### From: Nizich, Sharon Sent: Wednesday, September 16, 2015 1:42 PM
To: 'Aaron_L_Szabo@omb.eop.gov' Cc: Barnett, Keith Subject: FW: EO 12866_Brick Clay 2060_AP69 Response 9 16 2015

Hello Aaron

-
Please find attached 5 items in response to your questions.

1. Analysis of the final floors if synthetic area sources were removed. 2. Further discussion on the change from proposal to final regarding the PM MACT pool. 3. Expanded discussion of the differences between Options 1, 2 and 3 (RIA pages 3

- 1 to 3

- 2

an d pages 3

- 6 to 3

- 7). 4. Discussion of other ways to control Hg other than ACI (see pages 8

- 9 of Model Costs Memo). 5. Rationale in the 2010 portland cement final amendments relative to not shifting from 12% of a category, even if the pollutant specific data set contains less than 30 sources.

Let me know if you have any questions. Thanks.

Sharon Nizich Environmental Engineer U.S. EPA/OAR/OAQPS Sector Policies and Programs Division (SPPD) 109 TW Alexander Dr. (D243

- 04) RTP, NC 27711 (919) 541

- 2825

<< EO 12866_ Brick Clay 2060

- AP69_Removing_SA_Sources (2).docx >>

<< E O 12866_Brick Clay 2060

- AP69 RIA Final_20150812

- options revisions 9 16.docx >>

<< EO 12866 Brick Clay 2060

- AP69_Excerpts _use of top 12 percent of sources versus top 5 sources_Subpart LLL.docx >>

<< EO 12866_Brick Clay 2060

- AP69_BSCP_Model_Costs_Memo_9

- 14

- 15_w_other_Hg_ctrls 9 16.docx >>

<< EO 12866_Brick Clay 2060

- AP69_revisions to page 73_PM MACT pool.docx >>

### Evaluation of Removing Synthetic Minors from Ranking and UPL Calculations

1) Large Tunnel Kilns

– PM lb/ton

No. of Sources Industrywide No. of Sources

with Data Determinatio n of No. of Sources in MACT Floor N n Average of Top Sources Variance of Top Sources UPL Data Distribution Notes

122 68 12% Sources with Data 9 31 0.014 8. 48 E

- 05 0.035 lognormal All Kilns

122 40 12% Sources with Data 5 21 0.018 4.05E

- 04 0.059 lognormal Major Kilns



### Kiln No APCD Type Average PM (lb/ton) Variance n Class Rank All Kilns Rank Major Kilns 514 DIFF 0.00757 7.68E

- 06 2 Area Source (synthetic) 1 538 DIFF 0.00868 1.09E

- 05 5 Major Source 2 1 508 DIFF 0.01003 1.71E

- 05 5 Major Source 3 2 695 None 0.01278 1.26E

- 06 2 Major Source 4 3 503 DIFF 0.01399 3.67E

- 07 3 Area Source (synthetic) 5 568 DIFF 0.01709 5.99E

- 05 2 Area Source (synthetic) 6 696 DLA 0.01761 1.38E

- 04 3 Major Source 7 4 600 DIFF 0.01799 2.98E

- 04 6 Area Source (synthetic) 8 604 DLS 0.01843 3.98E

- 05 3 Area Source (synthetic) 9 688 DIFF 0.02899 1.41E

- 04 5 Area Source (synthetic) 10 603 DLS 0.03278 2.23E

- 04 3 Area Source (synthetic) 11 558 DIFF 0.03471 1.05E

- 03 6 Major Source 12 5 610 DIFF 0.03602 7.97E

- 05 5 Area Source (synthetic) 13 673 DLA 0.03627 1.23E

- 04 6 Major Source 14 6 674 DLA 0.03627 1.23E

- 04 6 Major Source 15 7 662 DLA 0.03784 6.66E

- 04 3 Major Source 16 8 543 DIFF 0.03790 1.10E

- 03 5 Area Source (synthetic) 17 606 DIFF 0.03901 1.80E

- 03 3 Major Source 18 9 502 DLS 0.04255 1.48E

- 03 6 Major Source 19 10 544 DIFF 0.04487 1.09E

- 03 14 Area Source (synthetic) 20 654 DIFF 0.04500 3.28E

- 05 3 Area Source (synthetic) 21 583 DLA 0.04765 3.08E

- 04 3 Major Source 22 11 680 DLA 0.04959 6.83E

- 05 3 Major Source 23 12 653 DIFF 0.05149 4.00E

- 05 5 Major Source 24 13 566 DIFF 0.06024 3.28E

- 03 8 Major Source 25 14 506 DLS 0.06262 4.10E

- 04 5 Area Source (synthetic) 26 770 DLA 0.06884 1.92E

- 04 3 Major Source 27 15 526 DIFF 0.06969 1.05E

- 03 9 Major Source 28 16 547 DIFF 0.07636 5.17E

- 04 3 Major Source 29 17 548 DIFF 0.07636 5.17E

- 04 3 Major Source 30 18 527 DIFF 0.07699 6.23E

- 03 9 Major Source 31 19 725 DLA 0.07840 1.93E

- 03 3 Area Source (synthetic) 32 691 DLA 0.08227 4.29E

- 04 3 Area Source (synthetic) 33 769 DLA 0.08635 4.66E

- 04 3 Major Source 34 20 625 DLA 0.09099 5.79E

- 04 3 Major Source 35 21 567 DIFF 0.09304 5.67E

- 04 3 Major Source 36 22

### Kiln No APCD Type Average PM (lb/ton) Variance n Class Rank All Kilns Rank Major Kilns 721 WS 0.09565 1.82E

- 03 5 Area Source (synthetic) 37 724 DLA 0.09599 7.78E

- 04 3 Area Source (synthetic) 38 641 DLA 0.09977 1.64E

- 03 3 Area Source (synthetic) 39 518 DLA 0.10624 5.28E

- 04 3 Major Source 40 23 679 DLA 0.10847 3.80E

- 03 3 Major Source 41 24 738 DIFF 0.11217 8.58E

- 03 6 Area Source (synthetic) 42 573 DLA 0.13228 2.02E

- 04 3 Area Source (synthetic) 43 730 DLA 0.13851 2.63E

- 03 6 Major Source 44 25 577 DLA 0.14145 3.56E

- 02 13 Major Source 45 26 578 DLA 0.14145 3.56E

- 02 13 Major Source 46 27 649 DLA 0.14213 9.04E

- 03 6 Major Source 47 28 646 DLA 0.14327 1.01E

- 02 6 Area Source (synthetic) 48 675 DIFF 0.14825 1.72E

- 03 3 Area Source (synthetic) 49 740 DLA 0.15802 2.68E

- 03 3 Area Source (synthetic) 50 729 DLA 0.17786 1.91E

- 03 3 Major Source 51 29 644 DLA 0.17806 9.79E

- 04 3 Major Source 52 30 676 DIFF 0.18995 3.55E

- 02 6 Area Source (synthetic) 53 736 DLA 0.20060 7.15E

- 03 3 Area source (synthetic) 54 647 DLA 0.23418 3.68E

- 02 7 Area Source (synthetic) 55 655 DIFF 0.23971 5.23E

- 02 5 Area Source (synthetic) 56 645 DLA 0.26210 6.74E

- 03 6 Major Source 57 31 539 None 0.28166 5.73E

- 03 2 Major Source 58 32 720 WS 0.32413 1.33E

- 01 5 Area Source (synthetic) 59 768 DLA 0.37699 1.40E

- 02 3 Major Source 60 33 643 WS 0.37757 5.25E

- 02 7 Area Source (synthetic) 61 612 DLA 0.41284 1.27E

- 02 3 Major Source 62 34 613 DLA 0.41284 1.27E

- 02 3 Major Source 63 35 551 DLA 0.57684 5.15E

- 02 16 Major Source 64 36 552 DLA 0.57684 5.15E

- 02 16 Major Source 65 37 775 None 0.64068 4.38E

- 02 6 Major Source 66 38 766 DLA 0.82067 7.89E

- 01 6 Major Source 67 39 767 DLA 0.82067 7.89E

- 01 6 Major Source 68 40

### 2) Large Tunnel Kilns

– Hg lb/ton

No. of Sources Industrywide No. of Sources

with Data Determination of No. of Sources in MACT Floor N n Average of Top Sources Variance of Top Sources UPL Data Distribution Notes

122 19 12% Sources with Data 3 9 1.6E

- 05 9.7E

- 12 4.1E

- 05 normal All Kilns

122 10 12% Sources with Data 2 6 2.0E

- 05 2.1E

- 11 5.7E

- 05 normal Major Kilns



### Kiln No APCD Type Average Hg Blank Corrected

(lb/ton) Variance Hg Blank Corrected

(lb/ton) Class Rank All Kilns Rank Major Kilns 568 DIFF 1.48E

- 05 8.83E

- 13 Area Source (synthetic) 1 558 DIFF 1.70E

- 05 1.43E

- 12 Major Source 2 1 655 DIFF 1.72E

- 05 3.10E

- 11 Area Source (synthetic) 3 547 DIFF 2.31E

- 05 2.33E

- 11 Major Source 4 2 548 DIFF 2.31E

- 05 2.33E

- 11 Major Source 5 3 676 DIFF 2.70E

- 05 8.99E

- 12 Area Source (synthetic) 6 503 DIFF 2.91E

- 05 7.63E

- 12 Area Source (synthetic) 7 566 DIFF 3.27E

- 05 2.37E

- 12 Major Source 8 4 606 DIFF 3.85E

- 05 3.30E

- 11 Major Source 9 5 721 WS 3.93E

- 05 4.84E

- 10 Area Source (synthetic) 10 720 WS 6.22E

- 05 2.92E

- 10 Area Source (synthetic) 11 543 DIFF 7.66E

- 05 7.09E

- 12 Area Source (synthetic) 12 775 None 7.79E

- 05 1.60E

- 09 Major Source 13 6 526 DIFF 8.50E

- 05 7.47E

- 10 Major Source 14 7 600 DIFF 8.94E

- 05 1.08E

- 10 Area Source (synthetic) 15 508 DIFF 9.08E

- 05 1.21E

- 10 Major Source 16 8 527 DIFF 9.08E

- 05 5.98E

- 11 Major Source 17 9 544 DIFF 9.78E

- 05 1.02E

- 10 Area Source (synthetic) 18 653 DIFF 1.02E

- 04 9.35E

- 12 Major Source 19 10

### 3 ) Small Tunnel Kilns

– PM lb/ton

No. of Sources Industrywide No. of Sources

with Data Determination of No. of Sources in MACT Floor N n Average of Top Sources Variance of Top Sources UPL Data Distribution Notes

99 18 12% Sources with Data 3 12 0.063 0.0057 0.36 lognormal All Kilns

98 18 12% Sources with Data 3 12 0.063 0.0057 0.36 lognormal Major Kilns



### Kiln No APCD Type Average PM (lb/ton) Variance n Class Rank All Kilns Rank Major Kilns 599 DIFF 0.0093 2.99E

- 05 3 Major Source 1 1 549 None 0.0196 1.36E

- 05 3 Major Source 2 2 531 SD/ESP 0.1115 0.006804 6 Major Source 3 3 532 SD/ESP 0.1115 0.006804 6 Major Source 4 4 533 SD/ESP 0.1815 0.001963 3 Major Source 5 5 180 None 0.1829 0.001063 3 Major Source 6 6 521 None 0.2312 0.001311 3 Major Source 7 7 178 None 0.2431 0.005222 3 Major Source 8 8 650 None 0.2502 0.004059 3 Major Source 9 9 516 None 0.2916 0.00725 6 Major Source 10 10 179 None 0.3129 0.000106 3 Major Source 11 11 669 None 0.3757 0.000273 3 Major Source 12 12 529 None 0.3819 0.019541 3 Major Source 13 13 530 None 0.3945 0.014853 9 Major Source 14 14 535 None 0.6640 0.019817 3 Major Source 15 15 706 None 0.7462 0.261192 6 Major Source 16 16 704 None 1.1877 0.06787 3 Major Source 17 17 705 None 1.1877 0.06787 3 Major Source 18 18



### Results Summary:

All kilns Major sources only Number of

sources

with data Number in pool UPL (lb/ton) Data distribution Number of

sources with data Number in pool UPL (lb/ton) Data distribution
PM Large 68 9 0.035 lognormal 40 5 0.059 lognormal

Hg Large 19 3 4.1E

- 05 normal 10 2 5.7E

- 05 normal

PM small 18 3 0.36 lognormal 18 3 0.36 lognormalE.O. 12866_Brick & Clay 2060

- AP69 RIA Final_20150812



# Regulatory Impact Analysis: Final Brick and Structural Clay Products NESHAP

U

. S

. Environmental Protection Agency Office of Air Quality Planning and Standards (OAQPS) Air Economics Group (MD

- C339

- 01) Research Triangle Park, NC 27711

July 201 5 Docket ID No. EPA

- HQ

- OAR

- 2013

- 0291***E.O. 12866 Review

- Draft

- Do Not Cite, Quote, or Release During Review***

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 docum ent should be

addressed to Tom Walton , U.S. Environmental Protection Agency, Office of Air Quality Planning and Standards, Research Triangle Park, North Ca rolina 27711
(email: walton.tom@epa.gov ).

ACKNOWLEDGEMENTS

Personnel from RTI International and K apur Energy Environmental Economics, LLC contributed significant data, analysis, and writing to this document under contract number EP

- W

11

- 029.***E.O. 12866 Review

- Draft

- Do Not Cite, Quote, or Release During Review***

iii CONTENTS

Section Page

Executive Summary

................................ ................................ ................................ .... ES

- 1

1 Introduction

................................ ................................ ................................ ................... 1

- 1

1.1 Background for the Final Rule

................................ ................................ ............. 1

- 1

1.2 Statement of Need for Policy Action

................................ ................................ ... 1

- 1
1.2.1 Need for Regulatory Intervention Because of Market Failure

................. 1

- 1

1.3 Organization of the Report

................................ ................................ ................... 1

- 2

2 Profile of the Affected Industry

................................ ................................ .................... 2

- 1

2.1 Overview of Current Conditions

................................ ................................ .......... 2

- 1

2.2 Supply

................................ ................................ ................................ .................. 2

- 2
2.2.1 What Types of Products Does the Industry Provide?

.............................. 2

- 2
2.2.2 What Factors Influence Market Supply?

................................ ................. 2

- 3
2.2.3 What Factors Influence the Relationship Between Output Prices and the Quantity Supplied?

................................ ................................ ...... 2

- 3

2.3 Demand

................................ ................................ ................................ ................ 2

- 4
2.3.1 Who Uses Brick?

................................ ................................ ..................... 2

- 5
2.3.2 What Factors Influence the Market Demand?

................................ ......... 2

- 5
2.3.3 What Factors Influence the Relationship Between Prices and the Quantity Demanded?

................................ ................................ ............... 2

- 6

2.4 Firm Behavior and Organization of Industry

................................ ....................... 2

- 6
2.4.1 Market Definition

................................ ................................ ..................... 2

- 6
2.4.2 Firm Pricing Behavior

................................ ................................ .............. 2

- 7
2.4.3 Affected Facilities and Ultimate Parent Companies

................................ 2

- 8

2.5 Market Data and Trends

................................ ................................ ..................... 2

- 11
2.5.1 Market Prices

................................ ................................ ......................... 2

- 20

2.6 Re ferences

................................ ................................ ................................ .......... 2

- 21***E.O. 12866 Review

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- Do Not Cite, Quote, or Release During Review***

iv 3 Engineering Cost Analysis

................................ ................................ ............................ 3

- 1

3.1 Summary of National Costs by Regulatory Approach

................................ ........ 3

- 1

3.2 Summary of Costs by Control Device

................................ ................................ . 3

- 4

3.3 Summary of Results

................................ ................................ ............................. 3

- 6

4 Human Health Benefits of Emissions Reductions

................................ ........................ 4

- 1

4.1 PM 2.5 - Related Human Health Co

- benefits

................................ .......................... 4

- 1
4.1.1 Health Impact Assessment

................................ ................................ ....... 4

- 2
4.1.2 Economic Valuation

................................ ................................ ................. 4

- 5
4.1.3 Benefit

- per

- Ton Estimates

................................ ................................ ....... 4

- 7
4.1.4 PM 2.5 Co

- benefits Results

................................ ................................ ........ 4

- 9
4.1.5 Characterization of Uncertainty in the Monetized PM 2.5 Co

benefits

................................ ................................ ................................ ..... 4

- 9

4.2 Energy Disbenefits

................................ ................................ ............................. 4

- 17
4.2.1 Social Cost of Carbon and Greenhouse Gas Disbenefits

....................... 4

- 18

4.3 Unquantified Benefits

................................ ................................ ........................ 4

- 21
4.3.1 HAP Benefits

................................ ................................ ......................... 4

- 23
4.3.2 Additional SO 2 Health Co

- benefits

................................ ....................... 4

- 34
4.3.3 Visibility Impairment Co

- benefits

................................ ......................... 4

- 35

4.4 References

................................ ................................ ................................ .......... 4

- 36

5 Economic Impact Analysis

................................ ................................ ........................... 5

- 1

5.1 Market Analysis

................................ ................................ ................................ ... 5

- 1
5.1.1 Market

- Level Results

................................ ................................ ............... 5

- 2
5.1.2 Social Cost Estimates

................................ ................................ ............... 5

- 2

5.2 Employment Impacts of the Final Rule

................................ ............................... 5

- 6
5.2.1 Theory

................................ ................................ ................................ ...... 5

- 6
5.2.2 Current State of Knowledge Based on the Peer

- Reviewed Literature

................................ ................................ ................................ 5

- 11
5.2.3 Regulated Sector

................................ ................................ .................... 5

- 12
5.2.4 Environmental Protection Sector

................................ ........................... 5

- 13
5.2.5 Labor Supply Impacts

................................ ................................ ............ 5

- 13
5.2.6 Macroeconomic Net Employment Effects

................................ ............. 5

- 14***E.O. 12866 Review

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- Do Not Cite, Quote, or Release During Review***

v 5.2.7 Information Specific to this Regulation

................................ ................. 5

- 14
5.2.8 Conclusion

................................ ................................ ............................. 5

- 15

5.3 Impacts on Small Entities

................................ ................................ .................. 5

- 16
5.3.1 Small Business Impact Screening Analysis

................................ ........... 5

- 16
5.3.2 Final Regulatory Flexibility Analysis

................................ .................... 5

- 18

5.4 References

................................ ................................ ................................ .......... 5

- 24

6 Statutory and Executive Order Reviews

................................ ................................ ....... 6

- 1

6.1 Synopsis

................................ ................................ ................................ ............... 6

- 1

6.2 Executive Order 12866: Regulatory Planning and Review and Executive Order 13563: Improving Regulation and Regulatory Revie w

............................. 6

- 1

6.3 Paperwork Reduction Act (PRA)

................................ ................................ ......... 6

- 2

6.4 Regulatory Flexibility Act (RFA)

................................ ................................ ........ 6

- 5
6.4.1 Need for the Rule

................................ ................................ ..................... 6

- 5
6.4. 2 Objectives and Legal Basis for the Rule

................................ .................. 6

- 5
6.4.3 Significant Issues Raised

................................ ................................ ......... 6

- 6
6.4.4 Small Business Administration Comments

................................ ............. 6

- 8
6.4.5 Affected Small Entities

................................ ................................ ............ 6

- 9
6.4.6 Reporting, Recordkeeping, and Other Compliance Requirements

.......... 6

- 9
6.4.7 Significant Alternatives

................................ ................................ ......... 6

- 10

6.5 Unfunded Mandates Reform Act

................................ ................................ ....... 6

- 10

6.6 Executive Order 13132: Federalism

................................ ................................ .. 6

- 11

6.7 Executive Order 13175: Consultation and Coordination with Indian Tribal Governments

................................ ................................ ................................ ...... 6

- 11

6.8 Executive Order 13045: Protection of Children from Environmental Health Risks and Safety Risks

................................ ................................ ........... 6

- 11

6.9 Executive Order 13211: Actions Concerning Regulations That Significantly Affect Energy Supply, Distribution or Use

................................ .. 6

- 11

6.10 National Technology Transfer and Advancement Act (NTAA) and ICFR Part 51

................................ ................................ ................................ ................ 6

- 11
6.10.1 Executive Order 12898: Federal Actions to Address Environmental Justice in Minority Populations and Low

- Income Populations

............. 6

- 12***E.O. 12866 Review

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vi 6.11 Congr essional Review Act (CRA)

................................ ................................ ..... 6

- 13

7 Comparison of Benefits and Costs

................................ ................................ ................ 7

- 1

7.1 Introduction

................................ ................................ ................................ .......... 7

- 1

7.2 Net Benefits of the Final Standards

................................ ................................ ..... 7

- 1

Appendix

A Economic Model

................................ ................................ ................................ . A

- 1***E.O. 12866 Review

- Draft

- Do Not Cite, Quote, or Release During Review***

vii LIST OF FIGURES

Number Page

2

- 1 Capacity Utilization for Nonmetallic Mineral Products (NAICS 327)

........................ 2

- 2 2

- 2 Real Price Trends fo r Brick and Structural Clay Products

................................ ......... 2

- 21

4

- 1 Total Monetized PM 2.5 Co

- benefits of Final Brick and Structural Clay Rule in 2018

................................ ................................ ................................ ............................. 4

- 12 4

- 2 Percentage of Adult Population by Annual Mean PM 2.5 Exposure in the Baseline

................................ ................................ ................................ ....................... 4

- 17 4

- 3 Cumulative Distribution of Adult Population by Annual Mean PM 2.5 Exposure in the Baseline

................................ ................................ ................................ ............. 4

- 22 4

- 4 2005 NATA Model Estimated Census Tract Carcinogenic Risk from HAP Exposure from Emissions of All Outdoor Sources (inclusive of other nonpoint sources) based on the 2005 National Toxic Inventory

................................ ................ 4

- 25 4

- 5 2005 NATA Model Estimated Census Tract Noncancer Risk from HAP Exposure from Emissions of All Outdoor Sources (inclusive of other nonpoint sources) based on the 2005 National Toxic Inventory

................................ ................ 4

- 27***E.O. 12866 Review

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viii LIST OF TABLES

Number Page

2

- 1. Distance Shipped Statistics: NAIC 327 (Nonmetallic Mineral Product Manufacturing)

................................ ................................ ................................ ............. 2

- 7 2

- 2. Mar ket Share Statistics

................................ ................................ ................................ . 2

- 8 2

- 3. Production Statistics by Census Region

................................ ................................ ....... 2

- 9 2

- 4. Ultimate Parent Companies for Affected Facilities

................................ .................... 2

- 10 2

- 5. Historical Data for Brick (Building or Common and Face) (10 3 bricks): 1993

– 2010

................................ ................................ ................................ ................... 2

- 12 2

- 6. Historical Data for Facing Tile and Ceramic Glazed Brick (Including Unglazed and Salt Glazed) and Vitrified Clay Sewer Pipe and Fittings (short tons): 1 993

– 2010

................................ ................................ ................................ ................... 2

- 14 2

- 7. Historical Data for Structural Clay Tile (Except Facing) (short tons): 1993

– 2010

.... 2

- 17 2

- 8. Average Price of Principal Brick and Structural Clay Products Shipped: 2010

......... 2

- 20 2

- 9. Regional Variation in Average Prices of Brick, Building or Common and Facing: 2010

................................ ................................ ................................ ................ 2

- 20

3

- 1. APCD Implementation Scenarios to Meet MACT Limits

................................ ............ 3

- 3 3

- 2. National Annual Costs of Compliance (2011 million USD)

................................ ........ 3

- 4 3

- 3. Capital and Annual Costs of APCD Implementation Scenarios (2011 USD)

.............. 3

- 5 3

- 4. Number of Stacks Taking Actions to Achieve Compliance (2011 USD)

.................... 3

- 8

4

- 1. Human Health Effects of Ambient PM 2.5

................................ ................................ ..... 4

- 3 4

- 2. Summary of Monetized PM 2.5 and its Precursor SO 2 - Related Health Co

benefits Estimates for the Brick and Structural Clay Rule in 2018 (2011$)

.............. 4

- 10 4

- 3. Summary of Reductions in Health Incidences from PM 2.5 and its Precursor SO 2 - Related Co

- benefits for Brick and Structural Clay Rul e in 2018

...................... 4

- 11 4

- 4. All PM 2.5 Benefits Estimates for the Brick and Structural Clay Rule in 2018 at Discount Rates of 3% and 7% Av eraged ($2011 millions)

................................ ........ 4

- 13 4

- 5. Population Exposure in the Baseline Above and Below Various Concentration Benchmarks in the Und erlying Epidemiology Studies

................................ ............... 4

- 16 4

- 6. Emission Increases Associated with Secondary Energy Disbenefits (short tons per year)

................................ ................................ ................................ ...................... 4

- 17 4

- 7. Estimated Global Disbenefits of CO 2 Increases in 2018 (million 2011$)

.................. 4

- 21

5

- 1. Estimated Market Impacts of Final BSCP NESHAP

................................ .................. 5

- 3 5

- 2. Estimated Additional Labor Requirements

................................ ................................ . 5

- 15 5

- 3. Small Business Impact Screening Assessment Results and Closure Estimates

......... 5

- 17***E.O. 12866 Review

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ix 7

- 1. Summary of the Monetized Benefits, Social Costs, and Net Benefits (million 2011$)

................................ ................................ ................................ ........................... 7

- 1***E.O. 12866 Review

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ES

- 1 EXECUTIVE SUMMARY

ES.1 Background

T he U.S. Environment Protection Agency ( EPA ) is proposing that all major sources in
Brick and S tructural C la y P roducts Manufacturing category meet health

- based standards for acid gas hazardous air pollutants; maximum achievable control t echnology standards for mercury and

non

- mercury metal hazardous air pollutants (or particulate matter surrogate); and work practice standards, where applicable. The final rules would protect air quality and promote public health by reducing emissions of the hazardous air pollutants listed in section 112 of the Clean A ir Act. As part of the regulatory process, EPA is require d to perform economic analysis and the Regulatory Impact Analysis (RIA) discusses the benefits and costs of the final rule

.
ES.2 Results

For the final rule, the key results of the RIA follow:

■ Enginee ring Cost Analysis : EPA estimates the total annualized costs (2011$) for t he final rule will be approximately $ 2 8 million.

■ Benefits Analysis: The EPA monetized human health benefits of reducing cases of morbidity and premature mortality among populations e xposed to PM 2.5

. In addition, EPA estimated the energy disbenefits associated with emissions from the control devices’ increas ed electricity usage

. Using a 3% discount rate, we estimate the total monetized benefits of the final standards to be $ 8 3 million to $1 9 0 million. Using a 7% discount rate, we estimate the total monetized benefits to be $ 7 5 million to $1 70 million. Data, resource, and methodological limitations prevented EPA from monetizing the benefits from several important benefit categories, incl uding benefits from reducing exposure to 375 tons of HAPs each year for the final standards and exposure, as well as ecosystem effects and visibility impairment . In addition to reducing emissions of PM precursors such as SO 2 , this rule would reduce several

non

- mercury HAP metals emissions (i.e., antimony, arsenic, beryllium, cadmium, chromium, cobalt, lead, manganese, mercury, nickel, and selenium) each year.

■ Market Analysis and Closure Estimates : Market

- level impacts include the price and production adjust ments for bricks. T he average national price under the final standards increases by 1. 8 %, or $ 4.37 per 1,000 SBE, while overall domestic production falls by 1. 5 %, or 52 million bricks per year. Under the final standards, EPA estimated that two to four bric k manufacturing facilities are at significant risk of closure.

■ Social Cost Analysis : Under the final standards , the economic model suggests that industries are able to pass on $ 15.1 million (2011$) of the rule ’ s costs to U.S. household s in the form of higher prices. Existing U.S. industries ’ surplus falls by $ 1 2.1 million, and the total U.S. economic surplus loss is $2 7.2 million.***E.O. 12866 Review

- Draft

- Do Not Cite, Quote, or Release During Review***

ES

- 2 ■ Comparison of Benefits and Costs : The estimated monetized human health benefits outweigh the social costs

. For the final s tandards

, t he net benefits are $ 5 6 million to $ 160 million at a 3% discount rate for the benefits and $ 48 million to $ 150 m illion at a 7% discount rate.

■ Final Regulatory Flexibility Analysis : As required by section 604 of the Regulatory Flexibility Act ( RFA ) , the EPA prepared a final regulatory flexibility analysis (FRFA) for this action. The FRFA addresses the issues raised by public comments on the IRFA for the proposed rule. The complete FRFA is in cluded in Section 5 of this report

.
ES.3 Organization o f this Report
The remainder of this report details the methodology and the results of the RIA. Section 1 provides an introduction, and Section 2 presents the industry profile

. Section 3 describes engineering cost analysis, and Section 4 presents the benefi ts analysis

. Section 5 presents market, employment impact, social cost, and small business impact analyses

. Section 6 address es statutory and Executive Order requirements, and Section 7 provides a summary of benefits and

c ost s.***E.O. 12866 Review

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- Do Not Cite, Quote, or Release During Review***

1

- 1 SECTION 1
INTRODUCTION

1.1 Background for the Final Rule

T he Environmental Protection Agency (EPA) is finalizing national emission standards for hazardous air pollutants (NESHAP) for Brick and Structural Clay Products Manufacturing. A ll major sources in these categories must meet maximum achievable control technology (MACT) standards for mercury (Hg) and nonmercury (non

- Hg) metal hazardous air pollutants (HAP s ) (or particu late matter [ PM ] surrogate s ); health

- based standards for acid gas HAP s ; and work practice standards, where applicable. The final rule , which has been informed by input from industry and other stakeholders including small businesses, protect s air quality an d promote s public health by reducing emissions of HAP s listed in section 112 of the Clean Air Act (CAA)

. This Regulatory Impact Analysis (RIA) examines the estimated costs, benefits, and economic impacts of the final
rule.

1.2 Statement of Need for Policy Acti on

1.2.1 Need for Regulatory Intervention Because of Market Failure
In general, regulatory intervention is required only when markets fail to allocate resources efficiently. For markets to allocate resources efficiently, both buyers and sellers must
have access to full information about the transaction; there must be many buyers and sellers so that neither buyers nor sellers have power to control prices; and the market must impose all the social costs of the transaction on the buyers and sellers in the market. In some situations, however, these conditions do not occur, and markets fail to allocate resources efficiently. One such market failure occurs in cases where a production or consumption activity imposes an external cost on members of society who are neither buyers nor sellers in the market for the good or service produced. In cases of external costs, or “ externalities, ” some costs are imposed on members of society who are not part of the market. Because the market is not affected by these costs, it fails to a ccount for these costs and thus does not allocate resources efficiently, and government must intervene to make the outcome more efficient. Environmental pollution that results from a production process is an example of an external cost borne by members of society who are neither producers nor consumers of the good whose production is generating the pollution.

In the case of bricks and structural clay products , manufacturing processes result in air emissions that impose external costs on individuals located near BSCP facilities who are exposed to the HAP emitted by the processes. Because these costs are borne by exposed individuals rather***E.O. 12866 Review

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- 2 than by the BSCP manufacturers, they are not considered by manufacturers in their production decisions. As a result, BSCP manufacturers produce more, and emit more pollutants, than they would if they bore the costs of the air pollution they generate. Because the market does not provide a signal that properly limits the quantity of air pollutants emitted by BSCP manufacturers, a market failure exists that requires EPA to promulgate air pollution standards to
limit their emissions.

1.3 Organization of the Report
The remainder of this economic analysis is organized as follows:

■ Section 2 presents a profile of the bricks and structural clay products industry.

■ Section 3 describes the final rule and the estimated costs of complying with it.

■ Section 4 presents a qualitative discussion of the benefits of the final rule.

■ Section 5 describes the estimated economic impacts of the final rule.

■ Section 6 describes analyses EPA conducted to assess requirements of statutes and Executive Orders.

■ Section 7 presents EPA ’ s summary of benefits and c ost s.***E.O. 12866 Review

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- 1 SECTION 2
PROFILE OF THE AFFEC TED INDUSTRY

Residential and commercial construction activities rely on bricks and structural clay materials. Most bricks are used as primary and secondary exterior wall materials, while other structural clay products are used in plumbing systems and roofing applications. Because over 80% of brick sales are associated with residential construction (Brick Industry Association,
2013a ), trends in the industry are influenced by tre nds in residential construction markets.

2.1 Overview of Current Conditions
To provide a general overview of current conditions in the affected industry, we used the U.S. government ’ s official measures reported in the Annual Survey of Manufactures (ASM), County Business Patterns, and Current Industrial Reports

. Because the latest year of data (2011) differs from historical industry trends, it is unclear whether the industry without the final rule would be similar to the industry today. As a result, the profile provides information on a range of factors that may influence how the brick

- related markets may evolve.

Federal statistical agencies classify business est ablishments in this industry using two North American Industry Classification System (NAICS) codes: 1

■ 327121 Brick and Structural Clay Tile Manufacturing

■ 327123 Other Structural Clay Product Manufacturing

In 2011, the value of products shipped in the two in dustries was approximately $1.1 billion. Nearly all of the value was centered in NAICS 327121. The ASM reported that 218
establishments (174 in NAICS 327121 and 44 in NAICS 327123) employed 8,000 people with a total annual payroll of about $300 million (U. S. Census Bureau, 2013a,b ).

During 2011, approximately 3 to 4 billion Standard Brick Equivalents (S.B.E.) 2 were produced by the industry (U.S. Census Bureau, 2011 ). Federal Reserve data and industry surveys suggest the capacity utilization rate for the brick industry is below 50% ( Board of Governors of the Federal Reserve System , 2013 ; Brick Industry Association, 2013b ) (see Figure 2

- 1). The current observed conditions are influenced by the recent steep declines in the residential

1 In 2012, these industries were classified under NAICS 32710 Clay Building Material and Refractories

Manufacturing

. See http://www.census.gov/cgi

- bin /sssd/naics/naicsrch?code=327120&search=2012

. 2 This is a common unit that accounts for various sizes of brick products. It measures 3

- 5/8 ′′ x 2

- 1/4 ′′” x 7

- 5/8 ′′.***E.O. 12866 Review

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- 2 Figure 2

- 1. Capacity Utilization for Nonmetallic Mineral Products (NAICS 327)

Source: Federal Reserve Board, 2013

construction market. For example, 2011 new privately owned housing starts (608,800) units are well below levels observed in 2000 (1.6 million) and 1990 (1.2 million) (U.S. Census Bureau,
2013c ). Since 2010, n ew residential housing starts have begun to grow again, but levels are still much lower than the previous two decades. New privately owned housing starts in July 2013 were at a seasonally adjusted annual rate of 852,000 (U.S. Census Bureau, 2013d ).

2.2 Supply
To better understand the markets for affected products, we consider ed the group of sellers that provide goods to the market and common factors that influence supply (e.g., input prices) and quantity of goods supplied (e.g. , output prices).

2.2.1 What Types of Products Does the Industry Provide?
The U.S. Current Industrial Report provides descriptions of the types of clay construction goods supplied to U.S. and international markets. They include

■ brick (building or common and face );

■ structural facing tile and ceramic glazed brick, including glazed and unglazed;

■ vitrified clay sewer pipe and fittings; and***E.O. 12866 Review

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- 3 ■ structural clay tile (except facing)

.
Bricks are the primary good produced in terms of value and physical quantities and
include face brick, paving brick, building brick, and thin brick. Face brick accounts for over 90% of brick shipments.

2.2.2 What Factors Influence Market Supply ?
The manufacturing process for brick and structural clay goods includes raw material processing (mining, gri nding, screening, and blending) followed by forming, cutting, or shaping; drying; firing; cooling; and storage (U.S. EPA, 1997 ). Census data for NAICS 327121 Brick and Structural Clay Tile Manufacturing suggest that 70% of the produc t ’ s value is associated with
value

- added activities (i.e., labo r and capital earnings ). During the last 5 years, labor costs have remained flat in the nonmetallic mineral products sector . The U.S. Bureau of Labor Statistics reports that average annual hour ly earnings (adjusted for inflation) of all employees was about $20 per hour (U.S. Bureau of Labor Statistics, 2013a,b ).

The value of intermediate goods used in these processes (i.e., raw materials like cla y and shale) make up the remaining 30% of the industry ’ s total product value (U.S. Census Bureau,
2013a ). Intermediate production costs can be influenced by changes in raw clay material prices, but the prices of these mate rials have not fluctuated recently. Since 2008, common clay prices (primarily used in brick) have remained steady at $12 per ton. The U .S. Geological Survey (U SGS ) notes that brick companies often consider sources of raw materials when considering purchasi ng other companies. For example, the Belden Brick Co. purchase of Lawrenceville
Brick Inc. included Lawrenceville Brick ’ s clay reserves (USGS, 201 1 ).

2.2.3 What Factors Influence the Relationship Between Output Prices and the Quantity Supplied?
All other things equal, brick manufacturers will likely offer to sell more bricks when the price of bricks rises. The price elasticity of supply measures how much the quantity of bricks supplied responds to changes in the brick price. 3 If manufac turers have a significant amount of flexibility to change the amount of bricks they produce when the price rises, the supply of bricks is elastic. In contrast, if the quantity of brick produced and supplied only changes by small amounts when the price rise s, the supply of bricks is inelastic.

A key determinant of the price elasticity of supply is the length of the time period over which the product choices can be made. During shorter periods, it is more difficult for the firm to

3 The measure is computed as the percentage change in quantity supplied divided by the percentage change in price.***E.O. 12866 Review

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- 4 adjust inputs and increase p roduction. Put another way, the firm typically has some fixed factors of production that limit its ability to respond to price changes. Rutherford ( 2002) develop ed an equation that can be used to derive a benchmark price elasticity of supply that considers the fixed factor value as a share of total product value. In our example, consider the case of two production inputs, one input that is fixed during a short time period 4 and the other input that varies with production

.

Supply Ela sticity = elasticity of substitution × 

### share ue factor val fixed share ue factor val fixed 1

−

.

To illustrate the approach, consider the value share of the fixed factor to be 5 0% to approximately match the non

- labor value added reported in the U.S. Census data above. In cases
where we lack data to estimate the elasticity of substitution, it is common to assume the elasticity is 1 (a Cobb

- Douglas production function). This means that a 1% change in the ratio of factor prices would result in a 1% change in the ratio of factor shares . If w e assume the elasticity of substitution between the fixed and variable input is one, the formula is

Supply Elasticity = 1 × 5

. 0 5

. 0 1

− = 1

.

Using these values for the fixed factor ’ s value share and elasticity of substitution, the supply elastic ity is approximately one

. This means if the price of brick rose by 1%, brick
manufacturers would plan to sell 1 % more bricks to the market. Given the current low capacity utilization rates and excess capacity available in the industry, this value may under estimate how responsive the brick industry would be to changes in the market price. As a result, the actual supply elasticity value may be elastic with a value higher than one.

2.3 Demand
Brick and structural clay products (BSCP) are primarily used in residen tial and commercial construction applications and are influenced by overall macroeconomic trends and conditions in the residential housing industry. Facing bricks are used in overall building structures (e.g., exterior walls), while clay pipe; structural c lay tile; and drain, sewer, and roof tiles are used in elements of the building structure such as plumbing systems, fireplaces, and roofs. Because the vast majority of affected products are brick products and available data for other structural clay produc ts are more limited, we focus on brick demand characteristics.

4 The fixed factor generally includes plant and capital equipment; factors that vary with production could include materials or labor.***E.O. 12866 Review

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- 5 2.3.1 Who Uses Brick ?
According to the Brick Industry Association, the vast majority of affected brick products

are sold for residential end uses and nonresidential building uses (Brick Industry Asso ciation,
2013b ). The pattern of shipments varies by brick type: approximately half of the industry shipments go to dealers or distributors who sell the products to final consumers and the other half
is sold directl y to end users like construction companies (Brick Industry Association, 2013b). Over half of the shipments flow to two census regions (South Atlantic and West South Central), and Texas is the largest consumer of face brick and paver shipments (Brick Indust ry Association, 2013b).

2.3.2 What Factors Influence the Market Demand ?

BSCP have a variety of characteristics desirable in building materials. According to the Brick Industry Association

, brick ’ s desirable attributes inc lude its durability, flexibility,
resistance to fire, weather, and pests; and little required maintenance. (Brick Industry Association, 2013a) A recent National Association of Homebuilders (NAHB) survey of buyers
of new homes found that “ To get brick, respondents reported they would add $7,500 in
additional costs ” (NAHB, 2013 ).

2.3.2.1 Price of Related Goods
In exterior wall applications, vinyl siding, stone, stucco, wood, and fiber cement are substitute building materials. Historically, bric k has maintained a 25% market share in the exterior wall application market (Brick Industry Association, 2013b). A recent NAHB survey
found that “ On a national level, respondents ranked brick highest at 34 percent, vinyl siding at 21 percent, stone at 16 p ercent, stucco at 12 percent, wood at 7 percent and fiber cement at 5
percent ” (NAHB, 2013 ).

2.3.2.2 Income
Homeowners purchasing more expensive homes are more likely to choose brick exteriors. A recent NAHB survey found that “ Ranked by price po int [sale price of the home]

, brick topped other home exteriors in the $150,000

– $499,000 range, while vinyl was preferred in the $150,000 or less range; brick ranked second to stone in the $500,000+ range with stucco following in third place ” (NAHB, 2013 ). This suggests demand for brick exterior is likely
influence d by income levels.***E.O. 12866 Review

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- 6 2.3.3 What Factors Influence the Relationship Between Prices and the Quantity Demanded?
All other things equal, consumers will likely buy fewer BSCP when the price of the product rises. The price elasticity of demand measures the size of the price response. 5 Several factors influence how sensitive consumers are to price changes. If consumers can easily switch from one product to another because there are many close substitutes, demand tends to be more elastic. This is particularly true for more narrow market definitions (king versus modular brick) and over longer time horizons for the consumption decision (months versus years).

Currently, EPA has not identified stati stically estimated price elasticities of demand for
BSCP . However, economy

- wide simulation models have suggested the nonmetallic mineral industry demand elasticity is approximately −0.8

, a 1% change in price results in a 0.8% decline in the quantity demand ed (Ho, Morgenstern, and Shih, 2008 ). Because the market definition for the product is broad, the price response for BSCP is likely more elastic than this value

.
2.4 Firm Behavior and Organization of Industry

2.4.1 Market Defi nition
Market definition boundaries are commonly defined in two dimensions: product substitution and geography. Based on product substitution characteristics and available data, we rely on the Census definitions to define three groups of markets in which b uyers are more likely to view products as substitutes:

■ Brick

– Brick (building or common and face)

■ Other Structural Clay Products

– Structural facing tile and ceramic glazed brick, including glazed and unglazed

– Vitrified clay sewer pipe and fittings

■ Other Clay Structural, Floor, and Wall Tile

– Structural clay tile (except facing)
Given the weight of bricks, transportation costs are high, relative to value. For this reason, bricks are more likely to be bought and sold within regions because of the cost of
transpo rtation across long distances. We found that international trade represented only a small fraction of economic activity (see Section 2.5), and the latest Census data show that a majority of

5 The measure is computed as the percentage change in quantity demanded divided by the percentage change in price.***E.O. 12866 Review

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- 7 nonmetallic mineral products were shipped less than 100 miles (U.S . Department of Transportation, 2010 ). 6 As shown in Table 2

- 1, approximately 75% of the total tons shipped are shipped in NAICS 327 is less than 50 miles. A comparison of Census region average prices for
bric ks shows substantial differences between regions in the average price of brick products shipped. To the extent these price differences persist over time, these differences may be
consistent with regional markets for brick.

Table 2

- 1. Distance Shipped Stati stics: NAIC 327 ( N onmetallic Mineral Product Manufacturin g)

Distance Shipped 2007 Value (million $) 2007 Tons (thousands) Share of Total Tons

Total 124,713 1,060,926

---- Less than 50 miles 53,721 796,412 75.1%

50

– 99 miles 12,351 82,342 7.8%

100

– 249 miles 21,760 113,384 10.7%

250

– 499 miles 15,117 39,645 3.7%

500

– 749 miles 8,495 16,040 1.5%

750

– 999 miles 4,872 6,039 0.6%
1,000

– 1,499 miles 3,790 4,722 0.4%
1,500

– 2,000 miles 2,364 1,344 0.1%
More than 2,000 miles 2,246 998 0.1%

Source: U.S. Department of Transportation (2010). Table 15.

2.4.2 Firm Pricing Behavior
Economists have developed a system for grouping markets that helps describe the pricing
behavior of firm s . At one end of the spectrum, fi rms have little control over pricing for their products. Put another way, firms are price takers, and price is determined by supply and demand conditions. This basic model is more likely to hold when the industry has a large number of sellers, goods are id entical, and barriers for entry and exit (laws, high capital requirements, or patents) are low. At the other end of the spectrum, there is a single firm that searches for the price

- output combination that maximizes its profit. This basic model is more like ly to hold when there are significant barriers to entry (industries with economies of scale or ownership of a patent).

6 The data include other product s such as cement, so it is unclear from this data whether brick and structural clay products face the same transportation and shipment patterns as cement products.***E.O. 12866 Review

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- 8 When markets have a small number of firms selling identical products, firms may not necessarily be price takers; instead, they may be abl e to determine their price while considering how competitors may respond to their own decisions . To assess the extent to which affected markets may be concentrated among a small number of sellers, we compiled and estimated national and regional market shar e statistics using historical kiln survey data. Across the United States, a large number of companies (50 companies) own and operate over 200 kilns. The largest U.S. market share for a U.S. company is low (about 16%). This is consistent with the latest 5

- y ear Census statistics describing U.S. concentration at the 6

- digit NAICS code level, which found that both affected industries are well below levels that government agencies consider moderately concentrated (U.S. Census Bureau, 2013 e ).

