CAPCOG Ozone Conceptual Model 2016

Transcription

1 PGA Task 3, Deliverable 3.2 CAPCOG Ozone Conceptual Model 2016 Prepared by the Capital Area Council of Governments September 23, 2016 PREPARED UNDER A GRANT FROM THE TEXAS COMMISSION ON ENVIRONMENTAL QUALITY The preparation of this report was financed through grants from the State of Texas through the Texas Commission on Environmental Quality. The content, findings, opinions, and conclusions are the work of the author(s) and do not necessarily represent findings, opinions, or conclusions of the TCEQ. Page 1 of 173

2 1 Executive Summary This ozone (O 3 ) conceptual model for the Capital Area Council of Governments (CAPCOG) region characterizes O 3 air pollution formation in the region between 2010 and This report was based on the analyses recommended by the U.S. Environmental Protection Agency (EPA) in its Draft Modeling Guidance for Demonstrating Attainment of Air Quality Goals for Ozone, PM 2.5, and Regional Haze from December This report focuses on three types of days: when maximum daily 8-hour average (MDA8) O 3 concentrations were >70 parts per billion (ppb), ppb, and <55 ppb. CAPCOG is a regional planning commission created under state law, and includes the city of Austin, all five counties in the Austin-Round Rock Metropolitan Statistical Area (MSA) (Bastrop, Caldwell, Hays, Travis, and Williamson Counties), and five additional nearby counties (Blanco, Burnet, Fayette, Lee, and Llano). This document includes the following analyses: An introduction, which includes descriptions of the regional air monitoring network and analysis of the quality of the data used in this report (Section 2); General summaries of O 3 data in the region from (Section 3); Analysis of the temporal profiles and features of O 3 pollution in the region (Section 4); Investigations of potential relationships between meteorology and O 3 pollution (Section 5); Analysis of correlations between O 3 pollution and ambient fine particulate matter (PM 2.5 ), nitrogen dioxide (NO 2 ), and sulfur dioxide (SO 2 ) concentrations (Section 6); Analysis of spatial patterns in regional O 3 pollution, and investigation of relationships between emissions and ambient O 3 concentrations in the region (Section 7); and Investigation of potential relationships between emissions and O 3 pollution (Section 8). Some of the key findings from this conceptual model are the following: 2014 and 2015 O 3 levels at the region s two Federal Reference Method (FRM) monitors and elsewhere within the region were attaining the 2015 O 3 National Ambient Air Quality Standard (NAAQS), but O 3 levels in the region exceeded this NAAQS from ; While the region s O 3 levels appear to be in compliance with the 2015 O 3 NAAQS, the region experiences several days each year when O 3 levels are considered unhealthy for sensitive groups and even more that are considered moderate. The region has measured MDA8 O 3 averages over 70 ppb as early as March and as late as October. Within the Austin-Round Rock MSA, high MDA8 levels are statistically less likely to occur on Sundays than other days, and in Fayette County, high MDA8 levels are statistically more likely to occur on Saturdays than other days. MDA8 values typically started at 10 am or 11 am in the Austin-Round Rock MSA, although the distribution of start times is much wider in Fayette County, where the start time was as late as 7:00 pm on a day when its MDA8 O 3 value exceeded 70 ppb. 1 Page 2 of 173

3 High O 3 tends to form when wind speed (WS) is slow, temperatures are high, relative humidity (RH) is low, and solar radiation (SR) is high. Hays County was the county within the MSA outside of Travis County most likely to be upwind of the region s two regulatory monitors on days when MDA8 values exceeded 70 ppb. Parts of the San Antonio-New Braunfels MSA were more likely to be upwind of the Austin-Round Rock MSA on high O 3 days than Bastrop or Caldwell Counties. On the few days a year when the region does measure a MDA8 O 3 concentration over 70 ppb, O 3 transported into the region accounts for about ppb of the peak levels. The region s high O 3 levels are substantially more impacted by anthropogenic NO X emissions than volatile organic compounds (VOC) emissions, with anthropogenic NO X contributing times more to high O 3 than VOC. It takes about 10 tons per day (tpd) of local NO X emission reductions in order to achieve a 1 ppb reduction in peak O 3 concentrations. This is about 11% of the total anthropogenic NO X emissions from the region in Overall trends in NO X emissions at the federal, state, and local level are expected to continue to drive O 3 concentrations down within the CAPCOG region, particularly in the on-road, non-road, and electric generating unit (EGU) sectors. Controls currently in place in the region are likely achieving about a 1 ppb reduction in peak O 3 levels each year. Page 3 of 173

4 Table of Contents 1 Executive Summary Introduction Availability of O 3 Data by Monitoring Station, Year, and Time of Year Review of O 3 Monitoring Data Quality for Review of O 3 Modeling Data Quality Analysis General O 3 Data High O 3 Measurements by Monitoring Station and Year High O 3 Measurements by Year Top 10 Measured MDA8 O 3 by Monitoring Station by Year Average of 4th Highest MDA8 O 3, Temporal Analysis Earliest and Latest Dates for High O High O 3 Days by Month High O 3 Days by Day of Week High O 3 Days by Start Time for MDA Peak 1-Hour O 3 Times on High O 3 Days Avg. by Hour Peak 3-Hour Avg. O Avg. 24-Hour O W126 O Meteorological Factors Wind Speed Temperature Humidity Solar Radiation Wind Direction Surface WD Back-Trajectories Discussion of Wind Direction Analysis Air Quality Forecasts Consolidated Meteorological Factor Analysis Correlations between MDA8 O 3 and Other Criteria Pollutants PM NO SO Spatial Pattern in Pollutant Levels Monitoring Transport Analysis Source Apportionment Data on Local and Non-Local O 3 Contributions Spatial Extent of High O 3 during the June 2012 Episode (v.0) Variation in High O 3 Levels within 3 x 3 Grid Cell Arrays for Extended 2012 Episode (v.1) Page 4 of 173

5 8 Relationships between Emissions and Regional O 3 Levels Relative Contributions to Travis County 2017 Modeled Design Value Relative Contribution of Anthropogenic NO X and VOC Emissions Sensitivity to Local NO X and VOC Emission Reductions Sensitivity to NO X Emissions Reductions by Source Region Sensitivity to NO X Emissions by Time of Day Emissions Estimates Emissions Estimates Comparison of CAPCOG-Region NO X Emissions by Sector, 2011, 2014, and Projected Changes in NO X and VOC Emissions, Comparison of Trends in NO X Emissions and Peak O 3 Levels Local Emission Controls Conclusion and Recommendations Appendix A: Explanation of Data Quality Concerns CAMS O 3 Data CAMS Temp. Data CAMS RH Data Temporary Monitoring Station Data Table 2-1. Ambient air monitoring stations evaluated in CAPCOG O 3 Conceptual Model Table 2-2. Example of automated calibration checks for CAMS 38, March 31, May 2, Table 2-3. LEADS compared to instrument reading for Top 4 MDA8 values, CAMS 3 (ppb) Table 2-4. LEADS compared to instrument reading for top 4 MDA8 values, CAMS 38 (ppb) Table 2-5. Average bias, average error, and range of deviations from 0 ppb calibrations, CAPCOG Table 2-6. Average bias, average error, and range of deviations from 90 ppb calibrations, CAPCOG Table 2-7. CAPCOG calibrations when 90 ppb check showed more than +/- 7% deviation from reference concentration Table 2-8. Comparison of modeling data for CAMS 3, observed MDA8 >=60 ppb Table 2-9. Comparison of modeling data for CAMS 38, observed MDA8 >=60 ppb Table 3-1. Days with MDA8 O 3 > 70 ppb by monitoring station and year Table 3-2. Days with MDA8 O ppb by monitoring station and year Table 3-3. Days with MDA8 O 3 <55 ppb by monitoring station and year Table 3-4. CAMS 3 top 10 measured MDA8 O 3 values by year Table 3-5. CAMS 38 top 10 measured MDA8 O 3 values by year Table 3-6. CAMS 601 top 10 measured MDA8 O 3 values by year Table 3-7. CAMS 614 top 10 measured MDA8 O 3 values by year Table 3-8. CAMS 674 and 6602 top 10 measured MDA8 O 3 values by year Table 3-9. CAMS 675/1675 top 10 measured MDA8 O 3 values by year Table CAMS 684 top 10 measured MDA8 O 3 values by year Table CAMS 690 top 10 measured MDA8 O 3 values by year Table CAMS 1603 top 10 measured MDA8 O 3 values by year Page 5 of 173

6 Table CAMS 1604 top 10 measured MDA8 O 3 values by year Table Average of 4th highest MDA8 values, (ppb) Table 4-1. Earliest and latest calendar dates for high MDA8 O Table 4-2. Statistical significance of day of week on MDA8 O Table 5-1. WD Definitions Table 5-2. Statistically significantly different avg. WS 12pm 4 pm by MDA8 category and CAMS Table 5-3. Avg. WS 12-4pm statistics for CAMS 3, Table 5-4. Avg. WS 12-4pm statistics for CAMS 38, Table 5-5. Avg. WS 12-4pm statistics for CAMS 601, Table 5-6. Avg. WS 12-4pm statistics for CAMS 614, Table 5-7. Avg. WS 12-4pm statistics for CAMS 674, Table 5-8. Avg. WS 12-4pm statistics for CAMS 675, Table 5-9. Avg. WS 12-4pm statistics for CAMS 684, Table Avg. WS 12-4pm statistics for CAMS 690, Table Avg. WS 12-4pm statistics for CAMS 1603, Table Avg. WS. 12-4pm statistics for CAMS 1604, Table Avg. WS 12-4pm statistics for CAMS 1675, Table Avg. WS. 12-4pm statistics for CAMS 6602, Table Statistically significantly different avg. temp. 12pm 4 pm by MDA8 category and CAMS Table Avg. temp. 12-4pm statistics for CAMS 3, Table Avg. temp. 12-4pm statistics for CAMS 38, Table Avg. temp. 12-4pm statistics for CAMS 601, Table Avg. temp. 12-4pm statistics for CAMS 614, Table Avg. temp. 12-4pm statistics for CAMS 684, Table Avg. temp. 12-4pm statistics for CAMS 690, Table Avg. temp. 12-4pm statistics for CAMS 1603, Table Avg. temp. 12-4pm statistics for CAMS 1604, Table Avg. temp. 12-4pm statistics for CAMS 1675, Table Avg. temp. 12-4pm statistics for CAMS 6602, Table Statistically significantly different diurnal temp. changes by MDA8 Category and CAMS Table Diurnal temp. change statistics for CAMS 3, Table Diurnal temp. change statistics for CAMS 38, Table Diurnal temp. change statistics for CAMS 601, Table Diurnal temp. change statistics for CAMS 614, Table Diurnal temp. change statistics for CAMS 684, Table Diurnal temp. change statistics for CAMS 690, Table Diurnal temp. change statistics for CAMS 1603, Table Diurnal temp. change statistics for 1604, Table Diurnal temp. change statistics for CAMS 1675, Table Diurnal temp. change statistics for CAMS 6602, Table RH measurement correlation matrix, Table Summary of RH data used for each CAMS Page 6 of 173

7 Table Statistically significantly different avg. RH. 12 pm 4 pm by MDA8 category and CAMS Table RH statistics for CAMS 3, Table RH statistics for CAMS 38, Table RH statistics for CAMS 614, Table RH statistics for CAMS 684, Table RH statistics for CAMS 690, Table RH statistics for CAMS 1603, Table RH statistics for CAMS 1604, Table RH statistics for CAMS 1675, Table RH statistics for CAMS 6602, Table SR statistics for CAMS 38, Table CAMS 3 WD chi-squared test statistics for days >70 ppb, ppb, and <55 ppb Table CAMS 38 WD chi-squared test statistics for days >70 ppb, ppb, and <55 ppb Table CAMS 601 WD chi-squared test statistics for days >70 ppb, ppb, and <55 ppb Table CAMS 614 WD chi-squared test statistics for days >70 ppb, ppb, and <55 ppb Table CAMS 674 WD chi-squared test statistics for days >70 ppb, ppb, and <55 ppb Table CAMS 675 WD chi-squared test statistics for days >70 ppb, ppb, and <55 ppb Table CAMS 684 WD chi-squared test statistics for days >70 ppb, ppb, and <55 ppb Table CAMS 690 WD chi-squared test statistics for days >70 ppb, ppb, and <55 ppb Table CAMS 1603 WD chi-squared test statistics for days >70 ppb, ppb, and <55 ppb Table CAMS 1604 WD chi-squared test statistics for days >70 ppb, ppb, and <55 ppb Table CAMS 1675 WD chi-squared test statistics for days >70 ppb, ppb, and <55 ppb Table CAMS 6602 WD chi-squared test statistics for days >70 ppb, ppb, and <55 ppb Table CAMS 3 meteorological factor regression results Table CAMS 38 meteorological factor regression results Table Meteorological conditions considered "necessary" for high MDA Table 6-1. CAMS 3 PM 2.5 analysis Table 6-2. CAMS 38 PM 2.5 analysis Table 6-3. CAMS 601 PM 2.5 analysis Table 6-4. NO 2 data availability by monitoring station and year Table 6-5. CAMS 3 NO 2 analysis Table 6-6. CAMS 38 NO 2 analysis Table 6-7. CAMS 601 NO 2 analysis Table 6-8. CAMS 614 MDA1 NO 2 v MDA8 O Table 6-9. CAMS 690 MDA1 NO 2 v MDA8 O Table CAMS 6602 MDA1 NO 2 v MDA8 O Table SO 2 Data Availability by Monitoring Station and Year Table CAMS 3 SO 2 analysis Table CAMS 601 SO 2 analysis Table CAMS 690 SO 2 analysis Table CAMS 6602 SO 2 analysis Table 7-1. Avg. high and low MDA8 O 3 when peak CAPCOG MDA8 >70 ppb, ppb, and <55 ppb Page 7 of 173

8 Table 7-2. Avg. high and low MDA8 O 3 when peak Austin-Round Rock MSA MDA8 >70 ppb, ppb, and <55 ppb Table 7-3. Highest Top 10 MDA8 values modeled by geographic area for any 4 km x 4 km cell, June 2012 v Table 7-4. Lowest top 10 MDA8 values modeled by geographic area for any 4 km x 4 km cell, June 2012 v Table 7-5. Differences in County maximum and minimum MDA8 values of top 10 modeled O 3 concentrations by geographic area, June 2012 v Table 7-6. Average MDA8 values of top 10 modeled O 3 concentrations by geographic area, June 2012 v Table NO X and VOC emissions by county Table NO X and VOC emissions by county Figure 2-1. CAPCOG region and CAMS used for conceptual model Figure 2-2. O 3 season MDA8 values available by site and year Figure 2-3. Number of monitors with MDA8 O 3 values recorded by month, Figure 2-4. Distribution of simulated instrument drift at CAMS 3 and 38 at a 70 ppb level of O Figure 2-5. Histogram of CAPCOG instrument deviation from 90 ppb calibration checks, Figure 2-6. Distribution of deviations from 90 ppb calibrations Figure 2-7. Comparison of normalized mean error for 2012 models when obs. MDA8 >=60 ppb for June 1 30, Figure 3-1. Percentage of O 3 season days when monitored MDA8 was ppb or > 70 ppb, Figure 3-2. Number of days when regional peak MDA8 O 3 was <55 ppb, ppb, and >70 ppb by year Figure 3-3. Comparison of / design value and average of 10 th highest MDA8 values Figure 4-1. Number of regional MDA8 values >70 ppb and ppb by month, Figure 4-2. Percentage of regional MDA8 values >70 ppb by month for and Figure 4-3. Percentage of regional MDA8 values >=55 ppb by month for and Figure 4-4. Distribution of high O 3 by day of the week Figure 4-5. Distribution of start hour for MDA8 > 70 ppb by monitoring station Figure 4-6. Peak 1-hour O 3 concentration hour for MDA8 > 70 ppb by monitoring station Figure 4-7. Avg. 1-hour O 3 concentration by hour for MDA8 > 70 ppb by monitoring station Figure 4-8. Avg. peak 3-hour O 3 by MDA8 range and monitoring station Figure hour O 3 avg. on days with MDA8 >70 ppb by start hour and monitoring station Figure Avg. 24-Hour O 3 by MDA8 range and monitoring station Figure W126 statistics for CAMS 3 and 38, Figure 5-1. Avg. WS 12-4 pm v. MDA8 O 3 at CAMS 3, Figure 5-2. Avg. WS 12pm-4pm v. MDA8 O and 95% confidence intervals Figure 5-3. Avg. temp. 12-4pm v. MDA8 O 3, CAMS 3, Page 8 of 173

9 Figure 5-4. Avg. temp. 12pm-4pm v. MDA8 O 3 and 95% confidence intervals Figure 5-5. Diurnal temp. change v. MDA8 O 3 at CAMS Figure 5-6. Avg. diurnal temp. change v. MDA8 O Figure 5-7. Camp Mabry RH 12 pm-4 pm v. CAMS 3 MDA8 O 3, Figure 5-8. Avg. RH 12pm-4pm v. MDA8 O Figure 5-9. Avg. SR 12pm - 4pm v. MDA8 O 3 at CAMS 38, Figure Avg. SR 12pm-4pm by CAMS 38 MDA8 O 3 and 95% confidence intervals Figure Res. WD for CAMS 3, 8 am - 12 pm Figure Res. WD for CAMS 3, 12 pm 4 pm Figure Res. WD for CAMS 38, 8 am - 12 pm Figure Res. WD for CAMS 38, 12 pm 4 pm Figure Res. WD for CAMS 601, 8 am - 12 pm Figure Res. WD for CAMS 601, 12 pm 4 pm Figure Res. WD for CAMS 614, 8 am - 12 pm Figure Res. WD for CAMS 614, 12 pm 4 pm Figure Res. WD for CAMS 674, 8 am - 12 pm Figure Res. WD for CAMS 674, 12 pm 4 pm Figure Res. WD for CAMS 675, 8 am - 12 pm Figure Res. WD for CAMS 675, 12 pm 4 pm Figure Res. WD for CAMS 684, 8 am - 12 pm Figure Res. WD for CAMS 684, 12 pm 4 pm Figure Res. WD for CAMS 690, 8 am - 12 pm Figure Res. WD for CAMS 690, 12 pm 4 pm Figure Res. WD for CAMS 1603, 8 am - 12 pm Figure Res. WD for CAMS 1603, 12 pm 4 pm Figure Res. WD for CAMS 1604, 8 am - 12 pm Figure Res. WD for CAMS 1604, 12 pm 4 pm Figure Res. WD for CAMS 1675, 8 am - 12 pm Figure Res. WD for CAMS 1675, 12 pm 4 pm Figure Res. WD for CAMS 6602, 8 am - 12 pm Figure Res. WD for CAMS 6602, 12 pm 4 pm Figure CAMS 3 24-hour back-trajectories on days with MDA8 >70 ppb at 100 m ( ) Figure CAMS hour back-trajectories on days with MDA8 >70 ppb at 100 m ( ) Figure CAMS hour back-trajectories on days with MDA8 >70 ppb ( ) Figure CAMS hour back-trajectories on days with MDA8 > 70 ppb ( ) Figure CAMS hour back-trajectories on days with MDA8 >70 ppb (2010) Figure CAMS hour back-trajectories when MDA8 >70 ppb (2010 and 2011) Figure CAMS hour back-trajectories when MDA8 >70 ppb ( ) Figure CAMS hour back-trajectories when MDA8 >70 ppb ( ) Figure CAMS hour back-trajectories when MDA8 >70 ppb ( ) Figure CAMS hour back-trajectories when MDA8 >70 ppb ( ) Page 9 of 173

10 Figure CAMS hour back-trajectories on days with MDA8 >70 ppb ( and 2015) Figure Areas upwind of CAMS 3 on days with MDA8 >70 ppb back-trajectories Figure Areas upwind of CAMS 38 on days with MDA8 >70 ppb back-trajectories Figure Areas upwind of CAMS 601on days with MDA8 >70 ppb back-trajectories Figure Areas upwind of CAMS 614 on days with MDA8 >70 ppb back-trajectories Figure Areas upwind of CAMS 674 on days with MDA8 >70 ppb back-trajectories Figure Areas upwind of CAMS 675 on days with MDA8 >70 ppb back-trajectories Figure Areas upwind of CAMS 684 on days with MDA8 >70 ppb back-trajectories Figure Areas upwind of CAMS 690 on days with MDA8 >70 ppb back-trajectories Figure Areas upwind of CAMS 1603 on days with MDA8 >70 ppb back-trajectories Figure Areas upwind of CAMS 1675 on days with MDA8 >70 ppb back-trajectories Figure Areas upwind of CAMS 6602 on days with MDA8 >70 ppb back-trajectories Figure Accuracy and success of OAD forecasts Figure Accuracy and success of moderate or worse O 3 AQI forecasts Figure CAMS 3 frequency of occurrences of "necessary" conditions for high MDA8 O Figure CAMS 38 frequency of occurrences of "necessary" conditions for high MDA8 O Figure 6-1. Average PM 2.5 v. MDA8 O Figure 6-2. Avg. MDA1 NO 2 v. MDA8 O Figure 6-3. CAMS 3 MDA1 SO 2 v. MDA8 O 3, Figure 6-4. CAMS 601 MDA1 SO 2 v. MDA8 O 3, Figure 6-5. CAMS 6602 MDA1 SO 2 v. MDA8 O 3, Figure 6-6. Average MDA1 SO 2 v. MDA8 O Figure 7-1. June 2006 source apportionment data summary top 10 days Figure 7-2. Highest MDA8 values modeled for each grid cell in the June 2012v.0 base case episode E. Texas Figure 7-3. Highest MDA8 values modeled for each grid cell in the June 2012v.0 base case episode CAPCOG Figure 7-4. Average of five highest MDA8 values modeled for each grid cell in the June 2012v.0 base case episode E. Texas Figure 7-5. Average of five highest MDA8 values modeled for each grid cell in the June 2012v.0 base case episode CAPCOG Figure 7-6. Average of ten highest MDA8 values modeled for each grid cell in the June 2012v.0 base case episode E. Texas Figure 7-7. Average of ten highest MDA8 values modeled for each grid cell in the June 2012v.0 base case episode - CAPCOG Figure 7-8. Percentage of grid cells in region with modeled MDA8 > 70 ppb Figure 7-9. Average modeled MDA8 for grid cell and 3x3 cell array max and min for 2012 extended episode Figure Average differences in modeled MDA8 between monitor and 3x3 cell array max, top 10 days, extended 2012 episode Page 10 of 173

