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Weight of Evidence Procedures and Their Potential for Corroborating

Baton Rouge Five Parish 8-hr Ozone SIP Modeling

Prepared by

T. W. TescheAlpine Geophysics, LLC

27 July 2006

Baton Rouge 5-Parish 8-hr Ozone Modeling Study Technical Review Meeting -27 Jul ‘06

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Goals of Collaborative WOE

Provide independent confirmation that: LDEQ modeling system is operating well Final proposed control strategy(s) are

sufficient to meet NAAQS within required time frame

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Elements of WOE Analyses (EPA, 2005, pg 32)

A fully-evaluated, high-quality modeling analysis that projects future values that are very close to the NAAQS (e.g., 82 to 87 ppb).

Multiple supplemental analyses in three categories: modeling ozone/emissions trends observational models

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Elements of WOE Analyses (EPA, 2005, pg 32)

Weighting of individual analysis based on its ability to quantitatively assess the likelihood proposed control measures to yield attainment

Analyses using well-established analytical procedures, supported by sufficient data

Written technical description why aggregate analyses lead to a conclusive determination regarding the future attainment status of the area that differs from the modeled attainment test.

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Benefits of Collaborative WOE

Draws upon stakeholder insight and resources

Increases opportunity for best modeling practice being brought to bear on ozone SIP

Allows introduction of information into the process that might not otherwise be available as the result of LDEQ and contractor resources, schedules, or capabilities

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WOE Benefits (concluded) Ensures that thoughtful, thorough weight of

evidence analyses are performed for each non-attainment monitor to ensure that targeted, cost effective controls are identified and evaluated

Technical information produced will allow LDEQ air quality decision-makers and EPA to understand the effects of local controls in the broader context of the substantial ozone benefits expected to accrue in the ‘mid teens’ time frame as integrated ‘on the books control programs’ come to fruition.

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Weight of Evidence Methods

Extended Use of PAQSM Results Trends-Based Assessments Observation-Based Methods Alternative Application of Attainment

Test Corroboration of Source-Receptor

Relationships Alternative Base Cases Comparison with egional Studies Corroborating Efficacy of Controls

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Extended Use of Model Results When the PAQSM is shown to perform well, there is increased

confidence using it to judge the adequacy of a control strategy

WOE metrics that a well-performing model can generate include: Relative change in total amount of ozone > 85 ppb within the

nonattainment area; Relative change in grid cells > 85 ppb within the nonattainment

area; Relative change in grid cell-hours > 85 ppb within the

nonattainment area; Relative change in maximum modeled 8-hour ozone within the

nonattainment area

These metrics can also be used to explore whether individual subregions are relatively unresponsive to emissions controls (“stiff”) while other parts of the domain are more response.

A well-performing model can be used to examine attainment in unmonitored areas in the domain, adding to the WOE determination.

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Trends-Based Assessments Independent of the PAQSM, it is

possible -- within limits -- to extrapolate future year air quality in a nonattainment area through analysis of historical measured emissions and aerometric trends.

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Trends-Based Assessments: Ambient Data

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Trends-Based Assessments: Emissions

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Observation-Based Methods Observation-based methods can help:

Corroborate the reasonableness of PAQSM base case predictions (e.g., Blanchard, 2000; Sillman, 1995, 1998);

Confirm model sensitivity to emissions input changes, and

Assess the directionality of modeled emissions control strategies for

photochemical oxidants (Trainer et al., 1993; Blanchard et al., 1999; 2003; Koerber and Kenski, 2005) and

secondary aerosols (Blanchard et al., 2000).

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Observation-Based Methods Indicator species ratios -- ‘diagnostic

probes’ -- are helpful in quantifying model’s response to emissions changes: The ozone response surface probe

[O3/NOx]; The chemical aging probe [NOz/NOy]; and The ozone production efficiency probe

[O3/NOz].

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Alternative Attainment Test Methods

8-hr ozone Attainment Test methods reflect considerable research by EPA and the science community.

The procedures recommended in the final ozone guidance explicitly defined.

But, there remains room for alternative methods for conducting the Attainment Test.

The main requirement is that full technical justification of the alternative method(s) is provided and successfully negotiated with the EPA regional offices.

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Alternative Attainment Test Methods

Alternate procedures for calculating the base year (current) 8-hr ozone DV;

Different thresholds in selecting days for RRF calculation

Elimination of some ‘RRF days’ due to model performance considerations

Use of a more recent base year

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Effect of Array Size on AttainDemo

Effect of Array Size on Design Value: No Constraint on 'Difference'

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8-hr

Ozo

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2009 DV (3x3) 2009 DV (5x5) 2009 DV (7x7)

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Effect of Imposing MPE CriterionEffect of 'Array Size" on Design Value: Peak Difference < 10%

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2009 DV (3x3) 2009 DV (5x5) 2009 DV (7x7)

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Array Size vs. No. of RRF DaysNumber of Days at Each Monitor With Peak 8-hr Ozone > 70 ppb

In 2003-2005 Base Year Simulations: Five Episodes

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DV

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2x2 3x3 5x5 7x7 DV Poly. (DV)

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More Recent Base Case Year

FastTrack ('2000 to 2004' Weighted) vs. 2000 Base DVs

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Use of Finer Modeling Grid Size

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Corroboration of S-R Relationships

Other tools, potentially more powerful than OBMs, can be used to determine whether ozone concentrations are sensitive to certain precursors (i.e., VOC, NOx) or source sectors (e.g., industrial, power generation, traffic).

