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EO12866_Mercury Emissions from Mercury Cell Chlor‐Alkali Plants 2060‐AN99 NPRM Redline

RIA_20101210

JulyNovember 2010

Regulatory Impact Analysis:

Proposed National Emission

Standards for Hazardous Air

Pollutants (NESHAP) for Mercury

Emissions from Mercury Cell Chlor 

Alkali Plants

Draft Report

U.S. Environmental Protection Agency

Office of Air Quality Planning and Standards (OAQPS)

Air Benefit and Cost Group

(MD-C439-02)

Research Triangle Park, NC 27711
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CONTENTS

Section Page

Section 1 Introduction......................................................1-1 and Executive Summary 1-1

1.1 Executive Summary........................................................................................1-11-1

1.2 Organization of this Report.............................................................................1-41-5

Section 2 Industry Profile ...................................................................................... 2-11

2.1 Supply Side .......................................................................................................... 2-1

2.1.1 Chlorine Production Process.................................................................... 2-1

2.1.2 Product Types.......................................................................................... 2-3

2.1.3 Materials and Costs of Production........................................................... 2-4

2.1.4 Chlor-alkali Transportation...................................................................... 2-5

2.2 The Demand Side................................................................................................. 2-7

2.2.1 Who Uses Chlorine, Caustic Soda, and Caustic Potash?......................... 2-7

2.2.2 What Factors Influence Demand?.......................................................... 2-12

2.3 Market Characteristics....................................................................................... 2-12

2.3.1 Geography.............................................................................................. 2-13

2.3.2 Product Differentiation .......................................................................... 2-13

2.3.3 Entry....................................................................................................... 2-13

2.3.4 Concentration......................................................................................... 2-13

2.4 Overview of Businesses Affected by the Rule .................................................. 2-14

2.4.1 Mercury Cell Plants............................................................................... 2-14

2.4.2 Ultimate Parent Companies ................................................................... 2-16

Section 3 Engineering Cost Analysis..................................................................... 3-11

3.1 Capital Costs...................................................................................................... 3-22

3.2 Annual Costs...................................................................................................... 3-67

3.2.1 Capital Recovery Costs.....................................................................3-6Cost 7

3.2.2 Annual Costs Associated with Storage of Unused Mercury................ 3-810
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3.2.3 Costs Savings Associated with the Elimination of Mercury-Related 

Environmental Compliance Costs...................................................... 3-1014

3.2.34 Energy Savings and Costs.................................................................. 3-1318

3.2.35 Overall Annual Costs......................................................................... 3-1621

3.3 Uncertainty Analysis...................................................................................... 3-1722

3.4 Summary of Results....................................................................................... 3-1925

Section 4 Economic Impact Analysis............................................................4-1 (EIA) 4-1

4.1 Conversion Versus Plant Closure .....................................................................4-4-1

4.2 Market Concentration and Pricing Behavior ....................................................4-4-4

4.3 Adjustment and Transition Costs in Local Labor Markets............................... 4-4.3 Impact 

4.3.1 Annual Payroll Statistics 2007 Economic Census............................................ 4-4.4 Transpo 

4.3.1 Direct and Indirect Job Effects ......................................................................... 4-4.5 Small E 

4.4 Transportation Issues Associated with Plant Closure........................ 4-4.5.1 Identify 

4.5 Small EntityImpact.2 ..........................................................Sales Test Analysis 4-4-11

4.5.1 Identify Affected Small Entities........................................................ 4-4.5.3 Profit T 

4.5.2 Sales Test Analysis........................................................................................... 4-4.6 Conclus

4.5.3 Profit Test Analysis........................................................................................... 4-4.7 Referen

4.6 Conclusions 4-Section 5 ........................Human Health Benefits of Emissions Reductions 5-1

4.7 References......................................................................................................... 4-5.1 Synopsi

5.2 Mercury Benefits ................................................................................................. 5-1

5.3 Energy Savings Co-benefits................................................................................. 5-4

5.3.1 PM2.5 Co-benefits..................................................................................... 5-4

5.3.2 Social Cost of Carbon and Greenhouse Gas Co-benefits ...................... 5-16

5.3.3 Total Monetized Co-benefits of Energy Savings................................... 5-19

5.4 Characterization of Uncertainty in the Monetized PM2.5 Co-Benefits............... 5-20

5.6 References.......................................................................................................... 5-27
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Section 6.....................................................................................................................................1

Comparison of Co-Benefits and Costs.......................................................................................1

5 Benefits of Emissions Reductions ................................................................................ 5-1

5.1 Synopsis............................................................................................................... 5-1

5.2 Mercury Benefits ................................................................................................. 5-1

5.3 Energy Co- Benefits............................................................................................. 5-4

5.3.1 PM2.5 Co-Benefits .................................................................................... 5-4

5.3.2 Social Cost of Carbon and Greenhouse Gas Co-benefits...................... 5-13

5.2.3 Total Monetized Co-Benefits of Energy Savings.................................. 5-12

5.4 Characterization of Uncertainty in the Monetized PM2.5 Co-Benefits............... 5-17

5.5 Comparison of Co-Benefits and Costs............................................................... 5-21

5.6 References.......................................................................................................... 5-24

Appendix A: Mercury Emissions Memo .............................................................................. A-1

Appendix B: Reduced Electricity Consumption for Mercury Cell Chlor-alkali Plants.........B-1

Appendixes

A: Mercury Emissions Memo.......................................................................................1

B: Emissions Reductions Associated with Reduced Mercury Cell Chlor-alkali 

Plant Electricity Consumption .............................................................................B-1
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LIST OF FIGURES

Number Page

2-1. Industry-wide Uses of Chlorine by Industry.....................................................................8

2-2. Use of Caustic Soda by Industry.......................................................................................9

2-3. Use of Caustic Potash by Industry..................................................................................10

2-4. Income (or Loss) as Net a Percentage of Sales, Basic Chemicals, Resins, and 

Synthetics (NAICS 3251 and 3252): 2000–2005 ...........................................................17

3-1. Capital Cost Factor ($/ton Cl2 produced) vs. Capacity................................................. 3-5

4-1. Price Trends: Alkalis and Chlorine Manufacturing: 2000 to 2009............................4-4-3

4-2. Unemployment Rates by County: 2000–2008...........................................................4-4-8

4-3. Unemployment Rate Differences from National Average: May 2009 and 

Historical Average: 2000–2008 ...............................................................................4-4-10

4-4. Historical ECU Cash Margins .................................................................................4-4-14

4-5. Profit Tests: ECU Cash Margin Reductions Associated with Conversion Costs...4-4-16

2-1. Industry-wide Uses of Chlorine by Industry.....................................................................8

2-2. Use of Caustic Soda by Industry.......................................................................................9

2-3. Use of Caustic Potash by Industry..................................................................................10

2-4. Income (or Loss) as Net a Percentage of Sales, Basic Chemicals, Resins, and 

Synthetics (NAICS 3251 and 3252): 2000–2005 ...........................................................17

3-1. Capital Cost Factor ($/ton Cl2 produced) vs. Capacity....................................................5

4-1. Price Trends: Alkalis and Chlorine Manufacturing: 2000 to 2009............................... 4-3

4-2. Unemployment Rates by County: 2000–2008.............................................................. 4-8

4-3. Unemployment Rate Differences from National Average: May 2009 and 

Historical Average: 2000–2008.................................................................................. 4-10

4-4. Historical ECU Cash Margins.................................................................................... 4-14

4-5. Profit Tests: ECU Cash Margin Reductions Associated with Conversion Costs....... 4-16

5-1. Breakdown of Monetized PM2.5 Health Co-Benefits using Mortality Function 

from Pope et al. (2002)a.............................................................................................. 5-11

5-2. Total Monetized PM2.5 Co-Benefits for the Proposed Mercury Chlor Alkali 

NESHAP in 2013 (Option 1)...................................................................................... 5-15

5-3. Breakdown of Monetized Co-benefits by Pollutant at 3% discount rate (Option 1).. 5-21

5-4. Percentage of Adult Population by Annual Mean PM2.5 Exposure (pre- and postpolicy policy).............................................................................................................. 5-24

5-5. Cumulative Distribution of Adult Population at Annual Mean PM2.5 levels (preand post-policy policy) ............................................................................................... 5-24
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6-1. Net Benefits for the Proposed Mercury Chlor Alkali NESHAP at 3% Discount 

Rate (Option 1)a................................................................................................................3

6-2. Net Benefits for the Proposed Mercury Chlor Alkali NESHAP at 7% Discount 

Rate (Option 1)a................................................................................................................4

5-1 Breakdown of Monetized PM2.5 Health Co- Benefits using Mortality Function 

from Pope et al. (2002) ............................................................................................... 5-10

5-2. Total Monetized PM2.5 Co-Benefits for the Proposed Mercury Chlor Alkali 

NESHAP in 2013........................................................................................................ 5-13

5-3. Breakdown of Monetized Co-Benefits by Pollutant at 3% discount rate ................... 5-17

5-4. Percentage of Adult Population by Annual Mean PM2.5 Exposure (pre- and postpolicy) ......................................................................................................................... 5-19

5-5. Cumulative Distribution of Adult Population at Annual Mean PM2.5 levels (preand post-policy) .......................................................................................................... 5-20

5-6. Net Benefits for the Proposed Mercury Chlor Alkali NESHAP at 3% Discount 

Rate ............................................................................................................................. 5-23

5-7. Net Benefits for the Proposed Mercury Chlor Alkali NESHAP at 7% Discount 

Rate ............................................................................................................................. 5-24
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LIST OF TABLES

Number Page

1-1. Summary of the Monetized Benefits, Social Costs, and Net Benefits for the 

Proposed Mercury Chlor Alkali NESHAP in 2013 (millions of 2007$)...................... 1-1

2-1. Comparison of the Processes........................................................................................ 2-2

2-2. Approximate Energy Requirements of Different Cell Types....................................... 2-5

2-3. Olin Corporation Products and Services and Major End Uses: 2008......................... 2-11

2-4. 2002 Economic Census Sales and Employment by Establishment Size .................... 2-15

2-5. Estimated Plant-Level Sales and Employment: 2008................................................. 2-15

2-6. Ultimate Parent Company Sales and Employment: 2008........................................... 2-16

3-1. Cost Factors for Conversion of Mercury Cell Chlor-Alkali Facilities to 

Membrane Cell Technology ($/ton Cl2 produced ........................................................ 3-4

3-2. Estimated Capital Costs for Existing Mercury Cell Chlor-Alkali Facilities................. 3-6

3-3. Estimated Capital Recovery Costs for Varying Finance Periods (Using 7 percent 

interest rate) .................................................................................................................. 3-9

3-4. Estimate of Annual Mercury Storage Costs................................................................ 3-10

3-5. Environmental Compliance Cost Savings Factors from Elimination of the 

Mercury Process........................................................................................................ 3-12

3-6. Annual Cost Savings from Elimination of the Mercury Processes, by Facility ........ 3-14

3-7. Energy Savings Associated with Conversion from the Mercury Cell to the 

Membrane Cell Process .............................................................................................. 3-15

3-8. Ranges of Individual Annual Cost/Savings Elements for the Conversion of 

Mercury Cells to Membrane Cells ............................................................................. 3-16

3-9. EPA Estimates of the Annual Costs of Conversion of Mercury Cells to 

Membrane Cells............................................................................................................ 3-1

3-10. Results of the Monte Carlo Simulation Compared to the EPA Estimates ................. 3-18

4-1. May 2009 County Employment Data (Not Seasonally Adjusted).............................4-4-6

4-2. Average Weekly Wages by County and Industry: 2008................................................. 4-

4-3. Estimated Job Losses Resulting from Plant Closures..................................................... 4-

4-4. Estimated Earnings Losses Resulting from Plant Closures............................................ 4-

1-1. Summary of the Monetized Co-Benefits, Social Costs, and Net benefits for the 

Proposed Mercury Chlor Alkali NESHAP in 2013 (millions of 2007$)a..................... 1-4

2-1. Comparison of the Processes............................................................................................2

2-2. Approximate Energy Requirements of Different Cell Types...........................................5

2-3. Olin Corporation Products and Services and Major End Uses: 2008.............................11

2-4. 2002 Economic Census Sales and Employment by Establishment Size ........................15

2-5. Estimated Plant-Level Sales and Employment: 2008.....................................................15
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2-6. Ultimate Parent Company Sales and Employment: 2008...............................................16

3-1. Cost Factors for Conversion of Mercury Cell Chlor-Alkali Facilities to 

Membrane Cell Technology ($/ton Cl2 produced)...........................................................4

3-2. Estimated Capital Costs for Existing Mercury Cell Chlor-Alkali Facilities ....................6

3-3. Estimated Capital Recovery Costs for Varying Finance Periods (Using 7 percent 

interest rate) ......................................................................................................................9

3-4. Estimate of Annual Mercury Storage Costs ...................................................................12

3-5. Environmental Compliance Cost Savings Factors from Elimination of the 

Mercury Process .............................................................................................................16

3-6. Annual Cost Savings from Elimination of the Mercury Processes, by Facility .............17

3-7. Energy Savings Associated with Conversion from the Mercury Cell to the 

Membrane Cell Process..................................................................................................19

3-8. Ranges of Individual Annual Cost/Savings Elements for the Conversion of 

Mercury Cells to Membrane Cells..................................................................................22

3-9. EPA Estimates of the Annual Costs of Conversion of Mercury Cells to 

Membrane Cells..............................................................................................................24

3-10.Results of the Monte Carlo Simulation Compared to the EPA Estimates......................25

4-1. May 2009 County Employment Data (Not Seasonally Adjusted)................................ 4-6

5-1. Human Health and Welfare Effects of PM2.5................................................................ 5-6

5-2. Summary of Monetized PM2.5 Energy Co-benefits for the Proposed Mercury 

Chlor Alkali NESHAP in 2013 (2007$) (Option 1) ................................................... 5-12

5-3. Summary of Reductions in Health Incidences from PM2.5 Co-Benefits for the 

Proposed Mercury Chlor Alkali NESHAP in 2013 (Option 1)a................................. 5-13

5-4. All Monetized PM2.5 Co-Benefits Estimates for the Proposed Mercury Chlor 

Alkali NESHAP at discount rates of 3% and 7% in 2013 (in millions of 2007$) 

(Option 1)a ................................................................................................................ 5-14

5-5. Social Cost of Carbon (SCC) Estimates (per tonne of CO2) for 2013 a ..................... 5-17

5-6. Monetized Co-benefits of CO2 Emission Decreases in 2013 (Option 1)a .................. 5-18

6-1. Summary of the Monetized Co-Benefits, Social Costs, and Net benefits for the 

Proposed Mercury Chlor Alkali NESHAP in 2013 (thousands of 2007$)a......................2

B-1. Estimated Changes in Electricity Generation ...............................................................B-2

B-2. Share of Electricity Generation by Fuel 2009 ..............................................................B-4

B-3. Power Company Emission Factors: Fuel=Coal (Short tons per kWh).........................B-5

B-4. Power Company Emission Factors: Fuel=Natural Gas (Short tons per kWh) .............B-6

B-5. Emission Factor Calculations: 2010 .............................................................................B-6

B-6. Emission Reductions by Plant (22 percent reduction)..................................................B-8

B-7. Emission Estimates by Plant (37 percent reduction) ....................................................B-9

5-1. Human Health and Welfare Effects of PM2.5................................................................ 5-5

5-2. Summary of Monetized Co-Benefits Estimates for the Proposed Mercury Chlor 

Alkali NESHAP in 2013 (millions of 2007$)............................................................. 5-11

5-3. Summary of Reductions in Health Incidences from PM2.5 Co-Benefits for the 

Proposed Mercury Chlor Alkali NESHAP in 2013 .................................................... 5-11
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5-4. All Monetized PM2.5 Co-Benefits from PM2.5 Benefits for the Proposed Mercury 

Chlor Alkali NESHAP in 2013................................................................................... 5-12

5-5. Social Cost of Carbon (SCC) Estimates (per tonne of CO2) for 2013........................ 5-16

5-6. Monetized Co-benefits of CO2 Emission Decreases in 2013 ..................................... 5-16

5-7. Summary of the Monetized Benefits, Social Costs, and Net Benefits for the 

Proposed Mercury Chlor Alkali NESHAP in 2013 (millions of 2007$).................... 5-22
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SECTION 1:
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SECTION 1

INTRODUCTION AND EXECUTIVE SUMMARY 

The U.S. Environmental Protection Agency (EPA) is proposing amendments to the 

national emission standards for hazardous air pollutants (NESHAP) for mercury emissions from 

mercury cell chlor-alkali plants. On June 11, 2008, EPA proposed NESHAP amendments in

response to a petition for reconsideration filed by the Natural Resources Defense Council 

(NRDC); this action supplements the June 11, 2008, proposal. The proposed rule would amend 

the NESHAP to prohibit emissions of mercury from the mercury cell process within 2 years from 

promulgation of the final rule and cease operation of mercury recovery units 3 years from 

promulgation of the final rule. 

In 2003, when the maximum achievable control technology (MACT) was promulgated, 

there were 12 mercury cell plants. EPA believes that by 2010 there will only be four plants still 

using the mercury cell process. The four plants using the mercury cell process are currently 

owned by three ultimate parent companies:

 ASHTA Chemicals, Inc.: one plant (Ohio)

 Olin Corporation: two plants (Georgia and Tennessee)

 PPG Industries, Inc.: one plant (West Virginia)

ASHTA Chemicals is a small company with approximately 100 employees. Olin 

Corporation operates 10 North American chlor-alkali plants; its other line of business is 

Winchester Ammunition. Currently, Olin employs over 3,600 people within both business 

segments. PPG’s commodity chemicals segment operates two chlor-alkali plants but operates 

over 100 coatings and glass manufacturing facilities and employees over 40,000 people 

company-wide.

As part of the regulatory process of preparing these amendments, EPA is required to 

develop a regulatory impact analysis (RIA). This report documents the RIA methods and results. 

0.11.1 Executive Summary

The key results of the RIA are as follows:

 Engineering Cost Analysis: The For Option 1 (Non-mercury Technology 

Option), the engineering cost analysis estimates the total annual capital costs of 

conversion costs to be $13 million; individual plant-level just under $300 million, 

which results in annual costs of $28 million per year annualized over 20 years. 
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Individual plant-level annualized capital conversion cost estimates range from $800 

thousand to $6.73–15 million per year. All estimates are in 2007$. The annual cost to 

store mercury is approximately $250,000 per year. The individual plant-level annual 

energy savings due to conversion may range from $1 million to $14 million per year 

depending on the energy consumption reduction level assumed. The total annual cost 

of conversion for all four facilities, considering the associated savings, is around $13 

million per year. For Option 2 (Enhanced Work Practice Standards Option) the 

capital cost is $120 thousand and the annual costs are $25 thousand. Because of the 

small magnitude of Option 2 compared to Option 1, the market analysis only 

addresses Option 1.

 Plant Closure: EPA does not have sufficient data to predict whether individual 

companies would choose to convert or close directly affected plants. In some 

cases, if a plant were to close, the closure may affect other closely related 

manufacturing operations. For example, ASHTA uses potassium hydroxide made 

from the mercury cell process to make potassium carbonate. If the AshtaASHTA

plant were to choose not to convert and close the mercury cell process, it is 

unclear whether existing technology and economics would allow the company to 

consider an alternative source of potassium hydroxide to continue making 

potassium carbonate. The economics of making potassium carbonate could 

influence Ashta’sASHTA’s decision on how to respond to this rulemaking.

 Local Job Effects: Because EPA is unable to estimate plant closures, job 

loseslosses associated with any closures are not estimated nor are any changes in 

employment associated with conversion.

 Market Analysis: Of the three major chlor-alkali products, the market for 

potassium hydroxide is the most highly concentrated. As of 2005, there were only 

four producers of potassium hydroxide (KOH) in the United States and 

approximately 50% is produced using mercury cells. As a result, closure of one or 

more mercury cell plants could raise concerns about competitiveness and 

subsequent pricing behavior in the potassium hydroxide market. In highly 

concentrated markets, non-mercury cell producers could have more scope to 

influence market prices above competitive levels by altering production decisions. 

EPA’s review of publicly available sources also suggests that closures would have 

similar market concentration consequences for a downstream commodity: 

potassium carbonate. Competitive issues have also been raised in other regulatory 

contexts; the Federal Trade Commission set conditions on a proposed asset 

purchase that reduced the number of competitors in the potassium hydroxide and 

potassium carbonate markets. 

 Small Business Analysis: EPA performed an impact analysis that compares 

annual conversion costs to sales. For Option 1 (Non-mercury Technology 

Option), EPA estimates that the one small entity’s cost-to-sales ratio (CSR) 

would range from 1 to 2%, which suggests a significant economic impact. The 

other three plants are owned by large ultimate parent companies with significant 

company-wide sales. As a result, the CSRs for the large ultimate parent 
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companies are below 1%. In contrast, when plant-only sales are considered, the 

CSRs for plants owned by large ultimate parent companies range from 4 to 10%. 

EPA also considered industry profitability effects by comparing annual 

conversion costs to reported industry margins for a representative electrochemical 

unit (ECU). The analysis confirms the results of the sales tests; plant conversion 

costs will likely have an economically significant effect. In a typical year, 

conversion costs could reduce the margins by 10 to 20%. However, as explained 

in section 3, we do not consider this to be a significant impact on a substantial 

number of small businesses. For Option 2 (Enhanced Work Practice Standards 

Option) CSR for the only plant estimated to incur costs is less than 0.1 % and is 

not a significant economic impact.

 Benefits Analysis: In the year of full implementation (2013), EPA estimates the 

monetized energy co- benefits of the proposed NESHAPOption 1 are $8722

million to $20043 million and $7321 million to $18040 million, at 3% and 7% 

discount rates, respectively. All estimates are in 2007$ for the year 2013. Using 

alternate relationships between PM2.5 and premature mortality supplied by 

experts, higher and lower benefits estimates are plausible, but most of the expertbased estimates fall between these estimates. There are no emission reductions for 

Option 2. 

 Net Benefits: The net benefits for the NESHAPOption 1 are $749 million to 

$19030 million and $608 million to $17027 million, at 3% and 7% discount rates, 

respectively (Table 1- 1).-1). The net benefits for Option 2 are $-25,000. All 

estimates are in 2007$ for the year 2013.
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Table 1-1. Summary of the Monetized Co-Benefits, Social Costs, and Net benefits for the 

Proposed Mercury Chlor Alkali NESHAP in 2013 (millionsthousands of 

2007$)1a

3% Discount Rate 7% Discount Rate

Option 1: Non-mercury Technology Option

Total Monetized Benefits2Benefitsb $8722,00

0

to $20043,000 $7321,00

0

to $18040,000

Total Social Costs3Costsc $13 ,000 $13 ,000

Net Benefits $749,000 to $19030,000 $608,000 to $17027,000

Non-monetized Benefits 656 pounds of mercury (including energy co-benefits)

Health effects from NO2 and SO2 exposure

Ecosystem effects 

Visibility impairment 

1

All

Option 2: Enhanced Work Practice Standards

Total Monetized Benefitsb $0 $0

Total Social Costsc $25 $25

Net Benefits $-25 $-25

a All estimates are for the implementation year (2013), and are rounded to two significant figures. 2b The total monetized co-benefits reflect the human health co-benefits associated with reducing exposure to PM2.5

through reductions of PM2.5 precursors such as NOx and VOC.. It is important to note that the monetized cobenefits include many but not all health effects associated with PM2.5 exposure. It is important to note that the 

monetized benefits include many but not all health effects associated with PM2.5 exposure. Benefits are shown as a 

range from Pope et al. (2002) to Laden et al. (2006). These models assume that all fine particles, regardless of 

their chemical composition, are equally potent in causing premature mortality because there is no clear scientific 

evidence that would support the development of differential effects estimates by particle type. CO2-related 

benefits were calculated using the social cost of carbon (SCC), which is discussed in Section 5. The net present 

value of reduced CO2 emissions is calculated differently than other benefits. The same discount rate used to 

discount the value of damages from future emissions (SCC at 5, 3, 2.5 percent) is used to calculate net present 

value of SCC for internal consistency. This table shows monetized CO2 co-benefits at discount rates of 3 and 7 

percent that were calculated using the global average SCC estimate at a 3% discount rate because the interagency 

workgroup on this topic deemed this marginal value to be the central value. In Section 5, we also provide the 

monetized CO2 co-benefits using discount rates of 5 percent (average), 2.5 percent (average), and 3 percent (95th 

percentile). 3 The annual compliances costs serve as a proxy for the annual social costs of this rule given the lack of difference 

between the two.

c The annual compliances costs serve as a proxy for the annual social costs of this rule. The compliance cost of a 

regulation is generally a slight overestimate of social cost for competitive markets. The size of the overestimate is 

roughly one half the price change times the quantity change. The markets for chlorine and sodium hydroxide are 

expected to be competitive with the market share provided by the affected facilities quite small. However, the 

market share for potassium hydroxide is large and the market may not be competitive. In this case, social cost 

might be larger than compliance cost. Because insufficient data was available to estimate price and quantity 

changes the compliance cost was used as a rough estimate of the social cost.
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0.21.2 Organization of this Report

The remainder of this report supports and details the methodology and the results of the 

RIA:

 Section 2 presents a profile of the affected industry and focuses on plants affected 

by the proposed rule. Although extensive individual plant information would help 

assess the economic impacts of the rule, in most cases, detailed information is not 

publicly available. As a result, we frequently rely on parent company information 

provided in company annual reports (e.g., form 10-K), local press and industry 

trade publications, and company Web sites. 

 Section 3 describes the engineering cost analysis.

 Section 4 describes the economic impact analysis and small business impact 

analysis.

 Section 5 presents the benefits estimates.
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SECTION 2: 

SECTION 2

INDUSTRY PROFILE 

There are four mercury cell chlor-alkali plants currently operating in the United 

States in 2010 that have the combined capacities to produce approximately 500,000 tons of 

chlorine per year. These plants are Olin Corporation in Augusta, Georgia (Olin GA); Olin 

Corporation in Charleston, Tennessee (Olin TN); PPG Industries in New Martinsville, West 

Virginia (PPG); and ASHTA Chemicals in Ashtabula, Ohio (ASHTA). 

EPA has developed an industry profile to provide the reader a general understanding of 

the technical and economic aspects of the industry. We outline processes and costs of getting 

chlorine products to market; identify key uses, consumers, and market characteristics; and 

provide economic data for the plants and owning companies affected by the proposed rule. 

Although we prefer to have extensive individual plant information, in most cases this 

information is not publicly available. As a result, we frequently rely on parent company 

information provided in company annual reports (e.g., form 10-K), local press and industry trade 

publications, and company websites.

2.1 Supply Side

2.1.1 Chlorine Production Process

Although chlorine can be generated as a by-product in a variety of chemical reactions, 

brine electrolysis accounts for 95% of total world chlorine production (World Chlorine Council, 

2002).). Through a chemical reaction catalyzed by an electric current in a series of electrolytic 

cells, a salt-based solution containing either sodium or potassium chloride yields elemental 

chlorine gas, a caustic solution, and hydrogen gas in fixed proportions (“Special Focus on 

Chlorine,” 2007).). The electrolysis occurs when electric current flows between the negatively 

charged cathodes and the anodes, which are the positive electrodes from which the chlorine is 

collected (World Chlorine Council, 2002).).

Three types of electrolytic cells can host this reaction: the diaphragm cell, the membrane 

cell, or the mercury cell. Although the three cell types share the basic chemical production 

formula, they are differentiated by the way in which the chlorine is kept separate from the coproducts generated in the cathode in the chemical process (“Special Focus on Chlorine,” 2007).).

The predominant manufacturing process in North America involves diaphragm cell technology, 

which is characterized by the asbestos-based diaphragm structure that keeps the cathodes 
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separate from the anodes. The membrane cell is structurally similar, though it uses an ionexchange membrane to separate the anodes and chlorine gas from the caustic product. Mercury 

cell technology uses two distinct cells and functions through a sodium-mercury stream that forms 

an amalgam and serves as the cathode (“Special Focus on Chlorine,” 2007).).

Of the three electrolytic processes, the diaphragm and membrane processes are the most 

similar (Table 2--1). Both share the advantage of lower electricity consumption, but the unique 

ion-exchange structure enables membrane cells to produce a purer caustic product than the 

asbestos-based diaphragm. Another disadvantage of the diaphragm cell is the caustic limitations; 

although mercury and membrane cells can use sodium or potassium chloride for brine solution, 

diaphragm cells require sodium chloride. Mercury cells produce a high-quality caustic solution 

and chlorine gas, but emit harmful mercury pollutants into the environment. New plant 

construction has favored membrane cell construction because of low capital investment and 

operating costs relative to diaphragm and mercury processes (“Special Focus on Chlorine,” 

2007).

Table 2-1. Comparison of the Processes

Cell Type

Diaphragm Mercury Membrane

Separation Technique Asbestos-based diaphragm Sodium-mercury amalgam Ion-exchange membrane

Caustic Capabilities Sodium hydroxide Sodium hydroxide, 

potassium hydroxide

Sodium hydroxide, 

potassium hydroxide

Advantages • Use of well brine (no 

solid salt needed)

• Low electricity 

requirements

• Simplest brine system

• High purity caustic, 

chlorine, hydrogen

• Simple purification of 

brine

• Low energy 

consumption

• Low capital investment

• Easily operable cells

• High purity caustic

• Immune from variations 

in cell load and 

shutdown

Disadvantages • Asbestos use

• High steam requirements 

for caustic concentration

• Mercury emissions and 

related environmental 

and regulatory costs

• Solid salt requirement

• Expensive cell 

operations

• Large physical floor 

space requirement

• Solid salt requirement

• High purity brine 

requirements

• Expensive membrane

• High oxygen 

contamination in 

chlorine product

Source: “Special Focus on Chlorine.” October 2007. Chemical Business. pp. 27-40. Accessed July 29, 2009, from 

Business Source Corporate database..
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ion-exchange structure enables membrane cells to produce a purer caustic product than the 

asbestos-based diaphragm. Another disadvantage of the diaphragm cell is the caustic limitations; 

although mercury and membrane cells can use sodium or potassium chloride for brine solution, 

diaphragm cells require sodium chloride. Mercury cells produce a high-quality caustic solution 

and chlorine gas, but emit harmful mercury pollutants into the environment. New plant 

construction has favored membrane cell construction because of low capital investment and 

operating costs relative to diaphragm and mercury processes (“Special Focus on Chlorine,” 

2007).

2.1.2 Product Types

2.1.2.1 Chlorine

Chlorine takes form in a greenish-yellow poisonous gas at STP. It has a pungent odor and 

is 2.48 times denser than air. When liquefied, it becomes a yellow mobile fluid with low 

electrical conductivity. As a solid, chlorine retains the yellow color in the form of rhombic 

crystals. Chlorine is soluble in cold water and in salt solutions, although the solubility decreases 

with salt strength and temperature. Chlorine is stored and transported as a liquefied gas (“Special 

Focus on Chlorine,” 2007).).

2.1.2.2 Caustic Products: Sodium Hydroxide and Potassium Hydroxide

Sodium hydroxide, commonly referred to as caustic soda, is produced as a co-product 

with chlorine and usually sold in the form of a 50% solution. All three cell types can use sodium 

chloride brine in the electrolysis process to derive sodium hydroxide, but the variations between 

the cell structures require different degrees of evaporation and purification to reach the 50% 

concentration. Only mercury cells generate the 50% liquid caustic solution directly; diaphragm 

cells yield a solution of 12% that is processed through filters and evaporators to reach the 

acceptable grade, while membrane cells produce a 30% liquid that is evaporated to the 50% level 

(Occidental Chemical Corporation, 2008b).).

