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.us 
Texas Commission on Environmental Quality 

Public Hearings 

Odober 28-29, 2009 

Houston-Galveston-Brazoria (HGB) 

Attainment Demonstration SIP Revision 

for the 1997 Eight-Hour Ozone Standard 

Projed Number 2009-017-SIP-NR 

Volume 2 of2 
REVISION TO THE STATE IMPLEMENTATION PLAN 

FOR THE CONTROL OF OZONE AIR POLLUTION 

HOUSTON-GALVESTON-BRAZORIA 1997 EIGHT-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 

Adopted 

March 10, 2010 
xv

LIST OF APPENDICES 

Appendix Appendix Name

Appendix A Meteorological Modeling for the HGB Attainment Demonstration SIP 

Revision for the 1997 Eight-Hour Ozone Standard 

Appendix B Emissions Modeling for the HGB Attainment Demonstration SIP 

Revision for the 1997 Eight-Hour Ozone Standard 

Appendix C Photochemical Modeling for the HGB Attainment Demonstration SIP 

Revision for the 1997 Eight-Hour Ozone Standard 

Appendix D Reasonably Available Control Technology Analysis 

Appendix E Reasonably Available Control Measure Analysis 

Appendix F Evaluation of Mobile Source 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), Prepared for 

Houston-Galveston Area Council, Prepared by ENVIRON International 

Corporation 

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), Prepared for 

Houston-Galveston Area Council, Prepared by ENVIRON International 

Corporation 

Appendix I Corroborative Analysis for the HGB Attainment Demonstration SIP 

Revision for the 1997 Eight-Hour Ozone Standard 

Appendix J Recommendations for Best Management Practices to Control and 

Reduce Inadvertent Cargo Vapor Emissions in the Tank Barge 

Community 
APPENDIX I: 

CORROBORATIVE ANALYSIS FOR THE HGB ATTAINMENT 

DEMONSTRATION SIP REVISION 

FOR THE 1997 EIGHT-HOUR OZONE STANDARD
This page is intentionally left blank
Appendix I: Corroborative Analysis for the HGB Attainment Demonstration SIP Revision 

for the 1997 Eight-Hour Ozone Standard 

The appendix to Chapter 5 includes three sections. The first section is a detailed description of 

the Chemical Process Analyses that have been performed for the TCEQ photochemical grid 

modeling for 2005-2006. The second section is a detailed model performance evaluation for five 

well-performing episode days. The third section shows the projected future design values when 

using a 2005 baseline emissions inventory. 

Chemical Process Analysis (CPA) of TCEQ Photochemical Grid Modeling 

One of the advanced analyses that can be performed upon photochemical grid modeling is 

chemical process analysis. Standard model evaluations examine the concentrations of reaction 

products of series of chemical reactions, such as ozone, formaldehyde, nitric acid, and others. 

Process analysis allows for examination of the reactions that create these products. The processes 

of radical initiation, propagation and termination can be examined in depth, which can provide 

insights into the model’s sensitivity to VOC and NOX concentrations (Jang et al. 1995, Zhang et 

al. 2004, CAMx User’s Guide, 2008). 

Due to the computational expense and storage demands of process analysis, a limited number of 

days were selected for CPA analysis. Table 1 shows which days were chosen. 

I-3
Table 1. Days Chosen for Chemical Process Analysis; Color-Coded by Flow Regime. 

Date of high 

ozone 

modeled 

Observed 

areawide peak 

8-hr O3 average 

Location of 

daily 

observed peak 

Number of 

sites exceeding 

85 ppb 8-hr 

O3 NAAQS Flow regime 

25-May-05 92.2 WALV 2 Flow reversal 

26-May-05 88 TOMB 1 Steady flow (NE) 

27-May-05 116.8 HNWA 10 Typical veering 

1-Jun-05 92.2 TXCT 3 Steady flow (N) 

2-Jun-05 125.8 CRBL 20 Flow reversal 

21-Jun-05 102.4 TOMB 12 Typical veering 

22-Jun-05 104.4 KATP 17 Typical veering 

23-Jun-05 96.4 HNWA 4 Typical veering 

1-Aug-05 93.7 KATP 6 Flow reversal 

2-Aug-05 104.6 WHOU 10 Flow reversal 

3-Aug-05 92 MEYE 2 Flow reversal 

4-Jun-06 111.7 H07H 13 Flow reversal 

5-Jun-06 109.1 H04H 16 Flow reversal 

6-Jun-06 110.5 CNR2 9 Flow reversal 

8-Jun-06 122.9 BYWC 19 Flow reversal 

9-Jun-06 106.5 BUHV 13 Flow reversal 

10-Jun-06 94.1 CRBL 7 Flow reversal 

12-Jun-06 101.8 DRPK 9 Flow reversal 

13-Jun-06 91.2 MSTG 3 Flow reversal 

14-Jun-06 120.4 TOMB 17 Typical veering 

16-Aug-06 95.5 MERC 6 Flow reversal 

17-Aug-06 113.6 TOMB 14 Typical veering 

18-Aug-06 89.7 KATP 1 Typical veering 

31-Aug-06 127.1 SHWH 14 Typical veering 

1-Sep-06 121.8 DRPK 27 Flow reversal 

6-Sep-06 87.9 CLHS 1 Flow reversal 

7-Sep-06 110.5 BAYP 12 Typical veering 

13-Sep-06 89 MACP 1 Flow reversal 

14-Sep-06 118.9 WHOU 8 Typical veering 

26-Sep-06 87.8 DNCG 1 Flow reversal 

27-Sep-06 90.5 MEYE 2 Flow reversal 

6-Oct-06 95.3 TOMB 3 Steady flow (NE) 

7-Oct-06 87 MACP 1 Steady flow (NE) 

Process rate values were derived by invoking the CPA module in CAMx version 4.53. For each 

receptor site, values were averaged through the depth of the PBL. PBL depth was diagnosed by a 

vertical averaging algorithm developed by Environ, which bases its diagnosed PBL depth on 

changes in the vertical mixing parameter KV. In some circumstances, the effective PBL depth in 

the model will differ somewhat from the diagnosed PBL depth, but diagnosed PBL depth is often 

an acceptable approximation. For the Moody Tower site, the value associated with model layer 

two, in which the top of the tower resides, is used instead of the PBL-averaged value. 

I-4
Progression of ozone formation across the HGB area 

TexAQS 2000 researchers showed that the highest ozone concentrations observed in the HGB 

area can invariably be linked to the industrial plumes emitted in the vicinity of the Houston Ship 

Channel (Daum et al., 2003,2004; Ryerson et al., 2003). These results are consistent with TCEQ 

case studies of ozone episodes in the HGB area (TCEQ Significant Events web page, 2009), and 

with subsequent analyses during TexAQS II (Gilman et al., 2009; de Gouw et al., 2009). In the 

HGB area, one common flow regime during ozone episodes is the typical veering pattern (TCEQ 

Conceptual Model, 2009). During a typical veering episode, the day begins with light winds from 

the northeast, which carry the industrial plumes from the Houston Ship Channel area to the 

southwest. Ozone begins forming in these concentrated plumes. During the day, the winds shift 

to the southeast, and then to the south or south-southwest. Consequently, the ozone is carried 

across southern and southwestern Harris County, across western Houston, to northwest Harris 

County. This typical flow pattern results in high ozone along a chain of monitors, beginning in 

the Houston Ship Channel area, and ending in western Harris County. The monitors experience 

the ozone plume during different times in its development, with the easternmost monitors 

observing fresh emissions and rapid ozone formation, and the westernmost observing the highest 

ozone concentrations, but the lowest ozone formation rates. This progression of ozone formation 

can be witnessed with process analysis of the model output. 

Three high ozone days have been chosen to illustrate the evolution of high ozone in the HGB 

area, June 21-23, 2005. All three of these days are classified as typical veering days, but there are 

some important differences among them. Figures 1-3 show the 12-hour forward trajectories for 

all three days, starting at 0800. The trajectories on June 21 have the southernmost path, June 22 

is slightly more northerly, and June 23 is almost northwest in orientation, pushing the industrial 

plumes through the urban core on the way to northwestern Harris County. As the process 

analysis will show, the different pathways affect the ozone formation process in important ways. 

The differing ozone behavior on these three days is first illustrated by examining the diurnal 

variation in ozone concentration for each day at all HGB area monitoring sites. Figures 4-6 show 

5-minute ozone averages for the three days. June 21 and June 22 are relatively similar, though 

the background ozone appears to be slightly higher on June 22. June 23, however, has some large 

ozone peaks that do not occur on the other two days. The largest of these peaks is observed at the 

West Houston (WHOU) monitor, and the other large peaks are near that monitor. Also note that 

the WHOU peak occurs earlier in the day in comparison to the peak concentrations observed on 

June 21-22. All three days have some early peaks at monitors in the vicinity of the Houston Ship 

Channel. 

I-5
I-6

' '., 

\ ... 

Daily Max 8hr 03 ppb 

ar monitors 

• 1)0 + 

• 95 to< 1)0 

• 90 to < 95 

• 85 to < 90 

• 80 to < 85 

• 75 to < 80 

0 < 75 

MetStat: ObseNed 

MetStat: ep1.eta.dbemis.fddats.newuhsstnewutcsriulc.grell 

Forward Trajectories 2005-06-21 

Max 8hr 03 (monitored): 102.4 at: TOMB 

MetStat: ObseNed 

Start time: 08:00 

8Hr frame: 1000-1700 

Daily Max 8hr 03 ppb 

ar monitors 

• 1)0 + 

• 95 to< 1)0 

• 90 to < 95 

• 85 to < 90 

• 80 to < 85 

• 75 to < 80 

0 < 75 

MetStat: ep1.eta.dbemis.fddats.newuhsstnewutcsriulc.grell 

Forward Trajectories 2005-06-22 

Max 8hr 03 (monitored): 104.4 at: KATP 

Start time: 08:00 

8Hr frame: 1100-1800 
Figures 1-3. Transport in the HGB area on June 21-23, 2005. Modeled transport is in blue, 

observed is in red. The forward trajectories begin at 0800 and proceed for 12 hours. 

I-7
June 21, 2005 5-min ozone

0

20

40

60

80

100

120

140

160

180

0:00 4:00 8:00 12:00 16:00 20:00

ppb

June 22, 2005 5-min ozone

0

20

40

60

80

100

120

140

160

180

0:00 4:00 8:00 12:00 16:00 20:00

ppb

Figures 4-6. Five-minute ozone data for June 21-23, 2005, for all HGB area ozone monitors. 

June 23, 2005 5-min ozone

0

20

40

60

80

100

120

140

160

180

0:00 4:00 8:00 12:00 16:00 20:00

ppb

WHOU

DRPK

I-8
To study the evolution of ozone formation during June 21-23, 2005, CPA data for three different 

areas in Houston have been examined. The first area is in eastern Harris County, in the vicinity 

of the industrial emission sources that apparently are the source of the highest plumes of ozone 

observed in Houston on these days. The second area is in central Houston, between the emission 

source area and the peak ozone area. Much of the ozone is formed in this area during June 21-23. 

The third area is where the peak ozone concentrations were observed, in western Houston. 

Figure 7. Map of ozone monitoring sites in Houston. The typical veering pattern of wind flow is 

approximately indicated by the arrow. 

Figure 8 shows one-hour ozone concentration observed at the Deer Park (DRPK) site in eastern 

Harris County, at the Houston Monroe (HSMA) and Houston Regional Office (HROC) sites in 

central Houston, and at the Tom Bass (TOMB), West Houston (WHOU) and Katy Park (KATP) 

I-9
sites in western Houston. The progression of ozone peaks differs slightly on each day. On June 

21, ozone peaks successively at DRPK, HSMA, TOMB, WHOU and KATP. On June 22, ozone 

peaks again successively at DRPK, HSMA, TOMB, WHOU and KATP, though the DRPK, 

HSMA, and TOMB peaks occur almost simultaneously. On June 23, ozone peaks successively at 

DRPK, HROC, HSMA, TOMB, WHOU and KATP, with the HROC, HSMA and TOMB peaks 

occurring almost simultaneously. In addition, the WHOU peak is much greater on June 23 than 

any other peak during the three days, and is much greater than the peaks earlier in the day, in 

spite of the lower background ozone on this day. The ozone data presented here suggests that it 

would be useful to examine ozone production at these selected monitoring sites. 

0

20

40

60

80

100

120

140

160

0:00 6:00 12:00 18:00 0:00 6:00 12:00 18:00 0:00 6:00 12:00 18:00

Ozone, ppb

DRPK

HROC

HSMA

WHOU

TOMB

KATP

June 21 June 22 June 23

Figure 8. One-hour ozone concentrations observed at selected sites, June 21-23, 2005. 

CPA can be used to examine the rate at which O3 is being created and destroyed, and to examine 

the environment in which O3 creation occurs. CPA will allow examination of the sensitivity of 

ozone formation to NOX or VOC availability along the entire path from emission area to peak 

ozone area. Figures 9-15 present modeled diurnal O3 production for June 21-23, 2005, for the 

selected sites in eastern, central, and western Harris County. Because these figures present 

unfamiliar information, a detailed explanation of Figure 9 (the Deer Park site) is presented below. 

I-10
DRPK, Ox production, June 2005 CPA

-10

-5

0

5

10

15

20

25

30

0369

12151821

0369

12151821

0369

12151821

ppb/hr

OxProd

OxLoss

PO3_net

PO3_VOCsns

PO3_NOxsns

Figure 9. Odd oxygen (Ox) production at the Deer Park monitor, June 21-23, 2005. 

OxProd refers to production of odd oxygen, which is approximately equal to O3 + NO2. In the 

ozone production cycle, O3 and NO2 essentially trade an oxygen atom back and forth, creating 

and destroying O3, NO2, and NO, until a radical termination reaction pulls the odd oxygen out of 

the cycle. 

OxLoss refers to destruction of odd oxygen, i.e., the sum of all radical termination reactions that 

pull the odd oxygen out of the ozone production cycle. 

PO3net refers to the net production of ozone. This quantity is usually positive during daylight 

hours, but can be negative at night. 

PO3_VOCsns refers to the amount of ozone produced under VOC-sensitive conditions, i.e., in an 

environment rich in NOx. If VOC were removed from this environment, ozone formation would 

decrease. 

PO3_NOxsns refers to the amount of ozone produced under NOx-sensitive conditions, i.e., in a 

NOx-poor environment. If NOx were removed from this environment, ozone formation would 

decrease. 

The ozone formation environment, VOC-sensitive or NOX-sensitive, is diagnosed in CAMx by 

the Chemical Process Analysis algorithms by determining the ratio of hydrogen peroxide 

production to nitric acid production (Sillman, 1995; CAMx User’s Guide, 2008). If this ratio 

exceeds 0.35, the environment is usually NOX-sensitive, because the VOC and/or radicals are in 

such abundance that the HO2 radicals formed by VOC oxidation are reacting vigorously with 

each other. If the ratio is less than 0.35, the environment is usually VOC-sensitive, because NO2

is in such abundance that it is destroying OH radicals to form nitric acid. In either case, the 

radicals are being removed from the ozone formation pathway. 

I-11
The ozone production sensitivity determined by PO3_VOCsns and PO3_NOxsns reflect what has 

occurred during the preceding hour. When examined at a single site or a single hour, these data 

alone cannot give fully accurate directional guidance on control strategies for the nonattainment 

area, because the ozone behavior at a single site may not be related to the peak areawide ozone. 

The Deer Park monitoring site encountered industrial plumes shortly after they had been emitted 

on June 21-23, and VOC-sensitive ozone production is quite vigorous in the morning hours, but 

ozone production shifts to NOX-sensitive by noon. Figures 10-12 show Ox production for three 

monitors in central Houston (Park Place, Houston Monroe, and Houston Regional Office), which 

encountered the plumes after they had aged for a few hours. Figures 13-15 show Ox production 

from three western Houston monitors that observed high ozone (Tom Bass, Katy Park, West 

Houston). 

PRKP, Ox production, June 2005 CPA

-10

-5

0

5

10

15

20

25

30

0369

12151821

0369

12151821

0369

12151821

ppb/hr

OxProd

OxLoss

PO3_net

PO3_VOCsns

PO3_NOxsns

Figure 10. Modeled Ox production at Park Place site, June 21-23, 2005. 

On June 21, Figures 9-15 show that ozone formation is more vigorous along a southerly path, 

from DRPK to HSMA to TOMB to KATP. The northerly path, through PRKP, HROC, and 

WHOU, shows lower overall ozone production rates. Each site shows VOC-sensitive ozone 

formation in the morning hours, and NOX-sensitive formation in the afternoon. However, the 

largest ozone production rates are associated with VOC-sensitive ozone formation. At PRKP, 

TOMB, and WHOU, the net ozone production rate drops when the chemistry switches from 

VOC-sensitive to NOX-sensitive ozone formation. By the time the ozone reaches KATP, ozone 

formation is much slower, and is dominated by NOX-sensitive formation. 

