Regulatory Impact Analysis for the Proposed Reconsideration of the National Ambient Air Quality Standards for Particulate Matter

                                                               EPA-452/P-22-001
                                                                  December 2022

Regulatory Impact Analysis for the Proposed Reconsideration of the National Ambient Air Quality Standards for Particulate Matter
                     U.S. Environmental Protection Agency
                 Office of Air Quality Planning and Standards
                   Health and Environmental Impacts Division
                          Research Triangle Park, NC

                              CONTACT INFORMATION
This document has been prepared by staff from the Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency. Questions related to this document should be addressed to U.S. Environmental Protection Agency, Office of Air Quality Planning and Standards, C439-02, Research Triangle Park, North Carolina 27711 (email: oaqpseconomics@epa.gov). Please submit comments on this document to the following docket for the regulatory impact analysis: EPA-HQ-OAR-2019-0587. The docket for the notice of proposed rulemaking is EPA-HQ-OAR-2015-0072.

                               ACKNOWLEDGEMENTS
In addition to EPA staff from the Office of Air Quality Planning and Standards, personnel from the Office of Policy's National Center for Environmental Economics contributed data and analysis to this document.

TABLE OF CONTENTS
LIST OF TABLES	x
LIST OF FIGURES	xvi
EXECUTIVE SUMMARY	ES-1
Overview of the Proposal	ES-1
Overview of the Regulatory Impact Analysis	ES-2
ES.1	 Design of the Regulatory Impact Analysis	ES-3
ES.1.1	Establishing the Analytical Baseline	ES-5
ES.1.2 	Estimating PM2.5 Emissions Reductions Needed for Annual and 24-hour Alternative Standard Levels Analyzed	ES-7
ES.1.3 	Control Strategies and PM2.5 Emissions Reductions	ES-10
ES.1.4 	Estimates of PM2.5 Emissions Reductions Still Needed after Applying Control Technologies and Measures	ES-11
ES.1.5 	Engineering Costs	ES-13
ES.1.6 	Human Health Benefits	ES-14
ES.1.7 	Welfare Benefits of Meeting the Primary and Secondary Standards	ES-19
ES.1.8 	Environmental Justice	ES-20
ES.2	Qualitative Assessment of the Remaining Air Quality Challenges	ES-22
ES.3	Results of Benefit-Cost Analysis	ES-24
ES.4	References	ES-29
CHAPTER 1: OVERVIEW AND BACKGROUND	1-1
Overview of the Proposal	1-1
Overview of the Regulatory Impact Analysis	1-1
1.1	Background	1-3
1.1.1	National Ambient Air Quality Standards	1-4
1.1.2	Role of Executive Orders in the Regulatory Impact Analysis	1-5
1.1.3	Nature of the Analysis	1-5
1.2	The Need for National Ambient Air Quality Standards	1-6
1.3	Design of the Regulatory Impact Analysis	1-7
1.3.1	Establishing the Baseline for Evaluation of Proposed and Alternative Standards	1-8
1.3.2	Cost Analysis Approach	1-9
1.3.3	Benefits Analysis Approach	1-10
1.3.4	Welfare Benefits of Meeting the Primary and Secondary Standards	1-10
1.4	Organization of the Regulatory Impact Analysis	1-10
1.5	References	1-12
CHAPTER 2: AIR QUALITY MODELING AND METHODS	2-1
Overview	2-1
2.1	PM2.5 Characteristics	2-2
2.1.1	PM2.5 Size and Composition	2-2
2.1.2	PM2.5 Regional Characteristics	2-5
2.1.3	PM2.5 Trends	2-7
2.2	Modeling PM2.5 in the Future	2-12
2.2.1	Air Quality Modeling Platform	2-13
<IP_ADDRESS>	Model Configuration	2-13
<IP_ADDRESS>	Emission Inventory	2-15
<IP_ADDRESS>	Model Evaluation	2-17
2.2.2	Future-Year PM2.5 Design Values	2-18
2.3	Calculating Emission Reductions for Meeting the Existing and Alternative Standard Levels	2-20
2.3.1	Developing Air Quality Ratios	2-20
2.3.2	Emission Reductions to Meet 12/35	2-24
2.3.3	Emission Reductions to Meet Alternative Standards	2-26
2.3.4	Limitations of Using Air Quality Ratios	2-28
2.4	Description of Air Quality Challenges in Select Areas	2-29
2.4.1	Delaware County, PA	2-29
2.4.2	Border Areas	2-31
<IP_ADDRESS>	Imperial County, CA	2-31
<IP_ADDRESS>	Cameron and Hidalgo County, TX	2-33
2.4.3	Small Mountain Valleys in the West	2-35
2.4.4	California Areas	2-39
<IP_ADDRESS>	San Joaquin Valley, CA	2-39
<IP_ADDRESS>	South Coast Air Basin, CA	2-43
<IP_ADDRESS>	San Luis Obispo and Napa, CA	2-47
2.5	Calculating PM2.5 Concentration Fields for Standard Combinations	2-49
2.5.1	Creating the PM2.5 Concentration Field for 2032	2-49
2.5.2	Creating Spatial Fields Corresponding to Meeting Standards	2-51
2.6	References	2-53
APPENDIX 2A: ADDITIONAL AIR QUALITY MODELING INFORMATION	2A-1
Overview	2A-1
2A.1	2016 CMAQ Modeling	2A-3
2A.1.1	Model Configuration	2A-3
2A.1.2	Model Performance Evaluation	2A-5
2A.2	Projecting PM2.5 DVs to 2032	2A-20
2A.2.1	Monitoring Data for PM2.5 Projections	2A-21
2A.2.2	Future-Year PM2.5 Design Values	2A-39
2A.3	Developing Air Quality Ratios and Estimating Emission Reductions	2A-45
2A.3.1	Developing Air Quality Ratios for Primary PM2.5 Emissions	2A-46
2A.3.2	Developing Air Quality Ratios for NOx in Southern California	2A-50
2A.3.3	Developing Air Quality Ratios for NOx in SJV, CA	2A-52
2A.3.4	Applying Air Quality Ratios to Estimate Emission Reductions	2A-54
2A.3.4.1 Emission Reductions Needed to Meet 12/35	2A-55
2A.3.4.2 Emission Reductions Needed to Meet 10/35, 9/35, 8/35, and 10/30	2A-59
2A.4	Calculating PM2.5 Concentration Fields for Standard Combinations	2A-64
2A.4.1	Creating the PM2.5 Concentration Field for 2032	2A-64
2A.4.2	Creating Spatial Fields Corresponding to Meeting Standards	2A-66
2A.5	Calculating DV Impacts for Further EGU Emission Reductions	2A-68
2A.5.1	Estimating the Influence of Additional Primary PM2.5 EGU Reductions	2A-68
2A.5.2	Estimating the Regional Influence of Additional SO2 and NOx EGU Emission Reductions	2A-69
2A.5.3	Estimating the Local Influence of Additional SO2 and NOx EGU Emission Reductions	2A-72
2A.6	References	2A-75
CHAPTER 3: CONTROL STRATEGIES AND PM2.5 EMISSIONS REDUCTIONS	3-1
Overview	3-1
3.1	Preparing the 12/35 g/m[3] Analytical Baseline	3-4
3.2	Illustrative Control Strategies and PM2.5 Emissions Reductions from the Analytical Baseline	3-5
3.2.1	Estimating PM2.5 Emissions Reductions Needed for Annual and 24-hour Alternative Standard Levels Analyzed	3-6
3.2.2	Applying Control Technologies and Measures	3-10
3.2.3	Estimates of PM2.5 Emissions Reductions Resulting from Applying Control Technologies and Measures	3-15
3.2.4	Potential Influence of EGU Emissions Reductions from Planned Retirements	3-22
3.2.5	Estimates of PM2.5 Emissions Reductions Still Needed after Applying Control Technologies and Measures	3-24
3.2.6	Qualitative Assessment of the Remaining Air Quality Challenges and Emissions Reductions Potentially Still Needed	3-31
<IP_ADDRESS>	Delaware County, Pennsylvania (Northeast)	3-32
<IP_ADDRESS>	Border Areas (Southeast, California)	3-34
<IP_ADDRESS>	Small Mountain Valleys (West)	3-37
<IP_ADDRESS>	California Areas	3-39
3.3	Limitations and Uncertainties	3-43
3.4	References	3-46
APPENDIX 3A: CONTROL STRATEGIES AND PM2.5 EMISSIONS REDUCTIONS	3A-1
Overview	3A-1
3A.1	Types of Control Measures	3A-1
3A.1.1	PM Control Measures for Non-EGU Point Sources	3A-1
3A.1.2	PM Control Measures for Non-point (Area) Sources	3A-2
3A.2	EGU Trends Reflected in EPA's Integrated Planning Model (IPM) v6 Platform, Summer 2021 Reference Case Projections	3A-3
3A.3	 Applying Control Technologies and Measures	3A-4
CHAPTER 4: ENGINEERING COST ANALYSIS AND QUALITATIVE DISCUSSION OF SOCIAL COSTS	4-1
Overview	4-1
4.1	Estimating Engineering Costs	4-2
4.1.1	Methods, Tools, and Data	4-3
4.1.2	Cost Estimates for the Control Strategies	4-4
4.2	Limitations and Uncertainties in Engineering Cost Estimates	4-11
4.3	Social Costs	4-13
4.4	References	4-17
APPENDIX 4A: ENGINEERING COST ANALYSIS	4A-1
Overview	4A-1
4A.1	Estimated Costs by County for Alternative Standard Levels	4A-1
CHAPTER 5: BENEFITS ANALYSIS APPROACH AND RESULTS	5-1
Overview	5-1
5.1	Updated Methodology Presented in the RIA	5-5
5.2	Human Health Benefits Analysis Methods	5-6
5.2.1	Selecting Air Pollution Health Endpoints to Quantify	5-7
5.2.2	Calculating Counts of Air Pollution Effects Using the Health Impact Function	5-9
5.2.3	Calculating the Economic Valuation of Health Impacts	5-11
5.3	Benefits Analysis Data Inputs	5-11
5.3.1	Demographic Data	5-12
5.3.2	Baseline Incidence and Prevalence Estimates	5-13
5.3.3	Effect Coefficients	5-16
<IP_ADDRESS>	PM2.5 Premature Mortality Effect Coefficients for Adults	5-17
5.3.4	Unquantified Human Health Benefits	5-19
5.3.5	Unquantified Welfare Benefits	5-22
<IP_ADDRESS>	Visibility Impairment Benefits	5-24
5.3.6	Climate Effects of PM2.5	5-25
<IP_ADDRESS>	Climate Effects of Carbonaceous Particles	5-26
<IP_ADDRESS>	Climate Effects: Summary and Conclusions	5-27
5.3.7	Economic Valuation Estimates	5-28
5.4	Characterizing Uncertainty	5-28
5.4.1	Monte Carlo Assessment	5-29
5.4.2	Sources of Uncertainty Treated Qualitatively	5-30
5.5	Benefits Results	5-31
5.5.1	Benefits of the Applied Control Strategies for the Alternative Combinations of Primary PM2.5 Standard Levels	5-31
5.6	Discussion	5-38
5.7	References	5-41
APPENDIX 5A: BENEFITS OF THE PROPOSED AND ALTERNATIVE STANDARD LEVELS	5A-1
Overview	5A-1
5A.1	Benefits of the Proposed and More Stringent Alternative Standard Levels of Primary PM2.5 Standards	5A-2
5A.2	 References	5A-8
CHAPTER 6: ENVIRONMENTAL JUSTICE	6-1
Introduction	6-1
6.1	Analyzing EJ Impacts in This Proposal	6-3
6.2	EJ Analysis of Exposures Under Current Standard and Alternative Standard Levels	6-6
6.2.1	Total Exposure	6-7
<IP_ADDRESS>	National	6-7
<IP_ADDRESS>	Regional	6-12
6.2.2	Exposure Changes	6-15
<IP_ADDRESS>	National	6-15
<IP_ADDRESS>	Regional	6-17
6.2.3	Proportional Changes in Exposure	6-20
<IP_ADDRESS>	National	6-21
<IP_ADDRESS>	Regional	6-22
6.3	EJ Analysis of Health Effects under Current Standards and Alternative Standard Levels    	6-23
6.3.1	Total Mortality Rates	6-25
<IP_ADDRESS>	National	6-25
<IP_ADDRESS>	Regional	6-26
6.3.2	Mortality Rate Changes	6-27
<IP_ADDRESS>	National	6-28
<IP_ADDRESS>	Regional	6-28
6.3.3	Proportional Changes in Mortality Rates	6-30
<IP_ADDRESS>	National	6-31
<IP_ADDRESS>	Regional	6-31
6.4	EJ Case Study of Exposure and Health Effects in Impacted Areas	6-32
6.4.1	Exposures	6-34
6.4.2	Mortality Rates	6-37
6.5	Summary	6-39
6.6	Environmental Justice Appendix	6-44
6.6.1	Input Information	6-44
<IP_ADDRESS>	EJ Exposure Analysis Input Data	6-44
<IP_ADDRESS>	EJ Health Effects Analysis Input Data	6-44
6.6.2	EJ Analysis of Total Exposures Associated with Meeting the Standards	6-47
<IP_ADDRESS>	National	6-47
<IP_ADDRESS>	Regional	6-49
6.6.3	EJ Analysis of Exposure Changes Associated with Meeting the Standards	6-53
<IP_ADDRESS>	National	6-53
<IP_ADDRESS>	Regional	6-55
6.6.4	Proportionality of Exposure Changes Associated with Meeting the Standards	6-58
<IP_ADDRESS>	National	6-58
<IP_ADDRESS>	Regional	6-59
6.6.5	EJ Analysis of Total Mortality Rates Associated with Meeting the Standards	6-61
<IP_ADDRESS>	National	6-61
<IP_ADDRESS>	Regional	6-62
6.6.6	EJ Analysis of Mortality Rate Change Associated with Meeting the Standards	6-64
<IP_ADDRESS>	National	6-64
<IP_ADDRESS>	Regional	6-65
6.6.7	Proportionality of Mortality Rate Changes Associated with Meeting the Standards   	6-67
<IP_ADDRESS>	National	6-67
<IP_ADDRESS>	Regional	6-68
6.7	References	6-70
CHAPTER 7: LABOR IMPACTS	7-1
Overview	7-1
7.1	Labor Impacts	7-1
7.2	References	7-6
CHAPTER 8: COMPARISON OF BENEFITS AND COSTS	8-1
Overview	8-1
8.1	Results	8-2
8.2	Limitations of Present Value Estimates	8-10
8.3	References	8-13
 LIST OF TABLESTABLE ES-1	Summary of PM2.5 Emissions Reductions Needed by Area in 2032 to Meet Current Primary Annual and 24-hour Standards of 12/35 g/m[3] (tons/year)	ES-7
Table ES-2	By Area, Summary of PM2.5 Emissions Reductions Needed, In Tons/Year and as Percent of Total Reduction Needed Nationwide, for Alternative Primary Standard Levels of 10/35 g/m[3], 10/30 g/m[3], 9/35 g/m[3], and 8/35 g/m[3] in 2032	ES-9
Table ES-3	Summary of PM2.5 Estimated Emissions Reductions from CoST by Area for the Alternative Primary Standard Levels of 10/35 g/m[3], 10/30 g/m[3], 9/35 g/m[3], and 8/35 g/m[3] in 2032 (tons/year)	ES-11
Table ES-4	Summary of PM2.5 Emissions Reductions Still Needed by Area for the Alternative Primary Standard Levels of 10/35 g/m[3], 10/30 g/m[3], 9/35 g/m[3], and 8/35 g/m[3] in 2032 (tons/year)	ES-12
Table ES-5	By Area, Summary of Annualized Control Costs for Alternative Primary Standard Levels of 10/35 g/m[3], 10/30 g/m[3], 9/35 g/m[3], and 8/35 g/m[3] for 2032 (millions of 2017$)	ES-14
Table ES-6 	Estimated Avoided PM-Related Premature Mortalities and Illnesses of the Control Strategies for the Alternative Primary PM2.5 Standard Levels for 2032 (95% Confidence Interval)	ES-17
Table ES-7	Estimated Monetized Benefits of the Control Strategies for Alternative Primary PM2.5 Standard Levels in 2032, Incremental to Attainment of 12/35 ug/m[3] (billions of 2017$)	ES-18
Table ES-8	Estimated Monetized Benefits by Region of the Control Strategies for the Alternative Primary PM2.5 Standard Levels in 2032, Incremental to Attainment of 12/35 ug/m[3] (billions of 2017$)	ES-19
Table ES-9	Summary of Counties by Bin that Still Need Emissions Reductions for Proposed Alternative Primary Standard Levels of 10/35 g/m[3] and 9/35 g/m[3]	ES-23
Table ES-10	Estimated Monetized Benefits, Costs, and Net Benefits of the Control Strategies Applied Toward the Primary Alternative Standard Levels of 10/35 g/m[3], 10/30 g/m[3], 9/35 g/m[3], and 8/35 g/m[3] in 2032 for the U.S. (millions of 2017$)	ES-26
Table ES-11	Summary of Present Values and Equivalent Annualized Values for Estimated Monetized Compliance Costs, Benefits, and Net Benefits of the Control Strategies Applied Toward the Proposed Primary Alternative Standard Level of 10/35 g/m[3] (millions of 2017$, 2032-2051, discounted to 2022 using 3 and 7 percent discount rates)	ES-27
Table ES-12	Summary of Present Values and Equivalent Annualized Values for Estimated Monetized Compliance Costs, Benefits, and Net Benefits of the Control Strategies Applied Toward the Proposed Primary Alternative Standard Level of 9/35 g/m[3] (millions of 2017$, 2032-2051, discounted to 2022 using 3 and 7 percent discount rates)	ES-28
Table 2-1	Annual and 24-Hour Air Quality Ratios for Primary PM2.5 Emissions	2-23
Table 2-2	Information on Areas with Challenging Residential Wood Combustion Issues	2-39
Table 2A-1	Definition of Statistics Used in the CMAQ Model Performance Evaluation	2A-8
Table 2A-2	CMAQ Performance Statistics for PM2.5 at AQS Sites in 2016	2A-10
Table 2A-3	CMAQ Performance Statistics for PM2.5 Sulfate at CSN and IMPROVE Sites in 2016       	2A-12
Table 2A-4	CMAQ Performance Statistics for PM2.5 Nitrate at CSN and IMPROVE Sites in 2016	2A-14
Table 2A-5	CMAQ Performance Statistics for PM2.5 EC at CSN and IMPROVE Sites in 2016         	2A-16
Table 2A-6	CMAQ Performance Statistics for PM2.5 OC at CSN and IMPROVE Sites in 2016        	2A-18
Table 2A-7	Wildfire Episodes and Counties Where Data Were Screened for Exclusion if PM2.5 Concentrations Exceeded the Extreme Value Threshold of 61 ug m[-3]	2A-23
Table 2A-8	PM2.5 DVs for 2032 Projection and 12/35 Analytical Baseline for the Highest DVs in the County for Counties with Annual 2032 DVs Greater 8 g m[-3] or 24-hour 2032 DVs Greater than 30 g m[-3]	2A-42
Table 2A-9	Annual and 24-Hour Air Quality Ratios for Primary PM2.5 Emissions	2A-48