11 Figure 8-1. Projected contribution of Texas and non-texas anthropogenic emissions to 2017 CAMS 3 design values (ppb) Figure 8-2. Ratio of anthropogenic NO X contribution to anthropogenic VOC contribution TCEQ 2017 APCA, top 5 modeled MDA8 O 3 values (March 2016 release) Figure 8-3. Sensitivity of MDA8 O 3 to Austin-Round Rock MSA NO X and VOC Emissions (ppb/tpd) June 2006 episode (Jan release) Figure 8-4. Relative sensitivity of MDA8 O 3 to Austin-Round Rock MSA NO X and VOC emissions (NO X /VOC) June 2006 episode (Jan release) Figure 8-5. Approximate sensitivities of 2017 O 3 design values to anthropogenic NO X emissions by geography Figure 8-6. AACOG modeled Impact of a 1 tpd reduction in on-road emissions on 2018 design values. 154 Figure OSD anthropogenic NO X emissions by sector and geography Figure OSD anthropogenic VOC emissions by sector and geography Figure 8-9. CAPCOG region NO X emissions by sector and year, 2011, 2014, 2017, and 2025 (tpy) Figure Projected change in annual NO X and VOC emissions by geography, Figure Projected change in annual NO X emissions by region and source type, Figure Trends in NO X emissions and Travis County O 3 design value Figure Travis County O 3 design values compared to 2015 O 3 NAAQS Figure Travis County O 3 design value percentiles compared to all U.S. monitoring stations Figure Travis County O 3 design values compared to maximum U.S. design value Figure 9-1. Overview of CAMS 6602 monitoring locations Figure 9-2. CAMS 6602 MDA8 O 3 values compared to all CAPCOG O 3 monitors, Figure 9-3. Avg. 12pm-4pm temp. at CAMS 601 by day, Figure 9-4. CAMS 5003 avg. 12pm-4pm RH compared to selected other stations Figure 9-5. Hourly O 3 concentration comparison for 2012 temporary sites Figure 9-6. Hourly O 3 concentration comparison for 2013 temporary sites Page 11 of 173

12 2 Introduction This document is designed to provide a conceptual description of the ground-level O 3 problem in the CAPCOG region. While the two Federal Reference Method (FRM) monitors in the region have official 3- year O 3 design values that are attaining the 2015 O 3 NAAQS of parts per million (ppm), the region s O 3 levels are close to the level of the NAAQS, and 8-hour O 3 levels exceed the level of the NAAQS several times a year, on average. The research monitors that CAPCOG operates are not FRM stations. One of CAPCOG s monitors in Georgetown does have a three-year average of recorded 4 th highest maximum-daily 8-hour O 3 average (MDA8) over 70 ppb, but, as the discussion in section 2.1 explains, this average is inflated due to measurement error in 2013 and would have a 3-year average at or below 70 ppb if CAPCOG s data was adjusted to account for measurement error the same way TCEQ s are. All counties in the CAPCOG region are designated unclassifiable/attainment for the 2008 O 3 NAAQS. The Texas Commission on Environmental Quality (TCEQ) has recommended to the Governor that he recommend to EPA that Travis County be designated attainment for the 2015 O 3 NAAQS and that the remaining 9 counties in the CAPCOG region without FRM monitors be designated unclassifiable/attainment. The U.S. Environmental Protection Agency s (EPA s) Draft Modeling Guidance for Demonstrating Attainment of Air Quality Goals for Ozone, PM 2.5, and Regional Haze from December 2014 describes conceptual models as, comprehensive summaries of the state of the knowledge regarding the influence of emissions, meteorology, transport, and other relevant atmospheric processes on air quality in the area. 2 While the EPA s guidance is directed primarily at states and local governments responsible for developing attainment demonstrations and developing plans for conducting photochemical modeling, EPA also points out that conceptual models can be helpful for investigating emissions program impacts, monitoring network design, and otherwise providing a good foundation for a region s air quality planning efforts. Over the years, CAPCOG has periodically developed conceptual models for ground-level O 3 for the Austin-Round Rock MSA, which is considered by the state to be a near-nonattainment area for the ground-level O 3 NAAQS. CAPCOG developed O 3 conceptual models for the region in 2004, 2007, 2010, 2012, and This conceptual model goes beyond the five counties in the Austin-Round Rock MSA to cover all ten counties in the CAPCOG region, and focuses on ground-level O 3 data for Data used for this conceptual model include: Air pollution and meteorological data from continuous air monitoring stations (CAMS) in the region between 2010 and 2015; Air modeling and emissions data for the region based on 2006, 2011, and 2012 photochemical modeling episodes developed by TCEQ and EPA; and County-level emissions data developed by TCEQ and EPA for the 2011 and 2014 National Emissions Inventories (NEIs). 2 EPA. Draft Modeling Guidance for Demonstrating Attainment of Air Quality Goals for Ozone, PM 2.5, and Regional Haze. December 3, RH_Modeling_Guidance-2014.pdf. Last accessed 8/15/2016. Page 12 of 173

13 For this project, CAPCOG used ambient CAMS data for the following parameters: O 3 ; Average Wind Speed (Avg. WS); Resultant Wind Speed (Res. WS); Resultant Wind Direction (Res. WD); Outdoor Temperature (Temp.); RH; SR; NO 2 ; NO X ; PM 2.5 ; and SO 2. A map of the monitoring stations that CAPCOG used data from is shown below. The green squares are TCEQ stations that collected O 3 and meteorological data between 2010 and 2015, blue squares are CAPCOG stations that collected O 3 and meteorological data for at least some time between 2010 and 2015, while the purple squares are National Weather System (NWS) monitoring stations that collected meteorological data used in this project. There is also a NWS meteorological station in Burnet County, but CAPCOG did not use the data from that station in this analysis. The map below also does not show any monitoring stations in the adjacent Alamo Area Council of Governments (AACOG) region or the Central Texas Council of Governments (CTCOG) region. Page 13 of 173

14 Figure 2-1. CAPCOG region and CAMS used for conceptual model Both of TCEQ s monitoring stations are FRM stations. CAPCOG s monitoring stations are not FRM or Federal Equivalent Method (FEM), although they do use EPA-approved sampling methods in a research capacity. Most of the data used for this analysis was obtained from TCEQ s Leading Environmental Analysis & Display System (LEADS ) data system, but some was obtained from other sources, as described below: CAPCOG obtained data for CAMS 5001 and 5003 directly from the NWS. Data for Liberty Hill and Elroy were directly downloaded from those stations when they were operational in Data for CAMS 1603 and CAMS 1604 were directly downloaded from these stations in 2013 when they were operational that year, while data from 2014 and 2015 was obtained from LEADS. In some cases, due to data quality concerns, CAPCOG did not use certain data that were available. This includes: O 3 data at CAMS 6602 in 2014; Temp. data at CAMS 601 in 2010 and 2011; Page 14 of 173

15 RH data at CAMS 684 in 2014 and 2015; and Temporary monitoring station data from Liberty Hill and Elroy in 2012, and temporary monitoring station data from Lockhart (CAMS 1604) and Gorzycki Middle School (CAMS 1603) in These data were used for only a limited number of analyses for which the specific data quality considerations would not have affected the analysis, such as the overall MDA8 O 3 value for the station on a given day. The following table provides identifying information on each of the monitoring stations CAPCOG used for this analysis. Page 15 of 173

16 Table 2-1. Ambient air monitoring stations evaluated in CAPCOG O 3 Conceptual Model 2016 CAMS AQS # Name Address County Latitude Longitude Owner Austin Northwest 3724 North Hills Dr, Austin Travis TCEQ Austin Audubon Society Lime Creek Rd, Leander Travis TCEQ Fayette County 636 Roznov Rd, Round Top Fayette CAPCOG Dripping Springs Ranch Road 12, Dripping Springs Hays CAPCOG CAPCOG Round Rock 212 Commerce St, Round Rock Williamson CAPCOG CAPCOG San Marcos 222 Sessoms Drive, San Marcos Hays CAPCOG McKinney Roughs 1884 State Hwy 71 W, Cedar Creek Bastrop CAPCOG CAPCOG Lake Georgetown 500 Lake Overlook Drive, Georgetown Williamson CAPCOG Gorzycki Middle School 7412 Slaughter Lane, Austin Travis CAPCOG Lockhart 214 Bufkin Lane, Lockhart Caldwell CAPCOG CAPCOG San Marcos Staples Road 599 Staples Road, San Marcos Hays CAPCOG Camp Mabry KATT Camp Mabry, Austin Travis NWS Austin Bergstrom KAUS Austin Bergstrom International Airport Travis NWS CAPCOG Hutto College Street 200 College Street, Hutto Williamson CAPCOG LH n/a Liberty Hill Temporary Site 301 Loop 332, Liberty Hill Williamson CAPCOG EL n/a Elroy Temporary Site FM812, Del Valle Travis CAPCOG Page 16 of 173

17 % of O 3 Season Days With MDA8 Values CAPCOG Ozone Conceptual Model Availability of O 3 Data by Monitoring Station, Year, and Time of Year In order to provide perspective on the overall availability of MDA8 O 3 values for analysis, the following figure shows the percentage of O 3 season MDA8 values available for each monitoring station for each year. Generally, EPA requires at least 75% data completeness during an area s official O 3 season for a monitor s data to be used in a design value calculation. The region s official O 3 season is now March 1 November 30, so the figure below represents the percentage of total possible MDA8 values available each year during these 275 days. Figure 2-2. O 3 season MDA8 values available by site and year 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Peak CAMS TOTAL 75% The following figure shows a summary of the number of O 3 monitors with MDA8 values used in this analysis by day of the year for each year. As the figure shows, CAPCOG s monitoring season expanded in 2015 to start at the beginning of March, rather than the beginning/middle of April as it had in prior years. CAPCOG monitoring stations have generally been shut down in early November, so there is very little data available beyond the first few days of November for any stations other than TCEQ s. Page 17 of 173

18 Figure 2-3. Number of monitors with MDA8 O 3 values recorded by month, Number of Monitors with MDA8 O Jan 1-Feb 1-Mar 1-Apr 1-May 1-Jun 1-Jul 1-Aug 1-Sep 1-Oct 1-Nov 1-Dec Review of O 3 Monitoring Data Quality for CAMS 3 and 38 are operated year-round by the TCEQ as FRM stations. TCEQ uses automated calibrators on these analyzers, and adjusts concentration recorded by the instrument to account for the slope and intercept from result of the most recent calibration. This process helps ensure that the instrument s reported O 3 concentrations account for the differences between reference O 3 concentrations and the concentrations recorded by the instrument. The following equation represents this relationship: Where: y = mx + b y = O 3 recorded by the instrument m = the slope, in terms of the ratio of O 3 reported to ambient O 3 x = ambient O 3 b = the intercept, representing the recorded O 3 concentration when ambient O 3 = 0 ppb For example, if the instrument is checked with a 0 ppb reference concentration, but it records a concentration of 3 ppb, then we would expect any reported O 3 concentrations to be 3 ppb higher than what was actually in the ambient air if the instrument had an ideal slope, whereby every 1 ppb increase in ambient O 3 concentration resulted in a 1 ppb increase in the O 3 reported by the instrument. In this case, the intercept b = 3 ppb. If the slope is not ideal, and, for instance, the instrument reports the following: 90 ppb reference concentration, 93.9 ppb recorded; 200 ppb reference concentration, 205 ppb recorded; 300 ppb reference concentration, 306 ppb recorded; and Page 18 of 173

19 400 ppb reference concentration, 407 ppb recorded. This would mean that the slope for the instrument was 1.01, and the overall equation representing the relationship between ambient O 3 and reported O 3 would be the following: Recorded O 3 = 1.01 Ambient O ppb Each day, at 10:45 pm, the calibrator performs a check of the instrument at 0 ppb and 400 ppb (80% of the full range). As long as the 0 ppb check is within +/- 5 ppb and the 400 ppb check is within +/- 7% (+/- 28 ppb at the 400 ppb level), the instrument s data is considered acceptable. Every 7 days, the automated calibrator also performed 3-point checks at the 0 ppb, 90 ppb, and 400 ppb levels, with the 90 ppb level also checked to ensure that it is +/- 7% (+/- 6.3 ppb). The data system then adjusts the intercept following these 3-point checks. Then, every 28 days and as needed during other times, a full calibration using checks at the 0 ppb, 90 ppb, 200 ppb, 300 ppb, and 400 ppb levels is conducted. Based on this check, the slope and intercept are adjusted, setting the intercept equal to the value recorded at the 0 ppb reference concentration, and setting the slope based on a linear regression through the five reference concentrations. LEADS then calculates what the ambient O 3 concentration should be in light of the instrument s recorded O 3 concentrations and the reference concentrations. Using the example above, the following equations shows how LEADS would transform an O 3 concentration recorded by the instrument into the value reported by TCEQ. LEADS O 3 = Recorded O 3 3 ppb 1.01 O 3 concentrations in the instrument are recorded in millivolts (mv), and the slope is expressed in terms of mv per ppm of O 3. Below is an example of how this worked for data at CAMS 38 from March 31, 2015, when a 5-point calibration was conducted, through May 2, 2015, which was the site s 4 th -highest MDA8 value for that year. Using the 3/31/2015 calibration as an example, a 70 ppb (0.070 ppm) measurement in LEADS following the 3/31/2015 represents a 69 ppb (0.069 ppm or 138 mv) concentration instrument reading/recording. Cal represents a full 5-point calibration at 0 ppb, 90 ppb, 200 ppb, 300 ppb, and 400 ppb; while Span represents a 3-point check at 0 ppb, 90 ppb, and 400 ppb; and SpanZ represents a 2-point check at 0 ppb and 400 ppb. Table 2-2. Example of automated calibration checks for CAMS 38, March 31, May 2, 2015 Date Check Type 0 mv check 180 mv check Intercept (mv) Slope (mv/ppm) 3/31/2015 Cal /1/2015 SpanZ -1.9 n/a /2/2015 SpanZ -1.5 n/a /3/2015 SpanZ -1.5 n/a /4/2015 Span /5/2015 SpanZ -2.2 n/a /6/2015 SpanZ -1.9 n/a /7/2015 SpanZ -1.4 n/a /8/2015 SpanZ -0.9 n/a /9/2015 SpanZ -1.2 n/a Page 19 of 173

20 Date Check Type 0 mv check 180 mv check Intercept (mv) Slope (mv/ppm) 4/10/2015 SpanZ -1.4 n/a /11/2015 Span /12/2015 SpanZ -0.8 n/a /13/2015 SpanZ -1.9 n/a /14/2015 SpanZ -1.5 n/a /15/2015 SpanZ -1.3 n/a /16/2015 SpanZ -1.5 n/a /17/2015 SpanZ -1.8 n/a /18/2015 Span /19/2015 SpanZ -1.4 n/a /20/2015 SpanZ -1.6 n/a /21/2015 SpanZ -0.8 n/a /22/2015 SpanZ -1.2 n/a /23/2015 SpanZ -1.2 n/a /24/2015 SpanZ -0.9 n/a /25/2015 Span /26/2015 SpanZ -0.7 n/a /27/2015 SpanZ -2 n/a /28/2015 Cal /29/2015 SpanZ -1.9 n/a /30/2015 SpanZ -2 n/a /1/2015 SpanZ -1.6 n/a /2/2015 Span On 5/2/2015, there was an MDA8 value of 73 ppb (0.073 ppm) at CAMS 3, the 4 th highest of the year. The following equation shows how to calculate the O 3 value recorded by the instrument: (0.073 ppm mv/ppm mv) O 3 recorded by instrument = = ppm 2000 /ppm In this way, the O 3 concentration reported in LEADS is intended to better represent ambient O 3 concentrations, since the last calibration showed that the instrument s O 3 readings were lower than the reference concentrations. CAPCOG conducted an analysis of the variation between the estimated value recorded at the instrument if a 70 ppb value were reported in LEADS. CAPCOG calculated the estimated value recorded by the instrument if a 70 ppb value were reported in LEADS based on that day s 5-point calibration and then calculated the difference from the previous calibration. This can be thought of as an estimate of the instrument drift over a 28-day period if the instrument were measuring a constant 70 ppb level of O 3. The histogram below shows the distribution of the simulated instrument drift for each station. Page 20 of 173

21 Figure 2-4. Distribution of simulated instrument drift at CAMS 3 and 38 at a 70 ppb level of O 3 CAMS 3 CAMS 38 50% 45% 40% 35% 30% 25% 20% 15% 10% 5% 0% Simulated O3 drift (O 3 ) For CAMS 3, 95% of the simulated drift was between and ppb, while for CAMS 38, 95% of the simulated drift was between 3.90 ppb and ppb. This suggests that for any 70 ppb measurement listed in LEADS at these regulatory monitors, there would be a 5% chance that the instrument s recorded O 3 concentrations would be outside of these ranges. However, for both of these stations, over 80% of the deviations were within +/- 1 ppb. So, while significant measurement error would not be expected to impact many MDA8 observations analyzed in this conceptual model, the sensitivity of certain analyses to a small number of observations makes it important to establish the extent to which measurement error may have impacted the specific subset of days that matter for assessing compliance with the NAAQS. To this end, CAPCOG analyzed the slope and intercept values applied to the top 4 days for CAMS 3 and 38 for each year. CAPCOG used the slope and intercept from the most recent 3-point or 5-point calibration in order to calculate the 8-hour O 3 level recorded by the instrument. The following tables summarize the differences for each monitoring station and year. Page 21 of 173

22 Table 2-3. LEADS compared to instrument reading for Top 4 MDA8 values, CAMS 3 (ppb) Rank Avg Table 2-4. LEADS compared to instrument reading for top 4 MDA8 values, CAMS 38 (ppb) Rank n/a n/a Avg Unlike TCEQ, CAPCOG s monitoring has generally not involved the use of automated calibrators. In general, CAPCOG s process for QAing monitoring data involves performing a 3-point or 5-point calibration once a month in order to ensure that the instrument is recording data within acceptable limits compared to reference concentrations (+/- 5 ppb for a 0 ppb check, and either +/- 7% or +/- 15% of any other checks, depending on the instrument and year that the monitoring was conducted). As long as the instrument performs within those parameters, the data are accepted. Therefore, most (but not all) of CAPCOG s data from in LEADS are unadjusted to account for the results of calibrations. The exceptions to this include data from CAMS 614 in 2010 and 2011, when the site was equipped with an automated calibrator. Other than that, there are a few instances in which a specific data problem was addressed using an adjustment, but generally, CAPCOG s data in LEADS is unadjusted. The following histogram shows the distribution in the deviations from the 90 ppb check performed at CAPCOG s monitors from Page 22 of 173

23 -21 to to to to to to to -8-7 to -6-5 to -4-3 to -2-1 to 0 1 to 2 3 to 4 5 to 6 7 to 8 9 to to to to to to 20 CAPCOG Ozone Conceptual Model 2016 Figure 2-5. Histogram of CAPCOG instrument deviation from 90 ppb calibration checks, pct pct pct pct pct. Total pct., % 40% 35% 30% 25% 20% 15% 10% 5% 0% Deviation from 90 ppb calibration checks (ppb) Page 23 of 173

24 -21 to to to to to to to -8-7 to -6-5 to -4-3 to -2-1 to 0 1 to 2 3 to 4 5 to 6 7 to 8 9 to to to to to to 20 CAPCOG Ozone Conceptual Model 2016 The following two tables summarize the average bias, average error, and range of values for 0 ppb and 90 ppb calibrations at CAPCOG monitoring stations from Table 2-5. Average bias, average error, and range of deviations from 0 ppb calibrations, CAPCOG Year Avg. Bias (ppb) Avg. Error (ppb) Range Low Range High Table 2-6. Average bias, average error, and range of deviations from 90 ppb calibrations, CAPCOG Year Avg. Bias (ppb) Avg. Error (ppb) Range Low Range High The following figure shows a comparison of the distribution of deviations from 90 ppb calibrations for all of CAPCOG s calibrations from and the calibrations for CAMS 3 and 38 for Figure 2-6. Distribution of deviations from 90 ppb calibrations CAPCOG CAMS 3 CAMS % 40.0% 35.0% 30.0% 25.0% 20.0% 15.0% 10.0% 5.0% 0.0% Deviation from 90 ppb calibration (ppb) Page 24 of 173

25 There are some notable situations in which CAPCOG s calibration data showed instrument-reported concentrations outside of the range of values that CAPCOG considers acceptable (+/- 7%) that may have a significant impact on some of the analyses in this report. The following table shows the instances in which a monitoring station had a 90 ppb check that was outside of this range. Table 2-7. CAPCOG calibrations when 90 ppb check showed more than +/- 7% deviation from reference concentration Date CAMS Year 90 ppb check value (ppb) Diff 90 ppb % Diff 90 ppb 8/18/ % 5/2/ % 6/13/ % 6/13/ % 6/14/ % 6/15/ % 6/26/ % 7/10/ % 7/23/ % 7/24/ % 7/25/ % 7/30/ % 8/28/ % 8/29/ % 9/29/ % 10/23/ % 10/23/ % 10/24/ % 10/24/ % 5/31/ % 6/27/ % 7/23/ % 7/30/ % 9/2/ % 9/27/ % 10/22/ % 10/29/ % One important impact of these deviations on this conceptual model is that the deviations at CAMS 690 in 2013 are a large part of the reason that the three-year average of the site s 4 th -highest MDA8 values is above 70 ppb. If the MDA8 values for CAPCOG s monitoring data were adjusted to account for the results of these calibrations similar to how the data reported by the TCEQ for CAMS 3 and 38 are, the 3-year average for CAMS 690 would be below 71 ppb. Page 25 of 173

26 2.3 Review of O 3 Modeling Data Quality This report used modeling data from a variety of photochemical modeling platforms. These include: TCEQ s May 31 July 2, 2006, base case platform, reg1c 3 o Released January 2012; o Photochemical model: CAMx version 5.40; o Gas-phase chemistry: CB6; o Meteorology: WRF v. 3.1; TCEQ s May 31 July 2, 2006/August 13 September 2006, base case platform, release 4 4 o Released November 5, 2016; o Photochemical model: CAMx v o Chemistry: CB6r2 o Meteorology: WRF v.3.2; EPA s May 1 September 30, 2011, base case platform (2011v6.2); 5 o Released July 23, 2015; o Photochemical Model: CAMx v. 6.11; o Chemistry: CB6r2; o Meteorology: WRF v. 3.4 TCEQ s June 1 June 30, 2012, base case platform, v. 0; o Released March 2, 2015; o Photochemical Model: CAMx 6.11; o Chemistry: CB6 r2; o Meteorology: WRF v. 3.61, and TCEQ s May 1 September 30, 2012, base case platform (v. 1); 6 o Released June 30, 2016; o CAMx v o Chemistry: CB6 r2h; and o Meteorology: WRF v The following table summarizes performance statistics for each model for CAMS 3 and 38 when observed MDA8 O 3 was >=60 ppb. Table 2-8. Comparison of modeling data for CAMS 3, observed MDA8 >=60 ppb Statistic June 2006, reg1c extended, release 4 EPA 2011v6.2 TCEQ June 2012 v.0 TCEQ 2012 Seasonal v.1 3 See Base_case_Performance_Evaluation_Final.pdf for more information on this model Modeling data available at Page 26 of 173

