U.S. Department of the Interior

Bureau of Ocean Energy Management

Gulf of Mexico OCS Region

OCS EIS/EA

BOEM 2017-074

Gulf of Mexico OCS Lease Sale

Final Supplemental Environmental Impact Statement 2018

Volume II: Appendices A-E 

U.S. Department of the Interior

Bureau of Ocean Energy Management Gulf of Mexico OCS Region

OCS EIS/EA

BOEM 2017-074

Gulf of Mexico OCS Lease Sale

Final Supplemental Environmental Impact Statement 2018

Volume II: Appendices A-E 

Author

Bureau of Ocean Energy Management

Gulf of Mexico OCS Region

Published by

New Orleans

December 2017

Table of Contents iii

TABLE OF CONTENTS

Volume I

Page

EXECUTIVE SUMMARY ..................................................................................................................... vii

LIST OF FIGURES................................................................................................................................ ix

LIST OF TABLES................................................................................................................................xvii

ABBREVIATIONS AND ACRONYMS ................................................................................................. lvii

CONVERSION CHART ....................................................................................................................... lxi

1 THE PROPOSED ACTION............................................................................................................. 1-3

1.0 Introduction ........................................................................................................................... 1-3 

1.1 Purpose of the Proposed Action........................................................................................... 1-6 

1.2 Need for the Proposed Action............................................................................................... 1-7 

1.3 OCS Oil and Gas Program Planning and Decision Process................................................ 1-7

1.3.1 Prelease Process ..................................................................................................... 1-8 

1.3.2 Gulf of Mexico Postlease Activities .......................................................................... 1-9

1.4 The Decision To Be Made .................................................................................................. 1-10

1.5 Regulatory Framework........................................................................................................ 1-10

1.6 Other OCS Oil- and Gas-Related Activities........................................................................ 1-11

1.7 Other Pertinent Environmental Reviews or Documentation............................................... 1-11

1.8 Format and Organization of this Supplemental EIS ........................................................... 1-12

2 ALTERNATIVES INCLUDING THE PROPOSED ACTION ........................................................... 2-3

2.0 Introduction ........................................................................................................................... 2-3 

2.1 Supplemental EIS NEPA Analysis........................................................................................ 2-3 

2.2 Alternatives, Mitigating Measures, and Issues ..................................................................... 2-4

2.2.1 What are the Alternatives that BOEM is Considering for Each Proposed Lease 

Sale?......................................................................................................................... 2-5

2.2.1.1 Alternative A—Regionwide OCS Lease Sale (The Preferred 

Alternative)................................................................................................ 2-5 

2.2.1.2 Alternative B—Regionwide OCS Lease Sale Excluding Available 

Unleased Blocks in the WPA Portion of the Proposed Lease Sale 

Area........................................................................................................... 2-7 

2.2.1.3 Alternative C—Regionwide OCS Lease Sale Excluding Available 

Unleased Blocks in the CPA/EPA Portions of the Proposed Lease 

Sale Area .................................................................................................. 2-8 
iv 2018 Gulf of Mexico Supplemental EIS

2.2.1.4 Alternative D—Alternative A, B, or C, with the Option to Exclude 

Available Unleased Blocks Subject to the Topographic Features, 

Live Bottom (Pinnacle Trend), and/or Blocks South of Baldwin 

County, Alabama, Stipulations ................................................................. 2-9 

2.2.1.5 Alternative E—No Action ........................................................................ 2-11

2.2.2 What Other Alternatives and Deferrals Has BOEM Considered But Not 

Analyzed in Detail?................................................................................................. 2-12

2.2.3 What Types of Mitigating Measures Does BOEM Apply? ..................................... 2-13

2.2.3.1 Proposed Lease Mitigating Measures (Stipulations).............................. 2-14

2.2.3.2 Prelease Mitigating Measures (Stipulations) by Alternative................... 2-15

2.2.3.3 Postlease Mitigating Measures............................................................... 2-16

2.2.4 What are the Primary Topics and Resources Being Evaluated?........................... 2-17

2.2.4.1 Issues to be Analyzed............................................................................. 2-18

2.2.4.2 Issues Considered but Not Analyzed ..................................................... 2-19

2.3 Comparison of Impacts by Alternative................................................................................ 2-19

2.4 Summary of Impacts ........................................................................................................... 2-21

3 IMPACT-PRODUCING FACTORS AND SCENARIO.................................................................... 3-3

3.0 Introduction ........................................................................................................................... 3-3 

3.1 Routine Activities .................................................................................................................. 3-4

3.1.1 What Activities Routinely Occur as a Result of a Single Lease Sale? .................... 3-4

3.1.1.1 Exploration and Delineation...................................................................... 3-5 

3.1.1.2 Development............................................................................................. 3-6 

3.1.1.3 Production................................................................................................. 3-7 

3.1.1.4 Decommissioning and Removal Operations ............................................ 3-8

3.1.2 How Much and Where is Activity Expected to Occur as a Result of a 

Proposed Action? ................................................................................................... 3-10

3.1.2.1 Exploration Scenario............................................................................... 3-14

3.1.2.2 Development Scenario ........................................................................... 3-17

3.1.2.3 Production Scenario ............................................................................... 3-19

3.1.2.4 Decommissioning Scenario .................................................................... 3-22

3.1.2.5 Transportation Scenario ......................................................................... 3-23

3.1.3 Summary of Routine Impact Producing Factors .................................................... 3-24

3.2 Accidental Events ............................................................................................................... 3-31

3.2.1 What Events Might Accidentally Occur as a Result of Operations Following 

a Lease Sale?......................................................................................................... 3-31

3.2.1.1 Releases into the Environment............................................................... 3-31

3.2.1.2 Collisions................................................................................................. 3-32

3.2.1.3 Spill Response........................................................................................ 3-32

3.2.2 How Many Oil Spills Could Occur as a Result of a Proposed Lease Sale?.......... 3-32

3.2.3 What is the Response to Accidental Events? ........................................................ 3-39

3.2.4 Summary of Accidental Impact-Producing Factors................................................ 3-40
Table of Contents v 

3.3 Cumulative Impacts ............................................................................................................ 3-43

3.3.1 What Additional Activities, Not Considered a Part of a Proposed Action, 

has BOEM Considered?......................................................................................... 3-43

3.3.2 Summary of Cumulative Activities.......................................................................... 3-43

3.3.2.1 Cumulative OCS Oil and Gas Program Scenario................................... 3-43

3.3.2.2 Non-OCS Oil- and Gas-Related Impact-Producing Factors .................. 3-46

4 DESCRIPTION OF THE AFFECTED ENVIRONMENT AND IMPACT ANALYSIS ...................... 4-3

4.0 Overview ............................................................................................................................... 4-3

4.0.1 What Encompasses the Affected Environment for a Gulf of Mexico Lease 

Sale?......................................................................................................................... 4-6 

4.0.2 How are the Potential Environmental Consequences Determined?........................ 4-7

4.0.2.1 Routine Activities .................................................................................... 4-10

4.0.2.2 Accidental Events ................................................................................... 4-10

4.0.2.3 Cumulative Impacts ................................................................................ 4-10

4.0.2.4 Incomplete or Unavailable Information................................................... 4-11

4.0.2.5 Alternatives ............................................................................................. 4-13

4.0.2.6 Summary................................................................................................. 4-14

4.1 Air Quality............................................................................................................................ 4-15

4.1.1 Description of the Affected Environment................................................................ 4-19

4.1.2 Environmental Consequences ............................................................................... 4-27

4.1.2.1 Routine Activities .................................................................................... 4-31

4.1.2.2 Accidental Events ................................................................................... 4-35

4.1.2.3 Cumulative Impacts ................................................................................ 4-38

4.1.2.3.1 Impacts Assessment.............................................................. 4-44

4.1.2.4 Incomplete or Unavailable Information................................................... 4-58

4.1.2.5 Alternative A—Regionwide OCS Lease Sale (The Preferred 

Alternative).............................................................................................. 4-60

4.1.2.6 Alternative B—Regionwide OCS Proposed Lease Sale Excluding 

Available Unleased Blocks in the WPA Portion of the Proposed 

Lease Sale Area ..................................................................................... 4-60

4.1.2.7 Alternative C—Regionwide OCS Proposed Lease Sale Excluding 

Available Unleased Blocks in the CPA/EPA Portions of the Proposed 

Lease Sale Area ..................................................................................... 4-60

4.1.2.8 Alternative D—Alternative A, B, or C, with the Option to Exclude 

Available Unleased Blocks Subject to the Topographic Features, 

Live Bottom (Pinnacle Trend), and/or Blocks South of Baldwin 

County, Alabama, Stipulations ............................................................... 4-61

4.1.2.9 Alternative E—No Action ........................................................................ 4-61

4.2 Water Quality ...................................................................................................................... 4-61

4.3 Coastal Habitats.................................................................................................................. 4-67

4.3.1 Estuarine Systems (Wetlands and Seagrass/Submerged Vegetation)................. 4-67

4.3.2 Coastal Barrier Beaches and Associated Dunes................................................... 4-72
vi 2018 Gulf of Mexico Supplemental EIS

4.4 Deepwater Benthic Communities ....................................................................................... 4-77

4.5 Sargassum and Associated Communities.......................................................................... 4-84

4.6 Live Bottom Habitats........................................................................................................... 4-89

4.6.1 Topographic Features and Associated Communities ............................................ 4-91

4.6.2 Pinnacles and Low-Relief Features and Associated Communities ....................... 4-99

4.7 Fishes and Invertebrate Resources..................................................................................4-106

4.8 Birds ..................................................................................................................................4-113

4.9 Protected Species.............................................................................................................4-119

4.9.1 Marine Mammals..................................................................................................4-125

4.9.2 Sea Turtles ...........................................................................................................4-133

4.9.3 Beach Mice (Alabama, Choctawhatchee, Perdido Key, and St. Andrew)...........4-137

4.9.4 Protected Birds.....................................................................................................4-140

4.9.5 Protected Corals...................................................................................................4-143

4.10 Commercial Fisheries .......................................................................................................4-146

4.11 Recreational Fishing .........................................................................................................4-150

4.12 Recreational Resources....................................................................................................4-154

4.13 Archaeological Resources ................................................................................................4-158

4.14 Human Resources and Land Use.....................................................................................4-164

4.14.1 Land Use and Coastal Infrastructure ...................................................................4-164

4.14.2 Economic Factors.................................................................................................4-170

4.14.3 Social Factors (Including Environmental Justice)................................................4-174

4.14.3.1 Environmental Justice Determination...................................................4-180

4.15 Unavoidable Adverse Impacts of a Proposed Action .......................................................4-181

4.16 Irreversible and Irretrievable Commitment of Resources.................................................4-185

4.16.1 Coastal Habitats ...................................................................................................4-185

4.16.2 Biological Resources............................................................................................4-185

4.16.2.1 Threatened and Endangered Species..................................................4-185

4.16.2.2 Fish and Invertebrate Resources, Deepwater Benthic Communities, 

Commercial Fisheries, and Recreational Fishing.................................4-185

4.16.3 Archaeological Resources....................................................................................4-186

4.16.4 Oil and Gas Development ....................................................................................4-186

4.16.5 Loss of Human and Animal Life ...........................................................................4-186

4.17 Relationship Between the Short-Term Use of Man’s Environment and the 

Maintenance and Enhancement of Long-Term Productivity ............................................4-186

4.17.1 Short-Term Use....................................................................................................4-186

4.17.2 Relationship to Long-Term Productivity ...............................................................4-188

5 CONSULTATION AND COORDINATION...................................................................................... 5-3

5.0 Introduction ........................................................................................................................... 5-3 

5.1 Coastal Zone Management Act ............................................................................................ 5-3 

5.2 Endangered Species Act ...................................................................................................... 5-4 

5.3 Magnuson-Stevens Fishery Conservation and Management Act........................................ 5-5 

5.4 National Historic Preservation Act ........................................................................................ 5-5 
Table of Contents vii

5.5 Government-to-Government Tribal Consultation ................................................................. 5-7 

5.6 National Environmental Policy Act........................................................................................ 5-8

5.6.1 Development of the Proposed Action....................................................................... 5-8

5.6.1.1 Call for Information and Area ID Memorandum........................................ 5-8 

5.6.1.2 Notice of Intent to Prepare a Supplemental EIS....................................... 5-9

5.6.2 Development of the Draft Supplemental EIS ........................................................... 5-9

5.6.2.1 Scoping ..................................................................................................... 5-9 

5.6.2.2 Summary of Scoping Comments............................................................ 5-10

5.6.2.3 Additional Public Input Opportunities...................................................... 5-16

5.6.2.4 Cooperating Agencies ............................................................................ 5-16

5.6.2.5 Distribution of the Draft Supplemental EIS for Review and Comment... 5-17

5.6.3 Development of the Final Supplemental EIS ......................................................... 5-21

5.6.3.1 Major Differences Between the Draft and Final Supplemental EISs...... 5-21

5.6.3.2 Public Meetings....................................................................................... 5-22

5.6.3.3 Comments Received on the Draft Supplemental EIS and BOEM’s 

Responses .............................................................................................. 5-23

6 REFERENCES CITED ................................................................................................................... 6-3

7 PREPARERS.................................................................................................................................. 7-3

8 GLOSSARY .................................................................................................................................... 8-3 

KEYWORD INDEX................................................................................................................Keywords-3 

Volume II

LIST OF FIGURES................................................................................................................................ ix

LIST OF TABLES................................................................................................................................xvii

APPENDICES

Appendix A Cooperating Agency Memorandum of Agreement......................................... A-3

Appendix B Air Quality: WRF Model Performance ........................................................... B-1

Appendix C Air Quality: Emissions For The Cumulative And Visibility Impacts ............... C-1

Appendix D Air Quality: Cumulative and Visibility Impacts............................................... D-1

Appendix E Responses to Public Comments on the Draft Supplemental EIS.................. E-3

List of Figures ix

LIST OF FIGURES

Page

Figure 1. Proposed Regionwide Lease Sale Area Combining the Western, Central, and 

Eastern Planning Areas. ................................................................................................viii

Figure 2. Proposed Regionwide Lease Sale Area, Encompassing the Available Unleased 

Blocks within All Three Planning Areas ......................................................................... xii 

Figure 3. Proposed Lease Sale Area for Alternative B, Excluding the Available Unleased 

Blocks in the WPA..........................................................................................................xiii

Figure 4. Proposed Lease Sale Area for Alternative C, Excluding the Available Unleased 

Blocks in the CPA and EPA.......................................................................................... xiv 

Figure 5. Identified Topographic Features, Pinnacle Trend, and Baldwin County Stipulation 

Blocks in the Gulf of Mexico........................................................................................... xv 

Figure 1-1. Proposed Regionwide Lease Sale Area Combining the Western, Central, and 

Eastern Planning Areas. ............................................................................................... 1-5 

Figure 1-2. OCS Oil and Gas Program Development Process....................................................... 1-7 

Figure 2-1. Proposed Regionwide Lease Sale Area, Encompassing the Available Unleased 

Blocks within All Three Planning Areas ........................................................................ 2-6 

Figure 2-2. Proposed Lease Sale Area for Alternative B, Excluding the Available Unleased 

Blocks in the WPA......................................................................................................... 2-7 

Figure 2-3. Proposed Lease Sale Area for Alternative C, Excluding the Available Unleased 

Blocks in the CPA and EPA.......................................................................................... 2-9 

Figure 2-4. Identified Topographic Features, Pinnacle Trend, and Blocks South of Baldwin 

County, Alabama, Stipulation Blocks in the Gulf of Mexico........................................ 2-10

Figure 3-1. Phases of OCS Activity Resulting from a Single Proposed Lease Sale over 

50 Years........................................................................................................................ 3-5 

Figure 3-2. Offshore Subareas in the Gulf of Mexico.................................................................... 3-12

Figure 3-3. (A) Number of Exploration and Delineation Wells Drilled over the Course of a 

Proposed Action under Alternative A for 50 Years. (B, C) Location of Exploration 

Wells Drilled during the Entire 50-Year Period. .......................................................... 3-16

Figure 3-4. (A) Number of Production Structures and Service Vessels Operating over the 

Course of a Proposed Action under Alternative A for 50 Years. (B, C) Total 

Number of Platforms Installed in the Low and High Production Scenario by 

Water Depth. ............................................................................................................... 3-18

Figure 3-5. (A) Number of Production Wells Drilled over the Course of a Proposed Action 

under Alternative A for 50 Years. (B, C) Total Number of Development and 

Production Wells Drilled in the Low and High Production Scenario by Water 

Depth for Alternative A................................................................................................ 3-20

Figure 3-6. Total Oil and Gas Production (BOE) in the Gulf of Mexico in the Low and High 

Production Scenario by Water Depth. ........................................................................ 3-22

Figure 3-7. The Oil Spill Risk Analysis Model Process. ................................................................ 3-33
x 2018 Gulf of Mexico Supplemental EIS

Figure 4-1. Gulf of Mexico Region with the Planning Areas, Nonattainment Areas, and 

Class I and Sensitive Class II Areas........................................................................... 4-18

Figure 4-2. Year 2011 Gulfwide Emission Inventory Results for Total Platform and 

Non-Platform Criteria Pollutant Emissions (TPY)....................................................... 4-26

Figure 4-3. Year 2011 Gulfwide Emission Inventory Results for Total Platform and 

Non-Platform Greenhouse Gas Emissions (TPY) ...................................................... 4-26

Figure 4-4. 2011 Criteria Pollutant Emissions (TPY) from Platform Sources. .............................. 4-27

Figure 4-5. 2011 Greenhouse Gases (TPY) from Platform Sources............................................ 4-27

Figure 4-1. Overview of the Gulf of Mexico Region’s Cumulative and Visibility Impacts 

Assessment................................................................................................................. 4-40

Figure 4-7. Geographic Domain of the “Air Quality Modeling in the Gulf of Mexico” Region” 

Study. .......................................................................................................................... 4-42

Figure 4-8. Sargassum Loop System............................................................................................ 4-85

Figure 4-9. Lease Blocks Subject to the Topographic Features and Live Bottom 

(Pinnacle Trend) Stipulations...................................................................................... 4-90

Figure 4-10. Gulf of Mexico Protected Species’ Critical Habitats .................................................4-121

Figure 4-11. Economic Land Use Patterns ...................................................................................4-166

Figure 4-12. Population of BOEM’s Economic Impact Areas in the Gulf of Mexico. ....................4-176

Figure B-1. Location of the “Air Quality Modeling in the Gulf of Mexico Region” Study 

with Class I Areas and Platform Locations .................................................................. B-1 

Figure B-2. Ozone Nonattainment Areas in the Southeastern U.S................................................ B-2 

Figure B-3. Overview of the “Air Quality Modeling in the Gulf of Mexico Region” Study Tasks .... B-4 

Figure B-4. WRF 36-km CONUS (d01), 12-km SE Regional (d02), and 4-km Gulf of Mexico 

Region (d03) Domains. ................................................................................................ B-7 

Figure B-5. BOEM Gulf of Mexico OCS Region WRF 36-km METSTAT Wind Direction 

Performance for 2012. ............................................................................................... B-16

Figure B-6. BOEM Gulf of Mexico OCS Region WRF 36-km METSTAT Wind Speed 

Performance for 2012. ............................................................................................... B-16

Figure B-7. BOEM Gulfof Mexico OCS Region WRF 36-km METSTAT Temperature 

Performance for 2012. ............................................................................................... B-17

Figure B-8. BOEM Gulf of Mexico OCS Region WRF 36-km METSTAT Humidity 

Performance for 2012. ............................................................................................... B-17

Figure B-9. BOEM Gulf of Mexico OCS Region WRF 12-km METSTAT Wind Direction 

Performance for 2012. ............................................................................................... B-18

Figure B-10. BOEM Gulf of Mexico OCS Region WRF 12-km METSTAT Wind Speed 

Performance for 2012. ............................................................................................... B-18

Figure B-11. BOEM Gulf of Mexico OCS Region WRF 12-km METSTAT Temperature 

Performance for 2012. ............................................................................................... B-19

Figure B-12. BOEM Gulf of Mexico OCS Region WRF 12-km METSTAT Humidity 

Performance for 2012. ............................................................................................... B-19

Figure B-13. BOEM Gulf of Mexico OCS Region WRF 4-km METSTAT Wind Direction 

Performance for 2012. ............................................................................................... B-20
List of Figures xi

Figure B-14. BOEM Gulf of Mexico OCS Region WRF 4-km METSTAT Wind Speed 

Performance for 2012. ............................................................................................... B-20

Figure B-15. BOEM Gulf of Mexico OCS Region WRF 4-km METSTAT Temperature 

Performance for 2012. ............................................................................................... B-21

Figure B-16. BOEM Gulf of Mexico OCS Region WRF 4-km METSTAT Humidity 

Performance for 2012. ............................................................................................... B-21

Figure B-17. Wind Rose Locations for Port Isabel, TX (PTIT), Calcasieu, LA (CAPL), 

Gulfport, MS (KGPT), and Naples, FL (NPSF).......................................................... B-22

Figure B-18. 2012 WRF Wind Rose Compared to 2012 Observation Wind Rose from 

Gulfport, MS in 4-km Domain..................................................................................... B-23

Figure B-19. 2012 WRF Wind Rose Compared to 2012 Observation Wind Rose from 

Naples, FL in 4-km Domain ....................................................................................... B-24

Figure B-20. 2012 WRF Wind Rose Compared to 2012 Observation Wind Rose from 

Port Isabel, TX in 4-km Domain................................................................................. B-25

Figure B-21. 2012 WRF Wind Rose Compared to 2012 Observation Wind Rose from 

Calcasieu, LA in 4-km Domain................................................................................... B-26

Figure B-22. Vertical Profile Soundings Comparing the 4-km WRF to Upper-Air Observations 

Data for Brownsville, TX on August 3, 2012, and Key West, FL on January 4, 

2012, at 00 UTC......................................................................................................... B-28

Figure B-23. January 2012 PRISM Precipitation and WRF Precipitation, 4-km Domain............... B-31

Figure B-24. February 2012 PRISM Precipitation and WRF Precipitation, 4-km Domain ............. B-32

Figure B-25. March 2012 PRISM Precipitation and WRF Precipitation, 4-km Domain.................. B-33

Figure B-26. April 2012 PRISM Precipitation and WRF Precipitation, 4-km Domain .................... B-34

Figure B-27. May 2012 PRISM Precipitation and WRF Precipitation, 4-km Domain..................... B-35

Figure B-28. June 2012 PRISM Precipitation and WRF Precipitation, 4-km Domain.................... B-36

Figure B-29. July 2012 PRISM Precipitation and WRF Precipitation, 4-km Domain ..................... B-37

Figure B-30. August 2012 PRISM Precipitation and WRF Precipitation, 4-km Domain ................ B-38

Figure B-31. September 2012 PRISM Precipitation and WRF Precipitation, 4-km Domain.......... B-39

Figure B-32. October 2012 PRISM Precipitation and WRF Precipitation, 4-km Domain............... B-40

Figure B-33. November 2012 PRISM Precipitation and WRF Precipitation, 4-km Domain........... B-41

Figure B-34. December 2012 PRISM Precipitation and WRF Precipitation, 4-km Domain........... B-42

Figure B-35. January 2012 TRMM Precipitation Average and Corresponding WRF 

Precipitation Average in the 12-km Domain .............................................................. B-44

Figure B-36. February 2012 TRMM Precipitation Average and Corresponding WRF 

Precipitation Average in the 12-km Domain .............................................................. B-45

Figure B-37. March 2012 TRMM Precipitation Average and Corresponding WRF Precipitation 

Average in the 12-km Domain ................................................................................... B-46

Figure B-38. April 2012 TRMM Precipitation Average and Corresponding WRF Precipitation 

Average in the 12-km Domain ................................................................................... B-47

Figure B-39. May 2012 TRMM Precipitation Average and Corresponding WRF Precipitation 

Average in the 12-km Domain ................................................................................... B-48

Figure B-40. June 2012 TRMM Precipitation Average and Corresponding WRF Precipitation 

Average in the 12-km Domain ................................................................................... B-49
xii 2018 Gulf of Mexico Supplemental EIS

Figure B-41. July 2012 TRMM Precipitation Average and Corresponding WRF Precipitation 

Average in the 12-km Domain ................................................................................... B-50

Figure B-42. August 2012 TRMM Precipitation Average and Corresponding WRF Precipitation 

Average in the 12-km Domain ................................................................................... B-51

Figure B-43. September 2012 TRMM Precipitation Average and Corresponding WRF 

Precipitation Average in the 12-km Domain .............................................................. B-52 

Figure B-44. October 2012 TRMM Precipitation Average and Corresponding WRF 

Precipitation Average in the 12-km Domain .............................................................. B-53

Figure B-45. November 2012 TRMM Precipitation Average and Corresponding WRF 

Precipitation Average in the 12-km Domain .............................................................. B-54

Figure B-46. December 2012 TRMM Precipitation Average and Corresponding WRF 

Precipitation Average in the 12-km Domain .............................................................. B-55

Figure B-47. Daily Precipitation Plots from WRF, PRISM, and TRMM on August 30, 2012 ......... B-57

Figure B-48. Daily Precipitation Plots from WRF, PRISM, and TRMM Databases on June 25, 

2012............................................................................................................................ B-58

Figure C-1. Location of the “Air Quality Modeling in the Gulf of Mexico Region” Study, with 

Class I Areas and Platform Locations.......................................................................... C-1 

Figure C-2. Ozone Nonattainment Areas in the Southeastern U.S................................................ C-2 

Figure C-3. Overview of the “Air Quality Modeling in the Gulf of Mexico Region” Study Tasks .... C-4 

Figure C-4. WRF 36-km CONUS (d01), 12-km SE Regional (d02), and 4-km Gulf of Mexico 

Region (d03) Domains Along With the PGM Grids. .................................................... C-6 

Figure C-5. 2012 Platform NOx Emissions Aggregated by Lease Block ...................................... C-11

Figure C-6. 2012 Platform VOC Emissions Aggregated by Lease Block..................................... C-12

Figure C-7. 2012 Platform PM2.5 Emissions Aggregated by Lease Block.................................... C-13

Figure C-8. 2012 Non-platform NOx Emissions ............................................................................ C-15

Figure C-9. 2012 Non-platform VOC Emissions........................................................................... C-16

Figure C-10. 2012 Non-platform PM2.5 Emissions.......................................................................... C-17

Figure C-11. Emission Estimates for all Planning Areas and Future Activities.............................. C-27

Figure C-12. Combined Annual NOx Emissions. ............................................................................ C-27

Figure C-13. Combined Annual VOC Emissions. ........................................................................... C-28

Figure C-14. Combined Annual PM2.5 Emissions. .......................................................................... C-28

Figure C-15. BOEM OCS Planning Areas and Water Depths........................................................ C-29

Figure D-1. Location of the “Air Quality Modeling in the Gulf of Mexico Region” Study, with 

Class I Areas................................................................................................................ D-1 

Figure D-2. Ozone Nonattainment Areas in the Southeastern U.S................................................ D-3 

Figure D-3. Class I and Sensitive Class II Areas in the Study Region ........................................... D-5 

Figure D-4. Overview of the “Air Quality Modeling in the Gulf of Mexico Region” Study Tasks .... D-6 

Figure D-5. Meteorological (WRF model) and PGM Modeling Domains Including the 36-km 

Horizontal Grid Resolution CONUS WRF Domain, 12-km Resolution Southeast 

Regional WRF and PGM Domains (d02), and 4-km Resolution Gulf of Mexico 

OCS Region WRF and PGM Domains (d03)............................................................... D-8 
List of Figures xiii

Figure D-6. BOEM’s 12-km 2012 Base Case NOx Emissions Summary in Tons per Year 

by Source Category and State (Alabama, Florida, Louisiana, Mississippi, and 

Texas)......................................................................................................................... D-19

Figure D-7. BOEM 12-km 2012 Base Case VOC Emissions Summary in Tons per Year 

by Source Category and State (Alabama, Florida, Louisiana, Mississippi, and 

Texas)......................................................................................................................... D-20

Figure D-8. BOEM 12-km 2012 Base Case PM2.5 Emissions Summary in Tons per Year 

by Source Category and State (Alabama, Florida, Louisiana, Mississippi, and 

Texas)......................................................................................................................... D-21

Figure D-9. BOEM 12-km 2012 Base Case SO2 Emissions Summary in Tons per Year 

by Source Category and State (Alabama, Florida, Louisiana, Mississippi, and 

Texas)......................................................................................................................... D-22

Figure D-10. BOEM 12-km Future Year NOx Emissions Summary in Tons per Year by 

Source Category and State (Alabama, Florida, Louisiana, Mississippi, and 

Texas)......................................................................................................................... D-23

Figure D-11. BOEM 12-km Future Year VOC Emissions Summary in Tons per Year by 

Source Category and State (Alabama, Florida, Louisiana, Mississippi, and 

Texas)......................................................................................................................... D-24

Figure D-12. BOEM 12-km Future Year PM2.5 Emissions Summary in Tons per Year by 

Source Category and State (Alabama, Florida, Louisiana, Mississippi, and 

Texas)......................................................................................................................... D-25

Figure D-13. BOEM 12-km Future Year SO2 Emissions Summary in Tons per Year by 

Source Category and State (Alabama, Florida, Louisiana, Mississippi, and 

Texas)......................................................................................................................... D-26

Figure D-14. Spatial Distribution of NOx, VOC, SO2, and PM2.5 Emissions (tons per year) 

from New OCS Oil and Gas Production Platforms under the Proposed Action........ D-29

Figure D-15. Spatial Distribution of Emissions (tons per year) of NOx, VOC, SO2, and PM2.5 

from BOEM’s OCS Additional Oil and Gas Support Vessels and Helicopters 

under the Proposed Action Scenario ......................................................................... D-30

Figure D-16. Spatial Distribution of NOx, VOC, SO2, and PM2.5 Emissions (tons per year) 

from BOEM’s OCS Oil and Gas Platforms, Support Vessels, and Helicopters 

under the No Action Alternative in BOEM’s 4-km Domain ........................................ D-31

Figure D-17. Spatial Distribution of NOx, VOC, SO2, and PM2.5 Emissions (tons per year) 

from All Other Marine Vessel Activity in the Gulf of Mexico under the Future 

Year Scenario in BOEM’s 4-km Domain.................................................................... D-32

Figure D-18. Spatial Distribution of NOx, VOC, SO2, and PM2.5 Emissions (tons per year) 

from Other Anthropogenic U.S. Sources for the Future Year Scenario within 

BOEM’s 4-km Domain................................................................................................ D-33

Figure D-19. Ozone Monitoring Sites Used in the Model Performance Evaluation: CASTNet 

Sites in the Southeastern U.S. and AQS Sites within the 4-km Modeling Domain... D-42

Figure D-20. Speciated PM Monitoring Sites Used in the Model Performance Evaluation: 

CSN Network, IMPROVE Network, and SEARCH Network...................................... D-44
xiv 2018 Gulf of Mexico Supplemental EIS

Figure D-21. Monthly Normalized Mean Bias and Normalized Mean Error for Daily Maximum 

8-hour Average Ozone at AQS and CASTNet Monitoring Sites Located within 

the 4-km Modeling Domain and the 12-km Domain .................................................. D-50

Figure D-22. Fraction of Site-days during Each Month of 2012 with Observed Daily Maximum 

8-hour Ozone Exceeding 60, 65, or 70 ppb Over All Monitoring Sites in the 

4-km Domain.............................................................................................................. D-51

Figure D-23. Observed and Predicted Monthly Mean Daily Maximum 8-hour Average Ozone 

Over All Sites in the 4-km Modeling Domain ............................................................. D-52

Figure D-24. Scatter and Scatter Density Plots for Observed vs. Predicted Daily Maximum 

8-hour Ozone in Q2 and Q3 for All AQS Monitoring Sites in the 4-km Modeling 

Domain....................................................................................................................... D-53

Figure D-25. Normalized Mean Bias (NMB) for Daily Maximum 8-hour Ozone for Q2 and Q3..... D-54

Figure D-26. Time Series of Daily Maximum 8-hour Ozone at Monitoring Sites with Highest 

Design Values in Harris, Brazoria, and Galveston Counties, Texas, for Q2 and 

Q3............................................................................................................................... D-56

Figure D-27. Time Series of Daily Maximum 8-hour Ozone at Monitoring Sites in the Baton 

Rouge Nonattainment Area: LSU and Carville for Q2 and Q3................................. D-56

Figure D-28. Time Series of Daily Maximum 8-hour Ozone at the ALC188 (Alabama-Coushatta, 

Texas) CASTNet Monitoring Site for Q2 and Q3....................................................... D-57

Figure D-29. PM Monitoring Sites in the Southeastern U.S. Domain............................................. D-59

Figure D-30. Soccer Plots of Total PM2.5 Mass Model Performance Across the IMPROVE, 

CSN, SEARCH, and FRM Daily Monitoring Networks for Sites in the 

Southeastern U.S. Domain ........................................................................................ D-60

Figure D-31. Comparisons of Predicted with Observed Daily Average PM at CSN Network 

Sites in the Southeastern U.S. for Q2 and Q4 for Total PM2.5, Other PM2.5, and 

Sodium ....................................................................................................................... D-61

Figure D-32. Comparisons of Observed vs. redicted OC and EC at SEARCH and CSN 

Network Sites in the Southeastern U.S ..................................................................... D-62

Figure D-33. Monthly Normalized Mean Bias and Normalized Mean Error for Hourly NO2 and 

Daily NOy at SEARCH Network Sites and AQS Sites in the 4-km Domain.............. D-63

Figure D-34. Monthly Normalized Mean Bias and Normalized Mean Error for NO3 at SEARCH 

Network Monitoring Sites and AQS Sites and NO3 Deposition at NADP Sites 

in the Southeastern U.S............................................................................................. D-64

Figure D-35. Monthly Normalized Mean Bias and Normalized Mean Error at Monitoring Sites 

in the 4-km Domain for SO2, SO4, and SO4 Deposition Measured at NADP Sites... D-66

Figure D-36. Annual Normalized Mean Bias for Hourly SO2 .......................................................... D-67

Figure D-37. Monthly Normalized Mean Bias and Normalized Mean Error for Daily Average 

NH4 at CSN and SEARCH Network Sites in the 4-km Modeling Domain................. D-68

Figure D-38. Monthly Normalized Mean Bias and Normalized Mean Error for Hourly CO at 

SEARCH Network Sites and AQS Sites.................................................................... D-69

Figure D-39. Class I and Sensitive Class II Areas for Which Incremental AQ/AQRV Impacts 

Were Calculated......................................................................................................... D-73
List of Figures xv

Figure D-40. Base Scenario Ozone Design Values, Future Year Ozone Design Values and 

Their Differences Calculated Using the MATS UAA Tool ......................................... D-87

Figure D-41. MATS UAA Future Year Ozone Design Values (DFV) Calculated After First 

Removing the Hourly Contributions from a Source Group and the Corresponding 

Contributions of the Source Group to DVF Calculated by Subtracting the DVFs 

Shown in the Left-hand Column from the “All Sources” DVF Shown in the Top 

Right-hand Corner of Figure D-40 ............................................................................. D-88

Figure D-42. Modeled 4th Highest MDA8 Ozone for the Base Year and Future Year Scenarios 

and Their Differences................................................................................................. D-89

Figure D-43. Contributions of Source Groups A, B, C, D, and E to Future Year All-sources 

4th Highest MDA8 ...................................................................................................... D-91

Figure D-44. Contributions from Source Group F (natural and non-U.S. emission sources 

including boundary conditions) and Boundary Conditions Only, to Future Year 

All-sources 4th Highest MDA8 ................................................................................... D-92

Figure D-45. Current Year (DVC) and Future Year (DVF) Annual Average PM2.5 Design 

Values from the MATS Unmonitored Area Analysis and the Difference, 

DVF – DVC................................................................................................................. D-98

Figure D-46. Contributions of Source Groups A, B, C, D, and E to the Future Year All-sources 

Annual Average PM2.5 Concentration Based on the MATS Unmonitored Area 

Analysis ...................................................................................................................... D-99

Figure D-47. Modeled 8th Highest Daily Average PM2.5 Concentrations for the Base Year, 

Future Year, and the Future – Base Difference....................................................... D-101

Figure D-48. Contributions of Source Groups A, B, C, D, and E to the Future Year 

All-sources 8th Highest Daily Average PM2.5 Concentration................................... D-102

Figure D-49. Contributions from Source Group F (natural and non-U.S. emission sources 

including boundary conditions) and Boundary Conditions Only to Future Year 

All-sources 8th Highest 24-hour PM2.5..................................................................... D-103

Figure D-50. Modeled Annual Average PM2.5 Concentrations for the Base Year, Future Year, 

and the Future – Base Difference............................................................................ D-104

Figure D-51. Contributions of Source Group A, B, C, D, and E to the Future Year All-sources 

Annual Average PM2.5 Concentration ...................................................................... D-105

Figure D-52. Contributions from Source Group F (natural and non-U.S. emission sources 

including boundary conditions) and Boundary Conditions Only to Future Year 

All-sources Annual Average PM2.5. .......................................................................... D-106

Figure D-53. Modeled 2nd Highest 24-hour Average PM10 Concentrations for the Base Year, 

Future Year, and the Future – Base Difference....................................................... D-107

Figure D-54. Contributions of Source Groups A, B, C, D, and E to the Future Year 

All-sources 2nd Highest Daily Average PM10 Concentration................................... D-108

Figure D-55. Contributions from Source Group F (natural and non-U.S. emission sources 

including boundary conditions) and Boundary Conditions Only to Future Year 

All-sources 2nd Highest Daily Average PM10 Concentration.................................... D-109

Figure D-56. Modeled 8th Highest 1-hour NO2 Concentrations for the Base Year, Future 

Year, and the Future – Base Difference. ................................................................. D-110
xvi 2018 Gulf of Mexico Supplemental EIS

Figure D-57. Contributions of Source Group A, B, C, D, and E to the Future Year All-sources 

8th Highest Daily Average NO2 Concentrations ...................................................... D-111

Figure D-58. Modeled Annual Average NO2 Concentrations for the Base Year), Future Year, 

and the Future – Base Difference............................................................................ D-112

Figure D-59. Contributions of Source Groups A, B, C, D, and E to the Future Year 

All-sources Annual Average NO2 Concentrations ................................................... D-113

Figure D-60. Modeled 4th Highest Daily Maximum 1-hour SO2 Concentrations for the Base 

Year, Future Year, and the Future – Base Difference............................................. D-115

Figure D-61. Contributions of Source Group A, B, C, D, and E to the Future Year All-sources 

4th Highest Daily Maximum 1-hour SO2 Concentration .......................................... D-116

Figure D-62. Modeled Annual 2nd Highest Block 3-hour SO2 Concentrations for the Base 

Year, Future Year, and the Future – Base Difference............................................. D-117

Figure D-63. Contributions of Source Group A, B, C, D, and E to the Future Year All-sources 

2nd Highest 3-hour Block Average SO2 Concentration........................................... D-118

Figure D-64. Modeled Annual 2nd Highest Non-overlapping Running 8-hour Average CO 

Concentrations for the Base Year, Future Year, and the Future – Base 

Difference................................................................................................................. D-119

Figure D-65. Modeled Annual 2nd Highest 1-hour Average CO Concentrations for the Base 

Year, Future Year, and the Future – Base Difference............................................. D-120
List of Tables xvii

LIST OF TABLES

Page

Table 1. Alternative Comparison Matrix ....................................................................................... xix 

Table 2-1. Applicable Stipulations by Alternative .......................................................................... 2-15

Table 2-2. Alternative Comparison Matrix ..................................................................................... 2-20

Table 3-1. Offshore Scenario Activities Related to a Single Proposed Lease Sale for 

Alternative A, B, or C from 2017 through 2066 ............................................................ 3-13

Table 3-2. Percent of Production of Each Alternative of a Single Proposed Lease Sale 

(2017-2066) in Relation to Each Cumulative Production Scenario.............................. 3-14

Table 3-3. Exploration and Seismic Survey Activity Leading Up To and Following a Proposed 

Lease Sale in the Gulf of Mexico.................................................................................. 3-15

Table 3-4. Existing Coastal Infrastructure Related to OCS Oil- and Gas-Related Activities 

in the Gulf of Mexico..................................................................................................... 3-19

Table 3-1. Projected Oil and Gas in the Gulf of Mexico OCS ....................................................... 3-21

Table 3-6. Depth Distributions within the Proposed Regionwide Lease Sale Area ...................... 3-22

Table 3-7. Oil Transportation Scenario under Alternative A, B, or C ............................................ 3-23

Table 3-8. Summary of the Timing of Impact-Producing Factors Associated with Routine Oil 

and Gas Activities......................................................................................................... 3-25

Table 3-9. General Description of Routine Impact-Producing Factors.......................................... 3-26

Table 3-10. Mean Number and Sizes of Spills Estimated to Occur in OCS Offshore Waters 

from an Accident Related to Rig/Platform and Pipeline Activities Supporting Each 

Alternative Over a 50-Year Time Period ...................................................................... 3-34

Table 3-11. Oil-Spill Occurrence Probability Estimates for Offshore Spills ≥1,000 Barrels 

Resulting from Each Alternative (2017-2066) and the Cumulative OCS Oil and 

Gas Program (2017-2086)............................................................................................ 3-35

Table 3-12. Oil-Spill Occurrence Probability Estimates for Offshore Spills ≥10,000 Barrels 

Resulting from Each Alternative (2017-2066) and the Cumulative OCS Oil and 

Gas Program (2017-2086)............................................................................................ 3-35

Table 3-13. Historic Spill Source, Location, and Characteristics of a Maximum Spill for Coastal 

Waters........................................................................................................................... 3-37

Table 3-14. Summary of the Timing of Impact-Producing Factors Associated with Accidental 

Oil and Gas Events....................................................................................................... 3-40

Table 3-15. General Description of Accidental Event Impact-Producing Factors........................... 3-41

Table 3-16. Future Activity Projections Associated with the Cumulative OCS Oil and Gas 

Program (2017-2086), Including All Future Activities that are Projected to Occur 

from Past, Proposed, and Future Lease Sales. ........................................................... 3-44

Table 3-17. Future Oil Transportation Projections Associated with the Cumulative OCS Oil 

and Gas Program (2017-2086), Including All Future Transportation that is 

Projected to Occur from Past, Proposed, and Future Lease Sales............................. 3-46

Table 3-18. General Description of Cumulative Non-OCS Oil- and Gas-Related 

Impact-Producing Factors ............................................................................................ 3-47
xviii 2018 Gulf of Mexico Supplemental EIS

Table 4-1. Air Quality Impact-Producing Factors That Are Reasonably Foreseeable.................. 4-17

Table 4-2. National Ambient Air Quality Standards....................................................................... 4-20

Table 4-3. Nonattainment and Maintenance Areas in the Gulf of Mexico Region. ....................... 4-22

Table 4-4. Source Categories for Source Apportionment Calculations......................................... 4-43

Table 4-5. Source Group for Incremental Impacts Analysis.......................................................... 4-44

Table 4-6. NAAQS and PSD Increments....................................................................................... 4-45

Table 4-7 Class I and Sensitive Class II Areas in Gulf Coast and Nearby States ....................... 4-50

Table 4-8. Water Quality Impact-Producing Factors That Are Reasonably Foreseeable............. 4-64

Table 4-9. Estuarine Systems Impact-Producing Factors That Are Reasonably Foreseeable..... 4-68

Table 4-10. Coastal Barrier Beaches and Associated Dunes Impact-Producing Factors .............. 4-74

Table 4-11. Deepwater Benthic Communities Impact-Producing Factors That Are Reasonably 

Foreseeable.................................................................................................................. 4-80

Table 4-12. Sargassum and Associated Communities Impact-Producing Factors That Are 

Reasonably Foreseeable.............................................................................................. 4-87

Table 4-13. Topographic Features and Associated Communities Impact-Producing Factors 

That Are Reasonably Foreseeable............................................................................... 4-94

Table 4-14. Pinnacles and Low-Relief Features and Associated Communities 

Impact-Producing Factors That Are Reasonably Foreseeable..................................4-102

Table 4-15. Fish and Invertebrate Resources Impact-Producing Factors That Are Reasonably 

Foreseeable................................................................................................................4-109

Table 4-16. Birds Impact-Producing Factors That Are Reasonably Foreseeable.........................4-116

Table 4-17. Species within the Gulf of Mexico That Are Protected Under the Endangered 

Species Act and/or the Marine Mammal Protection Act.............................................4-120

Table 4-18. Protected Species Impact-Producing Factors That Are Reasonably 

Foreseeable................................................................................................................4-122

Table 4-19. Commercial Fisheries Impact-Producing Factors That Are Reasonably 

Foreseeable................................................................................................................4-148

Table 4-20. Recreational Fishing Impact-Producing Factors That Are Reasonably 

Foreseeable................................................................................................................4-151

Table 4-21. Recreational Resources Impact-Producing Factors That Are Reasonably 

Foreseeable................................................................................................................4-155

Table 4-22. Archaeological Surveys and Resources Identified, 2009-2014 .................................4-159

Table 4-23. Land Use and Coastal Infrastructure Impact-Producing Factors That Are 

Reasonably Foreseeable............................................................................................4-167

Table 4-24. Forecasted Average Annual Growth in Population, Employment, Gross Regional 

Product from 2015 through 2050................................................................................4-173

Table B-1. Nonattainment and Maintenance Areas in the Southeastern U.S ................................ B-3

Table B-2. BOEM’s Gulf of Mexico OCS Region WRF Domain Configuration .............................. B-6

Table B-3. BOEM Gulf of Mexico OCS Region WRF Dataset Model Levels ................................. B-8

Table B-4. BOEM Gulf of Mexico OCS Region WRF Physics Options ........................................ B-11

Table B-5. Meteorological Model Performance Benchmarks for Simple and Complex 

Conditions.................................................................................................................... B-12

Table C-1. Nonattainment and Maintenance Areas in the Southeastern U.S ................................ C-3
List of Tables xix

Table C-2. Gulf of Mexico Air Quality Modeling Study Source Categories..................................... C-7

Table C-3. Base Case Offshore Oil and Gas Production Source Emissions Estimates 

for the GOM Western and Central/Eastern Planning Areas ....................................... C-10

Table C-4. Future Year Production Platform Emission Factors.................................................... C-21

Table C-5. Summary of Vessel Characteristics ............................................................................ C-23

Table C-6. Load Factors to be Used in the Future Year Projections............................................ C-24

Table C-7. Marine Vessel Emission Factors (g/kW-hr)................................................................. C-24

Table C-8. Emission Estimates for the Western, Central, and Eastern Planning Areas, 

All Depths, By Year and Pollutant ............................................................................... C-25

Table D-1. Nonattainment and Maintenance Areas in the Southeastern U.S. ............................... D-4

Table D-2. Gulf of Mexico OCS Region Air Quality Modeling Study Source Categories ............. D-10

Table D-3. 2012 Fire Criteria Air Pollutant Emissions Summary by Fire Type for BOEM’s 

36-, 12-, and 4-km Domains ........................................................................................ D-15

Table D-4. 2012 Base Case and Future Year Emissions Summary by State for BOEM’S 

12-km Domain (only Gulf Coast States: Alabama, Florida, Louisiana, Mississippi, 

and Texas)................................................................................................................... D-18

Table D-5. 2012 Base Case and Future Year Emissions Summary by Source Category 

for BOEM’s 4-km Domain............................................................................................ D-26

Table D-6. Changes in Emissions between the 2012 Base Case and Future Year Emissions 

(short tons per year) by Source Category for BOEM’s 4-km Domain......................... D-27

Table D-7. Source Categories for Source Apportionment Calculations........................................ D-34

Table D-8. Domain Grid Definitions for the WRF and CAMx/CMAQ Modeling. ........................... D-35

Table D-9. Vertical Layer Interface Definition for WRF Simulations and the Layer-collapsing 

Scheme for the CAMx/CMAQ Layers.......................................................................... D-36

Table D-10. CAMx Model Configuration.......................................................................................... D-39

Table D-11. Definitions of Model Performance Evaluation Statistical Metrics................................ D-45

Table D-12. Ozone and PM Model Performance Goals and Criteria.............................................. D-46

Table D-13. Model Performance Statistics at Different Observed Ozone Concentration 

Screening Thresholds Based on All Monitoring Sites in the 4-km Domain ................ D-55

Table D-14. NAAQS and PSD Increments...................................................................................... D-71

Table D-15. Source Group for Incremental Impacts Analysis......................................................... D-72

Table D-16. Class I and Sensitive Class II Areas in Gulf Coast and Nearby States ...................... D-74

Table D-17. Current Year (DVC) and Future Year (DVF) Ozone Design Values at Ambient 

Air Monitoring Sites within the 4-km Modeling Domain from MATS ........................... D-82

Table D-18. Ozone Current (DVC) and Future Year (DVF) Design Values and Reduction 

in DVF with Contributions from Individual Source Groups Removed ......................... D-84

Table D-19. MATS Ozone Design Value Results for All Monitoring Sites Where Exclusion 

of Contributions from Source Group A or B is Sufficient to Reduce the Predicted 

Future Design Value (DVF) from Above the NAAQS to Below the NAAQS 

(all values in ppb)......................................................................................................... D-86

Table D-20. Current Year (DVC) and Future Year (DVF) 24-Hour PM2.5 Design Values 

for Monitoring Sites in the 4-km Modeling Domain from MATS.................................. D-93
xx 2018 Gulf of Mexico Supplemental EIS

Table D-21. 24-Hour PM2.5 Current (DVC) and Future Year (DVF) Design Values and 

Reduction in DVF with Contributions from Individual Source Groups Removed........ D-94

Table D-22. Current (DVC) and Projected Future (DVF) Annual Average PM2.5 Design Values 

for Monitoring Sites in the 4-km Modeling Domain ..................................................... D-95

Table D-23. Annual Average PM2.5 Future Year Design Values (DVF) and Change in DVF 

with Contributions from Individual Source Groups Removed ..................................... D-96

Table D-24. Maximum Source Group Contributions for PSD Pollutants at Class I and 

Sensitive Class II Areas in the 4-km Modeling Domain ............................................ D-121

Table D-25. Source Group Contributions for PSD Pollutants at All Class I and Sensitive 

Class II Areas in the 4-km Modeling Domain............................................................ D-123

Table D-26. Incremental Visibility Impacts Relative to Natural Background Conditions from 

Source Group A ......................................................................................................... D-124

Table D-27. Incremental Visibility Impacts Relative to Natural Background Conditions from 

Source Group B ......................................................................................................... D-125

Table D-28. Cumulative Visibility Results for 20% Worst Visibility Days (W20%) at Class I 

Areas for Base (2012) Year (BY) and Future Year (FY) Scenarios with All 

Sources Included and with Contributions from Each Source Group Removed........ D-128

Table D-29. Differences in Cumulative Visibility Results for 20% Worst Visibility Days 

(W20%) at Class I Areas Between the Future Year (FY) and Base Year (BY) 

Scenarios and Contributions of Each Source Group to the Future Year Scenario 

Visibility ...................................................................................................................... D-130

Table D-30. Cumulative Visibility Results for 20% Best Visibility Days (B20%) at Class I 

Areas for Base (2012) Year (BY) and Future Year (FY) Scenarios with All 

Sources Included and with Contributions from Each Source Group Removed........ D-132

Table D-31. Differences in Cumulative Visibility Results for 20% Best Visibility Days (B20%) 

at Class I Areas Between the Future Year (FY) and Base Year (BY) Scenarios 

and Contributions of Each Source Group to the Future Year Scenario Visibility...... D-133

Table D-32. Deposition Analysis Threshold Values (kg/ha/yr) as Defined in the Federal Land 

Manager Guidance .................................................................................................... D-135

Table D-33. Incremental Deposition Impacts from Source Groups A and B at Class I and 

Sensitive Class II Areas in the 4-km Domain............................................................ D-135

Table D-34. Cumulative Nitrogen (N) and Sulfur (S) Deposition Impacts (kg/ha/yr) under the 

Base and Future Year Scenarios .............................................................................. D-136

Table E-1. Public Comments and BOEM’s Response Matrix....................................................... E-13
APPENDIX A 

 

COOPERATING AGENCY 

MEMORANDUM OF AGREEMENT

Cooperating Agency Memorandum of Agreement A-3

A COOPERATING AGENCY MEMORANDUM OF AGREEMENT
A-4 2018 Gulf of Mexico Supplemental EIS
Cooperating Agency Memorandum of Agreement A-5
A-6 2018 Gulf of Mexico Supplemental EIS
APPENDIX B 

 

AIR QUALITY: 

WRF MODEL PERFORMANCE

Table of Contents B-iii

TABLE OF CONTENTS

Page

B.1 INTRODUCTION........................................................................................................................ B-1

B.2 WRF MODELING METHODOLOGY......................................................................................... B-5

B.2.1 Gulf of Mexico Region Air Quality Meteorological Modeling........................................... B-5

B.2.2 Model Domain Configuration........................................................................................... B-6

B.2.3 Model Application............................................................................................................ B-7

B.2.3.1 Model Vertical Resolution................................................................................ B-7

B.2.3.2 Topographic Inputs.......................................................................................... B-8

B.2.3.3 Vegetation Type and Land Use Inputs............................................................ B-9

B.2.3.4 Atmospheric Data Inputs ................................................................................. B-9

B.2.3.5 Time Integration............................................................................................... B-9

B.2.3.6 Diffusion Options ............................................................................................. B-9

B.2.3.7 Lateral Boundary Conditions ........................................................................... B-9

B.2.3.8 Top and Bottom Boundary Conditions .......................................................... B-10

B.2.3.9 Sea-Surface Temperature Inputs .................................................................. B-10

B.2.3.10 FDDA Data Assimilation................................................................................ B-10

B.2.3.11 WRF Physics Options.................................................................................... B-11

B.2.3.12 WRF Application Methodology ...................................................................... B-11

B.3 WRF MODEL PERFORMANCE EVALUATION RESULTS.................................................... B-12

B.3.1 Quantitative Evaluation Using Metstat.......................................................................... B-12

B.3.1.1 Quantitative Statistics .................................................................................... B-13

B.3.1.2 METSTAT Evaluation Using Integrated Surface Hourly Observations 

and Offshore Buoy Observations .................................................................. B-15

B.3.2 Qualitative Evaluation Using Wind Roses..................................................................... B-22

B.3.3 Qualitative Evaluation Using Upper-Air Data................................................................ B-27

B.3.4 Qualitative Evaluation Using Precipitation .................................................................... B-29

B.3.4.1 Evaluation Over Land Using PRISM Precipitation ........................................ B-29

B.3.4.2 Evaluation Over Water Using Satellite Precipitation ..................................... B-43

B.3.4.3 Evaluation Using Tropical Cyclone Precipitation Events .............................. B-56

B.4 SUMMARY AND CONCLUSIONS........................................................................................... B-59

B.5 REFERENCES......................................................................................................................... B-59

List of Tables B-v 

LIST OF TABLES

Page

Table B-1. Nonattainment and Maintenance Areas in the Southeastern U.S.................................. B-3

Table B-2. BOEM Gulf of Mexico OCS Region WRF Domain Configuration................................... B-6

Table B-3. BOEM Gulf of Mexico OCS Region WRF Dataset Model Levels................................... B-8

Table B-4. BOEM Gulf of Mexico OCS Region WRF Physics Options.......................................... B-11

Table B-5. Meteorological Model Performance Benchmarks for Simple and Complex 

Conditions...................................................................................................................... B-12

LIST OF FIGURES

Page

Figure B-1. Location of the “Air Quality Modeling in the Gulf of Mexico Region” Study with 

Class I Areas and Platform Locations.......................................................................... B-1

Figure B-2. Ozone Nonattainment Areas in the Southeastern U.S................................................ B-2

Figure B-3. Overview of the “Air Quality Modeling in the Gulf of Mexico Region” Study 

Tasks............................................................................................................................ B-4

Figure B-4. WRF 36-km CONUS (d01), 12-km SE Regional (d02), and 4-km Gulf of Mexico 

Region (d03) Domains ................................................................................................. B-7

Figure B-5. BOEM Gulf of Mexico OCS Region WRF 36-km METSTAT Wind Direction 

Performance for 2012 ................................................................................................ B-16

Figure B-6. BOEM Gulf of Mexico OCS Region WRF 36-km METSTAT Wind Speed 

Performance for 2012 ................................................................................................ B-16

Figure B-7. BOEM Gulf of Mexico OCS Region WRF 36-km METSTAT Temperature 

Performance for 2012 ................................................................................................ B-17

Figure B-8. BOEM Gulf of Mexico OCS Region WRF 36-km METSTAT Humidity 

Performance for 2012 ................................................................................................ B-17

Figure B-9. BOEM Gulf of Mexico OCS Region WRF 12-km METSTAT Wind Direction 

Performance for 2012 ................................................................................................ B-18

Figure B-10. BOEM Gulf of Mexico OCS Region WRF 12-km METSTAT Wind Speed 

Performance for 2012 ................................................................................................ B-18

Figure B-11. BOEM Gulf of Mexico OCS Region WRF 12-km METSTAT Temperature 

Performance for 2012 ................................................................................................ B-19

Figure B-12. BOEM Gulf of Mexico OCS Region WRF 12-km METSTAT Humidity 

Performance for 2012 ................................................................................................ B-19

Figure B-13. BOEM Gulf of Mexico OCS Region WRF 4-km METSTAT Wind Direction 

Performance for 2012 ................................................................................................ B-20

Figure B-14. BOEM Gulf of Mexico OCS Region WRF 4-km METSTAT Wind Speed 

Performance for 2012 ................................................................................................ B-20
B-vi 2018 Gulf of Mexico Supplemental EIS

Figure B-15. BOEM Gulf of Mexico OCS Region WRF 4-km METSTAT Temperature 

Performance for 2012 ................................................................................................ B-21

Figure B-16. BOEM Gulf of Mexico OCS Region WRF 4-km METSTAT Humidity 

Performance for 2012 ................................................................................................ B-21

Figure B-17. Wind Rose Locations for Port Isabel, TX (PTIT), Calcasieu, LA (CAPL), 

Gulfport, MS (KGPT), and Naples, FL (NPSF).......................................................... B-22

Figure B-18. 2012 WRF Wind Rose Compared to 2012 Observation Wind Rose from 

Gulfport, MS in 4-km Domain..................................................................................... B-23

Figure B-19. 2012 WRF Wind Rose Compared to 2012 Observation Wind Rose from 

Naples, FL in 4-km Domain ....................................................................................... B-24

Figure B-20. 2012 WRF Wind Rose Compared to 2012 Observation Wind Rose from 

Port Isabel, TX in 4-km Domain................................................................................. B-25

Figure B-21. 2012 WRF Wind Rose Compared to 2012 Observation Wind Rose from 

Calcasieu, LA in 4-km Domain................................................................................... B-26

Figure B-22. Vertical Profile Soundings Comparing the 4-km WRF to Upper-Air 

Observations Data for Brownsville, TX on August 3, 2012, and Key West, FL 

on January 4, 2012, at 00 UTC.................................................................................. B-28

Figure B-23. January 2012 PRISM Precipitation and WRF Precipitation, 4-km Domain............... B-31

Figure B-24. February 2012 PRISM Precipitation and WRF Precipitation, 4-km Domain ............. B-32

Figure B-25. March 2012 PRISM Precipitation and WRF Precipitation, 4-km Domain.................. B-33

Figure B-26. April 2012 PRISM Precipitation and WRF Precipitation, 4-km Domain .................... B-34

Figure B-27. May 2012 PRISM Precipitation and WRF Precipitation, 4-km Domain..................... B-35

Figure B-28. June 2012 PRISM Precipitation and WRF Precipitation, 4-km Domain.................... B-36

Figure B-29. July 2012 PRISM Precipitation and WRF Precipitation, 4-km Domain ..................... B-37

Figure B-30. August 2012 PRISM Precipitation and WRF Precipitation, 4-km Domain ................ B-38

Figure B-31. September 2012 PRISM Precipitation and WRF Precipitation, 4-km Domain.......... B-39

Figure B-32. October 2012 PRISM Precipitation and WRF Precipitation, 4-km Domain............... B-40

Figure B-33. November 2012 PRISM Precipitation and WRF Precipitation, 4-km Domain........... B-41

Figure B-34. December 2012 PRISM Precipitation and WRF Precipitation, 4-km Domain........... B-42

Figure B-35. January 2012 TRMM Precipitation Average and Corresponding WRF 

Precipitation Average in the 12-km Domain .............................................................. B-44

Figure B-36. February 2012 TRMM Precipitation Average and Corresponding WRF 

precipitation Average in the 12-km Domain............................................................... B-45

Figure B-37. March 2012 TRMM Precipitation Average and Corresponding WRF 

Precipitation Average in the 12-km Domain .............................................................. B-46

Figure B-38. April 2012 TRMM Precipitation Average and Corresponding WRF Precipitation 

Average in the 12-km Domain ................................................................................... B-47

Figure B-39. May 2012 TRMM Precipitation Average and Corresponding WRF Precipitation 

Average in the 12-km Domain ................................................................................... B-48

Figure B-40. June 2012 TRMM Precipitation Average and Corresponding WRF Precipitation 

Average in the 12-km Domain ................................................................................... B-49

Figure B-41. July 2012 TRMM Precipitation Average and Corresponding WRF Precipitation 

Average in the 12-km Domain ................................................................................... B-50
List of Figures B-vii

Figure B-42. August 2012 TRMM Precipitation Average and Corresponding WRF 

Precipitation Average in the 12-km Domain .............................................................. B-51

Figure B-43. September 2012 TRMM Precipitation Average and Corresponding WRF 

Precipitation Average in the 12-km Domain .............................................................. B-52

Figure B-44. October 2012 TRMM Precipitation Average and Corresponding WRF 

Precipitation Average in the 12-km Domain .............................................................. B-53

Figure B-45. November 2012 TRMM precipitation average and Corresponding WRF 

Precipitation Average in the 12-km Domain .............................................................. B-54

Figure B-46. December 2012 TRMM precipitation average and Corresponding WRF 

Precipitation Average in the 12-km Domain .............................................................. B-55

Figure B-47. Daily Precipitation Plots from WRF, PRISM, and TRMM on August 30, 2012 ......... B-57

Figure B-48. Daily Precipitation Plots from WRF, PRISM, and TRMM Databases on June 25, 

2012............................................................................................................................ B-58

Air Quality: WRF Model Performance B-ix

ABBREVIATIONS AND ACRONYMS

ARW Advanced Research WRF

BOEM Bureau of Ocean Energy Management

CAI Climatologically Aided Interpolation

CAAA Clean Air Act Amendments

CAMx Comprehensive Air Quality Model with Extensions

CFL Courant-Friedrichs-Lewy

CFSR Climate Forecast System Reanalysis

CFSv2 Climate Forecast System Version 2

CMAQ Community Multi-scale Air Quality model

ECMWF European Center for Medium-Range Weather Forecasting

EIS Environmental Impact Statement

ERA European Center for Medium-Range Weather Forecasting Re-Analysis

ERG Eastern Research Group, Inc.

ESRL Earth System Research Laboratory

FDDA Four-Dimensional Data Assimilation

FNMOC Fleet Numerical Meteorology and Oceanography Center

IC/BC Initial Conditions/Boundary Conditions

IOA Index of Agreement

ISHO Integrated Surface Hourly Observation

KBRO Meteorological Call Sign for Brownsville

KSIL Meteorological Call Sign for Slidell

KTPA Meteorological Call Sign for Tampa

KEYW Meteorological Call Sign for Key West

LCC Lambert Conformal Conic 

LSM Land-Surface Model

MADIS Meteorological Assimilation Data Ingest System

METSTAT Meteorological Statistical Program

MM5 Mesoscale Meteorological Model version 5

MMIF Mesoscale Model Interface Program 

MPE Model Performance Evaluation

NAAQS National Ambient Air Quality Standards

NAM North American Model

NASA National Aeronautics and Space Administration

NCAR National Center for Atmospheric Research

NCDC National Climatic Data Center

NCEP National Centers for Environmental Prediction

NDBC National Data Buoy Center

NEPA National Environmental Policy Act

NMM Nonhydrostatic Mesoscale Model
B-x 2018 Gulf of Mexico Supplemental EIS

NOAA National Oceanographic Atmospheric Administration 

NWS National Weather Service

OCS Outer Continental Shelf

OCSLA OCS Lands Act 

PBL Planetary Boundary Layer

PGM Photochemical Grid Model

PRISM Parameter-elevation Regressions on Independent Slopes Model

RMSE Root Mean Square Error

RRTMG Rapid Radiative Transfer Model for GCMs

SCAS-OSU Spatial Climate Analysis Service at Oregon State University

SST Sea-Surface Temperature

TRMM Tropical Rainfall Measurement Mission

USEPA United States Environmental Protection Agency

USDOC United States Department of Commerce

USGS United States Geological Survey

UTC Universal Time Coordinate

WPS WRF Pre-processing System

WRAP Western Regional Air Partnership

WRF Weather Research and Forecasting model
Air Quality: WRF Model Performance B-1 

B AIR QUALITY: WRF MODEL PERFORMANCE

B.1 INTRODUCTION

The U.S. Department of the Interior’s Bureau of Ocean Energy Management (BOEM) is 

required under the Outer Continental Shelf Lands Act (OCSLA) (43 U.S.C. § 1334(a)(8)) to comply 

with the National Ambient Air Quality Standards (NAAQS) to the extent that Outer Continental Shelf 

(OCS) offshore oil and gas exploration, development, and production sources do not significantly 

affect the air quality of any state. The Gulf of Mexico OCS Region’s area of possible influence 

includes the States of Texas, Louisiana, Mississippi, Alabama, and Florida. BOEM’s Gulf of Mexico 

Region manages the responsible development of oil, gas, and mineral resources for the 

430 million acres in the Western, Central, and Eastern Planning Areas on the OCS, including the 

areas under moratoria (shown in Figure B-1). The Clean Air Act Amendments (CAAA) of 1990 

designate air quality authorities, giving BOEM air quality jurisdiction westward of 87°30'W. longitude 

and the U.S. Environmental Protection Agency (USEPA) air quality jurisdiction eastward of 87°30'W. 

longitude. In 2006, oil and gas leasing operations within 125 miles (201 kilometers [km]) of the 

Florida coastline were banned until 2022 under the Gulf of Mexico Energy Security Act (GOMESA). 

The GOMESA moratoria area is depicted on Figure B-1. 

Figure B-1. Location of the “Air Quality Modeling in the Gulf of Mexico Region” Study with Class I 

Areas (purple) and Platform Locations (gray dots). 

The USEPA has set NAAQS for six regulated air quality pollutants: ozone; particulate matter 

with an aerodynamic diameter of 2.5 micrometers and smaller (PM2.5); particulate matter with an 
B-2 2018 Gulf of Mexico Supplemental EIS

aerodynamic diameter of 10 micrometers and smaller (PM10); sulfur dioxide (SO2); nitrogen dioxide 

(NO2); carbon monoxide (CO); and lead (Pb). After promulgation of a NAAQS, the USEPA 

designates areas that fail to achieve the NAAQS as nonattainment areas (NAAs) and States are 

required to submit State Implementation Plans (SIPs) to the USEPA that contain emission control 

plans and a demonstration that the NAA will achieve the NAAQS by the required date. After an area 

comes into attainment of the NAAQS, the area can be redesignated as a maintenance area and 

must continue to demonstrate compliance with the NAAQS.

In 1997, the USEPA promulgated the first 8-hour ozone NAAQS with a threshold of 

0.08 parts per million (ppm) (84 parts per billion [ppb]). On March 12, 2008, the USEPA 

promulgated a more stringent 0.075 ppm (75 ppb) 8-hour ozone NAAQS. Figure B-2 presents the 

current ozone nonattainment areas in the southeastern U.S. On October 1, 2015, the USEPA 

strengthened the 8-hour NAAQS for ozone to 0.07 ppm (70 ppb). Under this more stringent ozone 

NAAQS, there may be more areas in the southeastern U.S. that will be in nonattainment. The 

USEPA plans to make attainment and nonattainment designations for the revised standards by 

October 2017, with the designations based on 2014-2016 air quality data.

On December 14, 2012, the USEPA revised the PM2.5 primary NAAQS by lowering the 

annual PM2.5 NAAQS threshold from 15.0 micrograms per cubic meter (μg/m3

) to 12.0 μg/m3. The 

USEPA retained the 24-hour PM2.5 primary NAAQS at 35 μg/m3

. The 24-hour coarse PM NAAQS 

(PM10) was also retained at 150 μg/m3

. 

Figure B-2. Ozone Nonattainment Areas in the Southeastern U.S. (USEPA, 2016a). 

In February 2010, the USEPA issued a new 1-hour NO2 NAAQS with a threshold of 100 ppb 

(98th percentile daily maximum average over three-years) and a new 1-hour SO2 NAAQS was 

promulgated in June 2010 with a threshold of 75 ppb (99th percentile averaged over 3 years). The 

USEPA has not yet designated the nonattainment areas for the 1-hour NO2 and 1 hour SO2 NAAQS.
Air Quality: WRF Model Performance B-3 

A new lead NAAQS was issued in 2008; NAAs for lead are associated with specific industrial 

sources. As oil and gas sources in the Gulf of Mexico OCS region produce negligible amounts of 

lead emissions and to be consistent with onshore oil and gas analysis, which does not include lead, 

lead was not included in the air quality analysis. The NAAQS for carbon monoxide has remained 

essentially unchanged since it was originally promulgated in 1971. As of September 27, 2010, all 

NAAs for carbon monoxide have been redesignated as maintenance areas. Table B-1 summarizes 

the nonattainment and maintenance areas in the southeastern U.S.

Table B-1. Nonattainment and Maintenance Areas in the Southeastern U.S.

State Area 8-hr O3

(1997)

8-hr O3

(2008)

SO2

(2010)

Lead

(2008)

Alabama Troy, AL NAAa

Florida

Tampa, FL NAA

Hillsborough County, FL NAA

Nassau County, FL NAA

Louisiana Baton Rouge, LA Mb NAA

St. Bernard Parish, LA NAA

Texas

Beaumont-Port Arthur, TX M

Houston-Galveston-Brazoria, 

TX NAA NAA

Frisco, TX NAA a NAA = nonattainment area

b M = maintenance area

Blank cells indicate the area is in attainment of the NAAQS.

The CAAA designated 156 Class I areas consisting of National Parks and Wilderness Areas 

that are offered special protection for air quality and air quality-related values (AQRVs). The Class I 

areas, compared to Class II areas, have lower Prevention of Significant Deterioration (PSD) air 

quality increments that new sources may not exceed and are protected against excessive increases 

in several AQRVs, including visibility impairment, acid (sulfur and nitrogen) deposition, and nitrogen 

eutrophication. The Regional Haze Rule (RHR) has a goal of natural visibility conditions by 2064 at 

Class I areas, and States must submit RHR SIPs that demonstrate progress towards that goal. 

Figure B-1 displays the locations of the mandatory Class I areas (in purple) in the Gulf of Mexico 

OCS region. In addition to the Class I areas, Federal Land Management (FLM) agencies have 

designated certain other areas as sensitive Class II areas for tracking PSD increment consumption 

and AQRV impacts.

On August 26, 2014, BOEM contracted with Eastern Research Group, Inc. (ERG) and team 

members Ramboll Environ US Corporation (Ramboll Environ) and Alpine Geophysics, LLC to 

complete a comprehensive air quality modeling study in the Gulf of Mexico OCS region. Under 

BOEM Contract Number M14PC00007, air quality photochemical grid modeling (PGM) will be 

conducted in the region to assess the impacts to nearby States of OCS oil and gas exploration, 

development, and production as required under OCSLA. This assessment is used by BOEM in the 

cumulative and visibility impacts analyses of the National Environmental Policy Act (NEPA) 
B-4 2018 Gulf of Mexico Supplemental EIS

environmental impact statements (EIS), which are the Gulf of Mexico OCS Oil and Gas Lease Sales: 

2017-2022; Gulf of Mexico Lease Sales 249, 250, 251, 252, 253, 254, 256, 257, 259, and 261—

Final Multisale Environmental Impact Statement (2017-2022 GOM Multisale EIS) and this 

Supplemental EIS. These analyses address both current and proposed NAAQS.

Air quality modeling requires several input datasets, including meteorology, emissions 

inventories, and ambient pollutant concentrations. Figure B-3 presents an overview of how these 

project datasets fit together for the “Air Quality Modeling in the Gulf of Mexico Region” study. 

Figure B-3. Overview of the “Air Quality Modeling in the Gulf of 

Mexico Region” Study Tasks. 

This report details the meteorological modeling performance evaluation (MPE) of a Weather 

and Research Forecast (WRF) model for 2012, the PGM year. A separate report (referred to herein 

as the “full WRF modeling report”) will provide a more comprehensive evaluation of the full 5-year 

WRF dataset.

Meteorological information is needed for air quality modeling. Parameters such as wind 

speed, wind direction, air temperature, and humidity are required by models to determine the rate 

that pollutants disperse and react in the atmosphere. Sources of meteorological information include 

datasets of measurements gathered at various locations within the Gulf of Mexico OCS Region’s

domain. However, the spatial coverage of measurements is insufficient to describe the 

three-dimensional structure of the atmosphere away from measurement locations. Using 

measurement data as inputs, gridded meteorological models capable of simulating the fluid 

dynamics of the atmospheric data can be used to estimate meteorological conditions over a 

complete modeling domain—including regions far from measurement sites—in a physically 

consistent fashion. The results of these models are often used to establish conditions near remote 
Air Quality: WRF Model Performance B-5 

pollutant sources or remote locations downwind of pollutant sources. Within the domain of the Gulf 

of Mexico OCS Region, the WRF meteorological model has been identified and was used to provide 

meteorological inputs for the air quality models.

Ramboll Environ previously evaluated the existing meteorological datasets and concluded 

that enough deficiencies were present in the datasets and there were not enough positive attributes 

to select any of them for air quality modeling in the study area (Brashers et al., official 

communication, 2014) and, therefore, new meteorological modeling was required. One purpose of 

the modeling is to provide the meteorological dataset for the 2012 simulation using PGM modeling in 

the OCS region. 

B.2 WRF MODELING METHODOLOGY

Over the past decade, emergent requirements for numerical simulation of urban and regional 

scale air quality have led to intensified efforts to construct high-resolution emissions, meteorological 

and air quality datasets. It is now possible, for example, to exercise sophisticated mesoscale 

prognostic meteorological models and Eulerian and Lagrangian photochemical/aerosol models for 

multi-seasonal periods over near-continental scale domains in a matter of weeks with the application 

tailored to a specific air quality modeling project.

The WRF model is the current preferred model for atmospheric research and operational 

forecasting needs at mesoscale resolution (approximately 5 to several hundred km). The model is 

the state-of-the-art atmospheric simulation system, commonly used to drive air quality dispersion 

models on the regional level.

The operational version of the model is the Nonhydrostatic Mesoscale Model (NMM) WRF 

core version 3, developed and maintained by the U.S. Department of Commerce’s National Oceanic 

and Atmospheric Administration (NOAA) and the National Centers for Environmental Prediction 

(NCEP). The Advanced Research WRF (ARW) core, currently version WRF 3.7.1, is supported by 

the National Center for Atmospheric Research (NCAR), Mesoscale and Microscale Meteorology 

Division (NCAR, 2015). The modeling described in this report used WRF version 3.7.

The WRF model contains separate modules to compute different physical processes such as 

surface energy budgets and soil interactions, turbulence, cloud microphysics, and atmospheric 

radiation. Within WRF, the user has many options for selecting the different schemes for each type 

of physical process. There is a WRF Pre-processing System (WPS) that generates the initial and 

boundary conditions used by WRF, based on topographic datasets, land use information, and largerscale atmospheric and oceanic models.

B.2.1 Gulf of Mexico Region Air Quality Meteorological Modeling

The USEPA CONUS WRF and Ramboll Environ Training WRF datasets were previously 

examined in detail and evaluated using both quantitative and qualitative techniques. Both datasets 

were identified as being inadequate for the study area, particularly in the offshore portions (Brashers
B-6 2018 Gulf of Mexico Supplemental EIS

et al., official communication, 2014). The development of a new high-resolution dataset was 

necessary to more accurately represent meteorological conditions in the over-water portions of the 

OCS region for use in air quality modeling.

B.2.2 Model Domain Configuration

The WRF domain configuration is comprised of a system of simultaneous nested grids. 

Figure B-3 shows the WRF modeling grids at 36/12/4 km. All WRF grids are defined on a Lambert 

Conformal Conic (LCC) projection centered at 40°N. latitude, 97°W. longitude with true latitudes at 

33°N. and 45°N. (the “standard RPO” projection). The outermost domain (outer box) with 36-km 

resolution includes the entire continental U.S. and parts of Canada and Mexico, and captures 

synoptic-scale (storm system-scale) structures in the atmosphere. The inner 12-km regional grid 

(d02) covers the southeastern U.S. and was used to ensure that large-scale meteorological patterns 

across the region are adequately represented and to provide boundary conditions to the 

4-km domain.

The 4-km domain (d03) shown in Figure B-4 is centered on the coastal areas of the 

southeastern U.S. and over-water portions of the Gulf of Mexico. Table B-2 provides the input 

configurations for this WRF domain. The NX and NY are the number of east-west and north-south 

staggered grid points, respectively, in each domain. I-start and J-start indicate the western and 

southern nested grid starting indices with respect to the parent grid. Geographic resolution relates to 

the geographic datasets employed for each grid in terms of minutes or seconds of degrees. 

The 36-, 12-, and 4-km grids were run simultaneously with one-way nesting, meaning that 

meteorological information flows down-scale via boundary conditions introduced from the coarser to 

finer grids without feedback from the finer to coarser grids. The WRF modeling domain was defined 

to be slightly larger than the CAMx/CMAQ PGM modeling domains to eliminate boundary artifacts in 

the meteorological fields. Such boundary artifacts occur for both numerical reason (the 3:1 grid 

spacing ratio) and because the imposed boundary conditions require some time/space to come into 

dynamic balance with WRF’s atmospheric equations. 

Table B-2. BOEM’s Gulf of Mexico OCS Region WRF Domain Configuration. 

Grid Resolution NX NY I-start J-start Geographic Resolution Coverage

36 km 165 129 1 1 10 minute CONUS

12 km 265 187 55 9 2 minute SE CONUS

4 km 481 211 72 27 30 second OCS Region

 
Air Quality: WRF Model Performance B-7 

Figure B-4. WRF 36-km CONUS (d01), 12-km SE Regional (d02), and 4-km Gulf of Mexico Region 

(d03) Domains. 

B.2.3 Model Application

The publicly available version of WRF, version 3.7, was used in the Gulf of Mexico OCS 

Region’s meteorological modeling. The WRF pre-processor programs, including GEOGRID, 

UNGRIB, METGRID, and OBSGRID, were used to develop model inputs. 

B.2.3.1 Model Vertical Resolution

The dataset was tested using both 33 and 37 vertical layers. Thirty-seven vertical layers 

allowed for higher vertical resolutions near the surface, which enabled the model to more accurately 

capture low-level inversions frequently present during winter. Additional layers in the mid-levels also 

allowed the model to more accurately re-create the convective updraft velocities seen in the summer 

months. The dataset model levels are shown in Table B-3. 
B-8 2018 Gulf of Mexico Supplemental EIS

Table B-3. BOEM Gulf of Mexico OCS Region WRF Dataset Model Levels.

Level eta Pressure (mb) Height (m) Mid Height (m) Thickness (m)

0 1 1,000 0.0

1 0.9985 999 12.2 6.1 12.2

2 0.9970 997 24.5 18.4 12.2

3 0.9950 995 40.8 32.7 16.4

4 0.9930 993 57.2 49.0 16.4

5 0.9910 991 73.6 65.4 16.4

6 0.9880 989 98.3 85.9 24.7

7 0.9850 986 123.0 110.6 24.7

8 0.9800 981 164.3 143.6 41.3

9 0.9700 972 247.4 205.9 83.1

10 0.9600 962 331.2 289.3 83.8

11 0.9500 953 415.7 373.4 84.5

12 0.9400 943 500.8 458.2 85.1

13 0.9300 934 586.6 543.7 85.8

14 0.9100 915 760.5 673.5 173.8

15 0.8900 896 937.2 848.8 176.8

16 0.8700 877 1,117.1 1,027.1 179.8

17 0.8400 848 1,392.8 1,254.9 275.8

18 0.8000 810 1,772.4 1,582.6 379.6

19 0.7600 772 2,166.7 1,969.6 394.3

20 0.7200 734 2,577.0 2,371.9 410.3

21 0.6800 696 3,005.0 2,791.0 427.9

22 0.6400 658 3,452.2 3,228.6 447.3

23 0.6000 620 3,921.0 3,686.6 468.7

24 0.5500 573 4,540.7 4,230.8 619.8

25 0.5000 525 5,203.7 4,872.2 662.9

26 0.4500 478 5,917.1 5,560.4 713.4

27 0.4000 430 6,690.5 6,303.8 773.4

28 0.3500 383 7,536.4 7,113.5 846.0

29 0.3000 335 8,472.3 8,004.4 935.8

30 0.2500 288 9,522.5 8,997.4 1,050.2

31 0.2000 240 10,724.1 10,123.3 1,201.6

32 0.1500 193 12,136.7 11,430.4 1,412.6

33 0.1000 145 13,866.9 13,001.8 1,730.1

34 0.0600 107 15,621.6 14,744.2 1,754.7

35 0.0270 76 17,503.4 16,562.5 1,881.8

36 0.0000 50 19,594.2 18,548.8 2,090.8

B.2.3.2 Topographic Inputs

Topographic information for WRF was developed using the standard WRF terrain databases 

available from NCAR. The 36-km CONUS domain was based on the 10-min (18-km) global data. 

The 12-km southeastern CONUS domain was based on the 2 min (~4-km) data. The 4-km Gulf of 

Mexico OCS region domain was based on the 30-sec (~900-m) data.
Air Quality: WRF Model Performance B-9 

B.2.3.3 Vegetation Type and Land Use Inputs

Vegetation type and land-use information was developed using the U.S. Department of the 

Interior, Geological Survey (USGS) land-use database from the most recently released WRF 

databases provided with the WRF distribution. The number of land categories in input data was the 

USGS default of 24. Standard WRF surface characteristics corresponding to each land-use 

category were employed.

B.2.3.4 Atmospheric Data Inputs

The WRF relies on some other model or re-analysis output to provide initial and boundary 

conditions (IC/BC). Sensitivity tests were performed on several datasets to evaluate their 

effectiveness over the Gulf of Mexico. The datasets tested include the ERA-Interim reanalysis 

product, available from the European Center for Medium-range Weather Forecasting (ECMWF) Data 

Portal website; the Climate Forecast System Reanalysis (CFSR, ended in 2010), and the Climate 

Forecast System model version 2 (CFSv2, after 2010) (Saha et al., 2014); and the 12-km North 

American Model (NAM) archives available from the National Climatic Data Center (NCDC) NOMADS 

server.

The NAM dataset was chosen for the lowest bias and error in model performance and was 

used as first guess fields for WRF. This dataset was objectively re-analyzed using traditional 

observation site data (meteorological towers) to the higher resolution of each WRF grid, using the 

OBSGRID program. These fields are then used both to initialize the model and to conduct analysis 

nudging to guide the model to best match the observations.

B.2.3.5 Time Integration

Adaptive time stepping was used to maximize the time step that the model can use while 

keeping the model numerically stable. The model time step was adjusted based on the domain-wide 

horizontal and vertical stability Courant-Friedrichs-Lewy (CFL) target value of 0.8.

B.2.3.6 Diffusion Options

Horizontal Smagorinsky first-order closure (km_opt = 4) with sixth-order numerical diffusion 

and suppressed up-gradient diffusion (diff_6th_opt = 2) was used.

B.2.3.7 Lateral Boundary Conditions

Lateral boundary conditions were specified from the initialization dataset on the 36-km 

domain with continuous updates nested from the 36-km domain to the 12-km domain and from the 

12-km domain to the 4-km domain, using one-way nesting (feedback = 0).
B-10 2018 Gulf of Mexico Supplemental EIS

B.2.3.8 Top and Bottom Boundary Conditions

The top boundary condition was selected as an implicit Rayleigh dampening for the vertical 

velocity. Consistent with the model application for non-idealized cases, the bottom boundary 

condition was selected as physical, not free-slip.

B.2.3.9 Sea-Surface Temperature Inputs

High-resolution, sea-surface temperature (SST) inputs aid in improving meteorological 

conditions for the over-water portions of the Gulf of Mexico OCS region. The Fleet Numerical 

Meteorology and Oceanography Center (FNMOC) dataset, available from the Global Ocean Data 

Assimilation Experiment (GODAE) archives, was selected after extensive testing of several SST 

databases. The FNMOC high-resolution database is updated every 6 hours using satellite-derived 

(AVHRR) SST and in-situ SST from ships and buoys with resolutions, ranging from 12 km at the 

equator to 9 km at the mid-latitudes. The FNMOC SST database was chosen for the lowest SST 

bias and error in model performance evaluation tests, which used open water observations from the 

National Data Buoy Center (NDBC) archives.

B.2.3.10 FDDA Data Assimilation

The WRF was created as a forecast tool, but it can also be applied in “hindcast” mode. In 

forecast mode, the initial conditions for a run might be the most recent analysis (a gridded version of 

the current state of the atmosphere). In hindcast mode, we know the state of the atmosphere both 

at the beginning and end of (and during) the WRF run. Using these 6-hourly analyses, an extra error 

term is introduced into the WRF equations, nudging the WRF atmosphere toward the real 

atmosphere. This is known as Four Dimensional Data Assimilation (FDDA) or analysis nudging and 

is applied to every grid cell in the domain. It works best at larger grid spacing scales and for larger 

domains.

Observational nudging is the process of nudging just the single grid cell toward a single-point 

observation. The observation could be taken at a traditional meteorological tower or by a weather 

balloon or other non-traditional sources. Observation nudging works best at finer grid spacing 

scales and could have been performed on higher resolution domains using the Meteorological 

Assimilation Data Ingest System (MADIS) observation archive.

The WRF model was run with analysis nudging and no observation nudging. For winds and 

temperature, analysis nudging coefficients of 5x10-4 and 3.0x10-4 were used on the 36- and 12-km 

domains, respectively. For mixing ratio, an analysis nudging coefficient of 1.0x10-5 was used for 

both the 36- and 12-km domains. Analysis nudging of winds was applied both at near the surface 

and aloft, but nudging for temperature and mixing ratio was not performed in the lower atmosphere 

(i.e., within the boundary layer).

Significant sensitivity testing was used to evaluate impacts of observational nudging on the 

4-km domain. The observational nudging coefficients for winds were tested at values set from 0 to 
Air Quality: WRF Model Performance B-11

1.2x10-3 with a radius of influence at 50 km. Ramboll Environ concluded that any observational 

nudging coefficient for winds above zero caused excessive convection in the offshore portions of the 

Gulf of Mexico, resulting in an extreme overstatement of precipitation. Additionally, humidity nudging 

was tested at values ranging from 0 to 1.0x10-5. The lower nudging values also prevented excess 

moisture in the model, primarily through the summer months. Setting wind, temperature, and 

moisture coefficients all to zero produced the most accurate precipitation results and are very similar 

to the nudging used in the USEPA 2011 CONUS WRF dataset (Gilliam and Pleim, 2010).

B.2.3.11 WRF Physics Options

The WRF model contains many different physics options. Model tests for the months of 

January and July 2012 were performed to evaluate various cumulus parameterizations, times 

between radiation physics calls, and land surface models to achieve the best WRF performance in 

the dataset. Table B-4 lists the BOEM Gulf of Mexico OCS Region WRF physics options.

Table B-4. BOEM Gulf of Mexico OCS Region WRF Physics Options. 

Option Scheme Notes

Microphysics Thompson State-of-the-art microphysics model

Longwave Radiation RRTMG

Rapid Radiative Transfer Model for GCMs 

includes random cloud overlap and 

improved efficiency over RRTM.

Shortwave Radiation RRTMG Same as above, but for shortwave 

radiation.

Land Surface Model 

(LSM) Noah Four-layer scheme with vegetation and sub-grid tiling.

Planetary Boundary 

Layer (PBL) scheme YSU

Yonsie University (Korea) Asymmetric 

Convective Model with non-local upward 

mixing and local downward mixing.

Cumulus 

Parameterization

Kain-Fritsch in the 36-km and 

12-km domains.

Deep and shallow convection sub-grid 

scheme using a mass flux approach with 

downdrafts and CAPE removal time scale.

Analysis Nudging

Nudging applied to winds, 

temperature and moisture in the 

36-km and 12-km domains.

Temperature and moisture nudged above 

PBL only.

Observation Nudging No nudging applied

Surface wind and moisture observational 

nudging can induce excessive convection, 

leading to increased rainfall.

Surface Layer Revised MM5 Monin-Obukhov 

scheme In conjunction with YSU PBL scheme.

B.2.3.12 WRF Application Methodology

The WRF model was executed in 5-day blocks initialized at 12Z every 5 days for calendar 

year 2012. Model results are output every 60 minutes and output files are split at 12-hour intervals. 

Twelve (12) hours of spin-up were included in each 5-day block before the data were used in the 

subsequent evaluation. 
B-12 2018 Gulf of Mexico Supplemental EIS

B.3 WRF MODEL PERFORMANCE EVALUATION RESULTS

A quantitative and qualitative evaluation of the BOEM Gulf of Mexico OCS Region WRF 

simulation was conducted. The quantitative evaluation compared integrated surface hourly

meteorological observations and offshore buoy observations with WRF predictions matched by time 

and location. The qualitative evaluation compared twice daily vertical profiles with upper-air data 

with WRF predictions matched by time and location and wind roses of coastal sites. Additionally, 

monthly and daily total spatial precipitation fields based on observations and satellite were compared 

with the WRF gridded monthly and daily total precipitation fields. Below, we summarize the main 

features of the WRF simulation model performance evaluation.

B.3.1 Quantitative Evaluation Using Metstat

A quantitative model performance evaluation of the BOEM Gulf of Mexico OCS Region WRF 

simulation was performed using integrated hourly surface and on-site meteorological measurements 

and the publicly available METSTAT software (Ramboll Environ, 2015) evaluation tool. METSTAT 

calculates statistical performance metrics for bias, error and correlation for surface winds, 

temperature, and mixing ratio (i.e., water vapor or humidity). To evaluate the performance of a 

meteorological model simulation for air quality model applications, a number of performance 

benchmarks for comparison are typically used. Table B-5 lists the meteorological model 

performance benchmarks for simple (Emery et al., 2001) and complex (Kemball-Cook et al., 2005) 

situations. The simple benchmarks were developed by analyzing well-performing meteorological

model evaluation results for simple, mostly flat terrain conditions and simple meteorological 

conditions (e.g., stationary high pressure) that were mostly conducted to support air quality modeling 

studies (e.g., ozone SIP modeling). The complex benchmarks were developed during the Western 

Regional Air Partnership (WRAP) regional haze modeling and are performance benchmarks for 

more complex conditions, such as the complex terrain of the Rocky Mountains and Alaska 

(Kemball-Cook et al., 2005). McNally (2009) analyzed multiple annual runs that included complex 

terrain conditions and suggested an alternative set of benchmarks for temperature under more 

complex conditions. The purpose of the benchmarks is to understand how good or poor the results 

are relative to other model applications run for the U.S. 

In this section, Ramboll Environ compare the WRF meteorological variables to the 

benchmarks as an indication of the BOEM Gulf of Mexico OCS Region WRF model performance. 

These benchmarks include bias and error in temperature, wind direction, and mixing ratio, as well as 

the wind speed bias and Root Mean Squared Error (RMSE) between the models and databases.

Table B-5. Meteorological Model Performance Benchmarks for Simple and Complex Conditions. 

Parameter Emery et al. (2001) Kemball-Cook et al. (2005) McNally (2009)

Conditions Simple Complex Both

Temperature Bias ≤ ±0.5 K ≤ ±2.0 K ≤ ±1.0 K

Temperature Error ≤ 2.0 K ≤ 3.5 K ≤ 3.0 K

Temperature IOA ≥ 0.8 (not addressed) (not addressed)

Humidity Bias ≤ ±1.0 g/kg ≤ ±0.8 g/kg ≤ ±1.0 g/kg
Air Quality: WRF Model Performance B-13

Parameter Emery et al. (2001) Kemball-Cook et al. (2005) McNally (2009)

Humidity Error ≤ 2.0 g/kg ≤ 2.0 g/kg ≤ 2.0 g/kg

Humidity IOA ≥ 0.6 (not addressed) (not addressed)

Wind Speed Bias ≤ ±0.5 m/s ≤ ±1.5 m/s (not addressed)

Wind Speed RMSE ≤ 2.0 m/s ≤ 2.5 m/s (not addressed)

Wind Speed IOA ≥ 0.6 (not addressed) (not addressed)

Wind Dir. Bias ≤ ±10 degrees (not addressed) (not addressed)

Wind Dir. Error ≤ 30 degrees ≤ 55 degrees (not addressed)

The output from the BOEM Gulf of Mexico OCS Region WRF simulation was compared 

against the NCDC’s global-scale, quality-controlled DS3505 integrated surface hourly observational 

(ISHO) data (USDOC, NOAA, NCDC, 2015) and the NDBC’s buoy database (USDOC, NOAA, 

NDBC, 2015) as verification data. Global hourly and synoptic observations are compiled from 

numerous sources into a single common ASCII format and common data model. The DS3505 

database contains records of most official surface meteorological stations from airports, military 

bases, reservoirs/dams, agricultural sites, and other sources dating from 1901 to the present, and 

quality control has corrected well over 99% of the errors present in the original data. The NDBC 

database contains records of moored buoys, coastal-marine automated network stations, and other 

sources dating from 1970 to the present.

B.3.1.1 Quantitative Statistics

Several statistical measures are calculated as part of the meteorological model evaluation. 

Additional plots and graphs are used to present these statistics on both hourly and daily timeframes. 

These measures are calculated for wind speed, wind direction, temperature, and humidity at the 

surface. The various statistical measures used for this evaluation are described below. 

The statistics used to evaluate meteorological model performance are all given in absolute 

terms (e.g., wind speed error in meters per second [m/s]) rather than in relative terms (percent error) 

as is commonly shown for air quality assessments. The major reason for this is that a very different 

significance is associated with a given relative error for different meteorological parameters. For 

example, a 10 percent error for wind speed measured at 10 m/s is an absolute error of 1 m/s, a 

minor error. Yet a 10 percent error for temperature at 300 K is an absolute error of 30 K, an 

unacceptably large error. On the other hand, pollutant concentration errors of 10 percent at 1 ppb or 

10 ppm carry practically the same significance.

Statistical Measures

Mean Observation (Mo): Calculated from all sites with valid data within a given analysis region and 

for a given time period (hourly or daily):
B-14 2018 Gulf of Mexico Supplemental EIS

∑∑= =

=

J

j

I

i

i

o Oj IJ

M

1 1

1

where Oi

j is the individual observed quantity at site i and time j, and the summations are over all 

sites (I) and over time periods (J).

Mean Prediction (Mp): Calculated from simulation results that are interpolated to each observation 

used to calculate the mean observation (hourly or daily):

∑∑= =

=

J

j

I

i

i

p Pj IJ

M

1 1

1

where Pi

j is the individual predicted quantity at site i and time j. Note that mean observed and 

predicted winds are vector-averaged (for east-west component u and north-south component v), 

from which the mean wind speed and mean resultant direction are derived. 

Least Square Regression: Performed to fit the prediction set to a linear model that describes the 

observation set for all sites with valid data within a given analysis region and for a given time 

period (daily or episode). The y-intercept a and slope b of the resulting straight line fit is 

calculated to describe the regressed prediction for each observation:

i

j

i

j += bOaP

The goal is for a 1:1 slope and a “0” y-intercept (no net bias over the entire range of 

observations), and a regression coefficient of 1 (a perfect regression). The slope and intercept 

facilitate the calculation of several error and skill statistics described below.

Bias Error (B): Calculated as the mean difference in prediction-observation pairings with valid data 

within a given analysis region and for a given time period (hourly or daily):

∑∑( ) = =

= −

J

j

I

i

i

j

i

j OP

IJ

B

1 1

1

Gross Error (E): Calculated as the mean absolute difference in prediction-observation pairings with 

valid data within a given analysis region and for a given time period (hourly or daily):

∑∑= =

= −

J

j

I

i

i

j

i

j OP

IJ

E

1 1

1

Note that the bias and gross error for winds are calculated from the predicted-observed residuals 

in speed and direction (not from vector components u and v). The direction error for a given 

prediction-observation pairing is limited to range from 0 to 180.

Root Mean Square Error (RMSE): Calculated as the square root of the mean squared difference in 

prediction-observation pairings with valid data within a given analysis region and for a given time 

period (hourly or daily):
Air Quality: WRF Model Performance B-15

( )

2/1

1 1

1 2





 



 = ∑∑ − = =

J

j

I

i

i

j

i

j OP

IJ

RMSE

The RMSE, as with the gross error, is a good overall measure of model performance. However, 

since large errors are weighted heavily (due to squaring), large errors in a small sub-region may 

produce a large RMSE even though the errors may be small and quite acceptable elsewhere.

It is important that RMSE is analyzed. For example, if only RMSE is estimated (and it 

appears acceptable), it could consist largely of the systemat¬ic component. This error might be 

removed through improvements in the model inputs or use of more appropriate options, thereby 

reducing the error transferred to the photochemical model. On the other hand, if the RMSE consists 

largely of the unsystematic component, this indicates that further error reduction may require model 

refinement (new algorithms, higher resolution grids, etc.) or that the phenomena to be replicated 

cannot be fully addressed by the model. It also provides error bars that may be used with the inputs 

in subsequent sensitivity analyses.

B.3.1.2 METSTAT Evaluation Using Integrated Surface Hourly Observations and Offshore

Buoy Observations

The METSTAT results for 2012 are presented in Figures B-5 through B-16. The WRF wind 

direction performed very well, with the majority of months falling within the simple conditions 

threshold for all spatial domains (36, 12, and 4 km). For all domains, WRF wind speed, temperature, 

and humidity also performed very well. For most months, there are slight positive biases in wind 

speed and humidity in all three spatial domains. Overall, the WRF model performed exceptionally 

well in the 36- and 12-km domains and well in the 4-km domain for onshore surface wind direction, 

wind speed, humidity and temperature observation comparisons.

METSTAT was also used to evaluate WRF performance in the innermost 4-km domain using 

observations from meteorological buoys throughout the Gulf of Mexico for 2012. Overall, WRF wind 

direction performed well with over half of all months falling with the simple conditions benchmark. 

Wind speed performance was acceptable with all months falling within the complex conditions 

benchmark. Temperature bias and error is slightly higher (warmer) in the winter months compared 

to the summer months, suggesting that the model is over-forecasting surface temperatures, or is an 

influence from the SST database input to WRF. Humidity performed well with a majority of months, 

falling within the simple conditions benchmark. In general, the offshore METSTAT evaluation is very 

similar to the onshore evaluation, suggesting consistent performance over both the land and sea 

portions of the Gulf of Mexico OCS region. 
B-16 2018 Gulf of Mexico Supplemental EIS

Figure B-5. BOEM Gulf of Mexico OCS Region WRF 36-km METSTAT Wind Direction 

Performance for 2012. 

Figure B-6. BOEM Gulf of Mexico OCS Region WRF 36-km METSTAT Wind Speed 

Performance for 2012. 
Air Quality: WRF Model Performance B-17

Figure B-7. BOEM Gulfof Mexico OCS Region WRF 36-km METSTAT Temperature 

Performance for 2012. 

Figure B-8. BOEM Gulf of Mexico OCS Region WRF 36-km METSTAT Humidity Performance 

for 2012. 
B-18 2018 Gulf of Mexico Supplemental EIS

Figure B-9. BOEM Gulf of Mexico OCS Region WRF 12-km METSTAT Wind Direction 

Performance for 2012. 

Figure B-10. BOEM Gulf of Mexico OCS Region WRF 12-km METSTAT Wind Speed 

Performance for 2012. 
Air Quality: WRF Model Performance B-19

Figure B-11. BOEM Gulf of Mexico OCS Region WRF 12-km METSTAT Temperature 

Performance for 2012. 

Figure B-12. BOEM Gulf of Mexico OCS Region WRF 12-km METSTAT Humidity Performance 

for 2012. 
B-20 2018 Gulf of Mexico Supplemental EIS

Figure B-13. BOEM Gulf of Mexico OCS Region WRF 4-km METSTAT Wind Direction 

Performance for 2012. 

Figure B-14. BOEM Gulf of Mexico OCS Region WRF 4-km METSTAT Wind Speed Performance 

for 2012. 
Air Quality: WRF Model Performance B-21

Figure B-15. BOEM Gulf of Mexico OCS Region WRF 4-km METSTAT Temperature 

Performance for 2012. 

Figure B-16. BOEM Gulf of Mexico OCS Region WRF 4-km METSTAT Humidity Performance for 

2012. 
B-22 2018 Gulf of Mexico Supplemental EIS

B.3.2 Qualitative Evaluation Using Wind Roses

The coastal sites of Gulfport, MS (KGPT); Naples, FL (NPSF); Port Isabel, TX (PTIT); and 

Calcasieu, LA (CAPL) were chosen to evaluate the frequency and intensity of onshore and offshore 

wind flow and WRF’s performance at the land-sea interface. The locations of these sites are shown 

in Figure B-17. The 5-year comparisons of observed and modeled wind direction at each coastal 

site will be provided in the full WRF modeling report. Below, in Figures B-17 through B-21, the 

comparisons are made for only 2012. Wind direction observations were obtained from the DS3505 

meteorological dataset, and modeled surface wind speed and wind direction were extracted from the 

4-km WRF domain dataset using the Mesoscale Model Interface (MMIF) program (Brashers and 

Emery, 2015). Overall, WRF performs just satisfactorily at forecasting the frequency and intensity of 

onshore and offshore wind flow at the coastal sites. The WRF simulates the predominant NE wind 

direction at NPSF, as well as the strong SE winds at port PTIT and CAPL. However, WRF wind 

direction does not compare particularly well to KGPT in 2012 and does not replicate much of the NW 

wind at PTIT, or the SW wind at NPSF. The decline in apparent wind direction performance for 

2012, compared to the 5-year analysis, is largely due to the shorter evaluation period.

Figure B-17. Wind Rose Locations for Port Isabel, TX (PTIT), Calcasieu, LA (CAPL), Gulfport, MS 

(KGPT), and Naples, FL (NPSF). 
Air Quality: WRF Model Performance B-23

Figure B-18. 2012 WRF Wind Rose (left) Compared to 2012 Observation Wind Rose from Gulfport, MS (right) in 4-km Domain. 
B-24 2018 Gulf of Mexico Supplemental EIS

Figure B-19. 2012 WRF Wind Rose (left) Compared to 2012 Observation Wind Rose from Naples, FL (right) in 4-km Domain. 
Air Quality: WRF Model Performance B-25

Figure B-20. 2012 WRF Wind Rose (left) Compared to 2012 Observation Wind Rose from Port Isabel, TX (right) in 4-km Domain. 
B-26 2018 Gulf of Mexico Supplemental EIS

Figure B-21. 2012 WRF Wind Rose (left) Compared to 2012 Observation Wind Rose from Calcasieu, LA (right) in 4-km Domain. 
Air Quality: WRF Model Performance B-27

B.3.3 Qualitative Evaluation Using Upper-Air Data

Plots of the sounding profiles of temperature and dew point for the vertical atmosphere were 

created using observational data from the Brownsville, TX (KBRO) and Key West, FL (KEYW) 

airports and the corresponding WRF data points. A random selection of upper air profiles was taken 

from the year-long dataset for a sampling of several different atmospheric situations. These are 

qualitatively compared, paying particular attention to how well the WRF model reproduces the 

observed near-surface inversion layers.

The KBRO and KEYW radiosonde datasets are collected by and maintained by the National 

Weather Service (NWS). Radiosondes are launched twice per day, at approximately 00 and 

12 UTC. Radiosondes provide high-resolution vertical profiles of temperature, humidity, wind speed, 

and wind direction throughout the troposphere. The data are made publicly available by NOAA’s 

Earth System Research Laboratory (USDOC, NOAA, ESRL, 2015). Ramboll Environ downloaded 

and stored the radiosonde data twice daily for 2012 for each upper air station in FSL format for use 

in WRF model dataset comparisons. 

For the qualitative analysis, Figure B-22 shows the vertical profiles of temperature and 

humidity from the observational and 4 km WRF datasets for Brownsville, TX and Key West, FL. The 

analysis focuses on how well the WRF model reproduces the vertical atmosphere structure using 

upper air observations from the selected sites within the 4-km domain, which have timeframes that 

overlap with the WRF model. The left panel in Figure B-22 shows an evening sounding in August 

for Brownville, TX, which contains a weak elevated subsidence inversion. The WRF forecasts the 

base of the inversion well at around 900 meters. The right panel of Figure B-22 shows observed 

and modeled vertical profiles for January in Key West, FL. The WRF forecasts the elevated 

subsidence inversion well, with a mixing height top at around 1,000 meters on the left panel. The 

dry air above the inversion is also represented well in the evening sounding at Key West, FL.
B-28 2018 Gulf of Mexico Supplemental EIS

Figure B-22. Vertical Profile Soundings Comparing the 4-km WRF (blue lines) to Upper-Air Observations Data (red lines) for 

Brownsville, TX on August 3, 2012, and Key West, FL on January 4, 2012, at 00 UTC. 
Air Quality: WRF Model Performance B-29

B.3.4 Qualitative Evaluation Using Precipitation

Precipitation removes chemicals and particulates from the air via wet deposition, and thus is 

an important parameter for high-quality dispersion modeling. Several precipitation datasets were 

evaluated for use in model comparisons. Ramboll Environ has used the Parameter-elevation 

Regressions on Independent Slopes Model (PRISM) dataset for rainfall extensively in the past, but it 

only covers the over-land portion of the modeling domain. Land-based RADAR retrievals of 

precipitation typically have larger uncertainty and are limited in geographic coverage to the area 

relatively near the coast and, as a result, were not chosen for this performance evaluation. Satellitebased retrievals are typically lower resolution and also feature larger uncertainty, but cover the entire 

Gulf of Mexico OCS region. Ramboll Environ performed comparisons between the BOEM Gulf of 

Mexico OCS Region WRF modeled precipitation output with the PRISM and Tropical Rainfall 

Measurements Mission (TRMM) satellite datasets.

The Oregon State University PRISM Climate Group gathers temperature and precipitation 

data from a range of monitoring networks, applies sophisticated quality control methods, and uses 

the data to produce spatial grids of climate parameters (Daly et al., 2008). The time series datasets 

are modeled using climatologically-aided interpolation (CAI), which uses the long-term average 

pattern as first-guess of the spatial pattern of climatic conditions. Both a daily product and a monthly 

product are available. The precipitation observations used in the daily PRISM product includes 

radar measurements, which the monthly product does not take into account. This may cause 

dramatic local differences between the two datasets in monthly totals.

TRMM was a joint mission being flown by the National Aeronautics and Space 

Administration (NASA, U.S.) and the Japan Aerospace Exploration Agency (JAXA, Japan) to 

improve our quantitative knowledge of the 3-dimensional distribution of precipitation in the tropics. 

TRMM had a passive microwave radiometer (TRMM Microwave Imager, TMI), the first active spaceborne Precipitation Radar (PR), a Visible-Infrared Scanner (VIRS), and other instruments. 

Coordinated observations are intended to result in a "flying raingauge" capability. The TRMM 

dataset is coarser than the PRISM data (0.5 degrees, or about 55 km, vs. 4 km) but is available 

every 3 hours.

B.3.4.1 Evaluation Over Land Using PRISM Precipitation

High-resolution (4 km) PRISM datasets cover the contiguous U.S. in both monthly and daily 

output versions (Daly et al., 2008). Here WRF precipitation output is compared to the PRISM 

over-land portions of the Gulf of Mexico. Ramboll Environ re-projected and aggregated the PRISM 

data to the WRF projection’s grid cell locations, and the resulting gridded data was plotted and the 

gridded fields saved. This allows for consistent visual qualitative comparison.

The full WRF modeling report will display 5-year average (2010-2014) monthly precipitation 

plots constructed from BOEM Gulf of Mexico OCS Region WRF output, masked to only display 

over-land measurements, and compared to PRISM 5-year average (2010-2014) monthly plots for 

January through December in the 4-km domain. Below, WRF monthly precipitation totals are 
B-30 2018 Gulf of Mexico Supplemental EIS

compared to corresponding PRISM totals for 2012 only. The results are mostly representative of the 

5-year monthly averages and are briefly summarized in the following paragraph.

