Abt Associates Inc., January 10, 2013 Contract EP-C-07-023, Assignment 5-17, QAPP i 

### Q UALITY 

### A SSURANCE 

### P ROJECT 

### P LAN 

### (QAPP) FOR 

### : E CONOMIC 

### I MPACT AND 

### B ENEFITS 

### A NALYSIS FOR 

### S TEAM 

### E LECTRIC 

### R ULEMAKING



## Table of Contents

1 Project Objectives, Organization, and Responsibilities ................................................................ 1

1.1 Project objective/goal ........................................................................................................ ........ 1

1.2 Project requirements related to primary and secondary data ..................................................... 2

1.3 Training and competency requirements necessary for key project personnel ........................... 3

1.4 Role and responsibilities of project personnel ........................................................................... 3

1.4.1 Project management and performance ........................................................................... 3

1.4.2 Summary of Quality Assurance Project Pl an responsibilities and implementation....... 4

2 Acquisition and Use of Primary Data ........................................................................................... .. 5

2.1 Steam Electric Survey ......................................................................................................... ...... 5

2.1.1 Data quality, data entry, and an alysis of survey data ..................................................... 5

3 Acquisition and Use of Secondary Data ......................................................................................... 6

3.1 Sources used to identify secondary data .................................................................................... 7

3.1.1 Government, peer-reviewed publi cations and other sources ......................................... 8

3.1.2 Models ........................................................................................................................ ... 9

3.1.3 Input costs ................................................................................................................... . 11

3.1.4 Environmental effects .................................................................................................. 11

3.2 Quality requirements of, and acceptance criteria for, secondary data ..................................... 11

3.3 Data reduction, validation, and verifi cation procedures and documentation .......................... 12

3.3.1 Data reduction procedures and documentation ............................................................ 12

3.3.2 Data validation and verification procedures and documentation ................................. 13

3.3.3 Special provisions for quick turnaround deliverables .................................................. 15

3.3.4 Data storage ................................................................................................................. 15

4 Expected Work Products ........................................................................................................ ....... 17

5 Acceptance by the EPA WAM ..................................................................................................... . 17Abt Associates Inc., January 10, 2013 Contract EP-C-07-023, Assignment 5-17, QAPP iiChanges to QAPP for Support of Work Assignment 5-17 under Contract EP-C-07-023Revision 0 1 2 3Comments Received NA NA NA NADelivered 9/8/2011 10/17/2011 05/23/2012 01/10/2013Cover PageCover PageRevised to reflect currentwork assignment number andchange in Abt Associates’contract-level QualityAssurance Manager1: Project Objectives, Organization, and Responsibilities1.1: Project objective/goalUpdated to reflect projectobjectives/goals as outlinedin work assignment 4-17,including informationpertinent to using survey dataand conducting analyses.Revised to reflect projectobjectives/goals as outlinedin work assignment 5-17.1.2: Project requirementsrelated to primary andsecondary dataIdem.Revised to reflect analysesneeds, notably benefitcategories.1.3: Training andcompetency requirementsnecessary for key projectpersonnelSection added in its entirety.1.4: Role and responsibilitiesof project personnelChanges to reflect currentproject staffing/needs. Addedmore information on PQA’srole and QA process.Corrected minor typo inSection 1.4.2Changed Elaine Haemiseggerto Michael Conti to reflect achange in QAM.Revised to reflect change inAbt Associates’ contractlevel Quality AssuranceManager.2: Acquisition and Use of Primary Data2 Steam Electric Survey Section added in its entirety.Minor revisions to thedescription of the survey.3: Acquisition and Use of Secondary Data3.1: Sources used to identifysecondary dataConsolidated contents ofSections 2.1 and 2.2 from theQAPP used for previouswork assignment. Updated toreflect current project needs.Revised to reflect additionalsecondary data and models tosupport analysis of additionalbenefit categories notpreviously covered.Abt Associates Inc., January 10, 2013 Contract EP-C-07-023, Assignment 5-17, QAPP iiiChanges to QAPP for Support of Work Assignment 5-17 under Contract EP-C-07-023Revision 0 1 2 3Comments Received NA NA NA NADelivered 9/8/2011 10/17/2011 05/23/2012 01/10/20133.2: Quality requirements of,and acceptance criteria for,secondary dataConsolidated contents ofSections 2.3 and 2.4 from theQAPP used for previouswork assignment.Revised to reflect additionalsecondary data and models tosupport analysis of additionalbenefit categories notpreviously covered.3.3: Data reduction,validation, and verificationprocedures anddocumentationAdded more detailedinformation on internalreview, data storage, anddocumentation processes.Corrected minor typo inSection 3.3.24: Expected Work Products4: Expected Work ProductsUpdated to reflect currentproject needs.Changed Elaine Haemiseggerto Michael Conti to reflect achange in QAM.Revised to note specificreports.5: Acceptance by the EPA WAM5: Acceptance by the EPAWAMNon-substantive changes tothe wording.Abt Associates Inc., January 10, 2013 Cont ract EP-C-07-023, Assignment 5-17, QAPP 1 

### 1 Project Objectives, Organization, and Responsibilities

1.1 Project objective/goal Under Contract EP-C-07-023, Work Assignment 5-17, Abt Associates is supporting the Office of Science and Technology/Engineering and Analysis Division in analyzing the cost and economic impacts, environmental impacts, and benef its of revisions to the Steam El ectric Power Generating effluent limitations guidelines and standards (Steam Elect ric ELGs) (40 CFR 423). Work under this assignment specifically includes:

 Analysis of the costs and economic impacts of the proposed ELGs;

 Technical support for Executive Orders a nd other Statutory requirements; and

 Analysis of the benefits of the proposed ELGs.
The work assignment builds on predecessor work assignments under Contract EP-C-07-023 which involved several related activities, most notably the re view and collection of primary data to characterize the ownership structure and financia l conditions of steam electric plants, the review and collection of secondary data to develop a profile of the Steam Electric industry, and other technical support of rulemaking activities, such as responding to questions about economic issues, and preparing briefing and meeting material. As such, this QAPP discusses not on ly the current tasks outlined above, but also tasks conducted under the predecessor work assignments whic h have potential implications for the cost and benefit analyses.
The economic impact analyses expected to be conduc ted to support revisions of Steam Electric ELGs were detailed in a separate Abt Associates memorandum (dated October 9, 2009). This memorandum, which is enclosed in Appendix A, provides additi onal description of the economic impact analyses for which primary and secondary data are needed. A separate memorandum, included in Appendix B, describes benefit analyses. Note th at these descriptions were prepared at the outset of the rulemaking effort and may differ from the analyses conducted under this work assignment, which will be described in the reports discussed in Section 4, i.e., the Regulator y Impact Analysis (RIA) and the Benefits and Costs Analysis (BCA) reports.
This QAPP revises the QAPP previously prepared under a predecessor work assignment (WA 4-17) to incorporate information and data s ources subsequently identified or descr ibe procedures relevant to this later phase of the project. For example, the revisions address the use of models to determine changes in water quality and for use as inputs in benefits analyses.
This QAPP contains procedures that are consistent with EPA’s quality assurance guidance specified in EPA Requirements for Quality Assurance Project Plans (EPA, 2001) and with Abt Associates’ own corporate quality management plan (this corporate plan meets the requirements of the American National Standard Specifications and Guidelines for Qualit y Systems for Environmental Data Collection and Environmental Technology Programs (ANSI/ASQC E4 -1994)). The QAPP was developed to meet the standards of accuracy and transparency for EPA regul atory analyses and will provide quality control for all primary and secondary data used under this work assignment. Abt Associates’ quality assurance coordinators and project management team plan , implement, and assess project quality procedures throughout all project activities. These procedures are ta ilored to the needs of each individual task and will be used on this work assignment. A copy of this QAPP will be provided to all Abt Associates staff involved in this project, including those who join the project after preparation of the QAPP.Abt Associates Inc., January 10, 2013 Cont ract EP-C-07-023, Assignment 5-17, QAPP 2 1.2 Project requirements related to primary and secondary data For analyzing the cost and economic impact of revi sions to the Steam Electric ELGs, Abt Associates will continue to rely on certain primary source data that were collected as part of a survey of Steam Electric facilities conducted in 2010 and on seconda ry data available from public sources.
Survey data provide information on the design and operation of steam electric plants, steam generation units, waste handling and treatment systems, and di scharge characteristics. Th e survey also provides detailed financial information on each plant and its respective immediate and ultimate owner(s). EPA plans to use these data to support important elements of the analysis, in particular for linking the costs of regulatory compliance to the plants and to their resp ective owners, and in evaluating the significance of compliance costs on regulated facilities and parent firm s. Several steps were taken to clean and validate the survey data, including an in-depth review of the completeness of the information for each plant, internal integrity checks, and outlier tests 1

. In addition to using this primar y source data from the Steam Electric facility questionnaire, Abt Associates will also rely substantially on secondary source data for this analysis. Secondary source data for the economic impacts analysis include:

 Data that are descriptive of current operati ng and business conditions at the electric power facilities expected to be subject to regulation, and the business conditions of the firms and other entities that own these facilities. These data w ill support the assessment of baseline operations and economic/financial performance for facilities subj ect to regulation, and thus provide the basis for understanding the impact of the regulation on these facilities and the firms that own them.

 Data describing economic/financial conditions in, and the regulator y environment of, the electric power industry, generally.

 Data on electricity prices, which may be affect ed by the regulation and thus in turn cause an economic impact on electricity consumers.

 Cost and/or price index data that are used to adjust dollar values from one time period to another time period.
Abt Associates also expects to rely on analysis and outputs from the Integrated Planning Model (IPM) to assess the potential impact of regulatory requirement s on power generating facilities and general market conditions within the context of regional and nati onal electricity markets. Outputs from IPM may be reviewed against information provided directly by plants in the Steam Electric questionnaire to assess whether the model results are reasonable.
For analyzing the benefits expected to be achie ved by revisions to the Steam Electric ELGs, Abt Associates will rely on primary and secondary source data to characterize the benefits of reducing pollutant loadings from Steam Electric plants on human health and aquatic ecosystems. The Steam Electric questionnaire provides primary data on the lo cation of each plant, type of receiving water body, name of the water body, and discharge characteristic s. These primary data are being compiled under a separate work assignment (they are part of the Environmental Assessment ) and quality assurance is therefore not described herein. For the purpose of th is effort, we generally assume that the data are accurate and plan to perform only general review to en sure completeness (e.g., all plants expected to have data are included in the data set, coordinates have valid).

1 For example, we flagged as potential outliers, values outside the range represented by the average plus three times the interquartile range.Abt Associates Inc., January 10, 2013 Cont ract EP-C-07-023, Assignment 5-17, QAPP 3 Secondary source data for the benefits analysis include:

 Data describing the characteristics of water bodies receiving discharges from Steam Electric facilities, including ambient water quality, impairme nt information, and environmental resources.

 Demographic data on the population located in proximity to each Steam Electric facility or which may otherwise be affected by Steam Elec tric discharges (e.g., fisher population).

 Data characterizing the changes in in-stream c oncentrations of discharged pollutants under each regulatory option determined as part of the Enviro nmental Assessment or modeled using pollutant fate and transport models.

 Data characterizing the human health effect s of discharged pollutants (e.g., dose response functions) and the monetary valu e of avoiding these effects (e.g., cost of illness, willingness to pay).

 As applicable, depending on the type of benef its expected to result from the regulation, data describing commercial landings and the value of commercial catch, and data describing recreational fishing (e.g., catch by species, value of recreational catch, and number of participants).

 As applicable, depending on the type of benefits expected to result from the regulation, data on the federally listed threatened and endangered species affected by changes in water quality.

 As applicable, depending on the type of benefits expected to result from the regulation, data on surface impoundments used to manage coal combustion residuals (CCR), historical releases from these impoundments, and cleanup and other costs resulting from these releases.
We provide details of the sources, criterion for selecti on, and use of secondary data, including selection of IPM to support this analysis in Section 3: Acquisition and Use of Secondary Data.

1.3 Training and competency requirements necessary for key project personnel Key personnel assigned to this work assignment will have training in a discipline relevant to the analyses contemplated under the work assignment (economics, fina nce, engineering, or environmental science) and demonstrated expertise in conducting economic impact and benefit analyses to support EPA rulemaking. Relevant expertise of key pers onnel will include, for example:

 Knowledge of the regulated indust ry (electric power generation);

 Experience with developing analytic frameworks to quantify impacts of regulations on affected entities and/or with quantifying market and n on-market benefits of regulations; and

 Familiarity and demonstrated experience with impl ementation of a variety of analytic techniques (e.g., statistics, systems modeling) or software tools (spreadsheet models, relational databases).

1.4 Role and responsibilities of project personnel

1.4.1 Project management and performance The Abt Associates Assignment Manager, Ms. Isabelle Morin, is responsible for the overall coordination and performance of the tasks under this project, including the analyses using primary and secondary source data and quality oversight.
Ms. Tatiana Melnikova is the Deputy Assignment Ma nager and lead economist working with Ms. Morin for the cost and economic impact analysis of revi sions to the Steam Electric ELGs. Dr. Elena Besedin leads the environmental assessment and benefits analys is for the regulation. Other Abt Associates analystsAbt Associates Inc., January 10, 2013 Cont ract EP-C-07-023, Assignment 5-17, QAPP 4 and research assistants report to, or work with, Ms. Morin, Ms. Melnikova, and Dr. Besedin in performing the analyses and are responsible for implementing QAQC procedures.
In addition, Mr. Michael Fisher is responsible as Abt Associates Project Quality Advisor (PQA) for reviewing and providing counsel on the overall regulator y analysis effort. The role of the PQA is to ensure that all data used in the project and the analyses based on these data w ill meet EPA project quality assurance requirements. As Abt Associ ates’ officer-level director of the EP-C-07-023 contract, Mr. Fisher is also responsible for the overa ll performance of the work assignment.
The Quality Assurance Manager for the EP-C-07-023 contract, Ms. Susan Day, is responsible for resolving any quality assurance concerns that arise fr om the technical review that cannot be resolved among the Abt Associates assignment manager, the task managers, and the PQA.
The organizational chart below summarizes the dist ribution of responsibilities for performance and quality assurance.
Figure 1-1: Work Assignment Quality Assurance/Quality Control Organizational Chart.

1.4.2 Summary of Quality Assurance Project Plan responsibilities and implementation In her capacity as overall work assignment manager (W AM), Ms. Morin serves as Abt Associates’ overall lead for the work assignment and is ultimately res ponsible for quality assurance. Ms. Morin will ensure that the methodologies, data, analyses, and work assi gnment deliverables meet Abt Associates standards for project quality, and also meet the standards set forth in this QAPP. Ms. Morin will work with the Project Quality Advisor (PQA) to conduct reviews of analytic components such as methods or data sources (see below). Each of the managers and othe r key personnel named above will also be responsible for implementing the provisions of this QAPP in th eir respective areas of resp onsibility in the work assignment.
In his capacity as PQA for the work assignment, Mr. Fi sher will participate in discussions regarding the methodology and will review major deliverables and/ or delegate PQA reviews to other personnel, as needed and appropriate, to ensure that the data, an alyses, and work product for the various parts of the work assignment meet the quality standards of this QAPP.
The Quality Assurance Manager (QAM) for the EP-C-07- 023 contract, Ms. Susan Day, is responsible for resolving any quality assurance concerns that arise fr om the technical review that cannot be resolved among the Abt Associates managers, and the work assignment PQA.Abt Associates Inc., January 10, 2013 Cont ract EP-C-07-023, Assignment 5-17, QAPP 5 

### 2 Acquisition and Use of Primary Data

2.1 Steam Electric Survey EPA collected primary source data through a survey of steam electric plants, conducted in 2010. EPA identified approximately 1,200 fossil- and nuclear-fueled steam electric power plants that are potentially within scope of the steam electric ELG rule. Of those, the owners or operators of 733 plants were asked to provide the requested information. Surveyed plants include all co al and petroleum coke-fired power plants, and a statistical subset of oil-fired, g as-fired, and nuclear power plants. The questionnaire consisted of nine sections and co llected general plant information and selected technical information about electric generating units and plant processes (e.g ., flue gas desulfurization (FGD) wastewater, ash handling, cleaning of metal process equipment, wastewater treatment, and surface impoundment and landfill operations). Most relevant for this work assignm ent, Part I of the questionnaire asked for detailed financial and economic information at the levels of the plants, owners , and generating units. Data were requested for 2007, 2008, and 2009, to mitigate the impacts of any abnormal year on steam electric operations or revenue.
Table 1 highlights selected data contained in the Stea m Electric survey database that may be used in conducting analyses of the cost impacts or benefits of the regulation.
Table 1: Example data from St eam Electric Survey Database.

Data Type Example Data Generation unit Annual operating costs Fuel costs Capacity utilization Annual outages Plant Steam electric generation capacity Revenue and costs Ash marketing revenue and costs Plant coordinates Receiving water body(ies) Immediate Parent Ownership share Identity of ultimate parent Income statement Balance sheet Cash flow information Ultimate Parent NAICS sector Total revenue and revenue from electricity generation Number of employees Total electricity sales

2.1.1 Data quality, data entry, and analysis of survey data In the period of fall 2010 through spring 2011, Abt Associates extracted data for Part I of the steam electric questionnaire provided by each respondent in individual Excel spreadsheets and assembled all responses in a single Microsoft Access relational datab ase. The data are organized in indexed tables with relationships between the tables defined to ensure inte rnal consistency and integrity of the data at the plant, owner, and unit level.
The data cleaning and review steps included revi ewing the data for completeness and internal consistency, making adjustments and/or following up with respondents as needed. For example, the following data checks were conducted (see A ppendix C for a more detailed description):

 Reviewing blank, zero, and not applicable entries . The data review included differentiating among values entered as zero, left blank, or not applicable.Abt Associates Inc., January 10, 2013 Cont ract EP-C-07-023, Assignment 5-17, QAPP 6  Standardizing owner records : For example, plants are associat ed to uniquely defined immediate owners and these immediate owners are associat ed with uniquely defined ultimate parent companies. Data for the immediate or ultimate parent companies were then consolidated to maximize the number of fields with information filled in.

 Correcting ownership shares : We calculated the total ownership shares reported for each plant and made sure that the total added to 100 per cent. In several instances, the respondents had entered a fraction instead of percentages (e.g., 0. 8 instead of 80); we corrected those entries.

 Total electricity sales and total employment . We generally confirmed that both fields contained non-zero values. We noted cases where either fiel d was blank and, in the event that this information is needed to assess SBA size category (i .e., the immediate parent is also the ultimate parent), we collected the data from other sources such as other Part I responses for the same entity or the entity’s annual report or SEC filing in orde r to determine the relevant SBA size category.

 Revenue from electricity generation vs. total revenue . We generally verified that electricity generation revenue reported for each immediate parent was smaller than the total revenue reported for that parent. Twenty-seven respondent s entered total revenue slightly lower than revenue from electricity generation for one or more years. In cases where more detailed revenue information was provided in Section 2 of the ques tionnaire, we used the detailed data to correct the summary information in Section 1.

 Compiling and linking ancillary data : We obtained publicly available data not requested as part of the survey and organized the data in tables within the database to facilitate querying. For example, relevant Census population data we re compiled for each owning entity identified as government to support classification of the entiti es as small/non-small. The source of each data item is identified directly in the table.
We anticipate that additional data cleaning and review may be conducted as analytic needs are identified and refined based on EPA direction. In accordance wi th this QAPP, any change to data provided by respondents will be flagged and documented with th e reason for the change and the source of the new values.
In cases where survey data are not available for a gi ven plant or owner, Abt Associates will discuss with the EPA assignment manager appropriate methods for imputing needed values based on available data, using either the survey data or secondary data di scussed in Section 3. Data imputation methods may entail, for example, using average values of data re ported for other plants or owners (e.g., using average fuel costs for other plants within the same NERC region) or estimating missing values based on other information available for the plant or owner (e.g., a llocating revenue to the plant in proportion to the quantity of electricity generated).
A substantive share of the survey data was cla ssified by the respondents as Confidential Business Information (CBI). Abt Associates will treat these data in accordance with the EPA-approved CBI plan for this contract. In order to protect CBI, any reportin g of the survey data (or deducible survey data) in documentation will only present data in aggregated form.


### 3 Acquisition and Use of Secondary Data Primary data described above (namely the Steam Electric survey) will be supplemented with data available from secondary data sources described in this section. Table 2 lists examples of secondary data.Abt Associates Inc., January 10, 2013 Cont ract EP-C-07-023, Assignment 5-17, QAPP 7 Table 2: Examples of Secondary Data Sources.