27 Statistic June 2006, reg1c extended, release 4 EPA 2011v6.2 TCEQ June 2012 v.0 TCEQ 2012 Seasonal v.1 # Obs. MDA8>=60 ppb Gross Bias (ppb) Gross Error (ppb) Normalized Mean Bias (%) Normalized Mean Error (%) Table 2-9. Comparison of modeling data for CAMS 38, observed MDA8 >=60 ppb Statistic June 2006, reg1c extended, release 4 EPA 2011v6.2 TCEQ June 2012 v.0 TCEQ 2012 Seasonal v.1 # Obs. MDA8>=60 ppb Gross Bias (ppb) Gross Error (ppb) Normalized Mean Bias (%) Normalized Mean Error (%) In early 2016, the TCEQ recommended that any future modeling efforts start using the June 2012 modeling data that was available at the time. Since then, the seasonal 2012 model has also become available. The following figure shows a comparison of the normalized mean error (NME) for each monitoring station in the CAPCOG region for June 2012 using each model. 7 Performance data calculated based on data available in the following report: These data differ slightly from the statistics in the performance evaluation produced by U.T. at Base_case_Performance_Evaluation_Final.pdf. 8 Performance data calculated based on data available in the following report: These data differ slightly from the statistics in the performance evaluation produced by U.T. at Base_case_Performance_Evaluation_Final.pdf. Page 27 of 173

28 Normalized Mean Error CAPCOG Ozone Conceptual Model 2016 Figure 2-7. Comparison of normalized mean error for 2012 models when obs. MDA8 >=60 ppb for June 1 30, % June 2012 v Seasonal Model v.1 50% 40% 30% 20% 10% 0% CAMS One point to note regarding the large error values shown for CAMS 1675 and 6602 in the chart above: both of these monitoring stations had calibration checks during June 2012 that showed substantial deviations from the 90 ppb reference value 20.5 ppb higher at CAMS 1675 and 9.5 ppb higher at CAMS The average mean bias on days with MDA8 >=60 ppb at CAMS 1675 in the June section of the 2012 seasonal model was ppb, and was ppb at CAMS 6602, so a significant share of the calculated bias at those two sites for this period may be attributable to measurement error. Page 28 of 173

29 3 Analysis General O 3 Data This section provides general data on the MDA8 levels measured in the region between 2010 and This includes analysis of days when MDA8 levels were >70 ppb, ppb, and <55 ppb, corresponding generally to the O 3 Air Quality Index values of unhealthy or unhealthy for sensitive groups ( ppb and ppb, respectively), moderate (55-70 ppb), and good (<55 ppb). Data is analyzed both monitor-by-monitor and region-wide. For regional analysis, the highest MDA8 value recorded in the region would determine that day s classification. 3.1 High O 3 Measurements by Monitoring Station and Year The following figure shows the % of total number of MDA8 values that were <55 ppb, ppb, and >70 ppb for each monitoring station and for the region during the official O 3 season from (March-November). While CAPCOG s monitors cannot be used in official design value calculations, it is prior to 2015, CAPCOG s monitors usually collected MDA8 values on less than 75% of the dates between March 1 and November 30, so the data presented in Table 3-1 may over-represent the % of O 3 -season days that would generally expected to be 55 ppb for CAPCOG monitoring stations compared to TCEQ monitoring stations, which are operated year-round. Figure 3-1. Percentage of O 3 season days when monitored MDA8 was ppb or > 70 ppb, % 25% 20% 15% 10% 5% 0% ppb > 70 ppb The following tables provide more detailed data on the number of days with MDA8 values >70 ppb, ppb, and <55 ppb at each monitoring station. Summaries of the total # of observations and the regional peak are also included. These data reflect the number of days for the entire year. Page 29 of 173

30 Table 3-1. Days with MDA8 O 3 > 70 ppb by monitoring station and year CAMS Total Any Station All Data Points Table 3-2. Days with MDA8 O ppb by monitoring station and year CAMS Total Any Station All Data Points ,820 Page 30 of 173

31 Table 3-3. Days with MDA8 O 3 <55 ppb by monitoring station and year CAMS Total , , , , Any Station ,766 All Data Points 1,647 1,399 1,565 1,674 1,855 2,202 10, High O 3 Measurements by Year The following figure shows the number of days when the regional peak MDA8 value for O 3 was <55 ppb, ppb, and >70 ppb by year. Figure 3-2. Number of days when regional peak MDA8 O 3 was <55 ppb, ppb, and >70 ppb by year <55 ppb ppb >70 ppb avg avg. Page 31 of 173

32 As the table shows, the average # of days when peak MDA8 values were >70 ppb decreased by nearly 50% from to The average number of days when peak MDA8 values in the region were considered good increased by 3% between these same periods. 3.3 Top 10 Measured MDA8 O 3 by Monitoring Station by Year Compliance with the O 3 NAAQS is based on the average of the yearly 4 th high MDA8 values over three years. EPA s modeling guidance recommends the use of the top 10 modeled MDA8 values in baseline and future analysis years for calculating relative response factors (RRFs). Therefore, the following tables present the top 10 days measured at each monitoring station each year, as well as the average of the top 4 days and the average of the top 10 days. Table 3-4. CAMS 3 top 10 measured MDA8 O 3 values by year Rank Avg. Top Avg. Top Table 3-5. CAMS 38 top 10 measured MDA8 O 3 values by year Rank Avg. Top Avg. Top Page 32 of 173

33 Table 3-6. CAMS 601 top 10 measured MDA8 O 3 values by year Rank Avg. Top Avg. Top Table 3-7. CAMS 614 top 10 measured MDA8 O 3 values by year Rank Avg. Top Avg. Top Table 3-8. CAMS 674 and 6602 top 10 measured MDA8 O 3 values by year Rank 2010 CAMS 2011 CAMS 2012 CAMS 2013 CAMS 2014 CAMS 2015 CAMS n/a n/a n/a n/a n/a n/a n/a 68 9 CAMS data not presented here due to data quality concerns. Page 33 of 173

34 Rank 2010 CAMS 2011 CAMS 2012 CAMS 2013 CAMS 2014 CAMS 2015 CAMS n/a n/a n/a 62 Avg. Top n/a 73.8 Avg. Top n/a 69.3 Table 3-9. CAMS 675/1675 top 10 measured MDA8 O 3 values by year Rank Avg. Top Avg. Top Table CAMS 684 top 10 measured MDA8 O 3 values by year Rank Avg. Top Avg. Top Page 34 of 173

35 Table CAMS 690 top 10 measured MDA8 O 3 values by year Rank Avg. Top Avg. Top Table CAMS 1603 top 10 measured MDA8 O 3 values by year Rank Avg. Top Avg. Top Page 35 of 173

36 Table CAMS 1604 top 10 measured MDA8 O 3 values by year Rank Avg. Top Avg. Top In order to test the extent to which the average of the top 10 MDA8 values matched the 4 th highest MDA8 values, CAPCOG compared the ratios of / design values to the ratios of the average of the annual top 10 MDA8 values for the same years. For the seven monitoring stations with data for , 10 the use of the 3-year average of the average of the 10 highest MDA8 values in each year produced / ratios very close to those produced using the 3-year average of the 4 th highest MDA8 values. The ratios varied from -2.3% to + 2.2% compared to the design value ratios. This suggests that the use of the average of the top 10 values in modeling analyses is a good indication of the approximate 4 th highest MDA8 value that would be expected if calculating a design value. 10 Including CAMS 675 and 1675 as a single location due to their proximity to one another. Page 36 of 173

37 Figure 3-3. Comparison of / design value and average of 10 th highest MDA8 values RRF / fourth highest MDA8 RRF / ten highest avg CAMS 3 CAMS 38 CAMS 601 CAMS 614 CAMS 684 CAMS 690 CAMS 675/ Average of 4th Highest MDA8 O 3, The following table shows the average of the 4 th highest MDA8 values at all of the monitoring stations that had data used in this report for2013, 2014, and For FRM sites, this 3-year average, once truncated, is used as the basis for evaluating compliance with the NAAQS if the monitor had at least 75% of its O 3 season monitoring data complete. CAMS 3 and 38 met this requirement for each of the three years, but while all of the CAPCOG monitoring stations had at least 75% data completeness for 2015, none of them had at least 75% of March November data completeness in each of the three years. Table Average of 4th highest MDA8 values, (ppb) CAMS Avg As the table shows, there is one research monitoring station operated by CAPCOG (CAMS 690) that has a three-year average over 70 ppb. While this statistic was calculated using the same method as an O 3 design value would be calculated, due to differences in data quality between FRM sites and CAPCOG s sites, it would not be appropriate to consider the three-year averages for any of CAPCOG s stations to be Page 37 of 173

38 design values or use these averages to determine if the region is in compliance with the NAAQS. The next section includes some data analysis of the calibrations conducted at these stations, which helps explain why the three-year average for CAMS 690, in particular, should not be considered equivalent to the three-year average for CAMS 3 or 38. Page 38 of 173

39 4 Temporal Analysis One of the topics that EPA recommends that a conceptual description for O 3 include is the temporal scope of poor air quality in the region. This section includes a number of temporal analyses of O 3 in the region. Among the analyses included in this section are: The earliest and latest dates of the year when high O 3 levels were recorded; The distribution of high O 3 days by month; The distribution of high O 3 days by day of the week; The distribution of high O 3 days by start time for MDA8; The distribution of high O 3 days by peak 1-hour O 3 concentration; The average O 3 concentration by hour; Peak 3-hour O 3 concentrations; Average 24-hour O 3 concentrations; and W126 seasonal O 3 exposure estimates. 4.1 Earliest and Latest Dates for High O 3 The following table shows the earliest and latest dates for some key MDA8 values. These dates are relevant for understanding the range of monitoring data that would need to be analyzed in order to draw conclusions about the various conditions under which high O 3 was expected to occur. The Regional Peak represents the highest MDA8 value recorded in the region at TCEQ or CAPCOG stations. Table 4-1. Earliest and latest calendar dates for high MDA8 O 3 MDA8 O 3 Range Earliest Date Latest Date Regional Peak >55 ppb February 10, 2015 November 8, 2012 Regional Peak>70 ppb March 25, 2012 October 17, 2015 CAMS 3 Top 4 April 13, 2011 October 24, 2014 CAMS 3 Top 10 March 13, 2013 October 25, 2014 CAMS 38 Top 4 May 2, 2015 October 24, 2014 CAMS 38 Top 10 March 13, 2013 October 26, High O 3 Days by Month The following table shows the number of days when MDA8 values were ppb and >70 ppb by month between 2010 and Page 39 of 173

40 Figure 4-1. Number of regional MDA8 values >70 ppb and ppb by month, ppb >70 ppb Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec The following two figures show a different perspective on the data above the percentage of total days >70 ppb and >=55 ppb recorded from that occurred during each month, with break-downs of the and averages. Figure 4-2. Percentage of regional MDA8 values >70 ppb by month for and Total % 30% 25% 20% 15% 10% 5% 0% Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Page 40 of 173

41 Figure 4-3. Percentage of regional MDA8 values >=55 ppb by month for and Total % 18% 16% 14% 12% 10% 8% 6% 4% 2% 0% Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec As the figures show, there is a bimodal distribution of high O3 days in the region, with the August/September/October timeframe being the most common period for days >70 ppb and >=55 ppb, with another April/May/June timeframe that had somewhat fewer days with high O 3. July tended to have significantly fewer high MDA8 values than these two other time periods. 4.3 High O 3 Days by Day of Week CAPCOG analyzed the frequency of high O 3 days by day of week. The following figure shows the percentage of days when the highest MDA8 O 3 levels in the region were >=55 ppb and >70 ppb. Page 41 of 173

42 Figure 4-4. Distribution of high O 3 by day of the week >=55 ppb >70 ppb 21% 16% 16% 16% 14% 15% 13% 15% 15% 16% 13% 14% 11% 6% Mon. Tue. Wed. Thu. Fri. Sat. Sun. CAPCOG performed a χ 2 test statistical analysis for each day at the 90% and 95% confidence levels. The critical χ 2 value at a 90% confidence level for 1 degree of freedom is 2.71 and is 3.84 for a 95% confidence level. The table below shows the results of this analysis. Table 4-2. Statistical significance of day of week on MDA8 O 3 Day >70 ppb Significant Significant >=55 Significant Significant at 90% at 95% ppb at 90% at 95% Mon No No No No Tues No No No No Wed No No No No Thu No No No No Fri No No No No Sat No No No No Sun Yes No Yes Yes These data indicate that there was a statistically significantly lower probability of high O 3 on Sundays compared to every other day of the week at the 90 but not the 95% level of confidence, while there was no statistically significant difference among the other days of the week. CAPCOG also performed this analysis for each monitoring station. This analysis revealed that Sundays had a statistically significantly lower probability of having an MDA8 O 3 level 55 ppb than other days of the week at a 90% confidence level at CAMS 38, 684, and 690. The analysis for CAMS 601, on the other Page 42 of 173

43 hand, showed a statistically significantly higher number of days with MDA8 >70 ppb on Saturdays compared to every other day of the week, accounting for 29% of all such days. 4.4 High O 3 Days by Start Time for MDA8 CAPCOG analyzed the distribution of start hours for high MDA8 measurements at each monitoring station, shown below. Figure 4-5. Distribution of start hour for MDA8 > 70 ppb by monitoring station 9:00 AM 10:00 AM 11:00 AM 12:00 PM 1:00 PM 2:00 PM 3:00 PM 4:00 PM 5:00 PM 6:00 PM 7:00 PM 70% 60% 50% 40% 30% 20% 10% 0% CAMS # As the figure shows, for most monitoring stations, the start hour when MDA8 >70 ppb is typically 10 am or 11 am, although the MDA8 sometimes starts as early as 9 am and as late as 1 pm. The one notable exception to this pattern is the distribution of start hours for CAMS 601 in Fayette County, which 4 pm as its most common start hour, and had start hours as late as 7 pm. This may reflect a difference in O 3 formation at CAMS 601 that may be more heavily influenced by O 3 formation in the Houston area, which is located to the southeast of Fayette County. 4.5 Peak 1-Hour O 3 Times on High O 3 Days CAPCOG also analyzed the peak 1-hour O 3 concentrations on days when MDA8 > 70 ppb. These results are shown below. Page 43 of 173

44 Figure 4-6. Peak 1-hour O 3 concentration hour for MDA8 > 70 ppb by monitoring station 10:00 AM 11:00 AM 12:00 PM 1:00 PM 2:00 PM 3:00 PM 4:00 PM 5:00 PM 6:00 PM 7:00 PM 70% 60% 50% 40% 30% 20% 10% 0% CAMS # For CAMS 3 and 38, 1 pm was most commonly the peak 1-hour O 3 hour when MDA8 >70 ppb, although other monitoring stations more typically had peak 1-hour O 3 concentrations at 2 or 3 pm, and CAMS 601 had a typical peak 1-hour O 3 concentration at 4 pm. These differences may reflect each monitor s location relative to the Austin-Round Rock MSA or, in the case of CAMS 601, relative to the Houston metro area, and the amount of time it takes for the urban plume to reach that monitoring station. 4.6 Avg. by Hour CAPCOG also calculated the average 1-hour O 3 concentrations at each monitoring station when MDA8 >70 ppb. These results are shown in the figure below. Page 44 of 173

45 1-Hour O 3 Avg. CAPCOG Ozone Conceptual Model 2016 Figure 4-7. Avg. 1-hour O 3 concentration by hour for MDA8 > 70 ppb by monitoring station CAMS 3 70 CAMS CAMS 601 CAMS 614 CAMS CAMS CAMS CAMS 690 CAMS 1603 CAMS :00 AM 2:00 AM 4:00 AM 6:00 AM 8:00 AM 10:0012:00 2:00 AM PM PM 4:00 PM 6:00 PM 8:00 PM 10:00 PM CAMS 6602 This figure shows average 1-hour O 3 concentrations >=71 ppb on days when MDA8 >70 ppb from 11 am/12pm to 6-8 pm, depending on the monitoring station. 4.7 Peak 3-Hour Avg. O 3 As an alternative perspective on regional O 3 levels, CAPCOG also calculated peak 3-hour O 3 concentrations on days when MDA8 > 70 ppb, ppb, and <55 ppb. A peak 3-hour average O 3 concentration may be more representative of the length of continuous outdoor exposure for someone engaged in outdoors exercise, for example, rather than 8 hours. The following figures summarize these data. Page 45 of 173

46 12:00 AM 1:00 AM 2:00 AM 3:00 AM 4:00 AM 5:00 AM 6:00 AM 7:00 AM 8:00 AM 9:00 AM 10:00 AM 11:00 AM 12:00 PM 1:00 PM 2:00 PM 3:00 PM 4:00 PM 5:00 PM 6:00 PM 7:00 PM 8:00 PM 9:00 PM Peak 3-Hour O 3 Avg. (ppb) Peak 3-Hour O 3 Avg. (ppb) CAPCOG Ozone Conceptual Model 2016 Figure 4-8. Avg. peak 3-hour O 3 by MDA8 range and monitoring station MDA8 <55 ppb MDA ppb MDA8 >70 ppb Figure hour O 3 avg. on days with MDA8 >70 ppb by start hour and monitoring station CAMS 3 CAMS 38 CAMS 601 CAMS 614 CAMS 674 CAMS 675 CAMS 684 CAMS 690 CAMS 1603 CAMS 1675 CAMS 6602 Page 46 of 173

47 24-Hour O 3 Avg. (ppb) CAPCOG Ozone Conceptual Model Avg. 24-Hour O 3 Since some exposure studies used for the 2015 O 3 NAAQS also analyzed 24-hour O 3 concentrations, CAPCOG also included an analysis of the typical 24-hour avg. O 3 concentrations when MDA8 O 3 was >70 ppb, ppb, and <55 ppb. These data are shown below. Figure Avg. 24-Hour O 3 by MDA8 range and monitoring station 60 MDA8 <55 ppb MDA ppb MDA8 >70 ppb W126 O 3 In the preamble for the 2015 O 3 NAAQS, EPA indicates that the impact of O 3 on vegetation and ecosystems is best represented using a W126 statistic. This statistic uses hourly O 3 data between 8 am and 8 pm, more heavily weighting higher values, and summing the weighted values across three months. CAPCOG calculated the W126 statistic for CAMS 3 for 2010 to 2015 using the formulas provided by EPA at CAPCOG only calculated these values for CAMS 3 and 38. The preamble states that a 3-year average W126 statistic of 17 ppm-hours or less would be protective of vegetation. Despite both CAMS 3 and 38 having a significant number of days > 70 ppb between 2010 and 2015 and having design values > 70 ppb from , its W126 values were only 56-60% of 17 ppm-hours for , and 45-49% of the 17 ppm-hour level for Page 47 of 173

48 O 3 ppm-hours CAPCOG Ozone Conceptual Model 2016 Figure W126 statistics for CAMS 3 and 38, CAMS 3 CAMS Page 48 of 173

49 5 Meteorological Factors CAPCOG evaluated a variety of potential meteorological factors that could influence the MDA8 O 3 values throughout the region, including: Avg. wind speed (WS) between 12 pm and 4 pm at each monitoring station; Average Temp. between 12 pm and 4 pm at each monitoring location; Diurnal Temp. changes at each monitoring location; Average relative humidity (RH) between 12 pm and 4 pm at all monitoring locations; Average solar radiation (SR) between 12 pm and 4 pm at each monitoring location; and Res. Wind direction (WD) from 8 am 12 pm and 12 pm 4 pm. CAPCOG used the 12 pm 4 pm time frame based on these being the four hours with the highest average 1-hour O 3 levels on days when MDA8 O 3 levels were >70 ppb at CAMS 3. CAPCOG included the 8 am 12 pm period for WD as well based on this time frame including all of the start hours for MDA8 values > 70 ppb at CAMS 3 and 38. For avg. WS, temp., diurnal temp. change, avg. RH, and avg. SR, CAPCOG calculated the number of days when O 3 MDA8 was >70 ppb, ppb, and <55 ppb with corresponding meteorological data, as well as the following statistics: Average (Avg.); Standard Deviation (S.D.); Minimum; Maximum; and 95% confidence interval (C.I.) of the mean. For these meteorological factors, CAPCOG first evaluated: 1. If the mean values for any of the MDA8 O3 ranges were outside the 95% C.I. for the other MDA8 O3 ranges (i.e., was the avg. WS for >70 ppb days outside the C.I. for the avg. WS for ppb days?); and 2. Whether there was a statistically significant difference in means between two sets of meteorological factors associated with MDA8 O 3 ranges. If either of these conditions were met, CAPCOG considered that meteorological factor to have a statistically significant impact on MDA8 O 3 formation at that site. CAPCOG also evaluated: 1. Whether the average for ppb days was outside the range of values for the >70 ppb days and 2. Whether the average for <55 ppb days was outside the range of values for the ppb days. Page 49 of 173

50 If either of these conditions were met, CAPCOG considered the minimum or maximum values associated with the MDA8 O 3 levels to be considered a necessary condition for high O 3. CAPCOG also evaluated whether any of these conditions could be considered sufficient for high O 3 formation. A condition was considered sufficient if all of the days when that meteorological condition occurred had high MDA8 O 3 levels. For resultant WD, CAPCOG used the 1-hour resultant WS and WD data in order to calculate 4-hour WS and WD vectors and assigned them to compass directions as shown in the following table. Table 5-1. WD Definitions WD Abbreviation Assigned Values (degrees) North N x 360 and 0 x > North-Northeast NNE x > Northeast NE x > East-Northeast ENE x > East E x > East-Southeast ESE x > Southeast SE x > South-Southeast SSE x > South S x > South-Southwest SSW x > Southwest SW x > West-Southwest SSW x > West W x > West-Northwest WNW x > Northwest NW x > North-Northwest NNW x > CAPCOG then grouped the data by MDA8 values of >70 ppb, ppb, and <55 ppb and used χ 2 - tests of independence in order to determine whether there were statistically significant differences between the actual distribution and the expected WD distribution given the data for all days. Finally, CAPCOG conducted a series of regression analyses in order to test the statistical significance and impact of each meteorological factor in light of all of the available meteorological data for the period. 5.1 Wind Speed Previous CAPCOG O 3 conceptual models indicated that Avg. WS had a generally negative correlation with MDA8 O 3. CAPCOG analyzed the data for 12-4 pm in order to limit the analysis to just the hours that typically included the peak O 3 concentrations for the day. The figure below shows a very weak relationship between these average WS during these times and MDA8 O 3. Page 50 of 173

