# 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: agoutenoir@irap.omp.eu
      role:  Software Ninja


# 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"
    # 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 ??)
        points:
          - [0.0, 0.0 ]
          - [300.0, 0.0 ]
          - [300.0, 100.77107567722328 ]
          - [4000.0, 866.2580844227083 ]
          - [4000.0, 844.2034018149334 ]
          - [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"
    # 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 ??)
        points:
          - [   300.0,  120.42928309 ]
          - [  1500.0,  278.88301355 ]
          - [  2500.0,  438.31863895 ]
          - [ 20000.0, 3335.62849772 ]

  - name: ADEME (RF=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"
    # 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 ??)
        points:
          - [0.0, 0.0 ]
          - [300.0, 0.0 ]
          - [300.0, 371.9202499999999 ]
          - [1000.0, 572.185 ]
          - [1000.0, 572.1850000000001 ]
          - [2000, 903.7033333333331 ]
          - [2000, 903.7033333333329 ]
          - [3000, 1090.2199999999998 ]
          - [3000, 1090.2200000000014 ]
          - [4000, 1617.2800000000013 ]
          - [4000, 1617.2800000000007 ]
          - [5000, 2120.875 ]
          - [5000, 2120.8749999999995 ]
          - [6000, 2198.489999999999 ]
          - [6000, 2198.4900000000007 ]
          - [7000, 2274.2999999999997 ]
          - [7000, 2274.2999999999993 ]
          - [8000, 2599.1999999999985 ]
          - [8000, 2599.2000000000007 ]
          - [9000, 2745.405000000001 ]
          - [9000, 2745.404999999999 ]
          - [10000, 3122.6499999999987 ]
          - [10000, 3122.650000000001 ]
          - [11000, 3752.594999999996 ]
          - [11000, 3739.599000000005 ]
          - [20000.0, 6783.912000000004 ]
          - [25000.0, 8475.197000000006 ]


  - name: DEFRA (RF=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"
    # 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 ??)
        points:
          - [0.0, 0.0 ]
          - [300.0, 0.0 ]
          - [300.0, 47.496000000000016 ]
          - [500.0, 79.16000000000003 ]
          - [500.0, 78.03232675954409 ]
          - [3700.0, 576.0823415958024 ]
          - [3700.0, 541.2334271596557 ]
          - [20000.0, 2878.919114979337 ]
          - [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"
    # 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 ??)
        points:
          - [0.0, 0.0 ]
          - [300.0, 0.0 ]
          - [300.0, 36.568484076385886 ]
          - [2000.0, 186.80815934370835 ]
          - [2000.0, 202.8769421141676 ]
          - [20000.0, 1291.6001262464672 ]
          - [25000.0, 1594.0232329498838 ]

  - 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"
    # 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,    4.5735209613707 ]
          - [   500.0,   84.2229231297094 ]
          - [  3000.0,  223.7823676144418 ]
          - [ 25000.0, 1033.0117495994948 ]

# 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)


  sections:
    # Add as many sections as you want.
    # Three blocks per section ; if you want another amount, it can be done, please ask.
    - blocks:

      - title: What does this do?
        content: |
          The tool helps computing your travel carbon footprint
          for a **round trip** from a given location,
          for a set of visited cities.

          Similarly, the tool allows to compute the travel footprint
          of a conference/meeting/... (the originating city of each 
          participant has then to be provided).
          It can also return the city that would minimize the travel footprint
          assuming the same audience of the conference/meeting for a set of city hosts 
          (which can be derived from the list of cities of the participants 
          to the conference/meeting).

          While online CO<sub>2</sub> calculators enable to compute the footprint
          of a limited number of trips with detailed trip information
          (e.g. connecting flights),
          this tool enables to compute the footprint of a larger number of travels,
          making some assumptions, e.g. to model connecting flights. In addition,
          it provides an estimate for up to **six** different methods.

          <!--
          For short distance travels, the CO<sub>2</sub> footprint associated with trains
          is calculated and added to the air travel footprint.
          -->

          ### Original Motivation

          Global warming is a threat for life on our planet. Evry day we hear about 
          scientific results demonstrating the devastating impacts this will have on
          Earth in the very near future.
          Emissions of carbon dioxide by aircraft were 0.14 Gt C/year in 1992.
          This was between 2% of total anthropogenic carbon dioxide emissions in 1992
          or about 13% of carbon dioxide emissions from all transportation sources
          (Intergovernmental panel on climate change, report 1999). Due to an 
          increasing demand and the growth of the world economy,
          the number has grown since then, reaching closer to 3% nowadays,
          a number which will keep growing.

          Carrying scientific research requires traveling all across the world,
          but time has come to critically look at the way we carry research,
          with the aim of raising awareness and reducing our environmental impact,
          whenever possible. As air travel is likely to dominate the CO<sub>2</sub> budget
          of most scientists, this tool offers a way to easily compute the footprint 
          associated with travels.

      - title: Which data are used?
        content: |
          There is a growing interest in getting the travel footprint of scientific events,
          such as conferences or large meetings.

          Those are based on freely available CO<sub>2</sub> calculators,
          some being relatively easy to use, requiring very limited user inputs.

          However, just by running some of them (including those from Carbon offset companies),
          it is amazing to see how their estimates can differ quite significantly
          (up to a factor of a few for the same trip).

