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 

and 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 8.48E-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-035 Area Source (synthetic) 37

724 DLA 0.09599 7.78E-043 Area Source (synthetic) 38

641 DLA 0.09977 1.64E-033 Area Source (synthetic) 39

518 DLA 0.10624 5.28E-043 Major Source 40 23

679 DLA 0.10847 3.80E-033 Major Source 41 24

738 DIFF 0.11217 8.58E-036 Area Source (synthetic) 42

573 DLA 0.13228 2.02E-043 Area Source (synthetic) 43

730 DLA 0.13851 2.63E-036 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-036 Major Source 47 28

646 DLA 0.14327 1.01E-026 Area Source (synthetic) 48

675 DIFF 0.14825 1.72E-033 Area Source (synthetic) 49

740 DLA 0.15802 2.68E-033 Area Source (synthetic) 50

729 DLA 0.17786 1.91E-033 Major Source 51 29

644 DLA 0.17806 9.79E-043 Major Source 52 30

676 DIFF 0.18995 3.55E-026 Area Source (synthetic) 53

736 DLA 0.20060 7.15E-033 Area source (synthetic) 54

647 DLA 0.23418 3.68E-027 Area Source (synthetic) 55

655 DIFF 0.23971 5.23E-025 Area Source (synthetic) 56

645 DLA 0.26210 6.74E-036 Major Source 57 31

539 None 0.28166 5.73E-032 Major Source 58 32

720 WS 0.32413 1.33E-015 Area Source (synthetic) 59

768 DLA 0.37699 1.40E-023 Major Source 60 33

643 WS 0.37757 5.25E-027 Area Source (synthetic) 61

612 DLA 0.41284 1.27E-023 Major Source 62 34

613 DLA 0.41284 1.27E-023 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-026 Major Source 66 38

766 DLA 0.82067 7.89E-016 Major Source 67 39

767 DLA 0.82067 7.89E-016 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 lognormal

E.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 2015

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 document should be 

addressed to Tom Walton, U.S. Environmental Protection Agency, Office of Air Quality 

Planning and Standards, Research Triangle Park, North Carolina 27711 

(email: walton.tom@epa.gov). 

ACKNOWLEDGEMENTS

Personnel from RTI International and Kapur Energy Environmental Economics, LLC

contributed significant data, analysis, and writing to this document under contract number EP-W11-029. 
***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 References.......................................................................................................... 2-21
***E.O. 12866 Review- Draft-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 PM2.5-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 PM2.5 Co-benefits Results........................................................................ 4-9

4.1.5 Characterization of Uncertainty in the Monetized PM2.5 Cobenefits..................................................................................................... 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 SO2 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- Draft-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 Review............................. 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- Draft-Do Not Cite, Quote, or Release During Review***

vi

6.11 Congressional 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 for Brick and Structural Clay Products......................................... 2-21

4-1 Total Monetized PM2.5 Co-benefits of Final Brick and Structural Clay Rule in 

2018............................................................................................................................. 4-12

4-2 Percentage of Adult Population by Annual Mean PM2.5 Exposure in the 

Baseline....................................................................................................................... 4-17

4-3 Cumulative Distribution of Adult Population by Annual Mean PM2.5 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- Draft-Do Not Cite, Quote, or Release During Review***

viii

LIST OF TABLES

Number Page

2-1. Distance Shipped Statistics: NAIC 327 (Nonmetallic Mineral Product 

Manufacturing) ............................................................................................................. 2-7

2-2. Market 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) (103 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): 

1993–2010................................................................................................................... 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 PM2.5 ..................................................................... 4-3

4-2. Summary of Monetized PM2.5 and its Precursor SO2- Related Health Cobenefits Estimates for the Brick and Structural Clay Rule in 2018 (2011$) .............. 4-10

4-3. Summary of Reductions in Health Incidences from PM2.5 and its Precursor 

SO2- Related Co-benefits for Brick and Structural Clay Rule in 2018 ...................... 4-11

4-4. All PM2.5 Benefits Estimates for the Brick and Structural Clay Rule in 2018 at 

Discount Rates of 3% and 7% Averaged ($2011 millions)........................................ 4-13

4-5. Population Exposure in the Baseline Above and Below Various Concentration 

Benchmarks in the Underlying 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 CO2 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- Draft-Do Not Cite, Quote, or Release During Review***

ix

7-1. Summary of the Monetized Benefits, Social Costs, and Net Benefits (million 

2011$) ........................................................................................................................... 7-1
***E.O. 12866 Review- Draft-Do Not Cite, Quote, or Release During Review***

ES-1

EXECUTIVE SUMMARY

ES.1 Background

The U.S. Environment Protection Agency (EPA) is proposing that all major sources in 

Brick and Structural Clay Products Manufacturing category meet health-based standards for acid 

gas hazardous air pollutants; maximum achievable control technology 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 Air Act.

As part of the regulatory process, EPA is required 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:

■ Engineering Cost Analysis: EPA estimates the total annualized costs (2011$) for the 

final rule will be approximately $28 million.

■ Benefits Analysis: The EPA monetized human health benefits of reducing cases of 

morbidity and premature mortality among populations exposed to PM2.5. In addition, 

EPA estimated the energy disbenefits associated with emissions from the control 

devices’ increased electricity usage. Using a 3% discount rate, we estimate the total 

monetized benefits of the final standards to be $83 million to $190 million. Using a 

7% discount rate, we estimate the total monetized benefits to be $75 million to $170

million. Data, resource, and methodological limitations prevented EPA from 

monetizing the benefits from several important benefit categories, including 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 SO2, 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 adjustments for bricks. 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 year. Under the final standards, 

EPA estimated that two to four brick 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. 

households in the form of higher prices. Existing U.S. industries’ surplus falls by 

$12.1 million, and the total U.S. economic surplus loss is $27.2 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 standards, the net benefits are $56 million to 

$160 million at a 3% discount rate for the benefits and $48 million to $150 million 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 included in Section 5 of this 

report.

ES.3 Organization of 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 benefits analysis. Section 5 presents market, 

employment impact, social cost, and small business impact analyses. Section 6 addresses

statutory and Executive Order requirements, and Section 7 provides a summary of benefits and 

costs.
***E.O. 12866 Review- Draft-Do Not Cite, Quote, or Release During Review***

1-1

SECTION 1

INTRODUCTION

1.1 Background for the Final Rule

The Environmental Protection Agency (EPA) is finalizing national emission standards for 

hazardous air pollutants (NESHAP) for Brick and Structural Clay Products Manufacturing. All 

major sources in these categories must meet maximum achievable control technology (MACT) 

standards for mercury (Hg) and nonmercury (non-Hg) metal hazardous air pollutants (HAPs) (or 

particulate matter [PM] surrogates); health-based standards for acid gas HAPs; and work practice 

standards, where applicable. The final rule, which has been informed by input from industry and 

other stakeholders including small businesses, protects air quality and promotes public health by 

reducing emissions of HAPs 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 Action

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 account 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 
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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 costs.
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SECTION 2

PROFILE OF THE AFFECTED 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 trends 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 establishments 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 industries 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′′.
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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, new 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 considered 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
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■ 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, grinding, 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 product’s value is associated with 

value-added activities (i.e., labor 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 hourly 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 clay 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 materials 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 

(USGS) notes that brick companies often consider sources of raw materials when considering 

purchasing other companies. For example, the Belden Brick Co. purchase of Lawrenceville 

Brick Inc. included Lawrenceville Brick’s clay reserves (USGS, 2011).

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 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 produced 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 

 3

The measure is computed as the percentage change in quantity supplied divided by the percentage change in price.
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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) developed 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 period4 and the other input that 

varies with production. 

Supply Elasticity = elasticity of substitution × fixed factor value share

1− fixed factor value share .

To illustrate the approach, consider the value share of the fixed factor to be 50% 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 we assume the elasticity of 

substitution between the fixed and variable input is one, the formula is

Supply Elasticity = 1 × 0.5

1 − 0.5 = 1.

Using these values for the fixed 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 

utilization rates and excess capacity available in the industry, this value may underestimate 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 residential 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 clay 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 products 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.
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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 Association, 

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 directly 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 Industry 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 include 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, brick 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 percent, 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 point [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 

influenced by income levels.
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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 statistically 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 demanded (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 Definition

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 buyers 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 

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 

 5

The measure is computed as the percentage change in quantity demanded divided by the percentage change in 

price.
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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 

bricks 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 Statistics: NAIC 327 (Nonmetallic Mineral Product 

Manufacturing)

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 firms. At one end of the spectrum, firms 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 identical, 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 likely to hold when 

there are significant barriers to entry (industries with economies of scale or ownership of a 

patent).

 6

The data include other products 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.
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When markets have a small number of firms selling identical products, firms may not 

necessarily be price takers; instead, they may be able 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 share 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-

year 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, 2013e).

As Table 2-2 indicates, looking 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. Market 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 27%

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 
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identified 44 ultimate parent companies with facilities that will need new or modified control 

devices to meet new emission standards. The companies own 85 facilities and operate 168 kilns

(see Table 2-3). The South Atlantic region accounts for a significant share of existing production 

capacity; 23 facilities and 53 kilns are operated in this region.

Table 2-3. Production Statistics by Census Region 

Census Region

Total S.B.E 

Shipped in 2010

(1000s)

Number of 

Affected Kilns

Number of 

Affected 

Facilities

Estimated Affected 

Production Share 

within Region

East North Central 285,508 29 11 81%

East South Central 388,685 28 14 100%

Mid-Atlantic 213,583 8 5 69%

Mountain 114,154 4 3 50%

New England 37,034 0 0 0%

Pacific 74,563 6 4 85%

South Atlantic 1,307,601 53 23 92%

West North Central 183,247 15 11 100%

West South Central 891,232 25 14 100%

United States 3,495,607 168 85 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 small 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 Refractories 

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).
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Table 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 12 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)
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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 manufacturers’ 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 presents 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 production 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 quantity 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.
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Table 2-5. Historical Data for Brick (Building or Common and Face) (103 bricksa): 1993–

2010

Year

Shipment of 

Bricksb Exports Imports

Apparent 

Consumptionb

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 37,640d,f 74,479e,f 3,622,320

2010 3,495,657 37,532d,f 79,054e,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 price, 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 overhead 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. 