51 MDA8 (ppb) CAPCOG Ozone Conceptual Model 2016 Figure 5-1. Avg. WS 12-4 pm v. MDA8 O 3 at CAMS 3, y = x R² = Avg. WS 12-4 pm (mph) CAPCOG calculated the 12pm 4 pm average WS at each site based on any available average WS data within that time frame. Therefore, if a site only had average WS data recorded in LEADS for 12pm 1pm, and the wind speed data for 1 pm 4 pm was not recorded, CAPCOG used the 12 pm 1 pm value. However, as the more detailed data below shows, there are statistically significant differences at some monitors between the average 12 pm 4 pm WS when MDA8 O 3 is <55 ppb, ppb, and >70 ppb. The figure below shows the average 12 pm-4 pm WS on days when MDA8 O 3 was <55 ppb, ppb, and >70 ppb at each monitoring station from Error bars represent the 95% confidence interval for the average, and values are expressed in miles per hour (mph). Page 51 of 173

52 Avg. WS 12-4pm (mph) CAPCOG Ozone Conceptual Model 2016 Figure 5-2. Avg. WS 12pm-4pm v. MDA8 O and 95% confidence intervals MDA8 <55 ppb MDA ppb MDA8 >70 ppb CAMS As the figure shows, there is a negative relationship between 12 pm-4 pm WS and MDA8 O 3 at all sites. There is a statistically significant difference in WS between days with MDA8 O 3 < 55 ppb compared to days when MDA8 O 3 is ppb at all monitoring stations, and statistically significant differences between ppb and >70 ppb WS at CAMS 3, 38, 601, 614, and 690. These five stations also happen to be equipped with different WS sensors than the other seven (Met One F460 at these five stations, compared to R.M. Young at the other stations), so it is possible that differences in performance characteristics at low WS account for the discrepancy. The figure also indicates that there are statistically significant differences in the average WS profiles for the various stations in the region. Since CAMS 3 and 38 were operated year-round during this time, while the other stations were operated seasonally, seasonal differences in WS patterns could explain some of these differences. However, differences in site configurations for CAPCOG sites relative to federal requirements for regulatory monitoring may also account for some of the difference. In particular, the much lower WS values for CAMS 674, which was only in service in 2010 during this period, suggest that there might have been some issues with the site configuration accounting for those lower WS. However, even for that site, the general pattern showing days with higher O 3 levels having a statistically significantly lower average WS from 12 pm-4 pm. The table below summarizes the results of 1-tailed difference of means tests CAPCOG performed to determine statistical significance. Page 52 of 173

53 Table 5-2. Statistically significantly different avg. WS 12pm 4 pm by MDA8 category and CAMS Station >70 ppb : ppb 1-tailed t-test P- value Statistically Significant Difference in Means >70 ppb : ppb ppb : <55 ppb 1-tailed t-test P- value Statistically Significant Difference in Means ppb : <55 ppb CAMS * *10-7 CAMS * *10-6 CAMS * *10-10 CAMS * *10-7 CAMS * *10-7 CAMS * *10-2 CAMS * *10-3 CAMS * *10-30 CAMS * *10-11 CAMS 1604 n/a 2.32*10-8 CAMS * *10-21 CAMS * *10-15 The tables below provide more details on the number of data points, average WS values, standard deviations, the range of values associated with each MDA8 range, and the confidence intervals. Page 53 of 173

54 Table 5-3. Avg. WS 12-4pm statistics for CAMS 3, MDA8 O 3 (ppb) Count Avg. WS pm (mph) St. Dev. (mph) Min Avg. WS 12-4 pm (mph) Max Avg. WS pm (mph) 95 % C.I. Low Value (mph) 95 % C.I. High Value (mph) >70 ppb ppb <55 ppb Table 5-4. Avg. WS 12-4pm statistics for CAMS 38, MDA8 O 3 (ppb) Count Avg. WS pm (mph) St. Dev. (mph) Min Avg. WS 12-4 pm (mph) Max Avg. WS pm (mph) 95 % C.I. Low Value (mph) 95 % C.I. High Value (mph) >70 ppb ppb <55 ppb Table 5-5. Avg. WS 12-4pm statistics for CAMS 601, MDA8 O 3 (ppb) Count Avg. WS pm (mph) St. Dev. (mph) Min Avg. WS 12-4 pm (mph) Max Avg. WS pm (mph) 95 % C.I. Low Value (mph) 95 % C.I. High Value (mph) >70 ppb ppb <55 ppb Page 54 of 173

55 Table 5-6. Avg. WS 12-4pm statistics for CAMS 614, MDA8 O 3 (ppb) Count Avg. WS pm (mph) St. Dev. (mph) Min Avg. WS 12-4 pm (mph) Max Avg. WS pm (mph) 95 % C.I. Low Value (mph) 95 % C.I. High Value (mph) >70 ppb ppb <55 ppb Table 5-7. Avg. WS 12-4pm statistics for CAMS 674, MDA8 O 3 (ppb) Count Avg. WS pm (mph) St. Dev. (mph) Min Avg. WS 12-4 pm (mph) Max Avg. WS pm (mph) 95 % C.I. Low Value (mph) 95 % C.I. High Value (mph) >70 ppb ppb <55 ppb Table 5-8. Avg. WS 12-4pm statistics for CAMS 675, MDA8 O 3 (ppb) Count Avg. WS pm (mph) St. Dev. (mph) Min Avg. WS 12-4 pm (mph) Max Avg. WS pm (mph) 95 % C.I. Low Value (mph) 95 % C.I. High Value (mph) >70 ppb ppb <55 ppb Page 55 of 173

56 Table 5-9. Avg. WS 12-4pm statistics for CAMS 684, MDA8 O 3 (ppb) Count Avg. WS pm (mph) St. Dev. (mph) Min Avg. WS 12-4 pm (mph) Max Avg. WS pm (mph) 95 % C.I. Low Value (mph) 95 % C.I. High Value (mph) >70 ppb ppb <55 ppb Table Avg. WS 12-4pm statistics for CAMS 690, MDA8 O 3 (ppb) Count Avg. WS pm (mph) St. Dev. (mph) Min Avg. WS 12-4 pm (mph) Max Avg. WS pm (mph) 95 % C.I. Low Value (mph) 95 % C.I. High Value (mph) >70 ppb ppb <55 ppb Table Avg. WS 12-4pm statistics for CAMS 1603, MDA8 O 3 (ppb) Count Avg. WS pm (mph) St. Dev. (mph) Min Avg. WS 12-4 pm (mph) Max Avg. WS pm (mph) 95 % C.I. Low Value (mph) 95 % C.I. High Value (mph) >70 ppb ppb <55 ppb Page 56 of 173

57 Table Avg. WS. 12-4pm statistics for CAMS 1604, MDA8 O 3 (ppb) Count Avg. WS pm (mph) St. Dev. (mph) Min Avg. WS 12-4 pm (mph) Max Avg. WS pm (mph) 95 % C.I. Low Value (mph) 95 % C.I. High Value (mph) >70 ppb 0 n/a n/a n/a n/a n/a n/a ppb <55 ppb Table Avg. WS 12-4pm statistics for CAMS 1675, MDA8 O 3 (ppb) Count Avg. WS pm (mph) St. Dev. (mph) Min Avg. WS 12-4 pm (mph) Max Avg. WS pm (mph) 95 % C.I. Low Value (mph) 95 % C.I. High Value (mph) >70 ppb ppb <55 ppb Table Avg. WS. 12-4pm statistics for CAMS 6602, MDA8 O 3 (ppb) Count Avg. WS pm (mph) St. Dev. (mph) Min Avg. WS 12-4 pm (mph) Max Avg. WS pm (mph) 95 % C.I. Low Value (mph) 95 % C.I. High Value (mph) >70 ppb ppb <55 ppb For all of the stations in the CAPCOG region, the highest 12 pm-4 pm Avg. WS on a day with MDA8 O 3 > 70 ppb was mph. Given the statistically significant differences between the average WS between >70 ppb, ppb, and <55 ppb days, CAPCOG will consider low average 12pm-4pm WS (<=10.35 mph) to be a necessary condition for MDA8 O 3 values to exceed 70 ppb. However, since MDA8 values in the Page 57 of 173

58 ppb and <55 ppb ranges were recorded when average 12 pm-4 pm WS was <=10.35 mph at all monitoring stations, low Avg. WS is not considered a sufficient condition for MDA8 O 3 > 70 ppb. Page 58 of 173

59 MDA8 (ppb) CAPCOG Ozone Conceptual Model Temperature There is a positive correlation between the average temperature measured between 12-4 pm and MDA8 O 3 levels. A graph showing this relationship at CAMS 3 between 2010 and 2015 is shown below. Figure 5-3. Avg. temp. 12-4pm v. MDA8 O 3, CAMS 3, y = x R² = Avg. Temp pm (deg. F) Temperature data for CAMS 3, 38, 601, 614, and 690 are available for , while temp. data for CAMS 684, 1603, 1604, and 1675 is only available for 2014 and Temperature data are not available for CAMS 674 or 675. For this analysis, CAPCOG excluded data from the following periods due to data quality concerns: CAMS 601 in 2010 and 2011 due to concerns about temp. data quality; and CAMS 6602 in 2014 due to concerns about O 3 data quality. CAPCOG calculated the 12pm 4 pm temp. averages based on any available temp. data within that time frame. Therefore, if a site only had temperature data recorded in LEADS for 12 pm 1 pm, and the temp. data for 1pm 4pm was not recorded, CAPCOG used the 12 pm 1 pm value. The figure below shows the average 12pm 4pm temp. at each monitoring station when MDA8 O 3 is <55 ppb, ppb, and >70 ppb. 95% confidence intervals for each average are shown. Page 59 of 173

60 Avg. Temp. 12-4pm (deg. F) CAPCOG Ozone Conceptual Model 2016 Figure 5-4. Avg. temp. 12pm-4pm v. MDA8 O 3 and 95% confidence intervals 100 MDA8 <55 ppb MDA ppb MDA8 >70 ppb CAMS The table below summarizes the results of 1-tailed difference of means tests CAPCOG performed to determine statistical significance. Table Statistically significantly different avg. temp. 12pm 4 pm by MDA8 category and CAMS Station >70 ppb : ppb 1-tailed t-test P- value Statistically Significant Difference in Means >70 ppb : ppb ppb : <55 ppb 1-tailed t-test P- value Statistically Significant Difference in Means ppb : <55 ppb CAMS * *10-67 CAMS * *10-82 CAMS * *10-2 CAMS * *10-4 CAMS 684 n/a *10-3 CAMS * *10-6 CAMS * *10-10 CAMS 1604 n/a 1.72*10-3 CAMS * *10-2 CAMS * * Only 1 >70 ppb value available to analyze for CAMS 684. This value was, however, outside of the confidence interval for the ppb average. Page 60 of 173

61 As the table above shows, there was at least one statistically significant difference in the average 12 pm- 4 pm temp. between lower and higher O 3 days at each monitoring station. For all stations other than CAMS 1675, there was a statistically significant difference between the average 12 pm-4 pm temperature for days when MDA8 O 3 was <55 ppb and days when MDA8 O 3 was ppb, and CAMS 1675 still showed a statistically significant difference in 12 pm-4 pm averages between days when MDA8 O 3 was ppb and days when MDA8 O 3 was >70 ppb. The higher average 12 pm-4 pm temp. at CAPCOG sites for days when MDA8 O 3 was <55 ppb compared to TCEQ s sites can be explained by the difference in the operating schedules, with TCEQ collecting data year-round and CAPCOG collecting data only seasonally. The tables below show the detailed statistics for each monitoring station, including the number of data points, the average temp., the standard deviations, the minimum and maximum average 12 pm-4 pm average temp., and the confidence intervals for days when MDA8 was >70 ppb, ppb, <55 ppb. Page 61 of 173

62 Table Avg. temp. 12-4pm statistics for CAMS 3, MDA8 O 3 (ppb) Count Avg. Temp pm (deg. F) St. Dev. (deg. F) Min Avg. Temp pm (deg. F) Max Avg. Temp pm (deg. F) 95 % C.I. Low Value (deg. F) 95 % C.I. High Value (deg. F) >70 ppb ppb <55 ppb Table Avg. temp. 12-4pm statistics for CAMS 38, MDA8 O 3 (ppb) Count Avg. Temp pm (deg. F) St. Dev. (deg. F) Min Avg. Temp pm (deg. F) Max Avg. Temp pm (deg. F) 95 % C.I. Low Value (deg. F) 95 % C.I. High Value (deg. F) >70 ppb ppb <55 ppb Table Avg. temp. 12-4pm statistics for CAMS 601, MDA8 O 3 (ppb) Count Avg. Temp pm (deg. F) St. Dev. (deg. F) Min Avg. Temp pm (deg. F) Max Avg. Temp pm (deg. F) 95 % C.I. Low Value (deg. F) 95 % C.I. High Value (deg. F) >70 ppb ppb <55 ppb Temperature data for 2010 and 2011 were excluded due to data quality concerns. Page 62 of 173

63 Table Avg. temp. 12-4pm statistics for CAMS 614, MDA8 O 3 (ppb) Count Avg. Temp pm (deg. F) St. Dev. (deg. F) Min Avg. Temp pm (deg. F) Max Avg. Temp pm (deg. F) 95 % C.I. Low Value (deg. F) 95 % C.I. High Value (deg. F) >70 ppb ppb <55 ppb Table Avg. temp. 12-4pm statistics for CAMS 684, MDA8 O 3 (ppb) Count Avg. Temp pm (deg. F) St. Dev. (deg. F) Min Avg. Temp pm (deg. F) Max Avg. Temp pm (deg. F) 95 % C.I. Low Value (deg. F) 95 % C.I. High Value (deg. F) >70 ppb n/a n/a n/a ppb <55 ppb Table Avg. temp. 12-4pm statistics for CAMS 690, MDA8 O 3 (ppb) Count Avg. Temp pm (deg. F) St. Dev. (deg. F) Min Avg. Temp pm (deg. F) Max Avg. Temp pm (deg. F) 95 % C.I. Low Value (deg. F) 95 % C.I. High Value (deg. F) >70 ppb ppb <55 ppb Page 63 of 173

64 Table Avg. temp. 12-4pm statistics for CAMS 1603, MDA8 O 3 (ppb) Count Avg. Temp pm (deg. F) St. Dev. (deg. F) Min Avg. Temp pm (deg. F) Max Avg. Temp pm (deg. F) 95 % C.I. Low Value (deg. F) 95 % C.I. High Value (deg. F) >70 ppb ppb <55 ppb Table Avg. temp. 12-4pm statistics for CAMS 1604, MDA8 O 3 (ppb) Count Avg. Temp pm (deg. F) St. Dev. (deg. F) Min Avg. Temp pm (deg. F) Max Avg. Temp pm (deg. F) 95 % C.I. Low Value (deg. F) 95 % C.I. High Value (deg. F) >70 ppb 0 n/a n/a n/a n/a n/a n/a ppb <55 ppb Table Avg. temp. 12-4pm statistics for CAMS 1675, MDA8 O 3 (ppb) Count Avg. Temp pm (deg. F) St. Dev. (deg. F) Min Avg. Temp pm (deg. F) Max Avg. Temp pm (deg. F) 95 % C.I. Low Value (deg. F) 95 % C.I. High Value (deg. F) >70 ppb ppb <55 ppb Page 64 of 173

65 Table Avg. temp. 12-4pm statistics for CAMS 6602, MDA8 O 3 (ppb) Count Avg. Temp pm (deg. F) St. Dev. (deg. F) Min Avg. Temp pm (deg. F) Max Avg. Temp pm (deg. F) 95 % C.I. Low Value (deg. F) 95 % C.I. High Value (deg. F) >70 ppb ppb <55 ppb These detailed data show that the lowest average 12 pm-4 pm average temp. that occurred on a day when an MDA8 O 3 level exceeded 70 ppb was 76.8 degrees F. Based on the statistical analysis above, high 12 pm-4 pm temp. (average >=76.8 degrees) can be considered a necessary condition for MDA8 O 3 levels >70 ppb. However, since MDA8 O 3 levels did not exceed 70 ppb on all days when 12 pm-4 pm average temp. were above 76.8 degrees, high temp. cannot be considered a sufficient condition for high O 3. Page 65 of 173

66 MDA8 (ppb) CAPCOG Ozone Conceptual Model 2016 CAPCOG s 2015 Ozone Conceptual Model indicated that diurnal temperature range was also positively correlated with MDA8 O 3 levels. The graph below shows the difference between the maximum and minimum 1-hour average temperatures compared to MDA8 values at CAMS 3 from Figure 5-5. Diurnal temp. change v. MDA8 O 3 at CAMS y = x R² = Diff. Between Max. and Min. 1-Hour Temp. (deg. F) Temperature data for CAMS 3, 38, 601, 614, and 690 are available for , while temperature data for CAMS 684, 1603, 1604, and 1675 is only available for 2014 and Temperature data are not available for CAMS 674 or 675. For this analysis, CAPCOG excluded data from the following periods due to data quality concerns: CAMS 601 in 2010 and 2011 due to concerns about temp. data quality; and CAMS 6602 in 2014 due to concerns about O 3 data quality. Due to the potential sensitivity of this analysis to missing 1-hour temperature data, CAPCOG limited the data to only days when a monitoring station had a full 24 hours of temperature data. The figure below shows the average diurnal change in temperature between the daily low and high at each monitoring station when MDA8 O 3 was <55 ppb, ppb, and >70 ppb. 95% confidence intervals for each average are shown. Page 66 of 173

67 Avg. Diurnal Temp. Change (deg. F) CAPCOG Ozone Conceptual Model 2016 Figure 5-6. Avg. diurnal temp. change v. MDA8 O MDA8 <55 ppb MDA ppb MDA8 >70 ppb CAMS 3 CAMS 38 CAMS 601 CAMS 614 CAMS 684 CAMS 690 CAMS 1603 CAMS 1604 CAMS 1675 CAMS 6602 The table below summarizes the results of 1-tailed difference of means tests CAPCOG performed to determine statistical significance. Table Statistically significantly different diurnal temp. changes by MDA8 Category and CAMS Station >70 ppb : ppb 1-tailed t-test P- value Statistically Significant Difference in Means >70 ppb : ppb ppb : <55 ppb 1-tailed t-test P- value Statistically Significant Difference in Means ppb : <55 ppb CAMS * *10-34 CAMS * *10-43 CAMS * *10-29 CAMS * *10-43 CAMS 684 n/a *10-13 CAMS * *10-43 CAMS * *10-16 CAMS 1604 n/a 3.96*10-15 CAMS * *10-10 CAMS * * Only 1 day at CAMS 684 had temperature data and MDA8 O 3 >70 ppb. This value was outside of the confidence interval for days with MDA8 O ppb. Page 67 of 173

68 These data show that the average diurnal change in temperature on days when MDA8 O 3 was ppb was statistically significantly different from the typical change in temperature on days when MDA8 O 3 was <55 ppb at all stations. However, the average diurnal temperature change on days when MDA8 O 3 was >70 ppb was only statistically significantly different from the average diurnal temperature change on days when MDA8 O 3 was ppb at a few of the monitoring stations. The tables below provide more details on the data for each individual monitoring station. Page 68 of 173

69 Table Diurnal temp. change statistics for CAMS 3, MDA8 O 3 (ppb) Count Avg. Temp Change (deg. F) St. Dev. (deg. F) Min Avg. Temp. Change (deg. F) Max Avg. Temp. Change (deg. F) 95 % C.I. Low Value (deg. F) 95 % C.I. High Value (deg. F) >70 ppb ppb <55 ppb Table Diurnal temp. change statistics for CAMS 38, MDA8 O 3 (ppb) Count Avg. Temp Change (deg. F) St. Dev. (deg. F) Min Avg. Temp. Change (deg. F) Max Avg. Temp. Change (deg. F) 95 % C.I. Low Value (deg. F) 95 % C.I. High Value (deg. F) >70 ppb ppb <55 ppb Table Diurnal temp. change statistics for CAMS 601, MDA8 O 3 (ppb) Count Avg. Temp Change (deg. F) St. Dev. (deg. F) Min Avg. Temp. Change (deg. F) Max Avg. Temp. Change (deg. F) 95 % C.I. Low Value (deg. F) 95 % C.I. High Value (deg. F) >70 ppb ppb <55 ppb Temperature data for 2010 and 2011 were excluded due to data quality concerns. Page 69 of 173

70 Table Diurnal temp. change statistics for CAMS 614, MDA8 O 3 (ppb) Count Avg. Temp Change (deg. F) St. Dev. (deg. F) Min Avg. Temp. Change (deg. F) Max Avg. Temp. Change (deg. F) 95 % C.I. Low Value (deg. F) 95 % C.I. High Value (deg. F) >70 ppb ppb <55 ppb Table Diurnal temp. change statistics for CAMS 684, MDA8 O 3 (ppb) Count Avg. Temp Change (deg. F) St. Dev. (deg. F) Min Avg. Temp. Change (deg. F) Max Avg. Temp. Change (deg. F) 95 % C.I. Low Value (deg. F) 95 % C.I. High Value (deg. F) >70 ppb n/a n/a n/a ppb <55 ppb Table Diurnal temp. change statistics for CAMS 690, MDA8 O 3 (ppb) Count Avg. Temp Change (deg. F) St. Dev. (deg. F) Min Avg. Temp. Change (deg. F) Max Avg. Temp. Change (deg. F) 95 % C.I. Low Value (deg. F) 95 % C.I. High Value (deg. F) >70 ppb ppb <55 ppb Page 70 of 173

71 Table Diurnal temp. change statistics for CAMS 1603, MDA8 O 3 (ppb) Count Avg. Temp Change (deg. F) St. Dev. (deg. F) Min Avg. Temp. Change (deg. F) Max Avg. Temp. Change (deg. F) 95 % C.I. Low Value (deg. F) 95 % C.I. High Value (deg. F) >70 ppb ppb <55 ppb Table Diurnal temp. change statistics for 1604, MDA8 O 3 (ppb) Count Avg. Temp Change (deg. F) St. Dev. (deg. F) Min Avg. Temp. Change (deg. F) Max Avg. Temp. Change (deg. F) 95 % C.I. Low Value (deg. F) 95 % C.I. High Value (deg. F) >70 ppb 0 n/a n/a n/a n/a n/a n/a ppb <55 ppb Table Diurnal temp. change statistics for CAMS 1675, MDA8 O 3 (ppb) Count Avg. Temp Change (deg. F) St. Dev. (deg. F) Min Avg. Temp. Change (deg. F) Max Avg. Temp. Change (deg. F) 95 % C.I. Low Value (deg. F) 95 % C.I. High Value (deg. F) >70 ppb ppb <55 ppb Page 71 of 173

72 Table Diurnal temp. change statistics for CAMS 6602, MDA8 O 3 (ppb) Count Avg. Temp Change (deg. F) St. Dev. (deg. F) Min Avg. Temp. Change (deg. F) Max Avg. Temp. Change (deg. F) 95 % C.I. Low Value (deg. F) 95 % C.I. High Value (deg. F) >70 ppb ppb <55 ppb Given the statistically significant relationship between higher diurnal changes in temperature and MDA8 O 3, it is reasonable to conclude that the minimum change in temperature measured from on a day when MDA8 O 3 was >70 ppb may be a necessary condition for O 3 levels that high. The data above show that this value was 25.6 degrees F. Since there are numerous days when the diurnal change in temp. was larger than that when MDA8 O 3 was <= 70 ppb, this condition would not be considered sufficient for high O 3 formation. Page 72 of 173

