i 

# Regional Air Quality Analyses for Ozone, PM 2. 5 

# , and Regional Haze:

Draft Modeling Protocol

August 2, 2010 (updated November 5, 2010)

States of Illinois, Indiana, Michigan, Ohio, and Wisconsinii 

# Table of Contents

Section

- Title Page

1.0 Overview of Modeling Analysis Project 1

1.1 Regulatory Requirements 2

1.2 Management Structure 4

1.3 Technical Committees 4

1.4 Participating Organizations 4

1.5 Schedule 5

1.6 Description of Conceptual Model 5

2.0 Model and Modeling Inputs 7

2.1 Model Selection 7

2.2 Modeling Domain and Grid Spacing 7

2.3 Initial and Boundary Conditions 8

2.4 Episode Selection 8

2.5 Meteorological Modeling 9

2.6 Base Year Emissions 9

2.7 Future Year Emissions 1 5

2.8 Quality Assurance Procedures 1 6

3.0 Base C ase Modeling 17

3.1 Ambient Data Base 17

3.2 Model Evaluation Procedures 17

4.0 Future Year Modeling 20

4.1 Model Future Year Control Scenarios 20

4.2 Apply Attainment Test 20

5.0 Weight

- of

- Evidence Demonstration 2 2

5.1 Ambient Data Analyses 2 2

5.2 Modeling Analyses 2 2

6.0 Procedural Requirements 2 3

6.1 Documentation 2 3

6.2 Deliverables 2 3

6.3 Resources 2 3

7.0 References 2 4

Appendix I Modeling Technical Details1 Section 1.0 Overview of Modeling Analysis Project

This document describes the plans of the Lake Michigan Air Directors Consortium (LADCO) to conduct an air quality assessment in support of state imp lementation plans (SIPs) for ozone

, fine particles ( PM 2.5 ), and regional haze for the States of Illinois, Indiana, Michigan, Ohio, and

Wisconsin. The assessment will b e conducted in accordance with U.S. Environmental Protection Agency ( EPA ) guidance: “Guidelines on the Use of Models and Other Analyses for Demonstrating Attainment of Air Quality Goals for Ozone, PM 2.5 , and Regional Haze”, EP A

454/B07

- 002, April 2007. As EPA’s guideline changes (and as new information becomes available) , th is protocol document will be updated

. Additional technical details for the new air quality assessment are pro vided in Ap pendix I

.

The assessment will focus on attainment of the National Ambient Air Quality Standards (NAAQS) for ozone (2008 version) and PM 2.5 (2006 version)

, and r easonable progress goals for regional haze. In addition, as discussed below, revised NAAQS for ozone and PM 2.5 are expected soon. As necessary, the assessment will address these new standards.

A regional, multi

- pollutant approach will be taken for technical reasons (e.g., commonality in precursors, emission sources, atmospheric processes, transport influences, and geographic areas of concern), and practical reasons (e.g., more efficient use of pr ogram resources). Furthermore, EPA has consistently encouraged multi

- pollutant planning in its rule for the haze program (64 FR 35719), and its implementation guidance for ozone (70 FR 71663) and PM 2.5 (72 FR 20609).

The assessment includes the followi ng tasks:

**•** A 2007/ 2008 base year emissions inventory will be prepared by the States and LADCO. 2007 and 2008 data will be provided for EGU point, nonroad, and biogenics. 2008 data (only) will be provided for the other sectors (on

- road, non

- EGU point, and area). For
these other sectors, LADCO will consult with the States and examine various emission surrogates (e.g., population, employment, and VMT) to determine whether the 2008 emissions can be used “as is” to represent 2007 or whether they need to be ad justed to approximate 2007.

**•** Both 2007 and 2008 meteorology will be used

. Base case modeling to evaluate m odel performance will be performed for both years.

**•** Future year modeling will be performed for three years: (TBD) . Depending on the

source secto r, either the 2007/ 2008 emissions will be adjusted (by applying appropriate growth and control factors) or direct emission estimates will be made (using emission models) to derive the future year emissions. A decision will be made later based on

technical reasons (e.g., meteorological and photochemical model performance) and policy reasons (e.g., ensure protection of public health) on which year(s) of meteorology to use in the future year modeling.

**•** Sensitivity analyses will be conducted and probing tools will be applied to support the development of candidate control strategies.2 **•** Control strategy modeling will include an initial scenario consisting of “on the books/on the way” controls. Additional strategies will be identified by the LADCO Project Team.

**•** Supplemental air quality analyses will be conducted as part of a “weight

- of

- evidence”

de monstration . In particular, th e results of the ambient data and alternative modeling analyses will be used to provide a more robust assessment of expected future year air quality.

The report is organized in the following sections. This section provides a summary of regulatory requirements and background information on regional planning. Section 2 reviews the model and modeling inputs. Section 3 discusses the model performance evaluation and Section 4 discusses the proposed strategy analyses, including application of EPA’s attainment test. The weight

- of

- evidence demonstration, based on the modeling and s upplemental analyses , is

addressed in Section 5. Section 6 rev iews the plans to document the technical analyses and key project deliverables.

1.1 Regulatory Requirement s On March 12, 2008, EPA announced that it was strengthening the 8

- hour primary (and secondary) ozone standard from the 1997 level of 0.08 parts per million (ppm) to 0.075 ppm. For the 2008 version of the ozone standard, EPA started the designation process b y calling on states to submit their nonattainment recommendations by March 2009. Based on these recommendations and a review of the most recent air quality data, EPA i ndicated its intent to promulgate designations by March 2010.

On January 6, 2010, EPA p roposed to tighten the 8

- hour primary ozone standard to a level within the range of 0.060

- 0.070 ppm, and to establish a cumulative, seasonal secondary standard at a level within the range of 7

- 15 ppm

- hours. The form of the primary standard

remains the sam e (i.e., compliance is based on the 3

- year average of 4 th high 8

- hour values). The form of the new proposed secondary standard is a “cumulative peak

- weighted index,” called W126. In conjunction with this action, EPA delayed the designations for the 2008 (0,075 ppm) standard from March 2010 to March 2011 in order to allow EPA to complete its reconsideration of the 2008 standard before determining whether designations are necessary. If, as a result of the reconsideration, EPA issues different ozone standar ds in 2010, then the new ozone standards would replace the 2008 ozone standards and implementation requirements associated with the 2008 ozone standards, including area designations, would no longer apply. Instead, EPA would begin a new process to designa te areas for the 2010 ozone
NAAQS on an accelerated schedule.

