June 9, 2004 

1

Midwest Regional Planning Organization 

MODELING PROTOCOL 

*This document was updated on October 21, 2005 

Major changes include technical details relating to landuse data, boundary 

condition data, and modeling episodes. 

More technical details on the photochemical modeling are available in the 

technical addendum on the website: 

http://www.ladco.org/tech/photo/photochemical.html
 June 9, 2004 

2

Midwest Regional Planning Organization 

MODELING PROTOCOL 

This document describes the plans of the Midwest Regional Planning Organization (MRPO) to 

conduct an air quality assessment to support the development of state implementation plans for 

ozone (O3), fine particles (PM2.5), and regional haze for the States of Illinois, Indiana, Michigan, 

Ohio, and Wisconsin. Consistent with USEPA’s policy to encourage integration of control 

strategies to reduce regional haze with those designed to meet the National Ambient Air Quality 

Standards (NAAQS) for O3 and PM2.5 (64 FR 35719) and to optimize available resources, a 

multi-pollutant planning approach will be pursued. 

The MRPO has made considerable progress over the past couple of years in evaluating and 

applying air quality models for O3, PM2.5, and haze. The “lessons learned” from this preliminary 

modeling helped shape this document. As new information becomes available, this document 

will be updated. 

Overview

Purpose: The air quality assessment will address what it will take to provide for attainment of the 

NAAQS for O3 and PM2.5 and meet the reasonable progress goals for haze. The assessment 

includes the following tasks: 

• prepare appropriate photochemical model inputs (e.g., emissions inventories and 

meteorological data); 

• perform basecase photochemical modeling, and evaluate model results; 

• perform sensitivity tests to assess the effect of changes in emissions on ambient 

concentrations; 

• perform strategy modeling to assess regional and local control programs, and 

support; and 

• conduct supplemental air quality data analyses as part of a “weight-of-evidence” 

approach. 

All analyses will be conducted in accordance with USEPA guidance, including “Draft Guidelines 

on the Use of Models and Other Analyses in Attainment Demonstrations for the 8-Hour Ozone 

NAAQS”, EPA-454/R-99-004, May 1999, and “Guidance for Demonstrating Attainment of Air 

Quality Goals for PM2.5 and Regional Haze”, draft 2.1, January 2, 2001. As these guidelines 

change, this document will be updated. 

The air quality assessment will also help to answer several policy-relevant questions (see Table 

1). These questions were identified by the Project Team as being critical to the development of 

effective control programs for O3, PM2.5, and regional haze. 
 June 9, 2004 

3

Table 1. Critical Questions 

EMISSIONS

1. What are the uncertainties in emissions estimates for PM, ozone and haze precursors? 

2. What are the critical sources that need additional improvement in emission estimates 

and can we make these changes within one year? 

CONTROL PROGRAMS 

General

1. How close to attainment will we be with “on-the-books” federal and state controls? with 

EPA’s proposed Clean Air Interstate Rule? 

2. What can we say about the effectiveness of certain control programs (I/M, RFG, etc)? 

3. Do we need a regional agreement and if so, then what form does it take? 

Ozone

1. What ozone precursor reduction strategy (in terms of pollutants and geographic 

coverage) will be most effective in lowering elevated 8-hour ozone concentrations in the 

upper Midwest (and eastern U.S.)? 

2. How do control strategies for 8-hour ozone differ (if at all) from those control strategies 

we employed for 1-hour ozone? 

3. Should we consider a waiver from the NOx requirements of the Clean Air Act? 

PM2.5

1. What are the limiting reagents to reduce PM and what are their sources? 

2. How important are organics in comparison to other constituents? 

a. Can we describe the composition of the organic fraction of the aerosol? 

b. What fraction of the organic aerosol is natural vs anthropogenic and for each of 

those categories how much is secondary aerosol? 

c. What are the sources of the high levels of organics in cities? 

3. How important are ammonia emissions in developing control strategies? 

MONITORING AND DATA ANALYSIS 

1. What is our conceptual model of 8-hour ozone, PM2.5, and regional haze in the Midwest? 

2. What have we learned from our special monitoring data? 

3. Should we add special monitoring projects at this time? If we do, when will the data 

become available for analysis and will it be useful (or relevant) to development of PM2.5, 

ozone and haze control programs? 