While most chlor-alkali production involves sodium chloride brine, potassium hydroxide 

or caustic potash is the caustic solution produced when potassium chloride is used as a feedstock 

in the brine electrolysis process (Sim, 2005).). Membrane and mercury cell electrolysis can 

produce a caustic potash solution that is evaporated to 45% or 50% concentration for sale. The 

solution can also be concentrated to dry form and sold as flakes or crystals (Occidental Chemical 

Corporation, 2008a).).
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2.1.3 Materials and Costs of Production

Energy, salt brine, and raw materials represent the majority of the production costs in the 

chlor-alkali industry. The recent U.S. Census Bureau’s 2007 Economic Census provides 

industry-level expenditures on production inputs for North American Industry Classification 

System (NAICS) code 325181 (Alkalis and Chlorine Manufacturers). The cost of materials 

(including electricity and purchased fuels) was 62.7% of the total production costs and nearly 

half of the industry’s total value of shipments. Electricity and fuels made up over 31% of total 

production costs. Labor expenses account for around 12.5% of the total reported costs in the 

industry. 

Although the census data provide insight into the chlor-alkali industry cost structure on 

the aggregate level, there is variation between companies in the industry because of size, 

structure, and technology. Olin Corporation, (2008)) operates a number of chlor-alkali facilities 

across the country and cites electricity and salt as the largest share of raw material expenditures, 

which represent 55% of total production costs for the company. Other principle materials include 

potassium chloride, sulfur dioxide, and hydrogen (Olin Corporation, 2008).).

Although energy costs are important for all producers, each cell type requires a different 

combination of energy inputs. For example, membrane cell technology uses 25% less electricity 

than mercury cells but requires steam to concentrate the caustic product that mercury cells do not 

(“Special Focus on Chlorine,” 2007). Table 2-). Table 2-2 illustrates the approximate energy 

requirements of the different cell types as well as the average electricity prices for the states in 

which the relevant plants are located.
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Table 2-2. Approximate Energy Requirements of Different Cell Types

Section 1 Cell Type

Diaphragm Mercury Membrane

Electricity (kWh) 2,800–3,000 3,200–3,600 2,600–2,800

Steam equivalent (kWh) 800–1,000 0 100–200

Total kWh 3,600–4,000 3,200–3,600 2,700–3,000

Relative energy 100 92 75

Average Electricity Price for Industrial Sector (2007 cents/kWh)

Georgia (Olin GA) 5.53

Ohio (ASHTA) 5.76

Tennessee (Olin TN) 5.19

West Virginia (PPG) 3.95

Sources: “Special Focus on Chlorine.” October 2007. Chemical Business. pp. 27-40. Accessed July 29, 2009, from 

Business Source Corporate database..

Energy Information Administration. 2009. “Electric Power Annual 2007: State Data Tables.” 

http://www.eia.doe.gov/cneaf/electricity/epa/epa_sprdshts.html. Accessed July 31, 2009.Accessed July 31, 2009.

Individual facility capital costs are also contingent on the specific requirements of the 

electrolytic cells used in the production process. For example, the complex mercury cell has a 

higher current density than the diaphragm or membrane and demands a relatively higher capital 

investment. The variations in purification requirements impose the highest brine costs for 

membrane cell plants, whereas the relatively simple brine system accounts for only 3 to 4% of a 

diaphragm cell facility’s capital costs (“Special Focus on Chlorine,” 2007).). A mid-sized 

mercury cell plant not only bears the additional costs of the mercury itself, but also spends 10 to 

15% of the total capital investment on equipment to prevent the hazardous emissions and to 

remove the mercury from the finished products (“Special Focus on Chlorine,” 2007).).

2.1.4 Chlor-alkali Transportation

A critical element in any production industry is the successful transfer of final products 

from the facility to the client. However, the hazardous nature of chemical products requires 

chlor-alkali companies to devote extra resources to developing a geographic network of facilities 

and shipping points that integrates both cost considerations and safety concerns. Industry experts 

are acutely aware of the risks associated with chemical production and strive to maintain security 

of their products, the safety of their employees and consumers, and the well-being of local 

communities. 
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In addition to complying with carefully developed industry standards and stewardship 

practices, chlor-alkali facilities are also subject to federal regulations regarding the proper 

handling of dangerous chemicals. The U.S. Department of Transportation’s Pipeline and 

Hazardous Materials Safety Administration (PHMSA) regulates the transportation of chlorine and 

its derivatives under the Hazardous Material Regulations (49 CFR 171-180) (U.S. Department of 

Transportation, 2009a and 2009b).). The PHMSA and other federal regulatory agencies control 

the movement of hazardous materials by all applicable modes of transportation. Chlorine and its 

derivatives are shipped via rail, highway, water vessel, and pipeline. According to the American 

Chemistry Council, rail hosts the majority of bulk chlorine shipments in the United States (30,000 

tank car/yr) and is the safest mode of chlorine transportation (American Chemistry Council, 

2009).). Although accidents are rare, a 2005 Norfolk Southern freight train collision in South 

Carolina that killed or injured over 200 people illustrates real risks that chlorine transportation 

poses to civilians and communities (Environmental News Service, 2005).). Even though industry 

experts work in conjunction with transportation authorities to ensure that procedures and policies 

are carefully executed, the risk of an accident can never be completely eliminated. 

One way to mitigate the risk of an accident is to minimize the distance from the producer 

to the end-user, which effectively curtails the potential for unexpected events or hazardous leaks 

during transit. Cutting down on travel distance and time is not only cost-effective for producers, 

but it also prevents unnecessary exposure of civilian communities to the dangers associated with 

a collision. Familiarity with travel routes and transportation contractors may also aid chlorine 

producers in reducing the potential for unforeseen circumstances that could threaten the security 

of the cargo.

In light of these issues, companies in the chlor-alkali industry have selected existing 

facility locations based on the financial, logistic, and safety concerns involved with shipping 

their products. Plants, warehouses, and distribution centers are deliberately constructed in 

specific locations to serve customers safely and efficiently. ASHTA’s production facility is 

located adjacent to the titanium dioxide plant to which it sells 100% of its chlorine (U.S. House 

of Representatives Committee on Commerce and Energy, 2009).). The company also has 

warehouses, liquid distribution points, and sales headquarters placed strategically across the 

United States to cater to nationwide potassium hydroxide demand (ASHTA, 2009a).). PPG 

pioneered 1,100-ton capacity barges as a safe mode of chlorine transport from the Natrium plant, 

which is ideally situated on the Ohio River easily accessible by the CSX rail line (PPG, 2009a).).

Olin Corporation’s Charleston plant produces potassium hydroxide and uses rail, barge and 
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trucks to ship the product to customers and the terminal facility located in nearby Chattanooga 

(Olin Corporation, 2009c).).

2.2 The Demand Side

A variety of applications use chlor-alkali products to make other goods. As a result, the 

demand for chlor-alkali products indirectly depends on conditions in downstream end-use 

markets. The organic chemicals industry uses chlorine to make polyvinyl chloride (PVC), and 

the construction industry subsequently uses PVC materials. The pulp and paper industry uses 

caustic soda during manufacturing processes that create paper and other products. Electronic 

products (e.g., televisions and computer monitors) requiring glass cathode ray tubes use 

potassium carbonate made from caustic potash. As a result of these links, growth or downturns in 

end-use markets ultimately influence the demand for chlor-alkali products.

2.2.1 Who Uses Chlorine, Caustic Soda, and Caustic Potash?

Plant-specific information regarding end-users and other within/between plant 

relationships is not generally available or is limited. According to company annual reports (Olin 

Corporation, 2009a),), industry-wide data show that the organic chemical industry uses over 60% 

of chlorine (Figure 2-1). Vinyl chemical producers are industrial consumers (37%), and other 

organic chemical producers use an additional 28%. For caustic soda (Figure 2-2), organic 

chemicals, pulp and paper, and inorganic chemicals are significant end users; each industry 

accounts for more than 20% of caustic soda demand. For caustic potash (Figure 2-3), potassium 

carbonate (28%), other potassium chemicals (15%), and potassium phosphates (10%) are the 

most significant end uses (The Innovation Group [TIG], 2009).). The remaining applications are 

diverse and all account for less than 10% of the market.
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Figure 2-1. Industry-wide Uses of Chlorine by Industry

Source: Olin Corporation, 2009a..

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Vinyls Organics Chorinated

intermediates

Inorganics Water

treatment

Pulp and 

paper

Distribution 

and other

Share

Uses

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Vinyls Organics Chorinated

intermediates

Inorganics Water

treatment

Pulp and 

paper

Distribution 

and other

Share

Uses
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2-9

Figure 2-2. Use of Caustic Soda by Industry

Source: Olin Corporation, 2009a..

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Pulp and 

paper

Alumina Organics Detergents 

and Textiles

Inorganics Water 

Treatment

Others

Share

Uses

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Pulp and 

paper

Alumina Organics Detergents 

and Textiles

Inorganics Water 

Treatment

Others

Share

Uses
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Figure 2-3. Use of Caustic Potash by Industry

Source: The Innovation Group (TIG). 2009. “Caustic Potash Chemical Profile.” http://www.the-innovationgroup.com/welcome.htm. Accessed July 2009. Accessed July 2009.

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Share

Uses

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Share

Uses
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Olin Corporation (2008)) also reports details regarding company-specific end uses and 

customers for their chlor-alkali products in the company’s annual reports (Table 2--3). This 

information applies to all 10 North American chlor-alkali plants and may not necessarily be 

representative of the end-users associated with the mercury cell plant. However, it is the best 

publicly available information EPA was able to identify. Olin sells a majority of its chlor-alkali 

products to third parties; in 2008, no single customer bought more than 8% of total sales (Olin 

Corporation, 2008).). Chlorine is also sold to a relatively small number of industrial customers; 

In contrast, caustic soda is sold to a large number of users or distributors (Olin Corporation, 

2008).).

Trade publications report that ASHTA supplies chlorine to a nearby titanium dioxide 

facility originally owned by Lyondell Chemicals (Sim, 1995);); the plant is now owned by 

Cristal’s Millennium Inorganic Chemicals business and continues to produce titanium dioxide 

(Millennium Inorganic Chemicals, 2009). AHSTA). ASHTA reports that all of its chlorine is 

sold to “a company located adjacent to ASHTA’s facility” (U.S. House of Representatives 

Committee on Commerce and Energy, 2009).). Some of ASHTA’s other alkali products are used 

within the 

Table 2-3. Olin Corporation Products and Services and Major End Uses: 2008

Products and Services Major End Uses Location

Chlorine/sodium hydroxide 

(caustic soda)

Pulp and paper processing, chemical 

manufacturing, water purification, 

manufacture of vinyl chloride, bleach, 

swimming pool chemicals, and 

urethane chemicals 

Augusta, GAa

Becancour, Quebec 

Charleston, TN a

TNa

Henderson, NV 

McIntosh, AL 

Niagara Falls, NY 

St. Gabriel, LA 

Potassium hydroxide (caustic 

potash)

Fertilizer manufacturing, soaps, 

detergents and cleaners, battery 

manufacturing, food processing 

chemicals, and deicers 

Charleston, TN a

a

Denotesa Denotes plant using mercury technology.

company to produce other chemicals. For example, liquid potassium hydroxide is used to make 

potassium carbonate. ASHTA (2009a)) also reports that it is a manufacturer and marketer in the 

following chemical markets:

 45% and 50% liquid potassium hydroxide

 anhydrous potassium carbonate K2CO3
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 anhydrous potassium carbonate flake

 chlorine

 47% liquid potassium carbonate

 anhydrous potassium hydroxide walnut (briquette)

 potassium hydroxide

 chloropicrin

2.2.2 What Factors Influence Demand?

The chlor-alkali industry is considered a procyclical industry where demand for product 

depends on trends in overall economic activity. For example, Olin Corporation (2008)) notes:

The business of most of our customers, particularly our vinyl, urethanes, and pulp 

and paper customers are, to varying degrees, cyclical and have historically 

experienced periodic downturns. These economic and industry downturns have 

been characterized by diminished product demand, excess manufacturing capacity 

and, in some cases, lower average selling prices. Therefore, any significant 

downturn in our customers’ businesses or in global economic conditions could 

result in a reduction in demand for our products and could adversely affect our 

results of operations or financial condition. (p. 8)

Recent research has also suggested that environmental regulations affecting chlorine enduse markets have reduced the demand for chlorine and help explain the exit of selected chlorine 

plants (Snyder, Miller, and Stavins, 2003).). Chlorine plants that were co-located with pulp and 

paper mills and plants affected by the Montreal Protocol were more likely to shutdown (11 to 

15% higher than the average chlorine plant) (Snyder, Miller, and Stavins, 2003).).

In addition to overall demand conditions, selected chlor-alkali product markets are very 

sensitive to price changes of close substitute products. For example, when the price of caustic 

soda rises, soda ash can be substituted for caustic soda in certain uses (e.g., pulp and paper, water 

treatment, and certain chemical sectors) (U.S. Geological Survey [USGS], 2009).).

2.3 Market Characteristics

A review and description of market characteristics (i.e., geography, product 

differentiation, entry barriers, and degree of concentration) can enhance our understanding of 

how chlor-alkali markets operate. These characteristics provide indicators of a firm’s ability to 

influence market prices by varying the quantity of product it sells. For example, in markets with 

large numbers of sellers and identical products, firms are unlikely to be able to influence market 

prices via their production decisions (i.e., they are “price takers”). However, in markets with few 
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firms, significant barriers to entry (e.g., licenses, legal restrictions, or high fixed costs), or 

products that are similar but can be differentiated, a firm may have some degree of market power 

(i.e., set or significantly influence market prices).

2.3.1 Geography

Most chlorine is not sold on the market and is consumed internally by the manufacturer. 

However, marketed chlorine and potassium hydroxide compete in a North American market; 

imports are limited by transportation costs and customer requirements for service and product 

availability (Olin Corporation, 2008;; U.S. Federal Trade Commission [FTC], 2005).). In 

contrast, caustic soda producers sell their product in a worldwide market (Olin Corporation, 

2008).).

2.3.2 Product Differentiation

Product differentiation can occur both from differences in product attributes and quality 

and from brand name recognition of products. For a given end use, industrial consumers are 

likely to view chlor-alkali products produced by different firms as very good substitutes. As a 

result, the products are likely to be sold primarily on a price basis (Olin Corporation, 2008).). In 

addition, a close substitute for caustic soda exists (soda ash) and limits the ability of caustic soda 

producers to significantly influence caustic soda prices by varying the quantities produced 

(USGS, 2009).).

2.3.3 Entry

Short-term entry into the chlor-alkali market is difficult because new plants require 

significant capital expenditures and take time to build. For example, the FTC concluded that new 

entry in the potassium hydroxide market would not be “timely, likely, or sufficient” in response 

to significant price increases (FTC, 2005, p. 5).5). Historically, imports have only played a major 

competitive role in the caustic soda markets only. 

2.3.4 Concentration

Of the three chlor-alkali products, the market for potassium hydroxide is the most highly 

concentrated. As of 2005, there were only four producers of potassium hydroxide in the United 

States (FTC, 2005b).). Approximately 50% is produced using mercury cells; ASHTA Chemicals 

reports a market share of approximately 15% (U.S. House of Representatives Committee on 

Commerce and Energy, 2009). The FTC (2005a, b)). The FTC (2005a, b) has also assessed 

competitive effects of proposed company acquisitions in this sector in some detail. Given these 

characteristics and conclusions of the FTC study, significant changes in production levels at a 
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single company using mercury cells are likely to influence market prices, particularly over short 

periods.

2.4 Overview of Businesses Affected by the Rule

The proposed rule affects four mercury cell plants operating in the United States. We 

provide basic economic statistics for each plant and the ultimate parent companies that own each 

plant. These data are subsequently used for the economic impact analysis described in Section 3. 

2.4.1 Mercury Cell Plants

The four mercury cell plants are located in four different states: Georgia, Ohio, 

Tennessee, and West Virginia. Annual plant sales ranges were estimated using economic data 

from the 2002 Economic Census (Table 2--4) and employment data. Given the uncertainties 

with sales data, we report a low and high range estimate for each plant. Lower-bound sales were 

obtained by multiplying the average value of shipments per employee by the number of 

employees. The upper-bound sales represent the average establishment value of shipments for 

the appropriate establishment size. In cases where census data were not disclosed, we used the 

industry average. As shown, annual plant sales estimates range from $30 to $130 million (Table

2--5).
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Table 2-4. 2002 Economic Census Sales and Employment by Establishment Size

Plant Establishments Employees

Value of 

Shipments

($Million)

$ per

Employee

$ per 

Establishment

($ Million)

All establishments 40 6,022 $2,702 $448,679 $68

1 to 4 employees 7 19 $8 $411,842 $1

5 to 9 employees 2

10 to 19 employees 4 52 $19 $358,231 $5

20 to 49 employees 7 246 $105 $428,415 $15

50 to 99 employees 1

100 to 249 employees 12 1,901 $980 $515,679 $82

250 to 499 employees 5 1,571 $662 $421,701 $132

Source: U.S. Census Bureau; generated by RTI International; using American FactFinder; “Sector 31: 

Manufacturing: Industry Series: Industry Statistics by Employment Size: 2002.” <http://factfinder.census.gov>; 

accessed July, 2009..

Table 2-5. Estimated Plant-Level Sales and Employment: 2008

Plant State

Owned by 

Small Entity

Sales Range

($ million) Employment Employment Source

ASHTA OH Yes $40–$70 ~100 U.S. House of Representatives 

Committee on Commerce and 

Energy, 2009

Olin GA No $40–$70 85 Pavey, 2008

Olin TN No $120–$130 280 Cleveland/Bradley Chamber 

of Commerce, Economic 

Development Council, 2009

PPG WV No $30–$70 540a West Virginia Development 

Office, 2009

a Ward (2007)) suggests that 60 employees are associated with mercury cell operations. 
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2.4.2 Ultimate Parent Companies

EPA has reviewed industry information and publicly available sales and employment 

databases to identify the chain of ownership by accounting for subsidiaries, divisions, and joint 

ventures to appropriately group companies by size. Table 2--6 provides sales and employment 

data for three ultimate parent companies operating mercury plants. EPA classified each parent 

company as a small or large entity using Small Business Administration (SBA) general size 

standard definitions for NAICS codes. These size standards are presented either by number of 

employees or by annual receipt levels, depending on the NAICS code. The chlor-alkali 

companies are covered by NAICS code 325181 and are categorized as small if the total number 

of employees at the ultimate parent company is fewer than 500; otherwise, the ultimate parent 

company is classified as large. As shown in Table 2-6 ASHTA Inc. is considered a small 

business.

Table 2-6. Ultimate Parent Company Sales and Employment: 2008

Plant State Parent Company Owned by Small Entity Sales Employment

ASHTA OH ASHTA Chemicals Inc. Yes <$75 million <100

Olin GA, TN Olin Corporation No $1.8 billion 3,600

PPG WV PPG Industries Inc. No $15.8 billion 44,900

Sources: Olin Corporation. December 31, 2008. Form 10-K. Filed February 25, 2009. http://b2i.api.edgaronline.com/EFX_dll/EdgarPro.dll?FetchFilingConvPDF1?SessionID=DOVFWfuqOuZBE-9&ID=6436012.

Accessed July 2009. Accessed July 2009.

PPG Industries, Inc. December 31, 2008. Form 10-K. Filed February 19, 2009. http://corporateportal.ppg.com/

NR/rdonlyres/EAC49DFC-DB9C-4320-B9A3- 421E40162220/0/10KYREND2008.pdf. Accessed July 2009.

Accessed July 2009.

2.4.2.1 Company Profitability Measures

Company profitability trends significantly influence the ability and desire to take on 

large-scale capital projects. Although data on profits for individual companies are limited, 

historical government statistics about industry groups and publicly traded companies provide 

accounting measures of profit in annual reports. In Figure 2-4, we present information from the 

U.S. Census Quarterly Manufacturing Reports about the Basic Chemicals, Resins, and Synthetics 

(NAICS 3251 and 3252) (U.S. Census Bureau, 2000–2006).). This is the finest level of detail 

reported by the Census and includes other chemical industries in addition to the chlor-alkali 

industry. As shown, there is substantial variation in the profitability rates for the industry; beforetax profits as a percentage of net sales range from 1 to 10% during this period, with an average of 

5% and a standard deviation of 3%.
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Figure 2-4. Income (or Loss) as Net a Percentage of Sales, Basic Chemicals, Resins, and 

Synthetics (NAICS 3251 and 3252): 2000–2005

0%

1%

2%

3%

4%

5%

6%

7%

8%

9%

10%

11%

12%

13%

14%

15%

1996 1997 1998 1999 2000 2001 2002 2003 2004 2005

Income (or loss) (percent of net sales)

Year

After Tax Before Tax

0%

1%

2%

3%

4%

5%

6%

7%

8%

9%

10%

11%

12%

13%

14%

15%

1996 1997 1998 1999 2000 2001 2002 2003 2004 2005

Income (or loss) (percent of net sales)

Year

After Tax Before Tax
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Source: U.S. Census Bureau. 2001–2006. Quarterly Financial Report for Manufacturing, Mining, and Trade 

Corporations, 1st Quarter reports. http://www.census.gov/prod/www/abs/qfr-mm.html. Accessed July 2009.

Accessed July 2009.

Census data also show that smaller companies (defined by Census as companies with less 

the $25 million in assets) have profit rates that are smaller than industry averages. For example, 

in a representative year during this period (2000), before-tax profits as a percentage of net sales 

for small companies were less than 1% compared to approximately 6% for the industry as a 

whole.

To assess how representative the census data were for individual companies, EPA 

examined annual reports for Olin Corporation and PPG Industries and found before-tax profit 

rates were comparable with quarterly financial report (QFR) 2000 industry averages. Olin 

reported a rate of approximately 8% and PPG reported a rate of 11% (Olin Corporation, 2001;;

PPG, 2001).). These values are based on income statements and include all operations in addition 

to the chlor-alkali segment. Olin reported similar profit rates for its chlor-alkali segment (~7%), 

but PPG did not report separate profitability information for their chemical commodity segment.
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SECTION 3: 
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3-1

SECTION 3

ENGINEERING COST ANALYSIS

Most of this section addresses the cost analysis for For Option 1 (Non-mercury 

Technology Option). The other option In order to estimate the capital and annual costs 

associated with a conversion from mercury cell chlor-alkali technology to membrane cell 

technology, information was used from the following resources:

• EPA’s Mercury Report to Congress1

• Recent news reports regarding plants converting or considering 

converting2,3,4,5,6,7, 8

• EPA waste minimization study9

• Fact sheet from the conversion of a Canadian facility10

• General chlor-alkali reference11

• European Best Available Techniques Document12

• Information from Oceana.

,. ,.

and the Chlorine industry.

,

.

,

.

,

.

,

.

,

.

,

.

,

.

,

.

 1 U.S. EPA. Mercury Study Report to Congress Volume VIII: An Evaluation of Mercury Control Technologies and 

Costs. U.S. Environmental Protection Agency, Office of Air Quality Planning and Standards, Research Triangle 

Park, NC. December 1997.

2 Bradbury, D. Portrait of a Polluter. Portland Press Herald. 1997. 3 Markets - —News Release. Houston Chronicle. January 30, 2007. 4 McCoy, M. PPG to Convert Chlorine Cells. Chemical and Engineering News. August 8, 2005. 5 Wise, A. Port Edwards sells School Forest Land to ERCO Worldwide; Nekoosa Considers Similar Deal.

Wisconsin Rapids Tribune. January 13, 2009. Available on the Internet at: www.wisconsinrapidstribune.com.

6 Westlake Chemical Corporation (2003, December 31). Form 10-K, United States Securities and Exchange 

Commission. Available on the Internet at 

http://www.sec.gov/Archives/edgar/data/1262823/000095012904001565/h13929e10vk.htm

7 Chlorine/Chlorate Newsletter. “Tessenderlo Upgrades Chlorine; Expands VCM, PVC.” March 2002. p. 10-11.

Available on the Internet at: 

http://www.eltechsystems.com/newsletter/ELTECH%20Newsletter%20March%202002.pdf. Accessed 3/2/2007.

8 Hydrocarbon Processing (2007, November 19). "Uhde Opens New Electrolysis Plant." 

9 Drabkin, M. and Rissmann, E. Project Summary Waste Minimization Audit Report: Case Studies of Minimization 

of Mercury Bearing Wastes at a Mercury Cell Chlor-alkali Plant. EPA/600/S2-88/011. U.S. Environmental 

Protection Agency, Hazardous Waste Engineering Research Laboratory, Cincinnati, OH. March 1988. 10 Fact Sheet No. 12. PPG Canada. St Lawrence Vision 2000, Beauhamois, Quebec, Canada. 1996. 11 Modern Chlor-Alkali Technology, Volume 2. Jackson, C., Editor. Society of Chemical Industry, London, 

England. 1983.

12 Reference Document on Best Available Techniques in the Chlor-Alkali Manufacturing Industry. European 

Integrated Pollution Prevention and Control (IPPC) Bureau, Seville, Spain. December 2001. Available on the 

Internet at http://eippcb.jrc.es/reference/cak.html. 
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 Oceana13

In addition to reviewing the Oceana correspondence, all directly relevant references cited 

by Oceana in their comments were obtained, reviewed, and considered. These references are 

compiled and available in the docket as one docket entry.

and the Chlorine industry

14

3.1 Capital Costs

Initially, to determine capital costs of conversion to non-mercury technology, EPA 

collected capital cost data for mercury cell conversion projects that occurred between 1992 and 

2008 from the search of the resources listed above.. . In their September 15, 2009 

memorandum,., Oceana pointed out that several of the capital cost data points were not 

appropriate because either the costs were from unsubstantiated estimates or they were developed 

from conversions that were done so long ago that they did not apply to membrane cell 

technologies currently being used.

Initially, Oceana identified seven capital cost data points for conversion to non-mercury 

technology that were derived from estimates rather than actual conversions. These were:

• One 1997 estimate published by a HoltraChem facility where the conversion did 

not in actuality occur;

• One 1988 estimate for a facility in the U.S. that could not be identified;

• One 1992 estimate for a “model plant” representing a mid-range facility size, with 

no documentation included; and 

• Four European estimates for conversions to non-mercury technology,., which did 

not include information on plant production capacities.

In addition, Oceana stated that conversion project costs prior to 1995 are not applicable to 

current-day conversion costs. According to Oceana, newer membrane-cell technology uses 

bipolar electrolyzers, which were not commercially available until around 1997.. . The 

conversions prior to 1995 would have used the older monopolar electrolyzers. Therefore, we 

agree with Oceana’s position that for this analysis it is not appropriate to include the data points 

 13 Oceana is a large international organization focused on ocean conservation (www.oceana.org). They have 

provided comments on EPA’s analyses of the costs and other impacts of converting mercury cell chlor-alkali 

plants to membrane cells on multiple occasions, along with providing substantial data and analyses to support 

their comments. 14 Memorandum from Brown, H.P., EC/R Incorporated, Chapel Hill, NC, to Docket EPA-HQ-OAR-2002-0017.

Capital and Annual Costs References Cited By Oceana in Their Comments on EPA’s Cost Analysis of the 

Conversion of Mercury Cells to Membrane Cells. (Docket No. EPA-HQ-OAR-2002-0017). March 15, 2010. 
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derived from conversions that took place prior to 1995; thus these data points were not used in 

our current analysis. 

We developed capital cost factors for conversion to membrane cell technology in units of 

dollars per ton ($/ton) of chlorine (Cl2) production using data from conversions anywhere in the 

world that took place after 1995, excluding the cost data described above. These costs and cost 

factors are shown in Table 3--1. The cost factors ranged from $267 to $941/ton Cl2 produced 

and averaged $535/ton Cl2. In addition, Table 3--1 shows the average of the cost factors from 

only the most recent US conversions (since 2000), which is $596/ton Cl2.

Since membrane cells are smaller than mercury cells, in some conversions the companies 

have elected to use the extra available space to install additional membrane cells, thus increasing 

the chlorine and caustic production capacity of the facility. Therefore, for some conversion 

projects included in Table 3--1, an increase in production capacity was also included. Oceana 

indicated in their comments. that a conversion cost analysis should either exclude the costs 

attributed to expanding capacity or include the cost saving benefits derived from expanding 

capacity. We do not believe that it is appropriate to make an assumption about savings because 

any benefits derived from additional sales due to increased capacity assumes that product 

demand would simultaneously increase. We do not disagree that the additional incremental costs 

of the expanded capacity should be excluded. However, the available information does not 

provide a breakdown of the costs associated with conversion versus the costs associated with the 

increased capacity. Therefore, the capital costs for some conversions may include expansion 

costs. This could result in the capital costs based on these data being biased high.

When providing comments on the June 2009 memorandum, ASHTA stated that 

differences in size, the new or expanded infrastructure required, and the end products desired 

(e.g., vapor or liquid chlorine, dilute or merchant concentration of caustic) all impact the actual 

cost of conversion.. . ASHTA suggested that, minimally, conversion cost estimates should take 

into account economies of scale. However, Oceana expressed concern with the use of an 

equation that relates increasing size to lower conversion costs to estimate the cost of conversion 

for the four remaining facilities, since extrapolation of the costs to very small or very large 

capacities produces illogical conclusions. But we do believe that there could be some economies 

of scale. An equation we developed using the limited data set of the recent U.S. conversions

showed a good correlation (correlation coefficient (R2),15 = 0.9981). of costs to facility 

 15 The correlation coefficient is a measure of how accurately a regression predicts a value. The regression is most 

accurate when R2 is equal to one (1).
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3-4

size/capacity. However, when the entire data set (in Table 3-1) was plotted, a similar correlation 

was not observed. 

Figure 3- 1 presents these cost factors versus plant chlorine capacity for all the 

facilities. As shown in Figure 3- 1, there is little correlation between cost factor and plant 

chlorine capacity (R2 = 0.0102) for all global conversions with documented data. Therefore, we 

agree with Oceana that it is most appropriate to use a single cost factor to estimate the capital 

costs of conversion.

Table 3-1. Cost Factors for Conversion of Mercury Cell Chlor-Alkali Facilities to 

Membrane Cell Technology ($/ton Cl2 produced)

Year of 

Estimate

Location of 

Conversion

Capital Cost 

(as provided)

Capacity

(ton Cl2

/yr)

Capital Cost Factor 

($/ton Cl2 produced/yr)

Base Year 2007 Reference a

1997 Europe $104,946,640 173,063 $606 $824 12

1997 Europe $32,856,014 110,231 $298 $405 12

1998 Europe $16,334,213 66,139 $247 $333 12

1998 Europe $13,094,369 66,139 $198 $267 12

1998 Europe $29,923,557 44,092 $679 $915 12

1998 US (OxyTech)a $57,327,236 135,033 $425 $573 12

1998 Asia $39,775,832 182,983 $217 $293 12

1999 Europe $131,159,254 330,693 $397 $533 12

1999 Europe $31,026,058 82,673 $375 $505 12

2002 US (Westlake, KY) $86,100,000 205,000 $420 $497 6

2004 Belgium $171,032,583 363,762 $470 $556 7

2005c US (PPG, LA) $90,000,000 275,000 $327 $367 4

2007c US (Pioneer, LA) $117,000,000c 197,000 $594 $594 3

2007c Germany $109,678,733 250,000 $439 $439 8

2008c US (ERCO, WI) $107,112,676b 118,000 $908 $908 5

Average $535

Average of Recent US Conversionsb $596

N/A = Not Available

a The conversion to 2007 dollars was estimated using the Chemical Engineering Plant Cost Index Economic 

Indicators. Base year costs were adjusted to 2007 dollars using the ratio of the 2007 economic indicator and the 

base year economic indicator. See Reference 16..