On September 21, 2006, EPA revised the NAAQS for particulate matter (PM). The revisions address two categories of particulate matter: fine particles (PM 2.5 ), which are 2.5 micrometers in

diamet er and smaller; and inhalable coarse particles (PM10), which are smaller than 10

micrometers in diameter. 1

1 On February 24, 2009, the U.S. Court of Appeals for the D.C. Circuit remanded the PM2.5 NAAQS to EPA for reconsideration of the annual level of the standard and reconsideration of the secondary PM2.5 NAAQS. EPA has yet to act on the Court ’s decision and has indicated that it will do so as part of next r eview of the standard , which it expects to propose in November 2010. EPA strengthened the 24

- hour PM 2.5 standard from 65 micrograms per cubic meter (μg/m 3 ) to 35 μg/m 3 , and retained the current annual PM 2.5 standard at 153 μg/m 3 . EPA also retained the existing national 24

- hour PM10 standard of 150 μg/m 3 and

revoked the annual PM10 standard.

On December 22, 2008, EPA announced designations for 211 counties (or portions thereof) in 25 states, including Illinois, Indiana

, Michigan, Ohio, and Wisconsin, as not meeting

the NAAQS for PM 2.5 based on 2005

– 2007 data. Because air quality monitoring data for 2008 was expected to become available shortly after EPA’s
action, EPA indicated that it would evaluate the

status of an a rea based on 2006, 2007, and 2008 air quality data. On November 13, 2009, EPA published final area designations for the 24

- hour national air quality standards for PM 2.5 .based on

2006

– 2008 data. EPA designated 31 areas, including some or all of 120 coun ties, as nonattainment areas, including five areas in the LADCO region: Milwaukee, Detroit, Cleveland, Canton, and Steubenville.
Figure 1. Counties designated as nonattainment of the daily PM 2.5 standard

These areas will need to develop and implement plans to meet the 24

- hour PM 2.5 standards within three years after the effective date of the designations. Nonattainment areas are required to meet the standards by 2014.

For haze, the Clean Air Act sets “as a national goal the prevention of any future , and the remedying of any existing, impairment of visibility in Class I areas which impairment results from manmade air pollution.” There are 156 Class I areas, including two in northern Michigan: Isle Royale National Park and Seney National Wildlife Ref uge 2

2 Although Rainbow Lake in northern Wisconsin is also a Class I area, the visibility rule does not apply

because the Fed eral Land Manager determined that visibility is not an air quality related value there. . EPA’s visibility rule (64 FR 35714, July 1, 1999) requires reasonable progress in achieving “natural conditions” by the year 2064. Per the Omnibus Appropriations Act of 2004, the first regional haze SIP was due in December

2007 and must address the initial 10

- year implementation period (i.e., reasonable progress by the year 2018). SIP requirements (pursuant to 40 CFR 51.308(d)) include setting reasonable progress goals, determining baseline conditions, determining natural conditions, providing a

lo ng

- term control strategy, providing a monitoring strategy (air quality and emissions), and establishing BART emissions limitations and associated compliance schedule.

EPA’s visibility rule also requires a report every five years “evaluating the reasonab le progress goal for each mandatory Class I Federal area”. The first progress report is due five years from submittal of the initial implementation plan. Because all the LADCO State s ha ve yet to submit a complete haze SIP, the due date for the first prog ress report is uncertain. However, the LADCO Project Team has agreed to assume a due date of about July 1, 2015. To assist the states in tracking progress for haze (as well as other pollutants, including ozone and PM 2.5 ), LADCO will prepare an annual air quality summary report. At the appropriate time, this report will be expanded to provide other required information (e.g., emissions trends) for the first progress
report.4 1.2 Management Structur e
The technical work will be coordinated and/or conducted by LADCO 3

Figure 2 . LADCO Organizational Structure . LADCO wa s established by the States of Illinois, Indiana, Michigan, and Wisconsin in 1989. The four states and EPA signed a Memorandum of Agreement (MOA) that initiated the Lake Michigan Ozone Study and identified LADCO as the organization to over see the study. Additional MOAs were signed by the States in 1991 (to establish the Lake Michigan Ozone Control Program), 2000 (to broaden LADCO’s responsibilities), and 2004 (to update LADCO’s mission and reaffirm the commitment to regional planning). In 2004, Ohio joined LADCO. LADCO consists of a Board of Directors (i.e., the State Air Directors), a technical staff, and various workgroups. The main purposes of LADCO are to provide technical assessments for and assistance to its member states, and to

p rovide a forum for its member states to discuss regional air quality issues.

1.3 Technical Committee s
The LADCO organization includes the LADCO staff and several LADCO committees

– see Figure 2 . The LADCO staff, working with these committees and, as necessary, contractors, will be responsible for conducting the technical work described in this document. Overall planning

will be provided by the Project Team and policy direction by the state Air Directors (Technical Steering Committee) and Env ironmental Commissioners (Policy Steering Committee)

.

1.4 Participating Organizations

G iven the large spatial extent of the modeling domain and the importance of transport in the

eastern U.S. for PM 2. 5 and ozone, a process is needed to provide consistency and coordination between regional planning efforts by the Midwest, Southeast, and Northeast States . Unlike the

3 Between 2000 and 2009, a similar entity known as the Midwest Regional Planning Organization (MRPO) helped to coordinate and/or conduct technical and regulatory activi ties for the LADCO States for regional haze. The MRPO

was led by the five LADCO States and involve d tribes in Michigan and Wisconsin, EPA, and Federal Land Managers. EPA discontinued the RPOs in 2009 when it eliminated funding for these groups.5 previous round of SIP modeling where the Regional Planning Organizations ( RPOs ) helped

pr ovide this function, there is no formal structure in place at this time to support the next round

of SIPs. A s such, the following process is proposed to ensure inter

- regional consistency:

**•** The Eastern Regional Technical Advisory Committee ( ERTAC ) should c ontinue its efforts, given its recent success to ensure consistency in area source methodologies and to provide a rail inventory for the eastern U.S. Other areas of collaboration include agricultural ammonia emissions, EGU emissions (i.e., temporal profil es and growth methodologies), and data format /transfer.