However, 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)
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Table 2-5. Historical Data for Brick (Building or Common and Face) (103 bricksa): 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 

shipment 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 estimating 

import quantities 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 did 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 import 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 systematic 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 systematically 

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 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.

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

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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 

Productsa Exportsb Importsb

Apparent 

Consumptionc

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

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

Note: This table 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 ratio used here.

(continued)
***E.O. 12866 Review- Draft-Do Not Cite, Quote, or Release During Review***

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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 select 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 same 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, freight 

charges, and returns. Shipments 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 export 

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 not 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 they 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 clay 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. 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. However, because 

we lack reliable data on export prices, we do not estimate quantities 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 same 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 simply 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, the 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 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 import 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 systematic 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 systematically 

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 (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 from 

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)
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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)

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 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, 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 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.

Both exports and imports of bricks increased 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) and 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 shipments 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% and 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- Draft-Do Not Cite, Quote, or Release During Review***

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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: This table 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 apparent 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 report.

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

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

2-18

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 2003, 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 growth 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 thousand 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 annual 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 due 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, when 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. For 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- Draft-Do Not Cite, Quote, or Release During Review***

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Boral Limited is an international building and construction materials group headquartered 

in Australia, 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 earnings 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 United 

States declined simultaneously 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 

EBIT 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 does 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 million 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 profit 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, raw 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 concrete roof tile manufacturer in the United States.
***E.O. 12866 Review- Draft-Do Not Cite, Quote, or Release During Review***

2-20

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 approximately $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.
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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-Report2012.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. Version 4.0.

Federal Reserve Board. 2013. Industrial Production and Capacity 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. 
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2-22

Mohawk Industries, Inc. 2012. 2011 Annual Report. http://phx.corporateir.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.saintgobain.com/files/Rapport_annuel_2002_EN.pdf.

Saint-Gobain. 2013. Registration Document 2012. http://www.saintgobain.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 2013a. Annual Survey of Manufactures: General Statistics: Statistics for 

Industry Groups and Industries: 2011 and 2010; generated by RTI International; using 

American Factfinder. http://factfinder2.census.gov. (August 16, 2013).

U.S. Census Bureau. 2013b. 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 International; 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.
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2-23

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. 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. 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 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.

U.S. Department of the Interior, U.S. Geological Survey. May 2013. 2011 Minerals Yearbook, 

Clay and Shale [Advance 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/myb1-2011-clays.pdf.
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2-24

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 search 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 (Cl2), mercury (Hg), and non-Hg hazardous air pollutant 

(HAP) metals from the kilns used in the production process. To control these emissions, EPA has 

developed emission standards for these HAPs under the authority of Section 112 of the CAA.

This section explains how the estimates of compliance costs associated with this regulation were

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 compliance 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 affected BSCP facilities under threetwo regulatory approaches:

■ Option 1 (Proposed Rule) : 

– Acid gases: Meet HBS. for acid gases,

– Hg: Cchoice of MACT limit for Hg in lb/ton, or concentration, or lb/hr.

■– PM/total non-Hg HAP metals:and a Cchoice 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: Cchoice 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 Cchoice of MACT limits for PM in lb/ton or 

gr/dscf or non-Hg HAP metals lb/hr for small and large kilns (calculated based on 

12 percent of the data in the subcategory).

Formatted: bullets-2nd level

Formatted: bullets-2nd level
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3-2

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

metals):

– Acid gases: Meet HBS. for acid gases, 

– Hg: Cchoice 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 cChoice 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 industry).

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 limestone 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 fabric filter (DIFF). DIFFs are used to remove HF, HCl, Cl2, sulfur 

dioxide (SO2), 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, Cl2, and SO2 from the exhaust stream.

■ Dry lime scrubber/fabric filter (DLS/FF). DLS/FFs are used to control HF, HCl, Cl2, 

SO2, 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 slurry 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, Cl2, and SO2

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, Cl2 and SO2

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

Formatted: bullets-2nd level
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3-3

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, Cl2, or SO2.

■ Activated carbon injection (ACI). An ACI system would pneumatically inject 

activated carbon into the flue gas ductwork of a kiln. The activated carbon 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 facility 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 required 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.
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■ If an uncontrolled kiln or a kiln with a DLA is located at a facility that can meet the 

health-based limits, then only an 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 are 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 minimum control “actions needed” based 

on a review of the contribution of each emission point’s to the allowable HClequivalent 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 

Rule 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

$27 $28 $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 
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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

■ No 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 Options

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 

Costs are presented for small and large APCDs. 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.
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The estimates of annual cost include

■ operation and maintenance (O&M) labor;

■ materials;

■ electricity;

■ waste disposal;

■ overhead; 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 Costs and Impacts of BSCP Air Pollution Control Devices.”

Annualization of the capital costs involves establishing an annual “payment” sufficient to 

finance the investment over the expected lifetime of the equipment or loan period. This payment 

is typically referred to as the “capital recovery cost.” The three 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 following is a 

summary of those results:

■ Option 1: approximately $27 million

■ Option 2 Final Rule: approximately $28 million

■ Option 3: approximately $50 million

Annual costs listed above for each compliance option also include costs for testing and 

monitoring, along with recordkeeping and reporting costs incurred by facilities that have testing 

and monitoring costs1

.

 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). 
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The consideration of raw material variability in the Hg limits in Options 2 and 3 results 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, compared 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 limits 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 costs 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. The 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 significantly 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 for 

purposes of becoming SA facilities.

When looking at annual costs per region of the country, the South Atlantic region (SAC)

consistently exhibits the highest cost and the Pacific region (PAC) 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 stacks required to take action to achieve 

compliance (Table 3-4). Additional 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.
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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

15 9 15 5 1 45

Capital Cost $19.6 $13.2 $24.7 $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 $26.3 $0.733 $3.82 $62.3

Annual Cost $3.68 $7.53 $11.0 $0.529 $1.02 $23.7

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 
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4-1

SECTION 4

HUMAN HEALTH BENEFITS OF EMISSIONS REDUCTIONS

Synopsis

Implementation of emissions controls required by the Brick and Structural Clay 

NESHAP is expected to reduce direct emissions of particulate matter (including PM2.5) and 

sulfur dioxide (SO2) 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 ambient fine particulate 

matter (PM2.5) by reducing emissions of precursors. The total PM2.5 and SO2 reductions are the 

consequence of the expected design changes to the affected manufacturing plants needed in order 

to meet the multiple limits. We estimate the total monetized co-benefits of the final rule to be 

$83 million to $190 million at a 3% discount rate and $75 million to $170 million at a 7% 

discount rate in 2018, including consideration of energy disbenefits. All estimates are in 2011$ as 

they are summarized in Table 4-1. These estimates reflect the monetized human health benefits 

of reducing cases of morbidity and premature mortality among populations exposed to PM2.5

reduced by this rule. Data, resource, and methodological limitations prevented EPA from 

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 PM2.5-Related Human Health Co-benefits

This rule is expected to reduce direct emissions of PM and emissions of SO2, which is a 

precursor to formation of ambient PM2.5. Therefore, reducing these emissions would also reduce 

human exposure to ambient PM2.5 and the incidence of PM2.5-related health effects. In this 

section, we provide an overview of the PM2.5-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 controls may lead to reductions in ambient PM2.5 

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, there 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 
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4-2

implementation of existing 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 reductions. 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 reductions 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 forward 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 review 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 Assessment for Particulate Matter (PM ISA) (U.S. EPA, 2009) 

identified the human health effects associated with ambient PM2.5, which include premature 

morality and a variety of morbidity effects associated with acute and chronic exposures. Table 

4-1 provides the quantified and unquantified benefits captured in EPA’s benefits estimates for 

reduced exposure to ambient PM2.5. Although the table below does not include entries for the 

unquantified health effects such as exposure to ozone and NO2 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 quantification of each effect complete.
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Table 4-1. Human Health Effects of Ambient PM2.5

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 PM2.5

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 PM2.5

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 ISAb

Other respiratory effects (e.g., pulmonary 

function, non-asthma ER visits, nonbronchitis chronic diseases, other ages and 

populations)

-- -- PM ISAb

Reproductive and developmental effects 

(e.g., low birth weight, pre-term births, etc.)

-- -- PM ISAb,c

Cancer, mutagenicity, and genotoxicity 

effects

-- -- PM ISAb,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 qualitatively because current evidence is only suggestive of causality or there are other 

significant concerns over the strength of the association.
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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 directly 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 PM2.5 or other air pollutants. We 

use the environmental Benefits Mapping and Analysis Program (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 PM2.5

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/m3 for PM2.5). 

These relative risks can be used to develop risk coefficients that relate a unit reduction in PM2.5 

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 effect 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 

epidemiology, toxicology, and clinical studies, the PM ISA documents the association between 

elevated PM2.5 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 PM2.5 based on the entire body of scientific 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 the exact shape of the concentration-response function. 
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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 PM2.5 exposure and premature 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 Cities 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 PM2.5 -mortality 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 uncertainty in estimates of the reduction in mortality among 

the adult U.S. population resulting from reductions in ambient annual average PM2.5 levels. In 

that study, twelve experts provided independent opinions of the PM2.5 -mortality concentrationresponse function. 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 the EPA emphasize that “scientific 

differences existed only with respect to the magnitude of the effect of PM2.5 on mortality, not 

whether such an effect existed” and that the expert elicitation “supports the conclusion that the 

benefits of PM2.5 control are 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 population. 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 mitigating the effect. These cost-of-illness (COI) estimates 
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4-6

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 value 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 

available, 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 Preparing 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 1974 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 

($2011). Further details on the methodology are available in section 5.6.8 of the PM RIA 

(U.S.EPA, 2012a).

 11In 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. 