MODELING

1. What are the major uncertainties in modeling analyses? 

2. Are there additional model improvements that we should pursue at this time? 

3. To what extent do we employ the single atmosphere concept in modeling? If PM 

modeling is not ready for prime-time, do we cut and run with ozone only? 

TRANSPORT

1. What are regional levels of pollutants, how are they transported, and what is their 

influence on urban and downwind regional levels of ozone and PM? 

2. What is the influence of transport of PM from outside the US (Asian and African dust, 

major forest fires in Canada and S. America) on PM levels in the Midwest? Can we 

distinguish natural or exceptional events (e.g., locally generated wind blown dust from 

construction, large wild fires from other combustion, Asian or Saharan dust storms from 

other sources of crustal related material) from typical air pollution events? 

3. Do natural events effect attainment of the 24-hr PM2.5 standards or annual standards in 

the Great Lakes States? 
 June 9, 2004 

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Regulatory Requirements: For PM2.5, USEPA must promulgate designations by December 31, 

2004, in accordance with the Omnibus Appropriations Act of 2004. (Note, it is our 

understanding that USEPA will actually promulgate these designations by November 17, 2004.) 

SIPs for PM2.5 are due no later than three years from the date of the nonattainment designation 

(per section 172(b) of the Clean Air Act) and for haze no later than three years after the date on 

which the Administrator promulgates the PM2.5 designations (per the Appropriations Act). For 

the purposes of this document, it is assumed that the SIP submittal date for PM2.5 and haze will 

be January 2008. The applicable attainment date for PM2.5 nonattainment areas is expected to 

be five years from the date of the nonattainment designation (i.e,. by January 2010). 

For O3, USEPA promulgated designations for the 8-hour ozone NAAQS on April 15, 2004 (69 

FR 23858, April 30, 2004). The designations became effective on June 15, 2004. SIPs for 

ozone are due no later than three years from the date of the nonattainment designation, per 

section 172(b) of the Clean Air Act (i.e., by June 2007). On April 15, 2004, USEPA also issued 

the first phase of its implementation rule for 8-hour ozone (69 FR 23951, April 30, 2004)1

. This 

phase addressed classifications for the 8-hour NAAQS, revocation of the 1-hour NAAQS, 

attainment dates, and timing of emissions reductions needed for attainment. According to this 

rule, the applicable attainment date for O3 varies as a function of nonattainment classification. 

For the region, the attainment dates are either June 2009 (basic nonattainment areas) and June 

2010 (moderate nonattainment areas)2

. 

For haze, the SIP requirements (pursuant to 40 CFR 51.308(d)) include establishing reasonable 

progress goals, determining baseline conditions, determining natural conditions, providing a 

long-term control strategy, providing a monitoring strategy (air quality and emissions), and 

establishing BART emissions limitations and associated compliance schedule. To assist states 

in meeting these requirements, USEPA issued two guidance documents (“Guidance for 

Estimating Natural Visibility Conditions Under the Regional Haze Program”, EPA-454/B-03-005, 

September 2003, and “Guidance for Tracking Progress Under the Regional Haze Program”, 

EPA-454/B-03-004, September 2003), and recently proposed “Guidelines for Best Available 

Retrofit Technology (BART) Determinations” (69 FR 25184, May 5, 2004). 

Schedule: The following milestones are proposed for the air quality assessment: 

2004 

August Deliver initial base year (2002) emissions inventory 

 Begin model basecase runs 

October Deliver updated base year emissions inventory 

 Update model basecase runs 

 

1

 The second phase of the rule, which is expected to be published later this year, will address mandatory 

control measures, interstate transport, attainment demonstrations, reasonable further progress, 

conformity, reasonably available control measures, and new source review. USEPA is also planning to 

publish an implementation rule for PM2.5 soon, which will address these same issues. This document 

assumes that an attainment demonstration will be required for O3 and PM2.5 for many nonattainment 

areas in the region. 

