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

QUALITY ASSURANCE PROJECT PLAN (QAPP) FOR: 

ECONOMIC IMPACT AND BENEFITS ANALYSIS FOR STEAM ELECTRIC RULEMAKING

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 Plan 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 analysis 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 publications 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 verification 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 ...................................................................................................... 17

 
Abt Associates Inc., January 10, 2013 Contract EP-C-07-023, Assignm

Changes to QAPP for Support of Work Assignment 5-17 under Contract EP-C-07-023 Revision 0 1 2 3 

Comments Received NA NA NA NA Delivered 9/8/2011 10/17/2011 05/23/2012 01/10/201Cover Page Cover Page 

Revised to reflect cwork assignment nuchange in Abt Assocontract-level QualAssurance Manage

1: Project Objectives, Organization, and Responsibilities 1.1: Project objective/goal 

Updated to reflect project objectives/goals as outlined in work assignment 4-17, including information pertinent to using survey data and conducting analyses. 

Revised to reflect pobjectives/goals as in work assignment 

1.2: Project requirements related to primary and secondary data 

Idem. 

Revised to reflect aneeds, notably benecategories. 

1.3: Training and competency requirements necessary for key project personnel 

Section added in its entirety. 

1.4: Role and responsibilities of project personnel 

Changes to reflect current project staffing/needs. Added more information on PQA’s role and QA process. 

Corrected minor typo in Section 1.4.2 

Changed Elaine Haemisegger to Michael Conti to reflect a change in QAM. 

Revised to reflect cAbt Associates’ conlevel Quality AssurManager. 

2: Acquisition and Use of Primary Data 2 Steam Electric Survey Section added in its entirety. Minor revisions to 

description of the s

3: Acquisition and Use of Secondary Data 3.1: Sources used to identify secondary data 

Consolidated contents of Sections 2.1 and 2.2 from the QAPP used for previous work assignment. Updated to reflect current project needs. 

Revised to reflect asecondary data and support analysis of benefit categories npreviously covered
Abt Associates Inc., January 10, 2013 Contract EP-C-07-023, Assignm

Changes to QAPP for Support of Work Assignment 5-17 under Contract EP-C-07-023 Revision 0 1 2 3 

Comments Received NA NA NA NA Delivered 9/8/2011 10/17/2011 05/23/2012 01/10/2013.2: Quality requirements of, and acceptance criteria for, secondary data 

Consolidated contents of Sections 2.3 and 2.4 from the QAPP used for previous work assignment. 

Revised to reflect asecondary data and support analysis of benefit categories npreviously covered

3.3: Data reduction, validation, and verification procedures and documentation 

Added more detailed information on internal review, data storage, and documentation processes. 

Corrected minor typo in Section 3.3.2 

4: Expected Work Products 4: Expected Work Products Updated to reflect current project needs. Changed Elaine Haemisegger to Michael Conti to reflect a change in QAM. Revised to note spe

reports. 

5: Acceptance by the EPA WAM 5: Acceptance by the EPA WAM 

Non-substantive changes to the wording. 
 

Abt Associates Inc., January 10, 2013 Contract 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 benefits of revisions to the Steam Electric Power Generating effluent 

limitations guidelines and standards (Steam Electric 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 and 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 review and collection of primary data to characterize 

the ownership structure and financial 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 only the current tasks outlined above, but also tasks 

conducted under the predecessor work assignments which have potential implications for the cost and 

benefit analyses. 

The economic impact analyses expected to be conducted 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 additional 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 that 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 Regulatory 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 sources subsequently identified or describe 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 Quality 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 regulatory 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 tailored 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 Contract 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 revisions 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 secondary 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 discharge characteristics. The 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 respective owners, and in evaluating the significance of 

compliance costs on regulated facilities and parent firms. 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 tests1

. 

In addition to using this primary 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 operating 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 will support the assessment of baseline operations 

and economic/financial performance for facilities subject 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 regulatory environment of, the electric 

power industry, generally. 

 Data on electricity prices, which may be affected 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 requirements on power generating facilities and general market 

conditions within the context of regional and national 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 achieved 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 location of each plant, type of receiving water body, 

name of the water body, and discharge characteristics. 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 this effort, we generally assume that the data are 

accurate and plan to perform only general review to ensure 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 Contract 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, impairment 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 Electric discharges (e.g., fisher population). 

 Data characterizing the changes in in-stream concentrations of discharged pollutants under each 

regulatory option determined as part of the Environmental Assessment or modeled using pollutant 

fate and transport models. 

 Data characterizing the human health effects of discharged pollutants (e.g., dose response 

functions) and the monetary value of avoiding these effects (e.g., cost of illness, willingness to 

pay). 

 As applicable, depending on the type of benefits 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 selection, 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, finance, engineering, or environmental science) and 

demonstrated expertise in conducting economic impact and benefit analyses to support EPA rulemaking. 

Relevant expertise of key personnel will include, for example: 

 Knowledge of the regulated industry (electric power generation); 

 Experience with developing analytic frameworks to quantify impacts of regulations on affected 

entities and/or with quantifying market and non-market benefits of regulations; and 

 Familiarity and demonstrated experience with implementation 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 Manager and lead economist working with Ms. Morin 

for the cost and economic impact analysis of revisions to the Steam Electric ELGs. Dr. Elena Besedin 

leads the environmental assessment and benefits analysis for the regulation. Other Abt Associates analysts 
 

Abt Associates Inc., January 10, 2013 Contract 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 regulatory analysis effort. The role of the PQA is to 

ensure that all data used in the project and the analyses based on these data will meet EPA project quality 

assurance requirements. As Abt Associates’ officer-level director of the EP-C-07-023 contract, Mr. Fisher 

is also responsible for the overall 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 from 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 distribution 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 (WAM), Ms. Morin serves as Abt Associates’ overall 

lead for the work assignment and is ultimately responsible for quality assurance. Ms. Morin will ensure 

that the methodologies, data, analyses, and work assignment 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 other key personnel named above will also be responsible 

for implementing the provisions of this QAPP in their respective areas of responsibility in the work 

assignment. 

In his capacity as PQA for the work assignment, Mr. Fisher 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, analyses, 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 from the technical review that cannot be resolved 

among the Abt Associates managers, and the work assignment PQA. 
 

Abt Associates Inc., January 10, 2013 Contract 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 coal and petroleum coke-fired power 

plants, and a statistical subset of oil-fired, gas-fired, and nuclear power plants. The questionnaire 

consisted of nine sections and collected 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 assignment, 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 Steam Electric survey database that may be used in 

conducting analyses of the cost impacts or benefits of the regulation. 