On June 22, ozone formation progresses in a similar manner to June 21, except that the PRKP and 

TOMB monitors both show large VOC-sensitive ozone formation peaks. Ozone formation at the 

WHOU and KATP monitors is modest, and dominated by NOX-sensitive ozone formation. 

On June 23, ozone formation behavior is somewhat different from June 21-22. The HSMA and 

TOMB monitors show relatively low ozone formation rates, with NOX-sensitive formation for 

I-12
HSMA, Ox production, June 2005 CPA

-10

-5

0

5

10

15

20

25

30

0369

12151821

0369

12151821

0369

12151821

ppb/hr

OxProd

OxLoss

PO3_net

PO3_VOCsns

PO3_NOxsns

Figure 11. Modeled Ox production at Houston Monroe site, June 21-23, 2005. 

HROC, Ox production, June 2005 CPA

-10

-5

0

5

10

15

20

25

30

0369

12151821

0369

12151821

0369

12151821

ppb/hr

OxProd

OxLoss

PO3_net

PO3_VOCsns

PO3_NOxsns

Figure 12. Modeled Ox production at Houston Regional Office site, June 21-23, 2005. 

I-13
TOMB, Ox production, June 2005 CPA

-10

-5

0

5

10

15

20

25

30

0369

12151821

0369

12151821

0369

12151821

ppb/hr

OxProd

OxLoss

PO3_net

PO3_VOCsns

PO3_NOxsns

Figure 13. Modeled Ox production at Tom Bass site, June 21-23, 2005. 

WHOU, Ox production, June 2005 CPA

-10

-5

0

5

10

15

20

25

30

0369

12151821

0369

12151821

0369

12151821

ppb/hr

OxProd

OxLoss

PO3_net

PO3_VOCsns

PO3_NOxsns

Figure 14. Modeled Ox production at West Houston site, June 21-23, 2005. 

I-14
KATP, Ox production, June 2005 CPA

-10

-5

0

5

10

15

20

25

30

0369

12151821

0369

12151821

0369

12151821

ppb/hr

OxProd

OxLoss

PO3_net

PO3_VOCsns

PO3_NOxsns

Figure 15. Modeled Ox production at Katy Park site, June 21-23, 2005. 

much of the day. The WHOU and KATP sites show much higher ozone formation rates than the 

two previous days, and at the HROC site, ozone formation is dominated by VOC-sensitive 

formation rather than NOX-sensitive. 

One of the causes for these ozone formation differences can be seen by examining Figures 1-3, 

which show how emissions from different parts of the HGB area are transported during 8:00am8:00pm on each day, respectively. On June 21-22, the industrial plumes are carried 

southwesterly, to the south of the urban core. Consequently, high ozone and high VOC-sensitive 

ozone production are seen along the trajectory paths that originated in the industrial areas. On 

June 23, however, the industrial emissions are carried due west, through the urban core, passing 

over the HROC, WHOU, and KATP sites. In both cases, the sites that encounter the industrial 

plumes have the highest ozone formation rates, and those that do not have lower ozone formation 

rates. The modeling on June 23 suggests that when the industrial plume mixes with the urban 

core plume, vigorous VOC-sensitive ozone formation can occur. Figures 4-6 show the 

consequences of higher ozone formation rates—ozone concentrations at WHOU and KATP are 

much higher on June 23 than any other observations during the other two days. 

Figures 16-20 show the modeled formaldehyde formation rates at sites with enhanced ozone 

formation. Formaldehyde formation is higher at sites closer to the industrial areas, and decreases 

as the emissions age. For sites unaffected by industrial plumes, HCHO formation is much lower, 

and is dominated by biogenic species. For sites affected by industrial plumes, even on the 

western side of Houston, HCHO formation is high, and anthropogenic HRVOC (ETH, OLE, and 

IOLE) are the major source of HCHO. 

Figures 21-25 compare the observed formaldehyde concentrations at three sites to the model 

output. At Moody Tower, the simulated formaldehyde matches the observed diurnal variations 

and the absolute magnitude most of the time, but misses the highest peaks, which is similar to the 

model’s ozone performance. At LYNF and H03H, the simulated formaldehyde is consistently 

underestimated. At LYNF, the diurnal variations match the observations relatively well, but at 

I-15
H03H, the modeled concentrations peak at rush hour, whereas the observed concentrations peak 

in the afternoon. The modeled formaldehyde appears to be associated with primary mobile 

source emissions, but the observed formaldehyde is consistent with secondary formation. Note 

also that the formaldehyde performance is considerably better at Moody Tower, an elevated 

location, than at the two ground-based sites, suggesting that vertical mixing may be playing a role 

in these differences. 

I-16
DRPK HCHO production from VOCs

0

0.5

1

1.5

2

2.5

0369

12151821

0369

12151821

0369

12151821

ppb/hr

HCHOp_ispd

HCHOp_isop

HCHOp_terp

HCHOp_iole

HCHOp_ole

HCHOp_eth

Figure 16. Formaldehyde production (HCHOp) from HRVOC and biogenic CB05 species at 

eastern site DRPK for June 21-23, 2005. 

HSMA HCHO production from VOCs

0

0.5

1

1.5

2

2.5

0369

12151821

0369

12151821

0369

12151821

ppb/hr

HCHOp_ispd

HCHOp_isop

HCHOp_terp

HCHOp_iole

HCHOp_ole

HCHOp_eth

Figure 17. Formaldehyde production (HCHOp) from HRVOC and biogenic CB05 species at 

central site HSMA for June 21-23, 2005. 

I-17
HROC HCHO production from VOCs

0

0.5

1

1.5

2

2.5

0369

12151821

0369

12151821

0369

12151821

ppb/hr

HCHOp_ispd

HCHOp_isop

HCHOp_terp

HCHOp_iole

HCHOp_ole

HCHOp_eth

Figure 18. Formaldehyde production (HCHOp) from HRVOC and biogenic CB05 species at 

central site HROC for June 21-23, 2005. 

TOMB HCHO production from VOCs

0

0.5

1

1.5

2

2.5

0369

12151821

0369

12151821

0369

12151821

ppb/hr

HCHOp_ispd

HCHOp_isop

HCHOp_terp

HCHOp_iole

HCHOp_ole

HCHOp_eth

Figure 19. Formaldehyde production (HCHOp) from HRVOC and biogenic CB05 species at 

western site TOMB for June 21-23, 2005. 

I-18
WHOU HCHO production from VOCs

0

0.5

1

1.5

2

2.5

0369

12151821

0369

12151821

0369

12151821

ppb/hr

HCHOp_ispd

HCHOp_isop

HCHOp_terp

HCHOp_iole

HCHOp_ole

HCHOp_eth

Figure 20. Formaldehyde production (HCHOp) from HRVOC and biogenic CB05 species at 

western site WHOU for June 21-23, 2005. 

Figures 21-22. Modeled and observed formaldehyde concentrations at Moody Tower (MDTW) 

during the August-October 2006 episode days. 

I-19
Figures 23-25. Modeled and observed formaldehyde data at LYNF and H03H for the AugustOctober 2006 episode days. Data for the August 15 - September 14 period at H03H are not 

shown, because only one complete day of data is available for that period at H03H. 

I-20
Another method of examining the characteristics of the air masses associated with high ozone 

formation rates is to look at the rate of OH oxidation rates, also known at OH reactivity. Figures 

26-28 show the OH reactivity for eastern, central and western sites in the HGB area. At each site, 

the OH reactivity is highest when ozone production is the highest, and when the site is 

encountering the industrial plumes. The site nearest the industrial areas, DRPK, shows the largest 

proportion of OH reactivity from alkenes of the three sites. 

DRPK June 21-23, 2005

0

1

2

3

4

5

6

7

8

9

10

0 6 12 18 0 6 12 18 0 6 12 18

OH reactivity

OVOCs

aromatics

alkenes

alkanes

NOx

CO

Figure 26. OH reactivity (second-1) modeled at eastern site DRPK on June 21-23, 2005. 

TOMB June 21-23, 2005

0

1

2

3

4

5

6

7

8

9

10

0 6 12 18 0 6 12 18 0 6 12 18

OH reactivity

OVOCs

aromatics

alkenes

alkanes

NOx

CO

Figure 27. OH reactivity (second-1) modeled at western site TOMB on June 21-23, 2005. 

I-21
WHOU June 21-23, 2005

0

2

4

6

8

10

12

14

16

0 6 12 18 0 6 12 18 0 6 12 18

OH reactivity

OVOCs

aromatics

alkenes

alkanes

NOx

CO

Figure 28. OH reactivity (second-1) modeled at western site WHOU on June 21-23, 2005. 

For the case study of June 21-23, 2005, the CPA tool is useful in examining why ozone formation 

on these three days behaved differently. Based upon this case study, and examination of CPA 

data for other days (not shown here), several conclusions can be reached about the model 

behavior. 

 Ozone formation occurs in both VOC-sensitive and NOX-sensitive conditions each 

episode day at many sites within the HGB area, with VOC-sensitive conditions 

dominating in the morning hours, and NOX-sensitive conditions dominating in the 

afternoon. 

 Vigorous ozone formation in VOC-sensitive conditions is closely associated with 

industrial plumes, both in the immediate vicinity of the emission sources, and downwind 

in the areas that experience the highest ozone. Relatively high formaldehyde formation 

rates from anthropogenic alkenes and high OH reactivity from alkenes are also associated 

with industrial plumes. 

 In general, VOC-sensitive ozone formation appears more vigorous than NOX-sensitive 

formation. When ozone formation shifts from VOC-sensitive to NOX-sensitive, the 

formation rate often drops considerably. 

 On June 23, the industrial plumes are advected through the urban core; the mixing of 

urban core emissions and industrial emissions appear to increase VOC-sensitive ozone 

formation in western Houston. 

I-22
Comparison of CAMx grid modeling to TexAQS II box modeling 

During TexAQS II, researchers monitored many species not routinely measured in Houston, and 

these data are useful in model evaluation, including OH, HO2, HONO, HCHO, HNO3 and other 

species (Mao et al., 2009; Chen et al., 2009). The researchers used a constrained photochemical 

steady-state box model to calculate the radical budgets at the Moody Tower site for each hour, 

based upon measured concentrations for August 17 – September 28, 2006. Mao et al. (2009) 

investigated the radical production rates for the Carbon Bond 2005 (CB05) and Regional 

Atmospheric Chemical Modeling (RACM) chemical mechanisms; Chen et al. (2009) built upon 

their work, and added modeling with four more chemical mechanisms: the Master Chemical 

Mechanism (MCM), State Air Pollution Research Center (SAPRC) mechanisms from 1999 and 

2007, and the Langley Research Center (LaRC) mechanism. 

Presented below is a comparison of the CAMx CPA radical budget to the radical budget 

calculated by Mao et al. and Chen et al. These comparisons should be considered with several 

important qualifications. First, the Mao et al. and Chen et al. results are based upon point 

measurements, which have been fed into a box model to constrain the chemistry to the 

observations, whereas the CPA results have been obtained by extracting the values from Layer 2 

for the 2km x 2km grid cell containing the Moody Tower site. The results from these two types 

of modeling probably have unexamined commensurability problems. Second, the results from 

the journal articles have been averaged for the entire sampling period, August 17 – September 28, 

which includes high and low ozone days, whereas the CPA results are from specific high ozone 

days only. Third, these results are based upon a photochemical steady-state box model, and 

constrained by the observed concentrations at the Moody Tower. The chemical environment at 

the Moody Tower, however, may not always be in a photochemical steady-state, which could bias 

the results of the model. 

Figure 29 shows the CPA radical budget for August 16, 2006. Figure 30 shows the same radical 

reactions for the CB05 constrained steady-state box modeling results, averaged over the TexAQS 

II measurement period (Mao et al., 2009). 

Radical Production 

Radical production rates (PHOX) are similar in magnitude and timing for both the CPA and Mao 

et al. results, with CPA rates slightly higher. The Mao box modeling indicates that HONO + h, 

O1D + H2O, and HCHO + h have similar rates, whereas the CPA results indicate that O1D + 

H2O rates are much higher than the other two reactions. The HCHO + h rate is about the same 

in both models, but the HONO + h rate is much lower in CPA. Therefore, underestimation of 

HONO photolysis is probably due to underestimated HONO concentrations, not errors in the 

predicted solar radiation. Figure 31 shows that at the Moody Tower, where HONO was measured 

during TexAQS II, the CAMx model consistently underestimated HONO concentrations. 

Modeled daytime OH production from photolysis of HONO does not exceed 0.2 ppb, well below 

the observed concentrations. Since modeled concentrations of HONO are consistently 

underestimated, it is not surprising that little OH radical is produced by this pathway. The 

standard model chemistry removes HONO rapidly by photolysis, and does not produce it in large 

enough quantities to explain the observed concentrations. Other researchers have found similar 

results (Sarwar et al., 2008; Kleffman et al., 2003, 2005; Acker et al., 2006; Zhou et al., 2003). 

Ziemba et al. (2009) have shown that daytime HONO concentrations at the Moody Tower during 

TexAQS II exceeded the expected concentrations based upon the current chemical mechanisms, 

and suggested that a HONO formation path has been left out of the existing chemical 

mechanisms. They hypothesize a new path that involves reactions of nitric acid on the surfaces 

I-23
of aerosols, and photolysis, to generate HONO. The proposed mechanism for HONO production 

is still in the early stages of investigation; it cannot be used to quantitatively estimate the missing 

source of HONO. 

Figure 32 shows the predicted OH and HO2 concentrations from seven different chemical 

mechanisms, including CB05; all of the mechanisms underestimate midday radical 

concentrations. While adding the missing HONO formation path(s) may help alleviate the 

underestimations in the mechanisms, note that there are many other hypotheses for the shortfall in 

radical production. These other hypotheses for the shortfall in radical formation include isoprene 

production of hydroxyl radical (OH) (Lelieveld et al., 2008; North and Ghosh, 2009); formation 

and decomposition of electronically excited nitrogen dioxide (NO2

*

) (Li et al., 2008); nitryl 

chloride (ClNO2) chemistry (Osthoff et al., 2008; Simon et al., 2008); alternative 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). None of these 

hypotheses have been adequately tested yet, and many of the proposed mechanisms for correcting 

the model chemistry are still speculative. TCEQ has refrained from experimenting with any of 

these hypotheses in its current round of modeling. 

Radical termination 

The relative rates at which radicals are terminated have been used to indicate whether the ozone 

formation is sensitive to NOX or to VOC (or radical) availability (Sillman, 1995). The radical 

termination rate OH+NO2 is indicative of nitric acid formation and VOC-sensitive ozone 

formation; the terminations HO2+HO2 and HO2+RO2 are indicative of peroxide formation and

NO

t 

ive 

AMx modeling. 

X-sensitive ozone formation. These reactions are depicted on Figures 29 and 30. Both 

models indicate that OH+NO2 termination is higher between sunrise and 1300, when OH+NO2

rates drop and HO2+HO2 rates increase. The transition between VOC-sensitive and NOXsensitive ozone formation occurs when the ratio (HO2+HO2)/(OH+NO2) is greater than abou

0.35 (Sillman, 1995). The transition appears to occur for both the model and monitored 

observations at about noon. For most monitoring sites in Houston, the shift from VOC-sensit

to NOX-sensitive ozone formation occurs every day. The Moody Tower box modeling indicates 

that the apparent shift from VOC-sensitive to NOX-sensitive conditions is not an artifact of the 

C

I-24
-4

-2

0

2

4

6

0 612 18

107 molecules / cm3 / sec

PHOx

O1D+H2O

HONO+hv

O3+alkenes

HCHO+hv

HO2+HO2

LHOx

HO2+RO2

OH+NO2

 

Figures 29 and 30. Modeled radical budget from CAMx CPA results for August 16, 2006 (top). 

Median CB05 results at Moody Tower, August 17 – September 28, 2006 (bottom). Units on this 

graph are molecules per cm3

 per second. Bottom figure is excerpted from Mao et al., 2009. 

I-25
Figure 31. Observed nitrous acid (HONO) concentrations, compared to modeled concentrations 

at the Moody Tower site during August 15 - September 14, 2006.

Figure 32. Diurnal Variation in OH and HO2 Radical Concentrations on September 2, 2006. 