73 5.3 Humidity CAPCOG compared the MDA8 O 3 at each of the region s monitoring stations to the nearest average RH from 12 pm 4 pm measured in the region. Until CAPCOG deployed RH/temp. sensors at seven of its eight O 3 monitoring stations in 2014, none of the region s O 3 monitoring stations had co-located RH sampling. Previous analyses relied on RH measurements collected at National Weather Service (NWS) stations at Camp Mabry (CAMS 5001/5002 in Travis County) and Austin-Bergstrom International Airport (ABIA) (CAMS 5003) in Travis County. Due to data gaps and errors in the NWS data reported to TCEQ s LEADS system, CAPCOG directly downloaded and organized the NWS RH sampling data for CAMS 5002 and CAPCOG used the data stored in LEADS for the 2014 and 2015 RH data at CAPCOG stations. First, CAPCOG analyzed the RH data collected at these three NWS stations and at its own stations in 2014 and 2015 in order to determine whether it would be appropriate to assume that RH data from one station was representative of RH at a nearby station, particularly since CAMS 3 and 38 lack any RH measurements. The table below shows a correlation matrix for the 12 pm 4 pm RH averages between each monitoring station. Table RH measurement correlation matrix, CAMS As the table shows, with the exception of CAMS 684, correlations between data collected at each site were very high. Therefore, CAPCOG assigned CAMS 3, 38, and 684 to the nearest NWS station s RH data, and excluded the RH data collected at CAMS 684. The table below summarizes the station assignments used for this analysis. Page 73 of 173

74 Peak MDA8 O 3 (ppb) CAPCOG Ozone Conceptual Model 2016 Table Summary of RH data used for each CAMS CAMS Assigned RH CAMS Days with Data Usable in Analysis Distance from Assigned Station (km) Direction from Assigned Station (degrees) , , n/a n/a n/a n/a n/a n/a , n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a CAMS 5002 is located approximately 4 km south of CAMS 3, putting it within the 3 x 3 array of 4km x 4km grid cells used for photochemical modeling for this region. While CAMS 38 and CAMS 684 are somewhat further from their assigned station than CAMS 3 is to Camp Mabry, they are close enough that they would be located within a 3 x 3 array of 12 km x 12 km grid cells around the station. Due to the distance between CAMS 601 and any RH sensor, CAPCOG did not include CAMS 601 in this analysis. Next, CAPCOG analyzed the relationship between RH and MDA8 O 3 levels. The following chart shows a plot of the CAMS 3 MDA8 O 3 values and average CAMS 5002 (Camp Mabry) RH measurements for 12 pm 4 pm on days when the region s peak MDA8 value was >70 ppb, ppb, and <55 ppb. Figure 5-7. Camp Mabry RH 12 pm-4 pm v. CAMS 3 MDA8 O 3, y = x R² = Avg. RH 12-4 pm (%) Page 74 of 173

75 Avg. RH 12-4 pm (%) CAPCOG Ozone Conceptual Model 2016 The following figure shows the average 12 pm-4 pm RH from each CAMS s assigned RH station on days when MDA8 O 3 was >70 ppb, ppb, and <55 ppb. 95% confidence intervals are also shown. Figure 5-8. Avg. RH 12pm-4pm v. MDA8 O 3 60 MDA8 <55 ppb MDA ppb MDA8 >70 ppb / / / CAMS The table below summarizes the results of 1-tailed difference of means tests CAPCOG performed to determine statistical significance. Table Statistically significantly different avg. RH. 12 pm 4 pm by MDA8 category and CAMS Station >70 ppb : ppb 1-tailed t-test P- value Statistically Significant Difference in Means >70 ppb : ppb ppb : <55 ppb 1-tailed t-test P- value Statistically Significant Difference in Means ppb : <55 ppb CAMS * *10-77 CAMS * *10-84 CAMS * *10-29 CAMS * *10-57 CAMS * *10-20 CAMS * *10-20 CAMS 1604 n/a 7.73*10-19 CAMS * *10-23 CAMS * *10-16 These results show that there are statistically significantly lower average 12 pm-4 pm RH levels on days when MDA8 O 3 levels are ppb compared to days when MDA8 O 3 levels are <55 ppb. There are Page 75 of 173

76 statistically significant differences between the average 12 pm-4 pm RH on days when MDA8 O 3 levels are >70 ppb compared to days when MDA8 O 3 levels are ppb. The tables below show the detailed RH statistics for each monitoring station. Page 76 of 173

77 Table RH statistics for CAMS 3, MDA8 O 3 (ppb) Count RH 12-4 pm (%) St. Dev. (%) Min RH 12-4 pm (%) Max RH 12-4 pm (%) 95 % C.I. Low Value (%) 95 % C.I. High Value (%) >70 ppb ppb <55 ppb Table RH statistics for CAMS 38, MDA8 O 3 (ppb) Count RH 12-4 pm (%) St. Dev. (%) Min RH 12-4 pm (%) Max RH 12-4 pm (%) 95 % C.I. Low Value (%) 95 % C.I. High Value (%) >70 ppb ppb <55 ppb Table RH statistics for CAMS 614, MDA8 O 3 (ppb) Count RH 12-4 pm (%) St. Dev. (%) Min RH 12-4 pm (%) Max RH 12-4 pm (%) 95 % C.I. Low Value (%) 95 % C.I. High Value (%) >70 ppb ppb <55 ppb Table RH statistics for CAMS 684, MDA8 O 3 (ppb) Count RH 12-4 pm (%) St. Dev. (%) Min RH 12-4 pm (%) Max RH 12-4 pm (%) 95 % C.I. Low Value (%) 95 % C.I. High Value (%) >70 ppb ppb <55 ppb Page 77 of 173

78 Table RH statistics for CAMS 690, MDA8 O 3 (ppb) Count RH 12-4 pm (%) St. Dev. (%) Min RH 12-4 pm (%) Max RH 12-4 pm (%) 95 % C.I. Low Value (%) 95 % C.I. High Value (%) >70 ppb ppb <55 ppb Table RH statistics for CAMS 1603, MDA8 O 3 (ppb) Count RH 12-4 pm (%) St. Dev. (%) Min RH 12-4 pm (%) Max RH 12-4pm (%) 95 % C.I. Low Value (%) 95 % C.I. High Value (%) >70 ppb ppb <55 ppb Table RH statistics for CAMS 1604, MDA8 O 3 (ppb) Count RH 12-4 pm (%) St. Dev. (%) Min RH 12-4 pm (%) Max RH 12-4 pm (%) 95 % C.I. Low Value (%) 95 % C.I. High Value (%) >70 ppb 0 n/a n/a n/a n/a n/a n/a ppb <55 ppb Table RH statistics for CAMS 1675, MDA8 O 3 (ppb) Count RH 12-4 pm (%) St. Dev. (%) Min RH 12-4 pm (%) Max RH 12-4 pm (%) 95 % C.I. Low Value (%) 95 % C.I. High Value (%) >70 ppb ppb <55 ppb Page 78 of 173

79 Table RH statistics for CAMS 6602, MDA8 O 3 (ppb) Count RH 12-4 pm (%) St. Dev. (%) Min RH 12-4 pm (%) Max RH 12-4 pm (%) 95 % C.I. Low Value (%) 95 % C.I. High Value (%) >70 ppb ppb <55 ppb Based on the statistical significance of the relationship between RH and MDA8 levels, CAPCOG concludes that the highest 12 pm-4 pm RH level on a day when MDA8 O 3 was >70 ppb could be considered a necessary condition for high O 3 levels. This level was 46.3%. Due to numerous occasions when MDA8 O 3 levels were <= 70 ppb when RH was <=46.3%, this is not a sufficient condition. Page 79 of 173

80 MDA8 (ppb) 5.4 Solar Radiation CAMS 38 is equipped with a sensor capable of measuring SR, measured in langleys per minute. These data enable CAPCOG to analyze the relationship between SR between 12pm 4pm and O 3 MDA8 values. The following figure shows the general relationship between SR and MDA8 O 3. Figure 5-9. Avg. SR 12pm - 4pm v. MDA8 O 3 at CAMS 38, y = x R² = Avg. SR 12-4 pm (langleys per minute) Averaging the SR values for the three ranges of MDA8 O 3 values provides the following results. The error bars represent the range of SR averages for each MDA8 O 3 category. Page 80 of 173

81 Avg. SR 12pm-4pm (langleys/min) CAPCOG Ozone Conceptual Model 2016 Figure Avg. SR 12pm-4pm by CAMS 38 MDA8 O 3 and 95% confidence intervals <55 ppb ppb >70 ppb Peak MDA8 O 3 As the figures above show, there is a positive correlation between the average SR measured between 12pm 4pm at CAMS 38 and its MDA8 O 3 levels, and the range of values associated with MDA8 levels > 70 ppb is higher than the average value for days with MDA8 O 3 < 55 ppb. For the purposes of this conceptual model, CAPCOG will assume that average SR of 0.9 langleys/minute between 12pm and 4pm is necessary for MDA8 levels at CAMS 38 to exceed 70 ppb since this is the lowest level measured between 2010 and Table SR statistics for CAMS 38, MDA8 O 3 (ppb) Count SR 12-4 pm (langleys / min) St. Dev. (langleys / min) Min SR 12-4 pm (langleys / min) Max SR 12-4 pm (langleys / min) 95 % C.I. Low Value (%) 95 % C.I. High Value (%) >70 ppb ppb <55 ppb 1, SR was statistically significantly different between the >70 ppb, ppb, and <55 ppb MDA8 ranges. The lowest average 12 pm-4 pm SR value on a day when CAMS 3 recorded an MDA8 O 3 value > 70 ppb was 0.87 langleys per minute. Since MDA8 levels <= 70 ppb also coincided with avg. 12 pm-4 pm SR >= 0.87 langleys per minute, this factor is considered necessary, but not sufficient, for MDA8 O 3 levels at CAMS 38 > 70 ppb. Page 81 of 173

82 5.5 Wind Direction CAPCOG analyzed the impact that wind direction had on regional O 3 formation, including the distribution of res. WD on days when MDA8 was >70 ppb, ppb, and <55 ppb, and analysis of 24- hour back-trajectories on days when MDA8 >70 ppb Surface WD CAPCOG analyzed the resultant (vector) WD over two time periods: 12 pm 4 pm (the period with the highest average O 3 concentration at CAMS 3) and 8 am 12 pm (the 4-hour period immediately preceding the highest 8-hour O 3 average). In order to convert hourly res. WD and res. WS data into these vectors, CAPCOG used following steps: 1. Converted the WD from degrees into radians; 2. Calculated the X- and Y- components of the resultant WD (X = Res. WS * sine (radians); Y = Res. WS * cosine (radians)); 3. Summed the components for the 8 am 12pm and 12 pm 4 pm periods; 4. Designated the WD quadrant (0-90, , , and ) based on the signs of the resultant X- and Y- components (+/+ = 0-90; +/- = ; -/- = ; -/+ = ); 5. Calculated the Res. WS (Res. WS = square root of X 2 + Y 2 ); and 6. Calculated the resultant WD using the arctangent of the ratio of the resultant X-component and Y- component, adjusting the number to reflect the quadrant it is in: o If 0-90, arctangent (resultant X-component/resultant Y-component); o If , π + arctangent (resultant X-component/resultant Y-component); o If , π + arctangent (resultant X-component/resultant Y-component); o If , 2π + arctangent (resultant X-component/resultant Y-component) CAMS 3 The figures below show radar plots of the percentages of 8 am 12 pm and 12 pm 4 pm resultant WD for all days when MDA8 was > 70 ppb, ppb, and <55 ppb. Page 82 of 173

83 Figure Res. WD for CAMS 3, 8 am - 12 pm NW NNW 35.00% 30.00% 25.00% N NNE NE 20.00% WNW W 15.00% 10.00% 5.00% 0.00% ENE E % MDA8 < 55 ppb % MDA ppb % MDA8 >70 ppb WSW ESE SW SE SSW SSE S Figure Res. WD for CAMS 3, 12 pm 4 pm NW NNW 30.00% 25.00% 20.00% N NNE NE WNW 15.00% 10.00% ENE 5.00% % MDA8 < 55 ppb W 0.00% E % MDA ppb % MDA8 >70 ppb WSW ESE SW SE SSW SSE S Page 83 of 173

84 Table CAMS 3 WD chi-squared test statistics for days >70 ppb, ppb, and <55 ppb Time Period Degrees of Freedom Chi-Squared Test Statistic P-value 8 am 12pm < pm 4 pm < CAMS 38 The figures below show radar plots of the percentages of 8 am 12 pm and 12 pm 4 pm resultant WD for all days when MDA8 was > 70 ppb, ppb, and <55 ppb. Figure Res. WD for CAMS 38, 8 am - 12 pm NNW 25.00% N NNE NW 20.00% 15.00% NE WNW 10.00% ENE 5.00% % MDA8 < 55 ppb W 0.00% E % MDA ppb % MDA8 >70 ppb WSW ESE SW SE SSW S SSE Page 84 of 173

85 Figure Res. WD for CAMS 38, 12 pm 4 pm NNW 25.00% N NNE NW 20.00% 15.00% NE WNW 10.00% ENE 5.00% % MDA8 < 55 ppb W 0.00% E % MDA ppb % MDA8 >70 ppb WSW ESE SW SE SSW S SSE Table CAMS 38 WD chi-squared test statistics for days >70 ppb, ppb, and <55 ppb Time Period Degrees of Freedom Chi-Squared Test Statistic P-value 8 am 12pm < pm 4 pm < CAMS 601 The figures below show radar plots of the percentages of 8 am 12 pm and 12 pm 4 pm resultant WD for all days when MDA8 was > 70 ppb, ppb, and <55 ppb. Page 85 of 173

86 Figure Res. WD for CAMS 601, 8 am - 12 pm NNW 25.00% N NNE NW 20.00% 15.00% NE WNW 10.00% ENE 5.00% % MDA8 < 55 ppb W 0.00% E % MDA ppb % MDA8 >70 ppb WSW ESE SW SE SSW S SSE Figure Res. WD for CAMS 601, 12 pm 4 pm WNW W NW NNW 40.00% 35.00% 30.00% 25.00% 20.00% 15.00% 10.00% 5.00% 0.00% N NNE NE ENE E % MDA8 < 55 ppb % MDA ppb % MDA8 >70 ppb WSW ESE SW SE SSW S SSE Page 86 of 173

87 Table CAMS 601 WD chi-squared test statistics for days >70 ppb, ppb, and <55 ppb Time Period Degrees of Freedom Chi-Squared Test Statistic P-value 8 am 12pm < pm 4 pm < CAMS 614 The figures below show radar plots of the percentages of 8 am 12 pm and 12 pm 4 pm resultant WD for all days when MDA8 was > 70 ppb, ppb, and <55 ppb. Figure Res. WD for CAMS 614, 8 am - 12 pm NW NNW 30.00% 25.00% 20.00% N NNE NE WNW 15.00% 10.00% ENE 5.00% % MDA8 < 55 ppb W 0.00% E % MDA ppb % MDA8 >70 ppb WSW ESE SW SE SSW S SSE Page 87 of 173

88 Figure Res. WD for CAMS 614, 12 pm 4 pm NW NNW 30.00% 25.00% 20.00% N NNE NE WNW 15.00% 10.00% ENE 5.00% % MDA8 < 55 ppb W 0.00% E % MDA ppb % MDA8 >70 ppb WSW ESE SW SE SSW S SSE Table CAMS 614 WD chi-squared test statistics for days >70 ppb, ppb, and <55 ppb Time Period Degrees of Freedom Chi-Squared Test Statistic P-value 8 am 12pm < pm 4 pm < CAMS 674 The figures below show radar plots of the percentages of 8 am 12 pm and 12 pm 4 pm resultant WDs for all days when MDA8 was > 70 ppb, ppb, and <55 ppb. Page 88 of 173

89 Figure Res. WD for CAMS 674, 8 am - 12 pm WNW W NW NNW 40.00% 35.00% 30.00% 25.00% 20.00% 15.00% 10.00% 5.00% 0.00% N NNE NE ENE E % MDA8 < 55 ppb % MDA ppb % MDA8 >70 ppb WSW ESE SW SE SSW S SSE Figure Res. WD for CAMS 674, 12 pm 4 pm NNW 50.00% N NNE NW 40.00% 30.00% NE WNW 20.00% ENE 10.00% % MDA8 < 55 ppb W 0.00% E % MDA ppb % MDA8 >70 ppb WSW ESE SW SE SSW S SSE Page 89 of 173

90 Table CAMS 674 WD chi-squared test statistics for days >70 ppb, ppb, and <55 ppb Time Period Degrees of Freedom Chi-Squared Test Statistic P-value 8 am 12pm < pm 4 pm < CAMS 675 The figures below show radar plots of the percentages of 8 am 12 pm and 12 pm 4 pm resultant WD for all days when MDA8 was > 70 ppb, ppb, and <55 ppb. Figure Res. WD for CAMS 675, 8 am - 12 pm NW NNW 35.00% 30.00% 25.00% N NNE NE 20.00% WNW W 15.00% 10.00% 5.00% 0.00% ENE E % MDA8 < 55 ppb % MDA ppb % MDA8 >70 ppb WSW ESE SW SE SSW SSE S Page 90 of 173

91 Figure Res. WD for CAMS 675, 12 pm 4 pm NW NNW 30.00% 25.00% 20.00% N NNE NE WNW 15.00% 10.00% ENE 5.00% % MDA8 < 55 ppb W 0.00% E % MDA ppb % MDA8 >70 ppb WSW ESE SW SE SSW S SSE Table CAMS 675 WD chi-squared test statistics for days >70 ppb, ppb, and <55 ppb Time Period Degrees of Freedom Chi-Squared Test Statistic P-value 8 am 12pm < pm 4 pm < CAMS 684 The figures below show radar plots of the percentages of 8 am 12 pm and 12 pm 4 pm resultant WD for all days when MDA8 was > 70 ppb, ppb, and <55 ppb. Page 91 of 173

92 Figure Res. WD for CAMS 684, 8 am - 12 pm NW NNW 30.00% 25.00% 20.00% N NNE NE WNW 15.00% 10.00% ENE 5.00% % MDA8 < 55 ppb W 0.00% E % MDA ppb % MDA8 >70 ppb WSW ESE SW SE SSW S SSE Figure Res. WD for CAMS 684, 12 pm 4 pm NNW 25.00% N NNE NW 20.00% 15.00% NE WNW 10.00% ENE 5.00% % MDA8 < 55 ppb W 0.00% E % MDA ppb % MDA8 >70 ppb WSW ESE SW SE SSW S SSE Page 92 of 173

93 Table CAMS 684 WD chi-squared test statistics for days >70 ppb, ppb, and <55 ppb Time Period Degrees of Freedom Chi-Squared Test Statistic P-value 8 am 12pm < pm 4 pm < CAMS 690 The figures below show radar plots of the percentages of 8 am 12 pm and 12 pm 4 pm resultant WD for all days when MDA8 was > 70 ppb, ppb, and <55 ppb. Figure Res. WD for CAMS 690, 8 am - 12 pm NW NNW 30.00% 25.00% 20.00% N NNE NE WNW 15.00% 10.00% ENE 5.00% % MDA8 < 55 ppb W 0.00% E % MDA ppb % MDA8 >70 ppb WSW ESE SW SE SSW S SSE Page 93 of 173

94 Figure Res. WD for CAMS 690, 12 pm 4 pm WNW W NW NNW 40.00% 35.00% 30.00% 25.00% 20.00% 15.00% 10.00% 5.00% 0.00% N NNE NE ENE E % MDA8 < 55 ppb % MDA ppb % MDA8 >70 ppb WSW ESE SW SE SSW S SSE Table CAMS 690 WD chi-squared test statistics for days >70 ppb, ppb, and <55 ppb Time Period Degrees of Freedom Chi-Squared Test Statistic P-value 8 am 12pm < pm 4 pm < CAMS 1603 The figures below show radar plots of the percentages of 8 am 12 pm and 12 pm 4 pm resultant WD for all days when MDA8 was > 70 ppb, ppb, and <55 ppb. Page 94 of 173

95 Figure Res. WD for CAMS 1603, 8 am - 12 pm NW NNW 35.00% 30.00% 25.00% N NNE NE 20.00% WNW W 15.00% 10.00% 5.00% 0.00% ENE E % MDA8 < 55 ppb % MDA ppb % MDA8 >70 ppb WSW ESE SW SE SSW SSE S Figure Res. WD for CAMS 1603, 12 pm 4 pm NNW 50.00% N NNE NW 40.00% NE 30.00% WNW 20.00% ENE 10.00% % MDA8 < 55 ppb W 0.00% E % MDA ppb % MDA8 >70 ppb WSW ESE SW SE SSW S SSE Page 95 of 173

96 Table CAMS 1603 WD chi-squared test statistics for days >70 ppb, ppb, and <55 ppb Time Period Degrees of Freedom Chi-Squared Test Statistic P-value 8 am 12pm pm 4 pm < CAMS 1604 The figures below show radar plots of the percentages of 8 am 12 pm and 12 pm 4 pm resultant WD for all days when MDA8 was > 70 ppb, ppb, and <55 ppb. Figure Res. WD for CAMS 1604, 8 am - 12 pm NNW 25.00% N NNE NW 20.00% 15.00% NE WNW 10.00% ENE 5.00% % MDA8 < 55 ppb W 0.00% E % MDA ppb % MDA8 >70 ppb WSW ESE SW SE SSW S SSE Page 96 of 173

97 Figure Res. WD for CAMS 1604, 12 pm 4 pm NW NNW 35.00% 30.00% 25.00% N NNE NE 20.00% WNW W 15.00% 10.00% 5.00% 0.00% ENE E % MDA8 < 55 ppb % MDA ppb % MDA8 >70 ppb WSW ESE SW SE SSW SSE S Table CAMS 1604 WD chi-squared test statistics for days >70 ppb, ppb, and <55 ppb Time Period Degrees of Freedom Chi-Squared Test Statistic P-value 8 am 12pm < pm 4 pm CAMS 1675 The figures below show radar plots of the percentages of 8 am 12 pm and 12 pm 4 pm resultant WD for all days when MDA8 was > 70 ppb, ppb, and <55 ppb. Page 97 of 173

98 Figure Res. WD for CAMS 1675, 8 am - 12 pm NNW 25.00% N NNE NW 20.00% 15.00% NE WNW 10.00% ENE 5.00% % MDA8 < 55 ppb W 0.00% E % MDA ppb % MDA8 >70 ppb WSW ESE SW SE SSW S SSE Figure Res. WD for CAMS 1675, 12 pm 4 pm NNW 25.00% N NNE NW 20.00% 15.00% NE WNW 10.00% ENE 5.00% % MDA8 < 55 ppb W 0.00% E % MDA ppb % MDA8 >70 ppb WSW ESE SW SE SSW S SSE Page 98 of 173

