FINAL REPORT

Development of Transformation Rate of SO2 to Sulfate for the Houston Ship Channel using the

TexAQS 2006 Field Study Data

AQRP Project 12-013

Prepared for: Dr. Elena C. McDonald-Buller

Texas Air Quality Research Program The University of Texas at Austin

Prepared by: Bonyoung Koo

Ralph Morris ENVIRON International Corporation

773 San Marin Drive, Suite 2115 Novato, California, 94998

www.environcorp.com P-415-899-0700 F-415-899-0707

October 2013

ENVIRON Project Number: 06-25699E

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ACKNOWLEDGMENT

The preparation of this report is based on work supported by the State of Texas through the Air Quality Research Program administered by The University of Texas at Austin by means of a Grant from the Texas Commission on Environmental Quality.

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CONTENTS

ACKNOWLEDGMENT ............................................................................................................I

EXECUTIVE SUMMARY ........................................................................................................ V

1.0 INTRODUCTION ............................................................................................................. 1

1.1 Background ...................................................................................................................... 1

1.2 Objectives ........................................................................................................................ 1

1.3 Report Organization and Accessibility ............................................................................. 1

2.0 ASSESSMENT OF FIELD STUDY DATA............................................................................... 2

2.1 TexAQS 2006 Field Study ................................................................................................. 2

2.2 Assessment of Flight Data ............................................................................................... 3

3.0 THREE-DIMENSIONAL GRID MODELING ........................................................................ 46

3.1 Grid Model ..................................................................................................................... 46

3.2 Modeling Domain .......................................................................................................... 46

3.3 Model Inputs ................................................................................................................. 50

3.4 Model Output Interval ................................................................................................... 55

4.0 RESULTS AND RECOMMENDATION .............................................................................. 58

4.1 Model Evaluation ........................................................................................................... 58

4.2 Recommendation .......................................................................................................... 66

5.0 REFERENCES ................................................................................................................ 68

TABLES Table 2-1. NOAA P-3 flights during the TexAQS 2006 field study. ........................................... 2

Table 3-1. Horizontal grid definitions of the 4 km HGB/BPA grid and the 1 km sub-grids. ...................................................................................................................... 49

Table 3-2. Vertical model layer structure (AGL = Above Ground Level). ............................... 49

Table 3-3. Domain-wide daily total SO2 emissions (tons) for the selected modeling dates. ..................................................................................................... 50

FIGURES Figure 2-1. NOAA P-3 flight track map during the 2006 TexAQS field campaign...................... 3

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Figure 2-2. (a) September 13 P-3 flight plan; (b) measured SO2 and SO4 concentrations (µg/m3) and flight altitudes (m). .................................................... 8

Figure 2-3. (a) September 15 P-3 flight plan; (b) measured SO2 and SO4 concentrations (µg/m3) and flight altitudes (m). .................................................. 10

Figure 2-4. (a) September 19 P-3 flight plan; (b) measured SO2 and SO4 concentrations (µg/m3) and flight altitudes (m). .................................................. 13

Figure 2-5. (a) September 20 P-3 flight plan; (b) measured SO2 and SO4 concentrations (µg/m3) and flight altitudes (m). .................................................. 16

Figure 2-6. (a) September 21 P-3 flight plan; (b) measured SO2 and SO4 concentrations (µg/m3) and flight altitudes (m). .................................................. 20

Figure 2-7. (a) September 25 P-3 flight plan; (b) measured SO2 and SO4 concentrations (µg/m3) and flight altitudes (m). .................................................. 22

Figure 2-8. (a) September 26 P-3 flight plan; (b) measured SO2 and SO4 concentrations (µg/m3) and flight altitudes (m). .................................................. 25

Figure 2-9. (a) September 27 P-3 flight plan; (b) measured SO2 and SO4 concentrations (µg/m3) and flight altitudes (m). .................................................. 30

Figure 2-10. (a) September 29 P-3 flight plan; (b) measured SO2 and SO4 concentrations (µg/m3) and flight altitudes (m). .................................................. 34

Figure 2-11. (a) October 5 P-3 flight plan; (b) measured SO2 and SO4 concentrations (µg/m3) and flight altitudes (m). ........................................................................... 36

Figure 2-12. (a) October 6 P-3 flight plan; (b) measured SO2 and SO4 concentrations (µg/m3) and flight altitudes (m). ........................................................................... 38

Figure 2-13. (a) October 8 P-3 flight plan; (b) measured SO2 and SO4 concentrations (µg/m3) and flight altitudes (m). ........................................................................... 42

Figure 2-14. (a) October 12 P-3 flight plan; (b) measured SO2 and SO4 concentrations (µg/m3) and flight altitudes (m). .................................................. 45

Figure 3-1. Map of the 4 km HBB/BPA grid along with the 1 km sub-grids (red rectangles). ............................................................................................................ 48

Figure 3-2. Daily total SO2 emissions (tons) on September 19, 2006 within the modeling domain by source category. .................................................................. 52

Figure 3-3. Daily total SO2 emissions (tons) from all the point sources and ships at and around the Houston Ship Channel area on September 19, 2006; the red rectangle indicates a source area that was tracked separately as the Houston Ship Channel sources. .................................................................. 53

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Figure 3-4. Average vertical concentration profiles of SO2 and sulfate at the west, east, south, and north boundaries of the 4-km modeling grid over the modeling period. ................................................................................................... 54

Figure 3-5. Modeled SO2 and sulfate concentrations of the September 19 flight transects with varying output intervals. ............................................................... 57

Figure 4-1. Observed and modeled SO2 and sulfate concentrations and modeled sulfate contributions for Transect E-F of the September 19 flight. ...................... 59

