E.O. 12866 Ferroalloys RIA 2060-AQ11 Proposal 20111006



# Regulatory Impact Analysis (RIA) for the Proposed Manganese Ferroalloys RTR

Final ReportNovember 2011

Regulatory Impact Analysis (RIA) for th e Proposed Manganese Ferroalloys RTR

By: Larry Sorrels and Souad Benromdhane U.S. Environmental Protection Agency Office of Air Quality Planning and Standards (OAQPS) Air Economics Group (AEG) and Risk and Benefits Group (RBG) Research Triangle Park, NC 27711

U.S. Environmental Protection Agency Office of Air Quality Planning and Standards Health and Environmental Impacts Division Research Triangle Park, North Carolinaiii CONTENTS

Section Page

Table of Contents

Contents ...................................................................................................................... ............. iii

Section 1 Executive Summary ............................................................................................... 1-1

1.1 Analysis Summary ............................................................................................... 1-1

1.2 Organization of this Report .................................................................................. 1-2

Section 2 Introduction ........................................................................................................ .... 2-1

2.1 Background for Proposed Rule ............................................................................ 2-1 2.1.1 What is this source category a nd how did the MACT regulate its HAP emissions? ....................................................................................... 2-1

Section 3 Industry Profile .................................................................................................... .. 3-1

Section 4 Baseline Emissions, Emi ssion Reductions, And Costs .......................................... 4-1

4.1 Introduction .......................................................................................................... 4-1

Section 5 Economic Impact Analysis and St atutory and Executive Order Analyses ............ 5-1

5.1 Background .......................................................................................................... 5-1

5.2 Regulatory Flexibility Act ................................................................................... 5-1

5.3 Energy Impacts .................................................................................................... 5-2

5.4 Unfunded Mandates Reform Act ......................................................................... 5-3 5.4.1 Future and Disproportionate Costs ............................................................ 5-3 5.4.2 Effects on the National Economy ............................................................ 5-3iv 5.5 Executive Order 13045: Protection of Children from Environmental Health Risks and Safety Risks ............................................................................. 5-3

5.6 Executive Order 12898: Federal Actions to Address Environmental Justice in Minority Populations and Low-Income Populations ....................................... 5-4 5.7 Employment Impacts Analysis.................................................................. 5-5 5.7.1 Employment Impacts from Po llution Control Requirements.........................5-6 5.7.2 Employment Impacts Within the Regulated Industry............................... ..5-9

Section 6 Human Health Benefits of Emissions Reductions ................................................. 6-1

6.1 Synopsis ............................................................................................................... 6-1

6.2 Calculation of PM 2.5 Human Health Benefits ...................................................... 6-1

6.3 Unquantified Benefits ........................................................................................ 6-12 6.3.1 HAP Benefits ......................................................................................... 6-12

6.4 Characterization of Uncertainty in the Monetized PM 2.5 Benefits ..................... 6-23

Section 7 Comparison of Moneti zed Benefits and Costs ..................................................... 7-28

7.1 Summary ............................................................................................................ 7-28

Section 8 References For RIA .................................................................................................. .11-1 SECTION 1 EXECUTIVE SUMMARY
The U.S. Environmental Protection Agency (EPA) is proposing amendments to the national emissions standards for hazardous ai r pollutants (NESHAP) for Ferroalloys Production to address the results of the re sidual risk and technology review that EPA is required to conduct by the Clean Air Act. These proposed amendmen ts include revisions to particulate matter standards for electric arc furnaces, metal oxygen refining process, and crushing and screening operations. The amendments add hydrochloric aci d, mercury, polycyclic aromatic hydrocarbons, and formaldehyde emission limits to electric arc furnaces. The amendments also expand and revise the requirements to control fugitive em issions from furnace operations and casting. Other requirements related to testing, monitori ng, notification, recor dkeeping, and reporting requirements are included. We ar e also proposing to revise pr ovisions addressing periods of startup, shutdown, and malfunction to ensure that the rules are consistent with a recent court decision.
This is an economically significant rule as defined by Executive Order 12866 since the annual effects (in this case, be nefits) are estimated to exceed $100 million. Therefore, EPA is required to develop a regulatory impact analysis (RIA) as part of the re gulatory process. The RIA includes an economic impact analysis (EIA), an d a benefits analysis along with documentation for the methods and results.

1.1 Analysis Summary The key results of the RIA are as follows:
Engineering Cost Analysis: EPA estimates the revised NESHAP’s total annualized costs will be $4.0 million ($2010). This estimate includes all of the compliance costs, with both control and administrative (monitoring, testing) costs included. Economic Impact Analysis: T he economic impacts for the firms affected by this proposed rule range are annual compliance cost s of less than 0.01 percent of sales. Thus, consumers will also experience mini mal changes in the price of ferroalloy output. Social Cost Analysis: The estimated social cost of the major source rule will be $4.0 million, which is also the total a nnualized cost of compliance ($2010). Small Entity Analyses: Neither of the two affected firms are small businesses according to the Small Business Administration’s (SBA’s) small business size standard for this industry . Thus, there are no small business or entity impacts associated with this proposed rule.1-2  Benefits Analysis:

– The benefits from reducing some air po llutants have not been monetized in this analysis, including reducing ar senic, chromium, nickel, manganese, mercury, polycyclic aromatic hydrocar bons (PAH) and other HAP emissions. We assessed the benefits of these emi ssion reductions qualita tively later in this analysis.

– We monetized the benefits from reduc ing particulate matte r (PM). Thus all monetized benefits reported re flect decreases in ambient PM 2.5 concentrations due to reduction of close to 257 tons of PM 2.5 . Although the monetized benefits likely underestimate the total be nefits, the extent of the underestimate is unclear.

– Using a 3% discount rate, we estimated the total monetized benefits of the proposed rule to be $71 million to $170 million (2010 dollars) in the year of analysis (2015). Using a 7% discount ra te, we estimate the total monetized benefits of the proposed rule to be $6 3 billion to $160 billion (2010 dollars) in 2015. Using alternative relationships between PM 2.5 and premature mortality supplied by experts, higher and lower be nefits estimates are plausible, but most of the expert-based estimates fall between these estimates.

Net Benefits: For the ferroalloys proposal, the net benefits are $67 million to $170 million in 2015 at a 3% discount rate for the benefits and $59 million to $150 million in 2015 at a 7% discount rate for the benefits. These results are s hown in Table 1-1.

1.2 Organization of this Report The remainder of this report supports and details the methodology a nd the results of the RIA:

 Section 2 describes the proposed regulation.

 Section 3 presents the profile of the affected industry.

 Section 4 describes the baseline emissions and emission reductions for the proposed regulation.

 Section 5 describes the economic impacts a nd analyses to comp ly with Executive Orders.

 Section 6 presents the benefits estimates.

 Section 7 presents the net be nefits of the proposed rule.

 Section 8 contains the references for the RIA.1-3 Table 1-1. Summary of the Annual Monetized Bene fits, Social Costs, and Net Benefits for the Proposed Ferroalloys RTR in 2015 ($2010 millions) a

3% Discount Rate 7% Discount Rate Proposed Standard Total Monetized Benefits b $71 to $170 $63 to $160 Total Social Costs $4.0 $4.0 Net Benefits $67 to $170 $59 to $150 Nonmonetized Benefits Reduced exposure to HAPs, including arsenic, chromium, nickel, manganese, mercury and polycyclic aromatic hydrocarbons Ecosystem effects Visibility impairment

a All estimates are for the year of implementation (2015) and are rounded to two significant figures. These results

include units anticipated to come online and the lowest cost disposal assumption.
b The total monetized benefits reflect the human health benefits associat ed with reducing exposure to PM 2.5 through

reductions of directly emitted PM 2.5 . It is important to note that the monetized benefits include many but not all health effects a ssociated with PM 2.5 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 the scientific evidence is not yet sufficie nt to allow differentiation of effect estimates by particle type.SECTION 2 INTRODUCTION

2.1 Background for Proposed Rule

2.1.1 What is this source category and ho w did the MACT regulate its HAP emissions? The NESHAP (or MACT rule) for Ferro alloys Production: Ferromanganese and Silicomanganese was promulgated on May 20, 1999 (64 FR 27450) and codified at 40 CFR part 63, subpart XXX. 1 The 1999 NESHAP (40 CFR 6 3.1650(a)) applies to all new and existing ferroalloys production faciliti es that manufactur e ferromanganese or silicomanganese and are major sources or are co-located at major sources of HAP emissions. The rule’s product-specific a pplicability reflected the only known major source at the time of promulgation. Since the n, one other producer of silicomanganese has started production.
Today, there are two ferroalloys producti on facilities that are subject to the MACT rule. No new ferroalloys production facilities have been built in over 20 years, and we anticipate no new ferroalloys producti on facilities in the foreseeable future, although one facility is currently exploring expanding operations.
Ferroalloys are alloys of iron in which one or more chemical elements (such as chromium, manganese, and silicon) are a dded into molten metal. Ferroalloys are consumed primarily in iron and steel making and are used to produce steel and cast iron products with enhanced or special properties.
Ferroalloys within the scope of this source category are produced using submerged electric arc furnaces, which are furnaces in which the electrodes are submerged into the charge. The submerged arc process is a reduction smelting operation. The reactants consist of metallic ores (ferrous oxides, silicon oxides, manganese oxides, etc.) and a carbon-source reducing agent, usually in the form of coke, charcoal, high- and low-volatility coal, or wood chips. Raw ma terials are crushed and sized and then conveyed to a mix house for weighing and ble nding. Conveyors, buckets, skip hoists, or cars transport the processed material to hoppers above the furnace. The mix is gravity-fed

1 The emission limits were revised on March 22, 2001 (66 FR 16024) in response to a petition for reconsideration submitted to EPA following promulgation of the final rule, and a petition for review filed in the U.S. Court of Appeals fo r the District of Columbia Circuit.through a feed chute either continuously or intermitt ently, as needed. At high temperatures in the reaction zone, the car bon source reacts with metal oxides to form carbon monoxide and to reduce the ores to base metal. 2 The molten material (product and slag) is tapped from the furnace, sometime s subject to post-furnace refining, and poured into casting beds on the furnace room floor. Once the material hardens, it is transported to product crushing and sizing systems and pack aged for transport to the customer.
HAP generating processes include elect rometallurgical (furnace) operations (primary and tapping), othe r furnace room operations (l adle treatment and casting), building fugitives, raw material handling and product handling. HAP are emitted from ferroalloys production as process emissions , process fugitive emissions, and outdoor fugitive dust emissions.
Process emissions are the exhaust gases from the control devices, primarily the furnace control device, metal oxygen refining control device and crushing operations control device. The HAP in process emissions are primarily composed of metals (mostly manganese, arsenic, nickel, lead and ch romium) and also may include organic compounds that result from incomplete combustion of coal or coke that is charged to the furnaces as a reducing agent. There is also evidence of mercury emissions. There are process metal HAP emissions from the produc t crushing control devices. Process fugitive emissions occur at various points during the smelting process (such as during charging and tapping of furnaces and casting) and are a ssumed to be similar in composition to the process emissions. Outdoor fugitive dust emissions result from the entrainment of HAP in ambient air due to material handling, vehicl e traffic, wind erosion from storage piles, and other various activities. Outdoor fugitiv e dust emissions are composed of metal HAP only.
The MACT rule applies to process emissions and process fugitive emissions from the submerged arc furnaces, the metal oxygen refining process, and the product crushing equipment and outdoor fugitive dust emissions s ources such as roadways, yard areas, and outdoor material storage and transfer ope rations. For process sources, the NESHAP specifies numerical emissions limits for part iculate matter (as a surrogate for metal HAP) from the electric (submerged) arc furnaces (including primary and tapping emissions), depending on furnace type, size, and product being made. Particulate matter emission

2 U.S. Environmental Protection Agency. AP-42, 12.4. Ferroalloy Production. October 1986.limits (again as a surrogate for metal HAP) ar e also in place for the metal oxygen refining process and product crushing and screening equi pment. Table 2-1 contains a summary of the applicable limits.Table 2-1. Emission Limits in Subpart XXXNew or Reconstructedor Existing SourceAffected SourceApplicable PM EmissionStandardsSubpart XXXReferenceNew or reconstructed Submerged arc furnace 0.23 kilograms per hour permegawatt (kb/hr/MW) (0.51pounds per hour permegawatt (lb/hr/MW) or 35milligrams per dry standardcubic meter (mg/dscm) (0.015grains per dry standard cubicfoot (gr/dscf)40 CFR63.1652(a)(1) and(a)(2)Existing Open submerged arc furnace producingferromanganese and operating at a furnacepower input of 22 MW or less9.8 kg/hr (21.7 lb/hr) 40 CFR63.1652(b)(1)Existing Open submerged arc furnace producingferromanganese and operating at a furnacepower input greater than 22 MW13.5 kg/hr (29.8 lb/hr) 40 CFR63.1652(b)(2)New or Reconstructedor Existing SourceAffected SourceApplicable PM EmissionStandardsSubpart XXXReferenceExisting Open submerged arc furnace producingsilicomanganese and operating at a furnacepower input greater than 25 MW16.3 kg/hr (35.9 lb/hr) 40 CFR63.1652(b)(3)Existing Open submerged arc furnace producingsilicomanganese and operating at a furnacepower input of 25 MW or less12.3 kg/hr (27.2 lb/hr) 40 CFR63.1652(b)(4)Existing Semi-sealed submerged arc furnace(primary, tapping, and vent stacks)producing ferromanganese11.2 kg/hr (24.7 lb/hr) 40 CFR 63.1652(c)New, reconstructed, orexistingMetal oxygen refining process 69 mg/dscm (0.03 gr/dscf) 40 CFR 63.1652(d)New or reconstructed Individual equipment associated with theproduct crushing and screening operation50 mg/dscm (0.022 gr/dscf) 40 CFR63.1652(e)(1)Existing Individual equipment associated with theproduct crushing and screening operation69 mg/dscm (0.03 gr/dscf) 40 CFR63.1652(e)(2)The 1999 NESHAP established a building opacity limit of 20 percent that is measured during the required furnace control device performance test. The rule provides an excursion limit of 60 percent opacity for one 6-munute peri od during the performance test. The opacity observation is focused only on emissions exiti ng the shop due solely to operations of any affected submerged arc furnace. In addition, blow ing taps, poling and oxygen lancing of the tap hole; burndowns associated with electrode measurements; and maintenance activities associated with submerged arc furnaces and casting operati ons are exempt from the opacity standards specified in §63.1653.
For outdoor fugitive dust sources, as de fined in §63.1651, the 1999 NESHAP requires that plants prepare and operate according to an outdoor fugitive dust control plan that describes in detail the measures that will be put in place to control outdoor fugitive dust emissions from the individual outdoor fugitive dust s ources at the facility. The owne r or operator must submit a copy of the outdoor fugitive dust control plan to the designated permitting authority on or before the applicable compliance date.