2

 Several counties are considering requesting that they be reclassified from moderate to marginal 

nonattainment. The attainment date for marginal nonattainment areas is June 2007. 
 June 9, 2004 

5

November Project Team meeting to review model performance, data analyses, and 

plans for control strategy modeling 

December Deliver initial future year control strategies 

 Begin control strategy modeling 

2005 

February Deliver “final” base year inventory and additional future year control 

strategies 

 Finalize basecase modeling 

 Continue control strategy modeling 

April Deliver additional future year control strategies 

Continue control strategy modeling 

June Project Team meeting to discuss strategy modeling, establish haze goals, 

and identify “draft” regional strategies for O3, PM2.5, and regional haze 

July – Oct Conduct further modeling and data analyses, based on direction from 

Project Team 

December Project Team meeting to discuss regional/local strategies for O3, PM2.5, 

and regional haze 

Responsibilities: The primary responsibility for this work will be with the LADCO staff. Additional 

assistance and involvement by the states will also be necessary, especially by the Project Team 

and various workgroups (Emissions, Modeling, Data Analysis, and Strategy Workgroups). 

Modeling System 

The major elements of the modeling system are summarized below. 

Periods: The modeling will focus on calendar year 2002, which is referred to as the base year. 

In addition, to provide a more complete evaluation of model performance, several additional 

periods will be considered: calendar years 2001 and 2003. Reasons for selecting these periods 

include: 

 Several periods of high O3 and PM2.5 concentrations occurred during 2002, and the 

other periods (e.g., June 25-30 and July 31-August 9, 2001) 

 Current design values for O3 and PM2.5 include 2002 data (i.e., 2001 – 2003 data) 

 The Midwest RPO sponsored several supplemental sampling programs in 2002 (e.g., 

aircraft measurements in summer 2002 and fall/winter 2002/2003; increased sampling 

frequency at rural speciation sites; nephelometers operated at several rural sites; 

continuation of St. Louis Supersite; and pilot DRUM and organics studies); and 

additional sampling at several Supersite locations occurred during the Eastern U.S. 

Supersites program. 

 A full year of modeled days (2002) are available to use in the modeled attainment test. 
 June 9, 2004 

6

 

 Preliminary modeling has already been done with 2002 (and the other periods). 

To assess the representativeness of 2002, the following analyses were conducted: 

For ozone, a Classification and Regression Tree (CART) analysis was performed with 

data from 1990 – 2002 for the following cities: Chicago, Cincinnati, Cleveland, Detroit, 

Indianapolis, Milwaukee, Minneapolis, and St. Louis (“CART Analysis of Historic Ozone 

Episodes”, January 2004, D. Kenski, Lake Michigan Air Directors Consortium). A 

representativeness index was calculated based on the variability from “average” 

conditions for this 12-year period. Lower values indicate years that are most similar to 

average conditions, and higher values indicate years that deviate more strongly from the 

average conditions. The table below shows the representativeness index for high ozone 

days. As can be seen, for most cities, 2002 is very close to “average”. (Note, the higher 

index (>10) in Indianapolis for 2002 (and 1998) is driven by two very high ozone days 

during each summer. These very high ozone days occurred only six times in the 12-

year period. If these two days are excluded from the analysis, then 2002 is close to 

average for Indianapolis, too.) 

Year Chic. Detr. Milw. St.L. Ind. Cin. Clev Minn. Ranka

1990 2.1 0.7 0.7 6.7 0.7 0.1 0.6 0.1 7

1991 19.8 1.6 35.2 0.2 1.1 0.3 3.8 0.1 12

1992 1.3 1.7 1.9 0.6 1.7 0.8 1.1 0.7 5

1993 1.5 0.1 15.5 0.2 0.5 1.6 0.2 0.0 10

1994 0.8 0.1 5.9 0.0 3.5 0.8 0.2 0.1 6

1995 55.0 1.3 4.5 2.3 2.8 0.7 6.2 4.9 13

1996 1.1 0.6 0.7 0.3 3.2 0.7 2.8 0.0 4

1997 9.3 0.9 1.0 0.2 0.6 0.2 1.9 0.0 8

1998 0.7 0.2 1.1 0.1 10.3 0.5 2.2 0.3 9

1999 0.2 0.3 1.4 0.2 0.5 2.1 0.1 0.5 1

2000 0.9 0.6 0.1 0.5 2.4 0.6 1.3 0.6 2

2001 0.8 0.6 0.5 0.3 0.9 0.7 0.5 3.8 3

2002 1.0 1.1 1.4 1.3 10.5 3.2 5.1 0.7 11

For PM2.5, a similar CART analysis was performed with data from 1999-2002 for each of 

the eight cities. The results for Chicago presented below show that the number of days 

in each node is consistent with the other years and seasons. This suggests that 2002 is 

similar to other recent years. 
 June 9, 2004 

7

 