As Table 2

- 2 indicates, l ooking within regions, the New England region has only two operating companies, while the South Atlantic region has 17. In several Census regions, a single parent company accounts for a majority of estimated regional production. To the extent that brick product markets are defined at the regional level versus national level , the price

- taking model of firm decisions may not describe business decisions as well as other economic models of pricing behavior.

Table 2

- 2. Mark et Share Statistics

Census Region Number of Companies Maximum Company Share of Region

Production

East North Central 12 38%

East South Central 9 49%

Mid

- Atlantic 5 66%

Mountain 6 50 %
New England 2 NA

Pacific 4 40%

South Atlantic 17 2 7 %

West North Central 9 31%

West South Central 5 52%

Source: U.S. EPA estimates and calculations.

2.4.3 Affected Facilities and Ultimate Parent Companies
Based on historical kiln inventory survey data, over 13 million tons of BSCP are produced by the industry

, which includes over 200 major and area source kilns. EPA has***E.O. 12866 Review

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- 9 identified 44 ultimate parent companies with facilities that will need new or modified control devices to meet new emission standards. The companies own 8 5 facilities and operate 1 68 kilns (see Table 2

- 3) . The South Atlantic region accounts for a significant share of existing production capacity; 2 3 facilities and 5 3 kilns are operated in this region.

Table 2

- 3. Production Statistics by Census Region

Census Region Total S.B.E Shipped in 2010 (1000s) Nu mber of Affected Kilns Number of Affected Facilities Estimated Affected Production Share

within Region
East North Central 285,508 29 1 1 81%
East South Central 388,685 28 14 100%
Mid

- Atlantic 213,583 8 5 69%
Mountain 114,154 4 3 5 0 % New England 37,034 0 0 0%
Pacific 74,563 6 4 85%
South Atlantic 1,307,601 5 3 2 3 92%
West North Central 183,247 15 11 100%
West South Central 891,232 25 14 100%
United States 3, 495,607 1 68 8 5 90%

Source: U.S. Census Bureau, 2011 and U.S. EPA calculations.

2.4.3.1 Small Businesses
The Regulatory Flexibility Act (RFA) as amended by the Small Business Regulatory Enforcement Fairness Act (SBREFA) requires federal departments and agencies to evaluate if and/or how their regulations affect sma ll business entities. Specifically, the Agency must determine if a regulation is expected to have a significant economic impact on a substantial number of small entities. Small entities include small businesses, small organizations, and small governmental jurisdictions. The business is defined as the owner company, rather than the facility; the size of the owner company determines the resources it has available to comply with
the rule.

Affected parent companies fall under the Clay Building Material and Refr actories Manufacturing (NAICS 327120) industry

, and the Small Business Administration (SBA) (2013 ) defines a small business as having fewer than 750 employees. There are 36 parent companies that are small businesses (see Table 2

- 4).***E.O. 12866 Review

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- 10 Tabl e 2

- 4. Ultimate Parent Companies for Affected Facilities

Company ICR NAICS Affected Facilities Affected Kilns Sales (million $) Employment Small
Acme Brick Company 327121 11 19 260.1 2,602 No American Eagle Brick Co. 327121 1 1 NA NA Yes

Belden Brick Company 327121 2 11 87.5 751 No Brampton Brick, Ltd. 327121 1 NA NA <750 Yes

Boral Bricks Inc. 327121 11 20 3,922.0 14,740 No Certainteed Corporation 327123 1 1 1,330.8 Over 10,000 No

Cherokee Brick & Tile Co. 327121 1 4 43.5 175 Yes

Columbus Brick Co. 327121 1 3 4.9 50 Yes Commercial Brick Corp. 327121 1 3 17.5 175 Yes

Continental Brick Co. 327121 1 2 15.0 75 Yes Elgin

- Butler Brick Co. 327122 1 2 2.7 30 Yes Endicott Clay Products Co. 327122 1 3 23.4 180 Yes
General Finance, Inc. 327121 1 1 212.2 229 Yes
General Shale Brick, Inc. 327121 7 16 285.4 1,900 No Glen Gery 327121 6 10 83.3 N/A No
Hanson Brick East, LLC 327121 8 1 2 51.2 1,021 No Hebron Brick Company 327121 1 1 NA 55 Yes Henry Brick Company, Inc. 327121 1 2 5.3 60 Yes International Chimney Corp. 327121 1 1 27.9 250 Yes Ironrock Capital (formerly Metropolitan Ceramics, Inc.) 327122 1 4 NA 175 Yes

Kansas Brick and Tile Co. 327121 1 1 3.5 35 Yes Kasten Clay Products Co. 327121 1 1 3.8 42 Yes
L.P. McNear Brick Co, Inc. 327121 1 1 11.0 75 Yes

Lee Brick and Tile Co. 327121 1 4 35.0 175 Yes Logan Clay Products 327123 0 0 13.5 175 Yes
Marion Ceramics, Inc. 327123 1 1 5.3 75 Yes McAvoy Brick Co. 327121 1 1 1.8 7 Yes

Mohawk Industries 327122 2 5 5,788.0 NA No

Mutual Materials Co. 327121 & 327123 2 2 7.5 35 Yes Old Virginia Brick Co. 327121 2 3 22.1 175 Yes (continued)***E.O. 12866 Review

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- 11 Table 2

- 4. Ultimate Parent Companies for Affected Facilities (continued)

Company ICR NAICS Affected Facilities Affected Kilns Sales (Million $) Employment Small
Pacific Clay Products 327121 1 3 27.2 175 Yes
Pine Hall Brick Co., Inc. 327121 1 6 30.2 35 Yes Ragland Clay Products, LLC 327121 1 1 1.9 35 Yes

Richards Brick Co. 327121 1 2 18.1 75 Yes Sioux City Brick and Tile Co. 327121 2 3 7.5 35 Yes

Statesville Brick Co. 327121 1 2 35.0 175 Yes

Summit Pressed Brick and Tile Co. 327121 1 1 8.5 75 Yes
Summitville Tiles, Inc. 327122 1 4 300.0 175 Yes Superior Clay Corp. 327121 0 0 7.4 75 Yes The Stiles & Hart Brick Company 327121 0 0 4.8 44 Yes Triangle Brick 327121 2 5 29.8 203 Yes

Watsontown Brick Co. 327121 1 2 4.1 35 Yes

Whitacre Greer 327121 1 2 8.7 75 Yes

Yankee Hill Brick and Tile 327121 1 1 NA 75 Yes

NA = No annual sales data

Sources: Data on total number of ultimate parent company employees and annual sales were gathered from Hoover ’ s, Manta, and company Web sites.

2.5 Market Data and Trends
This section presents historical market data for select bricks and structural clay products

. Historical market data include U.S. volumes for manufa cturers ’ shipments, 7 foreign trade, and apparent consumption. Data were obtained from various years of Current Industrial Reports published by the U.S. Bureau of the Census. Table 2

- 5 provides data for common, building, and face bricks, while Table 2

- 6 pre sents data for structural facing tile and ceramic glazed brick, including unglazed and glazed, and vitrified clay and sewer pipe. Table 2

- 7 focuses on structural clay tile (except facing), and Table 2

- 8 is for clay floor and wall tile.

7 The source reports list both shipment and producti on quantities. Here we have chosen shipment quantities over production quantities, even though these do not differ by much in each year or show different trends over time. The reason to choose shipment numbers over production numbers is that shipment quant ity is the number that is relevant for final consumption. In fact, when the data source reports calculate “apparent consumption,” they use shipment numbers, not production numbers.***E.O. 12866 Review

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- 12 Table 2

- 5. Historica l Data for Brick ( Building or Common and Face ) (10 3 bricks a ): 1993

– 2010

Year Shipment of Bricks b Exports Imports Apparent Consumption b

1993 6,655,400 42,643 10,170 6,622,927
1994 7,237,982 43,733 8,967 7,203,216
1995 6,890,321 43,627 16,867 6,863,561
1996 7,619,279 42,759 20,629 7,597,149
1997 7,732,971 46,518 20,267 7,706,720
1998 8,241,086 40,631 18,243 8,218,698
1999 8,931,700 34,171 24,920 8,922,449
2000 8,616,784 30,712 47,472 8,633,544
2001 7,941,432 30,547 27,579 7,938,464
2002 7,986,393 37,135 25,164 7,974,422
2003 8,519,678 46,286 20,807 8,494,199
2004 9,388,648 75,297 33,436 9,346,787
2005 9,418,759 52,008 49,432 9,416,183
2006 8,899,594 36,421 75,717 8,938,890
2007 7,237,176 40,613 70,914 7,267,477
2008 5,053,935 47,898 97,739 5,103,776
2009 3,585,481 37,640 d ,f 74,479 e ,f 3,622,320
2010 3,495,657 37,532 d ,f 79,054 e ,f 3,537,179

Note: This table presents data for brick (building or common and face), which, by the 2007 NAICS definition, is associated with NAICS 327121, Brick and Structural Clay Tile Manufacturing.

a Bricks are 2 1/4′′ by 3 5/8′′ by 7 5/8′′ brick equivalent.

b This represents shipment quantity of bricks. The definition of value of shipments can be found on the “ definitions ” Web page

for Current Industrial Reports at Census Bureau ’ s Web site ( http://www.census.gov/manufacturing/cir/definitions/index.html ). The relevant item is “ quantity and value of shipments. ” The figures on quantity and value of shipments represent physical shipments of all products sold, transferred to other establishments of the same company, or shipped on consignment, whether for domestic or export sale. The value represents the net sales p rice, f.o.b. plant, to the customer or branch to which the products are shipped, net of discounts, allowances, freight charges, and returns. Shipments to a company ’ s own branches are assigned the same value as comparable appropriate allocation of company o verhead and profit. Products bought and resold without further manufacture are excluded.

c Apparent Consumption = Shipments of Bricks − Exports + Imports

d The export data were not available for 2009 and 2010. The numbers here are estimates based on past trends. The export

numbers seem to have the same pattern as shipment numbers. In particular, during 2001

– 2002 and 2007

– 2008 when brick shipment numbers were low, brick export numbers were also low. So we have estimated the numbers for 2009 and 2010 based on the regression exports = a + b*shipments

, using 1993 to 2008 data. Another source of information for estimating export quantities is that, in the Current Industrial Reports , the values of exports for all years, including 2009 and 2010, are available. Ho wever, because we lack reliable data on export prices for those years, we do not estimate the quantities of exports for 2009 and 2010 from the values data. (continued)***E.O. 12866 Review

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- 13 Table 2

- 5. Historical Data for Brick (Building or Common and Face) (10 3 bricks a ): 1993

– 2010 (continued)

e The import data were not available for 2009 and 2010. The numbers here are estimates based on past trends. The import

numbers do not seem to be correlated with shipment numbers. For example, during 2001

– 2002 and 2007

– 2008 when brick shi pment numbers were low, brick import numbers were not that low. In fact, plotting the numbers suggests that imports show an increasing trend since 1993. So we have extrapolated to estimate the numbers for 2009 and 2010 assuming a linear trend beginning in the year 1993. We fond imports to be lower in 2009 and 2010 compared with 2008, because the linear trend starts in 1993, and the unusually high 2008 number is only an outlier outside this trend. Another source of information for estimati ng import quantitie s is that, in the Current Industrial Reports , the values of imports for all years, including 2009 and 2010, are available. The value of imports drops approximately 50% from 2008 to 2009. However, because we lack data on import prices for those years, we di d not estimate the quantities of imports for 2009 and 2010 from these values.

f Another method we tried for computing export and import quantities was based on the observation that although for 2009 and

2010 the industrial reports only list export and im port values and not quantities, they do report both quantities and values for shipment. So with the latter information, we were able to compute the unit price for shipments and then use that to get the export and import quantities. We explored any systemat ic differences in the unit price for shipments, the unit price for exports, and the unit price for imports. We looked at industrial reports before 2009 to find out whether the unit prices are systemati cally different and adjusted for those differences. We then divided the export and import values for 2009 and 2010 by the export and import unit prices to obtain the export and import quantities. However, the export quantities (47,775 for 2009 and 65,099 for 2010) and import quantities (26,069 for 2009 and 23, 956 for 2010) we obtained as a result of this method seemed to be quite different from past

- year trends. So we decided to opt for the regression method of estimation.

g As previous notes indicate, export and import numbers for 2009 and 2010 are estimates. So the annual growth rates are

computed for both 1993 to 2008 and 1993 to 2010.
Sources: U.S. Department of Commerce, Census Bureau. 2011. Current Industrial Reports for Clay Construction Products

— Summary 2010. U.S. Department of Commerce, Census Bureau. 2009. Current Industrial Reports for Clay Construction Products

— Summary 2008. U.S. Department of Commerce, Census Bureau. 2004. Current Industrial Reports for Clay Construction Products

— Summary 2003. U.S. Department of Commerce, Census Bureau. 2003. Current Industrial Reports for Clay Construction Products

— Summary 2002. U.S. Department of Commerce, Census Bureau . 2000

. Current Industrial Reports for Clay Construction Products

— Summary 1999. U.S. Department of Commerce, Census Bureau. 2000. Current In dustrial Reports for Clay Construction Products

— Summary 1998. U.S. Department of Commerce, Census Bureau. 1998. Current Industrial Reports for Clay Construction Products

— Summary 1997.

As shown in Table 2

- 5, the brick market shows declines in the quantity of shipments and apparent consumption between 1993 and 2010 with a marked decreases during the recessions beginning in 2007 . An examination of the data during the time period 1993 to 2010 shows that brick shipment and apparent consumption increased during some years and decreased during other years. However, because of the steep declines beginning in 2007, 2010 values are only
about 53% of 1993 values. Brick shipments steadily increased from about 6.6 billion bricks in
1993 to 8. 6 billion bricks in 2000, dr opped somewhat in 2001 and remained below the 2000 level until 2003, and rose again in 2004 and 2005 before beginning a steady decline starting in 2006.***E.O. 12866 Review

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- 14 Table 2

- 6. Historical Data for Facing Tile and Ceramic Glazed Brick (Including Unglazed and Salt Glazed) and Vitrified Clay Sewer Pipe and Fittings (short tons): 1993

– 2010

Year Shipments of Select Structural Clay

Product s a Exports b Imports b Apparent Consumption c

1993 193,500 287 648 193,861

1994 188,039 3,187 915 185,767

1995 183,967 1,543 388 182,812

1996 204,908 1,610 345 203,643

1997 218,013 1,334 888 217,568

1998 207,815 2,291 291 205,815

1999 231,876 1,176 389 231,089

2000 217,448 2,092 346 215,702

2001 216,685 1,219 220 215,686

2002 177,558 1,583 607 176,582

2003 177,620 1,258 374 176,736

2004 210,981 1,473 915 210,423

2005 258,393 1,218 526 257,701

2006 219,911 1,041 341 219,211

2007 195,064 1,102 536 194,497

2008 132,181 1,164 463 131,480

2009 98,439 d 1,138 e ,g 512 f ,g 97,813 h

2010 73,183 d 1,098 e ,g 512 f ,g 72,597 h

Note: T his t able presents data for facing tile and ceramic glazed brick, including unglazed and salt glazed, which, according to the 2007 NAICS definition, is associated with NAICS 327121, Brick and Structural Clay Tile Manufacturing, and vitrified clay and sewer pipe , which, according to the 2007 NAICS definition, is associated with NAICS 327123, Other Structural Clay Products Manufacturing. According to our communication with Casey Bretz at the Census Bureau, in all the Table 1s in the Current Industrial Reports, the category listed as “ Structural facing tile and ceramic glazed brick ” should in fact be “ Structural facing tile and ceramic glazed brick, including unglazed and salt glazed. ” The Current Industrial Reports since 1998 omitted the phrase “ including unglazed and salt glazed ” and only mentioned structural facing tile and ceramic glazed brick. Calculation rules used when computing numbers from the Industrial reports for this table are 1 million brick equivalent = 2,000 short tons and 1 metric ton = 1.10231131 short ton. The source for the first formula is http://midlandbrick.wikidot.com/standard

- brick

- equivalent, which says that 1 standard brick equivalent is equal to a 4 pound brick. Because 1 short ton is equal to 2,000 pounds, this implies the conversion ra tio used here.

(continued)***E.O. 12866 Review

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- 15 Table 2

- 6. Historical Data for Facing Tile and Ceramic Glazed Brick (Including Unglazed and Salt Glazed) and Vitrified Clay Sewer Pipe and Fittings (short tons): 1993

– 2010 (continued)

a This represents shipment quantity of selec t structural clay products. The definition of value of shipments can be found on the

“ definitions ” Web page for Current Industrial Reports at the Census Bureau ’ s Web site ( http: //www.census.gov/manufacturing/cir/definitions/index.html ). The relevant item is quantity and value of shipments. The figures on quantity and value of shipments represent physical shipments of all products sold, transferred to other establishments of the s ame company, or shipped on consignment, whether for domestic or export sale. The value represents the net sales price, f.o.b. plant, to the customer or branch to which the products are shipped, net of discounts, allowances, fre ight charges, and returns. Sh ipments to a company ’ s own branches are assigned the same value as comparable appropriate allocation of company overhead and profit. Products bought and resold without further manufacture are excluded.

b For export and import numbers between 1998 and 2008 , the export and import data for facing tile and ceramic glazed brick

including unglazed and salt glazed are not available in the source reports (marked as (X) in the source reports), so the expo rt and import numbers are computed with vitrified clay sewer pipe and fittings data only.

c Apparent Consumption = Shipments of Select SCP − Exports + Imports

d Readers should interpret these numbers carefully. For the 2009 and 2010 shipment numbers, the shipment data for facing tile

and ceramic glazed brick are n ot available in the source report and are marked as “ (S). ” “ (S) ” means that the numbers did not meet publication standards. We talked to Casey Bretz at the Census Bureau and learned that these numbers involved over 50% of imputation, which is the reason th ey were not published. However, these imputed numbers were available upon our request, and the 2009

– 2010 shipment numbers in this table were calculated using these numbers for facing tile and ceramic glazed brick including unglazed and salt glazed. Numbers for vitrified clay sewer pipe and fittings are available in the source reports.

e Because the export quantity data for vitrified clay sewer pipe and fittings are not available for 2009 and 2010, the numbers for

2009 and 2010 are estimates for vitrified c lay sewer pipe and fittings exports. The export numbers for vitrified clays do not seem to be correlated to shipment numbers. In particular, during the 2002

– 2003 and 2007

– 2008 recessions when shipment numbers are low, the vitrified clay export numbers are not low. Further, plotting the numbers suggests that the exports have decreased over time and exhibit smaller fluctuations over time since 1993. So we have extrapolated the numbers for 2009 and 2010 assuming a linear trend beginning in the year 1993. Anoth er source of information for estimating export quantities is that, in the Current Industrial Reports, the values of exports for all years, including 2009 and 2010, are available. However, beca use we lack reliable data on export prices, we do not estimate q uantities of exports for 2009 and 2010 from these values.

f Because import quantity data for vitrified clay sewer pipe and fittings are not available for 2009 and 2010, the numbers here

are based on estimates. The import numbers do not seem to have the sa me pattern as the shipment numbers. In particular, during 2002

– 2003 and 2007

– 2008 when shipment numbers were obviously low, the import numbers were not. Plotting the numbers suggests that imports of structural clay products have fluctuated widely. So we si mply set these numbers at their historical average. Another source of information for estimating import quantities is that, in the Current Industrial Reports , the values of imports for all years, including 2009 and 2010, are available. Similar to bricks, t he value of imports for vitrified clay sewer pipe and fittings dropped by about 50% from 2008 to 2009. However, because we lack reliable data on import prices, we did not estimate the quantities of imports for 2009 and 2010 from these values.

g Another me thod we tried for computing export and import quantities was based on the observation that although for 2009 and

2010 the industrial reports only list export and import values and not quantities, they do report both quantities and values for shipment. So w ith the latter information we were able to compute the unit price for shipments and then use that to get the export and import quantities. We explored any systematic differences in the unit price for shipments, the unit price for expo rts, and the unit pric e for imports. We looked at industrial reports before 2009 to find out whether the unit prices are systematically different and adjusted for those differences. We then divided the export and import values for 2009 and 2010 by the export an d import unit pri ces to obtain the export and import quantities. However, the export quantities (725 for 2009 and 1,346 for 2010) and import quantities (206 for 2009 and 206 for 2010) we obtained as a result of this method seemed to be quite different fro m past

- year trends . So we used the regression method of estimation for exports and historical average method for imports.

h These are based on estimates. Please see notes e, f, and g.

i As previous notes suggest, data for 2009 and 2010 are based on estimates. So the annual growth rates were computed for both

1993 to 2008 and 1993 to 2010.

Sources: U.S. Department of Commerce, Census Bureau. 2011. Current Industrial Reports for Clay Construction Products

— Summary 2010. U.S. Department of Commerce, Census Bureau. 2009. Current Industrial Reports for Clay Construction Products

— Summary 2008. U.S. Department of Commerce, Census Bureau. 2007. Current Industrial Reports for Clay Construction Products

— Summary 2006.

(continued)***E.O. 12866 Review

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- 16 Table 2

- 6. Historical Data for Facing Tile and C eramic Glazed Brick (Including Unglazed and Salt Glazed) and Vitrified Clay Sewer Pipe and Fittings (short tons): 1993

– 2010 (continued)
U.S. Department of Commerce, Census Bureau. 2005. Current Industrial Reports for Clay Construction Products

— Summary 200 4. U.S. Department of Commerce, Census Bureau. 2004. Current Industrial Reports for Clay Construction Products

— Summary 2003. U.S. Department of Commerce, Census Bureau. 2003. Current Industrial Reports for Clay Construction Products

— Summary 2002.
U.S. D epartment of Commerce, Census Bureau. 2002. Current Industrial Reports for Clay Construction Products

— Summary 2001. U.S. Department of Commerce, Census Bureau. 2000. Current Industrial Reports for Clay Construction Products

— Summary 1999. U.S. Department of Commerce, Census Bureau. 2000. Current Industrial Reports for Clay Construction Products

— Summary 1998. U.S. Department of Commerce, Census Bureau. 1998. Current Industrial Reports for Clay Construction Products

— Summary 1997. U.S. Department of Commerc e, Census Bureau. 1996. Current Industrial Reports for Clay Construction Products

— Summary 1995. U.S. Department of Commerce, Census Bureau. 1995. Current Industrial Reports for Clay Construction Products

— Summary 1994.

Both exports and imports of bricks in creased between 1993 and 2008. The largest quantity of brick exports are to Canada (approximately 78% in 2010) (U.S. International Trade Commission [USITC], 2013). The largest quantities of brick and structural clay imports are from Germany (40% in 2010) a nd Mexico (37% in 2010) 8 (USITC, 2013). The average annual growth rate for exports was 3.16% during this time period. The growth rate for imports was much larger at 22.61%. In 1993, imports were about 10 million and jumped to 98 million by 2010, with significant increases happening in 1995, 2000, 2006, and 2008. This difference between brick export and import growth rates is also evident if we examine exports and imports as proportions of shipments instead of their levels. Exports started at 0.64% of s hipments in the year 1993 but had dropped to 0.41% by 2006. Imports started at 0.15% of shipments in 1993 but rose to 0.85% of shipments in 2006. After 2006, both these ratios rose. By 2010, exports and imports as a percentage of shipments rose to 1.07% an d 2.26%, respectively. But the rises since 2006 were driven more by decreases in shipments, rather than by changes in the levels of exports and imports.

8 Although these two countries typically are the largest source of imports, the country shares vary from year to year. For example, in 2012, Germany and Mexico again accounted for more than 65% of imports, but Mexico represented 40% and Germany accounted for 24%.***E.O. 12866 Review

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- 17 Table 2

- 7. Historical Data for Structural Clay Tile (Except Facing) (short tons): 1993

– 2010

Year Shipments of Structural Clay Tile (Except Facing)
1993 (D) 1994 (D) 1995 53,727 1996 50,990 1997 49,729 1998 49,098 1999 47,156 2000 47,009 2001 49,453 2002 49,563 2003 40,330 2004 40,050 2005 47,704 2006 37,491 2007 35,477 2008 23,410 2009 16,749 2010 12,140 Average Annual Growth Rates
1995

– 2010 −8.31%

Note: T his t able presents data for structural clay tile (except facing), which, by 2007 NAICS definition, is associated with NAICS 327121, Brick and Structural Clay Tile Manufacturing. Unlike Table 2

- 7 and Table 2

- 8, this table does not show exports, imports, or appar ent consumption, because the export and import data for structural clay tile (except facing) are not available (marked as (X) in the source reports). “ (D) ” means that the number is “ withheld to avoid disclosing data of individual companies ” in the source r eport.

Sources: U.S. Department of Commerce, Census Bureau. 2011. Current Industrial Reports for Clay Construction Products

— Summary 2010 U.S. Department of Commerce, Census Bureau. 2009. Current Industrial Reports for Clay Construction Products

— Summary 2 008 U.S. Department of Commerce, Census Bureau. 2007. Current Industrial Reports for Clay Construction Products

— Summary 2006 U.S. Department of Commerce, Census Bureau. 2005. Current Industrial Reports for Clay Construction Products

— Summary 2004 U.S. De partment of Commerce, Census Bureau. 2004. Current Industrial Reports for Clay Construction Products

— Summary 2003 U.S. Department of Commerce, Census Bureau. 2003. Current Industrial Reports for Clay Construction Products

— Summary 2002 U.S. Department of Commerce, Census Bureau. 2002. Current Industrial Reports for Clay Construction Products

— Summary 2001 U.S. Department of Commerce, Census Bureau. 2000. Current Industrial Reports for Clay Construction Products

— Summary 1999 U.S. Department of Commerce, Ce nsus Bureau. 2000. Current Industrial Reports for Clay Construction Products

— Summary 1998 U.S. Department of Commerce, Census Bureau. 1998. Current Industrial Reports for Clay Construction Products

— Summary 1997. U.S. Department of Commerce, Census Bureau . 1996. Current Industrial Reports for Clay Construction Products

— Summary 1995. U.S. Department of Commerce, Census Bureau. 1995. Current Industrial Reports for Clay Construction Products

— Summary 1994.***E.O. 12866 Review

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- 18 The market for other structural clay products is much smaller than the brick market, but it still represents an important sector of the BSCP industry. As Table 2

- 6 shows, both shipments and apparent consumption of structural clay products in 2010 were less than 38% of 1993 values

. Similar to the trend in the brick market, structural clay product shipments exhibited a steady increase from 194 thousand short tons in 1993 to 232 thousand short tons in 1999, dropped somewhat during the recession in 2002 and 200 3, rose between 2003 and 2006, and began a steady decline starting in 2007.

Although structural clay product shipments and consumption declined over the time period 1993 to 2008, the average annual growth rate of exports was high at 67.42%. Although this g rowth rate looks large, it is relatively small in absolute terms. This high average growth rate is largely due to a substantial increase in exports of vitrified sewer pipe and fittings from 1993 to 1994. In 1993, 287 short tons of vitrified sewer pipe and fittings were exported from the United States, and in 1994, this number rose dramatically to 3,187 short tons. Since 1995, exports have mostly stayed between 1,000 and 2,000 short tons. Imports of structural clay products are small, never exceeding a thous and short tons in any year between 1993 and 2008.

The shipments of structural clay tile (except facing) are even smaller than other structural clay products (which are presented in Table 2

- 6). As Table 2

- 7 shows, the average annual growth rate of shipments of structural clay tile (except facing) is approximately −8.3% for the years 1995 to 2010. More specifically, the shipments exhibit a steady decrease from 54 thousand short tons in 1995 to 35 thousand short tons in 2007, during which period the average an nual growth rate is only −2.9%. Then in the years 2008, 2009

, and 2010, the shipment levels dropped sharply by 34.0%, 28.5%, and 27.5%, respectively.

As the data in Tables 2

- 5, 2

- 6, and 2

- 7 show, the quantities of all BSCP experienced declines starting in 2007, the year the recent economic crisis set in, and continued to decline
post

- crisis. The data show that shipment levels had recovered after the 2002

– 2003 recession and held steady for the years prior to 2007. The decline since 2007 also appears to be du e to the
2007

– 2008 recession rather than to structural changes within the industry. We expect the industry to come back to its prerecession levels in the future. This is supported by the fact that shipment levels for all BSCP were low during 2001

– 2003, whe n the early 2000s recession happened in the United States and the European Union. However, these shipment levels bounced back after the recession. This prediction is also supported by the recent annual reports of large companies producing these products. F or example, the annual reports of large companies such as
Boral Limited and Saint

- Gobain show them recovering after exhibiting declines during the
recession.***E.O. 12866 Review

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- 19 Boral Limited is an international building and construction materials group headquartered
in Austr alia, and its U.S. operations manufacture clay bricks, concrete, and clay roof tiles and
manufactured stone veneer for residential and mid

- rise commercial buildings. 9 The 2012 annual report of Boral Limited compares U.S. housing starts and Boral U.S.A. ’ s e arnings before interest and taxes (EBIT) during the years 2006

– 2012 and finds them to be highly correlated (Boral Limited, 2012 ). Both the numbers for U.S. housing starts and Boral U.S.A. ’ s EBIT in the U nited
States declined sim ultaneously between 2006 and 2011 but rose in 2012. U.S. housing starts went from 2,030 thousand in fiscal year 2006 to 570 thousand in fiscal year 2011

, and Boral
U.S.A. ’ s EBIT declined to − $ 99 million in 2011 from $ 139 million in 2006. Boral U.S.A. ’ s EBI T rose to − $ 87 million in fiscal year 2012 when U.S. housing starts increased to 685
thousand.

Saint

- Gobain S.A, which produces construction products marketed in the United States under the CertainTeed brand, is a Europe

- based multinational company and doe s not provide its U.S. operations data separately. However, its overall data exhibit synchronization with the economic cycles. Its net sales declined from 30,274 million euros in 2002 (Saint

- Gobain, 2003;
2013 ) to 29,590 mi llion euros in 2003, showed a steady recovery after that to 43,800 million euros in 2008, declined in 2009 to 37,786 million euros, and then recovered in 2011 and 2012 to 42,116 million euros and 43,198 million euros, respectively (Saint

- Gobain, 2013 ).

Although their annual reports do not provide data on quantities in shipment, production

, or exports as the Current Industrial Reports do, the recent trends in the financial performance of these large companies, in particular the pro fit and sales data, support that this industry will improve as the effects of the recession recede and the building and construction industry revives.

In addition, our prediction that the BSCP industry is only experiencing a temporary
setback and will come back to prerecession levels is supported by existing reports for the clay and shale industry, which is upstream of the BSCP industry. Put another way, r aw materials typically used in manufacturing BSCP include common clay and shale (Midwest Research Institute, 2001 ). A recent advance report published in 2013 by the U.S. Department of the Interior and USGS suggests that once statistical data become available, the country may see a moderate growth in common clay sales in 2012 (U.S. Department of the Interior, 2013 ). In their

9 This information is from the company’s Web site, http://www.boral.com . According to the Web site, Boral’s operations include the largest brick manufacturer and the largest clay tile manufacturer in the United States; through the 50% owned MonierLifetile, it is also the largest concret e roof tile manufacturer in the United States.***E.O. 12866 Review

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- 20 analysis, the factors supporting the growth are the increases in housing starts and construction spending for commercial buildings similar to what is evident from the Boral USA example.

2.5.1 Market Prices
Average prices for brick and structural products vary by product type and over time. In 2010, the average price of brick was approximately $ 248 per 1,000 S.B.E., clay floor and wall tile was approximate ly $1.30 per square foot, and vitrified clay sewer pipe and fitting were $496 per short ton (Table 2

- 8 ). There is substantial variation in average brick prices across Census regions ($183 to $541) , as shown in Table 2

- 9 . Since 2005, average nominal prices for bricks and clay floor and wall tile have remained flat or fallen (Figure 2

- 2), while average nominal prices for other structural clay products have risen to higher levels.

Table 2

- 8

. Average Price of Principal Brick and Structural Clay Products Shipped: 2010

Product Average Price Units Brick, building or common and facing $248 $ per 1,000 S.B.E. Vitrified clay sewer pipe and fittings $496 $ per short ton

Sources: U.S. Census Bureau, 2011.

Table 2

- 9

. Regional Variation in Average Prices of Brick, Building or Common and Facing: 2010

Census Region $ per 1,000 S.B.E.
New England $379

Middle Atlantic $324

East North Central $297

West North Central $272

South Atlantic $227

East South Central $183

West South Central $225

Mountain $355

Pacific $541

United States $248

Sources: U.S. Census Bureau, 2011.***E.O. 12866 Review

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- 21 Figure 2

- 2. Real Price Trends for Brick and Structural Clay Products

Source: U.S. Bureau of the Labor Statistics, 2013a,b

2.6 References

Boral Limited. 2012. Annual Report 2012

. http://www.boral.com.au/Images/common/pdfs/annual

- reports/Boral

- Annual

- Report

2012.pdf

. Brick Industry Association. 2013a. An Overview of the American Brick Industry. http://www.gobrick.com/resources/americanbrickindustry/tabid/7644/default.as
px ( accessed on August 16, 2013).

Brick Industry Association. 2013b. 2012 Brick Industry Annual Report

. V ersion 4.0.

Federal Reserve Board. 2013. Industrial Production and C apacity Utilization

— G.17. http://www.federalreserve.gov/releases/g17/ (August 16, 2013).

Ho, M., R. Morgenstern, J. Shih. 2008 . Impact of Carbon Price Policies on U.S. Industry. Resources for the Future Discussion Paper DP 08

- 37

. http://www.rff.org/documents/RFF

- DP

- 08

- 37.pdf

.
Midwest Research Institute. 2001. Industry Characterization for Brick and Structural Clay Products Manufacturing

.***E.O. 12866 Review

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- 22 Mohawk Industries, Inc. 2012. 2011 Annual Report

. http://phx.corporate

ir.net/External.File?item=UGFyZW50SUQ9MTMzMjE1fENoaWxkSUQ9LTF8VHlwZ T0z&t=1

. National Association of Homebuilders. 2013. NAHB Study Reveals What Home Buyers Really Want. February 19, 2013.

Rutherford, T.F. 2002. Lecture Notes on Constant Elasticity Functions. http://www.gamsworld.eu/mpsge/debreu/ces.pdf

.
Saint

- Gobain. 2003 Annual Report 2002 . http://www.saint

gobain.com/files /Rapport_annuel_2002_EN.pdf

.
Saint

- Gobain. 2013. Registration Document 2012. http://www.saint

gobain.com/files/Rapport_annuel_2012_EN.pdf

. U.S. Bureau of Labor Statistics. 2013a. Employment, Hours, and Earnings from the Current Employment Statistics survey (National) Series ID: CEU3132700003.

U.S. Bureau of Labor Statistics. 2013b. Consumer Price Index

— All Urban Consumers Series ID: CUUR0000SA0.

U.S. Census Bureau 2013 a

. Annual Survey of Manufactures: General Statistics: Statistics for Industry Groups and I ndustries: 2011 and 2010; generated by RTI International; using American Factfinder. http://factfinder2.census.gov . ( August 16, 2013).

U.S. Census Bureau. 2013 b. Geography Area Series: County Business Patterns: 2011; generated by RTI International; using American Factfinder

. http://factfinder2.census.gov

. (August 16, 2013).

U .S. Census Bureau. 2013c . Historical New Residential Construction Started. http://www.census.gov/construction/nrc/historical_data/

. (August 16, 2013).

U.S. Census Bureau. 2013d . New Residential Construction Press Release

. August 16, 2013. http://www.census.gov/construction/nrc/

. (August 16, 2013).

U.S. Census Bureau. 2013e. Manufacturing: Subject Series: Concentration Ratios: Share of Value of Shipments Accounted for by the 4, 8, 20, and 50 Largest Companies for Industries : 2007; generated by RTI Internatio nal; using American Factfinder. http://factfinder2.census.gov . ( September 12, 2013).

U.S. Department of Commerce, Census Bureau

. 2011: Current Industrial Reports for Clay Construction Products

— Summary 2010.

U.S. Department of Commerce, Census Bureau

. 2009: Current Industrial Reports for Clay Construction Products

— Summary 2008.***E.O. 12866 Review

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- 23 U.S. Department of Commerce, Census Bureau

. 2007: Curre nt Industrial Reports for Clay Construction Products

— Summary 2006.

U.S. Department of Commerce, Census Bureau

. 2005: Current Industrial Reports for Clay Construction Products

— Summary 2004.

U.S. Department of Commerce, Census Bureau

. 2004: Current Industria l Reports for Clay Construction Products

— Summary 2003.

U.S. Department of Commerce, Census Bureau

. 2003: Current Industrial Reports for Clay Construction Products

— Summary 2002.

U.S. Department of Commerce, Census Bureau

. 2002: Current Industrial Reports fo r Clay Construction Products

— Summary 2001.

U.S. Department of Commerce, Census Bureau

. 2000: Current Industrial Reports for Clay Construction Products

— Summary 1999.

U.S. Department of Commerce, Census Bureau

. 2000. Current Industrial Reports for Clay Const ruction Products

— Summary 1998.

U.S. Department of Commerce, Census Bureau

. 1998: Current Industrial Reports for Clay Construction Products

— Summary 1997.

U.S. Department of Commerce, Census Bureau. 1996. Current Industrial Reports for Clay Construction Prod ucts; Summary, 1995.

U.S. Department of Commerce, Census Bureau

. 1995: Current Industrial Reports for Clay Construction Products

— Summary 1994.

U.S. Department of the Interior, U.S. Geological Survey

. May 2013

. 2011 Minerals Yearbook, Clay and Shale [Advanc e Release]

. http://minerals.usgs.gov/minerals/pubs/commodity/clays/myb1

- 2011

- clays.pdf

. U.S. Department of Transportation, Bureau of Transportation Statistics. 2010. 2007 Commodity Flow Survey United States. Table 15. http://www.rita.dot.gov/bts/sites/rita.dot.gov.bts/files/ publications/commodity_flow_surv ey/final_tables_december_2009/index.html

. U.S. Environmental Protection Agency. 1997. Emission Factor Documentation for AP

- 42, Section 11.3

, “ Brick and Structural Clay Products Manufacturing: Final Report. ” http://www.epa.gov/ttnchie1/ap42/ch11/bgdocs/b11s03.pdf

U.S. Geological Survey. 2011. Minerals Yearbook: Clay and Shale. Written by R. L. Virta. http://minerals.usgs.gov/minerals/pubs/commodity/clays/m yb1

- 2011

- clays.pdf

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- 24 U.S. International Trade Commission. Interactive Trade and DataWeb. U.S. Imports for Consumption and U.S. Domestic Exports, NAICS 327121. (December 31, 2013). http://dataweb.usitc.gov/ , then sea rch for NAICS 327121.

U.S. Small Business Administration (SBA). 2013. Table of Small Business Size Standards. http://www.sba.gov/sites/default/files/files/size_table_07222013.pdf

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3

- 1 SECTION 3
ENGINEERING COST ANALYSIS

Production of BSCP results in emissions of pollutants such as hydrogen fluoride (HF ), hydrogen chloride (HCl), chlorine (Cl 2 ), mercury (Hg), and non

- Hg hazardous air pollutant (HAP) metals from the kilns used in the production process. To control these emi ssions, EPA has developed emission standards for these HAPs under the authority of Section 112 of the CAA.
This section explains how the estimate s of compliance costs associated with this regulation w ere developed , and it is organized as follows:

■ Section 3 .1, Summary of National Costs by Regulatory Approach: This section describes the regulatory approaches considered in this analysis and presents the annual cost for each of the compliance options and the various regions of the country. It also describes the air pollution control devices (APCDs) and the pollutants targeted because they are key to understanding how the annual costs were obtained.

■ Section 3.2, Summary of Costs by Control Device: There are various APCD implementation options to meet the complian ce requirements. This section presents the overall capital and annual costs for those implementation options. It also provides key considerations for how the costs were derived.

3.1 Summary of National Costs by Regulatory Approach

EPA evaluated costs for affe cted BSCP facilities under three two regulatory approaches:

■ Option 1 (Proposed Rule) :

– Acid gases: Meet HBS

. for acid gases,

– Hg: C c hoice of MACT limit for Hg in lb/ton

, or concentration, or lb/hr

.

■ – PM/total non

- Hg HAP metals: and a C c hoice of MACT limits for PM in lb/ton or gr/dscf (calculated based on data from kilns with fabric filter

- based APCD, up to 12 percent of the kilns in the industry) or non

- Hg HAP metals in lb/hr for all kilns.

■ Option 2 Final Rule :

– Acid gases: Meet HBS for acid gases,

.

– Hg: C c hoice of MACT limit

, with consideration of raw material variability, for Hg in lb/ton

, or concentration, or lb/hr

.

■ – PM/total non

- Hg HAP metals: and a C c hoice of MACT limits for PM in lb/ton or gr/dscf or non

- Hg HAP metals lb/hr for s mall and large kilns (calculated based on 12 percent of the data in the subcategory)

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- 2 ■ Option 3 (Final Rule but without size subcategories for PM/ total non

- Hg HAP metals) :

– Acid gases: Meet HBS

. for acid gases,

– Hg: C c hoice of MACT limit, with consideration of raw material variability, for Hg in lb/ton

, or concentration, or lb/hr

.

■ – PM/total non

- Hg HAP metals: and a c C hoice of MACT limits for PM in lb/ton or gr/dscf or non

- Hg HAP metals lb/hr for all kilns (calculated based on 12 percent of the data in the ind ustry)

.
All approaches assume the facility would choose to become a Synthetic Area (SA) by installing dry limestone adsorbers (DLAs) on uncontrolled kilns if that is less expensive than installing the control needed to comply with the compliance option. All approaches have separate Hg numeric limits for large and small kilns, and the HBS applies to all kilns at the facility for all compliance options. All approaches assume the facility would choose to become a Synthetic Area (SA) by installing dry limesto ne adsorbers (DLAs) on uncontrolled kilns if that is less expensive than installing the control needed to comply with the compliance option.

These costs include the implementation of various APCDs. The following are the APCDs
considered:

■ Dry injection fabr ic filter (DIFF). DIFFs are used to remove HF, HCl, Cl 2 , sulfur dioxide ( SO 2 ), and PM. They work by injecting hydrated lime (a dry lime powder) into the kiln exhaust. The lime and kiln exhaust mix in a reaction chamber or an exhaust duct and are ducted to a fabric filter. The lime reacts with and removes HF, HCl, Cl 2 , and SO 2 from the exhaust str eam.

■ Dry lime scrubber/ fabric filter (DLS/FF). DLS/FFs are used to control HF, HCl, Cl 2 , SO 2 , and PM emissions. These systems mix hydrated lime and water in a conditioning drum and then inject the lime/water slurry into a reaction chamber, where the slurr y mixes with the kiln exhaust. Acid gas removal takes place in the reaction chamber, subsequent ductwork, and across the lime

- caked fabric filter bags. From the reaction chamber, the exhaust stream is ducted to a fabric filter for PM removal.

■ Dry limestone adsorber (DLA). DLAs are used to control HF, HCl, Cl 2 , and SO 2 emissions. Limestone is fed into the top of a reaction chamber countercurrent to the kiln exhaust gases. The limestone cascades through multiple baffles within the chamber and reacts with and removes HF and, to a lesser degree, HCl , Cl 2 and SO 2 from the kiln exhaust. The system does not provide a mechanism for controlling PM.

■ Fabric filter (FF). FFs are used to control PM emissions. Most FFs use long, cylindrical bags made of a woven material that acts as a filter medium. Gas enters the Formatted: bullets-2nd level, Keep with next

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- 3 FF and is drawn through the bags, and PM accumulates in layers on the surface of the filter media until gas can no longer move through the bag. When the system reaches a sufficient pressure drop due to PM build

- up, the bag will be cleaned. The system does not provide a mechanism for controlling Hg, HCl, Cl 2 , or SO 2

.

■ Activated carbon injection (ACI). An ACI system would pneumatically inject activated carbon into the flue gas ductwork of a kiln. The activated carbo n adsorbs the vaporized mercury from the flue gas and is then collected with the fly ash in a particulate collection device. This device is assumed to work with a fabric filter for particulates collection.

Cost estimates were developed for each BSCP facili ty assuming the APCDs are implemented according to various scenarios. In general, an FF and ACI were assumed to be the
APCD needed to meet the MACT limits for an uncontrolled kiln. Table 3

- 1 presents the general implementation scenarios for tunnel kilns re quired to meet MACT for all pollutants.

Table 3

- 1. APCD Implementation Scenarios to Meet MACT Limits

APCD Meets Non

- Hg HAP Metals or

PM Limit Meets Mercury Limit APCD Implementation Scenario

None Yes No Install new FF with ACI

None No Yes Install new FF

None No No Install new FF with ACI Existing DIFF Yes Yes No action Existing DIFF Yes No Add ACI Existing DIFF No Yes Retrofit DIFF for PM control Existing DIFF No No Retrofit DIFF for PM control ; add ACI Existing DLS/FF Yes Yes No action Existing DLA Yes No Add FF with ACI Existing DLA No Yes Add FF Existing DLA No No Add FF with ACI

The option to “ Install new DLA ” was evaluated for facilities to become an SA. All
scenarios in Table 3

- 1 assume meeting the HBS for acid gases.

