v>EPA

United States
Environmental Protection
Agency

Work Breakdown Structure-Based Cost Model

for Drinking Water Treatment by Ultraviolet
Photolysis and Advanced Oxidation Processes

Office of Water (4607M)

EPA ***_*_*****

March 2023


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WBS-Based Cost Model for Drinking Water Treatment by Ultraviolet Photolysis and Advanced Oxidation

Processes

Table of Contents

1.	Introduction	1

1.1	Background	1

1.2	Objectives	1

1.3	Organization of the Report	2

1.4	List of Abbreviations and Symbols in this Chapter	2

1.5	References	2

2.	WBS Model Overview	3

2.1	Model Structure	3

2.2	The WBS Approach	8

2.3	Model Use	10

2.3.1	Input Sheet Structure and Use	10

2.3.2	Common Inputs	13

2.3.3	Input Sheet Examples	16

2.3.4	Output Sheet Structure and Use	18

2.3.5	Critical Design Assumptions Sheet Structure and Use	18

2.3.6	Index Sheet Structure and Use	21

2.4	General Cost Assumptions	22

2.4.1	Building Costs	24

2.4.2	Residuals Management Costs	24

2.4.3	Indirect Capital Costs	25

2.4.4	Add-on Costs	26

2.4.5	Annual O&M Costs	27

2.4.6	Total Annualized Cost	28

2.4.7	Updating and Adjusting Costs	28

2.5	List of Abbreviations and Symbols in this Chapter	29

2.6	References	29

3.	Ultraviolet Photolysis and Advanced Oxidation Process Model	31

3.1	Overview of the UV AOP Treatment Process	32

3.1.1	Direct Photolysis	33

3.1.2	UV-H2O2AOP	35

3.1.3	UV-CI2 AOP	36

3.1.4	Post-Treatment Requirements	37

3.1.5	UV Lamps, Sleeves and Ballasts	38

3.1.6	Reactors and Sensors	39

3.1.7	Point of Application	40

3.1.8	Fouling Potential and Cleaning	40

3.2	Input Sheet	40

3.3	Model Assumptions Sheets	48

3.4	Train Design Sheet	49

3.5	Oxidant Addition Sheet	50

3.6	Pumps, Pipe and Structure Sheet	50

3.7	Instrumentation and Control Sheet	51

3.8	O&M and HVAC Sheets	51

3.9	Indirect Sheet	52


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WBS-Based Cost Model for Drinking Water Treatment by Ultraviolet Photolysis and Advanced Oxidation

Processes

3.10	Output Sheet	53

3.11	Ancillary and Reference Model Components	53

3.12	List of Abbreviations and Symbols in this Chapter	54

3.13	References	54

Appendix A. Valves, Instrumentation and System Controls	61

Appendix B. Building Construction Costs	67

Appendix C. Residuals Management Costs	76

Appendix D. Indirect Capital Costs	85

Appendix E. General Assumptions for Operating and Maintenance Costs	108


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WBS-Based Cost Model for Drinking Water Treatment by Ultraviolet Photolysis and Advanced Oxidation

Processes

1. Introduction

This report is one of a series of reports describing cost models for drinking water treatment
technologies. Most of these technologies are used in drinking water systems to remove or destroy
pollutants such as arsenic, radon, disinfection byproducts, sulfates, hardness and waterborne
pathogens. In addition, several of these technologies can be used as add-on technologies to
existing treatment systems. For example, some of the technologies can be installed to provide
pre-oxidation to improve contaminant removal efficiency by subsequent treatment processes.

1.1	Background

The Safe Drinking Water Act Amendments of 1996, as well as a number of other statutes and
executive orders, require that the U.S. Environmental Protection Agency (EPA or the Agency)
estimate regulatory compliance cost as part of its rulemaking process. EPA developed the models
described in this document to assist in fulfilling this requirement. In other words, the primary
purpose of these models is to aid EPA in estimating national compliance costs. The models
might be acceptable, however, for other uses (e.g., developing a preliminary site-specific
estimate for a water system) if sufficient care is taken to account for site- or project-specific
factors appropriate to the intended use.

The compliance cost models described in this document differ from the drinking water cost
models previously used by the Agency in that the new models are based on a work breakdown
structure (WBS) approach to developing cost estimates. In general, the WBS approach involves
breaking a process down into discrete components for the purpose of estimating unit costs. EPA
pursued this approach as part of an effort to address recommendations made by the Technology
Design Panel, which convened in 1997 to review the Agency's methods for estimating drinking
water compliance costs (U.S. EPA, 1997).1

1.2	Objectives

In developing WBS-based models for estimating drinking water treatment system costs, EPA
had the following objectives:

•	Transparency of process design and cost

•	Defensibility of design criteria and assumptions

•	Ease of use and updating

•	Modularity of components for use with centralized cost database.

The Agency determined that the best way to meet these goals was to develop spreadsheet-based
engineering models drawing from a central database of component unit costs. Each engineering
model contains the work breakdown for a particular treatment process and preprogrammed
engineering criteria and equations that estimate equipment requirements for user-specified design
requirements (e.g., system size and influent water quality). Each model also provides unit and
total cost information by component (e.g., individual items of capital equipment) and totals the

1 The panel consisted of nationally recognized drinking water experts from U.S. EPA, water treatment consulting
companies, public and private water utilities, suppliers, equipment vendors and Federal and state regulators in
addition to cost estimating professionals.

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WBS-Based Cost Model for Drinking Water Treatment by Ultraviolet Photolysis and Advanced Oxidation

Processes

individual component costs to obtain a direct capital cost. Additionally, the models estimate add-
on costs (permits, pilot study and land acquisition costs for each technology), indirect capital
costs and annual operating and maintenance (O&M) costs, thereby producing a complete
compliance cost estimate.

1.3	Organization of the Report

This report is organized as follows:

•	Chapter 2 provides an overview of the general model components and the methods used
in these components to estimate treatment system costs.

•	Subsequent chapters describe the individual models, design criteria and assumptions for
the selected treatment technologies.

•	Appendices provide additional information on methods EPA used to estimate design
requirements and costs for specific components, such as buildings, system controls,
indirect capital costs and annual O&M costs.

1.4	List of Abbreviations and Symbols in this Chapter

EPA	U.S. Environmental Protection Agency

O&M	operating and maintenance

WBS	work breakdown structure

1.5	References

U.S. Environmental Protection Agency (U.S. EPA). 1997. Discussion Summary: EPA
Technology Design Workshop. Washington, D.C.: U.S. EPA, Office of Groundwater and
Drinking Water.

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WBS-Based Cost Model for Drinking Water Treatment by Ultraviolet Photolysis and Advanced Oxidation

Processes

2. WBS Model Overview

This chapter includes the following sections:

•	An overview of how the models are structured (Section 2.1)

•	A description of how this structure was developed using the work breakdown structure
(WBS) approach (Section 2.2)

•	A brief users guide describing how to operate the models (Section 2.3), including
documentation of general design assumptions

•	Documentation of the general cost assumptions incorporated in all of the models (Section
2.4).

2.1 Model Structure

The WBS-based engineering models integrate the following structural features to generate
treatment cost estimates:

•	Treatment component selection, design and cost output based on a WBS approach

•	Process design based on state-of-the-art techniques and generally recommended
engineering practices (GREPs)

•	A centralized reference database containing unit costs for components and reference
tables for component sizing and chemical properties.

Exhibit 2-1 shows how these features are integrated in a series of spreadsheets that include an
Excel workbook for each technology and a central cost and engineering reference database (the
WBS cost database).2 An input sheet allows the user to define treatment requirements such as
system design and average flows, target contaminant and raw water quality. Exhibit 2-2
provides an example of an input spreadsheet. The information provided via the input sheet
interacts with three critical design assumptions sheets (one each for process design, operating
and maintenance [O&M] and indirect capital costs) to generate inputs to the engineering design
sheets. Although the critical design assumption values are based on GREPs and can be used
without modification, the user can also revise these values to reflect site-specific requirements.
Each model also has a predetermined list of treatment equipment needs (e.g., tanks, vessels and
instrumentation) identified using the WBS approach. The engineering design sheets calculate
equipment quantity and size requirements based on the treatment needs and critical design
assumptions. The technology chapters of this report describe technology-specific content and
function of each sheet. General design and cost assumptions are described in Sections 2.3.5 and
2.4.

2 EPA maintains the central WBS cost database in a separate Excel workbook. The WBS cost database itself is not
provided along with the publicly released WBS models. Instead, for ease of review and to maintain vendor
confidentiality, relevant cost and engineering data have been extracted from the database and included directly in the
WBS model workbooks. Thus, users can review (and adjust, if needed) the information from the central cost
database in the same manner as other WBS model inputs and assumptions.

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WBS-Based Cost Model for Drinking Water Treatment by Ultraviolet Photolysis and Advanced Oxidation

Processes

Exhibit 2-1. Structure of the WBS Models

4


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WBS-Based Cost Model for Drinking Water Treatment by Ultraviolet Photolysis and Advanced Oxidation

Processes

Exhibit 2-2. Sample of Input Spreadsheet

MULTI-STAGE BUBBLE AERATION SYSTEM DESIGN AND COST INPUT

STEP 1

Select Contaminant

~I For VOCs, default design; available up to 1 MGD only, because information on using MSBA for these contaminants in larger systems is limited

Select one of the eiqht standard desiqns at riqht
OR

Select "CLEAR FOR MANUAL ENTRY"

STEP 3:

st-Trtdzrd designs?

Enter or change values in the and ;• cells below,
under "Manual Inputs"

0.030 mgd standard design

<- Ufitg this dtfigt

0.124 mgd standard design



0.305 mgd standard design



0.740 mgd standard design



2.152 mgd standard design



7.365 mgd standard design



22.614 mgd standard design



75.072 mgd standard design



CLEAR FOR MANUAL ENTRY





See model documentation for more information on standard designs

l*p«t Conplctt — Rtsilts Ready

STEP 4:

Results are ready fno need to click button]

Generate Results

MANUAL INPUTS

Ciifs f/t -Tfi Ttquir&t Ciffs f/t '

Results summaru fsee OUTPUT sheet for details'!
Direct Capital Cost: J107.797
Total Capital Cost: $158,397
Annual O&M Cost: J7.292
Annualized Cost: 123.629 f16.9 uears at 7%1

1 Select unit:

Dtsiqi Flow



0.030 MGD





Attnqt Flow



O.OOT MGD







For iiforntio*:

Treatment system design flow r
Bypass design flow r

0.030 Tigd
o.ooo Tigd
r

Flow lipit OK

Current bypass percentage is 05i. Go to Critical Design Assumptions to change this value.
Adjust bupass percentage



Dtsiqk Tfpc

pre-eiqiaeered packaqe



Vendor packages include aboveground stainless steel, plastic, or fiberglass basins and typically are used
bv small systems

Optimise Number
of Basins

Niabtr of optratiiq basils

1

40

3
8



Guidance: For VOCs, typical air to water ratios are between 10:1 and 300:1

Air to water ratio





Maiia«B water depth



Guidance: VOCs require no more than 2 to 3 feet water depth, beyond this depth no significant gain is
realised (Lowry peer review comments)

N»ber of staqts



Guidance: for VOCs, minimum of 6 stages, maximum of 12 stages, vendor uses 8 stages for most
applications (Lowry peer review comments)

Pilot rate coistut

0.17

ttmin



Pilot air iittisit*

2.54

cfmfcubic f*



For iaforaatioa:















Estimate only, based on pilot rate constant and air intensity. To increase, increase air to water ratio and/or



Theoretical Percent Removal

90.07%



number of staqes

Number of Basins (including redundancy)

1

units



Basin

.ength (including quiescent chamber)

4

feet





Basin Width

2.5

feet





Basin Height (including freeboard)

5

feet

Adjust freeboard



Diffusers per stage

1

units





Total diffusers

8

units











Adjust basin length constraints







Basil Ikpits OK

Adjust diffuser access space requirements

liflieat water coiceitratioi

5

us'L

Percent rcmor^l



not r*-)uir<-d

VOC release at which air pollitiot control
sfstea is aeeded

i

IbxfJ-ay

For iifor»atio»:

Off-gas coitrol systes May
lot be required



Of f-qas pollatio* coatrol techaoloqv

¦oie

4— pick nr.*

tfwrf rcc& rerw fww	

Speat GA C reqeaer^tioa





GAC bod life



F Off-qas Itpits OK

Used only to determine whether air pollution control might be required; not part of system design
Using theoretical removal from above

CMRP (2000) states this is the maximum emission level for all VOCs for California South Coast AQMD,
but other districts may require different emissions standards based on location of the site and regional
ambient air quality.

N»btr of booster p»p:



For iiforaatioi: tt of booster pumps



2 pump/

N»ber of blowers



tlouerr

For iiforaatioi: tt of blowers (including



2 blouprx

N»btr of rcdiidiit basias to be added



ur.itr





0 units

Coipoitit level



| 1 pick or I^cmp blink

Sfstea aitoaatioi

For reformatio*: Component level
Automation

r
r

f«llf a«toaated <" pick or li-ivi-blink

low cost
fally aitoiated

Optional Ikpits OK

Enter 0 to exclude booster pumps (i.e.
for all siaes in this technoloqy)

xisting pumps). Clear cell to accept model defaults (included

Designs should always include at least one blower. Leave blank to accept model default calculations.
Adjust number of redundant blowers

Leave blank to accept redundancy specified in critical design assumptions

Leave blank to use low cost components

Leave blank to allow model to pick based on component level

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WBS-Based Cost Model for Drinking Water Treatment by Ultraviolet Photolysis and Advanced Oxidation

Processes

Exhibit 2-3 shows an example of an output spreadsheet. The output sheet summarizes the results
of the calculations performed by the engineering design sheets, listing size and quantity required
for each item of equipment and the corresponding unit cost from the database. The output sheet
multiplies unit cost by quantity to determine total component cost for each WBS component. The
output sheet also lists the estimated useful life of every WBS component. The models use the
component useful lives in estimating total annualized cost (see Section 2.4.6).

For many of the components, there are optional materials, all of which are illustrated on the
output worksheet. For example, pressure vessels can be constructed with different types of body
material (stainless steel or carbon steel) and different types of internal materials (stainless steel or
plastic). Where there are optional materials, the output sheet selects from among these materials.
The specific selections are determined by input values and documented in the "use?" column of
the output worksheet. Direct capital cost is the sum of the selected component costs.

The output sheet also contains sections that calculate add-on costs, indirect capital costs, annual
O&M costs and total annualized cost. Annual O&M costs are based on the annual requirements
calculated on the O&M sheet. Indirect capital costs for certain items (standby power,
geotechnical, site work and yard piping) are based on calculations performed by the indirect
sheet. Other indirect capital costs and add-on costs are based on assumptions described in
Sections 2.4.3 and 2.4.4. Section 2.4.6 describes the calculation of total annualized cost.

The output sheet obtains unit costs (both capital and O&M) either from the central WBS cost
database or from estimated equipment cost curves. All of the treatment technology models use
information from the WBS cost database, which consists of a series of lookup tables that contain
costs by equipment or O&M element type and size. The database also provides useful life
estimates and documents the source of information. The central WBS cost database also contains
several tables that are used by the engineering design sheets of each model. For example, these
tables include information used in selecting pipe diameters, footprint for pumps and chemical
properties.

The WBS cost database itself is not provided along with the publicly released WBS models.
Instead, for ease of review and to maintain vendor confidentiality, relevant cost and engineering
data have been extracted from the database and included directly in the WBS model workbooks.
Thus, users can review (and adjust, if needed) the information from the central cost database in
the same manner as other WBS model inputs and assumptions.

6


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WBS-Based Cost Model for Drinking Water Treatment by Ultraviolet Photolysis and Advanced Oxidation

Processes

Exhibit 2-3. Sample of Output Spreadsheet

OUTPUT SUMMARY

Technology
Contaminant Type
Syxtem Silt Cateqary
Dexiqn Flou
Average Flou
Number of Earinx
Number of Staqex per Ea
Sarin Lenqth
Sarin Wi dth
Sarin Heiqht
Diffuxerx per Staqe
Total Jiffurerx
Off-Gar Treatment

Direct Capital Cart
AJJ-onCort

MSBA
TCE

0.03 MGD (exclu Jex hypar
0.00T MGD (excluJex bypax.
1 unitr
% xtaqex

4	feet
2.5 feet

5	feet
1 unitr

$ 107,737 Detailr
J	1,038 Detailr

$ 50,162 Detailr

fatal Capital Out	J

A»»l 0*H Cvt	$

A»«li»J Cmrt (H.t T*«« at TZ)	$

Per 1,000 qallonr aueraqe flou	$
	Per hoireholJ per year	j

158,997 Detailr
7,292 Detailr
29,629 Detailr
9.25
958

Direct Capital Cost Details ¦it^snsinitoiics, uMwt

fir- ti'J- \irj-i'mcpiwnn, .'//¦.wa

t oitj-snotj- carts on J tot of}















WBS * lt»>

Dtii^ft H««fttitT

D*xi«.

Six* Six*

u*4 ift uti.at.

U»

t Cut

fata

Cut Uxef.

Lif*

Uxt>



1.1 Curtam DexiqneJ

t.tt

Czincrj'tj-

ft unit.'

AM



AM



AM





AM



t.t.2





AM



am



AM





AS**



AA.Z





AM



am



AM





AfrJ*



Jtj(•/

StjjiOm'^r

¦

AM



AM



AM





AM



n.z

Pre-en qir.ee re J Paclcaqe





















t£t

St oiniiirs Stjj-i

t units

AV

foi

AV ?ci

f

2$ (W





Sft

ft

1.2.1

Plartic



374

1t|

374 «.l



2.114



2.114

7

1



Fiiisqiars

f vnitr

JW

foi

Jjtlf

f



t

fSjjg

tfi

ft

1.3

Eafflex





















1.3.1

Bafflu

X iftiti

12.5

jrflfcaffU

12.5 xfllaffU

%

123

$

»t2

7

1

i.«

Aeratorx





















1.4.1

Diff u*rx

• «ftitr

14

cf>

14 cf>

y

49

J

345

1*

1

2-

PiBfx a»JI Blouerx



















m



ADDTDONAL WBS COMPONENTS NOT SHOWN

13



13 «.

*

4.5K

*

9.432

17

i

AHf

Hj-Otf-VSSif-

	am	

Hit*

AM
	i



AM



/!M





	AM

37

i



















Dinct cut cateqarr

fatal G.iJa





















Procexx cartx

$ 101,53$ Exclu Jex alternate cart line itemx in italicx,uithaut a 1

the '(Jxef ' column. Inclu Jex inrtallatian, tranrpartation, an J C&P







EuilJinq cartx

$ 6,259 See inJirect arxumptiarirxheet

to excluJe huil Jinqx

















Total direct capital cost

~107.737 Total of

procexx an J buil Jinq ca

xtx















Add-on Cost Details f-W in ctirs- c t	to AY civ A- in Jit vjv oi c J J-Br, its&rf

AJJ-ift Li** Itt*

Tatal

GaiJaoce

Permitx

t 111



Pilot StuJy

t

Ma pilatxtu Jy require J far thir technalaqy

LanJ Cart

$ 026

For 0.01 acrex

Total add-on costs

$1,038

Total of per mi tr, pilot inq, an J Ian J

Indirect Capital Cost Details f£*
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WBS-Based Cost Model for Drinking Water Treatment by Ultraviolet Photolysis and Advanced Oxidation

Processes

2.2 The WBS Approach

These models represent improvements over past cost estimating methods by increasing
comprehensiveness, flexibility and transparency. By adopting a WBS-based approach to identify
the components that should be included in a cost analysis, the models produce a more
comprehensive assessment of the capital requirements for a treatment system. The models are
flexible in that users can change certain design parameters; warning messages indicate when user
inputs violate GREPs or logical functions. The transparent structure of each model allows users
to see how costs are built up from component unit costs to total treatment costs, which enables
users to identify cost drivers and determine whether the input assumptions generate a cost-
effective treatment design. Users also can perform sensitivity analyses showing how changes in
water quality parameters, chemical feed doses and equipment configuration affect cost.

Unlike prior EPA models, which used a variety of cost build-up methods, the WBS-based
engineering models have been developed using a consistent framework. Exhibit 2-4 shows this
framework. For each technology, the result is an engineering spreadsheet model that combines
user-identified inputs with pre-programmed engineering criteria and equations to generate
appropriate treatment design and equipment requirements. The models also result in a system-
level cost estimate for regulatory cost analysis.

Exhibit 2-4. Framework for Developing the WBS-Based Models

Step

Process

Step 1

Identify the treatment requirements based on the contaminant requiring removal, the flow for which treatment is
required, the influent water quality and treated water quality requirement, and then select a treatment technology
or combination of technologies capable of meeting the requirements.

Step 2

Develop the general design assumptions that apply to all the technologies (e.g., chemical storage capacity).

Step 3

Develop site- and technology-specific design assumptions that might affect treatment performance and, thereby,
design requirements (e.g., assumptions related to influent water constituents such as alkalinity or water quality
parameters such as pH).

Step 4

Construct a typical process flow diagram or P&ID showing the main unit processes for the technology and identify
equipment requirements.

Step 5

Calculate the equipment requirements, including dimensions and quantities, for the core elements of each unit
process. At each component (or group) level, identify choices of material (e.g., stainless steel or PVC pipe
material).

Step 6

Link the treatment equipment requirements to a database that contains unit costs by equipment type, size and
material. Multiplying the unit costs by the dimension and quantity requirements developed in Step 5 provides the
component-level design costs.

Step 7

Tally the costs of the selected components to determine direct capital cost.

Step 8

Develop and add indirect and add-on costs to determine total system capital cost.

Step 9

Develop operation and maintenance cost estimates.

The WBS approach provides EPA with a consistent method for identifying components to
include in a cost estimate. For each technology, the WBS approach develops a process and
instrumentation diagram (P&ID) or a typical schematic layout showing the main unit processes
needed to achieve the contaminant removal goals.

Exhibit 2-5 provides examples of several classes of components that can be included in a P&ID.
The models often include further breakdown for alternative materials of construction for each
component, because costs can differ substantially across materials. For example, most pipes can

8


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WBS-Based Cost Model for Drinking Water Treatment by Ultraviolet Photolysis and Advanced Oxidation

Processes

be constructed of stainless steel, steel, polyvinyl chloride (PVC) or chlorinated PVC. Stainless
steel piping can cost twice as much as PVC.

Exhibit 2-5. Component Classes Included in the WBS Inventory

Component Classes

Example Components

Vessels

Pressure vessels

Tanks/basins

Storage

Backwash

Mixing

Contact

Flocculation

Sedimentation

Filtration

Pipes

Process

Backwash

Chemical

Inlet/outlet

Bypass

Valves (see Appendix A for further details)

Check (one-way)
Motor- or air-operated
Manual

Pumps

Booster
Backwash

High-pressure (for membrane systems)
Chemical metering

Mixers

Rapid

Flocculation
Inline static

Instrumentation (see Appendix A for further details)

Pressure gauge
Level switch/alarm
Chlorine residual analyzer
Flow meter
pH meter
Air monitor/alarm
High/low pressure alarm
Gas flow meters—rotameters
Scales

System controls (see Appendix A for further details)

Programmable logic control units
Operator interface equipment
Controls software

Chemicals

Acids
Bases

Coagulants and coagulant aids
Antiscalants
Corrosion control
Oxidants and disinfectants

Treatment media

Activated alumina

Activated carbon

Membranes

Sand

Resins

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WBS-Based Cost Model for Drinking Water Treatment by Ultraviolet Photolysis and Advanced Oxidation

Processes

Component Classes

Example Components

Building (see Appendix B for further details)

Structure

Heating and air conditioning systems
Concrete pad

Indirect Capital Components (see Appendix D for further
details)

Geotechnical investigations
Standby power generators

The level of component detail (and by implication, design detail) in Exhibit 2-5 indicates that
the WBS-based approach is more sophisticated, and potentially more time consuming, than the
factored or parametric cost estimating methods used in earlier efforts. Nevertheless, the
Technology Design Panel considered it the right approach to developing unit costs for policy
analysis. Furthermore, EPA believes that developing unit cost models that are more
comprehensive, flexible and transparent will facilitate the policy analysis process by addressing a
frequent topic of dispute over regulatory cost estimates. Finally, the WBS-based models are
driven by technical scope and selection of suitable equipment and material to achieve a defined
treatment objective. This approach is superior to cost estimating methods that are not defined by
a desired treatment level or that cannot be changed easily to reflect raw water quality.

2.3 Model Use

This section provides basic guidance on operating the WBS technology models. As discussed
above, each model is an Excel workbook comprising a series of spreadsheets. In general, users
need only be concerned with the input sheet and output sheet, although advanced users might
also wish to examine the critical design assumptions spreadsheets.

2.3.1 Input Sheet Structure and Use

The input sheet in each of the technology models is similar to that pictured in Exhibit 2-2. A
step-by-step input process allows the user to quickly generate costs for standard designs built
into the model, modify those designs or construct an alternative design.

Overview of the Input Process

Many models require basic information
from the user before choosing an
appropriate standard design. For example,
contaminant selection is the first choice
that must be made in several of the
models. Such choices are made using a
drop-down list at the top of the input
sheet.

After making any basic, top-level choices,
the user can click on one of the eight
standard design buttons. Each button
corresponds to a system size category in
the flow characterization paradigm
described below in Exhibit 2-6. The
model will populate all inputs with values

STEP 1

Select Contaminant

STEP 2:

ore ef the- e oht stardom -le.. uns a! 
0 1MMGD.8* gpm\
0 305 MbD (212 gprm
0 ?40MGD;S14gpmi
2 152 MGD i1 4S4 ypnif
? 36b MGD (5 115 gpmi
22ht4NGDi15?ts4 gpm^
75 0/2 MGO (52 133 gpm:
CLEAR FOR MANUAL ENTRY

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WBS-Based Cost Model for Drinking Water Treatment by Ultraviolet Photolysis and Advanced Oxidation

Processes

appropriate for the selected design, then compute all costs. The direct capital cost, total capital
cost and annual O&M cost are displayed on the input sheet; details are available on the output
sheet (see Section 2.3.4). More information on the standard designs is provided below.