For the months of January through March, shown in Figures B-23 through B-25, WRF 

represents the spatial extent of the precipitation well, recreating the comparatively drier areas of 

central Texas and southern Florida. However, the model does under-estimate the total amount of 

average monthly rainfall across a small portion of southern Mississippi and south central Louisiana 

during this period. In April and May, Figures B-26 and B-27, the model shifts to overestimating 

rainfall in the same region, but otherwise depicts both the spatial distribution and amount of 

precipitation well over land, compared to PRISM. During the summer months of June through 

August, shown in Figures B-28 through B-30, WRF performs exceptionally well in re-creating the 

precipitation extent across the land portions of the domain, including the convergence zones across 

the east and west coasts of Florida. The model does slightly over-predict the amount of rainfall 

accumulations in the southern Georgia and southern Alabama areas. This is likely due to the higher 

humidity rates in the model during the summertime period. In September, shown in Figure B-31, 

WRF slightly under-predicts averaged precipitation rates over the land portion of the domain but 

over-forecasts the extent of rainfall over the northern Florida area. The WRF performed 

exceptionally well from October through December, shown in Figures B-32 through B-34, 

reproducing the extent and amount of rainfall very accurately, compared to PRISM totals. Overall, 

WRF performed very well in reproducing the spatial extent of precipitation over the land portions of 

Gulf of Mexico OCS region throughout 2012.
Air Quality: WRF Model Performance B-31

Figure B-23. January 2012 PRISM Precipitation (top) and WRF Precipitation (bottom), 4-km Domain. 
B-32 2018 Gulf of Mexico Supplemental EIS

Figure B-24. February 2012 PRISM Precipitation (top) and WRF Precipitation (bottom), 4-km Domain. 
Air Quality: WRF Model Performance B-33

Figure B-25. March 2012 PRISM Precipitation (top) and WRF Precipitation (bottom), 4-km Domain. 
B-34 2018 Gulf of Mexico Supplemental EIS

Figure B-26. April 2012 PRISM Precipitation (top) and WRF Precipitation (bottom), 4-km Domain. 
Air Quality: WRF Model Performance B-35

Figure B-27. May 2012 PRISM Precipitation (top) and WRF Precipitation (bottom), 4-km Domain. 
B-36 2018 Gulf of Mexico Supplemental EIS

Figure B-28. June 2012 PRISM Precipitation (top) and WRF Precipitation (bottom), 4-km Domain. 
Air Quality: WRF Model Performance B-37

Figure B-29. July 2012 PRISM Precipitation (top) and WRF Precipitation (bottom), 4-km Domain. 
B-38 2018 Gulf of Mexico Supplemental EIS

Figure B-30. August 2012 PRISM Precipitation (top) and WRF Precipitation (bottom), 4-km Domain. 
Air Quality: WRF Model Performance B-39

Figure B-31. September 2012 PRISM Precipitation (top) and WRF Precipitation (bottom), 4-km Domain. 
B-40 2018 Gulf of Mexico Supplemental EIS

Figure B-32. October 2012 PRISM Precipitation (top) and WRF Precipitation (bottom), 4-km Domain. 
Air Quality: WRF Model Performance B-41

Figure B-33. November 2012 PRISM Precipitation (top) and WRF Precipitation (bottom), 4-km Domain. 
B-42 2018 Gulf of Mexico Supplemental EIS

Figure B-34. December 2012 PRISM Precipitation (top) and WRF Precipitation (bottom), 4-km Domain. 
Air Quality: WRF Model Performance B-43

B.3.4.2 Evaluation Over Water Using Satellite Precipitation

In this analysis, WRF precipitation data are also compared to TRMM satellite precipitation 

data to assess the accuracy of the WRF precipitation. Ramboll Environ re-projected and aggregated 

the TRMM data to the WRF projection’s grid cell locations, and the resulting gridded data was 

plotted and the gridded fields saved. This allows for a consistent visual qualitative comparison, 

although the 0.5-degree (~55-km) TRMM dataset is at a lower resolution than the 4-km PRISM 

dataset and as a result, the satellite precipitation fields appear much coarser in the 4-km domain. 

Additionally, near the end of the WRF modeling period, the satellite hosting the TRMM sensor ran 

out of propellant. This caused its orbit to slowly decay, casting into doubt the validity of the derived 

rainfall quantities and is the reason only a qualitative comparison is presented below. Below, 

Figures B-35 through B-46 show monthly WRF precipitation averages compared to TRMM 

precipitation averages throughout 2012 in the 12-km domain.

The WRF under-predicts precipitation over the offshore portions of the domain, compared to 

TRMM for the averaging months of January through May, as shown in Figures B-35 through B-39. 

From June through October, WRF performs well at predicting precipitation spatially and numerically, 

shown in Figures B-40 through B-44. The increased amount of rainfall over the southeast Gulf 

Coast States, stretching out over the coastlines, is well represented through the summertime 

months. The WRF slightly under-predicts the amount of rainfall in the offshore portions of the Gulf, 

compared to the TRMM precipitation averages for November and December, shown in Figures B-45

and B-46. Even with the coarse TRMM resolution, it appears the model has a slight dry bias in the 

over-water portions of the domain in the colder months.

Given the coarser resolution of the TRMM plots, WRF tends to under-forecast precipitation 

intensity overall in the offshore portions of the Gulf throughout the winter and spring months and 

does a satisfactory job at forecasting the amount of rainfall over water in the summer and fall months 

in the 4-km domain.
B-44 2018 Gulf of Mexico Supplemental EIS

Figure B-35. January 2012 TRMM Precipitation Average (top) and 

Corresponding WRF Precipitation Average (bottom) in the 

12-km Domain. 
Air Quality: WRF Model Performance B-45

Figure B-36. February 2012 TRMM Precipitation Average (top) and 

Corresponding WRF Precipitation Average (bottom) in the 

12-km Domain. 
B-46 2018 Gulf of Mexico Supplemental EIS

Figure B-37. March 2012 TRMM Precipitation Average (top) and 

Corresponding WRF Precipitation Average (bottom) in the 

12-km Domain. 
Air Quality: WRF Model Performance B-47

Figure B-38. April 2012 TRMM Precipitation Average (top) and 

Corresponding WRF Precipitation Average (bottom) in the 

12-km Domain. 
B-48 2018 Gulf of Mexico Supplemental EIS

Figure B-39. May 2012 TRMM Precipitation Average (top) and 

Corresponding WRF Precipitation Average (bottom) in the 

12-km Domain. 
Air Quality: WRF Model Performance B-49

Figure B-40. June 2012 TRMM Precipitation Average (top) and 

Corresponding WRF Precipitation Average (bottom) in the 

12-km Domain. 
B-50 2018 Gulf of Mexico Supplemental EIS

Figure B-41. July 2012 TRMM Precipitation Average (top) and 

Corresponding WRF Precipitation Average (bottom) in the 

12-km Domain. 
Air Quality: WRF Model Performance B-51

Figure B-42. August 2012 TRMM Precipitation Average (top) and 

Corresponding WRF Precipitation Average (bottom) in the 

12-km Domain. 
B-52 2018 Gulf of Mexico Supplemental EIS

Figure B-43. September 2012 TRMM Precipitation Average (top) and 

Corresponding WRF Precipitation Average (bottom) in the 

12-km Domain. 
Air Quality: WRF Model Performance B-53

Figure B-44. October 2012 TRMM Precipitation Average (top) and 

Corresponding WRF Precipitation Average (bottom) in the 

12-km Domain. 
B-54 2018 Gulf of Mexico Supplemental EIS

Figure B-45. November 2012 TRMM Precipitation Average (top) and 

Corresponding WRF Precipitation Average (bottom) in the 

12-km Domain. 
Air Quality: WRF Model Performance B-55

Figure B-46. December 2012 TRMM Precipitation Average (top) and 

Corresponding WRF Precipitation Average (bottom) in the 

12-km Domain. 
B-56 2018 Gulf of Mexico Supplemental EIS

B.3.4.3 Evaluation Using Tropical Cyclone Precipitation Events

In order to evaluate the accuracy of the WRF model for precipitation performance, short-term 

rainfall events were also analyzed for local and regional scale impacts. Daily precipitation plots were 

created for every 24-hour period from the WRF, PRISM, and TRMM databases. Tropical cyclone 

events were chosen as each storm system typically produces a wide area of enhanced rainfall for 

both onshore and offshore areas.

A tropical cyclone is a warm-core, non-frontal synoptic-scale cyclone, originating over 

tropical or subtropical waters, with organized deep convection and a closed surface wind circulation 

about a well-defined center (NHC, 2015). Increased rainfall events from two cyclones, Hurricane 

Isaac and Tropical Storm Debby, are presented in a qualitative comparison.

Hurricane Isaac made landfall along the coast of southern Louisiana on August 29, 2012, 

and moved northward, where it was downgraded to a tropical storm on August 30th. Daily 

precipitation plots from each dataset on August 30th are shown in Figure B-47. The WRF depicts 

the large cyclonic rotation and enhanced precipitation bands from Isaac over southeast Louisiana 

very well, compared to the PRISM dataset. Compared to TRMM, the model does appear to overforecast the rainfall intensity for this 24-hour period.

Figure B-48 shows daily precipitation plots as Tropical Storm Debby’s outer rain bands 

begin to impact Florida’s west coast on June 25, 2012. The WRF performed very well in comparison 

to both PRISM and TRMM, forecasting the spatial extent of the large storm throughout the eastern 

Gulf of Mexico. The model did slightly under-predict the rainfall accumulations in this 24-hour 

period, compared to the observational and satellite databases.

Overall, WRF performed very well in recreating the daily precipitation events in these two 

scenarios. The daily precipitation plots from each WRF, PRISM, and TRMM dataset are available by 

request from Ramboll Environ.
Air Quality: WRF Model Performance B-57

Figure B-47. Daily Precipitation Plots from WRF, PRISM, and TRMM on August 30, 2012. 
B-58 2018 Gulf of Mexico Supplemental EIS

Figure B-48. Daily Precipitation Plots from WRF, PRISM, and TRMM Databases on June 25, 

2012. 
Air Quality: WRF Model Performance B-59

B.4 SUMMARY AND CONCLUSIONS

The BOEM Gulf of Mexico OCS Region WRF meteorological model simulation for January 

through December 2012 reproduced the observed surface and upper-air meteorological variables 

very well. The WRF performed exceptionally well in the onshore METSTAT analysis for the 36-km 

and 12-km domains and well in the onshore and offshore analysis for the 4-km domain, with a small 

bias in wind direction. This performance shows a very strong agreement overall between the model 

and surface observations.

Comparisons of selected wind roses along the Gulf Coast, which will be presented in the full 

WRF model evaluation, show WRF was able to forecast the offshore and onshore wind speed and 

wind direction very well in the 4-km domain. This suggests the model was able to accurately 

reproduce the land-sea breeze circulation.

Upper air performance in the 4-km (d03) domain for the two selected locations throughout 

the Gulf of Mexico reflects accurate predictions of the vertical atmosphere, as shown in comparisons 

between WRF and radiosonde data, especially in mixing layer heights and cases of surface-based 

temperature inversions.

The monthly precipitation analysis for the 4-km (d03) domain indicates there is a strong 

agreement between the model and observation-based precipitation measurements over land, 

including convergence zone and enhanced rainfall areas. The comparison with the 12-km (d02) 

WRF and satellite-based precipitation accumulations does indicate some understatement of 

precipitation over water, most notably in the winter months.

Based on our experience, the BOEM Gulf of Mexico OCS Region WRF modeling’s superior 

performance throughout 2012 provides a substantial basis for developing meteorological inputs for 

air quality modeling in the Gulf of Mexico region.

B.5 REFERENCES

Brashers, B. and C. Emery. 2015. The Mesoscale Model Interface Program (MMIF), Version 3.2, 

2015-07-24, Draft User’s Manual. Prepared for USEPA, Office of Air Quality Planning and 

Standards. Ramboll Environ US Corporation (Ramboll Environ). Internet website: 

http://www.epa.gov/ttn/scram/models/relat/mmif/MMIFv3.2_Users_Manual.pdf. 

Brashers, B., J. Knapik, and R. Morris. 2014. Official communication. Technical memorandum 

concerning BOEM Contract No. M14PC00007, Task 2 WRF Meteorological Model Dataset 

Assessment for the Air Quality Modeling in the Gulf of Mexico Region to Holli Ensz, Bureau of 

Ocean Energy Management, Gulf of Mexico Region. Prepared by ENVIRON International 

Corporation, Lynnwood, WA.

Daly, C., M. Halbleib, J.I. Smith, W.P. Gibson, M.K. Doggett, G.H. Taylor, J. Curtis, and 

P.P. Pasteris. 2008. Physiographically sensitive mapping of climatological temperature and 
B-60 2018 Gulf of Mexico Supplemental EIS

precipitation across the conterminous United States. Int. J. Climatol. Internet website: 

http://prism.nacse.org/documents/Daly2008_PhysiographicMapping_IntJnlClim.pdf. 

Emery, C.A., E. Tai, and G. Yarwood. 2001. Enhanced Meteorological Modeling and Performance 

Evaluation for Two Texas Ozone Episodes. Prepared for the Texas Natural Resource 

Conservation Commission (now TCEQ) by ENVIRON International Corp, Novato, CA. Internet 

website: http://www.tceq.texas.gov/assets/public/implementation/air/am/contracts/reports/mm/

EnhancedMetModelingAndPerformanceEvaluation.pdf. 

Gilliam, R.C. and J.E. Pleim. 2010. Performance assessment of new land-surface and planetary 

boundary layer physics in the WRF-ARW. Journal of Applied Meteorology and Climatology 49, 

760-774.

Kemball-Cook, S., Y. Jia, C. Emery, and R. Morris. 2005. Alaska MM5 Modeling for the 2002 

Annual Period to Support Visibility Modeling. Prepared for the Western Regional Air Partnership, 

by ENVIRON International Corp., Novato, CA. Internet website: http://pah.cert.ucr.edu/

aqm/308/docs/alaska/Alaska_MM5_DraftReport_Sept05.pdf. 

McNally, D.E. 2009. 12 km MM5 Performance Goals. Presentation to the Ad-Hoc Meteorology 

Group. June 25, 2009. Internet website: http://www.epa.gov/scram001/adhoc/mcnally2009.pdf. 

NCAR. 2015. National Center for Atmospheric Research. Internet website: 

http://www2.mmm.ucar.edu/wrf/users/download/get_source.html. 

Ramboll Environ US Corp. 2015. METSTAT. Internet website: http://www.camx.com/download/

support-software.aspx. 

Saha, S., S. Moorthi, X. Wu, J. Wang, S. Nadiga, P. Tripp, D. Behringer, Y-T. Hou, H-y. Chuang, 

M. Iredell, M. Ek, J. Meng, R. Yang, M. Peña Mendez, H. van den Dool, Q. Zhang, W. Wang, 

M. Chen, and E. Becker. 2014. The NCEP Climate Forecast System Version 2. Journal of 

Climate 27, 2185-2208. doi:http://dx.doi.org/10.1175/JCLI-D-12-00823.1.

SCAS-OSU. 2001. Climate Mapping with PRISM. Oregon State University (OSU)

U.S.Dept. of Commerce, National Oceanic and Atmospheric Administration, Earth System Research 

Laboratory. 2015. NOAA/ESRL Radiosonde Database. Internet website: www.esrl.noaa.gov/

raobs. 

USDOC, NOAA, NCDC. 2014. NOAA NCDC Integrated Surface Database. Internet website: 

www.ncdc.noaa.gov/isd. 
APPENDIX C 

 

AIR QUALITY: 

EMISSIONS FOR THE CUMULATIVE AND VISIBILITY IMPACTS

Table of Contents C-iii

TABLE OF CONTENTS

Page

C.1 INTRODUCTION........................................................................................................................ C-1

C.2 DEVELOPMENT OF EMISSION INVENTORIES ..................................................................... C-4

C.2.1 Pollutants......................................................................................................................... C-5

C.2.2 Base Case Year .............................................................................................................. C-5

C.2.3 Geographical Domain...................................................................................................... C-5

C.2.4 Inventory Sources ........................................................................................................... C-6

C.2.5 Spatial Resolution ........................................................................................................... C-8

C.2.6 Temporal Resolution ....................................................................................................... C-8

C.2.7 Speciation........................................................................................................................ C-8

C.3 BASE CASE EMISSION ESTIMATES ...................................................................................... C-8

C.3.1 Point Sources .................................................................................................................. C-8

C.3.2 Nonpoint Area Sources ................................................................................................... C-9

C.3.3 Mobile Sources................................................................................................................ C-9

C.3.4 Offshore Helicopters...................................................................................................... C-10

C.3.5 Offshore Oil and Gas Production Sources—Western and Central/Eastern 

Planning Areas in the Gulf of Mexico............................................................................ C-10

C.3.6 Offshore Vessels........................................................................................................... C-13

C.3.6.1 Oil and Gas Production Support Vessels........................................................ C-14

C.3.6.2 Non-Oil and Gas Production Offshore Vessels .............................................. C-17

C.3.7 Biogenic and Geogenic Sources................................................................................... C-19

C.3.8 Sources in Mexico......................................................................................................... C-19

C.3.9 Sources in Canada........................................................................................................ C-19

C.4 FUTURE YEAR MODELING SCENARIO EMISSION ESTIMATES....................................... C-19

C.4.1 Western, Central, and Eastern Planning Areas OCS Offshore Oil and Gas 

Production Sources....................................................................................................... C-20

C.4.1.1 Oil and Natural Gas Offshore Production Platforms....................................... C-21

C.4.1.2 Offshore Support Helicopters.......................................................................... C-22

C.4.1.3 Oil and Gas Production Offshore Support Vessels......................................... C-22

C.4.1.4 Future Year Emission Estimates and Selection of Future Modeling Year ..... C-24

C.4.1.5 Spatial Allocation............................................................................................. C-28

C.4.2 Onshore Sources and Marine Vessels ......................................................................... C-30

C.4.3 Other Sources ............................................................................................................... C-30

C.5 SOURCE APPORTIONMENT ................................................................................................. C-31

C.6 REFERENCES......................................................................................................................... C-32

List of Tables C-v 

LIST OF TABLES

Page

Table C-1. Nonattainment and Maintenance Areas in the Southeastern U.S. ............................... C-3

Table C-2. Gulf of Mexico Air Quality Modeling Study Source Categories..................................... C-7

Table C-3. Base Case Offshore Oil and Gas Production Source Emissions Estimates for 

the GOM Western and Central/Eastern Planning Areas............................................. C-10

Table C-4. Future Year Production Platform Emission Factors.................................................... C-21

Table C-5. Summary of Vessel Characteristics. ........................................................................... C-23

Table C-6. Load Factors to be Used in the Future Year Projections............................................ C-24

Table C-7. Marine Vessel Emission Factors (g/kW-hr)................................................................. C-24

Table C-8. Emission Estimates for the Western, Central, and Eastern Planning Areas, All 

Depths, By Year and Pollutant. ................................................................................... C-25

LIST OF FIGURES

Page

Figure C-1. Location of the “Air Quality Modeling in the Gulf of Mexico Region” Study, with 

Class I Areas (purple) and Platform Locations (gray dots).......................................... C-1

Figure C-2. Ozone Nonattainment Areas in the Southeastern U.S. (USEPA, 2016a)................... C-2

Figure C-3. Overview of the “Air Quality Modeling in the Gulf of Mexico Region” Study 

Tasks. ........................................................................................................................... C-4

Figure C-4. WRF 36-km CONUS (d01), 12-km SE Regional (d02), and 4-km Gulf 

of Mexico Region (d03) Domains Along With the PGM Grids..................................... C-6

Figure C-5. 2012 Platform NOx Emissions Aggregated by Lease Block ...................................... C-11

Figure C-6. 2012 Platform VOC Emissions Aggregated by Lease Block..................................... C-12

Figure C-7. 2012 Platform PM2.5 Emissions Aggregated by Lease Block.................................... C-13

Figure C-8. 2012 Non-platform NOx Emissions ............................................................................ C-15

Figure C-9. 2012 Non-platform VOC Emissions........................................................................... C-16

Figure C-10. 2012 Non-platform PM2.5 Emissions.......................................................................... C-17

Figure C-11. Emission Estimates for all Planning Areas and Future Activities.............................. C-27

Figure C-12. Combined Annual NOx Emissions. ............................................................................ C-27

Figure C-13. Combined Annual VOC Emissions. ........................................................................... C-28

Figure C-14. Combined Annual PM2.5 Emissions. .......................................................................... C-28

Figure C-15. BOEM OCS Planning Areas and Water Depths........................................................ C-29

Abbreviations and Acronyms C-vii

ABBREVIATIONS AND ACRONYMS

μg/m3 microgram(s) per cubic meter

2017-2022 GOM

Multisale EIS

Gulf of Mexico OCS Oil and Gas Lease Sales: 2017-2022; Gulf of Mexico 

Lease Sales 249, 250, 251, 252, 253, 254, 256, 257, 259, and 261—Final 

Multisale Environmental Impact Statement

AIS Automatic Identification System

AL Alabama

AQRV air quality-related value(s)

BOEM Bureau of Ocean Energy Management

CAAA Clean Air Act Amendments

CAMD Clean Air Markets Division (USEPA)

CAMx Comprehensive Air quality Model with eXtensions

CO carbon monoxide

CPA Central Planning Area

EC elemental carbon

ECA Emission Control Area

ECA North American Emission Control Area

EGUs electric generating units

EIS environmental impact statement

EPA Eastern Planning Area

ERG Eastern Research Group, Inc.

FINN Fire INventory

FL Florida

FLM Federal Land Management

FOCA Federal Office of Civil Aviation

GA Georgia

GOMESA Gulf of Mexico Energy Security Act

HC hydrocarbon

HIS Information Handling Service

hr hour(s)

IC/BC Initial Conditions/Boundary Conditions

ICAO International Civil Aviation Organization

ICI institutional/commercial/industrial

km kilometer(s)

kW kilowatt

kW-hr kilowatt-hour

LA Louisiana
C-viii 2018 Gulf of Mexico Supplemental EIS

LNG liquefied natural gas

LOOP Louisiana Offshore Oil Port

LTO landing and takeoff

M maintenance area

MARAD Maritime Administration

MNEI Mexico National Emissions Inventory

MS Mississippi

MSW municipal solid waste

MTSA Maritime Transportation Security Act of 2002

NAA nonattainment area

NAAQS National Ambient Air Quality Standards

NAAQS National Ambient Air Quality Standards

NAAs nonattainment areas

NCAR National Center for Atmospheric Research

NCAR National Center for Atmospheric Research

NEI National Emissions Inventory (USEPA) 

NEPA National Environmental Policy Act

NH3 ammonia

NO2 nitrogen dioxide

NOx nitrogen oxides

O3 ozone

OC organic carbon

OCS Outer Continental Shelf

OCSLA OCS Lands Act

OGOR Oil and Gas Operations Reports

OMSA Offshore Marine Service Association

PAHs polycyclic aromatic hydrocarbons

Pb lead

PGM Photochemical Grid Model

PM particulate matter

PM10 inhalable particulate matter (less than 10 microns in effective diameter)

PM2.5 fine particulate matter (less than 2.5 microns in effective diameter)

ppb parts per billion

ppm parts per million

PSD Prevention of Significant Deterioration

QA/QC quality assurance/quality control

Ramboll Environ Ramboll Environ US Corporation

RHR Regional Haze Rule
Abbreviations and Acronyms C-ix

SIPs State Implementation Plans

SMOKE Sparse Matrix Operator Kernel Emissions

SO2 sulfur dioxide

tpy tons per year

TRI Toxics Release Inventory

TX Texas

USDOI United States Department of the Interior

USEPA United States Environmental Protection Agency

USEPA United States Environmental Protection Agency

VOC volatile organic compound

WBD windblown dust

WPA Western Planning Area

WRF Weather Research and Forecasting model

yr year

Air Quality: Emissions for the Cumulative and Visibility Impacts C-1 

C AIR QUALITY: EMISSIONS FOR THE CUMULATIVE AND 

VISIBILITY IMPACTS

C.1 INTRODUCTION

The U.S. Department of the Interior’s Bureau of Ocean Energy Management (BOEM) is 

required under the Outer Continental Shelf Lands Act (OCSLA) (43 U.S.C. § 1334(a)(8)) to comply 

with the National Ambient Air Quality Standards (NAAQS) to the extent that Outer Continental Shelf 

(OCS) offshore oil and gas exploration, development, and production sources do not significantly 

affect the air quality of any state. The Gulf of Mexico OCS Region’s OCS area of possible influence 

includes the States of Texas, Louisiana, Mississippi, Alabama, and Florida. BOEM’s Gulf of Mexico 

OCS Region manages the responsible development of oil, gas, and mineral resources for the 

430 million acres in the Western, Central, and Eastern Planning Areas on the OCS comprising the 

Gulf of Mexico OCS Region, including the areas under moratoria (shown in Figure C-1). The Clean 

Air Act Amendments (CAAA) of 1990 designate air quality authorities in the Gulf of Mexico OCS 

Region, giving BOEM air quality jurisdiction westward of 87°30'W. longitude and the U.S. 

Environmental Protection Agency (USEPA) air quality jurisdiction eastward of 87°30'W. longitude. In 

2006, oil and gas leasing operations within 125 miles (201 kilometers [km]) of the Florida coastline 

were banned until 2022 under the Gulf of Mexico Energy Security Act (GOMESA). The GOMESA 

moratoria area is depicted on Figure C-1. 

Figure C-1. Location of the “Air Quality Modeling in the Gulf of Mexico Region” Study, with Class I 

Areas (purple) and Platform Locations (gray dots). 
C-2 2018 Gulf of Mexico Supplemental EIS

The USEPA has set NAAQS for six regulated air quality pollutants: ozone; particulate matter 

with an aerodynamic diameter of 2.5 micrometers and smaller (PM2.5); particulate matter with an 

aerodynamic diameter of 10 micrometers and smaller (PM10); sulfur dioxide (SO2); nitrogen dioxide 

(NO2); carbon monoxide (CO); and lead (Pb). After promulgation of a NAAQS, the USEPA 

designates areas that fail to achieve the NAAQS as nonattainment areas (NAAs) and States are 

required to submit State Implementation Plans (SIPs) to the USEPA that contain emission control 

plans and a demonstration that the NAA will achieve the NAAQS by the required date. After an area 

comes into attainment of the NAAQS, the area can be redesignated as a maintenance area and 

must continue to demonstrate compliance with the NAAQS.

In 1997, the USEPA promulgated the first 8-hour ozone NAAQS with a threshold of 

0.08 parts per million (ppm) (84 parts per billion [ppb]). On March 12, 2008, the USEPA 

promulgated a more stringent 0.075 ppm (75 ppb) 8-hour ozone NAAQS. Figure C-2 presents the 

current ozone nonattainment areas in the southeastern U.S. On October 1, 2015, the USEPA 

strengthened the 8-hour NAAQS for ozone to 0.07 ppm (70 ppb). Under this more stringent ozone 

NAAQS, there may be more areas in the southeastern U.S. that will be in nonattainment. The 

USEPA plans to make attainment and nonattainment designations for the revised standards by late 

2017, with the designations based on 2014-2016 air quality data.

Figure C-2. Ozone Nonattainment Areas in the Southeastern U.S. (USEPA, 2016a). 

On December 14, 2012, the USEPA revised the PM2.5 primary NAAQS by lowering the 

annual PM2.5 NAAQS threshold from 15.0 micrograms per cubic meter (μg/m3

) to 12.0 μg/m3. The 

USEPA retained the 24-hour PM2.5 primary NAAQS at 35 μg/m3

. The 24-hour coarse PM NAAQS 

(PM10) was also retained at 150 μg/m3

. 

In February 2010, the USEPA issued a new 1-hour NO2 NAAQS with a threshold of 100 ppb 

(98th percentile daily maximum average over 3 years) and a new 1-hour SO2 NAAQS was 
Air Quality: Emissions for the Cumulative and Visibility Impacts C-3 

promulgated in June 2010 with a threshold of 75 ppb (99th percentile averaged over 3 years). The 

USEPA has not yet designated the nonattainment areas for the 1-hour NO2 and 1 hour SO2 NAAQS.

A new lead NAAQS was issued in 2008; NAAs for lead are associated with specific industrial 

sources. The NAAQS for carbon monoxide has remained essentially unchanged since it was 

originally promulgated in 1971. As of September 27, 2010, all NAAs for carbon monoxide have been 

redesignated as maintenance areas. Table C-1 summarizes the nonattainment and maintenance 

areas in the southeastern U.S.

Table C-1. Nonattainment and Maintenance Areas in the Southeastern U.S.

State Area 8-hr O3

(1997)

8-hr O3

(2008)

SO2

(2010)

Lead 

(2008)

Alabama Troy, AL NAAa

Florida

Tampa, FL NAA

Hillsborough County, FL NAA

Nassau County, FL NAA

Louisiana Baton Rouge, LA Mb NAA

St. Bernard Parish, LA NAA

Texas

Beaumont-Port Arthur, TX M

Houston-Galveston-Brazoria, 

TX NAA NAA

Frisco, TX NAA a NAA = nonattainment area

b M = maintenance area

Blank cells indicate the area is in attainment of the NAAQS.

The CAAA designated 156 Class I areas consisting of National Parks and Wilderness Areas 

that are offered special protection for air quality and air quality-related values (AQRVs). The Class I 

areas, compared to Class II areas, have lower Prevention of Significant Deterioration (PSD) air 

quality increments that new sources may not exceed and are protected against excessive increases 

in several AQRVs including visibility impairment, acid (sulfur and nitrogen) deposition, and nitrogen 

eutrophication. The Regional Haze Rule (RHR) has a goal of natural visibility conditions by 2064 at 

Class I areas, and States must submit RHR SIPs that demonstrate progress towards that goal. 

Figure C-1 displays the locations of the mandatory Class I areas (in purple) in the Gulf of Mexico 

OCS Region. In addition to Class I areas, Federal Land Management (FLM) agencies have 

designated certain other areas as sensitive Class II areas for tracking PSD increment consumption 

and AQRV impacts.

On August 26, 2014, BOEM contracted with Eastern Research Group, Inc. (ERG) and team 

members Ramboll Environ US Corporation (Ramboll Environ) and Alpine Geophysics, LLC to 

complete a comprehensive air quality modeling study in the Gulf of Mexico OCS Region. Under 

BOEM Contract Number M14PC00007, air quality photochemical grid modeling (PGM) will be 

conducted in the Gulf of Mexico OCS Region to assess the impacts to nearby States of OCS oil and 

gas exploration, development, and production as required under OCSLA. This assessment is used 
C-4 2018 Gulf of Mexico Supplemental EIS

by BOEM in the cumulative and visibility impacts analyses of the National Environmental Policy Act 

(NEPA) environmental impact statements (EISs), which are the Gulf of Mexico OCSOil and Gas 

Lease Sales: 2017-2022; Gulf of Mexico Lease Sales 249, 250, 251, 252, 253, 254, 256, 257, 259, 

and 261—Final Multisale Environmental Impact Statement (2017-2022 GOM Multisale EIS) and this 

Supplemental EIS. These analyses address both current and proposed NAAQS.

Air quality modeling requires several input datasets, including meteorology, emissions 

inventories, and ambient pollutant concentrations. Figure C-3 presents an overview of how these 

project datasets fit together for the “Air Quality Modeling in the Gulf of Mexico Region” study.

Figure C-3. Overview of the “Air Quality Modeling in the Gulf of 

Mexico Region” Study Tasks. 

C.2 DEVELOPMENT OF EMISSION INVENTORIES

A key step in performing the “Air Quality Modeling in the Gulf of Mexico Region” study in 

support of the subsequent cumulative and visibility impacts analyses is development of 

comprehensive air emission inventories that accurately depict the base case emissions within the 

study area, and emissions associated with the scenario (the future year) for the 2017-2022 GOM 

Multisale EIS and this Supplemental EIS. 

The scope of the air pollutant emissions inventory development effort for the “Air Quality 

Modeling in the Gulf of Mexico Region” study includes selection of: pollutants, base case year, 

geographical domain, sources, spatial resolution, temporal resolution, speciation, and development 

of the base case and future year emission estimates. These elements are described below.
Air Quality: Emissions for the Cumulative and Visibility Impacts C-5 

C.2.1 Pollutants

Pollutants for the “Air Quality Modeling in the Gulf of Mexico Region” study consist of criteria 

air pollutants as defined by CAA Title I: CO; lead; NOx (stated as equivalent mass of nitrogen 

dioxide [NO2]); PM2.5; PM10; and SO2, as well as volatile organic compounds (VOCs, which are 

precursors to ozone formation) and ammonia (NH3, a precursor to PM formation).

C.2.2 Base Case Year

In determining the base case year for the “Air Quality Modeling in the Gulf of Mexico Region” 

study emissions inventory, 2011 was initially selected based on data availability. Calendar year 

2011 emissions data are readily available for most sources from the USEPA National Emissions 

Inventory (NEI) (USEPA, 2015a), and BOEM’s Year 2011 Gulfwide Emissions Inventory Study

(Wilson et al., 2014), hereby called the “2011 Gulfwide Inventory.” However, 2011 was an unusually 

hot and dry year in the Gulf of Mexico OCS Region, particularly in Texas, which experienced record 

heat and dry conditions during the summer of 2011 and had a very high incidence of wildfires. 

Therefore, 2012 was selected as the base case year as more representative of “typical” conditions in 

the Gulf of Mexico OCS Region. 

C.2.3 Geographical Domain

The domain of the “Air Quality Modeling in the Gulf of Mexico Region” study emissions 

inventory is the area depicted in Figure C-4, particularly the 4-kilometer (km) domain encompassing 

the Gulf of Mexico OCS. This area, which includes parts of Alabama, Georgia, Louisiana, 

Mississippi, and Texas; all of Florida; as well as the Western, Central, and Eastern Planning Areas in 

the Gulf of Mexico and part of the Atlantic Ocean, are the main focus of the emissions inventory 

efforts. Emissions data were also required for the 36- and 12-km expanded domains depicted in 

Figure C-4, which include parts of Mexico and Canada. The outermost domain with 

36-km resolution includes the entire continental U.S. and parts of Canada and Mexico, and captures 

synoptic-scale (storm system-scale) structures in the atmosphere. The inner 12-km regional grid 

covers the southeastern U.S. and is used to ensure that large-scale meteorological patterns across 

the region are adequately represented and to provide boundary conditions to the 4-km domain.
C-6 2018 Gulf of Mexico Supplemental EIS

Figure C-4. WRF 36-km CONUS (d01), 12-km SE Regional (d02), and 4-km Gulf of Mexico Region 

(d03) Domains Along With the PGM Grids. 

C.2.4 Inventory Sources

Emissions from anthropogenic (i.e., human caused) sources, including stationary point and 

nonpoint area sources located both onshore and offshore, onroad motor vehicles, nonroad

equipment, locomotives, marine vessels and other offshore sources, and airports, were compiled for 

the “Air Quality Modeling in the Gulf of Mexico Region” study emissions inventory. Table C-2 lists 

the source groups and categories included in the emissions inventory, along with the pollutants 

applicable to each source, and the spatial and temporal resolution. Note that emissions from 

non-anthropogenic sources (i.e., biogenic and geogenic sources) are also included as part of the “Air 

Quality Modeling in the Gulf of Mexico Region” study cumulative and visibility analyses.
Air Quality: Emissions for the Cumulative and Visibility Impacts C-7 

Table C-2. Gulf of Mexico Air Quality Modeling Study Source Categories. 

Group and Source Category CO NOx SO2 VOC Pb PM2.5 PM10 NH3

Spatial 

Resolutiona

NEI 

Onshore 

Sources

Point Sources         P

Nonpoint Area 

Sources         A 

Onroad Mobile 

Sources        A 

Commercial Marine 

Vessels         P, Ab

Locomotives         P, Ac

Aircraft and Airports         P

Other Nonroad Mobile 

Sources        A 

Offshore Oil & Gas Sources

Platforms in State 

Waters       P 

Platforms in Central 

and Western GOM 

OCS Planning Areas

        P 

Drilling Rigs         LB

Pipe-Laying Vessels         LB

Support Helicopters       LB

Support Vessels         LB

Survey Vessels         LB

Non-oil and Gas Offshore Vessels and Activities

Commercial Fishing 

Vessels         LB

Commercial Marine 

Vessels         LB

Louisiana Offshore Oil 

Port         P 

Military Vessels         LB

Recreational Vessels        LB

Vessel Lightering         P

Biogenic and Geogenic Sources

Subsurface Oil Seeps  LB

Mud Volcanoes  LB

Onshore Vegetation   A

Wildfires and 

Prescribed Burning        P 

Windblown Dust   A

Lightning  A

Sea Salt Emissions   A 

Sources in Mexico and Canada

Point Sources        P

Nonpoint Area 

Sources       A 

Mobile Sources       A 

a

 A = Area source (modeling grid cell, spatial surrogate); P = Point source (UTM coordinates, stack 

parameters); LB = Offshore lease block (modeling grid cell, spatial surrogate) 

b Larger ports and shipping will be represented as shape files; smaller ports as point sources.

c Rail yards will be represented as point sources; railway segments as area sources.
C-8 2018 Gulf of Mexico Supplemental EIS

C.2.5 Spatial Resolution

The spatial resolution of the emissions inventory is source-specific. For example, sources 

such as power plants are identified based on their geographic coordinates (i.e., latitude and 

longitude), while other sources such as nonroad mobile sources (e.g., construction equipment) are 

spatially distributed using surrogates within the county in which they are reported and that are 

typically related to the activity distribution of the category (e.g., construction sites).

The resolution of the geographical area covered by the emissions inventory is based on the 

grid cell size needed for photochemical modeling. Furthermore, the photochemical model grid 

resolution is dependent on the grid resolution of the WRF meteorological model output used.

C.2.6 Temporal Resolution

Emissions for all sources were estimated on an annual basis (i.e., emissions generated 

during 2012). For electric generating units (EGUs), emissions were allocated on a sub-annual basis 

to reflect variations in activity using data from the USEPA.

Emissions were allocated on an hourly, daily, and seasonal basis using default temporal 

allocation factors provided with the Sparse Matrix Operator Kernel Emissions (SMOKE) emissions 

model for some sources; other temporal allocations were source-specific, and profiles were 

developed and applied within the SMOKE model.

C.2.7 Speciation

When applying the PGM modeling, PM emissions were allocated to individual PM species as 

part of the SMOKE emissions processing using PM speciation factors obtained from the USEPA’s 

SPECIATE database (USEPA, 2014a) for each source category (as defined by the Source 

Classification Code). This resulted in the PM mass being broken into the mass associated with 

elemental carbon (EC), organic carbon (OC), and other elements, and particle-bound VOCs, such as 

polycyclic aromatic hydrocarbons (PAHs). The model predictions of EC will undergo further analysis 

and will be discussed in the “Air Quality Modeling in the Gulf of Mexico Region” study final report.

SMOKE was also used to convert VOC emissions into the photochemical mechanismspecific (e.g., CB05 or CB6r2h) model species used in air quality models.

C.3 BASE CASE EMISSION ESTIMATES

This section presents an overview of the methodologies used to compile the base case 2012 

emission estimates for all source categories in the emissions inventory.

C.3.1 Point Sources

Calendar year 2011 emissions data are available for onshore point sources from the USEPA 

NEI (USEPA, 2015a). In a separate modeling effort, the USEPA prepared a criteria pollutant 
Air Quality: Emissions for the Cumulative and Visibility Impacts C-9 

calendar 2012 year emissions inventory for some sectors, including onshore point sources (USEPA, 

2015b). The ERG obtained the USEPA 2012 point sources emissions inventory, conducted quality 

assurance/quality control (QA/QC) on the data, and supplemented and revised the criteria pollutant 

estimates, as needed. The USEPA prepared the 2012 point source emissions inventory as follows:

(1) 2012 data compiled by the USEPA from annual criteria pollutant reporting of 

Type A (large) sources that are submitted by responsible State and local air 

agencies;

(2) 2012 EGU emissions from the USEPA Clean Air Markets Division (CAMD) 

hourly emissions data;

(3) 2011 NEI data for other, smaller point sources that are not identified above; and

(4) 2011 airport and aircraft emission estimates developed by the USEPA updated 

to 2012 as needed.

Although the emissions data are likely complete for most point sources, ERG confirmed that 

offshore platforms within State boundaries are included in the NEI. Data from the USEPA’s 2012 

Toxics Release Inventory (TRI) for lead and ammonia were also used to supplement the inventory 

as needed (USEPA, 2015c).

C.3.2 Nonpoint Area Sources

The starting point for the 2012 nonpoint area source inventory was the data submitted by 

State and local agencies for the 2011 NEI. In addition, for completeness, the USEPA develops 

emission estimates for a number of nonpoint source categories (up to 165) for inclusion in the NEI if 

agencies do not provide estimates. The USEPA did not develop 2012 emission estimates for 

nonpoint area sources. The ERG prioritized key top-emitting source categories of NOx, PM, SO2, 

and VOCs in AL, FL, GA, LA, MS, and TX, and developed 2012 emission estimates using the 

USEPA nonpoint area source category tools (USEPA, 2014b). These categories are as follows: 

consumer products, architectural surface coatings, industrial maintenance coatings, open burning: 

municipal solid waste (MSW), residential and institutional/commercial/industrial (ICI) heating, 

upstream oil and gas, open burning, land clearing debris, paved and unpaved roads, and gasoline 

distribution Stage I. The ERG also conducted point source reconciliation for ICI heating, oil and gas, 

and gasoline distribution Stage I to verify that there are no gasoline distribution Stage II records in 

USEPA’s nonpoint file (now reported with onroad mobile sources).

C.3.3 Mobile Sources

The onroad mobile source category includes exhaust and evaporative emissions from 

onroad motor vehicles (e.g., automobiles, light-duty trucks, heavy-duty trucks) and exhaust and 

evaporative emissions from nonroad mobile sources. The ERG team ran the MOVES2014 model 

for onroad sources (USEPA, 2014c), and the USEPA ran the NONROAD model for nonroad sources 

to develop 2012 emission estimates for these categories. Locomotive emissions in the 2011 NEI 
C-10 2018 Gulf of Mexico Supplemental EIS

were not adjusted to represent 2012 activities because it was confirmed that the 2011 and 2012 fuel 

usage data from the Surface Transportation Board’s R-1 Class 1 railroad annual reporting data 

(Surface Transportation Board, 2015) show only a slight (2%) reduction in 2012 levels from 2011 

levels.

C.3.4 Offshore Helicopters

The Gulf of Mexico has more helicopter traffic than any other region of the U.S., primarily 

associated with offshore oil and gas support. Offshore support helicopter emission estimates were 

obtained from the 2011 Gulfwide inventory (Wilson et al., 2014). The estimates were supplemented 

with 2011 NEI helicopter data for onshore airports. The two datasets map out the full route between 

offshore platforms equipped with helipads and the closest onshore support facility; the NEI 

addresses emissions only at each airport and only for operations up to 3,000 feet of elevation (i.e., 

local mixing height). The two datasets were evaluated to ensure that the helicopter traffic data 

between the two are comparable and that there is no double counting of emissions.

C.3.5 Offshore Oil and Gas Production Sources—Western and Central/Eastern 

Planning Areas in the Gulf of Mexico

The starting point for offshore oil and gas production platforms in the Western and 

Central/Eastern Planning Areas (WPA and CPA/EPA) was the 2011 Gulfwide inventory. The ERG 

team supplemented the 2011 Gulfwide inventory with NH3 and Pb emission estimates for all 

applicable emission sources using USEPA emission factors. The ERG team conducted research to 

determine if the 2011 emissions values for platform sources should be adjusted to be more 

representative of 2012 emissions values. Offshore oil and gas production values for 2011 and 2012 

were obtained from the BOEM Part A Oil and Gas Operations Reports (OGOR) (USDOI, BOEM, 

2015). The OGOR data are presented at the lease level. Production of both oil and gas (including 

deepwater production) decreased from 2011 to 2012; thus, the 2011 emission estimates were 

modeled without adjustment in order to be conservative. Table C-3 presents the base case 

emission estimates for offshore oil and gas production sources in the WPA and CPA/EPA. Figures 

C-5 through C-7 show the NOx, VOC, and PM2.5 emissions from platform sources. Platform 

sources include the following emission source types: amine units, boilers/heater/burners, diesel and 

gasoline engines, drilling equipment, combustion flares, fugitives, glycol dehydrators, losses from 

flashing, mud degassing, natural gas engines, natural gas turbines, pneumatic pumps, 

pressure/level controllers, storage tanks, and cold vents.

Table C-3. Base Case Offshore Oil and Gas Production Source Emissions Estimates for the GOM 

Western and Central/Eastern Planning Areas. 

NOX

(TPY)

SO2

(TPY)

PM10

(TPY)

PM2.5

(TPY)

VOC 

(TPY)

CO 

(TPY)

Pb 

(TPY)

NH3

(TPY)

Platform 

Sources 84,128 3,197 838 835 54,724 70,339 <1 40

Non-platform 

Sources 232,765 22,977 8,632 8,225 7,937 41,880 701 70,139

Total 316,893 26,174 9,470 9,060 62,661 112,219 701 70,179
Air Quality: Emissions for the Cumulative and Visibility Impacts C-11

Figure C-5. 2012 Platform NOx Emissions Aggregated by Lease Block. (Note: This figure does not 

indicate the platform source count, location, or emissions at the time of publication of 

the 2017-2022 GOM Multisale EIS, from which this Supplemental EIS tiers.)
C-12 2018 Gulf of Mexico Supplemental EIS

Figure C-6. 2012 Platform VOC Emissions Aggregated by Lease Block. (Note: This figure does not 

indicate the platform source count, location, or emissions at the time of publication of the 

2017-2022 GOM Multisale EIS, from which this Supplemental EIS tiers.)
Air Quality: Emissions for the Cumulative and Visibility Impacts C-13

Figure C-7. 2012 Platform PM2.5 Emissions Aggregated by Lease Block. (Note: This figure does not 

indicate the platform source count, location, or emissions at the time of publication of the 

2017-2022 GOM Multisale EIS, from which this Supplemental EIS tiers.)

C.3.6 Offshore Vessels

Offshore vessels can be grouped into vessels that support the construction, operation, and 

decommissioning of oil and gas platforms; and vessels involved in other commercial, recreational, 

and military operations. All marine vessels included in this study operate using diesel engines. 

These include very large propulsion engines as well as smaller auxiliary diesel engines that provide 

power for electricity generation, winches, pumps, and other onboard equipment. Smaller engines 

tend to use distillate grade diesel fuel, while large engines are able to combust heavier residual 

blends.

40 CFR § 1043.109(b) created the North American Emission Control Area (ECA), which 

includes the Gulf of Mexico (USEPA, 2010). This regulation limits marine fuel sulfur content to 1% 

after August 1, 2012, for any vessel with a gross tonnage greater than 400. Vessels below this 

threshold tend to use distillate fuels, which are already at or below the 1% limit.
C-14 2018 Gulf of Mexico Supplemental EIS

C.3.6.1 Oil and Gas Production Support Vessels

The offshore oil and gas production sector requires a wide variety of vessels to support the 

exploration, development, and extraction of oil and gas, including the following: 

• seismic survey vessels; 

• drilling vessels; 

• pipe-laying vessels; 

• crewboats; and

• supply vessels. 

For the 2011 Gulfwide inventory, Automatic Identification System (AIS) data from PortVision 

were used to map spatial aspects of vessel movements (PortVision, 2012). The AIS is an 

automated tracking system that allows exchanges of location and contact data with other nearby 

ships, offshore platforms, satellites, and AIS base stations, enhancing navigation and reducing 

at-sea collisions.

On October 22, 2003, the U.S. harmonized the AIS mandates of the Safety of Life at Sea 

Convention with the Maritime Transportation Security Act of 2002 (MTSA), which requires the 

following vessels, including offshore support vessels, to participate in the AIS program:

(1) passenger vessels of 150 gross tonnage or more;

(2) tankers, regardless of tonnage; and

(3) vessels other than passenger vessels or tankers of 300 gross tonnage or more.

Vessels that do not meet these thresholds, such as crew boats and smaller support vessels, 

can still participate in AIS on a voluntary basis. The Offshore Marine Service Association (OMSA) is 

encouraging its membership to equip their vessels with AIS transponders, allowing for more efficient 

and safer ship movements in the highly congested central and western areas of the Gulf of Mexico.

The ERG team used the spatially distributed support vessel emission estimates from 

BOEM’s 2011 Gulfwide inventory. While the USEPA 2011 NEI also includes marine vessel emission 

estimates for the Gulf of Mexico, the emission estimates were derived from national vessel activity 

data. During QA/QC of the 2011 BOEM Gulfwide estimates, ERG found and corrected an error in 

the vessel power rating for a number of smaller vessels.

As discussed above for offshore oil and gas production platforms, the 2011 emission 

estimates for these vessels were not adjusted to reflect 2012 production levels. SOx and PM 

(associated with sulfates) were not adjusted to account for the introduction of low sulfur ECA 

compliant fuel in the last 5 months of 2012 because it was determined that most support vessels are 
Air Quality: Emissions for the Cumulative and Visibility Impacts C-15

Category 1 or 2, which already use ECA compliant fuels. Emission estimates for NH3 and Pb were 

also developed for vessels. Table C-3 presents the base case emission estimates for drilling rigs, 

pipe-laying operations, support helicopters, support vessels, and survey vessels. Figures C-8 

through C-10 show the NOx, VOC, and PM2.5 emissions from non-platform sources.

Figure C-8. 2012 Non-platform NOx Emissions. (Note: This figure does not indicate the non-platform 

source count, location, or emissions at the time of publication of the 2017-2022 GOM 

Multisale EIS, from which this Supplemental EIS tiers.)
C-16 2018 Gulf of Mexico Supplemental EIS

Figure C-9. 2012 Non-platform VOC Emissions. (Note: This figure does not indicate the 

non-platform source count, location, or emissions at the time of publication of the 

2017-2022 GOM Multisale EIS, from which this Supplemental EIS tiers.)
Air Quality: Emissions for the Cumulative and Visibility Impacts C-17

Figure C-10. 2012 Non-platform PM2.5 Emissions. (Note: This figure does not indicate the 

non-platform source count, location, or emissions at the time of publication of the 

2017-2022 GOM Multisale EIS, from which this Supplemental EIS tiers.)

The ERG team obtained drilling vessel data from BSEE to confirm that there was no drilling 

activity in the eastern Gulf of Mexico OCS region in 2012, and reviewed the permits granted by the 

USEPA for offshore platforms in the eastern Gulf of Mexico OCS region to confirm there were no 

active production platform activities in 2012.

C.3.6.2 Non-Oil and Gas Production Offshore Vessels

Vessels not directly associated with the offshore oil and gas activities include the following: 

• commercial marine vessels; 

• Louisiana Offshore Oil Port-associated vessels; 

• commercial and recreational fishing vessels; 

• ferries; 

• research vessels; 
C-18 2018 Gulf of Mexico Supplemental EIS

• harbor craft; and

• military vessels. 

Commercial marine vessels include large ships involved in international trade that visit 

coastal ports and operate in deep waters, as well as smaller general cargo ships and tugs that move 

barges along waterways and rivers. For the Federal waters of the central and western of the Gulf of 

Mexico, the ERG team used the commercial marine vessel data from the 2011 Gulfwide inventory. 

For completeness, for all other areas of the Gulf of Mexico, Atlantic Ocean, and State waters, the 

USEPA’s NEI data were used (which were developed from national vessel activity data as noted 

above). These inventories cover different geographical areas than the BOEM inventory, as well as 

different vessel types. BOEM’s data include large deepwater vessels as does the USEPA data 

beyond the Federal/State boundary, but they also include vessels such as ferries, dredging vessels, 

tugs, towboats, and harbor craft that tend to operate only in State waters.

The Louisiana Offshore Oil Port (LOOP) is a pumping platform for tankers to discharge 

imported crude oil to the mainland without having to maneuver through port traffic. Similarly, there 

are four offshore lightering zones in the Gulf of Mexico (i.e., Southtex, Gulfmex No. 2, Offshore 

Pascagoula No. 2, and South Sabine Point) where smaller shuttle tankers can move product from 

very large crude carriers, bringing the oil to port while the large tankers remain off the coast. 

Tankers that visit the LOOP or the lightering zones along with the shuttle tankers were identified in 

the 2011 Gulfwide inventory. The inventory also accounts for evaporative emissions from unloading 

and loading activities, and emissions from the operation of generators and pumps at the LOOP; 

adjustments were made to the 2011 LOOP emission estimates to reflect the 18% decline in crude 

imports in 2012.

Emissions from the operation of commercial and recreational fishing vessels are also 

included in the 2011 Gulfwide inventory for Federal waters. These were supplemented with the 

USEPA’s 2011 NEI data for these fishing vessels for operations in the Eastern Planning Area in the 

Gulf of Mexico, Atlantic Ocean, and State waters. For military vessels, the ERG team used the 2011 

Gulfwide inventory Navy and Coast Guard vessel emission estimates and the NEI’s Coast Guard 

emission estimates for State waters, as well as Federal waters in the eastern part of the Gulf of 

Mexico and the Atlantic Coast. The ERG team conducted research to determine that activity levels 

from 2011 to 2012 were similar for the other non-oil and gas vessels (e.g., tankers, container ships, 

bulk, and general cargo). Based on the most recent International Maritime Organization data 

(IMO, 2015), fuel combustion is projected to remain constant from 2010 to 2015. Thus, no 

adjustments were needed to approximate activities in 2012.

The SO2 and PM (associated with sulfates) emission estimates were adjusted for Category 3 

vessels to account for the introduction of low sulfur ECA-compliant fuel in the last 5 months of 2012.
Air Quality: Emissions for the Cumulative and Visibility Impacts C-19

C.3.7 Biogenic and Geogenic Sources

For completeness, it is important to include non-anthropogenic emission sources in the 

inventory. The ERG team also estimated emissions for the sources listed below.

• Onshore vegetation (biogenic): MEGAN (version 2.1) biogenic emission model

• Wildfires, prescribed burns, and agricultural burning: USEPA’s SMARTFIRE 

emissions inventory for the U.S.

• Windblown dust: Windblown dust (WBD) modeling using the WRF 

meteorological dataset

• Lightning: WRF data (preprocessor)

• Subsurface oil seeps: 2011 Gulfwide inventory

• Mud volcanoes: 2011 Gulfwide inventory

• Sea salt emissions: WRF data (preprocessor)

The ERG team used fire emission estimates from the National Center for Atmospheric 

Research (NCAR) Fire INventory (FINN) for Mexico and Canada.

C.3.8 Sources in Mexico

The ERG team developed the 2012 emission inventories for the portions of Mexico within the 

36-km modeling inventory domain using the municipality-level emission files from the 2008 Mexico 

National Emissions Inventory (MNEI) (SEMARNAT, 2014) combined with projection factors for point, 

nonpoint area, and nonroad mobile sources. Mexico onroad motor vehicle emissions were 

generated using a version of the USEPA vehicle emissions model MOVES, updated to reflect 

conditions in Mexico. MOVES2014 was the most recent version of the model available at the time of 

the analysis and reflects USEPA’s latest estimate of vehicle emissions and default U.S. activity data 

(USEPA, 2014c). The ERG also conducted research on the offshore oil production activities off the 

coast of Mexico. Based on a report published by the Congressional Research Service, it was 

determined that there was no offshore production within the 36-km modeling domain in 2012 (Seelke 

et al., 2015).

C.3.9 Sources in Canada

Emissions from the USEPA’s most recent modeling platform (2010) were used for sources in 

Canada.

C.4 FUTURE YEAR MODELING SCENARIO EMISSION ESTIMATES

Emission estimates were also needed as inputs for additional modeling scenarios that will 

predict future impacts from implementation of the 2017-2022 GOM Multisale EIS, from which this 

Supplemental EIS tiers. For modeling the future year impacts, the ERG team forecast emissions 
C-20 2018 Gulf of Mexico Supplemental EIS

estimates based on information provided by BOEM, combined with USEPA projected emission 

estimates and other data for onshore sources and marine vessels and other sources outside of the 

GOM region. The ERG team confirmed that offshore drilling in the EPA under USEPA air quality 

jurisdiction is included in BOEM’s 2017-2022 Outer Continental Shelf Oil and Gas Leasing: 

Proposed Final Program (Five-Year Program) spreadsheets. The ERG also reviewed the USEPA’s

offshore oil and gas production permits to confirm that no production platforms were permitted to be 

constructed prior to or during 2017. Projected emission estimates were developed for anticipated 

offshore drilling off the coast of Mexico.

C.4.1 Western, Central, and Eastern Planning Areas OCS Offshore Oil and Gas 

Production Sources

The ERG team developed annual emission estimates for all categories and pollutants for 

each year of activity for OCS offshore oil and gas production sources associated with the Five-Year 

Program using BOEM’s spreadsheet-based data analyses tools. BOEM provided information on the 

predicted levels of activity, sources, and locations (by planning area and water depth) to depict 

offshore oil and gas activities in the future scenario. The emissions estimates are based on a 

mid-price oil case scenario and cover the WPA, CPA, and EPA, which are under BOEM’s

jurisdiction.

After completion of the OCS offshore oil and gas production source emission estimates, the 

resulting cumulative emissions for each pollutant were assessed to determine which emission 

estimates should be selected for PGM modeling to support the cumulative and visibility impacts 

analyses.

Based on information provided by BOEM, it was assumed that emissions for the following 

sources occur during the total period of proposed activity based on the 2017-2022 GOM Multisale 

EIS scenario (2017-2056)1

, from which this Supplemental EIS tiers: 

• exploration and delineation well drilling activities (1,671 wells drilled); 

• development and production well drilling activities (1,135 wells drilled); 

• platform installation activities (535 platforms installed); 

• FPSO installation (1 FPSO installed); 

• FPSO operation (1 FPSO operating); 

• FPSO removal (1 FPSO removed); 

• pipeline installation excluding State waters (7,251 km of pipeline installed); 

 

1 Excluding the Gulf of Mexico Energy Security Act (GOMESA) moratorium area.
Air Quality: Emissions for the Cumulative and Visibility Impacts C-21

• platform oil and gas production (535 platforms in operation); 

• platform removal (535 platforms removed); 

• support helicopters (642,000 round trips); and

• support vessels (1,062,000 operations). 

The BOEM data analyses tools provide information on each of these anticipated activities by 

year, as well as water depth. The anticipated water depths by planning area were used to spatially 

allocate the emissions.

The ERG used this information to develop emission estimates for each source category 

based on emission estimation methods used in past Gulfwide emissions inventory studies and other 

data compiled for BOEM in order to determine which estimates should be selected for 

photochemical modeling to support the cumulative and visibility impacts analyses.

The following sections discuss the emission estimation methods that the ERG team used to 

estimate emissions for the BOEM oil and gas production sources in the future scenario.

C.4.1.1 Oil and Natural Gas Offshore Production Platforms

In order to develop reasonably foreseeable emission estimates for projected oil and natural 

gas production platforms, the emission factors presented in Table C-4 were developed based on the 

2011 Gulfwide inventory (Wilson et al., 2014). Because deepwater operations may significantly 

differ from conventional operations in shallower waters, are technologically more sophisticated, and 

produce at much higher rates, two sets of emission factors were developed and assigned to each 

projected platform based on water depth. Depths below 200 meters (656 feet) were assigned the 

shallow-water emission factors, and depths above were assigned deepwater emission factors.

Emission estimates for platform sources were developed based on platform installation and 

carried forward until the projected platform removal dates (provided by planning area and water 

depth).

Table C-4. Future Year Production Platform Emission Factors. 

Pollutant

Shallow Water 

Emission Factors (<200 m) 

(tons/platform/yr)

Deepwater 

Emission Factors (>200 m) 

(tons/platform/yr)

CO 56 192

NOx 46 582

PM10-PRI 0.5 5.17

PM2.5-PRI 0.50 5.15

SO2 0.51 44

VOC 22 96

Pb 2.38E-05 3.79E-03

NH3 0.0349 0.49

Source: Developed from the Year 2011 Gulfwide Emissions Inventory (Wilson et al., 2014).
C-22 2018 Gulf of Mexico Supplemental EIS

C.4.1.2 Offshore Support Helicopters

The ERG team obtained helicopter emission factors from the Switzerland Federal Office of 

Civil Aviation (FOCA) Guidance on Determination of Helicopter Emissions (FOCA, 2009). However, 

the landing and takeoff (LTO) cycle used by FOCA was determined to be too short for typical trips 

taken in the Gulf of Mexico. The time-in-mode values were therefore adjusted based on the 

International Civil Aviation Organization (ICAO) test cycles, which are considered to be appropriate 

for offshore operations in the Gulf of Mexico. Because the future fleet mix is unknown, ERG 

weighted the emission factors using fleet profile data from the Helicopter Safety Advisory 

Conference (HSAC, 2015). The VOC emission factors were developed by converting the 

hydrocarbon (HC) emission factors using data from the USEPA’s Procedures for Emission Inventory 

Preparation Volume IV: Mobile Sources (USEPA, 1992). The aggregated general aviation 

conversion factor of 1.0631 for turbine engines was used because the GOM support helicopter fleet 

is primarily equipped with turbine engines. The PM2.5 emission factors were speciated from PM10

factors using USEPA aircraft speciation data, and the SO2 emission factors were developed based 

on a typical jet fuel sulfur concentration of 0.05% (UNEP, 2012).

C.4.1.3 Oil and Gas Production Offshore Support Vessels

Four components are needed to estimate future offshore vessel emissions:

• vessel characteristics (engine power and speed); 

• engine operating load (percent of maximum engine power); 

• hours of operation (typically determined by the distance the vessel travels divided 

by the vessel speed); and

• appropriate emission factors (grams per kW-hr). 

Because there is uncertainty about the location of future activities, it was assumed that a 

typical vessel trip is 200 nautical miles, which is the round-trip distance from shore to the mid-point of 

Federal waters.

In projecting future year activity, it is not always possible to identify specific vessels that will 

be used. Therefore, the use of larger vessels that represent the upper bound of each vessel type 

was assumed, such that actual future year emissions should be similar to or lower than emission 

estimates developed using this fleet profile. These vessels were identified based on data compiled 

from the Information Handling Service (IHS) Register of Ships (IHS, 2015). Vessels from the global 

fleet were used because these larger ships move internationally based on local demand. It should 

also be noted that these larger vessels tend to be involved in deepwater activities because they are 

designed for extended open-water operations. As trends to develop deeper water locations in the 

Gulf of Mexico continue into the future, it is likely that these larger or similar vessels will support 

future year activities.
Air Quality: Emissions for the Cumulative and Visibility Impacts C-23

The selected vessels and their characteristics are presented in Table C-5. In order to 

correctly match the vessel to the appropriate emission factors, the vessel engine category is 

required. The USEPA vessel category was determined by calculating the cylinder volume based on 

the stroke length and diameter of the cylinder. The USEPA categories are defined by the following 

cylinder volumes:

• Category 1: Cylinder displacement less than 5 liters; 

• Category 2: Cylinder displacement from 5 to 30 liters; and

• Category 3: Cylinder displacement greater than 30 liters.

If a vessel’s cylinder volume was unknown, it was assumed that the vessel was powered by 

a Category 3 propulsion engine. It should also be noted that all of the selected vessels are foreign 

flagged, but it is assumed that they refuel using U.S.-regulated marine fuels as they shift equipment 

and supplies from nearby U.S. ports.

Table C-5. Summary of Vessel Characteristics. 

Vessel Type Total Main Power 

(kW) Vessel Name Propulsion Engine Category

Speed 

(knots)

Drillship 48,666 Rowan 

Renaissance 3 12

Jackup 12,485 Bob Palmer 2

(auxiliary) Not self-propelled

Platform Rig 8,100 Nabors Mods 087 2

(auxiliary) Not self-propelled

Semisubmersible 22,371 ENSCO 7500 2 3.5

Submersible 3,691 Hercules 78 2

(auxiliary) Not self-propelled

FPSO 14,1101 Terra Nova 

FPSO 2 12.0

FSO 51,519 Africa 3 16.5

Stimulation Vessel 15,840 Norshore Atlantic 2 14

Oil Tanker 13,369 SPT Explorer 3 15

Anchor Handling 

Vessel 27,000 KL Sandefjord 3 17

Crew Boat 11,520 R. J. Coco 

Mccall 3 23

Supply Vessel 18,000 Aleksey Chirikov 3 15

Tug Boat 19,990 Yury Topchev 3 15

Pipe-Laying Vessel 67,200 Castorone 3 14

1 Only distillate oil main engine kW included (430 kW & 2 x 6840 kW). Topside emissions are 

included in the deepwater production platform estimates. 

A vessel’s engine power varies relative to the type of operation that is implemented. While 

cruising in open waters, the propulsion engine load is typically 84% of maximum load; during 
C-24 2018 Gulf of Mexico Supplemental EIS

maneuvering, it can be 60% or lower; and when stationary,. it can be 10% or lower. Table C-6

presents the aggregated load factors that will be used in this Study for propulsion and auxiliary 

engines.

Table C-6. Load Factors to be Used in the Future Year Projections. 

Vessel Type Load Factor

Propulsion Cruising 0.8-0.85

Propulsion Idle 0.1

Propulsion Crew/Supply Boat 0.45

Propulsion Drill Ship and Semi-Submersible 0.83

Propulsion Pipe-Laying Vessel 0.16

Propulsion Tug 0.68

Auxiliary Emergency Generator 0.75

Drilling Equipment 1

The future year emission factors were developed in terms of grams of pollutant emitted per 

load-adjusted engine kW-hours based on the emission factors used in the USEPA’s 2014 NEI 

(Table C-7). The factors presented below are applicable for foreign-flagged vessels that are not 

required to comply with USEPA exhaust standards but that must comply with international Emission 

Control Area (ECA) standards. These future year factors account for the reduction in fuel sulfur level 

associated with the ECA. Because Category 2 foreign-flagged offshore support vessels will be 

refueling at U.S. ports, it was anticipated that these vessels will use low sulfur compliant U.S. fuels. 

Also, the NOx emission factors were adjusted to account for the 2016 ECA Tier III standard that 

requires high efficiency, after-treatment technology, and is applicable for U.S. and foreign-flagged 

vessels. The Category 3 PM emission factors were not adjusted to account for reductions in PM as 

sulfate compounds because the USEPA’s adjustment equation provided a PM factor lower than the 

PM emission factor for Category 2 powered vessels. 

Table C-7. Marine Vessel Emission Factors (g/kW-hr). 

Engine Category NOx SO2 PM10 PM2.5 VOC CO HC NH3 Pb

2 3.4 0.006 0.320 0.310 0.141 2.48 0.13 0.005 0.00003

3 3.4 0.362 0.450 0.437 0.632 1.40 0.60 0.003 0.00003

Source: USEPA, 2016b.

C.4.1.4 Future Year Emission Estimates and Selection of Future Modeling Year

The emission estimates developed for the future BOEM oil and gas production sources were 

reviewed to determine the most suitable future year emissions to model. The PGM modeling for the 

cumulative and visibility impacts analysis was conducted based on the emissions anticipated to have 

the greatest impact on the air quality of any state. This was determined based on the estimated 

annual emission trends. The future highest NOx emission year for all activities in all planning areas 

coincided with the highest PM, CO, NH3, and Pb emissions. These emissions are driven by support 

vessel activity for the most part. The future highest VOC emission year for all activities in all 

planning areas coincided with the highest SO2 emissions and is driven by production platform 
Air Quality: Emissions for the Cumulative and Visibility Impacts C-25

emissions. Table C-8 presents the resulting emission estimates, and Figure C-11 presents a 

graphical depiction of the annual emission estimates for all pollutants. Figures C-12 through C-14

present graphical depictions of the annual emission estimates for NOx, VOC, and PM2.5 by source 

category.

It was concluded that BOEM would model the activity data and resulting emission estimates 

for year 2033 for non-platform sources, and year 2036 activity data and resulting emission estimates 

for platform sources.

Table C-8. Emission Estimates for the Western, Central, and Eastern Planning Areas, All Depths, By 

Year and Pollutant.

Year NOx 

(TPY)

SO2

(TPY)

PM10

(TPY)

PM2.5

(TPY)

VOC 

(TPY)

CO 

(TPY)

Pb 

(TPY)

NH3

(TPY)

2017 3,693 40 360 349 200 2,591 0.03 10

2018 19,328 118 1,813 1,759 1,213 14,058 0.17 80

2019 34,958 158 3,199 3,104 2,150 25,462 0.30 98

2020 46,119 268 4,124 4,001 3,042 33,293 0.39 111

2021 50,126 379 4,368 4,238 3,807 35,937 0.42 125

2022 54,328 446 4,605 4,469 4,535 38,906 0.45 139

2023 57,639 527 4,888 4,743 5,311 41,426 0.48 154

2024 59,979 484 5,030 4,881 5,872 43,637 0.49 170

2025 64,527 523 5,413 5,252 6,543 47,198 0.53 189

2026 70,601 598 5,870 5,696 7,510 51,762 0.57 209

2027 76,146 704 6,305 6,118 8,419 55,747 0.61 228

2028 79,863 742 6,609 6,414 9,125 58,701 0.64 244

2029 85,277 803 7,012 6,805 10,034 62,750 0.68 262

2030 90,332 876 7,381 7,163 11,010 66,523 0.72 280

2031 97,123 984 7,860 7,628 12,185 71,365 0.77 298

2032 100,564 1,022 8,057 7,820 13,228 74,107 0.79 315

2033 108,4471 1,199 8,590 8,338 14,709 79,486 0.85 334

2034 101,673 1,193 7,919 7,687 14,939 74,742 0.79 329

2035 102,443 1,253 7,923 7,691 15,484 75,167 0.79 327

2036 103,354 1,395 7,865 7,635 15,940 75,096 0.79 318

2037 96,715 1,343 7,274 7,062 15,254 70,088 0.74 298

2038 92,539 1,327 6,935 6,732 14,560 66,732 0.71 283

2039 84,787 1,280 6,269 6,087 13,443 60,725 0.65 247

2040 79,475 1,235 5,841 5,672 12,317 56,455 0.61 226

2041 77,705 1,294 5,652 5,488 11,544 54,267 0.60 209

2042 71,710 1,292 5,110 4,962 10,485 49,266 0.55 187
C-26 2018 Gulf of Mexico Supplemental EIS

Table C-8. Emission Estimates for the Western, Central, and Eastern Planning Areas, All Depths, By 

Year and Pollutant. (continued). 

Year NOx 

(TPY)

SO2

(TPY)

PM10

(TPY)

PM2.5

(TPY)

VOC 

(TPY)

CO 

(TPY)

Pb 

(TPY)

NH3

(TPY)

2043 51,254 1,094 3,390 3,293 8,643 34,736 0.38 157

2044 46,692 1,077 3,018 2,932 7,842 31,076 0.35 143

2045 42,933 1,009 2,752 2,673 7,115 28,358 0.32 128

2046 39,227 974 2,433 2,364 6,492 25,503 0.29 117

2047 37,540 965 2,313 2,247 6,006 24,050 0.28 108

2048 34,738 954 2,083 2,024 5,495 21,808 0.26 98

2049 32,995 904 1,995 1,939 5,020 20,615 0.25 90

2050 28,873 849 1,688 1,640 4,403 17,665 0.22 82

2051 26,286 796 1,524 1,481 3,872 15,834 0.20 73

2052 24,303 747 1,406 1,367 3,475 14,510 0.18 67

2053 15,585 598 757 737 2,610 8,716 0.11 23

2054 13,131 592 542 527 2,333 6,838 0.09 17

2055 12,062 502 548 533 2,010 6,479 0.09 16

2056 10,119 453 434 422 1,615 5,185 0.07 12

2057 9,083 450 340 331 1,528 4,407 0.06 9

2058 8,519 405 344 335 1,321 4,185 0.06 8

2059 7,182 316 321 313 1,031 3,653 0.05 7

2060 6,052 314 215 209 984 2,829 0.04 5

2061 5,765 270 237 231 877 2,852 0.04 5

2062 5,075 268 180 176 760 2,305 0.04 4

2063 4,614 224 186 181 646 2,201 0.03 3

2064 3,524 136 183 178 433 1,872 0.03 2

2065 1,906 46 130 126 175 1,157 0.02 1

2066 1,392 46 81 79 153 782 0.01 1

1 Bold numbers are the highest emissions per year per pollutant. These were the amounts modeled.
Air Quality: Emissions for the Cumulative and Visibility Impacts C-27

Figure C-11. Emission Estimates for all Planning Areas and Future Activities. 

Figure C-12. Combined Annual NOx Emissions. 
C-28 2018 Gulf of Mexico Supplemental EIS

Figure C-13. Combined Annual VOC Emissions. 

Figure C-14. Combined Annual PM2.5 Emissions. 

C.4.1.5 Spatial Allocation

The estimated emissions were allocated by planning area (WPA vs. CPA/EPA) and water 

depth (i.e., 0-60 m, 60-200 m, 200-800 m, 800-1,600 m, 1,600-2,400 m, and >2,400 m). 

Figure C-15 depicts the planning area boundaries and water depth contours. (Note that the 

GOMESA Congressional Moratoria Area is not indicated in Figure C-15.) Emissions were not 

allocated to the GOMESA. The emission estimates were allocated spatially based on the 

anticipated future year activities provided by BOEM. Because helicopters, support vessels, and 
Air Quality: Emissions for the Cumulative and Visibility Impacts C-29

tankers transit multiple water depths, their emissions were allocated across multiple water depth 

contours based on assumed installed platform locations.

Figure C-15. BOEM OCS Planning Areas and Water Depths. 

For some sources, emissions were assigned to unleased blocks in each area (i.e., WPA and 

CPA/EPA) relative to the water depth where the activity is anticipated to occur. These categories 

include the following:

• exploratory drilling vessels; 

• development/production drilling vessels; and

• production platforms.

Production platforms were located as point sources with randomly selected locations. Using 

GIS, each lease block in the Gulf of Mexico was assigned to a water depth bin. Blocks with an

active lease and that have contained a platform were then removed. Blocks that have had a 

platform suggest that they were leased at some point in time, and therefore are less desirable for 

future exploration. Once the inactive blocks with no history of production were identified, random 

blocks were selected throughout each water depth for each future platform as depicted in 

Figure C-15. Each platform was placed in a separate block at the centroid. Pipe-laying vessel 
C-30 2018 Gulf of Mexico Supplemental EIS

activities were assigned to leased and unleased blocks as their operations were not limited to just 

the unleased blocks.

Emissions associated with BOEM’s existing OCS oil and gas production sources were held 

constant at 2012 levels.

C.4.2 Onshore Sources and Marine Vessels

In support of the proposed ozone NAAQS revisions, the USEPA released the 2011 air quality 

modeling platform (2011v6.1), with projections to 2018 and 2025, for point, nonpoint area, and 

mobile sources in the United States (USEPA, 2014d). In addition, the USEPA released the 2011 air 

quality modeling platform (2011v6.2), with projections to 2017, to support ozone transport modeling 

for the 2008 NAAQS as well as the 2015 ozone NAAQS (USEPA, 2015d). In early October, 2015, 

the USEPA also released the 2011v6.2 calendar year 2025 projected inventory (USEPA, 2015d). 

The ERG team used the 2011v6.2 platform for calendar year 2017, primarily because the platform is 

based on the most recent version of the NEI (2011v.2). Calendar year 2017 data were selected 

rather than 2025 data because there is less uncertainty associated with the 2017 estimated 

emissions because most of the controls factored in by the USEPA are already “on the books” and 

not speculative. The Technical Support Document (TSD) Preparation of Emissions Inventories for 

the Version 6.2, 2011 Emissions Modeling Platform (USEPA, 2015d) provides details on the 

development of the 2011v6.2 future year modeling platforms.

C.4.3 Other Sources

For sources in Mexico, the USEPA air quality modeling platform 2011v6.2 includes projected 

2018 emissions for onshore sources. The USEPA held emissions constant for sources in Canada.

For completeness, projected emissions estimates were also developed for platforms off the 

coast of Mexico; the ERG team researched the impacts of the restructuring of the energy sector in 

Mexico, which is predicted to include deepwater drilling within the modeling domain. Emissions were 

estimated based on projected deepwater production (PEMEX, 2012) and using production-based 

emission factors developed from the 2011 Gulfwide Inventory (Wilson et al., 2014).

For the LOOP and vessel lightering, emissions were held at 2012 levels because of 

uncertainties in future crude oil imports, which involve the very large crude carriers that visit the 

LOOP and lightering zones. The ERG team also investigated the need to include a liquefied natural 

gas (LNG) port to be located in Federal waters and originally expected to be operational in 2019. On 

September 18, 2015, however, the Maritime Administration (MARAD) and the U.S. Coast Guard 

stopped the permit application process, as Delphin LNG, LLC is amending the application. This 

potential source was not included in the future scenario given this uncertainty.
Air Quality: Emissions for the Cumulative and Visibility Impacts C-31

C.5 SOURCE APPORTIONMENT

Source apportionment, as applied in PGM modeling, provides a means of assessing the 

contributions of specified sources or source groups to predicted ozone and PM concentrations under 

the air quality conditions being simulated. Source contributions can be calculated for ozone and for 

PM using ozone or PM source apportionment routines included in the CAMx PGM modeling. In this 

Study, the primary receptor locations of interest for examining source contributions lie both along the 

shoreline and the State seaward boundary, although the PGM source apportionment output is for the 

entire modeling domain. Source apportionment analyses with the PGM will be applied to the future 

year scenario in order to analyze the pre- and postlease OCS oil and gas impacts to short-term and 

annual NAAQS. This will afford BOEM the opportunity to discern which source groups have the 

largest impacts and potentially need to be examined for control strategies. BOEM selected the 

following source groups for source apportionment:

• fires (U.S., Canada, and Mexico); 

• biogenic and other natural sources (e.g., lighting NOx and sea salt); 

• additional BOEM OCS oil and gas production platforms associated with the FiveYear Program; 

• additional BOEM oil and gas production support vessels and helicopters 

associated with the Five-Year Program; 

• BOEM OCS oil and gas production platforms, support vessels, and helicopters 

under No Action (base case) alternative; 

• all other marine vessel activity in the Gulf of Mexico; 

• other anthropogenic U.S. sources; 

• Mexican and Canadian anthropogenic sources; and

• initial and boundary conditions (IC and BC). 

These source groups aggregate similar sources based on jurisdiction (i.e., sources under 

BOEM control versus other Federal agencies) and sources beyond control (e.g., natural emission 

sources and foreign sources). This is helpful in showing whether BOEM’s sources are significantly 

contributing to any modeled air quality issues onshore and at the State seaward boundary, or if a 

source category regulated by another Federal agency is the more likely the problem source.

Having the additional OCS oil and gas production platforms, support vessels, and helicopters 

associated with the scenarios for the 2017-2022 GOM Multisale EIS and this Supplemental EIS as 

separate source groups allows BOEM to quantify the impact of these sources on the onshore air 

quality and at the State seaward boundary.
C-32 2018 Gulf of Mexico Supplemental EIS

C.6 REFERENCES

Helicopter Safety Advisory Conference (HSAC). 2015. 2014 Gulf of Mexico Offshore Helicopter 

Operations and Safety Review. HSAC Helicopter Safety Advisory Committee. Internet website: 

http://www.hsac.org. 

Information Handling Service (IHS). 2015. IHS Vessel Database. Internet website: 

http://www.ihs.com. 

International Maritime Organization (IMO). 2015. Third IMO Greenhouse Gas Study 2014. Internet 

website: http://www.imo.org/en/OurWork/Environment/PollutionPrevention/AirPollution/

Documents/Third%20Greenhouse%20Gas%20Study/GHG3%20Executive%20Summary%20

and%20Report.pdf. 

Petróleos Mexicanos (PEMEX). 2012. Investor Presentation. April 2012. Internet website: 

http://www.pemex.com/ri/Publicaciones/Presentaciones%20Archivos/201205_p_inv_e_120508_

LA.pdf. 

PortVision. 2012. AIS 2011 data provided to the U.S. Bureau of Ocean Energy.

Seelke, C.R., M. Ratner, M.A. Villarreal, P. Brown. 2015. Mexico’s Oil and Gas Sector: 

Background, Reform Efforts, and Implications for the United States. Congressional Research 

Service. 7-5700. Internet website: https://www.fas.org/sgp/crs/row/R43313.pdf. 

SEMARNAT. 2014. Inventario Nacional de Emisiones de México, 2008. Secretaría del Medio 

Ambiente y Recursos Naturales (Secretariat of the Environment and Natural Resources). 

Detailed municipality-level emission files provided by David Alejandro Parra Romero. 

January 31.

Surface Transportation Board. 2015. R-1 Class 1 Railroad Annual Reporting Data. Internet 

website: http://www.stb.dot.gov/econdata.nsf/f039526076cc0f8e8525660b006870c9?

OpenView. 

Switzerland Federal Office of Civil Aviation (FOCA). 2009. Guidance on Determination of Helicopter 

Emissions. March 2009 Reference: 0/3/33/33-05-20.

United Nations Environment Programme (UNEP). 2012. Intergovernmental Panel on Climate 

Change, Chapter 7. Aircraft Technology and Its Relation to Emissions. Internet website: 

http://www.grida.no/publications/other/ipcc_sr/?src=/climate/ipcc/aviation/111.htm. 

U.S. Dept of the Interior. Bureau of Ocean Energy Management. 2015. Oil and Gas Operations 

Reports – Part A (OGOR-A) Well Production (1996-2015). Internet website: 

https://www.data.boem.gov/homepg/pubinfo/freeasci/product/freeprod_ogora.asp. 

U.S. Environmental Protection Agency (USEPA). 1992. Procedures for Emission Inventory 

Preparation, Volume IV: Mobile Sources. EPA 420-R-92-009. Internet website: 

http://www3.epa.gov/otaq/models/nonrdmdl/r92009.pdf. 
Air Quality: Emissions for the Cumulative and Visibility Impacts C-33

U.S. Environmental Protection Agency (USEPA). 2010. Designation of North American Emission. 

Control Area to Reduce Emissions from Ships. U.S. Environmental Protection Agency, Office of 

Transportation and Air Quality. EPA-420-F-10-015. Internet website: http://www.epa.gov/

otaq/regs/nonroad/marine/ci/420f10015.pdf. 

U.S. Environmental Protection Agency (USEPA). 2014a. SPECIATE Version 4.4. U.S. 

Environmental Protection Agency, Office of Air Quality Planning and Standards. Internet 

website: http://www.epa.gov/ttn/chief/software/speciate/index.html. 

U.S. Environmental Protection Agency (USEPA). 2014b. 2011 NEI Nonpoint Emission Estimation 

Tools and Methods. U.S. Environmental Protection Agency, Office of Air Quality Planning and 

Standards. Internet website: http://www.epa.gov/ttn/chief/net/2011inventory.html#inventorydoc. 

U.S. Environmental Protection Agency (USEPA). 2014c. MOVES2014. U.S. Environmental 

Protection Agency. Internet website: http://pubweb.epa.gov/otaq/models/moves/. 

U.S. Environmental Protection Agency (USEPA). 2014d. Ozone NAAQS Emissions Modeling 

Platform (2011 v6.1). 2011, 2018, and 2025 Emissions Modeling Platform Technical Support 

Document. Internet website: http://www3.epa.gov/ttn/chief/emch/index.html. 

U.S. Environmental Protection Agency (USEPA). 2015a. 2011 National Emissions Inventory (NEI), 

Version 2. U.S. Environmental Protection Agency, Office of Air Quality Planning and Standards, 

Air Quality Assessment Division, Emission Inventory and Analysis Group, Research Triangle 

Park, NC. Internet website: http://www.epa.gov/ttn/chief/eiinformation.html. 

U.S. Environmental Protection Agency (USEPA). 2015b. 2012 National Emissions Inventory (NEI). 

Provided by the U.S. Environmental Protection Agency, Office of Air Quality Planning and 

Standards, Air Quality Assessment Division, Emission Inventory and Analysis Group, Research 

Triangle Park, NC. Internet website: http://www.epa.gov/ttn/chief/eiinformation.html. 

U.S. Environmental Protection Agency (USEPA). 2015c. Toxics Release Inventory (TRI) Program. 

U.S. Environmental Protection Agency, Office of Environmental Information, Washington, DC. 

Internet website: http://www2.epa.gov/toxics-release-inventory-tri-program. 

U.S. Environmental Protection Agency (USEPA). 2015d. Technical Support Document (TSD) 

Preparation of Emissions Inventories for the Version 6.2, 2011 Emissions Modeling Platform. 

Internet website: https://www.epa.gov/air-emissions-modeling/2011-version-62-platform. 

U.S. Environmental Protection Agency (USEPA). 2016a. Green Book Nonattainment Areas, 8 Hour 

Ozone Nonattainment Areas (2008 Standard). Internet website: https://www3.epa.gov/

airquality/greenbook/map8hr_2008.html. 

U.S. Environmental Protection Agency (USEPA). 2016b. 2014 National Emissions Inventory (NEI) 

Documentation. U.S. Environmental Protection Agency, Office of Air Quality Planning and 

Standards, Research Triangle Park, NC. Internet website: https://www.epa.gov/air-emissionsinventories/2014-national-emissions-inventory-nei-documentation. 
C-34 2018 Gulf of Mexico Supplemental EIS

Wilson, D., R. Billings, R. Chang, H. Perez, and J. Sellers. 2014. Year 2011 Gulfwide Emissions 

Inventory Study. U.S. Department of the Interior, Bureau of Ocean Energy Management, Gulf of 

Mexico OCS Region, New Orleans, LA. OCS Study BOEM 2014-666. 182 pp.
APPENDIX D 

 

AIR QUALITY: 

CUMULATIVE AND VISIBILITY IMPACTS

Table of Contents D-iii

TABLE OF CONTENTS

Page

D.1 INTRODUCTION........................................................................................................................ D-1

D.1.1 Background on Air Quality Impact Analyses and Thresholds........................................ D-2

D.1.1.1 Ambient Air Quality Standards.......................................................................... D-3

D.1.1.2 Air Quality-Related Values................................................................................ D-5

D.1.2 Overview of Approach .................................................................................................... D-6

D.2 METEOROLOGY....................................................................................................................... D-7

D.3 EMISSIONS ............................................................................................................................... D-8

D.3.1 Pollutants........................................................................................................................ D-9

D.3.2 Base Year....................................................................................................................... D-9

D.3.3 Geographical Domain..................................................................................................... D-9

D.3.4 Inventory Sources......................................................................................................... D-10

D.3.5 Spatial Resolution......................................................................................................... D-11

D.3.6 Temporal Resolution .................................................................................................... D-11

D.3.7 Speciation..................................................................................................................... D-12

D.3.8 Base Year and Future Year Emission Estimates......................................................... D-12

D.3.9 Emissions Processing for Preparation of Model-Ready Emissions............................. D-12

D.3.9.1 Smoke Processing .......................................................................................... D-12

D.3.9.2 Biogenic Emissions ......................................................................................... D-14

D.3.9.3 Fire Emissions................................................................................................. D-14

D.3.9.4 Sea Salt and Halogen Emissions.................................................................... D-15

D.3.9.5 Lightning NOx Emissions................................................................................ D-16

D.3.9.6 Windblown Dust .............................................................................................. D-16

D.3.9.7 QA/QC of Processed Emissions..................................................................... D-16

D.3.9.8 Development of Model-Ready Emissions....................................................... D-16

D.3.9.9 Summary of Processed Emissions ................................................................. D-17

D.3.10 Source Apportionment Design ..................................................................................... D-33

D.4 BASE CASE PHOTOCHEMICAL GRID MODELING.............................................................. D-34

D.4.1 Overview....................................................................................................................... D-34

D.4.2 Model Grid Configuration ............................................................................................. D-35

D.4.3 Meteorology.................................................................................................................. D-37

D.4.4 Configuration of Model Input Parameters .................................................................... D-38

D.5 MODEL PERFORMANCE EVALUATION ............................................................................... D-40

D.5.1 Implications of WRF Model Performance on PGM Simulations .................................. D-41

D.5.2 Ambient Data Used In the Model Performance Evaluation ......................................... D-41

D.5.3 Model Performance Statistics....................................................................................... D-45

D.5.4 Approach ...................................................................................................................... D-47
D-iv 2018 Gulf of Mexico Supplemental EIS

D.5.5 Initial Model Performance Results ............................................................................... D-49

D.5.6 Final Model Performance Results ................................................................................ D-49

D.5.6.1 Ozone.............................................................................................................. D-50

D.5.6.2 Particulate Matter............................................................................................ D-57

D.6 AIR RESOURCE ASSESSMENT APPROACH....................................................................... D-69

D.6.1 Future Year Modeling................................................................................................... D-69

D.6.1.1 Source Apportionment Design........................................................................ D-69

D.6.1.2 Future Year Source Apportionment Simulation .............................................. D-70

D.6.2 Post-Processing of Future Year Source Apportionment Modeling Results................. D-71

D.6.2.1 Overview ......................................................................................................... D-71

D.6.2.2 Comparison against NAAQS........................................................................... D-72

D.6.2.3 Impacts at Class I and Sensitive Class II Areas ............................................. D-73

D.6.2.4 PSD Increments .............................................................................................. D-80

D.7 AIR RESOURCE ASSESSMENT RESULTS .......................................................................... D-80

D.7.1 NAAQS Impacts ........................................................................................................... D-80

D.7.1.1 Ozone NAAQS Analysis using Relative Model Results.................................. D-80

D.7.1.2 Ozone NAAQS Analysis Using Absolute Modeling Results ........................... D-89

D.7.1.3 PM2.5 NAAQS Analysis using Relative Model Results.................................. D-92

D.7.1.4 PM2.5 NAAQS Analysis using Absolute Model Predictions........................... D-99

D.7.1.5 NAAQS Analysis for other Criteria Air Pollutants ......................................... D-106

D.7.2 PSD Increments ......................................................................................................... D-120

D.7.3 AQRV Impacts............................................................................................................ D-122

D.7.3.1 Visibility.......................................................................................................... D-122

D.7.3.2 Acid Deposition ............................................................................................. D-134

D.8 REFERENCES....................................................................................................................... D-137
List of Tables D-v 

LIST OF TABLES

Page

Table D-1. Nonattainment and Maintenance Areas in the Southeastern U.S. ............................... D-4

Table D-2. Gulf of Mexico OCS Region Air Quality Modeling Study Source Categories. ............ D-10

Table D-3. 2012 Fire Criteria Air Pollutant Emissions Summary by Fire Type for BOEM’s 

36-, 12-, and 4-km Domains........................................................................................ D-15

Table D-4. 2012 Base Case and Future Year Emissions Summary by State for BOEM’S 

12-km Domain (only Gulf Coast States: Alabama, Florida, Louisiana, 

Mississippi, and Texas). .............................................................................................. D-18

Table D-5. 2012 Base Case and Future Year Emissions Summary by Source Category for 

BOEM’s 4-km Domain. ................................................................................................ D-26

Table D-6. Changes in Emissions between the 2012 Base Case and Future Year 

Emissions (short tons per year) by Source Category for BOEM’s 4-km Domain. ...... D-27

Table D-7. Source Categories for Source Apportionment Calculations........................................ D-34

Table D-8. Domain Grid Definitions for the WRF and CAMx/CMAQ Modeling. ........................... D-35

Table D-9. Vertical Layer Interface Definition for WRF Simulations (left-most columns) and 

the Layer-collapsing Scheme for the CAMx/CMAQ Layers (right columns)............... D-36

Table D-10. CAMx Model Configuration.......................................................................................... D-39

Table D-11. Definitions of Model Performance Evaluation Statistical Metrics................................ D-45

Table D-12. Ozone and PM Model Performance Goals and Criteria.............................................. D-46

Table D-13. Model Performance Statistics at Different Observed Ozone Concentration 

Screening Thresholds Based on All Monitoring Sites in the 4-km Domain 

(shaded cells indicate values exceeding USEPA performance goals). ...................... D-55

Table D-14. NAAQS and PSD Increments...................................................................................... D-71

Table D-15. Source Group for Incremental Impacts Analysis......................................................... D-72

Table D-16. Class I and Sensitive Class II Areas in Gulf Coast and Nearby States. ..................... D-74

Table D-17. Current Year (DVC) and Future Year (DVF) Ozone Design Values at Ambient 

Air Monitoring Sites within the 4-km Modeling Domain from MATS. .......................... D-82

Table D-18. Ozone Current (DVC) and Future Year (DVF) Design Values and Reduction in 

DVF with Contributions from Individual Source Groups Removed............................. D-84

Table D-19. MATS Ozone Design Value Results for All Monitoring Sites Where Exclusion of 

Contributions from Source Group A or B is Sufficient to Reduce the Predicted 

Future Design Value (DVF) from Above the NAAQS to Below the NAAQS (all 

values in ppb). ............................................................................................................. D-86

Table D-20. Current Year (DVC) and Future Year (DVF) 24-Hour PM2.5 Design Values for 

Monitoring Sites in the 4-km Modeling Domain from MATS. ...................................... D-93

Table D-21. 24-Hour PM2.5 Current (DVC) and Future Year (DVF) Design Values and 

Reduction in DVF with Contributions from Individual Source Groups Removed........ D-94

Table D-22. Current (DVC) and Projected Future (DVF) Annual Average PM2.5 Design 

Values for Monitoring Sites in the 4-km Modeling Domain (highlighted values 

exceed the 12 μg/m3 NAAQS)..................................................................................... D-95
D-vi 2018 Gulf of Mexico Supplemental EIS

Table D-23. Annual Average PM2.5 Future Year Design Values (DVF) and Change in DVF 

with Contributions from Individual Source Groups Removed (highlighted values 

exceed the 12 μg/m3 NAAQS)..................................................................................... D-96

Table D-24. Maximum Source Group Contributions for PSD Pollutants at Class I and 

Sensitive Class II Areas in the 4-km Modeling Domain. ........................................... D-121

Table D-25. Source Group Contributions for PSD Pollutants at All Class I and Sensitive 

Class II Areas in the 4-km Modeling Domain............................................................ D-123

Table D-26. Incremental Visibility Impacts Relative to Natural Background Conditions from 

Source Group A......................................................................................................... D-124

Table D-27. Incremental Visibility Impacts Relative to Natural Background Conditions from 

Source Group B......................................................................................................... D-125

Table D-28. Cumulative Visibility Results for 20% Worst Visibility Days (W20%) at Class I 

Areas for Base (2012) Year (BY) and Future Year (FY) Scenarios with All 

Sources Included and with Contributions from Each Source Group Removed........ D-128

Table D-29. Differences in Cumulative Visibility Results for 20% Worst Visibility Days 

(W20%) at Class I Areas Between the Future Year (FY) and Base Year (BY) 

Scenarios and Contributions of Each Source Group to the Future Year Scenario 

Visibility...................................................................................................................... D-130

Table D-30. Cumulative Visibility Results for 20% Best Visibility Days (B20%) at Class I 

Areas for Base (2012) Year (BY) and Future Year (FY) Scenarios with All 

Sources Included and with Contributions from Each Source Group Removed........ D-132

Table D-31. Differences in Cumulative Visibility Results for 20% Best Visibility Days (B20%) 

at Class I Areas Between the Future Year (FY) and Base Year (BY) Scenarios 

and Contributions of Each Source Group to the Future Year Scenario Visibility...... D-133

Table D-32. Deposition Analysis Threshold Values (kg/ha/yr) as Defined in the Federal Land 

Manager Guidance (FLAG, 2010). ............................................................................ D-135

Table D-33. Incremental Deposition Impacts from Source Groups A and B at Class I and 

Sensitive Class II Areas in the 4-km Domain............................................................ D-135

Table D-34. Cumulative Nitrogen (N) and Sulfur (S) Deposition Impacts (kg/ha/yr) under the 

Base and Future Year Scenarios (shading indicates values exceeding the 

Critical Load threshold).............................................................................................. D-136
List of Figures D-vii

LIST OF FIGURES

Page

Figure D-1. Location of the “Air Quality Modeling in the Gulf of Mexico Region” Study, with 

Class I Areas (purple). ................................................................................................. D-1

Figure D-2. Ozone Nonattainment Areas in the Southeastern U.S................................................ D-3

Figure D-3. Class I and Sensitive Class II Areas in the Study Region........................................... D-5

Figure D-4. Overview of the “Air Quality Modeling in the Gulf of Mexico Region” Study 

Tasks (note that the meteorological model takes meteorological observations 

as inputs)...................................................................................................................... D-6

Figure D-5. Meteorological (WRF model) and PGM Modeling Domains Including the 36-km 

Horizontal Grid Resolution CONUS WRF Domain (outer box), 12-km 

Resolution Southeast Regional WRF (white) and PGM (blue) Domains (d02), 

and 4-km Resolution Gulf of Mexico OCS Region WRF (black) and PGM (blue) 

Domains (d03).............................................................................................................. D-8

Figure D-6. BOEM’s 12-km 2012 Base Case NOx Emissions Summary in Tons per Year by 

Source Category and State (Alabama, Florida, Louisiana, Mississippi, and 

Texas). ....................................................................................................................... D-19

Figure D-7. BOEM 12-km 2012 Base Case VOC Emissions Summary in Tons per Year by 

Source Category and State (Alabama, Florida, Louisiana, Mississippi, and 

Texas). ....................................................................................................................... D-20

Figure D-8. BOEM 12-km 2012 Base Case PM2.5 Emissions Summary in Tons per Year by 

Source Category and State (Alabama, Florida, Louisiana, Mississippi, and 

Texas). ....................................................................................................................... D-21

Figure D-9. BOEM 12-km 2012 Base Case SO2 Emissions Summary in Tons per Year by 

Source Category and State (Alabama, Florida, Louisiana, Mississippi, and 

Texas). ....................................................................................................................... D-22

Figure D-10. BOEM 12-km Future Year NOx Emissions Summary in Tons per Year by 

Source Category and State (Alabama, Florida, Louisiana, Mississippi, and 

Texas). ....................................................................................................................... D-23

Figure D-11. BOEM 12-km Future Year VOC Emissions Summary in Tons per Year by 

Source Category and State (Alabama, Florida, Louisiana, Mississippi, and 

Texas). ....................................................................................................................... D-24

Figure D-12. BOEM 12-km Future Year PM2.5 Emissions Summary in Tons per Year by 

Source Category and State (Alabama, Florida, Louisiana, Mississippi, and 

Texas). ....................................................................................................................... D-25

Figure D-13. BOEM 12-km Future Year SO2 Emissions Summary in Tons per Year by 

Source Category and State (Alabama, Florida, Louisiana, Mississippi, and 

Texas). ....................................................................................................................... D-26

Figure D-14. Spatial Distribution of (clockwise starting from top left) NOx, VOC, SO2, and 

PM2.5 Emissions (tons per year) from New OCS Oil and Gas Production 

Platforms under the Proposed Action........................................................................ D-29
D-viii 2018 Gulf of Mexico Supplemental EIS

Figure D-15. Spatial Distribution of Emissions (tons per year) of (clockwise starting from top 

left) NOx, VOC, SO2, and PM2.5 from BOEM’s OCS Additional Oil and Gas 

Support Vessels and Helicopters under the Proposed Action Scenario. .................. D-30

Figure D-16. Spatial Distribution of (clockwise starting from top left) NOx, VOC, SO2, and 

PM2.5 Emissions (tons per year) from BOEM’s OCS Oil and Gas Platforms, 

Support Vessels, and Helicopters under the No Action Alternative in BOEM’s 

4-km Domain.............................................................................................................. D-31

Figure D-17. Spatial Distribution of (clockwise starting from top left) NOx, VOC, SO2, and 

PM2.5 Emissions (tons per year) from All Other Marine Vessel Activity in the 

Gulf of Mexico under the Future Year Scenario in BOEM’s 4-km Domain. .............. D-32

Figure D-18. Spatial Distribution of (clockwise starting from top left) NOx, VOC, SO2, and 

PM2.5 Emissions (tons per year) from Other Anthropogenic U.S. Sources for the 

Future Year Scenario within BOEM’s 4-km Domain.................................................. D-33

Figure D-19. Ozone Monitoring Sites Used in the Model Performance Evaluation: CASTNet 

Sites in the Southeastern U.S. (top) and AQS Sites within the 4-km Modeling 

Domain (bottom) (color coding of AQS monitor locations is arbitrary). ..................... D-42

Figure D-20. Speciated PM Monitoring Sites Used in the Model Performance Evaluation: 

CSN Network (top), IMPROVE Network (bottom left), and SEARCH Network 

(bottom right).............................................................................................................. D-44

Figure D-21. Monthly Normalized Mean Bias and Normalized Mean Error for Daily Maximum 

8-hour Average Ozone at AQS (left) and CASTNet (right) Monitoring Sites 

Located within the 4-km Modeling Domain (top) and the 12-km Domain 

(bottom)...................................................................................................................... D-50

Figure D-22. Fraction of Site-days during Each Month of 2012 with Observed Daily 

Maximum 8-hour Ozone Exceeding 60 (top), 65 (middle), or 70 (bottom) ppb 

Over All Monitoring Sites in the 4-km Domain........................................................... D-51

Figure D-23. Observed (blue) and Predicted (red) Monthly Mean Daily Maximum 8-hour 

Average Ozone Over All Sites in the 4-km Modeling Domain................................... D-52

Figure D-24. Scatter (left) and Scatter Density (right) Plots for Observed vs. Predicted Daily 

Maximum 8-hour Ozone in Q2 (top) and Q3 (bottom) for All AQS Monitoring 

Sites in the 4-km Modeling Domain. .......................................................................... D-53

Figure D-25. Normalized Mean Bias (NMB) for Daily Maximum 8-hour Ozone for Q2 (top) 

and Q3 (bottom). ........................................................................................................ D-54

Figure D-26. Time Series of Daily Maximum 8-hour Ozone at Monitoring Sites with Highest 

Design Values in Harris (top), Brazoria (middle), and Galveston (bottom) 

Counties, Texas, for Q2 (left) and Q3 (right). ............................................................ D-56

Figure D-27. Time Series of Daily Maximum 8-hour Ozone at Monitoring Sites in the Baton 

Rouge Nonattainment Area: LSU (top) and Carville (bottom) for Q2 (left) and 

Q3 (right). ................................................................................................................... D-56

Figure D-28. Time Series of Daily Maximum 8-hour Ozone at the ALC188 (AlabamaCoushatta, Texas) CASTNet Monitoring Site for Q2 (top) and Q3 (bottom)............. D-57

Figure D-29. PM Monitoring Sites in the Southeastern U.S. Domain (triangles – AQS hourly, 

square – IMPROVE, diamond – CSN, circles – AQS FRM daily). ............................ D-59
List of Figures D-ix

Figure D-30. Soccer Plots of Total PM2.5 Mass Model Performance Across the IMPROVE 

(top left), CSN (top right), SEARCH (bottom left), and FRM Daily (bottom right) 

Monitoring Networks for Sites in the Southeastern U.S. Domain.............................. D-60

Figure D-31. Comparisons of Predicted with Observed Daily Average PM at CSN Network 

Sites in the Southeastern U.S. for Q2 (left) and Q4 (right) for Total PM2.5 (top), 

Other PM2.5 (middle), and Sodium (bottom). ............................................................. D-61

Figure D-32. Comparisons of Observed vs. Predicted OC (top) and EC (bottom) at SEARCH 

(left) and CSN (right) Network Sites in the Southeastern U.S................................... D-62

Figure D-33. Monthly Normalized Mean Bias and Normalized Mean Error for Hourly NO2

(top) and Daily NOy (bottom) at SEARCH Network Sites (left) and AQS Sites 

(right) in the 4-km Domain.......................................................................................... D-63

Figure D-34. Monthly Normalized Mean Bias and Normalized Mean Error for NO3 at 

SEARCH Network Monitoring Sites (top left) and AQS Sites (top right) and 

NO3 Deposition at NADP Sites (bottom) in the Southeastern U.S. (Note: 

Additional months for SEARCH NO3 not shown as the NMB and NME exceed 

the upper axis limits.) ................................................................................................. D-64

Figure D-35. Monthly Normalized Mean Bias and Normalized Mean Error at Monitoring Sites 

in the 4-km Domain for SO2 (top row, AQS sites left panel, SEARCH sites right 

panel), SO4 (middle row, CSN sites left panel, SEARCH sites right panel), and 

SO4 Deposition Measured at NADP Sites (bottom row)............................................ D-66

Figure D-36. Annual Normalized Mean Bias for Hourly SO2 (based on 12-km resolution 

CAMx results)............................................................................................................. D-67

Figure D-37. Monthly Normalized Mean Bias and Normalized Mean Error for Daily Average 

NH4 at CSN (top) and SEARCH (bottom) Network Sites in the 4-km Modeling 

Domain. ...................................................................................................................... D-68

Figure D-38. Monthly Normalized Mean Bias and Normalized Mean Error for Hourly CO at 

SEARCH Network Sites (left) and AQS Sites (right). ................................................ D-69

Figure D-39. Class I and Sensitive Class II Areas for Which Incremental AQ/AQRV Impacts 

Were Calculated......................................................................................................... D-73

Figure D-40. Base Scenario Ozone Design Values (DVC, top left), Future Year Ozone 

Design Values (DVF, top right) and Their Differences (DVF – DVC; bottom) 

Calculated Using the MATS UAA Tool. ..................................................................... D-87

Figure D-41. MATS UAA Future Year Ozone Design Values (DFV) Calculated After First 

Removing the Hourly Contributions from a Source Group (left column) and the 

Corresponding Contributions of the Source Group to DVF (right column) 

Calculated by Subtracting the DVFs Shown in the Left-hand Column from the 

“All Sources” DVF Shown in the Top Right-hand Corner of Figure D-40. Top 

row – source group B; middle row – source group D. ............................................... D-88

Figure D-42. Modeled 4th Highest MDA8 Ozone for the Base Year (upper left) and Future 

Year (upper right) Scenarios and Their Differences (bottom center). ....................... D-89

Figure D-43. Contributions of Source Groups A (top left), B (top right), C (middle left), D 

(middle right), and E (bottom) to Future Year All-sources 4th Highest MDA8 

(note different color scales in each panel)................................................................. D-91
D-x 2018 Gulf of Mexico Supplemental EIS

Figure D-44. Contributions from (left) Source Group F (natural and non-U.S. emission 

sources including boundary conditions) and (right) Boundary Conditions Only, 

to Future Year All-sources 4th Highest MDA8........................................................... D-92

Figure D-45. Current Year (DVC) and Future Year (DVF) Annual Average PM2.5 Design 

Values from the MATS Unmonitored Area Analysis (top left and top right, 

respectively) and the Difference, DVF – DVC (bottom)............................................. D-98

Figure D-46. Contributions of Source Groups A (top left), B (top right), C (middle left), D 

(middle right), and E (bottom) to the Future Year All-sources Annual Average 

PM2.5 Concentration Based on the MATS Unmonitored Area Analysis (note 

different color scales used in each panel). ................................................................ D-99

Figure D-47. Modeled 8th Highest Daily Average PM2.5 Concentrations for the Base Year 

(top left), Future Year (top right), and the Future – Base Difference (bottom)........ D-101

Figure D-48. Contributions of Source Groups A (top left), B (top right), C (middle left), D 

(middle right), and E (bottom) to the Future Year All-sources 8th Highest Daily 

Average PM2.5 Concentration (note different color scales used in each panel)...... D-102

Figure D-49. Contributions from (left) Source Group F (natural and non-U.S. emission 

sources including boundary conditions) and (right) Boundary Conditions Only to 

Future Year All-sources 8th Highest 24-hour PM2.5 (note use of different color 

scale in each panel). ................................................................................................ D-103

Figure D-50. Modeled Annual Average PM2.5 Concentrations for the Base Year (top left), 

Future Year (top right), and the Future – Base Difference (bottom). ...................... D-104

Figure D-51. Contributions of Source Group A (top left), B (top right), C (middle left), D 

(middle right), and E (bottom) to the Future Year All-sources Annual Average 

PM2.5 Concentration (note use of different color scales in each panel). ................. D-105

Figure D-52. Contributions from (left) Source Group F (natural and non-U.S. emission 

sources including boundary conditions) and (right) Boundary Conditions Only to 

Future Year All-sources Annual Average PM2.5 (note use of different color scale 

in each panel)........................................................................................................... D-106

Figure D-53. Modeled 2nd Highest 24-hour Average PM10 Concentrations for the Base Year 

(top left), Future Year (top right), and the Future – Base Difference (bottom)........ D-107

Figure D-54. Contributions of Source Groups A (top left), B (top right), C (middle left), D 

(middle right), and E (bottom) to the Future Year All-sources 2nd Highest Daily 

Average PM10 Concentration (note use of different color scales in each panel)..... D-108

Figure D-55. Contributions from (left) Source Group F (natural and non-U.S. emission 

sources including boundary conditions) and (right) Boundary Conditions Only to 

Future Year All-sources 2nd Highest Daily Average PM10 Concentration (note 

use of different color scale in each panel). .............................................................. D-109

Figure D-56. Modeled 8th Highest 1-hour NO2 Concentrations for the Base Year (top left), 

Future Year (top right), and the Future – Base Difference (bottom). ...................... D-110

Figure D-57. Contributions of Source Group A (top left), B (top right), C (middle left), D 

(middle right) and E (bottom) to the Future Year All-sources 8th Highest Daily 

Average NO2 Concentrations (note use of different color scales in each panel).... D-111
List of Figures D-xi

Figure D-58. Modeled Annual Average NO2 Concentrations for the Base Year (top left), 

Future Year (top right), and the Future – Base Difference (bottom). ...................... D-112

Figure D-59. Contributions of Source Groups A (top left), B (top right), C (middle left), D 

(middle right), and E (bottom) to the Future Year All-sources Annual Average 

NO2 Concentrations. ................................................................................................ D-113

Figure D-60. Modeled 4th Highest Daily Maximum 1-hour SO2 Concentrations for the Base 

Year (top left), Future Year (top right), and the Future – Base Difference 

(bottom).................................................................................................................... D-115

Figure D-61. Contributions of Source Group A (top left), B (top right), C (middle left), D 

(middle right), and E (bottom) to the Future Year All-sources 4th Highest Daily 

Maximum 1-hour SO2 Concentration (note different color scales used in each 

panel). ...................................................................................................................... D-116

Figure D-62. Modeled Annual 2nd Highest Block 3-hour SO2 Concentrations for the Base 

Year (top left), Future Year (top right), and the Future – Base Difference 

(bottom).................................................................................................................... D-117

Figure D-63. Contributions of Source Group A (top left), B (top right), C (middle left), D 

(middle right), and E (bottom) to the Future Year All-sources 2nd Highest 3-hour 

Block Average SO2 Concentration (note different color scales used in each 

panel). ...................................................................................................................... D-118

Figure D-64. Modeled Annual 2nd Highest Non-overlapping Running 8-hour Average CO 

Concentrations for the Base Year (top left), Future Year (top right), and the 

Future – Base Difference (bottom)........................................................................... D-119

Figure D-65. Modeled Annual 2nd Highest 1-hour Average CO Concentrations for the Base 

Year (top left), Future Year (top right), and the Future – Base Difference 

(bottom).................................................................................................................... D-120

Air Quality: Cumulative and Visibility Impacts D-xiii

ABBREVIATIONS AND ACRONYMS

ANC acid neutralizing capacity

AQRV air quality-related value(s)

BLM Bureau of Land Management (U.S. Department of the Interior)

CAMx Comprehensive Air quality Model with eXtensions

CH4 methane

CO carbon monoxide

CO2 carbon dioxide

DAT Deposition Analysis Threshold

dv deciview

DVB design value for base year

DVC design value for current (base) year

DVF design value for future year

FLAG Federal Land Managers’ Air Quality Related Values Workgroup

GHG greenhouse gas

HAP(s) hazardous air pollutant(s)

hp horsepower

hr hour(s)

IMPROVE Interagency Monitoring of Protected Visual Environments

kg/ha-yr kilogram(s) per hectare - year

km kilometer(s)

m meter(s)

MATS Modeled Attainment Test Software

mcf Thousand cubic feet

MDA8 Annual 4th highest daily maximum running 8-hour average (concentration)

Mm-1 inverse megameters

N2O nitrous oxide

NAAQS National Ambient Air Quality Standards

NO2 nitrogen dioxide 

NOx total oxides of nitrogen

O3 ozone

PM2.5 fine particulate matter (less than 2.5 microns in effective diameter)

PM10 inhalable particulate matter (less than 10 microns in effective diameter)

ppb parts per billion

ppm parts per million

PSD Prevention of Significant Deterioration

RRF Relative Reduction Factor

SO2 sulfur dioxide

tpy tons per year

UAA Unmonitored Area Analysis
D-xiv 2018 Gulf of Mexico Supplemental EIS

USDOI United States Department of the Interior

USEPA United States Environmental Protection Agency

VOC volatile organic compounds

WRF Weather Research and Forecasting model

yr year

μeq/l microequivalent(s) per liter

μg/m3 microgram(s) per cubic meter
Air Quality: Cumulative and Visibility Impacts D-1 

D AIR QUALITY: CUMULATIVE AND VISIBILITY IMPACTS

D.1 INTRODUCTION

The U.S. Department of the Interior’s Bureau of Ocean Energy Management (BOEM) is 

required under the Outer Continental Shelf Lands Act (OCSLA) (43 U.S.C. § 1334(a)(8)) to comply 

with the National Ambient Air Quality Standards (NAAQS) to the extent that Outer Continental Shelf 

(OCS) offshore oil and gas exploration, development, and production sources do not significantly 

affect the air quality of any state. The Gulf of Mexico OCS Region’s area of possible influence 

includes the States of Texas, Louisiana, Mississippi, Alabama, and Florida. BOEM’s Gulf of Mexico 

OCS Region manages the responsible development of oil, gas, and mineral resources for the 

430 million acres in the Western, Central, and Eastern Planning Areas (WPA, CPA, and EPA) on the 

OCS comprising the Gulf of Mexico region, including the areas under moratoria (shown in 

Figure D-1). The Clean Air Act Amendments (CAAA) of 1990 designate air quality authorities in the 

Gulf of Mexico OCS Region, giving BOEM air quality jurisdiction westward of 87°30'W. longitude and 

the U.S. Environmental Protection Agency (USEPA) air quality jurisdiction eastward of 87°30'W. 

longitude. In 2006, oil and gas leasing operations within 125 miles (201 kilometers [km]) off the 

Florida coastline were placed under moratoria until 2022 under the Gulf of Mexico Energy Security 

Act (GOMESA). The GOMESA moratoria area is depicted on Figure D-1. 

