Emissions Trend Analysis for the San Antonio-New Braunfels MSA: 1999, 2002, 2006, 2012, 2018, 2020, and 2023

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1 FY FY 2015 UPWP 3.3 MPO ALAMO AREA METROPOLITAN PLANNING ORGANIZATION Emissions Trend Analysis for the San Antonio-New Braunfels MSA: 1999, 2002, 2006, 2012, 2018, 2020, and 2023 Technical Report September 2015 Prepared by the Alamo Area Council of Governments

2 Title: Emissions Trend Analysis for the San Antonio-New Braunfels MSA: 1999, 2002, 2006, 2012, 2018, 2020, and 2023 Authors: AACOG Natural Resources Department Performing Organization Name & Address: Alamo Area Council of Governments 8700 Tesoro Drive Suite 700 San Antonio, Texas Report Date: September 2015 Type of Report: Technical Analysis Period Covered: Sponsoring Agency Name: Alamo Area Metropolitan Planning Organization Supplementary Notes: N/A Date of Approval: Reference No.: Abstract: This report provides an analysis of the emissions generated in the eight-county San Antonio-New Braunfels Metropolitan Statistical Area (MSA) that combine in the atmosphere to form tropospheric ozone, a federally-regulated air pollutant. Most ozone precursors fall into one of two chemical categories, volatile organic compounds (VOCs) and nitrogen oxides (NO x ), which are the focus of this report. Precursor emission trends were calculated for the MSA beginning with the year 1999 and forecasted through 2023 for multiple sources: on-road, non-road, off-road, area, and point emissions sources. The emissions associated with Eagle Ford oil and gas exploration are discussed independently. This emission trend analysis serves as both a measurement for evaluating the effectiveness of implemented air quality control strategies and as a guide for maintenance of federal ozone standards throughout the region. The results of this study indicate that anthropogenic VOC emissions are predicted to increase slightly, primarily as the result of forecasted population growth, while anthropogenic NO X emissions are expected to decline through For the year 2023, VOCs are expected to reach tons/day indicating an increase of tons/day, or a 16.21% increase compared to 1999 estimations. NO X emissions are predicted to reach a level of tons/day in 2023 indicating a reduction of tons/day, or a 69.86% reduction as compared to In light of continuous population growth in the region, from 1,681,307 persons in 1999 to 2,612,533 persons through 2023, or a 55.39% increase, these NO X emission reductions are a significant achievement. Related Reports: Emissions Trend Analysis for the San Antonio-New Braunfels MSA: 1999, 2002, 2006, 2012, 2018, and FY FY 2013, UPWP 3.3. AACOG, Oct No. of Pages: 78 Distribution Statement: Alamo Area Council of Governments, Natural Resources Department Permanent File: Alamo Area Council of Governments, Natural Resources Department

3 This study was funded by the U.S. Department of Transportation, the Texas Department of Transportation, and the Alamo Area Metropolitan Planning Organization The contents of this report reflect the views of the authors who are responsible for the opinions, findings and conclusions presented herein. The contents do not necessarily reflect the views or policies of the Federal Highway Administration, the Federal Transit Administration, the Texas Commission on Environmental Quality, or the Texas Department of Transportation. iii

4 Executive Summary State and local agencies use a variety of tools in support of air quality planning. An emissions trend analysis is one such tool that allows analysts to compare and predict emission rates over a period of time. For ozone pollution, an emission trend analysis is developed to document precursor chemicals that form ozone: nitrogen oxides (NO X ) and volatile organic compounds (VOCs). For this analysis, emissions of VOC and NO X were complied for non-road mobile, area, point, off-road, on-road mobile. Emissions from truck idling and oil and gas exploration in Eagle Ford region are also studied and included in the total emissions whenever applicable. Overall, the results indicate that the amount of anthropogenic NO X emissions generated by various sources in the eight-county San Antonio-New Braunfels MSA will continue to decline through 2023, while anthropogenic VOCs will increase. For the year 2023, VOCs are expected to reach tons/day indicating an increase of tons/day, or a 16.21% increase compared to NO X emissions are predicted to reach a level of tons/day indicating a reduction of tons/day, or 69.86% reduction as compared to In light of continuous population growth in the region, from 1,681,307 persons in 1999 to 2,612,533 persons through 2023, or a 55.39% increase, these NOX emission reductions are a significant achievement. Table ES 1: San Antonio-New Braunfels MSA VOC Emissions Trend, tons/ozone season wkday Emission Source On-Road Non-Road Area Point Off-road Eagle Ford Shale Total Table ES 2: San Antonio-New Braunfels MSA NO X Emissions Trend, tons/ozone season wkday Emission Source On-Road Non-Road Area Point Off-road Eagle Ford Shale Total iv

5 According to the State s agency Texas Water Department Board, the area s population will experience a 55.39% increase by A comparison between this population trend and the emissions trends presented in this study is made in the Figure ES 1. Figure ES 1: Population vs. VOC and NO X Emissions Trend, San Antonio-New Braunfels MSA According to data shown in tables E.S. 1 and E.S. 2, the on-road vehicles were the greatest source of NO X emissions prior to 2012, but now represents the greatest source of emission reductions in this study. Although there are major sources of emissions in Atascosa, Comal, and Guadalupe counties, emissions generated in Bexar County, account for the greatest share of San Antonio-New Braunfels MSA emissions. Also, the trends indicate that in the future years the NO X emissions will be reduced, due to closure of Deely power plant at the end of 2018, application of selective catalytic reduction (SCR) technology at Spruce Unit 1 at the end of 2020, and more stringent standards for on-road and non-road vehicles exhaust emissions, while the VOC levels will have an increasing gradient. 1 Texas Water Development Board, 2016 Regional and 2017 State Water Plan Projections Data, Austin, TX. Available online : Accessed 07/14/2015. v

6 Table of Contents Executive Summary...iv Table of Contents...vi List of Tables... viii List of Figures...ix List of Equations...ix 1 Introduction National Ambient Air Quality Standards Status of Ozone Attainment in San Antonio-New Braunfels MSA Data Used for Emissions Trend Analysis Non-road Source Emissions Non-road Equipment Emissions Projection Drilling Rigs Non-road Emissions Summary Off-road Source Emissions Locomotives Emissions Projected Emissions for Airports at Military Bases San Antonio International Airport and Other Small Airports Total Off-road Emissions Summary Area Source Emissions Fuel Combustion Oil and Gas Exploration Emissions Eagle Ford Shale Emissions Projection Methodology Total Area Source Emissions Summary Point Source Emissions Projected Point Source Emissions CPS Energy Emissions San Miguel Electric Corporative Cement Kiln Emissions Point Source Emission Summary Oil and Gas Exploration in Eagle Ford Shale Sources of Data Eagle Ford On-Road Vehicle Emission Factors Emissions from Non-Road Equipment and Area Sources Projected Emission Data Total Eagle Ford Counties Emissions Summary On-Road Source Emissions vi

7 7.1 Emissions Calculations Estimation of Vehicle Miles Traveled Estimation of 2020 and 2023 On-road Emissions Combination Long Haul Trucks Extended Idling Total On-road Emission Summary Summary Population and Emissions Trends Emission Trend by Emission Sources Emission Trends by MSA Counties Appendix A:... A-1 vii

8 List of Tables Table 1-1: Status of Compliance with 8-Hour Ozone Standard, San Antonio-New Braunfels MSA Table 2-1: Drilling Rigs VOC Emissions in San Antonio-New Braunfels MSA, tons/day Table 2-2: Drilling Rigs NO X Emissions in San Antonio-New Braunfels MSA, tons/day Table 2-3: Non-road Source VOC Emissions in San Antonio-New Braunfels MSA, ton/day Table 2-4: Non-road Source NO X Emissions in San Antonio-New Braunfels MSA, ton/day Table 3-1: Line haul Locomotive Projection Factors, San Antonio-New Braunfels MSA Table 3-2: Emissions from Locomotive Operations in San Antonio-New Braunfels MSA by SCC codes, tons/day Table 3-3: Aircraft Emissions at Military Bases, tons/day Table 3-4: Civilian Airport Aircraft VOC Emission, San Antonio-New Braunfels MSA, tons/day3-5 Table 3-5: Civilian Airport Aircraft NO X Emission, San Antonio-New Braunfels MSA, tons/day 3-6 Table 3-6: Off-road Source VOC Emissions in San Antonio-New Braunfels MSA, tons/day Table 3-7: Off-road Source NO X Emissions in San Antonio-New Braunfels MSA, tons/day Table 4-1: San Antonio-New Braunfels MSA Industrial Fuel Combustion Emission Trend, tons/day Table 4-2: Historic Emission Trend for Oil and Gas Exploration in Eagle Ford Counties, tons/day Table 4-3: Area Source VOC Emissions in San Antonio-New Braunfels MSA, tons/day Table 4-4: Area Source NO X Emissions in San Antonio-New Braunfels MSA, tons/day Table 5-1 CPS Energy Facilities Emissions, tons/day Table 5-2: Historical Cement Kilns Emissions in San Antonio-New Braunfels MSA, ton/day Table 5-3: Point Source VOC Emissions in San Antonio-New Braunfels MSA, ton/day Table 5-4: Point Source NO X Emissions in San Antonio-New Braunfels MSA, ton/day Table 6-1: Operational Phases and Associated Sources of Emissions Table 6-2: Eagle Ford Emissions by Operation Phase by Emission Source for Low Future Development Scenario, tons/day Table 6-3: Data Sources for Eagle Ford Emission Inventory Table 6-4: TxDOT Traffic Counts Converted to MOVES2014 Source Type ID, May Table 6-5: Ozone Season Emission Factors for On-road Vehicles in Eagle Ford Counties Table 6-6: Eagle Ford Shale Emissions within San Antonio-New Braunfels MSA, ton/ozone season weekday Table 7-1: MOVES2014 Source Use Type Table 7-2: MOVES2014 Model Data Used for Calculating Emission Factors for Truck Idling Survey Table 7-3: Emission Factors for Counties in AACOG s Truck Idling Survey Table 7-4: San Antonio-New Braunfels MSA Idling Emission Trend, tons/summer weekday Table 7-5: San Antonio-New Braunfels MSA On-road VOC Emissions, ton/ozone season weekday viii

9 Table 7-6: San Antonio-New Braunfels MSA On-road NO X Emissions, ton/ozone season weekday Table 8-1: San Antonio-New Braunfels MSA VOC Emissions by Source, tons/ozone season weekday Table 8-2: San Antonio-New Braunfels MSA NO X Emissions by Source, tons/ozone season weekday Table 8-3: VOC Emission Trend in San Antonio-New Braunfels MSA, tons/ozone season weekday Table 8-4: NO X Emission Trend in San Antonio-New Braunfels MSA, tons/ozone season weekday Table A-1: MOVES Model Emissions Growth Rates for San Antonio-New Braunfels MSA... 2 List of Figures Figure 1-1: San Antonio New Braunfels Metropolitan Statistical Area Boundaries Figure 6-1: Eagle Ford Shale Map Figure 8-1: Population vs. VOC and NO X Emissions Trend, San Antonio-New Braunfels MSA 8-2 Figure 8-2: VOC Emission Trend by Source, San Antonio-New Braunfels MSA, tons/ozone season weekday Figure 8-3: NO X Emission Trend by Source, San Antonio-New Braunfels MSA, tons/ozone season weekday Figure 8-4: Total VOC Emissions Trend by County, tons/ozone season weekday Figure 8-5: Total NO X Emissions Trend by County, tons/ozone season weekday List of Equations Equation 2-1, Non-road Emissions Projections Equation 3-1, Daily emissions from locomotives, 2020, or Equation 3-2, Daily Aircraft Emissions by County, Equation 4-1, Daily area source emissions Equation 6-1, Daily on-road emissions during pad construction Equation 6-2, Ozone season day idling emissions during pad construction Equation 6-3, Ozone season day seismic trucks emissions Equation 6-4, Total number of drill rigs for each projection year Equation 7-1: Projection of 2018 Emissions into 2020 or Equation 7-2: County-based Idling Emission Factors by Year of Interest ix

10 1 Introduction The purpose of this trend analysis is to evaluate the historical ozone precursor emissions as they relate to the National Ambient Air Quality Standards (NAAQS) and to forecast the emissions into future years. This will determine whether or not emission levels in the region are increasing or decreasing. The results of this analysis can be used for air quality planning and development of control strategies in Atascosa, Bandera, Bexar, Comal, Guadalupe, Kendall, Medina, and Wilson counties, which constitute the San Antonio-New Braunfels MSA. These counties are shown in Figure 1-1. Figure 1-1: San Antonio New Braunfels Metropolitan Statistical Area Boundaries Plot Date: January 5, 2008 Map Compilation: January 5, 2008 Source: U.S. Census Bureau 1-1

