Bryan W. Shaw, Ph.D., Chairman
Buddy Garcia, Commissioner

Carlos Rubinstein, Commissioner 

### -


### .

:**~~·.->** .:.\ \ .: I·**!d:~** 

## fJLr.;·u:i: . !·

Mark R. Vickery, P.G., Executive Director 

## 10 APR -9 Pii 

## 1:55

TEXAS COMMISSION ON ENVIRONMENTAL QUALITY

Protecting Texas bg Reducing and Preventing Pollution 

## April6,2010

Docket No. 2009-0802-SIP, Project No. 2009-017-SIP-NR**~** 

### Docket No. 2009-0932-RUL, Rule Project No. 2009-006-101-EN · Docket No. 2009-0867-RUL, Rule Project No. 2009-019-101-EN

A1 Armendariz, PhD, Regional Administrator
U.S. Environmental Protection Agency- Region 6


### 1445 Ross Avenue Dallas, Texas 75202-2733

.

Dear Dr. Armendariz:

On March 10, 2010, the Texas Commission on Environmental Quality (Commission) adopted revisions to 

### the
State Implementation Plan (SlP) for the control of ozone air pollution for the Houston-Galveston-Brazoria (HGB) 

### area.

The Commission adopted amendments to 

### 30 Texas Administrative Code (TAC) Chapter 101, Subchapter A,
General Rules, Section 101.1; and Subchapter H, Emissions Banking and Trading, Division 6, Highly Reactive
Volatile Organic Compound Emissions Cap and 

### Trade Program, 

### Sections 101.390

- 101.394, 101.396, and 

### 101.399

- 101.401; 30 TAC Chapter 101, Subchapter H, 

### Emissions Banking and Trading, Division 3, Mass
Emissions C and 

### Trade Pro 

### Sections 101.350 101.351 and 

### 101.353 and co · revisions to the SlP; and 

### GB Attsinment Demonstration SlP Revision for the 1997 Ei t-Hour Ozone Standard. These rule changes and SIP revisions demonstrate that the HGB area 

### will attain the 

### 1997 eight-hour ozone National
Ambient Air 

### Quality Standard by June 15, 2019.

Enclosed are 

### the proposed revisions to the SlP, a public hearing certification, a 

### complete record of the public hearings, and the accompanying orders.· I 

### look forward to your expeditious approval of these SlP revisions.

Sincerely, 

# B**~,;ktw.--·**

# B~haw,PhD.

Chairman

BWS/jmm

Enclosures

cc: The Honorable Rick Perry, Governor ofTexas
Mr. Toby Baker, Office ofBudget, Planning and Policy, Office of the Governor

Mr. Mark 

### R Vickery, P.G., Executive Director, Texas Cor!unission on Environmental Quality

P.O. Box 13087 Austin, Texas 78711-3087 512-239'1000 1ntemet address: www.tceq.state.tx.usTexas Commission on Environmental Quality
Public Hearings
October 28-29, 2009

Houston-Galveston-Brazoria (HGB)
Attainment Demonstration SIP Revision
for the 1997 Eight-Hour Ozone Standard Project Number 2009-017-SIP-NR
Volume 1 of 2

# PUBLIC
NOTIFICATION AND
PROPOSALPUBLIC NOTIFICATION

Notification to the public of the proposed revision was conducted by the following procedures:

1 . Publication of notice of public hearings in the following newspapers on the date listed:

Austin American-Statesman, September 28, 2009

Houston Chronicle, September 28, 2009

2. Publication of the Notice of Public Hearings in the October 9, 2009, issue of the Texas Register

(34 TexReg 7132)

3. Correspondence forwarding the notice of public hearing to the following officials and agencies:

Speaker of the House

Lieutenant Governor

Alamo Area Council of Governments

Capital Area Planning Council

City of Austin, Mayor's Office

City of El Paso

City of Houston, Mayor's Office

City of Victoria Planning Department

Dallas Department of Environmental and Health Services

Dallas Department of Aviation

East Texas Council of Governments

El Paso Metropolitan Planning Organization

Federal Highway Administration

Fort Worth Environmental Management DepartmentGalveston County Health District

Houston Department of Health and Human Services

Harris County Public Health and Environmental Services

Houston-Galveston Area Council

North Central Texas Council of Governments

South East Texas Regional Planning Commission

Texas Department of Transportation

Texas Transportation Institute

Travis County Judge

Arkansas Department of Pollution Control and Ecology

Louisiana Department of Environmental Quality

New Mexico Environmental Department

Oklahoma Department of Environmental Quality

U.S. Environmental Protection Agency

### Example of Newspaper Classified Ad

Houston Chronicle, September 28,2009(TCEQ) for proposed Registration N

, 40243, to construct and operate

a Type V municipal solid waste trans station. The proposed facility,
River City Recycles, will be located 000 Daffan Lane, Austin, Texas 78724, in Travis County. This facil is requesting authorization to recycle and transfer municipal solid aste which includes construction

and demolition waste. The regi 'on application is available for viewing and copying at the TCEQ gion 11 Office, 2800 S. lli 35,

Suite 100, Austin, Travis County, 78704-5712.

PUBLIC COMMENT/PUBLIC ME

or written requests for a public m · must be submitted to the Office

of Chief Clerk at the address include in the information section below.
Comments may also be received if a ublic meeting is held on the facility. A public meeting will be held by he executive director if requested by a member of the legislature who epresents the general area where

the development is to be located, or f there is a substantial public interest in the proposed development purpose of the public meeting

is for the public to provide input for nsideration by the commission,

and for the' applicant and the comm · sion staff to provide information

to the public. A public meeting is t a contested case hearing. The
executive director will review and ider public comments and written requests for a public meeting su mitted prior to the notice of final

determination. The executive dire is not required to file a response

to comments.

EXECUTIVE DIRECTOR ACTIO

. The executive director shall, after review of an application for regi tion, determine if the application will be approved or denied in hole or in part. If the executive

director acts on an application, the 'efclerk shall mail or otherwise

transmit notice of the action and an xplanation of the opportunity to
file a motion to reconsider the exec 've director's decision. The chief

clerk shall mail this notice to the o and operator, the public interest counsel, to adjacent landowners as own on the required land ownership map and landowners list, and other persons who timely filed public comment in response to pub ic notice. Not all persons on the mailing list for this notice will recei e the notice letter from the Office

of the Chief Clerk.

INFORMATION. Written public

on the permanent mailing list fo this application should be submitted to the Office of the Chief lerk, MC 105, TCEQ, P.O. Box 13087, Austin, TX 78711-3088 or electronically submitted to http://wwwS.tceq.state.tx.uslecmn index.cfm. Individual members

of the general public may contact e Office of Public Assistance at 1-800-687-4040. General info ·on regarding the TCEQ can be

found at our web site at www.tce .state.tx.us. Further information

may also be obtained from Ms. n Rodewald at the address stated
above or by calling (512) 832-83

TRD-200904422

LaDonna Castanuela

Chief Cleric

Texas Commission on Environmen

Flied: September 30, 2009 

# •

Notice of Public Hearings on Chapter I 0 I and to the State 

# •

oposed Revisions to 30 TAC plementation Plan

The Texas Commission on Enviro ental Quality (commission) will

conduct concurrent public he · to receive testimony regarding proposed revisions to 30 TAC Cha r 10 I, General Air Quality Rules, Subchapter A, Definitions, and Su hapter H, Emissions Banking and Trading, Division 6, Highly-Re 've Volatile Organic Compound

Emissions Cap and Trade Pro

, and corresponding revisions to
the state implementation plan (S ) under the requirements of Texas



### 34 TexReg 7132 October 9, 2009 Texas Register Health and Safety Code, §382.017; exas Government Code, Chapter 2001, Subchapter B; and 40 Code fFederal Regulations §51.102, of

the United States Environmental P tection Agency (EPA) concerning

SIPs.

The proposed amendments to C pter 101, Subchapter A, §101.1, Definitions, would update the de nition of volatile organic compound to link the 30 TAC defini on with the current definition in

40 Code of Federal Regulations d correct the reportable quantity

for 1,1,1,2,3,3,3-heptaftuoroprop

. The proposed amendment to Chapter 101, Subchapter H, Div ion 6, Highly-Reactive Volatile Organic Compound Emissions Ca and Trade Program, would also

reduce the total cap amount of al wances and revise the allocation methodology of allowances for p 'cipants in the Highly-Reactive
Volatile Organic Compound Emiss· ns Cap and Trade Program. (Rule Project No. 2009-006-101-EN)

Public hearings for this proposed lemaking and corresponding SIP
revision are scheduled in conjun n with the proposed amendments

to Chapter 101, Subchapter H, Di ision 3, Mass Emissions Cap and

Trade (MECn program; and Cha ter 115, Subchapter E, Division 4,
Offset Lithographic Printing at the allowing times and locations: October 28, 2009, 2:00p.m. and 6:00 .m., in Conference Room A at the

Houston-Galveston Area Council, 555 Tunmons Lane, Houston; and

in Austin on October 29, 2009, 1: 0 p.m. and 3:00p.m., at the Texas
Commission on Environmental Q ity complex, Building E, Room 201S, 12100 Park 35 Circle. The hearings will be structured for the receipt of oral or written commen by interested persons. Registration
will begin 30 minutes prior to eac hearing. Individuals may present
oral statements when called upon order of registration. There will
be no open discussion during the earing; however, commission staff

members will be available to disc the proposals 30 minutes before

each hearing and will answer que 'ons before and after the hearing.

Persons planning to attend the he · g, who have special communication or other accommodation n ds, should contact Charlotte Horn,

Texas Register Team (512) 239-0 9. Requests should be made as far
in advance as possible.

Comments may be submitted to Jessica Rawlings, Texas Register Team, Office of Legal Services, 1i xas Commission on Environmental Quality, MC 205, P.O. Box 130 7, Austin, Texas 78711-3087, or faxed to (512) 239-4808. Ele ·c comments may be submitted at www5.tceq.state.tt.us/ruleslecom ents/. File size restrictions may apply to comments being submitted ia the eComments system. Copies

of the proposed rules can be o · ed from the commission's Web site

at http://www.tceq.state.tt.us/nav. leslpropose_adopt.html. Copies

of the proposed SIP revisions d all appendices can be obtained

from the commission's Web site t http:/lwww.tceq.state.tt.us/imp/ementationlair/sip/Hottop.html F r further information regarding the proposed rules and SIP revisio please contact Ray Schubert, Air Quality Planning Section, at (512 239-6615.

TR0-200904274

Robert Martinez
Oiredor, Environmental Law Divis n

Texas Commission on Environme tal Quality

Filed: September 25, 2009 

# • • •

Notice of Public Hearings on Proposed Revisions to 30 TAC Chapters lOI and II5 and to the State Implementation Plan

The Texas Commission on Environmental Quality (commission) will

conduct public hearings to receive testimony regarding proposed
revisions to 30 TAC Chapter 101, General Air Quality Rules, and

30 TAC Chapter 115, Control of Air Pollution from Volatile OrganicCompounds and corresponding revisions to the state implementation plan (SIP) under the requirements of Texas Health and Safety Code, §382.017; Texas Government Code, Chapter 2001, Subchapter B; and
40 Code of Federal Regulations §5 1.1 02, and the United States Envi·
ronmental Protection Agency (EPA) concerning SIPs. Additionally,
the commission will also receive testimony regarding the proposed eight-hour ozone attainment demonstration and rea.Sonable further

progress (RFP) demonstration for the Houston-Galveston-Brazoria (HGB) area.

The proposed amendment to Chapter 101, Subchapter H, Division 3,
Mass Emissions Cap and Trade (MECn Program, would revise the definition of "Uncontrolled design capacity" to provide additional flexibility for certain stationary diesel engines and clarify both site and facility applicability. In addition, the proposed amendment would maintain the integrity of the nitrogen oxides (NO.) cap in the HGB ozone nonattainment area and minimize increases in the NO. cap by discontinuing the acceptance oflate ECT-3 forms, Level of Activity Certification, from major sources of NO. submitted after March 30, 2010. (Rule Projeet No. 2009-019-101-EN)

The proposed amendment to Chapter 101, Subchapter H, Division 6, Highly-Reactive Volatile Organic Compound Emissions Cap and Trade Program, would reduce the total cap amount of allowances and
revise the allocation methodology of allowances for participants in the Highly-Reactive Volatile Organic Compound (HRVOC) Emissions Cap and Trade Program. A proposed amendment to § 101.1 would also update the definition of volatile organic compound (VOC) to link the
30 TAC definition with the current definition in 40 Code of Federal Regulations and correct the reportable quantity for 1,1,1,2,3,3,3-heptafluoropropane. (Rule Project No. 2009-ooci-101-EN)

The proposed amendments to Chapter 115, Subchapter E, Division 4,
Offset Lithographic Printing, would reduce the VOC content limits on fountain solutions used by sources that are subject to the existing Chapter 115 rules. The proposed rulemaking would also limit the VOC

content of fountain and cleaning solutions used by certain sources that

are exempt from the existing Chapter 115 rules. (Rule Projeet No. 2008-019-115-EN)

The proposed HGB Attainment Demonstration SIP revision contains Federal Clean Air Act-required SIP elements, including a photochemical modeling analysis, a weight of evidence analysis, a reasonable
available control technology (RACT) analysis, a reasonably available
control measures (RACM) analysis, a motor vehicle emissions budget (MVEB) for 2018, and a contingency plan. In addition, the Houston-Galveston Area Council bas committed to emissions reductions through the Voluntary Mobile Emission Reduction Program and implementation of transportation control measures. The proposed revision also describes the concurrently proposed rule revisions in Chapters 101 and 115. The commission is also soliciting comments on whether it is appropriate to perform a 1997 eight-hour ozone standard
mid-course review analysis, and, if so, what elements should be contained in the analysis. The commission is also seeking input on the appropriate date to submit the mid-course review. (Rule Projeet No. 2009-017-SIP-NR)

The proposed HGB Eight-Hour Ozone Nonattainment Area RFP SIP revision demonstrates that the 18 percent ozone precursor emissions reduction requirement will be met for the analysis period of2002 to 2008,
9 percent between 2009 and 2011, 9 percent between 2012 and 2014,
9 percent between 2015 and 2017, 3 percent in 2018, and 3 percent for contingency purposes. This revision also includes a revised MVEB
for the milestone years 2008, 2011, 2014, 2017, and 2018. No new on-road mobile source controls have been adopted as part of the plan. However, on-road mobile source emissions inventories have been updated using the latest available data and the EPA's MOBILE6 inventory development tool. As a result of the required mobile source emission inventory updates, the MVEBs are updated as part of this SIP revision. (Rule Projeet No. 2009-018-SIP-NR)

Public hearings on these proposals will be held at the following times
and locations: October 28, 2009, 2:00 p.m. and 6:00 p.m., in Conference Room A at the Houston-Galveston Area Council, 3555 Tunmons Lane, Houston; and in Austin on October 29, 2009, 3:00p.m., at the
Texas Commission on Environmental Quality complex, Building E,
Room 201 S, 12100 Park 35 Circle. The hearings will be structured for the receipt of oral or written comments by interested persons. Registration will begin 30 minutes prior to each hearing. Individuals may present oral statements when called upon in order of registration. There will be no open discussion during the hearing; however, commission
staff members will be available to discuss the proposals 30 minutes before each hearing and will answer questions before and after the hear·
in g.

Persons planning to attend the bearing, who have special communi·
cation or other accommodation needs, should contact Charlotte Hom,
Texas Register Team (512) 239-0779. Requests should be made as far
in advance as possible.

Comments may be submitted to Jessica Rawlings, Texas Register Team, Office of Legal Services, Texas Commission on Environmental Quality, MC 205, P.O. Box 13087, Austin, Texas 78711-3087, or faxed to (512) 239-4808. Electronic comments may be submitted at www5.tceq.state.tx.uslruleslecommentsl. File size restrictions may apply to comments being submitted via the eComments system. All

comments sbould reference tbe rule or SIP projeet number tbat
the comment pertains to: Rule Project No. 2009-019-101-EN for the proposed MECT rule amendments, Rule Projeet No.
2009-ooci-101-EN for tbe proposed HRVOC rule amendments,
Rule Projeet No. 2008-019-115-EN for tbe proposed VOC rule amendments, SIP Projeet No. 2009-017-SIP-NR for the proposed HGB Attainment Demonstration SIP revision and SIP Projeet
No. 2009-018-SIP-NR for tbe proposed HGB RFP SIP revision.
Comments must be received by November 9, 2009. Copies of the proposed rules can be obtained from the commission's Web site

at http:llwww.tceq.state.tx.uslnav/ruleslpropose

_ adopt.html. Copies
of the proposed SIP revisions and all appendices can be obtained from the commission's Web site at hltp:llwww.tceq.state.t:x.IIS!implementationlairlsip/Hottop.html. For further information regarding the proposed rules and SIP revisions, please contact Ray Schubert, Air Quality Planning Section, at (512) 239-6615.

TRD-200904267

Robert Martinez
Diredor, Environmental Law Division

Texas Commission on Environmental Quality

Filed: September 25, 2009 

# • • •

Notice of Public Hearings on oposed Revisions to 30 TAC Chapter 115 and to the State I plementation Plan

The Texas Commission on En · ental Quality (commission) will
conduct public bearings to rece e testimony regarding proposed
revisions to 30 TAC Chapter 10

, General Air Quality Rules, and 30 TAC Chapter 11 5, Control of · Pollution from Volatile Organic Compounds and corresponding isions to the state implementation plan (SIP) under the requiremen of Texas Health and Safety Code, §382.017; Texas Government C de, Chapter 2001, Subchapter B; and 40 Code of Federal Regulati ns §5 1.1 02, and the United States Environmental Protection Agen (EPA) concerning SIPs. Additionally, the commission will al receive testimony regarding the



### IN ADDITION October 9, 2009 34 TexReg 7133Bryan W. Shaw, Ph.D., Chairman

Buddy Garcia, Commissioner

Carlos Rubinstein, Commissioner

Mark R. Vickery, P.G., Executive Director



### TEXAS COMMISSION ON ENVIRONMENTAL QUALITY

Protecting Texas by Reducing and Preventing Pollution

NOTICE OF PUBLIC HEARINGS BY THE
TEXAS COMMISSION ON ENVIRONMENTAL QUALITY

ON PROPOSED REviSIONS TO 30 TAC CHAPTERS 101 AND 115, AND TO THE STATE

IMPLEMENTATION PLAN

The Texas Commission on Environmental Quality (commission) will conduct public hearings to receive testimony regarding proposed revisions to 30 TAC Chapter 101, General 

### Air Quality Rules, and 30 T AC Chapter 115, Control of 

### Air Pollution from Volatile Organic Compounds and corresponding revisions to
the state implementation plan (SIP) under the requirements of Texas Health and Safety Code, §382.017;

Texas Government Code, Chapter 2001, Subchapter B; and 40 Code of Federal Regulations §51.1 02, and

the United States Environmental Protection Agency (EPA) concerning SIPs. Additi.onally, the

commission will also receive testimony regarding the proposed eight-hour ozone attainment

demonstration and reasonable further progress (RFP) demonstration for the Houston-Galveston-Brazoria (HGB) area.

The proposed amendment to Chapter 101, Subchapter H, Division 3, Mass Emissions Cap and Trade (MECT) Program, would revise the definition of "Uncontrolled design capacity" to provide additional flexibility for certain stationary diesel engines and clarify both site and facility applicability. 

### In addition,

the proposed amendment would maintain the integrity of the nitrogen oxides 

### (NOx) cap in the HGB

ozone nonattainment area and minimize increases in the 

### NOx cap by discontinuing the acceptance of late

ECT-3 forms, Level of Activity Certification, from major sources of 

### NOx submitted 

### after March 30,

2010. (Rule Project No. 2009-019-101-EN)

The proposed amendment to Chapter 101, Subchapter H, Division 6, Highly-Reactive Volatile Organic Compound Emissions Cap and Trade 

### Program, would reduce the total cap amount of allowances and

revise the allocation methodology of allowances for participants in the Highly-Reactive Volatile Organic Compound (HRVOC) Emissions Cap and Trade Program. A proposed amendment to §101.1 would also update the definition of volatile organic compound (VOC) to link the 30 TAC definition with the current
defmition in 40 Code of Federal Regulations and correct the reportable quantity for 1,1,1,2,3,3,3- heptafl.uoropropane. (Rule Project No. 2009-006-101-EN)

The proposed amendments to Chapter 115, Subchapter E, Division 4, Offset Lithographic Printing, would

reduce the VOC content limits on fountain solutions used by sources that are subject to the existing Chapter 115 rules. The proposed rulemaking would also limit the VOC content of fountain and cleaning
solutions used by certain sources that are exempt from the existing Chapter 115 rules. (Rule Project No. 2008-019-115-EN)

The proposed HGB Attainment Demonstration SIP revision contains Federal Clean 

### Air Act-required SIP elements, including a photochemical modeling analysis, a weight of evidence analysis, a reasonable

available control technology (RACT) analysis, a reasonably available control measures (RACM) analysis,

a motor vehicle emissions budget (MVEB) for 2018, and a contingency plan. 

### In addition, the HoustonGalveston Area Council has committed to emissions reductions through the Voluntary Mobile Emission
Reduction Program and implementation of transportation control measures. The proposed revision also
describes the concurrently proposed rule revisions in Chapters 101 and 115. The commission is also

Pn Rm**1~0R7** Anc;tin**TPY:o~** 7R71 VlOR7 :; 1**?.-?.~G-** 1 nonsoliciting comments on whether it is appropriate to perform a 1997 eight-hour ozone standard mid-course
review analysis, and, if so, what elements should be contained in the analysis. The commission is also seeking input on the appropriate date to submit the mid-course review. (Rule Project No. 2009-017-SIPNR)

.

The proposed HGB Eight-Hour Ozone Nonattainment Area RFP SIP revision demonstrates that the 18
percent ozone precursor emissions reduction requirement will be met for the analysis period of 2002 to 2008, 9 percent between 2009 and 2011, 9 percent between 2012 and 2014,9 percent between 2015 and 2017, 3 percent in 2018, and 3 percent for contingency purposes. This revision also includes a revised

MVEB for the milestone years 2008, 2011, 2014, 2017, and 2018. No new on-road mobile source controls have been adopted as part of the plan. However, on-road mobile source emissions inventories

have been updated using the latest available data and the EPA's MOBU.E6 inventory development tool.

As a result of the required mobile source emission inventory updates, the MVEBs are updated as part of

this SIP revision. (Rule Project No. 2009-018-SIP-NR)

Public hearings on these proposals will be held at the following times and locations: October 28, 2009,

2:00 p.m. and 6:00 p.m., in Conference Room A at the Houston-Galveston Area Council, 3555 Timmons Lane, Houston; and in Austin on October 29, 2009, 3:00 p.m., at the Texas Commission on Environmental Quality complex, Building E, Room 201S, 12100 Park 35 Circle. The hearings will be

structured for the receipt of oral or written comments by interested persons. Registration will begin 30
minutes prior to each hearing. Individuals may present oral statements when called upon 

### in order of registration. There will be no open discussion during the hearing; however, commission staff members

will be available to discuss the proposals 30 minutes before each hearing and will answer questions before

and after the hearing.

Persons planning to attend the hearing, who have special communication or other accommodation needs,

should contact Charlotte Hom, Texas Register Team (512) 239-0779. Requests should be made as far in

advance as possible.

Comments may be submitted to Jessica Rawlings, Texas Register Team, Office of Legal Services, Texas
Commission on Environmental Quality, MC 205, P.O. Box 13087, Austin, Texas 78711-3087, or faxed to (512) 239-4808. Electronic comments may be submitted at www5.tceq.state.tx.uslruleslecommentsl. File

size restrictions may apply to comments being submitted via the eComments system. All comments
should reference the rule or SIP project number that the comment pertains to: Rule Project No.

2009-019-101-EN for the proposed MECT rule amendments, Rule Project No. 2009-006-101-EN for
the proposed HRVOC rule amendments, Rule Project No. 2008-019-115-EN for the proposed VOC

rule amendments, SIP Project No. 2009-017-SIP-NR for the proposed HGB Attainment
Demonstration SIP revision and SIP Project No. 2009-018-SIP-NR for the proposed HGB RFP SIP
revision. Comments must be received by November 9, 2009. Copies of the proposed rules can be

obtained from the commission's Web site at http://www.tceq.state.tx.uslnav/ruleslpropose_adopt.html. Copies of the proposed SIP revisions and all appendices can be obtained from the commission's Web site

at http:/lwww.tceq.state.tx.uslimplementationlair/sip/Hottop.html. For further information regarding the proposed rules and SIP revisions, please contact Ray Schubert, Air Quality Planning Section, at (512)

239-6615.

Issued in Austin, Texas, on September 23, 2009.REVISION TO THE STATE IMPLEMENTATION PLAN

FOR THE CONTROL OF OZONE AIR POLLUTION

HOUSTON-GALVESTON-BRAZORIA 1997 EI GHT-HOUR OZONE STANDARD

NONATTAINMENT AREA

TEXAS COMMISSION ON ENVIRONMENTAL QUALITY

P.O. BOX 13087 AUSTIN, TEXAS 78711-3087

Houston-Galveston-Brazoria Attainment Demonstration State Implementation Plan Revision for the 1997 Eight-Hour Ozone Standard

PROJECT NO. 2009-017-SIP-NR

Proposed September 23, 2009This page is intentionally left blank.EXECUTIVE SUMMARY The United States Environmental Protection Agency (EPA) reclassified the eight-county Houston-Galveston-Brazoria (HGB) area from a modera te to a severe nonattainment area for the 1997 eight-hour ozone National Ambient Air Qua lity Standard (NAAQS) effective on October 31, 2008. The HGB eight-county area includes Brazoria, Chambers, Fort Bend, Galveston, Harris, Liberty, Montgomery, and Waller Counties. The EPA set April 15, 2010, as the date for the state to submit a state implementation plan (SIP) revision addressing the severe ozone nonattainment area requirements of the 1990 Federa l Clean Air Act Amendments (FCAA). The HGB area must attain the 1997 eight-hour ozone standard of 0.08 parts per million (ppm) as expeditiously as practicable but no later than the attainment date of June 15, 2019. Since

emission reductions needed for attainment must be implemented by the beginning of the ozone season immediately preceding the HGB area’s attainment date, implementation of controls need to be made by 2018, which is the attainment year for modeling.

This SIP revision addresses ozone formation in th e HGB area, the precursor emissions of nitrogen oxides (NO X ) and volatile organic compounds (VOC), the control strategies that are to be implemented, the quantity of emission reductions associated with each strategy, and when these reductions will occur. Based on photochemical modeling and an evaluation of corroborative evidence, ozone measurements in the HGB area ar e predicted to be compliant with the 1997 eight-hour ozone NAAQS by June 15, 2019.

The existing measures to control ozone formation in the HGB area that have been adopted in previous SIP revisions center on:

• approximately 80 percent NO X emission reductions from point sources through the Mass Emission Cap and Trade (MECT) program;

• NO X emission reductions from on-road and non-road sources through the vehicle inspection and maintenance (I/M) program, the Texas Emission Reduction Plan (TERP), and the Texas Low Emission Diesel (TxLED) program;

• highly reactive volatile organic compounds (HRVOC) controls through the associated HRVOC Emission Cap and Trade (HECT) program; and

• VOC controls.

See Chapter 4, Control Strategies and Required Elements , Section 4.2, Existing Control

Measures for a complete list of control measures.

Despite the significant decreases in one-hour and eight-hour ozone design values and in NO X and VOC emissions in the HGB area, further reductions are needed to bring the area into attainment of the 1997 eight-hour ozone NAAQS. Even as key ozone-targeting regul atory programs have reduced the number and magnitude of ozone ex ceedances, the area of exceedance, and the population exposed to exceedances, economic a nd population growth continue to create air quality challenges for the HGB area.

This submittal contains proposed new state and lo cal control measures. The Houston-Galveston Area Council (H-GAC), as the regional metropolitan transportation planning agency for the HGB area, has identified three voluntary programs that will aid in the improvement of the HGB area’s air quality. The H-GAC’s commitment for NO X emissions reductions from the Voluntary Mobile Emission Reduction Program (VMEP) is 2.25 tons per day (tpd). The H-GAC has also identified transportations control measures (TCMs) that have been or will be implemented in the

inonattainment area. By the start of the 2018 ozone season, these TCMs will reduce NO X emissions in the HGB area by 0.015 tpd.

Photochemical modeling analysis demonstrates th at a 25 percent reduction of the HECT cap on the total Harris County HRVOC allocation would c ontribute to attainment of the 1997 eight-hour ozone NAAQS by reducing the future 2018 oz one design values at all HGB monitors. Accordingly, this SIP revision contains a pr oposed 25 percent reduction in the total HRVOC allowance cap and revision to the HRVOC allo cation methodology. The HECT program will continue to be applicable only in Harris County.

This plan demonstrates attainment using photoc hemical modeling that includes the existing and proposed control strategies previously listed. The demonstration also relies on weight of evidence (WoE) corroborative analysis and add itional control measures not explicitly accounted for in the photochemical modeling (see Chapter 5, Weight of Evidence ).

This SIP revision includes base case modeling of representative ozone exceedance episodes that occurred during 2005 and 2006. In general, the model performance evaluation of the base cases for 2005 and 2006 indicates the modeling is suitable for use in conducting the modeling attainment test. The modeling attainment test was applied by modeling a 2006 baseline year and 2018 future year to project 2018 eight-hour ozone d esign values. Only two regulatory monitors, Deer Park (DRPK) and Bayland Park (BAYP), and one non-regulatory monitor, Wallisville (WALV), are projected to have modeled 2018 eight-hour ozone design values greater than the 1997 eight-hour ozone NAAQS.

Modeling analyses of the sensitivity of the 2018 projected eight-hour ozone design values to
emission reductions of NO X and VOC generally indicate that the ozone design values are more

sensitive to NO X reductions than VOC. However, the sensitivity of ozone design values to reductions in HRVOC is much greater than for other VOC.

Table ES-1: Summary of 2006 Baseline, 2018 Future Year, and 2018 Control Strategy Anthropogenic Modeling Emissions for HGB lists the anthropogenic m odeling emissions in tons per day (tpd) by source category for the 2006 b aseline, 2018 future year, and the 2018 control strategies for NO X and VOC. The differences in modeling emissions between the 2006 baseline and the 2018 future year reflect the net of grow th and existing controls. The existing controls

include both state and federal measures that have already been promulgated. The differences in modeling emissions between the 2018 future year and the 2018 control strategy reflect the proposed controls. These proposed controls include NO X reductions from both the VMEP measures and TCMs, and the 25 percent reduction in the Harris County total HRVOC cap for the HECT program.

iiTable ES-1: Summary of 2006 Baseline, 2018 Future Year, and 2018 Control Strategy Anthropogenic Modeling Emissions for HGB

2006 Baseline 2018 Future Year 2018 Control Strategy

NO X VOC CO NO X VOC CO NO X VOC CO Source Type (tpd) (tpd) (tpd)

Point 172.16 208.34 126.22 162.75 309.46 182.10 162.75 306.77 182.10

On-road 197.28 99.39 1115.23 50.76 50.39 733.17 49.21 50.39 733.17

Non-road 78.85 75.97 772.94 35.65 59.56 893.84 34.95 59.56 893.84

Off-road 73.55 6.05 53.25 85.72 6.93 44.71 85.72 6.93 44.71

Area 36.35 528.99 134.59 42.04 650.09 158.99 42.04 650.09 158.99

Totals 558.19 918.74 2202.23 376.92 1076.43 2012.81 374.67 1073.74 2012.81 Note: VOC is reported as sum of CB05 species

Table ES-2: Summary of 2006 Baseline, 2018 Future Year, and 2018 Control Strategy EightHour Ozone Design Values for BAYP and DRPK Monitors lists the eight-hour ozone design values in parts per billion (ppb) for the 2006 baseline (DV B ), 2018 baseline future year (DV F ), and 2018 control strategy for the two regulatory monitors with model-projected 2018 eight-hour ozone design values greater than the 1997 eigh t-hour ozone NAAQS. However, 18 regulatorymonitors have model-projected 2018 eight-hour ozone design values less than the 1997 eighthour ozone NAAQS. Since the modeling cannot provi de an absolute prediction of future year ozone design values, additional information fro m corroborative analyses are used in assessing whether the area will attain the standard in the future year.

Table ES-2: Summary of Modeled 2006 Baseline, 2018 Future Year, and 2018 Control Strategy Eight-Hour Ozone Design Values for BAYP and DRPK Monitors

Monitor

Site Code Monitor Designation 2006

DV B (ppb) 2018 Baseline

DV F (ppb) 2018 Control Strategy

DV (ppb)

DRPK Deer Park (CAMS 35) 92.0 88.2 87.9

BAYP Bayland Park (CAMS 53) 96.7 87.0 86.9

Note: The 2006 DV B is different from the 2006 regulatory design value (DV R ). Figure 3-1: Baseline Design Value Calculation Illustration in Chapter 3, Photochemical Modeling, illustrates how DV B s are calculated using the three DV R s containing 2006 data. The 2006 DV R is the average of the fourth high ozone values from 2004, 2005, and 2006.

This SIP revision provides ozone reduction tr ends analyses and supplementary data to demonstrate that the HGB eight-county nonattainment area will attain the 1997 eight-hour ozone standard of 0.08 ppm (84 parts per billion (ppb )). The EPA’s April 2007 “Guidance on the Use of Models and Other Analyses for Demonstrati ng Attainment of Air Quality Goals for Ozone,

PM 2.5 , and Regional Haze” states that a weight of evidence demonstration is allowed when the future design value is at or below 87.9 pp b. The quantitative and qualitative corroborative analyses in Chapter 5, Weight of Evidence , support a conclusion that this SIP revision demonstrates attainment of the 1997 eight-hour ozone NAAQS.

This revision also includes FCAA-required SIP elem ents, including a reasonably available control measures (RACM) analysis, a reasonably available control technology (RACT) analysis, a motor vehicle emissions budget (MVEB), and a contingency plan. For the MVEB, see Table ES-3:

iii2018 Attainment Demonstration Motor Vehicle Emissions Budget for the Eight-County HGB

Area

.

Table ES-3: 2018 Attainment Demonstr ation Motor Vehicle Emissions Budget for the Eight-County HGB Area

Eight-County HGB Area Summer Weekday Emissions (tpd)

NO X VOC 2018 MVEB 49.22 45.97

The Texas Commission on Environmental Quality (TCEQ) is committed to developing and applying the best science and technology towa rds addressing and reducing ozone formation in

HGB and other nonattainment areas in Texas. Th is SIP revision also includes a description of how the TCEQ continues to use new technology, such as infrared VOC imaging to identify and control unaddressed or under-addressed pollution sources, to investigate possible emission reduction strategies, and other practical methods to continue making progress in air quality improvement. For more information, see Chapter 6, Ongoing and Future Initiatives

.

ivSECTION V: LEGAL AUTHORITY

A. General The Texas Commission on Environmental Quality (TCEQ) has the legal authority to implement, maintain, and enforce the National Ambient Air Quality Standards (NAAQS) and to control the quality of the state’s air, including maintaining adequate visibility.

The first air pollution control act, known as the Clean Air Act of Texas, was passed by the Texas Legislature in 1965. In 1967, the Clean Air Act of Texas was superseded by a more comprehensive statute, the Texas Clean Air Ac t (TCAA), found in Article 4477-5, Vernon’s Texas Civil Statutes. The legislature amended the TCAA in 1969, 1971, 1973, 1979, 1985, 1987, 1989, 1991, 1993, 1995, 1997, 1999, 2001, 2003, 2005, 2007, and 2009. In 1989, the TCAA was codified as Chapter 382 of the Texas Health & Safety Code.

Originally, the TCAA stated that the Texas Air Control Board (T ACB) is the state air pollution control agency and is principal authority in the state on matters relating to the quality of air resources. In 1991, the legislature abolished the TACB effective September 1, 1993, and its powers, duties, responsibilities, and functions were transferred to the Texas Natural Resource Conservation Commission (TNRCC). With the creation of the TNRCC, the authority over air quality is found in both the Texas Water Code and the TCAA. Specifically, the authority of the TNRCC is found in Chapters 5 and 7. Chapter 5, Subchapters A - F, H - J, and L, include the general provisions, organization, and general powers and duties of the TNRCC, and the responsibilities and authority of the executive director. This chapter also authorizes the TNRCC to implement action when emergency conditions ari se, and to conduct hearings. Chapter 7 gives the TNRCC enforcement authority. In 2001, the 77 th Texas Legislature continued the existence of the TNRCC until September 1, 2013, and cha nged the name of the TNRCC to the Texas Commission on Environmental Quality (TCEQ). In 2009, the 81 st Texas Legislature, during a special session, amended § 5.014 of the Texas Water Code, changing the e xpiration date of the TCEQ to September 1, 2011, unless continued in existence by the Texas Sunset Act.

The TCAA specifically authorizes the TCEQ to esta blish the level of quality to be maintained in the state’s air and to control the quality of the st ate’s air by preparing and developing a general, comprehensive plan. The TCAA, Subchapters A - D, also authorize the TCEQ to collect information to enable the commission to develop an inventory of emissions; to conduct research and investigations; to enter pr operty and examine records; to prescribe monitoring requirements; to institute enforcement proceedings; to enter into contracts and execute in struments; to formulate rules; to issue orders taking into consideration factors bearing upon health, welfare, social and economic factors, and practicability and reasona bleness; to conduct hearings; to establish air quality control regions; to encourage cooperation with citizens’ groups an d other agencies and political subdivisions of the state as well as w ith industries and the fe deral government; and to establish and operate a system of permits for construction or modification of facilities.

Local government authority is found in Subchapter E of the TCAA. Local governments have the same power as the TCEQ to enter property a nd make inspections. They also may make recommendations to the Commission concerning any action of the TCEQ that affects their territorial jurisdiction, may bring enforcement actions, and may execute cooperative agreements with the TCEQ or other local governments. In addition, a city or town may enact and enforce ordinances for the control and abatement of air po llution not inconsistent with the provisions of

the TCAA and the rules or orders of the Commission.

vSubchapters G and H of the TCAA authorize th e TCEQ to establish vehicle inspection and maintenance programs in certain areas of the state, consistent with the requirements of the federal Clean Air Act; coordinate with federal, state, and local transportation planning agencies to develop and implement transportation programs and measures necessary to attain and maintain the NAAQS; establish gasoline volatility and low emission diesel standards; and fund and authorize participating counties to implement vehicle repair assistance, retrofit, and accelerated vehicle retirement programs.

B. Applicable Law The following statutes and rules provide necessar y authority to adopt and implement the State Implementation Plan (SIP). The rules listed belo w have previously been submitted as part of the

SIP.

Statutes All sections of each subchapter are included, unless otherwise noted.

TEXAS HEALTH & SAFETY CODE, Chapter 382 September 1, 2009

TEXAS WATER CODE September 1, 2009

Chapter 5: Texas Natural Resource Conservation Commission Subchapter A: General Provisions Subchapter B: Organization of the Tex as Natural Resource Conservation Commission Subchapter C: Texas Natural Resource Conservation Commission Subchapter D: General Powers and Duties of the Commission Subchapter E: Administrative Provisions for Commission Subchapter F: Executive Director (except §§ 5.225, 5.226, 5.227, 5.2275, 5.231, 5.232, and 5.236) Subchapter H: Delegation of Hearings Subchapter I: Judicial Review Subchapter J: Consolidated Permit Processing Subchapter L: Emergency a nd Temporary Orders (§§ 5.514, 5.5145, and 5.515 only) Subchapter M: Environmental Permitting Procedures (§ 5.558 only)

Chapter 7: Enforcement Subchapter A: General Provisions (§§ 7.001, 7. 002, 7.00251, 7.0025, 7.004, and 7.005 only) Subchapter B: Corrective Action and Injunctive Relief (§ 7.032 only) Subchapter C: Administrative Penalties Subchapter D: Civil Penalties (except §7.109) Subchapter E: Criminal Offenses and Penalties: §§ 7.177, 7.179-7.183

Rules All of the following rules are found in 30, Texas Administrative Code, as of the following

effective dates:

Chapter 7: Memoranda of Understanding, § 7.110 and § 7.119 May 2, 2002

Chapter 19: Electronic Reporting March 1, 2007

Chapter 35, Subchapters A-C, K: Emergency and Temporary Orders and Permits; Temporary Suspension or Amendment of Permit Conditions July 20, 2006

viChapter 39: Public Notice, §§ 39.201; 39.401; 39.403(a) and (b)(8)-(10); 39.405(f)(1) and (g); 39.409; 39.411 (a), (b)(1)-(6) and (8)-(10), (c)(1)-(6), and (d); 39.413(9), (11), (12), and (14); 39.418(a) and (b)(3) and (4); 39.419(a), (b), (d), and (e ); 39.420(a), (b) and (c)(3) and (4); 39.423 (a) and (b); 39.601-39.605 March 29, 2006

Chapter 55: Requests for Reconsideration and Contested Case Hearings; Public Comment, §§ 55.1; 55.21(a)-(d), (e)(2), (3), and (12), (f), and (g); 55.101(a), (b), and (c)(6)-(8); 55.103; 55.150; 55.152(a)(1), (2), and (6) and (b); 55.154; 55.156; 55.200; 55.201(a)-(h); 55.203; 55.205; 55.209, and 55.211 March 29, 2006

Chapter 101: General Air Quality Rules January 1, 2009

Chapter 106: Permits by Rule, Subchapter A June 30, 2004

Chapter 111: Control of Air Pollution from Visible Emissions and

Particulate Matter July 19, 2006

Chapter 112: Control of Air Pollution from Sulfur Compounds July 16, 1997

Chapter 113: Standards of Performance for Hazardous Air Pollutants and for Designated Facilities and Po llutants May 14, 2009

Chapter 114: Control of Air Pollution from Motor Vehicles June 26, 2008

Chapter 115: Control of Air Pollution from Volatile Organic Compounds July 19, 2007

Chapter 116: Permits for New Construction or Modification May 29, 2008

Chapter 117: Control of Air Pollution from Nitrogen Compounds March 4, 2009

Chapter 118: Control of Air Pollution Episodes March 5, 2000

Chapter 122: § 122.122: Potential to Emit December 11, 2002

Chapter 122: § 122.215: Minor Permit Revisi ons June 3, 2001

Chapter 122: § 122. 216: Applications for Minor Permit Revisions June 3, 2001

Chapter 122: § 122.217: Procedures for Minor Permit Revisions December 11, 2002

Chapter 122: § 122.218 Minor Permit Revision Procedures for Permit Revisions Involving the Use of Economic Incentives, Marketable Permits, and Emissions Trading June 3, 2001

viiSECTION VI. CONTROL STRATEGY

A. Introduction (No change)

B. Ozone (Revised)

1. Dallas-Fort Worth (No change)

2. Houston-Galveston-Brazoria (Revised) Chapter 1: General Chapter 2: Anthropogenic Emissions Inventory (EI) Description Chapter 3: Photochemical Modeling Chapter 4: Control Strategies and Required Elements Chapter 5: Weight of Evidence Chapter 6: Ongoing and Future Initiatives

3. Beaumont-Port Arthur (No change)

4. El Paso (No change)

5. Regional Strategies (No change)

6. Northeast Texas (No change)

7. Austin Area (No change)

8. San Antonio Area (No change)

C. Particulate Matter (No change)

D. Carbon Monoxide (No change)

E. Lead (No change)

F. Oxides of Nitrogen (No change)

G. Sulfur Dioxide (No change)

H. Conformity with the National Ambient Air Quality Standards (No change)

I. Site Specific (No change)

J. Mobile Sources Strategies (No change)

K. Clean Air Interstate Rule (No change)

L. Transport (No change)

M. Regional Haze (No change)

viiiLIST OF ACRONYMS

ACT Alternative Control Techniques

AERR Air Emissions Reporting Requirements

AGL Above Ground Level

AIRS Aerometric Information Retrieval System

APCA Anthropogenic Precursor Culpability Assessment

APU Auxiliary Power Unit

ARD Acid Rain Database

auto-GC Automated Gas Chromatograph

AWO American Waterways Operators

BACT Best Available Control Technology

BAYP Houston Bayland Park Monitor (CAMS 53)

BCCA-AG Business Coalition for Clean Air-Appeal Group

BELD Biogenic Emissions Landuse Data

BMP Best Management Practices

BPA Beaumont-Port Arthur

C35C Clinton Monitor (CAMS 403/CAMS 113/CAMS 304)

CAIR Clean Air Interstate Rule

CAMS Continuous Air Monitoring Station

CAMx Comprehensive Air Model with Extension

CARB California Air Resources Board

CEMS Continuous Emission Monitoring Systems

CENRAP/RPO Central Regional Air Pl anning Association/Regional Planning Organization

CFFP Clean Fuel Fleet Program

CFR Code of Federal Regulations

CFV Clean Fuel Vehicles

ClNO 2 Nitryl Chloride

CLU Common Land Unit

CNR2 Conroe Relocated (CAMS 78)

CO Carbon Monoxide

CTAC Chemical Transportation Advisory Committee

CTG Control Technique Guidelines

DACM AirCheckTexas Drive a Clean Machine

DERC Discrete Emissions Reduction Credit

DFW Dallas-Fort Worth

DIAL Differential Absorption Lidar

DMA Marine Distillate Fuel A

DMX Marine Distillate Fuel X

DOAS Differential Optical Absorption Spectroscopy

DRE Destruction and Removal Efficiency

DRPK Deer Park Monitor (CAMS 35/139)

DV Design Value

DV 18 2018 Ozone Design Value

ixDV B Baseline Year Ozone Design Value

DV F Future Design Value

EBI Euler Backward Iterative

ECA Emissions Control Area

EDAS Ecosystem Dynamics and the Atmosphere Section

EE/RE Energy Efficiency and Renewable Energy

EGAS Economic Growth Analysis System

EGU Electric Generating Unit

EI Emissions Inventory
EIQ Emissions Inventory Questionnaires

EPA United States Environmental Protection Agency

EPS3 Emissions Processing System version 3

ERC Emissions Reduction Credit

ESL Energy Systems Laboratory

ETH Ethylene

FCAA Federal Clean Air Act

FDDA Four-Dimensional Data Assimilation

FIP Federal Implementation Plan

FMVCP Federal Motor Vehicle Control Program

FORM Formaldehyde

GALV Galveston Airport Monitor (CAMS 34/CAMS 109/CAMS 154)

GAPP GEWEX Americas Prediction Project

GCIP GEWEX Continental International Project

GEWEX Global Energy and Water Cycle Experiment

GloBEIS Global Biosphere Emissi ons and Interactions System

GOES Geostationary Operati onal Environmental Satellite g/kW–hr Grams per Kilowatt Hour

GREASD Greatly Reduced Execution and Simplified Dynamics

GWEI Gulf-wide Emissions Inventory

HALC Aldine Monitor (CAMS 8)

HB House Bill

HCHV Channelview Monitor (CAMS 15/CAMS 115)
HCQA Croquet Monitor (CAMS 409)

HDDV Heavy-Duty Diesel Vehicle

HECT Highly Reactive Volatile Organic Compound Emissions Cap and Trade

H-GAC Houston-Galveston Area Council

HGB Houston-Galveston-Brazoria

HNWA Northwest Harris County Monitor (CAMS 26)

HO 2 Hydroperoxy Radical

HOEA Houston East Monitor (CAMS 1)

HONO Nitrous Acid hp Horsepower

HPMS Highway Performance Monitoring System

HRM Haden Road Monitor (CAMS 603)

xHROC TCEQ Houston Regional Office Monitor (CAMS 81)

HRVOC Highly Reactive Volatile Organic Compounds

HSMA Houston Monroe Monitor (CAMS 406)

HTCA Houston Texas Avenue Monitor (CAMS 411)

HYSPLIT Hybrid Single Particle Lagrangian Integrated Trajectory

I/M Inspection and Maintenance

IAF Ike Adjustment Factor

I-DOAS Imaging Differential Op tical Absorption Spectroscopy

IMO International Maritime Organization

IOLE Internal Olefins

ISOP Isoprene

JPL Jet Propulsion Laboratory

km Kilometer

K V Vertical Diffusivity Coefficient

kW Kilowatts

LDAR Leak Detection and Repair
LDEQ Louisiana Department of Environmental Quality

LEADS Leading Environmental Analysis and Display System

LIRAP Low Income Vehicle Repair Assistance, Retrofit, and Accelerated Vehicle Retirement Program

LULC Land-Use/Land-Cover

LYNF Lynchburg Ferry Monitor (CAMS 1015)

m/s Meters per Second

MACP Manvel Croix Park Monitor (CAMS 84)

MACT Maximum Achievable Control Technology

MARPOL Annex VI of the International Convention for the Prevention of Pollution from Ships

MCR Mid-Course Review

MECT Mass Emissions Cap and Trade

METDAT Omnibus Meteorological Database

MGO Marine Gas Oil

MM5 Fifth Generation Meteorological Model

MMS Minerals Management Services

MNB Mean Normalized Bias

MNGE Mean Normalized Gross Error

MOZART Model for Ozone and Related Chemical Tracers mph Miles per Hour

MVEB Motor Vehicle Emissions Budget

MW Megawatt
NAAQS National Ambient Air Quality Standard

NAM North American Model

NASA National Aeronautics and Space Administration

NCAR National Center for Atmospheric Research

NCEP National Center for Environmental Prediction

NEI National Emissions Inventory

xing/J Nanogram per Joule

NMIM National Mobile Inventory Model

NO Nitric Oxide

NO 2 Nitrogen Dioxide

NOAA National Oceanic and Atmospheric Administration

NO X Nitrogen Oxides

NO Y Total Reactive Nitrogen

NPL National Physical Laboratory

NSR New Source Review

NTIG New Technology Implementation Grants

O 3 Ozone

OGV Oceangoing Vessel

OH Hydroxyl Radical

OLE Olefins

OSAT Ozone Source Apportionment Technology

OSD Ozone Season Day

P3 The NOAA WP-3D Orion

PAMS Photochemical Assessment Monitoring Station

PAR Photosynthetically-Active Solar Radiation

PBL Planetary Boundary Layer

PEI Periodic Emissions Inventory

PFC Portable Fuel Container

PiG Plume-in-Grid

PM 2.5 Particulate Matter of 2.5 Microns and Less
ppb Parts per Billion ppbC Parts per Billion, Carbon

ppm Parts per Million

PPM Piecewise Parabolic Method psi Pounds per Square Inch

PUCT Public Utility Commission of Texas
QQ Quantile-Quantile

R 2 Correlation Coefficient

RACM Reasonably Available Control Measures

RACT Reasonably Available Control Technology

REMI Regional Economic Models, Inc.

rpm Revolutions per Minute

RFP Reasonable Further Progress

ROP Rate-of-Progress

RRF Relative Response Factor

RRF D Relative Response Factor Denominator

RRF N Relative Response Factor Numerator

RV Research Vessel

RVP Reid Vapor Pressure

xiiSB Senate Bill

SBFP Seabrook Friendship Park Monitor (CAMS 45)

SCR Selective Catalytic Reduction

SECO State Energy Conservation Office

SEER Seasonal Energy Efficiency Ratio

SEP Supplemental Environmental Project

SETPMTC Southeast Texas Photochemical Modeling Technical Committee

SGIA Smart Growth Implementation Assistance

SHARP Study of Houston Atmospheric Radical Precursors

SHWH Shell Westhollow Monitor (CAMS 410)

SI Special Inventory

SIP State Implementation Plan

SO 2 Sulfur Dioxide

SOF Solar Occultation Flux

SST Sea Surface Temperature

STARS State of Texas Air Reporting System

TAC Texas Administrative Code

TACB Texas Air Control Board

TAMU Texas A&M University

TCAA Texas Clean Air Act
TCEQ Texas Commission on Environmental Quality

TCM Transportation Control Measure

TDM Travel Demand Model

TERP Texas Emission Reduction Plan

TexAER Texas Air Emissions Repository
TexAQS 2000 Texas Air Quality Study 2000
TexAQS II Texas Air Quality Study 2006

TexN Texas NONROAD

THSC Texas Health and Safety Code

TKE Mellor-Yamada Turbulent Kinetic Energy

TNMHC Total Nonmethane Hydrocarbons

TNRCC Texas Natural Resource Conservation Commission

TOMS Total Ozone Mapping Spectrometer

TOPAZ Tunable Optical Profiler for Aerosol and oZone tpd Tons per Day

tpy Tons per Year

TSE Truck Stop Electrification

TTI Texas Transportation Institute

TXCT Texas City Monitor (CAMS 620)

TxLED Texas Low Emission Diesel

UH University of Houston

UPA Unpaired Peak Accuracy

USGS United States Geological Survey

UTC Coordinated Universal Time

xiiiUT-CSR University of Texas Center for Space Research

VMEP Voluntary Mobile Emission Reduction Program

VMT Vehicle Miles Traveled

VOC Volatile Organic Compounds

WALV Wallisville Monitor (CAMS 617)

WDIR Wind Direction

WoE Weight of Evidence

WSPD Wind Speed

xivTABLE OF CONTENTS

Executive Summary

List of Acronyms

Table of Contents

List of Appendices

List of Tables

List of Figures

Chapter 1: General 1.1 Background

1.2 Introduction 1.2.1 One-Hour Ozone National Ambient Air Quality Standard (NAAQS) History
1.2.1.1 December 2000 1.2.1.2 September 2001

1.2.1.3 December 2002

1.2.1.4 December 2004 1.2.1.5 EPA Approval of the One- Hour Ozone Attainment Demonstration 1.2.2 Eight-Hour Ozone NAAQS History 1.2.2.1 May 23, 2007 1.2.3 Existing Ozone Control Strategies 1.2.4 2010 Proposed Revision

1.3 Health Effects 1.4 Stakeholder Participation and Public Hearings 1.4.1 Local Program Control Strategy Development Meetings 1.4.2 TCEQ SIP and Control Strate gy Development Stakeholder Meetings 1.4.3 Public Hearings and Comment Information

1.5 Social and Economic Considerations 1.6 Fiscal and Manpower Resources

Chapter 2: Anthropogenic Emissions Inventory (EI) Description

2.1 Introduction 2.1.1 EI Improvement
2.2 Point Sources

2.3 Area Sources
2.4 Non-Road Mobile Sources

2.5 On-Road Mobile Sources

Chapter 3: Photochemical Modeling

3.1 Introduction 3.1.1 Overview of the Ozone Photochemical Modeling Process 3.1.2 Ozone Modeling 3.1.3 Base Case Modeling 3.1.4 Future Year Modeling 3.2 Episode Selection

xv3.2.1 EPA Guidance for Episode Selection 3.2.2 HGB Ozone Episode Selection Process 3.3 Meteorological Model 3.3.1 Modeling Domains 3.3.2 Model (MM5) Configuration 3.3.3 MM5 Application and Performance 3.4 Modeling Emissions 3.4.1 Biogenic Emissions

3.4.2 Base Cases
3.4.2.1 Point Sources

3.4.2.2 On-Road Mobile Sources

3.4.2.3 Non- and Off-Road Mobile Sources

3.4.2.4 Area Sources 3.4.2.5 Base Case Summary
3.4.3 2006 Baseline

3.4.3.1 Point Sources

3.4.3.2 On-Road Mobile Sources 3.4.4 2018 Future Base and Control Strategy

3.4.4.1 Point Sources
3.4.4.2 On-Road Mobile Sources

3.4.4.3 Non- and Off-Road Mobile Sources

3.4.4.4 Area Sources 3.4.5 2006 and 2018 Modeling Emissions Summary for HGB 3.5 Photochemical Modeling 3.5.1 Modeling Domains and Horizontal Grid Cell Size 3.5.2 Vertical Layer Structure 3.5.3 Model Configuration

3.5.4 Model Performance Evaluation

3.5.4.1 Performance Evaluations Overview 3.5.4.2 Operational Evaluations 3.5.4.3 Diagnostic Evaluations 3.6 Baseline (2006) and Future Case (2018) Modeling 3.6.1 2006 Baseline Modeling 3.6.2 Future Baseline Modeling 3.6.2.1 Matrix Modeling 3.6.2.2 Modeling Sensitivities: Emissions Reductions within 100 and 200 km
of HGB 3.6.2.3 Ozone Source Apportionment Tool and Anthropogenic Precursor Culpability Analysis 3.6.3 Future Case Modeling with Controls 3.6.3.1 25 Percent HECT Cap Reduction
3.6.3.2 VMEP Reductions 3.7 Modeling Archive and References 3.7.1 Modeling Archive 3.7.2 Modeling References

Chapter 4: Control Strategies and Required Elements

4.1 Introduction 4.2 Existing Control Measures 4.3 Updates to Existing Control Measures 4.3.1 Mass Emissions Cap and Trade (MECT) Program

xvi4.3.2 Repeal of State Portable Fuel Container Rule 4.3.3 Clean Fuel Fleet Requirement 4.4 Reasonably Available Control Technology (RACT) Analysis
4.4.1 General Discussion

4.4.2 NO X RACT Determination

4.4.3 VOC RACT Determination 4.4.3.1 CTG Documents That Are Not Applicable to the HGB Area

4.4.3.2 CTG Documents That Do Not Represent RACT for the HGB Area

4.4.3.3 CTG Documents That a RACT Determination Cannot Be Made at This

Time 4.4.3.4 CTG Documents That Represent RACT for the HGB Area 4.5 Reasonably Available Control Measures Analysis

4.5.1 General Discussion 4.5.2 Results of RACM Analysis
4.6 New Control Measures 4.6.1 Stationary Sources 4.6.1.1 HECT Cap Reduction and Allowance Reallocation 4.6.2 Local Programs 4.6.2.1 Transportation Control Measures 4.6.2.2 Voluntary Mobile Emission Reduction Programs 4.7 Motor Vehicle Emissions Budget (MVEB) 4.8 Monitoring Network 4.9 Contingency Plan

4.10 References

Chapter 5: Weight of Evidence 5.1 Quantitative Corroborative Analysis

5.1.1 Introduction 5.2 Corroborative Analysis: Modeling 5.2.1 Solving Modeling Problems 5.2.1.1 Industrial Point Source Emission Inventory Issues 5.2.1.2 Modeling of Emissions Events 5.2.1.3 Resolution of Photochemical Modeling Grids 5.2.1.4 Incommensurability and Model Performance Evaluation 5.2.1.5 Ensemble Modeling

5.2.1.6 Vertical Distribution of Ozone 5.2.1.7 Photolysis Discrepancies Due to Improper Placement of Clouds 5.2.1.8 Radical Shortage 5.2.2 Model Performance Evaluations: Implications of the Model Performance of the Current SIP Modeling 5.2.3 Model Response to Proposed Contro ls: Additional Ways to Measure Progress
5.2.4 Conclusion 5.3 Air Quality Trends in the HGB Area

5.3.1 Ozone Trends 5.3.2 Ozone Trends at Regulatory and Non-Regulatory Monitors 5.3.3 Trends in the Strength of Observed Ozone Gradients in the HGB Area 5.3.4 The Impact of Hurricane Ik e on Ozone Observations in the HGB Area 5.3.4.1 Approach

5.3.4.2 Results

5.3.5 NO X Trends

5.3.6 Ambient VOC Concentrations

xvii5.3.7 Geographic Patterns in Ambient HRVOC Concentrations Near the Houston Ship

Channel

5.3.8 Ambient Total VOC Concentrations 5.3.9 Meteorologically Adjusted Ozone Trends 5.3.10 Background Ozone Concentrations: Transport of Ozone into the HGB Area 5.3.11 Transport and Surface Wind Trajectories 5.3.12 Background Ozone in Texas 5.3.13 Air Quality Trends Conclusions 5.4 Qualitative Corroborative Analysis
5.4.1 Introduction 5.4.2 Federal Preemption Issues 5.4.2.1 Federal Assignment

5.4.3 Additional Measures

5.4.3.1 New International Marine Diesel Engine and Marine Fuel Standards for Oceangoing Vessels and Emissions Control Areas 5.4.3.2 SmartWay Transport Partnership and the Blue Skyways Collaborative

5.4.3.3 Control of VOC Emissions from Flash Emissions 5.4.3.4 Energy Efficiency and Renewable Energy (EE/RE) Measures 5.4.3.5 Clean Air Interstate Rule (CAIR) 5.4.3.6 Texas Emission Reduction Plan (TERP) 5.4.3.7 Low Income Vehicle Repair Assistance, Retrofit, and Accelerated Vehicle Retirement Program (LIRAP) 5.4.3.8 Clean School Bus Program

5.4.3.9 81 st Texas Legislature, 2009 5.4.3.10 American Waterways Operators Tank Barge Emissions Best Management Practices 5.4.3.11 Local Initiative Projects 5.4.3.12 Other Local Programs

5.5 Conclusions

5.6 References

Chapter 6: Ongoing and Future Initiatives

6.1 Introduction 6.2 Ongoing Work

6.2.1 Flare Task Force 6.2.2 Technologies for Detecting VOC 6.2.2.1 Optical Gas Imaging Technology 6.2.2.2 Open Path Sensing Technology 6.2.2.3 DIAL Remote Sensing Technology 6.2.2.4 Helicopter-Mounted DIAL Imaging System 6.2.2.5 Flare Study 6.2.2.6 Study of Houston Atmospheric Radical Precursors (SHARP)

6.3 Future Initiatives 6.3.1 Mid-Course Review (MCR) 6.3.2 2008 Ozone National Ambient Air Quality Standard (NAAQS)

Appendices

xviiiLIST OF APPENDICES

Appendix Appendix Name

Appendix A Meteorological Modeling for the HGB Attainment Demonstration SIP

Appendix B Emissions Modeling for th e HGB Attainment Demonstration SIP

Appendix C CAMx Modeling for the HGB Attainment Demonstration SIP

Appendix D Reasonably Available Control Technology Analysis

Appendix E Reasonably Available Control Measure Analysis

Appendix F Evaluation of Mobile Sour ce Control Strategies for the HoustonGalveston-Brazoria State Implementation Plan (With Detailed Strategies), Prepared for Houston-Galveston Area Council, Prepared by ENVIRON International Corporation

Appendix G Transportation Control Measures for the HGB Attainment Demonstration SIP Revision for the 1997 Eight-Hour Ozone Standard (Excerpt from Evaluation of Mobile Source Control Strategies for the Houston-Galveston-Brazoria State Implementation Plan)

Appendix H Voluntary Mobile Emission Reduction Program for the HGB Attainment Demonstration SIP Revision for the 1997 Eight-Hour Ozone Standard (Excerpt from Evaluation of Mobile Source Control Strategies for the Houston-Galveston-Brazoria State Implementation Plan)

Appendix I Corroborative Analysis for th e HGB Attainment Demonstration SIP

Appendix J Recommendations for Best Ma nagement Practices to Control and Reduce Inadvertent Cargo Vapor Emissions in the Tank Barge Community

xixLIST OF TABLES

Number Table Name

Table 1-1 Proposed Rule Revisions

Table 1-2 H-GAC Public and Stakeholder Meeting Dates

Table 3-1 Selected Episodes

Table 3-2 Eight-Hour Ozone Design Values and Number of Exceedance Days During Selected Episodes

Table 3-3 Selected MM5 Modeling Schemes

Table 3-4 2005 and 2006 Meteorological Modeling Episodes

Table 3-5 Average HGB Percent Accuracy for all Meteorological Modeling Episodes

Table 3-6 EPS3 Emissions Processing Modules

Table 3-7 2005 and 2006 Episode Days for Emissions Modeling

Table 3-8 2005 and 2006 Base Case Episode Point Source Modeling Emissions for HGB

Table 3-9 Summary of the Development of On-Road Mobile Sources Emissions

Table 3-10 2005 and 2006 Base Case Epis ode On-Road Modeling Emissions for HGB

Table 3-11 2005 and 2006 Base Case Episode Non- and Off-Road Modeling Emissions for

HGB

Table 3-12 2005 and 2006 Base Case Episode Anthr opogenic Modeling Emissions for HGB

Table 3-13 Summary of 2006 Baseline and 201 8 Future Base, and 2018 Control Strategy Anthropogenic Modeling Emissions for HGB

Table 3-14 CAMx Vertical Layer Structure for 2 km and 4 km Fine Grids

Table 3-15 CAMx Vertical Layer Struct ure for Intermediate and Coarse Grids

Table 3-16 2000 Baseline Design Value Calculation for Retrospective Analysis

Table 3-17 2000 Projected DVs Compared with Calculated DVs

Table 3-18 2006 DV B , RRF Denominator (RRF D ), and Number of 2006 Baseline Modeled Days Averaged

Table 3-19 Summary of 2006 Baseline M odeling, RRF, and Future Design Values

Table 3-20 VOC, NO X , and VOC+NO X Emissions Reductions Needed to Model Attainment

xxTable 3-21 200 km NO X Reduction Modeling Sensitivity

Table 3-22 200 km VOC Reduc tion Modeling Sensitivity

Table 3-23 OSAT/APCA Source Groups and Regions Defined

Table 3-24 HECT Modeling Sensitivity Results

Table 3-25 HECT and VMEP Modeling Sensitivity Results

Table 4-1 Existing Ozone Control Measures Applicable to the HGB Eight-County

Nonattainment Area

Table 4-2 2018 Attainment Demonstration MVEB for the Eight-County HGB Area

Table 4-3 2019 Contingency Demonstration for the HGB Area

Table 5-1 Changes in the Area and Population Affected by an Eight-Hour Ozone Design Value Greater than or Equal to 85 ppb in Response to Growth and Controls

Table 5-2 Eight-Hour Ozone Design Values (in ppb) for Each Regulatory Monitor in the

HGB Area

Table 5-3 One-Hour Ozone Design Values (in ppb) for Each Regulatory Monitor in the

HGB Area

Table 5-4 Number of Days with a 1997 Eight-Hour Ozone Exceedance

Table 5-5 Number of Days with a One-Hour Ozone Exceedance

Table 5-6 Eight-Hour Ozone Design Values at Regulatory and Non-Regulatory Monitors

Table 5-7 One-Hour Ozone Design Values at Regulatory and Non-Regulatory Monitors

Table 5-8 Exceedance Days at Regulatory a nd Non-Regulatory Mon itors, 2003 through

2008

Table 5-9 Monitors Recording the Annual Maximum One-Hour Ozone Design Value

Table 5-10 List of the Number of Days HGB Ozone Regulatory and Non-Regulatory Monitors were Not Operating Before and After the Landfall of Hurricane Ike

Table 5-11 Alternative Fourth-High Daily Peak Eight-Hour Ozone Concentration Calculations Using Different Ike Adjustment Factors (IAFs)