Figure 4-2. Observed and modeled SO2 and SO4 concentrations for the September 19 flight; red dotted boxes indicate the Ship Channel plumes; the model results are of the run with a conversion rate of 0.1 hr-1. ........................... 63

Figure 4-3. Root mean square errors of the modeled average excess SO4 to SO2 ratios. ..................................................................................................................... 64

Figure 4-4. Observed vs. modeled ratio (R) of sulfate to SO2 average excess concentrations; dotted lines are linear regression (LR) lines. .............................. 65

Figure 4-5. Box and whisker plots for ambient temperature, pressure and water vapor mixing ratio during the selected flights; diamond markers represent mean values. ......................................................................................... 67

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EXECUTIVE SUMMARY

In 2010, the US Environmental Protection Agency (EPA) revised the 1-hour sulfur dioxide (SO2) primary National Ambient Air Quality Standard (NAAQS) to be much more stringent, which can possibly affect attainment status in many areas in the US including the Houston region. Conversion of SO2 to sulfate in the atmosphere is a complex process involving various chemical species and multiple phases. However, the EPA-recommended approach for modeling 1-hour SO2 is to use the American Meteorological Society/Environmental Protection Agency Regulatory Model Improvement Committee Model (AERMOD) steady-state Gaussian plume model assuming no chemical transformation of SO2. This approach may not be adequate under certain atmospheric conditions, such as the highly reactive atmospheric conditions that occur in the Houston Ship Channel.

To address this issue, this study determines a representative SO2 transformation rate for the Houston Ship Channel area using measurements from the National Oceanic and Atmospheric Administration (NOAA) P-3 aircraft collected during the 2006 Texas Air Quality Study (TexAQS) that can be used with the AERMOD model to simulate 1-hour SO2 concentrations. The P-3 aircraft research platform provided high time resolution measurement data for SO2 and sulfate as well as meteorological data such as temperature and wind direction through 16 flights between September 11 and October 12, 2006. We assessed these flight data and selected four flights that pass across the Houston Ship Channel plumes and have relatively small interferences from background and sources outside the ship channel.

The selected flight data was then simulated using a three-dimensional grid model to find what transformation rate best fits the observations. The Comprehensive Air-quality Model with Extensions (CAMx) was used for this grid modeling. Instead of the full gas and aerosol chemistry mechanisms available in CAMx, a special chemistry mechanism that models a pseudo first-order conversion of SO2 to sulfate is used to mimic AERMOD’s treatment of SO2 transformation (exponential decay).

The model inputs of meteorological conditions and SO2 emissions over the Houston modeling domain were provided by the Texas Commission on Environmental Quality (TCEQ). Boundary conditions (SO2 and sulfate) to the modeling grid were extracted from a previous 2006 US modeling results. The model used multiple tracers to distinguish direct contributions of the Ship Channel emissions from those of other nearby sources and regional background. The model results with varying SO2-to-sulfate conversion rate were then evaluated against the P-3 aircraft measurement data.

To quantify the model performance, we employed the “average excess above background” concentration that is defined as a cumulative concentration difference (total – background) across a Ship Channel plume normalized by the plume width. This quantity was used to avoid the effect of inaccuracies in meteorological model inputs (e.g., wind direction) and regional background (through boundary conditions). More specifically, modeled ratios of sulfate to SO2

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average excess above background concentrations were evaluated against the corresponding observed ratios as this ratio is better suited to evaluate the SO2-to-sulfate conversion rate within the Houston Ship Channel.

The results showed that the SO2-to-sulfate conversion rate of 0.04 hr-1 (half-life of 17 hours) best fitted the aircraft measurement data for all selected flights. Therefore, we recommend using this conversion rate for transformation of SO2 in AERMOD modeling to address the new 1-hour SO2 NAAQS for the Houston Ship Channel sources. Our estimated SO2 conversion rate in the Houston Ship Channel plumes is higher than previously reported conversion rates in the power plant plumes, which is expected because high NOx concentrations in the power plant plumes would inhibit photochemistry. However, it should be noted that our result is based on a small number of flight data whose ambient conditions are limited to afternoon on late summer days in the region. Thus, caution is needed when applying this conversion rate to a significantly different condition (e.g., winter or nighttime).

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1.0 INTRODUCTION

1.1 Background In June 2010, US Environmental Protection Agency (EPA) promulgated a new 1-hour SO2 primary National Ambient Air Quality Standard (NAAQS) with a threshold of 75 ppb (EPA, 2010a). The 1-hour SO2 NAAQS is much more stringent and replaces the old 24-hour (140 ppb) and annual (30 ppb) SO2 NAAQS. States are required to submit 1-hour SO2 State Implementation Plans (SIPs) by February 2014 that demonstrates compliance with the NAAQS by August 2017. Preliminary modeling indicates that SO2 emissions for numerous sources will result in near-by exceedances of the 1-hour SO2 NAAQS. Fossil-fueled power plants (73%) and industrial facilities (20%) are the main sources of SO2 emissions in the US. Photochemical oxidants will convert some SO2 to sulfate thereby reducing SO2 concentrations. However, the EPA-recommended model for near-source 1-hour SO2 modeling is the AERMOD steady-state Gaussian plume model (EPA, 2010b) that does not treat photochemical oxidants and has a very simple treatment of chemistry (exponential decay). EPA recommends that AERMOD be run with no SO2 conversion for addressing 1-hour SO2 NAAQS issues. This assumption may be appropriate for fossil-fueled power plants where the high NOX concentrations inhibit photochemistry and consequently SO2 oxidation near the source. But it may not be appropriate for the Houston Ship Channel where the atmosphere can be very reactive due to highly reactive volatile organic compound (HRVOC) emissions resulting in faster SO2 to sulfate conversion rates.