Table 1: Example data from Steam 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 database. The data are organized in indexed tables with 

relationships between the tables defined to ensure internal consistency and integrity of the data at the 

plant, owner, and unit level. 

The data cleaning and review steps included reviewing 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 Appendix 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 Contract EP-C-07-023, Assignment 5-17, QAPP 6 

 Standardizing owner records: For example, plants are associated to uniquely defined immediate 

owners and these immediate owners are associated 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 percent. 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 field 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 order 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 respondents 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 questionnaire, 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 were compiled for each owning entity identified as 

government to support classification of the entities 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 with this QAPP, any change to data provided by 

respondents will be flagged and documented with the reason for the change and the source of the new 

values. 

In cases where survey data are not available for a given 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 discussed in Section 3. Data imputation methods may 

entail, for example, using average values of data reported 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., allocating revenue to the plant in proportion to the 

quantity of electricity generated). 

A substantive share of the survey data was classified 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 reporting 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 Contract 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 potentially affected U.S. Census 

Potentially affected 

resources 

Drinking water intake locations EPA SDWIS database 

Environmental effects Ambient concentrations of pollutants of concern 

Changes in pollutant concentration in fish tissue 

Extent of geographical area 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 and 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 estimates 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 experts 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 Contract 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 federal government data sources include the Energy 

Information Administration (EIA) of the U.S. Department 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 Statistics, and the Bureau of Economic Analysis. All 

of these data are compiled by the relevant federal agencies and thus meet federal government data quality 

standards. 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. 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 may also rely on firm financial data that have been 

compiled and reduced by private entities, including data 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 services 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 sources are expected to include the U.S. Census Bureau 

population and household data, peer-reviewed literature on dose response functions, cost of illness, and 

willingness to pay for avoiding adverse health effects or environmental improvements, data from EPA’s 

SDWIS Safe Drinking Water Information System (SDWIS) on public water systems, outputs from EPA’s 

Integrated Exposure, Uptake, and Biokinetics (IEUBK) Model for Lead in Children model, the NMFS 

Marine Recreational Fishing Statistics Survey, the 2006 USFWS Annual Survey of Fishing, Hunting, and 

Wildlife-related recreation, the U.S. FWS’ Threatened 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 discharges, we will use loading estimates developed as 

part of the Environmental Assessment to model concentrations downstream from steam electric plant 

discharges using water quality models such as the Spatially Referenced Regressions on Watershed 

Attributes (SPARROW) or the Risk-Screening Environmental Indicators (RSEI) models. In addition, the 

benefit analysis will use Bureau of Economic Analysis data on economic indicators (e.g., GDP Deflator, 

Consumer Price Index) to adjust dollar values to a common dollar-year. These data sources are 

appropriate for this analysis based on their applicability (e.g., Consumer Price Index) to benefits analysis 

of revisions to the Steam Electric ELGs. 

Additional sources of secondary data are likely to include 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 database, Infotrieve’s ArticleFinder database, the 

Internet (which is frequently a good source of working papers and other documents that have not reached 

the stage of formal publication), and bibliographies or publications from government organizations. These 

data sources will be peer-reviewed, widely used and 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 Contract EP-C-07-023, Assignment 5-17, QAPP 9 

This Work Assignment includes a specific benefits literature 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 analyzing 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 Facilities Rule, to assess the total electricity market 

impact of regulatory requirements including the impact on in-scope facilities and the extended total 

market effect accounting for changes in capacity management, production levels and costs across all 

facilities, regardless of whether the facilities are directly 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 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; 

 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 Transport Rule, the Mercury and Air Toxics Standards, 

and the Clean Air Visibility Rule, as well as implementation 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, and Biokinetics (IEUBK) Model for Lead in Children 

(v1.1, 2010) in estimating the benefits of such changes. The model is a risk assessment tool for use in 

quantifying the effects of lead exposure on children. 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 ages 
 

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

six months through 84 months exposed to lead in these environmental media. Blood lead levels can then 

be combined with with a dose-response relationship 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 children with IQs less than 70 and whose PbB is greater 

than 20 μg/dL who would require compensatory education. Monetary values for avoided neurological and 

cognitive damages are 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. 

SPARROW 

If outputs from the environmental assessment suggest potential changes in nutrient loadings, we may use 

the USGS SPARROW model to estimate the resulting changes 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 Development (C&D) rule. The model uses statistical techniques to relate 

concentrations of total nitrogen and total phosphorus to major sources of nutrients and processes in stream 

reaches defined at the resolution of E2RF1. The USGS 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 for each receiving reach by the TN or TP loading 

reduction estimated in EPA’s engineering 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 steam electric pollutant loadings are input into the 

model (i.e., as offset to a generic point source variable defined in population terms as opposed to specific 

loading from individual facilities) and potential changes from the baseline period over which the model 

was calibrated. We deem the model appropriate to provide 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 component of the RSEI model to estimate the resulting 

changes in in-stream concentrations downstream from 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 Contract EP-C-07-023, Assignment 5-17, QAPP 11 

each plant. The published national model has been described 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 partitioning). The model may be most appropriate 

to provide screening-level insight into the potential 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 undergone 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 generated 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 data 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 separate 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 pollutants of concern in receiving waters and/or tissue. 

For each round of analysis, Abt Associates will document the environmental data used in estimating the 

benefits by noting clearly in the analytic files, the date the environmental data were generated and/or 

received. 

In some instances, Abt Associates may use outputs from the Environmental Assessment 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 original published sources or from sources of high scientific 

merit, as determined by expert judgment. As discussed above, Abt Associates selected the secondary data 

sources used for analyzing the cost and economic impacts and benefits of revisions to the Steam Electric 

ELGs because they are peer-reviewed, widely used and accepted in economic and policy analyses 

performed by EPA and other government and private organizations, and publicly available. These data 
 

Abt Associates Inc., January 10, 2013 Contract 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 identified 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 modeled 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 secondary sources arises, the managers for this work 

assignment, Ms. Morin, Ms. Melnikova, and Dr. Besedin, will evaluate candidate sources of this 

information for scientific strength and merit, and will ensure 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 any additional secondary data 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 procedures 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 these data in subset databases by characteristics of 

interest (e.g., by state and North American Electric 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 data set will be appropriately described. Thus, Abt 

Associates staff will include full bibliographic information with all collected publications and databases, 

including the source/link and date accessed for information 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 pertinent to cost and economic impact and 

environmental and economic benefits analyses as PDF files. Abt Associates staff will document and 

appropriately flag 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 analyses of the Steam 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 are proven to be in error and error reports have been 

submitted to the data system of origin; or (3) adjustments are necessary to ensure consistency within the 

analytical framework. 