Table 2A-10	County Groups for Calculating Air Quality Ratios for NOx Emission Changes in Southern California	2A-51
Table 2A-11	2032 PM2.5 DVs and NOx-adjusted PM2.5 DVs for the Highest Annual and 24-Hour DV Monitors in South Coast Counties	2A-52
Table 2A-12	2032 PM2.5 DVs and NOx-adjusted PM2.5 DVs for the Highest Annual and 24-Hour DV Monitors in SJV Counties	2A-54
Table 2A-13	Summary of Primary PM2.5 Emissions Reductions by County Needed to Meet the Existing Standards (12/35) for Counties with 2032 Annual DVs greater than 8 g m-3 or 24-Hour DVs Greater than 30 g m[-3]	2A-56
Table 2A-14	Primary PM2.5 Emission Reductions Needed to Meet the Alternative Standard Levels of 10/35, 10/30, 9/35, and 8/35 Relative to the 12/35 Analytical Baseline	2A-60
Table 2A-15	Primary PM2.5 Emission Reductions from EGUs Expected beyond 2032 Modeling Case and Estimated Impact on DVs for Counties Exceeding Alternative Standards in the 2032 Case	2A-69
Table 2A-16	SO2 and NOx Emission Reductions from EGUs Expected Beyond 2032 Modeling Case by County	2A-70
Table 2A-17	2032 PM2.5 DVs and Estimated Influence of Emission Reductions from EGUs in Franklin and Jefferson, MO, and Randolph, IL on DVs in Nearby Counties	2A-73
Table 2A-18	2032 PM2.5 DVs and Estimated Influence of Emission Reductions from EGUs in Clermont and Hamilton, OH on DVs in Nearby Counties	2A-74
Table 3-1	Summary of PM2.5 Emissions Reductions Needed by Area in 2032 to Meet Current Primary Annual and 24-hour Standards of 12/35 g/m[3] (tons/year)	3-5
Table 3-2	By Area, Summary of PM2.5 Emissions Reductions Needed, in Tons/Year and as Percent of Total Reductions Needed Nationwide, for Alternative Primary Standard Levels of 10/35 g/m[3], 10/30 g/m[3], 9/35 g/m[3], and 8/35 g/m[3] in 2032	3-8
Table 3-3	By Inventory Sector, Control Measures Applied in Analyses of the Current Standards and the Alternative Primary Standard Levels	3-14
Table 3-4	Summary of PM2.5 Estimated Emissions Reductions from CoST by Area for the Alternative Primary Standard Levels of 10/35 g/m[3], 10/30 g/m[3], 9/35 g/m[3], and 8/35 g/m[3] in 2032 (tons/year)	3-15
Table 3-5	Summary of PM2.5 Emissions and Estimated Emissions Reductions from CoST by Inventory Sector for Alternative Primary Standard Levels of 10/35 g/m[3], 10/30 g/m[3], 9/35 g/m[3], and 8/35 g/m[3] in 2032 (tons/year)	3-17
Table 3-6	Summary of Estimated Emissions Reductions from CoST by Inventory Sector and Control Technology for Alternative Primary Standard Levels of 10/35 g/m[3], 10/30 g/m[3], 9/35 g/m[3], and 8/35 g/m[3] in 2032 (tons/year)	3-19
Table 3-7	Summary of Estimated PM2.5 Emissions Reductions from CoST by Inventory Source Classification Code Sectors for Alternative Primary Standard Levels of 10/35 g/m[3], 10/30 g/m[3], 9/35 g/m[3], and 8/35 g/m[3] in 2032 (tons/year)	3-21
Table 3-8	Summary of PM2.5 Emissions Reductions Still Needed by Area for the Alternative Primary Standard Levels of 10/35 g/m[3], 10/30 g/m[3], 9/35 g/m[3], and 8/35 g/m[3] in 2032 (tons/year)	3-26
Table 3-9	Summary of PM2.5 Emissions Reductions Still Needed by Area and by County for the Alternative Primary Standard Levels of 10/35 g/m[3], 10/30 g/m[3], 9/35 g/m[3], and 8/35 g/m[3] in 2032 (tons/year)	3-27
Table 3-10	Summary of Counties by Bin that Still Need Emissions Reductions for Proposed Alternative Primary Standard Levels of 10/35 g/m[3] and 9/35 g/m[3]	3-32
Table 3-11	Summary of Estimated PM2.5 Emissions Reductions Needed and Emissions Reductions Identified by CoST for the West for the Proposed Primary Standard Level of 9/35 g/m[3] in 2032 (tons/year)	3-37
Table 3A-1	By Area and Emissions Inventory Sector, Control Measures Applied in Analyses of the Current Standards and Alternative Primary Standard Levels	3A-8
Table 3A-2	Summary of PM2.5 Estimated Emissions Reductions from CoST for the Northeast (57 counties) for Alternative Primary Standard Levels of 10/35 g/m[3], 10/30 g/m[3], 9/35 g/m[3], and 8/35 g/m[3] in 2032 (tons/year)	3A-11
Table 3A-3	Summary of PM2.5 Estimated Emissions Reductions from CoST for the Adjacent Counties in the Northeast (75 counties) for Alternative Primary Standard Levels of 10/35 g/m[3], 10/30 g/m[3], 9/35 g/m[3], and 8/35 g/m[3] in 2032 (tons/year)      	3A-13
Table 3A-4	Summary of PM2.5 Estimated Emissions Reductions from CoST for the Southeast (35 counties) for Alternative Primary Standard Levels of 10/35g/m[3], 10/30 g/m[3], 9/35 g/m[3], and 8/35 g/m[3] in 2032 (tons/year)	3A-16
Table 3A-5	Summary of PM2.5 Estimated Emissions Reductions from CoST for the Adjacent Counties in the Southeast (32 counties) for Alternative Primary Standard Levels of 10/35 g/m[3], 10/30 g/m[3], 9/35 g/m[3], and 8/35 g/m[3] in 2032 (tons/year)      	3A-17
Table 3A-6	Summary of PM2.5 Estimated Emissions Reductions from CoST for the West (36 counties) for Alternative Primary Standard Levels of 10/35 g/m[3], 10/30 g/m[3], 9/35 g/m[3], and 8/35 g/m[3] in 2032 (tons/year)	3A-18
Table 3A-7	Summary of PM2.5 Estimated Emissions Reductions from CoST for California (26 counties) for Alternative Primary Standard Levels of 10/35 g/m[3], 10/30 g/m[3], 9/35 g/m[3], and 8/35 g/m[3] in 2032 (tons/year)	3A-19
Table 3A-8 	Remaining PM2.5 Emissions and Potential Additional Reduction Opportunities        	3A-20
Table 4-1	By Area, Summary of Annualized Control Costs for Alternative Primary Standard Levels of 10/35 g/m[3], 10/30 g/m[3], 9/35 g/m[3], and 8/35 g/m[3] for 2032 (millions of 2017$)	4-5
Table 4-2	By Emissions Inventory Sector, Summary of Annualized Control Costs for Alternative Primary Standard Levels of 10/35g/m[3], 10/30 g/m[3], 9/35 g/m[3], and 8/35 g/m[3] for 2032 (millions of 2017$)	4-7
Table 4-3	By Area and by Emissions Inventory Sector, Summary of Annualized Control Costs for Alternative Primary Standard Levels of 10/35 g/m[3], 10/30 g/m[3], 9/35 g/m[3], and 8/35 g/m[3] for 2032 (millions of 2017$)	4-7
Table 4-4	By Control Technology, Summary of Annualized Control Costs for Alternative Primary Standard Levels of 10/35 g/m[3], 10/30 g/m[3], 9/35 g/m[3], and 8/35 g/m[3] for 2032 (millions of 2017$)	4-9
Table 4-5	By Emissions Inventory Sector and Control Technology, Summary of Annualized Control Costs for Alternative Primary Standard Levels of 10/35 g/m[3], 10/30 g/m[3], 9/35 g/m[3], and 8/35 g/m[3] for 2032 (millions of 2017$)	4-10
Table 4A-1	Summary of Estimated Annual Control Costs for the Northeast (57 counties) for Alternative Primary Standard Levels of 10/35 g/m[3], 10/30 g/m[3], 9/35 g/m[3], and 8/35 g/m[3] for 2032 (millions of 2017$)	4A-1
Table 4A-2	Summary of Estimated Annual Control Costs for Adjacent Counties in the Northeast (75 counties) for Alternative Primary Standard Levels of 10/35 g/m[3], 10/30 g/m[3], 9/35 g/m[3], and 8/35 g/m[3] for 2032 (millions of 2017$)	4A-3
Table 4A-3	Summary of Estimated Annual Control Costs for the Southeast (35 counties) for Alternative Primary Standard Levels of 10/35 g/m[3], 10/30 g/m[3], 9/35 g/m[3], and 8/35 g/m[3] for 2032 (millions of 2017$)	4A-5
Table 4A-4	Summary of Estimated Annual Control Costs for Adjacent Counties in the Southeast (32 counties) for Alternative Primary Standard Levels of 10/35 g/m[3], 10/30 g/m[3], 9/35 g/m[3], and 8/35 g/m[3] for 2032 (millions of 2017$)	4A-6
Table 4A-5	Summary of Estimated Annual Control Costs for the West (36 counties) for Alternative Primary Standard Levels of 10/35 g/m[3], 10/30 g/m[3], 9/35 g/m[3], and 8/35 g/m[3] for 2032 (millions of 2017$)	4A-7
Table 4A-6	Summary of Estimated Annual Control Costs for California (26 counties) for Alternative Primary Standard Levels of 10/35 g/m[3], 10/30 g/m[3], 9/35 g/m[3], and 8/35 g/m[3] for 2032 (millions of 2017$)	4A-8
Table 5-1	Estimated Monetized Benefits of the Applied Control Strategies for the Proposed and Alternative Combinations of Primary PM2.5 Standard Levels in 2032, Incremental to Attainment of 12/35 (billions of 2017$)	5-5
Table 5-2	Human Health Effects of Pollutants Potentially Affected by Attainment of the Primary PM2.5 NAAQS	5-9
Table 5-3	Baseline Incidence Rates for Use in Impact Functions	5-14
Table 5-4 	Causal Determinations Identified in Integrated Science Assessment for Oxides of Nitrogen, Oxides of Sulfur, and Particulate Matter -- Ecological Criteria 2020b	5-23
Table 5-5 	Estimated Avoided PM-Related Premature Mortalities and Illnesses of the Applied Control Strategies for the Proposed and More Stringent Alternative Primary PM2.5 Standard Levels for 2032 (95% Confidence Interval)	5-34
Table 5-6 	Monetized PM-Related Premature Mortalities and Illnesses of the Applied Control Strategies for the Proposed and More Stringent Alternative Primary PM2.5 Standard Levels for 2032 (Millions of 2017$, 3% discount rate; 95% Confidence Interval)      	5-35
Table 5-7 	Monetized PM-Related Premature Mortalities and Illnesses of the Applied Control Strategies for the Proposed and More Stringent Alternative Primary PM2.5 Standard Levels for 2032 (Millions of 2017$, 7% discount rate; 95% Confidence Interval)      	5-36
Table 5-8	Estimated Monetized Benefits of the Applied Control Strategies for the Proposed and More Stringent Alternative Combinations of Primary PM2.5 Standard Levels in 2032, Incremental to Attainment of 12/35 (billions of 2017$)	5-37
Table 5-9	Estimated Monetized Benefits by Region of the Applied Control Strategies for the Proposed and More Stringent Alternative Combinations of Primary PM2.5 Standard Levels in 2032, Incremental to Attainment of 12/35 (billions of 2017$)	5-38
Table 5A-1 	Estimated Avoided PM-Related Premature Mortalities and Illnesses of Meeting the Proposed and More Stringent Alternative Primary PM2.5 Standard Levels for 2032 (95% Confidence Interval)	5A-3
Table 5A-2 	Monetized Avoided PM-Related Premature Mortalities and Illnesses of Meeting the Proposed and More Stringent Alternative Primary PM2.5 Standard Levels for 2032 (Millions of 2017$, 3% discount rate; 95% Confidence Interval)	5A-4
Table 5A-3 	Monetized Avoided PM-Related Premature Mortalities and Illnesses of Meeting the Proposed and More Stringent Alternative Primary PM2.5 Standard Levels for 2032 (Millions of 2017$, 7% discount rate; 95% Confidence Interval)	5A-5
Table 5A-4	Total Estimated Monetized Benefits of Meeting the Proposed and More Stringent Alternative Primary Standard Levels in 2032, Incremental to Attainment of 12/35 (billions of 2017$)	5A-6
Table 5A-5	Total Estimated Monetized Benefits by Region of Meeting the Proposed and More Stringent Alternative Primary Standard Levels in 2032, Incremental to Attainment of 12/35 (billions of 2017$)	5A-7
Table 6-1 	Populations Included in the PM2.5 Exposure Analysis	6-7
Table 6-2	Hazard Ratios, Beta Coefficients, and Standard Errors (SE) from Di et al., 2017	6-45
Table 7-1 	Baseline Industry Employment	7-3
Table 7-2 	Employment per $1 Million Output (2017$) by Industry (4-digit NAICS)	7-5
Table 8-1	Estimated Monetized Benefits, Costs, and Net Benefits of the Control Strategies Applied Toward Primary Alternative Standard Levels of 10/35 g/m[3], 10/30 g/m[3], 9/35 g/m[3], and 8/35 g/m[3] in 2032 for the U.S. (millions of 2017$)	8-3
Table 8-2	Summary of Present Values and Equivalent Annualized Values for Estimated Monetized Compliance Costs of the Control Strategies Applied Toward the Primary Alternative Standard Levels of 10/35 g/m[3], 10/30 g/m[3], 9/35 g/m[3] 8/35 g/m3 (millions of 2017$, 2032-2051, discounted to 2022, 3 percent discount rate)	8-5
Table 8-3	Summary of Present Values and Equivalent Annualized Values for Estimated Monetized Compliance Costs of the Control Strategies Applied Toward the Primary Alternative Standard Levels of 10/35 g/m[3], 10/30 g/m[3], 9/35 g/m[3] 8/35 g/m3 (millions of 2017$, 2032-2051, discounted to 2022, 7 percent discount rate)	8-6
Table 8-4	Summary of Present Values and Equivalent Annualized Values for Estimated Monetized Benefits of the Control Strategies Applied Toward the Primary Alternative Standard Levels of 10/35 g/m[3], 10/30 g/m[3], 9/35 g/m[3] 8/35 g/m3 (millions of 2017$, 2032-2051, discounted to 2022, 3 percent discount rate)	8-7
Table 8-5	Summary of Present Values and Equivalent Annualized Values for Estimated Monetized Benefits of the Control Strategies Applied Toward the Primary Alternative Standard Levels of 10/35 g/m[3], 10/30 g/m[3], 9/35 g/m[3] 8/35 g/m3 (millions of 2017$, 2032-2051, discounted to 2022, 7 percent discount rate)	8-8
Table 8-6	Summary of Present Values and Equivalent Annualized Values for Estimated Monetized Compliance Costs, Benefits, and Net Benefits of the Control Strategies Applied Toward the Proposed Primary Alternative Standard Level of 10/35 g/m[3] (millions of 2017$, 2032-2051, discounted to 2022 using 3 and 7 percent discount rates)	8-9
Table 8-7	Summary of Present Values and Equivalent Annualized Values for Estimated Monetized Compliance Costs, Benefits, and Net Benefits of the Control Strategies Applied Toward the Proposed Primary Alternative Standard Level of 9/35 g/m[3] (millions of 2017$, 2032-2051, discounted to 2022 using 3 and 7 percent discount rates)	8-10
 LIST OF FIGURESFIGURE ES-1	Geographic Areas Used in Analysis	ES-6
Figure ES-2	Counties Projected to Exceed in Analytical Baseline for Alternative Standard Levels of 10/35 ug/m[3], 9/35 ug/m[3], and 8/35 ug/m[3]	ES-9
Figure ES-3	Counties that Still Need PM2.5 Emissions Reductions for Proposed Alternative Standard Level of 10/35 ug/m[3]	ES-12
Figure ES-4	Counties that Still Need PM2.5 Emissions Reductions for Proposed Alternative Standard Level of 9/35 ug/m[3]	ES-13
Figure 2-1	Annual Average PM2.5 Concentrations over the U.S. in 2019 Based on the Hybrid Satellite Modeling Approach of van Donkelaar et al. (2021)	2-5
Figure 2-2	Seasonally Weighted Annual Average PM2.5 Concentrations in the U.S. from 2000 to 2019 (406 sites)	2-8
Figure 2-3	National Emission Trends of PM2.5, PM10, and Precursor Gases from 1990 to 2017     	2-8
Figure 2-4	Annual Anthropogenic Source Sector Emission Totals (1000 tons per year) for NOx, SO2, and PM2.5 for 2016 and 2032	2-10
Figure 2-5	Gridded PM2.5 Concentrations over Selected Urban Areas Based on the 2032 Modeling Case Described Below with the Enhanced Voronoi Neighbor Averaging Approach	2-12
Figure 2-6	Map of the Outer 36US3 (36 x 36 km Horizontal Resolution) and Inner 12US2 (12 x 12 km Horizontal Resolution) Modeling Domains	2-14
Figure 2-7	Regional Groupings for Calculating Air Quality Ratios	2-22
Figure 2-8	Counties with Projected 2032 PM2.5 DVs that Exceed the 24-Hour (24-hr Only), Annual (Annual Only) or Both (Both) Existing Standards (12/35 g m[-3])	2-25
Figure 2-9	Counties with PM2.5 DVs that Exceed Alternative Annual (Annual Only), 24-Hour (24-hr Only), or Both (Both) Standards in the 12/35 Analytical Baseline	2-27
Figure 2-10	Total Primary PM2.5 Emission Reductions Needed to Meet the Alternative Standard Levels of 10/35, 10/30, 9/35, and 8/35 Relative to the 12/35 Analytical Baseline in the Eastern and Western U.S.	2-28
Figure 2-11	Location of the Chester Site in Relation to the Evonik Degussa and PQ Corporation Facilities	2-30
Figure 2-12	Imperial County and the Nonattainment Area	2-32
Figure 2-13	Nighttime Aerial View of Calexico, CA and Mexicali, MX	2-32
Figure 2-14	Annual Source Sector Emission Totals (1000 tons per year) for PM2.5 for 2016 and 2032 in Imperial County	2-33
Figure 2-15	Location of Mission and Brownsville Monitors in Hidalgo and Cameron County, respectively, with Annual Wind Patterns from Meteorological Measurements	2-34