1.2 Objectives The purpose of this research effort is to use enhanced field study data from the 2006 Texas Air Quality Study (TexAQS) to develop SO2 to sulfate conversion rates for the Houston Ship Channel that can be used with AERMOD for modeling to address the new 1-hour SO2 NAAQS. More specifically, measurement data collected by the National Oceanic and Atmospheric Administration (NOAA) P-3 aircraft is simulated using a three-dimensional (3-D) grid model to infer what SO2 to sulfate conversion rate is needed for SO2 emissions emitted in the Houston Ship Channel to produce the SO2 and sulfate concentrations observed by the P-3 aircraft.

1.3 Report Organization and Accessibility Section 2 describes the 2006 TexAQS aircraft measurement data and discusses selection of flight data to be analyzed in this study. Section 3 describes the 3-D grid model set-up for simulation of the selected flight episodes. Section 4 discusses the grid model evaluation results and presents our recommendations.

This report has been written to conform to TCEQ's accessibility guidelines. For example, all figures and tables are described using alternative text entries, and Microsoft Word styles were used in the formatting of the document.

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2.0 ASSESSMENT OF FIELD STUDY DATA

2.1 TexAQS 2006 Field Study The 2006 TexAQS included an intensive field campaign, TexAQS/Gulf of Mexico Atmospheric Composition and Climate Study (GoMACCS), which was conducted in August-October 2006 in the near shore Gulf of Mexico and in and around the Houston/Galveston region (Parrish et al., 2009). This campaign consists of multiple measurement platforms, including the NOAA P-3 aircraft and NOAA R/V Ronald H. Brown ship, and provides high time resolution measurement data for various atmospheric pollutants in both gas and aerosol phases. In this project, we focused on the NOAA P-3 aircraft measurement data for SO2 and particulate sulfate upwind and downwind of the Houston Ship Channel. SO2 was measured using UV Pulsed Fluorescence with time resolution of 1 second. Particulate sulfate was measured using an Aerosol Mass Spectrometer (AMS) at 15-second intervals and/or Particle into Liquid Sampling (PiLS) at 3-minute intervals. Table 2-1 lists the 16 P-3 flights flown during the TexAQS 2006 field study, their purpose and whether they would be a candidate for use in this study to characterize SO2 to SO4 conversion rates in the Houston ship channel.

Table 2-1. NOAA P-3 flights during the TexAQS 2006 field study. Flight Date Purpose Candidate

September 11 Ronald H. Brown overflight and oil platforms in Gulf September 13 Houston and Dallas emissions characterization Yes September 15 Houston emissions characterization Yes September 16 Northeastern Texas power plants September 19 Houston urban plume, refineries Yes September 20 Houston urban plume, ship channel Yes September 21 Houston urban plume Yes September 25 Houston, Dallas urban plumes and power plants Yes September 26 Houston urban plume and industrial sources Yes September 27 Houston urban plume and industrial sources Yes September 29 Houston urban plume into night time Yes October 5 Houston urban plume and power plants Yes October 6 Houston urban plume and power plants Yes October 8 Houston urban plume into night time Yes October 10 Oklaunion power plant plume night flight October 12 Houston urban plume night flight Yes Figure 2-1 shows all 16 flight tracks on the eastern Texas map. Prescreening excluded flight tracks mostly far from the Houston Ship Channel area from further consideration: September 11 (over the Gulf of Mexico); September 16 (over Dallas/Fort Worth); and October 10 (downwind of Oklaunion Power Plan near Vernon, TX).

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Figure 2-1. NOAA P-3 flight track map during the 2006 TexAQS field campaign.

2.2 Assessment of Flight Data Direct analysis of conversion rate in plumes requires unique plume identification across several transects to track conversion and estimate plume age. Based on discussion with Dr. David Parrish and Dr. Charles Brock at NOAA, however, such plume identification appears to be difficult with the 2006 TexAQS P-3 aircraft data because of numerous SO2 plumes from local sources, complex meteorology, and background sulfate contributions. To circumvent this problem, this study employs a grid model with a simplified SO2 to sulfate conversion mechanism for sources in the Houston Ship Channel and determines the conversion rate that best fits the observed SO2 and sulfate concentrations.

Due to limited time and resources, the grid model is applied to simulate a selected set of the P-3 flight data. The selection criteria were as follows:

• The flight data should have more than one transect that show complete and clearly distinguishable Ship Channel plume

• Not all of the selected transects should be the same distance from the Ship Channel sources

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• SO2 and sulfate peaks of the Ship Channel plume on the selected transects should not be too narrow to be modeled by the grid model (our finest grid resolution is 1 km; see Section 3.2)

Below is our flight-by-flight assessment along with the selection result.

September 13 (Figure 2-2): On this day, the P-3 aircraft flew over both the Houston and Dallas areas. During the flight over Houston, only one transect (Transect A-B) passed downwind of the Houston Ship Channel (average wind direction was southerly). Moreover, the SO2 measurement data is missing between 12:19 and 12:20. Not selected.

September 15 (Figure 2-3): Average wind direction was southeasterly during this flight. Transect G-H passed directly over the Houston Ship Channel area, and the sharp SO2 peak between 13:12 and 13:13 coincide with the Ship Channel location. However, the peak is too narrow to be considered by the grid model. The next transect (I-J) passed close to the Parish power plant (indicated as star in the flight path maps) around 13:32, and picked up a small SO2 signal at that time. The wide peak of SO2 between 13:36 and 13:43 should be the Ship Channel plume. The SO2 signal from the Ship Channel is less clear on Transect K-L. The SO2 peak between 14:20 and 14:23 is probably from the Parish power plant. Transect M-N shows no distinguishable peak. Since only one transect (I-J) shows clear (and suitable-for-grid-model) Ship Channel plumes, this flight was not selected.