The following are the scenarios considered to meet the HBSs:

■ If a kiln can meet the non

- Hg HAP metals or PM and Hg MACT limits and is located at a facility that can meet the health

- based limits, no additional costs would be incurred.***E.O. 12866 Review

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- 4 ■ If an uncontrolled kiln or a kiln with a DLA is located at a facility that can meet the health

- based limits, then only a n FF would be needed to meet the non

- Hg HAP metals or PM MACT limit, and activated carbon injection would be needed to meet the Hg MACT limit

.

■ Because the health

- based limits a re on a facility

- wide basis, the owner or operator of a facility not meeting the health

- based limits with current controls may not have to add an APCD to every uncontrolled kiln and enhance every existing APCD. Engineering judgment was used to assign minim um control “ actions needed ” based on a review of the contribution of each emission point ’ s to the allow able HCl

equivalent emissions. Additional information about this assessment is presented in the memorandum “ Development of Cost and Emission Reduction Impacts for the Final BSCP NESHAP ” included in the docket.

Table 3

- 2 presents the annual cost for each of the regulatory approaches.

Table 3

- 2

. National Annual Costs of Compliance (2011 million USD)

Regions Option 1 Option 2 Final Ru le Option 3

NEG New England $0 $0 $0

MID Middle Atlantic $2 $2 $2

ENC East North Central $3 $3 $6

WNC West North Central $1 $1 $3

SAC South Atlantic $8 $9 $16

ESC East South Central $4 $4 $7

WSC West South Central $6 $5 $9

MTN Mountain $0 $0 $1

PAC Pacific $0 $0 $2

USA United States $24 $25 $47

USA United States , with recordkeeping and reporting $2 7 $2 8 $ 50

3.2 Summary of Costs by Control Device
A key component of the total annual costs presented in Table 3

- 1 is the implementation cost of the APCDs required to (1) meet the MACT limits for Hg and for non

- Hg HAP metals or
PM , (2) become an SA source, and/or (3) meet an HBS for acid gases, according to the compliance options. This section provides an overview of how the capital and annual costs of implementation were estimated. Additional information about those estimates is provided in the***E.O. 12866 Review

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- 5 memorandum “ Development of Cost and Emission Reduction Impacts for the Final BSCP
NESHAP ” included in the docket.

Consistent with the information presented in Section 3

. 1 , the following are the APCD implementation scenarios considered in this analysis:

■ Install new DLA

■ Install new FF

■ Install new ACI

■ Install new FF and ACI

■ Retrofit with DIFF

■ Retrofit with DIFF and ACI

■ N o action

Table 3

- 3 presents the capital and annual costs of each implementation option.

Table 3

- 3. Capital and Annual Costs of APCD Implementation Scenarios (2011 USD)

Control Option s Capital Costs Annual Costs

Small APCD Large APCD Small APCD Large APCD

Install new DLA $1,096,473 $1,489,548 $358,556 $459,886

Install new FF $1,200,000 $1,500,000 $503,144 $579,541

Install new ACI $102,224 $146,697 $81,307 $105,763

Install new FF and ACI $2,800,000 $3,820,000 $804,907 $1,017,978

Retrofit with DIFF $2,902,224 $3,966,697 $886,214 $1,123,741

Retrofit with DIFF and ACI $1,096,473 $1,489,548 $358,556 $459,886

C osts are presented for small and large APCD s

. A small control device would be used if
the operating capacity of the kiln(s) being routed to that device is less than 10 tons of bricks per
hour. A large control device would be used if the operating capacity of the kiln(s) being routed to
that device is 10 tons of bricks or more per hour. Capital cost data were generally obtained from the Information Collection Request (ICR) and supplemented with information from literature

sources.***E.O. 12866 Review

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- 6 The estimates of annual cost include

■ operation and maintenance (O&M) labor;

■ materials ;

■ electricity;

■ waste disposal ;

■ o verhead ; and

■ property taxes, insurance, and administration

.
Information pertaining to cost data sources and how they were used to develop unit costs for each APCD is provided in the memorandum “ Methodology and Assumptions Used to
Estimate the Final Model C osts and Impacts of BSCP Air Pollution Control Devices. ”

Annualization of the capital c o sts involves establi s hing an annual “ pay ment ” sufficient to
finance the invest m ent over the expected lifeti me of the equip ment or loan period. This pay m ent is typically referred to as t h e “ ca p ital recovery cost. ” The t h ree key inputs into the capital recovery costs are the capital costs, the interest rate, and the equipment life. This analysis
assumed a 20

- year equipment life and a 7% interest rate, which corresponds to the interest rate used in OAQPS ’ s analyses.

3.3 Summary of Results
This section presents total annualized costs for each regulatory approach. Total annualized cost is the sum of the annualized capital cost and the annual costs. The followin g is a summary of t hose results :

■ Option 1 : approximately $ 2 7 million

■ Option 2 Final Rule : approximately $ 2 8 million

■ Option 3: approximately $ 50 million

Annual costs listed above for each compliance option also include costs for testing and monitoring, along with recordkeepin g and reporting costs incurred by facilities that ha ve testing and monitoring costs 1

.

1 Recordkeeping and reporting costs reflect the annualized present value of the stream of recordkeeping and

reporting labor costs (reported in Section 6.3). between 2015 and 2038 ($3 million).***E.O. 12866 Review

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- 7 The consideration of raw material variability in the Hg limits in Options 2 and 3 result s in less stringent limits compared to Option 1, but the difference is not great enough to have a significant impact on the nationwide costs. In addition, c ompared to Option 1, Option 2 has more stringent PM/total non

- Hg HAP metals limits for large kilns but less stringent PM/total non

- Hg
HAP metals limi ts for small kilns. Therefore, more small kilns would be expected to meet the
PM/total non

- Hg HAP metals limits under Option 2, but fewer large kilns would be expected to
meet the PM/total non

- Hg HAP metals limits under Option 2. As a result, the overall c osts are slightly higher under Option 2 because more of the APCD being installed are larger, more expensive units.

The only difference between Option 2 and Option 3 is that Option 3 does not have size subcategories for PM/total non

- Hg HAP metals limits . Th e PM/total non

- Hg HAP metals limits
for all kilns under Option 3 are either equivalent or very close to the large kiln PM/total non

- Hg HAP metals limits for large kilns under Option 2. This has the effect of requiring all small kilns

to meet a significantl y more stringent limit under Option 3, and as shown in Table 3

- 4, more than twice the number of APCD would be needed to meet Option 3 compared to Options 1 or 2. Over half of the APCD expected to be installed would be DLA installed on uncontrolled kilns fo r purposes of becoming SA facilities.

When looking at annual costs per region of the country, t he South Atlantic region ( SAC ) consistently exhibit s the highest cost and the Pacific region ( P AC) the lowest nonzero cost.

Retrofitting with DIFF and ACI is the option that exhibits the highest cost and installing a new ACI system the lowest, which is consistent with the capital cost results.

We provide additional details on the number of stack s required to take action to achieve compliance (Table 3

- 4). Additiona l details on existing baseline control devices is presented in
the memorandum “ Development of Cost and Emission Reduction Impacts for the Final BSCP
NESHAP ” included in the docket.***E.O. 12866 Review

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- 8 Table 3

- 4

. Number of Stacks Taking Actions to Achieve Compliance (2011 USD )

Action to Achieve Compliance

Standards Parameter Install DLA (become SA) Install FF Install FF + ACI Add ACI to Existing APCD Retrofit with DIFF Totals Option 1 Number of Stacks 1 5 9 1 5 5 1 45

Capital Cost $1 9.6 $ 13.2 $2 4.7 $0. 733 $3.82 $ 62.0
Annual Cost $ 6.19 $ 5.14 $10. 3 $0. 529 $ 1.02 $ 23.2 Option 2 Number of Stacks 8 13 16 5 1 43

Capital Cost $ 11.9 $ 19.5 $2 6.3 $0. 733 $3.82 $ 62.3
Annual Cost $ 3.68 $7. 53 $ 11.0 $0. 52 9 $ 1.02 $2 3.7 Option 3 Number of Stacks 54 24 14 4 1 98
Capital Cost $63.5 $33.6 $23.1 $0.587 $3.82 $128
Annual Cost $20.5 $13.3 $9.59 $0.423 $1.02 $45.8***E.O. 12866 Review

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- 1 SECTION 4
HUMAN HEALTH BENEFIT S OF EMISSIONS REDUC TIONS

Synopsis
Implementation of emissions controls required by the Brick and Structural Clay NESHAP is expected to reduce direct emissions of p articulate m atter (including PM 2.5 ) and
sulfur d ioxide ( SO 2 ) that are the result of emissions limits that are being tightened for a number of categories, and imposed for the first time for other categories

. In this section, we quantify the
monetized co

- benefits for this rule associated with reducing exposure to amb ient fine particulate matter (PM 2.5 ) by reducing emissions of precursors. The total PM 2.5 and SO 2 reductions are the consequence of the expected design changes to the affected manufacturing plants needed in order to meet the multiple limits. We estimate th e total monetized co

- benefits of the final rule to be $83 million to $190 million at a 3% discount rate and $ 7 5 million to $170 million at a 7%
discount rate in 2018 , including consideration of energy disbenefits

. All estimates are in 2011$ as they are sum marized in Table 4

- 1 . These estimates reflect the monetized human health benefits of reducing cases of morbidity and premature mortality among populations exposed to PM 2.5 reduced by this rule . Data, resource, and methodological limitations prevented EPA f rom monetizing the benefits from several important benefit categories, including benefits from reducing exposure up to 375 tons of HAP (acid gases and metals) each year, as well as reducing ecosystem effects and visibility impairment.

4.1 PM 2.5 - Related Human Health Co

- b enefits
This rule is expected to reduce direct emissions of PM and emissions of SO 2 , which is a precursor to formation of ambient PM 2.5 . Therefore

, reducing these emissions would also reduce human exposure to ambient PM 2.5 and the incidence of P M 2.5 - related health effects. In this section, we provide an overview of the PM 2.5 - related benefits. A full description of the underlying data, studies, and assumptions is provided in the PM NAAQS RIA (U.S. EPA, 2012a).

In implementing this rule, emission c ontrols may lead to reductions in ambient PM 2.5 concentrations below the National Ambient Air Quality Standards (NAAQS) for PM in some areas and assist other areas with attaining the PM NAAQS. Because the PM NAAQS RIA (U.S. EPA, 2012a) also calculated PM benefits, t here are important differences worth noting in the design and analytical objectives of each RIA. The NAAQS RIAs illustrate the potential costs and benefits of attaining a revised air quality standard nationwide based on an array of emission reduction strategies for different sources including known and unknown controls, incremental to***E.O. 12866 Review

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- 2 implementation of ex isting regulations and controls need to attain the current standards. In short, NAAQS RIAs hypothesize, but do not predict, the reduction strategies that States may choose to enact when implementing a revised NAAQS. The setting of a NAAQS does not directly result in costs or benefits, and as such, the NAAQS RIAs are merely illustrative and the estimated costs and benefits are not intended to be added to the costs and benefits of other regulations that result in specific costs of control and emission reducti ons. However, it is possible that some costs and benefits associated with the required emission controls estimated in this RIA may account for the same air quality improvements as estimated in the illustrative PM NAAQS RIA.

By contrast, the emission reduc tions for implementation rules such as this rulemaking are generally for specific, well

- characterized sources. In general, EPA is more confident in the magnitude and location of the emission reductions for implementation rules. As such, emission
reductions achieved under these and other promulgated implementation rules will ultimately be reflected in the baseline of future NAAQS analyses, which would reduce the incremental costs and benefits associated with attaining revised future NAAQS. EPA remains forwar d looking
towards the next iteration of the 5

- year review cycle for the NAAQS. As a result, EPA does not

re

- issue NAAQS RIAs that retroactively update the baseline to account for implementation rules promulgated after a NAAQS RIA outside of the NAAQS revie w process. For more information on the relationship between the NAAQS and implementation rules such as analyzed here, please see Section 1.3 of the PM NAAQS RIA (U.S. EPA, 2012a ).

4.1.1 Health Impact Assessment

The Integrated Science Asse ssment for Particulate Matter (PM ISA) (U.S. EPA, 2009)
identified the human health effects associated with ambient PM 2.5, which include premature morality and a variety of morbidity effects associated with acute and chronic exposures. Table
4

- 1 provides t he quantified and unquantified benefits captured in EPA ’ s benefits estimates for reduced exposure to ambient PM 2.5 . Although the table below does not include entries for the unquantified health effects such as exposure to ozone and NO 2 nor welfare effects such as ecosystem effects and visibility impairment, these effects are itemized in Chapters 5 and 6 of the PM NAAQS RIA (U.S. EPA, 2012a). It is important to emphasize that the list of unquantified benefit categories is not exhaustive, nor is quantificatio n of each effect complete.***E.O. 12866 Review

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- 3 Table 4

- 1. Human Health Effects of Ambient PM 2.5

Category Specific Effect Effect Has Been Quantified Effect Has Been Monetized More Information

in PM NAAQS RIA
Improved Human Health

Reduced incidence of premature mortality from exposure to PM 2.5 Adult premature mortality based on cohort study estimates and expert elicitation estimates (age >25 or age >30)   Section 5.6

Infant mortality (age <1)   Section 5.6

Reduced incidence of morbidity from exposure to PM 2.5 Non

- fatal heart attacks (age > 18)   Section 5.6
Hospital admissions

— respiratory (all ages)   Section 5.6
Hospital admissions

— cardiovascular (age >20)   Section 5.6

Emergency room visits for asthma (all ages)   Section 5.6

Acute bronchitis (age 8

– 12)   Section 5.6
Lower respiratory symptoms (age 7

– 14)   Section 5.6
Upper respiratory symptoms (asthmatics age 9

– 11)   Section 5.6

Asthma exacerbation (asthmatics age 6

– 18)   Section 5.6
Lost work days (age 18

– 65)   Section 5.6

Minor restricted

- activity days (age 18

– 65)   Section 5.6
Chronic Bronchitis (age >26)

-- a

-- a Section 5.6
Emergency room visits for cardiovascular effects (all ages) -- a

-- a Section 5.6

Strokes and cerebrovascular disease (age 50

– 79) -- a

-- a Section 5.6

Other cardiovascular effects (e.g., other ages)

-- -- PM ISA b
Other respiratory effects (e.g., pulmonary function, non

- asthma ER visits, non

bronchitis chronic diseases, other ages and populations) -- -- PM ISA b

Reproductive and developmental effects (e.g., low birth weight, pre

- term births, etc.) -- -- PM ISA b,c

Cancer, mutagenicity, and genotoxicity effects -- -- PM ISA b,c

a We assess these benefits qualitatively due to time and resource limitations for this analysis. In the PM NAAQS

RIA, these benefits were quantified in a sensitivity analysis, but not in the core analysis.

b We assess these benefits qualitatively because we do not have sufficient confidence in available data or methods.

c We assess these benefits qualitative ly because current evidence is only suggestive of causality or there are other

significant concerns over the strength of the association.***E.O. 12866 Review

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- 4 We follow a “ damage

- function ” approach in calculating benefits, which estimates changes in individual health endpoints (specific effects that can be associated with changes in air quality) and assigns values to those changes assuming independence of the values for those individual endpoints. Because EPA rarely has the time or resources to perform new research to
measure d irectly either the health outcomes or their values for regulatory analyses, our estimates are based on the best available methods of benefits transfer, which is the science and art of adapting primary research from similar contexts to estimate benefits for the environmental quality change under analysis.

The health impact assessment (HIA) quantifies the changes in the incidence of adverse health impacts resulting from changes in human exposure to PM 2.5 or other air pollutants. We
use the environmental Ben efits M apping and A nalysis P rogram (BenMAP) to systematize health impact analyses by applying a database of key input parameters, including population projections, health impact functions, and valuation functions (Abt Associates, 2012). For this

assessment , the HIA is limited to those health effects that are directly linked to ambient PM 2.5 concentrations. Epidemiological studies generally provide estimates of the relative risks of a particular health effect for a given increment of air pollution (often per 10 μg/m 3 for PM 2.5 ). These relative risks can be used to develop risk coefficients that relate a unit reduction in PM 2.5 to changes in the incidence of a health effect. We refer the reader to section 5.6 of the PM NAAQS RIA for more information regarding the epidemiology studies and risk coefficients applied in this analysis (U.S. EPA, 2012a), and we briefly elaborate on adult premature mortality below. The size of the mortality effect estimates from epidemiological studies, the serious nature
of the effec t itself, and the high monetary value ascribed to prolonging life make mortality risk reduction the most significant health endpoint quantified in this analysis.

Considering a substantial body of published scientific literature, reflecting thousands of epi demiology, toxicology, and clinical studies, the PM ISA documents the association between
elevated PM 2.5 concentrations and adverse health effects, including increased premature mortality (U.S. EPA, 2009). The PM ISA, which was twice reviewed by the Clean Air Scientific Advisory Committee of EPA ’ s Science Advisory Board (SAB

- CASAC) (U.S. EPA

- SAB, 2009b, 2009c), concluded that there is a causal relationship between mortality and both long

- term and
short

- term exposure to PM 2.5 based on the entire body of scie ntific evidence. The PM ISA also concluded that the scientific literature consistently finds that a no

- threshold log

- linear model most adequately portrays the PM

- mortality concentration

- response relationship while recognizing potential uncertainty about th e exact shape of the concentration

- response function.***E.O. 12866 Review

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- 5 For mortality, we use the effect coefficients from the most recent epidemiology studies examining two large population cohorts: the American Cancer Society cohort (Krewski et al.,
2009 ) and the Harvard Six Cities cohort (Lepeule et al., 2012 ). The PM ISA (U.S. EPA, 2009) concluded that the ACS and Six Cities cohorts provide the strongest evidence of the association between long

- term PM 2.5 exposure and pre mature mortality with support from a number of
additional cohort studies. The SAB ’ s Health Effects Subcommittee (SAB

- HES) also supported using these two cohorts for analyses of the benefits of PM reductions (U.S. EPA

- SAB, 2010a).
As both the ACS and Six Ci ties cohort studies have inherent strengths and weaknesses, we present benefits estimates using relative risk estimates from both these cohorts (Krewski et al., 2009; Lepeule et al., 2012).

As a characterization of uncertainty regarding the PM 2.5 - mortalit y relationship, EPA graphically presents benefits derived from EPA ’ s expert elicitation study (Roman et al., 2008; IEc, 2006). The primary goal of the 2006 study was to elicit from a sample of health experts probabilistic distributions describing uncertain ty in estimates of the reduction in mortality among the adult U.S. population resulting from reductions in ambient annual average PM 2.5 levels. In that study, twelve experts provided independent opinions of the PM 2.5 - mortality concentration

response funct ion. Because the experts relied upon the ACS and Six Cities cohort studies to
inform their concentration

- response functions, the benefits estimates derived from the expert responses generally fall between results derived from the these studies (see Figure 7

- 1). We do not combine the expert results in order to preserve the breadth and diversity of opinion on the expert panel. This presentation of the expert

- derived results is generally consistent with SAB advice (U.S. EPA

- SAB, 2008), which recommended that t he EPA emphasize that “ scientific differences existed only with respect to the magnitude of the effect of PM 2.5 on mortality, not
whether such an effect existed ” and that the expert elicitation “ supports the conclusion that the
benefits of PM 2.5 control a re very likely to be substantial. ” Although it is possible that newer scientific literature could revise the experts ’ quantitative responses if elicited again, we believe that these general conclusions are unlikely to change.

4.1.2 Economic Valuation
After quantifying the change in adverse health impacts, we estimate the economic value of these avoided impacts. Reductions in ambient concentrations of air pollution generally lower the risk of future adverse health effects by a small amount for a large p opulation. Therefore, the appropriate economic measure is willingness to pay (WTP) for changes in risk of a health effect. For some health effects, such as hospital admissions, WTP estimates are generally not available, so we use the cost of treating or mi tigating the effect. These cost

- of

- illness (COI) estimates***E.O. 12866 Review

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- 6 generally (although not necessarily in every case) understate the true value of reductions in risk of a health effect. They tend to reflect the direct expenditures related to treatment but not the value of avoided pain and suffering from the health effect. The unit values applied in this analysis are provided in Table 5

- 9 of the PM NAAQS RIA for each health endpoint (U.S. EPA, 2012a).

Avoided premature deaths account for 98% of monetized PM

- related benefits. The economics literature concerning the appropriate method for valuing reductions in premature mortality risk is still developing. The adoption of a value for the projected reduction in the risk of premature mortality is the subject of continuing discussion within the economics and public policy analysis community. Following the advice of the SAB ’ s Environmental Economics Advisory Committee (SAB

- EEAC), the EPA currently uses the value of statistical life (VSL) approach in calculating estimates of mortality benefits, because we believe this calculation provides the most reasonable single estimate of an individual ’ s willingness to trade off money for reductions in mortality risk (U.S. EPA

- SAB, 2000). The VSL approach is a summary
measure for the valu e of small changes in mortality risk experienced by a large number of people.

EPA continues work to update its guidance on valuing mortality risk reductions, and the Agency consulted several times with the SAB

- EEAC on the issue. Until updated guidance is

a vailable, the Agency determined that a single, peer

- reviewed estimate applied consistently best
reflects the SAB

- EEAC advice it has received. Therefore, EPA has decided to apply the VSL that was vetted and endorsed by the SAB in the Guidelines for Preparin g Economic Analyses (U.S. EPA, 2000) 11 while the Agency continues its efforts to update its guidance on this issue. This approach calculates a mean value across VSL estimates derived from 26 labor market and contingent valuation studies published between 19 74 and 1991. The mean VSL across these studies is $6.3 million (2000$). 12

We then adjust this VSL to account for the currency year used in this RIA and to account for income growth from 1990 to the analysis year. The adjusted value for VSL is $ 9

. 7 million ($201 1 ). Further details on the methodology are available in section 5.6.8 of the PM RIA (U.S.EPA, 2012a).

11 In the updated Guidelines for Preparing Economic Analyses (U.S. EPA, 2010e), EPA retained the VSL endorsed

by the SAB with the understanding that further updates to the mortality risk valuation guidance would be forthcoming in the near future.

12 In 1990$, this VSL is $4 .8 million.***E.O. 12866 Review

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- 7 The Agency is committed to using scientifically sound, appropriately reviewed evidence in valuing mortality risk reductions and has made sig nificant progress in responding to the SAB

EEAC ’ s specific recommendations. In the process, the Agency has identified a number of important issues to be considered in updating its mortality risk valuation estimates. These are detailed in a white paper on “ Valuing Mortality Risk Reductions in Environmental Policy, ” (U.S. EPA, 2010c) which recently underwent review by the SAB

- EEAC. A meeting with the SAB on this paper was held on March 14, 2011 and formal recommendations were transmitted on July 29, 2011 (U.S . EPA

- SAB, 2011). Draft guidance responding to SAB recommendations will be developed shortly.

In valuing premature mortality, we discount the value of premature mortality occurring in future years using rates of 3% and 7% (OMB, 2003). We assume that there is a “ cessation ” lag between changes in PM exposures and the total realization of changes in health effects. The distributed lag accounts for the expected distribution of avoided deaths according to the cause of death. The lag assumes that the initial prop ortion of deaths is due to cardiovascular outcomes, while the latter proportion is due to lung cancer. Although the structure of the lag is uncertain,
the EPA follows the advice of the SAB

- HES to assume a segmented lag structure characterized by 30% of mor tality reductions in the first year, 50% over years 2 to 5, and 20% over the years 6
to 20 after the reduction in PM 2.5 (U.S. EPA

- SAB, 2004c). Changes in the cessation lag assumptions do not change the total number of estimated deaths but rather the timing of those
deaths.

4.1.3 Benefit

- per - T on Estimates
Due to analytical limitations, it was not possible to conduct air quality modeling for this rule. Instead, we used a “ benefit

- per

- ton ” approach to estimate the benefits of this rulemaking. EPA has applied in seve ral previous RIAs (e.g., U.S. EPA, 2011b, 2011d, 2012b ). These benefit

per

- ton estimates provide the total monetized human health benefits (the sum of premature mortality and premature morbidity) of reducing one ton of PM 2.5 (or PM 2 .5 precursor such as
NO x or SO 2 ) from a specified source. Specifically, in this analysis, we multiplied the estimates
from the “ Other Non

- EGU Point ” sector 13

, 14 by the corresponding emission reductions. The
method used to derive these estimates is described in the Technical Support Document (TSD) on estimating the benefits

- per

- ton of reducing PM 2.5 and its precursors from 17 sectors (U.S. EPA,

13 As explained in the TSD (U.S. EPA, 2013), we only have benefit

- per

- ton estimates for certain analysis years (i.e., 2005, 2016, 2020, 2025, and 2030). For this RIA, we selected the benefit

- per

- ton estimate closest to the analysis year for this RIA.

14 [Data from year 2016 was used as closest to full implementation year 2018 for this rule, and the sector was

matched with Non EGU Others category]***E.O. 12866 Review

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- 8 2013). One limitation of using the benefit

- per

- ton approach is an inability to provide estimates of
the health benefi ts associated with exposure to HAP, CO, NO 2 , or ozone.

The benefit

- per

- ton estimates described in the TSD (U.S. EPA, 2013) were derived using the approach published in Fann et al. (2012), but they have since been updated to reflect the
studies and population data in the final PM NAAQS RIA (U.S. EPA, 2012a). The approach in Fann et al. (2012) is similar to the work previously published by Fann et al. (2009), but the newer study includes improvements that EPA believes would provide more reliable estim ates of
PM 2.5 - related health benefits for emissions reductions in specific sectors. Specifically, the air quality modeling data reflect sectors that are more narrowly defined. In addition, the updated air quality modeling data reflects more recent emission s data (2005 rather than 2001) and has higher spatial resolution (12km rather than 36 km grid cells).

The benefit

- per

- ton of reducing directly emitted PM 2.5 from this sector represented by the above mentioned category is close to the median of the distrib ution of all 17 BPT values (TSD Table 7). For example, the sector ’ s BPT for directly emitted PM 2.5 is close t o the value for the
Cement Kilns sector and smaller than the Ferroalloys sector , but greater than the value for the
Coke Ovens or the Iron and Stee l sectors. The size of the benefit

- per

- ton estimate is influenced in part by factors including: proximity of sources to population receptors; the baseline health status of the population receptors; and, dispersion characteristics of the emitting source.

As noted below in the characterization of uncertainty, all benefit

- per

- ton estimates have inherent limitations. Specifically, all national

- average benefit

- per

- ton estimates reflect the geographic distribution of the modeled emissions, which may not exactly m atch the emission reductions in this rulemaking, and they may not reflect local variability in population density, meteorology, exposure, baseline health incidence rates, or other local factors for any specific
location . The photochemical modeled emissions of the bricks sector

- attributable PM 2.5 concentrations used to derive the BPT values may not match well the change in air quality resulting from the emissions controls described in Section 3 . For this reason, the health benefits reported here may be large r, or smaller, than those realized by this rule.

Even though we assume that all fine particles have equivalent health effects, the benefit

per

- ton estimates vary between precursors depending on the location and magnitude of their impact on PM 2.5 levels, wh ich drive population exposure. The sector

- specific modeling does not provide estimates of the PM 2.5 - related benefits associated with reducing VOC emissions, but these unquantified benefits are generally small compared to other PM 2.5 precursors (U.S. EPA,
2 012a).***E.O. 12866 Review

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- 9 4.1.4 PM 2.5 Co

- b enefits Results

Table 4

- 2 summarizes the monetized PM

- related health benefits by precursor pollutant, including the emission reductions and benefit

- per

- ton estimates using discount rates of 3% and
7%. Table 4

- 3 provides a summary of the re ductions in health incidences associated with these pollution reductions. Figure 4

- 1 provides a visual representation of the range of PM 2.5 - related benefits estimates using concentration

- response functions from Krewski et al. (2009) and Lepeule et al. (201 2) as well as the 12 functions supplied by experts. In Table 4

- 4, we provide the benefits using our anchor points of Krewski et al., and Lepeule et al., as well as the results from the 12 experts ’ elicitation on PM mortality.

4.1.5 Characterization of Uncertainty in the Monetized PM 2.5 Co

- b enefits
In any complex analysis using estimated parameters and inputs from numerous models, there are likely to be many sources of uncertainty. This analysis is no exception. This analys is includes many data sources as inputs, including emission inventories, air quality data from models (with their associated parameters and inputs), population data, population estimates, health effect estimates from epidemiology studies, economic data for monetizing benefits, and assumptions regarding the future state of the world (i.e., regulations, technology, and human behavior). Each of these inputs may be uncertain and would affect the benefits estimate. When the uncertainties from each stage of the a nalysis are compounded, even small uncertainties can have large effects on the total quantified benefits. Therefore, the estimates of annual benefits should be viewed as representative of the magnitude of benefits expected, rather than the actual
benefits that would occur every year.

This RIA does not include the type of detailed uncertainty assessment found in the PM NAAQS RIA (U.S. EPA, 2012a) because we lack the necessary air quality input and monitoring data to run the benefits model. However, the resul ts of the uncertainty analyses presented in the PM NAAQS RIA can provide some information regarding the uncertainty inherent in the benefits results presented in this analysis. Sensitivity analyses conducted for the PM NAAQS
RIA indicate that alternate ces sation lag assumptions could change the PM 2.5 - related mortality benefits discounted at 3% by between 10% and

− 27% and that alternate income growth adjustments could change the PM 2.5 - related mortality benefits by between 33% and

− 14%.***E.O. 12866 Review

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- 10 Table 4

- 2. Summary of Monetized PM 2.5 and its Precursor SO 2 - Related Health Co

b enefits Estimates for the Brick and Structural Clay Rule in 2018 (2011$) a , bOptions Pollutant Emissions Reductions

(tons) Benefit

per - ton (Krewski,

3%) Benefit

per - ton (Lepeule,

3%) Benefit

per - ton (Krewski,

7%) Benefit

per - ton (Lepeule,

7%) Monetized Benefits (millions

2011$ at 3%) Monetized Benefits (millions 2011$ at 7%)Option1 Direct ly emitted PM 2.5 235 $260,000 $600,000 $240,000 $540,000 $62 to $140 $56 to $130

PM 2.5 Precursors

SO 2 168 $41,000 $92,000 $37,000 $83,000 $6.8 to $15 $6.1 to $14

NO x - 41 $6,300 $14,000 $5,700 $13,000

- $0. 26 to

- $0. 59

- $0. 23 to

- $0 .53

Total $69 to $160 $62 to $14 0Final Rule: Option 2 Direct ly emitted PM 2.5 308 $260,000 $600,000 $240,000 $540,000 $8 2 to $180 $74 to $170

PM 2.5 Precursors

SO 2 72 $41,000 $92,000 $37,000 $83,000 $2.9 to $6.6 $2.6 to $6.0

NO x

- 46 $6,300 $14,000 $5,700 $13,000

- $0. 29 to

- $0. 66

- $0. 26 to

- $0. 59

Total $84 to $1 90 $7 6 to $1 70Option3 Direct ly emitted PM 2.5 415 $260,000 $600,000 $240,000 $540,000 $110 to $250 $100 to $220

PM 2.5 Precursors

SO 2 568 $41,000 $92,000 $37,000 $83,000 $ 23 to $ 52 $ 21 to $ 47

NO x

- 77 $6,300 $14,000 $5,700 $13,000

- $0. 49 to

- $ 1.1

- $0. 44 to

- $0. 99

Total $1 30 to $ 300 $1 20 to $2 70

a All estimates are rounded to two significant figures so numbers may not sum across columns. It is important to

note that the monetized benefits do not include reduced health effects from direct exposure to NO 2 , ozone exposure, ecosystem effects, or visibility impairment. All fine particles are assumed to have equivalent health effects, but the benefit per ton estimates vary depending on the location and magnitude of their impact on PM 2.5 levels, which drive population exposure. The monetized benefits incorporat e the conversion from precursor emissions to ambient fine particles. Confidence intervals are unavailable for this analysis because of the benefit

per

- ton methodology.

b These estimates reflect the net emissions impact after consideration of electricity di sbenefits. These estimates do

not include monetized CO 2 disbenefits, which range from $0.3 to $5 million depending on the option and discount
rate.***E.O. 12866 Review

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- 11 Table 4

- 3. Summary of Reductions in Health Incidences from PM 2.5 and its Precursor SO 2 - Related Co

- b enefits for Brick and Structural Clay Rule in 2018 a

Option 1 Final Rule : Option 2 Option 3

Avoided Premature Mortality
Krewski et al. (2009) (adult) 8 10 15 Lepeule et al. (2012) (adult) 18 22 34 Avoided Morbidity Emergency department visits for asthma (all ages) 4 5 8 Acute bronchitis (age 8

– 12) 12 15 23 Lower respiratory symptoms (age 7

– 14) 150 190 290 Upper respiratory symptoms (asthmatics age 9

– 11) 220 270 420

Minor restricted

- activity days (age 18

– 65) 6
, 100 7,500 12,000 Lost work days (age 18

– 65) 1

, 000 1

, 300 2,000 Asthma exacerbation (age 6

– 18) 230 280 430 Hospital admissions

— respiratory (all ages) 2 3 4 Hospital admissions

— cardiovascular (age > 18) 3 3 5

Non

- Fatal Heart Attacks (age >18) Peters et al. (2001) 8 10 16

Pooled estimate of 4 studies 1 1 2

a All estimates are rounded to whole numbers with two significant figures. Confidence intervals are unavailable for

this analysis because of the benefit

- per

- ton methodology. These estimates reflect the net impact after consideration of electricity disbenefits.***E.O. 12866 Review

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- 12 Figure 4

- 1. Total Monetized PM 2.5 Co

- b enefits of Final Brick and Structural Clay Rule in 2018 a ,b

a This graph shows the estimated benefits at discount rates of 3% and 7% using effect coefficients derived from the

Krewski et al. study and the Lepeule et al. study, as well as 12 effect coefficients derived from EPA ’ s expert elicitation on PM mortality. The results s hown are not the direct results from the studies or expert elicitation; rather, the estimates are based in part on the concentration

- response functions provided in those studies.

b These estimates reflect the net emissions impact after consideration of el ectricity disbenefits. These estimates do

not include monetized CO 2 disbenefits, which range from $0.3 to $5 million depending on the option and discount
rate. $0 $50 $100 $150 $200 $250 $300 Benefits Estimates from Two epidemiology Studies and 12 other expert functions for the Final Rule

— Option 2

3%

7%

Experts***E.O. 12866 Review

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- 13 Table 4

- 4. All PM 2.5 Benefits Estimates for the Brick and Structural Clay Rule in 2018 at Discount Rates of 3% and 7% Averaged ($2011 millions) a , b

Option 1 Final Rule: Option 2 Option 3

3% 7% 3% 7% 3% 7%

Benefit

- per - ton Coefficients Derived from Epidemiology Literature

Krewski $69 $62 $84 $76 $130 $120
Lepeule $160 $140 $190 $170 $300 $270

Benefit

- per - ton Coefficients Derived from Expert Elicitation

Expert A $180 $160 $220 $200 $340 $310
Expert B $140 $130 $180 $160 $280 $250
Expert C $140 $130 $170 $160 $270 $240
Expert D $99 $90 $120 $110 $190 $170
Expert E $230 $210 $280 $250 $440 $400
Expert F $130 $120 $160 $150 $260 $230
Expert G $83 $75 $100 $92 $160 $140
Expert H $100 $93 $130 $110 $200 $180
Expert I $140 $130 $170 $150 $270 $240
Expert J $110 $100 $140 $130 $220 $200
Expert K $17 $16 $21 $19 $33 $30
Expert L $96 $87 $120 $110 $180 $170

a All estimates are rounded to two significant figures. Estimates do not include confidence intervals because they

were derived through the benefit

- per

- ton technique described above. The benefits estimates from the expert elicitation are provided as a reason able characterization of the uncertainty in the mortality estimates associated with the concentration

- response function. Confidence intervals are unavailable for this analysis because of the benefit

- per

- ton methodology.

b These estimates reflect the net e missions impact after consideration of electricity disbenefits. These estimates do

not include monetized CO 2 disbenefits, which range from $0.3 to $5 million depending on the option and discount
rate. Unlike the PM NAAQS RIA, we do not have data on the sp ecific location of the air quality changes associated with this rulemaking. As such, it is not feasible to estimate the proportion of benefits occurring in different locations, such as designated nonattainment areas. Instead, we applied benefit

- per

- ton est imates, which reflect specific geographic patterns of emissions reductions and specific air quality and benefits modeling assumptions for each sector (U.S. EPA, 2013) . For example, these estimates do not reflect local variability in population density, met eorology, exposure, baseline health incidence rates, or other local factors that might
lead to an over

- estimate or under

- estimate of the actual benefits of controlling PM precursors. Use of these $/ton values to estimate benefits may lead to higher or lowe r benefit estimates than if benefits were calculated based on direct air quality modeling. Great care should be taken in***E.O. 12866 Review

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- 14 applying these estimates to emission emissions reductions occurring in any specific location, as
these reflect on national or regional emission changes and therefore represent average benefits

per

- ton over the entire United States (U.S. EPA, 2013). The benefits

- per

- ton for emission reductions in specific locations may be very different than the estimates presented here , and the approach a bove did not yield benefit per

- ton estimates at a sub

- national level for this sector

. To the extent that the geographic distributions of the emissions reductions for this rule are different than the modeled emissions, the benefits may be underestimated or overestimated. In general, there is inherently more uncertainty for new sources, which may not be included in the emissions inventory, than existing sources. For more information, see the TSD describing the calculation of
these benefit

- per

- ton estimates (U .S. EPA, 2013).

Our estimate of the total benefits is based on EPA ’ s interpretation of the best available scientific literature and methods and supported by the SAB

- HES and the NAS (NRC, 2002 ). Below are key assumptions underlying the estim ates for premature mortality which accounts for
98% of the total monetized PM 2.5 benefits:

1. We assume that all fine particles, regardless of their chemical composition, are equally potent in causing premature mortality. This is an important assumption, because PM 2.5 varies considerably in composition across sources, but the scientific evidence is not yet sufficient to allow differentiation of effect estimates by particle type. The PM ISA concluded that “ many constituents of PM 2.5 can be linked with multi ple health effects, and the evidence is not yet sufficient to allow differentiation of those constituents or sources that are more closely related to specific outcomes ” (U.S. EPA, 2009).

2. We assume that the health impact function for fine particles is lo g

- linear without a threshold in this analysis. Thus, the estimates include health benefits from reducing fine particles in areas with varied concentrations of PM 2.5 , including both areas that do not meet the fine particle standard and those areas that are in attainment, down to the lowest modeled concentrations.

3. 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 pre mature mortality related to PM 2.5 exposures occur in a distributed fashion over the 20 years following exposure based on the advice of the SAB

- HES (U.S. EPA

- SAB, 2004c), which affects the valuation of mortality benefits at different discount rates.

In gen eral, we are more confident in the magnitude of the risks we estimate from
simulated PM 2.5 concentrations that coincide with the bulk of the observed PM concentrations in the epidemiological studies that are used to estimate the benefits. Likewise, we are less confident
in the risk we estimate from simulated PM 2.5 concentrations that fall below the bulk of the***E.O. 12866 Review

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- 15 observed data in these studies. Concentration benchmark analyses (e.g., lowest measured level [LML] or one standard deviation below the mean of the a ir quality data in the study) a llow readers to determine the portion of population exposed to annual mean PM 2.5 levels at or above different concentrations, which provides some insight into the level of uncertainty in the
estimated PM 2.5 mortality benefits . There are uncertainties inherent in identifying any particular point at which our confidence in reported associations becomes appreciably less, and the scientific evidence provides no clear dividing line. However, the EPA does not view these
concentratio n benchmarks as a concentration threshold below which we would not quantify health benefits of air quality improvements. 15 Rather, the benefits estimates reported in this RIA are the best estimates because they reflect the full range of air quality concentr ations associated with the emission reduction strategies and because the current body of scientific literature
indicates that a no

- threshold model provides the best estimate of PM

- related long

- term mortality. In other words, although we may have less confi dence in the magnitude of the risk at concentrations below these benchmarks, we still have high confidence that PM 2.5 is causally associated with risk at those lower air quality concentrations.

For this analysis, policy

- specific air quality data is not ava ilable due to time or resource
limitations. For t his rule, we are unable to estimate the percentage of premature mortality associated with this specific rule ’ s emission reductions at each PM 2.5 level. However, we believe that it is still important to chara cterize the distribution of exposure to baseline air quality levels. As a surrogate measure of mortality impacts, we provide the percentage of the population exposed at each PM 2.5 level in the baseline of the source apportionment modeling used to
calculate the benefit

- per

- ton estimates for this sector. It is important to note that baseline exposure is only one parameter in the health impact function, along with baseline incidence rates population, and change in air quality. In other words, the percentage of the population exposed to air pollution below the LML is not the same as the percentage of the population experiencing health impacts as a result of a specific emission reduction policy. The most important aspect, which we are unable to quantify for rules without rule

- specific air quality modeling, is the shift in exposure associated with this specific rule. Therefore, caution is warranted when interpreting
the LML assessment for this rule because these results are not consistent with results from rules
th at had air quality modeling.

15 F or a summary of the scientific review statements regarding the lack of a threshold in the PM 2.5 - mortality

relationship, see the Technical Support Document (TSD) entitled Summary of Expert Opinions on the Existence of a Threshold in the Concentration

- Response Function for PM 2.5 - related Mortality (U.S. EPA, 2010b).***E.O. 12866 Review

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- 16 Table 4

- 5 provides the percentage of the population exposed above and below two concentration benchmarks (i.e., LML and 1 standard deviation below the mean) in the modeled baseline. Figure 4

- 2 shows a bar chart of the percenta ge of the population exposed to various air quality levels in the baseline, and Figure 4

- 3 shows a cumulative distribution function of the same data. Both figures identify the LML for each of the major cohort studies.

Table 4

- 5

. Population Exposure in the Baseline Above and Below Various Concentration Benchmarks in the Underlying Epidemiology Studies a

Epidemiology Study Below 1 Std. Dev. Below AQ Mean At or Above 1 Std. Dev. Below AQ Mean Below LML At or Above LML
Krewski et al. (2009) 89% 11% 7% 93%
Lepeule et al. (2012) N/A N/A 23% 67%

a One standard deviation below the mean is equivalent to the middle of the range between the 10 th and 25 th

percentile. For Krewski, the LML is 5.8 μg/m 3 and one standard deviation below the mean is 11.0 μg/m 3 . For Lepeule et al., the LML is 8 μg/m 3 and we do not have the data for one standard deviation below the mean. It is important to emphasize that although we have lower levels of confidence in levels below the LML for each study, the scientific evidence does not support the existence of a level below which health effects from exposure to PM 2.5 do not occur.***E.O. 12866 Review

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- 17 Figure 4

- 2. Percentage of Adult Population by Annual Mean PM 2.5 Exposure in the Baseline Among the populations exposed to PM 2.5 in the baseline:

93% are exposed to PM 2.5 levels at or above the LML of the Krewski et al. (2009) study 67% are exposed to PM 2.5 levels at or above the LML of the Lepeule et al. (2012) study

4.2 Energy Disbenefits
In this section, we provide an estimate of the energy disbenefits associated with the increased emissions from additional energy usage. We estimate that electricity usage associated with operation of the control devices would increase

. This electricity usage is anticipated to increase emissions of pollutants from electri c utility boilers (EGU boilers) that supply electricity

to these facilities . In the calculation of health benefits presented above , we have already
subtracted the PM, SO 2 , and NOx emission increases associated with increased electricity usage 0% 5% 10% 15% 20% 25%

<1 1

- 2 2

- 3 3

- 4 4

- 5 5

- 6 6

- 7 7

- 8 8

- 9 9

- 10 10

- 11 11

- 12 12

- 13 13

- 14 14

- 15 15

- 16 16

- 17 17

- 18 18

- 19 19

- 20Percentage of Population Exposed

Baseline Annual Mean PM 2.5 Level (μg/m 3 ) LML of Lepeule et al. (2012) study LML of Krewski et al. (2009) study***E.O. 12866 Review

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- 18 from the emission reductions associated with the regulatory requirements. Table 4

- 6 provides the estimated emission increases for each of the regulatory options analyzed in this RIA.

Table 4

- 6

. Emission Increases Associated with Secondary Energy Disbenefits (short tons per year) a

Option Energy Impacts , MMBtu/yr PM 2.5 NOx SO 2 CO 2
1 419,022 1 41 121 25,337

2 461,329 1 46 133 27,896

3 783,978 2 78 226 47,406

a Emission increases for PM 2.5 , NOx, and SO 2 have already been reflected in the monetized PM 2.5 co

- benefits

above.

4.2.1 Social Cost of Carbon and Greenhouse Gas Dis benefits
We estimate the global social dis

- benefits of CO 2 emission increases expected from the
final rulemaking using the SC

- CO 2 estimates presented in the Technical Support Document: Technical Update of the Social Cost of Carbon for Regulatory Impact Analysis Under Executive
Order 12866 (May 2013, Revised Ju ly 2015) ( “ current TSD ” )

. 16 We refer to these estimates, which were developed by the U.S. government, as “ SC

- CO 2 estimates. ” The SC

- CO 2 is a metric
tha t estimates the monetary value of impacts associated with marginal changes in CO 2 emissions in a given year. It includes a wide range of anticipated climate impacts, such as net changes in agricultural productivity and human health, property damage from in creased flood risk, and changes in energy system costs

, such as reduced costs for heating and increased costs for air conditioning. It is typically used to assess the avoided damages as a result of regulatory actions ( i.e.