We will document and appropriately flag 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 analyses of revisions to the Steam Electric ELGs. 
 

Abt Associates Inc., January 10, 2013 Contract EP-C-07-023, Assignment 5-17, QAPP 13 

3.3.2 Data validation and verification 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 appropriately 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 correctly processed/analyzed and interpreted; 

 Methodologies and assumptions are appropriate 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), different 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 individual categories to sum to the national total, we will 

verify that this is in fact the case and that no data are erroneously excluded. In cases where logic would 

suggest a direction to differences (e.g., values for Option A should be larger than those for Option B), we 

will verify that the expected relationship is met or that 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 processed. This will involve 

reviewing equations and/or conducting independent calculations to verify results. The Abt Associates 

WAM will designate a staff member, other than the individual 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 information” section with the following information: 

 Date a given file was created 

 Date of most recent modification/review 
 

Abt Associates Inc., January 10, 2013 Contract EP-C-07-023, Assignment 5-17, QAPP 14 

 General purpose of information/analysis contained in a given file 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 information/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 list 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, designated 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 analysis 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 management 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 ensure that they are reasonable and within the range of observed data. 

All written deliverables describing data, methodology, and analysis findings 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 discussion, proper citations and references, 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 exhibits with the results presented in text; 

 Conducting selected manual checks of analytic results presented in the report (e.g., making sure 

that individual values add up to totals); 

 Assessing whether results and their interpretation are consistent with the theory, existing 

literature and prior expectation; 

 Ensuring that a comprehensive list of assumptions is provided; 

 Confirming that limitations and uncertainty inherent 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 different 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 responsible for ensuring that the appropriate reviews have 

been conducted. 

When sending cost and economic impact and environmental 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 have taken place since the previous deliverable. A 

name of each deliverable file will include a date and a deliverable version in accordance with the 
 

Abt Associates Inc., January 10, 2013 Contract 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 assignment 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 have 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 deliverable, 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 submitting 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 decision making process. For example, the review may 

focus primarily on ensuring that assumptions and calculations 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 electronic 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 electronically in project folders with a structure 

designated by the Abt Associates managers for the 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 Associates has dedicated information technology (IT) staff responsible for 

the installation and maintenance of all hardware and software infrastructure. This includes automated 

daily backup of all data stored on networked resources. Key personnel assigned to this work assignment 

will work with the IT staff to ensure that data storage 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 and storage procedures for data that are declared 

Confidential Business Information (CBI). These procedures 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 example, specific folders containing project sensitive 

information (e.g., CBI data) are subject to additional restrictions for authorized project staff, with control 

administered by the project manager, Ms. Isabelle Morin. 

 
 

Abt Associates Inc., January 10, 2013 Contract 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 expected 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 frameworks 

 
 

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

4 Expected Work Products 

Abt Associates anticipates developing various products derived from this work, including: memoranda on 

topics specified in written technical direction from the EPA WAM; summaries of analysis and findings of 

cost and economic impact, environmental assessment, and benefits for alternative 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 analyses 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 final results, and limitations. Where appropriate, Abt 

Associates will include documentation of QAPP activities as an addendum to significant draft and final 

deliverables presenting data or analyses results. 

The final step in the quality assurance 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 revisions 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 this 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 the 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 resolving any quality assurance concerns. 

The Abt Associates assignment manager will allocate appropriate 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 will report on quality assurance activities in our monthly progress 

reports. All project deliverables will meet EPA’s standards 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 Disseminated 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 Associates 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 Guidelines 

 
Abt 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 Expected 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 develop national technology-based regulations for 

categories of industries that discharge pollutants directly to surface waters (effluent guidelines) or that 

discharge pollutants indirectly through sewage treatment plants (pretreatment standards). EPA is currently 

revising effluent limitation guidelines (ELGs) and standards 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 “primarily 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 employing 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(ies) 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 Electric ELGs and indicate which legal requirements the 

Agency would have to consider with respect to these analyses. The memorandum also identifies key data, 

analytic steps, and assumptions. Based on past experience with conducting cost and economic impact 

analyses in support of the Clean Water Act 316(b) Rules, which are also concerned with Steam Electric 

facilities, EPA would likely have to conduct the 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 the 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 capacity availability due to potential downtime of 

generating units for compliance technology installation 
Abt 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 from 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 Transfer 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. Additionally, this memorandum focuses primarily on economic 

impact analyses. While a cursory overview of the evaluation of benefits is included in the context of 

certain Executive Orders or for the analysis comparing 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 two general analysis frameworks: 

1. A cost and economic impact assessment reflecting baseline operating characteristics of in-scope 

facilities and with assignment of estimated compliance costs to those facilities. This analysis 

assumes no changes in those baseline operating characteristics – e.g., level of electricity 

generation and revenue – as a result of the requirements of the proposed regulatory options. This 

assessment, described in this section, includes four specific analyses: 

 A cost-to-revenue screening analysis to assess the 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 the 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 (“Market 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 operating 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 technology costs) with its operating revenue, and provides a 

screening-level assessment of the impact of regulatory 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 this 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 Integrated 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 closures and/or other types of economic impact on 

facilities expected to be subject to the regulatory options. 

2

 Guidelines for Preparing Economic Analyses. Report EPA 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 owners 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) Phase II Proposed Rule. The model would be 

appropriate for the purpose of the electric market analysis in support of revisions to the Steam Electric ELGs. 

6

 Run years are specified in the model 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 which 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 consistent analysis-year and dollar-year basis, all 

cost and revenue values will be brought to a given 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 facility-level costs and revenue and determine the number 

of instances in which facilities incurred costs in ranges of “less than one percent of revenue,” “between 

one and three percent of revenue,” 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 three percent thresholds. Consequently, to determine 

whether revisions to the Steam Electric ELGs will have 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 potential 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 impacts 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 will 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 compliance 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 these costs to parent entity revenue. This information 

is expected to be obtained through the Steam Electric survey currently being developed. 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) regulations, average values for each statistic – i.e., energy revenue and capacity revenue – 

over the data years, were calculated by setting aside values for years that are anomalously low, i.e., more than 30 percent 

below the 4-year average values. 

