From:	Harvey Jeffries <harvey@unc.edu>

To:	RTP3.RTMU540(sanders-dave,helms-tom,allman-joann),...

Date:	3/12/96 10:45am

Subject:	Conceptual Model/Issues

Please critique, add, modifiy, etc...

Tom, David. Pls send to those not on the email list.

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Science and Technical Support Work Group

A Conceptual Model for Ozone, PM, Regional Haze

1. The Need for a Conceptual Model

To develop an adequate understanding of ozone, PM formation and regional haze in different areas of the country, it would be very useful to develop conceptual models of the processes that lead to the formation of each. Further, it would useful to develop a conceptual model of how monitoring, data analysis, emissions, modeling, and assessment can be used in implementation programs. In setting out the initial model, there will be many more questions than available information to answer them.

Consequently, the conceptual models will provide mechanisms to identify additional needed information. While these will be useful to set research agendas, they also identify the

"act as if we know how it works" assumptions that will be necessary in formulating and applying any practical computational models within a time frame shorter than that needed to advance fundamental knowledge. The entire process of creating conceptual models is iterative in nature, but provides an overall frame work for increasing the scientific and technical information needed to provide a basis for sound planning. In addition, conceptual models can codify the processes independent of any air quality modeling, and thus provide an independent mechanism to evaluate the performance of computational air quality model(s).

2. The Formulation of a Conceptual Model

2.1 The Premises

In formulating a conceptual model, we accept that there are in the environment pollutants harmful to human health and welfare; that there are acceptably safe levels of these pollutants (codified as ambient air quality standards); and that human and civilized activities do influence or even create the harmful levels. The social goal desired is to modify human activities so as to reach safe levels of these pollutants. We accept that some form of regulation will be necessary to achieve this modification of human activities.

The issue is what form and what extent of regulation

should there be? Secondary issues are how long should

be allowed to attain the standards and, in a

non-deterministic world, how does one show that the

standards have been attained.

In the specific case of ozone, PM-fine, and regional haze, we accept that these are pollutants that have affects on humans and the environment. We accept that ambient levels of these need to be maintained below specific air quality standands and that the magnitude and form of these standards are outside the scope of this Work Group's activities.

Given that the standards for the three different

pollutants may have different forms, i.e., different

averaging times, different spatial extents, different

statistical forms (peak vs. average), how is

"attainment" in an integrated program defined?

Given that some pollutants have worse effects than other

pollutants, it may be more important to make progress on

achieving one standard faster than another standard. In

other words, the most achievable ozone reduction program

in a particular area may not be the set of reductions

that lead to the most achievable regional haze

reductions. Is there a hierarchy among the three problems?

While there are specific emissions, transport, and transformation process that are unique to ozone, to PM, and to regional haze, we accept that there are also common processes that link the three. That is, ozone, PM-fine, and regional haze have a sufficiently common origin that it makes sense to seek an integrated set of modified human activities that will achieve reduction and maintenance of ambient concentrations of these pollutants.

What are the parts of these three pollutants that have a

common origin or are affected by a common process? What

are the parts of these three pollutants that are not

common? (More detailed discussion of these occurs

below.) How does this understanding impact the

effectiveness of a common control program? Can an "add

on" to a common control program be effective in this

case?

2.2 Specific Parts of a Conceptual Model

2.2.1 The Environmental State

A major component of a conceptual model has to be identification of what consititues the characterization/ quantification of environmental state with regard to each of the pollutants. The conceptual model must also include a generalized description of such information. This can only be accomplished by making measurements, i.e., via monitoring studies or programs. Given existing scientific knowledge about the processes that might affect a particular pollutant, what monitoring would be needed to provide sufficient characterization/quantification of its environmental state, that, along with other efforts such as modeling, would permit effective control programs can be formulated and supported? Are existing networks and designs sufficient?

There is a need to explicitly address whether the

network design should take into account the idea of

better characterizing ambient ozone and PM levels to be

used for exposure assessment. Both of the standards are

health based, yet the present guidance in 40 CFR 58

provides minimal support for this type of siting.

Further, the present set of compliance criteria actively

discourage adding monitors to a network.

2.2.2 The Emissions State

Another major component of a conceptual model has to be the identification of what consititues the characterization/ quantification of the emissions state. This is the object that will be directly modified to achieve the lower ambient levels. The conceptual model must also include a generalized description of the current emissions state.