September 19 (Figure 2-4): Transects C-D, E-F and G-H overlap the same path approximately 30 km downwind of the Houston Ship Channel at an altitude of about 500 m. The SO2 peaks between 12:00 and 12:06 on Transect C-D, between 12:12 and 12:17 on Transect E-F, and between 12:25 and 12:31 on Transect G-H are all likely showing the Ship Channel plume, which is again detected in the next downwind transect (between 12:50 and 12:55 on Transect I-J). The SO2 peaks between 12:35 and 12:37 on Transect G-H and between 12:43 and 12:44 on Transect I-J are probably indicating other local sources in Texas City. Transect K-L shows a sharp SO2 peak from the Parish power plant plume which partially overlaps with the Ship Channel plume due to northeasterly wind. Similarly, the Ship Channel plume cannot be easily identified in the transects further downwind. Selected.

September 20 (Figure 2-5): The sharp SO2 peak between 12:42 and 12:43 on Transect E-F clearly indicate the Houston Ship Channel plume as the P-3 aircraft flew close to the Ship Channel sources during the segment. Transect I-J passes the Ship Channel plume between 13:36 and 13:39, and Transect G-H between 13:06 and 13:10. However, Transect I-J appears to cover only a part of the Ship Channel plumes, and the peak SO2 concentration on Transect G-H is not clear due to gaps (missing data) on the measurement. The sharp peak around 13:49 on Transect K-L is obviously the Parish power plant plume. The peak between 13:44 and 13:48 is probably the Ship Channel plume, but again incomplete due to missing data. The peaks between 14:22 and 14:32 on Transect M-N are all due to the Parish power plant plume as the aircraft circled around the small area right west of the power plant. The smaller peak between 14:32 and 14:35 might belong to the Ship Channel plume, but is partially overlapping with the Parish

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plume next to it. Transect Q-R is also showing the Parish and Ship Channel plumes that are partially overlapping with each other, and sulfate measurement data is missing during much of this transect. Since only one transect (E-F) shows clear and complete Ship Channel plumes, this flight was not selected.

September 21 (Figure 2-6): The SO2 peak around 13:40 on Transect E-F should indicate the Parish power plant plume while multiple sharp peaks between 13:44 and 13:48 are probably from the Houston Ship Channel emissions. However, these Ship Channel SO2 peaks are too narrow as this flight path is too close to the sources. Transects Q-R, S-T, U-V and W-X cross the same path as Transect E-F with varying altitudes and also show too sharp SO2 peaks (note that time axes of the plots for Transects S-T, U-V and W-X are enlarged). The peak around 14:06 on Transect G-H is probably the Ship Channel plume while the peak around 14:11 appears to be affected by the Parish power plant plume. On Transect I-J (approximately 70 km downwind of the Ship Channel), the Ship Channel plume becomes too dispersed to be distinguishable. Since only one transect (G-H) shows Ship Channel peaks suitable for the grid modeling, this flight was not selected.

September 25 (Figure 2-7): The SO2 peaks around 16:05 (Transect C-D), around 16:24 (Transect E-F), around 16:39 (Transect G-H), and around 17:06 (Transect I-J) are likely showing progress of the same plume from the Houston Ship Channel. The peaks around 16:45 and around 17:00 must be the Parish power plant plume. The SO2 peaks near 16:29, around 16:35 and around 17:10 probably indicate the same plume, but its source is not clear. Although the SO2 data is showing Ship Channel plumes on some of the transect segments, this flight is entirely missing the sulfate data, thus was not selected.

September 26 (Figure 2-8): The SO2 peaks between 13:07 and 13:13 (Transect C-D), between 13:30 and 13:36 (Transect E-F) and between 13:55 and 14:01 (Transect G-H) show three distinct plumes (the left two likely belong to the Ship Channel plumes). As these plumes dispersed, the peaks merged together on transects further downwind. The high peaks in the western segments of Transects I-J, O-P, K-L and M-N show the SO2 plume from the Parish power plant. Selected.

September 27 (Figure 2-9): Transects C-D, E-F, and G-H appear to show two distinct Ship Channel peaks around at 15:17, 15:38, and 15:58, respectively, but missing data makes it difficult to assess the plumes. The peaks around 15:11, 15:43, and 15:53 likely belong to the Parish power plant plume. At downwind transects (transect I-J and farther) the two Ship Channel peaks are merged into one (around 16:20, 16:40 and 17:28). On the farthest transect (S-T), the Ship Channel plume appears quite dispersed and partially overlapped with the Parish plume. Transects M-N and O-P shows SO2 and SO4 concentrations at altitudes of approximately 1100 m and 1500 m, respectively: The former shows similar peaks to other transects while the plot for the latter is noisier thus not very useful. Finally, transect U-V flew the same path as transect C-D but a few hours later, and shows larger peaks than the latter. Selected.

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September 29 (Figure 2-10): The SO2 peaks between 15:27 and 15:34 on Transect A-B are showing the Houston Ship Channel plume. Transect M-N shows changes in the Ship Channel plume SO2 and sulfate concentrations with gradually changing flight altitude, which would be difficult to be modeled by a grid model with discrete vertical layers (in our model, the layer thickness is 80-90 m in this altitude range). Transects G-H, I-J, K-L and O-P pass the same horizontal path with varying altitude, but the Ship channel plume is not clearly distinguishable on these transects. The farthest transect (E-F) does not show a distinguishable Ship Channel plume, either. Not selected.