8

 NERC is responsible for the overall reliability, planning, and coordination of the power grids; it is organized into regional

reliability management organizations that are responsible for the overall coordination of bulk power policies that affect their

regions’ reliability and quality of service. 

9

 For the purpose of this analysis, a parent entity is the ultimate parent firm is the highest level domestic business entity in the 

facility’s ownership structure. A firm that is owned by another U.S. firm is not an ultimate domestic parent firm. On the 

other hand, a U.S. firm that is owned by a foreign 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 markers of potentially significant impact for this 

analysis. 

In the event that information on parent entity revenue 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 parent 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, restated, 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 facilities in terms of a number of parent-entities with 

costs exceeding one and three percent thresholds. 

In conducting a parent entity-level analysis for the 316(b) Phase II Proposed Rule, which applies to a 

similar set of Steam Electric facilities, EPA found that on average the entity-level compliance costs are 

low in comparison to the entity-level revenues, i.e., the majority of parent entities are expected to incur 

costs of less than one percent of revenues. Consequently, it was determined that parent entities that own 

more than one in-scope facility were not going to be disproportionately “penalized” as the result of the 

Rule. Given the fact that revisions to the Steam Electric ELGs will concern a similar set of facilities, it is 

likely that the same findings will apply, unless ELG compliance 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 impacts of the rule, we will evaluate the “Altman-z” score 

of parent firms. Altman-Z is a commonly cited predictor of bankruptcy and has been 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 ratios 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 before 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 associated with this EPA action will increase the rate of bankruptcies 

and/or affect the financial health of firms that own regulated facilities. Altman-z functions have been 

developed for different types of firms (privately-held 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-score, 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 electricity 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 refined to account for the share of the costs that are 

expected to be passed on to ratepayers by different 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 electricity 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 and 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 some NERC regions for some of the 316(b) regulatory 

options. This analysis very likely overstates the residential price impact because it does not account for 

adjustments to the dispatch of electric generating units given expected changes in electricity production 

costs due to the regulation. We are currently investigating an approach to adjust the estimated household 

sector impact to reflect expected market response in the production profile, and to reflect whether 

electricity generation prices, at the state level, continue 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 impacts 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 effects accounting for changes in unit dispatch and provides an 

alternative estimate of potential cost to residential consumers. However, the IPM 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 concerned with estimating the potential impact on annual 

electricity costs by household. We expect that the analysis will be performed at the level of a NERC 

region, which is appropriate given the structure and 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 household, the total quantity of residential sales 

in each NERC region is divided by the number of households in that region. For this analysis, we 

will assume that average electricity sales per household would remain the same a given 

compliance year. 

3⁄4 To assess the potential annual cost impact per household, 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 survey and from the EIA-861 database will be used in 

these calculations: 

3⁄4 Total electricity sales quantity (in MWh) as reported 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- and 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 economic 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 (residential, 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 household impact analysis described in Section 1.3, the methodology for assessing 

regulatory impact on 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. 

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 survey 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 compliance 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 given analysis year, by NERC region; 

3⁄4 Estimate the approximate average price impact per unit of electricity consumption by dividing 

total compliance costs by the projected total MWh of sales in a given analysis year by NERC 

region, from the Energy Information Administration’s Annual Energy Outlook (AEO); and 

3⁄4 Compare the estimated average price effect (in dollars 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 determination 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, EPA used ICF International’s Integrated Planning 

Model (IPM®), a comprehensive electricity market optimization 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 Steam Electric ELGs, EPA may also want to use IPM to 

assess cost and economic impacts based on an integrated market-response analysis, which IPM provides. 

If EPA judges this analysis as necessary for the Steam 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 reductions in electricity output at directly affected 

facilities – whether due to the temporary shutdown 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 assessing the impact of the 316(b) Phase II 

regulation in its analyses for the suspended 2004 Phase II Rule. At that time, EPA concluded that IPM represented the best 

choice for 316(b) rule analyses considering a number of factors: ability to receive and account for as inputs, the cost and 

operating effect specifications of the 316(b) regulation; ability to assess the impact of 316(b) 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 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 Electric 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 facilities 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 choice” 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 regulations (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 dynamic optimization algorithm, IPM is typically run 

only for a limited number of representative years (“run 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 operation 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 performed 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 the 

revised Steam Electric ELGs, compliance costs will be developed for treatment systems operated by inscope facilities. The information used to map generating 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 Steam Electric survey currently being developed. We 

will use this information to allocate compliance costs to the individual generating units owned by inscope facilities. In the event that this information cannot be obtained through this survey, facility-level 

costs can be allocated across all affected steam generating units using allocation factors based either on 

steam generating capacity from IPM or on boiler-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 useful 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 the 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/airmarkets/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-compliance – 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 all generating units at the plant. The model 

differentiates between existing capacity, new capacity 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 result 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 available capacity. The capacity price is the premium 

required to stimulate new market entrants to construct 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 plant 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 required 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, including 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 expenditures 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, and capital. Capital costs are associated with 

investment in new equipment, e.g., the replacement 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 post-compliance cases will provide 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 first year after promulgation in which all in-scope 

facilities would have achieved compliance. If installation 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 installation downtime. This secondary analysis will provide 
Abt Associates Inc., October 29, 2009 Economic/Financial Analyses for Revisions to the Steam Electric ELGs 11

insight into potential market-level effects of temporary 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 compliance costs assigned to each steam electric generating 

unit, which steam electric generating units are assigned compliance costs, whether compliance with the 

revised requirements will require installation downtime, and the overall electricity market interaction 

modeled by the IPM. As previously stated, whether this level of analysis is warranted will depend on the 

expected magnitude of compliance costs, both for individual plants and in aggregate across the industry. 