Data Type Example Data Secondary Data Sources Technology costs Capital costs Annual O&M costs Life EPA (Engineering Analysis)

Plant and owner characteristics Electricity generation Nameplate capacity Number of ratepayers EIA; FERC

Parent company financials Revenue Electricity generation Size SEC Form 10-K; Annual Operating Report; SBA

Size thresholds NAICS-specific threshold for small entity determination SBA

Industry trends and
events Mergers and acquisitions Press releases; EIA; FERC; Economic Census

Economic indicators and indices GDP deflator Consumer Price Index Construction Cost Index Labor cost index BEA; BLS

Burden estimates Labor rates BLS Projected market behavior Changes in electricity production levels and
costs IPM

Demographic data Population poten tially affected U.S. Census

Potentially affected

resources Drinking water intake loca tions EPA SDWIS database

Environmental effects Am bient concentrations of pollutants of concern Changes in pollutant concentration in fish tissue Extent of geographical ar ea affected by Steam Electric discharges (e.g ., water body reach) Changes in air emissions EPA (Environmental Assessment); water quality models (e.g., SPARROW, RSEI); IPM

Hazard Identification Potential for human and ecological health impacts Dose response functions EPA IRIS; Health Effects Assessment Summary Tables (HEAST); EPA’s National Recommended Water Quality Criteria (WQC); EPA’s Maximum Contaminant Levels for Drinking Water (MCL), and Peer-reviewed journal articles a nd government reports. Avoided impoundment failure costs Historical impoundment failure data (year, size) Cleanup, environmental damage and litigation
costs EPA ORCR impoundment survey and CCR Rule support documents

Value of avoided health effects or other benefits Willingness to pay to avoid adverse health effects Cost of illness Value of a statistical life EPA benefit-per-ton es timates for avoiding mortality due to exposure to air pollutants; meta-analysis of valuation studies

Projected market behavior Changes in electricity production levels and
costs IPM

3.1 Sources used to identify secondary data Abt Associates identified secondary data sources for this work through research of relevant literature and publications, internet research, and communication with e xperts in the relevant fields of study. Each data source is evaluated relative to its appropriateness for the specific application to this project. Many data sources for this work are compiled and published by federal agencies. In this Work Assignment, Abt Associates will continue to review and compile these data for use in preparing a profile of the Steam Electric industry and in supporting the economic impact analysis.Abt Associates Inc., January 10, 2013 Cont ract EP-C-07-023, Assignment 5-17, QAPP 8 3.1.1 Government, peer-reviewed publications and other sources For the cost and economic impact analysis, the fe deral government data sources include the Energy Information Administration (EIA) of the U.S. Departme nt of Energy (in particular, the EIA 767, 860, 861, and 906 datasets) 2 , the Federal Energy Regulatory Commission (FERC) (in particular, Form 1), the U.S. Small Business Administration, the Bureau of Labor St atistics, and the Bureau of Economic Analysis. All of these data are compiled by the relevant federal ag encies and thus meet federal government data quality standards. These data sources are appropriate for th is analysis based on the standards underlying their collection and publication, and their applicability to analyzing the cost and economic impact of revisions to the Steam Electric ELGs. These federal government data will be used to supplement more detailed primary data collected through the Steam Electric detailed questionnaire.
In addition, the cost and economic impact analysis ma y also rely on firm financial data that have been compiled and reduced by private entities, including da ta and information reported by publicly traded firms in Forms 10-K as required to be submitted by the federal Securities and Exchange Commission or published by well-established financial analysis ser vices such as Standard & Poor’s or Value Line Investment Survey. These data sources are appropriate for this analysis based on the standards underlying their collection and publication, and their applicability to analyzing the cost and economic impact of revisions to the Steam Electric ELGs.
For the benefits analysis, the key secondary data sour ces are expected to include the U.S. Census Bureau population and household data, peer-re viewed literature on dose response functions, cost of illness, and willingness to pay for avoiding adverse health effects or environmental improveme nts, data from EPA’s SDWIS Safe Drinking Water Information System (SDW IS) on public water systems, outputs from EPA’s Integrated Exposure, Uptake, and Biokinetics (IEUB K) Model for Lead in Children model, the NMFS Marine Recreational Fishing Statistics Survey, the 20 06 USFWS Annual Survey of Fishing, Hunting, and Wildlife-related recreation, the U.S. FWS’ Threaten ed and Endangered Species System (TESS) database, the Environmental Valuation Resource Inventory (EVRI), and other data published by the U.S. Environmental Protection Agency or other federal government agencies. If needed to assess benefits in reaches downstream from Steam Electric plant dischar ges, we will use loading estimates developed as part of the Environmental Assessment to model c oncentrations downstream from steam electric plant discharges using water quality models such as th e Spatially Referenced Regressions on Watershed Attributes (SPARROW) or the Risk-Screening Environm ental Indicators (RSEI) models. In addition, the benefit analysis will use Bureau of Economic Analys is data on economic indicators (e.g., GDP Deflator, Consumer Price Index) to adjust dollar valu es to a common dollar-year. These data sources are appropriate for this analysis based on their applicability (e.g., Consumer Pr ice Index) to benefits analysis of revisions to the Steam Electric ELGs.
Additional sources of secondary data are likely to in clude academic journals and other peer-reviewed publications, government reports and databases, and working papers. We will identify these data sources through literature and data searches of the EconLit da tabase, Infotrieve’s ArticleFinder database, the Internet (which is frequently a good source of worki ng papers and other documents that have not reached the stage of formal publication), and bibliographi es or publications from government organizations. These data sources will be peer-reviewed, widely used a nd accepted in economic and policy analyses performed by EPA and other government and private organizations, and publicly available.

2 EIA-767: Annual Steam-Electric Plant Operation and Design Data (annual); EIA-860: Annual Electric Generator Report; EIA-861: Annual Electric Power Industry Database; EIA-923: Utility, Non-Utility, and Combined Heat & Power Plant Database (monthly).Abt Associates Inc., January 10, 2013 Cont ract EP-C-07-023, Assignment 5-17, QAPP 9 This Work Assignment includes a specific benefits litera ture review task that will seek to identify relevant additional secondary data sources for benefits analysis . The Benefit and Cost Analysis (BCA) report will detail all data sources used in analyzi ng the benefits of the proposed ELGs.

3.1.2 Models

Integrated Planning Model Subject to EPA direction, Abt Associates may also rely on analysis and outputs from the Integrated Planning Model (IPM) to assess the impact of regulatory requirements on electricity markets. Abt Associates and EPA used IPM in the 316(b) Phase II and Phase III regulatory analyses as well as during the proposal stage of the Revised 316(b) Existing F acilities Rule, to assess the total electricity market impact of regulatory requirements including the im pact on in-scope facilities and the extended total market effect accounting for changes in capacity ma nagement, production levels and costs across all facilities, regardless of whether the facilities are direc tly subject to regulatory requirements. IPM is also commonly used to evaluate the impacts of regulatory actions under the Clean Air Act, including the recently proposed Mercury and Air Toxics Standards (MATS) for Power Plants.
IPM was selected based on the following considerations:

 Ability to receive and account for as inputs, the cost and operating effect specifications of the steam electric ELG regulation;

 Ability to assess the impact of Steam Electric ELG regulatory requirements on capacity dispatch and utilization, capacity planning and management (i.e., capacity expansion, modifications, and retirements), and electricity production costs and prices;

 Level of documentation and acceptance of the models for use in assessing electricity market impacts of environmental regulations;

 Ability to incorporate other environmental re gulatory actions in the baseline analysis;

 Ability to incorporate EPA preferences in terms of adjustments to the baseline electricity demand; forecasts built into the model;

 Ability to meet EPA’s regulation development schedule;

 The cost of model usage.
The currently available version of IPM (version 4.10 ) reflects changes in the power plant universe and also includes updated forecasts of electricity demand over the expected timeframe of the Steam Electric ELG regulatory compliance. In addition, the current version of IPM in its baseline also accounts for, recently promulgated air regulations – Clean Air Tran sport Rule, the Mercury and Air Toxics Standards, and the Clean Air Visibility Rule, as well as implem entation of updated State Implementation Plans – whose impact will occur over the next five to ten years.

Integrated Exposure, Uptake, and Biokinetics Model for Lead in Children If outputs from the environmental assessment suggest potential changes in lead exposure, we may use data from EPA’s Integrated Exposure, Uptake, a nd Biokinetics (IEUBK) Model for Lead in Children (v1.1, 2010) in estimating the benefits of such cha nges. The model is a risk assessment tool for use in quantifying the effects of lead exposure on child ren. The IEUBK Model combines estimates of lead intake from lead in air, water, soil, dust, diet, and other ingested media, with an absorption model for the uptake of lead from the lung or gastrointestinal tract, and a biokinetic model of lead distribution, and elimination from a child's body, to predict the likely distribution of blood lead (PbB) for children of agesAbt Associates Inc., January 10, 2013 Cont ract EP-C-07-023, Assignment 5-17, QAPP 10 six months through 84 months exposed to lead in thes e environmental media. Blood lead levels can then be combined with with a dose-response relations hip between PbB and IQ decrements from published literature and the estimated number of exposed children to obtain the total change in the number of IQ points for the affected population, the number of child ren with IQs less than 70 and whose PbB is greater than 20 μ g/dL who would require compensatory education. Monetary values for avoided neurological and cognitive damages are based on the impact of an add itional IQ point on an individual’s future earnings and the cost of compensatory education for children with learning disabilities.

SPARROW If outputs from the environmental assessment suggest potential changes in nutrient loadings, we may use the USGS SPARROW model to estimate the resulting ch anges in in-stream nutrient concentrations to support analysis of the benefits of such changes. EPA used the SPARROW model as part of its analysis of the Construction and Developmen t (C&D) rule. The model uses statistical techniques to relate concentrations of total nitrogen a nd total phosphorus to major sources of nutrients and processes in stream reaches defined at the resolution of E2RF1. The US GS developed and calibrated the national TN and TP models; the two models have been described in peer reviewed papers. 3 For this analysis, we would use these published national SPARROW models to estimate changes in in-stream concentrations resulting from reductions in point source loadings of TN and TP for each of the regulatory options. This would be done by reducing the point source variable value fo r each receiving reach by the TN or TP loading reduction estimated in EPA’s engin eering analysis of each regulatory option. This approach implicitly accounts for other sources of nutrients to surface waters (e.g., agricultural sources, air deposition).
SPARROW was selected based on the following considerations:

 National scope;

 Ability to account for changes in nutrient loadings from point sources;

 Ability to account for the contribution of other nutrient sources to surface waters;

 Availability of calibrated and peer-reviewed models;

 Ability to meet EPA’s regulation development schedule;

 The cost of model usage.

Limitations include the indirect manner in which st eam electric pollutant loadings are input into the model (i.e., as offset to a generic point source vari able defined in population terms as opposed to specific loading from individual facilities) and potential changes from the b aseline period over which the model was calibrated. We deem the model appropriate to pr ovide insight into the potential changes in nutrient concentrations resulting from the proposed ELGs.

RSEI If outputs from the environmental assessment suggest potential changes in loadings of toxic pollutants (e.g., metals), we may use the water quality compone nt of the RSEI model to estimate the resulting changes in in-stream concentrations downstream fro m the reaches that receive steam electric discharges to support analysis of the benefits of such changes. EPA developed the RSEI model to estimate the effects of discharges from facilities subject to Toxics Release Inventory (TRI) reporting. 4 The RSEI model uses simple dilution equations to estimate concentrations of metals in all stream reaches downstream from

3 For more information about SPARROW, see http://water.usgs.gov/nawqa/sparrow/

4 For more information about RSEI, see http://www.epa.gov/oppt/rsei/Abt Associates Inc., January 10, 2013 Cont ract EP-C-07-023, Assignment 5-17, QAPP 11 each plant. The published national model has been descr ibed in peer reviewed papers and EPA reports. For this analysis, we would use the RSEI model to estimate changes in in-stream concentrations resulting from reductions in point source loadings of metals for each of the regulatory options. Since the RSEI database includes discharges for all facilities that report to TRI, including facilities other than steam electric plants, the analysis would account for loadings from other, non-steam electric, TRI dischargers. It would not, however, account for other sources of metals (e.g., mercury deposition, contaminated sediments, nonpoint sources).RSEI was selected based on the following considerations:

 National scope;

 Ability to account for changes in metal loadings from steam electric generating plants;

 Ability to account for the contribution of other point sources dischargers to surface waters;

 Ability to meet EPA’s regulation development schedule;

 The cost of model usage.
Limitations include the relatively simple algorithm used to model metal fate and transport (e.g., simple dilution model does not account for volatilization and pa rtitioning). The model may be most appropriate to provide screening-level insight into the poten tial downstream effects of the proposed ELGs.

3.1.3 Input costs Abt Associates anticipates that EPA will provide cost estimates for each technology that may be required by a regulatory option for each in-scope plant. These costs are being developed under a separate contract and work assignment and will be assumed to have un dergone their own set of QAQC review. For each round of analysis, Abt Associates will document the set of cost data used in estimating the impacts by noting clearly in the analytic files, the date the cost data were generate d and/or received. The analytic files will also describe each analyzed option in terms of the specific combination of control technologies assumed for FGD wastewater, ash handling wastewater, and landfill leachate.

3.1.4 Environmental effects Abt Associates anticipates that EPA will provide da ta on the environmental effects of steam electric discharges, and changes in environmental conditions expected to result from the revised ELGs. These effects are being assessed and quantified under a sep arate contract and work assignment and will be assumed to have undergone their own set of QAQC review . Effects expected to be quantified include, for example, ambient concentrations of Steam Electric pollu tants of concern in receiving waters and/or tissue.
For each round of analysis, Abt Associates will documen t the environmental data used in estimating the benefits by noting clearly in the analytic files, th e date the environmental da ta were generated and/or received.
In some instances, Abt Associates may use outputs from the Environmental As sessment being conducted separately as inputs to model environmental effects of these pollutants downstream from reaches directly receiving steam electric discharges. Section 3.1.2 describes the models that may be used for this activity.

3.2 Quality requirements of, and acceptance criteria for, secondary data All secondary data for this work will be from origin al published sources or from sources of high scientific merit, as determined by expert judgment. As discu ssed above, Abt Associates se lected the secondary data sources used for analyzing the cost and economic impact s and benefits of revisions to the Steam Electric ELGs because they are peer-reviewed, widely u sed and accepted in economic and policy analyses performed by EPA and other government and private or ganizations, and publicly available. These dataAbt Associates Inc., January 10, 2013 Cont ract EP-C-07-023, Assignment 5-17, QAPP 12 sources are subject to quality assurance measures before their publication. As a result, the quality of these data is widely acknowledged to the extent that additional quality assurance is not expected. Abt Associates evaluated these data sources relative to the appropriateness for their specific use on this project.
Abt Associates considers secondary data id entified from published sources as described in Section 3.1 , as appropriate for this effort. These data have been reviewed and approved by qualified EPA personnel and have been used to support cost and economic impact and environmental and economic benefit analyses of several regulatory actions to date. In the case of mode led data, Abt Associates will consider the extent to which each model has been peer reviewed, calibrated, and validated, before using the model to conduct analyses of rulemaking options. Abt Associates will review model outputs to ensure that they are reasonable given the range of observed data.
Going forward, as the need for additional data from se condary sources arises, the managers for this work assignment, Ms. Morin, Ms. Melnikova, and Dr. B esedin, will evaluate candidate sources of this information for scientific strength and merit, and will en sure that selected data sources meet the standards set forth in this QAPP. Selection of the data will be discussed with Mr. Fisher, project quality advisor for this effort. Abt Associates will discuss using an y additional secondary da ta with EPA before incorporating them into cost and economic impact analyses and environmental and economic benefit analyses for this project.

3.3 Data reduction, validation, and verification procedures and documentation

3.3.1 Data reduction procedures and documentation Abt Associates will use data extraction and reduction pr ocedures similar to those used in developing the analytical framework and datasets used in previous rulemaking efforts. We will extract data from the original source, and compile, query, and categorize th ese data in subset databases by characteristics of interest (e.g., by state and North American Electri c Reliability Corporation region, by primary energy input for electric power generation, or by type and regional location of waterbody to which the electric generating facilities discharges its effluent). Each da ta set will be appropriately described. Thus, Abt Associates staff will include full bibliographic inform ation with all collected publications and databases, including the source/link and date accessed for info rmation collected from the Internet, and will save appropriate Web pages as PDF files. In cases where the data are obtained via email, a copy of the email communication describing the data will be saved with the data set. Abt Associates staff will also save any email correspondence containing EPA’s guidance pe rtinent to cost and economic impact and environmental and economic benefits analyses as PD F files. Abt Associates staff will document and appropriately flag in the project files and docket materi als, any modifications to the data to differentiate between original values unchanged from the orig inal sources and values estimated or modified specifically for use in the economic analyses of the St eam Electric ELG rule and provide a date of the most recent modification/review.
Abt Associates will make any data modifications only when: (1) data for a given facility are not provided in the detailed survey questionnaire or relevant EIA or other dataset, and therefore need to be estimated to provide a comprehensive analysis baseline; (2) data ar e proven to be in error and error reports have been submitted to the data system of origin; or (3) adjust ments are necessary to ensure consistency within the analytical framework.
We will document and appropriately fl ag in the project files and docket materials, any modifications to the data to differentiate between original values unchanged from the original sources and values estimated or modified specifically for use in the economic an alyses of revisions to the Steam Electric ELGs.Abt Associates Inc., January 10, 2013 Cont ract EP-C-07-023, Assignment 5-17, QAPP 13 3.3.2 Data validation and verificat ion procedures and documentation
The Abt Associates WAM and the Abt Associates PQA will perform data validation and quality assurance to ensure that all information submitted will meet EPA’s technical standards. Quality assurance measures include verification that:

 Data and other information have been appropr iately and correctly transcribed from sources;

 Data used are complete, comparable, relevant, representative, and reasonable given the specific analysis or methodology;

 Information has been evaluated for scientific strength and merit;

 Information has been appropriately and corr ectly processed/analyzed and interpreted;

 Methodologies and assumptions are appr opriate and supported by the data;

 Calculations are implemented correctly in spreadsheets or model algorithms;

 Conclusions are specific, accurate, clear, and appropriate;

 Conclusions are clearly supported by the analysis presented;

 Limitations of the data source and analyses are enumerated;

 The objective or purpose of each document is defined;

 All topics of concern specified by EPA have been addressed;

 Appropriate references have been provided for data sources; and

 Documentation of the above is properly referenced in produced materials
Abt Associates will verify that the data are internally consistent by verifying that expected relationships are met. This will involve comparing summary data across different levels of aggregation (e.g., aggregations of data across different geographies (state vs. national), di fferent categories of facilities (e.g., electric generating facility types) and between framework elements (e.g., facility level vs. firm level) to ensure consistency. For example, we will verify that counts of records or facilities are consistent with expected values. Where one may expect the individua l categories to sum to the national total, we will verify that this is in fact the case and that no da ta are erroneously excluded. In cases where logic would suggest a direction to differences (e.g., values for Opti on A should be larger than those for Option B), we will verify that the expected relationship is met or th at exceptions have been investigated and explained. We will investigate observed data irregularities and either resolve or justify them in the written documentation provided to EPA.
Abt Associates will also verify that methodologies and calculations are correctly implemented in spreadsheets or model algorithms and that data are properly referenced and pr ocessed. This will involve reviewing equations and/or conductin g independent calculations to verify results. The Abt Associates WAM will designate a staff member, other than the in dividual who created a given analytical file or conducted the analysis, to review each analytic file . The types of checks to be conducted will be discussed with the reviewer.
To ensure transparency of calculations/analysis and efficiency of the internal review process, each analytic file will have a “file informatio n” section with the following information:

 Date a given file was created

 Date of most recent modification/reviewAbt Associates Inc., January 10, 2013 Cont ract EP-C-07-023, Assignment 5-17, QAPP 14  General purpose of information/an alysis contained in a given f ile and a brief description of assumptions used, including data years and sources

 When appropriate, a brief description of macros , user-defined functions, and external links

 When appropriate, a brief description of info rmation/analysis contained in each worksheet, including data years and sources

 Names of files/databases with data used in a file being reviewed
Each analytic Excel file will also contain a lis t of variable names used in a given file.
Further, to record the internal review process, each analytic file will have a Record of Internal Review/QA Process form to be filled out by a designated review staff member ( Table 3 , at the end of this section). This form will be modified, as appropriate, based on the software used and the contents/purpose of a given analytic file. Finally, when appropriate, d esignated review staff will reproduce analysis results using an alternative methodology and/ or software to ensure accuracy of analysis results. Such reviews may focus on a sample of data records for which an alysis results will be replicated and verified. Abt Associates will investigate observed data irregularities and either resolve or justify them in the written documentation provided to EPA. All analytic files will be saved in project folders on the Abt Associates network system using a project folder and file mana gement structure specified by the relevant content area manager (Ms. Morin, Ms. Melnikova, or Dr. Besedin), as described at Section 1.4: Role and responsibilities of project personnel.
Model outputs will be reviewed to en sure that they are reasonable and within the range of observed data.
All written deliverables describing da ta, methodology, and analysis findi ngs will also be reviewed by a staff member designated by the relevant manager before being sent to EPA. Review of written work product will include ensuring that the most recent and correct analysis results are presented and checking for correct interpretation of results, clarity of discussi on, proper citations and re ferences, and spelling and grammar. Examples of QA procedures for written work are provided below:

 Comparing results presented in the report or memoranda with the most recent output files;

 Comparing results presented in tables and/or e xhibits with the results presented in text;

 Conducting selected manual checks of analytic resu lts presented in the report (e.g., making sure that individual values add up to totals);

 Assessing whether results and their interpretati on are consistent with the theory, existing literature and prior expectation;

 Ensuring that a comprehensive list of assumptions is provided;

 Confirming that limitations and uncertainty inhere nt in the analysis are clearly presented; and

 Checking references included in the report chapters against the reference list.
The reviewer may not be a single individual as diffe rent review tasks may be performed by different individuals (one checking references and tables while another evaluating the clarity of the methodology description). The work assignment manager is responsib le for ensuring that the appropriate reviews have been conducted.
When sending cost and economic impact and environm ental and economic benefits analysis results to EPA, Abt Associates will include in each summary file a brief description of any changes to methodology, data, and/or assumptions that might ha ve taken place since the previous deliverable. A name of each deliverable file will include a date and a deliverable version in accordance with theAbt Associates Inc., January 10, 2013 Cont ract EP-C-07-023, Assignment 5-17, QAPP 15 Standard Naming Convention and Version Control specifications documented under Task 2 of this work assignment.
Until the deliverables have gone through the internal review process discussed in this section and have been approved by the Abt Associates overall work ass ignment manager and by the EPA work assignment manager, they will contain “ Internal Draft – Deliberative, Predecisional – Do Not Quote, City, or Distribute ”. Only when all quality assurance reviews ha ve been completed and approved by both Abt Associates and EPA will the documents be characterized as final.

3.3.3 Special provisions for quick turnaround deliverables The work assignment includes the requirement to provide analyses on a quick turnaround basis. While Abt Associates still conducts a quality review of any de liverable, we anticipate that it may not always be possible to complete all review components prior to sending an interim deliverable to the EPA WAM. In the event that an interim deliverable needs to be provided to EPA without having been subject to the full review, the Abt Associates WAM, Ms. Morin, will discuss the extent and type of review to be completed (or not) with the EPA WAM in advance of submitti ng the deliverable. Additionally, the submitted file will include notes on the extent of the review that was conducted, focusing on the aspects of the deliverable that are most consequential to the d ecision making process. For example, the review may focus primarily on ensuring that assumptions and cal culations are correct rather than focusing on the description of the methodology or findings. Review of these descriptions may follow in a later deliverable, as directed by the EPA WAM.