Table 5-12 Observed and Expected Design Va lues, Recalculated to Account for Hurricane

Ike

Table 5-13 NO X Values in the HGB Area by Year

xxiTable 5-14 Median and 90 th Percentile Hourly NO X Values

Table 5-15 Auto-GC Monitors in the Houston Ship Channel Area

Table 5-16 Parameter Estimates of Monthl y Geometric Mean Concentrations Trends

Table 5-17 Geometric Mean Ethylene for Ke y Wind Direction Lobes at Eastern Houston Ship Channel Monitors

Table 5-18 Geometric Mean Propylene Concentr ations for Key Wind Directions at Eastern Houston Ship Channel Monitors

Table 5-19 Parameter Estimates of Mont hly Geometric Mean TNMHC Concentration Trends Houston Ship Channel Area Auto-GC Monitors

Table 5-20 Area Ozone Monitoring Sites with Long-Term Data

Table 5-21 Summary Statistics for Meteorol ogically Adjusted Ozone Trends from 1996 to

2007

Table 5-22 Ozone Statistics for HYSPLIT Back Trajectory Clusters

Table 5-23 Average Maximum Ozone and 95 Percent Confidence Intervals

Table 5-24 Monitors Selected for Background Transport Analysis

Table 5-25 Range of Monthly 90 th Percentile Daily Peak Hourly Ozone Concentrations for Subject Wind Directions

Table 5-26 Parameter Estimates for Regression of West Orange C9 on Mauriceville

C642/C311/C665

Table 5-27 New MARPOL Annex VI Emissi on Standards for Marine Diesel Engines

xxiiLIST OF FIGURES

Figure Figure Name

Figure 1-1 One-Hour and 1997 Eight-Hour Oz one Design Values and HGB Area Population

Figure 3-1 Baseline Design Value Calculation Illustration

Figure 3-2 Eight-Hour Ozone Exceedance Days in HGB and Other Areas of Texas

Figure 3-3 Hourly Average Resultant Winds; Eight-Hour Exceedance Days, August through September 1998 through 2006

Figure 3-4 2005 and 2006 Non-TexAQS II Modeling Episodes

Figure 3-5 2006 TexAQS II Modeling Episodes

Figure 3-6 Map Depicting Regulatory Monitors in the HGB Area

Figure 3-7 MM5 Modeling Domains

Figure 3-8 Meteorological Modeling Performance

Figure 3-9 An Example of Day-Specific Biogenic Emissions

Figure 3-10 2006 Baseline and 2018 Future Base, and 2018 Control Strategy Anthropogenic

NO X and VOC Modeling Emissions for HGB

Figure 3-11 CAMx Modeling Domains

Figure 3-12.a Peak Eight-Hour Ozone Concentration, Measured versus Modeled for the 2005 Episode Days

Figure 3-12.b Peak Eight-Hour Ozone Concentr ation, Measured versus Modeled for the 2006 Episode Days

Figure 3-13.a Mean Normalized Gross Error (MNGE) and Bias (MNB) for 2005 Episode Days

Figure 3-13.b Mean Normalized Gross Error (MNGE) and Bias (MNB) for 2006 Episode Days

Figure 3-14 TexAQS II Monitoring Sites Outside HGB/BPA

Figure 3-15 Time Series of Hourly Ozone Con centrations for Episode bc05ep0 at the CNR2, HNWA, and WALV Monitors

Figure 3-16 Time Series of Hourly Ozone Con centrations for Episode bc05ep0 at the GRVL

and LACT Rural Monitors

Figure 3-17 Scatter Plots of Hourly Ozone, NO X , ETH, and OLE at the WALV Monitor for the bc05ep0 Episode

xxiiiFigure 3-18 Tile Plots of Daily Maximu m Eight-Hour Ozone Concentrations for May 27 and 31 and June 1 through 2, 2005

Figure 3-19 Time Series of Hourly Ozone Con centrations for Episode bc05ep1 at the DRPK, HCQA, and MACP Monitors

Figure 3-20 Time Series of Hourly Ozone Con centrations for Episode bc05ep1 at the GRVL

and LACT Rural Monitors

Figure 3-21 Scatter Plots of Hourly Ozone, NO X , ETH, and OLE at the DRPK Monitor for the bc05ep1 Episode

Figure 3-22 Tile Plots of Daily Maximu m Eight-Hour Ozone Concentrations for June 20 through 23, 2005

Figure 3-23 Time Series of Hourly Ozone Con centrations for Episode bc05ep2 at the BAYP, HROC, and TXCT Monitors

Figure 3-24 Time Series of Hourly Ozone Con centrations for Episode bc05ep2 at the GRVL, LACT, and SAGA Rural Monitors

Figure 3-25 Scatter Plots of Hourly Ozone, NO X , ETH, and OLE at the TXCT Monitor for the bc05ep2 Episode

Figure 3-26 Tile Plot of Daily Maximum Eight-Hour Ozone Concentrations for July 28, August 1 through 2, and August 4, 2005

Figure 3-27 Time Series of Hourly Ozone Con centrations for Episode bc06ep0 at the HROC, SHWH, and WALV Monitors

Figure 3-28 Time Series of Hourly Ozone Con centrations for Episode bc06ep0 at the GRVL, LACT, and SAGA Rural Monitors

Figure 3-29 Scatter Plots of Hourly Ozone, NO X , ETH, and OLE at the WALV Monitor for the bc06ep0 Episode

Figure 3-30 Tile Plot of Daily Maximum Eight-Hour Ozone Concentrations for June 5, 8 through 9, and 14, 2006

Figure 3-31 Time Series of Hourly Ozone Con centrations for Episode bc06aqs1 at the BAYP, DRPK, and HSMA Monitors

Figure 3-32 Time Series of Hourly Ozone Con centrations for Episode bc06aqs1 at the GRVL, LACT, and SAGA Rural Monitors

Figure 3-33 Scatter Plots of Hourly Ozone, NO X , ETH, and OLE at the DRPK Monitor for the bc06aqs1 Episode

Figure 3-34 Tile Plot of Daily Maximum Eight-Hour Ozone Concentrations for August 17 and 31, and September 1 and 7, 2006

xxivFigure 3-35 Time Series of Hourly Ozone Con centrations for Episode bc06aqs2 at the CNR2, DRPK, and GALC Monitors

Figure 3-36 Time Series of Hourly Ozone Con centrations for Episode bc06aqs2 at the GRVL, LACT, and SAGA Rural Monitors

Figure 3-37 Scatter Plots of Hourly Ozone, NO X , ETH, and OLE at the DRPK Monitor for the bc06aqs2 Episode

Figure 3-38 Tile Plot of Daily Maximum Eight -Hour Ozone Concentrations for September 20 and 27, and October 6 and 11, 2006

Figure 3-39 Comparison of Modeled and P3 Observed Ozone (O 3 ), August 31, 2006, 14:16 to

15:33 CST

Figure 3-40 TOPAZ-Observed and Modeled Ozone Concentrations on August 31, 2006

Figure 3-41 Comparison of Ozone Concentra tions Observed by the RV Ron Brown with Modeled Concentrations, August 31, 2006, 08:00 to 16:30

Figure 3-42 Comparison of Modeled and Obser ved Vertical Ozone Profiles from Two Sonde Launches at UH Campus and One Sonde Launch from the Ron Brown in the Gulf of Mexico, August 31, 2006

Figure 3-43 Comparison of P3 Measurements with Base Case and Enhanced Flare Emissions; observed ethylene (Panel A), formaldehyde (Panel B), and ozone (Panel C) compared to modeled concentrations us ing (left) the base case inventory, and (right) the base case inventory with 10X flare VOC emissions, minus the

HRVOC reconciliation

Figure 3-44 Log-Log Plots of Observed vs. M odeled Ethylene at Deer Park September 19 through October 11, 2006; with (Left) base case inventory, and (Right) base case inventory with 10X flare emissi ons minus the HRVOC reconciliation

Figure 3-45 Daily Peak Modeled Eight-Hour Ozone Concentrations with Base Case Inventory (Left) and 10X Flare Inventory (Center); the difference between the two plots (Flare 10X – Reg 10) is shown at right

Figure 3-46 Mean Observed NO X Concentrations at HGB Monitors as a Percentage of Wednesday Mean Values, May 15 through October 15, 2005 through 2008

Figure 3-47 Observed and Modeled Daily P eak Eight-Hour Ozone Concentrations as a Percentage of Wednesdays

Figure 3-48 Near Monitoring Site Grid Cell Array Size

Figure 3-49 DV F versus NO X and/or VOC Emissions Reduction Response Curves for the BAYP, DRPK, and WALV Monitors

Figure 3-50 Map of Counties within 100 km (R ed) and 200 km (Orange) of the Eight-County

HGB Area

xxvFigure 3-51 OSAT and APCA Results for BAYP

Figure 3-52 OSAT and APCA Results for DRPK

Figure 3-53 OSAT and APCA Results for WALV

Figure 5-1 Ozone Design Values for the HGB Area

Figure 5-2 Eight-Hour Ozone Design Value Sta tistics for All Monitors in the HGB Area

Figure 5-3 One-Hour Ozone Design Value Sta tistics for All Monitors in the HGB Area

Figure 5-4 Number of Monitors and Ozone Exceedance Days in the HGB Area

Figure 5-5 Number of 1997 Eight-Hour Ozone Exceedance Days by Monitor

Figure 5-6 Number of One-Hour Ozone Exceedance Days by Monitor

Figure 5-7 1997 Eight-Hour Ozone Exceedance Days in the HGB Area

Figure 5-8 Distributions of Eight-Hour Oz one Design Values at Regulatory and NonRegulatory Monitors in the HGB Area

Figure 5-9 Distributions of One-Hour Ozone Design Values at Regulatory and NonRegulatory Monitors in the HGB Area

Figure 5-10 1997 Eight-Hour Ozone Exceedance Days at Regulatory and Non-Regulatory Monitors, 2003 through 2008

Figure 5-11 One-Hour Ozone Exceedance Days at Regulatory and Non- Regulatory Monitors, 2003 through 2008

Figure 5-12 Eight-Hour Ozone Design Values for 2000, 2005, and 2008

Figure 5-13 Time of Day of Peak Hour ly Ozone on Low and High Ozone Days

Figure 5-14 Trends in the Strength of Ozone Gradients Measured in the HGB Area from 1995 through 2008

Figure 5-15 The Number of Occurrences of One-Hour Increases in Ozone Greater Than 40 ppb/hr in the HGB Area for the Subset of Monitors with Long Historical Records

Figure 5-16 Number of Days that Exceeded the 1997 Eight-Hour Ozone NAAQS by Month from 2000 through 2008

Figure 5-17 Frequency of Daily Peak Eight-Hour Ozone Values for All Ozone Monitoring Sites in Texas, September 2006

Figure 5-18 Frequency of Daily Peak Eight-Hour Ozone Values for All Ozone Monitoring Sites in Texas, September 2008

xxviFigure 5-19 Daily Peak Hourly NO X in the HGB Area

Figure 5-20: Median NO X Concentrations in the HGB Area

Figure 5-21 Houston Ship Channel Auto-GC Monitors and 2006 Reported Point Source

HRVOC Emissions Points and Plant Boundaries

Figure 5-22 Monthly Geometric Mean Ethylene Concentrations at the Eight Houston Ship Channel Monitors, July 1995 through December 2008

Figure 5-23 Monthly Geometric Mean Propylene Concentrations at the Eight Houston Ship Channel Monitors, July 1995 through December 2008

Figure 5-24 Geometric Mean Ethylene Concen tration at Western Houston Ship Channel

Monitors

Figure 5-25 Geometric Mean Ethylene Concen trations at Eastern Houston Ship Channel

Monitors

Figure 5-26 Geometric Mean Propylene Concen tration at Eastern Houston Ship Channel

Monitors

Figure 5-27 Geometric Mean Propylene Concen tration at Western Houston Ship Channel

Monitors

Figure 5-28 Monthly Geometric Mean TNMHC Concentrations, July 1995 through

December 2008

Figure 5-29 90 th Percentile TNMHC Concentration in the HGB Area

Figure 5-30 Actual Mean Eight-Hour Ozone C oncentrations (Blue Line) and Mean EightHour Predicted Concentrations with the Non-Meteorological Trend Removed (Red Line)

Figure 5-31 Residual Meteorologically Adjusted Eight-Hour Ozone Concentrations Trend

Figure 5-32 Six Clusters Found Using HYSPLIT Backward Trajectory Clustering Algorithm

Figure 5-33 Cluster 0 Backward Trajectories

Figure 5-34 Means of Six 60-Hour Backward Trajectory Clusters

Figure 5-35 Sites Used in Ozone Area Maximum and Background Determination

Figure 5-36 Average Maximum Ozone and 95 Percent Confidence Intervals

Figure 5-37 Relationship Between Minimu m and Maximum Ozone Concentrations

Figure 5-38 Distributions of End Points from HYSPLIT 48-Hour Back Trajectories

xxviixxviii Figure 5-39 Mauriceville C642/C311/C65 and West Orange C9/A141 Monitors

Figure 5-40 Karnack C85 Monitor

Figure 5-41 Hamshire C64/C654 Monitor

Figure 5-42 Selected Statistics for the West Orange C9 Monitor

Figure 5-43 Selected Statistics for the Mauriceville C642/C311/C665 Monitor

Figure 5-44 Selected Statistics for the Karnack C85 Monitor

Figure 5-45 Selected Statistics for the Hamshire C64/C654 Monitor

Figure 5-46 Scatter-plot of 90 th Percentile Hourly Values at West Orange C9 and

Mauriceville C642/C311/C61-1 CHAPTER 1: GENERAL

1.1 BACKGROUND The “History of the Texas State Implementation Plan (SIP),” a comprehensive overview of the SIP revisions submitted to the United States Environmental Protection Agency (EPA) by the State of Texas, is available at the following Web site: http://www.tceq.state.tx.us/implementation/air/sip/sipintro.html#History

.

1.2 INTRODUCTION The Houston-Galveston-Brazoria (HGB) area’s hot , sunny climate, large urban population activities, and extensive, highly concentrated indus trial complex provide the ingredients for ozone formation: sunlight, nitrogen oxides (NO X ), and volatile organic compounds (VOC). The Houston area’s significant biogenic VOC emissions and complex meteorology, which includes land/sea breeze air parcel recirculation, complicate air quality modeling. Economic and population growth continue to create air quality challenges for the HGB area. However, key ozone-targeting regulatory progr ams have reduced the number and magnitude of ozone exceedances, the area of exceedance, and the population exposed to exceedances.

1.2.1 One-Hour Ozone National Ambient Air Quality Standard (NAAQS) History The EPA established the one-hour ozone NAAQS of 0.08 parts per million (ppm) in the April 30, 1971, issue of the Federal Register (36 FR 8186). The EPA revise d the one-hour ozone standard to 0.12 ppm in the February 8, 1979, issue of the Federal Register(44 FR 4202). The eightcounty HGB area, defined as Brazoria, Chambers , Fort Bend, Galveston, Harris, Liberty, Montgomery, and Waller Counties, was first designated as a nonattainment area for the one-hour ozone NAAQS established by the Federal Clean Ai r Act (FCAA) in the November 6, 1991, issue

of the Federal Register (56 FR 56694). The HGB area was classified as a Severe-17 nonattainment area, which required it to attain the one-hour ozone NAAQS by November 15, 2007. The one-hour ozone NAAQS was revoked in the June 15, 2005, issue of the Federal Register (69 FR 23951).

The following summaries of HGB area one-hour ozon e SIP revisions are provided to give context and greater understanding of the complex issu es involved in HGB’s ozone challenge. For a summary of ozone SIP revisions in the HGB area prior to December 2000, please refer to the “History of the Texas State Implementation Plan (SIP ),” mentioned in Section 1.1 of this chapter.

1.2.1.1 December 2000 The Post-1999 Rate-of-Progress (ROP) and Attainment Demonstration SIP for the

Houston/Galveston Ozone Nonattainment Area revision contained rules and photochemical modeling analyses in support of the HGB one-hour ozone attainment demonstration. The majority of the emission reductions identified in this revision resulted from an overall 90 percent reduction in point source NO X implemented through 30 Texas Administrative Code (TAC) Chapter 117 and the Mass Emissions Cap and Trad e (MECT) program in 30 TAC Chapter 101. A modeling analysis, which showed a 141 parts pe r billion (ppb) peak ozone level, indicated a shortfall of 91 tons per day (tpd) in NO X emissions reductions that were necessary, but not readily available, for an approvable attainment demonstra tion. In addition, the revision contained a post1999 ROP plan for the milestone years 2002 and 2005, as well as the attainment year 2007, and transportation conformity motor vehi cle emissions budgets (MVEBs) for NO X and VOC. The SIP revision also contained enforceable commitments to implement further measures (in support

of the HGB area’s attainment demonstration a nd to remedy the estimated 91 tpd shortfall), Voluntary Mobile Emission Reduction Program (VMEP) measures, as well as a commitment to perform and submit a mid-course review (MCR) to the EPA.1-2 1.2.1.2 September 2001

The 

### Post-1999 ROP and Attainment Demonstration Follow-Up SIP for the
Houston/Galveston Ozone Nonattainment Area revision included the following elements: 1) corrections to the ROP table/budget for the years 2002, 2005, and 2007 due to a mathematical error; 2) incorporation of a change to the idling restriction control strategy, which clarified that the operator of a rented or leased vehicle is r esponsible for compliance with the requirements in situations where the operator of a leased or rented vehicle is not employed by the owner of the vehicle; 3) incorporation of revisions to the clean diesel fuel rules to provide greater flexibility in complying with the rule requirements while preserving the emission reductions previously represented; 4) incorporation of a stationary diesel engine rule; 5) incorporation of revisions to the point source NO X rules; 6) incorporation of revisions to the NO X emissions cap and trade rules; 7) removal of the construction equipment operating restriction and the accelerated purchase requirement for Tier 2/Tier 3 heavy-duty equipment; 8) replacement of the Tier 2/Tier 3 rules with the Texas Emission Reduction Plan (TERP); 9) layout of the MCR process that detailed how the state would fulfill the commitment to obtain the additional emission reductions necessary to demonstrate attainment of the one-hour ozone standard in the HGB area; and 10) replacement of

the 2007 ROP MVEB to be consistent w ith the attainment demonstration MVEB.

Despite the NO X measures adopted in the December 2000 SIP revision and the stationary diesel engine rules included in the September 2001 SIP revision, an estimated 56 tpd NO X reduction shortfall remained. The state committed to address the remaining shortfall through the MCR process. The EPA approved the December 2000 and September 2001 submittals in the November 14, 2001, issue of the Federal Register (66 FR 57160).

1.2.1.3 December 2002 In January 2001, the Business Coalition for Clean Air-Appeal Group (BCCA-AG) and several regulated companies challenged the December 2000 HGB SIP revision and the 90 percent NO X reduction requirement from stationary sources. Among other things, BCCA-AG contended that the last 10 percent of the NO X emissions reductions were not co st effective and that the ozone plan would fail because the Texas Commissi on on Environmental Quality (TCEQ) did not account for VOC emissions associated with upset co nditions. In May 2001, the parties agreed to a stay in the case, and Judge Margaret Cooper, Travis County District Court, signed a Consent Order, effective June 8, 2001. The order require d the commission to perform an independent and thorough analysis of the causes of rapid ozone formation events and to identify potential mitigating measures not yet included in the HGB attainment demonstration.

In compliance with the Consent Order, the comm ission conducted a scientific evaluation based in large part on aircraft data collected by the Texas Air Quality Study 2000 (TexAQS 2000). The TexAQS 2000 was a comprehensive research proj ect, conducted in August and September 2000, involving more than 40 research organizations a nd over 200 scientists that studied ground-level ozone air pollution in the HGB and east Texas re gions. These and other studies suggested that the HGB area’s high ozone events can be attributed, in part, to the presence of significant reactivity in the airshed. An analysis of auto mated gas chromatograph data revealed that four highly reactive volatile organic compounds (HRVOC ) were frequently responsible for high reactivity days: ethylene, propylene, 1,3-butadiene, and butenes. As such, these compounds

were selected as the best candidates for HRVOC emission controls. Analysis showed that the ozone control strategy involving limits on emissi ons of ethylene, propylene, 1,3-butadiene, and butenes from industrial sources, in conjunction with an 80 percent reduction in industrial or point

source NO X , was equivalent or better in terms of ai r quality benefit than the previous ozone control strategy (a 90 percent point source NO X emissions reduction requirement alone). Therefore, in December 2002, the TCEQ adopted a SIP revision that replaced 10 percent of industrial point source NO X emissions reductions with industrial source HRVOC controls. HRVOC is defined in 30 TAC Chapter 115 as ethylene, propylene, 1,3-butadiene, and all isomers of butene for Harris County and ethylene and propylene for the other seven counties in the HGB area. The result was an industrial source ozone control strategy that relies on an 80 percent1-3 reduction in NO X emissions through Chapter 117 and the MECT program, and HRVOC rules in Chapter 115 that better quantify and reduce em issions of HRVOC from four key industrial sources: fugitives, flares, process vents, and cooling tower heat exchange systems. The HRVOC fugitive emission controls are more stringent leak detection and repair requirements for components in HRVOC service such as valves and fl anges. The HRVOC rules for flares, process vents, and cooling tower heat exchange systems are performance-based and emphasize monitoring, recordkeeping, reporting, and enfor cement, rather than establishing individual unit emission rates. Site-wide HRVOC emission caps were established and adopted in the SIP for sites subject to the HRVOC rules for flares, pr ocess vents, and cooling tower heat exchange systems. The December 2002 SIP revision excha nging the two strategies for the one strategy met the FCAA, §110(l) requirement, which allows a re vision of the SIP where that revision would not interfere with reasonable further progr ess toward attainment of the NAAQS.

1.2.1.4 December 2004 As previously noted in Section 1.2.1.1 of this chapter, in December 2000, the TCEQ committed to perform an MCR to ensure attainment of the one-hour ozone standard. The MCR process provided the opportunity to update emissions inve ntory data, use current modeling tools, and enhance the photochemical grid modeling. The data gathered from the TexAQS 2000 was used to improve the photochemical modeling of the HGB area. These technical improvements provided a more comprehensive understanding of th e ozone challenge in the HGB area that is necessary to develop an attainment plan. In early 2003, as the TCEQ was preparing to moveforward with the MCR, the EPA announced its plans to begin implementation of the 1997 eighthour ozone standard. The EPA published its proposed implemen tation rule for the 1997 eighthour ozone standard in the June 2, 2003, issue of the Federal Register (68 FR 32802). In the same timeframe, the EPA formalized its inten tions to designate areas for the 1997 eight-hour ozone standard by April 15, 2004, requiring states to reassess their efforts and control strategies to address this new standard in a revised plan to be submitted to the EPA by June 2007. Recognizing that existing one-hour nonattainment areas would soon be subject to the 1997 eighthour ozone standard and in an effort to efficien tly manage the state’s limited resources, the TCEQ developed an approach that addressed the outstanding obligations under the one-hour ozone standard while beginning to analyze eight-hour ozone issues.

The TCEQ’s one-hour ozone SIP revision commitmen ts that were addressed in the December

2004 HGB Ozone Nonattainment Area SIP revision include: completion of a one-hour ozone MCR; performance of modeling; adoption of m easures sufficient to fill the shortfall of NO X reductions; adoption of measures sufficient to de monstrate attainment; revision of the MVEB using the EPA’s MOBILE6 model; and revision of the VMEP measures.

The December 2004 revision reflected a shift from primarily reducing industrial emissions of

NO X to reducing both industrial emissions of NO X and industrial point source HRVOC. This revision included measures to ensure compliance wi th the specific strategies to control HRVOC emissions and replaced the site-wide caps adopt ed in the SIP with the HRVOC Emissions Cap and Trade (HECT) program in 30 TAC Chapter 101. The HECT program is an annual cap and trade program developed to provide sources co mpliance flexibility in meeting the control requirements for flares, process vents, and coo ling tower heat exchange systems in 30 TAC Chapter 115. Sites subject to the program are required to possess an HRVOC allowance for each ton of HRVOC emissions. Sites have the opti on to trade excess HRVOC allowances on the open
market. The December 2004 SIP revision also re flected the repeal of the motor vehicle idling rules and modified certain recordkeeping requi rements of the general VOC fugitive emission rules to make them apply only to sources of HRVOC fugitive emissions.

1.2.1.5 EPA Approval of the One-Hour Ozone Attainment Demonstration The EPA published its approval of the HGB nonattainment area one-hour ozone attainment demonstration in the September 6, 2006, issue of the Federal Register (71 FR 52656). Also in a separate action, the EPA concurrently approved rules for the control of HRVOC, the HECT program, the MECT program, and the emissions reduction credit banking and trading program,1-4 and conditionally approved rules for the discret e emissions reduction credit banking and trading

program.

1.2.2 Eight-Hour Ozone NAAQS History In 1997, the EPA revised the h ealth-based NAAQS for ozone, setting it at 0.08 ppm averaged over an eight-hour time frame. The final 1997 eight-hour ozone NAAQS was published in the Federal Register on July 18, 1997 (62 FR 38856), and became effective on September 16, 1997. On April 30, 2004, the EPA finalized its attain ment/nonattainment designations and promulgated the first phase of its implementation rule for the 1997 eight-hour ozone standard (69 FR 23951). These actions became effective on June 15, 2004. The EPA classified the HGB area as a

moderate nonattainment area for the standard under the 1990 FCAA (42 United States Code, §§ 7401 et seq .). The TCEQ was required to submit a SIP revision for the 1997 eight-hour ozone NAAQS to the EPA by June 15, 2007, and demonstr ate attainment of the standard by June 15, 2010. In the November 29, 2005, issue of the Federal Register (70 FR 71612) the EPA published its second phase of the implementation rule for the 1997 eight-hour ozone NAAQS, which addressed the control obligations that apply to areas designated nonattainment for the standard.

The commission adopted the 1997 eight-hour ozone nonattainment area SIP revision and the reasonable further progress SIP revision for the HGB area on May 23, 2007. These SIP revisions were the first step in addressing the 1997 eight- hour ozone standard in the HGB area. The TCEQ demonstrated reasonable further progress toward attaining the 1997 eight-hour ozone standard and committed to attaining the 1997 standard as e xpeditiously as practicable and developing an HGB 1997 eight-hour ozone attainment demonstration SIP revision.

On June 15, 2007, these two revisions to the Te xas SIP and a letter from the governor of Texas requesting that the HGB ozone nonattainment area be reclassified from a moderate nonattainment

area to a severe nonattainment area were submitted to the EPA. The EPA granted the governor’s request to voluntarily reclassify the HGB ozone nonattainment area from a moderate to a severe nonattainment area for the 1997 ozone NAAQS in the October 1, 2008, issue of the Federal Register (73 FR 56983). The EPA set April 15, 2010, as the date for the state to submit a revised SIP addressing the severe ozone nonattainment area requirements of the FCAA. The area’s new attainment date for the 1997 eight-hour ozone sta ndard is as expeditiously as practicable but no later than June 15, 2019.

1.2.2.1 May 23, 2007 On May 23, 2007, the commission adopted th e HGB 1997 Eight-Hour Ozone Nonattainment
Area SIP revision. This SIP revision containe d the reasonably available control technology (RACT) analysis, additional VMEP commitments, and the Texas 2002 Periodic Emissions Inventory for the HGB Ozone Nonattainment Area. This SIP revision also included rule revisions to 30 TAC Chapter 114 to add marine di esel fuels to the definition of diesel fuels that are subject to the Texas Low Emission Diesel Rule and to 30 TAC Chapter 115 to control underestimated, unreported, or underreported VOC emissions from tank landings, flash emissions, and degassing of storage tanks, transport vessels, and marine vessels with liquid heels. In an associated rulemaking project, 30 TAC Ch apter 117 was reformatte d and the 10 nanogram per Joule (ng/J) heat input NO X standard for residential water h eaters was repealed in accordance with House Bill (HB) 965, 79th Texas Legislatur e, 2005. The emission standard of 40 ng/J NO X was retained.

This revision also described ongoing efforts to develop the eight-hour ozone attainment demonstration including a new modeling episode using days from 2005 and 2006, the continued implementation of increasingly lower federal on-road and non-road engine standards, and further

research and consideration of additional control strategies.

The HGB 1997 Eight-Hour Ozone Nonattainment Area Reasonable Further Progress SIP revision, also adopted by the commission on Ma y 23, 2007, demonstrates that the reasonable further progress 15 percent reduction requirement w ould be met for the analysis period of 2002 -2008. Demonstration of reasonable further pr ogress is based on the guidelines in the second phase of the EPA’s 1997 eight-hour ozone implementation rule. On April 22, 2009, the EPA published a direct final approval of the reasona ble further progress SIP revision, its associated MVEBs, and the 2002 base year em issions inventory (74 FR 18298).

1.2.3 Existing Ozone Control Strategies Existing ozone control strategies and VM EP measures, discussed in Chapter 4, Control Strategies and Required Elements , Section 4.2, Existing Control Measures show key control strategies for complying with both the one-hour and eight-hour ozone NAAQS in the HGB nonattainment area. Existing control strategies targeted to the one-hour standard are expected to continue to reduce emissions of ozone precursors in the HGB area and positively impact progress toward attainment of the 1997 eight-hour ozone standard. The one-hour and 1997 eight-hour ozone design values for the HGB area from 1991 to 2008 are illustrated in Figure 1-1: One-Hour and 1997 EightHour Ozone Design Values and HGB Area Population. Both design values have decreased over the past 18 years. The 2008 one-hour ozone desi gn value was 147 ppb, representing a 33 percent decrease from the value for 1991 (220 ppb). The 2008 eight-hour ozone design value was 91 ppb, a 24 percent decrease from the 1991 value of 119 ppb. These decreases occurred despite a 47 percent increase in area population, as shown in the Figure 1-1: One-Hour and 1997 EightHour Ozone Design Values and HGB Area Population

.

1-5 220 210 200 202

189 188 199 196 203 199

119 116
104 110 114 116 116 112 110 107 102 101 103 103 96 91 185

147 153 153 169 170 175 175 1-Hr DV

118 117

0 40 80 120 160 200 240199119921993199419951996199719981999200020012002200320042005200620072008 Design Value (ppb)

0 1 2 3 4 5 6 Population

(Millions)

*Source: Ozone -- EPA's AQS database. 1991-2008 Population --http://www.census.gov/ popest/archives/1990s/MA-99-03b.txt and http ://www.census.gov/popest/counties/CO-E ST2008-popchg2000_2008.html One-Hour NAAQS: 125 ppb Estimated

Po p ulation

Eight-Hour NAAQS: 85 ppb 8-Hr DV

Figure 1-1: One-Hour and 1997 Eight-Hour Ozone Design Values and HGB Area Population

1.2.4 2010 Proposed Revision The EPA reclassification of the HGB area as a severe nonattainment area for the 1997 eight-hour ozone NAAQS became effective on October 31, 20 08. Severe nonattainment areas are required to attain the 1997 eight-hour ozone standard as e xpeditiously as practicable but no later than June 15, 2019. The state must submit a SIP revision addressing the severe ozone nonattainment area requirements of the FCAA by April 15, 2010.1-6 This SIP revision demonstrates attainment of the 1997 eight-hour ozone NAAQS using a photochemical modeling analysis a nd a weight of evidence corroborative analysis. This submittal contains proposed new state and local contro l measures. The Houston-Galveston Area Council (H-GAC), as the regional metropolitan transporta tion planning agency for the HGB area, has identified VMEP measures and transportation control measures for NO X emission reductions.

Photochemical modeling analysis demonstrates th at a 25 percent reduction of the HECT cap on the total Harris County HRVOC allocation would c ontribute to attainment of the 1997 eight-hour ozone NAAQS by reducing the future 2018 oz one design values at all HGB monitors. Accordingly, this SIP revision contains a pr oposed 25 percent reduction in the total HECT allowance cap and revision of the HRVOC a llocation methodology. The HECT program will continue to be applicable only in Harris County.

This SIP revision also contains the RACT analysis, the reasonably available control measures (RACM) analysis, updates to existing control me asures, contingency measures, and the MVEB. The plan also describes ongoing technological research and development as well as future

initiatives.

The HGB Reasonable Further Progress SIP Revisi on for the1997 Eight-Hour Ozone Standard (Project No. 2009-018-SIP-NR), which demonstrates the FCAA requirement of interim reductions of ozone precursors through the 2019 attainment date, is being proposed in a

concurrent action.

Table 1-1: Proposed Rule Revisions contains the project number, title, and description of proposed rule revisions to 30 TAC Chapters 101 and 115 that are associated with this SIP revision. Additional information regarding these rule revisions is included in Chapter 4: Control Strategies and Required Elements

.1-7 Table 1-1: Proposed Rule Revisions
Rule Project Number Title Description

2009-019-101-EN MECT Program Cap Integrity for the HGB Eight-Hour Ozone

Nonattainment Area The proposed revision to the MECT program would ensure the integrity of the modeled HGB nonattainment area cap by prohibiting the issuance of allowance allocations to major sources that did not submit the required Level of Activity Certification forms by the compliance date in 30 TAC §101.360. This proposed rule change would

not reduce the current NO X cap in the HGB

nonattainment area.

2009-006-101-EN HECT Program Cap
Reduction and Allowance

Reallocation The proposed revisions to the HECT program cap rule would propose a 25 percent reduction in the

total HRVOC allowance ca p and revisions to the HRVOC allocation methodology. The HECT program was adopted by the commission as an

ozone control measure for the HGB area on December 1, 2004. The HECT program is applicable only in Harris County.

2008-019-115-EN VOC Control Technique Guidelines (CTG) Update The proposed revisions to 30 TAC Chapter 115, Subchapter E, Division 4 would limit the VOC content of solvents used by offset lithographic printing facilities located in the HGB area and would implement the CTG recommendations to

reduce the VOC content of the fountain solutions and cleaning materials used by such facilities. Additionally, the proposed revisions would expand the current rule applicability to include smaller sources not currently subject to the rule. The proposed revisions are to satisfy RACT for the 2006 federal CTG document for offset lithographic and letterpress printing operations.

The commission is soliciting comments on whether it is appropriate to perform a 1997 eight-hour ozone MCR analysis for the HGB area, and, if so, what elements should be contained in the analysis. The commission is also seeking input on the appropriate date to submit the MCR.

1.3 HEALTH EFFECTS In 1997, the EPA revised the NAAQS for ozone from a one-hour to an eight-hour standard. To support the 1997 eight-hour ozone standard, the EP A provided information indicating that health effects can occur at levels lower than the previ ous standard and at expos ure times longer than one hour. Exposure to ambient ozone can cause asthm a in some people. Repeated exposures to ozone can make people more susceptible to resp iratory infection and lung inflammation and can aggravate preexisting respiratory diseases, such as bronchitis and emphysema.

Children are at a relatively higher risk from expos ure to ozone when compared to adults, since they breathe more air per pound of body weight than adults and because children’s respiratory systems are still developing. Children also spe nd a considerable amount of time outdoors during summer and during the start of the school year (August - October) when high ozone levels are typically recorded. Adults most at risk to ozone exposure are people working or exercising
outdoors and individuals with preexisting respiratory diseases.

1.4 STAKEHOLDER PARTICIPATION AND PUBLIC HEARINGS 1.4.1 Local Program Control Strategy Development Meetings The TCEQ contracted with the H-GAC to identif y possible local on-road and non-road mobile source control strategies. As part of this pro cess, stakeholder meetings were held in the HGB

area. Table 1-2: H-GAC Public and Stakeholder Meeting Dates lists the stakeholder meetings1-8 held by H-GAC and its subcontractor, ENVI RON International Corporation from May 2008 through January 2009. These meeti ngs gave the stakeholders and the public in the HGB area the opportunity to hear about and comment on the de velopment of the local mobile source control strategies.

Table 1-2: H-GAC Public and Stakeholder Meeting Dates

Meetings Dates Airports/Airlines 5/22/08, 10/1/08, 1/6/09

Railroads 6/12/08, 12/1/08 Tug Boat Operators 12/3/08 Public Meetings 7/10/08, 12/8/08 Construction Industry 6/3/08, 12/15/08 Ports/Marine Equipment 6/12/08, 6/19/08, 12/15/08
Industrial Mobile Sources 8/13/08, 12/16/08, 1/8/09
Local Governments 1/27/09

1.4.2 TCEQ SIP and Control Strategy Development Stakeholder Meetings The TCEQ held two identical open-participati on HGB Eight-Hour Ozone SIP Stakeholder Group meetings to discuss concepts of potential cont rol strategies for the eight-county HGB ozone nonattainment area and to hear the public’s id eas on potential rulemaking concepts and provide the public an overview of the development of th e HGB Attainment Demonstration SIP Revision for the 1997 Eight-Hour Ozone Standard. The meet ings were held on March 25 and 26, 2008, at the Houston City Hall Annex. In these meeti ngs, the TCEQ presented attendees with an update

on the HGB Attainment Demonstration SIP Revision timeline, an update on modeling efforts, and a draft list of initial potential control strategy c oncepts for stationary, area, and mobile sources. The TCEQ held an additional stakeholder m eeting to discuss the initial 2018 HGB modeling results, provide an update on the development stat us of the HGB SIP revision, and provide an update from H-GAC regarding potential local mobile source control strategies. This meeting was held on November 3, 2008, at H-GAC. Additional information on the HGB Eight-Hour Ozone SIP Stakeholder Group is available at: http://www.tceq.state.tx.us/implementation/air/sip/hgb_stakeholder.html

.

A meeting was held on May 15, 2008, at H-GA C to discuss the development of the HGB

Attainment Demonstration SIP Revision for th e 1997 Eight-Hour Ozone Standard and potential local control measures with local governments. Lett ers inviting participation were sent to the 15 mayors of cities in the HGB area with populations greater than 20,000, the eight county judges, and the four Harris County commissioners. Notif ication was also sent to state representatives and senators representing the districts in the HGB area. Another meeting was held on July 22, 2008, at H-GAC to provide local governments informa tion on the SIP revision, as well as discuss the process to identify potential measures that can be implemented at the local level. For this meeting, 109 letters inviting participation were sent to mayors of cities in the HGB area with populations of 20,000 or less.1-9 1.4.3 Public Hearings and Comment Information The commission will hold public hearings for this proposed SIP revision and associated rulemakings at the following times and locations:

CITY DATE TIME LOCATION

Houston October 28, 2009 2:00 P.M. Houston-Galveston Area Council

3555 Timmons Lane

Houston, TX 77027

Conference Room A

Houston October 28, 2009 6:00 P.M. Houston-Galveston Area Council

3555 Timmons Lane

Houston, TX 77027

Conference Room A

Austin October 29, 2009 3:00 P.M. TCEQ

12100 Park 35 Circle
Austin, TX 78753
Building E, Room 201S

The public comment period will open on October 9, 2009, and close on November 9, 2009. Written comments will be accepted via mail, fax, or through the eComments system. All

comments should reference the “Houston-Galvest on-Brazoria Attainment Demonstration State Implementation Plan Revision for the 1997 Eight -Hour Ozone Standard” and Project Number 2009-017-SIP-NR. Comments may be submitted to Lola Brown, MC 206, State Implementation Plan Team, Chief Engineer’s Office, Texas Commission on Environmental Quality, P.O. Box 13087, Austin, Texas 78711-3087 or faxed to (512) 239-5687. Electronic comments may be

submitted at http://www5.tceq.state.tx.us/rules/ecomments . File size restrictions may apply to comments being submitted via the eComments system. Comments must be received by November 9, 2009.

Copies of the proposed SIP revision and all a ppendices can be obtained from the TCEQ’s Web

site at http://www.tceq.state.tx.us/implementation/air/sip/hgb.html#

.

1.5 SOCIAL AND ECONOMIC CONSIDERATIONS For a detailed explanation of the social and econom ic issues involved with any of the measures, please refer to the preambles that precede each ru le package accompanying this SIP revision.

1.6 FISCAL AND MANPOWER RESOURCES

The state has determined that its fiscal and manpower resources are adequate and will not be adversely affected through the implementation of this plan.2-1 CHAPTER 2: ANTHROPOGENIC EMISSIONS INVENTORY (EI) DESCRIPTION

2.1 INTRODUCTION The Air Emissions Reporting Requirements (AERR) , published in the December 17, 2008, issue

of the Federal Register (73 FR 76539), instruct states to submit EIs containing information regarding the emissions of criteria pollutants and criteria pollutant precursors (e.g., volatile organic compounds (VOC)). EIs are critical for the e fforts of state, local, and federal agencies to

attain and maintain the National Ambi ent Air Quality Standards (NAAQS).

EIs provide data for a variety of air quality planning tasks, including establishing baseline emission levels, calculating emission reduction targets, control strategy development for achieving required emission reductions, emission i nputs into air quality simulation models, and tracking actual emission reductions against the est ablished emissions growth and control budgets.

This chapter discusses general EI development fo r each of the AERR source categories. Chapter 3, Photochemical Modeling details specific emissions inventor ies and emissions inputs developed for the Houston-Galveston-Brazoria (HGB ) ozone photochemical modeling.

2.1.1 EI Improvement The Texas Commission on Environmental Quality (TCEQ) EI reflects years of continuous emissions data improvement, including extensiv e point and area source inventory reconciliation with ambient emissions monitoring data. Si nce the Texas Air Quality Study 2000 (TexAQS 2000), when ambient VOC concentrations were measured to be greater than EI estimates, EI improvements have targeted more accurate specia tion and reporting of industrial VOC emissions. The following have significantly improved the HGB point source or area source inventory.



### • Implementation of the 30 Texas Administrativ e Code (TAC) Chapter 115 highly reactive volatile organic compounds (HRVOC) monito ring rules improved the HGB point source VOC inventory with measurements required of vents, cooling towers, and the streams to

flares in HRVOC service.

• The Houston Advanced Research Center project H51C (http://www.harc.edu/Projects/AirQuality/Projects/Projects/H051C) identified thousands of tons of VOC flash emissions from upstream oil and gas operations in the HGB area that the TCEQ has added to the area source inventory.

• A special landing loss EI was conducted that required the reporting of landing loss emissions from floating roof tanks. This speci al inventory also required regulated entities
in the HGB area to revise their emissions inventories back to 2002, resulting in a reporting increase of approximately 7,000 to 8, 000 tons of VOC per year (2002-2004). The episodic nature of these emissions is represented in the 2005 and 2006 ozone modeling based on site-specific activity data.

• A month-long hourly EI of approximately 1, 200 emissions sources at 125 industrial sites was conducted during the TexAQS II intensive period. These hourly data are integrated into the 2006 modeling episode, providi ng highly resolved hourly VOC and nitrogen oxides (NO X ) emissions data for sources located in the HGB area. Monitored emissions data were collected for the majority of the VOC hourly emissions and all of the NO X emissions rates. Because these sources ar e not included in the United States Environmental Protection Agency’s (EPA) Acid Rain database, these hourly data present an opportunity to model a unique and extensive set of monitoring data 

### t hat characterizes the time-dependent nature of indust rial ozone precursor emissions.2-2 • The TCEQ Emissions Inventory Guidelines (RG-360A), a comprehensive guidance document which explains all aspects of th e point source EI process is updated and published annually. The latest version of this document is available on the TCEQ’s Point Source Emissions Inventory Web site at: ( http://www.tceq.state.tx.us/implementation/air/industei/psei/psei.html ). Currently, six technical supplements provide detailed guidance on determining emissions from potentially underreported VOC emissions sources such as cooling towers, flares, and storage tanks.

2.2 POINT SOURCES Stationary point source emissions data are collected annually from sites that meet the reporting requirements of 30 TAC § 101.10. These sites include , but are not limited to, refineries, chemical plants, bulk terminals, and utilities. To collect the data, the TCEQ mails EI questionnaires (EIQ) to all sites identified as meeting the reporting re quirements. Companies are required to report emissions data and to provide sample calculations used to determine the emissions. Information characterizing the process equipment, the abatem ent units, and the emission points is also required. All data submitted in the EIQ are reviewed for quality assurance purposes and then stored in the State of Texas Air Reporting System (STARS) database. At the end of the annual reporting cycle, point source emissions data are re ported each year to the EPA for inclusion in the National Emissions Inventory (NEI).

2.3 AREA SOURCES Area sources are stationary emission sources that are not included in the point source EI. Similar area sources such as plants, f acilities, equipment, and/or pro cesses are grouped into area source categories including, but not limited to, vehicle refu eling, architectural coatings, auto refinishing, dry cleaning, municipal solid waste landfills, bake ries, residential fuel combustion, structural fires, wildfires, and open burning.

Area source categories can further be characterized by the mechanism in which their emissions are released into the atmosphere: hydrocar bon evaporative emissions or fuel combustion emissions. Hydrocarbon evaporative emission s ources include, but are not limited to, printing operations, industrial coatings, degreasing solv ents, house painting, gasoline service station underground tank filling, and vehicl e refueling operations. Fuel combustion emission sources include, but are not limited to, stationary s ource fossil fuel combustion at residences and businesses, outdoor burning, structural fires, and wildfires. Since area source categories represent

individual emission sources that are small and nume rous and that have not been inventoried as specific point or mobile sources, the EI for an area source category is developed for a specified geographic area by estimating the emissions collectively.

The emissions from these area source categories, with some exceptions, may be calculated by applying an EPA-established emission factor (emiss ions per unit of activity) to the appropriate activity or activity surrogate responsible for generating emissions. Population is the most commonly used activity surrogate; examples of other activity data are the amount of gasoline sold in an area, employment by industry type, and acres of crop land. Activity data for an area source category is obtained via surveys, research, and/ or investigations. Air emissions data from the different area source categories are collected, re viewed for quality assurance purposes, stored in the Texas Air Emissions Repository database syst em, and compiled to develop the statewide area2-3 source EI. This area source Periodic Emissions Inventory (PEI) is reported every third year (triennially) to the EPA for inclusion in the NEI; the TCEQ submitted the most recent PEI for calendar year 2005.

2.4 NON-ROAD MOBILE SOURCES Non-road mobile sources include vehicles, engi nes, and equipment u sed for construction, agriculture, transportation, recreation, and ma ny other purposes. Non-road vehicles are also referred to as off-road or off-highway vehicles that do not normally operate on roads or highways. This broad category is comprised of a diverse co llection of machines, many of which are powered by diesel engines. Examples of non-road mob ile sources include, but are not limited to: agricultural equipment, commercial and indus trial equipment, construction and mining equipment, lawn and garden equipment, aircra ft, locomotives, and commercial marine vessels.

A Texas specific version of the EPA’s NONROAD 2005 model, called the Texas NONROAD (TexN) model, is used in calculating emi ssions from all non-road mobile equipment and recreational vehicles except aircraft, locomotives, and commercial marine vessels. Emissions for these three source categories are estimated using other EPA-approved methods and guidance documents. Airport emissions are calculated using the Federal Aviation Administration’s Emissions and Dispersion Modeling System, vers ion 5.1. Locomotive emission estimates for Texas are based on specific fuel usage data derived from railway segment level gross ton mileage activity (line haul locomotives) and hours of operation (yard locomotives) provided directly by the Class I railroad companies operating in Texas. Data captured from the Automatic Identification System program is applied to the latest known emission factors to quantify

emissions from commercial marine vessels.

2.5 ON-ROAD MOBILE SOURCES On-road mobile sources consist of automobiles, trucks, motorcycles, and other motor vehicles traveling on public roadways. Combustion-relate d emissions are estimated for vehicle engine exhaust, and evaporative hydrocarbon emissions are estimated for the fuel tank and other evaporative leak sources on the vehicle. The information necessary to estimate on-road mobile emissions is emission factors for each vehicle type, the estimated level of vehicle activity, and estimated roadway speed.

Emission factors were developed using the newest version of the EPA's mobile emissions factor model, MOBILE6.2.03. Various inputs are provided to the model to simulate the vehicle fleet in each nonattainment area. Inputs used to develop localized emission factors include vehicle speeds, vehicle age distributions, local meteorological conditions, type of inspection and maintenance program in place, and local fuel prope rties. Emission factors are developed for all 28 MOBILE6.2.03 vehicle types.

The level of vehicle travel activity is develope d using localized travel demand models (TDM) run by the Texas Transportation Institute, Texas Department of Transportation, or regional metropolitan planning organizations. The TDM have been validated using a large number of ground counts from traffic counters placed in vari ous locations throughout Texas. Estimates of vehicle miles traveled (VMT) are often calibrated to outputs from the federal Highway Performance Monitor System, which is a model validat ed using a different set of traffic counters. VMT is allocated to the appropriate vehicle t ypes using regional specific VMT mixes developed using ground counts and ve hicle registration data.2-4 Roadway speeds are needed to select the appropr iate MOBILE6.2.03 emission factors. Roadway speeds are calculated by a post-processor to the TDM. The speed models use roadway capacity information, the estimated volumes from the TDM, and speed correlations based upon volume to capacity ratios to estimate roadway speeds.

To develop on-road mobile emissions estimates, the speed specific MOBILE6.2.03 emission factors are multiplied by the VMT for each roadway link in the TDM network.

### 3-1 CHAPTER 3: PHOTOCHEMICAL MODELING

o ttainment of the 1997 eight-hour National Ambi ent Air Quality Standard (NAAQS) for ozone.

rroborate the model results and support the adequacy of a proposed control trategy package.

evision, submitted in December

04, was approved by EPA on September 6, 2006.

ossible to attain the eight- hour NAAQS in the HGB area by the prescribed

ttainment date.

lied to the previous ozone season. hus, 2018 is the attainment year used in the ozone modeling.

Extensive use is made of the data collected during TexAQS II to evaluate the model’s 3.1 INTRODUCTION This chapter describes modeling conducted in s upport of the Houston-Galveston-Brazoria (HGB) Attainment Demonstration State Implementation Plan (SIP) Revision for the 1997 Eight-Hour

Ozone Standard. The HGB nonattainment area c onsists of Brazoria, Chambers, Fort Bend, Galveston, Harris, Liberty, Montgomery, and Waller Counties. The 1990 Federal Clean Air Act (FCAA) amendments require that attainment de monstrations be based on photochemical grid modeling or any other analytical methods determined by the United States Environmental Protection Agency (EPA) to be at least as effec tive. The EPA’s April 2007 “Guidance on the Use of Models and Other Analyses for Demonstrati ng Attainment of Air Quality Goals for Ozone,

PM 2.5 , and Regional Haze” (EPA, 2007; hereafte r referred to as “modeling guidance”) recommends new procedures for determining whether a control strategy package will lead t

a

The current modeling guidance recommends several qualitative methods for preparing attainment

demonstrations that ac knowledge the limitations and uncertain ties of photochemical models when used to project ozone concentrations into futu re years. First, the guidance recommends using model results in a relative sense and applying th e model response to the observed ozone data. Second, the guidance recommends using available ai r quality, meteorology, and emissions data to develop a conceptual model for eight-hour ozone fo rmation and to use that analysis in episode selection. Third, the guidance recommends using other analyses (Weight of Evidence) to supplement and co

s

The 1990 FCAA amendments established five cl assifications for ozone nonattainment areas based on the magnitude of the monitored one-hou r ozone design values and established dates by

which each classified area should attain the NAAQS. Based on the monitored one-hour ozone design value at that time, the HGB Consolidat ed Metropolitan Statistical Area (Brazoria, Chambers, Fort Bend, Galveston, Harris, Liberty, Montgomery, and Waller counties) was classified severe-17, with an attainment date of November 15, 2007. Dating back to 1990, there have been six SIP revisions with supporti ng photochemical modeling addressing the one-hour ozone NAAQS. The most recent one-hour ozone HGB SIP r

20

With the change of the ozone NAAQS from a one-hour standard to an eight-hour standard, in April 2004, the EPA classified the HGB area as a moderate ozone nonattainment area with an attainment date of June 15, 2010. Ozone SIP revisions addressi ng the eight-hour ozone standard were due June 15, 2007. Ozone modeling and other analyses conducted by the Texas Commission on Environmental Quality (TCEQ) for the SIP revision resulted in a determination that it was not p

a

Therefore, the ozone SIP revision submitted to EPA on June 15, 2007, included a request to reclassify the area as severe nonattainment fo r the 1997 eight-hour ozone NAAQS, with an attainment date of June 15, 2019. Because the a ttainment date is early in the 2019 ozone season, the EPA has prescribed that the modeling attainment test be app

T

This attainment demonstration uses photochemi cal modeling in combination with corroborative analyses primarily associated with the 2000 and 2006 Texas Air Quality Studies (TexAQS 2000 and TexAQS II, respectively) to support a conclusion that the HGB eight-county nonattainment area will attain the 0.08 parts per million (ppm) 1997 eight-hour ozone standard by June 15, 2019.performance and to improve unde



### 3-2 rstanding of the physical and chemical processes leading to

zone formation in the HGB area.

The meteorological and emissions models rovide the major inputs to the air quality model.

with

ncentrations peaking during the day and fa lling during the night and early morning hours.

most effective tools to address both the chemical omplexity and the future case evaluation.

followed to evaluate the ozone in the urban rea and submitted the plan to the EPA for approval.

photochemical modeling a nd improving the science, the TCEQ selected pisodes to model. o

3.1.1 Overview of the Ozone Photochemical Modeling Process The modeling system is composed of a meteorological model, several emissions processing models, and a photochemical air quality model.

p

Ozone is a secondary pollutant; it is not generally emitted directly into the atmosphere. Ozone is created in the atmosphere by a complex set of chemical reactions between sunlight and several primary (directly emitted) pollutants. The reac tions are photochemical and require ultraviolet energy from sunlight. The primary pollutants fall into two groups, nitrogen oxides (NO X ) and volatile organic compounds (VOC). In add ition, carbon monoxide (CO) is also an ozone precursor, but much less effective than either NO X or VOC in forming ozone. As a result of these multiple factors, higher concentrations of ozone are most common during the summer

co

Ozone chemistry is complex, i nvolving hundreds of chemical compoun ds and chemical reactions. As a result, ozone cannot be evaluated using simple dilution and dispersion algorithms. Due to this chemical complexity, the modeling gui dance strongly recommends using photochemical computer models to simulate ozone formation and evaluate the effectiveness of future control strategies. Computer simulations are the

c

3.1.2 Ozone Modeling Ozone modeling involves two major phases, the ba se case modeling phase and the future year modeling phase (with substeps in each phase). Th e purpose of the base case modeling phase is to evaluate the model’s ability to adequately re plicate measured ozone and ozone precursor concentrations during recent periods with high oz one concentrations (base case episodes). The purpose of the future year modeling phase is to pr edict attainment year ozone design values, as
well as evaluate the effectiveness of controls in reaching attainment. The TCEQ developed a modeling protocol (plan) describing the process to be

a

3.1.3 Base Case Modeling Base case modeling involves several steps. First, recent episodes are analyzed to determine what
factors were associated with ozone formation in the area and whether those factors were consistent with the conceptual model. In c onsultation with the Southeast Texas Photochemical Modeling Technical Committee (SETPMTC), which serves in an advisory role for the technical aspects of applying

e

The next step is to generate and quality-assure the emissions and meteorological data for the selected episodes. Then the meteorological and emissions (NO X , VOC and CO) data are input to the photochemical model and the ozone photochemistry is simulated, resulting in predicted ozone and ozone precursor concentrations. Base case modeling results are evaluated by comparing
them to the observed measurements of ozone and oz one precursors. Typically this step is an iterative process incorporating feedback from successi ve evaluations to ensure that the model is adequately replicating observations throughout the modeling episode. The adequacy of the model in replicating observations is assessed based on compliance with statistical and graphical measures as recommended in the modeling guidance. In addition to the recommended analyses, the TCEQ used the TexAQS II observations to extend its model performance evaluation to areas and chemical species not normally monitored. This extended analysis included use of monitoring data collected on aircraft and ship-based plat forms. Satisfactory performance of the base casemodeling provides



### 3-3 a degree of reliability that the model can be used to predict future year ozone oncentrations (future year design values), as well as to evaluate the effectiveness of possible

d control factors are developed based on the projected growth in the emand for goods and services and the reduction in emissions expected from state, local, and

rs, and thus, the ratio of future year modeled ozone oncentrations to the baseline year concentrati ons provides a measure of the response of ozone

sign value is great er than 84 ppb, then additional controls may be

s in

igure 3-1: Baseline Design Value Calculation Illustration c control measures.

3.1.4 Future Year Modeling Future year modeling involves several steps. The procedure for predicting future year ozone design values (attainment test) involves determining the ratio of the future year to the baseline year modeled ozone concentrations. This ratio is called the relative response factor (RRF). Whereas the emissions data for the base case modeling are episode-specific, the emissions data for the baseline year are based on typical ozone season emissions. Similarly, the emissions data for the future year are developed applying grow th and control factors to the baseline year emissions. The growth an

d federal control programs.

Both the baseline and future years are modeled using their respective ozone season emissions and the base case episode meteorological data as inputs. The same meteorological data are used for modeling both the baseline and future yea

c concentrations to the change in emissions.

The future year ozone design value is calculated by multiplying the RRF by a baseline year ozone design value (DV B ). The DV B is the average of the regulatory design values for the three consecutive years containing the baseline year (see Figure 3-1: Baseline Design Value
Calculation Illustration ). When the calculated future year ozone design value is less than or equal to 0.08 ppm (84 parts pe r billion (ppb)), this signifies modeled attainment. When the calculated future year ozone de

needed and the model can be used to test th e effectiveness of various control measure developing a control strategy.

F

### 3-4 crite ria for selecting ozone episodes for eight-hour

quently

• Select periods during which observed eight-hour ozone concentrations are close to the y monitor;

ring sites that are in violation of the NAAQS.

igure 3-2: Eight-Hour Ozone Exceedance Days in HGB and Other Areas of Texas shows the frequency distribution of days with measured daily maximum eight-hour ozone concentrations greater than 84 ppb for the period 1991 through 2008. The distribution for the HGB area is somewhat bi-modal with a notable high frequency in the late May to early June period and the more prominent period of high frequency occu rring from late August through September. 3 .2 EPISODE SELECTION 3.2.1 EPA Guidance for Episode Selection The modeling guidance sets forth the primary

o zone attainment dem onstration modeling:

• Select a mix of episodes reflecting a variety of meteorological conditions that fre

c orrespond with observed eight-hour daily maxi mum ozone concentrations greater than 84 ppb at different monitoring sites;

eight-hour ozone design value at each ke

• Select periods for which extensive air quality/meteorological databases exist; and

• Model a sufficient number of days so that the modeled attainment test can be applied at

all of the ozone monito

3.2.2 HGB Ozone Episode Selection Process An episode selection analysis was performed to identify time periods with eight-hour ozone exceedance days that complied with the primary selection criteria. The analysis identified several episodes from 2005 and 2006.

FEight-Hour Ozone Exceedance Days in Texas

1991-2008

0 10 20 30 40 50 60 70 80 90 100Early JanLate JanEarly FebLate FebEarly MarLate Mar



### 3-5 r Ozone Exceedance Days in HGB and Other Areas of Texas

Notes:
t Arthur

ort Worth

ande Valley

LM = Tyler-Longview-Marshall

ld intensive period. Table

-1: Selected Episodes summarizes the dates of the selected episodes.

Selected Episodes Figure 3-2: Eight-Hou

AUS = Austin

BPA = Beaumont-Por CC = Corpus Christi

DFW = Dallas-F

ELP = El Paso

LRV = Lower Rio Gr

SAN = San Antonio

T

In consultation with the SETPMTC, the TCEQ selected three episodes from 2005 and three episodes from 2006. Two of these occurred during th e TexAQS II fie

3

Table 3-1:

Period of Episode Number of Exceedance days 5/19/05 through 6/3/05 8 6/15/05 through 6/30/05 9 7/26/05 through 8/8/05 8 5/31/06 through 6/15/06 12 8/15/06 through 9/14/06* 10 9/19/06 through 11/11/06* 5

* TexAQS II field study intensive period

These episodes contain 52 exceedance days with oc currences from late May to early October, the primary window during which high ozone concentr ations have been historically observed, and cover the periods depicted in Figure 3-2: Eight-Hour Ozone Excee dance Days in HGB and OtherEaLaEaLarly AprLate AprEarly MayLate MayEarly JunLate JunEarly JulLate JulEarly AugLate AugEarly Septe Seprly OctLate OctEarly Novte NovEarly DecLate Dec

Days

ELP CC
LRV HGB

DFW

TLM

BPA A US

SAN

### 3-6 e wind pattern haracterized by a diurnal clockwise rotational veering as depicted in Figure 3-3: Hourly

ion the wind blew. The distance of a point from the origin represents e average wind speed in meters per second. Th e pink arrow indicates the daily average of all 24

d ind pattern also frequently associated with ei ght-hour ozone exceedance days is characterized by a northerly morning to southerly afternoon flow reversal. Twenty-three of the 52 exceedance days exhibit this wind pattern. The selected episodes are consistent with the conceptual model. Areas of Texas . In addition, these episodes take advantage of the TexAQS II data and findings, including the August 1 through October 15, 2006, intensive field campaign.

Selecting a large number of days also increases the likelihood that the distribution of days associated with various ozone-conducive wind patterns will be consistent with the conceptual model. The conceptual model of ozone formation in the HGB area (see Appendix C: CAMx Modeling for the HGB Attainment Demonstration SIP) suggests that th

c Average Resultant Winds; Eight-Hour Exceedanc e Days, August through September 1998 through 2006 is most often associated with eight-hour ozone exceedance days.

Hourly average resultant winds are plotted in the figure. The x-axis represents the east-west component of the wind while the y-axis represents the north-south component. Each point on the loop represents an hour of the day. The red data point corresponds to midnight and the aqua point corresponds to noon. Wind vectors have two a ttributes, wind speed and direction, and these components were averaged across monitors for each hour of the day and then plotted. Each point represents the tail of that hour’s averaged resulta nt wind vector, and although not plotted, all the resultant wind vectors terminate at the origin. In other words, the direction from the point to the origin represents the direct

th one-hour vectors, and the green halo around each point gives an indication of the variability of

the data across monitors.

Of the 52 exceedance days in the selected episodes, 25 days exhibit this wind pattern. A secon

w

### 3-7 eedance Days, August rough September 1998 through 2006

um eight-hour oz one concentrations observed and the number of monitors exceeding 84 ppb. 

## 8-hour Exceedances Hourly Resultant Wind Vectors 170 days

Vector Wind Speed in meters per second (m/s) -3.5 -3.0 -2.5 -2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5

-3.5 -3.0 -2.5 -2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 00:00 12:00

Figure 3-3: Hourly Average Resultant Winds; Eight-Hour Exc

th

Figure 3-4: 2005 and 2006 Non-TexAQS II Modeling Episodes and Figure 3-5: 2006 TexAQS II Modeling Episodes show the daily maximFigure 3-4: 2005 and 2006 Non-TexAQS II Modeling EpisodesNote: 8-h o3= eight-hour ozone3-83-9Figure 3-5: 2006 TexAQS II Modeling Episodes

33.0 41.4 56.6 68.8 65.8 56.8 44.2 50.2 76.8 43.0 45.2 42.5 43.4 56.0 64.3 95.5 113.6 89.7 51.6 75.5 73.7 71.2 44.1 67.9 45.5 26.5 30.0 29.7 72.7 80.8 127.1 121.8 83.7 88.7

79.8 63.9 87.9 110.5 81.1 47.4 41.5 46.0 70.0 89.0 118.9

44.8 36.7 24.6 43.0 60.4 86.7 56.9 27.7 29.8 45.0 58.3 78.4 90.5 60.9 67.1 48.0 59.1 51.0 70.6 82.0 78.2 95.3 87.0 82.6 75.5 49.0 90.4 53.4 46.1 59.6 33.8

6 14 1 14 25 1 1 12 1 8 1 2 2 1 2152535455565758595105115125135 20060801 20060804 20060807 20060810 20060813 20060816 20060819 20060822 20060825 20060828 20060831 20060903 20060906 20060909 20060912 20060915 20060918 20060921 20060924 20060927 20060930 20061003 20061006 20061009 20061012 20061015

hgb daily max 8-h ozone (ppb)051015202530 # of sites >= 85 ppbdaily m ax 8-h o3# of sites >= 85ppb3-10 Table 3-2: Eight-Hour Ozone Design Values and Number of Exceedance Days During Selected Episodes lists the regulatory nonattainment monitors in the eight-county HGB area along with their 2005 and 2006 eight-hour ozone design values and the number of days during the selected episodes for which the daily maximum eight-hour ozone was greater than 84 ppb.

Table 3-2: Eight-Hour Ozone Design Values and Number of Exceedance Days During Selected Episodes

Monitor Designation Site Code 2005 Design Value (ppb) 2006 Design Value (ppb) Number Days > 84ppb Houston East (CAMS 1) HOEA 87 83 7 Aldine (CAMS 8) HALC 92 88 5 Channelview (CAMS 15) HCHV 89 85 5 Northwest Harris County (CAMS 26) HNWA 93 91 13 Galveston Airport (CAMS 34) GALV 87 83 3 Deer Park (CAMS 35) DRPK 100 96 10 Seabrook Friendship Park (CAMS 45) SBFP 92 90 8 Houston Bayland Park (CAMS 53) BAYP 103 103 14 Conroe Relocated (CAMS 78) CNR2 86 85 5 TCEQ Houston Regional Office (CAMS 81) HROC 88 84 9 Manvel Croix Park (CAMS 84) MACP 97 96 16 Clinton (CAMS 403) C35C 95 85 1 Houston Monroe (CAMS 406) HSMA 97 99 10 Croquet (CAMS 409) HCQA 98 94 8 Shell Westhollow (CAMS 410) SHWH 89 96 12

Houston Texas Avenue (CAMS 411) HTCA 88 84 1 Lynchburg Ferry (CAMS 1015) LYNF 96 89 8 Note: CAMS = Continuous Ambient Monitoring Station3-11 Figure 3-6: Map Depicting Regulatory Monitors in the HGB Area shows the location of the regulatory monitors in the eight-county HGB area.

Figure 3-6: Map Depicting Regulatory Monitors in the HGB Area

Even though there are 52 exceedance days in the 2005 and 2006 episodes, only a few of the regulatory monitors measured daily maximum eight- hour ozone concentrations of greater than 84 ppb on 10 or more days. This reflects the comp lexity of ozone formation and distribution in the HGB area. For example, the Houston Texas Avenue (HTCA, CAMS 411) and TCEQ Houston Regional Office (HROC, CAMS 81) monitors are in fairly close proximity to one another, but the Houston Texas Avenue (CAMS 411) monitor measured a daily maximum eight-hour ozone concentration of greater than 84 ppb on only one day, while the TCEQ Houston Regional Office (CAMS 81) monitor measured it on nine days. Th e attainment test considers the modeled daily maximum eight-hour ozone concentration from an array of grid cells around the cell containing a monitor. By considering an array of grid cells around the monitor, rather than the single grid cell where the monitor is located, the likelihood of modeled concentrations exceeding 84 ppb is increased. This increases the number of days used in the attainment test (i.e., the RRF calculation).