Concentrations observed at Moody Tower during TexAQS II, and modeled by CB05, RACM, 

LaRC, SAPRC-99, SAPRC-07, and MCMv3.1 chemical mechanisms run in a constrained box 

model. Figure reproduced from Chen et al., 2009.

I-26
-6

-4

-2

0

2

4

6

8

0 6 12 18 0 6 12 18 0 6 12 18 0 6 12 18 0 6 12 18 0 6 12 18 0 6 12 18 0 6 12 18 0 6 12 18

107 molecules / cm3 / sec

PHOx

O1D+H2O

HONO+hv

O3+alkenes

HCHO+hv

HO2+HO2

LHOx

HO2+RO2

OH+NO2

Aug 16 Aug 17 Aug 18 Aug 31 Sep 1 Sep 6 Sep 7 Sep 12 Sep 14

Figure 33. Modeled radical budget for Moody Tower for high ozone days during TexAQS II. 

Figure 34. Comparisons of Radical Budgets Estimated from Measurements of OH, HO2, and 

Other Species During Field Campaigns in Houston, New York City, and Mexico City. 

I-27
Figure 33 shows the diurnal variations in radical budget at the Moody Tower site for nine days 

modeled by TCEQ. The ozone production and loss rates vary by about a factor of two during 

these days. Most of the days show a transition from VOC-sensitive to NOX-sensitive ozone 

formation at about noon, based upon the relatively large OH+NO2 termination rates early in the 

day, and the relatively large HO2+HO2 and HO2+RO2 rates in the afternoon. Note that Moody 

Tower did not encounter the industrial plumes every day, so that the production rates and 

sensitivities differ according to the origin of the plumes. The absolute magnitudes compare well 

to those calculated by Mao et al. in Figures 30 and 34. 

Figure 34 shows the radical behavior in Houston in 2000 (TexAQS 2000) and 2006 (TRAMP 

2006). It isn’t immediately apparent from this analysis whether the differences between the two 

years is due to the differing locations of the monitoring sites in 2000 and 2006, or due to areawide 

emission or meteorological differences between the two years. In 2000, radical measurements 

were made at La Porte, which is a site very near the heavily-industrialized areas of the Houston 

Ship Channel and Galveston Bay. Figure 34 shows that VOC-sensitive ozone formation 

conditions prevailed at La Porte for the entire day, on average, in 2000. The VOC-sensitive 

conditions are characterized by the dominance of the OH+NO2 termination reaction in the upper 

left panel of Figure 34. By contrast, the lower right panel shows the radical termination behavior 

during TexAQS II in 2006, at the Moody Tower. The Moody Tower site is located on the 

University of Houston campus, in close proximity to major highways, and to the central business 

district. It is, however, close enough to the Ship Channel to be affected by industrial plumes 

fairly often. Its radical behavior is somewhat different from that observed at La Porte in 2000, in 

that the ozone formation conditions begin as VOC-sensitive and switch to NOX-sensitive about 

noon. The CPA results presented in the June 21-23, 2005 case study above, and other CAMx 

simulations for 2005-2006 show that VOC-sensitive ozone formation are closely associated with 

areas that encounter the industrial plumes, which would occur more frequently at La Porte than at 

Moody Tower. While it is possible that this difference between the Moody Tower 2006 data and 

the La Porte 2000 data represents a change in the chemical environment due to emission 

reductions since 2000, it seems as likely that sampling within a different chemical environment in 

Houston is responsible for the difference. 

Radical Propagation 

OH chain length is a measure of how many times OH is recreated before it is consumed by a 

termination reaction with NO2. It is an indication of the strength of radical propagation. Figure 

35 shows that OH chain length is particularly long at the Moody Tower site during TexAQS II. 

Long OH chain length implies that ozone production can occur very rapidly and effectively. 

However, long chain length is also associated with low-pollution environments. Figure 36 shows 

three days during June 2006 at the Bayland Park monitor. On the first two days, OH chain length 

peaks between 10 and 20, as ozone concentrations reach greater than 120 ppb. However, on June 

10, the OH chain length peaks at over 45, whereas the ozone concentrations peak at only about 80 

ppb. This pattern is common in Houston modeling; the very highest OH chain length is 

associated with air that is less polluted. The high median OH chain length measured by Mao et 

al. may be a sign that the air in Houston simply was less polluted during TexAQS II than during 

the TexAQS 2000 field study in Houston. Concentration data for ozone, NOx, formaldehyde, 

ethene, and other species confirm that the air was less polluted in Houston in 2006 than in 2000 

(Mao et al., 2009; TCEQ Conceptual Model, 2009; de Gouw et al., 2009). 

I-28
Figure 35. OH Chain Length During TexAQS II, as Measured at the Moody Tower 

(TRAMP2006). The long chain length implies that OH propagation was particularly efficient at 

Moody Tower during TexAQS II, compared to TexAQS 2000 at La Porte, or New York City, or 

Mexico City. 

BAYP, O3 production, June 2006 CPA

-10

0

10

20

30

40

50

0 6 12:00

June 8

18 0 6 12:00

June 9

18 0 6 12:00

June 10

18

ppb/hr

PO3_VOCsns

PO3_NOxsns

0

20

40

60

80

100

120

Mao CL 140

modeled O3

observed O3

Figure 36. Ozone Production and Concentrations at the Bayland Park Monitor, June 8-10, 2006. 

The “Mao CL” variable is the OH chain length, as calculated in Mao et al., 2009. The axis on the 

right is for OH chain length (unitless), and ozone production rates (ppb/hour); the axis on the left 

is for modeled and observed ozone concentrations (ppb). 

I-29
BAYP, Ox production, June 21-23, 2005

-10

-5

0

5

10

15

20

25

30

0369

12151821

0369

12151821

0369

12151821

ppb/hr

0

5

10

15

20

25

30

35

40

OxProd

PO3_net

PO3_VOCsns

PO3_NOxsns

JNO2

Figure 37. Ozone Production Rates, and NO2 Photolysis Rates, for BAYP, June 21-23, 2005. 

hows 

iazar 

 The 

ver, indicates that an accurate 

epiction of clouds is important to the model performance. 

indings from chemical process analysis 

e ozone 

d urban 

ive conditions appears to be more 

related to the shortfall in peak modeled eight-hour ozone concentrations. Due to the 

Photolysis 

Process analysis shows the importance of accurately modeling photolysis rates. Figure 37 s

how ozone production rates are directly correlated with NO2 photolysis. In this case, NO2

photolysis probably is correlated with all of the other relevant photolysis rates as well, so that the 

modeled dependence reflects sensitivity to all photolysis reactions, not just JNO2. This finding is

consistent with the findings of Koo et al., 2008, who used higher-order decoupled direct method 

(HDDM) analysis to test the sensitivity of the modeled ozone to all photolysis rates. Pour-B

et al. (2006) found in their modeling of Houston that modeled ozone performance could be 

substantially improved by assimilating satellite-derived cloud cover data into the modeling.

sensitivity of the model to photolysis, and hence, to cloud co

d

F

 Both VOC-sensitive ozone formation and NOX-sensitive ozone formation occur in 

Houston every day, with VOC-sensitivity tending to occur in the morning and NOXsensitivity in the afternoon. The radical data collected at the Moody Tower during

TexAQS II and the constrained steady-state box modeling indicate that th

formation behavior modeled in CAMx is actually occurring in Houston. 

 VOC-sensitive conditions occur more often and more strongly in the industrial an

core plumes. Ozone production in VOC-sensit

productive than in NOX-sensitive conditions. 

 The modeled shortfall in OH radical production is common to more than one chemical

mechanism, not just Carbon Bond 05. The shortfall in radical production is probably 

I-30
 Radical production from photolysis of HONO very low in the CAMx modeling, but not 

in the box modeling. The current chemical mechanisms do not have a path for producing 

the observed quantities of HONO during the daylight hours. The lack of daytime HONO 

could be one of the missing radical sources needed to improve the OH radical budget, but 

further studies in Houston are needed to describe the missing HONO formation pathway. 

 OH chain length was much longer in 2006 than in 2000, possibly because the air was 

cleaner in 2006. 

 Decreases in ozone production rates and other reaction rates correlate with decreases in 

NO2 photolysis, implying that most of the ozone formation chemistry is highly sensitive 

to photolysis, and hence, highly sensitive to cloud cover errors. 

I-31
 Intensive Model Performance Evaluation 

To examine the model performance in greater depth, case study analyses have been done for 

several high ozone days: June 2, 2005; June 23, 2005; June 5, 2006; August 16, 2006; and 

September 14, 2006. On these days, the model appears to have good meteorological 

performance, and therefore difficulties with chemistry or emissions can perhaps be diagnosed 

more easily on these days than on days that have meteorological difficulties as well. 

June 2, 2005 Episode 

On Thursday, June 2, 2005, high concentrations of ozone were observed throughout the Houston 

area, but were particularly high in northeast Harris and Montgomery Counties. One-hour 

maximum ozone concentrations of 148 ppb were observed at Crosby Library (CRBL) at 1500; six 

additional sites exceeded 125 ppb on this day. An areawide eight-hour maximum ozone 

concentration of 125.8 ppb was observed at CRBL from 1000-1700; 20 other sites exceeded the 

85-ppb eight-hour ozone standard on this day. A flow reversal occurred on this day, with 

stagnant conditions prevailing early, and then winds picking up from the south and then shifting 

to southeast. 

According to the TCEQ Conceptual Model analyses, daily flow regime in Houston is one of the 

factors that determines whether an ozone exceedance occurs, where the highest ozone 

concentrations are observed, and how high the concentrations reach. 

Figure 1 shows the flow occurring in Houston on the afternoon and evening of June 1, 2005, 

before the large exceedance on the next day. Trajectories indicate that winds from the previous 

day are from the north, carrying the day’s emissions to the south of Harris County. The next 

morning is almost completely stagnant. Figure 2 shows that the winds shift direction and begin 

blowing onshore. Due to the wind shift, it is likely that pollutants from the previous day are 

carried back into Houston. Winds continue from the S for much of the afternoon, carrying the 

urban core and industrial plumes to the north, and creating very high ozone in NE Harris County 

and in Montgomery County. 

I-32
Figure 1. Trajectories Calculated from MM5 Output and Observed Surface Wind Monitors. 

MM5 output is shown in blue; monitored observations are shown in red. Winds on the afternoon 

of June 1 are northerly, but become stagnant toward the end of the trajectory period, as indicated 

by endpoints that are very close together. 

Figure 2. Trajectories Calculated from MM5 Output and Observed Surface Wind Monitors. 

MM5 output is shown in blue; monitored observations are shown in red. The emissions from the 

previous day are carried north, back over Houston, creating a large area of high ozone both 

upwind and downwind of Houston. 

I-33
Figure 3. Scatter Plot for Areawide Average Wind Speeds in the Houston-Galveston Area for 

June 2, 2005. 

Figure 3 displays simulated and observed areawide average wind speeds for monitoring sites in 

the Houston area. Banta et al. (2007) and Hardesty et al. (2007) found that one of the most 

important factors in determining the intensity of ozone in Houston is wind speed. Errors in 

modeling wind speed can lead to errors in prediction of concentrations of ozone and its 

precursors; simulated winds that are too strong can simply advect precursors out of the area 

before they have had a chance to make ozone, and can prevent ozone from accumulating. Figure 

5-53 shows that simulated wind speeds for June 2, 2005 were very close to the observed; the 

slope indicates an average under-prediction of only five percent. 

I-34
Figure 4. Daily Maximum Eight-Hour Ozone by Grid Cell for the HGB Area. Monitoring sites 

are designated by circles. Ozone concentrations are designated for both model output and 

monitored observations by the color scale at right. 

Figure 4 shows that the model successfully places ozone in the correct locations, but that at some 

sites, including the peak sites, modeled concentrations are too low. 

Note that observed and modeled peak ozone occurs on the northeast edge of the monitoring 

network, and that the maximum modeled ozone occurs between the CRBL site and the CNR2 

site, in a region of sparse monitoring. Background ozone, observed at the upwind sites in 

Brazoria County (DNCG and LKJK) appear to be too low, suggesting that one possible cause of 

the underestimates of high ozone in northeast Harris County is underestimated background ozone. 

Figure 5 shows that when additional HRVOC and formaldehyde are added to modeled flare 

emissions, eight-hour ozone concentrations are enhanced, so that the degree of underestimation is 

much smaller. Areas in which higher concentrations appear, and the intensity of the enhanced 

ozone, suggest that flare emissions may play a role on this particular day. Note that much of the 

increase occurs in sparsely monitored areas, so that model performance assessed at the 

monitoring sites only would not detect the change. High ozone observed at sites nearest the 

industrial source region is still underestimated. 

I-35
Figure 5. Daily Maximum Eight-Hour Ozone by Grid Cell for the Sensitivity Run that Includes 

Additional HRVOC and Formaldehyde Emissions from Flares. Monitoring sites are designated 

by circles. Ozone concentrations are designated for both model output and observations by the 

color scale at right. 

To further examine model performance for ozone and its precursors, modeled and observed 

concentrations were examined along two transects. Since the main ozone plume is oriented 

approximately north-south on the east side of the urban core, sites were chosen starting upwind of 

the urban core and Ship Channel, moving northward toward the area of highest ozone in northeast 

Harris and in Montgomery Counties. 

For the western transect, which sampled upwind-to-downwind of the urban core and the western 

Ship Channel, ozone, NO2, ETH and OLE performance was generally very good. For the 

upwind-to-downwind transect that intersected the eastern Ship Channel, peak ozone in the 

afternoon was generally underestimated substantially, though in the morning hours, observed 

ozone increases of 30-50 ppb were well simulated. NO2 performance was relatively good, with 

no major over- or under-estimation at any site. All sites except WALV showed good ETH 

performance; at WALV, ETH was overestimated by a factor of two at about 0600. OLE was 

underestimated at LYNF by a factor of four in the morning hours, and underestimated by a factor 

of two at WALV at about the same time. The addition of HRVOC flares with HCHO did not 

change either the OLE or ozone performance at these two sites. These results suggest that there 

may be chemical and/or meteorological features occurring in the eastern Ship Channel that the 

I-36
model has not simulated well on this day. Figures 4 and 5 show that on a larger scale, the model 

simulated the extent, location, and relative intensity of ozone well on this day. 

Given the relatively good performance on this day, it seems useful to evaluate the model’s 

dynamic response to emission changes, since the lack of major flaws in the modeling for this day 

suggest it can be effectively used for evaluating emission changes. 

Figure 6 shows the model’s response on this day to the typical emission reductions that occur 

from Wednesday to Sunday, i.e., substantial decrease in mobile source NOx. The eight-hour 

maximum daily ozone shows strong NOx-sensitivity for the entire domain on this day, with the 

largest change occurring near the CNR2 site where some of the highest ozone was observed. 

Maximum eight-hour ozone decrease at CNR2 is about 20 ppb. There is a large area with ozone 

decreases of greater than five ppb. Note that much of this area is outside the current ozone 

monitoring network, suggesting that the response to emission changes may be greater outside the 

network than within it. This finding may have implications for control strategy evaluation. 

Figure 6. Change in Ozone when Emissions are Decreased on the Weekend (Sunday minus 

Wednesday). 

I-37
Figure 7. The Change in Eight-Hour Ozone Concentration by Switching from the Base Case 

reg10 EI to an HRVOC+HCHO Adjustment to the Flare Emissions. 

Figure 7 shows the change in eight-hour ozone on June 2, 2005 when HRVOC flares with HCHO 

are added. The maximum change in eight-hour ozone is over 10 ppb, and it occurs in one of the 

areas where ozone is being underestimated somewhat in the base case. The implication is that a 

change from a general emission reconciliation (PSCF VOC emission reconciliation) to a flaretargeted reconciliation (HRVOC+HCHO Adjustment), with an addition of the oxidized 

combustion product HCHO, may reflect the emissions more accurately. 

Figure 8 shows how ozone concentrations change when year 2000 emissions are substituted for 

2006 baseline emissions on June 2, 2005. This analysis demonstrates the difficulty of showing 

how the model responds to historical emission changes. Figure 9 shows the monitoring network, 

as it existed in 2000 and in 2006. As Figure 8 shows, many of the largest changes in ozone occur 

outside the monitoring network as it existed in 2000. Therefore, dynamic model evaluations may 

not always be able to assess the largest ozone changes in the domain, due to limited monitor 

coverage. Note that TCEQ added many monitors to the NE Harris County area, at the 

recommendation of TexAQS 2000 scientists, who found that unmonitored high ozone often 

occurred in this area (Daum et al., 2003; Ryerson et al., 2003). 