12In 1990$, this VSL is $4.8 million. 
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4-7

The Agency is committed to using scientifically sound, appropriately reviewed evidence 

in valuing mortality risk reductions and has made significant progress in responding to the SABEEAC’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 proportion 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 mortality reductions in the first year, 50% over years 2 to 5, and 20% over the years 6 

to 20 after the reduction in PM2.5 (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-Ton 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 several previous RIAs (e.g., U.S. EPA, 2011b, 2011d, 2012b). These benefitper-ton estimates provide the total monetized human health benefits (the sum of premature 

mortality and premature morbidity) of reducing one ton of PM2.5 (or PM2.5 precursor such as 

NOx or SO2) from a specified source. Specifically, in this analysis, we multiplied the estimates 

from the “Other Non-EGU Point” sector13,14 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 PM2.5 and its precursors from 17 sectors (U.S. EPA, 

 13As 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]
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4-8

2013). One limitation of using the benefit-per-ton approach is an inability to provide estimates of 

the health benefits associated with exposure to HAP, CO, NO2, 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 estimates of 

PM2.5-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 emissions 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 PM2.5 from this sector represented by the 

above mentioned category is close to the median of the distribution of all 17 BPT values (TSD 

Table 7). For example, the sector’s BPT for directly emitted PM2.5 is close to 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 Steel 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 match 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 PM2.5

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 larger, or smaller, than those realized by this rule.

Even though we assume that all fine particles have equivalent health effects, the benefitper-ton estimates vary between precursors depending on the location and magnitude of their 

impact on PM2.5 levels, which drive population exposure. The sector-specific modeling does not 

provide estimates of the PM2.5-related benefits associated with reducing VOC emissions, but 

these unquantified benefits are generally small compared to other PM2.5 precursors (U.S. EPA, 

2012a).
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4.1.4 PM2.5 Co-benefits 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 reductions in health incidences associated with these 

pollution reductions. Figure 4-1 provides a visual representation of the range of PM2.5-related 

benefits estimates using concentration-response functions from Krewski et al. (2009) and 

Lepeule et al. (2012) 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 PM2.5 Co-benefits

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 analysis 

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 analysis 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 results 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 cessation lag assumptions could change the PM2.5-related mortality 

benefits discounted at 3% by between 10% and −27% and that alternate income growth 

adjustments could change the PM2.5-related mortality benefits by between 33% and −14%.
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Table 4-2. Summary of Monetized PM2.5 and its Precursor SO2- Related Health Cobenefits Estimates for the Brick and Structural Clay Rule in 2018 (2011$)a,b

Options

Pollutant

Emissions 

Reductions 

(tons)

Benefitper-ton 

(Krewski, 

3%)

Benefitper-ton 

(Lepeule, 

3%)

Benefitper-ton 

(Krewski, 

7%)

Benefitper-ton 

(Lepeule, 

7%)

Monetized 

Benefits (millions 

2011$ at 3%)

Monetized 

Benefits 

(millions 2011$ 

at 7%)

Option 1 Directly emitted PM2.5 235 $260,000 $600,000 $240,000 $540,000 $62 to $140 $56 to $130

PM2.5 Precursors

SO2 168 $41,000 $92,000 $37,000 $83,000 $6.8 to $15 $6.1 to $14

NOx -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 $140

Final Rule: Option 2Directly emitted PM2.5 308 $260,000 $600,000 $240,000 $540,000 $82 to $180 $74 to $170

PM2.5 Precursors

SO2 72 $41,000 $92,000 $37,000 $83,000 $2.9 to $6.6 $2.6 to $6.0

NOx -46 $6,300 $14,000 $5,700 $13,000 -$0.29 to -$0.66 -$0.26 to -$0.59

Total $84 to $190 $76 to $170

Option 3 Directly emitted PM2.5 415 $260,000 $600,000 $240,000 $540,000 $110 to $250 $100 to $220

PM2.5 Precursors

SO2 568 $41,000 $92,000 $37,000 $83,000 $23 to $52 $21 to $47

NOx -77 $6,300 $14,000 $5,700 $13,000 -$0.49 to -$1.1 -$0.44 to -$0.99

Total $130 to $300 $120 to $270

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 NO2, 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 PM2.5 

levels, which drive population exposure. The monetized benefits incorporate the conversion from precursor 

emissions to ambient fine particles. Confidence intervals are unavailable for this analysis because of the benefitper-ton methodology.

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

not include monetized CO2 disbenefits, which range from $0.3 to $5 million depending on the option and discount 

rate. 
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Table 4-3. Summary of Reductions in Health Incidences from PM2.5 and its Precursor 

SO2- Related Co-benefits for Brick and Structural Clay Rule in 2018a

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.
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Figure 4-1. Total Monetized PM2.5 Co-benefits 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 shown 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 electricity disbenefits. These estimates do 

not include monetized CO2 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
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Table 4-4. All PM2.5 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 reasonable 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 emissions impact after consideration of electricity disbenefits. These estimates do 

not include monetized CO2 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 specific 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 estimates, 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, meteorology, 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 lower benefit estimates than 

if benefits were calculated based on direct air quality modeling. Great care should be taken in 
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4-14

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 benefitsper-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 above 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 estimates for premature mortality which accounts for 

98% of the total monetized PM2.5 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 PM2.5 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 PM2.5 can be linked with 

multiple 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 log-linear without a 

threshold in this analysis. Thus, the estimates include health benefits from reducing 

fine particles in areas with varied concentrations of PM2.5, 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 premature mortality related to PM2.5 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 general, we are more confident in the magnitude of the risks we estimate from 

simulated PM2.5 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 PM2.5 concentrations that fall below the bulk of the 
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observed data in these studies. Concentration benchmark analyses (e.g., lowest measured level 

[LML] or one standard deviation below the mean of the air quality data in the study) allow 

readers to determine the portion of population exposed to annual mean PM2.5 levels at or above 

different concentrations, which provides some insight into the level of uncertainty in the 

estimated PM2.5 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 

concentration 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 concentrations 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 confidence in the magnitude of the risk at 

concentrations below these benchmarks, we still have high confidence that PM2.5 is causally 

associated with risk at those lower air quality concentrations.

For this analysis, policy-specific air quality data is not available due to time or resource 

limitations. For this rule, we are unable to estimate the percentage of premature mortality 

associated with this specific rule’s emission reductions at each PM2.5 level. However, we believe 

that it is still important to characterize 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 PM2.5 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 

that had air quality modeling. 

 15For a summary of the scientific review statements regarding the lack of a threshold in the PM2.5-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 PM2.5-related Mortality (U.S. EPA, 2010b).
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4-16

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 percentage 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 Studiesa

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 10th and 25th

percentile. For Krewski, the LML is 5.8 μg/m3 and one standard deviation below the mean is 11.0 μg/m3

. For 

Lepeule et al., the LML is 8 μg/m3 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 

PM2.5 do not occur.
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Figure 4-2. Percentage of Adult Population by Annual Mean PM2.5 Exposure in the 

Baseline

Among the populations exposed to PM2.5 in the baseline:

93% are exposed to PM2.5 levels at or above the LML of the Krewski et al. (2009) study

67% are exposed to PM2.5 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 electric utility boilers (EGU boilers) that supply electricity 

to these facilities. In the calculation of health benefits presented above, we have already 

subtracted the PM, SO2, 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 19-20

Percentage of Population Exposed

Baseline Annual Mean PM2.5 Level (μg/m3)

 

LML of Lepeule et al. 

(2012) study

LML of Krewski et 

al. (2009) study
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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 PM2.5 NOx SO2 CO2

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 PM2.5, NOx, and SO2 have already been reflected in the monetized PM2.5 co-benefits 

above.

4.2.1 Social Cost of Carbon and Greenhouse Gas Disbenefits

We estimate the global social dis-benefits of CO2 emission increases expected from the 

final rulemaking using the SC-CO2 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 July 2015) (“current TSD”).

16 We refer to these estimates, 

which were developed by the U.S. government, as “SC-CO2 estimates.” The SC-CO2 is a metric 

that estimates the monetary value of impacts associated with marginal changes in CO2 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 increased 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 lead to an incremental reduction in cumulative global CO2

emissions) but is also used to assess increases in damages expected to result from rulemakings 

leading to an incremental increase in cumulative global CO2 emissions.

The SC-CO2 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, Technical 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 Environmental 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 2015). Available at: <https://www.whitehouse.gov/sites/default/files/omb/inforeg/scc-tsd-finaljuly-2015.pdf> Accessed 7/11/2015.
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4-19

integrated assessment models (IAMs) to develop the SC-CO2 estimates and recommended four 

global values for use in regulatory analyses. The SC-CO2 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-CO2 estimates in July 2015. 

The SC-CO2 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-CO2. 

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 literature 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 model 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 

concentrations, 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 consistent 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-CO2 analysis, including the 

incomplete way in which the integrated assessment models capture catastrophic and noncatastrophic impacts, their incomplete treatment of adaptation and technological change, 

uncertainty in the extrapolation of damages 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 modeling 

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_From_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. 
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4-20

terms of their influence on the SC-CO2 estimates, though taken together they suggest that the 

SC-CO2 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-CO2 estimates] underestimate the damage 

costs because they cannot include many non-quantifiable impacts.” Since then, the peerreviewed literature has continued to support this conclusion. For example, the IPCC Fifth 

Assessment report observed that SC-CO2 estimates continue to omit various impacts that would 

likely increase damages. 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-CO2 estimates from stakeholders through 

a range of channels, including public comments on Agency rulemakings that use the SC-CO2 in 

supporting analyses and through regular interactions with stakeholders and research analysts 

implementing the SC-CO2 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 develop the SC-CO2 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-CO2 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 Academies of Sciences, Engineering, and 

Medicine to ensure that the SC-CO2 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 to 

improving the SC-CO2 estimates in future updates. 

Concurrent with OMB’s publication of the response to comments on SC-CO2 and 

announcement of the Academies process, OMB posted a revised TSD that includes two minor 

technical corrections to the current estimates. 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-technicalupdate-of-the-social-cost-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.
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and the second addressed a minor indexing error in another model. On average the revised SCCO2 estimates are one dollar less than the mean SC-CO2 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 results from 

the model that was affected by the indexing error.

The four SC-CO2 estimates are: $13, $43, $64, and $120 per metric ton of CO2 emissions 

in the year 2018 (2011 dollars).22 The first three values are based on the average SC-CO2 from 

the three IAMs, at discount rates of 5, 3, and 2.5%, respectively. Estimates of the SC-CO2 for 

several discount rates are included because the literature shows that the SC-CO2 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 95th percentile of the SC-CO2 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-CO2 distribution. The SC-CO2 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 Disbenefits of CO2 Increases in 2018 (million 2011$)

Discount Rate and Statistic

Option

Metric Tonnes of CO2

Reduced 5% (average) 3% (average)

2.5% 

(average)

3% (95th

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 CO2 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 health 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-CO2 values have been rounded to two significant digits. Unrounded numbers from the 2013 SCC TSD were 

adjusted to 2012$ and used to calculate the CO2 benefits.
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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, chromium, cobalt, lead, manganese, mercury, nickel, and selenium).