, benefits of rulemakings that lea d to an incremental reduction in cumulative global CO 2 emissions ) but is also used to assess increases in damages expected to result from rulemakings leading to an incremental increase in cumulative global CO 2 emissions

.

The SC

- CO 2 estimates used in this analysis were developed over many years, using the best science available, and with input from the public. Specifically, an interagency working group (IWG) that included the EPA and other executive branch agencies and offices used three

16 Docket ID EPA

- HQ

- OAR

- 2013

- 0495, Te chnical Support Document: Technical Update of the Social Cost of Carbon for Regulatory Impact Analysis Under Executive Order 12866 , Interagency Working Group on Social Cost of Carbon, with participation by Council of Economic Advisers, Council on Environme ntal Quality, Department of Agriculture, Department of Commerce, Department of Energy, Department of Transportation, Environmental Protection Agency, National Economic Council, Office of Energy and Climate Change, Office of Management and Budget, Office of Science and Technology Policy, and Department of Treasury (May 2013, Revised July 201 5 ). Available at: < https://www.whitehouse.gov/sites/default/files/omb/inforeg/scc

- tsd

- final

july

- 2015.pdf > Accessed 7/11/2015.***E.O. 12866 Review

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- 1 9 integrated assessme nt models (IAMs) to develop the SC

- CO 2 estimates and recommended four global values for use in regulatory analyses. The SC

- CO 2 estimates were first released in February 2010 and updated in 2013 using new versions of each IAM. As discussed further below, the IWG published two minor corrections to the SC

- CO 2 estimates in July 2015.

The SC

- CO 2 estimates were developed using an ensemble of the three most widely cited integrated assessment models in the economics literature with the ability to estimate the SC

- CO 2

. A key objective of the IWG was to draw from the insights of the three models while respecting the different approaches to linking GHG emissions and monetized damages taken by modelers in the published literature. After conducting an extensive literat ure review, the interagency group selected three sets of input parameters (climate sensitivity, socioeconomic and emissions trajectories, and discount rates) to use consistently in each model. All other model features were left unchanged, relying on the mo del developers ’ best estimates and judgments, as informed by the literature. Specifically, a common probability distribution for the equilibrium climate sensitivity parameter, which informs the strength of climate ’ s response to atmospheric GHG
concentratio ns, was used across all three models. In addition, a common range of scenarios for the socioeconomic parameters and emissions forecasts were used in all three models. Finally, the marginal damage estimates from the three models were estimated using a consi stent range of discount rates, 2.5, 3.0, and 5.0 % . See the 2010 TSD for a complete discussion of the methods used to develop the estimates and the key uncertainties, and the current TSD for the latest
estimates. 17

The 2010 TSD noted a number of limitations to the SC

- CO 2 analysis, including the incomplete way in which the integrated assessment models capture catastrophic and non

catastrophic impacts, their incomplete treatment of adaptation and technological change, uncertainty in the extrapolation of damage s to high temperatures, and assumptions regarding risk aversion. Currently integrated assessment models do not assign value to all of the important physical, ecological, and economic impacts of climate change recognized in the climate change
literature due to a lack of precise information on the nature of damages and because the science incorporated into these models understandably lags behind the most recent research. 18 The limited amount of research linking climate impacts to economic damages makes the mod eling
exercise even more difficult. These individual limitations do not all work in the same direction in

17 See https://www.whitehouse.gov/omb/oira/social

- cost

- of

- carbon for both TSDs.

18 Climate change impacts and SCC modeling is an area of active research. For example, see: (1) Howard, Peter, “Omitted Damages: What’s Missing from the Social Cost of Carbon.” March 13, 2014, http://costofcarbon.org/files/Omitted_Damages_Whats_Missing_Fro m_the_Social_Cost_of_Carbon.pdf ; and (2) Electric Power Research Institute, “Understanding the Social Cost of carbon: A Technical Assessment,” October 2014, www.epri.com

.***E.O. 12866 Review

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- 20 terms of their influence on the SC

- CO 2 estimates, though taken together they suggest that the
SC

- CO 2 estimates are likely conservative. In particular, the IPCC Fourth Assessment Report (2007), which was the most current IPCC assessment available at the time of the IWG ’ s 2009

- 2010 review, concluded that “ It is very likely that [SC

- CO 2 estimates] underestimate the damage costs because they cannot include many non

- quantifiable impacts. ” Since then, the peer

reviewed literature has continued to support this conclusion. For example, the IPCC Fifth Assessment report observed that SC

- CO 2 estimates continue to omit various impacts that would likely increase dama ges. The 95th percentile estimate was included in the recommended range for regulatory impact analysis to address these concerns.

Accordingly, EPA and other agencies continue to engage in research on modeling and valuation of climate impacts with the goal to improve these estimates. The EPA and other agencies also continue to consider feedback on the SC

- CO 2 estimates from stakeholders through a range of channels, including public comments on Agency rulemakings that use the SC

- CO 2 in supporting analyses and through regular interactions with stakeholders and research analysts implementing the SC

- CO 2 methodology used by the interagency working group. In addition,
OMB ’ s Office of Information and Regulatory Affairs sought public comment on the approach
used to de velop the SC

- CO 2 estimates through a separate comment period that ended on February 26, 2014. 19

After careful evaluation of the full range of comments, the interagency working group
continues to recommend the use of the SC

- CO 2 estimates in regulatory impact analysis. 20 With the release of the response to comments, the interagency working group announced plans to obtain expert independent advice from the National Academ ies of Sciences , Engineering, and
Medicine to ensure that the SC

- CO 2 estimates continue to reflect the best available scientific and economic information on climate change. The Academies review will be informed by the public comments received and focus on the technical merits and challenges of potential approaches t o improving the SC

- CO 2 estimates in future updates.

Concurrent with OMB ’ s publication of the response to comments on SC

- CO 2 and
announcement of the Academies process, OMB posted a revised TSD that includes two minor
technical corrections to the current es timates. 21 One technical correction addressed an inadvertent omission of climate change damages in the last year of analysis (2300) in one model

19 See https://www.federalregister.gov/articles/2013/11/26/2013

- 28242/technical

- support

- document

- technical

update

- of

- the

- social

- cos t

- of

- carbon

- for

- regulatory

- impact

20 See https://www.whitehouse.gov/blog/2015/07/02/estimating

- benefits

- carbon

- dioxide

- emissions

- reductions

21 See https://www.whitehouse.gov/omb/oira/social

- cost

- of

- carbon for the response to comments, the blog post announcing the Academies’ process, and the current TSD.***E.O. 12866 Review

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- 21 and the second addressed a minor indexing error in another model. On average the revised SC

CO 2 estimates are o ne dollar less than the mean SC

- CO 2 estimates reported in the November 2013 TSD. The change in the estimates associated with the 95th percentile estimates when using a 3% discount rate is slightly larger, as those estimates are heavily influenced by the re sults from the model that was affected by the indexing error.

The four SC

- CO 2 estimates are: $13 , $ 43 , $ 64 , and $1 20 per metric ton of CO 2 emissions in the year 20 18 (201 1 dollars). 22 The first three values are based on the average SC

- CO 2 from
the three IA Ms, at discount rates of 5, 3, and 2.5 % , respectively. Estimates of the SC

- CO 2 for
several discount rates are included because the literature shows that the SC

- CO 2 is sensitive to assumptions about the discount rate, and because no consensus exists on the appropriate rate to use in an intergenerational context (where costs and benefits are incurred by different generations). The fourth value is the 95 th percentile of the SC

- CO 2 across all three models at a
3 % discount rate. It is included to represent higher

- than

- expected impacts from temperature change further out in the tails of the SC

- CO 2 distribution. The SC

- CO 2 increases over time because future emissions are expected to produce larger incremental damages as economies grow and physical and economic systems become more stressed in response to greater climate change.

Table 4

- 7

. Estimated Global Disb enefits of CO 2 Increases in 2018 (million 2011$)

Discount Rate and Statistic

Option Metric Tonnes of CO 2 Reduced 5% (average) 3% (average) 2.5% (average) 3% (95 th percentile)
1 22,985 $0.29 $1.0 $1.5 $2.8

2 25,307 $0.32 $1.1 $1.6 $3.1

3 43,006 $0.55 $1.8 $2.7 $5.3

After incorporating the CO 2 electricity disbenefits, the total monetized benefits of the final rule (Option 2) are $83 to $190 million at a 3 % discount rate.

4.3 Unquantified Benefits
The monetized benefits estimated in this RIA only reflect a subset of benefits attributable
to the he alth effect reductions associated with ambient fine particles. Data, time, and resource limitations prevented EPA from quantifying the impacts to, or monetizing the benefits from

22 The TSDs present SC

- CO2 in $2007. The estimates were adjusted to 2012$ using the GDP Implicit Price Deflator. Also available at: http://www.gpo.gov/fdsys/pkg/ECONI

- 2013

- 02/pdf/ECONI

- 2013

- 02

- Pg3.pdf

. The SC

- C O 2 values have been rounded to two significant digits. Unrounded numbers from the 2013 SCC TSD were adjusted to 2012$ and used to calculate the CO 2 benefits.***E.O. 12866 Review

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- 22 several important benefit categories, including benefits associated with the potential exposure to HAP, ecosystem effects, and visibility impairment due to the absence of air quality modeling data for these pollutants in this analysis. This does not imply that there are no benefits associated
with these emission reductions. In this section, we provide a qualitative description of these benefits. Below is a detailed qualitative assessment of health benefits related to multiple HAPs that have been reduced among including HAPs metals (i.e. antimony, arsenic, beryllium, cadmium, chromiu m, cobalt, lead, manganese, mercury, nickel, and selenium).

Figure 4

- 3. Cumulative Distribution of Adult Population by Annual Mean PM 2.5 Exposure in the Baseline
Among the populations exposed to PM 2.5 in the baseline:

93% are exposed to PM 2.5 levels at or above the LML of the Krewski et al. (2009) study 67% are exposed to PM 2.5 levels at or above the LML of the Lepeule et al. (2012) study

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20Cumulative percentage of population exposed

Baseline Annual Mean PM 2.5 Level (μg/m 3 ) LML of Krewski et al. (2009) study LML of Lepeule et al. (2012) study***E.O. 12866 Review

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- 23 4.3.1 HAP Benefits
Even though emissions of air toxics from all sources in the U.S. declined by approximately 42% since 199 0, the 2005 National

- Scale Air Toxics Assessment (NATA) 23 predicts that most Americans are exposed to ambient concentrations of air toxics at levels that have the potential to cause adverse health effects (U.S. EPA, 2011c). 24 The levels of air toxics to
whi ch people are exposed vary depending on where people live and work and the kinds of activities in which they engage. NATA includes four steps :

1. Compiling a national emissions inventory of air toxics emissions from outdoor

sources

2. Estimating ambient an d exposure concentrations of air toxics across the United States utilizing dispersion models

3. Estimating population exposures across the United States utilizing exposure models

4. Characterizing potential public health risk due to inhalation of air toxic s including both cancer and noncancer effects

Based on the 2005 NATA, EPA estimates that about 5% of census tracts nationwide have increased cancer risks greater than 100 in a million. The average national cancer risk is about 50 in a million. Nationwide, the key pollutants that contribute most to the overall cancer risks are formaldehyde and benzene. 25 Secondary formation (e.g., formaldehyde forming from other emitted pollutants) was the largest contributor to cancer risks, while stationary, mobile and
back ground sources contribute almost equal portions of the remaining cancer risk.

23 The NATA modeling framework has a number of limitations that prevent its use as the sole basis for setting regulatory standards. These limitations and uncertainties are discussed on the 2005 NATA website. Even so, this modeling framework is very useful in identifying air toxic pollutants and sources of greatest concern, setting regulatory priorities, and informing the decision making process. U.S. EPA (2011). 2005 National

- Scale Air Toxics Assessment. ht tp://www.epa.gov/ttn/atw/nata2005/

24 The 2005 NATA is available on the Internet at http://www.epa.gov/ttn/atw/nata2005/.

25 Details about the overall confidence of certainty ranking of the individual pieces of NATA assessments including both quantitative (e. g., model

- to

- monitor ratios) and qualitative (e.g., quality of data, review of emission inventories) judgments can be found at http://www.epa.gov/ttn/atw/nata/roy/page16.html.***E.O. 12866 Review

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- 24 Noncancer health effects can result from chronic, 26 subchronic, 27 or acute 28 inhalation exposures to air toxics, and include neurological, cardiovascular, liver, kidney, and respiratory effects as well as effects on the immune and reproductive systems. According to the 2005 NATA, about three

- fourths of the U.S. population was expo sed to an average chronic concentration of air toxics that has the potential for adverse noncancer respiratory health
effects. Results from the 2005 NATA indicate that acrolein is the primary driver for noncancer respiratory risk.

Figures 4

- 4 and 4

- 5 depi ct the 2005 NATA estimated census tract

- level carcinogenic risk and noncancer respiratory hazard from the assessment. It is important to note that l arge reductions in HAP emissions may not necessarily translate into significant reductions in health
risk be cause toxicity varies by pollutant, and exposures may or may not exceed levels of concern. Thus, it is important to account for the toxicity and exposure, as well as the mass of the targeted emissions.

26 Chronic exposure is defined in the glossary of the Integrated Risk Information (IRIS) database (http://www.epa.gov/iris) as repeated exposure by the oral, dermal, or inhalation route for more than approximately 10% of the life span in humans (more than approximately 90 days to 2 years in typically used laboratory animal species).

27 De fined in the IRIS database as repeated exposure by the oral, dermal, or inhalation route for more than 30 days, up to approximately 10% of the life span in humans (more than 30 days up to approximately 90 days in typically used laboratory animal species).

28 Defined in the IRIS database as exposure by the oral, dermal, or inhalation route for 24 hours or less.***E.O. 12866 Review

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- 25 Figure 4

- 4. 2005 NATA Model Estimated Census Tract C arcinogenic Risk from HAP Exposure from Emissions of All Outdoor Sources (inclusive of other nonpoint sources) based on the 2005 National Toxic Inventory
Because of methodology limitations, we were unable to estimate the benefits associated
with the hazard ous air pollutants that would be reduced as a result of this rule. In a few previous analyses of the benefits of reductions in HAP, EPA has quantified the benefits of potential
reductions in the incidences of cancer and non

- cancer risk (e.g., U.S. EPA, 199 5 ). In those analyses, EPA relied on unit risk factors (URF) and reference concentrations (RfC) developed through risk assessment procedures. The URF is a quantitative estimate of the carcinogenic potency of a pollutant, often expres sed as the probability of contracting cancer from a 70

- year lifetime continuous exposure to a concentration of one μg/m3 of a pollutant. These URFs are designed to be conservative, and as such, are more likely to represent the high end of the
distribution of risk rather than a best or most likely estimate of risk.

An RfC is an estimate (with uncertainty spanning perhaps an order of magnitude) of a continuous inhalation exposure to the human population (including sensitive subgroups) that is likely to be wit hout an appreciable risk of deleterious non

- cancer health effects during a lifetime.***E.O. 12866 Review

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- 26 As the purpose of a benefit analysis is to describe the benefits most likely to occur from a reduction in pollution, use of high

- end, conservative risk estimates would ove restimate the benefits of the regulation. While we used high

- end risk estimates in past analyses, advice from
the EPA ’ s Science Advisory Board (SAB) recommended that we avoid using high

- end estimates in benefit analyses (U.S. EPA

- SAB, 2002 ). Since this time, EPA has continued to develop better methods for analyzing the benefits of reductions in HAP.

As part of the second prospective analysis of the benefits and costs of the Clean Air Act (U.S. EPA, 2011a), EPA conducted a case study a nalysis of the health effects associated with reducing exposure to benzene in Houston from implementation of the Clean Air Act (IEc, 2009 ). While reviewing the draft report, EPA ’ s Advisory Council on Clean Air Compliance Analysis
concluded that “ the challenges for assessing progress in health improvement as a result of reductions in emissions of hazardous air pollutants (HAPs) are daunting

... due to a lack of

exposure

- response fu nctions, uncertainties in emissions inventories and background levels, the difficulty of extrapolating risk estimates to low doses and the challenges of tracking health progress for diseases, such as cancer, that have long latency periods ” (U.S. EPA

- SAB, 2 008 ).***E.O. 12866 Review

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- 27 Figure 4

- 5. 2005 NATA Model Estimated Census Tract Noncancer Risk from HAP Exposure from Emissions of All Outdoor Sources (inclusive of other nonpoint sources) based on the 2005 National Toxic Inventory In 2009, EPA convened a workshop to address the inherent complexities, limitations, and uncertainties in current methods to quantify the benefits of reducing HAP. Recommendations from this workshop included identifying research priorities, focusing on susceptible and

v ulnerable populations, and improving dose

- response relationships (Gwinn et al., 2011 ).

In summary, monetization of the benefits of reductions in cancer incidences requires several important inputs, including central estimates of cancer risks, estimates of exposure to carcinogenic HAP, and estimates of the value of an avoided case of cancer (fatal and non

- fatal). Due to methodology and time limitations under the court

- ordered schedule, we did not attempt to
monetize the health ben efits of reductions in HAP in this analysis. Instead, we provide a qualitative analysis of the health effects associated with the HAP anticipated to be reduced by these rules. EPA remains committed to improving methods for estimating HAP benefits by
contin uing to explore additional concepts of benefits, including changes in the distribution of
risk.***E.O. 12866 Review

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- 28 Below we describe the health effects associated with the HAP that would be reduced by this rulemaking , including 2 tons of chlorine, 22 tons of hydrogen chlori de, 344 tons of hydrogen
fluoride , 147 pounds of mercury, and 7 tons of other metal HAP (e.g., arsenic, cadmium, chromium, lead, manganese, nickel, and selenium).

4.3.1.1 Arsenic
Arsenic, a naturally occurring element, is found throughout the environment and is

co nsidered toxic through the oral, inhalation and dermal routes. Acute (short

- term) high

- level inhalation exposure to As dust or fumes has resulted in gastrointestinal effects (nausea, diarrhea, abdominal pain, and gastrointestinal hemorrhage); central and p eripheral nervous system disorders have occurred in workers acutely exposed to inorganic As. Chronic (long

- term) inhalation exposure to inorganic As in humans is associated with irritation of the skin and
mucous membranes. Chronic inhalation can also lead to conjunctivitis, irritation of the throat and respiratory tract and perforation of the nasal septum. 29 Chronic oral exposure has resulted in gastrointestinal effects, anemia, peripheral neuropathy, skin lesions, hyperpigmentation, and liver or kidney dama ge in humans. Inorganic As exposure in humans, by the inhalation route, has been shown to be strongly associated with lung cancer, while ingestion of inorganic As in humans has been linked to a form of skin cancer and also to bladder, liver, and lung cance r. EPA has classified inorganic As a Group A, human carcinogen. 30

4.3.1.2 Cadmium (Cd) 31

Breathing air with lower levels of Cd over long periods of time (for years) results in a
build

- up of Cd in the kidney, and if sufficiently high, may result in kidney disease. L ung cancer has been found in some studies of workers exposed to Cd in the air and studies of rats that inhaled Cd. The U.S. DHHS has determined that Cd and Cd compounds are known human carcinogens. The IARC has determined that Cd is carcinogenic to humans. EPA has determined that Cd is a probable human carcinogen.

29 Agency for Toxic Substances and Disease Registry (ATSDR). Medical Management Guidelines for Arsenic. Atlanta, GA: U.S. Department of Health and Human Services. Available on the Internet at < http://www.atsdr.cdc.gov/mhmi/mmg168.html#bookmark02>

30 U.S. Environmental Protection Agency (U.S. EPA). 1998. Integrated Risk Information System File for Arsenic. Research and Development, National Center for Enviro nmental Assessment, Washington, DC. This material is available electronically at: http://www.epa.gov/iris/subst/0278.htm.

31 Agency for Toxic Substances and Disease Registry (ATSDR). 2008. Public Health Statement for Cadmium

. CAS# 1306

- 19

- 0. Atlanta , GA: U.S . Department of Health and Human Services, Public Health Service. Available on the Internet at < http://www.atsdr.cdc.gov/PHS/PHS.asp?id=46&tid=15 >.***E.O. 12866 Review

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- 29 4.3.1.3 Chlorine (Cl 2 )
The acute (short term) toxic effects of Cl 2 are primarily due to its corrosive properties. Chlorine is a strong oxidant that upon contact with water moist tissue (e.g., eyes, skin, and upper respiratory tract) can produce major tissue damage. 32 Chronic inhalation exposure to low
concentrations of Cl 2 (1 to 10 parts per million, ppm) may cause eye and nasal irritation, sore throat, and coughing. Chronic exposure to Cl 2 , usually in the workplace, has been reported to cause corrosion of the teeth. Inhalation of higher concentrations of Cl 2 gas (greater than 15 ppm) can rapidly lead to respiratory distress with airway constriction and accumulation of fluid in the lungs (pulmonary edema). E xposed individuals may have immediate onset of rapid breathing, blue discoloration of the skin, wheezing, Rales

, or hemoptysis (coughing up blood or blood

- stain sputum). Intoxication with high concentrations of Cl 2 may induce lung collapse. Exposure to Cl 2 can lead to reactive airways dysfunction syndrome (RADS), a chemical irritant

- induced type of asthma. Dermal exposure to Cl 2 may cause irritation, burns, inflammation and blisters. EPA has
not classified Cl 2 with respect to carcinogenicity.

4.3.1.4 Chromium (Cr) 33

Chromium may be emitted in two forms, trivalent Cr (Cr+3) or hexavalent Cr (Cr+6).
The respiratory tract is the major target organ for Cr +6 toxicity, for acute and chronic inhalation exposures. Shortness of breath, coughing, and wheezing have been reported from acute exposure
to Cr +6 , while perforations and ulcerations of the septum, bronchitis, decreased pulmonary function, pneumonia, and ot her respiratory effects have been noted from chronic exposures. Limited human studies suggest that Cr +6 inhalation exposure may be associated with complications during pregnancy and childbirth, but there are no supporting data from animal studies reporting reproductive effects from inhalation exposure to Cr +6 . Human and animal studies have clearly established the carcinogenic potential of Cr +6 by the inhalation route, resulting in an increased risk of lung cancer. EPA has classified Cr +6 as a Group A, human carcinogen. Trivalent Cr is less toxic than Cr +6 . The respiratory tract is also the major target organ for Cr +3 toxicity, similar to Cr +6 . EPA has not classified Cr +3 with respect to carcinogenicity.

32 Agency for Toxic Substances and Disease Registry (ATSDR). Medical Management Guidelines for Chlorine. Atlan ta, GA: U.S. Department of Health and Human Services. http://www.atsdr.cdc.gov/mmg/mmg.asp?id=198&tid=36.

33 U.S. Environmental Protection Agency. Integrated Risk Information System (IRIS) on Chromium VI. National Center for Environmental Assessment, Office of Research and Development, Washington, DC. 1999.***E.O. 12866 Review

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- 30 4.3.1.5 Hydrogen Chloride (HCl)
Hydrogen chloride is a corrosiv e gas that can cause irritation of the mucous membranes of the nose, throat, and respiratory tract. Brief exposure to 35 ppm causes throat irritation, and levels of 50 to 100 ppm are barely tolerable for 1 hour. 34 The greatest impact is on the upper respira tory tract; exposure to high concentrations can rapidly lead to swelling and spasm of the throat and suffocation. Most seriously exposed persons have immediate onset of rapid breathing, blue coloring of the skin, and narrowing of the bronchioles. Exposure to HCl can lead to RADS, a chemically

- or irritant

- induced type of asthma. Children may be more vulnerable to corrosive agents than adults because of the relatively smaller diameter of their airways. Children may also be more vulnerable to gas exposure bec ause of increased minute ventilation per kg and failure to evacuate an area promptly when exposed. Hydrogen chloride has not been classified for carcinogenic effects. 35

4.3.1.6 Hydrogen Cyanide (HCN) 36

Hydrogen cyanide is highly toxic by all routes of exposure and m ay cause abrupt onset of profound central nervous system, cardiovascular, and respiratory effects, leading to death within minutes. Exposure to lower concentrations of hydrogen cyanide may produce eye irritation, headache, confusion, nausea, and vomiting f ollowed in some cases by coma and death. Hydrogen cyanide acts as a cellular asphyxiant. By binding to mitochondrial cytochrome oxidase, it prevents the utilization of oxygen in cellular metabolism. The central nervous system and myocardium are particularl y sensitive to the toxic effects of cyanide.

4.3.1.7 Hydrogen Fluoride (HF) 37

Acute (short

- term) inhalation exposure to gaseous HF can cause severe respiratory damage in humans, including severe irritation and pulmonary edema. Chronic (long

- term) oral

34 Agency for Toxic Substances and Disease Registry (ATSDR). Medical Management Guidelines for Hydrogen Chloride. Atlanta, GA: U.S. Department of Health and Human Services. Available online at http://www.at sdr.cdc.gov/mmg/mmg.asp?id=758&tid=147#bookmark02.

35 U.S. Environmental Protection Agency (U.S. EPA). 1995. Integrated Risk Information System File of Hydrogen Chloride. Research and Development, National Center for Environmental Assessment, Washington, DC. This material is available electronically at .http://www.epa.gov/iris/subst/0396.htm.

36 All health effects language for this section came from: Agency for Toxic Substances and Disease Registry (ATSDR). 2007. Medical Management Guidelines for Hydrogen Cyani de (HCN) ( CAS# : 7782

- 50

- 5). Atlanta, GA: U.S. Department of Health and Human Services, Public Health Service. Available on the Internet at http://www.atsdr.cdc.gov/Mhmi/mmg8.html#bookmark02

. 37 U.S. Environmental Protection Agency. Health Issue Assessment: Summary Review of Health Effects Associated with Hydrogen Fluoride and Related Compounds. EPA/600/8

- 89/002F. Environmental Criteria and Ass essment Office, Office of Health and Environmental Assessment, Office of Research and Development, Cincinnati, OH. 1989.***E.O. 12866 Review

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- 31 exposure to f luoride at low levels has a beneficial effect of dental cavity prevention and may also be useful for the treatment of osteoporosis. Exposure to higher levels of fluoride may cause dental fluorosis. One study reported menstrual irregularities in women occup ationally exposed to fluoride via inhalation. The EPA has not classified HF for carcinogenicity.

4.3.1.8 Lead (Pb) 38

The main target for Pb toxicity is the nervous system, both in adults and children. Long

term exposure of adults to Pb at work has resulted in decre ased performance in some tests that measure functions of the nervous system. Lead exposure may also cause weakness in fingers, wrists, or ankles. Lead exposure also causes small increases in blood pressure, particularly in
middle

- aged and older people. Lea d exposure may also cause anemia.

Children are more sensitive to the health effects of Pb than adults. No safe blood Pb level in children has been determined. At lower levels of exposure, Pb can affect a child ’ s mental and physical growth. Fetuses exposed to Pb in the womb may be born prematurely and have lower weights at birth. Exposure in the womb, in infancy, or in early childhood also may slow mental development and cause lower intelligence later in childhood. There is evidence that these effects

may p ersist beyond childhood.

There are insufficient data from epidemiologic studies alone to conclude that Pb causes cancer (is carcinogenic) in humans. The DHHS has determined that Pb and Pb compounds are reasonably anticipated to be human carcinogens based o n limited evidence from studies in humans and sufficient evidence from animal studies, and the EPA has determined that Pb is a probable human carcinogen.

4.3.1.9 Manganese (Mn) 39

Health effects in humans have been associated with both deficiencies and excess intak es of Mn. Chronic exposure to high levels of Mn by inhalation in humans results primarily in central nervous system effects. Visual reaction time, hand steadiness, and eye

- hand coordination were affected in chronically

- exposed workers. Manganism, character ized by feelings of weakness and lethargy, tremors, a masklike face, and psychological disturbances, may result from chronic exposure to higher levels. Impotence and loss of libido have been noted in male

38 Agency for Toxic Substances and Disease Registry (ATSDR). 2007. P ublic Health Statement for Lead. CAS# : 7439

- 92

- 1 . Atlanta , GA: U.S. Department of Health and Human Services, Public Health Service. Available on the Internet at < http://www.atsdr.cdc.gov/ToxProfiles/phs13.html >.

39 U.S. Environmental Protection Agency. Integrated Risk Information System (IRIS) on Manganese. Natio nal Center for Environmental Assessment, Office of Research and Development, Washington, DC. 1999.***E.O. 12866 Review

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- 32 workers afflicted with Manganism attributed to inha lation exposures. The EPA has classified Mn in Group D, not classifiable as to carcinogenicity in humans.

4.3.1.10 Mercury (Hg)
Mercury in the environment is transformed into a more toxic form, methylmercury (MeHg). Because Hg is a persistent pollutant, MeHg accumu lates in the food chain, especially the tissue of fish. When people consume these fish, they consume MeHg. In 2000, the NAS Study was issued which provides a thorough review of the effects of MeHg on human health

. 40 Many of the peer

- reviewed articles cited in this section are publications originally cited in the MeHg Study. In addition, the EPA has conducted literature searches to obtain other related and more recent publications to complement the material summarized by the NRC in 2000.

In its review of the literature, the NAS found neurodevelopmental effects to be the most sensitive and best documented endpoints and appropriate for establishing an RfD ; 39 in particular NAS supported the use of results from neurobehavioral or neuropsychological tests. The NAS report noted that studies in animals reported sensory effects as well as effects on brain development and memory functions and support the conclusions based on epidemiology studies. The NAS noted that their recommended endpoints for an RfD are associated w ith the ability of children to learn and to succeed in school. They concluded the following: “ The population at highest risk is the children of women who consumed large amounts of fish and seafood during pregnancy. The committee concludes that the risk to that population is likely to be sufficient to result in an increase in the number of children who have to struggle to keep up in school. ”

The NAS summarized data on cardiovascular effects available up to 2000. Based on these and other studies, the NRC conc luded that “ Although the data base is not as extensive for cardiovascular effects as it is for other end points (i.e. neurologic effects) the cardiovascular system appears to be a target for MeHg toxicity in humans and animals. ” The NRC also stated
that “ a dditional studies are needed to better characterize the effect of methylmercury exposure on blood pressure and cardiovascular function at various stages of life. ”

Additional cardiovascular studies have been published since 2000. The EPA did not to develop a quantitative dose

- response assessment for cardiovascular effects associated with MeHg exposures, as there is no consensus among scientists on the dose

- response functions for these effects. In addition, there is inconsistency among available studies as to the association between MeHg exposure and various cardiovascular system effects. The pharmacokinetics of

40 National Research Council (NRC). 2000 . Toxicological Effects of Methylmercury . Washington, DC: National Academies Press.***E.O. 12866 Review

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- 33 some of the exposure measures (such as toenail Hg levels) are not well understood. The studies have not yet received the review and scrutiny of the mo re well

- established neurotoxicity data
base.

The Mercury Study 41 noted that MeHg is not a potent mutagen but is capable of causing chromosomal damage in a number of experimental systems. The NAS concluded that evidence that human exposure to MeHg caused ge netic damage is inconclusive; they note that some earlier studies showing chromosomal damage in lymphocytes may not have controlled sufficiently for potential confounders. One study of adults living in the Tapajós River region in Brazil reported a
direct r elationship between MeHg concentration in hair and DNA damage in lymphocytes; as
well as effects on chromosomes

. 42 Long

- term MeHg exposures in this population were believed to occur through consumption of fish, suggesting that genotoxic effects (largely chromosomal aberrations) may result from dietary, chronic MeHg exposures similar to and above those seen in the Faroes and Seychelles populations.

Although exposure to some forms of Hg can result in a decrease in immune activity or an

a utoimmune response

, 43 evidence for immunotoxic effects of MeHg is limited

. 39

Based on limited human and animal data, MeHg is classified as a “ possible ” human carcinogen by the International Agency for Research on Cancer 44 and in IRIS

. 45 The existing evidence supporting the poss ibility of carcinogenic effects in humans from low

- dose chronic exposures is tenuous. Multiple human epidemiological studies have found no significant association between Hg exposure and overall cancer incidence, although a few studies have
shown an associ ation between Hg exposure and specific types of cancer incidence (e.g., acute leukemia and liver cancer). 39

41 U.S. Environmental Protection Agen cy (U.S. EPA). 1997. Mercury Study Report to Congress , EPA

– HQ

– OAR

– 2009

– 0234

– 3054. December. Available on the Internet at <http://www.epa.gov/hg/report.htm>.

42 Amorim, M.I.M., D. Mergler, M.O. Bahia, H. Dubeau, D. Miranda, J. Lebel, R.R. Burbano, and M. Luco tte. 2000. Cytogenetic damage related to low levels of methyl mercury contamination in the Brazilian Amazon. An. Acad. Bras. Ciênc. 72(4): 497

- 507.

43 Agency for Toxic Substances and Disease Registry (ATSDR). 1999. Toxicological Profile for Mercury. U.S. Dep artment of Health and Human Services, Public Health Service, Atlanta, GA.

44 International Agency for Research on Cancer (IARC). 1994. IARC Monographs on the Evaluation of Carcinogenic Risks to Humans and their Supplements: Beryllium, Cadmium, Mercury, and E xposures in the Glass Manufacturing Industry. Vol. 58. Jalili, H.A., and A.H. Abbasi. 1961. Poisoning by ethyl mercury toluene sulphonanilide. Br. J. Indust. Med. 18(Oct.):303

- 308 (as cited in NRC 2000).

45 U.S. Environmental Protection Agency (EPA). 2002. I ntegrated Risk Information System (IRIS) on Methylmercury. National Center for Environmental Assessment. Office of Research and Development. Available online at http://www.epa.gov/iris/subst/0073.htm***E.O. 12866 Review

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- 34 There is also some evidence of reproductive and renal toxicity in humans from MeHg exposure. However, overall, human data regarding reproductive, re nal, and hematological toxicity from MeHg are very limited and are based on either studies of the two high

- dose poisoning episodes in Iraq and Japan or animal data, rather than epidemiological studies of chronic exposures at the levels of interest in this analysis.

4.3.1.11 Nickel (Ni) 46
Respiratory effects have been reported in humans from inhalation exposure to Ni. No information is available regarding the reproductive or developmental effects of Ni in humans, but animal studies have reported such effects. Human a nd animal studies have reported an increased risk of lung and nasal cancers from exposure to Ni refinery dusts and nickel subsulfide. The EPA has classified nickel subsulfide as a human carcinogen and nickel carbonyl as a probable human carcinogen

. 47

, 48 The IARC has classified Ni compounds as carcinogenic to humans.

4.3.1.12 Selenium (Se) 49

Acute exposure to elemental Se, hydrogen selenide, and selenium dioxide (SeO 2 ) by inhalation results primarily in respiratory effects, such as irritation of the mucous membranes,

p ulmonary edema, severe bronchitis, and bronchial pneumonia. One Se compound, selenium sulfide, is carcinogenic in animals exposed orally. The EPA has classified elemental Se as a Group D, not classifiable as to human carcinogenicity, and selenium sulfide a s a Group B2, probable human carcinogen.

4.3.2 Additional SO 2 Health Co

- b enefits
In addition to being a precursor to PM 2.5 , SO 2 emissions are also associated with a variety of adverse health effects associated with direct exposure. Unfortunately, we were unable
to estimate the health co

- benefits associated with reduced SO 2 in this analysis because we do not have air quality modeli ng data available. Therefore, this analysis only quantifies and monetizes
the PM 2.5 co

- benefits associated with the reductions in SO 2 emissions.

46 Nickel (IARC Summary & Evaluation , Volume 49, 1990), Please check if there are relevant to this sectorhttp://www.inchem.org/documents/iarc/vol49/nickel.html

47 U.S. Environmental Protection Agency. Integrated Risk Information System (IRIS) on Nickel Subsulfide. National Center for Environmental Assessment, Of fice of Research and Development, Washington, DC. 1999.

48 U.S. Environmental Protection Agency. Integrated Risk Information System (IRIS) on Nickel Carbonyl. National Center for Environmental Assessment, Office of Research and Development, Washington, DC. 1999.

49 U.S. Environmental Protection Agency. Integrated Risk Information System (IRIS) on Selenium and Compounds. National Center for Environmental Assessment, Office of Research and Development, Washington, DC. 1999.***E.O. 12866 Review

- Draft

- Do Not Cite, Quote, or Release During Review***

4

- 35 Following an extensive evaluation of health evidence from epidemiologic and laboratory studies, the Integrated Science Assessment for Oxides of Sulfur

—

Health Criteria (SO 2 ISA) concluded that there is a causal relationship between respiratory health effects and short

- term exposure to SO 2

. 50 The immediate effect of SO 2 on the respiratory system in humans is
bronchoc onstriction. Asthmatics are more sensitive to the effects of SO 2 likely resulting from preexisting inflammation associated with this disease. A clear concentration

- response relationship has been demonstrated in laboratory studies following exposures to SO 2 at concentrations between 20 and 100 ppb, both in terms of increasing severity of effect and percentage of asthmatics adversely affected. Based on our review of this information, we
identified four short

- term morbidity endpoints that the SO 2 ISA identifie d as a “ causal relationship ” : asthma exacerbation, respiratory

- related emergency department visits, and respiratory

- related hospitalizations. The differing evidence and associated strength of the
evidence for these different effects is described in detail in the SO 2 ISA. The SO 2 ISA also concluded that the relationship between short

- term SO 2 exposure and premature mortality was

“ suggestive of a causal relationship ” because it is difficult to attribute the mortality risk effects to
SO 2 alone. Although the SO 2 ISA stated that studies are generally consistent in reporting a relationship between SO 2 exposure and mortality, there was a lack of robustness of the observed associations to adjustment for pollutants. We did not quantify these co

- benefits due to data

c onstraints.

4.3.3 Visibility Impairment Co

- b enefits
Reducing secondary formation of PM 2.5 would improve levels visibility in the U.S. because suspended particles and gases degrade visibility by scattering and absorbing light (U.S. EPA, 2009). Fine particles with significant light

- extinction efficiencies include sulfates, nitrates, organic carbon, elemental carbon, and soil. 51 Visibility has direct significance to people ’ s enjoyment of daily activities and their overall sense of well

- being. Good visibility increase s the quality of life where individuals live and work, and where they engage in recreational activities. Particulate sulfate is the dominant source of regional haze in the eastern U.S. and particulate nitrate is an important contributor to light extinction in California and the upper Midwestern

50 U.S. Environmental Protection Agenc y (U.S. EPA). 2008 a

. Integrated Science Assessment for Sulfur Oxides

— Health Criteria (Final Report)

. National Center for Environmental Assessment, Research Triangle Park, NC. September. Available at: < http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=198843>.
51 Sisler, J.F. 1996. Spatial and seasonal patterns and long

- term variability of the composition of the haze in the United States: an analysis of data from the IMPROVE network . CIRA Report, ISSN 0 737

- 5352

- 32, Colorado State University.***E.O. 12866 Review

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- Do Not Cite, Quote, or Release During Review***

4

- 36 U.S., particularly during winter (U.S. EPA, 2009). Previous analyses 52 show that visibility benefits can be a significant welfare benefit category. Without air quality modeling, we are not
unable to estimate visibilit y related benefits, nor are we able to determine whether the emission reductions associated with this rule would be likely to have a significant impact on visibility in
urban areas or Class I areas.

4.4 References Abt Associates, Inc. 2012. BenMAP User ’ s Manua l Appendices . Prepared for U.S. Environmental Protection Agency Office of Air Quality Planning and Standards. Research Triangle Park, NC. September. Available on the Internet at <http://www.epa.gov/air/benmap/models/BenMAPAppendicesOct2012.pdf>.

Fann, N., C.M. Fulcher, B.J. Hubbell. 2009. “ The influence of location, source, and emission type in estimates of the human health benefits of reducing a ton of air pollution. ” Air Qual Atmos Health 2:169

– 176.

Fann, N., K.R. Baker, and C.M. Fulcher. 2012. “ Character izing the PM2.5

- related health benefits of emission reductions for 17 industrial, area and mobile emission sectors across the U.S. ” Environment International 49 41

– 151.

Gwinn, M.R

., J . Craig, D.A . Axelrad, R . Cook, C . Dockins, N . Fann, R . Fegley, D.E . Guinnup, G

. Helfand, B . Hubbell, S.L . Mazur, T . Palma, R.L . Smith, J . Vandenberg, and B

. Sonawane. 2011. “ Meeting report: Estimating the benefits of reducing hazardous air pollutants

— summary of 2009 workshop and future considerations. ” Environ Health Perspect

. Jan; 119(1): p. 125

- 30.

Industrial Economics, Incorporated (IEc). 2009. Section 812 Prospective Study of the Benefits and Cost s of the Clean Air Act: Air Toxics Case Study

— Health Benefits of Benzene Reductions in Houston, 1990

– 2020 . Final Report, July 14, 2009. Available on the Internet at <http://www.epa.gov/air/sect812/dec09/812CAAA_Benzene_Houston_Final_Report_Jul y_2009.pdf>.

Industrial Economics, Incorporated (IEc). 2006. Expanded Expert Judgment Assessment of the Concentration

- Response Relationship Between PM 2.5 Exposure and Mortality . Prepared for: Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, Research Triangle Park, NC. September. Available on the Internet at <http://www.epa.gov/ttn/ecas/regdata/Uncertainty/pm_ee_tsd_expert_interview_summari es.pdf>.

52 U.S. Environmental Protection Agency (U.S. EPA). 2011a. The Benefits and Costs of the Clean Air Act from 1990 to 2020 . Office of Air and Radiation, Washington, DC. March. <http://www.epa.gov/air/sect812/feb11/fullr eport.pdf>. Accessed March 30, 2011.***E.O. 12866 Review

- Draft

- Do Not Cite, Quote, or Release During Review***

4

- 37 Krewski D, Jerrett M, Burnett RT, Ma R, Hughes E, Shi, Y, et al. 2009. Extended follow

- u p and spatial analysis of the American Cancer Society study linking particulate air pollution and mortality. HEI Research Report, 140, Health Effects Institute, Boston, MA.

Lepeule J, Laden F, Dockery D, Schwartz J 2012. “ Chronic Exposure to Fine Particles and Mortality: An Extended Follow

- Up of the Harvard Six Cities Study from 1974 to 2009. ” Environ Health Perspect. Jul;120(7):965

- 70.

National Research Council (NRC). 2002. Estimating the Public Health Benefits of Proposed Air Pollution Regulations

. Washington, DC: The National Academies Press.

Office of Management and Budget (OMB). 2003. Circular A

- 4: Regulatory Analysis. Washington, DC. Available on the Internet at http://www.whitehouse.gov/omb/circulars/a004/a

- 4.html.

Roman, Henry A., Katherine D. Walker, Tyra L. Walsh, Lisa Conner, Harvey M. Richmond, Bryan J. Hubbell, and Patrick L. Kinney. 2008. “ Expert Judgment Assessment of the Mortality Impact of Changes in Ambient Fine Particulate Matter in the U.S. ” Environ. Sci. Technol ., 42(7):2268

- 2274.

S isler, J.F. 1996. Spatial and seasonal patterns and long

- term variability of the composition of the haze in the United States: an analysis of data from the IMPROVE network . CIRA Report, ISSN 0737

- 5352

- 32, Colorado State University.

U.S. Environmental Prote ction Agency (U.S. EPA). 1995. Regulatory Impact Analysis for the Petroleum Refinery NESHAP. Revised Draft for Promulgation . Office of Air Quality Planning and Standards, Research Triangle Park, N.C. Available on the Internet at

< http://envinfo.com/caain/m act/petro r ia. html >.
U.S. Environmental Protection Agency (U.S. EPA). 2000. Guidelines for Preparing Economic Analyses. EPA 240

- R

- 00

- 003. National Center for Environmental Economics, Office of Policy Economics and Innovation. Washington, DC. September. Ava ilable on the Internet at <http://yosemite.epa.gov/ee/epa/eed.nsf/webpages/Guidelines.html/$file/cover.pdf>.

U.S. Environmental Protection Agency

- Science Advisory Board (U.S. EPA

- SAB). 2002. Workshop on the Benefits of Reductions in Exposure to Hazardous Air Pollutants: Developing Best Estimates of Dose

- Response Functions An SAB Workshop Report of an EPA/SAB Workshop (Final Report). EPA

- SAB

- EC

- WKSHP

- 02

- 001. January. Available on the Internet at <http://yosemite.epa.gov/sab%5CSABPRODUCT.NSF/34355712EC011A3 58525719A0 05BF6F6/$File/ecwkshp02001%2Bappa

- g.pdf>.

U.S. Environmental Protection Agency (U.S. EPA). 2006. Air Quality Criteria for Ozone and Related Photochemical Oxidants (Final) . EPA/600/R

- 05/004aF

- cF. Washington, DC: U.S. EPA. February. Available on th e Internet at <http://cfpub.epa.gov/ncea/CFM/recordisplay.cfm?deid=149923>.***E.O. 12866 Review

- Draft

- Do Not Cite, Quote, or Release During Review***

4

- 38 U.S. Environmental Protection Agency (U.S. EPA). 2008 a

. Integrated Science Assessment for Sulfur Oxides

— Health Criteria (Final Report)

. National Center for Environmental Assessment, Research Triangle Park, NC. September. Available at:

< http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=198843>.

U.S. Environmental Protection Agency (U.S. EPA). 2008c. Integrated Science Assessment for Oxides of Nitrogen

- Health Criteria (F inal Report). National Center for Environmental Assessment, Research Triangle Park, NC. July. Available at <http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=194645>.