11 The MSA is used in this study because it is likely to represent the non-attainment boundaries should the area fall under the non-attainment designation. To determine an area s nonattainment boundaries, the EPA will take into consideration factors such as locations and concentrations of industrial sources within the MSA, population density, and traffic and commuting patterns within MSA counties. The VOC and NO X emissions are the two main pollutants that form ozone and are, therefore, the focus of this analysis. Emissions data will be collected for non-road, off-road, area, point, and on-road emission sources. Emissions resulting from the Eagle Ford Shale oil and gas exploration activities are discussed independently. Emission totals are for typical ozone season weekday for each county. The historic and forecasted emission estimates provide planners with an indication of the change in emission levels by source and over time. 1.1 National Ambient Air Quality Standards The EPA is charged with the maintenance of air quality across the United States through the enforcement of national ambient air quality standards under the Clean Air Act. Primary standards are designed to protect human health including sensitive groups such as children, the elderly, and individuals suffering from respiratory diseases. Secondary standards are meant to protect public welfare from any known or anticipated adverse effects of a pollutant. When a region meets these standards, it is an "attainment area," otherwise the region can be declared a "non-attainment area". 2 To attain the ozone standard, the 3-year average of the fourth-highest daily maximum 8-hour average ozone concentrations measured at each monitor within an area over each year must not exceed 75 parts per billion. 3 Currently, this standard is under consideration to be lowered to 70 or 65 parts per billion. The EPA has legal mandate to announce its final decision by October 1, Status of Ozone Attainment in San Antonio-New Braunfels MSA The San Antonio region is an attainment area as of June 18, 2015; however, since the 3-year average of the fourth highest daily maximum ozone averages has exceeded the 70 ppb threshold, the region could be designated as non-attainment if the standard is lowered to 70 or 65 ppb. 2 Environmental Protection Agency (EPA), The Plain English Guide to the Clean Air Act. Available online: Accessed 4/18/ TCEQ, Air and Water Monitoring. Available online: Accessed 6/18/

12 Table 1-1: Status of Compliance with 8-Hour Ozone Standard, San Antonio-New Braunfels MSA Monitoring Site Fourth Highest (ppb) Year Average * Camp Bullis C San Antonio Northwest C Calaveras Lake C * as of June 18, Data Used for Emissions Trend Analysis The regional photochemical model s databases developed by TCEQ were used to estimate 2006, 2012, and 2018 emissions. For other years, locally collected empirical data and databases from the MOVES2014 4, EGAS 5, EDMS 6, and TexN 7 models were used. Each emission category includes the emission reduction effects of applicable federal, state, and/or local regulatory measures. The following is a list of EPA-approved software and data that were used to project emissions and develop emission trends. Category Data Source Non-road TexN model; Eastern Research Group s (ERG) drill rig emission inventory; local data for construction equipment, quarry equipment, mining equipment, landfill equipment, agricultural tractors, and combines Off-road Terminal Area Forecast (TAF) 8 ; Emission & Dispersion Modeling System (EDMS) version ; local data for Randolph AFB, San Antonio International Airport, and Lackland; ERG report on emissions at landing and take-off at small airports; Pechan & Associates locomotive emission inventory Area Economic Growth Analysis System (EGAS) 5.0 Point State of Texas Air Reporting System (STARS) 9, local data for EGUs in the San Antonio-New Braunfels MSA (CPS Energy and San Miguel power plants) and local data for Cement kilns (Alamo Cement, Chemical Lime, Capitol Cement, TXI, and CEMEX) 4 U.S. EPA, December Office of Transportation and Air Quality Washington, DC. Motor Vehicle Emission Simulator. Available online: Accessed 06/18/ U.S. EPA, April 27, Models and Tools. Economic Growth Analysis System Version 5.0. Available online: Accessed 06/18/ FAA, Nov Emissions & Dispersion Modeling System, Version Available online: Accessed 06/18/ TCEQ, Dec. 2008, Non-road Emissions Modeling, TexN. Available online: ftp://amdaftp.tceq.texas.gov/pub/nonroad_ei/texn/. Accessed 06/18/ Federal Aviation Administration, Terminal Area Forecast. Washington, DC. Available online: Accessed 06/18/ TCEQ, 2013, Point Source Emissions Inventory. Available online: Accessed 06/18/

13 Eagle Ford On-Road Draft Eagle Ford Emission Inventories, a low emission projection scenario based on projected number of drill rigs, well decline curves, estimated ultimate recover (EUR), MOVES2014, TexN model, Tier4 standards, and other emission controls EPA s MOVES2014 model and the data developed by the Texas Transportation Institute (TTI). The vehicle miles traveled (VMT) estimates are based on travel demand modeling (TDM) for major metropolitan areas and the Highway Performance Monitoring System (HPMS) for rural areas, and local data are used for extended diesel truck idling. 1-4

14 2 Non-road Source Emissions Non-road emission sources cover a wide range of mobile and stationary equipment. Unlike onroad vehicles, non-road equipment sources are not registered for on-road operation and include farming, quarry, industrial, lawn and garden, commercial, and construction equipment. This category does not include commercial marine vessels, railroad locomotives, and aircraft. These types of equipment are discussed under the section on off-road equipment. The primary non-road equipment categories include: Recreational Vehicles (ATVs, off-highway motorcycles) Agricultural Construction/Mining/landfills Commercial (e.g., warehouse forklifts) Industrial Lawn and Garden (commercial and residential) Recreational Marine Engines Airport Ground Support Equipment Railway Maintenance Drill Rigs for Conventional Oil and Gas development 2.1 Non-road Equipment Emissions Projection Apart from drilling rigs, the TexN model, which mimics the EPA's NONROAD2008a model, 10 was used to estimate 2020 and 2023 emissions from all other non-road equipment. Emission growth rates, from 2018 to 2020 and from 2018 to 2023, were determined using the TexN model s emissions output files and then applied to the 2018 data, which was a combination of local AACOG-generated and state level TCEQ-generated data used in the photochemical model s emission data. The complied data was organized by county and SCC code for each equipment type. The Texas NONROAD Model (TexN) provides emissions estimates for a large number of nonroad equipment categories operating in Texas. 11 The TexN model accounts for several future federal programs that set tighter emissions standards for off-road equipment based on the type of equipment, fuel, and horsepower. The federal programs include: Standards for Compression-ignition Vehicles and Equipment, Standards for Spark-ignition Off-road Vehicles and Equipment, Tier 1 to Tier 4 Heavy-duty Diesel Equipment, Recreational Marine Standards, and Lawn and Garden Equipment standards 12. Also, the requirements established by the Texas Low Emission Diesel (TxLED) program, small marine rule, and reformulated gasoline were 10 EPA, July Modeling and Inventories. Available online: Accessed 05/02/ Eastern Research Group, Inc. April 26, Texas NONROAD (TexN) Model. Austin, Texas. Available online: ftp://amdaftp.tceq.texas.gov/pub/nonroad_ei/texn/. Accessed 06/18/ Eastern Research Group, Inc., Sept. 28, TexN 1.6. Available online: ftp://amdaftp.tceq.texas.gov/pub/nonroad_ei/texn/. Accessed 04/22/

15 included. According to TCEQ, TxLED requirements are intended to result in reductions in NO X emissions from diesel engines. Currently, reduction factors of 5.7% (0.057) for on-road use and 7.0% (0.07) for non-road use have been accepted as a NO X reduction estimate resulting from use of TxLED fuel. However, this reduction estimate is subject to change, based on the standards accepted by the EPA for use in the Texas State Implementation Plan (SIP). 13 The TexN model run specifications used to project emissions were: Analysis Year = 2018, 2020 and 2023 Option File = Varies by run Period = Ozone season day Summation Type = Typical weekday of summer Post Processing Adjustments = All including TxLED Rules Enabled = All Regions = San Antonio-New Braunfels MSA counties Sources = All fuels and all classes of equipment Weight = Tons per day The following equation describes the procedure for calculating emissions from non-road equipment in 2020 and The county-based emission totals listed by SCC codes for a particular county were determined by aggregating all equipment emissions. Equation 2-1, Non-road Emissions Projections PYE A = BCE A x (FCNR A.TexN / BCNR A.TexN ) Where, PYE A = Projected Year Emissions for Equipment Type A for (VOC or NO X ) BCE A = Base Case 2018 Emissions for Equipment Type A (from 2018 photochemical modeling emission inventory & local data) FCNR A.TexN = 2020 or 2023 VOC or NO X Emissions for Equipment Type A (from TexN model) BCNR A.TexN = 2018 VOC or NO X Emissions for Equipment Type A (from TexN model) Sample Equation: NO X emissions for a diesel scraper in Bexar County in 2023 PYE A = tons of NO X /day from 2018 photochemical model x ( tons of NO X /day from 2023 TexN model / tons of NO X /day from 2018 TexN model) = tons of NO X day for a 2023 diesel scraper in Bexar County 13 TCEQ, July 24, Texas Emissions Reduction Plan (TERP) Emissions Reduction Incentive Grants Program. Austin, Texas. Available online: Accessed 6/19/

16 2.2 Drilling Rigs Historical emissions from drilling rig operations were obtained from the ERG s drilling rig emission inventory for Texas. This inventory only includes drill rigs that are used for conventional method of drilling oil and gas wells. Emissions associated with non-conventional or horizontal oil and gas well drilling, a technique which is used for oil and gas exploration in the Eagle Ford Shale, are not included in this section, rather they are discussed in the Eagle Ford are provided in Section 6. The purpose of ERG s study was to develop a comprehensive emissions inventory for drilling rig engines associated with onshore oil and gas exploration activities occurring in Texas in While drilling activities are generally short-term in duration, typically covering a few weeks to a few months, the associated diesel engines are usually very large, resulting in substantial amount of NO X emissions. 15 The ERG consultant firm back cast Drill Rig emissions to 2006 using BakerHughes.com and RigData.com drill rig counts. 16 Tables 2-1 and 2-2 list emissions from drill rigs used in conventional oil and gas well drilling in the San Antonio- New Braunfels MSA. Table 2-1: Drilling Rigs VOC Emissions in San Antonio-New Braunfels MSA, tons/day County Atascosa Bandera Bexar Comal Guadalupe Kendall Medina Wilson Total Note: This table does not include emissions from drill rigs operating in the Eagle Ford. 14 Eastern Research Group, Inc. July 15, Drilling Rig Emission Inventory for the State of Texas. Austin, Texas. p Available online: Accessed 06/19/ Eastern Research Group, Inc. July 15, Drilling Rig Emission Inventory for the State of Texas. Austin, Texas. p Available online: Accessed 06/19/ Doug Boyer, TCEQ, Nov. 5, /2012 DFW Modeling Update. Presented to the DFW Photochemical Modeling Technical Committee. p. 6. Available online: _PMTC_modeling_update.pdf. Accessed 06/19/

17 Table 2-2: Drilling Rigs NO X Emissions in San Antonio-New Braunfels MSA, tons/day County Atascosa Bandera Bexar Comal Guadalupe Kendall Medina Wilson Total Note: This table does not include emissions from drill rigs operating in the Eagle Ford. 2.3 Non-road Emissions Summary Tables 2-3 and 2-4 show estimated VOC and NO X emissions for non-road equipment, including emissions from drill rigs, for each county. Historical total VOC and NO X emissions for non-road sources indicate a downward trend after This decrease in emissions can be attributed to implemented state and federal fuel and exhaust emission regulations for non-road equipment. The EPA has developed a lengthy list of emissions standards for various non-road engine sizes and fuel types. Their effect will be more noticeable by the year 2018, resulting in reductions of both NO X and VOC emissions as compared to Reductions of sulfur levels from 500 ppm to 15 ppm in diesel fuel, for example, have been finalized in EPA, Nov. 14, 2012, Emission Standards Reference Guide. Non-road Engines and Vehicles. Available online: Accessed 06/24/ EPA, Nov. 14, 2012, Emission Standards Reference Guide. Highway, Nonroad, Locomotive, and Marine Diesel Fuel Sulfur Standards. Available online: Accessed 06/24/

18 Table 2-3: Non-road Source VOC Emissions in San Antonio-New Braunfels MSA, ton/day County Atascosa Bandera Bexar Comal Guadalupe Kendall Medina Wilson Total Table 2-4: Non-road Source NO X Emissions in San Antonio-New Braunfels MSA, ton/day County Atascosa Bandera Bexar Comal Guadalupe Kendall Medina Wilson Total