There were a few other ozone episodes during the 2005 and 2006 ozone season that were not developed due to unusual meteorol ogical conditions. For example, exceedance days that occurred in late August and September of 2005 may have been influenced by hurricanes Katrina and Rita.3-12 3.3 METEOROLOGICAL MODEL The TCEQ is using the Fifth Generation Meteor ological Model (MM5, version 3.7.3) developed jointly by the National Center for Atmosphe ric Research (NCAR) and Pennsylvania State University (Grell et al. , 1994). This model, supported by a broad user community including the Air Force Weather Agency, national laboratories, and academia, is being used extensively for regulatory air quality modeling analyses throughout the United States.

3.3.1 Modeling Domains MM5 was configured with three two-way nested outer grids (108 kilometer (km), 36 km, and 12 km horizontal resolution) to cover the United States and regional areas of interest. A one-way nested 4 km fine grid covering the eastern half of Texas was used to focus on metropolitan areas with air quality degradation, as shown in Figure 3-7: MM5 Modeling Domains . The extent of each of the MM5 modeling domains was selected to accommodate the embedding of the commensurate air quality modeling domains (see Section 3.5: PHOTOCHEMICAL MODELING ).

Vertically, MM5 is structured with 43 layers from the surface to approximately 20 km. Twenty layers are within the first 3,000 meters in orde r to resolve boundary layer phenomena. The same MM5 vertical layering structure is used for all of the domains.

Range Grid Points

Domain Eastin g ( km ) N orthin g ( km ) Eastin g N orthin g
108 km (-2808, 2808) (-2268, 2268) 53 43

36 km (-1296, 2160) (-1728, 972) 97 76

12 km (-648, 1080) (-1548, -360) 145 100

4 km (72, 372) (-1 80, -648) 3 166 184

F igure 3-7: MM5 Modeling Domains

3.3.2 Model (MM5) Configuration Based on past TCEQ modeling efforts, the EPA ’s modeling guidance (EPA, 2007), contractor experience, and other demonstrations including sensitivity tests and model performance evaluation, the MM5 was configured with parameterizati ons and improved input data to optimize the performance of the wind field (i.e., wind speed a nd direction). Wind speed and direction are the3-13 WN program was used to terpolate from the 12 km domain output to the 4 km domain input.

r udging. The NCEP NAM gridded output was also u sed for model initialization (NCEP, 2009).

iences, MM5 community use, and features of the ozone exceedance pisodes being modeled.

Table 3-3: Selected deling Schemes Nudging

C s Radiation Land-Surface

M most important parameters predicted by th e meteorological model for air quality modelingpurposes because the wind field determines the transport and dispersion of pollutants. The preprocessing of the MM5 input data followed th e standard progression using the TERRAIN, REGRID, and INTERPF (NCAR, 2005) programs. The NESTDO

in

To improve the MM5 simulation of the meteorological parameters, in particular the wind field, the

land use characteristics and sea surface temperatures on all domains were updated with high resolution satellite measurements. In addition, observed parameters are assimilated in MM5 during the model run through a process called Four-Dimensional Data Assimilation (FDDA), or nudging (Stauffer and Seaman, 1990; Stauffer et al. , 1991; Stauffer and Seaman, 1994). The outer domains (108 km, 36 km, and 12 km) were nudged to the Na tional Center for Environmental Prediction (NCEP) North American Model (NAM) gridded out put for winds, temperature, and water vapor.

The fine scale 4 km domain was observationall y nudged using quality-assured upper air wind profiler data. MM5 default nudging strength parameters were used for both the NAM and profile

n

MM5 schemes and options typically selected for air quality applications are shown in Table 3-3: Selected MM5 Modeling Schemes . The selection of these schemes and options was based on previous modeling exper

e

MM5 Mo

Domain Type PBL umulu Model icrophysics

108, 36, 12 km Analysis 3-D Eta Grell RRTM Noah Simple Ice

4 km Observational Eta Grell RRTM Noah Simple Ice N PBL = Planetary Boundary Layer

otes: RRTM = Rapid Radiative Transfer Model

KE) vertical diffusivity methodology, with a minimum vertical diffusivity coefficient (K ) of 1.0.

ature (SST) data, the nudging methodology, the KE methodology and the Grell cumulus scheme.

e xceedance episodes, as listed in Table 3-4: 2005 and 2006 Meteorological Modeling Episodes

. MM5 output was post-processed using the MM5CAM X utility to convert the MM5 meteorological fields to the Comprehensive Air Quality Model wi th Extensions (CAMx) grid and input format (Environ, 2008). The output was also processed with the Mellor-Yamada turbulent kinetic energy (T V

Appendix A: Meteorological Modeling for the HGB Attainment Demonstration SIP provides details on the development of the MM5 configuration, including the satellite-based LandUse/Land-Cover (LULC) and Sea Surface Temper

T

3.3.3 MM5 Application and Performance The final MM5 modeling configuration was app lied to periods spanning the eight-hour ozon

e3-14 Table 3-4: 2005 and 2006 Meteorological Modeling Episodes

Episode All Grids Begin Date/Time (UTC) Outer Grids End Date/Time (UTC) Fine Grid End Date/Time (UTC) 2005ep0 May 18, 2005 06:00 June 4, 2005 06:00 June 4, 2005 06:00
2005ep1 June 15, 2005 06:00 July 1, 2005 06:00 July 1, 2005 06:00
2005ep2 July 25, 2005 06:00 August 9, 2005 09:00 August 9, 2005 07:00
2006ep0 May 29, 2006 06:00 June 17, 2006 06:00 June 17, 2006 06:00
2006ep1a August 23, 2006 07:00
2006ep1b September 16, 2006 07:00
2006ep1c October 1, 2006 07:00
2006ep1d August 13, 2006 06:00 October 13, 2006 09:00

October 13, 2006 07:00 Note: UTC = Universal Time, Coordinated.

A detailed performance evaluation for each of the 2005 and 2006 meteorological modeling episodes is included in Appendix A: Meteorological Modeling for the HGB Attainment

Demonstration SIP . In addition, all performance evalua tion products are available on the TCEQ file transfer protocol (FTP) site (TCEQ, 2009).

As mentioned, the wind speed and direction are de emed to be the most important meteorological parameters input to the air quality model. The MM5 modeled wind field was evaluated by comparing the hourly modeled and measured wind sp eed and direction for all monitors in the HGB area. Figure 3-8: Meteorological Modeling Performance exhibits the percent of hours for which the average absolute difference between the mode led and measured wind speed and direction, for all monitors in the HGB area, was within the speci fied accuracy benchmarks (e.g., wind speed less than or equal to two meters per second: WSPD < 2 m/s).

TexAQS II Meteorological Modeling Performance Statistics

76 82

65 76 80

67 84 83 100 100 97 100

96 96 98

78

74 80 85 83 80

69 73 98

0 10 20 30 40 50 60 70 80 90 100

2005ep0 2005ep1 2005ep2 2006ep0 2006ep1a 2006ep1b 2006ep1c 2006ep1dPercent of Hours within Accuracy Threshold WDIR ≤ 30 °

WSPD ≤ 2 m/s

TEMP ≤ 2 °C

Figure 3-8: Meteorological Modeling Performance

Notes: WDIR = Wind Direction WSPD = Wind Speed TEMP = Temperature3-15 Table 3-5: Average HGB Percent Accuracy for a ll Meteorological Modeling Episodes provides an additional evaluation of MM5 predictio ns to stricter benchmarks (Emery et al., 2001).

Table 3-5: Average HGB Percent Accuracy for all Meteorological Modeling Episodes

Episode Wind Direction (°)

Error ≤ 30 / 20 / 10 Wind Speed (m/s)

Error ≤ 2 / 1 / 0.5 Temperature (°C)

Error ≤ 2 / 1 / 0.5
2005ep0 76 / 67 / 49 98 / 73 / 40 78 / 49 / 30
2005ep1 82 / 71 / 40 100 / 93 / 60 74 / 50 / 28
2005ep2 65 / 54 / 33 100 / 75 / 43 80 / 57 / 31
2006ep0 76 / 63 / 45 97 / 72 / 38 85 / 57 / 33
2006ep1a 80 / 67 / 43 100 / 83 / 43 83 / 61 / 39
2006ep1b 67 / 54 / 33 96 / 63 / 26 80 / 52 / 25
2006ep1c 84 / 76 / 57 96 / 57 / 29 69 / 33 / 16
2006ep1d 83 / 66 / 33 98 / 75 / 42 73 / 51 / 32

3.4 MODELING EMISSIONS For the stationary emission source types, which cons ist of point and area sources, routine emission inventories provided the major inputs for the emissions modeling processing. Emissions from mobile and biogenic sources were derived from rele vant emission models. Specifically, link-based
on-road mobile source emissions were derived fro m a travel demand model coupled with the EPA MOBILE6.2 emission factor model, and non-road mobile source emissions were derived from the EPA’s National Mobile Inventory Model (NMI M), or the Texas NONROAD (TexN) mobile

source models. The on- and non-road emissions were processed to air quality model-ready using version three of the Emissions Processing System (EPS3; Environ, 2007). Biogenic emissions

were derived from the Global Bios phere Emissions and Interacti ons System (GloBEIS) model, which outputs air quality model-ready emissions.

Appendix B: Emissions Modeling for the HGB Attainment Demonstration SIP provides details on the development and processing of the emissions using the various EPS3 modules. The modules,

listed in Table 3-6: EPS3 Emissions Processing Modules are used to create the chemically speciated, temporally (hourly) allocated, and spatia lly distributed emission f iles needed for the air quality model.

Table 3-6: EPS3 Emissions Processing Modules

EPS3 Module Description

PREAM Prepare area and non-link based mobile sources emissions for further processing

LBASE Spatially allocate link-based mobile source emissions among grid cells

PREPNT Group point source emissions into elevated and low-level for further processing

CNTLEM Apply controls to model strategies, apply adjustments, etc.

TMPRL Apply temporal profiles to hourly allocate emissions

CHMSPL Chemically speciate emissions into nitrogen oxide (NO), nitrogen dioxide (NO 2 ), CB05-VOC

GRDEM Spatially distribute emissions by grid cell using source category surrogates

MRGUAM Merge and adjust multiple gridded files for model-ready input

PIGEMS Assigns PiGs and merges elevated point source files

Notes: CB05 = the 2005 version of the Carbon Bond chemical mechanism

PiG = Plume-in-Grid

Model-ready emissions were developed for the episode days listed in Table 3-7: 2005 and 2006 Episode Days for Emissions Modeling

.3-16 Table 3-7: 2005 and 2006 Episode Days for Emissions Modeling 2005 and 2006 Base Case Episodes Episode Code Episode Designation Episode Days bc05ep0 May/June 2005 May 19 through June 3, 2005 bc05ep1 June 2005 June 17 through 30, 2005 bc05ep2 July/August 2005 July 26 through August 8, 2005 bc06ep0 June 2006 May 31 through June 15, 2006 bc06aqs1 August/September 2006 Augus t 13 through September 15, 2006 bc06aqs2 September/Oct ober 2006 September 16 through October 11, 2006

The following sections give a brief description of the development of each type of emissions.

3.4.1 Biogenic Emissions The TCEQ used Version 3.1 of the GloBEIS mo del to develop the biogenic emissions. It incorporates detailed locality-specific land-use data to generate the mix a nd density of vegetative species. In addition, solar radiation data from Geostationary Operational Environmental Satellite (GOES) imagery, which is used to generate the photosynthetically active solar radiation (PAR), can be input to the GloBEIS model. Further, th e GloBEIS model can accept hourly temperature data generated from weather station data.

Biogenic Emissions Landuse Data,Version 3 (BELD3 ; Kinnee et al., 1997), a vegetation database

for the entire North American c ontinent prepared specifically for creating biogenic emissions inventories, was used for the 36 km domain and the portion of the 12 km domain outside Texas.
For the land-use data in the 12 km domain with in Texas, the TCEQ used the Texas vegetation database (Wiedinmyer et al., 2001), which was de rived from Texas Parks and Wildlife vegetation data and agricultural statistics from the National Agricultural Statistics Su rvey, and field surveys
carried out in 1999. Within the 4 km nest ed domain, a new land-cover database from the University of Texas Center for Space Research (UT-CSR) was used (Feldman et al., 2007). This database was developed from classification of r ecent Landsat 7 data, S huttle Radar Topography

Mission and National Elevation datasets to iden tify wetlands, and United States Department of Agriculture, Common Land Unit CLU data to identify agricultural land.

The episode-specific PAR data input to GloBEIS were obtained from the website operated by the Global Energy and Water Cycle Experiment (GEW EX) Continental-Scale International Project (GCIP) and GEWEX Americas Prediction Project (GAPP) located at http://metosrv2.umd.edu/~srb/gci p/cgi-bin/historic.cgi?auth=no . The episode-specific temperature data were obtained from weather stations throug hout the United States, including data from the National Weather Service, the EPA Aerometric In formation Retrieval Syst em (AIRS) air quality database, the National Buoy Data Center, the Texas A&M Crop Weather Program, the Louisiana Agricultural Information Service, and the Tex as Coastal Oceanographic Observation Network.

GloBEIS3.1 was run for each of the modeling episode days listed in Table 3-7: 2005 and 2006 Episode Days for Emissions Modeling . Figure 3-9: An Example of Day-Specific Biogenic

Emissions shows the typical magnitude and distribution of biogenic VOC and NO X emissions in the 4 km modeling domain.3-17 

# Biogenic VOC and NO X 

# Emissions August 2, 2005

Figure 3-9: An Example of Day-Specific Biogenic Emissions

Since biogenic emissions are associated with me teorological features, the same episode dayspecific emissions were used as input for the 200 6 baseline and 2018 future air quality modeling.

3.4.2 Base Cases

3.4.2.1 Point Sources Point source modeling emissions were developed us ing data from regional inventories such as the Central Regional Air Planning Association/Re gional Planning Organization (CENRAP/RPO) emissions database and EPA’s Acid Rain Database (A RD), state inventories including the State of Texas Air Reporting System (STARS), and local inventories including the TexAQS II Hourly Special Inventory (SI). Data were processed w ith EPS3 to generate model-ready emissions, and similar procedures were used to develop each base case episode.

Outside Texas Point source emissions data for the regions of the modeling domains outside Texas were obtained

from a number of different sources. Emissions fro m point sources in the Gulf of Mexico (e.g., oil and gas production platforms) were obtaine d from the 2005 Gulf-wide Emissions Inventory (GWEI) provided by the Minerals Management Se rvices (MMS) as monthly totals. The Canadian emissions were obtained from EPA modeling em ission files developed for the 2001 Clean Air Interstate Rule (CAIR) base case analysis (EPA , 2005) and the Mexican emissions inventory data

were obtained from Phase III of the Mexican National Emissions Inventory (NEI; http://www.epa.gov/ttn/chief/net/mexico.html).

For all states beyond Texas, hourly NO X emissions for major electric generating units (EGUs) were obtained from the ARD for each episode day. Emissions for non-ARD sources in states beyond Texas were obtained from the 2002 CENRAP/RPO emissions database, with the exception of3-18 Arkansas, Louisiana, and Oklahoma. State- specific 2005 point source annual emissions for nonARD sources were provided by Arkansas and Ok lahoma. Louisiana pr ovided their 2004 point source emissions, since the 2005 emissions were in complete due to hurricane Katrina. The EPA’s Economic Growth Analysis System Version 5.0 (EGAS5) was used to grow these emissions to 2005 and 2006 as appropriate for the various episodes.

Within Texas Hourly NO X emissions from EGUs within Texas were obtained from the ARD for each episode day.

Emissions from non-ARD sources were obtained fro m the TCEQ 2005 and 2006 STARS emissions inventories. The 2006 TexAQS II hourly special inventory (SI) collected August 15 through September 15, 2006, was used for the August/Sep tember 2006 episode (bc06aqs1). In addition, agricultural and forest fire emissions for th e 2005 and 2006 episodes were obtained from a TCEQfunded study (Environ, 2008b), which treated fires as point sources. For the HGB area, 2005 and 2006 event-specific tank landing loss emissions were obtained from an SI revision requested by the TCEQ. Highly Reactive Volatile Organic Comp ounds (HRVOC) (ethylene (ETH), propylene, butenes and 1,3-butadiene) emissions were rec onciled with ambient measurements by comparing concentrations observed at automated gas ch romatographs (auto-GCs) in the area with concentrations expected at those locations based on the reported invent ory. See Appendix B: Emissions Modeling for the HGB Attainment Demonstration SIP for more details.

Table 3-8: 2005 and 2006 Base Case Episode Point Source Modeling Emissions for HGB summarizes the typical weekday point source emissions for the eight-county HGB area by episode.3-19 Table 3-8: 2005 and 2006 Base Case Episod e Point Source Modeling Emissions for HGB Bc05ep0 Bc05ep1 Bc05ep2

NO X VOC CO NO X VOC CO NO X VOC CO Point
Source Type (tpd) (tpd) (tpd)

ARD 1 43.89 3.28 29.59 43.03 3.08 38.56 55.26 4.04 48.24

N-ARD 2 147.52 224.87 95.51 147.52 224.87 95.51 147.52 224.87 95.51

Tank L 3 NA 49.50 NA NA 17.80 NA NA 33.10 NA

Fires 4 0.04 0.29 3.61 0.10 0.81 10.37 0.92 7.19 92.70

HRVOC 5 NA 29.92 NA NA 29.92 NA NA 29.92 NA

Totals 191.45 307.86 128.71 190.65 276.48 144.44 203.70 299.12 236.45

Bc06ep0 Bc06aqs1 Bc06aqs2

NO X VOC CO NO X VOC CO NO X VOC CO Point
Source Type (tpd) (tpd) (tpd)

ARD 1 46.65 2.87 39.66 40.41 2.45 29.45 48.42 2.72 36.47

N-ARD 2 124.13 180.62 89.52 121.95 165.39 88.34 124.13 180.62 89.52

Tank L 3 NA 17.40 NA NA 10.40 NA NA 0.30 NA

Fires 4 0.04 0.27 3.46 0.13 1.05 13.47 0.04 0.30 3.72

HRVOC 5 NA 21.17 NA NA 21.17 NA NA 21.17 NA

Totals 170.82 222.33 132.64 162.49 200.46 131.26 172.59 205.11 129.71 Notes: 1. ARD emissions listed are for a Wednesday in a specific episode. 2. Non-ARD emissions listed are for OSD weekday, OSD weekend days are slightly less. 3. Tank landing emissions listed are episode -specific average for days with non-zero

emissions. 4. Agriculture and forest fire emissions liste d are episode-specific average for days with

non-zero emissions. 5. HRVOC reconciled emissions listed are the amounts added through the emissions reconciliation procedure to those reported.

3.4.2.2 On-Road Mobile Sources On-road mobile source modeling emissions were developed using the EPA’s NMIM, and Highway Performance Monitoring System (HPMS) data and travel demand modeling (TDM) output coupled with the EPA MOBILE6.2 emissions model. The output from these emission modeling applications were processed through EPS3 to generate the air qua lity model-ready on-road mobile

source emission files.

Outside Texas For all of the states beyond Texas, the TCEQ used NMIM to generate average summer weekday mobile source emissions by county for 2005 and 2006. Average summer Friday, Saturday, and Sunday mobile source emissions were estimated using the weekday to Friday, Saturday, and Sunday ratios developed for the on-road m obile source emissions within Texas.

Within Texas
For the Texas counties outside of HGB and Beaum ont-Port Arthur (BPA) areas, on-road emissions were developed by the Texas Transportation Ins titute (TTI) using HPMS data for 2005 and 2006,

and the EPA’s MOBILE6.2 on-road mobile source emissions model to generate average summer emissions for the four day types of weekday (Monda y through Thursday average), Friday, Saturday, and Sunday.

For the eight-county HGB and three-county BPA areas, link-based on-road emission were developed by TTI using the TDM output for 20 05 and 2006, and the EPA MOBILE6.2 on-road mobile source emissions model to generate average summer and school season on-road emission3-20 for the four day types. For the 2005 and 2006 base case episodes, both the school and summer season day type emissions we re used as appropriate.

Table 3-9: Summary of the Development of On-Road Mobile Sources Emissions summarizes features of the on-road mobile emissions in the different regions of the modeling domain.

Table 3-9: Summary of the Development of On-Road Mobile Sources Emissions On-Road Inventory Development Parameter HGB and BPA Non- HGB and BPA Non-Texas
States/Counties

VMT Source and

Resolution TDM Roadway Links HPMS Data Sets -19 Roadways NMIM Database - 12 Roadways

Season Types School and Summer Summer Only Summer Only Day Types Weekday, Friday, Saturday, and Sunday Weekday, Friday, Saturday, and Sunday Weekday, Friday, Saturday, and Sunday Hourly VMT Mix By Day Type Yes Yes No Roadway Speed

Distribution Varies by

Hour and Link Varies by Hour and Roadway Type MOBILE6.2

Default

MOBILE6.2 Classes 28 28 12 Temperature/Humidity

Diesel NO X Correction Yes Yes No “18-Wheeler” Idling Emissions Separation Yes No No
Note: VMT= Vehicle Miles Traveled

Table 3-10: 2005 and 2006 Base Case Episode On-Road Modeling Emissions for HGB

summarizes the on-road mobile source emissions for each of the 2005 and 2006 base case episodes for the eight-county HGB area.

Table 3-10: 2005 and 2006 Base Case Episod e On-Road Modeling Emissions for HGB Bc05ep0 Bc05ep1 Bc05ep2

NO X VOC CO NO X VOC CO NO X VOC CO On-Road Day Type (tpd) (tpd) (tpd) Weekday 233.35 110.29 1307.35 221.67 104.27 1244.93 221.67 104.27 1244.93 Friday 241.06 123.43 1457.80 223.68 113.73 1359.36 223.68 113.73 1359.36 Saturday 192.67 85.51 1099.39 180.72 80.09 1032.63 180.72 80.09 1032.63 Sunday 148.68 70.51 906.86 143.17 67.81 873.70 143.17 67.81 873.70

Bc06ep0 Bc06aqs1 Bc06aqs2

NO X VOC CO NO X VOC CO NO X VOC CO On-Road Day Type (tpd) (tpd) (tpd) Weekday 197.28 99.39 1115.23 207.64 105.15 1171.27 207.64 105.15 1171.27 Friday 199.92 108.40 1217.36 215.43 117.70 1305.77 215.43 117.70 1305.77 Saturday 160.76 76.06 920.59 171.37 81.21 980.17 171.37 81.21 980.17 Sunday 127.68 64.42 778.75 132.59 66.99 808.41 132.59 66.99 808.41 Notes: 1. Episodes bc05ep0, bc06aqs1 and bc 06aqs2 use school season emissions; episodes bc05ep1, bc05ep2 and bc06ep0 use summer season emissions. 2. VOC is reported as sum of CB05 species.3-21 3.4.2.3 Non- and Off-Road Mobile Sources Non/Off-road mobile source modeling emissions were developed using the EPA NMIM, the EPA NEI, TexN, and data from the TCEQ’s Texas Ai r Emissions Repository (TexAER). The output from these emission modeling applications and da tabases were processed through EPS3 to generate the air quality model-ready non- and off- road mobile source emission files.

Outside Texas For all the states beyond Texas, the TCEQ used the EPA’s NMIM. NMIM generates average summer weekday non-road mobile source category emissions by county and was run for 2005 and 2006. For the off-road mobile source categories (aircraft, locomotive, and marine) in the nonTexas states, the TCEQ used the EPA’s 2002 NEI with EGAS5 growth factors and national

controls for locomotives and marine vessels to generate 2005 and 2006 average summer weekday off-road mobile source category emissions. Summe r weekend day emissions for the non- and offroad mobile source categories were develope d as part of the EPS3 processing using category specific weekly activity profiles.

Within Texas The TCEQ used the TexN model to generate av erage summer weekday non-road mobile source category emissions by county for 2005 and 2006. County-level off-road emissions for 2005 were obtained from the TCEQ’s 2005 TexAER, and th e 2006 county-level off-road emissions were estimated by adjusting the 2005 TexAER emissions with the Texas-specific Regional Economic Models, Inc. (REMI)-EGAS growth factors, except for the aircraft/airport emissions in the HGB and DFW areas. The 2005 and 2006 aircraft/airpor t emissions in the HGB and DFW areas were provided through a stakeholder process and these emis sions are airport-specific rather than countylevel. Summer weekend day emissions for the no n- and off-road mobile source categories were developed as part of the EPS3 processing usi ng category specific weekly activity profiles.

Table 3-11: 2005 and 2006 Base Case Episode Non- and Off-Road Modeling Emissions for HGB

summarizes the non- and off-road mobile source w eekday emissions for each of the 2005 and 2006 base case episodes for the eight-county HGB area. Since these are average summer weekday, the
2005 emissions are used for each of the 2005 base case episodes and the 2006 emissions are used for each of the 2006 base case episodes.

Table 3-11: 2005 and 2006 Base Case Episode Non- and Off-Road Modeling Emissions for
HGB Bc05ep0 Bc05ep1 Bc05ep2

NO X VOC CO NO X VOC CO NO X VOC CO Non-Road Type (tpd) (tpd) (tpd)

Non-Road 84.97 81.01 805.50 84.97 81.01 805.50 84.97 81.01 805.50 Airports 9.53 2.72 38.22 9.53 2.72 38.22 9.53 2.72 38.22

Locomotive 30.34 2.48 8.52 30.34 2.48 8.52 30.34 2.48 8.52

Marine 34.47 0.79 6.30 34.47 0.79 6.30 34.47 0.79 6.30

Totals 159.31 87.00 858.54 159.31 87.00 858.54 159.31 87.00 858.54

Bc06ep0 Bc06aqs1 Bc06aqs2

NO X VOC CO NO X VOC CO NO X VOC CO Non-Road Type (tpd) (tpd) (tpd)

Non-Road 78.85 75.97 772.94 78.85 75.97 772.94 78.85 75.97 772.94 Airports 9.89 2.80 38.07 9.89 2.80 38.07 9.89 2.80 38.07

Locomotive 28.56 2.45 8.77 28.56 2.45 8.77 28.56 2.45 8.77

Marine 35.10 0.80 6.41 35.10 0.80 6.41 35.10 0.80 6.41

Totals 152.40 82.02 826.19 152.40 82.02 826.19 152.40 82.02 826.19 Note: VOC is reported as sum of CB05 species3-22 3.4.2.4 Area Sources Area source modeling emissions we re developed using the EPA NE I and the TCEQ TexAER. The emissions information in these databases was pr ocessed through EPS3 to generate the air quality model-ready area source emission files.

Outside Texas For all the states beyond Texas, the TCEQ used the EPA’s 2002 NEI with EGAS5 growth factors to generate 2005 and 2006 daily area source emissions.

Within Texas The TCEQ used 2005 TexAER to generate 2005 daily area source emissions and for the 2006 daily area source emissions, applied the Texas-specific REMI-EGAS growth factors.

Since these are daily emissions, the 2005 emissi ons are used for each of the 2005 base case episodes and the 2006 emissions are used for each of the 2006 base case episodes.

3.4.2.5 Base Case Summary

Table 3-12: 2005 and 2006 Base Case Episode Anthropogenic Modeling Emissions for HGB summarizes the typical weekday emissions in the eight-county HGB area by source type for each base case episode.

Table 3-12: 2005 and 2006 Base Case Episode Anthropogenic Modeling Emissions for HGB Bc05ep0 Bc05ep1 Bc05ep2

NO X VOC CO NO X VOC CO NO X VOC CO Source Type (tpd) (tpd) (tpd)

Point 1 191.45 307.86 128.71 190.65 276.48 144.44 203.70 299.12 236.45

OnRoad 2 233.35 110.29 1307.35 221.67 104.27 1244.37 221.67 104.27 1244.37

Non –

Road 3 84.97 81.01 805.50 84.97 81.01 805.50 84.97 81.01 805.50

OffRoad 3, 4 74.35 5.99 53.04 74.35 5.99 53.04 74.35 5.99 53.04

Area 3 36.18 524.35 131.71 36.18 524.35 131.71 36.18 524.35 131.71

Totals 620.30 1029.50 2426.31 607.82 992.10 2379.06 620.87 1014.74 2471.07

Bc06ep0 Bc06aqs1 Bc06aqs2

NO X VOC CO NO X VOC CO NO X VOC CO Source Type (tpd) (tpd) (tpd)

Point 1 170.82 222.33 132.64 162.49 200.46 131.26 172.59 205.11 129.71

On-Road 2 197.28 99.39 1115.23 207.64 105.15 1171.27 207.64 105.15 1171.27

Non –Road 3 78.85 75.97 772.94 78.85 75.97 772.94 78.85 75.97 772.94

Off-Road 3, 4 73.55 6.05 53.25 73.55 6.05 53.25 73.55 6.05 53.25

Area 3 36.35 528.99 134.59 36.35 528.99 134.59 36.35 528.99 134.59

Totals 556.85 932.73 2208.65 558.88 916.62 2263.31 568.98 921.27 2261.76 Notes: 1. Point source emissions are based on non-startup Wednesday ARD emissions and average non-zero tank landing emissions 2. On-road emissions are season- (school or summer) and year-specific emissions 3. Non-road, off-road and area emis sions are year-specific OSD emissions

4. Off-road emissions consist of air port, locomotive, and marine emissions 5. VOC is reported as sum of CB05 species3-23 3.4.3 2006 Baseline In general, the baseline modeling emissions are based on typical ozone season emissions, whereas the base case modeling emissions are episode day-specific. The biogenic emissions are an exception in that the same episode day-specific em issions are used in the 2006 baseline and base cases. In addition, the 2006 baseline non- and off-road and area source modeling emissions are the same as used for the 2006 base case episodes, since they are based on typical ozone season

emissions. No fire emissions were included in the 2006 baseline.

3.4.3.1 Point Sources For the non-ARD point sources, the 2006 baseline emissions are the same as the modeling emissions used for the June 2006 (bc06ep0) an d the bc06aqs2 episodes. The 2006 baseline ARD sources EGUs emissions were estimated using th e average of the 2006 third quarter hourly ARD emissions. The 2006 baseline tank landing emissi ons were estimated as the average of the tank landing emissions for those 2006 episode days with non-zero emissions. The HRVOC emissions reconciliation developed for the 2006 base cases was used for the 2006 baseline. For the Gulf of Mexico, Canada, and Mexico, the 2006 baselin e uses the same emissions as the base cases.

3.4.3.2 On-Road Mobile Sources

The 2006 baseline on-road mobile source emissi ons are the same as used for the June 2006 (bc06ep0) base case episode. These are the summer season modeling emissions for each of the day types, weekday, Friday, Saturday, and Sunday.

3.4.4 2018 Future Base and Control Strategy The biogenic emissions used for the 2018 future base and control strategy modeling are the same episode day-specific emissions used in the base cases. In addition, similar to the 2006 baseline, no fire emissions were included in the 2018 future base and control strategy modeling.

3.4.4.1 Point Sources

Outside Texas The non-ARD point source emissions data in th e regions outside Texas were obtained from the 2018 CENRAP/RPO regional haze SIP. For the Gulf, Canada, and Mexico, the 2018 emissions are
the same as used in the 2006 baseline. The CAIR Phase 2 emission levels were used for the EGU 2018 emissions, with an adjustment for the ozone season. The ozone season adjustment was developed using the ratio of the average of the 2006 third quarter hourly ARD emissions to the annual average ARD emissions.

Within Texas Emissions for the non-ARD point sources were projected to 2018 using the larger of the Texas Industrial Production Index (TIPI) or Texas-specific REMI EGAS growth factors (or banked Emissions Reduction Credits and Discrete Emissions Reduction Credits in nonattainment areas). Controls pertinent to existing HGB, DFW, and BP A SIP revisions were applied to appropriate point source categories (e.g., Mass Emissions Cap and Trade program (MECT), HRVOC Emissions Cap and Trade program (HECT), and Ea st Texas Combustion Rule). The 2018 future base emissions for HECT-applicable point sources in Harris County used their HECT allocations. The 2018 control strategy includes a 25 percent reduction (2.69 tpd) to the HECT cap for applicable point sources in Harris County.

Similar to the 2018 emissions for ARD sources outsi de Texas, the ARD sources within Texas used the CAIR Phase 2 emissions adjusted to the oz one season, with the exception of ARD sources in the eight-county HGB area, which are subject to the MECT rule. The 2018 emissions for ARD

sources within the HGB area used the MECT alloca tions adjusted to the ozone season, similar to the adjustment for the ARD sources in the non- HGB area. Newly-permitted ARD sources were limited to the CAIR 9.5 percent set-aside for gr owth. The 2018 tank landing emissions were the3-24 same as the 2006 baseline, but the HRVOC reconciliation was reduced by the amount in Harris County associated with HECT applicable source categories.

For the eight-county HGB area, the point source NO X emissions are reduced by about 5 percent from the 2006 baseline (172.16 tpd) to the 2018 future base (162.75 tpd) and the VOC emissions are increased about 48 percent from the 2006 baseline (208.34 tpd) to the 2018 future base (309.46 tpd). The 25 percent HECT control strategy reduces the 2018 control strategy VOC emissions to 306.75 tpd.

3.4.4.2 On-Road Mobile Sources

Outside Texas The TCEQ used the EPA’s NMIM to generate average summer weekday mobile source emissions by county for 2018 for all of the states beyond Texas. Average summer Friday, Saturday, and Sunday mobile source emissions were estimated using the weekday to Friday, Saturday, and Sunday ratios developed for the on-road m obile source emissions within Texas.

Within TexasFor the Texas counties outside of the HGB and BPA areas, summer season, day type, non-link onroad emissions were developed by TTI usin g 2018 projected traffic data and the EPA’s MOBILE6.2. For the eight-county HGB and thre e-county BPA (Jefferson, Hardin, and Orange) areas, link-based on-road emissions were developed by TTI using the TDM output projected for 2018, and the EPA’s MOBILE6.2 on-road mobile source emissions model to generate average summer season on-road emissions for the four day t ypes. The 2018 control strategy includes a 1.55 tpd Voluntary Mobile Emission Reduction Program (VMEP) NO X reduction to the on-road mobile sources for alternative commuting, vehicle retrof it and replacement, and traffic flow improvement

measures.

For the eight-county HGB area, the on-road mobile source NO X emissions are reduced by about 74 percent from the 2006 baseline (197.28 tpd) to the 2018 future base (50.76 tpd) and the VOC emissions are decreased about 49 percent from th e 2006 baseline (99.39 tpd) to the 2018 future base (50.39 tpd). The VMEP control strategies reduce the 2018 control strategy NO X emissions to 49.21 tpd.

3.4.4.3 Non- and Off-Road Mobile Sources

Outside Texas For the states outside of Texas, the TCEQ u sed the EPA’s NMIM to generate average summer weekday non-road mobile source category emissions by county for 2018. For the off-road mobile source categories, aircraft, locomotive, and marine , in the states beyond Texas, the TCEQ used the EPA’s 2002 NEI with EGAS5 growth factors and na tional controls for locomotives and marine vessels to generate 2018 average summer weekday off-road mobile source category emissions. Summer weekend day emissions for the non- and off-road mobile source categories were developed as part of the EPS3 processing usi ng category specific weekly activity profiles.

Within Texas The TCEQ used the TexN model to generate av erage summer weekday non-road mobile source category emissions by county for 2018. 2018 coun ty-level off-road emissions were estimated by adjusting the 2005 TexAER emissions with the Te xas-specific REMI-EGAS growth factors, except for the aircraft/airport emissions in the HGB and DFW areas and marine vessels in HGB and BPA. The 2018 aircraft/airport emissions in the HGB and DFW areas were provided through a stakeholder process and these emissions are airport- specific rather than county-level. The 2018

emissions for marine vessels in HGB and BPA we re developed using emission trends provided by the HGB and BPA Port Authorities (Starcrest, 2000) . Summer weekend day emissions for the nonand off-road mobile source cate gories were developed as part of the EPS3 processing using category specific weekly activity profiles.3-25 For the eight-county HGB area, the non- and off-road mobile source NO X emissions are reduced by about 20 percent from the 2006 baseline (152.40 tpd) to the 2018 future base (121.37 tpd) and the VOC emissions are decreased about 19 percent from the 2006 baseline (82.02 tpd) to the 2018 future base (66.49 tpd). The 2018 control strategy includes 0.70 tpd NO X reduction to non-road

VMEP measures.

3.4.4.4 Area Sources
Outside Texas The TCEQ obtained emissions data used in the 2018 regional haze SIP revision that was created by the CENRAP/RPO for all the states beyond Texas.

Within Texas The 2018 county-level area source emissions were estimated by adjusting the 2005 TexAER emissions with the Texas-specific REMI-EGAS growth factors, except for the flash emissions category. Flash emissions will be controlled in the future as a result of the Storage Vessel and Degassing rule (30 Texas Administrative Code (TAC ) Chapter 115), so no growth was applied and

the same emissions were used for the 2018 futu re base and control strategy as the 2006 baseline.

For the eight-county HGB area, the area source NO X emissions are increased by about 16 percent from the 2006 baseline (36.35 tpd) to the 2018 future base (42.04 tpd) and the VOC emissions are increased about 23 percent from the 2006 baseline (528.99 tpd) to the 2018 future base (650.09 tpd).

3.4.5 2006 and 2018 Modeling Emissions Summary for HGB

Table 3-13: Summary of 2006 Baseline and 2018 Future Base, and 2018 Control Strategy Anthropogenic Modeling Emissions for HGB summarizes the typical weekday anthropogenic emissions in the eight-county HGB area by source ty pe for the 2006 and 2018 future base modeling emissions as well as the 2018 control strategy.

Table 3-13: Summary of 2006 Baseline and 2018 Future Base, and 2018 Control Strategy Anthropogenic Modeling Emissions for HGB

2006 Baseline 2018 Baseline 2018 Control Strategy

NO X VOC CO NO X VOC CO NO X VOC CO Source Type (tpd) (tpd) (tpd)

Point 172.16 208.34 126.22 162.75 309.46 182.10 162.75 306.77 182.10

On-Road 197.28 99.39 1115.23 50.76 50.39 733.17 49.21 50.39 733.17

Non -Road 78.85 75.97 772.94 35.65 59.56 893.84 34.95 59.56 893.84

Off-Road 73.55 6.05 53.25 85.72 6.93 44.71 85.72 6.93 44.71

Area 36.35 528.99 134.59 42.04 650.09 158.99 42.04 650.09 158.99

Totals 558.19 918.74 2202.23 376.92 1076.43 2012.81 374.67 1073.74 2012.81

Figure 3-10: 2006 Baseline and 2018 Future Base, and 2018 Control Strategy Anthropogenic NO X and VOC Modeling Emissions for HGB graphically compares the anthropogenic NO X and VOC modeling emissions for the eight-county HGB area.3-26 2006 Baseline and 2018 Future Anthropogenic NO X Modeling Emissions HGB Eight-County Area

172 163 163 197

51 48 152

121 121 36

42 42

0 100 200 300 400 500 600

2006BL 2018FY 2018CSNOXEmissions (TPD) Area

Non-Road

On-Road

Points Total NO X = 557 tpd

Total NO X = 377 tpd Total NO X = 374 tpd

2006 Baseline and 2018 Future Anthropogenic VOC Modeling Emissions HGB Eight-County Area

208 311 308 99 50 50 82 66 66 529 650 650

0 200 400 600 800 1000 1200

2006BL 2018FY 2018CSVOC Emissions (TPD) Area

Non-Road

On-Road

Points Total VOC = 918tpd Total VOC = 1077 tpd Total VOC = 1074 tpd

Figure 3-10: 2006 Baseline and 2018 Future Base, and 2018 Control Strategy Anthropogenic
NO X and VOC Modeling Emissions for HGB

Notes: 2006BL = 2006 Baseline

2018FY = 2018 Future Year or Future Base 2018CS = 2018 Control Strategy In the above figures, Non-Road includes the off-road emissions

3.5 PHOTOCHEMICAL MODELING To ensure that a modeling study can be successfully used as technical support for an attainment demonstration SIP revision, the air quality model mu st be scientifically sound and appropriate for the intended application and freely accessible to all stakeholders. In a regulato ry environment, it is crucial that oversight groups (e.g., the EPA), th e regulated community, and the interested public

have access to and also be convinced of the suitability of the model. The following three prerequisites were identified for selecting the air quality model to be used in the HGB attainment

demonstration:3-27 • must have a reasonably current, peer-reviewed, scientific formulation;

• must be available at no or low cost to stakeholders; and

• must be consistent with air quality models being used for other Texas nonattainment or

near nonattainment areas.

The only model to meet all three of these criteria is CAMx. The model is based on wellestablished treatments of advection, diffusion, de position, and chemistry. Another important

feature is that NO X emissions from large point sources can be treated with the PiG submodel, which helps avoid the artificial diffusion that o ccurs when point source emissions are introduced into a grid volume. The model software and th e CAMx user's guide are publicly available at http://www.camx.com (Environ, 2009). In addition, the TCEQ has many years of experience with CAMx. CAMx was used for the modeling con ducted in the DFW and BPA nonattainment areas, as well as for modeling being conducted in other areas of Texas (e.g., San Antonio).

CAMx Version 4.53 was used for this modeling study. Some of the features in this version include the ability to process in parallel on multiple pr ocessors and the following probing tools for sensitivity analysis:

• Process Analysis, which provides in depth details of ozone formation, showing the various physical and chemical processes that determ ine the modeled ozone concentrations at specified locations and times;

• Ozone Source Apportionment Technology (OSAT), which estimates the contribution of emissions from multiple geographical areas and source categories to ozone formation (including biogenic emissions); and

• Anthropogenic Precursor Culpability Asse ssment (APCA), which reallocates ozone apportioned to non-controllable biogenic emissions to the controllable portion of precursors that participated in ozone formation.

3.5.1 Modeling Domains and Horizontal Grid Cell Size Figure 3-11: CAMx Modeling Domains depicts the modeling domains used in CAMx. The horizontal configuration of the CAMx modeling domains consist of a 2 km x 2 km grid (2 km) encompassing a major portion of the HGB nonattainment counties (red box), nested within a 4 km x 4 km grid (4 km) encompassing both the HGB an d BPA counties (blue box), nested within a 12 km x 12 km grid (12 km) covering the eastern part of Texas (green box), nested within the outer (black box) 36 km x 36 km grid (36km). The 36 km outer domain was selected to minimize the effect of boundary conditions on pr edicted ozone concentrations.3-28 Figure 3-11: CAMx Modeling Domains

All grids align with the grid developed by th e EPA for nationwide modeling for regional haze and particulate matter. Choosing a grid system compatible with an existing large-scale grid system serves several functions, including ability to u se ready-made regional inventory data directly, ability to integrate the TCEQ’s modeling into regional modeling projects, and promoting consistency among various regional and urban modeling applications in the central United States.

A finer resolution subdomain within the 4 km HGB-BPA domain better replicates the emission gradients in the narrow industrial plumes emana ting from the Ship Channel and surrounding areas.3-29 3.5.2 Vertical Layer Structure The vertical configuration of the CAMx modeling domains consists of 28 layers of varying depth used with the 2 km and 4 km domains, and 17 laye rs of varying depth used with the 12 km and 36 km horizontal domains. The unique meteorology induced by the land/sea/bay effects and the diverse mixture of industrial source types, wh ich release pollutants across a wide range of elevations, require more vertical layers, particular ly near ground level, in the fine-grid domains.

Table 3-14: CAMx Vertical Layer Structure for 2 km and 4 km Fine Grids and Table 3-15: CAMx Vertical Layer Structure for Intermediate and Coarse Grids show the vertical structuring of the 28- layered and 17-layered configurations, respectively.

Table 3-14: CAMx Vertical Layer Structure for 2 km and 4 km Fine Grids CAMx Layer MM5 Layer Top (m AGL 1 ) Center (m AGL 1 ) Thickness (m)

28 38 15179.1 13637.9 3082.5

27 36 12096.6 10631.6 2930.0

26 32 9166.6 8063.8 2205.7

25 29 6960.9 6398.4 1125.0

24 27 5835.9 5367 937

23 25 4898 4502.2 791.6

22 23 4106.4 3739.9 733

21 21 3373.5 3199.9 347.2

20 20 3026.3 2858.3 335.9

19 19 2690.4 2528.3 324.3

18 18 2366.1 2234.7 262.8

17 17 2103.3 1975.2 256.2

16 16 1847.2 1722.2 256.3

15 15 1597.3 1475.3 249.9

14 14 1353.4 1281.6 243.9

13 13 1209.8 1139 143.6

12 12 1068.2 998.3 141.6

11 11 928.5 859.5 137.8

10 10 790.6 745.2 90.9

9 9 699.7 654.7 90.1

8 8 609.5 564.9 89.3

7 7 520.2 476.0 88.5

6 6 431.7 387.8 87.8

5 5 343.9 300.4 87.0

4 4 256.9 213.7 86.3

3 3 170.5 127.7 85.6

2 2 84.9 59.4 51.0

1 1 33.9 16.9 33.9 Note: 1. AGL - Above ground level.3-30 Table 3-15: CAMx Vertical Layer Struct ure for Intermediate and Coarse Grids CAMx Layer MM5 Layer Top (m AGL) Center (m AGL) Thickness (m)

17 38 15179.1 12172.9 6012.5

16 32 9166.6 7501.3 3330.7

15 27 5835.9 4970.9 1730

14 23 4105.9 3565.9 1080

13 20 3025.9 2564.5 922.9

12 17 2103 1728.1 749.8

11 14 1353.2 1210.6 285.2

10 12 1068.2 929.3 277.5

9 10 790.6 700.0 181.0

8 8 609.5 564.9 89.3

7 7 520.2 476.0 88.5

6 6 431.7 387.8 87.8

5 5 343.9 300.4 87.0

4 4 256.9 213.7 86.3

3 3 170.5 127.7 85.6

2 2 84.9 59.4 51.0

1 1 33.9 16.9 33.9

3.5.3 Model Configuration The TCEQ used CAMx version 4.53, which includes a number of upgrades and features from previous versions. The following CAMx 4.53 options were employed:

• Parallel processing of the chemis try and transport algorithms;

• CB05 chemical mechanism with Euler Back ward Iterative (EBI) chemistry solver;

• Piecewise Parabolic Method (PPM) advection solver;

• Flexi-nesting to interpolate the 4 km meteorological parameters to the 2 km CAMx domain; and

• PiG treatment of larger point sources of NO X using the Greatly Reduced Execution and Simplified Dynamics (GREASD) Lagrangian module.

In addition to the CAMx inputs developed from the meteorological and emissions modeling, inputs are needed for initial and boundary conditions, spatially resolved su rface characteristic parameters, spatially resolved albedo/haze/ozone (i.e., opac ity) and photolysis rates, and a chemistry parameters file.

The TCEQ contracted with Environ (Environ, 20 08b) who worked with National Aeronautics and Space Administration (NASA) Jet Propulsion Laboratory (JPL) to derive episode-specific boundary conditions from the Model for Ozone a nd Related Chemical Tracers (MOZART) global air quality model. Boundary conditions were deve loped for each grid cell along all four edges of the 36 km domain (number of horizontal grid cells [69 or 67 for east-west or north-south edges, respectively] times the number of vertical layers [17]) for each episode hour. This work also produced initial conditions for each of the episod es. The TCEQ used these episode-specific initial and boundary conditions for this modeling study. The top-boundary conditions were set at the clean concentration levels as previously derived by Environ and used in the recently approved

DFW Ozone Attainment Demonstr ation SIP revision (TCEQ, 2007).

Surface characteristic parameters, including roughn ess, vegetative distri bution, and water/land boundaries, are input to CAMx via a land-use f ile. The land-use file provides the fractional contribution (0 to 1) of eleven land-use categories, as defined by the United States Geological Survey (USGS) LULC database. For the 36 km and 12 km domains, the TCEQ used the land-use files developed by Environ for the DFW SIP re vision approved by the EPA in 2009, which were3-31 derived from the most recent USGS LULC database . For the 2 km domain and portions of the 4 km domain, in the vicinity of HGB, the TCEQ used updated land-use files developed by Texas A&M University (Popescu et al., 2008), which were derived from more highly resolved LULC data collected by the Texas Forest Service and the UT-CSR.

The spatially-resolved opacity and photolysis rates are input to CAMx via a photolysis rates file and an opacity file, which are specific to the ch emistry parameters file for the CB05 mechanism, which is also input to CAMx. The TCEQ used episode-specific satellite data from the Total Ozone Mapping Spectrometer (TOMS) to prepare the photolysis rates and opacity files.

3.5.4 Model Performance Evaluation The CAMx model configuration was applied to the 2005 and 2006 base cases using the episodespecific meteorological parameters and emissions. The CAMx modeling results were compared to the measured ozone and ozone precursor concentra tions, which resulted in a number of modeling iterations involving improvements to the meteor ological and emissions m odeling and subsequent CAMx modeling. A detailed performance evalua tion for each of the 2005 and 2006 base case modeling episodes is included in Appendix C: CAMx Modeling for the HGB Attainment

Demonstration SIP . In addition, all performance evalua tion products are available on the TCEQ FTP site (TCEQ, 2009).

3.5.4.1 Performance Evaluations Overview The performance evaluation of the base case modelin g demonstrates the adequacy of the model to correctly replicate the relationship between levels of ozone and the emissions of NO X and VOC. The model’s ability to suitably replicate this re lationship is necessary to have confidence in the model’s prediction of the response of ozone to various control measures. As recommended in the EPA modeling guidance, the TCEQ conducted two types of performance evaluations, operational and diagnostic.

3.5.4.2 Operational Evaluations Statistical measures including the Unpaired Peak Accuracy (UPA), the Mean Normalized Bias (MNB), and the Mean Normalized Gross Error (MNGE) were calculated by comparing measured and bi-linearly interpolated modeled ozone con centrations for all episode days and regulatorymonitors. Graphical measures including time series and scatter plots of hourly measured and bilinearly interpolated modeled ozone and where a pplicable, some ozone precursors (e.g., nitric oxide (NO), nitrogen dioxide (NO 2 ), ETH, and CO) concentrati ons were developed for each regulatory monitor. In addition, tile plot s of modeled daily maximum eight-hour ozone concentrations were developed and overlaid with the measured daily maximum eight-hour ozone concentrations. Detailed operati onal evaluations for each of the 2005 and 2006 base case modeling episodes are included in Appendix C: CAMx Modeling for the HGB Attainment Demonstration SIP

.

Statistical Evaluations The statistical evaluations presented focus on the comparison of the measured and modeled eighthour ozone concentrations. Figure 3-12.a: Peak Eight-Hour Ozone Concentration, Measured versus Modeled for the 2005 Episode Days and Figure 3-12.b: Peak Eight-Hour Ozone Concentration, Measured versus M odeled for the 2006 Episode Days compare the measured and modeled peak eight-hour ozone c oncentrations for each episode day of the 2005 and 2006 base cases, respectively. Figure 3-13.a: Mean Normalized Gross Error (MNGE) and Bias (MNB) for 2005 Episode Days and Figure 3-13.b: Mean Normalized Gross Error (MNGE) and Bias (MNB) for 2006 Episode Days show the MNGE and MNB for monitored eight-hour ozone concentrations greater than 40 ppb for each episode day of th e 2005 and 2006 base cases, respectively. Although there are no recommended criteria for the eight-hour UPA, MNGE, and MNB, the one-hour levels recommended by the EPA (i.e., plus or minus 20 percent, 30 percent, and plus or minus 15 percent, respectively) were used for statistical evaluations.3-32 The error bars on the daily peak measured eight -hour ozone concentrati ons, in Figures 3-12.a: Peak Eight-Hour Ozone Concentration, Measured versus Modeled for the 2005 Episode Days and 3-

12.b: Peak Eight-Hour Ozone Concen tration, Measured versus Modeled for the 2006 Episode Days represent the plus or minus 20 percent UPA range for comparison with the daily peak modeled eight-hour ozone concentr ations. For the 37 episode da ys in the 2005 base cases, only seven days have daily peak modeled eight-hour ozon e concentrations greater than 20 percent of the daily peak measured eight-hour ozone concentrations . For the 50 episode days in the 2006 base cases only ten days have daily peak modeled eight-hour ozone concentrations outside the plus or

minus 20 percent UPA range.3-33 June 19 - 29, 2005 (bc05ep1)

0 20 40 60 80 100 120 140 160

6 / 1 9 / 2 0 0 5 6/20/2 0 0 5

6 / 2 1 /2005

6/ 2 2 / 2 0 0 5 6/23/2005

6 / 2 4 / 2 0 0 5 6/25/2 0 0 5

6 / 2 6 /2005

6/ 2 7 / 2 0 0 5

6 / 28/2005

6 / 2 9 / 2 0 0 5



### Episode DayOzone (ppb) Peak Measured
Reg10 Peak Modeled

Ozone NAAQS

July 28 - August 8, 2005 (bc05ep2)

0 20 40 60 80 100 120 140 160

7 / 2 8 / 2 0 0 5 7/29/2005

7/ 3 0 / 2 0 0 5

7 / 31/2005

8 / 1 /2005

8 / 2/

2 0 0 5

8/ 3 /2005

8 / 4/

2 0 0 5

8/ 5 /2005

8 / 6/

2 0 0 5 8/7/2005

8 / 8 /2

0 0 5



### Episode DayOzone (ppb) Peak Measured
Reg10 Peak Modeled

Ozone NAAQS May 20 - June 2, 2005 (bc05ep0)

0 20 40 60 80 100 120 140 160

5/20/2005

5 /21/

2 0 0 5

5

/2

2 / 2 0 0 5

5/ 2 3 / 2005 5/24/2005

5 /25/

2 0 0 5

5

/2

6 / 2 0 0 5

5/ 2 7 / 2005 5/28/2005

5 /29/

2 0 0 5

5

/3

0 / 2 0 0 5

5/ 3 1 / 2005 6/1/2005 6/2 / 2 0 05



### Episode DayOzone (ppb) Peak Measured
Reg10 Peak Modeled

Ozone NAAQS

Figure 3-12.a: Peak Eight-Hour Ozone Concentration, Measured versus Modeled for the 2005 Episode Days3-34 June 2 - June 15, 2006 (bc06ep0)

0 20 40 60 80 100 120 140 160

6 /2/2006

6 /3

/ 2 0 0 6

6/ 4 /20

0 6 6/5/2006

6 /6/2006

6 /7

/ 2 0 0 6

6/ 8 /20

0 6 6/9/2006

6/ 1 0 / 2006

6 / 1 1 /2

0 0 6

6

/ 12/2

0 0 6 6/13/2006

6/ 1 4 / 2006

6 / 1 5 /2

0 0 6



### Episode DayOzone (ppb) Peak Measured
Reg10 Peak Modeled

Ozone NAAQS

August 15 - September 14, 2006 (bc06aqs1)

0 20 40 60 80 100 120 140 160

8 / 15/2

0 0 6

8 / 1 6 /2

0 0 6

8/

1 7 / 2006

8/18/2006 8/19/2 0 06

8 / 20/2 0 0 6

8 / 2 1 /2

0 0 6

8 / 2 2 / 2006

8/

2 9 / 2006

8/30/2006

8 / 31/2 0 0 6

9 /1

/ 2 0 0 6

9 /2/2

0 0 6

9 /3/2006 9/4/2006

9/

5 /2006

9/

6 /20

0 6

9 /7

/ 2 0 0 6

9 /8/2

0 0 6

9/

1 2 / 2006

9/13/2006

9 / 14/2

0 0 6



### Episode DayOzone (ppb) Peak Measured
Reg10 Peak Modeled

Ozone NAAQS

September 19 - October 11, 2006 (bc06aqs2)

0 20 40 60 80 100 120 140 160

9 /1

9 / 2 0 0 6

9/ 2 0 / 2006 9/25/2006

9 /26/

2 0 0 6

9/ 2 7 / 2 0 0 6

10 / 3/2006

1 0/4/

2 0 0 6

1 0/

5 / 2 0 0 6

10 / 6 / 2006

1 0/7/2006

1 0/

8 / 2 0 0 6

10 / 9 / 2006 10/10/2006

1 0 / 1 1 /200 6



### Episode DayOzone (ppb) Peak Measured
Reg10 Peak Modeled

Ozone NAAQS

Figure 3-12.b: Peak Eight-Hour Ozone Concentration, Measured versus Modeled for the 2006 Episode Days

Taking into consideration that only 17 days out of the 87 days modeled in the 2005 and 2006 base case episodes have daily peak modeled eight-hour ozone concentrations outside the plus or minus 20 percent UPA range, the model suitably predicts the daily peak eight-hour ozone concentrations.3-35 The area depicted in Figures 3-12.a: Mean Normalized Gross Error (MNGE) and Bias (MNB) for 2005 Episode Days and 3-12.b: Mean Normalized Gross Error (MNGE) and Bias (MNB) for 2006 Episode Days with MNGE < 30 percent and MNB < plus or minus 15 percent represents the joint
condition for which both the MNGE and MNB are within acceptable ranges. The episode days labeled in red indicate those days for which dail y peak measured eight-hour ozone concentrations were greater than or equal to 80 ppb.

For the 31 days of the 2005 base case episodes with daily peak measured eight-hour ozone concentrations greater than or equal to 80 ppb 19 days meet the joint condition of having both the

MNGE < 30 percent and MNB < plus or minus 15 percent. The average peak monitored ozone for those 31 days was 93.9 ppb, and the corresponding average peak modeled ozone concentration was 101.1 ppb. The average mean normalized bias an d mean normalized gross error were 11.4 and 19.0 percent, respectively.

For the 36 days of the 2006 base case episodes with daily peak measured eight-hour ozone concentrations greater than or equal to 80 ppb, 24 days meet the joint condition of having both the

MNGE < 30 percent and MNB < plus or minus 15 percent. The average peak monitored ozone for those 36 days was 96.9 ppb, and the corresponding average peak modeled ozone concentration was 95.1 ppb. The average mean normalized bias and normalized gross error were 8.8 and 16.9 percent, respectively.

Taking into consideration that 43 days out of th e 67 episode days in the 2005 and 2006 base cases with daily peak measured eight-hour ozone concen tration greater than or equal to 80 ppb meet the joint condition of having both the MNGE < 30 percent and MNB < plus or minus 15 percent, the model suitably predicts the temporal pattern of da ily eight-hour ozone concentrations at the various

monitors.May 20 - June 2, 2005 (bc05ep0)3-36Figure 3-13.a: Mean Normalized Gross Error (MNGE) and Bias (MNB) for2005 Episode Daysed Gro5/205/215/2235/255/265/275/316/125/5/26/245/285/295/30015304560-60 -45 -30 -15 0 15 30 45 60MNB (%)

MNGE (%)June 19 - 29, 2005 (bc05ep1)6/196/206/216/226/236/246/256/266/276/26/298015304560-60 -45 -30 -15 0 15 30 45 60MNB (%)

MNGE (%)July 28 - August 8, 2005 (bc05ep2)7/31015304560-60 -45 -30 -15 0 15 30 45 60MNB (%)

MNGE (%)7/287/297/308/18/28/38/58/68/78/88/43-37Figure 3-13.b: Mean Normalized Gross Error (MNGE) and Bias (MNB) for2006 Episode Dayszed Gross Error (MNGE) and Bias (MNB) forAugust 15 - September 14, 2006 (bc06aqs1)8/168/18/8/308/319/19/69/79/1348/192947189/239/9/89/18/158/208/218/228/9/9/59/12015304560-60 -45 -30 -15 0 15 30 45 60MNB (%)

MNGE (%)June 2 - June 15, 2006 (bc06ep0)6/26/36/46/56/66/76/86/96/106/116/126/136/146/15015304560-60 -45 -30 -15 0 15 30 45 60MNB (%)

MNGE (%)September 19 - October 11, 2006 (bc06aqs2)26710/510/7119/1910/310/910/10015304560-60 -45 -30 -15 0 15 30 45 60MNB (%)

MNGE (%)9/209/9/210/410/610/810/9/253-38 Graphical Evaluations A detailed graphical evaluation of modeling results is presented in Appendix C: CAMx Modeling for the HGB Attainment Demonstration SIP . A selection of graphical evaluations, organized by episode modeled, is presented in this section.

For each of the 2005 and 2006 base case episodes, time series comparing hourly measured (reddots) and modeled (blue line) ozone concentrations are shown for three monitors in the eightcounty HGB area. The monitors presented vary by episode and were selected on the basis of ozone measured. Included on the time-series gr aphic is the modeled maximum and minimum hourly ozone concentration within the 7 x 7 grid cell array around the monitor (green shading). Additionally, time series comparing hourly me asured and modeled ozone concentrations are shown for two or three rural monitors (GRVL and LACT, and SAGA, which was not in operation during bc05ep0 and bc05ep1). Figure 3-14: TexAQS II Monitoring Sites Outside HGB/BPA is a map of rural monitors.



### Site

Code Site Name

GRVL Greenville, NW of

Dallas

CLEB Cleburne, SW of Fort

Worth

LACT Livingston, NW of

Houston

BEVL Beeville, NW of Corpus Christi

CLVL Clarksville, eastern
TX-OK border

NTRD Newton, SouthCentral TX-LA

Border

PLTN Palestine, Central

East Texas

SAGA San Augustine,
Central TX-LA

Border

WMBA Wamba, Near

Texarkana

HTVL Halletsville, N of

Victoria

ITHS Italy, S of Dallas

PTOC Port O'Connor,
Middle TX Coast

TMPL Near Temple

Figure 3-14: TexAQS II Monitoring Sites Outside HGB/BPA

Also included for each of the episodes are loga rithmically-scaled scatter plots comparing the hourly measured and modeled concentrations of ozone (O 3 ), NO X , ETH, and olefins (OLE). Monitor sites included in the graphical representa tion were the three monitors with the highest daily maximum monitored eight-hour ozone concentrations. If one of the top three sites did not also have an auto-GC, the third highest ozone monitoring site was replaced by the auto-GC site measuring the highest ozone. OLE is a CAMx chemical surrogate representing olefinic VOC, such as propylene, but excluding ethylene and certain compounds known as internal olefins such3-39 as butenes (internal olefins are represented in CB05 by the surrogate species IOLE). Both ethylene and propylene are HRVOC and their emi ssions were adjusted in the base case modeling by the emissions reconciliation discussed previously in Section 3.4: Emissions Modeling

. Included on the scatter plots is the measured vers us modeled Quantile-Quantile (QQ) plot, which first sorts independently both the measured and modeled concentrations, then plots the sorted values together. QQ plot data, shown as red dots, provide a measure of how close the modeled

and measured distributions of values are to each ot her. If the red dots lie close to the diagonal one-to-one line, the model generates the corr ect proportions of small, medium, and large

concentration values.

Tile plots of the of the daily peak modeled eight-hour ozone concentrations are shown for selected episode days on which several monito rs measured maximum daily eight-hour ozone concentrations greater than 84 ppb. Include d on the tile plots are the monitor locations represented by small circles, color coded for the me asured ozone concentration. The same scale

is used for the measured and modeled maxi mum daily eight-hour ozone concentrations.

Bc05ep0: May 19 through June 3, 2005 For the bc05ep0 episode, hourly time series are presented for the Conroe Relocated (CNR2; CAMS 78), Northwest Harris County (HNWA; CAMS 26), and Wallisville Road (WALV; CAMS 617) 1 monitors in Figure 3-15: Time Series of Hourly Ozone Concentrations for Episode bc05ep0 at the CNR2, HNWA, and WALV Monitors . In general, the modeled ozone concentrations, including the 7 x 7 cell maximum- minimum range, replicate the diurnal pattern of

the observations. The lower ozone concentrati ons measured during the early morning hours, especially at the Conroe Relocated monitor, a nd the very highest ozone concentrations, for example, Northwest Harris County, May 27, 2005 , were less well replicated. The unfavorable comparison between the measured and modeled hourly ozone concentrations during the early morning hours at the Conroe Relocated monito r is likely due to local factors, such as NO X emissions and low wind speed meteorological c onditions, which reduces the areal representation of the monitor to much less than the 4 km gr id cell size on which the modeled concentration is simulated. Thus, this disparity is not necessar ily an indication of poor model performance since local factors may create greater ozone gradients.

1 Note that CAMS 617 is a non-regulatory monitor.3-40 Figure 3-15: Time Series of Hourly Ozone Concentrations for Episode bc05ep0 at the CNR2, HNWA, and WALV Monitors Note: WALV is a non-regulatory monitor.

Figure 3-16: Time Series of Hourly Ozone Concentra tions for Episode bc05ep0 at the GRVL and
LACT Rural Monitors provides a comparison of measured and modeled hourly ozone

concentrations at rural monitors. Modeled concen trations generally replicate the diurnal pattern of the observations, except for the latter part of the episode in the rural region represented by the LACT monitor, for which the modeled concentrati ons are relatively constant throughout the day. The lower ozone concentrations measured during the early morning hours on some days and not replicated by the model are likely due to loca lized emissions and meteorology limiting the areal representation of the monitors as described prev iously. Overall, modeled and measured rural concentrations compare favorably, and modeled rural concentrations are unlikely to cause any substantial predictive bias within the HGB area during this episode.3-41 Figure 3-16: Time Series of Hourly Ozone Concentrations for Episode bc05ep0 at the
GRVL and LACT Rural Monitors3-42 Scatter plots for the bc05ep0 episode comparing the hourly measured and modeled concentrations at the Wallisville Road (CAMS 617) monitor (non-regulatory monitor) are shown in Figure 3-17: Scatter Plots of Hourly Ozone, NO X , ETH, and OLE at the WALV Monitor for the bc05ep0 Episode. The model tends to over-predict ozone at the lower measured concentrations (less than 60 ppb), but compares favorably at the higher ozon e concentrations. Conversely, the model tends to under-predict the NO X at the lower measured concentrations, but compares favorably at the higher NO X concentrations. The rank correlation QQ plot for ETH is quite favorable, although there is notable scatter in the individual hourly comparisons. The model tends to under-predict the lower and higher OLE concentrations.