99 Table CAMS 1675 WD chi-squared test statistics for days >70 ppb, ppb, and <55 ppb Time Period Degrees of Freedom Chi-Squared Test Statistic P-value 8 am 12pm < pm 4 pm < CAMS 6602 The figures below show radar plots of the percentages of 8 am 12 pm and 12 pm 4 pm resultant WD for all days when MDA8 was > 70 ppb, ppb, and <55 ppb. Figure Res. WD for CAMS 6602, 8 am - 12 pm NW NNW 30.00% 25.00% 20.00% N NNE NE WNW 15.00% 10.00% ENE 5.00% % MDA8 < 55 ppb W 0.00% E % MDA ppb % MDA8 >70 ppb WSW ESE SW SE SSW S SSE Page 99 of 173

100 Figure Res. WD for CAMS 6602, 12 pm 4 pm NW NNW 30.00% 25.00% 20.00% N NNE NE WNW 15.00% 10.00% ENE 5.00% % MDA8 < 55 ppb W 0.00% E % MDA ppb % MDA8 >70 ppb WSW ESE SW SE SSW S SSE Table CAMS 6602 WD chi-squared test statistics for days >70 ppb, ppb, and <55 ppb Time Period Degrees of Freedom Chi-Squared Test Statistic P-value 8 am 12pm < pm 4 pm < Back-Trajectories CAPCOG developed HYSPLIT 24-hour back-trajectories for days when measured MDA8 O 3 levels were >70 ppb. CAPCOG used the NAM 12 km model, starting the back-trajectories at the time of day corresponding to the peak 1-hour O 3 concentration. If there was more than one 1 hour period that had the same peak level, CAPCOG used the earliest of the peak 1-hour concentrations. CAPCOG ran the model at 100 meters (m), 500 m, and 1000 m elevations. These back-trajectory lengths (24 hours) and elevations were selected to match the lengths and elevations EPA used by EPA in its O 3 designation mapping tool. 15 The figures below show the frequency with which a county in Texas was upwind of the monitor at 100 m, which would be expected to most closely track surface winds. 15 Available online at Accessed 9/19/2016. Page 100 of 173

101 Figure CAMS 3 24-hour back-trajectories on days with MDA8 >70 ppb at 100 m ( ) Page 101 of 173

102 Figure CAMS hour back-trajectories on days with MDA8 >70 ppb at 100 m ( ) Page 102 of 173

103 Figure CAMS hour back-trajectories on days with MDA8 >70 ppb ( ) Page 103 of 173

104 Figure CAMS hour back-trajectories on days with MDA8 > 70 ppb ( ) Page 104 of 173

105 Figure CAMS hour back-trajectories on days with MDA8 >70 ppb (2010) Page 105 of 173

106 Figure CAMS hour back-trajectories when MDA8 >70 ppb (2010 and 2011) Page 106 of 173

107 Figure CAMS hour back-trajectories when MDA8 >70 ppb ( ) Page 107 of 173

108 Figure CAMS hour back-trajectories when MDA8 >70 ppb ( ) Page 108 of 173

109 Figure CAMS hour back-trajectories when MDA8 >70 ppb ( ) Page 109 of 173

110 Figure CAMS hour back-trajectories when MDA8 >70 ppb ( ) Page 110 of 173

111 Figure CAMS hour back-trajectories on days with MDA8 >70 ppb ( and 2015) CAPCOG analyzed the back-trajectories to determine the number of back-trajectories that crossed the boundaries of nearby counties and metro areas. The following figures show the number of backtrajectories crossing over each area for each monitoring station at each elevation. Page 111 of 173

112 Atascosa Bandera Bastrop Bell Bexar Blanco Burnet Caldwell Comal Coryell Fayette Frio Gillespie Gonzales Guadalupe Harris Hays Karnes Kendall Kerr Lee Llano McMullen Medina Milam Williamson Wilson Days Upwind Atascosa Bandera Bastrop Bell Bexar Blanco Burnet Caldwell Comal Coryell Fayette Frio Gillespie Gonzales Guadalupe Harris Hays Karnes Kendall Kerr Lee Llano McMullen Medina Milam Williamson Wilson Days Upwind CAPCOG Ozone Conceptual Model 2016 Figure Areas upwind of CAMS 3 on days with MDA8 >70 ppb back-trajectories m 500 m 1000 m Figure Areas upwind of CAMS 38 on days with MDA8 >70 ppb back-trajectories 100 m 500 m 1000 m Page 112 of 173

113 Atascosa Bandera Bastrop Bell Bexar Blanco Burnet Caldwell Comal Coryell Fayette Frio Gillespie Gonzales Guadalupe Harris Karnes Kendall Kerr Lee Llano McMullen Medina Milam Travis Williamson Wilson Days Upwind Atascosa Bandera Bastrop Bell Bexar Blanco Burnet Caldwell Comal Coryell Frio Gillespie Gonzales Guadalupe Harris Hays Karnes Kendall Kerr Lee Llano McMullen Medina Milam Travis Williamson Wilson Days Upwind CAPCOG Ozone Conceptual Model 2016 Figure Areas upwind of CAMS 601on days with MDA8 >70 ppb back-trajectories 100 m 500 m 1000 m Figure Areas upwind of CAMS 614 on days with MDA8 >70 ppb back-trajectories 100 m 500 m 1000 m Page 113 of 173

114 Atascosa Bandera Bastrop Bell Bexar Blanco Burnet Caldwell Comal Coryell Fayette Frio Gillespie Gonzales Guadalupe Harris Karnes Kendall Kerr Lee Llano McMullen Medina Milam Travis Williamson Wilson Days Upwind Atascosa Bandera Bastrop Bell Bexar Blanco Burnet Caldwell Comal Coryell Fayette Frio Gillespie Gonzales Guadalupe Harris Hays Karnes Kendall Kerr Lee Llano McMullen Medina Milam Travis Wilson Days Upwind CAPCOG Ozone Conceptual Model 2016 Figure Areas upwind of CAMS 674 on days with MDA8 >70 ppb back-trajectories m 500 m 1000 m Figure Areas upwind of CAMS 675 on days with MDA8 >70 ppb back-trajectories 100 m 500 m 1000 m Page 114 of 173

115 Atascosa Bandera Bastrop Bell Bexar Blanco Burnet Caldwell Comal Coryell Fayette Frio Gillespie Gonzales Guadalupe Harris Hays Karnes Kendall Kerr Lee Llano McMullen Medina Milam Travis Wilson Days Upwind Atascosa Bandera Bell Bexar Blanco Burnet Caldwell Comal Coryell Fayette Frio Gillespie Gonzales Guadalupe Harris Hays Karnes Kendall Kerr Lee Llano McMullen Medina Milam Travis Williamson Wilson Days Upwind CAPCOG Ozone Conceptual Model 2016 Figure Areas upwind of CAMS 684 on days with MDA8 >70 ppb back-trajectories 100 m 500 m 1000 m Figure Areas upwind of CAMS 690 on days with MDA8 >70 ppb back-trajectories m 500 m 1000 m Page 115 of 173

116 Atascosa Bandera Bastrop Bell Bexar Blanco Burnet Caldwell Comal Coryell Fayette Frio Gillespie Gonzales Guadalupe Harris Karnes Kendall Kerr Lee Llano McMullen Medina Milam Travis Williamson Wilson Days Upwind Atascosa Bandera Bastrop Bell Bexar Blanco Burnet Caldwell Comal Coryell Fayette Frio Gillespie Gonzales Guadalupe Harris Hays Karnes Kendall Kerr Lee Llano McMullen Medina Milam Williamson Wilson Days Upwind CAPCOG Ozone Conceptual Model 2016 Figure Areas upwind of CAMS 1603 on days with MDA8 >70 ppb back-trajectories 100 m 500 m 1000 m Figure Areas upwind of CAMS 1675 on days with MDA8 >70 ppb back-trajectories 100 m 500 m 1000 m Page 116 of 173

117 Atascosa Bandera Bastrop Bell Bexar Blanco Burnet Caldwell Comal Coryell Fayette Frio Gillespie Gonzales Guadalupe Harris Hays Karnes Kendall Kerr Lee Llano McMullen Medina Milam Travis Wilson Days Upwind CAPCOG Ozone Conceptual Model 2016 Figure Areas upwind of CAMS 6602 on days with MDA8 >70 ppb back-trajectories m 500 m 1000 m These back-trajectory data highlight three notable features of O 3 transport for the region: 1. The San Antonio-New Braunfels MSA counties appear to be significantly more important as an upwind area for the Austin-Round Rock MSA on high O 3 days from than previous conceptual models indicated; 2. O 3 exceedances at the Fayette County monitoring station appear to have a substantially different set of upwind areas than the O 3 exceedances within the Austin-Round Rock MSA; 3. Within the Austin-Round Rock MSA, Hays County was the county most frequently upwind of CAMS 3 and 38 on days >70 ppb Discussion of Wind Direction Analysis CAPCOG s analysis of surface wind direction vectors and analysis of back-trajectories do not tell the same story of the relative importance of nearby areas as upwind source areas for MDA8 O 3 >70 ppb. The surface wind patterns at CAMS 3, for example, 25% of the morning resultant wind directions came from the WSW, SW, or SSW directions, and 0% of the afternoon resultant wind directions came from those directions. On the other hand, 39% of mornings and 53% of the afternoons when MDA8 was >70 ppb, the resultant wind direction was from the S, SSE, or SE directions. Yet, the back-trajectory analysis shows that Hays County, to the southwest of Travis County, while Bastrop County and Caldwell County, which are more to the south and southeast of Travis County, were upwind on only 14% and 19% of the days when MDA8 O 3 was >70 ppb, respectively. In the back-trajectory analysis in fact, Atascosa, Bexar, and Comal Counties, which are located in the San Antonio-New Braunfels MSA, were upwind of CAMS 3 more frequently than Bastrop, Caldwell, or Williamson Counties were, despite the latter counties being Page 117 of 173

118 within the Austin-Round Rock MSA. A similar picture emerges with analysis of the other monitoring stations and comparison between the surface wind data and the back-trajectories. These differences may suggest that future analysis should include some back-trajectories for each hour of the day included in MDA8 values over 70 ppb in order to assess the extent to which a back-trajectory for the peak 1-hour O 3 concentration hour is able to capture the overall wind patterns for that day and the relative importance of areas as potential upwind sources. Nevertheless, the backtrajectory analysis in this section seems to clearly demonstrate the importance of Hays County and counties in the San Antonio MSA as source regions upwind of the Austin-Round Rock MSA monitors for the region s highest 1-hour O 3 concentrations. 5.6 Air Quality Forecasts TCEQ provides daily air quality forecasts that include detail on the expected Air Quality Index (AQI) level for O 3, and provides O 3 Action Day (OAD) alerts for a given day if it has a high degree of confidence that the O 3 levels on that day will exceed the level of the NAAQS. Understanding the extent to which regional O 3 levels can be accurately and successfully predicted is useful for understanding the extent to which episodic emission reduction measures or efforts to help sensitive populations reduce exposure to ground-level O 3 when high levels do occur. For this analysis, accuracy and success rates are calculated as follows: Accuracy Rate = Success Rate = Number of days when AQI level forecast = AQI level observed Total number of days AQI level was forecast Number of days when AQI level forecast = AQI level observed Total number of days AQI level was observed From , the AQI for MDA8 O 3 was as follows: <60 ppb: Good 60 ppb 75 ppb: Moderate 76 ppb 95 ppb: Unhealthy for Sensitive Groups Therefore, for evaluating the accuracy and success of Ozone Action Day (OAD) alerts, for example, CAPCOG calculated the following: Accuracy Rate = Accuracy Rate = Number of OADs when MDA8 76 ppb Total number of OADs Number of OADs when MDA8 76 ppb Total number of days when MDA8 76 ppb Page 118 of 173

119 Figure Accuracy and success of OAD forecasts % of OADs with MDA8 >= 76 ppb % of Days with MDA8 >=76 ppb when OAD was declared 53% 48% 47% 43% 46% 41% 29% 25% 18% 18% Whereas CAPCOG had records of TCEQ OADs for , CAPCOG only has the detailed daily forecasts from TCEQ dating back to March The figure below shows the percentage of Moderate or worse forecasts for each year and the 3-year average. Figure Accuracy and success of moderate or worse O 3 AQI forecasts % of "Moderate" or Worse O3 Forecast with Actual O3 "Moderate" or Worse % of Actual "Moderate" or Worse O3 Days Forecast as "Moderate" or Worse O3 76% 66% 67% 82% 75% 66% 70% 41% Page 119 of 173

120 5.7 Consolidated Meteorological Factor Analysis This section provides a consolidated analysis of the meteorological factors described above. This includes a regression analysis of the statistical significance of meteorological factors on MDA8 levels when considered jointly, a summary of the meteorological factors that could be considered necessary for high O 3 concentrations (defined either as >70 ppb or 55 ppb), and the frequency of such days each year. These analyses consider avg. WS from 12pm-4pm, avg. temp. from 12pm-4pm, diurnal temp. change, avg. RH from 12pm-4pm, avg. SR from 12pm-4pm, whether the observation was on a Sunday, and year. CAPCOG performed a simple linear regression using Microsoft Excel s data analysis package regression analysis tool. CAPCOG screened the available data such that only days when all variables had data. MDA8 O 3 was defined as the dependent variable, and the following variables were defined as the regression analysis s independent variables: CAMS 3 or CAMS 38 avg. WS 12 pm 4pm (continuous); CAMS 3 or CAMS 38 avg. Temp. 12 pm 4pm (continuous); CAMS 3 or CAMS 38 diurnal Temp. difference 12 pm 4pm (continuous); CAMS 5001 avg. RH 12 pm 4pm (continuous); CAMS 38 SR 12 pm 4pm (continuous); Sunday (binary, Sunday = 1); 2010 (binary, 2010 = 1); 2011 (binary, 2011 = 1); 2012 (binary, 2012 = 1); 2013 (binary, 2013 = 1); 2014 (binary, 2014 = 1). The coefficients for the continuous variables represent the marginal impact of a change in the value of the independent variable on MDA8 O 3 (the change in ppb O 3 per change in mph WS or change in avg. temp., for example). The coefficient for Sunday represents the day of week impact on MDA8 O3 compared to MDA8 O3 Monday Saturday. The coefficients for represents the MDA8 O3 in those years compared to 2015, accounting for all other variables tested. These year-specific variables should capture any unique characteristics of O 3 formation or emissions in each of these years, and should capture trends in emissions over this time. CAPCOG performed regression analyses for CAMS 3 and 38 using these variables. For CAMS 3, there were a total of 2014 daily observations from that included data for all of these parameters, relying on CAMS 5001 RH data and CAMS 38 SR data, with CAMS 38 meteorological data for the remaining parameters. The regression analysis had an adjusted R-square value of The results are summarized below. Page 120 of 173

121 Table CAMS 3 meteorological factor regression results Item Units Coefficient (ppb / unit) P-value Significant at α = 0.05 Significant at α = 0.10 Intercept n/a *10-55 Yes Yes CAMS 3 Avg. WS 12-4pm Mph *10-2 Yes Yes CAMS 3 Avg. Temp. 12-4pm Deg. F *10-21 Yes Yes CAMS 3 Diurnal Temp. Diff Deg. F *10-10 Yes Yes CAMS 5001 Avg. 12-4pm RH % *10-47 Yes Yes CAMS 38 SR 12-4pm Langleys / min *10-1 No No Sunday 1 = Sunday *10-1 No No = E-01 No No = E-01 No No = E-01 No No = E-03 Yes Yes = E-03 Yes Yes For CAMS 38, there were a total of 2,034 daily observations from that included data for all of these parameters, relying on CAMS 38 meteorological data for all parameters except for RH, which used CAMS 5001 data. The regression analysis had an adjusted R-square value of The results are summarized below. Table CAMS 38 meteorological factor regression results Item Units Coefficient (ppb / unit) P-value Significant at α = 0.05 Significant at α = 0.10 Intercept n/a E-55 Yes Yes CAMS 38 Avg. WS 12-4pm Mph E-02 Yes Yes CAMS 38 Avg. Temp. 12-4pm Deg. F E-23 Yes Yes CAMS 38 Diurnal Temp. Diff Deg. F E-11 Yes Yes CAMS 5001 Avg. 12-4pm RH % E-43 Yes Yes CAMS 38 SR 12-4pm Langleys / min E-02 Yes Yes Sunday 1 = Sunday E-02 Yes Yes = E-02 Yes Yes = E-02 No Yes = E-01 No No = E-02 Yes Yes = E-01 No No Some key insights from these analyses include the following: Across these two analyses, there is a very similar intercept level for CAMS 3 and ppb for CAMS 38. Page 121 of 173

122 Avg. WS, avg. temp., diurnal temp. change, and avg. RH were all statistically significant factors at both monitoring stations at α = 0.05 significance level. SR levels at CAMS 38 were statistically significant for CAMS 38 at a α = 0.05 level, but were not for CAMS 3. Sundays were not a statistically significant factor at CAMS 3, but were at CAMS 38. At CAMS 3, 2013 and 2014 had statistically significantly lower MDA8 levels than 2015, once the meteorological factors were controlled for, but levels were not statistically significantly different from 2015 levels. At CAMS 38, 2013 and 2010 had statistically significantly lower MDA8 levels than 2015 at a α = 0.05 significance level, and 2011 also had statistically significantly lower MDA8 levels than 2015 at a α = 0.10 significance level. CAPCOG also reviewed the CAMS 3 and 38 data to determine the frequency of meteorological conditions considered necessary for high MDA8 each year and overall for the period. A summary of these criteria is provided below. Page 122 of 173

123 Table Meteorological conditions considered "necessary" for high MDA8 Parameter Necessary for MDA8 > 70 ppb Necessary for MDA8 55 ppb Avg. WS 12-4 pm mph mph Avg. Temp pm 76.8 deg. F 49.4 deg. F Diurnal Temp. Change 11.8 deg. F 10.3 deg. F Avg. RH 12-4 pm 46.3% 63.5% Avg. SR 12-4 pm 0.87 langleys/min 0.51 langleys/min The figures below show the frequency with which meteorological conditions met these thresholds for for CAMS 3 and 38. Figure CAMS 3 frequency of occurrences of "necessary" conditions for high MDA8 O 3 >70 ppb >=55 ppb 88% 100% 93% 89% 85% 83% 81% 71% 54% 57% 52% 27% 2% 14% CAMS 3 MDA8 O3 CAMS 3 Avg. WS CAMS 3 Avg. Temp. CAMS 3 Diurnal Temp. CAMS 5001 RH CAMS 38 SR All Factors Page 123 of 173

124 Figure CAMS 38 frequency of occurrences of "necessary" conditions for high MDA8 O 3 >70 ppb >=55 ppb 100% 92% 92% 91% 87% 83% 81% 53% 57% 52% 66% 29% 14% 1% CAMS 38 MDA8 O3 CAMS 38 Avg. WS CAMS 38 Avg. Temp. CAMS 38 Diurnal Temp. CAMS 5001 RH CAMS 38 SR All Factors These data indicate that, even in combination, the meteorological factors that may have been necessary for high MDA8 levels from were not sufficient for high MDA8 levels. Page 124 of 173

125 6 Correlations between MDA8 O 3 and Other Criteria Pollutants This section provides analysis of correlations between MDA8 O 3 and other criteria pollutants measured in the region. CAPCOG analyzed each other pollutant based on the averaging time and form of the pollutant s NAAQS. Therefore, CAPCOG analyzed PM hour concentrations, maximum daily 1-hour average (MDA1) NO 2 concentrations, and MDA1 SO 2 concentrations. 6.1 PM 2.5 CAPCOG calculated the average 24-hour PM 2.5 concentrations when the O 3 MDA8 values at the same monitor were > 70 ppb, ppb, and < 55 ppb. There were three monitors that had co-located O 3 and PM 2.5 sampling during this period: CAMS 3, CAMS 38, and CAMS 601. The current PM 2.5 NAAQS include a 24-hour standard of 35 micrograms per cubic meter (µg/m 3 ) and an annual standard of 12.0 µg/m 3. All three of these sites collected PM 2.5 measurements year-round for each of the six years analyzed, and CAMS 3 and 38 also collected O 3 measurements year-round, but CAMS 601 only collected O 3 data during O 3 season. Figure 6-1. Average PM 2.5 v. MDA8 O MDA8 <55 ppb MDA ppb MDA8 >70 ppb Avg. 24-hour PM 2.5 µg/m CAMS 3 CAMS 38 CAMS 601 Table 6-1. CAMS 3 PM 2.5 analysis O 3 MDA8 Count Avg. 24-hr µg/m 3 S.D. µg/m 3 Min µg/m 3 Max µg/m 3 C.I. C.I. Low C.I. High <55 ppb ppb >70 ppb Page 125 of 173

126 Table 6-2. CAMS 38 PM 2.5 analysis Avg. 24-hr S.D. Min Max C.I. C.I. O 3 MDA8 Count µg/m 3 µg/m 3 µg/m 3 µg/m 3 C.I. Low High <55 ppb ppb >70 ppb Table 6-3. CAMS 601 PM 2.5 analysis Avg. 24-hr S.D. Min Max C.I. C.I. O 3 MDA8 Count µg/m 3 µg/m 3 µg/m 3 µg/m 3 C.I. Low High <55 ppb ppb >70 ppb At all three of these monitoring stations, the average 24-hour PM 2.5 concentrations were statistically significantly higher on days when MDA8 O 3 was ppb compared to when MDA8 was <55 ppb, and was statistically significantly higher on days when MDA8 O 3 was >70 ppb compared to when MDA8 was ppb. 6.2 NO 2 This section provides an analysis of the typical maximum daily 1-hour average (MDA1) NO 2 concentrations when MDA8 O 3 was >70 ppb, ppb, and <55 ppb where NO 2 and O 3 analyzers were co-located. The following table shows the availability of NO 2 data by monitoring station and year. Table 6-4. NO 2 data availability by monitoring station and year CAMS CAPCOG analyzed the NO 2 data for each of these stations to determine the average MDA1 NO 2 concentrations within each MDA8 O 3 range, and determined the C.I. for each average. The following figure shows these data for each monitoring station. Page 126 of 173

127 Peak 1-hour NO 2 (ppb) CAPCOG Ozone Conceptual Model 2016 Figure 6-2. Avg. MDA1 NO 2 v. MDA8 O 3 25 MDA8 <55 ppb MDA ppb MDA8 >70 ppb CAMS CAPCOG analyzed the NO 2 data for each of these stations to determine the average MDA1 NO 2 concentrations within each MDA8 O 3 range, and determined the C.I. for each average. The following figure shows these data for each monitoring station. Table 6-5. CAMS 3 NO 2 analysis O 3 MDA8 Count Avg. MDA1 S.D. ppb Min ppb Max ppb C.I. C.I. Low C.I. High NO 2 (ppb) <55 ppb ppb >70 ppb Table 6-6. CAMS 38 NO 2 analysis O 3 MDA8 Count Avg. MDA1 S.D. ppb Min ppb Max ppb C.I. C.I. Low C.I. High NO 2 (ppb) <55 ppb ppb >70 ppb Page 127 of 173