19 3 Off-road Source Emissions Emissions from locomotives and aircraft are referred to as off-road mobile sources to distinguish them from other non-road sources 19. For this category of emissions, data was locally collected from military installations, railway operators, and airports, where mobile off-road emissions are generated. Emissions from aircraft ground support equipment used at military bases and airports, as well as emissions from maintenance of rail yards are included in the non-road category described in the previous section. Locomotive emissions include line haul and switching yards locomotives, and aircraft emissions include landing and take-off cycles for military, commercial, and general aviation aircraft at civil and military airports in the region. Emissions from commercial marine vessels are not included, since commercial marine vessel activity is insignificant in the San Antonio-New Braunfels MSA. 3.1 Locomotives Emissions The EPA s new regulatory requirements for locomotives became effective in as part of the EPA s National Clean Diesel Campaign (NCDC) goal to reduce across the board harmful emissions from diesel engines. Later on, the much stricter Tier 4 standards were devised to require significantly lower VOC and NO X emissions, compared to the Tier 3 standards 21. The Tier 4 standards will become effective in 2015 and are expected to reduce NOx emissions by 80% when fully implemented. The 2018 local emission data for line-haul (SCC ) and yard locomotives ( ) were used as a basis for projection into 2020 and These data originally were calculated by TCEQ and are used in the San Antonio s regional photochemical model emission inventories. For determining the growth ratios, the data developed by Pechan & Associates for 1990 through 2040 were used 22. These Pechan & Associates datasets for 2018, 2020, and 2023 were used to determine emission growth rates from 2018 to 2020 and from 2018 to 2023 (Table 3-1). Then, the growth rates were applied to the 2018 regional photochemical model emissions to project them into 2020 and This is shown in Equation TCEQ, December 2012, Non-road and Off-road Mobile Source Emissions Data. Available online: Accessed 06/19/ Ibid. 21 DieselNet, Emission Standards, Locomotives. Available online: Accessed 06/19/ Ms. Kirstin B. Thesing. E.H. Pechan & Associates, Inc., July Development of Locomotive and Commercial Marine Emissions Inventory TO Durham, NC. TCEQ Grant Agreement No p. 1. Available online: ftp://amdaftp.tceq.texas.gov/pub/offroad_ei/locomotives/. Accessed 06/19/

20 Table 3-1: Line haul Locomotive Projection Factors, San Antonio-New Braunfels MSA County 2018 to to 2023 VOC NO X VOC NO X Atascosa Bandera* Bexar Comal Guadalupe Kendall* Medina Wilson* * Counties with no railways in the San Antonio-New Braunfels MSA Equation 3-1, Daily emissions from locomotives, 2020, or 2023 E D.2020.A.B = E TCEQ.D.2018.A.B x (E Pechan.2020.B / E Pechan.2018.B ) Where, E D A.B = Daily 2020, or 2023 emissions in county A for locomotive type B (NO X or VOC) E TCEQ.D.2018.A.B = Daily 2018 emissions in county A for locomotive type B (NO X or VOC from TCEQ data) E Pechan.2018.B = Annual 2018 emissions for locomotive type B from Pechan & Associates (NO X or VOC) E Pechan.2020.B = Annual 2020, or 2023 emissions for locomotive type B from Pechan & Associates (NO X or VOC) Sample Equation: Daily 2020 NO X emissions from line-haul locomotives in Bexar County E Local.FY.A.B = 1.55 tons of NO X in 2018 x (79.88 tons of NO X per year in 2020 from Pechan & Associates / tons of NO X per year in 2018 from Pechan & Associates) = 1.45 tons of NO X per day from line-haul locomotives in Bexar County, 2020 As shown in Table 3-2, based on the calculations described above, emissions from locomotives will follow a gradual declining curve in years beyond 2006 as regulatory requirements are implemented and newer locomotives come online. 3-2

21 Table 3-2: Emissions from Locomotive Operations in San Antonio-New Braunfels MSA by SCC codes, tons/day County VOC NO X VOC NO X VOC NO X VOC NO X VOC NO X VOC NO X Atascosa Bandera Bexar Comal Guadalupe Kendall Medina Wilson Total Projected Emissions for Airports at Military Bases The photochemical modeling databases for 2018 do not include emissions from aircraft at military airports, emissions associated with aircraft landing and take-off cycles at Lackland and Randolph military airports were added to these emissions. Data for aircraft operating at military bases was obtained from Lackland and Randolph military bases. The total number of aircraft operation at Lackland has been reduced on more recent years; as a result, the emission totals presented in Table 3-3, below show a decline after the year The total number of operation at Randolph has remained steady and it is assumed will remain the same through The remaining military installations, including Lackland and Randolph Air Force bases, Fort Sam Houston and Camp Bullis are now managed together as Joint Base San Antonio (JBSA). 23 Port San Antonio, a business park developed on the site of the former Kelly Air Force Base owns the building that currently houses the 24th Air Force and has leased it back to the Air Force. 24 The runway at Port San Antonio is owned and operated by JBSA-Lackland. JBSA-Lackland JBSA-Lackland is classified as a major source of emissions and has an Air Pollution Control Title V Permit to Operate (LAFB 2009b). In addition, JBSA-Lackland holds three New Source Review Permits, and numerous sources registered under Permit-By-Rule requirements. As required by the TCEQ, 30 Texas Administrative Code (TAC) , JBSA-Lackland calculates annual criteria pollutant emissions from stationary sources and provides this information to the TCEQ. There are various sources at these bases that emit criteria pollutants, 23 San Antonio Business Journal, Apr. 5, San Antonio seeks to leverage its cyber-security advantage. Available online: Accessed 07/11/ Ibid. 3-3

22 including generators, boilers, hot water heaters, fuel storage tanks, gasoline service stations, surface coatings/paint booths, and use of miscellaneous chemicals. JBSA-Lackland is required to prepare an Air Emissions Inventory (AEI) each year. 25 JBSA-Randolph JBSA-Randolph is located in Bexar County, Texas, northeast of the City of San Antonio. The base has a variety of missions and is a part of Joint Base San Antonio s 502nd Air Base Wing. The base is home to the 12 th Flying Training Wing and is one of the few bases that conduct instructor pilot training. The 2008 emissions data presented here are based on the aircraft activity data that come from a report on the compatibility of JBSA-Randolph air installation with its adjacent neighborhoods 26. About 209,367 annual aircraft operations were estimated for calendar year 2008 at JBSA-Randolph. Aircraft emissions were calculated by applying the EDMS airport emission model. Numbers of sorties per each airplane type were entered into the EDMS model and the annual and daily emissions were generated for each aircraft type. The following table shows aggregation of these emissions. Table 3-3: Aircraft Emissions at Military Bases, tons/day Military Base Pollutant JBSA-Lackland JBSA-Randolph VOC NO X VOC NO X San Antonio International Airport and Other Small Airports Emissions from aircraft landing and take-off cycles for the San Antonio International Airport, Stinson, and smaller regional public and private airports throughout the San Antonio-New Braunfels MSA are compiled and extracted from the data collected by the ERG consultant firm. ERG developed statewide annual emission inventories for Texas airport activities for the calendar years 1996, 2000, 2002, 2011, 2014, 2017, 2020, 2023, 2026, 2029, and the base year The years 2012 and 2018, which are years of interest in current emission trend analysis, were missing in the ERG s report. The followings explain how the aircraft emissions were calculated for these years d Civil Engineer Squadron, October 2012, Environmental Assessment Addressing the Transportation Security Administration Canine Academy and Associated Training Facilities at Joint Base San Antonio-Lackland. Available online: Accessed 06/22/ Randolph Air Force Base, Texas, April 2008, Air Installation Compatible Use Zone Study Available online: Accessed 06/22/ Eastern Research Group, Inc. July 15, Development of Statewide Annual Emissions Inventory and Activity Data for Airports Morrisville, North Carolina. p. ES

23 ERG used publically available 2008 activity data and supplemented them with 2008 activity data obtained from local airports. Two approaches were used to estimate emissions from the compiled activity data. If the activity data had aircraft specific data, the EDMS software was employed. If such detailed data were not available, then ERG applied a more general approach for different aircraft types (i.e., air taxis, general aviation, and military aircraft) using available generic emission estimating procedures. Once the base year of 2008 was established, the inventory was backcasted and forecasted based on FAA s Terminal Area Forecast (TAF) data. 28 For the current trend analysis, annual rates of growth between 2002 and 2020 were calculated according to data in the ERG s report. The growth rates for any year of interest, such as 2012 or 2018, were applied to the preceding year s total emissions for any specific county and the annual emissions for that year were calculated. The emissions from GSEs and APUs were removed to remain consistent with the regional photochemical model, which classifies them as non-road source emissions. Using the ERG s data as input, the following equation was used for calculating the 2012 aircraft emissions for any particular county in Texas. Equation 3-2, Daily Aircraft Emissions by County, 2012 E YoI.A. = [(EPY _ A EFY A ) / (FY - PY) x (PY - YoI) + EPY A ] / 365 days per year Where, E YoI.A EPY A EFY A FY PY YoI = Emissions for Year of Interest in county A (NO X or VOC) = Emissions for Preceding Year in county A (NO X or VOC) = Emissions for Following Year in county A (NO X or VOC) = Following Year (2014, ERG studied year) = Preceding Year (2011, ERG studied year) = Year of Interest for which emission estimation is intended Sample Equation: 2012 NO X emissions from aircrafts in Bexar County E YoI.A = [( tons of NO X in tons of NO X in 2014) / (2014 FY 2011 PY ) x (2011 PY 2012 YoI ) tons of NO X in 2011 from ERG report] / 365 days per year = daily tons of NO X generated by aircrafts in Bexar County, 2012 The resultant emission data are shown in the following tables (Table 3-4 and Table 3-5). The 2020 and 2023 data directly and without any modification come from the ERG s report. Table 3-4: Civilian Airport Aircraft VOC Emission, San Antonio-New Braunfels MSA, tons/day County Atascosa Bandera Bexar Comal Guadalupe Eastern Research Group, Inc. July 15, Development of Statewide Annual Emissions Inventory and Activity Data for Airports Morrisville, North Carolina. p. ES

24 Kendall Medina Wilson Total Table 3-5: Civilian Airport Aircraft NO X Emission, San Antonio-New Braunfels MSA, tons/day County Atascosa Bandera Bexar Comal Guadalupe Kendall Medina Wilson Total Total Off-road Emissions Summary Table 3-6 and Table 3-7 list aggregated emissions from aircraft and railroad locomotives. Gradual reductions of NO X emissions, however, are mainly due to implementation of air quality control strategies that target reduction of exhaust related NO X emissions. 3-6

25 Table 3-6: Off-road Source VOC Emissions in San Antonio-New Braunfels MSA, tons/day County Atascosa Bandera Bexar Comal Guadalupe Kendall Medina Wilson Total Table 3-7: Off-road Source NO X Emissions in San Antonio-New Braunfels MSA, tons/day County Atascosa Bandera Bexar Comal Guadalupe Kendall Medina Wilson Total

26 4 Area Source Emissions Area source emissions come from of a variety of anthropogenic (human-made) sources that are too small, too abundant, or too dispersed geographically to inventory individually. Examples of these sources include dry cleaning, vehicle refueling, cooking, and solvent usage 29. Analysis of historical data for area sources indicates that emissions will have an upward trend due to increases in population and economic activities in the coming years. Major categories of area source emissions include 30 : Stationary source fuel combustion (residential, commercial, and industrial) Solvent use (e.g., small surface coating operations) Product storage and transport distribution (e.g., gasoline) Oil and gas exploration Light industrial/commercial sources Agriculture (e.g., pesticides, fertilizer) Waste management (e.g., landfills, wastewater) The source of data for all Area sources is the database used in the Texas State Implementation Plan, which has been produced by TCEQ and used in the Texas photochemical model. This data can be found on TCEQ s ftp site 31. For this trend analysis whenever AACOG staff had access to in-house data, that data was used instead of TCEQ s data. 4.1 Fuel Combustion AACOG conducted a study independent from this trend analysis to estimate 2012 and 2018 emissions for stationary source fuel combustion based on fuel consumption data collected by the Manufacturing Energy Consumption Survey (MECS), Fuel Oil and Kerosene Sales (FOKS), Economic Census, and Census of Agriculture (COA). 32 The emissions estimates for the San Antonio-New Braunfels MSA were primarily based on variant fuel intensities within the manufacturing industry sector. Industrial fuel consumption estimates published in the Annual Energy Outlook 2015 were used to project emissions to Since the 2020 and 2023 are included in this emission trend report, the 2018 fuel combustion data extracted from the AACOG report described above, were projected into 2020 and 2023 using the growth factors generated by the EGAS model. The results are shown in the table TCEQ, Area Source Emissions Data. Available online: Accessed 05/17/ Ibid. 31 TCEQ, Area EI, available online: ftp://amdaftp.tceq.texas.gov/pub/area_ei/. Accessed 06/18/ Area Source Industrial Fuel Combustion Emissions in San Antonio-New Braunfels Metropolitan Statistical Area for 2012 and 2018, AACOG, August