Exhibit 2-6. Standard Flow Rate Categories Used in WBS Standard Designs

Size Category

Population Served

Design Flow (MGD)

Average Flow (MGD)

1

25 to 100

0.030

0.007

2

101 to 500

0.124

0.035

3

501 to 1,000

0.305

0.094

4

1,001 to 3,300

0.740

0.251

5

3,301 to 10,000

2.152

0.819

6

10,001 to 50,000

7.365

3.200

7

50,001 to 100,000

22.614

11.087

8

Greater than 100,000

75.072

37.536

The standard designs, with their corresponding buttons, are primarily for EPA's use in estimating
costs for a median sized system in each size category, although some users may find them useful
as a starting point (see the examples in Section 2.3.3). The user can modify the standard designs
after clicking one of the buttons by entering values in the gold and blue input cells, under the
"Manual Inputs" heading on the input sheet. Alternately, many users will want to click the button
marked "CLEAR FOR MANUAL ENTRY" and enter all of the input values by hand. In any
case, the manual inputs section contains several types of cells:

•	Required user inputs, highlighted in gold

•	Optional user inputs, highlighted in blue

•	Greyed-out inputs, which are not required for a given design

•	Information and guidance, with text in green.

Some inputs, such as system flows, must contain a numeric value. Others have a drop-down
arrow that appears when the cursor is positioned in the input cell. These cells must contain one of
the drop-down values. Required inputs must be populated; optional inputs can be left blank to
accept model defaults or changed by the user to examine the effect of different assumptions. The
Autosize button, described below, is available in some models to facilitate design.

The input sheet in each model verifies user inputs against certain design constraints that reflect
GREPs. If user inputs result in designs that violate these constraints, a warning message appears
on the input sheet, explaining which input value needs to be corrected. In addition, the message
"Input Incomplete—Check for Error Messages Below" appears at the top of the input sheet.

Once all inputs are complete and the
model has verified that they meet design
constraints, the message at the top of the
input sheet changes to "Input
Complete—Press 'GenerateResults'."

The user must click the "Generate
Results" button to tell the model to
generate costs. Once the user has clicked

STEP 3:

(Optional for standard designs)

Enter or change values in the and blue ci
below, under "Manual Inputs"

STEP 4:

Results are ready (no need to click button)

Generate Results

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the button, the message at the top of the model changes to "Input Complete—Results Ready,"
and total costs are displayed on the input sheet. The output sheet provides more details for the
total costs.

Standard Designs

The input sheet in each of the technology
models contains up to eight buttons,
which correspond to the eight standard
flow sizes in the flow characterization
paradigm for public water systems (see
Exhibit 2-6). These buttons populate all
of the input fields with appropriate values
for the selected design flow. The values in
each standard design meet all relevant
design constraints. Each model includes a
separate sheet, entitled "standard inputs,"
that documents the specific input values
included in each standard design.

Advanced users can adjust the standard
designs by changing the values on the
standard input sheet. For example, a user
could change all the standard designs to use high cost components, rather than the default of low-
cost components (see Section 2.3.2 under "Component Level"), by changing values in the
appropriate column on the standard input sheet. The standard input sheet highlights values that
have been changed by the user and includes a button ("Reset to Defaults") that resets the
standard designs back to their original settings. Users that make significant adjustments to the
standard designs should take care to verify that their new designs still meet design constraints by
checking for warning messages on the input sheet after each new design is run.

The Autosize Routine

The models also can be used to estimate
costs for systems with design flows other
than the eight standard sizes. To aid in
developing designs for other flows, some
models include a button labeled
"Autosize." This button activates a
computer-aided design routine that
attempts to find a design meeting all
relevant design constraints for a given design and average flow. For example, the user could
change design flow to 3 million gallons per day (MGD) and average flow to 1 MGD, then click
the autosize button. This would populate some input fields with values that are both appropriate
for a 3 MGD system and that meet all design constraints. More information on the autosize
routines, including details on which inputs are and are not populated, is available in the
technology-specific chapters of this document.

STEP 2:

Select one of the eight standard designs at nght OR select
"CLEAR FOR MANUAL ENTRY"

0.030 MGD (21 gpm)

0.124 MGD (86 gpm)

0.305 MGD (212 gpm)

0.740 MGD (514 gpm)

2.152 MGD (1,494 gpm)

7.365 MGD (5,115 gpm)

22.614 MGD (15,704 gpm)

75.072 MGD (52,133 gpm)

CLEAR FOR MANUAL ENTRY

Pressure Vessels





The next four inputs may be entered manually, or calculated with Am



Bed depth



Auto Size Pressure Vessels

Vessel geometry



Length (straight)





Diameter





For information:





Number of treatment trains



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In the rare case that the autosize routine cannot find a design meeting all constraints, it will
display a pop-up warning message. This does not mean that it is impossible to design a system
for the selected size. The user might still be able to develop a design by manually adjusting the
input values, paying careful attention to the warning messages on the input sheet. It might be
necessary to relax some of the design constraints by adjusting values on the critical design
assumptions sheet.

Manual Input and "Generate Results"

All of the models allow the user to enter input values by typing them directly into the appropriate
fields on the input sheet. Users can develop complete designs from scratch, populating all the
input fields manually. Users also can adjust designs generated by the standard design or autosize
buttons, by adjusting one or more input fields manually after clicking one of these buttons. In
either case, after completing the manual changes, users should do two things:

•	Verify that no warning messages appear to ensure that the design meets all relevant
constraints

•	Click the button labeled "Generate Results."

The second step is necessary to tell the
models that the design process is
complete and to select the appropriate
items of equipment for inclusion in total
costs on the output sheet. This step is
particularly important if the system
automation or component level inputs
are adjusted manually, because these
inputs have a significant impact on the selection of equipment. To ensure correct calculation of
costs, however, users should click the "Generate Results" button after completing manual
changes to any of the inputs. It is not necessary to click this button when the input sheet message
reads "Input Complete—Results Ready." This message will appear, for example, when the
standard designs or autosize routine are used without subsequent manual changes to input values.
The standard design buttons and the autosize button automatically incorporate the "Generate
Results" step, telling the models to select the appropriate items of equipment.

2.3.2 Common Inputs

The user inputs in each model are largely technology-specific and are described in detail in the
technology chapters of this document. There are certain inputs, however, that are common to all
of the technology models. These common inputs are described below.

STEP 3:

(Optional for standard designs)
Enter or change values in the
below, under "Manual Inputs"

STEP 4:

Results are ready (no need to click button)

Input Complete — Results Ready

Generate Results

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Design and Average Flow

MANUAL INPUTS

Cells in are required; cells in blue are optional

Design Flow

0.74 MGD

Average Flow

0.251 MGD

System size inputs OK

Each model needs the design and average flow to determine the size and number of treatment
components needed. Design flow is the peak instantaneous flow of product water from a
treatment system, while average flow is the annual average flow, taking into account daily and
seasonal variations in demand.

Design flow can be entered in MGD or in gallons per minute (gpm). In either case, the design
flow is meant to represent a maximum instantaneous flow. Average flow can be entered in
MGD, in gpm or as a percentage of design flow.

The standard design functions included in each model (see above) can populate design and
average flow with values based on the flow characterization paradigm for public water systems.
The flow paradigm includes eight model size categories, as shown in Exhibit 2-6. These size
categories represent populations ranging from 25 persons to greater than 100,000 persons. Based
on the values in Exhibit 2-6, the ratio of average flow to design flow ranges from 25 percent for
very small systems to 50 percent for large systems.

Component Level

| Component level





pick or leave blank



low cost





mid cost





high cost



Each model includes an optional input that determines whether the cost estimate generated is a
low, medium or high cost estimate. This input, labeled "component level" or "cost level," drives
the selection of materials for items of equipment that can be constructed of different materials.
For example, a low cost system might include fiberglass pressure vessels and PVC piping. A
high cost system might include stainless steel pressure vessels and stainless steel piping. The
component level input also drives other model assumptions that can affect the total cost of the
system, including assumptions about system automation (see "System Automation" below),
building quality and heating and cooling (see Appendix B).3 If the component level input is left
blank, the models will generate a low cost estimate. The user can change this input to select a
medium or high cost estimate.

3 In some cases (e.g., the membrane models, which are under development), this input also determines the source
water quality that the model treats. In these models the input is called the "cost level."

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System Automation

| System automation





pick or leave blank



manual

semi-automated

fullv automated

	

As described in Appendix A, control of drinking water treatment systems can be manual,
automated or semi-automated. The method of control can have a significant impact on both
capital and O&M costs. Each model includes an optional input that allows the user to select from
among the three control options. If the system automation input is left blank, the control option
selected is determined by the system size and the component level input selected (see above),
using the logic shown in Exhibit 2-7. The user can change the system control input to force the
design of a system with manual, automated or semi-automated control.

Exhibit 2-7. Default Assumptions for System Control

Component Cost Level Selected

System Size (Design Flow)
Less than 1 MGD

System Size (Design Flow)
1 MGD or greater

Low

Manual

Manual

Medium

Manual"

Automated

High

Automated

Automated

* Automated for some models.

Include Buildings?







Include buildings?



<- pick or leave blank

Include HVAC?



<-- pick or leave blank

Include land?





z

pick or leave blank



_

E

es





no

By default, the WBS models include the capital cost of buildings to house the treatment system,
as discussed in Section 2.4.1 and Appendix B. Each model includes an optional input that allows
the user to exclude the capital cost of buildings. If the user excludes the capital cost of buildings,
the m odel also excludes the O&M cost of building maintenance and li ghting.

Include Heating, Ventilating and Air Conditioning (HVAC)?

By default, the WBS models choose whether to include the cost of heating and cooling systems
depending on system size, building structure type and user input for component level, as
discussed in Section 2.4.1 and Appendix B. Each model includes an optional input that allows
the user to override the model's default selection and choose to include or exclude the cost (both
capital and O&M) of HVAC systems.

Include Land?

Regardless of whether a system needs to purchase additional land on which to build the new
treatment train, there is an opportunity cost associated with using land for water treatment rather

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than an alternative use. By default, the WBS models include an add-on cost for land, as
discussed in Section 2.4.4. Each model includes an optional input that allows the user to exclude
the add-on cost for land.

2.3.3 Input Sheet Examples

Several examples are presented here to clarify the use of the WBS model input sheet. The
examples refer to particular technology models. Detailed information about the inputs for these
models can be found in the appropriate technology-specific chapters.

Standard Design

The simplest way to generate a design is by use of the standard design buttons. Suppose that a
user wishes to estimate costs for a system designed to treat trichloroethylene (TCE) using
granular activated carbon (GAC), serving a population of approximately 8,000 people. The
following are step-by-step instructions for using the adsorptive media model to generate such a
cost estimate:

1.	Open the Excel workbook named "WBS GAC.xlsm."4 Depending on your settings and
version of Excel, a message might appear regarding "active content" in the workbook.
For the models to function properly, macros must be enabled. Take the appropriate steps
to enable macros (for example, clicking "Options" and selecting "Enable this content,"
depending on your version of Excel).

2.	Navigate to the input sheet by clicking on the tab labeled "INPUT" at the bottom of the
Excel window. (It is also possible to page through the sheets by pressing Ctrl-Page Up
and Ctrl-Page Down.) Scroll to the top of the input sheet.

3.	The GAC model requires that the user first choose the contaminant. Select "TCE" from
the "Select Contaminant" dropdown list.

4.	The GAC model also requires that the user choose between pressure and gravity designs
(see the appropriate technology chapter for discussion of the difference between design
types). Select "Pressure" from the "Select Design Type" dropdown list.

5.	The user wishes to use a standard design appropriate for a population of 8,000 people.
Exhibit 2-6 indicates that size category 5, with a design flow of 2.152 MGD, is
appropriate for such a system. Therefore, click on the design button labeled "2.152 MGD
standard design." After a few seconds, the model will display the message "Using this
design" next to the design button and "Input Complete—Results Ready" underneath the
buttons. It displays the direct capital cost, total capital cost and annual O&M cost on the
input sheet.

6.	If desired, scroll down on the input sheet to see what inputs are used for the standard
design. For instance, the 2.152 MGD standard design for GAC treating TCE with a
pressure design uses a design flow of 2.152 MGD and an average flow of 0.819 MGD. It

4 Note that your model file name might vary. It likely will include a date following the model title (e.g., "WBS GAC
042514.xlsm" for April 25, 2014).

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assumes a carbon life of 66,600 bed volumes and a total theoretical empty bed contact
time (EBCT) of 7.5 minutes.

Modified Standard Design

Suppose that the user wishes to design a GAC system treating TCE for a population of 1,000,
using source water that entails a different carbon life and EBCT than that assumed in the
standard designs (e.g., because the source water contains a higher initial concentration of TCE).
The user determines that the source water characteristics entail a carbon life of 40,000 bed
volumes and an EBCT of 10 minutes. The following are step-by-step instructions for using the
GAC model to generate such a cost estimate:

1.	Open the Excel workbook named "WBS GAC.xlsm"5 and take the appropriate steps to
enable macros (see Step 1 described in the "Standard Design" section above). Navigate to
the input sheet, scroll to the top of that sheet and select "TCE" and "Pressure" from the
appropriate dropdowns (see Steps 2, 3 and 4 described in the "Standard Design" section
above).

2.	The user wishes to design a system for a population of 1,000 people. Exhibit 2-6
indicates that size category 3, with design flow 0.305 MGD, is appropriate for this
population, so start by clicking the "0.305 MGD standard design" button.

3.	The user wishes to design a system with a carbon life of 40,000 bed volumes. Scrolling
down the input sheet, note that the standard design uses an input carbon life of 66,600
bed volumes. Type the number 40,000 in the gold input cell to change the carbon. Note
that the green informational text below the input cell changes to show the number of
months between regenerations. Note also that the message above the manual inputs
changes to "Input Complete—Press 'Generate Results'" to indicate that costs have not
been updated for your new input.

4.	The user wishes to design a system with an EBCT of 10 minutes. Scroll down to the cell
labeled "Theoretical Empty Bed Contact Time" and enter the number 10.

5.	Changing the EBCT will change the optimal vessel geometry. To quickly estimate costs
for this new EBCT, click the "Autosize" button next to the inputs for vessel geometry.
The input values will flicker briefly while the model tries several different values and
then settles on a new value. Because the Autosize button was clicked, it is not necessary
to click the "Generate Results" button; the message above the manual inputs reads "Input
Complete—Results Ready," and the total costs are displayed on the input sheet.

Suppose that the user also wishes to estimate a high-end cost for this system. In this case, take
the following additional steps:

5 Again, your model file name might vary. It likely will include a date following the model title (e.g., "WBS GAC
042514.xlsm" for April 25, 2014).

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6.	Scroll down and place the cursor in the input cell labeled "Component Level." A
dropdown arrow appears to the right of the cell. Click on the arrow and choose "high
cost."

7.	Scroll back to the top of the sheet. Note that the sheet indicates that the user must click
"Generate Results." Click that button. The model displays costs for the high-end system.
To see what components are included, switch to the Output sheet and examine the details.

2.3.4	Output Sheet Structure and Use

The output sheet in each of the technology models is similar to that pictured in Exhibit 2-3. In
addition to the details described in Section 2.1, the output sheet includes several important totals:

•	Process cost, which is the sum of the installed capital cost of all equipment required for
the treatment process

•	Building cost, which is the sum of the installed capital cost of all buildings and the
concrete pad

•	Direct capital cost, which is the sum of the process and building costs

•	Total capital cost, which is the total of the direct capital cost, the indirect capital costs and
add-on costs (see Sections 2.4.3 and 2.4.4)

•	Annual O&M cost (see Section 2.4.5)

•	Total annualized cost (see Section 2.4.6).

The capital equipment section of the output sheet includes a column labeled "Use?" This column
tells the model which line items to include in the direct capital cost. Specifically, items with a
value of 1 in the "Use?" column are included in the total; items with a value of 0 or a blank are
not included in the total. Advanced users can manually adjust this column to include or exclude
certain items of equipment. For example, a user could examine process costs without booster
pumps by changing the "Use?" value to 0 for those pumps. The "Generate Results" button,
which is present on both the input and output sheets, will reset the "Use?" values back to pre-
programmed default values, as driven by system size and input values.

The output sheet also includes a button labeled "Record Output in a New Workbook." This
button generates a complete copy of the output sheet that will not change. Using this button
allows users to record the detailed design output for comparison purposes. For example, a user
could record the output from the standard design for 0.03 MGD, then select the 0.124 MGD
standard design and compare the output results for the two designs.

2.3.5	Critical Design Assumptions Sheet Structure and Use

Each of the technology models includes at least three critical design assumptions sheets:

•	One for process and building design assumptions

•	One for assumptions used in calculating annual O&M costs

•	One for assumptions used in calculating certain indirect capital costs

Some models include additional critical design assumptions sheets (e.g., in the aeration models,
for assumptions associated with off-gas treatment).

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These sheets contain design constraints and structural and chemical engineering assumptions
based on GREPs. Users can review these sheets for details on significant assumptions used in the
models. Advanced users might want to modify certain assumptions, particularly if adapting a
model for use with a source water quality different than assumed in the standard designs or to
reflect site-specific conditions. Most of the assumptions include a comment column explaining
the use of the assumption and/or providing guidance on appropriate values.

Most of the significant design assumptions are technology-specific and discussed in detail in the
technology chapters of this report. However, there are certain assumptions that are common to
many of the models. Exhibit 2-8 summarizes the general design assumptions that are common
across most of the models. As Exhibit 2-8 indicates, these assumptions are based on a
combination of sources, including standard design handbooks, engineering textbooks and
comments of external reviewers. Note that some of the general design assumptions (and some
technology-specific assumptions, as discussed in the relevant technology chapters) differ for
small versus large systems. In general, these differences are because small systems can often be
built as packaged, pre-engineered or skid-mounted systems. In most cases, the different design
and cost assumptions for small systems are based on comparison of model outputs with as-built
designs and costs for actual small treatment systems.

The user can change some of the assumptions shown in Exhibit 2-8 by editing the critical design
assumptions sheet; others can be edited in the data extracted from WBS cost database. The final
column of Exhibit 2-8 provides guidance on how to change each assumption. For example, the
design of pumps for any treatment system is based on the peak flow requirements of the system,
including a safety factor. As specified in Exhibit 2-8, the critical design assumptions sheet
assumes a safety factor of 25 percent. A user could change this factor based on an actual pump
performance curve.

Exhibit 2-8. General Design Assumptions Used in the WBS-based Models

Element

Assumption

Can be changed by:

Influent pumps

Include flooded suction

Replacing unit costs or cost coefficients
extracted from the WBS cost database

All pumps

Design flow incorporates a safety factor of
25 percent

Editing the critical design assumptions
sheet of each technology

Access space for pumps

Provide a minimum of 4 feet of service
space around three sides of each unit,
assuming the fourth side can share access
space with relevant tanks or vessels

Editing the critical design assumptions
sheet of each technology

Pipe size

Based on a maximum of 3 feet of head
loss per 100 feet of pipe

Editing the engineering lookup table
extracted from the WBS cost database

Process pipe size

Based on maximum flow to each unit (not
total system flow)

Cannot be changed

Tank and pressure vessel
capacity

Based on design capacity, freeboard and
standard manufactured sizes

Cannot be changed

Pressure vessel diameter

Based on user input, within limits specified
on a technology-specific basis

Changing user inputs (for diameter) and
editing the critical design assumptions
sheet of each technology (for constraints)

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Element

Assumption

Can be changed by:

Storage tank diameter

Assumes a cylindrical design, with
diameter equal to one half of the height

Cannot be changed

Access space for tanks and
pressure vessels

Provide service space around each unit
equal to its diameter (half its diameter for
small systems), to a maximum of 6 feet

Editing the critical design assumptions
sheet of each technology (only maximum
can be changed)

Process vessels and basins, all
pumps and chemical feed
systems

Multiple units required to protect from
single point failure

Editing the critical design assumptions or
input sheet of each technology (depending
on the specific item)

Chemical storage

Storage requirement based on 30-day
delivery frequency

Editing the critical design assumptions
sheet of each technology

Concrete pad under heavy
equipment

1 foot thick for large systems, 6 inches
thick for small systems

Editing the critical design assumptions
sheet of each technology

Office space

100 square feet per employee for large
systems (excluded for small systems)

Editing the critical design assumptions
sheet of each technology

Sources: U.S. EPA (1997); AWWA (1990); AWWA/ASCE (1998); Viessman and Hammer (1993); GREPs; and information from
manufacturers and technology experts who reviewed model critical design assumptions.

Cost Estimation Method

Equipment unit costs can be derived in one of two ways. The first (and recommended) method
uses component-specific cost equations developed from unit costs collected from equipment
vendors. The component cost equations are best-fit equations (developed using statistical
regression analysis across the sizes available for each item) that estimate the unit cost of an item
of equipment as a function of its size. Under the cost equation option, the models will generate
unit costs for each item of equipment by applying the appropriate cost equation to the exact size
determined by the design calculations.

The second method uses unit cost lookup tables extracted from the WBS cost database. These
lookup tables are based on quotes from equipment manufacturers for discrete equipment sizes.
To maintain vendor confidentiality, the tables do not identify the individual vendors associated
with the quotes and the unit costs typically are averages across multiple vendors. Under the
lookup table option, for each item of equipment, the models will search the appropriate lookup
table to locate a unit cost that best meets the design requirements for the component. In general,
this means that the models will select the discrete equipment size for each item of equipment that
is equal to or greater than the size determined by design calculations.

Each model includes a critical design assumption, labeled "cost estimating method," that
determines the method used to derive equipment costs. By default, the assumption is set to 1, to
use the component-specific cost equations. The user can set the assumption to a blank value to
select the lookup table method. EPA believes the cost equations method is most appropriate for
generating national cost estimates and for most user-specified designs. Using the equations,
instead of the price quotes, allows the models to generate unit costs for equipment of the exact
size determined by the design calculations. For example, a WBS model design might require a
250 gallon steel tank, but the available price quotes might be limited to 100 gallon, 500 gallon
and various larger sizes. The cost equation for steel tanks will allow the WBS model to generate
a unit cost for the intermediate sized 250 gallon tank. The lookup table method would use the
cost for the 500 gallon tank. The models retain the lookup table method for users who wish to
examine the specific cost data points on which the component-specific cost equations are based.

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2.3.6 Index Sheet Structure and Use

Each technology model includes an index of all inputs and critical design assumptions, including
hyperlinks to their locations. Exhibit 2-9 shows an example of the index sheet. The sheet
provides an alphabetized list of all inputs and assumptions. Due to the great number of inputs
and assumptions in the WBS models, the Find feature in Excel can be useful in locating a
specific input or assumption.

Next to the description of each input or assumption is a blue, underlined hyperlink. It shows the
internal name of the input or assumption used in the engineering formulas throughout the WBS
model. Clicking on the hyperlink takes the user to the cell where the assumption can be viewed
or adjusted.

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Exhibit 2-9. Sample of Index Spreadsheet

INDEX

This page provides an index to all user-adjustable inputs and assumptions. Click on a variable name to go directly to the adjustable cells.











User-adjustable Input or Assumption

Variable Name and Link







Access space per pump/blower for custom designed systems

space pumps cust







Access space per pump/blower for pre-engineered packages

space pumps pre







Additional blower head above water depth

add blow head







Additional building after...

add 2nd building







Administrative LOE as a percent of average technical labor

Clerical oercent







Air conditioning EER

EER







Air to water ratio

air water ratio







Always include NEPA compliance costs?

include NEPA





Annual cooling degree days

cool DD







Annual heating degree days

heat DD







Average Flow

averaqe flow 1







Basin excavation depth above which deeper boreholes are needed

deep bore need







Bedding depth below pipe

beddino depth







Bedding depth surrounding the pipe

beddino pet





Blower efficiency

blower effcy







Blower safety factor

blower safetv factor







Borehole depth (package systems)

bore depth p







Borehole depth for deep basins

bore depth max







Borehole depth for shallow basins

bore depth min







Borehole needed every x square feet

hole per sf







Boreholes per job

hole perjob





Buffer space around other sides of buildings

non fire buffer







Builders risk insurance percentage

br ins pet







Building height

Building height







Coefficient of passive pressure

Coeff Kp







Communications hardware

comm hardware







Component level

component level 1







Computer workstations per x operators

workstation ratio





Concrete pad thickness

pad thick







Concrete pad thickness for small systems

Dad thick small





Concrete thickness

cone thick







Contaminant-Specific Off-gas Assumptions

contaminant lookup







Cooling table for buildings 500 square feet or greater

coolina table







Cooling table for buildings less than 500 ft2

cooling table shed







Cooling ventilation/infiltration load

cool viload







Cost for parts & maintenance for pumps and blowers

Dump maint rate







Density of air

PA







Design Flow

desiqn flow 1







Design safety factor for standby power

std safety factor







Design Type

desiqn type 1





Diffuser access space

diffuser access space







Drive controllers per blower

S blower







Drive controllers per booster pump

S booster pump





Drive controllers per catalytic oxidizer

S CO





Drive controllers per thermal oxidizer

S TO







Efficiency of pumps

pump effcy







Electric resistance heating efficiency

resist eff







Electrical percentage

elect pet







Engineering percentage for large systems

enq pet large







Engineering percentage for medium systems

eng pet medium







Engineering percentage for small systems

enq pet small





Ethernet modules

pic ethernet







Excess air required

CO ex air







Excess air required

TO ex air







External air piping

air pipe add







Financing percentage

finance pet







2.4 General Cost Assumptions

An important feature of the WBS models is that they build up cost estimates from component-
level data. Each model shows the user the cost build-up, which makes the cost estimates more
transparent, giving the user an opportunity to evaluate the impact of design and unit cost
assumptions on treatment costs. There are several types of costs that need to be aggregated into a
total cost estimate: equipment costs, building cost, residuals discharge cost, indirect capital costs,
add-on costs and annual O&M costs. The sections below describe how each type of cost enters
the WBS models.

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The build-up process for equipment costs is straightforward. The design sheets in the model
generate the required dimensions and quantities for each item in the WBS list of equipment
components and materials. Then, the model obtains unit costs to match the component size and
material (e.g., a 10-inch diameter PVC pipe or a 4,000-gallon steel backwash tank). The model
multiplies unit costs by the quantity estimate (e.g., 30 feet of pipe or 2 tanks) to obtain total
component costs. Direct capital cost equals the sum of these costs across the selected
components, including costs for treatment equipment and buildings.

The models enable equipment unit costs to be derived in one of two ways (using lookup tables or
cost equations, as described in Section 2.3.5 under "Cost Estimation Method"). Regardless of the
method used, the estimates are intended to provide enough information to establish a budgetary
or preliminary cost estimate. Therefore, although the model results are point estimates shown to
the nearest $1, this precision is not meant to imply that the results are accurate to $1. Instead,
EPA's goal is for the resulting costs to be within +30 percent to -15 percent of actual cost. To
validate the engineering design methods used by the models and assess the accuracy of the
resulting cost estimates with this goal, EPA has subjected the individual models to a process of
external peer review by nationally recognized technology experts. The technology-specific
chapters of this document include a discussion of peer reviewer opinions on the accuracy of each
model's results. Users are encouraged to review all documentation, modify inputs and
assumptions as appropriate to their specific purpose, and form their own informed opinions about
the accuracy and suitability of the results.

