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
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. 
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
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 ......................................................................................... 4-22

4.3.2 Additional SO2 Health Co-benefits ........................................................ 4-33

4.3.3 Visibility Impairment Co-benefits ......................................................... 4-34

4.4 References .......................................................................................................... 4-35

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
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

5.4 References .......................................................................................................... 5-18

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 .................................................................. 6-10

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 (NTTAA) and 1 

CFR Part 51........................................................................................................ 6-11

6.10.1 Executive Order 12898: Federal Actions to Address Environmental 

Justice in Minority Populations and Low-Income Populations ............. 6-13

6.11 Congressional Review Act (CRA) ..................................................................... 6-13
vi 

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 
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 ................................................ 4-24

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 ................................................ 4-26
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
ix 

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

2011$) ........................................................................................................................... 7-1
ES-1 

EXECUTIVE SUMMARY 

ES.1 Background 

The U.S. Environment Protection Agency (EPA) is requiring 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 nonmercury 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. 
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. 
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 
1-2 

than by the BSCP manufacturers, they are not considered by manufacturers in their production 

decisions. As a result, BSCP manufacturers produce more, and emit more pollutants, than they 

would if they bore the costs of the air pollution they generate. Because the market does not 

provide a signal that properly limits the quantity of air pollutants emitted by BSCP 

manufacturers, a market failure exists that requires EPA to promulgate air pollution standards to 

limit their emissions. 

1.3 Organization of the Report 

The remainder of this economic analysis is organized as follows: 

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

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

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

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

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

Executive Orders. 

■ Section 7 presents EPA’s summary of benefits and costs. 
2-1 

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′′. 
2-2 

Figure 2-1. Capacity Utilization for Nonmetallic Mineral Products (NAICS 327) 

Source: Federal Reserve Board, 2013 

construction market. For example, 2011 new privately owned housing starts (608,800) units are 

well below levels observed in 2000 (1.6 million) and 1990 (1.2 million) (U.S. Census Bureau, 

2013c). Since 2010, 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 
2-3 

■ structural clay tile (except facing). 

Bricks are the primary good produced in terms of value and physical quantities and 

include face brick, paving brick, building brick, and thin brick. Face brick accounts for over 90% 

of brick shipments. 

2.2.2 What Factors Influence Market Supply? 

The manufacturing process for brick and structural clay goods includes raw material 

processing (mining, 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. 
2-4 

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. 
2-5 

2.3.1 Who Uses Brick? 

According to the Brick Industry Association, the vast majority of affected brick products 

are sold for residential end uses and nonresidential building uses (Brick Industry 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. 
2-6 

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

All other things equal, consumers will likely buy fewer BSCP when the price of the 

product rises. The price elasticity of demand measures the size of the price response.5 Several 

factors influence how sensitive consumers are to price changes. If consumers can easily switch 

from one product to another because there are many close substitutes, demand tends to be more 

elastic. This is particularly true for more narrow market definitions (king versus modular brick) 

and over longer time horizons for the consumption decision (months versus years). 

Currently, EPA has not identified 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. 
2-7 

nonmetallic mineral products were shipped less than 100 miles (U.S. Department of 

Transportation, 2010).6

 As shown in Table 2-1, approximately 75% of the total tons shipped are 

shipped in NAICS 327 is less than 50 miles. A comparison of Census region average prices for 

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. 
2-8 

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 
2-9 

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). 
2-10 

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) 
2-11 

Table 2-4. Ultimate Parent Companies for Affected Facilities (continued) 

Company ICR NAICS 

Affected 

Facilities

Affected 

Kilns 

Sales 

(Million $) Employment Small

Pacific Clay Products 327121 1 3 27.2 175 Yes 

Pine Hall Brick Co., Inc. 327121 1 6 30.2 35 Yes 

Ragland Clay Products, LLC 327121 1 1 1.9 35 Yes 

Richards Brick Co. 327121 1 2 18.1 75 Yes 

Sioux City Brick and Tile Co. 327121 2 3 7.5 35 Yes 

Statesville Brick Co. 327121 1 2 35.0 175 Yes 

Summit Pressed Brick and Tile 

Co. 327121 1 1 8.5 75 Yes 

Summitville Tiles, Inc. 327122 1 4 300.0 175 Yes 

Superior Clay Corp. 327121 0 0 7.4 75 Yes 

The Stiles & Hart Brick Company 327121 0 0 4.8 44 Yes 

Triangle Brick 327121 2 5 29.8 203 Yes 

Watsontown Brick Co. 327121 1 2 4.1 35 Yes 

Whitacre Greer 327121 1 2 8.7 75 Yes 

Yankee Hill Brick and Tile 327121 1 1 NA 75 Yes 

NA = No annual sales data 

Sources: Data on total number of ultimate parent company employees and annual sales were gathered from 