U.S. Environmental Protection Agency (U.S. EPA). 2008d. Integrated Science Assessment for Oxides of Nitrogen and Sulfur

–

Ecological Criteria National (Final Report ). National Center for Environmental Assessment, Research Triangle Park, NC. EPA/600/R

- 08/139. December. Available at <http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=201485>.

U.S. Environmental Protection Agency (U.S. EPA). 2009. Integrated Science Assessment for Particulate Matter (Final Report) . EPA

- 600

- R

- 08

- 139F. National Center for Environmental Assessment

– RTP Division. December. Available on the Internet at

< http://cfpub .epa.gov/ncea/cfm/recordisplay.cfm?deid=216546 >.
U.S. Environmental Protection Agency (U.S. EPA). 2010a. Integrated Science Assessment for Carbon Monoxide. National Center for Environmental Assessment, Research Triangle Park, NC. EPA/600/R

- 09/019F. January . Available at <http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=218686>.

U.S. Environmental Protection Agency (U.S. EPA). 2010b. Technical Support Document: Summary of Expert Opinions on the Existence of a Threshold in the Concentration

Response Functi on for PM 2.5 - related Mortality . Research Triangle Park, NC. June. Available on the Internet at < www.epa.gov/ttn/ecas/regdata/Benefits/ thresholds tsd.pdf>.

U.S. Environmental Protection Agency (U.S. EPA). 2010c. Valuing Mortality Risk Reductions for Environm ental Policy: A White Paper: SAB Review Draft . National Center for Environmental Economics December. Available on the Internet at <http://yosemite.epa.gov/ee/epa/eerm.nsf/vwAN/EE

- 0563

- 1.pdf/$file/EE

- 0563

- 1.pdf>.

U.S. Environmental Protection Agency (U.S. E PA). 2010e. Guidelines for Preparing Economic Analyses . EPA 240

- R

- 10

- 001. National Center for Environmental Economics, Office of Policy Economics and Innovation. Washington, DC. December. Available on the Internet
at < http://yosemite.epa.gov/ee/epa/eerm.nsf/vwAN/EE

- 0568

- 50.pdf/$file/EE

- 0568

- 50.pdf>.

U.S. Environmental Protection Agency (U.S. EPA). 2011a. The Benefits and Costs of the Clean Air Act from 1990 to 2020 . Office of Air and Radiation, Washington, DC. March.

< http://www.epa.gov/air/sect812/feb11/fullreport.pdf>. Accessed March 30, 2011.

U.S. Environmental Protection Agency (U.S. EPA). 2011b. Regulatory Impact Analysis for the Final Mercury and Air Toxics Standards. EPA

- 452/R

- 11

- 011. December. Available on the I nternet at <http://www.epa.gov/ttn/ecas/regdata/RIAs/matsriafinal.pdf>.***E.O. 12866 Review

- Draft

- Do Not Cite, Quote, or Release During Review***

4

- 39 U.S. Environmental Protection Agency (U.S. EPA). 2011c. 2005 National

- Scale Air Toxics Assessment

. Office of Air Quality Planning and Standards, Research Triangle Park, NC. March. Avai lable on the Internet at http://www.epa.gov/ttn/atw/nata2005/.

U.S. Environmental Protection Agency (U.S. EPA). 2011d. Regulatory Impact Analysis: National Emission Standards for Hazardous Air Pollutants for Industrial, Commercial, and Institutional Boile rs and Process Heaters

. February. Available on the Internet at <http://www.epa.gov/ttnecas1/regdata/RIAs/boilersriafinal110221_psg.pdf>.

U.S. Environmental Protection Agency (U.S. EPA). 2012a. Regulatory Impact Analysis for the Final Revisions to the Natio nal Ambient Air Quality Standards for Particulate Matter

. EPA

- 452/R

- 12

- 003. Office of Air Quality Planning and Standards, Health and Environmental Impacts Division. December. Available at <http://www.epa.gov/pm/2012/finalria.pdf>.

U.S. Environmental Prote ction Agency (U.S. EPA). 2012b. Regulatory Impact Analysis: Petroleum Refineries New Source Performance Standards Ja. Office of Air Quality Planning and Standards, Health and Environmental Impacts Division. June. Available at <http://www.epa.gov/ttnecas1/r egdata/RIAs/refineries_nsps_ja_final_ria.pdf>.

U.S. Environmental Protection Agency (U.S. EPA). 2013. Technical Support Document: Estimating the Benefit per ton of Reducing PM 2.5 Precursors from 17 sectors . Office of Air Quality Planning and Standards, Re search Triangle Park, NC. February.

U.S. Environmental Protection Agency

— Science Advisory Board (U.S. EPA

- SAB). 2008. Characterizing Uncertainty in Particulate Matter Benefits Using Expert Elicitation. EPA

- COUNCIL

- 08

- 002. July. Available on the Internet at <http://yosemite.epa.gov/sab/sabproduct.nsf/0/43B91173651AED9E85257487004EA6C B/$File/EPA

- COUNCIL

- 08

- 002

- unsigned.pdf>.

U.S. Environmental Protection Agency

— Science Advisory Board (U.S. EPA

- SAB). 200 0. An SAB Report on EPA ’ s White Paper Valuing the Benefit s of Fatal Cancer Risk Reduction. EPA

- SAB

- EEAC

- 00

- 013. July. Available on the Internet at

< http://yosemite.epa.gov/sab%5CSABPRODUCT.NSF/41334524148BCCD6852571A70 0516498/$File/eeacf013.pdf>.

U.S. Environmental Protection Agency

— Science Advisory Board (U.S. EPA

- SAB). 20 04 c

. Advisory Council on Clean Air Compliance Analysis Response to Agency Request on Cessation Lag. EPA

- COUNCIL

- LTR

- 05

- 001. December. Available on the Internet at

< http://yosemite.epa.gov/sab/sabproduct.nsf/0/39F44B098DB49F3C85257170005293E0/ $File/council_ltr_05_001.pdf >.
U.S. Environmental Protection Agency

— Science Advisory Board (U.S. EPA

- SAB). 2008. Benefits of Reducing B enzene Emissions in Houston, 1990

– 2020 . EPA

- COUNCIL

- 08

- 001. July. Available at <http://yosemite.epa.gov/sab/sabproduct.nsf/D4D7EC9DAEDA8A548525748600728A8 3/$File/EPA

- COUNCIL

- 08

- 001

- unsigned.pdf>.***E.O. 12866 Review

- Draft

- Do Not Cite, Quote, or Release During Review***

4

- 40 U.S. Environmental Protection Agency

— Science Advisory Board (U.S. EPA

- SAB). 2009b. Review of EPA ’ s Integrated Science Assessment for Particulate Matter (First External Review Draft, December 2008) . EPA

- COUNCIL

- 09

- 008. May. Available on the Internet
at <http://yosemite.epa.gov/sab/SABPRODUCT.NSF/81e39f4c09954fcb8525 6ead006be86 e/73ACCA834AB44A10852575BD0064346B/$File/EPA

- CASAC

- 09

- 008

- unsigned.pdf>.

U.S. Environmental Protection Agency

— Science Advisory Board (U.S. EPA

- SAB). 2009c. Review of Integrated Science Assessment for Particulate Matter (Second External Review Dr aft, July 2009) . EPA

- CASAC

- 10

- 001. November. Available on the Internet at <http://yosemite.epa.gov/sab/SABPRODUCT.NSF/81e39f4c09954fcb85256ead006be86 e/151B1F83B023145585257678006836B9/$File/EPA

- CASAC

- 10

- 001

- unsigned.pdf>.

U.S. Environmental Protection Agency

— Science Advisory Board (U.S. EPA

- SAB). 20 10a. Review of EPA ’ s DRAFT Health Benefits of the Second Section 812 Prospective Study of the Clean Air Act . EPA

- COUNCIL

- 10

- 001. June. Available on the Internet at <http://yosemite.epa.gov/sab/sabproduct.nsf/ 9288428b8eeea4c885257242006935a3/59e0 6b6c5ca66597852575e7006c5d09!OpenDocument&TableRow=2.3#2.>.

U.S. Environmental Protection Agency

— Science Advisory Board (U.S. EPA

- SAB). 2011. Review of Valuing Mortality Risk Reductions for Environmental Policy: A White Paper (December 10, 2010). EPA

- SAB

- 11

- 011 July

. Available on the Internet at <http://yosemite.epa.gov/sab/sabproduct.nsf/298E1F50F844BC23852578DC0059A616/$ File/EPA

- SAB

- 11

- 011

- unsigned.pdf>

.***E.O. 12866 Review

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5

- 1 SECTION 5
ECONOMIC IMPAC T ANALYSIS

EPA prepares an EIA to provide decision makers with a measure of the social costs of using resources to comply with a regulation (EPA, 201 0 ). The social costs can then be compared with estimated social benefits (as presented in Section 4). As noted in EPA ’ s (2010 ) Guidelines for Preparing Economic Analyses , several tools are available to estimate social costs and range from simple direct compliance cost methods to the development of a more complex market analysis that estimates market changes (e.g., price and consumption) and economic welfare changes (e.g., changes in consumer and producer surplus).

The Office of Air Quality Planning and Standards ( OAQPS) adopt ed a market

- level analysis described in the Office ’ s re source manual (EPA, 1999a ). The market approach uses a single

- period static partial

- equilibrium model to compare pre

- policy market baselines with expected post policy outcomes in the se markets. Key measures in this analysis include

■ market

- level effects (market prices, changes in domestic production and

consum ption, and international trade) and

■ social costs and their distribution between producers and consumers

.

We also assessed the im pacts on employment in the brick industry through a qualitative discussion and a quantitative analysis that is linked to the results of the market

- level analysis. Finally, we assessed how the regulatory program may influence the profitability of large and
small ultimate parent companies that own affected BSCP facilities. To do this, we used a screening analysis required to comply with the Regulatory Flexibility Act (RFA) as amended by the Small Business Regulatory Enforcement Fairness Act (SBREFA)

.
5.1 Market Analysis
The partial

- equilibrium analysis includes a market model that simulates how stakeholders (consumers and firms) might respond to the additional regulatory program costs. EPA used a perfectly competitive regional market model that accounts for the f act that brick shipments are not likely to be shipped long distances because of weight and transportation costs. In regional markets, it is more likely that only a few firms offer similar brick products and other market structures may be applicable (i.e., oligopoly). If market power exists, the use of a perfectly competitive model may understate the social costs of the final rule. Appendix A provides additional details about the economic model equations and parameters.***E.O. 12866 Review

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5

- 2 5.1.1 Market

- Level Results

Market

- level impa cts include the price and production adjustments for bricks. As shown
in Table 5

- 1, the average national price under the final standards increases by 1. 8 %, or $ 4.37 per 1,000 SBE, while overall domestic production falls by 1. 5 %, or 52 million bricks per ye ar. These values are slightly higher than the Option 1 approach: the average national price increase for the Option 1 standards is 1. 8 %
, or $4.27 per 1,000 SBE and U.S. brick production falls by about 50
million bricks. These values are lower than t he Option 3 approach: the average national price
increase for the Option 3 standards is 3

. 2 % and U.S. brick production falls by about 90 million
bricks.

Price increases are the highest in regions with high unit compliance costs. For example,
the East North C entral market price increase ($ 7.45 per 1,000 SBE) is associated with higher

per

- unit compliance costs ($1 6.56 per 1,000 SBE). Under the final standards, one region does not include any facilities with incremental compliance costs (New England). As a resul t, there are no
market

- level changes. For all of the census regions, the average regional price increases between
0% and 3. 7 %. Regional domestic production falls between 0% and 2. 9 % and 0 to 20 million bricks per year. Under the Option 1 standards, the ave rage regional price increases between 0%
and 3. 8 %. Regional domestic production falls between 0% and 3.0 %, or 0 to 1 6 million bricks

per year. Under the Option 3 standards, the average regional price increases between 0% and
5. 8 %. Regional domestic product ion falls between 0% and 4. 6 %, or 0 to 3 3 million bricks per

year.

5.1.2 Social Cost Estimates

Under the final standards, the economic model suggests that industries are able to pass on $ 1 5.1 million (2011$) of the rule ’ s costs to U.S. households in the form of higher prices (Table
5

- 1). Existing U.S. industries ’ surplus falls by $ 1 2.1 million, and the total U.S. economic surplus loss is $2 7.2 million. Under the Option 1 standards, total U.S. economic surplus loss is $ 0.6
million lo wer ($ 2 6.6 million) , and under the Option 3 standards

, total U.S economic surplus loss
is $ 21.4 million higher ( $ 4 8.6 million). Because higher brick prices reduce consumption, the estimated compliance costs are lower than the engineering cost estimate that does not account for price responses. However, the differences are very small (i.e., less than 0.01%).

### ***E.O. 12866 Review

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### Table 5

- 1. Estimated Market Impacts of Final BSCP NESHAP

Census Region Incremental Unit Compliance Costs

($/1,000 SBE) Market Price Change U.S. Production Change Change in:

Absolute Percent Absolute Percent Consumer Surplus Producer Surplus Total Surplus Option 2: Final Rule
New England $0.00 $0.00 0.0% 0 0.0% $0.0 $0.0 $0.0

Middle Atlantic $14.37 $5.51 1.7%

− 2,847

− 1.3%

− $1.2

− $0.9

− $2.1

East North Central $16.56 $7.45 2.5%

− 5,629

− 2.0%

− $2.1

− $1.7

− $3.8

West North Central $4.73 $2.63 0.9%

− 1,389

− 0.8%

− $0.5

− $0.4

− $0.9

South Atlantic $8.49 $4.34 1.9%

− 19,586

− 1.5%

− $5.6

− $4.5

− $10.1

East South Central $12.34 $6.85 3.7%

− 11,442

− 2.9%

− $2.6

− $2.1

− $4.7

West South Central $5.97 $3.32 1.4%

− 10,315

− 1.2%

− $2.9

− $2.4

− $5.3

Mountain $1.93 $0.54 0.1%

− 135

− 0.1%

− $0.1 $0.0

− $0.1

Pacific $3.51 $1.66 0.3%

− 179

− 0.2%

− $0.1

− $0.1

− $0.2
U.S. Average/Total $8.68 $4.37 1.8%

− 51,521

− 1.5%

− $15.1

− $12.1

− $27.2 ( continued)

### ***E.O. 12866 Review

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### Table 5

- 1. Estimated Market Impacts of Final BSCP NESHAP (continued)

Census Region Incremental Unit Compliance Costs

($/1,000 SBE) Market Price Change U.S. Production Change Change in:

Absolute Percent Absolute Percent Consumer Surplus Producer Surplus Total Surplus Option 1
New England $0.00 $0.00 0.0% 0 0.0% $0.0 $0.0 $0.0

Middle Atlantic $11.28 $4.33 1.3%

− 2,236

− 1.0%

− $0.9

− $0.7

− $1.6

East North Central $16.56 $7.45 2.5%

− 5,628

− 2.0%

− $2.1

− $1.7

− $3.8

West North Central $4.73 $2.63 0.9%

− 1,389

− 0.8%

− $0.5

− $0.4

− $0.9

South Atlantic $7.09 $3.62 1.6%

− 16,347

− 1.3%

− $4.7

− $3.8

− $8.5

East South Central $12.67 $7.04 3.8%

− 11,755

− 3.0%

− $2.7

− $2.2

− $4.9

West South Central $7.16 $3.98 1.7%

− 12,382

− 1.4%

− $3.5

− $2.8

− $6.3

Mountain $8.16 $2.27 0.6%

− 572

− 0.5%

− $0.3

− $0.2

− $0.5

Pacific $3.51 $1.66 0.3%

− 179

− 0.2%

− $0.1

− $0.1

− $0.2
U.S. Average/Total $8.49 $4.27 1.8%

− 50,487

− 1.4%

− $14.8

− $11.8

− $26.6 (continued)

### ***E.O. 12866 Review

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### Table 5

- 1. Estimated Market Impacts of Final BSCP NESHAP (continued)

Census Region Incremental Unit Compliance Costs

($/1,000 SBE) Market Price Change U.S. Production Change Change in:

Absolute Percent Absolute Percent Consumer Surplus Producer Surplus Total Surplus Option 3
New England $0.00 $0.00 0.0% 0 0.0% $0.0 $0.0 $0.0

Middle Atlantic $16.04 $6.15 1.9%

− 3,179

− 1.5%

− $1.3

− $1.0

− $2.3

East North Central $28.31 $12.74 4.2%

− 9,623

− 3.4%

− $3.6

− $2.8

− $6.4

West North Central $19.12 $10.62 3.8%

− 5,613

− 3.1%

− $1.9

− $1.5

− $3.4

South Atlantic $14.15 $7.23 3.1%

− 32,635

− 2.5%

− $9.3

− $7.4

− $16.8

East South Central $19.48 $10.82 5.8%

− 18,072

− 4.6%

− $4.1

− $3.3

− $7.4

West South Central $10.37 $5.76 2.5%

− 17,926

− 2.0%

− $5.1

− $4.1

− $9.1

Mountain $14.39 $4.00 1.1%

− 1,008

− 0.9%

− $0.5

− $0.4

− $0.8

Pacific $37.17 $17.55 3.2%

− 1,899

− 2.5%

− $1.3

− $1.0

− $2.3
U.S. Average/Total $15.62 $7.86 3.2%

− 89,954

− 2.6%

− $27.1

− $21.5

− $48.6***E.O. 12866 Review

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- 6 5.2 Employment Impacts of the Final Rule 53

Executive Order 13563 directs federal agencies to consider the effect of regulations on job creation and employment. According to the Executive Order, “ our regulatory system must protect public health, welfare, safety, and our environment w hile promoting economic growth, innovation, competitiveness, and job creation. It must be based on the best available sc ience ” (Executive Order 13563, 2011 ). Although standard benefit

- cost analy ses have not typically included a separate analysis of regulation

- induced employment impacts, 54 during periods of sustained high unemployment, empl oyment impacts are of particular concern and questions may arise about their existence and magnitude . This chapter provides a conceptual framework for considering the potential influence of environmental regulation on employment in the U.S. economy and dis cusses the limited empirical literature that is available. The chapter then
discuss es the potential employment imp acts in the BSCP industry, as well as the environmental protection sector ( e.g. , for construction, manufacture, installation and operation of needed pollution control equipment )

. Section 5 .2 .1 describes the economic theory used for analyzing regulation

- induced employment impacts , discussing how standard neoclassical theory alone does not point to a definitive net effect of regulation on labor de mand for regulated firms. Section
5

. 2.2 presents an overview of the peer

- reviewed literature relevant to evaluating the effect of environmental reg ulation on employment. Section 5.2.3 discusses macroeconomic net employment effects. EPA is currently in the process of seeking input from an independent expert panel on economy

- wide impacts, including employment effects. Section 5.2.4 addresses the particular influence of this final rule on employment. Finally, Section 5

. 2.5 offer s several
conclusions.

5.2.1 Theory

Th e effects of environmental regulation on employment are difficult to disentangle from other economic changes and business decisions that affect employment, over time and across regions and industries

. L abor markets respond to regulation in complex ways . That response depends on the elasticities of demand and supply for labor and the degree of labor market imperfections (e.g.

, wage stickiness, long

- term unemployment) . The unit of measurement (e.g., number of jobs, types of job hours worked, or earnings) may affect observability of that

response

. Net employment impacts are composed of a mix of potential declines and gains in different areas of the economy (i.e., the directly regulated sector, upstream and downstream

53 The employment analysis in this RIA is part of EPA ’ s ongoing effort to “ conduct continuing evaluations of potential loss or shifts of employment which may result from the administration or enforcement of [the Act] ”
pu rsuant to CAA section 321(a).
54 L abor expenses do, however, contribute toward total costs in EPA’s standard benefit

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- 7 sectors, and the pollution abatement sec tor) and over time. In light of these difficulties, e conomic theory provides a constructive framework for approaching these assessments and for better understanding the inherent complexities in such assessments. In this section, we briefly describe theory relevant to the impact of regulation on labor demand at the regulated firm, in the regulated industry, and in the environmental protection sector and highlight the importance of considering potential effects of regulation on labor supply, a topic addressed further in a subsequent section.

Neoclassical microeconomic theory describes how profit

- maximizing firms adjust their use of productive inputs in response to changes in their economic conditions. 55 In this framework, labor is one of many inputs to product ion, along with capital, energy, and materials. In competitive output markets, profit

- maximizing firms take prices as given and choose quantities of inputs and outputs to maximize profit. Factor demand at the firm, then, is determined by input and output p rices. 56 , 57

Berman and Bui (2001) and Morgenstern, Pizer, and Shih (2002) have specifically tailored one version of the standard neoclassical model to analyze how environmental regula tions
affect labor demand decisions. 58 Environmental regulation is modeled as effectively requiring certain factors of production, such as pollution abatement capital investment, that would not be freely chosen by profit

- maximizing/cost

- minimizing firms.

In Berman and Bui ’ s (2001, p. 274

– 75) theoretical model, the change in a firm ’ s labor demand arising from a change in regulation is decomposed into two main components: output
and substitution effects. 59 For the output effect, by affecting the marginal cost of production, regulation affects the profit

- maximizing quantity of output. The output effect describes how, if labor intensity of production is held constant, a decrease in output generally leads to a decrease in labor demand. However, as noted by Berman and Bui, although it is often assumed that regulation increases marginal cost, and thereby reduces output, it need not be the case. A regulation could induce a firm to upgrade to less polluting and more efficient equipment that

55 See Layard and Walters (1978) , a standard microeconomic theory textbook, for a discussion.
56 See Hamermesh (1993) , Chapter 2, for a derivation of the firm’s labor demand function from cost

- minimization.

57 In this framework, labor demand is a function of quantity of output and prices (of both output s and input s )

. 58 Berman and Bui (2001) and Morgenstern, Pizer, and Shih (2002) used a cost

- minimization framework, which is a special case of profit

- maximization with fixed output quantities.
59 The authors a lso discuss a third component, the impact of regulation on factor prices but conclude that this effect is unlikely to be important for large competitive factor markets, such as labor and capital. Morgenstern, Pizer, and Shih (2002) used a very similar model, but they break the employment effect into three parts: 1) the demand effect, 2) the cost effect, and 3) the factor

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- 8 lowers marginal production costs, for example. In such a case, output could theoretically
increase.

The substitution effect describes how, holding output constant, regulation affects the labor intensity of production. Although increased environmental regulation generally results in higher utilization of production factors such as pollution control equipment and energy to operate that equipment, the resulting impact on labor demand is ambiguous. For example, e quipment inspection requirements, specialized waste handling, or pollution technologies that alter the production process may affect the number of workers necessary to produce a unit of output. Berman and Bui (2001) modeled the substitution effect as the effect of regulation on “ quasi

fixed ” pollutio n control equipment and expenditures that are required by the regulation and the corresponding change in labor intensity of production. Within the production theory framework, when levels of a given set of inputs are fixed by external constraints such as r egulatory requirements, rather than allowing the firm to freely choose all inputs under cost

- minimization alone, these inputs are described as “ quasi

- fixed. ” For example, materials would be a “ quasi

fixed ” factor if there were specific requirements for lan dfill liner construction, but the footprint of the landfill was flexible. Brown and Christensen (1981) developed a partial static equilibrium model of production with quasi

- fixed factors, which Berman and Bui (2001) extended to analyze environmental regulations with technology

- based standards.

In summary, because the output and substitution effects may be both positive, both negative, or some combination, standard neoclassical theory alone does not point to a definitive net effect of regulation on labor demand at regulated firms. Operating within the bounds of standard neoclassical theory, however, rough e stimation of net employment effects is possible with empirical study, specific to the regulated firms, when data and methods of sufficient detail and quality are available. The available literature illustrates some of the difficulties for empirical
estimat ion: studies sometimes rely on confidential plant

- level employment data from the U.S. Census Bureau, possibly combined with pollution abatement expenditure data that are too dated to be reliably informative. In addition, the most commonly used empirical me thods in the literature do not permit the estimation of net effects. These studies will be discussed at greater length later in this chapter.

The above describes a conceptual framework for analyzing potential employment effects at a particular firm within a regulated industry. It is important to emphasize that employment impacts at a particular firm will not necessarily represent impacts for the overall industry; therefore, the theoretic approach requires some adjustment when applied at the industry level.***E.O. 12866 Review

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- 9 As stated, the responsiveness of industry labor demand depends on how the output and
substitution effects interact. 60 At the industry level, labor demand will be more responsive when (1) the price elasticity of demand for the product is high, (2) other fa ctors of production can be easily substituted for labor, (3) the supply of other factors is highly elastic, or (4) labor costs are a large share of the total costs of production. 61 So, for example, if all firms in the industry are faced with the same compli ance costs of regulation and product demand is inelastic, then industry output may not change much at all, and output of individual firms may only be slightly changed. 62 In this case, the output effect may be small, while the substitution effect will still depend on the degree of substitutability or complementarity between factors of production. Continuing the example, if new pollution control equipment requires labor to install and operate, labor is more of a complement than a substitute. In this case, the substitution effect may be positive, and if the output effect is small or zero, the total effect may then be positive. As with the potential effects for an individual firm, theory alone is unable to determine the sign or magnitude of industry

- level regulat ory effects on labor. Determining these signs and magnitudes requires additional sector

- specific empirical study. To conduct such targeted research would require estimates of product demand elasticity; production factor substitutability; supply elasticity of production factors; and the share of total costs contributed by wages, by industry, and perhaps even by facility. For environmental rules, many of these data items are not publicly available, would require significant time and resources to access confid ential U.S. Census data for research, and also would not be necessary for other components of a typical RIA.

In addition to changes to labor demand in the regulated industry, net employment impacts encompass changes within the environmental protection sec tor and, potentially, in other related sectors, as well. Environmental regulations often create increased demand for pollution control equipment and services needed for compliance. This increased demand may increase revenue and employment in the environmen tal protection industry

. At the same time, the regulated industry is purchasing the equipment, and these costs may affect labor demand at regulated firms. Therefore, it is important to consider the net effect of compliance actions on employment
across mult iple sectors or industries

.
On the one hand, i f the U.S. economy is at full employment, even a large

- scale environmental regulation is unlikely to have a noticeable impact on aggregate net employment. 63

60 On Marshall’s laws of derived demand, see Ehrenberg and Smith (2000), Chapter 4

. 61 See Ehrenberg and Smith (2000), p. 108.

62 This discussion draws from Berman and Bui (2001) , p. 293.
63 Full employment is a conceptual target for the economy where everyone who wants to work and is available to do so at prevailing wages is actively employed.***E.O. 12866 Review

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- 10 Instead, labor would primarily be reallocated from one productive use to another (e.g., from producing electricity or steel to producing pollution abatement equipment ). Theory supports the argument that, in the case of full employment, the net national employment effects from environmental regulation are like ly to be small and transitory (e.g., as workers move from one job to another)

. 64 On the other hand, if the economy is operating at less than full employment

, economic theory does not clearly indicate the direction or magnitude of the net impact of
environme ntal regulation on employment; it could cause either a short

- run net increase or short

run net decrease (Schmalansee and Stavins, 2011 ). An important fundamental research question is how to accommodate unemployment as a structural feature in economic models. This feature may be important in evaluating the impact of large

- scale regulation on employment (Smith,
2012 ).

Affected sector s may experience transitory effects as workers change jobs. Some workers may need to retrain or relocate in anticipation of the new requirements or require time to search for new jobs, while shortages in some sectors or regions could bid up wages to attract workers. It is important to recognize that these adjustment cos ts can entail local labor disruptions, and although the net change in the national workforce is expected to be small, localized reductions in employment can still have negative impacts on individuals and communities just as localized increases can have pos itive impacts

.
Although the current discussion focuses on labor demand effects, environmental regulation may also affect labor supply. In particular, pollution and other environmental risks

may affect labor productivity 65 or employees ’ ability to work. Alth ough there is an accompanying, and parallel, theoretical approach to examining impacts on labor supply, similar to labor demand, it is even more difficult and complex to study labor supply empirically. There is a small, nascent empirical literature using m ore detailed labor and environmental data and quasi

experimental techniques that is starting to find traction on this question. These ar e described in
Section 5.2.6.

To summarize the discussion in this section, economic theory provides a framework for
anal yzing the impacts of environmental regulation on employment. The net employment effect incorporates expected employment changes (both positive and negative) in the regulated sector, the environmental protection sector, and other relevant sectors. Using eco nomic theory, labor demand impacts for regulated firms, and also for the regulated industry, can be decomposed into

64 Arrow et al. (1996) ; see discussion on bottom of p. 8. In practice, distributional impacts on individual workers can be important, as discussed in later paragraphs of this section.
65 For example, Graff Zivin and Neidell (2012)

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- 11 output and substitution effects. With these potentially competing forces, under standard neoclassical theory estimation of net employment ef fects is possible with empirical study specific to the regulated firms and firms in the environmental protection sector and other relevant sectors when data and methods of sufficient detail and quality are available. Finally, economic theory suggests that labor supply effects are also possible. In the next section, we discuss the available empirical literature.

5.2.2 Current State of Knowledge Based on the Peer

- Reviewed Literature

In the labor economics literature, an extensive body of peer

- reviewed empirical wor k analyz es various aspects of labor demand, relying on the above theoretical framework. 66 This work focuses p rimarily on the effects of employment policies , for example, labor taxes and minimum wage. 67 In contrast, the peer

- reviewed empirical literature spec ifically estimating employment effects of environmental regulations is very limited

. In this section, w e present an
overview of the latter. As discussed in the preceding section on theory, determining the direction of employment effects in regulated indust ries is challenging because of the complexity of the output and substitution effects. Complying with a new or more stringent regulation may require additional inputs, including labor, and may alter the relative proportions of labor and capital used by regulated firms (and firms in other relevant industries) in their production processes.

S everal empirical studies

, including Berman and Bui (2001) and Morgenstern et al

. (2002)

, suggest that net employment impacts may be zero or slightly positive but small even in the regulated sector. Other research suggests that more highly regulated counties may generate fewer jobs than less regulated ones (Greenstone , 20 02 ; Walker

, 20 11 ). However, because t hese
latter studies compare more regulated to less regulated counties , they overstate the net national impact of regulation to the extent that regulation causes plants to locate in one area of the country rath er than another. List et al . (2003) found some evidence that this type of geographic relocation may be occurring. Overall , the peer

- reviewed literature does not contain evidence that environmental regulation has a large impact on net employment (either negative or positive) in the long run across the whole economy.

Environmental regulations seem likely to affect the environmental protection sector earlier than the regulated industry. Rules are usually announced well in advance of their effective
dates and then typically provide a period of time for firms to invest in technolog ies and process changes to meet the new requirements. When a regulation is promulgated, the initial response of

66 Again, see Hamermesh (1993) for a detailed treatment.

67 See Ehrenberg and Smith (2000)

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- 12 firms is often to order pollution c ontrol equipment and services to enable compl iance when the regulation becomes effective. This can produce a short

- term increase in labor demand for specialized workers within the environmental protection sector , particularly workers involved in
the design , construction, testing, installation, and operation of the new pollution control equipment required by the regulation (see Schmalansee and Stavins, 2011 ; Bezdek, Wendling, and Diperna, 2008 ). Estimates of short

- term increases in demand for specialized labor within the environmental protection sector have been prepared for several EPA regulations in the past, including the Mercury and Air Toxics Standards (MATS) (U.S. EPA, 201 1b ).

5.2.3 Regulated Sector
Determining the direction of net employment effects of regulation on industry is challenging. Two papers that present a formal theoretic model of the underlying profit

maximizing/cost

- minimizing problem of the firm are Berman and Bui (2001) and Morgenstern, Pizer, and Shih (2002 ) mentioned above.

Berman and Bui (2001) developed an innovative approach to esti mate the effect on employment of environmental regulations in California. Their model empirically examines how an increase in local air quality regulation affects manufacturing employment in the South Coast Air Quality Management District (SCAQMD), which i ncorporates Los Angeles and its suburbs. During the time frame of their study, 1979 to 1992, the SCAQMD enacted some of the country ’ s most stringent air quality regulations. Using SCAQMD ’ s local air quality regulations, Berman
and Bui identif ied the effect of environmental regulations on net employment in the regulated
industries. 68 In particular, they compare d changes in employment in affected plants to those in other plants in the same 4

- digit Standard Industrial Classification ( SIC ) industries but in regions not subject to the local regulations. 69 The authors f ou nd that “ while regulations do impose large costs, they have a limited effect on employment ” (Berman and Bui, 2001, p. 269 ). Their
conclusion is that l ocal air quality regulation “ probably increased labor demand slightly ” but that

“ the employment effects of both compliance and increased stringency are fairly precisely
estimated zeros , even when exit and dissuaded entry effects are included ” (Berman and B ui, 2001, p. 269 ). 70 In their view, the limited effects likely arose because 1) the regulations applied disproportionately to capital

- intensive plants with relatively little employment, 2) the plants sold

68 Note, like Morgenstern, Pizer, and Shih (2002) , this study does not estimate the number of jobs created in the environmental protection sector.

69 Berman and Bui include over 40 4

- digit SIC industries in their sample.
70 Including the employment effect of exiting plants and plants dissuaded from opening will increase the estimated impact of regulation on employment. This employment effect is not included in Morgenstern et al. (2002).***E.O. 12866 Review

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- 13 to local market s where competitors were subject to the same regulations (so that sales were relatively unaffected), and 3) abatement inputs served as complements to employment.

Morgenstern, Pizer, and Shih (2002) developed a s imilar structural approach to Berman
and Bui ’ s, but their empirical application use d pollution abatement expenditures from 1979 to 1991 at the plant level, including air, water, and solid waste, to estimate net employment effects in four highly regulated s ectors (pulp and paper, plastics, steel, and petroleum refining). Thus, in contrast to Berman and Bui (2001) , this study identifie d employment effects by examining differences in abatement expenditures rather than geographical differences in stringency. They conclude that increased abatement expenditures generally have not caused a significant change in net employment in those sectors.

5.2.4 Environmental Protection Sector
The long

- term effects of a regulation on the environmental protection sector

, which provides goods and services that help protect the environment to the regulated sector

, are difficult to assess. Employment in the industry supplying pollution control equipment or services is likely to increase with the increased d emand from the regulated industry for increased pollution control. 71

A report by the U.S. International Trade Commission (2013) shows that domestic environmental services revenues grew by 41% between 2000 and 2010. According to U.S. Department of Commerce (2010) data, by 2008, there were 119,000 environmental technology (ET) firms generating approximately $300 billion in revenues domestically, producing $43.8
billi on in exports, and supporting nearly 1.7 million jobs in the United States . Air pollution control accounted for 18% of the domestic ET market and 16% of exports. Small and medium

size companies represent 99% of private ET firms, producing 20% of total reve nue (OEEI,
2010 )

.
5.2.5 Labor Supply Impacts

As described above, t he small empirical literature on employment effects of environmental regulations focuses primarily on labor demand impacts. However, t here is a nascent literature focusing on regulation

- induced effects on labor supply, though this literature remains very limited because of empirical challenges. This new research uses innovative
methods and new data and indicates that there may be observable impacts of environmental regulation o n labor supply, even at pollution levels below mandated regulatory thresholds. Many

71 See Bezdek, Wendling, and Diperna (2008) , f or example, and U.S. Department of Commerce (2010)

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- 14 researchers have found that work

- loss days and sick days, as well as mortality, are reduced when air pollution is reduced (EPA, 2011 a ). EPA ’ s study of the benefits and costs of implementing the clean air regulations used these studies to predict how increased labor availability would increase the labor supply and improve productivity and t he economy (EPA, 2011 a).Another literature estimates how worker productivity improves at the work site when pollution is reduced. Graff Zivin and Neidell ( 2013 ) review ed this literature, focusing on how health and hum an capital may
be affected by environmental quality, particularly air pollution. In previous research

, Graff Zivin and Neidell (2012) use d detailed worker

- level productivity data from 2009 and 2010, pair ed with
local ozone air quality monitoring data for one large California farm growing multiple crops

, with a piece

- rate payment structure. Their quasi

- experimental structure identifie d a n effect of daily variation in monitored ozone levels on productivity. They f ou nd “ t hat ozone levels well below federal air quality standards have a significant impact on productivity: a 10 parts per billion (ppb) decrease in ozone concentrations increases worker productivity by 5.5 percent. ” (Graff Zivin and Neidell, 2012, p. 3654 ). Such studies are a compelling start to exploring this new area of research, considering the benefits of improved air quality on productivity, alongside the existing literature exploring the labor demand effects of environmental regulations.

5.2.6 Macroeconomic Net Employment Effects
The preceding sections have outlined the challenges associated with estimating net employment effects in the regulated sector and in the environmental protection sector and labor supply impacts. These challenges make it very difficult to accurately produce net employment estimates for the whole economy that would appropriately capture the way in which costs, compliance spending, and environmental benefits propagate through the macro

- economy. Quantitative estimates are further complicated by the fact that ma croeconomic models often have very little sectoral detail and usually assume that the economy is at full employment. EPA is currently in the process of seeking input from an independent expert panel on modeling

economy

- wide impacts, including employment ef fects.

5.2.7 Information Specific to this Regulation

In 2011, t he ASM reported that 218 establishments (174 in NAICS 327121 and 44 in NAICS 327123) employed 8,000 people with a total annual payroll of about $300 million (U.S. Census Bureau, 2013a, b ). Approximately 12 million production labor hours were used to produce BSCP in 2011.

For this analysis, EPA quantified a subset of possible types of employment e ffects
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- 15 ■ additional labor requirements (full

- time equivalents [FTEs]) associated with meeting the new regulation

■ e mpl oyment effect of facilities that may exit the BSCP industry

As shown in Table 5

- 2, EPA estimates that the regulation will require an additional
1 8 1,000 labor hours per year to operate control devices

. This is equivalent to about 87 additional FTEs. The total estimated cost of these additional labor requirements to operate control devices
is $ 4

. 24 million per year. For Option 2, the recordkeeping an d reporting labor hours are approximately 49 ,000 hours (see section 6.3) , or 23 additional FTE.

Table 5

- 2

. Estimated Additional Labor Requirements

Total Annual Labor Cost ($ million) Required to Operate Control Devices Total Annual Labor Hours Required to Operate Control Devices Option 1 $ 4.13 1 76,000 Option 2 Final $ 4.24 181,000 a Option 3 8.12 347,000

a Excludes record keeping and reporting labor hours (49 ,000) (see section 6.3).

In Section 5.3, EPA estimates that the regulation may lead to two to four affected facilities exiting the BSCP industry. According the U.S. Census Bureau ( 2013 b), the average number of employees per facility in 2011 was 37 (8,000/218 = 37). As a result, we estimate 74 to
148 employees may need to retrain or relocate in anti cipation of the new requirements or require time to search for new jobs.

5.2.8 Conclusion
Although EPA has quantified two types of employment effects in this RIA, deriving
estimates of how this regulation will affect net employment is a difficult task, requiring consideration of labor demand in both the regulated and environmental protection sectors.
E conomic theory predicts that the total effect of an environmental regulation on labor demand in regulated sectors is not necessarily positive or negative. Peer

- reviewed econometric studies that use a structural approach, applicable to overall net effects in the regulated sectors, converge on the finding that such effects, whether positive or negative, have been small and have not affected employment in the n ational economy in a significant way. Effects on labor demand in the environmental protection sector seem likely to be positive. Finally, new evidence suggests that environmental regulation may improve labor supply and productivity.***E.O. 12866 Review

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- 16 5.3 Impacts on Small Entit ies
As mentioned above, EPA was particularly concerned about the final rule ’ s potential impacts to small entities, because 36 of 44 firms owning BSCP facilities have fewer than 750 employees and thus meet the Small Business Administration ’ s (SBA ’ s) criteri on for a small business in this industry. EPA thus conducted a screening analysis of the potential impacts by computing the ratio of control costs to firm sales revenues (i.e., a sales test). Based on the results of the screening analysis, EPA concluded th at it is not able to certify that the rule will not have a Significant Impact on a Substantial Number of Small Entities (SISNOSE). As a result, EPA initiated a Small Business Advisory Review panel and undertook an Initial Regulatory Flexibility Analysis (I RFA).

5.3.1 Small Business Impact Screening Analysis

As discussed in Section 2, EPA has identified 44 ultimate parent companies with
facilities that will need new or modified control devices to meet new emission standards. Affected parent companies fall under t he Clay Building Material and Refractories Manufacturing (NAICS 327120 ) industry and the SBA (2013 ) defines a small business as having fewer than 750 employees. There are 36 parent companies that are small busine sses.

EPA assessed how the re gulatory program may influence the profitability of ultimate parent companies by comparing pollution control costs to total sales (i.e., a “ sales ” test or cost

to

- sales ratios [CSR] ). To do this, we divided an ultimate parent c ompany ’ s (i) total annualized compliance costs by its reported revenue:

Sales Test i = TTTTTTTTTT AAAAAAAA AAAAAAAA CC CCCC CC CC CC ii TTTTTTTTTT RR RR ii (5.1)

As shown in Table 5

- 3, 40 of the 44 ultimate parent companies had sales data available that enabled EPA to compute a sales test. The table shows that 58 % of all businesses and 59 % of small businesses affected by the final standards have CSRs of under 1%.

EPA estimated the range o f the number of ultimate parent companies that may close rather than comply with the regulation. The lower and upper bounds of the range were
determined as follows:

■ Lower bound: All ultimate parent companies with CSR > 10%.

■ Upper bound: All ultimate parent companies with CSR > 10%, 50% of ultimate parent companies with CSRs between 5% and 10%, and 25% of ultimate parent companies with CSRs between 3% and 5%

.

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### Table 5

- 3. Small Business Impact Screening Assessment Results and Closure Estimates

Capital Cost (Million $) Annual Cost (Million $) Ultimate Parent Companies with Cost

- to

- Sales Ratios (CSRs) a

Estimated b Closures Estimated Number of Facilities

Closed Less than 1% 1% to 3% 3% to 5% 5% to 10% Greater than 10%
All Businesses (n=40) Option 1 $64 $27 53 % 30 % 10 % 5 % 3 % 3

– 8 1

– 3 Option 2 Final $65 $27 58 % 28 % 3 % 8 % 5 % 5

– 9 2

– 4 Option 3 $131 $49 35 % 15 % 13 % 15 % 23 % 23

– 33 9

– 13
Small Businesses (n=32) Option 1 $16 $7 53 % 31 % 9 % 3 % 3 % 3

– 7 1

– 2 Option 2 Final Rule $14 $7 59 % 28 % 3 % 3 % 6 % 6

– 9 2

– 3

Option 3 $50 $19 34 % 9 % 16 % 13 % 28 % 28

– 38 9

– 12

a The screening assessment was conducted for 40 of the 44 ultimate parent companies with annual sales data available

. For small businesses, 32 of the 36 small

entities had annual sales data available.

b EPA estimated a lo wer and upper bound as follows: Lower bound: All ultimate parent companies with CSR > 10%.; Upper bound: All ultimate parent

companies with CS R > 10%, 50 % of ultimate parent companies with CSRs between 5% and 10%, and 25 % of ultimate parent companies with CSRs between 3% and 5%.***E.O. 12866 Review

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- 18 Under the final standards, EPA estimated that two to four brick manufacturing facilities

are at significant risk of closure. Under the Option 1 standards, one to three brick manufacturing facilities are at significant risk of closure, and under the Option 3 standards, nine to thirteen brick manufacturing facilities are at significant risk of closure.

As shown in Table 5

- 3, 32 of the 36 small ultimate parent companies had sales data available that enabled EPA to compute a sales test. Under the final standard s, EPA estimated that

two to three small brick manufacturing facilities are at significant risk of closure. Under the Option 1 standards, one to two small brick manufacturing facilities , and under Option 3 standards, nine to t welve small brick manufacturin g facilities are at significant risk of closure.
All of the facilities at risk of closure were one

- facility companies.

EPA has been informed that firms may have difficulty obtaining longer

- term financing needed to buy the control equipment and make process changes needed to comply with the final
standards. F irms may not have cash on hand or the ability to convert assets into cash in order to make these purchases; as a result, firms would have to consider other long

- term financing options. Affected firms are less likely to be publicly traded and thus would be more likely to consider debt versus equity options. The additional liabilities can put firms at additional risk of
closure if market conditions do not improve during the period when the rule is adopted. In addition, if creditors are concerned about existing or future market conditions in the brick industry, they may be less willing to enter a loan contract or may require higher rates of interest
than the 7 % interest rate used to annualize the capital cost s associated with the rule. EPA estimates of the range of the number of ultimate parent companies that may close rather than comply with the regulation may be an underestimate because of the difficulty in obtaining financing at a 7 % interest rate. The esti mates might be an overestimate if the industry has become more robust by 2018 when the control must be in place. The closure estimate did not include net effects on revenue due to price increases or reductions in sales attributable to the regulation.

5.3.2 Final Regulatory Flexibility Analysis
Pursuant to sections 603 and 609(b) of the RFA, the EPA prepared an initial regulatory flexibility analysis (IRFA) for the proposed rule and convened a Small Business Advocacy Review (SBAR) Panel to obtain advice and recom mendations from small entity representatives that potentially would be subject to the rule ’ s requirements. Summaries of the IRFA and Panel
recommendations are included at 79 FR 75669

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- 19 As required by section 604 of the RFA, the EPA prepared a final re gulatory flexibility analysis (FRFA) for this action. The FRFA addresses the issues raised by public comments on the IRFA for the proposed rule. The complete FRFA is included in Section 5 of “ Regulatory Impact Analysis: Final Brick and Structural Clay Prod ucts NESHAP, ” available for review in the docket (Docket ID No. EPA

- HQ

- OAR

- 2013

- 0291), and is summarized here.