2.1.2 What data collection activities were conducted to support this action?
In April 2010, we issued an information collection request (ICR), pursuant to CAA section 114, to the two companies that own and operate the two fe rroalloys production facilities producing ferromanganese and silicomanganese. The ICR requested available information regarding process equipment, control devices, po int and fugitive emissions, practices used to control fugitive emissions, and other aspect s of facility operations. The two companies completed the surveys for their facilities and su bmitted the responses to us in the fall of 2010. We also requested that the two facilities conduc t additional emissions tests in 2010 for certain HAP from specific processes that were considered representa tive of the industry. Pollutants tested included most HAP meta ls, hydrochloric acid, hydrofluor ic acid, formaldehyde, mercury, polycyclic aromatic hydrocarbons and dioxins and furans. The re sults of these tests were submitted to the EPA in the fall of 2010 and are available in the docket for this action.

The proposed rule is economically signifi cant according to Ex ecutive Order 12866. As part of the regulatory process of preparing these standards, EPA has prepared a regulatory impact analysis (RIA). This analysis includes an anal ysis of impacts to sma ll entities as part of compliance with the Small Business Regulat ory Enforcement Fairness Act (SBREFA) and analyses to comply with other Executive Orders.3-1 SECTION 3 INDUSTRY PROFILE EPA has developed this industry profile to provide the reader with a general understanding of the technical and economic asp ects of the industry that would be directly affected by this proposal.

Ferroalloys are alloys of iron in which one or more chemical elements (such as chromium, manganese, and silicon) are added in to molten metal. Ferroalloys are consumed primarily in iron and steel making and are used to produce steel and ca st iron products with enhanced or special properties.

Ferroalloys within the scope of this s ource category are produ ced using submerged electric arc furnaces, which are furnaces in whic h the electrodes are submerged into the charge. The submerged arc process is a reduction smelti ng operation. The reactants consist of metallic ores (ferrous oxides, silicon oxi des, manganese oxides, etc.) a nd a carbon-source reducing agent, usually in the form of coke, charcoal, high- and low-volatility coal, or wood chips. Raw
materials are crushed and sized and then c onveyed to a mix house for weighing and blending. Conveyors, buckets, skip hoists, or cars trans port the processed material to hoppers above the furnace. The mix is gravity-fed through a feed chute either continuously or intermittently, as needed. At high temperatures in the reaction zone , the carbon source reacts with metal oxides to
form carbon monoxide and to redu ce the ores to base metal. 1 The molten material (product and slag) is tapped from the furnace, sometimes subject to post-furnace refining, and poured into casting beds on the furnace room floor. Once the material hardens, it is transported to product crushing and sizing systems and packag ed for transport to the customer.

Ferroalloys are master alloys containing iron and one or more non-ferrous metals as alloying elements. The ferroalloys are usuall y classified in two groups: bulk ferroalloys (produced in large quantities in electric arc fu rnaces), and special ferro alloys (produced in smaller quantities, but with grow ing importance). Bulk ferroalloys are used in steel making and

1 U.S. Environmental Protection Agency. AP-42, 12.4. Ferroalloy Production. October 1986.3-2 steel or iron foundries excl usively, while the use of special ferroalloys is fa r more varied (used in batteries, animal feed). The U.S. military is a particularly notable consumer of manganese: In its weapons systems and munitions, the Departme nt of Defense uses approximately 25,000 short tons of manganese ore chemical/metal grade, 7,9 00 short tons of ferro-m anganese (either carbon or silicon) and 1,370 short tons of electrolytic manganese metal (EMM) each year. Manganese is a key ingredient in the produc tion of ferroalloys for use in th e steel and other industries. According the U.S. Geological Survey, “there are no substitutes for manganese in its major applications - the manufacture of steel, steel alloys, non-steel all oys, batteries, and fertilizers and animal feed.” (USGS, 2008). In total, about 87 % of the ferroalloys produced are used in the steel industry (European Commission, 2001).

Very little ferroalloy production takes place in the U.S. and Canada. Less than 1 percent of worldwide ferroalloy production takes place in the United States (SFSA, 2008). The amount of worldwide ferroalloy production occurs in Nort h America has declined over time. As of 2008, more than 56 percent of ferroalloy producti on took place in Asia (SFSA, 2008). The largest producer of ferroalloys is China, with more than 18 million tons produced in 2008. South Africa is second highest producti on, but is well behind China at around 4 million tons produced that same year. More than 80 percent of the fe rroalloys consumed in the U.S. are imported.

Worldwide, the top four ferroalloys produced are: ferrochromium (7.84 million metric tons), silicomanganese (7.46 million metric tons ), ferrosilicon (7.32 million metric tons), and ferromanganese (5.7 million metric tons) (SFSA, 2008).

Today, there are two ferroalloys production faci lities that are subject to the MACT rule. No new ferroalloys production facilities have be en built in over 20 years, and we anticipate no new ferroalloys production facilities in the forese eable future, although one facility is currently exploring expanding operations.

The affected facilities are owned by the Eramet Group and Group Privat. The Eramet Group is a French-owned conglomerate with more than 16,000 employees worldwide and revenues in 2010 of around $5 billion. Group Priv at is a loose conglomer ate of several large Ukrainian firms that have interests in metals, chemicals, banking, and other industries in that3-3 country and worldwide. There are at least 20,000 employees in th is conglomerate and at least $10 billion in revenues generated in 2008. Th e ferroalloys produced by these firms’ U.S. facilities use manganese as an input, and the mine s for this manganese are owned by these firms.4-1 SECTION 4 BASELINE EMISSIONS, EMISSI ON REDUCTIONS, AND COSTS

4.1 Introduction This section presents the baseline emissions fo r the pollutants emitted by affected units and also the resulting emissions in 2015 after imposition of the proposed RTR rule. We present the baseline emissions and emission reductions for HAP and other emissions such as PM 2.5 . Emission reductions were calculated from the baseline emissions base d on the proposed emissions limits, and the emission reductions were used as inputs to the be nefits analysis presented in Section 7.

4.2 Summary Of Cost Estimates And Emissions Reductions For The Regulatory Options Considered For Proposal
Regulatory options were considered for control of emissions of particulate metal hazardous air pollutants (HAP), Mercury (Hg), organic HAP, and Polycyclic Aromatic Hydrocarbons (PAH) from furnace stacks, and metal HAP from product sizing stacks and fugitive sources.

Emissions of each pollutant vary considerably among facilities, and multiple control options are available for different groups of pollutants. Because of this, and the limited num ber of facilities in the source category (two), specific regulatory options were assessed for each facility based on both technology review and modeled risk. B ecause of differences in modeled risk and existing controls, some options were not considered for all process lines at all facilities. Emissions reductions were estimated for each facility based on emissions data received in an information collection request (ICR) sent to the industry.

A brief description of the options selected fo r the proposed revisions to the NESHAP and the
associated costs and emissions reductions for each f acility in the source category are summarized in Table 4-1. All the options considered in this analysis are summarized in Table 4-2, along with the total estimated cost for implementing each option. A more de tailed description of all the regulatory options considered for proposal and their associated cost and emissions reductions estimates are presented in
section 2.0 of the cost memora ndum for this proposal.4-2 The emissions reductions associated with the co ntrol options are calculated as the difference
between baseline emissions and the estimated emissi ons for each control scenario. Details of the methodology employed to calculate these emissions are included in a separate memorandum. All costs
are estimated in 2010 dollars. The HAP emission re ductions estimated for this proposal are 83.6 tons.
PM emissions in this memo refer to total PM. Of the total PM, approxima tely 41 percent of the emissions are fine particulate (PM 2.5 ). Thus, of the 626 tons of total PM reduced, 257 tons are PM 2.5 .2Table 4-1: Summary of the Estimated Costs and Emissions Reductions of Regulatory Options Selected for ProposalFurnaceFabricFIlterUpgradeCarbonInjectionTapHoodUpgradeCastingCapture&ControlBuildingVentilationProductSizingFabricFilterUpgradeFacility PollutantPM,MetalHAPHg,PAH,HCHOPM,MetalHAPPM,MetalHAPPM,MetalHAPPM,MetalHAP$1,413,952$1,512,930$2,926,882 63.8 $23$756,465 $756,465 19.8 $19Note:Shadedoptionswerenotselectedforproposal.FelmanAnnualCostofControlTechnology($) CostEffectivenessTotalCost/Yr($)HAPReduction(Tons)CostEffectiveness($/lbHAP)ErametTable 4-2: Summary of the Estimated Costsand Reductions for All Considered OptionsControlOptionPMEmissionReduction(TPY)PM2.5EmissionReduction1(TPY)HAPEmissionReduction(TPY)CapitalCost($)AnnualCost($/Yr)PMCostEffectiveness($/Ton)PM2.5CostEffectiveness($/Ton)HAPCostEffectiveness($/lb) AffectedFacilitiesReplaceFurnaceFabricFilter224.6 10.1 2.95 $13,237,000 $1,543,603$62,761 $153,075 $261 ErametInstallACIforHgandPAH N/A N/A 3.55 $1,673,836 $1,413,952 N/A N/A $199 ErametImproveTappingCapture 63.2 25.9 6.86 $314,922 $81,792 $1,294 $3,155 $6 Eramet,FelmanCastingCapture&Control 100 40.9 22.9 $4,979,039 $1,592,762 $15,949 $38,900 $35 Eramet,FelmanInstallBuildingVentilation 626 257 80.4 $9,439,500 $2,269,394 $3,623 $8,838 $14 Eramet,FelmanImproveProductSizingBaghouse 11.4 4.65 4.66 $59,017 $14,394 $1,268 $3,092 $2 Eramet1PM2.5estimatedtobeapproximately41%oftotalPM.2Theemissionreductionsandannualcostforfabricfilterreplacementarebasedontheincrementaldifferencebetweenoperationofascrubberandafabricfilter.Thecosteffectivenessvalueswerecalculatedusingtheincrementalannualcostandtheincrementalemissionreductionsbetweenthescrubberandthefabricfilter.4-1 4.3 Regulatory Options Considered For Proposal
This section provides a detailed description of all regulatory options that were considered for the proposed revisions to the Ferroalloys NE SHAP and their associated costs and emissions
reductions.

4.3.1 Furnace Stack Emissions – Metal HAP

The selected standard for furnace stack emi ssions of PM (as a surrogate for metal HAP) is based on a technology review, and is designed to ensure that the standard in place will reflect actual current performance of existing sources. The selected option is a numeric emission standard with which both facilities are already in compliance through current controls. Although it was not selected for proposal, costs for a be yond-the-floor regulatory option were estimated, and are presented here.

4.3.1.1Replacement of Existing control device with a new negative-pressure fabric filter

This option was considered for a single furnace at one of the facilities, and represents a scenario of reducing fugitive PM emissions from the facility by 25 t ons per year (and HAP emissions by 3 tons per year) by replacing a wet sc rubber with a large negative pressure fabric filter. The total estimated capital cost for the replacement fabric filter is $13.2 million. Annualized capital cost and operational and main tenance costs are estimated at $2.5 million or $1.5 million above the current annual cost for the ex isting scrubber, according to the facility ICR

response.
4.3.2 Furnace Stack Emissions – Hg, PAH, Formaldehyde 1

The selected standards for Hg and PAH are numeric emission standards that represent a beyond-the-floor option considered under section 112(d) of the Clean Air Act (the Act). We selected this option largely based on the potential risk impacts based on multi-pathway screening and because of the potential to reduce the global pool of mercury. We determined that only one

1 The Hg and PAH controls will also achieve co-control of formaldehyde. We propose to set a MACT floor limit for this pollutant because there are no compelling risk or environmental r easons to control the relatively low levels of formaldehyde emitted at a beyond-the-floor level.4-2 of the facilities would be required to implement controls for these pollutants. 2 Estimated costs associated with these controls are presented here.

4.3.2.1Addition of Activated Carbon Injecti on for Fabric Filters and Scrubbers

This option was selected for two furnaces at one facility, and it repr esents a scenario of reducing emissions of Hg, PAH, and Formaldehyde from the facility by 3. 2 tpy by installation of activated carbon injectio n (ACI). The total estim ated capital cost for th e retrofit of ACI is $1.7 million. Annualized capital cost and operational and maintenance costs are estimated at $1.4
million.

2 Memorandum from Bradley Nelson, Ec/R to Conrad Chin, US EPA/OAQPS/SPPD/MMG, Methodology Used to Estimate Mercury Control Costs for the Ferroalloys Production Industry, September 8, 2011.4-3 4.3.3 Process Fugitive Emissions – Metal HAP

Several regulatory options were considered for control of fugitive metal HAP emissions, based on modeled risk. We focused the options on the individual emissions sources at each plant that appeared to be risk drivers. We looked at several options to cap ture and control these process fugitives ranging from lo cal ventilation and control, build ing ventilation and control, and fenceline monitoring. The regulatory options consid ered for control of process fugitive metal HAP emissions are presented in the following section.

4.3.3.1Improvements to Capture H oods for Tapping Operations

This option was considered for tapping opera tions at two furnaces each for both of the facilities, not including some hoods which were recently upgraded. This option represents a scenario of reducing fugitive PM emissions from the facilities by 63 tpy (and HAP emissions by 6.9 tpy) by upgrading the capture efficiency of capture hoods for tapping operations. The total estimated capital cost for the hood upgrades is approximately $315,000. A nnualized capital cost and operational and mainte nance costs are estimated at approximately $82,000.

4.3.3.2Addition of Capture and Control for Casting Operations

Some casting operations are already controlled at each facility. We developed costs to capture and control casting emissions the re maining uncontrolled ca sting operations. The estimated costs were based on the assumption th at one of the two facilities would require addition of capture and control fo r two of their three casting operat ions and the second facility would require addition of capture and control for one of their three casting operations. This scenario would reduce fugitive PM emissions fr om the facilities by 100 tpy (and HAP emissions by 23 tpy) by adding hoods, ductwork, and fabric f ilters to capture and control emissions from currently uncontrolled casting operations. The total estimated capital cost for the hoods, ductwork, and fabric filters is approximately $5 million. Annualized capital cost and operational
and maintenance costs are estimate d at approximately $1.6 million.4-4 4.3.3.3Building Ventilation

The selected control option involves insta llation of building ventilation for furnace buildings instead of installing f ugitive controls on individual ta pping and casting operations. This option would require installation of ductwork from the roof vents of furnace buildings and a new fabric filter for each building. We assumed that one of the two facilitie s would require building ventilation for two buildings a nd the second facility would requir e it for a single building. This option would reduce fugitive PM emissions from the facilities by 626 tpy (and HAP emissions by 80.4 tpy) by adding ductwork and fabric filters to capture and control all fugitive emissions from furnace buildings. The total estimated capital cost for the ductwork, and fabric filters is approximately $9.4 million. Annualized capital cost and operational and maintenance costs are estimated at approximately $2.3 million.