October 5 (Figure 2-11): Three SO2 peaks between 12:39 and 12:45 on Transect A-B and between 12:59 and 13:05 on Transect C-D likely belong to the Ship Channel plume. Transect E-F probably crossed the Ship Channel plume around 13:26, but SO2 measurement data is missing between 13:25 and 13:26. The Parish power plant plume created a sharp SO2 peak around 13:29-13:30 on Transect E-F. The peak between 13:54 and 13:56 on Transect G-H indicates the Parish plume possibly overlapped with the Ship Channel plume. Since two transects (A-B and C-D) are usable, this flight was selected.

October 6 (Figure 2-12): The SO2 peaks between 12:21 and 12:26 on Transect A-B must be the Houston Ship Channel plumes, but the SO2 data is missing around 12:22. The Ship Channel plume and the Parish plume are close to each other and partially overlapping each other on Transects C-D (between 13:28 and 13:33) and E-F (between 13:51 and 13:56 and between 14:06 and 14:12). Not selected.

October 8 (Figure 2-13): Transects G-H through O-P all pass the same horizontal path but at different altitudes. The transects with altitudes lower than 700 m show SO2 peaks from the Ship Channel plume, but no clear peak on the higher transects. Based on the average wind direction during the flight (southeasterly), the plume shown on Transect A-B is probably not from the Ship Channel. The peaks on Transects C-D, Q-R and S-T likely belong to the Parish plume. Clear Ship Channel plumes are available only on Transects G-H, I-J and K-L which are all the same distance from the Ship Channel sources; therefore, this flight was not selected.

October 12 (Figure 2-14): The SO2 peaks between 21:59 and 22:01 on Transect C-D should belong to the Ship Channel plume while the greater peak around 21:54 likely belongs to the Parish plume. However, it is expected based on the average wind direction that another Ship Channel SO2 peak should be seen between 21:57 and 21:58. Unfortunately, the SO2 measurement data is missing for this segment. The SO2 peaks shown between 22:08 and 22:11 on Transects E-F and G-H likely belong to the Ship Channel plume, but the aircraft turned to opposite direction (also changing its altitude) in the middle of the plume instead of completely crossing it. Since the Parish plume crossed Transect C-D around 21:54, extending the plume direction suggests that the SO2 peaks around 22:33 on Transect K-L also likely belong to the Parish plume. The three SO2 peaks on the right of the Parish plume likely belong to the Ship Channel plume, and the two plumes partially overlap each other. On Transect M-N which is farther downwind, they are no longer distinguishable. Since no Transect shows a complete and clearly distinguishable Ship Channel plume, this flight was not selected.

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Based on the above assessment, the following flights were selected for our 3-D grid model simulations:

• September 19 flight • September 26 flight • September 27 flight • October 5 flight

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(a) P-3 flight plan

(b) SO2 and SO4 measurement data and flight altitude

Figure 2-2. (a) September 13 P-3 flight plan; (b) measured SO2 and SO4 concentrations (µg/m3) and flight altitudes (m).

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(a) P-3 flight plan

(b) SO2 and SO4 measurement data and flight altitude

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Figure 2-3. (a) September 15 P-3 flight plan; (b) measured SO2 and SO4 concentrations (µg/m3) and flight altitudes (m).

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(a) P-3 flight plan

(b) SO2 and SO4 measurement data and flight altitude

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Figure 2-4. (a) September 19 P-3 flight plan; (b) measured SO2 and SO4 concentrations (µg/m3) and flight altitudes (m).

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(a) P-3 flight plan

(b) SO2 and SO4 measurement data and flight altitude

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Figure 2-5. (a) September 20 P-3 flight plan; (b) measured SO2 and SO4 concentrations (µg/m3) and flight altitudes (m).

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(a) P-3 flight plan

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(b) SO2 and SO4 measurement data and flight altitude

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Figure 2-6. (a) September 21 P-3 flight plan; (b) measured SO2 and SO4 concentrations (µg/m3) and flight altitudes (m).

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(a) P-3 flight plan

(b) SO2 and SO4 measurement data and flight altitude

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Figure 2-7. (a) September 25 P-3 flight plan; (b) measured SO2 and SO4 concentrations (µg/m3) and flight altitudes (m).

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(a) P-3 flight plan

(b) SO2 and SO4 measurement data and flight altitude

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Figure 2-8. (a) September 26 P-3 flight plan; (b) measured SO2 and SO4 concentrations (µg/m3) and flight altitudes (m).

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(a) P-3 flight plan

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(b) SO2 and SO4 measurement data and flight altitude

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Figure 2-9. (a) September 27 P-3 flight plan; (b) measured SO2 and SO4 concentrations (µg/m3) and flight altitudes (m).

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(a) P-3 flight plan

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(b) SO2 and SO4 measurement data and flight altitude

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Figure 2-10. (a) September 29 P-3 flight plan; (b) measured SO2 and SO4 concentrations (µg/m3) and flight altitudes (m).

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(a) P-3 flight plan

(b) SO2 and SO4 measurement data and flight altitude

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Figure 2-11. (a) October 5 P-3 flight plan; (b) measured SO2 and SO4 concentrations (µg/m3) and flight altitudes (m).

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(a) P-3 flight plan

(b) SO2 and SO4 measurement data and flight altitude

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Figure 2-12. (a) October 6 P-3 flight plan; (b) measured SO2 and SO4 concentrations (µg/m3) and flight altitudes (m).

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(a) P-3 flight plan

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(b) SO2 and SO4 measurement data and flight altitude

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Figure 2-13. (a) October 8 P-3 flight plan; (b) measured SO2 and SO4 concentrations (µg/m3) and flight altitudes (m).