Models: CAMx4 will be the primary model applied for these analyses. CMAQ and REMSAD may 

also be used for confirmatory purposes. The selection of CAMx4 as the primary model for this 

project is based on the following factors: performance, operator considerations (e.g., ease of 

application and resource requirements), 

technical support and documentation, model 

extensions (e.g., 2-way nested grids, process 

analysis, source apportionment, and plume-ingrid), science in the model, and no reliance on 

third party software. 

Domain/Grid: The National RPO grid projection 

will be used for this modeling. The National 

RPO grid will be run once and used to feed a 

smaller 36km domain (97 X 90 cells) shown in 

the figure to the right. A 12 km sub-grid over 

the Midwest (see shaded green box) will be 

used for ozone modeling (summer periods). 

The air quality model will contain 16 vertical 

layers, with higher resolution in the boundary layer. 

Model Inputs: Model inputs in this protocol are described for CAMx. Where other 

photochemical models are applied, they will be applied as consistently as possible with CAMx. 

Meteorological inputs will be derived using MM5. Based on a series of sensitivity runs, the 

following model physics configuration is proposed: 

• Pleim-Xu land-surface module 

• RRTM radiation scheme 
 June 9, 2004 

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• Simple ice moisture 

• Kain-Fritsch cumulus 

• ETA 3-hourly initialization 

• FDDA on above PBL 

The MM5 modeling domains extend at least nine grid cells (in each direction) beyond the edge 

of the air quality modeling domains identified above. The meteorological model will contain 34 

vertical layers, with higher resolution in the boundary layer. 

Performance of the meteorological model will be evaluated qualitatively with 12-hour surface 

weather maps, 12-hour satellite images, and vertical sounding plots for select monitor stations. 

Quantitative performance will be evaluated with daily and hourly statistics: bias, gross error, 

index of agreement, and mean values. An evaluation will be performed for both the MM5 output 

files and the meteorological input files for the air quality model. 

Emissions inputs will be prepared using the Emissions Modeling System (EMS). A new 

emissions model (CONCEPT) is currently under development and is expected to be essentially 

complete in early/mid 2005. Over the course of this SIP modeling, an effort will be made to 

transition from EMS to CONCEPT. 

For basecase modeling, a base year (2002) inventory will be prepared. The emissions data will 

reflect a combination of state 2002 data (which was prepared in compliance with USEPA’s 

Consolidated Emissions Reporting Rule), numerous LADCO-sponsored special inventory 

projects (e.g., ammonia, nonroad sources, and fires), and USEPA’s National Emissions 

Inventory (NEI) for 2002 (version 1). 

For strategy modeling, a baseline inventory and various future year strategy inventories will be 

prepared. The baseline inventory reflects a typical year and provides the reference modeled air 

quality conditions against which future year model runs will be compared to derive a relative 

reduction factor (see Strategy Modeling below). The future year inventories will be prepared by 

adjusting the baseline inventory using growth and control factors provided by the states or 

LADCO contractors, or available methods, such as MOBILE6.2 or the NONROAD model. 

For point, anthropogenic area, and on-road sources, a weekday, Saturday, and Sunday 

inventory will be prepared for each month. In addition, day-specific (accounting for ambient 

temperature) inventories will be prepared for on-road sources for select ozone episodes. Dayspecific biogenic emissions will be estimated using BIOME3 (biogenics model in EMS, which is 

equivalent to BEIS3), with modeled (MM5) temperatures and observed (satellite-based) PAR 

values. 