Figure 2-16	Annual Source Sector Emission Totals (1000 tons per year) for PM2.5 for 2016 and 2032 in Cameron and Hidalgo County Combined	2-35
Figure 2-17	Air Pollution Layer Associated with a Temperature Inversion in Missoula, MT in November 2018	2-36
Figure 2-18	Plumas County, CA (Grey), Portola Nonattainment Area (Red), and City of Portola (Purple)	2-37
Figure 2-19	Lincoln County, MT (Grey), Libby Nonattainment Area (Red), and City of Libby (Purple)	2-37
Figure 2-20	San Joaquin Valley Nonattainment Area and Location of Highest PM2.5 Monitor in Bakersfield (06-029-0016)	2-40
Figure 2-21	Recent Annual PM2.5 DVs at the Highest SJV Monitor for Design Value Periods (e.g., 11-13: 2011-2013).  Dashed line is the 2012 Annual PM2.5 NAAQS Level (12 g m[-3])	2-41
Figure 2-22	Decrease in the Number of Days SJV Exceeded the 24-hr NAAQS Level (35 g m[-3])   	2-41
Figure 2-23	Annual Source Sector PM2.5 Emission Totals in SJV Counties for 2032 Modeling Case	2-43
Figure 2-24	South Coast Air Basin Nonattainment Area and Locations of Highest PM2.5 Monitors in Los Angeles (06-037-4008), Riverside (06-065-8005), and San Bernardino (06-071-0027)	2-44
Figure 2-25	Recent Annual PM2.5 DVs at the Highest South Coast Monitor for Design Value Periods (e.g., 11-13: 2011-2013).  Dashed line is the 2012 Annual PM2.5 NAAQS Level (12 g m[-3])	2-45
Figure 2-26	Annual Source Sector PM2.5 Emission Totals in the SoCAB Counties for 2032 Modeling Case	2-46
Figure 2-27	San Luis Obispo County and Location of Highest PM2.5 Monitor in Arroyo Grande (06-079-2007)	2-47
Figure 2-28	Recent and Projected Annual PM2.5 DVs at the Arroyo Grande Monitor (06-079-2007) in San Luis Obispo County for DV Periods (e.g., 11-13: 2011-2013; 32-32: Projected 2032 DV)	2-48
Figure 2-29	Napa County and Location of PM2.5 Monitor (06-055-0003)	2-49
Figure 2-30	PM2.5 Concentration for 2032 based on eVNA Method	2-51
Figure 2-31	PM2.5 Concentration Improvement Associated with Meeting 12/35 Relative to the 2032 case	2-52
Figure 2A-1	Map of the Outer 36US3 (36 x 36 km Horizontal Resolution) and Inner 12US2 (12 x 12 km Horizontal Resolution) Modeling Domains Used for the PM NAAQS RIA	2A-5
Figure 2A-2	U.S. Climate Regions (Karl and Koss, 1984) Used in the CMAQ Model Performance Evaluation	2A-8
Figure 2A-3	Comparison of CMAQ Predictions of PM2.5 and Observations at AQS Sites for County Highest PM2.5 Monitors with 2032 PM2.5 DVs Greater than 8/30	2A-9
Figure 2A-4	NMB in 2016 CMAQ Predictions of PM2.5 Components at CSN and IMPROVE Sites  	2A-11
Figure 2A-5	NMB in 2016 CMAQ Predictions of PM2.5 Components at CSN and IMPROVE Sites for Monitors in Counties with 2032 PM2.5 DVs Greater than 8/30	2A-11
Figure 2A-6	Visible Satellite Imagery from NASA's Worldview Platform Showing Smoke from the Camp Fire on 11/10/2018	2A-27
Figure 2A-7	Visible Satellite Imagery from NASA's Worldview Platform Showing Smoke from the North Bay/Wine Country Fires on 10/09/2017	2A-27
Figure 2A-8	Visible Satellite Imagery from NASA's Worldview Platform Showing Smoke from Fires Across the Pacific Northwest/Northern California on 08/29/2017	2A-28
Figure 2A-9 	Visible Satellite Imagery from NASA's Worldview Platform Showing Smoke from Fires in Washington and Oregon on 08/09/2018	2A-28
Figure 2A-10	Visible Satellite Imagery from NASA's Worldview Platform Showing Smoke from Fires in Montana on 08/19/2018	2A-29
Figure 2A-11	Visible Satellite Imagery from NASA's Worldview Platform Showing Smoke from Fires in Montana, Washington and Idaho on 08/22/2015	2A-29
Figure 2A-12	Visible Satellite Imagery from NASA's Worldview Platform Showing Smoke from the 416/Burro Complex Fires on 06/10/2018	2A-30
Figure 2A-13	Visible Satellite Imagery from NASA's Worldview Platform Showing Smoke from the Butte Fire on 09/11/2015	2A-30
Figure 2A-14	Visible Satellite Imagery from NASA's Worldview Platform Showing Smoke from the Carr/Mendocino/Ferguson Fires on 08/04/2018	2A-31
Figure 2A-15	Visible Satellite Imagery from NASA's Worldview Platform Showing Smoke from Fires in the Appalachians on 11/10/2016	2A-31
Figure 2A-16	Daily PM2.5 (in ug m[-3]) from a Subset of Monitors Impacted by the Camp Fire in November 2018	2A-32
Figure 2A-17	Daily PM2.5 (in ug m[-3]) from a Subset of Monitors Impacted by the North Bay/Wine Country Fires in October 2017	2A-33
Figure 2A-18	Daily PM2.5 (in ug m[-3]) from a Subset of Monitors Impacted by Fires in the Pacific Northwest/Northern California in August-September 2017	2A-34
Figure 2A-19	Daily PM2.5 (in ug m[-3]) from a Subset of Monitors Impacted by Fires in Washington and Oregon in July-August 2018	2A-35
Figure 2A-20 	Daily PM2.5 (in ug m[-3]) from the Monitors Impacted by Fires and Smoke in Montana in August 2018	2A-36
Figure 2A-21 	Daily PM2.5 (in ug m[-3]) from a Subset of Monitors Impacted by Fires in Montana, Washington and Idaho in August 2015	2A-37
Figure 2A-22	Daily PM2.5 (in ug m[-3]) from the Monitor in Plata, CO Impacted by the 416/Burro Fire Complex in June 2018	2A-37
Figure 2A-23	Daily PM2.5 (in ug m[-3]) from the Two monitors Impacted by the Butte Fire in September 2015	2A-38
Figure 2A-24	Daily PM2.5 (in ug m[-3]) from a Subset of Monitors Impacted by the Carr/Mendocino/Ferguson Fires in August 2018	2A-38
Figure 2A-25 	Daily PM2.5 (in ug m[-3]) from a Subset of Monitors Impacted by Fires in the Appalachians in November 2016	2A-39
Figure 2A-26	Counties with Projected 2032 PM2.5 DVs that Exceed the 24-Hour (24-hr Only), Annual (Annual Only) or Both the 24-Hour and Annual (Both) Standards for the Combination of Existing Standards (12/35)	2A-40
Figure 2A-27	Counties with PM2.5 DVs in the 12/35 Analytical Baseline that Exceed the 24-Hour (24-hr Only), Annual (Annual Only) or Both the 24-Hour and Annual (Both) Standards for the Combination of Existing Standards	2A-41
Figure 2A-28	Counties with 50% Reduction in Anthropogenic Primary PM2.5 Emissions in 2028 Sensitivity Modeling	2A-47
Figure 2A-29	Regional Groupings for Calculating Air Quality Ratios	2A-48
Figure 2A-30	Counties Used in Estimating the Relative Impact of Emissions in Core and Neighboring Counties	2A-49
Figure 2A-31	Counties with 50% Reduction in Anthropogenic NOx Emissions in 2028 Sensitivity Modeling	2A-51
Figure 2A-32	Total Primary PM2.5 Emission Reductions Needed to Meet the Alternative Standard Levels of 10/35, 10/30, 9/35, and 8/35 Relative to the 12/35 Analytical Baseline in the East and West	2A-60
Figure 2A-33	PM2.5 Concentration for 2032 based on eVNA Method	2A-66
Figure 2A-34	PM2.5 Concentration Improvement Associated with Meeting 12/35 Relative to the 2032 Case	2A-67
Figure 2A-35 	PM2.5 Counties with 50% Reductions of SO2 Emissions in the 2028 CMAQ Sensitivity Simulations (Green) and Eastern States Considered in the EGU Sensitivity Analysis (Red)	2A-71
Figure 2A-36	Distributions of the Estimated Changes in Annual PM2.5 DVs in the Eastern U.S. Associated with NOx and SO2 EGU Emission Reductions in the Eastern US Beyond the 2032 Modeling Case	2A-72
Figure 2A-37	County Group in 2028 Sensitivity Modeling Used in Estimating the Response of DVs to EGU Emission Changes in Franklin and Jefferson, MO, and Randolph, IL	2A-73
Figure 2A-38	County Group in 2028 Sensitivity Modeling Used in Estimating the Response of DVs to EGU Emission Changes in Clermont and Hamilton, OH	2A-74
Figure 3-1	Geographic Areas Used in Analysis	3-4
Figure 3-2	Counties Projected to Exceed in Analytical Baseline for Alternative Standard Levels of 10/35 g/m[3], 9/35 g/m[3], and 8/35 g/m[3]	3-8
Figure 3-3	Counties Projected to Exceed in Analytical Baseline for Alternative Standard Levels of 10/30 g/m[3]	3-9
Figure 3-4	PM2.5 Emissions Reductions and Costs Per Ton (CPT) in 2032 (tons, 2017$)	3-13
Figure 3-5	Counties that Still Need PM2.5 Emissions Reductions for Proposed Alternative Standard Level of 10/35 g/m[3]	3-29
Figure 3-6	Counties that Still Need PM2.5 Emissions Reductions for Proposed Alternative Standard Level of 9/35 g/m[3]	3-29
Figure 3-7	Counties that Still Need PM2.5 Emissions Reductions for More Stringent Alternative Standard Level of 8/35 g/m[3]	3-30
Figure 3-8	Counties that Still Need PM2.5 Emissions Reductions for More Stringent Alternative Standard Level of 10/30 g/m[3]	3-30
Figure 5-1	Data Inputs and Outputs for the BenMAP-CE Model	5-12
Figure 6-1	Heat Map of National Average Annual PM2.5 Concentrations (ug/m[3]) by Demographic for Current and Alternative PM NAAQS Levels (10/35, 10/30, 9/35, and 8/35) After Application of Controls	6-9
Figure 6-2	National Distributions of Annual PM2.5 Concentrations by Demographic for Current and Alternative PM NAAQS Levels After Application of Controls	6-12
Figure 6-3	Heat Map of Regional Average Annual PM2.5 Concentrations (ug/m[3]) by Demographic for Current (12/35) and Alternative PM NAAQS Levels (10/35, 10/30, 9/35, and 8/35) After Application of Controls	6-13
Figure 6-4	Regional Distributions of Annual PM2.5 Concentrations by Demographic for Current and Alternative PM NAAQS Levels After Application of Controls	6-14
Figure 6-5	Heat Map of National Reductions in Average Annual PM2.5 Concentrations (ug/m[3]) for Demographic Groups When Moving from Current to Alternative PM NAAQS Levels After Application of Controls	6-16
Figure 6-6	National Distributions of Annual PM2.5 Concentration Reductions for Demographic Groups When Moving from Current to Alternative PM NAAQS Levels After Application of Controls	6-17
Figure 6-7	Heat Map of Regional Reductions in PM2.5 Concentrations (ug/m[3]) for Demographic Groups When Moving from Current to Alternative PM NAAQS Levels After Application of Controls	6-18
Figure 6-8	Regional Distributions of Total PM2.5 for Demographic Groups When Moving from Current to Alternative PM NAAQS Levels After Application of Controls	6-19
Figure 6-9	Heat Map of National Percent Reductions in Average Annual PM2.5 Concentrations (ug/m[3]) for Demographic Groups When Moving from Current to Alternative PM NAAQS Levels After Application of Controls	6-22
Figure 6-10	Heat Map of Regional Percent Reductions in Average Annual PM2.5 Concentrations (ug/m[3]) for Demographic Groups When Moving from Current (12/35) to Alternative PM NAAQS Level (10/35, 10/30, 9/35, and 8/35 After Application of Controls	6-23
Figure 6-11	Heat Map of National Average Annual Total Mortality Rates (per 100K) for Demographic Groups for Current and Alternative PM NAAQS Levels After Application of Controls	6-26
Figure 6-12	National Distributions of Total Annual Mortality Rates for Demographic Groups for Current and Alternative PM NAAQS Levels After Application of Controls	6-26
Figure 6-13	Heat Map of Regional Average Annual Total Mortality Rates (per 100K) for Demographic Groups for Current and Alternative PM NAAQS Levels After Application of Controls	6-27
Figure 6-14	Regional Distributions of Total Annual Mortality Rates for Demographic Groups for Current and Alternative PM NAAQS Levels After Application of Controls	6-27
Figure 6-15	Heat Map of National Average Annual Mortality Rate Reductions (per 100k) for Demographic Groups When Moving from Current to Alternative PM NAAQS Levels After Application of Controls	6-28
Figure 6-16	National Distributions of Annual Mortality Rate Reductions for Demographic Groups When Moving from Current to Alternative PM NAAQS Levels After Application of Controls	6-28
Figure 6-17	Heat Map of Regional Average Annual Mortality Rate Reductions (per 100k) for Demographic Groups When Moving from Current and Alternative PM NAAQS Levels After Application of Controls	6-29
Figure 6-18	Regional Distributions of Annual Mortality Rate Reductions for Demographic Groups When Moving from Current to Alternative PM NAAQS Levels After Application of Controls	6-30
Figure 6-19	Heat Map of National Average Percent Mortality Rate Reductions (per 100k People) for Demographic Groups When Moving from Current to Alternative PM NAAQS Levels After Application of Controls	6-31
Figure 6-20	Heat Map of Regional Average Percent Mortality Rate Reductions (per 100k) for Demographic Groups When Moving from Current to Alternative PM NAAQS Levels After Application of Controls	6-31
Figure 6-21	Map of Areas in which PM2.5 Concentrations Change when Moving from 12/35 to 9/35 After Application of Controls	6-33
Figure 6-22	Heat Map of National Average Annual PM2.5 Concentrations and Concentration Changes (ug/m[3]) by Demographic for 12/35, 9/35, and 12/35-9/35 in the Subset of Areas that Do and Do Not Experience Changes in Air Quality When Moving from 12/35 to 9/35	6-35
Figure 6-23	Heat Map of Regional Average Annual PM2.5 Concentrations and Concentration Changes (ug/m[3]) by Demographic for 12/35, 9/35, and 12/35-9/35 in the Subset of Areas that Do and Do Not Experience Changes in Air Quality When Moving from 12/35 to 9/35	6-36
Figure 6-24	Heat Map of National Percent Reductions in Average Annual PM2.5 Concentrations for Demographic Groups in the Subset of Areas in which PM2.5 Concentrations Change When Moving from 12/35 to 9/35	6-37
Figure 6-25	Heat Map of National Average Annual Total Mortality Rates and Mortality Rate Reductions (per 100K) by Demographic for 12/35, 9/35, and 12/35-9/35 in the Subset of Areas that Do and Do Not Experience Changes in Air Quality when Moving from 12/35 to 9/35	6-38
Figure 6-26	Heat Map of Regional Average Annual Total Mortality Rates and Mortality Rate Reductions (per 100K) by Demographic for 12/35 9/35, and 12/35-9/35, in the Subset of Areas that Do and Do Not Change When Moving from 12/35-9/35	6-38
Figure 6-27	Heat Map of National and Regional Percent Reductions in Average Annual Total Mortality Rates (per 100K) by Demographic in the Subset of Areas in which PM2.5 Concentrations Change When Moving from 12/35-9/35	6-39
Figure 6-28	Heat Map of National Average Annual PM2.5 Concentrations (ug/m[3]) Associated Either with Control Strategies (Controls) or with Meeting the Standards (Standards) by Demographic for Current (12/35) and Alternative PM NAAQS Levels (10/35, 10/30, 9/35, and 8/35)	6-48
Figure 6-29	National Distributions of Annual PM2.5 Concentrations Associated Either with Control Strategies or with Meeting the Standards by Demographic for Current and Alternative PM NAAQS Levels	6-49
Figure 6-30	Heat Map of Regional Average Annual PM2.5 Concentrations (ug/m[3]) Associated Either with Control Strategies or with Meeting the Standards by Demographic for Current and Alternative PM NAAQS Levels	6-51
Figure 6-31	Regional Distributions of Annual PM2.5 Concentrations Associated Either with Control Strategies or with Meeting the Standards by Demographic for Current and Alternative PM NAAQS Levels	6-52
Figure 6-32	Heat Map of National Average Annual Reductions in PM2.5 Concentrations (ug/m[3]) Associated Either with Control Strategies or with Meeting the Standards by Demographic When Moving from Current to Alternative PM NAAQS Levels	6-53
Figure 6-33	National Distributions of Annual Reductions in PM2.5 Concentrations Associated Either with Control Strategies or with Meeting the Standards by Demographic When Moving from Current to Alternative PM NAAQS Levels	6-54
Figure 6-34	Heat Map of National Reductions in Average Annual PM2.5 Concentrations (ug/m[3]) Associated Either with Control Strategies or with Meeting the Standards by Demographic When Moving from Current to Alternative PM NAAQS Levels	6-56
Figure 6-35	National Distributions of Reductions in Annual PM2.5 Concentrations Associated Either with Control Strategies or with Meeting the Standards by Demographic When Moving from Current to Alternative PM NAAQS Levels	6-57
