Past Projects
2006-2007
- USEPA Project
- New Jersey Mercury Project
2003-2005
- USEPA (RTP), Houston/Atlanta Project
-
USEPA (Washington, DC) Water Quality Project
-
NCDENR Wetlands Project
- NCDENR Charlotte PM fine Forecasting Project
Fall 2002
- USEPA (RTP) Project
-
USEPA (Washington) Project
-
NCDENR Project
Fall 2001
- USEPA Project
- Environment Canada Project
-
NCDENR Project
Fall 2000
- USEPA Project
-
Forsyth County Project
Spring 2000
- NCDENR Project
-
USEPA Project
Fall 1999
- Southern Oxidant Study
-
Charlotte Ozone Study
2006-2007
Understanding Historical Emission Trends
C
Clients...
Dr. Linda Chappell, US EPA
Brief Description
Air pollution is harmful to people and the environment. In order to better understand the nature of the environmental problem, emission inventories are developed for all sources in an area. They are based upon engineering estimates. They represent both gases and particles of air pollution that are emitted into the air by a variety of sources. Emission inventories (E/I) change over time and may be reduced as result of emission control programs. The U. S. Environmental Protection Agency’s (USEPA) Office of Air Quality Planning and Standards (OAQPS) is responsible for the National Emissions Inventory (NEI). Emissions data are collected by state, local, and tribal and the federal governments. The E/I includes a number of different sources: (1) Point sources – stationary locations of pollution include factories, pulp and paper mills, petroleum refineries, electric power plants, etc.; (2) Mobile Sources - cars and trucks, airplanes, etc.; (3) Biogenic sources – natural sources of emissions – trees, animals, etc.; (4) Area Sources – small stationary source of emission such as dry cleaners and degreasing operations. Future emissions are critically important when trying to determine the impact of air quality standard regulations that are protective of human health and the environment. How will regulations impact sources in the future making changes needed to reduce emissions to achieve the air quality standards? Emissions inventories are projected for future years to conduct analyses for our rulemakings. The methods for forecasting emissions into the future are complex. The objective of this project is to improve upon the existing method to forecast future emissions. Three sectors will be examined to forecast future emissions – petroleum refineries, chemical manufacturing, and the fuel combustion industrial sector. The pollutant that will be examined is nitrogen oxides. We will try and take technological change into account using gross domestic product and other variables. The Presidents Energy Plan to reduce oil consumption by 20 percent in 10 years will be used to forecast future emissions. Different alternatives will be examined in the analysis.
Students
Joshua Warren
Data
Emissions Data- EPA
New Jersey Mercury Data
Clients
New Jersey Department of Environment
Brief Description
This project examines gaseous elemental mercury, particle bound mercury and reactive
gas mercury measurements taken from June to August, 2005 in Elizabeth, NJ. It is expected
that this project will expand to include data for two years and from a second site in
New Jersey (New Brunswick).
Students
Fawn Hornsby
Wilma "Billie" Jackson
Data
Original Data
Data for June 2005 from Elizabeth, NJ - Excel spreadsheet
Data for July 2005 from Elizabeth, NJ - Excel spreadsheet
Data for August 2005 from Elizabeth, NJ - Excel spreadsheet
Transformed SAS Datasets (good data only)
Transformed June 2005 Elizabeth SAS dataset
Transformed July 2005 Elizabeth SAS dataset
Transformed August 2005 Elizabeth SAS dataset
Transformed June-August 2005 Elizabeth SAS dataset
Latest data from NJ
ncstate04.zip
ncstate05.zip
ncstatelog.xls
Tekran QA-QC Procedure.doc
2003-2005
USEPA (RTP), Houston/Atlanta Project with
University of Texas, Texas Commission on Environmental Quality, EPA
Region 4, Georgia Department of Natural Resources and Spelman
College
Clients
Mr. David Mobley, USEPA, Office of Research and
Development, RTP, NC
Email: Mobley.David@epamail.epa.gov
Dr. Cyril Durrenberger, University of Texas, Austin, TX
Email: cdurrenberger@mail.utexas.edua.gov
Mr. Erik Gribbin, Texas Commission on Environmental Quality, Austin, TX
Email: EGRIBBIN@tceq.stat.tx.us
Mr. Fred Dimmick, USEPA, Office of Air Quality Planning and
Standards, RTP, NC
Email: Dimmick.Fred@epamail.epa.gov
Mr. David Mintz, USEPA, Office of Air Quality Planning and
Standards, RTP, NC
Email: Mintz.David@epamail.epa.gov
Mr. Van Shrieves, USEPA Region 4, Atlanta, GA
Email: shrieves.van@epa.gov
Dr. Nagambal Shah, Spelman College, Atlanta, GA
Email: nshah@spelman.edu
Dr. Monica Stephens, Spelman College, Atlanta, GA
Email: mstephens@spelman.edu
Brief Description
This project examines both volatile organic compound and nitrogen
oxide data in both Houston and Atlanta. The Houston Project focuses on
the corroboration of the emission inventory. Can the discrepency between
VOC to NOx emission ratios and VOC to NOx ambient ratios be explained?