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(a) P-3 flight plan

(b) SO2 and SO4 measurement data and flight altitude

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Figure 2-14. (a) October 12 P-3 flight plan; (b) measured SO2 and SO4 concentrations (µg/m3) and flight altitudes (m).

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3.0 THREE-DIMENSIONAL GRID MODELING

3.1 Grid Model For this study, we employed the Comprehensive Air-quality Model with Extensions (CAMx; www.camx.com) version 5.41 to simulate SO2 and sulfate in the Houston Ship Channel area. CAMx is a publically available, state-of-science ‘One Atmosphere’ photochemical grid model capable of addressing ozone, particulate matter, visibility and acid deposition at the regional scale. CAMx has been widely used in scientific and regulatory modeling for various regions in the US, and TCEQ is currently using CAMx for their ozone State Implementation Plan (SIP) modeling. Since we are only modeling the SO2 to sulfate conversion, we used a special chemistry mechanism that models a pseudo first-order conversion of SO2 to sulfate, instead of the full gas and aerosol-phase chemistry mechanisms available in CAMx.

SO2 𝑘 �⎯⎯� SO4 (k represents the reaction rate constant)

𝑑[SO2]𝑑𝑡

= −𝑘[SO2] ([SO2] represents the concentration of SO2)

This approach supports the goal of developing a SO2 conversion rate that may be used by AERMOD, which is limited to using first-order (i.e., linear) chemical transformation. We used multiple tracers for SO2 and sulfate to separately track sources in the Houston Ship Channel, other nearby sources and the regional background to help in quantifying the contributions and interference due to SO2 sources outside of the Houston ship channel.

3.2 Modeling Domain Our modeling domain covers the Houston-Galveston-Brazoria/Beaumont-Port Arthur (HGB/BPA) region with 4 km horizontal grid resolution (Figure 3-1). The modeling grid is based on the map projection used by the Regional Planning Organizations (RPOs): Lambert Conformal Conic projection with 1st true latitude of 33°N, 2nd true latitude of 45°N, center longitude of 97°W and center latitude of 40°N. We introduced nested grids with finer resolution (1 km) to take advantage of the continuous measurement data as much as possible. This was done using the CAMx flexi-nesting feature which does not require additional model inputs (met, surface emissions, etc.) for the nested grid (inputs for the new grid were interpolated from the parent grid). The location and size of these nested grids vary by the flight routes that were modeled (see the red rectangles in Figure 3-1). Table 3-1 presents horizontal grid definitions of the 4 km HGB/BPA grid and the 1 km sub-grids. The vertical modeling grid was determined based on the meteorological modeling setup: Weather Research and Forecasting (WRF) model was used in this study. Table 3-2 provides the heights of the CAMx vertical layers and the corresponding WRF layers.

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Figure 3-1. Map of the 4 km HBB/BPA grid along with the 1 km sub-grids (red rectangles).

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Table 3-1. Horizontal grid definitions of the 4 km HGB/BPA grid and the 1 km sub-grids. Modeling Grid Origin Coordinates (km) Number of Grid Cells

X Y Column Row 4 km HGB/BPA grid 32 -1264 92 65

1 km sub-grids September 19 115 -1213 94 98 September 26 119 -1185 94 66 September 27 131 -1169 102 82 143 -1081 98 66 October 5 119 -1225 98 106

Table 3-2. Vertical model layer structure (AGL = Above Ground Level). Corresponding

WRF Layer Layer Top (m AGL)

CAMx Layer Layer Center (m AGL)

Thickness (m)

38 15179.1 28 13637.9 3082.5 36 12096.6 27 10631.6 2930 32 9166.6 26 8063.8 2205.7 29 6960.9 25 6398.4 1125 27 5835.9 24 5367 937.9 25 4898 23 4502.2 791.6 23 4106.4 22 3739.9 733 21 3373.5 21 3199.9 347.2 20 3026.3 20 2858.3 335.9 19 2690.4 19 2528.3 324.3 18 2366.1 18 2234.7 262.8 17 2103.3 17 1975.2 256.2 16 1847.2 16 1722.2 249.9 15 1597.3 15 1475.3 243.9 14 1353.4 14 1281.6 143.6 13 1209.8 13 1139 141.6 12 1068.2 12 998.3 139.7 11 928.5 11 859.5 137.8 10 790.6 10 745.2 90.9 9 699.7 9 654.7 90.1 8 609.7 8 565 89.3 7 520.3 7 476.1 88.5 6 431.8 6 387.9 87.8 5 344 5 300.5 87.1 4 256.9 4 213.8 86.3 3 170.6 3 127.8 85.6 2 85 2 59.4 51 1 33.9 1 17 33.9

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3.3 Model Inputs As mentioned above, the WRF model was used to produce meteorological conditions for our 3-D grid modeling. TCEQ provided the 2006 September and October WRF simulation outputs for the modeling domain, which were then processed to prepare the CAMx met inputs using the WRFCAMx processor.

SO2 emissions for the grid modeling were obtained from TCEQ for the following source categories:

• Hourly point source emissions derived from EPA’s Acid Rain database (ARD) • Other point source emissions from the ozone season emission data (OSD) • Ship emissions (SHIP) • Area source emissions (AREA)

Figure 3-2 shows spatial plot of daily total SO2 emissions on September 19, 2006 for each of the four source categories. No daily variation exists in the SO2 emissions except for the ARD and AREA emissions. The Acid Rain database provides real-time emissions recorded by a continuous emission monitoring (CEM) system. For the anthropogenic area sources, three representative temporal allocations were applied to weekdays, Saturdays and Sundays (the modeling days are all weekdays though). Table 3-3 lists domain-wide daily total SO2 emissions for each source type.