17

 16 Chemical Engineering Plant Cost Index. Chemical Engineering. February 2009. Available on the Internet at 

www.che.com. 
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b Refers to conversions that occurred in the United States after 2000.

c Used in this analysis to develop an average factor for near future U.S. conversions.

showed a good correlation (correlation coefficient (R2),18 = 0.9981) of costs to facility 

size/capacity.19

Figure 3-1 presents these cost factors versus plant chlorine capacity for all the facilities. 

As shown in Figure 3-1, there is little correlation between cost factor and plant chlorine capacity 

(R2 = 0.0102) for all global conversions with documented data. Therefore, we agree with Oceana 

that it is most appropriate to use a single cost factor to estimate the capital costs of conversion.

However, when the entire data set (in Table 3-1) was plotted, a similar 

correlation was not observed. 

Figure 3-1. Capital Cost Factor ($/ton Cl2 produced) vs. Capacity

 17 Chemical Engineering Plant Cost Index. Chemical Engineering. February 2009. Available on the Internet at 

www.che.com. 18 The correlation coefficient is a measure of how accurately a regression predicts a value. The regression is most 

accurate when R2 is equal to one (1).

19 Memorandum from Jones, D.L., PhD, EPA, Research Triangle Park, NC, Brown, H.P. and Norwood, P., EC/R 

Incorporated; Chapel Hill, NC; to Project File—Mercury Chlor-Alkali NESHAP. Revised Conversion Costs and 

Baseline Emissions—Conversion From Mercury Cell Chlor-Alkali to Membrane Cell Technology. (Docket Item 

No. EPA-HQ-OAR-2002-0017-0105). September 15, 2009.

 

0

100

200

300

400

500

600

700

800

900

1,000

0 100,000 200,000

pital Cost Factor ($/ton Cl2 produ

 

 
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3-6

In order to develop capital cost factors for the current four mercury cell facilities, the 

chlorine production capacities from the 1997 Directories of Chemical Producers20

Because of several known factors, including environmental regulations and process 

safety management, we do not believe the broad range of data represented by all the facilities 

shown in Table 3-1 to be as accurate as the recent conversions that have occurred since 2000 in 

the U.S. to use to estimate the potential capital costs of conversion for the four remaining U.S. 

facilities. We believe that the average cost factor from the four recent U.S. conversions results in 

the best estimate of the capital costs that would occur for all four mercury cell chlor-alkali plants

were obtained 

and are shown in Table 3--2. The capital costs of converting to membrane cell technology for 

the four facilities in current operation were then estimated using these capacities. As shown in 

Table 3--2, capital costs were estimated using both the average capital cost factor for the entire 

data set ($535/ton Cl2) in Table 3--1, and then also using the average of only the four most 

recent U.S. conversions ($596/ton Cl2) since 2000.

Figure 3-1. Capital Cost Factor ($/ton Cl2 produced) vs. Capacity

 20 1997 Directory of Chemical Producers - —United States of America. Stanford Research Institute International. 

Menlo Park, CA. 1997. 

 

0

100

200

300

400

500

600

700

800

900

1,000

 ost Factor ($/ton Cl2 produced)

 

 

produced/yr)
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Table 3-2. Table 3-2. Estimated Capital Costs for Existing Mercury Cell ChlorAlkali Facilities

Facility

Cl2 Production Capacity 

(ton/yr)a

Capital Costs ($)

Based on Entire 

Data Setb

Based on Recent 

U.S. Conversionsc,d

ASHTA 47,421 25,375,938 28,246,460

Olin GA 119,031 63,695,899 70,901,169

Olin TN 262,451 140,442,954 156,329,838

PPG 72,848 38,982,173 43,391,830

Totals 268,496,964 298,869,297

a From Reference 20. b Calculated using average capital cost factor of $535/ton Cl2 for entire data set.

c Calculated using average capital cost factor of $596/ton Cl2 for recent (i.e., after 2000) U.S. Conversions.

d Used in this analysis to develop costs for near future U.S. conversions.

to convert to membrane cells. Because of several known factors, including environmental 

regulations and process safety management, we do not believe the broad range of data 

represented by all the facilities shown in Table 3-1 to be as accurate as the recent conversions 

that have occurred since 2000 in the U.S. to use to estimate the potential capital costs of 

conversion for the four remaining U.S. facilities. We believe that the average cost factor from the 

four recent U.S. conversions results in the best estimate of the capital costs that would occur for 

all four mercury cell chlor-alkali plants to convert to membrane cells. The total estimated capital 

cost of conversion for all four facilities, therefore, is approximately $300 million, which is also 

shown in Table 3--2.

3.2 Annual Costs

The annual costs associated with the conversion of mercury cells to membrane cells 

include costs related to capital recovery, unused mercury storage costs, and energy costs due to 

the need for increased steam required to further concentrate caustic. However, some of these 

additional annual costs will be offset by savings realized due to the elimination of mercury, e.g., 

mercury-related environmental compliance costs and the reduced energy needs for the membrane 

cell process. Each of these costs and savings are described below.

3.2.1 Capital Recovery Cost

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.
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3-8

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 finance period. The 

estimates for capital costs were discussed above; the remainder of this discussion is focused on 

the interest rate and the finance period.

As pointed out by Olin in their February 2, 2010, correspondence. “access to 

capital and available interest rates are a function of many things, including the overall financial 

environment, the financial condition of the prospective borrower (including its debt load), and 

the amount and length of the loan.” In their June 25, 2009 correspondence,., Olin also stated that 

“a 7 percent interest rate is simply not available to industry in this economy.” They suggested 

replacing the 7 percent rate with a 10 percent, or even a 14 percent rate. In their February 2010 

correspondence, Olin provided an example to support the use of an interest rate higher than 

7 percent. Olin reported that they sold $150 million in Senior Notes, and that these notes had an 

interest rate of 8.875 percent and a maturity date of August 2019. According to Olin, the 

effective interest rate was over 9 percent considering the costs and discount.

The interest rate can result in significant differences in total annualized costs. For 

example, for a finance period of 15 years, the difference in capital recovery costs is 

approximately 20 percent higher for a 10 percent interest rate than for a 7 percent interest rate.

This difference is even more profound for longer finance periods.

EPA’s Office of Air Quality Planning and Standards always provides an interest 

rate of 7 percent for cost analysis. While we do not disagree with Olin’s information, we feel 

that it is important to maintain uniformity to allow decision-makers to consider consistent 

information across various regulatory decisions. Therefore, in this present analysis, an interest 

rate of 7 percent was used in the development of the capital recovery cost. It should be noted that 

for a particular firm at a particular time, this interest rate of 7% might not be available because of 

either the firms financial health or temporary economic condition. In previous versions of this 

analysis, a finance period of 15 years was used. Oceana commented that this underestimates the 

useful life of the equipment and overestimates the annualized costs.. . Oceana suggested that a 

30-year finance period was more appropriate, and cited a previous analysis for the mercury cell 

industry where EPA used a 30-year period to estimate the capital recovery costs.21

 21 Memorandum from Brown , H.P., EC/R Incorporated, Chapel Hill, NC, to D.L. Jones, U.S. Environmental 

Protection Agency, Research Triangle Park, NC. Documentation of Building Replacement Cost Estimates. June 

5. 2008.

However, it 

is important to note that the use of a 30-year finance period in the analysis cited by Oceana was 
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3-9

for a stationary building and not an operating industrial process. Therefore, we do not agree that 

this example establishes a precedent that is pertinent to our analysis.

To illustrate the importance of the choice of finance period, consider the fact that 

the capital recovery costs for a 30-year finance period at 7-percent interest rate would be 

approximately 30 percent lower than those for a 15 year finance period. Table 3--3 shows the 

annual capital recovery costs for both a 15-year and 30-year period, using the capital cost 

estimates based on the cost factor from the average of recent U.S. conversions shown in Table

3--2 of the previous section. While we recognize that a 15-year finance period may understate 

the lifetime of the membrane cell process equipment, we believe that the use of a 30-year period 

will bias the annualized costs unreasonably low. Therefore, we chose to base our capital 

recovery cost estimates on a 20-year finance period which is higher than our previous estimate of 

15 percent. This results in total annualized costs for the four U.S. facilities of approximately 

$30 million/yr, which we believe represent the best estimate of the capital recovery costs, as 

shown in Table 3--3.

3.2.2 Annual Costs Associated with Storage of Unused Mercury 

Table 3-3. According to the Chlorine Institute, there were 1,376 tons of mercury 

available at the five mercury cell plants operating in 2008.22

There were two sources of information identified that provided estimates of 

mercury storage costs. EPA’s Office of Pollution Prevention and Toxics and the EPA Office of 

Solid Waste and Emergency Response

These plants operated a total of 264 

mercury cells, which equates to 5.2 tons of mercury per cell (ton Hg/cell) on the average. To 

estimate the amount of mercury available at each of the four currently operating facilities, that 

would need to be stored if they converted to membrane cells, this average factor was multiplied 

by the number of cells in each of the facilities. As shown in Table 3-4, this results in an 

estimated total of 1,272 tons of mercury to be stored, ranging from 125 tons at ASHTA to over 

550 tons at Olin TN.

23

 22 The Chlorine Institute, Inc. “Chlor-Alkali Industry 2008. Mercury Use and Emissions in the United States 

(Twelfth Annual Report).” August 2009.

has estimated future mercury storage costs at a private 

facility would be between $0.081 and $0.186 per year per pound of mercury stored, with an 

average of $0.134 per year per pound. The Defense National Stockpile Center also has presented 

23 Mercury Storage Cost Estimates – —Final Report. U.S. Environmental Protection Agency. Office of Pollution 

Prevention and Toxics and Office of Solid Waste and Emergency Response, Washington, DC. November 6, 

2007. Page 28, Exhibit 15. Available on the Internet: 

http://www.epa.gov/mercury/stocks/Storage_Cost_Draft_Updated_11-6-final.pdf
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3-10

information indicating that the cost associated with the federal mercury storage is $0.0561/yr/lb 

Hg.24

Table 3-4 shows the estimated storage costs using both the average factor from EPA 

($0.134/yr/lb) and the factor from the Department of Defense ($0.0561/yr/lb). While there is a 

considerable difference in these estimates, the sources of the information are reliable. Use of 

either factor could bias the annual cost estimates high or low. Therefore, we assumed that these 

two points represent the upper and lower bounds of the storage costs, and that the midpoint of the 

range of storage costs represents the best estimate of the mercury storage costs that would be 

incurred. These midpoint costs, which are also shown in Table 3-4, total just over $240,000 per 

year for all four plants.

Table 3-3. Estimated Capital Recovery Costs for Varying Finance Periods (Using 7 percent 

interest rate)

Plant

Best Estimate of 

Capital Cost ($)a

Capital Recovery Costs ($/yr)

15 years

(CRFb = 0.1098)

30 years

(CRFb = 0.0806)

20 yearsc

(CRFb = 0.0944)

ASHTA $28,246,460 $3,101,309 $2,276,281 $2,666,266

Olin GA $70,901,169 $7,784,567 $5,713,670 $6,692,569

Olin TN $156,329,838 $17,164,176 $12,598,059 $14,756,431

PPG $43,391,830 $4,764,190 $3,496,792 $4,095,882

Totals $32,814,242 $24,084,802 $28,211,147

a Using the average cost factor from recent U.S. Conversions (See Table 3--2). b CRF = Capital Recovery Factor.

c Used in this analysis to develop costs for near future U.S. conversions.

3.2.2 Annual Costs Associated with Storage of Unused Mercury 

According to the Chlorine Institute, there were 1,376 tons of mercury available at the five 

mercury cell plants operating in 2008.25

 24 Lynch, Dennis, Environmental Protection Specialist. Presentation made at the Asia Mercury Storage Project 

Inception Workshop on March 4, 2009 at the Defense National Stockpile Center, Fort Belvoir, VA. 

These plants operated a total of 264 mercury cells, 

which equates to 5.2 tons of mercury per cell (ton Hg/cell) on the average. To estimate the 

amount of mercury available at each of the four currently operating facilities, that would need to 

25 The Chlorine Institute, Inc. “Chlor-Alkali Industry 2008. Mercury Use and Emissions in the United States 

(Twelfth Annual Report).” August 2009.
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3-11

be stored if they converted to membrane cells, this average factor was multiplied by the number 

of cells in each of the facilities. 
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3-12

Table 3-4. Estimate of Annual Mercury Storage Costs

Facility

Number 

Cellsa

Available 

Mercury 

(ton) b

Mercury Storage Costs ($/yr)

Using EPA 

Factor 

($0.134/yr/lb)

Using DOD 

Factor 

($0.0561/yr/lb)

Midpoint of EPA 

and DOD Factorsc

As shown in Table 3-4, this results in an estimated total of 1,272 tons of mercury to be 

stored, ranging from 125 tons at ASHTA to over 550 tons at Olin TN.

Table 3-4. Estimate of Annual Mercury Storage Costs

Facility

Number 

Cellsa

Available 

Mercury 

(ton) b

Mercury Storage Costs ($/yr)

Using EPA 

Factor 

($0.134/yr/lb)

Using DOD 

Factor 

($0.0561/yr/lb)

Midpoint of EPA 

and DOD 

Factorsc

ASHTA 24 125 $33,399 $14,035 $23,717

Olin GA 60 313 $83,498 $35,088 $59,293

Olin TN 106 552 $147,513 $61,989 $104,751

PPG 54 281 $75,148 $31,579 $53,364

Totals 244 1,271 $339,558 $142,691 $241,125

a Reference 20.

b Total amount of available mercury (5.28 tons/cell) distributed by number of mercury cells (see Reference 25). c Used in this analysis to develop costs for near future U.S. conversions.

There were two sources of information identified that provided estimates of mercury 

storage costs. EPA’s Office of Pollution Prevention and Toxics and the EPA Office of Solid 

Waste and Emergency Response26 has estimated future mercury storage costs at a private facility 

would be between $0.081 and $0.186 per year per pound of mercury stored, with an average of 

$0.134 per year per pound. The Defense National Stockpile Center also has presented 

information indicating that the cost associated with the federal mercury storage is $0.0561/yr/lb 

Hg.27

 26 Mercury Storage Cost Estimates – —Final Report. U.S. Environmental Protection Agency. Office of Pollution 

Prevention and Toxics and Office of Solid Waste and Emergency Response, Washington, DC. November 6, 

2007. Page 28, Exhibit 15. Available on the Internet: 

http://www.epa.gov/mercury/stocks/Storage_Cost_Draft_Updated_11-6-final.pdf 27 Lynch, Dennis, Environmental Protection Specialist. Presentation made at the Asia Mercury Storage Project 

Inception Workshop on March 4, 2009 at the Defense National Stockpile Center, Fort Belvoir, VA. 
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3-13

Table 3-4 shows the estimated storage costs using both the average factor from EPA 

($0.134/yr/lb) and the factor from the Department of Defense ($0.0561/yr/lb). While there is a 

considerable difference in these estimates, the sources of the information are reliable. Use of 

either factor could bias the annual cost estimates high or low. Therefore, we assumed that these 

two points represent the upper and lower bounds of the storage costs, and that the midpoint of the 

range of storage costs represents the best estimate of the mercury storage costs that would be 

incurred. 

These midpoint costs, which are also shown in Table 3-4, total just over $240,000 per 

year for all four plants.

The Mercury Export Ban Act (MEBA), which became public law on October 14, 2008 

(Public Law No. 110-414), is intended to reduce the availability of elemental mercury in 

domestic and international markets. MEBA prohibits the export of elemental mercury as of 

January 1, 2013, and requires the Department of Energy (DOE) to designate and operate a 

facility (or facilities) for the purpose of long-term management and storage of elemental mercury 

generated in the United States. MEBA also prohibits the transfer of elemental mercury held by 

federal agencies as of the date of enactment in order to further control the flow of elemental 

mercury in the domestic market. MEBA covers elemental mercury but not mercury compounds. 

MEBA requires DOE to publish guidance establishing procedures and standards for the 

receipt, management and long-term storage of elemental mercury by October 1, 2009. DOE 

issued an Interim Guidance document to fulfill this requirement, which is available at 

http://mercurystorageeis.com/Elementalmercurystorage%20Interim%20Guidance%20(dated%20

2009-11-13).pdf (See also Notice of Availability, November 16, 2009, 74 FR 58952). DOE must 

designate a facility or facilities for long-term management and storage of elemental mercury by 

January 1, 2010 according to MEBA. DOE has issued a Draft Long-Term Management and 

Storage of Elemental Mercury Environmental Impact Statement (EIS) which analyzes a number 

of candidate facilities. The draft Mercury Storage EIS is available at 

http://www.mercurystorageeis.com/ (See also Notice of Availability, January 29, 2010, 75 FR 

4801). DOE is due to release a draft environmental impact statement (dEIS) for evaluating 

potential storage sites by December 2010. 

MEBA requires that DOE to assess and collect fees for providing management and 

storage of elemental mercury. The amount of the fees will be made publicly available by October 

1, 2012. MEBA also requires a designated facility or facilities to be operational by January 1, 

2013; the facility will be subject to RCRA Subtitle C requirements, except for the storage 

prohibition contained in § 3004(j) of the Solid Waste Disposal Act. MEBA requires the storage 

facility to accept custody, for the purpose of management and storage, of elemental mercury 
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3-14

generated within the United States and delivered to the facility, and that persons who deliver 

elemental mercury to the storage facility are indemnified against any liability related to the 

release or threatened release of mercury after delivery to the facility. MEBA also requires EPA 

or an authorized state to issue a final decision on a RCRA permit application for a DOE facility 

by January 1, 2015. 

In addition, MEBA authorizes DOE to establish terms and conditions for the long-term 

management and storage of elemental mercury. DOE has indicated that elemental mercury to be 

stored at the DOE facility or facilities must be of a purity of 99.5 percent or greater by volume 

(see DOE Interim Guidance document and Draft Mercury Storage EIS). Therefore, elemental 

mercury of lower purity would need to be further refined before it could be stored at the DOE 

facility (or facilities), but export or federal agency transfer of such mercury is still prohibited. 

MEBA does not affect RCRA or RCRA regulations except that elemental mercury stored at the 

DOE facility, or elemental mercury that is destined for the DOE facility and accumulated for 90 

days or less is not subject to the RCRA storage prohibition, 3004(j) of the Solid Waste Disposal 

Act (42 U.S.C. 6924(j)). (See MEBA Sec. 5(g)(2)).

The elemental mercury that chlor-alkali facilities store on-site remains a commercial 

chemical product and its storage is not barred by federal environmental statutes as long as it is 

not discarded. This is the case whether the facility continues to operate a mercury cell process, 

converts to a non-mercury process or shuts down the plant. State or local restrictions may apply, 

however. After the establishment and operation of the DOE facility, mercury being stored at 

chlor-alkali plants can continue to be stored as a product. However, if storage continues over a 

long period of time, or if the supply of commodity grade mercury exceeds domestic demand, 

EPA may assess on a case-by-case basis the legitimacy of a claim that elemental mercury storage 

does not constitute discard. For a full discussion, see 

http://www.epa.gov/boston/topics/cleanup/compendium/2002-Mercury-from-the-HoltraChemManufacturing-Co.pdf The EPA encourages responsible stewardship of the elemental mercury 

designated to go to a DOE facility, which could involve arranging secure temporary storage, 

such as a RCRA-permitted facility with the capacity to store mercury on a short term basis, until 

the company can send it to DOE for long-term storage. 

3.2.3 Costs Savings Associated with the Elimination of Mercury-Related Environmental 

Compliance Costs

There are some expected costs savings related to the conversion from a mercurycontaining process to the membrane cell process due to the elimination of compliance costs 

associated with the use of mercury. These savings can be categorized into three environmental 
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3-15

elements: air, waste, and water. Air-related environmental compliance cost savings are realized 

when the facility no longer has to comply with mercury-related air regulations, as well as labor 

due to the elimination of mercury-related air monitoring, reporting, abatement measures, and 

occupational exposure monitoring. Waste-related environmental compliance cost savings are 

realized when a facility no longer incurs costs due to recycling, retorting, transporting, storing 

and/or disposing of mercury wastes. Water-related environmental compliance cost savings are 

realized when the facility no longer is required to operate mercury wastewater treatment 

programs.

We used information from the literature28 (with costs converted from Euros to U.S. 

dollars using the average 2004 exchange rate29 of 1.2439) and cost information presented to the 

State of Ohio by ASHTA as a part of their consent order30

20

to estimate the cost savings.

Information related to annual compliance costs associated with reducing mercury air emissions 

from the hydrogen and end box vent streams, presented to the Ohio EPA by ASHTA under the 

consent order, indicated that ASHTA would spend approximately $228,000 annually on air 

compliance. This value was converted to a $/ton Cl2 value based on ASHTA’s capacity of 

47,421 ton Cl2/yr, resulting in a cost factor of $4.81/ton Cl2 capacity. Since these costs would 

no longer be incurred after conversion, this factor represents a savings. In contrast, European 

information indicates that a savings of approximately $2.20/ton Cl2 in expenditures related to air 

compliance could be realized from the elimination of mercury.28

In addition to the air-related compliance costs described above, ASHTA presented 

to the Ohio EPA that they would be spending approximately $256,500 annually on fugitive 

mercury emission-related activities (including the implementation of leak detection and repair 

standards). Upon conversion to membrane cells, this would represent a savings. These costs and 

savings are not relevant for the other three facilities because ASHTA is the only facility that did 

not install a cell room instrumental monitoring program and, therefore, is required to perform a 

leak program.

 28 Maxon, Peter, Director. Concorde East/West Sprl. Status Report: Mercury Cell Chlor-Alkali Plants in Europe.

Prepared for European Environmental Bureau, Brussels, Belgium. October 2006.

29 Historic Exchange Rates. Prepared by GOCurrency.com. Available on the Internet at www.gocurrency.com.

Accessed April 1, 2009 and April 30, 2009. 30 ASHTA Chemicals. Early MACT Compliance. Consent Agreement. Exhibits B and C. (Docket No. EPA-HQOAR-2002-0017). August 2004. 
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3-16

ASHTA also presented information to the Ohio EPA related to costs for their 

water treatment system. According to ASHTA, they spend approximately $98,000 annually on 

their storm water recovery system. This converts to a cost/savings factor of $2.07/ton Cl2

capacity for elimination of water-related compliance costs due to mercury use. The European 

information indicates that a cost savings of approximately $1.92/ton Cl2 could be realized by the 

eliminations of a mercury wastewater treatment system.28

Waste-related environmental compliance cost savings are realized by facilities no longer 

being required to recycle, retort, transport, store and/or dispose of mercury-containing wastes.

The only information available was the European data that indicated that facilities could expect a 

cost savings of $6,470/ton waste, at an average mercury waste production rate of 4.2x10-5 ton 

waste per ton Cl2.

28 This results in a waste-related cost savings of $0.27/ton Cl2 capacity for 

elimination of waste-related compliance costs due to mercury use.

Table 3--5 presents the cost savings factors for each environmental compliance 

element discussed above from both the information from ASHTA as well as the European 

literature. A total environmental compliance cost savings factor was obtained from the sum of 

all the individual elements in each data set. Since ASHTA did not provide data related to annual 

cost of handling mercury-related wastes, the value from the literature was used to obtain a total 

from all media. With this approach, a value of $7.15/ton Cl2 shown in Table 3--5, was 

developed from data mostly from ASHTA, and a value of $4.63/ton Cl2 was developed from the 

European literature. 

Table 3-5. Environmental Compliance Cost Savings Factors from Elimination of the 

Mercury Process 

Environmental Element

Cost Saving Factors from Elimination of Mercury ($/ton Cl2)

ASHTA Factora Literature Factorb

Air 4.81 2.20

Water 2.07 2.16

Waste 0.27c 0.27

Totals 7.15 c,d 4.63

a See Reference 30. b See Reference 28. c Since ASHTA did not provide data related to annual cost of compliance for mercury-related wastes, the value from 

the literature was used for this element.

d Used in this analysis to develop costs for near future U.S. conversions.
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Table 3--6 presents the estimated annual cost savings from the elimination of mercuryrelated compliance costs for each of the four U.S. facilities using both total environmental 

compliance saving cost factors from Table 3--5. Since the cost data found in the literature were 

based on facilities in Europe and not from actual U.S. facilities, we believe that the annual cost 

savings from the elimination of mercury that is based mostly on the ASHTA cost factors 

represent the best estimate of the cost savings for the remaining U.S. facilities.

3.2.4 Energy Savings and Costs

The membrane cell process requires less energy than the mercury cell process. 

Therefore, there are reduced energy requirements with membrane cells as compared to mercury 

cells. Energy savings were estimated using information from literature and average State energy 

prices.12 Although there could be variations in local energy costs, according to the information 

in the literature, the energy used by the membrane cell technology is approximately 2,500 

kilowatt hours per ton chlorine produced (kWh/ton Cl2), which is about 700 kWh/ton Cl2 less 

than that used by the mercury cell process (3,230 kWh/ton Cl2).12 This equates to an 

approximately 22 percent reduction in energy requirements. Oceana provided information that 

indicated that a 37.5 percent reduction was possible.. Applying a 37.5 percent reduction to the 

mercury cell process energy usage estimate of 3,230 kWhr/ton Cl2 would yield a reduction in 

energy usage of approximately 1,211 kWhr/ton Cl2.

These energy savings are slightly offset by an increase in energy required to concentrate 

the caustic co-product generated in the membrane cell process. Mercury cells produce caustic at 

the market concentration of 50 percent, and membrane cells produce caustic at a 33 percent 

concentration. Therefore, there is an increase in energy use (in the form of steam) due to the 

need to further concentrate the caustic produced with the membrane cell technology..

,

.

,

.

,

.
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Table 3-6. Annual Cost Savings from Elimination of the Mercury Processes, by Facility 

Facility Chlorine Capacity (tpy)

Savings from Hg Elimination ($/yr)

ASHTA Factora Literature Factorb

ASHTAc 47,421 595,386 595,386

Olin GA 119,031 850,634 550,600

Olin TN 262,451 1,875,561 1,214,017

PPG 72,848 520,592 336,970

Totals 3,842,173d 2,696,973

a Using the ASHTA factor of 7.15 $/ton Cl2 presented in Table 3--5. b Using the literature factor of 4.63 $/ton Cl2 presented in Table 3--5. c As discussed above, the ASHTA compliance costs savings include $256,500/yr related to their fugitive emissions

compliance costs (that includes a leak detection and repair element, as well as the installation of a temporary 

canopy for the cell room); whereas, the other facilities do not include these costs because ASHTA was the only 

facility that did not install an instrumental monitoring program to comply with the NESHAP. d Used in this analysis to develop costs for near future U.S. conversions. 

3.2.4 Energy Savings and Costs

The membrane cell process requires less electricity than the mercury cell process. 

Therefore, there are reduced energy requirements with membrane cells as compared to mercury 

cells. Energy cost savings due to reduced electricity usage were estimated using information 

from literature and average State electricity prices.12 Although there could be variations in local 

electricity costs, according to the information in the literature, the electricity used by the 

membrane cell technology is approximately 2,500 kilowatt hours per ton chlorine produced 

(kWh/ton Cl2), which is about 700 kWh/ton Cl2 less than that used by the mercury cell process 

(3,230 kWh/ton Cl2).12 This equates to an approximately 22 percent reduction in electricity 

usage. The total chlorine production capacity of the four mercury cell plants is 500,000 tons per 

year. Using the 700 kWh/ton decrease in electricity usage, the total estimated electricity 

reduction after conversion of the four plants would be around 350 million kWh/year, or 350,000 

Megawatt hours/year.

Oceana provided information that indicated that a 37.5 percent reduction was Applying a 

37.5 percent reduction to the mercury cell process electricity usage estimate of 3,230 kWhr/ton 

Cl2 would yield a reduction in energy usage of approximately 1,211 kWhr/ton Cl2.

These energy cost savings from reduced electricity usage are slightly offset by an 

increase in energy required to concentrate the caustic co-product generated in the 

membrane cell process. Mercury cells produce caustic at the market concentration of 

50 percent, and membrane cells produce caustic at a 33 percent concentration. 
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Therefore, there is an increase in energy use (in the form of steam) due to the need to 

further concentrate the caustic produced with the membrane cell technology.

The energy requirement (in the form of steam) to concentrate the caustic to 50 percent 

was estimated to be 601 kWh/ton Cl2 ($13.6/ton Cl2), as obtained from the average of estimates 

provided for three U.S. facilities..

,

. . This cost was deducted from the energy savings described 

above to develop an estimate of overall energy cost savings with membrane cell technology due 

to reduced energy needs. The energy cost savings are shown in Table 3--7.

Further evaluation of Oceana’s claim of a 37.5 percent energy cost reduction31

.

shows that 

although the estimate is for an actual facility, it is not clear whether steam costs are included. In 

addition, Oceana also indicated in their September 16, 2009, letter that a 25 percent reduction 

was commonplace. Therefore, we believe that the total energy cost savings based on the 

22 percent energyelectricity usage reduction represents the best cost estimate.

In their September 29, 2009, letter,., Oceana stated that the steam cost was an 

overestimate of the required energy needs to concentrate the caustic. Oceana argued that even 

though additional energy is required to generate steam, the steam could be obtained without 

additional expense. According to Oceana, facilities could use byproduct hydrogen as fuel to 

generate the necessary steam.. . While it may be possible to assume that byproduct hydrogen 

could be used to generate the steam required to concentrate caustic from a membrane cell, we 

agree with industry’s claim that increases in the demand for and the value of high purity 

chemical hydrogen make this use of byproduct hydrogen economically impractical. Therefore, 

we have not made adjustments to the energy usage costs (in the form of steam) based on the use 

of byproduct hydrogen as fuel.

Table 3-7. Energy Savings Associated with Conversion from the Mercury Cell to the 

Membrane Cell Process

Facility

Chlorine 

Capacity 

(tpy)

Average 

Industrial 

Retail 

Electricity 

Cost 

(cents/kWh)a

Steam 

Cost

($/yr)b

Annual Energy Savings 

($/yr)

Total Energy Cost Savings 

($/yr)f

22% Energy 

Reductionc,d

37.5% 

Energy 

Reductione

22% 

Energy 

Reductionc,d

37.5% 

Energy 

Reductione

ASHTA 47,421 5.77 644,788 1,911,268 3,313,692 1,266,480 2,668,904

 31 Government of India Bureau of Energy Efficiency. 2006. “The Travancore-Cochin Chemicals Limited.”

December 14. http://www.beeindia.nic.in/sidelinks/EC%20Award/eca06/Award2006_CD/06ChlorAlkali/TheTravancoreCochinChemicalsLimited.pdf . .