**•** A group of met modelers sh ould continue its work to support meteorological modeling f or 2007 using the WRF model.

**•** A group of photochemical modelers sh ould work together to coordinate domain/grid configurations, model performance evaluations, and other issues , as necessary

.

T h is process consists of mainly state

- led initiatives . Further discussion is needed to determine the appropriate role of EPA ( and Federal Land Managers) and stakeholders. Involvement of these groups will pro vide for a more open process and, possibly, result in additional assistance

n eeded to accomplish key technical activiti es.

1.5 Schedule Base case modeling is currently underway. Future year strategy modeling is expected t o begin in early 2011. Approximate dates (and timeframes) for the modeling work are identified in Figure 3

.

Figure 3 . Schedule for SIP M odeling

1.6 Description of Conceptual Model An extensive network of air quality monitors in the 5

- state region provides data for ozone (and its precursors), PM 2. 5 (both total mass and individual chemical species), and visibility. These data are used to determine attainment/nonattainment designation s, support SIP development, and provide air quality information to public (see, for example, www.airnow.gov ).

Analyses of the ambient monitoring data w ere conducted previously to produce a conceptual
model, which is a q ualitative summar y of the physical, chemical

, and m eteorological processes6 that control the formation and distribution of pollutants in a given region

. Section 2 of “Regional Air Quality Analyses for Ozone, PM 2.5 , and Regional Haze: Final Technical Suppor t Document”, April 25, 2008 http://www.ladco.org/reports/technical_support_document/tsd/tsd_version_iv_april_25_2008_fin al.pdf ) reviews the se data analyses and describes our understanding of ozone, PM 2.5, and

r egional haze with respect to current conditions

, data variability ( spatial, temporal, and chemical)

, i nfluence of meteorology (including t ransport patterns )

, precursor s ensi tivity, and

so urce culpability.

Th e analyses will be revised with more recent air quality data and studies, including the following new technical reports:

“A Conceptual Model of PM 2.5 Episodes in the Midwest”, LADCO, January 2009 PM 2. 5

Blanchard, C. and S. Tanenbaum,”Analysis of Inorganic Particulate Matter Formation in the Midwestern United States”, Final Report, November 30, 2008

Schauer, J.J., A. Rutter, D. Snyder, E. Stone, M. Olson, J. Zhou, C. Worley, T. Katzman, R. Collins, R.

Bader, T. Dallmann, J. DeMinter, M. Mieritz, B. Shelton, and A. Plourde, “LADCO Organic Molecular
Marker Study”, Final Report, July 17 , 2009 , Universi ty of Wisconsin

- Madison

Sullivan, A.P., and J.L. Collett, “Biomass Burning Impacts on Air Quality in the Upper Midwest”, Final

R eport, January 28, 2009, Colorado State University

Baek, J., G. Caremichael, S. R. Lee, J. Oleson, N. Riemer, T. Rohlf, S. Sousan, S. Spak, and C. Stanier,
“Episodic Air Pollution in Wisconsin (LADCO Winter Nitrate Study) and Georgia (SEARCH Network)

Duri ng Jan

- May 2009”, Draft Phase I Report, July 22, 2010, University of Iowa and University of Illinois

Kenski, D., “Updated CART Analysis for Ozone through 2008 (Preliminary Draft) Ozone

Following completion of these analyses, an updated conceptual model will be prepared.7 Section 2 .0 Model and Modeling Inputs

All modeling analyses will b e conducted in accordance with EPA guidance: “Guidelines on the Use of Models and Other Analyses for Demonstrating Attainment of Air Quality Goals for Ozone, PM 2.5 , and Regional Haze”, EPA

- 454/B07

- 002, April 2007.

The new regional modeling will build upon the analys es conducted by LADCO, its member states, and its contractors to address the 1997 version of the ozone and PM 2.5 standards, and regional haze. Th e prior modeling , which reflects a 2005 base year (Base M), is documented in “Regional Air Quality Analyses for Ozone, PM 2.5 , and Regional Haze: Final Technical Support Document”, April 25, 2008 http://www.ladco.org/reports/technical_support_document/tsd/tsd_version_iv_april_25_2008_fin al.pdf ).

This section reviews the modeling system to be used and the development of model inputs

. Model e valuat ion and model application ( i.e., attainment demonstration) are covered in the following section s

.

2.1 Model Selection The proposed modeling system for the new modeling consists of:

Emissions

– CONCEPT ( the most current version will be used)

Meteorology

– MM5 or WRF (see Section 2.5 )

Photochemical

- CAMx ( the most current version will be used ) . Model set

- up is

summarized below:

CB05 gas phase chemistry SOA chemistry updates Wesley

- based dry deposition scheme ISORROPIA inorganic chemistry SOAP organic chemistry RADM aqueous phase chemistry PPM horizontal transport

CAMx is recommended for the following reasons: (1) familiarity and reliability (i.e., the LADCO States have been using CAMx for several years) , (2) operator considerations ( i.e., ease of application and resource requirements), and (3) model extensions (2

- way nesting, plume

- in

- grid, and source apporti onment).

Base case modeling will also be performed with CMAQ. The performance of CAMx and

CMAQ will be considered in decidin g whether to also use CMAQ for some of the future year modeling runs

2.2 Modeling Domain and Grid Spacing The proposed modeling domain will provide greater spatial coverage and finer horizontal grid spacing compared to the pr evious regional modeling. Spec ifically, it is proposed that the new modeling will use an e xpanded U.S. domain (36km grid spacing ), a slightly modified Midwest subdomain (12km), and Lake Michigan and Detroit

- Cleveland subgrids (4km)

– see Figure 4

.8 Figure 4 . Proposed m odeling d omain s

– 36 and 12 km grids (left) and 12 and 4 km grids (right)

The air quality model will resolve the atmosphere up to 15 km with 16 (??) vertical layers, with higher resolution in the boundary layer.