3.3.4 Data storage As data are collected according to the foregoing discussion, Abt Associates will compile the data as obtained from the original sources in protected el ectronic folders on the Abt Associates network electronic storage system and/or as the original ‘hard copies’ of data reports, for data not received electronically. We will archive the original data to preserve the data in the form in which they were originally received. We will store data compiled el ectronically in project folders with a structure designated by the Abt Associates managers for th e respective work assignment project areas:

 Cost and economic impact analysis – Ms. Tatiana Melnikova  Benefits analysis – Dr. Elena Besedin Abt Associates electronic records are only available to authorized users with access security enforced by general login procedures. Abt Asso ciates has dedicated information t echnology (IT) staff responsible for the installation and maintenance of all hardware a nd software infrastructure. This includes automated daily backup of all data stored on networked resources. Key personne l assigned to this work assignment will work with the IT staff to ensure that data st orage procedures are supported by the IT infrastructure. At the completion of the project, all data obtained or developed will be archived so as to preserve them without allowing for modifications.
Abt Associates applies special data management a nd storage procedures for data that are declared Confidential Business Information (CBI). These pro cedures prevent access to CBI by individuals who have not been approved for receipt and processing and/or use of CBI in accordance with the CBI management plan developed for the overall EPA Contract No. EP-C-07-023, and as specifically implemented for this work assignment. For exampl e, specific folders containing project sensitive information (e.g., CBI data) are subject to additional rest rictions for authorized project staff, with control administered by the project manager, Ms. Isabelle Morin.Abt Associates Inc., January 10, 2013 Cont ract EP-C-07-023, Assignment 5-17, QAPP 16 Table 3: Record of Internal Review/Quality Assurance Process

File Name

Date Reviewed

Reviewer

File General Formulas/calculations correctly reflect general methodology and assumptions
Summary values are consistent across analytical frameworks
Results have been replicated/ reproduced by external calculation
Results follow exp ected direction and approximate magnitude of change across analyzed cases (e.g., regulatory options)
References are appropriately cited
If analysis results are re-generated, provide information on software and methodology used. Worksheet Name_1 Data are read in correctly/data sources are verified
Formulas/calculations correctly reflect general methodology and assumptions
Formulas are correctly written
Formulas refer to the appropriate cells
Summary values are consistent across analytical frameworks Worksheet Name_2 Data are read in correctly/data sources are verified
Formulas/calculations correctly reflect general methodology and assumptions
Formulas are correctly written
Formulas refer to the appropriate cells
Summary values are consistent across analytical frameworksAbt Associates Inc., January 10, 2013 Cont ract EP-C-07-023, Assignment 5-17, QAPP 17 

### 4 Expected Work Products Abt Associates anticipates developing various produc ts derived from this work, including: memoranda on topics specified in written technical direction from th e EPA WAM; summaries of analysis and findings of cost and economic impact, environmental assessment, and benefits for altern ative regulatory options under consideration; draft chapters of the Economic, Environmental Assessment, and Benefits Analysis report to support proposal of revisions to the Steam Electric ELGs; and sections of the preamble for the proposed rule. Abt Associates will describe the analys es in detail in the reports prepared to support rulemaking (e.g., Regulatory Impact Analysis (RIA) and Benefit and Cost Analysis (BCA) reports), including data sources, methodology, interim and fi nal results, and limitations. Where appropriate, Abt Associates will include documentation of QAPP activ ities as an addendum to significant draft and final deliverables presenting data or analyses results.
The final step in the quality assu rance process is editorial review of final deliverables. After Abt Associates’ internal technical reviews have been completed (and EPA WAM reviews as well, as appropriate), all comments and revisi ons will be addressed by the relevant project management staff – usually the individual content area managers – and reviewed for final acceptance by the overall project manager and PQA, Mr. Fisher, or his designee. At th is point, a skilled copy editor will conduct a final editorial review. The editor’s role will be to verify correct grammar, spelling, and text organization/flow, as well as to ensure that the style and flow of th e document are appropriate for the intended audience. Upon direction by the EPA WAM, Abt Associates will facilitate peer review of the methodologies and finished products.
If any quality assurance concerns arise from the review that cannot be resolved within the project team, Mr. Fisher will refer these concerns to the Quality Assurance Manager for the EP-C-07-023 contract, Ms. Susan Day, who is responsible for r esolving any quality assurance concerns.
The Abt Associates assignment manager will allocate appropr iate time for review into the project or task schedule, and will dedicate adequate resources from the work assignment budget for technical review and quality assurance oversight. We w ill report on quality assurance activities in our monthly progress reports. All project deliverables will meet EPA’s sta ndards of transparency, reproducibility, objectivity, integrity, and utility as specified in EPA’s Guidelines for Insuring and Maximizing the Quality, Objectivity, Utility, and Integrity of Information Di sseminated by the Environmental Protection Agency (EPA/260R-02-008, October 2002), referred to as “EPA’s Information Quality Guidelines”.



### 5 Acceptance by the EPA WAM We will deliver all data used in the preparation of project deliverables to the EPA WAM for review and approval. Upon acceptance by the EPA WAM, Abt Associ ates will finalize the deliverables discussed in Section 4 above.Abt Associates Inc., January 10, 2013 Contract EP-C-07-023, Assignment 5-17, QAPP APPENDIX A
Abt Associates Memorandum – Detailed Description of Economic/Financial Analyses Conducted in Support of Revisions to the Steam Electric Effluent Limitations GuidelinesAbt Associates Inc., October 29, 2009 Economic/Financial Analyses for Revisions to the Steam Electric ELGs 1 

# memorandum

Environment and Resources 55 Wheeler Street, Cambridge, MA  Tel: 617 492-7100  www.abtassociates.com

Date October 29, 2009

To James Covington, U.S. EPA/OW/EAD

From Tatiana Melnikova, Isabelle Morin, and Michael Fisher

Subject Description of Economic/Financial Analyses E xpected to be Conducted in Support of Revisions to the Steam Electric Effluent Limitations Guidelines (WA 2-17, Task 7)

The 1972 Clean Water Act (CWA) directs EPA to de velop national technology- based regulations for categories of industries that discharge pollutants dire ctly to surface waters (effluent guidelines) or that discharge pollutants indirectly through sewage treatmen t plants (pretreatment standards). EPA is currently revising effluent limitation guidelines (ELGs) and st andards at 40 CFR 423 that apply to the Steam Electric Power Generating (“Steam Electric”) industry. These ELGs and standards apply to a subset of the electric power industry, namely those plants “prima rily engaged in the generation of electricity for distribution and sale which results primarily from a process utilizing fossil-type fuel (coal, oil, or gas) or nuclear fuel in conjunction with a thermal cycle em ploying the steam water system as the thermodynamic medium.”
Promulgation of effluent limits according to these CWA authorities requires an assessment of the economic achievability of the treatment technology(ie s) underlying the guidelines and standards. In addition, under Executive Order 12866, EPA will likely be required to estimate the potential benefits and costs to society of revisions to the Steam Electric ELGs.
The purpose of this memorandum is to outline the cost and economic impact analyses that EPA may need to conduct in support of revisions to the Steam El ectric ELGs and indicate which legal requirements the Agency would have to consider with respect to th ese analyses. The memorandum also identifies key data, analytic steps, and assumptions. Based on past e xperience with conducting cost and economic impact analyses in support of the Clean Water Act 316(b) Rul es, which are also concerned with Steam Electric facilities, EPA would likely have to conduct th e following cost and economic impact analyses:

3⁄4 Cost Impact Analysis

 Cost-to-Revenue Analysis: Facility-Level Screening Analysis

 Cost-to-Revenue Screening Analysis: Parent Entity-Level Analysis

 Multi-discriminant analysis (“Altman-z”) of th e potential for bankruptcy or other adverse effects on the financial health of firms

 Impact of Compliance Costs on Electricity Prices to all Consuming Sectors

 Impact of Compliance Costs on Household Electricity Costs

 Assessment of Potential Impact of Regulatory Options in the Context of National Electricity Markets

3⁄4 Assessment of short-term reduction in capac ity availability due to potential downtime of generating units for compliance technology installationAbt Associates Inc., October 29, 2009 Economic/Financial Analyses for Revisions to the Steam Electric ELGs 2 3⁄4 Assessment of Potential Impact of Regulatory Options on Small Entities – Regulatory Flexibility Act (RFA) Analysis

3⁄4 Unfunded Mandates Reform Act (UMRA) Analysis

3⁄4 Other Administrative Requirements

 Executive Order 12866: Regulatory Planning and Review

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

 Executive Order 13045: Protection of Children fro m Environmental Health Risks and Safety Risks

 Executive Order 13132: Federalism

 Executive Order 13158: Marine Protected Areas

 Executive Order 13175: Consultation and Coordination With Indian Tribal Governments

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

 Paperwork Reduction Act of 1995

 National Technology Transf er and Advancement Act

3⁄4 Assessment of Total Social Costs

3⁄4 Social Costs and Benefits
Note that methodologies described in this memorandum are based in part on Abt Associates’ past experience with conducting regulatory analyses of Steam Electric facilities in support of the Clean Water Act 316(b) Rules. EPA may ultimately use different methodologies to perform these analyses in support of revisions to the Steam Electric ELGs. Additionall y, this memorandum focuses primarily on economic impact analyses. While a cursory overview of the eval uation of benefits is in cluded in the context of certain Executive Orders or for the analysis compari ng social costs and benefits, a detailed exposition of methodologies that would be used in conducting the Environmental Assessment of the regulation is outside the scope of this memorandum.


### 1 Cost Impact Analyses
The purpose of economic impact analyses is to assess the magnitude and economic impact of regulatory options. Based on EPA’s past economic impact analyses of Steam Electric facilities, we expects that the assessment will be conducted using tw o general analysis frameworks:

1. A cost and economic impact assessment reflecti ng baseline operating characteristics of in-scope facilities and with assignment of estimated complia nce costs to those fac ilities. This analysis assumes no changes in those baseline operating characteristics – e.g., level of electricity generation and revenue – as a result of the require ments of the proposed regulatory options. This assessment, described in this section, includes four specific analyses:

 A cost-to-revenue screening analysis to assess th e impact of compliance outlays on individual in-scope facilities ( Section 1.1 );Abt Associates Inc., October 29, 2009 Economic/Financial Analyses for Revisions to the Steam Electric ELGs 3  A cost-to-revenue screening analysis to assess th e impact of compliance outlays on domestic parent-entities owning in-scope facilities ( Section 1.2 ); 1

 A multidiscriminant analysis (“Altman-z”) of the potential for bankruptcy or other adverse effects on the financial health of firms owning in-scope facilities ( Section 1.3 );

 An assessment of the potential electricity rate impact of compliance costs to the residential sector ( Section 1.3 ); and

 An assessment of the potential electricity rate impact of compliance costs, across sectors ( Section 1.5 ).

2. A broader electricity market-level analysis (“Ma rket Model Analysis”) based on the Integrated Planning Model (IPM) ( Section 1.6 ). Unlike the preceding analyses, the Market Model Analysis accounts for expected changes in the operati ng characteristics of facilities from both:

 Estimated changes in electricity markets and operating characteristics of facilities independent of the considered regulatory options ; and

 Estimated changes in markets and operating characteristics of facilities as a result of the considered regulatory options

. 

### 1.1 Cost-to-Revenue Analysis: Facility-Level Screening Analysis The cost-to-revenue measure compares the cost of reducing adverse environmental impact of facility effluents (e.g., wastewater treatment system technol ogy costs) with its operating revenue, and provides a screening-level assessment of the impact of regulator y options considered by EPA. The cost-to-revenue impact analysis concept is outlined in EPA’s Guidelines for Preparing Economic Analyses

. 2

1.1.1 Analysis Approach and Data Inputs For the facility-level cost-to-revenue analysis, we will compare annualized after-tax compliance costs, 3 calculated on a present value basis as of an estimated compliance year, with estimated facility revenue. 4
The information on facility-level revenue is expected to be obtained through the Steam Electric survey currently being developed. In the event that th is information cannot be obtained through the Steam Electric survey, facility-level revenue can be estimated as follows:

3⁄4 For all facilities modeled in the Integrat ed Planning Model (IPM) (discussed in Section 1.6 of this memorandum), 5 we can use the average of facility-specific baseline (i.e. pre-regulation) revenue projected by IPM for a given set of run years. 6 7 This revenue estimate captures expected changes

1 The purpose of the cost-to-revenue assessment is to indicate the relative magnitude of the compliance costs, controlling for the size or market share of the firm. The assessment does not predict closur es and/or other types of economic impact on facilities expected to be subject to the regulatory options.

2 Guidelines for Preparing Economic Analyses. Report EP A 240-R-00-003, September 2000. An updated version of the guidelines (Guidelines for Preparing Economic Analyses (2008)) is currently under review by the Science Advisory Board.

3 For private, tax-paying entities, after-tax costs are a more relevant measure of potential cost burden than pre-tax costs . For non tax-paying entities (e.g., State government and municipality ow ners of in-scope facilities), the estimated costs used in this calculation include no adjustment for taxes.

4 Compliance year may vary depending on a given technology and therefore may be different depending on an analyzed regulatory option.

5 The Integrated Planning Model (IPM) is a comprehensive model of the electric power sector. EPA used IPM to assess the market-level impact of the regulatory options under the CWA 316(b) Ph ase II Proposed Rule. The model would be appropriate for the purpose of the electric market analys is in support of revisions to the Steam Electric ELGs.

6 Run years are specified in the m odel based on a compliance schedule.Abt Associates Inc., October 29, 2009 Economic/Financial Analyses for Revisions to the Steam Electric ELGs 4 in electricity markets and in the utilization of facilities subject to the regulatory options in the period following rule promulgation.

3⁄4 For facilities not modeled in IPM or for whic h IPM reported no revenue, we can develop estimates of facility-level revenue using EIA data on electricity generation by prime mover and utility-level electricity prices.

3⁄4 To provide cost and revenue comparisons on a cons istent analysis-year and dollar-year basis, all cost and revenue values will be brought to a give n compliance year and expressed in dollars of a given analysis year.
Following EPA guidelines, cost-to-revenue thresholds of one and three percent will be used as markers of potentially significant impact. We will compare facilit y-level costs and revenue and determine the number of instances in which facilities incurred costs in rang es of “less than one percent of revenue,” “between one and three percent of reve nue,” and “greater than three percent of revenue.”

1.1.2 Expected Findings Analysis results will be assessed at the level of the North American Electric Reliability Corporation (NERC) regions. 8 We expect the analysis results to vary by NERC region and regulatory option. There is no specific threshold for determining the “severity” of regulatory impact on in-scope facilities in terms of a number of facilities with costs exceeding one and th ree percent thresholds. Consequently, to determine whether revisions to the Steam Electric ELGs will ha ve a “severe” impact on in-scope facilities, guidance from EPA will be required. In addition, the findings from the market-level analysis (discussed at Section 1.6 , below) would be more specifically indicative of po tential industry impacts in terms of generating unit closures, changes in total industry electricity production costs, etc. 

### 1.2 Cost-to-Revenue Screening Analysis: Parent Entity-Level Analysis In addition to facility-level impact s described above, we also anticipate assessing the economic impact of the regulatory options at the parent entity (firm) level. 9 The cost-to-revenue screening analysis at the parent entity level provides insight on the impact of compliance requirements on those firms that own multiple facilities. In conducting this analysis, we w ill rely on the cost-to-revenue impact analysis concept as outlined in Guidelines for Preparing Economic Analyses , but apply this analysis at the level of the parent entity. As a complement to this analysis, we will look at the Altman-z score of parent firms to assess financial distress that may result from revisions to the Steam Electric ELGs (see Section 1.3 ).

1.2.1 Cost-to-Revenue Analysis Approach and Data Inputs To assess the entity-level economic impact of complia nce requirements, we will aggregate facility-level compliance costs to the level of the parent entity identified as the ultimate domestic owner of the explicitly analyzed in-scope facilities and compare th ese costs to parent entity revenue. This information is expected to be obtained through the Steam Electric survey currently being de veloped. Compliance costs are obtained by summing across all facilities owned by the same parent entity. As above, we will use cost-

7 In analyses of the CWA 316(b) regulati ons, average values for each statistic – i.e. , energy revenue and capacity revenue – over the data years, were calculated by setting aside values fo r years that are anomalously low, i.e., more than 30 percent below the 4-year average values.

8 NERC is responsible for the overall reliab ility, planning, and coordination of the po wer grids; it is organized into regional reliability management organizati ons that are responsible for th e overall coordination of bulk pow er policies that affect their regions’ reliability and quality of service.

9 For the purpose of this analysis, a parent entity is the ulti mate parent firm is the highest level domestic business entity i n the facility’s ownership structure. A firm that is owned by anothe r U.S. firm is not an ultimate domestic parent firm. On the other hand, a U.S. firm that is owned by a fore ign firm is an ultimate domestic parent firm.Abt Associates Inc., October 29, 2009 Economic/Financial Analyses for Revisions to the Steam Electric ELGs 5 to-revenue thresholds of one and three percent as ma rkers of potentially significant impact for this analysis.
In the event that information on parent entity re venue cannot be obtained through the Steam Electric survey but must instead be obtained from public sources, the same steps as used in the 316(b) analysis can be used:

3⁄4 Determining the Parent Entity : The highest level domestic pare nt entity for each in-scope facility can be determined using public data sources such as EIA-861 database; EIA-860 database; financial information websites; corporate websites; and news articles.

3⁄4 Estimating Parent Entity Revenue: Parent entity-level revenue can be estimated using the following sources:

 For publicly owned utilities, for which revenue from corporate websites is not available, we can use a 5-year average revenue (retail plus wholesale) from EIA-861 database

 For revenue of privately owned entities, we can use corporate websites, Google Finance, Yahoo Finance, Hoovers, and Selectory.com (in order of preference)

All revenue values will be stated in dollars of a given analysis year using the Electric PPI.

3⁄4 Estimating Compliance Costs at the Level of the Parent Entity: Facility-level compliance costs are brought to a given compliance year, restat ed, as necessary, in dollars of a given analysis year, and aggregated to the level of a parent entity.

1.2.2 Expected Findings We expect the analysis results to vary by ownership type and regulatory option. As is the case with the facility-level cost-to-revenue analysis, there is no specific threshold for determination of “severity” of regulatory impact on parent entities owning in-scope f acilities in terms of a number of parent-entities with costs exceeding one and three percent thresholds.
In conducting a parent entity-level analysis for th e 316(b) Phase II Proposed Rule, which applies to a similar set of Steam Electric facilities, EPA found th at on average the entity-level compliance costs are low in comparison to the entity-level revenues, i.e., th e majority of parent entities are expected to incur costs of less than one percent of revenues. Conseque ntly, it was determined that parent entities that own more than one in-scope facility we re not going to be disproportionately “penalized” as the result of the Rule. Given the fact that revisions to the Steam Elec tric ELGs will concern a similar set of facilities, it is likely that the same findings will apply, unless ELG co mpliance costs are much greater than those of the CWA 316(b) regulations.


### 1.3 Altman-z Analysis of Financial Viability As a complementary analysis of the firm-level impact s of the rule, we will evaluate the “Altman-z” score of parent firms. Altman-Z is a commonly cited predicto r of bankruptcy and has b een used in several prior EPA effluent guidelines economic impact analyses (e.g ., pulp and paper, pharmaceuticals, transportation equipment cleaning).
The analysis involves calculating an overall firm-level score employing various indicators of financial viability (i.e., common business ratio s calculated from standard corporate financial statements) 10 under both baseline and post-compliance conditions. The purpose of the analysis is to evaluate the degree to

10 For firms in non-manufacturing industries, business ratios include: 1) working capital to total assets; 2) retained earnings to total assets; 3) earnings befo re interest and taxes (EBIT) to total assets; 4) book value of equity/book value of total liabilities.Abt Associates Inc., October 29, 2009 Economic/Financial Analyses for Revisions to the Steam Electric ELGs 6 which increased compliance costs as sociated with this EPA action will increase the rate of bankruptcies and/or affect the financial health of firms that ow n regulated facilities. Altman-z functions have been developed for different types of firms (privately-hel d or publicly-traded) and industries (manufacturing or non-manufacturing). The non-manufacturing function (Z ′′ ) would likely be the most appropriate for the Steam Electric industry analysis.
We would conduct this analysis at the level of the immediate parent firm to isolate the direct effects of increased compliance cost on firms’ financial health.
Note that in past analyses using the Altman z-sco re, EPA has typically assumed that no cost is passed through to customers and therefore has used the analysis as an upper bound of potential impacts on industry. In the case of the Steam Electric industry, however, firms may have a greater ability to pass on their costs to ratepayers, particularly in the case of regulated utilities. The draft detailed questionnaire requests specific information on the share of electric ity sales subject to different regulatory and pricing conditions to assess the firm’s ability to pass through increased compliance costs. The Altman-z analysis could therefore be performed first using a default assumption of zero cost pass-through and, depending on the outcome of this “worst-case” scenario – i.e., if this simple analysis suggests the potential for significant impacts – the analysis could be further re fined to account for the share of the costs that are expected to be passed on to ratepayers by di fferent firms depending on regulatory status.
Inputs for this analysis will primarily come from the detailed survey questionnaire.


### 1.4 Impact of Compliance Costs on Household Electricity Costs Given the relative “necessity” characteristic of elect ricity as a household-consumed commodity, EPA will likely need to assess the burden of compliance cost from potential increases in the cost of electricity to residential consumers. While the facility-level and parent entity-level cost-to-revenue screening analyses described in Sections 1.1 and 1.2 essentially reflect an assumption that in-scope facilities and their parent entities will absorb 100 percent of the compliance burden (zero cost pass-through), the household electricity cost analysis described in this section a nd the electricity price impact analysis described in Section 1.5, assume the other extreme, i.e., a simple 100 percent pass-through of compliance costs in electricity prices.
The methodology for assessing the regulatory impact on household electricity costs described in this section is the methodology used for this assessment under Clean Water Act 316(b) regulations, which are also concerned with Steam Electric facilities. Recently , this analysis has received close attention because of the relatively high estimated cost burden in so me NERC regions for some of the 316(b) regulatory options. This analysis very likely overstates the r esidential price impact because it does not account for adjustments to the dispatch of electric generating un its given expected changes in electricity production costs due to the regulation. We are currently investig ating an approach to adju st the estimated household sector impact to reflect expected market respon se in the production profile, and to reflect whether electricity generation prices, at the state level, con tinue to be set under a traditional cost-of-service rate regulation framework or are determined in deregulated wholesale markets. 11 We would expect to use this modified methodology for the household impact analysis of revised Steam Electric ELGs. The data that would support a more detailed analysis of the impa cts on household electricity costs would come from the Steam Electric survey currently being developed. In particular, the survey requests information on the fraction of electricity production and sales, by plant, that is sold under various pricing frameworks.