CAMx uses the TUV model to calculate photolysis rates based on solar zenith angle, height 

above ground, ultraviolet albedo of the ground, atmospheric turbidity, and total ozone column 

density. The TUV generates rates for each day as a function of 11 heights, 10 solar zenith 

angles, 5 ozone column values, 5 albedo values, and 3 turbidity values. The ozone column data 

is derived from daily TOMS satellite observations. The albedo data varies by month and is 

based on over 10 years of TOMS reflectivity observations.

The initial and boundary conditions will vary in the horizontal and vertical direction and are 

based on monthly averaged GEOS-CHEM global model output. GEOS-CHEM was applied to 

the calendar year of 2002 and that data is used to supply monthly averaged initial and boundary 
 June 9, 2004 

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concentrations to the CAMx model. Where an initial or boundary concentration is not specified 

for a pollutant, the model will default to a near-zero concentration. 

CAMx uses 11 land use categories to describe the surface. The land use data are based on 

BELD3 1 km data, which is aggregated to the appropriate grid resolution for photochemical 

modeling.

Quality Assurance: The following quality assurance activities are planned: 

Emissions

• Review model inputs and outputs – each emissions modeler will review the 

model input files, and the graphical and tabular model outputs for 

reasonableness and consistency 

• Benchmark modeling – each modeling group will duplicate a set of standard 

modeling results 

• Duplicative modeling – a few runs will be modeled by more than one group 

• Reports - a standard set of graphical and tabular model outputs will be identified 

• Documentation – appropriate written reports will be prepared which summarize 

the modeling analyses 

Modeling

• Establish consistent file naming convention 

• Review model inputs – each modeling group will review the air quality model 

emission (and, if appropriate, meteorological) input files (e.g., compare emission 

totals with EMS reports, and examine spatial maps of emissions) 

• Benchmark modeling – each modeling group will duplicate a set of standard 

modeling results 

• Duplicative modeling – a few runs will be modeled by more than one group 

• Reports - a standard set of graphical and tabular model outputs will be identified 

• Documentation – appropriate written reports will be prepared which summarize 

the modeling analyses 

Basecase Modeling 

The purpose of the basecase modeling is to evaluate model performance (i.e., assess the 

model's ability to reproduce the observed concentrations). The model performance evaluation 

will focus on the magnitude, spatial pattern, and temporal of modeled and measured 

concentrations. This exercise is intended to build confidence in the model prior to its use in 

examining candidate control strategies. Increased confidence in the model will increase the role 

of the modeling results in the design and establishment of any eventual control strategies. 

Model performance will be evaluated by comparing modeled and monitored concentrations. For 

O3, species of interest include O3, total VOC, NO2, NOX, and NOY. The relevant averaging 

times for these species are 1-hour and 8-hour. For PM and haze, species of interest include 

PM2.5-mass (gravimetric and RCFM), SO4, NO3, NH4, EC, OC, soil, bscat, coarse mass, as well 

as several gaseous precursors, such as NH3, HNO3, and SO2. Aloft data comparisons for O3, 

NOx, and bscat, using aircraft data will be also performed. The relevant averaging times for these 

species are 1-hour and 24-hour. The following evaluations are planned: 
 June 9, 2004 

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Operational Evaluation

• Statistical: unpaired peak, average accuracy of peak, normalized bias, 

normalized gross error 

• Graphical: scatter plots, side-by-side spatial plots, time series plots (ozone hourly 

concentration time series plots and PM2.5 species daily stacked bar charts for 

select monitoring sites [or groups of monitoring sites]) 

Diagnostic Evaluation 

• Use of process analysis 

Mechanistic Evaluation

• Assess relative model results (i.e., change in modeled concentration due to 

change in emissions) 

This evaluation will focus on the change in ambient ozone and sulfate 

concentrations between summer 2002 and summer 1991.3

 (Note, ozone and 

sulfate concentrations are generally highest during the summer in the eastern 

half of the U.S.) . 

 

No rigid acceptance/rejection criteria will be used for this study. Instead, the statistical 

guidelines recommended by USEPA and other modeling studies (e.g., modeling by the other 

RPOs) will be used to assess the reasonableness of the results here. 