For PM 2. 5 , a full year of met data will be run with the 36 and 12km grid s. For ozone, a summer season (May

– September) will be run with the 36, 12, and 4 km (Lake Michigan and Detroit

Cleveland) grids

2.3 Initial and Boundary Conditions Boundary conditions represent pollution inflow into the model from the lateral edges of the grid and initial conditions provide an estimation of pollution that already exists. The effect of boundary conditions is minimized by focusing on areas far removed from the edge of the modeling domain, and the effect of initial condit ions is minimized by assuming a “ spin

- up ” period

of a couple weeks

.

The initial conditions from the previous LADCO regional modeling (Base M), which were based

on GEOS

- CHEM, were used. New b oundary conditions were derived from NCAR’s “ Model for

O z one and Related C hemical Tracers ” (MOZART) using scripts and programs prepared by a

contractor for LADCO.

2.4 Episode Selection

The new modeling will use meteorological data for two recent full years: 2007 and 2008

. Specifically, base case modeling will be performed for both years to evaluate model performance. A decision will be made lat er based on technical and policy reasons on which year(s) to use in the future year modeling.

In addition, to provide a more complete model perf ormance evaluation, the periods associated with LADCO’s recent special monitoring studies will be considered (e.g., Biomass Burning Study

and Molecular Marker Study: J une

- J uly 2007 and January

– February 2008, and Winter Nitrate Study: December 2008

- March 20 09).9 2.5 Meteorological Modeling Two sets of meteorology will be considered for use in the modeling. First , MM5 wa s used by Alpine Geophysics, under contract to the Midwest Ozone Group, to generate meteorological

fields for 2007 and 2008 . Further discuss ion of this meteorological modeling , including an evaluation of model performance, is provided in “ Evaluation of 36/12 m MM5 for Calendar Year 2007 over the Continental and Midwest/Eastern United States”, August 31, 2009. T he initial regional modeling will rely on these meteorological fields. Key findings of this performance

evaluation include:

**•** Temperature bias performance on both the 36 and 12 km grids indicated only a few minor issues (i.e., the +0.5K benchmark was not met in some areas for certain months)

. Temperature error statistics, however, indicated difficulty in meeting the 2.0K benchmark, especially in western areas.

**•** Mixing ratio bias and error statistics were typically good at all levels on both the 36 and 12 km grids.

**•** The model showed mixe d results for the wind index of agreement, with good performance in western areas and poorer performance in eastern areas.

**•** The model does a reasonable job of replicating rainfall, but does overpredict the magnitude of rainfall and the spatial extent of rai nfall, especially in the summer months.

**•** Compared to other recent MM5 applications, the 36 and 12 km results from the current simulation were similar, although the 12 km mixing ratio results reflect slightly poorer performance.

Second, as noted above, a n a d hoc group of met modelers produce d meteorological data for 2007 using the WRF model. T hese meteorological fields will be evaluated, and a decision will

be made on whether to us e the MM5 data or the WRF data.

2.6 Base Year Emissions The emissions base year for the new regional modeling is 2007/ 200 8

. 2007 and 2008 data will be provided for EGU point, nonroad, and biogenics. 2008 data (only) will be provided for the other sectors (on

- road, non

- EGU point, and area). Based on consultat ion with the States,

LADCO believes that based on examin ation of various emission surrogates (e.g., population, employment, and VMT) , the 2008 emissions for these sectors can be used “as is” to repres ent

2007

.

For on

- road, off

- road, ammonia, and biogenic sources, emissions w ill be estimated by LADCO using emission models. Three other off

- road categories are not accounted for by the NONROAD emissions model: commercial marine, aircraft, and rail. Marine emissions will continue to be based on LADCO’s Base M (2005) inventory. Aircraft emissions will be provided by the States. Rail emissions will be based on the new (2008) inventory prepared by ERTAC. For point and area sources , emissions w ill be p repared using data supplied by the LADCO

States and other regional organizations

. Table 1 summarizes the development of the base year inventory. Further discussion is provided below for each source sector for the LADCO region.

For the rest of the modeli ng domain, the latest base year and future year inventories from other regional organizations will be used

. (Note, Base M inventories will be used in the interim until more recent inventories are available from other regional organizations.)10 Table 1. Ov erview of Base Year Emissions Development

Sector Method Responsible Group

EGU Point State NEI data, supplemented w/ CEM data (2007, 2008) States and S.Edick/LADCO

, w/ ERTAC

- derived temporal profiles

Non

- EGU Point State NEI data (2008) States

Area State NEI data based on ERTAC methods (2008) States

Off

- road NONROAD + LADCO fixes (2007, 2008) Grant Hetherington

Marine, Aircraft, and Rail (MAR) Marine

- LADCO inventory (Base M)

Aircraft

- State data

Rail

- ERTAC data (2008) States, EPA, and ERTAC

Agricultural Ammonia CMU

- based emissions (initially).

UC

- Riverside process

- based model w/ local data LADCO + state

- supplied

data , w/ ERTAC assistance

Biogenics MEGAN in CONCEPT (2007, 2008) Supplied by MOG contractor (Environ)

On

- road Select link

- level networks run with CONCEPT (2008) MPOs/States and LADCO

Fires Satellite

- based data (2007, 2008) S.Spak (Univ of Iowa)11 On

- Road Sources : To support regional emissions inventory development for upcoming photochemical modeling, LADCO will rely on EPA’s new MOVES2010 model for on

- road motor vehicles. MOVES2010, which was released by EPA in December 2010 4

**•** For the five LADCO States, a state

- level run will be conducted using national defaults for each month to produce a weekday and weekend emission estimate (for each month). The purpose of these runs is to produce a temporal profile for each state as a function of pollutant, emission type (exhaust and evaporative), and vehicle type (gasoline and diesel). , was developed for

s tate/local air qua lity and transportation agencies to use in preparing on

- road inventories for SIPs and transportation conformity. MOVES2010 replaced the previous model for estimating

on

- road mobile source emissions, MOBILE6.2. EPA guidance is for states to use MOVES2010 “in ozone, CO, PM, and NO2 SIP development as expeditiously as practicable.” Furthermore, EPA stated that MOVES2010 “must be used for developing on

- road mobile source inventory for
the 2006 PM2.5 NAAQS SIPs”.