Figure 3-17: Scatter Plots of Hourly Ozone, NO X , ETH, and OLE at the WALV Monitor for the bc05ep0 Episode Note: WALV is a non-regulatory monitor.3-43 Tile plots of daily maximum eight-hour ozone c oncentrations for May 27, May 31, June 1, and June 2, 2005, are shown in Figure 3-18: Tile Plots of Daily Maximum Eight-Hour Ozone Concentrations for May 27 and 31 and June 1 through 2, 2005 . The dots represent the monitored value, whereas the background color represents th e modeled results. Where a dot’s color matches the surrounding color, the model has accurately re plicated the measured ozone at that monitor. The model replicates the areas of highest eight -hour ozone for the selected days, with the exception of May 31, 2005.

Figure 3-18: Tile Plots of Daily Maximum Eight-Hour Ozone Concentrations for May 27 and 31 and June 1 through 2, 2005

Overall, the graphical evaluation of model pe rformance at key monitors on key episode days indicates the modeling adequately replicates th e features that produced high ozone during this episode.3-44 Bc05ep1: June 17 through 30, 2005 For the bc05ep1 episode, hourly time series are pres ented for the Deer Park (DRPK; CAMS 35), Houston Croquet (HCQA; CAMS 409) and Manvel Croix Park (MACP; CAMS 84) monitors in Figure 3-19: Time Series of Hourly Ozone Concentra tions for Episode bc05ep1 at the DRPK, HCQA, and MACP Monitors . In general the modeled ozone concentrations, including the 7 x 7 cell maximum-minimum range, replicate the diur nal pattern of the observations, with the exception of the lower ozone concentrations measu red during the early morning hours, especially at the Manvel Croix Park (CAMS 84) monitor.

Figure 3-19: Time Series of Hourly Ozone Concentrations for Episode bc05ep1 at the DRPK, HCQA, and MACP Monitors3-45 Figure 3-20: Time Series of Hourly Ozone Concentra tions for Episode bc05ep1 at the GRVL and
LACT Rural Monitors provides a comparison of measured and modeled hourly ozone

concentrations at rural monitors. Modeled concen trations generally replicate the diurnal pattern of the observations, with generally favorable co mparisons during the daytime. The model does not replicate the lower ozone concentrations measured on some days during the early morning hours, likely for reasons previously discu ssed. Overall, modeled and measured rural concentrations compare favorably, and modeled rural concentrations are unlikely to cause any substantial predictive bias within the HGB area during this episode.

Figure 3-20: Time Series of Hourly Ozone Concentrations for Episode bc05ep1 at the
GRVL and LACT Rural Monitors3-46 Scatter plots for the bc05ep1 episode comparing the hourly measured and modeled concentrations at the Deer Park (CAMS 35) monitor are shown in Figure 3-21: Scatter Plots of Hourly Ozone,

NO X , ETH, and OLE at the DRPK Monitor for the bc05ep1 Episode. The model tends to overpredict ozone at the lower measured concentrati ons, but compares quite favorably at the higher

ozone concentrations. The model tends to generally over-predict the NO X , especially at the lower measured concentrations. The QQ plot for ETH is quite favorable, although there is some scatter in the individual hourly comparisons. The model tends to under-predict the lower OLE concentrations and while the QQ plot shows a favorable rank correlation, there is notable scatter in the individual hourly comparisons.

Figure 3-21: Scatter Plots of Hourly Ozone, NO X , ETH, and OLE at the DRPK Monitor for the bc05ep1 Episode3-47 Tile plots of daily maximum eight-hour ozone con centrations for June 20-23, 2005, are shown in Figure 3-22: Tile Plots of Daily Maximum Eight-Hour Ozone Concentrations for June 20 through 23, 2005 . The model replicates the areas of hi ghest eight-hour ozone for the selected days quite favorably.

Figure 3-22: Tile Plots of Daily Maximum Eight-Hour Ozone Concentrations for June 20 through 23, 2005

Overall, the graphical evaluation of model pe rformance at key monitors on key episode days indicates the modeling adequately replicates th e features that produced high ozone during this episode.3-48 Bc05ep2: July 26 through August 8, 2005 For the bc05ep2 episode, hourly time series are pr esented for the Houston Bayland Park (BAYP; CAMS 53), TCEQ Houston Regional Office (HROC; CAMS 81), and Texas City (TXCT; CAMS 620) (non-regulatory monitor) monitors in Figure 3-23: Time Series of Hourly Ozone Concentrations for Episode bc 05ep2 at the BAYP, HROC, and TXCT Monitors . Relatively high ozone concentrations were measured at these monitors on several days during this episode. In general, the modeled ozone c oncentrations, including the 7 x 7 cell maximum-minimum range, replicate the diurnal pattern of the observa tions, with the exception of the lower ozone concentrations measured during the early morning ho urs, especially at the Houston Bayland Park (CAMS 53) monitor.

Figure 3-23: Time Series of Hourly Ozone Concentrations for Episode bc05ep2 at the BAYP, HROC, and TXCT Monitors Note: TXCT is a non-regulatory monitor.3-49 Figure 3-24: Time Series of Hourly Ozone Concentra tions for Episode bc05ep2 at the GRVL, LACT, and SAGA Rural Monitors provides a comparison of measured and modeled hourly ozone

concentrations at rural monitors. Modeled concen trations generally replicate the diurnal pattern of the observations, with a tendency to over-predict the peak hourly ozone concentrations during the daytime. The over-prediction at these rural m onitors appears to follow the same pattern as the over-prediction of ozone concentrations in the HGB area, especially during the latter part of the episode.

Figure 3-24: Time Series of Hourly Ozone Concentrations for Episode bc05ep2 at the GRVL, LACT, and SAGA Rural Monitors3-50 Scatter plots for the bc05ep2 episode comparing the hourly measured and modeled concentrations at the TXCT monitor (non-regulatory monitor) are shown in Figure 3-25: Scatter Plots of Hourly Ozone, NO X , ETH, and OLE at the TXCT Monitor for the bc05ep2 Episode. The model generally tends to over-predict ozone, especially at the lo wer measured concentrations. Although the QQ plot indicates a favorable rank correlation for the NO X , there is notable scatter in the individual hourly comparisons. The QQ plot for ETH indicates an even more favorable rank correlation, again with notable scatter in the individual ho urly comparisons. The model tends to underpredict the lower and higher OLE concentrations, also with considerable scatter in the individual hourly comparisons.

Figure 3-25: Scatter Plots of Hourly Ozone, NO X , ETH, and OLE at the TXCT Monitor for the bc05ep2 Episode Note: TXCT is a non-regulatory monitor.3-51 Tile plots of daily maximum eight-hour ozone c oncentrations for July 28, August 1 through 2, and August 6, 2005, are shown in Figure 3-26: Tile Plot of Daily Maximum Eight-Hour Ozone Concentrations for July 28, August 1 through 2, and August 4, 2005 . The model replicates the areas of highest eight-hour ozone for the selected days, although it over-predicts the daily maximum eight-hour ozone concentrations , especially on August 1 and 2, 2005.

Figure 3-26: Tile Plot of Daily Maximum Eight-Hour Ozone Concentrations for July 28, August 1 through 2, and August 4, 2005

Overall, the graphical evaluation of model pe rformance at key monitors on key episode days indicates the modeling only marginally replicates the features that produced high ozone during this episode.3-52 Bc06ep0: May 31 through June 15, 2006 For the bc06ep0 episode, hourly time series are presented for the TCEQ Houston Regional Office (HROC; CAMS 81), Shell Westhollow (SHWH, CAMS 410), and Wallisville (WALV; CAMS 617) (non-regulatory monitor) monitors in Figure 3-27: Time Series of Hourly Ozone Concentrations for Episode bc06ep0 at the HROC, SHWH, and WALV Monitors . Relatively high ozone concentrations were measured at these monitors on several days during this episode. In general, the modeled ozone c oncentrations, including the 7 x 7 cell maximum-minimum range, replicate the diurnal pattern of the observa tions, with the exception of the lower ozone concentrations measured during the early morn ing hours, especially at the Shell Westhollow (CAMS 410) monitor.

Figure 3-27: Time Series of Hourly Ozone Concentrations for Episode bc06ep0 at the HROC, SHWH, and WALV Monitors Note: WALV is a non-regulatory monitor.3-53 Figure 3-28: Time Series of Hourly Ozone Concentra tions for Episode bc06ep0 at the GRVL, LACT, and SAGA Rural Monitors provides a comparison of measured and modeled hourly ozone

concentrations at rural monitors. Modeled concen trations generally replicate the diurnal pattern of the observations, with generally favorable co mparisons during the daytime. The model does not replicate the lower ozone concentrations measured on some days during the early morning hours. Overall, modeled and measured rural concentrations compare favorably, and modeled rural concentrations are unlikely to cause any substantial predictive bias within the HGB area during this episode.

Figure 3-28: Time Series of Hourly Ozone Concentrations for Episode bc06ep0 at the GRVL, LACT, and SAGA Rural Monitors3-54 Scatter plots for the bc06ep0 episode comparing the hourly measured and modeled concentrations at the Wallisville Road (CAMS 617) monitor (non-regulatory monitor) are shown in Figure 3-29: Scatter Plots of Hourly Ozone, NO X , ETH, and OLE at the WALV Monitor for the bc06ep0 Episode. The model tends to over-predict ozone at the lower measured concentrations, but compares more favorably at the higher concentra tions. Conversely, the model tends to underpredict NO X at the lower measured concentrations, and slightly over-predict at the higher NO X concentrations. The QQ plot for ETH indicates a somewhat favorable rank correlation, although the model generally tends to under-predict the ETH concentrations. The model also tends to under-predict the OLE concentrations.

Figure 3-29: Scatter Plots of Hourly Ozone, NO X , ETH, and OLE at the WALV Monitor for the bc06ep0 Episode Note: WLAV is a non-regulatory monitor.3-55 Tile plots of daily maximum eight-hour ozone conc entrations for June 5, June 8 through 9, and June 14, 2006, are shown in Figure 3-30: Tile Plot of Daily Maximum Eight-Hour Ozone Concentrations for June 5, 8 through 9, and 14, 2006 . The model replicates the areas of highest eight-hour ozone for the selected days, although it somewhat under-predicts the daily maximum eight-hour ozone concentrations.

Figure 3-30: Tile Plot of Daily Maximum Eight-Hour Ozone Concentrations for June 5, 8 through 9, and 14, 2006

Overall, the graphical evaluation of model pe rformance at key monitors on key episode days indicates the modeling adequately replicates th e features that produced high ozone during this episode.3-56 Bc06aqs1: August 13 through September 15, 2006 For the bc06aqs1 episode, hourly time series are presented for the Houston Bayland Park (BAYP; CAMS 53), Houston Monroe (HSMA; CAMS 406), and Deer Park (DRPK; CAMS 35) monitors in Figure 3-31: Time Series of Hourly Ozone Concentra tions for Episode bc06aqs1 at the BAYP, DRPK, and HSMA Monitors . Relatively high ozone concentrations were measured at these monitors on several days during this episode. In general, the modele d ozone concentrations, including the 7 x 7 cell maximum-minimum ra nge, replicate the diurnal pattern of the observations, with the exception of the very highest measured hourly ozone concentrations.

Figure 3-31: Time Series of Hourly Ozone Concentrations for Episode bc06aqs1 at the BAYP, DRPK, and HSMA Monitors3-57 Figure 3-32: Time Series of Hourly Ozone Concentra tions for Episode bc06aqs1 at the GRVL, LACT, and SAGA Rural Monitors provides a comparison of measured and modeled hourly ozone

concentrations at rural monitors. Modeled concen trations generally replicate the diurnal pattern of the observations, with generally favorable comparisons during the daytime, with the exception of the region represented by the GRVL monitor on August 31 and September 1, 2006, when the higher measured ozone concentrations are notably under-predicted. In addition, the model tends to over-predict the ozone concentrations during the first segment of this episode, August 15 through 22, 2006, in the regions represented by LACT and SAGA monitors. Again, the model does not replicate the lower ozone concentrations measured on some days during the early morning hours. Overall, modeled and measured rural concentrations compare favorably enough

that the modeled rural concentrations are unlikel y to cause any substantial predictive bias within the HGB area during this episode.

Figure 3-32: Time Series of Hourly Ozone Concentrations for Episode bc06aqs1 at the GRVL, LACT, and SAGA Rural Monitors3-58 Scatter plots for the bc06aqs1 episode comp aring the hourly measured and modeled concentrations at the Deer Park (CAMS 35) monitor are shown in Figure 3-33: Scatter Plots of Hourly Ozone, NO X , ETH, and OLE at the DRPK Monitor for the bc06aqs1 Episode. The model tends to over-predict ozone at the lower measured concentrations, but compares more favorably at the higher concentrations. The model tends to generally over-predict NO X concentrations. The QQ plot for ETH indicates a somewhat favorable rank correlation, although the model tends to under-predict the higher ETH concentrations. Th e model tends to under-predict the lower range of OLE concentrations and also under-predicts the very highest.

Figure 3-33: Scatter Plots of Hourly Ozone, NO X , ETH, and OLE at the DRPK Monitor for the bc06aqs1 Episode3-59 Tile plots of daily maximum eight-hour ozone concentrations for August 17, August 31, September 1, and September 7, 2006, are shown in Figure 3-34: Tile Plot of Daily Maximum Eight-Hour Ozone Concentrations for A ugust 17 and 31, and September 1 and 7, 2006 . The model replicates the areas of highest eight-hour ozone for the selected days, although it somewhat under-predicts the daily maximum eight-hour ozone concentrations, except on August 17, 2006, when the model tends to over-predict the da ily maximum eight-hour ozone concentrations.

Figure 3-34: Tile Plot of Daily Maximum Eight-Hour Ozone Concentrations for August 17 and 31, and September 1 and 7, 2006

Overall, the graphical evaluation of model pe rformance at key monitors on key episode days indicates the modeling adequately replicates th e features that produced high ozone during this episode.3-60 Bc06aqs2: September 16 through October 11, 2006 For the bc06aqs2 episode, hourly time series are presented for the Conroe Relocated (CNR2; CAMS 78), Galveston (GALV; CAMS 34), and Deer Park (DRPK; CAMS 35) monitors in Figure 3-35: Time Series of Hourly Ozone Concentra tions for Episode bc06aqs2 at the CNR2, DRPK, and GALV Monitors . Relatively high ozone concentrations were measured at these monitors on several days during this episode. In general, the modele d ozone concentrations, including the 7 x 7 cell maximum-minimum ra nge, replicate the diurnal pattern of the observations, with the exception of the lower ozone concentrations measured during the early morning hours, especially at the Conroe Relocated (CAMS 78) monitor.

Figure 3-35: Time Series of Hourly Ozone Concentrations for Episode bc06aqs2 at the CNR2, DRPK, and GALV Monitors3-61 Figure 3-36: Time Series of Hourly Ozone Concentra tions for Episode bc06aqs2 at the GRVL, LACT, and SAGA Rural Monitors provides a comparison of measured and modeled hourly ozone

concentrations at rural monitors. Modeled concen trations generally replicate the diurnal pattern of the observations. However, the model performance in the rural areas represented by these monitors varies for the different segments of the episode. For example, during the first segment, the model notably under-predicts the peak daytime ozone concentrations at all three monitors but compares more favorably with the peak day time ozone concentrations measured during the middle portion of the third segment. Again, the model does not replicate the lower ozone concentrations measured on some days during th e early morning hours. Overall, modeled and measured rural concentrations compare favorably enough that the modeled rural concentrations are unlikely to cause any substantial predictive bias within the HGB area during this episode.

Figure 3-36: Time Series of Hourly Ozone Concentrations for Episode bc06aqs2 at the GRVL, LACT, and SAGA Rural Monitors3-62 Scatter plots for the bc06aqs2 episode comp aring the hourly measured and modeled concentrations at the Deer Park (CAMS 35) monitor are shown in Figure 3-37: Scatter Plots of Hourly Ozone, NO X , ETH, and OLE at the DRPK Monitor for the bc06aqs2 Episode. As shown, there is a favorable comparison for the mid-range and higher ozone concentrations, with a slight tendency for the model to over-predict the measured concentrations. Although the QQ plot for

NO X indicates a favorable rank correlation, the model tends to generally over-predict the NO X concentrations. The QQ plot for ETH also indi cates a favorable rank correlation, although the model tends to over-predict the lower con centrations and under-predict the higher ETH concentrations. The model tends to under-predict the lower range of OLE concentrations with considerable scatter in the higher concentrations.

Figure 3-37: Scatter Plots of Hourly Ozone, NO X , ETH, and OLE at the DRPK Monitor for the bc06aqs2 Episode3-63 Tile plots of daily maximum eight-hour ozone c oncentrations for September 20, September 27, October 6, and October 11, 2006, are shown in Figure 3-38: Tile Plot of Daily Maximum EightHour Ozone Concentrations for Sept ember 20 and 27, and October 6 and 11, 2006 . The model replicates the areas of highest eight-hour ozone for the selected days, with the exception of September 20, 2006, when the model under-predict s higher levels of daily maximum eight-hour

ozone concentrations.

Figure 3-38: Tile Plot of Daily Maximum Eight-Hour Ozone Concentrations for September 20 and 27, and October 6 and 11, 2006

Overall, the graphical evaluation of model pe rformance at key monitors on key episode days indicates the modeling adequately replicates th e features that produced high ozone during this episode.

Evaluations Based on TexAQS II Data Appendix C: CAMx Modeling for the HGB Attainment Demonstration SIP includes extensive comparisons of model predictions with observati ons collected by the many platforms employed during TexAQS II. This section provides genera l descriptions of the major sampling platforms employed and presents highlights of some of th e conclusions reached based on these comparisons.



### I n graphics comparing TexAQS II observations with modeled output, observational data are3-64 typically labeled as mixing ratios, which report moles of the pollutant per mole of ambient air. In practical terms, the term mixing ratio is synonymous with concentration.

Rural Monitoring Network The TexAQS II study included a number of additi onal monitoring sites, which began collecting

data in the summer of 2005 and continued until late October, 2006. During the TexAQS II intensive period, August 1 through October 15, 2006, a total of nine additional ozone monitors had been deployed in rural areas. Two of these additional monitors were the CLVL monitor near the Texas Oklahoma border, which also collected NO X and total reactive nitrogen (NO Y ) during this period, and the SAGA monitor, which collected NO X in addition to ozone. The SAGA monitor, discussed in the previous section, was one of those deployed for TexAQS II. A full discussion of model performance at these and other rural monitors is provi ded in Appendix C: CAMx Modeling for the HGB Attainment Demonstration SIP

.

National Oceanic and Atmospheric Administration (NOAA) WP3-3D Orion The NOAA WP-3D (P3) flew missions in the area between August 31 and October 13, 2006, and sampled many species not routinely monitored, including formaldehyde, NO Y , nitric acid, and a suite of reactive hydrocarbons. Figure 3-39: Comparison of Modeled and P3 Observed Ozone (O 3 ), August 31, 2006, 14:16 to 15:33 CST

, illustrates the flight of August 31, 2006, as the aircraft first arrived from Florida. The top two panels compare observed and modeled ozone concentrations (referred to on the plots as mixing ratio) along the flight track, while the bottom two compare the observed and modeled concentrations as a time series and a scatter plot superimposed with a QQ plot. The resu lts are consistent with Figure 3-34: Tile Plot of Daily Maximum Eight-Hour Ozone Concentrations fo r August 17 and 31, and September 1 and 7, 2006

, which showed that the model correctly placed th e highest ozone concentrations geographically, but did not replicate the magnitude of the highest observations at the surface. The P3 flight shows that at the elevation of the aircraft, around 500 meters above ground level (AGL), the model also replicated the position of the high est ozone concentrations, but, as above, the model did not replicate the high concentrations seen in western Harris County.3-65 Figure 3-39: Comparison of Modeled and P3 Observed Ozone (O 3 ), August 31, 2006, 14:16
to 15:33 CST

The model’s under-prediction of the highest observed ozone concentrations was common throughout most of the flights. A detailed discu ssion of model comparisons with P3 data can be found in Appendix C: CAMx Modeling for the HGB Attainment Demonstration SIP . Some of the conclusions reached are that the model usually re plicated the winds observed by the P3 well and even in cases where it showed a directional bias, usually placed the highest ozone concentrations in about the right location. The model reproduced the observed NO X concentrations well, but over-predicted CO. Most hydrocarbon species were under-predicted by the model, even after the HRVOC reconciliation, as was formaldehyde on mo st occasions. Isoprene concentrations were generally modeled well, but some high modele d isoprene concentrations did not match the

observations.

NOAA Twin Otter Tunable Optical Profiler for Aerosol and oZone (TOPAZ) A second NOAA aircraft, a Twin Otter, carried a downward-looking lidar tuned to ozone and aerosol loading called TOPAZ. Data from this instrument were valuable because they allowed modeled ozone to be compared with measurement s vertically through up to 3,000 meters AGL. The instrument was flown on 13 missions between August 15 and September 13, 2006. The top two panels of Figure 3-40: TOPAZ-Observed and Modeled Ozone Concentrations on August 31,

2006 compare observed and measured ozone con centrations between 255 and 377 meters AGL, which is the fifth vertical modeling layer. Th e lower plots are ozone curtains, showing ozone concentrations from the surface up to the aircraft elevation along the entire flight path and show that at around 15:00 the under-prediction carried upwards to over 1,500 meters. The TOPAZ concentrations near the surface are highly variab le and may include contamination from surface features and thus, may not accurately reflect ozone concentrations within the first 200 meters.3-66 Figure 3-40: TOPAZ-Observed and Modeled Ozone Concentrations on August 31, 2006

Like the P3, the TOPAZ also showed that the model usually placed the highest ozone concentrations in the correct location, but generally under-predicted the observed peak concentrations. A comparison between the TOPAZ measurements of ozone concentration with those made by the P3 (the two flew together on only two days), showed relatively good agreement. The TOPAZ measured ozone concentra tions above the mixed layer on most days that were notably higher than the model predicted.

The Research Vessel (RV) Ronald H. Brown

The NOAA RV Ron Brown arrived in the HGB area on August 15, 2006, and collected data until its departure on September 13. The ship carried a wide array of sampling platforms onboard and provided extensive data collected in the Gulf of Mexico, Galveston Bay, and in the Houston Ship Channel. Figure 3-41: Comparison of Ozone Concentrati ons Observed by the RV Ron Brown with Modeled Concentrations, August 31, 2006, 08:00 to 16:30 , compares observed and modeled ozone for the period from 8:00 to 16:30 on August 31. The ship sailed from Barbour’s Cut into the Gulf of Mexico, and then along the coast to ne ar Freeport. This figure shows that the model predicted the observed concentrations of ozone very well from Barbour’s Cut to Galveston and then showed a brief period of over-prediction as the observed concentrations dipped between

11:00 and 12:00. The decrease in measured ozone c oncentrations coincided with a period of very high NO X concentrations observed in the chan nel between Galveston Island and Bolivar

Peninsula. The observed NO X was probably emitted by local ship traffic and likely reduced the ozone concentrations through titration. As the ship sailed into the Gulf of Mexico, it measured unusually high ozone concentra tions moving onshore, which the model under-predicted. This under-prediction may be the result of long-range transport or of model boundary conditions that are too low on this day. As an alternative, the under-prediction may have resulted from air advected out into the Gulf of Mexico the prev ious day from the Houston or Beaumont areas.3-67 More often, the ship encountered low ozone concen trations in the Gulf of Mexico, particularly under southerly wind conditions, which the model often over-predicted.

Figure 3-41: Comparison of Ozone Concentrations Observed by the RV Ron Brown with Modeled Concentrations, August 31, 2006, 08:00 to 16:30

Ozone Sondes A number of ozone sondes, lightweight and comp act balloon-borne instruments, were launched from the University of Houston (UH) campus s outheast of downtown Houston and also from the

deck of the RV Ron Brown in 2006. Ozone m onitors attached to these balloons provide an opportunity to evaluate the model’s vertical ozone distribution. Figure 3-42: Comparison of Modeled and Observed Vertical Ozone Profiles from Two Sonde Launches at UH Campus and One Sonde Launch from the RV Ron Brown in the Gulf of Mexico, August 31, 2006, shows three vertical ozone profiles measured by sondes launched from the UH campus on August 31, 2006, compared with modeled concentrations on that day. The left-hand panel shows that for the morning (6:00 a.m.) launch from the UH campus, oz one concentrations fluctuated with altitude within the first 1,500 meters. This effect ma y not represent actual variability in concentrations, however, since the measurements made by the sondes launched from UH were susceptible to interference by sulfur dioxide (SO 2 ); each molecule of SO 2 encountered by the instrument effectively cancels out one molecule of ozone. Because there are numerous SO 2 sources relatively close to the UH campus, it is very likely that the balloon may have encountered one of these plumes during ascent.

Aside from the fluctuations, the model replicated ozone concentrations reasonably well up to around 1,200 meters. The model unde r-predicted ozone concentrati ons up to about 5,000 meters, but predicted concentrations fairly well above th at altitude. At 12:29 p.m. (center panel), the model slightly over-predicted ozone concentrations near the surface, but observed ozone concentrations increased dramatically within the first 100 meters or so to 30 ppb greater than3-68 modeled concentrations. Unlike the notches seen in the morning launch, this effect is most likely caused by ozone scavenging by nearby NO X sources, probably vehicular traffic. More significantly, after the first few meters, the model continued to under-p redict observed ozone concentrations up to 4,000 meters.

The right-hand panel of Figure 3-42: Comparison of Modeled and Observed Vertical Ozone Profiles from Two Sonde Launches at UH Cam pus and one Sonde Launch from the RV Ron Brown in the Gulf of Mexico, August 31, 2006 shows ozone concentrati ons observed and modeled

for a sonde launch from the deck of the RV Ron Brown, coincident with the 12:29 p.m. launch from the UH. In this case, the model initially ov er-predicted ozone concentrations near the surface by 15 ppb, but within the first 100 meters or so the sonde recorded a drop in ozone concentrations, followed by a rapid rise. This f eature is probably due to the balloon encountering sulfate emissions from a ship plume, possibly fro m a passing ship or from the Ron Brown. The modeled and observed profiles crossed at about 1, 200 meters, and then the observations exceeded the model by 10 to 20 ppb up to 4,000 meters. Farther above, the observa tions oscillated around

the modeled values.

Ozone Profiles August 31, 2006

Hour 6,UH Hour 12, UH Hour 12, RHB

Figure 3-42: Comparison of Modeled and Observed Vertical Ozone Profiles from Two Sonde Launches at UH Campus and One So nde Launch from the RV Ron Brown in the Gulf of Mexico, August 31, 2006 Notes: TOPP = Tropospheric Ozone Pollution Project
RHB = Ronald H. Brown

Moody Tower The Moody Tower site is located atop a dorm itory on the UH campus southeast of downtown

Houston. The site is useful because it is locat ed 60 meters AGL (in model layer 2), hence is

insulated from some of the more localized emissi on sources. Much of the Moody Tower data has been incorporated into the standard model performance evaluation processing performed at the3-69 TCEQ for surface sites, with special provisions to use modeled concentrations from layer 2 instead of layer 1. Within this framework, th e Moody Tower data offers measurements of some atmospheric constituents explicitly tracked in the CB05 mechanism, including nitric acid, nitrous acid, and formaldehyde. In addition, researchers at this site collected a wealth of information on radicals associated with photochemical ozone pr oduction. These data are used in conjunction with CAMx Chemical Process Analysis in Section 5.1: QUANTITATIVE CORROBORATIVE

ANALYSIS of this document.

Other TexAQS II Data During TexAQS II, formaldehyde data were collect ed at two sites, Lynchburg Ferry and Houston Regional Monitor-3. These data have been inco rporated into the TCEQ model performance evaluation database and are being used in rout ine comparisons between modeled and observed

concentrations.

Some additional TexAQS II data have not yet been used for model performance evaluation because they were not yet available in a usable fo rm, but may be useful in the future. These data sources include the Houston Triangle project, the Ba ylor Aztec flights, the Solar Occultation Flux (SOF) measurements, “smart” balloon data, Differential Optical Ab sorption Spectroscopy (DOAS) observations, and satellite observations.

3.5.4.3 Diagnostic Evaluations Since future design values are based solely on the model’s relative response and not on the magnitude of its future case ozone predictions , evaluating the model’s response to emission changes becomes at least as important as evalua tion of its ability to reproduce historically observed events. The EPA modeling guidance recommends several possible means of assessing model response to emission changes. However, most of these methods are either indirect (probing tools, alternative base cases, most observation-based models) or are difficult to employ in practice (retrospective analyses). In this secti on the TCEQ employs three tests to evaluate the model’s response to emission changes. The first of these is a sensitivity analysis designed to test the model’s response to a hypothetical inventory change, specifically, an increase in emissions from flares. The second test is a retrospectiv e analysis that uses an existing 2000 baseline inventory to test the model’s ability to predict ozone design values in a previous year. The third, a weekday-weekend analysis, is based on obser vational modeling designed to assess an area’s

VOC- or NO X -sensitivity.

Flare Sensitivity Modeling The TCEQ has been evaluating flares as a potential source of underreported VOC emissions since TexAQS 2000. Flare monitoring requirements in the HRVOC rules in 30 TAC Chapter 115, Subchapter H, Division 1, were adopted in 2002 and designed to provide more accurate

information on HRVOC and total flow rate to th e flares. More recently, the TCEQ has been evaluating potential issues with the destruction efficiencies used to calculate emissions from flares. Due to the open combustion nature of flares, direct measurement of flare emissions or

verification of flare destruction efficiencies is problematic. Remote sensing technologies such as differential absorption lidar (DIAL) can be used to estimate flare emissions and destruction efficiency. Recent work with DIAL during Tex AQS II indicated destruction efficiencies on an

actual industrial flare were less than assumed fo r reporting purposes. However, the use of such remote sensing technology is expensive and cu rrently limited to research activities such as TexAQS II. Therefore, companies must still use an assumed destruction efficiency to calculate VOC emissions from flares. Most companies assume a flare destruction efficiency of 98 to 99 percent, meaning the VOC emission rate is only one or two percent of the VOC mass rate sent to the flare. These assumptions are based on a small number of controlled studies conducted in the early 1980s and may not represent flare operations in real-world conditions. Furthermore, the chemistry that occurs within the flare flame is not well-understood in the majority of situations. Products of incomplete combustion may be fo rmed and emitted from flares in addition to3-70 uncombusted VOC from the material sent to the flares. Some researchers have speculated that flares could emit formaldehyde in sufficient qua ntities to significantly enhance photochemical reactivity in the flare plumes (Castineira and Edgar, 2006; Robinson et al., 2008).

To study the sensitivity of the model to poten tial unaccounted-for flare emissions, a model run

was conducted in which flare emissions were increa sed ten-fold (10X). This is equivalent to reducing assumed flare destruction efficiency from 99 percent to 90 percent. At the same time, the potential source contribution function (PSC F)-based HRVOC reconciliation was removed. The net effect on emissions was to replace the 23. 1 tpd of ground-level HRVOC emissions with 321.6 tpd of elevated flare VOC, of which 87.9 tpd is HRVOC.

Figure 3-43: Comparison of P3 Measurements with Base Case and Enhanced Flare Emissions; observed ethylene, formaldehyde, and ozone compa red to modeled concentrations using the base case inventory, and (right) the base case invento ry with 10X flare VOC emissions, minus the
HRVOC reconciliation compares (A) modeled ETH, (B) formaldehyde (FORM), and (C) Ozone

concentrations with observations made on th e NOAA WP-3D Orion aircraft during TexAQS II, inside the 2 km HGB modeling grid. In each row, the left-hand panel shows the comparison using the 2005-2006 base case mode ling inventory, while the right -hand panel shows a similar comparison using the inventory with the te n-fold increase in flare VOC emissions (and
concurrent removal of the HR VOC reconciliation discussed ear lier in Section 3.4.2.1: Point

Sources ). The green dots represent actual data pairs. The red dots are plotted by matching the smallest observed value with the smallest modeled value, then the next smallest of each, and so on. The resulting QQ plot provides a means to co mpare the two distributions; if it lies close to the diagonal line, then the model is simulating the correct proportions of small, medium, and large concentrations of the pollutant.3-71 

## (A)

(B)

(C)

Figure 3-43: Comparison of P3 Measurements with Base Case and Enhanced Flare Emissions; observed ethylene (Panel A), form aldehyde (Panel B), and ozone (Panel C) compared to modeled concentrations using (l eft) the base case inventory, and (right) the base case inventory with 10X flare VOC em issions, minus the HRVOC reconciliation

The flare sensitivity markedly improves the dist ribution of modeled ethylene concentrations compared with observations and also improves m odeled formaldehyde and ozone concentrations,3-72 although the highest modeled ozone concentrati on remains at about 105 ppb compared with observations ranging to near 145 ppb. This discrepancy is at least partly due to the incommensurability of the measurements: modeled values represent averages over one hour over a 2 km x 2 km region (also across a vertical dept h depending on model layer), while the aircraft measurements are essentially single points in space a nd time. However, the 10X flare sensitivity modeling degrades performance for some pollutants at the surface, as illustrated in Figure 3-44: Log-Log Plots of Observed vs. Modeled Ethylene at Deer Park September 19 through October 11, 2006; with base case inventory, and base case in ventory with 10X flare emissions minus the
HRVOC reconciliation , which compares modeled and observed ozone concentrations at Deer Park to base case and 10X flare emissions (note that these plots use a log-log scale; blue dots represent observed-modeled pairs, and red dots indicate the QQ plot).

Figure 3-44: Log-Log Plots of Observed vs. Modeled Ethylene at Deer Park September 19 through October 11, 2006; with (Left) base ca se inventory, and (Right) base case inventory
with 10X flare emissions mi nus the HRVOC reconciliation

Figure 3-45: Daily Peak Modeled Eight-Hour Ozone Concentrations with Base Case Inventory and 10X Flare Inventory; the difference between the two plots (Flare 10X – Reg 10) is shown at right shows the effect of the 10X flare VOC increa se on eight-hour peak ozone concentrations on October 6, 2006. The ozone plume, while s till under-estimated, clearly matches the observed

surface concentrations better with the 10X flar e inventory (center) than the base case inventory (left). Observed eight-hour peak ozone concentrations are shown as small circles at the monitor

locations.3-73 Figure 3-45: Daily Peak Modeled Eight-H our Ozone Concentrations with Base Case Inventory (Left) and 10X Flare Inventory (Center); the difference between the two plots (Flare 10X – Reg 10) is shown at right

In addition to the 10X VOC sensitivity, the TCEQ ran a sensitivity in which only HRVOC emissions from flares were increased (also 10X). A third sensitivity further modified the 10X HRVOC sensitivity to add a formaldehyde boost equal to 10 percent of the added HRVOC
emissions. Results of these sensitiv ities can be found in Appendix C: CAMx Modeling for the

HGB Attainment Demonstration SIP

.

More work is needed to determine whether a flare adjustment is superior to the surface-level reconciliation currently in use. The TCEQ plans to investigate using a PSCF-based technique applied to flare emissions in the near future.

Retrospective Modeling – 2000 Backcast The purpose of this test is to test the model in a forecast (in this case, backcast) mode, where the answer is known in advance. Retrospective mode ling is usually difficult to implement in practice

because of the need to create an inventory, but a 2000 i nventory was already available. In this test, most of the 2006 baseline inventory was replaced with a baseline inventory previously developed for the 2000 ozone episode used in prio r SIP revisions. However, the episode dayspecific biogenic emissions for the 2005 and 2006 episodes were not replaced, as is also the practice when modeling a future base emissi ons inventory. Similarly, the 2005 and 2006 meteorology was used with the 2000 baseline emis sions as is the procedure when modeling with

the future emissions.

Since the model predictions of the typi cal future design values are based on a DV B , which is the average of three regulatory design values (EPA, 2007), the quantity forecast in this test is not a specific future year’s design valu e but rather the average of three years. Thus, the regulatory design values for 2000, 2001, and 2002 were averaged in the same manner as the 2006 DV B was calculated as the average of the 2006, 2007, and 2008 regulatory design values. Table 3-16: 2000 Baseline Design Value Calculation for Retrospective Analysis shows the calculation. Only monitors that had at least one regulatory design value in the 2000-2002 window and also in the

2006-2008 window were used.3-74 Table 3-16: 2000 Baseline Design Value Calculation for Retrospective Analysis

Modeling CAMS Eight-Hour DV

Site Code Number 2000 2001 2002 2000
Baseline DV

BAYP 53 111 110 100 107.0

C35C 403 101 97 93 97.0

DRPK 35 112 108 103 107.7

GALV 34 108 98 89 98.3

HALC 8 111 108 107 108.7
HCQA 409 110 104 102 105.3

HLAA 408 96 91 83 90.0

HNWA 26 108 105 101 104.7

HOEA 1 102 103 101 102.0

HROC 95
- - 95 95.0

HSMA 406 106 93 90 96.3

HWAA 405 105 98 89 97.3

SHWH 410 102 104 95 100.3

Once the model was run with the 2000 baseline emissions, RRFs were calculated. In a retrospective analysis, most of the RRFs are e xpected to be greater than 1 because ozone has decreased since the retrosp ective year. Table 3-17: 2000 Projected DVs Compared with
Calculated DVs shows the calculated RRFs and the respective projected 2000 design values, compared with those listed in Table 3-16: 2000 Baseline Design Value Calculation for Retrospective Analysis

.

Table 3-17: 2000 Projected DVs Compared with Calculated DVs

Modeling
Site Code CAMS

Number 2006
Baseline

DV 2006-to2000

RRF Projected
2000 DV Baseline
2000 DV

BAYP 53 96.7 1.11 107.0 107.0

C35C 403 79.0 1.18 93.5 97.0

DRPK 35 92.0 1.18 108.1 107.7

GALV 34 83.0 1.11 92.5 98.3

HALC 8 85.0 1.15 97.9 108.7
HCQA 409 87.0 1.13 98.6 105.3

HLAA 408 77.7 1.11 86.4 90.0

HNWA 26 89.0 1.13 100.4 104.7

HOEA 1 80.3 1.17 94.0 102.0

HROC 95 79.7 1.15 91.6 95.0

HSMA 406 90.3 1.16 104.8 96.3

HWAA 405 76.3 1.14 86.9 97.3

SHWH 410 92.3 1.11 102.9 100.3

For two sites, Houston Bayland Park (CAMS 53) and Deer Park (CAMS 35), the projections were identical, or nearly identi cal, to the calculated baseline valu es. For all other sites but one, the model-projected 2000 DVs were lower than th e calculated values, indicating that the model3-75 did not respond as well to emission changes as the actual airshed for these sites. In only one case did the model respond notably more strongly than the airshed, Houston Monroe (CAMS 406).

In conclusion, the modeled response generally w as lower than the actual airshed’s response to 2000-2006 emission changes. This conclusion giv es confidence going forward that the model’s predictions are conservative, and that future ozone concentrations may be even lower than predicted by the model.

Observational Modeling – Weekday/Weekend
Weekend emissions of NO X in urban areas tend to be lower than weekday emissions because of fewer miles driven. The effect is most pronou nced on weekend morni ngs, especially Sundays, since commuting is much lower than weekdays. In a detailed analysis presented in Appendix C: CAMx Modeling for the HGB Attainment Demonstration SIP an analysis using modeled Wednesdays, Saturdays, and Sundays is described , but the results were rather inconclusive because of small sample sizes (15 Wednesdays and 11 each Saturdays and Sundays). A more comprehensive analysis was undertaken to simulate more of each day type; in three separate runs each day’s modeled emissions were substitu ted with, Wednesday, Saturday, and Sunday emissions. These runs provided a total of 88 each Wednesdays, Saturdays, and Sundays.

For comparison, 6:00 a.m. NO X concentrations were averaged for every Wednesday, Saturday, and Sunday between May 15 and October 15 in the years 2005 through 2008, which gives over 100 of each day (less for some monitors because of missing data). Figure 3-46: Mean Observed

NO X Concentrations at HGB Monitors as a Percentage of Wednesday Mean Values, May 15 through October 15, 2005 through 2008 shows observed and modeled 6:00 a.m. NO X concentrations at 15 sites in the HGB area. Except for anomalous behavior at Galveston Airport (CAMS 34), all monitors s how observed and modeled NO X concentrations that decline monotonically from Wednesday through Saturday to Sunday. The observed concentrations (excluding Galveston Airport (CAMS 34)) show si milar percentage declines, but the modeled values have much greater variability, with sites in eastern Harris County (near the Ship Channel) showing the slowest declines. This effect coul d be due to the model mixing down industrial NO X emissions too rapidly.

2005-8 Mean Observed 6 AM NO X Concentrations as a % of Wednesday

20% 40% 60% 80% 100% 120%

Wed Sat Sun BAYP

C35C

CNR2

DRPK

GALC

HALC

HCHV

HLAA

HNWA

HOEA

HTCA

LKJK

LYNF

MACP

SBFP Mean Modeled 6 AM NO X Concentrations as a % of Wednesday, all-WSS Runs

20% 40% 60% 80% 100% 120%

Wednesday Saturday Sunday BAYP

C35C

CNR2

DRPK

GALC

HALC

HCHV

HLAA

HNWA

HOEA

HTCA

LKJK

LYNF

MACP

SBFP

Figure 3-46: Mean Observed NO X Concentrations at HGB Monitors as a Percentage of Wednesday Mean Values, May 15 through October 15, 2005 through 2008

Figure 3-47: Observed and Modeled Daily Peak Eight-H our Ozone Concentrations as a Percentage of Wednesdays shows observed and modeled daily peak eight-hour ozone concentrations as a percentage of Wednesdays for the same sites. Because the modeled episodes represent periods of higher-than-average ozone c oncentrations, the observed concentrations were filtered to remove values less than 40 ppb. Th e left-hand panel of the figure shows observed3-76 concentrations trending downward for nearly all sites, but some seem to rebound on Sunday and exceed the respective Saturday concentrations. This effect is probably due to filtering concentrations below 40 ppb, which removes very low concentrations from the average.

2005-8 Mean Observed 8-Hour Peak O3 Concentrations as a % of Wednesday (days with min. 40 ppb 8-hour peak O3)

80% 90% 100% 110% 120%

Wed Sat Sun BAYP

C35C

CNR2

DRPK

GALC

HALC

HCHV

HCQA

HLAA

HNWA

HOEA

HROC

HSMA

HTCA

HWAA

LKJK

MACP

SBFP

SHWH 2005-8 Mean Observed 8-Hour Peak O3 Concentrations as a % of Wednesday (days with min. 40 ppb 8-hour peak O3)

80% 90% 100% 110% 120%

Wed Sat Sun BAYP

C35C

CNR2

DRPK

GALC

HALC

HCHV

HCQA

HLAA

HNWA

HOEA

HROC

HSMA

HTCA

HWAA

LKJK

MACP

SBFP

SHWH Mean Modeled 8-Hour Peak Ozone Concentrations as a % Of Wednesday, all-WSS Runs

80% 90% 100% 110% 120%

Wednesday Saturday Sunday BAYP

C35C

CNR2

DRPK

GALC

HALC

HCHV

HCQA

HLAA

HNWA

HOEA

HROC

HSMA

HTCA

HWAA

LKJK

LYNF

SBFP

SHWH

Figure 3-47: Observed and Modeled Daily Peak Eight-Hour Ozone Concentrations as a Percentage of Wednesdays

While the modeled concentrations are very tightly clustered in the figure, they universally decline from Wednesday through Saturday to Sunday, sim ilar to the pattern shown by the observations (ignoring the anomalous rebound effect). The airshed and model both show sensitivity to NO X reductions, at least for days with some ozone-forming potential. In fact, the airshed seems to show greater sensitivity to NO X than the model, which suggests that anticipated reductions to motor vehicle emissions over the next several year s may be more effective than suggested by the

model.

3.6 BASELINE (2006) AND FUTURE CASE (2018) MODELING 3.6.1 2006 Baseline Modeling The TCEQ selected 2006 as the baseline year fo r conducting the attainment modeling. Two features of the 2006 baseline year are used in the attainment modeling. First, the 2006 baseline year identifies the three consecutive years (2006, 2007, and 2008) with design values (DVs) that include the fourth high of the 2006 baseline year. These three DVs are averaged to calculate the baseline design value (DV B ), as previously illustrated in Figure 3-1: Baseline Design Value
Calculation Illustration . Second, typical 2006 ozone season day (OSD) emissions were developed, as previously su mmarized in Table 3-13: Summary of 2006 Baseline and 2018 Future Base, and 2018 Control Strategy Anthropogenic Modeling Emissions for HGB

.

The typical 2006 OSD emissions were modeled for all episode days to calculate the denominator of the RRF for each of the regulatory monitors. Th e denominator of the RRF is the average of the modeled maximum daily eight-hour ozone con centrations for those days with modeled concentrations greater than or equal to 85 ppb, within a grid cell array about each monitor.

Figure 3-48: Near Monitoring Site Grid Cell Array Size shows a map of the 2 km subdomain nested in a portion of the 4 km x 4 km fine grid domain depicting the monitors, and the extent of 7 x 7, 5 x 5, and 3 x 3 grid cell arrays based on the 2 km grid. The TCEQ has calculated RRF values for each of these array sizes, but used a 7 x 7 grid array about each monitor.3-77 Figure 3-48: Near Monitoring Site Grid Cell Array Size

The monitor-specific denominator of the RRF is calculated as the average of the modeled daily maximum eight-hour ozone concentrations above 84 ppb at that monitor. Per the EPA’s modeling guidance, if there are fewer than 10 days with 2006 baseline modeled concentrations greater than 84 ppb, then days with modeled con centrations less than or equal to 84 ppb can be used so the average is based on at least 10 days. Table 3-18: 2006 DV B , RRF Denominator (RRF D ), and Number of 2006 Baseline Modeled Days Averaged summarizes the DV B and the denominator of the RRF for the HGB regulatory monitors. There is also one non-regulatory monitor, Wallisville Road (CAMS 617), which has a DV B greater than or equal to 85 ppb. Including non-regulatory monitors that have a DV B and a RRF denominator greater than or equal to 85 ppb mitigates the need to conduct an unm onitored area analysis for the area represented by the monitor, as required by the EPA’s modeling guidance.3-78 Table 3-18: 2006 DV B , RRF Denominator (RRF D ), and Number of 2006 Baseline Modeled Days Averaged

Monitor Designation Site Code 2006 DV B (ppb)** 2006 RRF D (ppb) Modeled Days Averaged Houston East (CAMS 1) HOEA 80.3 96.662 20 Aldine (CAMS 8) HALC 85.0 97.069 17 Channelview (CAMS 15) HCHV 82.7 96.609 16 Northwest Harris County (CAMS 26) HNWA 89.0 93.773 21 Galveston Airport (CAMS 34) GALV 83.0 95.411 10 Deer Park (CAMS 35) DRPK 92.0 95.032 20 Seabrook Friendship Park (CAMS 45) SBFP 85.3 92.227 14 Houston Bayland Park (CAMS 53) BAYP 96.7 96.949 28 Conroe Relocated (CAMS 78) CNR2 83.0 91.325 10 TCEQ Houston Regional Office (CAMS 81) HROC 79.7 96.776 22 Manvel Croix Park (CAMS 84) MACP 90.7 94.912 23 Clinton (CAMS 403) C35C 79.0 98.297 20 Houston Monroe (CAMS 406) HSMA 90.3 95.494 25 Croquet (CAMS 409) HCQA 87.0 96.338 26 Shell Westhollow (CAMS 410) SHWH 92.3 101.532 22

Houston Texas Avenue (CAMS 411) HTCA 79.3 97.392 23 Lynchburg Ferry (CAMS 1015) LYNF 81.7 95.742 16 Wallisville Road (CAMS 617)* WALV 92.0 95.091 13 * Wallisville Road (CAMS 617) is not a regulatory monitor; ** Values 85 ppb or greater are shown in red.

3.6.2 Future Baseline Modeling Similar to the 2006 baseline modeling, the 2018 m odeling was conducted for each of the episode days using the projected 2018 ozone season day emi ssions, as previously summarized in Table 3-

13: Summary of 2006 Baseline and 2018 Future Base, and 2018 Control Strategy Anthropogenic Modeling Emissions for HGB . Using the same days as used in the 2006 baseline modeling to

calculate the RRF D , an RRF numerator (RRF N ) was calculated as the average of the of the 2018 modeled maximum daily eight-hour ozone concentra tions within the 7 x 7 grid cell array about

each monitor. The RRF at each monitor was calculated as the quotient of the RRF N and RRF D , and the 2018 future design value (DV F ) at each monitor was estimated as per EPA’s modeling guidance, by the multiplying the 2006 DV B by the RRF. Table 3-19: Summary of 2006 Baseline Modeling, RRF, and Future Design Values summarizes the 2006 DV B , RRF and 2018 DV F ateach of the regulatory monitors as well as the Wallisville Road (CAMS 617) monitor (nonregulatory monitor).3-79 Table 3-19: Summary of 2006 Baseline Modeling, RRF, and Future Design Values

Monitor Designation Site Code 2006 DV B (ppb)** RRF 2018 DV F (ppb) Houston East (CAMS 1) HOEA 80.3 0.959 77.0 Aldine (CAMS 8) HALC 85.0 0.920 78.2 Channelview (CAMS 15) HCHV 82.7 0.958 79.2 Northwest Harris County (CAMS 26) HNWA 89.0 0.869 77.4 Galveston Airport (CAMS 34) GALV 83.0 0.956 79.3 Deer Park (CAMS 35) DRPK 92.0 0.958 88.2 Seabrook Friendship Park (CAMS 45) SBFP 85.3 0.945 80.6 Bayland Park (CAMS 53) BAYP 96.7 0.900 87.0 Conroe Relocated (CAMS 78) CNR2 83.0 0.877 72.8 Houston Regional Office (CAMS 81) HROC 79.7 0.960 76.5 Manvel Croix Park (CAMS 84) MACP 90.7 0.900 81.6 Clinton (CAMS 403) C35C 79.0 0.959 78.5 Houston Monroe (CAMS 406) HSMA 90.3 0.935 84.4 Croquet (CAMS 409) HCQA 87.0 0.900 78.3 Shell Westhollow (CAMS 410) SHWH 92.3 0.859 79.3 Houston Texas Avenue (CAMS 411) HTCA 79.3 0.942 74.7 Lynchburg Ferry (CAMS 1015) LYNF 81.7 0.961 78.5 Wallisville Road (CAMS 617)* WALV 92.0 0.960 88.3 * Wallisville Road (CAMS 617) is not a regulatory monitor; ** Values 85 ppb or greater are shown in red.

The 2018 baseline attainment modeling projects tw o regulatory monitors (Houston Bayland Park (CAMS 53) and Deer Park (CAMS 35)) and one non-regulatory monitor (Wallisville Road (CAMS 617)) to have DV F s greater than 84 ppb.

3.6.2.1 Matrix Modeling A series of modeling sensitivities using across-th e-board percentage reductions to the 2018 baseline modeling emissions from sources in the eight-county HGB area was conducted. The results of the modeling were used to estimate the amount of NO X and/or VOC emissions

reduction needed to reduce the DV F s for each of the three monitors to 85 ppb. Figure 3-49: DV F versus NO X and/or VOC Emissions Reduction Response Curves for the BAYP, DRPK, and WALV

Monitors graphically shows the response of the DV F s for the Houston Bayland Park (CAMS 53), Deer Park (CAMS 35), and WALV (non-regulatory monitor) monitors to reductions in emissions

of NO X and/or VOC from sources in the eight-county HGB area.Deer Park Future Ozone Design Value Response:NOx, VOC and NOx+VOC Reductions70727476788082848688900 10 20 30 40 50 60Across-the-Board Percent Reduction

Future Design Value (ppb)VOC-RdctnNOx-RdctnNox+VOC-RdctnNAAQS19.95%70727476788082848688900 10 20 30 40 50 60Across-the-Board Percent Reduction

Future Design Value (ppb)VOC-RdctnNOx+VOC-RdctnNOx-RdctnNAAQS% Rdctn NOx VOC0 All 0 025 All 94 26950 All 188 5389.59%3-80Figure 3-49: DVFversus NOXand/or VOC Emissions Reduction Response Curves for the BAYP, DRPK, and WALV Monitors.8.23%43.42%Bayland Park Future Ozone Design Value Response:NOx, VOC and NOx+VOC Reductions% Rdctn NOx VOC0 All 0 025 All 94 26950 All 188 53837.95%14.25Wallisville Road Future Ozone Design ValueResponse: NOx, VOC and NOx+VOC Reductions70727476788082848688900 10 20 30 40 50 60Across-the-Board Percent Reduction

Future Design Value (ppb)VOC-RdctnNOx-RdctnNOx+VOC-RdctnNAAQS21.23%%Rdctn NOx VOC0 0 025 94 26950 188 53816.30%3-81 Table 3-20: VOC, NO X , and VOC+NO X Emissions Reductions Needed to Model Attainment summarizes the percent and mass emissions re ductions projected to be needed to model attainment for the Houston Bayland Park (CAM S 53), Deer Park (CAMS 35), and Wallisville Road (CAMS 617) (non-regulatory) monitors.

Table 3-20: VOC, NO X , and VOC+NO X Emissions Reductions Needed to Model
Attainment

VOC Reductions NO X Reductions VOC + NO X Reductions

Monitor

Site Code Percent Mass (tpd) Percent Mass (tpd) Percent Mass (tpd)

BAYP 43.4 467 9.59 36.2 8.23 120

DRPK 38.0 408 20.2 75.2 14.2 207

WALV > 50 > 538 21.2 80.0 16.3 237 Note: WALV is a non-regulatory monitor.

3.6.2.2 Modeling Sensitivities: Emissions Reductions within 100 and 200 km of HGB

Since the EPA allows NO X and VOC reduction credit for reasonable further progress within 200 km and 100 km of a nonattainment area, respectively, emissions reduction modeling sensitivities were conducted for selected point sources of NO X and area sources of VOC in the 200 km adjacent to the eight-county HGB area. Figure 3-50: Map of Counties within 100 km (Red) and 200 km (Orange) of the Eight-County HGB Area displays a map of the counties within 100 km

and 200 km of the HGB area.3-82 hese modeling sensitivities were conducted on an earlier version of the 2018 modeling

only those counties in the eastern segment of the 200 km region (the green ector in Figure 3-50: Map of Counties within 100 km (Red) and 200 km (Orange) of the EightFigure 3-50: Map of Counties within 100 km (Red) and 200 km (Orange) of the EightCounty HGB Area

T emissions inventory. However, the sensitiv ity of the HGB 2018 future design values to

reductions of NO X and VOC emissions from these outer regions is still representative for the final version of the 2018 modeling.

For the counties within 200 km of the eight-county HGB area, point source NO X emission reductions (i.e., 25 and 50 percent) were ma de to selected Texas non-ARD sources including compressor engines, boilers, and process heaters. Compressor engines account for approximately 47 tpd of the estimated 124 tpd of NO X emissions from the selected sources in the 2018 baseline modeling emissions. In addition, in a separate modeling run, a 50 percent NO X emissions

reduction was made to

s County HGB Area ). Compressor engines in the easter n segment account for approximately 11 tpd of the estimated 64 tpd of NO X emissions from the selected sources in the 2018 baseline modeling emissions.

Table 3-21: 200 km NO X Reduction Modeling Sensitivity summarizes the sensitivity of the projected DV F s for the Deer Park (CAMS 35), Houston Bayland Park (CAMS 53), and Wallisville Road (CAMS 617) (non-regulatory) monitors to NO X emissions reduction from the3-83 ction in this region. Of e three monitors, the Deer Park (CAMS 35) monitor DV shows the largest sensitivity to NO X d change rate for 50 percent NO X emissions red segm atin are not very sensitive to emission reductions from zed.

Table 3-21: 2 O X od nsi selected point sources in the 200 km region. Th e columns indicating change rate report the amount by which the DV F is reduced per 1.0 tpd of NO X emissions redu

th F emission reductions. However, even the 0.01 34 ppb per tp

uctions from the eastern ent is rather low, indic the sources analy g that the HGB monitors

00 km N Reduction M eling Se tivity

2 O X All

5% N (31 tpd) 5 O X All 0% N (62 tpd) 5 X East (32 tpd) 0% NO Monitor

Site

Code DV F Change

(ppb) Change Rate (ppb/tpd) DV F Change

(ppb) Change Rate ( ppb/tpd) DV F Change

(ppb) Change Rate ( ppb/tpd)

DRPK 0.23 0.0074 0.47 0.0076 0.43 0.0134

BAYP 0.14 0.0045 0.27 0.0044 0.23 0.0072

WALV 0.11 0.0035 0.30 0.0048 0.26 0.0081 Note: WALV is a non-regulatory monitor.

The TCEQ also tested the sensitivity of DV F s to reductions by 50 percent of VOC emissions from

area sources in the counties with in the 200 km region. The VOC reduction modeled was

pproximately 273 tpd. Table 3-22: 200 km VOC Reduction Modeling Sensitivity summarizes AMS 35), Houston Bayland Park (CAMS 53), an AMS 617) m onitors to VOC emission reduction from the

area sources in

20 OC R Modeling Sensitivity a the sensitivity of the projected DV F s for the Deer Park (C d Wallisville Road (C the200 km region.

Table 3-22: 0 km V eduction

50% V OC (27 3 tpd) Monitor

Site Code DV F nge Cha (ppb) Change Rate (ppb/tpd)

DRPK 0.09 0.0003

BAYP 0.06 0.0002

WALV 0.0 0.0 Note: WALV is a non-regulatory monitor.

3.6.2.3 Ozone Source Apportionment Tool and Anthropogenic Precursor Culpability Analysis The TCEQ applied the OSAT and APCA CAMx tools to the 2018 baseline modeling. For both types of analyses, emission source groups, for ex ample, on-road mobile, non- and off-road mobile, and biogenics, and source regi ons, HGB and non-HGB, are defined. OSAT keeps track of the origin of the NO X and VOC precursors creating the ozone, and ozone can then be ap portioned to

pecific sources groups and regions. APCA is similar to OSAT, but it recognizes that certain

f every episode for e Houston Bayland Park (BAYP; CAMS 53), D eer Park (DRPK; CAMS 35) and Wallisville

isodes for these three mon itors are included in Appendix C: CAMx Modeling for the HGB Attainment Demonstration SIP

.

Table 3-23: OSAT/APCA Source Groups and Regions Defined lists all of the source groups and regions tracked in the OSAT and APCA analyses. s sources groups, such as biogenics, are not contro llable. Where OSAT would apportion ozone production to biogenic emissions, APCA reallocates that ozone production to the controllable or anthropogenic emissions that combined with the biogenic emissions to create ozone.

Results are plotted as layered area plots for every rolling eight-hour average o

th Road (WALV; CAMS 617) (non-regulatory) monitors . Results of one episode of the six modeled are presented here as an example. Plots for all ep3-84 Table 3-23: OSAT/APCA Source Groups and Regions Defined Figure Legend

Abbreviation Description of Source Group and Region

TOPBC Top Boundary Condition

NTHBC North Boundary Condition

STHBC South Boundary Condition

ESTBC East Boundary Condition

WSTBC West Boundary Condition

IC Initial Condition

Other All emission source types outside HGB, with the exception of elevated point sources

Non-HGB El Points Elevated point sources outside HGB

HGB Non-Road Non-road sources in HGB

HGB Area Area sources in HGB

HGB On-Road On-road sources in HGB

HGB Low Points Low-level point sources in HGB

HGB El Points Elevated point sources in HGB HGB Ships Ship emissions in HGB

HGB HECT HECT sources in HGB

HGB MECT MECT sources in HGB Biogenics Biogenic emissions from the entire modeling domain

Figures 3-51: OSAT and APCA Results for BAYP , 3-52: OSAT and APCA Results for DRPK,

and 3-53: OSAT and APCA Results for WALV show the results of these analyses for Houston Bayland Park (CAMS 53), Deer Park (CAM S 35), and Wallisville Road (CAMS 617) (nonregulatory monitor), respectively. The laye r corresponding to the initial model conditions disappears after the first few days of the episode are modeled, as expected. Layers corresponding to boundary conditions give an indication of wind direction on individual episode days and

concentrations of ozone attri butable to that boundary.

Layers that correspond to HGB emission sources indicate HGB contribution to the total modeled ozone concentration. The other layers, Biogeni cs, Other, Initial and Bo undary Conditions, and Non-HGB Elevated Points, indicate non-HGB contri butions to ozone concentration. Differences between the depth of the biogenic layers betwee n the OSAT and APCA plots indicate how ozone of biogenic origin is reallocated to anthropogenic sources in APCA.

Lower-level local emission sources, including non -road mobile, area, on-road mobile, and lowlevel points, make a greater contribution to ozone at Houston Bayland Park (CAMS 53) than Deer Park (CAMS 35), although Ship Channel sour ces make a noticeable contribution at Houston Bayland Park (CAMS 53). Conversely, local elevated sources, including HGB elevated points, ships, HECT, and MECT, make a greater contribution at Deer Park (CAMS 35) than Houston Bayland Park (CAMS 53). Wallisville ozone origins are more like Deer Park (CAMS 35) than Houston Bayland Park (CAMS 53).BAYP 2018 8-Hour OSAT0204060801001201405/31/2006 6/1/2006 6/2/2006 6/3/2006 6/4/2006 6/5/2006 6/6/2006 6/7/2006 6/8/2006 6/9/2006 6/10/2006 6/11/2006 6/12/2006 6/13/2006 6/14/2006

Ozone (ppb)TOPBCNTHBCSTHBCESTBCWSTBCICOthernon-HGB El PointsHGB Non-RoadHGB AreaHGB On-RoadHGB Low PointsHGB El PointsHGB ShipsHGB HECTHGB MECTBiogenicsBAYP 2018 8-Hour APCA0204060801001201405/31/2006 6/1/2006 6/2/2006 6/3/2006 6/4/2006 6/5/2006 6/6/2006 6/7/2006 6/8/2006 6/9/2006 6/10/2006 6/11/2006 6/12/2006 6/13/2006 6/14/2006

Ozone (ppb)TOPBCNTHBCSTHBCESTBCWSTBCICOthernon-HGB El PointsHGB Non-RoadHGB AreaHGB On-RoadHGB Low PointsHGB El PointsHGB ShipsHGB HECTHGB MECTBiogenicsFigure 3-51: OSAT and APCA Results for BAYP3-85DRPK 2018 8-Hour OSAT0204060801001201405/31/2006 6/1/2006 6/2/2006 6/3/2006 6/4/2006 6/5/2006 6/6/2006 6/7/2006 6/8/2006 6/9/2006 6/10/2006 6/11/2006 6/12/2006 6/13/2006 6/14/2006

Ozone (ppb)TOPBCNTHBCSTHBCESTBCWSTBCICOthernon-HGB El PointsHGB Non-RoadHGB AreaHGB On-RoadHGB Low PointsHGB El PointsHGB ShipsHGB HECTHGB MECTBiogenicsDRPK 2018 8-Hour APCA0204060801001201405/31/2006 6/1/2006 6/2/2006 6/3/2006 6/4/2006 6/5/2006 6/6/2006 6/7/2006 6/8/2006 6/9/2006 6/10/2006 6/11/2006 6/12/2006 6/13/2006 6/14/2006

Ozone (ppb)TOPBCNTHBCSTHBCESTBCWSTBCICOthernon-HGB El PointsHGB Non-RoadHGB AreaHGB On-RoadHGB Low PointsHGB El PointsHGB ShipsHGB HECTHGB MECTBiogenicsFigure 3-52: OSAT and APCA Results for DRPK3-863-87Figure 3-53: OSAT and APCA Results for WALVWALV 2018 8-Hour OSAT0204060801001201405/31/2006 6/1/2006 6/2/2006 6/3/2006 6/4/2006 6/5/2006 6/6/2006 6/7/2006 6/8/2006 6/9/2006 6/10/2006 6/11/2006 6/12/2006 6/13/2006 6/14/2006

Ozone (ppb)TOPBCNTHBCSTHBCESTBCWSTBCICOthernon-HGB El PointsHGB Non-RoadHGB AreaHGB On-RoadHGB Low PointsHGB El PointsHGB ShipsHGB HECTHGB MECTBiogenicsWALV 2018 8-Hour APCA0204060801001201405/31/2006 6/1/2006 6/2/2006 6/3/2006 6/4/2006 6/5/2006 6/6/2006 6/7/2006 6/8/2006 6/9/2006 6/10/2006 6/11/2006 6/12/2006 6/13/2006 6/14/2006

Ozone (ppb)TOPBCNTHBCSTHBCESTBCWSTBCICOthernon-HGB El PointsHGB Non-RoadHGB AreaHGB On-RoadHGB Low PointsHGB El PointsHGB ShipsHGB HECTHGB MECTBiogenics3-88 3.6.3 Future Case Modeling with Controls Proposed controls include lowering the total point source HRVOC emissions allocated by the HECT rule in Harris County and voluntary emission reductions of NO X and VOC from on- and non-road mobile sources within the eight-county HGB area.

3.6.3.1 25 Percent HECT Cap Reduction The modeling sensitivity for the HECT rule revisi on reduced current total allocated point source HRVOC emissions by 25 percent, 2.69 tpd. Table 3-24: HECT Modeling Sensitivity Results

shows the DV F s at the Deer Park (CAMS 35), Houston Bayland Park (CAMS 53), and Wallisville Road (CAMS 617) (non-regulatory) monitors for the baseline as well as those resulting from a 25 percent reduction in the HRVOC from HECT applicable sources in Harris County.

Table 3-24: HECT Modeling Sensitivity Results

Monitor

Site Code Baseline DV F (ppb) HECT DV F (ppb)

DRPK 88.14 87.90

BAYP 86.97 86.89

WALV 88.28 88.12 Note: WALV is a non-regulatory monitor.

3.6.3.2 VMEP Reductions Up to 3 percent of the estimated emissions needed for attainment (i.e., 75.2 tpd NO X at Deer Park (CAMS 35) as shown in Table 3-20: VOC, NO X and VOC+NO X Emissions Reductions Needed to

Model Attainment ) can be obtained from voluntary control measures. The Houston-Galveston Area Council (H-GAC; http://www.h-gac.com/taq/ ) has estimated that approximately 2.25 tpd of

NO X emissions reductions from on-road (1.55 tpd) and non-road (0.70 t pd) mobile sources will result from the application of VMEPs, including alte rnative commuting, regional traffic flow and vehicle retrofit and replacement, as well as non-road equipment measures. The modeling sensitivity for VMEP was coupled with the HE CT modeling sensitivity. Table 3-25: HECT and VMEP Modeling Sensitivity Results shows the DV F s at the Deer Park (CAMS 35), Houston Bayland Park (CAMS 53), and Wallisville Road (CAMS 617) (non-regulatory) monitors for the baseline as well as those resulting from both a 25 pe rcent reduction in the HECT cap and a 2.25 (1.55 on-road and 0.70 non-road) tpd VMEP reduction.