Figure 4-3. Cumulative Distribution of Adult Population by Annual Mean PM2.5 

Exposure in the Baseline

Among the populations exposed to PM2.5 in the baseline:

93% are exposed to PM2.5 levels at or above the LML of the Krewski et al. (2009) study

67% are exposed to PM2.5 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 20

Cumulative percentage of population exposed

Baseline Annual Mean PM2.5 Level (μg/m3)

 

LML of Krewski et 

al. (2009) study

LML of Lepeule et 

al. (2012) study
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4.3.1 HAP Benefits

Even though emissions of air toxics from all sources in the U.S. declined by 

approximately 42% since 1990, 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 

which 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 and 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 toxics 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 

background 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. http://www.epa.gov/ttn/atw/nata2005/

24The 2005 NATA is available on the Internet at http://www.epa.gov/ttn/atw/nata2005/.

25Details 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.
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Noncancer health effects can result from chronic,26 subchronic,27 or acute28 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 exposed 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 depict the 2005 NATA estimated census tract-level carcinogenic risk 

and noncancer respiratory hazard from the assessment. It is important to note that large 

reductions in HAP emissions may not necessarily translate into significant reductions in health 

risk because 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.

 26Chronic 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).

27Defined 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).

28Defined in the IRIS database as exposure by the oral, dermal, or inhalation route for 24 hours or less.
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Figure 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

Because of methodology limitations, we were unable to estimate the benefits associated 

with the hazardous 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, 1995). 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 expressed 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 without an appreciable risk of deleterious non-cancer health effects during a lifetime.
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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 overestimate 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 analysis 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 functions, 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, 2008).
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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 

vulnerable 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 benefits 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 

continuing to explore additional concepts of benefits, including changes in the distribution of 

risk. 
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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 chloride, 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 

considered 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 peripheral 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 damage 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 cancer. 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. Lung 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.

 29Agency 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>

30U.S. Environmental Protection Agency (U.S. EPA). 1998. Integrated Risk Information System File for Arsenic. 

Research and Development, National Center for Environmental Assessment, Washington, DC. This material is 

available electronically at: http://www.epa.gov/iris/subst/0278.htm.

31Agency 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>.
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4.3.1.3 Chlorine (Cl2)

The acute (short term) toxic effects of Cl2 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 Cl2 (1 to 10 parts per million, ppm) may cause eye and nasal irritation, sore 

throat, and coughing. Chronic exposure to Cl2, usually in the workplace, has been reported to 

cause corrosion of the teeth. Inhalation of higher concentrations of Cl2 gas (greater than 15 ppm) 

can rapidly lead to respiratory distress with airway constriction and accumulation of fluid in the 

lungs (pulmonary edema). Exposed 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 Cl2 may induce lung collapse. Exposure to Cl2

can lead to reactive airways dysfunction syndrome (RADS), a chemical irritant-induced type of 

asthma. Dermal exposure to Cl2 may cause irritation, burns, inflammation and blisters. EPA has 

not classified Cl2 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 other 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.

 32Agency for Toxic Substances and Disease Registry (ATSDR). Medical Management Guidelines for Chlorine. 

Atlanta, GA: U.S. Department of Health and Human Services. 

http://www.atsdr.cdc.gov/mmg/mmg.asp?id=198&tid=36.

33U.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. 
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4.3.1.5 Hydrogen Chloride (HCl)

Hydrogen chloride is a corrosive 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 

respiratory 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 because 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 may 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 followed 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 particularly 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 

 34Agency 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.atsdr.cdc.gov/mmg/mmg.asp?id=758&tid=147#bookmark02.

35U.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.

36All health effects language for this section came from: Agency for Toxic Substances and Disease Registry 

(ATSDR). 2007. Medical Management Guidelines for Hydrogen Cyanide (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. 

37U.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 Assessment 

Office, Office of Health and Environmental Assessment, Office of Research and Development, Cincinnati, OH. 

1989.
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exposure to fluoride 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 occupationally 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. Longterm exposure of adults to Pb at work has resulted in decreased 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. Lead 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 persist 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 on 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 intakes 

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, characterized 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 

 38Agency for Toxic Substances and Disease Registry (ATSDR). 2007. Public 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>.

39U.S. Environmental Protection Agency. Integrated Risk Information System (IRIS) on Manganese. National 

Center for Environmental Assessment, Office of Research and Development, Washington, DC. 1999.
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workers afflicted with Manganism attributed to inhalation 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 accumulates 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 with 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 concluded 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 “additional 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 

 40National Research Council (NRC). 2000. Toxicological Effects of Methylmercury. Washington, DC: National 

Academies Press.
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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 more well-established neurotoxicity data 

base. 

The Mercury Study41 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 genetic 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 relationship 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 

autoimmune 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 Cancer44 and in IRIS.

45 The existing 

evidence supporting the possibility 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 association between Hg exposure and specific types of cancer incidence (e.g., acute 

leukemia and liver cancer).39

 41U.S. Environmental Protection Agency (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>.

42Amorim, M.I.M., D. Mergler, M.O. Bahia, H. Dubeau, D. Miranda, J. Lebel, R.R. Burbano, and M. Lucotte. 2000. 

Cytogenetic damage related to low levels of methyl mercury contamination in the Brazilian Amazon. An. Acad. 

Bras. Ciênc. 72(4): 497-507.

43Agency for Toxic Substances and Disease Registry (ATSDR). 1999. Toxicological Profile for Mercury. U.S. 

Department of Health and Human Services, Public Health Service, Atlanta, GA.

44International Agency for Research on Cancer (IARC). 1994. IARC Monographs on the Evaluation of Carcinogenic 

Risks to Humans and their Supplements: Beryllium, Cadmium, Mercury, and Exposures 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).

45U.S. Environmental Protection Agency (EPA). 2002. Integrated 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
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There is also some evidence of reproductive and renal toxicity in humans from MeHg 

exposure. However, overall, human data regarding reproductive, renal, 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 and 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 (SeO2) by 

inhalation results primarily in respiratory effects, such as irritation of the mucous membranes, 

pulmonary 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 as a Group B2, 

probable human carcinogen. 

4.3.2 Additional SO2 Health Co-benefits

In addition to being a precursor to PM2.5, SO2 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 SO2 in this analysis because we do not 

have air quality modeling data available. Therefore, this analysis only quantifies and monetizes 

the PM2.5 co-benefits associated with the reductions in SO2 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, Office 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 (SO2 ISA) 

concluded that there is a causal relationship between respiratory health effects and short-term 

exposure to SO2.

50 The immediate effect of SO2 on the respiratory system in humans is 

bronchoconstriction. Asthmatics are more sensitive to the effects of SO2 likely resulting from 

preexisting inflammation associated with this disease. A clear concentration-response 

relationship has been demonstrated in laboratory studies following exposures to SO2 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 SO2 ISA identified 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 SO2 ISA. The SO2 ISA also 

concluded that the relationship between short-term SO2 exposure and premature mortality was 

“suggestive of a causal relationship” because it is difficult to attribute the mortality risk effects to 

SO2 alone. Although the SO2 ISA stated that studies are generally consistent in reporting a 

relationship between SO2 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 

constraints.

4.3.3 Visibility Impairment Co-benefits

Reducing secondary formation of PM2.5 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 increases 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 Agency (U.S. EPA). 2008a. 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 0737-5352-32, Colorado 

State University.
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4-36

U.S., particularly during winter (U.S. EPA, 2009). Previous analyses52 show that visibility 

benefits can be a significant welfare benefit category. Without air quality modeling, we are not 

unable to estimate visibility 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 Manual 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. “Characterizing 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 Costs 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 PM2.5 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/fullreport.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-up 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.

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 0737-5352-32, Colorado State University.

U.S. Environmental Protection 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/mact/petroria.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. Available 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/34355712EC011A358525719A0

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 the 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***

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U.S. Environmental Protection Agency (U.S. EPA). 2008a. 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 (Final 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 ConcentrationResponse Function for PM2.5-related Mortality. Research Triangle Park, NC. June. 

Available on the Internet at <www.epa.gov/ttn/ecas/regdata/Benefits/thresholdstsd.pdf>.

U.S. Environmental Protection Agency (U.S. EPA). 2010c. Valuing Mortality Risk Reductions 

for Environmental 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. EPA). 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 Internet at <http://www.epa.gov/ttn/ecas/regdata/RIAs/matsriafinal.pdf>.
***E.O. 12866 Review- Draft-Do Not Cite, Quote, or Release During Review***

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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. Available 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 Boilers 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 National 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 Protection 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/regdata/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 PM2.5 Precursors from 17 sectors. Office of 

Air Quality Planning and Standards, Research 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). 2000. An 

SAB Report on EPA’s White Paper Valuing the Benefits 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). 2004c.

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 Benzene 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>.
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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/81e39f4c09954fcb85256ead006be86

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 

Draft, 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). 2010a. 

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>.
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5-1

SECTION 5

ECONOMIC IMPACT 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, 2010). 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) adopted a market-level 

analysis described in the Office’s resource 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 these markets. Key measures in this analysis include

■ market-level effects (market prices, changes in domestic production and

consumption, and international trade) and

■ social costs and their distribution between producers and consumers.