MOVES2010 was developed principally to be r un in an “inventory” mode (i.e., monthly average,
county

- level emission estimates), which is what state/local agencies need for their SIP inventories and conformity demonstrations. For photochemical modeling, however, more refined temporal and, perhaps, s patial information is desired. Two options exist for providing this more refined information: (1) running MOVES2010 for each hour (using concurrent meteorological conditions) to provide the appropriate emission factor, or (2) developing

MOVES2010 “look

- up ” tables which cover the expected ranges of key meteorological variables and then using the tables to provide the emission factor for each hour based on the concurrent meteorological conditions. Initial PC

- based modeling showed that the first option was

p rohibitive (i.e., model test run times with default meteorology were on the order of 2 calendar days per county group; assuming 150 county groups in the eastern U.S. and 2 fuel seasons, the total time to complete a model run is about 600 days!). Subsequen t L inux

- based modeling produced a factor of 2 decrease in model run times, but still suggested that the look

- up table option was preferable.

Using a Linux

- based version of MOVES2010 created by W isconsin DNR, initial on

- road motor

vehicle inventories will be prepared as follows:

**•** For the five LADCO States (and neighboring states: MN, IA, and MO 5 ), a county

- level run will be conducted using national defaults f or January and July to produce a weekday

and weekend emission estimate for these two months.

**•** The temporal profiles (from the state

- level runs) will then be applied to the county

- level emission estimates (for January and July) 6

4 In September 2010, EPA released an updated version of MOVES2010 (i.e., MOVES2010a). Although MOVES2010 was used in LADCO’s initial modeling, MOVES2010a will be used in any subsequent modeling.

5 County

- level runs were also completed for KY, TN, and WV a s part of the initial Base B MOVES processing, but were not included in the regional modeling inventory files.

6 The monthly emission estimates derived from applying the temporal profiles to the January

- July country

level emissions will match the specific January and July values. to produce a more weekday and weekend12 emission estimate for each month. (Note, for the non

- LADCO States, either the temporal profile for the closest LADCO State will be used or the July result will be used to represent the summer months, and the January result will be used to repr esent the other months.)

**•** The resulting county

- level weekday and weekend emission estimates for the nine states will be processed as an area source in EMS. Emission processing assumptions include:

Temporal: Weekday emissions assigned to Monday

- Friday, an d weekend emissions assigned to Saturday

- Sunday. It should be noted that the emission file s already reflect hourly values.

Spatial: Applied 2002 surrogates based on roadway type.

Speciation: Exhaust and evaporative emissions by vehicle type (gasoline and diesel) speciated separately.

To produce more refined on

- road emission estimates for the 5

- state LADCO region, the following steps will be taken:

**•** LADCO to read the 2007 and 2008 met data and identify appropriate ranges (and intervals) for key meteoro logical variables (e.g., ambient temperature). Use a default curve defined by min and max temperature to define hourly temperatures for the evaporative species.

**•** LADCO States to provide MOVES2010 a inputs for the 200 7 emissions base year, and identify the appropriate county groups in their state . L ADCO will use this information to

run the Linux

- based version of MOVES2010 a to produce two sets of look

- up tables for

2007

- one for the summer and one for the non

- summer fuel seasons

- as a function of
county g roup

.

**•** I ntegrate the MOVES2010 a look

- up tables into CONCEPT

Subsequent versions of the on

- road inventory will reflect the use of link

- level data for five (or six) core networks ( Chicago, Gary, Milwaukee, Cleve land, Detroit , and, perhaps, Cincinnati ) for a weekday/Saturday/Sunday for each month (36 days) and 12

- 20 a dditional episode days

, as time permits. For the other networks in the LADCO region

, the exis t ing 2005 networks will be

grown to reflect 200 7 VMT

. For these networks (and for other part s of the country ) , the best

available MOVES

- based emissions will be used

Off

- R oad Sources: NMIM2008 will be run (using default monthly temperatures) by Wisconsin

DNR for the 2007 and 2008, and the future years of interest for the five LADCO States plus MN, IA, and MO

. Additional off

- road sectors (i.e., commercial marine, aircraft, and railroads [MAR])

w ill be handled separately 7

7 Although EPA is preparing a national commercial marine inventory, questions have bee n raised about EPA’s methods. As such, LADCO will work with the States to update, if necessary, the 2005 Great Lakes commercial marine inventory developed by a contractor for Base M. Also, States will provide aircraft

emissions and ERTAC’s 2007 rail inve ntory will be used. . Local data for agricultural equipmen t, construction equipment, commercial marine, recreational marine, and railroads were prepared previously by contractors13 (Environ, 2004, E.H. Pechan, 2004 , and Environ, 2007b, 2007c). These data, along with any new information for rail developed by ERTAC, will be used.

Area and Point Sources: CONCEPT (or EMS) will be run by LADCO using data supplied by the

LADCO States to produce weekday, Saturday, and Sunday emissi ons for each month. The ERTAC recommendations on area sources will be followed in preparin g these data . For EGUs,

the annual and summer season emissions w ill be temporalized for modeling purposes using profiles prepared by Scott Edick (Michigan DEQ) based on CEM data

.

Biogenics: Environ, under contract to the Midwest Ozone Group, produce d day

- specific biogenic emissions for the full modeling domain using the CONCEPT/MEGAN biogenics model for 2007 and 2008. These emissions, which are generally consistent with preliminary MEGAN modeling by LADCO, will be used in the modeling.

Ammonia : LADC O will produce an agricultural ammonia inventory for the full modeling domain. An updated version of the process

- based ammonia emissions model was recently delivered by a contractor. Previously (i.e., for Base M), the process

- based model (Zhang, et al, 2005, and Mansell, et al, 2005) was used to develop temporal factors for t he CMU

- based (Base K)

ammonia emissions . (Note, 2002 Base K emissions were first projected to 2005 using growth factors from the Round 4 emissions modeling.) F or the initial new mo deling, this same approach will be used. It is hoped that the updated process

- based model will be available to use in subsequent versions of the modeling inventory.

Canadian Emissions: Scott Edick (Michigan DEQ) processed the 2005 Canadian National Pollutant Release Inventory, Version 1.0 (NPRI) and will determine if a newer version of the inventory is available.. A subset of the NPRI data (emissions and stack parameters) relevant to the air quality modeling were reformatted and will be used in the new regional modeling.