2 Assessing the Potential Impact on Small 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 substantial number of small entities” (SISNOSE). Small entities 

include small businesses, small organizations, and small governmental jurisdictions. Based on EPA’s past 

analyses of Steam Electric entities, we do not anticipate 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-level revenue for each small entity identified as owning 

in-scope facilities. To assess whether these parent entity-level costs could constitute a significant impact, 

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

2.1.1.1 Determining Whether Parent 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/operation 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 Rule, 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, municipal, and political subdivision entities: 

 Facilities owned by Federal and State governments 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 Natural Gas Distribution 500 Employees 

221310 Water Supply and Irrigation Systems Revenue of $7,000,000 

331315 Aluminum Sheet, Plate, and Foil Manufacturing 750 Employees 

524126 Direct Property and Casualty Insurance Carriers 1,500 Employees 

525990 Other Financial Vehicles 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 Facilities Revenue of $12,000,000 

611310 Colleges, Universities, and Professional 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 analysis. 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 the 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 size criterion. The appropriate SBA size metric 

for each parent entity will be obtained from the following sources: 

 Electricity output: For size determination based on electricity 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 Electric 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-year average revenue values reported for utilities 

in the EIA-861 database. When necessary, revenue values will be restated in dollars of a 

given analysis year using the Producer Price Index 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 incur a potentially significant impact 

substantial? 

and 
Abt 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 estimated to exceed one percent or three percent of 

entity-level revenue will be assessed 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 small 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 information 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 event where the data need to be estimated, we 

would adjust this estimate to account for potential 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 expect 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, the count of utilities that appear to be small entities on the basis 

of their utility-level electric power generation as reported in EIA-861 is likely to overstate the count of parent-level entities 

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 businesses at the parent level. (2) According to the SBA entity-size criteria, the 

determination of small entities for electric power facilities owned by municipalities and other political subdivisions should 

be based on population served instead of electric power generated. (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 generating 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 entities incurring potentially significant cost impacts 

represent small absolute numbers and percentages of the 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 significant 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, establishes 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 “Federal 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 promulgating 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, section 205 allows EPA to adopt an alternative other than the least costly, 

most cost-effective, or least burdensome alternative 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 governments, including Tribal governments, it must have 

developed under section 203 of the UMRA a small government agency plan. The plan must provide for 

notifying potentially affected small governments, enabling officials of affected small governments to have 

meaningful and timely input in the development of EPA regulatory proposals with significant 

intergovernmental mandates, and informing, educating, and advising small governments on compliance 

with regulatory requirements. 

Although whether a given rule contains a Federal mandate depends on the level of compliance costs, we 

expect that revisions to the Steam Electric ELGs may contain a Federal mandate.17 If so, under §202 of 

the UMRA, EPA will have to prepare a written statement, presented in the preamble to the proposed rule, 

that includes (1) a cost-benefit analysis; (2) an analysis of macroeconomic 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 data 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 the 316(b) Phase II Proposed Rule, EPA had determined that this regulation contained 

a Federal mandate that might result in expenditures of $100 million 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 regulatory 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 lower for small governments in comparison to large 

governments; consequently, small government was determined not to be significantly or uniquely affected 

by the Rule. 

4 Other Administrative Requirements 

4.1 Executive Order 12866: Regulatory Planning and Review 

Under Executive Order 12866 (58 FR 51735, October 4, 1993), EPA must determine whether the 

regulatory action is “significant” and 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 million or more or adversely affect in a material 

way the economy, a sector of the economy, productivity, 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 interfere with an action taken or planned by another 

agency; or 

3⁄4 Materially alter the budgetary impact of entitlements, 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 legal 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 technology requirements, costs associated with these technologies, as well 

as costs associated with administrative activities required to implement the revised Steam Electric ELGs. 

If this action meets the threshold, we will support 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 effect 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 (including populations) the benefits of, or (3) subjecting 

persons (including populations) to discrimination under such programs, policies, and activities because of 

their race, color, or national origin. 

The revisions to the Steam Electric ELGs will require that the location, design, construction, and capacity 

of treatment technologies underlying Steam Electric ELGs 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 expect 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 facilities, it is likely that all populations, including 

minority and low-income populations, will benefit from 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 revisions to the Steam Electric ELGs, EPA will need to 

analyze the benefits to affected populations of reducing pollutant discharges from Steam Electric 

facilities. Affected populations may be expected to include (1) all individuals who live within a 50-mile 

radius of the facilities 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. 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 improved aquatic ecosystem health of the area (e.g., 

satisfaction from knowing that the overall ecosystem health has improved). Anglers who live within the 

50-mile buffer zone are more likely to fish the affected water body and thus benefit from reduced human 

health impacts of consuming their catch and/or improved 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 population 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-state populations that are expected to benefit from 

the proposed rule with those demographic characteristics 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 affected by in-scope facilities will 

be conducted using the Fish Consumption Pathway (FCP) Module, which reports population estimates by 

socio-economic characteristics. The two demographic variables of interest for this EJ analysis are those 

within the FCP Module that best capture the low-income and minority aspects of the populations affected, 

which are: 

3⁄4 Annual household income: less than $19,999 (low-income) and more than $20,000 (not lowincome);19 and 

 

18 According to the US Fish and Wildlife Service, over 65% of anglers travel less than 50 miles 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-income 
Abt 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 facilities 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 lower 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, using 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 individuals residing within 50 miles of each facility. 

3⁄4 The FCP module will calculate the number of additional 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 the 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 spatially defined. They will then be superimposed on 

the FCP Module’s grid, and cell-level population data will be used to define a demographic 

profile for the affected populations 

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

3⁄4 To examine environmental justice concerns for 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 averages within each affected state; (2) calculating a 

ratio of minority to white individuals in the vicinity of in-scope facilities and comparing it to the 

averages within each affected state; and (3) testing 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 populations, 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. Thus, from this analysis, it is possible that the lowincome population group may participate to a lower extent in the benefits of the proposed regulation than 

the general population in the states with Steam Electric 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 contiguous 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) regulation 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 cover 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 Children from Environmental Health 

Risks and Safety Risks 

Executive Order 13045 (62 FR 19885, April 23, 1997) applies to any rule that (1) is determined to be 

“economically significant” as defined under Executive Order 12866 and (2) concerns an environmental 

health or safety risk that EPA has reason to 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 alternatives 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 administrative activities required to implement the revised 

Steam Electric ELGs. However, based on the prior regulatory 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 regulation 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) have 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 and 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 may not issue a regulation that has federalism 

implications, that imposes substantial direct compliance 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 State 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 population 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 systematically less present in the potential benefit 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 states with Phase II facilities. Finally, because all Phase II 

facilities are subject to the Phase II proposed regulation, there could be no systematic discrimination or exclusion of low 

income populations from participation in the Rule’s benefits, based, 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 ELGs will 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, 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 implemented through permits issued under the NPDES program. 