Inserted Cells
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Olin GA 119,031 5.48 1,618,476 4,556,346 7,899,639 2,937,870 6,281,163

Olin TN 262,451 5.40 3,568,575 9,901,023 17,166,059 6,332,448 13,597,484

PPG 72,848 3.90 990,515 1,986,964 3,444,931 996,449 2,454,416

Totals 11,533,247 25,001,967

a Average retail price of electricity to ultimate customers by end-use sector, by state (Reference 32

b Steam cost associated with concentrating caustic produced by membrane cells from 33 percent to 50 percent at an 

average cost of $13.60/ton Cl2 (Reference

).

12).

c Calculated using a 22 percent energy savings associated with the conversion, at 699 kWh/ton Cl2. (Reference 12). d Used in this analysis to develop costs for near future U.S. conversions. 

e Calculated using a 37.5 percent energy savings associated with the conversion, at 1,211 kWh/ton Cl2. (Reference .). f Energy Cost Savings = Energy Savings ($/yr) – Steam Cost ($/yr).

 32 U.S. Department of Energy. Average Retail Price of Electricity to Ultimate Customers by End-Use Sector, by 

State for 2006. Available on the Internet at http://www.eia.doe.gov/cneal/electricity/epm/table5_6_b.html.

Accessed February 24, 2009.

Inserted Cells

Inserted Cells

Inserted Cells

Inserted Cells

Inserted Cells
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Table 3-8. Ranges of Individual Annual Cost/Savings Elements for the Conversion of 

Mercury Cells to Membrane Cells

Facility

Capital Recovery Costs 

($/yr)a

Mercury Storage 

Costs ($/yr)b

Environmental 

Compliance Savings 

($/yr)

Energy Savings ($/yr)

7% and 

30 years

7% and 

15 years

EPA 

Factor

DOD 

Factor

ASHTA 

Factorsc

Literature 

Factors

22% Energy 

Reductionc

37.5% 

Energy 

Reduction

ASHTA $2,276,281 $3,101,309 $33,399 $14,035 ($595,386) ($595,386) ($1,266,480) ($2,668,904)

Olin GA $5,713,670 $7,784,567 $83,498 $35,088 ($850,634) ($550,600) ($2,937,870) ($6,281,163)

Olin TN $12,598,059 $17,164,176 $147,513 $61,989 ($1,875,561) ($1,214,017) ($6,332,448) ($13,597,484)

PPG $3,496,792 $4,764,190 $75,148 $31,579 ($520,592) ($336,970) ($996,449) ($2,454,416)

Totals $24,084,802 $32,814,242 $339,558 $142,691 ($3,842,173) ($2,696,973) ($11,533,247) ($25,001,967)

a

 A recovery period of 20 years and 7% was use in the final analysis.

b

 The midpoint of the EPA and DOD factor range was used in the final analysis.

c

 These data were used in the final analysis.

3.2.5 Overall Annual Costs 

For each of the costs and savings elements discussed in the previous sections, there is 

credible information that would result in different estimated levels of costs/savings. For each 

element, this resulted in a high- and low-end estimate. These values are shown in Table 3--8.

For each element, we chose the method of estimation that we believe is the best estimate 

of the cost or savings, as follows:

• For capital recovery costs and mercury storage costs, we concluded that neither 

the high-end nor the low-end of the ranges represented the best estimate of the 

costs that would be incurred. Instead, we concluded that using a 20-year finance 

period provided the best estimate. (See Table 3--3 above.)

• For the mercury storage costs, we determined that the midpoint of the range of 

data from two sources (list) was the best estimate. (See Table 3--4 above.)
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Table 3-8. Ranges of Individual Annual Cost/Savings Elements for the Conversion of 

Mercury Cells to Membrane Cells

Facility

Capital Recovery Costs 

($/yr)a

Mercury Storage 

Costs ($/yr)b

Environmental 

Compliance Savings ($/yr)

Energy Savings 

($/yr)

7% and 30 

years

7% and 15 

years

EPA 

Factor

DOD 

Factor

ASHTA 

Factorsc

Literature 

Factors

22% 

Energy 

Reductionc

37.5% 

Energy 

Reduction

ASHTA $2,276,281 $3,101,309 $33,399 $14,035 ($595,386) ($595,386) ($1,266,480) ($2,668,904)

Olin GA $5,713,670 $7,784,567 $83,498 $35,088 ($850,634) ($550,600) ($2,937,870) ($6,281,163)

Olin TN $12,598,059 $17,164,176 $147,513 $61,989 ($1,875,561) ($1,214,017) ($6,332,448) ($13,597,484)

PPG $3,496,792 $4,764,190 $75,148 $31,579 ($520,592) ($336,970) ($996,449) ($2,454,416)

Totals $24,084,802 $32,814,242 $ 0 $339,558 ($3,842,173) ($2,696,973) ($11,533,247) ($25,001,967)

a A recovery period of 20 years and 7% was use in the final analysis.

b The midpoint of the EPA and DOD factor range was used in the final analysis.

c These data were used in the final analysis.

• For the environmental compliance savings element, we chose the higher estimated 

savings, using the cost factors developed mostly from ASHTA data to provide the 

best estimate for these U.S. facilities. (See Table 3--6 above.)

• For the energy savings, we believe that the lower savings level based on a 

22 percent energyelectricity usage reduction provides the best estimate. (See 

Table 3--7 above.)

Table 3--9 shows the estimates for each facility for each individual cost element 

that incorporate the choices described above, and also shows the total annual costs calculated 

using these estimates for each facility for conversion to non-mercury technology. The values in 

Table 3--9 represent our best estimate of the annual costs that would be incurred due to the 

conversion of the four currently operating mercury cell facilities to membrane cells. These 

annual costs range from less than $1 million per year for ASHTA to almost $7 million per year 

for Olin TN, and a total estimate of $13 million for all four facilities.

3.3 Uncertainty Analysis

While we selected the values that we believe provide the best estimates of the 

costs that would be incurred and savings that would be realized in the conversion from mercury 

cells to membrane cells at these four facilities, there is some uncertainty associated with the 

estimates. While most of the information obtained and provided by commenters appears to be 

credible and representative of actual conversions that have occurred, there is a high amount of 

variability. This is most likely due to the fact that the conditions associated with the potential 
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3-23

conversion of each mercury cell plant are different, resulting in potentially significant 

differences in the costs and savings.
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3-24

Table 3-9. EPA Estimates of the Annual Costs of Conversion of Mercury Cells to 

Membrane Cells

Facility

Capital 

Recovery Costs 

($/yr)a

Annual Costs Total 

Annual Costs

($/yr)

Mercury 

Storage Costs 

($/yr)b

Environmental 

Compliance 

Savings ($/yr)c

Energy Savings 

($/yr)d

ASHTA $2,666,266 $23,717 ($595,386) ($1,266,480) $828,117

Olin GA $6,692,569 $59,293 ($850,634) ($2,937,870) $2,963,358

Olin TN $14,756,431 $104,751 ($1,875,561) ($6,332,448) $6,653,173

PPG $4,095,882 $53,364 ($520,592) ($996,449) $2,632,205

Totals $28,211,147 $25,325,589241

,125

($3,842,173) ($11,533,247) $13,076,853

a Using 20 year finance period with a resulting CRF of 0.0944

b Using midpoint of EPA and DOD factors.

c Using ASHTA factors for air and water compliance costs and a literature value for waste compliance costs not 

provided in ASHTA data.

d Using an estimate of 22 percent energy reduction with membrane process.

Table 3-10. Results of the Monte Carlo Simulation Compared to the EPA Estimates

Facility

EPA Estimate 

Total Annual Costs 

($/yr)

Monte Carlo Simulation Mean

Total Annual Costs 

($/yr)

ASHTA $828,117 $736,743

Olin GA $2,963,358 $2,821,114

Olin TN $6,653,173 $6,349,942

PPG $2,632,205 $2,608,708

Totals $13,076,853 $12,516,508
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In order to consider the uncertainties, we conducted a simple Monte Carlo 

simulation.33

Table 3-10. Results of the Monte Carlo Simulation Compared to the EPA Estimates

For this simulation, we assumed a normal distribution for each variable. We set 

the peak of the distribution at our best estimate. For the elements where we believe one end of 

the range provides the best estimate (i.e., the environmental compliance savings and the energy 

savings), we truncated the distribution so that the peak of the distribution curve was at the best 

estimate. We ran the simulation with 100,000 calculations to create distributions of the 

individual plant annual costs over all annual costs. The results are shown in Table 3--10. As 

can be seen, the results of this analysis are very close to our best estimated costs. This shows 

that collectively, considering the ranges of each parameter/input to the annual costs, a mean 

value is obtained from the simulation that is only slightly lower (4 percent) than our estimate. 

Attachment 1 contains the report of this simulation.

Facility

EPA Estimate

Total Annual Costs

($/yr)

Monte Carlo Simulation Mean

Total Annual Costs

($/yr)

ASHTA $828,117 $736,743

Olin GA $2,963,358 $2,821,114

Olin TN $6,653,173 $6,349,942

PPG $2,632,205 $2,608,708

Totals $13,076,853 $12,516,508

3.4 Summary of Results 

This memorandumFor Option 1 (Non-mercury Technology Option), this section

provided estimated costs for the conversion of the four currently operating mercury cell chloralkali facilities to membrane cells. The EPA estimate of the total capital cost for this conversion 

is slightly under $300 million, with the EPA estimate of total annual costs at approximately $13 

million. Per facility estimated costs range from a low of $828,117 (ASHTA) to $6,653,173 (Olin 

TN).

 33 Monte Carlo simulation is a computerized mathematical technique that is used to account for uncertainty in 

quantitative analyses and is often used in decision making and risk analysis. The simulation technique builds 

models of possible results by substituting a range of values –often a probability distribution—for any factor that 

has inherent uncertainty, and then recalculates the results numerous times, each time using a different set of 

random values from the probability functions. The results of Monte Carlo analyses are distributions of possible 

outcome values.
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3-1

SECTION 4:

For Option 2 (Enhanced Work Practice Standards Option), only the ASHTA facility 

incurs costs. These costs are estimated to be $120 thousand in capital costs and $25 thousand in 

total annualized costs.
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SECTION 4

ECONOMIC IMPACT ANALYSIS (EIA)

EPA prepares an EIA to provide information about a new environmental policy’s 

unfavorable effects (i.e., social costs) and how these costs are distributed among stakeholders 

(EPA, 2000).). Although several tools are available to estimate the economic costs of direct 

performance standards, the proposed regulation is unique in that it bans emissions of mercury 

from the mercury cell process within 2 years from final promulgation and bans operation of 

mercury recovery units 3 years from final promulgation. EPA’s Guidelines note that this type of 

regulation can be more difficult to assess when compared with traditional direct performance 

standards because it is hard to predict how stakeholders will respond (EPA, 2000).). Bans may 

lead to shutdowns that will involve adjustment costs for people working at the affected plants. 

Affected plants may also have strong links with other firms or downstream markets; as a result, 

secondary consequences of the regulation become more important to consider.

4.1 Conversion Versus Plant Closure

The facilities currently in operation that do not already have plans to convert or close 

would have to convert to one of the non-mercury technologies, such as membrane cells. As a 

result, the owners of a plant have to make an investment decision that compares the costs of 

conversion with future benefits of the conversion. Although there is historical evidence that 

owners have converted from mercury technologies in Europe and United States, other mercury 

plant owners have, to date, concluded the investment decision was currently not in their 

company’s interest given their assessment of future economic conditions (U.S. House of 

Representatives Committee on Commerce and Energy, 2009; PPG, 2009). ; PPG, 2009). The 

extremely concentrated markets (few suppliers) for some chlor-alkali products may provide 

manufacturers with an ability to pass on cost increases. ASHTA is one of only three producers of 

liquid potcarb and domestic entry is very difficult.

Although EPA does not have quantitative data to evaluate investment decisions (e.g., 

using capital budgeting techniques), the economics literature has emphasized three 

characteristics that influence the owner’s best investment decision (Dixit and Pyndick, 2004):):

 Uncertainty: the future rewards of an investment are unknown

 Irreversibility: the resources used to make the investment typically cannot be 

undone
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4-4-2

 Timing: owners who delay investment get more information that they value; as a 

result, there is an “opportunity cost” associated with making an investment 

decision now versus later

Supply and demand conditions in the chlor-alkali product markets are highly variable; 

chlor-alkali product prices regularly spike and fall during short periods (see Figure 4--1). Olin 

Corporation reports that the average product price for chlorine-caustic soda co product 

(electrochemical unit or ECU) dropped from approximately $1,300 per short ton to just under 

$600 per short ton in the first 6 months of 2009 (Olin Corporation, 2009). ). Figure 4.1 (below) 

shows that the long term price trend for chlor alkali products shows that prices have more than 

doubled since 2004, even when considering the recent price decreases.
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4-4-3

Figure 4-1. Price Trends: Alkalis and Chlorine Manufacturing: 2000 to 2009

Source: U.S. Bureau of Labor Statistics. 2009a. Producer Price Index Industry Data, Series ID = PCU 

PCU325181325181. http://data.bls.gov/PDQ/outside.jsp?survey=pc. Accessed August 18, 2009..

The sharp price changes highlight the risks associated with chlor-alkali capital 

investments. For example, OxyChem completed an announced $60 million investment at its 

membrane chlor-alkali plant in Taft, Louisiana, to produce KOH instead of caustic potash 

0

50

100

150

200

250

300

350

400

450

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

PPI Alkalies and chlorine manufacturing 

(1980_12= 100) 

0

50

100

150

200

250

300

350

400

450

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

PPI Alkalies and chlorine manufacturing 

(1980_12= 100) 
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4-4-4

(Access Intelligence, LLC, 2008).). Almost a year later, an announcement suggests the plant has 

idled because of unstable market conditions (Access Intelligence, LLC, 2009).).

Given the current market conditions, the benefits of delaying investment and waiting for 

new information are likely large if plants can delay conversion decisions. However, if plants 

delay, they risk other manufacturers entering the market before them and losing profits and 

market share. If for example, there are industrial consumers of chlorine nearby, it is unlikely that 

chlorine manufacturers will not meet that demand. And it appears to be cost-effective to 

produce chlor alkali products close to large industrial consumers. Firms would like to require 

rates of return that exceed the cost of capital to make new capital investments now. As reported 

above, prices for large industrial consumers of these facilities’ products could be sufficient to 

justify the investment in conversion

To our knowledge, the only existing economics literature that examines regulationinduced plant closures in the chlor-alkali industry is a study by Snyder and colleagues (2003).).

Environmental regulations affecting chlorine end-use markets have reduced the demand for 

chlorine and help explain the exit of selected chlorine plants (Snyder, Miller, and Stavins, 

2003).). For example, chlorine plants that were co-located with pulp and paper mills and plants 

affected by the Montreal Protocol were more likely to shutdown (11 to 15% higher than the 

average chlorine plant) (Snyder, Miller, and Stavins, 2003). ). In our case, the demand for 

chlorine and other products is not changing with the regulation. In contrast, regulatory factors 

did not appear to influence the decision to adopt membrane technologies at existing plants. EPA 

does not have sufficient data to predict whether individual companies would choose to convert or 

close, historical responses suggest that plant closure may be an option considered by some of 

these facilities. Of the last four plants to stop using this process, two converted and two closed.

4.2 Market Concentration and Pricing Behavior

Of the three major chlor-alkali products discussed in Section 2, the market for potassium 

hydroxide is the most highly concentrated. As of 2005, there were only four producers of 

potassium hydroxide in the United States (FTC, 2005b).). Approximately 50% is produced using 

mercury cells; ASHTA Chemicals, Inc. reports a market share of approximately 15% (U.S. 

House of Representatives Committee on Commerce and Energy, 2009).). Producers of potassium 

hydroxide may have more ability to pass on costs of conversion than producers of other chloralkali products. Any closure of one or more mercury cell plants could raise concerns about 

competitiveness and subsequent firm pricing behavior in the KOH market; the remaining 

companies could have more scope to influence market prices by altering production levels. 
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Given the small number of remaining KOH producers, removing an extra ton of KOH from the 

market may raise the market price and increase the profits on all the other KOH sold. If the price 

effect is large enough, the remaining companies may find it is more profitable to reduce 

production levels below the levels that they would be choose in a market with a large number of 

competitors. 

EPA’s review of publicly available sources also suggests that any closure would have 

similar market concentration consequences for a downstream commodity: potassium carbonate. 

ASHTA is one of only three producers of liquid potcarb and domestic entry is very difficult 

because it is very expensive; foreign entry (i.e., imports) has historically been limited (FTC, 

2009b).). In the absence of other market condition changes if ASHTA’s were to close, it would 

likely reduce competition and lead to higher prices in the liquid potcarb market. Although EPA 

does not have data to quantify the effect of higher potassium carbonate prices, we recognize that 

end users of potassium carbonate (e.g., specialty glasses including television tubes and the 

ceramics industry [Armond Products Company, 2009;; ERCO Worldwide, 2009])]) and the 

consumers of these goods could indirectly be affected by a price increase.34

4.3 Impact on Employment

Industry sources 

already suggest that high energy costs and reduced domestic demand in the video glass industry 

has contributed potassium carbonate industry decline although there is some evidence that other 

“niche” end users are emerging (Hoffmann, 2004).).

EPA does not have enough information to estimate whether individual plants will 

convert or close and therefore no estimate of changes in employment are provided. In the 

following section we provide information on each plants’ job contributions relative to the size of 

local labor markets and current and historical conditions. In Table 4-1, we use the latest 

monthly statistics about county labor forces and show the relative contributions of each plant in 

the context of current labor market conditions. In Figure 4-2, we compare the historical 

unemployment rates in the United States with unemployment rates for the counties where 

mercury cells are located. As shown in Figure 4-3, annual unemployment rates for three 

counties (Ashtabula, Richmond, and Wetzel) diverge and become higher than the national 

 34 Companies using potassium products may also be concerned about other events that tend to increase the cost of 

potassium products (e.g., recent increases in the input costs of potash used to make potassium hydroxide). For 

example, Superior Plus (2008)) notes that a current contract to purchase potash on favorable terms expired in 

2009, and production costs are likely to rise once potash is purchased at current (higher) market prices. Superior 

plus owns ERCO Worldwide, one of the four companies that compete in the U.S. potassium hydroxide market.
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4-4-6

average beginning in 2004. Recent data for the month of May 2009 also suggest the relative 

difference between Ashtabula County and the United States is higher than historical differences.

Table 4-1. May 2009 County Employment Data (Not Seasonally Adjusted)

Plant Location

Plant 

Employees

County Persons 

Employed

Plant Share of 

Persons Employed

County Persons 

Unemployed

ASHTA Ashtabula County, OH 100 42,481 0.2% 6,526

Olin Richmond County, GA 85 82,416 0.1% 8,634

Olin Bradley County, TN 280 42,132 0.7% 4,397

PPG Wetzel County, WV 540 5,663 9.5% 731

Source: U.S. Bureau of Labor Statistics. 2009b. LAU Local Area Unemployment Statistics Series Id: 

LAUPS39011004, LAUPS39011005, LAUPA47035004, LAUPA47035005, LAUCN13245004, 

LAUCN13245005, LAUCN54103004, LAUCN54103005. Accessed August 2009. Accessed August 2009.
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Figure 4-2. Unemployment Rates by County: 2000–2008

Sources: U.S. Bureau of Labor Statistics. 2009c. LAU Local Area Unemployment Statistics Series Id: 

LAUPS39011006, LAUPA47035006, LAUCN13245006, and LAUCN54103006. Accessed August 2009.

Accessed August 2009.

U.S. Bureau of Labor Statistics. 2009d. Current Employment Statistics—CES (National) Series Id: 

LNU04000000. Accessed August 2009. Accessed August 2009.
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-0.5

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

Ashtabula Bradley Richmond Wetzel

Unemployment Rate Difference From National Average

County

May 2009 Historical Average (2000–2008)

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

Ashtabula Bradley Richmond Wetzel

Unemployment Rate Difference From National Average

County

May 2009 Historical Average (2000–2008)
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4-4-10

Figure 4-3. Unemployment Rate Differences from National Average: May 2009 and 

Historical Average: 2000–2008

Source: U.S. Bureau of Labor Statistics. 2009c. LAU Local Area Unemployment Statistics Series Id: 

LAUPS39011006, LAUPA47035006, LAUCN13245006, and LAUCN54103006. Accessed August 2009..

4.4 Transportation Issues Associated with Plant Closure

If one or more mercury cell plants were to close, customers with existing arrangements 

with the plants will have to identify another outside supply source to maintain chemical 

production. For example, ASHTA’s production facility sells 100% of its chlorine to an adjacent 

titanium dioxide plant (U.S. House of Representatives Committee on Commerce and Energy, 

2009).). Although other chlorine supply sources may be available, transportation will likely be 

more expensive because of increased shipping distances between the supply source and its 

destination. Depending on the mode of transportation selected, this may also indirectly increase 

the volume of existing shipments passing through certain urban areas.

4.5 Small Entity Impact Analysis

The Regulatory Flexibility Act (RFA) generally requires an agency to prepare a 

regulatory flexibility analysis of any rule subject to notice and comment rulemaking 

requirements under the Administrative Procedure Act or any other statute unless the agency 

certifies that the rule will not have a significant economic impact on a substantial number of 

small entities (SISNOSE). The first step in this assessment was to determine whether the rule 

will have SISNOSE. To make this determination, EPA used an impact analysis to indicate 

whether EPA can certify the rule as not having a SISNOSE. The elements of this analysis 

included

 identifying affected small entities,

 selecting and describing the measures and economic impact thresholds used in the 

analysis, and

 completing the assessment and determining the SISNOSE certification category.

4.5.1 Identify Affected Small Entities

For the purposes of assessing the impacts of the proposed rule on small entities, a small 

entity is defined as (1) a small business as defined by the Small Business Administration’s 

regulations at 13 CFR 121.201; according to these size standards, ultimate parent companies 

owning mercury cell chlor-alkali facilities are categorized as small if the total number of 

employees at the ultimate parent company is fewer than 500; otherwise, the ultimate parent 
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4-4-11

company is classified as large. As discussed in the previous section, ASHTA, Inc. is the sole 

entity that meets these qualifications. 

4.5.2 Sales Test Analysis

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

parent companies by comparing annual conversion costs to total sales (i.e., a “sales” test). To do 

this, we divided an ultimate parent company’s total annualized compliance costs by its reported 

revenue:

j

n

i

TR

TACC

CSR

∑

= (4.1)

where 

CSR = cost-to-sales ratio

TACC = total annualized compliance costs

TRj = total sales from all operations of ultimate parent company j or annual 

government revenue

This method assumes the affected entity cannot shift pollution control costs to consumers 

(in the form of higher market prices). Instead, the owning entity experiences a one-for-one 

reduction in profits. For Option 1, EPA estimates that ASHTA’s CSR would range from 1 to 2%, 

which suggests a significant economic impact. For Option 2, EPA estimates that ASHTA’s CSR 

would be less than 0.1%. The other three plants are owned by large ultimate parent companies 

with significant company-wide sales. As a result, the CSRs for the large companies are below 

1%. However, when plant-only sales are considered, the CSRs for plants owned by large 

ultimate parent companies range from 4 to 9%.

4.5.3 Profit Test Analysis

Economic models assume that a chlor-alkali company acts in the best interest of its 

shareholders and tries to make the company’s profit (total revenue minus total costs) as large as 

possible. To measure of chlor-alkali profits, EPA used trade publication data for a representative 

ECU called the “cash margin” (CMAI, 2008). The measure approximates the average profit per 

metric ton of chlor-alkali product made. As shown in Figure 4-4, historical data suggest that 

cash margins can fluctuate over time. Assuming the market prices for chlor-alkali products do 

not change as a result of the proposed rule, the annual conversion costs ($/metric ton) associated 
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4-4-12

with the proposed rule will reduce the average profit for chlor-alkali products. To assess the size 

of this effect, EPA compared the conversion costs with economic data for a typical year (using 

historical industry ECU margins and capacity utilization rates from 1991 to 2005)

35. ).36

4.6 Conclusions

As 

shown, conversion costs could reduce the margins by 10 to 20% (Figure 4-5). EPA also 

considered data in weak and strong margin years; as shown, margin reductions range from 5 to 

100% for these years. As a result, the analysis confirms the results associated with the sales test; 

plant conversion costs will likely have an economically significant effect.

The EIA suggests theseOption 1 requirements are likely to have significant economic 

costs. Plants will either convert or close. Predicting whether, no plant, one plant, two plants, 

three plants, or all four plants will close or convert is not possible with the available data.

 35 For a typical year, we used the observed average industry ECU cash margin (2008 dollars) and average industry 

utilization rate between 1991 and 2005. For weak and strong years, we considered cash margins and industry 

utilization rates one standard deviation (lower and higher) from the average. 36 For a typical year, we used the observed average industry ECU cash margin (2008 dollars) and average industry 

utilization rate between 1991 and 2005. For weak and strong years, we considered cash margins and industry 

utilization rates one standard deviation (lower and higher) from the average.
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$232

$0

$366

$225

$0

$132

$173

$456

$0

$50

$100

$150

$200

$250

$300

$350

$400

$450

$500

1990 1992 1994 1996 1998 2000 2002 2004 2006

ECU margin

Year

$/metric ton, 2008$

$/metric ton
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4-4-14

Figure 4-4. Historical ECU Cash Margins

Source: EPA estimates using data from CMAI (2008).

Closure of one or more mercury cell process plants also raises concerns about 

competitiveness and subsequent pricing behavior in the potassium hydroxide and potassium 

carbonate markets. In highly concentrated markets with few producers, nonmercury cell 

producers may be able to influence market prices above competitive levels by altering 

production decisions. Similar competitive issues have also been raised in other regulatory 

contexts.

The small business impact analysis shows that one of the four plants is owned by a small 

business. A sales test suggests this small company will be significantly affected (CSR would 

range from 1 to 2%).% for Option 1). EPA also considered profitability effects by comparing 

annual conversion costs to reported industry margins for a representative ECU. Even in 

optimistic scenarios where ECU margins are higher than historical averages, conversion costs 

could significantly reduce the margins.

$232

$0

$366

$225

$0

$132

$173

$456

$0

$50

$100

$150

$200

$250

$300

$350

$400

$450

$500

1990 1992 1994 1996 1998 2000 2002 2004 2006

ECU margin

Year

$/metric ton, 2008$

$/metric ton
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4-4-15

-10%

-14% -14%

-20%

-53%

-75% -77%

-100%

-5% -7% -7% -10%

-100%

-95%

-90%

-85%

-80%

-75%

-70%

-65%

-60%

-55%

-50%

-45%

-40%

-35%

-30%

-25%

-20%

-15%

-10%

-5%

0%

Ashta Olin GA Olin TN PPG

Small Business Large Businesses

Annualized Conversion Costs as a Share of ECU Cash Margin

Typical Year Weak Year Strong Year
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4-4-16

Figure 4-5. Profit Tests: ECU Cash Margin Reductions Associated with Conversion 

Costs

-10%

-14% -14%

-20%

-53%

-75% -77%

-100%

-5% -7% -7% -10%

-100%

-95%

-90%

-85%

-80%

-75%

-70%

-65%

-60%

-55%

-50%

-45%

-40%

-35%

-30%

-25%

-20%

-15%

-10%

-5%

0%

Ashta Olin GA Olin TN PPG

Small Business Large Businesses

Annualized Conversion Costs as a Share of ECU Cash Margin

Typical Year Weak Year Strong Year
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4-17

4.7 References

Access Intelligence, LLC. 2008. “Oxychem Completes Taft, LA KOH Conversion.” 

ChemWeek’s Business Daily, April 29, 2008.

Access Intelligence, LLC. June 16, 2009. Chlor-alkali Market Wire.

American Chemistry Council. 2000. “Chlorine: Ensuring Rail Transportation Safety.” 

http://www.americanchemistry.com/s_acc/sec_article_acc.asp?CID=1695&DID=10018. 

Accessed August 19, 2009.

Armand Products Company. 2009. “Potassium Carbonate Handbook.” 

http://www.armandproducts.com/pdfs/k2so3P1_12.pdf. Accessed August 2009.

ASHTA Chemicals Inc. 2009a. About ASHTA. http://www.ashtachemicals.com/aboutfs.htm. 

Accessed August 2009.

ASHTA Chemicals, Inc. 2009b. Potassium Hydroxide, Liquid.

http://www.ashtachemicals.com/products/lkohfs.htm. Accessed August 2009.

Cleveland/Bradley Chamber of Commerce, Economic Development Council. 2009. 2009 

Industrial Directory. http://clevelandchamber.com/images/stories/pdf/2009inddir.pdf. 

Accessed August 7, 2009.

Dixit, A.K., and R.S. Pindyck. 1994. Investment under Uncertainty. Princeton University Press: 

Princeton, NJ.

Energy Information Administration. 2009. “Electric Power Annual 2007: State Data Tables.” 

http://www.eia.doe.gov/cneaf/electricity/epa/epa_sprdshts.html. Accessed July 31, 2009.

Environmental News Service. January 10, 2005. “Chlorine Gas from South Carolina Train Crash 

Kills Nine.” http://www.ens-newswire.com/ens/jan2005/2005-01-10-04.asp. Accessed 

18, 2009.

ERCO Worldwide. 2009. “Potassium Hydroxide.” http://www.ercoworldwide.com/

products_potassiumhydroxide.asp. Accessed August 2009.

Fullerton, D. 2008. Distributional Effects of Environmental and Energy Policy: An Introduction. 

Cambridge, MA: National Bureau of Economic Research. 

Hoffmann, J. April 19, 2004. “Potassium Carbonate Faces Pressures from the Video Glass.” 

Chemical Market Reporter, p. 15.

Millennium Inorganic Chemicals. 2009. “Site Fact Sheet Ashtabula Complex.” 

http://www.millenniumchem.com/NR/rdonlyres/6AE8BF59-D7CD-4768-951F37AE6F1C7321/0/SiteFactSheetAshtabula.pdf. Accessed August 2009.
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4-18

Occidental Chemical Corporation. 2008a. “OxyChem Caustic Potash Handbook.” 

http://www.oxy.com/Our_Businesses/chemicals/Pages/chem_products_basic_alkali.aspx

#alk_koh. Accessed July 28, 2009.

Occidental Chemical Corporation. 2008b. “OxyChem Caustic Soda Handbook.” 

http://www.oxy.com/Our_Businesses/chemicals/Documents/caustic_soda/caustic.pdf. 

Accessed August 6, 2009.

Olin Corporation. December 31, 2001. Form 10-K405. Filed March 4, 2002. http://b2i.api.edgaronline.com/EFX_dll/EdgarPro.dll?FetchFilingConvPDF1?SessionID=n9ZFWjsyBGA3E

-9&ID=1782286. Accessed August 2009.

Olin Corporation. December 31, 2008. Form 10-K. Filed February 25, 2009. http://b2i.api.edgaronline.com/EFX_dll/EdgarPro.dll?FetchFilingConvPDF1?SessionID=DOVFWfuqOuZB

E-9&ID=6436012. Accessed July 2009.

Olin Corporation. April 1, 2009a. “BB&T Capital Markets Presentation Manufacturing and 

Materials Conference.” http://www.olin.com/. Accessed July 31, 2009. 

Olin Corporation. 2009b. “Olin Transportation of KOH.” 

http://koh.olinchloralkali.com/Facilities/chas/ChasLogistics.aspx. Accessed August 2009.

Pavey, R. 2008. “Bill Would End Mercury Use at Chlorine Plants.” 

http://chronicle.augusta.com/stories/031308/met_190792.shtml. Accessed August 7, 

2009.