4.3.3.4Tapping and Casting Control w ith Fence line Monitoring

This is an alternative regu latory option selected by EPA for proposal in the revised NESHAP for the Ferroalloys Pr oduction source category. This opti on allows facilities who may have already implemented improved capture and control of tapping and casting emissions to avoid installation of building ventilation by perfor ming ambient monitoring for manganese at or
near the boundaries of th e facilities. Estimated emissions reduc tions would be the same as for the tapping and casting capture/control options described previousl y. Cost estimates were not prepared for this option.

4.3.5 Product Sizing Operations– Metal HA P – Improvements to Fabric Filters

The selected standard for product sizing stack emissions of PM (as a surrogate for metal HAP) is based on a technology review, and is designe d to ensure that the standard in place will reflect actual current performance of existing sour ces. The selected option is a numeric emission standard with which both facilities are already in compliance through current controls (fabric filters). Although it was not selected for proposal , costs for a beyond-the-floor regulatory option were estimated, and are presented here.4-5 4.3.5.1Upgrade fabric filter

For one facility, improvements to product si zing fabric filters were considered, and represent a scenario of reducing fugitive PM emissions from the facility by 11 tpy (and HAP emissions by 4.6 tpy) by upgrading the bag material of fabric filters and conversion to reverse-air cleaning. The total estimat ed capital cost for the fabric fi lter upgrades is approximately $59,000. Annualized capital cost and opera tional and maintenance costs ar e estimated at approximately $14,400.

4.3.6 Metal Oxygen Refining (M OR) Operations– Metal HAP

Metal Oxygen Refining (MOR) is a post-tapping process applied to the molten metal at
one of the facilities. The selected standard fo r MOR stack emissions of PM (as a surrogate for metal HAP) is based on a technology review, and is designed to ensu re that the standard in place will reflect actual current performance of exis ting sources. The selected option is a numeric emission standard with which the facility is al ready in compliance throu gh current controls (a fabric filter). Modeled risk did not indicate any need for consideration of a beyond-the-floor control option, so no costs were es timated for this emission source.

4.4 Methodology For Estimating Control Costs

The following sections present the methodologies used to estimate the costs associated with the regulatory options considered for propos al in the revised NESHAP for the Ferroalloys Production source category.

4.4.1 Furnace Stack Emissions – Metal HAP

The primary technologies used to control fu rnace stack emissions of metal HAP in the Ferroalloys source category are fabric filters (also known as baghouses). One facility uses a wet
scrubber to control emissions from one of their furnaces. Data from emission tests performed in conjunction with the ICR indi cate that baghouses that are properly designed, installed, maintained and operated can meet all of the metal HAP stack emissions limits selected for proposal in the revised NESHAP.4-6 In order to estimate the capital cost asso ciated with a particular option, we first determined which stacks would be required to re duce emissions. Only one stack was considered for any emission reductions, the one with a wet scrubber, for which an above-the-floor option was considered – replacing the stack with a larg e negative pressure fabric filter. Because the required fabric filter would be a large, custom model, we contacted a vendor who had recently supplied a similar model for installation at a ferroalloys facility to obtain assistance in developing a cost estimate. The equipment-onl y cost supplied by the vendor was used in conjunction with techniques descri bed in the sixth edition of the EPA Air Pollution Control Cost
Manual 3 to estimate total installed capit al cost and annual costs.

Our cost model included installation of the fa bric filter and any necessary fans, ductwork, and site work. The total installed capital cost of a fabric filter designe d for a flow-rate of 180,000 actual cubic feet per minute (acfm) was esti mated at $13.2 million. The annualized capital cost and operational and maintenance costs are estima ted at $2.5 million, via techniques described in
the sixth edition of the EPA Air Pollution Contro l Cost Manual. The annualized cost assumes a 20 year life expectancy for the unit and, to be consistent with OMB Guidance in Circular A-4, a 7 percent cost of capital as an estimate of the annualized capital cost as is commonly done for
EPA standards such as this one. All costs for this estimate were based on 2010 dollars from a current vendor estimate. The annual cost for ope ration of the scrubber was estimated to be $1.0 million based on information obtained from the ICR submitted by the facility. Therefore, the incremental annual cost of replacing the current operating scrubber with a new negative pressure fabric filter was estimated to be $1.5 million. The incremental cost was used to calculate the cost
effectiveness of this control option.

4.4.2 Furnace Stack Emissions – Hg, PAH, Formaldehyde

EPA believes that the most a ppropriate technology for contro l of exhaust emissions of Hg, PAH, and formaldehyde for the Ferroalloys Production source category is Activated Carbon Injection (ACI). Based on the proposed emissi on limit, we believe one facility would require installation of controls for Hg and PAH on two furnaces. To minimize generation of potentially

3 U.S. Environmental Protection Agency, EPA Air Pollution Control Cost Manual. October 2002, Sixth Edition, Found on the Internet at http://epa.gov/ttn/catc/ products.html#cccinfo4-7 hazardous waste (from contaminated carbon media) and avoid contamination of the saleable byproduct baghouse dust, it was assumed that the carbon injection would be performed at the outlet of the negative pressure fabric filter, with the carbon media collected by a second, small polishing baghouse. Activated carbon for the furnace equipped with a scrubber would be injected prior to the scrubber with no additi onal particulate control required.

Costs for ACI were estimated using cost equations developed for the Utility NESHAP 4 and information provided by activated carbon vendors. 5 The calculated equipment costs for ACI and fabric filters were used in conjunction with techniques described in the sixth edition of the EPA Air Pollution Control Cost Manual to estimate total installed capital cost and annual costs.
It was estimated that one fac ility would require installati on of ACI on two furnaces, one exhausting to a fabric filter with an outlet fl ow rate of 245,000 acfm, and a second exhausting to
a scrubber with an outlet flow rate of 184,000 acfm.

Our cost model included installation of the two activated carbon injection systems, one polishing fabric filter, and associ ated fans, ductwork, and site wo rk. The total installed capital cost was estimated at $1.7 million. The annualized capital cost and operational and maintenance costs were estimated at $1.4 million. Annualized co sts assume a 20 year life expectancy for the units and, to be consiste nt with OMB Guidance in Circular A-4, a 7 percent cost of capital as an estimate of the annualized capital cost as is co mmonly done for EPA standards such as this one. 6 All costs for this estimate were adjusted to 2010 dollars using Chemical Engineering Plant Cost Indices (CEPCI). 7 We did not consider the downtime associ ated with installation for the unit in

our costs.

4 Sargent & Lundy, IPM Model - Revisions to Cost and Performance for APC Technologies, Mercury Control Cost Development Methodology Final, March, 2011. http://www.epa.gov/airmarkt/progsregs/epaipm/docs/append5_3.pdf 5 Contact Report, Daryl Lipscomb, Albemarle, August 22, 2011. 6 U.S. Office of Management and Budget. Circular A-4, September 17, 2003. Found on the Internet at http://www.whitehouse.gov/o mb/circulars_a004_a-4/#e

. 7 Estimates of the Chemical Engineering Plant Cost Index can be found at http://www.che.com . CEPCI values employed were: 539.1 for 2010, 575.4 for 2008, and 361.3 for 1991.4-8 4.4.3 Process Fugitive Emissions – Metal HAP

Fugitive emissions of metal HAP at Ferroalloys Production facilities result from several areas of the process. Process fugitive emi ssions primarily result from furnace leaks and incomplete capture of emissions during tapping and casting of product. Fu rnace upsets can result in release of emissions that would normally be contained by negative pre ssure occurring inside furnace hood. Process fugitive emissions can also result from incomplete capture of emissions by tapping hoods, or from casting operations, some of which are uncontrolled at both facilities.

The 1999 NESHAP established a building opacity limit of 20 percent that is measured during the required furnace control device performance test. The rule provides an excursion limit of 60 percent opacity for one 6-minute peri od during the performance test. The opacity observation is focused only on emissions exiti ng the shop due solely to operations of any affected submerged arc furnace. In addition, blow ing taps, poling and oxygen lancing of the tap hole; burndowns associated with electrode measurements; and maintenance activities associated with submerged arc furnaces and casting operati ons are exempt from the opacity standards specified in §63.1653.

Both facilities employ nega tive-pressure hoods to collect emissions from tapping operations and direct them to a control device. Some casting operations at both facilities capture emissions and direct them to a fabric filter, while some casting operations are currently
uncontrolled.

Costs were estimated for several options for process fugitive control:

 Improvements to Capture Hoods for Tapping Operations

 Addition of Capture and Cont rol for Casting Operations

 Building Ventilation

Building ventilation was the opti on selected for proposal, because it was associated with the lowest levels of modeled risk, and would capture any emissions that would have been collected4-9 by improved tapping capture and captu re control of casting emissions , in addition to any furnace fugitives which escape current controls.

a) Improvements to Capture H oods for Tapping Operations

Estimated costs for tap hood improvements were assumed to cover only the cost of an improved replacement tapping hood on the assumption that sufficient control device capacity is already in place, since both facilities already ha ve tapping capture and control in place. Because the capture hood equations in EPA’s cost manual were insufficient for large, metal hoods of the type required, an equation from a book by Bill Vatavuk (the
author of EPA’s Air Pollution Control Cost Manual) was used 8 , in conjunction with techniques described in the sixth edition of the EPA Air Pollution Control Cost Manual 9 to estimate total installed capit al cost and annual costs.

Our cost model included installation of the replacement tap hood. The total installed capital cost of f our replacement tapping hoods (two at each facility) was estimated at $315,000. The annualized capital co st and operational and maintenance costs are estimated at $81,000 via techniques descri bed in the sixth edition of the EPA Air
Pollution Control Cost Manual. The annualized cost assumes a 20 year life expectancy for the equipment and, to be consistent with OMB Guidance in Circular A-4, a 7 percent cost of capital as an estimate of the annualized capital cost as is commonly done for EPA
standards such as this one. All costs for this estimate were adjusted to 2010 dollars using Chemical Engineering Plant Cost Indices (C EPCI). We did not consider the downtime
associated with installation for the unit in our costs.

b) Addition of Capture and Control for Casting Operations

Estimated costs for addition of capture and control of casting emissions were
assumed to cover the cost of hoods and ductw ork for capture, plus a fabric filter for control of particulate emissions. Because each facility already has installed capture and

8 Vatavuk, W.M., Estimating Costs of Air Pollution Control. Chelsea, Michigan, Lewis Book Publishers. 1990. P. 92. 9 http://epa.gov/ttn/catc/ products.html#cccinfo4-10 control for some of their casting operations, we estimated that additional capture and control for two casting operations would be re quired at one facil ity and for one casting operation at the second. Equipment costs for th e hoods and ductwork, plus a fabric filter a fabric filter designed for a flow-rate of 60,000 actual cubic fe et per minute (acfm) were estimated via techniques described in the si xth edition of the EPA Air Pollution Control
Cost Manual 10 to estimate total installed capit al cost and annual costs.

Our cost model included installation of casting hoods, ductwork, and a fabric filter. The total installed capital cost to add capture and control for three casting operations was estimated at $5.0 million. The annualized capital cost and operational and maintenance costs are estimated at $1.6 million via techniques described in the sixth
edition of the EPA Air Pollution Control Cost Manual. The annualized cost assumes a 20 year life expectancy for the equipment and, to be consistent with OMB Guidance in Circular A-4, a 7 percent cost of capital as an estimate of th e annualized capital cost as is commonly done for EPA standards such as this one. All costs for this estimate were adjusted to 2010 dollars using Chemical Engi neering Plant Cost Indi ces (CEPCI). We did
not consider the downtime associated with installation for the unit in our costs.

c) Building Ventilation

To estimate the cost for the building vent ilation fabric filter, EPA contacted a vendor who had recently supplied a fabric fi lter to one of the facilities to obtain assistance in developing a cost estimate fo r the installation. The equipment-only cost supplied by the vendor was used in conjunction with techniques described in the sixth
edition of the EPA Air Pollution Control Cost Manual 11 to estimate total installed capital
cost and annual costs.

Our cost model included installation of the baghouse and any necessary fans, ductwork, and site work, including extra duc twork for connection to the building roof monitors. The total installed capital cost of thr ee fabric filters (two at one facility, one at the second facility) designed for a flow-rate of 150,000 actual cubic feet per minute

10 http://epa.gov/ttn/catc/ products.html#cccinfo 11 http://epa.gov/ttn/catc/ products.html#cccinfo4-11 (acfm) was estimated at $9.4 million. The annualized capital cost and operational and maintenance costs are estimated at $2.3 milli on, via techniques described in the sixth
edition of the EPA Air Pollution Control Cost Manual. The annualized cost assumes a 20 year life expectancy for the unit and, to be consistent with OMB Guidance in Circular A4, a 7 percent cost of capital as an estimate of the annualized capital cost as is commonly
done for EPA standards such as this one. A ll costs for this estimate were based on 2010
dollars from a current vendor estimate. We di d not consider the downtime associated with
installation for the unit in our costs.4-12 4.4.4 Product Sizing Operations– Metal HA P – Improvements to Fabric Filters

The primary technology used to control emissi ons of particulate metal HAP from product sizing operations in the Ferroalloys Production s ource category are fabric filters. The fabric filters currently in use at the facilities are ca pable of meeting the proposed standard. Although it was not selected for proposal, costs for a beyond- the-floor regulatory option were estimated, and are presented here. The beyond-the-floor opti on was based on modeled risk, and only one product sizing line at one facility was determined to pose any exiting ris k. The option considered was an upgrade to the fabric filter via improve d bag materials and conversion to reverse-air cleaning. The costs associated with this upgrade we re calculated via techniques described in the
sixth edition of the EPA Air Pollution Control Cost Manual 12 to estimate total installed capital cost and annual costs. At the end, we concl uded that the potential risk reduction was not meaningful compared to the risk reduction achieved by the building ventilation option.