Table 3-25: HECT and VMEP Modeling Sensitivity Results

Monitor

Site Code Baseline DV F (ppb) HECT/VMEP DV F (ppb)

DRPK 88.14 87.88

BAYP 86.97 86.75

WALV 88.28 88.09 Note: WALV is a non-regulatory monitor.

Applying the truncating convention for calculating DV F s, as per the EPA’s modeling guidance, only the Wallisville Road (CAMS 617) (non-regu latory) monitor is projected to have a DV F greater than 87 ppb, the recommended limit for weight-of-evidence considerations.3-89 3.7 MODELING ARCHIVE AND REFERENCES 3.7.1 Modeling Archive The TCEQ has archived all modeling documentation and modeling input/output files generated as part of the HGB SIP modeling analysis. Interested parties can contact the TCEQ for information regarding data access or project documentation.

3.7.2 Modeling References Castineira and Edgar, 2006. Computational Fl uid Dynamics for Simulation of Steam-Assisted and Air-Assisted Flare Combustion Systems, Energy & Fuels, 20: 1044-1056.

Emery, C., E. Tai, and G. Yarwood, 2001. E nhanced Meteorological Modeling and Performance Evaluation for Two Texas Ozone Episodes, Fi nal Report to the Texas Natural Resource

Conservation Commission under TNRCC Umbre lla Contract No. 582-0-31984, Environ International Corporation, Novato, CA.

Environ, 2007. User’s Guide Emissions Processor, Version 3, Environ Inte rnational Corporation, Novato, CA.

Environ, 2008. Description from MM5CAMx README file contained in mm5camx.21feb08.tar.gz archive, http://www.camx.com/files/mm5camx.21feb08.tar.gz , Environ Holdings, Inc.

Environ, 2008b. Boundary Conditions and Fire Emissions Modeling, Final Report to the Texas Commission on Environmental Quality (TCEQ), Contract No. 582-7-84005-FY08-06, Environ International Corporation, Novato, CA.

Environ, 2009. User’s Guide Comprehensive Air Quality Model with Extensions (CAMx), Version 4.53, Environ International Corporation, Novato, CA.

EPA, 2005. Modeling files obtained via data request from the EPA in support of the Clean Air Interstate Rule Notice of Data Availability Technical Support Document, as documented at http://www.epa.gov/cair/technical.html.

EPA, 2007. Guidance on the Use of Models and Other Analyses for Demonstrating Attainment of Air Quality Goals for Ozone, PM 2.5 , and Regional Haze, http://www.epa.gov/scram001/guidance/guide/final-03-pm-rh-guidance.pdf

.

Feldman, M.S., T. Howard, E. McDonald-Buller, G. Mullins, D.T. Allen, A. Webb, Y. Kimura, 2007. Applications of Satellite Remote Sensing Data for Estimating Dry Deposition in Eastern Texas. Atmospheric Environment, 41(35): 7562-7576.

Grell, G., J. Dudhia, and D. Stauffer, 1994. A Description of the Fifth Generation Penn State/NCAR Mesoscale Model (MM5), Technical Report NCAR/TN-398+STR, National Center of Atmospheric Research (NCAR) Tech Note.

Kinnee et al., 1997. United States Land Use Inve ntory for Estimating Biogenic Ozone Precursor Emissions. Ecological Applications 7(1): 46-58.

NCAR, 2005. MM5 On-line Tutorial Home Pages, http://www.mmm.ucar.edu/mm5/On-LineTutorial/teachyourself.html , NCAR, Colorado.

NCEP, 2009. Global Energy and Water Cycle E xperiment (GEWEX) Continental International Project (GCIP) National Centers for Environm ental Prediction (NCEP) Eta Model Output,3-90 Computational and Information Systems Laborat ory (CISL) Research Data Archive (RDA): ds609.2 Home Page, http://dss.ucar.edu/datasets/ds609.2/ , NCEP.

Popescu, Sorin C., Jared Stukey, Mark Karnauch, Jeremiah Bowling, Xuesong Zhang, William Booth, and Nian-Wei Ku, 2008. The New Central Texas Land Use Land Cover Classification Project, Final Report to the TCEQ, Contract No . 582-5-64593-FY08-23, Texas A & M University, College Station, Texas.

Robinson, R., T. Gardiner, and B. Lipscomb e, 2008. Measurements of VOC Emissions from Petrochemical Industry Sites in the Houston Ar ea Using Differential Absorption Lidar (DIAL) During Summer 2007, Draft. Submitted to Russell Nettles, TCEQ, by Rod Robinson, Tom Gardiner, and Bob Lipscombe of the National Physical Laboratory, Teddington, Middlesex UK TW11 0LW, February 8, 2008, pp. 86.

Starcrest, 2000. Houston-Galveston Area Vessel Emissions Inventory, Starcrest Consulting Group, Houston, Texas.

Stauffer, D. R. and N. L. Seaman, 1990. U se of Four-Dimensional Data Assimilation in a Limited-Area Mesoscale Model. Part I: Experi ments with Synoptic-Scale Data. Monthly Weather Review, 118: 1250-1277.

Stauffer, D.R. and N.L. Seaman, 1994. Multiscale four-dimensional data assimilation. Journal of Applied Meteorology, 33: 416-434.

Stauffer, D. R., N. L. Seaman, and F. S. Binkowski, 1991. Use of Four-Dimensional Data

Assimilation in a Limited-Area Mesoscale Model. Part II: Effects of Data Assimilation Within the Planetary Boundary Layer. Monthly Weather Review, 119: 734-754.

TCEQ, 2007. Revisions to the State Implementation Plan (SIP) for the Control of Ozone Air Pollution, Dallas-Fort Worth Eight-Hour Ozone N onattainment Area Attainment Demonstration, TCEQ, Austin, Texas.

TCEQ, 2009. TCEQ Air Modeling and Data Analysis (AMDA) Section file transfer protocol (FTP) site, ftp://ftp.tceq.state.tx.us/

.

Wiedinmyer , C., A. Guenther, M. Estes, I.W. Strange, G. Yarwood, and D. Allen, 2001. A Land Use Database and Examples of Biogenic Isoprene Emission Estimates for the State of Texas, USA. Atmospheric Environment, 35: 6465-6477.4-1 CHAPTER 4: CONTROL STRATEGIE S AND REQUIRED ELEMENTS

ntrol measures (RACM), motor vehicle emissions budgets (MVEBs), and ontingency measures.

strategies at were implemented for the one-hour and ei ght-hour ozone standards in the HGB area.

zone Control Meas ures Applicable to the HGB Eight-County
Nonattainment Area 4.1 INTRODUCTION The Houston-Galveston-Brazoria (HGB) nonattainment area for the 1997 eight-hour ozone National Ambient Air Quality Standard (NAAQS), which c onsists of Brazoria, Chambers, Fort Bend, Galveston, Harris, Liberty, Montgomery, and Waller Counties, includes one of the most comprehensively controlled industrial comple xes in the world. The Texas Commission on Environmental Quality (TCEQ) has developed st ringent and innovative regulations that address nitrogen oxides (NO X ), volatile organic compounds (VOC), and highly reactive volatile organic compounds (HRVOC). Despite the significant decr eases in ozone design values and emissions of ozone precursors in the HGB area, further reductions are necessary to bring the area into attainment of the 1997 eight-hour standard. This chapte r describes existing and proposed ozone control measures for the HGB area, as well as how Texas meets the following severe ozone nonattainment area state implementation plan (SIP) requirements: reasonably available control technology (RACT), reasonably available co

c

4.2 EXISTING CONTROL MEASURES Over several years of ozone planning in the HGB ar ea, a broad range of cont rol measures have been implemented for each emission source category. Table 4-1: Existing Ozone Control Measures Applicable to the HGB Eight-County Nonattainment Area lists the existing ozone control

th

Table 4-1: Existing O

Measure Description Start Date(s)

POINT SOURCE MEASURES

NO X Mass Emissio ns Cap and Trade (MECT) Program

n , and many ed in through April 1, 2007 Overall 80 percent NO X reduction from existing industrial sources and utility power plants, impl emented through a cap and trade program. Affects utility boilers, gas turbines, heaters and furnaces, stationary internal combustio engines, industrial boilers

other industrial sources. April 1, 2003, and phas

HRVOC Rules and HRVOC

Emissions Cap and Trade (HECT)

rogram

s and monitoring d rogram is January 1,

2007 P Affects cooling towers, process vents, and flares, and establishes an annual emissions cap with a cap and trade for each site in Harris County. The seven perimeter counties ar e subject to permit

allowable limit requirements. Monitoring requirements are January 31, 2006, and cap an trade p

HRVOC Fugitive Rules

er and third part audit requirements. March 31, 2004 More stringent leak detection and repair (LDAR) requirements for components in
HRVOC service. Additional components included in LDAR program are more stringent repair times, low leak detection,4-2 Measure Description Start Date(s) VOC Rules on Storage and

egassing Operations es

r

torage

ng y of January 1, 2009

D Requires controls for slotted guide pol and more stringent controls for othe fittings on floating roof tanks, and control requirements or operational limitations on landing floating roof tanks. Eliminates exemption for s tanks for crude oil or natural gas condensate, and regulates flash emissions from these tanks. Requires vapors from degassing to be vented to a control device for a longer time period, and removes exemption from degassi to control for tanks with capacit 75,000 to 1,000,000 gallons.

NO X Emission Standards for Nitric Acid/Adipic Acid manufacturing anufacturing facilities November 15, 1999 NO X emission standards for nitric acid and adipic acid m
in the HGB area Utility Electric Gene ration in East

nd Central Texas s

on sites in East and , 2003, through May 1,

2005 a NO X control requirements (approximately 55%) on utility boiler and stationary gas turbines at utility electric generati

Central Texas. May 1

VOC Control Measures

rs

ent
x D:
ontrol Technology Analysis ). , 2002, and

arlier Additional control technology requirements for ba tch processes, bakeries, and offset lithographic printe by December 31, 2002. Examples of additional VOC measures adopted earlier for RACT purposes include: storage, general vent gas, industrial wastewater, loading and unloading operations, general VOC LDAR, solv using process, etc. (see Appendi Reasonably Available C December 31

e

AREA/NON-ROAD MEASRUES

Refueling - Stage I

s

air. 1990 Stage I vapor recovery captures gasoline vapors that are released when gasoline is delivered to a storage tank. The vapor

are returned to the tank truck as the storage tank is being filled with fuel,

rather than released into the ambient Refueling - Stage II ing

e , rather than 1992 Stage II vapor recovery captures gasoline vapors when a vehicle is be fueled at the pump. The vapors are returned through the pump hose to th petroleum storage tank

released into the air.

Federal Area/Non-Road Measures

ards Through 2007 The United States Environmental Protection Agency (EPA) has implemented a series of emissions limits for area and non-road sources. Examples are diesel and gasoline engine stand

for locomotives and leaf-blowers.

Texas Em ission Reduction Plan (TERP) (See also on-road TERP reduct ions) diesel engine replacement/retrofit. January 2002 Provides grant funds for heavy-duty

California Gasoline Engines engines 25 horsepower and May 1, 2004 California standards for non-road gasoline larger.

S tationary Diesel Engines

purposes between 6:00 April 1, 2002 Prohibition on operating stationary diesel and dual-fuel engines for testing

and maintenance4-3 Measure Description Start D ate(s)

A.M. and noon.

Natural Gas-Fired Small Boilers, its on small-scale 2002 Process Heaters, and Water Heaters NO X emission lim

residential and industr ial boilers, process heaters, and water heaters equal to or
less than 2.0 million British thermal units per hour.

Minor Source NO X Controls for

Non-MECT Sites s stationary engines and

ded in esign March 31, 2005 NO X emission limits on boilers, proces heaters, and

turbines at minor sites not inclu the MECT program (uncontrolled d capacity to emit less than 10 tons per year (tpy)).

VOC Control Measures

ters

nt December 31, 2002, and

earlier Additional control technology requirements for ba tch processes, bakeries, and offset lithographic prin by December 31, 2002. Examples of additional VOC measures adopted earlier for RACT purposes include: storage, general vent gas, industrial wastewater, loading and unloading operations, general VOC LDAR, solve using process, cutback asphalt, etc.

Texas Low Emission Diesel (TxLED) October 31, 2005 Requires all diesel for both on-road and

non-road use to have a lower aromatic content and a higher cetane number. Phase in began

TxLED for Marine Fuels June 24, 2007 Adds marine distillate fuels X and A commonly known as DMX and DMA, or Marine Gas Oil (MGO), into the definition of diesel fuels, requiring them to be TxLED compliant. Texas Low Reid Vapor Pressu (RVP) Gasoline re

om Requires all gasoline for both on-road

and non-road use to have a RVP of 7.8 pounds per square inch (psi) or less fr May 1 through October 1 each year. April 2000

Voluntary Mobile Emission Reduction Program(VMEP) s Voluntary measures administered by theHouston-Galveston Area Council (HGAC) (see Appendix F7 of the 2004 ) Through 2007

HGB Mid-Course Review SIP revision

ON-ROAD MEASRUES

Federal On-Road Measures s of

e

, Phase in through 2007 The EP A has implemented a serie

emissions limits for on-road vehicles.

Some of these include Tier 1/2 vehicl standards, low sulfur diesel standards

National Low Emission Vehicle standards, and reformulated gasoline.

TERP (See also area/non-road TERP) nuary 2002 Provides grant funds for heavy-duty diesel engine replacement/retrofit. Ja

Vehicle Inspection/ Maintenance (I/M) or vehicles.

May 1, 2003Yearly treadmill-type testing for pre1996 vehicles and computer checks f
1996 and newer -Begin May 1, 2002, in Harris County. -Begin May 1, 2003, in Brazoria, Fort Bend, Galveston, and Montgomery

Counties. May 1, 2002

Speed Li mit Reduction On roadways where speeds were 65 mph or higher, speed limits remain at 5 miles per hour (mph) below what was posted before May 1, 2002. September 2003

TxLED Requires all diesel for both on-road and
non-road use to have a lower aromatic content and a higher cetane number. Phase in be gan October 31, 20054-4 Measure Description Start Date(s)

Texas Low RVP Gasoline (see also non-road Low RVP

er April 2000

Gasoline) Requires all gasoline for both on-road
and non-road use to have a RVP of 7.8 psi or less from May 1 through Octob 1 each year.

VMEP Voluntary measures administered by the H-GAC (see Appendix F7 of the 2004 sion) Phase in through 2007

HGB Mid-Course Review SIP revi Transportation Control Measures Various measures in H-GAC’s longrange transportation plans. Phase in through 2007

OTHER

Portable Fuel Containers Rule
See section 4.3.2 Repeal of Sta te Portable Fuel Container Rule for

additional information about this ted in 04

measure. Establishes new design “no spill” criteria requirements for portable fuel containers sold, offered for sale, manufactured, and/or distribu

Texas. December 31, 20

Volunt ary Energy Efficiency/Renewable Energy couraged energy efficiency and renewable energy projects. December 2000 Senate Bill (SB) 5 and SB 7 from the

80 th session of the Texas Legislature

have en

Automotive Windshield Washer VOC content limitation on automotive sher fluid sold, supplied,

use in January 1, 1995

Fluid windshield wa distributed, or manufactured for

Texas.

4.3 UPDATES TO EXISTING MEASURES 4.3.1 Mass Emissions Cap and Trade (MECT) Program The MECT program in 30 Texas Administrativ e Code (TAC) Chapter 101 is a market-based component of the SIP th at provides flexibility for stationary source compliance with the emission

on to the MECT program would ensure the integrity of the modeled HGB ing t

ided for a system of

nces under existing regulations. s pecifications under 30 TAC Chapter 117, while establishing a mandatory cap for total NO X emissions from affected source categories in the HGB ozone nonattainment area. The MECT program was adopted as a primary control measure ofthe HGB attainment demonstration for the onehour NAAQS for ozone.

The proposed revisi

n onattainment area cap by prohibit he issuance of allowance allocations to major sources that did not submit the required Level of Activity Certifi cation forms by the compliance date in 30 TAC § 101.360. This proposed rule change would not reduce the current NO X cap in the HGB

nonattainment area.

The MECT program allocated NO X emission allowances to applicable existing facilities in the HGB area based on their 1997 to 1999 levels of activity . The program also prov

a llocating allowances to facilities that had submitted administratively complete permit applications before January 2, 2001. After Ja nuary 2, 2001, any applicable new or modified facilities in the HGB area must acquire allowances equal to their annual NO X emissions (one NO X ton per year equals one annual allowance) from existing facilities already participating in the program.

The current rule does not prohibit the issuance of ne w allowances to existing applicable facilities that failed to previously participate in the MECT program; therefore, an increase of the total NO X cap in the HGB ozone nonattainment area may occur in ce rtain circumsta

T he proposed rulemaking would prohibit these poten tial future increases in the MECT program NO X cap for maintenance of the HGB one-hour ozone atta inment demonstration. Additionally, maintaining the integrity of the MECT program NO X cap would prevent potential adverse impacts on the attainment and maintenance of the 1997 eight-hour ozone NAAQS.4-5 by revising the rule language to

a

perm he required level of activity certification by the

• facilities that were in operation prior to January 1, 1997;

e and restricted to 10 percent or ss of the normal annual operating schedule. Allowing companies to use this restriction to calculate tely reflect the actual restriction on use of the

September 15, 2005. The current Texas PFC gulations are inconsistent with the new federal standards, because they are based on the previous

ontainers , the Federal FC rule is more stringent than the Texas PFC rule.

ean Fuel Fleet Requirement articipation in a Clean Fuel Fleet Program (CFFP) is required by § 246 of the FCAA for T he proposed rulemaking would maintain the NO X cap integrity

e liminate the future allocation, after the effective date of the rule, of additional allowances to

pplicable facilities that failed to previously pa rticipate in the MECT program and previously

itted facilities that have failed to submit t

a pplicable deadlines. These facilities include:

• new and modified facilities not in operation prio r to January 1, 1997, but were included in

a submitted New Construction or Modification Permit determined to be administratively complete before January 2, 2001; and

• new and modified facilities not in operation pr ior to January 1, 1997, but qualified for a Permit by Rule and had commenced cons truction before January 2, 2001.

This proposed rulemaking would also revise Chapter 101, Subchapter H, Division 3, to clarify the definition of “uncontrolled design capacity” as it relates to applicability of this division. The TCEQ has received comments from stakeholders requ esting clarification of the MECT program applicability, specifically relating to uncontrolle d designed capacity and how it differs from a facility’s potential to emit. The definition of “unc ontrolled design capacity” would also be revised to allow owners or operators of emergency back-up engines at minor sources an alternative to using 8,760 hours to calculate the uncontrolled designed capac ity to emit for the engines. Emergency backup engines at minor sites are typically authorized by Permit-by-Rul

le the uncontrolled designed capacity would more accura engine while avoiding potentially making many minor sites needlessly subject to the MECT program solely because the engine is no longer exempt unde r Chapter 117. Because these sites would still be subject to the Chapter 117 minor source rules in S ubchapter D, Division 1, this proposed change does not constitute backsliding under th e Federal Clean Air Act (FCAA).

4.3.2 Repeal of State Portable Fuel Container Rule The EPA adopted a federal portable fuel container ( PFC) rule in the February 26, 2007, issue of the Federal Register (72 FR 8432) that set a national standard for gasoline, diesel, and kerosene PFCs. The rule requires all PFCs manufactured on or afte r January 1, 2009, to comply with the federal standards. The new federal PFC regulations are c onsistent with the revised PFC regulations adopted by the California Air Resources Board (CARB) on

re PFC testing methods adopted by CARB in 2001. Therefore, the state is proposing to repeal its PFC regulations (rule project number 2008-032-115-EN) and to rely on th e implementation of the federal PFC regulations to control VOC emissions from PFCs used within the state. According to an EPA analysis entitled, Federal Register Rule vs. Texas Register Rule Portable Fuel C

P

The repeal of the current Texas PFC regulations and reliance on the new federal PFC standards will not have a negative impact on the Texas SIP. Th e estimated emission reductions applicable to the implementation of the federal PFC rule in Texas are expected to be equivalent to the current Texas PFC rule in the early years and to provide greater reductions in the later years.

4.3.3 Cl

P nonattainment areas with 1980 populations greater than 250,000 that are classified as serious or above for ozone. In accordance with this requirement , a CFFP was instituted by rule in the HGB area beginning on September 1, 1998. The CFFP requires that a certain percentage of fleet purchases after model year 1998 be Clean Fuel Vehicles (CFV) that meet the standards set forth in § 243 of the

FCAA.The most recent federal standards

4-6 for both light- duty and heavy-duty vehicles have eclipsed the CFV tandards because subsequent to September 1, 2005, any new vehicle purchase ranging from 0-26,000

ill accomp lish equal long-term redu ctions attributable the CFFP. However, the EPA has not provided guidance on how states are to address the Clean

t federal le purchases subsequent to the date of repeal would meet more stringent

the eight-hour ozone standard, the HGB area is required to meet the mandates of the CAA under §§ 172(c)(1), 182(b)(2), and 182(f). Acco rding to the EPA’s Final Rule to Implement

available control technology (BACT) levels xpected of new sources or to maximum achievabl e control technology (MACT) levels required for s pounds gross vehicle weight rating would have e ither equaled or, in most cases, exceeded CFV standards. In a letter to manufacturers (EPA, 2005) , the EPA stated that “subsequent to publishing its CFV regulations, EPA has promulgate d new emission standards that ar e generally more stringent than or equivalent to the CFV emission standards for li ght-duty vehicles, light-duty trucks, and heavy-duty engines.” This EPA letter, dated July 21, 2005, applied to fleet purchases that began with the 2006 model year (September 1, 2005).

During the 79th Texas Legislature Regular Session in 2005, Senate Bill 1032 was signed into law, which repealed the Texas Clean Fleet Program in its entirety because the federal standards already in place at that time eclipsed the CFV standards refere nced in the FCAA. On April 26, 2006, the TCEQ formally repealed the Texas Clean Fleet Program because no additional benefit could be achieved from new vehicle purchases under CFFP. A revision to th e SIP that reflected the repeal of the Texas Clean Fleet Program was submitted to the EPA on May 15, 2006. EPA approval of measures that substitute for the initial requirement to implement CFFP is provided for in § 182(c)(4) of the FCAA as long as the EPA determines the substitute w

to Fuel Fleet substitution requirement in their SIP su bmittals, in light of the more stringen

standards. Since new vehic federal emission standards, cancellation of the Te xas Clean Fleet Program does not necessitate action to substitute this program with a separate emission reduction measure containing equivalent benefits. Such a substitution would only be warranted when a net increase in emissions would occur due to repeal or cancellation of an existing program.

4.4 REASONABLY AVAILABLE CONTROL TECHNOLOGY (RACT) ANALYSIS
4.4.1 General Discussion The HGB area is currently classified as a severe nonattainment area for the 1997 eight-hour ozone NAAQS. Under

F the 1997 eight-hour ozone NAAQS (40 Code of Fe deral Regulations (CFR) § 51.912), states containing areas classified as moderate nonattainment or higher must submit a SIP revision demonstrating that their current rules fulfill the RACT requirements for all Control Technique Guidelines (CTG) categories and all non-CTG major sources of NO X and VOC. The major source threshold for severe nonattainment areas is a potential to emit 25 tons per year (tpy) or more of either

NO X or VOC.

In the September 17, 1979, issue of the Federal Register (44 FR 53762) RACT is defined as the lowest emissions limitation that a particular source is capable of meeting by the application of control technology that is reasonably available considering technological and economic feasibility. RACT requirements for nonattainment areas classified as m oderate and higher are included in the FCAA to assure that significant source categories at major s ources of ozone precursor emissions are controlled to a reasonable extent, but not necessarily to best

e major sources of hazardous air pollutants. While RACT and RACM have similar consideration factors like technological and economic feasibility, there is a significant distinction between RACT and RACM. To be considered RACM, a control measure must advance attainment of the area towards meeting the NAAQS for th at measure (see § 172(c)(1) of the FCAA). Advancing attainment

of the area is not a factor of consideration when evaluating RACT because the benefit of implementing RACT is presumed under the FCAA.

Under the current state rules, the HGB area is subject to some of the most stringent NO X and VOC emission control requirements in the country, and fo r many source categories, the existing rules are more stringent than recommended RACT standards fo r those categories. In the final approval noticefor the revised HGB one-hour oz

4-7 one attainment de monstration SIP published in the September 6, 006, issue of the Federal Register (71 FR 52676), the EPA noted that the HGB VOC rules in 30

th e one-hour ozone attainme nt demonstration and reviously approved by the EPA.

he TCEQ's analysis demonstrates that the current NO X rules and controls for the HGB area fulfill

B area. he TCEQ has determined that RACT for the Longhorn Glass Corporation glass furnace is met view (NSR ) permit. TCEQ Permit Number 42623 requires

area. Therefore, the TCEQ is ot implementing any rule amendments or new rules for the glass furnaces in the HGB area.

a nd economically feasible is fulfilled by the EPApproved Chapter 115 rules or other federally enforceable measures.

The EPA issued 11 Consumer and Commercia l Products CTG documents between 2006 and 2008 with recommendations for VOC controls on a variety of consumer and commercial products. Some of the new CTG recommendations are updates to pr eviously issued CTG documents and some are recommendations for new categories. The TCEQ ev aluated these new CTG documents in this RACT analysis to determine if additional VOC controls were necessary to fulfill RACT requirements. The following is a list of the 11 CTG documents: 2 TAC Chapter 115 and NO X rules in Chapter 117 were previously determined to meet the FCAA RACT requirements. Under the one-hour ozone NAAQS, the HGB area was also designated as a

“severe” nonattainment area and the threshold for ma jor stationary sources under the one-hour ozone nonattainment designation was identical to the current threshold under the eight-hour ozone designation. Therefore, controls to satisfy RACT for most major sources under the eight-hour ozone designation were implemented by the TCEQ under

p

Specified information regarding the TCEQ's NO X and VOC RACT analysis is provided in Appendix

D: Reasonably Available Control Technology Analysis ; Table D-1: State Rules Addressing RACT Requirements in CTG and ACT Reference Documents provides additional details on the CTG and Alternative Control Techniques (ACT) source categories; and Table D-2: State Rules Addressing RACT Requirements for Major Emission Sources in the HGB Area provides additional detail on the non-CTG/ACT major emission source categories.

4.4.2 NO X RACT Determination

T the FCAA requirements for NO X RACT. The MECT program and accompanying Chapter 117 rules represent one of the most comprehensive NO X control strategies in the nation and encompass both RACT and beyond-RACT levels of control. Excep t for the EPA's Glass Furnace ACT document, the current EPA-approved Chapter 117 rules fulfill RACT requirements for all CTG and ACT NO X source categories. For non-CTG/ACT major NO X emission source categories, RACT is fulfilled by the MECT program or by separate source-specific rules in Chapter 117 for sources that NO X controls are technologically and economically feasible.

The TCEQ identified one major source glass manufacturing facility, Longhorn Glass Corporation (TCEQ Account No. HG-0028-R), in the 2006 point source emissions inventory for the HG

T through the site's New Source Re Longhorn's oxy-fired glass furnace to meet a NO X emission specification of 1.48 pounds per ton of glass produced. This control requirement is more stringent than the current Chapter 117 NO X emissions specification of 4.0 po unds per ton of glass produced for glass furnaces that was approved by the EPA as part of the 2007 Dallas-Fort Worth eight-hour ozone attainment demonstration and is sufficient to satisfy RACT for the glass furnace cate gory for the HGB

n

4.4.3 VOC RACT Determination The TCEQ's analysis demonstrates that the current VOC rules and controls for the HGB area satisfy the FCAA requirements for RACT for all CTG or ACT VOC source categories specific to any CTG or ACT documents issued prior to 2006. RACT for all non-CTG/ACT major VOC emission source categories that controls are technologically

a4-8 in 2006

006

008

2008

• Miscellaneous Metal and Plastic Parts Coatings, Group IV Issued in 2008

CTG documents are provided in ppendix D: Reasonably Available Control Technology Analysis

. • Flat Wood Paneling Coatings, Group II Issued in 2006

• Flexible Packaging Printing Materials, Group II Issued

• Industrial Cleaning Solvents, Group II Issued in 2006

• Offset Lithographic and Letterpress Printing, Group II Issued in 2

• Large Appliance Coatings, Group III Issued in 2007

• Metal Furniture Coatings, Group III Issued in 2007

• Paper, Film, and Foil Coatings, Group III Issued in 2007

• Auto and Light-Duty Truck Assembly Coatings, Group IV Issued in 2

• Fiberglass Boat Manufacturing Materials, Group IV Issued in

• Miscellaneous Industrial Adhesives, Group IV Issued in 2008

The following provides a brief summary of the TCEQ's determinations regarding these 11 CTG documents. Additional details regarding the eval uation of the 11

A

4.4.3.1 CTG Documents That Are Not Applicable to the HGB Area The TCEQ provides a negative declaration for th e Automobile and Light-Duty Truck Assembly Coatings and the Flat Wood Paneling Coatings CTG documents. The TCEQ determined that no sources meeting the applicability criteria recommende d in these two CTG documents are located in

e HGB area. th

4.4.3.2 CTG Documents That Do Not Represent RACT for the HGB Area For the following three CTG documents, the TCEQ determined that the CTG recommendations either do not represent RACT due to economic or technol ogical feasibility concerns or that the current Chapter 115 rules are equivalent or superior to the CTG-recommended controls: Fiberglass Boat Manufacturing Materials; Flexible Packaging Printing Materials; and Paper, Film, and Foil Coatings. Therefore, the TC EQ is not implementing any rule amendments or new rules associated with these

TG categories. C

4.4.3.3 CTG Documents That a RACT Dete rmination Cannot Be Made at This Time The TCEQ is not making a determination at this ti me whether the Industrial Cleaning Solvents or the

Miscellaneous Industrial Adhesives CTG recommenda tions represent RACT for Texas. The TCEQ's initial assessment indicates that the EPA substantially underestimated the scope and potential impact of the CTG recommendations and that implem enting the CTG recommendations would have widespread and potentially adverse impacts to small businesses and micro-businesses. The TCEQ

will continue to evaluate these CTG documents and plans to provide small business outreach to engage stakeholders that could be potentially impacted by the EPA's suggested control measures. A RACT determination for these CTG categories will be made after adequate stakeholder input and the TCEQ has determined the impact to small busin esses , economic and technological feasibility, and

ractical enforceability of the CTG recommendations. p

By letter dated December 8, 2008, the TCEQ reque sted clarification from the EPA regarding several issues related to the following three CTG documen ts: Large Appliance Coatings; Metal Furniture Coatings; and Miscellaneous Metal and Plastic Pa rts Coatings. A number of the recommended VOC content limits for specific coatings categories in th e CTG documents are less stringent than the more general VOC content limits specified in the EPA 's original CTG recommendations. The TCEQ requested clarification to assure that implementing the CTG recommendations would not be considered as backsliding and to be certain that the TCEQ has the appropriate information to determine whether the CTG recommendations actually represent RACT for Texas. As of September 4, 2009, the EPA has not responded to the TCEQ request for clarification on the CTG recommendations. Therefore, the TCEQ is not maki ng a determination at this time whether these CTG recommendations represent RACT for Texas until the EPA provides clarification to the issues4-9 ate the CTG recommendations in identified by the TCEQ and staff has had suffici ent time to evalu context with the EPA's response.

4.4.3.4 CTG Documents That Represent RACT for the HGB Area The TCEQ has determined that portions of the Offset Lithographic and Letterpress Printing CTG recommendations represent RACT for the HGB area. Concurrent with this SIP revision, the TCEQ is proposing rulemaking to limit the VOC content of solvents used by offset lithographic printing facilities in the HGB area (Rule Project 2008- 019-115-EN). The proposed rulemaking would implement the CTG recommendations to reduce the VOC content of the fountain solutions and cleaning materials. Additionally, the proposed rulemaking would expand the current rule applicability to include smaller sources not currently subject to the rule. The TCEQ is not implementing any rule amendments or new rul es associated with the CTG-recommended control requirements for heatset presses or with the letterp ress printing portion of this CTG document for the

GB area. Additional discussion concerning the TCEQ's determination regarding the CTG

endix D: Reasonably gy Analysis

.

AA as a requirement that st ates incorporate into their SIP all reasonably
vailable control measures that would advance a re gion’s attainment date. However, regions are

potential control strategy concepts for the RACM nalyses of stationary and mobile sources include both the strategies presented to stakeholders in March 2008 and the strategies suggested by stakehol ders during the informal stakeholder comment

process. H recommendations for heatset press and letterpress printing is provided in App
Available Control Technolo

4.5 REASONABLY AVAILABLE CONTROL MEASURES ANALYSIS
4.5.1 General Discussion States are required by § 172(c)(1) of the FCAA to “provide for implementation of all reasonably available control measures as expeditiously as practicable” and to include RACM analyses in the SIP. In the General Preamble for implementation of the FCAA Amendments of 1990 published in the April 16, 1992, issue of the Federal Register (57 FR 13498), the EPA explains that it interprets § 172(c)(1) of the FC

a obligated to adopt only those measures that are r easonably available for implementation in light of

local circumstances.

The TCEQ used a two-step process to identify pot ential control strategies for the HGB area RACM analysis. The TCEQ compiled a list of potentia l control strategy concepts based on an initial evaluation of the existing control stra tegies and existing sources of VOC and NO X in the HGB area. Stationary sources outside the HGB area within e ither a 100 kilometer (km) or 200 km range of the

HGB area were also considered fo r this initial evaluation. According to the EPA's guidance, sources

of VOC must be within 100 km of the nonattainment area and sources of NO X must be within 200 km. The EPA allows states the option of co nsidering control measures outside the ozone nonattainment area that can be shown to advance attainment; however, consideration of these sources is not a requirement of the FCAA. Draft lists of pot ential control strategy concepts for stationary and mobile sources were developed from this initial ev aluation. The draft lists of potential control strategy concepts were presented to stakeholders for comment at stakeholder meetings held in the HGB area on March 25 and 26, 2008. The TCEQ requested comment on the potential control strategies and invited stakeholders to suggest a ny additional strategies that might help advance

attainment of the HGB area. The final lists of

aEach potential control measure identified through the control strategy development process was

evaluated to determine if the measure would meet established criteria to be considered reasonably available. The TCEQ used the general criteria sp ecified by the EPA in the proposed approval of t

4-10 he ew Jersey RACM published in the January 16, 2009, issue of the Federal Register (74 FR 2945):

d and non-road emi ssion source categories that meets the

e does not cause ‘‘s ubstantial widespread and long-term

• The control measure can advance the attainment date by at least one year.

eight-hour ozone duction benefit in terms of parts per b illion (ppb) using modeling sensitivity runs.

ted control measure was onsidered not RACM because reasonable controls were already in place.

implemented earlier than January 1, 2018, the easure should be implemented as early as feasible.

re to reduce the HRVOC cap for Harris County is

cluded in Section 4.6: New Control Measures

.

impacts, or ability of the measure to advance atta inment of the NAAQS. Additional information and N

RACM is defined by the EPA as any potentia l control measure for application to point, area, on-roa f

ollowing criteria:

• The control measure is technologically feasible

• The control measure is economically feasible

• The control measur

a dverse impacts’’

• The control measure is not ‘‘absurd, unenforceable, or impracticable’’

The EPA did not provide guidance in the Federal Register on how to interpret the criteria " advance the attainment date by at least one year." Because modeling all possible year scenarios for potential control measures is not practical, the TCEQ evalua ted whether a potential control measure would help the HGB area make progress toward attainment of the NAAQS based on potential

re

The TCEQ also considered whether the control meas ure was similar or identical to control measures already in place in the HGB area. If the suggested control measure would not provide substantive and quantifiable benefit over the existing control measure, then the sugges

c

The control measure must be able to be implem ented before and reduce emissions prior to the beginning of the ozone season immediately before th e attainment date. The attainment date for the 1997 eight-hour ozone NAAQS for the HGB area is J une 15, 2019. Any control measures must be implemented and emissions reducti ons made no later than January 1, 2018. However, the HGB area must make progress toward attainment of the 1997 eight-hour ozone NAAQS as expeditiously as practicable. Therefore, if control measures can be

m

4.5.2 Results of RACM Analysis Based on the RACM analysis, the TCEQ determined that only one potential control measure met the

criteria to be considered RACM. A reduction in the HRVOC cap for Harris County under the HECT program was determined to help advance attainme nt of the HGB area and to meet the other RACM criteria. Reported HRVOC emissions from sources in the HECT program during the first two years of the HECT program, calendar years 2007 and 2008, av eraged approximately 56 percent of the total allocated HRVOC allowances for Harris County. Beca use there is a demonstrat ed substantial surplus in the HRVOC cap, a 25 percent reduction in the cap for Harris County is technologically feasible

and should have minimal economic impact. Modeling demonstrates that a 25 percent reduction in the HRVOC cap for Harris County will help the HGB ar ea make progress toward attainment of the 1997 eight-hour ozone NAAQS. Based on 2007-2008 emi ssions, a 25 percent reduction would leave a buffer of approximately 600 tpy, or more, in the cap that should be sufficient to account for any significant variations in HRVOC emissions in futu re years due to emission events and scheduled startup, shutdown, and maintenance events as well as allow for future economic growth. Additional discussion regarding the proposed control measu

in

All other potential control measures evaluated for both stationary and mobile sources were determined not to be RACM due to technologi cal or economic feasibility, enforceability, adversespecific details regarding the RACM analysis f

4-11

o r the HGB area are contained in Appendix E: easonably Available Control Measure Analysis

.

ASURES R

4.6 NEW CONTROL ME 4.6.1 Stationary Sources 4.6.1.1 HECT Cap Reduction and Allowance Reallocation The proposed revisions to the HECT Program Cap ru le would result in a 25 percent reduction in the total HECT allowance cap and revise the HRVOC allocation methodology. The HECT program was adopted by the commission as an ozone control m easure for the H GB area on December 1, 2004.

urrently, the HECT program is applicable only in Harris County.

. S ee Chapter 3: PHOTOCHEMICAL MODELING for rther discussion regarding the modeling.

eeded to account for the inherent variability of HRVOC emissions associated with these

ctivities.

pproach while contributing to the area’s attainment of the AAQS as expeditiously as practicable.

olymer, plastics, and other chemical producers may have not received a

ufficient allocation.

rates ssociated with the processes of the industry sect ors with HRVOC emissions in Harris County. C

Photochemical modeling analysis demonstrates that a 25 percent reduction of the HECT cap on the total Harris County HRVOC allocation would adva nce attainment of the 1997 eight-hour ozone NAAQS by reducing the future 2018 ozone design values (DV 18 s) at all HGB monitors. Future design value calculations were based on 2006. The largest decrease in the projected DV 18 s (0.24 ppb)

was at the Deer Park monitor. The average decrease for all sites was 0.11 ppb. The three HGB monitors projected to be exceeding the eight-hour ozone NAAQS (i.e., DV 18 > 84 ppb) in the 2018 future case modeling, also exceed in the HECT sensitivity modeling. The Wallisville monitor has the highest predicted DV 18 (88.3 ppb) in the 2018 future case modeling, and continues to be the highest in the HECT sensitivity modeling (88.1 ppb)

fu

HRVOC data from the first two years indicates that the total reported actual emissions from sources in the HECT program are approximately 50 percent of the total HRVOC cap. Because the HRVOC rules in Chapter 115, Subchapter H, Divisions 1 a nd 2, require emissions from startup, shutdown, and maintenance activities be included in the HECT progr am, the total surplus observed in the first two years of the program cannot be removed. Proposing a 25 percent reduction leaves a buffer in the cap

that is still n

a

Following the initial allocation of allowances, co mpanies participating in the HECT program commented that the allocation was not equitably di stributed and that some sites did not receive enough allocations while other sites received allocations greater than necessary. Monitoring data supports the assertion of an inequitable distributi on of allowances. Revisions to the rule are anticipated to result in a more equitable a

N

The existing allocation methodology was based on th e total amount, in pounds, of HRVOC produced as an intermediate, byproduct, or final product, or u sed by a process unit at each participating site. Analysis of the monitoring data from previous cont rol periods indicate that refineries may have been over-allocated while p

s

The rule revision proposes a new allocation me thodology beginning with the 2011 calendar-year control period based on actual emissions data with the goals of fairly and equitably distributing the compliance burden for HECT program participan ts, applying credit for controlling and reducing HRVOC emissions, and not rewarding or encour aging emissions from emissions events. The proposed revised allocation methodology is based on calculating “uncontrolled” or “precontrolled” emissions for facilities using reported control effi ciencies based on the specifications for flares in Chapter 115; creating a 250 ton emission event set aside pool to encourage market trading; and dividing the cap into four industry-type sector pools to account for different HRVOC emission

aThe proposed rulemaking would also reduce the cap in a gradual step down fashion beginning with a 10 percent cap reduction at the beginning of the 201 4 calendar-year control period, and co

4-12 ntinue to duce the cap to a total of 25 percent in a nnual five percent reductions from 2015 to 2017.

Houston- Galveston-Brazoria State Implementation Plan repared by ENVIRON for the H-GAC). re

4.6.2 Local Programs The H-GAC worked with HGB area local govern ments and business stakeholders to develop appropriate control strategies to meet the SIP re quirements and to recruit stakeholders who would take legal responsibility for implementing these stra tegies through the establishment of memoranda of agreement. As a result, six projects were iden tified as Transportation Control Measures (TCMs), and numerous strategies were agreed upon with local governments as voluntary measures. For more information regarding the development of local control strategies, see Appendix F: Evaluation of Mobile Source Control Strategies for the (p

4.6.2.1 Transportation Control Measures TCMs are transportation projects and related activi ties that are designed to reduce on-road mobile source emissions and are included as control measures in the SIP. Allowable types of TCMs are listed in § 7408 (Air Quality Cr iteria and Control Techniques) of the FCAA, and defined in the federal transportation conformity rule found in 40 CFR, Part 93 (Determining Conformity of Federal Actions to State or Federal Implementation Plans) . The federal transportation conformity rule requires that timely implementation of TCMs be dem onstrated. In general, TCMs are transportation related projects that attempt to reduce vehicle use, change traffic flow, or reduce congestion conditions. Projects that add single-occupancy-vehicle roadway capa city or are based on provements in vehicle technology or fu els are not considered to be TCMs.

AC’s Technical dvisory Committee approved and identified funding for these local commitments. im

The H-GAC has identified TCMs that have been or will be implemented in the nonattainment area. By the start of the 2018 ozone season, these TCMs will reduce NO X emissions in the HGB area by .015 tons per day (tpd). Appendix G: Transportation Control Measures for the HGB Attainment

Demonstration SIP Revision for the 1997 Eight-Hour Ozone Standard (prepared by ENVIRON for the H-GAC) summarizes the emission reductions by type of TCM. The H-G

A

4.6.2.2 Voluntary Mobile Emission Reduction Programs Voluntary mobile source measures have the potential to contribute, in a cost-effective manner,

mission reductions needed for progress toward attainment and maintenance of the NAAQS.

ctor activity levels or changes in vehicle and engine fleet composition were explored nd developed.

gaging the public to make changes in activities at will result in reducing mobile source emissions. e

Historically, federal mobile source control strategi es have focused primarily on reducing emissions per mile through vehicle and fuel technology impr ovements. Tremendous strides have been made resulting in new light-duty vehicle emission standards that are 70 to 90 percent less than that for the 1970 model year. However, mobile sources contin ue to constitute a significant portion of ozone precursor emissions in the HGB area due to popula tion and employment growth as well as an increase in daily vehicle miles traveled per person. Ther efore, mobile source strategies that attempt to complement existing regulatory programs through voluntary, non-regulatory changes in local transportation se

a

A number of voluntary mobile source and transportati on programs have already been initiated at the state and local levels in response to increasing interest by the public and business sectors in creating alternatives to traditional emission reduction strategies. Some examples include economic and market-based incentive programs, trip reduction pr ograms, growth management strategies, ozone action programs, and targeted public outreach. Thes e programs attempt to gain additional emissions reductions beyond mandatory FCAA pr ograms by en

thThe H-GAC identified three voluntary measures that w ill aid in the improvement of the HGB region’s air quality. These measures were identified through a contract between H-GAC and ENVIRON International Corporation. Nineteen meetings were held with stakeholders from the region to solicit comments and suggestions for voluntary programs. The H-GAC’s commitment for NO X from VMEP is 2.25 tpd. The H-GAC, as the regional metropo litan transportation planning agency for the HGB area, has committed to make a good faith effort to implement the projects and/or programs outlined in this document and will be responsible for monito ring and reporting the emission reductions to the TCEQ. More information on each of the VMEP commitments can be found in Appendix H: Voluntary Mobile Emission Reduction Programs for the HGB Attainment Demonstrat

4-13 ion SIP evision for the 1997 Eight-Hour Ozone Standard (prepared by ENVIRON for the H-GAC).

Eight-County HGB Area . For additional detail, see Appendix B : Emissions ventory Development

.

T n ight-County HGB Area R

4.7 Motor Vehicle Emissions Budget (MVEB)

The MVEB refers to the maximum allowable emissions from on-road mobile sources for each applicable criteria pollutant or precursor as de fined in the SIP. The budget must be used in transportation conformity analyses. Areas must demonstrate that the estimated emissions from transportation plans, programs, and projects do not exceed the MVEB. The attainment budget represents the on-road mobile source emissions that have been modeled for the attainment demonstration. The budget reflects all of th e on-road control measures reflected in that
demonstration. The MVEB is shown in Table 4-2: 2018 Attainment Demonstration Motor Vehicle Emissions Budget for the

In

able 4-2: 2018 Attainme t Demonstration MVEB for the E
Eight-County HGB Area Summer Weekday Emis tpd) sions (

NO X VOC 2018 MVEB 49.22 45.97

4.8 MONITORING NETWORK States are required by 40 CFR, Part 58, Subpart B, to submit an annual monitoring network review to the EPA by July 1 of each year. This network review is required to pr ovide the framework for establishment and maintenance of an air quality surv eillance system. The annual monitoring network review must be made available for public inspection for at least 30 days prior to submission to the EPA. The review, and any comments received du ring the 30 day inspection period, are then

forwarded to the EPA for final revi ew and approval. The TCEQ posted this plan from June 1 through June 30, 2009. The document presented the current Texas network of ambient air Photochemical Assessment Monitoring Station (PAMS) monitors as well as proposed changes to the network from

uly 1, 2009, through December 31, 2010.

sampling at the Deer Park

onitor (AQS ID 48-201-1039) will co ntinue January through December. J

This network review includes posting of the TC EQ's EPA-approved PAMS Network Plan which focuses on ozone precursors. The reclassification of the Houston ozone nonattainment area to severe requires one major change in the HGB area PAMS plan. The TCEQ will conduct intensive carbonyl sampling at the Clinton PAMS Type 2 Site (AQS ID 48-201-1035) each year. As agreed upon with the EPA, Region 6, the TCEQ will collect a total of 240 carbonyl samples at this site at a sampling frequency of eight 3-hour samples per day every three days during July-September. Carbonyl sampling will be terminated at the Houston Channe lview site to offset this increased sampling schedule at the Clinton site. The 24 hour sample ev ery sixth day carbonyl

m

4.9 CONTINGENCY PLAN SIP revisions for nonattainment areas are required by § 172(c)(9) of the FCAA to provide for specific measures to be implemented should a nonattainment area fail to meet reasonable further progress (RFP) requirements or attain the applicable NAAQS by the attainment date set by the EPA. These contingency measures are to be impl emented without further action by the state or the EPA. In theGeneral Preamble for implementation of the FCAA Amendments of 1990 published in the April 16, 1992, issue of the Federal Register (57 FR 13498), the EPA interprets the contingency requirement to

mean additional emissions reductions that are suffici ent to equal up to 3 percent of the e

4-14 missions in e adjusted base year inventory. These emissions reductions should be realized in the year following

our Ozone Nonattainment Area Reasonable Further Progress IP revision (Project No. 2009-018-SIP-NR), wh ich is being proposed concurrently with this

ble Further Progress Demonstration alculations Spreadsheet of the HGB 1997 Eight-Hour Ozone Nonattainment Area Reasonable

Table 4-3: 2019 Contingency n for the HGB Area th the year in which the failure is identified (i.e ., an RFP milestone year or attainment year).

The adjusted base year emissions inventory is used in the RFP planning process to calculate required emissions reduction targets and excludes certain on-road mobile source emissions reductions from controls that were promulgated prior to the 1990 amendments to the FCAA. This 1997 eight-hour
ozone attainment demonstration SIP revision also uses the adjusted base year inventory as the inventory from which to calculate the required 3 percent reduction for contingency. For further information regarding the adjusted base year inve ntory for the HGB area and how the area meets RFP requirements, see the HGB 1997 Eight-H

S
attainment demonstration SIP revision.

A summary of the 2019 contingency analysis is provided in Table 4-3: 2019 Contingency Demonstration for the HGB Area . Consistent with the EPA’s NO X substitution guidance, the 3 percent attainment demonstration contingency analysis for 2019 is based on a 2 percent reduction in

NO X emissions (17.16 tpd) and a 1 percent reduction in VOC emissions (9.36 tpd) to be achieved between 2018 and 2019 ( EPA, 1993). Inventory analyses were performed on the fleet turnover effects for the federal emission certification prog rams for on-road and non -road vehicles. The
emission reductions from 2018 to 2019 were estimated for these programs. For a detailed description of the contingency redu ctions, see Appendix 1: HGB Reasona

C Further Progress SIP revision (Project No. 2009-018-SIP-NR).

Demonstratio

Description NO X V OC

Adjusted 2018 Base Year Emissions Inventory 8 93 58.18 5.57

Percen t for Contingency Calculation (total of 3 percent) 2.00 1.00

2018 to 2 17.1 019 Required Contingency Reductions 6 9.36

Federal On-Road Mobile New Vehicl e Certification Standards 3.97 2.73

Federal On-Road Reformulated Gasoline (RFG) 5.09 0.70
State I/M and Anti-Tampering Programs (Brazoria, Fort Bend, ery Counties) Galveston, Harris, and Montgom 1.23 0.31

Federal Non-Road Mobile New Vehicl e Cert ification Standards 3.56 1.78

Non-Road RFG Gasoline 0.00 0.03

Federal Tier I and II Locomotive Standards 0.68 0.01

Federal Tier 2 Marine Diesel Standard 0.55 0.02

Additional Contingency Measures to be Quantified before 2019 2.08 3.78

Total Contingency Reductions 17.1 6 9.36

Contingency Excess ( +) or Shortfall (-) 0.00 0.00

N ote: Emissions are represented in tons per day.

re study before emissions reduc tions can be quantified To meet the contingency requirement, the TCEQ will evaluate potential control measures to be implemented at the state level that require mo4-15 are not yet final or have not yet been implemented. Potential measures clude but are not limited to the following:

Potentia and federal measures that

in

l State Measures

Gas Imaging "Find and Fix" Rule Contingency measure rule to require the use of gas imaging camera t • echnology for periodic spection of sources of VOC emissions such as storage tanks, barges, etc., that are not

ontingency measure rule to requiree use of gas imaging camera technology for more frequent monitoring on difficult-toto-monitor components that would normally have very long monitoring frequencies under traditional LDAR monitoring rules.

Potentia in

c urrently subject to leak detection monitoring programs and set reasonable time periods for companies to address possible problems found (e.g., leaking seals).

• Enhanced LDAR for Difficult-to-Monitor Components C

th

monitor and unsafel Federal Measures

• International Maritime Engine Emi ssion Standards for Oceangoing Vessels

m

nover.

•

r E rules are part of a larger federal energy bill, H.R. 6, which was signed into law on December 19, 2007. The

in 2019.

e in 2013.

• EPA Proposed Rule to Reduce Air Toxics Emi ssions from Area Source Asphalt Refining and

would likely go into effect before 2019.

• EPA Final Rule for National Volatile Organi c Compound (VOC) Emission Standards for

nd reactivity factors go into effect July 2009.

Any measure used to meet the contingency requirementwill be included in the SIP for the 1997 eighthour ozone standard in the HGB area before 2019. I f implemented by the EPA, this measure woul d result in annual emissions reductions fro

fleet tur

Potential Enhanced Corporate Average Fuel Economy (CAFE) Standards for Cars and

Trucks The original federal measure in creased the fuel economy of vehicles starting with model yea 2011 to approximately 35 miles per gallon (mpg) in 2020. The CAF

a dministration is proposing to move the 35-m pg requirement to 2016. This measure would

result in fleet turnover reductions that could be available

• EPA Proposed Rule to Reduce Air Toxics from Stationary Diesel and Gas-Fired Engines If finalized, this rule would become effectiv

A sphalt Roofing Manufacturing Facilities If finalized, this rule

Aerosol Coatings

Final rule amendments to a dd compounds a4-16 .10 REFERENCES

PA, 1993. NO Substitution Guidance, http://www.epa.gov/ttncaaa1/t1/memoranda/noxsubst.pdf 4

E X

EPA, 2005. Clean-Fuel Vehicle Standards, no. CCD-05-12.5-1 CHAPTER 5: WEIGHT OF EVIDENCE

5.1 QUANTITATIVE CORROBORATIVE ANALYSIS
5.1.1 Introduction The corroborative analysis presented in this ch apter demonstrates the progress that the HoustonGalveston-Brazoria (HGB) area is making towards attainment of the 1997 eight-hour ozone National Ambient Air Quality Standard (NAAQS) of 0.08 parts per million (ppm). The United States Environmental Protection Agency’s (EPA) April 2007 “Guidance on the Use of Models and Other Analyses for Demonstrating Attainment of Air Qu ality Goals for Ozone, PM2.5, and Regional Haze” (EPA, 2007) states that all model attainment demonstr ations should include supplemental evidence that

the conclusions derived from the basic attainment modeling are supported by other independent sources of information. This document will present the s upplemental evidence, i.e., the corroborative analyses, for the current modeling demonstration. The guidance also states that a weight of evidence demonstration is allowed when the future design value is at or below 87.9 parts per billion (ppb).

The first section of the quantitative corroborative an alysis will discuss photochemical grid modeling. Modeling is one of the most important tools availa ble for evaluating progress toward meeting air quality standards, but it is not a perfect tool. The firs t section will also discuss known issues with photochemical grid modeling and how the Texas Commission on Environm ental Quality (TCEQ) has dealt with them. It also discusses overall model performance. Finally, it discusses the diagnostic analyses performed by the TCEQ, and the implications of those analyses on the projected attainment status. The second section of the quantitative corroborative analysis will discuss tre nds in ozone and ozone precursors observed in the HGB area, and examines the possible causes for those trends. The third section describes air quality control measures that cannot yet be adequately quan tified but are nonetheless expected to yield tangible air quality benefits.

5.2 Corroborative Analysis: Modeling Photochemical grid modeling of the HGB area is cha llenging, due to complex coastal wind circulation, complex petrochemical point sources of emissions in Brazoria, Chambers, Galveston, and Harris Counties, and the challenges associated with modeling a metropolitan area of over five million

inhabitants.

One purpose of the Texas Air Quality Study 2000 (T exAQS 2000) and the Texas Air Quality Study 2006 (TexAQS II) field studies was to address the uncertain ties that affect photochemical grid modeling and their regulatory applications. Insights gleaned from the TexAQS 2000 and subsequent studies have helped resolve some of these uncertainties.

Several studies have tried to identify and reduce uncer tainties in the HGB photochemical grid modeling. Foremost among these efforts are the studies that have sought to quantify underreported industrial highly reactive volatile organic compounds (HRVOC) emissi ons (Wert et al., 2003; Xie and Berkowitz, 2007; Yarwood et al., 2004; TCEQ, 2002, 2004, 2006; Smith and Jarvie, 2008) and to assess the sensitivities of ozone simulations to underreporting these emissions (TCEQ, 2002, 2004, 2006; Byun et al., 2007; Jiang and Fast, 2004). Other modeling efforts have tested different chemical mechanisms in the HGB area’s photochemical grid modeling, to study the effect s of using different mechanisms on ozone model performance and control strategy effectiveness (Byun et al., 2005b; Faraji et al., 2008; Czader et al., 2008). Modeling sensitivity studies have also been performed to guide selection of model parameters such as vertical mixing schemes, number and depth of model layers, and horizontal grid resolution (Kemball-Cook et al., 2005; Byun et al., 2005b; Byun et al., 2007; Bao et al., 2005).5-2 Some of the most important findings of these studies include the following.

• Emissions inventories must be reconciled to so me extent with observational data before the model can accurately depict the ozone forma tion processes in the HGB area, especially for

HRVOC.

• Adding HRVOC to modeling emissions inventori es generally increases ozone concentrations and alleviates a portion of the ozone and HR VOC under-prediction problems found by every modeling group who has attempted to model the HGB area.

• Reactivities of the TCEQ-defined HRVOC are high regardless of which chemical mechanism is

used to evaluate their effects. In addition to the TCEQ list of HRVOC, formaldehyde also displays high reactivity.

Mesoscale meteorological modeling is used to drive photochemical grid models, and many studies have examined and reduced uncertainties in these models as well. One of the most successful efforts improved meteorological simulations of ozone episodes by usi ng radar profiler and other upper level wind data to “nudge” the meteorological modeling (Nielsen-Gammon et al., 2007; Zhang et al. 2007; Stuart et al., 2007; Bao et al., 2005; Fast et al., 2006). Other efforts improved land cover data and land surface modeling (Byun et al., 2005a; Cheng et al., 2008a, 2008b) and studied the sensitivity of ozone simulations to solar irradiance and photolysis rates (Zamora et al., 2005; Fast et al., 2006; Pour-Biazar et al., 2007; Byun et al., 2007; Koo et al., 2008).

Some of the most important findings of these mete orological modeling studies include the following.

• Assimilation of radar profiler and other upper ai r wind data is essential to good meteorological modeling performance in the HGB area.

• Modeling parameterizations need to be chosen carefully to alleviate the common problem of spurious thunderstorms and clouds.

• Accurate simulation of cloud c over is crucial to getting photolysis rates correct in the photochemical grid model, and ozone predictions are very sensitive to photolysis rates.

• An ensemble approach to meteorological and photochemical grid modeling may be warranted, given the sensitivity of ozone modeling to rela tively small changes in meteorology. The ensemble approach will allow probabilistic attainment demonstrations to be produced.

In the remainder of this section, modeling issues identified by the studies described above will be discussed, as well as issues raised by TexAQS 2000 research, by TexAQS II research, and by TCEQsponsored investigations. Overall performance of the photochemical grid modeling and the implications of the model’s ability to accurately simulate ozone episodes will also be discussed. Finally, additional metrics that show the effects of the proposed control strategies on ozone in the HGB area will be presented.

5.2.1 Solving Modeling Problems For the HGB area, there are several aspects of ozone m odeling that require special attention, due to their role in current or historical shortcomings in m odel performance. This section discusses some of these issues, and how TCEQ has attempted to resolve them in this round of modeling.

5.2.1.1 Industrial Point Source Emission Inventory Issues High concentrations of light alkenes such as propylen e, ethylene, 1,3-butadiene, and butenes have been observed in the HGB metropolitan area, and are closel y associated with petrochemical industry facilities in eastern Harris, Galveston, Chambers, and Brazoria Counties (Ryerson et al., 2003; Daum et al., 2003; Daum et al., 2004; Berkowitz et al., 2004; Berkowitz et al., 2005; Kleinman et al., 2002; Kleinman et al., 2005; Jobson et al., 2004; Karl et al., 2003; Buzcu and Fraser, 2006; Xie and Berkowitz, 2006, 2007; Kim et al., 2005). These compounds have been identified as highly reactive, and they play a major role in forming the highest concentrations of ozone observed in the HGB area (Ryerson et al., 2003; Daum et al., 2003, 2004; Kleinman et al., 2002, 2005; Wert et al., 2003; Czader et al., 2008). Historical analyses of routinely collected volatile organic compounds (VOC) data indicate that these compounds are present in5-3 high concentrations on a routine basis in the HGB ar ea (Hafner Main et al., 2001; Estes et al., 2002; Brown and Hafner Main, 2002; Brown et al., 2002; Hafner and Brown, 2003; Jolly et al., 2003; Fang and McDowell, 2003; Jolly, 2003; Kim et al., 2005; Bu zcu and Fraser, 2006; Xie and Berkowitz, 2006, 2007). Consequently, the high HRVOC concentrations observe d during the two field study periods in 2000 and 2006 are not anomalously large, and the conclusi ons drawn from those data should be generally applicable to the HGB area.

Both field studies sponsored by the TCEQ, TexAQS 200 0 and TexAQS II, have indicated that there are substantial discrepancies in the reported emissions of HRVOC, especially ethene and propylene (Ryerson et al., 2003; Daum et al., 2003; Daum et al., 2004; Wert et al., 2003; Gilman et al., 2009; de Gouw et al., 2009). The TCEQ remote sensing studies of flares, st orage tanks, cooling towers, and other sources have shown that large quantities of VOC emissions have gone unreported (Robinson et al., 2008; Smylie et al., 2004). In addition, solar occultation flux measureme nts have shown that 30-minute variations in industrial HRVOC emissions can be an order of magn itude or more (Mellqvist et al., 2007, 2008).

In an attempt to better quantify underreported HRVOC for purposes of photochemical grid modeling, the TCEQ commissioned a study by researchers at the Pacific Northwest National Laboratory (Xie and Berkowitz, 2006, 2007). The researchers used hist orical HRVOC measurements from the extensive automated gas chromatograph network currently in place in the industrial areas of the HGB area. Most of the sites in this network went into operation during 2 003. Using trajectories to link the source areas to the observations, the researchers were able to estimate whic h areas had the greatest emissions relative to other

areas.

For the current round of modeling, TCEQ research ers extended the methods developed by Pacific Northwest National Laboratory to quantitatively est imate underreported HRVOC emissions in the HGB
area. The Potential Source Contribution Function method has measurably improved model performance for ozone and its precursors by reconciling the industr ial point source emissions inventory with observed HRVOC concentrations during 2005-2006 (Smith and Jarvie, 2008). This method does not attempt to reproduce the temporal variations in emissions, but instead calculates a median rate of emission for each square kilometer of the HGB area. Since two years of data are used to estimate the medians, the metric is statistically robust.

5.2.1.2 Modeling of Emissions Events Attempts have been made to quantify temporal variations in industrial point source emissions by accessing emission event reports that are delivered by industry to the TCEQ (Murphy and Allen, 2005). Problems with the event report data include the following.

• Emission events were self-reported by industry, and the quantities of emissions reported were not independently observed or verified. Facilities are allowed, by rule, to estimate emissions during emergency releases due to safety concerns.

• Emission events were only reported if estimated emissions were greater than a certain threshold above the permitted emission level. Some facilities have very large permitted emissions levels, and therefore large fluctuations in emissions may occu r under an authorized emission rate that are not included in the data set. Consequently, the frequenc y and magnitude of emission events in this data set does not reflect the actual magnitudes or frequency of emission events.

• Emission event data for the Murphy and Allen study were collected before industry was required to monitor HRVOC. Therefore, most of the emission estimates are not based upon measurements of

the events.

• The TCEQ infrared camera studies have found numerous instances where emissions were emanating from locations that were not included in any emissions inventory.

• The TCEQ flare investigations have found that flares are typically managed to reduce noise, smoke, and glare. Optimizing the flare to keep destru ction efficiency at a maximum is a secondary consideration. In particular, flares used as both emergency flares and process flares have been observed to operate with poor combustion effici ency when operating in process flare mode (Robinson et al., 2008).5-4 • In addition, flare monitoring records only the chem icals flowing to the flare, not which species are actually being emitted. Combustion efficiencies are estimates of how much of the original material has been destroyed, and no effort is made to estimate the composition or reactivity of the combustion products. Circumstantial evidence from the TexAQS II and from the Study of Houston Atmospheric Radical Precursors (SHARP) suggests that formal dehyde may be produced during flare combustion, though the absolute quantity of emissions may only constitute a small part of the observed ambient formaldehyde (Gilman et al., 2009; De Gouw et al., 2009). The SHARP field campaign in April-May 2009 is investiga ting this hypothesis in greater depth.

• Field studies (Mellqvist et al., 2007, 2008; de Gouw et al., 2009) and recent infrared camera and differential absorption lidar (DIAL) results (Robins on et al., 2008) show that the techniques used by industry to estimate HRVOC point source emissions are still inadequate to quantify them properly, because these experiments measured much hi gher emission fluxes than were reported.

A number of recent modeling studies have attempted to investigate the frequency, magnitude, and impact of emission events upon ozone in Houston (Webster et al., 2007; Nam et al., 2006, 2008). Since these studies are based upon the emission event reports, they have not properly quan tified the frequency or magnitude of the emission events, due to the problem s discussed above. Therefore, the modeled impact

of emission events described in the Webster et al. an d Nam et al. studies are unlikely to accurately reflect the complete impact of emission events in the HGB area. Since the acquisition of properly quantified

emissions for all industrial emission events that occur in the HGB area appears to be far in the future, the TCEQ has not attempted to speculate on the exact freque ncy or magnitude of sporadic emission events in this modeling exercise.

5.2.1.3 Resolution of Photochemical Modeling Grids Numerous studies have investigated the effects of gr id size on model behavior (Cohan et al., 2006; Esler, 2003; Gego et al., 2005; Valari and Menut, 2008). The main interest in finer grid resolution is that higher resolution can increase concentrations of ozone pr ecursors in narrow plumes, which can affect ozone production rate and sensitivity to VOC or nitrogen oxides (NO X ) within the plumes. In a city such as Houston, using a higher resolution grid is sensible, given the abundance of industrial point sources, which can generate narrow plumes. Researchers during Te xAQS 2000 determined that rapid ozone formation occurring within narrow industrial plumes are respons ible for the highest observed ozone in the HGB area, and for the strong ozone gradients that can fo rm. Strong ozone gradients can cause large increases in ozone concentration at monitoring sites as the plume is carried across town by winds that have shifted direction and are no longer parallel to the plumes. To resolve these atmospheric features, the TCEQ is using smaller-sized grid cells than previ ous modeling exercises (2 kilometer (km) × 2 km instead of 4 km

× 4 km). In general, the TCEQ has found that sm aller grid sizes can yield higher ozone production and can alleviate, in part, the commonly observed low bi as for ozone within industrial plumes. There are limits to this solution, however; it is inappropriate to decrease grid size indefinitely. Parameterizations in both the meteorological modeling and the photochemical grid modeling are based upon the assumption that turbulence features within the planetary boundary layer (PBL) are much smaller than the grid size. If the grid size is decreased to 1 km × 1km or lower, the assumption probably no longer holds, and more uncertainty can be added to the modeling as a result of the finer resolution. If smaller grid sizes are desired, large eddy simulation modeling should be consid ered rather than photochemical grid modeling.