PPG Industries, Inc. December 31, 2001. Form 10-K. Filed February 22, 2002. 

http://www.secinfo.com/dV5Ff.32Wq.7.htm#25thPage. Accessed August 2009.

PPG Industries, Inc. December 31, 2008. Form 10-K. Filed February 19, 2009. 

http://corporateportal.ppg.com/NR/rdonlyres/EAC49DFC-DB9C-4320-B9A3-

421E40162220/0/10KYREND2008.pdf. Accessed July 2009.

PPG Industries. 2009a. “Chlorine Product Bulletin.” 

http://corporateportal.ppg.com/NA/Chemicals/CAD/ProductInformation/Bull

/English/EN. Accessed August 19, 2009.

PPG Industries. August 11, 2009b. “PPG Reaches Agreement with State of Maryland.” PPG 

News Release. http://corporateportal.ppg.com/PPG/Newsroom/News/20090811.htm. 

Accessed August 2009.

Sim, P.W. January 19, 2005. “ASHTA to Build Chlorine-KOH Plant in Arkansas.” Chemical 

Week p. 13.

Snyder, L.D., N.H. Miller, and R.N. Stavins. 2003. “The Effects of Environmental Regulation on 

Technology Diffusion: The Case of Chlorine Manufacturing.” American Economic 

Review 93(2):431-435. 
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4-19

“Special Focus on Chlorine.” October 2007. Chemical Business. pp. 27-40. Business Source 

Corporate database. Accessed July 29, 2009.

Superior Plus. 2009. Annual Report 2008. http://www.olin.com/. Accessed August 2009.

The Innovation Group (TIG). 2009. “Caustic Potash Chemical Profile.” http://www.theinnovation-group.com/welcome.htm. Accessed July 2009.

U.S. Bureau of Labor Statistics. 2009a. Current Employment Statistics—CES (National) Series 

Id: LNU04000000. Accessed August 2009.

U.S. Bureau of Labor Statistics. 2009b. LAU Local Area Unemployment Statistics Series Id: 

LAUPS39011004, LAUPS39011005, LAUPA47035004, LAUPA47035005, 

LAUCN13245004, LAUCN13245005, LAUCN54103004, LAUCN54103005. Accessed 

August 2009.

U.S. Bureau of Labor Statistics. 2009c. LAU Local Area Unemployment Statistics Series Id: 

LAUPS39011006, LAUPA47035006, LAUCN13245006, and LAUCN54103006. 

Accessed August 2009.

U.S. Bureau of Labor Statistics. 2009d. Producer Price Index Industry Data, Series ID = PCU 

PCU325181325181. http://data.bls.gov/PDQ/outside.jsp?survey=pc. Accessed August 

18, 2009.

U.S. Bureau of Labor Statistics. 2009e. Quarterly Census of Employment and Wages. Accessed 

August 2009.

U.S. Census Bureau. 2001–2006. Quarterly Financial Report for Manufacturing, Mining, and 

Trade Corporations, 1st Quarter reports. http://www.census.gov/prod/www/abs/qfrmm.html. Accessed July 2009.

U.S. Census Bureau. Economic Census. 2007. Sector 31: EC0731I1: Manufacturing: Industry 

Series: Detailed Statistics by Industry for the United States: 2007. NAICS code 325181. 

http://factfinder.census.gov/servlet/DatasetMainPageServlet?_program=ECN&_tabId=E

CN1&_submenuId=datasets_4&_lang=en&_ts=24636668839. Accessed July 23, 2009.

U.S. Census Bureau; generated by RTI International; using American FactFinder; “Sector 31: 

Manufacturing: Industry Series: Industry Statistics by Employment Size: 2002.” 

http://factfinder.census.gov. Accessed July 2009.

U.S. Department of Transportation. 2009a. “Part 172—Hazardous Materials Table, Special 

Provisions, Hazardous Materials Communications, Emergency Response Information, 

Training Requirements, And Security Plans.” http://ecfr.gpoaccess.gov/cgi/t/text/textidx?c=ecfr&sid=1dbcd9fcab84b206ffd37360976a4c4f&tpl=/ecfrbrowse/Title49/49cfr17

2_main_02.tpl. Accessed August 2009.

U.S. Department of Transportation. 2009b. Pipeline and Hazardous Materials Safety 

Administration. http://www.phmsa.dot.gov/regulations. Accessed August 2009. 
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4-20

U.S. Environmental Protection Agency (EPA). September 2000. Guidelines for Preparing 

Economic Analyses. EPA 240-R-00-003. Washington, DC: EPA. 

http://yosemite.epa.gov/ee/epa/eed.nsf/webpages/Guidelines.html.

U.S. Federal Trade Commission (FTC). 2005. “With Conditions, FTC Clears Occidental 

Chemical’s Purchase of Vulcan’s Chemical Assets.” 

http://www.ftc.gov/opa/2005/06/vulcan.shtm. Accessed August 7, 2009.

U.S. Geological Survey (USGS). 2009. Soda Ash. http://minerals.usgs.gov/minerals/pubs/

commodity/soda_ash/mcs-2009-sodaa.pdf. Accessed August 4, 2009.

U.S. House of Representatives Committee on Commerce and Energy, Subcommittee on 

Commerce, Trade, and Consumer Protection; Pertaining to the Mercury Pollution 

Reduction Act of 2009 (H. R. 2190), Testimony of Richard Jackson, Executive Vice 

President of Operations, ASHTA Chemicals Inc., May 12, 2009. 

http://energycommerce.house.gov/Press_111/20090512/testimony_jackson.pdf. Accessed 

August 2009.

Ward, K. Jr. 2007. “Report Cites PPG Savings on Mercury Process Could Boost Efficiency, 

Phase Out Toxic Discharge at Marshall Plant.” 

http://www.wvrivers.org/news2007/CharlestonGazette-Oceana.pdf. Accessed August, 

2009.

West Virginia Development Office. 2009. PPG Industries Invests Nearly $6 million in Marshall 

County Plant.” http://www.wvopenforbusiness.com/OFB_0609/index.aspx#PPG. 

Accessed August 7, 2009.

World Chlorine Council. April 2002. “Chlor-Alkali Manufacturing Processes.” The World 

Chlorine Council. http://www.worldchlorine.com/publications/pdf/mfg_processes.pdf. 

Accessed July 27, 2009.
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4-1

SECTION 5
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5-1

SECTION 5

HUMAN HEALTH BENEFITS OF EMISSIONS REDUCTIONS

5.1 Synopsis

In this section, we provide analysis of the benefits associated with the proposed Mercury 

Chlor Alkali NESHAP. As there are no emission reductions or energy impacts associated with 

Option 2 (enhanced work practice standards), the benefits in this chapter correspond to Option 1 

(non-mercury technology option). The primary benefit of this regulation is the reduction of 

mercury emissions from these sources. Due to data, time, and resource limitations, we were 

unable to model mercury dispersion, deposition, methylation, bioaccumulation in fish tissue, and 

human consumption of mercury-contaminated fish that would be needed in order to estimate the 

human health benefits from reducing mercury emissions. In addition, this regulation would 

reduce electricity demand at these sources. Using benefit-per-ton estimates, we estimate the 

monetized human health co-benefits of reducing cases of morbidity and premature mortality 

among populations exposed to particulate matter (PM) associated with the decreased electricity 

usage. Using the social cost of carbon (SCC), we estimate the monetized benefits associated with 

reduced CO2 emissions. At a 3% discount rate, we estimate the total monetized co-benefits of 

the proposed NESHAP to be $8722 million to $20043 million in the implementation year (2013). 

At a 7% discount rate, we estimate the total monetized co-benefits of the proposed NESHAP to 

be $7314 million to $18033 million in 2013. All estimates are in 2007$. These estimates reflect 

EPA’s most current interpretation of the scientific literature. Higher or lower estimates of PM2.5 

co-benefits are possible using other assumptions; examples of this are provided in Figure 5-2. 

and Table 5-6. Data, resource, and methodological limitations prevented EPA from monetizing 

the co-benefits from several important benefit categories, including benefits from reducing 

ecosystem effects and visibility impairment. It is important to emphasize that these monetized 

co-benefits do not include the benefits associated with reducing mercury emissions.

5.2 Mercury Benefits

Mercury is a highly neurotoxic contaminant that enters the food web as a methylated 

compound, methylmercury. (U.S. EPA, 2008c). The contaminant is concentrated in higher 

trophic levels, including fish eaten by humans. Mercury is emitted to the air from various manmade and natural sources. These emissions transport through the atmosphere and eventually 

deposit to land or water bodies. This deposition can occur locally, regionally, or globally, 

depending on the form of mercury emitted and other factors such as the weather. The form of 

mercury emitted from these sources is estimated to be about 98 percent elemental and two 

percent divalent mercury. Gaseous elemental mercury can be transported very long distances, 
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5-2

even globally, to regions far from the emissions source (becoming part of the global “pool”) 

before deposition occurs. Inorganic ionic (divalent) mercury has a shorter atmospheric lifetime 

and can deposit to land or water bodies closer to the emissions source. Furthermore, elemental 

mercury in the atmosphere can undergo transformation into ionic mercury, providing a 

significant pathway for deposition of emitted elemental mercury.

This source category emitted about 640 pounds of mercury in the air in 2008 in the U.S. 

Based on the EPA’s National Emission Inventory, about 103 tons of mercury were emitted from 

all anthropogenic sources in the U.S. in 2005. Moreover, the United Nations has estimated that 

about 2,100 tons of mercury were emitted worldwide by anthropogenic sources in 2005. We 

believe that total mercury emissions in the U.S. and globally in 2008 were about the same 

magnitude in 2005. Therefore, we estimate that in 2008, these sources emitted about 0.3% of the 

total anthropogenic mercury emissions in the U.S. and about 0.02% of the global emissions. 

Overall, this rule would directly reduce mercury emissions by about 640 pounds per year from 

current levels as well as an estimated 16 pounds per year indirectly through reduced electricity 

consumptiongeneration, and therefore, contribute to reductions in mercury exposures and health 

effects. Due to data, time, and resource limitations, we were unable to model mercury dispersion, 

deposition, methylation, bioaccumulation in fish tissue, and human consumption of mercurycontaminated fish that would be needed in order to estimate the human health benefits from 

reducing mercury emissions. 

Potential exposure routes to mercury emissions include both direct inhalation and 

consumption of fish containing methylmercury. In the U.S., the primary route of human 

exposure to mercury emissions from industrial sources is generally indirectly through the 

consumption of fish containing methylmercury. As described above, mercury that has been 

emitted to the air eventually settles into water bodies or onto land where it can either move 

directly or be leached into waterbodies. Once deposited, certain microorganisms can change it 

into methylmercury, a highly toxic form that builds up in fish, shellfish and animals that eat fish. 

Consumption of fish and shellfish are the main sources of methylmercury exposure to humans. 

Methylmercury builds up more in some types of fish and shellfish than in others. The levels of 

methylmercury in fish and shellfish vary widely depending on what they eat, how long they live, 

and how high they are in the food chain. Most fish, including ocean species and local freshwater 

fish, contain some methylmercury. For example, in recent studies by EPA and the U.S. 

Geological Survey (USGS) of fish tissues, every fish samplesampled from 291 streams across 

the country contained some methylmercury. (Scudder, 2009).
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The majority of fish consumed in the U.S. are ocean species. The methylmercury

concentrations in ocean fish species are primarily influenced by the global mercury pool. 

However, the methylmercury found in local fish can be due, at least partly, to mercury emissions 

from local sources. Research shows that most people’s fish consumption does not cause a 

mercury-related health concern. However, certain people may be at higher risk because of their 

routinely high consumption of fish (e.g., tribal and other subsistence fishers and their families 

who rely heavily on fish for a substantial part of their diet). It has been demonstrated that high 

levels of methylmercury in the bloodstream of unborn babies and young children may harm the 

developing nervous system, making the child less able to think and learn. Moreover, mercury 

exposure at high levels can harm the brain, heart, kidneys, lungs, and immune system of people 

of all ages. 

Several studies suggest that the methylmercury content of fish may reduce these cardioprotective effects of fish consumption. Some of these studies also suggest that methylmercury 

may cause adverse effects to the cardiovascular system. For example, the NRC (2000) review of 

the literature concerning methylmercury health effects took note of two epidemiological studies 

that found an association between dietary exposure to methylmercury and adverse cardiovascular 

effects.37 Moreover, in a study of 1,833 males in Finland aged 42 to 60 years, Solonen et al. 

(1995) observed a relationship between methylmercury exposure via fish consumption and acute 

myocardial infarction (AMI or heart attacks), coronary heart disease, cardiovascular disease, and 

all-cause mortality.38 The NRC also noted a study of 917 seven year old children in the Faroe 

Islands, whose initial exposure to methylmercury was in utero although post natal exposures may 

have occurred as well. At seven years of age, these children exhibited an increase in blood 

pressure and a decrease in heart rate variability.39 Based on these and other studies, NRC 

concluded in 2000 that, while “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 

methylmercury toxicity.”40

 37 National Research Council (NRC). 2000. Toxicological Effects of Methylmercury. Committee on the 

Toxicological Effects of Methylmercury, Board on Environmental Studies and Toxicology. National Academies 

Press. Washington, DC. pp. 168-173. 38 Salonen, J.T., Seppanen, K. Nyyssonen et al. 1995. “Intake of mercury from fish lipid peroxidation, and the risk 

of myocardial infarction and coronary, cardiovascular and any death in Eastern Finnish men.” Circulation, 91 

(3):645-655. 39 Sorensen, N, K. Murata, E. Budtz-Jorgensen, P. Weihe, and Grandjean, P., 1999. “Prenatal Methylmercury 

Exposure As A Cardiovascular Risk Factor At Seven Years of Age”, Epidemiology, pp370-375.

40 National Research Council (NRC). 2000. Toxicological Effects of Methylmercury. Committee on the 

Toxicological Effects of Methylmercury, Board on Environmental Studies and Toxicology. National Academies 

Press. Washington, DC. p. 229.
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5-4

Since publication of the NRC report there have been some 30 published papers 

presenting the findings of studies that have examined the possible cardiovascular effects of 

methylmercury exposure. These studies include epidemiological, toxicological, and toxicokinetic 

investigations. Over a dozen review papers have also been published. If there is a causal 

relationship between methylmercury exposure and adverse cardiovascular effects, then reducing 

exposure to methylmercury would result in public health benefits from reduced cardiovascular 

effects.

In early 2010, EPA sponsored a workshop in which a group of experts were asked to 

assess the plausibility of a causal relationship between methylmercury exposure and 

cardiovascular health effects and to advise EPA on methodologies for estimating population 

level cardiovascular health impacts of reduced methylmercury exposure. The report from that 

workshop is in preparation.

5.3 Energy Savings Co-benefits

Because the membrane cell process requires less energy than the mercury cell process, 

this rule is anticipated to reduce electricity consumption atgenerated for these facilities by over 

375 million kilowatt hours. Assuming a 22% energy reduction in electricity demand, the 

emission reductions associated with reduced electricity consumptiongeneration are estimated to 

be 480 tpy of NOx, 1,600 tpy of SO2, 68 tpy of PM2.5, 5 tpy of VOC, 0.1 tpy of NH3, 0.008 tpy 

(16 lbs) of mercury, and 287,000 tpy of CO2. The methodology for calculating these emission 

reductions is provided in Appendix B of this RIA.

5.3.1 PM2.5 Co-benefits

The energy savings anticipated from this rule would decrease emissions of PM, NOx, 

SO2, and VOCs. Because NOx, SO2, and VOCs are also precursors to PM2.5, decreasing these 

emissions would also decrease PM2.5 formation,thus reducing human exposure, and the incidence 

of PM2.5-related health effects. Due to time and resource limitations, it was not possible to 

provide a comprehensive estimate of the PM2.5-related co-benefits. Instead, we used the 

“benefit-per-ton” approach to estimate these co-benefits based on the methodology described in 

Fann, Fulcher, and Hubbell (2009). These PM2.5 benefit-per-ton estimates provide the total 

monetized human health co-benefits (the sum of premature mortality and premature morbidity) 

of reducing one ton of PM2.5 from a specified source. EPA has used the benefit per-ton technique 

in several previous RIAs, including the recent proposed Cement NESHAP (U.S. EPA, 2009a). 

For this analysis, we use the national average benefit-per-ton estimates associated with the 

electrical generating unit (EGU) sector. Because the anticipated emission reductions are assumed 
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to occur across multiple EGUs, the national average benefit-per-ton estimates best represent the 

regional scope of the anticipated emission reductions. Table 5-1 showsidentifies the quantified 

and unquantified co-benefits captured in those benefit-per-ton estimates.
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5-6

Table 5-1. Human Health and Welfare Effects of PM2.5 

Pollutant / 

Effect Quantified and Monetized in Primary Estimates Unquantified Effects Changes in:

PM2.5 Adult premature mortality

Bronchitis: chronic and acute

Hospital admissions: respiratory and cardiovascular

Emergency room visits for asthma

Nonfatal heart attacks (myocardial infarction)

Lower and upper respiratory illness

Minor restricted-activity days

Work loss days

Asthma exacerbations (asthmatic population)

Infant mortality

Subchronic bronchitis cases

Low birth weight

Pulmonary function

Chronic respiratory diseases other than chronic 

bronchitis

Non-asthma respiratory emergency room visits

Visibility

Household soiling

Consistent with the Portland Cement NESHAP (U.S. EPA, 2009a), the PM2.5 co-benefits 

estimates utilize the concentration-response functions as reported in the epidemiology literature, 

as well as the 12 functions obtained in EPA’s expert elicitation study as a sensitivity analysis.

 One estimate is based on the concentration-response (C-R) function developed 

from the extended analysis of American Cancer Society (ACS) cohort, as reported 

in Pope et al. (2002),), a study that EPA has previously used to generate its 

primary benefits estimate. When calculating the estimate, EPA applied the effect 

coefficient as reported in the study without an adjustment for assumed 

concentration threshold of 10 μg/m3 as was done in recent (2006-–2009) Office of 

Air and Radiation RIAs.

 One estimate is based on the C-R function developed from the extended analysis 

of the Harvard Six Cities cohort, as reported by Laden et al. (2006). One estimate 

is based on the C-R function developed from the extended analysis of the Harvard 

Six Cities cohort, as reported by Laden et al. (2006). This study, published after 

the completion of the Staff Paper for the 2006 PM2.5 NAAQS, has been used as an 

alternative estimate in the PM2.5 NAAQS RIA and PM2.5 benefits estimates in 

RIAs completed since the PM2.5 NAAQS. When calculating the estimate, EPA 

applied the effect coefficient as reported in the study without an adjustment for 

assumed concentration threshold of 10 μg/m3 as was done in recent (2006-–2009) 

RIAs.

 Twelve estimates are based on the C-R functions from EPA’s expert elicitation 

study (IEc, 2006; Roman et al., 2008) on the PM2.5 -mortality relationship and 

interpreted for benefits analysis in EPA’s final RIA for the PM2.5 NAAQS. For 

that study, twelve experts (labeled A through L) provided independent estimates 

of the PM2.5 -mortality concentration-response function. EPA practice has been to 
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5-7

develop independent estimates of PM2.5 -mortality estimates corresponding to the 

concentration-response function provided by each of the twelve experts, to better 

characterize the degree of variability in the expert responses.

The effect coefficients are drawn from epidemiology studies examining two large 

population cohorts: the American Cancer Society cohort (Pope et al., 2002) and the Harvard Six 

Cities cohort (Laden et al., 2006).41 These are logical choices for anchor points in our 

presentation because, while both studies are well designed and peer reviewed, there are strengths 

and weaknesses inherent in each, which we believe argues for using both studies to generate cobenefits estimates. Previously, EPA had calculated co-benefits based on these two empirical 

studies, but derived the range of co-benefits, including the minimum and maximum results, from 

an expert elicitation of the relationship between exposure to PM2.5 and premature mortality 

(Roman et al., 2008).42

Readers interested in reviewing the methodology for creating the benefit-per-ton 

estimates used in this analysis should consult Fann, Fulcher, and Hubbell (2009). As described in 

the documentation for the benefit per-ton estimates cited above, national per-ton estimates are 

developed for selected pollutant/source category combinations. The per-ton values calculated 

therefore apply only to tons reduced from those specific pollutant/source combinations (e.g., 

NOx emitted from electric generating units; NO2 emitted from mobile sources). Our estimate of 

PM2.5 control co-benefits is therefore based on the total PM2.5 emissions controlled by sector and 

multiplied by this per-ton value.

Within this assessment, we include the co-benefits estimates derived 

from the concentration-response function provided by each of the twelve experts to better 

characterize the uncertainty in the concentration-response function for mortality and the degree 

of variability in the expert responses. Because the experts used these cohort studies to inform 

their concentration-response functions, co-benefits estimates using these functions generally fall 

between results using these epidemiology studies (see Figure 6-2). In general, the expert 

elicitation results support the conclusion that the co-benefits of PM2.5 control are very likely to be 

substantial.

The benefit-per-ton coefficients in this analysis were derived using modified versions of 

the health impact functions used in the PM NAAQS Regulatory Impact Analysis. Specifically, 

this analysis uses the benefit-per-ton method first applied in the Portland Cement NESHAP RIA 

(U.S. EPA, 2009a), which incorporated three updates: a new population dataset, an expanded 

 41 These two studies specify multi-pollutant models that control for NOX, among other pollutants. 42 Please see the Section 5.2 of the Portland Cement proposal RIA in Appendix 5A for more information regarding 

the change in the presentation of co-benefits estimates. 
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5-8

geographic scope of the benefit-per-ton calculation, and the functions directly from the 

epidemiology studies without an adjustment for an assumed threshold.43

EPA strives to use the best available science to support our benefits analyses, and we 

recognize that interpretation of the science regarding air pollution and health is dynamic and 

evolving. Based on our review of the current body of scientific literature, EPA now estimates 

PM-related mortality without applying an assumed concentration threshold. EPA’s Integrated 

Science Assessment for Particulate Matter (U.S. EPA, 2009b), which was recently reviewed by 

EPA’s Clean Air Scientific Advisory Committee (U.S. EPA-SAB, 2009a; U.S. EPA-SAB, 

2009b), 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. 

Since then, the Health Effects Subcommittee (U.S. EPA-SAB, 2010) of EPA’s Council 

concluded, “The HES fully supports EPA’s decision to use a no-threshold model to estimate 

mortality reductions. This decision is supported by the data, which are quite consistent in 

showing effects down to the lowest measured levels. Analyses of cohorts using data from more 

recent years, during which time PM concentrations have fallen, continue to report strong 

associations with mortality. Therefore, there is no evidence to support a truncation of the CRF.” 

In conjunction with the underlying scientific literature, this document provided a basis for 

reconsidering the application of thresholds in PM2.5 concentration-response functions used in 

EPA’s RIAs. For a summary of these scientific review statements and the panel members 

commenting on thresholds since 2002, please consult the Technical Support Document (TSD) 

Summary of Expert Opinions on the Existence of a Threshold (U.S. EPA, 2010c).

Removing the threshold 

assumption is a key difference between the method used in this analysis of PM co-benefits and 

the methods used in RIAs prior to Portland Cement, and we now calculate incremental cobenefits down to the lowest modeled PM2.5 air quality levels.

Consistent with this finding, we have conformed the previous threshold sensitivity 

analysis to the current state of the PM science by incorporating a new “Lowest Measured Level” 

(LML) assessment. This information allows readers to determine the portion of population 

exposed to annual mean PM2.5 levels at or above the LML of each study; in general, our 

confidence in the estimated PM mortality decreases as we consider air quality levels further 

below the LML in major cohort studies that estimate PM-related mortality. While an LML 

assessment provides some insight into the level of uncertainty in the estimated PM mortality 

 43 The benefit-per-ton estimates have also been updated since the Cement RIA to incorporate a revised VSL, as 

discussed on the next page. 
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5-9

benefits, EPA does not view the LML as a threshold and continues to quantify PM-related 

mortality impacts using a full range of modeled air quality concentrations. It is important to 

emphasize that we have high confidence in PM2.5-related effects down to the lowest LML of the 

major cohort studies, which is 5.8 μg/m3

. Just because we have greater confidence in the 

benefits above the LML, this does not mean that we have no confidence that benefits occur 

below the LML. 

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

limitations. For these rules, 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 using the most recent modeling available from the recently proposed 

Transport Rule (U.S. EPA, 2010e). 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 air quality modeling, is the shift in exposure associated with 

this specific rule. Therefore, caution is warranted when interpreting the LML assessment. For 

more information on the data and conclusions in the LML assessment for rules without policyspecific air quality modeling, please consult the LML TSD (U.S. EPA, 2010d). The results of 

this analysis are provided in Section 5.4.

As is the nature of Regulatory Impact Analyses (RIAs), the assumptions and methods 

used to estimate air quality co-benefits evolve over time to reflect the Agency’s most current 

interpretation of the scientific and economic literature. For a period of time (2004-–2008), the 

Office of Air and Radiation (OAR) valued mortality risk reductions using a value of statistical 

life (VSL) estimate derived from a limited analysis of some of the available studies. OAR arrived 

at a VSL using a range of $1 million to $10 million (2000$) consistent with two meta-analyses of 

the wage-risk literature. The $1 million value represented the lower end of the interquartile range 

from the Mrozek and Taylor (2002) meta-analysis of 33 studies. The $10 million value 

represented the upper end of the interquartile range from the Viscusi and Aldy (2003) metaanalysis of 43 studies. The mean estimate of $5.5 million (2000$)44

 44.

44 After adjusting the VSL for a different currency year (2007$) and to account for income growth to 2015 to the 

$5.5 million value, the VSL is $8.0 million. 

was also consistent with the 
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5-10

mean VSL of $5.4 million estimated in the Kochi et al. (2006) meta-analysis. However, the 

Agency neither changed its official guidance on the use of VSL in rule-makings nor subjected 

the interim estimate to a scientific peer-review process through the Science Advisory Board 

(SAB) or other peer-review group.

During this time, the Agency continued work to update its guidance on valuing mortality 

risk reductions, including commissioning a report from meta-analytic experts to evaluate 

methodological questions raised by EPA and the SAB on combining estimates from the various 

data sources. In addition, the Agency consulted several times with the Science Advisory Board 

Environmental Economics Advisory Committee (SAB-EEAC) on the issue. With input from the 

meta-analytic experts, the SAB-EEAC advised the Agency to update its guidance using specific, 

appropriate meta-analytic techniques to combine estimates from unique data sources and 

different studies, including those using different methodologies (i.e., wage-risk and stated 

preference) (U.S. EPA-SAB, 2007).

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, the 

Agency 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)45 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 $6.3 million (2000$).46

Figure 5-1 illustrates the relative breakdown of the monetized PM2.5 health co-benefits 

by health endpoint.

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 SAB-EEAC’s specific recommendations. 

 45 In the (draft) update of the Economic Guidelines (U.S. EPA, 20082008b), 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. Therefore, this report does not represent final agency policy. 46 In this analysis, we adjust the VSL to account for a different currency year (2007$) and to account for income 

growth to 2015. After applying these adjustments to the $6.3 million value, the VSL is $9.1 million.
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5-11

Figure 75 5-1.Breakdown of Monetized PM2.5 Health Co-Benefits using Mortality Function 

from Pope et al. (2002)a

a This pie chart breakdown is illustrative, using the results based on Pope et al. (2002) as an example. Using the 

Laden et al. (2006) function for premature mortality, the percentage of total monetized co-benefits due to adult 

mortality would be 97%. This chart shows the breakdown using a 3% discount rate, and the results would be 

similar if a 7% discount rate was used.

Adult Mortality - Pope et 

al. 93%

Chronic Bronchitis 4%

AMI 2%

Acute Respiratory Symptoms 

0.5%

Infant Mortality 0.4%

Work Loss Days 0.2%

Hospital Admissions, Cardio 

0.2% Hospital Admissions, Resp 

0.04%

Asthma Exacerbation 0.01%

Acute Bronchitis 0.01%

Upper Resp Symp 0.00%

Lower Resp Symp 0.00%

ER Visits, Resp 0.00%

Other 1%

 

Adult Mortality - Pope et 

al. 93%

Chronic Bronchitis 4%

AMI 2%

Acute Respiratory Symptoms 

0.5%

Infant Mortality 0.4%

Work Loss Days 0.2%

Hospital Admissions, Cardio 

0.2% Hospital Admissions, Resp 

0.04%

Asthma Exacerbation 0.01%

Acute Bronchitis 0.01%

Upper Resp Symp 0.00%

Lower Resp Symp 0.00%

ER Visits, Resp 0.00%

Other 1%

 
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Table 5-2 provides a general summary of the monetized co-benefits results by pollutant, 

including the emission reductions and benefits-per-ton estimates at discount rates of 3% and 

7%.47

Table 5-2. Summary of Monetized PM2.5 Energy Co-benefits for the Proposed Mercury 

Chlor Alkali NESHAP in 2013 (2007$) (Option 1)

Table 5-3 provides a summary of the reductions in health incidences anticipated as a 

result of the pollution reductions. In Table 5-4, we provide the monetized co-benefits using our 

anchor points of Pope et al. and Laden et al. as well as the results from the expert elicitation on 

PM mortality. Figure 5-2 provides a visual representation of the range of monetized co-benefits 

estimates and the pollutant breakdown of the monetized co-benefits of the proposed option. As 

there are no emission reductions or energy impacts associated with Option 2 (enhanced work 

practice standards), the benefits in this chapter correspond to Option 1 (non-mercury technology 

option).

Pollutant

Emissions 

Reductions 

(tons)

Benefit 

per ton 

(Pope, 

3%)

Benefit 

per ton 

(Laden, 

3%)

Benefit 

per ton 

(Pope, 

7%)

Benefit

per ton 

(Laden, 

7%)

Monetized PM2.5 

Co-benefits 

(millions, 3%)

Monetized 

PM2.5 Cobenefits 

(millions, 7%)

Direct PM2.5 68 $220,000 $540,000 $200,000 $490,000 $15 to $37 $14 to $33

PM2.5

Precursors

SO2 1,568 $40,000 $97,000 $36,000 $88,000 $62 to $150 $56 to $140

NOX 483 $7,200 $18,000 $6,500 $16,000 $3.5 to $8.5 $3.1 to $7.7

VOC 5 $1,200 $2,900 $1,100 $2,600 $.01 to $.01 $.01 to $.01

Total $81 to $200 $73 to $180

a All estimates are for the implementation year (2013), and are rounded to two significant figures so numbers may 

not sum across columns. All fine particles are assumed to have equivalent health effects, but the benefit per ton 

estimates vary because each ton of precursor reduced has a different propensity to become PM2.5. The monetized 

co-benefits incorporate the conversion from precursor emissions to ambient fine particles. Confidence intervals 

are unavailable for this analysis because of the benefit-per-ton methodology. 