The total installed capital cost of the fabric filter upgr ade was estimated at $59,000. The Annualized capital cost and ope rational and maintenance cost s are estimated at $14,000, via techniques described in the si xth edition of the EPA Air Pollu tion Control Cost Manual. The annualized cost assumes a 5 year life expectancy for the equipment (fabric filter bags) and, to be consistent with OMB Guidance in Circular A-4, a 7 percent cost of capital as an estimate of the annualized capital cost as is commonly done for EPA standards such as this one. All costs for this estimate were adjusted to 2010 dollars us ing Chemical Engineering Plant Cost Indices (CEPCI). We did not consider the downtime associat ed with installation for the unit in our costs.

4.5 Summary of Cost By Facility

Table 4-3 summarizes estimated costs for each f acility in the Ferroalloys source category, assuming implementation of the emission re duction options selected for proposal.

12 http://epa.gov/ttn/catc/ products.html#cccinfo4-13 Table 4-3: Summary Cost Estimates by Facility *

Facility Total Capital Cost Total Annual Cost Eramet $7,966,836 $2,926,882 Felman $3,146,500 $756,465 Total $11,113,336 $3,683,347

* Overall cost estimates may be overstated since some facilities may be able to comply with the rule under the alternative compliance option (i.e., monitoring at facility boundary and improved casting/tapping capture & control) and may not need to install building ventilation. If so, actual costs would be significantly lower than shown here.5-1 SECTION 5 ECONOMIC IMPACT ANALYSIS AND STATUTORY AND EXECUTIVE ORDER ANALYSES

5.1 Background

In this chapter, we present the results of the economic impact analysis and analyses prepared in adherence to statutory and Executive Order requirements.

5.2 Regulatory Flexibility Act

The Regulatory Flexibility Act (RFA) gene rally 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 signifi cant economic impact on a substantial number of small entities. Small entities include small businesses, small organizations, and small governmental jurisdictions.
For purposes of assessing the impacts of this proposed rule on small entities, small entity is defined as: (1) a small business as define d by the Small Business Administration’s (SBA) regulations at 13 CFR 121.201; (2) a small government al jurisdiction that is a government of a city, county, town, school district or special district with a popul ation of less than 50,000; and (3) a small organization that is a ny not-for-profit enterprise that is independently owned and operated and is not dominant in its field. For th is source category, which has the NAICS code 331112 (i.e. , Electrometallurgical ferroalloy product manufacturing), the SBA small business size standard is 750 employees according to th e SBA small business standards definitions.
After considering the economi c impacts of today’s proposed rule on small entities, I certify that this action will not have a significant economic imp act on a substantial number of small entities. Neither of the compan ies affected by this rule is considered to be a small entity per the definition provided in this section.
Although this proposed rule will not have a significant economic im pact on a substantial number of small entities, the EPA nonetheless has tr ied to reduce the impact of this rule on small5-2 entities. To reduce the impacts, we are proposi ng emissions standards in a format that allow companies flexibility on how best to comply with them. Moreover, we are proposing stack limits that are based on a weighted average approach (as described in Sections V.C and V.D of the preamble) and have been establishe d at the least stringent levels th at we estimate will still result in acceptable risks to public health. Thus, the pr oposed stack limits are based on the least costly approach that will still provide an ample margin of safety for human health and the environment. In addition, the proposed compliance testing requ irements were established in a way that minimizes the costs for testing and reporting wh ile still providing the Agency the necessary information needed to ensure continuous complia nce with the proposed standards. We continue to be interested in the potential impacts of the proposed rule on small entities and welcome comments on issues related to such impacts.

5.3 Energy Impacts Executive Order 13211 (66 FR 28355, May 22, 2001) provides that agencies will prepare and submit to the Administrator of the Office of Information and Regulatory Affairs, Office of Management and Budget, a Statement of Energy Effects for certain actions identified as “significant energy actions.” S ection 4(b) of Executive Order 13211 defines “significant energy actions” as any action by an ag ency (normally published in the Federal Register ) that promulgates or is expected to lead to the pr omulgation of a final rule or regulation, including notices of inquiry, advance notices of proposed rulemaking, and notices of proposed rulemaking: (1) (i) that is a significant re gulatory action under Executive Order 12866 or any successor order, and (ii) is likely to have a significant adverse effect on the supply, distri bution, or use of energy; or (2) that is designated by the Administrator of the Office of In formation and Regulatory Affairs as a significant energy action.

This rule is not a signifi cant energy action as designated by the Administrator of the Office of Information and Regulatory Affairs because it is not likely to have a significant adverse impact on the supply, distribution, or use of energy. This action will not create any new requirements and therefore no additional costs fo r sources in the energy supply, distribution, or
use sectors.5-3 5.4 Unfunded Mandates Reform Act 5.4.1 Future and Disproportionate Costs The UMRA requires that we estimate, where accurate estimation is reasonably feasible, future compliance costs imposed by the rule and any disproportio nate budgetary effects. Our estimates of the future complian ce costs of the proposed rule are discussed previously in this RIA. We do not believe that ther e will be any disproportionate budgetary effects of the proposed rule on any particular areas of the country, st ate or local governments, types of communities (e.g., urban, rural), or par ticular industry segments.

5.4.2 Effects on the National Economy The UMRA requires that we estimate the e ffect of the proposed rule on the national economy. To the extent feasible, we must estim ate the effect on producti vity, economic growth, full employment, creation of productive jobs, an d international competitiveness of U.S. goods and services if we determine that accurate estima tes are reasonably feasible and that such effect is relevant and material. The nationwide economic impact of the proposed rule is presented earlier in this RIA chapter. This analysis provides estimates of the effect of the proposed rule on most of the categories mentioned above, and thes e estimates are presented earlier in this RIA chapter. The nature of this rule is such that it is not practical for us to use existing approaches, such as the Morgenstern et al. approach, 1 to estimate the impact on employment to the regulated entities and others from this pr oposed rule. In addition, we have determined that the proposed rule contains no regulatory requirements that might significantly or uniquely affect small governments. Therefore, today’s rule is not subj ect to the requirements of section 203 of the UMRA.

5.5 Executive Order 13045: Protection of Ch ildren from Environmental Health Risks and Safety Risks
Executive Order 13045, “Protection of Children from Environmental Health Risks and Safety Risks” (62 FR 19885, April 23, 1997), applies to any rule that (1) is determined to be “economically significant,” as defined under Executive Order 12866, and (2) concerns an environmental health or safety risk that EPA has reason to belie ve may have a disproportionate effect on children. If the re gulatory action meets both criteri a, EPA must evaluate the environmental health or safety effects of th e planned rule on childre n and explain why the

1 Morgenstern, R. D., W. A. Pizer, and J. S. Shih. 2002. “Jobs versus the Environment: An Industry-Level Perspective.” Journal of Environmental Economics and Management 43(3):412-436.5-4 planned regulation is preferable to other potentially effective and r easonably feasible alternatives considered by the Agency.

This proposed rule is not subject to Executive Order 13045 (62 FR 19885, April 23, 1997) because the Agency does not believe the e nvironmental health risks or safety risks addressed by this action present a disproportionate effect on children. If the regulatory action meets both criteria, the EPA must evaluate the en vironmental health or safety effects of the planned rule on children and explai n why the planned regulation is pr eferable to other potentially effective and reasonably feasible alte rnatives considered by the Agency.
This proposed rule is not subject to Executive Order 13045 (62 FR 19885, April 23, 1997) because the Agency does not believe the e nvironmental health risks or safety risks addressed by this action present a disproportionate risk to children. The report, Analysis of Socio-Economic Factors for Populations Living Near Ferroalloys Facilities , shows that on a nationwide basis, there are appr oximately 26,000 people exposed to a cancer risk at or above 1- in-1 million and approximately 28,000 people expos ed to a chronic noncancer TOSHI greater than 1 due to emissions from the source category. Except for persons in the “Ages 65 and Up” demographic group which are slightly elevated compared to the national average, the percentages for the other demographic groups , including children 18 years and younger, are similar to or lower than their respective nationwide percentages.
This proposed rule is expect ed to reduce enviro nmental impacts for everyone, including children. This action proposes em issions limits at the levels based on MACT, as required by the Clean Air Act. Based on our analysis, we believe that this rule does not have a disproportionate impact on children.
The public is invited to submit comments or id entify peer-reviewed st udies and data that assess effects of early life exposure to ma nganese, lead, arsenic, nickel, or mercury.

5.6 Executive Order 12898: Federal Actions to Address Environm ental Justice in Minority Populations and Low-Income Populations Executive Order 12898 (59 FR 7629 (Feb. 16, 1994)) establishes federa l executive policy on environmental justice. Its main provision di rects federal agencies, to the greatest extent practicable and permitted by law, to make environmental justice part of their mission by identifying and addressing, as appropriate, disp roportionately high and adverse human health or environmental effects of their programs, policie s, and activities on minority populations and lowincome populations in the United States.5-5 For the proposed ferroalloys rule, the EPA ha s determined that the current health risks posed to anyone by emissions from this sour ce category are unacceptabl e. There are about 26,000 to 28,000 people nationwide that are currently subject to health risks which are nonnegligible (i.e., cancer risks great er than 1 in a million or chro nic noncancer TOSHI greater than 1) due to emissions from this source category. The demographic distribution of this “at-risk” population is similar or below the national distri bution of demographics for all groups except for the “ages 65 and up” age group, which is 4 pe rcent greater than its corresponding national percentage. The proposed rule will reduce the nu mber of people in this at-risk group from 26,000 - 28,000 people to about 1,000 people, thereby provi ding disproportionate be nefits to a greater percentage of minorities. Therefore, the EPA has determined that the proposed rule will not have disproportionately high and advers e human health or environmen tal effects on minority or lowincome populations. Further, sin ce it so significantly reduces the at-risk population in the process of ensuring public health protec tion with an ample margin of safety, it will actually provide disproportionate benefit to peopl e ages 65 and up since they co mprise a larger portion of the current at-risk group.
5.7 Employment Impact Analysis
In addition to addressing the costs and bene fits of the proposed rule, EPA has analyzed the potential impacts of this rulemaking on employm ent, which are presented in this section. While a standalone analysis of employment impa cts is not included in a standard cost-benefit analysis, such an analysis is of particular co ncern in the current economic climate of sustained high unemployment. Executive Order 13563, states, “Our regulatory system must protect public health, welfare, safety, and our environmen t while promoting economic growth, innovation, competitiveness, and job creation” (emphasis added). Therefore, we seek to inform the discussion of labor demand and job impacts by exam ining labor requirements for the installation, operation, and maintenance of c ontrol requirements, as well as reporting and recordkeeping requirements. Unlike several recent RIAs, howev er, we do not provide estimates based on the study by Morgenstern et al. (2002); we discuss this decision after presenting estimates of the labor requirements associated with reporting an d recordkeeping and the installation, operation, and maintenance of control requir ements. Nor have we quantified th e rule’s effect s on labor in other sectors not regulated by the proposed rule, or the effects induced by changes in workers’ incomes. As such, this analysis presents only the gross increase in labor demand caused by the5-6 rule. It does not account for po ssible decreases in labor de mand caused by any reduction in output or change in production technology.

What follows is an overview of the various wa ys that environmental regulation can affect employment, followed by a discussion of the esti mated impacts of this rule. EPA continues to explore the relevant theoretical and empirical literature and to seek public comments in order to
ensure that such estimates are as accura te, useful and informative as possible.

From an economic perspective labor is an input into pr oducing goods and services; if regulation requires that more la bor be used to produce a given amount of output, that additional
labor is reflected in an increase in the cost of production. Moreove r, when the economy is at full employment, we would not expect an environmen tal regulation to have an impact on overall employment because labor is being shifted from one sector to another. On the other hand, in periods of high unemployment, an increase in labor demand due to regulation may result in a short-term net increase in overall employment due to the potential hiring of previously unemployed workers by the regulated sector to he lp meet new requirements (e.g., to install new equipment) or by the environmental protection s ector to produce new abatement capital. With significant numbers of workers unemployed, the opportunity costs associated with displacing jobs in other sectors are likely to be smaller.

To provide a partial picture of the employmen t consequences of this rule, EPA takes two approaches. First, EPA uses information derive d from its cost estimation documentation to generate estimates of employment impacts. Second, the analysis considers the results of Morgenstern, Pizer, and Shih (2002) in estimati ng the effects of the regulation on the regulated industry. This approach has been used by EPA previously in Regulat ory Impact Analyses prepared recently. EPA is interested in public comments on the merits of including information derived in this fashion for assessing the employment consequences of regulations.

5.7.1 Employment Impacts from Pollution Control Requirements
When a new regulation is promulgated, a re sponse of industry is to order pollution control equipment and services in order to comply with the regulation when it becomes effective. Revenue and employment in the environmen tal technology industry have grown steadily5-7 between 2000 and 2008, reaching an industry total of approximately $300 billion in revenues and 1.7 million employees in 2008. 2 While these revenues and employment figures represent gains for the environmental technologies industry, they ar e costs to the regulated industries required to install the equipment. Moreover, it is not cl ear the 1.7 million employees in 2008 represent new employment as opposed to workers being shifted from the production of goods and services to environmental compliance activities.

Once the equipment is installed, regulated firms may hire workers to operate and maintain the pollution control equipment – much like they hire workers to produce more output. Morgenstern et al. (2002) examined how regulat ed industries respond to regulation. The authors found that, on average for the industries they studi ed, employment increases in regulated firms. Of course, these firms may also reassign exis ting employees to perform these activities.

We do not estimate any potential changes in la bor outside of the affected sector. This analysis estimates the employme nt impacts due to the installa tion, operation, and maintenance of control equipment, as well as employment asso ciated with new reporting and recordkeeping requirements.

The employment analysis uses a bottom-up engineering-based met hodology to estimate employment impacts. The engineering cost anal ysis summarized earlier in this RIA includes estimates of the labor requirements associated with implementing the proposed regulations. Each of these labor changes may either be required as part of an initial effort to comply with the new regulation or required as a conti nuous or annual effort to mainta in compliance. We estimate upfront and continual, annual labor requiremen ts by estimating hours of labor required and

2 In 2008, the industry totaled approximately $315 billion in revenues and 1.9 million employees including indirect employment effects, pollution abatement equipment production employed approximately 4.2 million workers in 2008. These indirect employment effects are based on a multiplier for indirect employment = 2.24 (1982 value from Nestor and Pasurka - approximate middle of range of multipliers 1977-1991). Environmental Business International (EBI), Inc., San Diego, CA. Environmental Business Journal, monthly (copyright). http://www.ebiusa.com/ EBI data taken from the Depart ment of Commerce International Trade Administration Environmental Industries Fact Sheet from April 2010: http://web.ita.doc.gov/ete/eteinfo .nsf/068f3801d047f26e85256883006ffa 54/4878b7e2fc08ac6d85256883006c45 2c?OpenDocument5-8 converting this number to full-time equivale nts (FTEs) by dividing by 2,080 (40 hours per week multiplied by 52 weeks). We note that this type of FTE estimate cannot be used to make assumptions about the specific number of people involved or whether new jobs are created for new employees.