Table 3-3. Domain-wide daily total SO2 emissions (tons) for the selected modeling dates. Source Type Sep. 19 (Tue) Sep. 26 (Tue) Sep. 27 (Wed) Oct. 5 (Thu)

ARD 222 216 206 219 OSD 165 165 165 165 SHIP 80 80 80 80 AREA 52 52 52 52 Total 519 513 503 516

The model separately tracks SO2 (and sulfate) from the following source regions:

• Houston Ship Channel area • All other sources within the 4-km modeling grid • Sources outside of the modeling domain (i.e., contribution through the boundary

conditions)

The Houston Ship Channel sources are defined as those within the red rectangle shown in Figure 3-3.

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(a) Major point source emissions from the Acid Rain database (ARD)

(b) Other point source emissions from the ozone season data (OSD)

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(c) Ship emissions (SHIP)

(d) Area source emissions (AREA)

Figure 3-2. Daily total SO2 emissions (tons) on September 19, 2006 within the modeling domain by source category.

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Figure 3-3. Daily total SO2 emissions (tons) from all the point sources and ships at and around the Houston Ship Channel area on September 19, 2006; the red rectangle indicates a source area that was tracked separately as the Houston Ship Channel sources.

Boundary conditions for the 4-km modeling domain were extracted from the 2006 CAMx modeling of North America from the Air Quality Modeling Evaluation International Initiative (AQMEII) study (http://aqmeii.jrc.ec.europa.eu/). Figure 3-4 shows average vertical profiles of SO2 and sulfate concentrations at each boundary of the 4-km modeling grid.

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Figure 3-4. Average vertical concentration profiles of SO2 and sulfate at the west, east, south, and north boundaries of the 4-km modeling grid over the modeling period.

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3.4 Model Output Interval To better match the continuous measurement data, shorter model reporting (output) time intervals than the usual 1 hour were tested. The preliminary simulations were conducted for the September 19 flight with an initial SO2-to-sulfate conversion rate of 0.5 hr-1. Figure 3-5 plots the model-predicted SO2 and sulfate concentrations with three different output time intervals. Only the model results for the 1-km sub-grid are shown. The model predicted slightly lower peak SO2 and sulfate concentrations with the 60 minute output time interval than with the 15 or 6 minute interval at the transects closer to the Houston Ship Channel (Transects C-D, E-F and G-H). At further downwind (Transect I-J), the model showed slightly higher peak SO2 and sulfate concentrations with the 60 minute interval. Since the model results with 15 and 6 minute intervals do not show any significant differences, we selected the 15 minute output interval for the subsequent model evaluation runs.

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(a) Transect C-D

(b) Transect E-F

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(c) Transect G-H

(d) Transect I-J

Figure 3-5. Modeled SO2 and sulfate concentrations of the September 19 flight transects with varying output intervals.

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4.0 RESULTS AND RECOMMENDATION

4.1 Model Evaluation Figure 4-1 (a) and (b) compare the observed SO2 and sulfate concentrations, respectively, with the model-predicted concentrations with varying SO2-to-sulfate conversion rates for Transect E-F of the September 19 flight. The observed and modeled plumes are not exactly aligned because the meteorological model inputs are not sufficiently accurate to describe the actual wind direction at the time/height of each flight transect. Simply shifting the model plume direction will not help because multiple peaks are misaligned by different distances. In addition, Figure 4-1 (c) shows that the modeled background sulfate concentrations are too high: The model predicted about 1.5-2 µg/m3 of sulfate coming through BC while the observed background sulfate concentrations are estimated around 0.5 µg/m3. While the goal of this study is not directly related to accurate modeling of meteorology or background contributions, these factors make a conventional model evaluation methodology (i.e., biases and errors calculated from individual data points) less useful.

(a) Observed and modeled SO2 concentrations

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(b) Observed and modeled sulfate concentrations

(c) Modeled sulfate contributions (k = 0.1 hr-1)

Figure 4-1. Observed and modeled SO2 and sulfate concentrations and modeled sulfate contributions for Transect E-F of the September 19 flight.

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To overcome these shortcomings, we devised an alternate model evaluation methodology that employs an aggregated quantity to represent the whole plume segment crossing a transect. An “average excess above background” concentration is defined as follows:

∫(𝐶 − 𝐶𝐵)𝑑𝑡∫𝑑𝑡

where C and CB are the total and background concentrations, respectively. The integration is limited to a transect segment identified as the Ship Channel plume (i.e., a segment dominated by the Ship Channel plume). The excess concentration is normalized by plume width (represented by flight time) so that uncertainties in the plume dispersion do not affect the model evaluation. For the modeled SO2 and sulfate, the “excess above background” is simply the Ship Channel contribution as the model separately tracks SO2 and sulfate from the Ship Channel sources. For the observed data, the background concentration is defined as the minimum concentration within the transect segment attributed to the Ship Channel plume. For example, Figure 4-2 shows the transect segments representing the Houston Ship Channel plume (indicated by red dotted boxes) for the September 19 flight along with the observed and modeled SO2 and sulfate concentrations. For observed SO2 data which was measured with sampling frequency of 1 second (UV Pulsed Fluorescence), the observations during the time the aircraft spent in a model grid cell (1 km resolution in this case) were averaged to smooth out fluctuations in measurement data. For each flight transect, “average excess” SO2 and sulfate concentrations are calculated for both the observed and modeled data. The numerical integration was performed using a cubic natural spline interpolation.