 47 To comply with Circular A-4, EPA provides monetized co-benefits using discount rates of 3% and 7% (OMB, 

2003). These co-benefits are estimated for a specific analysis year (i.e., 2013), and most of the PM co-benefits 

occur within that year with two exceptions: acute myocardial infarctions (AMIs) and premature mortality. For 

AMIs, we assume 5 years of follow-up medical costs and lost wages. For premature mortality, we assume that 

there is a “cessation” lag between PM exposures and the total realization of changes in health effects. Although 

the structure of the lag is uncertain, 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, 2004). Changes in the lag assumptions do not change 

the total number of estimated deaths but rather the timing of those deaths. Therefore, discounting only affects the 

AMI costs after the analysis year and the valuation of premature mortalities that occur after the analysis year. As 

such, the monetized co-benefits using a 7% discount rate are only approximately 10% less than the monetized 

co-benefits using a 3% discount rate. 
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Table 5-3. Summary of Reductions in Health Incidences from PM2.5 Co-Benefits for the 

Proposed Mercury Chlor Alkali NESHAP in 2013a2013 (Option 1)a

Avoided Premature Mortality

Pope et al. 92

Laden et al. 245

Avoided Morbidity

Chronic Bronchitis 61

Acute Myocardial Infarction 153

Hospital Admissions, Respiratory 20

Hospital Admissions, Cardiovascular 51

Emergency Room Visits, Respiratory 92

Acute Bronchitis 153

Work Loss Days 1,200230

Asthma Exacerbation 16031

Acute Respiratory SymptomsMinor Restricted 

Activity Days

7,2001,400

Lower Respiratory Symptoms 17033

Upper Respiratory Symptoms 13025

a All estimates are for the analysis year (2013) and are rounded to whole numbers with two significant figures. All 

fine particles are assumed to have equivalent health effects, but each PM2.5 precursor pollutant has a different 

propensity to form PM2.5. Confidence intervals are unavailable for this analysis because of the benefit-per-ton 

methodology. 

Inserted Cells

Inserted Cells
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Table 5-4. All Monetized PM2.5 Co-Benefits Estimates for the Proposed Mercury Chlor 

Alkali NESHAP at discount rates of 3% and 7% in 2013 (in millions of 2007$)

(Option 1)a

3% 7%

Benefit-per-ton Coefficients derived from Epidemiology Literature

Pope et al. $8115 $7314

Laden et al. $20037 $18033

Benefit-per-ton Coefficients Derived from Expert Elicitation

Expert A $21039 $19035

Expert B $16030 $15027

Expert C $16030 $14027

Expert D $11021 $10019

Expert E $26048 $23043

Expert F $15027 $13024

Expert G $9518 $8716

Expert H $12022 $11020

Expert I $16029 $14027

Expert J $13024 $12022

Expert K $316 $295

Expert L $12022 $11020

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 co-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. 
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Figure 5-2. Total Monetized PM2.5 Co-Benefits for the Proposed Mercury Chlor Alkali 

NESHAP in 2013 (Option 1)

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

the Pope et al. study and the Laden 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 function provided in those studies.

$0

$50

$100

$150

$200

$250

$300

Pope et al.

Laden et al.

Millions (2007$)

Benefits estimates derived from 2 epidemiology functions and 12 expert functions

 

3% DR

7% DR

$0

$10

$20

$30

$40

$50

$60

$70

Pope et al.

Laden et al.

Millions (2007$)

Benefits estimates derived from 2 epidemiology functions and 12 expert functions

 

3% DR

7% DR
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5.3.2 Social Cost of Carbon and Greenhouse Gas Co-benefits

EPA has assigned a dollar value to reductions in carbon dioxide (CO2) emissions using 

recent estimates of the “social cost of carbon” (SCC). The SCC is an estimate of the monetized 

damages associated with an incremental increase in carbon emissions in a given year. It is 

intended to include (but is not limited to) changes in net agricultural productivity, human health, 

property damages from increased flood risk, and the value of ecosystem services due to climate 

change. The SCC estimates used in this analysis were developed through an interagency process 

that included EPA and other executive branch entities, and concluded in February 2010. EPA 

first used these SCC estimates in the co-benefits analysis for the final joint EPA/DOT 

Rulemaking to establish Light-Duty Vehicle Greenhouse Gas Emission Standards and Corporate 

Average Fuel Economy Standards; see the rule’s preamble for discussion about application of 

SCC (75 FR 25324; 5/7/10). The SCC Technical Support Document (SCC TSD) provides a 

complete discussion of the methods used to develop these SCC estimates.48

The interagency group selected four SCC values for use in regulatory analyses, which we 

have applied in this analysis: $5, $21, $35, and $65 per metric ton of CO2 emissions49

 48 Docket ID EPA-HQ-OAR-2009-0472-114577, Technical Support Document: 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 (February 2010). Also 

available at 

in 2010, in 

2007 dollars. The first three values are based on the average SCC from three integrated 

assessment models, at discount rates of 2.5, 3, and 5 percent, respectively. SCCs at several 

discount rates are included because the literature shows that the SCC is quite sensitive to 

assumptions about the discount rate, and because no consensus exists on the appropriate rate to 

use in an intergenerational context. The fourth value is the 95th percentile of the SCC from all 

three models at a 3 percent discount rate. It is included to represent higher-than-expected 

impacts from temperature change further out in the tails of the SCC distribution. Low 

probability, high impact events are incorporated into all of the SCC values through explicit 

consideration of their effects in two of the three models as well as the use of a probability density 

function for equilibrium climate sensitivity. Treating climate sensitivity probabilistically results 

in more high temperature outcomes, which in turn lead to higher projections of damages.

http://www.epa.gov/otaq/climate/regulations.htm 49 The interagency group decided that these estimates apply only to CO2 emissions. Given that warming profiles and 

impacts other than temperature change (e.g.., ocean acidification) vary across GHGs, the group concluded 

“transforming gases into CO2-equivalents using GWP, and then multiplying the carbon-equivalents by the SCC, 

would not result in accurate estimates of the social costs of non-CO2 gases” (SCC TSD, pg 13).
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The SCC increases over time because future emissions are expected to produce larger 

incremental damages as physical and economic systems become more stressed in response to 

greater climatic change. Note that the interagency group estimated the growth rate of the SCC 

directly using the three integrated assessment models rather than assuming a constant annual 

growth rate. This helps to ensure that the estimates are internally consistent with other modeling 

assumptions. The SCC estimates for the analysis years of 2013, in 2007 dollars are provided in 

Table 5-5.

Table 5-5. Social Cost of Carbon (SCC) Estimates (per tonne of CO2) for 2013 a

Discount Rate and Statistic SCC estimate (2007$)

5% Average $5.3

3% Average $22.8

2.5% Average $37.0

3% 95%ile $69.6

a The SCC values are dollar-year and emissions-year specific. SCC values represent only a partial accounting of 

climate impacts.

When attempting to assess the incremental economic impacts of carbon dioxide 

emissions, the analyst faces a number of serious challenges.When attempting to assess the 

incremental economic impacts of carbon dioxide emissions, the analyst faces a number of serious 

challenges. A recent report from the National Academies of Science (NRC, 2008) points out that 

any assessment will suffer from uncertainty, speculation, and lack of information about (1) future 

emissions of greenhouse gases, (2) the effects of past and future emissions on the climate system, 

(3) the impact of changes in climate on the physical and biological environment, and (4) the 

translation of these environmental impacts into economic damages. As a result, any effort to 

quantify and monetize the harms associated with climate change will raise serious questions of 

science, economics, and ethics and should be viewed as provisional.

The interagency group noted a number of limitations to the SCC 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. The limited amount of research linking climate impacts to economic damages makes 

the interagency modeling exercise even more difficult. The interagency group hopes that over 

time researchers and modelers will work to fill these gaps and that the SCC estimates used for 
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regulatory analysis by the Federal government will continue to evolve with improvements in 

modeling. Additional details on these limitations are discussed in the SCC TSD.

In light of these limitations, the interagency group has committed to updating the current 

estimates as the science and economic understanding of climate change and its impacts on 

society improves over time. Specifically, the interagency group has set a preliminary goal of 

revisiting the SCC values within two years or at such time as substantially updated models 

become available, and to continue to support research in this area. 

Applying the global SCC estimates to the estimated decreases in CO2 emissions for the 

range of policy scenarios, we estimate the dollar value of the climate-related co-benefits captured 

by the models for each analysis year. For internal consistency, the annual co-benefits are 

discounted back to NPV terms using the same discount rate as each SCC estimate (i.e.., 5%, 3%, 

and 2.5%) rather than 3% and 7%.50

Table 5-5. Social Cost of Carbon (SCC) Estimates (per tonne6. Monetized Cobenefits of CO2) for Emission Decreases in 2013 (Option 1)a

These estimates are provided in Table 5-6.

Discount Rate and Statistic

SCC estimate (-derived benefits (millions of 

2007$)

5% Average $1.5.3

3% Average $22.8 6.5

2.5% Average $37.0 11

3% 95%ile $69.6 20

a The SCC values are dollar-year and emissions-year specific. SCC values represent only a 

partial accounting of climate impacts.

Table 5-6. Monetized Co-benefits of CO2 Emission Decreases in 2013 a

Discount Rate and Statistic

SCC-derived benefits

(millions of 2007$)

5% Average $1.5

3% Average $6.5

2.5% Average $11

3% 95%ile $20

a The SCC values are dollar-year and emissions-year specific. SCC values represent only a partial accounting of 

climate impacts.

 50 It is possible that other co-benefits or costs of proposed regulations unrelated to CO2 emissions will be discounted 

at rates that differ from those used to develop the SCC estimates.
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5.3.3 Total Monetized Co-benefits of Energy Savings

The energy savings would decrease emissions of several pollutants. In this analysis, we 

were able to monetize the co-benefits associated with the decreased emissions of PM, NOX, SO2, 

VOCs, and CO2, but we were unable to monetize the co-benefits associated with the decreased 

emissions of NH3. mercury. We estimate that the total monetized co-benefits are $8722 to 

$20043 million and $73$14 to $18033 million, at discount rates of 3% and 7% respectively. 

Figure 5-3 shows the breakdown of the monetized co-benefits by pollutant.
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Figure 5-3. Breakdown of Monetized Co-benefits by Pollutant at 3% discount rate

5.4 Characterization of Uncertainty in the Monetized PM2.5 Co-Benefits

In any complex analysis, there are likely to be many sources of uncertainty. Many inputs 

are used to derive the estimate of monetized co-benefits, including emission inventories, air 

quality models (with their associated parameters and inputs), epidemiological estimates of 

concentration-response (C-R) functions, estimates of values, population estimates, income 

estimates, and estimates of the future state of the world (i.e., regulations, technology, and human 

behavior). For some parameters or inputs it may be possible to provide a statistical representation 

of the underlying uncertainty distribution. For other parameters or inputs, the necessary 

information is not available. Because we used the benefit-per-ton approach for this analysis, 

confidence intervals are unavailable. 

CO2

8% SO2 EGU

71%

Direct PM2.5 EGU

17%

NO2 EGU

4% VOC 

0%

 
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Figure 5-3. Breakdown of Monetized Co-benefits by Pollutant at 3% discount rate

(Option 1)

There are uncertainties associated with each analytical step to calculate the human health 

benefits associated with reducing electricity consumption. Important uncertainties associated 

with estimating the reduction in electricity consumption include variability across facilities and 

variability in local energy costs. 51 Important uncertainties associated with estimating the 

emission reductions associated with a specific electricity consumption reduction include 

representativeness of historical emissions factors across regions and over time, transmission 

losses, electricity market response to changes in demand, and emissions trading effects. 52

Important uncertainties associated with estimating the human health benefits associated with 

those emission reductions include assumptions regarding the PM2.5-related mortality relationship, 

the value-of-a-statistical-life, and average benefit-per-ton estimates.53

 51 These uncertainties are described in detail in Appendix B of this RIA.

It should be noted that the 

method used to the change in PM2.5 precursor emissions for this rule is consistent with the 

method used to calculated changes in CO2 emissions. Given the strong desire to estimate the 

effects of regulations on greenhouse gas (GHG) emissions, we will continue to investigate and 

improve the methodology for estimating all benefits categories associated with reducing 

electricity consumption, to the extent feasible.

52 These uncertainties are described in detail in Appendix B of this RIA. 53 These uncertainties are described in detail below.
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5-22

Although this is the first RIA for which U.S. EPA’s Office of Air and Radiation has 

calculated the monetized human health benefits specifically associated with a reduction in 

electricity consumption, there are several previous regulations that included the health benefits 

associated with energy changes. For example, the recently finalized Portland Cement NESHAP 

included the human health and climate disbenefits associated with increased electricity 

consumption and fuel usage from control devices (U.S. EPA, 2010i). U.S. EPA has previously 

calculated substantial human health benefits associated with reducing emissions from electrical 

generating units, including the proposed Federal Transport Rule (2010d), the SO2 NAAQS 

(2010g), and the Clean Air Interstate Rule (2005). In addition, several recent regulations from 

U.S. EPA’s Office of Transportation and Air Quality assessed the air quality changes and 

associated human health impacts from changes in fuel consumption and/or fuel production and 

distribution, including the Light Duty Vehicle GHG rule (U.S. EPA, 2010f),54 Renewable Fuel 

Standard II rule (U.S. EPA, 2010e),55 and the Locomotive Marine rule (U.S. EPA, 2008a).56

In addition to RIAs, other recent attempts to calculate the human health benefits 

associated with electricity consumption are available in the literature. For example, Levy et al. 

(2009) estimated the median monetized health-related damages associated with emissions of 

PM2.5, SO2, and NOx from coal-fired power plants. In addition, the National Research Council 

(NRC) estimated the monetized health benefits associated emissions of PM, SO2, and NOx to be 

for coal and natural gas power plants. It is important to note that there are important 

methodological differences between these two analyses and EPA’s approach to estimating PMFurthermore, the Iron and Steel Foundries NESHAP (U.S. EPA, 2003) included an estimate of 

the emission reductions associated with decreased energy consumption for alternate control 

devices, but no benefits analysis was conducted for that rule.

 54 In addition to downstream emission reductions, the Light Duty Vehicle GHG rule accounted for the emissions 

associated with the processes involved in getting petroleum to the pump, including the extraction and 

transportation of crude oil, and the production and distribution of finished gasoline. Changes were anticipated in 

upstream emissions due to the expected reduction in the volume of fuel consumed. Less gasoline consumed 

means less gasoline transported, less gasoline refined, and less crude oil extracted and transported to refineries. 

Thus, the analysis accounted for reductions in the emissions associated with each of these steps in the gasoline 

production and distribution process. 55 In addition to the effects of increased renewable fuel use on emissions from the vehicles and equipment that use 

the fuels, the RFS2 analysis accounted for shifts in the fuel production and transport/distribution methods that 

can have substantial impacts on emissions. These "upstream" emissions are associated with all stages of biofuel 

production and distribution, including biomass production (agriculture, forestry), fertilizer and pesticide 

production and transport, biomass transport, biomass refining (corn or cellulosic ethanol production facilities), 

biofuel transport to blending/distribution terminals, and distribution of finished fuels to retail outlets. 56 The locomotive and marine engine rule accounted for idle reduction technologies that provide substantial 

emission reductions as well as cost savings by reducing fuel consumption. Reduced idling time results in reduced 

fuel consumption and reduced idle emissions. The analysis estimated annual fuel savings, the associated cost 

savings, and the emissions reductions that would result from the idle reduction requirements.
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5-23

related monetized benefits, including characterization of secondary formation of PM2.5, 

population growth, income growth, the VSL, the cessation lag assumed, among others. However, 

these studies provide additional examples of conceptually similar attempts to monetize the 

human health benefits associated with electricity consumption.

The annual benefit estimates presented in this analysis are also inherently variable due to 

the processes that govern pollutant emissions and ambient air quality in a given year. Factors 

such as hours of equipment use and weather are constantly variable, regardless of our ability to 

measure them accurately. As discussed in the PM2.5 NAAQS RIA (Table 5.5) (U.S. EPA, 

2006a), there are a variety of uncertainties associated with these PM co-benefits. Therefore, the 

estimates of annual co-benefits should be viewed as representative of the magnitude of cobenefits expected, rather than the actual co-benefits that would occur every year.

It is important to note that the monetized benefit-per-ton estimates used here reflect 

specific geographic patterns of emissions reductions and specific air quality and co-benefits 

modeling assumptions. For example, these estimates do not reflect local variability in population 

density, meteorology, exposure, baseline health incidence rates, or other local factors. Use of 

these $/ton values to estimate co-benefits associated with different emission control programs 

(e.g., for reducing emissions from large stationary sources like EGUs) may lead to higher or 

lower benefit estimates than if co-benefits were calculated based on direct air quality modeling. 

Great care should be taken in applying these estimates to emission reductions occurring in any 

specific location, as these are all based on national or broad regional emission reduction 

programs and therefore represent average co-benefits-per-ton over the entire United States. The 

co-benefits- per-ton for emission reductions in specific locations may be very different than the 

estimates presented here.

PM2.5 mortality co-benefits are the largest benefit category that we monetized in this 

analysis. To better characterize the uncertainty associated with mortality impacts that are 

estimated to occur in areas with low baseline levels of PM2.5, we included the LML assessment.

Without policy-specific air quality modeling, we are unable to quantify the shift in exposure 

associated with this specific rule. For this rule, as a surrogate measure of mortality impacts, we 

provide the percentage of the population exposed at each PM2.5 level using the most recent 

modeling available from the recently proposed Transport Rule (U.S. EPA, 2010e). A very large 

proportion of the population is exposed at or above the lowest LML of the cohort studies 

(Figures 5-4 and 5-5), increasing our confidence in the PM mortality analysis. Figure 5-4 shows 

a bar chart of the percentage of the population exposed to various air quality levels in the preand post-policy policy. Figure 5-5 shows a cumulative distribution function of the same data. 
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Figure 5-4. Percentage of Adult Population by Annual Mean PM2.5 Exposure (pre- and 

post-policy policy)

Figure 5-5. Cumulative Distribution of Adult Population at Annual Mean PM2.5 levels 

(pre- and post-policy policy)
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Both figures identify the LML for each of the major cohort studies. As the policy shifts the 

distribution of air quality levels, fewer people are exposed to PM2.5 levels at or above the LML. 

Under baseline conditions, about 96 percent of the population is exposed to annual mean PM2.5

levels of at least 5.8 μg/m3, which is the lowest air quality level considered in the most recent 

study of the American Cancer Society cohort by Krewski et al. (2009). Using the Pope et al. 

(2002) study, the 85% of the population is exposed to annual mean PM2.5 levels at or above the 

LML of 7.5 μg/m3. Using the Laden et al. (2006) study, 40% of the population is exposed above 

the LML of 10 μg/m3. As we model mortality impacts among populations exposed to levels of 

PM2.5 that are successively lower than the LML of the lowest cohort study, our confidence in the 

results diminishes. However, the analysis above confirms that the great majority of the impacts 

occur at or above the lowest cohort study’s LML. It is important to emphasize that we have high 

confidence in PM2.5-related effects down to the lowest LML of the major cohort studies, which is 

5.8 μg/m3. . Just because we have greater confidence in the benefits above the LML, this does 

not mean that we have no confidence that benefits occur below the LML. 

Figure 5-4. Percentage of Adult Population by Annual Mean PM2.5 Exposure (pre- and 

post-policy policy)
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Figure 5-5. Cumulative Distribution of Adult Population at Annual Mean PM2.5 levels (preand post-policy policy)

Above we present the estimates of the total monetized co-benefits, based on our 

interpretation of the best available scientific literature and methods and supported by the SABHES and the NAS (NRC, 2002). The co-benefits estimates are subject to a number of 

assumptions and uncertainties. For example, for key assumptions underlying the estimates for 

premature mortality, which typically account for at least 90% of the total monetized co-benefits, 

we were able to quantify include the following:

1. PM2.5 co-benefits were derived through benefit per-ton estimates, which 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 underestimate of the actual co-benefits of controlling directly emitted fine particulates.

2. 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 produced via transported precursors emitted from EGUs may differ 

significantly from direct PM2.5 released from diesel engines and other industrial 

sources, but no clear scientific grounds exist for supporting differential effects 

estimates by particle type.

3. We assume that the health impact function for fine particles is linear down to the 

lowest air quality levels modeled in this analysis. Thus, the estimates include health 

co-benefits from reducing fine particles in areas with varied concentrations of PM2.5,

including both regions that are in attainment with fine particle standard and those that 

do not meet the standard down to the lowest modeled concentrations.
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4. To characterize the uncertainty in the relationship between PM2.5 and premature 

mortality (which typically accounts for 85% to 95% of total monetized co-benefits), 

we include a set of twelve estimates based on results of the expert elicitation study in 

addition to our core estimates. Even these multiple characterizations omit the 

uncertainty in air quality estimates, baseline incidence rates, populations exposed and 

transferability of the effect estimate to diverse locations. As a result, the reported 

confidence intervals and range of estimates give an incomplete picture about the 

overall uncertainty in the PM2.5 estimates. This information should be interpreted 

within the context of the larger uncertainty surrounding the entire analysis. For more 

information on the uncertainties associated with PM2.5 co-benefits, please consult the 

PM2.5 NAAQS RIA (Table 5-5).

This RIA does not include the type of detailed uncertainty assessment found in the PM 

NAAQS RIA because we lack the necessary air quality input and monitoring data to run the cobenefits model. Moreover, it was not possible to develop benefit-per-ton metrics and associated 

estimates of uncertainty using the co-benefits estimates from the PM RIA because of the 

significant differences between the sources affected in that rule and those regulated here. 

However, the results of the Monte Carlo analyses of the health and welfare co-benefits presented 

in Chapter 5 of the PM NAAQS RIA can provide some evidence of the uncertainty surrounding 

the co-benefits results presented in this analysis.

5.5 COMPARISON OF CO-BENEFITS AND COSTS

Using a 3% discount rate, we estimate the total monetized co-benefits of the proposed 

Mercury Chlor Alkali NESHAP to be $87 million to $200 million in the implementation year 

(2013). Using a 7% discount rate, we estimate the total monetized co-benefits of this rule to be 

$73 million to $180 million. The annualized social costs of the proposed NESHAP are $13 

million at a 7% interest rate.57

Table 5-7 shows a summary of the monetized co-benefits, social costs, and net benefits 

for the proposed Mercury Chlor Alkali NESHAP, respectively. Figures 5-5 and 5-6 show the full 

range of net benefits estimates (i.e., annual co-benefits minus annualized costs) utilizing the 14 

different PM2.5 mortality functions at discount rates of 3% and 7%. It is important to emphasize 

that these monetized co-benefits do not include the benefits associated with reducing mercury 

emissions. EPA believes that the co-benefits are likely to exceed the costs under this rulemaking 

even when taking into account uncertainties in the cost and benefit estimates.

 Thus, the net benefits are $73 million to $190 million at a 3% 

discount rate and $60 million to $170 million at a 7% discount rate. All estimates are in 2007$ 

for the year 2013. 

 57 For more information on the annualized social costs, please refer to Section 5 of this RIA.
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Table 5-7. Summary of the Monetized Co-Benefits, Social Costs, and Net benefits for 

the Proposed Mercury Chlor Alkali NESHAP in 2013 (millions of 2007$)1

3% Discount Rate 7% Discount Rate

Total Monetized Benefits2 $87 to $200 $73 to $180

Total Social Costs3 $13 $13 

Net Benefits $74 to $190 $60 to $170

Non-monetized Benefits

656 pounds of mercury (including energy co-benefits)

Health effects from NO2 and SO2 exposure

Ecosystem effects 

Visibility impairment 

1

All estimates are for the implementation year (2013), and are rounded to two significant figures. 

2 The total monetized co-benefits reflect the human health co-benefits associated with reducing exposure to PM2.5

through reductions of PM2.5 precursors such as NOx and VOC. It is important to note that the monetized cobenefits include many but not all health effects associated with PM2.5 exposure. It is important to note that the 

monetized benefits include many but not all health effects associated with PM2.5 exposure. Benefits are shown as a 

range from Pope et al. (2002) to Laden et al. (2006). These models assume that all fine particles, regardless of 

their chemical composition, are equally potent in causing premature mortality because there is no clear scientific 

evidence that would support the development of differential effects estimates by particle type.

3 The annual compliances costs serve as a proxy for the annual social costs of this rule given the lack of difference 

between the two.
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Figure 5-6. Net Benefits for the Proposed Mercury Chlor Alkali NESHAP at 3% 

Discount Rate a

a Net Benefits are quantified in terms of PM2.5 co-benefits for implementation year (2013). This graph shows 14 

benefits estimates combined with the cost estimate. All combinations are treated as independent and equally 

probable. All fine particles are assumed to have equivalent health effects, but the benefit per ton estimates vary 

because each ton of precursor reduced has a different propensity to become PM2.5. The monetized co-benefits 

incorporate the conversion from precursor emissions to ambient fine particles.

$0

$50

$100

$150

$200

$250

Pope et al.

Laden et al.

Millions (2007$)

Cost estimate combined with total monetized benefits estimates derived from 2

epidemiology functions and 12 expert functions

 
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Figure 5-7. Net Benefits for the Proposed Mercury Chlor Alkali NESHAP at 7% 

Discount Rate a

a Net benefits are quantified in terms of PM2.5 co-benefits for implementation year (2013). This graph shows 14 cobenefits estimates combined with the cost estimate. All combinations are treated as independent and equally 

probable. All fine particles are assumed to have equivalent health effects, but the benefit per ton estimates vary 

because each ton of precursor reduced has a different propensity to become PM2.5. The monetized co-benefits 

incorporate the conversion from precursor emissions to ambient fine particles.

5.6 References

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in estimates of the human health benefits of reducing a ton of air pollution. Air Qual 

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Kochi, I., B. Hubbell, and R. Kramer. 2006. “An Empirical Bayes Approach to Combining 

Estimates of the Value of Statistical Life for Environmental Policy Analysis.” 

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Laden, F., J. Schwartz, F.E. Speizer, and D.W. Dockery. 2006. “Reduction in Fine Particulate 

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Levy, J.I., L.K. Baxter, and J. Schwartz. 2009. “Uncertainty and variability in health-related 

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Mrozek, J.R., and L.O. Taylor. 2002. “What Determines the Value of Life? A Meta-Analysis.” 

Journal of Policy Analysis and Management 21(2):253-270.

$0

$50

$100

$150

$200

$250

Pope et al.

Laden et al.

Millions (2007$)

Cost estimate combined with total monetized benefits estimates derived from 2 

epidemiology functions and 12 expert functions

 
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National Research Council (NRC). 2002. Estimating the Public Health Benefits of Proposed Air 

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Pope, C.A., III, R.T. Burnett, M.J. Thun, E.E. Calle, D. Krewski, K. Ito, and G.D. Thurston. 

2002. “Lung Cancer, Cardiopulmonary Mortality, and Long-term Exposure to Fine 

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Roman, H.A., K.D. Walker, T.L. Walsh, L. Conner, H.M. Richmond, .J. Hubbell, and P.L. 

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Scudder, B.C., Chasar, L.C., Wentz, D.A., Bauch, N.J., Brigham, M.E., Moran, P.W., and 

Krabbenhoft, D.P. 2009. Mercury in fish, bed sediment, and water from streams across 

the United States, 1998–2005: U.S. Geological Survey Scientific Investigations Report 

2009–5109, 74 p.

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<http://yosemite.epa.gov/ee/epa/eed.nsf/webpages/Guidelines.html/$file/cover.pdf>.

U.S. Environmental Protection Agency (U.S. EPA). 2006a.2003. Economic Impact Analysis of 

Final Iron and Steel Foundries NESHAP. Office of Air Quality Planning and Standards, 

Research Triangle Park. EPA-452/R-03-012. August. Available on the Internet at 

<http://www.epa.gov/ttn/ecas/regdata/EIAs/foundry_report.pdf>.

U.S. Environmental Protection Agency (U.S. EPA). 2005. Regulatory Impact Analysis for the 

Final Clean Air Interstate Rule. EPA-452/R-05-002. Office of Air and Radiation. March. 

Available on the Internet at <http://www.epa.gov/cair/pdfs/finaltech08.pdf>.

U.S. Environmental Protection Agency (U.S. EPA). 2006. Regulatory Impact Analysis, 2006 

National Ambient Air Quality Standards for Particulate Matter, Chapter 5. Available at 

<http://www.epa.gov/ttn/ecas/regdata/RIAs/Chapter%205--Benefits.pdf >.>.

U.S. Environmental Protection Agency (U.S. EPA). 20082008a. Regulatory Impact Analysis, 

2008 National Ambient: Control of Emissions of Air Pollution from Locomotive Engines 

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Chapter 6. May. Available on the Internet at 

<http://www.epa.gov/ttn/ecas/regdata/RIAs/6-

ozoneriachapter6otaq/regs/nonroad/420r08001a.pdf>.
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U.S. Environmental Protection Agency (U.S. EPA). 2008c2008b. Guidelines for Preparing 

Economic Analyses: External Review Draft. National Center for Environmental 

Economics, Office of Policy Economics and Innovation. Washington, DC. Available at 

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01.pdf>.

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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). 2009a. Regulatory Impact Analysis: 

National Emission Standards for Hazardous Air Pollutants from the Portland Cement 

Manufacturing Industry. Office of Air Quality Planning and Standards, Research 

Triangle Park, NC. April. Available at 

<http://www.epa.gov/ttn/ecas/regdata/RIAs/portlandcementria_4-20-09.pdf >.>.

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Particulate Matter (Final Report). EPA-600-R-08-139F. National Center for 

Environmental Assessment—RTP Division. December. Available at 

<http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=216546>.

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(RIA) for the NO2 National Ambient Air Quality Standards (NAAQS). Office of Air 

Quality Planning and Standards, Research Triangle Park, NC. January. Available at < 

<http://www.epa.gov/ttn/ecas/regdata/RIAs/FinalNO2RIAfulldocument.pdf>.

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Existence of a Threshold in the Concentration-Response Function for PM2.5-related 

Mortality: Technical Support Document. Compiled by Office of Air Quality Planning and 

Standards, Research Triangle Park, NC. July. Available at 

<http://www.epa.gov/ttn/ecas/benefits.html>.

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Assessment for Rules without Policy-Specific Air Quality Data Available: Technical 

Support Document. Office of Air Quality Planning and Standards, Research Triangle 

Park, NC. July. Available at <http://www.epa.gov/ttn/ecas/benefits.html>.

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(RFS2) Regulatory Impact Analysis for the Transport Rule. . EPA-420-R-10-006. Office 

of Transportation and Air Quality Planning and Standards, Research Triangle Park, NC. 

July. . March. Available on the Internet at <http://www.epa.gov/ttn/ecas/ria.html>. 

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Light-Duty Vehicle Greenhouse Gas Emission Standards and Corporate Average Fuel 

Economy Standards Regulatory Impact Analysis. EPA-420-R-10-009. Office of 

Transportation and Air Quality. April. Available on the Internet at 

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(RIA) for the SO2 National Ambient Air Quality Standards (NAAQS). Office of Air 

Quality Planning and Standards, Research Triangle Park, NC. June. Available on the 

Internet at <http://www.epa.gov/ttn/ecas/regdata/RIAs/fso2ria100602full.pdf>.

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Proposed Federal Transport Rule. Office of Air Quality Planning and Standards, 

Research Triangle Park, NC. July. Available at 

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Amendments to the National Emission Standards for Hazardous Air Pollutants and New 

Source Performance Standards (NSPS) for the Portland Cement Manufacturing Industry. 

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Advisory on Plans for Health Effects Analysis in the Analytical Plan for EPA’s Second 

Prospective Analysis – —Benefits and Costs of the Clean Air Act, 1990-–2020. Advisory 

by the Health Effects Subcommittee of the Advisory Council on Clean Air Compliance 

Analysis. EPA-SAB-COUNCIL-ADV-04-002. March. Available at at 

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0433D5D/$File/council_adv_04002.pdf>.

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Advisory on EPA’s Issues in Valuing Mortality Risk Reduction. EPA-SAB-08-001. 