Also, note that if the spatial resolution of the photoc hemical grid modeling is re duced, then the temporal resolution of the meteorological and chemical proce sses within the model ought to be reduced, to match the shorter residence time of precursors in each grid cell. In other words, as the size of the box shrinks, the amount of time that a mass of air resides in the box also shrinks, affecting how the ozone chemistry plays out. While the Comprehensive Air Model with Extensions (CAMx) automatically adjusts the time step for chemical processes, the meteorological process time step is fixed, based upon the input data from the Fifth Generation Meteorological Model (MM5). While it is possible to extract meteorological output with higher temporal resolution, reduction of the time steps seems likely to cause unusual model behavior. The reduction of time steps in regulat ory photochemical grid modeling has not been well studied. In the future, it may be desirable to use grid sizes smaller than 2 km, and shorter time steps, but for now, TCEQ will refrain from experimenting with fi ner resolutions. For this round of modeling, the5-5 TCEQ has reduced the size of the CAMx modeling grid cells from 4 km to 2 km through flexi-nesting, but has kept the size of the MM5 modeling grid cells at 4 km.

5.2.1.4 Incommensurability and Model Performance Evaluation Swall and Foley (2009) discuss the problems inherent in comparing point measurements to grid cell values. In statistical parlance, this problem is known as incommensurability. A portion of the difference between point measurements and grid cell values is due solely to the fact that measurements made at a monitoring station do not generally represent an average of the conditions for the 2 km × 2 km grid cell in which it resides. The ability of a point measurement to represent the average of the entire grid cell area is related to how much sub-grid variation is observed in the area. If sub-grid variation is small, then the point measurement and the grid cell value are commensurate. If the spatial gradients of the variables of interest are large, the point measure ments are less able to reflect the av erage conditions of the entire grid cell, and therefore they are incommensurate with the grid cell value.

HGB area ozone often has strong spatial gradients due to the rapid ozone formation within industrial source plumes. In the HGB area, the worst ozone model performance is sometimes found in areas with the steepest ozone gradients, and the best ozone model performance is often found in areas further downwind, where the ozone gradients have lessened. Swall and Foley demonstrated that incommensurability alone is capable of degrading mode l performance in areas of steep gradients. They state in their discussion: “This means that, even if the model is performing perfectly and there is no observational error, we cannot expect that in a scatterplot, points representing paired modeled and

observed values will lie on a one-to-one line. Our co mparison of Gaussian and exponential correlation structures with the same effective range shows that th is concern looms larger for correlation structures in which there is a rapid decrease in correlation for sm all distances relative to grid cell size (like the exponential).” While there are other causes of poor model performance as well, note that incommensurability is likely to be responsible for some of the differences between model output and point measurements.

5.2.1.5 Ensemble Modeling A number of researchers have discussed the benefits of using ensembles of models to create more accurate forecasts (Pinder et al., 2009; Zhang et al., 2007). Pinder et al. and Zhang et al. have noted that probabilistic attainment demonstra tions could be made using ensemb le modeling and have argued that this approach can be more scientifically sound than a deterministic attainment de monstration. The TCEQ acknowledges the potential soundness of the ensemble a pproach but notes that the current regulatory framework does not easily allow for a pr obabilistic attainment demonstration.

5.2.1.6 Vertical Distribution of Ozone

Ozonesonde measurements have been made each summer in the HGB area since 2003 (Morris et al., 2006). Findings from this study indicate that elevated free tropospheric ozone (i.e ., above the PBL) in the HGB area is usually underestimated, and it often does not appear to mix down to the ground. Ozone in the lowest layers of the atmosphere often shows much more structure than the model simulates. The implication is that the model is mixing the lowest laye rs of the atmosphere more efficiently than they are actually mixing. The TCEQ has attempted to addr ess these two issues. For the free tropospheric ozone, the TCEQ has obtained global model output for the appr opriate time periods so that boundary conditions of free tropospheric ozone are more appropriate. Some of the discrepancies still pers ist; they appear to be related to phenomena that occur between the outer most domain boundaries and the HGB area. . For the PBL mixing issue, the TCEQ has improved the land cover data and sea surface temperature data in its latest round of modeling, in an attempt to improve the simulations of surface energy balance. In addition, the TCEQ has chosen the Eta PBL scheme (i.e., the Mellor-Yamada-Janjic scheme), which appears to be more effective at simulating PBL dynamics in the coastal regions than other available schemes. The TCEQ continues to investigate potential improvements for vertical mixing in the modeling.

5.2.1.7 Photolysis Discrepancies Due to Improper Placement of Clouds Researchers at the University of Alabama-Huntsville performed a modeling study that examined the effects of modeled cloud cover on ozone performance in the HGB area, and found that some of the5-6 shortcomings in model performance could be corrected with better depiction of clouds (Pour-Biazar et al., 2007). University of Houston researchers also found that their forecasts were occasionally biased due to poor depiction of cloud cover (Byun et al., 2007) . TCEQ-funded research found that higher-order decoupled direct method analysis of modeling sensitiv ities indicated substantial sensitivity to photolysis rates (Koo et al., 2008).

The TCEQ has found similar cloud cover effects in the photochemical modeling for this state implementation plan (SIP). The greatest discrepan cies tend to involve the model under-predicting cloud cover, and hence, greatly over-predicting ozone on low ozone days. Modeled episode days for which cloud cover problems exist include: May 28, 2005; J une 17, 2005; July 31, 2005; Aug 5, 2005; May 31- June 1, 2006; Aug 15, 2006; Aug 19, 2006; Aug 22, 2006; September 12, 2006; October 10, 2006. The average mean normalized bias for these days is +34.6 percent, compared to an average mean normalized bias on exceedance days of +9.7 percent. TCEQ pr ocess analysis shows that most of the radical initiation, propagation and termination steps are very sensitive to photolysis rates. Hence, improvements in cloud placement could greatly improve ozone and precursor performance, though the greatest improvements will likely occur on low ozone days.

To improve the cloud distribution, the TCEQ has followed the guidance of Texas A&M University (TAMU) researcher and state climatologist John Nielsen-Gammon and has u tilized the Grell cumulus parameterization, which reduces the amount of spurious thunderstorm formation in the HGB area.

5.2.1.8 Radical Shortage A number of researchers studying urban photochemistry in the HGB area and other cities have found that available mechanisms for simulating radical production are unable to replicate the observed radical formation and propagation rates (Mao et al., 2007, 20 09; Chen et al., 2009). The process analysis section of Appendix I: Corroborative Analysis for the HGB Attainment Demonstration SIP discusses this issue in detail and compares TCEQ process analyses to the Mao et al. and Chen et al. work. The TCEQ modeling

is consistent with the Mao et al. and Chen et al. fi ndings that there is apparently something missing in the current mechanisms. The atmospheric chemistry comm unity as a whole has not yet resolved the problem or problems with the current mechanisms. Several hypotheses for the missing radical formation mechanism exist, including daytime nitrous acid (HONO) production from nitric acid-aerosol interactions and photolysis (Ziemba et al., 2009); isoprene produc tion of hydroxyl radical (OH) (Lelieveld et al., 2008; North and Ghosh, 2009); forma tion and decomposition of electronically excited nitrogen dioxide (NO 2 * ) (Li et al., 2008); nitryl chloride (ClNO 2 ) chemistry (Osthoff et al., 2008; Simon et al., 2008); improved aromatic chemistry (Faraji et al., 2008; Hu et al., 2007); and molecular chlorine reactions (Chang et al., 2002; Tanaka et al., 2003; Chang and Allen, 2006; Sarwar and Bhave, 2007). Given the manifold hypotheses and the current lack of a definitive explanation, the TCEQ has not incorporated

modified chemical mechanisms into its base case mode ling at this time. However, the TCEQ continues to support investigations for improving chemical mech anisms, and is prepared to adopt an improved mechanism when it becomes sufficiently mature.

5.2.2 Model Performance Evaluations: Implications of the Model Performance of the Current SIP Modeling Model performance evaluation is presented in Chapter 3, Photochemical Modeling and in its associated appendices. Appendix I: Corroborative Analysis for the HGB Attainment Demonstration SIP includes two discussions of model performance in the Chemical Process Analysis and Intensive Model

Performance sections. In addition, Appendix I: Corroborative Analysis for the HGB Attainment

Demonstration SIP includes a discussion of using 2005 baseline modeling to estimate future 2018 design values. Based upon these evaluations, the fo llowing overall conclusions can be reached.

Ozone performance

• The model simulates the location, spatial extent, and relative intensity of ozone relatively well on most of the high-ozone days.

• The model consistently underestimates peak oz one within the highest concentration plumes.

• Simulated ozone depicts rapid morning ozone in creases (30-50 ppb) relatively well, but tends to5-7 miss afternoon peak concentrations.

• Radical and ozone precursor budgets were calcula ted directly from observations by Mao et al. (2009) at the Moody Tower during TexAQS II. They observed that ozone formation in the HGB

area is both VOC- and NO X -sensitive, with VOC-sensitive ozone formation usually occurring in the morning and NO X -sensitive formation occurring in the afternoon. Based upon the TCEQ’s process analysis, the TCEQ modeling appears to be simulating the VOC- and NO X -sensitivity of ozone formation at Moody Tower relatively well, because the relative radical termination rates generally agree with the Mao et al. data.

• Process analysis and modeling sensitivity analyses show that peak eight-hour ozone is primarily

NO X -sensitive in much of the domain, but can be VOC-sensitive downwind of the urban core and
the HGB industrial areas.

• According to TCEQ process analyses, VOC-sens itive conditions occur more often and more strongly in the industrial and urban core plum es. When ozone production is VOC-sensitive, usually more ozone is created than in NO X -sensitive conditions.

• Chen et al. (2009) used the Moody Tower Tex AQS II observations to constrain a steady-state photochemical box model. They used the Ca rbon Bond 05 chemical mechanism and several

other chemical mechanisms to simulate the chemistr y with the box model. They found that all of the chemical mechanisms underestimated peak da ytime radical concentrations. The Carbon Bond 05 mechanism used by the TCEQ in this mode ling exercise is one of the better performing mechanisms, but it still doesn’t make enough radicals. The shortfall in radical production may be

related to the shortfall in oz one production rates observed in th e photochemical grid modeling. Note, however, that the results from Chen et al. are based upon a constrained steady-state box model, which assumes that the chemical system is in a photochemical steady state. It isn’t clear whether this assumption is valid all of the time in the HGB area.

• Decreases in ozone production rates and other r eaction rates correlate with decreases in NO 2 photolysis, implying that most of the ozone formation chemistry is highly sensitive to photolysis, and hence, highly sensitive to cloud-cover errors.

• Background ozone concentrations are important in accurately simulating the modeling for the HGB area. For most of the modeled days, the background ozone is unlikely to bias the modeling results in the HGB area, but during the July -August 2005 episode, excessive ly high background concentrations seem to compromise the model performance.

• In rural areas, the model routinely over- predicts nighttime ozone and under-predicts NO X . The cause of this issue is unknown, but it could involve unreported NO X sources or problems with vertical mixing in rural areas.

• Above the planetary boundary layer, the model sometimes underestimated ozone concentrations, especially in the springtime. Usually the high ozone above the PBL was not being mixed downward, so that this error usually did not ha ve much effect upon the ozone concentrations in
the HGB area.

• Transport and mixing of urban a nd industrial emissions within the HGB area can apparently affect the ozone chemistry substantially, especially when the urban core plume and the industrial plumes mix together. Ozone behavior, including VOC- and NO X -sensitivity, appears to change when these plumes mix. The implication is that the VOC- and NO X -sensitivity of ozone formation in the HGB area depend somewhat on the wind direction.

• Since ozone was sometimes overestimated during the evening hours, the model did not display the amount of dynamic range present in the observations.

Ozone precursor performance

• In general, the modeling simulate d ozone precursors relatively well, albeit with a large degree of scatter, and the peak concentrations for some species were underestimated.

• NO 2 was usually simulated in an unbiased manner, but nitric oxide (NO) was often underestimated for the peak con centrations, which were usually observed in the pre-dawn hours, i.e., during morning rush hour.

• The highly reactive Carbon Bond 05 species ETH a nd OLE, which represent ethylene, propylene, and other alkenes, were well simulated much of the time, but the mode l tended to underestimate5-8 the peak concentrations. Concentrations of these two species were routinely overestimated at the Wallisville Road (CAMS 617) monitoring site.

• The performance of isoprene, represented by the Carbon Bond 05 species ISOP, was mixed, with some areas showing no bias, others showing high bias, and others showing low bias.

• Formaldehyde data were available during the Te xAQS II study at three sites. For the Moody Tower site, the concentrations were usually well simulated, but the peak concentrations were underestimated. For the Lynchburg Ferry (CAMS 1015) and HRM-3 Haden Road (CAMS 603) sites, the performance was mediocre. The HR M-3 Haden Road (CAMS 603) observations were consistent with secondary formal dehyde formation as the main source of formaldehyde, but the diurnal patterns of the modeled concentrations we re more consistent with a primary source: concentrations peaked in the pre-dawn hours, like NO. The aircraft data generally show that the model underestimated formaldehyde peaks, though the location, extent, and relative magnitude were well simulated, much like the ozone data.

Meteorological performance evaluation

• The meteorological modeling was able to successf ully replicate the major features of ozone episodes in the HGB area much of the time, incl uding the typical veering pattern of local winds, stagnation and flow reversal, and the coastal o scillations associated with the Galveston Bay

breeze and Gulf breeze.

• Trajectory analyses and vertical wind profiles in the HGB area show that much of the time on high ozone days, the model transported ozone and precursors to approximately the correct areas at approximately the correct times.

• The model occasionally did not generate enough cl oud cover, resulting in high ozone on days

when low ozone was observed. While the add ition of the Grell cumulus parameterization and improved land surface characteristics data appeared to reduce the common problem of spurious thunderstorms, the problem has not been completely eliminated.

• Episode days with strong stagnation were more difficult to model precisely than days for which the winds did not stagnate. The model sometimes simulated nighttime winds that were too brisk, resulting in more dilution of emissions than was actually observed.

• Ozonesonde and radar profiler data indicate th at for most episode days, the PBL over land appeared to be modeled with good accuracy. Ov er water, however, planetary boundary layer depth was consistently modeled less accurately.

Model response to emission changes

• The base case modeling has been challenged with different emissions inventories in order to evaluate its dynamic response to emission changes (Gilliland et al., 2009).

• Adding more VOC to the flare emissions incr eases peak ozone concentrations, though the emission changes do not completely correct the ozone underestima tions. Addition of formaldehyde emissions to HRVOC flares in creases peak ozone concentrations further.

• Substitution of flare emissions for the standard emission reconciliation tends to improve the model performance by increasing ozone production cl ose to the industrial emission sources and by increasing the peak ozone concentrations, w ithout adversely affecting ozone performance at other times and places.

• Modeled ozone appears to decrease slightly in response to NO X emission decreases typical of the changes that occur on weekends. The observed week end effect is a slightly stronger response to

NO X emission decreases, implying that the model may be slightly less NO X -sensitive than it

should be.

• Modeled ozone increases substantia lly in response to VOC and NO X emission increases

commensurate with the difference between 2006 em issions and 2000 emissions in the HGB area. When relative response factors are calculated using 2000 as the baseline year and 2006 as the future year, the modeled response to emission reductions is less vigorous than the observed response. This finding implies that the current modeling appears to underestimate the response to emission controls. If the atmosphere responds to the emission reductions from 2006 to 2018 in a manner similar to its response to the emission reductions between 2000 and 2006, the actual decrease in ozone design value will be greater than the model predicts.5-9 • Some of the strongest model responses to emi ssion changes occur outside the boundaries of the current ozone monitoring network, and sometimes outside the current nonattainment area. This finding suggests that the proposed controls ma y have a greater impact on ozone than the responses registered at the different monitoring sites would indicate.

5.2.3 Model Response to Proposed Contro ls: Additional Ways to Measure Progress

Table 5-1: Changes in the Area and Population Affected by an Eight-Hour Ozone Design Value Greater than or Equal to 85 ppb in Response to Growth and Controls shows how the area affected by high ozone is expected to shrink dramatically in response to the emission changes projected to occur between 2006 and 2018. Even though peak ozone drops by only 8 percent, the area with an estimated ozone design value greater than the 85 ppb standard shrinks by 96 percent. The population living in those areas and how the changes might reduce the number of people that encounter high ozone were considered. The estimated number of people residing in the high ozone areas decreases by 92 percent. Note that the population data is from the 2000 Census and has not been grown to reflect changes in population in those areas in 2006 or 2018. Also note that the numbers reflect areas where people reside, i.e., their home addresses, not necessarily where they might be during the hours of highest ozone during the ozone season. However, the dramatic decrease in the area with hi gh ozone suggests that ozone decreases arising from the proposed control strategies are likely to benefit many residents of the HGB area.

Table 5-1: Changes in the Area and Population Affected by an Eight-Hour Ozone Design Value Greater than or Equal to 85 ppb in Response to Growth and Controls

Run name Peak Ozone,

ppb Area with design

value > 85 ppb, km 2 2000 population

in area

with design
value > 85 Area × Concentration

(km 2 × ppb) Population × ppb Ozone design value > 85 ppb baseline 2006.reg2 95 7,236 2,680,249 19,864 11,024,868 future year 2018.cs05 87 296 219,285 291 197,713 Percentage decrease

from 2006 to 2018 8% 96% 92% 99% 98%

5.2.4 Conclusion The photochemical grid model performed by the TC EQ for this SIP revision has been rigorously evaluated against observational data. While there are a number of shortcomings that this modeling has in common with other modeling exercises in the HGB area as discussed in Sections 5.2.1, Solving Modeling Problems, and 5.2.2, , Model Performance Evaluations : Implications of the Model Performance of the Current SIP Modeling, modeling for many of the simu lated ozone days appears to behave in a manner

consistent with most of the atmo spheric phenomena of interest. Evaluation of the modeling response to emission changes appears to show that the modeled oz one is slightly less responsive to emission changes than the observed ozone. Thus, modeling of 2018 emi ssions with the proposed control package in place may overpredict the future ozone concentrations.

5.3 AIR QUALITY TRENDS IN THE HGB AREA This section describes analyses of air quality observationa l data in the HGB area. Trends in ozone and its precursors demonstrate not only the substantial pr ogress the HGB area has made in improving air quality but also the magnitude of the future challenge in attaining the ozone NAAQS. Trends are also useful to

show how ozone is re lated to its precursors. Decreases in NO X and VOC demonstrate the effectiveness of policies to reduce emissions; however, due to its de pendence on meteorological variables, ozone may not always exhibit trends identical to its precursors. Separating variations in meteorological factors from trends in ozone and its precursor s can highlight whether ozone reductions are due to decreases in5-10 precursor emissions or are due to year-to-year vari ability in local meteorology (Sullivan, 2009; Camalier, et al., 2007).

5.3.1 Ozone Trends This section examines the frequency at which the NAAQS for ozone are exceeded, with the understanding that the 1997 eight-hour standard of 0.08 ppm is the subject of interest for this SIP revision and that the one-hour standard is no longer in effect , but still a useful benchmar k for understanding ozone behavior in the HGB area. While the NAAQS is expressed in units of ppm, this section will use the familiar convention of expressing concentrations in ppb.

The trend in design values for the HGB ar ea is seen clearly in Figure 5-1: Ozone Design Values for the

HGB Area . While the HGB area continues to exceed bot h the one-hour and eight-hour ozone standards, one-hour ozone design values have generally decre ased over the past 17 years, and eight-hour ozone design values have decreased over at least the past nine years. The eight-hour ozone design value in 2008 was 91 ppb, a 24 percent decrease from the 1991 design value of 119 ppb. The 2008 value is approaching the 1997 eight-hour ozone NAAQS of 85 ppb. A regressi on analysis of design value on year estimates that eight-hour ozone design values decreased at the rate of 1.2 ppb per year, which is statistically significant at the 5 percent level ( α = 0.05). If this trend were to conti nue at that rate, attainment of the 1997 eight-hour standard could be reached in five years, though if the pace of recent years were maintained, it could occur even sooner.

Ozone Design Values for the HGB Area

104 110 114 116 117 116 118 112 110 107 102 101 103 103 96 210
200 202

189 188 199 196 203 199

185
175 175 170 169

153 153

91 116 119 147 220

0 50 100 150 200 250

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 Design Value (ppb)

1-Hour NAAQS: 125 ppb

8-Hour NAAQS: 85 ppb 1-Hour DV

8-Hour DV

Figure 5-1: Ozone Design Values for the HGB Area

The one-hour ozone design value in 2008 was 147 ppb, a 33 percent decrease from the 1991 design value of 220 ppb. Regression of one-hour design values on y ear shows they decreased at the rate of 3.6 ppb per year, which is faster than the decrease for eight-hour ozone design values; the slope is also statistically significant at the 5 percent level.Table 5-2: Eight-Hour Ozone Design Values (in ppb)for Each Regulatory Monitor in the HGB AreaMonitor/CAMS # 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008Houston Bayland Park C531111101001021011031039691Houston Westhollow C410951019510210210495878789969289Park Place C41689Hous.DeerPrk2 C35/235/1001/AFH139FP239108112108103102101100969387Manvel Croix Park C84919797969185Northwest Harris Co. C26/A110/X154981011001101131101061061091081051011009493919185Houston Aldine C8/AF108/F1501191161041021031141161161081111081071009592888483Houston Monroe C4061051029693971021091121131069390909597999181Houston Croquet C40911711210396104104117115118110104102999998948780Conroe Relocated C788586858480Channelview C15/C115879089858380Houston East C110410388861081061021031011009587837880Seabrook Friendship Park C45859492908679Houston Texas Avenue C411888988847876Lang C408105103939598991009696969183787979807776Lake Jackson C101679797676Houston North Wayside C4051141029491919196991041059889868582787675Lynchburg Ferry C101596898274Houston Regional Office C8195948888848174Clinton C403/C113/C3041151091001001061061071001031019793969695857973Galveston Airport C34/C109/C1549011210898898991878371Clute C11969391969292849593918687Texas City C10938290891141021059110098918380Conroe C6591Houston Crawford C40710598898995919796100100Houston Manchester C22103104104103106102103Houston Deer Park C18107968589107116Note: Missing values indicate a monitor was not operating during thatyear or did not produce a valid year of data. Three years of valid data are required to calculate an eight-hour ozone design value.5-115-12 The design value in a metropolitan area is the highest design value of all of the area’s monitors’ individual design values. Because ozone varies spatia lly, it is also prudent to investigate trends at
all monitors in an area. Table 5-2: Eight-Hour Ozone Design Values (in ppb) for Each Regulatory Monitor in the HGB Area and Table 5-3: One-Hour Ozone Design Values (in ppb) for Each Regulatory M onitor in the HGB Area contain the eight-hour and one-hour ozone design values at all regulatory monitors in the HGB ar ea from 1991 to 2008. More monitors than these operate in the HGB area, but because the data at those monitors do not meet the EPA’s quality control standards, the design values at those add itional monitors are not displayed here. These non-regulatory monitors are discussed in Section 5.2.2: Model Performance Evaluations: Implications of the Model Perfor mance of the Current SIP Modeling

.5-13Table 5-3: One-Hour Ozone Design Values (in ppb)for Each RegulatoryMonitor in the HGB AreaMonitor/CAMS # 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008Houston Bayland Park C53189185173154163148148143142139Houston Westhollow C410164155164155165150150141141128126131127126Park Place C416136132Hous.DeerPrk2 C35/235/1001/AFH139FP239147164203185182168161157153150150147Manvel Croix Park C84143132142134138128128Northwest Harris Co. C26/A110/X154160160166173172172165164163161157154156148131127127126Houston Aldine C8/AF108/X150220190197197189173189187187180166166143136139125122122Houston Monroe C406170170155147154161174196196170143151141141131133131117Houston Croquet C409200200178152167167168168167167160157150141136131126117Conroe Relocated C78119137128128128124116Channelview C15/C115154141140135134128120Houston East C1210200200202177182182198180180171171165154137119119Seabrook Friendship Park C45132135135153153153119Houston Texas Avenue C411146172157157127110110Lang C408200183158159159159158155155175175149128128127126108108Lake Jackson C101611911310599101Houston North Wayside C405210190173173155143155158189190168153131138138118100102Lynchburg Ferry C1015157157152149117Houston Regional Office C81185178175170169135131119Clinton C403/C113/C304210210176158173173173161183199176157175158158124121111Galveston Airport C34/C109/C15417017017616816413312312912911710397Galveston 99th St. C1034115115Clute C11150150132129144144148134154161154136133136Texas City C10150150163163184182182146175172139121116116124Conroe C65145145140Houston Crawford C407220190165165165166172172164173173194Houston Manchester C22190190180160172170175173176Houston Deer Park C18160160150157188188199163San Jacinto Monument C166/C24514312412494Note: Missing values indicate a monitor was not operating during thatyear or did not produce a valid year of data. Only one year of valid data is required to calculate a one-hour ozone design value; therefore, some monitorsthat have a one-hour ozone design value may nothave an eight-hour ozone design value.5-14 Figure 5-2: Eight-Hour Ozone Design Value Statistics for All Monitors in the HGB Area and Figure 5-3: One-Hour Ozone Design Value Statistic s for All Monitors in the HGB Area display three summary statistics for the eight-hour a nd one-hour design values, respectively: the maximum, median, and minimum design values computed across all monitors in the HGB area. These figures facilitate assessment of the range of design values observed within a year, as wellas how these distributions change over time. From these figures, it appears that neither eighthour nor one-hour design values exhibited a noti ceable trend until about 1999, after which both began falling steadily. Before 2002, no monitors in the HGB area me t either standard; since then, the area has seen a steady increase in the number of monitors attaining both standards. By 2008,

over half of the monitors in the area had atta ined both standards, as median ozone design values fell below the NAAQS that year.

Eight-Hour Ozone Design Value Statistics in the HGB Area

0 20 40 60 80 100 120 140199119921993199419951996199719981999200020012002200320042005200620072008 Design Value (ppb)

8-Hour NAAQS: 85 ppb MAX

Median

MIN

Figure 5-2: Eight-Hour Ozone Design Value Statistics for All Monitors in the HGB Area5-15 One-Hour Ozone Design Value Statistics in the HGB Area

0 50 100 150 200 250199119921993199419951996199719981999200020012002200320042005200620072008 Design Value (ppb)

1-Hour NAAQS: 125 ppb MAX

Median

MIN

Figure 5-3: One-Hour Ozone Design Value Statistics for All Monitors in the HGB Area

Ozone trends can also be investigated by look ing at the number of days an exceedance of the ozone NAAQS was recorded, termed an exceedan ce day. An exceedance day for the 1997 eighthour ozone NAAQS is any day that any monitor in the area measures an eight-hour average ozone concentration greater than or equal to 85 ppb over any eight-hour period. An exceedance day for the one-hour ozone NAAQS is any day th at any monitor in the area measures a one-hour average ozone concentration greater than or e qual to 125 ppb for at least one hour. Previous research (Savanich, unpublished, 2006) by the TCEQ has shown that, until 2006, the number of exceedance days was positively correlated with the nu mber of monitors in a particular area. As the number of monitors increases, so does the numb er of exceedance days recorded, at least until

the area has been saturated with monitors or un til ozone concentrations truly decrease. Because of this correlation, when examining exceedance-day trends, the number of monitors must always be considered. Thus, it is especially noteworthy that Figure 5-4: Number of Monitors and Ozone Exceedance Days in the HGB Area shows that, despite an increase in the number of monitors, the number of exceedance days for both one-hour and 1997 eight-hour ozone NAAQS has decreased, a decrease that is especially pronounced over the past three years. Since 1999, the number of 1997 eight-hour and one-hour ozone exceedance da ys occurring in the HGB area has fallen 83 percent and 96 percent, respectively. In just the last three years, the number of 1997 eight-hour and one-hour ozone exceedance days has fallen 76 percent and 92 percent, respectively.5-16 Number of Monitors and Ozone Exceedance Days

in the HGB Area

39

34 52 54

48 54

45

36 41 44 45

32

20

11 28 28 30 26 35 49

34

28

23 27 30 26

17

6 39 73

64

32 45 56

2 37

0 20 40 60 80 100199119921993199419951996199719981999200020012002200320042005200620072008 Days

0 5 10 15 20 25 Monitors

One-Hour Exceedances Eight-Hour Exceedances number of monitors

Figure 5-4: Number of Monitors and Oz one Exceedance Days in the HGB Area

Results for individual monitors, displayed in Figure 5-5: Number of 1997 Eight-Hour Ozone Exceedance Days by Monitor and Figure 5-6 : Number of One-Hour Ozone Exceedance Days by

Monitor support the conclusion that the number of ex ceedance days at individual monitors also appears to be decreasing. Figure 5-5: Number of 1997 Eight-Hour Ozone Exceedance Days by

Monitor highlights two monitors, Houston Aldine (CAMS 8) (red line) and Houston Bayland Park (CAMS 53) (blue line), that recorded the most 1997 eight-hour ozone NAAQS exceedances in the past. Since recent peaks in 1999 (at Houston Bayland Park (CAMS 53)) and in 2000 (Houston Aldine (CAMS 8)), neither monitor, in any year, has come within 60 percent of these peaks; in 2008 both monitors experienced at leas t an 85 percent reduction from the recent peaks. While results for other monitors are less impre ssive, overall, the trend in ozone exceedance days at monitors throughout the HGB area is clearly dow nward. Due to the large number of monitors in the HGB area, data from Figure 5-5: Number of 1997 Eight-Hour Ozone Exceedance Days by

Monitor and Figure 5-6: Number of One-Hour Ozone Exceedance Days by Monitor are presented in Table 5-4: Number of Days with a 1997 Eight-Hour Ozone Exceedance and Table 5-

5: Number of Days with a One-Hour Ozone Exceedance for detailed inspection.5-17 Eight-Hour Ozone Exceedance Days in the HGB Area

0 5 10 15 20 25 30 35 40

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 Days

Manvel Croix Park Lake Jackson Galveston Airport Galveston 99th St.
Houston Aldine Channelview NW Harris Co. North Wayside Lang Croquet Bayland Park Monroe Westhollow Hou. Reg. Office
Texas Avenue Park Place Lynchburg Ferry Houston East Clinton Deer Park 2 Seabrook Conroe Relocated

Figure 5-5: Number of 1997 Eight-Hour Ozone Exceedance Days by Monitor

One-Hour Ozone Exceedance Days in the HGB Area

0 5 10 15 20 25

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 Days

Manvel Croix Park Lake Jackson Galveston Airport Galveston 99th St. Houston Aldine Channelview NW Harris Co. North Wayside Lang Croquet Bayland Park Monroe Westhollow Hou. Reg. Office Texas Avenue Park Place Lynchburg Ferry Houston East Clinton Deer Park 2 Seabrook Conroe Relocated

Figure 5-6: Number of One-Hour Ozone Exceedance Days by Monitor

The progress achieved in recent years in reducing eight-hour and one-hour ozone concentrations

in the HGB area is evident in Table 5-4: Number of Days with a 1997 Eight-Hour Ozone

Exceedance and Table 5-5: Number of Days with a One-Hour Ozone Exceedance . The number of

times the monitors in the HGB area re gistered daily peak eight-hour ozone ≥ 85 ppb fell from a5-18 high of 340 occurrences in 1995, to 39 occurrences in 2007, to 19 occurrences in 2008. Prior to 2007, that number was never below 90. The number of monitors recording at least one exceedance of the 1997 eight-hour ozone standard has fallen by half, from a maximum of 23 monitors in 2003 to only 12 in 2008.

A similar pattern is apparent with the number of exceedances of the one-hour ozone NAAQS presented in Table 5-5: Number of Days with a One-Hour Ozone Exceedance . The table shows that the total number of one-hour ozone NAAQS exceedance occurrences fell from a high of 165 in 1995 to just three in 2008. Prior to 2005, the number of one-hour exceedances was never
below 50. The three exceedances in 2008 occurred at only two monitors. As recently as 2006, a

total of 15 monitors recorded at least one exceed ance. This significant progress has occurred in a fairly short amount of time in an area well known for its air quality challenges.5-19Table 5-4: Number of Days with a 1997 Eight-Hour Ozone ExceedanceMonitor 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008Houston Bayland Park C5317311917111616131233Houston Westhollow C410436816111711833981131Park Place C4161042Hou.DeerPrk2 C35/235/1001/AFHP139FP2391892620108181011742Manvel Croix Park C84581417131541Northwest Harris Co. C26/A110/X1543141221341312232571191199850Houston Aldine C8/AF108/X150151711193816252322291571195343Houston Monroe C40613107722528122112378613720Houston Croquet C409239983682819311591010149601Conroe Relocated C7813722701Channelview C15/C115151055510Houston East C191020013161213151061550900Seabrook Friendship Park C4524888441Houston Texas Avenue C41152961300Lang C4085108101885115823131400Lake Jackson C1016320001Houston North Wayside C4059855268912241452930210Lynchburg Ferry C101514104600Houston Regional Office C8111115935800Clinton C403/C113/C30416117621714112211671064102Galveston Airport C34/C109/C154181323534128220Clute C11810651534592363Conroe C654176Houston Crawford C407567415316101180Houston Manchester C22191081027518Houston Deer Park C18843182712Texas City C10619725110101161330San Jacinto Monument C166/C245051Galveston 99th St. C10344 1Number of Monitors in Operation131313141414151516172321232120212221Note: Monitors with exceedance days do not necessarily have a complete year ofozone data; therefore, there may be years wherea monitor has ozone exceedance days but no ozone design value.5-20Table 5-5: Number of Days with a One-Hour Ozone ExceedanceMonitor 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008Houston Bayland Park C5312188103646500Houston Westhollow C41032038512562221410Park Place C416702Hou.DeerPrk2 C35/C235/1001/AFH139/FP239137141365753401Manvel Croix Park C8412152310Northwest Harris Co. C26/A110/C15419101497499564212220Houston Aldine C8/AF108/X150987121115121281681622000Houston Monroe C406863311215810555325300Houston Croquet C40916554213141214645444100Conroe Relocated C7801211200Channelview C15/C11515622210Houston East C16620012138101174730200Seabrook Friendship Park C4534533210Houston Texas Avenue C41150830110Lang C408566694684632240000Lake Jackson C1016100000Houston North Wayside C4055634455871111520000Lynchburg Ferry C1015976100Houston Regional Office C81673513200Clinton C403/C113/C304138741568713873621000Galveston Airport C34/C109/C15457740031000Galveston 99th St. C103400Clute C113320613142021Texas City C10417214033730010Conroe C65152Houston Crawford C4075453941112580Houston Manchester C10291177718410Houston Deer Park C186216184San Jacinto Monument C166/C245020Number of Monitors in Operation1313131414141515161723212321202122215-21 The ozone season spans the entire year in the HGB area; the period of elevated ozone concentrations, however, varies from year to year. Figure 5-7: 1997 Eight-Hour Ozone Exceedance Days in the HGB Area shows the frequency of, and variation in, the number of 1997 eight-hour ozone NAAQS exceedance days in the HGB area by month and year. While the duration and intensity of the ozone season does vary from year to year, in the past few years the HGB area has experienced fewer ozone exceedance days over fewer months. The darker areas in the figure show that peak ozone season in th e HGB area typically occurs from August to September, with a smaller, secondary pe ak occurring earlier, roughly in June.199119921993199419951996199719981999200020012002200320042005200620072008 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Eight-Hour Ozone Exceedance Days in the HGB Area

1 - 3 17 - 19 15 - 17 13 - 15

11 - 13 9 - 11

7 - 9

5 - 7 3 - 5

Figure 5-7: 1997 Eight-Hour Ozone Exceedance Days in the HGB Area

In summary, the number and intensity of ozone exceedances in the HGB area has been dropping, especially since 2000, with 2007 and 2008 demonstrating the largest of these decreases.

5.3.2 Ozone Trends at Regulato ry and Non-Regulatory Monitors Twenty-three monitors in the HGB area, listed in Table 5-6: Eight-Hour Ozone Design Values at Regulatory and Non-Regulatory Monitors and Table 5-7: One-Hour Ozone Design Values at Regulatory and Non-Regulatory Monitors report ozone concentrations following EPA certification protocols and are used for attainme nt determinations for regulatory purposes. However, since 2003, over 20 additional monitors have become operational in the HGB area that measure ozone concentrations following protocols th at have not been certified to EPA standards. Usually, this means fewer calibrations and/or zero and span checks. These non-regulatory monitors are located throughout the HGB area. The locations were chosen with the aim of ensuring that all episodes of elevated ozone and precursors are observed. The additional monitoring sites also help to describe the spatial extent and distribution of high ozone more fully than the regulatory monitors alone. While th e non-regulatory monitors are not acceptable for making regulatory determinations, they help describe the spatial patterns of ozone more completely and thus provide a broader perspectiv e on trends in ozone concentrations across the

HGB area.5-22 Table 5-6: Eight-Hour Ozone Design Values at Regulatory and Non-Regulatory Monitors

AIRS Site Name 2003 2004 2005 2006 2007 2008 ppb ppb ppb ppb ppb ppb Regulatory Monitors

482010055 Houston Bayland Park C53 102 101 103 103 96 91

482010066 Houston Westhollow C410 87 87 89 96 92 89

482010416 Park Place C416 89

482011039 Houston Deer Park 2 C35/139 102 101 100 96 93 87

480391004 Manvel Croix Park C84 91 97 97 96 91 85

482010029 Northwest Harris Co. C26/A110/C154 100 94 93 91 91 85

482010024 Houston Aldine C8/AF108/X150 100 95 92 88 84 83

482010062 Houston Monroe C406 90 95 97 99 91 81

482010051 Houston Croquet C409 99 99 98 94 87 80
483390078 Conroe Relocated C78 85 86 85 84 80

482010026 Channelview C15/C115 87 90 89 85 83 80

482011034 Houston East C1 100 95 87 83 78 80

482011050 Seabrook Friendship Park C45 85 94 92 90 86 79

482010075 Houston Texas Avenue C411 88 89 88 84 78 76

482010047 Lang C408 78 79 79 80 77 76

480391016 Lake Jackson C1016 79 79 76 76

482010046 Houston North Wayside C405 86 85 82 78 76 75

482011015 Lynchburg Ferry C1015 96 89 82 74

482010070 Houston Regional Office C81 94 88 88 84 81 74

482011035 Clinton C403/C113/C304 96 96 95 85 79 73

481670014 Galveston Airport C34/C109/C154 89 91 87 83 71

480391003 Clute C11 87

481671002 Texas City C10 80

Non-Regulatory Monitors

482010554 West Houston C554 102 99 94

482010558 Tom Bass C558 104 100 93
482010559 Katy Park C559 98 96 92

482010562 Bunker Hill Villa ge C652 81 96 91

482010617 Wallisville Road C617 96 93 93 90

482010561 Meyer Park C561 90 89 84

482010557 Mercer Arboretum C557 88 88 84

482010560 Atascocita C560 88 86 83

482010556 La Porte Sylvan Beach C556 90 87 82

482010552 Baytown Wetlands Center C552 87 89 86 81

480390619 Mustang Bayou C619 93 89 84 81

482010572 Clear Lake High School C572 83 88 84 81

482010803 HRM-3 Haden Road C603 92 88 84 80

482010553 Crosby Library C553 87 86 84 80

481670056 Texas City 34th St, C620 89 90 84 79

482010570 Clear Brook High School C570 89 92 84 78

480390618 Danciger C618 80 83 80 78

482010555 Kingwood Library C555 82 81 77
482010551 Sheldon C551 92 85 80 76
481670571 Clear Creek High School C571 83 84

Source: Leading Environmental Anal ysis and Display System (LEADS). Monitors are sorted in descending order of 2008 design values, then 2007, 2006, etc. The annual maximum of each series is note d in boldface type. Because of the way design values are computed, some monitors in some years may have one-hour but not eight-hour design values. Table 5-7: One-Hour Ozone Design Values at Regulatory and Non-Regulatory Monitors5-23 AIRS Site Name 2003 2004 2005 2006 2007 2008 ppb ppb ppb ppb ppb ppb Regulatory Monitors

482010055 Houston Bayland Park C53 163 148 148 143 142 139

482010066 Houston Westhollow C410 141 128 126 131 127 126

482010416 Park Place C416 136 136 136
482011039 Houston Deer Park 2 C35/C139 161 157 153 150 150 147

480391004 Manvel Croix Park C84 132 142 134 138 128 128

482010029 Northwest Harris Co. C26/A110/C154 156 148 131 127 127 126

482010024 Houston Aldine C8/AF108/X150 143 136 139 125 122 122

482010062 Houston Monroe C406 141 141 131 133 131 117

482010051 Houston Croquet C409 150 141 136 131 126 117

483390078 Conroe Relocated C78 137 128 128 128 124 116

482010026 Channelview C15/C115 141 140 135 134 128 120

482011034 Houston East C1 171 165 154 137 119 119

482011050 Seabrook Friendship Park C45 135 135 153 153 153 119

482010075 Houston Texas Avenue C411 172 157 157 127 110 110

482010047 Lang C408 128 128 127 126 108 108

480391016 Lake Jackson C1016 119 113 105 99 101

482010046 Houston North Wayside C405 131 138 138 118 100 102

482011015 Lynchburg Ferry C1015 157 157 152 149 117

482010070 Houston Regional Office C81 175 170 169 135 131 119

482011035 Clinton C403/C113/C304 175 158 158 124 121 111

481670014 Galveston Airport C34/C109/C154 123 129 129 117 104 97

481671034 Galveston 99th St. C1034 115 115

480391003 Clute C11 133 136

481671002 Texas City C10 116 116 124

Non-Regulatory Monitors

482010554 West Houston C554 141 141 146 145 131

482010558 Tom Bass C 558 145 145 146 146 138

482010559 Katy Park C559 127 143 143 135 129

482010562 Bunker Hill Village C562 135 137 135 132

482010617 Wallisville Road C617 147 145 138 139 134

482010561 Meyer Park C561 139 133 127 111

482010557 Mercer Arboretum C557 108 118 121 121 121

482010560 Atascosita C 560 137 137 125 120

482010556 La Porte Sylvan Beach C556 148 149 149 133

482010552 Baytown Wetlands Ce nter C552 138 138 133 129 129

480390619 Mustang Bayou C619 134 130 127 112 107

482010572 Clear Lake High School C572 145 141 140 119 114

482010803 HRM-3 Haden Road C603 161 161 144 135 127 122

482010553 Crosby Library C553 141 147 141 126 123

481670056 Texas City 34th St C620 143 139 136 119 114

482010570 Clear Brook High School C570 140 140 135 117 109

480390618 Danciger C618 121 120 111 108 108

482010555 Kingwood Library C555 130 123 122 108

482010551 Sheldon C551 153 153 150 130 125 123

481670571 Clear Creek High School C571 138 138 138 119 99

480710013 Smith Point Hawkins Camp C96 143 143 133

482010808 HRM-8 LaPorte C608 149

482010804 HRM-4 Sheldon Rd. C604 128
480710900 HRM-10 Mont Belvieu C610 1195-24 482010807 HRM-7 W Baytown C607 113

Source: LEADS (Leading Environmenta l Analysis and Display System). The annual maximum of each series is noted in boldface type. Becau se of the way design values are computed, some monitors in some years may have one-hour but not eight-hour design values

Figure 5-8: Distributions of Eight-Hour Ozone Design Values at Regulatory and Non-Regulatory
Monitors in the HGB Area compares eight-hour ozone design values at regulatory and nonregulatory monitors in the HGB area from 2003 to 2008. This period was chosen because many non-regulatory monitors only became operational, or had complete data, in 2003 and later years. The distributions of eight-hour ozone design values dropped for both types of monitors over the six-year period, though the interquartile range, a measure of spread between high and low values, did not narrow noticeably for either. Annual medi an fourth high eight-hour ozone design values fell from 90 ppb in 2003 to 80 ppb in 2008 at regulatory monitors, a drop of 11.1 percent. The median at non-regulatory monitors fell from 89 ppb to 81 ppb over the period, a 9.0 percent drop.

While medians and other moments from the distri butions all dropped over the period, the annual maximum eight-hour ozone design value is most re levant, as this value is the current standard used for regulatory attainment determinati ons. The annual maximum eight-hour ozone design value measured at regulatory monitors fell from 102 ppb in 2003 to 91 ppb in 2008, a drop of 10.4 percent. The annual maximum at non-regul atory monitors fell from 96 ppb in 2005, when three-year design values were first computable, to 94 ppb in 2008, a drop of 2.1 percent. Note, however, that maximum eight-hour design values at non-regulatory monitors in 2006 and 2007 were higher than in 2008, 104 ppb and 100 ppb respectively, presumably because those years are strongly influenced by the fourth high value observed at Wallisville Road (CAMS 617) in 2006 (111 ppb). Even though this 2006 fourth high va lue continued to influence the 2008 design value, when averaged with the 2008 fourth high value of 85 ppb, the three-year average dropped to 94 ppb, a 6 percent decline in a single year.

81 86 89 89

80 84 87 91 94

90 94 100 104

96

91 96 103 103

101 102



### 70 75 80 85 90 95 100 105 110

2003 2004 2005 2006 2007 2008 2003 2004 2005 2006 2007 2008 90th percentile 

### non-regulatory monitors regulatory monitors

maximum

75th percentile

median

25th percentile 10th percentile ppb

no data no data

Figure 5-8: Distributions of Eight-Hour Ozone Design Values at Regulatory and NonRegulatory Monitors in the HGB Area5-25 The ozone design values computed for the non-regulatory monitors are within the range of design values computed for the regulatory monitors. This finding suggests that both sets of monitors

observe the same ozone behavior.

Figure 5-9: Distributions of One-Hour Ozone Design Values at Regulatory and Non-Regulatory
Monitors in the HGB Area compares one-hour ozone design values at regulatory and nonregulatory monitors in the HGB area from 2003 to 2008. This period was chosen because many non-regulatory monitors became operational or had co mplete data in 2003 and later years. The one-hour design value is computed as the fourth highest one-hour value observed among all values during each rolling three calendar-year period . The distributions of one-hour ozone design values dropped for both types of monitors over th e six-year period and the spread between high

and low values narrowed for both. Annual median fourth high one-hour ozone design values fell from 141 ppb in 2003 to 118 ppb in 2008 at regulatory monitors, a drop of 16.3 percent. The median at non-regulatory monitors fell from 149 ppb to 122 ppb over the period, an 18.1 percent drop.

While medians and other moments from the distri butions all dropped over the period, the annual maximum one-hour ozone design value is most relevant, as this design value would be compared to the one-hour ozone NAAQS to determine attainment, were the one-hour standard still in force. The annual maximum one-hour ozone design valu e measured at regulatory monitors fell from175 ppb in 2003 to 147 ppb in 2008, a drop of 16.0 percent. The annual maximum at nonregulatory monitors fell from 161 ppb to 138 ppb over th e period, or 14.3 percent. Note that the eight-hour design value does not change when the data from the non-regulatory monitors are

added to the calculation.

122 126 137 140 141 149

118 127 131 136 141 141 138 149 149 150 161 161

147 153 153 169 170 175



### 100 110 120 130 140 150 160 170 180

2003 2004 2005 2006 2007 2008 2003 2004 2005 2006 2007 2008 90th percentile 

### non-regulatory monitors regulatory monitors

75th percentile

median

25th percentile

10th percentile maximum ppb

# of monitors:

21 22 21 21 22 22 5 15 20 21 21 21Figure 5-9: Distributions of One-Hour Ozone Design Values at Regulatory and NonRegulatory Monitors in the HGB Area5-26 Figure 5-10: 1997 Eight-Hour Ozone Exceedance Days at Regulatory and Non-Regulatory Monitors, 2003 through 2008 presents the number of days per year from 2003 through 2008 that the 1997 eight-hour ozone NAAQS was exceeded in the HGB area at regulatory monitors and at all monitors, both regulatory and non-regulator y. Since 2005, the combined network has
recorded a total of 19 additional exceedances of the 1997 eight-hour ozone standard that would not have been captured by the regulatory network, i.e., about four to five per year. This result confirms earlier findings that suggest as the m onitoring network has expa nded, fewer episodes of elevated ozone concentrations are likely to elude detection.



### 54

48

37

26

12 43 50

41

31

16 51

44

0 10 20 30 40 50 60

2003 2004 2005 2006 2007 2008

Number of regulatory monitors operating:

21 22 21 21 22 22

Number of non-regulatory monitors operating:

5 15 20 21 21 21 Figure 5-10: 1997 Eight-Hour Ozone Exceedance Days at Regulatory and Non-Regulatory Monitors, 2003 through 2008

Figure 5-11: One-Hour Ozone Exceedance Days at Re gulatory and Non-Regulatory Monitors, 2003 through 2008 presents the number of days per year from 2003 through 2008 that the onehour ozone NAAQS was exceeded in the HGB area at regulatory monitors and at all monitors, both regulatory and non-regulatory. Both series initially increased, then fell at similar rates throughout the period, suggesting that the tw o sets of monitors measure broadly similar phenomena. During the first half of the period, non-regulatory monitors measured from five to nine additional exceedance days that were not de tected by regulatory monitors. However, in the second half of the period, that gap dropped to onl y two to three additional days, indicating that non-regulatory monitors are detecting fewer a nd fewer events not detected by regulatory monitors. This result confirms earlier findings that suggest that, as the monitoring network has expanded, fewer episodes of elevated ozone c oncentrations are likely to elude detection.5-27 

### 37

31 32

28

18 34

9

3 33

20

6 10

0 10 20 30 40

2003 2004 2005 2006 2007 2008 exceedance days at regulatory and unique non-regulatory

monitors

exceedance days at regulatory monitors

Number of regulatory monitors operating:

21 22 21 21 22 22

Number of non-regulatory monitors operating:

5 15 20 21 21 21 Figure 5-11: One-Hour Ozone Exceedance Days at Regulatory and Non-Regulatory Monitors, 2003 through 2008

Table 5-8: Exceedance Days at Regulatory and Non-Regulatory Monitors, 2003 through

2008

One-Hour Ozone Exceedance days Number of monitors

regulatory non-regulatory regulatory non-regulatory

Year monitors monitors tota l monitors monitors total

# # # # # #

2003 31 2 33 21 5 35

2004 32 5 37 22 15 37

2005 28 6 34 21 20 41

2006 18 2 20 21 21 42

2007 9 1 10 22 21 43

2008 3 3 6 22 21 43 Source: Leading Environmental Analysis and Display System (LEADS).5-28 Table 5-9: Monitors Recording the Annua l Maximum One-Hour Ozone Design Value Regulatory monitors Non-regulatory monitors

year site name value site name value ppb ppb 2003 Houston Bayland Park C53 163 HRM-3 Haden Road C603 161

2004 Houston Deer Park 2 C35/13 9 157 HRM-3 Haden Road C603 161
2005 Houston Deer Park 2 C35/139 153 Sheldon C551 150
2006 Houston Deer Park 2 C35/139 150 La Porte Sylvan Beach C556 149
2007 Houston Deer Park 2 C35/139 150 La Porte Sylvan Beach C556 149

2008 Houston Deer Park 2 C 35/139 147 Tom Bass C558 138 Source: Leading Environmental Analysis and Display System (LEADS).

Another way to see the ozone trend in the HGB area is to examine how the spatial distributions of ozone have changed over the years. Figure 5-12: Eight-Hour Ozone Design Values for 2000, 2005, and 2008 shows the spatial distribution of eight-hour ozone design values in the HGB area, for regulatory monitors only, and the changes that have occurred from 2000 to 2005 to 2008. In 2000, local peaks in design value were at H ouston Aldine (CAMS 8), Houston Bayland Park (CAMS 53), and Deer Park (CAMS 35/139), and all three peaks were 110 ppb or higher.

By 2005, eight-hour ozone design values had dropped across the region. While the highest concentrations still occurred at Houston Bayland Park (CAMS 53) and Deer Park (CAMS 35/139), they were no longer observed in the Hous ton Aldine (CAMS 8) area. Further, the 2005 peaks are much lower, between 100 and 103 ppb. The lowest eight-hour ozone concentration is still observed at Lang (CAMS 408), but low ozone al so occurs to the northeast at Houston North Wayside (CAMS 405), to the north at Conroe (C AMS 65) or Conroe Relocated (CAMS 78), and to the south at Galveston Airport (CAMS 34/CAMS 109/CAMS 154). The minimum eight-hour

ozone concentration in 2005 is below the 1997 NAAQS.

In 2008, eight-hour ozone design values dropped even further. Ozone concentrations are substantially lower across a large part of the HGB area, with the kriging model predicting design values below the 1997 eight-hour ozone NAAQS at many locations. Maximum eight-hour ozone concentrations are now considerably lowe r, between 89 ppb and 91 ppb. The highest measurements occurred at Houston Bayland Pa rk (CAMS 53) and Deer Park (CAMS 35/139), and also at a new monitor, Park Place (CAMS 416), which measured ozone in the same range as Houston Bayland Park (CAMS 53) and Deer Park (CAMS 35/139). The eight-hour ozone concentrations in 2008 are lower throughout the HGB area, with a local ozone minimum located in the urban core area surrounding the Lang (CAMS 408), Houston North Wayside (CAMS 405), Houston Texas Avenue (CAMS 411), Clint on (CAMS 403/CAMS 113/CAMS 304), and the TCEQ Houston Regional Office (CAMS 81) monitors.

Notice that while the overall concentrations of eight-hour ozone are lower, the areas that experience the highest and lowest ozone remain th e same. Spatial interpolation shows that high

ozone concentrations continue to occur sout h of downtown Houston, and stretch from the Houston Ship Channel in the east to west Houst on, near Houston Bayland Park (CAMS 53). The lowest ozone values are found to the south along the coast, at the northern edge of the nonattainment area towards Conroe (CAMS 65), and to the northwest of downtown Houston, at Lang (CAMS 408).5-29Figure 5-12: Eight-Hour Ozone Design Values for 2000, 2005, and 20085-30 The kriging method can also be employed to investigate the geographic origins of high ozone concentrations. Studies during the TexAQS 2000 field study reported that the highest ozone in the HGB area occurs in plumes emanating from i ndustrial areas (Daum et al., 2004; Kleinman et al., 2005; Ryerson et al., 2003; Berkowitz et al., 2005; Banta et al., 2005). As these plumes are transported across the region, they can be tracked by the high ozone concentrations recorded at successive downwind monitors as the day progr esses. An analysis of the time of day of maximum ozone at each monitoring site can confirm or challenge conclusions of the field study about these origins by revealing spatial pa tterns of ozone formation and movement.

Yet another way to examine the ozone behavior in the HGB area is to investigate the time of day that ozone peaks, on average, in each part of the monitoring network. Daily maximum ozone concentrations were divided into two groups: days with values exceeding the 1997 eight-hour ozone NAAQS, and days not exceeding the 1997 eight-hour ozone NAAQS. The time of day when peak ozone was recorded at each monito r was determined for each day, then averaged across the two groupings of days. Only monitors that report data to the EPA were included. Days were restricted to March through November to exclude months when few or no exceedance days occur in the HGB area.

Maps of the time of peak ozone in the HGB area, averaged from March through November 1998- 2008, are found in Figure 5-13: Time of Day of Peak Hour ly Ozone on Low and High Ozone Days . The left map shows that on days with low eight-hour ozone values, daily maximum values

are recorded in the Galveston ar ea early in the day, between 11:30 a.m. and 11:45 a.m. Inland monitors record their highest daily values at pr ogressively later times of day, as monitors are

located farther inland from the Gulf Coast. On low ozone days, the earliest ozone maxima occur near the coast, and the latest occur in the Conroe area between 2:00 p.m. and 2:15 p.m. This pattern of ozone concentrations is consistent with the occurre nce of the sea breeze, which often dominates local weather during the summer in the absence of strong synoptic-scale weather influences. After the plume is carried past a monitor, ozone levels often drop, reflecting the

cleaner maritime air behind the sea breeze front.

By contrast, the right map of the daily pattern on high eight-hour ozone days looks quite different. Daily maximum ozone concentrations are obser ved earliest in the industrial areas, and successively later at sites that are progressively farther away from these areas. This pattern indicates that high ozone forms first in the industria l areas, and is transported outward to urban, suburban, and rural sites later in the day. Ma ximum ozone occurs latest at Lake Jackson (CAMS 1016), Clute (CAMS 11), Northwest Harris Co. (CAMS 26), Conroe (CAMS 65) and Conroe Relocated (CAMS 78), the sites at the gr eatest distance from the industrial area.

The time of day of maximum ozone on high ei ght-hour ozone days represents a composite pattern: high ozone formed in industrial areas is carried by winds to Conroe (CAMS 65) and Conroe Relocated (CAMS 78) on some days, to Lake Jackson (CAMS 1016) on other days, and to western Houston on other days. Combined w ith the earlier spatial design value analysis, the patterns of peak ozone appear to show that the highest ozone concentrations are formed in the vicinity of the heavily industrialized areas of metropolitan Houston and are then transported throughout the area.5-31Figure 5-13: Time of Day of Peak Hourly Ozone on Low and High Ozone Days

### 5-32 5.3.3 Trends in the Strength of Observed Ozone Gradients in the HGB Area Rapid ozone increases have been observed at HGB area monitoring sites for many years, but the phenomenon was not sufficiently explained until the TexAQS 2000 study. Researchers from Brookhaven National Laboratory and National Oceanic and Atmospheric Administration (NOAA) Aeronomy Laboratory were able to establis h that the rapid ozone increases were due to strong spatial ozone gradients that arose when oz one formed very rapidly in industrial plumes. The rapid ozone formation observed by Daum et al . (2003, 2004) allowed ozone to build up in the plumes before ozone and its precursors could disperse. Shifting winds due to the coastal oscillation or bay/Gulf breeze phenomena pushed the strong ozone gradients over the monitoring sites, resulting in observations of rapid ozone increases (Banta et al., 2005). The rapid ozone

formation occurs when industrial HRVOC reacts with co-emitted NO X (Ryerson et al., 2003; Wert et al., 2003). The following analysis ex amines whether the strength of these ozone gradients has lessened, as measured by the magn itude of one-hour changes in ozone observed at monitoring sites.

One-hour changes in ozone concentrations exam ined for each hour during the ozone season (May through October) at each site for each year . The maximum daily peak change in ozone concentration was chosen for each day, and vari ous statistical measures were calculated from

those values. Not all sites were included in this analysis: only those with long operating histories
were included.

Figure 5-14: Trends in the Strength of Ozone Gradients Measured in the HGB Area from 1995 through 2008 shows how the daily maximum one-hour change in ozone has changed since 1995

in the HGB area. While at the mean and median levels the change is slight, the steepest observed ozone gradients have been reduced dramatically since 1995, decreasing by about 40 percent.

### 5-33 32

27 30 28 32

27 28 26 30

27 28
25 24

21 29

22 26

23 29

22 24

21 26

23 25 25

22 20 62

57 65 66

62 63

55 62

58

53 52

44 48

38

0 10 20 30 40 50 60 70

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008Peak 1-hr delta ozone, ppb/hr

Mean

Median 95th percentile

32

27 30 28 32 62

57 65 66

62 63

55 62

58

53 52

44 48

38

27 28 26 30

27 28
25 24

21 29

22 26

23 29

22 24

21 26

23 25 25

22 20

0 10 20 30 40 50 60 70

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008Peak 1-hr delta ozone, ppb/hr

95th percentile

Mean

Median

Figure 5-14: Trends in the Strength of Ozone Gradients Measured in the HGB Area from 1995 through 2008

Figure 5-15: The Number of Occurrences of One-Hour Increases in Ozone Greater Than 40 ppb/hr in the HGB Area for the Subset of Monitors with Long Historical Records shows that the number of strong ozone gradients observed by monitoring sites in the HGB area has also decreased substantially since the 1990s, matc hing the general trends in decreasing ozone concentrations. The intensity of ozone gradients has decreased, and the frequency of strong ozone gradient observations has also decreased, whic h strongly suggests that ozone is forming less rapidly in the HGB area than in previous years. Th is change in ozone behavi or is consistent with decreasing reactivity of VOC emitted in the HGB area. Note that the intensity of ozone gradients can depend upon meteorological factors as well as chemical factors. This analysis has not examined the importance of meteorological f actors upon the observed trends. Subsequent

sections will discuss trends in HRVOC concentrations.

### 5-34 y = -5.6593x + 92.659

R

2 = 0.6093

0 20 40 60 80 100 120

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008Number of observed strong ozone gradients

Figure 5-15: The Number of Occurrences of One-Hour Increases in Ozone Greater Than 40 ppb/hr in the HGB Area for the Subset of Monitors with Long Historical Records

5.3.4 The Impact of Hurricane Ike on Ozone Observations in the HGB Area The HGB area typically records high ozone values each year in September. Sometimes, these values help determine the area-wide design value for that year. The HGB eight-hour ozone design value has been declining recently and w as particularly low in 2008 (91 ppb). September 2008 was not typical for the HGB area. Hurricane Ike, a strong Category 2 hurricane, struck the Texas coast near Galveston Bay on September 13, 2008. Most monitors in the area were shut down and emissions patterns we re substantially altered.

Hurricane Ike struck the Texas co ast near Galveston Bay on September 13, 2008. Before the hurricane struck, the evacuation of Galveston Is land and the surrounding areas created enormous traffic jams. After the storm passed, there was far less automobile traffic than normal for several weeks. In preparation for the storm, many of the local petrochemical facilities shut down their operations, generating unknow n quantities of emissions in the process, and after the storm, their operations were atypical for an extended period. Rescue operations, tree cutting and burning, lack of electrical power, unusual traffic patterns, and abnormal industrial operations were among the atypical conditions that occurred before, during, and after the hurricane. The exact effect of the emission changes on ozone concentrations is unknown, due to the number of ozone monitoring sites disabled indirectly or directly by Hurricane Ike. Monitors in the HGB area ceased operations for as little as one day, and as l ong as 69 days at a site that was severely damaged by storm surge. Key monitors that typically record the area design values were down for as much as 16 days, e.g., Houston Bayland Park (CAMS 53) (see Table 5-10: List of the Number of Days HGB Ozone Regulatory and Non-Regulatory Monitors were Not Operating Before and After the Landfall of Hurricane Ike ).

### 5-35 Table 5-10: List of the Number of Days HGB Ozone Regulatory and Non-Regulatory Monitors were Not Operating Before and After the Landfall of Hurricane Ike

Monitor First Date

Monitor Did Not Report Data Restart

Date Days

Down

Houston Bayland Park C53/A146 9/13/2008 9/29/2008 16
Houston Westhollow C410 9/12/2008 9/30/2008 18
Park Place C416 9/12/2008 9/15/2008 3
Houston Deer Park 2 C 35/C139 9/12/2008 9/22/2008 10
Manvel Croix Park C84 9/12/2008 9/21/2008 9

Northwest Harris Co. C26/A110/X150 9/13/2008 9/14/2008 1
Houston Aldine C8/AF108 /X150 9/13/2008 9/15/2008 2

Houston Monroe C406 9/12/2008 9/19/2008 7 Houston Croquet C409 9/12/2008 9/26/2008 14
Conroe Relocated C78/A321 9/13/2008 9/17/2008 4

Channelview C15/AH115 9/13/2008 9/16/2008 3

Houston East C1/G316 9/13/2008 9/29/2008 16 Seabrook Friendship Park C45 9/13/2008 9/16/2008 3

Houston Texas Avenue C411 9/12/2008 9/16/2008 4
Lake Jackson C1016 9/12/2008 9/16/2008 4 Lang C408 9/12/2008 9/18/2008 6 Houston North Wayside C405 9/12/2008 9/15/2008 3 Lynchburg Ferry C1015/A165 9/12/2008 10/16/2008 34 Houston Regional Office C81 9/13/2008 9/20/2008 7
Clinton C403/C304/AH113 9/12/2008 9/30/2008 18

West Houston C554 9/13/2008 9/14/2008 1

Tom Bass C558 9/13/2008 9/18/2008 5
Wallisville Road C617 9/12/2008 9/17/2008 5 Meyer Park C561 9/13/2008 9/15/2008 2
Atascocita C560 9/14/2008 9/23/2008 9 La Porte Sylvan Beach C556 9/12/2008 11/6/2008 55 Baytown Wetlands Center C552 9/12/2008 10/31/2008 48 Mustang Bayou C619 9/12/2008 9/26/2008 14 Clear Lake High School C572 9/13/2008 9/14/2008 1
HRM-3 Haden Road C617 9/12/2008 9/22/2008 10 Crosby Library C553 9/13/2008 9/20/2008 7 Texas City 34 th St. C620 9/12/2008 9/18/2008 6 Dacinger C618 9/12/2008 9/19/2008 7 Kingwood Library C555 9/13/2008 9/14/2008 1
Mercer Arboretum C557 9/22/2008 10/8/2008 16

Sheldon C551 9/12/2008 9/22/2008 10 Clear Creek High School C571 9/13/2008 9/15/2008 2
Galveston 99 th St. C1034/A320/X183 9/12/2008 11/20/2008 69
Pasadena AAMS C672 9/12/2008 9/22/2008 10

Hurricane Ike’s greatest impact occurred during the second half of September and the first half of October. August and September are typically th e months when the HGB area records the most number of days that exceed the ozone standard. For 2000 through 2008, 21 percent of the 266 observed 85 ppb exceedance days in the HGB area were recorded in September (Figure 5-16: Number of Days that Exceeded the 1997 Eight-Hou r Ozone NAAQS by Mont h from 2000 through

2008 ).

### 5-36 3 20 26 49

32 54 55

22

5

0 10 20 30 40 50 60

Mar Apr May Jun Jul Aug Sep Oct Nov Number of Days

Figure 5-16: Number of Days that Exceeded the 1997 Eight-Hour Ozone NAAQS by Month from 2000 through 2008

Figure 5-17: Frequency of Daily Peak Eight-Hour Ozone Values for All Ozone Monitoring Sites in Texas, September 2006 and Figure 5-18: Frequency of Daily Peak Eight-Hour Ozone Values for All Ozone Monitoring Sites in Texas, September 2008 show peak eight-hour ozone at all Texas monitoring sites in September 2006, which was unaffected by tropical systems and in September 2008, the month in which Hurricane Ike struck. In 2008, the number of monitors in operation dropped substantially just before the hurricane made landfall, as they were shut down by the TCEQ. The monitors came back on-line gradually, as electrical power was restored, and storm damage was repaired. Ozone concentrations immediately before and after Ike were fairly

low.