The blue streak of reduced ozone stretching from Fort Bend County into Harris County is the 

Parish power plant plume; TexAQS II data, and continuous emissions monitoring data at the 

stack, have shown that the NOx emissions from Parish have dropped 80% since 2000. 

I-38
Figure 8: Change in Eight-Hour Ozone when Year 2000 Emissions are Substituted for 2006 

Emissions. 

I-39
Figure 9. Monitoring Network for Ozone in the HGB Nonattainment Area. Monitors labeled in 

green were operating in 2000; monitors labeled in red were operating in 2005-2006. The blue 

box indicates the area where monitors have been added to fill in a gap in monitoring coverage 

since 2000. 

I-40
 June 2 

Figure 10. Eight-hour ozone concentrations (simulated and observed) at the WALV monitoring 

site. The model run using the standard reconciled inventory is in green, the HRVOC+HCHO 

flare run is in blue, and the observations are in red. 

Figure 10 shows the eight-hour ozone performance for the base case modeling and the 

HRVOC+HCHO sensitivity. Note that the HRVOC_HCHO flare run duplicates the results of the 

standard reconciled inventory, except that it produces higher peaks, without degrading the model 

performance at other times. Since the high ozone peaks are underestimated at times, the 

HRVOC+HCHO flare sensitivity has better model performance on some days. 

June 5, 2006 

On Monday, June 5, 2006, eight-hour ozone exceedances were observed at 16 monitoring stations 

throughout the HGB area, with the highest eight-hour concentration of 109 ppb observed at the 

H04H site in the Channelview area. The same monitoring site observed a one-hour ozone 

concentration of 130 ppb. Exceedances of the eight-hour standard occurred in the northern half 

of Harris County. Winds were from the west-southwest in the morning, switching to eastsoutheast, resulting in a flow reversal. Figures 11-12 show the observed plume streamlines 

(TCEQ Significant Events website, 2006). Figure 13 shows forward trajectories calculated from 

the surface wind observations and from model output for June 5. Note that two different methods 

were used for the streamlines and the trajectories; the two techniques are not expected to yield 

identical results. Figure 13 shows that the trajectories derived from model results (in blue) and 

observations (in red) agree relatively well for this date, indicating that any differences in chemical 

concentrations between the model and the observations are more likely to caused by factors other 

than transport errors. 

I-41
Figures 11 and 12. Plume streamlines for June 5, 2006. 

I-42
Figure 13. Forward trajectories calculated from surface wind observations and model output. 

I-43
Figure 14. Comparison of modeled and observed average wind speed data for the HGB area, 

June 5, 2006. 

In addition to the trajectory data, the model’s ability to simulate the wind flow can be examined 

by comparing to the wind speed observations for the HGB area. Figure 14 shows that for the 

June 5, 2006 simulation, the wind speeds during the day were simulated quite accurately (in red); 

the wind speeds during the evening hours were biased slightly high, but 100% of the modeled 

evening averages fell within 2 meters per second of the observed averages. 

I-44
June 5, 2006 5-min Ozone

0

20

40

60

80

100

120

140

160

180

0:00 4:00 8:00 12:00 16:00 20:00

ppb

WALV

HNWA

Figure 15. Five-minute observations of ozone at every operational monitoring site in the HGB 

area for June 5, 2006. 

Figure 15 shows five-minute ozone average concentrations observed at every HGB area 

monitoring site for June 5, 2006. From this figure, the background ozone concentrations in the 

HGB area can be deduced from the lower boundary of ozone concentrations, as well as the 

approximate degree of maximum local contribution to the observed ozone. For this date, the 

background ozone is approximately 60 ppb, with an estimated local contribution of an additional 

60-70 ppb. Note that the lowest value is usually not used as the background, because it often 

represents an urban core monitoring site that has low ozone due to titration by fresh mobile 

source NO emissions. The morning peak ozone was observed at the Wallisville Road site, in far 

eastern Harris County, and the afternoon peak was observed at the Northwest Harris County site, 

but many sites observed high ozone in midday. 

Figures 16 and 17 show maps of the modeled and observed peak ozone concentrations for onehour and eight-hour averages. At both temporal scales, the extent, location, and relative 

magnitude of ozone concentrations is simulated accurately, but the peak concentrations are 

underestimated. The background concentrations on this day for the sites on the periphery of the 

urban area are simulated very well. 

Figures 18 and 19 show the diurnal variations of wind speed and direction, and planetary 

boundary layer depth at two different sites, Huntsville and Jefferson County Airport. Both sites 

show good agreement for PBL evolution, and the wind speeds and directions throughout the PBL, 

indicating that the vertical mixing in the model is simulated accurately on June 5, 2006. 

I-45
Figures 20 and 21 show the ozone and NOx concentrations observed and modeled for June 5, 

2006 for the Aldine monitoring site, north of the urban core. This site observed high ozone 

during the midday hours. Ozone was simulated very well on this date, even for the peak 

concentrations. NOx was also simulated well. Figure 22 shows the modeled and monitored 

OLE concentrations for the Wallisville Road site. OLE represents the alkenes with greater than 2 

carbon atoms, i.e., larger than ethene. The observations show that OLE concentrations were 

elevated at the Wallisville Road site on this day. The model underestimates the peak OLE 

concentrations in the early morning hours, but simulates the late morning and afternoon 

concentrations relatively well. As Figure 15 shows, the Wallisville Road site observed high 

ozone concentrations earlier than any other site in the HGB area on this day. The high OLE and 

high ozone concentrations suggest that industrial emissions upwind of WALV may have played a 

role in the ozone formation on this date. At the time of highest observed OLE concentrations, 

winds were from the west-southwest, suggesting that the Baytown or eastern Ship Channel area 

may have been the source of the high OLE concentrations. None of the other auto-GC 

monitoring sites observed high concentrations of ETH or OLE on this date. 

I-46
Figures 16 and 17. Daily peak 1-hour and 8-hour ozone concentrations for June 5, 2006. 

I-47
Figures 18 and 19. Vertical profiles of wind speed and direction measured at two sites in 

southeastern Texas. Modeled are in blue, observed are in red. Measurements were made by 

radar profiler. 

I-48
Figures 20, 21, and 22. Observed and modeled ozone concentrations (top) at Aldine, NOx 

concentrations (middle) at Aldine, and alkenes (bottom) at Wallisville Road on June 5, 2006 

(enclosed in red box). 

I-49
Figure 23. Model response to the degree of mobile source NOx reduction typical for a weekend 

(Sunday eight-hour peak ozone minus Wednesday eight-hour peak ozone). 

Figure 23 shows that the highest ozone on June 5, 2006 is sensitive to NOx reductions. A small 

area that had high ozone on this day showed a small increase in eight-hour ozone (1 ppb - 2.5 

ppb) in response to NOx decreases, suggesting that the ozone in this area may be more sensitive 

to VOC changes than to NOx changes. Figure 24 shows how the HGB area responded to a large 

increase in flare VOC emissions for the June 5, 2006 meteorology. The ozone in the area of NOx 

disbenefit as noted in Figure c13 shows the largest increase in response to added VOC in Figure 

24. The increase in eight-hour ozone of 13.6 ppb in response to the HRVOC+FORM 

substitution is one of the largest for any day during the six episodes modeled. Based upon these 

dynamic model evaluations, it appears that the high ozone observed on June 5, 2006 is likely 

sensitive to both VOC and NOx emissions, and to both mobile and industrial emissions. Since 

the meteorological performance on this day is excellent, these conclusions are likely to be robust. 

I-50
Figure 24. Model response to the large increase in HRVOC and FORM flare emissions in the 

industrial areas of the HGB area. 

I-51
August 16, 2006 

On Wednesday, August 16, 2006, eight-hour ozone exceedances were observed at six monitoring 

sites in the HGB area. The peak eight-hour ozone concentration of 95.5 ppb for the HGB area 

was observed at the Mercer Arboretum site in north-northwestern Harris County. Figure 25 and 

26 show the plume streamlines for this day. Note that the flow reversal pattern observed on this 

day is fairly similar to the pattern observed for June 5, 2006. The winds in the morning blew 

from the west-southwest, then switched to southeast. Figures 27 and 28 contrast the forward 

trajectories calculated from the model output (blue) and from surface wind observations (red). 

These trajectories confirm the flow reversal, and show that the model simulates the reversal 

relatively well. In addition, the wind speeds are relatively well simulated (Figure 29), with 96% 

of modeled wind speed averages within 1 meter/second of the observed average. 

Wind profiles in the vertical are shown in Figures 30 and 31. The La Porte radar profiler site is 

located just south of the Houston Ship Channel, and it shows that the PBL depth was relatively 

well simulated for most hours, though the modeled data show a drop in PBL depth at 1500 hour 

that doesn’t match the diagnosed PBL depth from the profiler data. However, both the modeled 

and observed wind speed and direction data show a discontinuity at about 0.25 km at 1500, 

suggesting that the bay breeze has penetrated to La Porte at that hour. The PBL depth at the 

Huntsville site is higher, but it is also modeled relatively well. 

Based upon the trajectories, wind speed scatterplots, estimated PBL depths, and wind profiles, the 

meteorology appears to be well simulated for August 16, 2006, so that meteorological errors are 

not likely to be the cause of problems. 

I-52
 

Figures 25 and 26. Plume streamlines observed on August 16, 2006, showing a flow reversal.

I-53
Figures 27 and 28. Forward trajectories calculated from surface wind observations and model 

output, starting at midnight (top) and 0800 (bottom). 

I-54
Figure 29. Scatterplot of HGB area average wind speeds, modeled and observed, for August 16, 

2006. 

I-55
Figure 30 and 31. Modeled and measured winds at La Porte and Huntsville, August 16, 2006. 

Observed wind profiles were derived from radar profiler data at these two sites.

I-56
Ozone concentrations were high across the northern portions of Harris County. Figure 32 and 33 

show the one-hour peak ozone and eight-hour peak ozone, respectively for August 16, 2006. The 

modeled and observed high ozone plumes from the Houston Ship Channel and the urban core 

areas match well for both time scales. The peak concentrations are slightly underestimated for 

one-hour averages, but are unbiased for the eight-hour averages. Background ozone 

concentrations are slightly overestimated. When examining all ozone data for the HGB area 

(Figure 34), the background ozone appears to be relatively low, only about 40 ppb, but the model 

simulates background at about 55 ppb. Local ozone production on this day is fairly large, 

averaging about 80 ppb for many high ozone sites, with a few sites even higher. 

Figure 35-38 show ozone concentrations for the aqs1 episode; the August 16, 2006 data are 

enclosed in the dotted-line red box. Data from the WALV, HALC, MERC, and CNR2 are shown 

to illustrate the approximate boundaries of the high ozone observed on this day. Ozone 

concentrations at HALC and WALV are well simulated, but ozone at MERC and CNR2 are 

slightly underestimated. Ozone observed at Moody Tower (not shown) peaked at only about 60 

ppb, but the model showed ozone peaking at about 90 ppb, much higher than observed. The 

Moody Tower did not encounter the industrial plume on this day, and could even be considered 

an upwind site, so the overestimated ozone is due at least in part to the overestimation of the 

background ozone. In spite of the fact that the ozone performance at the downwind sites was 

very good, the model still did not have enough dynamic range; it did not make as much locally 

produced ozone as was observed. 

The dynamic response of the model to emission changes was tested with the weekend effect 

sensitivity and the flare sensitivity. Figure 39 shows the model response to the Sunday mobile 

NOx decrease; Figure 40 shows the model response to substituting large HRVOC and 

formaldehyde flares for the standard emission reconciliation. The mobile NOx decrease resulted 

in a large eight-hour ozone decrease in Montgomery and far northeastern Harris Counties, 

dropping as much as 11 ppb. However, it resulted in a relatively large increase (8 ppb) in Harris 

County north of the Houston Ship Channel, suggesting that the ozone in that area is sensitive to 

changes in VOC emissions. The trajectories (Figure 28) indicate that the urban core plume was 

transported into the Houston Ship Channel area before the flow reversal occurred, which may 

have allowed the urban core and industrial emissions to mix. Other days for which the urban core 

and industrial plumes mix together show a similar response to mobile NOx decreases. Figure 40 

shows that the area of NOx disbenefit is indeed sensitive to VOC emission changes; the addition 

of large quantities of HRVOC and formaldehyde to the flares increases eight-hour ozone 

concentrations by up to 16 ppb, in the same area where the NOx disbenefit occurred. 

I-57
Figures 32 and 33. Daily peak 1-hour and 8-hour ozone for August 16, 2006. 

I-58
Aug 16, 2006 5-min ozone

0

20

40

60

80

100

120

140

160

180

0:00 4:00 8:00 12:00 16:00 20:00

ppb

CNR2 ATAS

MERC

Figure 34. Five-minute ozone observations on August 16, 2006 for all HGB area sites. 

I-59
Figures 35-38. Ozone concentrations for August 16, 2006 (enclosed in red box).

I-60

i 

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0 3 Concentration (ppb) at Layer 1 (20060815-20060914) 

camx453 _ cb05. hgb8h2. bc06aq s1 . reg1 051. 2006ep 1_ eta_ d bemis _ fddats _ newuhsst_ new utcsrl u! c _ gre!!. hgbpa _ 02km 

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12 0 12 0 12 0 12 0 12 0 12 0 12 0 12 0 12 a:xwl831 2(X)6C9J2 2(X)60904 ~09JB 

i'77n Mcdeled. 7x7-ce!l maximin 
Figure 39. Model response to the degree of mobile source NOx reduction typical for a weekend 

(Sunday eight-hour peak ozone minus Wednesday eight-hour peak ozone). 

I-61
Figure 40. Changes in 8-hour ozone due to the substitution of HRVOC + formaldehyde flares for 

PSCF emissions for August 16, 2006.

I-62
September 14, 2006 

On Thursday, September 14, 2006, a severe ozone episode occurred in the Houston area, with the 

highest concentrations observed in western Houston and western Harris County. The peak onehour ozone concentration observed was 165.1 ppb at the West Houston (WHOU) monitor at 

1400. Three other monitors exceeded 125 ppb one-hour ozone concentrations on this day as well. 

The peak eight-hour ozone concentration observed was 118.9 ppb at WHOU from 1100-1800. 

Eight other monitoring sites also observed peak eight-hour ozone exceedances. The flow regime 

on this day was the typical veering pattern, with light northeast winds in the morning, veering to 

east and southeast later in the day. Figure 41 shows simulated and observed trajectories for this 

day. The model accurately simulates the typical veering pattern, though the model places the 

trajectories slightly further south than the observations. 

Figure 41. Trajectories for September 14, 2006. Trajectories were calculated from MM5 output 

(blue) and from observed surface wind monitors (red). Winds veer from NE to E to SE during 

the course of the day, and emissions from the industrial areas are carried into west Houston. 

I-63
Figure 42. Scatter Plot for Areawide Average Wind Speeds in the Houston-Galveston Area for 

September 14, 2006. 

Figure 42 shows the comparison of wind speeds for the Houston-Galveston domain on this date. 

Note that the slope of the line is 1.033, i.e., very close to unity. The results presented in Figures 

41 and 42 indicate that the simulated transport for this date is excellent. 

I-64
Figure 43. Daily Maximum Eight-Hour Ozone by Grid Cell for the Houston-Galveston Area on 

September 14, 2006. Monitoring sites are designated by circles. Ozone concentrations are 

designated for both model output and monitored observations by the color scale at right. 

Figure 43 shows peak eight-hour ozone concentrations in each grid cell for this day of model 

simulation. The measured areawide peak is underestimated by the model, even though the eighthour background concentrations in Galveston, Brazoria, and southeast Harris Counties appear to 

be overestimated. 

I-65
Figure 44. Daily Maximum One-Hour Ozone by Grid Cell for the Houston-Galveston Area on 

September 14, 2006. Monitoring sites are designated by circles. Ozone concentrations are 

designated for both model output and observations by the color scale at right. 

Figure 44 shows peak one-hour ozone concentrations. In this case, background concentrations 

along the coastlines appear to be less severely overestimated, but they are still biased high. Peak 

one-hour ozone observed in western Harris County is underestimated by the model. Note that 

ozone greater than about 110 ppb is confined to the southwest portion of Harris County; this is 

probably due to the trajectory error shown in Figure 41, which keeps plumes from the Ship 

Channel area in southwest Harris, instead of spreading them into northwest Harris County as the 

observed trajectories would indicate. 

I-66
Figure 45. Difference in Simulated Peak One-Hour Ozone Concentrations Resulting from 

Substituting HRVOC and Formaldehyde-Laden Flare Emissions for reg10 (PSCF-based) 

Emissions. The ozone increase west of the urban core improves model performance in that area, 

without degrading performance elsewhere.