11 The IPM-based analysis estimates production cost and price e ffects accounting for changes in unit dispatch and provides an alternative estimate of potential cost to residential consumers. However, the IP M price impact analysis is based on an assumption of deregulated wholesale electricity markets, which is not applicable to all states. In states with cost-of-service pricing for electricity generation, the IPM analysis results may diverge considerably from (and understate) the expected consumer price impact.Abt Associates Inc., October 29, 2009 Economic/Financial Analyses for Revisions to the Steam Electric ELGs 7 1.4.1 Analysis Approach and Data Inputs The analysis assumes that compliance costs would be 100 percent passed through as increased electricity prices and allocated among customer classes in proportion to the baseline quantity of electricity consumption by customer class. The analysis is con cerned with estimating the potential impact on annual electricity costs by household. We expect that th e analysis will be performed at the level of a NERC region, which is appropriate given the structure a nd functioning of sub-national electricity markets, around which NERC regions are defined. The steps in this calculation are as follows:

3⁄4 To calculate an approximate total estimated annual cost in each NERC region, pre-tax facilitylevel annualized compliance costs, discounted to a given compliance year and expressed in dollars of a given analysis year, are aggregated across NERC regions.

3⁄4 To calculate an approximate average price impact per unit of electricity sales, total compliance costs are divided by the total EIA-based MWh of sales reported for each NERC region for the latest year for which EIA sales data are available. For this analysis, we will assume that total average electricity sales would remain the same in a given compliance year.

3⁄4 To calculate average annual electricity sales per hou sehold, the total quantity of residential sales in each NERC region is divided by the number of hou seholds in that region. For this analysis, we will assume that average electricity sales pe r household would remain the same a given compliance year.

3⁄4 To assess the potential annual cost impact per hou sehold, the estimated average price impact will be multiplied by the average quantity of electricity sales per household by NERC region.
The following information from the Steam Electric su rvey and from the EIA-861 database will be used in these calculations:

3⁄4 Total electricity sales quantity (in MWh) as reporte d in the Steam Electric survey or in EIA-861 database 3⁄4 Electricity sales quantity (in MWh) by customer class (in EIA-861 database) 3⁄4 Number of households (in EIA-861 database)

1.4.2 Expected Findings Average annual cost per residential household is expected to differ across NERC regions and by regulatory option. As is the case with the facility- an d firm-level cost-to-revenue analyses, there is no specific threshold for determination of “severity” of regulatory impact on households in terms of increase of annual electricity costs per household.


### 1.5 Impact of Compliance Costs on Electricity Prices As an additional measure of the potential cost and ec onomic impact of the revisions to the Steam Electric ELGs beyond the level of the complying entity, we also expect to assess the potential increase in electricity prices to all consumer groups (residen tial, commercial, industrial, and transportation), 12 again assuming a simple 100 percent pass-through of compliance costs in electricity prices.

As is the case with the househol d impact analysis described in Section 1.3 , the methodology for assessing regulatory impact on electricity costs described in th is section is the methodology used for this assessment under Clean Water Act 316(b) regulations, which are also concerned with Steam Electric facilities. However, it is possible that the methodology will need to be adjusted to support revisions to the Steam Electric ELGs. Data for a more detailed analysis of impacts on electricity costs would be obtained through the Steam Electric surv ey currently being developed.

12 These consumer groups are defined in the Energy Information Administration’s Annual Energy Outlook (

AEO) report.Abt Associates Inc., October 29, 2009 Economic/Financial Analyses for Revisions to the Steam Electric ELGs 8 1.5.1 Analysis Approach and Data Inputs This analysis also assumes that co mpliance costs would be fully passed through as increased electricity prices and allocated among customer classes in proportion to the baseline quantity of electricity consumption by customer class. The analysis would be performed at the level of the NERC region, as follows:

3⁄4 Sum pre-tax facility-level annualized compliance costs, discounted to a given compliance year and expressed in dollars of a give n analysis year, by NERC region;

3⁄4 Estimate the approximate average price impact pe r unit of electricity consumption by dividing total compliance costs by the projected total MW h of sales in a given analysis year by NERC region, from the Energy Information Admini stration’s Annual Energy Outlook (AEO); and

3⁄4 Compare the estimated average price effect (in do llars per MWh sales) to the projected electricity price by customer class and NERC region for a given year.

1.5.2 Expected Findings Annualized compliance costs (in dollars per MWh sales) are expected to differ across NERC regions and by regulatory option. As is the case with the facility- and firm-level cost-to-revenue and household impact analyses, there is no specific threshold for determinat ion of “severity” of regulatory impact on electricity consumers in terms of electricity price increase.


### 1.6 Assessing the Impact of the Regulatory Options in the Context of National Electricity Markets In the analyses for the 316(b) Phase II regulations, EP A used ICF International’s Integrated Planning Model (IPM ® ), a comprehensive electricity market optimi zation model, to assess the economic impact of regulatory options within the context of regional and national electricity markets. Depending on the expected level of compliance costs for revised Stea m Electric ELGs, EPA may also want to use IPM to assess cost and economic impacts based on an integrat ed market-response analysis, which IPM provides. If EPA judges this analysis as necessary for the Stea m Electric ELGs, we would use the IPM analytic system to assess facility and market-level effects, but with additional input from data collected through the Steam Electric survey currently being developed. 13
Again, depending on the expected cost of the regulation , use of an integrated market response analysis may be important for assessing the potential impact of revised Steam Electric ELGs, because of the interdependence of electricity generating units in supplying power to the electric transmission grid. Increases in electricity production costs and potential re ductions in electricity output at directly affected facilities – whether due to the temporary shutdow n of electric generating units during technology installation and/or the energy production penalties resulting from compliance system operation, which may of may not occur depending on the requirements under the Steam Electric ELGs – can have a range of broader market impacts that extend beyond the effect on complying facilities. In addition, the impact of

13 EPA reviewed a number of electricity market models for potential use in asse ssing the impact of the 316(b) Phase II regulation in its analyses for the suspended 2004 Phase II Rule. At that time, EPA concluded th at IPM represented the best choice for 316(b) rule analyses considering a number of factors: ability to r eceive and account for as inputs, the cost and operating effect specifications of the 316( b) regulation; ability to assess the im pact of 316(b) regulatory requirements on capacity dispatch and utilization, cap acity planning and manageme nt (i.e., capacity expans ion, modifications, and retirements), and electricity production costs and prices; level of documentation and acceptance of the models for use in assessing electricity market impacts of environmental regulations; ab ility to incorporate other environmental regulatory actions in the baseline analysis; ability to incorporate EPA preferences in terms of adjustments to the baseline electricity demand forecasts built into the model; and cost of model usage. Abt Associates expects that for the same reasons IPM would also be a good choice for analyzing the impacts of revisions to the Steam El ectric ELGs, particularly if the model outputs can be augmented by facility-specific data collected through the Steam Electric survey.Abt Associates Inc., October 29, 2009 Economic/Financial Analyses for Revisions to the Steam Electric ELGs 9 compliance requirements on directly affected fac ilities may be seen differently when the analysis considers the impact on those facilities in the context of the broader electricity market instead of looking at the impact on a standalone, single-facility basis. The IPM framework, which accounts for these considerations, is the longstanding “system of c hoice” for EPA Air Office analyses and would be appropriate for the Steam Electric ELGs analyses. 14
Another analysis capability that is provided by IPM is assessment of the impact of Steam Electric ELGs in conjunction with the impact of other regul ations (e.g., GHG regulations or revised emission requirements for Clean Air Act criteria pollutants) for which compliance response may be occurring during the same years that the Steam Electric ELGs requirements would be occurring.

1.6.1 Key Specifications for Electricity Market Model Analysis

1.6.1.1 Model Inputs and Specifications Years of interest will have to be specified for IPM model runs. Due to the data- and calculation-intensive computational procedures required for the IPM dyna mic optimization algorithm, IPM is typically run only for a limited number of representative years (“r un years”), which are selected based on analytical requirements (e.g., the need to capture changes over the modeled time horizon) and the estimated regulatory compliance schedule.
In addition to the specification of run years, other needed model inputs include:

3⁄4 Traditional cost items such as capital, fixed and variable O&M, and administrative costs

3⁄4 Year of compliance

3⁄4 Potential energy penalty effects – e.g., if opera tion of the compliance technology will require use of the plant’s electric production, which would otherwise be available for sale

3⁄4 Duration of generating unit downtime, if any, for technology installation.
Because the electricity market model analysis is perfo rmed at the level of the individual generating unit, this information has to be provided at the level of a generating unit. It is our understanding that for therevised Steam Electric ELGs, compliance costs will be developed for treatment systems operated by inscope facilities. The information used to map generati ng units to the waste streams and treatment systems, as well as revenue associated with each generating unit, waste stream, and treatment system at in-scope facilities, is expected to be obtained through the St eam Electric survey currently being developed. We will use this information to allocat e compliance costs to the individual generating units owned by inscope facilities. In the event that this information ca nnot be obtained through this survey, facility-level costs can be allocated across all affected steam gene rating units using allocati on factors based either on steam generating capacity from IPM or on bo iler-level water flow data from 2005 EIA-767. 15

1.6.1.2 Model Outputs IPM provides a broad set of outputs that may be u seful in assessing the overall cost and economic impact of the Steam Electric ELGs. IPM provides outputs for the NERC regions that lie within the continental United States. IPM does not analyze electric power operations in Alaska and Hawaii because these states’ electric power operations are not interconnected to th e continental U.S. power grid. The model generates a series of outputs on different levels of aggregation (generating unit, model plant, region, and nation).

14 For more information on the IPM model, see IPM documentation available online at: http://www.epa.gov/airmarke ts/progsregs/epa-ipm/

15 Note that this EIA database was discontinued; 2005 is the last year, for which these data are available.Abt Associates Inc., October 29, 2009 Economic/Financial Analyses for Revisions to the Steam Electric ELGs 10 For each model run (baseline case – i.e., pre-complian ce – and each analyzed regulatory option), the following model outputs will be generated:

3⁄4 Capacity – Capacity is a measure of the ability to generate electricity. This output measure reflects the summer net dependable capacity of a ll generating units at the plant. The model differentiates between existing capacity, new capac ity additions, and existing capacity that has been repowered.

3⁄4 Early Retirements – IPM models two types of plant closures: closures of nuclear plants as a result of license expiration and economic closures as a r esult of negative net present value of future operation. This analysis considers only economic closures in assessing the impacts of the final rule and other regulatory alternatives.

3⁄4 Energy Price – The average annual price received for the sale of electricity.

3⁄4 Capacity Price – The premium over energy prices received by facilities operating in peak hours during which system load approaches availabl e capacity. The capacity price is the premium required to stimulate new market entrants to cons truct additional capacity, cover costs, and earn a return on their investment. This price manifests as short term price spikes during peak hours and, in long-run equilibrium, need be only as large as is required to justify investment in new capacity.

3⁄4 Generation – The amount of electricity produced by each pl ant that is available for dispatch to the transmission grid (“net generation”).

3⁄4 Energy Revenue – Revenue from the sale of electricity to the grid.

3⁄4 Capacity Revenue – Revenue received by facilities operating in hours where the price of energy exceeds the variable production cost of generation for the next unit to be dispatched at that price in order to maintain reliable energy supply in the short run. At these peak hours, the price of energy includes a premium which reflects the cost of the required reserve margin and serves to stimulate investment in the additional capacity re quired to maintain a long-run equilibrium in the supply and demand for capacity.

3⁄4 Fuel Costs – The cost of fuel consumed in the generation of electricity.

3⁄4 Variable Operation and Maintenance Costs – Non-fuel O&M costs that vary with the level of generation, e.g., cost of consumables, in cluding water, lubricants, and electricity.

3⁄4 Fixed Operation and Maintenance Costs – O&M costs that do not vary with the level of generation, e.g., labor costs and capital expend itures for maintenance. In the post-compliance cases, fixed O&M costs also include annualized capital costs of compliance and permitting costs.

3⁄4 Capital Costs – The cost of construction, equipment, a nd capital. Capital costs are associated with investment in new equipment, e.g., the replace ment of a boiler or condenser, installation of technologies to meet the requirements of air regulations, or the repowering of a plant.

1.6.1.3 Analysis of Model Run Results Comparison of these outputs for the baseline and po st-compliance cases will pr ovide insight into the effect of the revised Steam Electric ELGs on affected facilities and broader electric power markets. To assess the impact of revised Steam Electric ELGs during the steady state period of post-compliance operations, we will analyze model run results for the fi rst year after promulgation in which all in-scope facilities would have achieved compliance. If installa tion downtime is required under the revised Steam Electric ELGs, we also will analyze results for a model run year within the compliance period during which in-scope facilities would experience installati on downtime. This secondary analysis will provideAbt Associates Inc., October 29, 2009 Economic/Financial Analyses for Revisions to the Steam Electric ELGs 11 insight into potential market-level effects of te mporary operation shut down to complete technology installation.

1.6.2 Expected Findings The findings for this analysis will depend, to a large degree, on the requirements specified under the revised Steam Electric ELGs, the level of complian ce costs assigned to each steam electric generating unit, which steam electric generating units are assi gned compliance costs, whether compliance with the revised requirements will require installation downtim e, and the overall electricity market interaction modeled by the IPM. As previously stated, whether th is level of analysis is warranted will depend on the expected magnitude of compliance costs, both for indi vidual plants and in aggregate across the industry.


### 2 Assessing the Potential Impact on Sm all Entities – Regulatory Flexibility Act (RFA) Analysis
In accordance with requirements of the Regulatory Flexibility Act (RFA), EPA assesses whether actions would have “a significant impact on a substantia l number of small entities” (SISNOSE). Small entities include small businesses, small organizations, and sma ll governmental jurisdictions. Based on EPA’s past analyses of Steam Electric entities, we do not antici pate that a majority of the businesses that will be affected by revisions to the Steam Electric ELGs will be defined as small.

2.1.1 Analysis Approach and Data Inputs The potential impact of regulatory options on small entities will be assessed by comparing the estimated entity-level annualized compliance cost to entity-le vel revenue for each small entity identified as owning in-scope facilities. To assess whether these pa rent entity-level costs could constitute a significant impact

, we will assess whether the parent-lev el costs exceed one percent or three percent of entity-level revenue.

2.1.1.1 Determining Whether Pare nt Entities Are Small Entities Whether a respondent is defined as small depends on the size of the domestic parent and is based on the appropriate Small Business Administration (SBA) entity size criterion. The criteria for entity size determination vary by the organization/opera tion category of the parent entity, as follows:

3⁄4 For private entities , which include investor-owned utilities, non-utility entities, and entities with a primary business other than electric power generation:

 For entities with electric power generation as a primary business, small entities are those with total annual electric output less than 4 million MWh.

 For entities with a primary business other than electric power generation, the relevant size criteria are based on revenue or number of employees by NAICS sector. In conducting an RFA analysis for the 316(b) Phase II Proposed Ru le, which applies to a similar set of steam electric facilities, EPA determined that certain in-scope facilities are owned by entities whose primary business is not electric power generation (see Table 2-1 , below).

3⁄4 For public entities , which include federal, state, muni cipal, and political subdivision entities:

 Facilities owned by Federal and State government s are considered to be large; facilities owned by municipalities and other political units with population less than 50,000 are considered to be small

3⁄4 For not-for-profit enterprises, which include rural electric cooperatives:

 Small entities are those with total annual electric output less than 4 million MWh.Abt Associates Inc., October 29, 2009 Economic/Financial Analyses for Revisions to the Steam Electric ELGs 12 Table 2-1: NAICS Codes and SBA Size Standards for Entities With a Primary Business Other Than Electric Power Generation

NAICS Code NAICS Description SBA Size Standard 221210 N atural Gas Distribution 500 Employees 221310 Water Supply and Irrigation Sy stems Revenue of $7,000,000 331315 Aluminum Sheet, Plate, and Foil Manufacturing 750 Employees 524126 Direct Property and Casualty In surance Carriers 1,500 Employees 525990 Other Financial Vehicl es Revenue of $7,000,000 551112 Offices of Other Holding Companies Revenue of $7,000,000 562212 Solid Waste Landfill Revenue of $12,000,000

562219 Other Nonhazardous Waster Treatment and Disposal Revenue of $12,000,000

562920 Materials Recovery Fac ilities Revenue of $12,000,000 611310 Colleges, Universities, and Profe ssional Schools Revenue of $7,000,000 Source: SBA, 2008

Parent entities for which the relevant measure is less than the SBA size criterion will be identified as small entities and carried forward in the RFA anal ysis. The number of small parent-entities will be estimated as follows:

3⁄4 Determine domestic parent entities of in-scope facilities: The domestic parent entity for each in-scope facility will be identified through th e Steam Electric survey or using the approach outlined in Section 1.2

. 3⁄4 Determine which of those domestic parent entities are small : To determine whether a parent entity is small according to the criteria listed above , we will compare the relevant measure for the identified parent entities to the appropriate SBA si ze criterion. The appropriate SBA size metric for each parent entity will be obt ained from the following sources:

 Electricity output : For size determination based on elect ricity output, we will use average utility-level electricity sales reported in the Steam Electric survey or, if the data are not available, the average utility-level sales over a specified 5-year period as reported in the EIA861 database. For facilities not listed in the EIA-861 database, the 5-year average facilitylevel generation values can also be obtained from the EIA-906/920 database.

 Revenue and Employment : For size determination based on revenue or total number of employees, we will use data from the Steam Elec tric survey. If the data are not available, these values can be obtained from other sources, such as corporate or other websites. To estimate revenue for utilities, we will use 5-y ear average revenue values reported for utilities in the EIA-861 database. When necessary, reve nue values will be restated in dollars of a given analysis year using the Producer Price I ndex for industrial electric power (Electric PPI) obtained from BLS (http://data.bls.gov/cgi-bin/srgate).

 Population data for municipalities and other non- state subdivisions will be obtained from the U.S. Census Bureau.

2.1.1.2 Assessing Parent Entity Impact Two criteria determine whether revisions to the Steam Electric ELGs would qualify for a no-SISNOSE finding:

3⁄4 Is the absolute number of small entities estimated to incu r a potentially significant impact substantial ?

andAbt Associates Inc., October 29, 2009 Economic/Financial Analyses for Revisions to the Steam Electric ELGs 13 3⁄4 Is the percentage of total small entities in the affected sectors that these significant impact entities represent a substantial fraction of all small entities in the electric power industry that could potentially be within the scope of a regulation?

This assessment is made as follows:

3⁄4 The potential impact of the regulatory options on small entities owning in-scope facilities will be assessed by comparing the estimated entity-level annualized compliance cost to entity-level revenue. Small entities with compliance costs estimat ed to exceed one percent or three percent of entity-level revenue will be asse ssed as incurring potentially significant impacts . Inputs for this analysis will include:

 Facility-level costs for in-scope facilities owned by small entities, aggregated to the level of the parent.

 Parent-level revenue values obtained from the Steam Electric survey or, in the absence of survey data, estimated using the methodology outlined in Section 1.2

. 3⁄4 We will assess whether those sm all entities incurring potentially significant impacts represent a substantial number of small entities based on (1) the estimated numbers of small entities incurring potentially significant impacts according to the two cost impact criteria, and (2) the fraction of total small entities in the relevant entity categories estimated to incur these impacts. The fraction of small entity totals represented by the significant impact entities is an important measure of the potential small entity impact of the proposed regulation. For example, if a high percentage of potentially in-scope small entities incur significant impacts even though the absolute number of significant impact entities is low , then the regulation could constitute a substantial burden on small entities.
Insight on the second factor requires information on the total number of small entities in the electric power sector and by entity type. This info rmation is expected to come from the Steam Electric survey currently being developed. In the absence of the survey data , the best alternative data source identified by EPA to support the parent entity-level determination of the number of small entities in the affected electric power generating segments are from the EIA-861 database, which reports total electric power generation for regulated utilities at the level of the electric power utility . These data thus provide a basis for estimating the total number of regulated utilities at the level of the utility that would qualify as small based on the 4,000 MWh production quantity threshold of electric power generation. In the ev ent where the data need to be estimated, we would adjust this estimate to account for poten tial errors in which this estimate may result. 16

2.1.2 Expected Findings While results are expected to vary by ownership type and regulatory option, based on the prior RFA analyses conducted for steam electric facilities, we exp ect that revisions to the Steam Electric ELGs will

16 Potential errors include the following: (1) The desired count of small entities is not at the level of the utility but at the level of the highest domestic parent, which in the electric power industry is often a holding company that may own several utilities operating in different state jurisdictions. As a result, th e count of utilities that appe ar to be small entities on t he basis of their utility-level electric power generation as reported in EIA-861 is likely to overstate the count of parent-level entiti es that would qualify as small entities if the determination were made of the basis of electric power generation aggregated over regulated utilities and non-regulated busine sses at the parent level. (2) Accordin g to the SBA entity-size criteria, the determination of small en tities for electric power facilities owned by muni cipalities and other poli tical subdivisions should be based on population served instead of electric power ge nerated. (3) EIA-861 includes information only for regulated utilities and includes no electric power generation data for non -regulated electric power generating businesses. Some of these non-regulated electric power genera ting businesses, which are not included in the EIA-861 database, are likely to qualify as small entities.Abt Associates Inc., October 29, 2009 Economic/Financial Analyses for Revisions to the Steam Electric ELGs 14 not have “a significant impact on a substantial number of small entities.” For instance, in conducting an RFA analysis for the 316(b) Phase II Proposed Rule, which applies to a similar set of Steam Electric facilities, EPA found that 21 percent of parent entities of Steam Electric facilities were small. Further, EPA found that the estimated numbers of small en tities incurring potentially si gnificant cost impacts represent small absolute numbers and percentages of th e total of small entities – less than one and a half percent – in the relevant affected sectors. Given (1 ) the small absolute number of small entities estimated to incur a potentially si gnificant cost impact and (2) the small percentage of total small entities in the affected sectors that these entities represent, we expect that analyses will show that this rule will not to have “a significant impact on a substantial number of small entities.”


### 3 Unfunded Mandates Reform Act (UMRA) Analysis

Title II of the Unfunded Mandates Reform Act of 1995, Pub. L. 104-4, est ablishes requirements for Federal agencies to assess the effects of their regulatory actions on State, local, and Tribal governments and the private sector. Under UMRA section 202, EPA generally must prepare a written statement, including a cost-benefit analysis, for proposed and final rules with “Fed eral mandates” that might result in expenditures by State, local, and Tribal governments, in the aggregate, or by the private sector, of $100 million or more in any one year. Before promul gating a regulation for which a written statement is needed, UMRA section 205 generally requires EPA to identify and consider a reasonable number of regulatory alternatives and adopt the least costly, most cost-effective, or least burdensome alternative that achieves the objectives of the rule. The provisions of section 205 do not apply when they are inconsistent with applicable law. Moreover, secti on 205 allows EPA to adopt an altern ative other than the least costly, most cost-effective, or least burdensome alternativ e if the Administrator publishes with the rule an explanation why that alternative was not adopted. Before EPA establishes any regulatory requirements that might significantly or uniquely affect small govern ments, including Tribal governments, it must have developed under section 203 of the UM RA a small government agency plan. The plan must provide for notifying potentially affected small governments, enab ling officials of affected small governments to have meaningful and timely input in the development of EPA regulatory proposals with significant intergovernmental mandates, and informing, edu cating, and advising small governments on compliance with regulatory requirements.
Although whether a given rule contains a Federal ma ndate depends on the level of compliance costs, we expect that revisions to the Steam Elec tric ELGs may contain a Federal mandate. 17 If so, under §202 of the UMRA, EPA will have to prepare a written statemen t, presented in the preamble to the proposed rule, that includes (1) a cost-benefit anal ysis; (2) an analysis of macroec onomic effects; (3) a summary of State, local, and Tribal input; (4) a discussion related to the least burdensome option requirement; and (5) an analysis of small government burden.