The results of this employment estimate are presented in Table 5-1 for the proposed
NESHAP. The tables breaks down the installatio n, operation, and maintenance estimates by type of pollution control evaluated in the RIA and present both the es timated hours required and the
conversion of this estimate to FTE. For th e proposed NESHAP, repor ting and recordkeeping requirements were estimated requirements were es timated for the entire rule rather than by anticipated control requirements; the reporting and recordkeeping estimates are consistent with estimates EPA submitted as part of its Information Collection Request (ICR) that is in the Supporting Statement for the proposed rule.

The up-front one-time labor requirement is estimated at 27 FTEs for the proposed NESHAP. These up-front FTE labor requirement s can be viewed as short-term labor requirements required for affected entities to comply with the new regulation. Ongoing requirements are estimated at about 4 FTEs for the proposed NESHAP. These ongoing FTE labor requirements can be viewed as sustained labor requirements required for affected entities to continuously comply with the new regulation. It is important to recogniz e that these seemingly precise estimates are not to be assumed to be ex act measures of the employment impacts of this rulemaking. They represent a rough approximation of the small positive impacts that this rule may have on employment.5-9 Table 5-1. Labor-based Employment Estimates for Reporting and Recordkeeping and Installing, Operating, and Maintaining Cont rol Equipment Requirements for Proposed NESHAP

Source/Emissions Point/Requirement Emission Control Measure Projecte d No. of Affected Units Per-UnitOneTime Labor Estimate (Hours) TotalOneTime Labor Estimate (Hours) Total Annual Labor Estimate (Hours) One-Time Full-Time Equivalent Annual Full-Time Equivalent

Furnace Shop Building Ventilation 3 13,636 40,909 3,564 19.67 1.71 EAF 1 ACI 2 545 1,090 904 0.52 0.43 EAF 1 ACI + Polishing Baghouse 1 13,563 13,563 3,564 6.52 1.71 Monitoring & Testing 2 N/A 2 Plants 190 0.00 0.09 Reporting & Recordkeeping 2 N/A 2 Plants 150 300 70 0.14 0.03 TOTAL: 27,895 55,862 8,292 26.9 4.0 Note : Full-time equivalents (FTE) are estimated by first multip lying the projected number of affected units by the per unit labor requirements and then dividing by 2,080 (40 hours multiplied by 52 weeks). Totals may not sum due to independent rounding. N/A = Not Applicable. ACI = Activated Carbon Injection. 1 EAF = Electric Arc Furnace. Estimate is from Draft Cost Impacts of the Revised NESHAP for the Ferroalloys Production Source Category, October 21, 2011. 2 Supporting Statement for NESHAP for Ferroalloys Produc tion: Ferromanganese and Silicomanganese, October 27, 2011.

5.7.2 Employment Impacts within the Regulated Industry

In recent RIAs we have applied estimates from a study by Morgenstern, Pizer and Shih (2002) 3 to derive the employment effects of new regul ations within the regulated industry. (See, for example, the Regulatory Impact Analyses for the recently released proposed MATS and final

3 Morgenstern, R. D., W. A. Pizer, and J. S. Shih. 200 2. Jobs versus the Environment: An Industry-Level Perspective. ԡ Journal of Environmental Economics and Management 43(3):412-436.5-10 CSAPR regulations). Determining the direction of employment effects in the regulated industry is also challenging due to competing effects. Complying with the new or more stringent regulation requires additional inpu ts, including labor, and may alte r the relative proportions of labor and capital used by regul ated firms in their production pr ocesses. Morgenstern, et al. (2002) demonstrate that envir onmental regulations can be un derstood as requiring regulated firms to add a new output (environmental qualit y) to their product mixes. Although legally compelled to satisfy this new demand, regulated firms have to finance this additional production with the proceeds of sales of their other (mar ket) products. Satisfying this new demand requires additional inputs, including labor, and may alter the relative proporti ons of labor and capital used by regulated firms in their productio n processes. It should be noted that this study assumes that the regulated entities will comply with the regul ation and continue to operate. It does not provide information on potential entry and exit d ecisions by firms in the regulated sectors and subsequent employment imp acts from those decisions.

More specifically, Morgenst ern, Pizer, and Shih (2002) decompose the effect of regulation on net employment in the regulated sector into the follo wing three subcomponents:

 The Demand Effect : higher production costs from comp lying with the regulation will raise market prices, reducing consum ption (and production), thereby reducing
demand for labor within the re gulated industry. The “extent of this effect depends on the cost increase passed on to consumers as well as the demand elasticity of industry output.” (p. 416)

 The Cost Effect : Assuming that the capital/labor ratio in the production process is held fixed, as “production costs rise, more inputs, including labor, are used to produce the same amount of output,” (p. 416). For example, to reduce pollutant emissions while holding output levels c onstant, regulated firms may re quire additional labor.

 The Factor-Shift Effect : Regulated firms’ production technologies may be more or less labor intensive after complying with the regulation (i.e., more/less labor is required relative to capital pe r dollar of output). “Envir onmental activities may be
more labor intensive than conventional production,” meaning that “the amount of labor per dollar of output will rise.” Howeve r, activities may, instead, be less labor5-11 intensive because “cleaner operations coul d involve automation and less employment, for example.” (p. 416)

The demand effect is expected to have an unambiguously negative effect on employment, the cost effect to have an unambiguously posi tive effect on employment, and the factor-shift effect to have an ambiguous effect on employment . Without more information with respect to the magnitudes of these competing effects, it is not possible to predict the total effect environmental regulation will have on overall employment levels in the regulated sector.

Morgenstern et al. estimated the effects of pollution abatement expenditures on net employment in four highly polluting/regulated sectors (pulp and paper, plastics, steel, and petroleum refining in 1980s). They conclude that increased abatement expenditures generally
have not caused a significant change in net employment in those sectors. More specifically, their results show that, on average across the indus tries studied, each addi tional $1 million (in 1987$) spent on pollution abatement results in a (statist ically insignificant) net increase of 1.5 jobs. While the specific sectors Morgenstern et al. exam ined are different than the sectors considered here, the methodology that Morgenstern et al. developed is still an informative way to qualitatively assess the effects of this rule making on employment in the regulated sector.

While the theoretical framework laid out by Morgenstern et al. can hold for the ferroalloys industry under this proposal, important differences in the markets and regulatory settings analyzed in their study and the setting pr esented here lead us to conclude that it is inappropriate to utilize their quantitative estimates to estimate the employment impacts from this proposal. The differences between the underlyi ng regulations motivating the abatement expenditures studied in Morgenstern et al. are potentially too many to allow for the direct transfer of their quantitative estimates for use in analysis of the proposed rule. There are important differences between the ferroalloy in dustry and the four manufacturing industries studied by Morgenstern et al. While the steel industry is one of th e industries studied by Morgenstern et al., and ferroalloys is an important input to stee l production, the differences in the two industries are significant enough to lead to questions about how applicable are the parameters in Morgenstern et al. in this analys is. In addition, the fact that this proposal only impacts a small subset of the regulated industry leads to concerns about whether the Morgenstern5-12 et al. approach, which uses compliance costs to analyze the impact of environmental compliance expenditures on industry employment levels, can be suitable to estimate employment impacts for this industry as part of this proposed rule. For these reasons we conc lude there are too many uncertainties as to the comparab ility of the Morgenstern et al. study to apply their estimates to quantify the employment impacts within the re gulated sector for this proposed regulation.6-1 SECTION 6 HUMAN HEALTH BENEFITS OF EMISSIONS REDUCTIONS

6.1 Synopsis In this section, we provide an estimate of th e monetized benefits as sociated with reducing particulate matter (PM) for the proposed NESH AP for Ferroalloys Production to address the
results of the residual risk a nd technology review, RTR. For this rule, the PM reductions are the
result of emission limits on the PM 2.5 . The total PM 2.5 reductions are the consequence of the technologies installed to meet th ese limits. These estimates reflect the monetized human health benefits of reducing cases of morbidity and premature mortality among populations exposed to
the PM 2.5 reduced by this rulemaking. Using a 3% discount rate, we estimate the total monetized benefits of the proposed ferroalloy RTR to be $71 million to $170 million in the implementation year (2015). Using a 7% discount rate, we estimat e the total monetized bene fits of the Ferroalloy RTR to be $63 million to $160 million in the year of analysis (2015). All estimates are in 2010$.

These estimates reflect EPA’s most current in terpretation of the scientific literature. Higher or lower estimates of benefits are possibl e using other assumptions; examples of this are provided in Figure 6-2 below. Data, resource, and methodologi cal limitations prevented EPA from monetizing the benefits from several importa nt benefit categories, including benefits from reducing hazardous air pollutants a nd visibility impairment. The be nefits from reducing other air pollutants have not been monetized in this an alysis, including reduci ng arsenic, chromium, nickel, manganese, mercury, polycyclic aromatic hydrocarbons (PAH) and other HAP emissions.

6.2 Calculation of PM 2.5 Human Health Benefits This rulemaking would reduce emissions of PM 2.5 , and the incidence of PM 2.5 -related health effects. For this rule, the PM reductions are the result of emission limits on directly emitted PM, which is used as a surrogate for metal HAP. The total PM 2.5 reductions are the consequence of the technologies installed to m eet these limits. Due to analytical limitations, it was not possible to provide a comprehensive estimate of PM 2.5 -related benefits. Instead, we used the “benefit-per-ton” approach to estimate th ese benefits. The methodology employed in this analysis is similar to the work described in Fa nn, Fulcher, and Hubbell (2 009), but represents an improvement that EPA feels leads to more reliable estimates of PM 2.5 -related health benefits for emissions reductions in specific sectors. The ke y assumptions are described in detail below.6-2 These PM 2.5 benefit-per-ton estimates pr ovide the total monetized hum an health benefits (the sum of premature mortality and prematur e morbidity) of reducing one ton of PM 2.5 from a specified source. EPA has used the benefit per-t on technique in several previous RIAs, including
the recent SO 2 NAAQS RIA (U.S. EPA, 2010b). Tabl e 6-1 shows the quantified and unquantified benefits captured in those benefit-per-ton estimates.

Table 6-1. Human Health and Welfare Effects of PM 2.5

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

(refers to CSAPR RIA) Improved Human Health
Reduced incidence of premature mortality from exposure to PM 2.5 Adult premature mortality based on cohort study estimates and expert elicitation estimates (age >25 or age >30)   Section 5.4
Infant mortality (age <1)   Section 5.4

Reduced incidence of morbidity from exposure to PM 2.5 Non-fatal heart attacks (age > 18)   Section 5.4 Hospital admissions—respiratory (all ages)   Section 5.4 Hospital admissions—cardiovascular (age >20)   Section 5.4 Emergency room visits for asthma (all ages)   Section 5.4 Acute bronchitis (age 8-12)   Section 5.4 Lower respiratory symptoms (age 7-14)   Section 5.4 Upper respiratory symptoms (asthmatics age 9-11)   Section 5.4 Asthma exacerbation (asthmatics age 6-18)   Section 5.4 Lost work days (age 18-65)   Section 5.4 Minor restricted-activity days (age 18-65)   Section 5.4 Chronic Bronchitis (age >26)   Section 5.4 Emergency room visits for cardiovascular effects (all ages) -- -- Section 5.4 Strokes and cerebrovascular disease (age 50-79) -- -- Section 5.4 Other cardiovascular effects (e.g., other ages) -- -- PM ISA 2 Other respiratory effects (e.g., pulmonaryfunction, non-asthma ER visits, nonbronchitis chronic diseases, other ages and populations) -- -- PM ISA 2

Reproductive and developmental effects (e.g., low birth weight, pre-term births, etc) -- -- PM ISA 2,3 Cancer, mutagenicity, and genotoxicity effects -- -- PM ISA 2,3

1 We assess these benefits qualitative due to time and resource limitations for this analysis.
2 We assess these benefits qualitatively because we do not have sufficient co nfidence in available data or methods. 3 We assess these benefits qualitatively because current evid ence is only suggestive of ca usality or there are other significant concerns over the strength of the association.6-3 Consistent with the Portland Cement NESHAP (U.S. EPA, 2009a), the PM 2.5 benefits
estimates utilize the concentratio n-response functions as reported in the epidemiology literature, as well as the 12 functions obtained in EPA’s expe rt elicitation study as a sensitivity analysis.

 One estimate is based on the concentrati on-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/m 3 as was done in recent (2006–2009) O ffice 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 report ed by Laden et al. (2006). This study, published after the completion of the Staff Paper for the 2006 PM 2.5 NAAQS, has been used as an alternative estimate in the PM 2.5 NAAQS RIA and PM 2.5 benefits estimates in RIAs completed since the PM 2.5 NAAQS. When calculating the estimate, EPA applied the effect coefficient as repor ted in the study without an adjustment for assumed concentration threshold of 10 μg/m 3 as was done in recent (2006–2009) RIAs.

 Twelve estimates are based on the C-R func tions from EPA’s e xpert elicitation study (IEc, 2006; Roman et al., 2008) on the PM 2.5 -mortality relationship and interpreted for benefits analysis in EPA’s final RIA for the PM 2.5 NAAQS. For that study, twelve experts (labeled A through L) provi ded independent estimates of the PM 2.5 -mortality concentration-response function. EPA pract ice has been to develop independent estimates of PM 2.5 -mortality estimates corresponding to the concentration-response function provided by each of the twelve expe rts, to better characterize the degree of variability in the expert responses.
Readers interested in reviewing the genera l methodology for creating the benefit-per-ton estimates used in this analys is should consult the draft Tech nical Support Document (TSD) on estimating the benefits per ton of reducing PM2.5 and its precursors from the Ferroalloy Sector. 1 The primary difference between the estimates used in this analysis and the estimates reported in Fann, Fulcher, and Hubbell (2009) is the air quality modeling data utilized. While the air quality data used in Fann, Fulcher, and Hubbell (2009) reflects broad pollutant/source category combinations, the source apportionment modeling data used in this analysis is sector-specific. As a result, the benefit-per- ton estimates presented herein better reflect the geographic areas and population likely to be affected by the proposed rule. In this analysis, we apply the national

1 U.S. Environmental Protection Agency. 2011. Technical support document: Estimating the benefit per ton of reducing PM 2.5

precursors from the ferroalloy sector (Draft) ; EPA: Research Triangle Park, NC.6-4 average benefit-per-ton estimate for a 2016 analys is year and multiply it by the corresponding emission reductions of directly emitted PM 2.5 to quantify the benefits of this rule.