Hoover’s, Manta, and company Web sites. 

2.5 Market Data and Trends 

This section presents historical market data for select bricks and structural clay products. 

Historical market data include U.S. volumes for 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. 
2-12 

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) 
2-13 

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.
2-14 

Table 2-6. Historical Data for Facing Tile and Ceramic Glazed Brick (Including Unglazed 

and Salt Glazed) and Vitrified Clay Sewer Pipe and Fittings (short tons): 

1993–2010 

Year 

Shipments of Select 

Structural Clay 

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) 
2-15 

Table 2-6. Historical Data for Facing Tile and Ceramic Glazed Brick (Including Unglazed 

and Salt Glazed) and Vitrified Clay Sewer Pipe and Fittings (short tons): 

1993–2010 (continued) 

a This represents shipment quantity of 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) 
2-16 

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%. 
2-17 

Table 2-7. Historical Data for Structural Clay Tile (Except Facing) (short tons): 1993–

2010 

Year Shipments of Structural Clay Tile (Except Facing) 

1993 (D) 

1994 (D) 

1995 53,727 

1996 50,990 

1997 49,729 

1998 49,098 

1999 47,156 

2000 47,009 

2001 49,453 

2002 49,563 

2003 40,330 

2004 40,050 

2005 47,704 

2006 37,491 

2007 35,477 

2008 23,410 

2009 16,749 

2010 12,140 

Average Annual Growth Rates

1995–2010 −8.31% 

Note: 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.
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. 
2-19 

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. 
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. 
2-21 

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

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

2.6 References 

Boral Limited. 2012. Annual Report 2012. 

http://www.boral.com.au/Images/common/pdfs/annual-reports/Boral-Annual-Report2012.pdf. 

Brick Industry Association. 2013a. An Overview of the American Brick Industry. 

http://www.gobrick.com/resources/americanbrickindustry/tabid/7644/default.aspx 

(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. 
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. 
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. 
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. 
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 three regulatory approaches: 

■ Option 1 (Proposed Rule): 

– Acid gases: Meet HBS. 

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

– PM/total non-Hg HAP metals: Choice 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. 

– Hg: Choice of MACT limit, with consideration of raw material variability, in 

lb/ton, concentration, or lb/hr. 

– PM/total non-Hg HAP metals: Choice 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). 
3-2 

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

metals): 

– Acid gases: Meet HBS. 

– Hg: Choice of MACT limit, with consideration of raw material variability, for Hg 

in lb/ton, concentration, or lb/hr. 

– PM/total non-Hg HAP metals: Choice 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 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 

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. 
3-3 

■ 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. 

■ 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. 
3-4 

■ 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 

memorandum “Development of Cost and Emission Reduction Impacts for the Final BSCP 

NESHAP” included in the docket. 
3-5 

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. 

The estimates of annual cost include 

■ operation and maintenance (O&M) labor; 
3-6 

■ 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

. 

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 

 

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). 
3-7 

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. 
3-8 

Table 3-4. Number of Stacks Taking Actions to Achieve Compliance (2011 USD) 

 Action to Achieve Compliance 

Standards Parameter 

Install DLA 

(become SA)

Install 

FF 

Install FF 

+ ACI 

Add ACI to 

Existing 

APCD 

Retrofit 

with 

DIFF Totals 

Option 1 Number of 

Stacks 

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 
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 
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. 
4-3 

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. 
4-4 

We follow a “damage-function” approach in calculating benefits, which estimates 

changes in individual health endpoints (specific effects that can be associated with changes in air 

quality) and assigns values to those changes assuming independence of the values for those 

individual endpoints. Because EPA rarely has the time or resources to perform new research to 

measure 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. 
4-5 

For mortality, we use the effect coefficients from the most recent epidemiology studies 

examining two large population cohorts: the American Cancer Society cohort (Krewski et al., 

2009) and the Harvard Six Cities cohort (Lepeule et al., 2012). The PM ISA (U.S. EPA, 2009) 

concluded that the ACS and Six Cities cohorts provide the strongest evidence of the association 

between long-term 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 
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. 
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] 
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). 
4-9 

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%. 
4-10 

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 2 Directly 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. 