Consistent with providing a budgetary or preliminary cost estimate, WBS models contain several
cost-related assumptions that allow the models to produce costs for some components without
having detailed site-specific information (e.g., pipe fitting sizes). Exhibit 2-10 summarizes these
assumptions.

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WBS-Based Cost Model for Drinking Water Treatment by Ultraviolet Photolysis and Advanced Oxidation

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Exhibit 2-10. General Equipment Cost Assumptions

1.	Costs are preliminary estimates based on major components as shown on piping and instrumentation diagrams or typical
layout drawings. Costs include consideration of package plants where relevant (see model-specific chapters for more
details).

2.	All equipment costs include costs of transportation and installation.

3.	All equipment costs are based on cost quotes from manufacturers or RSMeans database.

4.	Long-term storage of chemicals (greater than 30 days) is not taken into account unless specifically mentioned.

5.	Cost of waste disposal (residuals) is accounted for using the methods outlined in Section 2.4.2 and Appendix C.

6.	Building layout is for the process itself, with room for operation, maintenance and replacing equipment, if needed.

7.	Building costs are estimated using unit costs per square foot (see Section 2.4.1 and Appendix B for more details).

8.	Costs for a reinforced-concrete pad floor to handle equipment loads are added to building costs. Costs associated with
special unit or site-specific foundation requirements are not included and should be evaluated on a case-by-case basis.

9.	To account for the cost of fittings, pipe lengths are determined by applying a multiplier to the overall system building layout
length. The resulting lengths are considered conservative (i.e., erring on the high side), so that the resulting cost covers
the installed cost of the pipe and fittings. The specific multipliers are as follows:

Combined influent and treated water pipe length is 2 times the length of the overall system building layout length.

Process pipe length is 2 times the length of the overall system building layout length.

Backwash pipe length is 2.5 times the overall system layout length.

Bypass pipe length is 2.5 times the overall system layout length.

Chemical pipe length is 1 times the overall system layout length.

Residuals pipe length is 1 times the overall system layout length.

2.4.1	Building Costs

The WBS model building costs use three sources: RSMeans 2020 Square Foot Costs (RSMeans,
2020), Saylor 2020 Commercial Square Foot Building Costs (Saylor, 2020) and the Craftsman
2020 National Building Cost Estimator software model (described in Craftsman, 2020).

Appendix B provides a detailed description of these sources and the approach to developing
building costs.

In each WBS technology model, there are four possible design configurations for buildings: three
construction design and quality categories (low, medium and high) and small, very low cost,
prefabricated ("shed-type"). The WBS models select from among these configurations based on
system size, structure size and user input for component level (see Section 2.3.2), as shown in
Appendix B. Unit costs (in dollars per square foot) for each configuration vary by structure size.
When appropriate, the WBS models add costs for building heating and cooling systems as line
items separate from the base building costs. Whether the WBS models include these systems also
depends on system size, structure type and user input for component level, as shown in Appendix
B.

As discussed in Section 2.3.2, the input sheet of each model includes optional inputs that allow
the user to choose whether or not to include the costs of buildings and HVAC systems.

2.4.2	Residuals Management Costs

Many of the treatment technologies covered by the WBS-based models generate liquid, semi-
solid (sludge) and/or solid residuals. For these technologies, each model includes a sheet that

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estimates the cost of various options for managing these residuals. The residuals management
options available for a given technology vary depending on the types of residuals generated, their
quantity, the frequency of generation (e.g., intermittent versus continuous) and their
characteristics. Examples of residuals management options include (but are not limited to): direct
discharge to surface water, discharge to a publicly owned treatment works, land disposal of
solids and storage and/or treatment of sludge or liquid waste prior to disposal or discharge. The
individual technology chapters of this document describe the specific residuals management
options available for each technology. Appendix C provides detailed information about the data
and assumptions used to estimate costs for the various residuals handling and disposal options.

2.4.3 Indirect Capital Costs

Indirect capital costs are costs that are not directly related to the treatment technology used or the
amount or quality of the treated water produced, but are associated with the construction and
installation of a treatment process and appurtenant water intake structures. Indirect costs can be
considerable and must be added to cost estimates if they are not included as a line item
component or a factor in the major (cost driver) elements of a technology. They include indirect
material costs (such as yard piping and wiring), indirect labor costs (such as process engineering)
and indirect burden expenses (such as administrative costs).

The WBS models compute the costs of site work, geotechnical investigation, yard piping and
standby power based on the system requirements, as determined during the direct capital cost
buildup. Other indirect costs are computed as a percentage of the installed process cost, building
cost or direct capital cost estimate. The indirect assumptions sheet in each WBS model (see
Section 2.3.5) contains guidance regarding a typical range of percentages for each item and
indicates the base cost to which the percentage will be applied. The guidance also describes
conditions that might require an assumption outside the range of typical values. Finally, guidance
on the output sheet notes that items such as installation costs and contractor overhead and profits
are already included in the direct capital cost estimate, but entries can be made to increase these
cost items should circumstances merit higher costs. Any of these costs can also be excluded by
modifying assumptions on the indirect assumptions sheet. Costs that are computed as a
percentage can be excluded simply by setting the percentage to zero. Those that are computed
based on system requirements can be included or excluded by setting the appropriate flag to one
or zero on the indirect assumptions sheet.

The WBS models report the total capital cost directly below this section of the output sheet so
the user can determine the impact of altering the indirect cost assumptions on total capital costs.

Appendix D provides descriptions of the default assumptions for the following indirect costs:

•	Mobilization and demobilization

•	Architectural fees for treatment building

•	Equipment transportation, installation and contractor overhead and profit

•	Construction management and general contractor overhead

•	Process engineering

•	Site work

•	Yard piping

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•	Geotechnical

•	Standby power

•	Yard wiring

•	Instrumentation and control

•	Contingency

•	Financing during construction

•	Legal, fiscal and administrative

•	Sales tax

•	City index

•	Miscellaneous allowance.

2.4.4 Add-on Costs

Add-on costs are costs that may be attributed to one or more aspects of the treatment technology.
These add-on costs include permit costs (e.g., for construction and discharge permits), pilot and
bench testing costs and land use costs. Users can include or exclude these costs by setting
appropriate flags on the indirect assumptions sheet (see Section 2.3.5).

Permits

Systems installing new treatment technologies to comply with revised drinking water standards
will often need to build a new structure to house the new treatment train and might need to build
auxiliary structures to store chemicals (e.g., chlorine, which must be stored in a separate
building). In all jurisdictions, such construction activities require a building permit and
inspections to ensure that the structure meets local building codes. New treatment trains can also
create a new waste stream or supplement an existing one. New waste streams such as new point
source discharges to surface water generally require a state or federal permit; additions to
existing flows often require revisions to existing permits. The WBS models include costs for the
following permits:

•	Building permits

•	Permits under the National Pollutant Discharge Elimination System (when residuals
discharge to surface water is present)

•	Storm water permits (for systems requiring one acre of land or greater)

•	Risk management plans (when certain chemicals are present in large quantities)

•	Compliance with the National Environmental Protection Act (included by default only at
the high cost component level - see Section 2.3.2).

Pilot Study

Site-specific pilot tests are often required by regulatory agencies to better define design
conditions and to ensure that the proposed technology will protect public health. In addition,
pilot tests and bench-scale tests can be run for non-regulatory reasons, e.g., to determine
appropriate loading and chemical feed rates, waste handling requirements or other process
parameters. Options for pre-design and pre-construction testing can include full- or small-scale
pilot studies, bench tests and desktop feasibility studies. Costs for pilot testing vary accordingly.

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Pilot studies range from inexpensive small-scale efforts to full-scale tests that might be
warranted by site-specific conditions. Three variables affecting the costs of a pilot study are:
technology requirements, testing protocols and state requirements. Some states determine test
requirements on a case-by-case basis, particularly where drinking water standards or regulations
such as noise, air emissions, plume abatement or surface water discharges (e.g., the National
Pollutant Discharge Elimination System) are relatively stringent. The diversity of state
requirements, along with the many options for pre-design testing, means that requirements for
pilot- or bench-scale studies are difficult to define. Nevertheless, the WBS models include
default pilot study costs based on vendor quotes and estimated analysis costs. The user can alter
these costs by adjusting the cost data extracted from the central WBS cost database if site-
specific conditions warrant.

Land Cost

Regardless of whether a system needs to purchase additional land on which to build the new
treatment train, there is an opportunity cost associated with using land for water treatment rather
than an alternative use. The WBS models capture this cost in a land cost estimate that is based on
the calculated land requirement (in acres) and a unit cost per acre. As discussed in Section 2.3.2,
the input sheet of each model includes an optional input that allows the user to choose whether or
not to include the cost of land.

Each model estimates land required for the treatment system, plus a 40-foot buffer on one side
for emergency vehicle access and 10 feet on the other three sides. The user can change the
assumptions about buffer spacing using the critical design assumptions sheet for each
technology.

The WBS models incorporate land costs based on unit land costs that vary by system size and
land requirements that vary by technology and system size. Average land costs per acre are
estimated as probability-weighted averages using data from the Safe Drinking Water Information
System on system size and location, data for rural land costs for 50 states and data on urban land
costs for approximately 125 cities and metropolitan areas.

2.4.5 Annual O&M Costs

The O&M costs in each WBS model include annual expenses for:

•	Labor to operate and maintain the new treatment equipment and buildings

•	Chemicals and other expendable items (e.g., replacement media) required by the
treatment technology

•	Materials needed to carry out maintenance on equipment and buildings

•	Energy to operate all equipment and provide building heating, cooling, lighting and
ventilation

•	Residuals discharge fees.

The individual technology chapters of this document describe additional, technology-specific
O&M costs.

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O&M costs calculated in the models do not include annual costs for commercial liability
insurance, inspection fees, domestic waste disposal, property insurance and other miscellaneous
expenditures that are not directly related to the operation of the technology. These costs are
highly site-specific. Users wishing to include them should add the appropriate site-specific
estimates to the model results.

The WBS models calculate annual O&M costs based on the inputs provided by the user in the
input and O&M assumptions sheet. These inputs include system size, raw and finished water
quality parameters and other factors that affect operation requirements. Appendix E contains the
design assumptions used to develop default costs for the O&M sheet.

2.4.6	Total Annualized Cost

The output sheet in each model includes an estimated useful life, in years, for each WBS
component. The models take these component useful lives from the WBS cost database. The
useful lives vary by component type (e.g., buildings generally last longer than mechanical
equipment) and by material (e.g., steel tanks generally last longer than plastic tanks). The models
use the component useful lives to calculate an average useful life for the entire system. The
calculation uses a reciprocal weighted average approach, which is based on the relationship
between a component's cost (C), its useful life (L) and its annual depreciation rate (A) under a
straight-line depreciation method. The formula below shows the reciprocal weighted average
calculation:

N

2X r

Average Useful Life = -V	= —

14, A

n=l

where:

Cn denotes the cost of component n, n=l to N
C denotes total cost of all N components

An denotes the annual depreciation for component n, which equals Cn/Ln
A denotes total annual depreciation for the N components.

The models use this average useful life for the system, along with a discount rate, to annualize
total capital cost, resulting in capital cost expressed in dollars per year. The models use a default
discount rate of 7 percent, which users can adjust directly on the output sheet. The models add
annual O&M cost to the annualized capital cost to arrive at a total annual cost in dollars per year.

2.4.7	Updating and Adjusting Costs

There are many factors that contribute to the variation in capital and O&M costs for the same
treatment technology. One variable is location, which is captured by the city index indirect cost.
Another is time—over time, the nominal price of materials, labor and land can change due to
inflation. If relative prices do not change over time (i.e., if innovative materials or production
technologies do not affect production cost relative to the price of other goods), then nominal
component prices can be adjusted using standard cost indices. The WBS cost database
incorporates the following indices to adjust prices to values in a common year:

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•	The Producer Price Index (PPI) consists of a family of indices that measure the average
trends in prices received by producers for their output (BLS, 2010). Within the PPI is the
family of commodity-based indices. The commodity classification structure of the PPI
organizes products by similarity of end use or material composition. Fifteen major
commodity groupings (at the two-digit level) make up the all-commodities index. Each
major commodity grouping includes (in descending order of aggregation) subgroups
(three-digit level), product classes (four-digit level), subproduct classes (six-digit level)
and individual items (eight-digit level). The WBS cost database assigns components to
the most closely related PPI commodity index. The selected price index for a component
is generally the index with the smallest product space. For example, prices for stainless
steel pressure vessels are escalated using a four-digit level index called BLS 1072 Metal
Tanks.

•	Building and construction costs are escalated using either the Engineering News-Record
Construction Cost Index or the Building Cost Index (ENR, 2020).

•	Labor costs are escalated using the Employment Cost Index for "not seasonally adjusted,
total compensation, private industry and public utilities" (BLS, 2000; SIC series: 252).
The Bureau of Labor Statistics releases this index quarterly. The WBS cost database
utilizes an annual average.

•	The Consumer Price Index is used to adjust land costs and components that have not been
assigned a specific PPI (BLS, 2007).

2.5	List of Abbreviations and Symbols in this Chapter

EBCT	empty bed contact time

EPA	U.S. Environmental Protection Agency

GAC	granular activated carbon

gpm	gallons per minute

GREPs	generally recommended engineering practices

HVAC	heating, ventilating and air conditioning

MGD	million gallons per day

O&M	operating and maintenance

P&ID	process and instrumentation diagram

PPI	Producer Price Index

TCE	trichloroethylene

WBS	work breakdown structure

2.6	References

American Water Works Association (AWW A). 1990. Water Quality and Treatment: A
Handbook of Community Water Supplies. Fourth Edition. New York: McGraw Hill.

A WW AJ American Society of Civil Engineers (ASCE). 1998. Water Treatment Plant Design.
Third Edition. New York: McGraw-Hill.

Bureau of Labor Statistics (BLS). 2007. BLS Handbook of Methods: The Consumer Price Index.
Updated June 2007. Retrieved from http://www.bls.gov/opub/hom/pdf/homchl7.pdf

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BLS. 2010. BLS Handbook of Methods: The Producer Price Index. Last updated 10 July.
Retrieved from http://www.bls.gov/opub/hom/pdf/homchl4.pdf

BLS. 2000. Employment Cost Indices, 1976-1999. September. Retrieved from
http://www.bls.gov/ncs/ect/sp/ecbl0014.pdf

Craftsman Book Company. 2020. 2020 National Building Cost Manual. 68th Edition.

Engineering News-Record (ENR). 2020. Building and Construction Cost Indexes. Retrieved
from http://enr.construction.com/economics/

RSMeans. 2020. 2020 Square Foot Costs. 41st Annual Edition. Rockland, Massachusetts: the
Gordian Group.

Saylor Publications, Inc. 2020. 2020 Commercial Square Foot Building Costs Manual.

U.S. Environmental Protection Agency (U.S. EPA). 1997. Discussion Summary: EPA
Technology Design Workshop. Washington, D.C.: U.S. EPA, Office of Groundwater and
Drinking Water.

Viessman, W.J. and M.J. Hammer. 1993. Water Supply and Pollution Control. 5th Edition.
Harper Collins College Publishers, New York, NY.

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WBS-Based Cost Model for Drinking Water Treatment by Ultraviolet Photolysis and Advanced Oxidation

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3. Ultraviolet Photolysis and Advanced Oxidation Process

Model

Ultraviolet (UV) light can be used on its own, or in combination with chemical addition, to
remove or reduce the concentration of organic drinking water contaminants. While this
application of UV light has relatively few installations in municipal drinking water treatment at
present, there is considerable interest in UV technologies for the treatment of organic
micropollutants that may be difficult to address with other technologies, as well as for treatment
of taste and odor.

There are several types of UV lamps and reactors for use in water treatment applications. Both
open- and closed-vessel UV reactors are in use for water treatment. However, the UV
technologies used in municipal drinking water treatment generally use closed reactor vessels. In
this scenario, two types of lamps are in wide use: low-pressure high-output (LPHO) and
medium-pressure (MP) lamps. The work breakdown structure (WBS) model considers closed-
vessel UV technologies using LPHO or MP lamps. LPHO lamps generally have lower UV light
output, so more lamps are required to treat a given flow rate. However, they are more electrically
efficient than MP lamps: they convert more of their electrical energy into UV light in the
relevant spectral region. LPHO lamps emit monochromatic UV light at a wavelength of 254
nanometers (nm), while MP lamps emit light with a broad peak below about 240 nm and several
sharper peaks above that wavelength (as high as 580 nm). Below about 200 nm, water absorbs
UV light strongly, so the wavelengths of interest are generally between about 200 and 300 nm.

In UV photolysis, pollutants are degraded by direct exposure to UV light (Crittenden et al., 2005;
Linden and Rosenfeldt, 2010). This approach is effective for contaminants that strongly absorb
UV photons in the range emitted by UV lamps. N-nitrosodimethylamine (NDMA) is one such
contaminant.

An advanced oxidation process (AOP) is a process that generates hydroxyl radicals, which react
quickly and nonselectively to oxidize contaminants. One class of AOPs uses UV light in
combination with chemical addition to generate hydroxyl radicals. There are several chemicals
that can be used, including:

•	Hydrogen peroxide (H2O2), which can be photolyzed directly to form two hydroxyl
radicals.

•	Chlorine (CI2), which, when dissolved in water, forms chlorine species that can yield both
hydroxyl and chloride radicals when irradiated by UV light

•	Ozone, which reacts with ultraviolet light to produce H2O2, which in turn reacts with
ozone to produce hydroxyl radicals

•	Titanium dioxide, which, when exposed to ultraviolet light, can catalyze the formation of
hydroxyl radicals.

AOPs can also use addition of multiple chemicals (such as ozone and H2O2) with or without UV
exposure. The WBS model for UV AOP currently includes standard designs using MP lamps for
three process types: direct photolysis, the UV-H2O2 process, and a UV-CI2 process involving

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addition of sodium hypochlorite (NaOCl). It includes standard designs for removal of two
contaminants: NDMA and 1,4-dioxane. The model might be extended in the future to include
other contaminants and/or other UV AOPs, and other WBS models might be developed for other
AOPs.

3.1 Overview of the UV AOP Treatment Process

The UV photolysis process includes the following components:

•	Feed water pumping, if required

•	The UV treatment reactor(s), including lamps, sleeves, ballasts and sensors

•	Associated piping, valves and instrumentation.

The UV-H2O2 and UV-CI2 AOPs include all of the above components, plus a feed system for the
oxidant chemical (H2O2 or NaOCl), including tanks with secondary containment, valves and
metering pumps. Exhibit 3-1 provides a schematic drawing for UV AOP. For generality, the
system is shown with parallel trains, each of which contains reactors in series, to increase the UV
dose delivered. The exhibit also shows potential post-treatment steps, which can be needed to
quench residual H2O2 and possibly to remove oxidation products. Section 3.1.4 discusses post-
treatment considerations in more detail. To account for the costs of these post-treatment steps,
the U.S. Environmental Protection Agency (EPA) has developed separate WBS models that can
generate costs for the post-treatment processes.

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Exhibit 3-1. Typical Schematic Layout for Ultraviolet Photolysis/AOP

UV Reactors

Drain

Drain

H2O2 Quenching/
Post-Treatment

Chlorine or
Hypochlorite Contact
Tank and Associated
Equipment

-OR-

Treated
Water

HX>

GAC Contactor and
Associated
Equipment

Cost from Other
WBS Models

Equipment not shown:

-	UV intensity sensors and UVT monitors

-	Oxidant day tanks (optional)

-	pH meters (optional)

-Chlorine residual monitors (optional)

LEGEND

INSTRUMENTATION

(7) Temperature (O F,ow Meter
Meter W

Optional

LINES
Influent

Treated

Oxidant (optional)

Manual
Valve

XI NJ

Check Control
Valve Valve

C$3

Ultraviolet Photolysis and AOP
Typical Schematic Layout

UV Photolysis and AOP 9-29-2021 .vsd

3.1.1 Direct Photolysis

Crittenden et al. (2005) and Linden and Rosenfeldt (2010) provide overviews of the direct
photolysis process. UV light of wavelength X, reacts with a target contaminant T with the rate:

Yt — PuvVtW fr(.^)

Where:

rr is the rate of photolysis of contaminant T due to light of wavelength X, in mol/L/s
l\ x is the intensity of UV photons of wavelength X, in Einsteins per cubic centimeter

per second (an Einstein is equivalent to one mole of photons)
fr is the fraction of UV photons that are absorbed by target contaminant %
dimensionless

(pr is the quantum yield, defined as the fraction of UV absorbance that results in
photochemical degradation, in mol/Es

For simplicity, this discussion considers only the case of monochromatic UV light. The fraction
of UV photons that are absorbed by the target contaminant is equal to:

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et(X)[T]

Where square brackets denote molarity (concentration in moles per liter), and:

st is the molar absorption coefficient for contaminant in L/mol/cm
k is the absorption coefficient for the water matrix, in cm"1

We will use absorption coefficients in base e, so that the fraction of UV absorbed in a length / of
the water matrix is equal to 1 - exp(-kl). Waters are sometimes characterized by their percent UV
transmittance (UVT), the fraction of UV light that is transmitted through 1 cm of water. The
UVT is equal to exp(-&). Measured molar absorption coefficients and quantum yields for a
variety of contaminants are available in the literature.

Combining these expressions allows us to write kr, the pseudo-first-order rate constant for
photolysis of T(expressed in seconds"1):

rT(X) = kT[T], kT = Puv(X)(pT(X)-^^

With the rate constant, we can consider how the performance of photolysis is affected by water
quality and photochemical parameters. For instance, for an ideal plug flow reactor:

[T]out f
—— = exp (~kTt)

L1 J in

Where t is the residence time of the reactor (in seconds), equal to the volume divided by flow
rate. (Note that the WBS model does not assume an ideal reactor.)

Clearly, a higher quantum yield or molar absorption coefficient will make a contaminant more
susceptible to photolysis. The intensity of UV photons, Puv, is proportional to the amount of
electrical energy input to the reactor times the efficiency with which electrical energy is
converted to UV. Water quality has two effects in photolysis. First, a higher UV absorption
coefficient (lower UVT) means that less UV energy is absorbed by the target contaminant. In
addition, more UV absorption will reduce Puv, the average intensity of UV photons in the
reactor. This effect is difficult to quantify, because in practice UV light will be partially reflected
and partially absorbed by the reactor walls and lamp sleeves. Precipitation onto the reactor
components can increase the rate of UV absorption. Note that a larger UV reactor will lose less
energy to absorption at the walls, compared to a smaller one, since the UV light has a longer path
through the water before reaching the wall (Lem, no date).

Several design parameters can be used to characterize UV energy delivery, including UV dose or
fluence, electrical energy dose (EED), or electrical energy per order of contaminant destruction
(EE/O). UV dose or fluence is a direct measure of the UV energy imparted to the water, typically
measured in units of millijoules (or milliwatt-seconds) per square centimeter. EED measures the
electrical energy input to the reactor, with units of kilowatt-hours per thousand gallons
(kWh/kgal). EE/O measures the EED required to reduce a specific pollutant's concentration by

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WBS-Based Cost Model for Drinking Water Treatment by Ultraviolet Photolysis and Advanced Oxidation

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one order of magnitude (90 percent destruction), with units of kWh/kgal per order (kWh/kgal-
order). The WBS model accepts either EED or EE/O as an input, as discussed in Section 3.2.

3.1.2 UV-H2O2AOP

In the UV-H2O2 AOP, H2O2 is injected into the water upstream of the reactor. It then undergoes
photolysis, as described above, to create hydroxyl radicals. The hydroxyl radical is a strong
oxidant and rapidly oxidizes many organic compounds.

The considerations described above for photolysis will also affect the UV-H2O2 AOP. Peroxide's
quantum yield for the production of hydroxyl radicals is effectively equal to 1—that is, on
average, half of the hydroxyl radicals produced in H2O2 photolysis enter the water matrix
(Linden and Rosenfeldt, 2010). However, H2O2 is a rather weak UV absorber. Its molar
absorption coefficient for 254 nm UV light is approximately 16.6 liters per mole per centimeter,
compared with 1,400-1,650 for NDMA and 3,300 for ozone (Crittenden et al., 2005; Linden and
Rosenfeldt, 2010). For a water with 90 percent UVT and a H2O2 dose of 5 milligrams per liter
(mg/L), the fraction of UV light absorbed by H2O2 is approximately:

(16.6 L/mol/cm) x (5 mg/L) / (34,000 mg/mol)
fH202 =	— ln(0.9) cm"1

The result of this calculation is 2.3 percent. We see, therefore, that most of the UV energy is
delivered to other parts of the water matrix and not used in the AOP. Further, because of the
weak absorption of photons, not all of the H2O2 will undergo photolysis. Section 3.1.4 discusses
treatment of the residual H2O2.

One major factor that affects all AOPs is the presence of substances that may scavenge hydroxyl
radicals before they can react with the target compound (see, for instance, Hokanson and
Trussell, 2006). Carbonate, bicarbonate, nitrogen species, natural organic matter (NOM) and
reduced metal ions may all act as hydroxyl scavengers. In addition, H2O2 itself may consume
hydroxyl radicals. The rate at which the target contaminant, is destroyed is reduced by a
factor:

		kT0H [T]	

kr.oH [T] + kH202.OH [H2O2] + Us ks,OH [S]

Where the k's are second-order rate constants with hydroxyl, and the sum on S refers to all
species that may scavenge hydroxyl. The rate constant for carbonate ions (3.9x 108 liters per
second per mole or L/s/mol) is about 45 times that for bicarbonate (8.5x 106 L/s/mol), implying
that waters with higher pH will see more scavenging for the same amount of carbonate alkalinity
(Crittenden et al., 2005). The rate constant for NOM will vary for different waters, but one study
found that it was generally between 3.Ox 108 and 4.5x 108 L/s/mol carbon in NOM (Westerhoff et
al., 1999). This is, again, much greater than the constant for bicarbonate. It is comparable to the
constant for carbonate ions, but their concentration is small for typical pH values in drinking
water treatment. NOM scavenging, therefore, will often predominate in the computation of T}t, at
least for surface waters.

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WBS-Based Cost Model for Drinking Water Treatment by Ultraviolet Photolysis and Advanced Oxidation

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All of the scavenger rate constants are smaller than those for organic contaminants. However, the
scavengers generally have much higher concentrations than the micropollutants that are
generally targeted in an AOP. Scavenging can, therefore, substantially affect the effectiveness of
an AOP.

As with direct photolysis, UV energy delivery in UV-H2O2 AOP can be characterized by UV
dose or fluence, EED, or EE/O. The WBS model accepts either EED or EE/O as an input, as
discussed in Section 3.2.