We also assessed the impacts 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 fact 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.
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5.1.1 Market-Level Results

Market-level impacts 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 year. 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 the 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 Central market price increase ($7.45 per 1,000 SBE) is associated with higher 

per-unit compliance costs ($16.56 per 1,000 SBE). Under the final standards, one region does not 

include any facilities with incremental compliance costs (New England). As a result, 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 average regional price increases between 0% 

and 3.8%. Regional domestic production falls between 0% and 3.0%, or 0 to 16 million bricks 

per year. Under the Option 3 standards, the average regional price increases between 0% and 

5.8%. Regional domestic production falls between 0% and 4.6%, or 0 to 33 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 

$15.1 million (2011$) 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 $12.1 million, and the total U.S. economic surplus 

loss is $27.2 million. Under the Option 1 standards, total U.S. economic surplus loss is $0.6

million lower ($26.6 million), and under the Option 3 standards, total U.S economic surplus loss 

is $21.4 million higher ($48.6 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%). 
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5-3

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)
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5-4

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)
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5-5

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
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5.2 Employment Impacts of the Final Rule53

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 while promoting economic growth, 

innovation, competitiveness, and job creation. It must be based on the best available science”

(Executive Order 13563, 2011). Although standard benefit-cost analyses have not typically 

included a separate analysis of regulation-induced employment impacts,54 during periods of 

sustained high unemployment, employment 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 discusses the limited empirical literature that is available. The chapter then 

discusses the potential employment impacts 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 demand for regulated firms. Section 

5.2.2 presents an overview of the peer-reviewed literature relevant to evaluating the effect of 

environmental regulation 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 offers several 

conclusions.

5.2.1 Theory

The 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. Labor 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]”

pursuant to CAA section 321(a). 54Labor expenses do, however, contribute toward total costs in EPA’s standard benefit-cost analyses.
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sectors, and the pollution abatement sector) and over time. In light of these difficulties, economic

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 production, 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 prices.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 regulations 

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 

 55See Layard and Walters (1978), a standard microeconomic theory textbook, for a discussion. 56See Hamermesh (1993), Chapter 2, for a derivation of the firm’s labor demand function from cost-minimization. 57In this framework, labor demand is a function of quantity of output and prices (of both outputs and inputs). 58Berman 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. 59The authors also 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-shift effect.
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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, equipment 

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 “quasifixed” pollution 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 regulatory 

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 “quasifixed” factor if there were specific requirements for landfill 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 estimation 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 

estimation: 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 methods 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.
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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 factors 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 compliance 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 regulatory 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 confidential 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 sector 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 environmental 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 multiple sectors or industries.

On the one hand, if 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

 60On Marshall’s laws of derived demand, see Ehrenberg and Smith (2000), Chapter 4. 61See Ehrenberg and Smith (2000), p. 108. 

62This discussion draws from Berman and Bui (2001), p. 293. 63Full 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. 
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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 likely 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 

environmental regulation on employment; it could cause either a short-run net increase or shortrun 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 sectors 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 costs 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 positive 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 productivity65 or employees’ ability to work. Although 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 more detailed labor and environmental data and quasiexperimental techniques that is starting to find traction on this question. These are described in 

Section 5.2.6.

To summarize the discussion in this section, economic theory provides a framework for 

analyzing 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 economic theory, labor 

demand impacts for regulated firms, and also for the regulated industry, can be decomposed into 

 64Arrow 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. 65For example, Graff Zivin and Neidell (2012).
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output and substitution effects. With these potentially competing forces, under standard 

neoclassical theory estimation of net employment effects 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 work

analyzes various aspects of labor demand, relying on the above theoretical framework.66 This 

work focuses primarily on the effects of employment policies, for example, labor taxes and 

minimum wage.67 In contrast, the peer-reviewed empirical literature specifically estimating 

employment effects of environmental regulations is very limited. In this section, we present an 

overview of the latter. As discussed in the preceding section on theory, determining the direction 

of employment effects in regulated industries 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. 

Several 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, 2002; Walker, 2011). However, because these 

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 rather 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 technologies and process 

changes to meet the new requirements. When a regulation is promulgated, the initial response of 

 66Again, see Hamermesh (1993) for a detailed treatment. 67See Ehrenberg and Smith (2000), Chapter 4: “Employment Effects: Empirical Estimates” for a concise overview.
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firms is often to order pollution control equipment and services to enable compliance 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, 2011b).

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 profitmaximizing/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 estimate 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 incorporates 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 identified the effect of environmental regulations on net employment in the regulated 

industries.68 In particular, they compared 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 found that “while regulations do impose large 

costs, they have a limited effect on employment” (Berman and Bui, 2001, p. 269). Their 

conclusion is that local 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 Bui, 

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 

 68Note, like Morgenstern, Pizer, and Shih (2002), this study does not estimate the number of jobs created in the 

environmental protection sector. 69Berman and Bui include over 40 4-digit SIC industries in their sample. 70Including 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).
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to local markets 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 similar structural approach to Berman 

and Bui’s, but their empirical application used 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 sectors (pulp and paper, plastics, steel, and petroleum refining). Thus, in 

contrast to Berman and Bui (2001), this study identified 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 demand 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 

billion 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 mediumsize companies represent 99% of private ET firms, producing 20% of total revenue (OEEI, 

2010).

5.2.5 Labor Supply Impacts

As described above, the small empirical literature on employment effects of 

environmental regulations focuses primarily on labor demand impacts. However, there 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 on labor supply, even at pollution levels below mandated regulatory thresholds. Many 

 71See Bezdek, Wendling, and Diperna (2008), for example, and U.S. Department of Commerce (2010). 
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researchers have found that work-loss days and sick days, as well as mortality, are reduced when 

air pollution is reduced (EPA, 2011a). 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 the economy (EPA, 2011a).Another literature 

estimates how worker productivity improves at the work site when pollution is reduced. Graff 

Zivin and Neidell (2013) reviewed this literature, focusing on how health and human capital may 

be affected by environmental quality, particularly air pollution. In previous research, Graff Zivin 

and Neidell (2012) used detailed worker-level productivity data from 2009 and 2010, paired 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 identified an effect of 

daily variation in monitored ozone levels on productivity. They found “that 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 macroeconomic 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 effects. 

5.2.7 Information Specific to this Regulation 

In 2011, 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). 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 effects 

associated with the regulation:
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■ additional labor requirements (full-time equivalents [FTEs]) associated with meeting 

the new regulation 

■ employment effect of facilities that may exit the BSCP industry 

As shown in Table 5-2, EPA estimates that the regulation will require an additional 

181,000 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 and 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 $4.13 176,000

Option 2 Final $4.24 181,000a

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 (2013b), 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 anticipation 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. 

Economic 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 national 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. 
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5.3 Impacts on Small Entities

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) criterion 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 that 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 (IRFA). 

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 the 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 businesses.

EPA assessed how the regulatory program may influence the profitability of ultimate 

parent companies by comparing pollution control costs to total sales (i.e., a “sales” test or costto-sales ratios [CSR]). To do this, we divided an ultimate parent company’s (i) total annualized 

compliance costs by its reported revenue:

Sales Testi = 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 of 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

Estimatedb

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 lower and upper bound 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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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 standards, 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 twelve small brick manufacturing 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. Firms 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 costs 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 estimates 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 recommendations 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 75669-75671.
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As required by section 604 of the 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 included in Section 5 of “Regulatory 

Impact Analysis: Final Brick and Structural Clay Products 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 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 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 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 

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 EPA must consider not only the 

maximum degree of reduction in emissions of HAPs 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-HQ-OAR-2013-0291 for more 

detailed comment summaries and responses.
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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 the 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 noted 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 non-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 facilities. 

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.
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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 different 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 kilns 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-fired 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 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 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 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 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 additional details).
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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 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 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 rule 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 to 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 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, 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 proposed 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 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.
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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, equity financing, and financing 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 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 costs to company sales (costto-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, Recordkeeping, 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 

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.

5.3.2.7 Significant Alternatives

The EPA considered three major options for this final rule; see “Regulatory Impact 

Analysis: Final Brick and Structural Clay Products NESHAP,” in Docket ID No. EPA-HQOAR-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 
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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-HQ-OAR-2013-0291, 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 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 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 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.

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.” American 

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 in 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. 
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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, Princeton, 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.

Layard, P.R.G., and A.A. Walters. 1978. “Microeconomic Theory.” McGraw-Hill, Inc. 

List, J.A., D.L. Millimet, P.G. Fredriksson, and W.W. McHone. 2003. “Effects of Environmental 

Regulations on Manufacturing Plant Births: Evidence from a Propensity Score Matching 

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. 

Schmalansee, 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. Environmental 

Protection Agency. http://www.epa.gov/ttn/ecas/regdata/RIAs/matsriafinal.pdf. 
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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).
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SECTION 6

STATUTORY AND EXECUTIVE 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 Management 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 contained 

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-HQ-OAR-2013-

0291), and the analysis is briefly summarized here.

The EPA’s study estimates 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 have 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 mortality among populations exposed to PM2.5

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 HAPs each year for the promulgated standards, as well as 

ecosystem effects and visibility impairment. In addition to reducing emissions of PM precursors 

such as SO2, 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 
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$75 million to $170 million (2011 dollars) at a 7% discount rate on a yearly average 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 requirements 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. You 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 enforcement 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 continuous 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 records 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 practice 

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 
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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 kilns 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 standards. 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 is 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 initial 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 facilities 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 for 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 

calendar 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 completion of the performance 

test. For each initial compliance demonstration that does not involve a performance test, facilities 
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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 than 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 

(averaged 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, recordkeeping 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 respondent 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 annual 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 conduct 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 this ICR, the agency will announce that approval in the Federal Register and publish a 
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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 Flexibility 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 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 75669-75671.

As required by section 604 of the 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 included in Section 5 of “Regulatory 

Impact Analysis: Final Brick and Structural Clay Products NESHAP,” available for review in the 

docket (Docket ID No. EPA-HQ-OAR-2013-0291), 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 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.

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 

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 EPA must consider not only the 

maximum degree of reduction in emissions of HAPs but must also take into account costs, 
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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 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-HQ-OAR-2013-0291 for more 

detailed comment summaries and responses.

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 the 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 noted 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 non-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 facilities. 

Other commenters supported the EPA’s decision to propose health-based standards for acid 
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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.

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 different 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 kilns 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-fired 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 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 practices for minimizing emissions during these 

periods (see section V.C of this rule’s preamble for additional information).
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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 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 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 preamble for additional details).

6.4.4 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 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 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 rule 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 to 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 facilities in the BSCP industry. This 
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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 proposed 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 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, equity financing, and financing 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 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.

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 (costto-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 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. 
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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 

Analysis: Final Brick and Structural Clay Products NESHAP,” in Docket ID No. EPA-HQOAR-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 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-HQ-OAR-2013-0291, 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 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 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 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 million 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 sector. 
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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 responsibilities 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 direct 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 

action 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 assessments are contained 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-OAR2013-0291-0132.