 
4-11 

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. 
4-12 

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
4-13 

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 
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 
4-15 

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). 
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. 

 
4-17 

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 PopulationExposed

Baseline Annual MeanPM2.5 Level(μg/m3)

LML of Lepeule et al.

(2012)study

LML of Krewski et

al. (2009) study
4-18 

from the emission reductions associated with the regulatory requirements. Table 4-6 provides the 

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

Table 4-6. Emission Increases Associated with Secondary Energy Disbenefits (short tons 

per year)a

Option Energy Impacts, MMBtu/yr 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 

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

 

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. 
4-19 

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 

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

 

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. 
4-20 

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 and the 

second addressed a minor indexing error in another model. On average the revised SC-CO2

 

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. 
4-21 

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 

several important benefit categories, including benefits associated with the potential exposure to 

 

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. 
4-22 

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 

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

 

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 

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 populationexposed

Baseline Annual MeanPM2 5 Level(μg/m3)

LML of Krewski et

al. (2009) study

LML of Lepeule et

al. (2012) study
4-23 

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. 

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.

 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. 

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. 
4-24 

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. 

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 
4-25 

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. 

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). 
4-26 

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. 
4-27 

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>. 
4-28 

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. 
4-29 

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. 
4-30 

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. 
4-31 

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. 
4-32 

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 
4-33 

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.
4-34 

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. 
4-35 

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. 
4-36 

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>. 
4-37 

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>. 
4-38 

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>. 
4-39 

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>. 
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. 
5-2 

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%). 
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 Ch

Absolute Percent Absolute Percent 

Consumer 

Surplus 

Pr

S

Option 2: Final Rule New England $0.00 $0.00 0.0% 0 0.0% $0.0 Middle Atlantic $14.37 $5.51 1.7% −2,847 −1.3% −$1.2 East North Central $16.56 $7.45 2.5% −5,629 −2.0% −$2.1 West North Central $4.73 $2.63 0.9% −1,389 −0.8% −$0.5 South Atlantic $8.49 $4.34 1.9% −19,586 −1.5% −$5.6 East South Central $12.34 $6.85 3.7% −11,442 −2.9% −$2.6 West South Central $5.97 $3.32 1.4% −10,315 −1.2% −$2.9 Mountain $1.93 $0.54 0.1% −135 −0.1% −$0.1 Pacific $3.51 $1.66 0.3% −179 −0.2% −$0.1 U.S. Average/Total $8.68 $4.37 1.8% −51,521 −1.5% −$15.1 −
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 Ch

Absolute Percent Absolute Percent 

Consumer 

Surplus 

Pr

S

Option 1 New England $0.00 $0.00 0.0% 0 0.0% $0.0 Middle Atlantic $11.28 $4.33 1.3% −2,236 −1.0% −$0.9 −East North Central $16.56 $7.45 2.5% −5,628 −2.0% −$2.1 −West North Central $4.73 $2.63 0.9% −1,389 −0.8% −$0.5 −South Atlantic $7.09 $3.62 1.6% −16,347 −1.3% −$4.7 −East South Central $12.67 $7.04 3.8% −11,755 −3.0% −$2.7 −West South Central $7.16 $3.98 1.7% −12,382 −1.4% −$3.5 −Mountain $8.16 $2.27 0.6% −572 −0.5% −$0.3 −Pacific $3.51 $1.66 0.3% −179 −0.2% −$0.1 −U.S. Average/Total $8.49 $4.27 1.8% −50,487 −1.4% −$14.8 −
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 Ch