Figure D-1. Location of the “Air Quality Modeling in the Gulf of Mexico Region” Study, 

with Class I Areas (purple). 

BOEM published the Gulf of Mexico OCS Oil and Gas Lease Sales: 2017-2022; Gulf of 

Mexico Lease Sales 249, 250, 251, 252, 253, 254, 256, 257, 259, and 261—Final Multisale 

Environmental Impact Statement (2017-2022 GOM Multisale EIS) and has prepared the Gulf of 

Mexico Outer Continental Shelf Lease Sale: Final Supplemental Environmental Impact Statement 
D-2 2018 Gulf of Mexico Supplemental EIS

2018 (2018 GOM Supplemental EIS) for oil and gas resources under its jurisdiction within the Gulf of 

Mexico’s WPA, CPA, and EPA (the Proposed Action).

On August 26, 2014, BOEM contracted with Eastern Research Group, Inc. (ERG) and team 

members Ramboll Environ US Corporation (Ramboll Environ) and Alpine Geophysics, LLC (Alpine) 

to complete a comprehensive air quality modeling study in the Gulf of Mexico OCS region. Under 

BOEM Contract Number M14PC00007, “Air Quality Modeling in the Gulf of Mexico Region,”

photochemical air quality modeling was conducted to assess impacts to nearby states of OCS oil 

and gas exploration, development, and production as required under OCSLA. This assessment was

used by BOEM to disclose potential incremental and cumulative air quality impacts of a proposed 

action in the 2017-2022 GOM Multisale EIS, from which this Supplemental EIS tiers. This Technical 

Support Document (TSD) provides a detailed description of the data, modeling procedures, and 

results of the Air Quality Impact Analysis (AQIA). BOEM used this information to complete its 

analysis of potential impacts of a proposed action on air quality in the 2017-2022 GOM Multisale 

EIS, from which this Supplemental EIS tiers. 

D.1.1 Background on Air Quality Impact Analyses and Thresholds

This analysis examines the potential impacts of the 2017-2022 GOM Multisale EIS scenario, 

from which this Supplemental EIS tiers, with respect to the following: 

• the NAAQS for the criteria pollutants ozone (O3), nitrogen dioxide (NO2), sulfur 

dioxide (SO2), carbon monoxide (CO), fine particulate matter with aerodynamic 

diameter less than 2.5 μm (PM2.5) and fine plus coarse particulate matter with 

aerodynamic diameters less than 10 μm (PM10);

• air quality related values (AQRV), including visibility and acid deposition (sulfur 

and nitrogen) in nearby Class I and sensitive Class II areas (as defined below); 

and

• incremental impacts of Prevention of Significant Deterioration (PSD) pollutants 

(NO2, PM10, PM2.5) with respect to PSD Class I and Class II increments.

Note that the PSD increments are provided here for information purposes, but this analysis 

does not constitute a regulatory PSD increment consumption analysis as would be required for 

major sources subject to the New Source Review (NSR) program requirements of the Clean Air Act.

Results of each impact analysis are compared with applicable “thresholds of concern,” which 

have typically been used in air quality impact evaluations of other Federal actions, including onshore 

oil and gas leasing programs. The applicable comparison thresholds for criteria pollutant impacts 

are the corresponding NAAQS. For acid (i.e., sulfur and nitrogen) deposition impacts, thresholds are 

based on (a) incremental impacts considered sufficiently small as to have no consequential effect on 

the receiving ecosystems, i.e., Deposition Analysis Thresholds, and (b) critical load levels above 

which cumulative ecosystem effects are likely to or have been observed. For visibility impacts, 
Air Quality: Cumulative and Visibility Impacts D-3 

thresholds are based on incremental changes in light extinction below the level at which they would 

be noticeable to the average human observer. Additional information about these various thresholds 

is provided in relevant sections in the remainder of this appendix. 

D.1.1.1 Ambient Air Quality Standards

The USEPA has set NAAQS for six regulated air quality pollutants: ozone, particle pollution 

(PM2.5 and PM10), SO2, NO2, CO, and lead (Pb). After promulgation of a NAAQS, the USEPA 

designates areas that fail to achieve the NAAQS as nonattainment areas (NAAs), and States are 

required to submit State Implementation Plans (SIPs) to the USEPA that contain emission control 

plans and a demonstration that the NAA will achieve the NAAQS by the required date. After an area 

comes into attainment of the NAAQS, the area can be redesignated as a maintenance area and 

must continue to demonstrate compliance with the NAAQS.

In 1997, the USEPA promulgated the first 8-hour ozone NAAQS with a threshold of 

0.08 parts per million (ppm) (84 parts per billion [ppb]). On March 12, 2008, the USEPA 

promulgated a more stringent 0.075 ppm (75 ppb) 8-hour ozone NAAQS. Figure D-2 presents the 

current ozone nonattainment areas in the southeastern U.S. On October 1, 2015, the USEPA 

strengthened the 8-hour NAAQS for ozone to 0.07 ppm (70 ppb). Under this more stringent ozone 

NAAQS, there may be more areas in the southeastern U.S. that will be in nonattainment. The 

USEPA plans to make attainment and nonattainment designations for the revised standards by 

October 2017, with the designations based on 2014-2016 air quality data.

On December 14, 2012, the USEPA revised the PM2.5 primary NAAQS by lowering the 

annual PM2.5 NAAQS threshold from 15.0 micrograms per cubic meter (μg/m3

) to 12.0 μg/m3. The 

USEPA retained the 24-hour PM2.5 primary NAAQS at 35 μg/m3

. The 24-hour course PM NAAQS 

(PM10) was also retained at 150 μg/m3

. 

Figure D-2. Ozone Nonattainment Areas in the Southeastern U.S. (Source: USEPA, 2016; 

https://www3.epa.gov/airquality/greenbook/map8hr_2008.html).
D-4 2018 Gulf of Mexico Supplemental EIS

In February 2010, the USEPA issued a new 1-hour NO2 NAAQS with a threshold of 100 ppb 

(98th percentile daily maximum 1-hour average averaged over 3 years) and a new 1-hour SO2

NAAQS was promulgated in June 2010 with a threshold of 75 ppb (99th percentile daily maximum 

1-hour average averaged over 3 years). No areas are currently in nonattainment of either the 

annual or 1-hour NO2 NAAQS. On July 25, 2013, the USEPA designated 29 areas in 16 states as 

nonattainment for the 1-hour SO2 standard.1

 In June 2016, four additional areas were designated as 

nonattainment (Madison and Williamson Counties in southern Illinois, Anne Arundel-Baltimore 

Counties in Maryland and St. Clair County in Michigan).2

 The USEPA is currently in the process of 

gathering more information needed to complete designation of remaining unclassifiable areas with 

respect to the 1-hour SO2 NAAQS.

A new lead NAAQS was issued in 2008; NAAs for lead are associated with specific industrial 

sources. As oil and gas sources in the Gulf of Mexico OCS region produce negligible amounts of 

lead emissions and to be consistent with onshore oil and gas analysis, which does not include lead, 

lead emissions were calculated but lead was not included in the air quality analysis. The NAAQS for 

carbon monoxide has remained essentially unchanged since it was originally promulgated in 1971. 

As of September 27, 2010, all NAAs for carbon monoxide have been redesignated as maintenance 

areas.

Table D-1 summarizes the nonattainment and maintenance areas in the southeastern U.S. 

SO2 and lead NAAs are focused around specific large industrial sources of SO2 or lead emissions, 

whereas ozone nonattainment areas are more regional in nature, reflecting the formation of ozone 

as a secondary pollutant from emissions of NOx and VOC precursors from a wide range of sources.

Table D-1. Nonattainment and Maintenance Areas in the Southeastern U.S.

State Area 8-hr O3 

(1997)

8-hr O3 

(2008)

SO2

(2010)

CO 

(1971)

Lead 

(2008)

Alabama Troy, AL NAAa

Florida

Tampa, FL NAA

Hillsborough County, FL NAA

Nassau County, FL NAA

Louisiana Baton Rouge, LA Mb NAA

St. Bernard Parish, LA NAA

Texas

Beaumont-Port Arthur, TX M

Houston-GalvestonBrazoria, TX NAA NAA

Frisco, TX NAA a NAA = nonattainment area. b

 M = maintenance area. 

Blank cells indicate the area is in attainment of the NAAQS. 

 

1 https://www.epa.gov/sites/production/files/2016-03/documents/20130725fs.pdf 2 https://www.epa.gov/sites/production/files/2016-06/documents/so2d-r2-area-list.pdf
Air Quality: Cumulative and Visibility Impacts D-5 

D.1.1.2 Air Quality-Related Values

The CAAA designated 156 Class I areas consisting of National Parks and Wilderness Areas 

that are offered special protection for air quality and AQRVs. The Class I areas, compared to Class 

II areas, have lower PSD increments that new sources may not exceed and are protected against 

excessive increases in several AQRVs including visibility impairment, acid (sulfur and nitrogen) 

deposition, and nitrogen eutrophication. The Regional Haze Rule (RHR) specifies a goal of 

achieving “natural” visibility conditions by 2064 in Class I areas, and States must submit RHR SIPs 

that demonstrate progress towards that goal. Figure D-1 displays the locations of the mandatory 

Class I areas (in purple) in the Gulf of Mexico OCS region. 

In addition to the Class I areas described above, Federal Land Management (FLM) agencies 

have designated certain other areas as Class II sensitive areas for tracking PSD increment 

consumption and AQRV impacts. Sensitive Class II areas in the southeastern U.S. study region are 

shown in Figure D-3. 

Figure D-3. Class I and Sensitive Class II Areas in the Study Region. (Note: The South Atlantic 

Planning Area was removed from the Five-Year Program.)
D-6 2018 Gulf of Mexico Supplemental EIS

D.1.2 Overview of Approach

The Comprehensive Air-quality Model with extensions (CAMx; www.camx.com) and 

Community Multiscale Air Quality (CMAQ; https://www.cmascenter.org/cmaq/) Photochemical Grid 

Models (PGMs) were used to simulate the dispersion and chemical transformation of pollutants over 

the Study area. Similar to other air quality models, CAMx/CMAQ require several input datasets, 

including meteorology and an emissions inventory. Figure D-4 presents an overview of how these 

project datasets fit together for the “Air Quality Modeling in the Gulf of Mexico OCS Region” study. 

Preparation of the required meteorological and emissions data is described briefly in this TSD, along 

with references to more detailed reports.

Photochemical modeling was conducted for two emission scenarios:

• a base case scenario using the 2012 base year (BY) emissions inventory 

described in Section D.3 was used to evaluate model performance and to define 

current baseline air quality conditions; and

• a future year development scenario (FY) using an emissions inventory that 

includes potential new sources associated with the 2017-2022 GOM Multisale 

EIS, from which this Supplemental EIS tiers, and projections of emissions to 

2017 for all other sources as described in Section D.3 was used to estimate the 

cumulative and incremental air quality and AQRV impacts of the 2017-2022

GOM Multisale EIS scenario, from which this Supplemental EIS tiers. 

Note that both scenarios used the same meteorological dataset and the same photochemical 

model configuration. 

Figure D-4. Overview of the “Air Quality Modeling in the 

Gulf of Mexico Region” Study Tasks (note 

that the meteorological model takes 

meteorological observations as inputs).
Air Quality: Cumulative and Visibility Impacts D-7 

D.2 METEOROLOGY

Meteorological datasets required to determine the rate that pollutants disperse and react in 

the atmosphere include spatially and temporally varying parameters such as wind speed, wind 

direction, air temperature, and humidity, among others. Sources of meteorological information 

include datasets of measurements gathered at various locations within the Gulf of Mexico OCS 

Region domain. However, the spatial coverage of measurements is insufficient to describe the 

three-dimensional structure of the atmosphere away from measurement locations. Using 

measurement data as inputs, gridded meteorological models capable of simulating the fluid 

dynamics of the atmospheric can be used to estimate meteorological conditions over a complete 

modeling domain—including regions far from measurement sites—in a physically consistent fashion. 

Results of these meteorological models provide the inputs needed to exercise the photochemical 

grid air quality dispersion models used in this Study. For this “Air Quality Modeling in the Gulf of 

Mexico Region” study, the Advanced Research version of the Weather and Research Forecasting 

(WRF) model (version 3.7) was applied over a system of nested modeling grids. Figure D-5 shows 

the WRF modeling grids at horizontal resolutions of 36, 12, and 4 km. All WRF grids were defined 

on a Lambert Conformal Conic (LCC) projection centered at 40°N. latitude, 97°W. longitude with true 

latitudes at 33°N. and 45°N. (the “standard RPO” projection). The outermost domain (outer box) 

with 36-km resolution includes the entire continental U.S. and parts of Canada and Mexico, and 

captures synoptic-scale (storm system-scale) structures in the atmosphere. The inner 

12-km regional grid (d02) covers the southeastern U.S. and is used to ensure that large-scale 

meteorological patterns across the region are adequately represented and to provide boundary 

conditions to the 4-km domain. The 4-km domain (d03) is centered on the coastal areas of the 

southeastern U.S. and over-water portions of the Gulf of Mexico.
D-8 2018 Gulf of Mexico Supplemental EIS

Figure D-5. Meteorological (WRF model) and PGM Modeling Domains 

Including the 36-km Horizontal Grid Resolution CONUS WRF 

Domain (outer box), 12-km Resolution Southeast Regional WRF 

(white) and PGM (blue) Domains (d02), and 4-km Resolution 

Gulf of Mexico OCS Region WRF (black) and PGM (blue) 

Domains (d03).

The WRF ran the 36-, 12- and 4-km grids simultaneously with one-way nesting, meaning that 

meteorological information flows down-scale via boundary conditions introduced from the respective 

coarser to finer grids without feedback from the finer to coarser grids. The WRF modeling domain 

was defined to be slightly larger than the CAMx/CMAQ PGM modeling domains to eliminate 

boundary artifacts in the meteorological fields. Such boundary artifacts occur for both numerical 

reason (the 3:1 grid spacing ratio) and because the imposed boundary conditions require some 

time/space to come into dynamic balance with WRF’s atmospheric equations. All meteorological 

modeling domains, techniques, inputs, vertical resolution, parameters, nudging, physics options, and 

application strategy, along with quantitative and qualitative evaluation procedures and statistical 

benchmarks, are discussed in Appendix B. 

D.3 EMISSIONS

Analysis of the cumulative air quality impacts of the 2017-2022 GOM Multisale EIS scenario

required development of both a contemporary base year emissions inventory for the base case 

analysis and a projected future year inventory that includes emissions from all cumulative sources, 

as well as additional emissions anticipated to occur under the 2017-2022 GOM OCS Multisale EIS 

alternatives in which additional exploratory drilling and construction of new shallow-water and 

deepwater platforms to support oil and gas production would occur. Both the base case and future 
Air Quality: Cumulative and Visibility Impacts D-9 

year cumulative source inventories represent comprehensive compilations of pollutant emissions 

from all human activities, as well as emissions from biogenic and geogenic sources. This 

Supplemental EIS tiers from the 2017-2022 GOM Multisale EIS and uses the scenario and 

alternatives analyzed in the 2017-2022 GOM Multisale EIS.

The scope of the air pollutant emissions inventory for the “Air Quality Modeling in the Gulf of 

Mexico Region” study is defined in terms of: pollutants, representative time periods for the base case 

and future year analysis, geographical domain, and sources to be included.

D.3.1 Pollutants

Pollutants included in the inventories were selected to support analysis of air quality impacts 

in terms of impacts on attainment of NAAQS and on AQRVs, including acid deposition and visibility. 

The selected pollutants are: CO, NOx (which includes NO and NO2 and is stated in terms of 

equivalent mass of NO2), PM2.5, fine plus coarse PM (PM10), SO2, volatile organic compounds 

(VOCs, which are precursors to formation of ozone and organic particulates), and ammonia (NH3, a 

precursor to particulate matter formation). Note that lead emissions were calculated since lead is a 

criteria pollutant, but since oil and gas sources have negligible lead emissions, it was not modeled 

in the air quality analysis.

While the cumulative air quality impact analysis did not focus specifically on air toxics, 

compilation of VOC emissions by source type together with VOC speciation profiles by source type 

provides a mechanism for estimating emissions of individual air toxic species. 

D.3.2 Base Year

In determining the base case (base year) for the “Air Quality Modeling in the Gulf of Mexico 

Region” study emissions inventory, 2011 was initially selected based on data availability. Calendar 

year 2011 emissions data are readily available for most sources from the USEPA’s National 

Emissions Inventory (NEI) (USEPA, 2015a) and BOEM’s Year 2011 Gulfwide Emissions Inventory 

Study (Wilson et al., 2014). However, 2011 was an unusually hot and dry year in the Gulf of Mexico 

OCS region, particularly in Texas, which experienced record heat and dry conditions during the 

summer of 2011 and had a very high incidence of wildfires. Therefore, 2012 was selected as the 

base year as more representative of “typical” conditions in the Gulf of Mexico OCS region. 

D.3.3 Geographical Domain

Modeling domains used for the “Air Quality Modeling in the Gulf of Mexico Region” study

emissions inventory are depicted in Figure D-5. Emissions were spatially allocated over the three 

PGM modeling domains: an outer 36-km horizontal grid resolution domain covering all of the U.S. 

and parts of Mexico and Canada; a regional 12-km resolution domain covering the southeastern 

U.S.; and an inner 4-km domain encompassing the CPA and WPA. The influences of global 

emissions on the study area are accounted for by the use of a global air quality model to specify 

domain boundary conditions. 
D-10 2018 Gulf of Mexico Supplemental EIS

D.3.4 Inventory Sources

A comprehensive inventory of emissions from anthropogenic (i.e., human caused) sources, 

including stationary point and nonpoint area sources located both onshore and offshore, on-road 

motor vehicles, nonroad equipment, locomotives, marine vessels and other offshore sources, and 

airports, were compiled for the “Air Quality Modeling in the Gulf of Mexico Region” study emissions 

inventory. Table D-2 lists the source categories included in the emissions inventory, along with the 

pollutants applicable to each category, and the source type (area source, point source, offshore 

lease block). Note that emissions from non-anthropogenic sources (biogenic and geogenic sources) 

were developed in conjunction with the emissions modeling procedures described in Section D.3.9. 

Table D-2. Gulf of Mexico OCS Region Air Quality Modeling Study Source Categories. 

Group and Source Category CO NOx SO2 VOC Pb PM2.5 PM10 NH3 Source Typea NEI Onshore Sources

Point Sources         P 

Nonpoint Area 

Sources         A 

Onroad Mobile 

Sources        A 

Commercial Marine 

Vessels         P, Ab

Locomotives         P, Ac

Aircraft and Airports         P

Other Nonroad 

Mobile Sources        A 

Offshore Oil and Gas Sources

Platforms in State 

Waters       P 

Platforms in the CPA 

and WPA         P 

Drilling Rigs         LB

Pipelaying Vessels         LB

Support Helicopters        LB

Support Vessels         LB

Survey Vessels         LB

Non-oil and Gas 

Offshore Vessels and 

Activities

Commercial Fishing 

Vessels         LB

Commercial Marine 

Vessels         LB

Louisiana Offshore Oil 

Port         P 

Military Vessels         LB

Recreational Vessels        LB
Air Quality: Cumulative and Visibility Impacts D-11

Group and Source Category CO NOx SO2 VOC Pb PM2.5 PM10 NH3 Source Typea

Vessel Lightering         P

Biogenic and 

Geogenic Sources

Subsurface Oil Seeps  LB

Mud Volcanoes  LB

Onshore Vegetation   A

Wildfires and 

Prescribed Burning        P 

Windblown Dust   A

Lightning  A

Sea Salt Emissions   A

Sources in Mexico 

and Canada

Point Sources        P 

Nonpoint Area 

Sources       A 

Mobile Sources       A 

a A = area source (requires spatial surrogate); P = point source (requires UTM coordinates, stack 

parameters); LB = offshore lease block (requires GIS shape file). b Larger ports and shipping represented as shape files; smaller ports as point sources.

c Rail yards represented as point sources; railway segments as area sources.

D.3.5 Spatial Resolution

The spatial resolution of the emissions inventory is source specific. For example, sources 

such as power plants are identified based on their geographic coordinates (i.e., latitude and 

longitude), while other sources such as nonroad mobile sources (e.g., construction equipment) are 

spatially distributed using surrogates within the county in which they are reported and that are 

typically related to the activity distribution of the category (e.g., construction sites).

The resolution of the geographical area covered by the emissions inventory is based on the 

grid cell size needed for photochemical and dispersion modeling. Furthermore, the photochemical 

model grid resolution is dependent on the grid resolution of the WRF meteorological model output 

used. This is described further in Section D.3.9. 

D.3.6 Temporal Resolution

Emissions for all sources were estimated on an annual basis (i.e., emissions generated 

during 2012). For electric generating units (EGUs), emissions were allocated on a sub-annual basis 

to reflect variations in activity using data from the USEPA. Emissions were allocated on an hourly, 

daily, and seasonal basis during the emissions modeling process (Section D.3.9) using default 

temporal allocation factors provided with the Sparse Matrix Operator Kernel Emissions model 

(SMOKE) emissions model for some sources; other temporal allocations were source specific; and 

profiles were developed and applied within the SMOKE model. 
D-12 2018 Gulf of Mexico Supplemental EIS

D.3.7 Speciation

When applying the photochemical grid modeling, PM emissions were allocated to individual 

PM species as part of the SMOKE emissions processing using PM speciation factors obtained from 

the USEPA’s SPECIATE database for each source category (as defined by the Source Classification 

Code). This resulted in the PM mass being broken into the mass associated with elemental carbon 

(EC), organic aerosol (OA), primary sulfate (SO4) and nitrate (NO3) and other elements, and particlebound VOCs, such as polycyclic aromatic hydrocarbon (PAHs). The model predictions of EC will 

undergo for further analysis and discussed in the “Air Quality Modeling in the Gulf of Mexico Region” 

study final report. 

SMOKE was also used to convert VOC emissions into the photochemical mechanismspecific (e.g., CB05 or CB6r2h) model species used in air quality models as described in 

Section D.3.9. The CB6r2h chemical mechanism used in CAMx also models excess methane 

(ECH4) from local sources that is added to the background methane value (1.75 ppm) in the 

chemical mechanism. The excess methane species is calculated as part of the speciation of the 

VOC emissions that are first adjusted to total organic gases (TOG) before calculating the CB6 

chemical species. Thus, the excess methane species only includes methane emissions from local 

VOC sources (e.g., oil and gas) and will not include methane emissions not associated with VOC 

sources. 

D.3.8 Base Year and Future Year Emission Estimates

Details on the development of the base year and future year emission estimates are 

presented in Appendix C. 

D.3.9 Emissions Processing for Preparation of Model-Ready Emissions

D.3.9.1 Smoke Processing

Anthropogenic emissions inventories discussed in the previous section and other data were 

used to prepare PGM model-ready emission files using the Sparse Matrix Operator Kernel 

Emissions (SMOKE) system version 3.6 and other methods as described below. The inventories 

were processed through SMOKE to develop hourly, gridded, and speciated emissions required for 

input to the PGM models at 36-, 12-, and 4-km grid resolutions. During emissions processing, 

annual emissions inventories were speciated to model species, temporally allocated to hourly 

emissions, and spatially allocated to grid cells. 

The latest Carbon Bond 6 revision 2h (CB6r2h) photochemical mechanism with active local 

methane emissions and halogen chemistry was used for the CAMx modeling, whereas the Carbon 

Bond 5 (CB05) with updated toluene and chlorine chemistry photochemical mechanism was used for 

the CMAQ modeling, and emissions were processed accordingly. CMAQ versions 5.0 and later 

contain a thermodynamic equilibrium aerosol mechanism (ISORRPIA v2) that requires detailed 

speciation of PM2.5. This involves splitting PMFINE into additional elemental components. 
Air Quality: Cumulative and Visibility Impacts D-13

The SMOKE emissions model was used to perform the following tasks: 

• Spatial Allocation: Spatial surrogates contained in the USEPA 2011v6.2 

modeling platform3 were used to spatially distribute emissions to modeling grid 

cells. Spatial surrogates are generated by overlaying the PGM modeling grid on 

maps of geospatial indicators appropriate to each source category (e.g., housing 

units). The Surrogate Tool4

, a component of USEPA’s Spatial Allocator system, 

is used to calculate the fraction of geospatial indicator coverage in each model 

grid cell. 

• Temporal Allocation: Air quality modeling systems, such as CMAQ and CAMx, 

require hourly emissions input data. With the exception of a few source types 

(i.e., Continuous Emissions Monitoring data, biogenic emissions, and some fire 

inventories), most inventory data are estimated in the form of annual or daily 

emissions. SMOKE was used to allocate annual emissions to months and 

across the diurnal cycle to account for seasonal, day-of-week and hour-of-day 

effects. Temporal profiles and SCC cross references from the 2011v6.2 

modeling platform were used to incorporate seasonal and monthly variations into 

the development of the PGM model-ready emissions. 

• Chemical Speciation: The emissions inventories for the “Air Quality Modeling in 

the Gulf of Mexico OCS Region” study included the following pollutants: CO, 

NOx, VOC, NH3, SO2, PM10, and PM2.5. Ramboll Environ used SMOKE to 

convert inventoried VOC emissions into the CB6r2 photochemical mechanism 

model species. Chemical speciation profiles were assigned to inventory sources 

using cross-referencing data that match the profiles and inventory sources using 

country/state/county (FIPS) and source classification codes (SCCs). Ramboll 

Environ used NOx, VOC, and PM speciation profiles from the 2011v6.2 platform 

for SMOKE processing. In the 2011v6.2 platform, USEPA-generated emissions 

for Carbon Bond version 6 revision 2 (CB6r2) chemical mechanism used by 

CAMx. In addition, this platform generates the PM2.5 model species associated 

with the CMAQ Aerosol Module, version 6 (AE6). SMOKE also applied sourcespecific speciation profiles to convert inventoried NOx emissions to NO, NO2, and 

HONO components. After SMOKE processing, Ramboll Environ applied 

necessary species mapping to prepare CMAQ-ready emissions in CB05/AE6 

terms and CAMx-ready emissions in CB6r2/CF terms. Note that CB6r2 

chemistry also models local excess methane (ECH4) above background 

concentrations. Sea salt and halogen emissions from the Gulf of Mexico and 

other ocean portions of the modeling domain were also generated for CAMx as 

described below.

 

3 http://www.epa.gov/ttn/chief/emch/index.html#2011

4 https://www.cmascenter.org/sa-tools/documentation/4.2/html/srgtool/SurrogateToolUserGuide_4_2.pdf
D-14 2018 Gulf of Mexico Supplemental EIS

D.3.9.2 Biogenic Emissions

Biogenic emissions were generated using the MEGAN version 2.1 biogenics model 

developed at the National Center for Atmospheric Research (Guenther et al., 2012; 

Sakulyanontvittaya et al., 2008).

Biogenic emissions depend critically upon landuse/landcover input data. Biogenic VOC and 

NO emissions vary considerably on spatial scales ranging from a few meters to thousands of 

kilometers. The MEGAN model accounts for this variability with high-resolution estimates of 

vegetation type and quantity. The MEGAN landcover variables include total Leaf Area Index (LAI), 

tree fraction, and plant species composition. These variables are determined based primarily on 

satellite observations, such as 2003 1 km2 Moderate Resolution Imaging Spectroradiometer 

(MODIS) and 30-m resolution LANDSAT data (Guenther et al., 2006; Sakulyanontvittaya et al., 

2008). MEGAN driving variables include weather data, LAI, plant functional type (PFT) cover, and 

compound-specific emission factors that are based on plant species composition. All of these 

variables are available at various temporal scales and are provided in a geo-referenced gridded 

database in several formats (e.g., netcdf, ESRI GRID). The MEGAN database has global coverage 

at 30 sec (approximately 1 km) spatial resolution.

The MEGAN model was applied using the specific daily meteorology (e.g., temperature and 

solar radiation) extracted from the 2012 WRF model outputs to generate day-specific biogenic 

emissions for the 2012 calendar year in the 36-, 12-, and 4-km PGM modeling domains.

D.3.9.3 Fire Emissions

Forest fire emissions are highly episodic and very location specific. Using annual average 

fire emissions and temporally and spatially allocating these emissions using generic allocation 

schemes would result in significant inaccuracies. In this modeling study, Ramboll Environ used 

day-specific wild and prescribed fire (together called wildland fires [WLFs]) emission estimates 

developed by the USEPA for calendar year 2012.

5

 The emission estimates are based on the 

SMARTFIRE2 (SF2) framework and the BlueSky models.6

 The USEPA fire inventory was 

processed through SMOKE in separate processing streams for CMAQ and CAMx. The CMAQ 

model-ready emissions were developed in “in-line” point format. The term “in-line” means that the 

plume rise calculations are done inside the CMAQ model instead of being computed by SMOKE. To 

prepare CAMx model-ready emissions using a plume rise algorithm that is consistent with the 

algorithms in CMAQ, plume rise calculation was done in SMOKE and 3-D emissions files were 

prepared that were converted into a CAMx “PTSOURCE” type file where each grid cell centroid 

represents one virtual stack. The cmaq2uam program was used to convert 3-D fire emissions from 

SMOKE into CAMx format. Table D-3 shows total annual criteria air pollutant emissions by fire type 

for all U.S. wildland fires within each of BOEM’s PGM modeling domains.

 

5 ftp://ftp.epa.gov/EmisInventory/fires/

6 http://www.airfire.org/smartfire/
Air Quality: Cumulative and Visibility Impacts D-15

Table D-3. 2012 Fire Criteria Air Pollutant Emissions Summary by Fire Type for BOEM’s 36-, 12-, and 

4-km Domains.

Fire Type 

(SCC) Domain CO (TPY)

NOx

(TPY)

PM10

(TPY)

PM2.5

(TPY)

SO2

(TPY)

VOC 

(TPY)

Wildfires 

(2810001000)

36 km 59,794 613 5,901 5,001 387 14,050

12 km 6,568 74 654 554 44 1,545

4 km 1,087 6 103 87 6 254

Prescribed fires 

(2810015000)

36 km 27,331 391 2,796 2,370 211 6,453

12 km 20,126 308 2,077 1,760 161 4,757

4 km 7,020 58 680 577 41 1,646

Total

36 km 87,125 1,003 8,698 7,371 598 20,503

12 km 26,694 382 2,731 2,314 206 6,302

4 km 8,107 64 783 664 47 1,900

As noted above, the USEPA wildland fires inventory is restricted to fire sources within the 

lower 48 states and thus does not cover the portions of Canada and Mexico lying within the 36-, 12-, 

and 4-km PGM domains. To fill this gap, we used 2012 day-specific Fire INventory from NCAR 

(FINN) for Canada and Mexico. The FINN provides daily, 1-km resolution, global estimates of the 

trace gas and particle emissions from open burning of biomass, which includes wildfire, agricultural 

fires, and prescribed burning exclusive of biofuel combustion and trash burning. Each fire record 

was treated as a point source and emissions were distributed vertically into multiple model layers to 

better represent each fire plume. The day-specific FINN fire emissions in Canada and Mexico were 

processed to develop elevated "point sources" of fire emissions using plume rise estimates as a 

function of fire size based on the Western Regional Air Partnership (WRAP) 2002 fire plume rise 

approach (Mavko and Morris, 2013). The chemical speciation profile for the MODIS fire emissions 

were derived from a study on biomass burning (Karl et al., 2007). 

D.3.9.4 Sea Salt and Halogen Emissions

Ramboll Environ used an emissions processor that integrates published sea spray flux 

algorithms to estimate sea salt PM emissions for input to CAMx. The gridded data for input to the 

sea salt emissions model is a land-water mask file that identifies each modeling domain grid cell as 

open ocean, surf zone, or land. Additional details on the development and evaluation of the sea salt 

emissions processor that was used for the “Air Quality Modeling in the Gulf of Mexico Region” study

are available in the WestJumpAQMS Sea Salt and Lightning memo (Morris et al., 2012). The CAMx 

sea salt emissions processor was used with the 2012 WRF data to generate sea salt emissions for 

the 36-, 12-, and 4-km modeling domains. The sea salt emissions processor has recently been 

updated to also generate emissions for halogen compounds from the ocean (Yarwood et al., 2014). 

Gridded chlorophyll data is obtained from satellite data is used as input and the processor generated 

gridded hourly emissions of chlorine, bromine, and iodine. Halogen chemistry over the ocean 

depletes ozone concentrations near the surface so is especially important in the Gulf of Mexico OCS 

region. 
D-16 2018 Gulf of Mexico Supplemental EIS

The CMAQ model includes inline calculation of sea-salt emissions from the open ocean and 

coastal surf zone so no pre-processing of sea salt emissions is needed. The CMAQ does not treat 

halogen chemistry except for chlorine.

D.3.9.5 Lightning NOx Emissions

The NOx is formed in lightning channels as the heat released by the electrical discharge 

causes the conversion of nitrogen (N2) and oxygen (O2) to NO. Modeling of lightning and its 

emissions is an area of active research. For example, the mechanism for the buildup of electric 

potential within clouds is not well understood, and modeling the production, transport, and fate of 

emissions from lighting is complicated by the fact that the cumulus towers where lightning occurs 

may be sub-grid scale depending on the resolution of the model. Given the importance of lightning 

NOx in the tropospheric NOx budget and in understanding its effect on upper tropospheric ozone and 

OH-, lightning NOx is typically incorporated in global modeling (e.g., Tost et al., 2007; Sauvage et al., 

2007; Emmons et al., 2010) and has also been integrated into many regional modeling studies (e.g., 

Allen et al., 2012; Koo et al., 2010).

For the CMAQ modeling, Ramboll Environ used in-line lightning NOx emissions derived from 

the convective precipitation rate provided in the MCIP files. Since the CMAQ model includes inline 

calculation of lightening NOx emissions, no pre-processing of lightening NOx is needed. The CAMx

model requires pre-calculated lightening emissions for input. To better facilitate comparisons with 

CMAQ, lightening NOx emissions from the CMAQ modeling were output and converted into a format 

suitable for use in CAMx.

D.3.9.6 Windblown Dust

Windblown dust emissions are calculated in-line in the CMAQ model based on wind speed 

and soil moisture parameters passed to CMAQ from the WRF model. Spatially and temporally 

resolved CMAQ windblown dust emissions were output for use in CAMx.

D.3.9.7 QA/QC of Processed Emissions

Emissions were processed by major source category in several different processing 

“streams” to simplify the emissions modeling process and facilitate the QA/QC of results. SMOKE 

includes QA and reporting features to keep track of the adjustments at each step of emissions 

processing and to ensure that data integrity is not compromised. Ramboll Environ carefully 

reviewed the SMOKE log files for significant error messages and ensure that appropriate source 

profiles are being used. In addition, SMOKE output summary reports were reviewed and compared 

with input emission totals.

D.3.9.8 Development of Model-Ready Emissions

Since the “Air Quality Modeling in the Gulf of Mexico Region” study involved application of 

both the CAMx and CMAQ photochemical grid models, the emissions processing procedure 

included development of emissions ready for input to CMAQ, as well as for input to CAMx. Each 
Air Quality: Cumulative and Visibility Impacts D-17

SMOKE processing stream generates a set of pre-merged model-ready emissions in CMAQ input 

format (netCDF). As specified in the chemical speciation section, species mapping was applied to 

convert SMOKE generated model species to the appropriate input for CMAQ. SMOKE modeling 

generated VOC model species for CB6 chemical mechanism, which were converted into CB05 

model species for CMAQ. All pre-merged gridded emissions inputs were merged together to 

generate the final CMAQ-ready, two-dimensional gridded low-level (layer 1) and point source 

emissions inputs. Since CMAQ provides the option to specify point source emissions separately 

from the gridded emissions from other sources, only distributed sources (mobile sources, area 

sources, natural emissions) were merged in developing the CMAQ-ready emissions files.

The CAMx requires two types of emissions files, as described below, for every episode day; 

both of the emission files are UAM-based Fortran binary files.

(1) Surface-level 2D emissions: This file contains two-dimensional gridded fields of 

low-level (i.e., surface) emissions rates for all emitted species to be modeled.

(2) Elevated point source emissions: The elevated point source emissions file 

contains stack parameters and emissions rates for all elevated point sources 

and emitted species to be modeled. 

The merged two-dimensional gridded anthropogenic emissions, which were originally output 

in CMAQ format, were converted into CAMx format using the CMAQ2CAMX program7

. Ramboll 

Environ then merged natural source categories – sea salt, biogenic, fires, lightning and windblown 

dust with the surface-level emissions using the MRGUAM processor to develop CAMx model-ready 

emissions. Ramboll Environ first converted model species from CMAQ to CAMx compatible form 

and then converted CMAQ 2-D and in-line point emissions files to CAMx area-/point-source 

emissions files using the CMAQ2CAMx interface program. The point source emissions files in 

UAM-based binary format were merged together to develop the final CAMx-ready point-source 

emissions. The elevated point source file is independent of the modeling grid because it contains 

horizontal (X, Y) coordinates for each point source, and so one file includes all point sources in the 

12- and 4-km BOEM modeling grids. In addition, CAMx requires separate emissions inputs for 

source groups being tracked in the source apportionment modeling performed for the future year 

scenario.

D.3.9.9 Summary of Processed Emissions

This section presents 2012 base case and future year scenario emissions summaries for the 

BOEM 12- and 4-km domains. The summary is organized by state and by source category.

Table D-4 summarizes NOx, VOC, SO2, and PM2.5 air pollutant emissions in short tons per 

year for the states that border the Gulf of Mexico (i.e., Texas, Louisiana, Alabama, Mississippi, and 

 

7 http://www.camx.com/download/support-software.aspx
D-18 2018 Gulf of Mexico Supplemental EIS

Florida). The summary data are based on 12-km SMOKE processing of 2012 base case and future 

year inventories as described above. With the exception of fugitive dust and biogenic sources, 

emissions are summarized from the SMOKE reports generated by the SMKMRG program. Fugitive 

dust emissions were adjusted after SMOKE processing to account for fugitive dust correction factors 

derived from the Biogenic Emission Landuse Database version 3 (BELD3). Application of these dust 

transport correction factors accounts for suppression of grid-scale dust emissions via deposition on 

proximate vegetation surfaces such as roadside trees and bushes. As noted above, biogenic 

emissions were generated using the MEGAN model outside of SMOKE and so are generated 

directly on the 36/12/4-km grids rather than by state/county. Across the 5-state region, NOx

emissions were projected to go down 4% but VOC emissions are expected to increase by 3%, with 

PM2.5 emissions increasing by 10%. The largest change in emissions between the current and 

future year is for SO2 that is projected to go down by 39%.

Table D-4. 2012 Base Case and Future Year Emissions Summary by State for BOEM’S 12-km Domain 

(only Gulf Coast States: Alabama, Florida, Louisiana, Mississippi, and Texas). 

States 2012 Base Year Future Year Scenario

NOx

(TPY)

PM2.5

(TPY)

SO2

(TPY)

VOC 

(TPY)

NOX

(TPY)

PM2.5

(TPY)

SO2

(TPY)

VOC 

(TPY)

Alabama 210,701 183,321 201,810 1,763,216 178,015 208,531 104,688 1,744,057

Florida 299,738 182,492 144,640 1,754,031 263,778 201,117 127,170 1,690,680

Louisiana 464,962 299,510 203,154 2,030,042 406,421 301,052 127,260 2,007,720

Mississippi 119,430 216,950 57,466 1,622,369 98,334 277,025 32,403 1,610,893

Texas 911,470 683,209 451,018 5,155,944 970,493 739,791 257,073 5,588,049

Figures D-6 through D-9 present stacked bar chart summaries for the 2012 base case 

emissions that show BOEM 12-km domain anthropogenic, fire, and biogenic emissions by source 

category and pollutants for Alabama, Florida, Louisiana, Mississippi, and Texas. Note that these 

emission summaries are only for the states (and State waters) that border the Gulf of Mexico. 

Similarly, Figures D-10 through D-13 present stacked bar chart summaries for the future year 

scenario in short tons per year for the Gulf Coast States. Emission categories used in these 

summaries are defined below:

Source Category Description

ALM Aircraft, locomotive and smaller commercial marine vessels

Fugitive Dust Anthropogenic fugitive dust from paved and unpaved roads, agricultural, 

construction, and mining sources

C3 CMV Commercial marine vessels with Category 3 (C3) main engines

Nonpoint Stationary non-point sources

Area Oil and Gas Non-point oil and gas sector onshore sources

Point Oil and Gas Point oil and gas sector onshore sources

Onroad Motorized vehicles that are normally operated on public roadways (passenger 

cars, motorcycles, minivans, sport-utility vehicles, light-duty trucks, heavy-duty 

trucks, and buses

Nonroad Off-road equipment included in USEPA's nonroad model

EGU Point Electric Generating Unit point sources
Air Quality: Cumulative and Visibility Impacts D-19

Source Category Description

NonEGU Point NEI point sources that are not in the EGU or Point oil and gas sectors 

Fires Agricultural fires, wildfires and prescribed burning

Biogenic Vegetation and soils throughout domain

BOEM OCS Support

Vessel with Action 

(State waters only)

All BOEM OCS oil and gas support vessels and helicopter under the 2017-2022 

GOM Multisale EIS’s "Proposed Action" scenario, from which this Supplemental 

EIS tiers

Figure D-6. BOEM’s 12-km 2012 Base Case NOx Emissions Summary in Tons per Year by Source 

Category and State (Alabama, Florida, Louisiana, Mississippi, and Texas).
D-20 2018 Gulf of Mexico Supplemental EIS

Figure D-7. BOEM 12-km 2012 Base Case VOC Emissions Summary in Tons per Year by Source 

Category and State (Alabama, Florida, Louisiana, Mississippi, and Texas).
Air Quality: Cumulative and Visibility Impacts D-21

Figure D-8. BOEM 12-km 2012 Base Case PM2.5 Emissions Summary in Tons per Year by Source 

Category and State (Alabama, Florida, Louisiana, Mississippi, and Texas).
D-22 2018 Gulf of Mexico Supplemental EIS

Figure D-9. BOEM 12-km 2012 Base Case SO2 Emissions Summary in Tons per Year by Source 

Category and State (Alabama, Florida, Louisiana, Mississippi, and Texas).
Air Quality: Cumulative and Visibility Impacts D-23

Figure D-10. BOEM 12-km Future Year NOx Emissions Summary in Tons per Year by Source Category 

and State (Alabama, Florida, Louisiana, Mississippi, and Texas).
D-24 2018 Gulf of Mexico Supplemental EIS

Figure D-11. BOEM 12-km Future Year VOC Emissions Summary in Tons per Year by Source Category 

and State (Alabama, Florida, Louisiana, Mississippi, and Texas).
Air Quality: Cumulative and Visibility Impacts D-25

Figure D-12. BOEM 12-km Future Year PM2.5 Emissions Summary in Tons per Year by Source Category 

and State (Alabama, Florida, Louisiana, Mississippi, and Texas).
D-26 2018 Gulf of Mexico Supplemental EIS

Figure D-13. BOEM 12-km Future Year SO2 Emissions Summary in Tons per Year by Source Category 

and State (Alabama, Florida, Louisiana, Mississippi, and Texas).

Table D-5 summarizes NOx, VOC, SO2, and PM2.5 emissions within the 4-km domain in short 

tons for the 2012 base year and the 2017 future year scenario, and Table D-6 summarizes the 

changes in emissions between the base and future year scenarios by major source category. 

Table D-5. 2012 Base Case and Future Year Emissions Summary by Source Category for BOEM’s

4-km Domain.

Sectors 2012 Base Year (TPY) Future Year Scenario (TPY)

NOx PM2.5 SO2 VOC NOx PM2.5 SO2 VOC

Fugitive Dust 0 70,526 0 0 0 78,179 0 0

Agricultural 0 0 0 0 0 0 0 0

Fires 50,781 493,750 34,939 1,112,486 50,781 493,750 34,939 1,112,486

ALM 171,436 5,416 2,039 4,896 278,052 7,752 560 7,520

C3 CMV 68,857 3,650 36,339 2,466 108,654 2,666 25,892 4,769

Biogenic 19,015 0 0 3,140,424 19,015 0 0 3,140,424

Nonpoint 81,918 54,561 7,390 296,267 86,014 58,937 3,165 294,728

Nonroad 76,345 6,994 153 112,683 105,272 9,653 159 157,559

Area Oil and 

Gas 69,331 1,991 530 506,972 148,131 5,535 2,134 1,283,385

Onroad 270,364 8,467 1,731 145,061 183,305 7,124 940 106,904
Air Quality: Cumulative and Visibility Impacts D-27

Sectors 2012 Base Year (TPY) Future Year Scenario (TPY)

NOx PM2.5 SO2 VOC NOx PM2.5 SO2 VOC

Non-U.S. 

Fugitive Dust 0 0 0 0 0 0 0 0 

Non-U.S. 

Area 38,832 4,361 719 15,208 35,625 4,429 502 16,787

BOEM 

Gulfwide 186,636 6,337 26,968 7,310 129,814 4,117 31,839 36,109

Non-U.S. 

Onroad 13,894 438 73 6,217 9,097 447 27 4,041

Non-U.S. 

Point (with 

GOM offshore 

platforms)

106,344 2,663 7,795 57,361 32,045 2,181 4,646 11,337

Point Oil and 

Gas 101,530 4,587 50,861 39,192 95,052 4,961 47,086 42,884

EGU Point 137,932 17,943 306,031 3,545 117,518 21,802 136,784 4,371

Non-EGU 

Point 319,924 105,264 271,961 208,773 344,080 120,826 269,191 240,212

BOEM OCS 

Platform No 

Action

0 0 0 0 84,351 837 3,205 54,449

BOEM OCS 

Platform 

w/Action

0 0 0 0 22,973 223 1,037 7,015

BOEM OCS 

Support

Vessel No 

Action

0 0 0 0 234,796 8,296 23,089 8,093

BOEM OCS 

Support

Vessel 

w/Action

0 0 0 0 106,163 9,749 396 10,238

Table D-6. Changes in Emissions between the 2012 Base Case and Future Year Emissions (short tons 

per year) by Source Category for BOEM’s 4-km Domain.

Sector Future Year - Base Year (TPY) Future Year - Base Year (%)

NOx PM2.5 SO2 VOC NOx PM2.5 SO2 VOC

Fugitive Dust 0 7,653 0 0 -- 11% -- --

Agricultural 0 0 0 0 -- -- -- --

Fires 0 0 0 0 0% 0% 0% 0%

ALM 106,616 2,336 (1,479) 2,624 62% 43% -73% 54%

C3 CMV 39,797 (984) (10,447) 2,303 58% -27% -29% 93%

Biogenic 0 0 0 0 0% -- -- 0%

Nonpoint 4,096 4,376 (4,225) (1,539) 5% 8% -57% -1%

Nonroad 28,927 2,659 6 44,876 38% 38% 4% 40%

Area Oil and Gas 78,800 3,544 1,604 776,413 114% 178% 303% 153%

Onroad (87,059) (1,343) (791) (38,157) -32% -16% -46% -26%
D-28 2018 Gulf of Mexico Supplemental EIS

Sector Future Year - Base Year (TPY) Future Year - Base Year (%)

NOx PM2.5 SO2 VOC NOx PM2.5 SO2 VOC

Non-U.S. Fugitive 

Dust 0 0 0 0 -- -- -- --

Non-U.S. Area (3,207) 68 (217) 1,579 -8% 2% -30% 10%

BOEM Gulfwide (56,822) (2,220) 4,871 28,799 -30% -35% 18% 394%

Non-U.S. Onroad (4,797) 9 (46) (2,176) -35% 2% -63% -35%

Non-U.S. Point 

(with GOM 

offshore platforms)

(74,299) (482) (3,149) (46,024) -70% -18% -40% -80%

Point Oil and Gas (6,478) 374 (3,775) 3,692 -6% 8% -7% 9%

EGU Point (20,414) 3,859 (169,247) 826 -15% 22% -55% 23%

Non-EGU Point 24,156 15,562 (2,770) 31,439 8% 15% -1% 15%

Figure D-14 presents spatial plots of future year scenario NOx, VOC, PM2.5, and SO2

emissions in short tons per year within the 4-km domain for the Bureau of Ocean Energy 

Management’s OCS oil and gas production platforms under the 2017-2022 GOM Multisale EIS, from 

which this Supplemental EIS tiers. Note that the deepwater platforms have higher annual emissions 

than the shallow-water platforms. Figure D-15 presents 4-km spatial plots for the same pollutants 

and future year scenario in short tons per year for BOEM’s OCS oil and gas support vessels and 

helicopters under the 2017-2022 GOM Multisale EIS, from which this Supplemental EIS tiers. 

Figure D-16 shows emissions for the Bureau of Ocean Energy Management’s OCS oil and gas 

platforms, support vessels, and helicopters under the No Action alternative, which are the existing 

sources. Figure D-17 shows emissions for all other marine vessel activity in the Gulf of Mexico. 

Figure D-18 shows emissions for all other anthropogenic U.S. sources. 
Air Quality: Cumulative and Visibility Impacts D-29

Figure D-14. Spatial Distribution of (clockwise starting from top left) NOx, VOC, SO2, and PM2.5

Emissions (tons per year) from New OCS Oil and Gas Production Platforms under the 

Proposed Action.
D-30 2018 Gulf of Mexico Supplemental EIS

Figure D-15. Spatial Distribution of Emissions (tons per year) of (clockwise starting from top left) NOx, 

VOC, SO2, and PM2.5 from BOEM’s OCS Additional Oil and Gas Support Vessels and 

Helicopters under the Proposed Action Scenario.
Air Quality: Cumulative and Visibility Impacts D-31

Figure D-16. Spatial Distribution of (clockwise starting from top left) NOx, VOC, SO2, and PM2.5

Emissions (tons per year) from BOEM’s OCS Oil and Gas Platforms, Support Vessels, and 

Helicopters under the No Action Alternative in BOEM’s 4-km Domain.
D-32 2018 Gulf of Mexico Supplemental EIS

Figure D-17. Spatial Distribution of (clockwise starting from top left) NOx, VOC, SO2, and PM2.5

Emissions (tons per year) from All Other Marine Vessel Activity in the Gulf of Mexico under 

the Future Year Scenario in BOEM’s 4-km Domain.
Air Quality: Cumulative and Visibility Impacts D-33

Figure D-18. Spatial Distribution of (clockwise starting from top left) NOx, VOC, SO2, and PM2.5

Emissions (tons per year) from Other Anthropogenic U.S. Sources for the Future Year 

Scenario within BOEM’s 4-km Domain.

D.3.10 Source Apportionment Design

Source apportionment, as applied in CAMx, provides a means of assessing the contributions 

of specified sources or categories of sources to predicted ozone and PM concentrations under the 

air quality conditions being simulated. Source contributions can be calculated for ozone and for PM 

using ozone or PM source apportionment routines included in CAMx. Source apportionment 

analyses were applied to the future year scenario in order to analyze the pre- and postlease OCS oil 

and gas impacts to short-term and annual NAAQS, AQRVs, and PSD increments. BOEM selected a 

set of nine source categories for source apportionment as listed in Table D-7.
D-34 2018 Gulf of Mexico Supplemental EIS

Table D-7. Source Categories for Source Apportionment Calculations.

Category ID Sources

SC1 Fires (U.S., Canada, and Mexico)

SC2 Biogenic and other natural sources (e.g., lighting NOx and sea salt)

SC3

Additional BOEM OCS oil and gas production platforms associated with the 

2017-2022 GOM Multisale EIS scenario, from which this Supplemental EIS 

tiers (w/Action)

SC4

Additional BOEM oil and gas production support vessels and helicopters 

associated with the 2017-2022 GOM Multisale EIS scenario, from which this 

Supplemental EIS tiers (w/Action)

SC5 BOEM’s OCS oil and gas production platforms, support vessels, and 

helicopters under the base case (No Action) alternative

SC6 All other marine vessel activity in the Gulf of Mexico, not associated with OCS 

oil and gas activities

SC7 Other anthropogenic U.S. sources8

SC8 Mexican and Canadian anthropogenic sources9

SC9 Initial Conditions (IC)

SC10 Boundary Conditions (BC)

These source categories aggregate similar sources based on jurisdiction (i.e., sources under 

BOEM’s jurisdiction versus other Federal agencies) and sources beyond direct domestic regulatory 

control (e.g., natural emission sources and foreign sources). Additional OCS oil and gas production 

platforms and additional support vessel and helicopter trips associated with the 2017-2022 GOM 

Multisale EIS are included as a separate source category, thus providing estimates of the impacts of 

these new sources, which are projected to occur under the future year scenario associated with the 

2017-2022 GOM Multisale EIS. Platforms and support vessels and helicopters projected for the 

future year scenario under the base case (No Action) scenario are also included as a separate 

source apportionment category. This Supplemental EIS tiers from the 2017-2022 GOM Multisale 

EIS and uses the scenario and alternatives analyzed in the 2017-2022 GOM Multisale EIS.

Isolating fires and biogenic emissions shows the component of the air quality concentrations 

that are typically beyond the control of Federal agencies and states. Similarly, the Mexican and 

Canadian anthropogenic emissions are beyond the control of U.S. regulators. 

D.4 BASE CASE PHOTOCHEMICAL GRID MODELING

D.4.1 Overview

The CAMx Photochemical Grid Model (PGM) was applied on a set of nested domains with 

horizontal resolutions of 36, 12 and 4 km centered on the Gulf of Mexico OCS Region (Figure D-5). 

For the 2012 base case analysis, CAMx was run with the 2012 base case emissions described in 

Section D.3. Meteorological fields required by CAMx were obtained from the WRF meteorological 

 

8 Includes onshore oil and gas production sources and oil and gas production sources in State waters.

9 Also includes oil and gas production sources.
Air Quality: Cumulative and Visibility Impacts D-35

model results for 2012, which were developed as described in Section D.2. Modeling procedures 

were based on the USEPA’s current and revised draft modeling guidance procedures (USEPA, 2007

and 2014). Additional features of the modeling approach are listed below.

• Anthropogenic and non-anthropogenic model-ready emissions for the 2012 base 

case were developed as described in the emission inventory TSD.

• Photochemical grid modeling was based on CAMx version 6.20 with the Carbon 

Bond 6 revision 2h (CB6r2h) photochemical mechanism, including active excess 

methane emissions and halogen chemistry. 

• Day-specific boundary conditions (BCs) for the lateral boundaries of the 36-km 

modeling domain were based on 2012 GEOS-Chem global chemistry model 

(GCM) output. 

• A model performance evaluation was conducted for the initial 2012 base case 

simulation using all available aerometric data within the modeling domain. Based 

on these initial results, a number of potential issues with model inputs were 

identified and appropriate modifications tested to confirm that the extent to which 

the modifications resolved the identified issues and resulted in improved model 

performance. These initial results and test results are described in Section D.5. 

Revised inputs were then used in the final model simulations and revised model 

performance metrics based on the final model runs were prepared. Results of 

the final model performance evaluation are also presented in Section D.5. 

D.4.2 Model Grid Configuration

The PGM domain configuration is comprised of a system of nested grids with 36-, 12-, and 

4-km horizontal resolution as shown in Figure D-5. Table D-8 provides the modeling grid definitions 

for the WRF and CAMx simulations. Since a large portion of the eastern GOM is under 

Congressional moratoria (GOMESA), the 4-km PGM domain excluded this area to limit the grid 

dimension to allow for a more manageable size for computation efficiency.

Table D-8. Domain Grid Definitions for the WRF and CAMx/CMAQ Modeling. 

Modeling 

Grid

WRF CAMx

Origin1 Coordinates 

(x, y) (km)

Grid Dimension 

(column × row)

Origin1 Coordinates 

(x, y) (km)

Grid Dimension 

(column × row)

36-km grid (-2592, -2304) (164 × 128) (-2736, -2088) (148 × 112)

12-km grid (-1008, -2016) (264 × 186) (-948, -1956) (254 × 176)

4-km grid (-156, -1704) (480 × 210) (-136, -1684) (299 × 200)

1 Southwest corner of each domain grid.

For CAMx, BCs for the 12-km domain were extracted from the 36-km simulation results, and 

the 12-and 4-km grids were modeled using 2-way nesting (allowing interactions between the two 

grids in both directions). Specification of the CAMx vertical domain structure depends on the 
D-36 2018 Gulf of Mexico Supplemental EIS

definition of the WRF vertical layers structure. The WRF simulation was run with 33 vertical layer 

interfaces (which is equivalent to 32 vertical layers) from the surface up to 50 mbar (approximately 

20 km above mean sea level [AMSL]). The WRF model employs a terrain following coordinate 

system called eta (η) coordinate, which is defined by relative pressure differences between layers. 

As shown in Table D-9, the WRF levels are more finely stratified near the surface in an attempt to 

improve simulation of the atmospheric boundary layer structure and processes. A layer collapsing 

scheme is adopted for the CAMx simulations whereby multiple WRF layers are combined into single 

CAMx layers to improve the PGM computational efficiency. Table D-9 also shows the layer 

collapsing from the 32 WRF layers to 28 PGM layers. The mixing heights over the study domain are 

typically below 2 km. Therefore, the WRF modeling layers up to the 16th layer (approximately 2 km) 

are directly mapped to the PGM layers (no layer-collapsing) to better simulate the stable thermal 

stratification of the boundary layer and avoid errors potentially introduced by layer collapsing. Above 

the 20th WRF layer, two WRF layers were combined into a single PGM layer up to the 50 hPa region 

top.

Table D-9. Vertical Layer Interface Definition for WRF Simulations (left-most columns) and the 

Layer-collapsing Scheme for the CAMx/CMAQ Layers (right columns). 

WRF CAMx/CMAQ

Layer 

Interface Eta (η) Pressure (mbar)

Height 

(m)

Thickness 

(m) Layer Layer Top Height (m)

Thickness 

(m)

33 0.0 50 19,594.2 2,090.8 24 19,594.2 3,972.6

32 0.027 76 17,503.4 1,881.8

31 0.06 107 15,621.6 1,754.7 23 15,621.6 3,484.9

30 0.1 145 13,866.9 1,730.1

29 0.15 193 12,136.7 1,412.6 22 12,136.7 2,614.2

28 0.2 240 10,724.1 1,201.6

27 0.25 288 9,522.5 1,050.2 21 9,522.5 1,986.1

26 0.3 335 8,472.3 935.8

25 0.35 383 7,536.4 846 20 7,536.4 1,693.2

24 0.4 430 6,690.5 847.3

23 0.455 482 5,843.2 910.3 19 5,843.2 1,679.1

22 0.52 544 4,932.9 768.8

21 0.58 601 4,164.1 711.8 18 4,164.1 1,375.4

20 0.64 658 3,452.2 663.5

19 0.7 715 2,788.7 418.9 17 2,788.7 821.1

18 0.74 753 2,369.8 402.1

17 0.78 791 1,967.6 386.8 16 1,967.6 386.8

16 0.82 829 1,580.8 280.8 15 1,580.8 280.7

15 0.85 858 1,300.1 273.3 14 1,300.1 273.4

14 0.88 886 1,026.7 178.3 13 1,026.7 178.2

13 0.9 905 848.5 131.7 12 848.5 131.8

12 0.915 919 716.7 130.1 11 716.7 130.1

11 0.93 934 586.6 85.8 10 586.6 85.8

10 0.94 943 500.8 85.1 9 500.8 85.1

9 0.95 953 415.7 84.5 8 415.7 84.5
Air Quality: Cumulative and Visibility Impacts D-37

WRF CAMx/CMAQ

Layer 

Interface Eta (η) Pressure (mbar)

Height 

(m)

Thickness 

(m) Layer Layer Top Height (m)

Thickness 

(m)

8 0.96 962 331.2 83.8 7 331.2 83.8

7 0.97 972 247.4 83.1 6 247.4 83.1

6 0.98 981 164.3 57.8 5 164.3 57.8

5 0.987 988 106.5 41.1 4 106.5 41.1

4 0.992 992 65.4 24.6 3 65.4 24.6

3 0.995 995 40.8 20.4 2 40.8 20.4

2 0.9975 998 20.4 20.4 1 20.4 20.4

1 1.0 1,000 0 -- -- -- --

D.4.3 Meteorology

Given the objectives of the air quality analysis and the availability of full annual WRF 

simulations for 2009 through 2013, the CAMx model was exercised for a full calendar year. The 

decision to model for an entire calendar year rather than just a single season is consistent with the 

need to address ozone, PM2.5, visibility and annual deposition. Given the extremely hot, dry, and 

smoky conditions during 2011, the 2012 calendar year was selected for the base year, base case 

modeling. 

Meteorological inputs for CAMx were generated by processing the WRF outputs using 

appropriate meteorological input preprocessors. The WRFCAMx Version 4.3 was used to translate 

WRF output meteorological fields to daily CAMx meteorological inputs. For a single day, 25 hours of 

meteorology must be present (midnight through midnight, inclusive) as these fields represent hourly 

instantaneous conditions and CAMx internally time-interpolates these fields to each model time step. 

Precipitation fields are not time-interpolated but rather time-accumulated, so cloud/precipitation files 

contain one less hour than other meteorological files (e.g., 24 hours of clouds/precipitation vs. 

25 hours for other meteorology fields). 

Several methodologies are available in WRFCAMx to derive vertical diffusivity (Kv) fields 

from WRF output. For this modeling, a method consistent with the Yonsei University (YSU) bulk 

boundary layer scheme (Hong and Noh, 2006; this is the default option in WRF) was used to 

generate the Kv profile. The lower bound Kv value is set based on the land-use type for each grid 

cell. Another issue is deep cumulus convection, which is difficult to simulate in a grid model because 

of the small horizontal spatial scale of the cumulus tower. Inadequate characterization of this 

convective mixing can cause ozone and precursor species to be overestimated in the boundary

layer. To address this issue, a patch was developed that increases transport of air from the 

planetary boundary layer into the free troposphere and up to the cloud top within cloudy grid cells 

(ENVIRON, 2012). This patch was shown to improve surface layer ozone in a recent modeling 

study in Texas (Kemball-Cook et al., 2015), and thus was also employed in this modeling study. 

The WRFCAMx provides an option to process sub-grid cloud data from WRF fields. 

Selecting the “DIAG” sub-grid cloud method diagnoses sub-grid cloud fields from WRF gridded 
D-38 2018 Gulf of Mexico Supplemental EIS

thermodynamic fields. The DIAG option is generally selected for the 36- and 12-km WRF output 

extraction but not for grid spacing less than about 10 km. However, a recent modeling study showed 

that, without the sub-grid cloud, the 4-km grid produced too much ozone over the Houston area due 

to enhanced photochemistry (Nopmongcol et al., 2014). Therefore, the DIAG option was used for 

the 4-km grid as well as the 36- and 12-km grids. 

D.4.4 Configuration of Model Input Parameters

Configuration of the CAMx model is summarized in Table D-10. Additional key configuration 

selections include the following: 

Chemical Mechanism: Gas phase chemistry using the Carbon Bond 6 revision 2h (CB6r2h) 

photochemical mechanism including active local excess methane emissions and halogen chemistry. 

For particles, CAMx was configured to use the Coarse-Fine (CF) aerosol scheme in which primary 

species are modeled using two static modes (coarse and fine), while all secondary species are 

modeled as fine particles only. 

Photolysis Rates: The CAMx requires a lookup table of photolysis rates as well as gridded 

albedo/haze/ozone/snow as input. Day-specific ozone column data are based on the Total Ozone 

Mapping Spectrometer (TOMS) data measured using the satellite-based Ozone Monitoring 

Instrument (OMI). Albedo is based on land use data, which includes enhanced albedo values when 

snow cover is present. For CAMx, there is an ancillary snow cover input that is based on WRF 

output that overrides the land use-based albedo input to use an enhanced snow cover albedo value. 

The Tropospheric Ultraviolet and Visible (TUV) Radiation Model photolysis rate processor was used. 

The CAMx is configured to use the in-line TUV to adjust for cloud cover and account for the effects 

aerosol loadings have on photolysis rates; this latter effect on photolysis may be especially important 

in adjusting the photolysis rates due to the occurrence of PM concentrations associated with 

emissions from fires. Note that the same photolysis rates are used in the 2012 base case and future 

year scenario model runs. 

Landuse: Landuse fields were generated based on U.S. Geological Survey (USGS) 

Geographic Information Retrieval and Analysis System (GIRAS) data10. The WRF 

estimated snow cover data is used to override the USGS land cover categories when 

snow cover is present.

Meteorological Inputs: The WRF-derived meteorological fields were processed to 

generate CAMx meteorological inputs for the using the WRFCAMx processor. 

Plume in Grid: The subgrid-scale Plum-in-Grid module was not used to avoid 

unacceptably long model run times and given the fact that most sources in the OCS 

are far upwind of the receptor sites of interest. 

 

10 http://pubs.usgs.gov/ds/2006/240/
Air Quality: Cumulative and Visibility Impacts D-39

Boundary Conditions: Boundary conditions (BCs) for the 36-km domain were 

derived from a GEOS-Chem global chemistry model run for 2012 as described bove. 

The BCs for the 12/4-km model runs were based on BCs extracted from the 36-km 

simulations. 

Advection/Diffusion Methods: The piecewise parabolic method (PPM) advection 

solver was used for horizontal transport (Colella and Woodward, 1984), along with 

the spatially varying (Smagorinsky) horizontal diffusion approach. The CAMx used 

K-theory for vertical diffusion, using the CMAQ-like vertical diffusivities from 

WRFCAMx. 

Initial Conditions: The 36-km simulation used default initial conditions (ICs) that 

represent clean remote conditions. A 10-day spin-up period was then used to 

eliminate any significant influence of the ICs. The ICs and BCs for the nested 

(12/4-km) grid simulations were extracted from the parent grid simulation outputs 

with a shorter (3 day) spin-up period.

Boundary Conditions: The lateral boundary conditions (BCs) for the 36-km grid were 

based on results from a GEOS-Chem GCM simulation for year 2012. The 

GEOS2CAMx processor was used to interpolate from the GEOS-Chem horizontal 

and vertical coordinate system to the CAMx coordinate system and to map the 

GEOS-Chem chemical species to the chemical mechanisms being used by CAMx. 

The use of an alternative global model (MOZART-4/GEOS5; available at 

http://www.acd.ucar.edu/wrf-chem/mozart.shtml) as a source for the BCs was 

explored via a test simulation on the 36-km domain with BCs derived from MOZART 

and subsequent comparison of model predictions with observations at rural 

monitoring sites. Results of this comparison indicated slightly worse model 

performance for ozone when using the MOZART BCs as compared to GEOS-Chem 

with mixed results for PM depending on species and monitoring network used for 

evaluation. Based on these results and the fact that, in contrast to GEOS-Chem, 

MOZART does not use day-specific values for dust emissions, resulted in the 

selection of BCs based on the GEOS-Chem model. 

Table D-10. CAMx Model Configuration.

Science Options Configuration Notes

Model Codes CAMx V6.20

Horizontal Grid 36/12/4 km Refer to Section D.2

36-km grid 148 x 112 cells

12-km grid 254 x 176 cells

4-km grid 299 x 200 cells

Vertical Grid

19 vertical layers (layercollapsed from 23 WRF 

layers)

Grid Interaction 36/12 km one-way nesting 

12/4 km two-way nesting
D-40 2018 Gulf of Mexico Supplemental EIS

Science Options Configuration Notes

Initial Conditions Clean initial conditions Use 10-day spin-up for the 36-km grid; 3-day 

spin-up for the nested (12/4 km) grids

Boundary 

Conditions 36 km from GCM simulation GEOS-Chem GCM 2012 output data

Land-use Data Land-use fields based on 

USGS GIRAS data

Photolysis Rate 

Preprocessor TUV V4.8 Clear-sky photolysis rates based on day-specific Total Ozone Mapping Spectrometer (TOMS) data

Chemistry

Gas-phase CB6r2h

Updated isoprene chemistry; heterogeneous 

hydrolysis of organic nitrates; active methane 

chemistry and ECH4 tracer species (Hildebrandt 

Ruiz and Yarwood, 2013); halogen chemistry 

(Yarwood et al., 2014)

Aerosol-phase CF Coarse and fine mode aerosols

Meteorological 

Input 

Preprocessor

WRFCAMx V4.3 Compatible with CAMx V6.20

Diffusion Scheme

Horizontal-grid Explicit horizontal diffusion Spatially varying horizontal diffusivities determined 

based on the methods of Smagorinsky (1963)

Vertical-grid K-theory 1st-order closure

WRFCAMx-derived vertical diffusivities based on 

the Yonsei University (YSU) planetary boundary 

layer (PBL) scheme (Hong and Noh, 2006); landuse dependent minimum diffusivity (minimum Kv = 

0.1 to 1.0 m2

/s) with a cloud Kv patch recently 

developed to address deep convective mixing 

(ENVIRON, 2012)

Deposition Scheme

Dry deposition ZHANG03 Dry deposition scheme by Zhang et al. (2001; 2003)

Wet deposition CAMx-specific formulation Scavenging model for gases and aerosols (Seinfeld 

and Pandis, 1998)

Numerical Solvers

Gas-phase 

chemistry

Euler Backward Iterative 

(EBI) solver Hertel et al., 1993

Horizontal 

advection

Piecewise Parabolic 

Method (PPM) Colella and Woodward, 1984

Vertical 

advection

Implicit scheme w/ vertical 

velocity update 

D.5 MODEL PERFORMANCE EVALUATION

Results from the CAMx base case model runs were compared with available air quality 

observations within the 12/4-km domain to evaluate the ability of the model to accurately reproduce 

observed conditions. Evaluation of CAMx model performance focused on ozone and PM species as 

these predictions play the primary role in the air quality impact analysis. Evaluation of the CAMx 

2012 base case simulation followed USEPA’s current (USEPA, 2007) and new draft (USEPA, 2014) 

PGM modeling guidance. The model performance evaluation (MPE) used the Atmospheric Model 
Air Quality: Cumulative and Visibility Impacts D-41

Evaluation Tool (AMET11), which is the evaluation tool discussed in USEPA’s latest PGM guidance 

(USEPA, 2014). Note that AMET requires that a monitoring site have at least 75% valid data 

capture in order to be used in the MPE, which eliminated observed data from some sites for use in 

the MPE.

D.5.1 Implications of WRF Model Performance on PGM Simulations

The WRF model performance evaluation results are presented in Appendix B. The effects 

of the meteorological model performance on PGM modeled concentrations, visibility and deposition 

is difficult to predict given the multiple effects the meteorological model can have. As described in 

Appendix B, overall WRF model performance was found to be good and significant impediments to 

PGM model performance due to errors in meteorology are not anticipated.

D.5.2 Ambient Data Used In the Model Performance Evaluation

Ozone model performance was evaluated using observed hourly and daily maximum 8-hour 

(DMAX8) ozone concentrations from the USEPA’s Air Qu ality System (AQS12) and the Clean Air 

Status and Trends Network (CASTNet13). Figure D-19 displays the locations of the AQS and 

CASTNet ozone monitoring sites used in the ozone model performance evaluation. Historically, 

CASTNet ozone monitoring sites operated by the U.S. Dept. of the Interior’s National Park Service 

(NPS) were included as part of AQS (i.e., ozone compliance monitors), while those operated by the 

USEPA were not. This has recently been changed and now all CASTNet ozone data are also 

reported in AQS. Thus, CASTNet ozone monitoring sites operated by the NPS are included in both 

the AQS and CASTNet monitoring databases. Apart from this overlap, most AQS monitoring sites 

tend to be more urban-oriented, while CASTNet sites tend to be more rural. Ramboll Environ 

therefore provides separate performance results for the AQS and CASTNet monitoring sites in order 

to provide insight into ozone performance at urban vs. rural sites.

11 https://www.cmascenter.org/help/documentation.cfm?MODEL=amet&VERSION=1.1

12 http://www.epa.gov/ttn/airs/airsaqs/aqsweb/

13 http://java.epa.gov/castnet/
D-42 2018 Gulf of Mexico Supplemental EIS

CASTNET

AQS

Figure D-19. Ozone Monitoring Sites Used in the Model Performance 

Evaluation: CASTNet Sites in the Southeastern U.S. (top) and 

AQS Sites within the 4-km Modeling Domain (bottom) (color 

coding of AQS monitor locations is arbitrary). 

45-

019-0046

A

LC188

I

RL14

S

UM156
Air Quality: Cumulative and Visibility Impacts D-43 

The PM2.5 model performance was evaluated using observed speciated PM data from CSN, 

IMPROVE, and SEARCH monitoring sites in the southeastern U.S. as shown in Figure D-20. This 

was augmented by 24-hour integrated total PM2.5 mass measurements using Federal Reference 

Method (FRM) or equivalent method monitoring sites reporting to the AQS. Most of these FRM sites 

collect samples on a 1-in-3 day schedule, although some collect data every day. The CSN data 

consist of 24-hour integrated particulate samples analyzed for SO4, NO3, NH4, EC, OC, and 

elements using a 1:3 or 1:6 day sampling frequency. The Interagency Monitoring of Protected 

Visual Environments (IMPROVE14) network collects 24-hour average PM2.5 and PM10 mass and 

speciated PM2.5 concentrations (with the exception of ammonium) using a 1:3 day sampling 

frequency. The SEARCH network data consist of hourly and 24-hour PM2.5 mass and speciated 

PM2.5 data (including ammonia). The FRM and CSN monitoring sites tend to be more urban, 

whereas the IMPROVE sites are mostly located at national parks and wilderness areas and so are 

more rural. 

There are additional monitoring sites within the modeling domain that collect hourly PM2.5

and PM10 total mass. However, automated hourly PM measurements are in some cases subject to 

additional measurement artifacts and uncertainties relative to data collected on filters and do not 

include speciated PM measurements. Although MPE results were generated using hourly PM data, 

they are not shown here to maintain consistency with the 24-hour PM NAAQS and the speciated PM 

results, as well as for the sake of brevity. Some hourly PM data, including speciated PM data, are 

available at SEARCH network sites. Comparison of MPE results for model bias and error did not 

show large overall differences between the hourly and daily SEARCH network comparisons. 

 

14 http://vista.cira.colostate.edu/IMPROVE/
D-44 2018 Gulf of Mexico Supplemental EIS

CSN

IMPROVE

SEARCH (source: EPRI, 2011) 

Figure D-20. Speciated PM Monitoring Sites Used in the Model Performance Evaluation: CSN Network 

(top), IMPROVE Network (bottom left), and SEARCH Network (bottom right).

482030002

220330009

220150008 481130069

482011039

120111002

280670002 13215001

1

130210007

130690002

120730012

121030026

120573002

CHAS

1

EVER1

OKEF1

SAMA1

ROMA1
Air Quality: Cumulative and Visibility Impacts D-45

D.5.3 Model Performance Statistics

Statistical performance measures applicable to air quality model evaluation are defined in 

Table D-11. 

Table D-11. Definitions of Model Performance Evaluation Statistical Metrics. 

Statistical Measure Mathematical 

Expression Notes

Ap: Accuracy of paired 

peak

Comparison of the peak observed value (Opeak) 

with the predicted value at same time and location

NME: Normalized Mean 

Error Reported as %

RMSE: Root Mean 

Square Error Reported as %

FE: Fractional Gross 

Error Reported as % and bounded by 0% to 200%

MAGE: Mean Absolute 

Gross Error Reported as concentration (e.g., μg/m3

) 

MNGE: Mean 

Normalized Gross Error Reported as %

MB: Mean Bias Reported as concentration (e.g., μg/m3) 

MNB: Mean Normalized 

Bias Reported as %

FB: Mean 

Fractionalized Bias Reported as %, bounded by -200% to +200%

NMB: Normalized Mean 

Bias Reported as %

For over two decades, ozone model performance for bias and error has been compared 

against the USEPA’s 1991 ozone modeling guidance model performance goals as follows (USEPA, 

1991):

• Mean Normalized Bias (MNB) ≤ ±15%

• Mean Normalized Gross Error (MNGE) ≤ 35%

peak

peak

O

− OP

∑

∑

=

=

−

N

i

i

N

i

ii

O

OP

1

1

( ) 2

1

1

1 2





 



 ∑ − =

N

i

OP ii N

∑= +

− N

i ii

ii

OP

OP

N 1

2

∑=

−

N

i

OP ii N 1

1

∑=

− N

i i

ii

O

OP

N 1

1

∑( ) =

−

N

i

OP ii N 1

1

( ) ∑=

− N

i i

ii

O

OP

N 1

1

∑= 















+

− N

i ii

ii

OP

OP

N 1

2

∑

∑

=

=

−

N

i

i

N

i

ii

O

OP

1

1

)(
D-46 2018 Gulf of Mexico Supplemental EIS

In the USEPA’s 1991 ozone modeling guidance, these performance metrics were for hourly 

ozone concentrations that were consistent with the form of the ozone NAAQS in those days. The 

MNB performance statistic uses hourly predicted and observed ozone concentrations paired by time 

and location and is defined as the difference between the predicted and the observed hourly ozone 

divided by the observed hourly ozone concentrations averaged over all predicted/observed pairs 

within a given region and for a given time period (e.g., by day, month or modeling period). The 

MNGE is defined similarly only it uses the absolute value of the difference between the predicted 

and observed hourly ozone concentrations, so it is an unsigned metric. Note that, because the MNB 

and MNGE performance metrics divide by the observed ozone concentrations, they weigh 

performance for low ozone concentrations highly and can become unstable as the observed ozone 

approaches zero. Consequently, they are no longer recommended. Instead, the Fractional Bias 

and Error (FB/FE) and Normalized Mean Bias and Error (NMB/NME) are the preferred bias and error 

statistical performance measures.

For PM species, a separate set of model performance statistics and performance goals and 

criteria have been developed as part of the regional haze modeling performed by several Regional 

Planning Organizations (RPOs). The USEPA’s modeling guidance notes that PM models might not 

be able to achieve the same level of model performance as ozone models. Indeed, PM2.5 species 

definitions are defined by the measurement technology used to measure them, and different 

measurement technologies can produce very different PM2.5 concentrations. Given this, several 

researchers have developed PM model performance goals and criteria that are less stringent than 

the ozone goals that are shown in Table D-12 (Boylan, 2004; Boylan and Russell, 2006; Morris 

et al., 2009a and 2009b). However, unlike the 1991 ozone model performance goals that use the 

MNB and MNGE performance metrics, the Fractional Bias (FB) and Fractional Error (FE) are 

typically used for PM species with no observed concentration threshold screening. The FB/FE 

differs from the MNB/MNGE in that the difference in the predicted and observed concentrations are 

divided by the average of the predicted and observed values, rather than just the observed value as 

in the MNB/MNGE. This results in the FB being bounded by -200% to +200%, and the FE being 

bounded by 0% to +200%. There are additional statistical performance metrics that evaluate 

correlation, scatter, and normalized mean bias and error (NMB/NME), as shown in Table D-12. 

Table D-12. Ozone and PM Model Performance Goals and Criteria. 

Bias 

(FB/NMB)

Error 

(FE/NME) Comment

≤±15% ≤35% Ozone model performance goal that would be considered very good 

model performance for PM species

≤±30% ≤50% PM model performance Goal, considered good PM performance

≤±60% ≤75% PM model performance Criteria, considered average PM performance

More recently, the USEPA compiled and interpreted the model performance from 69 PGM 

modeling studies in the peer-reviewed literature between 2006 and March 2012 and developed 

recommendations on what should be reported in a model performance evaluation (Simon et al., 
Air Quality: Cumulative and Visibility Impacts D-47

2012). Although these recommendations are not official USEPA guidance, their recommendations 

were integrated in this CAMx MPE.

• The PGM MPE studies should, at a minimum, report the Mean Bias (MB) and 

Error (ME or RMSE), and Normalized Mean Bias (NMB) and Error (NME) and/or 

Fractional Bias (FB) and Error (FE). Both the MNB and FB are symmetric 

around zero with the FB bounded by -200% to +200%.

• Use of the Mean Normalized Bias (MNB) and Gross Error (MNGE) is not 

encouraged because they are skewed toward low observed concentrations and 

can be misinterpreted due to the lack of symmetry around zero.

• The model evaluation statistics should be calculated for the highest resolution 

temporal resolution available (e.g., hourly ozone) and for important regulatory 

averaging times (e.g., daily maximum 8-hour ozone). 

• It is important to report processing steps in the model evaluation and how the 

predicted and observed data were paired and whether data are 

spatially/temporally averaged before the statistics are calculated.

• Predicted values should be taken from the grid cell that contains the monitoring 

site, although bilinear interpolation to the monitoring site point can be used for 

higher resolution modeling (<12 km).

• The PM2.5 should also be evaluated separately for each major component 

species (e.g., SO4, NO3, NH4, EC, OA, and remainder other PM2.5 [OPM2.5]).

• Evaluation should be performed for subsets of the data, including high observed 

concentrations (e.g., ozone >60 ppb) by subregion and by season or month.

• Spatial displays should be used in the model evaluation to evaluate model 

predictions away from the monitoring sites. Time series of predicted and 

observed concentrations at a monitoring site should also be used.

• It is necessary to understand measurement artifacts in order to make meaningful 

interpretation of the model performance evaluation.

D.5.4 Approach

The PGM evaluation focused on ozone, both hourly and daily maximum 8-hour (DMAX8) 

ozone concentrations; total PM2.5 mass and speciated PM2.5 concentrations; gaseous NO2, SO2, and 

CO concentrations; and visibility. The evaluation was performed across all monitoring sites within 

either the southeastern U.S. as shown in the top panel of Figure D-20 (in order to capture the 

regional CSN and IMPROVE network sites) or the 4-km modeling domain (Figure D-5), as well as at 

each individual site on an annual, seasonal (quarterly), and monthly basis. In addition to generating 

numerous statistical performance metrics (refer to Table D-11), graphical representation of model 

performance used three main types of displays. 
D-48 2018 Gulf of Mexico Supplemental EIS

• Soccer Plots of monthly bias and error that are compared against the ozone 

performance goals and the PM performance goals and criteria (refer to 

Table D-11). Monthly soccer plots allow the easy identification of when 

performance goals/criteria are achieved and an evaluation of performance across 

seasons.

• Spatial statistical performance maps that display bias/error on a map at the 

locations of the monitoring sites in order to better understand spatial attributes of 

model performance, along with tabular summaries of statistical performance 

metrics. 

• Time series plots that compare predicted and observed concentrations at a 

monitoring site as a function of days.

• Scatter plots of predicted and observed concentrations.

All performance statistics and displays are performed matching the predicted and observed 

concentrations by time and location using the modeled prediction in the 12/4-km grid cell containing 

the monitoring site. 

The CAMx model performance for PM was evaluated using total PM2.5 mass and speciated 

PM2.5 measurements compared against the PM performance goals and criteria given in Table D-12. 

Note that the PM goals and criteria are not as stringent as those for ozone because the 

measurements themselves, as well as the PM emissions, are much more uncertain and there are 

more processes involved in PM (e.g., dispersion, transformation and deposition of primary PM and 

formation of secondary PM from gaseous precursors). Each PM measurement technique has its 

own artifacts; different measurement technology could produce different observed PM2.5 values that 

differ by as much as 30 percent. The USEPA’s latest PGM modeling guidance includes a section on 

PM measurement artifacts for the monitoring technologies used in routine networks in the U.S. 

(USEPA, 2014). Thus, the PM model performance needs to recognize these measurement 

uncertainties and artifacts and take them into account in the interpretation of model performance, as 

even a “perfect” model may not achieve the PM performance goals and criteria.

The PM10 consists of particles with a mean aerodynamic diameter of 10 microns or less and 

consists of fine (PM2.5, i.e., particles with a diameter of 2.5 microns or less) and coarse (PMC, i.e., 

particles with a diameter between 2.5 and 10 microns) modes. The PM2.5 is composed of the 

following component species:

• sulfate (SO4) that is typically in the form of ammonium sulfate;

• nitrate (NO3) that is typically in the form of ammonium nitrate;

• ammonium (NH4) that is associated with SO4 and NO3; 

• elemental carbon (EC) that is also called black carbon (BC) and light-absorbing 

carbon (LAC);
Air Quality: Cumulative and Visibility Impacts D-49

• organic aerosol (OA) that includes primary (POA) and secondary organic aerosol 

(SOA) and is composed or organic carbon (OC) and other atoms (e.g., oxygen) 

that are adhered to the OC; and

• other PM2.5 (OPM2.5) that is primarily crustal in nature (SOIL) but can also include 

other compounds as well as measurement artifacts.

Model performance statistics were calculated for total PM mass using observations from the 

FRM, CSN, SEARCH, and IMPROVE networks and then evaluated for PM10 and PM2.5 component 

species using data from the CSN, SEARCH, and IMPROVE sites. 

D.5.5 Initial Model Performance Results

Results of initial CAMx runs for the 36- and 12-km domains configured as described in 

Section D.4 were evaluated in terms of the MPE statistics described above to determine if any 

corrections or adjustments to model inputs were needed. In some cases, results from CAMx were 

compared with results from CMAQ to determine potential underlying causes of poor model 

performance. Results of these analyses indicated ozone and PM2.5 over prediction biases, which 

were especially pronounced along the Gulf Coast. Evaluation of results for individual PM 

components showed that much of the PM2.5 over prediction in coastal areas was associated with 

over prediction of sea salt emissions as evidenced by over prediction of sodium (Na) and 

consequently over prediction of nitrate PM as a result of nitrate substitution of chloride ions. This 

was confirmed by sensitivity tests in which sea salt emissions were reduced by a factor of five as 

suggested by regressions of predicted vs. observe Na at IMPROVE and CSN monitoring sites. 

Consistent with results of other modeling studies in the southeastern U.S., the ozone over 

prediction bias was judged to likely be associated at least in part with known over prediction biases 

of ozone over the Gulf of Mexico in many different global models, including GEOS-Chem resulting in 

over estimates of boundary condition ozone and over prediction of isoprene by the MEGAN biogenic 

model (Johnson et al., 2015). A series of sensitivity tests based on CAMx performance over the 

36-km domain with reduced ozone and ozone precursor BCs and reduced sea salt emissions 

confirmed that these modifications resulted in generally improved model performance. To this were 

added two additional modifications: the application of a commonly used adjustment to vertical 

diffusivity coefficients (Kv patch), which has been shown to improve model performance overnight 

and in urban areas (ibid); and a reduction in residential wood combustion (RWC) emissions following 

results of Adelman et al. (2014). A set of final 36-km and 12/4-km model runs were then completed 

with these modifications in place. 

D.5.6 Final Model Performance Results

After making the model input and configuration revisions described in the previous section, 

CAMx was rerun on the 36-km grid and boundary conditions extracted for the 12/4-km, two-way 

nested grid run. Results of the MPE for the 12/4-km grid run are presented in this section. 
D-50 2018 Gulf of Mexico Supplemental EIS

D.5.6.1 Ozone

Model performance results for ozone are summarized in terms of monthly NMB and NME in 

soccer plots for AQS and CASTNet network monitors within the 4-km and 12-km domains in 

Figure D-21. Model performance for nearly all months is within the ±15% NMB and <35% NME 

ozone performance goals listed in Table D-12 (which corresponds to the innermost “goal” box 

shown in the figure), with the principal exceptions being performance during July and August for 

sites in the 4-km domain (note only one CASTNet site – site ALC188, Alabama-Coushatta – is 

located within the 4-km domain). 

Figure D-21. Monthly Normalized Mean Bias and Normalized Mean Error for Daily Maximum 8-hour 

Average Ozone at AQS (left) and CASTNet (right) Monitoring Sites Located within the 

4-km Modeling Domain (top) and the 12-km Domain (bottom).

As illustrated by the threshold exceedance counts in Figure D-22, the ozone season in the 

far South generally follows a bimodal distribution with a pronounced ozone peak in spring and a 

secondary peak in late summer to early fall. There is a noticeable lack of high ozone events during 

July. This seasonal pattern is reproduced in the model results as shown in Figure D-23. Model

performance statistics generated using the AMET tool are summarized by calendar quarter. We 
Air Quality: Cumulative and Visibility Impacts D-51

therefore focus further attention on ozone model performance results for Q2 (April-June) and Q3 

(July-September), as these roughly coincide with the seasonal ozone peaks.

Figure D-22. Fraction of Site-days during Each Month of 2012 with Observed Daily Maximum 

8-hour Ozone Exceeding 60 (top), 65 (middle), or 70 (bottom) ppb Over All Monitoring Sites 

in the 4-km Domain.
D-52 2018 Gulf of Mexico Supplemental EIS

Figure D-23. Observed (blue) and Predicted (red) Monthly Mean Daily Maximum 8-hour Average Ozone 

Over All Sites in the 4-km Modeling Domain.

Ozone model performance for Q2 (April-May) and Q3 (July-September) over sites in the 

4-km domain is illustrated by the scatter plots in Figure D-24. Standard scatter plots are shown in 

the left-hand column and corresponding scatter density plots are shown in the right-hand column. 

Colors in the scatter density plot indicate the fraction of data in each 2 ppb bin, thus revealing the 

data density variations that are otherwise obscured in regions with numerous overlapping points in 

the standard scatter plots. Model performance in Q2 is better than in Q3 primarily due to a lower 

bias (NMB of 5.2% in Q2 as compared to 20.1% in Q3). The scatter density plots show that the Q3 

bias is primarily associated with over prediction of mid- and low-range values with less bias for 

values exceeding 60 ppb. Summaries of ozone performance statistics with a 60 ppb observed 

ozone cutoff applied are further discussed below. 
Air Quality: Cumulative and Visibility Impacts D-53

Figure D-24. Scatter (left) and Scatter Density (right) Plots for Observed vs. Predicted Daily Maximum 

8-hour Ozone in Q2 (top) and Q3 (bottom) for All AQS Monitoring Sites in the 4-km Modeling 

Domain.

The spatial distribution of NMB over the full 12-km domain is shown in Figure D-25. Note 

that these results are based on the 12-km gridded model resolution for all sites shown. The NMB is 

within ±15% at most sites during Q2 but exceeds +15% at most sites along the Gulf Coast and 

throughout the southern tier and southeast Atlantic States in Q3. 
D-54 2018 Gulf of Mexico Supplemental EIS

Figure D-25. Normalized Mean Bias (NMB) for Daily Maximum 8-hour Ozone for Q2 (top) and Q3 

(bottom).

The USEPA recommends that ozone model performance statistics be calculated using a 

60-ppb observed ozone concentration cut-off value (Simon et al., 2012; USEPA 2014). That is, the 

model performance statistics are calculated for all predicted and observed ozone pairs matched by 

time and location for which the observed value is 60 ppb or higher. Table D-13 lists model 

performance summary statistics derived from the 4-km resolution model output for hourly and 8-hour 

daily maximum ozone with no concentration cut-off applied and with cut-offs of 40 or 60 ppb applied 
Air Quality: Cumulative and Visibility Impacts D-55

for Q2 and Q3. Values of NMB and NME exceeding USEPA’s performance goals as listed in 

Table D-12 are highlighted. Biases trend from positive to slightly negative as the threshold 

concentration increases but are always within the Performance Goal for Q2 and also under 

application of the 40- and 60-ppb thresholds in Q3. The NME is always within the USEPA 

Performance Goal except for hourly values in Q3 when no cut-off is applied. 

Table D-13. Model Performance Statistics at Different Observed Ozone Concentration Screening 

Thresholds Based on All Monitoring Sites in the 4-km Domain (shaded cells indicate values 

exceeding USEPA performance goals).

Monitor Site Q2 (April – June) Q3 (July – September)

N NMB (%) NME (%) NMB (%) NME (%)

USEPA Performance Goal ≤±15% ≤35% ≤±15% ≤35%

Ozone Cut-Off Concentrations DMAX8 Ozone

0 6399 5.2 14.1 6217 20.1 25.6

40 4326 2.1 11.6 3218 7.9 15.9

60 1246 -5.7 9.9 375 -9.2 12.6

Ozone Cut-Off Concentrations Hourly Ozone

0 152327 10.9 30.5 149676 30.6 46.7

40 53213 -3.5 16.7 22751 1.5 19.6

60 11229 -10.6 14.7 3498 -13.9 17.8

Time series of observed and predicted daily maximum 8-hour ozone are plotted in 

Figure D-26 for the monitoring site in each county in the Houston-Galveston-Brazoria ozone 

nonattainment area with the highest ozone design values during the 2010-2014 design value periods 

(2010-2012, 2011-2013, 2012-2014): Northwest Harris County site (AQS ID 48-201-0029)15, Manvel 

Croix Park – Brazoria County (AQS ID 48-039-1004), and Galveston 99th St. – Galveston County

(AQS ID 48-167-1034). 

Time series of observed and predicted daily maximum 8-hour ozone are plotted in 

Figure D-27 for two monitoring sites in the Baton Rouge ozone nonattainment area: LSU (AQS ID 

22-033-0003) and Carville (AQS ID 22-047-0012). These sites typically had the highest ozone 

design values in the Baton Rouge area during the 2010-2014 design value periods. 

The time series for the ALC188 (Alabama-Coushatta, Texas) CASTNet site (the only 

CASTNet site in the 4-km domain) are shown in Figure D-28. 

Overall model performance as seen in these time series is good, especially in Q2 and 

especially in the Houston-Galveston area. There is a tendency towards over prediction in Q3 at 

Galveston and more noticeably at the Baton Rouge sites, consistent with the results for all sites 

presented above. 

 

15 This site recorded either the maximum or was within 1 ppb of the maximum ozone design value of all 

sites in Harris County during this period.
D-56 2018 Gulf of Mexico Supplemental EIS

Figure D-26. Time Series of Daily Maximum 8-hour Ozone at Monitoring Sites with Highest Design 

Values in Harris (top), Brazoria (middle), and Galveston (bottom) Counties, Texas, for Q2 

(left) and Q3 (right).

Figure D-27. Time Series of Daily Maximum 8-hour Ozone at Monitoring Sites in the Baton Rouge 

Nonattainment Area: LSU (top) and Carville (bottom) for Q2 (left) and Q3 (right).
Air Quality: Cumulative and Visibility Impacts D-57

Figure D-28. Time Series of Daily Maximum 8-hour Ozone at the ALC188 (Alabama-Coushatta, Texas) 

CASTNet Monitoring Site for Q2 (top) and Q3 (bottom).

D.5.6.2 Particulate Matter

The CAMx model performance for particulate matter (PM) was evaluated for total PM2.5

mass and speciated PM2.5 measurements. The PM performance was compared against the 

performance goals and criteria given in Table D-12. Note that the PM goals and criteria are not as 

stringent as those for ozone because both PM measurements and PM emissions are subject to 

greater uncertainties and PM formation and transformation processes are more complex and difficult 

to model. Each PM measurement technique has its own artifacts; different measurement 

technologies can produce different observed PM2.5 values that differ by as much as 30 percent. The 

USEPA’s latest PGM modeling guidance includes a section on PM measurement artifacts for the 

monitoring technologies used in routine networks in the U.S. (USEPA, 2014). The PM model 

performance results must be evaluated in light of these measurement uncertainties and artifacts as 

even a “perfect” model may not achieve the PM performance goals and criteria relative to the 

imperfect measurements.
D-58 2018 Gulf of Mexico Supplemental EIS

The PM10 consists of particles with a mean aerodynamic diameter of 10 microns or less and 

consists of fine (PM2.5, i.e., particles with a diameter of 2.5 microns or less) and coarse (PMC, i.e., 

particles with diameter between 2.5 and 10 microns) modes. The PM2.5 is composed of the following 

component species:

• sulfate (SO4) that is typically in the form of ammonium sulfate;

• nitrate (NO3) that is typically in the form of ammonium nitrate;

• ammonium (NH4) that is associated with SO4 and NO3; 

• elemental carbon (EC) that is also called black carbon (BC) and light-absorbing 

carbon (LAC);

• organic aerosol (OA) that includes primary (POA) and secondary organic aerosol 

(SOA) and is composed or organic carbon (OC) and other atoms (e.g., oxygen) 

that are adhered to the OC; and

• other PM2.5 (OPM2.5) that is primarily crustal in nature (SOIL) but can also include 

other compounds such as sea salt and may include measurement artifacts as it 

is determined by subtraction of the sum of individual measured species from the 

measured total PM2.5. 

In the following subsections, we first evaluate the CAMx 2012 base case simulation for total 

PM2.5 mass using observations from the FRM, CSN, and IMPROVE monitoring networks and then 

evaluate results for PM10 and PM2.5 component species. There are also numerous hourly PM2.5 and 

PM10 monitoring sites in the region that are also used in the MPE, but results for these are not 

presented here as they may suffer from additional measurement artifacts and uncertainties and are 

not directly comparable to the speciated PM data. 

D.5.6.2.1 Total PM2.5 Mass

Daily total PM2.5 mass is measured at FRM, IMPROVE, and CSN network monitors, and 

hourly PM2.5 is measured at FRM equivalent and non-FRM monitoring sites. Because only three 

CSN sites and no IMPROVE network sites are located within the 4-km CAMx modeling domain, 

some performance statistics are presented here for all monitors within the southeastern U.S. domain 

shown in Figure D-29.

16

 

16 This area corresponds to the high-resolution domain used for the meteorological (WRF) modeling 

described in Section D.2. 
Air Quality: Cumulative and Visibility Impacts D-59

Figure D-29. PM Monitoring Sites in the Southeastern U.S. Domain (triangles – AQS hourly, 

square – IMPROVE, diamond – CSN, circles – AQS FRM daily).

Figure D-30 displays soccer plots of total PM2.5 mass model performance across the FRM, 

CSN, and IMPROVE monitoring networks in the southeastern U.S. domain. Note that these results 

are based on 12-km resolution CAMx output. Also shown in the soccer plots are boxes that 

represent the performance goals for ozone (most inner) and PM (middle), and the PM performance 

criteria (most outer). Performance for the late fall and winter months (October-February) is 

characterized by larger positive NMB and higher NME in each network. This bias is somewhat more 

extreme in the FRM data. Performance results are within or nearly within the PM performance goals 

except for January and October-December for all networks and within the PM performance criteria 

for all months at all networks.

As illustrated in Figure D-31, over prediction in Q4 appears to be primarily associated with 

“other PM2.5” (OPM2.5). Measured OPM likely consists mostly of crustal material (dust) in addition to 

sea salt. Modeled OPM2.5 is defined as the sum of unspeciated PM, crustal material, and sea salt. 

Comparisons of particulate OC and EC performance statistics are presented in Figure D-32. 

The NMB and NME are within the PM performance goals with the exception of July and August EC 

predictions at CSN sites; the over prediction bias is smaller at SEARCH sites. Note that both the 

SEARCH and CSN networks use the Thermal Optical Reflectance (TOR) method to determine OC 

and EC.
D-60 2018 Gulf of Mexico Supplemental EIS

Figure D-30. Soccer Plots of Total PM2.5 Mass Model Performance Across the IMPROVE (top left), CSN 

(top right), SEARCH (bottom left), and FRM Daily (bottom right) Monitoring Networks for 

Sites in the Southeastern U.S. Domain.
Air Quality: Cumulative and Visibility Impacts D-61

Figure D-31. Comparisons of Predicted with Observed Daily Average PM at CSN Network Sites in the 

Southeastern U.S. for Q2 (left) and Q4 (right) for Total PM2.5 (top), Other PM2.5 (middle), 

and Sodium (bottom).
D-62 2018 Gulf of Mexico Supplemental EIS

Figure D-32. Comparisons of Observed vs. redicted OC (top) and EC (bottom) at SEARCH (left) and 

CSN (right) Network Sites in the Southeastern U.S.

D.5.6.2.2 Nitrogen Species (NO2, NOy, and NO3) 

Soccer plot summaries of NMB and NME for nitrogen species are shown in Figures D-33

and D-34 for monitoring sites in the 4-km domain. The NO2, NOy, and particulate NO3 are over 

predicted, especially in the summer months. The NO3 over prediction at coastal sites could be at 

least partially due to over prediction of sea salt emissions as a result of Cl- ion substitution. This is 

consistent with under prediction of particulate Cl at some sites despite over prediction of Na. Nitrate 

deposition biases fall within the performance criteria in all but one month, but errors are large 

indicating a lack of model precision. Measurement uncertainties may also be contributing to the 

large errors. 
Air Quality: Cumulative and Visibility Impacts D-63

N/A

Figure D-33. Monthly Normalized Mean Bias and Normalized Mean Error for Hourly NO2 (top) and Daily 

NOy (bottom) at SEARCH Network Sites (left) and AQS Sites (right) in the 4-km Domain.
D-64 2018 Gulf of Mexico Supplemental EIS

Figure D-34. Monthly Normalized Mean Bias and Normalized Mean Error for NO3 at SEARCH Network 

Monitoring Sites (top left) and AQS Sites (top right) and NO3 Deposition at NADP Sites 

(bottom) in the Southeastern U.S. (Note: Additional months for SEARCH NO3 not shown as 

the NMB and NME exceed the upper axis limits.) 
Air Quality: Cumulative and Visibility Impacts D-65

D.5.6.2.3 Sulfur Species (SO2 and SO4) 

Model performance for hourly SO2 within the 4-km domain is summarized in terms of 

monthly NME and NMB in Figure D-35. The AQS network SO2 monitors are typically cited to 

represent the influence of major utility or industrial SO2 sources and thus may measure short-term 

peaks associated with plume impacts from a discrete source. As a result, the timing, location, and 

magnitudes of peak SO2 concentrations are not well represented within the 4-km grid modeling 

results. In addition, monitors near large ports may be influenced by discrete plumes from passing 

marine vessels, which could be sufficient to cause 1-hour peaks in the monitoring data. Since 

marine vessel emission inputs to the model are temporally averaged, these discrete events cannot 

be properly simulated by the model. Given these characteristics of the SO2 monitoring data, we 

would expect large 1-hour SO2 modeling errors as shown in Figure D-35, although we would not 

necessarily expect the positive normalized mean biases that occur in every month. 

Over prediction bias of hourly SO2 at SEARCH network sites seen in the top row of 

Figure D-35 is in contrast to lower SO4 bias shown in the next row. Good performance for SO4 is 

also evident at CSN network sites. The SO4 deposition is under predicted in most months. Reasons 

for the overall SO2 over prediction bias at sites in the 4-km domain (top row of Figure D-33) are not 

immediately apparent. Examination of results over all sites in the 12-km domain (Figure D-36) 

shows wide variations in bias from site-to-site, including between sites in the 4-km domain, 

suggesting that the lower bias in the network average performance statistics in Figure D-33 are 

partly the result of over- and under-predictions cancelling each other out. 
D-66 2018 Gulf of Mexico Supplemental EIS SO2 SO4 SO4 Deposition

Figure D-35. Monthly Normalized Mean Bias and Normalized Mean Error at Monitoring Sites in the 

4-km Domain for SO2 (top row, AQS sites left panel, SEARCH sites right panel), SO4

(middle row, CSN sites left panel, SEARCH sites right panel), and SO4 Deposition 

Measured at NADP Sites (bottom row). 
Air Quality: Cumulative and Visibility Impacts D-67

Figure D-36. Annual Normalized Mean Bias for Hourly SO2 (based on 12-km resolution CAMx 

results).

D.5.6.2.4 Ammonium (NH4) 

Model performance for particulate ammonium at monitors within the 4-km domain is 

summarized in terms of monthly NME and NMB in Figure D-37. Performance at the two SEARCH 

network sites falls within the PM criteria bounds, but positive biases and large errors are seen at the 

three CSN sites. Note that results based on all sites in the southeastern U.S. domain (at 

12-km resolution) are very similar. The NH4 overestimation bias at the CSN sites is likely due to NO3

over-prediction (Figure D-34), as SO4 is showing biases closer to zero (Figure D-35). Examination 

of individual CSN site results shows acceptable performance at the Houston site (NMB=20%, 

NME=59%), but large positive biases and errors at the Baton Rouge, Louisiana, and Laurel, 

Mississippi, monitors. 
D-68 2018 Gulf of Mexico Supplemental EIS

Figure D-37. Monthly Normalized Mean Bias and Normalized Mean Error for Daily Average NH4 at CSN 

(top) and SEARCH (bottom) Network Sites in the 4-km Modeling Domain.
Air Quality: Cumulative and Visibility Impacts D-69

D.5.6.2.5 Carbon Monoxide (CO)

Model performance for hourly CO within the 4-km domain is summarized in terms of monthly 

NME and NMB in Figure D-38. Hourly CO is under predicted on average at AQS sites where the 

influenced of local mobile sources at sub-grid scales is not adequately resolved by the model’s 4-km 

grid resolution; model performance is better at the SEARCH sites, several of which are in rural 

locations. 