Model evaluation was performed over the ratios of average excess SO2 and sulfate concentrations because our goal is to find the transformation rate of SO2 to sulfate that best fits the aircraft measurement data. The ratio (R) for each transect is given as follows:

𝑅AB =average excess sulfate concentration for Transect A-B

average excess SO2 concentration for Transect A-B

To avoid discrepancies caused by incomplete observed data, transect segments that are missing measurement data for more than 1 minute are excluded from the evaluation. Figure 4-3 presents the root mean square error (RMSE) of the modeled ratio for each flight as well as the overall RMSE. Figure 4-4 shows scatter plots of observed vs. modeled R values along with linear regression results (coefficient of determination, r2) for various conversion rates.

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(a) Transect E-F (observed)

(b) Transect E-F (modeled)

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(c) Transect G-H (observed)

(d) Transect G-H (modeled)

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(e) Transect I-J (observed)

(f) Transect I-J (modeled)

Figure 4-2. Observed and modeled SO2 and SO4 concentrations for the September 19 flight; red dotted boxes indicate the Ship Channel plumes; the model results are of the run with a conversion rate of 0.1 hr-1.

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Figure 4-3. Root mean square errors of the modeled average excess SO4 to SO2 ratios.

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Figure 4-4. Observed vs. modeled ratio (R) of sulfate to SO2 average excess concentrations; dotted lines are linear regression (LR) lines.

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4.2 Recommendation Based on the evaluation results discussed above, the SO2-to-sulfate conversion rate of 0.04 hr-1 appears to best fit the selected flight measurement data, which translates to a 17-hour half-life.

Our result cannot be directly compared to previously estimated SO2 conversion rates from power plant plume studies because high NOx concentrations in the power plant plumes will inhibit photochemistry and thus secondary PM formation (Miller et al., 1978; Ryerson et al., 2001). However, they may serve as a lower bound for our estimate. Luria et al. (2001) estimated SO2 conversion rates of 0.069 hr-1 and 0.034 hr-1 using aircraft measurement data made in the plumes of the Cumberland power plant (Cumberland City, TN) in 1998 and 1999, respectively. However, it should be noted that their estimated rates are upper limit values as they assumed that the measured aerosol volume was completely comprised of ammonium bisulfate. Studying coal-fired power plant plumes impacting at the Southeastern Aerosol Research and Characterization (SEARCH) monitoring sites using continuous measurement data and back-trajectory analysis, Edgerton and Jansen (2004) estimated that mean SO2 oxidation rate in the power plant plumes ranges 0.003-0.01 hr-1 (fall-winter) and 0.005-0.025 hr-1 (spring-summer).

Note that the conversion rate would not depend on oxidant concentrations because we are modeling first-order conversion of SO2 to sulfate. This is because our conversion rate is intended for AERMOD that simplifies the chemistry of SO2 oxidation to an exponential decay. The goal of this study is to develop a SO2 to sulfate conversion rate for the Houston Ship Channel that can be used with AERMOD to address the SO2 NAAQS.

However, the single conversion rate may not be universally applicable since our result is based on a limited set of measurement data. Meteorological conditions during the selected flights represent a typical afternoon on a late summer day in the region (Figure 4-5). Therefore, our result may not be applicable to, for example, a winter or nighttime condition when SO2 to sulfate conversion rates would be expected to be lower.

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Figure 4-5. Box and whisker plots for ambient temperature, pressure and water vapor mixing ratio during the selected flights; diamond markers represent mean values.

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5.0 REFERENCES Edgerton, E., J. Jansen. 2004. “An ARIES, SEARCH, and Mercury Update,” Atmospheric Research

and Analysis, Inc., May 5. (http://www.atmospheric-research.com/PDFs/SEARCH/2004%20SEARCH_ARIES_HG%20Update.pdf)

EPA. 2010a. “Primary National Ambient Air Quality Standard for Sulfur Dioxide; Final Rule,” Federal Register, 40 CFR Parts 50, 53, and 58. June 22. (http://www.epa.gov/ttn/naaqs/standards/so2/fr/20100622.pdf)

EPA, 2010b. “Applicability of Appendix W Modeling Guidance for the 1-hr SO2 National Ambient Air Quality Standard,” Memorandum. August 23. (http://www.epa.gov/ttn/scram/guidance/clarification/ClarificationMemo_AppendixW_Hourly-SO2-NAAQS_FINAL_08-23-2010.pdf)

Luria, M., R.E. Imhoff, R.J. Valente, W.J. Parkhurst, R.L. Tanner. 2001. "Rates of Conversion of Sulfur Dioxide to Sulfate in a Scrubbed Power Plant Plume," J. Air & Waste Manage. Assoc., 51, 1408-1413.

Miller, D.F., A.J. Alkezweeny, J.H. Hales, R.N. Lee. 1978. "Ozone Formation Related to Power Plant Emissions," Science, 202, 1186-1188 (doi:10.1126/science.202.4373.1186).

Parrish, D.D., D.T. Allen, T.S. Bates, M. Estes, F.C. Fehsenfeld, G. Feingold, R. Ferrare, R.M. Hardesty, J.F. Meagher, J.W. Nielsen-Gammon, R.B. Pierce, T.B. Ryerson, J.H. Seinfeld, E.J. Williams. 2009. “Overview of the Second Texas Air Quality Study (TexAQS II) and the Gulf of Mexico Atmospheric Composition and Climate Study (GoMACCS),” J. Geophys. Res., 114, D00F13 (doi:10.1029/2009JD011842).

Ryerson, T.B., M. Trainer, J.S. Holloway, D.D. Parish, L.G. Huey, D.T. Sueper, G.J. Frost, S.G. Donnelly, S. Schauffler, E.L. Atlas, W.C. Kuster, P.D. Goldan, G. Hublet, J.F. Meagher, F.C. Fehsenfeld. 2001. "Observations of Ozone Formation in Power Plant Plumes and Implications for Ozone Control Strategies," Science, 292. 719-723 (doi: 10.1126/science.1058113).