This may be the easiest process magnitude to quantify. It may also be the most expensive.

<other...>

2.2.3 The Transformation Processes

2.2.3.1 VOCs, NOx, Ozone

Ozone is both a natural component of the earth's atmosphere and an air pollutant. Ozone is formed in the stratosphere from molecular oxygen in air and intense ultraviolet solar radiation. Its formation consumes almost all radiation below 300 nm and thus prevents harmful radiation from reaching the earth's surface. Ozone is slowly transported from the stratosphere to the earth's surface and there is thus a natural background of O3 near the earth's surface that has been estimated to be near 20 ppb due solely to stratospheric sources. Current background is about 40 ppb and the increase has been attributed to global pollution including fossil fuel use and agriculturially related biomass burning. It may be increasing slowly. Continential

O3 backgrounds (i.e., Eastern US and Western Europe) may be much higher due to region wide, slow chemical production processes similar to those in urban areas and dependent upon widely dispersed NOx as well as due to direct transport of urban produced O3.

The general explanation for the formation of ozone in or near urban areas is that combustion sources that use air as an oxidizer will produce oxides of nitrogen (NO, NO2) when temperatures are above 2500K. In addition, incomplete combustion results in the emission of raw components and oxygenated organic components from the fuels. In sunlight these are sources of free radicals (e.g., .OH, HO2., RO.,

RO2.) that oxidize volatile organic compounds to carbonyls,

CO, and CO2, while simulanteously oxidizing NO to NO2 and recreating the free radical. Each free radical is cycled up to 5 times. The NO2 reacts with sunlight to recreate NO and to produce O3. After the first oxidation of NO to NO2, every subsequent operation of the cycle produces an O3 with an efficiency of >90%. In current chemical reaction mechanisms, a typical nitrogen is cycled 3 to 5 times. Some of the O3 produced reacts with organics and with sunlight to produce more free radicals to maintain the cyclic oxidation process. This represents a powerful positive feedback process on the formation of more O3, given available NOx.

The carbonyls produced in the organic oxidation also react with sunlight to produce more free radicals. As the cycle operates, NO2 is converted into inorganic and organic nitrates and this form of nitrogen can not cycle. This also removes free radicals. A system that converts all nitrogen oxides to such products cannot create any more O3. NO2 reacts rapidly with free radicals and in situations that have a limited supply of radicals, NO2 can compete with the

VOCs for the limited free radicals. This results in a virtually no production of O3. Thus different mixtures of

VOCs and NOx can result in different ozone levels such that the total system is non-linear. That is, large amounts of

VOC and small amounts of NOx make O3 rapidly but are quickly limited by removal of the NOx. VOC reductions under these circumstances show little effect on O3. Large amounts of NO and small amounts of VOC (which usually implies smaller radical source strengths) result in the formation of inorganic nitrates, but little O3. In these cases, reduction of NOx results in an increase in O3. Some combination of VOC and NOx is optimum at producing O3.

Larger molecular weight VOCs that are oxygenated or that react to from organic nitrates often have lower vapor pressures and can condense on exisiting aerosol surfaces to promote secondary aerosol growth. In addition, SO2 is oxidized to low volitility H2SO4 by the same radical processes described above as well as being oxidized in aqueous phases of clouds.

The proceeding is a static description. In the world, physical processes complete with chemical processes and change the outcomes in complex ways. The existence of feed back and non-linearlity in the transformation system confound the description. Competing processes determine the ambient concentration and there are an infinite set of process magnitudes that can give rise to the same ambient concentrations and changes in concentrations. Lack of any direct measurement of process magnitudes result in the need to use inferential methods to confirm any one explanation of a particular O3 concentration.

2.2.3.2 Particular Matter

<Nature and man-made>

<explanation of how PM comes to be in atm>

<identification of non-linearities, feedbacks, linkages>

2.2.3.3 Regional Haze

<Nature and man-made>

<explanation of how haze comes to be in atm>

<identification of non-linearities, feedbacks, linkages>

2.2.3.4 Linkage among, Ozone, PM, and Regional Haze

<brief articulation of the linkages--Rich??>

2.2.4 The Transport Processes

We accept that there are sufficient theoretical and empirical evidence to say that regional transport of O3 and/or its precursors, of PM and/or its precursors, and regional haze does occur. Such transport does not exclude in-situ transformation/production along the way.