Fires: the University of Iowa will produce an inventory based on MODIS satellite data from

NCAR for 2007 and 2008. In addition, EPA is preparing a national inventory for wild fires, prescribed fires, and agricultural burns. These two inventories will be examined and a decision will be made about which will be used in the modeling.

The base year inventory will be developed in phases, as described in Table 2. Outstanding issues for the base year inventory include:

**•** Reliability of the MOVES

- based on

- road emission estimates . (Note, a separate effort is underway to do a top

- down evaluation of these emissions using ambient monitoring data

– i.e., a comparison of ambient and emissions ratios for select species.)

**•** Accepta bility of new MEGAN emission estimates

**•** Development of agricultural ammonia emission estimate s

**•** Use of i mproved PM and VOC speciation profiles

**•** Incorporation of ERTAC rail emissions and improved commercial marine emissions

**•** Inclusion of both PM

- filterable and PM

- condensible emissions14 Table 2. Contents of Basecase Inventory

Sector Base A Base B Base C

EGU Point 2007 CEM data (annualized w/

2005

- 2007 temporal) 2007 CEM data (annualized w/

2005

- 2007 temporal) 2007 CEM data (annualized w/ updated temporal ) (updated EGU

- nonEGU splitting)

Non

- EGU Point Base M (new grid) 2008 State dat a 2008 State data (updated EGU

- nonEGU splitting)

Area Base M (new grid) 2008 State data 2008 State data

Nonroad Base M (new grid) 2007, 2008 NONROAD2008 2007, 2008 NONROAD2008

MAR Base M (new grid) Rail

– Base M (new grid)

Marine

- Base M (new grid)

Aircraft

- 2008 State data Rail

- ERTAC

Marine

– Modified Base M

Aircraft

- 2008 State data

Agricultural

Ammonia Base M (new grid) Base M (new grid) Base M (new grid) or new ammonia

emissions model

Biogenics MEGAN w/ 2007 met (new grid) MEGAN w/ 2007 met (new grid) MEGAN w/ 2007 met (new grid)

On

- road Base M (new grid) MOVES

- based emissions (national default inputs) MOVES

- based emissions (state inputs)

Fires (not included) 2007, 2008 data (S.Spak) 2007, 2008 data (S.Spak)

Non

- LADCO Region Base M (new grid) Base M (new grid) New 2007 emissions (per State Collaborative process) or EPA data15 2

. 7 Future Year Emissions The future years of interest for the new regional modeling are: (TBD)

.

For on

- road and nonroad sources, the future year emissions will be estimated by models (i.e.,

CO NCEPT and NMIM, respectively). Future year data will be supplied for five select networks.

For area, MAR, and non

- E GU point sources, the future year emissions for the LADCO States

w ill be derived by applying growth and control facto rs to the base year inventory. Given resource constraints, the growth factors from the previous regional modeling (E.H. Pechan, 2007) be u sed, subject to review and, if necessary, modification by a workgroup of state and local agency personnel.

For EGU point sources, ERTAC will be developing an appropriate g rowth methodology

.

Due to a lack of information on future year conditions, the biogenic VOC and NOx emissions,

and all Canadian emissions 8

**•** Federal Motor Vehicle Emission Control Program, low

- sulfur gasoline and ultra

- low sulfur

diesel fuel w ill be assumed to remain constant between the base year and future years

.

A “base” control scenario w ill be prepared based on the following “on the books” controls:

On

- Highway Mobile Sources

**•** Inspection

- maintenance programs

**•** Reformulated gasoline

Off

- Highway Mobile Sources

**•** Federal control programs incorporated into NONROAD model (e.g., nonroad diesel rule), plus the evaporative Large Spark Ignition and Recreational Vehicle standards

**•** Heavy

- duty diesel (2007) engine standard/Low sulfur fuel

**•** Federal railroad/locomotive standards

**•** Federal commercial marine vessel engine standards

Area Sources

**•** Consu mer solvents

**•** AIM coatings

**•** Aerosol coatings

**•** Portable fuel containers

Power Plants

**•** CAIR or proposed Transport Rule

Other Point Sources

**•** VOC 2

- , 4

- , 7

- , and 10

- year MACT standards

**•** Combustion turbine MACT

**•** Consent decrees (e.g., petroleum refineries, ethanol plants, and ALCOA in Indiana)

**•** NOx RACT

**•** BART emission limitations for units subject to BART

8 Future year Canadian emissions will be used, if available.16 Further discussion (and coordination with other regions and EPA) is needed to confirm the list of

“on the books” controls. Additional co ntrol scenarios will be modeled based on direction from

t he LADCO Project Team.

2.8 Q uality Assurance Procedures In its September 1, 2004, “Quality Management Plan”, LADCO describe its policies and practices to ensure the integrity and accuracy of the information produced. The plan was approved by EPA on January 26, 2005. In accordance with the plan, t he following quality

assurance activities will be conducted :

• Review model inputs and outputs

– each emissions modeler will review the model input files, and the gr aphical and tabular model outputs for reasonableness and consistency Emissions

• Benchmark modeling

– each modeling group will duplicate a set of standard modeling results

• Reports

- a standard set of graphical and tabular m odel outputs will be generated and

re viewed

• Documentation

– appropriate written reports will be prepared which summarize the modeling analyses

• Establish consistent file naming convention Modeling

• 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 m odeling 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 m odel outputs will be generated and

reviewed

• Documentation

– appropriate written reports will be prepared which summarize the modeling analyses17 Section 3 .0 Base Case Modeling

The purpose of the base case 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 candida te control strategies.

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

ozone , species of interest include ozone , total NMOC, select VOCs and carbonyls (e.g., benzene and formaldehyde), and NOx (and/or NOy). The relevant averaging times for these species are 1

- hour and 8

- hour. For PM and haze, species of interest include PM 2.5 - mass (gravimetric and RCFM), SO4, NO3, NH4, EC, OC, soil, bscat, coarse mass, as well as several gaseous precursors, such as NH3, HNO3, an d SO2. The relevant averaging times for these species are 1

- hour and 24

- hour.

3.1 Ambient Data Base

For 2007 and 2008 , ground

- level air quality measurements from routine state/local

- operated ambient monitoring stations will be obtained from EPA’s Air Quality System (AQS). Other

sources of air quality measurements include data from LADCO

- sponsored field studies (i.e., Molecular Marker Study, Biomass Burning Study, and Winte r Nitrate Study).