Figure 6-36	Heat Map of National Percent Reductions in Average Annual PM2.5 Concentrations (ug/m[3]) Associated Either with Control Strategies or with Meeting the Standards by Demographic When Moving From Current to Alternative PM NAAQS Levels	6-58
Figure 6-37	Heat Map of Regional Percent Reductions in Average Annual PM2.5 Concentrations (ug/m[3]) Associated Either with Control Strategies or with Meeting the Standards by Demographic When Moving From Current to Alternative PM NAAQS Levels	6-60
Figure 6-38	Heat Map of National Average Annual Total Mortality Rates (per 100K People) Associated Either with Control Strategies or with Meeting the Standards by Demographic for Current and Alternative PM NAAQS Levels	6-61
Figure 6-39	National Distributions of Total Mortality Rates Associated Either with Control Strategies or with Meeting the Standards by Demographic for Current and Alternative PM NAAQS Levels	6-62
Figure 6-40	Heat Map of Regional Average Annual Total Mortality Rates (per 100K People) Associated Either with Control Strategies or with Meeting the Standards by Demographic for Current and Alternative PM NAAQS Levels	6-62
Figure 6-41	Regional Distributions of Total Mortality Rates Associated Either with Control Strategies or with Meeting the Standards by Demographic for Current and Alternative PM NAAQS Levels	6-63
Figure 6-42	Heat Map of National Average Annual Total Mortality Rate Reductions (per 100K People) Associated Either with Control Strategies or with Meeting the Standards by Demographic When Moving from Current to Alternative PM NAAQS Levels	6-64
Figure 6-43	National Distributions of Annual Total Mortality Rate Reductions Associated Either with Control Strategies or with Meeting the Standards by Demographic When Moving from Current to Alternative PM NAAQS Levels	6-65
Figure 6-44	Heat Map of Regional Average Annual Total Mortality Rate Reductions (per 100K People) Associated Either with Control Strategies or with Meeting the Standards by Demographic When Moving from Current to Alternative PM NAAQS Levels	6-65
Figure 6-45	Regional Distributions of Average Annual Total Mortality Rate Reductions Associated Either with Control Strategies or with Meeting the Standards by Demographic for When Moving from Current to Alternative PM NAAQS Levels	6-66
Figure 6-46	Heat Map of National Percent Changes in Average Mortality Rate Reductions Associated Either with Control Strategies or with Meeting the Standards by Demographic When Moving from Current to Alternative PM NAAQS Levels	6-67
Figure 6-47	Heat Map of Regional Percent Reductions in Average Mortality Rate Reductions Associated Either with Control Strategies or with Meeting the Standards by Demographic When Moving from Current to Alternative PM NAAQS Levels	6-69
 EXECUTIVE SUMMARY
 Overview of the Proposal
In setting primary and secondary national ambient air quality standards (NAAQS), the Environmental Protection Agency's (EPA) responsibility under the law is to establish standards that protect public health and welfare. The Clean Air Act (CAA) requires the EPA, for each criteria pollutant, to set standards that protect public health with "an adequate margin of safety" and public welfare from "any known or anticipated adverse effects." As interpreted by the Agency and the courts, the CAA requires the EPA to base the decisions for primary standards on health considerations only; economic factors cannot be considered. The prohibition against considering cost in the setting of the primary air quality standards does not mean that costs, benefits, or other economic consequences are unimportant. The Agency believes that consideration of costs and benefits is an essential decision-making tool for the efficient implementation of these standards. The impacts of costs, benefits, and efficiency are considered by the States when they make decisions regarding what timelines, strategies, and policies are appropriate for their circumstances.
On June 10, 2021, the EPA announced its decision to reconsider the 2020 Particulate Matter (PM) NAAQS final action. The EPA is reconsidering the December 2020 decision because the available scientific evidence and technical information indicate that the current standards may not be adequate to protect public health and welfare, as required by the CAA. The EPA has concluded that the existing annual primary PM2.5 standard for PM, set at a level of 12.0 ug/m[3], is not requisite to protect public health with an adequate margin of safety. The EPA Administrator is proposing to revise the existing standard to provide increased public health protection. Specifically, the EPA Administrator is proposing to revise the level of the standard within the range of 9-10 ug/m[3], while soliciting comment on levels down to 8 ug/m[3] and up to 11 ug/m[3]. The primary 24-hour PM2.5 standard provides protection against exposures to short-term "peak" concentrations of PM2.5 in ambient air. The EPA Administrator is proposing to retain the primary 24-hour PM2.5 standard at its current level of 35 ug/m[3] and is soliciting comment on revising the level of the standard to as low as 25 ug/m[3].
The EPA has also concluded that the existing secondary PM standards are requisite to protect public welfare from known or anticipated effects and is proposing to retain the secondary standards for PM. Specifically, for the secondary annual PM2.5 standard, the EPA Administrator is proposing to retain the existing standard of 15.0 ug/m[3]. For the secondary 24-hour PM2.5 standard, the EPA Administrator is proposing to retain the existing standard of 35 ug/m[3]; however, the Administrator is soliciting comment on revising the level of the standard to as low as 25 ug/m[3]. For the secondary 24-hour PM10 standard, the EPA Administrator is proposing to retain the existing standard of 150 ug/m[3].
 Overview of the Regulatory Impact Analysis
Per Executive Orders 12866 and 13563 and the guidelines of the Office of Management and Budget's (OMB) Circular A-4, in this Regulatory Impact Analysis (RIA) we are analyzing the proposed annual and current 24-hour alternative standard levels of 10/35 g/ - m - [3] -  and 9/35 g/m[3], as well as the following two more stringent alternative standard levels: (1) an alternative annual standard level of 8 g/ - m - [3] -  in combination with the current 24-hour standard (i.e., 8/35 g/ - m - [3] - ), and (2) an alternative 24-hour standard level of 30 g/ - m - [3] in combination with the proposed annual standard level of 10 g/ - m - [3] -  (i.e., 10/30 g/ - m - [3] - ). Because the EPA is proposing that the current secondary PM standards be retained, we did not evaluate alternative secondary standard levels. The RIA includes the following chapters: Chapter 2: Emissions, Air Quality Modeling and Methods; Chapter 3: Control Strategies and PM2.5 Emissions Reductions; Chapter 4: Engineering Cost Analysis and Social Costs; Chapter 5: Benefits Analysis Approach and Results; Chapter 6: Environmental Justice Impacts; Chapter 7: Labor Impacts; and Chapter 8: Comparison of Benefits and Costs.
The RIA presents estimates of the costs and benefits of applying illustrative national control strategies in 2032 after implementing existing and expected regulations and assessing emissions reductions to meet the current annual and 24-hour particulate matter NAAQS (12/35 g/ - m - [3]). The selection of 2032 as the analysis year in the RIA does not predict or prejudge attainment dates that will ultimately be assigned to individual areas under the CAA. The CAA contains a variety of potential attainment dates and flexibility to move to later dates, provided that the date is as expeditious as practicable. For the purposes of this analysis, the EPA assumes that it would likely finalize designations for the proposed particulate matter NAAQS in late 2024. Furthermore, also for the purposes of this analysis and depending on the precise timing of the effective date of those designations, the EPA assumes that nonattainment areas classified as Moderate would likely have to attain in late 2032. As such, we selected 2032 as the primary year of analysis.
      The analyses in this RIA rely on national-level data (emissions inventory and control measure information) for use in national-level assessments (air quality modeling, control strategies, environmental justice, and benefits estimation). However, the ambient air quality issues being analyzed are highly complex and local in nature, and the results of these national-level assessments therefore contain uncertainty. It is beyond the scope of this RIA to develop detailed local information for the areas being analyzed, including populating the local emissions inventory, obtaining local information to increase the resolution of the air quality modeling, and obtaining local information on emissions controls, all of which would reduce some of the uncertainty in these national-level assessments. For example, having more refined data would be ideal for agricultural dust and burning, prescribed burning, and non-point (area) sources due to their large contribution to primary PM2.5 emissions and the limited availability of emissions controls.
 ES.1		Design of the Regulatory Impact Analysis
The goal of this RIA is to provide estimates of the potential costs and benefits of the illustrative national control strategies in 2032. Because States are ultimately responsible for implementing strategies to meet alternative standard levels, this RIA provides insights and analysis of a limited number of illustrative control strategies that states might adopt to implement a proposed standard level.
We developed our projected baselines for emissions and air quality for 2032. To estimate the costs and benefits of the illustrative national control strategies for the proposed and more stringent annual and 24-hour PM2.5 alternative standard levels, we first prepared an analytical baseline for 2032 that assumes full compliance with the current standards of 12/35 g/m[3]. From that analytical baseline, we estimate PM2.5 emissions reductions needed to reach the proposed and alternative annual and 24-hour PM2.5 standard levels and then analyze illustrative control strategies that areas might employ.
Because PM2.5 concentrations are most responsive to direct PM emissions reductions, for the illustrative control strategies we analyze direct, local PM2.5 emissions reductions by individual counties. For the eastern U.S. where counties are relatively small and terrain is relatively flat, we identified potential PM2.5 emissions reductions within each county and in adjacent counties within the same state, where needed. As discussed in Chapter 3, Section 3.2.2, when we applied the emissions reductions from adjacent counties, we used a g/m[3] per ton PM2.5 air quality ratio that was four times less responsive than the ratio used when applying in-county emissions reductions. Because the counties in the western U.S. are generally large and the terrain is more complex, we only identified potential PM2.5 emissions reductions within each county.
We then prepare illustrative control strategies. We apply end-of-pipe control technologies to non-electric generating unit (non-EGU) stationary sources (e.g., fabric filters, electrostatic precipitators, venturi scrubbers) and control measures to nonpoint (area) sources (e.g., installing controls on charbroilers), to residential wood combustion sources (e.g., converting woodstoves to gas logs), and for area fugitive dust emissions (e.g., paving unpaved roads) in analyzing PM2.5 emissions reductions. The estimated PM2.5 emissions reductions from these control applications do not fully account for all the emissions reductions needed to reach the proposed and more stringent alternative standard levels in some counties in the northeast, southeast, west, and California. In Chapter 2, Section 2.4 and Chapter 3, Section 3.2.6, we discuss the remaining air quality challenges for areas in the northeast and southeast, as well as in the west and California for the proposed alternative standard levels of 10/35 g/ - m - [3] -  and 9/35 g/ - m - [3] - ; the areas include a county in Pennsylvania affected by local sources, counties in border areas, counties in small western mountain valleys, and counties in California's air basins and districts. The characteristics of the air quality challenges for these areas include features of local source-to-monitor impacts, cross-border transport, effects of complex terrain in the west, and identifying wildfire influence on projected PM2.5 DVs that could potentially qualify for exclusion as atypical, extreme, or unrepresentative events (U.S. EPA, 2019a). Lastly, we estimate the engineering costs and human health benefits associated with the illustrative control strategies, as well as assess environmental justice considerations.
Chapter 2, Section 2.1.3, includes discussions of historical and projected emissions trends for direct PM2.5 and precursor emissions (i.e., SO2, NOx, VOC, and ammonia), as well as of the "urban increment" of consistently higher PM2.5 concentrations over urban areas. We did not apply controls to EGUs or mobile sources beyond what is reflected in the projections between 2016 and 2032. The projections reflect SO2 and NOX emissions decreases between 2016 and 2032 -- over this period (1) NOX emissions are projected to decrease by 3.8 million tons (40 percent), with the greatest reductions from mobile source and EGU emissions inventory sectors, and (2) SO2 emissions are projected to decrease by 1 million tons (38 percent), with the greatest reductions from the EGU emissions inventory sector.
    ES.1.1	 Establishing the Analytical Baseline
To project air quality to the future, the Community Multiscale Air Quality Modeling System (CMAQ) model was applied to simulate air quality over the U.S. during 2016 and for a case with emissions representative of 2032. In the 2032 projections, PM2.5 design values (DVs) exceeded the current standards for some counties in the west. As described in Chapter 2, Section 2.3.2, we adjusted the PM2.5 DVs for 2032 to account for emissions reductions needed to attain the current annual and 24-hour PM2.5 standards of 12/35 g/m - [3] to form the 12/35 g/ - m - [3] -  analytical baseline; it is from this baseline that we estimate the incremental costs and benefits associated with control strategies for the proposed and more stringent alternative standard levels relative to the current standards. The analytical baseline reflects, among other existing regulations, the Revised Cross-State Air Pollution Rule Update, the Safer Affordable Fuel Efficient (SAFE) Vehicles Final Rule for Model Years 2021-2026, the Standards of Performance for Greenhouse Gas Emissions from New, Modified, and Reconstructed Stationary Sources: EGUs, and the Mercury and Air Toxics Standards. For a more complete list of regulations, please see Chapter 2, Section 2.2.1.
We present results throughout the RIA by northeast, southeast, west, and California, and Figure ES-1 includes a map of the U.S. with these areas identified. Table ES-1 presents a summary of the PM2.5 emissions reductions needed by area to meet the current standards to form the 12/35 g/ - m - [3] -  analytical baseline.

