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Research Abstract

Government Perfonnance Results Act (GPRA) Goal 1
Annual Performance Measure 231

Significant Research Findings:

Reports on Recommendations for Monitoring Strategy
Improvements for States to Use Observations-Based

Methods

Scientific
Problem and
Policy Issues

Ozone is a pollutant of concern because of its adverse effects on ecological
and human health. It is well-known that the photochemical system that
produces ozone in the atmosphere behaves nonlinearly. This means that
estimating the effectiveness of emissions reductions or control strategies, is
non-trivial because the ozone response to incremental emission changes
depends on a complex balance among chemical precursor species and
meteorological conditions. Thus, 3-dimensional air quality models that can
account for these factors are needed to develop and evaluate emission
control strategies. Since compliance costs are large, we wish to reduce the
risk of error providing modeling guidance. We gain confidence in the
model through model evaluation, but standard evaluation metrics alone are
not sufficient for a nonlinear system. In the ozone system, different
combinations of the precursor emissions of volatile organic carbon (VOCs)
and nitrogen oxides (NOx) can produce the same ozone. Also, the state of
the system can be either VOC-limited, NOx-limited or in between and this
cannot be ascertained by simply examining simulated and observed ozone
levels. The state of the chemical system is important because when it is
VOC-limited, control of VOC emissions is most effective compared to
control of NOx emissions. When it is NOx-limited, control of NOx
emissions is more effective than control of VOC emissions. Thus, if the air
quality model predicts the ozone well for the wrong reason, with the model
in the wrong state, then the modeling guidance could be erroneous. The
key is that evaluating model predictions of ozone alone cannot determine
whether the model is in either the right or wrong state of VOC or NOx
limitation. Given the use of the model for policy support, more effective,
diagnostic probing is needed to test the photochemical model's
representation of the ozone production system and its responses to emission
control strategies. The objective of the research is to develop a set of
observationally-based indicators of the photochemical processes, termed
observationally based methods or OBMs, that involve species that can be or


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could in the near-future be measured in the field to support not only
diagnostic testing of the photochemical models, but also empirical checks
on the efficacy of control strategies that have been implemented.

Research	The research approach is to develop special combinations of chemical

Approach	species from in situ measurements that are capable of probing and testing

the photochemical processes in the air quality model. The special
combinations of in situ measurements are termed observationally-based
indicators. The general approach is termed an OBM approach. This
approach supports a special sort of diagnostic model evaluation oriented
towards the ozone predictions of the model. The conceptual model of the
overall photochemical processing guides the identification of key aspects of
photochemical dynamics for which to develop diagnostic indicators. Then
process-oriented studies using theoretical constructs, model-derived
detailed process-level explanations and results from sensitivity studies with
instrumented air quality models (to track the inner workings of the
chemistry) are used to develop the indicator probes. The diagnostic or
indicator probes are realized in terms of combinations of in situ species or
relationships among or between the species. The set of species developed in
this analysis also identify species that must be routinely measured in order
to carry out OBM studies and to diagnostically test the photochemical
models. Comparative studies with model sensitivity analyses are used to
identify the most promising and reliable indicators and hence establish the
priority set of species to be measured to augment the more routine ozone
measurements.

Results and	Diagnostic indicators were developed for three major aspects of the

Impact	photochemical dynamics. They were air mass aging, ozone production

efficiency per NOx termination and the system state relative to the
separation line between VOC- and NOx- limitation. A fourth indicator, the
competition between termination pathways, developed by researchers
outside EPA, was included for analysis. A small set of priority species that
supported these indicators was identified. The critical species needed for
augmentation of current monitoring are total oxidized nitrogen, or NOy,
nitrogen oxide, NO (already available), and an unbaised measure of
nitrogen dioxide, or true-N02. Nitrogen oxide and true-N02 are combined
into an accurate measure of NOx (= NO + true-N02). Air mass aging is
defined as NOy - NOx also termed NOz. Ozone production efficiency is
measured by the slope of the relationship between ozone and NOz. And the
indicator 03/N0x is informative of the state of the system relative to the
line separating NOx- and VOC-limitation. For the competition between
termination pathways two (or three) additional species are needed: nitric
acid (HN03) and hydrogen peroxide (H202) (or total peroxide). The
priority list of species: NOy. True-N02 (to be combined with NO), HN03,
and H202 were communicated to HEASD scientists. The NOy
measurement was already available due to development during the


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Southern Oxidants Study. HEASD scientists worked with the rest of the
list, especially true-N02, and outside manufacturers to develop methods for
the field to be able to measure these species. Significant progress has been
made in getting these measurements ready for monitoring programs. With
these measurements, we will be able to more effectively test the air quality
(photochemical) models with regard to their intended purpose, that is, the
prediction of emissions control effectiveness and reduce the uncertainty in
and build confidence in model predictions.

The conceptual model development, theoretical studies, model process
instrumentation and the model studies to develop the key set of OBM
indicators was conducted by an in house team of NERL scientists and post
docs. The NERL team also brought in OBM indicators from university
researchers for inclusion and comparison. The key species were
communicated to scientists within NERL for instrumentation development.
These recommendations have been incorporated into OAQPS planning
regarding the new national air monitoring network. The basic, underlying
NERL studies are published in:

G.S. Tonnesen and R.L. Dennis, Analysis of Radical Propagation Efficiency to
Assess Ozone Sensitivity to Hydrocarbons and NOx. Part 1: Local Indicators of
Instantaneous Odd Oxygen Production Sensitivity, Journal of Geophysical
Research, 105, 9213-9225, 2000.
and

G.S. Tonnesen and R.L. Dennis, Analysis of Radical Propagation Efficiency to
Assess Ozone Sensitivity to Hydrocarbons and NOx. Part 2: Long-Lived Species as
Indicators of Ozone Concentration Sensitivity, Journal of Geophysical Research,
105, 9227-9241, 2000.

Interpretation and explanation of the basic studies leading to measurement
recommendations are published in:

Arnold, J.R., R.L. Dennis and G.S. Tonnesen, 2003. Diagnostic evaluation of
numerical air quality models with specialized ambient observations: testing the
Community Multiscale Air Quality modeling system (CMAQ) at selected SOS 95
ground sites, Atmospheric Environment, 37, 1185-1198.
and

R. L. Dennis, J.R. Arnold, and G.S. Tonnesen. On the need for better ambient
observations of important chemical species for air quality model evaluation. W.A.
McClenny (Ed.). In Recommended methods for ambient air monitoring of NO,
N02, NYy, and individual NOz species. EPA/600/R-01/005, National Exposure
Research Laboratory, U.S. Environmental Protection Agency, Research Triangle
Park, NC (2001).

Future Research No future research with respect to ozone is planned. Diagnostic techniques
are being investigated for the inorganic fine particulate system.

Research
Collaboration and
Research
Products

Contacts for

Additional

Information

Questions and inquiries can be directed to
Robin L. Dennis, Ph.D.

US EPA, Mail Drop E243-01


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National Exposure Research Laboratory
Research Triangle Park, NC 27711

Phone: 919/541-2870
E-mail: Dennis.Robin@epa.gov

Funding for this project was through the U.S. EPA's Office of Research and
Development, National Exposure Research Laboratory, and the work was
conducted by the Atmospheric Modeling Division


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