Figure D-38. Monthly Normalized Mean Bias and Normalized Mean Error for Hourly CO at SEARCH 

Network Sites (left) and AQS Sites (right).

D.6 AIR RESOURCE ASSESSMENT APPROACH

D.6.1 Future Year Modeling

The CAMx was run with the Future Year scenario emissions inventory, including emissions 

from the 2017-2022 GOM Multisale EIS sources described in Appendix C; this Supplemental EIS 

tiers from the 2017-2022 GOM Multisale EIS. Model results were post-processed for analysis of air 

quality impacts with respect to the NAAQS and AQRVs; PSD increments were also calculated for 

information purposes. Source apportionment technology was used to provide estimates of source 

group impacts, including impacts of potential new sources associated with the 2017-2022 GOM 

Multisale EIS, from which this Supplemental EIS tiers. Details of the source apportionment and 

post-processing procedures are presented in this section. 

D.6.1.1 Source Apportionment Design

The CAMx Ozone Source Apportionment Technology (OSAT) and Particulate Source 

Apportionment Technology (PSAT) tools were used to obtain the separate air quality, deposition, 

and visibility impacts associated with existing and new (2017-2022 GOM Multisale EIS, from which 

this Supplemental EIS tiers) OCS oil and gas development in the GOM, as well as from other 

emission sources in the GOM and several other source categories as described in Appendix C. 

The CAMx OSAT and PSAT source apportionment tools use reactive tracers that operate in parallel 

to the host PGM to provide air quality and deposition contributions due to user-selected source 
D-70 2018 Gulf of Mexico Supplemental EIS

groups. The CAMx determines the contributions of emissions from each source category to the total 

CAMx model concentrations and depositions during the course of the simulation. A detailed 

description of the CAMx source apportionment tools is available in the CAMx user’s guide 

(ENVIRON, 2014).

The Anthropogenic Precursor Culpability Assessment (APCA) version of the CAMx Ozone 

Source Apportionment Technology (OSAT) was used in the future year scenario modeling. The 

APCA differs from OSAT in that it distinguishes between natural and anthropogenic emissions; when 

ozone is formed due to the interaction of biogenic VOC and anthropogenic NOx under VOC-limited 

conditions, a case OSAT would assign the ozone formed to the biogenic VOC, APCA recognizes 

that biogenic VOC is uncontrollable and re-directs the ozone formed to the anthropogenic NOx. 

Thus, APCA only assigns ozone formed to natural emissions when it is due to natural VOC 

interacting with natural NOx emissions. The APCA requires that the first source category is always 

natural emissions. Like OSAT, APCA uses four reactive tracers to track the ozone contributions of 

each source group: NOx emissions (Ni); VOC emissions (Vi);and ozone formed under VOC-limited 

(O3Vi) and NOx-limited (O3Ni) conditions.

For PM, three families of Particulate Source Apportionment Technology (PSAT) source 

apportionment tracers were used to track contributions of SO4, NO3/NH4, and primary PM that 

require, respectively, 2, 7, and 6 reactive tracers for each family. Thus, combined APCA/PSAT 

source apportionment uses 19 reactive tracers to track the contribution of each source category. 

The Secondary Organic Aerosol (SOA) family of PSAT tracers was not used in the future year 

scenario source apportionment modeling because (1) only a few specific kinds of VOC species form 

SOA (i.e., isoprene, terpenes, sesquiterpenes, and aromatics), and these VOCs are mainly emitted 

by biogenic sources with some aromatic species (e.g., toluene and xylene) emitted by anthropogenic 

sources (e.g., gasoline combustion) (emissions from oil and gas exploration and production has 

negligible aromatic VOC emissions); and (2) the chemistry of SOA is quite complex, involving 

numerous gaseous, semi-volatile, and particulate species so that PSAT requires 21 tracers to track 

the SOA contributions of each source group (Morris et al., 2015). As a result, including SOA would 

more than double the number of reactive tracers, resulting in doubling of the computer time needed 

for the CAMx source apportionment run. 

D.6.1.2 Future Year Source Apportionment Simulation

The CAMx 2017 source apportionment simulation was conducted for 1 January to 

31 December calendar year over the 12-km southeastern U.S. modeling domain shown in 

Figure D-5. The boundary conditions (BCs) defining inflow concentrations around the lateral 

boundaries of the 12-km domain were obtained from a future year CAMx simulation of the 36-km 

continental U.S. (CONUS) domain shown in Figure D-5. Both the 36-km and 12-km simulations 

made use of the same 2012 WRF meteorology and model configuration used in the base case 

simulation. 
Air Quality: Cumulative and Visibility Impacts D-71

D.6.2 Post-Processing of Future Year Source Apportionment Modeling Results

D.6.2.1 Overview

The CAMx future year scenario model and ozone and particulate matter source 

apportionment modeling outputs were post-processed for comparison against the NAAQS and PSD 

concentration increments listed in Table D-14 and other thresholds of concern (TOC), as discussed 

below. For analyzing NAAQS and AQRV impacts at Class I and sensitive Class II areas, the 

Thresholds of Concern (TOCs) used were as defined by the Federal Land Manager (FLM) that 

manages each Class I/II area as prescribed in the June 23, 2011, Memorandum of Understanding 

(MOU) for evaluating onshore oil and gas AQ/AQRV impacts.17

The CAMx source apportionment results for individual source categories were used to 

evaluate the incremental impacts of each of a set of hierarchical source groups as defined in 

Table D-15. Note that Source Group B represents all new direct emissions associated with the 

2017-2022 GOM Multisale EIS, from which this Supplemental EIS tiers, and Source Group C 

represents these sources in addition to all existing OCS platforms and associated support vessel 

and aircraft activity. Also note that Source Group E includes Source Groups A-D, along with all 

other anthropogenic sources, but excludes fires and other natural sources (biogenics, lightning NOx, 

sea salt) and the contribution of boundary conditions. 

Table D-14. NAAQS and PSD Increments. 

Pollutant Pollutant/Averaging 

Time NAAQS PSD Class I Increment1

PSD Class II 

Increment1

CO 1-hour2 35 ppm 40,000 μg/m3 -- --

CO 8-hour2 9 ppm 10,000 μg/m3 -- --

NO2 1-hour3 100 ppb 188 μg/m3 -- --

NO2 Annual4 53 ppb 100 μg/m3 2.5 μg/m3 25 μg/m3

O3 8-hour5 0.070 ppm 137 μg/m3 -- --

PM10 24-hour6 150 μg/m3 8 μg/m3 30 μg/m3

PM10 Annual7 -- 4 μg/m3 17 μg/m3

PM2.5 24-hour8 35 μg/m3 2 μg/m3 9 μg/m3

PM2.5 Annual9 12 μg/m3 1 μg/m3 4 μg/m3

SO2 1-hour10 75 ppb 196 μg/m3

SO2 3-hour11 0.5 ppm 1,300 μg/m3 25 μg/m3 512 μg/m3

SO2 24-hour -- 5 μg/m3 91 μg/m3

SO2 Annual4 -- 2 μg/m3 20 μg/m3

 

17 http://www.epa.gov/compliance/resources/policies/nepa/air-quality-analyses-mou-2011.pdf
D-72 2018 Gulf of Mexico Supplemental EIS

Pollutant Pollutant/Averaging 

Time NAAQS PSD Class I Increment1

PSD Class II 

Increment1

1 The PSD demonstrations serve information purposes only and do not constitute a regulatory PSD 

increment consumption analysis.

2 No more than one exceedance per calendar year. 3

 98th percentile, averaged over 3 years. 4 Annual mean not to be exceeded. 5 Fourth-highest daily maximum 8-hour ozone concentrations in a year, averaged over 3 years, 

NAAQS promulgated December 28, 2015. 6 Not to be exceeded more than once per calendar year on average over 3 years. 7

 3-year average of the arithmetic means over a calendar year. 8

 98th percentile, averaged over 3 years. 9 Annual mean, averaged over 3 years, NAAQS promulgated December 14, 2012. 10 99th percentile of daily maximum 1-hour concentrations in a year, averaged over 3 years. 11 No more than one exceedance per calendar year (secondary NAAQS). 

Table D-15. Source Group for Incremental Impacts Analysis. 

Source 

Group 

Included Source 

Categoriesa Comment

A SC3

New oil and gas platform sources under the 2017-2022 GOM 

Multisale EIS scenario, from which this Supplemental EIS tiers

(w/Action)

B SC3, SC4 Add support vessels and aircraft associated with new platform 

sources (w/Action)

C SC3, SC4, SC5

Add oil and gas platforms and associated support vessels and 

aircraft under the No Action alternative (existing base case 

sources)

D SC3, SC4, SC5, 

SC6

Add all other marine vessel activity in the GOM, not associated 

with OCS oil and gas activities

E SC3, SC4, SC5, 

SC6, SC7, SC8 Add all other U.S. and non-U.S. anthropogenic sources

F SC1, SC2, SC8, 

SC10

Natural and non-U.S. sources (including U.S. sources outside of 

the 12-km modeling domain) a Refer to Table D-6.

D.6.2.2 Comparison against NAAQS

The CAMx future year scenario predicted total concentrations from all emission sources 

were post-processed for comparison to the applicable NAAQS, as listed in Table D-14, in two 

different ways. First, the CAMx predictions were compared directly against each NAAQS. This is 

referred to as the “absolute” prediction comparison. These absolute prediction comparisons may be 

misleading in cases in which the model exhibits significant prediction bias. In recognition of this, 

USEPA modeling guidance (USEPA, 2007 and 2014) recommends using the model in a relative 

sense when projecting future year ozone, PM2.5, and regional haze levels; and the USEPA has 

developed the Modeled Attainment Test Software (MATS; Abt., 2014) for making such future year 

projections. This approach uses the ratio of future year to current year modeling results to develop 

Relative Response Factors (RRFs) that are applied to observed current year Design Values 

(abbreviated as either DVC or DVB) to make future year Design Value (DVF) projections (i.e., 
Air Quality: Cumulative and Visibility Impacts D-73

DVF = DVC x RRF). The MATS was applied to the prediction of both ozone and PM2.5 DVFs. The 

MATS was also used for assessing the cumulative visibility impacts at IMPROVE monitoring sites in 

the 12-km domain, as discussed in more detail below.

D.6.2.3 Impacts at Class I and Sensitive Class II Areas

The incremental AQ/AQRV contributions associated with emissions from each source group 

listed in Table D-15 were calculated at the Class I and sensitive Class II areas shown in 

Figure D-39. The selected areas include all Class I and sensitive Class II areas within the 

4-km modeling domain plus additional Class I areas within the 12-km modeling domain. 

Table D-16 lists those areas that are located in Gulf Coast or nearby states and thus are of 

greatest interest to this analysis. Refer to Section D.7.3.1 for a complete list of all areas shown in 

Figure D-39, along with the results of the visibility analyses. 

Receptors for each Class I and sensitive Class II area were defined based on the spatial 

extent of the Class I/II area defined using shapefiles obtained from the applicable Federal Land 

Management Agency. A GIS was used to determine the set of grid cells overlapping each area by at 

least 5%. Model results for the identified grid cells were then used to represent predicted ambient 

concentrations and deposition in each area. 

Figure D-39. Class I and Sensitive Class II Areas for Which Incremental AQ/AQRV Impacts 

Were Calculated.
D-74 2018 Gulf of Mexico Supplemental EIS

Table D-16. Class I and Sensitive Class II Areas in Gulf Coast and Nearby States.

Type Name Agency1 State Modeling Domain

Class I Breton Wilderness FWS LA 4 km

Class II Breton NWR FWS LA 4 km

Class II Gulf Islands NS NPS MS, FL 4 km

Class II Padre Island NS NPS TX 4 km

Class I Bradwell Bay FS FL 12 km

Class I St. Marks FWS FL 12 km

Class I Chassahowitzka FWS FL 12 km

Class I Everglades NP NPS FL 12 km

Class I Okefenokee FWS GA 12 km

Class I Wolf Island FWS GA 12 km

Class I Cohutta FS GA 12 km

Class I Sipsey FS AL 12 km

Class I Guadalupe Mountains NPS TX 12 km

Class I Big Bend NPS TX 12 km

Class I Wichita Mountains FWS OK 12 km

Class I Caney Creek FS AR 12 km

Class I Upper Buffalo FS AR 12 km

1 FWS = U.S. Dept. of the Interior, Fish and Wildlife Service; FS = U.S. Dept. of Agriculture, 

Forest Service; NPS = U.S. Dept. of the Interior, National Park Service; NS = National 

Seashore; NWR = National Wildlife Refuge.

D.6.2.3.1 Incremental Visibility Impacts

Visibility impacts were calculated for each source group using incremental concentrations as 

quantified by the CAMx PSAT tool. Changes in light extinction from CAMx model concentration 

increments due to emissions from each source group were calculated for each day at grid cells 

representing each Class I and sensitive Class II area. The FLAG (2010) procedures were used in 

the incremental visibility assessment analysis.

The visibility evaluation metric used in this analysis is based on the haze index (HI), which is 

measured in deciview (dv) units and is defined as follows:

HI = 10 × ln[bext/10]

Where bext is the atmospheric light extinction measured in inverse megameters (Mm-1) and is 

calculated primarily from atmospheric concentrations of particulates.

A more intuitive measure of haze is visual range (VR), which is defined as the distance at 

which a large black object just disappears from view, and is measured in km. Visual range is related 

to bext by the formula VR = 3912/bext. The advantage of using the HI rather than VR is that a given 

change in HI is approximately associated with the same degree of perceived change in visibility 

regardless of the baseline conditions whereas small changes in VR are much more noticeable under 

clean conditions as compared to hazy conditions.
Air Quality: Cumulative and Visibility Impacts D-75

The incremental concentrations due to each source group were added to natural background 

extinction in the extinction equation (bext) and the difference between the haze index with the source 

group concentrations included and the haze index based solely on natural background 

concentrations is calculated. This quantity is the change in haze index, which is referred to as “delta 

deciview” (Δdv):

Δdv = 10 × ln[bext(SC+background)/10] - 10 × ln[bext(background)/10]

Δdv = 10 × ln[bext(SC+background)/bext(background)] 

Here bext(SCi+background) refers to atmospheric light extinction due to impacts from the source 

category plus background concentrations, and bext(background) refers to atmospheric light extinction due 

to natural background concentrations only.

For each source group, the estimated visibility degradation at the Class I areas and sensitive 

Class II areas due to the source group are presented in terms of the number of days that exceed a 

threshold change in deciview (Δdv) relative to background conditions. The number of days with a 

deciview greater than 0.5 and 1.0 are reported.

IMPROVE Reconstructed Mass Extinction Equations

The FLAG (2010) procedures for evaluating visibility impacts at Class I areas use the revised 

IMPROVE reconstructed mass extinction equation to convert PM species in μg/m3 to light extinction 

(bext) in inverse megameters (Mm-1) as follows:

bext = bSO4 + bNO3 + bEC + bOCM + bSoil + bPMC+ bSeaSalt+ bRayleigh+ bNO2

where

bSO4 = 2.2 × fS(RH) × [Small Sulfate] + 4.8 × fL(RH) × [Large Sulfate]

bNO3 = 2.4 × fS(RH) × [Small Nitrate] + 5.1 × fL(RH) × [Large Nitrate]

bOCM = 2.8 × [Small Organic Mass] + 6.1 × [Large Organic Mass]

bEC = 10 × [Elemental Carbon]

bSoil = 1 × [Fine Soil]

bCM = 0.6 × [Coarse Mass]

bSeaSalt = 1.7 × fSS(RH) × [Sea Salt]

bRayleigh = Rayleigh Scattering (Site-specific)

bNO2 = 0.33 × [NO2 (ppb)] {or as: 0.1755 × [NO2 (μg/m3

)]}.

f(RH) are relative humidity adjustment factors that account for the fact that sulfate, nitrate, 

and sea salt aerosols are hygroscopic and are more effective at scattering solar radiation at higher 
D-76 2018 Gulf of Mexico Supplemental EIS

relative humidity. FLAG (2010) recommends using monthly average f(RH) values rather than the 

hourly averages recommended in the previous FLAG (2000) guidance document in order to 

moderate the effects of extreme weather events on the visibility results. 

The revised IMPROVE equation treats “large sulfate” and “small sulfate” separately because 

large and small aerosols affect an incoming beam of light differently. However, the IMPROVE 

measurements do not separately measure large and small sulfate; they measure only the total PM2.5

sulfate. Similarly, CAMx writes out a single concentration of particulate sulfate for each grid cell. 

Part of the definition of the new IMPROVE equation is a procedure for calculating the large and 

small sulfate contributions based on the magnitude of the model output sulfate concentrations; the 

procedure is documented in FLAG (2010).18 The sulfate concentration magnitude is used as a 

surrogate for distinguishing between large and small sulfate concentrations. For a given grid cell, 

the large and small sulfate contributions are calculated from the model output sulfate (which is the 

“Total Sulfate” referred to in the FLAG [2010] guidance) as

For Total Sulfate <20 μg/m3

: 

[Large Sulfate] = ([Total Sulfate] / 20 μg/m3

) × [Total Sulfate]

For Total Sulfate ≥20 μg/m3

: 

[Large Sulfate] = [Total Sulfate]

For all values of Total Sulfate:

[Small Sulfate] = [Total Sulfate] – [Large Sulfate]

The procedure is identical for nitrate and organic mass. 

The PSAT source apportionment algorithm does not separately track NO2 concentrations but 

instead tracks total reactive nitrogen (RGN) that consists of NO, NO2, and other reactive nitrogen 

compounds (e.g., N2O5, HONO, etc.). Thus, for each hour and each grid cell representing a 

Class I/II area, a source group’s incremental PSAT RGN contribution is converted to NO2 by 

multiplying by the total (all emissions) CAMx model NO2/RGN concentration ratio. Note that this 

same procedure is also used for contributions to NO2 concentrations.

Although sodium and particulate chloride are treated in the CAMx core model, these species 

are not carried in the CAMx PSAT tool. This does not affect the calculations of visibility impacts from 

individual source groups other than impacts from the natural source category (SC2). 

 

18 http://www.nature.nps.gov/air/Pubs/pdf/flag/FLAG_2010.pdf
Air Quality: Cumulative and Visibility Impacts D-77

Predicted daily average modeled concentrations due to each source group for receptor grid 

cells containing Class I and sensitive Class II areas were processed using the revised IMPROVE 

reconstructed mass extinction equation FLAG (2010) to obtain changes in bext at each sensitive 

receptor area that are converted to deciview and reported.

Annual average natural conditions for each Class I area were obtained from Table 6 in FLAG 

(2010) and monthly relative humidity factors for each Class I area from Tables 7-9 in FLAG (2010). 

The ∆dv was calculated for each grid cell that overlaps a Class I or sensitive Class II area by 5% or 

more for each day of the annual CAMx run. The highest ∆dv across all grid cells overlapping a 

Class I or sensitive Class II area by at least 5% was selected to represent the daily value at that 

Class I/II area. Visibility impacts due to emissions from each source group that exceed the 0.5 and 

1.0 Δdv thresholds are noted. 

Cumulative Visibility Impacts

The cumulative visibility impacts of the 2017-2022 GOM Multisale EIS, from which this 

Supplemental EIS tiers, were assessed following the recommendations from the U.S. Dept. of the 

Interior’s Fish and Wildlife Service (FWS) and NPS (USDOI, FWS and USDOI, NPS, official 

communication, 2012). This approach is based on an abbreviated regional haze rule method that 

estimates the future year visibility at Class I and sensitive Class II areas for the average of the Worst 

20% (W20%) and Best 20% (B20%) visibility days with and without the effects of the source group 

emissions on visibility impairment. The cumulative visibility impacts used CAMx model output from 

the 2012 Base Year and 2017 Future Year emissions scenarios in conjunction with monitoring data 

to produce cumulative visibility impacts at each Class I and sensitive Class II area. The USEPA’s 

Modeled Attainment Test Software (MATS19) was used to make the 2017 visibility projections for the 

W20% and B20% days. The basic steps in the recommended cumulative visibility method are as 

follows (USDOI, FWS and USDOI, NPS, official communication, 2012):

(1) Calculate the observed average 2012 current year cumulative visibility impact 

using the haze index (HI, in deciviews) at each Class I area using 

representative IMPROVE measurement data to determine the 20% of days with 

the worst and 20% of days with the best visibility. The MATS is designed to use 

5 years of monitoring data centered on the base case year, which for 2012 

would include 2010-2014. However, MATS only includes IMPROVE monitoring 

data through 2012, so the 2008-2012 5-year period was used to define the 

visibility baseline conditions in the MATS visibility projections. 

(2) Estimate the relative response factors (RRFs) for each component of PM2.5 and 

for coarse mass (CM) corresponding to the new IMPROVE visibility algorithm 

using the CAMx 2012 and 2017 model output. The RRFs are based on the

 

19 http://www.epa.gov/ttn/scram/modelingapps_mats.htm
D-78 2018 Gulf of Mexico Supplemental EIS

average concentrations across a 3 x 3 array of 4-km grid cells centered on the 

IMPROVE monitoring site location.

(3) Using the RRFs and ambient data, calculate 2017 future year daily 

concentration data for the B20% and W20% days using the CAMx 2012 base 

case and 2017 standard model concentration estimates and PSAT source 

apportionment modeling results two ways: 

(a) 2017 Total Emissions: Use total 2017 CAMx concentration results due to all 

emissions;

(b) 2017 No Cumulative Emissions: Use PSAT source apportionment results to 

eliminate contributions of PM concentrations associated with each source 

group. 

(4) Use the information in Step 3 to calculate the average 2017 visibility for the 20% 

Best and 20% Worst visibility days and the 2017 emissions.

(5) Assess the average differences in cumulative visibility impacts for each source 

group and also compare with the future and current observed Baseline visibility 

conditions.

Because of the need for IMPROVE observations, monitoring data from nearby Class I areas 

were used to represent areas without any IMPROVE monitors. 

D.6.2.3.2 Sulfur and Nitrogen Deposition

The CAMx-predicted wet and dry fluxes of sulfur- and nitrogen-containing species were 

processed to estimate total annual sulfur and nitrogen deposition values at each Class I and 

sensitive Class II area. The maximum annual sulfur and nitrogen deposition values from any grid 

cell that intersects a Class I receptor area was used to represent deposition for that area, in addition 

to the average annual deposition values of all grid cells that represent a Class I receptor area. 

Although the convention in the past has been to report just the maximum deposition in any receptor 

in a Class I/II area, since deposition relates to the total amount deposited across an entire 

watershed, the average metric may be considered a more relevant parameter for evaluating 

potential environmental effects. Maximum and average predicted sulfur and nitrogen deposition 

impacts are reported separately for each source group. 

Nitrogen deposition impacts were calculated by taking the sum of the nitrogen contained in 

the fluxes of all nitrogen species modeled by the CAMx PSAT source apportionment tool. The 

CAMx species used in the nitrogen deposition flux calculation are reactive gaseous nitrate species, 

RGN (NO, NO2, NO3 radical, HONO, N2O5), TPN (PAN, PANX, PNA), organic nitrates (NTR), 

particulate nitrate formed from primary emissions plus secondarily formed particulate nitrate (NO3), 

gaseous nitric acid (HNO3), gaseous ammonia (NH3), and particulate ammonium (NH4). The CAMx 

species used in the sulfur deposition calculation are primarily sulfur dioxide emissions (SO2) and 

particulate sulfate ion from primary emissions plus secondarily formed sulfate (SO4). 
Air Quality: Cumulative and Visibility Impacts D-79

FLAG (2010) recommends that applicable sources assess impacts of nitrogen and sulfur 

deposition at Class I areas. This guidance recognizes the importance of establishing critical 

deposition loading values (“critical loads”) for each specific Class I area as these critical loads are 

completely dependent on local atmospheric, aquatic, and terrestrial conditions and chemistry. 

Critical load thresholds are essentially a level of atmospheric pollutant deposition below which 

negative ecosystem effects are not likely to occur. FLAG (2010) does not include any critical load 

levels for specific Class I areas and refers to site-specific critical load information on FLM websites 

for each area of concern. This guidance does, however recommend the use of deposition analysis 

thresholds (DATs 20) developed by the NPS and FWS. The DATs represent screening level values 

for nitrogen and sulfur deposition for individual projects with deposition impacts below the DATS 

considered negligible. A DAT of 0.005 kilograms per hectare per year (kg/ha/yr) for both nitrogen 

and sulfur deposition has been established for both nitrogen and sulfur deposition in western Class I 

areas. A DAT of 0.01 kg/ha/yr has been established for both nitrogen and sulfur deposition for areas 

in the eastern U.S. As a screening analysis, results for Source Group B (new platforms and 

associated support vessels and aircraft associated with the 2017-2022 GOM Multisale EIS scenario, 

from which this Supplemental EIS tiers) were compared to the DATs. Comparison of deposition 

impacts from cumulative sources to the DAT is not appropriate.

For the 2012 base case and the combined source groups and total 2012 and future year 

emissions, the annual nitrogen and sulfur deposition were compared against critical load values 

established by the Federal Land Management agencies. Published nitrogen critical load values for 

areas managed by the NPS21 include minimum critical loads of 3 kg/ha/yr at the Gulf Islands 

National Seashore, as well as at Guadalupe Mountains and Big Bend, and 5 kg/ha/yr at Padre Island

National Seashore and Everglades National Park. These values represent the minimum of the 

critical loads for each biological community type (i.e., forests, herbaceous plants, lichen, mycorrhizal 

fungi, and nitrate leaching). Nitrogen and sulfur critical load values for areas managed by the U.S. 

Dept. of Agriculture’s Forest Service (USFS) include 5 kg/ha/yr at Bradwell Bay, Cohutta, Sipsey, 

Caney Creek and Upper Buffalo. The 5 kg/ha/yr critical load value for these areas applies

separately to nitrogen and to sulfur deposition. As no separate critical load values for sulfur are 

available from the NPS areas, the sulfur critical loads were set equal to the values for nitrogen. No 

published critical load values were found for areas managed by the FWS; critical loads for these 

areas were set by reference to the NPS and USFS critical loads based on proximity and similarity of 

ecoregion types. Using this approach, both nitrogen and sulfur critical loads for the Breton 

Wilderness, Breton National Wildlife Refuge, St. Marks, Chassahowitzka, Okefenoke, and Wolf 

Island were set at 3 kg/ha/yr based on the Gulf Islands National Seashore value for Eastern 

Temperate Forests. The values for Wichita Mountains was set at 5 kg/ha/yr based on the NPS’ 

Chickasaw National Recreation Area Great Plains ecoregion value.

 

20 http://www.nature.nps.gov/air/Pubs/pdf/flag/nsDATGuidance.pdf

21 http://www.nature.nps.gov/air/Studies/criticalloads/Ecoregions/index.cfm
D-80 2018 Gulf of Mexico Supplemental EIS

D.6.2.4 PSD Increments

The maximum contribution of new oil and gas emissions in the Gulf of Mexico under the 

2017-2022 GOM Multisale EIS scenario were reported for each Class I and sensitive Class II area 

and were compared against the PSD increments given in Table D-14. Under the Clean Air Act, a 

PSD increment consumption analysis requires major stationary sources subject to PSD review to 

demonstrate that emission increases from the proposed source, in conjunction with all other 

emissions increases or reductions in the impacted area (typically within 50 kilometers), will not cause 

or contribute to concentrations of air pollutants that exceed PSD increments. The PSD increments 

have been established for NOx, SO2, and PM in Class I and Class II areas. Actions to be authorized 

by BOEM under the 2017-2022 GOM Multisale EIS scenario do not typically constitute major 

stationary sources and do not typically trigger PSD permits or review. However, a comparison of 

ambient concentrations from an accumulation of new oil and gas sources within the entire study area 

to PSD increments at specific Class I and Class II areas is included in this analysis for information 

purposes. This information is presented to aid State agencies in tracking the potential minor source 

increment consumption and to aid Federal Land Managers or Tribal governments responsible for

protecting air resources in Class I areas. This Supplemental EIS tiers from the 2017-2022 GOM 

Multisale EIS and uses the scenario and alternatives analyzed in the 2017-2022 GOM Multisale EIS.

D.7 AIR RESOURCE ASSESSMENT RESULTS

D.7.1 NAAQS Impacts

Future year CAMx modeling results were used to examine future air quality relative to the 

NAAQS and the individual contributions of each source group relative to the NAAQS. For the ozone 

and PM2.5 NAAQS, comparisons are presented both in terms of the “absolute” CAMx results and in 

terms of using the base case and future year CAMx results in a relative sense to scale the observed 

base (“current” or “base”) year design value (DVC or DVB) to obtain the projected future year design 

value (DVF) as recommended by the USEPA’s modeling guideline (USEPA, 2007 and 2014) and as 

described in Section D.6.2.2.

D.7.1.1 Ozone NAAQS Analysis using Relative Model Results

The USEPA’s Model Attainment Test Software (MATS) was used to make future year ozone 

DVF projections using the CAMx 2012 base case and future year scenario modeling results as 

described in Section D.6.2.2. The MATS was used to make DVF projections at the locations of 

ambient air monitoring sites as well as throughout the 4-km modeling domain using the MATS 

Unmonitored Area Analysis (UAA) procedures.

D.7.1.1.1 Monitored Ozone Design Value Projections using MATS

The MATS results for the future year ozone design values (DVFs) at individual ambient air 

monitoring sites in the 4-km domain are listed in Tables D-17 and D-18. Updated MATS data files 
Air Quality: Cumulative and Visibility Impacts D-81

containing ozone design values up through 2014 were obtained from the USEPA.22 To make future 

year projections, MATS starts with a current year design value (DVC) that is based on an average of 

three ozone design values from the 5-year period centered on the base case modeling year, which 

was 2012 for this analysis. Thus, MATS DVCs are based on ozone design values from the 

2010-2012, 2011-2013, and 2012-2014 periods. The MATS makes ozone DVF projections using the 

changes in daily maximum 8-hour ozone concentrations near (3 x 3 array of 4-km grid cells) a 

monitor using the ratio of future year to current year modeling results to scale the observed DVCs. 

These modeled derived scaling factors are called Relative Response Factors (RRFs; DVF = DVC x 

RRF). The RRFs are based on the 10 highest modeled ozone days above a threshold ozone 

concentration. A lower bound observed ozone threshold value of 50 ppb was used in MATS.

Of the 74 monitors with valid DVCs as calculated by MATS, 39 have DVCs exceeding the 

NAAQS (70 ppb). The DVFs are less than DVCs at all 74 sites. A total of 22 sites have predicted 

DVFs exceeding the MATS, all of which are among the sites with DVCs above the NAAQS. 

Contributions of each source group to the DVFs were calculated as the difference between 

the DVF calculated from the CAMx results with all sources included and a revised DVF calculated 

after first subtracting out the individual hourly contributions of each source group in the future year 

model run. These source group contributions are tabulated in Table D-18. The maximum 

contribution from Source Group A (new platforms associated with the 2017-2022 GOM Multisale EIS 

scenario, from which this Supplemental EIS tiers) is 0.5 ppb. The maximum contribution from 

Source Group B (new platforms and support vessels and helicopters associated with the 2017-2022 

GOM Multisale EIS scenario, from which this Supplemental EIS tiers) is 5.1 ppb.

Five sites in Texas and one in Louisiana were identified where the contribution of the new 

platforms and associated support vessels and aircraft under the 2017-2022 GOM Multisale EIS 

(from which this Supplemental EIS tiers) scenario (Source Group B) to the DVF was enough to push 

the DVF from just below the 70-ppb NAAQS (with Source Group B contributions removed) to just 

above the NAAQS when all sources were included (Table D-19). In each case, the “contribution” 

from Source Group B is less than 5 ppb. At each of these sites, the DVCs are all also greater than 

70 ppb as noted above. At the Galveston, Texas, monitor, the 0.3-ppb contribution of Source Group 

A (new platforms) alone was sufficient to bump the future year design value from just below the 

NAAQS to just above the NAAQS (recall comparisons to the 70 ppb NAAQS are made after 

truncating design values to the nearest ppb). 

For the ozone impacts assessment, please note that the states will not designate under the 

2015 ozone standard of 70 ppb until 2017, with the earliest attainment date of March 2021 for 

marginal areas. For this impacts assessment, the non-OCS source emissions were based on the 

USEPA’s 2017 emission projections, with a future modeled year of 2017 and compared to the 

70-ppb standard. This assessment is assuming the standard will be attained way before the actual 

 

22 https://www3.epa.gov/scram001/modelingapps_mats.htm
D-82 2018 Gulf of Mexico Supplemental EIS

attainment date, but it wanted to give maximum OCS oil and gas impacts under the new 70 ppb 

ozone standard. 

Table D-17. Current Year (DVC) and Future Year (DVF) Ozone Design Values at Ambient Air Monitoring 

Sites within the 4-km Modeling Domain from MATS.

Site ID Site Name State County DVC DVF

10030010 FAIRHOPE HIGH SCHOOL, FAIRHOPE, 

ALABAMA AL Baldwin County 68 66.2

10970003 CHICKASAW, MOBILE CO., ALABAMA AL Mobile County 67.3 64.4

10972005 BAY RD. ,MOBILE AL. AL Mobile County 72 66.5

120330004 ELLYSON INDUSTRIAL PARK-COPTER 

ROAD FL Escambia County 67.7 65.1

120330018 NAS PENSACOLA FL Escambia County 70.7 68.1

120910002 720 Lovejoy Rd FL Okaloosa County 65 62.9

121130015 1500 WOODLAWN WAY FL Santa Rosa County 69.3 67.4

220050004 11153 Kling Road LA Ascension Parish 71.3 67.8

220190002 HIGHWAY 27 AND HIGHWAY 108 LA Calcasieu Parish 70.7 68.9

220190008 2646 John Stine Road LA Calcasieu Parish 66.7 64.7

220190009 2284 Paul Bellow Road LA Calcasieu Parish 70 67.3

220330003 EAST END OF ASTER LANE LA East Baton Rouge 

Parish 75.3 71.3

220330009 1061-A Leesville Ave LA East Baton Rouge 

Parish 72.3 68.3

220330013 11245 Port Hudson-Pride Rd. Zachary, La LA East Baton Rouge 

Parish 69 65.1

220470009 65180 Belleview Road LA Iberville Parish 70.3 64.6

220470012 HIGHWAY 171, CARVILLE LA Iberville Parish 73.3 68.6

220511001 West Temple Pl LA Jefferson Parish 71.3 68.4

220550007 646 Cajundome LA Lafayette Parish 69.7 67.2

220570004 Nicholls University Farm Highway 1 LA Lafourche Parish 71 65.7

220630002 Highway 16, French Settlement LA Livingston Parish 72.3 68.6

220710012 Corner of Florida Ave & Orleans Ave LA Orleans Parish 68.3 66.5

220770001 TED DAVIS RESIDENCE. HIGHWAY 415 LA Pointe Coupee Parish 74 68.2

220870004 4101 Mistrot Dr. Meraux, LA 70075 LA St. Bernard Parish 68 64.4

220890003 1 RIVER PARK DRIVE LA St. Charles Parish 67.7 65.2

220930002 ST. JAMES COURTHOUSE, HWY 44 @ 

CANAPELLA LA St. James Parish 66.3 62.7

220950002 Anthony F. Monica Street LA St. John the Baptist 

Parish 72 69.3

221030002 1421 Hwy 22 W, Madison Ville, LA 70447 LA St. Tammany Parish 72.3 68.7

221210001 1005 Northwest Drive, Port Allen LA West Baton Rouge 

Parish 68 63.8

280450003 400 Baltic St MS Hancock County 66.3 63.4

280470008 47 Maple Street MS Harrison County 70.3 67

280590006 Hospital Road at Co. Health Dept. MS Jackson County 71.3 69.2

480271047 1605 Stone Tree Drive TX Bell County 73.7 71

80.3 78
Air Quality: Cumulative and Visibility Impacts D-83

Site ID Site Name State County DVC DVF

68.7 66.3

480391004 4503 CROIX PKWY TX Brazoria County 85 81.9

480391016 109 B BRAZORIA HWY 332 WEST TX Brazoria County 69.3 66.8

480610006 344 PORTER DRIVE TX Cameron County 60.7 59.2

69.3 66.6

481671034 9511 AVENUE V 1⁄2 TX Galveston County 75.3 71.2

482010024 4510 1/2 ALDINE MAIL RD. TX Harris County 76.7 75.1

482010026 1405 SHELDON ROAD TX Harris County 73 71.2

482010029 16822 KITZMAN TX Harris County 80 76.3

482010046 7330 1/2 NORTH WAYSIDE TX Harris County 73.7 71.6

482010047 4401 1/2 LANG RD. TX Harris County 77 74.8

482010051 13826 1/2 CROQUET TX Harris County 78.7 76.3

482010055 6400 BISSONNET STREET TX Harris County 78.7 77.3

482010062 9726 1/2 MONROE TX Harris County 76.7 74.4

482010066 3333 1/2 HWY 6 SOUTH TX Harris County 77.7 75.2

482010070 5425 POLK AVE., SUITE H TX Harris County 75 73.5

482010416 7421 PARK PLACE BLVD TX Harris County 77.3 74.8

482011015 1001 B LYNCHBURG ROAD TX Harris County 71 68.5

482011034 1262 1/2 MAE DRIVE TX Harris County 78 76.1

482011035 9525 CLINTON DR TX Harris County 74.7 72.5

482011039 4514 1/2 DURANT ST. TX Harris County 78.3 75.5

482011050 4522 PARK RD. TX Harris County 76.3 74

482151048 325 Golf Course Road TX Hidalgo County 60 58.1

482450009 1086 Vermont Avenue TX Jefferson County 71.7 68.3

482450011 800 EL VISTA ROAD & 53RD STREET TX Jefferson County 74 70.5

482450022 12552 SECOND ST. TX Jefferson County 70.3 66.7

482450101 6019 MECHANIC TX Jefferson County 75 72.3

482450102 SETRPC 43 Jefferson Co Airport TX Jefferson County 67 64.4

482450628 UNAVAILABLE TX Jefferson County 69.3 66.4

482451035 Seattle Street TX Jefferson County 69.3 66.9

483091037 4472 MAZANEC RD TX McLennan County 71.7 69.1

483390078 9472 A HWY 1484 TX Montgomery County 78 74.7

483491051 Corsicana Airport TX Navarro County 70 68.2

483550025 CORPUS CHRISTI STATE SCHOOL, 

AIRPORT RD TX Nueces County 69.3 68.2

483550026 9860 LA BRANCH TX Nueces County 68.3 66.2

483611001 2700 AUSTIN AVE TX Orange County 69.3 66.5

483611100 INTERSECTION OF TX HWYS 62 AND 

12 TX Orange County 68 65.4

484530014 3724 NORTH HILLS DR, AUSTIN, TX 

78758 TX Travis County 71.3 67.7

484530020 12200 LIME CREEK RD. TX Travis County 71.7 68.3

484690003 106 MOCKINGBIRD LANE TX Victoria County 66.3 64.2
D-84 2018 Gulf of Mexico Supplemental EIS

Table D-18. Ozone Current (DVC) and Future Year (DVF) Design Values and Reduction in DVF with 

Contributions from Individual Source Groups Removed.

Site ID State County DVC DVF

Change in DVF with Source Group 

Removed

A B C D E

10030010 AL Baldwin County 68 66.2 0.3 4.7 7.6 10.2 42.6

10970003 AL Mobile County 67.3 64.4 0.1 2.3 4.2 5.4 40.4

10972005 AL Mobile County 72 66.5 0.1 5.1 6.5 7.9 44.7

120330004 FL Escambia County 67.7 65.1 0.3 1.7 5.5 7.4 35.3

120330018 FL Escambia County 70.7 68.1 0.4 2.6 7.8 10.9 37.8

120910002 FL Okaloosa County 65 62.9 0.3 1.9 6.8 9.5 33.6

121130015 FL Santa Rosa County 69.3 67.4 0.5 2.6 9.3 12.7 37.5

220050004 LA Ascension Parish 71.3 67.8 0.1 0.7 2.3 3.1 43.6

220190002 LA Calcasieu Parish 70.7 68.9 0.3 2 5.6 8.3 40.2

220190008 LA Calcasieu Parish 66.7 64.7 0.3 1.7 4.9 7.4 37.6

220190009 LA Calcasieu Parish 70 67.3 0.2 1.5 4.2 6.1 39.7

220330003 LA East Baton Rouge Parish 75.3 71.3 0.1 0.7 2.9 4 45.3

220330009 LA East Baton Rouge Parish 72.3 68.3 0.1 0.7 2.6 3.7 43.3

220330013 LA East Baton Rouge Parish 69 65.1 0.2 1 3.2 4.3 37.7

220470009 LA Iberville Parish 70.3 64.6 0 0.2 0.7 1.1 41.2

220470012 LA Iberville Parish 73.3 68.6 0 0.4 1.5 2.3 45.7

220511001 LA Jefferson Parish 71.3 68.4 0.2 1.1 5.2 6.6 45

220550007 LA Lafayette Parish 69.7 67.2 0.1 1.4 3.9 5.6 41.5

220570004 LA Lafourche Parish 71 65.7 0.1 0.5 1.7 2.4 40.9

220630002 LA Livingston Parish 72.3 68.6 0.2 1.1 4.4 5.9 44.3

220710012 LA Orleans Parish 68.3 66.5 0.3 1.2 5.6 7.2 42

220770001 LA Pointe Coupee Parish 74 68.2 0 0.5 2 3 43.7

220870004 LA St. Bernard Parish 68 64.4 0.3 1.4 5.5 7.2 41.1

220890003 LA St. Charles Parish 67.7 65.2 0.1 0.6 2.5 3.3 44.7

220930002 LA St. James Parish 66.3 62.7 0.1 0.5 2.1 2.8 39.3

220950002 LA St. John the Baptist 

Parish 72 69.3 0.2 0.9 3.5 4.6 45

221030002 LA St. Tammany Parish 72.3 68.7 0.2 1.1 5 6.3 42.9

221210001 LA West Baton Rouge 

Parish 68 63.8 0 0.5 2.1 2.9 40

280450003 MS Hancock County 66.3 63.4 0.3 1.6 5.3 7.1 39.9

280470008 MS Harrison County 70.3 67 0.3 1.7 5.4 7.3 42.8

280590006 MS Jackson County 71.3 69.2 0.4 2.7 6 8.9 44.9

480271047 TX Bell County 73.7 71 0 0.3 0.9 1.2 30.9

80.3 78 0 0.3 0.9 1.3 37.4

68.7 66.3 0.1 0.2 0.4 0.5 33.3

480391004 TX Brazoria County 85 81.9 0.1 0.7 2.2 3.1 49.5

480391016 TX Brazoria County 69.3 66.8 0.2 1.3 3.4 4.8 37.4

480610006 TX Cameron County 60.7 59.2 0.2 1.3 2.4 3.3 29.2

69.3 66.6 0.1 0.2 0.3 0.5 29.9

481671034 TX Galveston County 75.3 71.2 0.3 3.6 9.8 16.6 46.6
Air Quality: Cumulative and Visibility Impacts D-85

Site ID State County DVC DVF

Change in DVF with Source Group 

Removed

A B C D E

482010024 TX Harris County 76.7 75.1 0.2 1.5 4 5.8 44.1

482010026 TX Harris County 73 71.2 0.2 1.6 4.1 5.9 42.1

482010029 TX Harris County 80 76.3 0.2 1.1 3.3 4.8 48

482010046 TX Harris County 73.7 71.6 0.2 1.3 3.4 4.9 41.8

482010047 TX Harris County 77 74.8 0.2 1 3 4.4 46

482010051 TX Harris County 78.7 76.3 0.1 0.6 1.8 2.6 47.5

482010055 TX Harris County 78.7 77.3 0.1 0.8 2.4 3.3 46.9

482010062 TX Harris County 76.7 74.4 0.2 1.1 3.1 4.5 45.3

482010066 TX Harris County 77.7 75.2 0.1 0.7 2.2 3.1 46.6

482010070 TX Harris County 75 73.5 0.2 1.3 3.4 5 41.6

482010416 TX Harris County 77.3 74.8 0.1 1.2 3.1 4.6 44.4

482011015 TX Harris County 71 68.5 0.2 1.3 3.7 5.3 39.1

482011034 TX Harris County 78 76.1 0.3 1.7 4.1 5.9 44.3

482011035 TX Harris County 74.7 72.5 0.2 1.3 3.3 5 41.7

482011039 TX Harris County 78.3 75.5 0.2 1.3 3.4 5.1 42.8

482011050 TX Harris County 76.3 74 0.3 2.2 5.8 9.1 43.5

0.1 0.6 1.5 2.2 27.5

482151048 TX Hidalgo County 60 58.1 0.1 0.6 1.4 2 24.3

482450009 TX Jefferson County 71.7 68.3 0.1 0.7 2 2.9 42.2

482450011 TX Jefferson County 74 70.5 0.2 1.9 4.9 7.2 43.9

482450022 TX Jefferson County 70.3 66.7 0.1 0.8 2.4 3.5 40.3

482450101 TX Jefferson County 75 72.3 0.3 3 8.2 12.4 45.9

482450102 TX Jefferson County 67 64.4 0.2 1.3 4.1 6 40

482450628 TX Jefferson County 69.3 66.4 0.2 2 5.3 7.8 41.8

482451035 TX Jefferson County 69.3 66.9 0.2 1.5 4.5 6.7 41.9

483091037 TX McLennan County 71.7 69.1 0 0.2 0.5 0.7 31.3

483390078 TX Montgomery County 78 74.7 0.2 1 3.1 4.5 45.8

483491051 TX Navarro County 70 68.2 0.1 0.2 0.6 0.8 33.5

483550025 TX Nueces County 69.3 68.2 0.3 1.9 5.4 7.4 35

483550026 TX Nueces County 68.3 66.2 0.3 1.3 3.6 4.9 32.7

483611001 TX Orange County 69.3 66.5 0.1 1.4 4.8 6.9 41.3

483611100 TX Orange County 68 65.4 0.1 1.5 4.6 6.9 40

484530014 TX Travis County 71.3 67.7 0 0.2 0.9 1.3 37.5

484530020 TX Travis County 71.7 68.3 0.1 0.3 1 1.4 35.8

484690003 TX Victoria County 66.3 64.2 0.2 1 3 4.2 32.6
D-86 2018 Gulf of Mexico Supplemental EIS

Table D-19. MATS Ozone Design Value Results for All Monitoring Sites Where Exclusion of 

Contributions from Source Group A or B is Sufficient to Reduce the Predicted Future Design 

Value (DVF) from Above the NAAQS to Below the NAAQS (all values in ppb).

Site ID Location State DVC1 DVF2 DVF_A3 DVF –

DVF_A DVF_B3 DVF –DVF_B

220330003 East Baton 

Rouge Parish LA 75.3 71.3 71.2 0.1 70.6 0.7

480271047 Bell County TX 73.7 71.0 71.0 0.0 70.7 0.3

481671034 Galveston TX 75.3 71.2 70.9 0.3 69.1 4.9

482010026 Houston TX 73 71.2 71.0 0.2 69.6 1.6

482010046 Houston TX 73.7 71.6 71.4 0.2 70.3 1.3

482450101 Port Arthur TX 75 72.3 72.0 0.3 69.3 3.0

1 The MATS base period ozone design value (ppb) representing combined contributions of all sources.

2 The MATS future year ozone design value (ppb) representing combined contributions of all sources. 3 The MATS future year ozone design value (ppb) calculated after removing source apportionment 

contributions of Source Group A or B. 

Figure D-40 displays the MATS Unmonitored Area Analysis (UAA) results, which were 

generated using the observed ozone data in MATS and the base year and future year scenario 

CAMx results. The MATS UAA spatially interpolates the DVCs obtained from observations across 

the modeling domain and then calculates the DVF for each model grid cell by multiplying the 

interpolated DVC by the RRF value (i.e., the ratio of the modeled future year to base year design 

values) in each grid cell. Future year design values calculated using the MATS UAA procedure are 

lower than base year design values throughout most of the 4-km modeling domain with the 

exception of a maximum 1.6-ppb increase of less than 3 ppb off the Louisiana coast.
Air Quality: Cumulative and Visibility Impacts D-87

Figure D-40. Base Scenario Ozone Design Values (DVC, top left), Future Year Ozone Design Values 

(DVF, top right) and Their Differences (DVF – DVC; bottom) Calculated Using the MATS 

UAA Tool.

D.7.1.1.2 Ozone MATS Unmonitored Area Analysis

The MATS UAA DVF values calculated after first removing the hourly contributions from 

Source Groups A (new platforms), B (new platforms and associated support vessels and aircraft), 

and D (all Gulf of Mexico sources) are shown in the left column of Figure D-41. The contributions of 

Source Groups A, B, and D calculated as the difference between these DVF values and the DVF 

values from all sources (as shown in the upper right-hand corner of Figure D-40) are shown in the 

right column of Figure D-41. Source Group A contributions are centered in the Gulf of Mexico 

offshore of Louisiana, with a peak impact of 2.2 ppb; maximum impacts from the State seaward 

boundaries inland are in the 1- to 1.2-ppb range along the coast of Cameron Parish. For Source 

Group B, the maximum contribution (10.8 ppb) is in approximately the same location, but the support 

vessel and helicopter activities result in greater impacts landward of the State seaward boundary, 

with maximum contributions in the 6- to 7-ppb range.
D-88 2018 Gulf of Mexico Supplemental EIS

Source 

Group1

DVF with Source Group Contribution 

Removed Source Group Contribution2

A 

B 

D 

1 As defined in Table D-14. 2 Source group contributions are calculated by subtracting the DVF values calculated after removing 

the hourly source group contributions from the DVF values calculated when all sources are 

included.

Figure D-41. MATS UAA Future Year Ozone Design Values (DFV) Calculated After First Removing the 

Hourly Contributions from a Source Group (left column) and the Corresponding 

Contributions of the Source Group to DVF (right column) Calculated by Subtracting the 

DVFs Shown in the Left-hand Column from the “All Sources” DVF Shown in the Top 

Right-hand Corner of Figure D-40. Top row – source group B; middle row – source 

group D. 
Air Quality: Cumulative and Visibility Impacts D-89

D.7.1.2 Ozone NAAQS Analysis Using Absolute Modeling Results

The CAMx source apportionment absolute modeling results from the future year scenario are 

analyzed and compared with the ozone NAAQS in this section. The ozone NAAQS is defined as the 

3-year average of the 4th highest maximum daily average 8-hour (MDA8) ozone concentration. Since 

only one calendar year of modeling results are available for the base year and future year scenarios, 

the future year 4th highest MDA8 ozone concentration is used as a pseudo-NAAQS comparison 

metric. 

Modeled 4th highest MDA8 values in each model grid cell for the base and future year 

scenarios and the corresponding differences are shown in Figure D-42. Similar to the MATS results 

presented in Figure D-40, the 4th highest MDA8 is lower under the future year scenario throughout 

most of the 4-km domain, with isolated areas of increases of less than 4 ppb located off the coasts of 

Louisiana and Texas and onshore in Cameron Parish, Louisiana. 

Figure D-42. Modeled 4th Highest MDA8 Ozone for the Base Year (upper left) and Future Year (upper 

right) Scenarios and Their Differences (bottom center). 
D-90 2018 Gulf of Mexico Supplemental EIS

Contributions of each source group to the all sources future year 4th highest MDA8 values 

shown in the upper right-hand panel of Figure D-42 are shown in Figures D-43 and D-44. These 

contributions are matched in time to the all sources 4th highest MDA8 values; contributions may be 

different during other periods with elevated MDA8 values. As shown in Figure D-43, new platform 

sources under the 2017-2022 GOM Multisale EIS (from which this Supplemental EIS tiers) scenario 

(Source Group A) are estimated to contribute as much as 7.4 ppb to design values out over the Gulf

of Mexico. Within the states out to the State Seaward Boundary (SSB), the contributions range from 

near zero to approximately 3 ppb, with the maximum contributions occurring along the coast of 

Cameron Parish, Louisiana. Contributions increase by about 10 ppb when contributions from 

support vessels and helicopters associated with the 2017-2022 GOM Multisale EIS scenario, from 

which this Supplemental EIS tiers, are added in (Source Group B). Also, adding in all existing 

platforms and support vessels and helicopters (Source Group C) raises the maximum contribution 

out over the Gulf of Mexico to nearly 38 ppb. Contributions landward of the SSB are generally below 

15 ppb but with some areas along the Louisiana coast reaching maximum contributions up to 

35 ppb. Adding in all other marine vessel activity in the Gulf of Mexico (Source Group D) only 

increases the contributions by a few ppb. The addition of land-based and Mexican and Canadian 

anthropogenic sources (Source Group E) results in source contributions that are typically about 

30 ppb higher than the contributions from Gulf of Mexico sources alone (Source Group D). 

Contributions over the land areas are higher than for Source Group D although the highest 

contributions remain out over the Gulf of Mexico where biogenic emissions have minimal influence. 

In other words, to the extent that elevated ozone levels are predicted over the Gulf of Mexico, they 

are nearly entirely attributable to anthropogenic sources. 

Contributions from natural sources (including biogenics and fires) and non-U.S. emissions, 

including 12-km domain boundary conditions (Source Group F), are shown in the left panel of 

Figure D-44; contributions from just the boundary conditions (BCs) are shown in the right panel. 

These results show an area south of Galveston where ozone design values were almost entirely 

driven by U.S. or Mexican anthropogenic BCs; however, over the rest of the Gulf of Mexico, 

including the near coastal areas, contributions are generally between 20 and 30 ppb and are 

overwhelmingly attributable to the BCs. Higher contributions are seen inland where biogenic 

sources play a larger role in ozone formation.
Air Quality: Cumulative and Visibility Impacts D-91

Figure D-43. Contributions of Source Groups A (top left), B (top right), C (middle left), D (middle right), 

and E (bottom) to Future Year All-sources 4th Highest MDA8 (note different color scales in 

each panel).
D-92 2018 Gulf of Mexico Supplemental EIS

Figure D-44. Contributions from (left) Source Group F (natural and non-U.S. emission sources 

including boundary conditions) and (right) Boundary Conditions Only, to Future 

Year All-sources 4th Highest MDA8. 

D.7.1.3 PM2.5 NAAQS Analysis using Relative Model Results

There are two PM2.5 NAAQS, one for 24-hour averaging time that is expressed as a 3-year 

average of the annual 98th percentile in a year with a threshold of 35 μg/m3 and an annual average 

over 3 years with a threshold of 12 μg/m3

. With 1 year of complete everyday modeling, the annual 

98th percentile will correspond to the 8th highest 24-hour PM2.5 concentration in a year. 

Predictions of future year 24-hour and annual average PM2.5 design values were made 

based on the use of model results in a relative sense as was done for ozone design values in 

Section D.7.1.1. The MATS software was used to generate predicted future year design values 

(DVFs) from current (base year) design values (DVB or DVC). The MATS was configured to use 

ambient measurements of total PM2.5 for the period 2008-2012 to generate DVCs based on an 

average of three overlapping 3-year average DVs as recommended in the USEPA’s guidance 

(USEPA, 2014) and speciated PM2.5 monitoring data for the period 2010-2012 to generate the 

projected DVFs based on model predicted species RRFs. 

D.7.1.3.1 24-Hour PM2.5

As described for the ozone NAAQS analysis in Section D.7.1.1, the MATS was used to 

calculate DVFs for the 24-hour and annual PM2.5 NAAQS. Observational data for use in the MATS 

were provided by the USEPA23 for use in calculating the DVCs. For total PM2.5, observational data 

covered the period 2008-2012; for the speciated PM2.5 calculations, observational data covered the 

period 2010-2012.

Results of the MATS analysis are shown in Table D-20. All current and future year design 

values are below the 35 μg/m3 NAAQS, and the future year design values are projected to be lower 

 

23 https://www3.epa.gov/scram001/modelingapps_mats.htm
Air Quality: Cumulative and Visibility Impacts D-93

than the current year design values at all sites. The reductions in the projected DVFs calculated 

after removing source contributions from each Source Group A, B, C, D, and E (i.e., DVF from 

Table D-20 minus DVF calculated with hourly source group contributions removed) are listed in 

Table D-21. The largest of the Source Group A, B, C, or D contributions calculated in this manner 

occur at the Bay Rd. monitor in Mobile County, Alabama. New platforms and associated support 

vessels and helicopters (Source Group B) are calculated to contribute 1.2 μg/m3 or 6.4% of the 

18.9 μg/m3 DVF at this location. 

Table D-20. Current Year (DVC) and Future Year (DVF) 24-Hour PM2.5 Design Values for Monitoring 

Sites in the 4-km Modeling Domain from MATS.

Site ID Site Name State County DVC DVF 

10030010 FAIRHOPE HIGH SCHOOL, FAIRHOPE, 

ALABAMA AL Baldwin County 19.5 17.7

10970003 CHICKASAW, MOBILE CO., ALABAMA AL Mobile County 19.1 17.2

10972005 BAY RD., MOBILE AL. AL Mobile County 20 18.9

120330004 ELLYSON INDUSTRIAL PARK-COPTER 

ROAD FL Escambia County 19.2 17.6

220190009 2284 Paul Bellow Road LA Calcasieu Parish 18.6 17

220190010 Common and East McNeese LA Calcasieu Parish 20.5 18.4

220330009 1061-A Leesville Ave LA East Baton Rouge 

Parish 21 19.2

220331001 Highway 964 LA East Baton Rouge 

Parish 16.7 14.2

220470005 St Gabriel Agricultural Exp. Station LA Iberville Parish 21 19.9

220470009 65180 Belleview Road LA Iberville Parish 18.6 17.5

220511001 West Temple Pl LA Jefferson Parish 18.7 17.1

220512001 Patriot St. and Allo St. LA Jefferson Parish 18.5 16.6

220550006 121 East Point Des Mouton LA Lafayette Parish 18.8 17.5

220550007 646 Cajundome LA Lafayette Parish 20.2 18.1

220790002 8105 Tom Bowman Drive LA Rapides Parish 19.6 17.7

220870007 24 E. CHALMETTE CIRCLE LA St. Bernard Parish 20.2 17.4

221050001 21549 Old Hammond Hwy, Hammond, LA 

70403 LA Tangipahoa Parish 18.8 17.2

221090001 4047 Highway 24 North Gray LA Terrebonne Parish 17.6 16.2

221210001 1005 Northwest Drive, Port Allen LA West Baton Rouge 

Parish 21.7 20.2

280010004 Natchez Municipal Water Works,

Brenham St. MS Adams County 20.3 17.7

280350004 205 Bay Street MS Forrest County 22.4 21

280450003 400 Baltic St. MS Hancock County 20 18.3

280470008 47 Maple Street MS Harrison County 18.3 16

280590006 Hospital Road at Co. Health Dept. MS Jackson County 20.8 19.6

280670002 26 Mason St. MS Jones County 23 21.7

480290059 14620 LAGUNA RD. TX Bexar County 21.4 20.9

480612004 LOT B 69 1⁄2 TX Cameron County 22.7 22.4
D-94 2018 Gulf of Mexico Supplemental EIS

Site ID Site Name State County DVC DVF 

482010058 7210 1/2 BAYWAY DRIVE TX Harris County 20.8 20.2

482011035 9525 CLINTON DR TX Harris County 24 22.7

483550032 3810 HUISACHE STREET TX Nueces County 24.3 23.3

484530020 12200 LIME CREEK RD. TX Travis County 20.7 19.1

484530021 2600 B WEBBERVILLE RD. TX Travis County 21.8 20.5

Table D-21. 24-Hour PM2.5 Current (DVC) and Future Year (DVF) Design Values and Reduction in DVF 

with Contributions from Individual Source Groups Removed. 

Site ID State County DVC DVF

Change in DVF with Source Group 

Removed

A B C D E

10030010 AL Baldwin County 19.5 17.7 0.0 0.2 0.3 0.4 8.8

10970003 AL Mobile County 19.1 17.2 0.0 0.1 0.1 0.2 10.2

10972005 AL Mobile County 20 18.9 0.0 1.2 1.2 1.3 12.0

120330004 FL Escambia County 19.2 17.6 0.0 0.0 0.1 0.1 9.2

220190009 LA Calcasieu Parish 18.6 17 0.0 0.1 0.2 0.5 9.9

220190010 LA Calcasieu Parish 20.5 18.4 0.0 0.0 0.1 0.3 12.1

220330009 LA East Baton Rouge 

Parish 21 19.2 0.0 0.1 0.2 0.3 12.3

220331001 LA East Baton Rouge 

Parish 16.7 14.2 0.0 0.1 0.2 0.4 9.1

220470005 LA Iberville Parish 21 19.9 0.0 0.0 0.2 0.4 14.2

220470009 LA Iberville Parish 18.6 17.5 0.0 0.0 0.1 0.3 10.2

220511001 LA Jefferson Parish 18.7 17.1 0.0 0.0 0.2 0.3 12.0

220512001 LA Jefferson Parish 18.5 16.6 0.0 0.1 0.2 0.4 13.1

220550006 LA Lafayette Parish 18.8 17.5 0.1 0.2 0.5 1.0 12.1

220550007 LA Lafayette Parish 20.2 18.1 0.0 0.0 0.2 0.3 12.3

220790002 LA Rapides Parish 19.6 17.7 0.0 0.0 0.2 0.4 8.1

220870007 LA St. Bernard Parish 20.2 17.4 0.0 0.0 0.2 0.4 12.0

221050001 LA Tangipahoa Parish 18.8 17.2 0.1 0.1 0.3 0.5 9.1

221090001 LA Terrebonne Parish 17.6 16.2 0.0 0.1 0.3 0.4 10.8

221210001 LA West Baton Rouge 

Parish 21.7 20.2 0.0 0.0 0.2 0.3 13.8

280010004 MS Adams County 20.3 17.7 0.0 0.1 0.1 0.2 7.8

280350004 MS Forrest County 22.4 21 0.0 0.1 0.1 0.2 11.4

280450003 MS Hancock County 20 18.3 0.0 0.1 0.6 1.1 11.4

280470008 MS Harrison County 18.3 16 0.0 0.0 0.3 0.4 8.8

280590006 MS Jackson County 20.8 19.6 0.1 0.1 0.4 1.1 14.3

280670002 MS Jones County 23 21.7 0.0 0.1 0.1 0.1 11.0

480290059 TX Bexar County 21.4 20.9 0.0 0.0 0.0 0.0 11.8

480612004 TX Cameron County 22.7 22.4 0.0 0.7 0.7 0.8 5.4

482010058 TX Harris County 20.8 20.2 0.0 0.0 0.2 0.5 13.1

482011035 TX Harris County 24 22.7 0.0 0.0 0.1 0.2 14.9

483550032 TX Nueces County 24.3 23.3 0.0 0.1 0.1 0.2 12.3
Air Quality: Cumulative and Visibility Impacts D-95

Site ID State County DVC DVF

Change in DVF with Source Group 

Removed

A B C D E

484530020 TX Travis County 20.7 19.1 0.0 0.0 0.0 0.1 9.4

484530021 TX Travis County 21.8 20.5 0.0 0.0 0.0 0.1 12.1

D.7.1.3.2 Annual Average PM2.5

The MATS projections of DVF for the annual average PM2.5 design values are shown in 

Table D-22. The only design value exceeding the 12 μg/m3 annual average NAAQS is the current 

year design value at the Clinton Dr. monitor in Houston, Texas. The projected future year design 

value at this location is below the NAAQS. Future year design values are projected to be less than 

the current year design values at all monitoring sites except for a 0.3 μg/m3 increase at the Hidalgo 

County monitoring site just west of Brownsville, Texas. 

Reductions in the projected annual average DVFs calculated after removing source 

contributions from each Source Group A, B, C, D, and E (i.e., DVF from Table D-22 minus DVF 

calculated with hourly source group contributions removed) are shown in Table D-23. The largest of 

the Source Group A, B, C, or D contributions calculated in this manner occur at the Bay Rd. monitor 

in Mobile County, Alabama. New platforms and associated support vessels and helicopters (Source 

Group B) are calculated to contribute 0.7 μg/m3 or 7.7% of the 9.1 μg/m3 DVF at this location. 

Source Group B contributions at the Clinton Dr. monitor are calculated to be less than 0.05 μg/m3

. 

Source Group B contributions at the Hidalgo County monitoring site are calculated to be 0.1 μg/m3

. 

Table D-22. Current (DVC) and Projected Future (DVF) Annual Average PM2.5 Design Values for 

Monitoring Sites in the 4-km Modeling Domain (highlighted values exceed the 12 μg/m3

NAAQS). 

Site ID Site Name State DVC DVF 

10030010 FAIRHOPE HIGH SCHOOL, FAIRHOPE, ALABAMA AL 9.8 9.1

10970003 CHICKASAW, MOBILE CO., ALABAMA AL 9.7 8.9

10972005 BAY RD., MOBILE AL. AL 9.2 9.1

120330004 ELLYSON INDUSTRIAL PARK-COPTER ROAD FL 8.9 8.3

220190009 2284 Paul Bellow Road LA 8.6 7.9

220190010 Common and East McNeese LA 9.1 8.5

220330009 1061-A Leesville Ave LA 10.3 9.6

220331001 Highway 964 LA 9.3 8.3

220470005 St Gabriel Agricultural Exp. Station LA 10.2 9.5

220470009 65180 Belleview Road LA 8.9 8.1

220511001 West Temple Pl LA 9 8.2

220512001 Patriot St. and Allo St. LA 9.2 8.3

220550006 121 East Point Des Mouton LA 8.9 8.2

220550007 646 Cajundome LA 9.1 8.4

220790002 8105 Tom Bowman Drive LA 8.8 8

220870007 24 E. CHALMETTE CIRCLE LA 10.5 9.7

221050001 21549 Old Hammond Hwy, Hammond, LA 70403 LA 9 8.1
D-96 2018 Gulf of Mexico Supplemental EIS

Site ID Site Name State DVC DVF 

221090001 4047 Highway 24 North Gray LA 8.5 7.8

221210001 1005 Northwest Drive, Port Allen LA 10.8 10.1

280010004 Natchez Municipal Water Works Brenham St MS 10.2 9.3

280350004 205 Bay Street MS 11.7 10.9

280450003 400 Baltic St MS 9.9 9.1

280470008 47 Maple Street MS 9.6 8.7

280590006 Hospital Road at Co. Health Dept. MS 9.5 9

280670002 26 Mason St. MS 11.8 11.3

480290059 14620 LAGUNA RD. TX 9 8.8

480612004 LOT B 69 1⁄2 TX 11 10.9

482010058 7210 1/2 BAYWAY DRIVE TX 11.1 10.9

482011035 9525 CLINTON DR TX 12.4 11.6

482150043 2300 NORTH GLASSCOCK TX 10.4 10.7

483550032 3810 HUISACHE STREET TX 10.3 10

484530020 12200 LIME CREEK RD. TX 8.4 7.9

484530021 2600 B WEBBERVILLE RD. TX 10.2 9.8

Table D-23. Annual Average PM2.5 Future Year Design Values (DVF) and Change in DVF with 

Contributions from Individual Source Groups Removed (highlighted values exceed the 

12 μg/m3 NAAQS). 

Site ID State County DVC DVF 

Change in DVF with Source Group 

Removed

A B C D E

10030010 AL Baldwin County 9.8 9.1 0.0 0.1 0.2 0.3 5.5

10970003 AL Mobile County 9.7 8.9 0.0 0.1 0.1 0.2 6.2

10972005 AL Mobile County 9.2 9.1 0.0 0.7 0.8 0.9 6.1

120330004 FL Escambia County 8.9 8.3 0.0 0.1 0.1 0.2 5.2

220190009 LA Calcasieu Parish 8.6 7.9 0.0 0.1 0.2 0.4 5.0

220190010 LA Calcasieu Parish 9.1 8.5 0.0 0.0 0.2 0.4 6.3

220330009 LA East Baton Rouge 

Parish 10.3 9.6 0.0 0.1 0.2 0.3 7.2

220331001 LA East Baton Rouge 

Parish 9.3 8.3 0.0 0.0 0.1 0.2 6.0

220470005 LA Iberville Parish 10.2 9.5 0.0 0.0 0.1 0.2 7.4

220470009 LA Iberville Parish 8.9 8.1 0.0 0.0 0.1 0.3 5.5

220511001 LA Jefferson Parish 9 8.2 0.0 0.1 0.2 0.3 6.0

220512001 LA Jefferson Parish 9.2 8.3 0.0 0.0 0.1 0.2 6.6

220550006 LA Lafayette Parish 8.9 8.2 0.0 0.0 0.2 0.4 5.9

220550007 LA Lafayette Parish 9.1 8.4 0.0 0.1 0.2 0.4 6.1

220790002 LA Rapides Parish 8.8 8 0.0 0.0 0.1 0.2 4.7

220870007 LA St. Bernard Parish 10.5 9.7 0.0 0.1 0.2 0.3 7.3

221050001 LA Tangipahoa Parish 9 8.1 0.0 0.1 0.2 0.3 5.0

221090001 LA Terrebonne Parish 8.5 7.8 0.0 0.0 0.2 0.4 5.5

221210001 LA West Baton Rouge 

Parish 10.8 10.1 0.0 0.0 0.1 0.2 7.9
Air Quality: Cumulative and Visibility Impacts D-97

Site ID State County DVC DVF 

Change in DVF with Source Group 

Removed

A B C D E

280010004 MS Adams County 10.2 9.3 0.0 0.0 0.1 0.2 5.4

280350004 MS Forrest County 11.7 10.9 0.0 0.0 0.1 0.2 7.2

280450003 MS Hancock County 9.9 9.1 0.0 0.0 0.2 0.4 6.1

280470008 MS Harrison County 9.6 8.7 0.0 0.0 0.2 0.3 5.6

280590006 MS Jackson County 9.5 9 0.0 0.1 0.2 0.3 6.9

280670002 MS Jones County 11.8 11.3 0.0 0.0 0.1 0.1 7.4

480290059 TX Bexar County 9 8.8 0.0 0.0 0.1 0.1 5.0

480612004 TX Cameron County 11 10.9 0.0 0.3 0.4 0.5 4.9

482010058 TX Harris County 11.1 10.9 0.0 0.0 0.1 0.3 8.0

482011035 TX Harris County 12.4 11.6 0.0 0.0 0.0 0.2 8.8

482150043 TX Hidalgo County 10.4 10.7 0.0 0.1 0.1 0.1 6.4

483550032 TX Nueces County 10.3 10 0.0 0.0 0.1 0.1 6.0

484530020 TX Travis County 8.4 7.9 0.0 0.0 0.0 0.1 4.4

484530021 TX Travis County 10.2 9.8 0.0 0.0 0.0 0.1 6.1

Figure D-45 displays the MATS UAA results for the annual average PM2.5 DVC, DVF, and 

the difference, DVF - DVC.24 Reductions in annual average PM2.5 design values associated with 

emission reductions from all sources combined are projected throughout nearly the entire domain, 

with the exception of increases near the Freshwater Bayou Canal in Vermilion Parish, Louisiana,

and Brownsville, Texas, in addition to a few additional areas in Texas and southern Louisiana. 

Some of the isolated areas of increases may represent artifacts of the MATS UAA spatial 

interpolation procedure and are not necessarily physically meaningful. Increases in the coastal ports 

are associated with new platforms and support vessel and helicopter traffic (Source Group B), as 

shown by the unmonitored area source group contributions in Figure D-46. Source Group B 

contributes as much as 1.8 μg/m3 in these areas. 

 

24 The UAA analysis could only be performed for the annual average PM2.5 NAAQS as the MATS 

software cannot calculate UAA results for the 24-hour average PM2.5 NAAQS.
D-98 2018 Gulf of Mexico Supplemental EIS

Figure D-45. Current Year (DVC) and Future Year (DVF) Annual Average PM2.5 Design Values from 

the MATS Unmonitored Area Analysis (top left and top right, respectively) and the 

Difference, DVF – DVC (bottom).
Air Quality: Cumulative and Visibility Impacts D-99

Figure D-46. Contributions of Source Groups A (top left), B (top right), C (middle left), D (middle right), 

and E (bottom) to the Future Year All-sources Annual Average PM2.5 Concentration Based 

on the MATS Unmonitored Area Analysis (note different color scales used in each panel). 

D.7.1.4 PM2.5 NAAQS Analysis using Absolute Model Predictions

The CAMx source apportionment absolute modeling results from the future year scenario are 

analyzed and compared with the PM2.5 24-hour and annual NAAQS in this section.
D-100 2018 Gulf of Mexico Supplemental EIS

D.7.1.4.1 24-Hour PM2.5

The 24-hour PM2.5 NAAQS is defined as the three-year average of the annual 98th percentile 

daily average which corresponds to the 8th highest daily average in each year assuming complete 

data. Since only one calendar year of modeling results are available for the base year and future 

year scenarios, the future year 8th highest daily average PM2.5 concentration is selected for 

comparison with the NAAQS.

Modeled 8th highest daily PM2.5 concentrations in each model grid cell for the base and future 

year scenarios and the corresponding differences are shown in Figure D-47. Areas of high 

predicted PM2.5 occur along the Alabama, Louisiana and east Texas Gulf coasts in both the base 

and future year scenarios. Although predicted 8th highest daily PM2.5 concentrations in these areas 

exceed the 35 μg/m3 NAAQS, both base-year monitored design values (DVCs) and projected future 

year design values (DVFs) are below the NAAQS at monitoring sites in these areas as noted in 

Section D.7.1.3.1 above. A tendency towards over prediction of daily PM2.5 noted in the model 

performance evaluation results presented in Section D.5. The difference plot at the bottom of 

Figure D-47 shows PM2.5 reductions in the majority of the domain with some areas of increases in 

PM2.5 along portions of the immediate shoreline and offshore in the western Gulf where additional 

activities are anticipated under the 2017-2022 GOM Multisale EIS scenario, from which this 

Supplemental EIS tiers. Where PM2.5 increases are predicted, they are limited to less than 15 μg/m3

for nearly all grid cells.

Source group contributions to the annual 8th highest daily average PM2.5 concentrations 

under the future year scenario are shown in Figure D-48. These contributions are matched in time 

to the all sources 8th highest daily average PM2.5 concentrations; contributions may be different 

during other periods with elevated daily average PM2.5 values. Impacts of the new sources 

associated with the 2017-2022 GOM Multisale EIS scenario (Source Groups A and B) are largely 

focused on the area offshore of western Louisiana. Impacts from new platforms associated with the 

2017-2022 GOM Multisale EIS scenario (Source Group A) are less than 1 μg/m3

; adding in support 

vessels and helicopters (Source Group B) increases the near-shore impacts up to a maximum of 

7 μg/m3 as compared to a combined maximum impact of all Gulf of Mexico sources (Source 

Group D) of 44 μg/m3

. This Supplemental EIS tiers from the 2017-2022 GOM Multisale EIS and 

uses the scenario and alternatives analyzed in the 2017-2022 GOM Multisale EIS.

Contributions from Source Group E, which includes Source Group D plus all other U.S. and 

non-U.S. anthropogenic sources, shows the influence of inland urban areas on PM2.5 levels, 

especially in Baton Rouge and Lake Charles, Louisiana. 

Contributions from Source Group F (natural and non-U.S. emission sources including 

boundary conditions) shown in the left panel of Figure D-49 are dominated by fire emissions near 

Beaumont, Texas, and in Vermilion and Lafourche Parishes, Louisiana. Boundary condition 

contributions are less than 4 μg/m3 in the coastal areas as shown in the right panel of Figure D-49. 
Air Quality: Cumulative and Visibility Impacts D-101

Figure D-47. Modeled 8th Highest Daily Average PM2.5 Concentrations for the Base Year (top left), 

Future Year (top right), and the Future – Base Difference (bottom). 

 
D-102 2018 Gulf of Mexico Supplemental EIS

Figure D-48. Contributions of Source Groups A (top left), B (top right), C (middle left), D (middle right), 

and E (bottom) to the Future Year All-sources 8th Highest Daily Average PM2.5

Concentration (note different color scales used in each panel). 
Air Quality: Cumulative and Visibility Impacts D-103

Figure D-49. Contributions from (left) Source Group F (natural and non-U.S. emission sources including 

boundary conditions) and (right) Boundary Conditions Only to Future Year All-sources 

8th Highest 24-hour PM2.5 (note use of different color scale in each panel).

D.7.1.4.2 Annual Average PM2.5

Modeled annual average PM2.5 for the base year, future year, and the future – base 

differences are shown in Figure D-50. Average PM2.5 concentrations decrease on most locations 

between the base and future year scenarios with changes over the western GOM between 

± 0.5 μg/m3

. Increases of up to 2.5 μg/m3 are calculated to occur in coastal Vermilion Parish, 

Louisiana. 

Source group contributions to the annual average PM2.5 concentrations under the future year 

scenario are shown in Figure D-51. Impacts of the new sources associated with the 2017-2022 

GOM Multisale EIS (from which this Supplemental EIS tiers) scenario (Source Group B) are largely 

focused on the area offshore of western Louisiana with a maximum impact of 2.2 μg/m3 as 

compared to a combined maximum impact of all GOM sources (Source Group D) of 9.3 μg/m3

. 

Source Group F contributions (natural and non-U.S. emission sources including boundary 

conditions) shown in the left panel of Figure D-52 are dominated by fire emissions near Beaumont, 

Texas, and in Vermilion and Lafourche Parishes, Louisiana. Boundary condition contributions are 

less than 2 μg/m3 in the coastal areas as shown in the right panel of Figure D-52. 
D-104 2018 Gulf of Mexico Supplemental EIS

Figure D-50. Modeled Annual Average PM2.5 Concentrations for the Base Year (top left), Future Year 

(top right), and the Future – Base Difference (bottom). 
Air Quality: Cumulative and Visibility Impacts D-105

Figure D-51. Contributions of Source Group A (top left), B (top right), C (middle left), D (middle right), 

and E (bottom) to the Future Year All-sources Annual Average PM2.5 Concentration (note 

use of different color scales in each panel).
D-106 2018 Gulf of Mexico Supplemental EIS

Figure D-52. Contributions from (left) Source Group F (natural and non-U.S. emission sources including 

boundary conditions) and (right) Boundary Conditions Only to Future Year All-sources 

Annual Average PM2.5 (note use of different color scale in each panel).

D.7.1.5 NAAQS Analysis for other Criteria Air Pollutants

D.7.1.5.1 PM10

Figure D-53 displays modeled 2nd highest daily average PM10 concentrations than can be 

compared with the 24-hour average PM10 NAAQS (150 μg/m3

) for the base and future scenarios and 

the base-future differences. Areas of elevated PM10 are evident in urban and port areas and in fire 

zones along the Gulf Coasts of Texas and Louisiana (impacts of fires on PM10 can be discerned 

from the left panel of Figure D-55 described below). The PM10 decreases are modeled along the 

Louisiana coast with increases of between 2 and 5 μg/m3 in waters farther offshore associated with 

new emissions from the 2017-2022 GOM Multisale EIS scenario sources, from which this 

Supplemental EIS tiers. 

Source group contributions to the 2nd highest daily average PM10 concentrations are shown 

in Figure D-54. The maximum contribution of the new platforms and associated support vessels 

and aircraft under the 2017-2022 GOM Multisale EIS (from which this Supplemental EIS tiers) 

scenario (Source Group B) is predicted to be 10.7 μg/m3 or 7% of the NAAQS. The maximum 

contribution of all oil and gas platforms and support vessels and helicopters (Source Group C) is 

41 μg/m3 (28% of the NAAQS). Fires dominate contributions from natural and non-U.S. sources 

(Figure D-55).
Air Quality: Cumulative and Visibility Impacts D-107

Figure D-53. Modeled 2nd Highest 24-hour Average PM10 Concentrations for the Base Year (top left), 

Future Year (top right), and the Future – Base Difference (bottom). 
D-108 2018 Gulf of Mexico Supplemental EIS

Figure D-54. Contributions of Source Groups A (top left), B (top right), C (middle left), D (middle right), 

and E (bottom) to the Future Year All-sources 2nd Highest Daily Average PM10

Concentration (note use of different color scales in each panel).
Air Quality: Cumulative and Visibility Impacts D-109

Figure D-55. Contributions from (left) Source Group F (natural and non-U.S. emission sources including 

boundary conditions) and (right) Boundary Conditions Only to Future Year All-sources 

2nd Highest Daily Average PM10 Concentration (note use of different color scale in each 

panel).

D.7.1.5.2 NO2

Results are presented here for both the 1-hour average NO2 NAAQS (100 ppb) and the 

annual average NO2 NAAQS (53 ppb). Figures D-56 and D-57 display modeled 1-hour average 

NO2 design values (based on the 8th highest daily average) for the base and future year scenarios 

along with source group contributions to the future year design values. All modeled 1-hour NO2

concentrations are below the NAAQS (100 ppb); concentrations in the immediate vicinity of the 

Louisiana Offshore Oil Port (LOOP) peak at 98.5 ppb. Concentrations decrease between the base 

and future year scenarios at most locations except for of as much as a 32-ppb increase in coastal 

Vermilion Parish, Louisiana. Increases are also projected offshore of Texas and Alabama and in 

some interior portions of Texas.

Source Group contributions to the 8th highest daily average NO2 concentrations are shown in 

Figure D-57. Contributions from new platforms and support vessels and helicopters associated with 

the 2017-2022 GOM Multisale EIS (from which this Supplemental EIS tiers) scenario (Source 

Group B) are dominated by vessel and possibly helicopter traffic in the port areas, most notably in 

Vermilion Parish, Louisiana, where the maximum contribution is 55.6 ppb. Combined contributions 

from new and existing platforms and support vessels and helicopters (Source Group C) are 

dominant in the area of the LOOP. Contributions from natural and foreign sources are less than 

10 ppb (not shown).
D-110 2018 Gulf of Mexico Supplemental EIS

Figure D-56. Modeled 8th Highest 1-hour NO2 Concentrations for the Base Year (top left), Future Year 

(top right), and the Future – Base Difference (bottom). 
Air Quality: Cumulative and Visibility Impacts D-111

Figure D-57. Contributions of Source Group A (top left), B (top right), C (middle left), D (middle right), 

and E (bottom) to the Future Year All-sources 8th Highest Daily Average NO2

Concentrations (note use of different color scales in each panel).

Figures D-58 and D-59 display modeled annual average NO2 concentrations for the base 

case and future year scenarios, along with source group contributions to the future year annual 
D-112 2018 Gulf of Mexico Supplemental EIS

averages. All modeled concentrations are below the NAAQS. Increases between the base case 

and future year scenarios of as much as 8 ppb are modeled to occur near the entrance to the 

Freshwater Bayou Canal in Vermilion Parish, Louisiana. Somewhat larger increases are modeled in 

the Permian Basin of west Texas. 

Contributions of Source Groups to the annual average NO2 concentrations are shown in 

Figure D-59. These results are similar to those for 1-hour NO2 shown above. Maximum impacts 

from new platforms and support vessels and helicopters associated with the 2017-2022 GOM 

Multisale EIS (from which this Supplemental EIS tiers) scenario are as much as 8.6 ppb (16% of the 

NAAQS).

Figure D-58. Modeled Annual Average NO2 Concentrations for the Base Year (top left), Future Year (top 

right), and the Future – Base Difference (bottom). 
Air Quality: Cumulative and Visibility Impacts D-113

Figure D-59. Contributions of Source Groups A (top left), B (top right), C (middle left), D (middle right), 

and E (bottom) to the Future Year All-sources Annual Average NO2 Concentrations.
D-114 2018 Gulf of Mexico Supplemental EIS

D.7.1.5.3 SO2

Results are presented here for both the 1-hour average primary SO2 NAAQS (75 ppb) and 

the 3-hour average secondary SO2 NAAQS (0.5 ppm). 

Figure D-60 displays modeled 1-hour SO2 design values (based on the 4th highest daily 

maximum 1-hour average SO2 concentration) for the base, future, and future-base scenarios. 

Modeled values for the base year are generally below the NAAQS except in the immediate vicinity of 

some major point sources. Sources in areas with deepwater platforms are evident with maximum 

values up to 50 ppb. Concentrations decrease in most locations in the future year scenario as 

sources are retired or apply control equipment with projected maximum impacts all below the 

NAAQS. No increases in excess of 5 ppb are modeled along the Gulf Coast or over the open 

ocean.

Contributions of source groups to the modeled 1-hour SO2 concentrations are shown in 

Figure D-61. New sources associated with the 2017-2022 GOM Multisale EIS (from which this 

Supplemental EIS tiers) scenario (Source Group B) are modeled to contribute less than 1 ppb.

Figure D-62 displays modeled 3-hour SO2 design values (based on the annual 2nd highest 

block, 3-hour average SO2 concentration) for the base, future, and future-base scenarios. All 

modeled values are below the NAAQS (500 ppb). These results are similar to those for the 1-hour 

SO2 described above.

Contributions of source groups to the modeled 3-hour SO2 concentrations are shown in 

Figure D-63. Results are similar to those for the 1-hour SO2 concentrations described above.
Air Quality: Cumulative and Visibility Impacts D-115

Figure D-60. Modeled 4th Highest Daily Maximum 1-hour SO2 Concentrations for the Base Year (top 

left), Future Year (top right), and the Future – Base Difference (bottom). 
D-116 2018 Gulf of Mexico Supplemental EIS

Figure D-61. Contributions of Source Group A (top left), B (top right), C (middle left), D (middle right), and 

E (bottom) to the Future Year All-sources 4th Highest Daily Maximum 1-hour SO2

Concentration (note different color scales used in each panel).
Air Quality: Cumulative and Visibility Impacts D-117

Figure D-62. Modeled Annual 2nd Highest Block 3-hour SO2 Concentrations for the Base Year (top left), 

Future Year (top right), and the Future – Base Difference (bottom).
D-118 2018 Gulf of Mexico Supplemental EIS

Figure D-63. Contributions of Source Group A (top left), B (top right), C (middle left), D (middle right), 

and E (bottom) to the Future Year All-sources 2nd Highest 3-hour Block Average SO2

Concentration (note different color scales used in each panel). 
Air Quality: Cumulative and Visibility Impacts D-119

D.7.1.5.4 CO

Results are presented here for both the 8-hour average (9 ppm) and 1-hour average 

(35 ppm) CO NAAQS. 

Figure D-64 displays modeled 8-hour CO design values (based on the annual 2nd highest 

nonoverlapping running 8-hour average) for the base, future, and future-base scenarios. Similarly, 

Figure D-65 displays modeled 1-hour CO design values (based on the annual 2nd highest daily 

maximum 1-hour average) for the base, future, and future-base scenarios. All values are below the 

NAAQS. The maximum predicted 8-hour design value in the future year is predicted to be 8.3 ppb at 

the entrance to the Freshwater Bayou Canal in Vermilion Parish, Louisiana. Differences between 

the base and future year scenarios are less than 3 ppm. 

Individual source group contributions to CO design values were not calculated as the CAMx

source apportionment methods do not include tracers for CO. 

Figure D-64. Modeled Annual 2nd Highest Non-overlapping Running 8-hour Average CO 

Concentrations for the Base Year (top left), Future Year (top right), and the 

Future – Base Difference (bottom).
D-120 2018 Gulf of Mexico Supplemental EIS

Figure D-65. Modeled Annual 2nd Highest 1-hour Average CO Concentrations for the Base Year (top 

left), Future Year (top right), and the Future – Base Difference (bottom).

D.7.2 PSD Increments

Incremental impacts of each source group at Class I and sensitive Class II areas were 

calculated for all pollutants for which PSD increments have been set (NO2, SO2, PM10, PM2.5). 

Increment consumption is based on the source group contribution calculated from the CAMx source 

contribution results. Increment consumption for 24-hour averages and the 3-hour average SO2 are 

based on the annual second highest values. Comparisons of impacts from the 2017-2022 GOM 

Multisale EIS (from which this Supplemental EIS tiers) scenario with maximum allowed PSD 

increments are presented here as an evaluation of a “threshold of concern” for potentially significant 

adverse impacts, but they do not represent a regulatory PSD increment consumption analysis. 

Results of the PSD increments analysis are summarized in Table D-24 in terms of the 

maximum increment consumption over all Class I/II areas within the 4-km modeling domain. 

Maximum impacts occur at the Breton Wilderness Class I area for all PSD pollutants and averaging 

times. Concentration increments from Source Groups A and B are less than the maximum allowed 
Air Quality: Cumulative and Visibility Impacts D-121

PSD increments for all pollutants and averaging times except for the 24-hour PM2.5 increment from 

Source Group B at the Breton Wilderness Class I area where the maximum impact (2.19 μg/m3

) 

exceeds the Class I PSD increment (2 μg/m3

) by just under 10%. The maximum Source Group A 

24-hour average PM2.5 increment is 0.53 μg/m3

, indicating that support vessels or helicopter traffic 

associated with new offshore platforms, rather than emissions from the platforms themselves, are 

largely responsible for pushing the maximum impact above the Class I PSD increment at Breton 

Wilderness. The 24-hour PM2.5 impact from Source Group B averaged over all grid cells covering 

the Breton Wilderness Class I area is 1.79 μg/m3

. Maximum impacts from Source Group C exceed 

the annual and 24-hour PM2.5, the 24-hour PM10, and the annual NO2 Class I PSD increments at 

Breton Wilderness. A summary of impacts from Source Groups A, B, and C for all Class I/II areas is 

provided in Table D-25. 

Table D-24. Maximum Source Group Contributions for PSD Pollutants at Class I and Sensitive Class II 

Areas in the 4-km Modeling Domain. 

Group Max @ Any 

Class I Area

Percent of PSD 

Class I 

Increment

Class I Area 

Where Max 

Occurred

Max @ Any 

Class II Area

Percent of 

PSD Class II 

Increment

Class II Area 

Where Max 

Occurred

PM10 Annual (Increment = 4 μg/m3, 17 μg/m3)

A 0.04449 1.1% Breton Wilderness 0.04196 0.2% Gulf Islands NS

B 0.29475 7.4% Breton Wilderness 0.35482 2.1% Gulf Islands NS

C 1.44391 36.1% Breton Wilderness 1.24095 7.3% Gulf Islands NS

PM10 24-Hour (Class I, II Increment = 8 μg/m3, 30 μg/m3)

A 0.53529 6.7% Breton Wilderness 0.61362 2.0% Gulf Islands NS

B 2.19999 27.5% Breton Wilderness 2.45061 8.2% Gulf Islands NS

C 14.4191 180.2% Breton Wilderness 13.9928 46.6% Gulf Islands NS

PM2.5 Annual (Class I, II Increment = 1 μg/m3, 4 μg/m3)

A 0.04449 4.4% Breton Wilderness 0.04196 1.0% Gulf Islands NS

B 0.29152 29.2% Breton Wilderness 0.34969 8.7% Gulf Islands NS

C 1.43641 143.6% Breton Wilderness 1.23711 30.9% Gulf Islands NS

PM2.5 24-Hour (Class I, II Increment = 2 μg/m3, 9 μg/m3)

A 0.53527 26.8% Breton Wilderness 0.6136 6.8% Gulf Islands NS

B 2.19194 109.6% Breton Wilderness 2.44002 27.1% Gulf Islands NS

C 14.3964 719.8% Breton Wilderness 13.9795 155.3% Gulf Islands NS

NO2 Annual (Class I, II Increment = 2.5 μg/m3, 25 μg/m3)

A 0.12789 5.1% Breton Wilderness 0.14467 0.6% Gulf Islands NS

B 0.65768 26.3% Breton Wilderness 0.93535 3.7% Gulf Islands NS

C 2.61628 104.7% Breton Wilderness 1.95517 7.8% Breton NWR

SO2 Annual (Class I, II Increment = 2 μg/m3, 20 μg/m3)

A 0.00113 0.1% Breton Wilderness 0.00121 0.0% Gulf Islands NS

B 0.00271 0.1% Breton Wilderness 0.00178 0.0% Gulf Islands NS

C 0.0684 3.4% Breton Wilderness 0.05601 0.3% Breton NWR

SO2 24-Hour (Class I, II Increment = 5 μg/m3, 91 μg/m3)

A 0.01009 0.2% Breton Wilderness 0.01104 0.0% Breton NWR

B 0.01891 0.4% Breton Wilderness 0.0156 0.0% Breton NWR

C 0.53913 10.8% Breton Wilderness 0.41742 0.5% Breton NWR
D-122 2018 Gulf of Mexico Supplemental EIS

Group Max @ Any 

Class I Area

Percent of PSD 

Class I 

Increment

Class I Area 

Where Max 

Occurred

Max @ Any 

Class II Area

Percent of 

PSD Class II 

Increment

Class II Area 

Where Max 

Occurred

SO2 3-Hour (Class I, II Increment = 25 μg/m3, 512 μg/m3)

A 0.02228 0.1% Breton Wilderness 0.01655 0.0% Breton NWR

B 0.03451 0.1% Breton Wilderness 0.02296 0.0% Breton NWR

C 1.17783 4.7% Breton Wilderness 1.03688 0.2% Breton NWR

NS = National Seashore; NWR = National Wildlife Refuge.

D.7.3 AQRV Impacts

D.7.3.1 Visibility

Incremental visibility impacts were calculated for each source group as well as the 

cumulative impact of all sources combined. The approach used the incremental concentrations as 

quantified by the CAMx PSAT source apportionment tool simulation for each source group. 

Changes in light extinction from CAMx model concentration increments due to emissions from each 

source group were calculated for each day at grid cells that intersect Class I and sensitive Class II 

areas within the 12-km modeling domain. 

Calculation of incremental visibility impacts followed procedures recommended by the 

Federal Land Managers (FLAG, 2010) as described in Section D.6.2.3.1. 

For each individual source group, the estimated visibility degradation at each Class I and 

sensitive Class II area in the 12-km modeling domain due to emissions from the source group are 

presented in terms of the number of days that exceed a threshold change in deciview (∆dv) relative 

to background conditions. The number of days with a ∆dv greater than 0.5 and 1.0 are reported.

Results of the FLAG (2010) incremental visibility impact assessment for Source Groups A 

and B are presented in Tables D-26 and D-27, respectively. For Source Group A, the annual 

8th highest ∆dv exceed the 1.0 threshold at Breton Wilderness, Breton National Wildlife Refuge, and 

Gulf Islands National Seashore. Incremental impacts for Source Group B are larger and include 

days with the 8th highest ∆dv greater than 1.0 at Padre Island National Seashore in addition to the 

areas mentioned above, as well as values greater than 0.5 at Chassahowitzka Wilderness and 

St. Marks National Wildlife Refuge. 
Air Quality: Cumulative and Visibility Impacts D-123

Table D-25. Source Group Contributions for PSD Pollutants at All Class I and Sensitive Class II Areas in the 4-km Modeling Domain.

Source Group A

Pollutant NO2 (μg/m3) PM10 (μg/m3) PM25 (μg/m3) SO2 (μg/m3)

Averaging Time Annual3 24-hour2 Annual3 24-hour4 Annual3 3-hour2 24-hour2 Annual3

Class I State Owner PSD Class I Increment1

2.5 8 4 2 1 25 5 2

Breton Wilderness LA FWS 0.128 0.535 0.044 0.535 0.044 0.022 0.010 0.001

Class II State Owner PSD Class II Increment1

25 30 17 9 4 512 91 20

Breton NWR LA FWS 0.063 0.436 0.036 0.436 0.036 0.017 0.011 0.001

Gulf Islands NS FL,MS NPS 0.145 0.614 0.042 0.614 0.042 0.014 0.007 0.001

Padre Island NS TX NPS 0.014 0.169 0.014 0.169 0.014 0.006 0.002 0.000

Source Group B

Pollutant NO2 (μg/m3) PM10 (μg/m3) PM25 (μg/m3) SO2 (μg/m3)

Averaging Time Annual3 24-hour2 Annual3 24-hour4 Annual3 3-hour2 24-hour2 Annual3

Class I State Owner PSD Class I Increment1

2.5 8 4 2 1 25 5 2

Breton Wilderness LA FWS 0.658 2.200 0.295 2.192 0.292 0.035 0.019 0.003

Class II State Owner PSD Class II Increment1

25 30 17 9 4 512 91 20

Breton NWR LA FWS 0.321 1.752 0.182 1.748 0.181 0.023 0.016 0.002

Gulf Islands NS FL,MS NPS 0.935 2.451 0.355 2.440 0.350 0.017 0.008 0.002

Padre Island NS TX NPS 0.181 1.013 0.166 1.012 0.165 0.006 0.003 0.001

Source Group C

Pollutant NO2 (μg/m3) PM10 (μg/m3) PM25 (μg/m3) SO2 (μg/m3)

Averaging Time Annual3 24-hour2 Annual3 24-hour4 Annual3 3-hour2 24-hour2 Annual3

Class I State Owner PSD Class I Increment1

2.5 8 4 2 1 25 5 2

Breton Wilderness LA FWS 2.616 14.419 1.444 14.396 1.436 1.178 0.539 0.068

Class II State Owner PSD Class II Increment1

25 30 17 9 4 512 91 20

Breton NWR LA FWS 1.955 12.577 1.127 12.559 1.122 1.037 0.417 0.056

Gulf Islands NS FL,MS NPS 1.521 13.993 1.241 13.979 1.237 0.410 0.196 0.016

Padre Island NS TX NPS 0.198 2.031 0.225 2.030 0.224 0.044 0.022 0.002

NS = National Seashore; NWR = National Wildlife Refuge.

1 The PSD demonstrations serve information purposes only and do not constitute a regulatory PSD increment consumption analysis.

2 Based on 2nd highest 24-hour average. 3 Annual arithmetic mean.

4 Based on 2nd highest 24-hour average.
D-124 2018 Gulf of Mexico Supplemental EIS

Table D-26. Incremental Visibility Impacts Relative to Natural Background Conditions from Source 

Group A.

Area Max ∆dv 8th High ∆dv

No. of Days

>1.0 >0.5

Class I Areas

Bandelier National Monument 0.00067 0.00016 0 0

Black Canyon of the Gunnison National Park 0.00002 0.00000 0 0

Bosque del Apache National Wildlife Refuge 0.00050 0.00018 0 0

Bosque del Apache (Chupadera Unit) Wilderness 0.00036 0.00013 0 0

Bosque del Apache (Indian Well Unit) Wilderness 0.00036 0.00014 0 0

Bosque del Apache (Little San Pascual Unit) Wilderness 0.00072 0.00023 0 0

Big Bend National Park 0.00746 0.00286 0 0

Bradwell Bay Wilderness 0.08487 0.05269 0 0

Breton Wilderness 2.65806 1.54415 22 57

Caney Creek Wilderness 0.21478 0.07569 0 0

Cape Romain Wilderness 0.08319 0.01800 0 0

Carlsbad Caverns National Park 0.00337 0.00163 0 0

Chassahowitzka Wilderness 0.26500 0.11299 0 0

Cohutta Wilderness 0.07214 0.02483 0 0

Dolly Sods Wilderness 0.01130 0.00424 0 0

Eagles Nest Wilderness 0.00009 0.00001 0 0

Everglades National Park 0.13374 0.04721 0 0

Flat Tops Wilderness 0.00002 0.00000 0 0

Great Sand Dunes National Monument 0.00020 0.00006 0 0

Great Smoky Mountains National Park 0.02866 0.01263 0 0

Guadalupe Mountains National Park 0.00283 0.00094 0 0

Hercules-Glades Wilderness 0.05899 0.02394 0 0

James River Face Wilderness 0.00768 0.00391 0 0

Joyce-Kilmer-Slickrock Wilderness 0.02655 0.00881 0 0

La Garita Wilderness 0.00013 0.00001 0 0

Linville Gorge Wilderness 0.01892 0.00436 0 0

Mammoth Cave National Park 0.04330 0.01815 0 0

Maroon Bells-Snowmass Wilderness 0.00007 0.00001 0 0

Mingo National Wildlife Refuge 0.07764 0.04615 0 0

Mount_Zirkel Wilderness 0.00002 0.00000 0 0

Okefenokee National Wildlife Refuge 0.06476 0.03510 0 0

Otter Creek Wilderness 0.01108 0.00356 0 0

Pecos Wilderness 0.00091 0.00023 0 0

Rawah Wilderness 0.00005 0.00001 0 0

Rocky Mountain National Park 0.00023 0.00003 0 0

Saint Marks National Wildlife Refuge 0.24139 0.19294 0 0

Salt Creek Wilderness 0.00278 0.00149 0 0

San Pedro Parks Wilderness 0.00038 0.00010 0 0

Shenandoah National Park 0.02361 0.00945 0 0

Shining Rock Wilderness 0.02231 0.01030 0 0

Sipsey Wilderness 0.09946 0.02484 0 0
Air Quality: Cumulative and Visibility Impacts D-125

Area Max ∆dv 8th High ∆dv No. of Days

>1.0 >0.5

Swanquarter National Wildlife Refuge 0.01852 0.00864 0 0

Upper Buffalo Wilderness 0.05460 0.02255 0 0

Weminuche Wilderness 0.00018 0.00002 0 0

West Elk Wilderness 0.00006 0.00001 0 0

Wheeler Peak Wilderness 0.00037 0.00012 0 0

White Mountain Wilderness 0.00085 0.00042 0 0

Wichita Mountains National Wildlife Refuge 0.02963 0.01625 0 0

Wichita Mountains (Charons Garden Unit) Wilderness 0.02932 0.01390 0 0

Wichita Mountains (North Mountain Unit) Wilderness 0.02983 0.01408 0 0

Wolf Island Wilderness 0.10444 0.02825 0 0

Class II Areas

Breton National Wildlife Refuge 2.51391 1.44000 13 41

Gulf Islands National Seashore 3.59820 1.79194 26 64

Padre Island National Seashore 1.28497 0.44893 2 5

Table D-27. Incremental Visibility Impacts Relative to Natural Background Conditions from Source 

Group B.

Area Max ∆dv 8th High ∆dv No. of Days

>1.0 >0.5

Class I Areas

Bandelier NM 0.00588 0.00225 0 0

Black Canyon of the Gunnison National Park 0.00027 0.00003 0 0

Bosque del Apache National Wildlife Refuge 0.00927 0.00254 0 0

Bosque del Apache (Chupadera Unit) Wilderness 0.00674 0.00173 0 0

Bosque del Apache (Indian Well Unit) Wilderness 0.00692 0.00183 0 0

Bosque del Apache (Little San Pascual Unit) Wilderness 0.01274 0.00311 0 0

Big Bend National Park 0.06000 0.03458 0 0

Bradwell Bay Wilderness 0.43077 0.29328 0 0

Breton Wilderness 7.77098 6.27094 155 256

Caney Creek Wilderness 1.37302 0.48258 1 7

Cape Romain Wilderness 0.31147 0.08130 0 0

Carlsbad Caverns National Park 0.03024 0.01639 0 0

Chassahowitzka Wilderness 1.35442 0.55791 3 9

Cohutta Wilderness 0.37888 0.12203 0 0

Dolly Sods Wilderness 0.06063 0.03063 0 0

Eagles Nest Wilderness 0.00128 0.00016 0 0

Everglades National Park 0.72032 0.18655 0 2

Flat Tops Wilderness 0.00022 0.00003 0 0

Great Sand Dunes National Monument 0.00329 0.00067 0 0

Great Smoky Mountains National Park 0.15002 0.07991 0 0

Guadalupe Mountains National Park 0.02529 0.01502 0 0

Hercules-Glades Wilderness 0.41027 0.16105 0 0

James River Face Wilderness 0.05739 0.02478 0 0
D-126 2018 Gulf of Mexico Supplemental EIS

Joyce-Kilmer-Slickrock Wilderness 0.15156 0.07538 0 0

La Garita Wilderness 0.00252 0.00019 0 0

Linville Gorge Wilderness 0.10346 0.03554 0 0

Mammoth Cave National Park 0.23624 0.09683 0 0

Maroon Bells-Snowmass Wilderness 0.00103 0.00006 0 0

Mingo National Wildlife Refuge 0.44782 0.25368 0 0

Mount_Zirkel Wilderness 0.00019 0.00003 0 0

Okefenokee National Wildlife Refuge 0.40346 0.21507 0 0

Otter Creek Wilderness 0.06577 0.02996 0 0

Pecos Wilderness 0.00863 0.00303 0 0

Rawah Wilderness 0.00062 0.00016 0 0

Rocky Mountain National Park 0.00128 0.00028 0 0

Saint Marks National Wildlife Refuge 1.04546 0.79486 2 23

Salt Creek Wilderness 0.03543 0.01558 0 0

San Pedro Parks Wilderness 0.00562 0.00171 0 0

Shenandoah National Park 0.13636 0.05190 0 0

Shining Rock Wilderness 0.12422 0.06132 0 0

Sipsey Wilderness 0.47703 0.15148 0 0

Swanquarter National Wildlife Refuge 0.09369 0.04563 0 0

Upper Buffalo Wilderness 0.42865 0.16699 0 0

Weminuche Wilderness 0.00268 0.00031 0 0

West Elk Wilderness 0.00100 0.00006 0 0

Wheeler Peak Wilderness 0.00491 0.00148 0 0

White Mountain Wilderness 0.01424 0.00635 0 0

Wichita Mountains National Wildlife Refuge 0.19286 0.10693 0 0

Wichita Mountains (Charons Garden Unit) Wilderness 0.18960 0.08842 0 0

Wichita Mountains (North Mountain Unit) Wilderness 0.19390 0.09435 0 0

Wolf Island Wilderness 0.39934 0.13342 0 0

Class II Areas

Breton National Wildlife Refuge 7.10912 4.34015 104 193

Gulf Islands National Seashore 10.54646 6.33562 198 311

Padre Island National Seashore 5.10452 3.05326 115 204

D.7.3.1.2 Cumulative Visibility Analysis

For the cumulative visibility impacts analysis, the MATS software was applied with observed 

PM species concentrations and monthly average relative humidity from IMPROVE monitoring sites 

to calculate daily visibility impairment at Class I areas from which the W20% and B20% visibility days 

metrics are determined as described in Section D.7.2.3.1. Since not all Class I areas have a colocated IMPROVE monitoring site, IMPROVE observations were mapped to nearby Class I areas 

that did not include an IMPROVE monitor. In Table D-28, the Class I area of interest is shown in the 

first column and the IMPROVE site used to represent observed visibility at the Class I area is shown 

in the third column. For example, the IMPROVE data from Dolly Sods Wilderness was used to 

represent observed visibility for both Dolly Sods Wilderness and Otter Creek Wilderness. The MATS 

includes mappings of IMPROVE site to Class I areas. However, MATS does not include a mapping 
Air Quality: Cumulative and Visibility Impacts D-127

for the Breton Wilderness or Bradwell Bay Class I areas and, therefore, cumulative visibility results 

for these areas are not included in this analysis.

Tables D-28 and D-29 resent results for the W20% visibility days, and Tables D-30

and D-31 present results for the B20% visibility days. Visibility improvement between the base and 

future year scenarios (i.e., positive BY-FY results in Tables D-29 and D-31) are seen at most Class I 

areas, with eight areas experiencing reductions in visibility on the W20% days. All of these areas 

are in New Mexico and Colorado, and Gulf of Mexico sources (Source Group D) contribute less than 

0.02 dv to visibility impairment in these areas. The maximum contribution from new platforms and 

support vessels and helicopters associated with the 2017-2022 GOM Multisale EIS (from which this 

Supplemental EIS tiers) scenario (Source Group B) to any area on the W20% days is 0.04 dv at 

Caney Creek, Arkansas. Contributions from all Gulf of Mexico sources (Source Group D) are the 

greatest (0.34 dv) at St. Marks National Wildlife Refuge, Florida. 

For the B20% visibility days, 11 areas experience reductions in visibility. All but one of these 

areas are located in New Mexico and Colorado; the lone exception is Big Bend National Park in 

Texas. Contributions from Gulf of Mexico sources to these 11 areas are all less than 0.01 dv. The 

maximum contribution from new platforms and support vessels and helicopters associated with the 

2017-2022 GOM Multisale EIS (from which this Supplemental EIS tiers) (Source Group B) to any 

area on the B20% days is 0.01 dv, which occurs at several sites. Contributions from all Gulf of 

Mexico sources (Source Group D) are the greatest (0.08 dv) at St. Marks Wilderness in Florida. 
 

D-128 2018 Gulf of Mexico Supplemental EIS

Table D-28. Cumulative Visibility Results for 20% Worst Visibility Days (W20%) at Class I Areas for Base (2012) Year (BY) and Future Year (FY) 

Scenarios with All Sources Included and with Contributions from Each Source Group Removed.

