# 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, 100.77107567722328 ]
          - [3999.9, 866.2373955846341 ]
          - [4000.0, 844.2034018149334 ]
          - [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
        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

        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
        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
        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
        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
      <br>
      <span class="glyphicon glyphicon-globe" aria-hidden="true"></span>
      CNRS,
      <span class="glyphicon glyphicon-home" aria-hidden="true"></span>
      [IRAP](http://www.irap.omp.eu),
      <span class="glyphicon glyphicon-user" aria-hidden="true"></span>
      [@DidierBarret](https://twitter.com/DidierBarret),
      <span class="glyphicon glyphicon-envelope" aria-hidden="true"></span>
      [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 to be provided.
          If multiple host cities are provided,
          the tool ranks the 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
          and finally from the KLM carbon compensation service.

          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 also been fitted with linear functions.

      - content: |
          ### What about radiative forcing? {#rfi}
          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.

      - 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. This tool was first developed to enable each scientist to easily access its travel footprint. It was then used to compute the travel footprint associated with the development of a large international project, such as the Athena X-ray Integral Field Unit. The numbers were then used to propose concrete actions to reduce the footprint of the project, by reducing the number of large meeting, implementing different ways of interacting and working collectively in a world-wide consortium. Finally, by comparing different, widely used methods, providing so different estimates, the tool is expected to raise awareness within the scientific community (and hopefully the authorities) about the lack of regulations or framework on the critical matter of flight emissions.

    - blocks:

      - 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 considered arbitrarily to be 300 km. Below that, 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 train and normal train respectively. This low value is due to the fact that electricity is provided by nuclear plants. It is larger by some factor across Europe. The tool 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.
          
      - title: Input and output data and trouble shooting
        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.  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 or unavailable. 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. 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 city against the carbon dioxide emissions. Cities found identical in the input form are grouped, and their number in the group is given by the number of trips, and the distance given is the cumulative distance over the group.
          
      - 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. 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 preparatiion). 
 
      - 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 this tool be used for that purpose. 
          

      - 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
          - [DGAC](https://eco-calculateur.dta.aviation-civile.gouv.fr)
            Direction Générale de l'Aviation Civile
          - [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 <small>(almost)</small> immediately.

      <br>

      It may take from a few seconds up to a few minutes,

      depending on the amount of locations you provided.

  # 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.
    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 <br>
        (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 <acronym title="Radiative Forcing Index">RFI</acronym>
        multiplier recommended by <a href="https://www.atmosfair.de">atmosfair</a>
        (i.e. <code>3</code> for all emissions above <code>9km</code>)
        <br>
        For long flights, the multiplier may reach <code>2.8</code> or so.
        Otherwise, by default, <code>1.9</code> 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.
      <br>
      This webpage will automatically update when it is done.

estimation:
  hero:
    title: Your estimation is now available!
    description: |
      Thank you for using our service.
      <br>
      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.
        <br>
        Thank you for using our service.

footer:
  credits: |

    Didier Barret (IRAP) © 2019