Current Projects

Emission Factor Uncertainty

Client

Mr. J. David Mobley, Deputy Director, Atmospheric Modeling and Analysis Division, USEPA

Brief Description

Emission factors are important for estimating and characterizing emissions from sources of air pollution. An emission factor is a representative value that attempts to relate the quantity of a pollutant released to the atmosphere with an activity associated with the release of that pollutant. These factors are usually expressed as the weight of pollutant divided by a unit weight, volume, distance, or duration of the activity emitting the pollutant (e. g., kilograms of particulate emitted per megagram of coal burned). Such factors facilitate estimation of emissions from various sources of air pollution. In most cases, these factors are simply averages of all available data of acceptable quality, and are generally assumed to be representative of long-term averages for all facilities in the source category (i. e., a population average).

The general equation for emission estimation is: E = A x EF x (1 - ER/100). Where: E=Emissions, A=Activity Rate, EF=Emissions Factor, and ER=overall reduction efficiency, %.

The objectives of this project are to: (1) Verify the NOx emission factors from combustion sources with currently available continuous emission monitoring data; (2) Develop quantitative uncertainty indicators for A through E rated emission factors on NOx emissions from combustion sources; and (3) Determine the limitations of applying these quantitative uncertainty indicators to other pollutant and source types.

Complete Description

Students

Allissa Anderson
Colin Geisenhoffer
Brody Heffner
Michael Shaw
Emily Wisner

Data

egu_plant_info.xls
neicemeia2002ncq1.csv
neicemeia2002ncq1.sas7bdat
neicemeia2002ncq2.csv
neicemeia2002ncq2.sas7bdat
neicemeia2002ncq3.csv
neicemeia2002ncq3.sas7bdat
neicemeia2002ncq4.csv
neicemeia2002ncq4.sas7bdat
alldata_nc_2007
allen.xls
roxboro_plant.xls
EF_NOx_Webfire.xls
egu_plant_info_spring_2010

Secondary Ozone Standard

Client

Mr. David Mintz, Statistician, Air Quality Analysis Group, USEPA

Brief Description

The Clean Air Act, which was last amended in 1990, requires EPA to set National Ambient Air Quality Standards (NAAQS) for wide-spread pollutants from numerous and diverse sources considered harmful to public health and the environment. Currently, there are six such pollutants – carbon monoxide, lead, nitrogen dioxide, ozone, particulate matter, and sulfur dioxide. The Clean Air Act established two types of national air quality standards for these pollutants. Primary standards set limits to protect public health, including the health of "sensitive" populations such as asthmatics, children, and the elderly. Secondary standards set limits to protect public welfare, including protection against visibility impairment, damage to animals, crops, vegetation, and buildings. The Clean Air Act requires EPA to review the latest scientific information and standards every five years.

The focus of this project is the secondary standard for ozone. In 2006, EPA proposed a new metric as a possible secondary ozone standard based on scientific consensus that it was more relevant to use to protect vegetation than the 8-hour average health-related metric (which was also the primary standard). However, in 2008, the EPA Administrator ultimately recommended the secondary ozone standard be the same as the primary ozone standard. The goal of this project is to perform exploratory analysis on this metric (called the “cumulative peak-weighted index”) using data sets supplied by the client and provide graphical summaries and interpretations to answer the following 8 questions: (1.) Where and when do higher values tend occur in the US? (2.) How does the peak-weighted hourly value vary during the day, in various types of areas? (3.) How does the monthly cumulative index vary during a year? (4.) How does the 3-month cumulative index vary from year to year? What meteorology conditions are most conducive to high values? (5.) Is it possible to prepare met-adjusted trends? What do they show? (6.) How does monitor altitude matter? (7.) Can ambient analysis help explain the causes of high values, e.g., transport versus local formation? (8.) In light of the above, what issues exist in using air quality models to make predictions of future levels of the 3-month cumulative peak-weighted index?

Complete Description
Ozone NFR draft Sections V and Appendix P Revised 19feb08.doc