3.1.3 UV-CI2 AOP

AOP using UV-CI2 is an emerging technology that has been studied, primarily at the
demonstration scale, for treatment purposes including taste and odor control, control of emerging
contaminants (including 1,4-dioxane), and reduction of pharmaceutical and personal care
products. In the UV-CI2 AOP, chlorine is injected into the water upstream of the reactor.
Theoretically, the chlorine injection could use any of several chemical forms, including chlorine
gas, chlorine dioxide, calcium hypochlorite, or NaOCl. Those studies that identified the form of
injected chlorine, however, universally used NaOCl.

Regardless of the injected form of chlorine, studies of UV-CI2 AOP generally measure and report
the free available chlorine concentration as a key design parameter. Achieving a given free
chlorine concentration can require injecting a higher concentration of total chlorine. The
additional injection required will depend primarily on ammonia concentration because ammonia
and chlorine react to form nitrogen gas, nitrates, and chloramines.

When the injected chlorine dissolves in water, the free chlorine forms hypochlorous acid (HOC1)
and hypochlorite ion (OC1"). These chlorine species then undergo photolysis to create hydroxyl
and chlorine radicals. As discussed above, the hydroxyl radical is a strong oxidant and rapidly
oxidizes many organic compounds. The literature does not discuss the relative contribution of the
chlorine radical to the effectiveness of the UV-CI2 AOP. Bonvin et al. (2016), however, found
that the chloride radical did not appear to attack 1,4-dioxane (to form highly toxic chlorinated
dioxanes).

As with the UV-H2O2 AOP, the presence of hydroxyl radical scavengers in the influent water is a
major factor in the effectiveness of the UV-CI2 AOP. The literature agrees, however, that pH a
greater influence on the UV-CI2 AOP effectiveness than other factors because OC1- is a rapid
hydroxyl radical scavenger, but the hydroxyl scavenging rate for HOC1 is five orders of
magnitude lower (Watts et al., 2012). Exhibit 3-2 shows the relationship between these two
species at different pH values.

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WBS-Based Cost Model for Drinking Water Treatment by Ultraviolet Photolysis and Advanced Oxidation

Processes

Exhibit 3-2. pH Dependence of Chlorine Species

100

80

60

40

20

0









**

~

«*» *









bo

* i

~ Cf











L *
\ /

' #











\ '
\ 1













1 #













/ \













/ \











*

/ \
* \











*

*























8

Because of this relationship, studies that examined both UV-H2O2 and UV-CI2 AOPs generally
concluded that UV-CI2 is more effective only at pH values of 6.5 and lower, where OC1"
scavenging of hydroxyl radicals can be minimized. Rosenfeldt et al. (2013) added acid before
UV-H2O2 AOP to assure efficient oxidation. The WBS model for UV AOP does not include the
costs of this pre-treatment. EPA has, however, developed a separate acid addition WBS model
that can generate costs for this pre-treatment option.

As with other AOPs discussed here, UV energy delivery in UV-CI2 AOP can be characterized by
UV dose or fluence, EED, or EE/O. The WBS model accepts either EED or EE/O as an input, as
discussed in Section 3.2.

3.1.4 Post-Treatment Requirements

There are two important concerns about treated water from AOPs that include an oxidant (UV-
H2O2 or UV-CI2): it will contain residual oxidant and it may have increased disinfection
byproduct (DBP) formation potential due to the presence of oxidation products.

Residual Oxidants

The residual H2O2 in treated water from the UV-H2O2 AOP must be quenched prior to
distribution. H2O2 can be quenched by the addition of chlorine or hypochlorite, among other
chemicals (Collins et al., 2010). It can also be adsorbed in a granular activated carbon (GAC)
filter, where it reduces to hydrogen and water (Collins et al., 2010; Dotson et al., 2010). GAC
has the advantage of removing oxidation products, and, because the H2O2 does not remain at the
adsorption site, it likely has little effect on the lifetime of the carbon bed. Further, chlorination

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WBS-Based Cost Model for Drinking Water Treatment by Ultraviolet Photolysis and Advanced Oxidation

Processes

may exacerbate DBP formation. However, GAC's capital costs may be higher than those for
chemical addition.

Residual free chlorine from the UV-Ch AOP could be desirable in some cases, reducing the
quantity needed for primary or secondary disinfection (Robinson, 2016). Roccaro et al. (2012),
however, noted that residual chlorine following UV-Ch AOP could be much higher than
required for primary disinfection. In this case, the additional residual chlorine would require
removal by physical or chemical means.

Oxidation Byproducts

Both the UV-H2O2 and UV-CI2 AOPs will oxidize organic compounds that are already present in
the water. Depending on the nature of the organic matter, the type of UV used (LPHO or MP),
the UV and oxidant doses and perhaps the presence of other substances such as nitrate, this
oxidation may increase or decrease the DBP formation potential of the water (Chin and Berube,
2005; Dotson and Linden, 2009; Kleiser and Frimmel, 2000; Lamsal et al., 2010; Watts et al.,
2012; Rosenfeldt et al., 2013; Watts et al., 2016; Bonvin et al., 2016; Royce et al., 2015; Zhang
et al., 2015; Xiang et al., 2016; Yang et al., 2016; Wang et al., 2015b).

With such a wide variety of considerations, specific concerns about DBP precursors will likely
vary from site to site. Facilities where the AOP enhances DBP formation may then remove
oxidation products with GAC post-treatment, which, as described above, has the additional
advantage of quenching H2O2.

Post-Treatment Costs

The WBS model for UV AOP does not include the costs of post-treatment. To account for these
costs, EPA has developed separate WBS models that generate costs for the post-treatment steps.
For example, the chlorine gas, hypochlorite and GAC models are capable of estimating the cost
of post-treatment using these technologies. In generating national costs, EPA would add costs
from the separate post-treatment models to costs from the UV AOP model for scenarios that
incorporate post-treatment. At present, the GAC model includes standard designs for polishing of
treated water from the UV-H2O2 AOP. Significant operating parameters for the GAC model in
this mode include:

•	An empty bed contact time of 4 minutes (based on Dotson et al., 2010)

•	A carbon bed life of 12 months, with spent carbon regenerated off-site

•	A backwash interval of 7 days; the GAC model assumes that the capital equipment
required for management of the backwash stream is already present at the plant, but that
the increased residuals volume will increase operating and maintenance (O&M) costs.

These costs are not considered further in the UV AOP model.

3.1.5 UV Lamps, Sleeves and Ballasts

Producing UV radiation requires electrically powered UV lamps. The lamps typically used in
drinking water treatment consist of a quartz tube filled with an inert gas, such as argon, and small
quantities of mercury. Ballasts control the power to the UV lamps.

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WBS-Based Cost Model for Drinking Water Treatment by Ultraviolet Photolysis and Advanced Oxidation

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Many commercially available UV lamps operate in much the same way as fluorescent lamps.
UV radiation is emitted from electron flow through ionized mercury vapor to produce UV energy
in most units. The difference between the two lamps is that a fluorescent lamp bulb is coated
with phosphorus, which converts the UV radiation to visible light. The UV lamp is not coated, so
it transmits the UV radiation generated by the arc (White, 1992).

The LPHO and MP lamps typically used in UV treatment technologies vary in their intensity and
their emission spectra. LPHO lamps emit less light than MP lamps and emit primarily at 253.7
nm. MP lamps emit a broad range of wavelengths from 180 to 1370 nm and operate at much
higher power. A single MP lamp therefore emits more photons than a single LPHO lamp, and a
reactor using MP lamps will require fewer lamps to treat a given flow of water, typically by a
factor of 5 to 10. However, only part of the MP spectrum is effective at degrading contaminants
or photolyzing H2O2. LPHO lamps generally convert 25 to 35 percent of their input power to UV
light in the relevant part of the spectrum, with one manufacturer claiming greater than 40 percent
efficiency (Wedeco, 2010). MP lamps convert about 10 to 15 percent. MP lamps also must be
replaced more frequently, with a lifetime of roughly 4,000 to 8,000 hours, as compared to
roughly 12,000 hours for LPHO (U.S. EPA, 2006).

At present, the reactor data in the WBS model corresponds to MP lamps. EPA is presently
obtaining new data and expects to include LPHO as well as MP reactors in the future. Nothing in
the model programming depends on the lamp type.

Typically, UV lamps are enclosed in a quartz sleeve to separate the water from the lamp surface.
This arrangement is required to maintain the lamp surface operating temperature near its
optimum and prevent lamp breakage. Sleeves can foul during operation, due to deposition of
material on the interior or exterior of the sleeve. Exterior fouling is removed by a cleaning
system, as described below.

Ballasts are used to regulate the incoming power supply at the necessary level to power the UV
lamps. The efficiency of the ballast affects the fraction of electrical energy converted to UV
light. Ballasts have a design lifetime of 10 to 15 years (U.S. EPA, 2006).

3.1.6 Reactors and Sensors

Closed-channel reactors are used for drinking water applications. These reactors offer modular
design, which simplifies installation. They also minimize the exposure of personnel to UV light
(U.S. EPA, 1996). Manufacturers design their UV reactors to optimize dose distribution,
considering inlet and outlet conditions as well as the placement of lamps and baffles. Typically,
to optimize hydraulics, reactors should be installed with lengths of straight piping at the inlet and
outlet, with no more than gradual changes in diameter (U.S. EPA, 2006). Lamps are usually
installed perpendicular to the flow and may be in a criss-cross pattern. Some UV reactors are
designed so that a small number of lamps are on for routine disinfection, but more can be turned
on for seasonal or intermittent taste and odor treatment. The WBS model is designed to estimate
the cost of micropollutant treatment, rather than that of taste and odor, so it does not consider this
mode of operation.

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WBS-Based Cost Model for Drinking Water Treatment by Ultraviolet Photolysis and Advanced Oxidation

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UV intensity sensors are installed in reactors to monitor the dose administered. Some operational
strategies used for UV disinfection also require online UVT monitors. These strategies can be
useful for photolysis and AOPs, as well.

3.1.7	Point of Application

The most common point of application for UV radiation is the end of the treatment process train,
downstream of the combined filter effluent (for surface water treatment) and before the
clearwell. Upstream processes such as clarification and filtration may increase UVT and remove
scavengers, thereby benefiting the UV treatment process. It may be necessary to install reactors
below grade, to ensure that UV lamps remain submerged at all times.

3.1.8	Fouling Potential and Cleaning

In addition to turbidity, other water parameters such as hardness, alkalinity, temperature,
oxidation reduction potential and pH directly affect the rate of fouling on external surfaces of the
lamp sleeves and wetted components. The accumulation of precipitation of compounds onto the
surface of the UV sleeves and other wetted components can reduce the applied UV intensity and,
consequently, treatment efficiency. Waters containing high concentrations of iron, hardness,
hydrogen sulfide and organics are more susceptible to fouling and may require more frequent
sleeve cleaning. Studies have shown that standard cleaning protocols and wiper frequencies are
adequate to prevent fouling if the total and calcium hardness is less than 140 mg/L and iron less
than 0.1 mg/L (U.S. EPA, 2006).

Periodic cleaning of the UV system is necessary to minimize fouling of the quartz sleeves.
Cleaning systems often depend on lamp type. LPHO reactors typically use off-line chemical
cleaning. These chemical cleaning systems are self-contained and consist of chemical solution
mixing tanks, flushing pumps, tubing and provisions for draining. The frequency of chemical
cleaning varies according to the quality of the influent water. MP reactors are more likely to use
a wiper system for the sleeves (on-line mechanical cleaning), because the higher lamp
temperatures may accelerate fouling.

3.2 Input Sheet

The input sheet accepts the user-defined design parameters that determine fundamental process
requirements. The user can indicate system size and select basic equipment parameters (e.g.,
H2O2 dose). Key design considerations that the user identifies on this worksheet are described in
detail below and include the following:

•	Target contaminant

•	Process type

•	Lamp type

•	Design and average flow (see Section 2.3)

•	Contaminant removal requirement

•	Desired oxidant dose

•	Oxidant dose safety factor

•	UV energy input type and electrical energy dose (EED) or electrical energy per order of
destruction (EE/O)

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WBS-Based Cost Model for Drinking Water Treatment by Ultraviolet Photolysis and Advanced Oxidation

Processes

•	Flow distribution strategy

•	Include uninterruptible power supply (UPS)

•	Excavation

•	Number of booster pumps (optional)

•	Redundant reactors (optional)

•	Component level (optional, see Section 2.3)

•	System automation (optional, see Section 2.3)

•	Include buildings; heating, ventilating and air conditioning (HVAC) and land? (optional,
see Section 2.3)

•	Add-on (i.e., pre- or post-treatment) (optional).

Exhibit 3-3 summarizes the units and constraints (i.e., Excel validation criteria) for each of these
inputs, along with conditions under which the model generates warnings. The sections below
describe each input in greater detail.

Exhibit 3-3. Ultraviolet Photolysis and Advanced Oxidation Process Model Input

Constraints and Warnings

Input

Units

Constraints

Warning Conditions

Select Contaminant

Pick list

Pick list

None

Select Process Type

Pick list

Pick list

None

Select Lamp Type

Pick list

Pick list

None

Design flow

MGDor gpm

Greater than 0

Blank

Average flow

MGDor gpm

Greater than 0

Blank, greater than design flow or
less than 0.1 times design flow

Contaminant removal as percent

Fraction

Greater than 0

Blank or outside of minimum and
maximum constraints

Desired hydrogen peroxide dose (if
process type is UV-H2O2)

mg/L

Greater than 0

Blank

Desired chlorine dose (if process type
is UV-CI2)

mg/L as free
chlorine

Greater than 0

Blank

Dose safety factor (if process type is
not direct photolysis)

Injected

dose/desired dose

Greater than or equal
to 1

Blank

Select UV energy input type

Pick list

Pick list

Blank

Electrical energy per order
contaminant removal (EE/0) (if UV
energy input type is EE/0)

kWh/1000 gal/order

Greater than 0

Blank

Electrical energy dose (EED) (if UV
energy input type is EED)

kWh/1000 gal

Greater than 0

Blank

Flow distribution

Pick list

Pick list

Blank

Include UPS for UV power supply

Pick list

Pick list

Blank

Excavation for proper hydraulic
profile

Pick list

Pick list

Blank

Number of booster pumps

pumps

Integer greater than
or equal to 0

Pump flow is greater than maximum
for which prices are available

Redundant reactors to be added

units

Integer greater than
or equal to 0

None

Component level (optional)

Pick list

Pick list

None

System automation (optional)

Pick list

Pick list

None

Include buildings? (optional)

Yes/No/Blank

Yes/No/Blank

None

Include HVAC? (optional)

Yes/No/Blank

Yes/No/Blank

None

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WBS-Based Cost Model for Drinking Water Treatment by Ultraviolet Photolysis and Advanced Oxidation

Processes

Input

Units

Constraints

Warning Conditions

Include land? (optional)

Yes/No/Blank

Yes/No/Blank

None

CI2 = chlorine; gal=gallons; gpm = gallons per minute; H2O2 = hydrogen peroxide; kWh=kilowatt-hour; MGD = million gallons per
day; mg/L=milligrams per liter; UV = ultraviolet

Target Contaminant, Process Type and Lamp Type

STEP 1:

Select Contaminant

1,4 Dioxane

~

STEP 2:





Select Process Type

AOP (UV/CI)

~

STEP 3:





Select Lamp Type

MP

~

The WBS model for UV AOP includes three "drop-down" list boxes that allow the user to select
among standard designs for:

(1)	removal of different contaminants (i.e., NDMA or 1,4-dioxane)6

(2)	direct photolysis or AOP using UV-H2O2 or UV-CI27

(3)	lamp type.8

These boxes are located at the top of the input sheet, above the standard design buttons. The user
should verify that the selections shown in these boxes are correct before populating the other
design input values. The user can change the scenario modeled by picking different selections
from the lists. After doing so, the user should then repopulate the input sheet with values
appropriate for the new options selected by clicking one of the standard design buttons or
manually adjusting inputs and clicking the "Generate Results" button (see Section 2.3 for further
discussion of each of these methods).

Contaminant Removal Requirement

|Contaminant removal as percent	90.0%

The input sheet requires the user to enter the target contaminant destruction as a percentage. At
present, most target contaminants for photolysis and AOPs are not regulated at the Federal level.

6	The model also includes a selection in the list of contaminants entitled "1,4-dioxane (reuse train)." These standard
designs are meant to be used in conjunction with other WBS models as part of a forthcoming tool to estimate the
costs of a complete series of treatment processes that might be used as part of an advanced water treatment train for
potable reuse. Because this tool is currently under development, this document does not discuss the specific inputs
associated with the reuse train standard designs.

7	The direct photolysis option is disabled for 1,4-dioxane because that contaminant's degradation rate by direct UV
photolysis is reported to be insignificant (Martijn et al., 2010; Sharpless and Linden, 2005). The UV-H2O2 option is
disabled for NDMA based on recent data indicating that H2O2 hinders, rather than helps, NDMA photolysis (Sgroi,
2013).

8	The lamp type option is limited to MP lamps in the current model version.

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WBS-Based Cost Model for Drinking Water Treatment by Ultraviolet Photolysis and Advanced Oxidation

Processes

Therefore, the degree of contaminant destruction is site-specific. The model standard designs use
90 percent destruction (i.e., one order of magnitude).

Desired Oxidant Dose

Desired hydrogen peroxide dose



mg/L

Desired chlorine dose



mg/L as free chlorine

If the user selects AOP using UV-H2O2 or UV-CI2, the model requires input of the oxidant dose.
For UV-H2O2, the model requires the dose input in mg/L of H2O2. For UV-CI2, the dose input is
in units of mg/L measured as free chlorine. In this case, the model assumes that the chlorine is
added in the form of liquid NaOCl and calculates the amount of NaOCl required based on the
free chlorine dose.

When the user selects a process including either oxidant, the model includes capital items (e.g.,
storage tanks, metering pumps) related to the oxidant (H2O2 or NaOCl) in the cost buildup. The
oxidant dose affects the equipment sizing as well as the O&M cost of chemicals. If the user
selects direct photolysis, oxidant dose input is not required and the model excludes the capital
items related to oxidant chemicals from the cost buildup.

For AOP using UV-H2O2, the literature points to 10 mg/L as the dosage usually used for
treatment because it guarantees a high ratio of hydroxyl radicals to target contaminants under UV
light (assuming good mixing), but the hydroxyl radical concentration is still low enough that
recombination of hydroxyl radicals to H2O2 occurs at a slow rate. Accordingly, the model
standard designs for AOP using UV-H2O2 use a H2O2 dose of 10 mg/L.

For AOP using UV-CI2, studies of destruction of 1,4-dioxane that measured free chlorine used
oxidant doses that provided from 1 to 6.17 mg/L of free chlorine, with 2 to 4 mg/L being the
most common range. The model standard designs for AOP using UV-CI2 use a free chlorine dose
of 4 mg/L.

Oxidant Dose Safety Factor

Dose safety factor

1 injected dose/desired dose

For information: Injected dose

4 mg/L chlorine

Oxidant dose input OK

When the user selects AOP using either oxidant, the model requires input of a dose safety factor,
which is defined as the ratio of the injected oxidant dose to the desired dose. The safety factor
should be entered as a value greater than or equal to 1. When the safety factor is greater than 1,
the model calculations will result in an actual oxidant dose that is proportionally greater than the
desired dose. For example, a safety factor of 1.2 will result in an applied dose 20 percent greater
than the desired dose. When chlorine is the oxidant, a safety factor can be necessary to account
for the loss of free available chlorine to reaction with ammonia in the influent water. The use of a
safety factor also can be useful to account for variability or uncertainty in influent water
characteristics. The model standard designs for AOP using either oxidant use a safety factor of 1,
reflecting known influent water characteristic and limited loss of active oxidant (e.g., to reaction
with ammonia).

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WBS-Based Cost Model for Drinking Water Treatment by Ultraviolet Photolysis and Advanced Oxidation

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UV Energy Input Type and Electrical Energy Dose (EED) or Electrical Energy per
Order (EE/O)

Select UV energy input type

Electrical energy dose (EED)

<— pick one

Electrical energy per order contaminant removal
(EE/O)



kWh/1000 gal/order

Electrical energy dose (EED)

0.44

kWh/1000 gal

UV energy input OK

As discussed above, several design parameters can be used to characterize UV energy delivery.
The WBS model includes an input, entitled UV Energy Input Type, that allows users to choose
between two common measures for the UV energy required: EED or EE/O. The model then
requires the user to input a value for the selected measure. Mathematically, these two related
measures are defined by the following equations:

P

EED = 	

(Q X 60/1000)

And:

EED

EE/O = , rr lr ,

1^8 {Cin/Cout)

Where:

P is the electrical power input to the reactor, in kilowatts (kW)

O is the flow rate through the reactor, in gallons per minute (gpm)

Cm,out are the concentrations of the contaminant entering and leaving the reactor,
respectively, in any convenient units

The model uses units of kWh/kgal for EED and kWh/kgal-order for EE/O. These measures of
UV energy required can vary depending on factors including:

•	Water quality, including alkalinity, pH, UV transmittance, and NOM and other hydroxyl
scavenger concentrations

•	The susceptibility of the target contaminant to decomposition/oxidation by hydroxyl
radicals and light at various wavelengths

•	Reactor fluid dynamics

•	Lamp type

•	Oxidant dose (or lack thereof, in the case of direct photolysis).

Variations in these factors and others can lead to variations of several orders of magnitude. For
example, in a real surface water, scavenging will vary seasonally and can be difficult to predict
theoretically. Low flow rates through a reactor lead to reduced turbulence and can also result in
higher values. Manufacturers recommend pilot-testing to determine water-specific designs that
will meet treatment goals. Note, however, some pilot studies may use smaller-scale UV reactors
than will be used in a full installation. A smaller reactor will experience more UV absorption on
its walls, and will therefore have a larger energy requirement than expected for full-scale reactors
(Lem, no date).

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WBS-Based Cost Model for Drinking Water Treatment by Ultraviolet Photolysis and Advanced Oxidation

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Reviews of recent literature identified 29 different studies containing more than 350 values for
EED and/or EE/O. In the absence of site-specific data such as pilot study results, the literature
data can help users in selecting an appropriate input value. The model includes a sheet, the AOP
references sheet, presenting the data from the literature, along with information on relevant
parameters (e.g., lamp type, oxidant dose, water quality) for each reported value.

For direct photolysis and UV-H2O2, the literature most commonly reports UV energy input in the
form of EE/O. For removal of NDMA under direct photolysis using MP lamps, the literature
reports EE/O values from 1.3 to 112.1 kWh/kgal-order (Stephan and Bolton, 2002; Sharpless and
Linden, 2005). The model standard designs for this contaminant/technology combination use an
EE/O value of 2.6 kWh/kgal-order, which reflects the median of this range. Users are
encouraged to substitute water-specific and reactor-specific values when known.

For removal of 1,4-dioxane using UV-H2O2 and MP lamps, the literature reports EE/O values
from 2.3 to 11.4 kWh/kgal-order (Martiijn et al., 2010). The model standard designs for this
contaminant/technology combination use an EE/O value of 7.4 kWh/kgal-order, which reflects
the median of this range. Again, users are encouraged to substitute water-specific and reactor-
specific values when known.

The literature does not report data for removal of 1,4-dioxane using UV-CI2 and MP lamps. For
LP lamps, the literature includes data that supports the following two equations relating EED,
contaminant removal and free chlorine dose:

log (Cin/Cout) — 0.13

EED = 	————	 [from Wetterau 2015]

laOkD X l* C

Or:

log (Cin/Cout) - 0.17

EED = 	 [from Robinson 2016 data]

0.47 xFC	u	J

Where:

Cin,out are the concentrations of the contaminant entering and leaving the reactor,

respectively, in any convenient units
FC is the free chlorine dose in mg/L

Both of the equations reflect treatment of water that has already been pre-treated using reverse
osmosis. For the model standard design inputs of 90 percent removal (1-log) and 4 mg/L free
chlorine, these equations suggest an EED between 0.14 and 0.44 kWh/kgal. For purposes of
model testing, the model standard designs for removal of 1,4-dioxane using UV-CI2 use an EED
value corresponding to the upper bound of this range (0.44 kWh/kgal). However, because this
value reflects the use of LP lamps and reverse osmosis pre-treatment, users are encouraged to
substitute water-specific and reactor-specific values.

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WBS-Based Cost Model for Drinking Water Treatment by Ultraviolet Photolysis and Advanced Oxidation

Processes

Flow Distribution Strategy

Flow distribution | active flow! -

- pick one



active flow

Els I

passive flow

If there are multiple reactor trains operating in parallel, the flow through each one can be
controlled actively or passively. The input sheet requires the user to select one of these strategies.
If the flow control strategy input is set to active, the model will assume that the flow is balanced
equally across all trains. It will require that the system be fully automated and, therefore, will use
motor- or air-operated valves on each reactor. The model standard designs use this control
method.

If the flow distribution strategy input is set to passive, then the model increases the design flow
rate for each train by a safety factor percentage to account for possible imbalances in flow
distribution (U.S. EPA, 2006). The percent safety factor is specified on the critical design
assumptions sheet (see Section 3.3) and can be changed as needed.

For either distribution strategy, the model includes a flow meter for each reactor.

Include Uninterruptible Power Supply

Include UPS for UV power supply

yes!-

- pick one

Excavation for p-oper hydraulic profile

no



The model requires the user to select whether to include a UPS. A UPS provides continuous
power to the UV reactor during voltage sags or power interruptions, thereby ensuring the reactor
delivers the necessary dose. The UPS battery has a capacity large enough to power the UV
system until the electrical feed stabilizes or a generator starts. Cotton and Schultz (2005) found
that most UV disinfection systems in the field do not include a UPS. The model standard designs
do not include a UPS.

Excavation

1 Excavation for proper hydraulic profile

no



-- pick one



yes

F configuration inputs OK|

To prevent overheating and damage to UV equipment, the UV lamps should be submerged at all
times (U.S. EPA, 2006). This may require installing the UV reactors below grade to maintain the
necessary hydraulic profile. The model requires the user to select whether or not to include
excavation to achieve this profile. If excavation is required, the model will install the reactors
below grade. The specific depth can be adjusted on the critical design assumptions sheet (see
Section 3.3). The model standard designs do not include excavation.

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WBS-Based Cost Model for Drinking Water Treatment by Ultraviolet Photolysis and Advanced Oxidation

Processes

Number of Booster Pumps

Number of booster pumps

0 pumps

For information: # of booster pumps'

0 pumps

Review of actual as-built designs for small systems using various technologies (U.S. EPA, 2004)
shows that these systems often can operate without additional booster pumps using existing
supply pump pressure. Therefore, the model assumes zero booster pumps for small systems (less
than 1 million gallons per day design flow). For larger systems, the model calculates the number
of pumps using a method that attempts to minimize the number of pumps, while still
accommodating variations in flow and providing redundancy to account for possible equipment
failure. The model includes an optional input that allows the user to change these default
calculations by specifying the number of pumps required to operate the treatment system. If the
user enters zero, the model excludes booster pumps from the design and cost estimate. Cotton
and Schultz (2005) found that roughly one-third of UV disinfection systems in the field used
booster pumps. The model standard designs enter zero for this input for all system sizes,
excluding booster pumps.