3.1.1 Analysis Approach and Data Inputs For UMRA analyses, government entities include only State, local, and Tribal governments and exclude Federal governments. The analysis will involve the following steps:

3⁄4 Determine domestic parent entity : We will use the information collected through the Steam Electric survey, or determined from public da ta sources following the methodology outlined in Section 1.2

. 3⁄4 Estimate compliance costs : In evaluating a magnitude of the regulatory impact on government entities, we will consider two burden concepts : (1) compliance costs incurred by government

17 In conducting an UMRA analysis for th e 316(b) Phase II Proposed Rule, EPA had de termined that this regulation contained a Federal mandate that might result in expenditures of $100 millio n or more for State, local, and Tribal governments, in the aggregate, or the private sector in any one year.Abt Associates Inc., October 29, 2009 Economic/Financial Analyses for Revisions to the Steam Electric ELGs 15 entities owning facilities required to meet the standards of the regulation and (2) administrative costs incurred to implement the revised Steam Electric ELGs. Parent entity-level compliance costs will be calculated by aggregating annualized pre-tax facility-level compliance costs to the level of the parent entity.

3.1.2 Expected Findings Analysis results are expected to vary by regulat ory option. As stated above, depending on technologies required by revisions to the Steam Electric ELGs, EPA expects that regulatory options may result in expenditures of at least $100 million for State and local government entities, in the aggregate or for the private sector in any one year.
In conducting UMRA analysis for the 316(b) Phase II Proposed Rule, which also concerns steam electric facilities, EPA found that 47 percent of all in-scope facilities were owned by government entities, where 28 percent of these government-owned facilities were owned by small governments, all of which were municipalities. This constitutes one third of the total number of facilities owned by municipalities. Both in the aggregate and per facility costs were lowe r for small governments in comparison to large governments; consequently, small govern ment was determined not to be significantly or uniquely affected by the Rule.


### 4 Other Administrative Requirements
4.1 Executive Order 12866: Regul atory Planning and Review Under Executive Order 12866 (58 FR 51735, Octobe r 4, 1993), EPA must determine whether the regulatory action is “significant” a nd therefore subject to the Office of Management and Budget (OMB) review and the requirements of the Executive Order. The order defines a “significant regulatory action” as one that is likely to result in a rule that may:

3⁄4 Have an annual effect on the economy of $100 milli on or more or adversely affect in a material way the economy, a sector of the economy, produc tivity, competition, jobs, the environment, public health or safety, or State, local, or Tribal governments or communities; or

3⁄4 Create a serious inconsistency or otherwise interfe re with an action taken or planned by another
agency; or
3⁄4 Materially alter the budgetary impact of entitlement s, grants, user fees, or loan programs or the rights and obligations of recipients thereof; or

3⁄4 Raise novel legal or policy issues arising out of le gal mandates, the President’s priorities, or the principles set forth in the Executive Order.

Whether revisions to the Steam Electric ELGs will be determined to be an “economically significant regulatory action” depends on technol ogy requirements, costs associated with these technologies, as well as costs associated with administrative activities requi red to implement the revised Steam Electric ELGs. If this action meets the threshold, we will s upport EPA in performing the needed analyses and documentation of costs and benefits for OMB review.



### 4.2 Executive Order 12898: Federal Actions to Address Environmental Justice in Minority Populations and Low-Income Populations Executive Order 12898 (59 FR 7629, February 11, 1994) requires that, to the greatest extent practicable and permitted by law, each Federal agency must make the achievement of environmental justice part of its mission. E.O. 12898 provides that each Federal agency must conduct its programs, policies, and activities that substantially affect human health or the environment in a manner that ensures such programs, policies, and activities do not have the effe ct of (1) excluding persons (including populations)Abt Associates Inc., October 29, 2009 Economic/Financial Analyses for Revisions to the Steam Electric ELGs 16 from participation in, or (2) denying persons (incl uding populations) the benefits of, or (3) subjecting persons (including populat ions) to discrimination under such progr ams, policies, and activities because of their race, color, or national origin.
The revisions to the Steam Electric ELGs will require th at the location, design, construction, and capacity of treatment technologies underlying Steam Electric EL Gs at Steam Electric facilities reflect the best available, practicable, and economically achievable technology. For several reasons, we do not expect that the revisions to the Steam Electric ELGs would be found to have an exclusionary effect, deny persons the benefits of the participation in a program, or subject persons to discrimination because of their race, color, or national origin. In fact, because we e xpect that revisions to the Steam Electric ELGs will improve water quality in receiving waterbodies and help preserve the health of aquatic ecosystems located in reasonable proximity to existing Steam Electric fa cilities, it is likely that all populations, including minority and low-income populations, will benefit fro m improved environmental conditions as a result of this rule.

4.2.1 Analysis Approach and Data Inputs As part of analyses performed in support of the revi sions to the Steam Electric ELGs, EPA will need to analyze the benefits to affected populations of reducing pollutant dischar ges from Steam Electric facilities. Affected populations may be expected to in clude (1) all individuals who live within a 50-mile radius of the facilities and (2) any additional angler s who live outside of the 50-mile facility buffer and within a 50-mile radius of the reaches nearest to in-s cope facilities. Individuals who live within a 50-mile radius of the facility may receive both use (e.g., drinking water, swimming, recreational fishing or wildlife viewing) and non-use benefits from the impr oved aquatic ecosystem health of the area (e.g., satisfaction from knowing that the overall ecosystem h ealth has improved). Anglers who live within the 50-mile buffer zone are more likely to fish the aff ected water body and thus benefit from reduced human health impacts of consuming their catch and/or im proved catch rates as a result of the proposed rule. 18
To meet the objectives of Executive Order 12898, we will assess whether the revisions to the Steam Electric ELGs could distribute benefits among popula tion sub-groups in a way that is significantly unfavorable to low income and minority populations . Specifically, on a state-by-state basis, we will compare key demographic characteristics of the sub-st ate populations that are expected to benefit from the proposed rule with those demographic characteris tics at the level of the state. If the demographic profile of the sub-state “benefit population” is found to be statistically similar to the demographic profile of the state, and not exclusionary of minority and low income populations specifically, then the regulation would be assessed as not yielding an unfavorable distribution of benefits, from the perspective of the public policy principles of Executive Order 12898.
The analysis of the socio-economic characteristics of the populations a ffected by in-scope facilities will be conducted using the Fish Cons umption Pathway (FCP) Module, which reports population estimates by socio-economic characteristics. The tw o demographic variables of interest for this EJ analysis are those within the FCP Module that best capture the low-inco me and minority aspects of the populations affected, which are:

3⁄4 Annual household income: less than $19,999 (l ow-income) and mo re than $20,000 ( notlowincome); 19 and

18 According to the US Fish and Wildlife Service, over 65% of anglers travel less than 50 mi les one-way on a typical fishing trip. (U.S. DOI, 2005)

19 Annual household income data in the FCP Module is available for the following categories: less than $10,000; $10,000 to $19,999; $20,000 to $24,999; $25,000 to $29,999; $30,000 to $34,999; $35,000 to $39,999; $40,000 to $49,999; $50,000 to $74,999; $75,000 to $99,999; and more than $100,000. These categories were combined into low- and not low-incomeAbt Associates Inc., October 29, 2009 Economic/Financial Analyses for Revisions to the Steam Electric ELGs 17 3⁄4 Race: white, black or African American, Asian or Native Hawaiian or Other Pacific Islander, American Indian and Alaska Native, and some other race.
As stated above, the primary groups that benefit from revisions to the Steam Electric ELGs are assumed to consist of (1) all individuals who live within a 50-mile radius of the fac ilities and (2) any additional anglers who live outside of the 50-mile facility buffer and within a 50-mile radius of the reaches nearest to in-scope facilities. To assess whether a lowe r income or minority group would experience a disproportionately low share of the regulation’s use and non-use benefits in relation to the general population, the income and ethnicity of the affected populations will be calculated in the FCP Module and analyzed statistically, usi ng the following procedures:

3⁄4 The coordinate locations of each of the facilities will be imported into the FCP Module.

3⁄4 The FCP module will estimate the number of indivi duals residing within 50 miles of each facility.

3⁄4 The FCP module will calculate the number of additiona l anglers that fish in the affected reaches but do not live within a 50-mile radius of the facility on the affected reach by estimating the number of anglers within a 50-mile radius of th e affected reach and then subtracting the number of anglers within 50 miles of the facility that overlap with the 50-mile radius surrounding the affected reach.

3⁄4 Areas affected by in-scope facilities will be spa tially defined. They will then be superimposed on the FCP Module’s grid, and cell- level population data will be u sed to define a demographic profile for the affected populations

3⁄4 Once these population estimates are made, the da ta will exported and examined on a state-bystate basis.

3⁄4 To examine environmental justice concerns fo r the regulatory options, we will compare the composition of the affected populations’ income and race with the demographic composition of the state population by (1) calculating a ratio of low- to high-income individuals in the vicinity of in-scope facilities and comparing it to the averag es within each affected state; (2) calculating a ratio of minority to white individuals in the vici nity of in-scope facilities and comparing it to the averages within each affected state; and (3) tes ting the statistical significance of difference in these observed state-by-state relationships.
If the demographic profiles of the affected population and the state are not statistically different and not exclusionary of low income and minority populations specifically, then revisions to the Steam Electric ELGs would be assessed as not yielding an unfavorable distribution of benefits, from the perspective of the public policy principles of Executive Order 12898.

4.2.2 Expected Findings In conducting this analysis for the 316(b) Phase II Proposed Rule, which also covers steam electric facilities, EPA concluded that, overall, the Rule was consistent with the policy intent of E.O. 12898. Based on the comparison of socio-economic characteristics of individuals affected by the Phase II existing facilities to the affected states’ overall popula tions, EPA found that the low income population is less present, in a statistically significant way, in the estimated benefit population than in the states’ general populations. However, minority populations are not less present in the estimated benefit population than in the states’ general populations. Th us, from this analysis, it is possible that the lowincome population group may participate to a lower exte nt in the benefits of the proposed regulation than the general population in the states with Steam Elec tric facilities. However, EPA did not judge this

groups based on the U.S. Department of Health and Human Services’ 2007 poverty guidelines, which state that the poverty guideline in 2007 for a family of four living in the cont iguous United States or D. C. is $20,650 (U.S. HHS, 2007).Abt Associates Inc., October 29, 2009 Economic/Financial Analyses for Revisions to the Steam Electric ELGs 18 observation to mean that the proposed 316(b) regulati on systematically discriminates against, or excludes or denies participation of, the lower income population group, in a way that would be contrary to the intent of E.O. 12898. 20

Because revisions to the Steam Electric ELGs will co ver a similar set of Steam Electric facilities, it is possible that findings will be similar to those for the 316(b) Phase II Proposed Rule, i.e, that this regulation will be determined to be consistent with the policy intent of E.O. 12898.



### 4.3 Executive Order 13045: Protection of Ch ildren from Environmental Health Risks and Safety Risks Executive Order 13045 (62 FR 19885, April 23, 1997) app lies 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 believe might have a disproportionate effect on children. If the regulatory action meets both criteria, the Agency must evaluate the environmental health and safety effects of the planned rule on children and explain why the planned regulation is preferable to other potentially effective and reasonably feasible alterna tives considered by the Agency. As discussed above, the revisions to the Steam Electric ELGs may be economically significant – as defined under Executive Order 12866 – depending on technology requirements, and the resulting costs associated with these technologies as well as costs associated with administ rative activities required to implement the revised Steam Electric ELGs. However, based on the prior re gulatory analyses of the electric power industry, we do not expect the revisions to the Steam Electric ELGs to concern an environmental health or safety risk that would have a disproportionate effect on children. This regulatio n is expected to improve water quality by establishing more stringent effluent treatment requirements.
While the regulation may not be subject to Executive Order 13045, EPA may still wish, as part of the Environmental Assessment of the regulation, to analyze effects on children and other susceptible populations of effluent discharges from Steam Electric facilities, since many of the pollutants associated with the discharges (e.g., lead, mercury) ha ve health effects on children specifically.



### 4.4 Executive Order 13132: Federalism Executive Order 13132 (64 FR 43255, August 10, 1999) requires EPA to develop an accountable process to ensure “meaningful and timely input by State a nd local officials in the development of regulatory policies that have federalism implications.” “Policies that have federalism implications” are defined in the Executive Order to include regulations that have “substantial direct effects on the States, on the relationship between the national government and the States, or on the distribution of power and responsibilities among the various levels of government.”
Under section 6 of Executive Order 13132, EPA ma y not issue a regulation that has federalism implications, that imposes substantial direct complian ce costs, and that is not required by statute unless the Federal government provides the funds necessary to pay the direct compliance costs incurred by State and local governments or unless EPA consults with St ate and local officials early in the process of developing the regulation. EPA also may not issue a regulation that has federalism implications and that

20 EPA observed that the lower income popul ation group was materially present in the benefit population for all states and in all but three states the difference in presence was very small. In addition, EPA determined that the finding that low income populations were observed to be systemat ically less present in the potential be nefit population, would mean that this population group had systematically incurred less damage from the ongoing operation of cooling water intake structures at Phase II power facilities than the general population of the stat es with Phase II facilities. Finally, because all Phase II facilities are subject to the Ph ase II proposed regulation, there could be no sy stematic discrimination or exclusion of low income populations from participation in the Rule’s benefits, base d, for example, on selection of only specific facilities to which the regulation would apply.Abt Associates Inc., October 29, 2009 Economic/Financial Analyses for Revisions to the Steam Electric ELGs 19 preempts State law, unless the Agency consults with State and local officials early in the process of developing the regulation.
It is unlikely that revisions to the Steam Electric ELG s will have substantial direct effects on the States, on the relationship between the nati onal government and the States, or on the distribution of power and responsibilities among the various levels of government, as specified in Executive Order 13132. This is based on the fact that none of the 316(b) Regulations , which also dealt with Steam Electric facilities, had federalism implications.
The Steam Electric requirements will be implemente d through permits issued under the NPDES program. Forty-six States and territories are currently author ized pursuant to section 402(b) of the CWA, to implement the NPDES program. In States not authorized to implement the NPDES program, EPA issues NPDES permits. Under the CWA, States are not require d to become authorized to administer the NPDES program. Rather, such authorization is available to States if they operate their programs in a manner consistent with section 402(b) and applicable regulations. We do not expect revisions to the Steam Electric ELGs to have substantial direct effects on ei ther authorized or nonauthorized States or on local governments because it will not change how EPA and th e States and local governments interact or their respective authority or responsibilities for implemen ting the NPDES program. NPDES-authorized States that currently do not comply with th e proposed regulations based on this rule might need to amend their regulations or statutes to ensure that their NPDES programs are consistent with revised Steam Electric ELG requirements. For purposes of revisions to the St eam Electric ELGs, the relationship and distribution of power and responsibilities betwee n the Federal government and the State and local governments are established under the CWA (e.g., sections 402(b) and 510); nothing in EPA’s action pertaining to the Steam Electric ELGs is expected to alter that. Thus , the requirements of section 6 of the Executive Order are not expected to apply to the revisions to the Steam Electric ELGs.



### 4.5 Executive Order 13158: Marine Protected Areas Executive Order 13158 (65 FR 34909, May 31, 2000 ) requires EPA to “expeditiously propose new science-based regulations, as necessary, to ensure ap propriate levels of protection for the marine environment.” EPA may take action to enhance or e xpand protection of existing marine protected areas and to establish or recommend, as appropriate, new marine protected areas. The purpose of the Executive Order is to protect the significant natural and cultu ral resources within the marine environment, which means “those areas of coastal and ocean waters, th e Great Lakes and their connecting waters, and submerged lands thereunder, over which the United States exercises jurisdiction, consistent with international law.” We expect that the proposed St eam Electric regulation will advance the objective of Executive Order 13158.
Marine protected areas (MPAs) include designated areas with varying levels of protection, from fishery closure areas, to aquatic National Parks, Marine Sanctuaries, and Wildlife Refuges (NOAA, 2008). 21 MPAs can help address problems related to the deple tion of marine resources by prohibiting, or severely curtailing, activities that are permitted or regulated by law outside of MPAs. Such activities include oil exploration, dredging, dumping, fishi ng, certain types of vessel traffic, and the focus of revisions to the Steam Electric ELGs: discharge of pollutants.
Discharge of pollutants such as arsenic, boron, cad mium, cobalt, and other inorganic and organic substances found in Steam Electric plant effluents to surface waters affect many kinds of aquatic

21 The Departments of Commerce and the Inte rior have developed an inventory of MP As in the U.S. that are protected and managed under Federal, St ate, Territorial, Tribal, or local laws. Examples of marine protected areas include the Great Bay National Wildlife Refuge in New Hampshire, the Cape Cod Ba y Northern Right Whale Critical Habitat in Massachusetts, the Narragansett Bay National Estuarine Research Reserve in Rhode Island, Everglades National Park and the Tortugas Shrimp Sanctuary in Florida, and the Point Reyes National Seashore in California.Abt Associates Inc., October 29, 2009 Economic/Financial Analyses for Revisions to the Steam Electric ELGs 20 organisms, including fish, shellfish, birds, and marine mammals. In addition to the harm that results from the direct ingestion of these pollutants, there are indirect effects that result from the accumulation of toxins across species. Ecological impacts of Steam El ectric facility effluent pollutants are expected to include acute and chronic toxicity to aquatic recept ors, uptake of certain pollutants into aquatic food webs, sublethal effects on metabolic and reproductive functions, habitat degradation, eutrophication, dissolved oxygen depletion, and loss of prey organisms. Metals are of particular concern to this regulation because they (1) do not volatilize, (2) do not biodegrade, (3) can be toxic to plants, invertebrates and fish, (4) adsorb to sediments and (5) bi oconcentrate in biological tissues. There are also cumulative impacts that result from multiple Steam Electric facilities ope rating in the same local area, or when multiple effluents affect individuals within the same population over a broad geographic range.
By reducing the amount of pollutants discharged to surface waters, the revisions to the Steam Electric ELGs are expected to not only help protect individu al species but also the overall marine environment, thereby advancing the objective of Execu tive Order 13158 to protect marine areas.

4.5.1 Analysis Approach and Data Inputs To assess the potential MPA effects of revisions to the Steam Electric ELGs, we will identify the instances in which in-scope facilities would be expect ed to reduce the amount of pollutants discharged in areas that include MPAs. We will use ArcGIS to map facilities and MPAs. 22 Because MPAs are necessarily areas of water, while facilities are located on land, the latitude-longitude coordinates of a facility withdrawing from an MPA may not necessaril y fall within the boundaries of the MPA. In identifying in-scope facilities withdrawing from MPAs, we will consider any facility within 1 kilometer of an MPA to be affecting that MPA.

4.5.2 Expected Findings In conducting this analysis for the 316(b) Phase II Pr oposed Rule, which applies to a similar set of Steam Electric facilities, EPA found that nearly all affect ed MPAs were improved regardless of the option. However, because revisions to the Steam Electric ELGs focuses on damages to the environment due to pollutant discharges as opposed to damages due to im pingement and entrainment, the results of this analysis may be different.



### 4.6 Executive Order 13175: Consultation a nd Coordination with Indian Tribal Governments Executive Order 13175 (65 FR 67249, November 6, 2000) requires EPA to develop an accountable process to ensure “meaningful and timely input by tr ibal officials in the development of regulatory policies that have tribal implications.” “Policies that have tribal implications” is defined in the Executive Order to include regulations that ha ve “substantial direct effects on one or more Indian Tribes, on the relationship between the Federal government and the I ndian Tribes, or on the distribution of power and responsibilities between the Federal government and Indian Tribes.”
The revisions to the Steam Electric ELGs is not expect ed to have substantial direct effects on tribal governments, on the relationship between the Fede ral government and Indian Tribes, or on the distribution of power and responsibilities between the Federal government and Indian Tribes, as specified in Executive Order 13175. The national Steam Electr ic requirements would be implemented through permits issued under the NPDES program. No tribal governments are currently authorized pursuant to section 402(b) of the CWA to implement the NPDES pr ogram. In addition, EPA’s past analyses of the Steam Electric industry show that no facility subject to the ELGs is owned by tribal governments and thus

22 GIS data of MPAs will be obtained fro m the national inventory of MPAs website (http://mpa.gov/helpful_resour ces/inventory.html) and fa cility locations from the Steam Electric Surveys.Abt Associates Inc., October 29, 2009 Economic/Financial Analyses for Revisions to the Steam Electric ELGs 21 we do not anticipate revisions to the Steam Electric EL Gs to affect Tribes in an y way in the foreseeable future. 23 Consequently, Executive Order 13175 w ould not apply to this regulation.



### 4.7 Executive Order 13211: Actions Concer ning Regulations That Significantly Affect Energy Supply, Distribution, or Use The OMB implementation memorandum for E.O. 13211 24 outlines specific criteria for assessing whether a regulation constitutes a “significant energy action” and would have a “significant adverse effect on the supply, distribution or use of energy.” Those criteria include:

3⁄4 Reductions in crude oil supply in excess of 10,000 barrels per day;

3⁄4 Reductions in fuel production in excess of 4,000 barrels per day;

3⁄4 Reductions in coal production in excess of 5 million tons per year;

3⁄4 Reductions in natural gas production in excess of 25 million mcf 25 per year;
3⁄4 Reductions in electricity production in excess of 1 billion kilowatt-hours per year, or in excess of 500 megawatts of installed capacity;

3⁄4 Increases in the cost of energy production in excess of 1 percent;

3⁄4 Increases in the cost of energy distribution in excess of 1 percent;

3⁄4 Significant increases in dependence on foreign supplies of energy; or

3⁄4 Having other similar adverse outcom es, particularly unintended ones.
Of the potential significant adverse effects on the supply, distribution, or use of energy (listed above) only four would potentially apply to the revisions to the Steam Electric ELGs. Through increases in the cost of generating electricity and shifts in the types of generators employed, the revised Steam Electric ELGs might affect: (1) the production of electricity, (2) the amount of installed capacity, (3) the cost of energy production, and (4) the dependence on foreign supplies of energy.