Figure 45 shows how substituting flare emissions spiked with formaldehyde can increase the 

ozone concentrations compared to the PSCF-based industrial source emissions inventory. This 

shows that even though the flares are located in eastern Harris and western Chambers Counties, 

they can still greatly affect ozone concentrations throughout the Houston metropolitan area. 

Examination of time series for September 14, 2006 shows that the monitoring sites along the 

southern edge of Harris County, i.e., TOMB, MACP, HCQA, BAYP, SHWH, show ozone 

overestimation by the model, whereas sites located a little further north, i.e., WHOU, HLAA, 

BUHV, HNWA, KATP, show ozone is underestimated. Moving upstream, sites along the 

southern route (HSMA, PRKP, FWCB) are also somewhat overestimated, whereas HALC and 

HOEA are both slightly underestimated. These patterns of over- and under-estimation are 

consistent with the too-southerly misalignment of plumes shown in Figure 41. At many of the 

west and central Houston sites, NO2 shows major spikes (up to 40 ppb) in the hours before noon, 

which appear to be simulated relatively well by the model. NO2 provided by this plume appears 

to effectively supply the fuel for high ozone later in the day. Three auto-GC sites on the western 

end of the Ship Channel (C35C, CECH, MIPK), DRPK, and WALV all observed spikes of ETH 

and OLE up to 20 ppb in the morning hours, which were usually simulated well by the model. 

Moody Tower at the UH campus observed a very large HCHO spike (30 ppb) during the midday 

I-67
hours, which was not well simulated by the model, though the model did simulate a HCHO peak 

earlier in the day near the Moody Tower site. When the HRVOC+HCHO flares were substituted 

into the modeling, the HCHO performance at Moody Tower improved slightly. 

Based upon the time series, it appears that industrial emissions from the Ship Channel area laden 

with HRVOC and NOX were pushed to the west-southwest by morning winds. The plumes 

generated HCHO and NO2 along the way, then produced large quantities of ozone as they entered 

the west Houston area. While modeled wind speeds were approximately correct, the orientation 

of the industrial plumes was too far south, resulting in overestimated ozone in southerly areas, 

and underestimated ozone in northerly areas. The WHOU site experienced very high ozone 

concentrations that were not simulated anywhere in the domain, indicating that a transport error 

alone is not the cause of the missed peak at WHOU. Addition of flare emissions alleviated some 

but not all of the underestimation problems; the observed peak ozone was still not simulated 

anywhere in the domain. Although the highest ozone peaks were not well simulated, the location, 

extent, and relative intensity of high ozone are depicted relatively well (Figure 44). 

Figure 46. September 14, 2006: Change in Ozone When Emissions are Decreased on the 

Weekend (Sunday Minus Wednesday). 

Figure 46 shows how the model responds to the emission reductions that occur on the weekends. 

The four to ten ppb decrease in maximum eight-hour ozone in the western portion of the domain 

suggests that the highest ozone is somewhat sensitive to decreases in NOX. Note that the largest 

I-68
changes in ozone occur outside the monitoring network, in Waller County. A very small area of 

NOX disbenefit is found in the center of the urban core, which is likely due to the lessening of 

ozone titration by decreasing mobile NO emissions. 

June 23, 2005 Episode 

June 23, 2005 had similar flow characteristics to September 14, 2006. The flow pattern is 

characterized as typical veering, though on this day, the veering is more subtle, giving trajectories 

that are nearly straight (Figure 47). Trajectories that originate in the eastern Ship Channel area 

pass directly through the urban core, and create high ozone in western Harris County. Modeled 

transport is excellent on this day. Figure 48 shows that modeled wind speeds perform well on 

this day, too. 

Figure 47. Trajectories for June 23, 2005. Trajectories were calculated from MM5 output (blue) 

and from observed surface wind monitors (red). Winds veer from ENE to E to SE during the 

course of the day, and emissions from the industrial areas are carried into west Houston. 

I-69
Figure 48. Scatterplots of Areawide Average Wind Speeds in the Houston-Galveston Area for 

June 23, 2005. 

I-70
Figure 49. Daily Maximum Eight-Hour Ozone by Grid Cell on June 23, 2005. Monitoring sites 

are designated by circles. Ozone concentrations are designated for both model output and 

monitored observations by the color scale at right. 

Simulated peak eight-hour ozone concentrations are shown in Figure 49. The location, extent, 

and relative intensity of high ozone are well-depicted by the model simulations. The highest 

ozone is observed in the proper area (northwest Harris County), but it is slightly lower than 

observed. In addition, ozone concentrations along the trajectory pathways from the Ship Channel 

area to NW Harris County are also underestimated. Substitution of HRVOC- and HCHO-laden 

flares in the industrial areas improves model performance somewhat (Figure 50). Note that in 

both Figures 49 and 50, some of the highest simulated ozone occurs outside the monitoring 

network. 

I-71
Figure 50. Daily Maximum Eight-Hour Ozone by Grid Cell on June 23, 2005, with the 

Substitution of HRVOC+HCHO Flares. Monitoring sites are designated by circles. Ozone 

concentrations are designated for both model output and monitored observations by the color 

scale at right. 

Given the relatively good model performance on this date, it is appropriate to examine how the 

simulation responds to emission changes. Figure 51 shows how weekend mobile NOX reductions 

change peak eight-hour ozone for this simulation day. 

I-72
Figure 51. June 23, 2005: Change in Ozone When Emissions are Decreased on the Weekend 

(Sunday Minus Wednesday). 

The large area of ozone increase in response to NOX decreases suggests that peak eight-hour 

ozone in west Houston on this day is sensitive to VOC emissions. To further examine this 

possibility, the model response to flare emissions is examined in Figure 52. 

I-73
Figure 52. Peak One-Hour Ozone Response to Substituting HRVOC+HCHO Flares for PSCFBased Emissions on June 23, 2005. 

Figure 52 shows that the June 23, 2005 episode responds vigorously to the substitution of 

HRVOC and formaldehyde flares in the emissions inventory. The June 23, 2005 episode 

enhances the peak one-hour ozone by about 30 ppb, and enhances peak eight-hour ozone by about 

6 ppb (not shown). The area of extremely high enhancement occurs in approximately the same 

area that shows increases in ozone with NOX cuts. This phenomenon is quite interesting, 

especially given that the two previous days, which had similar flow, did not show this degree of 

enhancement. 

All modeling days were examined to find other days for which ozone concentrations increased 

when the weekend mobile NOX decrease was applied. We found that these days were not 

common; out of 95 modeled days, only 13 days showed ozone increases of five ppb or more in 

the presence of weekend mobile NOX decreases. Table 1 shows a list of these days, along with 

the maximum ozone increase resulting from the weekend mobile source NOX decreases. 

Table 1. Modeling Days for Which Weekend Mobile NOX Decreases Yielded Ozone Increases 

Date 

Maximum 

1-hr ozone 

increase 

Maximum 

8-hr ozone 

increase 

Location of VOCsensitive ozone Flow regime 

May 20, 2005 11 ppb 9 ppb NE of urban core Flow reversal 

May 22, 2005 15 ppb 5 ppb E and NE of urban core Flow reversal 

May 25, 2005 6 ppb 4 ppb ENE of urban core Flow reversal 

June 23, 2005 8 ppb 4 ppb W of urban core Typical veering 

June 26, 2005 6 ppb 3 ppb W of urban core Typical veering 

I-74
June 28, 2005 11 ppb 2 ppb W of urban core Typical veering 

June 29, 2005 13 ppb 5 ppb W of urban core Typical veering 

August 3, 2005 17 ppb 6 ppb NNE of urban core Flow reversal 

June 12, 2006 11 ppb 11 ppb SW of urban core Flow reversal 

August 16, 2006 18 ppb 8 ppb NE of urban core Flow reversal 

August 18, 2006 6 ppb 2 ppb SW of urban core Flow reversal 

August 20, 2006 10 ppb 10 ppb W of urban core Typical veering 

August 21, 2006 11 ppb 5 ppb W of urban core Typical veering 

Note: all other modeling days had 1-hr ozone decreases, or increases of less than 5 ppb. 

Trajectory analysis of all modeling days suggests that the days listed in Table 1 have something 

in common: on these days, the urban core plume mixes with the industrial plume. The flow 

conditions that allow these plumes to mix are not particularly common; most of the local flow 

patterns in Houston do not allow these plumes to mix. On days dominated by the coastal 

oscillation, wind shifts tend to occur throughout the domain at approximately the same time, 

allowing urban and industrial plumes to remain on parallel courses rather than intersecting. On 

days dominated by bay or Gulf breezes, cooler air from the breezes can push under the urban air, 

so that the air masses do not mix well (see the TOPAZ data discussion). 

Conclusions from case study analyses 

This section has examined a number of high ozone days for which the meteorological modeling 

has performed well, so that the chemistry, emissions, and response to emission changes can be 

examined without the uncertainty added by meteorological errors. The following conclusions can 

be reached from these analyses. 

 The model is capable of accurately simulating the wind patterns for both typical veering 

and flow reversal days. 

 The extent, location, and relative magnitude of ozone are well simulated on each of these 

selected days. 

 Peak ozone concentrations are often underestimated; background ozone concentrations 

are sometimes overestimated. The model’s dynamic range of ozone variation is not as 

large as the observed dynamic range. 

 Some of the peak underestimation problem may be alleviated by allocating additional 

VOC emissions to the flares. The addition of formaldehyde to HRVOC flares can 

increase modeled one-hour ozone concentrations by up to 25 ppb, but usually increases 

one-hour ozone by less than 10 ppb. 

 The weekend effect sensitivity analysis shows that peak eight-hour ozone is generally 

sensitive to NOX reductions in the base case. For a few days (e.g., June 23, 2005, August 

16, 2006), however, a pocket of NOX disbenefit appears. When the model is run for 

those days with additional VOC from flares, the model responds vigorously, generating 

much larger ozone concentrations in the area of NOX disbenefit. This behavior indicates 

that the NOX disbenefit area has conditions suitable for VOC-sensitive ozone formation. 

The implication of these results is that both NOX and VOC emission controls will be 

needed to suppress ozone formation. 

 The retrospective analysis showed that the model responds strongly to the emission 

changes that are believed to have occurred between 2000 and 2006. One of the areas of 

greatest change in ozone is in northeast Harris County, which was not well monitored in 

I-75
 The model’s response to emission changes is sometimes greatest in areas outside the 

current (2006) ozone monitoring network. 

Future 2018 design values based upon 2005 baseline modeling 

Future eight-hour ozone design values were calculated with 2005 baseline emissions (bl05.reg1). 

The emissions used in the modeling scenario and the future design values are described below. 

For the 2018 future estimate, the point source NOX emissions were estimated as follows: 

 For the region outside Texas, the CENRAP/RPO regional haze 2018 emission levels (e.g. 

IPM, CAIR2 trading, controls) were used; 

 For the attainment region of Texas, CAIR Phase 2 allocations were used for existing 

EGUs, new EGUs were limited to the 9.5% set-aside; all controls included in the recent 

DFW and BPA SIPs (e.g., East Texas Engine Rule) were applied; and growth was 

projected to 2018 with Economy.com factors; 

 For the DFW and BPA nonattainment areas, CAIR Phase 2 and Chapter 117 ESAD were 

used; and 

 For the HGB nonattainment area, MECT and HECT were used, as well as controls 

included in the recent HGB SIP (e.g., VOC rules for tanks and degassing). 

The point source NOX emissions within the HGB eight-county nonattainment area were reduced 

by about 20% from a 2005 baseline of 194 tpd to 156 tpd in 2018. 

The on-road mobile source NOX emissions were estimated as follows: 

 For areas outside of Texas, county-level emission derived from NMIM were used and 

projected to 2018; 

 For Texas counties outside of BPA and HGB, county-level hourly emissions by summer 

“day type” from TTI based on projected traffic count data from TxDOT were used; and 

 For both HGB and BPA, link-based hourly emissions by summer “day type” from TTI 

based on projected travel demand modeling were used; 

The on-road mobile source NOX emissions within the HGB eight-county nonattainment area 

were reduced by about 78% from a 2005 baseline of 222 tpd to 49.8 tpd in 2018. 

The non-road and off-road (i.e., marine, locomotive and aircraft) mobile source NOX emissions 

were estimated as follows: 

 For the region outside Texas, EPA’s NMIM was used for non-road categories, and 2002 

NEI with EGAS growth was used for all off-road categories with national controls on 

locomotives and marine vessels; 

 For the non-road categories within Texas the Tex-N model was used; 

 For the off-road categories within Texas 

o 2005 TexAER was used with REMI-EGAS growth with national controls for 

locomotives and marine vessels, except locomotives in HGB and DFW, and 

marine vessels in HGB and BPA 

 2018 emissions for locomotives in HGB and DFW were provided from a 

contract with ERG (now in TexAER) 

 2018 emissions for marine vessels in HGB and BPA were developed 

using emission trends provided by the HGB and BPA Port Authorities 

and 2007 and 2000 emission projections, respectively, provided from a 

contract with Starcrest 

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o For aircraft within Texas, except for HGB and DFW, 2002 TexAER was used 

with REMI-EGAS growth. For HGB and DFW, 2005 emission estimates from 

AQP were used with REMI-EGAS growth. 

The non-road and off-road mobile source NOX emissions within the HGB eight-county 

nonattainment area were reduced by about 22% from a 2005 baseline of 148 tpd to 116 tpd in 

2018. 

The area source NOX emissions were estimated as follows: 

 For the region outside Texas, 2002 NEI with EGAS growth was used; and 

 For the region within Texas, 2005 TexAER with REMI-EGAS growth was used. 

The area source NOX emissions within the HGB eight-county nonattainment area were increased 

slightly from a 2005 baseline of 36.2 tpd to 42.0 tpd, in 2018. 

Note that no ERCs or DERCs have been included in this modeling scenario. 

In total, the NOX emissions within the HGB eight-county nonattainment area were reduced by 

about 39% from a 2005 baseline of 600 tpd to 364 tpd in 2018 (Figure 1). 

2005 Baseline vs 2018 Future Year NOx Emissions 

194.02

155.93

221.65

49.82

148.31

115.85

36.18

42.04

0

100

200

300

400

500

600

700

2005 - BASELINE 2018 - FUTURE

NOx Emissions in tons per day

"Area"

"Non-Road"

"On-Road"

"Points"

Figure 1. Baseline 2005 and future 2018 NOX emissions in the eight-county HGB area.

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The 2018 eight-hour ozone concentrations modeled at the various monitoring sites were 

compared to the 2005 baseline modeled concentrations, per the EPA Guidance to develop a 

Relative Response Factor (RRF) for each of the monitoring sites (Table 1). These RRFs were 

then multiplied by the 2005 baseline ozone Design Values (DVb05s) to estimate the 2018 future 

ozone Design Values (DV18s). Of the 20 HGB monitoring sites with a DVb05 greater than 85 

ppb, only four are projected to have a DV18 of 85 ppb or greater. The future DVs for those four 

sites are presented in Table 1. The future DVs for those four sites are presented in Table 1. 

Table 1. Design values and relative reduction factors for 2005 baseline runs. 

Monitoring 

Site Code

2005 Baseline 

8-Hour Design 

Value (ppb)

RRFs

2018 Future 

8-Hour Design 

Value (ppb)

DRPK – C35 96.3 0.921 88.7 

BAYP – C53 100.7 0.862 86.8 

HSMA –C406 95.3 0.896 85.4 

WALV – C617* 94.0 0.924 86.8 

*Note: WALV is not a regulatory monitor. 

Supplemental Corroborative Analysis and Weight-of-Evidence 

Effects of Meteorological Conditions on 2007-2009 Ozone Monitoring Data 

In Chapter 5 of the HGB attainment SIP, the TCEQ presented an analysis of ozone trends that 

accounted for the effects of meteorological conditions (i.e., Sullivan, 2009). Since that time, 

questions have arisen about whether the Sullivan analysis was sufficient to show that 

meteorological conditions were unable to explain the substantial decrease in ozone concentrations 

since 2000. The EPA argued that higher than average wind speeds occurred in both 2007 and 

2008, leading to lower ozone concentrations. 

The TCEQ agrees that meteorological factors may have played some role in the recently observed 

ozone trends, but disagrees that the meteorological factors are the primary reason for decreasing 

ozone. Analyses from the TCEQ and others show that ozone trends are still decreasing in the 

Houston area, even when the effects of meteorology have been accounted for. 

The TCEQ disagrees with the EPA that meteorological conditions in Houston during 2006-2009 

have been unfavorable for high ozone, and therefore the decline in ozone concentrations is not 

due to local emission reductions. They base their position on a finding from an analysis by Sather 

and Snyder, which shows that higher wind speeds occurred more frequently during 2008 than in 

2000-2007. Figure 1: Wind data from Houston Aldine shows the graph of interest. 