These models assume that all fine particles, regardless of their chemical composition, are equally potent in causing prem ature mortality because the scientific evidence is not yet
sufficient to allow differentiation of effect es timates by particle type (U.S. EPA, 2009b) . Directly emitted PM is the only PM 2.5 precursor affected by this rule. Even though we assume that all fine particles have equi valent health effects, the benefi t-per-ton estimates vary between precursors because each ton of precursor re duced has a different propensity to form PM 2.5 and a different pattern of transport, resulting geographic di stribution of exposure. When more people are exposed, the benefits per ton are greater. For example, VOC emissions have a lower benefitper-ton estimate than direct PM 2.5 because it does not directly transform into PM 2.5 and because particles formed from VOC can transport many miles, in cluding over areas with low populations. The benefit-per-ton coefficients in this analysis were derived us ing modified versions of the health impact functions used in the PM NAAQS Regulatory Impact Analysis. Specifically, this analysis uses the benefit-per-ton method firs t applied in the Portland Cement NESHAP RIA (U.S. EPA, 2009a), which incorporated three up dates: a new population dataset, an expanded geographic scope of the benef it-per-ton calculation, and the f unctions directly from the epidemiology studies without an adjustment for an assumed threshold. 2 Removing the threshold assumption is a key difference between the method us ed in this analysis of PM benefits and the methods used in RIAs prior to the Portland Ce ment proposal, and we now calculate incremental
benefits down to the lowest modeled PM 2.5 air quality levels.

Based on our review of the current body of scientific literature, EPA estimated PMrelated mortality without applying an assume d concentration threshold. EPA’s Integrated Science Assessment for Particulate Matter (U .S. EPA, 2009b), which was reviewed by EPA’s Clean Air Scientific Advisory Committee (U.S. EPA-SAB, 2009a; U.S. EPA-SAB, 2009b),
concluded that the scientific literature consis tently finds that a no-th reshold log-linear model most adequately portrays the PM-mortality c oncentration-response relationship while also

2 These updates were already included in Fa nn et al. (2009). An example of the ef fect of these updates is available in the Portland Cement proposal RIA (U.S. EPA, 2009a). The benefit-per-ton estimates have also been updated since the Portland Cement proposal RIA (U.S. EPA, 2009a) to incorporate a revised VSL, as discussed on the next page.6-5 recognizing potential uncertainty about the exact shape of the concentration-response function. Consistent with this finding, we incorporated a “Lowest Measured Le vel” (LML) assessment, which is a method EPA has employed in severa l recent RIA’s including the Cross-State Air Pollution Rule (U.S. EPA, 2011b). One key feature of this LML assessment is that it arrays the
estimated PM 2.5 -related avoided deaths relative to an ai r quality scenario in which the Ferroalloyattributable PM 2.5 would be eliminated entirely. While this is a conservative assumption, the source apportionment air quality modeling inform ing this LML assessment is not designed to predict PM 2.5 levels from marginal changes in emissions from each sector.

For this analysis, policy-specific air quality data is not availa ble due to time or resource limitations. For this rule, we are unable to es timate the percentage of premature mortality associated with this specific ru le’s emission reductions at each PM 2.5 level. However, we believe that it is still important to characterize the dist ribution of exposure to ba seline air quality levels. As a surrogate measure of mortality impacts, we provide the percentage of the population exposed at each PM 2.5 level using the air quality baseline used for the source apportionment modeling. Readers interested in a full discussion of the s ource apportionment air quality modeling may consult “Air Quality Modeling Technical Support Document: Source Sector Assessments” (EPA, 2011c). It is important to note that baseline exposure is only one parameter in the health impact function, along with baseline incidence rate s population, and change in air quality. In other words, the percentage of th e population exposed to air pollution below the LML is not the same as the percentage of the populat ion experiencing health im pacts as a result of a specific emission reduction policy. The most impo rtant aspect, which we are unable to quantify for rules without air quality modeli ng, is the shift in exposure associ ated with this specific rule. Therefore, caution is warranted when interpre ting the LML assessment. For more information on
the data and conclusions in the LML assessmen t for rules without policy-specific air quality modeling, please consult the LML TSD (U.S. EPA, 2010d). The results of this analysis are provided in Section 6.4 of this RIA.

As is the nature of Regulatory Impact An alyses (RIAs), the assumptions and methods used to estimate air quality benefits evolve over time to reflect the Agency’s most current interpretation of the scientif ic 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 statistical6-6 life (VSL) estimate derived from a limited analysis of some of the availabl e 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-a nalysis 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 $5.5 million (2000$) 3 was also consistent with the 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 pe er-review group.

During this time, the Agency continued work to update its guidance on valuing mortality risk reductions; including commissioning a repo rt 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 Ag ency consulted several times w ith the Science Advisory Board Environmental Economics Advisory Committee (SAB-EEAC) on the i ssue. With input from the meta-analytic experts, the SAB-EEAC advised the Agency to update its guidance using specific, appropriate meta-analytic tech niques to combine estimates from unique data sources and different studies, including those using differe nt methodologies (i.e., wage-risk and stated preference) (U.S. EPA-SAB, 2007).

Until updated guidance is availabl e, the Agency determined that a single, peer-reviewed estimate applied consistently best reflects the SAB-EEAC advice it has re ceived. 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) 4 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 st udies published between 1974 and

3 After adjusting the VSL to account for a different curre ncy year (2010$) and to account for income growth to 2015, the $5.5 million VSL is $8.0 million. In this analysis, we use 2016 estimates as a surrogate for 2015 estimates, which results in a slight overestimate of the benefits. 4 In the (draft) update of the Economic Guidelines (U.S. EPA, 2010f), 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.6-7 1991. The mean VSL across these studies is $6.3 million (2000$). 5 The Agency is committed to using scientifically sound, appropriately reviewed evidence in valuing mortality risk reductions and has made significant progr ess in responding to the SAB-EEA C’s specific recommendations.

In implementing these rules, emission cont rols may lead to reductions in ambient PM 2.5 below the National Ambient Air Quality Standard s (NAAQS) for PM in some areas and assist other areas with attaining th e PM NAAQS. Because the PM NAAQS RIAs also calculate PM benefits, there are important differences worth no ting in the design and anal ytical objectives of each RIA. The NAAQS RIAs illustrate the potential costs and benefits of attaining a new air quality standard nationwide based on an array of emission control st rategies for different sources. In short, NAAQS RIAs hypothesize, but do not pred ict, the control strate gies that States may choose to enact when implementing a NAAQS. The setting of a NAAQS doe s not directly result in costs or benefits, and as such, the NAAQS RI As are merely illustrative and are not intended to be added to the costs and benefits of other regula tions that result in speci fic costs of control and emission reductions. However, some costs and be nefits estimated in this RIA account for the same air quality improvements as estimated in the illustrative PM 2.5 NAAQS RIA.

By contrast, the emission reductions for this RTR rule are from a specific class of wellcharacterized sources (ferroalloy facilities). In general, EPA is more confident in the magnitude
and location of the emission reductions for these rules. It is important to note that emission reductions anticipated from these rules do not re sult in emission increases elsewhere. Emission reductions achieved under these and other promul gated rules will ultimately be reflected in the baseline of future NAAQS analyses, which woul d reduce the incrementa l costs and benefits associated with attaining the NAAQS. EPA rema ins forward looking towards the next iteration of the 5-year review cycle for the NAAQS, and as a result does not issue updated RIAs for existing NAAQS that retroactively update th e baseline for NAAQS implementation. For more information on the relationship between the NAAQS and rules such as analyzed here, please see
Section 1.2.4 of the SO 2 NAAQS RIA (U.S. EPA, 2010b).

5 In this analysis, we adjust the VSL to account for a different currency year (2010$ ) and to account for income

growth to 2015. After applying these adjustments to the $6.3 million value, the VSL is $9.2 million. In this analysis, we use 2016 estimates as a surrogate for 2015 estimates, which results in a slight overestimate of the benefits.6-8 Figure 6-1. Breakdown of Monetized PM 2.5 Health Benefits Estimates 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 premat ure mortality, the percentage of total monetized 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. Table 6-2 provides a general summary of th e primary approach results by pollutant, including the emission reductions and monetized benefits -per-ton at discount rates of 3% and
7%. 6 Table 6-3 provides a summary of the reductions in health incidences as a result of the pollution reductions. In Table 6-4, we provide the benefits using our anchor points of Pope et al.
and Laden et al. as well as the results from th e expert elicitation on PM mortality. Figure 6-2 provides a visual representation of th e range of benefits estimates of PM 2.5 reductions.

6 To comply with Circular A-4, EPA provides monetized benefits using discount rates of 3% and 7% (OMB, 2003). These benefits are estimated for a specific analysis year (i .e., 2015 using 2016 values as a surrogate), and most of the PM benefits occur within that year with two excep tions: acute myocardial infarc tions (AMIs) and premature mortality. For AMIs, we assume 5 years of follow-up me dical costs and lost wages. For premature mortality, we assume that there is a “cessation” lag between PM expo sures 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 re ductions in the first year, 50% over years 2 to 5, and 20% over the years 6 to 20 after the reduction in PM 2.5 (U.S. EPA-SAB, 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 benefits using a 7% discount rate are only appr oximately 10% less than the monetized benefits using a 3% discount rate. 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%6-9 Table 6-2. Summary of Monetized Benefits Estimates for the Ferroalloy Industry in 2015 (2010$) a

Pollutant Emissions Reductions

(tons) Benefit per ton (Pope,

3%) Benefit per ton (Laden,

3%) Benefit per ton (Pope, 7%) Benefit per ton (Laden,

7%) Total Monetized Benefits (millions

2010$ at 3%) Total Monetized Benefits (millions

2010$ at 7%) Direct PM 2.5 257 $280,000 $690,000 $250,000 $620,000 $71 to $170 $63 to $160
Total $71 to $170 $63 to $160

a All estimates are for the year of an alysis (2015), and are rounded to two significant figures so numbers may not

sum across columns. In this analysis, we use 2016 estimate s as a surrogate for 2015 estimates, which results in a slight overestimate of the benefits. These models assume that all fine particles, regardless of their chemical composition, are equally potent in causing premature morta lity the scientific evidence is not yet sufficient to allow differentiation of effect estimate s by particle type. The benefit-per-ton estimates are updated and reflect new air quality modeling specific to the ferroalloys sector. Th e monetized 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.6-10 Table 6-3. Summary of Reductions in Health Incidences from PM 2.5 Benefits for the Ferroalloy Sector in 2015 a

Reductions Avoided Premature Mortality Pope et al. 8
Laden et al. 20 Avoided Morbidity
Chronic Bronchitis 5 Acute Myocardial Infarction 9 Hospital Admissions, Respiratory 2 Hospital Admissions, Cardiovascular 3 Emergency Room Visits, Respiratory 5
Acute Bronchitis 11 Work Loss Days 950
Asthma Exacerbation 230 Lower Respiratory Symptoms 140 Upper Respiratory Symptoms 100

a All estimates are for the year of anal ysis (2015) and are rounded to whole numbers with two significant figures. In

this analysis, we use 2016 estimates as a surrogate for 2015 estimates, which results in a slight overestimate of the benefits. These models assume that all fine particles, regardless of their chemical composition, are equally potent in causing premature mortality because the scientific evidence is not yet sufficient to allow differentiation of effect estimates by particle type.6-11 Table 6-4. All PM 2.5 Benefits Estimates for the Ferroalloy Sector at Discount Rates of 3% and 7% in 2015 (in millions of 2010$) a

PM 2.5 Benefits
3% 7% Benefit-per-ton Coefficients Derived from Epidemiology Literature

Pope et al. $71 $63 Laden et al. $170 $160 Benefit-per-ton Coefficients D erived from Expert Elicitation

Expert A $190 $170 Expert B $62 $56 Expert C $140 $130 Expert D $100 $89 Expert E $230 $210 Expert F $54 $48 Expert G $84 $75 Expert H $110 $95 Expert I $140 $130 Expert J $110 $100 Expert K $13 $11 Expert L $39 $35

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

were derived through the benefit-per-ton technique described above. The benefits estimates from the expert elicitation are provided as a reasonable characterization of the uncertainty in the mortality estimates associated with the concentration-response function. Confidence intervals are unavailable for this analysis because of the benefit-per-ton methodology.6-12 Figure 6-2. Total Monetized PM 2.5 Benefits Estimates for the Ferroalloy Sector in 2015

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

Pope et al. (2002) study and the Laden et al. (2006) stud y, as well as 12 effect co efficients 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.

6.3 Unquantified Benefits

The monetized benefits estimated in this RIA only reflect the portion of benefits
attributable to the health effect reductions associated with ambien t fine particles. Methodological and time limitations prevented EPA from quantifyi ng or monetizing the benefits from several important benefit categories, including bene fits from reducing toxic emissions, ecosystem effects, and visibility impairment. The health benefits from reducing hazardous air pollutants (HAPs) including metals, polycyclic aromatic hydrocarbons (PAH), and mercury have not been monetized in this analysis. Because we were una ble to monetize the direct benefits associated with reducing HAPs among others, the monetized benefits estimate is an underestimate of the
total benefits. The extent of this underesti mate, whether small or large, is unknown.

6.3.1 HAP Benefits Even though emissions of air toxics from all sources in the U.S. declined by approximately 42% since 1990, the 2005 National-Scale Air Toxi cs Assessment (NATA) predicts that most $0 $50,000,000 $100,000,000 $150,000,000 $200,000,000 $250,000,000 

### Benefits Estimated from 2 Epidemiology Functions and 12 Expert Functions

3%
7%6-13 Americans are exposed to ambient concentrations of air toxics at levels that have the potential to cause adverse health effects (U.S. EPA, 2011b). 7 The levels of air toxics to which people are exposed vary depending on where people live and wo rk and the kinds of activities in which they engage. In order to identify and prioritize air toxics, emission s ource types and locations that are of greatest potential concern, U.S. EPA conducts the NATA. 8 The most recent NATA was conducted for calendar year 2005 and was released in March 2011. NATA includes four steps:

1) Compiling a national emissions inventory of air toxics emissions from outdoor sources
2) Estimating ambient and exposure concentratio ns of air toxics across the United States
3) Estimating population exposur es across the United States
4) Characterizing potential public health risk due to inhalation of air toxics including both cancer and noncancer effects
Based on the 2005 NATA, EPA estimates that a bout 5% of census tracts nationwide have increased cancer risks greater than 100 in a milli on. The average national cancer risk is about 50 in a million. Nationwide, the key pollutants that contribute most to the overall cancer risks are formaldehyde and benzene. 9 Secondary formation (e.g., formaldehyde forming from other emitted pollutants) was the largest contributor to cancer risks, while stationary, mobile and background sources contribute almost equal portions of the remaining cancer risk.