27 Table 4-1: San Antonio-New Braunfels MSA Industrial Fuel Combustion Emission Trend, tons/day County VOC NO X VOC NO X VOC NO X VOC NO X Atascosa Bandera Bexar Comal Guadalupe Kendall Medina Wilson TOTAL Oil and Gas Exploration Emissions The source of data for oil and gas production is Texas State Implementation Plan, which has been produced by TCEQ and used in the photochemical model. This data can be found on TCEQ s ftp site 33. The TCEQ s data includes emission information associated with all equipment that are traditionally used for non-horizontal wells, including drill rigs for 2006, 2012, 2013, and AACOG staff did not use that part of TCEQ s data that was generated for the Atascosa and Wilson counties since these 2 counties are within the Eagle Ford Shale. The AACOG staff has done its own emission inventory for these 2 counties and prefers to use it as locally collected data for this trend analysis. The TCEQ s data for 2018, which contained databases for 2 categories of Oil & Gas and drill Rigs by SCC codes was used for projection and forecast. These 2 databases were combined into a spreadsheet and emission growth rates, generated by EGAS model were used to project them into 2020 and The results are shown in tables 4-3 and Eagle Ford Shale Emissions The data was obtained from a variety of sources, including existing databases (such as the Texas Railroad Commission (TRC) oil and gas production data. The methodology for calculating emissions from oil and gas exploration activities in Eagle Ford area is discussed in detail in Chapter 6. The following table comes from Chapter 6 and indicates a historical trend for total emissions for various phases of oil and gas exploration for two Eagle Ford counties within the San Antonio-New Braunfels MSA. Total emissions for counties of Atascosa and Wilson in 33 TCEQ, Oil & Gas EI, available online: ftp://amdaftp.tceq.texas.gov/pub/oil_gas_ei/. Accessed 06/18/

28 this table are aggregated with the rest of area source emission totals and shown in tables 4-4 and 4-5. Table 4-2: Historic Emission Trend for Oil and Gas Exploration in Eagle Ford Counties, tons/day County VOC NO X VOC NO X VOC NO X VOC NO X Atascosa Wilson TOTAL Projection Methodology The projected 2020 and 2023 emissions for all categories were generated using emissions growth rates calculated by the Economic Growth Analysis System (EGAS) 34. The EGAS model was developed by the EPA to provide "creditable growth factors" for projecting future emissions. 35 EPA endorses the use of EGAS when emission source growth estimates are not available by facility survey or other local sources. EGAS output files for each year were compared for specific SSC and FIPS codes to determine the growth rates and develop emission growth factors for these SCC s and FIPS of interest for 2020 and The EGAS model s configuration option, which is shown below was used to generate output data files organized by SCC codes. Parameters Selected to Run EGAS Version 5.0: Configuration Name: Default REMI 6.0 SCC Configuration Output: SCC Configuration Base Year: 2018 FIPS Texas Projection Years: 2020, and 2023 Base Year: 2006 EGAS model growth rates were calculated and future emissions were calculated using the following formula. Equation 4-1, Daily area source emissions E Local.FY.A.B = E Local.18.A.B x E EGAS.23.A.B Where, 34 E.H. Pechan & Associates, EGAS 5.0 Reference Manual. Available online: Accessed 06/18/ Ibid. 4-3

29 E Local.FY.A.B = Daily 2023 emissions in county A for SCC code B (NO X or VOC) E Local.18.A.B = Daily 2018 emissions in county A for SCC code B (NO X or VOC) E EGAS.23.A.B = EGAS Growth Rate from 2018 to 2023 in county A for SCC code B (NO X or VOC) Sample Equation: 2023 NO X emissions from Industrial Distillate Oil fuel combustion in Atascosa County, SCC code E Local.FY.A.B = 0.01 tons of NO X in 2018 x 1.07 EGAS Growth Rate for 2023 = tons of NO X per day from Distillate Oil fuel combustion in Atascosa County, Total Area Source Emissions Summary Area source emissions from 1999 to 2023 for each county are shown in tables 4-3 and 4-4. Area source emissions are expected to increase through the year 2023, due to population growth and increased oil exploration and other economic activities. Table 4-3: Area Source VOC Emissions in San Antonio-New Braunfels MSA, tons/day County Atascosa Bandera Bexar Comal Guadalupe Kendall Medina Wilson Total Table 4-4: Area Source NO X Emissions in San Antonio-New Braunfels MSA, tons/day County Atascosa Bandera Bexar Comal Guadalupe Kendall Medina Wilson Total

30 5 Point Source Emissions Point source emissions are generated at stationary facilities engaging in industrial or commercial activities. A facility is considered a point source if it generates at least 10 tons per year of VOC, 25 tons per year of NO X, or 100 tons per year of any other contaminant subject to NAAQS. 36 Examples of point sources are cement kilns, power plants, and large manufacturing plants. TCEQ collects data on point sources by sending annual emissions inventory questionnaires (EIQs) to all sources identified as meeting the reporting requirements. Subject entities are required to report levels of emissions subject to regulation from all emissions-generating units and emissions points, and also must provide representative samples of calculations used to estimate the emissions. Descriptive information is also required on process equipment, including operating schedules, emission control devices, abatement device control efficiencies, and emission point discharge parameters such as location, height, diameter, temperature, and exhaust gas flow rate. 37 The 2012 point source emission data presented in current report, come from spreadsheets posted on the TCEQ s site Projected Point Source Emissions The future years emissions for the San Antonio-New Braunfels MSA from electric generating units (EGU) and non-electric generating units (NEGU), two subcategories of point source emissions, come from databases developed by TCEQ, CPS Energy, and San Miguel power plant. Properly assessing future point source emissions also requires identifying and calculating emissions from new point source facilities that are slated for construction. For this reason, the 2018 through 2023 projected emission estimates include emissions from expansion of new point source facilities and take into account the effects of installation of emission control devices at cement factories and power plants. 36 Texas Administrative code, amended December 23, 1999 Chapter 101: General Rules, Rule (1). Available online: pg=1&p_tac=&ti=30&pt=1&ch=101&rl=10. Accessed 06/12/ TCEQ. Appendix B: Emissions Modeling for the DFW Attainment Demonstration SIP Revision for the 1997 Eight-Hour Ozone Standard. Austin, Texas. p. B-12. Available online: Accessed 06/12/ TCEQ s site, 2013 Point Source Emissions, 4/1/2015, Available online: Accessed 06/12/

31 5.2 CPS Energy Emissions CPS Energy is the nation s largest municipally owned energy utility providing both natural gas and electric service. Acquired by the City of San Antonio in 1942, CPS Energy serves customers in Bexar County and portions of Atascosa, Bandera, Comal, Guadalupe, Kendall, Medina, and Wilson Counties. 39 The 2012 CPS Energy emission data, which are also the basis for CPS 2018, 2020, and 2023 forecasted years, were obtained from CPS Energy. The emission forecast procedure took into consideration that in 2012, the Rio Nogales natural gas plant in Seguin, Texas, was acquired 40 by CPS, the W.B. Tuttle power plant was decommissioned in 2013, and the J. T. Deely, a coal burning power plant, would be taken off line by the end of , an SCR technology will be installed on Spruce #1 unit at the end of The projected levels of emissions for 2018 through 2023, which are shown in Table 5-1 may change in the future, because of market demand. The annual totals were derived using variable daily generation rates, i.e., some days with higher generation and some days with lower generation. Therefore, multiplying daily figures by 365 does not produce annual emissions rates. Overall, the emissions from CPS Energy s power plants are expected to decrease in the coming years. 39 CPS Energy, Who We Are, Available online: Accessed 07/09/ CPS Energy, The History of CPS Energy, Available online: Accessed 07/09/ Reuters, Available online: Accessed 03/31/

32 Table 5-1 CPS Energy Facilities Emissions, tons/day CPS Energy Plant VOC NO X VOC NO X VOC NO X VOC NO X VOC NO X VOC NO X VOC NO X O.W. Sommers J.T. Deely* J.K. Spruce V.H. Brauning Rio* Leon Creek W.B. Tuttle* A. V. Rosenberg Total *Not included in CPS Energy totals because Rio was not owned by CPS Energy before W.B. Tuttle shut down in J. T. Deely will be shut down at the end of

33 5.3 San Miguel Electric Corporative San Miguel is a power plant located in the city of Christine in Atascosa County. San Miguel Electric Cooperative, Inc. (San Miguel) was created on February 17, 1977, under the Rural Electric Cooperative Act of the State of Texas, for the purpose of owning and operating a 400- MW mine-mouth, lignite-fired generating plant and associated mining facilities that furnish power and energy to Brazos Electric Power Cooperative, Inc. and South Texas Electric Cooperative, Inc. 42 The 2012 emissions data, consisting of tons/day of NO X and 0.22 ton/day of VOC emissions, were obtained from the power plant. Due to installation of emission control equipment, the above values reported to TCEQ in 2013, were decreased to 7.32 tons/day of NO X and 0.17 ton/day of VOC emissions. 43 The San Miguel is expected to generate 5.75 tons of NO X for a typical summer day in 2018, according to their latest to AACOG. Their 2013 VOC has been reported to TCEQ as ton per day. These recent values will be used for future years of 2018 through 2023 for this particular facility. 5.4 Cement Kiln Emissions Due to the abundance of limestone in the San Antonio-New Braunfels MSA, several cement companies have been active in this area. Currently major cement manufacturers in the region are TXI, Alamo Cement, Capitol Cement, APG Lime Corp (sold to LHOIST), and lately CEMEX, which is a Mexico-based cement company 44. As 2018 data in Table 5-2 indicate, these companies have spent significant amounts of resources to control their emissions by adopting modern emission control technologies 45, however they will remain major contributors to air pollution in coming years. Table 5-2 summarizes a historical review of emissions associated with operation of cement factories in the San Antonio-New Braunfels MSA. The 2012 data have been reported to the TCEQ by each company listed in Table 5-2 and AACOG is using them for this report without any modification. The 2013 data downloaded from TCEQ s site are presented in this table as the latest available data and AACOG is using them as future years data for years 2018, 2020, and 2023 in the Table San Miguel Electric Cooperative, Inc. Available online: Accessed 08/05/ TCEQ s site, 2013 Point Source Emissions, 4/1/2015, Available online: 44 CarrTracks, A Short History and Production Statistics of the Cement Industry for Rail fans. Available online: Accessed 08/27/ By Ron Maloney, Sept. 21, Breath of Fresh Air, The Herald-Zeitung. Available online Accessed 08/27/

34 Table 5-2: Historical Cement Kilns Emissions in San Antonio-New Braunfels MSA, ton/day Plant APG Lime Corp/ LHOIST County VOC NO X VOC NO X VOC NO X VOC NO X VOC NO X VOC NO X VOC NO X Comal Alamo Cement Bexar Capitol Cement Bexar CEMEX Comal TXI Comal Total

35 5.5 Point Source Emission Summary Tables 5-3 and 5-4 below summarize point source emission totals for the San Antonio-New Braunfels MSA. Projected emissions totals reflect the additional point source facilities, as well as implementation of control technologies, such as NO X controls applied by the cement companies. As shown in these tables, decreases in total emissions from point sources are expected during coming years as alternative fuels, shut down of coal burning power plants, and newer emission control technologies are being used to make operations of these facilities comply with stricter air quality and pollution standards. Table 5-3: Point Source VOC Emissions in San Antonio-New Braunfels MSA, ton/day County Atascosa Bandera Bexar Comal Guadalupe Kendall Medina Wilson Total Table 5-4: Point Source NO X Emissions in San Antonio-New Braunfels MSA, ton/day County Atascosa Bandera Bexar Comal Guadalupe Kendall Medina Wilson Total