Absolute Percent Absolute Percent 

Consumer 

Surplus 

Pr

S

Option 3 New England $0.00 $0.00 0.0% 0 0.0% $0.0 Middle Atlantic $16.04 $6.15 1.9% −3,179 −1.5% −$1.3 −East North Central $28.31 $12.74 4.2% −9,623 −3.4% −$3.6 −West North Central $19.12 $10.62 3.8% −5,613 −3.1% −$1.9 −South Atlantic $14.15 $7.23 3.1% −32,635 −2.5% −$9.3 −East South Central $19.48 $10.82 5.8% −18,072 −4.6% −$4.1 −West South Central $10.37 $5.76 2.5% −17,926 −2.0% −$5.1 −Mountain $14.39 $4.00 1.1% −1,008 −0.9% −$0.5 −Pacific $37.17 $17.55 3.2% −1,899 −2.5% −$1.3 −U.S. Average/Total $15.62 $7.86 3.2% −89,954 −2.6% −$27.1 −
5-6 

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. 
5-7 

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. 
5-8 

lowers marginal production costs, for example. In such a case, output could theoretically 

increase. 

The substitution effect describes how, holding output constant, regulation affects the 

labor intensity of production. Although increased environmental regulation generally results in 

higher utilization of production factors such as pollution control equipment and energy to operate 

that equipment, the resulting impact on labor demand is ambiguous. For example, 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. 
5-9 

As stated, the responsiveness of industry labor demand depends on how the output and 

substitution effects interact. 60 At the industry level, labor demand will be more responsive when 

(1) the price elasticity of demand for the product is high, (2) other 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. 
5-10 

Instead, labor would primarily be reallocated from one productive use to another (e.g., from 

producing electricity or steel to producing pollution abatement equipment). Theory supports the 

argument that, in the case of full employment, the net national employment effects from 

environmental regulation are 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). 
5-11 

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. 
5-12 

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). 
5-13 

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). 
5-14 

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: 
5-15 

■ 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. 
5-16 

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 = 

்௢௧௔௟	஺௡௡௨௔௟௜௭௘ௗ	஼௢௠௣௟௜௔௡௖௘	஼௢௦௧೔

்௢௧௔௟	ோ௘௩௘௡௨௘೔

 (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%.
5-17 

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 

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% Option 2 Final $65 $27 58% 28% 3% 8% 5% Option 3 $131 $49 35% 15% 13% 15% 23% Small Businesses (n=32) Option 1 $16 $7 53% 31% 9% 3% 3% Option 2 Final Rule 

$14 $7 59% 28% 3% 3% 6% 

Option 3 $50 $19 34% 9% 16% 13% 28% 

a The screening assessment was conducted for 40 of the 44 ultimate parent companies with annual sales data available. For small busin

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: A

companies with CSR > 10%, 50% of ultimate parent companies with CSRs between 5% and 10%, and 25% of ultimate parent compa3% and 5%. 
5-18 

Under the final standards, EPA estimated that two to four brick manufacturing facilities 

are at significant risk of closure. Under the Option 1 standards, one to three brick manufacturing 

facilities are at significant risk of closure, and under the Option 3 standards, nine to thirteen brick 

manufacturing facilities are at significant risk of closure. 

As shown in Table 5-3, 32 of the 36 small ultimate parent companies had sales data 

available that enabled EPA to compute a sales test. Under the final 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. 

5.4 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. 
5-19 

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. 

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. 
5-20 

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. 

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). 
6-1 

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. 

The EPA’s study estimates that affected BSCP facilities will incur total annualized costs 

of $24.6 million (2011 dollars) under the BSCP Manufacturing NESHAP, 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 VI of this 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 HAP 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-percent discount 

rate and $75 million to $170 million (2011 dollars) at a 7-percent discount rate on a yearly 

average in 2018 for the promulgated standards. 
6-2 

Based on the EPA’s examination of costs and benefits of the final BSCP Manufacturing 

NESHAP, the EPA believes that the benefits of the BSCP Manufacturing NESHAP will exceed 

the costs. 

6.3 Paperwork Reduction Act (PRA) 

The information collection activities in the BSCP Manufacturing NESHAP and Clay 

Ceramics Manufacturing NESHAP have been submitted for approval to OMB under the PRA. 