Redundant Reactors

| Redundant reactors to be added	un'ts

This input sheet allows the user to specify the number of redundant reactors for the facility. If the
user leaves this input blank, the model calculates the number of redundant vessels based on a
redundancy frequency specified on the critical design assumptions sheet. The model standard
designs leave this input blank, resulting in one redundant unit per ten operating units, with a
maximum of two redundant reactors.

Add-On (Pre- or Post-Treatment)

Add-on (pre- or post-treatment)



- pick or leave blank



add-on





The WBS model for UV AOP includes an optional input that allows the user to specify that the
AOP treatment system is an addition to an existing treatment plant, intended as pre- or post-
treatment for another primary treatment process. When the user selects "add-on" for this input,
the model changes certain assumptions and calculations to reflect this scenario. Specifically, the
model excludes (or reduces the quantity or size of) certain capital components that would already
be present at the existing treatment plant. For example, the model includes only the incremental
system control components that would be required to integrate with the existing treatment
process control system. It includes O&M cost items because the model calculates them on an
incremental basis (e.g., the labor hours cover only the additional hours required to operate the
new UV AOP system).

In the "add-on" scenario, the model also excludes certain indirect costs that would be required in
constructing a full new treatment plant. Specifically, the model does not include yard piping,
because installing the add-on process should not require additional exterior pipelines. It also does
not include standby power costs, because the additional electrical demand from the add-on

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process should not require significant additional standby capacity. Except when excavation is
selected, it excludes geotechnical costs, because the pre-existing geotechnical survey for the
treatment plant should be sufficient to cover the construction associated with the add-on process.
When excavation is needed to maintain the hydraulic profile, however, the model includes
geotechnical costs because additional surveying may be needed for this excavation.

Finally, although the UV AOP system is assumed to be an addition to an existing treatment plant
in the add-on scenario, the model does include the full cost of buildings and land for the
incremental footprint of the process. While some treatment plants might be able to accommodate
the new process within existing space, others will require expansion to house the process.
Therefore, the inclusion of buildings and land is conservative (i.e., errs on the side of higher
costs) in terms of the actual cost of installing the process. Furthermore, even where existing
buildings and land are sufficient, the use of this existing space represents an economic
opportunity cost that is appropriate to include in regulatory cost estimates.

3.3 Model Assumptions Sheets

There are three sheets that contain assumptions needed to facilitate process design: the critical
design assumptions sheet, the O&M assumptions sheet and the indirect assumptions sheet. These
sheets contain a variety of structural and chemical engineering parameters used in the
engineering design sheets. There are more than 100 critical design assumptions in the model that
cover process, O&M and indirect cost parameters. Key critical design assumptions include
instrumentation requirements, frequency of parts replacement and maintenance, excavation
depth, oxidant solution characteristics, safety factor for passive flow distribution and storage
requirements. The following sections provide descriptions and default values for these
assumptions. Any assumption value can be modified, as needed.

Instrumentation Requirements

The critical design assumptions sheet specifies that each facility will have three reference UV
intensity sensors (used to ensure that the operating intensity sensors, which are included in the
costs for each reactor, are correctly calibrated). For direct photolysis, it specifies one UVT
monitor (used to monitor UV transmittance) and one redundant UVT monitor (included only
when an operating UVT monitor is specified). For UV AOP using either oxidant, it includes one
UVT monitor for influent plus one per treatment line after oxidant addition, based on the process
control scheme recommended in Antolovich and Robinson (2016). When chlorine is the oxidant,
it also includes one pH meter per treatment line, because of the importance of influent pH (see
Section 3.1.3). It also includes two chlorine residual analyzers per treatment line (before and
after the reactors) to calculate reduction of chlorine as a control point (Antolovich and Robinson,
2016).

Frequency of Parts Replacement and Maintenance

Parts that need to be periodically replaced include ballasts, mechanical wiper rings, UV sensors,
quartz sleeves and lamps. Of these, the replacement costs of wiper rings and sleeves are
generally incidental. The model therefore accounts for replacement costs for ballasts, sensors and
lamps. Lifetimes of these parts are based on estimates from industry representatives and the UV
Disinfection Guidance Manual (Swaim, 2007; Young, 2007; U.S. EPA, 2006):

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•	Ballasts, 10 years

•	UV intensity sensors, 5 years

•	MP UV lamps, 5,000 hours of operation.

Among the maintenance assumptions in the model is the frequency of sleeve visual exams. The
model assumes four exams per year based on data from the UV Disinfection Guidance Manual
(U.S. EPA, 2006). Section 3.8 identifies other maintenance assumptions. Users can change any
of the replacement and maintenance assumptions on the O&M assumptions sheet.

Excavation Depth

When the user specifies excavation on the input sheet, as described in Section 3.2, the model
assumes reactors are installed 5 feet below grade to maintain hydraulic profile and ensure
reactors remain submerged.

Oxidant Solution Characteristics

H2O2 is delivered at a common commercial grade, but added to water as a dilute solution
(Crittenden et al., 2005). The model assumes delivery of 50 percent grade H2O2 solution and feed
at a dilute concentration of 5 percent. For NaOCl, the model assumes the solution is delivered
and fed at the common commercial grade of 12.5 percent as chlorine.

Safety Factor for Passive Flow Distribution

When the user specifies a passive flow distribution strategy on the input sheet, as described in
Section 3.2, the model increases the design flow rate for each train by a safety factor of 20
percent (U.S. EPA, 2006).

Storage Requirements

The frequency, quantity of use and availability of chemicals used on-site determines the size of
chemical storage facilities. For H2O2, the model assumes 30 days of storage capacity. AWWA
(2010) reports that NaOCl solution should not be stored for more than 15 to 25 days. Therefore,
the model assumes 20 days of storage capacity for this oxidant. The model also includes storage
space for spare parts and ancillary equipment equal to 20 percent of the reactor footprint.

3.4 Train Design Sheet

The design of the reactor is determined by the peak influent flow, the specified EED or EE/O and
the required contaminant removal. The train design sheet uses the EED or the EE/O and required
contaminant removal to calculate the total power requirement for the system. It then examines a
table of reactor data that is part of the lookup tables ancillary sheet (see Section 3.11) to find the
smallest reactor that will provide the required power. Each column in this table contains a
reactor's flow capacity and power output, as well as further design information such as hydraulic
capacity, number of lamps and reactor dimensions.

When the model finds the reactor that has the nearest power output, it uses that value in
conjunction with the total power requirement to determine the total number of reactors. To
determine the number of trains operating in parallel, it divides the design flow by the hydraulic
capacity of the selected reactor. Reactors are then placed in series in the trains to provide the
required amount of UV energy.

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The train design sheet then retrieves information on the reactor footprint and material
requirements from the same table, for use in later calculations. Finally, if the user specified that
reactors be installed below grade, this sheet will determine the excavation requirements.

3.5	Oxidant Addition Sheet

The oxidant addition sheet calculates the quantities of oxidant needed, based on the assumed
concentration listed on the critical design assumptions sheet and the user inputs for design flow
and chemical dose. The sheet also calculates the number and size of chemical tanks needed based
on user inputs for design flow and chemical dose. The model assumes separate day tanks, in
addition to the primary bulk storage tanks, are required if daily oxidant usage at design flow
exceeds a number of gallons specified on the critical design assumptions sheet. To provide
secondary containment for the tanks, this sheet also includes calculations for concrete curbing
around the storage area and chemical resistant coating for the curbing and the underlying
concrete pad.

3.6	Pumps, Pipe and Structure Sheet

Other elements of the technology for which the size and cost need to be determined include
pumps and piping. The pumps, pipe and structure sheet performs the required calculations to
determine the number and size (in terms of flow capacity) of the following pumps:

•	Booster pumps (if required)

•	Oxidant metering pumps (if required).

This sheet uses the input values for flow and water quality parameters, as well as the parameters
on the critical design assumptions sheet, to determine the number of pumps needed, including
redundant units. Pump sizing depends on the maximum corresponding flow rate. For example,
booster pumps are sized based on the system design flow and oxidant pumps are sized based on
the oxidant solution flow. As discussed in Section 2.3, the sizing of all pumps incorporates a
safety factor, which is specified on the critical design assumptions sheet.

This sheet also performs calculations for the following pipes:

•	Influent and outlet piping

•	Process piping

•	Drain piping

•	Oxidant piping (if required).

The size (diameter) of pipes is determined using the design flow and a look-up pipe flow chart
that is part of the WBS cost database. The pipe diameter selection method incorporates a
reasonable head loss and flow velocity, as documented in Exhibit 2-8. These design assumptions
may result in some over sizing of pipes, which means the costs for pipes may be conservative
(i.e., err on the high side).

The flow used to determine influent and treated water pipe size is the design flow. The diameter
of interconnecting process piping uses the same pipe flow chart, after splitting the inflow by the
number of parallel treatment trains. A similar approach is used in determining the size and
capacity of oxidant piping. Assumptions that affect pipe length are in Exhibit 2-10, except as

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described above for the process pipe. In addition, the model assumes a length for the reactor
drain pipe equal to the facility length.

This sheet also calculates the required housing area for this technology based on the footprint of
the treatment components and the spacing criteria specified on the critical design assumptions
sheet. The space requirements for reactors, pumps, tanks and service space are based on
manufacturer specification, "to scale" drawings and the experience of engineers. The amount of
additional concrete needed to support heavy equipment, such as pumps and tanks, is based on the
footprint of the tanks and pumps.

For smaller space requirements (less than a square footage specified on the critical design
assumptions sheet), the model assumes a single building containing all process equipment. For
larger requirements, the model assumes two buildings, one that contains treatment equipment
and power supplies and one that contains office space. The number of buildings affects the total
land required and energy costs for heating, ventilating and cooling.

3.7	Instrumentation and Control Sheet

The instrumentation and control sheet calculates requirements for valves, instrumentation (e.g.,
flow meters) and automated system controls. UV reactor systems come with some control
features. These control features range from simple alarm and shutoff control to programmable
logic controllers that manage lamps and UV units. The instrumentation and control sheet models
the system needs to control other equipment that is connected to the UV reactors, including the
oxidant delivery system. The number of valves and instruments is based on the number of
process components (e.g., number of treatment lines) and assumptions from the critical design
assumptions sheet (e.g., number of valves per treatment line). The assumptions correspond to the
general schematic layout for this technology shown in Exhibit 3-1. Sizing of valves corresponds
to the size of the appropriate pipe determined on the pumps, pipe and structure sheet. Appendix
A describes the method used in the WBS models to estimate the number and type of system
control components.

This sheet also determines the size of a UPS for the UV reactors, if required, and determines its
footprint using a table that is part of the lookup tables ancillary sheet (see Section 3.11).

3.8	O&M and HVAC Sheets

The O&M and HVAC calculations cover two sheets: the O&M sheet (annual labor, materials
and energy usage) and the HVAC sheet (HVAC capacity requirements). The O&M sheet derives
O&M requirements based on the engineering design, O&M critical design assumptions and input
values. It determines the following O&M requirements based on the approach outlined in Section
2.4 and Appendix E:

•	Operator labor for system operation and maintenance

•	Managerial and clerical labor

•	Booster pump maintenance materials and operating energy

•	Building and HVAC maintenance materials

•	Energy for building lighting and HVAC.

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In addition, the O&M sheet adds the following technology-specific O&M requirements:

•	Energy for operation of the UV lamps and control panels

•	Labor for the UV process system, including component replacement and cleaning

•	Replacement lamps, ballasts and UV intensity sensors

•	Disposal of spent lamps, ballasts and UV intensity sensors

•	Usage of oxidant.

The energy required to operate the UV lamps and control panels is determined by the parameters
of the reactor selected in the train design sheet and the average flow specified by the user. The
model determines the power required to provide this output at the beginning and end of lamp
life, using the relationship between power and UV output specified on the O&M assumptions
sheet. It computes the average power draw per lamp by averaging the power required at the
beginning and end of lamp life.

Replacement requirements for lamps, ballasts and UV intensity sensors are calculated explicitly
using the respective useful life assumptions specified on the O&M assumptions sheet (see
Section 3.3). Disposal costs for the spent items assume the spent materials are classified as
hazardous waste, although the user can change this assumption on the critical design assumptions
sheet. Chemical usage also is calculated explicitly based on the outputs of the oxidant addition
sheet.

The model makes the following assumptions regarding labor:

•	20 minutes to visually inspect a quartz sleeve for fouling

•	1.5 hours to replace a ballast

•	15 minutes to replace a UV intensity sensor

•	5 minutes to replace a UV lamp

•	30 minutes per month per UV sensor to perform calibration checks

•	30 minutes per week per UVT analyzer to perform calibration checks

•	1 hour per reactor to perform automatic cleaning system effectiveness checks

•	10 minutes per reactor for inspection for manual systems

•	10 minutes per day for reporting for manual systems.

It is assumed that other reporting labor is included in the model's managerial and clerical
allowances. Users can change the unit labor hours for the UV process on the O&M assumptions
sheet.

3.9 Indirect Sheet

As stated in Section 2.4, indirect capital costs are costs that are not directly related to the
treatment technology used or the amount or quality of the finished water, but that are associated
with the construction and installation of a treatment technology and water intake structures. The
indirect sheet derives capital costs for the following components of indirect costs:

•	Construction management and general contractor overhead

•	Standby power

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•	Geotechnical

•	Sitework

•	Yard piping.

Appendix D contains detailed information on the derivation of these and other indirect capital
costs. This sheet also contains calculations to estimate permit costs.

3.10	Output Sheet

The output sheet contains the list of components identified for UV AOP based on the WBS
approach. For each component, the output sheet provides information on size (e.g., tank capacity
or pipe diameter) and quantity, as well as estimated capital cost and estimated useful life. The
output sheet also contains cost estimates for indirect capital costs (e.g., mobilization and
demobilization, site work and yard piping), add-on costs (for permitting, pilot testing and land)
and O&M costs. These estimates are described generally in Section 2.4 and in more detail in
Appendix D (indirect capital costs) and Appendix E (O&M costs). Finally, the output sheet
combines the total capital cost, system useful life and annual O&M cost to estimate total
annualized cost, as discussed in Section 2.4. Sections 2.1 and 2.3 provide further details about
the output sheet.

As discussed in Section 2.4, the output sheet shows model results to the nearest $1, but this
precision is not meant to imply that the results are accurate to $1. The UV AOP model
underwent peer review in 2007. One peer reviewer responded that the costs in general seemed
reasonable and the annual operating costs were consistent with those at a comparison installation.
A second reviewer commented that the costs in general were reasonable, but that the costs for
electrical components and annual O&M were under-estimates. The third reviewer thought the
total installed capital costs were conservative (i.e., erring on the side of higher costs). EPA made
substantive revisions to the UV AOP model in response to the peer review, including specific
revisions recommended by the second reviewer to address the under-estimates for electrical
components and O&M. Users are encouraged to review all documentation, modify inputs and
assumptions as appropriate to their specific purpose, and form their own informed opinions about
the accuracy and suitability of the results shown on the output sheet.

3.11	Ancillary and Reference Model Components

The UV AOP model contains four ancillary sheets: index, standard inputs, cost equations, cost
coefficients, cost data, engineering data and lookup tables. The index is a hyperlinked list of
user-adjustable inputs and assumptions that can assist the user in finding these inputs and
assumptions, should they wish to change them. The standard inputs worksheet documents the
inputs used in the standard designs. Advanced users can adjust these standard inputs, if desired.
The cost equations and cost coefficients sheets use the component-level cost curve equations
from the WBS cost database to generate unit costs on an item-by-item basis. The cost data and
engineering data sheets contain component cost and engineering reference data extracted from
the central cost database. The lookup tables contain information about footprints for
uninterruptible power supplies of various capacities, UV reactor parameters as described in
Section 3.4, dose requirements and factors used in computing a validation factor. This sheet is
also used internally in populating the drop-down boxes on the model input sheet. The UV AOP
model also includes a reference sheet presenting EED and EE/O data from the literature, along

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with information on relevant parameters (e.g., lamp type, oxidant dose, water quality) for each
reported value.

3.12 List of Abbreviations and Symbols in this Chapter

AOP	advanced oxidation process

Ch	chlorine

DBP	disinfection byproduct

EED	electrical energy dose

EE/O	electrical energy per order of contaminant destruction

EPA	U.S. Environmental Protection Agency

GAC	granular activated carbon

gpm	gallons per minute

H2O2	hydrogen peroxide

HOC1	hypochlorous acid

HVAC	heating, ventilating and air conditioning

kW	kilowatts

kWh/kgal	kilowatt hours per thousand gallons

kWh/kgal-order kilowatt hours per thousand gallons per order of destruction

LPHO	low-pressure-high-output

L/s/mol	liters per second per mole

mg/L	milligrams per liter

MP	medium-pressure

NaOCl	sodium hypochlorite

NDMA	N-nitrosodimethylamine

nm	nanometers

NOM	natural organic matter

O&M	operating and maintenance

UPS	uninterruptible power supply

UV	ultraviolet

UVT	UV transmission

WBS	work breakdown structure

3.13 References

Antolovich, A. and K. Robinson. 2016. Optimizing AOP to Solve Water Reuse Challenges.
Xylem webinar. 20 May.

AWWA. 2010. Principles and Practices of Water Supply Operations: Water Treatment. Denver,
CO: AWWA.

Barazesh, J.M., T. Henneble, J.T. Jasper and D.L. Sedlak. 2015. "Modular Advanced Oxidation
Process Enabled by Cathodic Hydrogen Peroxide Production." Env. Sci. & Tech. 49: 7391-7399.

Beerendonk, E.F., D.J. Harmsen, D.H. Metz, A.H. Knol, J. Geboers and G.F. IJpelaar. 2009.
New DBD-lamp combines the advantages of the mercury LP and MP UV lamps for UV/H202
oxidation. Presented at American Water Works Association Water Quality Technology
Conference. November.

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WBS-Based Cost Model for Drinking Water Treatment by Ultraviolet Photolysis and Advanced Oxidation

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Benotti, M.J., B.D. Stanford, E.C. Wert and S.A. Snyder. 2009. "Evaluation of a photocatalytic
reactor membrane pilot system for the removal of pharmaceuticals and endocrine disrupting
compounds from water." Water Research 43: 1513-1522.

Bertelkamp, C., K. Lekkerkerker-Tenissen, A.H. Knol, J.Q.J.C. Verberk, J.C. van Dijk and C.J.
Houtman. 2010. Granular Activated Carbon Filtration or Ion Exchange as Pre-Treatment
Option for the Advanced Oxidation Process; Advantages and Limitations. Presented at American
Water Works Association Water Quality Technology Conference. November.

Bonvin, F., E. Marron, J. Barazesh and D. Sedlak. 2016. UV/Chlorine: elucidating the role of
chlorine radical in 1,4 dioxane degradation. Presented at WateReuse Research Conference.

May.

Bradshaw, G. 2007. UV Oxidation for Groundwater Recharge Reuse at West Basin. Presented at
American Water Works Association Water Quality Technology Conference. November.

Chan, P.Y., M.G. El-Din and J.R. Bolton. 2012. "A solar-driven UV/chlorine advanced oxidation
process." Water Research 46: 5672-5682.

Chin, A. and P. R. Berube, 2005. "Removal of disinfection byproduct precursors with ozone-UV
advanced oxidation process." Water Research 39:2136-2144.

Collins, J., C. Cotton, S. Jousset, A. Dotson, K. Linden. 2010 Evaluation of Hydrogen Peroxide
Quenching Alternatives for AOP TreatmentPresented at American Water Works Association
Water Quality Technology Conference. November.

Cotton, C. and K. Schultz. 2005. Malcolm Pirnie, Inc. UV Disinfection Cost Update: Current
North American UV Facility Costs. Presented at American Water Works Association Water
Quality Technology Conference. November.

Cotton, C.A. and J.R. Collins. 2006. Dual Purpose UV Light: Using UV light for Disinfection
andfor Taste and Odor Oxidation. AWWA Presented at American Water Works Association
Water Quality Technology Conference. November.

Crittenden, J.C., S. Hu, D.W. Hand, and S.A. Green. 1999. "A Kinetic Model for H202/UV
Process in a Completely Mixed Batch Reactor." Water Research Vol. 33, No. 10, pp. 2315-2328.

Crittenden, J.C., R.R. Trussell, D.W. Hand, K.J. Howe, G. Tchobanoglous. 2005. Water
Treatment: Principles and Design. Second edition. Hoboken: John Wiley and Sons.

Dotson, A.D., and K. Linden. 2009. Effect of advanced oxidation (UV/ H2O2) followed by
chlorination on the formation of disinfection by-products. Presented at American Water Works
Association Water Quality Technology Conference. November.

Dotson, A.D., C. Rowley, M. Downs, C.J. Corwin, and K.G. Linden. 2010. UV/H2O2: Dynamics
of bench scale quenching of hydrogen peroxide by GAC. Presented at American Water Works
Association Water Quality Technology Conference. November.

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Freibert, J. 2004. Infilco Degremont, Inc. Personal communication with Jon Fetter (SAIC).

Hokanson, D.R. and R.R. Trussell, 2006. Understanding the Impact of Water Quality onAOP
Effectiveness in Removing Persistent Organic Pollutants. Presentation at the 10th Annual Water
Reuse Research Conference. 15-16 May.

Jin, J., M.G. El-Din and J.R. Bolton. 2011. "Assessment of the UV/Chlorine process as an
advanced oxidation process." Water Research 45: 1890-1896.

Kleiser, G. and F.H. Frimmel. 2000. "Removal of precursors for disinfection by-products
(DBPs)—differences between ozone- and OH-radical-induced oxidation." The Science of the
Total Environment 256:1-9.

Lamsal, R., et al. 2010. Comparison of advanced oxidation processes in mitigating natural
organic matter and disinfection by-product precursors. Presented at American Water Works
Association Water Quality Technology Conference. November.

Lekkerkerker-Teunissen, K., A.H. Knol, J.G. Derks, C.J. Houtman, E.F. Beerendonk, J.Q.J.C.
Verberk and J.C van Dijk. 2010. Performance comparison of LP vsMP UV lamps for advanced
oxidation process. Presented at American Water Works Association Water Quality Technology
Conference. November.

Lem, W. no date. Scale-up of a Medium Pressure UV System for the Treatment of N-
Nitrosodimethylamine and its Advantages Over Low Pressure UV Systems. Calgon Carbon Corp.

Li, K., D.R. Hokanson, J.C. Crittenden, R.R. Trussell and D. Minakata. 2008. "Evaluating
UV/H202 processes for methyl tert-butyl ether and tertiary butyl alcohol removal: Effect of
pretreatment options and light sources." Water Research 42: 5045-5053.

Li, L., S. Patton, K. Ishida and H. Liu. 2016. Comparison of Four UV/AOPs for Water Reuse:
Implications on the Removal of Emerging Contaminants. Presented at WateReuse Research
Conference. May.

Linden, K.G. and E.J. Rosenfeldt. 2010. "Ultraviolet Light Processes." Chapter 18 of Water
Quality and Treatment: A Handbook on Drinking Water, sixth edition, ed. James K. Edzwald.
New York: McGraw Hill.

MacNevin, D. 2016. Where Wastewater Ends and Drinking Water Begins. Presented at
WateReuse Research Conference. May.

Martijn, B.J., A.L. Fuller, J.P. Malley, and J.C. Kruithof. 2010. "Impact of IX-UF Pretreatment
on the Feasibility of UVH202 Treatment for Degradation of NDMA and 1,4-Dioxane " Ozone
Science & Engineering 32: 383-390.

Metz, D.H. 2012. The Effect of Natural Organic Matter on UV/H202 Treatment and the Effect
of UV/H202 Treatment on Natural Organic Matter. PhD Dissertation at University of
Cincinnati.

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Meyer, M., D. Metz, Y. Le Gouellec, R. Kashinkunti, and E. Beerendonk. 2009. Energy
efficiency evaluation of benchmarked UV/H2O2 pilot reactors for EDC destruction with
conventional and GAC-contacted water. Presented at American Water Works Association Water
Quality Technology Conference. November.

MIOX. 2017. Case Study: Groundwater Remediation at the Aerojet Rocketdyne Site. Available
at http://www.miox.com/documents/MIOX Aerojet Case Study - Digital Low Res.pdf.
Accessed 26 May.

Montgomery Watson Harza. 2007. Final Report: City of San Diego Advanced Water Treatment
Research Studies. August.

Muller, Jennifer. 2004. Trojan Technologies. Personal communication with Jon Fetter (SAIC).

Neiminski, E.C. Date unknown. Role oflJV in Recent Regulations and State Perspective on UV
Approval. Utah Department of Environmental Quality. Copy of slide presentation.

Oppenheimer, J., K.-P. Chiu, J. DeCarolis, M. Kumar, S. Adham, S. Snyder and W. Pearce.
2006. Evaluating the Effect of UV Peroxide for Control of NDMA on Endocrine Disrupters,
Pharmaceuticals, and Personal Care Products. Presented at American Water Works Association
Annual Conference and Exposition.

Pagan, J. and O. Lawal. 2015. "Proposed Testing Protocol for Measurement of UV-C LED Lamp
Output." IUVA News 17(2): 7.

Paradis, N. and R. Hofmann. 2006. Mitigation of Taste and Odour Compounds by UV/H202
Advanced Oxidation. Presented at American Water Works Association Water Quality
Technology Conference. November.

Patton, S., W. Li, K.D. Couch, S.P. Mezyk, K.P. Ishida and H Liu. 2017 "Impact of the
Ultraviolet Photolysis of Monochloramine on 1,4-Dioxane Removal: New Insights into Potable
Water Reuse." Ijiviron. Sci. Technol. Lett. 4: 26-30.

Robinson, K. 2016. UV/Chlorine AOP for Potable Reuse: Lower Cost Option. Presented at
Water Reuse in Texas. San Marcos, Texas. 15 June.

Robinson, K. 2015. UV AOP for Potable Reuse. Presented at WateReuse Annual Symposium
IUVA AOP Workshop. September.

Rocarro, J., P. Brandt, S. Meyerdierks, E. Rosenfeldt and A. Royce. 2012. Advanced Oxidation
for 1, 4 Dioxane and VOC Removal From Drinking Water: Results of a Demonstration-Scale
Pilot Study. Presented at American Water Works Association Annual Conference and
Exposition.