          This is because they use different input data and consider different perimeters and assumptions,
          e.g. excluding freight or not, assuming different radiative forcing indices,
          seat accommodation in the plane…

          The straight numbers provided should therefore not be taken at face value,
          but should be looked at, for what they include and mean.
          It is also striking to me that there is hardly any scientific literature
          on the comparison between CO<sub>2</sub> calculators,
          although often discrepancies are noticed in some communications,
          more particularly for long distance flights.

          Relying on one calculator is therefore not possible. This tool thus 
          enables to compute your travel carbon footprint (for round trips),
          based on data provided by 6 independent calculators:

          1. the International Civil Aviation Organization (ICAO),
          2. the UK Department for Environment, Food & Rural Affairs (DEFRA),
          3. the ATMOSFAIR German Carbon offsetting company,
          4. the French Environment & Energy Management Agency (ADEME)
          5. the data provided on the KLM website to introduce their CO2 compensation service (KLM)
          6. the MyClimate Carbon offseting company (used by Lufthansa)

          ICAO, DEFRA, MyClimate, ATMOSFAIR and to some extent KLM have 
          their methodology very well described
          (see resources section below).

          ADEME and DEFRA provide mean emission factors.
          ATMOSFAIR and ICAO provide on line emission calculators requiring limited user inputs.
          Those on-line calculators have been run for a variety of flight distances,
          so that the estimates (without error bars) could be approximated with linear functions.

      - title: How does this tool work?
        content: |
          The tool starts by decoding the origin cities listed in the form, and geolocate them. 
          It then decodes the destination cities and geolocate them as well. 
          
          Cities that cannot be located are ignored from the computation. To resolve ambiguity 
          between cities of similar names (e.g. Cambridge), the name of the country is required.

          From the longitude and lattitude of the origin and destination cities, the great 
          circle distance is computed. This is the shortest path a plane can follow. However,
          traveling between cities often involves connexion. A 5% increase of the great circle 
          distance is considered as a mean value.
          
          DEFRA, ICAO, Atmosfair and MyClimate include uplift factors to account for the fact 
          than planes, even during direct flight, do not strictly follow the shortest path,
          e.g. to avoid bad weather conditions. For instance, MyClimate considers what is 
          called a detour constant of 95 km.

          CO<sub>2</sub> emissions per passenger take into consideration the load factor
          and are based only on passenger operations
          (i.e. fuel burn associated with belly freight is not charged to the passenger).
          From the travel distance, and the emission coefficients, the tool computes the amount
          of  CO<sub>2eq</sub> generated by each flight. The user can select one 
          or more methods, and a mean value will be reported if more than one method is considered. 

        
    # Second row of "blocks"
    - blocks:

      - title: What about Radiative Forcing?
        content: |
          CO<sub>2</sub> emissions is computed from the total fuel burnt during the flight.
          For ICAO one of kg of fuel leads to **3.16** kg of CO<sub>2</sub> emissions
          MyClimate instead considers the same emission factor but adds a 
          factor for pre-production of 0.538 kg CO2e/kg jet fuel (ecoinvent 2018).
        
          Radiative forcing account for the fact that aviation contributes to climate change
          more than just from the emission of CO<sub>2</sub> 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 (CO<sub>2</sub>),
          ozone (O<sub>3</sub>), and methane (CH<sub>4</sub>);
          trigger formation of condensation trails (contrails);
          and may increase cirrus cloudiness;
          all of which contribute to climate change.
          A radiative forcing index of 1.9/2 is recommended by DEFRA, MyClimate and ADEME.
          ATMOSFAIR considers a multiplier of 3, for all emissions above 9 km.
          ICAO, on the other hand does not include a multiplier,
          waiting for the scientific community to settle on a value. KLM data do 
          not account for radiative forcing either.
          

      - title: Which seat category are you considering?
        content: |
          The tool considers only economy seats for the time being.
          Note that DEFRA emission factors are a factor of 3 larger for a business class seat
          (proportional to the larger area used in the plane).
          Similarly, a factor of 1.5 should be considered when flying on Premium economy seats
          (ICAO would consider a factor of 2).

      - title: What about uncertainties?
        content: |
          Each estimate may have an uncertainty between 10 and 25%
          (really this is a best guess, and not substantiated by any statistical 
          analysis and it could be more probably).
          We would therefore refrain from using the numbers derived as absolute values.
          Larger differences are found when long distance flights are considered.
          In all cases, the estimates can be used for relative comparisons.

    # Third row, etc.
    - blocks:

      - title: Considering train travel for short travel distance
        content: |
          There is a minimum distance (by default 300 km)
          under which the calculator excludes flight travel.
          The calculator proposes instead to compute the travel footprint associated with train.
          The French emission factors are between 4 and 5 grams of CO2eq per km per passenger.
          This low value is likely due to the fact that electricity is provided by nuclear plants.
          It is larger by some factor accross Europe.
          Here I am assuming that the French factor are multiplied by a factor of 5.
          This makes train typically 10% less emitting than plane (including radiative forcing).

      - 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

      - content: |
          ### Disclaimer

          This tool is provided on a best effort basis as a service to members of the science community
          to get some ideas of travel footprints associated with scientific projects and activities.

          ### Confidentiality

          The data provided will remain confidential, as will be the results.

          ### Troubleshooting
         
          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 (<acronym title="Open Street Map">OSM</acronym>)
          is confused or unavailable.
          An error should be listed at the end of the result page.


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 © 2019