The Atlanta portion of the project will focus on examination of the VOC
data to see if the PAMS sites are being influenced by VOC sources. Time
permitting, the study will corroborate the VOC and NOx emission
inventories in Atlanta as well.
Students
Louise Camalier
Brendan Yoshimoto
Bryan Stines
Data
Original SAS dataset
Transformed SAS dataset
Transformed
SAS dataset (reposted in Excel format)
The transformed dataset has variables named according to the EPA parameter numbers.
See here to determine
what parameter codes correspond to what parameters.
Met data SAS
dataset
USEPA (Washington, DC) Water Quality
Project
Clients
USEPA, Office of Environmental Information, Washington, DC
Dr. Barry Nussbaum
Email: Nussbaum.Barry@epamail.epa.gov
Dr. Ming Chang
Email: chang.ming@epa.gov
Brief Description
The project focuses on the water quality trends in the Raleigh-Durham metropolitan area.
The students will:
(1) identify the water quality parameters with the most complete water data over 30 and 20 year periods;
(2) determine if there are any collinear water quality data and display them graphically;
(3) determine the impacts of both environmental regulations and urban growth on water quality; and
(4) create one or more statistical model to fit the data over different time periods.
Students
Ornella Darlington
Brian Currier
Data
New Data:
Chapel Hill Rainfall Data
Durham Rainfall Data
NC State Rainfall Data
Raleigh Rainfall Data
RDU Rainfall Data
Rougemount Rainfall Data
Old Data:
Original Excel data file
SAS dataset
brian.sas7bdat
ornella.sas7bdat
Updated
ornella.sas7bdat
You will need to look in the original Excel file (worksheet Parameters) to
find what columns in the SAS dataset correspond to what parameters. The row number
in the Parameters worksheet corresponds to the number in the variable name (the first
variable is P33, so look in row 33 of the Excel file to see what parameter is there.)
Note that the original dataset was drastically reduced in size from roughly 1000
variables to 31 variables. The criterion for keeping a parameter's data was that it
had to have at least 2500 observations out of the roughly 6000 observations in the
original file.
NCDENR Wetlands Project
Clients
Mr. Steve Kroeger
Email: steve.kroeger@ncmail.net
Mr. Bryn Tracy
Email: bryn.tracy@ncmail.net
Brief Description
This project examines the question,
"Can 'swamp waters' be defined or characterized using water quality measurements?"
The project focuses on the Coastal Plain and Sandhills.
The students will look at dissolved oxygen and other parameters to identify wetlands
and examine previous classification of swamplands.
Students
Sudria Humes
Jera Mendenhall
Data
Modified Coastal Basins Dataset
Station Information Excel Spreadsheet
Merged SAS Dataset
Cleaned
Dataset
NCDENR Charlotte PM fine Forecasting
Project
Clients
Sheila Holman
Email: sheila.homan@ncmail.net
George Bridgers
Email: Bridgers.George@ncmail.net
Mike Abraczinskas
Email: Michael.Abraczinskas@ncmail.net
Brief Description
A model to forecast PM fine air pollution for Charlotte will be
developed by the students. The model will examine both the current form
of the PM fine standard as well as daily maximum hour and 3-hour form of
the PM fine standard.
Students
Not yet assigned.
Data
Map of Site Locations
Directory listing of Original Data from Client
Directory listing of SAS datasets
Note that there are two different sites included in the Charlotte PM
fine data set (charlotte_pm).
Ozone
dataset
Fall 2002 Semester
USEPA (RTP) Project
Clients
USEPA, Office of Air Quality Planning and Standards, RTP, NC
Fred Dimmick
Email: Dimmick.Fred@epamail.epa.gov
Neil Frank
Email: Frank.Neil@epamail.epa.gov
David Mintz
Email: Mintz.David@epamail.epa.gov
Brief Description
This project involves an exploratory analysis of fine particulate matter speciated data and gaseous volatile organic compound data. Is there a relationship between the fine particulate carboneous data and the gaseous VOC data? Data sets in four cities will be examined.