I-78
Figure 1: Wind data from Houston Aldine 

(Source: The data are from June-Aug, 0500-1900 LST, with 65% minimum data capture. Winds 

of greater than 10 mph were more frequent during 2008 than any year since 1998. This figure is 

copied from Sather and Snyder, Region 6 “State of the Ozone” Report for 2008, presented at the 

Southeast Texas Photochemical Modeling Technical Committee Meeting, April 28, 2009.) 

Sather and Snyder assert that the higher winds in 2008 are the primary cause of lower ozone in 

2008. As they have noted, the frequency of high winds in 2008 is comparable to the frequency 

observed in 1998. The maximum 4th-high 8-hour ozone concentrations in 1998 ranged from 90 to 

117 ppb at regulatory monitors throughout Houston, but the maximum 4th-high 8-hour ozone 

concentrations in 2008 ranged from 68 to 83 ppb at Houston regulatory monitors. This represents 

a 29% decrease in maximum 8-hour ozone from 1998 to 2008. Since the frequency of high winds 

is similar in 1998 and 2008, the frequency of high winds cannot explain the difference between 

ozone concentrations during these two years. 

The TCEQ contends that four extensive analyses of meteorological conditions presented below 

(each of which includes more than just the frequency of high winds) indicate meteorological 

factors cannot explain the recent decrease in ozone. In addition, an analysis of the frequency of 

wind speed and direction will show that the period of high winds in 2008 noted by Sather and 

Snyder occurred at a time of year when high ozone usually doesn’t occur, because of the direction 

of the wind flow at that time of year. It will also show that the wind conditions were in fact more 

suitable for high ozone formation in August and September of 2008 and 2009 than in 2000 and 

2004, but the number of exceedance days were far fewer in 2008 and 2009. 

Chapter 5 of the HGB SIP contains an analysis from the University of Texas at Austin (UTAustin), which show the ozone trends adjusted for meteorology. Figures 2 and 3, and Table 1 

illustrate the observed trends, and trends with the meteorological effects removed. Those trends 

show that the ozone through 2007 is decreasing even with meteorological influences removed 

from the trends. Much of the work from UT-Austin was based upon a variation of the analysis 

technique developed by Camalier, Cox, and Dolwick, which is the technique recommended by 

the EPA for removing the influences of meteorology from trend data. UT-Austin’s analysis 

shows that when the portion of the ozone variation associated with meteorological factors is 

removed from the observed ozone trend, the residual trend is still downward. The presence of a 

strong downward trend after the removal of meteorological effects strongly suggests that the 

overall downward trend is related to factors other than meteorology. 

A second analysis of meteorologically-adjusted ozone trends can be found on the EPA website, 

www.epa.gov/airtrends/weather/region06.pdf . The EPA trends are shown in Figure 4: 

I-79
Meteorologically Adjusted Ozone Trends in the HGB Area from 1997 through 2008, which

illustrates the observed seasonal average ozone trend, and the seasonal average ozone trend 

adjusted for weather. The ozone trend adjusted for weather represents the expected ozone levels 

for typical weather conditions. According to the EPA analysis, the downward trend in Houston’s 

ozone is unrelated to meteorological variations, beginning in 2002 and continuing through the end 

of the analysis period in 2008. 

Figure 2: Actual Mean Eight-Hour Ozone Concentrations (Blue Line) and Mean EightHour Predicted Concentrations with the Non-Meteorological Trend Removed (Red Line) 

Figure 3: Residual Meteorologically Adjusted Eight-Hour Ozone Concentrations Trend 

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Table 1: Summary Statistics for Meteorologically 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, 2009) 

Figure 4: Meteorologically Adjusted Ozone Trends in the HGB Area from 1997 through 

2008 (Source: EPA) 

URS Corporation performed a third analysis of the effects of meteorology on ozone trends, which 

is included in comments from the Coalition. A presentation that discusses this analysis can be 

found at 

http://www.tceq.state.tx.us/assets/public/implementation/air/am/committees/pmt_set/20071212/2

0071212-setpmtc-hgb_ozone_trend.pdf . In this analysis, the author used the Classification and 

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Regression Tree (CART) method, a multivariate statistical analysis technique, to classify ozone 

season days according to the meteorological conditions, and whether the conditions are conducive 

to high ozone in Houston. From this analysis, URS calculated trends of the number of ozoneconducive days per year. Figure 5: Number of Ozone Conducive Days and Number of Ozone 

Conducive Days with Ozone Greater Than 84 ppb shows that the number of ozone conducive 

days in 2007, 2008, and 2009 is similar to or greater than previous years, indicating that the past 

three ozone seasons have been just as conducive to high ozone formation as previous years. 

Since 2005, there appear to be more ozone conducive days than average, but fewer eight-hour 

ozone exceedance days. Although 2005 had the largest number of ozone conducive days since 

1990, there were fewer exceedance days in 2005 than during than previous years with a lower 

number of ozone conducive days, such as 1995, 2000, or 2003. 

Figure 5: Number of Ozone Conducive Days and Number of Ozone Conducive Days with 

Ozone Greater Than 84 ppb 

(Source: URS Corporation)

A fourth analysis is presented as a response to the comment by ED/GHASP about evaluating the 

trends in forecasted high ozone days. A possible surrogate for the number of ozone conducive 

days during each ozone season is the number of TCEQ-forecasted eight-hour ozone exceedance 

days. Figure 6: Forecasted and Actual Eight-Hour Ozone Exceedance Days (1997 NAAQS) in 

the HGB Area shows that the number of forecasted eight-hour ozone exceedance days is typically 

greater than the number of actual eight-hour ozone exceedances to avoid missing potentially high 

ozone days. To adjust the forecasted eight-hour ozone exceedances to compensate for the bias, a 

bias-adjusted forecast was developed by accounting for the average rates of false positives 

(predicted exceedances that did not occur) and false negatives (predicted non-exceedances on 

days with high ozone). The average percent of false negative days was added to the number of 

forecasted ozone exceedance days, and the average percent of false positive days was subtracted. 

The bias-adjusted forecasted ozone exceedance days approximately match the actual number of 

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eight-hour ozone exceedance days, with the exception of 2004 and 2008. In 2004, the biasadjusted ozone exceedance forecast was much lower than the actual number of eight-hour ozone 

exceedance days. However, in 2008, the bias-adjusted forecast of ozone exceedance days was 

much higher than the actual number of eight-hour ozone exceedance days, indicating decreases 

due to factors other than meteorology. There are uncertainties in this analysis, because TCEQ 

meteorologists adjust their forecast techniques as they learn more about which conditions are 

most conducive to ozone formation, accumulation, and transport in Houston. In other words, the 

criteria used for developing forecasts in 2000 may have differed somewhat from the criteria used 

in 2008. The results, however, are fairly consistent with the three previous analyses, in that the 

peak number of ozone-conducive days in recent years appears to be in 2005, with the number 

decreasing slightly in 2006-2007. The number of forecast ozone days in 2008 approximately 

matched the number in 2006, but there were about half as many actual exceedance days in 2008 

as in 2006. 

 

Forecasting 8-hour ozone exceedances, Houston

0

20

40

60

80

100

2000 2001 2002 2003 2004 2005 2006 2007 2008

Count

Bias-adjusted forecasts

Mean forecast

Actual forecast

Actual exceedances

Figure 6: Forecasted and Actual Eight-Hour Ozone Exceedance Days (1997 NAAQS) in the 

HGB Area 

These four analyses of the effects of inter-annual meteorological variations on ozone trends all 

imply that meteorological factors alone cannot explain the decrease in ozone concentrations in the 

Houston area. 

The TCEQ has also analyzed the frequency of wind speeds and directions by month and by year, 

to show in greater detail the wind data that the EPA had originally cited in their comment. The 

winds in the HGB area were examined for each month of the ozone season from 2000 to 2009 to 

determine if higher wind speeds in 2008 and 2009 caused decreases in ozone concentrations. 

Daytime wind speeds were grouped into six levels and the frequencies of those levels were 

examined by wind direction for each month from May to September, which represents the peak of 

the ozone season in the HGB area. Figure 7: Frequency of Morning Wind Direction and Wind 

Speed by Month in the HGB Area for 2000, 2004, 2008, and 2009 compares years with similar 

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winds and shows the number of eight-hour ozone exceedances that occurred in each month (1997

NAAQS). Winds from 0 to 90 degrees are from the north to east, and, as shown in Chapter 5 of 

the SIP, winds from that direction typically represent higher background ozone concentrations, as

well as winds that can interact with the bay breeze and Gulf breeze to create stagnant conditions 

(Darby, 2005; Pakalapati et al., 2008; Sullivan, 2009; Ngan and Byun, 2008; Rappenglueck et a

2008). Winds from 90 to 225 degrees are from the east to southwest and represent cleaner air 

blowing in from the Gulf of Mexico (Sullivan, 2009; Rappenglueck et al., 2008). These winds 

accentuate the bay and Gulf breezes rather than opposing them (Darby, 2005; Banta et al., 2005). 

The findings of these previous studies have indicated that low winds are more favorable for high

ozone, whereas high winds are less favorable. The findings also show that northerly wind

l., 

s are 

ore favorable for high ozone in Houston, and that southerly winds are less favorable. 

he wind analysis by the TCEQ found that: 

formation based upon wind speeds, but had more exceedances than May 2008 and 2009. 

ore 

ive based upon wind direction, yet had fewer exceedances than May 2000 or 

2004. 

ed by 

r of 

 winds in June 2008 was 

unlikely to affect the number of exceedances in that month. 

e only two exceedance days 

in July 2009 compared to ten exceedance days in July 2000. 

8 

high ozone than August 2000, based upon wind speeds, but had far fewer exceedances. 

re conducive to high ozone, but 

has far fewer exceedances than September 2000 or 2004. 

08 

and 2009. The greater frequency of high winds in 2008 noted by Sather and Snyder occurred 

m

T

 Wind speeds in May 2000 and May 2004 were higher than those observed in May 2008 

and May 2009, but the number of eight-hour ozone exceedance days was higher in 2000 

compared to 2008 and 2009. May 2000 and 2004 were less conducive to ozone 

 May 2009 also had more winds from the north to northeast direction, which typically 

indicates higher background ozone, but only three exceedance days. May 2009 was m

conduc

 June 2008 and 2009 had higher wind speeds than those observed in June of 2000 and 

2004; however, winds in June are mainly out of the south, which brings in clean air from 

the Gulf of Mexico. There were only three exceedance days in June of 2000, five in June 

of 2005, and two in both June 2008 and June 2009. For all years, June was dominat

southerly winds, which are not conducive to ozone formation. The low numbe

exceedances each year reflects how unfavorable southerly winds are to ozone 

exceedances; therefore, the slightly greater frequency of high

 July winds were very similar in 2000 and 2009, but there wer

 Winds in August 2008 were slower than those observed in August 2000, yet August 200

had one exceedance day compared to 15 in 2000. August 2008 was more conducive to 

 September 2009 had slightly lower winds in the northeast direction compared to 

September 2000 and 2004, but only three exceedance days compared to 10 in September 

2000 and 13 in September 2004. September 2009 was mo

In summary, Figure 7: Frequency of Morning Wind Direction and Wind Speed by Month in the 

HGB Area for 2000, 2004, 2008, and 2009 shows that the wind speed and direction were actually 

more conducive to ozone formation during the peak of the ozone season in August and September 

in 2008 and 2009 than in 2000 and 2004, but 2000 and 2004 had far more exceedances than 20

I-84
I-85

during June, when winds were southerly, and therefore not conducive to high ozone, during all 

four years. 

The TCEQ believes that evidence provided in the SIP, along with additional analyses presented 

here, show that favorable meteorology is not adequate to explain the decreases in ozone observed 

in 2007, 2008, and 2009. Evidence presented in Chapter 5 shows that decreases in ozone 

precursor emissions played a significant role in the recent decreases in ozone. 
May

June

July

August

September

2000 HGB Winds (0500 – 1900 LST)

8-Hr Ozone 

Exceedance Days

5

3

101510

May

June

July

August

September

2000 HGB Winds (0500 – 1900 LST)

May

June

July

August

September

2000 HGB Winds (0500 – 1900 LST)

8-Hr Ozone 

Exceedance Days

5

3

101510

8-Hr Ozone 

Exceedance Days

5

3

101510

2004 HGB Winds (0500 – 1900 LST)

8-Hr Ozone 

Exceedance Days

1

58

1213

May

June

July

August

September

2004 HGB Winds (0500 – 1900 LST)

8-Hr Ozone 

Exceedance Days

1

58

1213

2004 HGB Winds (0500 – 1900 LST)

May

June

July

August

September

8-Hr Ozone 

Exceedance Days

1

58

1213

8-Hr Ozone 

Exceedance Days

1

58

1213

May

June

July

August

September*

2008 HGB Winds (0500 – 1900 LST)

8-Hr Ozone 

Exceedance Days

0

2114

May

June

July

August

September*

2008 HGB Winds (0500 – 1900 LST)

* Incomplete data due to the passage of Hurricane Ike

8-Hr Ozone 

Exceedance Days

0

2114

8-Hr Ozone 

Exceedance Days

0

2114

S

2009 HGB W

S

2009 HGB W

W nd Speed, mph i

< 5 5 - 10 10 - 15 15 - 20

W nd Speed, mph i

< 5 5 - 10 10 - 15 20 - 25 > 25

Figure 7: Frequency of Morning Wind Direction and Wind Speed by Month in the HGB Area for 2000, 2004, 2008, and 2009

I-86
Effects of Economic Downturn on 2007-2009 Ozone Monitoring Data 

Detailed analysis of actual economic data from the HGB area, Texas, and the refining industry 

along the Gulf Coast does not support the assertion that the decrease in ozone concentrations in 

the HGB area is primarily due to the national economic downturn. 

Though the national economy entered a recession beginning in December of 2007 (well past the 

peak ozone season), both Texas and the HGB area continued to experience economic expansion 

during 2007 and 2008. Only in early 2009 did either Texas or the HGB area begin to exhibit flat 

or slightly reduced economic activity. While Texas Gross Domestic Product (GDP) increased 7.3 

percent in nominal terms from 2006 to 2007 (see Figure 8: Gross Domestic Product of Texas), 

and 6.5 percent from 2007 to 2008, the economy of the Houston-Sugarland-Baytown area grew 

even faster, at 8.4 percent and 7.4 percent over those years, respectively (see Bureau of Economic 

Analysis, Regional Economic Accounts: www.bea.gov/regional/gsp/ and Gross Domestic Product 

by Metropolitan Area: www.bea.gov/regional/gdpmetro/). Though these figures are not corrected 

for inflation, inflation was exceptionally low over this period. “Houston-Sugarland-Baytown” is 

the definition of the HGB metropolitan area used by the U.S. Department of Commerce. 

$-

$200

$400

$600

$800

$1,000

$1,200

$1,400

1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Source: Bureau of Economic Analysis, U.S. Department of Commerce http://www.bea.gov/regional/gsp/

$ billions

Figure 8: Gross Domestic Product of Texas 

Another measure of economic activity for the Houston-Sugarland-Baytown metro area, the 

business cycle index computed by the Federal Reserve Bank of Dallas 

(www.dallasfed.org/data/data/houcoini.htm), exhibits a downward trend beginning only in early 

2009 (Figure 9: Metro Area Business Cycle Index, Houston-Sugarland-Baytown). The index, 

which incorporates measures of employment, real wages, and retail commerce, grew 5.6 percent 

from December 2006 to December 2007, and 2.5 percent from December 2007 to December 

2008. Through September 2009, the index is down -2.7 percent from the end of 2008. It is 

I-87
especially noteworthy that this index, available through the first three quarters of 2009, shows 

that during each of the years 2007, 2008, and 2009 to date, the HGB area generated greater 

economic activity than in any previous year on record, exceeding an index value of 245 in every 

month. Previous to 2007, the index never exceeded that value. Despite this burgeoning 

economic activity, the HGB area continued to exhibit reductions in both precursor emissions and 

resultant ozone over those three years. 

150

175

200

225

250

275

300

Jan-00 Jan-01 Jan-02 Jan-03 Jan-04 Jan-05 Jan-06 Jan-07 Jan-08 Jan-09

October 1980 = 100

Source: Federal Reserve Bank of Dallas

Figure 9: Metro Area Business Cycle Index, Houston-Sugarland-Baytown

While the overall economies of Texas and the HGB area were not impacted by the economic 

downturn until early 2009, industries linked to petrochemicals and refining, which are key to 

HGB area air quality, also failed to exhibit the claimed downward trend (see Figure 10: Gross 

Domestic Product of Selected Petroleum Related Industries). From 2006 to 2007, the most recent 

annual period for which sub-industry GDP data are available, oil and gas extraction increased 7.6 

percent. Similar patterns emerge for other segments of the petroleum industry over that period. 

