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Title: Updated greenhouse gas and criteria air pollutant emission factors and their probability distribution functions for electricity generating units

Abstract

Greenhouse gas (CO{sub 2}, CH{sub 4} and N{sub 2}O, hereinafter GHG) and criteria air pollutant (CO, NO{sub x}, VOC, PM{sub 10}, PM{sub 2.5} and SO{sub x}, hereinafter CAP) emission factors for various types of power plants burning various fuels with different technologies are important upstream parameters for estimating life-cycle emissions associated with alternative vehicle/fuel systems in the transportation sector, especially electric vehicles. The emission factors are typically expressed in grams of GHG or CAP per kWh of electricity generated by a specific power generation technology. This document describes our approach for updating and expanding GHG and CAP emission factors in the GREET (Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation) model developed at Argonne National Laboratory (see Wang 1999 and the GREET website at http://greet.es.anl.gov/main) for various power generation technologies. These GHG and CAP emissions are used to estimate the impact of electricity use by stationary and transportation applications on their fuel-cycle emissions. The electricity generation mixes and the fuel shares attributable to various combustion technologies at the national, regional and state levels are also updated in this document. The energy conversion efficiencies of electric generating units (EGUs) by fuel type and combustion technology are calculated on the basismore » of the lower heating values of each fuel, to be consistent with the basis used in GREET for transportation fuels. On the basis of the updated GHG and CAP emission factors and energy efficiencies of EGUs, the probability distribution functions (PDFs), which are functions that describe the relative likelihood for the emission factors and energy efficiencies as random variables to take on a given value by the integral of their own probability distributions, are updated using best-fit statistical curves to characterize the uncertainties associated with GHG and CAP emissions in life-cycle modeling with GREET.« less

Authors:
; ; ;  [1]
  1. Energy Systems
Publication Date:
Research Org.:
Argonne National Lab. (ANL), Argonne, IL (United States)
Sponsoring Org.:
EE OFFICE OF BIOMASS PROGRAM; VEHICLE TECHNOLOGY PROGRAM; HYDROGEN AND FUEL CELLS PROGRAM; GEOTHERMAL TECHNOLOGIES PROGRAM
OSTI Identifier:
1045758
Report Number(s):
ANL/ESD/12-2
TRN: US1203664
DOE Contract Number:  
DE-AC02-06CH11357
Resource Type:
Technical Report
Country of Publication:
United States
Language:
ENGLISH
Subject:
21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS; 32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; COMBUSTION; DISTRIBUTION FUNCTIONS; ELECTRICITY; ENERGY CONVERSION; FUEL CYCLE; GREENHOUSE GASES; HEATING; LIFE CYCLE; ORGANIC COMPOUNDS; POWER GENERATION; POWER PLANTS; PROBABILITY; TRANSPORTATION SECTOR; VOLATILE MATTER; AIR POLLUTION

Citation Formats

Cai, H, Wang, M, Elgowainy, A, and Han, J. Updated greenhouse gas and criteria air pollutant emission factors and their probability distribution functions for electricity generating units. United States: N. p., 2012. Web. doi:10.2172/1045758.
Cai, H, Wang, M, Elgowainy, A, & Han, J. Updated greenhouse gas and criteria air pollutant emission factors and their probability distribution functions for electricity generating units. United States. doi:10.2172/1045758.
Cai, H, Wang, M, Elgowainy, A, and Han, J. Fri . "Updated greenhouse gas and criteria air pollutant emission factors and their probability distribution functions for electricity generating units". United States. doi:10.2172/1045758. https://www.osti.gov/servlets/purl/1045758.
@article{osti_1045758,
title = {Updated greenhouse gas and criteria air pollutant emission factors and their probability distribution functions for electricity generating units},
author = {Cai, H and Wang, M and Elgowainy, A and Han, J},
abstractNote = {Greenhouse gas (CO{sub 2}, CH{sub 4} and N{sub 2}O, hereinafter GHG) and criteria air pollutant (CO, NO{sub x}, VOC, PM{sub 10}, PM{sub 2.5} and SO{sub x}, hereinafter CAP) emission factors for various types of power plants burning various fuels with different technologies are important upstream parameters for estimating life-cycle emissions associated with alternative vehicle/fuel systems in the transportation sector, especially electric vehicles. The emission factors are typically expressed in grams of GHG or CAP per kWh of electricity generated by a specific power generation technology. This document describes our approach for updating and expanding GHG and CAP emission factors in the GREET (Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation) model developed at Argonne National Laboratory (see Wang 1999 and the GREET website at http://greet.es.anl.gov/main) for various power generation technologies. These GHG and CAP emissions are used to estimate the impact of electricity use by stationary and transportation applications on their fuel-cycle emissions. The electricity generation mixes and the fuel shares attributable to various combustion technologies at the national, regional and state levels are also updated in this document. The energy conversion efficiencies of electric generating units (EGUs) by fuel type and combustion technology are calculated on the basis of the lower heating values of each fuel, to be consistent with the basis used in GREET for transportation fuels. On the basis of the updated GHG and CAP emission factors and energy efficiencies of EGUs, the probability distribution functions (PDFs), which are functions that describe the relative likelihood for the emission factors and energy efficiencies as random variables to take on a given value by the integral of their own probability distributions, are updated using best-fit statistical curves to characterize the uncertainties associated with GHG and CAP emissions in life-cycle modeling with GREET.},
doi = {10.2172/1045758},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2012},
month = {7}
}

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