5.3.2.1 Need for the Rule
The EPA is required under CAA section 112(d) to establish emission standards for each category or subcategory of major and are a sources of HAP s listed for regulation in Section 112(b). These standards are applicable to new or existing sources of HAP s and require the maximum degree of emission reduction. In the Administrator ’ s judgment, the pollutants emitted
from BSCP manufacturi ng facilities cause or contribute significantly to air pollution that may reasonably be anticipated to endanger public health. Consequently, a NESHAP for the BSCP
source category is being finalized.

5.3.2.2 Objectives and Legal Basis for the Rule

Section 112(d) of the CAA requires the EPA to set emissions standards for HAP s emitted by major stationary sources based on the performance of the MACT. The MACT standards for existing sources must be at least as stringent as the average emissions limitation achieved by th e best performing 12 % of existing sources (for which the Administrator has emissions information) or the best performing five sources for source categories with fewer than 30 sources (CAA section 112(d)(3)(A) and (B)). For new sources, MACT standards must be at least as stringent as the control level achieved in practice by the best controlled similar source (CAA section 112(d)(3)). The EPA also must consider more stringent “ beyond

- the

- floor ” control options. When considering beyond

- the

- floor options, the E PA must consider not only the maximum degree of reduction in emissions of HAP s but must also take into account costs,

energy , and non

- air environmental impacts when doing so. This rule is being proposed to comply with CAA section 112(d).

5.3.2.3 Significant Issues Raised
The EPA received comments on the proposed standards and requests for comment that
were included based on the SBAR Panel recommendations. See sections V and VI of this rule’s preamble and “ National Emission Standards for Hazardous Air Pollutants for Brick and Structural Clay Products Manufacturing: Background Information for Final Rule

- Summary of Public Comments and Responses ” in Docket ID No. EPA

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- 0291 for more detailed comment summaries and responses.***E.O. 12866 Review

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- 20 Work practices for dioxin/furan: One commenter stated that work practices for dioxin/furan emissions from BSCP tunnel kilns are not lawful under the CAA, and even if they were, the work practices proposed are not sufficient to minimize dioxin/furan emissions. Other commenters supported th e proposed work practices for dioxin/furan.

Response: The EPA is finalizing work practices for dioxin/furan as proposed.

Work practices for Hg and other metals: Several commenters responded to the EPA ’ s request for comment on work practices for Hg and non

- Hg HAP metals. Numerous commenters stated that the EPA should finalize work practices instead of numeric limits and provided support for their assertion that the numeric limits are technically and economically impracticable to
enforce. Commenters also note d that the emissions reduced by these numeric standards are not justified by the high cost that would be incurred to meet the standards.

Response: Emissions of Hg and non

- Hg HAP metals were detected using standard EPA test methods; therefore, the Hg and no n

- Hg HAP metals data sets do not meet the criteria for setting work practice standards under CAA section 112(h). The EPA is finalizing numeric standards for Hg and non

- Hg HAP metals under CAA section rather than work practices. The
final numeric standards are revised from proposal to account for new data from the industry (including data on the Hg content of raw materials), removal of test data found not to meet the requirements of the applicable data, and changes in the EPA ’ s approach to selecting the MACT floor pools (see section V.A of this rule’s preamble for additional details).

Health

- based standard for acid gases: Several commenters asserted that the EPA may not legally set CAA section 112(d)(4) health

- based standards for acid gases for BSCP facilitie s. Other commenters supported the EPA ’ s decision to propose health

- based standards for acid gases but noted that the EPA ’ s approach was overly conservative and requested that the EPA consider setting multiple limits based on site characteristics.

Response: The EPA is finalizing the health

- based standards for acid gases as proposed.
The EPA ’ s response to the legal arguments made against health

- based standards is presented in
section V.B of this rule’s preamble. The EPA is not changing the numeric limit from proposal,
because the proposed limit provides low potential for both chronic and acute health effects.

Size subcategories for MACT floors: Several commenters requested that the EPA subcategorize by size for the non

- Hg HAP metal/PM MACT floor limits, as was proposed for Hg.***E.O. 12866 Review

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- 21 Response: As part of recalculating the MACT floor limits based on the final data set, the EPA is finalizing separate limits for small and large kilns for non

- Hg HAP metals/PM as well as Hg. The EPA is also finalizing limits in three diffe rent formats for both pollutants to provide additional flexibility for small tunnel kilns and tunnel kilns with a low metals content in the PM
emissions.

Sawdust dryers: Several commenters requested that the EPA finalize a subcategory of
sawdust

- fired kiln s venting to sawdust dryers. Commenters provided general descriptions of how the operation of these kilns is different than tunnel kilns and stated that there are only two operating that would be subject to the BSCP NESHAP.

Response: Although one commenter noted that stack testing of a sawdust dryer is being considered, commenters did not provide test data to demonstrate that emissions from sawdust dryers are different than other tunnel kilns. Therefore, the EPA is not finalizing a subcategory of
sawdust

- fi red kilns venting to sawdust dryers.

Periods of startup and shutdown: One commenter stated that work practices for periods of startup and shutdown of BSCP tunnel kilns are not lawful under the CAA. Other commenters supported the proposal to provide work pr actices for periods of startup and shutdown but suggested improvements to the standards to make them feasible for all tunnel kilns.

Response: The EPA evaluated the comments and is finalizing work practice standards for periods of startup and shutdown that reflect best practices for minimizing emissions during these periods (see section V.C of this rule’s preamble for additional information).

MACT floor pool: Several commenters supported the EPA ’ s proposal to calculate MACT
floor standards for PM based on the top 12 % of the kilns in the industry (i.e., the best

- performing
sources with a n FF

- based APCD). One commenter asserted that the EPA ’ s proposal is unlawful and the EPA must consider other factors than the APCD type when setting MACT standards.

Response: The EPA reviewed all the data used for the MACT floor for PM as a surrogate
for non

- Hg HAP metals and found that some of the test data did not meet the requirements of EPA Method 5. When these data were removed, the EPA could no longer confirm that the da ta available to the agency represented all the best

- performing sources. Therefore, the final PM and

non

- Hg HAP metals are based on the top 12 % of sources for which we had test data, regardless of APCD type (see section V.A of this rule’s preamble for addit ional details).***E.O. 12866 Review

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- 22 5.3.2.4 Small Business Administration Comments

The U.S. Small Business Administration ’ s Office of Advocacy supported the EPA ’ s proposals to set work practice standards and health

- based emission standards in all instances allowed by statute and sugg ested other areas of improvement. The comments on areas of improvement and the EPA ’ s responses are summarized below:

Hg standards: The EPA should pursue subcategorization by input (raw material) type, delaying promulgation of a n Hg standard to gather more information if needed. Standards may need to be combined with a significantly longer averaging time to allow for continuous compliance.

Response: Following proposal, the EPA received additional information on the Hg
content of raw materials from facilities in the BSCP industry. This information did not provide the EPA with the information needed to establish subcategories based on the class or type of raw materials. However, it did allow the EPA to finalize Hg standards that account for the variability
of H g content in raw materials. As an initial point, it is doubtful that EPA had the option of delaying the promulgation of an Hg standard. Under CAA 112(e), EPA was scheduled to complete standards for all source categories by 2000. EPA’s 2003 Brick MACT rul e was vacated, and that vacatur re

- created EPA’s obligation to set standards for the Brick source category. Sierra Club v. EPA, 850 F.Supp.2d 300, 303

- 304 (D.D.C. 2012). Under the consent decree in that case, as amended in August 2014, EPA was obligated t o sign a notice of final rulemaking to set standards for the Brick source category by September 24, 2015.

In any event, delay is not warranted. Following proposal, the EPA received additional information on the Hg content of raw materials from facili ties in the BSCP industry. This information did not provide the EPA with the information needed to establish subcategories based on the class or type of raw materials. However, EPA has concluded that it has sufficient
information to allow it to finalize Hg standards that account for the variability of Hg content in raw materials. Thus, EPA’s conclusion is that there is no need to delay promulgation of the Hg standards in order to gather more information.

Economic analysis: The economic impact of the propose d rule on small entities is significantly underestimated. Specifically, the EPA should not annualize costs at 7 % over 20 years because that does not reflect the financing options available to small entities, the EPA underestimated the cost for a facility t o become a synthetic area source, and the EPA has underestimated the cost to comply with the Hg standards given the limited information the agency has on the performance of Hg controls in this industry.***E.O. 12866 Review

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- 23 Response: EPA standard engineering cost practice is t o annualize over the expected life of the control equipment at 7%. EPA does not have the data available to model the way a firm pays for a control device because each firm has a different set of potential options for financing including debt financing, equ ity financing, and financing through re t ained earnings. EPA acknowledges that some firms may not be able to borrow the money and some may close. EPA's closure analysis is quite uncertain but we do not have the detailed firm specific information

necessary to refine the analysis. The EPA agrees that the costs to become a synthetic area source at proposal were underestimated, and the final rule impacts include testing costs for all facilities,
because potential synthetic area sources would have to demonstrate that their emissions qualify them to apply for synthetic area status. Finally, the EPA must use the best information available to the agency to estimate the impact of the standards on all entities. The final Hg standards incorporate variability in the Hg content of raw materials, which is expected to ease the burdens
on some small entities.

5.3.2.5 Affected Small Entities
Of 44 parent companies owning BSCP facilities, 36 parent companies are small businesses. The EPA computed the ratio of estimated compliance cost s to company sales (cost

to

- sales ratio) to measure the magnitude of potential impacts on small companies. Under the final standards, the EPA estimated that two to three small BSCP manufacturing facilities are at significant risk of closure.

5.3.2.6 Reporting, Rec ordkeeping, and Other Compliance Requirements
Respondents would be required to provide one

- time and periodic notifications, including initial notification, notification of performance tests, and notification of compliance status. Respondents would also be required to submit semiannual reports documenting compliance with the rule and detailing any compliance issues, and they would be required to submit the results of performance tests to the EPA ’ s ERT. Respondents would be required to keep documentation

supp orting information included in these notifications and reports, as well as records of the operation and maintenance of affected sources and APCD at the facility.

5.3.2.7 Significant Alternatives
The EPA considered three major options for this final rule; see “ Regu latory Impact Analysis: Final Brick and Structural Clay Products NESHAP, ” in Docket ID No. EPA

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- 0291), for more information about the alternatives. Finalizing the proposed changes without revision is expected to have similar cost and emission re duction impacts to the standards the EPA is finalizing, with a similar number of closures (one to two small BSCP manufacturing***E.O. 12866 Review

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- 24 facilities rather than two to three). However, for the various legal and technical reasons outlined
in this rule’s preamble and “ National Emission Standards for Hazardous Air Pollutants for Brick and Structural Clay Products Manufacturing: Background Information for Final Rule

- Summary of Public Comments and Responses ” in Docket ID No. EPA

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- 0291, the EPA
determined that the PM/non

- Hg HAP metals and Hg standards should not be finalized as proposed. The other alternative considered included the same standards for acid gases and Hg that are being finalized but only provided one set of limits PM/non

- Hg HAP metals (i.e., did n ot provide separate sets of limits for small and large tunnel kilns). This alternative is expected to have significantly higher cost impacts than the standards the EPA is finalizing, along with a significantly higher number of closures (five to ten small B SCP manufacturing facilities rather than two to three). Therefore, the EPA determined that it is necessary to exercise its discretion to subcategorize by kiln size to minimize the significant economic impact on small entities.

In addition, the EPA is prepa ring a Small Entity Compliance Guide to help small entities comply with this rule. The guide will be available on the World Wide Web approximately 1 year after promulgation of the rule.

5.4 References Arrow, K.J. , M.L. Cropper, G.C. Eads, R.W. Hahn, L.B. Lave, R.G. Noll, P.R. Portney, M. Russell, R. Schmalensee, V.K. Smith, and R.N. Stavins. 1996. “ Benefit

- Cost Analysis in Environmental, Health, and Safety Regulation

- A Statement of Principles. ” Ameri can Enterprise Institute, The Annapolis Center, and Resources for the Future. AEI Press. http://www.hks.harvard.edu/fs/rstavins/Papers /Benefit Cost Analysis in Environmental.AEI.1996.pdf

. Berman, E. , and L.T. M. Bui. 2001. “ Environmental Regulation and Labor Demand: Evidence from the South Coast Air Basin. ” Journal of Public Economics 79(2): 265

- 295.

Bezdek, R.H., R. M. Wendling, and P. Diperna. 2008. “ Environmental Protection, the Economy, and Jobs: National and Regional Analyses. ” Journal of Environmental Management 86(1): 63

- 79.

Brown, R.S., and L.R. Christensen. 1981. “ Estimating the Elasticities of Substitution i n a Model of Partial Static equilibrium: An Application to U.S. Agriculture 1947 to 1974

. ” In Berndt, E.R., Field, B.C. (Eds.), Modeling and Measuring Natural Resource Substitution

. Ehrenberg, R.G., and R.S. Smith. 2000. “ Modern Labor Economics: Theory and Public Policy. ” Addison Wesley Longman, Inc., Executive Order 13563. January 21, 2011. “ Improving Regulation and Regulatory Review. Section 1. General Principles of Regulation. ” Federal Register 76(14): 3821

- 3823.***E.O. 12866 Review

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- 25 Graff Zivin, J

. , and M

. Neidell. 2012. “ The Impact of Pollution on Worker Productivity. ” American Economic Review 102(7) : 3652

- 73.

Graff Zivin, J

. , and M . Neidell. 2013

. “ Environment, Health, and Human Capital. ” Journal of Economic Literature 1 ( 3 ): 689

- 730.

Greenstone, M. 2002. “ The Impacts of Environmental Regulations on Industrial Activity: Evidence from the 1970 and 1977 Clean Air Act Amendments and the Census of Manufactures. ” Journal of Political Economy 110(6): 1175

- 1219.

Hamermesh, D.S. 1993. “ Labor Demand. ” Princeton University Press, P rinceton, NJ.

Internal Revenue Service. SOI Tax Stats

— Corporation Tax Statistics. Last updated April 2014. http://www.irs.gov/uac/SOI

- Tax

- Stats

- Corporation

- Tax

- Statistics

. Lay ard, P.R.G., and A.A. Walters. 1978. “ Microeconomic Theory. ” McGraw

- Hill, Inc.

List, J.A., D.L. Millimet, P. G. Fred riksson, and W. W. McHone. 2003. “ Effects of Environmental Regulations on Manufacturing Plant Births: Evidence from a Propensity Score Matchi ng Estimator. ” The Review of Economics and Statistics 85(4): 944

- 952.

Morgenstern, R.D., W. A. Pizer, and J

- S. Shih. 2002. “ Jobs Versus the Environment: An Industry

- Level Perspective. ” Journal of Environmental Economics and Management 43(3): 412

- 436.

Schm alansee, R., and R. Stavins. 2011. “ A Guide to Economic and Policy Analysis for the Transport Rule. ” White Paper. Boston, MA: Exelon Corp.

Smith, K. 2012. “ Reflections

— In Search of Crosswalks between Macroeconomics and Environmental Economics. ” Review of Environmental Economics and Policy 6(2) : 298

- 317.

U.S. Department of Commerce, International Trade Administration. April 2010

. “ Environmental Industries Fact Sheet, using 2008 data from Environmental Business International, Inc. ” http://web.ita.doc.gov/ete/eteinfo.nsf/068f3801d047f26e85256883006ffa54/4878b7e2fc0 8ac6d85256883006c452c?OpenDocument

.
U.S. Environmental Protection Agency. April 2011a. “ The Benefits and Costs of the Clean Air Act from 1990 to 2020 Final Report

– Rev. A. ” Washington, DC: U.S. Environmental Protection Agency, Office of Air and Radiation. http://www.epa.gov/air/sect812/feb11/fullreport_rev_a.pdf

. U.S. Environmental Protection Agency. December 2011b. “ Regulatory Impact Analysis for the Mercury and Air Toxics Standards (MATS). ” Washington, DC: U.S. Environment al Protection Agency

. http://www.epa.gov/ttn/ecas/regdata/RIAs/matsriafinal.pdf

.***E.O. 12866 Review

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- 26 U.S. International Trade Commission. March 2013. Environmental and Related Services. Publication No. 4389, Investigation No. 332

- 533. http://www.usitc.gov/publications/332/pub4389.pdf

. Walker, R. 2011. “ Environmental Regulation and Labor Reallocation. ” American Economic Review: Papers and Proceedings 101(2).***E.O. 12866 Review

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- 1 SECTION 6
STATUTORY AND EXECUT IVE ORDER REVIEWS

6.1 Synopsis
This chapter summarizes the Statutory and Executive Order (EO) impact analyses
relevant for the final NESHAP for Bricks and Structural Clay Products . For each EO and Statutory requirement

, we describe both the requirements and the way in which our analysis addresses these requirements.

6.2 Executive Order 12866: Regulatory Planning and Review and Executive Order 13563: Improving Regulation and Regulatory Review
This action is an economically significant regulatory action that was submitted to the
Office of Mana gement and Budget (OMB) for review. Any changes made in response to OMB recommendations have been documented in the dockets for this action. The EPA prepared an analysis of the potential costs and benefits associated with this action. This analysis is cont ained
in “ Regulatory Impact Analysis: Final Brick and Structural Clay Products NESHAP. ” A copy of the analysis is available in the docket for the BSCP rule (Docket ID No. EPA

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- 0291)

, and the analysis is briefly summarized here.

The EPA ’ s study e stimates that affected BSCP facilities will incur total annualized costs of $24.6 million (2011 dollars) under the BSCP rule, including costs of emission controls, testing and monitoring, along with recordkeeping and reporting costs for facilities that hav e testing and monitoring. The EPA gathered information on firm sales and overall industry profitability for firms owning affected BSCP facilities. The EPA estimated that two to four BSCP manufacturing facilities are at significant risk of closure under the final standards.

The EPA also conducted an assessment of the benefits of the final rule, as described in
section VII of this rule’s preamble. These estimates reflect the monetized human health benefits of reducing cases of morbidity and premature mortali ty among populations exposed to PM 2.5 reduced by this rule. Data, resource

, and methodological limitations prevented the EPA from monetizing the benefits from several important benefit categories, including benefits from reducing exposure to 375 tons of HA P s each year for the promulgated standards, as well as ecosystem effects and visibility impairment. In addition to reducing emissions of PM precursors
such as SO 2 , this rule will reduce several non

- Hg HAP metals emissions (i.e., arsenic, cadmium, chromium, lead, manganese, nickel, and selenium) each year. The EPA estimates the total
monetized co

- benefits to be $83 million to $190 million (2011 dollars) at a 3 % discount rate and***E.O. 12866 Review

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- 2 $75 million to $170 million (2011 dollars) at a 7 % discount rate on a yearly ave rage in 2018 for the promulgated standards.

Based on the EPA ’ s examination of costs and benefits of the final BSCP rule, the EPA
believes that the benefits of the BSCP rule will exceed the costs.

6.3 Paperwork Reduction Act (PRA)

The information collection re quirements in the BSCP rule have been submitted for approval to OMB under the PRA, 44 U.S.C. 3501 et seq. The Information Collection Request (ICR) document that the EPA prepared for the BSCP Manufacturing NESHAP has been assigned
EPA ICR number 2509.01. Yo u can find copies of the ICR in the docket for the BSCP rule, and they are briefly summarized here. The information collection requirements are not enforceable until OMB approves them.

The information collected from respondents will be used by EPA enforcem ent personnel to: (1) identify new, modified, reconstructed and existing sources subject to the standards; (2) ensure that MACT is being properly applied; and (3) ensure that the emission control devices are being properly operated and maintained on a cont inuous basis. In addition, records and reports are necessary to enable the EPA to identify facilities that may not be in compliance with the standards. Based on the reported information, the EPA can decide which facilities should be inspected and what reco rds or processes should be inspected at these facilities. The records that facilities maintain will indicate to the EPA whether the owners or operators are in compliance with the emission limitations (including emission limits, operating limits) and work p ractice standards. Much of the information the EPA would need to determine compliance would be recorded and retained onsite at the facility. Such information would be reviewed by enforcement personnel during an inspection and would not need to be routinely reported to the EPA.

All information submitted to the EPA for which a claim of confidentiality is made will be safeguarded according to EPA policies set forth in title 40, chapter 1, part 2, subpart B

- Confidentiality of Business Information. (See 40 CFR 2; 41 FR 36902, September 1, 1976; amended by 43 FR 39999, September 28, 1978; 43 FR 42251, September 28, 1978; and 44 FR 17674, March 23, 1979.)

Potential respondents to the information collection requirements in the BSCP rule are owners or operators of new and existing sources at BSCP manufacturing facilities. A BSCP facility manufactures brick, including face brick, structural brick, brick pavers, or other brick and/or structural clay products including clay pipe; roof tile; extruded floor and wall tile ; or other***E.O. 12866 Review

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- 3 extruded, dimensional clay products. The BSCP facilities typically form, dry and fire bricks and shapes that are composed primarily of clay and shale. Kilns are used to fire BSCP. The rule applies to all new and existing tunnel and periodic kiln s at BSCP facilities.

The information requirements are based on notification, recordkeeping and reporting requirements in the NESHAP General Provisions (40 CFR part 63, subpart A), which are mandatory for all operators subject to national emissions standar ds. These recordkeeping and reporting requirements are specifically authorized by CAA section 114 (42 U.S.C. 7414). All information submitted to the EPA pursuant to the recordkeeping and reporting requirements for which a claim of confidentiality is made i s safeguarded according to the EPA policies set forth in 40 CFR part 2, subpart B.

In addition to the notification, recordkeeping and reporting requirements in the NESHAP General Provisions, the final rule includes paperwork requirements associated with in itial and 5

- year repeat testing for selected process equipment, electronic reporting of performance test results, parameter monitoring, preparation of an OM&M plan, maintenance and inspection of process and control equipment, compliance with work practice standards and periods of
malfunction.

Collection of data will begin after the effective date of the final BSCP manufacturing NESHAP. The compliance date for existing sources is 3 years after the effective date. The compliance date for new or reconstructed sources is the effective date if the source startup date is before the effective date, or upon startup if the startup date is on or after the effective date. The schedule for notifications and reports required by the rule is summarized below.

For BSCP faci lities with existing affected sources, the initial notification stating that the facility is subject to the rule must be submitted no later than 120 calendar days after the effective
date of the rule. Facilities with new or reconstructed affected sources f or which startup occurs on or after the effective date must submit the initial notification no later than 120 calendar days after the source becomes subject to the rule (although we are projecting no new affected sources in the short term). Facilities may choose to submit a request for a routine control device maintenance exemption 30 calendar days prior to the compliance date. Facilities required to conduct a performance test must submit a notification of intent to conduct a performance test at least 60

ca lendar days before the performance test is scheduled to begin. For each initial compliance demonstration that includes a performance test, facilities must submit an initial notification of compliance status no later than 60 calendar days following the comp letion of the performance test. For each initial compliance demonstration that does not involve a performance test, facilities***E.O. 12866 Review

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- 4 must submit an initial notification within 30 calendar days of completing the initial compliance demonstration. Records necessary to determine compliance with the emission limitations and work practice standards must be compiled on a daily basis, and compliance reports must be submitted to the Administrator on a semiannual basis. Repeat performance tests are to be conducted every 5 years to ensure ongoing compliance.

There are 91 BSCP facilities that are currently major sources of HAP, 85 of which have at least one tunnel kiln. An estimated 22 of these facilities are projected to become synthetic area sources by promulgation rather t han comply with the BSCP standards. The remaining 69 facilities (63 of which have a tunnel kiln) are expected to be subject to the BSCP rule. For these 69 facilities, the annual recordkeeping and reporting burden associated with the BSCP standards (average d over the first 3 years after the effective date of the standards) is estimated to be 20,963 labor hours per year, at a cost of $1,113,105 per year (yr). Burden is defined at 5 CFR 1320.3(b).

No capital costs associated with monitoring, testing, recordkee ping or reporting are expected to be incurred during this period. The annual operation and maintenance costs are estimated to be $682/yr.

The total burden for the federal government (averaged over the first 3 years after the
effective date of the standards ) is estimated to be 71 labor hours per year, at a total labor cost of $3,698/yr. (All costs are in 2011 dollars.)

Because BSCP facilities are not required to come into full compliance with the standards until 3 years after promulgation, much of the respo ndent burden (e.g., performance tests, inspections, notification of compliance status, compliance report, records of compliance data and malfunctions) does not occur until the fourth year following promulgation.

For the BSCP rule, we estimate an average an nual recordkeeping and reporting burden of 48,674 labor hours per year, at a cost of $2,702,447/yr, for years 4 through 6. We also estimate annualized capital costs of $606,760/yr and annual operating and maintenance costs of $206,872/yr over this period, for a total annualized cost of $813,632/yr. The average annual burden for the federal government for years 4 through 6 is estimated to be 3,891 labor hours per year, at a total labor cost of $204,550/yr. (All costs are in 2011 dollars.)

An agency may not c onduct or sponsor, and a person is not required to respond to, a collection of information unless it displays a currently valid OMB control number. The OMB control numbers for the EPA’s regulations in 40 CFR are listed in 40 CFR part 9. When OMB
approves t his ICR, the agency will announce that approval in the Federal Register and publish a***E.O. 12866 Review

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- 5 technical amendment to 40 CFR part 9 to display the OMB control number for the approved
information collection activities contained in this final rule.

6.4 Regulatory Flexibi lity Act (RFA)
Pursuant to sections 603 and 609(b) of the RFA, the EPA prepared an initial regulatory flexibility analysis (IRFA) for the proposed rule and convened a Small Business Advocacy Review (SBAR) Panel to obtain advice and recommendations from sma ll entity representatives that potentially would be subject to the rule ’ s requirements. Summaries of the IRFA and Panel
recommendations are included at 79 FR 75669

- 75671.

As required by section 604 of the RFA, the EPA prepared a final regulatory flexibilit y analysis (FRFA) for this action. The FRFA addresses the issues raised by public comments on the IRFA for the proposed rule. The complete FRFA is included in Section 5 of “ Regulatory Impact Analysis: Final Brick and Structural Clay Products NESHAP, ” avail able for review in the docket (Docket ID No. EPA

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- 0291), and is summarized here.

6.4.1 Need for the Rule
The EPA is required under CAA section 112(d) to establish emission standards for each category or subcategory of major and area sources of HAPs listed for regulation in Section 112(b). These standards are applicable to new or existing sources of HAPs and require the maximum degree of emission reduction. In the Administrator’s judgment, the pollutants emitted from BSCP manufacturing facilities caus e or contribute significantly to air pollution that may reasonably be anticipated to endanger public health. Consequently, a NESHAP for the BSCP source category is being finalized.

6.4.2 Objectives and Legal Basis for the Rule
Section 112(d) of the CAA requires the EPA to set emissions standards for HAPs emitted by major stationary sources based on the performance of the MACT. The MACT standards for existing sources must be at least as stringent as the average emissions limitation achieved by the best performing 12% of existing sources (for which the Administrator has emissions information) or the best performing five sources for source categories with fewer than 30 sources (CAA section 112(d)(3)(A) and (B)). For new sources, MACT standards must be at least as

str ingent as the control level achieved in practice by the best controlled similar source (CAA section 112(d)(3)). The EPA also must consider more stringent “beyond

- the

- floor” control options. When considering beyond

- the

- floor options, the EPA must consider n ot only the maximum degree of reduction in emissions of HAPs but must also take into account costs,***E.O. 12866 Review

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- 6 energy, and non

- air environmental impacts when doing so. This rule is being proposed to comply with CAA section 112(d).

6.4.3 Significant Issues Raised

The EPA re ceived comments on the proposed standards and requests for comment that
were included based on the SBAR Panel recommendations. See sections V and VI of this rule’s preamble and “National Emission Standards for Hazardous Air Pollutants for Brick and
Structu ral Clay Products Manufacturing: Background Information for Final Rule

- Summary of Public Comments and Responses” in Docket ID No. EPA

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- 0291 for more detailed comment summaries and responses.

Work practices for dioxin/furan: One commenter state d that work practices for dioxin/furan emissions from BSCP tunnel kilns are not lawful under the CAA, and even if they were, the work practices proposed are not sufficient to minimize dioxin/furan emissions. Other commenters supported the proposed work pra ctices for dioxin/furan.

Response: The EPA is finalizing work practices for dioxin/furan as proposed.

Work practices for Hg and other metals: Several commenters responded to the EPA’s request for comment on work practices for Hg and non

- Hg HAP metals. Nume rous commenters stated that the EPA should finalize work practices instead of numeric limits and provided support for their assertion that the numeric limits are technically and economically impracticable to
enforce. Commenters also noted that the emission s reduced by these numeric standards are not justified by the high cost that would be incurred to meet the standards.

Response: Emissions of Hg and non

- Hg HAP metals were detected using standard EPA test methods; therefore, the Hg and non

- Hg HAP metals dat a sets do not meet the criteria for setting work practice standards under CAA section 112(h). The EPA is finalizing numeric standards for Hg and non

- Hg HAP metals under CAA section rather than work practices. The final numeric standards are revised from pr oposal to account for new data from the industry (including data on the Hg content of raw materials), removal of test data found not to meet the requirements of the applicable data, and changes in the EPA’s approach to selecting the MACT floor pools (see s ection V.A of this rule’s preamble for additional details).

Health

- based standard for acid gases: Several commenters asserted that the EPA may not legally set CAA section 112(d)(4) health

- based standards for acid gases for BSCP facilities.
Other commenters supported the EPA’s decision to propose health

- based standards for acid***E.O. 12866 Review

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- 7 gases but noted that the EPA’s approach was overly conservative and requested that the EPA consider setting multiple limits based on site characteristics.

Response: The EPA is finaliz ing the health

- based standards for acid gases as proposed. The EPA’s response to the legal arguments made against health

- based standards is presented in
section V.B of this rule’s preamble. The EPA is not changing the numeric limit from proposal,
because t he proposed limit provides low potential for both chronic and acute health effects.

Size subcategories for MACT floors: Several commenters requested that the EPA subcategorize by size for the non

- Hg HAP metal/PM MACT floor limits, as was proposed for Hg.

R esponse: As part of recalculating the MACT floor limits based on the final data set, the EPA is finalizing separate limits for small and large kilns for non

- Hg HAP metals/PM as well as Hg. The EPA is also finalizing limits in three different formats for bo th pollutants to provide additional flexibility for small tunnel kilns and tunnel kilns with a low metals content in the PM
emissions.

Sawdust dryers: Several commenters requested that the EPA finalize a subcategory of
sawdust

- fired kilns venting to sawdus t dryers. Commenters provided general descriptions of how the operation of these kilns is different than tunnel kilns and stated that there are only two operating that would be subject to the BSCP NESHAP.

Response: Although one commenter noted that stack t esting of a sawdust dryer is being considered, commenters did not provide test data to demonstrate that emissions from sawdust dryers are different than other tunnel kilns. Therefore, the EPA is not finalizing a subcategory of
sawdust

- fired kilns venting t o sawdust dryers.

Periods of startup and shutdown: One commenter stated that work practices for periods of startup and shutdown of BSCP tunnel kilns are not lawful under the CAA. Other commenters supported the proposal to provide work practices for periods of startup and shutdown but suggested improvements to the standards to make them feasible for all tunnel kilns.

Response: The EPA evaluated the comments and is finalizing work practice standards for periods of startup and shutdown that reflect best practi ces for minimizing emissions during these periods (see section V.C of this rule’s preamble for additional information).***E.O. 12866 Review

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- 8 MACT floor pool: Several commenters supported the EPA’s proposal to calculate MACT floor standards for PM based on the top 12% of the ki lns in the industry (i.e., the best

- performing
sources with an FF

- based APCD). One commenter asserted that the EPA’s proposal is unlawful and the EPA must consider other factors than the APCD type when setting MACT standards.

Response: The EPA reviewed all the data used for the MACT floor for PM as a surrogate
for non

- Hg HAP metals and found that some of the test data did not meet the requirements of EPA Method 5. When these data were removed, the EPA could no longer confirm that the data
available to the a gency represented all the best

- performing sources. Therefore, the final PM and

non

- Hg HAP metals are based on the top 12% of sources for which we had test data, regardless of APCD type (see section V.A of this preamble for additional details).

6.4.4 Small Busine ss Administration Comments
The U.S. Small Business Administration’s Office of Advocacy supported the EPA’s proposals to set work practice standards and health

- based emission standards in all instances allowed by statute and suggested other areas of improvement. The comments on areas of improvement and the EPA’s responses are summarized below:

Hg standards: The EPA should pursue subcategorization by input (raw material) type, delaying promulgation of an Hg standard to gather more information if needed . Standards may need to be combined with a significantly longer averaging time to allow for continuous compliance.

Response: Following proposal, the EPA received additional information on the Hg content of raw materials from facilities in the BSCP industry . This information did not provide the EPA with the information needed to establish subcategories based on the class or type of raw materials. However, it did allow the EPA to finalize Hg standards that account for the variability of Hg content in raw mate rials. As an initial point, it is doubtful that EPA had the option of delaying the promulgation of an Hg standard. Under CAA 112(e), EPA was scheduled to complete standards for all source categories by 2000. EPA’s 2003 Brick MACT rule was vacated, and th at vacatur re

- created EPA’s obligation to set standards for the Brick source category. Sierra Club v. EPA, 850 F.Supp.2d 300, 303

- 304 (D.D.C. 2012). Under the consent decree in that case, as amended in August 2014, EPA was obligated to sign a notice of fi nal rulemaking to set standards for the Brick source category by September 24, 2015.

In any event, delay is not warranted. Following proposal, the EPA received additional information on the Hg content of raw materials from facilities in the BSCP indu stry. This***E.O. 12866 Review

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- 9 information did not provide the EPA with the information needed to establish subcategories based on the class or type of raw materials. However, EPA has concluded that it has sufficient information to allow it to finalize Hg standards that acco unt for the variability of Hg content in raw materials. Thus, EPA’s conclusion is that there is no need to delay promulgation of the Hg standards in order to gather more information.

Economic analysis: The economic impact of the proposed rule on small enti ties is significantly underestimated. Specifically, the EPA should not annualize costs at 7% over 20 years because that does not reflect the financing options available to small entities, the EPA underestimated the cost for a facility to become a synthetic area source, and the EPA has underestimated the cost to comply with the Hg standards given the limited information the agency has on the performance of Hg controls in this industry.

Response : EPA standard engineering cost practice is to annualize over the expected life of the control equipment at 7%. EPA does not have the data available to model the way a firm pays for a control device because each firm has a different set of potential options for financing including debt financing, eq u ity financing, and f inancing through retained earnings. EPA acknowledges that some firms may not be able to borrow the money and some may close. EPA's closure analysis is quite uncertain but we do not have the detailed firm specific information necessary to refine the analys is. The EPA agrees that the costs to become a synthetic area source at proposal were underestimated, and the final rule impacts include testing costs for all facilities, because potential synthetic area sources would have to demonstrate that their emission s qualify them to apply for synthetic area status. Finally, the EPA must use the best information available to the agency to estimate the impact of the standards on all entities. The final Hg standards incorporate variability in the Hg content of raw mater ials, which is expected to ease the burdens
on some small entities.

6.4.5 Affected Small Entities
Of 44 parent companies owning BSCP facilities, 36 parent companies are small businesses. The EPA computed the ratio of estimated compliance costs to company sales (cost

to

- sales ratio) to measure the magnitude of potential impacts on small companies. Under the final standards, the EPA estimated that two to three small BSCP manufacturing facilities are at significant risk of closure.

6.4.6 Reporting, Recordkeeping, and Oth er Compliance Requirements
Respondents would be required to provide one

- time and periodic notifications, including initial notification, notification of performance tests, and notification of compliance status.***E.O. 12866 Review

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- 10 Respondents would also be required to submit semiannual reports documenting compliance with the rule and detailing any compliance issues, and they would be required to submit the results of performance tests to the EPA’s ERT. Respondents would be required to keep documentation supporting information included in these notifications and reports, as well as records of the operation and maintenance of affected sources and APCD at the facility.

6.4.7 Significant Alternatives
The EPA considered three major options for this final rule; see “Regulatory Impact Analy sis: Final Brick and Structural Clay Products NESHAP,” in Docket ID No. EPA

- HQ

OAR

- 2013

- 0291), for more information about the alternatives. Finalizing the proposed changes without revision is expected to have similar cost and emission reduction impacts to the standards the EPA is finalizing, with a similar number of closures (one to two small BSCP manufacturing facilities rather than two to three). However, for the various legal and technical reasons outlined
in this rule’s preamble and “National Emission S tandards for Hazardous Air Pollutants for Brick and Structural Clay Products Manufacturing: Background Information for Final Rule

- Summary of Public Comments and Responses” in Docket ID No. EPA

- HQ

- OAR

- 2013

- 0291, the EPA
determined that the PM/non

- Hg HAP m etals and Hg standards should not be finalized as proposed. The other alternative considered included the same standards for acid gases and Hg that are being finalized but only provided one set of limits PM/non

- Hg HAP metals (i.e., did not provide separate sets of limits for small and large tunnel kilns). This alternative is expected to have significantly higher cost impacts than the standards the EPA is finalizing, along with a significantly higher number of closures (five to ten small BSCP manufacturing f acilities rather than two to three). Therefore, the EPA determined that it is necessary to exercise its discretion to subcategorize by kiln size to minimize the significant economic impact on small entities.

In addition, the EPA is preparing a Small Entity Compliance Guide to help small entities comply with this rule. The guide will be available on the World Wide Web approximately 1 year after promulgation of the rule

.
6.5 Unfunded Mandates Reform Act

This action does not contain an unfunded mandate of $100 mil lion or more as described in the Unfunded Mandates Reform Act (UMRA), 2 U.S.C. 1531

- 1538, and does not significantly or uniquely affect small governments. This action imposes no enforceable duty on any state, local, or tribal government or the private sect or.***E.O. 12866 Review

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- 11 6.6 Executive Order 13132: Federalism
This action does not have federalism implications. It will not have substantial direct effects on the states, on the relationship between the national government and the states

, or on the distribution of power and res ponsibilities among the various levels of government.

6.7 Executive Order 13175: Consultation and Coordination with Indian Tribal Governments
This action does not have tribal implications, as specified in Executive Order 13175. It
will not have substantial dir ect effects on tribal governments, on the relationship between the federal government and Indian tribes, or on the distribution of power and responsibilities between the federal government and Indian tribes, as specified in Executive Order 13175. The
actio n imposes requirements on owners and operators of BSCP manufacturing facilities and not tribal governments. Thus, Executive Order 13175 does not apply to this action.

6.8 Executive Order 13045: Protection of Children from Environmental Health Risks and Safety Risks
This action is not subject to Executive Order 13045 because the EPA does not believe the environmental health or safety risks addressed by this action present a disproportionate risk to
children. This action ’ s health and risk assessment s are containe d in the memorandum “ Risk
Assessment to Determine a Health

- Based Emission Limitation for Acid Gases for the Brick and Structural Clay Products Manufacturing Source Category, ” Docket Item No. EPA

- HQ

- OAR

2013

- 0291

- 0132.

6.9 Executive Order 13211: Actions Concern ing Regulations That Significantly Affect Energy Supply, Distribution or Use

This action is not a “ significant energy action ” because it is not likely to have a significant adverse effect on the supply, distribution, or use of energy. This action will not adversely directly affect productivity, competition, or prices in the energy sector.

6.10 National Technology Transfer and Advancement Act (NTAA) and ICFR Part 51
This action involves technical standards. The EPA has decided to use the following four voluntary consensus standards as acceptable alternatives to the EPA test methods for the purpose
of this rule. ANSI/ASME PTC 19

- 10

- 1981, Part 10, “ Flue and Exhaust Gas Analyses, ” is acceptable as an alternative to Method 3A and 3B for the manual procedures only and not the instrumental procedures.***E.O. 12866 Review

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- 12 ASTM D6735

- 01 (Reapproved 2009), “ Standard Test Method for Measurement of Gaseous Chlorides and Fluorides from Mineral Calcining Exhaust Sources

- Impinger Method, ” is acceptable as an alternative to Methods 26 and 26A.

ASTM D6784

- 02 (Reapproved 2008), “ Standard Test Method for Elemental, Oxidized,
Particle

- Bound and Total Mercury Gas Generated from Coal

- Fired Stationary Sources (Ontario Hydro Method), ” is acceptable as an alternative to Method 29 (portion for Hg only).

ASTM D6348

- 03 (Reapproved 2010), “ Standard Test Method for Determination of Gaseous Compounds by Extractive Direct Interface Fourier Transform Infrared (FTIR) Spectroscopy, ” is acceptable as an alternative to Method 320 with the following conditions: (1)
the te st plan preparation and implementation in the Annexes to ASTM D 6348

- 03, Sections A1 through A8 are mandatory and (2) in ASTM D6348

- 03 Annex A5 (Analyte Spiking Technique), the percent recovery (%R) must be determined for each target analyte (Equation A5.5 ). For the test data to be acceptable for a compound, %R must be greater than or equal to 70 % and less than or equal to 130 % . If the %R value does not meet this criterion for a target compound, the test
data are not acceptable for that compound and the tes t must be repeated for that analyte (i.e., the sampling and/or analytical procedure should be adjusted before a retest). The %R value for each compound must be reported in the test report

, and all field measurements must be corrected with
the calculated %R value for that compound by using the following equation: Reported Result = (Measured Concentration in the Stack x 100)/%R.

6.10.1 Executive Order 12898: Federal Actions to Address Environmental Justice in Minority Populations and Low

- Income Populations

The EPA b elieves the human health or environmental risk addressed by this action will not have potential disproportionately high and adverse human health or environmental effects on minority, low

- income, or indigenous populations because it does not affect the leve l of protection provided to human health or the environment. As explained in the December 2014 proposal (79 FR 75672), the EPA determined that this final rule will not have disproportionately high and adverse human health or environmental effects on minori ty or low

- income populations, because it increases the level of environmental protection for all affected populations without having any disproportionately high and adverse human health or environmental effects on any population, including any minority or low

- income population. Additionally, the agency has conducted a proximity analysis for this rulemaking, which is located in the docket. (See “ EJ Screening Report for Brick and Structural Clay, ” Docket Item No. EPA

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- 0291

- 0102

. )***E.O. 12866 Review

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- 13 6.11 Congressional Revi ew Act (CRA)
This action is subject to the CRA, and the EPA will submit a rule report to each ho u se of the Congress and to the Comptroller General of the United States. This action is not a “ major
rule ” as defined by 5 U.S.C. 804(2).***E.O. 12866 Review

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7

- 1 SECTION 7
COMPARISON OF BENEFI TS AND COSTS

7.1 Introduction

The EPA compared the monetized human health benefits of reducing cases of morbidity and premature mortality among populations exposed to PM2.5 (Section 4) with the estimated
annualized soci al costs (Section 5) and found that the benefits of the final rule outweigh the costs. The net benefits are likely higher since EPA was not able to monetize other environmental benefits from reducing exposure to 375 tons of HAPs each year and ecosystem eff ects and visibility impairment associated with PM emissions.

7.2 Net Benefits of the Final Standards
Using a 3% discount rate, we estimate the total monetized benefits of the final standards to be $ 83 million to $1 9 0 m illion (Table 7

- 1). Using a 7% discount ra te, we estimate the total monetized benefits to be $ 75 million to $1 7 0 million. The annualized costs are $2 7 million at a 7% interest rate. The net benefits are $ 5 6 million to $ 160 million at a 3% discount rate for the benefits and $ 48 million to $ 150 m ill ion at a 7% discount rate.

Table 7

- 1. Summary of the Monetized Benefits, Socia l Costs, and Net Benefits (million 2011$)

Total (3% Discount Rate) Total (7% Discount Rate)

Final Standards

Total Monetized Benefits $ 83 to $1 90 $ 75 to $1 70

Total Social Costs a $2 7

Net Benefits $ 5 6 to $ 16 0 $ 48 to $ 150

a The methodology uses the estimate social costs from the baseline year of economic model. As a result, the same

value of social costs is used for both discount rates. All estimates are independently rounded to two significant figures, so estimates may not appear to sum in this table.***E.O. 12866 Review

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A

- 1 APPENDIX A
ECONOMIC MODEL

A.1 Baseline Data for Economic Model

Table A

- 1

. Affected Production Statistics by Census Region

Census Region 1,000 S.B.E Shipped in 2010 Estimated Affected Production Share within Region a

East North Central 285,508 81%

East South Central 388,685 100%

Mid

- Atlantic 213,583 69%

Mountain 114,154 5 0 % New England 37,034 0%

Pacific 74,563 85%

South Atlantic 1,307,601 92%

West North Central 183,247 100%

West South Central 891,232 100%

United States 3,495,657 90%

a To approximate the affected shares, EPA estimated affected production from kiln capacity and operating hours of

major sources.
Source: U.S. Census Bureau, 2011 and U.S. EPA calculations.***E.O. 12866 Review

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- 2 Table A

- 2

. Average Prices of Brick, Building or Common and Facing: 2010

Census Region $ per 1,000 S.B.E. Expressed in 2010 dollars $ per 1,000 S.B.E. Expressed in 2011 dollars
New England $379 $387

Middle Atlantic $324 $331

East North Central $297 $302

West North Central $272 $277

South Atlantic $227 $232

East South Central $183 $186

West South Central $225 $229

Mountain $355 $362

Pacific $541 $551

United States $248 $253

Sources: U.S. Census Bureau, 2011. Prices adjusted using the Implicit Price Deflator for Gross Domestic Product

(GDP).