3.2 Model Evaluation Procedures EPA’s modeling guidelines i dentify two way s to evaluate the performance of an air quality

mo del : (1) how well is the model able to replicate observed concentrations of PM 2.5 components, ozone and/or precursors (surface and aloft) , and

(2) how accurate is the model in characterizing the sensitivity of ozone and/or PM 2.5 to changes in emissions?

An operational evaluation is performed to answer the first question, while a more in

- depth, diagnostic evaluation is performed to answer the second question. This second questions is important given that the modeled attainment tests use models to predict the response of ozone

and PM 2.5 to changes in emissions and then applies the resulting relative response factors to ambient monitoring data.

The proposed operational evaluation of model performance consists of the following comparisons of modeled and mon itored concentrations:

Time series plot of mean bias

**•** Peak daily 8

- hour ozone with 40/60/80 ppb thresholds

**•** Monthly average PM2.5 by chemical species

Scatterplots

**•** Ozone

– hourly concentrations

**•** PM2.5

– daily concentrations18 Spatial concentration plots

**•** Ozone: May 22

- 24, 2007 (or May 29

- 31, 2007), June 15

- 18, 2007, Aug 1

- 3, 2007,
and July 16

- 18, 2008

**•** PM2.5: May 29

- June 2, 2007, Aug 2

- 3, 2007, Dec 18

- 21, 2007, Feb 23

- 24, 2008,
and July 18

- 19, 2008

Individual monitor time series

– one for 2007, and one for 2008

Oz one Warren OH 391650007 Cincinnati

– Taft 390610040 PM2.5

Ashtabula OH 390071001 Cleveland

- G.T. Craig 390350060

Holland MI 260050003

Port Huron MI 261470005 Detroit

- Dearborn 261630038 Sheboygan WI 551170006 Green Bay WI 550090005

Chiw aukee WI 550590019 Milwaukee

– SE Hdqs 550790026

St.Louis

– W. Alton 291831002 Granite City IL 171630010 Chicago

– Springfield 170310057

Minn.

– Anderson 270530963

Columbus OH 390490029 Steubenville OH 390810017

Noblesville IN 180570005 Indianapolis

- 18 th St 180970081

Charlestown IN 180190008 Jeffersonville IN 180190006

New Paris OH 391351001 New Paris OH 391351001 Mayville WI 550270007 Mayville WI 550270007 Port Stanley ON Port Stanley ON

Northbrook IL 170314201 Gary IITRI 180890022 Ozone precursors (NOx or NO2, and VOC

– which species?? )

Detroit

- E. 7 mile 261630025 Milwaukee

- SE Hdqs 550790026

Cincinnati

– Taft 390610040 Braidwood IL 171971011

T he model

- to

- monitor comparisons wi ll be paired in time and space. The modeled values should be taken from grid cells “near” a monitor (e. g. , from the 3x3 grid cells centered on the monitor for 12 km modeling).

No rigid acceptance/rejection criteria will be used for this study. Instead, the statistical guidelines recommended by EPA and other modeling studies (e.g., modeling by the other RPOs) will be used to assess the reasonableness of the results here.

The proposed diagnostic evaluation of model performance will focus on the change in ambient

ozone and PM 2.5 concentrations between 2002 , 2005, and 200 8

. A p r evious operational evaluation by LADCO compared observed and modeled ozone concentrations for the summers

of 2002 and 2005 ( Baker , 2007) . Figure 5 below shows the paired change in observed concentration (x

- axis) and modeled c oncentration (y

- axis). Even though the model tends to underestimate higher observed absolute ozone concentrations, the figure shows that the model response matches the observed response.19 Figure 5 . Paired observed concentration change and modeled concentration change (absolute values in red and percentage values in blue)20 Section 4 .0

Future Year Modeling

The purpose of the future year modeling is to assess the effectiveness of existing and possible additional control programs. T he model will be used in a relative sense to project future year
values, which are then compared to the NAAQS to determine attain ment/nonattainment.

F urther discussion of the future year control scenarios and application of EPA’s attainment test is provided below.

4.1 Model F uture Y ear C ontrol S cenarios

A “base” control scenario reflecting “on the books” controls will be modeled : Additional control

scenarios will be identified by t he LADCO Project Team.

To help guide the development of control scenarios, s ensitivity modeling will be conducted. The purpose of these model runs is to assess t he effect of changes in the amount, type, and location of primary and precursor emissions. Possible sensitivity tests include:

**•** General control path analyses, such as “matrix” runs, which examine the effect of reductions by species, source categories, and geographic area.

**•** 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.

Probing tools, such as OSAT/PSAT and DDM, will also be used to provide information on

source contributions and source sensitivity, respectively.

4.2 Apply A ttainment T est The absolute modeled concentrations from the future year control scenario modeling will be processed to assess attainment of the NAAQS. The basic analysis steps are as follows:

(1) Calculate base year design values: F or ozone and PM 2.5 , the base year design

values w ill be derived by averaging the three 3

- year pe riods centered on the base

year:

200 7 base year: 200 5

- 200 7 , 200 6

- 200 8 , and 200 7

- 20 09 9

(2) Estimate future years values: For each grid cell, a relative reduction factor (RRF) is calculated by taking the ratio of the future year and baseline modeling results. For Ground

- level air quality measurements for 2005

- 2009 from routine state/local

operated ambient monitoring stations will be obtained from EPA’s Air Quality System (AQS).

9 As noted above, a decision will be made later based on technical and policy reasons on wh ether to use 2007 or 2008 meteorology to use in the future year modeling. For the p urpose of this document, it is assumed that 2007 meteorology will be used.21 each grid cell (with a monitor), the RRFs are multiplied by the base year design values to project the future year values

Ozone concentrations will be estimated f or those grid cells/counties with ozone
monitors. PM 2.5 concentrations will be estimated for those grid cells/counties with FRM (PM2.5

- mass) monitors. Spatial mapping will be performed to extrapolate

PM 2.5 - speciation data from STN and IMPROVE sites to FRM sites.