Students
Not yet assigned.
Data
PM fine hourly data from a New York City site with more data to come. Four cities with PAMS data and PM fine speciated data. Data files:
pm25speciation.sas7bdat
An email from David Mintz.
pm25hour_header.sas7bdat
pm25hour_2000.sas7bdat
pm25hour_2001.sas7bdat
The preceding three files are available in ZIP format as well.
four_cities_speciation.xls
The following dataset should contain the 2001 data for 69 different pollutants (and some ambient conditions) from the PAMS monitors:
pams2001.sas7bdat available in ZIP format.
USEPA (Washington) Project
Clients
USEPA, Office of Environmental Information, Washington, DC
Barry Nussbaum
Email: Nussbaum.Barry@epamail.epa.gov
Cary Roberts
Email: Roberts.Cary@epamail.epa.gov
Brief Description
Assessing urban growth land use patterns and air quality trends in the Phoenix and Raleigh-Durham metropolitan areas. To facilitate the understanding of urban pressures on the environment by integrating and analyzing current data, such as urban environmental indicators and criteria air pollutant monitoring data, to understand the relationship between population growth, land use/land cover change, and air quality in large metropolitan areas. To communicate the relationship, i.e., tell the story of changing urban landscapes and air quality.
Students
Not yet assigned.
Data
Twenty years worth of summary statistics provided by David Mintz for TSP, PM10, PM fine, CO, lead, NO2, O3 and SO2. Data files (modified datasets are in parantheses):
phxral_co_1982_2001.sas7bdat (co) phxral_no2_1982_2001.sas7bdat (no2)
phxral_o3_1982_2001.sas7bdat (o3) phxral_pb_1982_2001.sas7bdat (pb)
phxral_pm10_1988_2001.sas7bdat (pm10) phxral_pm25_1999_2001.sas7bdat (pm25)
phxral_so2_1982_2001.sas7bdat (so2) phxral_tsp_1982_1991.sas7bdat (tsp)
A WordPerfect document from the clients.
raleigh_data.xls (raleigh_info.doc)
phoenix_data.xls
SAS dataset of Raleigh & Phoenix data (Reference sheet for variable names)
NCDENR Project
Clients
North Carolina Department of Environment and Natural Resources
Harvi Cooper
Email: Harvi.Cooper@ncmail.net
Steve Few
Email: Steve.Few@ncmail.net
Brief Description
Examine the Guidance for Statistical Evaluation of Hazardous Waste Constituent Levels in Soils. Focus on sampling variability, sample size and defining hazardous waste conditions.
Students
Not yet assigned.
Data
Data provided by Steve Few. Data files:
USCG_cut.xls
SAS dataset: uscg.sas7bdat
SAS program to read in the Excel file: coast_guard.sas
metals.xls
Fall 2001 Semester
USEPA Project
Clients
Fred Dimmick
Email: Dimmick.Fred@epamail.epa.gov
David Mintz
Email: Mintz.David@epamail.epa.gov
Brief Description
Students
Data
The data for this project is located in the following SAS datasets. For all of these datasets, you will need to right-click on the dataset and save it to a directory of your choice that you can access from SAS. Then use a libname in SAS to allow SAS to access the datasets.
The first of these datasets are meteorological data.
barometricpressure
temperature
winddirection
windspeed
solarradiation
relativehumidity
The next datasets are described below.
pm25 (hourly PM2.5 data)
rpfunf263 (corresponding 24 hour PM2.5 FRM data)
hpfunf263 (header file for rpfunf263 (contains variables like state and county names, lat long, etc. It can be merged with rpfunf263 by site.))
ozone (hourly ozone data)
ozone8hrdailymax (corresponding 8-hour daily max)
The PAMS sites data is located in the following two SAS datasets. They are located in Bill Hunt's Atlanta-Ozone directory. (If you add whunt in UNITY, you can access these files in /ncsu/whunt/Atlanta-Ozone/.)
atlanta conyers
Notes
When David Mintz sent the data, he included some information in an email. You may be interested in reading it. He also sent another email with more description of the data.
Environment Canada Project
Clients
Tom Dann
Email: dann.tom@etc.ec.gc.ca
Tom Furmanczyk
Email: Tom.Furmanczyk@EC.GC.CA
Brief Description
Students
Data
The following Excel files contain meteorological data from 5 sites in Canada for the years 1998, 1999 and 2000.