Forty-six States and territories are currently authorized 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 required 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 either authorized or nonauthorized States or on local 

governments because it will not change how EPA and the States and local governments interact or their 

respective authority or responsibilities for implementing the NPDES program. NPDES-authorized States 

that currently do not comply with the 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 Steam Electric ELGs, the relationship and distribution 

of power and responsibilities between 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 appropriate levels of protection for the marine 

environment.” EPA may take action to enhance or expand 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 cultural resources within the marine environment, which 

means “those areas of coastal and ocean waters, the 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 Steam 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 depletion 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, fishing, 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, cadmium, 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 Interior have developed an inventory of MPAs in the U.S. that are protected and 

managed under Federal, State, Territorial, Tribal, or local laws. Examples of marine protected areas include the Great Bay 

National Wildlife Refuge in New Hampshire, the Cape Cod Bay 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 Electric facility effluent pollutants are expected to 

include acute and chronic toxicity to aquatic receptors, 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) bioconcentrate in biological tissues. There are also cumulative impacts 

that result from multiple Steam Electric facilities operating 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 individual species but also the overall marine environment, 

thereby advancing the objective of Executive 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 expected 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 necessarily 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 Proposed Rule, which applies to a similar set of Steam 

Electric facilities, EPA found that nearly all affected 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 impingement and entrainment, the results of this 

analysis may be different. 

4.6 Executive Order 13175: Consultation and 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 tribal 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 have “substantial direct effects on one or more Indian Tribes, on the 

relationship between the Federal government and the Indian 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 expected to have substantial direct effects on tribal 

governments, on the relationship between the Federal government and Indian Tribes, or on the 

distribution of power and responsibilities between the Federal government and Indian Tribes, as specified 

in Executive Order 13175. The national Steam Electric 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 program. 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 from the national inventory of MPAs website 

(http://mpa.gov/helpful_resources/inventory.html) and facility 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 ELGs to affect Tribes in any way in the foreseeable 

future.23 Consequently, Executive Order 13175 would not apply to this regulation. 

4.7 Executive Order 13211: Actions Concerning Regulations That Significantly 

Affect Energy Supply, Distribution, or Use 

The OMB implementation memorandum for E.O. 1321124 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 mcf25 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 outcomes, 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 requirements specified under the 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 the overall electricity market interaction modeled by 

the IPM. Based on the analysis conducted in support 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 facilities, 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 commonly 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) (superseding the PRA of 1980) is implemented by OMB 

and requires that agencies submit a supporting statement 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 paperwork burden imposed on the public by the collection. 

The definition of “information collection” includes 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 information to or for a Federal agency, or to otherwise 

fulfill statutory or regulatory requirements. PRA paperwork 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 collection, 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 unless it displays a currently valid OMB control number. 

Whether OMB approves the information collection requirements 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 specifications, 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, explanations when the Agency decides not to use 

available and applicable voluntary consensus standards. 

Provided that revisions to the Steam Electric ELGs will 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 costs 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 environmental damage from effluent discharge from Steam 

Electric facilities. 

5.1 Analysis Approach and Data Inputs 

To assess the economic costs to society 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 of 
Abt Associates Inc., October 29, 2009 Economic/Financial Analyses for Revisions to the Steam Electric ELGs 23

those resources to comply with the regulatory requirements. 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 consumers 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-level compliance costs on an as-incurred, year-by-year 

basis – that is, this analysis will take the components 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 facilities 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 requirements. We will then sum the costs expected 

to be incurred in each year for each facility and aggregate these costs to estimate the total cost to the 

industry for each year in the analysis period. After being 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 Outlook (AEO) Electricity Price Projections, and GDP 

deflator, as appropriate.26 We will then calculate the present value 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 equivalent value (annualized value), again using the two discount rates, 3 

percent and 7 percent. Costs will be annualized over a time period that encompasses the full duration of 

both costs and benefits, which will reflect the time elapsed from the first incurrence 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 regulatory 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 likely 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) incrementally 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 deflator; energy penalty and downtime costs will be adjusted to 

their incurrence year(s) using AEO projections (which do not require adjustment for inflation). Costs will be aggregated in 

three separate groups according to the index used to adjust them, 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 are 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 relationship 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., benefits 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 regulatory proposals that otherwise have a similar 

quantitative relationship between benefits and costs based on a one-option-at-a-time comparison. 

We will estimate total costs to society using the methodology discussed in Section 5.1. The economic 

benefits27 from the revisions to Steam Electric ELGs will be estimated using a range of valuation 

methods, depending on the benefit category, 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 calculate 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 dollars 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 associated with these requirements, as well as the 

degree to which we will be able to monetize economic benefits. The difference in benefits and costs 

across regulatory options will depend on the effectiveness of the installed technology in reducing 

pollutant discharges. 

 

27 Benefits from the Steam Electric ELGs would occur due to reduction of discharges of pollutants such as arsenic, boron, 

cadmium, cobalt, and other inorganic and organic substances to surface waters. This in turn would directly and indirectly

improve human health (e.g., through reduced exposure to contaminated fish tissue and to contaminated water) and use

benefits, such as those associated with recreational and commercial fisheries. Other types 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 Guidelines 

 
Abt 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 Steam 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 March 31, 2010. The discussion is organized according to 

each type of benefits analysis expected to be conducted in support of the Steam Electric Effluent 

Limitations Guidelines (ELGs) regulations: Human Health 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 (Engineering Analysis or Environmental Assessment) of 

the regulation. 

1 Estimation of Ambient Concentrations 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 regulatory options under consideration. To evaluate 

human health and ecological benefits of the Steam Electric 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 navigator to determine the downstream waters for a 

specified distance (to be determined) from Steam Electric discharges. 

 Groundwater: affected aquifer identifier and path to surface water, if relevant 
Abt 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-stream concentrations, if provided by engineers, 

would be used directly in the analysis. Alternatively, 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 directly 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., impacts to private wells), we would evaluate the 

use of groundwater models such as CHEMFLOW to estimate changes in pollutant 

concentration as part of the benefit analysis. 

 Other media: pollutant loadings to other media (e.g., air or soil) as mass per year, and/or 

concentration 

The estimated baseline and post-compliance pollutant concentrations 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 functions 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 and ingestion of contaminated drinking water for the 

exposed population. The monetary value of avoided cancer is typically estimated using the value of a 

statistical life saved (VSL). The monetary value of avoiding 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-related benefits. The first is the changes in fish 

consumption and drinking water exposures to non-cancer 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 pollutant concentrations that are estimated 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 articles 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 necessary information. These databases will provide us 

with information on uptake via various routes of exposure, metabolism, and retention, including any 

special considerations of age, gender, or health status. 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 quantitatively 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 given dose level, we will use these functions to calculate 

the number of cases of injury, disease, or premature mortality that might occur in an exposed population 

under baseline conditions and under post-compliance scenarios (using the changes in concentration as 

described in Section 1). 