Note that there may be differences in the definition of certain chemical species from the 

measurement networks and the modeling output. To ensure consistent matching of measured 

and modeled species, the conventions identified in Table 2 will be followed. 

 

3

 Meteorological conditions can strongly influence air quality concentrations. The difference in 

concentrations from one year to the next can be due to changes in emissions, changes in meteorology, or 

both. In order to assess the effect of emission changes, it is necessary to remove (or minimize) the effect 

of meteorological changes. This can be done by comparing two periods with similar meteorological 

conditions. To determine which previous summer was meteorologically similar, several metrics were 

considered. First, average summer temperature and precipitation for the upper Midwest indicate that 

2002 is comparable to 1991. Examining each month shows that June from each year has the best 

agreement. Second, CART statistics for the major cities in the upper Midwest shows that there are a 

comparable number of days in the higher ozone nodes for June 1991 and June 2002. Thus, the June 

1991 and June 2002 measured and modeled ozone and sulfate concentrations should provide a 

reasonable initial basis for assessing relative model performance. 
 June 9, 2004 

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Table 2. Species Definitions..........
 June 9, 2004 

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Sensitivity Modeling 

Application of the modeling system to assess the need for (and, if so, the types of) national, 

regional, and local control strategies will consist of two types of analyses. First, several 

sensitivity tests will be performed. These tests are discussed in this section. Second, candidate 

control strategies (i.e., sets of control measures) will be modeled. These strategy runs are 

discussed in the following section. 

Sensitivity tests can provide useful general information to help guide the development of control 

strategies. A desirable feature of these tests is that the model inputs can usually be prepared 

quickly and easily; thereby, allowing many model simulations to be performed. 

The sensitivity tests will focus on the effect of changes in the amount, type, and location of 

primary and precursor emissions. Possible sensitivity tests include: 

(1) General control path analyses, such as “matrix” runs, which examine the effect of 

reductions by species, source categories, and geographic area. 

(2) Focused attainment analyses, which attempt to estimate the type and amount of 

emission reductions needed to meet the ambient standards using USEPA’s 

attainment tests. For example, a series of runs could be performed based on the 

future year base strategy to estimate how much additional control is needed to 

provide for attainment. 

(3) NOx “disbenefit” runs, which examine the effect of NOx reductions for elevated v. 

low-level sources and in urban v. rural areas. Note, these runs should consider 

both local and regional changes in ozone concentrations associated with NOx 

reductions, and how these concentration changes may effect attainment of the 

ozone standard (i.e., do any concentration increases occur when and where high 

absolute ozone concentrations are predicted?). 

The Project Team will identify the specific sensitivity tests. 

The modeling results will be presented in graphs, such as scatter plots, concentration difference 

plots, threshold difference plots, time series plots, and stacked bar charts. 

Strategy Modeling 

The initial strategies to be modeled include a future year base strategy, which reflects “on-thebooks” federal and state controls, and a Clean Air Interstate Rule (or Clear Skies Act) strategy, 

which reflects the additional SOx and NOx reductions from USEPA’s proposed national rule. A 

contractor has been hired to provide the necessary growth and control factors for these 

strategies, plus another strategy (to be determined) later this year. 

The Project Team will identify additional control strategies to be modeled. 

USEPA’s attainment tests will be applied to the results of the strategy modeling to determine 

whether a given strategy is sufficient to provide for attainment of the NAAQS for O3 and PM2.5

and meet the reasonable progress goals for haze. USEPA guidelines recommend using the 

model in a relative sense to project future year design values. This is done through the use of a 

relative reduction factor (RRF), which is defined as the ratio of the future year and baseline 

modeling results. The RRFs are multiplied by the base year design values to project the future 
 June 9, 2004 

13

year design values, which are then compared to the NAAQS to assess attainment. For O3 and 

PM2.5, the base year design values will be based on 2001-2003 data, which represents the 3-

year period used to establish the nonattainment designations and is consistent with the base 

year (2002) emissions inventory. For haze, the baseline visibility levels will be based on 2000-

2004 data, in accordance with 40 CFR 51.308(d)(2)(i). 

O3 results will be presented for those grid cells/counties with O3 monitors. PM2.5 results will be 

presented for those grid cells/counties with FRM (PM2.5-mass) monitors. Spatial mapping will 

be performed to extrapolate PM2.5-speciation data from STN and IMPROVE sites to FRM sites. 

