title: Evaluation of low wind modeling approaches for two tall-stack databases.
abstract: The performance of the AERMOD air dispersion model under low wind speed conditions, especially for applications with only one level of meteorological data and no direct turbulence measurements or vertical temperature gradient observations, is the focus of this study. The analysis documented in this paper addresses evaluations for low wind conditions involving tall stack releases for which multiple years of concurrent emissions, meteorological data, and monitoring data are available. AERMOD was tested on two field-study databases involving several SO2 monitors and hourly emissions data that had sub-hourly meteorological data (e.g., 10-min averages) available using several technical options: default mode, with various low wind speed beta options, and using the available sub-hourly meteorological data. These field study databases included (1) Mercer County, a North Dakota database featuring five SO2 monitors within 10 km of the Dakota Gasification Company's plant and the Antelope Valley Station power plant in an area of both flat and elevated terrain, and (2) a flat-terrain setting database with four SO2 monitors within 6 km of the Gibson Generating Station in southwest Indiana. Both sites featured regionally representative 10-m meteorological databases, with no significant terrain obstacles between the meteorological site and the emission sources. The low wind beta options show improvement in model performance helping to reduce some of the over-prediction biases currently present in AERMOD when run with regulatory default options. The overall findings with the low wind speed testing on these tall stack field-study databases indicate that AERMOD low wind speed options have a minor effect for flat terrain locations, but can have a significant effect for elevated terrain locations. The performance of AERMOD using low wind speed options leads to improved consistency of meteorological conditions associated with the highest observed and predicted concentration events. The available sub-hourly modeling results using the Sub-Hourly AERMOD Run Procedure (SHARP) are relatively unbiased and show that this alternative approach should be seriously considered to address situations dominated by low-wind meander conditions.
  
  
  CONCLUSIONS
  AERMOD was evaluated with two tall stack databases (in North Dakota and Indiana) in areas of both flat and elevated terrain. AERMOD cases included the regulatory default mode, low wind speed beta options, and use of the Sub-Hourly AERMOD Run Procedure (SHARP). The low wind beta options show improvement in model performance (especially in higher terrain areas), helping to reduce some of the over-prediction biases currently present in regulatory default AERMOD. The SHARP results are relatively unbiased and show that this approach should be seriously considered to address situations dominated by low-wind meander conditions.
authors: a AECOM , Chelmsford , MA , USA.
authors: Robert
authors: R
authors: Paine
authors: a AECOM , Chelmsford , MA , USA.
authors: Olga
authors: O
authors: Samani
authors: a AECOM , Chelmsford , MA , USA.
authors: Mary
authors: M
authors: Kaplan
authors: b Electric Power Research Institute , Palo Alto , CA , USA.
authors: Eladio
authors: E
authors: Knipping
authors: b Electric Power Research Institute , Palo Alto , CA , USA.
authors: Naresh
authors: N
authors: Kumar
mesh_terms: D000393:Air Pollutants / Q000032:analysis*; D016208:Databases, Factual; D004784:Environmental Monitoring / Q000379:methods*; D007196:Indiana; D008962:Models, Theoretical; D009658:North Dakota; D011210:Power Plants; D013458:Sulfur Dioxide / Q000032:analysis*; D014919:Wind
chemical_list: D000393:Air Pollutants; D013458:Sulfur Dioxide