For contaminants believed to have a threshold below which adverse responses are unlikely to occur, we 

will use these threshold values (i.e., Reference Doses (RfDs)) in the analysis 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 determining 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 nature and size of the population exposed to a 

substance or substances and the magnitude and duration 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 Electric 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 discharges and populations relying on groundwater from 

the affected aquifers (including public and private wells). 

 Populations served by surface water intakes affected by Steam Electric discharges. To 

identify population exposed to Steam Electric contaminant via drinking water, we will identify 

the location of any drinking water intakes in the initial and downstream reaches where pollutant 

concentrations were calculated (see Section 1). For this analysis, we will overlay the identified 

NHD Plus stream segments over the Drinking water 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 served by the drinking water system for which the 
Abt Associates Inc., May 26, 2010 Additional Input on Data Sources and Methodology for Benefits Analyses 4

drinking water intake was identified. EPA’s Safe Drinking Water Information System (SDWIS) 

provides information on populations served by drinking water intakes. 

 Populations served by groundwater intakes (public wells). To identify populations potentially 

exposed to Steam Electric contaminants via groundwater 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 well 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 affected 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 affected reaches, as well as members of these anglers' 

households. We will use the National Survey of Fishing, Hunting, and Wildlife-Associated Recreation 

(U.S. Department of the Interior 2006) data to identify the total number of recreational anglers in a given 

state and a typical distance which recreational anglers would travel to fish. We will apportion total state 

anglers to the areas located within the identified travel 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 population 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 baseline 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 changes 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 risks for carcinogens will be characterized by the 

number of cancer cases under the baseline and post compliance scenarios. The expected benefits from 

reducing discharges of Steam Electric pollutant is the 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 including the number of hypertension cases from lead 

exposure, premature mortality, incidence of coronary heart diseases, etc. For these analyses, the analytic 

steps and data sources are the same as in the analysis 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 affected 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 benefits from reducing Steam Electric 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 predict 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-response relationship between PbB and IQ decrements 

from published literature (e.g., Schwartz, 1994) and the estimated number of exposed children to obtain 

the total change in the number of IQ points for the affected population. The output from the IEUBK 

model can also be used to estimate the number of children with IQs less than 70 and whose PbB is greater 

than 20 μg/dL who would require compensatory education. The number of children in the affected 

population (e.g., recreational angler households or populations 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 health-based WQC values with the estimate in-stream 

concentrations of Steam Electric pollutants. This analysis provides a measure of benefits in terms of the 

difference of the number of discharge reaches exceeding 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 monetary values of avoiding non-cancer effects using 

either the cost of illness (COI) approach or WTP values 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 obtained from published economic literature. 

2.4.2 Value of Health Benefits to Children 

We will calculate monetary values for avoided neurological 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 loss effects we will first obtain information on the 
Abt 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)) from 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 children 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 compensatory education for children with IQs less than 

70 and whose PbB is greater than 20 μg/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 remain in regular class rooms. We will use this 

information in combination with the estimated reduction in the number of children with IQs less than 70 

and whose PbB is greater than 20 μg/dL under the post-compliance scenario to estimate the avoided cost 

of compensatory education. 

3 Ecological Benefits 

In this analysis, we will estimate ecological benefits 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 protection of aquatic life, changes in the water quality 

index (WQI) between the baseline and post-compliances scenarios, and reduction in the number of 

protected species or critical habitat areas adversely affected by discharges of steam electric pollutants. We 

will also explore other ecological assessment endpoints 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 National Recommended WQC for protection of aquatic life. 

Pollutant concentrations in excess of WQC limits indicate a significant detriment to the aquatic species 

habitat. Therefore, we will evaluate potential impacts 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 Steam Electric regulation will significantly improve aquatic species 

habitat and thus provide a quantitative measure of ecological benefits. Ecological improvements will be 

expressed in terms of reduction in reach miles where 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 provided by the affected waterbodies, we will use a 

Water Quality Index (WQI) to link water quality measurements 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 WQI values can be classified into suitable water use 

categories such as drinking, swimming, game fishing, rough fishing and boating to provide a link between 
Abt Associates Inc., May 26, 2010 Additional Input on Data Sources and Methodology for Benefits Analyses 7

water quality improvements, ecological services provided by a waterbody (e.g., aquatic life support or 

recreation) and non-market benefits derived from these improvements.1

 . 

The WQI version EPA used in the analysis of the 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 propose to modify the WQI to include TDS using 

information from the available literature (Abt Associates 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 parameters into the WQI definition to provide a more 

comprehensive tool for evaluating the impacts of this regulation. 

To quantify ecological benefits of water quality improvements 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 WQI 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 each facility can be determined by using data on 

species ranges (e.g., from the US Fish and Wildlife 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 stages 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 areas 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 responses, 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 test organisms show a significant sub-lethal response), 

NOEC (No Observed Effect Concentration), LOEC (Lowest Observed Effect Concentration), or MATC 

(Maximum Allowable Toxicant Concentration). The output 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 selected aquatic species or affected critical habitat/aquatic ecosystems from 

exposure to steam electric pollutants of concern. 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 affected 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 waterbodies 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 Literature Review of Water Quality Indices in Support of 

National Modeling Efforts for the Valuation of Improved 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 benefits of water quality improvements resulting from the 

Steam Electric regulation, we will use a benefit transfer approach based on a meta-analysis of surface 

water valuation studies. The technical details involved 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 estimated baseline WQI, the predicted change in 

WQI (WQI) representing a resource change from the Steam Electric regulation (U.S. EPA 2009). To 

estimate total WTP for surface water quality improvements 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 day 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 pollutants; this would be pursued if we are able to 

adjust the WQI to incorporate parameters representing 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 monetary value of improved groundwater protection using 

a benefit transfer approach based on a meta-analysis of groundwater valuation studies (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 concentrations 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 groundwater valuation studies. To estimate total WTP for improved 

groundwater protection resulting from the Steam Electric 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 changes in property values from water quality improvements 

resulting from the Steam Electric regulation, contingent 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 number 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 concentrations or changes in WQI) we will assess property values 

qualitatively. 