EPA’s attainment test program (referred to as MATS) will be used . Issues to be considered in applying the attainment test include:

**•** Cell Selection: For a given monitor, how far away should modeled values be

taken ?

**•** Model Performance: Should on ly those days with good model performance be

used in the calculation ?

**•** Concentration Threshold: A th reshold concentration of 70 ppb will be assumed in calculating RRFs for ozone (i.e., only those days with base case modeled values equal to or greater than 70 ppb will be used ).

(3) Assess attainment: Future year values are compared to the NAAQS to determine

attainment or nonattainment.

The modeling results will be presented in graphs, such as scatter plots, concentration difference plots, threshold difference plots, and time series plot s, and

in tables.

Consistent with EPA’s modeling guid ance, an “unmonitored area analysis” will also be performed to identify areas where absolute modeled v alues are predicted to be greater than the NAAQS (see Baker, 2005).22 Section 5 .0 Weight of Evidence Demonstration

This section provides an overview of information that will be considered along with the future year modeling in a “weight of evidence” demonstration of whether an area is likely to attain the NAAQS by the applicable date. EPA guid ance recommend s that “supplemental evidence should accompany a ll model attainment demonstrations.” In particular, EPA encourages analyses that “help determine whether the model likely overpredicts, underpredicts, or accurately predicts the air quality improvement projected to occur by the a ttainment date.”

5.1 Ambient Data Analyses

The following analyses of monitoring data will provide information on the effect of emission

reductions b y pollutant, geographic area, and s ource category:

**•** observation

- based modeling ;

**•** trends in air quality and emissions (e.g., how have reductions in certain precursors affected ozone and PM2.5 concentrations over time?);

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

on certain downwind locations ) ; and

**•** monitor

- based source apportionment ana lyses (e.g., what can we say about the contribution of individual source categories on PM2.5 nonattainment areas ).

For example, based on the results of several air quality studies, LADCO prepared a White Paper which identified measures which will be effective in lowering PM2.5 daily concentrations in the Midwest. This document will be updated using more recent studies and expanded to address other pollutants.

5.2 Modeling Analyses The following modeling analyses will be provide information on sourc e contributions and the

likelihood of attaining the standards:

**•** a lternative modeling (i.e., use of the guideline modeling described in the previous

sections with different assumptions, such as alternative calculation of base year design values) ;

**•** additional modeling (e.g., EPA’s latest regional ozone and PM 2.5 modeling as part of the proposed Transport Rule w ill be considered as corroborative information) ; and

**•** model

- based source apportionment using the source apportionment tools in CAMx to

estimate the impact of specific geographic source regions and specific source sectors at monitoring sites in the region.23 Section 6 .0 Procedural Requirements

This section summarizes several important procedural issues related to the air quality

a ssessment, including documentation, deliverables, and resources.

6.1 Documentation To document the air quality assessment, technical memoranda will be prepared for the following topics:

**•** B ase year and future year emission inventories

**•** B ase year and future ye ar modeling

**•** C onceptual model

In addition, appropriate work products, including data files, tables, graphics, technical memoranda and reports will be made available on LADCO’s website (see Technical Activities

page: http://www.ladco.org/tech/ ).

6.2 Deliverables As the technical analyses proceed, p eriodic updates will be provided at Project Team meetings

and conference calls . Results will also be shared with interested stakeholders at public workshops.

Upon completion of the analyses, a Technical Support Document will be prepared, similar to the

document from the last assessment

– see “Regional Air Quality Analyses for Ozone, PM 2.5 , and Regional Haze: Final Technical Support Document”, April 25, 2008 http://www.ladco.org/reports/technical_support_document/tsd/tsd_version_iv_april_25_2008_fin al.pdf ).

6.3 Resources

No additional federal or state f unding for contractor assistance is expected to be available for the new air quality assessment. I f such funding does become available, then using these funds may be used for contractor assistance for certain key activities, such as :

**•** Updated growth and c ontrol factors

**•** Link

- based motor vehicle emissions

**•** Agricultural ammonia emissions

**•** Review and improve nonroad emission estimates

**•** White papers for candidate control strategies.24 Section 7 .0

References

Alpine Geophysics, 2009, “Evaluation of 36/12 m MM5 for Calendar Year 2007 over the Continental and Midwest/Eastern United States”, August 31, 2009.

Baker, K. “Hot Spot Test (Draft)”, Lake Michigan Air Directors Consortium, March 23, 2005.

Baker, K. an d D. Kenski, “Diagnostic and Operational Evaluation of 2002 and 2005 Estimated 8

- hr Ozone to Support Model Attainment Demonstrations”, October 2007, CMAS Conference,

North Carolina.

Blanchard, C. and S. Tanenbaum,”Analysis of Inorganic Particulate Matter Formation in the Midwestern United States”, Final Report, November 30, 2008

EPA, “ Guidelines on the Use of Models and Other Analyses for Demonstrating Attainment of Air Quality Goals for Ozone, PM 2.5 , and Regional Haze”, EP A

- 454/B07

- 002, April 2007.

Kens ki, D., “Updated CART Analysis for Ozone through 2008 (Preliminary Draft) ”, Lake Michigan Air Directors Consortium, 2008

LADCO, “Quality Mana gement Plan”, September 1, 2004

LADCO, “Regional Air Quality Analyses for Ozone, PM 2.5 , and Regional Haze: Final Technical Support Document”, April 25, 2008

LADCO, “A Conceptual Model of PM 2.5 Episodes in the Midwest”, LADCO, January 2009

LADCO, “White Paper: Approaches for Attaining the PM2.5 Daily Standard”, October 8, 2009

Schauer, J.J., A. Rutter, D. Snyder, E. Stone, M. Olson, J. Zhou, C. Worley, T. Katzman, R.

Collins, R. Bader, T. Dallmann, J. DeMinter, M. Mieritz, B. Shelton, and A. Plourde, “LADCO
Organic Molecular Marker Study”, Final Report, July 17, 2009, University of Wisconsin

- Madison

State Collabor ative Modeling Workgroup, “Regional Modeling for the Eastern U.S.: Technical Support Document”, July 9, 2009

Sullivan, A.P., and J.L. Collett, “Biomass Burning Impacts on Air Quality in the Upper Midwest”,
Final Report, January 28, 2009, Colorado State Un iversity