Train: SQUAKE

💡 High-Level Description:

The SQUAKE methodology has emerged as a refined and operator-centric approach to calculating carbon emissions in the train travel sector. Recognizing the complexities and variances across different train operators, SQUAKE prioritizes operator-specific data over generic assessments. This focus on granularity ensures that emissions estimates are not only precise but also reflect the unique practices, technologies, and efficiencies of individual operators.

With its emphasis on operator-specific data, the SQUAKE methodology provides invaluable insights into the variability of emissions profiles among train operators. It enables companies and regulators to identify best practices and areas for improvement. For instance, two train operators might have significantly different emissions profiles because one uses more renewable energy sources while the other relies heavily on fossil fuels. SQUAKE, by providing such detailed data, paves the way for more informed sustainability strategies and decisions in the train travel industry.

API Request

{
  "expand": [
    "items"
  ],
  "items": [
    {
      "type": "train",
      "external_reference": "test_1",
      "origin": "Stockholm",
      "destination": "Malmo",
      "number_of_travelers": 1,
      "train_type": "high_speed",
      "seat_type": "second_class",
      "fuel_type": "electricity",
      "operator_name": "sj",
      "methodology": "SQUAKE"
    }
  ]
}

API Request Items

  • "type": "train" (required)

  • "methodology": "SQUAKE" (required)

  • "external_reference": A unique identifier that helps you link the resulting emissions to the requested item. Especially useful if multiple items are requested since SQUAKE cannot guarantee to keep the same order. The maximum length is 128 characters.

  • "number_of_travelers": Minimum value is 1. The default value is 1.

  • "origin": SQUAKE will try to resolve the origin/destination regardless of its format. Ideally, for addresses use the Post standard, for airports use IATA/ICAO code (format: ^[A-Z]{3,4}$, e.g., "MUC"), for other locations used in trade and transportation use UN/LOCODE codes (format: ^[A-Z]{2}\W?[A-Z2-9]{3}$, e.g., "DEHAM"). You can also pass lat/long (format: ^[-+]?\d{1,3}\.\d{1,10}\s?,\s?[-+]?\d{1,3}\.\d{1,10}$, e.g., "+40.712,-74.006").

  • "destination": SQUAKE will try to resolve the origin/destination regardless of its format. Ideally, for addresses use the Post standard, for airports use IATA/ICAO code (format: ^[A-Z]{3,4}$, e.g., "MUC"), for other locations used in trade and transportation use UN/LOCODE codes (format: ^[A-Z]{2}\W?[A-Z2-9]{3}$, e.g., "DEHAM"). You can also pass lat/long (format: ^[-+]?\d{1,3}\.\d{1,10}\s?,\s?[-+]?\d{1,3}\.\d{1,10}$, e.g., "+40.712,-74.006").

  • "distance_in_km": Prioritized over origin and destination. If you don't have a distance_in_km, you can use origin and destination and the distance will be automatically resolved. If you pass both distance_in_km and origin/destination, then distance_in_km will be used.

  • "train_type": SQUAKE's methodology defaults to regional without and high_speed with an operator_name given. Values are high_speed, regional, or international.

  • "fuel_type": Values are diesel, electricity, hydrogen, hybrid, or average.

  • "operator_name": SQUAKE's methodology allows passing the operator's name to obtain a more accurate result. train_type defaults to high_speed if operator_name is passed. Here is the database with the supported operators.

  • "seat_type": Values are first_class or second_class. The default value is first_class.

  • Default Values

    • "train_type": "high_speed"

    • "seat_class": "first_class"

    • "fuel_type": "diesel"

Sample API Response

{
    "carbon_quantity": 261,
    "carbon_unit": "gram",
    "items": [
        {
            "carbon_quantity": 261,
            "carbon_unit": "gram",
            "external_reference": "test_1",
            "type": "train",
            "methodology": "SQUAKE",
            "distance": 616.0,
            "distance_unit": "kilometer"
        }
    ]
}

Bibliography

  • “Which Form of Transport Has the Smallest Carbon Footprint?” Our World in Data, ourworldindata.org/travel-carbon-footprint.

  • CO2- Berechnung Geschäftsreise VDR-Standard Teil I (2016, March). VDR. Retrieved from https://www.atmosfair.de/wp-content/uploads/vdr_reportingstandard_teil1_30032016-1.pdf

  • CO2- Berechnung Geschäftsreise VDR-Standard Teil II (2016, March). VDR. Retrieved from https://www.atmosfair.de/wp-content/uploads/vdr_reportingstandard_teil2_30032016.pdf

  • VDR standard CO2 calculation for business trips (n.d.). VDR. Retrieved from https://www.vdr-service.de/arbeitsvorlagen/vdr-standard-co2-berechnung-geschaeftsreise

  • Thistlethwaite, G., et al. (2022, June). 2022 Government Greenhouse Gas Conversion Factors for Company Reporting. Department for Business, Energy, & Industrial Strategy. Retrieved from https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/1083857/2022-ghg-cf-methodology-paper.pdf

  • Environmental Mobility Check. nachhaltigkeit.deutschebahn.com/en/measures/environmental-mobility-check.

  • Polkinghorne, John. “Public Transport Emissions in NZ.” Greater Auckland, 13 Dec. 2013, www.greaterauckland.org.nz/2013/07/19/public-transport-emissions-in-nz.

  • Ngila, Faustine. “Tanzania’s New Electric Rail Will Help It Cut Carbon Emissions.” Quartz, 20 July 2022, qz.com/africa/2185031/tanzanias-new-electric-rail-will-help-it-cut-carbon-emissions.

  • Miller, C. Andrew. “Savings in Per-passenger CO2 Emissions Using Rail Rather Than Air Travel in the Northeastern U.S.” Journal of the Air &Amp; Waste Management Association, vol. 71, no. 12, Informa UK Limited, Sept. 2021, pp. 1458–71. https://doi.org/10.1080/10962247.2020.1837996.

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