Manufacturing of chemicals grew 9.9 percent, while manufacturing of plastics and rubber 

products increased 2.7 percent. Only manufacturing of petroleum and coal products declined (at 

a rate of -1.9 percent) from 2006 to 2007. 

I-88
$-

$10

$20

$30

$40

$50

$60

$70

$80

$90

1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

$-

$5

$10

$15

$20

$25

$30

$35

$40

$45

Oil and gas extraction (left axis)

Petroleum and coal products mfg (right axis)

Chemical mfg (right axis)

Plastics and rubber products mfg (right axis)

$ billions $ billions

Source: Bureau of Economic Analysis, U.S. Department of Commerce http://www.bea.gov/regional/gsp/

Figure 10: Gross Domestic Product of Selected Petroleum Related Industries 

While more recent data on GDP trends in the petrochemical and refining industries are not yet 

available, other recent information on activity in these industries corroborates the above findings. 

The Energy Information Administration of the U.S. Department of Energy reports refining 

activity along the Gulf Coast, termed Petroleum Administration for Defense District (PADD) 3, 

which includes the HGB area (tonto.eia.doe.gov/dnav/pet/pet_sum_sndw_dcus_r30_w.htm). As 

evident in Figure 11: Weekly Gulf Coast (PADD 3) Crude Oil Inputs to Refineries, reported 

weekly inputs are highly variable. A thirteen-week, or roughly quarterly, moving average is 

super-imposed on the weekly data to smooth out some of this variability. This measure reveals 

the seasonal cycles in the industry, as refineries ramp up production for periods of high product 

demand. Though inputs to refineries appear to be on a slight downward trend since 2007, they 

have actually been increasing since early 2009, though this is likely a cyclical phenomenon. In 

fact, neither high nor low values of the quarterly average since 2007 have strayed beyond the 

highest or lowest values observed over the previous decade, indicating the industry as a whole has 

neither grown nor shrunk markedly. 

A quadratic fit to the weekly data reveals a very slight long-term downward trend in the refining 

industry, beginning around 2004. Since 2004, PADD 3 inputs to refineries have generally 

dropped, at a rate of about seven-tenths of one percent per year, even when hurricane-affected 

periods in 2005 (Katrina, Rita) and 2008 (Ike) are excluded. 

I-89
3,000

4,000

5,000

6,000

7,000

8,000

Sep-92

Mar-93

Aug-93

Feb-94

Aug-94

Feb-95

Aug-95

Feb-96

Aug-96

Feb-97

Aug-97

Feb-98

Aug-98

Jan-99

Jul-99

Jan-00

Jul-00

Jan-01

Jul-01

Jan-02

Jul-02

Jan-03

Jul-03

Jan-04

Jul-04

Dec-04

Jun-05

Dec-05

Jun-06

Dec-06

Jun-07

Dec-07

Jun-08

Dec-08

Jun-09

Source: U.S. Dept. of Energy, Energy Information Admin., http://tonto.eia.doe.gov/dnav/pet/hist/w crrip32w .htm

Katrina Ike

 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 

EIA reports inputs by Petroleum Administration for Defense District (PADD). PADD 3 includes refining 

operations

Reported weekly inputs (light blue)

13-week moving average (dark blue)

Quadratic regression fit to weekly data

upper bound

lower bound

1998-2009 range

Figure 11: Weekly Gulf Coast (PADD 3) Crude Oil Inputs to Refineries 

This may suggest factors other than an economic downturn in 2007 or 2008 were influencing the 

industry. Average weekly inputs to refineries in 2007 were 7.35 million barrels, 1.4 percent 

above the average of the previous year, and nearly as high as in 2004, when they averaged 7.37 

million barrels per week. Though inputs to refineries in 2008 fell about 3 percent after six weeks 

of hurricane-affected data were removed, they were back on trend again by 2009, dropping -0.6 

percent. 

An additional perspective on trends in the petrochemical industry is provided in Figure 12: 

Weekly Percent Utilization of Refinery Operable Capacity, PADD 3, which summarizes 

utilization of available refining capacity, also reported by the Energy Information Administration 

of the U.S. Department of Energy (tonto.eia.doe.gov/dnav/pet/hist/wpuleus3w.htm). Capacity 

utilization, like inputs to refineries, is highly variable from week-to-week, but is clearly on a long 

term downward trend, having peaked in 1998 at 100.5 percent of operable capacity. Since then, 

despite considerable seasonal variation, it has fallen in most years, as evident from the quadratic 

regression fitted to the series. When considered on an annualized basis to smooth out short term 

fluctuations, average capacity utilization decreased -0.7 percent from 2006 to 2007, -4.3 percent 

from 2007 to 2008, and -1.1 percent from 2008 to 2009. The decade-long duration of this 

downward trend corroborates the earlier conclusion that the petroleum refining industry may 

likely be experiencing phenomena unrelated to the national recession that began in 2007. In 

summary, the data presented here indicate that the decreasing ozone in the HGB area is not likely 

primarily due to the recent economic downturn. 

I-90
60

65

70

75

80

85

90

95

100

Jan91Jan92Jan93Jan94Jan95Jan96Jan97Jan98Jan99Jan00Jan01Jan02Jan03Jan04Jan05Jan06Jan07Jan08Jan09

Source: U.S. Dept. of Energy, Energy Information Admin.

Katrina

Ike

%

Reported weekly capacity utilization (light olive)

Quadratic regression fit to weekly data (dark olive)

 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 

Figure 12: Weekly Percent Utilization of Refinery Operable Capacity, PADD 3 

Emission Trend Analysis 

As the EPA correctly stated on pages 102-103 of its modeling guidance, “a simpler (and more 

uncertain) way to qualitatively assess progress toward attainment is to examine recently observed 

air quality and emissions trends.” Refer to Guidance on the Use of Models and Other Analyses 

for Demonstrating Attainment of Air Quality Goals for Ozone, PM2.5, and Regional Haze, EPA -

454/B-07-002, April 2007. An emission trend analysis is less sophisticated, less certain, and less 

quantitative than other analyses, and for that reason, no emission trend data were included in the 

original proposal. The TCEQ contends that ambient NOX and VOC data are a more reliable 

indicator for historical emission trends than the emissions inventory data, which have known and 

well-documented problems for industrial emissions. Chapter 5 of the Attainment Demonstration 

SIP contains extensive historical ozone precursor trend analyses that are based upon monitoring 

data. These ozone precursor concentration trends are not subject to the underestimates observed 

in the industrial emissions inventories. 

However, the EPA’s request for a trend analysis for past and future emissions by major source 

category can be satisfied with the Reasonable Further Progress (RFP) emission estimates that are 

included in Section 2.7 of the HGB RFP SIP (pages 2-16 through 2-18). For more detail on the 

development of these emission inventories, the RFP SIP along with its accompanying appendices 

can be consulted. Figure 13: RFP NOX Emission Trends from 2002-2018 and Figure 14: RFP 

VOC Emission Trends from 2002-2018 present bar chart summaries of the controlled NOX and 

VOC emissions compared with uncontrolled emission totals. Tables 2-5 show the data used to 

make these graphs. 

I-91
HGB 8-County RFP Controlled Ozone Season 

Weekday NOx emissions

0

200

400

600

800

1000

1200

1400

2002 2008 2011 2014 2017 2018

tons per day

reductions

onroad

nonroad

area

point

Figure 13: RFP NOX Emission Trends from 2002-2018 

Includes each source category, based upon weekday emissions within the eight-county HGB area. 

The reductions shown here represent the mass of weekday NOX emissions eliminated by controls 

each year. 

HGB 8-County RFP Controlled Ozone Season 

Weekday VOC emissions

0

200

400

600

800

1000

1200

1400

2002 2008 2011 2014 2017 2018

tons per day

reductions

onroad

nonroad

area

point

Figure 14: RFP VOC Emission Trends from 2002-2018 

Includes each source category, based upon weekday emissions within the eight-county HGB area. 

The reductions shown here represent the mass of weekday VOC emissions eliminated by controls 

each year. 

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Table 2: HGB Eight-County RFP Uncontrolled Ozone Season Weekday NOX Emissions 

Calendar 

Year 

Point 

Sources 

Area 

Sources 

Non-Road 

Mobile 

On-Road 

Mobile 

Grand 

Total 

2002 339.29 89.11 166.98 387.09 982.47

2008 375.56 89.63 202.72 363.05 1,030.96

2011 383.85 93.90 210.01 372.46 1,060.22

2014 401.05 96.01 220.48 407.05 1,124.59

2017 421.57 98.23 230.99 432.04 1,182.83

2018 428.69 99.38 237.25 443.70 1,209.02

Table 3: HGB Eight-County RFP Controlled Ozone Season Weekday NOX Emissions 

Calendar 

Year 

Point 

Sources 

Area 

Sources 

Non-Road 

Mobile 

On-Road 

Mobile 

Grand 

Total 

2002 339.29 89.11 156.98 326.72 912.10

2008 155.73 89.63 149.44 175.80 570.60

2011 156.21 93.90 138.83 123.41 512.35

2014 157.17 96.01 128.45 86.61 468.24

2017 158.33 98.23 121.15 61.78 439.49

2018 158.75 99.38 119.88 55.39 433.40

Table 4: HGB Eight-County RFP Uncontrolled Ozone Season Weekday VOC Emissions

Calendar 

Year 

Point 

Sources 

Area 

Sources 

Non-Road 

Mobile 

On-Road 

Mobile 

Grand 

Total 

2002 316.62 407.61 100.15 189.08 1,013.46

2008 333.14 371.82 113.68 194.89 1,013.53

2011 338.75 382.72 120.10 205.03 1,046.60

2014 347.70 393.07 126.28 222.41 1,089.46

2017 358.79 404.84 132.38 237.86 1,133.87

2018 362.90 408.82 134.29 242.84 1,148.85

Table 5: HGB Eight-County RFP Controlled Ozone Season Weekday VOC Emissions

Calendar 

Year 

Point 

Sources 

Area 

Sources 

Non-Road 

Mobile 

On-Road 

Mobile 

Grand 

Total 

2002 316.62 407.61 84.32 132.64 941.19

2008 170.05 371.82 69.23 86.15 697.25

2011 164.33 379.04 64.03 68.35 675.75

2014 172.31 383.42 61.42 56.21 673.36

2017 181.86 394.74 60.05 48.39 685.04

2018 185.38 398.57 59.84 46.68 690.47

I-93
Additional Description of Retrospective Modeling for 2000 and 2006 

In accordance with EPA’s modeling guidance, the TCEQ performed a retrospective modeling 

analysis. The model’s response to emission changes between 2000 and 2006 was compared to 

the actual ozone design value changes between 2000 and 2006. The initial description of this 

analysis is presented in Appendix C: Photochemical Modeling for the HGB Attainment 

Demonstration SIP Revision for the 1997 Eight-Hour Ozone Standard of the current HGB 

Attainment Demonstration SIP. The purpose of this section is to describe more completely the 

modeled ozone response to the emission changes, and to compare the response in the 

retrospective analysis to other studies of modeled ozone response. 

Uncertainty does exist in both the 2000 and 2006 emission inventories, as it does for any set of 

emission estimates. The TCEQ has reconciled both of these inventories with observational data, 

so that the emission inputs used in the retrospective modeling analyses reflect available adjusted 

inventories. The TCEQ asserts that the retrospective analysis included in this modeling 

demonstration is appropriate, and is in accordance with EPA modeling and analyses guidance. 

The EPA’s modeling and analyses guidance does not precisely specify how a retrospective 

analysis should be done, but rather provides flexibility to states in how to carry out this kind of 

analysis. The TCEQ decided to use the same methodology as the EPA prescribes for an 

attainment demonstration, which includes modifying the observed design values by the RRF 

developed from the modeling. In this instance, the relative change between 2000 and 2006 was 

used in the same way that the relative change between 2006 and 2018 was used in the RRF 

calculation. 

Figure 15: Modeled and Observed Response to Emission Changes Between 2000 and 2006

shows how the model and observations respond to the emission changes between 2000 and 2006. 

The model predicts ozone values 15 percent lower with 2006 emissions compared to 2000 

emissions. But the observations show that the ozone design values actually decreased by 28 

percent from 2000 to 2006. Figure 16: Modeled and Observed Response to Weekend Emission 

Reductions shows how the model and observations respond to emission changes that occur 

between weekdays and weekends. For the weekend effect, the model response is also less than 

the observed response. Other studies have also found weaker responses by the model than 

observed. Another example of how photochemical grid models have underestimated the response 

to emission reductions can be found in a study by EPA scientist Alice Gilliland and colleagues, 

published in 2008 in Atmospheric Environment. In this study, the authors show that both relative 

and absolute model response to the NOX SIP call emission reductions is less than the observed 

responses. For the CB05 chemical mechanism (which is used by the TCEQ), the relative 

response in modeled ozone concentrations from 2002 to 2005 is about 73 percent of the observed 

relative response. The retrospective analysis presented in Appendix C: Photochemical 

Modeling for the HGB Attainment Demonstration SIP Revision for the 1997 Eight-Hour 

Ozone Standard is in agreement with other studies showing that modeled ozone response to 

emission controls is underestimated. 

I-94
Retrospective analysis, response to emission 

changes from 2000 to 2006

y = 0.7206x + 12.662

R2

 = 0.3995

75

80

85

90

95

100

105

110

75 80 85 90 95 100 105 110

2000 Ozone DV, ppb

2006 Ozone DV, ppb

y = 0.8501x + 2.6019

R2

 = 0.9026

Modeled

Observed

Linear (Observed)

Linear (Modeled)

Figure 15: Model and Observed Response to Emission Changes Between 2000 and 2006 

Each point represents the modeled or observed eight-hour ozone values for a particular 

monitoring site. The slopes of the response lines show the degree of ozone decrease from 2000 to 

2006. 

I-95
Observed and Modeled weekend effect, 

8-hour ozone

30

40

50

60

70

80

30 40 50 60 70 80

Wednesday 8-hr O3

Sun 8-hr O3

Mod Sunday

Obs Sunday

Obs Sun >50ppb

1:1 line

 -10%

 -20%

Observed and Modeled weekend effect, 

1-hour ozone

30

40

50

60

70

80

90

30 50 70 90

Wednesday 1-hr O3

Sun 1-hr O3

Mod Sunday

Obs Sunday

Obs Sun >50ppb

1:1 line

 -10%

 -20%

Observed and Modeled weekend effect, 

8-hour ozone

30

40

50

60

70

80

30 40 50 60 70 80

Wednesday 8-hr O3

Sat 8-hr O3

Mod Saturday

Obs Saturday

Obs Sat >50ppb

1:1 line

 -10%

 -20%

Observed and Modeled weekend effect, 

1-hour ozone

30

40

50

60

70

80

90

30 50 70 90

Wednesday 1-hr O3

Sat 1-hr O3

Mod Saturday

Obs Saturday

Obs Sat >50ppb

1:1 line

 -10%

 -20%

Figure 16: Modeled and Observed Response to Weekend Emission Reductions 

Blue squares show average daily maximum modeled ozone concentrations on Wednesday and 

Saturday or Sunday; green triangles show the average daily maximum observed ozone 

concentrations on Wednesday and Saturday or Sunday for days with maximum area-wide peak 

eight-hour ozone over 50 ppb. The latter values are more comparable to the modeled days, since 

the modeled days are usually high ozone days. The green triangles show greater degree of 

decrease during the weekends than the blue squares, indicating that the model has less response to 

emission decreases than the observations. 

I-96
Trends in the reactivity of volatile organic compounds in the HGB area 

Since 2000, the TCEQ and its research partners have routinely and systematically examined the 

reactivity of VOCs observed in Texas. Studies to date have shown that light alkenes (ethylene, 

propylene, butenes, and 1,3-butadiene) were the VOCs most likely to contribute to ozone 

formation in Houston; these studies helped form the basis for the HRVOC regulations currently in 

place in Houston. The purposes of this analysis are to track the progress in reducing HRVOC 

emissions in Houston by examining how HRVOC reactivity has changed over time, and to 

determine whether the official TCEQ HRVOCs still comprise the largest portion of the VOC 

reactivity. The analysis will also show how overall VOC reactivity has changed in recent years. 