Figure ES-1	Geographic Areas Used in Analysis

Table ES-1	Summary of PM2.5 Emissions Reductions Needed by Area in 2032 to Meet Current Primary Annual and 24-hour Standards of 12/35 g/ - m - [3] -  (tons/year)
Area
                                     12/35
Northeast
                                       0
Southeast
                                       0
West
                                     2,298
CA
                                     6,907
Total
                                     9,205
Eighteen counties need PM2.5 emissions reductions to meet the current standards in 2032  -  9 counties in California and 9 counties in the west. The counties in California include several counties in the San Joaquin Valley Air Pollution Control District and the South Coast Air Quality Management District, as well as Plumas County in Northern California and Imperial County in southern California. No counties in the northeast or southeast U.S. need PM2.5 emissions reductions to meet the current annual and 24-hour standards.
    ES.1.2 	Estimating PM2.5 Emissions Reductions Needed for Annual and 24-hour Alternative Standard Levels Analyzed
      We apply regional PM2.5 air quality ratios to estimate PM2.5 DVs at air quality monitor locations and then again to estimate the emissions reductions needed to reach the proposed and more stringent annual and 24-hour alternative standard levels analyzed. To develop air quality ratios that relate the change in DV in a county to the change in primary PM2.5 emissions in that county, we performed air quality sensitivity modeling with reductions in primary PM2.5 emissions in selected counties. More specifically, we conducted a 2028 CMAQ sensitivity modeling simulation with 50 percent reductions in primary PM2.5 emissions from anthropogenic sources in counties with annual 2028 DVs greater than 8 g/m[3]. We divided the change in annual and 24-hour PM2.5 DVs in these counties by the change in emissions in the respective counties to determine the air quality ratio at individual monitors.
      We developed representative air quality ratios for regions of the U.S. from the ratios at individual monitors as in the 2012 PM - 2.5 NAAQS review (U.S. EPA, 2012). These regions are shown in Chapter 2, Figure 2-7, and the air quality ratios for primary PM2.5 emissions used in estimating the emission reductions needed to just meet the alternative standard levels analyzed are listed in Chapter 2, Table 2-1. We estimated the emissions reductions needed to just meet the alternative standard levels analyzed using the primary PM2.5 air quality ratios in combination with the required incremental change in concentration. Chapter 2, Section 2.3.1 includes a brief discussion of developing air quality ratios and estimated emissions reductions needed to just meet the alternative standard levels analyzed, and Appendix 2A, Section 2A.3 includes more detailed discussions.
Table ES-2 presents a summary of the estimated emissions reductions needed by area to reach the annual and 24-hour alternative standard levels. For each alternative standard level, Table ES-2 also includes an area's percent of the total estimated emissions reductions needed nationwide to reach that alternative standard level in all locations. For example, for the proposed standard level of 10/35 g/m[3], California's 10,128 estimated tons needed is 81 percent of the total estimated emissions reductions needed nationwide to meet 10/35 g/m[3]. See Appendix 2A, Table 2A-14 for the estimated PM2.5 emissions reductions, from the analytical baseline, needed by county for the alternative standard levels analyzed. Figure ES-2 shows the counties projected to exceed the annual and 24-hour alternative standard levels of 10/35 g/ - m - [3] - , 9/35 g/ - m - [3] - , and 8/35 g/ - m - [3] -  in the analytical baseline. Additional information on the air quality modeling, as well as information about projected future DVs, DV targets, and air quality ratios is provided in Chapter 2 and Appendix 2A.
Table ES-2	By Area, Summary of PM2.5 Emissions Reductions Needed, In Tons/Year and as Percent of Total Reduction Needed Nationwide, for Alternative Primary Standard Levels of 10/35 g/ - m - [3] - , 10/30 g/ - m - [3] - , 9/35 g/ - m - [3] - , and 8/35 g/ - m - [3] -  in 2032
Area
                                     10/35
                                     10/30
                                     9/35
                                     8/35
Northeast
                                     1,068
                                     1,221
                                     6,996
                                    30,843
Southeast
                                      474
                                      474
                                     4,088
                                    18,028
West
                                      820
                                     7,852
                                     3,078
                                     9,708
CA
                                    10,128
                                    12,230
                                    17,750
                                    28,293
Total
                                    12,490
                                    21,776
                                    31,912
                                    86,872