3012205_1998.xls
3012205_1999.xls
3012205_2000.xls
3031093_1998.xls
3031093_1999.xls
3031093_2000.xls
6137287_1998.xls
6137287_1999.xls
6137287_2000.xls
6153194_1998.xls
6153194_1999.xls
6153194_2000.xls
6158733_1998.xls
6158733_1999.xls
6158733_2000.xls
The following text files contain pollution data (ozone and PM 2.5). There is a Word file below that contains a key to these text files.
Ozone data
PM 2.5 data
Notes
Meteorological Data Sites (Excel file)
Data Collection Sites (Excel file)
Key to Text Files (Word file)
NCDENR Project
Clients
Steve Few
Email: Steve.Few@ncmail.net
Brief Description
Students
Data
Below is a SAS dataset that contains ozone, PM 2.5 and met data for the Millbrook site in Raleigh for June 2000 through December 2000.
mball
The QC project data is below:
PAM98QC.xls
UAM98CL.xls
Notes
Here is some SAS code to help in making the u-v wind transformations: uv_transform.sas
Steve Few sent a description of the QA/QC dataset. He also sent an email. The following links may be of interest:
http://www.epa.gov/ttnamti1/files/ambient/pams/stvlt.pdf
http://www.epa.gov/ttnamti1/files/ambient/pams/
http://www.epa.gov/ttnamti1/pamsmain.html
Fall 2000 Semester
USEPA Project
Clients
Barbara Parzygnat
Email: Parzygnat.Barbara@epamail.epa.gov
Conniesue Oldham
Email: Oldham.Conniesue@epamail.epa.gov
Brief Description
Data
R29496
- EPA Region 2, 1994 to 1996
Notes
EPA
PAMS Databases
Forsyth County Project
Clients
Lewis Weinstock
Program Manager, Air Monitoring Division
Forsyth County Environmental Affairs
Department
Email: weinstl1@hathor.co.forsyth.nc.us
Web: http://www.co.forsyth.nc.us/EnvAffairs/
Pat Reagan
Email: reaganpa@co.forsyth.nc.us
Brief Description
Develop 2 models to predict PM fine for Pollutant Standards
Index reporting; one model will be for summer and another for winter.
Data
You can import these files into SAS using the SAS import faciility,
or there are harder ways that you can ask me about.
Forsyth2.xls
forsyth_met99.txt
forsyth_met00.txt
triado3.xls
- ozone data
Raw
Met Data 01/99 to 04/00
Raw
Met Data 05/00 to 08/00
Notes
These are just the emails that came along with the respective files
(from Lewis Weinstock)
Forsyth
County Notes #1 - Regarding forsyth2.xls
Forsyth
County Notes #2 - Regarding Met data
Forsyth
County Notes #3 - Regarding Ozone data
Forsyth
County Notes #4 - Regarding Raw Met Data
Spring 2000 Semester
NCDENR Project
Clients
Mr. George Murray, NCDENR
Mr. Steve Few, NCDENR
Mr. Pat Bello, NCDENR
Brief Description
AWMA Abstract
Students
Data
8
- Hour Ozone Data
DurhamHealth0630001
GreensboroEB0810009
greenvilleGV1470005
Hickory0350004
kinstonLCC1070004
Millbrook1830014
(Includes links to millbrook met data)
dates_julian.xls
(Excel 97 Format)
master8hr.xls
(Excel 97 Format)
readmeDATA.doc
(Word 97 Format)
Notes
USEPA Project
Clients
Dr. Conniesue Oldham, USEPA
Mr. Bill Cox, USEPA
Brief Description
AWMA Abstract
Students
Data
WASCPORT
(File sent by Bill Cox can be imported into SAS using the import_epa_data.sas
program).
Notes
Fall 1999 Semester
Southern Oxidant Study
Clients
Dr. Ellis Cowling, NCSU, SOS
Dr. Kenneth Schere, USEPA
Brief Description
Analyze the impact of precursor pollutants and meteorology
on ozone in the Memphis, TN area.
AWMA
Abstract
Students
Joe McMichael
Ronnie DeFrancis
Charlotte Ozone Study
Clients
Mr. George Murray, NCDENR
Mr. Steve Few, NCDENR
Brief Description
Analyze the impact of meteorological variables on ozone
level and formulate a model to predict next day ozone based on the most
significant meteorological variables for the Charlotte, NC area.
AWMA
Abstract
Students
Daric Harrington
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