128 Table 6-7. CAMS 601 NO 2 analysis O 3 MDA8 Count Avg. MDA1 NO 2 S.D. ppb Min ppb Max ppb C.I. C.I. Low C.I. High (ppb) <55 ppb ppb >70 ppb n/a n/a n/a n/a Table 6-8. CAMS 614 MDA1 NO 2 v MDA8 O 3 O 3 MDA8 Count Avg. MDA1 S.D. ppb Min ppb Max ppb C.I. C.I. Low C.I. High NO 2 (ppb) <55 ppb ppb >70 ppb Table 6-9. CAMS 690 MDA1 NO 2 v MDA8 O 3 O 3 MDA8 Count Avg. MDA1 NO 2 S.D. ppb Min ppb Max ppb C.I. C.I. Low C.I. High (ppb) <55 ppb ppb >70 ppb n/a n/a n/a n/a Table CAMS 6602 MDA1 NO 2 v MDA8 O 3 O 3 MDA8 Count Avg. MDA1 S.D. ppb Min ppb Max ppb C.I. C.I. Low C.I. High NO 2 (ppb) <55 ppb ppb >70 ppb As the data above show, MDA1 NO 2 concentrations tend to be higher on higher O 3 days, which is expected, given the role of NO X in O 3 formation. Page 128 of 173

129 MDA8 O 3 (ppb) CAPCOG Ozone Conceptual Model SO 2 This section provides an analysis of the typical maximum daily 1-hour average (MDA1) SO 2 concentrations when MDA8 O 3 was >70 ppb, ppb, and <55 ppb where SO 2 and O 3 analyzers were co-located. The following table shows the availability of SO 2 data by monitoring station and year. Table SO 2 Data Availability by Monitoring Station and Year CAMS The following figures show scatter plots of the MDA1 SO 2 compared to MDA8 at each monitoring station with data. Figure 6-3. CAMS 3 MDA1 SO 2 v. MDA8 O 3, y = x R² = MDA1 SO 2 (ppb) Page 129 of 173

130 MDA8 O 3 (ppb) MDA8 O 3 (ppb) CAPCOG Ozone Conceptual Model 2016 Figure 6-4. CAMS 601 MDA1 SO 2 v. MDA8 O 3, y = x R² = MDA1 SO 2 (ppb) Figure 6-5. CAMS 6602 MDA1 SO 2 v. MDA8 O 3, y = x R² = MDA1 SO 2 (ppb) CAPCOG analyzed the SO 2 data for each of these stations to determine the average MDA1 SO 2 concentrations within each MDA8 O 3 range, and determined the C.I. for each average. The following Page 130 of 173

131 MDA1 SO 2 (ppb) CAPCOG Ozone Conceptual Model 2016 figure shows these data for each monitoring station. Higher ambient SO 2 concentrations during high O 3 could be an indication of the influence of industrial sources. Figure 6-6. Average MDA1 SO 2 v. MDA8 O 3 25 MDA8 <55 ppb MDA ppb MDA8 >70 ppb CAMS The following tables show additional details for each monitoring station. Table CAMS 3 SO 2 analysis O 3 MDA8 Count Avg. MDA1 SO 2 (ppb) S.D. ppb Min ppb Max ppb C.I. C.I. Low C.I. High <55 ppb ppb >70 ppb Table CAMS 601 SO 2 analysis O 3 MDA8 Count Avg. MDA1 S.D. ppb Min ppb Max ppb C.I. C.I. Low C.I. High SO 2 (ppb) <55 ppb ppb >70 ppb n/a n/a n/a n/a Page 131 of 173

132 Table CAMS 690 SO 2 analysis O 3 MDA8 Count Avg. MDA1 S.D. ppb Min ppb Max ppb C.I. C.I. Low C.I. High SO 2 (ppb) <55 ppb ppb >70 ppb n/a n/a n/a n/a Table CAMS 6602 SO 2 analysis O 3 MDA8 Count Avg. MDA1 S.D. ppb Min ppb Max ppb C.I. C.I. Low C.I. High SO 2 (ppb) <55 ppb ppb >70 ppb These data show a mixed picture, with the largest data set at CAMS 3 showing statistically significant differences between average MDA1 SO 2 concentrations when MDA8 O 3 was ppb, but not between days when MDA8 O 3 was >70 ppb compared to when MDA8 O 3 was ppb. Page 132 of 173

133 7 Spatial Pattern in Pollutant Levels This section provides a description of the patterns in O 3 formation in the region. It includes an analysis of the difference between high and low O 3 levels measured and modeled in the region, as well as analysis of the extent of elevated O 3 pollution within the region and the variation in O 3 levels near monitoring stations. 7.1 Monitoring Transport Analysis The following table shows the average highest and lowest MDA8 values in the region when the highest measured MDA8 in the CAPCOG region was >70 ppb, ppb and <55 ppb. Using these data, and assuming that the lowest value represents the background for the region, and the difference between the lowest and highest values represent the local contribution, it is possible to estimate the average local contribution to MDA8 values. The following table shows this analysis for the entire CAPCOG region, along with the standard deviation across all monitoring stations. The analysis only uses O 3 data when at least three O3 monitors recorded an MDA8 value. Table 7-1. Avg. high and low MDA8 O 3 when peak CAPCOG MDA8 >70 ppb, ppb, and <55 ppb Regional Peak MDA8 Avg. Highest MDA8 in Region (ppb) Avg. Lowest MDA8 in Region (ppb) Avg. Diff. Between Highest and Lowest MDA8 (ppb) Standard Deviation MDA8 (ppb) Total MDA8 Observations < 55 ppb ppb > 70 ppb TOTAL ,344 CAPCOG also analyzed these data for just the MSA in order to evaluate to what extent these numbers changed when CAMS 601 was excluded. Based on the back-trajectories from CAMS 601, its high O 3 problems seem to be influenced by a different set of upwind areas than the monitors located in the Austin-Round Rock MSA. In particular, the inclusion of dates when O 3 was high at CAMS 601 but low in the MSA could misrepresent the difference between the highest and lowest values measured in the region as a contribution from the region to the Fayette monitoring station s high O 3 levels, even if the rest of the region was not upwind of Fayette County on that day. The CAMS 601 back-trajectories for days when MDA8 O3 was >70 ppb showed very few occasions when counties in the MSA were upwind of CAMS 601 on these days. Page 133 of 173

134 Avg. MDA8 O 3 Contribution (ppb) CAPCOG Ozone Conceptual Model 2016 Table 7-2. Avg. high and low MDA8 O 3 when peak Austin-Round Rock MSA MDA8 >70 ppb, ppb, and <55 ppb Regional Peak MDA8 Avg. Highest MDA8 in Region (ppb) Avg. Lowest MDA8 in Region (ppb) Avg. Diff. Between Highest and Lowest MDA8 (ppb) Standard Deviation MDA8 (ppb) Total MDA8 Obs. < 55 ppb ppb > 70 ppb TOTAL ,333 Compared to the CAPCOG-wide analysis, this average difference between the highest and lowest MDA8 when at least one MDA8 was >70 ppb was 1.5 ppb lower. This analysis shows a background level of about 61 ppb when MDA8 levels exceeded 70 ppb. 7.2 Source Apportionment Data on Local and Non-Local O 3 Contributions The most recent source apportionment modeling data CAPCOG has for the impacts of geographic areas within Texas on Austin-Round Rock MSA O 3 levels is from a 2012 project completed by the University of Texas at Austin (U.T.) based on the June 2006 model that was release in January The following figure shows an overview of the impact of emissions from the Austin-Round Rock MSA, the rest of Texas, the rest of the modeling domain, and initial and boundary conditions on peak O 3 levels in the region. CAPCOG used the top 10 modeled MDA8 values for this analysis. Figure 7-1. June 2006 source apportionment data summary top 10 days Austin-Round Rock MSA Rest of Texas Rest of U.S. Initial and Boundary Conditions CAMS 3 CAMS Report available at: APCA_Analysis_Final.pdf. Page 134 of 173

135 Since this analysis was performed on modeled 2006 O 3 levels, and O 3 precursor emissions and ambient O 3 concentrations were substantially lower between , it is important to note that the local contribution in particular for would be expected to be substantially lower too. These data indicate that extent that O 3 transport from outside the MSA, accounted for about ppb of the region s peak MDA8 O 3 values. These results, therefore, are broadly consistent with the monitoring transport analysis from the previous section, showing a background level of about 59 ppb on days when MDA8 > 70 ppb between Spatial Extent of High O 3 during the June 2012 Episode (v.0) CAPCOG analyzed the MDA8 O 3 modeled for each grid cell in the 4 km x 4 km East Texas domain for the June 2012 episode in order to spatially characterize high O 3 levels in the region. 17 CAPCOG loaded the modeled MDA8 O 3 for each grid cell into ArcGIS and generated a shapefile containing the MDA8 for each day from June 1, 2012 June 29, CAPCOG then determined the top 10 highest MDA8 values modeled for each grid cell during the episode and produced the following maps, showing the highest MDA8 modeled for each grid cell, the average of the top five MDA8 O 3 values modeled for each grid cell, and the average of the top 10 MDA8 O 3 values modeled for each grid cell. The maps include a picture of the entire 4 km x 4 km grid cell domain covering East Texas, as well as a close-up of the CAPCOG region that shows the location and value of the single highest and lowest MDA8 values for each set of criteria. MDA8 values are color-coded in accordance with the new 2015 O 3 NAAQS AQI. The locations of all TCEQ and CAPCOG monitors in the CAPCOG region are show in the close-up maps of the CAPCOG region. As detailed in section 2.3 of this report, this particular modeling platform had an average normalized mean bias of +3.88% for MDA8 O 3 when observed MDA8 O 3 was 60 ppb at CAMS 3, and a normalized mean bias of +5.29% for when observed MDA8 O 3 was 60 ppb at CAMS 38. While there are tools available to adjust modeling results to account for model bias for base case modeling results, given the substantial measurement uncertainty for some of the CAPCOG monitors in June 2012 and the extra levels of complexity these tools entail, CAPCOG believes that directly using the modeling results to create these spatial fields without adjusting for model bias provides an adequate representation of the general spatial extent of elevated O 3 concentrations in the region when they occurred in Due to lack of availability of the modeling data for the June 30 day of the episode, this analysis only covers June 1 June 29, MDA8 values in the CAPCOG region ranged from ppb on that day. Statewide, June 30 was only among the top 10 days for the month of June at 13% of monitoring locations, no monitoring station recorded an MDA8 >70 ppb, and only 9 recorded MDA8 values ppb. Page 135 of 173

136 Figure 7-2. Highest MDA8 values modeled for each grid cell in the June 2012v.0 base case episode E. Texas Page 136 of 173

137 Figure 7-3. Highest MDA8 values modeled for each grid cell in the June 2012v.0 base case episode CAPCOG Page 137 of 173

138 Figure 7-4. Average of five highest MDA8 values modeled for each grid cell in the June 2012v.0 base case episode E. Texas Page 138 of 173

139 Figure 7-5. Average of five highest MDA8 values modeled for each grid cell in the June 2012v.0 base case episode CAPCOG Page 139 of 173

140 Figure 7-6. Average of ten highest MDA8 values modeled for each grid cell in the June 2012v.0 base case episode E. Texas Page 140 of 173

141 Figure 7-7. Average of ten highest MDA8 values modeled for each grid cell in the June 2012v.0 base case episode - CAPCOG Page 141 of 173

142 Table 7-3. Highest Top 10 MDA8 values modeled by geographic area for any 4 km x 4 km cell, June 2012 v.0 Area Bastrop County Blanco County Burnet County Caldwell County Fayette County Hays County Lee County Llano County Travis County Williamson County Austin-Round Rock MSA CAPCOG Region 1 st High 2 nd High 3 rd High 4 th High 5 th High 6 th High 7 th High 8 th High 9 th High 10 th High Avg. top 5 Avg. top Page 142 of 173

143 Table 7-4. Lowest top 10 MDA8 values modeled by geographic area for any 4 km x 4 km cell, June 2012 v.0 Area Bastrop County Blanco County Burnet County Caldwell County Fayette County Hays County Lee County Llano County Travis County Williamson County Austin-Round Rock MSA CAPCOG Region 1 st High 2 nd High 3 rd High 4 th High 5 th High 6 th High 7 th High 8 th High 9 th High 10 th High Avg. top 5 Avg. top Page 143 of 173

144 Table 7-5. Differences in County maximum and minimum MDA8 values of top 10 modeled O 3 concentrations by geographic area, June 2012 v.0 Area Bastrop County Blanco County Burnet County Caldwell County Fayette County Hays County Lee County Llano County Travis County Williamson County Austin-Round Rock MSA CAPCOG Region 1 st High 2 nd High 3 rd High 4 th High 5 th High 6 th High 7 th High 8 th High 9 th High 10 th High Avg. top 5 Avg. top Page 144 of 173

145 Table 7-6. Average MDA8 values of top 10 modeled O 3 concentrations by geographic area, June 2012 v.0 Area Bastrop County Blanco County Burnet County Caldwell County Fayette County Hays County Lee County Llano County Travis County Williamson County Austin-Round Rock MSA CAPCOG Region 1 st High 2 nd High 3 rd High 4 th High 5 th High 6 th High 7 th High 8 th High 9 th High 10 th High Avg. top 5 Avg. top Page 145 of 173

146 Percentage of Grid Cells with MDA8 >70 ppb CAPCOG Ozone Conceptual Model 2016 Figure 7-8. Percentage of grid cells in region with modeled MDA8 > 70 ppb Bastrop County Blanco County Burnet County Caldwell County Fayette County Hays County Lee County Llano County Travis County Williamson County Austin-Round Rock MSA CAPCOG Region 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 1st High 2nd High 3rd High 4th High 5th High 6th High 7th High 8th High 9th High 10th High Avg. top 5 Avg. top 10 Rank of Modeled MDA8 Page 146 of 173

147 MDA8 O 3 (ppb) 7.4 Variation in High O 3 Levels within 3 x 3 Grid Cell Arrays for Extended 2012 Episode (v.1) EPA s modeling guidance recommends using the maximum modeled MDA8 O 3 concentrations in the 3 x 3 grid cell array around the cell containing a monitoring location in order to calculate relative response factors (RRF) when modeling future design values. However, EPA also suggests that the use the cell with the monitoring station located in it could also provide a valid method of projecting a future design value. Therefore, understanding the extent to which modeled MDA8 O 3 varies within a 3 x 3 grid cell array can be helpful in understanding the extent to which the choice of a basis for calculating the RRF could influence a projected design value calculation. The first part of such an analysis would involve evaluating the difference in the modeled base case concentrations. This analysis also helps establish to what extent a monitor is measuring the highest MDA8 O 3 concentration in its immediate vicinity. CAPCOG analyzed the variation in MDA8 O 3 values within the 3 x 3 array of 4 km x 4 km grid cells around each monitoring station in the CAPCOG region that reported to LEADS during the 2012 O 3 season modeled by TCEQ (May 1, 2012 September 30, 2012). The following figure shows average modeled MDA8 values for the grid cell containing a monitoring station when modeled MDA8 values were <55 ppb, ppb, and >70 ppb, as well as the average maximum and minimum MDA8 values modeled for the 3 x 3 array around those monitors. Figure 7-9. Average modeled MDA8 for grid cell and 3x3 cell array max and min for 2012 extended episode <55 Cell Modeled MDA Cell Modeled MDA8 >70 Cell Modeled MDA CAMS The following figure shows the differences between the highest MDA8 modeled within the 3 x 3 array around each monitor and the MDA8 modeled for the grid cell containing the monitor on the top 10 modeled MDA8 values at each station. Page 147 of 173

148 Difference in MDA8 O 3 (ppb) CAPCOG Ozone Conceptual Model 2016 Figure Average differences in modeled MDA8 between monitor and 3x3 cell array max, top 10 days, extended 2012 episode 1st High 2nd High 3rd High 4th High 5th High 6th High 7th High 8th High 9th High 10th High Avg. 10 Highest CAMS As the figure shows, the modeled MDA8 O 3 at CAMS 3 was, on average 3.4 ppb lower than the peak MDA8 modeled within the 3 x 3 grid cell array around CAMS 3 on the top 10 days modeled for the extended 2012 episode, with differences ranging from ppb. This translates into the average peak within the 3 x 3 grid being an average of 5% higher than modeled MDA8 O 3 at CAMS 3, ranging from 2% to 11% higher among the top 10 days. This analysis suggests that the highest MDA8 O 3 concentration in the 3 x 3 grid cell array around CAMS 3 could be as high as 71 ppb if the measured MDA8 O 3 at CAMS 3 was ppb. 8 Relationships between Emissions and Regional O 3 Levels This section includes analyses of relationships between emissions and MDA8 O 3 levels. This section includes analysis of the relative contributions of NO X emissions to VOC emissions, source categories, and source regions to high O 3 levels in the CAPCOG region, as well as trends in emissions and O 3 design values. 8.1 Relative Contributions to Travis County 2017 Modeled Design Value CAPCOG analyzed two sets of source apportionment modeling data for 2017 in order to compare the estimated contributions of Texas anthropogenic emissions, non-texas anthropogenic emissions in the lower 48 states, biogenic emissions, and initial and boundary modeling conditions: Page 148 of 173

149 EPA s 2011v source apportionment modeling data for interstate transport analysis for the 2008 O 3 NAAQS 18, and TCEQ s 2017 source apportionment modeling using the May 31 July 2, 2006, and August 13 September 15, 2006, base case. 19 As described in the Technical Support Document for EPA s 2008 O 3 NAAQS Transport Modeling, EPA calculated Relative Contribution Factors for each source based on the average contributions to the top five 2017 MDA8 concentration days modeled for a monitoring station. 20 In order to provide a direct comparison between the two 2017 source apportionment analyses, CAPCOG calculated the average contributions for the top 5 days modeled for 2017 using the TCEQ s 2006 base case as well. TCEQ s modeling does not provide a break-out of fire emissions, whereas EPA s 2011v6.2 platform did. The relative contributions for each model are shown below. Figure 8-1. Projected contribution of Texas and non-texas anthropogenic emissions to 2017 CAMS 3 design values (ppb) EPA 2011v6.2 TCEQ 2006 Base Case (March 2016 release) 40% 41% 31% 33% 22% 16% 7% 6% 4% Initial & Boundary Conditions Texas Anthropogenic Non-Texas Anthropogenic Biogenic Fires 18 Last accessed 8/24/ This data was obtained from TCEQ on April 1, 2016, and was based on data for CAMS 3. Files used for this section included sa camx620apca_cb6r2.tx.fy17_06jun.c0j.2006_5layer_ysu_wsm6_3dsfc1h_fddats_gq_sfc_0.tx_4km.an WC.8h_cellvalu.csv.gz and sa camx620apca_cb6r2.tx.fy17_06aqs1.c0j.2006_5layer_ysu_wsm6_3dsfc1h_fddats_gq_sfc_0.tx_4km.a NWC.8h_cellvalu.csv.gz. These data are no longer available on TCEQ s FTP site. In order to obtain these files, please contact TCEQ at amda@tceq.texas.gov last accessed 8/24/2016. See page 19. Page 149 of 173

150 Ratio NO X contribution / VOC contribution CAPCOG Ozone Conceptual Model 2016 As the figure shows, anthropogenic emissions account for 48% of the modeled design value contribution in EPA s 2011v6.2 model 2017 projection, and 63% of the modeled design value contribution in TCEQ s projection. Of the share of anthropogenic shares of modeled 2017 design values, 67% of the contribution is from Texas in EPA s modeling and 65% are from Texas in TCEQ s modeling. 8.2 Relative Contribution of Anthropogenic NO X and VOC Emissions Using the detailed anthropogenic precursor culpability assessment (APCA) data available from TCEQ using the 2006 base case, CAPCOG calculated the relative contributions of anthropogenic NO X emissions and anthropogenic VOC emissions to MDA8 O 3 at each monitoring station from Texas and non-texas sources. These data reflect the top 5 modeled MDA8 values for each monitoring station. Figure 8-2. Ratio of anthropogenic NO X contribution to anthropogenic VOC contribution TCEQ 2017 APCA, top 5 modeled MDA8 O 3 values (March 2016 release) TX Non-TX CAMS As the figure shows, anthropogenic NO X emissions from Texas and elsewhere in the country contribute anywhere from 15 to 60 times more to peak O 3 levels in the region than anthropogenic emissions from those areas. 8.3 Sensitivity to Local NO X and VOC Emission Reductions Modeling conducted by U.T. for CAPCOG in 2012 included sensitivity modeling runs for the June 2006 (May 31 July 2, 2006) base case that tested the sensitivity of modeled O 3 levels at CAMS 3, CAMS 38, and the average modeled O 3 levels across all of Travis County to 25% and 50% across-the-board Page 150 of 173

151 reductions in anthropogenic NO X and VOC emissions within the Austin-Round Rock MSA. 21 Using the top 5 and top 10 modeled MDA8 values for each geographic area and the tons per day of NO X and VOC emission reductions, CAPCOG calculated sensitivity ratios in terms of the ppb change in MDA8 values relative to a tpd change in NO X and VOC emissions. CAPCOG calculated these ratios for both the top 5 modeled MDA8 values and the top 10 modeled MDA8 values for each area. The results are shown below. Figure 8-3. Sensitivity of MDA8 O 3 to Austin-Round Rock MSA NO X and VOC Emissions (ppb/tpd) June 2006 episode (Jan release) CAMS 3 CAMS 38 Travis County NOX-Top 10 Days NOX-Top 5 Days VOC-Top 10 Days VOC-Top 5 Days Next, CAPCOG compared the ratio of NO X -sensitivity to VOC-sensitivity for each area, as shown below Page 151 of 173