Area
                                     10/35
                                     10/30
                                     9/35
                                     8/35
Northeast
                                      9%
                                      6%
                                      22%
                                      36%
Southeast
                                      4%
                                      2%
                                      13%
                                      21%
West
                                      7%
                                      36%
                                      10%
                                      11%
CA
                                      81%
                                      56%
                                      56%
                                      33%

Figure ES-2	Counties Projected to Exceed in Analytical Baseline for Alternative Standard Levels of 10/35 g/ - m - [3] - , 9/35 g/ - m - [3] - , and 8/35 g/ - m - [3] -
For each alternative standard level, Chapter 2, Section 2.3.3 includes a discussion of the number of counties that are projected to exceed in 2032, and Figure 2-9 includes maps of counties projected to exceed along with the number of counties. The following summarizes the number of counties, by alternative standard level, in each geographic area that need PM2.5 emissions reductions from the analytical baseline.
 10/35 g/ - m - [3] - -- 24 counties need PM2.5 emissions reductions. This includes 4 counties in the northeast, 2 counties in the southeast, 3 counties in the west, and 15 counties in California.
 10/30 g/ - m - [3] - -- 47 counties need PM2.5 emissions reductions. This includes 4 counties in the northeast, 2 counties in the southeast, 23 counties in the west, and 18 counties in California.
 9/35 g/ - m - [3] -  -- 51 counties need PM2.5 emissions reductions. This includes 14 counties in the northeast, 8 counties in the southeast, 8 counties in the west, and 21 counties in California.
 8/35 g/ - m - [3] -  -- 141 counties need PM2.5 emissions reductions. This includes 57 counties in the northeast, 35 counties in the southeast, 24 counties in the west, and 25 counties in California.
    ES.1.3 	Control Strategies and PM2.5 Emissions Reductions
We identified control measures using the EPA's Control Strategy Tool (CoST) (U.S. EPA, 2019b) and the control measures database. CoST estimates emissions reductions and engineering costs associated with control technologies or measures applied to non-electric generating unit (non-EGU) point, non-point (area), residential wood combustion, and area fugitive dust sources of air pollutant emissions by matching control measures to emissions sources by source classification code (SCC). For these control strategy analyses, to maximize the number of emissions sources we included a lower emissions source size threshold (5 tons per year) and a higher marginal cost per ton threshold ($160,000/ton) than reflected in prior NAAQS RIAs (25-50 tpy, $15,000-$20,000/ton). In Chapter 3, Figure 3-4 shows estimated PM2.5 emissions reductions for several emissions source sizes and cost thresholds up to the $160,000/ton marginal cost threshold. We selected the $160,000/ton marginal cost threshold because it is around that cost level that (i) road paving controls get selected and applied, and (ii) opportunities for additional emissions reductions diminish.
By area, Table ES-3 includes a summary of the estimated emissions reductions from control applications for the alternative standards analyzed. These emissions reductions were used to create the PM2.5 spatial surfaces described in Appendix 2A, Section 2A.4.2 for the human health benefits assessments presented in Chapter 5. See Chapter 3, Tables 3-5 through 3-7 for additional summaries of estimated PM2.5 emissions reductions from CoST.
Table ES-3	Summary of PM2.5 Estimated Emissions Reductions from CoST by Area for the Alternative Primary Standard Levels of 10/35 g/ - m - [3] - , 10/30 g/ - m - [3] - , 9/35 g/ - m - [3] - , and 8/35 g/ - m - [3] -  in 2032 (tons/year)

                          PM2.5 Emissions Reductions
Area
                                     10/35
                                     10/30
                                     9/35
                                     8/35
Northeast
                                     1,070
                                     1,222
                                     6,334
                                    19,142
Northeast (Adjacent Counties)
                                       0
                                       0
                                     1,737
                                    15,440
Southeast
                                      475
                                      475
                                     3,040
                                    12,212
Southeast (Adjacent Counties)
                                       0
                                       0
                                      194
                                     4,892
West
                                      224
                                     2,206
                                      947
                                     4,711
CA
                                     1,792
                                     2,481
                                     2,958
                                     4,925
Total
                                     3,561
                                     6,384
                                    15,210
                                    61,321
   Note: Totals may not match related tables due to independent rounding. In the northeast and southeast when we applied the emissions reductions from adjacent counties, we used a ppb/ton PM2.5 air quality ratio that was four times less responsive than the ratio used when applying in-county emissions reductions.

    ES.1.4 	Estimates of PM2.5 Emissions Reductions Still Needed after Applying Control Technologies and Measures
The estimated PM2.5 emissions reductions from the control strategies do not fully account for all the emissions reductions needed to reach the proposed and more stringent alternative standard levels in some counties in the northeast, southeast, west, and California. By area, Table ES-4 includes a summary of the estimated emissions reductions still needed after control applications for the alternative standards analyzed. See Chapter 3, Table 3-9 for an additional summary of estimated emissions reductions still needed. Figure ES-3 and Figure ES-4 show the counties that still need emissions reductions after control applications for the proposed alternative standard levels of 10/35g/m[3] and 9/35 g/m[3]. Section ES.2 below includes a qualitative discussion of the remaining air quality challenges. In addition, Chapter 2, Section 2.4 and Chapter 3, Section 3.2.6 provide more detailed discussions of these air quality challenges.
Table ES-4	Summary of PM2.5 Emissions Reductions Still Needed by Area for the Alternative Primary Standard Levels of 10/35 g/ - m - [3] - , 10/30 g/ - m - [3] - , 9/35 g/ - m - [3] - , and 8/35 g/ - m - [3] -  in 2032 (tons/year)
Region
                                     10/35
                                     10/30
                                     9/35
                                     8/35
Northeast
                                       0
                                       0
                                      238
                                     6,741
Southeast
                                       0
                                       0
                                      994
                                     4,780
West
                                      595
                                     5,651
                                     2,132
                                     5,023
CA
                                     8,336
                                     9,749
                                    14,793
                                    23,368
Total
                                     8,931
                                    15,400
                                    18,157
                                    39,912

Figure ES-3	Counties that Still Need PM2.5 Emissions Reductions for Proposed Alternative Standard Level of 10/35 g/ - m - [3] -

Figure ES-4	Counties that Still Need PM2.5 Emissions Reductions for Proposed Alternative Standard Level of 9/35 g/ - m - [3] -
    ES.1.5 	Engineering Costs
The EPA also used CoST and the control measures database to estimate engineering control costs. We estimated costs for non-EGU point, non-point (area), residential wood combustion, and area fugitive dust sources of air pollutant emissions. CoST calculates engineering costs using one of two different methods: (1) an equation that incorporates key operating unit information, such as unit design capacity or stack flow rate, or (2) an average annualized cost-per-ton factor multiplied by the total tons of reduction of a pollutant. The engineering cost analysis uses the equivalent uniform annual costs (EUAC) method, in which annualized costs are calculated based on the equipment life for the control measure and the interest rate incorporated into a capital recovery factor. Annualized costs represent an equal stream of yearly costs over the period the control technology is expected to operate. The cost estimates reflect the engineering costs annualized using a 7 percent interest rate.
By area, Table ES-5 includes a summary of estimated control costs from control applications for the alternative standard levels analyzed. See Chapter 4, Tables 4-2 through 4-5 for additional summaries of estimated control costs associated with the control strategies.
Table ES-5	By Area, Summary of Annualized Control Costs for Alternative Primary Standard Levels of 10/35 g/ - m - [3] - , 10/30 g/ - m - [3] - , 9/35 g/m - [3] - , and 8/35 g/ - m - [3] -  for 2032 (millions of 2017$)
Area
                                     10/35
                                     10/30
                                     9/35
                                     8/35
Northeast
                                     $7.3
                                     $12.8
                                    $183.5
                                    $560.2
Northeast (Adjacent Counties)
                                      $0
                                      $0
                                     $22.3
                                    $539.7
Southeast
                                     $4.1
                                     $4.1
                                     $50.4
                                    $250.6
Southeast (Adjacent Counties)
                                      $0
                                      $0
                                     $18.2
                                    $186.5
West
                                     $19.0
                                    $150.0
                                     $34.2
                                    $121.8
CA
                                     $64.1
                                     $90.4
                                     $84.7
                                    $162.9
Total
                                     $94.5
                                    $257.2
                                    $393.3
                                   $1,821.7

For the proposed alternative standard level of 10/35 g/ - m - [3] - , the majority of the estimated costs are incurred in California because 15 of the 24 counties that need emissions reductions are located in California. Looking at the more stringent alternative standard level of 10/30 g/m - [3] - , in the west an additional 20 counties need emissions reductions and estimated costs increase significantly; estimated costs for the proposed alternative standard level of 9/35 g/ - m - [3] are higher than for 10/35 g/ - m - [3] -  -  but lower than for 10/30 g/ - m - [3] -  -  in this area -  - . For alternative standard levels of 9/35 g/ - m - [3] -  and 8/35 g/m - [3] - , more controls are available to apply in the northeast and the southeast as compared to California and the west. Therefore, the estimated costs for the northeast and southeast are higher for 9/35 g/ - m - [3] -  and 8/35 g/m - [3].
In the northeast and southeast when we applied the emissions reductions from adjacent counties, we applied a ratio of 4:1. That is, four tons of PM2.5 emissions reductions would be required from an adjacent county to reduce one ton of emissions reduction needed in a given county. Application of this ratio contributes to the higher estimated cost estimates for alternative standard levels of 9/35 g/ - m - [3] -  and 8/35 g/m - [3] - .