Rosenfeldt, E., A.K. Boal, J. Springer, B. Stanford, S. Rivera, R.D. Kasinkunti and D.H. Metz.
2013. "Comparison of UV-mediated Advanced Oxidation." Journal of the American Water
Works Association 105(7): 29-33.

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Royce, A., A. Festger, M. Stefan and G Wetterau. 2015. A Full-Scale Demonstration Study
Comparing UV/C12 and UV/H202for the Treatment of 1,4-Dioxane in Potable Reuse. Presented
at WateReuse Annual Symposium. September.

Salveson, A., A. Parker, N. Fontaine and H. Wright. 2015. Optimizing AOP for Potable Water
Reuse Applications. Presented at WateReuse Annual Symposium. September.

Sgroi, Massimiliano. 2013. Formation and Control of N-Nitrosodimethylamine (NDMA) in
Wastewater Reclaimedfor Indirect Potable Reuse. Universita degli Studi di Catania, Piazza
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Sharpless, C.M. and K.G. Linden. 2005. "Interpreting collimated beam ultraviolet photolysis rate
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Shu, Z., J.R. Bolton, M. Belosevic and M.G. El Din. 2013. "Photodegradation of emerging
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Sichel, C., C. Garcia and K. Andre. 2011. "Feasibility Studies: UV/Chlorine Advanced
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80.

Stefan, M.I. and J.R. Bolton. 2002. "UV Direct Photolysis of N-Nitrosodimethylamine (NDMA):
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Sutherland, J., C. Adams and J. Kekobad. 2004. "Treatment of MTBE by air stripping, carbon
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Swaim, P.D., R. Morgan, L. Foster, P. Mueller, M. Vorissis and W. Carter. 2008. Implementing
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WBS-Based Cost Model for Drinking Water Treatment by Ultraviolet Photolysis and Advanced Oxidation

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Appendix A. Valves, Instrumentation and System Controls
A.1 Valves in the WBS Models

There are many types of valves used to control water and chemical flow rates, pressure and
direction in a water treatment plant. Valves can be distinguished by function, mode of operation,
materials of construction, size (i.e., diameter), design or shape and connection method. For
purposes of estimating valve costs, the most important of these distinctions are function, mode of
operation, size and materials of construction. Therefore, the work breakdown structure (WBS)
models group valves according to these four distinctions. The WBS models identify valve size
explicitly, using the same methodology used to size pipes. The WBS models also explicitly
identify materials of construction. The output sheet of each model includes line item costs for
valves of each material (plastic, stainless steel and cast iron), so that the user can observe
variations in cost among materials.

To distinguish by function and mode of operation, the WBS models use a generic nomenclature.
The WBS models identify valves as one of the following:

•	Check valves

•	Manual valves

•	Motor/air-operated valves.

Check valves are those that serve the function of backflow prevention. They generally do not
vary significantly in mode of operation or design/shape.

The other two categories of valves serve the function of flow control and are distinguished by
their mode of operation (i.e., whether they are manual or automated). An example of a valve that
must be a manual valve is an emergency shut-off valve that, in an extreme event such as
complete power failure, can be shut off by an operator. Manual valves can vary in design
according to their specific opening/closing method (e.g., hand wheel or chain). Automated valves
(identified in the WBS models as motor/air operated) can be motor-operated valves, air-operated
valves or solenoid valves. Solenoid valves are electrically operated on/off control valves. Motor-
operated valves open and close more slowly than solenoid valves. This action reduces likelihood
of a water hammer. While the different opening/closing methods for manual and automated
valves have various advantages and disadvantages, cost differences among designs are relatively
small and the WBS unit costs do not distinguish between them at this level of detail. The key
cost difference is whether the valves are automated or manual, because of the cost of the motor,
air actuator or solenoid.

A.2 Instrumentation for Process Measurements

Each of the models includes the cost of various instruments that perform process measurements.
Most of these measurement devices are categorized into the following groups:

•	Hydraulic measurement instruments and control devices. Hydraulic measurement
instruments include: flow meters, pressure gauges, head loss sensors and water level
meters/alarms. Hydraulic control devices include: pump control, motor control and valve
control.

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• Water quality measurement and control devices. These include water quality parameter
measurement devices, such as pH meters, oxidation-reduction potential (ORP) sensors,
temperature meters, turbidity meters and sampling devices and ports.

The WBS models determine instrumentation requirements for each technology based on review
of the schematic flow diagram for the appropriate technology, along with certain general
assumptions that are applied to all of the technologies. Exhibit A-l documents the general
assumptions about instrumentation that are applied in the WBS models. Slightly different
assumptions hold when a model is intended as an add-on to an existing process (e.g., acid feed)
rather than a complete process (e.g., anion exchange).

Exhibit A-1. General Design Assumptions for Instrumentation

Instrument Type

Assumption

Chlorine analyzers

Varies by technology; for chlorine and hypochlorite disinfection, 1 per treatment train
to monitor residual

Conductivity meters

Varies by technology

Dissolved oxygen analyzers

Varies by technology

Drive controllers

1 per each pump (including booster, backwash and chemical metering pumps) or
other motorized item of equipment (e.g., mixers, blowers) in fully automated systems

Electric enclosures

Only for technologies with significant electric-powered equipment outside a building
structure

Flow meters

Varies by technology; usually 1 for the influent or treated water line and 1 for
backwash discharge. Some technologies also include flow meters on process lines.

Head loss sensors

Continuous level sensors. 1 per process vessel for technologies with pressure
vessels. Some technologies omit head loss sensors for systems with design flows
less than 1 million gallons per day.

High/low alarms

1 per backwash tank and 1 per chemical storage tank

Level switch/alarms

1 per process basin; 2 per contact tank for chemical disinfection technologies.
Technologies with chemical cleaning use 1 or 2 per chemical tank in the cleaning
system.

ORP sensors

Varies by technology

Particle meters

Varies by technology

pH meters

1 each for the influent and treated water lines for systems with pH adjustment, plus
others on a technology-specific basis

Pressure transducers

Included in the cost of flow meter assemblies for venturi and orifice plate meters

Sampling ports

Varies by technology; usually 1 per process vessel, plus 1 each for the influent line,
treated water line and discharge side of the backwash line for complete process
models. Others are included on a technology-specific basis.

Total dissolved solids monitors

Varies by technology

Temperature meters

Varies by technology; often 1 for the influent and/or treated water lines, except for
add-on models. Some technologies omit temperature meters for systems with design
flows less than 1 million gallons per day.

Total organic carbon analyzers

Varies by technology

Turbidity meters

Varies by technology

Several types of flow meters can appear in the model output: propeller, venturi, orifice plate and
magnetic flow meters. In general, the choice of meter depends on the cost level and design flow
of the system, although some technologies require particular types of flow meters for specific
purposes. For smaller and/or low-cost systems, the preference order in the models will have
propeller flow meters as a first choice; for intermediate systems, venturi flow meters top the

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preference order; and for larger and/or high-cost systems, the top preference is magnetic flow
meters. In all cases, the component buildup will display the price for all available types of flow
meters at a given size, so that a user can assess the cost impact of different types.

The critical design assumptions sheet of each model incorporates these general assumptions.
Therefore, the user can adjust instrumentation assumptions on a technology-specific basis.

Individual technologies—in particular, aeration technologies and chlorine and hypochlorite
disinfection—have additional or differing instrumentation requirements.

A.3 Control Systems

Automated control systems comprise the hardware and software used to monitor and control a
treatment process. There are two general types of systems: programmable logic controls (PLCs)
and/or remote telemetry units (RTUs). PLCs are stand-alone microprocessor-based control
systems that can be programmed to monitor and control process equipment. RTUs were
originally developed to communicate with systems from remote, outdoor locations. Newer RTU
models can provide full equipment control through remote operator interface (AWW A, 2001).
Because the WBS cost models (except for the nontreatment model) pertain to centralized
treatment facilities, the assumptions reflect the control of all system components using a PLC
system; RTUs are generally more appropriate for remote communications.

PLC hardware consists of a rack-mounted system with plug-in slots for the input and output
(I/O) modules, which provide connections for the instruments and equipment, and one or more
central processing unit (CPU) modules, which process the monitoring data inputs and control
command outputs. The PLC equipment requires a power supply unit to operate the PLC data and
command processing functions. In addition, an uninterruptible power supply (UPS) will protect
the PLC system from undesired features such as outages and surges that can adversely affect the
performance of the PLC unit. A system operator can monitor and operate with the PLC using
either a computer or an operator interface unit, which is a panel mounted on the PLC enclosure.
These units can be as simple as 2-line light-emitting diode text panels or as advanced as full
color touch panels. The WBS models have default assumptions that PLC systems for smaller
drinking water systems will be operated using an advanced, fully-functional operator interface
unit after the control system installer has programmed the PLC. Larger systems will include an
operator interface unit with more limited functionality and use at least one computer workstation
with PLC programming software and printers to accomplish more advanced control functions
from a central location. Large systems also include plant intelligence software to assist operation
of the extensive control system.

The PLC system design in the WBS models depends on the design of the treatment system,
which dictates the total number and type of I/O connections. The PLC system receives input
signals from and transmits output signals to ports on instruments and equipment controllers. The
I/O signals may be discrete or analog, depending on the type of equipment generating or
receiving the signals. Discrete signals indicate which of two conditions apply such as whether a
switch is on or off. Analog signals indicate a value along a predefined range such as temperature
or rate of flow. Exhibit A-2 identifies the assumptions used in the WBS models to determine the
total number of I/O connections required for the PLC system.

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Exhibit A-2. I/O Port Requirements for Instrumentation and Control

Instrument Type

Inputs to and Outputs from PLC System

Alarm (level switch/alarm, high/low alarm or low alarm)

1 input and 1 output—discrete

Chlorine analyzer

1 input—analog

Conductivity meter

1 input—analog

Dissolved oxygen analyzer

1 input—analog

Drive controller

3 inputs (1 for the auto switch position, 1 for the run status signal
and 1 for overload or fault signal) and 1 output—discrete

Flow meter

1 input—analog

Venturi and orifice plate meters also include inputs and outputs
for the associated pressure transducer (below)

Head loss sensor

1

nput—discrete

Motor/air-operated valve

1

nput and 1 output—analog

ORP sensor

1

nput—analog

Particle meter

1

nput—analog

pH meter

1

nput—analog

Pressure transducer

1

nput—analog

Sampling port

1

nput—discrete

Total dissolved solids monitor

1

nput—discrete

Temperature meter

1

nput—analog

Total organic carbon analyzer

1

nput—analog

Turbidity meter

1

nput—analog

The degree of automated control at a treatment facility can range from none to a fully automated
control system that can monitor and control the hydraulic regime at the plant, the chemicals
addition system, the power system and the communication system. To reflect potential ranges in
treatment costs, the WBS models can provide equipment and operator labor cost outputs for
three degrees of control:

•	Fully automated control with safety overrides

•	Semi-automated control where instruments provide data and information to the control
station, but operators manually activate valves and mechanical equipment (e.g., this
option removes outputs from the PLC system and removes automated drive controllers
from mechanical equipment)

•	Fully manual control where operators collect data directly from the instruments and
manually activate valves and mechanical equipment.

Users can select among these three control schemes using the system automation input in each
WBS model (see Section 2.3). Exhibit A-3 shows the general design assumptions about control
equipment used for each control scheme in the WBS models. The paragraphs below provide
additional information regarding the equipment components and calculations.

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Exhibit A-3. General Design Assumptions for System Controls



Small

Medium

Large



Item of Control Equipment

System
(<1 MGD)

System
(1-10 MGD)

System
(>10 MGD)

WBS Assumption

PLC Rack/Power Supply

A,S

A,S

A,S

1 base and expansion bases
as needed for I/O (see text)

CPU

A,S

A,S

A,S

2 per system1

I/O Discrete Output Module

A

A

A

1 for every 32 outputs2

I/O Discrete Input Module

A,S

A,S

A,S

1 for every 32 inputs2

I/O Combination Analog Module

A,S

A,S

A,S

1 for every 12 inputs (for A
and S) and outputs (for A
only)3

Ethernet Module

A,S

A,S

A,S

2 per system1

Base Expansion Module

A,S

A,S

A,S

1 per expansion base

Base Expansion Controller Module

A,S

A,S

A,S

1 per expansion base

UPS

A,S

A,S

A,S

1 per system

Operator Interface Unit - limited
functionality

NA

A,S

A,S

2 per system1 (see text)

Operator Interface Unit - advanced,
fully functional

A,S

NA

NA

2 per system1 (see text)

Computer Workstations

NA

A,S

A,S

1 per operator

Printers

NA

A,S

A,S

1 per 4 workstations

PLC Programming Software

NA

A,S

A,S

1 per workstation

Operator Interface Software

A,S

NA

NA

1 per system

PLC Data Collection Software

NA

A,S

A,S

1 per workstation

Plant Intelligence Software

NA

A,S

A,S

1 per workstation

A = included in a fully automated system; S = included in a semi-automated system; NA = not applicable for this design size
Notes: Fully manual systems do not include system controls

1.	Includes one to provide redundancy

2.	Discrete input and output modules can have fewer I/O connections, but price differences are small. To keep the equipment
requirement calculation tractable, the WBS models use a 32-connection module, which will slightly overstate cost when fewer
connection points are needed on the last module.

3.	A combination module accommodates 8 inputs and 4 outputs. This 2-to-1 ratio is generally consistent with the ratio of analog
inputs-to-outputs in the WBS models for a fully automated system.

The primary PLC system is a rack and power supply (i.e., a "base") with nine slots for control
modules.9 The CPU module requires one slot. An ethernet module necessary for PLC
programming requires a second slot, leaving seven for I/O modules. If additional I/O slots are
needed to accommodate instruments and equipment, then up to four additional expansion bases
can be added, giving the single CPU the capacity to run up to 8,192 I/O connections. Each
expansion base has nine module slots and is linked to the CPU module on the primary base.

The total number of PLC racks and power supplies include the primary rack and any expansion
racks. The calculation for the total number of racks must take into account the module slots that
will be occupied by all types of modules including the CPU module, the ethernet module and
expansion base controller modules. Each expansion rack requires a base expansion controller
module, which occupies one of the module slots on the expansion rack, leaving eight slots for

9 Bases with fewer slots are also available, but cost differences across base sizes are small. To keep the equipment
requirement calculation tractable, the WBS models use a 9-slot base, which will slightly overstate cost when fewer
slots are needed.

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I/O modules. Each expansion rack also requires a base expansion module, which is attached to
the outside of the rack and, therefore, does not require a module slot. The following calculations
illustrate how the WBS models calculate total PLC racks:

IF (pic cpu + pic ethernet + pic discrete input + pic discrete output +
pic combination analog) < 9

THEN pic rack = 1, pic base expansion = 0, pic base expansion controller = 0

IF (pic cpu + pic ethernet + pic discrete input + pic discrete output +
pic combination analog) > 9 AND <17

THEN pic rack = 2, pic base expansion = 1, pic base expansion controller = 1

IF (pic cpu + pic ethernet + pic discrete input + pic discrete output +
pic combination analog) >17 AND < 25

THEN pic rack = 3, pic base expansion = 2, pic base expansion controller = 2

IF (pic cpu + pic ethernet + pic discrete input + pic discrete output +
pic combination analog) > 25 AND <33

THEN pic rack = 4, pic base expansion = 3, pic base expansion controller = 3

IF (pic cpu + pic ethernet + pic discrete input + pic discrete output +
pic combination analog) >36 AND <41

THEN pic rack = 5, pic base expansion = 4, pic base expansion controller = 4

A.5 References

American Water Works Association (AWW A). 2001. Instrumentation and Control, Manual of
Water Supply Practices—M2. Third Edition. Denver, Colorado: AWWA.

A.4

CPU

I/O

ORP

PLCs

RTUs

UPS

WBS

List of Abbreviations and Symbols in this Appendix

central processing unit
input and output
oxidation-reduction potential
programmable logic controls
remote telemetry units
uninterruptible power supply
work breakdown structure

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Appendix B. Building Construction Costs
B.1 Introduction

The work breakdown structure (WBS) cost database incorporates building costs from three
sources: RSMeans 2020 Square Foot Costs (RSMeans, 2020), Saylor 2020 Commercial Square
Foot Building Costs (Saylor, 2020) and the Craftsman 2020 National Building Cost Estimator
(NCBE) software model (described in Craftsman, 2020). Each of these sources enables a user to
create a cost estimate by combining costs for different elements of a building—for example, the
foundation, exterior walls or light fixtures.

For each source, the WBS cost database includes three sets of options to represent low, medium
and high building design and material qualities. Section B.2 provides descriptions of the relevant
options for each source within these categories, as well as the options selected for each of the
three building types used in the WBS models. The WBS models cost heating and cooling
systems as individual capital cost line items separate from the building construction costs.
Therefore, the building costs discussed here exclude heating and cooling systems.

For each of the three types of building, EPA used the three sources described here to develop
cost buildups for 24 building sizes ranging from 500 to 200,000 square feet and tabulated costs
for each of the models. The resulting costs from each model are included in the WBS cost
database. The database escalates these costs from 2020 dollars using the Engineering News-
Record Building Cost Index (ENR, 2020) and averages them following the same procedure as
for other components, as described in Chapter 2. The WBS models use these costs to estimate
costs per square foot for buildings larger than 500 square feet (ft2).

EPA also developed a fourth building type that applies only to structures smaller than 500 ft2—
essentially a shed with steel walls and a roof. This additional building type allows the WBS
models to use, for very small systems, building costs that reflect very inexpensive building
construction methods and materials. For this type of building, EPA used the Craftsman NCBE
model to estimate costs for a low-profile steel building. However, the WBS models do not use
this building type for chlorine storage buildings because chlorine gas use necessitates a non-
corrodible building material and special ventilation requirements. Thus, for chlorine storage
buildings smaller than 500 ft2, the WBS models use the same unit costs as for larger buildings.

B.2 Buildup Options and Building Quality Selections

EPA developed building cost estimates using comparable assumptions across data sources: the
Craftsman NBCE model, building costs from RSMeans 2020 Square Foot Costs and Saylor 2020
Commercial Square Foot Building Costs. Each source provides unit costs for different building
types and construction qualities.

The Craftsman NBCE model is a software model that generates building cost estimates based on
user input (i.e., building size and quality of building features and fixtures). Given the variation in
unit costs for components by size, it appears to function as a parametric model. The costs in the
NBCE model are based on data obtained from U.S. government building cost surveys.

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The RSMeans and Saylor manuals contain unit costs, usually in dollars per square foot, for
various building components (e.g., exterior walls, floor structure or roof structure). The costs are
based on data obtained from the construction industry and independent research of construction
costs. By combining unit costs across components, one can build up a total building unit cost.
The approach is essentially a WBS cost approach where most components are priced on the basis
of building area, with little or no variation in the cost per unit area as building size increases. For
example, the RSMeans unit cost for a foundation slab varies with the thickness of the slab (EPA
chose thicker slabs for higher quality buildings), but not with the building size. Notable
exceptions are the cost of exterior walls and roof structures. Exterior wall cost in dollars per ft2
declines as building size increases because the ratio of exterior wall linear footage to square
footage declines. For roof structures, EPA chose roof spans based on the length of a side of the
building (assumed square). For building side lengths greater than 70 feet, EPA included support
columns to give a maximum roof span of 70 feet. Larger buildings, therefore, may have
somewhat more expensive superstructures on a per-square-foot basis, since they may have a
wider roof span or support columns.

EPA chose inputs to the NBCE model and chose components from the RSMeans and Saylor
manuals to reflect the different levels of building quality used in the WBS models (high,
medium, low and very small low quality).

Based on the NBCE industrial building quality classifications, EPA determined that the NBCE
Class 1&2 (best/good quality), Class 3 (average quality) and Class 4 (low quality) reflected WBS
high, medium and low quality buildings, respectively. EPA used the NBCE low-profile steel
building for very small low quality buildings.

The RSMeans and Saylor manuals do not contain building types that are closely comparable to
the very small low quality building. Therefore, there are no RSMeans or Saylor costs for this
type of structure. RSMeans and Saylor building cost estimates were "built" by selecting specific
building elements of differing quality for each type of building from the assemblies sections of
their respective manuals.

From each source, EPA obtained cost estimates for the following building areas in square feet:
500; 1,000; 2,000; 3,000; 4,000; 5,000; 7,500; 8,000; 10,000; 12,000; 15,000; 18,000; 20,000;
24,000; 25,000; 30,000; 36,000; 42,000; 48,000; 50,000; 54,000; 60,000; 100,000 and 200,000.
The resulting costs do not include costs for site improvements (e.g., land, landscaping, parking
and utilities), permits, furnishings and production equipment, homeland security responses or
contingency allowance.

The RSMeans and Saylor costs include installation costs as well as overhead and profit for the
contractors installing the building components, but do not include architectural fees or general
contractor markup for general conditions, overhead and profit (RSMeans, 2020; Saylor, 2020).
According to Craftsman (Ogershok, 2009), the NBCE model's costs do not include installing
contractor markup directly, but do include a markup of 30 percent for the general contractor,
which they assume to also cover the installing contractor's markup. Since the Craftsman costs
were generally lower than those from Means or Saylor and since the installing contractor's
markup in Means and Saylor is usually 30 percent or more, EPA assumed that the 30 percent
markup in the Craftsman costs was passed along directly to the installing contractor and further

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markup would be required for the general contractor. Architectural fees and the general
contractor's markup are included in the WBS model indirect cost output, as described in
Appendix D.

Each source has a different set of options. They can be grouped into six categories:

•	Substructure

•	Superstructure

•	Exterior closure

•	Interior finish

•	Mechanical services, excluding heating and cooling

•	Electrical services.

B.2.1 Substructure

Building substructure was selected using application scenarios for each of the three quality
options. For low quality buildings, EPA assumed an average industrial use scenario. For medium
quality buildings, EPA assumed a heavy industrial use scenario. For higher quality buildings,
EPA assumed a heavy industrial with live loads use scenario. EPA assumed light foot traffic for
the very small (less than 500 ft2) buildings (other than those used to store chlorine gas).

Exhibit B-l shows the detailed choices that EPA made for each of the three sources.

Exhibit B-1. Substructure Selections for NBCE, RSMeans and Saylor

Building
Variable

Lower Quality Building

Medium Quality
Building

Higher Quality Building

Very Small Lower
Quality Building

Craftsman
NBCE

Foundation: reinforced
concrete pads under
pilasters.

Floor. 6" rock base, 4"
concrete with reinforcing
mesh.

Foundation: continuous
reinforced concrete.
Floor. 6" rock base, 5"
concrete with reinforcing
mesh or bars.

Foundation: continuous
reinforced concrete.
Floor. 6" rock base, 6"
concrete with reinforcing
mesh or bars.

Foundations as required
for normal soil conditions;
a 4" concrete floor with
reinforcing mesh and a 2"
sand fill.

RSMeans

Foundation: poured
concrete; strip and spread
footings.

Slab: 4" reinforced,
industrial concrete with
vapor barrier and granular
base. Site preparation for
slab and trench for
foundation wall and
footing. 4' foundation wall.

Foundation: poured
concrete; strip and spread
footings.

Slab: 5" reinforced, heavy
industrial concrete with
vapor barrier and granular
base. Site preparation for
slab and trench for
foundation wall and
footing. 4' foundation wall.

Foundation: poured
concrete; strip and spread
footings.

Slab: 6" reinforced, heavy
industrial concrete with
vapor barrier and granular
base. Site preparation for
slab and trench for
foundation wall and
footing. 4' foundation wall.

not applicable

Saylor

Foundation: concrete strip
and spread footings, 4'
foundation wall.

Slab on grade: reinforced
concrete, vapor barrier, 4"
thick, on 4' sand or gravel
base.

Foundation: concrete strip
and spread footings, 4'
foundation wall.

Slab on grade: reinforced
concrete, vapor barrier, 5"
thick, on 4' sand or gravel
base.

Foundation: concrete strip
and spread footings, 4'
foundation wall.

Slab on grade: reinforced
concrete, vapor barrier, 6"
thick, on 4' sand or gravel
base.

not applicable

' = feet;" = inches

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B.2.2 Superstructure

EPA assumed the same quality of superstructure for each of the three quality options—metal
deck and open web steel joists, supported by columns and exterior walls. However, the
superstructure support column spans range up to 70 feet, depending upon building size. To
establish the column span, EPA computed the length of a building side, assuming the building to
be square. For buildings with side lengths larger than 70 feet, EPA included support columns in a
square grid to provide a roof span of 70 feet or less, assuming that the roof would also be
supported on the exterior walls. For instance, a 10,000 ft2 building (100 feet on a side) would
have one support column in the center, with a 50 foot roof span. A 30,000 ft2 building (173 feet
on a side) would have four support columns at 58 foot intervals. Since the sources included roof
spans in increments of 10 feet, EPA rounded up to a 60 foot roof span for this building. EPA
used a steel building quality superstructure for the very small (less than 500 ft2) buildings (other
than those used to store chlorine gas).

Exhibit B-2 displays the superstructure options that EPA selected for each source.

Exhibit B-2. Superstructure Selections for NBCE, RSMeans and Saylor

Building
Variable

Lower Quality Building

Medium Quality Building

Higher Quality Building

Very Small
Lower
Quality
Building

Craftsman
NBCE

Roof structure: glu-lams wood or
steel trusses on steel intermediate
columns, short span. Roof cover.
panelized roof system, 1/4" plywood
sheathing, 4-ply built-up roof. 10 ft2
of skylight per 2,500 ft2 of floor
area (1-2'x 4'skylight 40' to 50'

O.C.).

Roof structure: glu-lams
wood or steel trusses on
steel intermediate columns,
short span. Roof cover:
panelized roof system, 1/4"
plywood sheathing, 4-ply
built-up roof. 24 ft2 of skylight
per 2,500 ft2 of floor area (1-
4'x 6' skylight 40' to 50' o.c.).

Roof structure: glu-lams
wood or steel trusses on
steel intermediate columns,
span exceeds 70'.

Roof cover: panelized roof
system, 1/4" plywood
sheathing, 4-ply built-up
roof. 32 ft2 of skylight per
2,500 ft2 of floor area (1-4'x
8' skylight 40' to 50' o.c.).

Steel roof
purlins 4!4
to 5!4 feet
on centers,
26-gauge
galvanized
steel on
roof

RSMeans

Roof. 1.5" galvanized metal deck,
open web steel joists, joist girders,
on columns and walls; total load =
60-65 lbs/ft2. Column spacing
chosen to give a maximum span of
70', with the building assumed
square. Steel columns.

Roof cover: Built-up tar and gravel
roof covering with flashing,
perlite/EPS composite insulation.
Roof hatches with curb.