36 6 Oil and Gas Exploration in Eagle Ford Shale The information presented in this section come from the latest but unpublished draft emission inventory conducted by AACOG, which is an update to the previous Eagle Ford Emissions Inventory published on April 4, and provides key information on the impact of increased oil and gas production from the Eagle Ford Shale. Unlike the Haynesville and Barnett Shale formations in northern Texas that primarily produce gas, the Eagle Ford Shale features high oil yields and wet gas/condensate across much of the play. Consequently, equipment types, processes, and activities in the Eagle Ford may differ from those employed in more traditional shale formations. Hydraulic fracturing used in the Eagle Ford Shale is a technological advancement which is used to recover natural gas and oil resources from shale formations. In the Eagle Ford Shale, product is extracted by pumping water, sand and other additives under high pressure into the formation to create fractures. The newly created fractures are propped open by the sand, which allows the natural gas and oil to flow into the wellbore and be collected at the surface. The core area of Eagle Ford production is in Karnes County and its surrounding areas. This section of the Eagle Ford Shale, which exhibits the most intensive development and potential for future growth, includes two of the San Antonio-New Braunfels MSA s counties: Atascosa and Wilson. Emissions associated with Eagle Ford oil and gas exploration in these two counties will be discussed in the current emissions trends analysis. There are three different types of wells in the Eagle Ford Shale development included in the emission inventory: dry gas wells, wet gas wells that produce condensate, a petroleum product, and oil wells that in addition to oil can also produce casinghead gas. NO X and VOC emissions are released in the Eagle Ford area during five main phases of well construction and production: These phases are described and listed below: Exploration and Pad Construction: Exploration uses vibrator trucks to produce sound waves beneath the surface that are useful in the exploration for oil and natural gas. Construction of the drill pad requires clearing, grubbing, and grading, followed by placement of a base material by construction equipment and trucks. Reserve pits are also usually required at each well pad because the drilling and hydraulic fracturing process uses a large volume of fluid that is circulated through the well and back to the surface. 46 AACOG, April 4, Oil and Gas Emission Inventory, Eagle Ford Shale. San Antonio, Texas. Available online: Accessed 06/30/

37 Figure 6-1: Eagle Ford Shale Map 47 Drilling Operation: Drilling of a new well is typically a two to three week process from start to finish and involves several large diesel-fueled generators. 48 Other emission sources related to drilling operations includes construction equipment and trucks to haul supplies, equipment, fluids, and employees. Hydraulic Fracturing and Completion Operation: Hydraulic fracturing is the high pressure injection of water mixed with sand and a variety of chemical additives into the well to fracture the shale and stimulate natural gas production from the well. Fracking operations can last for several weeks and involve many large diesel-fueled generators 49 Once drilling and other well construction activities are finished, a well must be completed in order to begin producing. The completion process requires venting of the well for a sustained period of time to remove mud and other solid debris in the well, to remove any inert gas used to stimulate the well (such as CO 2 and/or N 2 ) and to bring the gas composition to pipeline grade. 50 In the Eagle Ford, vented gas from completion is usually flared. 47 Aurora Oil & Gas Limited, Production Results. Available online: Accessed 07/15/ University of Arkansas and Argonne National Laboratory. Fayetteville Shale Natural Gas: Reducing Environmental Impacts: Site Preparation. Available online: Accessed 08/2/ Ibid. 50 Amnon Bar-Ilan, Rajashi Parikh, John Grant, Tejas Shah, Alison K. Pollack, ENVIRON International Corporation. Nov. 13, Recommendations for Improvements to the CENRAP States Oil and Gas Emissions Inventories. Novato, CA. p. 48. Available online: Accessed 07/30/

38 Production: Once the product is collected from the well, emissions may be released at well sites from compressors, flares, heaters, and pneumatic devices. There can also be significant emissions from equipment leaks, storage tanks, and loading operations fugitives. Trucks are also a source of emissions during production as they are often used to transport product to processing facilities and refineries. Midstream Sources: Midstream sources in the Eagle Ford consist mostly of compressor stations and processing facilities, but other sources can include cryogenic plants, saltwater disposal facilities, tank batteries, and other facilities. The most significant emissions from compressors stations are usually from combustion at the compressor engines or turbines. Other emissions sources may include equipment leaks, storage tanks, glycol dehydrators, flares, and condensate and/or wastewater loading. Processing facilities generally remove impurities from the natural gas, such as carbon dioxide, water, and hydrogen sulfide. These facilities may also be designed to remove ethane, propane, and butane fractions from the natural gas for downstream marketing. Processing facilities are usually the largest emitting natural gas-related point sources including multiple emission sources such as, but not limited to equipment leaks, storage tanks, separator vents, glycol dehydrators, flares, condensate and wastewater loading, compressors, amine treatment and sulfur recovery units. 51 The AACOG emission inventory for Eagle Ford Shale did not include emissions associated with construction of mid-stream facilities, building offices, quarrying of fracturing sands, pipeline construction, etc. Generators and other equipment at camp houses and offices used by oil field workers were also not part of the emission inventory. Table 6-1 shows a list of emission sources for each phase of operation for counties of Atascosa and Wilson. Mud and hydraulic fracturing storage ponds were not included in the emission inventory because of insufficient data on emission factors. Emission sources outside of the Eagle Ford shale region that are directly or indirectly affected by the shale development were not included. The emission inventory did not include trucks that bring supplies to midstream sources, worker camps, and other facilities not located at the well head. Emissions from the production of cement, steel pipes, and other non-recycled material are not included in the emission inventory. The emission inventory excludes emissions from railroad activity related to Eagle Ford development. Railroads carry fracturing sands, pipelines, petroleum products, equipment, building materials, and other supplies to production sites in the Eagle Ford. Emissions for equipment used in various phases of operation were calculated for a low future development for counties of Wilson and Atascosa, and shown in the Table Eastern Research Group Inc. July 13, Fort Worth Natural Gas Air Quality Study Final Report. Prepared for City of Fort Worth, Fort Worth, Texas. p Available online: Accessed 08/02/

39 Table 6-1: Operational Phases and Associated Sources of Emissions Operation Phase Exploration & Pad Construction Drilling Operation Hydraulic Fracturing and Completion Operation Production Mid-stream Sources Emission Sources seismic trucks non-road equipment used for pad construction heavy duty trucks light duty trucks electric drill rigs mechanical drill rigs other non-road equipment used during drilling heavy duty trucks light duty trucks pump trucks other non-road equipment used during hydraulic fracturing heavy duty trucks light duty trucks completion venting completion flares wellhead compressors heaters flares dehydrators flash vessels and regenerator vents storage tanks fugitives (leaks) loading fugitives well blowdowns pneumatic devices heavy duty trucks light duty trucks compressor station production facilities other mid-stream sources 6-4

40 Table 6-2: Eagle Ford Emissions by Operation Phase by Emission Source for Low Future Development Scenario, tons/day Operation Phase Emission Sources Low 2020 Low 2023 Low Atascosa Wilson Atascosa Wilson Atascosa Wilson Atascosa Wilson VOC NO X VOC NO X VOC NO X VOC NO X VOC NO X VOC NO X VOC NO X VOC NO X Exploration & Pad Construction Drilling Operation Hydraulic Fracturing and Completion Operation seismic trucks non-road equipment heavy duty trucks light duty trucks electric drill rigs mechanical drill rigs other non-road equipment heavy duty trucks light duty trucks pump trucks other non-road equipment heavy duty trucks light duty trucks completion flare

41 Operation Phase Production Mid-stream Sources Emission Sources wellhead compressors heaters flares dehydrators vents storage tanks fugitives (leaks) loading fugitives well blowdown pneumatic devices heavy duty trucks light duty trucks Low 2020 Low 2023 Low Atascosa Wilson Atascosa Wilson Atascosa Wilson Atascosa Wilson VOC NO X VOC NO X VOC NO X VOC NO X VOC NO X VOC NO X VOC NO X VOC NO X TOTAL

42 6.1 Sources of Data A variety of data sources were used to estimate emissions from oil and gas production in Eagle Ford shale. Whenever possible, locally conducted surveys and existing local data were used for emissions calculation and projection. Counts of drill rigs and number of wells drilled were extracted from Schlumberger and Baker Hughes databases. Well characteristics and production amounts were downloaded from the Railroad Commission of Texas website. Emissions from Non-road equipment were calculated using results of AACOG s survey of drill rig and hydraulic pumps, as well as local industry data, emission factors from ERG s Statewide Drilling Rigs Emission Inventories for the Years 1990, 1993, 1996, and 1999 through 2040, 52 TexN model, equipment manufacturers, TCEQ, and the results from Texas Center for Applied Technology s (TCAT) Eagle Ford Survey. Emissions from Compressor engines were calculated based on the findings of final survey results of Barnett Shale Special Inventory conducted by TCEQ. Emission calculations for Production phase relied on final results of TCEQ s Barnett Shale special inventory. Other sources for Production phase included data from local oil companies, TCEQ s pneumatic device survey, ERG s Texas emission inventory, ENVIRON s CENRAP emission inventory, and original AP42 emission factors for flares; data sources for on-road emissions are the NCTCOG s study in the Barnett Shale, TxDOT s study also in the Barnett Shale, TxDOT s traffic count data in the Eagle Ford area, and ENVIRON s report for oil and gas exploration in state of Colorado. Emission factors for heavy duty and light duty trucks were produced by applying the EPA s MOVES2014 model. 52 Eastern Research Group, Inc., August 15, Development of Texas Statewide Drilling Rigs Emission Inventories for the Years 1990, 1993, 1996, and 1999 through TCEQ Contract No Austin, Texas. Available online: ergi-drilling_rig_ei.pdf. Accessed 10/24/

43 Table 6-3: Data Sources for Eagle Ford Emission Inventory Operation Phase Source Category Activity Emission Factor Exploration and Pad Construction Exploration and Pad Construction Drilling Seismic Trucks Construction Eq. Heavy Duty On-Road Vehicles Heavy Duty Idling Vehicles Light Duty On-Road Vehicles Light Duty Idling Vehicles Mechanical Drill Rigs Number of Trucks: Marathon Oil Corporation Horsepower: Equipment Manufacturers Activity Rate: Marathon Oil Corporation Load Factor: TexN Model Equipment Population: Aerial Imagery Horsepower: San Juan Inventory (Colorado) Activity Rate: San Juan Inventory (Colorado) Load Factor: TexN Model Number of wells per well pad: RRC of Texas Vehicle Type: TxDOT Traffic Counts Number of Vehicles: TxDOT (Barnett) Distance Traveled: NCTCOG (Barnett) Diurnal Profiles: TxDOT Traffic Counts Number of wells per well pad: RRC of Texas Vehicle Type: TxDOT Traffic Counts Number of Vehicles: TxDOT (Barnett) Hours Idling: ENVIRON Colorado Report Number of wells per well pad: RRC of Texas Number of Vehicles: ENVIRON Colorado Report Distance Traveled: Railroad Commission of Texas Diurnal Profiles: TxDOT Traffic Counts Number of wells per well pad: RRC of Texas Number of Vehicles: ENVIRON Colorado Report Hours Idling: ENVIRON Colorado Report Number of wells per well pad: RRC of Texas Total Depth Drilled: Schlumberger Limited, Percentage of time Drill rigs are mobilized: Oil and Gas Financial Journal Length of Laterals: RRC of Texas Number of Laterals per well: RRC of Texas Number of Drill rigs: Baker Hughes TexN Model TexN Model MOVES2014 Model MOVES2014 Model MOVES2014 Model MOVES2014 Model ERG Drill Rig EI 6-1

44 Operation Phase Source Category Activity Emission Factor Drilling Electric Drill Rigs Non-Road Eq. used during Drilling Heavy Duty On-Road Vehicles Percentage of Electric Drill Rigs: Eagle Ford Emission Inventory Survey Total Depth Drilled: Schlumberger Limited, Percentage of time Drill rigs are mobilized: Oil and Gas Financial Journal Length of Laterals: RRC of Texas Number of Laterals per well: RRC of Texas Drill rig Population: Baker Hughes Percentage of Electric Drill Rigs: Eagle Ford Emission Inventory Survey Number of Engines per Drill Rig: Eagle Ford Survey and other local industry data Horsepower: Eagle Ford Survey and other local industry data Load Factor: TexN Model Tier profile for Drill rigs: Eagle Ford Survey Number of Equipment: Eagle Ford survey and other local data Horsepower for cement pumps: Local data Horsepower for cranes, loaders, and forklifts: TexN model Total Depth Drilled: Schlumberger Limited Percentage of time each equipment operates: Eagle Ford survey Percentage of time Drill rigs are mobilized: Oil and Gas Financial Journal Length of Laterals: RRC of Texas Number of Laterals per well: RRC of Texas Load Factor: TexN Model Vehicle Type: TxDOT Traffic Counts Number of Vehicles: NCTCOG (Barnett) Distance Traveled: NCTCOG (Barnett) Diurnal Profiles: TxDOT Traffic Counts Number of wells per well pad: RRC of Texas TCEQ TERP program TexN Model EPA Caterpillar TexN Model MOVES2014 Model 6-2