4.3 Reduced Cost of Drinking Water Treatment 

We will review information on typical 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 treatment costs, and assess feasibility of estimating cost 

savings from improved quality of source water. Data requirements for this analysis include changes in 

Steam Electric pollutant concentrations in the source 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 published 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 Consistency 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 Association. 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 Aquatic Resource Improvements and Implications for 

Benefit Transfer: A Meta-Analysis.” Canadian Journal of Agricultural Economics 53(2-3):221-248. 

Rosenberger, R.S. and T.T. Phipps. 2007. “Correspondence and Convergence 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.23-43. 

Salkever, D. S. 1995. “Updated Estimates of Earnings 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. Benefit 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 Review 
Yes, 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 Melnikova, and Isabelle Morin 

Subject Steam Electric Questionnaire Part I Responses: 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 provided by respondents in individual Excel workbooks, 

reviewed and cleaned as necessary. Note that the database 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 Commission (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 after 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, immediate 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. The design of each table (which can be seen in “Design 

View” in Access) provides the characteristics of each field, namely the data type, units of measurement if 

applicable, and a description which includes the reference to the relevant Part I question or requested data 

item. Fields added by Abt Associates for quality assurance 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. 

memorandum 
Abt 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_General 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_Annual 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-explanatory, but certain entries have specific meaning: 

 Blank: Indicates a value not provided by the respondent, 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 available 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 specifically 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 information 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 answer 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 submitted 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 expect 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 corrections 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 Economic and Financial Information 

Ownership Shares. Of 684 plants, 584 plants have a single 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 several 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 electric units instead of the 

plant’s immediate parent firms. To determine the 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 share) owner. One survey 

respondent (1429) provided an incorrect value; we received 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 smaller than the total revenue reported for that parent. 

Twenty-seven respondents 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 

questionnaire, we used the detailed data to correct 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 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 order to determine the relevant SBA size category. 

Section 2: Primary Immediate Parent Firm Economic and Financial Information 

In general, we confirmed that in case of multiple ownership, 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 immediate parent is a FERC reporter, we checked if 

FERC Form 1 was attached as a supplemental form. If the 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 immediate 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 quality 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 description 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 provide 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 “Total 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 “Other Revenue” streams but did not include “NonGeneration Revenue” values, 9 plants reported “non-generation revenue” but not “other 

revenue” streams, 80 plants reported both numbers 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 generation (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 did not report income statement revenue. 

 Finally, we confirmed whether for the “After-Tax Income” a given respondent reported Total 

Net Income or Net Operating Income. If “After-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 reported income values that differ from the calculated 

income value by less than 1 percent. 

We performed no quality assurance activities 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 provided cash flow information for the primary 

immediate parent. Out of 411 plants, 38 did not provide 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 not 
Abt 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 with 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 charges (credits) to income”, and the other three 

items in this Table. We could not compare values for 24 plants because the survey respondent 

did not report enough information. Of the remaining 349 plants, 13 plants had equal values; 11 

of these plants reported zero values for all three items. For 331 of the 336 plants with unequal 

values, the difference exceeds 1 percent. 

 Finally, we checked if the reported “Net increase/decrease in cash and cash equivalents” is the 

sum of reported “Cash flow from operating activities”, “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 remaining 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 equivalent is because the firms’ accounting framework is 

different from the form that was provided in the survey; 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 did not provide this information. Consequently, 

the next quality assurance steps for this question 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 plants because of missing information. Of the 

remaining 318 plants, the summed values equaled “Total 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, “Sales 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 Electricity Sales (MWh)” values, respectively; for 107 

of 147 the absolute difference exceeds 1 percent. 

 We also checked that the sum of “Revenue from 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 the calculated and the reported values because of 

missing reported values. Of the remaining 342, 170 plants had equal values. Of the remaining 
Abt Associates Inc., February 20, 2011 Preliminary QA Procedures Steam Electric Part I 7 

172 plants with unequal values, 85 have “Revenue 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 Generation” 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 “Revenue 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 the 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 unequal values, the reported “Revenue from electric 

power generation and sales” value is greater and 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 immediate 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 immediate 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 parent is the same as the ultimate parent while 

420 plants reported that the immediate parent and the ultimate parent are different entities. The 

last 24 plants did not provide an answer to this question. Of the 420 plants that were different, all 

plants reported the ultimate parent’s percent 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 parent percent ownership 

while 27 of these plants did. Two plants overlapped and reported percent ownership for some 

ultimate parents but not for others. 

 . 

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 immediate parent. Of the 684 plants in the survey, 11 plants1

did not report any information for Section 4. Consequently, the quality assurance 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 plants2

 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 checked 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 here were consistent with those in 

Question I2-5. More specifically, we checked to see if revenue streams not associated with electricity 

generation are reported for both, plant and its immediate 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 plants 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. Also, 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 generating 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 the 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 have the monitoring capabilities to measure 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 generator ID. The remaining unidentified SE-Units 

may not have clear matches because of generator units 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 costs 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 equal 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 comparison 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 following 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 does 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 Table 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 reported 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). 

Section 4.2: Detailed Plant 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, 126 respondents provided description of their own 

methodology; all estimation methods implemented 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 assets/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 provided and reviewed the methodology (Question I4-12). Of 

673 plants, 159 did not provide information for this section. Of the remaining 514 plants, 316 

plants did not check the box and provided plant-level information while 198 checked the box 

and provided estimated values; of these 198 plants, 76 provided their own methodology; all 

estimation methods implemented by the respondents are reasonable. 

 We also checked that information reported in this 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 higher 
Abt 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 these 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 description, 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 Generating 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 reported in the 2009 EIA-860 database to confirm 

that these generators are indeed steam. Of the 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 may be missing because of generator units being 

mislabeled in the survey or because of different labeling conventions between the survey and the 

EIA database. 

 In case of multiple ownership structure, we confirmed 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 multiple 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 Generating Unit Economic and Financial Information 

We performed the following quality assurance steps for Question I5-2 (Table I-22): 

 We confirmed that generators, for which 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 this 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 database 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 Operation” 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 Generated (MWh)” is greater than or equal to “Net 

Electricity Generated (MWh)” reported in this Table. 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 greater 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 IDs 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-service 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 likely 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” and “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 costs 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 Costs” 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 for 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. 

Owners of Multiple Plants 

 In the case where the same owner is reported for different plants, we compared data provided in 

Sections 1 through 3 to verify that descriptive information are consistent across the plant 

responses. 

 When the same ultimate parent owner was reported for different plants, we consolidated these 

responses into a list of unique companies and consolidated 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.