title: Accounting for spatial variation of ozone productivity in NOx emission trading.
abstract: The potential air quality benefits of NO(x) emission-trading programs were compared to the air quality benefits of across-the-board NO(x) reductions for point sources in eastern Texas. The comparison was performed by first determining, using the Comprehensive Air Quality Model with extensions (CAMx), the changes in ozone concentrations associated with NO(x) reductions at more than 50 individual facilities in eastern Texas. These facility-specific changes in ozone concentrations due to NO(x) reductions were then converted into a variety of indices representing ozone reduction benefits. Trading scenarios were then evaluated through Monte Carlo simulations. The results indicate that approximately 20% of all trading scenarios result in ozone reduction benefits that deviate by 25% or more from the ozone reduction benefits achieved by across-the-board reductions. This result was independent of the index used to calculate ozone reduction benefit. This variability in the benefits associated with trading scenarios was comparable to the variability in benefits associated with changes in meteorological conditions over the days that were modeled. Additional Monte Carlo simulations indicated that the average benefit associated with NO(x) trading could be improved and that the variability in benefit was reduced by creating a trading program where a small group of high impact facilities are allowed to sell but may not buy NO(x) allowances.
authors.affiliation: Center for Energy and Environmental Resources, University of Texas at Austin, 78758, USA.
authors.forename: C E
authors.initials: CE
authors.lastname: Nobel
authors.forename: E C
authors.initials: EC
authors.lastname: McDonald-Buller
authors.forename: Y
authors.initials: Y
authors.lastname: Kimura
authors.forename: D T
authors.initials: DT
authors.lastname: Allen
mesh_terms: D000393:Air Pollutants / Q000032:analysis*; D000397:Air Pollution / Q000517:prevention & control*; D004784:Environmental Monitoring; D005544:Forecasting; D008962:Models, Theoretical; D009010:Monte Carlo Method; D009584:Nitrogen / Q000032:analysis / Q000737:chemistry*; D010083:Oxidants, Photochemical / Q000032:analysis*; D010087:Oxides / Q000032:analysis / Q000737:chemistry; D010126:Ozone / Q000032:analysis*
chemical_list: D000393:Air Pollutants; D010083:Oxidants, Photochemical; D010087:Oxides; D010126:Ozone; D009584:Nitrogen