FY DV without Source Group

Class I Name State IMPROVE Site BY DV FY DV A B C D E

Bandelier NM NM BAND1 11.79 11.93 11.93 11.93 11.93 11.93 7.56

Big Bend NP TX BIBE1 16.40 16.11 16.11 16.11 16.10 16.09 11.13

Black Canyon of the Gunnison NM CO WEMI1 10.11 10.05 10.05 10.05 10.05 10.05 9.34

Bosque del Apache NM BOAP1 13.65 13.90 13.90 13.90 13.90 13.90 10.69

Caney Creek Wilderness AR CACR1 22.66 20.59 20.58 20.55 20.45 20.36 13.36

Carlsbad Caverns NP TX GUMO1 15.17 15.14 15.14 15.14 15.14 15.14 9.33

Chassahowitzka FL CHAS1 21.77 20.43 20.43 20.41 20.35 20.18 11.45

Cohutta Wilderness GA COHU1 23.94 21.11 21.11 21.11 21.09 21.06 12.89

Dolly Sods Wilderness WV DOSO1 23.45 19.52 19.52 19.52 19.52 19.51 14.64

Eagles Nest Wilderness CO WHRI1 8.81 8.72 8.72 8.72 8.72 8.72 7.84

Everglades NP FL EVER1 18.33 17.63 17.63 17.63 17.63 17.51 15.00

Flat Tops Wilderness CO WHRI1 8.81 8.72 8.72 8.72 8.72 8.72 7.84

Great Sand Dunes NM CO GRSA1 11.52 11.62 11.62 11.62 11.62 11.62 8.94

Great Smoky Mountains NP TN GRSM1 23.75 20.30 20.30 20.29 20.29 20.28 13.84

Guadalupe Mountains NP TX GUMO1 15.17 15.14 15.14 15.14 15.14 15.14 9.33

Hercules-Glades Wilderness MO HEGL1 23.50 21.48 21.47 21.46 21.42 21.37 13.21

James River Face Wilderness VA JARI1 23.50 20.75 20.75 20.74 20.74 20.73 16.07

Joyce-Kilmer-Slickrock Wilderness TN GRSM1 23.75 20.30 20.30 20.29 20.29 20.28 13.84

La Garita Wilderness CO WEMI1 10.11 10.05 10.05 10.05 10.05 10.05 9.34

Linville Gorge Wilderness NC LIGO1 22.61 19.38 19.38 19.37 19.37 19.36 13.29

Maroon Bells-Snowmass Wilderness CO WHRI1 8.81 8.72 8.72 8.72 8.72 8.72 7.84

Mammoth Cave NP KY MACA1 26.11 22.68 22.68 22.68 22.67 22.66 14.97

Mount Zirkel Wilderness CO MOZI1 9.33 9.20 9.20 9.20 9.20 9.20 7.25

Okefenokee GA OKEF1 23.31 21.99 21.99 21.98 21.93 21.87 12.62

Otter Creek Wilderness WV DOSO1 23.45 19.52 19.52 19.52 19.52 19.51 14.64

Pecos Wilderness NM WHPE1 10.04 10.10 10.10 10.10 10.10 10.10 6.73

Rawah Wilderness CO MOZI1 9.33 9.20 9.20 9.20 9.20 9.20 7.25

Cape Romain SC ROMA1 23.40 21.77 21.77 21.77 21.73 21.68 13.12

Rocky Mountain NP CO ROMO1 12.02 11.86 11.86 11.86 11.86 11.86 9.19
Table D-28. Cumulative Visibility Results for 20% Worst Visibility Days (W20%) at Class I Areas for Base (2012) Year (BY) and Future Year (FY) 

Scenarios with All Sources Included and with Contributions from Each Source Group Removed. (continued)

Air Quality: Cumulative and Visibility Impacts D-129

FY DV without Source Group

Class I Name State IMPROVE Site BY DV FY DV A B C D E

Salt Creek NM SACR1 17.22 17.79 17.79 17.79 17.79 17.78 7.30

St. Marks FL SAMA1 23.01 21.18 21.18 21.16 21.06 20.84 13.43

San Pedro Parks Wilderness NM SAPE1 9.94 9.98 9.98 9.98 9.98 9.98 7.15

Shenandoah NP VA SHEN1 22.95 19.42 19.42 19.42 19.41 19.39 14.90

Shining Rock Wilderness NC SHRO1 21.90 18.78 18.78 18.77 18.77 18.76 12.25

Sipsey Wilderness AL SIPS1 23.98 21.48 21.48 21.47 21.46 21.44 13.01

Swanquarter NC SWAN1 22.29 20.39 20.39 20.39 20.38 20.37 13.42

Upper Buffalo Wilderness AR UPBU1 22.93 20.90 20.89 20.87 20.79 20.71 12.97

West Elk Wilderness CO WHRI1 8.81 8.72 8.72 8.72 8.72 8.72 7.84

Weminuche Wilderness CO WEMI1 10.11 10.05 10.05 10.05 10.05 10.05 9.34

White Mountain Wilderness NM WHIT1 14.24 14.60 14.60 14.60 14.59 14.59 8.15

Wheeler Peak Wilderness NM WHPE1 10.04 10.10 10.10 10.10 10.10 10.10 6.73

Wichita Mountains OK WIMO1 21.55 20.33 20.33 20.32 20.31 20.30 10.33

Wolf Island GA OKEF1 23.31 21.99 21.99 21.98 21.93 21.87 12.62

NM = National Monument; NP = National Park.
. 

D-130 2018 Gulf of Mexico Supplemental EIS

Table D-29. Differences in Cumulative Visibility Results for 20% Worst Visibility Days (W20%) at Class I Areas Between the Future Year (FY) and 

Base Year (BY) Scenarios and Contributions of Each Source Group to the Future Year Scenario Visibility. 

FY DV without Source Group

Class I Name State IMPROVE Site BYFY DV A B C D E

Bandelier NM NM BAND1 -0.14 0.00 0.00 0.00 0.00 4.37

Big Bend NP TX BIBE1 0.29 0.00 0.00 0.01 0.02 4.98

Black Canyon of the Gunnison NM CO WEMI1 0.06 0.00 0.00 0.00 0.00 0.71

Bosque del Apache NM BOAP1 -0.25 0.00 0.00 0.00 0.00 3.21

Caney Creek Wilderness AR CACR1 2.07 0.01 0.04 0.14 0.23 7.23

Carlsbad Caverns NP TX GUMO1 0.03 0.00 0.00 0.00 0.00 5.81

Chassahowitzka FL CHAS1 1.34 0.00 0.02 0.08 0.25 8.98

Cohutta Wilderness GA COHU1 2.83 0.00 0.00 0.02 0.05 8.22

Dolly Sods Wilderness WV DOSO1 3.93 0.00 0.00 0.00 0.01 4.88

Eagles Nest Wilderness CO WHRI1 0.09 0.00 0.00 0.00 0.00 0.88

Everglades NP FL EVER1 0.70 0.00 0.00 0.00 0.12 2.63

Flat Tops Wilderness CO WHRI1 0.09 0.00 0.00 0.00 0.00 0.88

Great Sand Dunes NM CO GRSA1 -0.10 0.00 0.00 0.00 0.00 2.68

Great Smoky Mountains NP TN GRSM1 3.45 0.00 0.01 0.01 0.02 6.46

Guadalupe Mountains NP TX GUMO1 0.03 0.00 0.00 0.00 0.00 5.81

Hercules-Glades Wilderness MO HEGL1 2.02 0.01 0.02 0.06 0.11 8.27

James River Face Wilderness VA JARI1 2.75 0.00 0.01 0.01 0.02 4.68

Joyce-Kilmer-Slickrock Wilderness TN GRSM1 3.45 0.00 0.01 0.01 0.02 6.46

La Garita Wilderness CO WEMI1 0.06 0.00 0.00 0.00 0.00 0.71

Linville Gorge Wilderness NC LIGO1 3.23 0.00 0.01 0.01 0.02 6.09

Maroon Bells-Snowmass Wilderness CO WHRI1 0.09 0.00 0.00 0.00 0.00 0.88

Mammoth Cave NP KY MACA1 3.43 0.00 0.00 0.01 0.02 7.71

Mount Zirkel Wilderness CO MOZI1 0.13 0.00 0.00 0.00 0.00 1.95

Okefenokee GA OKEF1 1.32 0.00 0.01 0.06 0.12 9.37

Otter Creek Wilderness WV DOSO1 3.93 0.00 0.00 0.00 0.01 4.88

Pecos Wilderness NM WHPE1 -0.06 0.00 0.00 0.00 0.00 3.37

Rawah Wilderness CO MOZI1 0.13 0.00 0.00 0.00 0.00 1.95

Cape Romain SC ROMA1 1.63 0.00 0.00 0.04 0.09 8.65

Rocky Mountain NP CO ROMO1 0.16 0.00 0.00 0.00 0.00 2.67
Table D-29. Differences in Cumulative Visibility Results for 20% Worst Visibility Days (W20%) at Class I Areas Between the Future Year (FY) and 

Base Year (BY) Scenarios and Contributions of Each Source Group to the Future Year Scenario Visibility (continued)

Air Quality: Cumulative and Visibility Impacts D-131

FY DV without Source Group

Class I Name State IMPROVE Site BYFY DV A B C D E

Salt Creek NM SACR1 -0.57 0.00 0.00 0.00 0.01 10.49

St. Marks FL SAMA1 1.83 0.00 0.02 0.12 0.34 7.75

San Pedro Parks Wilderness NM SAPE1 -0.04 0.00 0.00 0.00 0.00 2.83

Shenandoah NP VA SHEN1 3.53 0.00 0.00 0.01 0.03 4.52

Shining Rock Wilderness NC SHRO1 3.12 0.00 0.01 0.01 0.02 6.53

Sipsey Wilderness AL SIPS1 2.50 0.00 0.01 0.02 0.04 8.47

Swanquarter NC SWAN1 1.90 0.00 0.00 0.01 0.02 6.97

Upper Buffalo Wilderness AR UPBU1 2.03 0.01 0.03 0.11 0.19 7.93

West Elk Wilderness CO WHRI1 0.09 0.00 0.00 0.00 0.00 0.88

Weminuche Wilderness CO WEMI1 0.06 0.00 0.00 0.00 0.00 0.71

White Mountain Wilderness NM WHIT1 -0.36 0.00 0.00 0.01 0.01 6.45

Wheeler Peak Wilderness NM WHPE1 -0.06 0.00 0.00 0.00 0.00 3.37

Wichita Mountains OK WIMO1 1.22 0.00 0.01 0.02 0.03 10.00

Wolf Island GA OKEF1 1.32 0.00 0.01 0.06 0.12 9.37

NM = National Monument; NP = National Park.
D-132 2018 Gulf of Mexico Supplemental EIS

Table D-30. Cumulative Visibility Results for 20% Best Visibility Days (B20%) at Class I Areas for Base 

(2012) Year (BY) and Future Year (FY) Scenarios with All Sources Included and with 

Contributions from Each Source Group Removed. 

FY DV without Source Group

Class I Name State IMPROVE 

Site

BY 

DV

FY 

DV A B C D E 

Bandelier NM NM BAND1 3.81 3.96 3.96 3.96 3.96 3.96 1.51

Big Bend NP TX BIBE1 5.76 5.86 5.86 5.86 5.86 5.86 3.50

Black Canyon of the 

Gunnison NM CO WEMI1 2.04 2.18 2.18 2.18 2.18 2.18 1.55

Bosque del Apache NM BOAP1 5.57 5.60 5.60 5.60 5.60 5.60 3.60

Caney Creek 

Wilderness AR CACR1 9.82 9.25 9.25 9.24 9.22 9.20 5.15

Carlsbad Caverns NP TX GUMO1 5.08 5.03 5.03 5.03 5.03 5.03 2.39

Chassahowitzka FL CHAS1 14.05 13.55 13.55 13.54 13.52 13.34 8.22

Cohutta Wilderness GA COHU1 11.47 10.59 10.59 10.59 10.59 10.58 4.62

Dolly Sods Wilderness WV DOSO1 9.18 8.38 8.38 8.38 8.38 8.37 5.63

Eagles Nest Wilderness CO WHRI1 0.48 0.39 0.39 0.39 0.39 0.39 0.00

Everglades NP FL EVER1 11.29 11.08 11.08 11.07 11.06 10.99 8.01

Flat Tops Wilderness CO WHRI1 0.48 0.39 0.39 0.39 0.39 0.39 0.00

Great Sand Dunes NM CO GRSA1 3.57 3.56 3.56 3.56 3.56 3.56 2.20

Great Smoky Mountains 

NP TN GRSM1 11.10 9.78 9.78 9.78 9.78 9.77 4.22

Guadalupe Mountains 

NP TX GUMO1 5.08 5.03 5.03 5.03 5.03 5.03 2.39

Hercules-Glades 

Wilderness MO HEGL1 11.29 10.84 10.84 10.84 10.83 10.82 5.94

James River Face 

Wilderness VA JARI1 12.36 11.26 11.26 11.26 11.25 11.25 7.13

Joyce-Kilmer-Slickrock 

Wilderness TN GRSM1 11.10 9.78 9.78 9.78 9.78 9.77 4.22

La Garita Wilderness CO WEMI1 2.04 2.18 2.18 2.18 2.18 2.18 1.55

Linville Gorge 

Wilderness NC LIGO1 9.96 9.21 9.21 9.21 9.20 9.19 4.85

Maroon BellsSnowmass Wilderness CO WHRI1 0.48 0.39 0.39 0.39 0.39 0.39 0.00

Mammoth Cave NP KY MACA1 14.20 13.04 13.04 13.04 13.03 13.02 7.41

Mount Zirkel Wilderness CO MOZI1 0.89 0.79 0.79 0.79 0.79 0.79 0.00

Okefenokee GA OKEF1 13.40 12.89 12.89 12.89 12.88 12.85 7.58

Otter Creek Wilderness WV DOSO1 9.18 8.38 8.38 8.38 8.38 8.37 5.63

Pecos Wilderness NM WHPE1 1.09 1.24 1.24 1.24 1.24 1.24 0.00

Rawah Wilderness CO MOZI1 0.89 0.79 0.79 0.79 0.79 0.79 0.00

Cape Romain SC ROMA1 13.79 13.09 13.09 13.09 13.09 13.08 8.48

Rocky Mountain NP CO ROMO1 1.64 1.62 1.62 1.62 1.62 1.62 0.53

Salt Creek NM SACR1 7.11 7.42 7.42 7.42 7.42 7.42 2.89

St. Marks FL SAMA1 13.73 13.00 12.99 12.99 12.92 12.75 8.31

San Pedro Parks 

Wilderness NM SAPE1 1.30 1.37 1.37 1.37 1.37 1.37 0.61
Air Quality: Cumulative and Visibility Impacts D-133

FY DV without Source Group

Class I Name State IMPROVE 

Site

BY 

DV

FY 

DV A B C D E 

Shenandoah NP VA SHEN1 8.68 7.66 7.66 7.66 7.65 7.65 4.56

Shining Rock 

Wilderness NC SHRO1 6.58 5.81 5.80 5.80 5.79 5.79 2.03

Sipsey Wilderness AL SIPS1 13.10 12.20 12.20 12.19 12.16 12.13 6.79

Swanquarter NC SWAN1 11.76 11.09 11.09 11.08 11.08 11.08 7.45

Upper Buffalo 

Wilderness AR UPBU1 10.35 9.80 9.80 9.79 9.77 9.76 5.03

West Elk Wilderness CO WHRI1 0.48 0.39 0.39 0.39 0.39 0.39 0.00

Weminuche Wilderness CO WEMI1 2.04 2.18 2.18 2.18 2.18 2.18 1.55

White Mountain 

Wilderness NM WHIT1 3.24 3.45 3.45 3.45 3.45 3.45 1.41

Wheeler Peak 

Wilderness NM WHPE1 1.09 1.24 1.24 1.24 1.24 1.24 0.00

Wichita Mountains OK WIMO1 9.53 9.24 9.24 9.24 9.24 9.24 5.36

Wolf Island GA OKEF1 13.40 12.89 12.89 12.89 12.88 12.85 7.58

NM = National Monument; NP = National Park.

Table D-31. Differences in Cumulative Visibility Results for 20% Best Visibility Days (B20%) at Class I 

Areas Between the Future Year (FY) and Base Year (BY) Scenarios and Contributions of 

Each Source Group to the Future Year Scenario Visibility. 

Source Group Contribution to FY 

DV

Class I Name State IMPROVE 

Site

BY - FY 

DV A B C D E 

Bandelier NM NM BAND1 -0.15 0.00 0.00 0.00 0.00 2.45

Big Bend NP TX BIBE1 -0.10 0.00 0.00 0.00 0.00 2.36

Black Canyon of the Gunnison 

NM CO WEMI1 -0.14 0.00 0.00 0.00 0.00 0.63

Bosque del Apache NM BOAP1 -0.03 0.00 0.00 0.00 0.00 2.00

Caney Creek Wilderness AR CACR1 0.57 0.00 0.01 0.03 0.05 4.10

Carlsbad Caverns NP TX GUMO1 0.05 0.00 0.00 0.00 0.00 2.64

Chassahowitzka FL CHAS1 0.50 0.00 0.01 0.03 0.21 5.33

Cohutta Wilderness GA COHU1 0.88 0.00 0.00 0.00 0.01 5.97

Dolly Sods Wilderness WV DOSO1 0.80 0.00 0.00 0.00 0.01 2.75

Eagles Nest Wilderness CO WHRI1 0.09 0.00 0.00 0.00 0.00 0.39

Everglades NP FL EVER1 0.21 0.00 0.01 0.02 0.09 3.07

Flat Tops Wilderness CO WHRI1 0.09 0.00 0.00 0.00 0.00 0.39

Great Sand Dunes NM CO GRSA1 0.01 0.00 0.00 0.00 0.00 1.36

Great Smoky Mountains NP TN GRSM1 1.32 0.00 0.00 0.00 0.01 5.56

Guadalupe Mountains NP TX GUMO1 0.05 0.00 0.00 0.00 0.00 2.64

Hercules-Glades Wilderness MO HEGL1 0.45 0.00 0.00 0.01 0.02 4.90

James River Face Wilderness VA JARI1 1.10 0.00 0.00 0.01 0.01 4.13

Joyce-Kilmer-Slickrock 

Wilderness TN GRSM1 1.32 0.00 0.00 0.00 0.01 5.56
D-134 2018 Gulf of Mexico Supplemental EIS

Source Group Contribution to FY 

DV

Class I Name State IMPROVE 

Site

BY - FY 

DV A B C D E 

La Garita Wilderness CO WEMI1 -0.14 0.00 0.00 0.00 0.00 0.63

Linville Gorge Wilderness NC LIGO1 0.75 0.00 0.00 0.01 0.02 4.36

Maroon Bells-Snowmass 

Wilderness CO WHRI1 0.09 0.00 0.00 0.00 0.00 0.39

Mammoth Cave NP KY MACA1 1.16 0.00 0.00 0.01 0.02 5.63

Mount Zirkel Wilderness CO MOZI1 0.10 0.00 0.00 0.00 0.00 0.79

Okefenokee GA OKEF1 0.51 0.00 0.00 0.01 0.04 5.31

Otter Creek Wilderness WV DOSO1 0.80 0.00 0.00 0.00 0.01 2.75

Pecos Wilderness NM WHPE1 -0.15 0.00 0.00 0.00 0.00 1.24

Rawah Wilderness CO MOZI1 0.10 0.00 0.00 0.00 0.00 0.79

Cape Romain SC ROMA1 0.70 0.00 0.00 0.00 0.01 4.61

Rocky Mountain NP CO ROMO1 0.02 0.00 0.00 0.00 0.00 1.09

Salt Creek NM SACR1 -0.31 0.00 0.00 0.00 0.00 4.53

St. Marks FL SAMA1 0.73 0.01 0.01 0.08 0.25 4.69

San Pedro Parks Wilderness NM SAPE1 -0.07 0.00 0.00 0.00 0.00 0.76

Shenandoah NP VA SHEN1 1.02 0.00 0.00 0.01 0.01 3.10

Shining Rock Wilderness NC SHRO1 0.77 0.01 0.01 0.02 0.02 3.78

Sipsey Wilderness AL SIPS1 0.90 0.00 0.01 0.04 0.07 5.41

Swanquarter NC SWAN1 0.67 0.00 0.01 0.01 0.01 3.64

Upper Buffalo Wilderness AR UPBU1 0.55 0.00 0.01 0.03 0.04 4.77

West Elk Wilderness CO WHRI1 0.09 0.00 0.00 0.00 0.00 0.39

Weminuche Wilderness CO WEMI1 -0.14 0.00 0.00 0.00 0.00 0.63

White Mountain Wilderness NM WHIT1 -0.21 0.00 0.00 0.00 0.00 2.04

Wheeler Peak Wilderness NM WHPE1 -0.15 0.00 0.00 0.00 0.00 1.24

Wichita Mountains OK WIMO1 0.29 0.00 0.00 0.00 0.00 3.88

Wolf Island GA OKEF1 0.51 0.00 0.00 0.01 0.04 5.31

NM = National Monument; NP = National Park.

D.7.3.2 Acid Deposition

The CAMx-predicted wet and dry fluxes of sulfur- and nitrogen-containing species were 

processed to estimate total annual sulfur and nitrogen deposition values at each Class I and 

sensitive Class II area in the 12/4-km modeling domain. As described in Section D.6.2.3.2, the 

maximum annual sulfur and nitrogen deposition values from any grid cell that intersects a Class I or 

sensitive Class II receptor area was used to represent deposition for that area, in addition to the 

average annual deposition values of all grid cells that intersect a Class I or sensitive Class II 

receptor area. Maximum and average predicted sulfur and nitrogen deposition impacts were 

estimated separately for each source group and together across all source groups. 

As a screening analysis, incremental deposition values in Class I/II areas for combined 

Source Groups A (new platforms associated with the 2017-2022 GOM Multisale EIS scenario, from 

which this Supplemental EIS tiers) and B (new platforms and associated support vessels and 
Air Quality: Cumulative and Visibility Impacts D-135

helicopters associated with the 2017-2022 GOM Multisale EIS scenario, from which this 

Supplemental EIS tiers) were compared to the eastern and western U.S. Deposition Analysis 

Thresholds (DATs) listed in Table D-32. These DATs are specified in the FLAG guidance25 and are 

further described in Section D.6.2.3.2 above. Results of the incremental deposition analysis are 

summarized in Table D-33 for Class I/II areas in the 4-km modeling domain. Deposition results were 

also obtained for all other sensitive areas throughout the 12 km-modeling domain, but the highest 

deposition values all occurred within the 4-km domain. The dividing line between the eastern and 

western DATs specified in the FLAG guidance is the Mississippi River, which makes sense for most 

locations in the U.S. but it is not necessarily clear which DAT would be most appropriate for coastal 

locations along the Gulf of Mexico so results are compared here against both DATs. Note that 

comparisons of deposition impacts from cumulative sources as represented by Source Groups C, D, 

E, and F to the DAT are not appropriate. Incremental nitrogen deposition exceeds the western and 

eastern DATs at all three locations. Incremental sulfur deposition is below the DATs in all cases 

except the sulfur deposition from Source Group B at Breton Wilderness and Gulf Islands National 

Seashore, which exceeds the western DAT but not the eastern DAT. 

Table D-32. Deposition Analysis Threshold Values (kg/ha/yr) as 

Defined in the Federal Land Manager Guidance 

(FLAG, 2010).

Nitrogen Sulfur

East 0.010 0.010

West 0.005 0.005

Table D-33. Incremental Deposition Impacts from Source Groups A and B at Class I and Sensitive Class 

II Areas in the 4-km Domain.

Area

Source Group A Source Group B

Nitrogen Sulfur Nitrogen Sulfur

Max Avg Max Avg Max Avg Max Avg

Breton 

Wilderness 

Annual 

Deposition 0.0589 0.0501 0.0045 0.0039 0.3496 0.2701 0.0079 0.0061

Exceeds 

Eastern DAT? Yes Yes No No Yes Yes No No

Exceeds 

Western DAT? Yes Yes No No Yes Yes Yes Yes

Gulf Islands 

National 

Seashore

Annual 

Deposition 0.0909 0.0383 0.0046 0.0025 0.4560 0.2151 0.0064 0.0039

Exceeds 

Eastern DAT? Yes Yes No No Yes Yes No No

Exceeds 

Western 

DAT?

Yes Yes No No Yes Yes Yes No

 

25 Guidance on Nitrogen and Sulfur Deposition Analysis Thresholds (http://www.nature.nps.gov/air/Pubs/

pdf/flag/nsDATGuidance.pdf).
D-136 2018 Gulf of Mexico Supplemental EIS

Area

Source Group A Source Group B

Nitrogen Sulfur Nitrogen Sulfur

Max Avg Max Avg Max Avg Max Avg

Padre 

Island 

National 

Seashore

Annual 

Deposition 0.0458 0.0190 0.0012 0.0010 0.2410 0.1044 0.0019 0.0015

Exceeds 

Eastern DAT? Yes Yes No No Yes Yes No No

Exceeds 

Western DAT? Yes Yes No No Yes Yes No No

Cumulative deposition from all sources combined for the base case and future year 

scenarios were compared against applicable critical load levels in each Class I/II area for which 

critical loads were identified as described in Section D.6.2.3.2. Results are summarized in 

Table D-34. Cumulative nitrogen deposition is projected to decrease in all areas between the 2012 

base case and the 2017 future year, consistent with an overall reduction in NOx emissions. 

Nevertheless, maximum nitrogen deposition is modeled to continue exceeding the critical load 

thresholds under the future year scenario for all areas except the Padre Island National Seashore. 

Sulfur deposition values are lower, and larger sulfur emission reductions help to reduce sulfur 

deposition from above the critical load to below the critical load at Breton Wilderness, Breton 

National Wildlife Refuge, and Cohutta Wilderness (based on maximum grid cell values). 

Nevertheless, the maximum grid cell sulfur deposition still exceeds the critical load at the Gulf 

Islands National Seashore by a small margin.

Table D-34. Cumulative Nitrogen (N) and Sulfur (S) Deposition Impacts (kg/ha/yr) under the Base and 

Future Year Scenarios (shading indicates values exceeding the Critical Load threshold).

Class I/II Area Critical Load 

Threshold

2012 Base Case 2017 Future Year

NMaxNAvgSMaxSAvgNMaxNAvgSMaxSAvg

Big Bend National Park 3 3.6 2.5 2.3 1.1 3.6 2.5 2.2 1.0

Breton Wilderness 3 7.8 7.1 4.1 3.6 7.7 6.9 2.8 2.5

Breton National Wildlife 

Refuge 3 7.2 6.9 3.7 3.5 7.0 6.7 2.6 2.4

Gulf Islands National 

Seashore 3 13.8 7.0 5.3 4.4 13.0 6.7 3.6 2.9

Padre Island National 

Seashore 5 4.5 2.2 1.5 1.2 4.6 2.2 1.1 0.9

Bradwell Bay Wilderness 5 6.5 6.2 2.5 2.3 6.0 5.8 1.8 1.7

Saint Marks National 

Wildlife Refuge 3 6.8 5.2 2.5 2.0 6.2 4.7 1.8 1.5

Saint Marks Wilderness 3 6.1 4.9 2.0 1.9 5.6 4.5 1.5 1.4

Chassahowitzka 

Wilderness 3 6.8 6.1 2.5 2.5 6.0 5.4 1.9 1.9

Everglades National Park 5 7.5 4.7 3.9 2.2 6.9 4.5 2.4 1.7

Okefenokee National 

Wildlife Refuge 3 6.0 5.7 2.3 2.1 5.6 5.3 1.8 1.7

Okefenokee Wilderness 3 6.5 5.5 2.6 2.1 6.1 5.1 2.1 1.7

Wolf Island Wilderness 3 3.3 3.1 2.1 2.0 3.0 2.8 1.5 1.4
Air Quality: Cumulative and Visibility Impacts D-137

Class I/II Area Critical Load 

Threshold

2012 Base Case 2017 Future Year

NMaxNAvgSMaxSAvgNMaxNAvgSMaxSAvg

Cohutta Wilderness 5 11.5 10.2 5.4 4.3 10.6 9.3 3.6 2.9

Sipsey Wilderness 5 9.4 9.0 3.2 3.2 9.1 8.6 2.1 2.1

Guadalupe Mountains 

National Park 3 3.3 2.6 1.1 0.7 3.2 2.5 0.9 0.6

Wichita Mountains 

(Charons Garden Unit) 

Wilderness

5 5.6 5.6 1.7 1.7 5.4 5.4 1.5 1.5

Wichita Mountains (North 

Mountain Unit) Wilderness 5 6.3 6.3 1.8 1.8 6.1 6.1 1.5 1.5

Wichita Mountains National 

Wildlife Refuge 5 6.5 6.0 1.8 1.7 6.2 5.8 1.5 1.5

Caney Creek Wilderness 5 9.3 9.2 3.7 3.6 9.1 9.0 2.3 2.3

Upper Buffalo Wilderness 5 7.4 7.4 2.5 2.5 7.1 7.1 1.7 1.7

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APPENDIX E 

RESPONSES TO PUBLIC COMMENTS 

ON THE DRAFT SUPPLEMENTAL EIS 

Responses to Public Comments on the Draft Supplemental EIS E-3 

E RESPONSES TO PUBLIC COMMENTS ON THE DRAFT 

SUPPLEMENTAL EIS 

All comments (i.e., letters, public meeting transcripts, electronic submissions, etc.) were 

analyzed to identify all substantive issues raised by the public. Each substantive issue within an 

individual’s comment was assigned a unique identifier. For example, the first substantive comment 

from the United States Environmental Protection Agency was assigned USEPA-1. Comments were 

then grouped by similar issues into nine major categories, and responses are provided for each 

issue. The comments were reproduced verbatim as they were received. When similar issues were 

raised by several commenters, a single response has been provided for multiple comments. The 

comments and responses are presented in a matrix (Table E-1) and are organized by the following 

nine topics: Topic 1–NEPA Process and Public Involvement; Topic 2–NEPA Analysis; Topic 3–

Alternatives; Topic 4–Environmental Issues and Concerns; Topic 5–Cumulative Analysis; Topic 6–

Oil Spills; Topic 7–Mitigation; Topic 8–Regulations and Safety; and Topic 9–Other. Some topics 

include subtopics to further group similar comments. Topic 3 includes a subtopic on stated 

preference for those commenters who stated a preference for a particular alternative. Topic 4 has 

15 subtopics (i.e., Climate Change, Greenhouse Gases, Well Stimulation, Renewable Energy and 

Alternative Uses of the OCS, Natural Stressors, Air Quality, Water Quality, Coastal Habitats, 

Deepwater Benthic Communities, Sargassum and Associated Communities, Marine Mammals, 

Commercial Fisheries, Land Use and Coastal Infrastructure, Economic Factors, and Social Factors 

[Including Environmental Justice]) to separate the various environmental issues and concerns raised 

by commenters.

An index of comments, which is organized by topic and commenter, can be found below. An 

individual or group can search by name to more quickly find BOEM’s response.

Topic 1 – NEPA Process and Public Involvement

• American Petroleum Institute: API-1 

• Louisiana Mid-Continent Oil and Gas Association: LMOGA-1 

• National Ocean Industries Association: NOIA-1 

• Offshore Operators Committee: OOC-1 

• Maggi Roberts: MaRo-1 

• Jackie Antalan: JA-1, JA-8, JA-5 

• M. Fleming: MF-5, MF-4 

• Barbara Brewster: BB-2, BB-1 

• Lorie Chinn: LC-1, LC-2 
E-4 2018 Gulf of Mexico Supplemental EIS

Topic 2 – NEPA Analysis

• Center for Biological Diversity, Sierra Club, Gulf Restoration Network, Louisiana 

Bucket Brigade: CBD,SC,GRN,LBB-1; CBD,SC,GRN,LBB-3; 

CBD,SC,GRN,LBB-4; CBD,SC,GRN,LBB-5; CBD,SC,GRN,LBB-6 

• David Quist: DQ-13

• Sierra Club: SC-3, SC-2 

• John Warden: JW-2 

• Joint Trades: JT-28

• Alicia Cooke: AC-7 

• Gulf Restoration Network: GRN-11

• Allison Kalnik: AK-3 

• M. Fleming: MF-3 

• Peter Shrock: PS-8 

• Mobile Environmental Justice Action Coalition: MEJAC-4 

• Dyan Gibson: DyGi-1 

• Jodi Koszarek: JK-1 

• June Charles: JC-3 

• Rebecca King: RK-9 

• 350 Louisiana - New Orleans: 350LANO-2 

• Renate Heurich: RH-2 

• United States Environmental Protection Agency: USEPA-3 

• United States Fish and Wildlife Service: USFWS-1 

Topic 3 – Alternatives

• Peter Shrock: PS-7, PS-10, PS-9 

• Gulf Restoration Network: GRN-4 

• Allison Kalnik: AK-2 

• Eli Lamb: EL-1 

• Alicia Cooke: AC-1 
Responses to Public Comments on the Draft Supplemental EIS E-5 

Stated Preference

• Consumer Energy Alliance: CEA-1, CEA-4 

• Beth Everage, Consumer Energy Alliance: BECEA-1 

• Florida Department of Environmental Protection: FDEP-1 

• Alicia Cooke: AC-6 

• Amy Merrill: AmMe-1 

• Bill Clarke: BC-1 

• Carole Tebay: CT-1 

• David Quist: DQ-1 

• Jean Publeee: JP-1 

• June Charles: JC-4 

• Sierra Club: SC-1 

• Lisa Rogers: LR-1 

• Center for Biological Diversity, Sierra Club, Gulf Restoration Network, Louisiana 

Bucket Brigade: CBD,SC,GRN,LBB-14; CBD,SC,GRN,LBB-2 

• Nicholas Gault: NG-1 

• Peter Shrock: PS-13

• Mobile Environmental Justice Action Coalition: MEJAC-9 

• Rebecca King: RK-10

• Ryan Bowman: RB-1 

• Sarah Danner: SD-1 

• Kevin Holm: KH-1 

• Sarah Howard: SH-1 

• Valerie Longa: VL-2 

• Carol “Cay” Burton: CB-1, CB-3 

• Jackie Hartstein: JH-3 

• Care2: Care2-1 

• Bob Smith: BoSm-1 

• Carol A. “Cay” Burton: CAB-1, CAB-3 
E-6 2018 Gulf of Mexico Supplemental EIS

• Kathleen McBride: KM-1 

• Lorie Chinn: LC-3 

• Bonnie Aylward: BA-4 

• Pam Scaggs, South Baldwin Democrats: PSSBD-2 

• Donna Baker: DB-1 

• Francine Slack: FS-1 

• Deborah Jiminez: DJ-1 

• Brian A. Mayhew: BAM-1 

• Daryl Frahn: DaFr-1 

• Mobile Environmental Justice Action Coalition: MEJAC-1, MEJAC-8 

• Janice Overstreet: JO-1 

• James Sorrells: JaSo-1 

• Daniel Gillis: DaGi-1 

• Dennis Rentschler: DR-1 

• Gary Stephens: GS-1 

• Ron Masters: RM-1 

• David Gorchov: DaGo-1, DaGo-5 

• Jensie Madden: JM-1 

Topic 4 – Environmental Issues and Concerns

Climate Change

• Allison Kalnik: AK-1 

• Peter Shrock: PS-11

• Rebecca King: RK-11, RK-7 

• David Quist: DQ-3, DQ-6 

• David Gorchov: DaGo-4 

• Gulf Restoration Network: GRN-12, GRN-13 

• Wendy King: WK-1, WK-2 
Responses to Public Comments on the Draft Supplemental EIS E-7 

• Jodi Koszarek: JK-2 

• Amanda Munson: AmMu-1 

Greenhouse Gases

• Center for Biological Diversity, Sierra Club, Gulf Restoration Network, Louisiana 

Bucket Brigade: CBD,SC,GRN,LBB-7; CBD,SC,GRN,LBB-8; 

CBD,SC,GRN,LBB-9 

• Renate Heurich: RH-3, RH-1 

• Michael Robertshaw: MiRo-1 

• Eli Lamb: EL-2 

• Rebecca King: RK-8 

• 350 Louisiana - New Orleans: 350LANO-1; 350LANO-5 

Well Stimulation

• Center for Biological Diversity, Sierra Club, Gulf Restoration Network, Louisiana 

Bucket Brigade: CBD,SC,GRN,LBB-10

• Peter Shrock: PS-4 

• Maggi Roberts: MaRo-3 

• Rebecca King: RK-6 

• 350 Louisiana - New Orleans: 350LANO-4 

• William Myers: WM-1 

• June Charles: JC-2 

Renewable Energy and Alternative Uses of the OCS

• Alicia Cooke: AC-2, AC-5 

• Ryan Bowman: RB-2 

• Valerie Longa: VL-1, VL-3 

• Jackie Hartstein: JH-4 

• Kathryn R. Smith: KS-1 

• Lorie Chinn: LC-6 

• M. Fleming: MF-1, MF-6 

• Pam Scaggs, South Baldwin Democrats: PSSBD-3 
E-8 2018 Gulf of Mexico Supplemental EIS

• Carol A. “Cay” Burton: CAB-5 

• Carol “Cay” Burton: CB-5 

• David Gorchov: DaGo-3 

• John Warden: JW-3 

Natural Stressors

• Jean Publeee: JP-3 

• Carol “Cay” Burton: CB-4 

• Carol A. “Cay” Burton: CAB-4 

Air Quality

• Consumer Energy Alliance: CEA-3 

• David Quist: DQ-4 

• Maggi Roberts: MaRo-2 

• United States Environmental Protection Agency: USEPA-1, USEPA-4, 

USEPA-5, USEPA-6, USEPA-7, USEPA-8, USEPA-9, USEPA-10, USEPA-11, 

USEPA-12, USEPA-13, USEPA-14, USEPA-15, USEPA-16, USEPA-17, 

USEPA-18, USEPA-19, USEPA-20, USEPA-21, USEPA-22, USEPA-23, 

USEPA-24, USEPA-25, USEPA-26, USEPA-27, USEPA-28, USEPA-29, 

USEPA-30, USEPA-31, USEPA-32, USEPA-33, USEPA-34, USEPA-35, 

USEPA-36, USEPA-37, USEPA-38, USEPA-39, USEPA-40, USEPA-41, 

USEPA-42, USEPA-43, USEPA-44, USEPA-45, USEPA-46, USEPA-47

• Joint Trades: JT-1, JT-2, JT-3, JT-4, JT-5, JT-6, JT-7, JT-8, JT-9, JT-10, JT-11, 

JT-12, JT-13, JT-14, JT-15, JT-16, JT-17, JT-18, JT-19, JT-20, JT-21, JT-22, 

JT-23, JT-24, JT-25, JT-26, JT-27, JT-30, JT-31

Water Quality

• David Quist: DQ-5 

Coastal Habitats

• Center for Biological Diversity, Sierra Club, Gulf Restoration Network, Louisiana 

Bucket Brigade : CBD,SC,GRN,LBB-11

• Joint Trades: JT-29

• Chelsea Gray: CG-1 
Responses to Public Comments on the Draft Supplemental EIS E-9 

• United States Environmental Protection Agency: USEPA-2 

• National Park Service: NPS-1 

Deepwater Benthic Communities

• Chelsea Gray: CG-2 

• David Quist: DQ-9 

Sargassum and Associated Communities

• David Quist: DQ-10

• Gulf Restoration Network: GRN-8 

Marine Mammals

• Chelsea Gray: CG-4 

• Rebecca King: RK-2 

• Gulf Restoration Network: GRN-9, GRN-10

• David Quist: DQ-12

Commercial Fisheries

• Chelsea Gray: CG-5, CG-7 

Land Use and Coastal Infrastructure

• Alicia Cooke: AC-3 

• Gulf Restoration Network: GRN-2 

• Chris Werle: CW-1 

• June Charles: JC-1 

• Penny Dipuma: PD-1 

• Carol “Cay” Burton: CB-2 

• Carol A. “Cay” Burton: CAB-2 
E-10 2018 Gulf of Mexico Supplemental EIS

Economic Factors

• Chelsea Gray: CG-6 

• Jackie Antalan: JA-2 

• Mobile Environmental Justice Action Coalition: MEJAC-5 

• Jean Publeee: JP-2, JP-4 

Social Factors (Including Environmental Justice) 

• Center for Biological Diversity, Sierra Club, Gulf Restoration Network, Louisiana 

Bucket Brigade: CBD,SC,GRN,LBB-13

• Peter Shrock: PS-6 

• Mobile Environmental Justice Action Coalition: MEJAC-2 

• Sierra Club: SC-5 

• Gulf Restoration Network: GRN-14

Topic 5 – Cumulative Analysis

• Chelsea Gray: CG-3 

• David Quist: DQ-2 

• Lorie Chinn: LC-5 

• Peter Shrock: PS-12

Topic 6 – Oil Spills

• David Quist: DQ-8 

• Maggi Roberts: MaRo-4 

• Gulf Restoration Network: GRN-1, GRN-3, GRN-6, GRN-5, GRN-7 

• Sierra Club: SC-4 

• Rebecca King: RK-1, RK-3, RK-4, RK-5 

• Eli Lamb: EL-3 

• Susan Prerost: SP-1 

• Lorie Chinn: LC-4 

• Bill McBride: BM-1 

• Alan Ackerman: AA-1 
Responses to Public Comments on the Draft Supplemental EIS E-11

• Judith Shields: JuSh-1 

• Anonymous: ANON-1 

• Ryan Bowman: RB-4 

• Peter Shrock: PS-1, PS-2 

• 350 Louisiana - New Orleans: 350LANO-3 

• Bonnie Aylward: BA-1 

• Pam Scaggs, South Baldwin Democrats: PSSBD-1 

• Jackie Hartstein: JH-1 

Topic 7 – Mitigation

• David Quist: DQ-11

• Peter Shrock: PS-5 

• Alabama Department of Environmental Management: ADEM-1 

• Mobile Environmental Justice Action Coalition: MEJAC-7 

• Charles Frey: CF-1 

Topic 8 – Regulations and Safety

• Center for Biological Diversity, Sierra Club, Gulf Restoration Network, Louisiana 

Bucket Brigade: CBD,SC,GRN,LBB-12

• Peter Shrock: PS-3 

• Jackie Antalan: JA-4 

• Bill McBride: BM-2 

• M. Fleming: MF-2 

• Jodi Koszarek: JK-3 

• Jackie Hartstein: JH-2 

• Judy Fisher: JF-1, JF-2, JF-3, JF-4, JF-5, JF-6, JF-7, JF-8 

• Bud See: BuSe-1 

• John Warden: JW-1 
E-12 2018 Gulf of Mexico Supplemental EIS

Topic 9 – Other

• David Quist: DQ-7 

• Maggi Roberts: MaRo-5, MaRo-6 

• David Gorchov: DaGo-2 

• Mobile Environmental Justice Action Coalition: MEJAC-6, MEJAC-3 

• Bill McBride: BM-3 

• Alicia Cooke: AC-4 

• Ryan Bowman: RB-3 

• Consumer Energy Alliance: CEA-2 

• Beth Everage, Consumer Energy Alliance: BECEA-2 

• Jackie Antalan: JA-3, JA-6, JA-7 

• Bonnie Aylward: BA-2, BA-3 

• Denise Folley: DeFo-1 
Responses to Public Comments on the Draft Supplemental EIS E-13

Table E-1. Public Comments and BOEM’s Response Matrix. 

Commenter Comment ID Comment Response

Topic 1 – NEPA Process and Public Involvement

American 

Petroleum 

Institute

API-1 On March 31, 2017 the Bureau of Ocean Energy 

Management (BOEM) provided a notice of 

availability of the Gulf of Mexico Outer Continental 

Shelf Lease Sale Draft Supplemental Environmental 

Impact Statement 2018 (Draft Supplemental EIS). 

The Draft Supplemental EIS is expected to be used 

to inform decisions on each of two lease sales 

scheduled in 2018.

The American Petroleum Institute (API) requests that 

BOEM extend the comment period for the Draft 

Supplemental EIS by an additional 30 days 

(providing a 75-day comment period). The Draft 

Supplemental EIS includes information on an air 

quality analysis that was completed for the Final 

2017-2022 GOM Multisale EIS but which was not 

previously made available for public review. This 

new air quality information is extensive and complex, 

and additional time to review the air quality modeling 

inputs, methodologies and results would allow for 

more substantive and meaningful stakeholder 

comment. BOEM specifically notes in Chapter 4 of 

the Draft Supplemental EIS that it “looks forward to 

receiving relevant comments on the methods used in 

air quality modeling and the resulting analyses”.

We appreciate your consideration of this request.

On March 31, 2017, BOEM published a Notice of 

Availability for the Draft 2018 GOM Supplemental EIS. 

The National Environmental Policy Act (NEPA) 

requires a 45-day comment period on Draft EISs, 

which is a period that may be extended at the 

discretion of the agency issuing the document. In the 

case of the Draft 2018 GOM Supplemental EIS, 

BOEM determined that an additional 30-day review 

would be granted to the five parties that specifically 

requested an extension to provide comments on the 

air quality analysis. An email was sent to the five 

parties that requested the extension, indicating that 

BOEM would accept comments on the air quality 

analysis in the Draft 2018 GOM Supplemental EIS 

until June 14, 2017. Comments on the rest of the 

Draft 2018 GOM Supplemental EIS, however, were to 

be submitted by the end of the 45-day comment 

period, which was May 15, 2015. No additional 

comments were received on the air quality analysis 

during the extension period.

Louisiana 

Mid-Continent 

Oil and Gas 

Association

LMOGA-1 The Louisiana Mid-Continent Oil & Gas Association 

respectfully requests that the Bureau of Ocean 

Energy Management (BOEM) extend the 45-day 

comment period on the proposed Gulf of Mexico 

Outer Continental Shelf Lease Sale Draft 

Supplemental Environmental Impact Statement 2018 

(the “Draft SEIS”) to 75 days (an additional 30 days). 

LMOGA recognizes the Bureau’s need to issue the 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-14 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

Draft SEIS in order to provide business critical 

services supporting oil and natural gas development; 

however, we would appreciate more time to review 

the document in order to provide informed, 

substantive feedback.

An extension of the comment period is justified given 

that BOEM has included substantial new information 

in the Air Quality section of the document. In fact, 

BOEM has stated in the Draft SEIS that, “...since this 

air quality analysis was completed for the Final 

2017-2002 GOM Multisale EIS and did not have the 

benefit of public review, the complete analysis is

included in this Supplemental EIS for public review 

and comment. BOEM looks forward to receiving 

relevant comments on the methods used in air 

quality modeling and the resulting analyses.” Given 

the complexity of the air quality information included 

in the Draft SEIS, and the fact that this is the first 

opportunity for the public to review and comment on 

the air quality analysis, we believe additional time is 

warranted to generate relevant comments to benefit 

BOEM’s final SEIS.

The Louisiana Mid-Continent Oil & Gas Association 

(LMOGA) is Louisiana’s longest standing trade 

association, exclusively representing all aspects of 

the oil and gas industry onshore and offshore,

including exploration, production, mid-stream 

activities, pipeline, refining and marketing. Louisiana 

is a significant supporter of OCS activity in the Gulf, 

which accounts for more than 17 percent of the 

Nation’s oil production and about five percent of

natural gas production.

Comments submitted on behalf of LMOGA are 

submitted without prejudice to any member’s right to 

have or express different or opposing views. We 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-15

Commenter Comment ID Comment Response

appreciate your consideration of this request for an 

extension.

National 

Ocean 

Industries 

Association

NOIA-1 The National Ocean Industries Association (NOIA) 

respectfully requests that the Bureau of Ocean 

Energy Management (BOEM) extend the 45-day 

comment period on the proposed Gulf of Mexico 

Outer Continental Shelf Lease Sale Draft 

Supplemental Environmental Impact Statement 2018 

(the “Draft SEIS”) to 75 days (an additional 30 days).

NOIA is the only trade association representing all 

segments of the offshore industry and has nearly 

300 member companies with an interest in the 

exploration and production of both traditional and 

renewable energy resources. NOIA’s mission is to 

secure reliable access and a fair regulatory and 

economic environment for the companies that 

develop the nation’s valuable offshore energy 

resources in an environmentally responsible manner.

NOIA recognizes the Bureau’s need to issue the 

Draft SEIS in order to provide business critical 

services supporting oil and natural gas development: 

however, we would appreciate more time to review 

the document in order to provide informed, 

substantive feedback.

An extension of the comment period is justified given 

that BOEM has included substantial new information 

in the Air Quality section of the document. In fact, 

BOEM has stated in the draft SEIS that, “...since this 

air quality analysis was completed for the Final 

2017-2022 GOM Multisale EIS and did not have the 

benefit of public review, the complete analysis is 

included in this Supplemental EIS for public review 

and comment. BOEM looks forward to receiving 

relevant comments on the methods used in air 

quality modeling and the resulting analyses.” Given 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-16 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

the complexity of the air quality information included 

in the Draft SEIS, and the fact that this is the first 

opportunity for the public to review and comment on 

the air quality analysis, we believe additional time is 

warranted to generate relevant comments to benefit 

BOEM’s final SEIS.

We appreciate your consideration of this request for 

an extension.

Offshore 

Operators 

Committee

OOC-1 The Offshore Operators Committee (OOC) 

respectfully requests that the Bureau of Ocean 

Energy Management (BOEM) extend the 45-day 

comment period on the proposed Gulf of Mexico 

Outer Continental Shelf Lease Sale Draft 

Supplemental Environmental Impact Statement 2018 

(the “Draft SEIS”) to 75 days (an additional 30 days). 

OOC recognizes the Bureau’s need to issue the 

Draft SEIS in order to provide business critical 

services supporting oil and natural gas development; 

however, we would appreciate more time to review 

the document in order to provide informed, 

substantive feedback.

An extension of the comment period is justified given 

that BOEM has included substantial new information 

in the Air Quality section of the document. In fact, 

BOEM has stated in the Draft SEIS that, “...since this 

air quality analysis was completed for the Final 

2017-2002 GOM Multisale EIS and did not have the 

benefit of public review, the complete analysis is 

included in this Supplemental EIS for public review 

and comment. BOEM looks forward to receiving 

relevant comments on the methods used in air 

quality modeling and the resulting analyses.”

1

 Given 

the complexity of the air quality information included 

in the Draft SEIS, and the fact that this is the first 

opportunity for the public to review and comment on

the air quality analysis, we believe additional time is 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-17

Commenter Comment ID Comment Response

warranted to generate relevant comments to benefit 

BOEM’s final SEIS.

The OOC is an organization of 47 producing 

companies and 61 service providers to the offshore 

oil and natural gas industry who conduct essentially 

all of the Outer Continental Shelf (OCS) oil and gas 

exploration and production activities in the Gulf of 

Mexico (GOM). Comments submitted on behalf of 

the OOC are submitted without prejudice to any 

member’s right to have or express different or 

opposing views.

We appreciate your consideration of this request for 

an extension.

Maggi Roberts MaRo-1 Given the complexity of the air quality information 

included in the Draft SEIS, and the fact that this is 

the first opportunity for the public to review and 

comment on the air quality analysis, additional time 

is needed to gather appropriate information and 

make it available to the public.

Jackie Antalan JA-1 BOEM continues to fail in their methodology of 

conducting meaningful community engagement. We 

appreciate the outreach being extended to later 

hours, but it still continues to create barriers to 

people who reside in the southern coastal 

communities that are directly impacted by the lease 

sales.

Thank you for your comment. BOEM did its best to 

consider work hours and locations that were easily 

accessible for the public. BOEM has also held public

meetings at locations in southern coastal 

communities, such as Larose, Louisiana, but did not 

have any attendees. BOEM will continue to consider 

work hours and locations when planning future public 

participation opportunities. BOEM welcomes 

suggestions for public meeting locations. 

M. Fleming MF-5 Hosting this meeting in Metairie – a location that 

many people who feel strongly on this matter find 

difficult to reach – also demonstrates a lack of actual 

interest in hearing and acknowledging points counter 

to the one it seems that this agency is most 

interested in.

Jackie Antalan JA-8 This public hearing was conducted with the fear 

factor where the public servant, NOAA and BOEM 

were under strict security. I was escorted to the 

Thank you for your comment. BOEM has provided 

security at the open-house meetings to ensure the 

safety of the public attending the meetings, as well as 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-18 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

recorder under security, private security. This fear 

factor is one of the major reasons why the 

community is not fully engaged. This increased 

security is going to further divide the communities 

who are fearful and uninformed about what is 

happening in the community, and it does not serve 

the mission or the best interest of the United States 

of America and its citizens.

the safety of BOEM’s employees. Security presence 

is not meant to intimidate attendees but to make them 

feel safe. BOEM will consider this factor when 

planning future public meetings.

Barbara 

Brewster

BB-2 And I would like to say that I was very happy with 

how I was treated by the people here today and feel 

like I am much better informed and would like to say 

that I would like to see an end to offshore oil 

production.

Thank you for your comment. BOEM is continually 

looking for ways to improve public involvement. 

BOEM’s open-house meeting format is designed to 

create a better atmosphere for open and honest 

dialogue to not only provide information to the public 

but also to help with the solicitation of meaningful 

comments to improve the NEPA review.

Lorie Chinn LC-1 This EIS information was very useful in my research. 

It was the alternatives maps that showed all of the 

leases in each area that was the most impactful to 

me.

M. Fleming MF-4 The information handed to me gave a lot of time and 

attention to the benefits of leasing, how safe it will 

be, etc., and I would feel much more trusting of a 

government agency if equal information was 

provided that more thoroughly accounted for the 

risks and described the benefits of not leasing the 

Gulf.

Thank you for your comment. The purpose of the 

public meeting was to obtain comments on the Draft 

2018 GOM Supplemental EIS. Through the openhouse format, BOEM worked diligently to inform the 

public of our mission and the potential impacts of a 

proposed regionwide lease sale. More details on the 

impacts associated with a proposed regionwide lease 

sale can be found in this Supplemental EIS.

Jackie Antalan JA-5 BOEM should undergo a comprehensive review and 

implement new outreach and meaningful community

engagement consistent with its 2016 and pending 

2017 strategic framework.

BOEM’s mission is to “manage development of U.S. 

Outer Continental Shelf energy and mineral resources 

in an environmentally and economically responsible 

way.” BOEM accomplishes this through responsible 

stewardship, science-informed decisions, and integrity 

and ethics. BOEM’s Strategic Framework can be 

found on BOEM’s website at https://www.boem.gov/

Strategic-Framework/. 

As part of the NEPA process, BOEM collects and 

considers public comments at the scoping and public 

comment stages of the preparation of an EIS. Please 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-19

Commenter Comment ID Comment Response

refer to 40 CFR § 1506.6 for detailed information of 

public participation in the NEPA process. BOEM has 

recently changed our scoping and public comment 

meetings to an open-house format to increase public 

outreach and interaction. Chapter 5 of this 

Supplemental EIS details the number of comments 

received and number of participants that attended 

each meeting.

Barbara 

Brewster

BB-1 My name is Barbara Brewster, and I'm here today as 

a concerned citizen. I was tragically affected by the

BP oil spill. We have a very good friend who was a 

charter boat owner who committed suicide over the 

impact of the BP oil spill, and I would like to do better 

at being informed with oil leases and what the impact 

will be on the Gulf of Mexico and the coastal areas.

Thank you for your comment. BOEM acknowledges 

the potential harmful impacts to sea life, seafood 

industry, and tourism industry as a result of an oil spill. 

These negative consequences are analyzed for each 

resource chapter in Chapter 4 and in the Catastrophic 

Spill Event Analysis white paper (USDOI, BOEM, 

2017a).

BOEM appreciates that you came to our open-house

meeting for the public comment period on the Draft 

2018 GOM Supplemental EIS. We restructured the 

public meetings to an open-house format in hopes of 

providing more open dialogue with individual members 

of the public to create more understanding and solicit 

better comments about the potential impacts of 

offshore oil and gas leases.

Lorie Chinn LC-2 I’ve learned that the federal lease areas is farther out 

into the Gulf than the state. This information was not 

disclosed in the advertisement / announcement 

about the meeting.

Thank you for your comment. BOEM will clarify in 

future newspaper ads that the proposed regionwide 

lease sales are in Federal waters.

Topic 2 – NEPA Analysis

Center for 

Biological 

Diversity, 

Sierra Club, 

Gulf 

Restoration 

Network,

Louisiana 

CBD,SC,GRN,

LBB-1 

The Bureau’s proposal fails to comply with clear 

requirements of the Outer Continental Shelf Lands 

Act (“OCSLA”) and the National Environmental 

Policy Act (“NEPA”) to precisely define areas 

available for leasing and conduct environmental 

analyses on a finer geographic scale. The Draft 

SEIS provides little to no meaningful analysis of the 

site-specific environmental impacts of the proposed 

The Outer Continental Shelf Lands Act (OCSLA)

provides the Congressional mandate for BOEM to 

make “available for expeditious and orderly 

development, subject to environmental safeguards, in 

a manner which is consistent with the maintenance of 

competition and other national needs” the land of the 

Federal OCS. The Secretary of the Interior oversees 

the OCS Oil and Gas Program and is required to 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-20 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

Bucket 

Brigade

lease sale. balance orderly resource development with protection 

of the human, marine, and coastal environments while 

simultaneously ensuring that the public receives an 

equitable return for these resources and that freemarket competition is maintained. It is during this 

national-level review that the location (GOM 

regionwide leasing) and timing of lease sales (number 

of lease sales per year) is set in the schedule of 

proposed lease sales.

The OCSLA requires a staged decisionmaking 

process beginning with the Five-Year Program, 

continuing through individual lease sales under the 

Five-Year Program, and ultimately to individual 

postlease activities requiring a permit or approval. As 

stated in Chapters 1 and 2, the 2017-2022 GOM 

Multisale EIS (USDOI, BOEM, 2017b) discusses all 

10 Federal actions, i.e., 10 proposed regionwide oil 

and gas lease sales, as scheduled under the 2017-

2022 Five-Year Program, and this Supplemental EIS 

updates the analyses of a single proposed regionwide 

lease sale in the 2017-2022 Five-Year Program. The 

multisale EIS approach is intended to focus the 

NEPA/EIS process on the staged OCSLA process for 

decisionmaking, including the proposed regionwide 

lease sales and any new issues and information 

identified since a prior stage. It also lessens 

duplication and saves resources when BOEM and the 

Bureau of Safety and Environmental Enforcement 

(BSEE) conduct postlease reviews.

Additionally, the issuance of leases does not conclude 

the environmental analysis of planned OCS oil- and 

gas-related activities. Each plan throughout the 

exploration, production, and decommissioning 

processes receives a site-specific environmental 

analysis pursuant to NEPA and the OCSLA’s 

pyramidal structure, going from large scale to site 

Center for 

Biological 

Diversity, 

Sierra Club, 

Gulf

Restoration 

Network, 

Louisiana 

Bucket 

Brigade

CBD,SC,GRN,

LBB-3 

In addition, NEPA regulations recognize that “tiering” 

from one environmental analysis to another may 

sometimes be appropriate where a broad 

environmental analysis has been conducted and the 

agency wishes to refer back to that assessment at a 

subsequent stage to avoid repetition. However, the 

process cannot be used to evade the thorough 

review required by NEPA. Indeed, “it is not better 

documents but better decisions that count. NEPA’s 

purpose is not to generate paperwork — even 

excellent paperwork — but to foster excellent action.” 

The Bureau cannot continue to use tiering to avoid 

the requisite in-depth analysis required by NEPA. 

The Draft SEIS fails to cure the deficiencies from the 

2017-2022 programmatic EIS and the Gulf of Mexico 

multi-lease sale EIS, and lacks adequate analysis of 

the issues raised in our scoping comments for Lease 

Sales 250 and 251.

Center for 

Biological 

Diversity, 

Sierra Club, 

Gulf 

Restoration 

Network, 

Louisiana 

Bucket 

Brigade

CBD,SC,GRN,

LBB-4 

The area-wide lease sale alternative violates OCSLA 

and NEPA by failing to precisely define the location 

and provide a hard look at the site-specific 

environmental impacts. As courts have made clear, 

OCSLA’s procedures for authorizing oil and gas 

activities on the OCS “are pyramidic in structure, 

proceeding from broad-based planning to an 

increasingly narrower focus as actual development 

grows more imminent.” Thus, the lease sale stage 

must have a fine scale analysis and full disclosure of 

the environmental impacts of its action.

But rather than “precisely” defining the location of the 

lease sale, the Bureau’s proposed action takes an 

area-wide approach that designates the entire Gulf of 

Mexico as the area eligible for the lease sale. This 

area-wide lease sale approach is incompatible with 

OCSLA. Indeed, under this approach, the Bureau 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-21

Commenter Comment ID Comment Response

allows the oil industry to determine which areas are 

explored and developed, thereby abdicating the 

agency’s responsibility under OCSLA to direct oil 

activities and assure that they do not cause 

environmental harm.

The area-wide lease sale approach undermines the 

ability of the Bureau to take a “hard look” at the 

environmental impacts of its proposal as required by 

NEPA. An agency must take a “hard look” at the 

environmental impacts of an agency’s decision 

before an agency acts, and include a discussion of 

the need for the proposal, alternatives to the 

proposal, and the environmental impacts of the 

proposal and the alternatives. “The hallmarks of a 

‘hard look’ are thorough investigation into 

environmental impacts and forthright 

acknowledgment of potential environmental harms.” 

The Draft SEIS lacks a site-specific environmental 

analysis of the offshore drilling leases and 

subsequent activities. Offshore leasing is carried out 

in stages, with each step triggering a more detailed 

and site-specific NEPA environmental review. 

Instead, at the five year plan, multi-lease sale, and 

lease sale NEPA review the geographic scope and 

detail of the impacts has remained the same. But 

according to Marble Mountain Audubon Society Rice, 

unless the programmatic documents address sitespecific impacts, they must be addressed in later 

individual NEPA documents.

The Bureau’s area-wide lease sale approach is 

particularly troubling considering that this approach 

was cited as one of the problems in the offshore oil 

regime that led to the Deepwater Horizon oil spill. In 

response to the spill, President Obama established 

the National Commission on the BP Deepwater 

Horizon Oil Spill and Offshore Drilling 

specific. For more information on BOEM’s postlease 

processes, please refer to Appendix A of the 

2017-2022 GOM Multisale EIS, from which this 

Supplemental EIS tiers.

Because of these multiple and tiered programmatic 

documents, along with future site-specific reviews that 

tier to these programmatic and discretionary 

documents, BOEM takes a hard look at the potential 

for environmental consequences at each phase of the 

decisionmaking process that considers a proposed 

action in the GOM. At each phase, BOEM has 

identified numerous environmental safeguards to 

minimize the impacts, i.e., through the consideration 

of EISs and programmatic mitigation at the Five-Year 

Program level, consideration of alternatives to limit 

impacts to sensitive topographic features in this 

Supplemental EIS, and commonly applied mitigation 

measures.

Further, the 2017-2022 Five-Year Program EIS 

analyzes the environmental impacts of the entire 

10 lease sale program in the Gulf of Mexico. The 

regional-level NEPA analysis covered in this 

Supplemental EIS provides a regional-level analysis of 

the environmental impacts of a single proposed 

regionwide lease sale in the 2017-2022 Five-Year 

Program. In addition, BOEM analyzes Alternatives B, 

C, and D, which would scale back the regionwide 

leasing to planning area (Western Planning Area 

[WPA] or Central Planning Area/Eastern Planning 

Area [CPA/EPA]) leasing, similar to leasing in the 

2012-2017 Five-Year Program. Therefore, the 

analysis in this Supplemental EIS evaluates several 

smaller actions consistent with the OCSLA’s 

pyramidal structure.
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-22 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

(“Commission”) as an independent, nonpartisan 

entity charged with providing a thorough analysis of 

the causes of the disaster and recommending 

reforms for making offshore drilling safer. The 

Commission issued its final report in January 2011, 

in which it highlighted the need for a fundamentally 

different approach to management of offshore 

drilling. The Commission noted that the area-wide 

approach favored industry at the cost of meaningful 

environmental analysis. According to the 

Commission:

OCS lease sales cover such large geographic areas 

that meaningful NEPA review is difficult. A decision 

to dramatically increase the size of lease sales—

known as area-wide leasing—was made over 

20 years ago at the request of industry; it has 

necessitated environmental analyses of very large 

areas at the lease sale stage. For example, the Final 

Environmental Impact Statement for the 2007–2012 

multilease sales in the Gulf of Mexico covered more 

than 87 million acres, while the Final Environmental 

Impact Statement for Chukchi Sea Lease Sale 193 

covered about 34 million acres. Given that 2008 

lease sales in the Central Gulf of Mexico and the 

Chukchi Sea attracted almost $3.7 billion and almost 

$2.7 billion in high bids, respectively, it is appropriate 

to conduct environmental reviews on a finer 

geographic scale before private-sector commitments 

of this magnitude are made to purchase leases.

However, the Bureau’s current proposal does just the 

opposite. In fact, it backslides from prior programs 

with respect to the lease sale in the Gulf of Mexico. 

Previous lease sales were based on the three 

separate planning areas—the Western Gulf, the 

Central Gulf and the Eastern Gulf—compared to the 

proposed action of offering all unleased portions of 

Pursuant to NEPA, this Supplemental EIS analyzes a 

range of alternatives, but NEPA does not require 

carrying all of the alternatives considered through a 

full analysis of impacts. BOEM has ensured that a 

reasonable range of alternatives to a proposed action, 

within the framework of the 2017-2022 Five Year 

Program, was considered in the 2017-2022 GOM 

Multisale EIS, from which this Supplemental EIS tiers. 

Chapter 2.2.3 of the 2017-2022 GOM Multisale EIS 

discusses additional alternatives that were considered 

but eliminated based on the best available information 

currently available. All of the alternatives considered 

were not analyzed in detail because they were either 

outside the scope of the lease sale decision, were 

speculative, were not warranted, did not meet the 

purpose of and need for the oil and gas leasing 

program, or current data did not support the 

alternative. As noted in Chapter 1.0, any individual 

lease sale could still be scaled back during the 

prelease sale process to offer a smaller area should 

circumstances warrant. Examples of smaller lease 

areas include the WPA and CPA/EPA planning area 

alternatives, which were analyzed throughout this 

Supplemental EIS.

In reference to the National Commission on the BP 

Deepwater Horizon Oil Spill and Offshore Drilling,

as suggested in the Commission’s final report, BOEM 

(along with BSEE) has implemented many 

fundamental changes to improve the management of 

offshore leasing and drilling. Some of the changes 

made since 2010 include the following: an 

Investigations and Review Unit was instituted to root 

out problems within the regulatory agencies and target 

companies that aim to game the system; BOEM 

created multiple Implementation Teams, tasked with 

analyzing various aspects of BOEM’s regulatory 

structure and helping to implement the reform agenda; 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-23

Commenter Comment ID Comment Response

the “Gulf of Mexico.” But the Gulf of Mexico contains 

nearly 160 million acres, more than 75 million of 

which are currently unleased and available for lease 

under the Bureau’s proposal. The Gulf also contains 

a great diversity of environmental and socioeconomic 

characteristics.

For example, as the Bureau has repeatedly admitted, 

the separate regions in the Gulf of Mexico have 

distinct ecological features. According to the Bureau 

the Gulf of Mexico is “subject to an array of 

environmental conditions, resulting in a large number 

of ecological community types” ranging from highly 

productive coral reefs to less diverse benthic 

habitats. Coastal areas are biologically important for 

calving coastal bottlenose dolphins, and dolphins in 

Barataria Bay are especially vulnerable because of 

their site fidelity and continuing harm from the 

Deepwater Horizon oil spill. Bryde’s whales have an 

incredibly limited range, and they have been 

documented only in the eastern Gulf of Mexico—

specifically their habitat is focused in the De Soto 

canyon. Like Bryde’s whales Cuvier’s beaked 

whales also have high site fidelity and would be more 

vulnerable to noise impacts from airguns and oil 

development than in other Gulf locations. Also, new 

science shows that there is chronically elevated 

noise in important marine habitats with airgun 

surveys dominating the acoustic environment. 

These differences illustrate how a meaningful 

environmental analysis would disclose specific 

locations or populations of wildlife that may be 

affected by the proposed action. The area-wide 

environmental review covers a massive geographic 

range and fails to disclose the environmental impacts 

on these special areas or provide a meaningful 

analysis to inform a decision about which areas 

would be the preferred environmental alternative.

BOEM implemented a recusal policy for employees to 

deal with real and perceived conflicts of interest; and 

Secretary Salazar and Director Bromwich launched a 

full review of the use of NEPA and categorical 

exclusions for the approval of proposed deepwater 

drilling projects.

BOEM places a significant emphasis on public input 

and scientific analysis, which are critical to safe 

exploration and development of offshore resources. 

Public comment is solicited in our environmental 

review programs for both oil and gas and renewable 

energy proposals. Plans submitted by industry are

subject to rigorous scientific review to ensure that 

environmental safeguards are the foundation of all 

offshore energy development.

A brief summary of the reforms within BOEM and 

BSEE since the Deepwater Horizon explosion, oil spill, 

and response can be found on BOEM’s website at 

https://www.boem.gov/Regulatory-Reform/. BOEM 

and BSEE will remain vigilant in instituting reform 

efforts and lessons learned since the Deepwater 

Horizon explosion, oil spill, and response.

Mitigating measures are an integral part of BOEM’s 

program to ensure that postlease operations are 

conducted in an environmentally sound manner (with 

an emphasis on minimizing any adverse impact of 

routine activities on the environment). BOEM assigns 

site-specific mitigation by imposing conditions of 

approval on a plan, permit, or authorization. 

Appendix A of the 2017-2022 GOM Multisale EIS 

discusses BOEM’s rigorous postlease process, and 

Appendix B of the 2017-2022 GOM Multisale EIS 

describes over 120 standard mitigations that may be 

required by BOEM or BSEE as a result of the plan and 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-24 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

This new area-wide leasing approach also directly 

contradicts the Commission’s express 

recommendations that the Bureau conduct 

environmental reviews on a finer geographic scale.

permit review processes for the Gulf of Mexico OCS 

Region.

David Quist DQ-13 In short, the EIS does not adequately assess the full 

range, and the significance, of impacts associated 

with offshore energy exploration, drilling, and 

production in the Gulf. If does not adequately 

address impacts on specific areas, and given its 

generic nature and broad geographic coverage, 

cannot adequately assess impacts within the 

demands of the law.

Thank you for the opportunity to comment.

Center for 

Biological 

Diversity, 

Sierra Club, 

Gulf 

Restoration 

Network,

Louisiana 

Bucket 

Brigade

CBD,SC,GRN,

LBB-5 

The Bureau’s purpose and need statement fails to 

comply with NEPA. NEPA’s implementing 

regulations provide that an EIS should “specify the 

underlying purpose and need to which the agency is 

responding in proposing the alternatives including 

the proposed action.” This purpose and need inquiry 

is crucial for a sufficient environmental analysis 

because “[t]he stated goal of a project necessarily 

dictates the range of ‘reasonable’ alternatives.” 

Thus, “an agency cannot define its objectives in 

unreasonably narrow terms” without violating NEPA.

The Bureau’s stated purpose and need for its 

proposal is “to offer for lease those areas that may 

contain economically recoverable oil and gas 

resources” to manage the development of oil and 

gas resources on the OCS. This purpose and need 

is too narrow and thus inadequate because the 

agency considered an unreasonably narrow range of 

alternatives. By framing its statement as needing to 

auction off areas of the OCS that might contain 

recoverable oil and gas, the Bureau necessarily 

Per Section 18 of the OCSLA, BOEM is required to 

develop a schedule of oil and gas lease sales on the 

OCS for 5-year periods. Thus, the OCSLA is the 

implementing legislation driving the purpose, and it is 

the law requiring the Secretary of the Interior to 

propose an action. The need is founded in the 

sources of energy consumption in the United States, 

which were detailed in the 2017-2022 GOM Multisale 

EIS and summarized in this Supplemental EIS. The 

proposed action under NEPA is the proposed 

regionwide lease sales identified in the 2012-2022 

Five-Year Program, and this Supplemental EIS 

determined possible environmental impacts of a 

proposed action in comparative form to other lease 

sale alternatives allowable under Section 18 of the 

OCSLA, including the No Action alternative (i.e., no 

lease sale). Thus, the Secretary of the Interior has the 

ability to choose any of the alternatives, including the 

No Action alternative, after weighing possible benefits 

and adverse environmental impacts.

The alternatives in this Supplemental EIS provide a 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-25

Commenter Comment ID Comment Response

makes auctioning off all of the Gulf of Mexico not 

under moratorium, i.e., the proposed alternative, the 

only way to meet such a need. But OCSLA charges 

the Bureau with ensuring that “environmental 

safeguards” are in place for offshore oil development 

and ensuring the “balance [of] orderly energy 

resource development with protection of the human, 

marine, and coastal environments” and “national 

needs.” Accordingly, the agency should have 

focused its purpose and need inquiry on objectives 

that comport with these statutory duties. The 

narrowly framed purpose and need fails to establish 

and justify a national need for developing these 

areas given that there is already adequate oil and 

gas resources under lease or in development 

coupled with significant growth of renewable and 

cleaner fuels and a commitment to reduce 

greenhouse gas pollution. The Bureau has already 

leased more than 15 million acres of the Gulf of 

Mexico to oil companies, 70 percent of those leased 

acres are not currently in production. Consequently, 

the Bureau overlooks alternatives that use renewable 

energy or conservation to reduce energy 

development. Additionally, the purpose and need of 

leasing everything is not limited to meeting our 

regional and national energy needs, as required by 

OCSLA, and instead could carelessly lease areas for 

export or waste. Nationally, our needs are to shift 

away from oil and gas reliance.

Moreover, NEPA evaluation must take place “before 

decisions are made.” Such an approach ensures 

that agencies will take the requisite “hard look” at 

environmental consequences before approving any 

major federal action. But the Bureau’s purpose and 

need statement indicates that it did just the opposite 

and predetermined the result of its decision-making 

process. In other words, the statement 

reasonable range of alternatives that provide 

environmental safeguards, including alternatives and 

mitigations that can be included at the site-specific 

decision level.

BOEM has also considered alternatives and deferrals 

in addition to Alternatives A-E to ensure that all 

reasonable alternatives have been considered in this 

Supplemental EIS. However, not all of the 

alternatives considered were analyzed in detail 

because they were either outside the scope of the 

lease sale decision, were speculative, were not 

warranted, did not meet the purpose of and need for 

the oil and gas leasing program, or current data did 

not support the alternative. For a summary of the 

alternatives and deferrals considered but not analyzed

in detail, refer to Chapter 2.2.2 of this Supplemental 

EIS and Chapter 2.2.3 of the 2017-2022 GOM 

Multisale EIS for a detailed analysis of each 

eliminated alternative.

As required by the 2017-2022 Five-Year Program, 

10 individual phased decisions on whether or how to 

proceed with each proposed regionwide lease sale will 

be made. So while the obligation to fully comply with 

NEPA does not mature until leases are issued (Center 

for Biological Diversity v. U.S. Department of the 

Interior, 2009; Center for Sustainable Economy v. 

Sally Jewell, 2015), BOEM has chosen to prepare an 

EIS at this stage to analyze the potential 

environmental impacts that could result if exploration, 

development, production, and decommissioning 

activities eventually occur in order to provide the 

context and setting of future proposed actions and to 

better understand the potential impacts associated 

with these types of activities, as well as the cumulative 

impacts on GOM resources. The approach to this 

Supplemental EIS allows more time to include more 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-26 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

demonstrates that the Bureau already made the 

decision to hold offshore oil and gas leases across 

all of the Gulf of Mexico and that its entire analysis 

was framed in a way to support that pre-determined 

outcome. This backward approach reflects a 

fundamental misunderstanding of its legal obligations 

and an apparent desire to appease the oil industry at 

the expense of our ocean environment and climate.

public involvement, evaluate potential impacts, and 

provide for a more informed decision, which in turn 

allows site-specific reviews to tier from this 

Supplemental EIS and be more streamlined.

Because of these multiple and tiered programmatic 

documents, along with future site-specific reviews that 

tier to these programmatic and discretionary 

documents, BOEM has taken a hard look at the 

potential for environmental consequences at each 

phase of the decisionmaking process that considers a 

proposed action in the GOM. At each phase, BOEM 

has identified numerous environmental safeguards to 

minimize the impacts, i.e., through the consideration 

of EISs and programmatic mitigation at the Five-Year 

Program level, consideration of alternatives to limit 

impacts to sensitive topographic features in this 

Supplemental EIS, and commonly applied mitigation 

measures.

Center for 

Biological 

Diversity, 

Sierra Club, 

Gulf 

Restoration 

Network,

Louisiana 

Bucket 

Brigade

CBD,SC,GRN,

LBB-6 

The Draft SEIS fails to properly define baseline 

conditions. NEPA requires the agency to “describe 

the environment of the areas to be affected or 

created by the alternatives under consideration.” 

Thus, the establishment of the baseline conditions of 

the affected environment is a fundamental 

requirement of the NEPA process. “Without 

establishing the baseline conditions which exist in 

the vicinity. . . there is simply no way to determine 

what effect the proposed [project] will have on the 

environment and, consequently, no way to comply 

with NEPA.” The primary deficiency with the Draft 

EIS’ baseline is that it fails to address new key 

information gaps and new information that the Gulf’s 

wildlife, habitat, and human environment continue to 

be adversely affected by the Deepwater Horizon oil 

spill.

The Bureau concedes that it lacks critical information 

Thank you for your comment. BOEM acknowledges 

that there is some lingering uncertainty regarding the 

impacts of the Deepwater Horizon oil spill. However, 

this uncertainty has diminished as new data and 

studies have become available. BOEM has 

incorporated this additional information as appropriate 

and has complied with NEPA procedures for dealing 

with incomplete or unavailable information.

Current baselines are described for all resources 

under their respective “Description of the Affected 

Environment” chapters in the 2017-2022 GOM 

Multisale EIS, from which this Supplemental EIS tiers. 

Specific to the Natural Resource Damage Assessment 

Trustees’ (Trustees) Deepwater Horizon Oil Spill: 

Programmatic Damage Assessment and Restoration 

Plan and Final Programmatic Environmental Impact 

Statement (PDARP/PEIS) (Deepwater Horizon 

Natural Resource Damage Assessment Trustees, 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-27

Commenter Comment ID Comment Response

regarding the effects of the Deepwater Horizon oil 

spill on the Gulf of Mexico, and yet declines to 

consider the latest new information in its baseline 

description. The Deepwater Horizon disaster 

resulted in the deaths of 11 workers and caused a 

spill of approximately 206 million gallons of oil over 

the course of at least 87 days. More than 

1,000 miles of shoreline were contaminated with oil; 

88,522 square miles of ocean—totaling one-third of 

the Gulf of Mexico—were closed to commercial and 

recreational fishing; millions of animals were killed or 

harmed; and local residents were sickened.

Seven years later, the Gulf is still reeling from the 

effects of the spill. Recent studies demonstrate 

severe lung disease in dolphins; near-record lows of 

critically endangered Kemp’s Ridley sea turtle 

nesting; oil dispersants toxic to corals and jellyfish; 

and a “bathtub ring” of oil on the seafloor. Another 

recent study published in April 2016 indicates that 

the spill impacted 19% more coastline than originally 

believed, finding that oil washed up on 1,313 miles of 

coastline along the Gulf of Mexico. In addition, the 

50,000 people involved in cleanup efforts suffer from 

an increased risk of physical and psychological 

injury. Gulf residents are still suffering from 

increased symptoms of depression, anxiety, mental 

illness, and posttraumatic stress.

However, there is new information about the spill and 

longer-term impacts are still being studied. The 

agency notes the availability of the Final 

Programmatic Damage Assessment and Restoration 

Plan and Final Programmatic Environmental Impact 

Statement, but declines to use the information for its 

baseline. The Draft SEIS arbitrarily and capriciously 

states that the injuries assessed in the Deepwater 

Horizon oil spill Natural Damage Resource 

2016), the altered baseline in this Supplemental EIS 

already includes individual protected species directly 

affected by this unexpected, unique catastrophic 

event. The injuries assessed within the PDARP/PEIS 

do not necessarily equate the baseline as defined in 

NEPA, but they were considered when determining 

the baseline for our impact determinations.

BOEM understands that each oil-spill event is unique 

and that its outcome depends on several factors, 

including time of year and location of the release 

relative to winds, currents, land, and sensitive 

resources, as well as specifics of the well and 

response effort. BOEM also understands that the 

severity of impacts from an oil spill cannot be 

predicated on volume alone. BOEM has analyzed a 

low-probability catastrophic event (USDOI, BOEM, 

2017a) in conjunction with its analysis of potential 

effects, as requested by the Council on Environmental 

Quality (CEQ) pursuant to its regulation at 40 CFR 

§ 1502.22. A low-probability catastrophic spill is, by 

definition, not reasonably certain to occur. The return 

period of a catastrophic oil spill in OCS areas is 

estimated to be 165 years, with a 95% confidence 

interval between 41 years and more than 500 years 

(Ji et al., 2014).

Regarding marine mammals, sea turtles, and fish, 

although the Natural Resource Damage Assessment

studies are ongoing, the Trustees’ PDARP/PEIS has 

been released and BOEM has analyzed it for relevant 

information. The injuries assessed within the 

PDARP/PEIS do not necessarily equate the baseline 

as defined in NEPA, but they were considered when 

determining the baseline for our impact 

determinations. With the release of the Trustees’ 

PDARP/PEIS, our understanding of the environmental 

impacts of the Deepwater Horizon explosion, oil spill, 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-28 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

Assessment don’t equate with NEPA baseline. The 

assessment concluded that the recovery of marine 

mammals and sea turtles could take decades and 

significant restoration efforts. Moreover, the Bureau 

has repeatedly admitted in other environmental 

review documents that there are data gaps regarding 

numerous resources in the Gulf of Mexico, including 

wetlands, coastal water quality, offshore water 

quality, air quality, commercial and recreational 

fishing and environmental justice, and that the 

impacts of the Deepwater Horizon oil spill on such 

resources may have changed baseline conditions.

The Bureau must analyze significant new information 

about the effects of the Deepwater Horizon oil spill 

and especially its significant impacts on protected 

species that the agency failed to incorporate into its 

Draft SEIS. For example, the Bureau failed to 

consider an important new special issue in 

Endangered Species Research dedicated to the 

impacts of the Deepwater Horizon oil spill on 

threatened and endangered species. The scientific 

articles in the journal describe a wide range of 

damaging impacts on protected species. The oil spill 

caused significant harm to sea turtles and marine 

mammals including death and injuries, reproductive 

failure, organ damage and massive stranding events.

New research quantifies impacts of the oil spill on 

sea turtles, marine mammals, and fish. For example, 

the science shows the oil spill caused Florida 

loggerhead nest densities to decline 43.7 percent 

from expected nesting rates in 2010. More than half 

of Kemp’s Ridley sea turtles were exposed to oil and 

scientists suspect a link to slowed population growth 

rates. Other research estimates mortality of sea 

turtles based on oiling, models sea turtle oiling and 

confirms effects from the oil spill. For marine 

and response has greatly increased; however, there 

are many ongoing, long-term and monitoring studies 

that are not complete. Therefore, our understanding 

of the lasting effects or long-term recovery of the 

system is still incomplete and has data gaps, but the 

information is not essential to a reasoned choice 

among alternatives and has been analyzed as 

required by regulation at 40 CFR § 1502.22. Where 

gaps remained, BOEM’s subject-matter experts 

exercised their best professional judgment to 

extrapolate baseline conditions and impact analyses 

using accepted methodologies based on credible 

information. BOEM’s subject-matter experts have 

applied other scientifically credible information using 

accepted theoretical approaches and research 

methods, such as information on related or surrogate 

species. Moreover, BOEM will continue to monitor 

these resources for effects caused by the Deepwater 

Horizon explosion, oil spill, and response, and will 

ensure that future BOEM environmental reviews take 

into account any new information that may emerge.

In reference to the Section 7 Consultation, BOEM and 

BSEE have submitted Biological Assessments to the 

National Marine Fisheries Service (NMFS) and U.S. 

Fish and Wildlife Service (FWS), and are actively 

engaged with them in consultation concerning all of 

our past and reasonably foreseeable future activities. 

Until the NMFS’ formal consultation is complete, 

BOEM is under an interim consultation agreement 

with NMFS. The NMFS and FWS understand the 

types and levels of activities that BOEM is engaged in 

and have not raised concerns with our ongoing 

activities. They are fully informed of the potential 

impacts identified in this Supplemental EIS, as well as 

those in the Biological Assessments. The Protected 

Species Stipulation, if applied, would require already 

existing terms and conditions and mitigations 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-29

Commenter Comment ID Comment Response

mammals, the new science documents numerous 

species of cetaceans observed in the oil footprint and 

the oil spill’s lasting impacts.

Researchers found marine mammal reproductive 

failure, impaired stress response and death caused 

by the oil spill. The estimated time to recovery for 

the Barataria Bay dolphins has been estimated at 

39 years.

The location of the Deepwater Horizon oil spill was in 

core sperm whale habitat. The Mississippi Canyon 

provides year-round sperm whale habitat. It is well 

established, on the basis of historic whaling records, 

mark-recapture data, and extensive surveys 

including by GulfCet II and the Sperm Whale Seismic 

Study, that this area constitutes important habitat for 

the Gulf’s small, biologically distinct population of 

sperm whales, most likely due to the input of a 

nutrient-rich, freshwater plume from the Mississippi 

Delta. Nearly all sightings of females and mother-calf 

groups have occurred in the Mississippi Canyon 

area, strongly suggesting it functions as a nursery 

ground. Reports to the Gulf of Mexico Research 

conference in 2016 and 2017 indicated that the 

animals are no longer feeding in a large area around 

the Deepwater Horizon wellhead. Acoustic 

monitoring also shows that this area constitutes the 

area with the vast majority of social activity. Surveys 

also show that the sperm whales are present here

throughout the year. New information that the 

Bureau must consider includes the unusually high 

number of four reported stranded sperm whale 

calves in the Gulf in 2016.

New scientific studies of the impacts of the 

Deepwater Horizon oil spill on fish shows that not 

only did the oil spill cause up to $1.2 billion in 

implemented to protect species at the lease sale 

stage. As the stipulation notes, BOEM and BSEE can 

condition approval of any postlease authorization or 

permit on compliance with the most current mitigations 

or requirements to protected listed species or habitats 

at the time. The staged OCSLA decisionmaking and 

approval process ensures that BOEM and BSEE can 

require additional protected species protections after 

leases are issued.

Refer to Chapter 5.8 of this Supplemental EIS for 

more information on the Endangered Species Act 

(ESA) consultations.

In addition, refer to the response to Comment 

USFWS-1, which indicates that FWS is developing a 

Biological Opinion for BOEM on the effects of oil and 

gas leasing, exploration, development, production, 

decommissioning, and all related activities in the Gulf 

of Mexico OCS within existing lease areas and those 

proposed for future leasing in the WPA, CPA, and 

EPA through the year 2022.
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-30 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

damage to the Gulf’s commercial fisheries, but also 

significantly harmed fish habitat. For example, the oil 

spill affected about five percent of the spawning 

habitat during the peak spawning time for Atlantic 

bluefin tuna—an imperiled, overfished species. 

Researchers are concerned that because the oil has 

been linked to deformation and death of eggs and 

larval fish that there could be continuing populationlevel impacts. Additionally, new science shows that 

the phenanthrene, a polycyclic aromatic hydrocarbon 

(PAH), released from the oil caused the heart 

malfunctions in fish affected by the oil spill. The 

scientists note that there are also human health 

concerns associated with this finding because similar 

effects can occur in humans.

The Draft SEIS section on protected species is 

wholly inadequate, not only for not incorporating this 

new information, but also because it doesn’t take a 

hard look at the impacts from the leasing. 

Compounding this problem, the Bureau reinitiated 

Section 7 consultation under the ESA following the 

Deepwater Horizon oil spill in 2010, but the agency 

has yet to complete that consultation seven years 

later. Accordingly, the Bureau does not have an 

accurate picture of the effects that authorizing more 

offshore oil and gas drilling (including in the very 

same area where the Deepwater Horizon spill 

occurred) could have on already imperiled species.

Sierra Club SC-3 BOEM has repeatedly admitted that it lacks critical 

information regarding the effects of the Deepwater 

Horizon oil spill on the Gulf of Mexico. It has also 

repeatedly admitted that there are data gaps 

regarding numerous resources in the Gulf, including 

wetlands, coastal water quality, offshore water 

quality, air quality, commercial and recreational 

fishing and environmental justice, and that the 

impacts of the Deepwater Horizon oil spill on such 

BOEM acknowledges that there is some lingering 

uncertainty regarding the impacts of the Deepwater 

Horizon oil spill. However, this uncertainty has 

diminished as new data and studies have become 

available. BOEM continues to analyze the Deepwater 

Horizon explosion, oil spill, and response as 

information becomes available, and it was evaluated 

as part of the baseline for resources in this 

Supplemental EIS. In addition, in each resource 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-31

Commenter Comment ID Comment Response

resources may have changed baseline conditions. 

BOEM cannot properly define the environmental 

baseline, and cannot conduct a proper NEPA 

analysis unless and until these significant data gaps 

are filled.

chapter, BOEM has complied with NEPA procedures, 

as described in the regulation at 40 CFR § 1502.22, 

for dealing with incomplete or unavailable information. 

BOEM has made some changes to this Supplemental 

EIS in order to clarify the nature of the incomplete or 

unavailable information related to the impacts of the 

Deepwater Horizon oil spill on the baseline conditions 

of various resources.

BOEM has revisited the baseline description and 

cumulative impacts analysis in the Final 2017-2022 

GOM Multisale EIS and has added clarifications and 

additional information where appropriate (i.e., in the 

land use and social factors chapters). That 

information is incorporated into this Supplemental EIS 

by reference.

John Warden JW-2 BOEM has repeatedly admitted that it lacks critical 

information regarding the effects of the Deepwater 

Horizon oil spill on the Gulf of Mexico. BOEM cannot 

properly define the environmental baseline, and 

cannot conduct a proper NEPA analysis unless and 

until significant data gaps are filled.

Joint Trades JT-28 In comments on the Draft Multisale EIS dated 

June 6, 2016, API noted the confusion concerning 

BOEM’s use of the acronym “EIA” to describe one 

thing in the DSEIS (economic impact area) and 

another in the 5-Year Program Programmatic EIS 

(environmentally important area). This confusion 

persists in the Draft SEIS.

In this Supplemental EIS, the term EIA (i.e., economic 

impact area) represents regions of important 

environmental value where there is potential for 

conflict between ecologically important or sensitive 

habitats; maintenance of social, cultural, and 

economic resources; and possible oil and gas 

development.

As far as the use of the term “areas of concern” 

versus “environmentally important areas” in the 

2017-2022 Five-Year Program EIS, the use of 

environmentally important areas is broader than areas 

of concern and therefore more appropriate in this 

context. The acronym “EIA” has been used in the 

Bureau of Ocean Energy Management’s NEPA 

documents for economic impact areas since the 

2007-2012 WPA/CPA Supplemental EIS (USDOI, 

MMS, 2007a).

No CEQ regulations or guidance exist for the use of 

acronyms. However, style guides recommend, when 

you introduce new or unfamiliar acronyms, spelling out 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-32 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

the component words first and then placing the 

acronym in parentheses. As is common with most 

technical and government documents, BOEM also 

includes a list of abbreviations and acronyms for each 

NEPA document.

Sierra Club SC-2 BOEM has already leased over 23 million acres of 

the Gulf to oil companies, and nearly three million 

acres of the Alaskan Arctic. Many of the leases in 

the Gulf of Mexico are relatively new leases, 

meaning that, by BOEM's own admission, production 

under these leases will last up to 70 years. BOEM's 

analysis fails to consider why the OCS areas already 

under lease are not sufficient to supply the nation's 

energy needs while we transition away from dirty 

fossil fuels and toward clean, sustainable energy.

BOEM is responsible for administering the leasing 

program for oil and gas resources on the OCS and for 

developing a 5-year schedule of proposed lease sales 

designed to “best meet national energy needs for the 

five-year period following [the schedule’s] 

approval . . .” (Section 18 of the OCSLA [43 U.S.C. § 

1344]). The 2017-2022 Five-Year Program is an 

important component of President Trump’s America 

First Energy Plan, which calls for energy policies that 

stimulate our economy, ensure our security, and 

protect our health. For more information, please refer 

to The White House’s website (The White House, 

2017). As stated in Chapter 1.2 of the 2017-2022 

Five-Year Program EIS (USDOI, BOEM, 2016a), 

“Offshore oil and gas production represents 

approximately 11% of the total national oil and gas 

production. Domestic oil and natural gas supplies 

contribute to meeting domestic demand and enhance 

national economic security. The development of an 

OCS oil and gas lease sale schedule for 2017-2022 

will facilitate domestic oil and gas production to meet 

this need.” This Supplemental EIS tiers from the 

2017-2022 GOM Multisale EIS, which tiers from the 

2017-2022 Five-Year Program EIS, which provides an 

analysis of existing and future leases and their 

sufficiency to supply the Nation’s energy needs.

For the GOM’s regionwide single lease sale analysis, 

all areas currently under lease are taken into 

consideration throughout the environmental analyses 

(i.e., cumulative impacts). The cumulative impacts 

analysis considers all of BOEM’s past, present, and 

reasonably foreseeable future actions, as well as 

Alicia Cooke AC-7 The scientific credentials of the BOEM staff, and the

conversations I have had with them in public 

meetings, leave me with no doubt that they 

understand the severity of the climate crisis and a 

need to not only scale back on existing oil production 

but to halt any new development of fossil fuel 

infrastructure. In keeping with the Bureau's mission 

of developing resources in an "environmentally and 

economically responsible way," I see no path forward 

that both opens the Gulf to new drilling and still 

abides by the Paris Agreement.

Gulf 

Restoration 

Network

GRN-11 BOEM cannot permit more drilling when the threat of 

drilling to national security hasn't been evaluated.
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-33

Commenter Comment ID Comment Response

other non-OCS oil- and gas-related activities.

Further, commenters should be aware that any past or 

present commitments made by the U.S. concerning a 

reduction of greenhouse gas (GHG) emissions (e.g., 

Paris Agreement) do not broaden the scope of the 

Bureau of Ocean Energy Management’s NEPA 

analysis at the lease sale stage or require BOEM to 

venture into analyzing the potential worldwide effect of 

GHG emissions that could result from a lease sale.

Allison Kalnik AK-3 If the GoM OCS Lease Sale is to genuinely analyze 

greenhouse gas emissions generated by the project, 

renewable energy must be included as an alternative 

to offshore oil production. This would render the 

current No Action Alternative null and void, which 

states that "If a lease sale were to be cancelled, the 

resulting development of oil and gas would most 

likely be postponed to a future lease sale; therefore, 

the overall level of OCS oil- and gas-related activity 

would only be reduced by a small percentage, if 

any." Furthermore, it is arbitrary and capricious to 

assert that no alternative to fossil fuel production 

exists when a neighboring state, Texas, has become 

an industry leader in both wind and solar energy 

production.

Per Section 18 of the OCSLA, BOEM is required to 

develop a schedule of oil and gas lease sales on the 

OCS for 5-year periods. Thus, the OCSLA is the 

implementing legislation driving the purpose, and it is 

the law requiring the Secretary of the Interior to 

propose an action. The need is founded in the 

sources of energy consumption in the United States, 

which were detailed in the 2017-2022 GOM Multisale 

EIS and summarized in this Supplemental EIS. The 

proposed action under NEPA is the proposed 

regionwide lease sales identified in the 2012-2022 

Five-Year Program, and this Supplemental EIS 

determined possible environmental impacts of a 

proposed action in comparative form to other lease 

sale alternatives allowable under Section 18 of the 

OCSLA, including the No Action alternative (i.e., no 

lease sale). Thus, the Secretary of the Interior has the 

ability to choose any of the alternatives, including the 

No Action alternative, after weighing possible benefits 

and adverse environmental impacts.

BOEM has also considered alternatives and deferrals 

in addition to Alternatives A-E to ensure that all 

reasonable alternatives have been considered in this 

Supplemental EIS. However, not all of the 

alternatives considered were analyzed in detail 

because they were either outside the scope of the 

lease sale decision, were speculative, were not 

M. Fleming MF-3 If the same amount of attention and money were 

directed at developing renewable energy sources as 

are currently being given the oil industry, we would 

already be well on our way to seeing a Gulf Coast 

that wouldn’t need to be evacuated within the next 

foreseeable chunk of time due to pipeline-related 

erosion, rising water related to an increasing 

greenhouse effect, and environmental disasters like 

the BP spill.

Peter Shrock PS-8 In general, the EIS is not comprehensive enough 

regarding alternatives. As the BOEM currently 

manages renewable resources, it is reasonable for 

them to consider using the OCS land for projects 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-34 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

other than fossil fuel extraction. warranted, did not meet the purpose of and need for 

the oil and gas leasing program, or current data did

not support the alternative. For a summary of the 

alternatives and deferrals considered but not analyzed

in detail, refer to Chapter 2.2.2 of this Supplemental 

EIS and Chapter 2.2.3 of the 2017-2022 GOM 

Multisale EIS for a detailed analysis of each 

eliminated alternative.

BOEM determined that an analysis of the potential for 

alternative energy is outside the scope of this 

Supplemental EIS for a proposed action. Alternative 

energy is not a reasonable alternative to achieve the 

purpose of and need for the proposed action because 

the development of renewable energy resources in the 

foreseeable future does not fully or partially satisfy the 

purpose of and need for the proposed action at this 

time. The objective of this Supplemental EIS is to 

provide an analysis of the environmental impacts of oil 

and gas leasing.

However, BOEM does recognize the need to 

investigate the potential for alternative energy on the 

Federal OCS. BOEM’s Office of Renewable Energy is 

responsible for developing an offshore renewable 

energy program in the Gulf of Mexico. Information on 

BOEM’s renewable energy program, OCS leases, and 

renewable energy projects (34 proposed or currently 

in development) is available at on BOEM’s website at 

http://www.boem.gov/Renewable-Energy/. 

In response to comments on alternate use of 

platforms, BOEM has analyzed the alternate use of 

facilities on the OCS in the Programmatic 

Environmental Impact Statement for Alternative 

Energy Development and Production and Alternate 

Use of Facilities on the Outer Continental Shelf: Final 

Mobile 

Environmental 

Justice Action 

Coalition 

MEJAC-4 BOEM's pending offshore renewables study offers 

yet another compelling reason to accept 

Alternative E for 2018. Much of the available 

literature on renewable use in Europe suggests in 

comparison that the Gulf of Mexico is not only 

windier and sunnier but that it also has very good 

tidal energy potential, as well. The fact that there is 

such a dearth of parity in renewable energy and 

fossil fuel exploitation in the Gulf is itself a glaringly 

compelling reason to do more renewables and less 

OCS drilling.

Dyan Gibson DyGi-1 Our inevitable fate is a planet run on sustainable and 

clean energy, either now to preserve our fragile 

ecosystems and curb the effects of climate change, 

or later because all our reserves are dried up and we

have descended into the dystopian future of a manmade mass extinction event, where the ravaging of 

our planet has led to famine and wars over dwindling 

resources. Offshore drilling is a a shortsighted and 

environmentally disastrous tactic. Exxon, Chevron, 

Shell, and others - it is time to embrace the green 

energy movement and be the heros of our future. 

Refit your platforms for offshore wind and wave 

energy, and refit your drills for asteroid mining - send 

us into an amazing future of clean air and water and 

healthy ecosystems - please!

Jodi Koszarek JK-1 It is time for America to concentrate her efforts on 

renewable sustainable energy with an eye on the 

future. We can no longer afford to fall behind the 

rest of the world in this regard. A focus on the future 

embraces clean, renewable energy that supports 

health and maintains our future national security.

June Charles JC-3 Fossil fuel has become obsolete and completely 

dangerous to our water, land and air. Our children's 

children will be the recipients of your ignorance and 

greed. We the people say NO to continued use of 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-35

Commenter Comment ID Comment Response

fossil fuel and YES to increased funding and 

attention by the government to renewables. WE are 

ready. They are ready.

Environmental Impact Statement” (USDOI, MMS, 

2007b).

In response to specific questions about the impacts of 

wind energy on resources in the Gulf of Mexico, 

because analysis of the potential for alternative 

energy is outside the scope of this Supplemental EIS, 

these types of questions are not answered in this 

Supplemental EIS. However, several renewable 

energy studies have already been conducted in the 

Atlantic and Pacific regions (https://www.boem.gov/

Environmental-Stewardship/EnvironmentalStudies/Renewable-Energy/Renewable-Energy.aspx), 

and renewable energy feasibility studies have begun 

in the Gulf of Mexico region (https://www.boem.gov/

SDP-2017-2019/).

Rebecca King RK-9 How is BOEM working to implement sustainable 

energy in the Gulf in order to address climate 

change?

350 Louisiana 

- New Orleans

350LANO-2 - With what urgency does BOEM work towards a 

shift to renewable sources of energy in the Gulf of 

Mexico? What are timelines for key steps to make 

this shift?

- According to a Stanford study by Marc Jacobson 

(thesolutionsproject.org) offshore wind energy could 

provide for 60% of all energy needs for Louisiana 

(electricity, transportation, heating/ cooling, industry). 

To what extend is BOEM aware of this study?

- BOEM is promoting offshore wind development on 

the Atlantic and Pacific coast and in Hawaii. How 

does BOEM plan to encourage development of 

offshore wind energy in the GOM?

- What are key challenges to developing wind energy 

resources in the GOM?

- What steps has BOEM undertaken so far to explore 

the potential for wind energy in the GOM?

- What is the level of interest of the offshore wind 

industry in leases in the GOM?

- What is the level of interest on part of the 

governor's office in Texas, Louisiana, Alabama, or 

Florida? Have any attempts been made to establish 

an intergovernmental task force with any of them?

- Have there been any studies evaluating the 

economic impact of developing an offshore wind 

industry in the GOM?

- To what extent can existing oil/gas infrastructure in 

the GOM be utilized to facilitate development of 

renewable sources of energy in the GOM?

- What effect would wind farms in the GOM have on 

migrating birds? Has BOEM initiated any avian 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-36 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

studies in the GOM related to offshore wind farms?

- What effect would wind farms in the GOM have on 

fisheries? Would it be comparable to oil rigs minus 

the pollution associated with the fossil fuel industry? 

Has BOEM initiated any fisheries studies in the GOM 

related to offshore wind farms?

- What would be the economic impact of an offshore 

wind industry in Gulf Coast states? Have there been 

any studies evaluating the economic impact of 

developing wind industry in the GOM? If yes, what 

are the results? If no, when will such studies be 

initiated?

- Given the fact that the platforms for the wind farm in 

Rhode Island were constructed in Houma, LA, how 

does BOEM evaluate the unique position of 

Louisiana's workforce in constructing wind farms in 

the GOM?

- How does the environmental impact of offshore 

wind energy compare to the environmental impact of 

oil and gas production in the GOM?

Renate 

Heurich

RH-2 Offshore wind is a viable source of renewable energy 

in the Gulf of Mexico. What are BOEM's estimates 

as far as delaying the development of renewable 

energy from the GOM by promoting more fossil fuel 

infrastructure at this point?

United States 

Environmental 

Protection 

Agency

USEPA-3 EPA recommends that BOEM include in the DSEIS 

discussions regarding the direct, indirect, and 

cumulative impacts of Tribes or Tribal land within the 

parameter of the specific Lease Sale Blocks for the 

single Oil and Gas lease sales 250 and 251.

Impacts to onshore lands are included in the analysis 

where BOEM discusses direct, indirect, and 

cumulative impacts to land use/coastal infrastructure 

in Chapter 4.14.1. Impacts to populations, including 

Tribal populations, are considered in the social factors’ 

analysis in Chapter 4.14.3, where impacts to 

environmental justice communities have their own 

analysis in Chapter 4.14.3.1. There is no discussion 

of impacts to Tribal lands or their artifacts “within the 

parameter of the specific Lease Sale Blocks for the 

single Oil and Gas lease sales 250 and 251” because 

these leases are 3 miles (mi) (5 kilometers [km]) or 

more offshore. Therefore, there are no Tribal – or 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-37

Commenter Comment ID Comment Response

other – populations living within or along the 

boundaries of the proposed lease sale blocks.

United States 

Fish and 

Wildlife 

Service

USFWS-1 In order to properly address federally threatened and 

endangered species under the jurisdiction of the U.S. 

Fish and Wildlife Service, the Service is developing a 

Biological Opinion for BOEM on the effects of oil and 

gas leasing, exploration, development, production, 

decommissioning, and all related activities in the Gulf 

of Mexico OCS within existing lease areas and those 

proposed for future leasing in the Western Planning 

Area, Central Planning Area, and Eastern Planning 

Area through the year 2022.

BOEM and BSEE have submitted Biological 

Assessments to both NMFS and FWS, and are 

actively engaged with them in consultation concerning 

all of our past and reasonably foreseeable future 

activities. Until the above-mentioned formal 

consultation with NMFS is completed, BOEM is under 

an interim consultation agreement with NMFS. The 

NMFS and FWS understand the types and levels of 

activities that BOEM is engaged in and have not 

raised concerns with our ongoing activities. They are 

fully informed of the potential impacts identified in this 

Supplemental EIS, as well as in the Biological 

Assessments. Copies of the interim concurrence 

letters can be found in Appendix K of the 2017-2022 

GOM Multisale EIS.

Topic 3 – Alternatives

Peter Shrock PS-7 The National Environmental Policy Act (NEPA) 

requires a "detailed statement" of "alternatives to the 

proposed action," which is considered "the heart of 

the environmental impact statement." But BOEM's 

alternatives analysis is seriously lacking. For 

example, BOEM failed to consider an alternative that 

would prohibit drilling in certain biologically sensitive 

areas, such as critical habitat for imperiled 

loggerhead sea turtles; an alternative that would 

restrict the number of wells to be drilled; or an 

alternative that would end all new offshore oil and 

gas leasing pending a plan to limit warming to 1.5 

or 2C.

Thank you for your comment. Per Section 18 of the 

OCSLA, BOEM is required to develop a schedule of 

oil and gas lease sales on the OCS for 5-year periods. 

Thus, the OCSLA is the implementing legislation 

driving the purpose, and it is the law requiring the 

Secretary of the Interior to propose an action. The 

need is founded in the sources of energy consumption 

in the United States that were presented in the 

2017-2022 GOM Multisale EIS and summarized in this 

Supplemental EIS. The proposed action under NEPA 

is a proposed regionwide lease sale identified in the 

2017-2022 Five-Year Program, and this Supplemental 

EIS determined possible environmental impacts of a 

proposed action in comparative form to other lease 

sale alternatives allowable under Section 18 of the 

OCSLA, including the No Action alternative (i.e., no 

lease sale). Thus, the Secretary of the Interior has the 

ability to choose any of the alternatives, including the 

No Action alternative, after weighing possible benefits

Peter Shrock PS-10 Lastly, BOEM failed to look outside their jurisdiction 

for alternatives for the lease sale.

Gulf 

Restoration 

Network

GRN-4 BOEM must develop alternatives to avoid these 

thousands of accidents.

Allison Kalnik AK-2 In particular, the Draft EIS alternatives analysis 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-38 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

provides a narrow range of alternatives that deal only 

with excluding certain sections of the Proposed 

Lease Sale Area. CEQ clearly states that the 

alternatives analysis must include "reasonable 

alternatives not within the jurisdiction of the lead 

agency." All of the proposed alternatives are within 

the jurisdiction of the lead agency.

and adverse environmental impacts.

BOEM has ensured that a reasonable range of 

alternatives to the proposed action, within the 

framework of the 2017-2022 Five-Year Program, has 

been considered in this Supplemental EIS. BOEM 

has considered alternatives and deferrals in addition 

to Alternatives A-E to ensure that all reasonable 

alternatives have been considered in this 

Supplemental EIS. However, not all of the 

alternatives considered were analyzed in detail 

because they were either outside the scope of the 

lease sale decision, were speculative, were not 

warranted, did not meet the purpose and need for the 

oil and gas leasing program, or current data did not 

support the alternative. For a summary of the 

alternatives and deferrals considered but not analyzed 

in detail, refer to Chapter 2.2.2 of this Supplemental 

EIS and Chapter 2.2.3 of the 2017-2022 GOM 

Multisale EIS for a detailed analysis of each 

eliminated alternative.

In those chapters, there are discussions on the 

alternatives excluding loggerhead sea turtle critical 

habitat. A summary analysis can be found in 

Chapter 4.9.2 of this Supplemental EIS, and a full 

analysis of sea turtles, including loggerhead sea 

turtles, can be found in Chapter 4.9.2 of the 2017-

2022 GOM Multisale EIS.

Further, any alternative to delay activities is analyzed 

in this Supplemental EIS as Alternative E. The No 

Action alternative is the cancellation of a single 

proposed regionwide lease sale, and a new decision 

will be made for the next proposed regionwide lease 

sale in the 2017-2022 Five-Year Program.

