Automobile impact calculation

Provided in real time by Brighter Planet at 01:16AM UTC on Thursday, May 23, 2013 for timeframe beginning 2013-01-01 and ending 2014-01-01.

Characteristics

Brighter Planet is performing this calculation based on the following characteristics of this automobile as provided in the request:

Characteristic Input Interpretation
Make saab Saab
Model 900s 900
Year 1990 1990

Calculation

This calculation uses version 893c5b832cc65ec3393ea3e1b1e0f5ab84ff38e9 of Brighter Planet's automobile carbon model. The automobile emission estimate is the total anthropogenic emissions from fuel and air conditioning used by the automobile during the timeframe. It includes CO2 emissions from combustion of non-biogenic fuel, CH4 and N2O emissions from combustion of all fuel, and fugitive HFC emissions from air conditioning. For vehicles powered by grid electricity it includes the emissions from generating that electricity.

Calculations are performed adaptively, so methodology will vary depending on automobile characteristics. Impact values, listed below, are based on a number of input factors, which in turn are based on others, and so forth. In each case, the methodology used in the calculation is specified, and, wherever possible, the source code of the method is displayed.

  1. Carbon

    Conclusion: 2576.8 kg

    Method: from co2 emission, ch4 emission, n2o emission, and hfc emission.

    (((co2_emission + ch4_emission) + n2o_emission) + hfc_emission)

  2. Co2 emission

    Conclusion: 2389.4039676662

    Method: from fuel use and co2 emission factor.

    (fuel_use * co2_emission_factor)

  3. Co2 biogenic emission

    Conclusion: 0.0

    Method: from fuel use and co2 biogenic emission factor.

    (fuel_use * co2_biogenic_emission_factor)

  4. Ch4 emission

    Conclusion: 10.033729580700001

    Method: from distance and ch4 emission factor.

    (distance * ch4_emission_factor)

  5. N2o emission

    Conclusion: 109.91861254800001

    Method: from distance and n2o emission factor.

    (distance * n2o_emission_factor)

  6. Hfc emission

    Conclusion: 67.46951676510001

    Method: from distance and hfc emission factor.

    (distance * hfc_emission_factor)

  7. Co2 emission factor

    Conclusion: 2.34183

    Method: from automobile fuel.

    automobile_fuel.co2_emission_factor

  8. Co2 biogenic emission factor

    Conclusion: 0.0

    Method: from automobile fuel.

    automobile_fuel.co2_biogenic_emission_factor

  9. Ch4 emission factor

    Conclusion: 0.00109361

    Method: from type fuel year.

    type_fuel_year.ch4_emission_factor

  10. N2o emission factor

    Conclusion: 0.0119804

    Method: from type fuel year.

    type_fuel_year.n2o_emission_factor

  11. Hfc emission factor

    Conclusion: 0.00735373

    Method: from activity year type.

    activity_year_type.hfc_emission_factor

  12. Activity year type

    Conclusion: 2009 Passenger cars

    Method: from active subtimeframe and automobile type.

    AutomobileActivityYearType.find_by_type_name_and_closest_year(automobile_type.value, active_subtimeframe.start_date.year)

  13. Activity year

    Conclusion: 2009

    Method: from active subtimeframe.

    AutomobileActivityYear.find_by_closest_year(active_subtimeframe.start_date.year)

  14. Energy

    Conclusion: 35330.6 MJ

    Method: from fuel use and automobile fuel.

    (fuel_use * automobile_fuel.energy_content)

  15. Fuel use

    Conclusion: 1020.3148681442292

    Method: from annual fuel use, active subtimeframe, and timeframe.

    (annual_fuel_use * (active_subtimeframe / timeframe.year))

  16. Annual fuel use

    Conclusion: 1,020.3148681442292 l

    Method: from fuel efficiency, annual distance, and automobile fuel.

    if automobile_fuel.non_liquid? then
  (((annual_distance / fuel_efficiency) * AutomobileFuel.find("gasoline").energy_content) / automobile_fuel.energy_content)
else
  (annual_distance / fuel_efficiency)
end

  17. Distance

    Conclusion: 9174.87

    Method: from annual distance, active subtimeframe, and timeframe.