45 Operation Phase Source Category Activity Emission Factor Hydraulic Fracturing and Completion Heavy Duty Idling Vehicles Light Duty On-Road Vehicles Light Duty Idling Vehicles Pump Trucks Other Non-Road Eq. used during Fracturing Heavy Duty On-Road Vehicles Heavy Duty Idling Vehicles Vehicle Type: TxDOT Traffic Counts Number of Vehicles: NCTCOG (Barnett) Hours Idling: ENVIRON Colorado Report Number of wells per well pad: RRC of Texas Number of Vehicles: ENVIRON Colorado Report Distance Traveled: Railroad Commission of Texas Diurnal Profiles: TxDOT Traffic Counts Number of wells per well pad: RRC of Texas Number of Vehicles: ENVIRON Colorado Report Hours Idling: ENVIRON Colorado Report Number of wells per well pad: RRC of Texas Number of Generators: Local aerial imagery Horsepower: Eagle Ford Survey Activity Rate: ENVIRON (Haynesville) Load Factor: Local industry data Tier profile for generators: Eagle Ford Survey Eagle Ford Emission Inventory Survey Equipment Population: TCAT Survey Horsepower: TCAT Survey Activity Rate: ENVIRON (Haynesville) Percentage of time equipment operates: Eagle Ford survey Load Factor: TexN Model Vehicle Type: TxDOT Traffic Counts Number of Vehicles: TxDOT (Barnett) Distance Traveled: NCTCOG (Barnett) Diurnal Profiles: TxDOT Traffic Counts Number of wells per well pad: RRC of Texas Vehicle Type: TxDOT Traffic Counts Number of Vehicles: NCTCOG (Barnett) Hours Idling: ENVIRON Colorado Report Number of wells per well pad: RRC of Texas MOVES2014 Model MOVES2014 Model MOVES2014 Model TCEQ TERP program, TexN Model, EPA, and Caterpillar TexN Model MOVES2014 Model MOVES2014 Model Light Duty Vehicles Number of Vehicles: ENVIRON Report state for Colorado MOVES2014 Model 6-3

46 Operation Phase Source Category Activity Emission Factor Production Light Duty Idling Vehicles Completion Flares Wellhead Compressors Heaters Wellhead Flares Dehydrators Storage Tanks Fugitives from Natural Gas Wells Distance Traveled: RRC of Texas Diurnal Profiles: TxDOT Traffic Counts Number of wells per well pad: RRC of Texas Number of Vehicles: ENVIRON Colorado Report Hours Idling: ENVIRON Colorado Report Number of wells per well pad: RRC of Texas Volume of Gas: ENVIRON Western Gulf Basin Heat Content: ENVIRON Western Gulf Basin Percentage of Wells Controlled by Flares: Local data Percentage of Wells Serviced by a Compressor: Final Results from Barnett Shale Special Inventory Engine Type: Final Results from Barnett Shale Special Inventory Horsepower: Final Results from Barnett Shale Special Inventory Activity Rate: Final Results from Barnett Shale Special Inventory Percentage of Wells with Heaters: ERG Texas EI Heater Rating: ERG Texas EI Activity Rate: ERG Texas EI Natural Gas Heating Value: ERG Texas EI Volume of Gas Flared: RRC of Texas Heating Value: ENVIRON Western Gulf Basin Percentage of Tanks with Controls: ERG s condensate tank study Control Efficiency: ERG s condensate tank study NA MOVES2014 Model Original AP42 Final Results from Barnett Shale Special Inventory ENVIRON CENRAP EI (Western Gulf) TexN Model California Air Resources Board ENVIRON s CENRAP emission inventory in the Western Gulf Basin TCEQ Original AP42 ERG Texas EI ERG Texas EI and ERG s condensate tank study Final Results from Barnett Shale Special Inventory 6-4

47 Operation Phase Source Category Activity Emission Factor Fugitives from Oil Wells Loading Loss Blowdowns Pneumatic Devices Heavy Duty On-Road Vehicles Heavy Duty Idling Vehicles Light Duty On-Road Vehicles Light Duty Idling Vehicles NA ERG Texas EI Temperature Data: NOAA Molecular Weight: AP42 Volume of Gas Vented: ENVIRON s CENRAP emission inventory Molecular Weight: ENVIRON CENRAP EI (Western Gulf) Number of Blowdowns per Well: ENVIRON s CENRAP emission inventory Fraction of Blowdowns Controlled by Flares: ENVIRON s CENRAP emission inventory Control Efficiency of Flaring during Blowdowns: ENVIRON s CENRAP emission inventory Fraction of Blowdowns Controlled by Green Techniques: ENVIRON s CENRAP emission inventory Vehicle Type: TxDOT Traffic Counts Number of Vehicles: NCTCOG (Barnett) Distance Traveled: NCTCOG (Barnett) Diurnal Profiles: TxDOT Traffic Counts Number of wells per well pad: RRC of Texas Vehicle Type: TxDOT Traffic Counts Number of Vehicles: NCTCOG (Barnett) Hours Idling: ENVIRON Colorado Report Number of wells per well pad: RRC of Texas Number of Vehicles: ENVIRON Colorado Report Distance Traveled: RRC of Texas Diurnal Profiles: TxDOT Traffic Counts Number of wells per well pad: RRC of Texas Number of Vehicles: ENVIRON Colorado Report Hours Idling: ENVIRON Colorado Report AP42 ERG s Texas emission inventory TCEQ Pneumatic Survey MOVES2014 Model MOVES2014 Model MOVES2014 Model MOVES2014 Model 6-5

48 Operation Phase Source Category Activity Emission Factor Midstream Compressor Stations, Production facilities, etc. Number of wells per well pad: RRC of Texas Equipment Counts: TCEQ Standard Permit Database Final Results from Barnett Shale Special Inventory TCEQ Standard Permit Database 6-6

49 6.2 Eagle Ford On-Road Vehicle Emission Factors Since local data was not available for Eagle Ford activities, the number of trips by vehicle type and the length of idling time per vehicle trip were taken from TxDOT s findings in the Barnett Shale and ENVIRON s report on the Piceance Basin of Colorado. These reports were selected because the TxDOT report provided data from well pad construction in a similar area in Texas and ENVIRON s report is the only one with specific data on idling rates. TxDOT collected short term traffic count data during May 2012 in districts that are being impacted by oil, gas, and wind energy expansion activities. 53 Traffic count data was collected in the Eagle Ford from the TxDOT districts of Corpus Christi, Laredo, Pharr, San Antonio, and Yoakum. Most of the 15 minute traffic counts were collected over one or two days. The data collected included data hourly counts by vehicle classification for each traffic lane at the 16 sites used in this study. TxDOT collected traffic count data at 10 additional sites, but the data for these sites was not used for this study because the sites were not located in the Eagle Ford or were on major highways. The traffic count data was collected by TxDOT using the Federal Highway Administration s (FHWA) 13-bin vehicle classification system. 54 The FHWA bin classifications were converted to MOVES2014 Source Type ID, as shown in Table 6-4, to calculate on-road emission factors. The vehicle types included in the on-road emissions calculations were either passenger trucks or short-haul trucks because trucks operating in the Eagle Ford travel short distances and passenger cars do not have the capability to drive on well pad sites. 53 Lorri Pavliska, Texas Department of Transportation, SAT District. San Antonio, Texas. 54 Federal Highway Administration (FHWA), Nov Introduction to the LTPP Information Management System (IMS). FHWA-RD Available online: Accessed 07/14/

50 Table 6-4: TxDOT Traffic Counts Converted to MOVES2014 Source Type ID, May 2012 Vehicle Type FHWA Vehicle Class Average Traffic Counts (all sites) MOVES Source Type ID Fuel Type Percentage Motorcycles Passenger cars 2 23,880 Not Used Other 2-axle, 4-tire single-unit 31 (Passenger Gasoline and 3 52,200 vehicles Truck) Diesel 100.0% Buses Not Used 2-axle, 6-tire single-unit trucks 5 3, (Single 3-axle single-unit trucks 6 2,410 Unit Shorthaul Diesel 19.5% 4- or more axle single-unit trucks Truck) 4- or less axle single-trailer trucks 8 2,641 5-axle single-trailer trucks 9 17, or more axle single-trailer trucks 10 1, or less axle multi-trailer trucks 11 1,222 6-axle multi-trailer trucks or more axle multi-trailer trucks 13 1, (Combination Short-haul Truck) Diesel 80.5% Eagle Ford EI Vehicle Classification Employees and Supplies Equipment 6-8

51 EPA s MOVES2014 model was used to estimate emissions from vehicles while idling or transporting employees, equipment, and materials to the oil fields for 2012 through For climate and transportation inputs, all MOVES s default data was used with the exception of the vehicle speed table which had been modified for an average speed of 35 miles per hour. Similar to the Pinedale Anticline Project in Wyoming, an average speed of 35 miles per hour was used for both on-road vehicle types because the 25 miles per hour speed used in other studies is too slow for rural areas typical of the Eagle Ford. Table 6-5: Ozone Season Emission Factors for On-road Vehicles in Eagle Ford Counties Vehicle Type VOC NO X VOC NO X VOC NO X VOC NO X Heavy Duty Truck Exhaust(g/mil) Heavy Duty Truck Idling(g/hour) Light Duty Truck Exhaust(g/mil) Light Duty Truck Idling(g/hour) The on-road VOC and NO X exhaust and idling emissions for vehicles were calculated using the formulas described below. The various parameters of these formulas come from collected local data, the MOVES2014 model s emission factors, TxDOT s databases, and data from the survey conducted by ENVIRON in Colorado. Heavy duty vehicle trip lengths were set at 50 miles, since this is similar to data collected by NCTCOG. 55 NO X emission reductions from the use of TxLED diesel fuel were taken into account; according to TCEQ, TxLED requirements are intended to result in reductions in NO X emissions from diesel engines. Currently, reduction factors of 5.7% (0.057) for on-road use and 7.0% (0.07) for non-road use have been accepted as a NO X reduction estimate resulting from use of TxLED fuel. 56 Equation 6-1, Daily on-road emissions during pad construction E pad.road.abc = NUM BC x TRIPS A.TXDOT x (DIST B.RCC x 2) x (1 - TxLED TCEQ ) x OEF A.MOVES / WPAD B.RCC / 907, grams per ton / 365 days/year 55 Lori Clark, Shannon Stevenson, and Chris Klaus North Central Texas Council of Governments, August Development of Oil and Gas Mobile Source Inventory in the Barnett Shale in the 12-County Dallas-Fort Worth Area. Arlington, Texas. Texas Commission on Environmental Quality Grant Number: pp. 11, 13. Available online: Accessed 07/12/ TCEQ, July 24, Texas Emissions Reduction Plan (TERP) Emissions Reduction Incentive Grants Program. Austin, Texas. Available online: Accessed 8/27/

52 Where, E pad.road.abc NUM BC = Ozone season day NO X or VOC emissions from type A on-road vehicles in county B for Eagle Ford development type C wells (Gas or Oil) = Annual number of wells drilled in county B for Eagle Ford development type C wells (from Schlumberger Limited) TRIPS A.TXDOT = Annual number of trips for vehicle type A per pad, 70 for heavy duty trucks (from TxDOT s Barnett report) and for light duty trucks for equipment, and 69.6 light duty trucks for employees (from ENVIRON s Colorado report) DIST B.RCC = Distance, 25 miles (25 miles one way, 50 miles per round trip) for heavy duty trucks and to the nearest town for light duty vehicles in county B (from Railroad Commission of Texas) TxLED TCEQ = On-road emission reductions from TxLED, for NO X from Heavy Duty Diesel Trucks, 0.0 for VOC, and 0.0 for Gasoline Light Duty Vehicles (from TCEQ) OEF A.MOVES = NO X or VOC on-road emission factor for vehicle type A in Table 6-5 (from MOVES2014 Model) WPAD B.RCC = Number of wells per pad for county B (calculated from data provided by the Railroad Commission of Texas) Sample Equation: 2012 Wilson County NO X emissions for Heavy Duty Truck Exhaust during the construction of oil well pads E pad.road.abc = 35 oil wells x 70 trips x (25 miles x 2) x ( ) x g/mile / wells per well pad / 907, grams per ton / 365 days/year = tons of NO X per ozone season day from heavy duty truck exhaust in Wilson County during the construction of oil well pads, 2012 Equation 6-2, Ozone season day idling emissions during pad construction E pad.idling.abc = NUM BC x TRIPS A.TXDOT x IDLE A x (1 - TxLED TCEQ ) x IEF A.EPA / WPAD BC.RCC / 907, grams per ton / 365 days/year Where, E pad.idling.abc = Ozone season day NO X or VOC emissions from idling vehicles in county B for Eagle Ford development type C wells (Gas or Oil) NUM BC = Annual number of wells drilled in county B for Eagle Ford development type C wells (from Schlumberger Limited) TRIPS A.TXDOT = Annual number of trips for vehicle type A per pad, 70 for heavy duty trucks (from TxDOT s Barnett report), for light duty trucks for equipment, and 69.6 light duty trucks for employees (from ENVIRON s Colorado report) IDLE A = Number of idling hours/trip for vehicle type A, 0.4 hours for heavy duty trucks, 2.0 for light duty trucks for equipment, and 2.15 light duty trucks for employees (from ENVIRON s Colorado report) TxLED TCEQ = On-road emission reductions from TxLED, for NO X from Heavy Duty Diesel Trucks, 0.0 for VOC, and 0.0 for Gasoline Light Duty Vehicles (from TCEQ) IEF A.EPA = NO X or VOC idling emission factor for vehicle type A in Table 6-5 (from EPA based on the MOVES model) WPAD B.RCC = Number of wells per pad for county B (calculated from data provided by the Railroad Commission of Texas) 6-10

