title: Modeled response of ozone to electricity generation emissions in the northeastern United States using three sensitivity techniques.
abstract: Electrical generation units (EGUs) are important sources of nitrogen oxides (NOx) that contribute to ozone air pollution. A dynamic management system can anticipate high ozone and dispatch EGU generation on a daily basis to attempt to avoid violations, temporarily scaling back or shutting down EGUs that most influence the high ozone while compensating for that generation elsewhere. Here we investigate the contributions of NOx from individual EGUs to high daily ozone, with the goal of informing the design of a dynamic management system. In particular, we illustrate the use of three sensitivity techniques in air quality models-brute force, decoupled direct method (DDM), and higher-order DDM-to quantify the sensitivity of high ozone to NOx emissions from 80 individual EGUs. We model two episodes with high ozone in the region around Pittsburgh, PA, on August 4 and 13, 2005, showing that the contribution of 80 EGUs to 8-hr daily maximum ozone ranges from 1 to >5 ppb at particular locations. At these locations and on the two high ozone days, shutting down power plants roughly 1.5 days before the 8-hr ozone violation causes greater ozone reductions than 1 full day before; however, the benefits of shutting down roughly 2 days before the high ozone are modest compared with 1.5 days. Using DDM, we find that six EGUs are responsible for >65% of the total EGU ozone contribution at locations of interest; in some locations, a single EGU is responsible for most of the contribution. Considering ozone sensitivities for all 80 EGUs, DDM performs well compared with a brute-force simulation with a small normalized mean bias (-0.20), while this bias is reduced when using the higher-order DDM (-0.10).
  
  
  CONCLUSIONS
  Dynamic management of electrical generation has the potential to meet daily ozone air quality standards at low cost. We show that dynamic management can be effective at reducing ozone, as EGU contributions are important and as the number of EGUs that contribute to high ozone in a given location is small (<6). For two high ozone days and seven geographic regions, EGUs would best be shut down or their production scaled back roughly 1.5 days before the forecasted exceedance. Including online sensitivity techniques in an air quality forecasting model can provide timely and useful information on which EGUs would be most beneficial to shut down or scale back temporarily.
authors.affiliation: a Environmental Sciences & Engineering, University of North Carolina , Chapel Hill , North Carolina , USA.|b Department of Education , University of North Carolina at Asheville , Asheville , North Carolina , USA.
authors.forename: Evan
authors.initials: E
authors.lastname: Couzo
authors.affiliation: a Environmental Sciences & Engineering, University of North Carolina , Chapel Hill , North Carolina , USA.|c Ramboll Environ , Arlington , Virginia , USA.
authors.forename: James
authors.initials: J
authors.lastname: McCann
authors.affiliation: a Environmental Sciences & Engineering, University of North Carolina , Chapel Hill , North Carolina , USA.
authors.forename: William
authors.initials: W
authors.lastname: Vizuete
authors.affiliation: d Energy and Mineral Engineering, Penn State University , University Park , Pennsylvania , USA.
authors.forename: Seth
authors.initials: S
authors.lastname: Blumsack
authors.affiliation: a Environmental Sciences & Engineering, University of North Carolina , Chapel Hill , North Carolina , USA.
authors.forename: J Jason
authors.initials: JJ
authors.lastname: West
mesh_terms: D000393:Air Pollutants / Q000032:analysis*; D004784:Environmental Monitoring / Q000379:methods*; D008962:Models, Theoretical; D009511:New England; D009589:Nitrogen Oxides / Q000032:analysis*; D010126:Ozone / Q000032:analysis*; D011210:Power Plants; D014481:United States
chemical_list: D000393:Air Pollutants; D009589:Nitrogen Oxides; D010126:Ozone