The purpose of this analysis is to examine how the ozone behavior in September and October 2008 deviated from the 2000 through 2007 average, and thus to ascertain whether the lower design value observed in 2008 was due primarily to the effects of Hurricane Ike.

### 5-37 0 20 40 60 80 100 120

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29

Sept 2006 dateSite Count below 15 ppb

15 to 29 ppb

30 to 44 ppb

45 to 59 ppb

60 to 74 ppb

75 to 84 ppb

85 ppb or abov e

Figure 5-17: Frequency of Daily Peak Eight-Hour Ozone Values for All Ozone Monitoring Sites in Texas, September 2006

0 20 40 60 80 100 120

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29

Sept 2008 dateSite Count below 15 ppb

15 to 29 ppb

30 to 44 ppb

45 to 59 ppb

60 to 74 ppb

75 to 84 ppb

85 ppb or abov e

Figure 5-18: Frequency of Daily Peak Eight-Hour Ozone Values for All Ozone Monitoring Sites in Texas, September 2008

5.3.4.1 Approach One approach to estimate the influence of Hurri cane Ike on the HGB area’s ozone design value is to estimate what the eight-hour ozone design value might have been in 2008 if Hurricane Ike had

not occurred. This estimate is derived from historical data collected during 2000-2007. Removing calendar days affected by Hurricane Ike and replacing them with averages derived from historical data yields a re-calculated four th-highest eight-hour ozone concentration for each monitor. The actual fourth-high is then divide d by the re-calculated fourth-high to obtain an

### 5-38 adjustment ratio or an Ike Adjustment Factor (IAF). This ratio is expected to be greater than one, and can be used to adjust 2008 ozone data to non-hurricane conditions. The IAF can be calculated as an area-wide average IAF or as a m onitor-specific IAF. An area-wide average IAF is computed as the average of all IAFs from all m onitors in the region, applied to all 2008 data. The monitor-specific IAF was applied only to the monitor in question. After the data were adjusted with IAFs, an IAF-corrected design va lue was calculated and compared to the current unadjusted ozone design value to determine the influence of Hurricane Ike.

The days affected by Hurricane Ike are not easy to identify. As stated before, many unusual
activities occurred in the HGB area before the arri val of Hurricane Ike, and many others occurred in the aftermath. For example, many industria l facilities shut down operations before the storm arrived, releasing emissions that they usually would not release. After the hurricane, electrical power was not available in parts of the HGB area for two or more weeks. Given the difficulties in establishing the exact period of Hurricane Ike’s in fluence, alternative IAFs were calculated by removing three different time periods from the histor ical ozone data. The first period considered for exclusion was a two-week period from Sept ember 11 through September 25, 2008, which includes days immediately before and after the hurricane. Two other periods considered for exclusion were a one-month period from Septembe r 6 through October 5, 2008, and a one-month period after the storm (September 13 through October 12, 2008). All data used in this analysis were obtained from the TCEQ-LEADS system, and are eight-hour ozone averages. The HGB area eight-hour ozone design value was obtained from the EPA.

5.3.4.2 Results

Table 5-11: Alternative Fourth-High Daily Peak Eight-Hour Ozone Concentration Calculations Using Different Ike Adjustment Factors (IAFs) shows results of the six different methods for estimating the fourth-high daily peak eight-hour ozone concentration for each monitoring site. The table shows that the expected fourth high is gr eater than the observed at most sites, regardless

of which method is used to calcula te the expected fourth high. This indicates that the atypical conditions experienced during and after Hurrican e Ike during September and October in 2008 did have an effect on the monitored values, but th e effect was no greater than 4 ppb on the fourthhigh daily maximum ozone concentration.

### 5-39 Table 5-11: Alternative Fourth-High Daily Peak Eight-Hour Ozone Concentration Calculations Using Different Ike Adjustment Factors (IAFs)

Monitoring site 2008
observed

fourth high 9/11-
9/26

average

IAF 9/11-
9/26

monitorspecific

IAF 9/6-

10/5

average

IAF 9/6-10/5

monitorspecific

IAF 9/13-

10/12

average

IAF 9/13-

10/12

monitorspecific

IAF
ppb ppb ppb ppb ppb ppb ppb

Houston Aldine C8 /AF108/X150 83 85 86 87 86 86 86 Houston Bayland Park C53 83 85 84 87 86 86 85

Channelview C15/C115 76 78 77 79 78 79 78 Houston Croquet C409 76 78 78 79 80 79 79

Houston Deer Park C18 76 78 78 79 79 79 78

Lake Jackson C1016 76 78 77 79 80 79 78

Northwest Harris Co. C26/A110/C154 76 78 78 79 81 79 80

Manvel Croix Park C84 75 77 77 78 81 78 78

Conroe C65 73 75 74 76 75 76 75

Houston East C1 73 75 74 76 76 76 76

Houston Monroe C406 71 73 73 74 75 74 74 Seabrook Friendship Park C45 71 73 75 74 75 74 75 Houston North Wayside C405 70 72 70 73 71 73 71

Houston Texas Avenue C411 70 72 71 73 73 73 73 Lang C408 70 72 73 73 75 73 74

Clinton C403/C113/C304 69 71 70 72 72 71 72

Houston Westhollow C410 69 71 70 72 71 71 71 Houston Regional Office C81 68 70 69 71 71 70 70 Lynchburg Ferry C1015 65 66 65 68 66 67 66 This table compares the observed 2008 fourth-high at each monitor to the expected fourth high, as calculated by six different methods.

The attainment status of an area is not based upon fourth-high ozone c oncentrations, but upon design values. Table 5-12: Observed and Expected Design Values, Recalculated to Account for

Hurricane Ike shows the observed 2008 design value, and the expected design values, as

calculated with the six different methods described above. As Table 5-12: Observed and Expected Design Values, Recalculated to Account for Hurricane Ike shows, the effect upon the design value for the HGB area is at most 1 ppb, and for two of the alternatives there is no effect. This analysis is robust, because six different methods of estimating the effect of the hurricane on ozone design value have given substantially th e same answer: the 2008 eight-hour ozone design value was not different from the expected design value, based upon comparisons with historical data. Therefore, based upon the historical anal ysis, the effect of Hurricane Ike upon the eighthour ozone design value in the HGB area was apparently minimal.

Table 5-12: Observed and Expected Design Values, Recalculated to Account for Hurricane

Ike

Observed Design Value: 91 ppb 2-weeks

9/11-9/25 1-month

9/13-10/12 1-month

9/6-10/5
Estimated Design Value after applying area-wide average Ike Adjustment Factor 91 ppb 92 ppb 92 ppb

Estimated Design Value after applying monitorspecific Ike Adjustment Factor 92 ppb 91 ppb 92 ppb

### 5-40 5.3.5 NO X Trends Nitrogen oxides, or NO X , are a variable mixture of NO and NO 2 and are critical precursors to
ozone formation. NO X is primarily created by fossil fuel combustion, lightni ng, biomass burning,

and microbial action in the soil.

Previous analyses performed using aircraft measurements and emission inventories obtained during TexAQS 2000 and TexAQS II indicate that NO X emissions in the Houston Ship Channel area have decreased between 2000 and 2006 (Cowling et al., 2007). Furthermore, aircraft data obtained during the two field studies were in ag reement with data measured by continuous emission monitoring systems (CEMS) located at the facilities. Analyses done by the Rapid Science Synthesis Team of the 2005-2006 Texas Air Quality Study (TexAQS II) indicate that

NO X emissions at several electric generating units (EGUs) have decreased by factors ranging from two to four between 2000 and 2006 (Cowli ng et al., 2007). These reductions were seen at EGUs that implemented NO X control features, such as selective catalytic reduction (SCR), between 2000 and 2006, which suggests these control strategies are working. The two field studies effectively describe the emissions during two short time windows, six years apart. To complement these analyses, the TCEQ has performed a more comprehensive investigation of long-term trends in NO X concentrations.

Daily peak one-hour NO X from all monitors in the HGB area from 1991 through 2008 is plotted in Figure 5-19: Daily Peak Hourly NO X in the HGB Area . The increasing density of NO X data points shows that the number of NO X monitors in the HGB area ha s greatly increased since 1991.
Annual 90 th percentile and annual average NO X values are also plotted in the figure. Both of

these measures have decreased ma rkedly over the 1991 to 2008 pe riod, falling 64 percent and 68 percent, respectively. Even more remarkable may be the 53 percent and 48 percent declines since

1999.5-411991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008Date of 90thpercentile:Oct Dec Dec Oct Nov Dec Nov Feb Nov Sep Apr Dec Dec Apr Dec Nov Nov Oct22 15 25 30 22 12 19 24 12 5 27 15 19 28 1 16 14 22Figure 5-19: Daily Peak Hourly NOXin the HGB Area

### 5-42 Table 5-13: NO X Values in the HGB Area by Year shows the degree of decrease in NO X concentrations from 1991 through 2008 and 1999 through 2008.

Table 5-13: NO X Values in the HGB Area by Year

annual annual maximum average year NO X NO X ppb ppb

1991 880 110

1992 780 110

1993 622 103
1994 523 99
1995 524 99

1996 773 98
1997 521 75
1998 520 67
1999 696 75

2000 641 57

2001 629 66

2002 678 52
2003 809 53
2004 509 49
2005 609 49
2006 593 49

2007 461 48
2008 409 35

overall decrease through 2008 since:

1991 -53.5% -67.7%
1999 -41.2% -53.0%

annual decrease through 2008 since:

1991 -4.4% -6.4%
1999 -5.7% -8.0% Annual decreases are computed as compound annual rates.

Though highly variable from season to season, daily peak hourly NO X also shows a general decreasing trend since 1991. Maximum NO X concentrations have decreased overall by 41 percent since 1999, an average of roughly 32 ppb per year, or nearly 6 percent per year. The drop since the 1991 high of 880 ppb is 54 percent or greater than 4 percent annually.

Average daily peak hourly NO X has dropped even more precipitously, falling 53 percent, or 8 percent per year, from 75 ppb to 35 ppb, since 1999. Since 1991, average hourly NO X has dropped 68 percent, or over 6 percent per year, from the series high of 110 ppb. Notice that in 2008, both the NO 2 design value and maximum daily peak NO X recorded the lowest values of any previous year back to 1991.

### 5-43 While the highest NO X values occur in the winter, the NO X values during the summer months, when ozone production is the highest, are of part icular interest. Trends in median hourly NO X concentrations at individual monitors in the HGB area from May through October, 1998 to 2008, are shown in Figure 5-20: Median NO X Concentrations in the HGB Area . Four monitors of particular interest, Houston Texas Avenue (CAMS 411), Lang (CAMS 408), Clinton (CAMS 403/CAMS 113/CAMS 304), and H ouston Bayland Park (CAMS 53), are highlighted. Sites with less than 75 percent complete data for a year were not plotted for that year; for example, Clinton (CAMS 403/CAMS 113/CAMS 304) had less than 75 percent complete data in 2008 and therefore was not plotted.

Median NO X Concentrations in the HGB Area (May through October)

0 5 10 15 20 2519981999200020012002200320042005200620072008 NO X (ppb) Conroe Deer Park Lynchburg Ferry Manvel Croix NW Harris Co. Park Place Texas Ave

Houston East Clinton Lang

Galveston Airport Lake Jackson A ldine

Seabrook Channelview Bayland Park

Figure 5-20: Median NO X Concentrations in the HGB Area

Median NO X values tend to vary from year to year, but most monitors show overall decreases in
median NO X since 1998. Monitors that show the sma llest decreases or show no change are at sites that have traditionally had lower NO X concentrations. Some of the largest median NO X concentrations were measured at the Lang (CAM S 408) monitor (in close proximity to Highway 290), and at the Houston Texas Avenue (CAMS 411) monitor (in downtown Houston). These monitors are both near major roadways; their similar trends suggest they may be measuring

decreases in NO X emissions from mobile sources. Monitors at Galveston Airport (CAMS 34/C109/C154), Seabrook Fr iendship Park (CAMS 45), and Lake Jackson (CAMS 1016)

measured the lowest median NO X concentrations.

Sites recording among the highest ozone design values, for example, Houston Bayland Park (CAMS 53) and Park Place (CAMS 416), are not necessarily the sites with the highest median

NO X concentrations. The previous section showed that Houston Bayland Park (CAMS 53) has the highest eight-hour ozone design value in the HGB area of 91 ppb, yet it has a lower median

NO X concentration than many other sites in the ar ea. This observation is consistent with the behavior expected from ozone chemistry; in add ition to being an ozone precursor, NO also reacts directly with ozone and in areas with high NO emi ssions, can destroy more ozone than it creates.

### 5-44 Downwind from the high emission areas, however, ozone destroyed by reaction with NO can reform.

The largest decreases since 1998 (Table 5-14: Median and 90 th Percentile Hourly NO X Values ) were observed at monitors primarily influenced by mobile source emissions, rather than industrial sources. Clinton (CAMS 403/CAMS 113/CAMS 3 04) and Houston East (CAMS 1), which are located near both industrial sources and highway s, have seen larger decreases in median NO X values than in 90 th percentile values since 1998. At Houston East (CAMS 1), the 90 th percentile value decreased 34 percent, while the median decreased 42 percent between 1998 and 2008. The Clinton (CAMS 403/CAMS 113/CAMS 304) monitor experienced a drop of 16 percent in the 90 th
percentile, with a 21 percent decrease in the me dian between 1998 and 2007 (2008 was not used due to incomplete data), though these m easures have increased in recent years.

Table 5-14: Median and 90 th Percentile Hourly NO X Values
median 90 th percentile % change % change

monitor 1998 2007 2008 1998-2008 * 1998 2007 2008 1998-2008 *
ppb ppb ppb % ppb ppb ppb %

monitors with decreasing trends

Houston Bayland Park C53 8 8 3 -63 33 30 19 -42

Northwest Harris Co. C26/ 10 5 4 -60 21 12 12 -43

A110/C154 Lang C408 21 16 11 -48 65 48 35 -46

Houston East C1 19 15 11 -42 56 46 37 -34
Clinton C403/C113/C304 * 24 19 - -21 56 47 - -16

monitors with increasing trends

Houston Aldine C8/AF108/X150 3 10 9 200 30 32 30 0

Houston Deer Park C18 3 5 5 67 25 21 18 -28

monitors with indeterminate trends

Channelview C15/C115 - 9 8 - 24 20

Conroe C65 - 4 4 - 10 10 Galveston Airport

C34/C109/C154 0 - - 1 - -

Houston Texas Avenue C411 - 17 14 - 53 37
Lake Jackson C1016 - 2 2 - 7 6 Lynchburg Ferry C1015 - 11 - - 33 -

Manvel Croix Park C84 - 5 4 - 17 15

Park Place C416 - 11 8 - 47 32 Seabrook Friendship Park C45 - 4 3 - 12 12 * Percentage changes computed from 1998 to 2007 for years missing 2008 data, due to incomplete data. Monitors are sorted in increasing order by percenta ge change in median values. Monitors with

indeterminate trends be gan operating after 1998.

While several monitors recorded large decrea ses from 2007 to 2008, most others observed only minimal changes over that same period. Th ese large disparities in patterns of ambient NO X concentrations across the region are appropriate fo r further investigation, suggesting that larger decreases are not due solely to variations in me teorological conditions, which would be expected

### 5-45 to influence all monitors similarly, though not identically. The differences seem to be related to the relative magnitudes of the overall concentrati ons. Sites with the highest concentrations, which tend to be urban sites, showed the greatest decrease. More rural sites like Lake Jackson (CAMS 1016), Conroe (CAMS 65), and Conroe Relocated (CAMS 78) may reflect slight changes in background values, while more urba n sites may reflect actual emission changes.

Similar to ozone, NO X concentrations in the HGB area appear to be decreasing over time, in large measure the result of the comprehensive suite of NO X -targeted controls implemented since 2000. Stringent point source NO X standards have been adopted along with numerous factors affecting
mobile source NO X emissions.

5.3.6 Ambient VOC Concentrations The other major class of compounds that are ozone precursors are VOC. TexAQS 2000 researchers identified a specific subset of VOC that were closely associated with rapid and efficient ozone formation, i.e., light alkenes (Ryerson et al., 2003; Daum et al., 2003, 2004; Jobson et al., 2004). The TCEQ examined the hi storical data for these compounds, and decided to regulate several light alkenes emitted by industry that were particularly reactive, and that often had particularly high concentrations: ethylene , propylene, 1,3-butadiene, and butenes.

Since the mid-1990s, the TCEQ has collected 40-mi nute measurements, on an hourly basis, of 45 VOC compounds using automated gas chromat ograph (auto-GC) instruments. Initially, measurements were collected at just one s ite (Clinton (CAMS 403/CAMS 113/CAMS 304)), but in subsequent years, auto-GC monitors have been added to new sites (see Figure 5-21: Houston Ship Channel Auto-GC Monitors and 2006 Reported Point Source HRVOC Emissions Points and

Plant Boundaries ). Currently, eight sites, listed in Table 5-15: Auto-GC Monitors in the Houston Ship Channel Area , along or near the Houston Ship Channel, along with three in Brazoria County and one in Texas City, are collecting VOC measurements with auto-GCs.

### 5-46 Figure 5-21: Houston Ship Channel Auto-GC Monitors and 2006 Reported Point Source
HRVOC Emissions Points and Plant Boundaries

Ambient concentrations of the TCEQ-defined HR VOC (ethylene, propylene, 1,3-butadiene, 1- butene, c-2-butene, and t-2-butene) were analyzed from 1995 to 2008.

Table 5-15: Auto-GC Monitors in the Houston Ship Channel Area

start
site name CAMS AIRS code latitude longitude city date
Channelview C15/C115 482010026 29.8 025 -95.1256 Channelview 8/3/2001 Houston Milby Park A169 482010069 29.7062 -95.2611 Houston 2/19/2005
HRM-3 Haden Road C603 482010803 29.7483 -95.1811 Houston 8/20/2001 Lynchburg Ferry C1015 482011015 29.7646 -95.0780 Houston 5/24/2003
Clinton C403/113/304 482011035 29. 7337 -95.2576 Houston 7/1/1995
HousDeerPrk2 C35/139 482011039 29.6 700 -95.1285 Deer Park 1/5/1997
Cesar Chavez C1020/175 482016000 29. 6844 -95.2536 Houston 4/13/2004
Wallisville Road C617 482010617 29.8214 -94.99 Baytown 6/5/2003

Trends at each of the eight Houston Ship Channe l monitors were examined. Data from the four other auto-GC monitors were analyzed only for tr end slope and possible statistical significance of trends. Daily geometric means were computed from valid ambient hourly measurements for days with at least 18 valid hours of data. A geomet ric mean was calculated by taking the natural logarithm of each of the measurements, averaging these logs, then calculating the antilog of this mean log value. The geometric mean is a preferab le statistic to median or arithmetic (ordinary) mean for evaluating the central tendency of data when the data are skewed, that is, when the data are not symmetrically, or normally, distributed, but clustered around extreme high or low values. It is more robust than an ordinary average, meani ng its value is not greatly influenced by one or a few very high or very low values. Many distribut ions of pollutant measurements in the HGB area are skewed. Monthly geometric means were also computed with a 75 percent data completeness criterion for valid days in a month.

Figure 5-22: Monthly Geometric Mean Ethylene Concen trations at the Eight Houston Ship Channel Monitors, July 1995 through December 2008 shows monthly geometric mean ethylene concentrations, ordered according to the monitor lo cation from west to east. Grey bars denote the range of values from the 25 th through 75 th percentile concentrations, for all monitors. Noteworthy in this figure is the frequency of extremely high values recorded during the 1990s at Clinton (CAMS 403/CAMS 113/CAMS 304), at the western e nd of the Houston Ship Channel, and Deer Park (CAMS 35/139), in south central Houston Ship Channel. These were the only monitors operating during the early years of this period; this pattern suggests that high ethylene
concentrations were not restricted to certain areas of the Houston Ship Channel, but were somewhat geographically widespread.

### 5-47 Figure 5-22: Monthly Geometric Mean Ethylene Concentrations at the Eight Houston Ship Channel Monitors, July 1995 through December 2008

For four consecutive years, July 1995 through July 1999, valid monthly geometric mean concentrations at Clinton (CAMS 403/CAMS 113/CAMS 304) exceeded the 75 th percentile of the multi-decade series. Deer Park (CAMS 35/139) also exhibited high concentrations in the first several years, including the highest mean value for any complete month, 10.2 parts per billion, carbon (ppbC) in March 2001. By contrast, few monthly mean concentrations exceeded the 75 th
percentile in the most recent four years, 2005 through 2008.

Though measured ethylene and propylene concentrat ions show a large degree of variability at all auto-GC monitors, downward trends are apparent at seven of the eight; only Wallisville Road

### 5-48 (CAMS 617) appears to show no decrease. A statis tical trend analysis, described below, provides further insight into this.

Peak monthly geometric mean ethylene concentra tions at all monitors, 6.9 ppbC and 8.4 ppbC in 2003 and 2004 respectively, decreased to 5.6 ppbC in 2005, 4.9 ppbC in 2006, and 4.5 ppbC in 2007, before climbing to 5.1 ppbC in 2008. This decline in ambient ethylene concentrations suggests that ethylene emissions in the Houston Ship Channel are declining, though meteorology could be responsible for some or all of th e decline in geometric mean concentrations.

Similar to Figure 5-22: Monthly Geometric Mean Ethylene Con centrations at the Eight Houston Ship Channel Monitors, July 1995 through December 2008 , Figure 5-23: Monthly Geometric Mean Propylene Concentrations at the Eight Houston Ship Channel Monitors, July 1995 through

December 2008 displays monthly geometric mean concentrations of propylene for the eight Houston Ship Channel area auto-GC monitors . Again, Clinton (CAMS 403/CAMS 113/CAMS 304) and Deer Park (CAMS 35/139) show higher concentrations in earlier years compared to recent ones; however, the magnitude of concentrati ons at the two monitors are dissimilar, unlike ethylene, suggesting elevated propylene concen trations are more geographically limited than elevated ethylene concentrations. Two ot her eastern Houston Ship Channel monitors, Channelview (CAMS 15/CAMS 115) and Lynchburg Ferry (CAMS 1015), report concentrations
well above the 75 th percentile in 2003, and to a lesser ex tent in 2004 and subsequent years, suggesting there are greater propylene emissions in the eastern Houston Ship Channel than the western Houston Ship Channel. However, the relatively fast reactivity of propylene, compared to ethylene, may explain part or all of the low c oncentrations seen in the western Houston Ship

Channel.

Similar analyses were performed for 1, 3-butadiene and the isomers of butene; however, trends in these pollutants can be difficult to interpret, as their relatively low concentrations are frequently within accepted measurement uncertainty. Further work is needed before trend estimation for these compounds can be considered accurate.

Though still variable from month to month, pervasi ve decreases in the ambient concentrations of ethylene and propylene suggest that overall industrial emissions of these compounds have decreased considerably since 1995. This finding agrees with early reports from TexAQS II that ethylene emissions along the Houston Ship Cha nnel have decreased approximately 40 percent

from 2000 to 2006.

### 5-49 Figure 5-23: Monthly Geometric Mean Propylene Concentrations at the Eight Houston Ship Channel Monitors, July 1995 through December 2008

A preliminary analysis was performed to verify whether decreases observed were statistically significant. Ordinary least squares regression lines were fit to the monthly geometric mean ethylene and propylene concentrations, using an index of month, where the first recorded month was given a value of zero. Results of these fits are reported in Table 5-16: Parameter Estimates of Monthly Geometric Mean Concentrations Trends . In 23 of the 24 regressions, concentrations decreased across the respective study pe riods, with correlation coefficient (R 2 ) values ranging from 0.045 to 0.549. Eight of 12 monitors reco rded statistically significant decreases for ethylene, including six of eight Houston Ship Channel monitors. All 12 monitors recorded statistically significant decreases for propylene. However, caution must be exercised when

### 5-50 interpreting these results. First, some of the computed R 2 values are very low, confirming there is a substantial degree of variation in the measured values, with only a portion of it explained by a simple linear model. Further statistical testing and verification, such as testing for and correcting possible autocorrelation, is necessar y to fully validate these models.

Table 5-16: Parameter Estimates of Monthly Geometric Mean Concentrations Trends ethylene propylene

monitoring site N slope intercept R 2 N slope intercept R 2

Houston Ship Channel-area auto-GC monitors:
Cesar Chavez C1020/175 52 -0.019 * 2.74 0.09 52 -0.025 * 2.86 0.16
Channelview C15/C115 62 -0.017 * 3.85 0.22 62 -0.039 * 4.64 0.49
Clinton C403/C113/C304 60 -0.032 * 4.75 0.44 62 -0.018 * 3.85 0.36
Deer Park C35/139 54 -0.033 * 4.12 0.25 65 -0.026 * 4.09 0.22
HRM-3 Haden Road C603 56 -0.051 * 5.37 0.55 55 -0.026 * 3.82 0.42 Houston Milby Park A169 39 -0.011 1.88 0.06 39 -0.021 * 2.05 0.20 Lynchburg Ferry C1015 56 -0.029 * 3.41 0.24 56 -0.059 * 4.89 0.42
Wallisville Road C617 55 -0 .002 1.79 0.00 55 -0.017 * 2.08 0.17

Non-Houston Ship Channel-area auto-GC monitors: Mustang Bayou C619 53 -0.008 * 0.72 0.20 53 -0.006 * 0.83 0.13 Danciger C618 56 -0.003 0.57 0.05 56 -0.006 * 0.78 0.16
Lake Jackson C1016 50 -0. 006 1.00 0.05 50 -0.007 * 0.77 0.18 Texas City 34 th St. C620 59 -0.027 * 2.43 0.50 59 -0.020 * 2.19 0.37 *Significant at the 5 percent (0.05) level. Signi ficance levels for intercepts are not reported. Parameter estimates from ordinary least squares fits of monthly geometric mean concentrations of ethylene and propylene on an index of month, by monitoring site and compound.

5.3.7 Geographic Patterns in Ambient HRVO C Concentrations Near the Houston Ship
Channel The next analysis showed that, for some HRVOC, geographic patterns are apparent. Wind speed and wind direction measurements, collected in tandem with HRVOC concentrations at the Houston Ship Channel auto-GC monitors, were us ed not only to identify these patterns, but to track their changes over time. Radar plots of ge ometric mean concentrations of ethylene and propylene, by wind direction, were plotted, superimposed on maps of the Houston Ship Channel, and displayed in Figure 5-24: Geometric Mean Ethylene Concentr ation at Western Houston Ship
Channel Monitors through Figure 5-27: Geometric Mean Propylene Concentration at Western Houston Ship Channel Monitors

.

These plots consist of jagged rings encircling a m onitor. Each ring around a particular monitor represents the geometric mean concentration of the subject HRVOC at each of the 360 degrees surrounding the monitor, for a particular year. The distance from the origin to any point on the ring is proportional to the concentration of HRVO C arriving at the monitor from that direction. For example, Figure 5-25: Geometric Mean Ethylene Concentrations at Eastern Houston Ship
Channel Monitors shows that in 2003 at Deer Park (CAMS 35/139), the highest mean ethylene concentration, 16 ppbC, occurred when winds we re blowing from the northeast, suggesting there may be large ethylene emissions sources upwind of Deer Park (CAMS 35/139) in that direction.

To help interpret these graphs, it is useful to d escribe a couple of hypothetical scenarios. In the first one, if HRVOC did not vary when winds a rrived from different directions, i.e., the same concentrations were observed regardless of the wi nd direction, the ring would be a smooth circle.

### 5-51 Conversely, in the second scenario, if HRVOC we re detected only when winds arrived from a single direction, the ring would simply be an elongated spike pointing in that direction.

In Figures 5-24: Geometric Mean Ethylene Concentrati on at Western Houston Ship Channel

Monitors through 5-27: Geometric Mean Propylene Concentr ation at Western Houston Ship
Channel Monitors , for the Houston Ship Channel monitors , a strong directional association with mean concentration is typical. The directional spikes seen in these rings are referred to as “lobes”

in this section.

Figure 5-24: Geometric Mean Ethylene Concentration at Western Houston Ship Channel
Monitors

Sources of ethylene (blue circles) and propylene (b rown circles) are also depicted on the map of the respective compound, with sizes proportional to values reported in the 2006 TCEQ point source emissions inventory. Valid hourly measurements from 2002 through 2008 were used; hours with hourly wind speed measurements less th an two miles per hour (mph) were discarded,

due to considerable error in wind dir ection measurements at low wind speeds.

While a compound’s concentration for a particular wind direction at a particular monitor is proportional to the distance from the monitor to the ring at that direction, the scale differs across monitors. For example, peak 2003 ethylene concentration (see Figure 5-25: Geometric Mean Ethylene Concentrations at East ern Houston Ship Channel Monitors ) at Lynchburg Ferry (CAMS 1015) is 24 ppbC, and 15 ppbC at Wallisville Road (CAMS 617), yet the length from each monitor to its respective peak (tip of sharp “point”) is approximately the same. For this reason, peak concentration at each mon itor, for each pollutant, is labeled.

### 5-52 Figure 5-25: Geometric Mean Ethylene Concentrations at Eastern Houston Ship Channel
Monitors

Figure 5-24: Geometric Mean Ethylene Concentrati on at Western Houston Ship Channel

Monitors shows mean ethylene concentrations at th e three western-most Houston Ship Channel auto-GC monitors. Sources of ethylene having the greatest impact on these monitors are all located east of the monitors, because the greatest peaks for each monitor point in this direction for all the years. The plot also shows trends across time at each monitor. At Clinton (CAMS 403/CAMS 113/CAMS 304), peak ethylene occurre d in 2003 from almost due east, as seen in the lobe labeled “14 ppbC.” Followi ng 2003 and 2004, peak concentrations from that direction have been somewhat lower. Also, the lobes pointing south observed in 2003 and 2004 are markedly smaller in 2005 and subsequent years. An olefins production plant located in the Houston Milby Park (A169) area shut down in 2005; its emissions may have been responsible for those lobes.

The plot shows mean ethylene concentrati ons for the Cesar Chavez (CAMS 1020/175) and Houston Milby Park (A169) monitors, which star ted operation in 2004 and 2005, respectively. While these monitors measured peak concentrations in different years, both monitors have peaks pointing in the direction of the Houston Milby Park (A169) olefins plant while it was in operation; Houston Milby Park (A169) observed a large lobe to the southeast in 2005, and Cesar Chavez (CAMS 1020/175) observed a notable lobe to the north in 2004 and 2005. This provides a stronger indication, when combined with the Clinton (CAMS 403/CAMS 113/CAMS 304) peak to the south, of the influence of emissions from that plant on local concentrations.

Figure 5-25: Geometric Mean Ethylene Concentrati ons at Eastern Houston Ship Channel

Monitors shows mean ethylene concentrations at the fi ve auto-GC monitors located in the eastern part of the Houston Ship Channel. Variation in mean concentrations by direction is even more pronounced here than in the western portion of th e Houston Ship Channel. The pattern in mean concentrations at Lynchburg Ferry (CAMS 1015) suggests there is a large source of ethylene emissions south-southeast of the monitor, n ear Battleground Road and Highway 225, and that
emissions from this area have decreased.

### 5-53 Table 5-17: Geometric Mean Ethylene for Key Wind Direction Lobes at Eastern Houston Ship
Channel Monitors shows that this lobe’s mean 2003 con centration of 24.3 ppbC has halved in
recent years.

Table 5-17: Geometric Mean Ethylene for Key Wind Direction Lobes at Eastern Houston Ship Channel Monitors principal Monitor direction(s) 2003 2004 2005 2006 2007 2008 ppbC ppbC ppbC ppbC ppbC ppbC

lobes pointing to the same sources in th e central Houston Ship Channel area:

HRM 3 ESE 24.8 18.0 15.6 5.0 4.7 5.2
Channelview C15/C115 SW 8.9 8.9 5.6 4.3 3.6 4.1

lobes pointing to the same sources in the eastern Houston Ship Channel area:

Hous.DeerPrk2 C35/139 NE 16.6 missing 12.1 10.7 11.1 13.0 Lynchburg Ferry C1015 SSE 24.3 17.7 14.5 10.8 14.0 12.6
Channelview C15/C115 SE 12.5 11.9 6.6 6.9 7.1 6.8
Wallisville Road C617 SW 15.0 9.8 8.4 11.1 9.9 12.8

lobes pointing in other directions:

Channelview C15/C115 N 10.5 9.0 3.7 6.3 7.9 6.9
Wallisville Road C617 ENE 9.7 11.5 9.6 10.8 9.2 11.6 Annual maxima are noted in boldface type.

The pattern observed at Deer Park (CAMS 35/139) may provide additional evidence of suspected

emission decreases in the same source area. The northeast lobe in Table 5-17: Geometric Mean Ethylene for Key Wind Direction Lobes at Eastern Houston Ship Channel Monitors has dropped from a high of 16.6 ppbC in 2003 to a range of about 11 to 13 ppbC in recent years. Similarly, the southeast lobe at Channelview (CAMS 15/CA MS 115), which points yet again to the same source area, peaked at 12.5 ppbC in 2003, dro pped to 11.9 ppbC in 2004, and has not exceeded 7.1 ppbC since. While this monitor is farthe r from this source region than are the other two monitors, and therefore is more likely to be im pacted by other emissions sources, consistent

decreases observed at these three monitors across the six-year span of available data suggest ethylene emissions have decreased in the subject source region.

HRM-3 Haden Road (CAMS 603) shows a peak of 24. 8 ppbC to the southeast in 2003, which fell to 18 ppbC in 2004, then further to 15.6 ppbC in 2005. The mean concentration has dropped since then, not exceeding 5.2 ppbC. The ma gnitude of the decrease over 2006 to 2008, as compared to 2005 and earlier years, suggests a shut down of one or more major process units, or even entire plants, somewhere southeast of this monitor, or implementation of HRVOC rules.

Peaks at the Wallisville Road (CAMS 617) monitor point southwest, toward the east Houston Ship Channel, and east-northeast, in the direction of the Mont Belvieu industrial area, where there is considerable ethylene and propylene stor age in underground salt caverns. Table 5-17: Geometric Mean Ethylene for Key Wind Directi on Lobes at Eastern Houston Ship Channel

Monitors shows that ethylene originating to the so uthwest decreased from the six-year peak in 2003 (15 ppbC), to a range from 9.9 to 11.1 ppbC, befo re rising slightly to 12.8 ppbC in 2008. In contrast, the east-northeast lobe at this monito r shows relatively unvarying mean concentrations

### 5-54 across the entire six-year period, ranging from 9.2 to 11.6 ppbC, with the six-year peak occurring

in 2008.

These conclusions for five monitors and eight dir ectional lobes show a nearly consistent pattern across these monitors. Seven of eight lobes witness ed their highest mean concentration in 2003. Within one or two years of this peak, concentrations at all seven had dropped, from 27 to 65 percent, and have leveled off since; mean con centrations have not varied appreciably from 2006 to 2008. These findings suggest ethylene emissions from source areas close to these monitors, especially Battleground Road, Highway 225 in La Port e, and the petrochemical complex north of the Channelview (CAMS 15/CAMS 115) monitor, ha ve decreased considerably in recent years. These observations suggest that the new TCEQ regulations specifically targeting HRVOC emissions and requiring full compliance by 2006 are proving effective in controlling point source HRVOC emissions. However, the trends shown he re have not been corrected for meteorological

variations.

Results for the lobe pointing east-northeast from the Wallisville Road (CAMS 617) monitor disagree with some key findings at other lob es. The Wallisville Road (CAMS 617) east-northeast lobe, unique among the eight, experienced an increase in mean concentration from 2003 (9.7 ppbC) to 2004 (11.5 ppbC). While 2006 to 2008 me an concentrations at Wallisville Road (CAMS 617), like those of other monitors and lobes, changed relatively little, mean concentrations of the east-northeast Wallisville Road (CAMS 617) lobe changed relatively little across the entire sixyear period. The absence of recen t decreases at this lobe compared to earlier years suggests that meteorology may not have caused high concentrations seen at most other lobes in earlier years.

Figure 5-26: Geometric Mean Propylene Concentra tion at Eastern Houston Ship Channel

Monitors displays monthly geometric mean concentra tions of propylene in the same area of the eastern Houston Ship Channel. Table 5-18: Geometric Mean Propylene Concentrations for Key Wind Directions at Eastern Houston Ship Channel Monitors lists mean propylene concentrations across the study period, for each monitor and lobe. Similarities with ethylene are evident. For propylene, all seven lobes measured their highest concentrations in 2003 or 2004; five of the
seven had their two lowest annual concentra tions in 2007 and 2008. All seven lobes had

concentrations in 2007 and 2008 that were 40 percent or more lower than their respective six-year peaks.

### 5-55 Figure 5-26: Geometric Mean Propylene Concentration at Eastern Houston Ship Channel
Monitors

These results suggest that the propylene emissions in the source regions near the monitors have dropped considerably in the six-year study pe riod, and that the HRVOC regulations may be responsible for the decreases. As seen with ethylene, patterns in geometric mean propylene

concentrations at the east-northeast Wallisville Road (CAMS 617) lobe differed considerably from the other seven. Propylene concentrations va ried relatively little across the six-year period, suggesting that, like ethylene, Mont Belvieu propyl ene emissions have changed little or not at all, on average, across the study period.

Figure 5-27: Geometric Mean Propylene Concentratio n at Western Houston Ship Channel

Monitors shows mean propylene concentrations by wind direction at the three western Houston Ship Channel monitors. Patterns depicted here exhibit strong similarities to those seen with ethylene in this area: the largest propylene source areas are to the east, and judging from the disappearance of strong peaks from 2006 onward, emissions from the now-defunct olefins plant located in the Houston Milby Park (A169) area were probably affecting these monitors.

### 5-56 Figure 5-27: Geometric Mean Propylene Concentration at Western Houston Ship Channel
Monitors

Table 5-18: Geometric Mean Propylene Concentrations for Key Wind Directions at Eastern Houston Ship Channel Monitors lists mean propylene concentrations across the study period, for

each monitor and lobe.

Table 5-18: Geometric Mean Propylene Concentrations for Key Wind Directions at Eastern Houston Ship Channel Monitors principal Monitor direction(s) 2003 2004 2005 2006 2007 2008 ppbC ppbC ppbC ppbC ppbC ppbC

lobes pointing to the same source in the eastern Houston Ship Channel area:

HRM-3 Haden Road C603 SE 17.1 20.5 15.2 12.4 7.8 7.0
Hous.DeerPrk2 C35/139 NE 50.0 30.3 25.4 21.2 19.6 18.6 Lynchburg Ferry C1015 S 82.8 75.4 51.5 46.2 31.5 26.3
Channelview C15/C115 SE 30.1 19.0 11.7 13.8 11.7 8.2

Wallisville Road C617 SW 35.6 27.3 22.3 18.4 14.5 21.3

lobes pointing to other sources:

Lynchburg Ferry C1015 SW 68.7 33.9 13.7 18.8 9.9 6.8
Channelview C15/C115 N 11.3 7.7 3.0 5.5 8.1 5.2
Wallisville Road C617 ENE 9.0 12.2 9.7 12.3 9.7 11.2 Annual maxima are noted in boldface type.

### 5-57 5.3.8 Ambient Total VOC Concentrations Considerable research has focused on patterns and trends in HRVOC concentrations in the HGB area (Hafner Main et al. 2001; Brown and Hafn er Main, 2002; Jolly et al., 2003; Fang and McDowell, 2003). Less examined are patterns fo r other, less-reactive VOC. This section presents a detailed examination of patterns in to tal VOC concentrations in the HGB area, using concentrations of total nonmethane hydrocarbons (TNMHC) as a measure of total VOC. Each TNMHC measurement corresponds to the sum of all chromatogram peaks (identified and unidentified) from the start to the end of sample collection. TNMHC is a useful measure of total

VOC because it has been calculated in a consis tent manner over the entire study period, unlike other parameters, such as the sum of Photoche mical Assessment Monitoring Stations (PAMS) target compounds, whose constituents have changed periodically.

Similar to the first HRVOC analysis presented in this section, geometric mean TNMHC concentrations, by monitor, year, and month, were calculated for valid months for all availabledata from each of the 12 HGB monitors. Further analysis of the four non-Houston Ship Channelarea monitors has not been completed at this time.

Figure 5-28: Monthly Geometric Mean TNMHC Con centrations, July 1995 through December

2008 shows, for each of the eight Houston Ship Channel monitors, monthly geometric mean TNMHC concentration for all months with comple te data, between the start of monitoring and December 2008. Monitors are sorted according to their location from west (top) to east (bottom); the grey bars denote the 25th through 75th per centile concentrations (85 ppbC and 149 ppbC respectively) of all valid months across all monitors.

As with ethylene and propylene, the two m onitors with data before 2001, Clinton (CAMS 403/CAMS 113/CAMS 304) and Deer Park (CAM S 35/139), recorded their highest monthly geometric mean values before 2001. Both m onitors exhibited overall decreases across their respective data collection periods. A statistical an alysis of possible trends, using ordinary least squares regression, is presented in Table 5-19: Parameter Estimates of Monthly Geometric Mean TNMHC Concentration Trends Houston Ship Channel Area Auto-GC Monitors . This statistical

model indicates that all 12 monitors had d ecreasing monthly mean concentrations, from the beginning to the end of each monitor’s respective data range. As well, this model indicates that eight of the 12 monitors’ decreases were statisti cally significant at the 95 percent confidence

level.

### 5-58 Figure 5-28: Monthly Geometric Mean TNMHC Concentrations, July 1995 through
December 2008

### 5-59 Table 5-19: Parameter Estimates of Monthly Geometric Mean TNMHC Concentration Trends Houston Ship Channel Area Auto-GC Monitors

Sitename Slope of

Trend Intercept Degrees of

Freedom R squared

Cesar Chavez C1020/175 -0.61 132 47 0.07
Channelview C15/C115 -0.37* 153 49 0.10
Clinton C403/C113/C304 -0.63* 225 78 0.46
Hous.DeerPrk2 C35/139 -0.55* 148 80 0.31 Houston Milby Park A169 -0.33 99 33 0.03
HRM-3 Haden Road
C603 -1.22* 173 47 0.52 Lynchburg Ferry C1015 -1.14* 156 47 0.27
Wallisville Road C617 -0.31* 79 49 0.11

Non-Houston Ship Channel-area auto-GC monitors

Sitename Slope of

Trend Intercept Degrees of

Freedom R squared Danciger C618 -0.22* 44 47 0.12

Lake Jackson C1016 -0.18 34 43 0.04 Mustang Bayou C619 -0.11 61 43 0.01 Texas City 34 th St. C620 -0.95* 102 57 0.46 *Significant at the 5 percent (0.05) level. Significance levels for intercepts are not reported. Parameter estimates from ordinary least squares fits of monthly geometric mean concentrations of TNMHC on an index of month, by monitoring site.

Figure 5-29: 90 th Percentile TNMHC Concentr ation in the HGB Area presents 90 th percentile

TNMHC concentrations at each auto -GC monitor. The area-wide 90 th percentile TNMHC
concentrations and the 90 th percentile TNMHC at most of the individual monitors are decreasing.

Smaller decreases are evident at Wallisville Road (CAMS 617), Channelview (CAMS 15/CAMS 115), Lake Jackson (CAMS 1016), Mustang Ba you (CAMS 619), and Danciger (CAMS 618), while larger decreases are observed primarily at m onitors closer to the Houston Ship Channel. Monitors in Brazoria County (Danciger (CAMS 618), Lake Jackson (CAMS 1016), and Mustang Bayou (CAMS 619)) and Galveston County (Texas City 34 th St. (CAMS 620)) tend to report
lower 90 th percentile TNMHC than monitors located in Harris County. In the past, Clinton (CAMS 403/CAMS 113/CAMS 304) has recorded the highest TNMHC concentrations, but since

2006 Clinton has decreased at a faster rate and Channelview (CAMS 15/CAMS 115) has recorded the highest concentrations.

### 5-60 90 th Percentile TNMHC Concentration in the HGB Area

0 100 200 300 400 500 600 700

1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 Concentration (ppb C )

Mustang
Milby Park

HRM-3

Cesar Chavez Clinton

Channelview

Deer Park Lynchburg

Danci g er Lake Jackson Texas City Wallisville

Figure 5-29: 90 th Percentile TNMHC Concentration in the HGB Area

5.3.9 Meteorologically Adjusted Ozone Trends Ozone formation is dependent not only on its precursors (NO X and VOC), but also on meteorological variables. While trends in oz one design values have been decreasing, design

value trends must be examined to determine if the values are decreasing due to emission controls or if they are decreasing simply because of me teorological conditions in the area in the past several years. To determine whether control strategies have been effective, meteorological
influences must be removed from ozone trends. Analysis done by Sullivan (2009) used a generalized linear model to account for meteorol ogical influences in ozone trends. The following discussion is based upon Sullivan (2009), who used a modified version of the Camalier et al. (2007) technique for removing the meteorol ogical influences from the ozone trends.

Before meteorological influences can be remove d from ozone trends, the meteorological factors that are most important to ozone formation must first be identified. Various correlations and factor analyses were used to identify the most important meteorological variables for ozone formation in the HGB area. Data from the Omnibus Meteorological Database (METDAT) maintained by the EPA was compared to ozone da ta obtained from surface monitors in the HGB
area. Because the set of observed ozone levels can be influenced by the number of monitors in an area, Sullivan (2009) used a consistent set of ozone monitors in the HGB area. These monitors

are listed in Table 5-20: Area Ozone Monitoring Sites with Long-Term Data . Most contain a
consistent set of data from 1990 to 2007. Data from monitors that were moved a short distance during the period from 1990 to 2007 were combined with data from monitors in nearby locations, for example, data at Clute (CAMS 11) were combined with data from Lake Jackson (CAMS 1016).

### 5-61 Table 5-20: Area Ozone Monitoring Sites with Long-Term Data

AQS Number Site Name

482011039 Hous.DeerPrk2 C35/139

482011035 Clinton C403/C113/C304

482011034 Houston East C1

482010075 Houston Texas Avenue C411

482010062 Houston Monroe C406

482010051 Houston Croquet C409

482010047 Lang C408

482010046 Houston North Wayside C405

482010029 Northwest Harris Co. C26/A110/C154

482010024 Houston Aldine C8/AF108/X150

480391016 Lake Jackson C1016 (and Clute C11)
Source: Sullivan, 2009.

Figure 5-30: Actual Mean Eight-Hour Ozone Concentrations (Blue Line) and Mean Eight-Hour
Predicted Concentrations with the Non- Meteorological Trend Removed (Red Line) , which was reproduced from Sullivan (2009), displays two time series. The values in blue represent the observed mean daily maximum eight-hour ozone c oncentrations; values in red represent the daily peak ozone based purely on the meteorological variations, with the non-meteorological factors removed. In other words, the statistical model described above has been used to re-create the ozone time series with only the meteorology taken into account.

For 2006 and 2007, the statistical model predicts that the observed mean daily peak eight-hour ozone should have been higher than observed, based upon the conduciveness of the meteorology toward ozone formation. In other words, based on the weather, ozone con centrations should have been higher in 2006 and 2007. Subtracti ng the meteorologically-based eight-hour ozone estimates from the actual eight-hour ozone results in a trend with the meteorological effects removed (Figure 5-31: Residual Meteorologically Adjusted Eight-Hour Ozone Concentrations

Trend ). This trend represents how the sum of anthropogenic factors, model error, and undiagnosed meteorological factors have changed from 1996 to 2007. Figure 5-31: Residual Meteorologically Adjusted Eight-H our Ozone Concentrations Trend , which was reproduced from Sullivan et al., 2009, represents the trend in peak daily maximum ozone with the meteorological factors removed. The meteorologically-adjusted ozone trend is clearly downward. Since the meteorological variations have been removed, this downward trend shows the effect of emission reductions in the HGB area. Statistical results of this analysis are listed in Table 5-21: Summary Statistics for Meteorologically Adjusted Ozone Trends from 1996 to 2007 . The slope of -0.86 shows that eight-hour ozone trends in the HGB ar ea are decreasing and that they are significant (p-value = 0.00).

### 5-62Figure 5-30: Actual Mean Eight-Hour Ozone Concentrations (Blue Line) and Mean EightHour Predicted Concentrations with the No n-Meteorological Trend Removed (Red Line)

Figure 5-31: Residual Meteorologically Adjusted Eight-Hour Ozone Concentrations Trend

### 5-63 Table 5-21: Summary Statistics for Meteorol ogically Adjusted Ozone Trends from 1996 to

2007

Parameter Value Intercept 6.438 Slope -0.86 *

t-statistic -4.20 p-value 0.00 Lag 1 Coefficient -0.20

t-statistic -0.63 * Value is statistically significant. (Sullivan et al., 2009)

The analysis from Sullivan (2009) shows that, afte r adjusting for meteorology, concentrations of ozone has declined substantially in the HGB area . All else held equal, daily maximum eight-hour
ozone concentrations in the HGB area should be around 9 ppb lower in 2007 compared to 1996.

5.3.10 Background Ozone Concentrations: Transport of Ozone into the HGB Area Estimating the levels of ozone transported into th e HGB area is important in order to identify so that the amount of locally produced ozone. Seve ral researchers have previously investigated the background ozone concentrations in Texas and the tr ansport winds that are associated with them. Nielsen-Gammon et al. (2005) investigated background ozone from 1998-2003 in the HGB area and obtained the following insights (paraphrased from Nielsen-Gammon et al., 2005):

• The seasonal variability in eight-hour maximum ozone in eastern Texas is primarily associated with background ozone. Local c ontributions tend to be highest during the summer when background ozone reaches a minimum.

• The late spring peak in eight-hour maximum ozone in eastern Texas is primarily associated with “tropospheric background” ozone. This ozone maximum has been

observed at rural sites elsewhere and is associated with variations in the lifetime of ozone, the concentrations of NOx, and enhanced transport from the stratosphere.

• The midsummer minimum in background ozone in eastern Texas leads to a minimum in eight-hour peak ozone that is strongest in southeastern Texas and barely noticeable in northeastern Texas. The primary cause of the summertime minimum is a decline in the tropospheric background ozone. Although the relatively clean southerly flow is weakening during this period, most air pa rcel paths remain maritime in nature.

• When easterly and northeasterly winds b ecome more frequent in late summer, background ozone and total ozone in eastern Texas begin rising. Winds are also less steady than in the middle of summer, so continental transport becomes increasingly frequent.

Langford et al. (2009) showed that the techniques used by Nielsen-Gammon et al. (2005) yielded results consistent with a different technique of estimating background, except on some occasions when the Galveston Airport (CAMS 34/CAMS 109/CAMS 154) site was chosen as the background site. Langford et al. showed that the Galveston site is the site most strongly affected by the Gulf breeze, and that on some days, th e maritime air from the Gulf does not affect the Houston area, even though this air affects Galv eston. Hardesty et al. (2007) have shown that during the TexAQS II study in August throug h September 2006, background ozone in southeast Texas averaged about 50 ppb, with background con centrations lower near the coast, and higher in northeast Texas. On one day, September 8, 20 06, the background ozone entering Texas from east was 85-90 ppb. The results of these studies have shown that bac kground ozone entering southeast Texas can have a large effect on the to tal observed eight-hour ozone concentrations. To investigate the role of background ozone for th e most recent years, the TCEQ commissioned a study of background ozone and its relationship to larger-scale wind patterns. Below is a description of this work.

### 5-64 Sullivan (2009) used 72-hour back trajectories calculated with the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) algorithm, using data from the Ecosystem Dynamics and the Atmosphere Section (EDAS) meteorological model to estimate the amount of ozone entering into the HGB area. A total of 1,456 backward trajectories were run starting at 12:00 Central Standard Time in central Houston, at 300 meters above gr ound level, during the peak of ozone season in the HGB area (May 1 through October 31, 2000 to 2007). Analysis of multiple trajectories can distinguish between source areas, or paths, that lead to higher than average, or lower than average ozone concen trations (Sullivan et al., 2009). A clustering algorithm was used to group multiple trajectori es based on trajectory size and shape. Six identified clusters appear in Figure 5-32: Six Clusters Found Using HYSPLIT Backward Trajectory Clustering Algorithm , which was reproduced from Sullivan, 2009. Forty backward trajectories that did not end up in any of the six clusters, illustrated in Figure 5-33: Cluster 0 Backward Trajectories , reproduced from Sullivan (2009), were grouped and assigned a cluster number of zero. All but one of the back trajector ies in cluster zero originate from the south and that these trajectories appear to extend beyond the EDAS modeling domain, which is the only

difference between cluster zero and cluster two.5-65Figure 5-32: Six Clusters Found Using HYSPLITBackward Trajectory Clustering Algorithmz<D(j)(\JcoCluster1of6-Standard217backwardtrajectoriesendingatvarioustimesEDASMeteorologicalDataCluster4of6 -Standard314backwardtrajectoriesendingatvarioustimesEDASMeteorologicalData:J0(/)Cluster2of6 -Standard512backwardtrajectoriesendingatvarioustimesEDASMeteorologicalData·f················.f....Cluster5of6-Standard167backwardtrajectoriesendingatvarioustimesEDASMeteorologicalDatazCluster3of6-Standard49backwardtrajectoriesendingatvarious timesEDASMeteorologicalDataCluster6of6-Standard157backwardtrajectoriesendingatvarioustimesEDASMeteorologicalData<D1::'--..;---l1"-oi(\Jco

### 5-66 Figure 5-32 : Six Clusters Found Using HYSPLIT Backward Trajectory Clustering Algorithm shows that cluster one and cluster two represent da ys in which winds originated from the Gulf of Mexico; these trajectories typically represent clean er air coming from the Gulf of Mexico and
hence lower observed ozone concentrations in the HGB area. Cluster three represents long trajectories, which come into the HGB area from th e north as far away as Canada. This type of trajectory can also bring clean air from northern states and Canada into the HGB area. Cluster four represents stagnant air conditions, a frequent cause of ozone accumulation. Cluster five shows trajectories that originate from the northeast, in the Ohio River Valley, that bring polluted air from more populated areas into the HGB area. Cluster six illustrates trajectories from the east,
some of which cross over Louisiana and the B eaumont-Port Arthur (BPA) area and some of

which cross over the Gulf of Mexico. The mean ce nterline from each of the six clusters is shown in Figure 5-34: Means of Six 60-Hour Backward Trajectory Clusters . Trajectories were compared to ozone concentrations in the HGB area to quantify how these trajectories are related

to ozone in the HGB area.

Figure 5-33: Cluster 0 Backward Trajectories

### 5-67 Figure 5-34: Means of Six 60-Hour Backward Trajectory Clusters

Twelve ozone sites, shown in Figure 5-35: Sites Used in Ozone Area Maximum and Background

Determination , that had near continuous operation from 2000 to 2007 in the HGB area were selected to compare with trajectory clusters. In an effort to use measurements from a consistent, long-term set of monitors, data from sites that were shut down were combined with data from sites that began collecting data near the sites th at were taken off-line. Sites where data were combined are Lake Jackson (CAMS 1016) and Clute (CAMS 11), and Galveston Airport (CAMS 34/CAMS 109/CAMS 154) and Galveston Airport 99 th St. (CAMS 1034). Sites were selected based on locations as either a site upwind or downwind of the HGB area. Northwest Harris County (CAMS 26), the Lake Jackson (CAMS 1016) / Clute (CAMS 11) combined site pair, and the Galveston Airport (CAMS 34/CAMS 109/CAMS 154)/ Galveston 99 th St. (CAMS 1034) combined site pair generally represent sites me asuring background ozone concentrations. Sites

on the downwind side of downtown Houston and the Houston Ship Cha nnel generally represent sites measuring maximum ozone concentrations in the HGB area. Maximum peak and minimum peak eight-hour ozone concentrations from the tw elve monitors were found for each day, then merged with the cluster classification from each day. Following Nielson-Gammon et al. (2005), that minimum peak eight-hour average ozone concentration was used to represent the “background” ozone level in the HGB Area.

### 5-68 Figure 5-35: Sites Used in Ozone Area Maximum and Background Determination

Table 5-22: Ozone Statistics for HYSPLIT Back Trajectory Clusters summarizes average maximum and average minimum, or background, oz one concentrations for each cluster. Average maximum peak daily eight-hour ozone among th e clusters ranges from 40.6 ppb to 73.3 ppb, while average minimum peak daily eight-hour ozone, considered a proxy for background ozone concentrations, ranges from 21.4 ppb to 45.1 ppb. The difference between these two means can be used as a surrogate for locally produced ozone . Cluster four and cluster five, which represent the short fetch and the northeast fetch, have th e highest average maximum ozone concentrations, 71.6 ppb and 73.3 ppb, respectively, and the highest average background, 40.8 ppb and 45.1 ppb. These two clusters also exhibit some of the larg est average differences or local contributions. Cluster zero, the far southeast cluster, cluster one , the east southeast cluster, and cluster two, the southeast cluster, exhibited some of the lo west average background and average peak ozone; these clusters are expected to have a lower bac kground ozone due to their origins over the Gulf of

Mexico.

### 5-69 Table 5-22: Ozone Statistics for HYSPLIT Back Trajectory Clusters Average Average Average Number maximum minimum difference, of back peak daily peak daily minimum trajec- eight-hour eight-hour and maximum

Cluster Fetch tories ozone ozone ozone *
# ppb ppb ppb

5 NE 166 73.3 45.1 28.1
4 Short 312 71.6 40.8 30.8

6 East 151 61.1 35.6 25.5
3 North 49 59.1 37.2 21.9

2 SE 506 48.5 24.8 23.7
0 far SE 40 45.0 23.8 21.1

1 ESE 217 40.6 21.4 19.1

* May not sum due to rounding. Note: Data is May through October, 2000 to 2007. Fetch represents the main direction of the cluster, c ount is the number of back trajectories in each cluster, average minimum peak daily eight-h our ozone is taken as the background ozone concentration. Clusters are sorted in descending order by average maximum peak daily eight-hour

ozone.

The 95 percent confidence intervals for the mean eight-hour ozone maximum for each cluster are

shown in Table 5-23: Average Maximum Ozone and 95 Percent Confidence Intervals . Two
standard errors were used for the confidence inte rvals in each row. The confidence intervals in

the table show that differences between means are statistically significant for most of the pairwise comparison. This is shown graphically in Figure 5-36: Average Maximum Ozone and 95 Percent Confidence Intervals

. Fetches originating from the northeast and east, as well as the “short” fetch, have the highest average peak dail y ozone values, and they are tightly clustered. Clusters originating from the north and far south east have noticeably wider confidence intervals, indicating more variability, but with lower averag e peak daily ozone concentrations than the

northeast and east clusters.

Table 5-23: Average Maximum Ozone and 95 Percent Confidence Intervals Average Average Average
Cluster maximum maximum maximum ranked by peak daily + 2 - 2 maximum eight-hour standard standard average Fetch Count ozone errors errors # ppb ppb ppb

5 NE 166 73.3 76.7 69.8
4 Short 312 71.6 74.3 68.9

6 East 151 61.1 64.5 57.8
3 North 49 59.1 65.2 53.0

2 SE 506 48.5 50.3 46.6
0 far SE 40 45.0 51.5 38.4

1 ESE 217 40.6 42.7 38.5
Note: Confidence intervals were c onstructed using two standard erro rs. Clusters are sorted in descending order by average maximum peak daily eight-hour ozone. Confidence intervals for differences between the area ozone maximums gene rally do not overlap beyond one or two rows.

Although many of the selected sites were inte nded to represent background and maximum ozone in the HGB area, note that on many days true background ozone concentra tions may be observed

### 5-70 farther away, in more rural areas, and the tr ue maximum ozone concentration may also be underestimated. Despite uncertainty in estim ates of true background and maximum ozone concentrations, the large number of observations used in this analysis, as well as evidence presented earlier, provide clear evidence that ozone in the HGB area is affected by transport of

ozone from external sources.



### 0 20 40 60 80

NE Short East North SE far SE ESE ppb

average maximum peak ozone upper bound of 95% confidence interval

lower bound of 95% confidence interval

Figure 5-36: Average Maximum Ozone and 95 Percent Confidence Intervals

Figure 5-37 : Relationship Between Minimum and Maximum Ozone Concentrations , recreated from Sullivan (2009), shows there is a significant linear relationship between mean HGB area minimum and maximum eight-hour average ozone con centrations by trajectory cluster (p-value < 0.01). The dark red points and estimated regr ession line represent the relationship between mean maximum ozone and mean minimum (background) oz one concentrations by cluster. The olive points and estimated regression line represent the relationship between “local contribution” (difference between maximum and minimum) a nd mean minimum ozone concentrations by cluster. The relationship between maximum and minimum ozone by cluster suggests that trajectory direction is a factor determining severity of both HGB area maximum and background ozone concentrations (Sullivan, 2009) . The estimated slope parameter ( β = 1.36) of the ordinary least squares regression of average minimum ozone concentration against average maximum ozone concentration shows that maximum ozone concentration increases at a greater rate with trajectory direction when compared to minimum ozone.

### 5-71 

## O 3max 

### = 1.36 

## O 3min 

### + 12.76

R 2 = 0.96



## O 3(max-min) 

### = 0.36 

## O 3min 

### + 12.67

R 2 = 0.65



### 10 30 50 70

10 30 50 70 1 0 2 3 4 5

6 ppb

ppb ESE far SE SE north short NE

east

Figure 5-37: Relationship Between Minimum and Maximum Ozone Concentrations

Figure 5-37: Relationship Between Minimum and Maximum Ozone Concentrations also shows

that the difference between mean HGB area maximu m and minimum ozone conc entrations is also roughly linear with area minimum, but with a lower slope ( β =0.36) and lesser statistical significance (p-value=0.03) (Sullivan, 2009). The linear relationship between the difference and mean HGB area minimum ozone suggests the transport direction also affects local ozone production. The slower air movement of cluster f our, which is the “short” cluster, allows greater

accumulation in the area under lower local surface wind speeds. Winds originating from the directions of cluster six, the “east” cluster, and cluster five, the “northeast” cluster, help to move surface air along the area around the Houston Ship Channel and across the downtown Houston area, which, as noted, contain large amounts of ozon e precursors. Overall, this analysis shows that directions of back trajectories can account for up to 24 ppb of variation in background ozone concentrations, and up to 35 ppb of variation in maximum ozone concentrations.

5.3.11 Transport and Surface Wind Trajectories While still incomplete, a preliminary analysis of u pper level, or transport, wind trajectories was

conducted to confirm and extend findings from the previously discussed directional analysis. Additional HYSPLIT modeling of 48-hour back tr ajectories at 1,500 meters altitude for May through August, 2000 to 2008, was used to detect difference in trajectori es across years that may

have influenced ozone concentrations in the HGB area.

A simple visual inspection of the densities of distributions of trajectory end points presented in Figure 5-38: Distributions of End Points from HYSPLIT 48-Hour Back Trajectories shows that upper level wind patterns for 2008, a year which ha d relatively low ozone concentrations, do not noticeably differ from patterns in other years. Of the years analyzed, the pattern for 2000, a year with relatively high levels of ozone, is perhaps the most similar to 2008. The spatial distribution is similar among years and wind speeds are also similar. Higher wind speeds are evident in 2004 and 2005, as implied by trajectories with longer fetc hes. The implication is that the wind patterns

### 5-72 observed during 2008 were not responsible for th e lower ozone concentrations observed, since high ozone was observed during other years that had wind patterns similar to 2008.

Figure 5-38: Distributions of End Points from HYSPLIT 48-Hour Back Trajectories

5.3.12 Background Ozone in Texas Research on the meteorology of the HGB area has found that the highest background ozone transported into the HGB area predominately originates from the north and northeast (NielsonGammon et al., 2005). In the present analysis , two techniques are used to examine background
ozone concentrations in Texas since 2000. Th e first technique examines the trend in ozone

concentrations at four sites that can be consid ered background sites under certain flow conditions. The second technique examines ozone concentrations associated with different patterns of longterm backward trajectories.

Identifying appropriate backgroun d ozone monitoring sites from which to ascertain trends is complicated by local ozone, complex wind patte rns, and natural variability in background ozone itself. To estimate background ozone, Nielson- Gammon et al. evaluated all monitors in the region to identify those that could be considered to be recording background ozone values. They proposed a modification of a TCEQ procedure to identify such sites.

The TCEQ procedure involves determining the dir ection of transport winds, then selecting a rural monitor upwind of the area in that direction. Nielson-Gammon et al. simply select as the background value the lowest of the peak eight-h our ozone values from all monitors. Unlike the

### 5-73 Nielson-Gammon procedure, which used gridded out put of a meteorological model, this analysis follows the TCEQ approach using direct measu rements of surface winds and tracking background ozone concentrations over time at selected monitors. Modifying the Nielson-Gammon procedure, the approach presented here identifies the 90 th percentile values recorded at the selected monitors and examines the distribution of daily maximum ozone concentrations ove r time to determine whether these supposed background concentrati ons have increased or decreased. Both the Nielson-Gammon method and the TCEQ method may not strictly estimate background ozone, as defined above, because they do not remove any pot ential recirculation of pollutants generated via local emissions. Also, background ozone alone may not tell the complete story, since ozone precursors, which can react with each other and w ith local emissions to produce ozone, may also be present in transported air.

Four candidate monitors were selected for th is analysis and are listed in Table 5-24: Monitors Selected for Background Transport Analysis . Two monitors, West Orange (CAMS 9) and Mauriceville (CAMS 642/CAMS 311/CAMS 665), are located east of the HGB area, adjacent to the Texas-Louisiana border, east of the BPA area; one, Karnack (CAMS 85), is located in northeast Texas near the Texas-Louisiana-Arkansas border and the Tyler-Longview-Marshall (TLM) area; and one, Hamshire (CAMS 64/CAMS 654), is located east of the HGB area,

between the HGB area and the BPA area. Each of these monitors was selected for specific purposes. West Orange (CAMS 9) and Mauriceville (CAMS 642/CAMS 311/CAMS 665) were chosen because they are as close as possible to the Texas border and, thus, are useful for isolating background ozone being transported into the state from the east. Karnack (CAMS 85), in northeast Texas, is also very near the Texas borde r, and was selected to provide an assessment of background ozone transport from more northerly regions. The final site, Hamshire (CAMS 64/CAMS 654), was selected to aid stratification of background ozone being transported into the HGB area into a component originating outside the state, and a component contributed by the

BPA area.

Table 5-24: Monitors Selected for Background Transport Analysis

Monitor metro area location years CAMS code West Orange BPA TX-LA border 2000-2008 C9/A141

Mauriceville BPA TX-LA border 2000-2008 C642/C311/C665

Karnack TLM TX-LA-AR border 2001-2008 C85/AFHP303

Hamshire HGB between BPA and HGB 2000-2008 C64/C654 Source: TCEQ/LEADS database. Data with wind speeds less than 3 miles per hour were excluded to minimize influences from periods of stagnation which may result in over estimation of background concentrations.