October. Available at 

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Review of EPA’s Integrated Science Assessment for Particulate Matter (First External 

Review Draft, December 2008). EPA-COUNCIL-09-008. May. Available at 

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e/73ACCA834AB44A10852575BD0064346B/$File/EPA-CASAC-09-008-

unsigned.pdf>.
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U.S. Environmental Protection Agency—Science Advisory Board (U.S. EPA-SAB). 2009b. 

Consultation on EPA’s Particulate Matter National Ambient Air Quality Standards: 

Scope and Methods Plan for Health Risk and Exposure Assessment. EPA-COUNCIL-09-

009. May. Available at at 

<http://yosemite.epa.gov/sab/SABPRODUCT.NSF/81e39f4c09954fcb85256ead006be86

e/723FE644C5D758DF852575BD00763A32/$File/EPA-CASAC-09-009-unsigned.pdf>.

Viscusi, V.K., and J.E. Aldy. 2003. “The Value of a Statistical Life: A Critical Review of Market 

Estimates throughout the World.” Journal of Risk and Uncertainty 27(1):5-76.
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5-1

SECTION 6

COMPARISON OF CO-BENEFITS AND COSTS

Using a 3% discount rate, we estimate the total monetized co-benefits of Option 1 of the

Mercury Chlor Alkali NESHAP to be $22 million to $43 million in the implementation year 

(2013). Using a 7% discount rate, we estimate the total monetized co-benefits of this option to be 

$21 million to $40 million. The annualized social costs of this option HAP are $13 million at a 

7% interest rate.58

Option 2 does not have emission reductions, thus no monetized benefits. The annualized 

social costs of this option HAP are $25,000 at a 7% interest rate. Thus, the net benefits of this 

option are $-25,000.

Thus, the net benefits of this option are $9 million to $30 million at a 3% 

discount rate and $8 million to $27 million at a 7% discount rate. All estimates are in 2007$ for 

the year 2013. 

Table 6-1 shows a summary of the monetized co-benefits, social costs, and net benefits 

for the proposed Mercury Chlor Alkali NESHAP, respectively. Figures 6-1 and 6-2show the full 

range of net benefits estimates (i.e., annual co-benefits minus annualized costs) utilizing the 14 

different PM2.5 mortality functions at discount rates of 3% and 7%. It is important to emphasize 

that these monetized co-benefits do not include the benefits associated with reducing mercury 

emissions. EPA believes that the co-benefits are likely to exceed the costs under this rulemaking 

even when taking into account uncertainties in the cost and benefit estimates.

 58 For more information on the annualized social costs, please refer to Section 3 of this RIA.
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5-2

Table 6-1. Summary of the Monetized Co-Benefits, Social Costs, and Net benefits for the 

Proposed Mercury Chlor Alkali NESHAP in 2013 (thousands of 2007$)a

3% Discount Rate 7% Discount Rate

Option 1: Non-mercury Technology Option

Total Monetized Benefitsb $22,000 to $43,000 $21,000 to $40,000

Total Social Costsc $13,000 $13,000

Net Benefits $9,000 to $30,000 8,000 to $27,000

Non-monetized Benefits 656 pounds of mercury (including energy co-benefits)

Health effects from NO2 and SO2 exposure

Ecosystem effects 

Visibility impairment 

Option 2: Enhanced Work Practice Standards

Total Monetized Benefitsb $0 $0

Total Social Costsc $25 $25

Net Benefits $-25 $-25

a All estimates are for the implementation year (2013), and are rounded to two significant figures. 

b The total monetized co-benefits reflect the human health co-benefits associated with reducing exposure to PM2.5. It 

is important to note that the monetized co-benefits include many but not all health effects associated with PM2.5

exposure. It is important to note that the monetized benefits include many but not all health effects associated with 

PM2.5 exposure. Benefits are shown as a range from Pope et al. (2002) to Laden et al. (2006). These models 

assume that all fine particles, regardless of their chemical composition, are equally potent in causing premature 

mortality because there is no clear scientific evidence that would support the development of differential effects 

estimates by particle type. CO2-related benefits were calculated using the social cost of carbon (SCC). The net 

present value of reduced CO2 emissions is calculated differently than other benefits. The same discount rate used 

to discount the value of damages from future emissions (SCC at 5, 3, 2.5 percent) is used to calculate net present 

value of SCC for internal consistency. This table shows monetized CO2 co-benefits at discount rates of 3 and 7 

percent that were calculated using the global average SCC estimate at a 3% discount rate because the interagency 

workgroup on this topic deemed this marginal value to be the central value. In Section 5, we also provide the 

monetized CO2 co-benefits using discount rates of 5 percent (average), 2.5 percent (average), and 3 percent (95th 

percentile).

c The annual compliances costs serve as a proxy for the annual social costs of this rule given the lack of difference 

between the two.
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5-3

Figure 6-1. Net Benefits for the Proposed Mercury Chlor Alkali NESHAP at 3% 

Discount Rate (Option 1)a

a Net Benefits are quantified in terms of PM2.5 co-benefits for implementation year (2013). This graph shows 14 

benefits estimates combined with the cost estimate. All combinations are treated as independent and equally 

probable. All fine particles are assumed to have equivalent health effects, but the benefit per ton estimates vary 

because each ton of precursor reduced has a different propensity to become PM2.5. The monetized co-benefits 

incorporate the conversion from precursor emissions to ambient fine particles. The net benefits at a 3% discount 

rate also include CO2-related benefits calculated using the social cost of carbon. 

-$10

$0

$10

$20

$30

$40

$50

Pope et al.

Laden et al.

Millions (2007$)

Cost estimate combined with total monetized benefits estimates derived from 2

epidemiology functions and 12 expert functions

 
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5-4

Figure 6-2. Net Benefits for the Proposed Mercury Chlor Alkali NESHAP at 7% 

Discount Rate (Option 1)a

a Net benefits are quantified in terms of PM2.5 co-benefits for implementation year (2013). This 

graph shows 14 co-benefits estimates combined with the cost estimate. All combinations 

are treated as independent and equally probable. All fine particles are assumed to have 

equivalent health effects, but the benefit per ton estimates vary because each ton of 

precursor reduced has a different propensity to become PM2.5. The monetized co-benefits 

incorporate the conversion from precursor emissions to ambient fine particles.

-$10

$0

$10

$20

$30

$40

$50

Pope et al.

Laden et al.

Millions (2007$)

Cost estimate combined with total monetized benefits estimates derived from 2 

epidemiology functions and 12 expert functions

Net Benefits for Mercury Chlor Alkali in 2013 at 7% discount rate*
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5-6-1

APPENDIX A:

This table shows monetized CO2 co-benefits at discount rates of 3 and 7 percent that were calculated using the 

global average SCC estimate at a 3% discount rate because the interagency workgroup on this topic deemed this 

marginal value to be the central value.

APPENDIX A:

MERCURY EMISSIONS MEMO

MEMORANDUM

TO: Donna Lee Jones, PhD, USEPA/OAQPS/SPPD/MMG

FROM: Phil Norwood, Incorporated

DATE: March 15, 2010

SUBJECT: Mercury Emission Reductions and Other Mercury Waste Impacts – —Conversion 

from Mercury Cell Chlor-Alkali to Membrane Cell Chlor Alkali Technology

The purpose of this memorandum is present the mercury air emission and other 

mercury waste impacts that would result from the conversion of the four mercury cell chloralkali plants currently operating in the U.S. to non-mercury (membrane cell) technology. These 

plants are ASHTA Chemicals in Ashtabula, Ohio (ASHTA), Olin Corporation in Augusta, 

Georgia (OLIN-GA), Olin Corporation in Charleston, Tennessee (OLIN-TN), and PPG in New 

Martinsville, West Virginia (PPG). The first two sections address the baseline mercury air 

emissions and mercury releases to other media. In the event of conversion, these routine releases 

would be eliminated. This is followed by a discussion of the mercury releases and mercurycontaminated wastes that would be generated during the cleanup and decommissioning of the 

mercury cell plants. The final section summarizes these air and other media impacts.

BASELINE MERCURY AIR EMISSIONS

Table 1 shows the mercury air releases reported in EPA’s Toxics Release Inventory 

(TRI) for 2007 and 2008 for each of the currently operating mercury cell chlor-alkali plants.

In addition to the TRI information available online, the companies operating these four 

facilities provided emission estimates (which matched the totals in Table 1 reported to TRI) in 
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correspondence in the summer of 2009.59,60, 61 Later in 2009, EPA requested documentation of 

these emission estimates using their authority under section 114 of the Clean Air Act. In 

February of 2010, this documentation was submitted to the EPA.62,63,64

Table 1. Mercury Air Releases Reported in TRI for 2007 and 2008

This information, which 

is available in Docket EPA-HQ-OAR-2002-0017, was carefully reviewed. More discussion on 

the conclusions of this review is provided below.

Plant

TRI Mercury Air Releases (pounds/yr)

2007 2008

Fugitive Stack Total Fugitive Stack Total

ASHTA 0.0 0.0 0.0 0.0 0.2 0.2

OLIN-GA 119 5 124 77 9 86

OLIN-TN 353 67 420 241 43 285

PPG 145 55 200 149 58 207

Summary of Reported Facility Emissions and Supporting Information

ASHTA

As shown in Table 1, ASHTA reported no mercury releases to the air in 2007 and 

0.2 pounds in 2008. In the June 30, 2009 correspondence, ASHTA submitted emission estimates 

for 2007 and 2008. The estimates for 2008 were consistent with those in the 2008 TRI. For 

 59 Letter. Jackson, R.L., ASHTA Chemicals Inc., to Jones, D.L., U.S. Environmental Protection Agency. RE: 

Docket No. EPA-HQ-OAR-2002-0017 – —National Emission Standards for Hazardous Air Pollutants: Mercury 

Emissions from Mercury Cell Chlor-Alkali Plants – —ASHTA Chemicals Inc. Comments and Rebuttal on 

Recent EC/R Study. June 30, 2009. 60 Letter. Hall, R.K., Olin Chlor Alkali Products, to Jones, D.L., U.S. Environmental Protection Agency. June 25, 

2009. 61 Letter. Smith, T.P., PPG Industries, Inc., to Jones, D.L., U.S. Environmental Protection Agency. Re: Docket 

No. EPA-HQ-OAR-2002-0017 – —National Emission Standards for Hazardous Air Pollutants: Mercury 

Emissions from Mercury Cell Chlor-Alkali Plants – —Memo: “Updated Cost Impacts Associated with the 

Conversion from Chlorine Production Utilizing Mercury Cell Chlor-Alkali Technology to Membrane Cell 

Technology,” from Heather P. Brown, P.E. (EC/R Inc.) to Donna Lee Jones, PhD (USEPA), dated June 5, 2009.” 

July 13, 2009. 62 Letter. Jackson, R.L., ASHTA Chemicals Inc., to Jones, D.L., U.S. Environmental Protection Agency. RE: 

Docket Response to USEPA Questions. February 15, 2010. 63 Letter. Hall, R.K., Olin Chlor Alkali Products, to Jones, D.L., U.S. Environmental Protection Agency. Re: 

Information requested pursuant to section 114 of the Clean Air Act. February 2, 2010. 64 Letter. Smith, T.P., PPG Industries, Inc., to Jones, D.L., U.S. Environmental Protection Agency. Re: Response 

to Request for Information under Section 114 of the Clean Air Act, 42 U.S.C. § 7414, dated December 4, 2009, 

with regards to the Mercury Cell Chlor-Alkali MACT and background data to support the estimates provided to 

USEPA by PPG in a letter dated July 13, 2009.” February 18, 2010.

Inserted Cells
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2007, ASTA reported 0.12 pounds of point source emissions. Consistent with the TRI, they 

reported “0 (Trace) lbs./yr” fugitive emissions for both 2007 and 2008.

The EPA section 114 requested documentation for the point source emissions reported in 

the June 30, 2009 correspondence. It also questioned the report that the fugitive emissions are 

zero and requested that ASHTA provide a “precise, substantiated, fugitive emissions estimate.”

In their February 15, 2010 response ASHTA provided details of the calculation of 

the point source (i.e., stack) emissions. ASHTA conducted emissions tests on their hydrogen and 

cell end box air emission streams in March 2006, and they provided a copy of the report for this 

testing. ASHTA using the periodic testing alternative to demonstrate compliance with the 

emission limitation for by-product hydrogen streams and end-box ventilation systems, which 

means that they perform tests three times per week. They use alternative methods for this testing 

which have been approved by EPA. Results for each of the tests conducted in 2007 and 2008 

were provided, along with the 52-week rolling average calculations.

The calculations show point source mercury emissions of 0.09 pounds in 2007 

and 0.11 pounds in 2008. These estimates are lower than previously reported because the earlier 

estimates included emissions from a noncontact cooling tower and not from the mercury cell 

process.

ASHTA did not provide any fugitive emission estimates in response to EPA’s 

request. They indicated that, since EPA does not have an approved method for estimating 

fugitive mercury emissions from a mercury cell chlor-alkali plant, they cannot provide emission 

estimates. ASHTA indicated that the zero emissions levels reported were determined from the 

annual mercury balance, the low floor level mercury levels, and the operation of mercury control 

systems. They said that they are “confident that the fugitive emissions collection system 

installed on the cell room removes large amounts of off-process mercury emissions” but they are 

“unable to provide the level of conclusion with any direct measurements.” The EPA estimate of 

these emissions is discussed at the end of this section.

OLIN

The mercury emission estimates provided in Olin’s June 25, 2009 correspondence 

for 2007 and 2008 were consistent with those reported in the TRI for both their Augusta, 

Georgia, and Charleson, Tennessee facilities. In their February 2, 2010 correspondence, they 

provided documentation for these estimates.

At both facilities, Olin utilizes continuous mercury emission monitoring systems.

These units were produced by Mercury Instruments GmbH Analytical Technologies of Germany, 
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and are equipped with factory supplied calibration gas generators. Zero calibrations are 

performed every hour the units are in operation as well as span checks at least once per day.

These units measure and record the mercury concentrations for both the point sources and 

throughout the cell rooms. Stack velocity/flow rates are monitored for the point sources, and cell 

room flow rates are estimates using engineering equations.

For the point sources, Olin provided daily emission results for each point source, 

along with detailed ten-minute readings for representative days to illustrate how the daily 

emissions were determined. For the fugitive emissions, Olin provided daily measured 

concentrations, estimated flow rates, and emissions. They also provided detailed calculation 

sheets illustrating how the emissions were calculated.

PPG

In their July 13, 2009 correspondence, PPG indicated that the mercury stack air 

releases in the TRI include 50 pounds/yr from coal-fired boilers at the site. Therefore, they 

indicated that the 2007 stack emissions from the mercury cell chlor-alkali plant should be 5 

pounds for 2007 and 8 pounds for 2008. The fugitive emission estimates reported in this 

correspondence were consistent with those reported to TRI for 2007 (145 pounds) and 2008 (149 

pounds). Therefore, PPG’s mercury emissions from mercury cell operations total 150 pounds in 

2007 and 157 pounds in 2008.

For their three point sources (Hydrogen De-gas inlet box ventilation system, 

Chlorine De-gas end box ventilation system, and Hydrogen Purification system), PPG operates 

continuous mercury emission monitors to measure the mercury concentration and flow meters to 

monitor the flow rate. In their February 28, 2010 correspondence PPG provided daily average 

measured concentrations, flow rates, and emission rates for 2007 and 2008. They also provided 

equations illustrating the calculations performed.

PPG also utilizes a continuous mercury monitoring system to measure mercury 

concentration throughout the cell room, and estimates the flow rate from the building based on 

the number of roof exhaust fans operating. They provided average cell room concentrations, 

flow rates, and emission rates for each day in 2007 and 2008. They also provided equations 

illustrating the calculations performed.

PPG has entered into an agreement with the Attorney General of Maryland 

regarding their West Virginia facility. As part of this agreement, PPG will limit mercury 

emissions to no more than 150 pounds/yr in 2011 and 2012, and no more than 145 pounds/yr in 
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2013 and beyond. Therefore, in 2011 and 2012 there will be around a 2 percent decrease from 

the average 2007/2008 levels and around a 6 percent decrease in 2013 and beyond.

Estimating Fugitive Emissions for ASHTA

Because ASHTA did not provide data documenting and substantiating their claim 

of zero fugitive emission estimates, we estimated their fugitive emissions since it is not 

reasonable to assume there are no emissions. The approach we used was to develop a fugitive 

emissions factor based on the amount of mercury contained in their cells. Since a previous 

analysis found little correlation between chlorine production and fugitive mercury emissions,65

We developed the emissions factor for fugitive mercury emissions based on the estimated 

amount of mercury in the cells for the other three facilities and used this factor to estimate 

ASHTA’s fugitive mercury emissions. These data are shown in Table 2. The data used to 

calculate the average factor, at approximately 0.5 pounds of fugitive mercury emissions per year 

per ton of mercury in the cells, shows reasonable agreement between the factors developed for 

the three other mercury cell facilities.

this other approach was not considered viable.

At ASHTA, there are 24 mercury cells.66

Table 2. Development of Fugitive Mercury Emissions Factor Based on Mercury in Cells

Multiplying this number of cells by the average 

factor shown in Table 2 results in an estimated fugitive mercury emission estimate of 62 pounds 

per year for ASHTA. For purposes of estimating the emissions for the whole industry, this value 

was used for both the 2007 and 2008 in this analysis.

Plant

Number 

of Cellsa

Mercury 

in Cellsb

(tons)

Fugitive Mercury Emissions 

(lb/yr)

Fugitive Emissions-toCell Mercury Factor 

(lb/yr emissions per ton 

2007 2008 Avg mercury in cells)

OLIN—GA 60 298 124 86 105 0.33576

OLIN—TN 106 527 420 284 352 0.63712

PPG—WV 54 268 145 149 147 0.52229

Average 0.49839

a From 1997 Directory of Chemical Producers (Reference 67

 65 U.S. Environmental Protection Agency, Office of Air Quality Planning and Standards, Research Triangle Park, 

NC. “Summary of 2005 Cell Room Mercury Emissions Data for Occidental Chemical Company Mercury Cell 

Chlor-Alkali Plants: Delaware City, Delaware and Muscle Shoals, Alabama.” March 2008.

).

66 Reference 8. 67 1997 Directory of Chemical Producers—United States of America. Stanford Research Institute International. 

Menlo Park, CA. 1997.
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b Using a factor of 5.2 tons of mercury per cell, which is the amount of mercury in the Chlorine Institute’s 2008 

process inventory (1,376 tons) divided by the number of operating cells in 2008 (264) (Reference 68

Summary of Baseline Air Emissions

).

Table 3 summarizes the mercury emissions from the four currently operating 

mercury cell chlor-alkali plants for 2007 and 2008.

Table 3. Baseline Mercury Emission Levels

Plant

Mercury Emissions (pounds per year)

2007 2008 Average 2007–2008

Point Fugitive Total Point Fugitive Total Point Fugitive Total

ASHTA 0.09 62 62 0.11 62 62 0.10 62 62

OLIN—GA 5 124 129 9 86 95 7 105 112

OLIN—TN 67 420 487 43 284 327 55 352 407

PPG 5 145 150* 8 149 157* 7 147 154

Total 77 751 828 60 581 641 69 666 735

Note: PPG’s emissions is limited by a court settlement to 150 pounds per year in 2001 and 2012, and 145 pounds per 

year in 2013 and thereafter.

BASELINE NONAIR MERCURY RELEASES

Table 4 shows the nonair mercury releases reported to the TRI for 2007 and 

2008. These releases include the total amount of mercury released to water or land on or at a 

facility’s site and the amount that is transferred from a facility site to another site and then 

released to the environment via water or land. Attachment 1 includes a detailed analysis of TRI 

mercury release data for these four facilities.

Table 4. Total Nonair Mercury Releases Reported in the TRI

Plant

Total Nonair Mercury Releases (pounds/year)

2007 2008 Average

ASHTA 202 179 190

OLIN -GA 82 105 93

OLIN -TN 414 197 306

PPG 1,408 751 1,080

Total 2,106 1,232 1,669

 68 The Chlorine Institute, Inc. “Chlor-Alkali Industry 2008. Mercury Use and Emissions in the United States 

(Twelfth Annual Report).” August 2009.
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WASTE GENERATION FROM CLEANUP/DECOMMISSIONING

In addition to the elimination of the routine mercury releases discussed above, 

there would be one-time environmental impacts associated with the clean-up and 

decommissioning of the mercury cell chlor-alkali plants. The discussion and quantification of 

these impacts are discussed below.

Table 2. Development of Fugitive Mercury Emissions Factor Based on Mercury in Cells

Plant

Number 

of Cellsa

Mercury in 

Cellsb

(tons)

Fugitive Mercury Emissions 

(lb/yr)

Fugitive 

Emissions-to-Cell 

Mercury Factor 

(lb/yr emissions per 

ton mercury in cells)

2007 2008 Avg

OLIN – GA 60 298 124 86 105 0.33576

OLIN – TN 106 527 420 284 352 0.63712

PPG - WV 54 268 145 149 147 0.52229

Average 0.49839

a From 1997 Directory of Chemical Producers (Reference 69

b Using a factor of 5.2 tons of mercury per cell, which is the amount of mercury in the Chlorine Institute’s 2008 

process inventory (1,376 tons) divided by the number of operating cells in 2008 (264) (Reference 

).

70).

Table 3. Baseline Mercury Emission Levels

Plant

Mercury Emissions (pounds per year)

2007 2008 Average 2007 – 2008

Point Fugitive Total Point Fugitive Total Point Fugitive Total

ASHTA 0.09 62 62 0.11 62 62 0.10 62 62

OLIN – GA 5 124 129 9 86 95 7 105 112

OLIN – TN 67 420 487 43 284 327 55 352 407

PPG 5 145 150* 8 149 157* 7 147 154

Total 77 751 828 60 581 641 69 666 735

Note: PPG’s emissions is limited by a court settlement to 150 pounds per year in 2001 and 

2012, and 145 pounds per year in 2013 and thereafter.

Table 4. Total Nonair Mercury Releases Reported in the TRI

 69 1997 Directory of Chemical Producers – United States of America. Stanford Research Institute International. 

Menlo Park, CA. 1997. 70 The Chlorine Institute, Inc. “Chlor-Alkali Industry 2008. Mercury Use and Emissions in the United States 

(Twelfth Annual Report).” August 2009.
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Plant

Total Nonair Mercury Releases (pounds/year)

2007 2008 Average

ASHTA 202 179 190

OLIN -GA 82 105 93

OLIN -TN 414 197 306

PPG 1,408 751 1,080

Total 2,106 1,232 1,669

When cell rooms are closed and decommissioned, there will be some loss of 

mercury to the environment. The extent of the loss will be influenced by cell room design and 

geographic location. However, once the cells are shut down, the cell room temperature will 

decrease, and the evaporation rate of any exposed mercury is reduced.71

There is little quantitative information available to estimate the amount of 

mercury-containing waste that would need to be disposed of during cleanup/decommissioning.

When the Borregaard mercury cell chlor-alkali plant in Norway was decommissioned, a large 

number of samples were taken to determine the quantity of mercury-contaminated wastes. The 

total quantity of contaminated waste material was estimated at 1,750 cubic meters, of which 

around 55 percent was contaminated process equipment such as steel and rubber-lined steel.

Therefore, we estimated 

that there would not be measured mercury air emissions during cleanup/decommissioning.

72

However, information available for the Borregaard plant provided no estimate of 

the mass amount of mercury in the wastes. In order to obtain an estimate of the potential mass, 

the release information in the TRI was examined for closed or converted facilities. There are six 

former mercury chlor-alkali plants in the TRI that have at least five years worth of release data to 

analyze. For each of these facilities, the average air releases during the years prior to the last 

year for which release data were reported in the TRI was compared to the air releases in the last 

year. If those air releases in the last year were less than 50 percent of the average air releases for 

the previous years for which TRI releases were reported, it was assumed that the mercury cell 

plant had ceased operations during that year and was in the process of cleanup/decommissioning.

For those situations, the ratio of the offsite transfers during that year was calculated to represent 

an estimate of the amount that offsite transfers could increase during cleanup/decommissioning.

This information is summarized in Table 5. 

Assuming this level of waste is representative, this would mean approximately 7,000 cubic 

meters of waste could be generated during the conversion/closure of the four currently operation 

U.S. plants.

 71 European Commission. Integrated Pollution Prevention and Control (IPPC). Reference Document on Best 

Available Techniques in the Chlor-Alkali Manufacturing Industry. December 2001. p. 96 72 Reference 11, pp. 93, 97.
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Table 5.In order to estimate the mercury contaminated wastes that would be generated 

during cleanup/decommissioning and transferred offsite for the four currently operating mercury 

cell chlor-alkali plants, the average level of nonair releases for reported for all years of operation

are multiplied by 253 percent. These estimates are shown in Table 6.

Therefore, it is estimated that the closure/conversion of the four currently operating 

mercury cell chlor-alkali plants in the U.S. could result in the generation of around 7,000 cubic 

meters of hazardous wastes containing over 6 tons of mercury. Given the unique aspects of each 

mercury cell plants, the extreme paucity of specific data on the wastes generated during mercury 

cell closures/conversions, and the major assumptions in this analysis, there is significant 

uncertainty in these estimates.

Table 5. Summary of TRI Information Used to Estimate Mercury 

Cleanup/Decommissioning Wastes

Plant

Last 

Yr

Air Mercury Releases 

(pounds/yr)

Offsite Mercury Transfers 

(pounds/yr)

Avga Last Yr

Last 

Year ÷ 

Avg Avga Last Yr

Last 

Year ÷ 

Avg

WESTLAKE

CALVERT 

CITYWestlake

Calvert City, KY

2002 983 6 1% 10,108 27,777 275%

OCCIDENTAL

MUSCLE 

SHOALSOccidental

Muscle Shoals, AL

2008 667 322 48% 4,405 12,806 291%

OCCIDENTAL

NEW 

CASTLEOccidental

New Castle, DE

2008 649 0.4 0% 3,166 16,520 522%

HOLTRACHEM

ORRINGTONHoltrache

m

Orrington, ME

1999 660 116 18% 2,103 1,612 77%

HOLTRACHEM

REIGELWOODHoltrach

em

Reigelwood, NC

1999 1,176 328 28% 171 176 103%

PPG

WESTLAKE

Westlake, LA

2005 997 1,211 121% b b b

Average 253%

a Avg = average of all years for which data were reported except for the last year.

Inserted Cells
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b Since the air releases in the last reporting year were greater than 50 percent of the average for the previous years, 

it was assumed that the plant was operating during this year and the offsite transfers did not represent 

cleanup/decommissioning activities.

In order to estimate the mercury contaminated wastes that would be generated during 

cleanup/decommissioning and transferred offsite for the four currently operating mercury cell 

chlor-alkali plants, the average level of nonair releases for reported for all years of operation are 

multiplied by 253 percent. These estimates are shown in Table 6.

Therefore, it is estimated that the closure/conversion of the four currently operating 

mercury cell chlor-alkali plants in the U.S. could result in the generation of around 7,000 cubic 

meters of hazardous wastes containing over 6 tons of mercury. Given the unique aspects of each 

mercury cell plants, the extreme paucity of specific data on the wastes generated during mercury 

cell closures/conversions, and the major assumptions in this analysis, there is significant 

uncertainty in these estimates.

Table 6. Estimated Cleanup/Decommissioning Wastes for Mercury Cell Plants

Plant

Average Reported Nonair Releases

Over All Years (pounds/yr)

Estimated Cleanup/

Decommissioning Wastes (pounds/yr)

Plant

Average Reported Nonair Releases

Over All Years (pounds/yr)

Estimated Cleanup/

Decommissioning Wastes (pounds/yr)

ASHTA 620 1,571

OLIN - —GA 1,264 3,203

OLIN – —TN 1,364 3,457

PPG 1,651 4,185

TOTAL 12,416

SUMMARY

If the four currently operating mercury cell chlor-alkali plants converted to 

membrane processes, the result would be the elimination of mercury emissions, the elimination 

of mercury releases to the water and other media, and the termination of the creation of mercurycontaminated wastes from the routine operation of the mercury cells. As discussed above, the 

estimated levels of these routine releases are:

• Mercury air emissions of between 600 and 800 pounds per year.

• Nonair mercury releases of between 1,200 and 2,000 pounds per year.

Inserted Cells
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During the cleanup and decommissioning, there will be mercury-contaminated wastes 

that will be created and that will need to be treated. A rough estimate is approximately 

7,000 cubic meters of waste created during this process that contains over six tons (12,000 lb) of 

mercury.

ATTACHMENT 1

Detailed Analysis of Toxic Release Inventory (TRI) Data

Detailed Analysis of Toxic Release Inventory (TRI) Data

MEMORANDUM

DATE: January 5, 2010

SUBJECT: Summary of Mercury Cell Chlor-Alkali Plant Mercury Releases Reported in the 

Toxics Release Inventory (TRI)

FROM: Phil Norwood, EC/R

TO: Dr. Donna Lee Jones, EPA/OAQPS/SPPD/MMG 

The purpose of this memo is to present mercury release information from EPA’s

Toxics Release Inventory (TRI) (http://www.epa.gov/tri/) from the four currently operating 

mercury cell chlor-alkali plants in the U.S.. These plants are ASHTA Chemicals in Ashtabula, 

Ohio (ASHTA), Olin Corporation in Augusta, Georgia (OLIN-GA), Olin Corporation in 

Charleston, Tennessee (OLIN-TN), and PPG in New Martinsville, West Virginia (PPG). In 

addition to presenting historical release information, the final section presents what are estimated 

to be “typical” annual levels of Nonair mercury releases that would be eliminated in the event 

that these facilities ceased to operate.

TRI MERCURY RELEASE INFORMATION

These four mercury cell chlor-alkali plants have been operating since the 1970s. 

The TRI contains mercury release data beginning in 1988. Attachment 1 contains annual release 

information for each of the four plants for the 21 years from 1988 to 2008. Table 1 shows the 

sum of the average annual releases from these four plants for the entire 21-year period, the most 

recent ten years (1999 – –2008), and the most recent two years (1997 and 1998), and Figure 1 

shows the 21 year trends for total mercury releases for each of the four plants. Table 2 provides 

more detailed plant-specific averages. As can be seen in Tables 1 and 2, Figure 1, and 
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Attachment A, mercury releases from these four mercury cell chlor-alkali plants have steadily 

decreased in the 21 year period from 1988 to 2008.

There appears to be an anomaly in the offsite releases for the PPG facility in 2001 

(see Figure 1 and Attachment A). In 2001, PPG reported almost 17,000 pounds released offsite 

(While not shown in the table, the specific release reported was attributed to “Offsite 

Landfill/Surface Impoundment). This value is over 12 times higher than the next highest level of 

offsite mercury release for any year in the 10-year period. We believe it is reasonable to assume 

the activities in 2001 that resulted in this large release represent a unique and nonroutine event. 

Therefore, the PPG average release for the period 1999 – –2008 was calculated excluding the 

2001 values, and a separate total of the plant-specific averages calculated. This was shown in 

Table 2. Therefore, both the 10-year total and the 2007-–2008 total Nonair releases were just 

under 2,000 pounds per year.