BOEM has addressed the alternative to stop issuing 

Eli Lamb EL-1 I feel, as a landowner and community member in a 

region which is literally the most vulnerable to both 

climate change-induced disaster and localized 

destruction (land loss, subsidence, fishery damage, 

etc.) directly caused by oil production and 

distribution, that insufficient scholarly rigor has been 

applied to analyzing the differences between the 

5 “Alternatives” included in the EIS.
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-39

Commenter Comment ID Comment Response

leases in the Gulf of Mexico in Chapters 2.4, 

“Reduced Proposed Action (Alternative C),” and 2.5, 

“No Action (Alternative D)” of the 2017-2022 Five-Year 

Program EIS. These alternatives evaluated the 

environmental effects of having reduced areas of 

leasing or no new lease sales during the 2017-2022 

Five-Year Program. The impacts of these alternatives 

are discussed in Chapters 4.4.3.4, “C(4): Exclusion of 

the Gulf of Mexico Program Area,” and 4.4.4, 

“Alternative D – The No Action Alternative,” of the 

2017-2022 Five-Year Program EIS. However, it 

should be noted that oil -and gas-related activities 

stemming from previous programs would continue, 

and only activity resulting from proposed lease sales 

in the new Five-Year Program would be halted.

Peter Shrock PS-9 The required "no-action" alternative is not rigorous; 

to suggest that "no-action" on one particular lease 

sale will have the same effect as some foreseeable 

future sale fails to consider that the "no-action" 

alternative will be selected in the future, and also 

fails to appraise the reduction of cumulative and 

indirect effects as required by NEPA.

The OCSLA requires a staged decisionmaking 

process, beginning with the Five-Year Program, 

continuing through individual lease sales under the 

Five-Year Program, and ultimately to individual 

postlease activities requiring a permit or approval. At 

the lease sale stage of the OCSLA process, BOEM 

typically evaluates all individual lease sale decisions in 

one or more GOM planning areas under the Five-Year 

Program in an EIS. This EIS approach is intended to 

focus the NEPA/EIS process on the staged OCSLA 

process for decisionmaking, including the proposed 

regionwide lease sales, and any new issues and 

information identified since a prior stage. The impact 

analyses in this Supplemental EIS specifically address 

resource impacts associated with holding one 

proposed regionwide lease sale. Therefore, the No 

Action alternative associated with the analyzed 

Federal proposed action is the cancellation or delay of 

a single proposed regionwide lease sale.

If a single proposed regionwide lease sale would be 

cancelled, under the OCSLA, BOEM would be 

required to consider any proposed regionwide lease 

Alicia Cooke AC-1 I appreciate the opportunity to sumbit a public 

comment on the BOEM Draft Supplemental EIS for 

the proposed 2018 lease sales in the Gulf of Mexico. 

In dismissing the environmental and economic 

benefit to a no-action scenario (Alternative E), the 

EIS states: "If a lease sale were to be cancelled, the 

resulting development of oil and gas would most 

likely be postponed to a future lease sale; therefore, 

the overall level of OCS oil- and gas-related activity 

would only be reduced by a small percentage, if 

any." This reasoning fails to consider that the 

"no-action" alternative will be selected in the future,

and also fails to appraise the reduction of cumulative 

and indirect effects (both environmental and 

economic) as required by NEPA.
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-40 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

sales remaining in the current Five-Year Program, if 

applicable, or proposed as part of a future Five-Year 

Program. Therefore, a decision to cancel a single 

proposed regionwide lease sale will not alter future 

decisions for proposed regionwide lease sales in the 

GOM, as required by the OCSLA. The decision point 

is at the individual proposed action or lease sale 

stage.

By selecting the No Action alternative and avoiding 

those activities associated with a proposed regionwide 

lease sale, those potential impacts related to a single 

proposed regionwide lease sale would be avoided; 

however, please be advised that a decision to cancel 

a single proposed regionwide lease sale would not 

preclude activity related to past lease sales or 

decisions on future lease sales. There are a number 

of currently leased blocks within the proposed 

regionwide lease sale area with proposed plans, and 

BOEM anticipates another decision point for the 

proposed regionwide lease sale, which is proposed as 

part of the 2017-2022 Five-Year Program. Should the 

No Action alternative be selected, in the interim, 

industry may explore and develop their existing 

portfolio of leaseholds subject to the terms of those 

leases and any conditions of approval for plans or 

permits. An individual decision or a series of 

decisions on proposed regionwide lease sales in a 

given planning area may influence industry’s 

decisionmaking or strategy to develop existing leases. 

In this context, the No Action alternative does not 

explicitly presume an identical proposal or one that is 

only delayed into the future. As noted above, under 

the OCSLA, BOEM would be required to consider any 

proposed regionwide lease sales remaining in the 

current Five-Year Program, if applicable, or proposed 

as part of a future Five-Year Program. As such, each 

proposed regionwide lease sale will have its own 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-41

Commenter Comment ID Comment Response

decision point.

Analyzing a permanent no lease option is outside the 

scope of this Supplemental EIS. Cancellation of all 

10 proposed regionwide lease sales in the 2017-2022 

Five-Year Program was analyzed in the 2017-2022 

Five-Year Program EIS (USDOI, BOEM, 2016a), from 

which the 2017-2022 GOM Multisale EIS and this 

Supplemental EIS are tiered.

Stated Preference for an Alternative

Consumer 

Energy 

Alliance

CEA-1 As the Voice of the Energy Consumer, Consumer 

Energy Alliance (CEA) is a nationwide association of 

energy consumers who advocate for balanced 

policies that support access to affordable, reliable 

energy. In addition to our nearly 300 company and 

association members that represent nearly every 

sector of the U.S. economy, CEA’s membership 

includes more than 450,000 individual citizens 

across the country, including over 90,000 in the Gulf 

Coast region. From everyday citizens to truckers, 

manufacturers, farmers, and beyond, our members 

and the American public at large depend on access 

to affordable, reliable energy – and the products it 

produces -- in order to meet daily needs, sustain and 

create jobs, and power the economy.

In recent years, the domestic energy revolution has 

provided a major boost to the American economy 

and consumer pocketbooks, while fundamentally 

transforming the global geopolitical landscape to the 

benefit of U.S. national security. At the same time, 

thanks to continuing improvements in technology, 

practices, and oversight, the United States has 

demonstrated that offshore energy development and

environmental stewardship can and do coexist.

CEA understands that, to meet our long-term energy 

Thank you for your comment. We note that your 

preferred alternative is Alternative A. The Secretary of 

the Interior oversees the OCS Oil and Gas Program 

and is required to balance orderly resource 

development with protection of the human, marine, 

and coastal environments while simultaneously 

ensuring that the public receives an equitable return 

for these resources and that free-market competition 

is maintained. The decision on whether and how to 

proceed with each proposed regionwide lease sale is 

under the authority of the Assistant Secretary for Land 

and Minerals Management and will be disclosed in the 

Record of Decision following publication of this Final 

Supplemental EIS.
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-42 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

needs, we will need access to all of our resources, 

including oil and natural gas, nuclear, solar, wind, 

and beyond. We also understand that oil and natural 

gas will continue to be a critical and dominant part of 

that mix for decades to come. The federal 

government understands this as well, as 

underscored by the Energy Information 

Administration’s forecast that oil and natural gas will 

contribute just as much if not more to our nation’s 

energy portfolio in 2040 than it did in 2016. In 

addition, the Interior Department has concluded that 

not holding Gulf of Mexico lease sales could cause 

billions of dollars in environmental and social costs, 

with imports having to replace the vast majority of 

foregone production. As Interior Secretary Ryan 

Zinke recently stated, "American energy production 

benefits the economy, the environment, and national 

security,” and “it is better to develop our energy here 

under reasonable regulations...rather than have it 

produced overseas under little or no regulations.”

CEA agrees. Indeed, industry and regulators alike 

have taken a number of actions in recent years that 

have further strengthened the safety of offshore 

operations in U.S. waters, including what the Obama 

administration termed “the most aggressive and 

comprehensive reforms to offshore oil and gas

regulation and oversight in U.S. history.”

In short, contrary to assertions by a small but vocal 

group of anti-energy groups, whose unproven and 

unrealistic “just say no to fossil fuels” strategy 

threatens the most vulnerable among us -- low-

income and fixed-income families -- we can protect 

our environment AND meet our energy needs. This 

fact is highlighted by a recent Interior Department 

conclusion that Gulf lease sales have beneficial 

impacts for commercial and recreational fishing and 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-43

Commenter Comment ID Comment Response

recreational resources. More broadly, it is 

highlighted by human experience around the world, 

which shows that modern day energy enables people 

to live healthier and more prosperous lives with 

dignity, all the while contributing to a reduced environmental footprint, while societies that don’t 

have access to modern energy experience greater 

incidences of poverty and increased health and 

environmental risks.

For all these reasons, CEA supports the proposed 

action to hold region-wide lease sales in the Gulf of 

Mexico in 2018, and opposes any alternative that 

would cancel them or further reduce or restrict the 

areas available in those lease sales.

Consumer 

Energy 

Alliance

CEA-4 On behalf of energy consumers across the Gulf 

Coast region and the entire nation, CEA encourages 

the Interior Department to ensure that all Americans are able to affordably air condition and heat their 

homes and feed their children. An “all of the above” 

approach to energy policy is the only sensible 

solution, and that must include the Gulf of Mexico.

That is why CEA urges the Interior Department to 

include valuable offshore opportunities in the Gulf of 

Mexico, and reject any demands to take actions that 

would in any way delay, restrict, or prohibit Lease 

Sales 250 and 251, by finalizing a Supplemental EIS 

that allows these lease sales to proceed without any 

further exclusions or restrictions.

Beth Everage, 

Consumer 

Energy 

Alliance

BECEA-1 Good afternoon. My name is Beth Everage, and I'm 

speaking today on behalf of Consumer Energy 

Alliance (CEA). CEA represents producers and 

consumers of energy from every sector of the 

economy, with more than 450,000 individual 

supporters across the United States, including over 

90,000 in the Gulf Coast region. From everyday 

citizens to truckers, manufacturers, farmers, and 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-44 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

beyond, our members and the American public at 

large depend on access to affordable, reliable energy 

- and the products it produces -- in order to meet 

daily needs, sustain and create jobs, and power the 

economy.

In recent years, the domestic energy revolution has 

provided a major boost to the American economy 

and consumer pocketbooks, while fundamentally 

transforming the global geopolitical landscape to the 

benefit of U.s. national security. At the same time, 

thanks to continuing improvements in technology, 

practices, and oversight, the United States has 

demonstrated that offshore energy development and 

environmental stewardship can and do coexist.

CEA understands that, to meet our long-term energy 

needs, we will need access to all of our resources, 

including oil and natural gas, nuclear, solar, wind, 

and beyond. We also understand that oil and natural 

gas will continue to be a critical and dominant part of 

that mix for decades to come. The federal 

government understands this as well, as 

underscored by the Energy Information 

Administration's forecast that oil and natural gas will 

contribute just as much if not more to our nation's 

energy portfolio in 2040 than it did in 2016.

In addition, the Interior Department has concluded 

that not holding Gulf of Mexico lease sales could 

cause billions of dollars in environmental and social 

costs, with imports having to replace the vast 

majority of foregone production. In the wake of the 

most aggressive and comprehensive reforms to 

offshore oil and gas regulation and oversight in U.S. 

history, it is clearer than ever before that offshore 

energy development and a healthy environment can 

and do exist.
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-45

Commenter Comment ID Comment Response

In short, contrary to assertions by a small but vocal 

group of anti-energy groups, whose unproven and 

unrealistic "just say no to fossil fuels" strategy 

threatens the most vulnerable among us -- low-

income and fixed-income families -- we can protect 

our environment AND meet our energy needs. This 

is borne out not only by government conclusions that 

Gulf lease sales have beneficial impacts for 

commercial and recreational fishing and recreational 

resources, but more broadly by human experience 

around the world, which shows that modern day 

energy enables people to live healthier and more 

prosperous lives with dignity, all the while 

contributing to a reduced environmental footprint, 

while societies that don't have access to modern 

energy are relegated experience greater poverty and 

increased health and environmental risks.

For all these reasons, while CEA will have additional 

comments on the draft supplemental EIS in its formal 

comment letter, we support the proposed action to 

hold regionwide lease sales in the Gulf of Mexico in 

2018, and oppose any alternative that would cancel 

Gulf of Mexico lease sales 250 or 251, or further 

reduce or restrict the areas available in those lease 

sales.

On behalf of energy consumers across Texas, the 

Gulf Coast region, and the entire nation, CEA urges 

the Interior Department to ensure that all Americans 

are able to affordably air condition and heat their 

homes and feed their children. An "all of the above" 

approach to energy policy is the only sensible 

solution, and that must include the Gulf of Mexico.

That is why CEA urges the Interior Department to 

include valuable offshore opportunities in the Gulf of 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-46 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

Mexico, and reject any demands to take actions that 

would in any way delay, restrict, or prohibit Lease 

Sales 250 and 251, by finalizing a Supplemental EIS 

that allows these lease sales to proceed without any 

further exclusions or restrictions.

Florida 

Department of 

Environmental 

Protection

FDEP-1 Florida State Clearinghouse staff has reviewed the 

proposal under the following authorities: Presidential 

Executive Order 12372; § 403.061(42), Florida 

Statutes; the Coastal Zone Management Act, 

16 U.S.C. §§ 1451-1464, as amended; and the 

National Environmental Policy Act, 42 U.S.C. §§ 

4321-4347, as amended.

Based on the information submitted and minimal 

project impacts, the state has no objections to the 

subject project and, therefore, it is consistent with the 

Florida Coastal Management Program (FCMP). 

Thank you for the opportunity to review the proposed 

plan.

Thank you for your comment. The States’

coordination with BOEM is an important part of the 

lease sale process.

Alicia Cooke AC-6 The two main alternatives appear to be:

1) Take no action/cancel lease sale (Alternative E): 

Exceed the world's carbon budget in all 

PROBABILITY via future drilling and other avenues 

of fossil fuel exploitation, but with a small path 

forward toward meeting the Paris Agreement as the 

price of oil continues to rise and global public 

pressure leads to reforms such as improved 

renewable technology and carbon pricing initiatives;

2) Continue drilling (Alternatives A-D): Exceed the 

world's carbon budget in all CERTAINTY, albeit 

perhaps less quickly than in a "no action" alternative.

This is not an attractive choice, but as it is what we 

are faced with and it leaves "No Action" as the only 

remotely responsible choice.

Thank you for your comment. We note that your 

preferred alternative is Alternative E. The Secretary of 

the Interior oversees the OCS Oil and Gas Program 

and is required to balance orderly resource 

development with protection of the human, marine, 

and coastal environments while simultaneously 

ensuring that the public receives an equitable return 

for these resources and that free-market competition 

is maintained. The decision on whether and how to 

proceed with each proposed regionwide lease sale is 

under the authority of the Assistant Secretary for Land 

and Minerals Management and will be disclosed in the 

Record of Decision following publication of this Final 

Supplemental EIS.

BOEM determined that an analysis of alternative 

energy and alternative uses of the OCS is outside the 

scope of this Supplemental EIS. BOEM also Amy Merrill AmMe-1 The gulf coast has been hit by the BP oil spill and 

Hurricane Katrina and is STILL trying to recover. 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-47

Commenter Comment ID Comment Response

Please, for pity's sake, do NOT allow a perfect storm 

of another leaking oil well plus a hurricane 

completely devastate this part of the world! Not 

much can be done about hurricanes, but oil wells DO 

NOT HAVE TO BE THERE.

determined that alternative energy is not a reasonable 

alternative to achieve the purpose of and need for the 

proposed action because the development of 

renewable energy resources in the foreseeable future 

does not fully or partially satisfy the purpose of and 

need for the proposed action at this time. However, 

BOEM does recognize the need to investigate the 

potential for alternative energy on the Federal OCS, 

and this is addressed in the 2017-2022 Five-Year 

Program EIS (Chapters 1.4.6.1 and 2.7.4) from which 

the 2017-2022 GOM Multisale EIS tiers, and this 

Supplemental EIS tiers from the 2017-2022 GOM 

Multisale EIS. BOEM's Office of Renewable Energy is 

responsible for developing an offshore renewable 

energy program in the Gulf of Mexico. Information on 

BOEM’s renewable energy program, OCS leases, and 

renewable energy projects (34 proposed or currently 

in development) is available at on BOEM’s website at 

http://www.boem.gov/Renewable-Energy/. 

In reference to fishing, the economy, and tourism, 

BOEM analyzes the impacts of oil and gas production 

on a number of important habitats, resources, and 

socioeconomic entities. For specific information on 

commercial fisheries, recreational fishing, and tourism, 

refer to Chapters 4.10, 4.11, and 4.12, respectively.

In reference to climate change, BOEM analyzes and 

considers many facets of the potential effects of 

climate change in its decisionmaking with respect to 

oil and gas leasing, whether in the Five-Year Program 

or lease sale analyses. This Supplemental EIS tiers 

from the 2017-2022 GOM Multisale EIS, which tiers 

from the 2017-2022 Five-Year Program EIS. It 

incorporates by reference a summary of the 

greenhouse gas and downstream emissions 

information that may result from a Gulf of Mexico oil 

and gas lease sale discussed in Chapter 4.0 of the 

Bill Clarke BC-1 Drilling in the Gulf of Mexico for gas and/or oil is 

extremely hazardous and has the potential for severe 

environmental damage, similar to that which has 

happened in the past. Therefore, I am strongly 

opposed to ANY drilling in the Gulf of Mexico.

Carole Tebay CT-1 I am in opposition to the sale of new leases for oil 

and gas in the Gulf because of the......

-oil and gas disasters that have already occurred in 

the Gulf and their effect on wildlife, health, tourism 

and fishing. 

-contribution to ocean acidification

-contribution to climate change

-halting oil and gas leases in the Gulf of Mexico will 

keep tons of carbon in the ground

David Quist DQ-1 I provide these comments both as to the wisdom of 

further leasing in the Gulf, and specifically with 

regard to the proposed EIS for the Gulf of Mexico 

Outer Continental Shelf Lease Sale. The Gulf has 

been abused for far too long and additional lease 

sales make no sense. The environmental risks are 

too great, it frustrates efforts to modernize our 

energy sources and respond to the realities of 

climate change, and damages critical resources.

Jean Publeee JP-1 THE UNITED STATES SHOULD STOP GIVING 

LEASES FOR OIL DRILLING IN THE GULF OF 

MEXICO. THIS GULF IS ALREADY POLLUTED 

WHERE NOTING CAN LIVE AND THIS IS JUST 

FURTHER DESTRUCTION OF AMERICA.

June Charles JC-4 FOSSIL FUEL MUST GO. FOSSIL FUEL MUST 

STAY IN THE GROUND. Do we determine right 

now never to enjoy the fish in the ocean and the 

leisure of beachfront play. You are the government; 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-48 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

you protect us. DO YOUR JOBS - SAY NO TO BIG 

OIL.

2017-2022 GOM Multisale EIS.

Further, commenters should be aware that any past or 

present commitments made by the U.S. concerning a 

reduction of GHG emissions (e.g., Paris Agreement) 

do not broaden the scope of the Bureau of Ocean 

Energy Management’s NEPA analysis at the lease 

sale stage or require BOEM to venture into analyzing 

the potential worldwide effect of GHG emissions that 

could result from a lease sale.

In reference to comments within the Sierra Club form 

letter (SC-1), please refer to the responses to 

Comments SC-2, SC-3, SC-4, and SC-5.

In addition, the petition submitted by Care2 has been 

sent to BOEM Headquarters for consideration in the 

new proposed Five-Year Program. The individual 

comments within the petition were focused at the 

program level rather than comments on this 

Supplemental EIS.

Sierra Club SC-1 3,679 Sierra Club members and supporters have 

submitted comments objecting to the expansion of 

offshore Gulf oil drilling.

Please find two spreadsheets with all of the 3,679 

signatures attached. More than 205 people have 

taken the time to write a personalized comment and 

3474 have signed to the following text:

Seven years ago, an explosion on BP's Deepwater 

Horizon oil rig took 11 lives and led to the largest 

offshore oil spill in US history: 210 million gallons of 

oil flowed out for 87 days.

Damages are still being felt by local communities and 

wildlife. Gulf communities cannot afford the risk that 

comes with new oil and gas leases. I urge you to 

consider the following and reject plans for new oil 

and gas leases in the Gulf:

BOEM's proposal to lease over 70 million acres of 

the Gulf of Mexico so that oil and gas companies can 

drill up to 9.5 billion barrels of oil equivalent over the 

next 70 years will deepen the climate crisis. Climate 

change, driven primarily by the combustion of fossil 

fuels, poses a severe and immediate threat to the 

health, welfare, ecosystems and economy of the

United States and the world. Halting new oil and gas 

leases off our coasts would keep up to 62 billion tons 

of carbon emissions in the ground the pollution 

equivalent of more than 16,000 coal-fired power 

plants.

BOEM has already leased over 23 million acres of 

the Gulf to oil companies, and nearly three million 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-49

Commenter Comment ID Comment Response

acres of the Alaskan Arctic. Many of the leases in 

the Gulf of Mexico are relatively new leases, 

meaning that, by BOEM's own admission, production 

under these leases will last up to 70 years. BOEM's 

analysis fails to consider why the OCS areas already 

under lease are not sufficient to supply the nation's 

energy needs while we transition away from dirty 

fossil fuels and toward clean, sustainable energy.

BOEM has repeatedly admitted that it lacks critical 

information regarding the effects of the Deepwater 

Horizon oil spill on the Gulf of Mexico. It has also 

repeatedly admitted that there are data gaps 

regarding numerous resources in the Gulf, including 

wetlands, coastal water quality, offshore water 

quality, air quality, commercial and recreational 

fishing and environmental justice, and that the 

impacts of the Deepwater Horizon oil spill on such 

resources may have changed baseline conditions. 

BOEM cannot properly define the environmental 

baseline, and cannot conduct a proper NEPA 

analysis unless and until these significant data gaps 

are filled.

Similarly, BOEM must analyze the impacts of 

another catastrophic oil spill. Oil spills and air 

pollution from offshore drilling and industrial facilities 

like refineries that support the industry make people 

sick and disproportionately harm low-income 

neighborhoods and communities of color. But BOEM 

fails to adequately analyze the environmental justice 

impacts of its proposal.

I urge you to halt all new oil and gas lease sales in 

federal waters and keep these dirty fossil fuels in the 

ground.

Lisa Rogers LR-1 As a Florida resident, my husband and I do NOT 

want any more oil leases sold this year, or any year. 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-50 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

Thank you in advance for listening to our concerns.

Center for 

Biological 

Diversity, 

Sierra Club, 

Gulf 

Restoration 

Network,

Louisiana 

Bucket 

Brigade

CBD,SC,GRN,

LBB-14

In conclusion, the Bureau’s leasing proposal would 

cause a wide variety of serious harms to the 

environment, including greenhouse gas emissions 

that will exacerbate climate change, oil spills, and 

further impacts to already imperiled wildlife and local 

communities, many of which are still suffering the 

effects of the Deepwater Horizon oil spill six years 

later.

Accordingly, we urge the Bureau to adopt the 

no-action alternative, end new offshore oil and gas 

leasing, and keep dirty fossil fuels in the ground. If 

the Bureau nevertheless decides to proceed with its 

proposal, it must first address and remedy the 

numerous deficiencies within the Draft SEIS and 

should circulate a revised Draft SEIS with a robust 

site-specific analysis for public comment.

Nicholas Gault NG-1 Please continue to protect our ocean wildlife and 

continue to disallow new leases and drilling in US 

coastal waters.

Peter Shrock PS-13 For these reasons I advocate strongly delaying or 

perhaps even stopping the Gulf of Mexico OCS 

Lease Sale.

Mobile 

Environmental 

Justice Action 

Coalition 

MEJAC-9 I hope BOEM and its leadership within the 

Department of Interior take these and the concerns 

of others seriously enough to understand the very 

positive encouragement available from among 

impacted communities all along our Gulf for a 

concerted effort to thoroughly reconsider Gulf of 

Mexico OCS drilling priorities that adopting 

Alternative E of the 2018 Gulf of Mexico OCS Lease 

Sale Draft SEIS could represent.

Rebecca King RK-10 In conclusion, I recommend no new drilling leases.

Ryan Bowman RB-1 We cannot risk another Deep Water Horizon 

incident. Please do not allow any new offshore 

drilling in the Gulf of Mexico.
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-51

Commenter Comment ID Comment Response

Sarah Danner SD-1 As a lifelong resident of the Gulf Coast, we retired to 

the Florida Panhandle in '03. After checking out 

coastal Texas we decided on Florida because of its 

clean beaches and clear water. The rest of the Gulf 

area aside from Florida was too dirty and polluted 

from extensive oil and gas exploration. I am 

sensitive to fossil fuel pollution. It triggers my 

asthma causing asthmatic bronchitis. Please do not 

extend the leases closer to Florida. We depend on 

tourist dollars for the economy well-being of the 

state. Deepwater Horizon was an example of both

environmental and economic devastation wrought by 

drilling disasters. It also proved that leaks and 

mistakes happen, are not fool-proof, often with 

catastrophic results. Please protect Florida and keep 

one area of the Gulf clean and less polluted. Both 

people and wildlife depend on it.

Kevin Holm KH-1 As a Florida resident, this is important to me. Our 

economy is based on tourism. And tourism revolves 

around our beaches. Oil and our beaches do not go 

well together. And besides Floridas special issues, 

climate science alone should be enough for any 

reasonable person to fight against oil. We need to 

focus on renewables, not filth.

Sarah Howard SH-1 I support ALTERNATIVE E - No new leases in the 

Gulf of Mexico!

Valerie Longa VL-2 The responsibility that we have in Alabama to care 

for this precious environment is great. Alabama is 

number one in aquatic biodiversity, and the Mobile 

Tensaw Delta was recently placed as one of the 

most endangered river systems in the country. The 

resources that we have here need our care, including 

the gulf. My stance on the environmental impact 

statement from BOEM is the no-action option. I 

believe that the no-action option reduces the 

possibility for greater wells to be explored and 

greater infrastructure and expansion of the oil and 

gas industry in the gulf.
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-52 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

Carol “Cay” 

Burton

CB-1 I believe that leasing in the Gulf should cease.

Jackie 

Hartstein

JH-3 But I vote for Alternative E.

Care2 Care2-1 For Earth Day, Donald Trump is trying to open up 

95 million acres of the Gulf of Mexico to new oil 

drilling. He's also working on overturning efforts by 

President Obama to protect the Arctic and the 

Atlantic.

It's been exactly seven years since we watched BP's 

Deepwater Horizon offshore drilling disaster threaten 

the Gulf coast and its communities. We watched the 

oil wash into the nation's most productive fishing 

grounds, and heard from fisherfolk who didn't know 

how they would provide for their families.

We also saw one of the largest oil companies on the 

planet screw up every step of the way as they tried to 

clean up and contain their pollution. Sick workers, 

toxic and ineffective cleanup techniques, oiled turtles 

and dead sperm whales, government agencies 

incapable and unwilling to hold BP accountable to 

their own clean up plan. It was a disgrace.

Offshore drilling is a dirty and dangerous business, 

and we should not allow it on any more of our 

sensitive coastlines.

Petition signed by more than 89,000+ Care2 

members

Signed and sent via this Care2 petition: 

http://www.care2.com/go/z/BOEM

Bob Smith BoSm-1 As a retired middle school science teacher, I 

understand the importance of preserving our natural 

resources. Our beaches and Gulf waters are vital to 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-53

Commenter Comment ID Comment Response

our economy and our future health and prosperity. 

No oil leases should be granted!! I am opposed to 

any new leases.

Carol A. “Cay” 

Burton

CAB-1 I believe that leasing in the Gulf should cease.

Kathleen 

McBride

KM-1 After the disaster with the Deepwater Horizon, I don’t 

think any drilling in the Gulf should be done. It is not 

safe. This spill has impacted our lives and there is 

still oil off the shore of Pensacola.

Lorie Chinn LC-3 There has been a great amount of leases sold 

already. I think that (No Action) or the cancellation of 

the proposed lease sale should be the main focus at 

this time.

Bonnie 

Aylward

BA-4 I encourage no more leasing or drilling in the Gulf of 

Mexico.

Pam Scaggs, 

South Baldwin 

Democrats

PSSBD-2 To issue permits for more drilling offshore is insane. 

Our oceans are our life. Without them being healthy 

and productive, we will perish. Without plankton, all 

forms of life will die.

Carol “Cay” 

Burton

CB-3 While Florida waters are not included at this time, 

Florida waters have been and will be affected by 

spills in nearby states west. Fish, plants and people 

must not be exposed to further chemical pollution 

from predictable spills and their cleanup chemicals.

Carol A. “Cay” 

Burton

CAB-3 While Florida waters are not included at this time, 

Florida waters have been and will be affected by 

spills in nearby states west. Fish, plants, and people 

must not be exposed to further chemical pollution 

from predictable spills and their clean-up chemicals.

Donna Baker DB-1 Like millions of baby boomers, I moved to SW 

Florida for the beaches and beautiful waterways. 

The tourist and fishing industry are huge here. We 

do not want oil rigs offshore. Another spill would be 

disastrous to the wildlife, the economy of Florida, and 

devastate our property values. People come here to 

boat and to fish and vacation on the beach. An oil 

spill would devastate the economy here once again. 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-54 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

Please respect Florida's unique beauty and 

ecosystems and the people who live and work here, 

and the tourist industry. Florida has nothing else. 

Oil rigs employ few people compared to the 

fishing/tourism industry here. Canadians and 

Europeans love to vacation here. Why risk ruining it 

all? Please don't allow offshore drilling in the gulf of 

Mexico!

Francine Slack FS-1 Florida, the land of sunshine, needs more solar 

power investment, not a search for dirty, destructive 

oil.

Additionally, since our economy rests on tourism, as 

well as seafood harvests, it would be suicidal to risk 

fouling our environment with oil exploration and the 

attendant support industries and personnel.

Please refuse any proposals for oil exploration in the 

Gulf of Mexico.

Deborah 

Jiminez

DJ-1 Along with opposing offshore drilling in the Gulf I 

urge you to stop the proposals and Congressional 

bills for fracking in Florida. The state is a beautiful 

state to live in as well as many tourists from around 

the world to visit. Let's keep our waters and our state 

as pristine as possible for future generations to 

come. Let's focus on clean sustainable energy 

alternatives.

Brian A. 

Mayhew

BAM-1 Florida's Gulf coast communities cannot afford the 

economic risk that comes with new oil and gas 

leases in the eastern part of the Gulf. Tar balls and 

oil spills like they have in Louisiana and on Texas 

beaches will ruin our state's beautiful waters, 

beaches, and will ruin our very important tourism 

industry.

There are plenty of areas in the Gulf that have been 

leased and not yet developed. Please reject 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-55

Commenter Comment ID Comment Response

BOEM?s proposal to lease more acreage in the 

eastern Gulf.

Thank you for considering my comments.

Daryl Frahn DaFr-1 The economy of the cities and small towns on the 

Gulf of Mexico rely on tourism. The impact of a spill 

would be catastrophic to businesses and residents.

Mobile 

Environmental 

Justice Action 

Coalition 

MEJAC-1 There are many compelling reasons why 

Alternative E of the 2018 Gulf of Mexico OCS Lease 

Sale Draft SEIS is the only reasonable action for the 

Department of the Interior to take. Taken together 

with respect to the lack of critical data corresponding 

to lingering human and environmental health 

stressors from OCS petrochemical mineral 

extraction, transport, and refining, risk management 

best practice would suggest implementation of the 

precautionary principle as exercised in Alternative E 

is the socially responsible course of action among all 

available alternatives, although not necessarily for 

the reasons cited by BOEM staff.

Mobile 

Environmental 

Justice Action 

Coalition 

MEJAC-8 These points taken in consideration with outstanding 

concerns surrounding the Bureau of Safety and 

Environmental Enforcement's implementation and

oversight protocols by the Government Accounting 

Office paint a picture of Alternative E that isn't just 

attractive to sloganeering activists, but suggests 

sound policy consideration and defensible 

precautionary principle bona fides.

Center for 

Biological 

Diversity, 

Sierra Club, 

Gulf 

Restoration 

Network, 

Louisiana 

Bucket 

CBD,SC,GRN,

LBB-2 

We urge the Bureau to adopt the no action 

alternative and cancel this lease sale because of its 

detrimental impacts on wildlife and coastal 

communities in the Gulf of Mexico. Offshore oil and 

gas activities damage the Gulf’s vulnerable 

ecosystems, erode its coastlines, and deepen our 

climate crisis.
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-56 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

Brigade

Janice 

Overstreet

JO-1 I strongly object to the proposal to lease addition 

acres of the Gulf of MExico to oil companies! This 

would lead to increased risk of accidents which will 

harm the gulf, echosystems, and beaches as well as 

Florida economy.

James Sorrells JaSo-1 The statistics highlight the path we are already on. 

Our inaction will ultimately lead to the demise of 

other species and eventually the human race. How 

we respond in this moment will determine the future 

for our children. ?Americans are already feeling the 

effects of climate change -- and it's bound to get 

worse, according to the National Climate 

Assessment released this week. Among the report's 

findings: Sea level at many of America's largest 

coastal cities could rise 4 feet or more by 2100, 

average temperatures could rise by 10 degrees, 

hurricanes will become stronger, yields of major U.S. 

crops could decline by 2050, more wildlife will go 

extinct, and biodiversity will be altered so much in 

some places "that their mix of plant and animal life 

will become almost unrecognizable." 

~biodiversity.com

Daniel Gillis DaGi-1 Enough is enough! Another Deep water Horizon 

would devastate the the economy as well as the 

ecology of the Gulf states. It is time to back off 

drilling until the ecology heals. The livelihood of 

millions are put at risk to profit the few.

Dennis 

Rentschler

DR-1 SEVERAL OF THE SO CALLED 'THIRD WORLD' 

COUNTRIES ARE NOW AHEAD OF US IN CLEAN 

ENERGY PRODUCTION AND MANUFACTURING. 

WHY ARE WE MOVING BACKWARDS INTO 

THIRD WORLD STATUS???? FOSSIL FUELS ARE 

A DYING ENERGY SOURCE AND YOU CAN'T 

STOP IT. IT'S WHAT THE PEOPLE WANT. IT'S 

WHAT THE ENERGY COMPANIES ARE MOVING 

TOWARD. IT'S WHAT THE PLANET NEEDS TO 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-57

Commenter Comment ID Comment Response

SURVIVE IN THE LONG RUN. FOSSIL FUELS 

WILL NOT 'MAKE AMERICA GREAT AGAIN'. 

THEY WILL MAKE AMERICA DIRTY AGAIN WITH 

POLLUTION, HEALTH ISSUES, LOST REVENUES, 

A LOSS OF GLOBAL TRUST TO CARRY OUT A 

PROMISE, ETC., ETC. IT'S A DYING FUEL 

SOURCE. LET IT R.I.P.

Gary 

Stephens

GS-1 I believe that we have enough evidence from a 

variety of sources that the last thing we need to be 

doing now is encouraging more drilling. We need to 

give this a break for a few years, while we see what 

will change in the energy market. The last thing we 

want is a bunch of drilling that gets abandoned if the 

push for renewable energy makes the progress we 

hope it will.

Ron Masters RM-1 To meet the whole world's COP21 goal of limiting 

warming to 2øC, humanity can afford to emit no 

more than 1 trillion tons of additional CO

2 over the 

next several millennia. That's equivalent to the 

proven reserves of oil; i.e., assets on company 

books. Proven reserves of natural gas would 

contribute almost as much; of coal, three times more. 

Exploration for fossil fuels is a crime against 

humanity. Stop leasing!

David Gorchov DaGo-1 Off-shore drilling necessarily involves risks of spills, 

blowouts, and other accidents, some of which have 

extensive impacts on marine and coastal life and on 

livelihoods, especially in tourism and fishing. I live 

15 miles from the Gulf of Mexico, and strongly 

expose any new offshore drilling.

David Gorchov DaGo-5 I urge you to reject plans for new oil and gas leases 

in the Gulf of Mexico:

Jensie 

Madden

JM-1 Please do not allow any new leases for oil and gas 

exploration in the Gulf. 

For generations my family has lived in Texas, 

enjoying excursions to Gulf beaches for decades of 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-58 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

summers. In my own lifetime I have seen the 

change in the beach, especially Padre Island, from 

pristine to almost constant "tar" in the sand and in 

the water.

The disadvantages of continued oil and gas 

exploration are numerous: degradation of the ocean 

and the beach, the possibility of another Deepwater 

Horizon-type oil spill, and the continued use of fossil 

fuels to the detriment of our future climate.

Resist the short-term advantages and consider the 

long-lasting consequences for our children and 

grandchildren. Please say no to all new oil and gas 

leases in federal waters.

Topic 4 – Environmental Issues and Concerns

Climate Change

Allison Kalnik AK-1 The Gulf of Mexico OCS Lease Sale Draft 

Supplemental Environmental Impact Statement 2018 

does not adequately comply with NEP and fails to 

genuinely address climate change concerns already 

mentioned in previous comments submitted to 

BOEM, namely that: New leases are not compatible 

with U.S. commitment to reduce greenhouse gas 

emissions and remain under 2 degrees Celsius of 

global warming (which requires that 80% of known 

fossil fuel reserves remain in the ground).

BOEM considers many facets of the potential effects 

of climate change in its decisionmaking with respect to 

oil and gas leasing, whether in a Five-Year Program 

or lease sale analysis. This Supplemental EIS tiers 

from the 2017-2022 GOM Multisale EIS, which tiers 

from the 2017-2022 Five-Year Program EIS. It 

incorporates by reference a summary of the 

greenhouse gas and downstream emissions 

information that may result from a Gulf of Mexico oil 

and gas lease sale discussed in Chapter 4.0 of the 

2017-2022 GOM Multisale EIS. The effects that a 

proposed action could have on climate change or the 

effects that climate change could have on the 

proposed action are incorporated by reference into

this Supplemental EIS. BOEM decided to qualitatively 

address climate change impacts since it

acknowledges that methods for quantifying 

greenhouse gas and potential social costs of such 

emissions are still subject to continual improvement.

Peter Shrock PS-11 The EIS does not adequately consider any (indirect, 

direct, cumulative etc) climate change impacts. This 

is especially serious as climate change is the gravest 

threat that the United States and even the world 

faces at present.

Rebecca King RK-11 I feel that this EIS is so compartmentalized that it 

misses the big picture of climate change and how all 

of these ecosystems are connected. Just looking at 

what is in close proximty to the proposed leases is

not acceptable.
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-59

Commenter Comment ID Comment Response

David Quist DQ-3 Finally, it makes no effort to consider the climatic 

impact of further exploration, drilling, and production 

of additional fossil fuels.

Further, commenters should be aware that any past or 

present commitments made by the U.S. concerning a 

reduction of GHG emissions (e.g., Paris Agreement) 

do not broaden the scope of the Bureau of Ocean 

Energy Management’s NEPA analysis at the lease 

sale stage or require BOEM to venture into analyzing 

the potential worldwide effect of GHG emissions that 

could result from a lease sale.

David Gorchov DaGo-4 BOEM?s proposal to lease over 70 million acres of 

the Gulf of Mexico so that oil and gas companies can 

drill up to 9.5 billion barrels of oil equivalent over the 

next 70 years will worsen our nation's emissions of 

greenhouse gases, and make it more difficult to 

mitigate emissions enough to reduce the risk of rapid 

climate change.

Rebecca King RK-7 How were the affects of climate change and the loss 

of Louisiana wetlands due to climate change and oil 

and gas activity analysed?

Louisiana’s land loss has been acknowledged in this

Supplemental EIS, but the contribution from the oil 

and gas industry has been more from inshore 

activities such as the dredging of location canals 

through marshes as opposed to OCS oil- and 

gas-related activity. Separating the causes of such 

land loss is difficult, but one study estimated that the 

total of direct and indirect impacts from OCS oil- and 

gas-related activities from 1955 to 1978 accounted for 

21,863-49,884 hectares (ha) (54,024-123,266 acres

[ac]), or 8-17% of Louisiana’s total wetland loss 

(Baumann and Turner, 1990; Turner and Cahoon, 

1987).

BOEM summarizes estimates of the impact of OCS 

oil- and gas-related activity on coastal wetlands and 

beaches in this Supplemental EIS and elaborates in 

greater detail in the 2017-2022 GOM Multisale EIS, 

from which this Supplemental EIS tiers, based on 

currently available information.

Coastal storms, hurricanes, and sea-level rise are 

addressed in the land use/coastal infrastructure and 

social factors chapters based on existing peerreviewed research.

BOEM analyzes and considers many facets of the 

Gulf 

Restoration 

Network

GRN-12 BOEM must assess the degree to which production 

projected in this SEIS and Multi-year plan contributes 

to the increased annual flood damages outlined by 

the Louisiana Coastal Plan. Climate Change will 

increase Louisiana's flood damages by $3 billion 

annually buy 2040 and $12 billion annually by 2060. 

BOEM must determine what component of that 

$3 Billion or $12 Billion is due to carbon emissions 

from these leases and the leases in the multi-year 

EIS Carbon emissions must be accounted for 

quantitatively.

David Quist DQ-6 Loss of hundreds of acres of wetlands, in the context 

of ongoing damage over decades, rising sea levels, 

climate change, and increased storm intensity, is 

significant and more than moderate, taken in context. 

Wetland acreage needs to grow, not shrink, in order 

to retain the viability of both the Gulf and shoreline 

areas.

Wendy King WK-1 Contrary to what the oil industry's supporters say, 

this is about our long-term environmental survival, 

and about the survival of fence-line communities 

near oil refineries and petrochemical plants. Oil 

industry supporters talk about the importance of their 

jobs to the wetlands, and how they hunt and fish 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-60 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

there. These same industries put the canals and 

pipelines through the marshes and wetlands that are 

buffers and protective barriers during tropical storms 

and hurricanes. Those marshes and wetlands are 

now disappearing, because of the saltwater 

introduced by the dredging for those canals and 

pipelines.

potential effects of climate change in its 

decisionmaking with respect to oil and gas leasing, 

whether in the Five-Year Program or lease sale 

analyses. The Five-Year Program EIS includes a full 

analysis of the impact of greenhouse gas emissions 

on different resources, including coastal wetlands, and 

an analysis quantifying the lifecycle GHG emissions 

associated with all 10 GOM lease sales in the 

2017-2022 Five-Year Program. This Supplemental 

EIS tiers from the 2017-2022 GOM Multisale EIS, 

which tiers from the 2017-2022 Five-Year Program 

EIS, and both EISs incorporate the greenhouse gas 

analysis of the Five-Year Program EIS by reference.

Gulf 

Restoration 

Network

GRN-13 The draft supplement also fails to evaluate the social 

impact of the lease sale. Communities within the Gulf 

of Mexico are at the front lines of climate change; 

tribes like isle de Jean Charles band of Biloxi, 

Chitimacha, and Choctaw have left their homes due 

to the effects of climate change. The sale of these 

leases will only exacerbate an impending social and 

economic catastrophe.

Impacts of coastal storms, hurricanes, sea-level rise

and subsidence are addressed in the cumulative 

portion of the land use/coastal infrastructure chapter 

(Chapter 4.14.1), the social factors chapter 

(Chapter 4.14.3), and Chapter 3.3.2 based on 

existing peer-reviewed research. An environmental 

justice determination can be found in Chapter 

4.14.3.1. 

The impacts of climate change are addressed in the 

2017-2022 Five-Year Program and are incorporated 

by reference into this Supplemental EIS. For more 

information on this analysis, please refer to the 

responses to Comments RK-7, GRN-12, DQ-6, and 

WK-1.

Jodi Koszarek JK-2 Climate change is real and it's time we stop 

contributing to it. Coastal communities are the most 

vulnerable to climate change consequences.

Amanda 

Munson

AmMu-1 BOEM?s proposal to lease over 70 million acres of 

the Gulf of Mexico so that oil and gas companies can 

drill up to 9.5 billion barrels of oil equivalent over the 

next 70 years will create problems for local 

communities. It has been proven that offshore drilling 

contributes to coastal erosion--a problem that is ever 

worsening along the Gulf Coast. Louisiana loses 

roughly a football field of coast every day. The loss 

of the coast means that storms coming from the Gulf 

are able to reach further inland where people live, 

and they devastate the areas with torrential rains and 

fierce winds. These storms cause flash floods that 

lead to loss of life and millions of dollars worth of 

property damage. Our communities cannot afford to 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-61

Commenter Comment ID Comment Response

pay this price, and we should not have to. Our 

nation's energy resources should not be obtained at 

the expense of our communities. Please reject 

BOEM's proposal.

Wendy King WK-2 Coastal communities, particularly Native American 

communities like Isle de Jean Charles and PointeAu-Chien, are now moving inland, to higher ground, 

and away from their home territories, due to 

sea-level rise, which is worsened by the 70+ years of 

oil and gas extraction and the canals and pipelines 

constructed to make it easier to move oil and gas 

from the offshore drilling platforms to our state's 

onshore distribution grid.

Greenhouse Gas

Center for 

Biological 

Diversity, 

Sierra Club, 

Gulf 

Restoration 

Network, 

Louisiana 

Bucket 

Brigade

CBD,SC,GRN,

LBB-7 

The Bureau’s analysis of lifecycle greenhouse gas 

emissions resulting from the FPP concludes that 

adding 3.7 billion barrels of oil to the world would 

make no difference for GHG emissions, and would 

even reduce emissions compared to the No Action 

Alternative of no new leasing: “America’s GHG 

emissions will be little affected by leasing decisions 

under the Bureau’s 2017– 2022 OCS Oil and Gas 

Leasing Program and could, in fact, increase slightly 

in the absence of new OCS leasing.” The Bureau 

explains this contradictory conclusion with the 

argument that, in the No Action Alternative, “foreign 

sources of oil will substitute for reduced OCS supply, 

and the production and transport of that foreign oil 

would emit more GHGs.”

The Bureau’s conclusion that the No Action 

Alternative will lead to higher, rather than lower, 

GHGs compared to the lease scenario is deeply 

flawed in several key aspects. First, the Bureau 

reaches this conclusion by failing to conduct a full 

accounting of the GHG emissions that would result 

from the No Action Alternative. The Bureau 

concedes up front that its GHG analysis is limited in 

BOEM considers many facets of the potential effects 

of climate change in its decisionmaking with respect to 

oil and gas leasing, whether in the Five-Year Program 

or lease sale analyses. In the 2017-2022 Five-Year 

Program EIS, BOEM compares greenhouse gas 

emissions from direct OCS emissions to those that 

could occur from energy substitutes that would 

presumably replace OCS production in the absence of 

a new OCS Program and comparable demand levels. 

Downstream greenhouse gases have been quantified

for both the OCS Program and energy substitutes 

required to replace foregone production in the 

absence of leasing. Please refer to the 2017-2022 

Five-Year Program EIS for additional information 

about how BOEM evaluates greenhouse gas 

emissions and climate change. That analysis 

concludes that reducing OCS oil and gas consumption 

in the U.S. and the associated emissions from limiting 

OCS leasing would largely be offset by substitutes 

from other energy sources, either within the United 

States or elsewhere. BOEM has considered a No 

Action alternative (i.e., cancellation of a proposed 

regionwide lease sale); however, that does not 

necessarily equate to zero downstream greenhouse 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-62 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

“not fully capturing global market and GHG 

implications.” In a section on “critical assumptions” 

that affect its GHG estimates, the Bureau states that 

foreign consumption of oil and gas will be 

significantly reduced under the No Action Alternative, 

but that the GHG savings from this reduction “is not 

taken into account” in its analysis. The Bureau 

states that its MarketSim model estimates a 

reduction in foreign oil consumption under the No 

Action Alternative of “approximately 1, 4, and 6 billion 

barrels of oil for the low-, mid-, and high-price 

scenarios, respectively, over the duration of the 

2017–2022 Program.” However, the GHG benefits 

of this reduction of oil consumption are not included 

in the calculation of the GHG emissions that would 

result from the No Action Alternative.

The Bureau justifies this decision not to include these 

significant GHG savings from the No Action 

Alternative by stating that “[o]il consumption in each 

country is different, and the Bureau does not have 

information related to which countries would 

consume less oil.” The Bureau also does not include 

the GHG benefits from the reduction in the foreign 

consumption in natural gas under the No Action 

Alternative because MarketSim does not model 

natural gas fluctuations in the global market.

However, as pointed out in an analysis by experts at 

the Stockholm Environment Institute, despite this 

lack of information, the Bureau is able to estimate the 

GHG savings resulting from the reduced foreign 

consumption of 1, 4, and 6 billion barrels of oil under 

the different price scenarios. Using standard energy 

contents (from the U.S. Department of Energy) and 

carbon contents (from the U.S. Environmental 

Protection Agency), and discounting the oil used in 

products and not combusted (International Energy 

gas emissions from oil and gas unless energy demand 

or supply changes drastically or cost-competitive 

clean energy sources are substituted.

This Supplemental EIS tiers from the 2017-2022 

Five-Year Program EIS, and Chapter 4.1 of this 

Supplemental EIS includes a summary of the 

greenhouse gas and downstream emissions 

information that may result from a Gulf of Mexico oil 

and gas lease sale.

The determination of the U.S. energy needs is based 

on the U.S. Dept. of Energy’s Energy Information 

Administration’s 2016 demand projections and is 

discussed in detail in the 2017-2022 Five-Year 

Program EIS. The Energy Information Administration 

is the principal Federal agency responsible for 

collecting, analyzing, and disseminating energy 

information to promote sound policymaking, efficient 

markets, and public understanding of energy and its 

interaction with the economy and the environment. 

The Energy Information Administration forecasts 

future energy demand and supply based on current 

laws and regulations. BOEM relies on special runs 

performed by the Energy Information Administration’s 

National Energy Modeling System (NEMS) to feed its 

MarketSim model that, in turn, is used to determine 

changes in energy demand and energy substitutes 

under the No Action alternative.

The energy demand analysis from the 2017-2022 

Five-Year Program EIS is incorporated into this 

Supplemental EIS through the tiering process. This 

Supplemental EIS analyzes environmental and 

economic impacts and benefits for the alternatives, 

including the proposed action and No Action 

alternative (i.e., no new leasing).
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-63

Commenter Comment ID Comment Response

Agency), SEI estimated that the reduction in global 

oil consumption would result in a savings of 

2.3 billion tonnes CO2 in high-price scenarios for oil, 

1.6 billion in mid-price scenarios, and 0.4 billion in 

the low-price scenarios. As the SEI analysis points 

out, the decreases in rest-of-world GHG emissions 

under the No Action Alternative are enormous:

These decreases in rest-of-world emissions dwarf 

the official estimated increases in U.S. emissions 

that the Bureau’s official Programmatic 

Environmental Impact Statement reports for its No 

Action Alternative (relative to the Proposed 

Program), which instead amount to just 0.13 billion, 

0.12 billion and 0.013 billion tonnes CO2 for the high, 

mid, and low-price scenarios, respectively. Those 

calculations exclude the far larger emissions 

attributable to the global market effect.

In short, if the Bureau were to account for the effects 

of reducing production on international oil 

consumption, the global GHG impact of the No 

Action Alternative over the life of the 2017-2022 

Program would be a decrease of up to 2.3 billion 

tonnes of CO2 which is greater than a year’s worth of 

emissions from the entire U.S. transportation section 

(i.e.,1.7 billion tonnes CO2).

The failure of the Bureau to account for the GHG 

benefits of reduced foreign oil consumption illustrates 

a problematic inconsistency in how it accounts for 

GHGs occurring outside the US. Under the No 

Action Alternative, the Bureau includes the higher 

GHG emissions associated with importing more 

foreign oil and gas to the US, even though these 

emissions occur primarily outside US borders. 

However, under the No Action Alternative, the 

Bureau does not include the much larger reductions 

Further, commenters should be aware that any past or 

present commitments made by the U.S. concerning a 

reduction of GHG emissions (e.g., Paris Agreement) 

do not broaden the scope of the Bureau of Ocean 

Energy Management’s NEPA analysis at the lease 

sale stage or require BOEM to venture into analyzing 

the potential worldwide effect of GHG emissions that 

could result from a lease sale.
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-64 2018 Gulf of Mexico Supplemental EIS

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in GHG emissions occurring outside US borders that 

result from lower foreign consumption of oil and gas.

The Bureau should also be more transparent in 

acknowledging and accounting for the effects of the 

global market on oil and gas consumption. As noted 

by the Bureau, MarketSim models oil as a “global 

market.” The Bureau briefly acknowledges that, in 

the No Action Alternative, decreased oil and gas 

production reduces demand through reduced energy 

consumption. The Bureau should also directly 

acknowledge that in the case of increased oil and 

gas production under the FPP, global markets will 

respond by decreasing prices that lead to increased 

global consumption. As summarized by SEI:

“the oil market is also highly global, with oil readily 

traded among countries, and substantial 

infrastructure in place to do so. The U.S. both 

imports and exports oil, and world and domestic oil 

prices very closely track each other (U.S. EIA 2016). 

For this reason, we expect that changes in U.S. oil 

production would affect an integrated global oil 

market, an assumption also made by many other 

analysts that have looked at changes in U.S. oil 

supply (Bordoff and Houser 2015; Rajagopal and 

Plevin 2013; Allaire and Brown 2012; Metcalf 2007; 

IEc 2012). Though in the past the oil market could 

be strongly influenced by cartel behavior among a 

small number of producers, many analysts now see 

the market as more likely to behave competitively 

(The Economist 2016; U.S. EIA 2016), meaning that 

increases or decreases in supply do translate into 

shifts in prices and, in turn, consumption.”

A recent, comprehensive analysis of the emissions 

consequences of the US ceasing to issue new 

leases for oil extraction on federal waters and lands, 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-65

Commenter Comment ID Comment Response

and avoiding renewal of existing leases for resources 

that are not yet producing, found that ceasing new 

leasing led to a large GHG emissions benefit. Like 

the Bureau’s analysis, this study accounted for the 

effects of substitution of other fuels for the oil that 

was foregone by ceasing leasing. The analysis 

estimated that cutting federal oil leasing reduces 

global CO

2 emissions in 2030 from oil consumption 

by 54 Mt CO

2, and leads to an increase in CO2

emissions from other fuels of 23 Mt CO

2, for a net 

emissions benefit of 31 Mt CO

2. The study 

recommended that “policy-makers should give 

greater attention to measures that slow the 

expansion of fossil fuel supplies.”

Another problematic element of the Bureau’s 

analysis is that the agency makes several “critical 

assumptions” that are not well-founded and help 

contribute to the flawed conclusion that GHG 

emissions resulting from the No Action Alternative 

will exceed the emissions from extracting and 

consuming billions of barrels of oil. For example, 

one critical assumption is that “near constant 

demand is assumed over the next 40-70 years for oil 

and gas” and that “oil and gas will remain a primary 

energy source” over the next 70 years. The Bureau 

states that it uses the EIA’s 2016 AEO reference 

case projection of near constant demand in oil and 

gas, which “does not assume any future changes in 

laws or policies other than what is incorporated in 

existing laws and policies.” However, the AEO 

reference case makes projections only for the next 

23 years through 2040, whereas the Bureau is 

making the assumption of no change in oil and gas 

demand over the much longer time span of the next 

40 to 70 years. The assumption that oil and gas 

demand will not change during the next 40 to 

70 years is simply not realistic in light of national and 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

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international GHG reduction commitments and the 

rapidly expanding capacity and price 

competitiveness of solar and wind energy that can 

substitute for fossil fuels.

As acknowledged by the Bureau, the US has 

committed to GHG targets that require the US to 

steadily decrease GHG emissions. Under the Paris 

Agreement, which the US signed on April 22, 2016 

as a legally binding instrument through executive 

agreement, the United States has committed to 

holding the long-term global average temperature “to 

well below 2°C above preindustrial levels and to 

pursue efforts to limit the temperature increase to 

1.5°C above preindustrial levels.” The Agreement 

requires a “well below 2°C” climate target because 

2°C of warming is no longer considered a safe 

guardrail for avoiding catastrophic climate impacts 

and runaway climate change. Under the Agreement, 

the US Nationally Determined Contribution (NDC) is 

to reduce net GHG emissions by 26–28% below 

2005 by 2025. Independent of the Paris Agreement, 

the US set a long-term goal of reducing emissions by 

83% below 2005 levels by 2050.

US GHG commitments are not compatible with 

continuing fossil fuel extraction from federal waters 

and lands. The lifecycle GHG emissions from the 

FPP would consume a substantial portion of the 

remaining US carbon budget for staying below 2°C, 

and an even greater portion of the budget for staying 

“well below 2°C” or below 1.5°C. As the Bureau 

acknowledges, for a reasonable chance of 

constraining global temperature rise to 2°C, “full 

lifecycle GHG emissions from past OCS oil and gas 

leasing and the 2017-2022 Program could represent 

as much as one half percent of the remaining global 

carbon budget and potentially could represent up to 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-67

Commenter Comment ID Comment Response

9 percent of the remaining carbon budget for the 

United States.” These percentages of the US carbon 

budget, though high, are actually underestimates 

because they are calculated for a 2°C target, rather 

than the more ambitious targets required under the 

Paris Agreement, and they do not account for the 

substantial portion of the carbon budget that was 

consumed between 2011 and 2015. According to 

the IPCC, total cumulative anthropogenic emissions 

of CO

2 must remain below about 1,000 gigatonnes 

(GtCO2) from 2011 onward for a 66 percent 

probability of limiting warming to 2°C above 

pre-industrial levels, and to 400 GtCO

2 from 2011 

onward for a 66 percent probability of limiting 

warming to 1.5°C. These carbon budgets have been 

reduced to 850 GtCO

2 and 240 GtCO2, respectively, 

from 2015 onward. Using these updated carbon 

budgets, FPP emissions would consume a greater 

portion of global and US carbon budgets than 

reflected in Table 8-10.

The Bureau should also acknowledge the large body 

of scientific research that concludes that vast 

majority of global and US fossil fuels must stay in the 

ground in order to hold temperature rise to well 

below 2°C.90 Scientific studies have estimated that 

68 to 80 percent of global fossil fuel reserves must 

not be extracted and consumed to limit temperature 

rise to 2°C based on a 1,000 GtCO

2 carbon budget. 

An estimated 85 percent of known fossil fuel 

reserves must stay in the ground for a 50 percent 

chance of limiting temperature rise to 1.5°C. 

Effectively, to limit temperature rise to 2°C, fossil fuel 

emissions must be phased out globally by 

mid-century.

In addition, a 2016 analysis found that carbon 

emissions from developed reserves in currently 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-68 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

operating oil and gas fields and mines would lead to 

global temperature rise beyond 2°C. Excluding coal, 

currently operating oil and gas fields alone would 

take the world beyond 1.5°C. To stay well below 

2°C, the study recommends that no new fossil fuel 

extraction or transportation infrastructure should be 

built, and governments should grant no new permits 

for new fossil fuel extraction and infrastructure. 

Moreover, some fields and mines, primarily in rich 

countries, must closed before fully exploiting their 

resources. The analysis concludes that, because 

“existing fossil fuel reserves considerably exceed 

both the 2°C and 1.5°C carbon budgets[, i]t follows 

that exploration for new fossil fuel reserves is at best 

a waste of money and at worst very dangerous.”

Finally, according to a US-focused analysis, the 

United States alone has enough recoverable fossil 

fuels, split about evenly between federal and 

non-federal resources, that if extracted and burned, 

would exceed the global carbon budget for a 1.5°C 

limit, and would consume nearly the entire global 

budget for a 2°C limit. Specifically, the analysis 

found:

• Potential greenhouse gas emissions of federal 

fossil fuels (leased and unleased) if developed would 

release up to 492 gigatons (Gt) of carbon dioxide 

equivalent pollution (CO

2e), representing 46 percent 

to 50 percent of potential emissions from all 

remaining U.S. fossil fuels.

• Of that amount, up to 450 Gt CO

2e have not yet 

been leased to private industry for extraction;

• Releasing those 450 Gt CO

2e (the equivalent 

annual pollution of more than 118,000 coalfired 

power plants) would be greater than any proposed 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-69

Commenter Comment ID Comment Response

U.S. share of global carbon limits that would keep 

emissions well below 2°C.

Specifically for the OCS, recent analyses also show 

that the potential emissions from unleased OCS 

areas alone would consume between 11.6% and 

13.8% of that global 450 Gt CO

2e budget. A report 

issued in August 2016 report finds that burning oil 

and gas under unleased federal waters in the Gulf of 

Mexico would release between 27.79 to 32. Gt CO

2e 

into the atmosphere—the pollution equivalent of 

running 9,500 coal-fired power plants for a year. The 

report also notes that developing the entire Gulf of 

Mexico oil and gas resources would nearly double 

the greenhouse gas pollution of all fossil fuels 

currently under federal leases; and that the 

combined consumption of fossil fuels from the Gulf of 

Mexico with other leased areas would result in the 

United States monopolizing 27 percent of the 

scientifically advised global carbon budget needed to 

limit global warming to 1.5°C.101 Any reasonable 

path towards meeting that goal does not comport 

with continued area-wide lease sales in the OCS.

In sum, the urgent need to prevent the worst impacts 

of climate change means that the US cannot afford 

to invest in new offshore oil and gas leasing that 

locks in carbon intensive production for years into the 

future. Investment in offshore oil infrastructure is 

particularly susceptible to carbon lock-in. Offshore 

oil and gas production requires investments in 

capital-intensive, high-carbon fuel infrastructure that 

resists being shut down and locks in long-term fuel 

supplies, making it more difficult and expensive to 

later shift to a low-carbon pathway and reach 

greenhouse gas targets.

Renate 

Heurich

RH-3 New fossil fuel leasing in the Gulf of Mexico could 

ultimately contribute nearly 33 billion tons of carbon 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-70 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

dioxide equivalent to global warming as much 

greenhouse gas pollution as 9,500 coal-fired power 

plants operating for a year. To what extent will the 

lease sales deepen our climate crisis?

Michael 

Robertshaw

MiRo-1 BOEM's analysis states that more drilling won't have 

an impact on fossil fuel emissions because if no 

drilling takes place in expanded areas, it will take 

place in other areas to make up for it. Is this 

scenario realistic given the Paris Agreement, global 

pressure to promote renewable alternatives and the 

continuously rising price of oil

Renate 

Heurich

RH-1 BOEM's analysis states that more drilling won't have 

an impact on fossil fuel emissions because if no 

drilling takes place in expanded areas, it will take 

place in other areas to make up for it. How realistic 

is this scenario given the Paris Agreement and 

strong global efforts to promote renewable 

alternatives?

Eli Lamb EL-2 Chief among these is the assertion that “No Action” 

would automatically produce more GHG than the 

other alternatives mentioned. It is an abject failure of 

the imagination to suggest that the only result of the 

denial of this lease sale would be a postponed, 

inevitable later lease sale; this failure is made all the 

more absurd when one considers that BOEM itself 

manages a diverse portfolio of renewable energy.

Rebecca King RK-8 Since climate scientists recommend that 80% of the 

remaining fossil fuels must remain in the ground to 

prevent passing the critical 2 degree point, how does 

it make any sense to lease for new drilling?

350 Louisiana 

- New Orleans

350LANO-1 Climate scientist tell us that a majority of all known 

fossil have to stay in the ground if we want to have a 

50/50 chance avoid catastrophic climate change 

(McGlade, Ekins, Nature, 1/8/2015). The U.S. has 

signed the Paris Climate Agreement, pledging to cut 

emissions between 26 and 28% compared with 2005 

levels by 2025.
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-71

Commenter Comment ID Comment Response

- Does BOEM agree that climate change is 

presenting a significant danger to our society and 

societies globally?

Center for 

Biological 

Diversity, 

Sierra Club, 

Gulf 

Restoration 

Network,

Louisiana 

Bucket 

Brigade

CBD,SC,GRN,

LBB-8 

In calculating the warming impact of methane 

produced by offshore production, the Bureau uses an 

outdated, incorrect global warming potential (GWP) 

for methane which substantially underestimates its 

climate impact. The Bureau uses a GWP for 

methane of 25 over a 100-year time period. 

However the 2013 IPCC Fifth Assessment Report 

clearly establishes a GWP of 36 for fossil fuel 

sources of methane over a 100-year time period. 

Importantly, the GWP of methane over a 20-year 

period is even higher at 87, meaning that methane is 

87 times stronger in trapping heat than CO2 over a 

20-year period. It is critical that the Bureau’s 

quantitative assessment account for methane’s 

short-term (20-year) warming impact using the latest 

peer reviewed science to ensure that potentially 

significant impacts are not underestimated or 

ignored. These estimates are essential given the 

importance of near-term action to ameliorate climate 

change focused on preventing the emission of shortlived but potent GHGs like methane that can drive 

the crossing of climate tipping points.

Thank you for your comment. BOEM used the Global 

Warming Potential (GWP) as cited by USEPA. The 

USEPA’s conversion factors are used (USEPA, 2015) 

and are as follows:

Greenhouse Gas Global Warming Potential 

(CO2e)

CO2 1

CH4 25

N2O 298

Source: USEPA, 2015. 

BOEM used the U.S. Environmental Protection 

Agency’s GWPs from the 2014 Emissions Inventory 

study, which is a calendar year 2014 inventory, and 

the most recent emissions inventory. These data can 

be found in the U.S. Environmental Protection 

Agency’s Emission Factors for Greenhouse Gas 

Inventories (USEPA, 2015) and at the following 

website: https://www.epa.gov/sites/production/files/

2015-12/documents/emission-factors_nov_2015.pdf. 

If there are updated GWPs at the time that BOEM 

conducts future inventory efforts, the updated GWPs 

will be evaluated for use in BOEM’s future inventory 

efforts.

In addition, BOEM used the 20-year warming impacts 

from USEPA’s website: https://www.epa.gov/

ghgemissions/understanding-global-warmingpotentials#Learn why. 

The U.S. primarily uses the 100-year GWP as a 

measure of the relative impact of different GHGs. 

350 Louisiana 

- New Orleans

350LANO-5 What is the estimated amount of methane spilled/ 

leaked into the GOM annually associated with gas 

production?
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-72 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

However, the scientific community has developed a 

number of other metrics that could be used for 

comparing one GHG to another. These metrics may 

differ based on timeframe, climate endpoint 

measured, or method of calculation.

Estimated methane releases are beyond the scope of 

this Supplemental EIS because BOEM’s postlease 

plan approvals assess emissions and require air 

quality dispersion modeling to assess VOCs and 

GOADS (Gulfwide Offshore Activity Data System) 

reports to compare data to review for compliance by 

BSEE.

Center for 

Biological 

Diversity, 

Sierra Club, 

Gulf 

Restoration 

Network,

Louisiana 

Bucket 

Brigade

CBD,SC,

GRN,LBB-9 

The Draft SEIS’s finding that GHG emissions would 

be lower with a lease sale than in the absence of a 

lease sale is arbitrary and capricious because it also 

assumes that the regulatory structure to reduce 

greenhouse gas emissions in place in 2016 under 

President Obama would continue through the 

lifespan of the lease sale. The Trump administration, 

however, has reversed course on pollution controls, 

especially for the fossil fuel industry. Specifically, 

Trump lifted the permanent ban on offshore leasing 

in the Arctic and other areas, froze pending climate 

and energy regulations, cancelled a reporting 

requirement for onshore oil and gas methane 

emissions, lifted a freeze on new coal leases on 

public lands, withdrew the NEPA greenhouse gas 

guidance, opened reviews of important climate rules 

including fuel-efficiency standards, the Clean Power 

Plan, limits on methane emissions at oil and gas 

drilling sites, and the nationwide five-year offshore oil 

and gas leasing plan. These rollbacks and potential 

revisions will impact the greenhouse gas analysis in 

two key ways. These climate rollbacks invalidate the 

models used to prepare the lifecycle greenhouse gas 

analysis because emissions from downstream oil 

and gas use will increase. They also bring into 

BOEM is aware of changing regulations under a new 

administration. However, the analyses conducted for 

a proposed 2018 lease sale are valid in that it is a

proposed regionwide lease sale conducted under the 

current 2017-2022 Five-Year Program. The 

information used to conduct these analyses was the 

best available information at that time.

During preparation of this Supplemental EIS, BOEM 

was working under President Obama’s The All-of-theAbove Energy Strategy as a Path to Sustainable 

Economic Growth (The White House, 2014), which 

has three main goals: to support economic growth 

and job creation; to enhance energy security; and to 

deploy low-carbon energy technologies and lay the 

foundation for a clean energy future. According to that 

plan, oil and natural gas supplies are integral to 

meeting national energy demand.

This plan also aligns with President Trump’s America 

First Energy Plan, which calls for energy policies that 

stimulate our economy, ensure our security, and 

protect our health. For more information, please refer 

to The White House’s website (The White House, 

2017).
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-73

Commenter Comment ID Comment Response

question the underlying assumption that foreign fossil 

fuels have a higher carbon footprint in the absence of 

robust greenhouse gas pollution controls in the US.

In sum, the Draft EIS needs to be revised to fix the 

error in its substitution effects greenhouse gas 

analysis and meaningfully disclose the impacts of its 

action on climate change.

Further, commenters should be aware that any past or 

present commitments made by the U.S. concerning a 

reduction of GHG emissions (e.g., Paris Agreement) 

do not broaden the scope of the Bureau of Ocean 

Energy Management’s NEPA analysis at the lease 

sale stage or require BOEM to venture into analyzing 

the potential worldwide effect of GHG emissions that 

could result from a lease sale.

Well Stimulation

Center for 

Biological 

Diversity, 

Sierra Club, 

Gulf 

Restoration 

Network,

Louisiana 

Bucket 

Brigade

CBD,SC,GRN,

LBB-10

The Bureau must consider new information revealing 

the scope of inherently dangerous offshore fracking 

permitted in the Gulf of Mexico. New information 

reveals that the Bureau permitted oil companies to 

frack offshore wells in the Gulf of Mexico more than 

1,200 times between 2010 and 2014 alone. The 

fracks occurred in at least 630 different wells off the 

coasts of Texas, Louisiana, Mississippi, and 

Alabama; and many took place in critical habitat for 

imperiled loggerhead sea turtles. New information 

also reveals that at least one of the wells connected 

to the flow line involved in a nearly 90,000-gallon oil 

spill in the Gulf of Mexico discovered on May 12, 

2016 was fracked. Offshore fracking has several 

significant harmful impacts beyond that of 

conventional offshore oil and gas development.

For example, oil companies are allowed to dump 

their wastewater — including fracking chemicals — 

into the Gulf of Mexico, which may harm the Gulf’s 

sensitive wildlife. Many fracking chemicals are 

known to be toxic to people and marine animals. 

Forty percent of the chemicals added to fracking 

fluids have ecological effects, meaning they can 

harm aquatic and other wildlife. An analysis of the 

chemicals used during offshore fracking events in 

California found that many of the chemicals could kill 

or harm a broad variety of marine organisms, 

Thank you for your comments. Chapter 3.1.3.1 

(“Development and Production Drilling”) of the 

2017-2022 GOM Multisale EIS provides detailed 

information on hydraulic fracturing on the OCS in the 

Gulf of Mexico, how it is accomplished, and how it 

differs from onshore fracking. Onshore and offshore 

fracking are two very different processes with different 

potential environmental impacts, even though they are 

commonly referred to by the same term, “fracking.” 

Chapter 3.1.5.1 (“Operational Wastes and Discharges 

Generated by OCS Oil- and Gas- Related Facilities”) 

of the 2017-2022 GOM Multisale EIS details 

information on discharges and regulations on OCS oil 

and gas discharges. Chapter 4.2 (“Water Quality”) of 

the 2017-2022 GOM Multisale EIS has detailed 

language on operational discharges and wastes, 

including those from hydraulic fracturing. The 

language in the above-mentioned chapters was added 

to the Final 2017-2022 GOM Multisale EIS based on a 

similar comment from CBD and its joint commenters 

during the 2017-2022 GOM Multisale EIS comment 

period. This Supplemental EIS tiers from the 2017-

2022 GOM Multisale EIS and incorporates the 

language by reference.

The primary impact-producing factor of concern 

related to well stimulation activities in the Gulf of 

Mexico OCS would be discharges of well treatment, 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-74 2018 Gulf of Mexico Supplemental EIS

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including sea otters, fish, and invertebrates. Indeed, 

scientists list some of the chemicals frequently used 

in offshore fracking as among the most toxic in the 

world with respect to aquatic life. Numerous 

scientists and reports have linked fracking to water 

contamination, air contamination, spills, earthquakes 

and birth defects. The Bureau’s supplemental EIS 

must properly account for the added harms and risks 

caused by offshore fracking in the Gulf.

The Draft SEIS, and the documents to which it tiers, 

fail to analyze the environmental impacts of offshore 

fracking and discharge of produced waters, including 

fracking chemicals. There is one vague reference to 

a “frac pack” in describing development and 

production operations, without any analysis of the 

environmental impacts of offshore fracking, in the 

Draft SEIS. The Bureau’s failure to meaningfully 

analyze the impacts of fracking violates NEPA’s 

requirement to take a hard look and to disclose those 

impacts to the public. To the extent that the Bureau 

relies on the Environmental Protection Agency’s 

water pollution permit to account for these impacts, 

such reliance is invalid. Mere reliance on a pollution 

control permit does not excuse an agency from its 

duties to disclose the impacts under NEPA. The 

Draft SEIS doesn’t discuss fracking chemicals in the 

analysis of water quality issues from produced water. 

Nor does it consider the fact that water quality testing

is infrequent and can be taken at-will when such 

chemicals would not be detected.

Additionally, it appears that the brief section of the 

Draft SEIS describing produced water contradicts 

federal records on the amount of wastewater being 

discharged into the Gulf. The Bureau states that all 

offshore oil and gas platforms in the Gulf of Mexico 

discharged roughly 16.7 billion gallons of produced 

completion, and workover fluids, which are discussed 

in Table 3-9 of this Supplemental EIS and in detail in 

Chapters 3.1.3.1, 3.1.5.1, and 4.2 of the 2017-2022 

GOM Multisale EIS. Based on this information, it is 

estimated that 63-70% of development wells may be 

completed for production. A typical completion 

process may include the use of a “frac pack/sand 

proppant pack.” The use of stimulation treatments are 

permitted by BSEE, and the production discharges are 

permitted by USEPA under the National Pollutant 

Discharge Elimination System (NPDES) permit. The 

potential effects of produced waters (including well 

treatment, completion, and workover fluids) on other 

resources, such as deepwater benthic communities 

(Chapter 4.4), live bottom habitats (Chapter 4.6), and 

protected species (Chapter 4.9), have also been 

analyzed and are expected to be negligible due to the 

assumed compliance with all permitting requirements 

and existing regulations.

Environmental issues associated with offshore oil and 

gas operations in Federal waters are governed by 

BSEE’s regulations at 30 CFR § 250.107, Safety and 

Environmental Management Systems’ (SEMS) 

regulations at 30 CFR § 250.1910, and the National 

Pollutant Discharge Elimination System (NPDES) at 

40 CFR part 122. Generally, however, under these 

regulations, oil and gas wastes are not considered 

hazardous.

Produced water, the largest waste stream from 

offshore oil and gas operations, may be discharged to 

the Gulf of Mexico in accordance with USEPA 

Regions 4 and 6 NPDES permits. Spent chemicals 

used in well treatment, completion, and workover 

fluids may be commingled and discharged with 

produced water. Because chemicals used in well 

completions are discharged with produced water, it is 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-75

Commenter Comment ID Comment Response

water in 2014. However, a review of records 

obtained from the Environmental Protection Agency 

pursuant to a request under the Freedom of 

Information Act reveals that offshore oil and gas 

platforms under the jurisdiction of Region 6— federal 

waters in the Western Planning Area and the Central 

Planning Area off the coasts of Texas and 

Louisiana—discharged more than 75 billion gallons 

of produced waters in 2014. This is a significant 

discrepancy that must be remedied, particularly 

considering that produced water contains toxic 

pollutants released during the drilling process. For 

example, produced water can contain harmful 

substances like benzene, arsenic, lead, hexavalent 

chromium, barium, chloride, sodium, sulfates, and 

boron, and it also can be radioactive. Produced 

water itself is potentially harmful to humans, aquatic 

life, and ecosystems—in fact, a study sponsored by 

the U.S. Department of Energy demonstrated that oil 

production yields “environmentally hazardous” 

produced water.

The Bureau must significantly revise its Draft SEIS to 

provide a meaningful analysis of the scope and 

environmental impacts of offshore fracking and other 

unconventional well stimulation practices, or prohibit 

the use of these practices entirely to mitigate the 

potentially hazardous impacts of fracking.

difficult to obtain the volume of produced water that is 

fracking fluid. However, the volume of fracking fluid in 

produced waters is not necessary for this NEPA 

analysis because BOEM accounts for the fracking 

fluid in its analysis of impacts from produced water as 

a whole. BOEM considers the potential impacts from 

the offshore discharge of all produced water to be 

negligible beyond 1,000 meters (m) (3,281 feet [ft]) 

from the discharge point due to rapid dilution of 

produced waters from the discharge point to moderate 

within 1,000 m (3,281 ft) of the discharge. In addition, 

produced-water discharge must meet regulations set 

forth in the U.S. Environmental Protection Agency’s

NPDES permit. The effects of these discharges are 

considered in the water quality analysis in 

Chapter 4.2. For a full water quality analysis, refer to 

Chapter 4.2 of the 2017-2022 GOM Multisale EIS, 

from which this Supplemental EIS tiers.

In reference to the USEPA’s data on produced water, 

BOEM's produced-water data are collected from the 

Office of Natural Resources Revenue (ONRR). The 

ONRR's “Oil and Gas Operations Report” (OGOR) 

collects produced-water data, which can be found on 

ONRR’s website at http://www.onrr.gov/ReportPay/

production-reporting.htm. The OGOR-B report 

includes a disposition code to indicate how the 

produced water is disposed of (i.e., injected on lease, 

injected or transferred off lease, or disposed of). 

BOEM does not manage USEPA’s data. It is likely 

that data collected in different databases will be 

different due to differences in definitions, time periods, 

and data management practices. Despite the 

difference, BOEM considers the potential impacts 

from the offshore discharge of produced water to be 

negligible beyond 1,000 m (3,281 ft) from the 

discharge point to moderate within 1,000 m (3,281 ft). 

The conclusions reached in this Supplemental EIS 

Peter Shrock PS-4 Another issue is that BOEM fails to adequately 

disclose the amount of hydraulic fracturing and other 

unconventional well stimulation will take place under 

the lease sale, and it entirely fails to evaluate the 

impact of discharging wastewater, including toxic 

fracking chemicals, into the Gulf of Mexico.

Maggi Roberts MaRo-3 Toxic waters from fracking are being dumped into 

our Gulf waters with no oversight.

Rebecca King RK-6 A BOEM scientist I spoke with at the public meeting 

said he was concerned about the fracking waste 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-76 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

dumped into the Gulf currently. It is the EPA's job to 

regulate that. In light of Trump's rollback of the EPA 

has BOEM considered that new wells will be 

dumping more and less regulated fracking waste?

remain the same, regardless of which estimate is used 

in an impact analysis, based on the rapid dilution of 

discharge from the source.

350 Louisiana 

- New Orleans

350LANO-4 What is the estimated amount of fracking fluid 

spilled/ leaked into the GOM annually associated 

with oil and gas production?

William Myers WM-1 Hundreds of billions of gallons of TOXIC oil fracking 

waste water are currently being released into the 

world's oceans. Environmental concerns are 

contrary to oil drilling profits. Environmental 

standards will always sink to the lowest allowed by 

law. There are no laws regarding the release of toxic 

fracking waste water into the ocean from drilling 

platforms. Oil companies' motives are no different 

than tobacco companies' motives: Profits at all costs. 

Governmental leaders act as Pontius Pilot while 

God's most precious gift in the known universe is 

being fouled. It's already too late. The 

Anthropocene Era of mass extinctions is upon us.

We must limit strictly limit fracking.

June Charles JC-2 Oh, and what about the increased earthquakes? To BOEM’s knowledge, there have been no reported 

or documented seismic events linked to OCS well 

stimulation activities in the GOM. Onshore and 

offshore fracking are two very different processes with 

different potential environmental impacts, even though 

they are commonly referred to by the same term, 

“fracking.” The onshore operations associated with 

the occurrence of increased seismic activity tend to 

use much higher volumes of water and proppants and 

create much more expansive fractures in the 

formation to stimulate the flow of natural gas or oil. 

For a description of the difference between onshore 

fracking and offshore hydraulic fracturing, please refer 

to Chapter 3.1.3.1 of the 2017-2022 GOM Multisale 

EIS.
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-77

Commenter Comment ID Comment Response

Renewable Energy and Alternative Uses of the OCS

Alicia Cooke AC-2 Without considering the current global understanding 

of the gravity of the climate crisis and political and 

economic measures being subsequently taken (the 

arrogance of the current U.S. administration on this 

issue notwithstanding), this analysis therefore relies 

upon an outdated assumption of the continuing value 

of oil and impracticality of renewable energy. This is 

a dangerous assumption both from a climate

standpoint and economic one.

This Supplemental EIS provides an analysis of the 

environmental impacts of oil and gas leasing. Per 

Section 18 of the OCSLA, BOEM is required to 

develop a schedule of oil and gas lease sales on the 

OCS for 5-year periods. Thus, the OCSLA is the 

implementing legislation driving the purpose, and it is 

the law requiring the Secretary of the Interior to 

propose an action. The proposed action under NEPA 

is a proposed regionwide lease sale identified in the 

2017-2022 Five-Year Program, and this Supplemental 

EIS determined possible environmental impacts of a 

proposed action in comparative form to other lease 

sale alternatives allowable under Section 18 of the 

OCSLA, including the No Action alternative (i.e., no 

lease sale).

BOEM has also considered alternatives and deferrals 

other than Alternatives A-E to ensure that all 

reasonable alternatives have been considered in this 

Supplemental EIS. However, not all of the 

alternatives considered were analyzed in detail 

because they were either outside the scope of the 

lease sale decision, were speculative, were not 

warranted, did not meet the purpose of and need for 

the oil and gas leasing program, or current data did 

not support the alternative. For a summary of the 

alternatives and deferrals considered but not analyzed

in detail, refer to Chapter 2.2.2 of this Supplemental 

EIS and Chapter 2.2.3 of the 2017-2022 GOM 

Multisale EIS for a detailed analysis of each 

eliminated alternative.

BOEM does recognize the need to investigate the

potential for alternative energy on the Federal OCS 

and has considered this alternative in the 2017-2022 

Five-Year Program EIS. However, BOEM did not 

Alicia Cooke AC-5 In light of the previous administration's recognition of 

the collective, global need to limit global temperature 

rise to 1.5 degrees C above pre-industrial levels in 

order to avoid catastrophic climate change, the 

Secretary of the Interior (or other responsible figure) 

should have mandated that BOEM examine a further 

alternative, which is the use of the planning areas 

under its jurisdiction exclusively for the development 

of renewable energy technology. Without seriously 

considering and analyzing such an alternative (even 

if this would necessitate a rulemaking change in 

BOEM leasing protocol), how can the Department of 

Interior/Bureau of Ocean Energy Management 

possibly claim a true understanding of the global 

climate crisis and commitment to meaningful action 

to abide by the Paris Agreements?

Ryan Bowman RB-2 The energy industry worldwide is shifting to 

renewable sources.

Valerie Longa VL-1 I have been a resident of Mobile County for 13 years 

now, and I live in Alabama because of the beautiful 

environment that we have here. I personally 

experienced the BP oil spill and was a part of the 

clean-up efforts. We would go out at night and clean 

up the massive mats of oil that would coat the 

beaches. I also worked with sea turtles and ensuring 

that the baby sea turtles were released in the Atlantic 

side of Florida for a start to a safe life. Because of 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-78 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

those experiences and others in my local community, 

such as an oil pipeline being put through our drinking 

water, a pipeline being put through a historic African 

American community, elementary school, and other 

oil and gas-related projects, I feel very strongly about 

the pursuit of sustainable green energy. It is my 

desire for our government to focus its plans and 

policies on the production of renewable, clean and 

green energy.

perform a detailed analysis of this alternative at the 

2017-2022 Five-Year Program stage because it was 

not a reasonable alternative to achieve the purpose of 

and need for the proposed action because the 

development of renewable energy resources in the 

foreseeable future does not fully or partially satisfy the 

purpose of and need for the proposed action at this 

time.

BOEM's Office of Renewable Energy is responsible 

for developing an offshore renewable energy program 

in the Gulf of Mexico. Information on BOEM’s 

renewable energy program, OCS leases, and 

renewable energy projects (34 proposed or currently 

in development) is available at on BOEM’s website at 

http://www.boem.gov/Renewable-Energy/. 

Further, commenters should be aware that any past or 

present commitments made by the U.S. concerning a 

reduction of GHG emissions (e.g., Paris Agreement) 

do not broaden the scope of the Bureau of Ocean 

Energy Management’s NEPA analysis at the lease 

sale stage or require BOEM to venture into analyzing 

the potential worldwide effect of GHG emissions that 

could result from a lease sale.

Valerie Longa VL-3 I would like to see a divestment from fossil fuels and 

a greater focus on renewables. The focus on 

renewables allows us to be a leader in this energy 

sector. It allows us to create new jobs, expansion of 

job opportunity, and it allows for creativity. The time 

is now for us to step up and to take greater care of 

our natural resources. It is a fact that the health of 

our environment and ecosystems directly equates to 

the greatness of quality of life for people. Therefore, 

it is in our best interest to divest from fossil fuels and 

to make serious plans on how we can begin to utilize 

renewable energy and in greater ways.

Jackie 

Hartstein

JH-4 Just skip us or give us a turbine and our windmill 

thing. If you were here yesterday, we had plenty of 

wind to disperse. And we can do solar panels. If 

you drive down East Bay Boulevard to State 

Road 87, there's acres of solar panels there. We are 

the Sunshine State. We should not be the surrender 

state. That's what I think.

Kathryn R. 

Smith

KS-1 My name is Kathryn R. Smith. I’ve lived in NW 

Florida since June, 1977. I moved here from Dayton, 

Ohio, and the pollution I experienced in Dayton, Ohio 

confirms my strong desire to resist any and all oil 

leases in any portion of Florida. Not only is pollution 

a personal concern, but our economy depends on 

clean, beautiful beaches. Not is not an option once 

leases are approved. Leave our beaches for the 

tourist, who support our economy, and the residents 

to enjoy. I vote!! Keep oil out of Florida! Use solar 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-79

Commenter Comment ID Comment Response

and wind energy!

Lorie Chinn LC-6 Please focus on renewable energy and stop the 

drilling.

M. Fleming MF-1 Please do not lease the Gulf for non-renewable 

energy ventures. While I’m not able to substantiate 

my request with the volume of data available 

regarding the negative impact continuing to use 

natural resources to extract non-renewable fuel, 

hopefully y’all are in direct contact with organizations 

like the Gulf Restoration Network, and the Louisiana 

Bucket Brigade. They have done expensive 

research as to the incredible environmental and 

social costs of keeping the oil industry in Louisiana.

M. Fleming MF-6 Regardless, hopefully your consciences in addition to 

general public outcry will at least put a pause in the 

leasing plans until a better source of renewable 

energy can be utilized.

Pam Scaggs, 

South Baldwin 

Democrats

PSSBD-3 As the Bureau of Ocean ENERGY Management, my 

emphases on Energy, why don't you think about 

turbo wind power? Clean, renewable and there is 

always a wind in the Gulf. Let's try being realistic 

and responsible here. Doing the same thing over 

and over and getting the same results is a sign of 

????

Carol A. “Cay” 

Burton

CAB-5 This country needs to use energy reduction of use 

techniques and invest in alternative renewable fuels, 

not lease the Gulf for further drilling and exploration.

Carol “Cay” 

Burton

CB-5 This country needs to use energy reduction of use 

techniques and invest in alternative renewable fuels, 

not lease the Gulf for further drilling and exploration. 

An example could be that this room that we're using 

today is about 40 degrees. We're wasting energy 

constantly, and it needs to stop.

David Gorchov DaGo-3 We have an expansion of wind and other renewable 

sources of electricity, at prices competitive with fossil 

fuels. We can improve fuel efficiency of vehicles and 

expand mass transit, reducing the need for 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-80 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

petroleum-based fuels.

John Warden JW-3 My family has made its living in the oil bidness for a 

generation. We recognize the opportunities and the 

need to pursue superior alternatives to further 

exploitation of the Gulf of Mexico. I urge you to halt 

all new oil and gas lease sales in federal waters and 

keep these dirty fossil fuels in the ground.

Natural Stressors

Jean Publeee JP-3 THE GULF IS ALREADY HALF DEVOID OF 

OXYGEN FOR ANY FISH OR OCEAN MAMMAL TO 

STAY ALIVE. THE DEAD ZONE KEEPS GROWING 

CONTINUALLY. CRAP AND GARBAGE OF ALL 

KINDS IS ALLOWED TO FLOW INTO THIS GULF.

The hypoxic zone in the Gulf of Mexico is described in 

Chapter 3.3.2.12 of the 2017-2022 GOM Multisale 

EIS, from which this Supplemental EIS tiers. 

Chapter 4.2 of the 2017-2022 GOM Multisale EIS 

describes how hypoxia occurs in the Gulf of Mexico, 

i.e., from upland river runoff with excessive nutrients

and not oil and gas activities. The resource chapters 

in Chapter 4 considered this seasonal occurrence in 

the analysis of potential impacts. Refer to 

Chapters 4.2, 4.5, 4.6.1, 4.6.2, and 4.9.1.

Carol “Cay”

Burton

CB-4 Also, oxygen in the water is rapidly shrinking from 

pollution.

Carol A. “Cay” 

Burton

CAB-4 Also, oxygen in the water is rapidly shrinking from 

pollution.

Air Quality

Consumer 

Energy 

Alliance

CEA-3 At the same time, CEA is concerned about the draft 

Supplemental EIS’ reliance on preliminary results 

from an ongoing study to make conclusions about air 

quality impacts, and use of the draft Supplemental 

EIS to solicit public review and comment on the yetto-be finalized study. Making conclusions based on 

incomplete, inaccurate, or unavailable information --

and seeking input through non-transparent means --

erodes public trust and confidence in government 

and can negatively impact families, citizens, and 

businesses across the country. To ensure sound, 

science-based decision-making, CEA urges the 

Interior Department to exclude the interim study and 

any related conclusions from the final Supplemental 

EIS and to provide adequate opportunities for 

engagement on the study prior to its finalization.

Thank you for your comment. The air quality analysis 

in this Supplemental EIS is centered on the best 

available and credible scientific information. BOEM is 

committed to using the best available scientific 

information in all of its EISs, consistent with the 

information requirements under NEPA. Even though it 

has already been included in the 2017-2022 GOM 

Multisale EIS, the air quality analysis was specifically 

published in the Draft 2018 GOM Supplemental EIS in 

order to obtain public review and comment.

BOEM is in the process of updating the air quality 

modeling based on public comments, and the results 

of the final air quality modeling will be included in a 

future NEPA analysis that will be available for public 

review and comment. The revised air quality model 

run will not be completed before the publication of this 

Final Supplemental EIS. The results of the initial air 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-81

Commenter Comment ID Comment Response

quality model are therefore the best available 

information we have, and they are included in this 

Supplemental EIS as a reference for NEPA analysis. 

The air quality modeling results currently available 

allow consideration of anticipated air quality impacts 

without those impacts being underestimated.

No activities beyond certain ancillary activities are 

actually authorized by the lease; therefore, there are 

few environmental impacts, including on air quality, 

reasonably expected from a proposed lease sale itself 

(refer to Chapter 1.3.1). Should there be any air 

quality impacts suggested from the updated air quality 

modeling, regulations governing postlease plan 

approvals allow for mitigations to address these 

impacts. During its review of any plan submitted 

postlease, BOEM conducts an air quality review to 

determine if additional controls are necessary. At this 

postlease stage, BOEM has the authority to 

disapprove or require additional mitigation to reduce 

impacts from site-specific activities as additional 

information related to the revised air quality modeling 

becomes available. It is anticipated that new air 

quality modeling results will be available for 

consideration before any plan is submitted on a block 

leased as a result of proposed Lease Sale 250. 

Therefore, while additional air quality data would be 

useful in consideration of this lease sale, it is not 

necessary for a decision on this lease sale. Any 

concerns raised by the modeling study will be further 

refined by the time plans are submitted, and/or 

additional plan-specific modeling may be required 

consistent with BOEM’s regulations when the plan is 

submitted for approval.

David Quist DQ-4 As to particular classes of impacts identified in the 

EIS:

Air Quality -

Thank you for your comment. The air quality analysis 

in this Supplemental EIS is centered on the best 

available and credible scientific information. BOEM is 

committed to using the best available scientific 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-82 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

- how can air quality impacts be assessed if the 

necessary air modeling studies won't be completed 

until the fall of 2017?

- the EIS must consider the impact of the lease sale, 

not just the incremental impact in the context of 

existing leases. Focusing on the latter effectively 

underestimates the impacts on those areas not 

currently leased, but which will be after lease sale 

250

- a moderate effect on coastal non-attainment areas 

for certain pollutants is itself significant, and can't be 

minimized simply because the cumulative impacts do 

not, on their own, cause an exceedence

information in all of its EISs, consistent with the 

information requirements under NEPA. The air quality 

analysis was specifically published in the Draft 2018 

GOM Supplemental EIS in order to obtain public 

review and comment. Please refer to BOEM’s 

response to Comment CEA-3 for information detailing 

BOEM’s update of the air quality modeling run and the 

use of the initial air quality analysis in this 

Supplemental EIS. 

This Supplemental EIS considers both the incremental 

impact of a single proposed regionwide lease sale and 

the cumulative impacts of the OCS Oil and Gas 

Program. Refer to Chapter 4.1 for a full analysis of 

air quality.

In reference to the coastal nonattainment areas, 

BOEM is currently in the process of updating the air 

quality modeling based on public comments and will 

publish the results when the analysis is complete.

Maggi Roberts MaRo-2 The full impact of drilling in the Gulf on our air quality 

as well as the impact of pollution to our ocean waters 

needs full consideration.

Thank you for your comment. BOEM has analyzed 

the impacts to air quality and water quality in 

Chapters 4.1 and 4.2 of this Supplemental EIS. For a 

detailed water quality analysis, refer to Chapter 4.2 of 

the 2017-2022 GOM Multisale EIS, from which this 

Supplemental EIS tiers.

Joint Trades JT-1 Our members recognize that offshore operations 

must be conducted safely and in a manner that 

protects the environment. We also recognize that 

policy decisions that impact the offshore oil and gas 

industry must be based on sound science, 

transparency, consultation and adequate review. 

The Draft SEIS raises serious concerns regarding 

these important criteria. Specifically, BOEM has 

elected to include new, substantive, yet still 

incomplete, information from the ongoing Gulf of 

Mexico (GOM) Air Quality Modeling study in the Draft 

SEIS. Even more concerning, BOEM is choosing to 

Thank you for your comment. The air quality analysis 

in this Supplemental EIS is centered on the best 

available and credible scientific information. BOEM is 

committed to using the best available scientific 

information in all of its EISs, consistent with the 

information requirements under NEPA. The air quality 

analysis was specifically published in the Draft 2018 

GOM Supplemental EIS in order to obtain public 

review and comment. Please refer to BOEM’s 

response to Comment CEA-3 for information detailing 

BOEM’s update of the air quality modeling run and the 

use of the initial air quality analysis in this 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-83

Commenter Comment ID Comment Response

use preliminary, incomplete results from this study to 

make National Environmental Policy Act (NEPA) 

environmental impact determinations. Use of an 

incomplete, ongoing work product as a basis for 

drawing conclusions on possible environmental 

impacts is neither prudent nor transparent, and does 

not present an accurate depiction of offshore 

operations to the public and interested stakeholders. 

The Joint Trades believe it is imperative that BOEM 

not utilize the preliminary results from the ongoing 

study as a basis for impact determinations. We 

recommend that the preliminary results only be used 

for analysis and review, but conclusions regarding 

any potential impacts to onshore air quality should 

not be based on an unfinished study.

These concerns are not new. In an earlier letter 

dated January 18, 2017, API objected to BOEM’s 

conclusion in the Final Programmatic Environmental 

Impact Statement for the 2017-2022 Five-year 

Program (5-year Program FPEIS) that offshore oil 

and natural gas activity will lead to moderate onshore 

air quality impacts based on an interim deliverable 

from an ongoing BOEM study. To our knowledge, 

the interim deliverable was not publicly released for 

review. API raised similar concerns again in a letter 

to BOEM on April 10, 2017 regarding the inclusion of 

the preliminary air modeling results in the Gulf of 

Mexico OCS Oil and Gas Lease Sales: 2017-2022; 

Gulf of Mexico Lease Sales 249, 250, 251, 252, 253, 

254, 256, 257, 259, and 261; Final Multisale 

Environmental Impact Statement (Multisale EIS).

Also, the Joint Trades submitted comments on 

June 20, 2016 on BOEM’s proposed Air Quality, 

Reporting and Compliance Rule (Docket ID: 

BOEM-2013-0081) recommending that agency 

decisions should not proceed until there is a 

Supplemental EIS.

BOEM has not discounted industry’s concern on this 

issue and has actively engaged in communications 

with industry to discuss the air quality modeling. In 

addition, BOEM has examined incorporating industry’s 

comments into the new air quality modeling and 

analysis. The results of the final air quality modeling 

will be included in a future NEPA analysis that will be 

available for public review and comment.
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-84 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

demonstration that OCS sources significantly affect 

onshore air quality and jeopardize compliance with 

the NAAQS.

It appears that BOEM continues to discount 

industry’s concerns regarding use of preliminary data 

from the incomplete GOM Air Quality Modeling 

study. We cannot emphasize this point enough – the 

study must be completed and made available for 

public comment and input before the results and 

conclusions are used for policy-making, agency 

decisions, or future rulemaking.

We recommend that BOEM change the process for 

review of the GOM Air Modeling study moving 

forward to one that allows for substantial input from a 

multi-stakeholder group. By establishing such a

group, model inputs, assumptions and results could 

be improved and the overall process would become 

more transparent. Such an approach would likely be 

more cost effective for BOEM as well, since 

re-running year-long photochemical models with 

updated assumptions can be time consuming and 

expensive.

Joint Trades JT-2 The air quality information included in the Draft SEIS 

is incomplete. BOEM has not provided sufficient

documentation on the assumptions that were made 

related to the models, the assumptions and basis for 

the data used as model inputs, and what type of 

adjustments were made as the result of sensitivity 

analysis. Some examples of critical information that 

has not been included in the Draft SEIS are:

• Model input data from the 2011 GOM Emissions 

Inventory (GOADS), including how the emissions 

estimates in the 2011 emissions inventory were 

adjusted prior to use in the modeling study.

• The methodology for developing the default 

Please refer to BOEM’s response to Comment CEA-3 

for information detailing BOEM’s update of the air 

quality modeling run and the use of the initial air 

quality analysis in this Supplemental EIS. 

Based on the revised air quality modeling, BOEM will 

consider including in future NEPA analyses more 

documentation for (1) model input data from the 

Gulfwide Offshore Activity Data System (GOADS) 

adjustments, (2) development of the default emissions 

factors for shallow-water and deepwater platforms 

(and perhaps other water-depth groups) used to 

project future emissions, and (3) development of 

emissions factors for ammonia and lead. Final 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-85

Commenter Comment ID Comment Response

emission factors for Shallow and Deepwater 

platforms used to project future emissions.

• Information on how emission factors for ammonia 

and lead were developed; this information is 

important since the 2011 GOM Emissions Inventory 

did not contain emissions estimates for ammonia and 

lead.

In short, the public has received an unfinished workin-progress document that does not include relevant

information required for the public and interested 

stakeholders to make well-informed, constructive

comments.

modeling results will also be included in these future 

NEPA documents that will be available for public 

review and comment.

Joint Trades JT-3 Since not all supporting information has been made 

available and the GOM air study is still underway, the 

public has no means to determine whether the 

information presented in the Draft SEIS represents 

“the best available data” for NEPA decision-making. 

Of greater concern is the fact that BOEM has chosen 

to utilize an unfinished, work-in-progress study as the 

one of the bases for important decisions regarding 

further development of resources in the GOM.

The air quality analysis in this Supplemental EIS is 

centered on the best available and credible scientific 

information. BOEM is committed to using the best 

available scientific information in all of its EISs, 

consistent with the information requirements under 

NEPA. The air quality analysis was specifically 

published in the Draft 2018 GOM Supplemental EIS in 

order to obtain public review and comment. Please 

refer to BOEM’s response to Comment CEA-3 for 

information detailing BOEM’s update of the air quality 

modeling run and the use of the initial air quality 

analysis in this Supplemental EIS.

Joint Trades JT-4 In numerous instances, information is referenced that 

has been omitted from the Draft SEIS, or the Draft 

SEIS makes contradictory conclusions. Some 

examples include:

• Section 4.1.2.1, Drilling and Production Associated 

Vessel Support, page 4-29 BOEM references 

Section 3.1.4.4 for a discussion of support vessels 

for OCS oil and gas related activities; however, there 

no such section in the Draft SEIS document. In 

addition, other sub-sections in Section 3.1 “Routine 

Activities” do not provide a discussion of support 

BOEM has updated the information in Chapter 

4.1.2.1, under the “Drilling and Production Associated 

Vessel Support” section, to reflect the correct 

reference of Chapter 3.1.4.3, “Service Vessels,” of the 

2017-2022 GOM Multisale EIS.

In reference to assumptions in the air quality 

modeling, all emissions within the GOM geographical 

area were included in the model. BOEM is now in the 

process of updating the air quality model based on 

public comments. The results of the final air quality 

modeling will be included in a future NEPA analysis 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-86 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

vessels.

The conclusion paragraph stating that the impacts of 

support vessels are minor offers no substantiated 

basis for this conclusion; it only references impacts 

“as shown in the model” – a model, as discussed 

above, that has not been completed and made 

available for comment. In addition, it is unclear how

emissions from support vessels were assessed in 

the model. As referenced in BOEM guidance, 

operators are required to assess support vessel 

emissions when the vessel is within 25 miles of a 

facility. For consistency and future comparison of 

the model results to actual OCS emissions, we 

recommend that BOEM include similar assumptions 

in the modeling.

 

• Section 4.1.2.2, Accidental Events, page 4-31

The Draft SEIS states that air emissions from 

accidental events are discussed in Section 3.2.3. 

However, Section 3.2.3 discusses accidental events 

response, but offers no discussion of air emissions 

from accidental events.

that will be available for public review and comment.

BOEM has updated the information in Chapter 

4.1.2.2, “Accidental Events” to reflect the information

described in Chapter 3.2.3.”

Joint Trades JT-5 • The existing OCS oil and gas platform and support 

vessel emissions were developed from the 2011 

Gulfwide inventory based on activity data from 

GOADS. The existing GOM oil and gas emissions 

were held constant for future year projects at the 

2011 level, even though these emissions would likely

decrease over time as existing assets reach the end 

of their productive life and are removed from service. 

For these future year projections, the new emissions 

from new oil and gas platform and support vessels 

from the upcoming lease sale were taken as the 

maximum emissions from any future year in the 

lease period. The total emissions from these new 

platforms and support vessels were estimated to be 

the highest in 2033 for NOx, CO, PM10, PM2.5, lead, 

Please refer to BOEM’s response to Comment CEA-3 

for information detailing BOEM’s update of the air 

quality modeling run and the use of the initial air 

quality analysis in this Supplemental EIS. 

New air quality modeling will contemplate including 

improved projections of activities by removing 

platforms that reached the end of their productive life. 

Decommissioning data from the existing base year to 

2016 will be considered to assist with this effort, along 

with using the cumulative scenario data to further 

decommission existing sources past 2017.
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-87

Commenter Comment ID Comment Response

and ammonia and in 2036 for SO2 and VOC 

emissions. By 2033 and 2036, the emissions from 

the existing GOM oil & gas related sources would 

likely be much lower due to asset retirement, and 

emissions from unrelated onshore sources would 

likely be less as well due to control technology 

installation, calling into question specific changes in 

design values at regulatory monitors that are 

discussed in multiple sections of the Draft SEIS.

Joint Trades JT-6 • There appears to be quite a bit of overprediction

throughout the modeling process, such as the 

number of platforms forecasted for future years in the 

GOM, the direction of onshore flow winds used in the 

WRF model, and the development of worst case 

emissions based on a combination of two different 

forecasted emission years (2033 and 2036), yet the 

uncertainty due to these overpredictions does not

seem to be addressed in the impact section. If 

BOEM is going to issue qualitative conclusions, then 

the uncertainty due to model overpredictions must 

also be addressed. The Draft SEIS makes 

statements about OCS sources contributing to 

exceedances, but those contributions might not be 

impacting NAAQS compliance status considering the 

overpredictions. The Draft SEIS does not discuss 

the uncertainty caveats in the 

summaries/conclusions.

Please refer to BOEM’s response to Comment CEA-3 

for information detailing BOEM’s update of the air 

quality modeling run and the use of the initial air 

quality analysis in this Supplemental EIS. 

BOEM will address the Joint Trades’ comments in 

future NEPA documents as follows:

BOEM’s Office of Resource Evaluation will provide 

updated scenario data that will be reviewed for futureyear emissions inventory development in the new air 

quality modeling run. 

The WRF model is the state-of-the-art atmospheric 

simulation system, commonly used to drive air quality 

models on the regional level. Winds are critically 

important since they drive pollutant dispersion. BOEM 

will therefore consider evaluating and documenting 

the evaluation of winds on significant impact events, if 

any, suggested by the new modeling.

BOEM will examine using reasonably foreseeable 

high year for future-year emissions inventory 

development in the new modeling.

BOEM will contemplate adding an uncertainty 

analysis.
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-88 2018 Gulf of Mexico Supplemental EIS

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Joint Trades JT-7 • Figure C-15 in the Draft SEIS appears to 

overpredict the future number of platforms in 

shallower water depths, particularly platforms in less 

than 60 m of water. A review of Figure C-15 reveals 

that BOEM’s future predictions show 137 new 

platforms (60% of the future total) in less than 60 m 

water depth. However, Figure C-15 does not 

account for historical trends nor ongoing platform 

removals. Using data from BSEE’s Online Data 

Center, the Joint Trades have determined that for 

each year from 1990 to 2016, platform removals 

exceed platform installations in water depths less 

than 60 m (see chart below). Therefore, GOM 

activity in areas of less than 60 m water are centered 

on structure removal not installation. Any future 

projections must account for this type of historical 

trend.

BOEM is now in the process of updating the air quality 

modeling based on public comments. Please refer to 

BOEM’s response to Comment CEA-3 for information 

detailing BOEM’s update of the air quality modeling 

run and the use of the initial air quality analysis in this 

Supplemental EIS. 

BOEM’s Office of Resource Evaluation will provide 

more reasonable shallow-water, future-year 

development with the updated scenario, and caisson 

emissions factors will be considered for single well 

structures in shallow water depths less than 60-m 

(197-ft) in the new modeling. Documentation, 

including final modeling results, will be provided in a 

future NEPA document.

Joint Trades JT-8 Similarly, the number of wells drilled annually since 

1990 has dramatically declined in shallower water 

depths (less than 200 meters). As the chart below 

demonstrates, activity as measured by the number of 

wells drilled is shifting from shallower water depths to 

deeper waters. Any future projections on platform 

locations used in the GOM Air Quality Modeling 

study and Draft SEIS should account for these trends 

to realistically represent future GOM projections.

BOEM is now in the process of updating the air quality 

modeling based on public comments. Please refer to 

BOEM’s response to Comment CEA-3 for information 

detailing BOEM’s update of the air quality modeling 

run and the use of the initial air quality analysis in this 

Supplemental EIS. 

BOEM’s Office of Resource Evaluation will provide 

updated data that will be considered to be used for 

future projections on platform locations in the new 

modeling.

Documentation will be provided in a future NEPA 

document, including final modeling results.

Joint Trades JT-9 • The underlying assumption used in the CAMx 

future year projections is that any currently unleased 

blocks in GOM are equally likely to be developed as 

part of the upcoming lease sale. This assumption 

ends up placing a substantial number of exploration 

and delineation wells (Figure 3-3 on page 3-16) and 

BOEM is now in the process of updating the air quality 

modeling based on public comments. Please refer to 

BOEM’s response to Comment CEA-3 for information 

detailing BOEM’s update of the air quality modeling 

run and the use of the initial air quality analysis in this 

Supplemental EIS.
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-89

Commenter Comment ID Comment Response

development wells (Figure 3-4 on page 3-18) in the 

areas closest to shore, where emissions are most 

likely to have an impact on on-shore receptors. 

Given that the placement of support vessel 

emissions is a function of the location of placement 

in the model, this decision compounds the 

overestimation of near-shore emissions and further 

overstates the on-shore impact. It also contradicts 

the general trends in development in the GOM 

region, which is increasingly moving to deepwater 

leases, which due to their distance from shore would 

likely have a lesser impact on onshore air quality. 

For example, BOEM data on bids received for lease 

sales in 2015 for the Western and Central GOM were 

94% and 70%, respectively at a depth of 400 m 

(~1320 ft) greater2.

