You are here:
Nonparametric Trajectory Analysis of R2PIER Data
Citation:
Henry, R., G. Hagler, AND D. Birkett. Nonparametric Trajectory Analysis of R2PIER Data. AWMA Air Quality Measurements and Technology, Long Beach, California, November 07 - 09, 2017.
Impact/Purpose:
This is an abstract to propose a presentation on the Region 2 Port-area Investigation of Emissions Reductions project at the AWMA Measurements Conference.
Description:
Strategies to isolate air pollution contributions from sources is of interest as voluntary or regulatory measures are undertaken to reduce air pollution. When different sources are located in close proximity to one another and have similar emissions, separating source emissions trends in situ is difficult. During 2012-2015, the EPA conducted the Region 2 Port-area Investigation of Emissions Reduction (R2PIER) project which collected 1-minute air quality and meteorological data at a site just south of the Port of Newark, New Jersey. The primary data analysis method used is Nonparametric Trajectory Analysis (NTA). New advances in NTA methodology were developed for this project, including estimating background concentrations from a single site, and sensitivity of the results to the basic assumptions of NTA. NTA isolated the impact of the Port of Newark on the R2PIER monitoring site, and the effect of four other sources: Newark International Airport, Newark Bay, New York Container Terminal, and a nearby section of the New Jersey Turnpike. Urban background was the major contributor to concentrations of sulfur dioxide (43%), nitrogen oxides (56%), carbon monoxide (76%), particulate black carbon (59%), and particulate matter less than 2.5 micrometers in aerodynamic diameter (PM2.5, 73%). After subtracting the background, the highest or second highest average concentrations of these pollutants were associated with air that came from the Port of Newark. These Port-attributed concentrations decreased by up to ~50% during the study. The notable exception was PM2.5 which increased during the study period. Analysis showed that the results are not sensitive to key model assumptions.