(No other mapping of O3 or PM2.5 data will be performed.) 

The future years of interest in the attainment demonstration are 2006, 2008, 2009, and 2018. 

Phase I of USEPA’s implementation rule for ozone states that emission reductions needed for 

attainment must be implemented by the beginning of the ozone season immediately preceding 

the area’s attainment date. For example, for areas with an attainment date in May 2010, the 

emission reductions need to be implemented by the beginning of the 2009 ozone season. As 

noted above, the applicable ozone attainment dates in the region are June 2007 (marginal 

nonattainment areas), June 2009 (basic nonattainment areas), and June 2010 (moderate 

nonattainment areas). Thus, the strategy modeling for ozone must address 2006, 2008, and 

2009. Although USEPA has yet to issue its implementation rule for PM2.5, a similar approach is 

assumed for PM2.5 (i.e., emission reductions must be implemented by the beginning of calendar 

year 2009). Thus, the strategy modeling for PM2.5 must address 2009. For haze, the RPOs 

have all agreed to use 2018 as the official year to model for the first regional haze milestone 

(see May 25, 2004, letter from Chris Recchia, MANE-VU to USEPA). 

Weight-of-Evidence 

A weight-of-evidence approach will be used to support SIP development with extensive data 

analysis and modeling. Because USEPA has yet to finalize its implementation guidance on 

attainment demonstrations for 8-hour of O3 (and has yet to proposed such guidance for PM2.5), it 

is unclear what is required to demonstrate attainment for these pollutants. For the purposes of 

this document, it is assumed that a demonstration based on photochemical modeling, 

supplemented with analyses of air quality data will be sufficient.4

Air quality data analyses should be used to provide both a conceptual model (i.e., a qualitative 

description of the regional haze and nonattainment problem) and information on the 

effectiveness of emission reductions. Given uncertainties in the emissions inventories and 

models for haze (and PM2.5), these data analyses are a necessary part of the overall technical 

support. 

The conceptual model will draw upon AER’s 2001 “Scoping Study for Regional Haze in the 

Upper Midwest” and their forthcoming analysis of recent regional haze data, as well as two 

LADCO reports (“PM2.5 in the Upper Midwest”, June 2003; “PM2.5 in Urban Areas in the Upper 

Midwest”, February 2004). 

The effect of reducing emissions by pollutant, geographic area, and source category can be 

assessed through the following: 

 

4

 It should be noted that several recent Court have upheld the use of a weight-of-evidence approach for 1-

hour ozone SIPs, including BCCA Appeal Group v. EPA, 335 F. 3d 817 (5th Cir. 2003), and 

Environmental Defense v. EPA, ??? (2nd Cir. 2004). 
 June 9, 2004 

14

• examination of indicator species (see “VOC and NOx Limitation of Ozone 

Formation at Monitoring Sites in Illinois, Indiana, Michigan, Missouri, Ohio, and 

Wisconsin, 1998 – 2002”, February 24, 2004; “The Effects of Changes in Sulfate, 

Ammonia, and Nitric Acid on Fine PM Composition at Monitoring Sites in Illinois, 

Indiana, Michigan, Missouri, Ohio, and Wisconsin, 2000 – 2002”, February 20, 

2004; and “Analysis of Recent Regional Haze Data”, Draft, April 2004). 

• trends (e.g., how have significant SO2 emission reductions in the eastern U.S. 

over the past decade affected sulfate and nitrate concentrations?). 

• trajectory analyses (e.g., what can we say about the contribution from individual 

states on Class I areas – see “Quantifying Transboundary Transport of PM2.5 : A 

GIS Analysis”, 2003). 

• source apportionment analyses (e.g., what can we say about the contribution of 

individual source categories on Class I areas - see “Source Apportionment 

Analysis of Air Quality Monitoring Data: Phase I – Final Report”, May 2002; 

“Source Apportionment Analysis of Air Quality Monitoring Data: Phase II”, Draft, 

April 2004; and Clarkson University’s forthcoming analyses of Midwest PMrelated measurements).