To isolate ozone being transported into the stat e, measurements at the selected monitors were restricted by wind direction. The West Orange (CAMS 9) monitor is located less than 3 miles

from the Louisiana border but is near several indus trial sites. Only ozone measurements taken when winds originated from directions ranging from 30° to 90° (Figure 5-39: Mauriceville C642/C311/C665) and West Orange (C9) Monitors ) were considered, to minimize possible influence from these sources. Thirty degrees corresponds to a north-northeast direction and 90 o is due east. The Mauriceville (CAMS 642/CAMS 311 /CAMS 665) monitor is located ten miles from the Louisiana border, north of the West Ora nge (CAMS 9) monitor. This site may have some minor influence from relatively small NO X and VOC sources. Data from this monitor was restricted to wind directions originating from 30° to 90°, similarly to West Orange (CAMS 9), to minimize any possible influence of nearby point sources.

The Karnack (CAMS 85) monitor in the TLM ar ea is located eight miles from the TexasLouisiana border, and roughly 20 miles from Ar kansas. Measurements from Karnack (CAMS 85) were restricted to wind directions or iginating from 30° to 135° (Figure 5-40: Karnack

C85Monitor ), that is, from north-northeast clockwise to southeast. Though this site is not near

### 5-74 the HGB area, it records large influxes of contin ental air transported from the Midwestern United States into Texas, which ultimately may raise b ackground ozone concentrat ions throughout the state. Also, estimates of background ozone c oncentrations from Karnack (CAMS 85) can be compared to background estimates from West Orange (CAMS 9) and Mauriceville (CAMS 642/CAMS 311/CAMS 665), which is useful for co rroborating estimates at these two sites, and determining the range of bac kground ozone entering the state.

The final site under consideration is Hamshire (CAMS 64/CAMS 654), located between the HGB

area and the BPA area. Ozone measurements from this site can be used to estimate background ozone concentrations transported to the HGB area when winds are from the east. These background ozone measurements are a combination of pollution transported into Texas, as well as the contribution of pollution from the BPA area. To avoid undue influence of nearby industrial sites, similar to Karnack (CAMS 85), data from Hamshire (CAMS 64/CAMS 654) are restricted to measurements obtained when winds originat e from directions ranging from 30° to 135°. For the four monitors, monthly 10 th , 25 th , 50 th , 75 th and 90 th percentiles of hourly ozone concentrations were calculated for the spring and summer ozone season, May through September, 2000 through 2008, except Karnack (CAMS 85) whic h only has data since 2001. These values are plotted in Figure 5-42: Selected Statistics for the West Orange C9 Monitor , Figure 5-43: Selected Statistics for the Mauriceville C642/C311/C665 Monitor , Figure 5-44: Selected Statistics for the Karnack C85 Monitor , and Figure 5-45: Selected Statistics for the Hamshire
C64/C654 Monitor . Ninetieth percentile values are reported in Table 5-25: Range of Monthly

90 th Percentile Daily Peak Hourly Ozone Con centrations for Subject Wind Directions

.

### 5-75 Figure 5-39: Mauriceville C642/C311/C 65 and West Orange C9/A141 Monitors

Figure 5-40: Karnack C85 Monitor

Figure 5-41: Hamshire C64/C654 MonitorWest Orange0102030405060708090 May Sep May Sep May Sep May Sep May Sep May Sep May Sep May Sep May200020200020200020012012012012001200220022022022002200320320320032003200420420420420042005200520520520052006206206200620062007207207207200720082082008208note: data shown is May - September onlymedian90th75th25th10th2000 2001 2002 2003 2004 2005 2006 2007 2008Figure 5-42: Selected Statistics for the West Orange C9 MonitorMauriceville0102030405060708090 May Sep May Sep May Sep May Sep May Sep May Sep May Sep May Sep May Sep20002020020020002001201201201200120022002202202200220032032032032003200420420420420042005205205205200520062062062062006200720720720720072008208208208208note: data shown is May - September onlymedian90th75th25th10th2000 2001 2002 2003 2004 2005 2006 2007 2008Figure 5-43: Selected Statistics for the MauricevilleC642/C311/C665 MonitorKarnack0102030405060708090 May Sep May Sep May Sep May Sep May Sep May Sep May Sep May Sep May2000202000202000200120120120012001200220220220220022003200320320320032004204200420420042005205205200520052006206206206200620072007207207200720082082008208medianth90th75th2510th2000 2001 2002 2003 2004 2005 2006 2007 2008note: data shown is May - September onlyFigure 5-44: Selected Statistics for the Karnack C85 MonitorHamshire0102030405060708090 May Sep May Sep May Sep May Sep May Sep May Sep May Sep May Sep May Sep2000202002002000200120120120012001200220220220220022003203203203200320042042004204200420052052052052005200620620620620062007207200720720072008208208208208median90th75th25th10thnote: data shown is May - September only2000 2001 2002 2003 2004 2005 2006 2007 2008Figure 5-45: Selected Statistics for the Hamshire C64/C654Monitor5-76

### 5-77 Table 5-25: Range of Monthly 90 th Percentile Daily Peak Hourly Ozone Concentrations for Subject Wind Directions

Hamshire Karnack Mauriceville West Orange

C64/C654 C85 C642/C311/C665 C9

year min max min max min max min max

ppb ppb ppb ppb ppb ppb ppb ppb

2000 38 74 . . 56 81 43 83

2001 50 71 . 54 45 69 57 68

2002 51 62 58 84 40 68 53 69

2003 30 68 60 64 39 61 38 66

2004 43 71 39 66 30 61 41 66

2005 55 79 62 75 43 76 52 75

2006 45 76 42 78 32 63 43 75

2007 37 62 55 67 40 62 47 69

2008 40 62 . 65 47 70 50 60

9-year period 30 79 39 84 30 81 38 83 Note: Though data has been restricted by wind direction to mitigate influences from nearby pollution sources, there may be unknown influences that are unaccounted for. Maximum values for each year are highlighted in boldface
type.

To statistically verify whether a trend across time exists in the data, an index of date was fit to the daily peak values using ordinary least squares re gression. Additional regressions were performed using an index of month against the selected percentiles of the monthly distributions. The resulting parameter estimates from these models revealed no statistically significant trend at the 5 percent significance level; however, the data likely suffer from autocorrelation, a problem

common to time series data. Time series data are often not independent, but correlated with themselves across time, which complicates formal statistical estimation by biasing parameter

estimates.

Rather than performing the procedures necessary to detect, measure, and correct for autocorrelation, a careful visual inspection of time series plots, presented in Figure 5-42: Selected Statistics for the West Orange C9 Monitor through Figure 5-45: Selected Statistics for the
Hamshire C64/C654 Monitor , satisfies that no time trend is pe rceptible. These four figures plot the five selected percentiles of the monthly dist ributions at each monitor. While no trend is detectable, what is apparent is that ozone concen trations measured at these monitors, which have been restricted in such a way as to proxy b ackground levels, vary s ubstantially. Background

ozone at these monitors varies as much as 35 ppb, due to meteorological effects and ozone dynamics occurring in upwind regions.

Notable in Figure 5-45: Selected Statistics for the Hamshire C64/C654 Monitor , hourly ozone concentrations at Hamshire (CAMS 64/CAMS 654) behave similarly to West Orange (CAMS 9) and Karnack (CAMS 85), in that there is no observa ble or statistically significant trend of the
median or 90 th percentile values. The 90 th percentile value at Hamshire (CAMS 64/CAMS 654), considering directionally restricted data for May to September, 2000 through 2008, is 59 ppb. This value is in the range of values computed by Nielson-Gammon using different procedures; however, the 90 th percentile can exceed 80 ppb at any of the sites, and even exceeded 90 ppb at Mauriceville (CAMS 642/CAMS 311/CAMS 665) in 2000. TexAQS II also found background

### 5-78 ozone concentrations that exceed the 1997 ei ght-hour ozone NAAQS (TexAQS II Rapid Science Synthesis Team 2006).

Over the 2000 through 2008 period, the maximum 90 th percentile one-hour ozone concentrations at West Orange (CAMS 9) and Mauriceville (CAMS 642/CAMS 311/CAMS 665) are 79 and 92, respectively. The maximum 90 th percentile for Karnack (CAM S 85) over the 2001 through 2008 period is 81. Karnack (CAMS 85) appears to consistently measure a higher background than either West Orange (CAMS 9) or Mauri ceville (CAMS 642/CAMS 311/CAMS 665). These results are consistent with estimates reported by Nielson-Gammon, et al. (2005), which also found higher background ozone con centrations during the ozone season in northeast Texas than

in the HGB area.

Regression analysis was used to determine whether the 90 th percentile values at West Orange (CAMS 9) and Mauriceville (CAMS 642/CAMS 311/CAMS 665) track one another, which suggests they are measuring roughly eq uivalent phenomena. The resulting R 2 of 0.78, which is significant at a probability level less than 0.1 percent (Table 5-26: Parameter Estimates for Regression of West Orange C9 on Mauriceville C 642/C311/C665, indicates very strong

correlation between measurements at the two sites. The scatter plot of the data is illustrated in Figure 5-46: Scatter-plot of 90 th Percentile Hourly Values at West Orange C9 and Mauriceville
C642/C311/C665 . The values in the scatter plot are from May through September, 2000 to 2008. The scatter plot supports the contention that these two monitors are measuring roughly the same phenomena, under wind-restricted regimes.

Table 5-26: Parameter Estimates for Regre ssion of West Orange C9 on Mauriceville
C642/C311/C665 intercept slope

β estimate 4.95706 1.01251

Std. Error 0.55480 0.01421
t-statistic 8.935 71.278 Pr(>|t|) <2e-16 <2e-16

R 2 0.78

### 5-79 Figure 5-46: Scatter-plot of 90 th Percentile Hourly Values at West Orange C9 and
Mauriceville C642/C311/C665

In summary, none of the four sites used for estim ating background ozone concentrations recorded a statistically significant trend. The Karnack (CAMS 85) monitoring site recorded the highest

90 th percentile measurement of the four background sites, with 90 th percentile ozone concentrations reaching as high as 63 ppb. Sin ce it is farthest from the HGB area, however, the HGB area may not be strongly affected by the ozone observed at this site, at least not on the same day.

5.3.13 Air Quality Trends Conclusions

Ozone concentrations have decreased drama tically in the HGB area since the 1990s. Examination of trends in one-hour ozone, ei ght-hour ozone, the number of exceedances, the spatial distribution of ozone, the seasonal dist ribution of ozone, and the strength of ozone gradients all show substantial dow nward trends. The causes of the trends were investigated by examining the meteorological variations that have occurred over the years, by evaluating the local changes in ozone precursor concentrations, and by examining trends in background ozone. The analyses found that the interannual meteorologi cal variations cannot explain the observed decreases in ozone, and that the ozone precursors are on statistically significant downward trends. In addition, the analyses have found that backgr ound ozone has not droppe d substantially since 2000, suggesting that the significant ozone reductions in the HGB area are due to local emission controls, not due to background ozone decreases.

5.4 QUALITATIVE CORROBORATIVE ANALYSIS
5.4.1 Introduction Because photochemical modeling is an evaluation t ool and not an absolute prediction of future ozone concentrations, additional data must be considered in orde r to draw conclusions about the validity of the final predicted design value and wh ether the attainment demonstration satisfies the requirements of the Federal Clean Air Act (FCAA) . The EPA’s “Guidance on the Use of Models

### 5-80 and Other Analyses for Demonstrating Attainment of Air Quality Goals for Ozone, PM 2.5, and Regional Haze,” referenced as modeling guidance in Chapter 3, Photochemical Modeling acknowledges that many issues cannot be accurately quantified and therefore cannot be properly included in the photochemical modeling demonstra tion. The qualitative corroborative analysis contains information regarding federal preemption issues and analysis of additional measures that were not included in the modeling.

5.4.2 Federal Preemption Issues The TCEQ has limited authority to regulate cert ain components of the emissions inventory. The federal government has jurisdiction over on-road and non-road vehicles, ships, locomotives, and aircraft, among other sources. Since states cannot control sources that are under federal jurisdiction or located in other states, the state is limited in its ability to impose controls on all of

the sources that contribute to ozone formation in a nonattainment area.

5.4.2.1 Federal Assignment While these categories have been addressed thr ough expeditiously implemented state incentive programs such as the Low Income Vehicle Repair Assistance, Retrofit, and Accelerated Vehicle Retirement Program (LIRAP) and the Texas Emissi ons Reduction Plan (TERP), future reductions are dependent on the prompt implem entation of new federal engine and fuel standards for on-road and non-road vehicles, ships, locomotives, and aircraft.

5.4.3 Additional Measures 5.4.3.1 New International Marine Diesel Engi ne and Marine Fuel Standards for Oceangoing

Vessels and Emissions Control Areas In October 2008, the United States ratified the International Maritime Organization's (IMO) adoption of the amendments to Annex VI of th e International Convention for the Prevention of Pollution from Ships (MARPOL) for new internati onal marine diesel engine and marine fuel standards for oceangoing vessels (OGV). The new Annex VI Tier II and Tier III emission standards will apply to diesel engines with a pow er rating above 130 kilowatts (kW) (i.e., 175 horsepower) installed on marine ve ssels constructed on or after January 1, 2011 (Tier II), and January 1, 2016 (Tier III), or diesel engines above 130 kW that undergo a major conversion on or after those dates. The revised MARPOL Annex VI will become effective on July 1, 2010.

In March 2009, the United States submitted a request to the IMO for the creation of an emissions control area (ECA) around the nation's coastlines. If the ECA is granted, all marine diesel fuels used by OGV in the ECA will be limited to a maximum sulfur content of 1,000 ppm beginning January 1, 2015, and all new engines on OGV operating in these areas must use emission controls that achieve an 80 percent reduction in NO X emissions beginning January 1, 2016. Table 5-27: New MARPOL Annex VI Emission Standards for Marine Diesel Engines lists the new emission standards for marine diesel engines with gr eater than 30 liter per cylinder displacement.

### 5-81 Table 5-27: New MARPOL Annex VI Emission Standards for Marine Diesel Engines New MARPOL Annex VI emission standards for marine diesel engines with >30 liter per cylinder displacement

NO X Emission Standards (g/kW–hr) Engine Speed (n) Tier 1 Tier 2 Tier 3

N < 130 revolutions per minute (rpm) 17.0 14.4 3.4

2000 > n ≥ 130 rpm 45.0 × n -0.20 44.0 × n -0.23 9.0 × n -0.20

N ≥ 2000 rpm 9.8 7.7 2.0 Applicable to engines

installed in vessels

constructed on: 01/01/2000 –

12/31/2010 01/01/2011 -

12/31/2015 01/01/2016 and

thereafter

Note: NO X emission standards presented in grams per kilowatt hour.

In the August 28, 2009, issue of the Federal Register (74 FR 44442), the EPA proposed rulemaking to adopt new federal Tier 2 and Tier 3 engine standards for new marine engines above 30 liters per cylinder displacement (i.e., Category 3 marine diesel engines) that are consistent

with the new MARPOL Annex VI NO X emission standards shown in Table 5-27: New MARPOL Annex VI Emission Standards for Marine Diesel Engines . The EPA's proposed new Category 3 marine diesel engine standards also include ne w standards limiting the emissions of hydrocarbons

and carbon monoxide from new Tier 2 and later Category 3 engines to 2.0 g/kW-hr and 5.0 g/kW-hr, respectfully.

The EPA regulations for marine diesel fuel and new marine engines less than 30 liters per cylinder displacement and the new MARPOL Anne x VI standards for marine residual fuels and new marine diesel engines above 30 liters per cylinder displacement will apply to all OGV flagged and registered in the United States. The EPA's proposed new regulations for new Category 3 marine engines and new sulfur limits fo r marine diesel fuel will also apply to all OGV flagged and registered in the United States. In addition, the new MARPOL Annex VI standards will apply to all new marine diesel engines and fu els on foreign marine vessels that operate near United States coasts and ports.

The new marine diesel engine and fuel standards will provide a 96 percent reduction in sulfur in marine diesel fuels, as well as an 85 percent reduc tion in particulate matter emissions and an 80 percent reduction in NO X emissions, when compared to current standards (EPA, 2009a, http://www.epa.gov/otaq/oceanvessels.htm#emissioncontrol ). The cumulative effects of these new marine diesel engine and fuels standards will re sult in a 0.5 to 1.0 ppb reduction of ozone in the ambient air of the HGB ozone nonattainment area by 2020 (EPA, 2009b).

5.4.3.2 SmartWay Transport Partnership and the Blue Skyways Collaborative Among its various efforts to improve air quality in Texas, the TCEQ is currently promoting two voluntary programs in cooperation with the EPA: the SmartWay Transport Partnership and the Blue Skyways Collaborative.

The SmartWay Transport Partnership is a vol untary EPA program for the freight transport industry that promotes strategies and technologies to help improve fleet efficiency while also reducing air emissions. Fleets participating in the SmartWay Transport Partnership commit to implementing voluntary measures over three year s, providing the EPA with annual updates of their progress throughout that period.

SmartWay carriers typically commit to integra ting fuel-saving strategies and technologies into their fleet including: improved aerodynamics, single-wide tires, lighter wheels and rims, idle reduction, automatic tire inflation systems, driver training, and advanced powertrain technologies.

### 5-82 Rolling resistance is estimated by the EPA to account for as much as 13 percent of a heavy-duty vehicle’s fuel consumption. By reducing rollin g resistance, as well as vehicle weight, the EPA believes that single-wide tires will help to improve fuel economy and reduce NO X emissions by an average of 5 percent. Aerodynamic drag accounts for most of a long-haul truck’s energy losses at highway speeds. As a result, the EPA estimates that improving the aerodynamics of both a long-haul truck and its trailer can he lp to improve fuel economy and reduce NO X emissions by another 5 percent.

The extended periods of idling typically associated with long-haul trucks consume an average of one gallon of fuel per hour, while generating associ ated emissions. New technologies such as auxiliary power units (APU) and truck stop electri fication (TSE) systems reduce vehicle idling by providing power for air conditioning, heating, a nd onboard electrical accessories, even when the vehicle is not in operation. The EPA estimates that, assuming typical idling levels, idling reduction technologies such as APU and TSE can reduce NO X emissions by approximately 10
percent.

The transient nature of freight transportation makes it difficult to isolate emissions reductions to a certain region or even a certain state. As a result, any estimates of the impact of these technologies will largely rely on estimates of accumu lated reductions based on estimated levels of overall fleet integration. These estimates ar e possible through ongoing research, and in conjunction with the more than 2,000 compan ies nationwide already committed as SmartWay partners, the EPA has identified a variety of technologies and the potential fuel savings and emissions reductions from those technologies. Th ere are 87 Texas companies that are currently SmartWay partners.

The Blue Skyways Collaborative is a related effort, spearheaded by the EPA Region 6 office in Dallas, Texas and the Region 7 office in Kansas City, Missouri.

Partnering with the EPA Region 6 and Region 7 through this effort are the environmental and energy agencies from the 10 states along the Interstate Highway 35 (IH-35) corridor, including Texas, New Mexico, Louisiana, Arkansas, Okla homa, Kansas, Missouri, Nebraska, Iowa, and Minnesota. In implementing the Blue Skyways Collaborative, the EPA and the participating states recognize that because air quality is ofte n a regional concern, greater reductions are possible through cooperative efforts as opposed to individual efforts initiated independently in

each state.

The primary objective of the Blue Skyways Collabo rative is to improve air quality in these states by promoting innovative technologies in a variety of sectors. In addition to promoting reduction strategies through the SmartWay Partnership for fre ight transportation via air, water, and rail, Blue Skyways also focuses on promoting emissions reduction strategies for other on-road sources, non-road sources, and highway fueling and idling reduction infrastructure, while also promoting renewable, efficient, and alternative energy sources.

To achieve these objectives, the collaborative devel ops partnerships among in ternational, federal, state, and local governments, as well as non-pr ofit organizations, environmental groups, and private industries. These partnerships work together in projects along the key transportation corridors by sharing emission reduction technolog ies and leveraging financial resources from a variety of sources.

### 5-83 5.4.3.3 Control of VOC Emissions from Flash Emissions When the TCEQ and its research partners bega n the second Texas air quality study, TexAQS II, in May 2005, one of the study’s primary goals was to identify VOC emission sources that have been historically underestimated, unreported, or underreported in the TCEQ emissions inventory and could potentially be contributing to a discrepan cy between measured and reported emissions. TexAQS II remote sensing VOC project results indicate that certain types of storage tank emissions, including flash, generally have been underestimated, unreporte d, or underreported in the emission inventory. Flash emissions occur when a liquid with entrained gases goes from a high pressure to a low pressure. As the pressure on the liquid drops, some of the lighter VOC dissolved in the liquid are released or flashed. Compounds that are liquids at the initial pressure may transform from a liquid into a vapor and are also released from the liquid. As these gases are released, some of the heavier compounds in the liquids may become entrained in these gases and are emitted with the lighter VOC.

In May 2007, the commission adopted rule amen dments to 30 Texas Administrative Code (TAC) Chapter 115, Subchapter B, Division 1 that revised the requirements for VOC storage tanks

located in the HGB ozone nonattainment area. Th e revised requirements were developed to reduce VOC emissions that result from uncontrolled flash emissions at upstream oil and gas exploration and production sites and other sources of tank emissions. At the time of the rule proposal, the amount of flash emissions from minor sources was unknown.

A method for quantifying flash emissions became available around the same time. Houston Advanced Research Center Project 51C, conduc ted in 2006, quantified emission rates from heater-treaters (separators) and storage tank batteries, including flash and condensate tanks, associated with the upstream oil and gas indus try in the Dallas-Fort Worth and HGB ozone nonattainment areas, and Jefferson County. In Ap ril 2007, the TCEQ used the results of this study to determine the flash emissions from the oil and gas production industry. However, the flash emissions were not included in the 2005 area source periodic emissions inventory (PEI) because there was not sufficient time to incorpor ate the emissions before the 2005 area source PEI was submitted to the EPA in May 2007. However, the updated 2005 area source emissions inventory is being used for this SIP revision. More information on this study can be found at: http://www.harc.edu/Projects/AirQuality/Projects/Projects/H051C

.

The rule amendments adopted in May 2007 resulted in actual reductions to flash emissions but no credit is claimed in this SIP revision. Crude and condensate storage tanks at upstream oil and gas exploration and production sites or midstream pi peline breakout stations with uncontrolled flash emissions greater than 25 tons per year (tpy) are controlled under the rule. Since the method of calculating the emissions was based on county-leve l production, it is unknown at this time how many sites were over 25 tpy and were required to put on controls. Also unknown is how much flash emissions were already controlled due to economic reasons. Because of the unknown total effect of this rule, the reduction in flash emissi ons cannot be quantified at this time and is not included in the modeling for this SIP revision. These amendments to Chapter 115 are described in more detail in the preamble of the adopted rule (Project Number 2006-038-115-EN).

5.4.3.4 Energy Efficiency and Renewable Energy (EE/RE) Measures Energy efficiency efforts are typically programs that reduce the amount of electricity and natural gas consumed by residential, commercial, industrial, and municipa l energy consumers. Examples of energy efficiency include increasing insulation in homes, installing compact fluorescent light bulbs, and replacing motors and pumps with high efficiency units. Renewable energy efforts include programs that generate energy from resour ces that are replenished or are otherwise not consumed as with traditional fuel-based energy production. Examples of renewable energy include wind energy and solar energy projects.

### 5-84 The Texas Legislature has enacted a number of EE/RE measures and programs. The following is a summary of Texas EE/RE legislation since 1999.

• 76th Texas Legislature, 1999

o Senate Bill (SB) 7 (Regular Session)

o House Bill (HB) 2492 (Regular Session)

o HB 2960 (Regular Session)

• 77th Texas Legislature, 2001

o SB 5 (Regular Session)

o HB 2277 (Regular Session)

o HB 2278 (Regular Session)

o HB 2845 (Regular Session)

• 78th Texas Legislature, 2003

o HB1365 (Regular Session)

• 79th Texas Legislature, 2005

o SB 20 (First Call Session)

o HB 2129 (Regular Session)

o HB 2481 (Regular Session)

• 80th Texas Legislature, 2007

o HB 66 (Regular Session)

o HB 3070 (Regular Session)

o HB 3693 (Regular Session)

o SB 12 (Regular Session)

SB 5, 77th Texas Legislature, 2001, set goals fo r political subdivisions in affected counties to implement measures to reduce energy consumpti on from existing facilities by 5 percent each year for five years from January 1, 2002 through January 1, 2006. In 2007, the 80th Texas Legislature passed SB 12, which extended the timeline set in SB 5 through 2007 and made the 5 percent each year a goal instead of a requirement. The Stat e Energy Conservation Office (SECO) is charged with tracking the implementation of SB 5 and SB 12. Also during the 77th Texas Legislature, the Energy Systems Laboratory (ESL), part of the Texas Engineering Experiment Station, Texas A&M University System, was mandated to provide an annual report on EE/RE efforts in the state as part of the Texas Emissions Reduction Plan (TERP) under Texas Health and Safety Code (THSC), § 388.003(e). HB 2129, 79th Texas Legislature, 2005, directed the ESL to collaborate with the TCEQ to develop a methodology for com puting emission reductions attributable to use of renewable energy and for the ESL to quantif y annually such emission reductions. HB 2129

directed the Texas Environmental Research Cons ortium to use the Texas Engineering Experiment Station to develop this methodology. With the TCEQ’s guidance, the ESL produces an annual report detailing these efforts ( Statewide Air Emissions Calculations from Energy Efficiency, Wind and Renewables) . The report:

• analyzes power production from wind and other renewable energy sources;

• provides quantification of energy savings and NO X reductions resulting from the installation of wind and other renewable energy sources;

• describes methodologies developed to quantify energy savings and NO X reductions from energy efficiency, wind and other renewable energy initiatives; and

• provides degradation analysis for future pred ictions of power production of wind farms.

The ESL documents methods used to devel op estimates of energy savings and NO X emissions reductions resulting from reductions in natura l gas consumption and displaced power from conventional electric generation facilities. Th e ESL used the EPA’s Emissions and Generation Resource Integrated Database to spatially allocate energy use and emission reductions among electric generation facilities. The THSC, § 389.002 and § 389.003 contain requirements that the Public Utility Commission of Texas (PUCT), SECO, and the ESL report to the TCEQ all

### 5-85 emission reductions resulting from EE/RE projects in Texas. The ESL analyzed the following areas/programs:

Renewable Energies The 79th Texas Legislature, 2005, amended SB 5 through SB 20, HB 2129, and HB 2481 to add, among other initiatives, the following renewable energy initiatives, which require: 5,880 megawatts of generating capacity from renewabl e energy by 2015; the TCEQ to develop a methodology for calculating emission reducti ons from renewable energy initiatives and associated credits; the ESL to assist the TCEQ in quantifying emissions reductions from EE/RE programs; and the PUCT to establish a target of 10,000 megawatts of installed renewable technologies by 2025.

Residential Building Codes and Programs The THSC, Chapter 388, Texas Building Energy Performance Standards, as adopted by the 77th Texas Legislature, 2001, states in § 388.003(a) th at single-family residential construction must meet the energy efficiency perfo rmance standards established in the energy efficiency chapter of

the International Residential Code. The Furn ace Pilot Light Program includes energy savings accomplished by retrofitting existing furnaces. Al so included are Seasonal Energy Efficiency Ratio (SEER) 13 upgrades to single-family and multi- family buildings. In January 2006, federal regulations mandated that the minimum efficiency for residential air conditioners be increased

from SEER 10 to SEER 13.

Commercial Building Codes The THSC, Chapter 388, Texas Building Energy Performance Standards, as adopted by the 77th Texas Legislature, 2001, states in § 388.003(b) that all other residential, commercial, and industrial construction must meet the energy efficiency performance standards established in the energy efficiency chapter of the In ternational Energy Conservation Code.

Federal Facilities EE/RE Projects Federal facilities are required to reduce energy use by Presidential Executive Order 13123 and the Energy Policy Act of 2005 (Public Law 109-58 EPACT20065). The ESL compiled energy reductions data for the federal EE/RE projects in Texas.

Political Subdivisions Projects SECO funds loans for energy-efficiency project s for state agencies, institutions of higher education, school districts, county hospitals, a nd local governments. Political subdivisions in nonattainment and affected counties are required by SB 5 to report EE/RE projects to SECO. These projects are typically building systems retr ofits, nonbuilding lighting projects, and other mechanical and electrical systems retrofits such as municipal water and waste water treatment
systems.

Electric Utility Sponsored Programs Utilities are required by SB 7, 76th Texas Legislature, 1999, and SB 5, 77th Texas Legislature, 2001, to report these projects to the PUCT. See THSC, § 386.205 and Texas Utilities Code, § 39.905. These projects are typically air cond itioner replacements, ven tilation duct tightening,

and commercial and industria l equipment replacement.

In addition to the programs discussed and analyzed in the ESL report, local governments may have enacted measures beyond what has been reported to SECO and the PUCT. The TCEQ encourages local political subdivisions to pr omote EE/RE measures in their respective

communities and to ensure these measures ar e fully reported to SECO and the PUCT.

HB 3693, 80th Texas Legislature, 2007, amended the Texas Education Code, Texas Government Code, THSC, and Texas Utilities Code. The bill:

### 5-86 • requires state agencies, universities and local governments to adopt energy efficiency

programs;

• provides additional incentives for electric utilities to expand energy conservation and efficiency programs;

• includes municipal-owned utilities and cooperatives in efficiency programs;

• increases incentives and provides consumer e ducation to improve efficiency programs;

and

• supports other programs such as revision of bu ilding codes and research into alternative technology and renewable energies.

Emissions reductions as a result of the above programs were not explicitly included in the photochemical modeling because local efficiency efforts may not result in local emissions reductions or may be offset by increased demand in electricity. The complex nature of the electrical grid also makes accurately quantif ying emission reductions from EE/RE projects difficult. At any given time, it is impossible to determine exactly where on the electrical grid electricity comes from for any certain electrical us er. The electricity for a user could be from a power plant in west Texas, a nearby attainment county or from within the nonattainment area. If electrical demand is reduced in the HGB area due to these kinds of measures, then emission reductions from power generation facilities may o ccur in any number of locations around the

state.

5.4.3.5 Clean Air Interstate Rule (CAIR) The EPA projects that CAIR regional controls will improve air quality in the HGB area, as well as most of Texas, according to EPA’s Texas CAIR Web page, http://www.epa.gov/cair/tx.html

.

Under CAIR, 28 eastern states (plus the District of Columbia) are required to comply with a cap on sulfur dioxide (SO 2 ) and NO X for EGU emissions. The defin ition of an EGU for the CAIR program is approximately the same definition as that for an FCAA Title IV Acid Rain unit (i.e., larger than 25 megawatt (MW) and more than one-t hird of its generation going to the public grid for sale). CAIR is a cap and trade program, with each of the CAIR-applicable states given a

calculated NO X budget and a calculated SO 2 budget by the EPA. The EPA modeled all of these

states in order to test the effectiveness of cont rols. A result of EPA’s CAIR modeling was that Texas “significantly contributed” to the nonattainment of the particulate matter of 2.5 microns and less (PM 2.5 ) standard of two counties in Illinois, th erefore, Texas was included in CAIR for the transport of PM 2.5 . Texas is not covered under the CA IR program for 1997 eight-hour ozone

standard contribution.

CAIR is implemented in two phases: for NO X , Phase I covers the years 2009 through 2014 and Phase II is for the years 2015 and later; for SO 2 , Phase I covers the years 2010 through 2014 and Phase II is for the years 2015 and later. The Phase I NO X budget calculated and assigned to Texas was 181,014 tons per year, and the Phase II NO X budget was 150,845. Because 2018 is the HGB ozone attainment year, this SIP revision inco rporates CAIR Phase II (post 2014 step-down of CAIR) which provides for a Texas state-wide NO X budget of 150,845 tons per year, or 413.3 tons per day.

See Appendix B: Emissions Modeling for the HGB Attainment Demonstration SIP , Section 2.3.1.2.1 for the procedural details that the TCEQ used to simulate CAIR Phase II in Texas and the regional states.

On July 11, 2008, the United States Court of App eals District of Columbia Circuit (Court) (No. 05-1244) vacated CAIR and the CAIR Federal Implementation Plan (FIP). On December 23, 2008, the Court issued a revised opinion to re mand, without vacating, CAIR to the EPA. Therefore, CAIR will remain in effect while the EPA analyzes data and conducts rulemaking to

### 5-87 modify the program to comply with the Court’s July 2008 opinion. The Court declined to impose a schedule by which the EPA must complete th e rulemaking, but reminded the EPA that the Court does “. . . not intend to grant an indefin ite stay of the effectiveness of this Court’s decision.” For more information on the ruling, see EPA’s CAIR Web page, http://www.epa.gov/cair/ , or the TCEQ CAIR/CAMR Web page, http://www.tceq.state.tx.us/implementation/air/sip/caircamr.html

.

Any future EPA revision to the CAIR program to comply with the court’s ruling may result in

additional reductions.

5.4.3.6 Texas Emission Reduction Plan (TERP) The TERP program was created in 2001 by the 77th Texas Legislature to provide grants to offset the incremental costs associated with reducing NO X emissions from high-emitting internal combustion engines. To date the TERP program has funded over $700 million in grants for projects in Texas ozone nonattainment and near- nonattainment areas. Over $300 million of that amount has been awarded to projects in the HGB area since 2001, which will help reduce more than 66,000 tons of NO X emissions. Of that $300 million, $5 million was awarded to the H-GAC through a third-party grant to administer additional grants in the HGB area.

Additional funds are expected to be awarded to the HGB area in subsequent grant application periods that will result in further NO X reductions. HB 1796, 81st Texas Legislature, 2009, extended the TERP program beyond its current 2013 date to 2019, which will result in continued reductions in the significant emissions source categories of on-road and non-road engines.

5.4.3.7 Low Income Vehicle Repair Assistance, Retrofit, and Accelerated Vehicle Retirement Program (LIRAP) SB 12, 80th Texas Legislature, 2007, enhanced LIRAP to expand participation by increasing the income eligibility to 300 percent of the federal poverty rate and increasing the amount of assistance toward the replacement of a retired vehicle. The program, known as AirCheckTexas Drive a Clean Machine (DACM), provides $3,500 fo r hybrids of the current or previous model year; $3,000 for cars of the current or three model years; and, $3,000 for trucks of the current or previous two model years. The retired vehicle must be 10 years or older or have failed an emissions test. In the HGB area, DACM is ava ilable to vehicle owners in five counties: Brazoria, Fort Bend, Galveston, Harris, and Montgomery. Between December 2007 and May 31, 2009, LIRAP/DACM has retired and replaced 9, 330 vehicles at a cost of $28,370,520. An additional 3,949 vehicles have had emissions-related repairs at a cost of $2,136,602. The total repair and retirement/replacement funding for the HGB area since December 2007 is $30,507,122.

5.4.3.8 Clean School Bus Program HB 3469, 79th Texas Legislature, 2005, established the Clean School Bus Program. The new program is codified in THSC, Chapter 390 and implemented through 30 TAC §§ 114.640 –

114.648.

The program is based on the EPA guidance documents, Improving Air Quality with Economic Incentive Programs (EPA-452/R-01-001) and Diesel Retrofits: Quantifying and Using Their Benefits in SIPs and Conformity (EPA-420-B-06-005). Under the economic incentive program guidance, the TCEQ is using the financial mech anism option, which is described as subsidies targeted at promoting pollution-reducing activities or products.

The Clean School Bus Program was established to provide monetary incentives for school districts in the state for reducing emissions of diesel exhaust in school buses. Eligible technologies include those approved by the EPA, certified by the California Air Resources Board,

or those that the executive director finds will br ing about significant emissions reductions. Some

### 5-88 of the technologies eligible for funding under the program reduce NO X emissions. However, the technologies mainly reduce particulate matter and reduce only negligible amounts of NO X . The 80th Texas Legislature, 2007, provided funding for the Clean School Bus Program.

As of May 2009, the TCEQ Clean School Bus grant program has allocated $13.8 million in grants for nearly 5,000 school buses in Texas. In ad dition, through Supplemental Environmental Projects (SEPs), the TCEQ has also allocated over $3.5 million to third-party SEP receivers for

the same kind of school bus retrofits.

5.4.3.9 81 st Texas Legislature, 2009 HB 432 requires state agencies that purchase passenger vehicles or other ground transportation vehicles for general use to ensure that not less th an 25 percent of new vehicles purchased during a biennium meet or exceed EPA’s Tier II, Bin 3 emission standards. This bill also limits the purchase of state agency passenger vehicles or other ground transportation vehicles purchased for general use to only those vehicles that use compress ed natural gas, liquefied natural gas, liquefied petroleum gas, methanol or methanol/gasoline bl ends of 85 percent or greater, ethanol or ethanol/gasoline blends of 85 percent or greater, biodiesel or biodiesel/diesel blends of 20 percent or greater, or electricity, including electricity to power a plug-in hybrid motor vehicle.

HB 1796 establishes a New Technology Implementa tion Grants (NTIG) program for facilities and stationary sources under TERP, requires the current New Technology Research and Development under TERP to be administered by the TCEQ, and extends the TERP to August 31, 2019. See Section 5.4.3.6, Texas Emission Reduction Plan (TERP), for additional information.

SB 1759 establishes a Texas Clean Fleet Program to be administered by the TCEQ, funding it with 5 percent of the 87.5 percent of the Emis sion Reduction Incentives Grant within TERP. TheTexas Clean Fleet Program will provide grants to encourage large fleets to replace dieselpowered fleet vehicles with hybrid vehicles or alternative fuel-powered vehicles.

5.4.3.10 American Waterways Operators Tank Barge Emissions Best Management Practices

Using infrared gas imaging technology in field studies conducted in the summer of 2005, the TCEQ detected inadvertent VOC emissions from tank barges operating in the HGB area. The Louisiana Department of Environmental Quality (LDEQ) also detected inadvertent emissions from tank barges in similar field studies conducted in the same time period. In response to these field studies, the American Waterways Operator s (AWO) voluntarily developed industry Best Management Practices (BMP) to reduce VOC em issions from tank barges. The BMP includes procedures to reduce VOC emissions from equi pment and operations on tank barges. The recommendations are a combination of inspection, corrective action, preventative maintenance, operational, procedural, and training practices.

The BMP was reviewed by the Chemical Tran sportation Advisory Committee (CTAC), United States Coast Guard, LDEQ, and TCEQ. The BMP was distributed to AWO members in 2006 for implementation on a voluntary basis. In 2009, AWO reconvened the Tank Barge Emissions Working Group to review the BMP and make further improvements to the document. The improved BMP will be sent to CTAC, the Coast Guard, LDEQ, and TCEQ for review once it has been finalized by industry. While the BMP is a voluntary measure and does not impose an enforceable commitment on AWO members, the im plementation of the BMP, where applicable, may contribute to reducing inadvertent VOC em issions from barges during dock operations and during transit, which will help improve the air quality in the HGB area. A copy of the 2006 BMP document is provided in Appendix J: Recommendations for Best Management Practices to Control and Reduce Inadvertent Cargo Vapor Emissions in the Tank Barge Community

.

### 5-89 5.4.3.11 Local Initiative Projects SB 12, 80th Texas Legislature, 2007, allowed the use of unexpended LIRAP funds to be used for Local Initiative Projects. These projects provide funding to LIRAP-participating counties for implementation of air quality improvement strategi es through local projects and initiatives. Local Initiative Projects may include:

• expand and enhance the repair and replacement program;

• develop and implement programs to remotely determine vehicle emissions and notify the vehicle’s operator;

• develop and implement projects for coordinatin g with local law enforcement officials to reduce the use of counterfeit state inspection stickers;

• develop and implement programs to enhance transportation system improvements; or

• develop and implement new air control strategi es designed to assist local areas in complying with state and federal air quality rules and regulations.

5.4.3.12 Other Local Programs

The Houston-Galveston Area Council submitted th e following programs, which were not committed to as Transportation Control Measur es or Voluntary Mobile Emission Reduction Program measures, but may be implemented locally in the HGB area. For a detailed analysis of these programs, see Appendix F: Evaluation of Mobile Source Control Strategies for the
Houston-Galveston-Brazoria State Implementation Plan (prepared by ENVIRON for the Houston-Galveston Area Council).

Scrappage and Buy-Back Plan This measure would build on the existing LIRA P, implemented as part of the AirCheckTexas Vehicle Emissions Testing program, by increasi ng the number of on-road light-duty gasoline vehicles scrapped. The plan would also make sep arate funds available to help with the purchase of new on-road heavy-duty diesel vehicles (HD DV) to replace old, highly polluting vehicles.

Pay-As-You-Drive Insurance Pay-As-You-Drive Vehicle Insurance, also called Distance-Based Vehicle Insurance and Mileage-Based Insurance, is a program that allo ws a vehicle’s insurance premiums to be based directly on how many miles the vehicle is driven during the policy term. Currently, vehicle insurance is structured where high-mileage driver s are, in essence, subsidized by low-mileage drivers since all drivers are charged the same premiums after accounting for driving history
related to collisions and traffic violations.

Limitations on Idling of Heavy-Duty Vehicles; Creation of Regional Government Idling

Restrictions Idling of vehicles is inherently an inefficient operation that can produce unwanted air pollutants. Idling also occurs during normal driving and othe r operations such as when the engine powers necessary accessories, known as power take-off, including man-lifts or concrete tumblers. It is not possible to eliminate all idling, but idle re duction programs are typically low in cost and may result in a net savings to the owner/operator of the vehicle while also reducing air emissions.

Encourage/Mandate Livable Centers The EPA developed the Smart Growth Implementati on Assistance (SGIA) program in response to communities' requests for help achieving their de velopment goals. Through this program, the EPA provides technical assistance from private-sect or experts to help communities find the best tools and resources for planning growth in ways that sustain environmental and economic progress and create a high quality of life. The Gulf Coast Institute, Main Street Coalition, and Texas A&M partnered to apply for and received an SGIA grant in 2006. While the City of Houston is not participating in th e SGIA program at this time, the area has expressed interest in evaluating the potential effects of these measures on travel activity and emissions.

### 5-90 Enhanced Enforcement of Smoking Vehicles This measure would encourage local law enfo rcement officers to enforce existing smoking vehicle laws and enable the emissions inspecti on status of smoking vehicles to be checked. Owners of smoking vehicles displaying a valid in spection sticker would be fined. Smoking vehicles not having a valid inspection sticker woul d be impounded if the sticker were found to be

fraudulent.

Limitation on Idling of Heavy-Duty Construction Equipment Idling is an inefficient use of equipment in general and generates unnecessary emissions. Idling however cannot be avoided in all cases, such as during normal work, when work is performed intermittently, and when the time to restart the e ngine would be considered a significant delay. This measure would seek to limit excessive idling when equipment is not required immediately. Suggested periods for limiting idling could be as little as 15 minutes maximum. Many on-road trucks have factory-installed engine shutdown sy stems that automatically shut down the engine after a set period, or devices could be added to ex isting equipment. To implement this measure, engine shutdown systems could be employed with idle timers set to a period that would not cause typical operational problems. Operator training co uld provide significant idle reduction perhaps beyond engine shutdown systems.

5.5 CONCLUSIONS The TCEQ has employed several sophisticated t echnical tools to evaluate the past and present causes and effects of high ozone in the HGB area in an effort to predict the area’s future air quality. Photochemical grid modeling has b een performed and its performance has been rigorously evaluated. Historical trends in oz one and ozone precursor concentrations and their causes have been investigated exhaustively. The following conclusions can be reached from

these evaluations.

First, the photochemical grid modeling performs relatively well. Problems observed with the modeling are those that are known to exist in all photochemical modeling exercises. In spite of the known shortcomings, the model can be used car efully to predict ozone concentrations. The photochemical grid modeling predicts that the cont rol strategy package chosen by the TCEQ can lower the ozone design values in the HGB area dow n to a value very near the 0.08 ppm eighthour ozone standard. The dynamic model evaluati ons show that the model response to emission decreases is less than the response observed in the atmosphere, suggesting that the proposed emission controls are more likely to yield attain ment of the eight-hour 0.08 ppm ozone standard than the absolute modeled design values indicate.

Second, the ozone trend analyses show that ozone has decreased significantly since the late 1990s. Meteorological variati ons alone cannot explain the significant downward trend. Decreases in background ozone cannot explain the downward trend either. Significant decreases in ozone precursors, however, coincide with th e decreases in ozone, indicating that the ozone

decreases observed in the HGB area are due to local emission controls.

Third, many additional air quality improvement m easures are being adopted in the HGB area that cannot be included in the photochemical modeling analysis because they cannot be accurately quantified. These additional measures can provide additional assurance that the HGB area is on the path toward attainment.

Based upon the photochemical grid modeling results and these corroborative analyses, the weight

of evidence indicates that the HGB area will atta in the 1997 eight-hour ozone standard by June 15, 2019.

### 5-91 5.6 REFERENCES Banta R., C. Senff, J. Nielsen-Gammon, L. Darby, T. Ryerson, R. Alvarez, P. Sandberg, E. Williams, and M. Trainer, 2005. A bad air da y in Houston. Bull. of the American Meteorological Society, 86(5): 657-669.

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Cheng, F.-Y., S. Kim, and D. W. Byun, 2008b. Application of high resolution land use and land cover data for atmospheric modeling in the Houston-Galveston Metropolitan area: Part II: Air quality simulation results, Atmos. Environ., 42:4853-4869.

Cohan, D., Y. Hu, and A. Russell, 2006. Depe ndence of ozone sensitivity analysis on grid resolution. Atmos. Environ., 40:126-135.

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Czader, B. H., D. W. Byun, S.-T. Kim, and W. P.L. Carter, 2008. A study of VOC reactivity in the Houston-Galveston air mixture utilizing an extended version of SAPRC-99 chemical mechanism, Atmos. Environ., 42, Issue 23, Selected Papers from the First International Conference on Atmospheric Chemical Mechanisms, July, 5733-5742 pp,

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Houston urban and industria l plumes during the 2000 Texas Air Quality Study. J. of Geophysical Research, 108:4715, doi:10.1029/2003JD003552.

Daum, P.H., L. I. Kleinman, S. R. Springston, L. J. Nunnermacker, Y.-N. Lee, J. WeinsteinLloyd, J. Zheng, and C. M. Berkowitz, 2004. Origin and properties of plumes of high ozone observed during the Texas 2000 Air Quality Study (TexAQS 2000). J. of Geophysical Research, 109, D17306, doi:10.1029/2003JD004311.

De Gouw, J., S. Te Lintel Hekkert, J. Mellqvist, C. Warneke, E. Atlas, F. Fehsenfeld, A. Fried, G. Frost, F. Harren, J. Holloway, B. Lefer, R. Lueb , J. Meagher, D. Parrish, M. Patel, L. Pope, D. Richter, C. Rivera, T. Ryerson, J. Samuelsson, J. Walega, R. Washenfelder, P. Weibring, and X. Zhu, 2009. Airborne measurem ents of ethene from industrial sources using laser photo-acoustic spectroscopy, Environ. Sci. Technol., March 9, 10.1021/es802701a.

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### 5-93 EPA, 2009b. Regulatory Announcement: Proposal of Emission Control Area Designation for Geographic Control of Emissions from Ships, EPA-4 20-F-09-015, Figure 4: Potential Benefits of U.S. ECA Ozone Reductions in 2020, March 2009.

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Fang, Z., and S. McDowell, 2003. Analysis of canister data for the Houston-Galveston and

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Fast, J. D., W. I. Gustafson Jr., R. C. Easter, R. A. Zaveri, J. C. Barnard, E. G. Chapman, G. A. Grell, and S. E. Peckham, 2006. Evolution of ozone, particulates, and aerosol direct radiative forcing in the vicinity of Houston using a fully coupled meteorology-chemistry-aerosol model, J. Geophys. Res., 111, D21305, doi:10.1029/2005JD006721.

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Gilman, J., W. Kuster, P. Goldan, S. Herndon, M. Zahniser, S. Tucker, A. Brewer, B. Lerner, E. Williams, R. Harley, F. Fehsenfeld, C. Warneke, and J. de Gouw. 2009, Measurements of volatile organic compounds during the 200 6 TexAQS/GoMACCS campaign: Industrial influences, regional characteristics, and diurnal dependencies of the OH reactivity, J. Geophys. Res., 114, D00F06, doi:10.1029/2008JD011525.

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### 5-94 Hafner, H. and S. Brown, 2003. Exploratory Source Apportionment of Houston’s Clinton Drive Auto-GC 1998-2001 Data. Prepared for Erik Gribbin, Texas Commission on Environmental Quality, May 15, 144 pp. http://www.tceq.state.tx.us/assets/public/implement ation/air/am/contracts/reports/da/Source_App ortionment_of_AutoGC_Data.pdf

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Karl, T., T. Jobson, W. C. Kuster, E. Williams, J. Stutz, R. Shetter, S. R. Hall, P. Goldan, F. Fehsenfeld, and W. Lindinger, 2003. Use of proton-transfer-reaction mass spectrometry to characterize volatile organic compound sources at the La Porte super site during the Texas Air Quality Study 2000, J. Geophys. Res., 108(D16), 4508, doi:10.1029/2002JD003333, 2003.

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Lelieveld, J., T. Butler, J. Crowley, T. Dillon, H. Fischer, L. Ganzeveld, H. Harder, M. Lawrence, M. Martinez, D. Taraborrelli, and J. Williams, 2008. Atmospheric oxidation capacity sustained by a tropical forest, Nature, 452, doi: 10.1038/nature06870, 10 April 2008.

Li, S., J. Matthews, and A. Sinha, 2008. Atmospheric hydroxyl radical production from electronically excited NO2 and H2O, Science, 319: 1657, doi: 10.1126/science.1151443.

Mao, J., Ren, X., Chen, S., Brune, W.H., Chen , Z., Martinez, M., Harder, H., Lefer, B., Rappenglück, B., Flynn, J., and M. Leuchner, 20 09. Atmospheric Oxidation Capacity in the Summer of Houston 2006: Comparison with Summer Measurements in Other Metropolitan Studies, Atmospheric Environment, doi: 10.1016/j.atmosenv.2009.01.013

Mellqvist, J., J. Samuelsson, C. Rivera, B. Lefer, and M. Patel, 2007. Measurements of industrial emissions of VOCs, NH 3 , NO 2 and SO 2 in Texas using the Solar Occultation Flux method and mobile DOAS, Final Report HARC project H-53, August 20,. http://www.tercairquality.org/AQR/Projects/H053.2005

Mellqvist, J., J. Johansson, J. Samuelsson, C. Rivera, B. Lefer, and S. Alvarez, 2008. Comparison of solar occultation flux measurement s to the 2006 TCEQ emission inventory and airborne measurements for the TexAQS II, November 7, Report submitted to the TCEQ.

Morris, G., S. Hersey, A. Thompson, S. Pawson, E. Nielsen, P. Colarco, W. McMillan, A. Stohl, S. Turquety, J. Warner, B. Johnson, T. Kucsera, D. Larko, S. Oltmans, and J. Witte, 2006.

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Nam, J., M. Webster, Y. Kimura, H. Jeffries, W. Vizuete, and D. T. Allen, 2008. Reductions in
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### 5-96 Nielsen-Gammon, J. W., R. T. McNider, W. M. Angevine, A. B. White, and K. Knupp, 2007. Mesoscale model performance with assimilation of wind profiler data: Sensitivity to assimilation parameters and network configuratio n, J. Geophys. Res., 112, D09119,
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North, S. and B. Ghosh, 2009. Refining hydrocarbon oxidation mechanisms via isomeric specific radical initiated chemistry, Final Report. TCEQ tracking number 2008-93, Grant Activity No. 582-5-64593-FY08-22. 16 pp.

Osthoff, H., J. Roberts, A. Ravishankara, E. Williams, B. Lerner, R. Sommariva, T. Bates, D. Coffman, P. Quinn, J. Dibb, H. Stark, J. Burkhol der, R. Talukdar, J. Meagher, F. Fehsenfeld, and S. Brown, 2008. High levels of nitryl chloride in the polluted subtropical marine boundary layer. Nature Geoscience doi: 10.1038/ngeo177, published online April 6.

Pinder, R., R. Gilliam, K. W. Appel, S. Napele nok, K. Foley, and A. Gilliland, 2009. Efficient probabilistic estimates of surface ozone concentrati on using an ensemble of model configurations and direct sensitivity calculations, Environ. Sci. Technol., Article ASAP, March 3, doi:

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Pour-Biazar, A. R. McNider, S. Roselle, R. Suggs, G. Jedlovec, D. Byun, S. Kim, C. Lin, T. Ho, S. Haines, B. Dornblaser, and R. Cameron, 2007. Correcting photolysis rates on the basis of satellite observed clouds, J. Geophys. Res ., 112, D10302, doi:1 0.1029/2006JD007422.

Robinson, R., T. Gardiner, and B. Lipscomb e, 2008. Measurements of VOC emissions from petrochemical industry sites in the Houston ar ea using Differential Absorption Lidar (DIAL) during summer 2007, Draft. Submitted to Russell Nettles, TCEQ, by Rod Robinson, Tom Gardiner, and Bob Lipscombe of the National Physical Laboratory, Teddington, Middlesex UK TW11 0LW, February 8, 86 pp.

Ryerson, T. B., M. Trainer, W. M. Angevine, C. A. Brock, R. W. Dissly, F. C. Fehsenfeld, G. J. Frost, P. D. Goldan, J. S. Holloway, G. Huebler, R. O. Jakoubek, W. C. Kuster, J. A. Neuman, D. K. Nicks Jr., D. D. Parrish, J. M. Roberts, and D. T. Sueper, E. L. Atlas, S. G. Donnelly, F. Flocke, A. Fried, W. T. Potter, S. Schauffler, V. Stroud, A. J. Weinheimer, B. P. Wert, and C. Wiedinmyer, R. J. Alvarez, R. M. Banta, L. S. Darby, and C. J. Senff, 2003. Effect of petrochemical industrial emissions of reactive alkenes and NO X on tropospheric ozone formation in Houston, Texas. J. of Geophysi cal Research, 108:4249, doi :10.1029/2002JD003070.

Sarwar, G., and P.V. Bhave, 2007. Modeling the Effect of Chlorine Emissions on Ozone Levels over the Eastern United States. J. Appl. Meteor. Climatol., 46 : 1009–1019.

Savanich, K., 2006. Ozone Exceedance Days as a Function of the Number of Monitors. Unpublished analysis for TCEQ, February.

Simon H., Y. Kimura, G. McGaughey, D. T. Allen, S. S. Brown, H. D. Osthoff, J. M. Roberts, D. Byun, and D. Lee, 2009. Modeling the impact of ClNO 2 on ozone formation in the Houston area, J. Geophys. Res., 114, D00F03, doi:10.1029/2008JD010732.

Smith, J. and J. Jarvie, 2008. Reconciling repor ted VOC emissions with ambient measurements,

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Stuart, A. L., A. Aksoy, F. Zhang, and J. W. Nielsen-Gammon, 2007. Ensemble-based data assimilation and targeted observation of a chemical tracer in a sea breeze model, Atmos. Environ., 41:3082-3094.

Sullivan, D., 2009. Effects of Meteorology on Po llutant Trends. Final Report to TCEQ. Grant Activities No. 582-5-86245-FY08-01. Prepared by Dave Sullivan, University of Texas at Austin Center for Energy and Environmental Resources, Prepared for Kasey Savanich, for the Texas Commission on Environmental Quality, March 16. http://www.tceq.state.tx.us/assets/public/implementation/air/am/contracts/reports/da/5820586245 FY0801-20090316-ut-met_eff ects_on_pollutant_trends.pdf

Swall, J. and K. Foley, 2009. The impact of spatial correlation and incommensurability on model evaluation. Atmos. Environ. 43:1204-1217, doi:10.1016/j.atmosenv.2008.10.057.

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6.1 INTRODUCTION The Texas Commission on Environmental Quality (TCEQ) is committed to improving the air quality in the Houston-Galveston-Brazoria (HGB) ar ea and continues to work toward identifying and reducing ozone precursors. Texas is investing resources into technological research and development for advancing pollution contro l technology, improving the science for ozone modeling and analysis, and refining quantif ication of volatile organic compound (VOC) emissions. Refining quantification of VOC emis sions benefits SIP planning by improving understanding of ozone formation. Additionally, the TCEQ is working with the United States Environmental Protection Agency (EPA), local area leaders, and the scientific community to identify new measures for reducing ozone precurs ors. This chapter describes ongoing technical work that will be beneficial to improvi ng air quality in Texas and the HGB area.

6.2 ONGOING WORK
6.2.1 Flare Task Force In November 2008, the TCEQ formed an agency-w ide task force to comprehensively evaluate all aspects of flares in Texas. The Flare Task Force is evaluating how flares factor into air quality challenges with an emphasis on air toxics and ozone. Some of the specific issues under evaluation include: different factors affecting fl are performance, such as waste gas flow rates, turndown ratio, and waste gas to steam assist ratios; the adequacy of existing monitoring requirements for flares; and alternatives to fl aring routine emissions. A stakeholder group

associated with the Flare Task Force has been formed to solic it comment on these issues related to flares. A report for executive management is planned that will include options, considerations, and recommendations for improving our understanding and regulation of flares with the goal of improving air quality. Additional information abou t the Flare Task Force is available at the

stakeholder Web site: http://www.tceq.state.tx.us/implementation/air/rules/flare_stakeholder.html

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6.2.2 Technologies for Detecting VOC 6.2.2.1 Optical Gas Imaging Technology Optical gas imaging technology offers a unique technological advancement in pollution detection capability and has proved to be highly effective in the detection of VOC emissions. An optical gas imaging system is a useful tool that assists the agency in ac tions such as facility investigations, reconnaissance investigations, mobile monitoring, and special projects. This technology is also useful in identifying sour ces of VOC emissions that are underestimated, underreported, unreported, or prev iously unregulated. The system also has the potential to advance leak detection and repair (LDAR) work practices and enable monitoring of components

that are difficult to monitor with traditional LDAR methods. However, the commission has

technical and enforcement concerns associated with the potential regulatory implementation of this technology. A standardized method or pe rformance specification is necessary to ensure consistent and reliable application of optical gas imaging instrumentation. Methods and specifications are also necessary to set minimum standards of performance to evaluate different potential technologies.

The TCEQ uses the optical gas imaging technology as a screening tool in the following areas: offsite surveillance to identify potential sources of contaminants in response to ambient or other monitoring results; identification of sites, or areas with a specific site, where a focused investigation may be conducted; identification of potential source control strategies or to assist in an assessment of existing strategies; and identifi cation of sources for emissions inventory issues.

6.2.2.2 Open Path Sensing Technology Open path sensing technology allows specific pollutants to be monitored over a given distance (10 meters up to several kilometers) and genera lly provides very rapid measurements. Some of these techniques, such as solar occulation flux (SOF), differential absorption lidar (DIAL), and6-2 imaging differential optical absorption spectro scopy (I-DOAS) provide specific capabilities that include the ability to monitor air pollutants not only at ground level but also along a given path length in the sky, which allows measurements of specific elevated sources such as flares, vents, and storage tanks. This information coupled with meteorological measurements and modeling tools are capable, in some cases, of providing emission estimates not otherwise available. These data can be helpful in evaluating actual emi ssions from specific sources. These measurement techniques also have limitations or challenges that include the following.

• They are non-separatory techniques, i.e., do not physically isolate the chemical or chemicals of interest from other constituents, and as such are more prone to interference.

• They normally measure a path length average concentration or number of molecules and as such do not provide a specific concentration at any given point and can thus be difficult to compare with standards or guideline concentrations.

• They are difficult to assess from a data quality standpoint because they are an open path technology and thus have limitations for enforcement or compliance-related purposes.

• They are complex instrumentation with lim ited commercial availability that requires a highly experienced operator and data analyst to obtain quality data. In some cases, such as SOF and DIAL, there may be only a few operational instruments and qualified personnel in the world, which limits the ability of Texas to either acquire and operate the instrumentation or contract operation on anything but a sporadic basis.

6.2.2.3 DIAL Remote Sensing Technology The TCEQ continued to advance the science of determining emissions fro m industrial sources by performing a five-week emissions monitoring study in the Texas City area during the summer of 2007. For the first time, a regulatory agency in the United States used a mobile DIAL remote sensing technology to measure emissions from indus trial sources. The study, funded by the EPA and the TCEQ, focused on gathering data from indus trial sources that are difficult to measure using conventional sampling techniques. The resulti ng scientific data and future studies will help guide future research efforts and may result in additional control measures, refined emissions models for common sources, and improved emissions inventories.

The TCEQ contracted with the National Phys ical Laboratory (NPL), based in the United Kingdom, to perform DIAL measurements on industrial emissions sources located in a refinery and a storage terminal near Houston during 2007.

Measurements focused on those industrial sources th at are difficult to measure using conventional sampling techniques. Specifically, the study involved:

• identifying potentially under-repor ted industrial emissions sources;

• conducting remote sensing measurements of these sources;

• collecting process and operational data from these sources; and

• comparing emissions determined using conve ntional EPA-approved determination methods to the remote sensing measurements.

The NPL submitted a draft report in February 2008, which is expected to be finalized in fall 2009. An independent third party is currently comparing remote sensing measurements to conventionally determined emissi ons. Although these results are still being analyzed, preliminary total VOC measurements indicate that flare emissions may be underreported when emissions are determined using conventional material balan ce calculation methods. Additionally, preliminary

results as well as other research indicate flare d estruction and removal efficiency (DRE) may be reduced during certain operating conditions, such as combusting small volumes of waste gas and during flare air- or steam-assist operations.

These preliminary results indicate the need to c onduct a study that determines the relationship between flare design, operation, and DRE.6-3 6.2.2.4 Helicopter-Mounted DIAL Imaging System The TCEQ completed field work in June 2009 to demonstrate the capabilities of a helicoptermounted DIAL. The study’s major focus will be using the DIAL to locate sources of benzene emissions from industrial facilities in the Houston Ship Channel area. The DIAL system used was developed to detect methane leaks during flyo vers of gas pipelines. The system uses the infrared absorption of methane to detect leaks. The system has been used extensively and successfully to find pipeline leak s in concentrations as low as 1.7 parts per million (ppm) of methane. Instrument sensitivity has been shown in the laborator y to be approximately 100 ppm for benzene. However, with tuning and adju stments during flight measurements, the benzene sensitivity could be as low as 10 ppm. While the primary purpose of this project will be to determine the capabilities of a helicopter-mounted DI AL, results from this project could also be used to determine potentially unreported or underreported sources of benzene. Successful location of benzene sources in the surveyed ar eas may show the potential benefit of a full-scale survey of the entire Houston Ship Channel as well as other industrial areas. A final report is due to the agency by August 2009 and the agency final evaluation of the technology should be completed by the fall of 2009.

6.2.2.5 Flare Study The purpose of the flare study is to measure flare emissions and collect required process and operational data in a controlled laboratory envi ronment to determine the relationship between flare design, operation, and DRE. Direct measurement techniques of flare emissions, conceptually similar to those employed by th e EPA flare studies in the 1980s, as well as remote sensing measurement techniques will be employed in the laboratory environment. Analysis of collected process and operational data will allow comparisons between traditional flare material balance emissions determinations, process stream measurements, and the emissions rates and concentrations measured by the direct and remote sensing technologies.

The TCEQ anticipates that the results of the labor atory tests will be broadly applicable, since

these measurements will be conducted under contro lled conditions. The TCEQ also anticipates that the tests will provide insight to operationa l conditions that may impact flare VOC DRE and flare combustion efficiency, such as assist rates or waste gas volumetric flow rates.

The primary study objectives include:

• assessing the potential impact of waste stream flow rate turndown on flare DRE and combustion efficiency;

• assessing the potential impact of steam/air assist on flare DRE and combustion efficiency at various operating conditions, in cluding low flow rate conditions;

• assessing whether flares operating over the range of requirements stated in 40 Code of Federal Regulations § 60.18 achieve the assumed hydrocarbon DRE of 98 percent at varying flow-rate turndown and assist ratios as well as variable waste stream heat content; and

• identifying and quantifying the hydrocarbon speci es in flare plumes currently visualized with passive infrared cameras.

Field tests should be conducted during the N ovember 2009 to March 2010 time frame, depending on approval of the final test plan and the availab ility of a test facility. A final report is expected during the summer of 2010.

6.2.2.6 Study of Houston Atmospheric Radical Precursors (SHARP) An extensive field study of ozone precursors and formation was conducted in the HGB area in April, May, and June 2009 usi ng cutting-edge measurement te chnology. Approximately $2 million of air quality research funds for this project were provided by the state legislature. The goal of the SHARP study is to investigate the:6-4 • contribution of direct emissions of formalde hyde and nitrous acid from flares, stacks, and other point and mobile sources;

• importance of secondary formation of formal dehyde from the ozonolysis of olefins;

• identification of formation pathways of nitrous acid;

• ambient levels of nitryl chloride and potential impact as a ozone precursor; and

• spring and early summer ozone formation mechanisms in the HGB area.

The data from this study will be analyzed in 2009 and 2010 and used to better understand HGB area emissions and chemistry, enhance model inputs and mechanisms, and aid in the evaluation of control strategy development.

6.3 FUTURE INITIATIVES 6.3.1 Mid-Course Review (MCR) The commission is soliciting comments on whether it is appropriate to perform a 1997 eight-hour ozone standard MCR analysis for the HGB area, and, if so, what elements should be contained in the analysis. The commission is also seeking input on the appropriate date to submit the MCR.

6.3.2 2008 Ozone National Ambient Air Quality Standard (NAAQS) On March 12, 2008, the EPA strengthened its NAAQS for ground-level ozone from 0.08 parts per million (ppm) to 0.075 ppm. Governor Rick Perry submitted the state's recommendation regarding boundaries and designatio ns under the federal 2008 eight-hour ozone standard to the EPA on March 10, 2009. The HGB area (Brazoria, Chambers, Fort Bend, Galveston, Harris, Liberty, Montgomery, and Waller Counties) was included in the governor’s recommended nonattainment areas. Continued efforts to reduce ozone precursors will be necessary to address this new ozone standard.

### Appendices are located at: http://www.tceq.state.tx.us/implementation/air/sip/hgb.html

For persons who do not have access to the Internet, please contact:

Lola Brown

Air Quality Planning Section

Texas Commission on Environmental Quality

Phone: (512) 239-0348