4.7.1 Analysis Approach and Data Inputs The results from the electricity Market Model Analysis (see Section 1.6 ) will be used to analyze this rule for each of these potential effects.

4.7.2 Expected Findings The findings for this analysis will depend on the re quirements specified under th e revised Steam Electric ELGs, the level of compliance costs assigned to each steam electric generating unit, which steam electric generating units are assigned compliance costs, and th e overall electricity market interaction modeled by the IPM. Based on the analysis conducted in sup port of 316(b) Phase II Proposed Rule, EPA concluded that 316(b) Phase II Proposed Rule would not have a significant adverse effect at a national or regional level and, consequently, did not prepare a Statement of Energy Effects. It is possible that the same conclusion will be reached for this action.

23 None of the 316(b) regulations, which also dealt with Steam Electric fa cilities, were determined to have tribal implications.

24 Executive Order 13211 was issued May 18, 2002. The Office of Management and Budget later released an Implementation Guidance memorandum on July 13, 2002.

25 Mcf stands for one thousand cubic feet. It is a unit of measure that is more comm only used in the low volume sectors of the gas industry.Abt Associates Inc., October 29, 2009 Economic/Financial Analyses for Revisions to the Steam Electric ELGs 22 

### 4.8 Paperwork Reduction Act of 1995 The Paperwork Reduction Act of 1995 (PRA) (supersed ing the PRA of 1980) is implemented by OMB and requires that agencies submit a supporting statem ent to OMB for any information collection that solicits the same data from more than nine parties. The PRA seeks to ensure that Federal agencies balance their need to collect information with the paperw ork burden imposed on the public by the collection.

The definition of “information collection” includ es activities required by regulations, such as permit development, monitoring, record keeping, and reporting. The term “burden” refers to the “time, effort, or financial resources” the public expends to provide inform ation to or for a Federal agency, or to otherwise fulfill statutory or regulatory requirements. PRA pape rwork burden is measured in terms of annual time and financial resources the public devotes to meet one -time and recurring information requests (44 U.S.C. 3502(2); 5 C.F.R. 1320.3(b)). Information collection activities may include:

3⁄4 reviewing instructions; 3⁄4 using technology to collect, process, and disclose information; 3⁄4 adjusting existing practices to comply with requirements; 3⁄4 searching data sources; 3⁄4 completing and reviewing the response; and 3⁄4 transmitting or disclosing information.
Agencies must provide information to OMB on the parties affected, the annual reporting burden, the annualized cost of responding to the information coll ection, and whether the request significantly impacts a substantial number of small entities. An agency may not conduct or sponsor, and a person is not required to respond to, an information collection unle ss it displays a currently valid OMB control number.
Whether OMB approves the information collection requi rements under the revisions to the Steam Electric ELGs, depends on what will be required.


### 4.9 National Technology Transfer and Advancement Act Section 12(d) of the National Technology Transfer and Advancement Act (NTTAA) of 1995, Pub L. No. 104-113, Sec. 12(d) directs EPA to use voluntary consensus standards in its regulatory activities unless doing so would be inconsistent with applicable law or otherwise impractical. Voluntary consensus standards are technical standards (e.g., materials sp ecifications, test methods, sampling procedures, and business practices) that are developed or adopted by voluntary consensus standard bodies. The NTTAA directs EPA to provide Congress, through OMB, expl anations when the Agen cy decides not to use available and applicable vol untary consensus standards.

Provided that revisions to the Steam Electric ELGs w ill not involve such technical standards, then no voluntary consensus standards would have to be considered.



### 5 Assessment of Total Social Costs
EPA will likely need to develop estimates of the cost s to society resulting from revisions to the Steam Electric ELGs. For this analysis, the social costs of regulatory actions are the opportunity costs to society of employing scarce resources to prevent the envir onmental damage from effluent discharge from Steam Electric facilities.


### 5.1 Analysis Approach and Data Inputs

To assess the economic costs to soci ety of the Steam Electric ELGs, we will rely first on the estimated costs to facilities for the labor, equipment, material, and other economic resources needed to comply with the revised Steam Electric ELGs. For this analysis , we will assume that the market prices for labor, equipment, material, and other compliance resources represent the opportunity costs to society for use ofAbt Associates Inc., October 29, 2009 Economic/Financial Analyses for Revisions to the Steam Electric ELGs 23 those resources to comply with the regulatory requir ements. Further, if the estimated impact of the revisions to the Steam Electric ELGs on electricity production costs for the total industry – estimated through IPM ( Section 1.6 ) – is small, we will assume that the regulation does not affect the aggregate quantity of electricity that would be sold to consum ers and, thus, that the regulation’s social cost will include no loss in consumer and producer surplus from lost electricity sales by the electricity industry in aggregate. The social cost analysis will consider facility-lev el compliance costs on an as-incurred, year-by-year basis – that is, this analysis will take the com ponents of costs before escalation to compliance year, discounting, or annualizing and will assign them to the years in which they are assumed to occur relative to the assumed promulgation and compliance years. For estimating costs to society, compliance costs are considered without accounting for any tax effects. The costs to society are the full value of the resources used, whether they are paid for by the regulated fac ilities or by all taxpayers in the form of lost tax revenues. We will develop – with EPA’s guidance – a year-explicit schedule of compliance cost and operational effects based on the Steam Electric ELGs re quirements. We will then sum the costs expected to be incurred in each year for each facility and a ggregate these costs to estimat e the total cost to the industry for each year in the analysis period. After bei ng distributed, costs will be adjusted for real change between their stated year and the year(s) of their incurrence using the Employment Cost Index (ECI), Construction Cost Index (CCI), Annual Energy Ou tlook (AEO) Electricity Price Projections, and GDP deflator, as appropriate. 26 We will then calculate the present va lue of these cost outlays as of the promulgation year by discounting the cost in each year back to promulgation year, using both 3 percent and 7 percent discount rates. These discount rates follow guidance from the OMB regulatory analysis guidance document, Circular A-4. After calculating the present value of these cost streams, we will calculate their constant annual equi valent value (annualized value), again using the two discount rates, 3 percent and 7 percent. Costs will be annualized ove r a time period that encompasses the full duration of both costs and benefits, which will reflect the time el apsed from the first incurre nce of costs in response to the revised ELGs through the last year of achievement of benefits, respectively.
Administrative costs to NPDES permitting authorities and the Federal government will also be accounted for on an as-incurred, year-explicit basis and before adjustment to incurrence year, discounting, or annualizing. For the social cost analysis, government administrative costs reflect the opportunity cost of expending taxpayer dollars to administer this regulation in lieu of other public projects.


### 5.2 Expected Findings Social costs are expected to vary across regulator y options based on administrative and technology compliance requirements and costs associated with these requirements. Based on past analyses of regulatory costs to society, compliance costs are likel y to account for the largest proportion of total social

costs.


### 6 Social Costs and Benefits of the Proposed Rule
EPA will need to compare total monetized benefits and social costs for each option considered for the revisions to the Steam Electric ELGs. Benefits and costs will be compared on two bases: (1) for each of the options analyzed and (2) incremen tally across options. This part of the analysis will also satisfy the requirements of Executive Order 12866: Regulatory Planning and Review.

26 Technology costs will be adjusted to their incurrence year(s ) using the CCI and GDP deflator; Administrative Costs will be adjusted to their incurrence year(s) using the ECI and GDP defl ator; energy penalty and downtime costs will be adjusted to their incurrence year(s) using AEO projections (which do not re quire adjustment for inflation). Costs will be aggregated in three separate groups according to the index used to adjust th em, and will then be summed to estimate total industry cost.Abt Associates Inc., October 29, 2009 Economic/Financial Analyses for Revisions to the Steam Electric ELGs 24 

### 6.1 Analysis Approach and Data Inputs In this analysis, net benefits and the benefit-cost ratio to society ar e first calculated for each regulatory option. This comparison addresses a simple quantitative relationship between estimated benefits and costs for each option by itself: for a given option, which is greater – costs or benefits – and by how much in relative terms? The benefits and costs of the options are then analyzed on an incremental basis. This incremental analysis looks at the differential relati onship of benefits and costs across options and poses a different question: as increasingly more costly options are considered, by what amount do benefits, costs, and net benefits (i.e., bene fits minus costs) change from option to option? Incremental net benefit analysis provides insight into the net gain to society from imposing increasingly more costly requirements and may aid decision-makers in choosing among a set of re gulatory proposals that otherwise have a similar quantitative relationship between benefits and co sts based on a one-option-at-a-time comparison.

We will estimate total costs to soci ety using the methodology discussed in Section 5.1 . The economic benefits 27 from the revisions to Steam Electric ELGs will be estimated using a range of valuation methods, depending on the benefit cate gory, data availability, and other appropriate factors. We will derive national benefit estimates for the proposed options from a series of regional studies across the country representing a range of water body types and aquatic resources. National benefit estimates will be obtained by summing regional benefits. We will calcula te the monetary value of use benefits of the national categorical regulatory options for in-scope facilities using two discount rates – 3 percent and 7 percent – and state these values in dol lars of a given analysis year.


### 6.2 Expected Findings The results of these analyses are expected to vary across regulatory options depending on administrative and technology compliance requirements and costs as sociated with these requirements, as well as the degree to which we will be able to monetize economi c benefits. The difference in benefits and costs across regulatory options will depend on the effec tiveness of the installed technology in reducing pollutant discharges.

27 Benefits from the Steam Electric ELGs would occur due to re duction of discharges of pollutants such as arsenic, boron, cadmium, cobalt, and other inorganic and organic subs tances to surface waters. This in turn would directly and indirectly improve human health (e.g., through reduc ed exposure to contaminated fish tissue and to contaminated water) and use benefits, such as those associated with recreational and commercial fisheries. Other ty pes of benefits, including nonuse values of the affected resources, would also be enhanced.Abt Associates Inc., January 10, 2013 Contract EP-C-07-023, Assignment 5-17, QAPP APPENDIX B
Abt Associates Memorandum – Additional Input on Data Sources and Methodology for Benefits Analyses Expected to be Conducted in Support of Revisions to the Steam Electric Effluent Limitations GuidelinesAbt Associates Inc., May 26, 2010 Additional Input on Data Sources and Methodology for Benefits Analyses 1 

# memorandum

Environment and Resources 55 Wheeler Street, Cambridge, MA  Tel: 617 492-7100  www.abtassociates.com

Date May 26, 2010

To James Covington, U.S. EPA/OW/EAD

From Elena Besedin and Isabelle Morin

Subject Additional Input on Data Sources and Methodology for Benefits Analyses Expected to be Conducted in Support of Revisions to the St eam Electric Effluent Limitations Guidelines (WA 2-17, Task 5)

This memorandum provides additional information on data sources and methodologies for the analyses described in Abt Associates’ memorandum of Marc h 31, 2010. The discussion is organized according to each type of benefits analysis expected to be c onducted in support of the Steam Electric Effluent Limitations Guidelines (ELGs) regulations: Human H ealth Benefits (Section 2); Ecological Benefits (Section 3) and Other Benefits (Section 4).
Section 1 describes inputs common to the three types of analyses and highlights those inputs that would be expected to be come from separate analyses (Engi neering Analysis or Environmental Assessment) of the regulation.



### 1 Estimation of Ambient Concentrati ons of Steam Electric Pollutants of Concern
The first step in estimating benefits is the analysis of changes in environmental concentrations of Steam Electric pollutants resulting from the regulation.
We expect that EPA engineers will provide estimates of baseline pollutant loadings and the expected reductions in pollutant releases resulting from the regu latory options under consideration. To evaluate human health and ecological benefits of the Steam El ectric ELG regulation, we would need information on the universe of facilities affected by each option to be analyzed and expected effects of the regulation, including the following data:

 Facilities affected :

 Unique identifier (e.g., Survey ID or EIA ID)

 Geographical location (latitude and longitude)

 Affected environmental medium and extent of the impacted area, by affected facility :

 Surface water: we expect that the project engineers will link Steam Electric point sources to the segment(s) of the National Hydrography Dataset (NHD) Plus stream network that receive the discharge (e.g., based on responses to the steam electric detailed questionnaire). Alternatively, we could identify the closest NHD Plus segment based on overland distance. We will then use the NHD Plus tool flow naviga tor to determine the downstream waters for a specified distance (to be determined) from Steam Electric discharges.

 Groundwater: affected aquifer identifier a nd path to surface water, if relevantAbt Associates Inc., May 26, 2010 Additional Input on Data Sources and Methodology for Benefits Analyses 2  Other media (if applicable): information on the affected media and spatial extent

 Pollutant loadings by pollutant of concern, affected facility, and environmental media :

 Surface water: At a minimum, we would need the pollutant loadings (as mass per year) entering the affected surface waterbody. In-strea m concentrations, if provided by engineers, would be used directly in the analysis. Alterna tively, if these concentrations are not available, we would use a water quality model such as HAWQS (EPA, 2009) to translate changes in loadings at the edge-of-site to changes in in -stream concentrations as part of the benefit analysis.

 Groundwater: pollutant loadings to the affected aquifer (s) and, if available and relevant, delivery factor to surface waterbody, as mass per year. Groundwater pollutant concentrations, if provided by engineers, would be used dir ectly in the analysis. Alternatively, if these concentration are not available and if benefits expected to result from changes in loadings to aquifers are expected to be significant (e.g., im pacts to private wells), we would evaluate the use of groundwater models such as CHEM FLOW to estimate changes in pollutant concentration as part of the benefit analysis.

 Other media: pollutant loadings to other medi a (e.g., air or soil) as mass per year, and/or concentration
The estimated baseline and post-compliance pollutant c oncentrations will serve as input data into human health and ecological benefits analyses.



### 2 Human Health Benefits
In this analysis, EPA will estimate human health benefits from reduced exposure to carcinogens (e.g., arsenic) and systemic health toxicants (e.g., lead and mercury). For carcinogens and pollutants with noncancer health effects for which dose response func tions are available from epidemiological literature or EPA databases, we will estimate reductions in cancer cases or other diseases from two exposure pathways: consumption of contaminated fish tissue a nd ingestion of contaminated drinking water for the exposed population. The monetary value of avoided ca ncer is typically estimated using the value of a statistical life saved (VSL). The monetary value of av oiding noncancer effects is usually estimated using the cost of illness (COI) approach or WTP values to avoid specific diseases. We propose to quantify, but not monetize, two additional measures of human health-re lated benefits. The first is the changes in fish consumption and drinking water exposures to non-can cer causing pollutants measured against non-cancer health effect reference doses (RfDs), an indicator of non-cancer health risk. The second benefit measure is the change in occurrence of polluta nt concentrations that are estim ated to exceed human health-based water quality criteria (WQC).


### 2.1 Hazard Identification and Dose Response Assessment For human health risk assessment, we will gather and evaluate all relevant toxicological and epidemiological data on the chemicals of concern to determine whether the chemicals pose a hazard to human and ecological health. In this analysis, Abt Associates will rely on the following data sources:

 EPA’s Integrated Risk Information System (IRIS)

 Health Effects Assessment Summary Tables (HEAST),

 EPA’s National Recommended Water Quality Criteria (WQC),

 EPA’s Maximum Contaminant Levels for Drinking Water (MCL), and

 Peer-reviewed journal artic les and government reports.Abt Associates Inc., May 26, 2010 Additional Input on Data Sources and Methodology for Benefits Analyses 3 Abt Associates has already compiled some of the n ecessary information. These da tabases will provide us with information on uptake via various routes of exposure, metabolism, and retention, including any special considerations of age, gender, or health st atus. We will carefully evaluate dose-response data in terms of the relevance to the specific exposure scenario and population of interest.
We will use available dose-response data to quant itatively characterize the relationship between the amount of exposure to a substance and the extent of toxic injury or disease. Because the dose-response functions estimate the probability of effects for a give n dose level, we will use these functions to calculate the number of cases of injury, disease, or premature mo rtality that might occur in an exposed population under baseline conditions and under post-compliance s cenarios (using the changes in concentration as described in Section 1).

For contaminants believed to have a threshold belo w which adverse responses are unlikely to occur, we will use these threshold values (i.e., Reference Doses (RfDs)) in the anal ysis of human health risk. Lack of probabilistic dose-response functions limits the ability to quantify the non-cancer health benefits. For these pollutants, our analysis will focus on determini ng whether the affected population is at risk for developing adverse health effects by comparing the estimated exposure with the relevant RfD.


### 2.2 Exposure Assessment Exposure evaluation involves the assessment of the na ture and size of the population exposed to a substance or substances and the magnitude and dur ation of the exposure. The major components of exposure assessment are pathways and fate analysis and population analysis.

2.2.1 Identifying Exposure Pathways Potential exposure pathways of Steam Electric pollutants include:

 Consumption of contaminated fish;

 Ingestion of contaminated drinking water; and

 Exposure to contaminants in waters used recreationally (e.g., swimming).
In assessing the potential for exposure to Steam Electri c pollutants through contaminated drinking water, we will rely on EPA’s Maximum Contaminant Levels for Drinking Water (MCL) data. We will also assess whether drinking water technologies commonly used by drinking water treatment plants currently remove pollutants of concerns.

2.2.2 Exposed Population Analysis To identify the size and characteristics (e.g., age/sex distribution) and location of potentially exposed populations, we will rely on a wide range of data sources, depending on the exposure route.

Population exposed to Steam Electric pollutants via drinking water Populations potentially exposed to Steam Electric pollutants include populations served by surface water intakes located downstream from Steam Electric di scharges and populations relying on groundwater from the affected aquifers (including public and private wells).

 Populations served by surface water intak es affected by Steam Electric discharges . To identify population exposed to Steam Electric c ontaminant via drinking water, we will identify the location of any drinking water intakes in th e initial and downstream reaches where pollutant concentrations were calculated (see Section 1). Fo r this analysis, we will overlay the identified NHD Plus stream segments over the Drinking wate r intake point file from EPA’s Reach Address Database (RAD). The exposed population for each combination of discharging facility and drinking water intake is the general population ser ved by the drinking water system for which theAbt Associates Inc., May 26, 2010 Additional Input on Data Sources and Methodology for Benefits Analyses 4 drinking water intake was identified. EPA’s Sa fe Drinking Water Information System (SDWIS) provides information on populations ser ved by drinking water intakes.

 Populations served by groundwater intakes (public wells) . To identify populations potentially exposed to Steam Electric contaminants via gr oundwater drinking water sources we will use information of the affected groundwater aquifers provided by the project engineers (see Section 1) and overlay this information with the we ll public well location from EPA’s SDWIS, which also provides information on population served by public wells.

 Populations served by ground water intakes (private wells) . We will overlay Census Block data with the geographic boundaries of the a ffected aquifer to determine the number of households potentially exposed to Steam Electric pollutant via private wells.

Populations exposed to Steam Electric pollutants via fish consumption The population exposed to contaminated fish and thus expected to benefit from reduced discharges includes recreational anglers who fish the affect ed reaches, as well as members of these anglers' households. We will use the National Survey of Fish ing, Hunting, and Wildlife-Associated Recreation (U.S. Department of the Interior 2006) data to iden tify the total number of recreational anglers in a given state and a typical distance which recreational angler s would travel to fish. We will apportion total state anglers to the areas located within the identified trav el distance from the affected reach based on the ratio of total population residing within the given distance from the affected reach to total state population. We will use the U.S. Census data to identify total populati on within the relevant areas and at the state level. Family members will be included in the exposed population estimates. Information on the average household size is readily available for the U.S. Census data.
Finally, we will use EPA’s listing of fish and wildlife advisory to identify affected reaches that have fish advisories in place. We will adjust the estimated angler populations for the presence of fish advisories assuming that some proportion of anglers would adhere to the advisory and not fish those reaches. We will use information from the published literature to determine the fraction of anglers who may change their behavior in response to fish consumption advisories.



### 2.3 Quantification of Human Health Benefits In this step, we will combine exposure data with dose-response information to estimate the risks to affected human populations and changes in the baselin e risks that will result from the Steam Electric ELG regulations.

2.3.1 Cancer Effects For human cancer risk assessment, we will combine cancer potency factors or unit risks with the estimated pollutant concentrations to estimate cha nges in individual health risks. We will estimate population risks based on expected case or average exposure scenarios and the size of the exposed population. To characterize average exposure scenarios we propose to use the Exposure Factors Handbook (1997) and other data sources, including the Estimated Per Capita Water Ingestion in the United States (EPA, 2004) and the Methodology for Deriving Ambient Water Quality Criteria for the Protection of Human Health (EPA, 2000a). We will consult additional data sources such as published literature, as necessary. The aggregate population ri sks for carcinogens will be characterized by the number of cancer cases under the baseline and post co mpliance scenarios. The expected benefits from reducing discharges of Steam Electric pollutant is th e difference in the number of cancer cases between the baseline and post-compliance scenarios.Abt Associates Inc., May 26, 2010 Additional Input on Data Sources and Methodology for Benefits Analyses 5 2.3.2 Non-cancer Effects

Adult population For selected non-carcinogenic contaminants with dose -response information (e.g., lead), cases of a variety of human health endpoints can be estimated in cluding the number of hypertension cases from lead exposure, premature mortality, incidence of coronary heart diseases, etc. For th ese analyses, the analytic steps and data sources are the same as in the analys is of cancer effects. For non-carcinogens, for which dose-response data are not available we will compare the relevant RfDs with the estimated exposure to Steam Electric pollutants and determine whether the a ffected population is at risk for developing adverse health effects. The aggregate population risks for non- carcinogens will be characterized by the number of people exposed above the RfD. The expected benef its from reducing Steam Elect ric pollutant discharges is the difference in the number of people exposed above RfD between the baseline and post-compliance scenarios.

Children The analysis of benefits to children from reduced exposure to lead will rely on EPA’s Integrated Exposure, Uptake, and Biokinetics (IEUBK) Model for Lead in Children (IEUBKwin v1.1 build 11, February 2010). The IEUBK model is used to predic t the blood lead (PbB) concentration for children exposed within each reach affected by lead discharges from the Steam Electric facilities. The output from the IEUBK model will be combined with a dose-res ponse relationship between PbB and IQ decrements from published literature (e.g., Schwar tz, 1994) and the estimated numbe r of exposed children to obtain the total change in the number of IQ points fo r the affected population. The output from the IEUBK model can also be used to estimate the number of ch ildren with IQs less than 70 and whose PbB is greater than 20 μ g/dL who would require compensatory education. The number of children in the affected population (e.g., recreational angler households or po pulations served by the affected drinking water intakes) will be estimated using the U.S. Census data.