Noncancer health effects can result from chronic, 10 subchronic, 11 or acute 12 inhalation exposures to air toxics, and incl ude neurological, cardiovascular, liver, kidney, and respiratory

7 The 2005 NATA is available on the Internet at http://www.epa.gov/ttn/atw/nata2005/.
8 The NATA modeling framework has a number of limitations that prevent its use as the sole basis for setting regulatory standards. These limitations and uncertain ties are discussed on the 2005 NATA website. Even so, this modeling framework is very useful in identifying ai r toxic pollutants and sources of greatest concern, setting regulatory priorities, and informing the decision making process. U.S. EPA. (2011d) 2005 National-Scale Air Toxics Assessment. http://www.epa.gov/ttn/atw/nata2005/
9 Details about the overall confidence of certainty ranking of the individual pieces of NATA assessments including both quantitative (e.g., model-to-monitor ratios) and qua litative (e.g., quality of data, review of emission inventories) judgments can be found at h ttp://www.epa.gov/ttn/atw/nata/roy/page16.html.
10 Chronic exposure is defined in the glossary of the Integrated Risk Information (IRIS) database (http://www.epa.gov/iris) as repeated exposure by the oral, dermal, or inhalation route for more than approximately 10% of the life span in humans (more than approximately 90 days to 2 years in typically used laboratory animal species).6-14 effects as well as effects on the immune and reproductive systems. According to the 2005 NATA, about three-fourths of the U.S. popul ation was exposed to an average chronic concentration of air toxics that has the potential for adverse noncancer respiratory health effects.
Results from the 2005 NATA indicate that acro lein is the primary driver for noncancer respiratory risk.

Figure 6-3 and Figure 6-4 depict the estimated census tract-level carcinogenic risk and noncancer respiratory hazard from the assessment. It is important to note that large reductions in HAP emissions may not necessarily translate into significant reductions in health risk because toxicity varies by pollutant, and exposures ma y or may not exceed levels of concern. For example, acetaldehyde mass emissions are more than double acrolein emissions on a national basis, according to EPA’s 2005 National Emissions Inventory (NEI). However, the Integrated Risk Information System (IRIS) reference concentr ation (RfC) for acrolein is considerably lower than that for acetaldehyde, suggesting that acro lein could be potential ly more toxic than acetaldehyde. Thus, it is important to account for the toxicity and exposure, as well as the mass of the targeted emissions.

11 Defined in the IRIS database as repeated exposure by the oral, dermal, or inhalation route for more than 30 days, up to approximately 10% of the life span in humans (more than 30 days up to approximately 90 days in typically used laboratory animal species).
12 Defined in the IRIS database as exposure by the oral, dermal, or inhalation route for 24 hours or less.6-15 Figure 6-3 Estimated Chronic Census Trac t Carcinogenic Risk from HAP exposure from outdoor sources (2005 NATA)6-16 Figure 6-4 Estimated Chronic Census Trac t Noncancer (Respiratory) Risk from HAP exposure from outdoor sources (2005 NATA)

Due to methodology and time limitations under the court-ordered schedule, we were
unable to estimate the benefits associated with the hazardous air pollutants that would be reduced as a result of these rules. In a few previous anal yses of the benefits of reductions in HAPs, EPA has quantified the benefits of poten tial reductions in the incidences of cancer and non-cancer risk (e.g., U.S. EPA, 1995). In those analyses, EPA relied on unit risk f actors (URF) developed through risk assessment procedures. 13 These URFs are designed to be conservative, and as such, are more likely to represent the hi gh end of the distribution of risk rather than a best or most likely estimate of risk. As the purpose of a benefit analysis is to describe the benefits most likely
to occur from a reduction in pollution, use of high-end, conser vative risk estimates would

13 The unit risk factor is a quantitative estimate of the ca rcinogenic potency of a pollutant, often expressed as the probability of contracting cancer from a 70-year lifetime continuous exposure to a concentration of one μg/m 3 of a pollutant.6-17 overestimate the benefits of the regulation. While we used high-end risk estimates in past analyses, advice from the EPA’s Science Adviso ry Board (SAB) recommended that we avoid using high-end estimates in benefit analyses (U.S. EPA-SAB, 2002). Since this time, EPA has continued to develop better methods for anal yzing the benefits of reductions in HAPs.

As part of the second prospective analysis of the benefits and costs of the Clean Air Act (U.S. EPA, 2011a), EPA conducted a case study analys is of the health eff ects associated with reducing exposure to benzene in Houston from implementation of the Clean Air Act (IEc, 2009). While reviewing the draft report, EPA’s Adviso ry Council on Clean Air Compliance Analysis concluded that “the challenges for assessing progress in health improvement as a result of reductions in emissions of hazardous air polluta nts (HAPs) are daunting...due to a lack of exposure-response functions, uncertainties in em issions inventories and background levels, the difficulty of extrapolating risk estimates to low doses and the challenges of tracking health progress for diseases, such as cancer, that have long latency periods ” (U.S. EPA-SAB, 2008).

In 2009, EPA convened a workshop to address th e inherent complexities, limitations, and uncertainties in current methods to quantify the benefits of reducing HAPs. Recommendations from this workshop included identifying rese arch priorities, focu sing on susceptible and vulnerable populations, and improving dose-respon se relationships (Gwinn et al., 2011).

In summary, monetization of the benefits of reductions in cancer incidences requires several important inputs, includi ng central estimates of cancer risk s, estimates of exposure to carcinogenic HAPs, and estimates of the value of an avoided case of cance r (fatal and non-fatal). Due to methodology and time limitations under the cour t-ordered schedule, we did not attempt to
monetize the health benefits of reductions in HAPs in this analysis. Instead, we provide a qualitative analysis of the health effects associated with the HAPs anticipated to be reduced by
these rules and we summarize the results of th e residual risk assessmen t for the NESHAP. EPA remains committed to improving methods for estimating HAP benefits by continuing to explore additional concepts of benefits, including changes in the distribution of risk.

Available emissions data show that several different HAPs are emitted from this sector. In the subsequent sections, we describe the health effects associated with the main HAPs of6-18 concern. This rule is anticipa ted to reduce 83.6 tons of total HAP s per year as shown in Chapter 4 of this RIA, with 81 tons being metal HAP, 0.2 tons being mercury, and 2.5 tons being PAHs.

6.3.3.1 Arsenic (As) Arsenic, a naturally occurring element, is found throughout the environment and is considered toxic through the oral, inhalation and dermal routes. Acute (short-term) high-level inhalation exposure to As dust or fu mes has resulted in gastrointes tinal effects (nausea, diarrhea, abdominal pain, and gastrointestinal hemorrhage); central and peripheral nervous system disorders have occurred in workers acutely exposed to inorganic As. Chronic (long-term) inhalation exposure to inorganic As in humans is associ ated with irritation of the skin and mucous
membranes. Chronic inhalation can also lead to conjunctivitis, irritation of the throat and respiratory tract and perforation of the nasal septum. 14 Chronic oral exposure has resulted in gastrointestinal effects, anemia, peripheral ne uropathy, skin lesions, hype rpigmentation, and liver or kidney damage in humans. I norganic As exposure in humans, by the inhalation route, has been shown to be strongly associated with lung cancer, while ingestion of inorganic As in humans has
been linked to a form of skin cancer and also to bladder, liver, a nd lung cancer. EPA has classified inorganic As as a Gro up A, human carcinogen. 15

6.3.3.3 Chromium (Cr) 16
Chromium may be emitted in two forms, trivalent Cr (Cr +3 ) or hexavalent Cr (Cr +6 ). The respiratory tract is the major target organ for Cr +6 toxicity, for acute and chronic inhalation exposures. Shortness of breath, coughing, and wheezing have been reported from acute exposure
to Cr +6 , while perforations and ulcerations of the septum, bronchitis, decreased pulmonary function, pneumonia, an d other respiratory effects have be en noted from chronic exposures. Limited human studies suggest that Cr +6 inhalation exposure may be associated with complications during pregnancy and childbirth, but there are no supporting data from animal studies reporting

14 Agency for Toxic Substances and Disease Registry (ATSDR). Medical Management Guidelines for Arsenic. Atlanta, GA: U.S. Department of Health and Hu man Services. Available on the Internet at < http://www.atsdr.cdc.gov/m hmi/mmg168.html#bookmark02>
15 U.S. Environmental Protection Agency (U.S. EPA). 1998. In tegrated Risk Information System File for Arsenic. Research and Development, National Center for Environm ental Assessment, Washington, DC. This material is available electronically at: http://www.epa.gov/iris/subst/0278.htm.
16 U.S. Environmental Protection Agency . Integrated Risk Information Syst em (IRIS) on Chromium VI. National Center for Environmental Assessment, Office of Re search and Development, Washington, DC. 1999a.6-19 reproductive effects from inhalation exposure to Cr +6 . Human and animal studies have clearly established the carcinogenic potential of Cr +6 by the inhalation route, re sulting in an increased risk of lung cancer. EPA has classified Cr +6 as a Group A, human carci nogen. Trivalent Cr is less
toxic than Cr +6 . The respiratory tract is also the major target organ for Cr +3 toxicity, similar to
Cr +6 . EPA has not classified Cr +3 with respect to carcinogenicity.

6.3.3.8 Manganese (Mn) 17

Health effects in humans have been associated with both deficiencies and excess intakes of Mn. Chronic exposure to high levels of Mn by inhalation in humans results primarily in central nervous system effects. Visual reaction time, hand steadiness, and eye-hand coordination were affected in chronically-exposed workers. Mangani sm, characterized by feelings of weakness and lethargy, tremors, a masklike f ace, and psychological disturba nces, may result from chronic exposure to higher levels. Impotence and loss of lib ido have been noted in male workers afflicted with manganism attributed to inhalation exposures . The EPA has classified Mn in Group D, not classifiable as to carcinogenicity in humans.

6.3.3.9 Mercury (Hg)
In this section, we provide a qualitative description of hu man health and environmental effects due to exposure to MeHg. In 2000, the NAS Study was issued which provides a thorough review of the effects of MeHg on human health (NRC, 2000) 18 . Many of the peer-reviewed articles cited in this section are publications originally cited in the MeHg Study. In addition,
EPA has conducted literature searches to obtain other related and more recent publications to complement the material summarized by the NRC in 2000.

In its review of the literature, the NAS f ound neurodevelopmental effects to be the most sensitive and best documented endpoints and a ppropriate for establishing an RfD (NRC, 2000); in particular NAS supported the use of results fr om neurobehavioral or ne uropsychological tests.

17 U.S. Environmental Protection Agency. Integrated Risk Information System (IRIS) on Manganese. National Center for Environmental Assessment, Office of Research and Development, Washington, DC. 1999b.
18 NRC (2000) . Toxicological Effects of Methylmercury . National Research Council. Washington, DC: National Academies Press.6-20 The NAS report noted that studies in animals reported sensory eff ects as well as effects on brain development and memory functions and support th e conclusions based on epidemiology studies. The NAS noted that their recommended endpoints fo r an RfD are associated with the ability of
children to learn and to succeed in school. They concluded th e following: “The population at highest risk is the children of women who consumed large amounts of fish and seafood during pregnancy. The committee concludes that the risk to that population is likel y to be sufficient to
result in an increase in the num ber of children who have to st ruggle to keep up in school.”

The NAS summarized data on cardiovascular effects available up to 2000. Based on these and other studies, the NRC concluded that “Alt hough the data base is not as extensive for cardiovascular effects as it is for other end point s (i.e. neurologic eff ects) the cardiovascular system appears to be a target for MeHg toxicity in humans and animals.” The NRC also stated
that “additional studies are needed to better ch aracterize the effect of methylmercury exposure on blood pressure and cardiovascular f unction at various stages of life.”

Additional cardiovascular studies have been published since 2000. EPA did not to develop a quantitative dose-re sponse assessment for cardiovascul ar effects associated with MeHg exposures, as there is no consensus amon g scientists on the dose-response functions for these effects. In addition, ther e is inconsistency among available studies as to the association between MeHg exposure and vari ous cardiovascular system eff ects. The pharmacokinetics of some of the exposure measures (such as toena il Hg levels) are not well understood. The studies have not yet received the review and scrutiny of the more well-established neurotoxicity data
base.

The Mercury Study noted that MeHg is not a potent mutagen but is capable of causing chromosomal damage in a number of experiment al systems. The NAS concluded that evidence that human exposure to MeHg caused genetic damage is inconclusive; they note that some earlier studies showing chromosomal damage in lymphocyt es may not have controlled sufficiently for potential confounders. One study of adults living in the Tapajós River region in Brazil (Amorim et al., 2000) reported a direct re lationship between MeHg concentration in hair and DNA damage6-21 in lymphocytes; as well as effects on chromosomes 19 . Long-term MeHg exposures in this population were believed to occur through consump tion of fish, suggesting that genotoxic effects (largely chromosomal aberrations ) may result from dietary, chronic MeHg exposures similar to
and above those seen in the Fa roes and Seychelles populations.

Although exposure to some forms of Hg can resu lt in a decrease in immune activity or an autoimmune response (ATSDR, 1999), evidence for immunotoxic effects of MeHg is limited (NRC, 2000) 20

.
Based on limited human and animal data, Me Hg is classified as a “possible” human carcinogen by the International Agency for Res earch on Cancer (IARC, 1994) and in IRIS (USEPA, 2002) 21 , 22

. The existing evidence supporting the possi bility of carcinogenic effects in humans from low-dose chronic exposures is te nuous. Multiple human ep idemiological studies have found no significant association between Hg exposure and overall cancer incidence, although a few studies have shown an associatio n between Hg exposure and specific types of cancer incidence (e.g., acute leuke mia and liver cancer) (NRC, 2000).

There is also some evidence of reproductiv e and renal toxicity in humans from MeHg exposure. However, overall, human data rega rding reproductive, renal, and hematological toxicity from MeHg are very limited and are based on either studies of the two high-dose poisoning episodes in Iraq and Japan or animal data, rather than epidemiological studies of chronic exposures at the levels of interest in this analysis.