BOEM’s Office of Resource Evaluation will provide a 

more realistic account of where future-year activity 

"might" occur, which will be reviewed to aid in spatial 

allocation of future-year estimated emissions in the 

new modeling. Documentation, including final 

modeling results, will be provided in a future NEPA 

document.

Joint Trades JT-10 • In Appendix B which discusses the WRF modeling, 

every wind rose plot presented shows the model 

overpredicted onshore flow at every site in 2012. 

This impacts any results that show an onshore 

impact from offshore sources. It doesn’t appear that 

the overprediction was considered in the 

uncertainties for the results. Data from 2012 is 

particularly important since it was the meteorology 

used in the CAMx model.

BOEM is now in the process of updating the air quality 

modeling based on public comments. Please refer to 

BOEM’s response to Comment CEA-3 for information 

detailing BOEM’s update of the air quality modeling 

run and the use of the initial air quality analysis in this 

Supplemental EIS. 

BOEM will examine providing a robust model 

evaluation for winds in a future NEPA document.

Joint Trades JT-11 • It appears that a limited number of sites were 

selected for the wind rose plot evaluation used in the 

WRF model. For example, no wind data were 

selected for Galveston, TX. Since it seems to be 

important in the future year design value comparison, 

and since Galveston is one of the few nonattainment 

areas along the Gulf Coast, it would be beneficial to 

have the meteorological evaluation for Galveston in 

the WRF model.

BOEM is now in the process of updating the air quality 

modeling based on public comments. Please refer to 

BOEM’s response to Comment CEA-3 for information 

detailing BOEM’s update of the air quality modeling 

run and the use of the initial air quality analysis in this 

Supplemental EIS. 

BOEM will contemplate providing more wind rose 

analysis for 2012, including Galveston, Texas, and will 

include a discussion of those wind rose plots in an 

uncertainty analysis in a future NEPA document.
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

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Joint Trades JT-12 • The upper air qualitative evaluation presented in 

Appendix B is very limited and as such raises several 

questions. Evaluation results are presented for just 

two sites and for just one sounding at each site. 

Using such limited data to represent the upper air 

modeling performance for the entire year is

incomplete and inadequate. How did the rest of the 

year look for these two sites? Why were only two 

sites evaluated when there are nearly ten sounding 

sites along the Gulf Coast? What do the soundings 

look like at times of high ozone and/or PM? We 

recommend that further evaluation be completed and

presented for multiple sounding sites and during 

times of elevated ozone and/or PM.

BOEM is now in the process of updating the air quality 

modeling based on public comments. Please refer to 

BOEM’s response to Comment CEA-3 for information 

detailing BOEM’s update of the air quality modeling 

run and the use of the initial air quality analysis in this 

Supplemental EIS. 

BOEM will consider including more upper air sites 

along the Gulf Coast. Documentation, including final 

modeling results, will be provided in a future NEPA 

document.

Joint Trades JT-13 • Actual monitoring data show that the 

attainment/nonattainment areas along the Gulf Coast 

tend to have their cleanest days when there is a 

consistent onshore flow. The times where there are 

elevated levels of ozone with onshore flow, for 

example, is when there is recirculation of onshore 

emissions and not an impact of offshore emissions. 

The modeling does not appear to match actual 

monitoring conditions. The Joint Trades offer the 

following technical references as additional 

information regarding onshore

ozone concentrations:

o Background ozone concentrations in southeast 

Texas average about 50 ppb, with higher 

concentrations observed when winds originate 

from the continental U.S., and much lower 

concentrations observed when winds originate 

directly from the Gulf of Mexico (NielsenGammon et al., 2005a).

o Days that are dominated by a stationary 

anticyclone (the Bermuda High, for example) tend 

to have lower ozone, in part because this 

BOEM is now in the process of updating the air quality 

modeling based on public comments. Please refer to 

BOEM’s response to Comment CEA-3 for information 

detailing BOEM’s update of the air quality modeling 

run and the use of the initial air quality analysis in this 

Supplemental EIS. 

A more comprehensive data analysis (including 

dominant patterns of wind circulation and pollutant 

concentration at sensitive areas) will be examined in a 

future NEPA document.
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

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circulatory pattern brings steady southeast winds 

from the Gulf of Mexico (Davis et al., 1998).

o Sullivan et al (2009) performed cluster analysis 

on daily 72-hour HYSPLIT back trajectories for 

2000 to 2007 to determine which transport 

patterns were associated with high ozone in the 

HoustonGalveston-Brazoria area. The lowest 

concentrations were observed for the trajectory 

cluster with a long fetch from the Gulf of Mexico 

(Sullivan et. al 2009).

o Higher ozone levels were generally associated 

with backward trajectories over land compared 

with backward trajectories over the Gulf of Mexico 

(Hendler, 2012).

Joint Trades JT-14 • Assumptions regarding support vessel emissions 

are overly conservative and do not represent actual 

GOM operations. It is likely that support vessel 

emissions associated with existing platforms would 

decrease as older platforms are decommissioned, 

and would not be constant at 2012 levels in future 

year predictions. If nearer shore blocks were to be 

developed, they would likely be serviced by some of 

the same support vessels as existing facilities and 

may not have as high of incremental emissions as a 

result. In addition, there are potentially future year 

emission reductions for support vessels that would 

be realized based on new requirements for emission 

performance for vessels (MARPOL Annex 6),

specifically near port locations. Also, the support 

vessel data presented in the Draft SEIS appears to 

show that most support vessel activity is originating 

in Vermilion Parish, Louisiana. However, industry 

operational experience would lead to the conclusion 

that most support vessel activity is originating from 

lower Lafourche Parish, Louisiana. We recommend 

that BOEM specifically examine these assumptions 

BOEM is now in the process of updating the air quality 

modeling based on public comments. Please refer to 

BOEM’s response to Comment CEA-3 for information 

detailing BOEM’s update of the air quality modeling 

run and the use of the initial air quality analysis in this 

Supplemental EIS. 

BOEM’s Office of Resource Evaluation will provide 

updated scenario data that will be considered to 

characterize more reasonably foreseeable support 

vessel activity. Documentation, including final 

modeling results, will be provided in a future NEPA 

document.
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

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in the GOM Air Quality Modeling study and the Draft 

SEIS to ensure support vessel activity is 

characterized correctly.

Joint Trades JT-15 • The Draft SEIS states that fugitive emissions can 

occur during all phases of OCS oil- and gas-related 

activity (Section 4.1.2, Page 4-28). However, 

production activities are the main source of fugitive 

emissions. There may be small fugitive emissions 

from diesel components on vessels and rigs, but 

production fugitive emissions are the primary source 

of fugitive emissions from OCS oil and gas activities. 

The 2011 GOADS report states, “Evaporative losses 

are insignificant in diesel engines due to the low 

volatility of diesel fuels (USEPA 2010).” Fugitive 

emissions are not calculated for diesel components 

on vessels and rigs as part of GOADS. In addition, 

BOEM has previously indicated that fugitive 

emissions may be overestimated by current emission 

factors. But the Draft SEIS contains no discussion of 

if or how adjustments to fugitive emissions data were 

made during the calculation of the platform emission 

factor used for projected future platforms.

BOEM is now in the process of updating the air quality 

modeling based on public comments. Please refer to 

BOEM’s response to Comment CEA-3 for information 

detailing BOEM’s update of the air quality modeling 

run and the use of the initial air quality analysis in this 

Supplemental EIS. 

BOEM will contemplate discussing an uncertainty 

analysis in a future NEPA document. Documentation 

will include final modeling results.

Joint Trades JT-16 One of the Joint Trades’ primary concerns is that the 

Draft SEIS does not contain a complete data set that 

describes the GOM Air Quality Modeling study and 

that the study is not complete. BOEM has elected to 

use the NEPA process and this, as well as 

subsequent SEISs to publish the results of the GOM 

Air Quality Modeling study for public review. Using 

the NEPA process for this purpose is inappropriate 

and decreases the transparency of how the modeling 

study was developed and executed. The use of 

incomplete information presents conclusions about 

the impacts on air quality from offshore operations 

that are not accurate – ultimately, resulting in 

providing incorrect information to the public. In 

addition, by utilizing preliminary, work-in-progress 

information in this (and possibly future) SEIS 

Thank you for your comment. The air quality analysis 

in this Supplemental EIS is centered on the best 

available and credible scientific information. BOEM is 

committed to using the best available scientific 

information in all of its EISs, consistent with the 

information requirements under NEPA. The air quality 

analysis was specifically published in the Draft 2018 

GOM Supplemental EIS in order to obtain public 

review and comment. Please refer to BOEM’s 

response to Comment CEA-3 for information detailing 

BOEM’s update of the air quality modeling run and the 

use of the initial air quality analysis in this 

Supplemental EIS. 

BOEM used the initial results of the “Air Quality 

Modeling in the Gulf of Mexico Region” study, which 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-93

Commenter Comment ID Comment Response

documents, the agency is arriving at conclusions and 

making decisions based on information that may 

significantly change once the study is complete. This 

is not a credible definition of “best available data.”

To maximize transparency and ensure that the best 

available information is made available to the public, 

BOEM must establish a collaborative, multistakeholder input process to review the study inputs, 

methods, assumptions and results, complete the 

study, and make the complete study report available 

for public comment. Preliminary study results should 

not be used in NEPA decisions or future rule-making 

as this is inconsistent with sound science practices 

and could mislead the public.

was the best available science at this time in order to 

draw impact conclusions on air quality. BOEM is 

currently revising the air quality modeling and is taking 

comments from Federal agencies, industry, and the 

general public into consideration in the model run, 

which will be available for review in a future NEPA 

document. BOEM is examining correcting the initial 

air quality model for sea-salt estimates, along with 

caisson emissions, decommissioned structures, and 

locations of platforms. In addition, BOEM is 

considering tagging the model for a single lease sale, 

which was not done in the initial model run. However, 

because the revised air quality modeling will not be 

completed before the publication of this Final 

Supplemental EIS, the results of the initial air quality 

model are still included in this Supplemental EIS as a 

reference for NEPA analysis. The air quality modeling 

results currently available allow consideration of 

anticipated air quality impacts without those impacts 

being underestimated.

In order to address data gaps and current impacts for 

this analysis, BOEM used the initial air quality 

modeling results, emissions inventory data, available 

studies of OCS oil- and gas-related activities, 

postlease exploration and development plan 

information, and current proposed lease sale scenario 

data, as well as previous proposed action scenario 

data, to reach the impact conclusions. This approach 

was adequate because it assessed a combination of 

pollutants from OCS oil- and gas-related activities, 

non-OCS oil- and gas-related activities, and non-oil 

and gas activities.

BOEM is now in the process of updating the air quality 

model based on public comments. BOEM has 

collaborated with USEPA, as well as industry, on the 

review and discussions of the air quality model. In 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

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addition, BOEM has examined and considered 

incorporating industry’s comments into the new air 

quality modeling and analysis. The results of the final 

air quality modeling will be included in a future NEPA 

analysis that will be available for public review and 

comment.

Joint Trades JT-17 BOEM’s air quality authority set forth in OCSLA and 

the Clean Air Act is limited to onshore impacts to the 

NAAQS from offshore development and production. 

Although it may be appropriate for BOEM to consider 

and analyze other pollutants and activities in addition 

to the NAAQS when developing an EIS, only 

potential impacts to the NAAQS should be 

considered when determining future mitigations. For 

example, the Draft SEIS contains extensive 

discussion of greenhouse gases (GHGs). GHGs are 

not NAAQS pollutants, and any future mitigations 

prescribed by BOEM should not be based on 

potential GHG impacts. Specifically, in the Draft 

SEIS:

• Section 4.1.2, Greenhouse Gases Including 

Downstream Gas, Page 4-26 - The entire discussion 

from the beginning of this section on page 4-25 

centers on GHGs, pollutants that BOEM does not 

have authority to regulate because there is no 

NAAQS for these pollutants. However, on page 

4-26, BOEM mentions N2O and black carbon as a 

by-product of flaring. The next sentence states that 

“This practice is rare on the OCS”. Is BOEM 

referring to flaring as being rare, or the conversion of 

flared gas into N2O and black carbon as being rare? 

This distinction is key because in the next paragraph, 

BOEM states that they have used the PM2.5 

concentration to estimate the maximum amount of 

black carbon released because black carbon is a 

specific type of PM2.5. BOEM justifies this 

assumption in the final sentence of the second 

This Supplemental EIS is a disclosure document. 

Although BOEM does not regulate greenhouse gas 

(GHG), BOEM has taken a step toward complete 

disclosure to the public of the contribution of BOEMpermitted OCS oil and gas leasing and development 

activities to national GHG emissions in accordance 

with NEPA. Because BOEM must consider impacts of 

offshore OCS oil- and gas-related activities from all 

sources, BOEM has discussed GHG and black carbon 

in this Supplemental EIS. Black carbon is mentioned 

as a method of managing natural gas removed from 

wells. However, the practice of releasing N2O and 

black carbon via flaring is rare on the Gulf of Mexico

OCS. BOEM states that PM2.5 can be used to 

estimate the amount of black carbon released. Since 

BOEM has regulatory authority over National Ambient 

Air Quality Standards (NAAQS) pollutants, and PM2.5

is a NAAQS pollutant, BOEM has regulatory authority 

over PM2.5. However, because BOEM does not have 

the authority to regulate GHG, BOEM is not proposing

to mitigate GHG or black carbon in this Supplemental 

EIS.

In reference to the discussion of black carbon in 

Chapter 4.1.2, under the “Greenhouse Gases 

Including Downstream Gas” section, BOEM has 

clarified that the practice of releasing N2O and black 

carbon via flaring is rare on the Gulf of Mexico OCS.
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-95

Commenter Comment ID Comment Response

paragraph stating “BOEM has regulatory authority 

over PM2.5”.

Section II.A of the Joint Trades comments on the 

proposed air rule (dated June 20, 2016) discusses 

BOEM’s lack of authority to regulate pollutants that 

do not have a corresponding NAAQS, including 

precursors that have not been explicitly defined as 

such by EPA.

Although ozone modeling considers CO emissions 

from a facility, EPA has not defined it as a regulated 

precursor for ozone. We also note that BOEM 

should not regulate black carbon separately, to the 

extent it seeks to regulate precursors, as it lacks 

authority to regulate precursor elements absent a 

supporting EPA regulatory record, which is the 

agency with the expertise to make such a finding.

It is unclear what BOEM is seeking to accomplish 

with this discussion of GHGs and black carbon in the 

Draft SEIS. The Joint Trades recommends that the 

entire discussion of GHGs be removed from the Draft 

SEIS, especially since BOEM lacks the proper 

regulatory authority to impose mitigations for black 

carbon. Black carbon is not a NAAQS pollutant.

Joint Trades JT-18 Similarly, BOEM’s authority over certain activities in 

the GOM is limited, especially as that authority 

relates to offshore support vessels. Like GHGs, 

information contained in the Draft SEIS regarding 

support vessels should not be used to justify future 

mitigations. Specifically,

• Section 4.1.1, Emissions Inventories, Page 4-21 - 

BOEM states that production sources include survey 

vessels, pipe-laying operations, support vessels and 

helicopters, yet does not mention that BOEM does 

It is appropriate for NEPA analyses to include direct 

and indirect impacts; therefore, support vessel 

emissions were included in this NEPA analysis.
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-96 2018 Gulf of Mexico Supplemental EIS

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not have the authority to regulate air pollution 

emissions from vessels and helicopters. See 

section III.A of the Joint Trades comments on the 

proposed air rule (dated June 20, 2016) inserted 

below:

OCSLA limits BOEM’s authority over offshore 

facilities to “artificial islands[] and [] installations . . . 

permanently or temporarily attached to the seabed, 

which may be erected thereon for the purpose of 

exploring for, developing, or producing resources 

therefrom.”45 MSCs, aircraft, and onshore facilities 

are clearly not “artificial islands . . . permanently or 

temporarily attached to the seabed” that are 

“exploring for, developing, or producing” oil and gas. 

The Supreme Court has made clear that “the 

purpose of [OCSLA] was to define a body of law 

applicable to the seabed, the subsoil, and the fixed 

structures . . .on the Outer Continental Shelf.” The 

Supreme Court has noted that Congress’ approach 

under OCSLA “was deliberately taken in lieu of 

treating the structures as vessels, to which admiralty 

law supplemented by the law of the jurisdiction of the 

vessel's owner would apply.”

Joint Trades JT-19 The Draft SEIS makes several conclusions that 

appear to be overly conservative and do not appear 

to meet the impact definitions described Section 4.1, 

page 4-15. The impact definitions shown on page 

4-15 are as follows:

• Negligible – No measurable impact(s).

• Minor – Most impacts on the affected resource 

could be avoided with proper mitigation; if impacts 

occur, the affected resource would recover 

completely without mitigation once the impacting 

stressor is eliminated.

• Moderate – Impacts on the affected resource are 

unavoidable. The viability of the affected resource is 

The conclusions developed by BOEM’s subject-matter 

experts regarding the potential effects of a proposed 

regionwide lease sale for most resources are 

necessarily qualitative in nature; however, they are 

based on the science-based judgment of the highly 

trained subject-matter experts. Staff approach this 

effort utilizing credible scientific information and apply 

it to the subject resources using accepted 

methodologies.
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-97

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not threatened although some impacts may be 

irreversible, or the affected resource would recover 

completely if proper mitigation is applied or proper 

remedial action is taken once the impacting stressor 

is eliminated.

• Major – Impacts on the affected resource are 

unavoidable. The viability of the affected resource 

may be threatened although some impacts may be 

irreversible, and the affected resource would not fully 

recover even if proper mitigation is applied or 

remedial action is implemented once the impacting 

stressor is eliminated.

Joint Trades JT-20 • Section 4.1.2.1, Flaring and Venting, page 4-31 -

The conclusion paragraph stating that the impacts of 

flaring and venting are minor offers no substantiated 

basis for this conclusion, and in fact, states that any 

such release would likely dissipate before reaching 

coastal areas. The justification presented supports a 

conclusion of “Negligible” not “Minor.”

BOEM selected the conclusion of “minor” because 

flaring and venting include a wide range of scenarios. 

The processes of flaring and venting can be sorted 

into two processes: continuous or intermittent, which 

can include subcategories (i.e., planned, unplanned, 

and safety situations). The location, volume, and 

duration, as well as the sulfur content and resultant 

SOx content for flares, may vary as well. “Minor” was 

selected because not every possible scenario would 

be “negligible.” It is possible for flaring and venting 

events to be below the NAAQS but still be above the 

Significant Impact Levels (SILs) established by 

USEPA for the protection of human health and welfare 

in offshore areas near the flare. “Minor” allows for 

some situations of extended duration closer to shore. 

This impact conclusion definition does not include 

accidental flaring.

BOEM used the initial results of the “Air Quality 

Modeling in the Gulf of Mexico Region” study, which 

was the best available science at this time in order to 

draw impact conclusions on air quality. BOEM is 

currently revising the air quality modeling and taking 

comments from Federal agencies, industry, and the 

general public into consideration in the model run, 

which will be available for review in a future NEPA 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

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document. Please refer to BOEM’s response to 

Comment CEA-3 for information detailing BOEM’s 

update of the air quality modeling run and the use of 

the initial air quality analysis in this Supplemental EIS.

Joint Trades JT-21 • Section 4.1.2.1, Decommissioning, page 4-31 -

BOEM is again drawing a conclusion that the air 

quality impacts from decommissioning activities, 

specifically from vessels which are not under 

BOEM’s jurisdiction for air quality purposes, are 

“Minor” without offering any substantiated basis for 

this conclusion. What is the justification for labeling 

this activity as “Minor” instead of “Negligible” in this 

section, as well as in Table 4-1?

BOEM selected the conclusion of “minor” because 

decommissioning includes a wide range of scenarios. 

Decommissioning projects will vary because different 

projects require different types of equipment due to 

water depth and platform size and weight. 

Decommissioning may require a large amount of 

engines with a broad range of engine sizes, and 

application of engine use varies as the uses occur 

both onshore and offshore. Therefore, the potential 

for air pollution emissions is large as well. While 

potential impacts to air quality from decommissioning 

some projects may be very low, the process of 

removing other facilities has the potential to cause 

adverse impacts to air quality. “Minor “was selected 

because not every possible scenario would be 

“negligible.”

BOEM used the initial results of the “Air Quality 

Modeling in the Gulf of Mexico Region” study, which 

was the best available science at this time in order to 

draw impact conclusions on air quality. BOEM is 

currently revising the air quality modeling and taking 

comments from Federal agencies, industry, and the 

general public into consideration in the model run, 

which will be available for review in a future NEPA 

document. Please refer to BOEM’s response to

Comment CEA-3 for information detailing BOEM’s 

update of the air quality modeling run and the use of 

the initial air quality analysis in this Supplemental EIS.

Joint Trades JT-22 • Section 4.1.2.3.1, Impacts Assessment, PM10, 

page 4-42 – The Draft SEIS states, “The impacts to 

air quality from PM10 are minor because, while there 

are concentrations increases in water farther 

offshore, no overall standards were exceeded.” The 

BOEM selected the conclusion of “minor” because, 

while no overall standards were exceeded, it does not 

mean there will be no impacts to air quality. It is 

possible for the concentrations to be below the 

NAAQS but still be above the SILs established by 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-99

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conclusion that no overall standards were exceeded 

should justify an impact classification of “Negligible.”

USEPA for the protection of human health and welfare 

in offshore areas. A “minor” conclusion allows for 

such instances.

BOEM used the initial results of the “Air Quality 

Modeling in the Gulf of Mexico Region” study, which 

was the best available science at this time in order to 

draw impact conclusions on air quality. BOEM is 

currently revising the air quality modeling and taking 

comments from Federal agencies, industry, and the 

general public into consideration in the model run, 

which will be available for review in a future NEPA 

document. Please refer to BOEM’s response to 

Comment CEA-3 for information detailing BOEM’s 

update of the air quality modeling run and the use of 

the initial air quality analysis in this Supplemental EIS.

Joint Trades JT-23 Section 4.1.2.3.1, Impacts Assessment, Nitrogen 

Dioxide (NO2), page 4-42 – The Draft SEIS states, 

“The impacts to air quality from 1-hour NO2 and 

annual NO2 are minor because overall, 

concentrations decrease between the base and 

future year scenarios at most locations.” A decrease 

in projected emissions appears to indicate that air 

quality may be improving in projected future years. 

Therefore, the impact conclusion must be 

“Negligible.”

BOEM selected the conclusion of “minor” because, 

while overall concentrations decreased between the 

base- and future-year scenarios, it does not mean 

there will be no impacts to air quality. It is possible for 

the concentrations to be below the NAAQS but still be 

above the SILs established by USEPA for the 

protection of human health and welfare. A “minor” 

conclusion allows for such instances.

BOEM used the initial results of the “Air Quality 

Modeling in the Gulf of Mexico Region” study, which 

was the best available science at this time in order to 

draw impact conclusions on air quality. BOEM is 

currently revising the air quality modeling and taking 

comments from Federal agencies, industry, and the 

general public into consideration in the model run, 

which will be available for review in a future NEPA 

document. Please refer to BOEM’s response to

Comment CEA-3 for information detailing BOEM’s 

update of the air quality modeling run and the use of 

the initial air quality analysis in this Supplemental EIS.
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

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Joint Trades JT-24 • Section 4.1.2.3.1, Impacts Assessment, Sulfur 

Dioxide (SO2), page 4-43 – The Draft SEIS states, 

“The impacts to air quality from 1-hour SO2 and 

3-hour SO2 are minor because overall, 

concentrations decrease between the base and 

future year scenarios at most locations as sources 

retire or apply control equipment.” A decrease in 

projected onshore concentrations appears to indicate 

that air quality may be improving in projected future 

years. Therefore, the impact conclusion must be 

“Negligible.”

BOEM selected the conclusion of “minor” because, 

while overall concentrations decreased between the 

base- and future-year scenarios, it does not mean 

there will be no impacts to air quality. It is possible for 

the concentrations to be below the NAAQS but still be 

above the SILs established by USEPA for the 

protection of human health and welfare. A “minor” 

conclusion allows for such instances.

BOEM used the initial results of the “Air Quality 

Modeling in the Gulf of Mexico Region” study, which 

was the best available science at this time in order to 

draw impact conclusions on air quality. BOEM is 

currently revising the air quality modeling and taking 

comments from Federal agencies, industry, and the 

general public into consideration in the model run, 

which will be available for review in a future NEPA 

document. Please refer to BOEM’s response to

Comment CEA-3 for information detailing BOEM’s 

update of the air quality modeling run and the use of 

the initial air quality analysis in this Supplemental EIS.

Joint Trades JT-25 • Section 4.1.2.3.1, Impacts Assessment, Carbon 

Monoxide (CO), page 4-43 – The Draft SEIS states, 

“The impacts to air quality from 1-hour CO and 

8-hour CO are minor because overall, concentrations 

decrease between the base and future year 

scenarios at all locations.” A decrease in projected 

onshore concentrations appears to indicate that air 

quality may be improving in projected future years. 

Therefore, the impact conclusion must be 

“Negligible.”

BOEM selected the conclusion of “minor” because, 

while no overall concentrations decreased between 

the base- and future-year scenarios, it does not mean 

there will be no impacts to air quality. It is possible for 

the concentrations to be below the NAAQS but still be 

above the SILs established by USEPA for the 

protection of human health and welfare. A “minor” 

conclusion allows for such instances.

BOEM used the initial results of the “Air Quality 

Modeling in the Gulf of Mexico Region” study, which 

was the best available science at this time in order to 

draw impact conclusions on air quality. BOEM is 

currently revising the air quality modeling and taking 

comments from Federal agencies, industry, and the 

general public into consideration in the model run, 

which will be available for review in a future NEPA 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-101

Commenter Comment ID Comment Response

document. Please refer to BOEM’s response to 

Comment CEA-3 for information detailing BOEM’s 

update of the air quality modeling run and the use of 

the initial air quality analysis in this Supplemental EIS.

Joint Trades JT-26 • Characterization in Table 4-1 does not match text 

section discussions for Accidental Events 

(Emergency Flaring and Venting and Oil Spills) - 

Emergency Flaring and Venting, and Oil Spills are 

identified in Table 4-1 as having a “Minor” impact on 

air quality, however, the second paragraph on page 

4-32 in the “Emergency Flaring and Venting” section, 

and the first paragraph on page 4-33 in the “Oil 

Spills” section states “...potential impacts as a result 

of the much smaller reasonably foreseeable 

accidental gas release (Emergency Flaring and 

Venting) spills (Oil Spills) analyzed in this 

Supplemental EIS would be localized and short term, 

and would have no impact on coastal areas....”. The 

concluding sentence of these paragraphs draws the 

unsubstantiated conclusion that “the accidental 

event’s impact on air quality over the OCS and 

adjacent onshore areas on oil spills is therefore 

expected to be minor.” If there is no impact to the 

coastal areas, Table 4-1 should reflect a “negligible” 

impact for Emergency Flaring and Venting and Oil 

Spills.

The OCS is not subject to the NAAQS. As explained 

in the Joint Trades written comments on the 

Proposed Air Quality Rules (June 20, 2016), “First, 

as discussed, under section 5(a)(8) the Secretary’s 

authority is limited to promulgating regulations for 

“compliance with the [NAAQS] pursuant to the [CAA] 

to the extent that activities authorized under [OCSLA] 

significantly affect the air quality of any State.” 

Under the relevant state implementation plans, the 

border of the air quality control regions appears to 

extend only to the shoreline and not to the respective 

BOEM selected the conclusion of “minor” because the 

location, volume, and duration (as well as the sulfur 

content and resultant SOx content for flares) may vary 

for flaring and venting and oil-spill events. “Minor” 

was selected because not every possible scenario 

would be “negligible.” It is possible for flaring and 

venting and oil-spill events to be below the NAAQS 

but still be above the SILs established by USEPA for 

the protection of human health and welfare in offshore 

areas near the flare. “Minor” allows for such 

instances.

BOEM used the initial results of the “Air Quality 

Modeling in the Gulf of Mexico Region” study, which 

was the best available science at this time in order to 

draw impact conclusions on air quality. BOEM is 

currently revising the air quality modeling and taking 

comments from Federal agencies, industry, and the 

general public into consideration in the model run, 

which will be available for review in a future NEPA 

document. Please refer to BOEM’s response to 

Comment CEA-3 for information detailing BOEM’s 

update of the air quality modeling run and the use of 

the initial air quality analysis in this Supplemental EIS. 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

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states’ territorial waters. As such, NAAQS do not 

apply in the territorial waters.”

Since the NAAQS do not apply to OCS, and BOEM 

has concluded that emergency flaring and venting 

and oil spills will have no impact on coastal areas air 

quality, Table 4-1 must be changed to document a 

“Negligible” impact from Emergency Flaring and 

Venting and Oil Spills, as opposed to “Minor”.

Joint Trades JT-27 Many of the issues discussed above such as 

overprediction of future platforms and overlyconservative assumptions regarding onshore wind 

flows do not have a singular effect on the 

conclusions of the Draft SEIS. Overly conservative 

assumptions utilized in multiple ways in the GOM Air 

Modeling study and the Draft SEIS have a compound 

effect upon the final results. Inappropriate and 

inaccurate assumptions and model inputs, taken 

cumulatively, greatly exaggerate the potential 

impacts and conclusions presented in the Draft 

SEIS.

Therefore, it is critical that assumptions and model 

inputs are realistic and appropriate. Because of this 

compounding effect, the Joint Trades’ 

recommendation of establishing a collaborative, 

multi-stakeholder work group to provide input to the 

GOM Air Quality Modeling study becomes 

imperative. By establishing a more collaborative, 

transparent process, where input from stakeholders 

is considered and utilized, the impact of 

overpredictions can be minimized and, ultimately, the 

model results are improved.

BOEM is now in the process of updating the air quality 

modeling based on public comments and will publish 

the results when the analysis is complete. Please 

refer to BOEM’s response to Comment CEA-3 for 

information detailing BOEM’s update of the air quality 

modeling run and the use of the initial air quality 

analysis in this Supplemental EIS. 

BOEM has collaborated with USEPA, as well as 

industry, on the review and discussions of the air 

quality model. In addition, BOEM has considered 

addressing and incorporating industry’s comments 

into the new air quality model and analysis.

Joint Trades JT-30 The Joint Trades appreciate the opportunity to 

provide these written comments on the air quality 

data that has been made available in the Draft SEIS. 

However, as discussed in this letter, overall, we 

remain extremely concerned that BOEM is utilizing 

BOEM is now in the process of updating the air quality 

model based on public comments and will publish the 

results when the analysis is complete. Please refer to 

BOEM’s response to Comment CEA-3 for information 

detailing BOEM’s update of the air quality modeling 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-103

Commenter Comment ID Comment Response

an inappropriate process for public review of the 

GOM Air Quality Modeling study. In addition, we 

have even greater concern that BOEM is using a yetunfinished study to justify conclusions regarding 

potential environmental impacts and to present those 

conclusions to the public as “best available science.” 

This is clearly not a prudent, sound and common 

sense approach to policy making.

run and the use of the initial air quality analysis in this 

Supplemental EIS. 

BOEM has collaborated with USEPA, as well as 

industry, on the review and discussions of the air 

quality model. In addition, BOEM has considered 

addressing and incorporating industry’s comments 

into the new air quality model and analysis. Once the 

air quality model is complete, the public will have an 

opportunity to comment on the model and analysis.

Joint Trades JT-31 In addition, the Joint Trades were notified on May 15, 

2017 that BOEM extended the comment period until 

June 14, 2017 to allow for additional review of air 

quality information in the Draft SEIS. At the time 

notification of the comment period extension was 

received, the comments contained in this letter had 

been finalized. However, the Joint Trades will utilize 

the additional time granted to continue our review of 

the Draft SEIS air quality information, and we reserve 

the right to submit additional comments before the 

extended deadline of June 14, 2017.

Thank you for your comments. We accepted air 

quality comments until June 14, 2017.

United States 

Environmental 

Protection 

Agency

USEPA-1 Since the air quality analysis and supporting 

appendices for the Gulf of Mexico Outer Continental 

Shelf (OCS) Lease Sale 2018 are identical to the 

Gulf of Mexico OCS Oil and Gas 2017-2022 Final 

Multisale EIS, the EPA refers BOEM to our previous 

air quality comments in our letter dated April 10, 

2017. The EPA appreciates BOEM’s continued 

interagency coordination with respect to the air 

quality study that supports these lease sales.

Thank you for your comment. BOEM will continue to 

coordinate with USEPA on the new air quality 

modeling. Responses to individual comments from 

the April 10, 2017, letter follow in the responses to 

Comments USEPA-4 through USEPA-47.

United States 

Environmental 

Protection 

Agency

USEPA-4 General Comments

Model Receptors 

EPA fully supports BOEM's consideration of Outer

Continental Shelf (OCS) impacts at the State

seaward boundary in BOEM's air quality modelling

study and impacts analysis. Such analysis is

necessary to ensure that the National Ambient Air

Thank you for your comment. Your comment is noted.
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

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Quality Standards (NAAQS) are protected and that

States can meet their State Implementation Plan

and Coastal Zone Management Act (CZMA)

responsibilities, as well as, to ensure that the air

quality within this nearshore area is not adversely

impacted by OCS activity.

United States

Environmental 

Protection 

Agency

USEPA-5 Impact Level Determinations

According to Table 1 in the Executive Summary and 

Chapter 4 Table 4.1, overall impacts on air quality 

have been concluded to be minor for Alternatives 

A-D. This conclusion is not fully supported by other 

statements of the Executive Summary, as well as the 

detailed analyses in Section 4.1 (Air Quality) of the 

EIS. For instance, page XIX of the Executive 

Summary refers to potential impacts to Breton 

Wilderness Area as moderate. Additionally, page XX 

of the Executive Summary refers to impacts from the 

cumulative lease sales as moderate to both Breton 

Wilderness Area and the Gulf Islands National 

Seashore and "...would most likely have a moderate 

effect on coastal nonattainment areas for certain 

pollutants." Page XX refers to the cumulative 

impacts having a minor effect "...because most 

impacts on the affected resources could be avoided 

with proper mitigation." However, there is no 

detailed discussion of what constitutes proper 

mitigation for the specific impacts nor analysis 

(modelled or otherwise) of how it will alleviate or 

counteract air quality impacts. EPA suggests that 

quantitative analysis of assumed emissions 

reductions using emission factors associated with 

control technologies or mitigation is a valuable tool 

for determining if specific mitigation measures would 

reduce impacts to minor levels. In addition, current 

offshore operations employ very little targeted 

mitigation, and if they did, these reductions would 

likely be accounted for in the emissions reported by 

operators and used as the basis for the inventory 

As discussed in the Executive Summary, the

incremental contribution of a proposed lease sale to 

the cumulative impacts would most likely have a 

minor effect on coastal nonattainment areas because 

most impacts on the affected resource could be 

avoided with proper mitigation. Portions of the Gulf 

Coast onshore areas have ozone levels that exceed 

the Federal air quality standard, but the incremental 

contribution from a proposed lease sale would be very 

small and would not on their own cause an 

exceedance. Any minor to moderate impact 

conclusions were for cumulative impacts for the OCS 

Oil and Gas Program, not for an individual lease sale.

BOEM is now in the process of updating the air quality 

model based on public comments. The revised air 

quality model run will not be completed before the 

publication of this Final Supplemental EIS; therefore, 

the results of the initial air quality model are still 

included in this Supplemental EIS as a reference for 

NEPA analysis. The air quality modeling results 

currently available allow consideration of anticipated 

air quality impacts without those impacts being 

underestimated. Should the results of the revised 

model change the impact conclusions, the impact 

table will be revised.

In reference to the request for detailed air quality 

mitigation information, refer to Appendix B of the 

2017-2022 GOM Multisale EIS, “Commonly Applied 

Mitigating Measures,” for full descriptions of the air 

quality mitigations.
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-105

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that resulted in the adverse impacts of the current 

study.

Additional inconsistencies were found in Section 4.1 

regarding the conclusion of minor versus moderate 

impacts of this EIS. For example, according to page 

4-39 of this Section, "[t]he impacts to air quality from 

ozone (03) for all proposed and existing oil and gas 

emissions from Gulf of Mexico OCS sources and 

their support vessels/aircraft (Source Group C) are 

moderate because future year design values were 

above the current year design value (which was 

already above the [national ambient air quality 

standards] NAAQS)." The EIS identifies Galveston, 

Texas, as a current nonattainment area, which is the 

location of the maximum impacts from Source 

Group C (new and existing) emissions. The 

paragraph further concludes that the impacts from 

Source Group B (new emissions) are minor, since 

design values in the future are lower than the current 

year design values. However, since the current year 

design values are already above the NAAQSs and 

the area is designated nonattainment (Galveston, 

TX), it cannot be concluded that Source Group B will 

not continue to contribute to the existing violations of 

the NAAQS and, therefore, have just minor impacts, 

as "minor" is defined in the EIS.

Based on our review of the analysis contained in the 

FEIS, and supporting documentation, EPA concurs 

with the text of the analysis that the air quality 

impacts range from minor to moderate. EPA

recommends that any such impact summary tables 

in the record of decision (ROD) and future EIS 

documents reflect BOEM's conclusions of minor to 

moderate impacts, unless otherwise supported by 

revised impact analyses.
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

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United States 

Environmental 

Protection 

Agency

USEPA-6 c) Monitoring and Mitigation

EPA continues to recommend that BOEM develop

measures to monitor and mitigate NAAQS

pollutants, such as NOx, and PM2.5, as well as,

regulated toxic and greenhouse gas pollutants, and

to include recommendations for these measures in

the ROD. EPA suggests that reasonable mitigation

measures that should be considered include the

use of low sulfur fuels, including liquefied natural

gas, inherently lower polluting and high efficiency

engine designs, use of required tier certified nonroad and marine engines (rather than engines

certified for US export), flaring (rather than cold

venting), and electrification of cranes and support

equipment. EPA also encourages BOEM to include 

provisions for periodic or continuous emissions

monitoring for large emission units to ensure that

emissions are maintained below the exemption

thresholds, and hence, ensure compliance with the

NAAQS and CZMA. EPA supports BOEM's

inclusion of these recommended measures in 

BOEMs table of mitigation.

BOEM will consider the use of reasonable mitigation 

measures suggested by USEPA in future NEPA 

documents. During the postlease stage, stack testing 

is required when operator emissions factors are lower 

than default emission factors (e.g., lower than USEPA

tier standards). Additionally, when actual or historical 

fuel usage is used, a fuel usage mitigation that

requires submission of monthly fuel records is applied 

to operators. Likewise, BSEE completed a study, 

“Analysis of Potential Opportunities to Reduce Venting 

and Flaring on the OCS”, intended to support the 

advancement of knowledge about venting and flaring 

practices in offshore operations and to foster 

improvements in the oversight and regulation of 

venting and flaring activities.

United States 

Environmental 

Protection 

Agency

USEPA-7 Section 3.1 Impact Producing Factors 

Section 3.1.8, Air Emissions, page 3-92:

EPA recommends that the line that begins, "the 

Clean Air Act Amendments" require the USEPA to 

set the NAAQS ..., should be revised to state, "the 

Clean Air Act," as EPA was required to establish the 

NAAQS prior to the 1980 Amendments.

Chapters 3.1 and 3.3 of the 2017-2022 GOM Multisale 

EIS describe in detail the routine and accidental 

impact-producing factors and activity scenarios 

associated with Alternatives A-D that could potentially 

affect the biological, physical, and socioeconomic 

resources of the Gulf of Mexico. In this Supplemental 

EIS, a summary of the impact-producing factors and 

scenario incorporated from the 2017-2022 GOM 

Multisale EIS are included in Chapter 3.1.2.

BOEM will make this requested language change in 

the next EIS that uses this language. All air quality 

comments from USEPA were submitted for the Final 

2017-2022 GOM Multisale EIS, but they were 

re-referenced in the comment letter from USEPA for

the Draft 2018 GOM Supplemental EIS. Because the 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-107

Commenter Comment ID Comment Response

text referenced in this comment was not reproduced in 

this Supplemental EIS, the change could not be made 

to this Supplemental EIS. However, the change will 

be made in the next NEPA document that uses this 

language.

United States 

Environmental 

Protection 

Agency

USEPA-8 EPA recommends that Section 3.1.8.l and 3.1.8.3

be revised to include VOCs as combustion gases.

In addition to being non-combustion sources of 

emission, fuel carbon not converted to C02, results in 

CH4, CO, and/or VOC emissions due to incomplete 

combustion.

Refer to the response to Comment USEPA-7 above.

United States 

Environmental 

Protection 

Agency

USEPA-9 Section 4.2 Air Quality 

Appropriateness of Reference Measures

According to Page 4-13 of this section, the air quality 

impacts of the oil and gas related activities planned 

as part of this multisale lease activity are being 

compared to several reference measures, such as 

the NAAQS, significant impact levels (SILs), and 

other air quality related values (AQRVs), including 

visibility and acid deposition. As outlined in 

Table 4-2, the NAAQS take many different forms with 

varying averaging times for several of the pollutants. 

Page 4-37 of this section provides an overview of the 

modeling results compared to these reference 

measures, beginning with the NAAQS. While there 

are several NAAQS that may be appropriate for 

comparison (e.g., long-term, annual standards), EPA 

believes the use of actual emissions (instead of 

allowable maximum hourly emissions), the nature of 

photochemical grid-based modeling and the 

uncertainties associated with the future year (2033 

and 2036) emissions inventories, as well as the 

unknown location and number of future platforms 

and vessel activity, makes comparison of the future 

year emission impacts to short-term (1-hour and 

3-hour) NAAQSs far too uncertain and potentially 

Please refer to BOEM’s response to Comment CEA-3 

for information detailing BOEM’s update of the air 

quality modeling run and the use of the initial air

quality analysis in this Supplemental EIS. 

The results of the initial air quality model are the best 

available information we have, and they are included 

in this Supplemental EIS as a reference for NEPA 

analysis. The air quality modeling results currently 

available allow consideration of anticipated air quality 

impacts without those impacts being underestimated. 

Including comparisons to the short-term (e.g., 1-hour) 

NAAQS were included in the analysis for disclosure. 

Caveats were included in the analysis regarding 

uncertainties as suggested by USEPA. While 

cumulative impacts relative to short-term (e.g., 1-hour) 

NAAQS are disclosed in this Supplemental EIS, 

readers should be aware that these impact estimates 

are subject to greater uncertainties than impacts 

relative to longer term (e.g., annual average) NAAQS 

since they will typically occur very close to a specific 

source and are therefore more sensitive to the exact 

characteristics and locations of individual sources; this 

information is not generally available at this point in 

the planning process. Also worth noting is that this 

analysis did include temporal profiles that are source 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

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misleading to the public.

Additionally, in order to perform a PSD increment 

analysis, one would have to ascertain which 

emission units/facilities are increment consuming 

and expanding, since all existing emission 

units/facilities do not consume PSD increments and 

decreases in emissions from PSD affecting sources 

expand PSD increments. Further, the pollutant’s 

minor source baseline date, which determines PSD 

increment affecting emission sources, is location 

dependent. This kind of location specific information 

was not included as part of the increment analysis 

described on Pages 4-43 to 4-45 of this section. 

Because of this, photochemical grid-based modeling 

is not conducive to the assessment of PSD 

increments. The EIS did acknowledge that the 

analysis done “...did not constitute a regulatory PSD 

increment analysis.” However, since the analysis 

that was performed shows several exceedances of 

the PSD increment, EPA believes it is misleading to 

present the results in the EIS document. The 

assessment of PSD increments are more 

appropriately part of an individual receptor-based 

impact modeling assessment using air quality 

dispersion modeling.

EPA recommends that short-term NAAQSs and PSD 

increments cannot be properly assessed with the 

available emission inventory information and air 

quality modeling technique used for the EIS. 

Therefore, it is recommended that these ambient air 

quality standards be removed from future EIS 

documents for multisale lease activity. EPA believes 

a better comparison to determine the air quality 

impacts of the future lease sale activities would be to 

compare only the future platform and support vessel 

emissions (i.e., Group B emissions) impacts to the 

category specific based on previous Gulfwide 

emissions inventories; therefore, some emissions 

adjustments were made with respect to time, and not 

all of the emissions are based the same hourly 

emissions.

No regulatory Prevention of Significant Deterioration 

(PSD) analysis was included in the analysis; instead, 

impacts from new sources associated with the 

proposed action (Source Group B) at Class I and 

sensitive Class II areas were compared against the 

PSD increments for informational purposes only. The 

PSD increments are merely adopted as a set of 

convenient benchmarks. This has become common 

practice in air quality impact disclosures for upstream 

oil and gas NEPA documents. BOEM has chosen to 

disclose impacts relative to the PSD increments in 

Class I and sensitive Class II areas in light of the fact 

that this has become common practice in NEPA 

documents for upstream oil and gas projects; full 

disclosure of all impacts with appropriate caveats 

noted is more appropriate. In keeping with this 

approach, impacts at Class I/II areas from Source 

Groups A, B, and C are presented in this 

Supplemental EIS, and it is noted that Source 

Group C includes sources that are not exclusively 

associated with the proposed action.

The SILs are designed to represent de minimus levels 

below which it is presumed that impacts of an 

individual source will not “cause or contribute to the 

violation of a NAAQS” or the exceedance of a PSD 

increment, thus obviating the need to perform detailed 

modeling of cumulative impacts (for NAAQS) or a full 

regulatory PSD analysis. The source contribution 

analysis presented in Appendix H of the 2017-2022 

GOM Multisale EIS (Appendix D of this Supplemental 

EIS) gives estimates of the combined impacts of all 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-109

Commenter Comment ID Comment Response

SILs. This would allow a more applicable analysis of 

the effects of the new OCS activities being proposed 

as part of the EIS. In addition, impacts from the 

emissions associated with the lease sales that are 

less than the SIL would not be considered significant 

enough to cause or contribute to ambient standard 

violations.

new sources associated with the proposed action as a 

group (Source Group B) and does not focus on any 

individual new source. Each of the individual new 

sources within Group B will be subject to further 

regulatory review before being approved. Thus, 

comparing Group B impacts to the SILs is 

inappropriate. Furthermore, there is no value in 

examining impacts relative to the SILs since the 

regional-scale photochemical modeling already 

provides estimates of cumulative impacts and 

compares them to the NAAQS.

United States 

Environmental 

Protection 

Agency

USEPA-10 Section 4.1.1: Description of the Affected 

Environment 

The EIS (Page 4-16) included the following Class I 

areas in the analysis: Breton Wilderness Area, 

Bradwell Bay Wilderness Area, Chassahowitzka 

National Wilderness Area, Everglades National Park, 

and St. Marks Wilderness Area. It is unclear why 

only these particular Class I areas were included in 

the analysis. EPA recommends that the EIS include 

a description of the criteria used to determine which 

Class I areas were of concern (e.g., distance from 

shoreline, etc.).

Under BOEM Contract Number M14PC00007, “Air 

Quality Modeling in the Gulf of Mexico Region” study, 

photochemical air quality modeling was conducted to 

assess impacts to nearby states of OCS oil and gas 

exploration, development, and production as required 

under the OCSLA. Since the Gulf of Mexico OCS 

Region manages the WPA, CPA, and EPA on the 

OCS, the area of possible influence includes the 

States of Texas, Louisiana, Mississippi, Alabama, and 

Florida. In addition, the NEPA analysis included the 

Class I areas located in the coastal waters of these 

states adjacent to the OCS because they fall within 

BOEM’s Gulf of Mexico OCS Region’s area of 

responsibility.

United States 

Environmental 

Protection 

Agency

USEPA-11 Section 4.1.1: Gulf of Mexico OCS Region 

Attainment Status

This section describes the NAAQS and attainment 

status of the criteria pollutants. However, this 

section no longer discusses the NAAQS or 

attainment status for particulate matter (i.e. the 

paragraph that was in the draft was removed). Since 

particulate matter is a pollutant of concern for health 

effects, Class I area visibility, and regional haze, and 

is directly emitted by OCS facilities, EPA 

recommends including a description of the 

particulate matter standards in the EIS, as was 

included in the draft.

The previously removed language has been 

reinserted in this Supplemental EIS.
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-110 2018 Gulf of Mexico Supplemental EIS

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United States 

Environmental 

Protection 

Agency

USEPA-12 Section 4.1.1: Emissions Inventories

It is our understanding that the emission inventory 

used for the base year (2012) analysis is actually a 

compilation of several different emission inventories 

as described in various areas of the EIS, as well as 

the appendices. These inventories include: 1) EPA’s 

2011 National Emissions Inventory (NEI), 2) BOEM’s 

2011 Gulf-wide Emissions Inventory (GWEI) study, 

3) EPA’s Clean Air Markets Division (CAMD) data 

from 2012 and 4) onshore mobile source emissions 

from 2012 used in EPA’s MOVES model. However, 

the discussion in Section 4.1.1 regarding emissions 

inventories only describes the GWEI from BOEM. 

Section 4.1.2.3 (Page 4-34) briefly mentions the EPA 

NEI as well as the use of 2012 meteorological 

datasets. EPA strongly recommends the emissions 

inventory discussion in Section 4.1 include at least a 

brief description of all the emission inventories used 

in the base year analysis, as well as references to 

additional information in the appropriate appendices.

This Supplemental EIS has been updated to include 

the different emission inventories used in the base 

case analysis, as well as reference to additional 

information in the appropriate appendices.

United States 

Environmental 

Protection 

Agency

USEPA-13 This section, page 4-20, indicates that emission 

estimates were provided for directly emitted 

pollutants, and indicates that only four of the 

common air pollutants, for which there are NAAQS 

(i.e. CO, Pb, NO2 and SO2), are emitted directly. 

EPA recommends that this statement be revised to 

include particulate matter (PM2.5 and PM10) as 

common air pollutants that are emitted directly from 

OCS facilities and for which there are NAAQS.

The chapter has been updated to include PM2.5 and 

PM10. 

United States 

Environmental 

Protection 

Agency

USEPA-14 Section 4.1.2.1: Routine Activities-Drilling and 

Production with Associated Vessel Support

This section, pages 4-28 and 4-29, discusses the 

contributions of drilling and vessel support, and 

describes vessel support as emitting NOx, CO and 

CO2. EPA recommends including PM2.5 and PM10 in 

the list on page 4-29. In addition, EPA recommends 

that the EIS clarify, that for the purpose of the 

emissions inventory, BOEM considers drillships and 

This chapter has been updated to include (1) PM2.5

and PM10, (2) drillships and well stimulation vessels 

considered as non-platform sources, and (3) 

clarification of the scenario and how the results align 

with the Source Categories/Source Groups.
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-111

Commenter Comment ID Comment Response

well stimulation vessels to be non-platform sources 

of emissions. This helps to provide perspective on 

the emission rates for the non-platform/support 

vessel contribution. Finally, the concluding 

statement, “because the projected activities in this 

scenario for a proposed lease sale are less than the 

current 2011 GWEI activities, the impacts would be 

minor,” seems out of place and is not well supported 

by the prior statements. A “scenario” as not been 

described prior to this statement, nor is it clear how 

this result aligns with SC3-SC6 categories discussed 

in the context of the modelling results.

United States 

Environmental 

Protection 

Agency

USEPA-15 Section 4.1.2.3.1: Impacts Assessment

In this section, the EIS describes many of the future 

year pollutant impacts as having decreased 

concentrations from those estimated for the base 

year. The EIS makes several statements that the 

future year design values and/or concentrations are 

lower than current year values. For example, Page 

4-39 describes the future year design values based 

on Group B emissions for Ozone as lower than 

current year values. A similar statement is made on 

Page 4-41 that PM2.5 design values decrease in the 

future without reference to which Source Group was 

used to make this assessment. Additionally, on page 

4-41, the conclusion is made that impacts to the 

1-hour nitrogen dioxide (NO2) and annual NO2

standards are minor because overall concentrations 

decrease between base and future year scenarios at 

most locations. No reference is made to whether this 

analysis is based on Source Group B or C 

emissions. EPA recommends that the basis should 

be provided as part of the EIS. In addition, EPA 

recommends that the reason(s) for the decreases in 

future year impacts and/or design values, 

considering the addition of new OCS activities 

associated with these lease sales and possible 

increased land based development, be described in 

Please refer to BOEM’s response to Comment CEA-3 

for information detailing BOEM’s update of the air 

quality modeling run and the use of the initial air 

quality analysis in this Supplemental EIS. 

In future NEPA documents, BOEM will consider 

adding a detailed description of the reason impacts 

decreased in future years, including supporting 

documentation and analyses, as well as quantitative 

summary tables comparing the modeled 

concentrations to NAAQS or other reference 

measures.

This comment suggests that there is some 

misinterpretation of BOEM’s air quality analysis. 

BOEM acknowledges that this section of Chapter 4

did not include a full explanation of the air quality 

modeling results because detailed explanation of the

results are included in Appendices B, C, and D, and 

are incorporated by reference into the analysis in this 

Supplemental EIS.
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-112 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

detail in the EIS documents and that supporting 

documentation or analyses should be included, as 

needed, in order for the reader to understand the 

conclusions made by BOEM with regard to the 

impact assessments. In general, this particular 

section is difficult to understand and to draw 

reasonable conclusions from. EPA recommends that 

this section contained quantitative summary tables 

comparing the modeled concentrations to NAAQS or 

other reference measures.

United States 

Environmental 

Protection 

Agency

USEPA-16 Section 4.1.2.3.1: Comparison at the Class I and 

Sensitive Class II Areas

The notes to this section in italics (page 4-44) 

indicate: “Actions to be authorized by BOEM under 

this Multisale EIS do not typically constitute major 

stationary sources and do not typically trigger PSD 

permits or review... This information is presented to 

aid State agencies in tracking potential minor source 

increment consumption.” While it is true that sources 

under this BOEM action are generally not subject to 

PSD permitting, EPA believes these statements 

could be misinterpreted to mean that the sources 

covered by this action have emissions that are 

generally below EPA’s PSD major source thresholds. 

The vast majority of the sources covered by this EIS 

are located in the area of the Gulf under BOEM 

jurisdiction and are not subject to PSD requirements, 

despite having emission above the PSD “trigger” 

thresholds. All of the sources under EPA jurisdiction 

have had emissions above the PSD thresholds and 

have received PSD permits.

This chapter has been updated to reflect that these 

sources fall under BOEM’s jurisdiction. Sources that 

fall under BOEM’s air quality jurisdiction do not require 

PSD permits or review. The information provided in 

that chapter is presented here as an evaluation of a 

“threshold of concern” for potentially significant 

adverse impacts, but they do not represent a 

regulatory PSD increment consumption analysis.

United States 

Environmental 

Protection 

Agency

USEPA-17 Section 4.1.2.3.1: Non-OCS Oil and Gas Related 

Impacts

This section includes a discussion of intercontinental 

dust transport from Central America and North Africa 

on the Gulf of Mexico air quality and Texas, in 

particular. While EPA concurs that such transport 

may contribute to cumulative visibility impairment, 

The suggested revision has been included in this 

Supplemental EIS.
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-113

Commenter Comment ID Comment Response

EPA is concerned that the referenced material does 

not directly support the EIS conclusion that “an 

increase in visibility impairment in Texas is likely due 

to transport of dust rather than OCS oil and gas 

emissions sources,” given that multiple factors, 

including increased port emissions, increased 

wildfires, etc. contribute to visibility impairment. EPA 

recommends that this conclusion be revised to 

indicate the intercontinental transport likely 

contributes to visibility impairment.

United States 

Environmental 

Protection 

Agency

USEPA-18 Section 4.1.2.4: Incomplete or Unavailable 

Information

In this section, the EIS acknowledges that the Air 

Quality Modeling in the Gulf of Mexico Region study 

is not complete and the analyses relied upon 

preliminary data. However, the section does not 

discuss how the final study results will be used in 

future lease sale activities. Since, the current Final 

Multisale EIS will be used for all Gulf of Mexico lease 

sales in 2017-2022, EPA recommends that the ROD 

address how any final study results will be used in 

future lease sale activities (i.e. through Supplemental 

EIS documents, etc.)

Please refer to BOEM’s response to Comment CEA-3 

for information detailing BOEM’s update of the air 

quality modeling run and the use of the initial air 

quality analysis in this Supplemental EIS. 

BOEM acknowledged USEPA’s comment by including 

language in the Record of Decision (ROD) for Lease 

Sale 249 discussing how any final study results will be 

used in future lease sale activities. The Lease Sale 

249 ROD included language that BOEM does conduct

further air quality review during the postlease plan 

process, and BOEM will consider requiring controls 

should results of the updated modeling suggest 

controls are necessary to protect the NAAQS of any 

state. The language in the Lease Sale 249 ROD 

follows: “In reviewing the initial results [of the air 

quality model run] and after considering several 

modeling assumptions used in the study, BOEM has 

decided to conduct further refined modeling in 

coordination with the U.S. Environmental Protection 

Agency, the U.S. Fish and Wildlife Service, and the 

U.S. National Park Service. It is anticipated that any 

new results would be provided in a supplemental EIS, 

and furthermore, the results will be available and 

considered before any plan is submitted on a block 

leased as a result of Lease Sale 249. Therefore, 

while additional air quality data would be useful in 

consideration of this lease sale, it is not necessary for 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-114 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

my decision on this lease sale. Any concerns raised 

by the modeling study will be further refined by the 

time plans are submitted and/or additional plan 

specific modeling may be required consistent with 

BOEM regulations when the plan is submitted for 

approval. During its review of any submitted plan, 

BOEM conducts an air quality review to determine if 

additional controls would be necessary.”

United States 

Environmental 

Protection 

Agency

USEPA-19 Inconsistencies

The definition of Source Categories (SCs) as used in 

Section 4.1 and in Appendix H should are not 

consistent. Section 4.1 Source Categories only go 

from SC3 to SC6 (Table 4-4) and their descriptions 

are not exactly the same as provided in Appendix H. 

The appendix has added SC1-SC2 and SC7-SC10 

(see Table H-7). EPA recommends that the EIS and 

future documents based on the Appendices, explain

the differences and/or revise these definitions to be 

more consistent throughout the NEPA document.

The suggested clarification has been included in this 

Supplemental EIS.

United States 

Environmental 

Protection 

Agency

USEPA-20 Similar to our comment regarding the source 

category definitions above, the source groups in 

Section 4.1 are only provided and defined for Source 

Groups A-D and appear to be the same definitions 

as those provided in Appendix H. However, the 

appendix also includes Source Groups D-F with their 

definitions (see Table H-15). EPA recommends 

providing a definition for each of the source groups 

and source categories used in the EIS analyses 

sooner in the documents and consistently when 

describing “Source Groups/Source Categories” as a 

whole.

In this Supplemental EIS, “Source Categories” were 

only used to discuss the source apportionment 

assessment. However, the modeling results and 

impacts assessment reference the “Source Groups.” 

Table 4-5, which showcases “Source Groups” in 

relation to “Source Categories,” as well as providing a 

definition of the corresponding source, has been 

moved up in this Supplemental EIS for better 

explanation for the reader.

United States 

Environmental 

Protection 

Agency

USEPA-21 Appendix F - Specific Comments

Overall, BOEM’s 2012 Weather Research & 

Forecasting (WRF) dataset model performance 

results based on METSTAT appears reasonable; 

however, EPA suggests that BOEM consider 

including EPA’s Atmospheric Model Evaluation Tool 

for some meteorological parameters in future WRF 

The WRF modeling has been finalized for this 

Supplemental EIS analysis and refined modeling 

efforts. The METSTAT tool will continue to be used 

for this modeling since it is recognized and historically 

used as the meteorological modeling evaluation tool. 

However, BOEM will consider including other model 

evaluation tools in future WRF performance 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-115

Commenter Comment ID Comment Response

performance evaluations. evaluations.

United States 

Environmental 

Protection 

Agency

USEPA-22 EPA recommends, per Appendix W’s Section 9.0 

Regulatory Application of Models-9.1 Discussion, 

that BOEM extend its WRF datasets to 3 years. The 

3-year WRF datasets do not necessarily have to be 

consecutive years as long as an adequate 

performance evaluation (see comment 1) of the 

3-year WRF dataset is performed.

Only 1 year of WRF data is used in this analysis, 

which is typical for regional scale photochemical 

modeling. Also, given current limitations in computer 

processing power, it is not technically feasible to 

prepare photochemical modeling results of the type 

presented in this Supplemental EIS for a 3-year 

period.

The WRF modeling is finalized for this Supplemental 

EIS analysis and refined modeling efforts. However, 

BOEM will consider running 3-year WRF datasets for 

future photochemical modeling efforts if sufficient time 

and computing power become available.

United States 

Environmental 

Protection 

Agency

USEPA-23 Appendix G - Specific Comments

Section G.2.1, page G-5, describes the selection of 

2012 as the base case year due to an unusually hot 

and dry year in the region during 2011. Since the 

selection of time specific meteorology and emission 

inventories are the basis on which all modeling 

impacts are assessed, EPA recommends that the 

report provide more quantitative information to 

support the decision to choose 2012 as the base 

year.

BOEM will consider including more quantitative 

information in support of the selection of 2012 as a 

base year over 2011 in BOEM’s final study report and 

NEPA analysis.

United States 

Environmental 

Protection 

Agency

USEPA-24 Section G.3.3, page G-9, indicates that the ERG 

team ran the MOVES2014 model for onroad sources 

to develop 2012 emission estimates. However, no 

further discussion was provided explaining what 

assumptions or procedures were employed when 

generating these emission estimates. EPA 

recommends that this technical report provide 

additional documentation for this approach.

Onroad emissions were generated using the SMOKEMOVES integration tool. This SMOKE-MOVES 

processing approach has been used in various 

regulatory applications by USEPA. The SMOKEMOVES uses emission rate lookup tables generated 

by the MOVES mobile source emissions model. The 

MOVES generates emissions by process (i.e., 

running, start, vapor venting, etc.), vehicle type, road 

type, ambient temperature, vehicle speed, hour of 

day, and other factors. To generate the MOVES 

emission rates that could be applied across the U.S., 

USEPA uses an automated process to run MOVES to 

produce emission factors by temperature and speed 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-116 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

for a series of “representative counties,” to which 

every other county is mapped. Representative 

counties are used because it is impractical to generate 

a full suite of emission factors for each of the more 

than 3,000 counties in the U.S. Representative 

counties are selected according to the state in which 

they are located, elevation, fuel characteristics, 

vehicle age distribution, ramp fraction, and inspection 

and maintenance programs. Each county is then 

mapped to a representative county based on its 

similarity with the representative county with respect 

to these attributes.

In this modeling study, the SMOKE-MOVES system 

was used with the WRF gridded hourly meteorological 

data, MOVES2014 emission factor lookup table for the 

2012 calendar year, and 2011 NEI version 2 

(2011NEIv2) vehicular activity data to generate 

gridded, day-specific, hourly onroad mobile source 

emissions.

Further documentation on assumptions used for 

MOVES2014 is expected to be included in BOEM’s 

final study report and NEPA analysis.

United States 

Environmental 

Protection 

Agency

USEPA-25 EPA recommends that the caption of Figures G-1 

and F-1 be revised to more accurately indicate that 

the gray dots are active leases or potential platform 

locations, rather than defining the gray dots as 

platform locations. As defined, when the reader 

compares Figures G-5 through G-7 with Figure G-1, 

it is confusing, as it would appear that many existing 

platforms west of the 87.5-degree line that are 

missing if the reader is not aware that the gray dots 

actually represent active lease blocks.

BOEM is now in the process of updating the air quality 

model based on public comments and will publish the 

results when the analysis is complete. Please refer to 

BOEM’s response to Comment CEA-3 for information 

detailing BOEM’s update of the air quality modeling 

run and the use of the initial air quality analysis in this 

NEPA document. Based on the results of the 

analyses, BOEM will consider changing the titles of 

Figures G-1 and F-1 of the 2017-2022 GOM Multisale 

EIS (Figures C-1 and B-1 of this Supplemental EIS) 

to “Location of the “Air Quality Modeling in the Gulf of 

Mexico Region” Study, with Class I areas (purple) and 

existing wells (gray dots)” in BOEM’s future NEPA 

documents.
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-117

Commenter Comment ID Comment Response

United States 

Environmental 

Protection 

Agency

USEPA-26 In Section G.3.7, on page G-19, BOEM lists the 

biogenic and geogenic sources. Onshore biogenic 

(vegetation) emissions are included in the modeling; 

however, this Section does not seem to include 

offshore biogenic emissions such as dimethysulfide 

(DMS), which are a significant source of atmospheric 

sulfur compounds. EPA recommends including DMS 

or providing an explanation in the report for the 

exclusion of this category of biogenic emission 

sources.

BOEM’s Year 2011 Gulfwide Emissions Inventory

(Wilson et al., 2014) was reviewed to uncover 

emissions estimates from biogenic sources in the 

GOM. The only available emissions data seemed to 

be on VOC subsurface seeps of oil and N2O from 

bacterial processes, which were included in the 

inventory and in this modeling study.

The DMS emissions and DMS chemistry is included in 

the GEOS-Chem global model used to generate 

boundary conditions (BCs) for the CAMx modeling 

used in this study. The DMS from GEOS-Chem is 

added to the CAMx CB6r2h SO2 BC, and MSA 

(methylsulfonic acid) from GEOS-Chem is added to 

the CAMx CB6r2h PSO4 BC. While DMS emissions 

within the CAMx domain are not modeled, their main 

effect would be to increase natural (background) 

sulfate, which is not likely to have any significant effect 

on predictions of new oil and gas source emission 

impacts on PM species.

United States 

Environmental 

Protection 

Agency

USEPA-27 In Section G.4.1, on page G-20, when describing 

future year modeling scenario estimates off the coast 

of Mexico, the analsyis includes just one sentence: 

“Projected emission estimates were developed for 

anticipated offshore drilling off the coast of Mexico.” 

EPA recommends that the report include additional 

detail of what sources and assumptions were used to 

estimate these emissions, as well as the magnitude 

of these emissions, or include a specific reference in 

this section to the developed emissions inventory for 

this area.

The ERG developed projected emissions estimates 

for platforms off the coast of Mexico. The ERG 

researched the impacts of the restructuring of the 

energy sector in Mexico, which is predicted to include 

deepwater production within the modeling domain. 

The ERG estimated emissions based on projected 

deepwater production (PEMEX, 2012) and using the 

production-based emission factors developed from the 

Year 2011 Gulfwide Emissions Inventory (Wilson 

et al., 2014). These estimates were developed using 

the Year 2011 Gulfwide Emissions Inventory

estimates for major platforms (excluding caissons, 

living quarters, and wellhead protectors), combined 

with production data from BOEM’s Part A Oil and Gas 

Operations Reports (OGOR) (USDOI, BOEM, 2015).

BOEM will consider including additional 

documentation on Mexico’s future-year offshore oil 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-118 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

and gas emissions estimates in BOEM’s final study 

report and NEPA analysis.

United States 

Environmental 

Protection 

Agency

USEPA-28 Section G.4.1, on page G-20, describes how the 

ERG team developed annual emission estimates for 

each year of activity for OCS offshore oil and gas 

production sources using BOEM’s “spreadsheetbased data analyses tools.” EPA recommends that 

the report provide a brief description of these data 

analysis tools and a description of how these 

emission factors may vary by source and year. 

BOEM used past Gulfwide emissions inventory 

studies to compute an average emissions factor for 

each equipment type by water depth. A similar 

approach was used for vessels and helicopters; 

engine power ratings and load factors were taken from 

past Gulfwide emissions inventory studies and 

combined with the most up-to-date USEPA emission 

factors. The spreadsheet-based data analyses tool 

then calculates annual emissions using these 

emission factors and proposed activity scenario. The 

resulting annual emissions estimates vary by year 

depending on the proposed activity scenario.

BOEM will consider explaining BOEM’s Excel 

“spreadsheet-based data analyses tool” that BOEM 

also updated recently to use GOADS emissions to 

generate typical emissions per source in BOEM’s final 

study report and NEPA analysis.

United States 

Environmental 

Protection 

Agency

USEPA-29 Section G.4.1, page G-20, states that the emissions 

estimates are based on mid-price oil case scenarios. 

Further elaboration on the assumptions and details 

of this scenario would be helpful to determine the 

impact on potential emission estimates. EPA 

recommends including a link to the references that 

were used to develop these scenarios. Further, EPA 

recommends looking at a range of oil price cases in 

addition to the mid-price case and performing 

sensitivity analyses to estimate how the emissions 

could vary depending on a range of oil price 

scenarios. If these types of analyses were 

conducted, they should be included in the EIS 

reference documents. 

BOEM uses a series of spreadsheet-based data 

analyses tools to develop the forecasts of oil and gas 

exploration, development, and production activity 

scenario for each action alternative presented in the 

2017-2022 GOM Multisale EIS and this Supplemental 

EIS. A more detailed description of the assumptions 

and details of how BOEM develops the oil and gas 

activity scenarios can be found in Chapter 3.1.2. 

Based on previous analyses by BOEM (USDOI, MMS, 

2007c), the actual activity falls generally below the 

level of activity forecasted in its NEPA documents, 

and the majority of time the actual activity was at or 

near the low end of the forecasted range. The 

analysis of potential environmental and 

socioeconomic impacts presented in this 

Supplemental EIS is therefore considered 

conservative. The air quality model aggregates the 

highest year contribution for all scenario activities into 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-119

Commenter Comment ID Comment Response

a single year to create an estimated high year. BOEM 

used the mid-price exploration and development 

activity scenarios (50th percentile level of activity) in 

the air quality model because this activity level would 

be most reasonably foreseeable to occur, especially in 

light of developing an estimated high year of 

emissions for the air quality modeling input. The use 

of the mid-case scenario to develop the estimated

high emissions year would result in an estimation of 

emissions in a hypothetical future year that BOEM 

feels would be high but reasonably foreseeable.

In reference to the request for links to references that 

were used to develop the scenario, no direct links to 

references are available at this time because much of 

the data used to develop the scenarios is proprietary.

United States 

Environmental 

Protection 

Agency

USEPA-30 Section G.4.1.1, page G-21, projects future oil and 

gas production platforms based on two different 

emission factors distinguished by shallow water 

(<200 m) vs. deepwater (>200m). EPA recommends 

that the report provide the specific reasoning as to 

why this is the delineated depth cut-off. Since 

emissions are significantly higher for the deepwater 

depth, EPA suggests generating more emission 

depth bins, similar to the ocean depth bins used 

during the platform location distribution performed for 

the future year estimates. This will provide a more 

accurate representation of future year emissions.

Please refer to BOEM’s response to Comment CEA-3 

for information detailing BOEM’s update of the air 

quality modeling run and the use of the initial air 

quality analysis in this NEPA document. 

The updated modeling and final report could possibly 

include more than two emission depth bins. BOEM 

will consider looking into generating emissions factors 

for different water-depth bins (more than just two 

conducted in the original modeling), including a 

shallow-water “caisson” emission factor, for the final 

study report and NEPA analysis. 

United States 

Environmental 

Protection 

Agency

USEPA-31 Section G.4.1.3, page G-22, discusses the approach 

of estimating emissions from oil and gas production 

offshore support vessels. BOEM used an estimated 

vessel trip of 200 nautical miles, which is the roundtrip distance from shore to the mid-point of Federal 

waters. Since the platforms were randomly placed in 

lease blocks and modeled as point sources from 

these set locations, EPA suggests that BOEM use 

the actual modeled platform distances, which could 

Please refer to BOEM’s response to Comment CEA-3 

for information detailing BOEM’s update of the air 

quality modeling run and the use of the initial air 

quality analysis in this NEPA document.

BOEM will consider generating vessel emissions 

based on the placement of future year platforms, 

including the helicopter sources with BOEM’s Office of 

Resource Evaluation’s assistance for the final study 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-120 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

vary significantly from the mid-point assumption. effort and NEPA analysis and to make clear the vessel 

and helicopter spatial allocation through 

documentation.

United States 

Environmental 

Protection 

Agency

USEPA-32 Section G.4.1.5, page G-29, indicates that the 

production platforms were located as point sources 

with randomly assigned locations. The location of 

these sources may significantly alter the modeling 

impacts. EPA suggests that the report provide 

further detail into the assumptions and reasoning of 

the random assignment. If not part of the analysis, 

EPA suggests using a probabilistic function applied 

to this random distribution, such as the likelihood 

(probability) for new platforms to set up in shallow 

water vs deep water, etc. Additionally, EPA 

recommends investigating multiple scenarios to 

support a sensitivity analysis (i.e., more deepwater 

development vs more shallow water scenarios). 

Please refer to BOEM’s response to Comment CEA-3 

for information detailing BOEM’s update of the air 

quality modeling run and the use of the initial air 

quality analysis in this NEPA document.

The number of future-year platforms was not random, 

as this is determined by BOEM’s lease sale scenario. 

However, the locations of these platforms were 

random within the water depth and planning area for 

unleased blocks given in the scenario. BOEM’s air 

quality personnel will work with BOEM’s Office of 

Resource Evaluation, who developed the scenario to 

have improved spatial allocation based on where the 

future oil and gas resources are located for the refined 

modeling effort. 

United States 

Environmental 

Protection 

Agency

USEPA-33 Section G.4.1.5, page G-29, describes how the 

emissions were spatially allocated. Only one 

sentence was used to detail allocation for helicopters 

and support vessels: “Because helicopters, support 

vessels, and tankers transit multiple water depths, 

their emissions were allocated across multiple water 

depth contours based on assumed installed platform 

locations.” EPA recommends that the report provide 

more information explaining in further detail how 

these emissions are spatially represented in the 

modeling, or provide such information in a technical 

support document to be released with the final 

report.

Please refer to BOEM’s response to Comment CEA-3 

for information detailing BOEM’s update of the air 

quality modeling run and the use of the initial air 

quality analysis in this NEPA document.

BOEM anticipates including in the final study report 

and NEPA analysis more explanation detailing how 

vessel and helicopter emissions were spatially 

represented in the modeling. BOEM anticipates 

including well stimulation vessels and floating and 

production storage and offloading vessels (FPSOs). 

United States 

Environmental 

Protection 

Agency

USEPA-34 Section G.4.2, page G-30, describes how the 2017 

projections were selected for onshore sources and 

marine vessels over projected 2025 inventory data. 

The reasoning provided was that there is less 

uncertainty associated with the 2017 estimated 

emissions. Although this may be true, it is also 

possible that 2025 projections may match more 

The USEPA’s modeling platform emissions 

projections for 2017 are more conservative (i.e., 

higher) than USEPA’s 2025 emissions projections for 

all pollutants except for ammonia and PM10. For 

additional details on USEPA’s modeling platforms, 

please refer to their website at https://www.epa.gov/
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-121

Commenter Comment ID Comment Response

closely with the future year emissions of the OCS 

offshore oil and gas production sources in years 

2033 and 2036. EPA suggests that it would be 

helpful to describe how the onshore and marine 

vessel emission projections differ from the 2017 and 

2025 projections and to discuss which data set is 

more conservative and why.

air-emissions-modeling/2011-version-62-platform.

Overall, the projections to calendar years 2017 and 

2025 are based on anticipated point source closures, 

implementation of future regulatory control programs, 

and predictions of future activity levels. The year 2017 

was selected because it represents the starting point 

for the 5-year lease sale program and is believed to 

be more realistic of future onshore and marine 

activities. 

BOEM anticipates discussing the reasoning behind 

the choice of 2017 as the future year instead of 2025, 

with perhaps some quantitative discussion of which is 

more conservative in BOEM’s final study report and 

NEPA analysis.

United States 

Environmental 

Protection 

Agency

USEPA-35 Section G.4.3, page G-30, discusses projected 

emissions for platform development off the coast of 

Mexico, which is predicted to include deepwater 

drilling within the modeling domain. Emissions were 

estimated based on projected deepwater production 

in which BOEM includes a citation to a report from 

Petróleos Mexicanos (PEMEX). EPA suggests that 

BOEM elaborate more on the scope and magnitude 

of these included projected emissions.

The ERG developed projected emissions estimates 

for platforms off the coast of Mexico. The ERG 

researched the impacts of the restructuring of the 

energy sector in Mexico, which is predicted to include 

deepwater drilling within the modeling domain. The 

ERG estimated emissions based on projected 

deepwater production (PEMEX, 2012) using the 

production-based emission factors developed from the 

Year 2011 Gulfwide Emissions Inventory (Wilson 

et al., 2014). These estimates were developed using 

the Year 2011 Gulfwide Emissions Inventory

estimates for major platforms (excluding caissons, 

living quarters, and wellhead protectors), combined 

with production data from BOEM’s Part A Oil and Gas 

Operations Reports (OGOR) (BOEM, 2015).

BOEM anticipates elaborating on the scope and 

magnitude of Mexico’s offshore deepwater drilling 

emissions in BOEM’s final study report and NEPA 

analysis.
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-122 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

United States 

Environmental 

Protection 

Agency

USEPA-36 Appendix H - Specific Comments

Throughout Appendix H, Congestion Mitigation and 

Air Quality (CMAQ) modeling inputs and procedures 

are discussed and referenced; however, there is very 

little to no discussion of the CMAQ modeling results 

and how they were applied in this study. EPA 

recommends that the report provide further 

elaboration on how the CMAQ modeling was used, 

including how it compared with the Comprehensive 

Air Quality Model with Extensions (CAMx) results 

and overall model performance.

The Community Multisale Air Quality model (CMAQ) 

was run for comparison with CAMx and also to 

generate wind-blown dust and lightning NOx emissions 

for use in CAMx. The rational for basing the futureyear air quality impacts analysis on CAMx is described 

in Appendix D. 

BOEM anticipates including discussion of the 

comparison of CMAQ to CAMx in BOEM’s final study 

report and NEPA analysis. Upon completion, this 

report and NEPA analysis will be made available for 

public review and comment.

United States 

Environmental 

Protection 

Agency

USEPA-37 Section H.3.9.9 on Page H-27 summarizes the preprocessed emissions in Table H-5. EPA suggests 

that BOEM also describe the BOEM OCS Action and 

No Action alternatives and other sources that were 

not already described in Table H-4. 

BOEM acknowledges that this table is confusing and 

will clarify it in future NEPA documents.

United States 

Environmental 

Protection 

Agency

USEPA-38 Section H.3.9.9, page H-27, in Table H-5 there are 

zero (0) emissions listed under the base year (2012) 

for 2 categories (platform and support vessel) of 

BOEM OCS activity for both the No Action and 

Action scenarios. It is unclear why there are no 

emissions listed in the no action scenarios for the 

base year, since it is our understanding that the base 

year no action emissions represent existing OCS 

activity. Additionally, it is unclear why the future year 

platform and support vessel No Action scenarios 

have higher emissions than the corresponding action 

scenario for several pollutants. EPA recommends 

that the study report provide information on the basis 

for these assumptions and results.

We recognize that Table H-5 of the 2017-2022 GOM 

Multisale EIS (Table D-5 of this Supplemental EIS) is 

confusing. In addition, we recently identified some 

errors that were made when this table was originally 

prepared. However, these errors only pertain to the 

table and not the actual emissions that were modeled; 

the modeled emissions are correct. The corrected 

Table H-5 of the 2017-2022 GOM Multisale EIS 

(Table D-5 of this Supplemental EIS) is at the end of 

this comment response section.

Emissions in the “BOEM OCS Platform No Action” and 

“BOEM OCS Sup. Vessel No Action” categories 

represent only emissions included in the future-year 

scenario. Existing platform emissions in the 2012 

base case were included in the “Non-US Point (with 

GOM offshore platforms)” category and 2012 base 

case support vessel emissions were included in the 

“BOEM Gulfwide” category.
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-123

Commenter Comment ID Comment Response

In addition, all of the emission categories in Table H-5 

of the 2017-2022 GOM Multisale EIS (Table D-5 of 

this Supplemental EIS) are mutually exclusive. In 

particular, the “BOEM OCS Platform w/Action” and 

“BOEM OCS Sup. Vessel w/Action” categories 

represent just the additional emissions from new 

sources associated with the proposed action.

United States 

Environmental 

Protection 

Agency

USEPA-39 EPA recommends that Section H.3.9.9 on page 

H-28, in Table H-6, provide additional information to 

explain why emissions in the BOEM Gulfwide Sector 

are not increasing due to the OCS offshore projected 

activity. EPA suggests this table also include 

information about both scenarios (action and no 

action) and include further description of the sources 

categories for clarity.

Comments from Federal agencies, industry, and the 

general public obtained during the public comment 

period and from meetings concerning the initial air 

quality model are being taken into consideration as 

BOEM revises the initial air quality model. Please 

refer to BOEM’s response to Comment CEA-3 for 

information detailing BOEM’s update of the air quality 

modeling run and the use of the initial air quality 

analysis in this Supplemental EIS. 

The decrease in NOx and PM2.5 in the BOEM Gulfwide 

category is misleading because some sources are 

included in other row categories, but all sources were 

included in the analyses and our impacts results from 

this initial modeling will not change. For future 

documentation, BOEM will present all data more 

clearly.

United States 

Environmental 

Protection 

Agency

USEPA-40 In Section H.3.9.9 on pages H-29 through H-31, for 

Figures H-14 through H-16, EPA suggests it may be 

beneficial to show difference plots between the two 

scenarios to explore the incremental changes in the 

magnitude and spatial representation of the 

emissions. In addition, EPA suggests BOEM break 

up the “No Action” plots in a similar manner to the 

“With Action” plots (i.e., platform emissions vs. 

support vessel emissions). In addition, it is unclear 

why the time stamps on the spatial plots read 

“August, 15 2002” in these Figures. EPA 

recommends that the report provide an explanation 

for this past date or correct the time stamp, as 

necessary. 

BOEM acknowledges USEPA’s comment and will take 

it into consideration when we include the updated air 

quality modeling in a future NEPA analysis. BOEM 

anticipates addressing the time stamp on these 

figures and looking into breaking up the “No Action” 

and the “With Action” plots in BOEM’s final study 

report and NEPA analysis. Upon completion, this 

report and NEPA analysis will be made available for 

public review and comment.
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-124 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

United States 

Environmental 

Protection 

Agency

USEPA-41 Section H.3.10, page H-33, discusses the source 

categories for the source apportionment modeling 

performed. Among these is the base case “No 

Action” scenario where platforms and support 

vessels and helicopters were projected for the future 

year scenario. It was not clear to EPA how these 

emission projections were calculated; EPA 

recommends the report provide additional 

information to support these results.

Emissions estimates are provided in Appendix G of 

the 2017-2022 GOM Multisale EIS (Appendix C of 

this Supplemental EIS). The “No Action” scenario 

emissions are the existing emissions. For the 

preliminary modeling, base case platforms and 

support vessels and helicopters remained static for 

the future-year modeling run. BOEM will clarify this in 

the final study report and NEPA analysis. Upon 

completion, this report and NEPA analysis will be 

made available for public review and comment.

United States 

Environmental 

Protection 

Agency

USEPA-42 Section H.4.2, page H-35, describes the model grid 

configuration. Florida is largely excluded from the 

smallest, highest resolution, 4-km grid. EPA 

recommends including additional information on the 

impacts to Florida. If the impacts are expected to be 

insignificant, EPA recommends providing a more 

detailed explanation supporting this conclusion.

Florida is included in the 12-km domain, and impacts 

were assessed in Florida through the 12-km domain. 

However, the analysis was not detailed in the Draft 

Supplemental EIS because the 4-km domain includes 

the potential areas of interest. The limited domain

does not suggest the impacts to Florida are 

insignificant; however, Florida was outside of the area 

of interest for this Supplemental EIS. BOEM can 

provide clarification of this point in BOEM’s final study 

report and NEPA analysis.

United States 

Environmental 

Protection 

Agency

USEPA-43 The title of Table H-18 (page H-84) is unclear; 

“...with Source Groups Removed.” It appears that 

this table provides the contribution from each source 

group, less F, to the design year future (DVF) value. 

Summing the A-E Source Groups values does not 

equal the provided DVF value. It appears that to 

obtain the DVF value provided, Source Group E 

should have been included. EPA recommends that 

the source of the values in the Table be clarified.

Table H-19 of the 2017-2022 GOM Multisale EIS 

(Table D-19 of this Supplemental EIS) provides MATS 

results at air quality monitoring sites for ozone design 

values. These MATS results are only available for 

ozone and PM2.5 at locations of ozone and PM2.5 air 

quality monitors. Analysis of impacts at Class I/II 

areas is presented in Section H.7.2 of the 2017-2022 

GOM Multisale EIS (Section D.7.2 of this 

Supplemental EIS).

United States 

Environmental 

Protection 

Agency

USEPA-44 Table H-19 (page H-86) provides important 

information concerning anticipated impacts from 

oil/gas OCS activities associated with the lease 

sales. Similar tables addressing other pollutants of 

interest at PSD Class I and sensitive PSD Class II 

areas would be valuable in the final report, and for 

reference in future EIS documents.

Table H-19 of the 2017-2022 GOM Multisale EIS 

(Table D-19 of this Supplemental EIS) provides MATS 

results at air quality monitoring sites for ozone design 

values. These MATS results are only available for 

ozone and PM2.5 at locations of ozone and PM2.5 air 

quality monitors. Analysis of impacts at Class I/II 

areas is presented in Section H.7.2 of the 2017-2022 

GOM Multisale EIS (Section D.7.2 of this 

Supplemental EIS).
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-125

Commenter Comment ID Comment Response

United States 

Environmental 

Protection 

Agency

USEPA-45 The footnote in Figure H-41 (page H-88) referring to 

Table H-14 (page H-71) for definitions of Source 

Groups is not correct. Table H-14 provides values 

for NAAQS and PSD Increments. EPA suggest that 

this should be corrected in future documents 

associated with this EIS.

BOEM is now in the process of updating the air quality 

modeling based on public comments and will publish 

the results when the analysis is complete. Revisions 

to associated documents will be made as necessary. 

However, correcting the footnote would not change 

BOEM’s impact determinations.

United States 

Environmental 

Protection 

Agency

USEPA-46 The NAAQS comparison used two methods; direct 

comparison of modeled results (absolute) and use of 

the relative response factors to obtain modeled 

concentrations (Model Attainment Test Software 

(MATS)). The inclusion of both the MATS and the 

absolute O3 NAAQS (Section H.7.1.2, beginning on 

Page H-87) and explanation is somewhat confusing 

and may be misinterpreted. EPA suggests that only 

the O3 NAAQS assessment method deemed most 

appropriate (i.e., MATS) be provided, with a brief 

explanation or footnote on other methods 

considered.

It is customary to include both the MATS results (both 

at monitoring sites and, when appropriate, the MATS 

unmonitored area analysis) and the absolute model 

results in an air quality impact assessment conducted 

for inclusion in an EIS. Characteristics of both 

approaches are compared in Section H.6.2.2 of the 

2017-2022 GOM Multisale EIS (Section D.6.2.2 of 

this Supplemental EIS). While MATS is USEPA’s 

recommended approach for calculating future-year O3

and PM2.5 design values at monitoring sites, the MATS 

unmonitored area analysis can produce misleading 

results in areas with limited monitoring data, in which 

case the absolute model predictions provide the best 

available estimate.

The discussion of the two different methods in 

Section H.6.2.2 of the 2017-2022 GOM Multisale EIS 

(Section D.6.2.2 of this Supplemental EIS) can be 

expanded to clarify the relative advantages and 

disadvantages of each approach. BOEM may also 

decide to include results from only the MATS method 

in future EISs.

United States 

Environmental 

Protection 

Agency

USEPA-47 The footnote on page H-97 indicates that the MATS 

software cannot perform the unmonitored area 

analysis (UAA) for the 24-hour average PM2.5

NAAQS. EPA recommends that the effect of this 

limitation on the provided 24-hour estimates be 

provided in the final report.

The provided future-year, 24-hour PM2.5 design values 

are based on the absolute model predictions. The 

characteristics of this approach vs. the MATS 

approach are described in Section H.6.2.2 of the 

2017-2022 GOM Multisale EIS (Section D.6.2.2 of 

this Supplemental EIS) (refer to the response to 

Comment USEPA-46).
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-126 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

Water Quality

David Quist DQ-5 Water Quality

- just because the Gulf, or portions of it, has become 

a sacrifice zone in many respects does not mean 

that additional incremental impacts pushing it even 

further over the edge are acceptable. Such impacts 

are significant - impact of spills are catastrophic, and 

routine operations are NOT "negligible" or 

"moderate" even by the description in the executive 

summary portion of the EIS.

Thank you for your comment. A summary of the 

impacts of a proposed action on water quality can be 

found in Chapter 4.2, and a full analysis of these 

impacts can be found in Chapter 4.2 of the 2017-2022 

GOM Multisale EIS, from which this Supplemental EIS 

tiers.

BOEM’s conclusion that a proposed action will have a 

negligible incremental contribution to water quality is 

based on the analysis of an incremental contribution 

of a single proposed regionwide lease sale to all 

cumulative impacts in the Gulf of Mexico. The 

USEPA’s regulations on waste streams generated 

from offshore oil- and gas-related activities help to 

mitigate routine oil and gas activity impacts.

Reasonably foreseeable oil spills are anticipated to 

have moderate impacts on water quality, as discussed 

in Chapter 4.2. A catastrophic oil spill is not part of a 

proposed action nor is it considered likely to occur. 

BOEM, nevertheless, provides an analysis of such a 

spill in the Catastrophic Spill Event Analysis white 

paper (USDOI, BOEM, 2017a).

Coastal Habitats

Center for 

Biological 

Diversity, 

Sierra Club, 

Gulf 

Restoration 

Network,

Louisiana 

Bucket 

Brigade

CBD,SC,GRN,

LBB-11

The Draft SEIS inadequately addresses this lease 

sale’s impact on coastal habitat. The Draft SEIS 

incorrectly states there is no new information on 

coastal impacts and concludes that the proposed 

action’s impacts will be moderate without any 

analysis of the site-specific and species specific 

damage to expect. This falls short of NEPA’s 

requisite hard look analysis. The Gulf Coast will lose 

significant coastal wetlands as a result of the 

proposed action. The Bureau concedes that the 

reasonably foreseeable impacts of offshore oil and 

gas activities on coastal habitats are major, meaning 

Thank you for your comment. Please refer to 

Chapters 4.3.1 and 4.3.2 for a summary of the 

analysis of oil and gas development impacts on 

wetlands and coastal barrier beaches and associated

dunes. Detailed analyses of these resources can be 

found in Chapters 4.3.1 and 4.3.2 of the 2017-2022 

GOM Multisale EIS, from which this Supplemental EIS 

tiers. Please note that this Supplemental EIS 

indicates that no new information was discovered that

would alter the impact conclusion for estuarine 

systems presented in the 2017-2022 GOM Multisale 

EIS, not that there was no new information on coastal 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-127

Commenter Comment ID Comment Response

there will be longstanding and extensive 

“widespread, permanent loss of habitat; changes in 

species composition and abundance and/or altered 

ecological function well beyond that of normal 

variability.” The area’s coastal wetlands are 

experiencing a “death-by-a-thousand-cuts.” The 

largest category of damage is from the large crude 

oil pipelines that are the foreseeable consequence of 

OCS development. The maintenance of old crude oil 

pipelines, such as Shell’s Ship Shoal Pipeline, as 

well as construction of new oil transport pipelines like 

Energy Transfer Partners’ Bayou Bridge Pipeline 

have impacted an average of over 700 acres of 

wetlands per year in the New Orleans District of the 

Corps alone.

The Bureau’s analysis here improperly accounts for 

the appreciable damage that this lease sale adds to 

the overall degraded condition of wetland forest and 

coastal habitats. To fully inform the decision-maker 

about the impacts of the proposed action, the Bureau 

must identify which areas, habitats, species, and 

communities will be directly and indirectly harmed 

and to what extent by the lease sale. This is 

necessary to guide the decision on which alternative 

to select and mitigation. From 1932 to 2010, coastal 

Louisiana lost about 1.2 million acres, equating to 

coastal wetlands disappearing at a rate of about a 

football field per hour. The oil and gas industry 

admits that it is responsible for at least 36% of the 

total loss of this area, though the Department of the 

Interior has stated that the industry could be 

responsible for as much as 59% of the loss. And 

scientists say that at current rates, coastal erosion 

and sea level rise will lead to nearly all of Southeast 

Louisiana to be under water by 2100. Models 

estimate a loss up to 1,739 square miles over the 

next 50 years. A large amount of remaining 

impacts.

BOEM has analyzed both the impacts of a single 

proposed regionwide lease sale and the cumulative 

impacts of the OCS Oil and Gas Program in this 

Supplemental EIS. BOEM classifies the incremental 

contribution of a proposed action (an individual 

proposed regionwide lease sale) to the cumulative 

impacts on estuarine systems to be minor to 

moderate, depending on the selected alternative. In 

addition, BOEM classifies the incremental contribution 

of a proposed action (an individual proposed 

regionwide lease sale) to the cumulative impacts on 

coastal barrier beaches and associated dunes to be 

minor. There are two “major” impact determinations, 

which are different from the possible impacts of a 

single proposed regionwide lease sale. One is the 

impact determination of the entire cumulative Oil and 

Gas Program (i.e., routine activities projected to occur 

and accidental events that could occur) from past, 

proposed, and future lease sales. The other is the 

non-OCS oil- and gas-related impacts, which include 

past, present, and reasonably foreseeable future 

activities occurring within the same geographic range 

and within the same timeframes as the proposed 

action; however, they are not related to the OCS Oil 

and Gas Program.

Louisiana’s land loss has been acknowledged in this 

Supplemental EIS, but the contribution from the oil 

and gas industry has been more from inshore 

activities, such as the dredging of location canals 

through marshes, as opposed to OCS oil- and 

gas-related activity. Separating the causes of such 

land loss is difficult, but one study estimated that the 

total of direct and indirect impacts from OCS oil- and 

gas-related activities from 1955 to 1978 accounted for 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-128 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

Louisiana’s wetlands will not keep pace with sea 

level rise. A new model shows that coastal damage 

from disasters, like an oil spill, produces “acute, 

chronic, and cumulative stress in humans” because 

the loss of ecosystem services harms people’s 

livelihoods and health.

The Bureau must specify the additional, site-specific 

coastal impacts by the proposed lease sale, 

including areas where habitat will be lost, impacts to 

wildlife, and human health.

21,863-49,884 ha (54,024-123,266 ac), or 8-17% of 

Louisiana’s total wetland loss (Turner and Cahoon, 

1987). There is only 0-1 pipeline landfall projected to 

result from a proposed action. About 12-20 ac 

(5-8 ha) of land loss for the projected 1.2 mi (2 km) of 

pipeline (based on historic loss rates) are expected 

from the proposed action. This represents 

approximately 0.19% of the total land loss estimated 

to occur along the Louisiana coast in 1 year 

(Couvillion et al., 2011). This estimate does not take 

into account mitigating measures from the present 

regulatory programs of Federal or State agencies, 

modern installation techniques, and the Federal “no 

net loss” policy, which would reduce land loss 

associated with OCS oil- and gas-related activity. In 

reference to the request for site-specific coastal 

impacts of a proposed regionwide lease sale, the 

following paragraphs apply.

The OCSLA requires a staged decisionmaking 

process beginning with the Five-Year Program, 

continuing through individual lease sales under the 

Five-Year Program, and ultimately to individual 

postlease activities requiring a permit or approval. As 

stated in Chapters 1 and 2 of this Supplemental EIS, 

the 2017-2022 GOM Multisale EIS discusses all 

10 Federal actions, i.e., 10 proposed regionwide oil 

and gas lease sales, as scheduled under the 

2017-2022 Five-Year Program, and this Supplemental 

EIS analyzes a single proposed regionwide lease sale 

in the 2017-2022 Five-Year Program. This 

Supplemental EIS approach is intended to focus the 

NEPA/EIS process on the staged OCSLA process for 

decisionmaking, including the proposed regionwide 

lease sales and any new issues and information 

identified since a prior stage. It also lessens 

duplication and saves resources when BOEM and 

BSEE conduct postlease reviews.

Joint Trades JT-29 Our review shows that there were no changes 

between the impact determination table (Table 4-9, 

p. 4- 62) in the Draft SEIS and the Multisale EIS. 

However, for estuarine systems the cumulative 

impact for both OCS oil and natural gas and nonOCS oil and natural gas is shown as “major”. This is 

not what is reflected in the text on page 4-63 which 

describes only minor to moderate impacts.
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-129

Commenter Comment ID Comment Response

Additionally, the issuance of leases does not conclude 

the environmental analysis of planned OCS oil- and 

gas-related activities. Each plan throughout the 

exploration, development, production, and 

decommissioning processes receives a site-specific 

environmental analysis pursuant to NEPA and the 

OCSLA’s pyramidal structure going from large scale to 

site specific. For more information on BOEM’s 

postlease processes, refer to Appendix A of the 

2017-2022 GOM Multisale EIS, from which this 

Supplemental EIS tiers.

Because of these multiple and tiered programmatic 

documents, along with future site-specific reviews that 

tier to these programmatic and discretionary 

documents, BOEM takes a hard look at the potential 

for environmental consequences at each phase of the 

decisionmaking process that considers a proposed 

action in the GOM. At each phase, BOEM has 

identified numerous environmental safeguards to 

minimize the impacts, i.e., through the consideration 

of EISs and programmatic mitigation at the Five-Year 

Program level, consideration of alternatives to limit 

impacts to sensitive topographic features in this 

Supplemental EIS, and commonly applied mitigating

measures.

Chelsea Gray CG-1 I do not believe that EIS supplied is sufficient, and 

therefore leases should not be sold. Statements like 

this are a serious cause for concern: "Due to the 

distance of deep water from shore, the possibility of 

a spill from a deepwater blowout reaching coastal 

wetlands with the toxicity to significantly impact the 

coastal wetlands is low because of the response 

procedures implemented during a catastrophic spill". 

There is nothing in the report to indicate that this is 

100% achievable, and sufficient consideration is not 

given to how foul weather will effect the 

Catastrophic spills, such as a deepwater blowout, are 

not analyzed in this Supplemental EIS, but they are 

analyzed in a separate white paper. For a detailed 

analysis of reasonably foreseeable impacts 

associated with a low-probability catastrophic spill, 

such as the Deepwater Horizon explosion and oil spill, 

refer to the Catastrophic Spill Event Analysis white 

paper (USDOI, BOEM, 2017a).

BOEM determined that, because a catastrophic event 

like the Deepwater Horizon explosion, oil spill, and 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-130 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

environmental impacts, spread of oil, and clean up 

efforts in the event of a spill.

response is not considered reasonably foreseeable as 

a result of a proposed action, the analysis should not 

be included in this Supplemental EIS to avoid 

confusion over whether it is or is not part of a 

proposed action. This is allowed under CEQ’s 

regulations, which removed the requirement to 

analyze worst-case scenarios. However, in 

accordance with CEQ guidance and to inform the 

public of the potential impacts in the unlikely event of 

such a spill (though not reasonably foreseeable), 

BOEM has made this information available to the 

public through its website. BOEM also acknowledges 

that one of the key ways of managing the risk of such 

an event is to implement a rigorous regulatory regime 

to ensure that postlease drilling activities are 

conducted in a safe manner.

Additionally, BOEM is concerned about the potential 

impacts of oil spills on the environment. In this 

Supplemental EIS, impacts of smaller, reasonably 

foreseeable OCS oil- and gas-related oil spills are 

analyzed in the “Accidental Events” section of 

Chapter 4.3.1, and other spills (e.g., in State waters

or from other sources on the OCS) are analyzed in the 

“Cumulative Impacts” section of Chapter 4.3.1. 

In reference to the impacts of foul weather on oil spills 

and cleanup, BOEM has incorporated BOEM’s Oil 

Spill Risk Analysis (OSRA) estimates to determine the 

risk of oil-spill contact to sensitive offshore and 

onshore environmental resources and socioeconomic 

features. Included in this analysis are trajectory 

simulations based on historical surface ocean currents 

and winds, which incorporate periods of hurricane 

conditions. In addition, BSEE provides a robust set of 

regulations relating to hurricane preparedness that 

help lower the risk of oil spills occurring and help 

prevent any loss of life. The effects of hurricanes on 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-131

Commenter Comment ID Comment Response

coastal areas and oil and gas structures are discussed 

in Chapters 3.1.6.1 and 3.2.1.1 of the 2017-2022 

GOM Multisale EIS and in relevant resource sections 

in Chapter 4 of the 2017-2022 GOM Multisale EIS. 

In addition, finalization of the Well Control Rule on 

April 29, 2016, resulted in reforms, such as increased 

regulation of blowout preventers, that are expected to 

decrease the probability of deepwater blowouts and 

the extent of oil spills from such blowouts.

United States 

Environmental 

Protection 

Agency

USEPA-2 It is noted that several impact levels have changed 

since the DSEIS was prepared. Section 4.31 

identifies routine impacts ranging from negligible to 

minor for pipeline construction and maintenance, 

navigation channel maintenance and vessel 

operations, and use of coastal support infrastructure. 

It is still unclear how impacts are deemed negligible 

or minor when a routine activity estimates a wetland 

loss to occur. The Final EIS estimates 12-20 acres 

of wetlands impacts from 0-1 pipeline, 70-860 acres 

of impacts from navigation channel maintenance and 

vessel operations, and notes that large coastal 

infrastructure projects such as the projected 0-1 new 

gas plants and 0-1 new pipeline landfall is likely to 

impact some wetland acreage. In the locations 

where wetland loss is projected, the losses are 

anticipated to be long term or permanent, and 

therefore should be considered moderate based 

upon the impact level definitions being utilized. The 

DSEIS should farther clarify how impacts are 

deemed either negligible or minor.

Thank you for your comment. Chapter 4.3.1

describes the impacts to estuarine systems from 

routine activities associated with a proposed action. 

This Supplemental EIS has been updated to indicate 

that potential impacts from routine activities could be 

negligible to moderate. Impacts from pipeline 

construction and maintenance, navigation channel 

maintenance dredging, and construction and use of 

coastal support infrastructure would range from 

negligible to minor, while vessel operations (support 

use of navigation channels) would range from minor to 

moderate. Refer to Chapter 4.3.1 for details on the 

impacts of each routine activity.

To address the comment on the permanence of 

wetland loss, the impact level definition for “minor” has 

been updated to say “Minor – Noticeable but shortterm or localized impacts.”

In order to clarify the basis for pipeline impacts, BOEM 

projects that the majority of new pipelines constructed 

as a result of a proposed action would connect to the 

existing pipeline infrastructure offshore; therefore, 

there would be no coastal or wetland impacts from 

pipeline landfalls. In the rare instance that a new 

pipeline to shore would need to be constructed, it 

would likely be because there are no existing pipelines 

reasonably close and because constructing a pipeline 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-132 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

to shore is considered more cost effective, although it 

is highly unlikely for an operator to choose this 

contingency (Dismukes, official communication, 2011). 

BOEM anticipates that pipelines from most of the new 

offshore production facilities would tie into the existing 

pipeline infrastructure offshore or in State waters, 

which would result in few new pipeline landfalls 

(page 3-42 of the 2017-2022 GOM Multisale EIS). 

Impacts from pipeline construction and maintenance 

are deemed negligible due primarily to the fact that 

only 0-1 pipeline landfalls are projected with a 

proposed action. In addition, the 12- to 20-ac (5- to 

8-ha) estimate represents the impact that could occur 

without mitigation. In practice, it would likely be an 

overestimate, given current regulatory policies of the 

Corps of Engineers and Gulf Coast States.

National Park 

Service

NPS-1 Thank you for the opportunity to comment on the 

Bureau of Ocean Energy Management' s (BOEM's) 

Final 2018 Supplemental Environmental Impact 

Statement (SEIS) for offshore lease sales in the Gulf 

of Mexico (GOM), specifically the "Coastal Barrier 

Beaches and Associated Dunes" and "Recreational 

Resources" sections of the SEIS. In addition, the 

2017-2022 GOM Multisale Environmental Impact 

Statement (EIS) was referenced. The proposed 

Outer Continental Shelf Oil and Gas Leasing 

Program: 2017-2022 will include regionwide lease 

sales including areas near or with associated 

activities within close proximity to Gulf Islands 

National Seashore (GUIS) in Mississippi and Florida.

The SEIS section on "Coastal Barrier Beaches and 

Associated Dunes" concludes that navigation 

channel maintenance dredging associated with the 

proposed lease sales will have minor environmental 

impacts. While the EIS appears to adequately cover 

the benefits as well as the detrimental impacts 

caused by dredging and dredge disposal methods 

Thank you for your comment. Dredging is discussed 

in Chapter 4.3.2.2.1 of the 2017-2022 GOM Multisale 

EIS, which is incorporated by reference into this 

Supplemental EIS. The 2017-2022 GOM Multisale 

EIS states that “Periodic maintenance dredging is 

expected in existing navigation channels through 

barrier passes and associated bar channels. 

Maintenance dredging of barrier inlets and bar 

channels removes sediment from the system, 

contributing to beach erosion. Materials from 

maintenance dredging of bar and pass channels are 

typically discharged to nearby ocean dumping sites in 

the GOM (Chapter 3.3.2.8.5) or they are used for 

marsh creation or beach nourishment projects as part 

of mitigation . . . . These dredging activities are 

permitted, regulated, and coordinated by the U.S. 

Army Corps of Engineers (USACE) with the 

appropriate State and Federal resource agencies. 

Effects from maintenance dredging related to a 

proposed action on coastal barrier beaches and 

associated dunes are expected to be minor due to the 

small contribution from a proposed action to total 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-133

Commenter Comment ID Comment Response

that may occur at navigational channels, it is unclear 

if the mitigation measures will be required or 

incorporated into the individual leases. The EIS 

states that the US Army Corp of Engineers (USACE) 

uses dredge material beneficially if the material is 

suitable and funds are available. It also states that 

the applicant would need funds to cover the excess 

cost over the least cost environmentally acceptable 

alternative since open water disposal is permitted 

and completed often.

GUIS has several navigational channels adjacent or 

within close proximity to coastal barrier beaches 

within park boundaries. It has been our experience 

that the USACE will generally place dredged material 

in deep water outside the littoral zone because it is 

more cost effective to do so. USACE staff have 

studied swash zone deposition and have 

acknowledged the benefits as keeping the maximum 

amount of sand near or on the beach where the surf 

can move the sand around naturally, increasing 

beach habitat for use by animals (e.g., sea turtles, 

beach mice), birds, and humans. However, cheaper 

and easier options are most often implemented 

which require less monitoring (e.g. of archeological 

resources and protected species) and it can be done 

using a boat rather than setting up a relatively 

complicated pipeline system on the beach. The 

resulting impact s are a sand starved and eroding 

beach downdrift of the navigational channel.

Swash zone placement of dredge material from 

navigational channels should not be funding 

dependent. If and when the leases occur a 

commitment or mitigation requirement that includes 

the additional costs should be included during

subsequent compliance/permitting phases. Leases 

should include a long-term strategy which would 

channel use and the offsetting effects of beach 

nourishment.” 

In reference to NPS asking if BOEM is requiring 

mitigating measures for dredge and dredge disposal 

methods, BOEM is unable to require mitigation on 

another agency’s (Corps of Engineers [COE]) activity 

(dredging). In addition, BOEM is unable to collect 

costs for swash zone placement of dredge material as 

part of the leasing process because another agency 

(COE), not BOEM, is the lead agency for the dredging 

of navigation channels. As discussed in Chapter 

3.3.2.8.5 of the 2017-2022 GOM Multisale EIS, which 

is incorporated by reference into this Supplemental 

EIS, the Corps of Engineers is the lead agency for 

maintenance and construction dredging and is also in 

charge of dredge material disposal and the beneficial 

use of dredge material, such as marsh creation or 

beach nourishment. In addition, dredge material must 

meet certain physical characteristics to be used in a 

beneficial use program. BOEM, however, does 

indicate in this Supplemental EIS that mitigation of 

dredging activity (marsh creation or beach 

nourishment) implemented by COE on their own 

action would additionally mitigate impacts to barrier 

beaches from usage of the navigation channels by 

OCS oil- and gas-related vessels.

Currently, as the lead agency for dredging projects, 

COE has implemented a monitoring and adaptive 

management program through the Mississippi Coastal 

Improvement Program (MsCIP) to evaluate placement 

of dredge material from the Pascagoula Federal 

Navigation Channel in the littoral zone at Horn Island 

Pass, in Mississippi. Monitoring of dredge material 

will occur before, during, and after the placement of 

dredge material. Monitoring will enable COE to 

assess short- and long-term effects of the restoration 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-134 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

facilitate and fund the "swash zone" or nearshore 

placement of suitable dredge materials along coastal 

barrier islands by the US Army Corp of Engineers 

(USACE). Otherwise the barrier islands will continue 

to erode and diminish just as has occurred in the 

Mississippi islands downdrift of the Pascagoula 

shipping channel.

process and provide necessary information for 

adaptive management for other coastal resources 

(U.S. Dept. of the Army, COE, 2016).

Even though BOEM is unable to require lessees to 

fund another agency’s activities, BOEM is part of the 

MsCIP ongoing effort. BOEM was a Cooperating 

Agency on the COE’s 2016 Supplemental EIS for 

Mississippi barrier island restoration and has a 

Memorandum of Agreement with COE’s Mobile 

District to make OCS sand available for barrier island 

restoration in support of the MsCIP (USDOI, BOEM, 

2016d).