The ICR document that the EPA prepared for the BSCP Manufacturing NESHAP has been 

assigned EPA ICR number 2509.01. You can find a copy of the ICRs in the dockets for the 

BSCP Manufacturing NESHAP 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 APCD 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 and 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 

Manufacturing NESHAP are owners and 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 extruded, dimensional clay products. The BSCP facilities 

typically form, dry and fire bricks and shapes that are composed primarily of clay and shale. 
6-3 

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 to use the routine control device 

maintenance alternative standard no later than 120 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 must submit an initial notification within 30 calendar days of 
6-4 

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 90 BSCP facilities that are currently major sources of HAP, 84 of which have 

at least one tunnel kiln. An estimated 21 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 Manufacturing 

NESHAP. 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 reports, records of compliance data 

and malfunctions) does not occur until the fourth year following promulgation. 

For the BSCP Manufacturing NESHAP, 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 
6-5 

technical amendment to 40 CFR part 9 to display the OMB control number for the approved 

information collection activities contained in this final rule. 

6.4 Regulatory Flexibility Act (RFA) 

Pursuant to sections 603 and 609(b) of the RFA, the EPA prepared an IRFA that 

examines the impact of the proposed rule on small entities along with regulatory alternatives that 

could minimize that impact. The complete IRFA is available for review in the docket and is 

summarized here. We convened a 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. 

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 HAP listed for regulation in section 112(b). 

These standards are applicable to new or existing sources of HAP and shall 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, NESHAP for the BSCP 

source category are 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 HAP 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 percent of existing sources (for which the Administrator has emissions 

information) or the best performing five sources for source categories with less 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 HAP, but must 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). 
6-6 

6.4.3 Significant Issues Raised 

The EPA received comments on the proposed standards and requests for comment that 

were included based on SBAR Panel recommendations. See section V of this 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. The EPA’s 

response to the legal arguments made against work practice standards is presented in “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” found in the docket (Docket ID No. EPA-HQ-OAR-2013-0291). 

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 have been revised since the 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.B.1 of this 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. 
6-7 

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.A of this preamble. The EPA is not changing the HBEL from proposal, as the 

proposed HBEL 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 Manufacturing 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.B.2 of this preamble for additional information). 
6-8 

MACT floor pool: Several commenters supported the EPA’s proposal to calculate MACT 

floor standards for PM based on the top 12 percent of the kilns in the industry (i.e., the bestperforming sources with a 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 percent of sources for which we had test data, 

regardless of APCD type (see section V.B.1 of this preamble for additional details). 

6.4.4 Small Business Administration Comments 

The SBA’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 and 

delay promulgation of a 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: The EPA maintains that a delay in promulgation of an Hg standard is not 

appropriate for two reasons. First, under CAA section 112(e), the EPA was scheduled to 

complete standards for all source categories by 2000. The EPA’s 2003 BSCP Manufacturing 

NESHAP was vacated, and that vacatur re-created the EPA’s obligation to set standards for the 

BSCP 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, the EPA was obligated to sign a 

notice of final rulemaking to set standards for the BSCP source category by September 24, 2015. 

Second, the EPA notes that following proposal, it 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, the 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. 
6-9 

Thus, the EPA’s conclusion is that there is no basis 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 percent 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: The EPA standard engineering cost practice is to annualize over the expected 

life of the control equipment at 7 percent. The EPA does not have the data available to model the 

way a firm pays for an APCD because each firm has a different set of potential options for 

financing including debt financing, equity financing, and financing through retained earnings. 

The EPA acknowledges that some firms may not be able to borrow the money and some may 

close. The EPA’s closure analysis is quite uncertain, but we do not have the detailed firmspecific 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, as 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 (two to four 

BSCP manufacturing facilities overall) 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. 

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 
6-10 

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. 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 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 10 small BSCP manufacturing facilities rather 

than two to three small BSCP manufacturing facilities). 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, at http://www.epa.gov/ttn/atw/brick/brickpg.html. 

6.5 Unfunded Mandates Reform Act 

This action does not contain an unfunded mandate of $100 million or more as described 

in the 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 governments 

or the private sector. 

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. 
6-11 

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 and clay ceramics 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 risks or safety risks addressed by this action present a disproportionate risk 

to children. This action’s health and risk assessments are contained in the memoranda “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 (NTTAA) and 1 CFR 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. 