    ES.1.6 	Human Health Benefits
We estimate the quantity and economic value of air pollution-related effects using a "damage-function." This approach quantifies counts of air pollution-attributable cases of adverse health outcomes and assigns dollar values to those counts, while assuming that each outcome is independent of one another. We construct this damage function by adapting primary research -- specifically, air pollution epidemiology studies and economic value studies -- from similar contexts. This approach is sometimes referred to as "benefits transfer."
We use the environmental Benefits Mapping and Analysis Program -- Community Edition (BenMAP-CE) software program to quantify counts of premature deaths and illnesses attributable to photochemical modeled changes in annual mean PM2.5 for the year 2032 using a health impact function (Sacks et al., 2018). A health impact function combines information regarding: the concentration-response relationship between air quality changes and the risk of a given adverse outcome; the population exposed to the air quality change; the baseline rate of death or disease in that population; and the air pollution concentration to which the population is exposed.
After quantifying the change in adverse health impacts, the final step is to estimate the economic value of these avoided impacts. The appropriate economic value for a change in a health effect depends on whether the health effect is viewed ex ante (before the effect has occurred) or ex post (after the effect has occurred). Reductions in ambient concentrations of air pollution generally lower the risk of future adverse health effects by a small amount for a large population. The appropriate economic measure is therefore ex ante willingness-to-pay (WTP) for changes in risk. However, epidemiological studies generally provide estimates of the relative risks of a particular health effect avoided due to a reduction in air pollution. A convenient way to use this data in a consistent framework is to convert probabilities to units of avoided statistical incidences. This measure is calculated by dividing individual WTP for a risk reduction by the related observed change in risk.
Applying the impact and valuation functions to the estimated changes in PM2.5 yields estimates of the changes in physical damages (e.g., premature mortalities, cases of hospital admissions and emergency department visits) and the associated monetary values for those changes. Table ES-6 presents the estimated avoided incidences of PM-related illnesses and premature mortality resulting from emissions reductions associated with the application of the illustrative control strategies for each of the alternative standard levels in 2032. Table ES-7 and Table ES-8 present a summary of the monetized benefits associated with emissions reductions from the application of the illustrative control strategies for each of the alternative standard levels, both nationally and by region, thereby allowing the comparison of cost and benefits of the application of the illustrative controls. As mentioned above and discussed in Chapter 3, Section 3.2.5, the estimated PM2.5 emissions reductions from control applications do not fully account for all the emissions reductions needed to reach the proposed and more stringent alternative standard levels in some counties in the northeast, southeast, west, and California. In Chapter 2, Section 2.4 and Chapter 3, Section 3.2.6, we discuss the remaining air quality challenges for areas in the northeast and southeast, as well as in the west and California for the proposed alternative standard levels of 10/35 g/ - m - [3] -  and 9/35 g/ - m - [3] - . In Appendix 5A a set of tables summarizes the benefits associated with identifying all of the emissions reductions needed to reach the proposed and more stringent alternative standard levels. For Table ES-7 and Table ES-8, the monetized value of unquantified effects is represented by adding an unknown "B" to the aggregate total. This B represents both uncertainty and a bias in this analysis, as it reflects health and welfare benefits that we are unable to quantify. Note that not all known PM health effects could be quantified or monetized.
Table ES-6 	Estimated Avoided PM-Related Premature Mortalities and Illnesses of the Control Strategies for the Alternative Primary PM2.5 Standard Levels for 2032 (95% Confidence Interval)
Avoided Mortality[a]
                           10/35 g/ - m - [3] -
                             10/30 g/m - [3] -
                            9/35 g/ - m - [3] -
                            8/35 g/ - m - [3] -
Pope III et al., 2019 (adult mortality ages 18-99 years)
                                     1,700
                               (1,200 to 2,100)
                                     1,900
                               (1,400 to 2,400)
                                     4,200
                               (3,000 to 5,300)
                                     9,200
                               (6,600 to 12,000)
Wu et al., 2020 (adult mortality ages 65-99 years)
                                      810
                                 (710 to 900)
                                      920
                                (810 to 1,000)
                                     2,000
                               (1,800 to 2,200)
                                     4,400
                               (3,900 to 4,900)
Woodruff et al., 2008 (infant mortality)
                                      1.6
                                (-0.99 to 4.0)
                                      1.8
                                 (-1.1 to 4.6)
                                      4.7
                                 (-3.0 to 12)
                                      11
                                 (-6.9 to 28)
Avoided Morbidity
                          10/35g/ - m - [3] -
                          10/30g/ - m - [3] -
                           9/35g/ - m - [3] -
                           8/35g/ - m - [3] -
Hospital admissions -- cardiovascular (age > 18)
                                      140
                                 (100 to 170)
                                      150
                                 (110 to 190)
                                      310
                                 (230 to 400)
                                      660
                                 (480 to 840)
Hospital admissions -- respiratory
                                      93
                                  (31 to 150)
                                      100
                                  (35 to 170)
                                      210
                                  (74 to 350)
                                      460
                                 (160 to 740)
ED visits--cardiovascular
                                      260
                                 (-100 to 610)
                                      290
                                 (-110 to 670)
                                      630
                                (-240 to 1,500)
                                     1,400
                                (-530 to 3,200)
ED visits -- respiratory
                                      490
                                 (95 to 1,000)
                                      530
                                (100 to 1,100)
                                     1,200
                                (240 to 2,600)
                                     2,700
                                (540 to 5,700)
Acute Myocardial Infarction
                                      29
                                  (5.9 to 17)
                                      32
                                  (19 to 45)
                                      67
                                  (39 to 94)
                                      143
                                  (83 to 200)
Cardiac arrest
                                      15
                                 (-5.9 to 33)
                                      16
                                 (-6.6 to 37)
                                      34
                                  (-14 to 76)
                                      72
                                 (-29 to 160)
Hospital admissions-- Alzheimer's Disease
                                      360
                                 (270 to 440)
                                      390
                                 (300 to 480)
                                      850
                                (640 to 1,000)
                                     1,900
                               (1,500 to 2,400)
Hospital admissions-- Parkinson's Disease
                                      48
                                  (25 to 70)
                                      54
                                  (28 to 79)
                                      120
                                  (63 to 180)
                                      270
                                 (140 to 390)
Stroke
                                      55
                                  (14 to 94)
                                      61
                                  (16 to 110)
                                      130
                                  (33 to 220)
                                      270
                                  (71 to 470)
Lung cancer
                                      65
                                  (20 to 110)
                                      73
                                  (22 to 120)
                                      150
                                  (46 to 250)
                                      320
                                  (99 to 530)
Hay Fever/Rhinitis
                                    15,000
                               (3,500 to 25,000)
                                    16,000
                               (4,000 to 28,000)
                                    35,000
                               (8,500 to 60,000)
                                    75,000
                              (18,000 to 130,000)
Asthma Onset
                                     2,200
                               (2,100 to 2,300)
                                     2,500
                               (2,400 to 2,600)
                                     5,400
                               (5,100 to 5,600)
                                    11,000
                              (11,000 to 12,000)
Asthma symptoms  -  Albuterol use
                                    310,000
                             (-150,000 to 750,000)
                                    350,000
                             (-170,000 to 850,000)
                                    740,000
                            (-360,000 to 1,800,000)
                                   1,600,000
                            (-780,000 to 3,900,000)
Lost work days
                                    110,000
                              (97,000 to 130,000)
                                    130,000
                             (110,000 to 150,000)
                                    270,000
                             (230,000 to 310,000)
                                    580,000
                             (490,000 to 660,000)
Minor restricted-activity days
                                    680,000
                             (550,000 to 800,000)
                                    750,000
                             (610,000 to 890,000)
                                   1,600,000
                           (1,300,000 to 1,900,000)
                                   3,400,000
                           (2,700,000 to 4,000,000)
Note: Values rounded to two significant figures.
a Reported here are two alternative estimates of the number of premature deaths among adults due to long-term exposure to PM2.5. These values should not be added to one another.
Table ES-7	Estimated Monetized Benefits of the Control Strategies for Alternative Primary PM2.5 Standard Levels in 2032, Incremental to Attainment of 12/35 ug/m[3] (billions of 2017$)
                               Benefits Estimate
                 10 ug/m[3] Annual &
35 ug/m[3] 24-hour
                 10 ug/m[3] Annual &
30 ug/m[3] 24-hour
                  9 ug/m[3] Annual &
35 ug/m[3] 24-hour
                  8 ug/m[3] Annual &
35 ug/m[3] 24-hour
Economic value of avoided PM2.5-related morbidities and premature deaths using PM2.5 mortality estimate from Pope III et al., 2019
  3% discount rate
                                    $17 + B
                                    $20 + B
                                    $43 + B
                                    $95 + B
  7% discount rate
                                    $16 + B
                                    $18 + B
                                    $39 + B
                                    $86 + B
Economic value of avoided PM2.5-related morbidities and premature deaths using PM2.5 mortality estimate from Wu et al., 2020
  3% discount rate
                                   $8.5 + B
                                   $9.6 + B
                                    $21 + B
                                    $46 + B
  7% discount rate
                                   $7.6 + B
                                   $8.6 + B
                                    $19 + B
                                    $41 + B
Note: Rounded to two significant figures. Avoided premature deaths account for over 98% of monetized benefits here, which are discounted over the SAB-recommended 20-year segmented lag. It was not all possible to quantify all benefits due to data limitations in this analysis. "B" is the sum of all unquantified health and welfare benefits.

Table ES-8	Estimated Monetized Benefits by Region of the Control Strategies for the Alternative Primary PM2.5 Standard Levels in 2032, Incremental to Attainment of 12/35 ug/m[3] (billions of 2017$)
                               Benefits Estimate
                                    Region
                                 10 ug/m[3]
                       Annual &
35 ug/m[3] 24-hour
                                 10 ug/m[3]
                       Annual &
30 ug/m[3] 24-hour
                                  9 ug/m[3]
                       Annual &
35 ug/m[3] 24-hour
                  8 ug/m[3] Annual &
35 ug/m[3] 24-hour
Economic value of avoided PM2.5-related morbidities and premature deaths using PM2.5 mortality estimate from Pope III et al., 2019
  3% discount rate
                                  California
                                    $13 + B
                                    $14 + B
                                    $17 + B
                                    $23 + B

                                   Northeast
                                   $2.3 + B
                                   $2.6 + B
                                    $15 + B
                                    $40 + B

                                   Southeast
                                   $1.8 + B
                                   $1.8 + B
                                   $8.8 + B
                                    $22 + B

                                     West
                                  $0.018 + B
                                   $1.1 + B
                                   $2.2 + B
                                    $11 + B
  7% discount rate
                                  California
                                    $12 + B
                                    $13 + B
                                    $16 + B
                                    $21 + B

                                   Northeast
                                    $2 + B
                                   $2.3 + B
                                    $13 + B
                                    $36 + B

                                   Southeast
                                   $1.6 + B
                                   $1.6 + B
                                   $7.9 + B
                                    $20 + B

                                     West
                                  $0.016 + B
                                    $1 + B
                                    $2 + B
                                   $9.5 + B
Economic value of avoided PM2.5-related morbidities and premature deaths using PM2.5 mortality estimate from Wu et al., 2020
  3% discount rate
                                  California
                                   $6.5 + B
                                   $6.9 + B
                                   $8.4 + B
                                    $11 + B

                                   Northeast
                                   $1.1 + B
                                   $1.3 + B
                                   $7.3 + B
                                    $19 + B

                                   Southeast
                                   $0.84 + B
                                   $0.84 + B
                                   $4.1 + B
                                    $10 + B

                                     West
                                  $0.0092 + B
                                   $0.56 + B
                                   $1.1 + B
                                   $5.1 + B
  7% discount rate
                                  California
                                   $5.8 + B
                                   $6.2 + B
                                   $7.5 + B
                                    $10 + B

                                   Northeast
                                    $1 + B
                                   $1.2 + B
                                   $6.6 + B
                                    $17 + B

                                   Southeast
                                   $0.75 + B
                                   $0.75 + B
                                   $3.6 + B
                                   $9.2 + B

                                     West
                                  $0.0082 + B
                                   $0.5 + B
                                   $0.97 + B
                                   $4.6 + B
Note: Rounded to two significant figures. Avoided premature deaths account for over 98% of monetized benefits here, which are discounted over the SAB-recommended 20-year segmented lag. It was not possible to quantify all benefits due to data limitations in this analysis. "B" is the sum of all unquantified health and welfare benefits.

    ES.1.7 	Welfare Benefits of Meeting the Primary and Secondary Standards
Even though the primary standards are designed to protect against adverse effects to human health, the emissions reductions would have welfare benefits in addition to the direct health benefits. The term welfare benefits covers both environmental and societal benefits of reducing pollution. Welfare benefits of the primary PM standard include reduced vegetation effects resulting from PM exposure, reduced ecological effects from particulate matter deposition and from nitrogen emissions, reduced climate effects, and changes in visibility. This RIA does not assess welfare effects quantitatively; this is discussed further in Chapter 5.
    ES.1.8 	Environmental Justice
Environmental justice (EJ) concerns for each rulemaking are unique and should be considered on a case-by-case basis, and EPA's EJ Technical Guidance states that "[t]he analysis of potential EJ concerns for regulatory actions should address three questions:
 Are there potential EJ concerns associated with environmental stressors affected by the regulatory action for population groups of concern in the baseline?
 Are there potential EJ concerns associated with environmental stressors affected by the regulatory action for population groups of concern for the regulatory option(s) under consideration?
 For the regulatory option(s) under consideration, are potential EJ concerns created or mitigated compared to the baseline?"
To address these questions, EPA developed an analytical approach that considers the purpose and specifics of the proposed rulemaking, as well as the nature of known and potential exposures and impacts. For the proposal, we quantitatively evaluate the potential for disparities in PM2.5 exposures and mortality effects across different demographic populations under illustrative control strategies associated with implementation of the current standard (12/35 g/m[3], or baseline) and potential alternative PM2.5 standard levels (10/35 mg/m[3], 10/30 g /m[3], 9/35 g /m[3], and 8/35 g /m[3]) at the national and regional levels. Specifically, we provide information on totals, changes, and proportional changes in 1) exposures, in terms of annual average PM2.5 concentrations and 2) premature mortality, in terms of rates per 100,000 individuals across and within various demographic populations. Each type of analysis has strengths and weaknesses, but when taken together, can respond to the above three questions from EPA's Environmental Justice (EJ) Technical Guidance.
Beginning with the first question, under the 12/35g/m[3] analytical baseline, some populations are predicted to experience disproportionately higher annual PM2.5 exposures nationally than the reference (overall) population, both in terms of aggregated average exposure and across the distribution of air quality. Specifically, Hispanics, Asians, Blacks, and those less educated (no high school) have higher national annual exposures, on average and across the distributions, than both the overall reference population or other populations (e.g., non-Hispanic, White, and more educated). In particular, the Hispanic population is estimated to experience the highest exposures, both on average and across PM2.5 concentration distributions, of all demographic groups analyzed. These disproportionalities are also observed at the regional level, though to different extents.
In response to the second question, while a lower standard level would be predicted to reduce PM2.5 exposures and mortality rates across all demographic groups, disparities seen in the baseline are also reflected in the standard levels under consideration. However, as to the third question, for most populations assessed, PM2.5 exposure disparities are mitigated in the illustrative air quality scenarios reflecting control strategies (10/35 g/m[3], 10/30 g/m[3], 9/35 g/m[3], and 8/35 g/m[3]) as compared to the baseline (12/35 g/m[3]), and more so as the alternative standard levels become more stringent. At the national scale, Hispanics, Asians, and those less educated are estimated to see greater proportional reductions in PM2.5 concentrations than reference populations under all alternative standard levels evaluated, with proportional reductions increasing as the alternative standard levels decrease. However, exposures in the Black population are estimated to proportionally decrease on par with exposures in reference population. Considering the four geographic regions (northeast, southeast, west, and California), proportionally greater reductions in PM2.5 concentrations experienced by Asian, Hispanic, and less educated populations are most notable in the southeast and California, whereas PM2.5 concentration reductions among Black populations tend to be proportionally larger than among the reference population in California, the west, and the northeast, especially under the proposed alternative standard level of 9/35 g/m[3] and the more stringent alternative standard level of 8/35 g/m[3]. In Section <IP_ADDRESS> we provide some insight into exposures in areas with remaining air quality challenges (i.e., without sufficient emissions control strategies to reach alternative standard levels).
In terms of health effects, some populations are also predicted to experience disproportionately higher rates of premature mortality than the reference population under the baseline scenario (question 1). Black populations are estimated to have the highest national and regional PM2.5-attributable mortality rates, both on average and across population distributions. Differential PM2.5 exposures for this population in some parts of the country, which may contribute to higher magnitude concentration-response relationships between exposure and premature mortality, as well as other underlying health factors that may increase susceptibility to adverse outcomes among Black populations. Health disparities associated with the baseline scenario are also predicted for the proposed and more stringent standard levels (question 2), although as the alternative standard levels become increasingly stringent, differences in mortality rates across demographic groups decline, particularly for the proposed and more stringent alternative standard levels evaluated (9/35 g/m3 and 8/35g/m[3]) (question 3).
 ES.2	Qualitative Assessment of the Remaining Air Quality Challenges
For the proposed alternative standard levels of 10/35 g/ - m - [3] -  and 9/35 g/ - m - [3], the analysis indicates that some areas in the northeast and southeast, as well as in the west and California may still need emissions reductions (Figure ES-3 and Figure ES-4). As discussed in Chapters 2 and 3, the remaining air quality challenges for the proposed alternative standard levels can be grouped into the following "bins": Delaware County, Pennsylvania, border areas, small mountain valleys, and California areas. By bin, Table ES-9 below summarizes the counties that may need additional emissions reductions for the proposed alternative standard -  levels.
Table ES-9	Summary of Counties by Bin that Still Need Emissions Reductions for Proposed Alternative Primary Standard Levels of 10/35 g/ - m - [3] -  and 9/35 g/ - m - [3] -
Bin
Area
Counties[a] for
10/35 mg/ - m - [3]
Additional Counties[a] for
9/35 mg/ - m - [3] -
Delaware County, Pennsylvania
Northeast
--
Delaware County, PA
Border Areas
Southeast
--
Cameron County, TX
Hidalgo County, TX