19 Amorim, M.I.M., D. Mergler, M.O. Bahia, H. Dubeau, D. Miranda, J. Lebel, R.R. Burbano, and M. Lucotte. 2000. Cytogenetic damage related to low levels of methyl mercury contamination in the Brazilian Amazon. An. Acad. Bras. Ciênc. 72(4): 497-507.
20 Agency for Toxic Substances and Dis ease Registry (ATSDR). 1999. Toxicological Profile for Mercury. U.S. Department of Health and Human Services , Public Health Service, Atlanta, GA.
21 U.S. Environmental Protection Agency (EPA). 2002. Integrated Risk Information System (IRIS) on Methylmercury. National Center for Environmental Assessment. Office of Research and Development. Available online at http://www.epa.gov/iris/subst/0073.htm
22 International Agency for Research on Cancer (IARC). 1994. IARC Monographs on the Evaluation of Carcinogenic Risks to Humans and their Supplements: Beryllium, Cadmium, Mercury, and Exposures in the Glass Manufacturing Industry. Vol. 58. Jalili, H.A., and A.H. Abbasi. 1961. Poisoning by ethyl mercury toluene sulphonanilide. Br. J. Indust. Med. 18 (Oct.):303-308 (as cited in NRC 2000).6-22 6.3.3.10 Nickel (Ni) 23
Respiratory effects have been reported in hu mans from inhalation exposure to Ni. No information is available regarding the reproductive or developmental effects of Ni in humans, but animal studies have reported such effects. Hu man and animal studies have reported an increased risk of lung and nasal cancers from exposure to Ni refinery dusts an d nickel subsulfide. The EPA
has classified nickel subsulfide as a human car cinogen and nickel carbo nyl as a probable human carcinogen 24,25. The IARC has classified Ni co mpounds as carcinogenic to humans.

6.3.3.11 Other Metals

Metals can cause a range of effects including, mucous membrane irritation (e.g. bronchitis, decreased lung function); gastrointe stinal effects; nervous system disorders (from loss of function to tremors and numbness); skin irritation; and reproductive and developmental disorders. Additionally, several of the metals accumulate in the environment and in the human body. Cadmium, for example, is a cumulative pollutant which causes kidney effects after the cessation of exposure. Similarly, the onset of effects from beryllium exposure may be delayed by months to years. Many of the metal listed above are also k nown (arsenic, chromium (V I), nickel) or probable (cadmium, nickel carbonyl, lead, and beryllium) human carcinogens.

6.3.3.12 Polycyclic organic matter (POM)
The term polycyclic organic matter (POM) de fines a broad class of compounds that includes the polycyclic aromatic hydrocarbon com pounds (PAHs), of which benzo[a]pyrene is a member. POM compounds are formed primarily from combustion and are present in the atmosphere in particulate form. Sources of air emissions are diverse and include cigarette smoke, vehicle exhaust, home heating, laying tar, and gr illing meat. Cancer is the major concern from exposure to POM. Epidemiologic studies have reported an increase in lung cancer in humans

23 Nickel (IARC Summary & Eval uation , Volume 49, 1990), http://www.inchem.org/documents/iarc/vol49/nickel.html
24 U.S. Environmental Protection Agency. Integrated Risk Information System (IRIS) on Nickel Subsulfide. National Center for Environmental Assessment, Office of Research and Development, Washington, DC. 1999c.
25 U.S. Environmental Protection Agency. Integrated Risk Information System (IRIS) on Nickel Carbonyl. National Center for Environmental Assessment, Office of Research and Development, Washington, DC. 1999d.6-23 exposed to coke oven emissions, roofing tar emi ssions, and cigarette smoke; all of these mixtures contain POM compounds. Animal studies have re ported respiratory tract tumors from inhalation exposure to benzo[a]pyrene and forestomach tu mors, leukemia, and lung tumors from oral exposure to benzo[a]pyrene. EPA has classified seven PAHs (benzo[a]pyrene, benz[a]anthracene, chrysene, benzo[b]fluoranthene, benzo[k]fluoran thene, dibenz[a,h]anthracene, and indeno[1,2,3- cd]pyrene) as Group B2, pr obable human carcinogens

6.3.3.13 Other Air Toxics In addition to the compounds described a bove, other compounds from the ferroalloy sector would be affected by this rule. Inform ation regarding the health effects of these compounds can be found in EPA’s IRIS database. 26

6.4 Characterization of Uncertainty in the Monetized PM 2.5 Benefits In any complex analysis, there are likely to be many sources of uncertainty. Many inputs are used to derive the final estimate of econo mic benefits, including emission inventories, air quality models (with their associated paramete rs and inputs), epidemio logical estimates of concentration-response (C-R) f unctions, estimates of values , population estimates, income estimates, and estimates of the future state of the world (i.e., regula tions, technology, and human behavior). For some parameters or inputs it may be possible to provide a st atistical representation of the underlying uncertainty distribution. For other parameters or inputs, the necessary information is not available.
The annual benefit estimates presen ted in this analysis are also inherently variable due to the processes that govern pollutant emissions a nd ambient air quality in a given year. Factors such as hours of equipment use a nd weather are constantly variable , regardless of our ability to measure them accurately. As discussed in the PM 2.5 NAAQS RIA (Table 4-5) (U.S. EPA, 2006b), there are a variety of uncer tainties associated with these PM benef its. Therefore, the estimates of annual benefits should be viewed as representative of the magnitude of benefits expected, rather than the actual bene fits that would o ccur every year.
It is important to note that the monetized benefit-per-ton estimates used here reflect specific geographic patterns of emissions redu ctions and specific air quality and benefits modeling assumptions. However, these estimates be tter reflect local variability in population density, meteorology, exposure, baseline health inci dence rates, or other local factors than the

26 U.S. EPA Integrated Risk Information System (IR IS) database is available at: www.epa.gov/iris6-24 benefit-per-ton estimates previous ly used, due to the sector-speci fic air quality modeling utilized. Nonetheless, use of these $/ton values to estimate benefits asso ciated with different emission control programs may lead to hi gher or lower benefit estimates than if benefits were calculated based on direct air quality mode ling. Great care should be taken in applying these estimates to emission reductions occurring in any specific location, as these re present average benefits-perton for the sector over the entire United Stat es. The benefits-per-ton fo r emission reductions in specific locations may be very different than the estimates presented here.

PM 2.5 mortality benefits are the largest benef it category that we monetized in this analysis. To better characterize the uncertainty associated with mort ality impacts that are estimated to occur in areas with low baseline levels of PM 2.5 , we included the LML assessment. This approach summarizes the distribution of avoided PM mortality impacts according to the baseline PM 2.5 levels experienced by the population receiving the PM 2.5 mortality benefit (Figures 6-5 and 6-6). We identify on this figure th e lowest air quality levels measured in each of the two primary epidemiological studies EPA used to quantify PM-related mortality. This information allows readers to determine the por tion of PM-related morta lity benefits occurring above or below the LML of each study; in genera l, our confidence in the estimated PM mortality decreases as we consider air quality levels fu rther below the LML in the two epidemiological studies. While the LML analysis provides some insight into the level of uncertainty in the estimated PM mortality 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. While this figure describes the relationship between baseline PM 2.5 exposure and mortality for the air quality modeled policy case, we expect the distribution of mo rtality impacts to be fairly similar between the two cases.
Some proportion of the avoided PM-related imp acts we estimate in this analysis occur among populations exposed at or above the LM L of the Laden et al. (2006) study, while a majority of the impacts occur at or above the LM L of the Pope et al. (2002) study (Figure 6-5), increasing our confidence in the PM mortality anal ysis. Based on the air quality baseline used for the source apportionment modeling, 31% and 89% of the estimated avoided mortality impacts occur at or above an annual mean PM 2.5 level of 10 μg/m 3 (the LML of the Laden et al. 2006 study) and 7.5 μg/m 3 (the LML of the Pope et al. 2002 study), respectively. As we model mortality impacts among populations exposed to levels of PM 2.5 that are successively lower than the LML of each study our confidence in the results diminishes.
While the LML of each study is important to consider when characterizing and interpreting the overall level PM-related benefits , as discussed earlier in this chapter, EPA6-25 believes that both cohort-based mortality estimates are suitable for use in air pollution health impact analyses. When estimating PM mortality im pacts using risk coefficients drawn from the Laden et al. (2006) analysis of the Harvard Six Ci ties and the Pope et al. (2002) analysis of the American Cancer Society cohorts there are innumera ble other attributes that may affect the size of the reported risk estimates—including differe nces in population demogr aphics, the size of the cohort, activity patterns and particle compos ition among others. The LML assessment presented here provides a limited representation of one key difference between the two studies.

Figure 6-5. Percentage of Total PM-Related Mortalities Avoided by Baseline Air Quality Level6-26 Figure 6-6. Cumulative Percentage of Total PM-Related Mortalities Avoided by Baseline Air Quality Level Above we present the estimates of the total monetized benefits, based on our interpretation of the best avai lable scientific literature a nd methods and supported by the SABHES and the NAS (NRC, 2002). The benefits estima tes are subject to a number of assumptions and uncertainties. For example, for key assu mptions underlying the estimates for premature mortality, which typically account for at least 90% of the total monetized benefits, we were able to quantify include the following:

1. PM 2.5 benefits were derived through benefit pe r-ton estimates, which in general 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 benefits of controlling directly emitted fine particulates. However, these estimates better reflect variability in these local factors than the benefit-per-ton estimates pr eviously used, due to the sector-specific air quality modeling utilized.
2. We assume that all fine particles, re gardless of their chemical composition, are equally potent in causing pr emature mortality. This is an important assumption, because PM 2.5 produced via transported precursors emitted from EGUs may differ significantly from direct PM 2.5 released from diesel engi nes and other industrial6-27 sources, but the scientific ev idence is not yet sufficient to allow differentiation of effect estimates by particle type.
3. We assume that the health impact functi on for fine particles is linear down to the lowest air quality levels modeled in this analysis. Thus, the estimates include health benefits from reducing fine particles in areas with varied concentrations of PM 2.5, including both regions that are in attainment with fine particle standard and those that do not meet the standard down to th e lowest modeled concentrations.
4. To characterize the uncertainty in the relationship between PM 2.5 and premature mortality (which typically accounts for 85% to 95% of total monetized 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 PM 2.5 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 PM 2.5 benefits, please consult the PM 2.5 NAAQS RIA (Table 5-5).
This RIA does not include the type of detail ed uncertainty assessment found in the PM NAAQS RIA (U.S. EPA, 2006b) because we lack th e necessary air quality input and monitoring data to run the benefits model. In addition, we have not conducted any air quality modeling for this rule. Moreover, it was not possible to de velop benefit-per-ton metrics and associated estimates of uncertainty using the benefits estim ates 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 benefits presented in Chapter 5 of the PM RIA can provide some evidence of th e uncertainty surrounding the benefits results presented in this analysis.7-28 SECTION 7 COMPARISON OF MONETIZED BENEFITS AND COSTS

7.1 Summary Because we were unable to monetize the co-b enefits associated with reducing HAPs, all monetized benefits reflect improvements in ambient PM 2.5 concentrations from reductions in
PM 2.5 emissions. This results in an underestim ate of the monetized benefits. Using a 3% discount rate, we estimate the total monetized benef its of this proposed rule to be $71 million to $170 million in the year of implementation (2015) as shown in Table 7-1. Using a 7% discount rate, we estimate the total monetized benefits to be $63 million to $160 million in 2015. The annualized social costs are $4.0 million. The ne t benefits are therefore $67 million to $170
million at a 3% discount rate for the benefits and $59 million to $150 million at a 7% discount rate. All estimates are in 2010$. The benefits from reducing other air poll utants have not been monetized in this analysis, including reducing tons of, black carbon and several HAPs emissions such as formaldehyde, mercury and ni ckel among others each year.

Figure 7-1 shows the full range of net benef its estimates (i.e., annual benefits minus annualized costs) quantified in terms of PM 2.5 benefits for the year of implementation (2015).

Table 7-1. Summary of the Annual Monetized Be nefits, Social Costs, and Net Benefits for the Proposed Ferroalloys RTR in 2015 ($2010 millions) a

3% Discount Rate 7% Discount Rate Proposed Standard Total Monetized Benefits b $71 to $170 $63 to $160 Total Social Costs $4.0 $4.0 Net Benefits $67 to $170 $59 to $150 Nonmonetized Benefits Reduced exposure to HAPs, including arsenic, chromium, nickel, manganese, mercury and polycyclic aromatic hydrocarbons Ecosystem effects Visibility impairment

a All estimates are for the year of implementation (2015) and are rounded to two significant figures. These results

include units anticipated to come online and the lowest cost disposal assumption.
b The total monetized benefits reflect the human health benefits associat ed with reducing exposure to PM 2.5 through

reductions of directly emitted PM 2.5 . It is important to note that the monetized benefits include many but not all health effects a ssociated with PM 2.5 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 the scientific evidence is not yet sufficie nt to allow differentiation of effect estimates by particle type.7-29 Figure 7-1. Net Annual Benefits Range in 2015 for PM 2.5 Reductions for the Proposed Standard $0 $50,000,000 $100,000,000 $150,000,000 $200,000,000 $250,000,000

Pope et al. Laden et al.(2010$)

Cost estimate combined with total monetized benefits estimates derived from 2 epidemiology functions and 12 expert functionsSECTION 8 REFERENCES FOR RIA Agency for Toxic Substances and Disease Registry (ATSDR). 1995. Toxicological profile for Polycyclic Aromatic Hydrocarbons (PAHs) . Atlanta, GA: U.S. Department of Health and Human Services, Public Health Service. Available electronically at http://www.atsdr.cdc.gov/ToxP rofiles/TP.asp?id=122&tid=25.
Agency for Toxic Substances and Disease Registry (ATSDR). Medical Management Guidelines for Arsenic . Atlanta, GA: U.S. Department of He alth and Human Services. Available on the Internet at < http://www.at sdr.cdc.gov/mhmi/mmg168.html#bookmark02>
Agency for Toxic Substances and Disease Registry (ATSDR). 1999. Toxicological Profile for Mercury . Agency for Toxic Substances and Disease Registry.
Amorim, M.I.M., D. Mergler, M.O. Bahia, H. Dubeau, D. Miranda, J. Lebel, R.R. Burbano, and M. Lucotte. 2000. Cytogenetic damage relate d to low levels of methyl mercury contamination in the Brazilian Amazon. An. Acad. Bras. Ciênc. 72(4): 497-507.
Dun & Bradstreet (D&B). 2010. D&B Marketplace . A company information database searchable by NAICS code. Accessed on July 15, 2010.
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