6.9 Executive Order 13211: Actions Concerning 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. 
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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 test 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 test 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 believes 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 level 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 minority 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-HQ-OAR-2013-0291-

0102.)
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6.11 Congressional Review Act (CRA)

This action is subject to the CRA, and the EPA will submit a rule report to each house 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).
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SECTION 7

COMPARISON OF BENEFITS 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 social 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 effects 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 $190 million (Table 7-1). Using a 7% discount rate, we estimate the total 

monetized benefits to be $75 million to $170 million. The annualized costs are $27 million at a 

7% interest rate. The net benefits are $56 million to $160 million at a 3% discount rate for the 

benefits and $48 million to $150 million at a 7% discount rate.

Table 7-1. Summary of the Monetized Benefits, Social Costs, and Net Benefits (million 

2011$)

Total (3% Discount Rate) Total (7% Discount Rate)

Final Standards

Total Monetized Benefits $83 to $190 $75 to $170

Total Social Costsa $27

Net Benefits $56 to $160 $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. 
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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 

Regiona

East North Central 285,508 81%

East South Central 388,685 100%

Mid-Atlantic 213,583 69%

Mountain 114,154 50%

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.
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A-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 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. As a result, we use a perfectly competitive partial equilibrium model with nine regional 

brick markets (defined by census region). 

The market demand (D) in region (r) with regulation is:

QQDDDD

′ = QQDDDD × �1 + �

PP′

− 1� × ηη� (A.1)

The affected market supply (SA) in region (r) with regulation is:

 72The data include other products 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.
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A-3

QQSS

′ = QQSS × �1 + �

�PP′− �

− 1� × εε� (A.2)

The unaffected market supply (SU) in region (r) with regulation is:

QQSSSS

′ = QQSSSS × �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):

QQDDDD

′ = QQSS

′ + QQSSSS′ (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 decisions 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 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 statistically estimated price elasticities for BSCP. 

However, economy-wide simulation models have suggested the nonmetallic mineral industry 

demand elasticity 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 price response for BSCP is likely more elastic than this 

value.

 73The measure is computed as the percentage change in quantity demanded divided by the percentage change in 

price.
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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 produced 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) developed 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 period75 and the other input that 

varies with production. 

Supply Elasticity = elasticity of substitution × fixed factor value share

1− fixed factor value share

(A.4)

To illustrate the approach, consider the value share of the fixed factor to be 50% 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 × 0.5

1 − 0.5 = 1 (A.5)

Using these values for the fixed 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 

utilization rates and excess capacity available in the industry, this value may underestimate how 

 74The measure is computed as the percentage change in quantity supplied divided by the percentage change in price. 75The fixed factor generally includes plant and capital equipment; factors that vary with production could include 

materials or labor.
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A-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 market 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]

The change in consumer surplus is measured as follows:

∆CS = – [∆Q1 × ∆p] + [0.5 × ∆Q × ∆p]. (A.6)

Higher market prices and lower quantities lead to consumer welfare losses.

For affected supply, the change in producer surplus is measured as follows:

∆PS = [Q1 × ∆p] – [Q1 × unit cost increase] – [0.5 × ∆Q × (∆p –unit cost increase)]. (A.7)

Q1 Q0

P1

P0

h

c

a

$

Output

e

d

S1 : With Regulation

S0 : Without Regulation Price

Increase }

Unit Cost Increase g }

f

b
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A-6

Higher unit costs and lower production level reduce producer surplus. The losses are 

offset to some degree because market prices tend to rise. In contrast, for unaffected supply, the 

change in producer surplus is:

∆PS = [Q0 × ∆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, Student’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 subcategory 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 parenthetical ‘‘(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 emission 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 the 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 THC 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 kilns equipped with CEMs.

22 As noted, basing the proposed existing source THC floor on data from two sources (i.e. 12 

percent of the 15 sources for which we have CEM data) largely eliminates the distinction 

between new and existing source THC floors. 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 should 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 Administrator 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 facilities 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 considering 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 approach 
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 accurately 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 comparison 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 

BSCP Air Pollution Control Devices for the Final Rule

I. Introduction

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 pollutants 

(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 and existing units.1 Therefore, on 

December 18, 2014, the EPA proposed new standards for BSCP manufacturing, including 

standards for HF, HCl, chlorine (Cl2), 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 

appropriate, 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 Model Parameters

Model 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. This section discusses the basis for the general model parameters, which are 

presented in Appendix A at the end of this memorandum.

The model production rates (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 section 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 surveys. 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. The 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 (Regina, 2015).

The model exhaust gas flow rates (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 with 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 dry 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 

pressure):

Equation 1—Flow rate conversion

(100% )

100%

T tan %H O

T Q Q

s dard 2

stack

acfm dscfm − = × ×

where:

Qacfm = exhaust flow rate (acfm),

Qdscfm = exhaust flow rate (dscfm),

Tstack = stack temperature (converted from degrees Fahrenheit [°F] to degrees Rankine 

[°R]),

Tstandard = standard temperature (528°R), and

% H2O = moisture content (percent [%]).
3

Unit costs for electricity ($0.083/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 operator 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, 2012). Wage rates from the 

Bureau of Labor Statistics were used because they were more conservative than those provided 

by BSCP survey respondents. The maintenance 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 2008 survey (Holloway, 2014).

The capital recovery factor (0.0944) was calculated 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 (Cl2), PM, HAP metals, and sulfur 

dioxide (SO2). The model uncontrolled emissions estimates for HF, HCl, PM, Cl2, and SO2 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 emission control devices that BSCP facilities are expected 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 for 

scaling costs at the time that costs were first being developed for the BSCP rule. The model cost 

tables for new and retrofit control devices are presented in Appendices B and C, respectively. 

(Note: The annual 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 retrofitted 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 devices:

• 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 [ft2])

• Compressed air (0.9 cubic feet [ft3

] of compressed air/1,000 ft3 of gas)

• Time to replace bags (2.25 hr/bag)

• Hydrated lime unit cost ($160/ton)

• Bag fabric cost ($8.15/ft2)

• Compressed air unit cost ($0.363/1,000 ft3

)

• Bag capital recovery factor (0.244, based on 5-yr bag life and 7% interest)

With three exceptions, the 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 

the 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, 2014). 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 for 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 pollutants 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) (CE, 2011), scaling the costs 

to the large and small model sizes using the six-tenths cost rule (see Equation 3 below), taking 

the average 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

where:

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 (estimated 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 

$0.083/kWh)

• Lime (estimated based on hydrated lime makeup and $160/ton hydrated lime 

unit cost)

• Compressed air (estimated based on 0.9 ft3

/1,000 ft3 compressed air 

requirements and $0.363/1,000 ft3 compressed air unit cost)

• Replacement bags (estimated based on 3.4 ft/min gas-to-cloth ratio, $8.15/ft2

bag fabric, and 0.244 bag capital recovery factor)

• Bag replacement labor (estimated based on 3.4 ft/min gas-to-cloth ratio, 28 ft2

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 capital 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 have 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 used 

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, 2013b):

• Without the dry lime injection that reduces the acid gas, there will not be 

enough particulates in the kiln exhaust to coat the bags and get good 

performance from the fabric filter.

• The uncontrolled acid in the exhaust stream could rot the bags.

• The exhaust gas temperatures from BSCP tunnel kilns can be high (about 400°F 

on average, as high as 668°F).

• The 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 one of the fabric filter vendors (Solios Environment) agreed with 

industry concerns that that the lack of a dust cake would negatively impact total outlet emissions 

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 to 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 the other fabric filter vendor (McGill AirClean) 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 

woven 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 gases 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 operation 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 

used safely (Childress, 2013b).

A representative from the bag fabric vendor (W.L. Gore & Associates) noted that his 

company had done business with the brick industry before and that they have two kinds of bags 

that could be used for the industry: (1) high-temperature fiberglass bags, and (2) hightemperature 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 not speak to the concern regarding PM 

loading, but did say that there 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 are 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, 2013c).

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 questioned 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 control 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 this 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 that 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 the slight increase in inlet PM loading to the baghouse should not affect the 

performance of the baghouse (Childress, 2013a).

We then contacted an ACI vendor (Cabot Norit Activated Carbon) to obtain information 

on the feasibility and cost of installing an ACI 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,

2013a). 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 were 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 technical support document (TSD) for the HWC MACT 

replacement 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, 2013a]) from the ACI vendor. To determine the purchased 

equipment cost (PEC), the 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 (CE, 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, performance 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 hour/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 $0.083/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 their 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 has been demonstrated for similar sources, e.g., 

Portland cement kilns. Nonetheless, as a result of these comments, we investigated other possible 

technologies for limiting mercury emissions, including, but not limited to, the following:

• Halogenated carbon sorbents, such as brominated activated carbon from 

Albemarle Corp., which is effective in reducing both elemental and oxidized 

mercury (Albemarle, 2015).
9

• Reagents, such as Amended Silicates HgX (As-HgXTM) from Novinda, which 

reacts 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-CureTM mercury reduction system 

from Alstom, which uses a unique injection methodology designed to minimize 

mass transfer limitations between the vapor phase mercury and carbon sorbent 

(Alstom, 2014).

• New technologies, such as Mercury Capture Systems (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 could be used.

Brominated ACI and AS-HgXTM 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 costs for the Mer-CureTM system may 

become less expensive than plain ACI over time (Alstom, 2014), this is a new market that will 

likely need time to grow. The costs to measure mercury content of individual plant locations and 

limit raw material collection accordingly are expected to be very site-specific, and 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 obtaining a federally enforceable 

limit reducing emissions below major source thresholds, those 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 impacted 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 to control HF emissions and also provide limited 

control of HCl and Cl2 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 [small]/90 hp [large])

• Total horsepower for other motors (10 hp [small]/40 hp [large])

• Limestone rate (85 lb/hr [small]/120 lb/hr[large])

• Limestone 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 the 

values of the other model DLA parameters were determined based on averages of industry 

responses to the 2008 BSCP survey (Holloway, 2014).

The model DLA capital costs were estimated by taking DLA capital cost data from 

industry responses 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 adjusted by a 

factor of 1.070.5 to equalize the net present value (NPV).