A.2 Model Equations
Given the weight of bricks, transportation costs are high relative to value. For this reason, bricks are more likely to be bought and sold within regions because of the cost of transportation across long distances. We found that international trade represented only a small fraction of economic activity (see Section 2.5), and the latest Census data show that a majority of nonmetallic mineral products were shipped less than 100 miles (U.S. Department of Transportation, 2010 ). 72 Approximately 75% of the total tons shipped are shipped in NAICS is
less than 50 miles. A comparison of Census region average prices for bricks shows substantial
differences between regions in the av erage price of brick products shipped. To the extent these price differences persist over time, these differences may be consistent with regional markets for brick. As a result, we use a perfectly competitive partial equilibrium model with nine regional
br ick markets (defined by census region).

The market demand (D) in region (r) with regulation is :

QQ DDDD

′ = QQ DDDD × � 1 + � PP ′

− 1 � × ηη � (A.1 )

The affected market supply (SA) in region (r) with regulation is :

72 The data include other product s such as cement, so it is unclear from this data whether brick and structural clay products face the same transportation and shi pment patterns as cement products.***E.O. 12866 Review

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- 3 QQ SS

′ = QQ SS × � 1 + � � PP ′

− �

− 1 � × εε � (A.2 )

The unaffected market supply (SU) in region (r) with regulation is :

QQ SSSS

′ = QQ SSSS × � 1 + � PP ′

− 1 � × εε � (A.3 )

At the new with

- regulation market

- clearing price, quantities in A.1, A.2, and A.3 satisfy the following market equilibrium condition for each region (r) :

QQ DDDD

′ = QQ SS ′ + QQ SSSS ′ (A.3 )

As reported in Section 2, a single parent company accounts for a majority of estimated

census region production. As a result, the price

- taking model of firm decisions may not describe
business decisio ns as well as other economic models of pricing behavior (i.e., oligopoly)

. If market power exists, the use of a perfectly competitive model may understate the social costs of
the final rule.

A.3 Model Parameters

A.3.1 Demand
All other things equal, consumers will likely buy fewer brick and structural clay products (BSCP) when the price of the product rises. The price elasticity of demand measures the size of the price response. 73 Several factors influence how sensitive consumer s are to price changes. If consumers can easily switch from one product to another because there are many close substitutes, demand tends to be more elastic. This is particularly true for more narrow market definitions (king versus modular brick) and over longer time horizons for the consumption decision (months versus years).

Currently, EPA has not identified statistically estimated price elasticities for BSCP

. However, economy

- wide simulation models have suggested the nonmetallic mineral industry
demand e lasticity is approximately −0. 8. As are result, a 1% change in price results in a 0.8% decline in the quantity demanded (Ho, Morgenstern, and Shih, 2008 ). Because the market definition for the product is broad, the p rice response for BSCP is likely more elastic than this
value

.

73 The measure is computed as the percentage change in quantity demanded divided by the percentage change in price.***E.O. 12866 Review

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- 4 A.3.2 Supply
All other things equal, brick manufacturers will likely offer to sell more bricks when the price of bricks rises. The price elasticity of supply measures how much the quantity of bricks supplied responds to changes in the brick price. 74 If manufacturers have a significant amount of flexibility to change the amount of bricks they produce when the price rises, the supply of bricks is elastic. In contrast, if the quantity of brick prod uced and supplied only changes by small amounts when the price rises, the supply of bricks is inelastic.

A key determinant of the price elasticity of supply is the length of the time period over which the product choices can be made. During shorter periods , it is more difficult for the firm to adjust inputs and increase production. Put another way, the firm typically has some fixed factors of production that limit its ability to respond to price changes. Rutherford ( 2002) develop ed an equation that can be used to derive a benchmark price elasticity of supply that considers the fixed factor value as a share of total product value. In our example, consider the case of two production inputs, one input that is fixed during a short time p eriod 75 and the other input that varies with production

.

Supply Elasticity = elasticity of substitution × 

### share ue factor val fixed share ue factor val fixed 1

− (A.4)

To illustrate the approach, consider the value share of the fixed factor to be 5 0% to approximately match the nonlabor value added reported in the U.S. Census data above. In cases where we lack data to estimate the elasticity of substitution, it is common to assume the elasticity is 1 (a Cobb

- Douglas production function). This means that a 1% change in the ratio of factor prices would result in a 1% change in the ratio of factor shares . If we assume the elasticity of substitution between the fixed and variable input is one, the formula is

Supply Elasticity = 1 × 5

. 0 5

. 0 1

− = 1 (A.5)

Using these values for the f ixed factor ’ s value share and elasticity of substitution, the supply elasticity is approximately one

. This means if the price of brick rose by 1%, brick
manufacturers would plan to sell 1 % more bricks to the market. Given the current low capacity
utilizati on rates and excess capacity available in the industry, this value may underestimate how

74 The measure is computed as the percentage change in quantity supplied divided by the percentage change in price.
75 The fixed factor generally includes plant and capital equipment; factors that vary with production could include materials or labor.***E.O. 12866 Review

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- 5 responsive the brick industry would be to changes in the market price. As a result, the actual supply elasticity value may be elastic with a value higher than one.

A. 4 Partial Equilibrium Measures of Social Cost: Changes Consumer and Producer Surplus
In partial equilibrium analysis, the social costs are estimated by measuring the changes in consumer and producer surplus. These values can be approximated using the mark et supply and demand model (Figure A

- 1).

Figure A

- 1. Partial Equilibrium Measures of Social Cost: Changes Consumer and Producer Surplus
Change in consumer surplus =

– [fghd + dhc] Change in producer surplus = [fghd

– aehb]

– bdc Change in total surplus = consumer surplus + producer surplus =

– [aehb + dhc + bdc]

T he change in consumer surplus is measured as follows :

∆

CS =

– [ ∆ Q 1 × ∆ p ] + [ 0.5 × ∆ Q × ∆ p ]

. (A.6 )

H igher market prices and lower quantities lead to consumer welfare losses.

For affected supply, the change in producer surplus is measured as follows :

∆

PS = [ Q 1 × ∆ p ]

– [ Q 1 × unit cost increase]

– [ 0.5 × ∆ Q × ( ∆ p

– unit cost increase ) ]

. (A.7 ) Q 1 Q 0 P 1

P 0 h

c

a $

Output e d S 1 : With Regulation

S 0 : Without Regulation Price Increase } Unit Cost Increase 

# } g

f

b***E.O. 12866 Review

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- 6 Higher unit costs and lower production level reduce producer surplus

. The losses are
offset to some d egree because market prices tend to rise. In contrast, for unaffected supply, the change in producer surplus is :

∆ PS = [ Q 0 × ∆ p ] + [ 0.5 × ∆ Q × ∆ p ]

. (A.8 )

Higher prices increase producer surplus for unaffected producers in the U.S. and other
countries.

## Excerpts for Portland Cement Proposal and Final Rule on use of top 12 percent of sources versus top 5 sources.

Proposed Rule

The average performance of the best performing 12 percent of kilns (2 kilns ) is 4.8 ppmvd THC (a daily average expressed as propane at 7 percent oxygen ). We calculated variability based on the variances in the performance of the two lowest emitting kilns. This includes day

- to

- day variability at the same kiln, variability among the two lowest emitting kilns, and because one dataset included 695 daily measurements , it represents long term variability at a single kiln. We calculated the MACT floor (7 ppmvd)based on the UPL (upper 99thpercentile) as described earlier from the average performance of the 2 lowest emitting kilns, S tudent’s t

- factor, and the total variability, which was adjusted to account for the lower variability when using 30 day
averages.

In this case the proposed new and existing source MACT floors are almost identical because the best performing 12 percent of kilns (for which we have emissions information) is only two

sources . The reason we look to the best performing 12 percent of sources is that the cement kiln source category consists of 30 or more kilns. Section 112(d)(3)(A)of the Clean Air Act provides that standards for existing sources shall not be less stringent than ‘‘the average emission limitation achieved by the best performing 12 percent of the existing sources (for which the Administrator has emissions information), * * * in the category or subc ategory for categories and subcategories with 30 or more sources.’’ A plain reading of the above statutory provisions is to apply the 12 percent rule in deriving the MACT floor for those categories or subcategories with 30 or more sources. The parenthetica l ‘‘(for which the Administrator has emissions information)’’ in section 112(d)(3)(A) modifies the best performing 12 percent of existing sources, which is the clause it immediately follows. However, in cases where there are 30 or more sources but little e mission data this results in only a few kilns setting the existing source floor with the result that the new and existing source MACT floors are almost identical. In contrast, if this source category had less than 30 sources, we would be required to use th e top five best performing sources, rather than the two that comprise the top 12 percent. Section 112 (d)(3)(B).

We are seeking comment on whether, with the facts of this rulemaking, we should consider reading the intent of Congress to allow us to consider five sources rather than just two. First, it seems evident that Congress was concerned that floor determinations should reflect a minimum quantum of data: At least data from five sources for source categories of less than 30 sources (assuming that data from five sources exist). Second, it does not appear that this concern would be any less for source categories with 30 or more sources. The concern, in fact, would appear to be greater. 22 

## We note further that if we were to use five sources as best T HC performers here, the existing source floor would be 10 ppmvd. We are specifically requesting comment on

## interpretive and factual issues relating to the proposed THC floors, and also reiterate requests for further THC performance data, especially from ki lns equipped with CEMs.

22 

## As noted, basi ng the proposed existing source THC floor on data from two sources ( i.e. 12 percent of the 15 sour ces for which we have CEM data) largely eliminates the distinction between new and existing source THC f loors. Yet this is an important statutory distinction.

Final Rule

i. Floor Determination. EPA proposed THC emissions limits of 7 and 6 parts per million by volume dry (ppmvd) for existing and new sources respectively for both cement kilns and raw material dryers. The existing source standard was based on the performance of the best performing 12 percent of cement kilns for which we had THC CEMS data. At proposal we requested comment on the issue of whether or not we should base the existing source floor on the best performing five kilns, rather than on the best performing 12 percent (two kilns). Industry commenters supported the use of the best five kilns stating that this would be in keeping with what appeared to be the intent of Congress that five kilns sh ould be the minimum number of sources on which to set an existing source floor. However, other commenters noted that a plain reading of the statute is that when the source category has 30 or more sources, the top performing 12 percent for which the Adminis trator has data must be used, even if this results in less than five facilities due to lack of available data. In this final rule we are reaffirming our decision at proposal to use the best performing 12 percent rather that the best performing five facilit ies because we believe this result to be unavoidably compelled by the literal language of the statute.

Final Rule Comments and Responses

Comment: Several industry commenters (2845, 2846, 2874, and 2915) stated that EPA is proposing to calculate MACT floors by averaging the top 12 percent of sources for which CEMS data are available (even if that amounts to less than 30 sources), rather than by consi dering the top 12 percent of sources for which EPA has emissions information. As a result, EPA is proposing to establish the MACT floor based on data from only 2 sources. The industry commenters stated that CAA section 112(d) obligates EPA to set the MACT floor looking at no fewer than 5 sources, recognizing the value of relying on the maximum amount of data available. Industry commenter 2841 stated that the use of a minimum of five facilities should be adopted in the establishment of THC standards as well as the other standards in this proposed regulation. The establishment of requirements based on a small amount of data would run counter to the intent of the CAA in utilizing data that is truly representative of the best

- performing facilities throughout an entire industry. Industry commenter 2841 stated that in previous MACT rulemakings, EPA used the five best performing facilities if the number of facilities was less than 30. Consistent with these prior rulemakings, the industry commenter stated that this a pproach

## should be used for this proposed Portland Cement NESHAP rule and that EPA needs additional data points in order to appropriately set limits for the industry as a whole.

Response: EPA believes that it has discretion to use the data which most accu rately measure sources’ performance, which for THC case are data obtained from CEM

- equipped sources. EPA also believes that it has a reasoned technical basis for not combining CEMS data with non

- CEM data, since this would be a classic apples

- to

- oranges com parison due to the difference in measuring times and methods. EPA does not agree that section 112 (d)(3) mandates a minimum of 5 sources in all instances, notwithstanding the incongruity of having less data to establish floors for larger source categories than is mandated for smaller ones. The literal language of the provision appears to compel this result.

## Date: September 14, 2015

To: Sharon Nizich , EPA/OAQPS/SPPD

From: Thomas Holloway , RTI International

Subject: Methodology and Assumptions Used to Estimate the Model Costs and Impacts of BSC P Air Pollution Control Devices for the Final Rule

I. I ntroduction

In accordance with section 112 of the Clean Air Act (CAA), the U.S. Environmental Protection Agency (EPA) established national emission standards for hazardous air pollutant s (NESHAP) on May 16, 2003 for the brick and structural clay products (BSCP) manufacturing industry. The NESHAP regulated emissions of hydrogen fluoride (HF)

, hydrogen chloride (HCl), and particulate matter (PM)

— a surrogate for hazardous air pollutant (HAP ) metals

— from tunnel kilns located at BSCP facilities

. On March 13, 2007, the D.C. Circuit Court vacated the emission standards for BSCP manufacturing due to issues associated with the methodology used to determine the minimum regulatory “floors” for new a nd existing units. 1 

## Therefore, on December 18, 2014, the EPA propos ed new standards for BSCP manufacturing , including standards for HF, HCl, chlorine (Cl 2 

## ), mercury (Hg), and non

- Hg HAP metals (or PM surrogate)

. The EPA provided a 90

- day public comment period following proposal of the BSCP Manufacturing NESHAP, during which all affected parties were given the opportunity to comment on the proposed rule. The EPA has considered the comments received and, as appropri ate, incorporated them into the final rule

. The purpose of this memorandum is to present the methodology and assumptions used in estimating the model costs and environmental and
energy impacts for the control technologies used to meet the standards in the final rule

.
II. General M odel Parameters

M odel costs and impacts were developed for two sizes of BSCP control devices

— large control devices (LCD) and small control devices (SCD ) , reflecting the size subcategories of the BSCP Manufacturing NESHAP

, which are based on a kiln capacity threshold of 10 tons per hour (tph) . The model costs and impacts were estimated based on a variety of model parameters

— (1) general parameters such as production rate, operating hours, gas flow rate, electricity and waste disposal unit costs, labor wage rates, and uncontrolled emissions ; and (2) control

- specific parameters such as control device horsepower ( hp ) requirements

, sorbent requirements, and

1 

### Sierra Club v. EPA , 479 F.3d 875 (D.C. Cir. 2007)

.

## 2 sorbent unit cost

. T his section discusses the basis for the general model parameters , which are presented in Appendix A at the end of this memo randum

. The model production rate s (in tph) were based on data from the BSCP inventory ( Holloway , 2014) . The BSCP inventory is a combination of (1) industry responses to the 2008 BSCP sec tion 114 survey ; (2) responses to a survey similar to the 2008 BSCP section 114 survey that was administered by the Brick Industry Association; and ( 3 ) industry data from the 2003 BSCP database (from the original 2003 BSCP Manufacturing NESHAP) for plants not included in the 2008 survey s

. The average kiln production rate (7.0 tph) for the small model was calculated from those tunnel kilns with a kiln capacity less than 10 tph . T he average kiln production rate (15 tph) for the large model was calculated from those tunnel kilns with a kiln capacity of 10 tph or greater. The model kiln production rates were based on a mix of permitted and design capacities, i.e. , those capacities to which the kilns are actually limited.

The model kiln operating hours (8,760 hours per year [hr/yr]) for both large and small model sizes were based on data from a 2015 survey of the BSCP industry conducted by the Brick Industry Association (BIA), provided to the EPA in the BIA’s public comments on the proposed rule (R egina, 2015).

The model exhaust gas flow rate s (in actual cubic feet per minute [ acfm ]) were based on data from BSCP stack tests (Raymond

, 2014 ) , with the model flow rate for the small model (23,100 acfm) calculated from stack test data for tunnel kilns wi th a kiln capacity less than 10 tph , and the model flow rate for the large model (38,700 acfm) calculated from stack test data for tunnel kilns with a kiln capacity of 10 tph or greater. In those cases where flow rate data were only available in units of d ry standard cubic feet per minute (dscfm), those flow rates were converted to units of acfm using Equation 1 below, based on stack temperature and moisture
content data from the stack test (assuming a stack pressure equivalent to standard atmospheric
press ure):

Equation 1

— Flow rate conversion



# ( ) % 100 % 100

tan 

## O %H T

T Q Q

2 dard s stack dscfm acfm



## − × × =

where:

Q acfm 

## = exhaust flow rate (acfm)

, Q dscfm 

## = exhaust flow rate (dscfm),

T stack 

## = stack temperature (converted from degrees Fahrenheit [ °F ] to degrees Rankine [ °R ] ),

T standard 

## = standard temperature (528°R), and

% H 2 

## O = moisture content ( percent [ % ] ).

## 3 Unit costs for electricity ($0.0 8 3/kilowatt

- hour [kWh]) and waste disposal ($ 51.90 /ton waste) were based on the average of data from the aforementioned 2015 BIA survey ( Regina, 2015 )

. The o perator wage rate ($22.67/hr) was based on mean hourly wage data from the May 2011 Bureau of Labor Statistics for NAICS 327100 (Clay Product and Refractory Manufacturing) for an Industrial Engineering Technician (BLS

, 201 2 )

. Wage rates from the Bureau of L abor Statistics were used because they were more conservative than those provided by BSCP survey respondents. The m aintenance wage rate ($24.94/hr) was assumed to be 10 percent higher than the operator wage rate , similar to the ratio of maintenance to operator wage rates provided by one BSCP company in its response to the 200 8 survey ( Holloway

, 2014 )

. The capital recovery factor (0.0944) was c alculated using Equation 2 below , assuming a 7 percent interest rate and 20

- year equipment life for the control devices expected to be used to comply with the new standards for BSCP manufacturing :
Equation 2

— Capital recovery factor:



# ( ) 1 1 ) 1 (

− + + ×

= n n



## i i i CRF

where:

i = interest rate (%) and

n = payment period

, e.g. , equipment life (yrs).

Model uncontrolled emissions estimates (in pounds per ton [ lb/ton ]) were used to estimate the amount of material captured by the control devices, based on each device’s control efficiency. The pollutants of interest were HF, HCl, chlorine ( Cl 2 

## ), PM, HAP metals, and sulfur dioxide ( SO 2 

## ) . The model uncontrolled emissions estimates for HF, HCl, PM, Cl 2 

## , and SO 2 

## were based on the average of uncontrolled emissions data from BSCP stack tests (Raymond

, 2014 )

. The model uncontrolled emissions estimate for total HAP metals was assumed to be 1. 1 percent of the PM estimate, based on the average ratio of metals to PM emissions in BSCP stack tests (Raymond

, 2014 )

.
III. Model Costs

This section discusses the methodology and assumptions used to estimate the model costs for the new or retrofit emissio n control devices that BSCP facilities are e xpected to install in order to comply with the new standards for the BSCP industry. The cost estimates are presented in 2011 dollars , which was the latest year for which an annual cost index value was available f or scaling costs at the time that costs were first being developed for the BSCP rule . The model cost tables for new and retrofit control device s are presented in Appendices B and C, respectively. (Note: The a nnual operating costs for replacement control devices presented in this memorandum are a conservative estimate . The operating costs for control devices to be replaced have not been subtracted out. )

## 4 Dry sorbent injection/fabric filter (DIFF)

. Dry sorbent injection followed by a fabric filter (DIFF) can be used to reduce emissions of both particulates and acid gases from BSCP tunnel kilns. This type of control system is already in use in the BSCP industry ( Holloway

, 2014 ) and is expected to be installed on uncontrolled kilns or r etrofitted to replace less efficient kiln controls to enable facilities to comply with the new BSCP manufacturing standards

. The DIFF costs were estimated using the cost algorithms from the original BSCP manufacturing rulemaking ( Shrager

, 2003) , which were generated following guidelines in the OAQPS Control Cost Manual (EPA

, 2002)

. The algorithms were updated to include more recent model parameters, including the general parameters discussed previously and the following parameters specific to DIFF control d evices:

• Control efficiency ( e.g. , 99.5% HF, 94% PM)

• Fan horsepower (150 hp [small]/190 hp [large])

• Total horsepower for other motors (30 hp)

• Stoichiometric ratio of hydrated lime (2.65 [small], 1.79 [large])

• Bag life (5 yrs)

• Gas

- to

- cloth ratio (3.4 feet per minute [ft/min])

• Bag area (28 square feet [ft 2 

## ])

• Compressed air (0.9 cubic feet [ft 3 

## ] of compressed air/1,000 ft 3 

## of gas)

• Time to replace bags (2.25 hr/bag)

• Hydrated lime unit cost ($160/ton)

• Bag fabric cost ($8.15/ft 2 

## )

• Compressed air unit cost ($ 0.363 /1,000 ft 3 

## )

• Bag capital recovery factor (0.244, based on 5

- yr bag life and 7% interest)

With three exceptions, t he values of the model DIFF parameters were determined based on averages of industry responses to the 2008 BSCP survey ( Holloway

, 2014 )

. The compressed air unit cost was based on the average of data from the 2015 BIA survey (Regina, 2015), while
t he DIFF control efficiencies and stoichiometric ratios of hydrated lime were determined differently, as discussed below.

The control efficiencies for new and retrofit DIFF were estimated based on the average of those stack tests with better efficiencies than the baseline control efficiency (which was determined based on the average of all available stack tests with control efficiency data) (Raymond

, 201 4 )

. For example, the baseline HF control efficiency for a DIFF is estimated to be 98 percent; in stack tests with HF control efficiencies better than 98 percent, the average HF control efficiency is 99.5 percent.

The stoichiometric ratio of hydrated lime f or new and retrofit DIFF was estimated based on average reagent rates from industry responses to the 2008 BSCP survey ( Holloway

, 2014 )

, average uncontrolled emissions data from stack tests (Raymond

, 2014 ) , and molecular weight information for the primary p ollutants and hydrated lime, scaled up from baseline using the ratio of the aforementioned control efficiencies (99.5 percent/98 percent).

## 5 The model DIFF capital costs were estimated by taking DIFF capital cost data from industry responses to the 2008 BSCP survey ( Holloway

, 2014 ) , escalating the costs to 2011 dollars using the Chemical Engineering Plant Cost Index (CEPCI) (C E
, 2011) , scaling the costs to the large and small model sizes using the six

- tenths cost rule (see Equation 3 below), taking the averag e of the scaled costs for each model size, and rounding the results to three significant figures.

Equation 3

— Six

- tenths cost rule:

0.6

2 1

2 1 

##        

= Q Q
C C

w here:

C = capital cost and Q = capacity parameter ( e.g. , exhaust gas flow rate).

For retrofits, the capital costs were further adjusted using a retrofit factor of 1.4, which is in the middle of the range of retrofit factors for emission control devices, according to guidance from the OAQPS Control Cost Manual (EPA

, 2002)

.
The model DIFF annual costs were estimated based on the aforementioned cost algorithms, and include the following cost items:

• Operating labor (assumed to be twice the maintenance labor hours at $22.67/hr)

• Supervisory labor (estimated at 15% of operating labor)

• Maintenance labor (esti mated based on 1.25 hr/shift from BSCP survey responses and an assumed $24.94/hr wage rate)

• Maintenance materials (estimated at 100% of maintenance labor)

• Electricity (estimated based on hp requirements, 0.745 kW/hp, and $0.0 8 3/kWh)

• Lime (estimated based on hydrated lime makeup and $160/ton hydrated lime unit cost)

• Compressed air (estimated based on 0.9 ft 3 

## /1,000 ft 3 

## compressed air requirements and $ 0.363 /1,000 ft 3 

## compressed air unit cost)

• Replacement bags (estimated based on 3.4 ft/min gas

- to

- cloth ratio , $8.15/ft 2 

## bag fabric, and 0.244 bag capital recovery factor)

• Bag replacement labor (estimated based on 3.4 ft/min gas

- to

- cloth ratio, 28 ft 2 

## bag area, $29.94/hr maintenance wage rate, and 0.244 bag capital recovery factor)

• Waste disposal (estimated based on waste generated and $ 51.90 /ton waste)

• Overhead (estimated at 60% of labor and maintenance materials)

• Property taxes, insurance, and administrative charges (estimated at 4 % of total capital cost)

## 6 • Capital recovery (estimated as the product of a 0.0944 ca pital recovery factor and total capital cost, minus the cost of capital recovery for replacement bags and bag replacement labor)

Fabric filter

. Fabric filters can be used to reduce emissions of particulates from BSCP tunnel kilns at plants that already hav e acid gas control or have inherently low acid gas emissions ( e.g. , due to low fluoride and chloride content in the raw materials). Stand

- alone fabric filters are not currently used by the BSCP industry to control tunnel kiln emissions, although DIFF are u sed to control emissions from the larger tunnel kilns ( Holloway

, 2014 )

. The BSCP industry has expressed the following concerns about using stand

- alone fabric filters ( Holloway

, 2013 b ) :

• W ithout the dry lime injection that reduces the acid gas, there will no t be enough particulates in the kiln exhaust to coat the bags and get good performance from the fabric filter.

• T he uncontrolled acid in the exhaust stream could rot the bags

.

• T he exh aust gas temperatures from BSCP tunnel kilns can be high (about 400°F

on average, as high as 668°F).

• T he use of membrane bags on low inlet loadings.

In response to these concerns, we contacted two major fabric filter vendors

— Solios Environment and McGill AirClean

— and a major filter bag vendor

— W.L. Gore & Associates

— to determine the feasibility of using stand

- alone fabric filters in the BSCP industry.

A representative from o ne of the fabric filter vendors (Solios Environment) agreed with industry concerns that that the lack of a dust cake would negatively impact total outlet emis sions and that the dust cake serves an important function for acid gas neutralization. He noted that the bag choices for high

- temperature applications are limited to fiberglass, with an upper temperature limit of 500°F, and that fiberglass degrades rapidly in the presence of HF acid gas. While PTFE (Teflon) fabric also has a limit of 500°F and is impervious to most acid gases, he noted that it carries a very significant price premium. He indicated that Aramid, Ryton, and P

- 84 fabrics are generally limited t o 400°F operation, but noted that these fabrics are sensitive to degradation not only by the acid gases but also the relatively high oxygen concentration in brick kiln gases ( Hansen
, 2013 )

. A representative from t he other fabric filter vendor (McGill AirCl ean) stated that a brick plant should be able to use a stand

- alone baghouse to control just filterable particulate emissions from a brick kiln. According to the vendor, if the concern is low dust load and not being able to establish a good dust cake, then bags with an expanded PTFE membrane could be used. He noted that membrane bags usually control outlet particulate emissions to very low levels and are not cost prohibitive any more. Like Solios, he stated that the base fabric for the membrane can be a

wove n fiberglass fabric, which is good for a 500°F continuous operating temperature. If there is HF in the gas stream, he said that this could damage the fiberglass, so scrubbing would be a good idea, depending on the amount of HF present. He said that acid ga ses in moderate concentrations usually do not cause fabric degradation if the bags are continuously operated above the acid gas dewpoints. Regarding operating temperatures above 500°F, he said there are some fabrics that are available for continuous operat ion at these temperatures but none with a membrane. He noted that the plant could consider flue gas cooling using a dry

- bottom evaporative cooler or a gas

- to

-

## 7 air heat exchanger to reduce the gas temperature to a level where conventional fabrics could be

us ed safely ( Childress

, 2013 b )

. A representative from t he bag fabric vendor (W.L. Gore & Associates) noted that his
company ha d done business with the brick industry before and that they have two kinds of bags that could be used for the industry: (1) high

- te mperature fiberglass bags, and (2) high

temperature PTFE (Teflon) bags. Both are rated to 500 ° F. He indicated that a ceramic style bag would be needed for temperatures above 500 ° F. He could n o t speak to the concern regarding PM loading, but did say that th ere would be no problem with PM loadings as low as 1 to 2 grains per cubic foot. He noted that HF destroys fiberglass, so PTFE bags would be needed if HF emissions

are a concern. He noted that PTFE bags, unlike fiberglass bags, are chemically inert, but ar e very expensive, about 2 to 5 times more expensive than fiberglass. He also noted that PTFE bags have high chemical and thermal resistance and would control PM but not acid gas (Holloway

, 2013 c )

. Based on the information obtained from vendors, we stated at proposal that fabric filters can potentially be an effective control option, if acid gas levels (especially HF) are already inherently low or effectively controlled and exhaust gas temperatures are not too high. While some commenters on the proposal que stioned whether stand

- alone fabric filters were feasible for the BSCP industry, they did not provide specific data to support their contention (EPA, 2015). The fabric filter costs were estimated using the DIFF cost algorithms, minus the capital cost for a dry sorbent injection system and annual cost for sorbent, and with a revised annual cost for waste disposal that excludes any acid gas control.

Activated carbon injection (ACI) and other mercury controls

. Injecting activated carbon before the particulate c ontrol device ( e.g. , fabric filter) has been demonstrated to improve the removal efficiency of mercury from a variety of combustion devices ( e.g. , waste incinerators, industrial boilers, Portland cement kilns). In the absence of a national mercury standard for the BSCP industry, there are currently no BSCP plants that use ACI. However, given the effective mercury control performance achieved in these other industries and on similar sources ( e.g. , Portland cement kilns) , we believed it prudent to explore thi s control technology as an option to reduce the mercury emissions from the BSCP industry.

To obtain information on the feasibility and cost of adding an ACI system to an existing DIFF control system for BSCP kilns, we first contacted a fabric filter vendor

, McGill AirClean. While a representative from the vendor indicated that his company does not have data on control of mercury emissions from BSCP kilns (all of the company’s mercury control experience is with municipal waste incinerators), he indicated tha t it should not be difficult or expensive to add an ACI system to an existing DIFF control system on a BSCP kiln. He said that a simple bag dump system with a blower could be used and would require little additional space at the site. He also noted that th e slight increase in inlet PM loading to the baghouse should not affect the performance of the baghouse ( Childress

, 2013 a )

. We then contacted an ACI vendor (Cabot Norit Activated Carbon) to obtain information on the feasibility and cost of installing an AC I system for control of mercury emissions from BSCP kilns. A representative from the company stated that he thought ACI would work well with BSCP kilns. He indicated that it would cost about $0.80 to $0.90/lb for carbon (Holloway

, 2013 a )

. He also indicated that, for applications using baghouses ( e.g. , a DIFF), an activated

## 8 carbon feed rate of 0.5 to 3 pounds per million actual cubic feet (lb/MMacf) is typical; he suggested using 2 lb/MMacf as a baseline ( Thompson

, 2013)

.
The model ACI costs for BSCP kilns w ere estimated based on ACI cost algorithms for a similarly

- sized combustion device, specifically hazardous waste combustors (HWCs). We used the cost algorithms in the 2005 t echnical support d ocument (TSD) for the HWC MACT

r eplacement standards (EPA

, 2005)

, using the general parameters discussed in the previous section and the carbon injection rate (2 lb/MMacf [ Thompson

, 2013] ) and carbon unit cost (average of $0.85/lb [Holloway

, 2013 a ] ) from the ACI vendor. To determine the purchased equipment cost (PEC), t he total equipment cost from the TSD was scaled to the large and small BSCP model sizes using the six

- tenths cost rule, sales tax and freight charges were added, the resulting cost was escalated to 2011 dollars, and a retrofit factor of 1.15 was applied (C E, 2011 ; EPA

, 2005)

. To determine the total direct capital costs, installation costs were added to the total PEC (EPA

, 2005)

. In addition to these direct costs, indirect costs of engineering, construction and field expense, contractor fees, startup, perfor mance test, model study, and contingencies were also estimated (EPA

, 2005)

.
The model ACI annual costs were also estimated based on the aforementioned cost algorithms (EPA

, 2005) and include the following cost items:

• Operating labor (assumed based on 1 hou r/day at $22.67/hour)

• Supervisory labor (estimated at 15% of operating labor)

• Maintenance labor (estimated based on 0.5 hour/shift and an assumed $29.94/hr wage rate)

• Maintenance materials (estimated at 5% of the PEC)

• Electricity (estimated based on hp requirements, 0.9 fan efficiency, 0.745 kW/hp, and $0.0 8 3/kWh)

• Carbon (estimated based on carbon feed rate and $0.85/lb)

• Waste disposal (estimated based on waste generated and $ 51.90 /ton waste)

• Overhead (estimated at 60% of labor and maintenance materials)

• Property taxes, insurance, and administrative charges (estimated at 4 % of total capital cost)

• Capital recovery (estimated as the product of a 0.1098 capital recovery factor and total capital cost, assuming a 15

- year equipment life and 7% interest)

In thei r public comments on the proposed rule, a number of BSCP companies led by the BIA (EPA, 2015) objected to the assumption that activated carbon injection (ACI) systems could be used in their industry. However , the commenters did not provide specific data to demonstrate the infeasibility of the emission control, which ha s been demonstrated for similar sources, e.g. , Portland cement kilns. Nonetheless, a s a result of th e se comments, we investigate d other possible technologies for limiting mercury emissions

, including , but not limited to, the following:

• Halogenated carbon sorbent s , such as brominated activated carbon from Albemarle Corp. , which is effective in reducing both elemental and oxidized
mercury (Albemarle, 2015)

.

## 9 • Reagents, such as A mended S ilicates HgX (As

- HgX TM 

## ) from Novinda , which
react s chemically with vapor

- phase mercury to create a solid compound that is effectively captured by the plant ’s PM control system (Novinda, 2015)

.

• Enhanced ACI technology, such as the Mer

- Cure TM 

## mercury reduction syste m from Alstom, which uses a unique injection methodology designed to minimize mass transfer limitations between the vapor phase mercury and carbon sorbent (Alstom, 201 4 ).

• New t echnologies

, such as M ercury C apture S ystems (MCS) from SCB International Materials, Inc. , which thermally desorb and chemically capture
mercury (Poling et al., 2015)

.

• Measurement of the mercury content of the raw material for individual plant locations (Tayler, 2015) ; if significant amounts of mercury are found at one location onsite , material found at another onsite location with a lower mercury
content c ould be used

.
Brominated ACI and AS

- HgX TM 

## are expected to be more expensive that plain ACI ( Morris , 2012 ; Novinda, 2015)

. Because Mercury Capture Systems include more complex equipment, such as thermal desorbers and gas reactors (Poling et al. 2015), compared to plain ACI, they also are expected to be more expensive. While c osts for the Mer

- Cure TM 

## system may be come less expen sive than plain ACI over time (Alstom, 2014)

, this is a new market that will likely need time to grow . The cost s to measure mercury content of individual plant locations and limit raw material collection accordingly are expected to be very site

- specific, a nd a correlation between mercury content of raw materials and mercury emissions from the stack has not yet been proven. For these reasons , we decided to use ACI costs in our cost and impacts analyses for mercury control . However, this decision is not intended to indicate that the EPA expects every BSCP owner or operator to select ACI as the technology to reduce mercury emissions. Instead, the EPA expects that each owner or operator will evaluate the available technologies, including those listed above, and determine which technology would be most appropriate for the individual kiln.

Dry limestone adsorber (DLA) . Instead of installing control equipment such as a DIFF to meet the new BSCP manufacturing standards, some BSCP facilities may choose to install less expensive DLA systems on one or more of their uncontrolled tunnel kilns to reduce facility emissions below the threshold for major sources of HAP

— 10 tons per year (tpy) or more of any single HAP or 25 tpy or more of any combination of HAP. By obtaini ng a federally enforceable limit reducing emissions below major source thresholds, t hose BSCP facilities would become synthetic area sources and would not be subject to the major source BSCP Manufacturing NESHAP

. Only those BSCP facilities that would be im pacted under the new BSCP manufacturing standards and that could reduce their HAP emissions below the major source threshold using a DLA system are expected to install such controls on their uncontrolled tunnel kilns.

Dry limestone adsorbers are designed t o control HF emissions and also provide limited control of HCl and Cl 2 

## emissions. The systems do not provide a mechanism for controlling PM emissions and would be expected to get only incidental PM control. This type of control system is already in use in the BSCP industry ( Holloway

, 2014 )

. The DLA costs were estimated using the cost algorithms from the original BSCP manufacturing rulemaking ( Shrager

, 2003), which

## 10 were generated following guidelines in the OAQPS Control Cost Manual (EPA

, 2002)

. The algorithms were updated to include more recent model parameters, including the general parameters discussed previously and the following parameters specific to DLA control devices:

• Control efficiency ( e.g. , 95% HF, 30% HCl)

• Fan horsepower (60 hp [smal l]/90 hp [large])

• Tota l horsepower for other motors (1 0 hp [small]/40 hp [large] )

• L ime stone rate ( 8 5 lb/hr [small] /120 lb/hr [large])

• L ime stone unit cost ($ 58.17 /ton)

The model DLA control efficiencies for HF, HCl, and other pollutants were estimated based on averages of data from BSCP stack tests (Raymond

, 2014 ), the limestone unit cost was estimated based on the average of data from the 2015 BIA survey (Regina, 2015), while t he values of the other model D LA parameters were determined based on averages of i ndustry responses to the 2008 BSCP survey ( Holloway

, 2014 )

.

T he model D LA capital costs were estimated by taking D LA capital cost data from industry respon ses to the 2008 BSCP survey ( Holloway

, 2014 ), escalating the costs to 2011 dollars using the CEPCI (CE

, 2011), scaling the costs to the large and small model sizes using the six

- tenths cost rule (see Equation 3), taking the average of the scaled costs for each model size, and rounding the results to three significant figures. These costs were then adjus ted by a factor of 1.07 0.5 

## to equalize the net present value (NPV).

The model D LA annual costs were estimated based on the aforementioned cost algorithms, and include the following cost items:

• Operating labor (assumed to be twice the maintenance labor hours at $22.67/hr)

• Supervisory labor (estimated at 15% of operating labor)

• Maintenance labor (estimated based on 0.75 hr/shift from BSCP survey responses and an assumed $24.94/hr wage rate)

• Maintenance materials (estimated at 100% of maintenance labor)

• El ectricity (estimated based on hp requirements, 0.745 kW/hp, and $0.0 8 3/kWh)

• Lime stone (estimated based on lime stone rate and $ 58.17 /ton lime stone unit cost)

• Waste disposal (estimated based on waste generated and $ 51.90 /ton waste)

• Overhead (estimated at 60% of labor and maintenance materials)

• Property taxes, insurance, and administrative charges (estimated at 4 % of total capital cost)

• Capital recovery (estimated as the product of a 0.0944 capital recovery factor and total capital cost)

Summary . Table 1 prese nts the model costs for the DIFF, fabric filter, ACI , and DLA control options discussed above for the small and large BSCP control devices. For additional information, see Appendix B and C at the end of this memorandum.

## 11 Table 1. Summary o f Control Option M odel Costs Control Option Cost p arameters SCD LCD
Install new DIFF Total capital investment $ 2,000,000 $ 2,730,000
Total annual cost $ 697,321 $ 871,337
Install new fabric filter Total capital investment $ 1,200,000 $ 1,500,000
Total annual cost $ 503,074 $ 579,392 Replace with DIFF Total capital investment $ 2,800,000 $ 3,820,000
Total annual cost $ 804,836 $ 1,017,826 Retrofit ACI system
MACT floor Total capital investment $102,224 $146,697
Total annual cost $ 81,307 $ 105,763 Beyond the floor Total capital investment $102,224 $146,697
Total annual cost $ 92,050 $ 124,179
Install DLA Total capital investment $ 1,096,473 $ 1,489,548
Total annual cost $ 358,556 $ 459,886



## IV. Model Impacts

This section discusses the methodology and assumptions used to estimate the model environmental and energy impacts associated with new or retrofit emission control devices that BSCP plants are e xpected to install in order to comply with the new standards for the BSCP industry. The model impacts parameters and calculations are presented in Appendix D

. The model impacts tables for new and retrofit control device s are presented in Appendices E and F, respectively.

A. Emission Reductions

Model emission reductions were estimated for the major pollutants emitted from BSCP
t unnel kilns, including both HAP (HF, HCl, Cl 2 

## , and HAP metals) and non

- HAP (PM and SO 2 

## ). In most cases, we were able to determine the model emission reductions (tpy) by multiplying the model uncontrolled emission factors (lb/ton) in Appendix A by th e model production rate (tph) and operating hours (hr/yr) in Appendix A and the appropriate control efficiency (%) in Appendix D, and dividing by a conversion factor of 2,000 lb/ton.

B. Energy Impacts

To determine the annual amount of electricity (in kilow att

- hours per year [kWh/yr]) needed to power the control device, the horsepower requirements (hp) of the control device were multiplied by a conversion factor of 0.745 kW/hp and the annual operating hours (hr/yr). The annual amount of energy (in million Br itish thermal units per year [MMBtu/yr]) needed to generate this electricity was then determined by dividing the electricity requirements (kWh/yr) by the nationwide average power plant efficiency (35 percent) and multiplying by a con version factor of 3,415 British thermal units per kilowatt hour ( Btu/kWh )

.

## 12 The efficiency for each type of power plant was determined by dividing the h eat content of electricity (3,415 Btu/kWh) by the heat rate for each type of plant ( 10,415 Btu/kWh for coal; 8,185 Btu/kWh for n atural gas; 10,452 Btu/kWh for nuclear power; and 9,756 Btu/kWh for renewable energy). The nationwide average power plant efficiency was determined as a weighted average of these power plant efficiencies, based on the projected fuel mix for 2015 from Version 3.0 of EPA’s Integrated Planning Model (IPM) , which is a forecast model of the U.S. electric power sector (EPA

, 2011)

. The projected fuel mix is 53 percent coal, 22 percent natural gas/other, 17 percent nuclear, and 8 percent renewable/hydroelectri c (EPA

, 2011)

.
C. Secondary Air Emissions

Once the model energy impacts were determined, the associated model secondary air emissions were estimated. Secondary emissions typically include the criteria air pollutant emissions

— PM, carbon monoxide (CO), nitro gen oxides (NO X 

## ), and SO 2



## — that result from the generation of electricity used to operate the control devices. For purposes of this analysis, the electricity was assumed to be purchased from offsite power plants. The secondary emissions were estimated by mu ltiplying emission factors for the pollutants by the energy impacts, assuming a specific mix of fuels to generate the needed electricity. (EPA

, 2011)

We used a variety of information sources to obtain the emission factors used to estimate the secondary emissions . For natural gas combustion , we used emission factors (in pound s per cubic foot [lb/ft 3 

## ] of natural gas) from the AP

- 42 chapter on natural gas combustion to estimate the secondary emissions for PM, CO, NO X 

## , and SO 2 

## (EPA

, 1998a)

. We used the AP

- 42 conversion factor of 1,020 Btu/ft 3 

## of natural gas to convert the emission factors to pounds per million British thermal units ( lb/MMBtu ) to facilitate estimat ing the secondary emissions for these pollutants from natural gas (EPA

, 1998a)

.

For solid fuel (coal) combustion, we used emission limits (in lb/MMBtu) from the new source performance standards (NSPS) for utility plants (40 CFR part 60, subpart Da ; 2006 CFR edition ) to estimate the secondary emissions for PM and SO 2 

## (EPA

, 2006 )

. We used emis sion fac tors (in lb/ton coal) from the AP

- 42 chapter on coal combustion to estimate the secondary emissions for NO X 

## and CO ; we specifically used the AP

- 42 emission factors for bituminous/subbituminous coal combustion/spreader stoker s (EPA

, 1998b)

. The NO X 

## emission factor was based on an average of the AP

- 42 emission factors for spreader stoker type boilers burning bituminous ( 11 lb/ton ) and subbituminous ( 8.8 lb/ton ) coal. We used the AP

- 42 conversion factor of 13,000 Btu/lb of coal to facilitate estimating the sec ondary emissions for NO X 

## and CO from coal (EPA

, 1998b)

. All secondary air impacts were attributed to the combustion of coal, natural gas, or “other” fuels at offsite power plants. We attributed no secondary air impacts to nuclear, hydroelectric, o r renewable energy generation. The secondary air impacts for “other” fuels were assumed to be equi valent to those for natural gas.

## 13 D. Solid Waste and Wastewater Impacts

We estimated the solid waste impacts by calculating the amount of material captured by the control device. The material captured by the fabric filter includes just PM from the kiln, while the material captured by the DIFF includes:

• R eaction products from the reaction of the lime with the acid gases

,

• Unreacted lime, and

• Particulate matter fro m the kiln.

In the absence of information, the amount of solid waste captured by a spray dryer/electrostatic precipitator (ESP) (the control system currently employed at one BSCP facility) was assumed to be the same as that captured by a DIFF, since both e mission control systems include a combination of acid gas and PM controls, unlike a stand

- alone fabric filter (which captures only PM) or a DLA (which captures mostly acid gases, primarily HF).

We e stimated the wastewater impacts associated with using a sp ray dryer/ESP by calculating the amount of water usage for the spray dryer, using the equation shown in Appendix E. There are no wastewater impacts for the other control devices.

E. Model Impacts for Control Options

Model impacts were estimated for the fol lowing control scenarios and are presented in the appendix tables cited below:

• Installation of new DIFF on uncontrolled kiln (see Table E

- 1)

• Installation of new fabric filter on uncontrolled kiln (where acid gas levels and exhaust gas temperatures are low) (see Table E

- 2)

• Installation of fabric filter after an existing acid gas control ( e.g. , DLA) (see Table E

- 2)

• Installation of DLA on uncontrolled kiln(s) to become synthetic area source (see Table E

- 3)

• Installation of ACI system to an existing control sys tem ( e.g. , DIFF) (see Table F

- 1 )

• Replacement of existing DLA with a new DIFF (see Table F

- 2)

• Replacement of existing spray dryer/ESP with a new DIFF (see Table F

- 3)

• Replacement of existing DIFF with a new, more efficient DIFF (see Table F

- 4)

To estimate th e incremental impacts for replacement control devices, the impacts associated with baseline controls were subtracted from the impacts associated with new controls. For DLA and spray dryer/ESP controls being replaced with a DIFF, the incremental impacts inc lude the emission reductions, energy impacts, secondary air impacts, solid waste impacts, and wastewater impacts (spray dryer/ESP controls only). For those cases where a facility replaces an existing DIFF with a new, more efficient DIFF to comply with the new standards , we assumed no change in energy requirements or the associated secondary emissions, but we estimated the difference in emissions and solid waste impacts that would accompany the improved control of PM and acid gases.