The EPA has decided to use ANSI/ASME PTC 19.10-1981, “Flue and Exhaust Gas 

Analyses,” for its manual methods of measuring the oxygen or carbon dioxide content of the 

exhaust gas. This standard is acceptable as an alternative to Method 3A and 3B and is available 

from the American Society of Mechanical Engineers (ASME) at http://www.asme.org; by mail at 

Three Park Avenue, New York, NY 10016-5990; or by telephone at (800) 843-2763. 

The EPA has also decided to use ASTM D6735-01 (Reapproved 2009), “Standard Test 

Method for Measurement of Gaseous Chlorides and Fluorides from Mineral Calcining Exhaust 
6-12 

Sources—Impinger Method,” for its measurement of the concentration of gaseous HCl and HF 

and other gaseous chlorides and fluorides. This standard is acceptable as an alternative to 

Methods 26 and 26A. 

In addition, the EPA has decided to use 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),” for its determination of elemental, 

oxidized, particle-bound, and total Hg emissions. This standard is acceptable as an alternative to 

Method 29 (portion for Hg only). 

Finally, the EPA has decided to use ASTM D6348-03 (Reapproved 2010), “Standard 

Test Method for Determination of Gaseous Compounds by Extractive Direct Interface Fourier 

Transform Infrared (FTIR) Spectroscopy,” for its use of an extractive sampling system to direct 

stationary source effluent to an FTIR spectrometer for the identification and quantification of 

gaseous compounds. This standard 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). In order for the test data to be acceptable for a compound, %R must be 

greater than or equal to 70 percent and less than or equal to 130 percent. 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. 

The standards ASTM D6735-01, ASTM D6784-02, and ASTM D6348-03 are available 

from the American Society of Testing and Materials (ASTM) at http://www.astm.org; by mail at 

100 Barr Harbor Drive, Post Office Box C700, West Conshohocken, PA 19428-2959; or by 

telephone at (610) 832-9585. 

While the EPA identified ASTM D7520–13, “Standard Test Method for Determining the 

Opacity in a Plume in an Outdoor Ambient Atmosphere” as being potentially applicable as an 

alternative to Method 9 for measuring opacity from BSCP tunnel kilns, the agency decided not to 

use it. The use of this voluntary consensus standard would be impractical. The five provisions for 

the use of this standard appear to be based on the assumption that the optical camera will be used 
6-13 

on a daily basis. However, this rulemaking does not include daily Method 9 tests. The rule 

requirements are such that a Method 9 observation would need to be made unexpectedly and 

only when the Method 22 test failed. It would be unreasonable to expect that a source would be 

making daily calibrations of the camera when its use would be so infrequent. Given that, it is 

unlikely that the camera could be made ready in the time specified for the Method 9 readings. 

Therefore, this standard is not usable based on the current requirements in this rulemaking. 

6.11 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). 

6.12 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 a “major rule” 

as defined by 5 U.S.C. 804(2). 
7-1 

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. 
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. 
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: 

ܳ஽௥

ᇱ ൌ ܳ஽௥ ൈ ቂ1 ൅ ቀ௉ᇲ

௣ െ 1ቁ ൈ ߟቃ (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. 
A-3 

ܳௌ஺௥

ᇱ ൌ ܳௌ஺௥ ൈ ቂ1 ൅ ቀ൫௉ᇲି௨௡௜௧	௖௢௦௧	௜௡௖௥௘௔௦௘൯

௣ െ 1ቁ ൈ ߝቃ (A.2) 

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

ܳௌ௎௥

ᇱ ൌ ܳௌ௎௥ ൈ ቂ1 ൅ ቀ௉ᇲ

௣ െ 1ቁ ൈ ߝቃ (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): 

ܳ஽௥

ᇱ ൌ ܳௌ஺௥

ᇱ ൅ ܳௌ௎௥ᇱ (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. 
A-4 

A.3.2 Supply 

All other things equal, brick manufacturers will likely offer to sell more bricks when the 

price of bricks rises. The price elasticity of supply measures how much the quantity of bricks 

supplied responds to changes in the brick price.74 If manufacturers have a significant amount of 

flexibility to change the amount of bricks they produce when the price rises, the supply of bricks 

is elastic. In contrast, if the quantity of brick 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. 
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) 
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.