152 NO X Sensitivity / VOC Sensitivity CAPCOG Ozone Conceptual Model 2016 Figure 8-4. Relative sensitivity of MDA8 O 3 to Austin-Round Rock MSA NO X and VOC emissions (NO X /VOC) June 2006 episode (Jan release) CAMS 3 CAMS 38 Travis County Top 10 Days Top 5 Days The average ratio of NO X sensitivity to VOC sensitivity was , depending on the location and # of days included in the average. This means that a tpd of local NO X emission reductions would be expected to have approximately times the impact of a tpd of local VOC emission reductions. 8.4 Sensitivity to NO X Emissions Reductions by Source Region CAPCOG used the 2017 APCA modeling performed by EPA using the 2011v6.2 modeling platform in order to estimate the sensitivity of the projected design values to anthropogenic O 3 season NO X emissions in each state and offshore areas. In order to calculate these sensitivities, CAPCOG used the modeled contributions EPA developed for the 2008 O 3 NAAQS transport modeling. 22 CAPCOG divided the average contribution of anthropogenic emissions from each area to CAMS 3 and 38 by the average ozone season day (OSD) NO X emissions for that geography. 23 While this method does not account for anthropogenic VOC contributions, other modeling analyses for the area have shown that anthropogenic VOC emissions do not contribute significantly to peak O 3 levels. Since there is a non-linear response of MDA8 O 3 to anthropogenic NO X emissions, this figure represents the average O 3 contribution per tpd of NO X emissions, not the marginal change in O 3 concentrations that would be expected from a reduction in 1 tpd of NO X emissions from the expected 2017 emissions OSD NOX emissions calculated using data from ftp://ftp.epa.gov/emisinventory/2011v6/v2platform/reports/2017eh_cb6v2_v6_11g_state_sector_totals.xlsx, for the May September period. Biogenic emissions, prescribed fires, and wildfires were excluded from each state s totals. Page 152 of 173

153 Figure 8-5. Approximate sensitivities of 2017 O 3 design values to anthropogenic NO X emissions by geography O 3 ppb per tpd NO X CAMS 3 CAMS Sensitivity to NO X Emissions by Time of Day While CAPCOG has not conducted sensitivity modeling to the impact of emission reductions by time of day, AACOG did complete such modeling for the San Antonio area in The following figure shows the modeled impact on the San Antonio s 2018 design value from removal of 1 tpd of on-road NO X emissions by hour. Table 4-5 of the report details the photochemical modeling inputs AACOG used to adjust each hour s on-road NO X emissions for each day type Section 4.4 Page 153 of 173

154 Change in 2018 Design Value (ppb) CAPCOG Ozone Conceptual Model 2016 Figure 8-6. AACOG modeled Impact of a 1 tpd reduction in on-road emissions on 2018 design values CAMS 58 CAMS While these data are not directly representative of conditions in the Austin-Round Rock MSA, they strongly suggest that peak O 3 concentrations that would affect the area s design value are significantly more influenced by NO X emissions that occur between 9 am and 11 am than in the 2-3 hours before or after Emissions Estimates EPA s 2011v6.2 modeling platform groups its anthropogenic NO X and VOC emissions estimates into the following categories: 25 ptegu = non-peaking point source EGUs from the 2011NEIv2; pt_oilgas = point sources that include oil and gas production emissions from the 2011NEIv2; ptnonipm = all 2011NEIv2 point sources not included in ptegu or pt_oilgas, including aircraft emissions and some rail yard emissions; agfire = 2011NEIv2 agricultural fires; c1c2rail = locomotives and category 1 (C1) and category 2 (C2) commercial marine vessel (CMV) emission sources from the 2011NEIv2; c3marine = category 3 (C3) CMV emissions from the 2011NEv2; np_oilgas = 2011NEIv2 nonpoint sources from oil and gas production; nonpt = 2011NEIv2 nonpoint sources not included in other sectors; rw = residential wood combustion; 25 Page 154 of 173

155 nonroad = 2011NEIv2 nonroad equipment emissions; and onroad = 2011 onroad emissions. The following figure shows the percentages of 2011 annual NO X emissions in each sector among the lower 48 states, Texas, CAPCOG, and the Austin-Round Rock MSA. 26 Figure OSD anthropogenic NO X emissions by sector and geography Lower 48 States Texas CAPCOG Austin-Round Rock MSA 70% 60% 50% 40% 30% 20% 10% 0% The following figure shows the percentages of annual VOC emissions in each sector among the lower 48 states, Texas, CAPCOG, and the Austin-Round Rock MSA ftp://ftp.epa.gov/emisinventory/2011v6/v2platform/reports/2011eh%202025eh%20county%20sector%20compari son%20nox.xlsx 27 ftp://ftp.epa.gov/emisinventory/2011v6/v2platform/reports/2011eh%202025eh%20county%20sector%20compari son%20voc.xlsx. Page 155 of 173

156 Figure OSD anthropogenic VOC emissions by sector and geography 60% Lower 48 States Texas CAPCOG Austin-Round Rock MSA 50% 40% 30% 20% 10% 0% The following table shows the annual and average OSD NO X and VOC emissions estimates for all 10 counties in the CAPCOG region using the 2011v6.2 data, as well as the totals for the Austin-Round Rock MSA and the entire region. The OSD estimates represent average emissions for any given day from May 1 September 30, 2011, rather than an OSD weekday estimate. Table NO X and VOC emissions by county Area 2011 NO X 2011 OSD NO X 2011 VOC 2011 OSD VOC (tpy) (tpd) (tpy) (tpd) Bastrop County 3, , Blanco County Burnet County 1, , Caldwell County 2, , Fayette County 10, , Hays County 7, , Lee County 1, , Llano County Travis County 19, , Williamson County 9, , Austin-Round Rock MSA 43, , CAPCOG Region 57, , Page 156 of 173

157 Emissions Estimates This section summarizes the NO X and VOC emissions estimates for each county in the CAPCOG region based on data TCEQ submitted to the EPA for the 2014 NEI. EPA has not yet made the 2014 NEI data publicly available, and for mobile sources, the 2014 NEI estimates will be based on the activity data that the states submit, rather than the actual emissions estimates. These emissions estimates were summarized and analyzed in a report produced by CAPCOG earlier in The following table includes both annual and OSD Weekday (Monday-Friday) emissions estimates (unlike the 2011 OSD estimates presented in the previous section, which includes Saturday and Sunday estimates in the average OSD estimates). Table NO X and VOC emissions by county Area 2014 NO X (tpy) 2014 OSD Weekday NO X (tpd) 2014 VOC (tpy) 2014 OSD Weekday VOC (tpd) Bastrop County 2, , Blanco County Burnet County 1, , Caldwell County 1, , Fayette County 9, , Hays County 5, , Lee County 1, , Llano County Travis County 14, , Williamson County 5, , Austin-Round Rock MSA 30, , CAPCOG Region 43, , Using the sensitivity ratios calculated earlier, the tpd of NO X emissions would be expected to contribute about 7.0 ppb to the region s design value and the 2014 VOC emissions would be expected to contribute about 0.2 ppb to the region s design value. This is broadly consistent with the region having a ppb background design value before anthropogenic emissions from within the region are considered. 8.8 Comparison of CAPCOG-Region NO X Emissions by Sector, 2011, 2014, and 2017 The following figure shows the annual NO X emissions estimates for the CAPCOG region by sector for 2011, 2014, and The 2011 and 2017 estimates are from EPA s 2011v6.2 modeling platform. The 2014 estimates are from the emissions estimates TCEQ submitted to EPA for the 2014 NEI. These data are detailed in a report prepared by CAPCOG in early For the 2011, 2017, and 2025 estimates, the following sectors are grouped together for the figure below: 28 m_report_final.pdf Page 157 of 173

158 Annual NO X Emissions (tpy) CAPCOG Ozone Conceptual Model 2016 Point = ptegu + ptnonipm + pt_oilgas Area = agfire + nonpt + np_oilgas + rwc Non-Road = c1c2rail + nonroad + c3marine On-Road = onroad + onroad_ca_adj For the 2014 NEI data presented below, Non-Road includes emissions estimates from the Texas NONROAD (TexN) model, locomotives, and oil and gas drill rigs. Since EPA models airports as point sources, these non-road sources are grouped with ptnonipm sources in the 2011v6.2 model files. For comparability, CAPCOG moved the 2014 NEI aviation emissions sources from the Non-Road sector into the Point sector in the figure below. The overall NO X emissions estimate for 2014 was 881 tpy. Figure 8-9. CAPCOG region NO X emissions by sector and year, 2011, 2014, 2017, and 2025 (tpy) 35, ,000 25,000 20,000 15,000 10,000 5,000 0 Point Area On-Road Non-Road As the figure above shows, on-road sources were the most important sector of NO X emissions within the CAPCOG region in 2011 and 2014, followed by point sources, non-road sources, and area sources. Mobile sources (on-road plus non-road) are still projected to make up a majority of the NO X emissions in the region in 2017, but are projected to make up less than half of the region s NO X emissions by 2025 due to continuing mobile source emission reductions due to federal engine and fuel standards and fleet turnover. 8.9 Projected Changes in NO X and VOC Emissions, The following figure shows the projected changes in NO X and VOC emissions in the lower 48 states, offshore, in Texas, in the CAPCOG region, and in the Austin-Round Rock MSA between 2011 and Page 158 of 173

159 Figure Projected change in annual NO X and VOC emissions by geography, % Lower 48 States Offshore Texas CAPCOG Austin-Round Rock MSA 20% 10% 0% -10% NOX VOC -20% -30% -40% As the figure shows, there are steep reductions in NO X emissions expected for all geographies, with especially steep emission reductions expected for the Austin-Round Rock MSA for this period. The picture is not as clear with VOC emissions, with Texas s VOC emissions projected to increase between due to oil and gas production, but projected to decrease to varying degrees at the national and local/regional level. Due to reductions in the price of oil, growth in oil and gas production has also slowed significantly, so projections for this sector may not be reliable any longer. CAPCOG also analyzed the NO X emissions data sector-by-sector, as shown below. Page 159 of 173

160 2017 NO X Emissions Relative to 2011 CAPCOG Ozone Conceptual Model 2016 Figure Projected change in annual NO X emissions by region and source type, % 40% 20% 0% Lower 48 States Texas CAPCOG Austin-Round Rock MSA -20% -40% -60% The reductions in mobile source emissions, and to a lesser extent EGUs account for the steep reduction in NO X emissions over this time frame. Increases in NO X emissions are only projected in the nonpoint, and non-egu point source categories Comparison of Trends in NO X Emissions and Peak O 3 Levels The following figure shows the projected trends in Travis County s modeled O 3 design value compared to trends in annual NO X emissions in Travis County, the Austin-Round Rock MSA, the state, and the lower 48 states between 2011 and These data are based on EPA s 2011v6.2 modeling platform and 2017 emissions: ftp://ftp.epa.gov/emisinventory/2011v6/v2platform/reports/2011ed_2018ed_2011eh_2017eh_cou nty_annual_totals.xlsx Baseline and 2017 O 3 design values: emissions: ftp://ftp.epa.gov/emisinventory/2011v6/v2platform/reports/2011eh%202025eh%20county%20sect or%20comparison%20nox.xlsx design values: &disposition=attachment&contentType=excel12book (docket folder for 2015 O 3 NAAQS RIA, Copy of Docket data final RIA v2 Page 160 of 173

161 Design Value as % of 2015 O 3 NAAQS 2,011 2,012 2,013 2,014 2,015 2,016 2,017 2,018 2,019 2,020 2,021 2,022 2,023 2,024 2,025 Value Relative to 2011 Base CAPCOG Ozone Conceptual Model 2016 Figure Trends in NO X emissions and Travis County O 3 design value Travis County Design Value Travis County NOX Austin-Round Rock NOX CAPCOG NOX Texas NOX U.S. Lower 48 NOX 0.00 The following figure shows a comparison of the official O 3 design values at CAMS 3 and CAMS 38 for , as well as the projected 2017 and 2025 design values, divided by the level of the 2015 O 3 NAAQS. As the figure shows, both monitoring stations are projected have design values that will continue to decline from Figure Travis County O 3 design values compared to 2015 O 3 NAAQS 110% CAMS 3 CAMS % 100% 95% 90% 85% 80% Page 161 of 173

162 Percentile (compared to national data) CAPCOG Ozone Conceptual Model 2016 While both monitoring station s design values are projected to decline over this period, the design values across the rest of the country are projected to experience a sharper decline over this time period, leading the design value for CAMS 3 to be higher than approximately 70% of the rest of the monitoring stations in the country in 2017 and higher than about 80% of the rest of the monitoring stations in the country by 2025, compared to about 65% of the country in Figure Travis County O 3 design value percentiles compared to all U.S. monitoring stations CAMS 3 CAMS % 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Similarly, while Travis County s design value is projected to decline somewhat faster than the highest design value in the country between 2015 and 2017, the highest design values are projected to decline significantly more sharply between 2017 and 2025 than the Travis County design value, as the figure below shows. Page 162 of 173

163 Percentile (compared to national data) CAPCOG Ozone Conceptual Model 2016 Figure Travis County O 3 design values compared to maximum U.S. design value CAMS 3 CAMS % 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 8.11 Local Emission Controls There are a number of local emission reduction controls that help reduce the CAPCOG region s contribution to high O 3 formation. These include: 29 A vehicle emissions inspection and maintenance (I/M) program in Travis and Williamson Counties the two largest counties in the country to have an I/M program that have never been designated nonattainment. CAPCOG estimates that this program achieved about tpd of NO X reductions in 2015, accounting for about a ppb reduction in peak O 3 levels. This program has been in place since 2005, and achieves approximately a 12% reduction in NOX and VOC emissions from gasoline-powered vehicles. Emission reduction grants offered through the Texas Emission Reduction Plan (TERP) program that accelerate the benefits of more stringent federal engine standards and fleet turnover, including the Diesel Emission Reduction Incentive (DERI) grants (estimated to be achieving about a 2.87 tpd reduction in NO X in the Austin-Round Rock MSA in 2015), the Texas Clean Fleet Program (TCFP) grants (estimated to be achieving a 0.10 tpd NO X reduction in the Austin-Round Rock MSA in 2015), and the Texas Natural Gas Vehicle Grant Program (TNGVGP) grants (0 tpd NOX reductions in 2015, but 0.05 tpd NO X reductions expected for ). CAPCOG estimates that these programs achieved approximately a 0.3 ppb reduction in peak O 3 levels. 29 For more information, see CAPCOG s 2015 annual air quality report at: Page 163 of 173

164 TERP grants have been awarded since All five counties in the Austin-Round Rock MSA are eligible to receive TERP grants. A voluntary NO X reduction program at Texas Lehigh Cement Company on predicted high O 3 days, which accounts for approximately ppb in peak O 3 reductions, with impacts as high as ppb at CAMS 3 and 38. This program was implemented in 2009, was resumed in 2013, and remains in practice. Texas Lehigh is located in Buda in Hays County. Heavy-duty vehicle idling restrictions implemented by Travis County and the cities of Austin, Bastrop, Elgin, Georgetown, Lockhart, Round Rock, and San Marcos. Of these jurisdictions, Travis County, Austin, and Georgetown have a memorandum of agreement (MOA) with the TCEQ to implement the state s locally enforced idling restrictions, while Bastrop, Elgin, Lockhart, Round Rock, and San Marcos rely instead on their general authority as home-rule cities to implement these restrictions through city code. These restrictions have been in place for some time, and, up through the end of 2013, were also in place county-wide in Bastrop, Caldwell, Hays, and Williamson Counties. While these restrictions have been on the books, there has been very little actual enforcement action taken, and it is unclear how much of an emission reduction benefit these restrictions are having for the region. The Drive a Clean Machine (DACM) program, which helps accelerate the replacement of older personal vehicles and helps improve compliance with the I/M program. CAPCOG has estimated that this program achieves about a 0.01 tpd reduction in NO X emissions. This program is linked to the I/M program, and only Travis and Williamson Counties participate. Voluntarily implemented NO X controls at power plants operated by Austin Energy, the Lower Colorado River Authority (LCRA), and the University of Texas at Austin (UT) in the 2000s. State rules lowering the applicability levels for Stage I vapor control requirements for gasoline service stations 25,000 gallons per month, compared to the 100,000 gallon per month nationwide standard set by EPA. These rules apply to all five counties in the Austin-Round Rock MSA. Although there haven t been any recent estimates of the emission reductions from this rule, it is likely at least a few tpd of VOC emission reductions, based on the estimates used in the Austin-Round Rock MSA Early Action Compact (EAC) State Implementation Plan (SIP). State rules restricting the use of cutback asphalt in all five counties in the Austin-Round Rock MSA. Due to the increased nationwide substitution of emulsified asphalt for cutback asphalt, this control is not likely achieving substantial reductions in VOC emissions any longer. State rules restricting degreasing activities, which are likely achieving several tpd of VOC reductions. An array of other emission reductions implemented by members of the Central Texas Clean Air Coalition and organizations participating in the Clean Air Partners Program managed by the CLEAN AIR Force of Central Texas. Page 164 of 173

165 9 Conclusion and Recommendations This O 3 Conceptual Model provides a State of the Knowledge regarding the influence of emissions, meteorology, transport, and other processes on O 3 pollution within the region. Unlike previous Conceptual Models CAPCOG has developed, which focused only on the five counties in the Austin-Round Rock MSA, this Conceptual Model covers all 10 counties in the CAPCOG region. This Conceptual Model also brings a much closer focus on more recent air pollution data by limiting the analysis to , whereas the previous two Conceptual Models developed by CAPCOG in 2015 and 2012 included O 3 observations as far back as By including these years, CAPCOG is covering two full three-year averaging periods used in design value calculations and both of which include a periodic emissions inventory (PEI) year in the middle years. This period also includes both the 2011 and 2012 ozone seasons, which have been developed by EPA and TCEQ, respectively, as photochemical modeling platforms. The sharp declines in emissions even within the three-year period from 2011 to 2014 shows up clearly in the region s O 3 levels, with the average number of days with MDA8 >70 ppb in the region declining by 47% between and Whereas in the first half of this period, significant portions of the region had O 3 concentrations that exceed the new 2015 O 3 NAAQS, the monitoring data for suggests that all areas of the region have O 3 concentrations that are attaining this new NAAQS, and that O 3 levels are well below the levels that EPA believes are necessary to attain for protection of vegetation and ecosystems. Nevertheless, as the 2015 O 3 season demonstrated, having O 3 levels that meet the NAAQS does not necessarily mean that the region can t still experience several days a year when O 3 levels are considered unhealthy for sensitive groups. Whereas the region s fourth-highest MDA8 values did not vary much between 2010 and 2012, they varied substantially between 2013 and At CAMS 3, the standard deviation among the three MDA8 values included in the design value was 0.6 ppb, while it was 5.6 ppb for At CAMS 38, the standard deviation for was 3.0 ppb, while for , it was 5.1 ppb. A typical high O 3 day when MDA8 was >70 ppb in the CAPCOG region had the following characteristics: There appear to be some statistically significant differences in the conditions associated with high O 3 days in the Austin-Round Rock MSA compared to high O 3 days in Fayette County; High O 3 occurred as early as March and as late as October; High O 3 most frequently occurred between August and October; High O 3 was least likely to occur on Sundays in the MSA, and most likely to occur on Saturdays in Fayette County; Start hours for MDA8 were as early as 9 am and as late as 1 pm within the MSA, with a much wider range of times for Fayette County; High O 3 was associated with low afternoon wind speeds, usually around 7 mph or less; High O 3 was associated with high afternoon temperatures, usually 90 degrees or higher; High O 3 was associated with large diurnal changes in temperature, usually more than 20 degrees; Page 165 of 173

166 High O 3 was associated with low afternoon humidity, usually less than 30%; and High O3 was associated with high afternoon solar radiation, usually over 1.10 langleys/second. High O 3 days also typically coincide with higher PM 2.5, NO 2, and SO 2 concentrations. This is especially relevant for PM 2.5, since a significant portion of days when O 3 is high are also days when PM 2.5 concentrations are considered Moderate based on the AQI. Typically, interstate and intrastate transport each contribute more to peak O 3 concentrations than emissions from within the region do, bringing the region s background O 3 concentrations to approximately ppb on high ozone days. However, local emissions are what push the region s O 3 levels over 70 ppb on the few times a year when that occurs, with local emissions contributing ppb on a typical day when MDA8 O 3 was >70 ppb from The region s O 3 concentrations are much more heavily influenced by NO X emissions than VOC emissions, with anthropogenic NO X emissions contributing anywhere from times more to MDA8 O 3 than anthropogenic VOC emissions. Mobile sources make up a large majority of these NO X emissions, and federal engine controls have resulted in substantial declines in emissions even within the six years covered by this conceptual model. Additional local efforts have helped further control O 3 concentrations, and may have been enough to make the difference in the region s ability to avoid nonattainment designations for the 2008 O 3 NAAQS and possibly avoiding a nonattainment designation for the 2015 O 3 NAAQS. Given the large changes in emissions that are projected to occur between 2014 and 2017 and beyond, recommendations for future work are focused on ensuring that characterizations of air quality remain current. More frequent, smaller annual analyses of the prior O 3 season along the lines of the 2016 data analysis included in CAPCOG s work plan may be more useful most of the time than larger, multi-year conceptual models. The next multi-year conceptual model should be developed until 2019 or 2020 in order to account for the 2017 NEI and the significant emission reductions expected in 2017 from implementation of the Tier 3 fuel and vehicle standards and the 2008 O 3 CSAPR Update EGU emission reductions. Future wind direction analyses should take hour-by-hour analyses of surface wind directions and back-trajectories on high O 3 days. As O 3 concentrations continue to decline in the region, using lower O 3 thresholds for high O 3 for these analyses may prove more relevant for future planning purposes. As emissions from mobile sources continue to decrease, the relative efficacy of controls focused on reducing mobile source activity will also significantly decrease. Similarly, as EGUs become cleaner and cleaner, energy efficiency and renewable energy programs will have less of an air quality benefit. Non-EGU stationary sources, both point sources and non-point sources, will increasingly become important parts of the emissions inventory as these other sectors emissions decline. Page 166 of 173

167 Legacy vehicles, non-road equipment, and power plants continue to have a disproportionately large impact on regional air pollution compared to their share of energy output, and efforts to retire and replace this older, dirtier fleet of equipment with newer, cleaner equipment will continue to be the most important strategy for the region to improve air quality. Page 167 of 173

168 10 Appendix A: Explanation of Data Quality Concerns 10.1 CAMS O 3 Data CAPCOG has had to move the physical location of the sampling equipment at CAMS 6602 twice during this period once following the 2013 O 3 season, and another time after the 2014 O 3 season. The aerial imagery shown below indicates the location of the equipment from , in 2014, and in 2015 (its current location). Figure Overview of CAMS 6602 monitoring locations Based on comparisons to other stations in the region in 2014, CAPCOG and our contractor believed that the O 3 readings at CAMS 6602 were too low. After multiple calibrations and co-located sampling, CAPCOG and our contractors concluded that the issue was the siting of the equipment in 2014 elevated higher, with an inlet close enough to trees that they could have interfered with the sampling. The figure below shows the percentage of sampling days in each year from when MDA8 at CAMS 6602 was the region s highest, the region s lowest, or in between. As the figure shows, the vast majority of days in and 2015, CAMS 6602 had MDA8 values between the region s maximum and minimum values, with small percentages of days when the site recorded the region s highest or lowest MDA8 value. In 2014, however, the vast majority of days show CAMS 6602 recording the region s lowest MDA8 values. Likewise, CAMS 6602 s MDA8 values averaged ppb higher than the regionwide minimum excluding CAMS 6602, whereas it averaged 8.0 ppb below the region-wide minimum excluding CAMS 6602 in Page 168 of 173