Same as lower quality

Same as lower quality

not

applicable

Saylor

Roof: metal deck, open web steel
joists, on columns and walls. Wide
flange steel columns, steel beams
and girders. Column spacing
chosen to give a maximum span of
70', with the building assumed
square.

Roof cover: built-up tar and gravel.

Same as lower quality

Same as lower quality

not

applicable

' = feet;" = inches; EPS = expanded polystyrene; o.c. = on center

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B.2.3 Exterior Closure

EPA used different building exterior qualities to estimate unit costs that vary by exterior
material. EPA selected reinforced concrete block exteriors for the lower quality buildings,
reinforced tilt-up concrete panel exteriors for the medium quality buildings10 and brick-faced,
reinforced cavity/composition wall exteriors for the higher quality buildings. EPA used
corrugated metal exteriors for the very small lower quality structures (smaller than 500 ft2).

A cavity wall (e.g., masonry) is a wall in which the inner and outer wythes are separated by an
air space, but tied together with wires or metal stays. A composition wall is a wall combining
different materials to work as a single unit. A tilt-up wall is a method of concrete construction in
which wall sections are cast horizontally at a location adjacent to their eventual position and
tilted into place after removal of forms.

Exhibit B-3 shows the exterior closure options that EPA selected for each model.

Exhibit B-3. Exterior Closure Selections for NBCE, RSMeans and Saylor

Building
Variable

Lower Quality Building

Medium Quality
Building

Higher Quality Building

Very Small Lower
Quality Building

Craftsman
NBCE

8" reinforced concrete
block or brick, unpainted.
(Same for both lower and
medium quality.)

8" reinforced concrete
block or brick, unpainted.
(Same for both lower and
medium quality.)

8" reinforced concrete
block or brick with
pilasters 20' on centers,
painted sides and rear
exterior, front wall brick
veneer

Steel frames/bents set 20'
to 24' on centers, steel
wall girts 3/4' to 4/4' on
centers, post and beam
type end wall frames, 26-
gauge galvanized steel
on ends and sides

RSMeans

Concrete block,
reinforced, regular weight,
hollow, 4x8x16', 2,000 psi

Tilt-up concrete panels,
broom finish, 5/4" thick,
3,000 psi

Brick face composite wall-
double wythe: utility brick,
concrete block backup
masonry, 8" thick, perlite
core fill.

not applicable

Saylor

Concrete block, 4x8x16',
reinforced

Tilt-up concrete panel, 6"
thick, no pilasters.

Brick cavity wall,
reinforced, 10" thick.

not applicable

' = feet;" = inches; psi = pounds per square inch
B.2.4 Interior Finish

Choices of interior finish reflect the quality and duty of the interior construction materials such
as floor coverings, wall coverings and ceilings. EPA selected functional, minimally attractive
interior finishes for the lower quality buildings and more functional and attractive interiors for
medium and higher quality buildings. EPA also selected functional, unattractive interior finishes
for the very small (less than 500 ft2) buildings (other than those used to store chlorine gas).

Exhibit B-4 shows the interior finish options that EPA selected for each source.

10 Tilt-up concrete panel exteriors were selected in the RSMeans and Saylor cost estimation buildups. Tilt-up
concrete panels were not an exterior option in the Craftsman NBCE cost estimation model; therefore, reinforced
concrete block exterior was selected in the Craftsman NBCE cost estimation model for medium quality buildings.

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Exhibit B-4. Interior Finish Selections for NBCE, RSMeans and Saylor

Building
Variable

Lower Quality Building

Medium Quality
Building

Higher Quality Building

Very Small Lower
Quality Building

Craftsman
NBCE

Concrete floors. Rest
rooms: unfinished
wallboard partitions and 2
low cost fixtures.

Concrete floors. Rest
rooms: painted gypsum
wallboard partitions and 2
average fixtures.

Concrete floors. Rest
rooms: enameled gypsum
wallboard partitions, 3
good fixtures, vinyl
asbestos tile floors.

Minimal quality, minimal
duty, functional,
unattractive

RSMeans

One minimal quality 2-
fixture restroom per 5,000
ft2 building area.
Unpainted walls.

Concrete floors.
Fiberglass ceiling board
on exposed grid system
covering 10 percent of
building area.

One minimal quality 2-
fixture restroom per 5,000
ft2 building area. Painted
walls. Vinyl composition
tile floors covering 10
percent of building area.
Fiberglass ceiling board
on exposed grid system
covering 10 percent of
building area.

One high quality 3-fixture
restroom per 5,000 ft2
building area. Acrylic
glazed walls. Vinyl
composition tile floors
covering 10 percent of
building area. Fiberglass
ceiling board on exposed
grid system covering 10
percent of building area.

not applicable

Saylor

One restroom per 5,000
ft2 building area, with 2
economy fixtures, baked
enamel partitions.
Unpainted walls.
Concrete floors. Ceiling:
5/8" gypsum board on
metal frame, covering 10
percent of building area.

One restroom per 5,000
ft2 building area, with 2
standard fixtures, baked
enamel partitions. Painted
walls. Vinyl composition
floor covering 10 percent
of building area. Ceiling:
5/8" gypsum board on
metal frame, covering 10
percent of building area.

One restroom per 5,000
ft2 building area, with 3
standard fixtures, baked
enamel partitions. Painted
walls. Vinyl composition
floor covering 10 percent
of building area. Ceiling:
5/8" gypsum board on
metal frame, covering 10
percent of building area.

not applicable

' = feet;" = inches

B.2.5 Mechanical Services

Mechanical services include fire protection, plumbing, heating, ventilation and cooling. The
WBS models cost heating and cooling systems as individual capital cost line items separate from
the building construction costs, so the mechanical services included in the building costs are
limited to fire protection, plumbing and ventilation. EPA assumed no sprinkler systems for the
lower quality buildings and normal hazard wet sprinkler systems for medium and higher quality
buildings. EPA also assumed no sprinkler systems for the very small (less than 500 ft2) buildings
(other than those used to store chlorine gas).

Exhibit B-5 shows the mechanical services options that EPA selected for each source.

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Exhibit B-5. Mechanical Services Selections NBCE, RSMeans and Saylor

Building
Variable

Lower Quality Building

Medium Quality
Building

Higher Quality Building

Very Small Lower
Quality Building

Craftsman
NBCE

No sprinklers. 1 small
rotary vent per 2,500 ft2 of
floor area.

Sprinklers. 1 medium
rotary vent per 2,500 ft2 of
floor area. (Same for both
medium and higher
quality.)

Sprinklers. 1 medium
rotary vent per 2,500 ft2 of
floor area. (Same for both
medium and higher
quality.)

Minimal quality, minimal
duty, functional, no
sprinklers

RSMeans

Gas-fired water heater.
No sprinklers.

Gas-fired water heater.
Wet pipe sprinkler
system. (Same for both
medium and higher
quality.)

Gas-fired water heater.
Wet pipe sprinkler
system. (Same for both
medium and higher
quality.)

not applicable

Saylor

Gas-fired water heater (1
per 5,000 ft2), 50 gallon,
100 GPH. No sprinklers.

Gas-fired water heater (1
per 5,000 ft2), 50 gallon,
100 GPH. Exposed wet
sprinkler system, normal
hazard. (Same for both
medium and higher
quality.)

Gas-fired water heater (1
per 5,000 ft2), 50 gallon,
100 GPH. Exposed wet
sprinkler system, normal
hazard. (Same for both
medium and higher
quality.)

not applicable

' = feet;" = inches; GPH = gallons per hour

B.2.6 Electrical Services

EPA included the cost of light fixtures and convenience power, along with associated wiring and
conduits. EPA selected inexpensive lighting fixtures that provide minimal lighting and a minimal
number of wall switches and receptacles for the lower quality buildings and selected increasingly
expensive lighting fixtures that provide bright lighting and an increased number of wall switches
and receptacles for the medium and higher quality buildings. EPA also selected minimal lighting
fixtures for the very small (less than 500 ft2) buildings (other than those used to store chlorine
gas).

EPA did not include electrical feed, switchgear, motor control centers, etc. in building costs.
These costs are likely to vary significantly by technology for buildings of the same size and
quality; for example, a mid-sized reverse osmosis system and a small packaged conventional
filtration system might occupy roughly the same footprint in similar buildings, but the reverse
osmosis system will likely have much greater power requirements. It is therefore not appropriate
to base these costs on the building's area or quality. These costs are included in the indirect cost
buildup based on a percentage of process cost, as described in Appendix D.

Exhibit B-6 shows the electrical services options that EPA selected for each source.

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Exhibit B-6. Electrical Services Selections for NBCE, RSMeans and Saylor

Building
Variable

Lower Quality Building

Medium Quality
Building

Higher Quality Building

Very Small Lower
Quality Building

Craftsman
NBCE

Lighting: low cost
incandescent fixtures,
20'x30' spacing

Lighting: low cost single
tube fluorescent fixtures
20'x20' spacing

Lighting: 4" single tube
fluorescent fixtures
10'x12' spacing

Minimal quality, minimal
duty, basic wiring and
minimal lighting fixtures

RSMeans

Lighting: Incandescent
fixtures recess mounted,
type A: 1 W/ft2, 8 FC. 6
lighting fixtures, 1 wall
switch and 2.5
receptacles per 1,000 ft2.
1 W miscellaneous
power.

Lighting: Fluorescent
fixtures recess mounted
in ceiling: T-12, 40 W
lamps, 2 W/ft2,40 FC. 10
lighting fixtures, 2.5 wall
switches and 5
receptacles per 1,000 ft2.
1.5 W miscellaneous
power.

Lighting: Fluorescent
fixtures recess mounted
in ceiling: T-12, 40 W
lamps, 4 W/ft2, 80 FC. 20
lighting fixtures, 5 wall
switches and 10
receptacles per 1,000 ft2.
3 W miscellaneous
power.

not applicable

Saylor

Lighting: Incandescent
fixtures, surface mounted,
100 W, commercial
grade, 10 per 1,000 ft2 for
1 W/ft2 total. 1
commercial grade single-
pole switch and 2.5
commercial-grade duplex
receptacles per 1,000 ft2.
In slab/PVC conduit and
wire for 60 A current,
length assumed equal to
building perimeter for a
square building.

Lighting: Fluorescent
fixtures, recessed, 2 13 W
bulbs each, 16 per 1,000
ft2 for 2 W/ft2 total. 2.5
commercial grade single-
pole switches and 5
commercial-grade duplex
receptacles per 1,000 ft2.
EMT conduit and wire for
60 A current, length
assumed equal to
building perimeter for a
square building.

Lighting: Fluorescent
fixtures, recessed, 2 13 W
bulbs each, 31 per 1,000
ft2 for 4 W/ft2 total. 5
commercial grade single-
pole switches and 10
commercial-grade duplex
receptacles per 1,000 ft2.
RGS conduit and wire for
60 A current, length
assumed equal to
building perimeter for a
square building.

not applicable

' = feet;" = inches; A = amp; EMT = electrical metallic tubing; FC = foot candles; PVC = polyvinyl chloride; RGS = rigid
galvanized steel; W = watt

B.3 List of Abbreviations and Symbols in this Appendix

EPA	U.S. Environmental Protection Agency

ft2	square feet

NBCE	National Building Cost Estimator

WBS	work breakdown structure

B.4 References

Craftsman Book Company. 2020. 2020 National Building Cost Manual. 68th Edition.

Engineering News-Record (ENR). 2020. Building and Construction Cost Indexes. Retrieved
from http://enr.construction.com/economics/

Ogershok, Dave, Craftsman Book Company. 2009. Personal communication with Danielle Glitz,
SAIC. 6 March.

RSMeans. 2020. 2020 Square Foot Costs Manual. 41st Annual Edition. Rockland,
Massachusetts: the Gordian Group.

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Saylor Publications, Inc. 2020. 2020 Commercial Square Foot Building Costs Manual.

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Appendix C. Residuals Management Costs
C.1 Introduction

The purpose of this appendix is to outline the approach used to estimate costs for managing the
residuals generated by different drinking water treatment technologies. The work breakdown
structure (WBS) model for each treatment technology includes its own residuals cost estimate.
Each model allows the user to choose from different residual management options that reflect the
methods most likely to be used for the drinking water treatment technology being modeled.

Based on the residuals management option selected, each model identifies the specific
component equipment and operating and maintenance (O&M) requirements and generates costs
using the WBS approach based on engineering design. Costs for residuals management
equipment appear as line items in the model output, as is the case for other WBS elements. The
residuals management design also affects indirect costs, land costs and building costs.

The residuals management options available in each model are specific to the technology being
modeled, driven by the types of residuals generated, their quantity, the frequency of generation
(e.g., intermittent versus continuous) and their characteristics. There are, however, similarities
among groups of technologies that generate similar residuals. Exhibit C-l, below, lists the
technology groups, the residuals generated and the frequency of generation.

The technology-specific chapters of this report identify the residuals management options
available in each model. Because many of the options are similar within (or even across)
technology groups, this appendix describes the methodology and assumptions used for each
option in a single location, rather than repeating the information in each technology chapter. The
residuals management options that may be included in a given model include the following:

•	Holding tanks (with or without coagulant addition)

•	Direct discharge to surface water

•	Discharge to a publicly owned treatment works (POTW)

•	Recycle to treatment plant headworks

•	Evaporation ponds

•	Septic system

•	Off-site disposal (non-hazardous, hazardous, radioactive or hazardous and radioactive)

•	Land application

•	Liquid hazardous waste disposal

•	Deep well injection

•	Off-gas treatment.

Section C.2, below, describes general design methods and assumptions common across residuals
management options. With two exceptions, subsequent sections describe each of the above
options. Deep well injection is included as an option only in the reverse osmosis/nanofiltration
model and, therefore, is discussed in detail in the chapter relating to that model. Off-gas
treatment is relevant only to aeration technologies and, therefore, is discussed in detail in
chapters relating to aeration models (e.g., packed tower aeration, multi-stage bubble aeration).

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Exhibit C-1. Technologies and Residuals Generated

Residuals Generated

Type of
residual

Generation
Frequency

Technologies

Spent regenerant or brine1

Liquid

Intermittent or
continuous

Adsorptive Media, Anion Exchange, Cation
Exchange

Spent backwash

Liquid

Intermittent

Adsorptive Media, Anion Exchange, Biologically
Active Filtration, Biological Treatment, Cation
Exchange, Greensand Filtration, Granular
Activated Carbon

Spent media or resin

Solid

Intermittent

Adsorptive Media, Anion Exchange, Biologically
Active Filtration, Biological Treatment, Cation
Exchange, Greensand Filtration, Granular
Activated Carbon

Membrane concentrate

Liquid

Continuous

Reverse Osmosis/Nanofiltration

Spent backwash/tank drain and
crossflow

Liquid

Intermittent

Low-pressure Membranes
(Microfiltration/Ultrafiltration)

Cleaning waste

Liquid

Intermittent

Reverse Osmosis/Nanofiltration, Low-pressure
Membranes (M icrof i I trati on/U I traf i I tration)

Spent membrane modules/elements

Solid

Intermittent

Reverse Osmosis/Nanofiltration, Low-pressure
Membranes (M icrof i I trati on/U I traf i I tration)

Used cartridge filters

Solid

Intermittent

Reverse Osmosis/Nanofiltration

Off-gas

Gas

Continuous

Packed Tower Aeration, Multi-stage Bubble
Aeration, Diffuse Aeration, Tray Aeration

Spent lamps, ballasts and intensity
sensors

Solid

Intermittent

Ultraviolet Disinfection, Ultraviolet Advanced
Oxidation

The chlorine gas, hypochlorite, chlorine dioxide, chloramine, nontreatment, ozone, permanganate addition, phosphate feed,

caustic feed and acid feed models are not shown because no process residuals are generated.

Note:

1. Generated when the technology is used with media regeneration, rather than on a throw away basis.

C.2 General Assumptions

Some of the general assumptions used in developing the costs for management of residuals are

listed below:

•	For intermittently generated liquid residuals (e.g., filter backwash), the models calculate
residuals quantities based on the volume of a single generation event (e.g., backwashing
one vessel) and assuming a staggered schedule between generation events (e.g., if vessels
must be backwashed every 48 hours and there are two vessels in operation, the facility
will backwash vessel one at 0 and 48 hours and backwash vessel two at 24 and 72 hours).

•	For intermittently generated liquid residuals, flow rates depend on whether flow
equalization is used (e.g., through the use of holding tanks, as described in Section C.3).

•	Without flow equalization, the maximum residuals flow rate for intermittently generated
liquid residuals is single generation event volume/event duration.

•	With flow equalization, the models assume residuals are released continuously during the
time between generation events. Therefore, the maximum residuals flow rate for
intermittently generated liquid residuals is (single generation event volume/time between
events) x capacity factor. The variable, capacity factor, is present to account for less than
perfect staggering between generation events. The models assume capacity factor equals

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2, but the user can change this assumption on the critical design assumptions sheet of
each model.

•	The models size residuals piping, valves and other downstream equipment based on the
maximum flow rates calculated as described above for intermittently generated liquid
residuals and on the maximum continuous flow rate determined by the engineering
models for continuously generated liquid residuals.

•	The models assume the length of interconnecting piping between treatment process
equipment and residuals management equipment is equal to 1 times the overall system
building layout length. Like the pipe length assumptions documented in Exhibit 2-10,
this assumption is designed to account for the cost of fittings.

•	With a few exceptions (noted in the individual model chapters), the models assume an
additional 40 feet of piping is required for liquid residuals to reach their ultimate
destination (e.g., the discharge point, head of the treatment plant or evaporation pond).
Except when this piping is used to recycle the residual, the models assume this piping is
buried and, therefore, include the cost of excavation, bedding, thrust blocks, backfill and
compaction for the additional pipe length. The user can change the assumption about the
length of the additional residuals piping on critical design assumptions sheet of each
model.

•	The models generally assume that total suspended solids (TSS) in the influent water are
completely removed during treatment and accumulate in the residuals generated. This
assumption provides a conservative (high) estimate of the TSS concentration in the
residuals. Assumptions about the concentration of TSS in the influent water vary on a
technology-by-technology basis, but the user can change the assumption on the critical
design assumptions sheet of each model.

C.3 Holding Tanks

The purpose of a holding tank is to equalize the rate of flow at which residuals are released or
discharged. A holding tank may be desirable for intermittently generated liquid residuals that
ultimately are recycled to the treatment plant headworks or discharged to a POTW. The
instantaneous flow of intermittently generated liquid residuals (e.g., filter backwash) during a
generation event can be quite high. The use of a holding tank allows the discharge of these
residuals over the time between generation events, so that the ultimate flow is lower, but more
continuous. When residuals such as filter backwash are recycled to the head of a treatment plant,
recommended engineering practice is that the recycle stream should be no more than 5 percent to
10 percent of total system flow (U.S. EPA, 2002; U.S. EPA, 1996). Flow equalization through
the use of a holding tank may be necessary to meet this generally recommended engineering
practice. It also may be reasonable to include a holding tank for other discharge options (e.g., to
prevent instantaneous flow from overwhelming the capacity of a POTW).

When holding tanks are used for intermittently generated liquid residuals, the models determine
the capacity required as follows: single generation event volume x capacity factor. This capacity
factor is the same variable discussed in Section C.2 and is intended to account for less than
perfect staggering between generation events.

Holding tanks can also be desirable for certain continuously generated liquid residuals (e.g.,
membrane reject) to accommodate variations in flow that occur as influent flow varies. In this

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case, the models determine the capacity required based on a desired detention time. The user can
change this detention time on the critical design assumptions sheet of the appropriate models.

When holding tanks are included, residuals pumps are required to move residuals from the
holding tank to their ultimate destination. The models size these pumps based on maximum
residuals flow rate, as discussed in Section C.2. The models also include maintenance labor,
materials and energy for these pumps in the O&M calculations using the same approach
described for booster pumps in Appendix E.

When holding tanks are used, they can result in the generation of secondary residuals in the form
of solids that settle in the holding tank. The models also allow for the addition of coagulant to the
holding tank to increase the percentage of TSS removed. Users can model this option by
changing the appropriate triggering variable on the critical design assumptions sheet of each
model. When the coagulant addition option is chosen, users also can choose the coagulant used.
Options available (specified on the critical design assumptions sheet) are polymers, ferric
chloride or both ferric chloride and polymers.

By default, holding tanks can be constructed of plastic, fiberglass or steel or they can be open
concrete basins. When the coagulant addition option is chosen, however, the models
automatically assume the tanks will be open concrete basins, to allow for easier solids cleanout.
The models also size the tanks so that a minimum settling time is achieved. When coagulant
addition is chosen, the models also add other required equipment, specifically mixers and dry
feeders or metering pumps.

The following are the model assumptions relevant to solids generation and coagulant addition:

•	Without coagulant addition, most models assume that 25 percent of the TSS present in
the residuals is removed in a holding tank11

•	With coagulant addition, this assumption increases to 50 percent

•	With coagulant addition, the holding tanks must provide a minimum settling time of 90
minutes

•	Coagulant dose is 10 milligrams per liter

•	Coagulant sludge production factor is 1 pounds of sludge per pound of polymers added
and 0.99 pounds of sludge per pound of ferric chloride added

•	Holding tank solid density is 25 pounds per cubic foot

•	Holding tank solids are removed when the solids accumulation reaches 10 percent of tank
capacity.

The user can change each of these assumptions on the critical design assumptions sheet of the
individual models.

11 Exceptions are models, such as anion exchange, that assume low influent solids or include pretreatment filtration
to remove influent solids. These models assume no settling in the holding tank without coagulant addition, because
of the low solids content present (or remaining) in the water being treated.

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C.4 Direct Discharge to Surface Water

Some liquid residuals may be amenable to direct discharge to surface water. Such discharges
require a National Pollutant Discharge Elimination System permit, the costs of which are
included in the add-on costs line item for permits. The only items of capital equipment required
for direct discharges are piping and valves, although the models will include pumps if holding
tanks are used in conjunction with direct discharge (see Section C.3, above).

C.5 Discharge to POTW

Discharge to a POTW is another possible management option for liquid residuals. The discharge
should meet certain pretreatment requirements and must not overwhelm the capacity of the
POTW. The only items of capital equipment required for POTW discharges are piping and
valves, although the models will include pumps if holding tanks are used in conjunction with
POTW discharge (see Section C.3, above).

Discharge to a POTW, however, entails certain charges that are included in the O&M costs of
each model when this discharge option is included. POTW rate structures vary nationwide, but
the most common types of charges are the following:

•	Flat fees (e.g., dollars per month).

•	Volume-based fees (e.g., dollars per 1,000 gallons discharged).

•	TSS-based fees (e.g., dollars per pound of TSS in the discharge if over a certain TSS
concentration). For this fee type, the models assume that the POTW TSS discharge limit
over which a fee is imposed to be 250 parts per million (which is the most common limit
for cities with a limit on TSS).

Individual POTW rate structures can reflect a combination of one or more of these fee types. To
model POTW charges in a way that is nationally representative, the models include all three fee
types and calculate them based on unit charges that represent the average for each fee type based
on data from AWWA (2013). The user can change these average unit charges in the data
extracted from the central WBS cost database. Alternatively, the user can model a specific type
of POTW rate structure by selecting the appropriate option on the critical design assumptions
sheet of each model. The user can indicate which fee types to include (e.g., flat fee only). The
model will then use "typical" unit charges for the selected fee type(s). These "typical" unit
charges, which can be changed in the data extracted from the WBS cost database, reflect the
average including only cities that use that specific fee type (i.e., the average not counting zeros).

C.6 Recycle to Treatment Plant Headworks

Certain liquid residuals can be recycled to the treatment plant headworks provided the system
complies with the backwash recycling rule and the practice does not negatively impact finished
water quality. The recommended engineering practice is that the recycle stream should be no
more than 5 to 10 percent of total system flow (U.S. EPA, 2002; U.S. EPA, 1996). The only
items of capital equipment required for recycling are piping and valves, although a holding tank
(and, therefore, pumps) also would be necessary in most cases to meet the recommendation.

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C.7 Evaporation Ponds

When large quantities of liquid residuals are generated (e.g., spent brine from ion exchange), an
evaporation pond can be an appropriate management method, particularly for facilities in dry
climates. Holding tanks are never necessary with an evaporation pond, even for designs with
intermittent generation frequency, because the design of the pond would provide sufficient
capacity to handle instantaneous flow. A minimum of two cells is recommended to ensure
availability of storage space during cleaning, maintenance or emergency conditions (U.S. EPA,
1987).

When evaporation ponds are selected, the models include the following evaporation pond capital
expenses: excavation, backfill, lining and dike construction. Also, when evaporation ponds are
selected, the models always include the cost of a geotechnical investigation (see Appendix D).
These items are in addition to the pipes and valves required to deliver residuals to the pond. The
models make the following assumptions to design evaporation ponds:

•	Arid climate with annual average precipitation of 70 centimeters per year (cm/yr)

•	Average annual pan evaporation rate is 180 cm/yr

•	Evaporation ratio (which takes into account conversion of pan to lake evaporation rate
and the effect of salinity) of 0.7

•	180 days of storage with no net evaporation

•	Evaporation pond safety factor (which accounts for years with below average
evaporation) of 1.1

•	Maximum evaporation pond cell area of 5 acres.

The user can change each of these assumptions on the critical design assumptions sheet in each
model that includes the evaporation pond option. If evaporation ponds are selected, the user
should also review the other climate-based assumptions included in the model (e.g., the heating
and cooling requirements on the O&M assumptions sheet) to determine that they are sufficiently
consistent with the assumption of an arid climate that is implicit in the selection of evaporation
ponds as a residuals management method.

The use of an evaporation pond results in the generation of a secondary residual stream in the
form of evaporation pond solids. The models calculate the accumulation of evaporation pond
solids by including all suspended and dissolved solids present in the residuals. The models
assume evaporation pond solids removal frequency of once per year. Users can change this latter
assumption on the critical design assumption sheet of the appropriate models.

C.8 Septic System

Based on comments from peer reviewers, discharge to an in-ground septic tank and drain field (a
septic system) might be an option for some liquid residuals with intermittent generation in small
systems using certain technologies (e.g., adsorptive media, anion exchange). Users selecting this
option should evaluate whether the characteristics of the residuals are appropriate for this type of
discharge. Holding tanks are never necessary with septic systems because the design of the septic
tank would provide sufficient capacity to handle instantaneous flow.

When a septic system is selected, the models include the following capital expenses:

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•	Septic tanks

•	Excavation for septic tanks

•	Di stributi on b oxe s

•	Distribution pipe (perforated polyvinyl chloride)

•	Drain field trench excavation

•	Drain field gravel.