53 Sample Equation: 2012 NO X emissions from Heavy Duty Truck Idling in Wilson County during the construction of oil well pads E pad.road.abc = 35 oil wells x 70 trips x 0.4 hours idling x ( ) x g/hour / wells per well pad / 907, grams per ton / 365 days/year = tons of NO X per ozone season day from heavy duty truck idling in Wilson County during the construction of oil well pads Emissions from Non-Road Equipment and Area Sources Emissions associated with area sources and non-road equipment were calculated using data collected from local industry, emission factors from the TexN model, manufacturers information, TCEQ, and the results of surveys conducted by the Texas Center for Applied Technology (TCAT). Existing data in the TexN Model was used to calculate emission factors for non-road equipment, although default horsepower ratings were replaced with horsepower inputs that matched equipment used in the Eagle Ford. Counts of drill rigs operating in the Eagle Ford and number of wells drilled were provided by Schlumberger Limited. 57 Similarly, well characteristics and production data were collected from Schlumberger and the Railroad Commission of Texas 58. The following equation was used to calculate emissions from non-road equipment Equation 6-3, Ozone season day seismic trucks emissions E Seismic.BC = (NUM BC / WPAD B ) x POP x HP x HRS x LF TexN x EF TexN / 907, grams per ton / 365 days/year Where, E Seismic.BC NUM BC WPAD B POP HP HRS LF TexN EF TexN = Ozone season day NO X or VOC emissions from seismic trucks in county B for Eagle Ford development type C wells (gas or oil) = Annual number of wells drilled in county B for Eagle Ford development type C wells, (from Schlumberger Limited) = Number of wells per pad for county B, (calculated from data provided by the Railroad Commission of Texas) = Number of seismic trucks, 3 (from Marathon Oil Corporation in the Eagle Ford) = Average horsepower seismic trucks, 400hp (based on average hp of seismic trucks from Equipment Manufactures) = Hours per pad construction, 2 hours per well pad (from Marathon Oil Corporation in the Eagle Ford) = Load factor for off road trucks, 0.59 (from TexN Model) = Emission factor for off road trucks, g/hp-hr for NO X for TxLED Counties, g/hp-hr for NO X for non-txled Counties, g/hp-hr for VOC, or g/hp-hr for CO (from TexN Model) Sample Equation: 2012 NO X emissions from seismic trucks in Wilson County for Oil Wells E Pad.ABC = (35 oil wells /1.225 wells per well pad) x 3 seismic trucks x 400 hp x 2 hours x 0.59 x grams of NO X /hp-hr / 907, grams per ton / 365 days/year 57 Schlumberger Limited. STATS Rig Count History. Available online: Accessed: 04/21/ Railroad Commission of Texas, April 3, Eagle Ford Information. Austin, Texas. Available online Accessed: 05/01/

54 = tons of NO X /ozone season day from seismic trucks in Wilson County for oil wells, Projected Emission Data VOC and NO X emissions were projected using the latest information extracted from published studies, local data, and regional data. Projections of future activities in the Eagle Ford were completed using a methodology similar to what ENVIRON used in development of the Haynesville Shale emission inventory, which was based on three growth scenarios: low development, moderate development, and high development. 59 Projected emissions are derived by the drilling activity in the region and production estimations for each well. Since hydraulic fracturing of oil reserves on a wide scale is relatively new occurrence, activity and emission projections will have a high uncertain factor. The Railroad Commission of Texas June 2014 adjustment factors of for oil wells and for gas well applies only to preliminary statewide totals for that month and is not used to adjust production totals in the Eagle Ford. 60 The number of drill rigs operating in the Eagle Ford, increased from 56 in January 2010 to 196 rigs in August By using the estimate annual change in the number of drill rigs, three different scenarios were developed and used to estimate future rig counts: Low Development: Decrease of 10 rigs per year Moderate Development: The number of drill rigs remain the same Aggressive Development: Increase of 10 rigs per year The following equation was used to estimate the number of new rigs for each year between 2012 and Equation 6-4, Total number of drill rigs for each projection year RPROJ B = (RCUR A ) + [RNEW x (YEAR B - YEAR A )] Where, RPROJ B = Number of drill rigs for Year B RCUR A = Number of current drill rigs in Year A, 197 for August 2014 (from Baker Hughes) RNEW = Increase in the number of drill rigs each year under each scenario (-10 rigs for Low, 0 rigs for Moderate, 10 rigs for Aggressive Development with a cap of 225 rigs total) YEAR B = Projection year B, June John Grant, Lynsey Parker, Amnon Bar-Ilan, Sue Kemball-Cook, and Greg Yarwood, ENVIRON International Corporation. August 31, Development of an Emission Inventory for Natural Gas Exploration and Production in the Haynesville Shale and Evaluation of Ozone Impacts. Novato, CA. p. 13. Available online: Accessed: 04/19/ Ibid. 61 Baker Hughes. Interactive US Rig Counts. Available online: Accessed 08/08/

55 YEAR A = Base year A, August 2014 Sample Equation: Number of drill rigs operating in the Eagle Ford under the low scenario for 2018 RPROJ B = (196 drill rigs operating in August 2014) + [-10 annual reduction under the low scenario x (July 2018 August 2014)] = 157 drill rigs operating in the Eagle Ford under the low scenario in 2018 The Eagle Ford low growth scenario was used for 2018 through Input data such as number of wells, equipment population, HP, hours, and load factor from the 2018 moderate growth scenario were used with growth factors from the TexN model, EPA, and TCEQ to calculate emissions in 2020 and input data from 2018 aggressive or high development were used to project 2023 emissions. 6.5 Total Eagle Ford Counties Emissions Summary Emissions from the various oil and gas exploration phases described above were calculated based on emission factors for each piece of equipment, projected level of activities associated with number of wells that will be drilled, and the anticipated productivity level of these wells. The calculated emissions are shown in the Table 6.5. Table 6-6: Eagle Ford Shale Emissions within San Antonio-New Braunfels MSA, ton/ozone season weekday County Atascosa Operation Phase Exploration/Pad Construction VOC NO X VOC NO X VOC NO X VOC NO X Drilling Hydraulic Fracturing Production Midstream Wilson Exploration/Pad Construction Drilling Hydraulic Fracturing Production Midstream TOTAL

56 7 On-Road Source Emissions On-road source emissions are produced during the operation of vehicles on urban and rural roadway networks. Due to the significantly adverse contribution of on-road sources to air quality, these emissions are regulated by the EPA and subject to certain standards. The onroad emissions for all 254 counties within the state of Texas are regularly estimated by the Texas Transportation Institute (TTI). TTI utilizes vehicle miles traveled (VMT) data, compiled by the Texas Department of Transportation (TxDOT), to estimate link-based and virtual-linkbased hourly emissions. The virtual-link-based network is based on the Highway Performance Monitoring System (HPMS) road network. The results are used both in the transportation conformity determination process and mobile source inventory development in support of the Federal Clean Air Act. In developing the current trend analysis, emission data for the years 1999 through 2002 were extracted from the TTI s previous report for on-road emissions inventory 62, and for the years 2006, 2012, and 2018 the latest trend emission inventories report for all of the 254 counties within the state of Texas was used. The 2020 and 2023 data were produced in-house using MOVES2014 model. In TTI s report, published in Dec. 2014, school days and summer season emissions have been produced for the four day types of Weekday, Friday, Saturday, and Sunday, and covered time periods comprise years of 2006, 2012, and Previous on-road emissions inventory development work for each Texas county was conducted with the 2010 versions of the Motor Vehicle Emission Simulator (MOVES2010a and MOVES2010b), the on-road model from the U.S. Environmental Protection Agency (EPA). The EPA s latest version of MOVES, MOVES2014 October release, incorporates significant changes to the emissions rates for each vehicle type. For the 2017-and-later calendar years, a substantial difference with MOVES2014 is the incorporation of new federal standards for Tier 3 light-duty vehicles and gasoline with a sulfur content of 10 parts per million (ppm). The currently available MOVES-based inventories incorporate 30 ppm sulfur gasoline and Tier 2 light-duty vehicle standards that began with the 2004 model year. 64 TTI used county-based historical TxDOT VMT data to forecast future years emissions using U.S. Census population statistics and projections and a methodology consistent with current practice for virtual link applications. Emissions from MOVES gasoline and diesel source use 62 TCEQ, July On-Road, Mobile Source Trend Emissions Inventories for All 254 Counties in Texas for TTI, College Station, Texas. p TTI, Dec. 2014, Production of Statewide Non-Link, On-Road Emissions Inventories with MOVES2014 for 2006, 2012, TX, College Station. 64 Ibid. p

57 types (SUT), shown in Table 7-1, were estimated. TTI used an hourly, Highway Performance Monitoring System (HPMS) virtual link, MOVES rates-per-activity emissions inventory method to produce hourly emissions estimates by MOVES source use type (SUT) and fuel type, pollutant, and pollutant process for all 254 Texas counties for each year, period, and day type. 65 Table 7-1: MOVES2014 Source Use Type Source Use Type Description Source Use Type ID Source Use Type Abbreviation Motorcycle 11 MC Passenger Car 21 PC Passenger Truck 31 PT Light Commercial Truck 32 LCT Intercity Bus 41 IBus Transit Bus 42 TBus School Bus 43 SBus Refuse Truck 51 RT Single Unit Short-Haul Truck 52 SUShT Single Unit Long-Haul Truck 53 SULhT Motor Home 54 MH Combination Short-Haul Truck 61 CShT Combination Long-Haul Truck 62 CLhT 7.1 Emissions Calculations For calculating on-road emissions relevant to the San Antonio-New Braunfels MSA the following were taken into account by TTI: 66 Modeled the MOVES pollutant processes of running exhaust, crankcase running exhaust, start exhaust, crankcase start exhaust, extended idle exhaust, crankcase extended idle exhaust, auxiliary power exhaust, evaporative permeation, evaporative fuel vapor venting, evaporative fuel leaks, brake wear, and tire wear. Used the latest available Highway Performance Monitoring System (HPMS) data from the Texas Department of Transportation (TxDOT) for each Texas county as the basis for 2006 and 2012 vehicle miles traveled (VMT) estimates; For the 2018 future year, projected the HPMS VMT for each county out to the designated future years based on expected growth trends in both vehicle travel and human population; For the 2006 base case, used hourly temperature, hourly humidity, and daily barometric pressure inputs, which were provided by TCEQ based on weather station data averaged from June 15 through August 15, 2006; 65 TTI, Dec. 2014, Production of Statewide Non-Link, On-Road Emissions Inventories with MOVES2014 for 2006, 2012, College Station, Texas. Available online: ftp://amdaftp.tceq.texas.gov/pub/mobile_ei/statewide/mvs/reports/. Accessed 02/04/ Ibid. 7-2

58 For the 2012 and 2018 future years, used hourly temperature, hourly relative humidity, and daily barometric pressure inputs, which were provided by TCEQ based on weather station data averaged from June 15 through August 15, 2012; Used VMT mixes corresponding to the 23 gasoline and diesel fuel combinations of source use type (SUT) from the MOVES model in accordance with the August 2009 Used the most recently available seasonal, day-of-week, and hour-of-day VMT adjustment factors to distinguish Monday through Thursday weekdays from Friday, Saturday and Sunday for both the school and summer seasons. Automatic traffic recorder (ATR) data collected by TxDOT may be used for these purposes; For the 2006 base case inventories, used the July 2006 Texas registration database queries as the basis for SUT age distribution and fuel engine fractions compatible with MOVES; For the 2012 base case inventories, used the July 2012 registration data queries from the Texas Department of Motor Vehicles (TxDMV) as the basis for SUT age distribution and fuel engine fractions compatible with MOVES. Prior to 2012, responsibility for managing this database was transferred from TxDOT to TxDMV; For the 2018 future year, used the latest available July queries of the TxDMV vehicle registration database, which were from July 2014; For all counties for the 2006 base case, used fuel property inputs from surveys of retail For all counties for both the 2012 base case and 2018 future year, used recent survey data (and for 2018, expected ethanol usage based on Renewable Fuel Standard) to estimate the ethanol portion of gasoline. Used MOVES individual fuel parameter inputs to model the Low Reid Vapor Pressure (RVP) gasoline control strategy for 95 counties in east Texas, consistent with Sections of TCEQ rules. For the 2006 and 2012 base cases, used actual historical estimates based on fuel survey data. Since specific data are were not available for these years, used available data for the closest calendar years; Post-processed the diesel vehicle NO, NO2, HONO, and NOx emission factors for the 110 east Texas counties subject to the Texas Low Emission Diesel (TxLED) program, consistent with Sections of the TCEQ rules. NO, NO2, HONO, and NOx adjustment factors were provided by TCEQ using reductions of 4.8 percent for 2002-and-newer model year vehicles, and 6.2 percent for 2001-and-older model year vehicles; Modeled the effects of all the federal motor vehicle control programs that are included as defaults in the MOVES model. 7-3

