In 2010, the U.S. Environmental Protection Agency (EPA) adopted a 1-hour nitrogen dioxide (NO2) National Ambient Air Quality Standard (NAAQS) of 100 parts per billion (ppb) or approximately 188 micrograms per cubic meter (µg/m3) that is considerably more stringent than the longstanding annual standard of 53 ppb (100 µg/m3). New or modified compressor units may be encumbered by federal or state regulatory requirements to demonstrate compliance with the NO2 NAAQS using AERMOD, EPA’s dispersion model, because the new NAAQS greatly reduces the compliance margin. Compressor...
In 2010, the U.S. Environmental Protection Agency (EPA) adopted a 1-hour nitrogen dioxide (NO2) National Ambient Air Quality Standard (NAAQS) of 100 parts per billion (ppb) or approximately 188 micrograms per cubic meter (µg/m3) that is considerably more stringent than the longstanding annual standard of 53 ppb (100 µg/m3). New or modified compressor units may be encumbered by federal or state regulatory requirements to demonstrate compliance with the NO2 NAAQS using AERMOD, EPA’s dispersion model, because the new NAAQS greatly reduces the compliance margin. Compressor stations have been increasingly requested to model source contribution to other nearby permitting actions through no new action on their part. Model conservatism and performance concerns has limited NO2 NAAQS compliance options necessitating the need to improve model estimates for reciprocating engine drivers at pipeline compressor stations.
AERMOD was developed and validated with a primary focus on larger sources with taller stacks, such as electric utility boilers, which results in model conservatism for sources such as compressor stations with shorter stacks that result in near-field modeled impacts. This report summarizes additional analyses conducted and reviewed with EPA that were completed to assess and reduce model conservatism and improve overall model performance. This report presents a more detailed analysis of modeled versus observed results, model performance, and recommendations for model improvements. These analyses also evaluated other ongoing efforts (e.g., PRIME2 downwash improvements and integration of the ADMS chemistry module an alternative in AERMOD) using the data collected from this program may be used to assess these revisions.
This final report summarizes the deeper dive into the NOx chemistry, dispersion, and downwash performance assessments within AERMOD based on the Balko dataset. Specific recommendations are made throughout this report to improve overall model performance.