2.3.3 Exceedance of Human Health WQC Finally, we will estimate the occurrence of pollutant concentrations in affected waterways that exceed human health-based WQC by comparing human heal th-based WQC values with the estimate in-stream concentrations of Steam Electric pollutants. This anal ysis provides a measure of benefits in terms of the difference of the number of discharge reaches exceed ing health-based WQC for regulated pollutants due to Steam Electric activities under the baseline and post-compliance scenario. Human health based WQC will be obtained from EPA’s National Recommended WQC.



### 2.4 Monetization of Human Health Benefits

2.4.1 Value of Health Benefits to Adults
To monetize human health benefits from avoided cancer cases we will use the estimate of the value of a statistical life saved recommended in the Guidelines for Preparing Economic Analysis (U.S. EPA, 2008). For steam electric pollutants for which dose-response functions are available and the number of avoided disease cases can be estimated, we will estimate the m onetary values of avoiding non-cancer effects using either the cost of illness (COI) approach or WTP va lues to avoid specific diseases. To estimate COI for the estimated health endpoints, we will use EPA ’s Cost of Illness Handbook (U.S. EPA, 2001). WTP values to avoid specific diseases will be obt ained from published economic literature.

2.4.2 Value of Health Benefits to Children We will calculate monetary values for avoided neur ological and cognitive damages based on the impact of an additional IQ point on an individual’s future earnings and the cost of compensatory education for children with learning disabilities. To monetize IQ lo ss effects we will first obtain information on theAbt Associates Inc., May 26, 2010 Additional Input on Data Sources and Methodology for Benefits Analyses 6 effects of IQ on earnings (e.g., Salkever (1995)) fro m published literature. We will then combine the estimate of percent wage loss per IQ point with the value of lifetime earnings per person to estimate the value of an IQ point. Data on money income for the U.S. population is available from the U.S. Census Bureau. The monetary value of benefits to childre n from reduction in IQ losses under the post-compliance scenario is a product of the estimated monetary value of an IQ point and the estimated number of avoided losses in IQ points.
In addition, we will estimate the avoided cost of co mpensatory education for children with IQs less than 70 and whose PbB is greater than 20 μ g/dL. We will use information compiled for the Department of Education's Office of Special Education Programs to obtain estimates of special education costs for children suffering low-level cognitive damage who rema in in regular class rooms. We will use this information in combination with the estimated reducti on in the number of children with IQs less than 70 and whose PbB is greater than 20 μ g/dL under the post-compliance scenario to estimate the avoided cost of compensatory education.


### 3 Ecological Benefits
In this analysis, we will estimate ecological bene fits from reducing discharges of Steam Electric pollutants to surface waters. Pollutants of concern include, but are not limited to, selenium, arsenic, mercury, chlorides and total dissolved solids (TDS), nitrogen and phosphorus, pH , and biological oxygen demand (BOD). The ecological evaluation endpoints for this analysis potentially include reduction in the number of reach miles exceeding EPA’s WQC for protec tion of aquatic life, changes in the water quality index (WQI) between the baseline and post-complia nces scenarios, and reduction in the number of protected species or critical habitat areas adversely aff ected by discharges of steam electric pollutants. We will also explore other ecological assessment endpoi nts as needed. Quantitative estimates of ecological improvements such as changes in WQI will be used in conjunction with benefit valuation functions to assess total willingness to pay (WTP) for water quality improvements resulting from the Steam Electric regulations.


### 3.1 Analysis of Ecological Improvements

3.1.1 Analysis of Ambient (In-Stream) Concentrations Relative to Aquatic Life WQC Limits In this analysis, we will rely on the EPA’s Nati onal Recommended WQC for protection of aquatic life. Pollutant concentrations in excess of WQC limits i ndicate a significant detriment to the aquatic species habitat. Therefore, we will evaluate potential impact s to aquatic life from the Steam Electric regulation by comparing the estimated in-stream concentrations of Steam Electric pollutants with WQC limits for protection of aquatic species under the baseline and post-compliance scenario. Eliminating these exceedances as the result of the St eam Electric regulation will significantly improve aquatic species habitat and thus provide a quantita tive measure of ecological benefits. Ecological improvements will be expressed in terms of reduction in reach miles wher e in-stream concentrations of Steam Electric pollutants no longer exceed aquatic-life WQC under the post-compliance scenario.

3.1.2 Analysis of Improvements in Ecological Services Provided by the Affected Waterbodies To analyze changes in ecological improvements pr ovided by the affected waterbodies, we will use a Water Quality Index (WQI) to link water quality measu rements to water use categories such as aquatic life support, fishing, swimming, and etc. Water quality indices provide a means of integrating measurements of various water quality parameters into a single number to facilitate communication with the general public and policy makers. Calculated WQ I values can be classified into suitable water use categories such as drinking, swimming, game fishing, rough fishing and boating to provide a link betweenAbt Associates Inc., May 26, 2010 Additional Input on Data Sources and Methodology for Benefits Analyses 7 water quality improvements, ecological services provide d by a waterbody (e.g., aquatic life support or recreation) and non-market benef its derived from these improvements. 1

. The WQI version EPA used in the analysis of th e C&D Effluent Limitations Guidelines includes six parameters: TSS, nitrogen, phosphorus, BOD, DO, and pathogens. To analyze water quality improvements from Steam Electric regulations we pr opose to modify the WQI to include TDS using information from the available literature (Abt A ssociates 2009). The WQI currently does not account for changes in ambient concentrations of toxic pollutants (i.e., selenium, arsenic, mercury, chlorides), but we would propose to explore incorporating these parame ters into the WQI definition to provide a more comprehensive tool for evaluating the impacts of this regulation.
To quantify ecological benefits of water quality impr ovements expected from the regulation, we will use the estimated ambient concentrations (see Section 1) from the water quality model and information on WQI parameter transformation and aggregation (U.S . EPA 2009; Abt Associates 2009) to calculate the WQI for each policy option. The difference in WQ I between baseline conditions and a given policy option (hereafter denoted as  WQI) is a measure of the change in water quality attributable to the policy option.

3.1.3 Threatened and Endangered (T&E) Species impacts The number of T&E species potentially affected by e ach facility can be determined by using data on species ranges (e.g., from the US Fish and W ildlife Service and NatureServe Explorer ( www.natureserve.org/explorer) ) and overlaying this information with the geographic areas affected by Steam Electric pollutant discharges. Potential for impact occurs if a facility’s discharge is located within the geographic range of vulnerable life history stag es for T&E species. Geographic overlap between life history stages and aquatic habitat areas affected by steam electric facilities can be calculated using Geographical Information System (GIS) software.
To assess potential for adverse impacts on T&E we will compare the estimated in-stream concentrations for pollutants of concern in the critical habitat area s with EPA’s WQC for protection of aquatic species, if, no WQC exists for a given pollutant of concern, to other aquatic toxicity data corresponding to lethal responses (reported as the LC50) and sub-lethal respon ses, such as changes in reproduction or growth in the affected organisms. The sub-lethal responses can be reported in various ways, including EC5 or EC50 (i.e., the concentration at which 5% or 50% of the t est organisms show a significant sub-lethal response), NOEC (No Observed Effect Concentration), LOEC (L owest Observed Effect Concentration), or MATC (Maximum Allowable Toxicant Concentration). The ou tput from this analysis is the number of T&E species and the number of reach miles corresponding to critical habitat that are no longer adversely affected by Steam Electric pollutant discharges.
If feasible, further analysis can be performed using AQUATOX (U.S. EPA 2009) or similar models to estimate changes in risk to select ed aquatic species or affected critical habitat/aquatic ecosystems from exposure to steam electric pollutants of concer n. The approach may involve developing a few representative case studies and extrapolating the findings to the broader set of affected ecosystems. The output of this analysis is the change in the affect ed species population, aquatic community structure, or other relevant ecological metrics due to reducing Steam Electric pollutant discharges.

1 The WQI methodology and its application to quantification of improvements in ecological services resulting from water quality improvements in the waterbodi es affected by construction site discharges is described in detail in Chapter 10 of the Environmental Assessment and Benefits of the Construction and Development Effluent Limitations Guidelines (U.S. EPA 2009) and a memorandum entitled “Methodology Summary and Litera ture Review of Water Quality Indices in Support of National Modeling Efforts for the Valuation of Impr oved Surface Water Quality” (Abt Associates, 2009)Abt Associates Inc., May 26, 2010 Additional Input on Data Sources and Methodology for Benefits Analyses 8 

### 3.2 Monetization of Ecological Benefits To estimate a monetary value of ecological benef its of water quality improvements resulting from the Steam Electric regulation, we will use a benefit tr ansfer approach based on a meta-analysis of surface water valuation studies. The technical details involve d in the estimation of original meta-analyses are presented in U.S. EPA (2009) as well as in sources such as Johnston et al. (2005), Bateman and Jones (2003), Shrestha et al. (2007), Rosenberger and Phipps (2007). This benefit function allows us to forecast total WTP for water quality improvements based on the est imated baseline WQI, the predicted change in WQI (  WQI) representing a resource change from the St eam Electric regulation (U.S. EPA 2009). To estimate total WTP for surface water quality improveme nts from the Steam Electric regulation, we will combine per household WTP with data on the population residing in the vicinity of the affected water bodies (e.g., within a typical travel distance for one da y recreation trips). Census Block data will provide information on the number of households residing in the affected areas. Depending on availability of relevant surface water valuation studies, we may be able to revise the benefit function to include variables representing changes in ambient concentrations of toxic pol lutants; this would be pursued if we are able to adjust the WQI to incorporate parameters repr esenting toxic pollutants (see Section 3.1.2).



### 4 Other Benefits
4.1 Improved Protection of Groundwater Resources If baseline and post-compliance concentrations of Steam Electric pollutants in the affected aquifers are available (see Section 1), we will estimate the moneta ry value of improved groun dwater protection using a benefit transfer approach based on a meta-analysis of groundwater valuation st udies (e.g., Besedin et al. 2000). This benefit function allows us to calculate total WTP for improvements in groundwater protection based on the estimated change in pollutant concen trations in groundwater and other resource and demographic variables. For this analysis, we will review recent groundwater valuation studies and update the 2000 meta-analysis (Besedin et al.) as needed. We will also review and assess applicability of other published meta-analyses of groundw ater valuation studies. To estimate total WTP for improved groundwater protection resulting from the Steam Elect ric regulation we will combine per household WTP with data on population served by drinking water wells affected by Steam Electric discharges (see Section 2.2 for detail on estimating affected population).


### 4.2 Increased Property Values We will explore a feasibility of estimating chang es in property values from water quality improvements resulting from the Steam Electric regulation, contin gent on a link being established between the Steam Electric regulation and aesthetic or other improvements. In this analysis, we will rely on the review hedonic studies currently underway for the Urban Stormwater Runoff regulation; output from the water quality model discussed in Section 1; and the numbe r of potentially affected housing units. If water quality measures included in hedonic studies cannot be linked to quantified water quality effects used in this analysis (e.g., changes in pollutant concentra tions or changes in WQI) we will assess property values qualitatively.


### 4.3 Reduced Cost of Drinking Water Treatment We will review information on typi cal drinking water treatment processes used for removal of Steam Electric pollutants (e.g., addition of chemicals or use of treatment technology), provided that the pollutants of concern impose an incremental treatme nt costs, and assess feasibility of estimating cost savings from improved quality of sour ce water. Data requirements for this analysis include changes in Steam Electric pollutant concentrations in the s ource water provided in the output from the water quality model; drinking water treatment volume provided by SDWIS, and per unit cost of drinking water treatment to be obtained from publishe d literature or government reports.Abt Associates Inc., May 26, 2010 Additional Input on Data Sources and Methodology for Benefits Analyses 9 

### 5 References
Bateman, I.J. and A.P. Jones. 2003. Contrasting Conventional with Multi-Level Modeling Approaches to Meta-Analysis: Expectation Consistenc y in U.K. Woodland Recreation Values . Land Economics 79(2): 235-258.
Besedin E., S. Smith, D. Widawsky, and L. Akeson. 2000. Willingness to Pay for Groundwater Cleanup and Protection: a Meta-analysis with Application to State Pesticide Management Plans . Presented at the annual meeting of Southern Economic Asso ciation. Alexandria, VA. November 2000.
Johnston, R.J., E.Y. Besedin, R. Iovanna, C.J. Miller, R.F. Wardwell and M.H. Ranson. 2005. “Systematic Variation in Willingness to Pay for Aqua tic Resource Improvements and Implications for Benefit Transfer: A Meta-Analysis.” Canadian J ournal of Agricultural Economics 53(2-3):221-248.
Rosenberger, R.S. and T.T. Phipps. 2007. “Co rrespondence and Convergence in Benefit Transfer Accuracy: Meta-Analytic Review of the Litera ture.” In S. Navrud and R. Ready (eds.), Environmental Value Transfer: Issues and Methods. Dordrecht, The Netherlands: Springer. pp.23-43.
Salkever, D. S. 1995. “Updated Estimates of Earn ings Benefits from Reduced Exposure of Children to Environmental Lead.” Environmental Research 70: 1-6. Schwartz, J. 1994. “Low-level Lead Exposure and Children’s IQ: A Meta-analysis and Search for a Threshold.” Environmental Research 65: 42-55. Shrestha, R., R. Rosenberger, and J. Loomis. 2007. Be nefit Transfer Using Meta-Analysis in Recreation Economic Valuation, in Benefit Transfer Accuracy: Meta-Analytic Review of the Literature.” In S. Navrud and R. Ready (eds.), Environmental Value Transfer: Issues and Methods. Dordrecht, The Netherlands: Springer. pp.161-177.

..Abt Associates Inc., January 10, 2013 Contract EP-C-07-023, Assignment 5-17, QAPP APPENDIX C

Abt Associates Memorandum – Steam Electric Questionnaire Part I Responses: Database Description and Preliminary Quality Assurance ReviewYes, tha 

## Environment and Resources 55 Wheeler Street, Cambridge, MA  Tel: 617 492-7100  www.abtassociates.com

Date February 20, 2011

To James Covington

From Robert Chew, Tatiana Meln ikova, and Isabelle Morin

Subject Steam Electric Questionnaire Part I Resp onses: Database Description (WA 3-17, Task 6)



### 1 Database Overview Part I data are being delivered to EPA as an Access database.
The relational database includes all Part I data provi ded by respondents in individual Excel workbooks, reviewed and cleaned as necessary. Note that the data base contains data from to the Steam Electric (SE) survey only; it does not include supplementary data obtained from the Energy Information Administration (EIA) or from the Federal Energy Regulatory Co mmission (FERC); compilation of these separate data sets is underway and will supplement the SE Part I database.
While Abt Associates compiled a database with all responses received, the version provided to EPA contains data only for the in-scope facilities, i.e., facilities that did not get eliminated from (or kicked-out of) the questionnaire based on information provided in Part A (as determined by ERG). Accordingly, this database contains information about 684 in-scope SE facilities. Note that 9 of these in-scope facilities did not provide Part I data as agreed to with EPA afte r discussing their special circumstances. While these 9 facilities are included in the database, data fields are largely blank.
Data are organized by entity level (e.g., plant, immedi ate owner, ultimate owner, unit) and by type of information (general vs. annual). Table 1 below summarizes the primary data tables while Figure 1 illustrates the relationships between these tables. Th e design of each table (which can be seen in “Design View” in Access) provides the characteristics of each fiel d, namely the data type, units of measurement if applicable, and a description which incl udes the reference to the relevant Part I question or requested data item. Fields added by Abt Associates for quality assu rance or documentation purposes are also described.

Table 1: Summary of Primary Data Tables. Fields listed in the “Unique Index” column indicate combinations that represent unique entries in each table.

Table Unique Index Questionnaire Section and Table Description DTbl_Plant_List Plant ID Contains tracking data on plants who returned a questionnaire. DTbl_Plant_General Plant ID Part I, Section 4 Contains general data for each SE plant. DTbl_Plant_Annual Plant ID; Year Part I, Section 4 Contains annual data for each SE plant, by year. 

# memorandumAbt Associates Inc., February 20, 2011 Preliminary QA Procedures Steam Electric Part I 2 Table Unique Index Questionnaire Section and Table Description DTbl_Plant_AncillaryInfo Plant ID Part A Contains data obtained from Part A used for QA purposes (EIA ID). The table also includes corrections Abt Associates made to the plant EIA ID following our review of the EIA data. DTbl_ImmediateParent_General Plant ID; IParent ID Part I, Sections 1 and 2 Contains general data for each immediate owner of a SE plant. DTbl_ImmediateParent_Annual Plant ID; IParent ID; Year Part I, Section 1 and 2 Contains annual data for each immediate owner of a SE plant, by year. DTbl_UltimateParent_Gener al Plant ID; IParent ID; UParent Name Part I, Section 3 Contains general data for each ultimate owner of a SE plant (by immediate owner). DTbl_UltimateParent_Ann ual Plant ID; IParent ID; UParent Name; Year Part I, Section 3 Contains annual data for each ultimate owner of a SE plant, by immediate owner and year. RTbl_UltimateParentCies UParentName Part I, Section 3 Provides a consolidated list of ultimate parents for SE plants, based on Dtbl_UltimateParent_General RTbl_UltimateParentCies _Annual UParentName; Year Part I, Section 3 Provides consolidated annual data on ultimate parents for SE plants, based on reconciliation of DTbl_UltimateParent_Annual and targeted data collection DTbl_GenUnit_General Plant ID; GenUnit ID; Part I, Section 5 Contains data relevant to each SE generating unit within the plant. DTbl_GenUnit_Annual Plant ID; GenUnit ID; Part I, Section 5 Contains annual data relevant to each SE generating unit within the plant, by year. DTbl_Comments Plant ID Part I, Comments Contains comments on Part I.Abt Associates Inc., February 20, 2011 Preliminary QA Procedures Steam Electric Part I 3 Figure 1: Relationship between Primary Data Tables



### 2 Data Coding In general values entered in each field are self-explan atory, but certain entries have specific meaning:  Blank : Indicates a value not provided by the responde nt, either because the information does not apply (e.g., as determined by the questionnaire skip pattern or by a response to another item) or because no information was availabl e at the requested level of detail. Note that in this second case, Abt Associates plans to impute values when conducting our analyses based on other information provided in the SE questionnaire (e.g., estimating plant- level data based on immediate parent-level data) or other sources (e.g., EIA). Blank entries are distinct from “0” which indicate when the respondent specifica lly entered a 0 value in the Excel cell.

 -999 : Indicates a blank entry in a text field.

 No Answer : Indicates a missing entry in a text field. In several cases, we contacted the respondent to get the minimal amount of info rmation necessary to impute information (e.g., minimum information necessary to determine SBA size category) and are awaiting a response.

 Not Applicable : Entry is not applicable based on answ er provided in a separate field (e.g., facility does not perform non-generation related activities, description of such activities is therefore not applicable). 

### 3 Preliminary Quality Assurance Review A summary of our preliminary review of the data s ubmitted by respondents, organized by questionnaire section, is provided below.

List of Facilities We checked off the facility from the list of plants from which we exp ect to get data. We conducted the detailed review of the data reported only for the in-scope plants, i.e., plants that were not “kicked-out” of the questionnaire.Abt Associates Inc., February 20, 2011 Preliminary QA Procedures Steam Electric Part I 4 Comments As a first step in the series of QA activities, we reviewed the respondent Comments to identify replacement data. We made the appropriate correctio ns in the data tables (e.g., replacing actual negative values for “0” entries in Tables I-4 or I-5 for which formatting constraints did not allow for negative values to be entered).

Section 1: Immediate Parent Ec onomic and Financial Information Ownership Shares . Of 684 plants, 584 plants have a singl e immediate owner and 100 plants have multiple immediate parent firms. We calculated the total ownership shares reported in the table and made sure that the total added to 100 percent. In sever al instances, the respondents had entered a fraction instead of percentages (e.g., 0.8 instead of 80); we corrected those entries. Following our review, two plants have ownership shares that sum to greater than 100 percent (4857 and 7572). The survey respondent for plant 7572 provided the ownership shares of the plant’s steam elect ric units instead of the plant’s immediate parent firms. To determine th e immediate parent ownership shares, we used a capacity-weighted method similar to that outlined in the instruction of the Part I Section 2 of the survey. For plant 4857, we contacted the plant directly and received corrected percent ownership figures. Another 16 plants have ownership shares that do not sum to 100 percent (or close to 100 percent). These respondents generally provided information for the majority (or largest shar e) owner. One survey respondent (1429) provided an incorrect value; we re ceived the correct percent ownership figure after contacting the plant directly. This information will be used in conducting the parent-level analyses.
Revenue from electricity generation vs. total revenue . We generally verified that electricity generation revenue reported for each immediate parent was smalle r than the total revenue reported for that parent. Twenty-seven respondents entered to tal revenue slightly lower than revenue from electricity generation for one or more years. In cases where more detailed re venue information was provi ded in Section 2 of the questionnaire, we used the detailed data to corr ect the summary information in Section 1.
Total electricity sales and total employment . We generally confirmed that both fields contained nonzero values. We noted cases where either field was blank a nd, in the event that this information is needed to assess SBA size category (i.e., the immediate parent is also the ultimate parent), we collected the data from other sources such as other Part I responses for th e same entity or the entity’s annual report or SEC filing in order to determine the relevant SBA size category.

Section 2: Primary Immediate Parent Fi rm Economic and Financial Information In general, we confirmed that in case of multiple owners hip, the information provided in this section is for the primary (i.e., the majority) immediate parent of steam capacity at a given facility and/or checked how many entities filled out Section 2 (this included transcribing data from additional tabs inserted by the respondent for the additional entities). If the primary i mmediate parent is a FERC reporter, we checked if FERC Form 1 was attached as a supplemental form. If th e form was not attached (of the 273 plants with FERC reporting primary immediate parent, 160 did not provide FERC Form 1 as a supplemental attachment), a note was made so that the information can be incorporated in a latter stage of the data processing. Plants with FERC reporting primary imme diate parents – 273 out of 684 - were omitted from the quality assurance of Section 2 ; the information asked for in the Survey will be brought in from the FERC database. Consequently, the quali ty assurance results described for Section 2 are for 411 plants.