59 7.2 Estimation of Vehicle Miles Traveled TTI forecast VMT as a function of both annual historical HPMS AADT VMT and population projections. Adjustments were applied using seasonal day-type-specific activity factors, hourly distributions, and directional factors derived from other traffic data. 67 For estimating vehicle populations, a historical analysis year is defined as any year where actual TxDMV registration data and HPMS VMT data (used in developing population scaling factors) exists. Therefore, the 2006 analysis year was considered a historical year and the vehicle population estimates were based on the TxDMV registration data for the analysis year. Since the HPMS VMT data was not available for either 2012 or 2018, these analysis were considered future analysis years. For the future analysis years, the vehicle population estimates were based on the most recent year (2011) TxDMV registration data set for which HPMS VMT data exists and analysis year population scaling factors. 68 TTI post-processed the diesel vehicle NO, NO2, HONO, and NOx emission factors for the 110 east Texas counties subject to the Texas Low Emission Diesel (TxLED) program, consistent with Sections of the TCEQ rules. NO, NO2, HONO, and NOx adjustment factors were provided by TCEQ using reductions of 4.8 percent for 2002-and-newer model year vehicles, and 6.2 percent for 2001-and-older model year vehicles. 69 In the San Antonio-New Braunfels MSA, Atascosa, Bexar, Comal, Guadalupe, and Wilson counties are subject to the low RVP and TxLED rules. 7.3 Estimation of 2020 and 2023 On-road Emissions The EPA s MOVES2014 was run in-house for a summer weekday to determine vehicle-typebased emissions growth rates from the year 2018 to the years 2020, and 2023 according to the MOVES model s default database; the two years of 2020 and 2023 were needed for this emission trend study but were missing in the TTI s report. The growth rates were calculated based on the results of MOVES runs and then applied to the TTI-generated 2018 vehicle-typebased emissions to project them into future years of 2020 and Since it was intended to use the AACOG s locally produced idling emissions for this trend analysis, the idling emissions included in the TTI s 2018 emissions were removed from the totals for the Combination Long- Haul Trucks. The results of these projections are shown in detail in Appendix A. Equation 7-1: Projection of 2018 Emissions into 2020 or 2023 SWDEV AA2020 = (2018SWDEV AATTI SWDEVI AATTI ) x 2020SWDEV AA / 2018SWDEV AA / 907, grams/ton Where, 67 Ibid. p Ibid. p Ibid. p

60 SWDEV AA2020 = summer weekday VOC or NO X emissions for vehicle type A in county of A in SWDEV AATTI = summer weekday VOC or NO X emissions for vehicle type A in county of A in 2018 generated by TTI SWDEVIAATTI = summer weekday VOC or NO X idling emissions for vehicle type A in county of A in 2018 generated by TTI, used only for Source Type ID 62 in Table SWDEV AA = summer weekday VOC or NO X emissions for vehicle type A in county of A in 2020, MOVES SWDEV AA = summer weekday VOC or NO X emissions for vehicle type A in county of A in 2018, MOVES2014 Sample calculation, 2020 summer weekday NO X emissions for Bexar County for gasoline Passenger Cars: SWDEV AA2020 = ( grams of NO X for passenger cars in grams of NO X from extended Idling, passenger cars in 2018) * ( grams of NO X for passenger cars in 2020 / grams of NO X for passenger cars in 2018) / 907, grams/ton = 5.63 tons of NO X per a summer weekday 7.4 Combination Long Haul Trucks Extended Idling The Department of Transportation requires resting of 10 hours after every 11 hours driving for property-carrying commercial motor vehicle drivers. Truck drivers frequently use truck stops, and other facilities in the San Antonio area to rest and idle their engines when they need to cool or heat their cabins, or to keep their engine fluids warm. AACOG has conducted a survey of locations where long haul trucks stop for resting and recorded frequency and time of idling. Because no idling trucks were observed in Bandera and Wilson counties, no idling emissions were calculated for these counties. The emission factors for long haul trucks idling were determined using in-house MOVES2014 runs for the years 2012, 2018, 2020, and The MOVES2014 model generated total idling hours, as well as total emissions, for the long haul trucks for each county. Table 7-2 shows data generated by MOVES2014 model for counties included in AACOG s idling survey. This data helped calculate emission factors for each pollutant per each county in grams/hour. Dividing total emissions for each pollutant by total hours of idling, will achieve the emission factor for that pollutant. The following equation describes how these emission factors were calculated. Equation 7-2: County-based Idling Emission Factors by Year of Interest SWDEF A2020 = (2020SWDIE A2020 / SWDIH A2020 Where, SWDEF A2020 = summer weekday VOC or NO X emission factor for trucks in county of A in 2020 SWDIE A2020 = summer weekday VOC or NO X idling emissions for trucks in county of A in 2020 SWDIH A2020 = summer weekday VOC or NO X idling hours for trucks in county of A in

61 Sample calculation, 2020 summer weekday NO X emission factor for Bexar County : SWDEF A2020 = (5,372,276 grams of NO X for idling trucks in 2020 / 28,894 truck Idling hours 2020 = grams/hour of NO X per a summer weekday Calculated idling emission factors for all counties and all years of interest are shown in the Table 7-2. The idling emission factors were applied to the results of 2006 AACOG s idling survey to estimate future years idling emissions. The data shown in Table 7-4 is based on this survey. 7-6

62 Table 7-2: MOVES2014 Model Data Used for Calculating Emission Factors for Truck Idling Survey County Total Truck Idling Hours 2012 Emission, grams 2018 Emission, grams 2020 Emission, grams 2023 Emission, grams NO X VOC NO X VOC NO X VOC NO X VOC Atascosa 14,454 14,947 14,747 14,725 2,746, ,535 2,769, ,498 2,706, ,893 2,670, ,701 Bexar 28,319 29,285 28,894 28,849 5,451,978 1,341,192 5,497,232 1,137,357 5,372,276 1,055,838 5,300, ,133 Comal 3,136 3,269 3,226 3, , , , , , , , ,861 Guadalupe 16,749 17,320 17,089 17,062 3,222, ,214 3,249, ,660 3,175, ,449 3,132, ,717 Kendall 8,550 8,842 8,724 8,710 1,687, ,930 1,701, ,388 1,663, ,777 1,640, ,410 Medina 6,460 6,681 6,591 6,581 1,248, ,949 1,259, ,451 1,230, ,855 1,214, ,445 Table 7-3: Emission Factors for Counties in AACOG s Truck Idling Survey County 2012, grams/hour 2018, grams/hour 2020, grams/hour 2023, grams/hour NO X VOC NO X VOC NO X VOC NO X VOC Atascosa Bexar Comal Guadalupe Kendall Medina

63 Table 7-4: San Antonio-New Braunfels MSA Idling Emission Trend, tons/summer weekday County NO X VOC NO X VOC NO X VOC NO X VOC NO X VOC NO X VOC NO X VOC Atascosa Bexar Comal Guadalupe Kendall Medina Total Total On-road Emission Summary Application of MOVES model with local input data produces more accurate and SIP grade data. The 2018 data generated by TTI, included local data for the San Antonio-New Braunfels MSA. The TTI s emissions results for the years 1999, 2002, 2006, 2012, 2018, as well as projected emissions for 2020, and 2023, which, as described above, were based on the 2018 TTI s run, were added to the emissions associated with truck idling to determine the total emissions from on-road vehicles. The results are shown in Table 7-5 and Table 7-6. Notice the significant decreases in VOC and NO X emissions from 1999 to 2023, as on-road control strategies become fully utilized and older vehicles are replaced by newer vehicles. From 1999 to 2023, VOC emissions are expected to decrease by tons per day, whereas NO X emissions are expected to decrease by tons per day. In light of population and economic increases in the region in the past years, these emission reductions indicate significant achievement in implementation of the on-road control strategies. Table 7-5: San Antonio-New Braunfels MSA On-road VOC Emissions, ton/ozone season weekday County Atascosa Bandera Bexar Comal Guadalupe Kendall Medina Wilson Total

64 Table 7-6: San Antonio-New Braunfels MSA On-road NO X Emissions, ton/ozone season weekday County Atascosa Bandera Bexar Comal Guadalupe Kendall Medina Wilson Total

65 8 Summary The San Antonio-New Braunfels MSA emission trend analysis provide insight into historical and future emissions that may also serve as supplementary analysis to the modeling conducted for attainment demonstrations, or to support control strategy effectiveness evaluations. Information on the status of emissions in future years should assist local air quality planners in their attempt to meet federal air quality standards throughout the region. During the development of this trend analysis, all federal and state regulations currently in use or scheduled to be implemented by 2020 and 2023 were accounted for and integrated into the projected emissions calculations. 8.1 Population and Emissions Trends The following figure depicts the results of this emission trend analysis coupled with data on population growth. It indicates a general downward trend in total NO X and VOC emissions through 2018, despite continued predicted growth in the region s population and economic activities. After this point, NO X emissions are predicted to continue a downward trend through the year 2023, while VOC emissions are forecast to creep up to levels higher than This is indicative of the impact of air quality controls that mainly target NO X emissions reductions. The increase in VOC emissions estimates is attributed to the application of growth factors that account for predicted increases in population and economic activity levels, as the area source emissions appear to be contributing the most. Population forecasts used for construction of this line chart come from the Texas Water Development Board population projections for the San Antonio-New Braunfels MSA Texas Water Development Board Regional and 2017 State Water Plan Projections Data. Texas. Available online: Accessed 07/14/

66 Figure 8-1: Population vs. VOC and NO X Emissions Trend, San Antonio-New Braunfels MSA 8.2 Emission Trend by Emission Sources The results of this emission trend analysis for various studied years and emission sources are shown in table 8-1 and table 8-2. Emissions from Eagle Ford oil and gas activities are shown independently for better understanding of the impacts of these new sources of emissions. Table 8-1: San Antonio-New Braunfels MSA VOC Emissions by Source, tons/ozone season weekday Emission Source On-Road Non-Road Area Point Off-road Eagle Ford Shale Total

67 Table 8-2: San Antonio-New Braunfels MSA NO X Emissions by Source, tons/ozone season weekday Emission Source On-Road Non-Road Area Point Off-road Eagle Ford Shale Total Anthropogenic VOC emission totals by source category for each inventory year are provided in Figure 8-2. The largest source of anthropogenic VOC emissions in future years will be Area Source emissions followed by Eagle Ford Shale emissions. On-road and non-road emissions show a marked reduction between 1999 and the forecasted year of Changes in point source and off-road VOC emissions will not be significant in the coming years. Figure 8-2: VOC Emission Trend by Source, San Antonio-New Braunfels MSA, tons/ozone season weekday Anthropogenic NO X emissions by source category for each inventory year are shown in Figure 8-3. The two largest sources of NO X emissions on-road and point sources show the greatest reduction in NO X emissions between 1999 and This reduction is directly related to 8-3

68 improvements in motor vehicle emission controls and coal powered plants between 1999 and For the future years Point and Area sources will be significant sources of NO X emissions. Figure 8-3: NO X Emission Trend by Source, San Antonio-New Braunfels MSA, tons/ozone season weekday 8.3 Emission Trends by MSA Counties Although there are major sources of emissions in Atascosa, Comal, and Guadalupe counties, VOC and NO X emissions generated by emission sources in Bexar County account for the greatest share of the future total emissions in the San Antonio-New Braunfels MSA. The projections indicate that every county in the San Antonio-New Braunfels MSA will experience considerable reductions in NO X emissions in coming years (Tables 8-3 and 8-4). Figures 8-4 and 8-5 provide VOC and NO X emissions by county for each emission inventory year. Although Bexar County dominates the charts, there are also large sources of NO X emissions in Comal, Atascosa, and Guadalupe counties. All counties show a reduction in NO X emissions by