The model DLA 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)

• Electricity (estimated based on hp requirements, 0.745 kW/hp, and 

$0.083/kWh)

• Limestone (estimated based on limestone rate and $58.17/ton limestone 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 presents 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 of Control Option Model Costs

Control Option Cost parameters 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 expected 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 devices are presented in Appendices E and F, 

respectively.

A. Emission Reductions

Model emission reductions were estimated for the major pollutants emitted from BSCP 

tunnel kilns, including both HAP (HF, HCl, Cl2, and HAP metals) and non-HAP (PM and SO2). 

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 the 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 kilowatt-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 British 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 conversion 

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 heat 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 natural 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/hydroelectric (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), nitrogen oxides (NOX), and SO2—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 multiplying 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 pounds per 

cubic foot [lb/ft3

] of natural gas) from the AP-42 chapter on natural gas combustion to estimate 

the secondary emissions for PM, CO, NOX, and SO2 (EPA, 1998a). We used the AP-42

conversion factor of 1,020 Btu/ft3 of natural gas to convert the emission factors to pounds per 

million British thermal units (lb/MMBtu) to facilitate estimating 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 SO2 (EPA, 2006). We used emission 

factors (in lb/ton coal) from the AP-42 chapter on coal combustion to estimate the secondary 

emissions for NOX and CO; we specifically used the AP-42 emission factors for 

bituminous/subbituminous coal combustion/spreader stokers (EPA, 1998b). The NOX 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 secondary emissions for 

NOX 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, or renewable energy generation. The secondary air impacts for “other” fuels were 

assumed to be equivalent 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:

• Reaction products from the reaction of the lime with the acid gases,

• Unreacted lime, and

• Particulate matter from 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 emission 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 estimated the wastewater impacts associated with using a spray 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 following 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 system (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 the 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 

include 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 control 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 emissions reductions, tpy

SCD LCD

Replace dry limestone adsorber 

with new 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

Replace spray dryer/ESP with new 

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

Replace existing DIFF with new, 

more efficient 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 impacts1

SCD LCD

Replace dry limestone adsorber 

with new DIFF

Energy impacts, MMBtu/yr 7,055 5,772

Solid waste impacts, tpy 80.10 165

Replace spray dryer/ESP with new 

DIFF

Energy impacts, MMBtu/yr -9,299 -27,577

Solid waste impacts, tpy 8.66 14.43

Wastewater impacts, gpy -2,281 -4,563

Replace existing DIFF with new, 

more efficient 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 pollutant1

Secondary air impacts, tpy

SCD LCD

Install new DIFF Particulate matter 0.09 0.10

PM2.5 0.029 0.035

Carbon monoxide 0.14 0.18

Nitrogen oxides 1.14 1.39

Sulfur dioxide 3.33 4.06

Install fabric filter Particulate matter 0.09 0.10

PM2.5 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

PM2.5 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

PM2.5 0.0009 0.0015

Carbon monoxide 0.005 0.008

Nitrogen oxides 0.04 0.06

Sulfur dioxide 0.11 0.18

1 PM2.5 = PM with particles less than 2.5 micrometers in diameter.
17

Table 4b. Summary of Model Secondary Impacts for Control Replacement Options

Control option Secondary pollutant2

Increase in secondary air 

impacts, tpy1

SCD LCD

Replace dry limestone adsorber 

with new DIFF

Particulate matter 0.05 0.04

PM2.5 0.017 0.014

Carbon monoxide 0.09 0.07

Nitrogen oxides 0.70 0.57

Sulfur dioxide 2.03 1.66

Replace spray dryer/ESP with new 

DIFF

Particulate matter -0.07 -0.20

PM2.5 -0.023 -0.068

Carbon monoxide -0.12 -0.34

Nitrogen oxides -0.92 -2.73

Sulfur dioxide -2.68 -7.94

Replace existing DIFF with new, 

more efficient DIFF

Particulate matter 0 0

PM2.5 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 PM2.5 = PM with particles less than 2.5 micrometers in diameter.

V. References

Albemarle Corp. 2015. Sorbents. Available at: http://www.albemarle.com/products---

markets/performance-chemicals/specialty-chemicals/mercury-control/sorbents-164.html. 

Accessed September 14, 2015.

Alstom. 2014. Mer-CureTM: Mercury reduction system. Boiler Service Solutions. 2014. 

Available at: http://www.alstom.com/Global/Power/Resources/Documents/Brochures/aqcsmer-cure-mercury-reduction-system.pdf?epslanguage=en-GB. Accessed September 14, 2015.

BLS (U.S. Department of Labor, Bureau of Labor Statistics). 2012. Occupational Employment 

Statistics: May 2011 National Industry-Specific Occupational Employment and Wage 

Estimates. NAICS 327100 - Clay Product and Refractory Manufacturing. Industrial 

Engineering Technician. March 27, 2012. Available 

at: http://www.bls.gov/oes/2011/may/naics4_327100.htm. Docket Item No. EPA-HQ-OAR2013-0291-0069.

CE (Chemical Engineering). 2011. Plant Cost Index.

Childress, J. 2013a. “RE: From McGill AirClean Web Site.” E-mail from Jerry Childress, 

McGill AirClean LLC, to Thomas Holloway, RTI International. April 18, 2013. Docket Item 

No. EPA-HQ-OAR-2013-0291-0224.
18

Childress, J. 2013b. “RE: From McGill AirClean Web Site.” E-mail from Jerry Childress, 

McGill AirClean LLC, to Thomas Holloway, RTI International. June 27, 2013. Docket Item 

No. EPA-HQ-OAR-2013-0291-0219.

EPA (U.S. Environmental Protection Agency). 1998a. Compilation of Air Pollutant Emission 

Factors. Volume 1: Stationary Point and Area Sources. AP-42, Section 1.4: Natural Gas 

Combustion. July 1998. Docket Item No. EPA-HQ-OAR-2013-0291-0001.

EPA (U.S. Environmental Protection Agency). 1998b. Compilation of Air Pollutant Emission 

Factors. Volume 1: Stationary Point and Area Sources. AP-42, Section 1.1: Bituminous and 

Subbituminous Coal Combustion. September 1998. Docket Item No. EPA-HQ-OAR-2013-

0291-0002.

EPA (U.S. Environmental Protection Agency). 2002. EPA Air Pollution Control Cost Manual. 

Sixth Edition. Office of Air Quality Planning and Standards, Research Triangle Park, NC. 

Publication No. EPA/452/B-02-001. January 2002. Docket Item No. EPA-HQ-OAR-2013-

0291-0011.

EPA (U.S. Environmental Protection Agency). 2005. Technical Support Document for the HWC 

MACT Replacement Standards, Volume V: Emissions Estimates and Engineering Costs. 

Office of Solid Waste and Emergency Response, Washington, DC. September 2005. Docket 

Item No. EPA-HQ-OAR-2013-0291-0025.

EPA (U.S. Environmental Protection Agency). 2006. “Subpart Da—Standards of Performance 

for Electric Utility Steam Generating Units for Which Construction is Commenced After 

September 18, 1978.” Code of Federal Regulations, Title 40, Part 60. Published by Office of 

the Federal Register, National Archives and Records Administration. As of July 1, 2006.

EPA (U.S. Environmental Protection Agency). 2011. Regulatory Impact Analysis for the Final 

Mercury and Air Toxics Standards. Table 3-6: Generation Mix with the Base Case and the 

MATS, 2015 (Thousand GWh). Publication No. EPA-452/R-11-011. December 2011.

Docket Item No. EPA-HQ-OAR-2013-0291-0067.

EPA (U.S. Environmental Protection Agency). 2015. 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. September 2015.

Hansen, L. 2013. “RE: Question regarding use of fabric filters for brick kilns.” E-mail from Lars

Hansen, Solios Environment Corp., to Thomas Holloway, RTI International. July 2, 2013.

Docket Item No. EPA-HQ-OAR-2013-0291-0218.

Holloway, T. 2009. Revised Baseline Operating Costs for Existing HMIWI. Memorandum from 

Thomas Holloway, RTI International, to Ketan Patel, OAQPS/SPPD/NRCG. June 19, 2009.

Holloway, T. 2013a. Telephone Contact Summary: Jeff Thompson, Cabot Norit Activated 

Carbon. Contacted by Thomas Holloway, RTI International. May 16, 2013. Docket Item No.

EPA-HQ-OAR-2013-0291-0221.
19

Holloway, T. 2013b. “RE: From McGill AirClean Web Site.” E-mail from Thomas Holloway, 

RTI International, to Jerry Childress, McGill AirClean LLC. June 26, 2013. Docket Item No.

EPA-HQ-OAR-2013-0291-0219.

Holloway, T. 2013c. Telephone Contact Summary: Chris Polizzi, W.L. Gore & Associates, Inc.

Contacted by Thomas Holloway, RTI International. July 16, 2013. Docket Item No. EPAHQ-OAR-2013-0291-0217.

Holloway, T. 2014. Updated Inventory Database and Documentation for Brick and Structural 

Clay Products Proposed Rule. Memorandum from Thomas Holloway, RTI International, to 

Jeff Telander, EPA/OAQPS/SPPD. November 6, 2014. Docket Item No. EPA-HQ-OAR2013-0291-0125.

Morris, L. 2012. “Solutions for Controlling Mercury.” Power Engineering. Volume 116, Issue 4. 

April 1, 2012. Available at: http://www.power-eng.com/articles/print/volume-116/issue4/features/solutions-for-controlling-mercury.html. Accessed September 14, 2015.

Novinda. 2015. What is Amended SilicatesTM? Available at: http://www.novinda.com/producttechnologies/mercury-removal/what-is-amended-silicates/. Accessed September 14, 2015.

Poling, C. et al. 2015. A Novel Approach for Mercury Capture. Presentation by Christopher L. 

Poling, Melissa Harrison, and Paul Longo, SCB International Materials, Inc., to U.S. 

Environmental Protection Agency. 2015.

Raymond, G. 2014. Test Data Used in BSCP Proposed Rule. Memorandum from Gabrielle 

Raymond, RTI International, to Jeff Telander, EPA/OAQPS/SPPD. November 6, 2014.

Docket Item No. EPA-HQ-OAR-2013-0291-0121.