For Question I2-6 (Table I-3), we generally reviewed that the activities described in this Table, if any, are not associated with electricity generation, and that the “Revenue (000$)” reported here does not exceed “Total Revenue (000$)” reported in Section 1 . In cases where the entity reported no “other” activity, we specifically entered “not applicable” in the descr iption field to clarify instances where no entry is expected.Abt Associates Inc., February 20, 2011 Preliminary QA Procedures Steam Electric Part I 5 For Question I2-7 , we checked if any respondents (i.e., plants), were missing information for their primary immediate parent firms in the section. Of the 411 plants with a non-FERC reporting primary immediate parent, 78 plants were missing information for at least 1 of the 4 major Questions in this Section - balance sheet, cash flow, income statement, or sources of energy; 34 plants were missing information for all of these questions. To check responses to Question I2-8 (Table 1-4) , we performed the following quality assurance checks:  First, we checked how many respondents provided income statement information for the primary immediate parent. Out of 411 plants, 43 did not pr ovide this information. Consequently, the next quality assurance steps for this question were performed for the remaining 368 plants.

 We confirmed that “Total Revenue” is the sum of the three revenue values reported in this Table. We were able to make this comparison only for 286 plants: for 168 plants the values are equal and for 118 they are not. For the remaining 82 plants we were not able to make this comparison because of missing data: 77 plants did not report “Total Revenue” but reported itemized revenue values while 5 plants reported “T otal Revenue” but did not report the itemized revenue values.

 We then confirmed that “Other Revenue” values in Question I2-8 are the same as the “NonGeneration Revenue” values reported in Question I2-6 . This is the case for 213 plants. For the remaining 155 plants: 15 plants reported “Oth er Revenue” streams but did not include “NonGeneration Revenue” values, 9 plants reporte d “non-generation revenue” but not “other revenue” streams, 80 plants reported both numbe rs but had different values for each, and the remaining 51 plants did not report either value. “

 Further, we confirmed that “Revenue from electric power generation and sales” is equal to “Revenue from electricity gene ration (000$)” values reported in Question I1-1 . This is the case for 216 of 368 plants. Of the remaining 152 plants with different electric revenue values, 42 of did not report either “Revenue from electric power generation and sales” or “Revenue from electricity generation (000$)”.

 Additionally, we checked to see if the sum of the three revenue values from Question I2-8 equals to “Total Revenue” reported in Question I1-1 . This is the case for 224 plants. Of the remaining 144 plants with different values, 11 di d not report income statement revenue.

 Finally, we confirmed whether for the “Afte r-Tax Income” a given respondent reported Total Net Income or Net Operating Income. If “Afte r-Tax Income” is the difference between Total Revenue and Total Expenses reported in this table, then the income values reported are Total Net Income as opposed to Net Operating Income. Of 368 plants, 293 plants reported Total Net Income. Of the remaining 75 plants, 5 reporte d income values that differ from the calculated income value by less than 1 percent.
We performed no quality assurance activ ities to check information reported in Question I2-9 (Table 1-5)

. The quality assurance checks for Question I2-10 (Table 1-6) consisted mostly of making sure that specific cash flow items sum to their aggregated equivalents:  First, we checked how many respondents provi ded cash flow information for the primary immediate parent. Out of 411 plants, 38 did not pr ovide this information. Consequently, the next quality assurance steps for this question were performed for the remaining 373 plants.

 We checked to confirm that “Non-cash charges (credits) to income” was the sum of “Depreciation and depletion” and “Amortization of electricity generating plants". We could notAbt Associates Inc., February 20, 2011 Preliminary QA Procedures Steam Electric Part I 6 compare the reported and calculated values for 74 plants because of missing reported values. Of the remaining 299 plants, 18 plants have equal values; 16 of these plants reported zero values for all three items. For 217 of the 281 plants w ith unequal reported and calculated values, the difference exceeds 1 percent.

 We also checked to confirm that “Net cash provided by (used in) operating activities” is the sum of “Net income from operations”, “Non-cash charge s (credits) to income”, and the other three items in this Table. We could not compare va lues for 24 plants because the survey respondent did not report enough information. Of the remain ing 349 plants, 13 plants had equal values; 11 of these plants reported zero values for all thr ee items. For 331 of the 336 plants with unequal values, the difference exceeds 1 percent.

 Finally, we checked if the reported “Net incr ease/decrease in cash and cash equivalents” is the sum of reported “Cash flow from operating activ ities”, “Cash flow from investing activities”, and “Cash flow from financing activities”. For 29 plants we could not compare the two because of missing reported values. Of the remaini ng 344 plants, 265 plants had equal values and 79 plants did not. For 66 of the 79 plants that did not, the difference exceeds 1 percent.
For many plants, the reported total values exceed the calculated sum of the individual cash flow items in the last three quality assurance checks. Consequently, it is possible that the reason why specific cash flow items did not sum to its reported aggregate equiva lent is because the firms’ accounting framework is different from the form that was provided in the surv ey; additional items that were not included in the survey’s balance sheet might have contributed to the higher than expected aggregated values.
To check information reported for Question I2-12 (Table 1-8) , we looked at various aspects of the final disposition of the electricity produced:

 First, we checked how many respondents provided final disposition of electricity information for the primary immediate parent. Of 411 plants, 65 di d not provide this information. Consequently, the next quality assurance steps for this questi on were performed for the remaining 346 plants.

 Next, we confirmed that “Total uses of electric energy” is the sum of the items in this Table. We could not compare the two values for 28 plan ts because of missing information. Of the remaining 318 plants, the summed values equaled “T otal uses of electric energy” for 182 plants and were not equal for 136 plants.

 Next, we confirmed that “Total uses of electric energy” is less than or equal to the “Total Electricity Sales (MWh)” reported in Question I1-1 (Table I-1) . We could not compare values for 23 plants because the survey respondent did not report enough information. Of the remaining 323 plants, “Total uses of electric energy” is less than “Total Electricity Sales (MWh)” for 71 plants, is equal for 75 plants, and is greater for 177 plants.

 We checked if the sum of “Sales for resale, “Sal es to end users”, and “Electric energy furnished without charge” is equal to the “Total Electricity Sales (MWh)” reported in Question I1-1 (Table I-1) . This is true for 199 plants. For 40 ad 107 of the remaining 147 plants, calculated values are greater and less then the reported “Total Electric ity Sales (MWh)” values, respectively; for 107 of 147 the absolute difference exceeds 1 percent.

 We also checked that the sum of “Revenue fro m sales for resale” and “Revenue from sales to end users” equals “Revenue from Electricity Generation” in Question I1-1 (“Revenue from Electricity Generation” may include capacity revenue, i.e., revenue for electricity never generated). For 4 plants we could not compare th e calculated and the reported values because of missing reported values. Of the remaining 342, 1 70 plants had equal values. Of the remainingAbt Associates Inc., February 20, 2011 Preliminary QA Procedures Steam Electric Part I 7 172 plants with unequal values, 85 have “Reve nue from Electricity Generation” values greater than the sum of “Revenue from sales for resale” and “Revenue from sales to end users” while 87 plants had “Revenue from Electricity Generati on” values less than the sum of “Revenue from sales for resale” and “Revenue from sales to end users”; for 135 of these 172 plants, the absolute percent difference exceeds 1 percent.

 Likewise, we also checked that the sum of “R evenue from sales for resale” and “Revenue from sales to end users” equals to “Revenue from electric power generation and sales” in Question I2- 8 (Table I-4) . For 11 plants we could not compare th e reported and calculated values because of missing reported values. Of the remaining 335 plants, 181 have equal reported and calculated values. Of the remaining 154 plants with une qual values, the reported “Revenue from electric power generation and sales” value is greater a nd less than the calculated sum for 85 and 69 plants, respectively; for 109 of the 154 plants the absolute difference exceeds 1 percent.

 Lastly, we confirmed that “disposition of electricity” does not exceed “sources of energy” reported in Question I2-11 (Table I-7) . This is true for 187 plants, i.e., the majority.

For Question I2-13 (Table 1-9) and Question I2-14 (Table 1-10) , we confirmed that the reported percentage values added up to 100 percent. This is the case for both questions for the majority of primary immediate parent firms. For 26 and 92 plants, percentage values reported for Question I2-13 and/or Question I2-14 , respectively, do not add up to 100 percent; for 22 plants, values reported for both Question I2-13 and Question I2-14 do not add up to 100 percent.

Section 3: Ultimate Parent Economic and Financial Information We performed two quality assurance checks for Question I3-2 (Table 1-11) :
 We first confirmed that the list of immedi ate parent firms (reported in column 1 of Table I-11 ) is the same as the one in Question I1-1 (Table I-1) . Of the 684 plants, 55 reported a different list of immediate parent firms. This resulted in 77 i mmediate parent firms - 18 are primary immediate and 59 secondary immediate parent firms - with no information.

 We then confirmed that the ultimate parent reported for each of the immediate parent in Table I11 is the majority owner by checking the reported ownership shares in column 4. For majority owners, 240 plants reported that the immediate pa rent is the same as the ultimate parent while 420 plants reported that the immediate parent a nd the ultimate parent are different entities. The last 24 plants did not provide an answer to this qu estion. Of the 420 plants that were different, all plants reported the ultimate parent’s percen t ownership of the immediate parent firm. Additionally, 51 of the 684 plants have non- majority immediate parents with corresponding ultimate parents. Twenty six of these plants did not report ultimate pa rent percent ownership while 27 of these plants did. Two plants overl apped and reported percent ownership for some ultimate parents but not for others.

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Section 4.1: Basic Plant Economic and Financial Information In general for all of Section 4 , if a given intermediate parent owns more than one facility, we tried to confirm (1) that information provided for each plant is consistent and (2) the totals for all plants are less than or equal to the values reported for the immediat e parent. Of the 684 plants in the survey, 11 plants 1 did not report any information for Section 4 . Consequently, the quality assu rance checks in this Section are for the 673 remaining plants.

1 Plant IDs 1061, 2548, 2569, 3701, 3917, 5647, 6592, 7264, 8676, 9686, and 9715.Abt Associates Inc., February 20, 2011 Preliminary QA Procedures Steam Electric Part I 8 For Question I4-1 and Question I4-2 (Table I-12) , we first checked if the requested information was provided. Only 16 plants did not answer these two Questions , leaving both blank. Of the 657 plants that answered both Questions, only 10 plants 2 reported fiscal year periods for Question I4-1 that would have resulted in less than 12 months per year; according to the Comments, these plants were not purchased or built in the middle of fiscal year. Lastly, we check ed to see if the fiscal year period reported in Question I4-1 is the same as the calendar year. Of 657 plants, 583 plants have a fiscal year period that coincides with the calendar year, i.e., a vast majority.

For Question I4-3 (Table 1-13), we checked if the answers provided he re were consistent with those in Question I2-5 . More specifically, we checked to see if reve nue streams not associated with electricity generation are reported for both, plant and its imme diate parent. Of 673 plants, 20 did not answer Question I4-3 . Of the remaining 653 plants, 498 plants did not report revenue not associated with electricity generation at the plant level. Of the 155 plan ts that reported such revenue at the plant level, 15 did not report it at the immediate parent level.

We checked if the answers to Question I4-4 (Table 1-13) are consistent with the responses to Question I2- 6 . Similar to the check performed for Question I4-3 we confirmed that the description of revenue generating activities match when going from plant to immediate parent level. This was not the case for 45 plants. When more than one activity is listed at both levels and the plant and immediate parent had a common activity listed, the entry was not flagged. Al so, we confirmed that activities described in this table were not associated with electricity generation. Indeed, all activities provided were confirmed not to be associated with the generation of electricity.

For Question I4-5 , we checked if activities described in Question I4-4 can be associated with specific units. No information was reported for Question I4-4 by 501 plants either because these respondents did not participate in revenue generati ng activities not associated with electricity generation (470 plants) or because they did not report the information (31 plants ). Of the remaining 172 plants, 45 plants said the revenue could be associated with a specific unit. Of th e remaining 127 plants that said that their revenue could not be attributed to specific generating units, 36 plants reported activities that usually can be attributed to specific units (ex: steam generation, ash sales, etc.) but were labeled as not being associated with a specific unit. We are unsure if these 36 plants labeled these activities as not being associated with a specific unit because they do not ha ve the monitoring capabilities to me asure revenue streams at the generating unit level or because of an error in completing the survey.
We performed the following quality assurance steps for Question I4-6 (Table 1-14) :
 First, we compared the reported unit IDs with unit IDs reported in the 2009 EIA-860 database. In the survey, there are 1,770 SE-Units. In the EIA database, there are 1,373 SE-Units for which the generator ID matches with the survey ge nerator ID. The remaining unidentified SE-Units may not have clear matches because of generator uni ts being mislabeled in the survey or because of different labeling conventions between the survey and the EIA database.

 Next, we confirmed that the units provided in this Table are indeed steam (EIA-860 database provides fuel type info). Of 1,373 using with matching unit IDs, 1,361 were identified as steam electric units.

 Lastly, we compared the total revenue and total co sts reported in this Table to revenue and costs reported in Question I2-8 (Table I-4) . For 669 of 673 plants we could not make this comparison

2 Plant IDs 369, 1324, 1429, 2240, 2825, 3369, 4591, 5983, 7168, and 7838.Abt Associates Inc., February 20, 2011 Preliminary QA Procedures Steam Electric Part I 9 because of missing reported values. For 3 of the 4 remaining plants, total revenue and total costs in this Table are less than or e qual to revenue and costs reported in Question I2-8.

For Question I4-7 (Table 1-15), we compared employment reported in this Table to that reported for Question I1-1 (Table I-1) . We were not able to make this comp arison for 53 of 673 plants because of missing immediate parent-level data. For 606 and 14 of the remaining 620 plants, employment reported in this Table is less than or equal to and less than employment reported for Question I1-1 , respectively.

For Question I4-8 (Table 1-16) we performed the followi ng quality assurance checks:

 We confirmed that the answer in the check box is consistent with the answer provided to Question I4-1 . While 590 plants reported that their fiscal year coincides with the calendar year (checked the box), 83 plants reported that it do es not. Of the 590 plants who checked the box, 7 respondents provided conflicting responses to these two Questions

.  We also confirmed that information in the Tabl e is provided if the check box is not checked. For the 83 plants that did not check the box, 5 plants did not provide information.

 Lastly, we confirmed that generation values repor ted in this Table do not exceed those reported in Question I2-11 (Table I-7) . For 26 plants of the 77 plants that did not check the box and did not provide information, values reported in Table I-16 exceed values reported in Table I-7 ; 10 of these 26 plants reported “zero” for “Total Sources of Electricity” in Table I-7

. We performed no quality assurance checks for Question I4-9 (Table 1-17)

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Section 4.2: Detailed Plan t Financial Information
For Question I4-10 (Table I-18) , we performed two quality assurance steps:

 If the check box is checked (i.e., the plant-level information is estimated), we checked if the methodology description is provided and reviewed the methodology ( Question I4-12 ). Of 673 plants, 73 plants did not report information in Table I-18 and 103 plants reported only zeroes. Of the remaining 497 plants, 285 plants did not check the box and provided plant-level balance sheet information while 212 checked the box and provided estimated values. Of the 212 plants with estimated balance sheet information, 12 6 respondents provided d escription of their own methodology; all estimation methods implem ented by the respondents are reasonable.

 In addition, we checked if information provided in Question I4-10 (Table I-18) is consistent with the information provided in Question I2-9 (Table I-5) . For 94 out of 673 plants, reported plantlevel assets/ liabilities are higher than the asset s/liabilities reported for the immediate parent firm.
We performed three QA checks for Question I4-11 (Table I-19) , the first two of which are similar to the ones performed for Question I4-10 :  First, if the check box is checked (i.e., the plant- level information is estimated), we checked if the methodology description is provid ed and reviewed the methodology (Question I4-12) . Of 673 plants, 159 did not provide information for th is section. Of the remaining 514 plants, 316 plants did not check the box and provided plan t-level information while 198 checked the box and provided estimated values; of these 198 pl ants, 76 provided their own methodology; all estimation methods implemented by th e respondents are reasonable.

 We also checked that information reported in th is Table is consistent with the information reported in Question I2-8 (Table I-4) . Generally, the values reported at the plant level are less than the values reported at the immediate parent level. Only 6 plants have revenues/costs higherAbt Associates Inc., February 20, 2011 Preliminary QA Procedures Steam Electric Part I 10 than their primary immediate parent; 1 of these 6 plants – plant 5183 – has multiple immediate parents.
 Finally, we confirmed that if “Other revenue” values are reported, the description of activities is the same as that reported in Question I4-4 . Of 673 plants, 221 plants did not report “Other revenue” values while 452 plants did (295 of th ese reported a value of zero). Of the 452 plants that reported “Other revenue” values, 304 plants reported “Not Applicable” or a related phrase (“NA”, “none”, “No Answer”, or “-999” ) for “Other revenue” description in Question I4-4 , 57 plants have the same or nearly the same descrip tion, and 91 plants have this section blank.
To complete our quality assurance of information provided in Section 4 , we confirmed that the cost values reported in Question I4-13 (Table I-20) are less than or equal to cost values reported in Question I4-11 (Table I-19) . This comparison was not possible for 88 plants because of missing values. To confirm this fr the remaining 585 plants, we summed all the cost values in Question I4-13 and compared them to the summed cost values in Question I4-11 . For 547 and 38 of these 585 plants, total expenses reported in Question I4-13 were less than or equal to and greater than those reported in Question I4-11 , respectively.

Section 5.1: Basic Steam Electric Generati ng Unit Economic and Financial Information Of 684 plants, 11 did not provide information for the entirety of Section 5 . The subsequent quality assurance of the data reported in Section 5 was performed for 673 plants. We performed two quality assurance checks for Question I5-1 (Table I-21):  We first compared generator IDs reported here ( as determined through cross reference with Part A of the Detailed Questionnaire) with those re ported in the 2009 EIA-860 database to confirm that these generators are indeed steam. Of th e 1,770 SE-Units present in Section 5, 1361 units were found in the EIA database as Steam Electric units. The remaining SE-Units in Section 5 that were not found in the EIA database ma y be missing because of generator units being mislabeled in the survey or because of different labeling conventions betw een the survey and the EIA database.

 In case of multiple ownership structure, we confir med that more than one owner was listed in the “Immediate parent firm(s) in 2002” column. Of 673 plants, 573 plants have a single immediate owner and 100 plants have multip le owners. Of those 100 plants, only 65 reported ownership information in the “Immediate parent firm(s) in 2002” column in Table I-21 while 35 plants did not report any ownership share information.

Section 5.2: Basic Steam Electric Generati ng Unit Economic and Financial Information We performed the following quality assurance steps for Question I5-2 (Table I-22) :
 We confirmed that generators, for whic h the information is reported in this Table , are indeed steam (see quality assurance discussion for Questions I5-1 and I4-6 ).

 We checked generator primary fuel source in th is Table against the EIA-860 database. We used the fuel source information from the 1,361 steam electric units where we had matching generator ID numbers between the survey and the EIA data base to develop a list of unique fuel sources used by each plant. We then compared this to the unique reported fuel sources for each plant in the survey. Of the 673 plants with reported Section 5 data, 617 plants reported fuel sources that were the same as those reported to EIA while 56 plants reported different fuel sources.

 We confirmed that the “Number of Days in Opera tion” is less than 365 (or 366 in 2008). This is true for all respondents.Abt Associates Inc., February 20, 2011 Preliminary QA Procedures Steam Electric Part I 11  Finally, we confirmed that “Gross Electricity Gene rated (MWh)” is greater than or equal to “Net Electricity Generated (MWh)” reported in this Ta ble. For 12 of 673 plants we were unable to make comparisons due to missing values. Of the remaining 661 plants, 651 and 10 reported “Gross Electricity Generated” values that are gr eater than or equal to and less than “Net Electricity Generated”, respectively.

Section 5.3: Planned and Forced Outages and Annual Operating Cost

For Question I5-3 (Table I-23) , we performed the following quality assurance steps:

 We first confirmed that the generating unit ID s are the same as in other Tables asking for generating unit-level information (i.e., Question I5-2 (Table I-22) ).

 We then confirmed that the sum of out-of-servi ce days provided here (hours/24) is consistent with the “Number of Days in Operation” provided in Question I5-2 (Table I-22) . The sum of the number of days provided in these two Tables should not exceed 365 days (or 366 days in 2008). For 337 of 673 plants the sum of the number of days in operation ( Table I-22 ) and the number of days of planned and forced outages ( Table I-23 ) does not exceed the total number of days in a year (i.e., 365/366) but for 336 plants it does. However, because the difference is very small for these 336 plants – approximately 1 percent – it is lik ely that this difference is due to rounding.

For Question I5-4 (Table I-24) , we performed the following QA checks:

 We confirmed that the sum of “Fuel Costs” a nd “O&M Costs” does not exceed “Total Costs”. This was the case for all facilities. For 171 of 673 plants, the “Total Costs” value exceeds the sum of “Fuel Costs” and “O&M Costs”, which means that the reported generating unit-level “Total Costs” values include other cost s in addition to fuel and O&M costs.

 We also confirmed that “Fuel Costs” reported in this Table equal to “Average Cost of Fuel per Unit of Fuel Burned” times “Quantity of Fuel Burned (Units)” reported in Question I5-2 (Table I-22) . None of the plants reported Fuel Costs that equaled exactly the calculated Fuel Costs; however, 410 of 673 plants reported “Fuel Cost s” values that are different from the calculated Fuel Cost values only by approximately 1 percent, suggesting a rounding error.

 Further, we confirmed that “Total Costs” and “Fuel Costs” reported in this Table do not exceed total and fuel costs reported in Question I4-11 (Table I-19) , respectively. Due to blank entries in both Question I5-4 and Question I4-11 , the cost relationships could not be determined for 341 of 673 plants. Of the remaining 332 plants, 94 have generating unit-level costs that do not exceed the plant-level costs..

 Finally, we confirmed that cost values reported here are not the same as those reported in Question I4-6 (Table I-14) (if these values are the same, the responded did not answer Question I4-6 correctly). This comparison was not done fo r 667 of 673 plants, because they did not answer the question. For only 1 of the remaining 6 plants, cost values reported for Question I5-4 are equal to those reported for and Question I4-6

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Owners of Mult iple Plants  In the case where the same owner is reported for di fferent plants, we compared data provided in Sections 1 through 3 to verify that descriptive informa tion are consistent across the plant
responses.
 When the same ultimate parent owner was reporte d for different plants, we consolidated these responses into a list of unique companies and cons olidated the data reported for ultimate parents by every plant they own to generate a consistent and complete set of ultimate parent-level data.Abt Associates Inc., February 20, 2011 Preliminary QA Procedures Steam Electric Part I 12 We are now doing the same for the data reported for immediate parents and will complete this step once all the FERC data are brought into the database.