California
Imperial County, CA
--
Small Mountain Valleys
West
Plumas County, CA
Lemhi County, ID
Shoshone County, ID
Lincoln County, MT
Benewah County, ID
California Areas

Fresno County, CA (SJVAPCD)
Kern County, CA (SJVAPCD)
Kings County, CA (SJVAPCD)
Los Angeles County, CA (SCAQMD)
Madera County, CA (SJVAPCD)
Merced County, CA (SJVAPCD)
Riverside County, CA (SCAQMD)
San Bernardino County, CA (SCAQMD)
Stanislaus County, CA (SJVAPCD)
Tulare County, CA (SJVAPCD)
Napa County, CA (BAAQMD)
San Joaquin County, CA (SJVAPCD)
San Luis Obispo County, CA
Note: For California counties that are part of multi-county air districts, the relevant district is indicated in parentheses; BAAQMD = Bay Area Air Quality Management District, SCAQMD = South Coast Air Quality Management District, and SJVAPCD= San Joaquin Valley Air Pollution Control District.
[a] The following counties have no identified PM2.5 emissions reductions because available controls were applied for the current standard of 12/35 g/m[3] and additional controls were not available: Imperial, Kern, Kings, Lemhi, Plumas, Riverside, San Bernardino, Shoshone, and Tulare.

The characteristics of the air quality challenges for these areas include features of local source-to-monitor impacts, cross-border transport, effects of complex terrain in the west and California, and identifying wildfire influence on projected PM2.5 DVs that could potentially qualify for exclusion as atypical, extreme, or unrepresentative events (U.S. EPA, 2019a). For bin-specific detailed discussions of these air quality challenges, see Chapter 2, Section 2.4. Further, for each bin for discussions of the estimated PM2.5 emissions reductions needed, the control strategy analyses and controls applied, the estimated PM2.5 emissions reductions still needed after the application of controls, and the bin-specific air quality challenges, see Chapter 3, Section 3.2.6.
For Delaware County, Pennsylvania, a more detailed local analysis of the local source emissions reductions impacts is needed. For the border areas that may be influenced by cross-border emissions, more detailed analyses of international transport emissions are needed to assess the relevance of Section 179B of the Clean Air Act. For the small mountain valleys in the west that are influenced by the temperature inversions, residential wood combustion, and wildfire smoke additional detailed analyses that reflect local PM2.5 response factors, emissions inventory information, and control measure information are needed. In addition, more detailed analyses are needed to characterize the influence of wildfires on PM2.5 concentrations and the potential for some wildfires to qualify for exclusion as atypical, extreme, or unrepresentative events.
Lastly, the air quality in the SJVAPCD and SCAQMD is influenced by complex terrain and meteorological conditions that are best characterized with a high-resolution air quality modeling platform developed for the specific conditions of the air basins. Specific, local information on control measures to reduce emissions from agricultural dust and burning, prescribed burning, and many of the non-point (area) emissions sources (e.g., commercial and residential cooking) is needed given the magnitude of emissions from these sources in these areas. Further, more detailed analyses are needed to characterize the influence of wildfires on PM2.5 concentrations and the potential for some wildfires to qualify for exclusion as atypical, extreme, or unrepresentative events.
 ES.3	Results of Benefit-Cost Analysis
As discussed above and in Chapter 3, Section 3.2.5, the estimated PM2.5 emissions reductions from control applications do not fully account for all the emissions reductions needed to reach the proposed and more stringent alternative standard levels in some counties in the northeast, southeast, west, and California. In Chapter 2, Section 2.4 and Chapter 3, Section 3.2.6, we discuss the remaining air quality challenges for areas in the northeast and southeast, as well as in the west and California for the proposed alternative standard levels of 10/35 g/ - m - [3] -  and 9/35 g/ - m - [3] - . The EPA calculates the monetized net benefits of the proposed alternative standard levels by subtracting the estimated monetized compliance costs from the estimated monetized benefits in 2032. These estimates do not fully account for all of the emissions reductions needed to reach the proposed and more stringent alternative standard levels. In 2032, the monetized net benefits of the proposed alternative standard level of 10/35 g/m3 are approximately $8.4 billion and $17 billion using a 3 percent real discount rate for the benefits estimates, and the monetized net benefits of the proposed alternative standard level of 9/35 g/m3 are approximately $20 billion and $43 billion using a 3 percent real discount rate for the benefits estimates (in 2017$). The benefits are associated with two point estimates from two different epidemiologic studies discussed in more detail in Chapter 5, Section 5.3.3. Table ES-10 presents a summary of these impacts for the proposed alternative standard levels and the more stringent alternative standard levels for 2032.
Table ES-10	Estimated Monetized Benefits, Costs, and Net Benefits of the Control Strategies Applied Toward the Primary Alternative Standard Levels of 10/35 g/ - m - [3] - , 10/30 g/ - m - [3] - , 9/35 g/ - m - [3] - , and 8/35 g/ - m - [3] -  in 2032 for the U.S. (millions of 2017$)

                                     10/35
                                     10/30
                                     9/35
                                     8/35
                                  Benefits[a]
                              $8,500 and $17,000
                              $9,600 and $20,000
                              $21,000 and $43,000
                              $46,000 and $95,000
                                   Costs[b]
                                      $95
                                     $260
                                     $390
                                    $1,800
                                 Net Benefits
                              $8,400 and $17,000
                              $9,300 and $19,000
                              $20,000 and $43,000
                              $44,000 and $93,000
Notes: Rows may not appear to add correctly due to rounding. We focus results to provide a snapshot of costs and benefits in 2032, using the best available information to approximate social costs and social benefits recognizing uncertainties and limitations in those estimates.
[a] We assume that there is a cessation lag between the change in PM exposures and the total realization of changes in mortality effects. Specifically, we assume that some of the incidences of premature mortality related to PM2.5 exposures occur in a distributed fashion over the 20 years following exposure, which affects the valuation of mortality benefits at different discount rates. Similarly, we assume there is a cessation lag between the change in PM exposures and both the development and diagnosis of lung cancer. The benefits are associated with two point estimates from two different epidemiologic studies, and we present the benefits calculated at a real discount rate of 3 percent. The benefits exclude additional health and welfare benefits that could not be quantified (see Chapter 5, Sections 5.3.4 and 5.3.5).
b The costs are annualized using a 7 percent interest rate.
As part of fulfilling analytical guidance with respect to E.O. 12866, the EPA presents estimates of the present value (PV) of the monetized benefits and costs over the twenty-year period 2032 to 2051. To calculate the present value of the social net benefits of the proposed alternative standard levels, annual benefits and costs are discounted to 2022 at 3 percent and 7 percent discount rates as directed by OMB's Circular A-4. The EPA also presents the equivalent annualized value (EAV), which represents a flow of constant annual values that, had they occurred in each year from 2032 to 2051, would yield a sum equivalent to the PV. The EAV represents the value of a typical cost or benefit for each year of the analysis, in contrast to the 2032-specific estimates.
For the twenty-year period of 2032 to 2051, for the proposed alternative standard level of 10/35 g/m3 the PV of the net benefits, in 2017$ and discounted to 2022, is $200 billion when using a 3 percent discount rate and $90 billion when using a 7 percent discount rate. The EAV is $13 billion per year when using a 3 percent discount rate and $8.5 billion when using a 7 percent discount rate. For the twenty-year period of 2032 to 2051, for the proposed alternative standard level of 9/35 g/m3 the PV of the net benefits, in 2017$ and discounted to 2022, is $490 billion when using a 3 percent discount rate and $220 billion when using a 7 percent discount rate. The EAV is $33 billion per year when using a 3 percent discount rate and $21 billion when using a 7 percent discount rate. The comparison of benefits and costs in PV and EAV terms for the proposed alternative standard levels can be found in Table ES-11 and Table ES-12. Estimates in the tables are presented as rounded values.
Table ES-11	Summary of Present Values and Equivalent Annualized Values for Estimated Monetized Compliance Costs, Benefits, and Net Benefits of the Control Strategies Applied Toward the Proposed Primary Alternative Standard Level of 10/35 g/m[3] (millions of 2017$, 2032-2051, discounted to 2022 using 3 and 7 percent discount rates)

                                  Benefits[a]
                                   Costs[b]
                                 Net Benefits
                                     Year
                                      3%
                                      7%
                                      3%
                                      7%
                                      3%
                                      7%
                                     2032
                                    $13,000
                                    $8,000
                                      $70
                                      $48
                                    $13,000
                                    $7,900
                                     2033
                                    $13,000
                                    $7,500
                                      $68
                                      $45
                                    $13,000
                                    $7,400
                                     2034
                                    $12,000
                                    $7,000
                                      $66
                                      $42
                                    $12,000
                                    $6,900
                                     2035
                                    $12,000
                                    $6,500
                                      $64
                                      $39
                                    $12,000
                                    $6,500
                                     2036
                                    $12,000
                                    $6,100
                                      $63
                                      $37
                                    $11,000
                                    $6,100
                                     2037
                                    $11,000
                                    $5,700
                                      $61
                                      $34
                                    $11,000
                                    $5,700
                                     2038
                                    $11,000
                                    $5,300
                                      $59
                                      $32
                                    $11,000
                                    $5,300
                                     2039
                                    $11,000
                                    $5,000
                                      $57
                                      $30
                                    $10,000
                                    $4,900
                                     2040
                                    $10,000
                                    $4,600
                                      $56
                                      $28
                                    $10,000
                                    $4,600
                                     2041
                                    $9,900
                                    $4,300
                                      $54
                                      $26
                                    $9,900
                                    $4,300
                                     2042
                                    $9,700
                                    $4,100
                                      $52
                                      $24
                                    $9,600
                                    $4,000
                                     2043
                                    $9,400
                                    $3,800
                                      $51
                                      $23
                                    $9,300
                                    $3,800
                                     2044
                                    $9,100
                                    $3,500
                                      $49
                                      $21
                                    $9,100
                                    $3,500
                                     2045
                                    $8,800
                                    $3,300
                                      $48
                                      $20
                                    $8,800
                                    $3,300
                                     2046
                                    $8,600
                                    $3,100
                                      $47
                                      $19
                                    $8,500
                                    $3,100
                                     2047
                                    $8,300
                                    $2,900
                                      $45
                                      $17
                                    $8,300
                                    $2,900
                                     2048
                                    $8,100
                                    $2,700
                                      $44
                                      $16
                                    $8,000
                                    $2,700
                                     2049
                                    $7,900
                                    $2,500
                                      $43
                                      $15
                                    $7,800
                                    $2,500
                                     2050
                                    $7,600
                                    $2,400
                                      $41
                                      $14
                                    $7,600
                                    $2,300
                                     2051
                                    $7,400
                                    $2,200
                                      $40
                                      $13
                                    $7,400
                                    $2,200
                                 Present Value
                                   $200,000
                                    $91,000
                                    $1,100
                                     $540
                                   $200,000
                                    $90,000
                          Equivalent Annualized Value
                                    $13,000
                                    $8,500
                                      $72
                                      $51
                                    $13,000
                                    $8,500
Notes: Rows may not appear to add correctly due to rounding. The annualized present value of costs and benefits are calculated over a 20-year period from 2032 to 2051.
[a] The benefits values use the larger of the two avoided premature deaths estimates presented in Chapter 5, Table 5-7, and are discounted at a rate of 3 percent over the SAB-recommended 20-year segmented lag. The benefits exclude additional health and welfare benefits that could not be quantified (see Chapter 5, Sections 5.3.4 and 5.3.5).
[b] The costs are annualized using a 7 percent interest rate.

Table ES-12	Summary of Present Values and Equivalent Annualized Values for Estimated Monetized Compliance Costs, Benefits, and Net Benefits of the Control Strategies Applied Toward the Proposed Primary Alternative Standard Level of 9/35 g/m[3] (millions of 2017$, 2032-2051, discounted to 2022 using 3 and 7 percent discount rates)

                                  Benefits[a]
                                   Costs[b]
                                 Net Benefits
                                     Year
                                      3%
                                      7%
                                      3%
                                      7%
                                      3%
                                      7%
                                     2032
                                    $32,000
                                    $20,000
                                     $290
                                     $200
                                    $32,000
                                    $20,000
                                     2033
                                    $31,000
                                    $18,000
                                     $280
                                     $190
                                    $31,000
                                    $18,000
                                     2034
                                    $30,000
                                    $17,000
                                     $280
                                     $170
                                    $30,000
                                    $17,000
                                     2035
                                    $29,000
                                    $16,000
                                     $270
                                     $160
                                    $29,000
                                    $16,000
                                     2036
                                    $29,000
                                    $15,000
                                     $260
                                     $150
                                    $28,000
                                    $15,000
                                     2037
                                    $28,000
                                    $14,000
                                     $250
                                     $140
                                    $27,000
                                    $14,000
                                     2038
                                    $27,000
                                    $13,000
                                     $250
                                     $130
                                    $27,000
                                    $13,000
                                     2039
                                    $26,000
                                    $12,000
                                     $240
                                     $120
                                    $26,000
                                    $12,000
                                     2040
                                    $25,000
                                    $11,000
                                     $230
                                     $120
                                    $25,000