Provided in real time by Brighter Planet at 03:49PM UTC on Saturday, February 16, 2019 for timeframe beginning 2019-01-01 and ending 2020-01-01.
Brighter Planet is performing this calculation based on the following characteristics of this lodging as provided in the request:
Characteristic | Input | Interpretation |
---|---|---|
Rooms | 1 |
1 |
Duration | 172800 |
172,800 s |
Zip code | 89109 |
89109 |
This calculation uses version of Brighter Planet's lodging carbon model. The lodging emission estimate is the anthropogenic emissions from lodging room energy use. It includes CO2 emissions from direct fuel combustion and indirect fuel combustion to generate purchased electricity.
Calculations are performed adaptively, so methodology will vary depending on lodging 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.
Conclusion: 50.6 kg
Method: from co2 emission, ch4 emission, and n2o emission.
((co2_emission + ch4_emission) + n2o_emission)
Conclusion: 50.40317520344753
Method: from fuel uses and electricity mix.
gas = Fuel.find("Pipeline Natural Gas") oil = Fuel.find("Distillate Fuel Oil No. 2") dh = Fuel.find("District Heat") (((((fuel_uses[:natural_gas] / gas.energy_content) * gas.co2_emission_factor) + ((fuel_uses[:fuel_oil] / oil.energy_content) * oil.co2_emission_factor)) + ((fuel_uses[:district_heat] / dh.energy_content) * dh.co2_emission_factor)) + (fuel_uses[:electricity].megajoules.to(:kilowatt_hours) * electricity_co2_emission_factor))
Conclusion: 0.016862969036462845
Method: from fuel uses and electricity mix.
ch4_gwp = GreenhouseGas[:ch4].global_warming_potential gas_ef = ((0.1.grams.to(:kilograms) / 1000.kbtus.to(:megajoules)) * ch4_gwp) oil_ef = ((0.6.grams.to(:kilograms) / 1000.kbtus.to(:megajoules)) * ch4_gwp) dh_ef = ((((gas_ef / 0.817) + (oil_ef / 0.846)) / 2.0) / 0.95) ((((fuel_uses[:natural_gas] * gas_ef) + (fuel_uses[:fuel_oil] * oil_ef)) + (fuel_uses[:district_heat] * dh_ef)) + (fuel_uses[:electricity].megajoules.to(:kilowatt_hours) * electricity_ch4_emission_factor))
Conclusion: 0.16550581199831513
Method: from fuel uses and electricity mix.
n2o_gwp = GreenhouseGas[:n2o].global_warming_potential gas_ef = ((0.1.grams.to(:kilograms) / 1000.kbtus.to(:megajoules)) * n2o_gwp) oil_ef = ((0.6.grams.to(:kilograms) / 1000.kbtus.to(:megajoules)) * n2o_gwp) dh_ef = ((((gas_ef / 0.817) + (oil_ef / 0.846)) / 2.0) / 0.95) ((((fuel_uses[:natural_gas] * gas_ef) + (fuel_uses[:fuel_oil] * oil_ef)) + (fuel_uses[:district_heat] * dh_ef)) + (fuel_uses[:electricity].megajoules.to(:kilowatt_hours) * electricity_n2o_emission_factor))
Conclusion: 459.4 MJ
Method: from fuel uses.
fuel_uses.values.sum
Conclusion: {:natural_gas=>159.83846128863277, :fuel_oil=>23.028708075178542, :electricity=>266.3424031534399, :district_heat=>10.219586755878016}
Method: from adjusted fuel intensities and room nights.
intensities = adjusted_fuel_intensities { :natural_gas => ((intensities[:natural_gas] * room_nights)), :fuel_oil => ((intensities[:fuel_oil] * room_nights)), :electricity => ((intensities[:electricity] * room_nights)), :district_heat => ((intensities[:district_heat] * room_nights)) }
Conclusion: {:natural_gas=>79.91923064431639, :fuel_oil=>11.514354037589271, :electricity=>133.17120157671994, :district_heat=>5.109793377939008}
Method: from fuel intensities and amenity adjustments.
intensities = fuel_intensities.dup pool_adjustment = 0.0 characteristics.except(:fuel_intensities).each do |characteristic, adjustment| adjustment.each do |fuel, value| if (fuel == :pool_energy) then pool_adjustment = (pool_adjustment + value) else intensities[fuel] = 0.0 if ((intensities[fuel] += value) < 0.0) end end end if (pool_adjustment.abs > 0.0) then if ((intensities[:natural_gas] += pool_adjustment) < 0.0) then if ((intensities[:fuel_oil] += intensities[:natural_gas]) < 0.0) then if ((intensities[:electricity] += intensities[:fuel_oil]) < 0.0) then intensities[:electricity] = 0 end intensities[:fuel_oil] = 0 end intensities[:natural_gas] = 0 end end intensities
Conclusion: {:natural_gas=>79.91923064431639, :fuel_oil=>11.514354037589271, :electricity=>133.17120157671994, :district_heat=>5.109793377939008}
Method: from degree days, occupancy rate, and user inputs.
inputs = characteristics.dup inputs.delete(:occupancy_rate) inputs[:lodging_rooms] = inputs.delete(:property_rooms) inputs[:percent_cooled] = inputs.delete(:ac_coverage) inputs.delete_if { |k, v| v.nil? } kernel = CommercialBuildingEnergyConsumptionSurveyResponse.new(inputs) n, f, e, d = kernel.fuzzy_infer(:natural_gas_per_room_night, :fuel_oil_per_room_night, :electricity_per_room_night, :district_heat_per_room_night) { :natural_gas => ((n / occupancy_rate)), :fuel_oil => ((f / occupancy_rate)), :electricity => ((e / occupancy_rate)), :district_heat => ((d / occupancy_rate)) }
Conclusion: 0.601
Method: from country.
country.lodging_occupancy_rate
Conclusion: 0.540387
Method: from electricity mix.
electricity_mix.co2_emission_factor
Conclusion: 0.00021695
Method: from electricity mix.
electricity_mix.ch4_emission_factor
Conclusion: 0.0021062
Method: from electricity mix.
electricity_mix.n2o_emission_factor
Conclusion: AZNM egrid subregion electricity
Method: from egrid subregion.
egrid_subregion.electricity_mix
Conclusion: 1166.11
Method: from climate division.
climate_division.heating_degree_days
Conclusion: 1552.22
Method: from climate division.
climate_division.cooling_degree_days
Conclusion: US
Method: from state.
Country.united_states
Conclusion: AZNM
Method: from zip code.
zip_code.egrid_subregion
Conclusion: Las Vegas
Method: from zip code.
zip_code.description
Conclusion: NV4
Method: from zip code.
zip_code.climate_division
Conclusion: 2.0
Method: from rooms, duration, date, and timeframe.
date = if date.is_a?(Date) then date else Date.parse(date.to_s) end if timeframe.include?(date) then ((duration / 86400.0) * rooms) else 0 end
Conclusion: 2019-01-01
Method: from timeframe.
timeframe.from
Estimate provided by Brighter Planet CM1. Calculations are performed using data from a variety of public sources. To cite this estimate, credit Brighter Planet, "Lodging impact calculation." <http://impact.brighterplanet.com/lodgings?duration=172800&rooms=1&timeframe=2019-01-01%2F2020-01-01&zip_code=89109>, retrieved 2019-02-16T15:49:23Z.