Evaluation of NO2 predictions by the plume volume molar ratio method (PVMRM) and ozone limiting method (OLM) in AERMOD using new field observations.
The U.S. Environmental Protection Agency (EPA) plume volume molar ratio method (PVMRM) and the ozone limiting method (OLM) are in the AERMOD model to predict the 1-hr average NO2/NO(x) concentration ratio. These ratios are multiplied by the AERMOD predicted NO(x) concentration to predict the 1-hr average NO2 concentration. This paper first briefly reviews PVMRM and OLM and points out some scientific parameterizations that could be improved (such as specification of relative dispersion coefficients) and then discusses an evaluation of the PVMRM and OLM methods as implemented in AERMOD using a new data set. While AERMOD has undergone many model evaluation studies in its default mode, PVMRM and OLM are nondefault options, and to date only three NO2 field data sets have been used in their evaluations. Here AERMOD/PVMRM and AERMOD/OLM codes are evaluated with a new data set from a northern Alaskan village with a small power plant. Hourly pollutant concentrations (NO, NO2, ozone) as well as meteorological variables were measured at a single monitor 500 m from the plant. Power plant operating parameters and emissions were calculated based on hourly operator logs. Hourly observations covering 1 yr were considered, but the evaluations only used hours when the wind was in a 60 degrees sector including the monitor and when concentrations were above a threshold. PVMRM is found to have little bias in predictions of the C(NO2)/C(NO(x)) ratio, which mostly ranged from 0.2 to 0.4 at this site. OLM overpredicted the ratio. AERMOD overpredicts the maximum NO(x) concentration but has an underprediction bias for lower concentrations. AERMOD/PVMRM overpredicts the maximum C(NO2) by about 50%, while AERMOD/OLM overpredicts by a factor of 2. For 381 hours evaluated, there is a relative mean bias in C(NO2) predictions of near zero for AERMOD/PVMRM, while the relative mean bias reflects a factor of 2 overprediction for AERMOD/OLM.


CONCLUSIONS
This study was initiated because the new stringent 1-hr NO2 NAAQS has prompted modelers to more widely use the PVMRM and OLM methods for conversion of NO(x) to NO2 in the AERMOD regulatory model. To date these methods have been evaluated with a limited number of data sets. This study identified a new data set of ambient pollutant and meteorological monitoring near an isolated power plant in Wainwright, Alaska. To supplement the existing evaluations, this new data were used to evaluate PVMRM and OLM. This new data set has been and will be made available to other scientists for future investigations.
Epsilon Associates, Inc., 3 Clock Tower Place, Suite 250, Maynard, MA 01754, USA. ehendrick@epsilonassociates.com
Elizabeth M
EM
Hendrick
Vincent R
VR
Tino
Steven R
SR
Hanna
Bruce A
BA
Egan
D000393:Air Pollutants / Q000032:analysis*; D000413:Alaska; D016208:Databases, Factual; D004784:Environmental Monitoring / Q000379:methods*; D008962:Models, Theoretical; D009585:Nitrogen Dioxide / Q000032:analysis; D009589:Nitrogen Oxides / Q000032:analysis*; D010126:Ozone / Q000737:chemistry; D011210:Power Plants; D014919:Wind
D000393:Air Pollutants; D009589:Nitrogen Oxides; D010126:Ozone; D009585:Nitrogen Dioxide