_many: | The carbon dioxide equivalent emission is provided for each city of destination. Identical trips (i.e. identical destinations) are summed and the cumulative distance is provided. many_to_one: | The carbon dioxide equivalent emission is provided for each city of origin. Identical trips (i.e. identical origins) are summed and the cumulative distance is provided. many_to_many: | The carbon dioxide equivalent emission is summed over all cities of origin and provided for each city of destination. The cumulative distance to each city of destination is provided. Duplicates in the destinations are removed. footer: credits: | Didier Barret (IRAP) © 2019