Regina, P. 2015. “RE: Docket no. EPA-HQ-OAR-2013-0291 Brick and Structural Clay Products 

Manufacturing.” Letter from Paul Regina, The Brick Industry Association, to Environmental 

Protection Agency, EPA Docket Center. March 19, 2015. Docket Item No. EPA-HQ-OAR2013-0291-0542.

Shrager, B. 2003. Final Rule: Costs for Air Pollution Control Devices on Kilns. Memorandum 

from Brian Shrager, RTI International, to Mary Johnson, U.S. Environmental Protection 

Agency. February 25, 2003.

Tayler, G. 2015. “RE: Docket no. EPA-HQ-OAR-2013-0291 Brick and Structural Clay Products 

Manufacturing.” Letter from Dr. Garth Tayler, Acme Brick Co., to Environmental Protection 

Agency, EPA Docket Center. March 14, 2015. Docket Item No. EPA-HQ-OAR-2013-0291-

0516.

Thompson, J. 2013. “FW: Cabot Norit Activated Carbon–question.” E-mail from Jeff Thompson, 

Cabot Norit Activated Carbon, to Thomas Holloway, RTI International. May 31, 2013.

Docket Item No. EPA-HQ-OAR-2013-0291-0220.
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 0.083 0.083 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

SO2 64 64

CaF2 78 78 7

CaCl2 111 111 7

CaSO3 120 120 7

Ca(OH)2 74 74 8

Uncontrolled emissions, lb/ton

HF 0.594 0.594 3

HCl 0.0808 0.0808 3

Cl2 0.00346 0.00346 3

Non-Hg HAP Metals 0.00356 0.00356 9

PM 0.324 0.324 3

SO2 3.23 3.23 3

Uncontrolled emissions, lb/hr

HF 4.16 8.91 10

HCl 0.566 1.21 10

Cl2 0.0242 0.0519 10

Non-Hg HAP Metals 0.0249 0.0534 10

PM 2.27 4.86 10

SO2 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. Mean hourly wage, from Bureau of Labor Statistics, May 2011 National Industry-Specific Occupational 

Employment and Wage Estimates, NAICS 327100, 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; CaF2 = calcium fluoride; CaCl2 = calcium chloride; CaSO3 = calcium sulfite.

8. Hydrated lime.

9. Assume 1.1 percent of PM.

10. Calculated from lb/ton times production rate.
Appendix B

Installation 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

Cl2 89.3% 89.3% 3

Non-Hg HAP Metals 94% 94% 4

PM 94% 94% 1

SO2 48.7% 48.7% 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, ft2 28 28 6

Compressed air, ft3/1,000 ft3 0.9 0.9 6

Time to replace bags, hr/bag 2.25 2.25 6

Added cooling air, ft3/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, $/ft2 8.15 8.15 6

Compressed air, $/1,000 ft3 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 Cl2 reduction.

4. Assume same as PM.

5. Based on ratio of enhanced HF reduction and baseline SO2 reduction.

6. Average from section 114 survey responses.

7. Assume hydrated lime is 2.64/1.78 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. CaF2 (calcium fluoride), CaCl2 (calcium chloride), and CaSO3 (calcium 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 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, ft2 28 28 3

Compressed air, ft3/1,000 ft3 0.9 0.9 3

Time to replace bags, hr/bag 2.25 2.25 3

Added cooling air, ft3/min 0 0 5

Calculated parameters

Waste, lb/hr 2.1 4.6 6

Cost factors

Bag fabric cost, $/ft2 8.15 8.15 3

Compressed air, $/1,000 ft3 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 Operating 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 injection 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 30% 30% 1

Cl2 42% 42% 1

Non-Hg HAP Metals 20% 20% 2

PM 20% 20% 1

SO2 12% 12% 1

Design and operating parameters

Fan hp 60 90 3

Total hp for other motors 10 40 3

Limestone, lb/hr 85 120 3

Operator labor, hr/shift 1.5 1.5 4

Maintenance labor, hr/shift 0.75 0.75 3

Calculated parameters

Reaction products, lb/hr 13.2 28.3 5

Reacted limestone, lb/hr 14.5 31.1

Particulate matter, lb/hr 0.07 0.07

Waste, lb/hr 83.7 117.2 6

Cost factors

Limestone, $/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

Limestone 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. CaF2 (calcium fluoride), CaCl2 (calcium chloride), and CaSO3 (calcium sulfite).

6. Inlet limestone minus reacted limestone plus reaction products and PM.

7. Average from 2015 BIA survey data.
B-7

8. Factor to equalize the net present value (NPV) = 1.070.5 = 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.

12. Based on conversion factor of 0.745 kW/hp.

13. Some facilities have minimal waste disposal costs.

14. 60 percent of labor and maintenance materials.

15. 2 percent of TCI.

16. 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

Cl2 89.3% 89.3% 3

Non-Hg HAP Metals 94% 94% 4

PM 94% 94% 1

SO2 48.7% 48.7% 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, ft2 28 28 6

Compressed air, ft3/1,000 ft3 0.9 0.9 6

Time to replace bags, hr/bag 2.25 2.25 6

Added cooling air, ft3/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, $/ft2 8.15 8.15 6

Compressed air, $/1,000 ft3 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 5,563 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 Cl2 reduction.

4. Assume same as PM.

5. Based on ratio of enhanced HF reduction and baseline SO2 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. CaF2 (calcium fluoride), CaCl2 (calcium chloride), and CaSO3 (calcium 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 factor, 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

SCD LCD SCD LCD Footnotes

Design and operating parameters

Carbon injection rate (lb/MMft3) [CIR] 2 2 3 3 1

Injection blower fan power (hp) [Powerfan] 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

SCD LCD SCD LCD Footnotes

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/MMft3.

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, 2013a. 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 Powerfan / (1.34 hp/kW) / (0.9 Efficiencyfan) 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 

(HCelec)

3,415 Btu/kWh

Heat rate

 Coal (HRcoal) 10,415 Btu/kWh

 Natural gas (HRgas) 8,185 Btu/kWh

 Nuclear power (HRnuclear) 10,452 Btu/kWh

 Renewable energy (HRrenew) 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 (Ecoal) 33% % = HCelec / HRcoal * 100

Natural gas/other (Egas) 42% % = HCelec / HRgas* 100

Nuclear (Enuclear) 33% % = HCelec / HRnuclear * 100

Renewable/hydroelectric 

(Erenew)

35% % = HCelec / HRrenew * 100

Average (Eavg) 35% % = (Ecoal x % coal) + (Egas x % gas/other) + (Enuclear x 

% nuclear) + (Erenew 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 (HCelec) x (MMBtu/1E6 Btu) / Eavg

Secondary emissions

Emission factors, natural gas

Particulate matter/PM2.5 1.9 lb/MM ft3 natural gas

0.00186275 lb/MMBtu natural gas

Carbon monoxide 84 lb/MM ft3 natural gas

0.0824 lb/MMBtu natural gas

Nitrogen oxide 100 lb/MM ft3 natural gas

0.0980 lb/MMBtu natural gas

Sulfur dioxide 0.6 lb/MM ft3 natural gas

0.00059 lb/MMBtu natural gas

Emission factors, solid fuel

Particulate matter 0.03 lb/MMBtu solid, liquid, gaseous fuel

PM2.5 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 Regulatory Impacts Analysis for the final Mercury 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 capacity expansion, electricity dispatch, and emission control 

strategies for meeting energy demand and environmental, transmission, dispatch, and reliability constraints.

3. For natural gas, used PM, CO, NOX, and SO2 emission factors from AP-42 chapter on natural gas combustion.

Assumed 1,020 Btu/ft3 of natural gas in estimating PM, CO, NOX, and SO2 secondary emissions. Also assumed 

that 100% of PM is PM2.5, 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 SO2 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 NOX and CO emission factors from AP-42 chapter on

coal combustion (bituminous/subbituminous coal). The NOX emission factor was based on average of NOX

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 NOX and CO secondary emissions. According to AP-42, 

the percentage of PM that is PM2.5 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-fired 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%

HCl 83.3% 83.3%

Cl2 89.3% 89.3%

Non-Hg HAP metals 94% 94%

PM 94% 94%

SO2 48.7% 48.7%

Parameters

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

Cl2 0.09 0.20

Non-Hg HAP metals 0.1026 0.220

PM 9.33 19.99

SO2 48.26 103.42

Energy impacts, MMBtu/yr 11,544 14,109

Secondary air impacts, tpy

Particulate matter 0.09 0.10

PM2.5 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 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%

Parameters

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

PM2.5 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%

Cl2 42% 42%

Non-Hg HAP metals 20% 20%

PM 20% 20%

SO2 12% 12%

Parameters

Fan hp 60 90

Total hp for other motors 10 40

Waste, lb/hr 83.7 117.2

Emissions reductions, tpy

HF 17.61 37.73

HCl 0.74 1.59

Cl2 0.04 0.10

Non-Hg HAP metals 0.025 0.053

PM 2.27 4.86

SO2 11.88 25.47

Energy impacts, MMBtu/yr 4,489 8,337

Secondary air impacts, tpy

Particulate matter 0.03 0.06

PM2.5 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 0.00163 0.00349 0.00182 0.00390

Energy impacts, MMBtu/yr 371 621 371 621

Secondary air impacts, tpy

Particulate matter 0.0027 0.0046 0.0027 0.0046

PM2.5 0.0009 0.0015 0.0009 0.0015

Carbon monoxide 0.0046 0.0077 0.0046 0.0077

Nitrogen oxides 0.0367 0.0614 0.0367 0.0614

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%

Cl2 42% 89.3% 42% 89.3%

Non-Hg HAP metals 20% 94% 20% 94%

PM 20% 94% 20% 94%

SO2 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

Cl2 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

SO2 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

PM2.5 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/ESP1 DIFF Increm.2 SD/ESP1 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

Cl2 -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

SO2 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

PM2.5 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 negative 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

Existing 

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%

Cl2 88% 89.3% 88% 89.3%

Non-Hg HAP metals 72% 94% 72% 94%

PM 72% 94% 72% 94%

SO2 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

Cl2 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

SO2 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

PM2.5 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 change 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-based 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 number 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 test 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 emissions. 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 requested 

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 

because 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 basing 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 performing 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-Hg HAP metals standards in section IV.Q.1 

of the preamble to the proposed rule (79 FR 75649).