Assuming reliable PAQSM base case MPE, ‘probing tools’ can be used to help explain why attainment is (or is not) demonstrate. Examples are: Source apportionment analyses (OSAT/APCA) Trajectory-based analyses Process Analysis (PA)

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Alternative Base Cases Use of ‘alternative base cases’ is potentially helpful in

Elucidating model performance of a PAQSM, Providing insight into the range of control strategy

outcomes that can be expected as the result of uncertainties in or alternate methods for preparing model inputs.

Method demonstrated in various regions of U.S. (Reynolds, et al., 1996; Roth et al., 2005).

Method entails use of multiple, corroborative air quality models and associated input data sets (e.g., multiple meteorological data sets, alternative chemical mechanisms or emissions inventories)

For the 8-hr ozone Attainment Test and control strategy design, alternative base cases help reveal the sensitivity of estimated RRFs and DVs to the variations in inputs or model formulations.

In this way, decision-makers are supplied with additional information to help inform their choices.

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Comparison with Other Studies Results from nearby attainment demonstration or

overlapping large regional scale studies may provide useful information complementing the LDEQ’s 8-hr ozone modeling.

Results of ongoing attainment demonstrations in one part of a state or subregion may provide corroborating information for another nonattainment area.

Two immediately relevant examples include the ozone SIPS for the DFW and HGB areas.

While the Texas SIP modeling focuses on different episodes, they entail many other similarities and offer the potential for useful synergism.

There are also several recent EAC modeling studies in the Texas, Oklahoma, Florida, and the Gulf Coast region.

At the larger regional scale, the modeling being performed by the CENRAP, WRAP, VISTAS and MRPO each cover the Gulf Coast Region in their domains using the 2002 annual episode. MPRO has developed annual data bases for 2001 and 2003 as well.

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HGB Model Results Compared with VISTAS 2009/2018 Projections

ExtendedModeled 8-hr Ozone DVs for the HGB Region

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HGB Model Results Compared with VISTAS 2009/2018 Projections

Estimated Rate of Progress in Attaining the 8-hr Ozone NAAQS in the HGB Region: DRPK Monitor

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Comparison with Other Studies Use of the VISTAS modeling in a Weight of Evidence’

mode for Houston revealed: The 2000 monitored design values lead to

significantly higher 2009 DVs in the HGB region when compared to use of the more recent 2002-2004 measured DVs (the red vs. blue bars);

Compared with the VISTAS 36 km results (light yellow bars), the DVs from the 4 km grid modeling with the post-2000 episodes (blue bars) are generally 2-4 ppb higher.

This result is directionally consistent with the North Carolina modeling (Arunanchalam et al., 2006) where moving from the 36 km to 4 km grid increased the DVs in many cases by 1-3 ppb.

This result is opposite the trend seen in the Upper Midwest modeling (Tesche et al., 2006d); and

At all monitors, the calculated DVs in 2018 are all well below the NAAQS.

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Corroborating Efficacy of Emissions Controls Various methods have been postulated for

assessing a model’s reliability in predicting air quality response to changes in emissions.

EPA suggests examination of conditions for which substantial

changes in (accurately estimated) emissions occur; ‘retrospective modeling’, that is, modeling before

and after historical significant changes in emissions to assess whether the observed air pollution changes are adequately simulated; and

use of predicted and observed ratios of ‘chemical indicator species’.

In some urban-scale analyses, the use of weekday/weekend information has been helpful in assessing the model’s response to emissions changes.

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Corroborating Efficacy of Emissions Controls

Innovative statistical methods are available for estimating the reasonableness of modeled ozone control programs

Hogrefe and Rao, (2001) developed a probabilistic framework that enables decision makers to assess the chances that a given emissions control program will achieve the 8-hr NAAQS when the controls are applied.

Hogrefe et al., (2000) used the observed ozone time series power spectrum to corroborate that the model is responding consistent with ozone observations.

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Corroborating Efficacy of Emissions Controls

Hogrefe et al., (2000) examined underlying forcing mechanisms distinguishing days with high ozone vs. average or non episodic days (by spectral decomposition of a 3-month episode). They found that: Ozone power spectrums represent sum of four temporal

components: intraday timescale to the multi week timescale. Form of the 8-h ozone NAAQS emphasizes the importance of

longer-term fluctuations embedded in ozone time series data Use of ozone time series power spectrum corroborated the

MPE and provided additional information about efficacy of modeled control programs.

To adequately account for the interplay between the diurnal, synoptic, and baseline components influencing 8-hr ozone levels, it may be necessary to model domains of spatial extend 2000 to 2500 km and at least four synoptic cycles.

Modeling studies confined to small local grids and short episode durations may restrict the analysis to the intraday component, and thereby lose the ability to assess the efficacy of emissions control strategies needed to meet and maintain the 8-hr ozone NAAQS and to improve long-term trends in ozone air quality.

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Recommendations Encourage stakeholder technical support to

LDEQ and contractors Share emergent data bases and modeling

findings to: Encourage independent corroboration of

technical work within meaningful timeframe Facilitate development of technically sound,

cost-effective emissions controls Collaborate on performance of Weight of

Evidence analyses to enable best decisions made with current and new modeling science and policy guidelines