## 14 Because we had no control efficiency data for spray dryer/electrostatic precipitator (ESP), we used stack test data for the kilns equipped with this emission control as the baseline emissions and subtracted the baseline emissions for the DIFF to determine the incremental emissions reduction from replacing a spray dryer/ESP with a DIFF.

Tables 2 through 4 present the model impacts for the DIFF, fabric filter, and ACI control installation/retrofit options and control replacement options discussed above for the small and large BSCP co ntrol devices. For additional information, see the aforementioned tables in Appendices E and F at the end of this memorandum.

Table 2a. Summary of Model Emission Reductions for Control Installation/Retrofit Options

Control option Pollutant Emissions reductions, tpy SCD LCD
Install new DIFF Hydrogen fluoride 18.13 38.85 Hydrogen chloride 2.06 4.42 Chlorine 0.09 0.20
HAP metals 0.103 0.220
Particulate matter 9.33 19.99 Sulfur dioxide 48.26 103.42
Install fabric filter HAP metals 0.103 0.220
Particulate matter 9.33 19.99
Install new DLA Hydrogen fluoride 17.61 37.73 Hydrogen chloride 0.74 1.59 Chlorine 0.04 0.10
HAP metals 0.025 0.053
Particulate matter 2.27 4.86 Sulfur dioxide 11.88 25.47 Retrofit ACI system
MACT floor Mercury 0.0016 0.0035 Beyond the floor Mercury 0.0018 0.0039

## 15 Table 2b. Summary of Model Emission Reductions for Control Replacement Options

Control option Pollutant Net e missions reductions, tpy SCD LCD Replac e d ry l imestone a dsorber with n ew DIFF Hydrogen fluoride 0.82 1.76 Hydrogen chloride 1.32 2.83 Chlorine 0.05 0.11
HAP metals 0.081 0.173
Particulate matter 7.35 15.74 Sulfur dioxide 36.38 77.96 Replac e s pray dryer/ESP with n ew DIFF Hydrogen fluoride 20.96 41.91 Hydrogen chloride 4.72 9.38 Chlorine 0.64 1.28
HAP metals 0.00 0.00
Particulate matter 0.00 0.00 Sulfur dioxide 0.73 1.56 Replac e e xisting DIFF with n ew,
more e fficient DIFF Hydrogen fluoride 0.27 0.59 Hydrogen chloride 0.03 0.07 Chlorine 0.001 0.003
HAP metals 0.024 0.051
Particulate matter 2.18 4.68 Sulfur dioxide 0.73 1.56



### Table 3a. Summary of Model Energy and Solid Waste Impacts for Control Installation/Retrofit Options Control option Type of impact SCD LCD
Install new DIFF Energy impacts, MMBtu/yr 11,544 14,109 Solid waste impacts, tpy 447 678
Install fabric filter Energy impacts, MMBtu/yr 11,544 14,109 Solid waste impacts, tpy 9.33 19.99
Install new DLA Energy impacts, MMBtu/yr 4,489 8,337 Solid waste impacts, tpy 367 513 Retrofit ACI system
MACT floor Energy impacts, MMBtu/yr 371 621 Solid waste impacts, tpy 12.26 20.15 Beyond the floor Energy impacts, MMBtu/yr 371 621 Solid waste impacts, tpy 18.40 30.66

## 16 Table 3b. Summary of Model Energy, Solid Waste, and Wastewater Impacts for Control Replacement Options

Control option Type of impact Increase in impacts 1


### SCD LCD Replac e d ry l imestone a dsorber with n ew DIFF Energy impacts, MMBtu/yr 7,055 5,772 Solid waste impacts, tpy 80.10 165 Replac e s pray d ryer/ESP wi th n ew DIFF Energy impacts, MMBtu/yr

- 9,299

- 27,577 Solid waste impacts, tpy 8.66 14.43 Wastewater impacts, gpy

- 2,281

- 4,563 Replac e e xisting DIFF with new,
m ore e fficient DIFF Energy impacts, MMBtu/yr 0 0 Solid waste impacts, tpy 8.66 14.43

1 A negative increase in impacts would be equivalent to a reduction in impacts.



### Table 4a. Summary of Model Secondary Impacts for Control Installation/Retrofit Options

Control option Secondary pollutant 1 

### Secondary air impacts, tpy SCD LCD
Install new DIFF Particulate matter 0.09 0.10
PM 2.5 

### 0 .029 0.035 Carbon monoxide 0.14 0.18 Nitrogen oxides 1.1 4 1.39 Sulfur dioxide 3.33 4.06
Install fabric filter Particulate matter 0.09 0.10
PM 2.5 

### 0.029 0.035 Carbon monoxide 0.14 0.18 Nitrogen oxides 1.14 1.39 Sulfur dioxide 3.33 4.06
Install new DLA Particulate matter 0.03 0.06
PM 2.5 

### 0.011 0.021 Carbon monoxide 0.06 0.10 Nitrogen oxides 0.44 0.82 Sulfur dioxide 1.29 2.40 Retrofit ACI system (MACT floor/beyond the floor) Particulate matter 0.003 0.005
PM 2.5 

### 0.0009 0.0015 Carbon monoxide 0.005 0.008 Nitrogen oxides 0.04 0.06 Sulfur dioxide 0.11 0.18

1 PM 2.5 = PM with p articles less than 2.5 micrometers in diameter

.

## 17 Table 4b. Summary of Model Secondary Impacts for Control Replacement Options

Control option Secondary pollutant 2 

### Increase in s econdary air impacts, tpy 1


### SCD LCD Replac e d ry l imestone adsorber with n ew DIFF Particulate matter 0.05 0.04
PM 2.5 

### 0.017 0.014 Carbon monoxide 0.09 0.07 Nitrogen oxides 0.70 0.57 Sulfur dioxide 2.03 1.66 Replac e s pray dryer/ESP with n ew DIFF Particulate matter

- 0.07

- 0.20
PM 2.5 

### - 0.023

- 0.068 Carbon monoxide

- 0.12

- 0.34 Nitrogen oxides

- 0.92

- 2.73 Sulfur dioxide

- 2.68

- 7.94 Replac e existing DIFF with n ew,
m ore e fficient DIFF Particulate matter 0 0
PM 2.5 

### 0 0 Carbon monoxide 0 0 Nitrogen oxides 0 0 Sulfur dioxide 0 0

1 A negative increase in secondary air impacts would be equivalent to a reduction in secondary air impacts.

2 PM 2.5 = PM with p articles less than 2.5 micrometers in diameter

.



## V. References

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## : Mercury reduction system

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at: http://www.bls.gov/oes/2011/may/naics4_327100.htm

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## 18 Childress, J. 2013b. “RE: From McGill AirClean Web Site.” E

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## 19 Holloway, T. 2013 b

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.

## Appendix A

Model Parameters

## A

- 2 Table A

- 1. General Parameters for BSCP Model Control Devices

Parameters SCD LCD Footnotes Process parameters
Production rate, ton/hr 7.0 15.0 1 Operating hours, hr/yr 8,760 8,760 2 Exhaust flow, acfm 23,100 38,700 3 Unit costs Electricity cost, $/kwh 0.0 8 3 0.0 8 3 1 Waste disposal cost, $/ton 51.90 51.90 2 Operator wage rate, $/hr 22.67 22.67 4 Maintenance wage rate, $/hr 24.94 24.94 5 Capital recovery factor

-- system 0.0944 0.0944 6 Molecular weights
HF 20 20 HCl 36.5 36.5 SO 2 

### 64 64 CaF 2 

### 78 78 7 CaCl 2 

### 111 111 7 CaSO 3 

### 120 120 7 Ca(OH) 2 

### 74 74 8 Uncontrolled emissions, lb/ton
HF 0. 594 0. 594 3 HCl 0.08 08 0.08 08 3 Cl 2 

### 0.00346 0.00346 3
Non

- Hg HAP Metals 0.0035 6 0.0035 6 9
PM 0.32 4 0.32 4 3 SO 2 

### 3.23 3.23 3 Uncontrolled emissions, lb/hr
HF 4. 16 8.91 10 HCl 0.56 6 1.2 1 10 Cl 2 

### 0.024 2 0.05 19 10
Non

- Hg HAP Metals 0.02 49 0.05 34 10
PM 2.2 7 4.8 6 10 SO 2 

### 22.6 48.5 10 1. Average from section 114 survey responses

. 2. Average from 2015 BIA survey data.
3 . Average from test data

. 4 . M ean hourly wage, from Bureau of Labor Statistics, May 2011 National Industry

- Specific Occupational

Employment and Wage Estimates, NAICS 32710 0, Industrial Engineering Technician. Website: http://www.bls.gov/oes/2011/may/naics4_327100.htm

. Wage rates from Bureau of Labor Statistics were used because they are more conservative than those provided by section 114 survey respondents.
5 . 10 percent higher than operator rate

. 6 . Based on equipment life of 20 years and 7 percent interest.
7

. Reaction product ; CaF 2 = c alcium fluoride ; CaCl 2 = c alcium chloride ; CaSO 3 = c alcium sulfite

. 8 . Hydrated lime

. 9 . Assume 1.1 percent of PM

. 10 . Calculated from lb/ton times production rate

.

## Appendix B

In stallation Model Costs

## B

- 2 Table B

- 1. Model Costs to Install New DIFF

Parameters SCD LCD Footnotes Control efficiency, percent
HF 99.5% 99.5% 1 HCl 83 .3 % 83 .3 % 2 Cl 2 

### 89 .3 % 89 .3 % 3 Non

- Hg HAP Metals 94% 94% 4
PM 94% 94% 1 SO 2 

### 4 8.7 % 4 8.7 % 5 Design and operating parameters Fan hp 150 190 6 Total hp for other motors 30 30 6 Hydrated lime, fraction of stoichiometric amount 2.65 1.79 7 Operator labor, hr/shift 2.5 2.5 8 Maintenance labor, hr/shift 1.25 1.25 6 Bag life, yr 5 5 6 Gas

- to

- cloth ratio (gross), ft/min 3.4 3.4 6 Bag area, ft 2 

### 28 28 6 Compressed air, ft 3 

### /1,000 ft 3 

### 0.9 0.9 6 Time to replace bags, hr/bag 2.25 2.25 6 Added cooling air, ft 3 

### /min 0 0 9 Calculated parameters Hydrated lime makeup, lb/hr 91.4 132.0 Reaction products, lb/hr 29. 4 63. 1 10 Reacted lime, lb/hr 20.9 44. 7 Particulate matter, lb/hr 2.1 4. 6 Waste, lb/hr 102. 1 154. 9 11 Cost factors Hydrated lime, $/ton 160 160 6 Bag fabric cost, $/ft 2 

### 8.15 8.15 6 Compressed air, $/1,000 ft 3 

### 0.363 0.363 12 Capital recovery factor

-- bags 0.244 0.244 13 Capital costs Total capital investment 2,000,000 2,730,000 14
Annual costs Operating labor 62,059 62,059 Supervisory labor 9,309 9,309 15
Maintenance labor 34,133 34,133
Maintenance materials 34,133 34,133 16 Electricity 97,501 119,168 17
Lime 64,018 92,471 Compressed air 3,967 6,645 Annualized replacement bags 13,505 22,625 Annualized bag replacement labor 3,320 5,563 18 Cage replacement 19

## B

- 3 Parameters SCD LCD Footnotes
Waste disposal 23,199 35,209 Overhead 83,780 83,780 20 Administrative charges 40,000 54,600 21 Property taxes 20,000 27,300 22
Insurance 20,000 27,300 22 Capital recovery 188,399 257,044 Total annual cost, $/yr 697,321 871,337 1. Average from test data with better efficiency than baseline

. 2. Based on ratio of enhanced HF reduction and baseline HCl reduction

. 3. Based on ratio of enhanced HF reduction and baseline Cl 2 reduction

. 4. Assume same as PM

. 5. Based on ratio of enhanced HF reduction and b aseline SO 2 reduction

. 6. Average from section 114 survey responses

. 7. Assume hydrated lime is 2.6 4 /1.7 8 times the stoichiometric amount needed to get additional control re baseline

(from 98% to 99.5%)

. 8. Assume 2 times maintenance labor ( EPA, 2002 )

. 9. Assume none

. 10. CaF 2 (c alcium fluoride ), CaCl 2 (c alcium chloride ), and CaSO 3 (c alcium sulfite ). 11. Inlet lime minus reacted lime plus reaction products and PM

. 12. Average from 2015 BIA survey data

. 13. Based on equipment life of 5 years and 7 percent in terest

. 14. Average of costs from section 114 survey responses scaled using 6/10 rule (based on acfm), escalated to 2011

dollars, and rounded

. 15. 15 percent of operator labor

. 16. 100 percent of maintenance labor

. 17. Based on conversion factor of 0.745 kW/hp

. 18. Performed by maintenance personnel

. 19. Maybe no need to replace

. 20. 60 percent of labor and maintenance materials

. 21. 2 percent of TCI

. 22. 1 percent of TCI

.

## B

- 4 Table B

- 2. Model Costs to Install New Fabric Filter

Parameters SCD LCD Footnotes Control efficiency, percent
Non

- Hg HAP Metals 94% 94% 1
PM 94% 94% 2 Design and operating parameters Fan hp 150 190 3 Total hp for other motors 30 30 3 Operator labor, hr/shift 2.5 2.5 4 Maintenance labor, hr/shift 1.25 1.25 3 Bag life, yr 5 5 3 Gas

- to

- cloth ratio (gross), ft/min 3.4 3.4 3 Bag area, ft 2 

### 28 28 3 Compressed air, ft 3 

### /1,000 ft 3 

### 0.9 0.9 3 Time to replace bags, hr/bag 2.25 2.25 3 Added cooling air, ft 3 

### /min 0 0 5 Calculated parameters Waste, lb/hr 2.1 4. 6 6 Cost factors Bag fabric cost, $/ft 2 

### 8.15 8.15 3 Compressed air, $/1,000 ft 3 

### 0.363 0.363 7 Capital recovery factor

-- bags 0.244 0.244 8 Cost of dry injection system 800,907 1,230,278 9 Capital costs Total capital investment 1,200,000 1,500,000 10
Annual costs Operating labor 62,059 62,059 Supervisory labor 9,309 9,309 11 Maintenance labor 34,133 34,133
Maintenance materials 34,133 34,133 12 Electricity 97,501 119,168 13 Compressed air 3,967 6,645
Annualized replacement bags 13,505 22,625 Annualized bag replacement labor 3,320 5,563 14 Cage replacement 0 0 15 Waste disposal 484 1,038 Overhead 83,780 83,780 16 Administrative charges 24,000 30,000 17 Property taxes 12,000 15,000 18
Insurance 12,000 15,000 18 Capital recovery 112,884 140,940 Total annual cost, $/yr 503,074 579,392

1. Assume same as PM

. 2. Average from test data with better efficiency than baseline

. 3. Average from section 114 survey responses

. 4. Assume 2 times maintenance labor ( EPA, 2002 )

.

## B

- 5 5. Assume none

. 6. Particulate matter

. 7. Average from 2015 BIA survey data

. 8. Based on equipment life of 5 years and 7 percent interest

. 9. Based on cost equations in the June 19, 2009 memorandum Revised Baseline Oper ating Costs for Existing HMIWI

, in Docket ID No. EPA

- HQ

- OAR

- 2006

- 0534 for the hospital/medical/infectious waste incinerator ( HMIWI ) rule

. 10. Average of costs from section 114 survey responses scaled using 6/10 rule (based on acfm), subtracted cost of

dry injec tion system, escalated to 2011 dollars, and rounded

. 11. 15 percent of operator labor

. 12. 100 percent of maintenance labor

. 13. Based on conversion factor of 0.745 kW/hp

. 14. Performed by maintenance personnel

. 15. Maybe no need to replace

. 16. 60 percent of labor and maintenance materials

. 17. 2 percent of TCI

. 18. 1 percent of TCI

.

## B

- 6 Table B

- 3. Model Costs to Install New DLA

Parameters SCD LCD Footnotes Control efficiency, percent
HF 95% 95 % 1 HCl 3 0 % 30 % 1 Cl 2 

### 42 % 42 % 1 Non

- Hg HAP Metals 20 % 20 % 2
PM 20 % 20 % 1 SO 2 

### 12 % 12 % 1 Design and operating parameters Fan hp 6 0 90 3 Total hp for other motors 1 0 4 0 3
L ime stone, lb/hr 8 5 1 20 3 Operator labor, hr/shift 1 .5 1 .5 4 Maintenance labor, hr/shift 0.7 5 0.7 5 3 Calculated parameters Reaction products, lb/hr 13. 2 28. 3 5 Reacted lime stone , lb/hr 14. 5 3 1.1 Particulate matter, lb/hr 0. 07 0. 07 Waste, lb/hr 83. 7 117. 2 6 Cost factors
L ime stone , $/ton 58.17 58.17 7 Factor to equalize NPV 1.034408 1.034408 8 Capital costs Total capital investment 1,096,473 1,489,548 9
Annual costs Operating labor 37,235 37,235 Supervisory labor 5,585 5,585 10 Maintenance labor 20,480 20,480
Maintenance materials 20,480 20,480 11 Electricity 37,917 70,418 12
Lime stone 21,657 30,574 Waste disposal 19,035 26,644 13 Overhead 50,268 50,268 14 Administrative charges 21,200 28,800 15 Property taxes 10,600 14,400 16 Insurance 10,600 14,400 16 Capital recovery 103,499 140,603 Total annual cost, $/yr 358,556 459,886 1. Average from test data

. 2 . Assume same as PM

. 3 . Average from section 114 survey responses

. 4 . Assume 2 times maintenance labor ( EPA, 2002 )

. 5

. CaF 2 (c alcium fluoride ), CaCl 2 (c alcium chloride ), and CaSO 3 (c alcium sulfite )

. 6 . Inlet lime stone minus reacted lime stone plus reaction products and PM

. 7. Average from 2015 BIA survey data.

## B

- 7 8 . Factor to equalize the net present value (NPV) = 1.07 0.5 = 1.034408
9 . Average of costs from section 114 survey responses scaled using 6/10 rule (based on acfm), escalated to 2011

dollars, and rounded , then multiplied by the NPV factor

. 10 . 15 percent of operator labor

. 11 . 100 percent of maintenance labor

. 1 2 . Based on conversion factor of 0.745 kW/hp

. 1 3 . Some fa cilities have minimal waste disposal costs.
1 4 . 60 percent of labor and maintenance materials

. 1 5 . 2 percent of TCI

. 1 6 . 1 percent of TCI

.

## Appendix C

Retrofit /Replacement Model Costs

## C

- 2 Table C

- 1. Model Costs to Replace Existing Control Device with DIFF

Parameters SCD LCD Footnotes Control efficiency, percent
HF 99.5% 99.5% 1 HCl 83 .3 % 83 .3 % 2 Cl 2 

### 89 .3 % 89 .3 % 3 Non

- Hg HAP Metals 94% 94% 4
PM 94% 94% 1 SO 2 

### 4 8.7 % 4 8.7 % 5 Design and operating parameters Fan hp 150 190 6 Total hp for other motors 30 30 6 Hydrated lime, fraction of stoichiometric amount 2.65 1.79 7 Operator labor, hr/shift 2.5 2.5 8 Maintenance labor, hr/shift 1.25 1.25 6 Bag life, yr 5 5 6 Gas

- to

- cloth ratio (gross), ft/min 3.4 3.4 6 Bag area, ft 2 

### 28 28 6 Compressed air, ft 3 

### /1,000 ft 3 

### 0.9 0.9 6 Time to replace bags, hr/bag 2.25 2.25 6 Added cooling air, ft 3 

### /min 0 0 9 Calculated parameters Hydrated lime makeup, lb/hr 91.4 132.0 Reaction products, lb/hr 29. 4 63. 1 10 Reacted lime, lb/hr 20.9 44. 7 Particulate matter, lb/hr 2.1 4. 6 Waste, lb/hr 102. 1 154. 9 11 Cost factors Hydrated lime, $/ton 160 160 6 Bag fabric cost, $/ft 2 

### 8.15 8.15 6 Compressed air, $/1,000 ft 3 

### 0.363 0.363 12 Capital recovery factor

-- bags 0.244 0.244 13 Retrofit factor 1.4 1.4 14 Capital costs Total capital investment 2,800,000 3,820,000 15
Annual costs Operating labor 62,059 62,059 Supervisory labor 9,309 9,309 16
Maintenance labor 34,133 34,133
Maintenance materials 34,133 34,133 17 Electricity 97,501 119,168 18
Lime 64,018 92,471 Compressed air 3,967 6,645 Annualized replacement bags 13,505 22,625 Annualized bag replacement labor 3,320 5,56 3 19

## C

- 3 Parameters SCD LCD Footnotes Cage replacement 0 0 20 Waste disposal 23,199 35,209 Overhead 83,780 83,780 21 Administrative charges 56,000 76,400 22 Property taxes 28,000 38,200 23 Insurance 28,000 38,200 23 Capital recovery 263,913 359,932 Total annual cost, $/yr 804,836 1,017,826 1. Average from test data with better efficiency than baseline

. 2. Based on ratio of enhanced HF reduction and baseline HCl reduction

. 3. Based on ratio of enhanced HF reduction and baseline Cl 2 reduction

. 4. Assume same as PM

. 5. Based on ratio of enhanced HF reduction and baseline SO 2 reduction

. 6. Average from section 114 survey responses

. 7. Assume hydrated lime is 2.65/1.79 times the stoichiometric amount needed to get additional control re baseline

(from 98% to 99.5%)

. 8. Assume 2 times maintenance labor ( EPA, 2002 )

. 9. Assume none.
10. CaF 2 (c alcium fluoride ), CaCl 2 (c alcium chloride ), and CaSO 3 (c alcium sulfite )

. 11. Inlet lime minus reacted lime plus reaction products and PM

. 12. Average from 2015 BIA survey data

. 13. Based on equipment life of 5 years and 7 percent interest

. 14. Average for various control devices ( EPA, 2002 )

. 15. Average of costs from section 114 survey responses scaled using 6/10 rule (based on acfm), escalated to 2011

dollars, multiplied by retrofit cost fac tor, and rounded

. 16. 15 percent of operator labor

. 17. 100 percent of maintenance labor

. 18. Based on conversion factor of 0.745 kW/hp

. 19. Performed by maintenance personnel

. 20. Maybe no need to replace

. 21. 60 percent of labor and maintenance materials

. 22. 2 percent of TCI

. 23. 1 percent of TCI

.

## C

- 4 Table C

- 2 . Model Costs to Retrofit ACI System to Existing Control Device

Parameters MACT Floor Beyond the Floor
Foot notes SCD LCD SCD LCD Design and operating parameters Carbon injection rate (lb/MMft 3 

### ) [CIR] 2 2 3 3 1 Injection blower fan power (hp) [Power fan 

### ] 5.2 8.7 5.2 8.7 2,3 Projected equipment life (yrs) [n] 15 15 15 15 2 Interest rate (%) [i] 7 7 7 7 Calculated parameters Carbon feed rate (lb/hr) [CFR] 2.8 4.6 4.2 7.0 4 Cost factors Carbon unit cost ($/lb) [CC] 0.85 0.85 0.85 0.85 5 Escalation factor [EF] 1.78 1.78 1.78 1.78 2, 6,7 Capital recovery factor [CRF] 0.1098 0.1098 0.1098 0.1098 2,8 Retrofit factor [RF] 1.15 1.15 1.15 1.15 2 Direct capital costs Purchased equipment costs Total equipment [TEC] (see Note) 24,294 34,864 24,294 34,864 2 ,9 Sales tax 729 1,046 729 1,046 2 ,10 Freight 1,215 1,743 1,215 1,743 2 ,11 Purchased equipment with tax and freight 26,238 37,653 26,238 37,653 2 ,12 Purchased equipment with escalation 46,784 67,138 46,784 67,138 2 ,13 Purchased equipment with retrofit factor [PEC] 53,802 77,209 53,802 77,209 2 ,14
Installation cost [IC] 16,141 23,163 16,141 23,163 2 ,15 Total direct costs [TDC] 69,942 100,371 69,942 100,371 2 ,16 Indirect capital costs Engineering 10,760 15,442 10,760 15,442 2 ,17 Construction and field expense 10,760 15,442 10,760 15,442 2 ,17 Contractor fees 5,380 7,721 5,380 7,721 2 ,18 Start

- up 538 772 538 772 2 ,19 Performance test 538 772 538 772 2 ,19 Model study 1,076 1,544 1,076 1,544 2 ,20 Contingencies 3,228 4,633 3,228 4,633 2 ,21

## C

- 5 Parameters MACT Floor Beyond the Floor
Foot notes SCD LCD SCD LCD Total indirect costs [TIC] 32,281 46,325 32,281 46,325 2 ,22 Total capital cost Total capital investment [TCI] 102,224 146,697 102,224 146,697 2 ,23
Annual costs Operating labor 8,275 8,275 8,275 8,275 2 ,24 Supervisory labor 1,241 1,241 1,241 1,241 2 ,25
Maintenance labor 13,653 13,653 13,653 13,653 2 ,26
Maintenance materials 2,690 3,860 2,690 3,860 2 ,27 Electricity cost 3,135 5,245 3,135 5,245 2 ,28 Carbon cost 20,849 34,252 31,273 52,122 2 ,29 Solid waste disposal cost 637 1,046 955 1,591 2 ,30 Overhead 15,515 16,218 15,515 16,218 2 ,31 Administrative charges 2,044 2,934 2,044 2,934 2 ,32 Property tax 1,022 1,467 1,022 1,467 2 ,33
Insurance 1,022 1,467 1,022 1,467 2 ,33 Capital recovery 11,224 16,107 11,224 16,107 2 ,34 Total annual cost 81,307 105,763 92,050 124,179 2 ,35

Note : Total equipment includes storage silo, feed bin, gravimetric feeders, pneumatic conveyor, and injection ports.

Footnotes : 1. Thompson , 2013. Suggested carbon concentration of 2 lb/MMft 3

. 2. EPA, 2005, Appendix J. 3. Scaled HWC hp estimate using ratio of exhaust flow rates: (15 hp) x Q / (66,870.6 acfm)

. 4. Equal to CIR / 1E6 x exhaust flow x (60 min/hr)

. 5. Holloway , 2013 a . Indicated carbon price would be $0.80 to $0.90/lb. Used average of $0.85/lb. 6. Escalating costs from 2004 (HWC) to 2011 (BSCP) using the following factors: (HWC escalation factor, 1.1319 x 1.064) x (BSCP escalation factor, 1.4805)

. 7. Chemical Engineering Plant Cost Index

. 8. Equal to = [i x (1 + i) n ] / [(1 + i) n

- 1], where i = 7 percent interest and n = 15

- year equipment life

. 9. Equal to 90,000 x (exhaust flow/150,000) 0.7

. 10. Equal to 0.03 x TEC

. 11. Equal to 0.05 x TEC

.

## C

- 6 12. Equal to TEC + (sales tax) + (freight)

. 13. Equal to EF x (purchased equipment with tax and freight)

. 14. Equal to RF x (purchased equipment with escalation)

. 15. Equal to 0.3 x PEC

. 16. Equal to PEC + IC

. 17. Equal to 0.2 x PEC

. 18. Equal to 0.1 x PEC

. 19. Equal to 0.01 x PEC

. 20. Equal to 0.02 x PEC

. 21. Equal to 0.06 x PEC

. 22. Equal to sum of indirect costs

. 23. Equal to TDC + TIC

. 24. Equal to (1 hr/d) x operating hr/yr / (24 hr/d) x operator wage rate ($/hr)

. 25. Equal to 0.15 x (operator labor cost)

. 26. Equal to (0.5 hr/shift) x (3 shifts/d) x operating hr/yr / (24 hr/d) x maintenance wage rate ($/hr)

. 27. Equal to 0.05 x PEC

. 28. Equal to Power fan / (1.34 hp/kW) / (0.9 Efficiency fan ) x operating hr/yr x electricity unit cost ($/kWh)

. 29. Equal to CFR x operating hr/yr x carbon unit cost ($/lb)

. 30. Equal to CFR x operating hr/yr / (2000 lb/ton) x waste disposal unit cost ($/ton )

. 31. Equal to 0.6 x (operating labor cost + maintenance cost)

. 32. Equal to 0.02 x TCI

. 33. Equal to 0.01 x TCI

. 34. Equal to CRF x TCI

. 35. Equal to sum of annual costs

.

## Appendix D

Model Impacts Equations

## D

- 2 Table D

- 1. Equations Used to Estimate Model Energy and Secondary Impacts

Parameters Value Notes, units, and equations Energy impacts
Heat factors Heat content of electricity (HC elec 

### ) 3,415 Btu/kWh

Heat rate

Coal (HR coal 

### ) 10,415 Btu/kWh Natural gas (HR gas 

### ) 8,185 Btu/kWh Nuclear power (HR nuclear 

### ) 10,452 Btu/kWh Renewable energy (HR renew 

### ) 9,756 Btu/kWh Percent of generation Coal (% coal) 48% Used for solid fuel Oil/natural gas (% gas) 18% Used for natural gas Nuclear (% nuclear) 20% No secondary emissions estimated Hydroelectric (% hydro) 7% No secondary emissions estimated Renewable (% renew) 6% No secondary emissions estimated Other (% other) 1% Used for natural gas (assumed equivalent) Power plant efficiency (E) Coal (E coal 

### ) 33% % = HC elec 

### / HR coal 

### * 100 Natural gas/other (E gas 

### ) 42% % = HC elec 

### / HR gas 

### * 100 Nuclear (E nuclear 

### ) 33% % = HC elec 

### / HR nuclear 

### * 100 Renewable/hydroelectric (E renew 

### ) 35% % = HC elec 

### / HR renew 

### * 100

Average (E avg 

### ) 35% % = (E coal 

### x % coal) + (E gas 

### x % gas/other) + (E nuclear 

### x % nuclear) + (E renew 

### x % renew/hydro) Energy impacts calculations Electricity requirements model

- specific kWh/yr = total hp x (0.745 kW/hp) x operating hr/yr Energy impacts model

- specific MMBtu/yr = (kWh/yr) x (HC elec 

### ) x (MMBtu/1E 6 

### Btu) / E avg 

### Secondary emissions Emission factors, natural gas Particulate matter/PM 2.5 

### 1.9 lb/MM ft 3 

### natural gas
0.00186275 lb/MMBtu natural gas Carbon monoxide 84 lb/MM ft 3 

### natural gas
0.0824 lb/MMBtu natural gas Nitrogen oxide 100 lb/MM ft 3 

### natural gas
0.0980 lb/MMBtu natural gas Sulfur dioxide 0.6 lb/MM ft 3 

### natural gas
0.00059 lb/MMBtu natural gas Emission factors, solid fuel
Particulate matter 0.03 lb/MMBtu solid, liquid, gaseous fuel
PM 2.5 

### 0.00957 lb/MMBtu solid, liquid, gaseous fuel Carbon monoxide 0.19 lb/MMBtu bituminous coal Nitrogen oxide 0.38 lb/MMBtu solid fuel Sulfur dioxide 1.2 lb/MMBtu solid fuel

## D

- 3 Parameters Value Notes, units, and equations Secondary emissions calculation Secondary emissions, for each pollutant model

- specific lb/yr = MMBtu/yr x [(lb/MMBtu natural gas) x (% gas/other) + (lb/MMBtu solid fuel) x (% coal)] 

### Solid waste and wastewater impacts Solid waste impacts model

- specific tpy = waste (lb/hr) x operating hr/yr / (2,000 lb/ton) Wastewater impacts model

- specific gpy = water usage (gpd) x operating hr/yr / (24 hr/d) 1. gpy = gallons per year; gpd = gallons per day.
2 . Assume electricity generated using the above mix (from IPM Version 3.0 for the year 2015), as determined from

Table 3

- 6 of R egulatory I mpacts A nalysis for the final M ercury and Air Toxics Standards . IPM = EPA Integrated Planning Model, which is a multi

- regional, dynamic, deterministic linear programming model of the U.S. electric power sector that provides forecasts of least

- cost c apacity expansion, electricity dispatch, and emission control strategies for meeting energy demand and environm ental, transmission, dispatch, and reliability constraints.
3 . For natural gas, used PM, CO, NO X , and SO 2 emission factors fr om AP

- 42 chapter on natural gas combustion

.

Assume d 1,020 Btu/ft 3 of natural gas in estimating PM, CO, NO X , and SO 2 secondary emissions. Also assumed that 100% of PM is PM 2.5 , based on statement in AP

- 42 that PM from natural gas combustion is estimated to be less than 1 micron in size.
4 . For solid fuel, used PM and SO 2 emission limits for solid fuel

- fired boilers from 2006 CFR edition of NSPS for

electric utility plants (40 CFR part 60, subpart Da) and used NO X and CO emission factors from AP

- 42 chapter on coal combustion (bituminous/subbituminous coal)

. The NO X emission factor was based on average of NO X emission factors for PC dry

- bottom wall

- fired NSPS boilers burning bituminous (12 lb/ton) and subbituminous (7.4 lb/ton) coal. Assumed 13,000 Btu/lb of coal in estimating NO X and CO secondary emissions. A ccording to AP

- 42, the percentage of PM that is PM 2.5 for dry

- bottom coal

- fired boilers is 29% with ESP, 53% with FF, and 6% if uncontrolled. Assumed 84% of utility boilers controlled with ESP and 14% with FF, leaving 2% uncontrolled, based on information from EPA document on control of emissions from coal

- f ired utility boilers.

## Appendix E

Installation Model Impacts

## E

- 2 Table E

- 1. Model Impacts of Installing New DIFF

Parameters SCD LCD Control efficiency
HF 99.5% 99.5%
H Cl 83 .3 % 83 .3 % C l 2 

### 89 .3 % 89 .3 %
Non

- Hg HAP metals 94% 94%
PM 94% 94% SO 2 

### 4 8.7 % 4 8.7 %
P arameters Fan hp 150 190 Total hp for other motors 30 30 Waste, lb/hr 102. 1 154. 9 Emissions reductions, tpy
HF 18.13 38.85 HCl 2.06 4.42 Cl 2 

### 0.09 0.20
Non

- Hg HAP metals 0.1026 0.220
PM 9.33 19.99 SO 2 

### 48.26 103.42 Energy impacts, MMBtu/yr 11,544 14,109 Secondary air impacts, tpy
Particulate matter 0.09 0.10
PM 2.5 

### 0.029 0.03 5 Carbon monoxide 0.14 0.18 Nitrogen oxides 1.14 1.39 Sulfur dioxide 3.33 4.06 Solid waste impacts, tpy 447 678

## E

- 3 Table E

- 2 . Model Impacts of Installing Fabric Filter

Parameters SCD LCD Control efficiency
Non

- Hg HAP metals 94% 94%
PM 94% 94%
P arameters Fan hp 150 190 Total hp for other motors 30 30 Waste, lb/hr 2.1 4. 6 Emissions reductions, tpy
Non

- Hg HAP metals 0.10 0.22
PM 9.33 19.99 Energy impacts, MMBtu/yr 11,544 14,109 Secondary air impacts, tpy
Particulate matter 0.09 0.10
PM 2.5 

### 0.029 0.035 Carbon monoxide 0.14 0.18 Nitrogen oxides 1.14 1.39 Sulfur dioxide 3.33 4.06 Solid waste impacts, tpy 9.33 19.99

## E

- 4 Table E

- 3 . Model Impacts of Installing New DLA

Parameters SCD LCD Control efficiency
HF 95% 95% HCl 30% 30% Cl 2 

### 42% 42%
Non

- Hg HAP metals 20% 20%
PM 20% 20% SO 2 

### 12% 12%
P arameters Fan hp 6 0 90 Total hp for other motors 1 0 4 0 Waste, lb/hr 83. 7 117. 2 Emissions reductions, tpy
HF 17.61 37.73 HCl 0.74 1.59 Cl 2 

### 0.04 0.10
Non

- Hg HAP metals 0.025 0.053
PM 2.27 4.86 SO 2 

### 11.88 25.47 Energy impacts, MMBtu/yr 4,489 8,337 Secondary air impacts, tpy
Particulate matter 0.03 0.06
PM 2.5 

### 0.011 0.021 Carbon monoxide 0.06 0.10 Nitrogen oxides 0.44 0.82 Sulfur dioxide 1.29 2.40 Solid waste impacts, tpy 367 513

## Appendix F

Retrofit /Replacement Model Impacts

## F

- 2 Table F

- 1

. Model Impacts of Retrofitting ACI System to Existing Control Device

Parameters MACT Floor Beyond the Floor SCD LCD SCD LCD
Parameters Injection blower fan power, hp 5.2 8.7 5.2 8.7 Carbon feed rate, lb/hr 2.8 4.6 4.2 7.0 Mercury emissions reduction, tpy 0.001 6 3 0.003 49 0.001 8 2 0.003 90 Energy impacts, MMBtu/yr 371 621 371 621 Secondary air impacts, tpy
Particulate matter 0.002 7 0.004 6 0.002 7 0.004 6
PM 2.5 

### 0.000 9 0.001 5 0.000 9 0.001 5 Carbon monoxide 0.00 46 0.00 77 0.00 46 0.00 77 Nitrogen oxides 0.036 7 0.0 614 0.036 7 0.0 614 Sulfur dioxide 0. 1069 0. 1789 0. 1069 0. 1789 Solid waste impacts, tpy 12.26 20.15 18.40 30.66

## F

- 3 Table F

- 2 . Model Impacts of Replacing Dry Limestone Adsorber with New DIFF

Parameters SCD LCD
DLA DIFF Increm. DLA DIFF Increm. Control efficiency
HF 95% 99.5% 95% 99.5% HCl 30% 83.3% 30% 83.3% Cl 2 

### 42% 89.3% 42% 89.3%
Non

- Hg HAP metals 20% 94% 20% 94%
PM 20% 94% 20% 94% SO 2 

### 12% 48.7% 12% 48.7%
Parameters Fan hp 60 150 90 190 Total hp for other motors 10 30 40 30 Waste, lb/hr 83.8 102.1 117.3 154.9 Emissions reductions, tpy
HF 17.31 18.13 0.82 37.09 38.85 1.76 HCl 0.74 2.06 1.32 1.59 4.42 2.83 Cl 2 

### 0.04 0.0947 0.05 0.10 0.203 0.11
Non

- Hg HAP metals 0.022 0.1026 0.081 0.047 0.220 0.173
PM 1.99 9.33 7.35 4.25 19.99 15.74 SO 2 

### 11.88 48.26 36.38 25.47 103.42 77.96 Energy impacts, MMBtu/yr 4,489 11,544 7,055 8,337 14,109 5,772 Secondary air impacts, tpy
Particulate matter 0.03 0.09 0.05 0.06 0.10 0.04
PM 2.5 

### 0.011 0.029 0.017 0.021 0.035 0.014 Carbon monoxide 0.06 0.14 0.09 0.10 0.18 0.07 Nitrogen oxides 0.44 1.14 0.70 0.82 1.39 0.57 Sulfur dioxide 1.29 3.33 2.03 2.40 4.06 1.66 Solid waste impacts, tpy 367 447 80.10 514 678 165

## F

- 4 Table F

- 3 . Model Impacts of Replacing Spray Dryer/ESP with New DIFF

Parameters SCD LCD SD/ESP 1 

### DIFF Increm. 2 

### SD/ESP 1 

### DIFF Increm

. 2


### Parameters Fan hp 125 250 Total hp for other motors 200 400 Water usage, gpd 6.25 12.5 Emissions reductions, tpy
HF

- 2.83 18.13 20.96

- 3.06 38.85 41.91 HCl

- 2.65 2.06 4.72

- 4.95 4.42 9.38 Cl 2 

### - 0.55 0.09 0.64

- 1.08 0.20 1.28
Non

- Hg HAP metals 0.103 0.103 0.00 0.220 0.220 0.00
PM 9.33 9.33 0.00 19.99 19.99 0.00 SO 2 

### 47.54 48.26 0.73 101.86 103.42 1.56 Energy impacts, MMBtu/yr 20,843 11,544

- 9,299 41,686 14,109

- 27,577 Secondary air impacts, tpy
Particulate matter 0.15 0.09

- 0.07 0.31 0.10

- 0.20
PM 2.5 

### 0.052 0.029

- 0.023 0.103 0.035

- 0.068 Carbon monoxide 0.26 0.14

- 0.12 0.52 0.18

- 0.34 Nitrogen oxides 2.06 1.14

- 0.92 4.12 1.39

- 2.73 Sulfur dioxide 6.00 3.33

- 2.68 12.01 4.06

- 7.94 Solid waste impacts, tpy 438 447 8.66 664 678 14.43 Wastewater impacts, gpy 2,281 0

- 2,281 4,563 0

- 4,563

1 The n egative emission reduction estimates for the SD/ESP are a result of the small dataset for kilns with this type of

control and the lack of control efficiency information for SD/ESP

. 2 A negative increase in impacts would be equivalent to a reduction in impacts.

## F

- 5 Table F

- 4 . Model Impacts of Replacing Existing DIFF with New, More Efficient DIFF

Parameters SCD LCD
Existin g

DIFF New DIFF Increm. Existing DIFF New DIFF Increm.
Control efficiency
HF 98% 99.5% 98% 99.5% HCl 82% 83.3% 82% 83.3% Cl 2 

### 88% 89.3% 88% 89.3%
Non

- Hg HAP metals 72% 94% 72% 94%
PM 72% 94% 72% 94% SO 2 

### 48% 48.7% 48% 48.7%
Parameters Fan hp 150 150 190 190 Total hp for other motors 30 30 30 30 Waste, lb/hr 100.1 102.1 151.6 154.9 Emissions reductions, tpy
HF 17.86 18.13 0.27 38.26 38.85 0.59 HCl 2.03 2.06 0.03 4.36 4.42 0.07 Cl 2 

### 0.09 0.09 0.00 0.20 0.20 0.00
Non

- Hg HAP metals 0.079 0.103 0.024 0.168 0.220 0.051
PM 7.15 9.33 2.18 15.31 19.99 4.68 SO 2 

### 47.54 48.26 0.73 101.86 103.42 1.56 Energy impacts, MMBtu/yr 11,544 11,544 0 14,109 14,109 0 Secondary air impacts, tpy
Particulate matter 0.09 0.09 0 0.10 0.10 0
PM 2.5 

### 0.029 0.029 0 0.035 0.035 0 Carbon monoxide 0.14 0.14 0 0.18 0.18 0 Nitrogen oxides 1.14 1.14 0 1.39 1.39 0 Sulfur dioxide 3.33 3.33 0 4.06 4.06 0 Solid waste impacts, tpy 438 447 8.66 664 678 14.43

### Additional discussion on chang e to PM MACT floor pool, page 71

- 73 of preamble:



## 2. Changes to the MACT Floor Pool and Calculations

At proposal, the MACT floors for PM as a surrogate for

total non

- Hg HAP metals were based on kilns with FF

- ba sed APCD,

as the EPA considered those to be the best performing sources in

the industry. However, as noted in section IV.A.1 of this

preamble, the EPA after proposal examined the PM test data in an

effort to insure that the data were valid. We found a numb er of

the EPA Method 5 test runs had probe or filter temperatures

outside of the range of acceptable values. These out

- of

- range

temperatures invalidated the test runs, and in some cases,

invalidated entire PM tests, reducing the set of valid,

available tes t data. Some of the PM test data removed from the

data set were for kilns controlled with a DIFF. As a result, the

EPA no longer has data on all the kilns with a FF

- based APCD in

the industry, which undercuts one of the bases for EPA’s

proposal to use the best performing FF

- based kilns to set a MACT

floor based on 12% of the entire category. In addition at

proposal the EPA requested more data to further substantiate

that FF controlled kilns actually represented the best

performing sources in terms of PM emi ssions. For example, there

was some data in the record at the time of the proposal

suggesting that in some cases uncontrolled kilns actually had

## emissions below the PM emissions of some FF controlled kiln,

which is contrary to what we would expect. EPA req uested

information to explain these anomalies. However, data was not

received during the comment period sufficient to explain why

some kilns without FF controls emitted at levels as low as or

lower than some FF controlled kilns. For this reason, and

becaus e some of the emissions data on DIFF kilns had to be

removed from the data pool as discussed above, the record does

not support the conclusion that we have PM emissions data on all

the best performing kilns in the industry. Given that, we are

instead basin g the PM MACT floor on 12 percent of the kilns for

which we have emissions data. Therefore, the final MACT floor

pools for PM as a surrogate for total non

- Hg HAP metals are not

based on the top 12 percent of the kilns in the industry ( i.e.
,
the 27 best per forming sources). Instead, the final MACT floor

limits are based on the top 12 percent of the sources for which

we have emissions data available in each of the kiln size

subcategories, consistent with the approach described for the

proposed alternate non

- H g HAP metals standards in section IV.Q.1

of the preamble to the proposed rule (79 FR 75649).