A major component of the conceptual model, however, has to be a description of the atmospheric lifetimes and transport distances of pollutants as well as description of the dynamic interaction among transport processes and transformation processes. In addition to specific episode treatments, the conceptual model must include seasonal and climatological descriptions of such events. The role of various transport mechanisms on each pollutant should be included in the conceptual model. The role of clouds in both transport and transformation should be described.

3.0 Uses and Limitations of Mathematical Models; Uncertainty

While ozone has been studied for more than 40 and modeled for more than 20 years, and while there is a large body of scientific knowlege and several evaluated forecasting models, there are still major scientific gaps and thus uncertainties about the effects of various proposed control strategies forecasted by the models. That is, even in ozone modeling it is still necessary to make assumptions about how some potentially important ozone formation processes should be formulated/represented in models, there are still limited monitoring data, and there are still computer and input data limitations associated with the operation of the models.

Yet, an assessment of this gas-phase secondary pollutant shows that the number and nature of the processes affecting its concentration are large and complex, that they exhibit non-linearity, and that they include positive and negative feedbacks. Such systems are not readily comprehended, much less manipulated, by human minds. Thus, only mathematical/computational models provide even the possibility of understanding what effective control programs might require and what benefits they might provide. At the same time, we recognize that any such models are over-generalized, have numerous distortions, and suffer from intentional and unintential deletion. How do we become confortable using such tools to make expensive decisions?

We accept that while research agendas are being pursued, it will be necessary to use mathematical models to integrate the various effects and interactions of our best process descriptions as well as our best descriptions of the input data, such as emissions. We also accept that such models are not completely based on scientific knowledge, and of necessity include a number of "parameterized" and otherwised fitted or assumed components and inputs that permit them to make a prediction. The sensitivity of the model to these assumptions may be large or small. Further, because the model is based upon incomplete scientific knowledge, the model may be missing critical processes that are important in the real world, but because they are not known to scientists, are not even included in the model's formulation

(i.e., unintentional deletion).

We accept that it is not possible to validate models of such open systems as the ambient atmosphere, and that models must be repeatly evaluated and "stress tested" whenever possible. Such stress testing requires high quality observational data and other high quality operational input data.

We accept that even under these circumstances, a major concern for model use has to be the existence of internal compensating errors among the model's process representations. Such errors would permit the model to make present day predictions that are in good agreement with present observations, but which are achieved via a sum of incorrectly computed individual process changes. When future forecasts are made with the model, the starting environmental state and the changed inputs may not lead to the same compensation of errors and the model's predictions may be of low fidelity compared to what would have happened in the real world.

<more....>

4.0 Conceptual Model for the Treatment of Uncertainty

Section 3.0 describes the origin of uncertainty in models.

It is important that we understand the overall effects of the individual uncertainties on any assessments that are carried out.

How should uncertainty be propagated through the system

of emissions (present and future projections), air

quality, meteorology and models?

Comparison of the San Joaquin Valley Air Quality Study and the Gulf of Mexico Air Quality Study have been invaluable in leading to model improvements for identifying uncertainties in the modeling results.

The interface between modeling and monitoring and the

differentiation between total aerosol concentrations

(including ammonia nitrate, semi volitile organics and

water) and the portion measured by the FRM

4.0 Conceptual Model of Technical Assessment

<Some of these were raised in 1.0>

All of these issues point out the lack of understanding that we now have about PM, as well as the lack of information and tools to carry out a technically sound assessment for PM and ozone. These issues need to be described in further detail, including the time it will take to develop the necessary information. It is critical that the other two work groups have a clear understanding as to what methodolgies and tools are or will be available prior to proposing specific regulations. Otherwise, we will repeat the problems that we are encountering with the present ozone planning process and regulations.

Issue Questions Rasied by Working Group Members

I. Ambient Monitoring and Data Analysis

II. Emission Measurements and Inventories

III. Atmospheric Processes

IV. Modeling Formulation/Evaluation

V. Uncertainty

VI. Implementation and Control Strategies

VII. Other/Miscellaneous

I. Ambient Monitoring and Data Analysis

Where do we place monitors, what information do we seek from the monitors, what is the duration of monitoring, the types of monitors etc.

