Investigation of Indicators for Ozone-NOx-VOC Sensitivity

EPA Grant Number: R826765
Title: Investigation of Indicators for Ozone-NOx-VOC Sensitivity
Investigators: Sillman, Sanford
Institution: University of Michigan
EPA Project Officer: Shapiro, Paul
Project Period: October 1, 1998 through September 30, 2001
Project Amount: $306,407
RFA: Air Pollution Chemistry and Physics (1998) RFA Text |  Recipients Lists
Research Category: Air Quality and Air Toxics , Air , Engineering and Environmental Chemistry

Description:

The project seeks to investigate the use of observation-based indicators for identifying the sensitivity of ozone to nitrogen oxides (NOx) and volatile organic compounds (VOC). In the past, O3-NOx-VOC sensitivity has been based on model predictions, which are difficult to test in the real world. Sillman (1995a) found that model NOx-VOC predictions are correlated with the values of certain "indicator ratios", involving total reactive nitrogen (NOy) and peroxides. Measured values of these ratios might be used either to obtain an observation-based estimate of O3-NOx-VOC sensitivity or as an indirect method for evaluating the accuracy of model NOx-VOC predictions and identifying biases. Model-measurement comparisons for these species can also be used to establish the rate of removal of NOy, which is necessary to evaluate the role of large power plants in ozone formation. The proposal seeks to (i) evaluate the use and limitations of indicators as a basis for evaluating O3-NOx-VOC sensitivity; (ii) develop methods for interpreting measured VOC in comparison with models, accounting for uncertainties in model formulation, e.g. vertical mixing; and (iii) evaluate the removal rate for NOx and NOy using observation-based techniques.

Approach:

The proposed model-measurement comparison uses a "scenario-based approach" which seeks to test specific hypotheses about ozone chemistry rather then just validate the model. In this type of comparison, the critical test is not just whether the models agree with measurements, but whether model scenarios with changed assumptions and different sensitivity predictions would show a noticeable difference in model-measurement comparisons. Model applications will be developed for three locations where rich measurement sets are available: The eastern U.S. during July, 1995 (including the Middle Tennessee Ozone Study), the NARSTO-northeast corridor during July, 1996, and a region in the southwest U.S. associated with a planned future measurement intensive (Phoenix, Arizona, May-July, 1998). A series of model scenarios will be developed that test how model predictions vary in response to uncertainties in (i) emissions, (ii) deposition, and (iii) rates of daytime vertical mixing. These scenarios will be used to quantify the extent of uncertainty in model-based predictions, including predictions the impact of reduced NOx and VOC emissions on O3 and for rates of production of O3 and removal of NOx in power plant plumes. Model-measurement comparisons will then be performed for the various scenarios in an attempt to reduce this uncertainty. Investigation of model scenarios with different NOx-VOC sensitivity will use comparisons with measured indicator ratios (reactive nitrogen and peroxides). In order to be successful, it must be shown that model-measurement comparisons reflect real differences in NOx-VOC sensitivity between the different scenarios rather than uncertainties in deposition and other removal processes or aerosol chemistry. The approach will be extended to include measured VOC as a possible indicator for NOx-VOC sensitivity. In this case it must be shown that model-measurement comparisons for VOC reflect differences in emissions rather than uncertainties about vertical mixing, especially when surface measurements are used. Ozone production efficiency and NOx removal rate in large power plants has been the subject of several recent studies, which used measured correlations between measured O3, NOy, CO and SO2 to infer ozone production and NOx removal. The proposed research would use correlations between these species in model scenarios with different assumptions, in an attempt to evaluate the validity and uncertainty associated with these measurement-based inferences.

Expected Results:

Efforts to reduce ozone have been baffled by the difficulty in identifying precursors, including impacts of NOx vs. VOC and the relative contribution of power plants. The current solicitation cited the need for research on "observation-based techniques for discriminating between emissions control strategy preferences." The NOx-VOC indicators, described above, are a direct response to this need. The proposed work would establish the limits of usefulness of this and other similar approaches. Recent studies have identified uncertainties concerning the contribution of large power plants to ozone formation and transport. These studies have used observation-based methods, but there has been no evaluation of the validity of these methods through model-measurement comparisons. The proposed work would provide new information on the role of power plants and the usefulness and limitations of observation-based approaches. The proposed work would also further efforts to evaluate the EPA Models 3 system, including combined ozone-and-aerosol models; and would develop data interpretations based on the extensive EPA PAMS network.

Improvement in Risk Assessment or Risk Management: The response of O3 to VOC vs NOx controls represents a major uncertainty for management associated with ozone. Identification and reduction of this uncertainty represents a significant contribution to risk management. The NOy removal rate is critical information for evaluations of the role of power plants in ozone formation and transport, which has also emerged as a major uncertainty for air quality management.

Publications and Presentations:

Publications have been submitted on this project: View all 17 publications for this project

Journal Articles:

Journal Articles have been submitted on this project: View all 6 journal articles for this project

Supplemental Keywords:

tropospheric, oxidants, RFA, Air, Toxics, VOCs, tropospheric ozone, Engineering, Chemistry, & Physics, risk assessment, nitrous oxide, air quality standards, ozone, air modeling, EPA Model 3 Systems, power plants, ambient emissions, bias, indicator ratios, modeling predictions, Nitric oxide, model measurement comparisons

Progress and Final Reports:

  • 1999 Progress Report
  • 2000
  • Final Report