Updated Greenhouse Gas and Criteria Air Pollutant Emission Factors and Their Probability Distribution Functions for Electricity Generating Units

Technical Report · Tue May 01 00:00:00 EDT 2012

DOI:https://doi.org/10.2172/1045758· OSTI ID:1045758

Cai, H. ^[1]; Wang, M. ^[1]; Elgowainy, A. ^[1]; Han, J. ^[1]

---

1. Argonne National Laboratory (ANL), Argonne, IL (United States)

Greenhouse gas (CO₂, CH₄ and N₂O, hereinafter GHG) and criteria air pollutant (CO, NO_x, VOC, PM₁₀, PM_2.5 and SO_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.

• Research Organization: Argonne National Laboratory (ANL), Argonne, IL (United States)
• Sponsoring Organization: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Office of Sustainable Transportation. Bioenergy Technologies Office (BETO); USDOE Office of Energy Efficiency and Renewable Energy (EERE), Office of Sustainable Transportation. Vehicle Technologies Office (VTO); USDOE Office of Energy Efficiency and Renewable Energy (EERE), Office of Sustainable Transportation. Hydrogen Fuel Cell Technologies Office (HFTO); USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Geothermal Technologies Office
• DOE Contract Number: AC02-06CH11357
• OSTI ID: 1045758
• Report Number(s): ANL/ESD/12---2
• Country of Publication: United States
• Language: ENGLISH

Related Subjects

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION
AIR POLLUTION
COMBUSTION
DISTRIBUTION FUNCTIONS
ELECTRICITY
ENERGY CONVERSION
FUEL CYCLE
GREENHOUSE GASES
HEATING
LIFE CYCLE
ORGANIC COMPOUNDS
POWER GENERATION
POWER PLANTS
PROBABILITY
TRANSPORTATION SECTOR
VOLATILE MATTER