Table 1. Total Average Mercury Releases from Mercury Cell Chlor-Alkali Plants

Period

Sum of Average Mercury Releases

(pounds/yr)

Total Releases Total Air Releases Total Nonair Releases

1988 - –2008 9,410 4,510 4,900

1999 - –2008 6,839 3,459 3,380

2007 - –2008 2,331 661 1,669

Note: These plants are ASHTA Chemicals in Ashtabula, Ohio (ASHTA), Olin Corporation in Augusta, Georgia 

(OLIN-GA), Olin Corporation in Charleston, Tennessee (OLIN-TN), and PPG in New Martinsville, West 

Virginia (PPG). 

Table 2. Average Mercury Release Values
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Table 2. Average Mercury Release Values
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Average Mercury Releases (pounds/yr)

Total 

(On & Off Site)

Total Nonair 

(On & Off Site) Onsite Air

Onsite 

Nonair Onsite Water Offsite

21-Year Average (1988 - –2008)

ASHTA 1,875 620 1,255 102 2 518

OLIN –GA 2,263 1,264 1,000 10 10 1,254

OLIN –TN 2,583 1,364 1,218 1,333 21 31

PPG 2,689 1,651 1,037 60 59 1,591

Total of Averages 9,410 4,900 4,510 1,505 92 3,394

Total of Averages (excluding PPG 2001) 8,646 4,148 4,498 1,507 94 2,641

10-Year Average (1999 - –2008)

ASHTA 1,096 212 885 0 0 212

OLIN –GA 761 106 655 10 10 96

OLIN –TN 1,716 648 1,068 584 11 64

PPG 3,265 2,414 852 27 25 2,387

Total of Averages 6,839 3,380 3,459 621 46 2,759

Total of Averages (excluding PPG 2001) 5,207 1,794 3,413 621 46 1,173

2007 – –2008 Average

ASHTA 191 190 0 0 0 190

OLIN -GA 199 93 105 11 11 82

OLIN -TN 658 306 352 305 7 1

PPG 1,283 1,080 204 23 23 1,057

Total 2,331 1,669 661 340 41 1,329
***E.O. 12866 Review – Revised Version – Do Not Cite, Quote, or Release During Review***

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ATTACHMENT A. Annual Mercury Release Data from TRI 1988 – –2008

Facility Year

Mercury Releases Reported in TRI (pounds/yr)

Onsite Releases

Off Site 

Releases

Total 

Releases (On 

& Off Site)

Total Nonair

Releases

(On & Off Site)

Total 

Onsite 

Releases

Fugitive 

Air

Stack 

Air Total Air

Onsite 

Nonair Water Land

ASHTA 1988 1,569 1,046 516 1,562 7 6 1 1,877 3,446 1,884

ASHTA 1989 1,303 1,046 250 1,296 7 6 1 2,215 3,518 2,222

ASHTA 1990 1,804 1,046 750 1,796 8 6 2 0 1,804 8

ASHTA 1991 1,306 1,046 250 1,296 10 5 5 978 2,284 988

ASHTA 1992 1,653 1,046 595 1,641 12 7 5 792 2,445 804

ASHTA 1993 1,652 1,046 596 1,642 10 5 5 551 2,203 561

ASHTA 1994 2,871 1,046 614 1,660 1,211 6 1,205 1,177 4,048 2,388

ASHTA 1995 2,530 1,046 608 1,654 876 5 871 0 2,530 876

ASHTA 1996 1,658 1,046 607 1,653 5 5 0 524 2,182 529

ASHTA 1997 1,654 1,046 607 1,653 1 1 0 347 2,001 348

ASHTA 1998 1,653 1,046 607 1,653 0 0 0 297 1,950 297

ASHTA 1999 1,653 1,046 607 1,653 0 0 0 242 1,895 242

ASHTA 2000 1,390 1,046 344 1,390 0 0 0 219 1,609 219

ASHTA 2001 1,396 1,046 350 1,396 0 0 0 100 1,496 100

ASHTA 2002 1,395 1,046 349 1,395 0 0 0 173 1,568 173

ASHTA 2003 1,383 1,046 337 1,383 0 0 0 128 1,511 128

ASHTA 2004 813 464 349 813 0 0 0 134 947 134

ASHTA 2005 813 464 349 813 0 0 0 434 1,247 434

ASHTA 2006 2 0 2 2 0 0 0 306 308 306

ASHTA 2007 0 0 0 0 0 0 0 202 202 202
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ATTACHMENT A. Annual Mercury Release Data from TRI 1988 – –2008

Facility Year

Mercury Releases Reported in TRI (pounds/yr)

Onsite Releases

Off Site 

Releases

Total 

Releases (On 

& Off Site)

Total Nonair

Releases

(On & Off Site)

Total 

Onsite 

Releases

Fugitive 

Air

Stack 

Air Total Air

Onsite 

Nonair Water Land

ASHTA 2008 0 0 0 0 0 0 0 179 179 179

OLIN-GA 1988 1,329 1,048 271 1,319 10 10 0 6,014 7,343 6,024

OLIN-GA 1989 1,327 1,046 271 1,317 10 10 0 2,129 3,456 2,139

OLIN-GA 1990 1,331 1,046 271 1,317 14 14 0 4,730 6,061 4,744

OLIN-GA 1991 1,285 1,000 270 1,270 15 15 0 5,740 7,025 5,755

OLIN-GA 1992 1,329 1,046 271 1,317 12 12 0 5,933 7,262 5,945

OLIN-GA 1993 1,324 1,046 271 1,317 7 7 0 712 2,036 719

OLIN-GA 1994 1,328 1,046 271 1,317 11 10 1 23 1,351 34

OLIN-GA 1995 1,325 1,046 271 1,317 8 8 0 23 1,348 31

OLIN-GA 1996 1,324 1,046 271 1,317 7 7 0 8 1,332 15

OLIN-GA 1997 1,323 1,046 271 1,317 6 6 0 5 1,328 11

OLIN-GA 1998 1,326 1,046 271 1,317 9 9 0 50 1,376 59

OLIN-GA 1999 1,245 1,046 189 1,235 10 10 0 23 1,268 33

OLIN-GA 2000 730 562 157 719 11 11 0 21 751 32

OLIN-GA 2001 773 608 158 766 7 7 0 39 812 46

OLIN-GA 2002 746 585 154 739 7 7 0 282 1,028 289

OLIN-GA 2003 742 563 169 732 10 10 0 114 856 124

OLIN-GA 2004 753 563 182 745 8 8 0 36 789 44

OLIN-GA 2005 835 563 261 824 11 11 0 136 971 147

OLIN-GA 2006 591 493 86 578 13 13 0 149 740 162
***E.O. 12866 Review – Revised Version – Do Not Cite, Quote, or Release During Review***

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ATTACHMENT A. Annual Mercury Release Data from TRI 1988 – –2008

Facility Year

Mercury Releases Reported in TRI (pounds/yr)

Onsite Releases

Off Site 

Releases

Total 

Releases (On 

& Off Site)

Total Nonair

Releases

(On & Off Site)

Total 

Onsite 

Releases

Fugitive 

Air

Stack 

Air Total Air

Onsite 

Nonair Water Land

OLIN-GA 2007 138 119 5 124 14 14 0 68 206 82

OLIN-GA 2008 96 77 9 87 9 9 0 96 192 105

OLIN-TN 1988 4,421 1,046 282 1,328 3,093 26 3,067 0 4,421 3,093

OLIN-TN 1989 5,750 1,045 249 1,294 4,456 25 4,431 0 5,750 4,456

OLIN-TN 1990 5,236 1,045 240 1,285 3,951 25 3,926 5 5,241 3,956

OLIN-TN 1991 3,780 1,045 378 1,423 2,357 22 2,335 12 3,792 2,369

OLIN-TN 1992 4,353 1,045 180 1,225 3,128 17 3,111 3 4,356 3,131

OLIN-TN 1993 2,777 1,045 192 1,237 1,540 26 1,514 0 2,777 1,540

OLIN-TN 1994 1,704 1,045 464 1,509 195 53 142 0 1,704 195

OLIN-TN 1995 1,719 1,045 488 1,533 186 43 143 0 1,719 186

OLIN-TN 1996 1,868 1,045 249 1,294 574 40 534 0 1,868 574

OLIN-TN 1997 2,165 1,045 428 1,473 692 31 661 0 2,165 692

OLIN-TN 1998 3,279 1,045 255 1,300 1,979 15 1,964 0 3,279 1,979

OLIN-TN 1999 2,640 1,045 584 1,629 1,011 13 998 0 2,640 1,011

OLIN-TN 2000 2,185 1,045 369 1,414 771 7 764 1 2,186 772

OLIN-TN 2001 2,126 1,045 85 1,130 996 8 988 0 2,126 996

OLIN-TN 2002 2,137 1,045 85 1,130 1,007 14 993 375 2,512 1,382

OLIN-TN 2003 1,711 1,046 85 1,131 580 18 562 26 1,737 606

OLIN-TN 2004 1,455 1,049 105 1,154 301 14 287 30 1,485 331

OLIN-TN 2005 1,517 1,046 204 1,250 267 12 255 5 1,522 272
***E.O. 12866 Review – Revised Version – Do Not Cite, Quote, or Release During Review***

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ATTACHMENT A. Annual Mercury Release Data from TRI 1988 – –2008

Facility Year

Mercury Releases Reported in TRI (pounds/yr)

Onsite Releases

Off Site 

Releases

Total 

Releases (On 

& Off Site)

Total Nonair

Releases

(On & Off Site)

Total 

Onsite 

Releases

Fugitive 

Air

Stack 

Air Total Air

Onsite 

Nonair Water Land

OLIN-TN 2006 1,440 1,032 109 1,141 299 13 286 198 1,638 497

OLIN-TN 2007 834 353 67 420 414 8 406 0 834 414

OLIN-TN 2008 481 241 43 285 196 6 191 1 482 197

PPG 1988 1,500 1,000 250 1,250 250 250 0 4,300 5,800 4,550

PPG 1989 1,500 1,000 250 1,250 250 250 0 750 2,250 1,000

PPG 1990 1,500 1,000 250 1,250 250 250 0 250 1,750 500

PPG 1991 1,145 1,000 85 1,085 60 60 0 1,800 2,945 1,860

PPG 1992 1,163 1,045 85 1,130 33 33 0 250 1,413 283

PPG 1993 1,152 1,045 85 1,130 22 22 0 1,340 2,492 1,362

PPG 1994 1,256 1,045 193 1,238 18 18 0 230 1,486 248

PPG 1995 1,266 1,045 192 1,237 29 29 0 250 1,516 279

PPG 1996 1,275 1,045 190 1,235 40 40 0 191 1,466 231

PPG 1997 1,254 1,045 188 1,233 21 21 0 102 1,356 123

PPG 1998 1,258 1,045 189 1,234 24 24 0 80 1,338 104

PPG 1999 1,254 1,045 187 1,232 22 22 0 62 1,316 84

PPG 2000 1,239 1,045 182 1,227 12 12 0 93 1,332 105

PPG 2001 1,301 1,045 227 1,272 29 29 0 16,658 17,959 16,687

PPG 2002 1,267 1,045 188 1,233 34 34 0 900 2,167 934

PPG 2003 1,238 1,045 177 1,222 16 16 0 1,130 2,368 1,146

PPG 2004 1,248 1,045 171 1,216 32 32 0 1,145 2,393 1,177
***E.O. 12866 Review – Revised Version – Do Not Cite, Quote, or Release During Review***

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ATTACHMENT A. Annual Mercury Release Data from TRI 1988 – –2008

Facility Year

Mercury Releases Reported in TRI (pounds/yr)

Onsite Releases

Off Site 

Releases

Total 

Releases (On 

& Off Site)

Total Nonair

Releases

(On & Off Site)

Total 

Onsite 

Releases

Fugitive 

Air

Stack 

Air Total Air

Onsite 

Nonair Water Land

PPG 2005 425 169 231 400 25 25 0 657 1,082 682

PPG 2006 356 172 134 306 50 34 0 1,115 1,471 1,165

PPG 2007 230 145 55 200 30 30 0 1,378 1,608 1,408

PPG 2008 223 149 58 207 16 16 0 735 958 751
***E.O. 12866 Review – Revised Version – Do Not Cite, Quote, or Release During Review***

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APPENDIX B:

Appendix B:

EMISSIONS REDUCTIONS ASSOCIATED WITH REDUCED MERCURY CELL 

CHLOR-ALKALI PLANT ELECTRICITY CONSUMPTION FOR MERCURY 

CELL CHLOR-ALKALI PLANTS

RTI estimatedAs discussed in Section 3 of the RIA, EPA analysis estimates that 

electricity requirements may be 700 to 1,211 kWh per short ton of chorine lower after 

conversion, which corresponds to a 22% and 37.5% reduction in electricity consumption, 

respectively.73

Table B-1. Estimated Changes in Electricity Consumption

Using the range of estimates and plant chlorine capacities, EPA calculated 

changes in the annual electricity consumption for four chlorine plants: OLIN Corporation 

(facilities in Augusta, GA and Charleston, TN), PPG Industries (New Martinsville, VA), and 

ASHTA Chemicals (Ashtabula, OH). EPA provided capacity and kWh requirements per ton of 

chlorine. RTI assumes 10% of power is lost during transmission (friction/heat, electromagnetic 

fields etc.). As a result, the power plant needs to generate approximately 10% more energy 

(and emissions) than are directly indicated by the reduction in energy consumption at the 

production plant. To account for this, we divided the kWh reductions by 0.9 (electricity 

generated = electricity consumed / (1-fraction transmission loss)).WV), and ASHTA Chemicals 

(Ashtabula, OH). This corresponds to a reduction of approximately 350 million kilowatt hours 

per year of reduced electricity consumption associated with converting the four existing 

mercury chlor-alkali plants to membrane cells.

Due to transmission and distribution losses, electrical generating units (EGU) supplying 

the electricity grid need to generate more electricity (and emissions) to meet each plant’s 

electricity consumption. EPA has assumed approximately 10% of power is lost during 

transmission and distribution. This factor is commonly used to approximate losses and selected 

using professional judgment. To account for the possible losses and convert consumption 

changes to equivalent electricity generation changes, we divided the kWh consumption 

reductions by 0.9 (electricity generated = electricity consumed / (1-fraction transmission and 

 73 As discussed in Section 3, EPA believes that the 22 percent electricity reduction represents is the best estimate of 

reduced electricity demand, but we provide estimates based on the 37.5 percent electricity reduction to represent the 

data provided by Oceana.
***E.O. 12866 Review – Revised Version – Do Not Cite, Quote, or Release During Review***

B-B-2

distribution loss)) (Table B-1). Therefore, the total amount of reduced electricity generation 

associated with converting the four existing mercury chlor-alkali plants to membrane cells is 

estimated to be 375 million kilowatt hours per year. Depending on assumed capacity factors, 

this is approximately equivalent to the electricity produced annually by a 40 to 60 megawatt 

power plant. 

B.1 Share of Electricity Generation by Fuel Type

EPA recognizes there are alternative methods for determining electricity generation by 

fuel type (i.e., the fuel mix that produced the electricity). As a result, we have documented the 

results and sources of the information to allow comparisons with the other methods (e.g., use of 

NERC region electricity grid generation statistics by fuel type). EPA’s analysis reviewed the 

Table B-1. Estimated Changes in Electricity Generation

Change in Electricity 

ConsumptionGeneration (kWh) for a

Chlorine Plant

Assumed 

Electricity 

Provider Capacity

22 % 

Consumption 

reduction a

37.5 % 

consumption 

reduction b

OLIN Corp. (Augusta, GA) Southern Company 47,421 36,883,000 63,807,590

OLIN Corp. (Charleston, TN) TVA 119,031 92,579,667 160,162,823

PPG Industries (New Martinsville, 

VAWV)

American Electric 

Power

262,451 189,839,557c 328,422,433c

ASHTA Chemicals (Ashtabula, OH) First Energy 72,848 56,659,556 98,021,031

Total 375,961,779 650,413,877

a Electricity Consumption = Capacity (tpy) × 700 (kwh/ton) / / (0.9). b Electricity Consumption = Capacity (tpy) × 1,211 (kwh/ton) / (0.9).

c PPG produces 70 percent of its electricity requirements. The remainderremaining 30 percent is purchased from 

Wheeling Electric Co., a subsidiary of American Electric Power.

For all but one plant, electricity is provided by local electric utilitylocation for the four facilities 

and used the Homeland Security Information Program (Gold), a multiple layer geospatial 

database, to identify the two closest power plants and companies (see Table B-1). DHS, 

2009).74

 74 http://proceedings.esri.com/library/userconf/feduc08/papers/hifld_hsip_overview_esri_feduc_feb_2008_jms.pdf

Using physical location information and engineering assessments EPA selected a 

power company that most likely provides the electricity to each plant (Table B-1, Column 2). In 

the case of PPG Industries New Martinsville, WV facility generates 70% of their electricity 
***E.O. 12866 Review – Revised Version – Do Not Cite, Quote, or Release During Review***

B-B-3

demand, while remaining 30%. Therefore, EPA assumes only 30% of the plant’s electricity 

requirements are provided by local utilityanother power company.

B.2 Electricity Generation by Fuel

For each power company, the share of electricity generation provided by fuel type is 

reported in Table B-2 presents the 2010 energy portfolios for utility companies that provided 

electricity to chlorine plants. RTI B-2. EPA collected thisthe latest historical information 

(2009) from electricity provider websites including annual reports75 and the engineering 

assessment considers it representative for the analysis year (2013) and the fuel mix of the 

electricity generated to meet the chlorine plants electricity requirements.

 75 American Electric Power.,(2009), First Energy (2009), Southern Company (2009). And the Tennessee Valley 

Authority (2009).
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Table B-2. Utility Company Energy Portfolios: 2010 Share of Electricity Generation by 

Fuel 2009

Assumed Electricity 

ProviderUtility Coal Gas Nuclear Hydro Purchased

Southern Company 57% 23% 16% 4% NA

TVA 46% 2% 23% 7% 13%

American Electric Power 88% 6% 5% 1% NA

First Energy 54% 12% 29% 3% NA

EPA’s eGrid database provided emission factors for NOX, SO2, CO2, and Hg (see 

attached XL spreadsheet). RTI calculated emission factors for pollutants for which EPA’s eGrid 

data was unavailable. The Co-Benefits Risk Assessment model (COBRA) provided total 

emissions estimates by fuel type and by pollutant for 2010. The COBRA model was developed 

by the U.S. Environmental Protection Agency (EPA) to be used as a screening tool that enables 

users to obtain a first-order approximation of benefits due to different air pollution mitigation 

policies. U.S. electricity production estimates by fuel type were obtained from EIA’s Annual 

Energy Outlook. RTI calculated emission factors by fuel type by dividing COBRA emissions 

estimates by EIA’s electricity production estimates. Emission estimates were calculated by 

multiplying electricity consumption estimates (Table B-1) by percentage production by fuel type 

from utility company energy portfolios (Table B-2) and by the emission factors (see XL 

spreadsheet). Emission reduction estimates equaling 22% are presented in Table B-3, while 

emission reduction estimates equaling 37% are presented in Table B-4.

Table B-3. Emission Reductions by Plant (22 percent reduction)

B.3 Emission Factors

EPA’s eGRID2007 Version 1.1 provided pollutant emission factors (e.g., short tons per 

kWh) for several pollutants, including NOX, SO2, CO2, and Hg, from EGUs in the U.S. (U.S. 
***E.O. 12866 Review – Revised Version – Do Not Cite, Quote, or Release During Review***

B-B-5

EPA, 2008).76

Table B-3. Power Company Emission Factors: Fuel=Coal (Short tons per kWh)

The emissions data contained within eGRID2007 Version 1.1 represents the year 

2005 and also includes operator, parent company, owner, and electric grid configuration as of 

December 31, 2007. It is the latest version available. eGRID2010 covering year 2007 data is 

expected to be published at the end of 2010. We applied the appropriate conversion factors to 

eGRID2007’s reported power company emissions factors in common units (short tons) 

(Table B-3 and Table B-4). The emissions data contained within eGRID reflect EPA’s Emissions 

Tracking System/Continuous Emissions Monitoring data. The engineering assessment considers the 

emissions factors representative and reasonable for the analysis given the physical location of 

chlorine plants and the power companies and the power companies fuel mix used to meet it 

customer’s electricity requirements.

Power Company

Emission 

Sources (Short 

Tons)NOX SO2 CO2 Hg

American Electric Power Co 1.72E-06 5.71E-06 9.71E-04 2.96E-11

First Energy Corp 1.64E-06 6.41E-06 1.03E-03 3.76E-11

Southern Company Services Inc 1.39E-06 6.41E-06 1.03E-03 2.60E-11

Tennessee Valley Authority 1.89E-06 4.50E-06 1.07E-03 2.15E-11

 76 The Emissions & Generation Resource Integrated Database (eGRID) is a comprehensive inventory of 

environmental attributes of electric power systems. The preeminent source of air emissions data for the electric 

power sector, eGRID is based on available plant-specific data for all U.S. electricity generating plants that 

provide power to the electric grid and report data to the U.S. government. eGRID integrates many different 

federal data sources on power plants and power companies, from three different federal agencies: EPA, the 

Energy Information Administration (EIA), and the Federal Energy Regulatory Commission (FERC). Emissions 

data from EPA are carefully integrated with generation data from EIA to produce useful values like pounds per 

megawatt-hour (lb/MWh) of emissions, which allows direct comparison of the environmental attributes of 

electricity generation. eGRID also provides aggregated data by state, U.S. total, company, and by three different 

sets of electric grid boundaries. For more information on eGRID, please see 

http://www.epa.gov/cleanenergy/energy-resources/egrid/index.html

Inserted Cells

Inserted Cells

Inserted Cells
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Table B-4. Power Company Emission Factors: Fuel=Natural Gas (Short tons per kWh)

Power Company NOX SO2 CO2

American Electric Power Co 1.48E-06 9.15E-09 6.30E-04

First Energy Corp 1.73E-07 2.45E-08 5.70E-04

Southern Company Services Inc 1.23E-07 2.68E-08 4.66E-04

Tennessee Valley Authority 1.14E-07 2.80E-09 4.86E-04

Emission factors could not be identified for PM2.5, NH3, and VOCs in eGRID. As a 

result, EPA calculated the emission factors using information from two different sources. The 

first source, Co-Benefits Risk Assessment model (COBRA), provided total U.S. emissions 

estimates by fuel type and by pollutant for 2010 (U.S. EPA, 2009).77

The second source, the EIA’s Annual Energy Outlook 2009 (Table 8), reports electricity 

supply, disposition, prices, and emissions and provides 2010 electricity generation (billion 

kWh) by fuel. EPA calculated emission factors by fuel type by dividing COBRA emissions 

estimates by the Energy Information Administration’s (EIA) electricity generation estimates 

(Table B-5) (EIA, 2009). 

The model contains 

detailed emissions estimates projected for the years 2010 and 2015 that were developed by EPA 

for its 2005 regulatory analysis of the Clean Air Interstate Rule (CAIR) (U.S. EPA, 2005). 

Emissions data undergoes quality assurance at both the state and federal level.

Table B-5. Emission Factor Calculations: 2010

Variable Coal Gas Petroleum

Generation (billion kWh) AEO 2009 

Electricity 2,057 814 56

Emissions (Short tons) COBRA Model 

PM2.5 506,294 6,696 17

NH3 390 1,762 0

 77 The Co–Benefits Risk Assessment (COBRA) screening model is a stand–alone Windows application that enables 

policy analysts to quickly obtain a first–order approximation of the costs and benefits of different emission 

scenarios and to compare outcomes in terms of changes in ambient particulate matter (PM) concentrations, 

related health effects, and monetary impacts. For more information on COBRA, please see 

http://www.epa.gov/statelocalclimate/resources/cobra.html
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VOC 36,135 5,360 0

Emission Factor (Short tons per kWh) EPA Calculations

PM2.5 2.46E-07 8.22E-09 3.02E-10

NH3 1.90E-10 2.16E-09 0

VOC 1.76E-08 6.58E-09 0

B.4 Emissions Reductions

Emission reductions were calculated in three steps. First, we allocate each change in 

electricity generation (Table B-1) by fuel source using the share data (Table B-2). The 

engineering assessment concluded it was reasonable to assume electricity demand declines 

proportionally for all fuel types. In reality, power companies would presumably reduce 

generation at the EGU with the highest average production costs. However, data was not 

available to refine the analysis. Next, we multiplied the generation reduction by fuel by the 

appropriate fuel emission factors (Tables B-3, B-4, B-5). Since the reductions in kWh 

requirements per ton of chlorine is uncertain, EPA considered two scenarios: a 22% reduction 

(Table B-6) and 37% reduction (Table B-7).

It is important to note that we assume that these emission reductions occur across the 

multiple EGUs associated with the presumed electricity provider. Although we identify the 

location of the mercury chlor alkali plant that would consume less electricity in the tables 

below, those locations do not reflect the location of the emission reductions from the EGUs. 

Because the emission reductions occur across multiple EGUs over a large geographic area, 

these estimates are representative of regional emission reductions. 
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Table B-6. Emission Reductions by Plant (22 percent reduction)

Emission Sources (Short Tons)

Chlorine Plant PM2.5 NH3 VOC NOX SO2 CO2 Hg

OLIN Corp. (Augusta, GA) 5.2 0.02 0.4 30.2 135.0 25,508 0.001

OLIN Corp. (Charleston, TN) 10.5 0.01 0.8 80.7 191.4 46,400 0.001

PPG Industries (New 

Martinsville, VAWV)

45.1 0.04 3.2 320.5 1,045.0 179,882 0.005

ASHTA Chemicals 

(Ashtabula, OH)

7.6 0.02 0.6 51.3 196.4 35,207 0.001

Total 68.4 0.10 5.0 482.6 1,567.8 286,997 0.008
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Table B-4. 7. Emission Estimates by Plant (37 percent reduction)

Emission Sources (Short Tons)

Chlorine Plant PM2.5 NH3 VOC NOX SO2 CO2 Hg

OLIN Corp. (Augusta, GA) 9.1 0.04 0.7 52.2 233.5 44,129 0.001

OLIN Corp. (Charleston, TN) 18.2 0.02 1.3 139.6 331.2 80,272 0.002

PPG Industries (New 

Martinsville, VAWV)

78.0 0.07 5.6 554.4 1,807.8 311,195 0.009

ASHTA Chemicals (Ashtabula, 

OH)

13.1 0.03 1.0 88.8 339.7 60,907 0.002

Total 118.3 0.17 8.7 835.0 2,712.3 496,504 0.014

B.5 Uncertainties

This appendix provides sufficient documentation to reproduce the calculations of 

emission reductions anticipated to occur as a result of this proposed regulation. In any complex 

analysis, there can be many sources of uncertainty that could affect the results, especially if the 

analysis involves predicting future behaviors. In addition, there are always analytical choices that 

could have incorporated alternate assumptions. Below, we include a qualitative discussion of 

some of the main sources of uncertainty, including the direction and general magnitude of the 

potential bias to the extent feasible given data limitations.

 There are several uncertainties associated with the estimate of reduced electricity 

demand. As shown in this appendix, assuming a 37.5% reduction as suggested by 

Oceana would nearly double the magnitude of the emission reductions.

 EPA has assumed a 10 percent transmission and distribution loss factor. In 2007, 

the national average transmission loss was 6.5%, but varied by state (EIA, 2008). 

Using the EIA reported value lowers emission reductions by approximately 2 

percent. 

 The underlying historical data from analyses/models represent different points of 

time (between 2005 and 2010). EPA has assumed they are reasonable 

representations of the analysis year (2013). To our knowledge, forecasts of 

portfolio mixes and emission factors for the analysis year are not readily 

available. Although it is possible that current year or projected data may more 

accurately reflect the regulatory scenario, this analysis is based on the best 

available data. 

 There are a variety of sources of uncertainty implicit within the emissions factors, 

including changes over time. For example, new emissions reduction technologies 
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may be introduced earlier than planned and reduce emission factors. Other 

regulations on EGUs may result in lower emissions factors in the future. In 

contrast, higher natural gas prices relative to fuels like coal may change power 

company generation portfolios with higher emission rates. To the extent the 

emissions factors are higher than those used, the current analysis understates 

emissions reductions. In contrast, if the emissions factors are lower, the current 

analysis overstates emissions reductions. 

 Since NOx and SO2 are covered by capped emissions trading programs, we're 

only estimating Pm2.5 emission reductions from reduced electricity demand.

 The analysis of energy savings assumes that the four facilities all convert rather 

than close. If one or more were to close, the reduction in electricity use would be 

greater at the facility (e.g., rather than a 22% reduction for the process there 

would be a 100% reduction). However, if the facility closing no longer provided 

chlorine and caustic, most of it would be produced elsewhere with an associated 

increase in electricity use in another place. Since this would have to be at a 

facility that uses a process similar to the one the closing facility would have 

converted to, the national electricity savings would be expected to be similar for 

either conversion or closure although the resulting pollution reductions would 

differ spatially. If closure of the process led to closing other processes being 

produced at the same facility, the same reasoning would apply. Therefore, it is 

likely that in the event of closure, the emissions reductions would be similar. 

However if prices increased as a result closure and overall quantities decreased 

then emission reductions would have been underestimated by the amount of 

emissions associated with the reduced production.

 There are other pre-existing conditions in electricity markets such as taxes and 

imperfect competition and taxes. EPA has only accounted for the externality 

associated with selected pollutant emissions reductions. While these other factors 

may influence benefit-cost analysis, we believe that they are likely to be small 

compared to the health effects associated with the emissions from the pollutants 

considered in the analysis. 

B.6 References

American Electric Power. 2009. Available on the internet at 

http://www.aep.com/investors/edgar/docs/AEP_10K_2009.pdf

First Energy. 2009. Available on the internet at 

http://investors.firstenergycorp.com/phoenix.zhtml?c=102230&p=irol-sec10k

Southern Company. 2009. Available on the internet at 

http://www.southerncompany.com/sotogo/SOtoGo.pdf

Tennessee Valley Authority. 2009. Available on the internet at 

http://www.tva.com/finance/reports/pdf/fy2009ar.pdf
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U.S. Department of Homeland Security. Homeland Security Information Program Gold (HSIP 

Gold), Version 2 (April 2007)

U.S. Energy Information Administration. 2008. State Electricity Profiles. Table 10. Available on 

the internet at 

http://tonto.eia.doe.gov/ftproot/electricity/stateprofiles/07st_profiles/062907.pdf

U.S. Energy Information Administration. 2009. Supplemental Tables to the Annual Energy 

Outlook 2010. Table 2. Available on the internet at 

http://www.eia.doe.gov/oiaf/aeo/aeoref_tab.html

U.S. Environmental Protection Agency (U.S. EPA). 2005. Clean Air Interstate Rule Emissions 

Inventory Technical Support Document. Office of Air Quality Planning and Standards. 

March. Available on the internet at http://www.epa.gov/CAIR/pdfs/finaltech01.pdf 

U.S. Environmental Protection Agency (U.S. EPA). 2008. The Emissions and Generation 

Resource Integrated Database for 2007 (eGRID2007) Technical Support Document. 

Office of Atmospheric Programs Climate Protection Partnerships Division. November. 

Available on the internet at 

http://www.epa.gov/cleanenergy/documents/egridzips/eGRID2007TechnicalSupportDoc

ument.pdf

U.S. Environmental Protection Agency (U.S. EPA). 2009. User’s Manual for the Co-Benefits 

Risk Assessment (COBRA) Screening Model. Climate Protection Partnerships Division 

State and Local Climate and Energy Programs. November. Available on the internet at 

http://www.epa.gov/statelocalclimate/documents/pdf/COBRA_manual.pdf