There is a need to explicitly decide if the network design should take into account the idea of better characterizing ambient ozone and PM levels to be used for exposure assessment. Both of the standards are health based, yet the present guidance in 40 CFR 58 provides minimal support for this type of siting.

What can be done to address the present set of compliance criteria that actively discourage adding monitors to a network.

Based upon existing PM data, how can we predict PM fine concentrations for a system of area designations and classifications?

Particle mass concentration is an imprecise metric: seek out more precise technologies that characterize particle constituents (e.g., sulfate,nitrate, organics) and minimize adulteration caused by sampling techniques.

Are the present PAMS network adequate for charterizing the environmental states of VOC, NOx. O3?

Do we need to begin using monitoring networks for NH3?

Assuming that monitoring with the Federal Reference Method

(FRM) will be required by the monitoring regulations, do we need to recommend that monitoring by the Federal Reference

Method (FRM) be supplement and do we need to recommend that existing monitoring networks be made more real time and have a larger coverage?

II. Emission Measurements and Inventories

How will equitable (meaning like quality) multi-pollutant emission inventories (gridded data sets) be established for use with multi-pollutant models?

Do we need to, and if so, how do we improve the accuracy of biogenic emission measurements and inventories?

If necessary how do we inventory sinks of pollutants and precursors?

How do we improve the accuracy of emission inventories in general?

III. Atmospheric Processes

What data do we need to understand, evaluate and predict the concentrations of PM and O3 and the impairment from regional haze?

What are the transport mechanisms and how important are they for regional haze, PM and O3?

How do we determine what portion of the problem are natural, local generated or transported in?

If VOC reactivity is an important factor, how can it be determined and added in to the system?

How will data gaps/data quality (chemistry, meteorology, emissions, etc) be addressed?

What is the minimum acceptable modeling, monitoring and emissions data analyses need to characterize long range transport?

Secondary aerosol is a major component of PM2.5. Do we have sufficient knowledge of its formation to construct a credible PM control strategy?

II. Modeling Formulation/Evaluation/Application

How will a PM model be validated without ambient data?

Will the model(s) be able to characterize PM concentrations which are comparable to the measurements produced by the

Federal Reference Method (FRM).

Will the model(s) be able to characterize regional transport; assist with identifying culpable sources; provide information to assist with monitoring site selection?

How do we identify the uncertainty in the model outputs so that the information can be reasonably used and not misused?

How sensitive are the models to the uncertainty of the input data?

Does it make sense to emphasize the peak concentrations predicted by the models for attainment demonstration or is it better to use some averaging mechanism?

How will one determine the need for a common platform, what is sufficient input data, what is acceptable performance and how does one define #acceptable#?

How does a regional model become an EPA #guideline# model?

What is the relationship between urban and superregional modeling?

How does one determine the appropriate episode to model, given different pollutants, averaging times, frequency of important modeling conditions (i.e., health responses), temporal and spatial emissions changes, meteorological and transport patterns, etc.

What role (if any) will receptor modeling play in the PM fine implementation program?

VI. Implementation and Control Strategies

What are the technical tools needed to develop integrated control strategies?

If appropriate how do we include reactivity of VOC in the control programs?

How do we demonstrate the effectiveness of control measures and strategies?

Should modeled demonstrations be required for an area to show attainment of the revised NAAQSs?

What would be a logical procedure for the

#too-close-to-call# classification? This procedure is directly linked to how the standard is defined.

How will regional haze, PM NAAQS, acid rain, and ozone programs be integrated?

V. Uncertainty

How do we handle uncertainty identified in the modeling and inventories?

How will a PM model be validated without ambient data?

What role (if any) will receptor modeling play in the PM fine implementation program?

VII. Other/Miscellaneous

How important are sinks for O3 and precursors in the system?

If necessary how do we inventory sinks of pollutants and precursors?

To what extent will Title IV SOx and NOx reductions, Title I

NOx RACT and the proposed PM2.5 NAAQS have an impact on regional haze?

Since the global background O3 level are increasing at a rate of 1 to 2% per year, what impact will it have on attainment of the standards?

How do we determine the O3 season, i.e., what are the spatial and temporal parameters that generate high O3 concentration days?

WORK PRODUCTS

Suggested Papers

#Modeling - State of the Art

#What is Meant by Ozone, Particulate Matter, and Regional

Haze Integration?