The analysis provides weight of evidence that concentrations of ambient HRVOCs, and the 

emissions that put them into the air, are decreasing, and the reduced reactivity of the VOC 

mixture in Houston correlates with decreasing ozone concentrations. 

Background and methods 

The ability of VOCs to participate in ozone formation can be estimated by two methods. The first 

method is to calculate OH reactivity, i.e., to determine from chemical kinetics how often each 

VOC can react with the OH radical, which is the first step towards participating in the ozone 

formation process. The second method is to calculate the Maximum Incremental Reactivity, i.e., 

to determine the maximum amount of additional ozone that can be formed when adding an 

incremental amount of VOC to an urban air mixture rich in NOx. Both of these methods involve 

multiplying the observed concentration of each VOC by its distinctive reactivity factor. OH 

reactivity is determined by multiplying the concentration by the OH reaction rate coefficient; 

MIR reactivity is determined by multiplying the concentration by the Maximum Incremental 

Reactivity coefficient (Carter, 2008), and by a unit conversion factor that converts the MIR 

coefficient to molar units. The units for OH reactivity are second-1. This can be interpreted as the 

number of OH reactions per second (at standard temperature and pressure), but the calculated OH 

reactivities are only used in a relative sense in this application, not to calculate the number of 

reactions occurring. The units for MIR reactivity are ppbv of ozone formed per incremental 

addition of ppbv VOC, but since these units are primarily applicable for smog chamber or box 

model calculations, they are presented as unitless in this context. The calculated MIR reactivity 

is only used in a relative sense anyway, to identify which VOCs are likely to be more reactive 

than others under ideal reaction conditions, not to estimate how much ozone is formed from each 

VOC. 

The OH reactivity indicates how quickly a compound is consumed by reactions with the OH 

radical, and thus how quickly the VOC can enter the ozone formation process. OH reactivity is 

therefore only indirectly related to the amount of ozone formed by each particular VOC, but it 

can indicate how likely it is for an emitted VOC molecule to react in the hours immediately after 

it is emitted, and thus whether it is likely to create ozone on the day it is emitted. 

The MIR reactivity indicates how much ozone each VOC is capable of creating, given ideal 

ozone formation conditions. However, it does not tell how quickly the ozone could be formed. 

These calculations only give the approximate reactivity of VOCs, because they do not account for 

availability of radicals for reaction with the VOCs, or for competition among VOCs and other 

compounds for the available radicals. 

Geometric mean reactivities were calculated separately for each VOC. VOCs were classified into 

groups, and the calculated reactivity of all VOCs in the group were added together to get a 

cumulative reactivity for each group. Official TCEQ HRVOCs comprised the “light alkenes” 

group. Table A: Classification of measured VOCs shows how the classifications were made for 

I-97
the canister and auto-GC samples. Geometric mean reactivities were calculated for each year, for 

each monitoring site, for both every-sixth-day, 24-hour canister samples and continuous 1-hour 

automated gas chromatography measurements, for both OH and MIR reactivities. All available 

data were used in the analysis. OH reaction rate coefficients were obtained from Gilman et al., 

2009 and from Atkinson, 2002; MIR reactivity coefficients were obtained from Carter, 2008. 

Results and Discussion 

Figures 17-64 present the reactivity trends for canister and auto-GC data, for both the OH and 

MIR reactivity calculations, at each monitoring site. This analysis includes data from sites with 

at least four years of data, though many of the canister sites have more than 10 years of 

measurements. 

In general, the OH reactivity and MIR reactivity measures tell a similar story: the official TCEQ 

HRVOCs (ethylene, propylene, butene isomers, and 1,3-butadiene) comprise a larger portion of 

both the total OH and MIR reactivity than any of the other groups of compounds. The higher OH 

reactivity associated with light alkenes indicates that they can form ozone more quickly than the 

other compound groups, and the higher MIR reactivity indicates they are capable of creating 

more ozone than the other groups. 

 There is an apparent downward trend in total VOC reactivity at all sites, for both 

reactivity scales. The downward trends have not yet been tested for statistical 

significance. The downward trends in total reactivity due to substantial decreases in the 

concentrations of light alkenes (i.e., HRVOCs), though in some cases, decreases in heavy 

alkenes also play a role. 

 Monitoring sites in and near the industrial areas (Baytown, Galena Park, Clinton, HRM3, 

Deer Park, Nessler Pool) consistently observe higher VOC reactivity than sites in urban 

and suburban areas (Aldine, Bayland Park, Northwest Harris County). They also tend to 

show the greatest differences in proportion of total reactivity between the light alkenes 

and the other classes of compounds. 

 The greatest differences between TCEQ HRVOCs and other classes of compounds in 

MIR reactivity are observed at sites located near large ethylene and propylene sources: 

Baytown, Clute, Deer Park. 

 Although the sites far downwind of the industrial areas have considerably lower 

reactivities than sites near industrial areas, they still have a substantial portion of their 

reactivity composed of HRVOCs, and they still show decreasing trends in the reactivity 

of these HRVOCs over the period of study. 

 The reactivity calculations do not take into account reactions with unusual radicals such 

as chlorine. The MIR reactivity is based upon box modeling of typical urban mixtures 

using the SAPRC07 chemical mechanism. There is evidence to suggest that all of the 

major chemical mechanisms are missing an important radical formation pathway, and 

therefore the reactivity data presented here may not fully represent what is actually 

occurring in Houston’s atmosphere. Since there is no scientific consensus on the missing 

radical formation pathways, however, this assessment represents the best reactivity 

assessment currently available. 

 Studies of TexAQS 2000 data have shown that the 90th percentile of MIR reactivity 

values for aircraft canister samples was 166, and 90th percentile OH reactivity values was 

10. The TexAQS aircraft samples were taken throughout the HGB area, and therefore 

represent a wide geographic area. Subsequent TCEQ reactivity studies at individual 

monitoring sites have used these criteria to identify samples with high reactivity. In 

1998, the geometric mean MIR reactivity values exceeded 166 at the canister monitoring 

I-98
-1; Galena Park dropped below the 

high reactivity threshold in 2007. 

 Of the 46 trend analyses shown below, 45 show the lowest calculated reactivity occurring 

during the final year of the trend. The sole exception is the Galveston Airport MIR trend 

(Figure 12), for which the final year of 2007 is slightly higher than the lowest year of 

2005, though both years are at or below 30, i.e., less than 20% of the high reactivity 

threshold of 166. 

I-99
Figures 17 and 18: Geometric mean maximum incremental reactivity for VOCs measured in 24-

hour canisters at Baytown and Galena Park from 1998 through 2008. 

I-100

Maximum Incremental Reactivity (MIR) of VOCs 

BAYTOWN- 482010058 

1998 

De toiled c;:!QS::> 

1999 2000 2001 

- c2c3 - cydos - liqhl o\kenes 

2002 2003 2004 

- Qlk.c;mes 

- ho!oganotes 

- O)tygenoles 

2005 2006 2007 

- cromclic.:s - l"leo\ly o!kenes 

Maximum Incremental Reactivity (MIR) of VOCs 

GALENA PARK- 48201 005 7 

1998 

De toiled c;:IQS::> 

1999 2000 2001 

- c2c3 - cydos - li9hl o!kenes 

2002 2003 2004 

- Qlk.c;mes 

- ho!oganotes 

- O)tygenoles 

2005 2006 2007 

- cromclic;::; 

- t'leovy o!kenes 

2008 

2008 
Figures 19 and 20: Geometric mean maximum incremental reactivity for VOCs measured in 24-

hour canisters at Haden Road/HRM3 and Deer Park from 1998 through 2008. 

I-101
Figures 21 and 22: Geometric mean maximum incremental reactivity for VOCs measured in 24-

hour canisters at Clute and Aldine from 1998 through 2008. 

I-102
Figures 23 and 24: Geometric mean maximum incremental reactivity for VOCs measured in 24-

hour canisters at Bayland Park and Northwest Harris County from 1998 through 2008. 

I-103

Max·rrum ncrementc Recct"v"ty (rv R) of VOCs 

HOUSTON BAYLAND PARK- 4820' 0055 

10 

60 

!>() 

JO 

20 

10 

0 

1998 

Del oiled elou 

1999 '000 ?001 

- c2c3 - cydos - light olkenef-1 

2002 2003 2004 

- olkon~s 

- hologenotes 

- O)tygenoles 

2005 2006 200 / 

- Qromotic, 

hoovy olkones 

Maximum Incremento Recct;v·ty (MIR) of VOCs 

NORTHW[ST HARRIS COUNTY- 482010029 

1995 

Crlo' ed c:IOn 

I 999 ?000 ?001 

- c2c3 - t)'d09 

- 'ql'lt o~<.enes 

2002 2003 200< 

- co~.ore$ 

- l'!oog6f"'otes 

- O)t)'geno1es 

2005 2006 2007 

- oromot.t:'"i 

- heovy 0 II;QI"CS 

2006 

2006 
Figures 25 and 26: Geometric mean maximum incremental reactivity for VOCs measured in 24-

hour canisters at Shore Acres (1998-2008) and Clinton (1998-2006). 

I-104
Figures 27 and 28: Geometric mean maximum incremental reactivity for VOCs measured in 24-

hour canisters at Nessler Pool (Texas City) and Galveston Airport from 1998 through 2007. 

I-105
Figures 29 and 30: Geometric mean OH reactivity for VOCs measured in 24-hour canisters at 

Baytown and Galena Park from 1998 through 2008. 

I-106
Figures 31 and 32: Geometric mean OH reactivity for VOCs measured in 24-hour canisters at 

Haden Road/HRM3 and Deer Park from 1998 through 2008. 

I-107
Figures 33 and 34: Geometric mean OH reactivity for VOCs measured in 24-hour canisters at 

Clute and Aldine from 1998 through 2008. 

I-108
Figures 35 and 36: Geometric mean OH reactivity for VOCs measured in 24-hour canisters at 

Bayland Park and Northwest Harris County from 1998 through 2008. 

I-109
Figures 37 and 38: Geometric mean OH reactivity for VOCs measured in 24-hour canisters at 

Shore Acres (1998-2008) and Clinton (1998-2006). 

I-110
Figures 39 and 40: Geometric mean OH reactivity for VOCs measured in 24-hour canisters at 

Nessler Pool (Texas City) and Galveston Airport from 1998-2007. 

I-111
Figures 41 and 42: Geometric mean maximum incremental reactivity for VOCs measured by 

automated gas chromatography at Wallisville Road (2003-2008) and Cesar Chavez High School 

(2004-2008). 

I-112
Figures 43 and 44: Geometric mean maximum incremental reactivity for VOCs measured by 

automated gas chromatography at Channelview (2001-2008) and Clinton (1998-2008). 

I-113
Figures 45 and 46: Geometric mean maximum incremental reactivity for VOCs measured by 

automated gas chromatography at Danciger (2003-2008) and Deer Park (1998-2008). 

I-114
Figures 47 and 48: Geometric mean maximum incremental reactivity for VOCs measured by 

automated gas chromatography at Milby Park (2005-2008) and Haden Road/HRM3 (2001, 2003-

2008). 

I-115
Figures 49 and 50: Geometric mean maximum incremental reactivity for VOCs measured by 

automated gas chromatography at Lake Jackson (2003-2008) and Lynchburg Ferry (2003-2008). 

I-116
Figures 51 and 52: Geometric mean maximum incremental reactivity for VOCs measured by 

automated gas chromatography at Mustang Bayou (2003-2008) and Texas City (2003-2008). 

I-117
Figures 53 and 54: Geometric mean OH reactivity for VOCs measured by automated gas 

chromatography at Wallisville Road (2003-2008) and Cesar Chavez High School (2004-2008). 

I-118
Figures 55 and 56: Geometric mean OH reactivity for VOCs measured by automated gas 

chromatography at Channelview (2001-2008) and Clinton (1998-2008). 

I-119
Figures 57 and 58: Geometric mean OH reactivity for VOCs measured by automated gas 

chromatography at Danciger (2003-2008) and Deer Park (1998-2008). 

I-120
Figures 59 and 60: Geometric mean OH reactivity for VOCs measured by automated gas 

chromatography at Milby Park (2005-2008) and Haden Road/HRM3 (2001, 2003-2008). 

I-121
Figures 61 and 62: Geometric mean OH reactivity for VOCs measured by automated gas 

chromatography at Lake Jackson (2003-2008) and Lynchburg Ferry (2003-2008). 

I-122
Figures 63 and 64: Geometric mean OH reactivity for VOCs measured by automated gas 

chromatography at Mustang Bayou (2003-2008) and Texas City (2003-2008). 

Table A: Classification of measured VOCs 

Class Canister Compounds Auto-GC Compounds 

Alkanes isobutane isobutane 

I-123
n-Butane 

isopentane 

n-Pentane 

2,3-Dim

ethyl Butane 

2-Methyl Pentane 

2,2-Dimethyl Butane 

3-Methylpentane 

2-Methyl Pentane 

n-Hexane 

2,3-Dimethyl Pentane 

2,4-Dimethyl Pentane 

2-Methyl Hexane 

3-Methyl Hexane 

n-Heptane 

2,2,4-Trimethyl Pentane 

2,3,4-Trimethyl Pentane 

2-Methyl Heptane 

3-Methyl Heptane 

n-Octane 

n-Nonane 

n-Decane 

n-Undecane 

n-butane 

isopentane 

n-pentane 

2,2-dimethyl butane 

2,3-dimethyl butane 

2-methyl pentane 

3-methyl pentane 

n-hexane 

2,3-dimethyl pentane 

2,4-dimethyl pentane 

2-methyl hexane 

3-methyl hexane 

n-heptane 

2,2,4-trimethyl pentane 

2,3,4-trimethyl pentane 

2-methyl heptane 

3-methyl heptane 

n-octane 

n-nonane 

n-decane 

Aromatics Benzene 

Toluene 

Ethyl Benzene 

o-Xylene 

m-Xylene 

Styrene 

1,2,3-Trimethyl Benzene 

1,2,4-Trimethyl Benzene 

1,3,5-Trimethyl Benzene 

Isopropyl Benzene 

m-Ethyl Toluene 

n-Propyl Benzene 

o-Ethyl Toluene 

p-Ethyl Toluene 

m-Diethyl Benzene 

Naphthalene 

p-Diethyl Benzene 

t_Butylbenzene 

benzene 

toluene 

ethyl benzene 

o-xylene 

p-xylene 

styrene 

m-xylene 

1,2,3-trimethyl benzene 

1,2,4-trimethyl benzene 

1,3,5-trimethyl benzene 

isopropyl benzene 

m-ethyl toluene 

n-propyl benzene 

o-ethyl toluene 

p-ethyl toluene 

m-diethyl benzene 

p-diethyl benzene 

C2C3 Methanol 

Acetylene 

Ethane 

Acetone 

Propane 

acetylene 

ethane 

propane 

Cyclos Cyclopentane 

Cyclopentene 

Cyclohexane 

Methylcyclopentane 

Methylcyclohexane 

cyclopentane 

cyclopentene 

cyclohexane 

methyl cyclopentane 

methyl cyclohexane 

I-124
Halogenates Chloroprene 

Cis-1,3-dichloropropylene 

Methylene chloride 

Trans-1,3-dichloropropylene 

Trichlorofluoromethane 

Methyl Bromide 

Carbon Tetrachloride 

Chloroform 

1,1,2-Trichloroethane 

1,1-Dichloroethane 

1,2-Dibromoethane 

1,2-Dichloroethane 

1,1,1-Trichloroethane 

Perchloroethylene 

Trichloroethylene 

Vinyl Chloride 

Monochlorobenzene 

1,1,2,2-tetrachloroethane 

1,1-Dichloroethylene 

1,2-Dichloropropane 

2-Chloropentane 

none 

Heavy alkenes Isoprene 

trans-2-butene 

1-Pentene 

2-Methyl-2-Butene 

3-Methyl-1-Butene 

cis-2-Pentene 

trans-2-Pentene 

1-Hexene 

2-Methyl-1-Pentene 

4-Methyl-1-Pentene 

Cis-2-Hexene 

Trans-2-Hexene 

1-Heptene 

1-Octene 

1-pentene 

2-methyl-2-butene 

3-methyl-1-butene 

cis-2-pentene 

isoprene 

trans-2-pentene 

2-methyl-1-pentene 

Light alkenes ethene 

propene 

1,3-butadiene 

1-butene 

cis-2-butene 

ethene 

propene 

1,3-butadiene 

1-butene 

cis-2-butene 

trans-2-butene 

Oxygenates Acetaldehyde 

n-Butyl Alcohol 

Methyl Ethyl Ketone 

Vinyl Acetate 

Methyl t-Butyl Ether 

Hexanal 

n-butyl acrylate 

None 

I-125
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