    (annual_distance * (active_subtimeframe / timeframe.year))

  18. Annual distance

    Conclusion: 9,174.87 km

    Method: from type fuel year.

    type_fuel_year.annual_distance

  19. Type fuel year

    Conclusion: Passenger cars gasoline 1990

    Method: from automobile type, automobile fuel, and year.

    AutomobileTypeFuelYear.find_by_type_name_and_fuel_family_and_closest_year(automobile_type.value, automobile_fuel.family, year.year)

  20. Type fuel

    Conclusion: Passenger cars gasoline

    Method: from automobile type and automobile fuel.

    AutomobileTypeFuel.find_by_type_name_and_fuel_family(automobile_type.value, automobile_fuel.family)

  21. Automobile type

    Conclusion: Passenger cars

    Method: from make model year.

    make_model_year.type_name

  22. Speed

    Conclusion: 50.94382232429702 km/h

    Method: from urbanity.

    (1 / ((urbanity / Country.fallback.automobile_city_speed) + ((1 - urbanity) / Country.fallback.automobile_highway_speed)))

  23. Fuel efficiency

    Conclusion: 8.99219474933993 km/l

    Method: from fuel efficiency city, fuel efficiency highway, and urbanity.

    (1.0 / ((urbanity / fuel_efficiency_city) + ((1.0 - urbanity) / fuel_efficiency_highway)))

  24. Fuel efficiency city

    Conclusion: 7.68112 km/l

    Method: from make model year and automobile fuel.

    if automobile_fuel.same_as?(make_model_year.automobile_fuel) then
  make_model_year.fuel_efficiency_city
else
  if automobile_fuel.same_as?(make_model_year.alt_automobile_fuel) then
    make_model_year.alt_fuel_efficiency_city
  end
end

  25. Fuel efficiency highway

    Conclusion: 10.3212 km/l

    Method: from make model year and automobile fuel.

    if automobile_fuel.same_as?(make_model_year.automobile_fuel) then
  make_model_year.fuel_efficiency_highway
else
  if automobile_fuel.same_as?(make_model_year.alt_automobile_fuel) then
    make_model_year.alt_fuel_efficiency_highway
  end
end

  26. Automobile fuel

    Conclusion: gasoline

    Method: from make model year.

    make_model_year.automobile_fuel

  27. Hybridity multiplier

    Conclusion: 1.0

    Method: default.

    1.0

  28. Urbanity

    Conclusion: 0.43

    Method: default.

    Country.fallback.automobile_urbanity

  29. Active subtimeframe

    Conclusion: 2013-01-01/2014-01-01

    Method: from acquisition and retirement.

    if (acquisition.value <= retirement.value) then
  Timeframe.constrained_new(acquisition.to_date, retirement.to_date, timeframe)
else
  Timeframe.constrained_new(retirement.to_date, retirement.to_date, timeframe)
end

  30. Acquisition

    Conclusion: 1990-01-01

    Method: from year.

    Date.new(year.year, 1, 1)

  31. Retirement

    Conclusion: 2014-01-01

    Method: from timeframe.

    [timeframe.to, acquisition].compact.max

  32. Make model year

    Conclusion: Saab 900 1990

    Method: from make model and year.

    AutomobileMakeModelYear.find_by_make_name_and_model_name_and_year(make_model.make_name, make_model.model_name, year.year)

  33. Make year

    Conclusion: Saab 1990

    Method: from make and year.

    AutomobileMakeYear.find_by_make_name_and_year(make.name, year.year)

  34. Make model

    Conclusion: Saab 900

    Method: from make and model.

    AutomobileMakeModel.custom_find(characteristics)

Estimate provided by Brighter Planet CM1. Calculations are performed using data from a variety of public sources. To cite this estimate, credit Brighter Planet, "Automobile impact calculation." <http://impact.brighterplanet.com/automobiles?make=saab&model=900s&timeframe=2013-01-01%2F2014-01-01&year=1990>, retrieved 2013-05-23T01:16:33Z.