Deepwater Benthic Communities

Chelsea Gray CG-2 An effective EIS should not only rely on "best case" 

scenarios, and yet it does throughout. "Studies 

indicate that periods as long as hundreds of years 

are required to reestablish a seep community once it 

has disappeared (depending on the community type) 

(Powell, 1995; Fisher, 1995). There is evidence that 

substantial impacts on these communities could 

permanently prevent reestablishment (Fisher, 1995), 

particularly if hard substrate required for 

recolonization is buried by resuspended sediments 

from a loss of well control. Because widely 

scattered, high-density chemosynthetic communities 

would typically be located at more than 2,000 ft 

(610 m) away from a loss of well control event due to 

mitigating measures, potential accidental impacts 

from the CPA proposed action are expected to cause 

little damage to ecological or biological function of 

these communities." I see nothing in the report to 

indicate that 2,000 ft is a magically safe distance for 

such delicate communities. This is once again a 

"best case" scenario, even wishful thinking.

Protective measures have been developed over time 

based on the nature and sensitivity of various benthic 

habitats and their associated communities, as 

understood from decades of BOEM-funded and other 

environmental studies. One such study (CSA, 2006) 

indicated a separation distance of 2,000 ft (610 m) 

between sensitive deepwater benthic communities 

and drilling activity to be sufficient to protect those 

communities from disturbance. NTL 2009-G40, 

“Deepwater Benthic Communities,” provides operators 

with relevant information and consolidates guidance 

for the avoidance and protection of the various types 

of potentially suitable habitat for chemosynthetic 

organisms and deepwater coral. As detailed in NTL 

2009-G40, all plans submitted for permitted deepwater 

(300 m [984 ft] or greater) activities are reviewed for 

the presence of deepwater benthic communities that 

may be impacted by the proposed activity. Conditions 

of approval are applied at that time. Specifically, for 

deepwater benthic communities, the general types of 

protective measures are identified and summarized in 

the section titled “Historical Protections for Deepwater 

Benthic Communities.” Commonly applied mitigating 

measures during the postlease process are described 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-135

Commenter Comment ID Comment Response

in Appendix B of the 2017-2022 GOM Multisale EIS.

David Quist DQ-9 - Benthic

- no consideration of the impact of catastrophic spills 

or events, the risk of which is not negligible and 

which, if they are occur, are drastic and wide-ranging

Catastrophic spills, such as a deepwater blowout, are 

not analyzed in this Supplemental EIS, but they are 

analyzed in a separate white paper. For a detailed 

analysis of reasonably foreseeable impacts 

associated with a low-probability catastrophic spill, 

such as the Deepwater Horizon explosion and oil spill, 

refer to the Catastrophic Spill Event Analysis white 

paper (USDOI, BOEM, 2017a).

BOEM determined that, because a catastrophic event 

like the Deepwater Horizon explosion, oil spill, and 

response is not considered reasonably foreseeable as 

a result of a proposed action, the analysis should be 

removed from this Supplemental EIS to avoid 

confusion over whether it is or is not part of a 

proposed action. This is allowed under CEQ’s 

regulations, which removed the requirement to 

analyze worst-case scenarios. However, in 

accordance with CEQ guidance and to inform the 

public of the potential impacts in the unlikely event of 

such a spill (though not reasonably foreseeable), 

BOEM has made this information available to the 

public through its website. BOEM also acknowledges 

that one of the key ways of managing the risk of such 

an event is to implement a rigorous regulatory regime 

to ensure that postlease drilling activities are 

conducted in a safe manner.

Additionally, in this Supplemental EIS, impacts of 

reasonably foreseeable OCS oil- and gas-related oil 

spills are summarized in Chapter 4.4, “Deepwater 

Benthic Communities.”

Sargassum and Associated Communities

David Quist DQ-10 - Saragassum

the EIS uses a population-level impact analysis - the 

issue is also ecosystem impact in a specific location. 

Thank you for your comment. Sargassum is 

summarized in Chapter 4.5 of this Supplemental EIS 

and described in full detail in Chapter 4.5 of the 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-136 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

The approach taken in the EIS grossly, and 

artificially, underestimates impact

2017-2022 GOM Multisale EIS. As indicated in the 

“Impact-Level Definitions” in Chapter 4.5, impacts are 

analyzed from the immediate area of impact on a plant 

up through population-level changes in species 

composition. An in-depth analysis of potential 

impact-producing factors determined that, although 

many may occur within the GOM, few occur at an 

extent that could cause impacts to the population of 

Sargassum as a whole. This is because localized 

impacts may occur to a small percentage of a 

population, but Sargassum has a yearly cycle that 

promotes quick recovery from impacts where new 

plants rapidly replace impacted plants. The unique 

and transient characteristics of the life history of 

Sargassum and globally widespread nature of the 

plants and animals that use the plant matrix buffer 

against impacts that could occur at any given location. 

In fact, Sargassum has proliferated in recent years to 

the point that huge amounts of it are found washing up 

on Caribbean island shorelines, fouling beaches and 

affecting tourism (Louime et al., 2017).

In addition, the issuance of leases does not conclude 

the environmental analysis of planned OCS oil- and 

gas-related activities. Each plan throughout the 

exploration, development, production, and 

decommissioning processes receives a site-specific 

environmental analysis pursuant to NEPA and the 

OCSLA’s pyramidal structure going from large scale to 

site specific. For more information on BOEM’s 

postlease processes, refer to Appendix A of the 

2017-2022 GOM Multisale EIS, from which this 

Supplemental EIS tiers.

Gulf 

Restoration 

Network

GRN-8 Because Sargassum passes through the Mississippi 

Canyon area, it is likely that the Taylor leak oils some 

Sargassum. The impact of Taylor on Sargassum 

must be evaluated. Oiled Sargassum could also 

affect juvenile sea turtles and other finfishes that use 

The cumulative oil-spill analysis in this Supplemental 

EIS takes the Taylor leak into account. The impacts 

of oil spills on Sargassum and its associated 

communities are summarized in Chapter 4.5 of this 

Supplemental EIS and discussed in detail in Chapter 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-137

Commenter Comment ID Comment Response

Sargassum for habitat. 4.5.2.2 (“Accidental Events”) of the 2017-2022 GOM 

Multisale EIS. The analyses included in these 

chapters discuss impacts of oil on Sargassum and 

associated communities, which would be similar to 

those that could occur from a spill, such as the Taylor 

platform leak. In addition, oil impacts on sea turtles 

and finfish are summarized in Chapters 4.9.2 and 4.7

of this Supplemental EIS and discussed in detail in 

Chapters 4.9.2.2.2 and 4.7.2.2 of the 2017-2022 GOM 

Multisale EIS, from which this Supplemental EIS tiers.

Marine Mammals

Chelsea Gray CG-4 And also a discussion of chronic issues, especially 

as many large marine mammals are still recovering 

from the BP oil spill.

Thank you for your comment. BOEM acknowledges 

the potential harmful impacts to marine mammals as a 

result of an oil spill. These negative consequences 

are summarized for marine mammals in Chapter 4.9.1

of this Supplemental EIS and discussed in detailed in 

Chapter 4.9.1.2.2 (“Accidental Events”) of the 2017-

2022 GOM Multisale EIS. Impacts of a catastrophic 

spill are analyzed in the Catastrophic Spill Event 

Analysis white paper (USDOI, BOEM, 2017a). As 

impacts from the Deepwater Horizon explosion, oil 

spill, and response continue to be assessed, 

additional analyses will be completed at the sitespecific approval stage and in future Supplemental 

EISs.

Rebecca King RK-2 Has BOEM considered that baby dolphins are still 

dying at an abnormally high rate since the spill?.

Gulf 

Restoration 

Network

GRN-9 BOEM cannot permit more drilling when 2 juvenile 

sperm whales were stranded last year. This is 

unprecedented in the history of the Gulf. Sperm 

Whales have endemic populations in the Gulf--what 

if these children were from those endemic 

populations? Loss of such a keystone predator is 

devastating for the whole system, and BOEM does 

not know the cause. All new activity must cease, in 

order to comply with the ESA plan for this species.

BOEM and BSEE are actively engaged in ESA 

consultation with NMFS and FWS concerning all of 

our past and reasonably foreseeable future activities. 

Until the above-mentioned NMFS’ formal consultation 

is complete, BOEM is under an interim consultation 

agreement with NMFS. The NMFS and FWS are 

informed of the types, levels, and potential impacts 

that may result from proposed oil- and gas-related 

activities and will provide Biological Opinions as part 

of the formal consultation process. The Protected 

Species Stipulation, if applied, would require already 

existing terms and conditions and mitigations 

implemented to protect species from postlease 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-138 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

activities. As the stipulation notes, BOEM and BSEE 

add the most current mitigations or requirements 

about protected species or critical habitats to the 

conditions for approval of any postlease authorization

or permit. The staged OCSLA decisionmaking and 

approval process ensures that BOEM and BSEE can 

require additional protected species protections after 

leases are issued.

Refer to Chapter 5.2 for more information on the ESA 

consultations.

Gulf 

Restoration 

Network

GRN-10 Whale tracking studies have shown that the animals 

have stopped eating in an area around the DWH site. 

We urgently need information on Sperm Whale diet 

and how its diet is changing after the BP DWH 

disaster.

BOEM has an ongoing study to obtain more 

information on sperm whale prey and is currently 

waiting for the final study report. More information on 

this study can be found on BOEM’s website at 

https://www.boem.gov/Environmental-Stewardship/

Environmental-Studies/Gulf-of-Mexico-Region/SDP2008-2010-pdf.aspx. 

Additionally, BOEM is actively involved in the scientific 

community and uses the most current and best

available science for a more informed decisionmaking 

process. As noted in the Protected Species 

Stipulation, should new information become available, 

BOEM and BSEE will add that information to 

postlease site-specific NEPA documents for the 

decisionmaker and can add mitigation or other 

requirements as part of the conditions of approvals.

David Quist DQ-12 Wildlife

- proceeding with the lease sale will involve 

additional exploration which would not occur under 

the no-action alternative. Those activities, 

particularly seismic exploration tools/airguns, have 

significant to catastrophic impact upon marine life, 

particularly protected marine mammals. The fact 

that populations may be experiencing other 

environmental stressors does not change the fact 

By selecting the No Action alternative and avoiding 

those activities associated with a proposed regionwide 

lease sale, those potential impacts related to a single 

proposed regionwide lease sale would be avoided; 

however, please be advised that a decision to cancel 

a single proposed regionwide lease sale would not 

preclude activity related to past lease sales or 

decisions on future lease sales. There are a number 

of currently leased blocks within the proposed 

regionwide lease sale area with proposed plans, and 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-139

Commenter Comment ID Comment Response

adding yet more stressors make a bad situation 

worse, and could lead to the death of individuals, the 

decline or elimination of populations, and the 

collapse of ecosystems.

BOEM anticipates another decision point for the 

proposed regionwide lease sale, which is proposed as 

part of the 2017-2022 Five-Year Program. Should the 

No Action alternative be selected, in the interim, 

industry may explore and develop their existing 

portfolio of leaseholds subject to the terms of those 

leases and any conditions of approval for plans or 

permits.

A full discussion of impacts associated with geological 

and geophysical (G&G) activities is outside the scope 

of this Supplemental EIS because these activities are 

permitted outside of the leasing process and would 

continue regardless of the alternative selected here. 

However, Chapter 4.9.1 (“Marine Mammals”) of the 

2017-2022 GOM Multisale EIS includes a summary of 

G&G operations and potential impacts to marine 

mammal species that may result from G&G activities. 

For a full analysis of the impacts of G&G activities in 

the Gulf of Mexico, refer to the Gulf of Mexico OCS 

Proposed Geological and Geophysical Activities: 

Western, Central, and Eastern Planning Areas—Final 

Programmatic Environmental Impact Statement

(USDOI, BOEM, 2017c).

Commercial Fisheries

Chelsea Gray CG-5 Furthermore, there is little real discussion of the 

serious economic consequences of oil spills. 

Fisheries can be destroyed, not only through the loss 

of fish, but also because consumers fear purchasing 

fish after an oil spill (even if the fish is not from the 

affected area). The economic consequences of an 

oil spill are more far reaching then the EIS implies.

Thank you for your comment. BOEM analyzes the 

impacts of oil and gas production on a number of 

important habitats, resources, and socioeconomic 

entities. For specific information on commercial 

fisheries, recreational fishing, and tourism, refer to 

Chapters 4.10, 4.11, and 4.12, respectively.

BOEM determined that, because a catastrophic event 

like the Deepwater Horizon explosion, oil spill, and 

response is not considered reasonably foreseeable as 

a result of a proposed action, the analysis should be 

removed from this Supplemental EIS to avoid 

confusion over whether it is or is not part of a 

Chelsea Gray CG-7 It is irresponsible to continue to give out any more oil 

leases, when they do not benefit the nation as a 

whole and put a profitable industry (fisheries) at great 

risk.
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-140 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

proposed action. This is allowed under CEQ’s 

regulations, which removed the requirement to 

analyze worst-case scenarios. However, in 

accordance with CEQ guidance and to inform the 

public of the potential impacts in the unlikely event of 

such a spill (though not reasonably foreseeable), 

BOEM has made this information available to the 

public through its website. BOEM also acknowledges 

that one of the key ways of managing the risk of such 

an event is to implement a rigorous regulatory regime 

to ensure that postlease drilling activities are 

conducted in a safe manner.

For a detailed analysis of reasonably foreseeable 

impacts associated with a low-probability catastrophic 

spill, such as the Deepwater Horizon explosion and oil 

spill, refer to the Catastrophic Spill Event Analysis

white paper (USDOI, BOEM, 2017a).

Land Use and Coastal Infrastructure

Alicia Cooke AC-3 As oil infrastructure ages, the costs of maintenance 

and development rises. Suncor, for example, 

currently has obligations for debts and 

decommissioning approaching $30 billion 

(http://oilprice.com/Energy/EnergyGeneral/A-Sobering-Look-At-The-Future-OfOil.html).

Thank you for your comment. For more information 

on well workovers and abandonment, refer to 

Chapter 3.1.3 of this Supplemental EIS and 

Chapter 3.1.3.5 of the 2017-2022 GOM Multisale EIS. 

For more information on pipelines and pipeline age, 

refer to Chapters 3.1.3.3.1 and 3.1.6.1 of the 2017-

2022 GOM Multisale EIS. For more information on 

decommissioning and removal, refer to Chapter 3.1.3

of this Supplemental EIS and Chapter 3.1.6 of the 

2017-2022 GOM Multisale EIS.

Gulf 

Restoration 

Network

GRN-2 The draft supplement inadequately addresses the 

risks associated with the aging infrastructure of over 

3,400 offshore rigs in the Gulf of Mexico, and the 

inevitable risk of oil spills resulting from the lease.

BOEM has also modeled oil spills and analyzed trends 

in reported spill volumes and numbers (Chapter 

3.2.1.1.1 of the 2017-2022 GOM Multisale EIS, from 

which this Supplemental EIS tiers) and reported the 

total number and volume of oil spills reported to the 

U.S. Coast Guard (USCG) from various sources, 

including barges, tankers, pipelines, and platforms. 

The analysis reported in Etkin (2009) reinforces the 

fact that hurricanes are the most common cause of 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-141

Commenter Comment ID Comment Response

spills from both platforms and pipelines, but it also 

reports that structural failures (e.g., corrosion) account 

for a significant percentage of the total volume of 

spilled oil from offshore pipelines. Preventative 

measures are taken, including inspecting pipelines at 

routine intervals and using corrosion resistant or 

corrosion-inert materials. In addition, when pipelines 

are protected by rectifiers or anodes for which the 

initial cathodic protection system either cannot be 

calculated or calculations indicate a life expectancy of 

less than 20 years, the pipelines are inspected 

annually. For more information, refer to Chapters 

3.1.6.1 (“Structure Age and Idle Iron”) and 3.2.4 

(“Pipeline Failures”) of the 2017-2022 GOM Multisale 

EIS, which is where BOEM addresses potential 

environmental hazards and impacts relating to 

pipelines.

Chris Werle CW-1 Given the past disasters with oil spills in the gulf, and 

the thousands that are currently *known* to be 

leaking, paired with the coming cuts or elimination of 

the EPA, I believe that expanded drilling operations 

presents a clear and present risk to coast 

communities and all those who depend on the gulf 

ecosystem.

The issues discussed in the following response are 

independent of the leaking wells from the Taylor 

Energy platform that was lost during Hurricane Ivan 

and which is located in Mississippi Canyon Block 20. 

For more information on the response to the Taylor 

Energy platform leak and BOEM’s analysis of this leak 

in this Supplemental EIS, please refer to the response 

to Comment GRN-7.

Refer to Chapters 3.1.3.3 and 3.1.6.1 of the 2017-

2022 GOM Multisale EIS for more information on 

infrastructure (platforms and pipelines) and 

infrastructure age. BOEM is currently unaware of any 

issues related to the decommissioning of offshore 

wells, including plugging, sealing, and abandonment. 

A review of spill data reported to both USCG and 

BSEE provides no information showing that 

abandoned wells are currently leaking.

BOEM’s analysis in this Supplemental EIS 

acknowledges the risks of accidental spills and 

June Charles JC-1 Every day there is another pipeline that leaks, a

platform that leaks oil and poisoning of our water by 

chemicals used in fracking.

Penny Dipuma PD-1 There is still oil leaking in the gulf. The oil 

companies need to fix those leaks.
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-142 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

events, even in light of the rigorous safety regulations 

in place. Accidental events are identified and 

described in Chapter 3.2. Potential impacts from 

these activities are analyzed in each resource chapter 

of Chapter 4. 

Nevertheless, BOEM acknowledges that, even with 

the stringent standards, risk is not wholly eliminated. 

For example, Table 3-17 of the 2017-2022 GOM 

Multisale EIS acknowledges that, even with 

application of these standards, certain small spills 

(≥1,000 barrels [bbl]) may be reasonably foreseeable. 

BOEM and BSEE are constantly evaluating and 

responding to potential risks through strengthening 

enforcement and inspection, and continually updating 

regulatory requirements.

Carol “Cay” 

Burton

CB-2 We had multiple leaks going unpublished and

unaddressed according to Coast Guard data and 

statistics.

Operators are required to immediately report to BSEE 

all spills of oil or other liquid pollutants that are known 

or suspected to be 1 bbl in volume or greater, per 

30 CFR § 250.187 and 30 CFR § 254.46(a). This 

requirement is in addition to, but does not substitute 

for, the National Response Center’s reporting 

requirements. Per 30 CFR § 254.46(b)(2), spills 

>50 bbl in volume require more detailed reporting and 

monitoring, and such spills trigger greater investigative 

response by BSEE, which may require the operator to 

submit additional information about the response.

Carol A. “Cay” 

Burton

CAB-2 We have multiple leaks going unpublished and 

unaddressed, according to Coast Guard data and 

statistics.

Economic Factors

Chelsea Gray CG-6 Finally, the economic benefit of yet another oil lease 

is simply not worth the potential impacts. Oil does 

not bring in enough jobs, and frequently private 

sector jobs are cut in order to make room for tax cuts 

for oil rigs (resulting in a net loss of jobs overall).

Thank you for your comment. BOEM presents data 

regarding the beneficial impacts of the alternatives in 

Chapter 4.14.2. 

BOEM is responsible for administering the leasing 

program for oil and gas resources on the OCS and for 

developing a 5-year schedule of proposed lease sales 

designed to “best meet national energy needs for the 

five-year period following [the schedule’s] 

Jackie Antalan JA-2 We also feel that there is no need for an additional 

75 million acres to be leased in that it is unjustified 

economically and socially.

Mobile MEJAC-5 While OCS drilling activities contributes significantly 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-143

Commenter Comment ID Comment Response

Environmental 

Justice Action 

Coalition 

to the federal revenue stream, it's true that recent 

lease sales haven't proven to be huge contributors. 

Taking Alternative E would not significantly diminish 

federal revenue.

approval . . .” (Section 18 of the OCSLA [43 U.S.C. § 

1344]). The 2017-2022 Five-Year Program is an 

important component of the President’s 

comprehensive energy strategy to allow for safe and 

responsible domestic oil and natural gas production as 

a means to support economic growth and job creation, 

and enhance energy security.

In addition, the OCSLA grants the Secretary of the 

Interior the authority to issue leases on the OCS. 

Section 18(a)(4) of the OCSLA states that “Leasing 

activities shall be conducted to assure receipt of fair 

market value for the lands leased and the rights 

conveyed by the Federal Government.” Lessees pay 

bonuses, rentals, and royalties reflecting the value of 

the rights to explore and potentially develop and 

produce OCS oil and gas resources. BOEM sets 

minimum bid levels, rental rates, and royalty rates by 

individual lease sale based on its assessment of 

market and resource conditions as the proposed 

regionwide lease sale approaches.

A description of the revenue generated from offshore 

oil- and gas-related activities is described in Chapter 

4.14.2.1 of the 2017-2022 GOM Multisale EIS. When 

the lease is acquired, a bonus bid is paid. The bonus 

bid is the winning highest dollar amount paid at the 

time of the lease sale. This acquisition cost reflects 

the opportunity cost of exploring and producing those 

mineral resources. During the initial term of a lease 

and before royalty on production is paid, the lessee 

pays annual rentals in an amount prescribed in the 

Final Notice of Sale. Rentals reflect the holding cost 

of the lease during the initial term prior to production in 

paying quantities. In recent lease sales, BOEM has 

imposed rentals that escalate over time to encourage 

faster exploration and development of leases. The 

Government receives a royalty payment once 

Jean Publeee JP-2 THE AMERICAN TAXPAYERS GET ZERO MONEY 

FROM THESE LEASES AND IT IS ALL SUCKED 

AWAY BY OUIR FAT CAT SWAMP 

BUREAUCRATS SO THEY GIVE THE AMERICAN 

TAXPAYERS NO HELP SO THERE IS NO REASON 

TO CONTINUALLY DESTROY THE GULF OF 

MEXICO.

Jean Publeee JP-4 THIS PLOT TO ALLOW RICH WHITE MEN PALS 

OF OUR CORRUPT GOVT TO MAKE BIG MONEY 

THROUGH THIS ENDLESS DESTRUCTION OF 

THIS LAND IN THE OCEAN WHICH BELONGS TO 

325 MILLION PEOPLE IS SAD AND SHOWS A US 

GOVT WHICH CAN BE BOUGHT. ALL OF THE 

PEOPLE IN THIS COUNTRY ARE CLAMORING TO 

STOP THE TOTAL DESTRUCTION OF LANDS 

OWNED BY ALL OF THEM - THOSE 325 MILLION 

PEOPLS AND THE CORRUPT GANG IN 

WSHINGTON DC KEEPS DESTROYING THE 

PUBLIC LAND. THE LAW CALLED THE POUBLIC 

TRUST IS EXTREMELY IGNORED AND BULLIED 

BY THIS CORRUPT GANG IN WASHINGTON DC. 

WE WANT THIS DESRUCTION OF THE GULF TO 

STOP. NOW. THIS PLAN SUCKS.
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-144 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

production starts. The royalty rate is a percentage of 

production. The royalty rate is used to calculate the 

royalty payment, i.e., the dollar amount paid based on 

the value of the amount of production. Under certain 

conditions, the royalty payment might be temporarily 

waived. Known as royalty relief, this generally occurs 

when an economic incentive is needed to spur 

additional production, such as in a frontier area or 

deeper water depth. Price thresholds or triggers 

suspend royalty payments if market prices are low but 

do not suspend royalty payments if market prices are 

high. Price thresholds provide an incentive when 

production might not otherwise occur. Additionally, 

they provide protection when market prices are high 

and the incentive is no longer needed.

Revenues from OCS leases consist of bonuses, 

royalties, and rentals and are collected by the Office of 

Natural Resources Revenue. These revenues are 

shared with coastal states, as directed by statute, and 

the remaining funds are deposited in the U.S. 

Treasury. The OCS revenues provide annual 

deposits of nearly $900 million to the Land and Water 

Conservation Fund and $150 million to the Historical 

Preservation Fund. By statute, coastal states share a 

portion of the revenues from OCS leasing and 

production under three programs: (1) the OCSLA’s 

Section 8(g) revenue sharing program, which provides 

that states with offshore Federal leases located within 

the first 3 mi (5 km) of the State’s seaward boundary 

receive 27% of the revenue generated from those 

leases; (2) the Coastal Impact Assistance Program 

(CIAP) for Alaska, Alabama, California, Louisiana, 

Mississippi, and Texas; and (3) the Gulf of Mexico 

Energy Security Act (GOMESA) for Alabama, 

Louisiana, Mississippi, and Texas.

For more information on OCS oil and gas leasing, 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-145

Commenter Comment ID Comment Response

refer to BOEM’s leasing fact sheet (USDOI, BOEM, 

2016c).

Social Factors (Including Environmental Justice)

Center for 

Biological 

Diversity, 

Sierra Club, 

Gulf 

Restoration 

Network,

Louisiana 

Bucket 

Brigade

CBD,SC,GRN,

LBB-13

The Bureau’s determination that lease sales do not 

disproportionately impact communities of color is 

premised on a flawed assumption that there’s no 

appreciable difference because there’s so much 

cumulative harm from oil and gas activities in the 

Gulf. Specifically, the Bureau said the harmful 

impacts of the lease sale on environmental justice "is 

like a blip on a radar screen" for Gulf communities 

already inundated by prior oil and gas activities, 

infrastructure, and pollution.

The industry is dangerous for workers and the 

welfare of people of color. The risk of fatality for 

offshore oil workers is seven times higher than the 

national average. And the industry harms public 

health with pollution and neighborhood blight from 

onshore oil infrastructure, including refineries. 

Refineries and other petroleum facilities in Alabama, 

Louisiana, Mississippi, and Texas reported 

422.98 million pounds of toxic chemical releases 

between 2004 and 2014, the majority of that was air 

pollution followed by water discharges. Some of the 

most commonly released hazardous chemicals 

included xylene, cyanide, and toluene that are toxic 

to humans and harm the human nervous system, 

among other effects. Toxic pollution from these 

refineries and petrochemical facilities 

disproportionately impact low income neighborhoods, 

indigenous and communities of color. For example, 

Port Arthur, Texas is home to two facilities that refine 

more than 900,000 barrels of crude per day. The 

Environmental Protection Agency’s Toxics Release 

Inventory places Jefferson County, where Port Arthur 

is located, among the worst in the nation for 

emissions of chemicals known to cause cancer, birth 

The proposed Federal action being analyzed in this 

Supplemental EIS is to offer for lease those areas that 

may contain economically recoverable oil and gas 

resources in accordance with the OCSLA, which 

specifically states that these resources “should be 

made available for expeditious and orderly 

development, subject to environmental safeguards” 

(OCSLA, 43 U.S.C. §§ 1331 et seq.). The purpose of 

this Supplemental EIS is to evaluate the direct and 

indirect effects of a proposed action (i.e., a proposed 

regionwide lease sale) as well as the incremental 

contribution of a proposed regionwide lease sale to 

the cumulative effects. A low-probability catastrophic 

oil spill is not reasonably foreseeable, not part of the 

proposed action, and therefore is not included in this 

analysis. A detailed analysis of reasonably 

foreseeable impacts associated with a low-probability 

catastrophic spill is available in the Catastrophic Spill 

Event Analysis white paper (USDOI, BOEM, 2017a).

BOEM acknowledges that there could be impacts from 

onshore infrastructure supporting oil and gas activities 

on the OCS, whether through development and 

production or through refining onshore. Refer to 

Chapters 4.14.1 and 4.14.3 for a discussion of 

indirect impacts to land use and coastal infrastructure 

and social factors (including discussion of 

environmental justice communities and an 

environmental justice determination). Refer to 

Chapter 4.1 for the air quality analysis. Oil and gas 

from the OCS represent only a fraction of what is 

transported or refined onshore, and BOEM does not 

have the authority to regulate or permit onshore 

infrastructure, facilities, or activities that contribute to 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-146 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

defects, and reproductive disorders. Data collected 

by the Texas Cancer Registry indicates that cancer 

rates among African Americans in Jefferson County 

are roughly 15% higher than they are for the average 

Texan, and the mortality rate from cancer is more 

than 40% higher.

pollution.

Employment in OCS-related industries is complex and 

variable. BOEM recognizes this complexity; refer to 

Chapter 4.14.3 of this Supplemental EIS for a 

summary of this topic and Chapter 4.14.3 of the 

2017-2022 GOM Multisale EIS for a full discussion of 

this topic.

Peter Shrock PS-6 BOEM improperly dismisses air pollution that 

resulting from the proposed lease on Gulf

communities because there is already significant 

Outer Continental Shelf (OCS) – related 

infrastructure in Gulf States. This approach 

undercuts the entire purpose of a cumulative impacts 

analysis and efforts to inform and engage 

environmental justice communities, in violation of 

NEPA.

Mobile 

Environmental 

Justice Action 

Coalition 

MEJAC-2 What Gulf residents deserve is a sober quantification 

of the potential impacts from the refining of OCS 

minerals in Gulf refineries. An analysis of this nature 

should include particulate matter, heavy metals, and 

polycyclic aromatic hydrocarbons quantification in 

addition to photochemical smog components. It is 

impossible to even being to properly consider the 

environmental justice and human health impacts 

without this elementary data. Also included in this 

data should be the amount of hazardous vapors 

released in routine storage and transport of product 

with an OCS origin.

Sierra Club SC-5 Oil spills and air pollution from offshore drilling and 

industrial facilities like refineries that support the 

industry make people sick and disproportionately 

harm low-income neighborhoods and communities of 

color. But BOEM fails to adequately analyze the 

environmental justice impacts of its proposal.

Gulf 

Restoration 

Network

GRN-14 Climate change negatively impacts all of us, but 

communities on the front line of fossil fuel 

development in the Gulf of Mexico - most often 

people of color - have had to shoulder that burden 

BOEM analyzes and considers many facets of the 

potential effects of climate change in its 

decisionmaking with respect to oil and gas leasing, 

whether in the Five-Year Program or lease sale 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-147

Commenter Comment ID Comment Response

disproportionately. Each step of fossil fuel 

development - extraction, transportation, refining, 

and burning - directly threatens the health and wellbeing of communities across the Gulf. It is time to 

stop treating the Gulf as a sacrifice zone for the fossil 

fuel industry, and halt new offshore drilling.

analyses. This Supplemental EIS tiers from the 

2017-2022 GOM Multisale EIS, which tiers from the 

2017-2022 Five-Year Program EIS. Chapter 4.0 of 

the 2017-2022 GOM Multisale EIS has a summary of 

the greenhouse gas and downstream emissions 

information that may result from a Gulf of Mexico oil 

and gas lease sale.

BOEM acknowledges that methods for quantifying 

greenhouse gas and potential social costs of such 

emissions are subject to continual improvement. 

BOEM continues to consider different ways to 

quantitatively address and disclose downstream 

greenhouse gas emissions and effects, and will 

update its analysis as warranted.

Topic 5 – Cumulative Analysis

Chelsea Gray CG-3 The EIS also seems to ignore the cumulative effects 

of multiple oil drills/spills in a region, and acts as if 

the area in question in isolated. There should be a 

discussion on what happens if multiple spills happen 

in the gulf at the same time, both minor and major.

Chapter 4 of this Supplemental EIS summarizes the 

effects of oil spills to each of the identified resources. 

Refer to Chapter 4 of the 2017-2022 GOM Multisale 

EIS for detailed analyses on the effects of oil spills to 

each of the identified resources. In addition, 

Chapter 3.2 of this Supplemental EIS summarizes oil 

spills, while Chapter 3.2 of the 2017-2022 GOM 

Multisale EIS provides a full analysis of past trends in 

reported spill volumes and numbers, showing that the 

majority of offshore spills are <1 bbl and result in only 

negligible and minor impacts to resources.

While the occurrence of multiple spills of significance 

is low, the ability to respond to those spills is 

supported by the multiple staging areas for oil-spill 

response equipment across the GOM. For a 

discussion of the spill-response requirements, as well 

as the variety of methods employed, refer to 

Chapter 3.2.8 of the 2017-2022 GOM Multisale EIS.

David Quist DQ-2 The proposed EIS erroneously focuses on 

incremental impacts rather than cumulative impact, 

Thank you for your comment. This Supplemental EIS 

includes analysis of both the incremental impact of a 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-148 2018 Gulf of Mexico Supplemental EIS

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fails to acknowledge localized impacts, and fails to 

provide an impact assessment recognizing local as 

well as regional impacts.

single proposed regionwide lease sale and the 

cumulative impacts of the OCS Oil and Gas Program, 

as well as the cumulative impacts of non-OCS oil- and 

gas-related activities in the Gulf of Mexico. Refer to 

each resource summary in Chapter 4 of this 

Supplemental EIS for impact analyses. For a full 

analysis on each resource, refer to Chapter 4 of the 

2017-2022 GOM Multisale EIS.

The geographic scale of analysis varies depending on 

the stage of the leasing process. The OCSLA 

requires a staged decisionmaking process beginning 

with the Five-Year Program, continuing through 

individual proposed regionwide lease sales under the 

Five-Year Program, and ultimately to individual 

postlease activities requiring a permit or approval. As 

stated in Chapters 1 and 2, this Supplemental EIS 

discusses a single proposed oil and gas lease sale, as 

scheduled under the 2017-2022 Five-Year Program. 

This approach is intended to focus the NEPA/EIS 

process on the staged OCSLA process for 

decisionmaking, including the proposed regionwide 

lease sales and any new issues and information 

identified since a prior stage. It also lessens 

duplication and saves resources when BOEM and 

BSEE conduct postlease reviews.

Additionally, the issuance of leases does not conclude 

the environmental analysis of planned OCS oil- and 

gas-related activities. Each plan throughout the 

exploration, production, and decommissioning 

processes receives a site-specific environmental 

analysis pursuant to NEPA and the OCSLA’s 

pyramidal structure going from large scale to site 

specific. For more information on BOEM’s postlease 

processes, refer to Appendix A of the 2017-2022 

GOM Multisale EIS.

Lorie Chinn LC-5 The study shows that one lease won’t effect much, 

but multiple leases has a major effect.
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-149

Commenter Comment ID Comment Response

Peter Shrock PS-12 The EIS does not consider connected, cumulative or 

similar actions and their indirect or cumulative 

impacts; the suggestion that these only need to be 

considered every 5 years is a violation of NEPA.

Thank you for your comment. As part of the 

cumulative analysis, BOEM considers both connected 

and similar actions. Cumulative impacts of the OCS 

Oil and Gas Program, as well as the cumulative 

impacts of non-OCS oil and gas activities in the Gulf 

of Mexico, are considered. Refer to each resource 

summary in Chapter 4 of this Supplemental EIS for 

impact analyses. For a full analysis on each resource, 

refer to Chapter 4 of the 2017-2022 GOM Multisale 

EIS.

The OCSLA provides the Congressional mandate for 

BOEM to make “available for expeditious and orderly 

development, subject to environmental safeguards, in 

a manner which is consistent with the maintenance of 

competition and other national needs” the land of the 

Federal OCS. The Secretary of the Interior oversees 

the OCS Oil and Gas Program and is required to 

balance orderly resource development with protection 

of the human, marine, and coastal environments while 

simultaneously ensuring that the public receives an 

equitable return for these resources and that 

free-market competition is maintained. It is during this 

national-level review that the location (GOM 

regionwide leasing) and timing of lease sales (number 

of lease sales per year) is set in the schedule of 

proposed regionwide lease sales.

The 2017-2022 Five-Year Program EIS analyzes the 

environmental impacts of the entire 10 lease sale 

program in the Gulf of Mexico. The regional-level 

NEPA analysis covered in the 2017-2022 GOM 

Multisale EIS and this Supplemental EIS provide a 

regional-level analysis of the environmental impacts of 

a single proposed regionwide lease sale in the 

2017-2022 Five-Year Program. A NEPA analysis 

must be conducted for each proposed regionwide 

lease sale in the Five-Year Program. This 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-150 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

Supplemental EIS tiers from the 2017-2022 Five-Year 

Program EIS and 2017-2022 GOM Multisale EIS, and 

incorporates the analyses (including connected and 

cumulative analyses) into this Supplemental EIS by 

reference. The decision on whether or how to 

proceed with each proposed regionwide lease sale is 

under the authority of the Assistant Secretary for Land 

and Minerals Management and will be disclosed in the 

Record of Decision following the NEPA analysis for 

each proposed regionwide lease sale.

Topic 6 – Oil Spills

David Quist DQ-8 - increased drilling = increased risk of spills. If 

Deepwater Horizon taught anything, it's that the 

impacts on water quality, shoreline, beaches, dunes, 

estuarine ecosystems, and marine ecology and 

wildlife are severe. The Gulf still hasn't recovered 

from that one spill event.

BOEM is concerned about the potential impacts of oil 

spills on the environment. In this Supplemental EIS, 

OCS oil- and gas-related oil spills are analyzed under 

“Accidental Events,” and other spills (e.g., in State 

waters or from other sources on the OCS) are 

analyzed under “Cumulative Impacts” for all relevant 

resources. As impacts from the Deepwater Horizon

explosion, oil spill, and response continue to be 

assessed, additional analyses will be completed at the 

site-specific approval stage and in future NEPA 

documents.

BOEM understands that the Deepwater Horizon

explosion, oil spill, and response had impacts on the 

Gulf of Mexico. However, the Deepwater Horizon

explosion and oil spill was a catastrophic event, and a 

catastrophic oil spill is not part of a proposed action 

nor is it considered likely to occur. The return period 

of a catastrophic oil spill on OCS areas is estimated to 

be 165 years, with a 95% confidence interval between 

41 years and more than 500 years (Ji et al., 2014). 

BOEM determined that, because a catastrophic event 

like the Deepwater Horizon explosion, oil spill, and 

response is not considered reasonably foreseeable as 

a result of a proposed action, the analysis should not 

be overly emphasized in this Supplemental EIS to 

avoid confusion over whether it is or is not part of a 

Maggi Roberts MaRo-4 We are still recovering from the Oil Spill that 

devastated the Fishing and Tourist Industries on the 

Gulf Coast. We all know the impact and 

consequences of drilling in the Gulf that the Deep 

Horizon incident had.

Gulf 

Restoration 

Network

GRN-1 Seven years after the Deepwater Horizon spill, 

hundreds of miles of coastal habitat, sea turtles, sea 

birds, dolphins, and other wildlife in the Gulf of 

Mexico are still suffering. Key fishing grounds have 

still not recovered.
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-151

Commenter Comment ID Comment Response

proposed action. This is allowed under CEQ’s 

regulations that removed the requirement to analyze 

worst-case scenarios. For a detailed analysis of 

reasonably foreseeable impacts associated with a 

low-probability catastrophic spill, such as the 

Deepwater Horizon explosion and oil spill, refer to the 

Catastrophic Spill Event Analysis white paper (USDOI, 

BOEM, 2017a).

The Natural Resource Damage Assessment studies 

are ongoing, but the Trustees’ PDARP/PEIS has been 

released and analyzed for relevant information. With 

the release of the Trustees’ PDARP/PEIS, our 

understanding of the environmental impacts of the 

Deepwater Horizon explosion, oil spill, and response 

has greatly increased; however, there are many 

ongoing long-term and monitoring studies that are not 

complete. Therefore, our understanding of the lasting 

effects or long-term recovery of the system is still 

incomplete and has data gaps, but the information is 

not essential to a reasoned choice among 

alternatives.

Current baselines are described for all resources 

under their respective “Description of the Affected 

Environment” chapters in the 2017-2022 GOM 

Multisale EIS, from which this Supplemental EIS tiers. 

Specific to the Trustees’ PDARP/PEIS (Deepwater 

Horizon Natural Resource Damage Assessment 

Trustees, 2016), the altered baseline in this 

Supplemental EIS already includes individual 

protected species directly affected by this unexpected 

unique catastrophic event. The injuries assessed 

within the PDARP/PEIS do not necessarily equate the 

baseline as defined in NEPA, but they were 

considered when determining the baseline for our 

impact determinations.
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-152 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

Where gaps remained, BOEM’s subject-matter 

experts exercised their best professional judgment to 

extrapolate baseline conditions and impact analyses 

using accepted methodologies based on credible 

information. BOEM’s subject-matter experts have 

applied other scientifically credible information using 

accepted theoretical approaches and research 

methods, such as information on related or surrogate 

species. Moreover, BOEM will continue to monitor 

these resources for effects caused by the Deepwater 

Horizon explosion, oil spill, and response, and will 

ensure that future BOEM environmental reviews take 

into account any new information that may emerge.

BOEM considers a key to managing risk is through 

implementing a rigorous regulatory regime to ensure 

that postlease drilling activities are conducted in a 

safe manner. Refer to Appendix A of the 2017-2022 

GOM Multisale EIS for information on BOEM’s and 

BSEE’s rigorous postlease processes.

Safety measures and technologies have increased 

since the Deepwater Horizon oil spill. A fact sheet on 

research and regulatory reforms can be found on 

BOEM’s website at http://www.boem.gov/2017-2022-

GOM-Multisale-Public-Meeting-Handouts-Visuals/.

Sierra Club SC-4 Similarly, BOEM must analyze the impacts of 

another catastrophic oil spill.

BOEM has analyzed the impacts of a catastrophic oil 

spill. BOEM determined that, because a catastrophic 

event like the Deepwater Horizon explosion, oil spill, 

and response is not considered reasonably 

foreseeable as a result of a proposed action, the 

analysis should not be overly emphasized in this 

Supplemental EIS to avoid confusion over whether it 

is or is not part of a proposed action. This is allowed 

under CEQ’s regulations that removed the 

requirement to analyze worst-case scenarios. For a 

detailed analysis of reasonably foreseeable impacts 

Rebecca King RK-1 I would like to know how BOEM addressed the 

catastrophic BP spill. This EIS is based on smaller 

more common spills, however it only takes one spill 

like the Deepwater Horizon to cause damage that 

lasts for years or possibly decades.

Eli Lamb EL-3 Additionally, the recent (and still not fully 

ameliorated) BP oil spill still demonstrates that an 

agency responsible for management (BOEM) must 

consider outlying negative outcomes even more 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-153

Commenter Comment ID Comment Response

seriously than the statistically certain ones. 

Otherwise its role is obsolete, and we could trust to 

the “common sense” propaganda of the oil 

companies themselves. Remember, if you align your 

motives too closely with those you are supposed to 

oversee, they will eventually decide you are an 

unnecessary burden to their bottom line – and they 

will be correct.

associated with a low-probability catastrophic spill, 

such as the Deepwater Horizon explosion and oil spill, 

refer to the Catastrophic Spill Event Analysis white 

paper (USDOI, BOEM, 2017a).

Susan Prerost SP-1 I ask BOEM to reconsider implementation of 250. 

The incredibly detailed analysis is limited re: future 

catastrophic events such as the BP oil spill. There is 

no way to know how devastating – to our already 

fragile ecosystem – another unstoppable surge 

would be to our estuary. The analysis is finite as is 

our estuary, culture, biodiversity.

Lorie Chinn LC-4 The impact of a major catastrophe happening again 

out in this Gulf would have an even greater lasting 

effect on the environment.

Rebecca King RK-3 Has BOEM considered that people in Grand Isle are 

still getting cancer at much higher rates since the 

spill?

The proposed action in this Supplemental EIS is to 

hold a regionwide lease sale in the GOM according to 

the schedule of proposed regionwide lease sales set 

forth by the 2017-2022 Five-Year Program. The 

purpose of the proposed regionwide lease sale 

analyzed in this Supplemental EIS is to offer for lease 

those areas in the Gulf of Mexico (GOM) that may 

contain economically recoverable oil and gas 

resources in accordance with the OCSLA, subject to 

environmental safeguards in order to further the 

orderly development of OCS oil and gas resources. 

BOEM acknowledges that there could be impacts from 

the proposed action on coastal communities (as 

discussed in Chapter 4.14.3), but a low-probability 

catastrophic oil spill is not reasonably foreseeable, not 

part of the proposed action, and therefore is not 

included in this analysis.

BOEM acknowledges that a low-probability 

catastrophic spill, such as the Deepwater Horizon
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-154 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

explosion and oil spill, may cause impacts to coastal 

communities, including health impacts. A detailed 

analysis of reasonably foreseeable impacts 

associated with a low-probability catastrophic spill is 

available in the Catastrophic Spill Event Analysis

white paper (USDOI, BOEM, 2017a).

BOEM has revisited the baseline description for the 

social factors chapter and does not agree that enough 

evidence exists yet to conclusively determine that the 

Deepwater Horizon explosion, oil spill, and response 

has changed the baseline conditions for evaluating the 

impact of a lease sale. BOEM has identified 

unavailable information that is relevant to people and 

communities regarding the impacts of the Deepwater 

Horizon explosion, oil spill, and response. This 

information cannot be obtained because long-term 

health impact studies, subsistence studies, and the 

Natural Resource Damage Assessment restoration 

process are ongoing and because data from these 

efforts would be unavailable and unobtainable for 

some time. In order to fill this data gap, BOEM has 

used existing information and reasonably accepted 

scientific methodologies to extrapolate from available 

information in completing the relevant analysis, 

including information that has been released after the 

Deepwater Horizon explosion, oil spill, and response 

and studies of past oil spills, which indicate that a lowprobability, catastrophic oil spill, which is not part of a 

proposed lease sale and not likely or expected to 

occur, may have adverse impacts on residents in 

GOM coastal communities. Research into possible 

long-term health impacts of the Deepwater Horizon 

explosion, oil spill, and response continues (National 

Institute of Environmental Health Science, 2014; 

National Center for Disease Preparedness, 2013 and 

2014; Substance Abuse and Mental Health Services 

Administration and Centers for Disease Control and 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-155

Commenter Comment ID Comment Response

Prevention, 2013). Because long-term health impacts 

to coastal populations are unknown, this information 

may be relevant to the evaluation of impacts from the 

Deepwater Horizon explosion, oil spill, and response; 

therefore, BOEM continues to seek additional 

information as it becomes available and bases the 

previous analysis on the best information currently 

available. Although long-term health impacts to 

people and communities may be relevant to this 

analysis, BOEM has determined that the unavailable 

information is not essential to a reasoned choice 

among alternatives based on the information 

discussed above.

Some additional clarifying language and references 

are provided in the social factors chapter of the 2017-

2022 GOM Multisale EIS’s baseline descriptions and 

cumulative impacts analysis. Because health studies 

and other research are ongoing, BOEM is monitoring 

the results and will revise the analysis if warranted.

Rebecca King RK-4 Has this EIS considered BP oil just showed up in 

sparrows this past year so it in the food chain.

This Supplemental EIS has been updated to include 

this new information. Refer to Chapter 4.8 for this 

information.

Rebecca King RK-5 Much of the oil is still on the bottom of the Gulf. Thank you for your comment. Current baselines are 

summarized in this Supplemental EIS and described 

in detail for all resources under their respective 

“Description of the Affected Environment” chapters in 

the 2017-2022 GOM Multisale EIS. BOEM has 

included information from the Trustees’ PDARP/PEIS 

(Deepwater Horizon Natural Resource Damage 

Assessment Trustees, 2016) for the altered baseline 

affected by this unexpected, unique catastrophic 

event. BOEM acknowledges that there is some 

lingering uncertainty regarding the impacts of the 

Deepwater Horizon oil spill. However, this uncertainty 

has diminished as time passes and as new data and 

studies have become available. In addition, BOEM 

has complied with NEPA procedures for dealing with 

Bill McBride BM-1 There exists a case study in why there should be no 

drilling in the Gulf of Mexico, the 2010 Deepwater 

Horizon blowout that killed 11 people and countless 

wildlife in the Gulf ecosystem. From all reports the 

bottom of the Gulf remains blanketed in oil.

Alan 

Ackerman

AA-1 NOW THEY FINDING 10 MILLION GALLON TAR 

MAT ON GULF BOTTOM ???

Judith Shields JuSh-1 An enormous mat of oil still lies in the Gulf. Big Oil 

wants to risk that again. 

http://www.cbsnews.com/news/oil-2-inches-thickfound-on-gulf-sea-floor/
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-156 2018 Gulf of Mexico Supplemental EIS

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incomplete or unavailable information.

Anonymous ANON-1 I was born and raised in Pensacola, Florida and have 

now retired back to the area. I enjoyed the beaches 

and local waters growing up in Northwest Florida. 

That is one of the primary reasons for returning here 

in retirement. Over the years, I have been 

disappointed to see the Gulf of Mexico become an 

“oil field” with platforms dotting the once clear waters. 

I recognize the need for energy as well as other 

products that come from oil such is synthetic 

materials. However, my major concern is the human 

factor in farther development in the Gulf (actually, 

any offshore drilling). Please consider the following 

accidents: 

1) The Exxon Valdez oil spill occurred in Prince 

William Sound, Alaska, March 24, 1989, when Exxon 

Valdez, an oil tanker owned by Exxon Shipping 

Company, bound for Long Beach, California, struck 

Prince William Sound's Bligh Reef at 12:04 am local 

time and spilled approximately 10.8 million US 

gallons of crude oil over the next few days. 

2) Ixtoc I was an exploratory oil well being drilled by 

the semi-submersible drilling rig Sedco 135-F in the 

Bay of Campeche of the Gulf of Mexico, about 

62 miles northwest of Ciudad del Carmen, 

Campeche in waters 160 ft deep. On 3 June 1979, 

the well suffered a blowout resulting in one of the 

largest oil spills, in history (to that date).

3) The Deepwater Horizon oil spill (aka BP oil spill, 

BP oil disaster, the Gulf of Mexico oil spill, and the 

Macondo blowout) began on April 20, 2010, in the 

Gulf of Mexico on the BP-operated Macondo 

Prospect. Eleven people went missing and were 

never found and it is considered the largest 

accidental marine oil spill in the history of the 

The Six Sigma approach to managing quality is not 

used to evaluate oil- and gas-related incident rates; 

however, BSEE monitors incident statistics including, 

but not limited to, injuries, losses of well control, and 

fires and explosions, which can be found on BSEE’s 

website at https://www.bsee.gov/stats-facts/offshoreincident-statistics. The BSEE uses the results of 

incident investigations and data analysis to identify 

incident causes and trends. Appropriate actions are 

then identified to prevent the recurrence of these 

incidents and to enhance safety and environmental 

protection on the OCS. These actions may include 

publishing Safety Alerts, initiating technical research, 

developing new/revised regulations or standards, 

changing inspection strategies, holding safety 

workshops, etc. Incident data are also used to 

calculate performance indicators.

On April 17, 2006, MMS published a Final Rule 

(Federal Register, 2006) that revised the agency's 

incident reporting requirements. The new Incident 

Reporting Rule more clearly defines which incidents 

must be reported, broadens the scope to include 

incidents that have the potential to be serious, and 

requires the reporting of standard information for both 

oral and written reports. This has resulted in more 

consistent incident reporting and the collection of 

more reliable incident information. Prevention of 

future undesirable incidents on the OCS is a 

paramount goal of both industry and MMS. For more 

information on incident reporting, refer to BSEE’s 

website at https://www.bsee.gov/resourcestools/incident-reporting. This information is 

considered in the “Accidental Events” section in 

Chapter 3.2. 

In addition, a BOEM/BSEE-sponsored study entitled 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-157

Commenter Comment ID Comment Response

petroleum industry, an estimated 8% to 31% larger in 

volume than the previously largest, the Ixtoc I oil 

spill. The US Government estimated the total 

discharge at 210 million US gallons. After several 

failed efforts to contain the flow, the well was 

declared sealed on September 19, 2010. Reports in 

early 2012 indicated the well site was still leaking. 

Please ask your engineers to provide calculations for 

mean time between failures and other failure rate 

data before making a decision that could affect the 

environment of the Gulf of Mexico for future 

generations. Please consider this from the Six 

Sigma approach to managing quality. The scale 

shows how well a vital feature performs compared to 

its requirements. The higher the sigma score, the 

more efficient the feature is:

Sigma 

Level

Defects per Million 

Opportunities 

(DPMO)

Percent of 

Defects 

(%)

Percent of 

Successes 

(Yield %)

Capability 

(CP)

1 691,462 69 31 0.33

2 308,538 31 69 0.67

3 66,807 6.7 93.3 1.00

4 6,210 0.62 99.38 1.33

5 233 0.023 99.977 1.67

6 3.4 0.00034 99.99966 2.00

Human error is inevitable, so even if the developer 

achieves Six Sigma Level 6 (the highest level) there 

is still a predictable error rate that could result in 

another disaster. Please refrain from permitting 

additional offshore production platforms.

“2016 Update of Occurrence Rates for Offshore Oil 

Spills,” recently updated the previous work presented 

in Anderson et al. (2012). While this update includes 

oil spills reported through 2015, it also examines 

causal factors associated with each individual spill. 

The information in Anderson et al. (2012) can be 

found in the 2017-2022 GOM Multisale EIS and is 

incorporated by reference into this Supplemental EIS, 

which tiers from the 2017-2022 GOM Multisale EIS. 

While there will always be incomplete or unavailable 

information regarding offshore spills that could 

conceivably result in potential future shifts in baseline 

conditions and affect BOEM’s decisionmaking, BOEM 

has determined that it can make an informed decision 

on a proposed regionwide lease sale using the most 

recent spill information provided by ABS Consulting, 

Inc. (2016). Through the tiered NEPA process for oil 

and gas leasing, future BOEM environmental reviews 

can take into account any new information that may 

emerge.

Ryan Bowman RB-4 Having more offshore drilling sites increases the

probability of another catastrophic oil spill. The risk 

of such a catastrophe far outweighs the potential 

temporary benefits of opening new sites.
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-158 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

Peter Shrock PS-1 The Bureau of Ocean Energy Management's 

(BOEM) analysis of threats to the environment is 

inadequate. BOEM's oil spill analysis, for example, 

vastly understates the damage to the environment 

and wildlife and risk of oil spills. It ignores the reality 

that transporting oil and gas is inherently dangerous 

and spills occur routinely in offshore oil and gas 

operations from both tankers and pipelines.

BOEM’s analysis of oil-spill risk, which is summarized 

in Chapter 3.2 of this Supplemental EIS and 

discussed in detail in Chapter 3.2.1 of the 2017-2022 

GOM Multisale EIS, includes detailed discussions of 

offshore spills <1,000 bbl and ≥1,000 bbl, and coastal 

spills. As described in Chapter 3.2.1.4.2 (“Trajectory 

Modeling for Offshore Spills ≥1,000 bbl”) of the 

2017-2022 GOM Multisale EIS, the Bureau of Ocean 

Energy Management’s OSRA model simulates the 

trajectory of thousands of spills throughout the Gulf of 

Mexico OCS and calculates the probability of these 

spills being transported and contacting specified 

geographic areas and features. Using these 

assumptions, BOEM’s subject-matter experts then 

evaluated the potential impacts to resources in the 

Gulf of Mexico. While there is always some 

professional judgment that must be used when 

developing forecasts for a scenario and the potential 

resulting impacts, BOEM believes this is a reasonable 

approach and that it would tend to be conservative 

and to probably overestimate impacts rather than 

underestimate them.

BOEM has summarized oil and gas transport, safety 

requirements, and accidents from both tankers and 

pipelines in Chapter 3.2.4 of this Supplemental EIS. 

Pipeline failures are discussed in detail in Chapter 

3.2.4 of the 2017-2022 GOM Multisale EIS. Oil 

tankers and their safety requirements are discussed in 

detail in Chapter 3.1.4.2 of the 2017-2022 GOM 

Multisale EIS, and vessel collisions are discussed in 

Chapter 3.2.5 of the 2017-2022 GOM Multisale EIS.

350 Louisiana 

- New Orleans

350LANO-3 What is the estimated amount of oil spilled/ leaked 

into the GOM annually associated with oil 

production?

Chapter 3.2 of this Supplemental EIS summarizes 

and Chapter 3.2.1.1.1 (“Trends in Reported Spill 

Volumes and Numbers") of the 2017-2022 GOM 

Multisale EIS reports the total number and volume of 

oil spills reported to USCG from various sources, 

including barges, tankers, pipelines, and platforms. 

Gulf 

Restoration 

Network

GRN-3 BOEM cannot permit more drilling when it does not 

know the rolling sheen size of the thousands of spills 

that routinely cover the Gulf.
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-159

Commenter Comment ID Comment Response

Historical data on oil spills from 2001 through 2015, 

including the number of spills and volume of spills 

each year, is shown in Table 3-11 of the 2017-2022 

GOM Multisale EIS. Tables 3-10, 3-11, and 3-12 of 

this Supplemental EIS show estimated spill data for an 

individual lease sale and the cumulative OCS Oil and 

Gas Program. The analysis reported in Etkin (2009) 

reinforces the fact that hurricanes are the most 

common cause of spills from both platforms and 

pipelines; it also reports that structural failures (e.g., 

corrosion) account for a significant percentage of the 

total volume of spilled oil from offshore pipelines. 

Preventative measures are taken, including inspecting 

pipelines at routine intervals and using corrosion 

resistant or corrosion-inert materials. In addition, 

when pipelines are protected by rectifiers or anodes 

for which the initial cathodic protection system either 

cannot be calculated or calculations indicate a life 

expectancy of less than 20 years, the pipelines are 

inspected annually. Also, refer to Chapter 3.1.6.1 

(“Structure Age and Idle Iron”) and Chapter 3.2.4 

(“Pipeline Failures”) of the 2017-2022 GOM Multisale 

EIS, which is where BOEM addresses potential 

environmental hazards and impacts relating to 

pipelines.

In addition, natural oil seeps are geographically 

common and have likely been active throughout 

history. Natural seeps have been estimated to 

account for approximately 47% of the crude oil 

entering the marine environment (Kvenvolden and 

Cooper, 2003). For more information on seeps in 

comparison to other petroleum inputs to Gulf of 

Mexico waters, refer to Table 3-29 and Chapter 

3.3.2.9.2 of the 2017-2022 GOM Multisale EIS.

The impacts of oil spills are summarized for each 

resource in Chapter 4 of this Supplemental EIS and 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-160 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

analyzed in detail in Chapter 4 of the 2017-2022 GOM 

Multisale EIS.

Gulf 

Restoration 

Network

GRN-6 These spills represent much more oil than natural 

seeps, and represent a different chemistry than 

natural seeps. BOEM cannot claim that the 

ecosystem has adapted to cope with accidental spills 

because of the differences in density and chemistry 

between natural seeps and crude oil spills.

As discussed in the 2017-2022 GOM Multisale EIS, 

natural oil and gas seeps do occur in the Gulf of 

Mexico and there are some bacteria and deepwater 

benthic communities that inhabit areas with seeps. 

Natural oil seeps are geographically common and 

have likely been active throughout history. Natural 

seeps have been estimated to account for 

approximately 47% of the crude oil entering the 

marine environment (Kvenvolden and Cooper, 2003). 

For more information on seeps in comparison to other 

petroleum inputs to Gulf of Mexico waters, refer to

Table 3-29 and Chapter 3.3.2.9.2 of the 2017-2022 

GOM Multisale EIS. Chemosynthetic organisms are 

naturally adapted to handle the limited amounts of 

hydrocarbons that are typical at slow-flowing seeps. 

While they have not been as well studied as 

deepwater corals, there have been no documented 

impacts from the Deepwater Horizon oil spill to

chemosynthetic communities (USDOI, BOEM, 2012; 

Shedd, official communication, 2015). It is possible 

that some deepwater coral species also have limited 

capabilities to endure oil exposure. Results from 

DeLeo et al. (2015) suggested that Callogorgia delta, 

a soft coral often associated with natural hydrocarbon 

seeps, may have some natural adaptation to shortterm oil exposure. Al-Dahash and Mahmoud (2013) 

suggest that a possible mechanism for this is coral 

harboring of symbiotic oil-degrading bacteria.

Gulf 

Restoration 

Network

GRN-5 BOEM cannot move forward until companies are 

required to report oil spills according to NOAA or 

USCG standards.

Operators are required to immediately report to BSEE 

all spills of oil or other liquid pollutants that are known 

or suspected to be 1 bbl in volume or greater, per 

30 CFR § 250.187 and 30 CFR § 254.46(a). This 

requirement is in addition to, but does not substitute 

for, the National Response Center’s reporting 

requirements. Per 30 CFR § 254.46(b)(2), spills 

>50 bbl in volume require more detailed reporting and 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-161

Commenter Comment ID Comment Response

monitoring, and such spills trigger greater investigative 

response by BSEE, who may require the operator to 

submit additional information about the response.

The National Oceanic and Atmospheric 

Administrations’ (NOAA’s) Office of Response and 

Restoration is charged with responding to oil spills, 

chemical accidents, and other emergencies in coastal 

areas. Under the National Contingency Plan, NOAA 

is responsible for providing scientific support to the 

Federal On-Scene Coordinator for oil and hazardous 

material spills. To support this mandate, the Office of 

Response and Restoration provides 24-hour, 7-day-aweek response to spills (USDOC, NOAA, Office of 

Response and Restoration, 2016).

A Federal On-Scene Coordinator is a representative 

of a Federal agency such as USCG or USEPA. The 

Federal On-Scene Coordinator oversees the oil-spill 

response effort and determines if the efforts were 

conducted in accordance with the National 

Contingency Plan (USDHS, CG, 2016).

Gulf 

Restoration 

Network

GRN-7 Ongoing leaks like the Taylor platform have not been 

evaluated for environmental impact. It is ludicrous to 

say that oil from Taylor does not impact some 

proportion of spawning for Bluefin Tuna, Cobia, and 

other highly migratory species that spawn in the Gulf. 

The sheen has been emitted from the well site year 

round since 2004. The oil slick increases in size 

during the summer, and seems to be getting longer, 

according to NRC reports. The site may be used for 

dumping by other parties, since it is well known that 

there are no consequences for dumping oil into 

waters of the United States at this site.

Information regarding the Taylor Energy platform that 

was lost during Hurricane Ivan and that was located in

Mississippi Canyon Block 20 is discussed in Chapter 

3.2.1.1.3 of the 2017-2022 GOM Multisale EIS and is 

incorporated by reference into this Supplemental EIS. 

The BSEE and BOEM have worked with USCG under 

a Unified Command to monitor and respond to 

discharges from Taylor Energy’s Mississippi Canyon 

Block 20 site since the oil production platform and 

25 of the 28 connected wells were impacted and 

damaged during Hurricane Ivan in 2004. The multiagency effort has worked continuously to prevent and 

control oil discharge, improve the effectiveness of 

containment around the source of the oil discharge, 

and mitigate environmental impacts. The Unified 

Command’s collaborative efforts have resulted in the 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-162 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

removal of the platform deck, removal of subsea 

debris, decommissioning of the oil pipeline, and 

intervention of 9 of the 25 impacted wells. Taylor 

Energy, as the responsible party, has a continuing 

legal obligation and responsibility to pay for oil-spill 

recovery and response costs under the Oil Pollution 

Act of 1990.

The Taylor Energy leak has been included in the oilspill analysis that is summarized in Chapter 3 of this 

Supplemental EIS and discussed in detail in the 

2017-2022 GOM Multisale EIS. Although analysis of 

the impacts of the Taylor Energy platform is out of the 

scope for this Supplemental EIS, impacts to fish from 

oil spills are summarized in Chapter 4.7 of this 

Supplemental EIS and analyzed in detail in 

Chapter 4.7 of the 2017-2022 GOM Multisale EIS.

Bonnie 

Aylward

BA-1 I am a resident of Venice, FL and was there for the 

Deepwater Horizon event. We were never 

compensated and are unable to sell out house. We 

have lost a lot of money and know the housing 

market has gone down, but think there is a 

relationship with the Deepwater Horizon event and 

that there were impacts to the housing market.

Thank you for your comment. BOEM has no authority 

to provide compensation for changes in the housing 

market. However, the Federal Government has 

provided funding through other means in recognition 

of these ongoing impacts. The Coastal Impact 

Assistance Program (CIAP) was established by The 

Energy Policy Act of 2005 (Public Law 109-58). The 

CIAP authorizes funds from OCS oil and gas 

revenues to be distributed to OCS oil- and 

gas-producing states for the conservation, protection, 

and preservation of coastal areas, including wetlands. 

In recent years, Louisiana has received over $1 billion 

in offshore 8(g) revenues, over $500 million dollars in 

CIAP funds, and stands to receive more offshore 

revenue shares in coming years from the Gulf of 

Mexico Energy Security Act of 2006 (Public Law 

109-432).

Pam Scaggs, 

South Baldwin 

Democrats

PSSBD-1 We signed a contract to buy our house April 19, 

2010. The BP oil rig blew the next day. We were 

devastated. We did go through with buying our 

house, only because we believed what BP said 

about how the spill was not that bad and was under 

control and we believed them. After we settled our 

contact and bought the house, all the truth came out 

and how bad it was. It really took a toll on us. We 

put our retirement money into buying our last home 

to spend our final days here on the Gulf. Our whole 

community suffered greatly from the spill. Everything 

went downhill. Housing prices dropped, restaurants 

closed, condos on the beach just stopped building. 

Our fishery suffered and not sure to this day how 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-163

Commenter Comment ID Comment Response

safe it is. It has taken years for our community to get 

back to stability.

Peter Shrock PS-2 In particular, the Environmental Impact Statement 

(EIS) is not comprehensive in its risk analysis of 

catastrophic oil spills, which increase in probability as 

drilling is forced into deeper reserves, and which are 

subject to climate change effects (e.g. fiercer storms, 

rising sea levels) that increase the risk of damage to 

infrastructure and catastrophic spills.

BOEM acknowledges that each oil-spill event is 

unique; its outcome depends on several factors, 

including time of year and location, atmospheric and 

oceanographic conditions (e.g., winds, currents, 

coastal type, and sensitive resources), specifics of the 

well (i.e., flow rates, hydrocarbon characteristics, and 

infrastructure damage), and response effort (i.e.,

speed and effectiveness). For this reason, the 

severity of impacts from an oil spill cannot be 

predicted based on volume alone, although a 

minimum volume of oil must be spilled to reach 

catastrophic impacts. BOEM’s resource assessment 

studies show a higher probability of large oil reservoirs 

being discovered and produced in deep water as 

compared with shallow water (DeCort, official 

communication, 2012). BOEM provides an analysis of 

a catastrophic oil spill in the Catastrophic Spill Event 

Analysis white paper (USDOI, BOEM, 2017a) 

because a spill of that magnitude is not reasonably 

foreseeable and not part of a proposed action (Ji 

et al., 2014). While it is possible that, as a result of 

climate change, both the number and severity of 

hurricanes may increase, the Bureau of Ocean Energy 

Management’s OSRA includes data collected during 

hurricane conditions. In addition, BSEE provides a 

robust set of regulations related to hurricane 

preparedness that help lower the risk of oil spills 

occurring and that help prevent any loss of life. 

Severe weather, including hurricanes, are addressed 

in Chapters 3.2.1.1, 3.2.4, and 3.3.2.9.3 of the 2017-

2022 GOM Multisale EIS. In addition, severe weather 

is addressed in Chapter 1.2.2.8 of the Catastrophic 

Spill Event Analysis white paper (USDOI, BOEM, 

2017a). Rising sea levels are addressed in Chapter 

3.3.2.8.1 of the 2017-2022 GOM Multisale EIS.

Jackie 

Hartstein

JH-1 Well, anyways, I'm here because I was hoping that I 

could say something in terms of the depth if the 

leases are sold. I think the more depth to the drilling 

increases the risk, and I just really don't think we 

deserve any more risk after 2010. It hasn't been a 

very long time and we all remember it very well.
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-164 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

Topic 7 – Mitigation

David Quist DQ-11 Topographic Features -

- if the impacts are being assessed assuming that 

the Topographic Features Stipulation are in place, 

those Stipulations should be a required part of the 

leases under any alternative, rather than simply a 

possible mitigation strategy

The Topographic Features and Live Bottom (Pinnacle 

Trend) Stipulations have been applied as 

programmatic mitigation in the 2017-2022 Five Year 

Program EIS (USDOI, BOEM, 201a); therefore, these 

stipulations would apply to all leases issued under the 

2017-2022 Five-Year Program in designated lease 

blocks.

In Chapter 2.2.3.1, BOEM defines all prelease 

mitigating measures (stipulations) analyzed in this 

Supplemental EIS and identifies which stipulations are 

applicable to which alternative in Table 2-1. 

Appendix B of the 2017-2022 GOM Multisale EIS 

provides definitions of all commonly applied postlease 

mitigating measures.

Peter Shrock PS-5 BOEM's proposal lacks meaningful mitigation of the 

harms that it discloses such as coastal erosion, 

harms to birds, and noise impacts on marine 

mammals.

In Chapter 2.2.3.1, BOEM defines all prelease 

mitigating measures (stipulations) analyzed in this 

Supplemental EIS and identifies which stipulations are 

applicable to which alternative in Table 2-1. 

Appendix B of the 2017-2022 GOM Multisale EIS 

provides definitions of all commonly applied postlease 

mitigating measures. Where applicable, the mitigating 

measures applied for each resource are identified in 

that resource analysis in Chapter 4. 

The Topographic Features and Live Bottom (Pinnacle 

Trend) Stipulations have been applied as 

programmatic mitigation in the Five-Year Program EIS 

(USDOI, BOEM, 2016a); therefore, these stipulations 

would apply to all leases issued under the 2017-2022 

Five-Year Program in designated lease blocks.

The analysis of the other eight stipulations for any 

particular alternative does not ensure that the 

Assistant Secretary for Land and Minerals 

Management will make a decision to apply the 

Mobile 

Environmental 

Justice Action 

Coalition 

MEJAC-7 There are additionally many unanswered questions 

about the effectiveness of industry's preferred Gulf of 

Mexico marine mammal impact mitigation 

techniques. Thorough vetting and duplication of 

these policies and procedures to reduce impacts 

from such activities like ultrasound mapping has yet 

to be undertaken appropriately.
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-165

Commenter Comment ID Comment Response

stipulations to leases that may result from any 

proposed regionwide lease sale nor does it preclude 

minor modifications in wording during subsequent 

steps in the prelease process if comments indicate 

changes are necessary or if conditions change. Any 

prelease mitigating measures are disclosed in the 

Record of Decision for that particular lease sale. 

Those stipulations become enforceable provisions of 

the lease and are enforced by BSEE through their 

rigorous enforcement programs.

Postlease mitigating measures are implemented on a 

case-by-case basis throughout the postlease process 

through site-specific plan and/or permit reviews and 

cannot be speculated on at this point in the program. 

Appendix A of the 2017-2022 GOM Multisale EIS 

provides detailed information on BOEM’s and BSEE’s 

postlease permitting and approval processes.

Noise impacts to marine mammals are primarily from 

G&G activities. A full discussion of impacts 

associated with G&G activities is outside the scope of 

this Supplemental EIS because these activities are 

permitted outside of the leasing process and would 

continue regardless of the alternative selected here. 

A summary of G&G operations can be found in 

Chapter 4.9.1 (“Marine Mammals”) of this 

Supplemental EIS, and a more detailed discussion 

can be found in Chapter 4.9.1 of the 2017-2022 GOM 

Multisale EIS. This chapter includes the potential 

impacts to marine mammal species that may result 

from G&G activities and the information that is 

currently available. In addition, ancillary activities or 

G&G exploration and development activities may be 

conducted on a lease. For more detail on these 

activities and the mitigations and stipulations 

associated with those activities, refer to Appendix A

(“Postlease Processes”) of the 2017-2022 GOM 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-166 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

Multisale EIS.

Mitigating measures for seismic surveys are described 

in NTL 2016-BOEM-G02. The Protected Species 

Stipulation is one of BOEM’s prelease stipulations that 

may be disclosed in the Record of Decision for that 

particular lease sale. It will then become an 

enforceable provision of the lease and is enforced by 

BSEE through their rigorous inspection program. The 

Protected Species Stipulation has been applied to all 

blocks leased in the GOM since December 2001. 

This stipulation was developed in consultation with the 

U.S. Department of Commerce’s National Oceanic 

and Atmospheric Administration’s NMFS and the U.S. 

Department of the Interior’s FWS in accordance with 

Section 7 of the Endangered Species Act, and it is 

designed to minimize or avoid potential adverse 

impacts to federally protected species. In addition, 

NMFS, BOEM, and BSEE collaborated to publish 

National Standards for a Protected Species Observer 

Program, which provides guidance on how to reduce 

impacts to protected species from G&G activities by 

standardizing the variation in and improving the 

management of the program (Baker et al., 2013), 

although this guidance is not mandatory.

More detailed information on Gulf of Mexico G&G 

activities can be found in the Gulf of Mexico 

Geological and Geophysical Activities: Western, 

Central, and Eastern Planning Areas—Final 

Programmatic Environmental Impact Statement

(USDOI, BOEM, 2017c), which BOEM prepared with 

BSEE and the National Oceanic and Atmospheric 

Administration’s NMFS as cooperating agencies, to 

evaluate the potential environmental impacts of 

multiple G&G activities within Federal waters of the 

Gulf of Mexico’s OCS and adjacent State waters.
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-167

Commenter Comment ID Comment Response

Alabama 

Department of 

Environmental 

Management

ADEM-1 On behalf of the Alabama Coastal Area Management 

Program (ACAMP, the Alabama Department of 

Environmental Management (ADEM) reviewed 

BOEM's draft Supplemental EIS 2018 for the 

referenced proposed five-year lease sale for 

activities in the Gulf of Mexico. This five-year plan 

includes Sales 249, 250, 251, 252, 253, 254, 256, 

257, 259, and 261.

The ADEM supports the leasing of any unleased 

blocks in the Gulf of Mexico except those blocks 

which are within 15 miles of the Baldwin County 

coastline. Alabama's Governors have consistently 

opposed the sale of those leases. In addition, the 

ADEM requests BOEM require adequate protection 

for the live bottom areas, pinnacle reefs, 

chemosynthetic communities, and other sensitive 

environments in the OCS off Alabama's coast.

As noted in the Alabama Department of 

Environmental Management’s letter, the Governors of 

Alabama have historically indicated opposition to new 

leasing south and within 15 mi (24 km) of Baldwin 

County; however, they have requested that, if the area 

is offered for lease, a lease stipulation to reduce the 

potential for visual impacts be applied to all new 

leases in this area. Protective measures are in place 

to mitigate the potential impacts to the areas south of 

Baldwin County and to the biologically significant 

bottom-founded marine communities and 

archaeological resources. Coordination requirements 

are described in the Blocks South of Baldwin County, 

Alabama and Topographic Features Stipulations 

(which can be found in Appendix D of the 2017-2022 

GOM Multisale EIS), and in the resource analyses in 

Chapter 4. In addition, during postlease reviews, 

BOEM and BSEE have a suite of mitigations that are 

included as conditions of approval, as the site-specific 

conditions warrant. Examples of such relevant 

postlease mitigations might include, but is not limited 

to, prohibiting discharges near sensitive live bottom 

habitats (e.g., chemosynthetic communities), 

anchoring restrictions, distancing requirements, and 

remotely operated vehicle surveys. Appendix B of the 

2017-2022 GOM Multisale EIS provides more detail 

on the suite of applicable mitigations that could be 

applied to protect the areas of concern presented in 

your comment.

Charles Frey CF-1 PRESERVE THE MILITY TRAING AREA IN THE 

EASTERN GULF.

The Military Areas Stipulation is discussed in Chapter 

2.2.4.1 and outlined in Figure 2-8 of the 2017-2022 

GOM Multisale EIS, from which this Supplemental EIS 

tiers.

The Military Areas Stipulation has been applied to all 

blocks leased in military areas since 1977 and 

reduces potential impacts, particularly in regards to 

safety, but it does not reduce or eliminate the actual 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-168 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

physical presence of OCS oil- and gas-related

operations in areas where military operations are 

conducted. The stipulation contains a “hold harmless” 

clause (holding the U.S. Government harmless in 

case of an accident involving military operations) and 

requires lessees to coordinate their activities with 

appropriate local military contacts.

The Assistant Secretary for Land and Minerals 

Management will make a decision to apply stipulations 

to leases, and those prelease mitigating measures are 

disclosed in the Record of Decision for that particular 

lease sale. Those stipulations become enforceable 

provisions of the lease and are enforced by BSEE 

through their rigorous inspection program.

Topic 8 – Regulations and Safety

Center for 

Biological 

Diversity, 

Sierra Club, 

Gulf 

Restoration 

Network,

Louisiana 

Bucket 

Brigade

CBD,SC,GRN,

LBB-12

The Draft SEIS fails to consider the failure of the 

Bureau to reform safety and environmental oversight 

of offshore oil and gas development in the Gulf of 

Mexico. On one hand, numerous recommendations 

to improve regulation of the industry have never 

been implemented. On the other hand, voluntary 

measures to promote a culture of safety have been 

ineffective.

First, in 2017, the Government Accountability Office 

(GAO) expanded the high risk status of management 

of federal oil and gas resources to include the failure 

to institute needed safety and environmental reforms 

providing oversight of offshore oil and gas activities. 

The GAO investigation concluded that the safety and 

enforcement agency, the Bureau of Safety and 

Environmental Enforcement, had failed to make 

progress in improving its regulatory oversight—as 

needed after Deepwater Horizon oil spill. It found 

many problems including that the Bureau was still 

using deficient pre-Deepwater Horizon policies and 

procedures and that the environmental compliance 

Thank you for your comment. In response to the 

Deepwater Horizon explosion and oil spill in the Gulf 

of Mexico in 2010, DOI launched the most aggressive 

and comprehensive reforms to offshore oil and gas 

regulation and oversight in U.S. history (USDOI, 

BSEE, 2016). The DOI has implemented a suite of 

regulatory changes following the Deepwater Horizon

explosion, oil spill, and response. These changes are 

discussed in detail in Chapter 3.2 and Appendix A of 

the 2017-2022 GOM Multisale EIS. In addition, safety 

measures and technologies have improved since the 

Deepwater Horizon oil spill. A fact sheet on research 

and regulatory reforms can be found on BOEM’s 

website at http://www.bsee.gov/About-BSEE/BSEEHistory/Reforms/Reforms/. BOEM and BSEE will 

remain vigilant in instituting reform efforts and lessons 

learned since the Deepwater Horizon explosion, oil 

spill, and response.

The findings in the Government Account Office’s 

report concerning BSEE’s operations are outside the 

scope of this Supplemental EIS because BSEE’s
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-169

Commenter Comment ID Comment Response

program had reversed course on actions taken to 

improve its oversight. The GAO made numerous 

recommendations that seek to address the Bureau’s 

insufficient regulatory oversight of the offshore oil 

and gas industry. This new information must be 

disclosed and evaluated in the SEIS. Moreover, new 

research found that people would pay $17.2 billion in 

taxes for regulatory programs that would avoid an oil 

spill in the Gulf of Mexico.

Second, past practice indicates that the industry 

lacks follow-through on environmental and safety 

programs. For example, the Bureau of Safety and 

Environmental Enforcement reports that its effort to 

improve safety through voluntary industry selfreporting of near-miss incidents has failed. It noted a 

lack of industry interest in the program and found 

that the only reports were those that were made 

mandatory. Another example is the chronic problem 

of companies failing to decommission old platforms, 

a problem that prompted a 2016 increase in financial 

assurances for decommissioning via NTL No. 

2016-N01 – a notice repealed by President Trump.

Third, President Trump issued an Executive Order 

that seeks to expand leasing and rollback regulatory 

oversight of offshore oil and gas. The Order directs 

the Secretary of Interior to review the blowout 

preventer rule, the financial assurance bonding rule, 

and a rule addressing air pollution. These actions 

could increase the environmental impacts of offshore 

oil and gas development as well as increase the risk 

of a catastrophic oil spill, which must be analyzed 

here.

Fourth, reliance on mitigation to reduce 

environmental impacts on protected species is 

misplaced because expert protected species 

operations are outside of the leasing process. 

However, BOEM acknowledges your concerns and 

recommends that you contact BSEE directly regarding 

your concerns.

In response to the third comment, BOEM is aware of 

changing regulations under a new administration. 

However, the analysis conducted for the 2018 lease 

sale was performed under the current 2017-2022 

Five-Year Program. The information used to conduct 

these analyses was the best available information at 

that time.

In reference to the fourth comment concerning 

protected species, BOEM and BSEE have submitted 

Biological Assessments to NMFS and FWS, and are 

actively engaged with them in consultation concerning 

all of our past and reasonably foreseeable future 

activities. Until the above-mentioned NMFS’ formal 

consultation is complete, BOEM is under an interim 

consultation agreement with NMFS with all terms and 

conditions being followed. The determinations within 

this Supplemental EIS are required under NEPA to 

help inform the decisionmaker at the lease sale stage 

and are not necessarily for the determinations under 

the ESA or Marine Mammal Protection Act. The 

NMFS and FWS understand the types and levels of 

activities that BOEM is engaged in and have not 

raised concerns with our ongoing activities. They are 

fully informed of the potential impacts identified in this 

Supplemental EIS as well as in the Biological 

Assessments. Furthermore, the Protected Species 

Stipulation, if applied, would require already existing 

terms and conditions and mitigations implemented to 

protect species at the lease sale stage. As the 

stipulation notes, BOEM and BSEE can condition 

approval of any postlease authorization or permit on 

compliance with the most current mitigations or 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-170 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

evaluations have yet to be completed to prescribe 

and recommend necessary mitigation. The 

biological opinion on the impact of offshore oil and 

gas activities in the Gulf of Mexico is woefully 

outdated since consultation took place before the 

Deepwater Horizon oil spill caused an enormous toll 

on the Gulf’s wildlife and habitat. Recognizing that it 

had a duty to reinitiate consultation, the Bureau did 

so more than seven years ago in 2010. Section 7 

consultation is required for “any action [that] may 

affect listed species or critical habitat.” Once the 

action agency has initiated formal consultation, the 

Service is required to complete a biological opinion 

on the impacts of that proposed action. If the

Service determines the agency action is likely to 

jeopardize the continued existence of a listed 

species or result in adverse modification, the 

biological opinion must suggest “reasonable and 

prudent alternatives” which would reduce actionrelated impacts such that the agency action may 

avoid jeopardizing listed species. Absent the 

completion of such consultation, the Bureau’s Draft 

EIS is invalid with respect to its conclusions on 

threatened and endangered species. Similarly, the 

industry takes marine mammals in violation of the 

Marine Mammal Protection Act. Only by going 

through the requisite process for compliance can the 

Bureau rely on mitigation to reduce and avoid 

impacts to marine mammals. In issuing an 

“incidental take” authorization, the Service must 

prescribe methods and means of affecting the “least 

practicable adverse impact” on the species or stock 

and its habitat. According to the courts, the least 

practical adverse impact requirement is a stringent 

standard. The least practicable adverse impact 

mandate is “an independent threshold statutory 

requirement” that must be met in addition to the 

requirements that “take” authorizations have only a 

requirements to protected listed species or habitats at 

the time. The staged OCSLA decisionmaking and 

approval process ensures that BOEM and BSEE can 

require additional protected species protections after 

leases are issued.

Refer to Chapter 5.8 for more information on the ESA 

consultations.

In addition, refer to the response to Comment 

USFWS-1, which indicates that FWS is developing a 

Biological Opinion for BOEM on the effects of oil and 

gas leasing, exploration, development, production, 

decommissioning, and all related activities in the Gulf 

of Mexico OCS within existing lease areas and those 

proposed for future leasing in the WPA, CPA, and 

EPA through the year 2022.
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-171

Commenter Comment ID Comment Response

negligible impact and be only for small numbers of 

marine mammals. Additionally, post-Deepwater 

Horizon research shows that oil spill response for 

marine mammal stranding was insufficiently 

prepared, and that there was a significant lack of 

people with adequate training.

Peter Shrock PS-3 Additionally, the feds have failed to adopt reforms 

that address the safety and environmental risks since 

the Deepwater Horizon oil spill. A 2016 General 

Accounting Office report found that the Bureau of 

Safety and Environmental Enforcement (BSEE) "has 

not fully addressed deficiencies in its investigative, 

environmental compliance, and enforcement 

capabilities identified by investigations after the 

Deepwater Horizon incident" and that BSEE is still 

using "pre-Deepwater Horizon policies and 

procedures." Among other things, this means that 

our environment and offshore workers are still facing 

significant, unacceptable dangers.

Thank you for your comment. The findings in the 

Government Account Office’s report concerning 

BSEE’s operations are outside the scope of this 

Supplemental EIS because BSEE’s operations are 

outside of the leasing process. However, BOEM 

acknowledges your concerns and recommends that 

you contact BSEE directly regarding your concerns.

Jackie Antalan JA-4 This lease sale should be canceled until such time as 

BOEM will adequately analyze the impacts of 

offshore drilling, including safety requirements for 

public safety and public health. Further, the lease 

sale should be canceled based on the GAO report 

that found that BSEE has not fully addressed the 

deficiencies of the BP oil spill and further leasing put 

coastal rural underserved communities at risk for 

public safety which includes air and water pollution.

Bill McBride BM-2 We cannot trust profit-driven oil companies to drill 

safely. BP cut corners to save money.

The BSEE promotes compliance with safety and 

environmental standards through regular inspections 

and other monitoring activities, timely notice to 

operators of detected violations, clear direction for 

coming into compliance, and a reasonable opportunity 

for improvement. The BSEE’s intent is to prevent 

incidents; however, should they occur, BSEE has a 

duty to investigate, to determine the causal 

elements/factors, and to take the appropriate 

M. Fleming MF-2 No amount of safety measures could be put in place 

to make these leases a good idea. 

Jodi Koszarek JK-3 Please do not further erode the health of our Gulf of 

Mexico! After suffering through the BP disaster, it is 

difficult to express my dismay at the prospect of 

millions of more acres of the gulf falling victim to an 

industry who does not regulate itself especially with 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-172 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

today's deregulation atmosphere in DC. The people 

who live along the shores of the Gulf of Mexico 

deserve better not to mention the myriad wildlife that 

live in the sea and along the shore that this industry 

has a history of decimating.

corrective actions. Refer to Appendix A.4 of the 

2017-2022 GOM Multisale EIS for more information 

on BSEE’s inspection and enforcement 

responsibilities, as authorized by the OCSLA.

In addition, after the Deepwater Horizon explosion and 

oil spill in the Gulf of Mexico in 2010, DOI launched 

the most aggressive and comprehensive reforms to 

offshore oil and gas regulation and oversight in U.S. 

history (USDOI, BSEE, 2016). The DOI has 

implemented a suite of regulatory changes following 

the Deepwater Horizon explosion, oil spill, and 

response. These changes are discussed in detail in 

Chapter 3.2 and Appendix A of the 2017-2022 GOM 

Multisale EIS. In addition, safety measures and 

technologies have increased since the Deepwater 

Horizon oil spill. A fact sheet on research and 

regulatory reforms can be found on BOEM’s website 

at http://www.bsee.gov/About-BSEE/BSEEHistory/Reforms/Reforms/. BOEM and BSEE will 

remain vigilant in instituting reform efforts and lessons 

learned since the Deepwater Horizon explosion, oil 

spill, and response.

Jackie 

Hartstein

JH-2 We're also losing ground with the EPA and -- what is 

it? -- the National Ocean Atmospheric --

BOEM Representative: Administration.

MS. HARTSTEIN:

-- Administration is taking a hit. So who's going to 

help us when there is a problem? And I don't like to 

call them accidents, because, to me, my puppy has 

accidents. An oil spill is not an accident. It's a big 

deal. And there's nobody to really police them, even 

though I heard about BES and I'm great -- it's a great 

thing, but day by day, a rich company does not do 

things to protect the environment. Time is money. If 

they don't want to do a safety precaution or a 

maintenance job, they're not going to do it. And I 

don't think the State of Florida can go into litigation 

with BP and win. I don't think we have the money to 

do that. But our state rep -- well, our representative 

to Washington, D.C., wants to do away with the EPA. 

So he wants like the State of Florida to give 

guidelines and protect us. Well, that's just more 

politics, and politics is part of what causes the 

accidents in my book, because we don't have 

enough people to really police these guys. And it's 

nobody's fault. Certainly not you all's fault.

Judy Fisher JF-1 As a business person I was shocked and horrified by 

the Deep Horizon/Macondo Well blowout in April of 

2010 that claimed 10 lives and destroyed the 

environment around it. I couldn't wrap my mind 

around the fact that neither industry or government 

had a clue or plan in place in how to react to the 

catastrophe.

As a result of the Oil Pollution Act of 1990 and the 

reorganization of the Bureau of Ocean Energy 

Management, Regulation and Enforcement into 

BOEM and BSEE, BSEE was tasked with a number of 

oil-spill response duties and planning requirements. 

Within BSEE, the Oil Spill Preparedness Division 

addresses all aspects of offshore oil-spill planning, 

preparedness, and response. Additional information Judy Fisher JF-2 It really hasn't been explained to the public how the 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-173

Commenter Comment ID Comment Response

"reaction" would be different if another "accident" 

were to occur.

about the Oil Spill Preparedness Division can be 

found on BSEE’s website at http://www.bsee.gov/

About-BSEE/Divisions/OSPD/index/. Refer to 

Chapter 3.2.8.1 of the 2017-2022 GOM Multisale EIS 

for a more detailed discussion of BSEE’s spillresponse requirements and initiatives.

The responsible party for covered offshore facilities 

must demonstrate oil-spill financial responsibility, as 

required by 30 CFR part 553. These regulations 

implement the oil-spill financial responsibility 

requirements of Title I of the Oil Pollution Act of 1990, 

as amended. Penalties for noncompliance with these 

requirements are covered at 30 CFR § 553.51 and in 

NTL 2008-N05, “Guidelines for Oil Spill Financial 

Responsibility for Covered Facilities.” A covered 

offshore facility, as defined in 30 CFR § 553.3, is any 

structure and all of its components (including wells 

completed at the structure and the associated 

pipelines), equipment, pipeline, or device (other than a 

vessel or other than a pipeline or deepwater port 

licensed under the Deepwater Port Act of 1974) used 

for exploring, drilling, or producing oil, or for 

transporting oil from such facilities. The BSEE 

ensures that each responsible party has sufficient 

funds for removal costs and damages resulting from 

the accidental release of liquid hydrocarbons into the 

environment for which the responsible party is liable. 

More information on oil-spill response plan regulations 

and processes can be found in Appendix A.5 of the 

2017-2022 GOM Multisale EIS.

In response to the Deepwater Horizon explosion and 

oil spill in the Gulf of Mexico in 2010, DOI launched 

the most aggressive and comprehensive reforms to 

offshore oil and gas regulation and oversight in U.S. 

history (USDOI, BSEE, 2016). The DOI has 

implemented a suite of regulatory changes following 

Judy Fisher JF-3 Does the oil exploration industry and the federal 

government know for certain that another disaster 

would not occur and if it did that any entity would 

know how to respond.

Judy Fisher JF-4 Why do we need to try mitigate a disaster when we 

should have knowledgeable people who can 

implement regulations that will prevent a disaster?

Judy Fisher JF-5 The fact that permits were issued for the exploration 

of this well without adequate emergency plans in 

place should be an embarrassment for the industry 

and for our regulatory agencies.

Judy Fisher JF-6 The other issue is that industry was relied upon to 

solve the problem (after the fact) that they created 

with their negligence but really it is the regulators 

who were negligent in not anticipating such a 

disaster could occur and require the proper 

mechanisms are in place to prevent unprecedented 

loss of life and damage and death to the 

environment.

Judy Fisher JF-7 We are learning that a clean environment is 

invaluable and that we do not have the technology 

mitigate a disaster and bring our environment back to 

a clean state in a human life span.

Judy Fisher JF-8 I ask the BOEM to provide to the general population 

the information that explains how we can now trust 

that these types of disasters will be prevented in the 

future before more auctions are held and more 

permits are issued.

Bud See BuSe-1 But I am just an ordinary citizen with no money, so 

government officials ignore me and cater to the 

millionaires and the big corporations. Now, my state 

government requires me to have liability insurance 

before I can drive my car. We know that several 

offshore oil wells have had problems, and millions of 

gallons of crude oil have leaked into the oceans and 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-174 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

the Gulf of Mexico. If the federal government insists 

on allowing companies to drill for offshore oil, it 

should require the oil company to post a multimilliondollar bond that is great enough to cover the 

following costs:

 Repair the break,

 Scoop up the spilled crude,

 Rescue as many whales, dolphins, turtles, fish, 

shrimp, and birds as possible.

Yes, this would make the offshore oil drilling too 

expensive for a small, mom-and-pop company to 

pursue--but we SHOULD NOT have small 

companies drilling for offshore oil!!!! The Deepwater 

Horizon oil spill demonstrated to us what a great 

danger is involved in offshore oil drilling. Before any 

company embarks on such a risky business venture, 

that company should guarantee that it will pay the 

cost of repairing the damage that it might inflict upon 

our coast. The oil company stands to make millions 

of dollars in profits from the offshore oil, so it should 

be willing to guarantee that it will pay the cost of 

repairing its possible damage.

the Deepwater Horizon explosion, oil spill, and 

response. These changes are discussed in detail in 

Chapter 3.2 and Appendix A of the 2017-2022 GOM 

Multisale EIS. In addition, safety measures and 

technologies have increased since the Deepwater 

Horizon oil spill. A fact sheet on research and 

regulatory reforms can be found on BOEM’s website 

at http://www.bsee.gov/About-BSEE/BSEEHistory/Reforms/Reforms/. BOEM and BSEE will 

remain vigilant in instituting reform efforts and lessons 

learned since the Deepwater Horizon explosion, oil 

spill, and response.

John Warden JW-1 Risk management practices within the offshore 

drilling and production industries have proven to be 

inadequate. Cost-benefit analyses cannot 

adequately account for the complexity of 

environmental, economic and societal costs of a 

major spill which is a certainty -- not an If, only a 

When.

Topic 9 – Other

David Quist DQ-7 US gas production is booming - it is not credible, 

under current market conditions, to expect increased 

imports under alternative E.

Oil from the Gulf of Mexico OCS contributes to 

meeting domestic demand and enhances national 

economic security. Although peak OCS production 

may not occur until some point in the future, oil and 

gas production is still necessary to bridge to a 

balanced, or even different, energy future. Over the 

Maggi Roberts MaRo-5 There are ample reserves that oil and gas 

companies can tap into from previous oil and gas 

leases so allowing this activity to continue is 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-175

Commenter Comment ID Comment Response

unnecessary in 2018. next 20 years, the U.S. Dept. of Energy’s Energy 

Information Administration expects the U.S. to rely on 

more oil and natural gas to meet its energy demands, 

even as alternative sources of energy provide an 

increasing share of U.S. energy needs. Since the 

U.S. is expected to continue to rely on oil and natural 

gas to meet its energy needs, a proposed action 

would contribute to meeting domestic demand. The 

OCS is a major long-term supplier of crude oil and 

natural gas, and the Gulf of Mexico OCS region has 

the greatest resource potential of the four OCS 

regions in the United States.

The determination of the U.S. energy needs is based 

on the U.S. Dept. of Energy’s Energy Information 

Administration's 2016 demand projections and is 

discussed in detail in the 2017-2022 Five-Year 

Program. The Energy Information Administration is 

the principal Federal agency responsible for collecting, 

analyzing, and disseminating energy information to 

promote sound policymaking, efficient markets, and 

public understanding of energy and its interaction with 

the economy and the environment. The Energy 

Information Administration forecasts future energy 

demand and supply based on current laws and 

regulations. BOEM relies on special runs performed 

by the Energy Information Administration's National 

Energy Modeling System (NEMS) to feed its 

MarketSim model that, in turn, is used to determine 

changes in energy demand and energy substitutes 

under the No Action alternative.

The energy demand analysis from the 2017-2022 

Five-Year Program EIS is incorporated into this 

Supplemental EIS through the tiering process. This 

Supplemental EIS analyzes environmental and 

economic impacts and benefits for the alternatives, 

including the proposed action and No Action 

David Gorchov DaGo-2 The risks are not worth it. We have a glut of oil and 

gas from hydraulic fracturing on inland sites. 

Mobile 

Environmental 

Justice Action 

Coalition 

MEJAC-6 Also, given the glut oil market we are in where 

petrochemical export options are being actively 

explored, Alternative E would not significantly 

deprive the market of a supply to meet its short-term 

demands.

Bill McBride BM-3 With huge reserves elsewhere, why take this terrible 

risk! No Leases.

Alicia Cooke AC-4 BP predicts a peak oil demand in the 2040's with 

assets likely to be stranded after that point 

(https://resourcegovernance.org/blog/oil-companiesface-stranded-assets-producercountries-have-itworse).

Ryan Bowman RB-3 It does not make sense to open new offshore oil sites 

when the oil industry will begin to wane in the near 

future.

Mobile 

Environmental 

Justice Action 

Coalition 

MEJAC-3 Data related to the amount of petrochemical mineral 

stock processed at Gulf refiners or stored at Gulf 

transport facilities from OCS leased properties 

should be tracked not just to monitor environmental 

justice and human health impacts but also account 

for how much, if any, product is being exported 

abroad.
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-176 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

alternative (i.e., no new leasing).

Consumer 

Energy 

Alliance

CEA-2 CEA understands that, to meet our long-term energy 

needs, we will need access to all of our resources, 

including oil and natural gas, nuclear, solar, wind, 

and beyond. We also understand that oil and natural 

gas will continue to be a critical and dominant part of 

that mix for decades to come. The federal 

government understands this as well, as 

underscored by the Energy Information

Administration’s forecast that oil and natural gas will 

contribute just as much if not more to our nation’s 

energy portfolio in 2040 than it did in 2016. In 

addition, the Interior Department has concluded that 

not holding Gulf of Mexico lease sales could cause 

billions of dollars in environmental and social costs, 

with imports having to replace the vast majority of 

foregone production.

Thank you for your comment. BOEM is working under 

President Trump’s America First Energy Plan, which 

calls for energy policies that stimulate our economy, 

ensure our security, and protect our health. For more 

information, refer to The White House’s website (The 

White House, 2017).

The decision on whether and how to proceed with 

each proposed regionwide lease sale is under the 

authority of the Assistant Secretary for Land and 

Minerals Management and will be disclosed in the 

Record of Decision following publication of this Final 

Supplemental EIS.

Further, commenters should be aware that any past or 

present commitments made by the U.S. concerning a 

reduction of GHG emissions (e.g., Paris Agreement) 

do not broaden the scope of the Bureau of Ocean 

Energy Management’s NEPA analysis at the lease 

sale stage or require BOEM to venture into analyzing 

the potential worldwide effect of GHG emissions that 

could result from a lease sale.

Beth Everage, 

Consumer 

Energy 

Alliance

BECEA-2 CEA understands that, to meet our long-term energy 

needs, we will need access to all of our resources, 

including oil and natural gas, nuclear, solar, wind, 

and beyond. We also understand that oil and natural 

gas will continue to be a critical and dominant part of 

that mix for decades to come. The federal 

government understands this as well, as 

underscored by the Energy Information 

Administration's forecast that oil and natural gas will 

contribute just as much if not more to our nation's 

energy portfolio in 2040 than it did in 2016. In 

addition, the Interior Department has concluded that 

not holding Gulf of Mexico lease sales could cause 

billions of dollars in environmental and social costs, 

with imports having to replace the vast majority of 

foregone production.

350 Louisiana 

- New Orleans

350LANO-1 Climate scientist tell us that a majority of all known 

fossil have to stay in the ground if we want to have a 

50/50 chance avoid catastrophic climate change 

(McGlade, Ekins, Nature, 1/8/2015). The U.S. has 

signed the Paris Climate Agreement, pledging to cut 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-177

Commenter Comment ID Comment Response

emissions between 26 and 28% compared with 2005 

levels by 2025.

- Does BOEM agree that climate change is 

presenting a significant danger to our society and 

societies globally?

Maggi Roberts MaRo-6 We need to assess what gas and oil companies are 

doing to preserve and protect the ocean waters and 

how they contribute to stop the pollution of the Gulf 

of Mexico.

It is outside the scope of this Supplemental EIS to 

assess preservation activities conducted by industry. 

However, BOEM’s mission is to “manage 

development of U.S. Outer Continental Shelf energy 

and mineral resources in an environmentally and 

economically responsible way.” BOEM accomplishes 

this through responsible stewardship, scienceinformed decisions, and integrity and ethics. The 

Secretary of the Interior oversees the OCS Oil and 

Gas Program and is required to balance orderly 

resource development with protection of the human, 

marine, and coastal environments while 

simultaneously ensuring that the public receives an 

equitable return for these resources and that freemarket competition is maintained.

Jackie Antalan JA-3 BOEM's supplemental EIS does not fully or clearly 

comply with the law. BOEM still continues to forget 

that its mission is to protect the public and the 

interests of the United States as opposed to private 

foreign corporations.

The OCSLA provides the Congressional mandate for 

BOEM to make “available for expeditious and orderly 

development, subject to environmental safeguards, in 

a manner which is consistent with the maintenance of 

competition and other national needs” the land of the 

Federal OCS. The Secretary of the Interior oversees 

the OCS Oil and Gas Program and is required to 

balance orderly resource development with protection 

of the human, marine, and coastal environments while 

simultaneously ensuring that the public receives an 

equitable return for these resources and that 

free-market competition is maintained.

BOEM places a significant emphasis on public input 

and scientific analysis, which are critical to safe 

exploration and development of offshore resources. 

Public comment is solicited in our environmental 

review programs for both oil and gas and renewable 

Jackie Antalan JA-6 It is BOEM's responsibility, again, to protect the 

public, to keep the public fully informed of the risks 

and the benefits of oil and gas leases. In as much, 

there are limited benefits and numerous risks, these 

lease sales should be canceled.
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

E-178 2018 Gulf of Mexico Supplemental EIS

Commenter Comment ID Comment Response

energy proposals. Plans submitted by industry are 

subject to rigorous scientific review to ensure that 

environmental safeguards are the foundation of all 

offshore energy development.

Mitigating measures are an integral part of BOEM’s 

program to ensure that postlease operations are 

conducted in an environmentally sound manner (with 

an emphasis on minimizing any adverse impact of 

routine activities on the environment). BOEM assigns 

site-specific mitigation by imposing conditions of 

approval on a plan, permit, or authorization. 

Appendix A of the 2017-2022 GOM Multisale EIS 

discusses BOEM’s rigorous postlease process, and 

Appendix B of the 2017-2022 GOM Multisale EIS 

describes over 120 standard mitigations that may be 

required by BOEM or BSEE as a result of the plan and 

permit review processes for the Gulf of Mexico OCS 

Region.

Jackie Antalan JA-7 Please consider these comments, ensure that all 

department heads all the way up to the secretary 

receives this information. I appreciate this 

opportunity to comment.

BOEM considers all comments received during the 

public comment period and addresses those 

comments in the Final EIS. BOEM follows/implements 

a transparent NEPA process to ensure that all 

stakeholders (i.e., Federal and State agencies 

[comments and consultations], Tribes, nongovernment 

organizations, industry, and public comments/

concerns) are aware of and are a part of the process. 

There are numerous opportunities for stakeholder 

involvement throughout the Bureau of Ocean Energy 

Management’s NEPA process. The NEPA documents 

and analyses incorporate all relevant and important 

input from all stakeholders that was received during 

scoping and public comment periods.

While BOEM considers and evaluates all substantive 

relevant comments from the public, this remains a 

BOEM document meant to inform the decisionmaker 

and the public of reasonably foreseeable impacts from 
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-179

Commenter Comment ID Comment Response

a proposed action and its alternatives. BOEM 

employs a team of highly trained technical staff of 

subject-matter experts who develop the analyses 

based on rigorous scientific reviews, consultations 

with other Federal and State agencies, expert 

opinions, and all relevant and important stakeholder 

considerations.

The Secretary of the Interior oversees the OCS Oil 

and Gas Program and is required to balance orderly 

resource development with protection of the human, 

marine, and coastal environments while 

simultaneously ensuring that the public receives an 

equitable return for these resources and that 

free-market competition is maintained. The decision 

on whether or how to proceed with each proposed 

regionwide lease sale is under the authority of the 

Assistant Secretary for Land and Minerals 

Management and will be disclosed in the Record of 

Decision following publication of this Supplemental 

EIS.

Bonnie 

Aylward

BA-2 I am worried about the waters in the Gulf of Mexico. 

I don’t know if there is a connection between red tide 

and drilling.

There are many different species of harmful 

phytoplankton and many different types of harmful 

algal blooms, and to speculate as to which types 

would be enhanced or suppressed in the GOM due to 

oil and gas activity is unduly speculative and not 

possible at this time.

Bonnie 

Aylward

BA-3 The debris on our shoreline is terrible. NTL 2015-BSEE-G03, “Marine Trash and Debris 

Awareness and Elimination,” presents BSEE’s policy 

regarding marine debris prevention.

“The discharge of garbage and debris has been the 

subject of strict laws, such as MARPOL-Annex V and 

the Marine Debris Act, 33 U.S.C. §§ 1951 et seq., and 

regulations imposed by various agencies including the 

United States Coast Guard and the Environmental

Protection Agency. Since oil and gas operations in 

the Gulf of Mexico may contribute to this problem, 

Denise Folley DeFo-1 I'm a longtime resident of the Gulf coast and would 

like to see an end to drilling in the Gulf. Not only 

because of potential spills and the pollution but 

because of all the trash that washes up on our 

beaches from the rigs and the boats serving them.
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

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Commenter Comment ID Comment Response

30 CFR §§ 250.300(a) and (b)(6) prohibit you from 

discharging containers and other materials into the 

marine environment, and 30 CFR §§ 250.300(c) and 

(d) require you to make durable identification markings 

on skid-mounted equipment, portable containers, 

spools or reels, and drums, and to record and report 

such items when lost overboard to the District 

Manager through facility daily operations reports.”

However, BOEM acknowledges the fact that debris 

from OCS oil- and gas-related activities contributes to 

the debris found on coastal beaches. For example, 

this Supplemental EIS states that the offshore oil and 

gas industry was shown to contribute 13% of the 

debris found at the Padre Island National Seashore 

(Miller et al., 1995). However, this debris does not 

alter beach profiles, species composition and 

abundance, or ecological function beyond a minor 

extent.
Table E-1. Public Comments and BOEM’s Response Matrix. (continued).

Responses to Public Comments on the Draft Supplemental EIS E-181

Corrected Version of Table H-5 of the 2017-2022 GOM Multisale EIS (Table D-5 of this Supplemental EIS) for Comment USEPA-39

Simplified Sector 2012 Base Year (TPY) Future Year Scenario (TPY)

NOx PM2.5 SO2 VOC NOx PM2.5 SO2 VOC

Fugitive Dust 0 70,526 0 0 0 78,179 0 0

Agricultural 0 0 0 0 0 0 0 0

Fires 27,335 250,850 17,852 559,643 27,335 250,850 17,852 559,643

ALM 171,436 5,416 2,039 4,896 139,026 3,876 280 3,760

C3 CMV 68,857 3,650 36,339 2,466 72,701 2,280 25,033 3,059

Biogenic 19,015 0 0 3,140,424 19,015 0 0 3,140,424

Nonpoint 81,464 50,730 7,334 291,650 85,532 55,032 3,106 290,118

Nonroad 76,345 6,994 153 112,683 52,636 4,826 79 78,780

Area O&G 69,331 1,991 530 506,972 74,065 2,768 1,067 641,692

Onroad 270,364 8,467 1,731 145,061 183,305 7,124 940 106,904

Non-U.S. Fugitive Dust 0 0 0 0 0 0 0 0

Non-U.S. Area 38,832 4,361 719 15,208 35,625 4,429 502 16,787

BOEM Gulfwide 363,607 12,453 57,060 44,924 126,566 4,013 31,039 36,825

Non-U.S. Onroad 13,894 438 73 6,217 9,097 447 27 4,041

Non-U.S. Point (with GOM 

offshore platforms) 106,344 2,663 7,795 57,361 32,045 2,181 4,646 11,337

Point O&G 50,765 2,294 25,431 19,596 47,526 2,480 23,543 21,442

EGU Point 137,932 17,943 306,031 3,545 117,518 21,802 136,784 4,371

Non-EGU Point 159,962 52,632 135,981 104,387 172,040 60,413 134,595 120,106

BOEM OCS Platform No Action 0 0 0 0 84,351 837 3,205 54,449

BOEM OCS Platform w/Action 0 0 0 0 22,973 223 1,037 7,015

BOEM OCS Sup. Vessel 

No Action 0 0 0 0 232,765 8,224 22,977 7,936

BOEM OCS Sup. Vessel w/Action 0 0 0 0 88,637 8,144 341 8,345
E-182 2018 Gulf of Mexico Supplemental EIS

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The Department of the Interior Mission

The Department of the Interior protects and manages the Nation’s natural 

resources and cultural heritage; provides scientific and other information 

about those resources; and honors the Nation’s trust responsibilities or 

special commitments to American Indians, Alaska Natives, and affiliated 

island communities.

The Bureau of Ocean Energy Management Mission

The Bureau of Ocean Energy Management (BOEM) is responsible for 

managing development of U.S. Outer Continental Shelf energy and mineral 

resources in an environmentally and economically responsible way.