These items are in addition to the pipes and valves required to deliver residuals to the septic tank.
Also, when a septic system is selected, the models always include the cost of a geotechnical
investigation (see Appendix D). The models make the following assumptions to design septic
systems:

•	Minimum septic tank discharge time of 2 days

•	Minimum septic tank volume of 1,000 gallons

•	Maximum septic tank volume of 100,000 gallons

•	Septic tank volume safety factor of 150 percent

•	Long-term acceptance rate (a value, based on soil type, used by states/localities to
determine the minimum drain field infiltration area) of 0.5 gallons per day per square foot

•	Septic drain field trench width of 4 feet

•	Septic drain field trench depth of 4 feet

•	Septic drain field trench gravel depth below distribution pipe of 1 foot

•	A minimum of two septic drain field trenches

•	A maximum septic drain field trench length of 100 feet

•	8 feet between drain field trenches

•	Septic drain field trench total gravel depth of 28 inches, based on 1 foot below and 1 foot
above the distribution pipe and a 4 inch pipe diameter

•	Septic drain field buffer distance of 10 feet

•	Septic tank overexcavation depth of 1 foot above and to each side of the tank

•	A maximum of 7 distribution pipe connections per distribution box

•	Septic system distribution pipe diameter of 4 inches.

These assumptions are based on values typically found in state and local regulations for septic
systems. The user can change each of these assumptions on the critical design assumptions sheet
of each model that includes the septic system option. The use of a septic system results in the
generation of a secondary residual stream in the form of septic tank solids. The models calculate
the accumulation and disposal cost for these solids using the same assumptions used for holding
tank solids (except that addition of coagulant is not included for septic systems).

C.9 Off-Site Disposal

For solid residuals, including secondary residuals like holding tank solids or evaporation pond
solids, most of the models offer two options: disposal in a hazardous or non-hazardous off-site
landfill. The models do not include disposal in an on-site landfill as an option. This option would
be economically viable only for facilities with an existing on-site landfill—a factor that is highly
site-specific. For these facilities, the cost of this option would be less than that for off-site

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disposal, because it would involve much lower transportation costs. Therefore, the off-site
disposal options available in the models provide a conservative cost estimate for these facilities.

For certain solid residuals, many of the models also offer two additional options: off-site disposal
as a radioactive waste or off-site disposal as a hazardous and radioactive waste. The radioactive
waste disposal options assume that the residuals are classified as low-level radioactive wastes
(LLRW), instead of technologically-enhanced, naturally-occurring radioactive materials
(TENORM). In some cases, TENORM is accepted at traditional non-hazardous or hazardous
waste disposal facility. In such cases, disposal costs would be lower than those at specialized
radioactive waste disposal sites. Therefore, the LLRW disposal costs assumed in the models
provide a conservative cost estimate for cases where residuals might be classified instead as
TENORM.

The models calculate annual disposal costs for non-hazardous solid residuals as follows:

Annual disposal costs = Disposal costs + Transportation costs

where:

Disposal costs = quantity of solids per disposal event (in tons per event) x disposal
frequency (in events per year) x unit cost for non-hazardous waste disposal (in dollars
per ton)

Transportation costs = quantity of solids per disposal event (in tons per event) x disposal
frequency (in events per year) x distance to disposal site (in miles) x unit cost for non-
hazardous waste transportation (in dollars per ton per mile).

The disposal costs for hazardous, radioactive and hazardous radioactive solid residuals are
calculated in a similar fashion. For transportation costs, however, there is a minimum charge per
shipment applied. If transportation costs calculated based on dollars per ton per mile are less than
this minimum, the models calculate transportation costs based on this minimum.

The following are the model assumptions relevant to off-site landfill disposal:

•	10 miles to the nearest non-hazardous waste disposal site

•	200 miles to the nearest hazardous waste disposal site

•	700 miles to the nearest radioactive or hazardous radioactive waste disposal site

•	Maximum waste shipment size of 18 tons.

The user can change each of these assumptions on the critical design assumptions sheet of each
model.

C.10 Land Application

When secondary solids (e.g., holding tank solids, evaporation pond solids) are non-hazardous,
most models provide the option of assuming land application instead of landfill disposal. Users
can select this option on the critical design assumptions sheet. When land application is chosen,
the models assume that transportation and disposal costs for the secondary solids are zero,

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although they still include the operator labor costs associated with managing the secondary
solids.

C.11 Liquid Hazardous Waste Disposal

In some site-specific cases, the only viable option for certain liquid residuals (e.g., anion
exchange brine) might be off-site disposal as a hazardous waste. When this option is chosen, the
models automatically include a holding tank, which is required to store the residuals for
shipment. Any solids that settle in the holding tank also are assumed to require hazardous waste
disposal.

The models calculate costs for the liquid hazardous waste disposal option similarly to the off-site
hazardous waste landfill option (e.g., disposal cost + transportation cost, with a minimum charge
per shipment), except that unit costs are different. These unit costs are specific to off-site liquid
hazardous waste disposal, instead of off-site hazardous waste solids landfilling, and expressed in
dollars per gallon or dollars per gallon per mile. The models assume the maximum liquid
hazardous waste shipment size is 6,000 gallons.

C.12 List of Abbreviations and Symbols in this Appendix

cm/yr	centimeters per year

LLRW	low-level radioactive waste

O&M	operating and maintenance

POTW	publicly owned treatment works

TENORM	technologically-enhanced, naturally-occurring radioactive materials

TSS	total suspended solids

WBS	work breakdown structure

C.13 References

American Water Works Association (AWW A). 2013. 2012 Water and Wastewater Rate Survey.
Denver, Colorado: AWWA. February.

U.S. Environmental Protection Agency (U.S. EPA). 1987. DewateringMunicipal Wastewater
Sludge. EPA Design Manual. EPA/625/1-87/014. September.

U.S. EPA. 1996. Technology Transfer Handbook: Management of Water Treatment Plant
Residuals. United States Environmental Protection Agency, Office of Research and
Development. EPA 625-R-95-008. April.

U.S. EPA. 2002. Filter Backwash Recycling Rule: Technical Guidance Manual. United States
Environmental Protection Agency, Office of Groundwater and Drinking Water. EPA 816-R-02-
014. December.

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Appendix D. Indirect Capital Costs
D.1 Introduction

Indirect capital costs are costs that are not directly related to the treatment technology used or the
amount or quality of the treated water produced, but are associated with the construction and
installation of a treatment technology and appurtenant water intake structures. These costs
represent some of the expenditures required in order to get a technology or the treated water
production process up and running. They include indirect material costs (such as yard piping and
wiring), indirect labor costs (such as process engineering) and indirect burden expenses (such as
administrative costs).

Indirect capital costs included in the work breakdown structure (WBS) models include the
following:

•	Mobilization and demobilization

•	Architectural fees for treatment building

•	Equipment delivery, equipment installation and contractor overhead and profit

•	Site work

•	Yard piping

•	Geotechnical

•	Standby power

•	Electrical infrastructure

•	Instrumentation and control

•	Process engineering

•	Contingency

•	Miscellaneous allowance

•	Legal, fiscal and administrative

•	Sales tax

•	Financing during construction

•	Construction management and general contractor overhead

•	City index.

The following sections describe each of these indirect cost elements in more detail, address their
effect on capital costs and explain the reasoning behind including them as an additional indirect
capital cost allowance or contingency.

D.2 Mobilization and Demobilization

Mobilization and demobilization costs are costs incurred by the contractor to assemble crews and
equipment onsite and to dismantle semi-permanent and temporary construction facilities once the
job is completed. The types of equipment that may be needed include: backhoes, bulldozers,
front-end loaders, self-propelled scrapers, pavers, pavement rollers, sheeps-foot rollers, rubber
tire rollers, cranes, temporary generators, trucks (e.g., water and fuel trucks) and trailers. In some
construction contracts, mobilization costs also include performance bonds and insurance.

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To estimate mobilization and demobilization costs in the absence of site-specific data, the WBS
models use a multiplication factor of 2 to 5 percent. The models apply this multiplication factor
to direct process costs, building costs and the physical portions of indirect capital costs (site
work, yard piping, geotechnical, standby power, electrical, instrumentation and control and
miscellaneous). Examples of mobilization and demobilization percentages include:

•	Buckeye, Arizona Water System Infrastructure Improvements (multiple projects)
Mobilization/Demobilization/Bonds/Insurance = 5 percent (Scoutten, Inc., 2009)

•	City of New Port Richey Maytum Water Treatment Plant Modifications,
Mobilization/Demobilization (limit included in bid instructions) = 4 percent (Tampa Bay
Water, 2006)

•	Alton Water Works Mobilization = 1 percent (AWWC, 1999)

•	Fairfax Water Authority New Intake, Mobilization = 4.6 percent, Demobilization =1.8
percent, Total = 6.4 percent (FWA, 2003)

•	Fairfax Water Authority Trunk Sewer Project Mobilization = 5 percent (FWA, 2003)

•	Forest Park Water Treatment Plant, Chalfont, PA = 0.26 percent (Allis, 2005).

The last example, for the Forest Park treatment plant, applied to a retrofit of an existing
conventional filtration facility with a membrane system. The project involved modifications to
existing buildings and treatment basins and the construction of one new building. Since the
project involved less new construction than a greenfield project, the mobilization cost may be
lower than it otherwise would be.

Mobilization/demobilization costs tend to be proportionately higher for smaller projects because
of fixed costs that are the same regardless of project size. For example, if construction requires
use of a large crane, then the mobilization/demobilization cost will be the same regardless of
whether it is onsite for a long time to complete a large construction project or a short time to
complete a small project. Therefore, small projects will most likely have
mobilization/demobilization percentages in the higher end of the range and larger projects will
tend to have values in the lower end of the range. The default values in the WBS models reflect
this type of variation. For small systems with a design flow less than 1 million gallons per day
(MGD), the default mobilization/demobilization factor is 5 percent. For medium systems (design
flows between 1 MGD and 10 MGD), the default factor is 4 percent and for large systems
(design flows above 10 MGD), the default factor is 2 percent. The models make an exception in
the case of small systems that use pre-engineered package treatment plants. Because these
package plants typically are skid-mounted, they require only a short time to install onsite and
should use a minimum of heavy equipment in the process. Therefore, the models assume a
mobilization/demobilization factor of 0 percent for small, pre-engineered package systems. The
user can change this assumption on the indirect assumptions sheet of each model.

Because the installation costs in the models include rental of equipment for installation (see
Section D.4.2), there may be some redundancy between the default mobilization and
demobilization costs and the installation costs (which are included in the model unit costs). The
extent of this redundancy is difficult to determine, but is a potential source of conservatism in
model cost estimates (i.e., the potential redundancy would tend to make model cost results
higher).

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D-3 Architectural Fees for Treatment Building

The architectural fees for the treatment building include the costs of designing the structure and
preparing technical drawings. By convention, the architectural fee also includes the fees for
structural, electrical and mechanical engineering associated with the treatment building
(RSMeans, 2013). Furthermore, the architectural fees include the costs of preparing final
drawings and the tender document package. The building costs in the WBS cost database (see
Appendix B) do not include architectural fees, so the fees are added as an indirect cost. The
models apply the architectural percentage only to treatment building costs, not to other process
costs.

The WBS models use architectural fees from RSMeans (2013), based upon the direct cost of the
building, as shown in Exhibit D-l. The models make an exception in the case of small systems
with a design flow of less than 1 MGD. Because they are typically housed in small, prefabricated
buildings that require a minimum of design and engineering, the models assume no architectural
fee for these small systems. The user can change this assumption on the indirect assumptions
sheet of each model.

Exhibit D-1. Architectural Fees

Building Direct Cost Range

Architectural Feea

<$250,000

9.0%

$250,000 to $500,000

8.0%

$500,000 to $1,000,000

7.0%

$1,000,000 to $5,000,000

6.2%

$5,000,000 to $10,000,000

5.3%

$10,000,000 to $50,000,000

4.9%

>$50,000,000

4.5%

a. The architectural fee is a percentage of the direct cost for buildings. It includes a structural engineering fee, as well as
mechanical and electrical engineering fees that are associated with the building.

Source: RSMeans (2013), reference table R011110-10.

D.4 Equipment Delivery, Equipment Installation and Contractor
Overhead and Profit

The equipment unit cost estimates in the WBS database include the cost of equipment delivery,
equipment installation and contractor overhead and profit (O&P). Because these costs are
included in the direct or process costs, the default value of this multiplier in the WBS models is 0
percent. If the user has site-specific or technology-specific data that show delivery, installation or
O&P costs outside of typical ranges, the user can change this factor on the indirect assumptions
sheet of each model to better account for actual installation costs.

The sources of unit cost quotes include manufacturers, vendors, published construction cost data
reference books and peer-reviewed literature. Price quotes for an item vary across sources
because of inherent price variability or product quality differences that are not relevant to overall
performance. The U.S. Environmental Protection Agency (EPA) addressed this source of price
variability by including quotes from multiple vendors in the WBS cost database; the unit costs

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used in the WBS models are simple averages across vendor quotes. Differences also arise
because vendors include different information in price quotes. For example, prices obtained from
RSMeans (2013) include all components needed for installed process costs (i.e., delivered
equipment, installation and O&P costs). Quotes from other sources may not include installation
costs, contractor O&P or transportation costs. Thus, before EPA calculated average costs, all
prices needed to be adjusted to the same installed cost basis. EPA converted costs to this basis by
adding transportation, installation and O&P costs where they were missing from the original unit
price estimates.

D.4.1 Equipment Delivery

Incorporating delivery costs in unit costs that will be used for a national cost analysis is
challenging because of variability in the methods used to assess transportation costs. For
example, transportation costs can be based on a cost per mile, a cost per unit of weight, a cost per
unit of volume, a cost per region or within a radius or a proportion of sales price. EPA developed
standardized transportation cost multipliers that vary by equipment type and size. The type of
multiplier selected for each equipment category is based on a likely method of transportation.

For tanks, vessels and towers, EPA applied transportation costs that are scaled to equipment
volume units (e.g., gallons). These costs are based on quotes for shipping from several vendors
for tanks of varying volumes and materials. For steel tanks, the costs range from a minimum of
$600 for tanks of 1,000 gallons or less to a maximum of $9,000 for tanks of 280,000 gallons or
greater. For plastic/fiberglass tanks, the costs range from a minimum of $120 for tanks of 1,000
gallons or less to a maximum of $2,800 for tanks of 50,000 gallons or greater.

To estimate transportation costs for pipe, EPA calculated delivery costs per linear foot of pipe
using vendor delivery cost estimates and linear feet/truck load estimates. EPA obtained a vendor
delivery estimate of $1,000 for a truckload of steel pipe. Information obtained from vendors was
used to estimate the number of linear feet of each size pipe that could fit in a truckload.

For valves, pumps, blowers and mixers, EPA developed transportation cost estimates based on
equipment weight and costs for "less than a load" (LTL) shipments obtained from vendors. The
estimates assume an average delivery distance of 100 miles. For shipping cost estimation
purposes, average weights were assumed for the small, medium and large sizes of valves, pumps,
blowers and mixers. The assigned weights (which are based on the actual weights of valves,
pumps, blowers and mixers for which EPA received vendor quotes) are as follows:

•	Small steel valves -30 pounds

•	Medium steel valves ~ 80 pounds

•	Large steel valves ~ 400 pounds

•	Small pumps / blowers -100 pounds

•	Medium pumps / blowers - 300 pounds

•	Large pumps / blowers - 600 pounds

•	Small mixers - 50 pounds

•	Medium mixers - 100 pounds

•	Large mixers - 400 pounds.

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Since the density of 304 stainless steel is approximately 5.6 times greater than the density of
polyvinyl chloride, the following weights were assigned to plastic valves:

•	Small plastic valve ~ 5 pounds

•	Medium plastic valves -15 pounds

•	Large plastic valves ~ 70 pounds.

Exhibit D-2 provides the weight categories and LTL costs for valves, pumps, blowers and
mixers, along with a complete summary of transportation cost methods for all categories of
equipment.

EPA assumed a 2.5 percent markup on instrumentation, based on typical shipping charges from
two vendors for large orders ($600 to greater than $4000). For system control components, EPA
assumed no transportation costs, because the vendors contacted did not charge for shipping on
large orders (greater than $49 to greater than $300). EPA assumed a 5 percent markup on
miscellaneous equipment and filter components for membrane systems. Transportation costs for
chemicals, resins and filter media are averages of delivery costs obtained from vendors.

D.4.2 Installation, Overhead and Profit

EPA incorporated installation and O&P costs using multipliers derived from RSMeans (2013)
cost data. RSMeans provides complete installed cost estimates for the unit costs in its database.
The following cost components are reported for each unit cost:

•	Bare material costs, including delivery

•	Installation labor, materials and any rental cost for installation equipment

•	Overhead for installing contractor (i.e., labor and business overhead costs)

•	Profit for installing contractor (i.e., a 10 percent rate of profit charged on materials,
installation and overhead costs).

These component cost data provide enough information to calculate adjustment factors that can
be applied to price quotes that exclude installation and O&P costs. By dividing total unit cost,
which includes all components, by bare material cost including delivery, EPA obtained
adjustment factors for several types of equipment in the WBS cost database. For example, if the
bare material cost, including delivery, for an item of equipment is $1.00 and the total unit cost is
$1.78, then the adjustment factor is 1.78. When unit costs obtained for the database did not
include installation, overhead and profit (as is typical when obtaining costs from manufacturers),
EPA applied these adjustment factors to escalate the unit costs so that they represented the full
installed cost. For example, if a manufacturer's price for a 20,000 gallon steel tank was $25,000,
EPA would first add delivery cost ($1,000 per 10,000 gallons capacity, as described in Section
D.4.1), resulting in a cost with delivery of $27,000. EPA would then multiply that cost by the
appropriate adjustment factor (for instance, 1.17) to obtain a complete unit cost—that is, the total
unit cost in this example would be ($25,000 + $2,000) x 1.17 = $31,500.

Most of the installation and O&P multipliers in the WBS cost database fall between 1.03 and
1.73, with an average around 1.36.

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Exhibit D-2. Transportation Cost Estimation Methods

Equipment Category

Transportation Costs (year 2020 dollars)

Vessels, Tanks, Towers - steel

Varies by tank volume in gallons, from a minimum of $600 for tanks of 1.000 gallons or
less to a maximum of $9,000 for tanks of 280,000 gallons and greater

Vessels, Tanks, Towers -
plastic/fiberglass

Varies by tank volume in gallons, from a minimum of $120 for tanks of 1,000 gallons or
less to a maximum of $2,800 for tanks of 50,000 gallons and greater

Pipes

Varies by pipe diameter and material of construction.
Plastic pipes: range is $0.37 to $208 per 100 linear feet.

Iron and steel pipes: range is $32.68 to $494 per 100 linear feet.

Valves-steel/iron
Weight Class 60
LTL rate = $189.13 per 100 lb

Small valves: $57 (1" to 4" diameter)
Medium valves: $151 (5" to 9" diameter)
Large valves: $757 (>9" diameter)

Valves-plastic

Weight Class 70 - plastics

LTL rate = $189.13 per 100 lb

Small valves: $9 (1" to 3" diameter)
Medium valves: $28 (4" to 6" diameter)
Large valves: $132 (>6" diameter)

Pumps and blowers
Weight Class 85

LTL rate = $48.81 to $189.13 per
100 lb depending on total weight

Small units: $189 (0 to 50 gpm)
Medium units: $595 (51 to 300 gpm)
Large units: $1,757 (>300 gpm)

Mixers

Weight Class 85

LTL rate = $48.81 to $189.13 per
100 lb depending on total weight

Small mixers: $95 (includes mounted and portable mixers)
Medium mixers: $189 (includes inline and static mixers)

Large mixers: $978 (includes turbine, rapid, flocculant, impeller mixers)

Instrumentation

2.5% of equipment cost

System Controls

None

Miscellaneous Equipment

5% of equipment cost

RO/NF and MF/UF Skids and
Equipment

5% of equipment cost

Chemicals, Resins and Filter Media

$0.26 per lb for hazardous materials
$0. 32 per lb for filter media and resins
$0.22 per lb for 150 lb chlorine cylinders
$0.29 per lb for 1 ton chlorine cylinders
$0.07 per lb for all other chemicals

lb = pound; gpm = gallons per minute;" = inch; RO/NF = reverse osmosis/nanofiltration; MF/UF = microfiItration/uItrafiItration

D.5 Site Work

Every construction site requires a certain amount of site preparation and finish work. Site work
costs include site preparation, excavation and backfilling, temporary and permanent road
construction, retaining wall construction, final grading, landscaping, parking lots, fencing, storm
water control structures, yard structures, site cleanup, waste disposal and utilities.

Estimating the site work cost based on a factor applied to the direct capital cost is an approach
commonly used when detailed information about the site plan is not known. Under this approach,
site work costs are typically estimated between 5 and 15 percent of the direct capital costs,
depending on project size and scope.

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Site work costs vary directly with the land area requirement. The WBS models generate land
area estimates, which allows the models to use an alternative cost estimation approach based on
total project land area instead of total project costs. RSMeans (2013) provides an analysis of
actual reported project and component costs for different types of construction. Of the many
building categories reported in the summary database, the "factory" category best fits the scope
of construction associated with drinking water treatment plants. Therefore, the models use the
national average median project cost for site work at factories from RSMeans (2013). The WBS
cost database automatically updates this unit cost to current year dollars using the Engineering
News-Record (ENR) Building Cost Index (see Chapter 2). The models compute a site work cost
based on this unit cost and the total project land area, excluding land used for residuals holding
lagoons and evaporation ponds. Since the models include the cost of excavation and backfill for
these facilities, there is no need to include them in the site work calculations.

EPA believes that using an approach based on land area instead of direct process costs provides a
better estimate of site work costs because the unit costs from RSMeans (2013) are primarily
based on quantities of area and earthwork volume. Furthermore, this approach is less sensitive to
cost fluctuations caused by high cost equipment—the site work cost for a 0.5-acre project site
will be the same regardless of whether the treatment building houses chemical addition or a
membrane filtration process. This is particularly important because expensive, advanced
treatment technologies often have smaller footprints than lower-cost, conventional technologies
such as conventional filtration. Basing site work costs on process costs will tend to overstate site
work costs for such advanced technologies.

Although the default site work cost in the WBS models reflects a median value, the user can
enter a different rate in the data extracted from the WBS cost database based on site-specific
conditions. A higher cost factor should be entered for projects where the site conditions may
require higher-than-average site work costs (e.g., a site with steep terrain that may require
retaining walls). Conversely, a lower rate should be entered for projects where the site conditions
may require lower-than-average site work costs (e.g., a site where little grading is needed and
where requirements for infrastructure and other site improvement are minimal or where portions
are already in-place).

D.6 Yard Piping

Yard piping costs reflect the costs to install piping for untreated, partially treated and treated
water to and from the site, between new treatment plant buildings or between existing and new
treatment units. It does not include piping of treatment residuals to a residuals treatment system,
to disposal in a sewer or to a direct discharge connection; those costs are included as explicit
capital cost line items in the relevant WBS technology models, as discussed in Appendix C.

Yard piping costs include the following components:

•	Trench excavation, backfill and pipe bedding

•	Piping from the boundary of the building buffer zone to and from the building inlet and
building outlet and in between buildings that house water treatment components

•	Optionally, piping from the water source to the property boundary and piping from the
property boundary to the distribution system connection

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• Thrust blocks.

The sections below describe each of these components.

D.6.1 Trench Excavation, Backfill and Pipe Bedding

Costs of pipe contained in the WBS cost database are installed costs for aboveground pipes
within the treatment facility. Yard piping generally is installed below ground. Therefore, yard
piping entails additional costs. These costs include trench excavation costs, bedding costs,
backfill costs and thrust block costs (discussed in Section D.6.3).

Technology land area requirements are calculated on a basis of starting with a square building
with the required footprint and adding a non-fire buffer (10 feet) on three sides of each building
and a fire buffer (40 feet) on the fourth side. The general configuration assumption is that the fire
buffer will be located along the front side and the distance between buildings will be two times
the non-fire buffer distance (20 feet) and, therefore, yard piping will not cross the fire buffer
area. Thus, the minimum initial trench length is 20 feet (10 feet at inlet and 10 feet at outlet) for a
system with one building or 30 feet (20 feet inlet and outlet and 10 feet between buildings) for a
system with two buildings. Since the inlet and outlet piping may not always line up and may
extend inside the building perimeter, an offset distance is added to the 10 foot buffer distance
based on the building size. The offset distance is assumed to be Vi the length of one side of the
building footprint (based on square root of total building footprint).

The models assume yard piping will be buried with the top of the pipe set at or below the local
frost depth. Where frost depth is less than 30 inches, a minimum depth of 30 inches is assumed
to provide a protective cover. The default frost depth is 38 inches and corresponds to the frost
depth in St. Louis. Users can change the frost depth on the indirect assumptions sheet of each
model based, for example, on the climate data for a selected city in the climate database
(AFCCC, 2000). Trench depth also incorporates the pipe diameter and the bedding depth, which
the models assume to be 6 inches below the bottom of the pipe. This default value is sufficient to
approximate bedding requirements for large size pipes laid in soils where bedding is necessary.
The user has the option of changing the default value on the indirect assumptions sheet of each
model.

Trench width is equal to the pipe diameter plus 1 foot on either side. Trench volume is based on
the calculated trench length times the trench cross-sectional area, which incorporates trench
width and depth and assumes sloped trench sides, with an angle of 45 degrees (expressed in
radians on the indirect assumptions sheet). Excavation and backfill costs are based on total
trench volume plus thrust block volume and the unit cost for excavation and backfill. Although
backfill quantities are generally smaller than excavation quantities, they are assumed to be the
same in the WBS models. This approach is assumed to cover to the cost of backfill and the cost
of spreading or hauling excess soil off site. Pipe bedding volume accounts for the bedding depth,
incorporating additional volume to account for the sloped sides of the trench and the assumption
that the bedding covers 25 percent of the pipe diameter. The user can change this latter
assumption on the indirect assumptions sheet of each model.

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D.6.2 Piping

The basic assumptions for yard piping from the boundary of building buffer zone to and from the
building inlet and building outlet and in between buildings are:

•	Pipe length will be equal to trench length plus two times the trench depth.

•	Pipe costs will be based on an equivalent pipe length, which will include an additional
length to account for cost of fittings (e.g., elbows). The equivalent length will be equal to
two times the pipe length, using the same factor used for process piping within the
buildings (see Section 2.4).

•	Yard piping costs do not include valves.

•	Piping materials, diameter and unit cost are the same as those selected in the treatment
model for inlet and outlet piping within the building.

In addition, the indirect assumptions sheet in each model contains an optional assumption for the
length of yard piping from the water source and another optional assumption for the desired
length of yard piping to the distribution system. Therefore, if the technology is not the initial step
in the treatment train, the default value length of pipe from the water source should be 0 feet,
because there is already a pipe from the water source to the existing facility. Similarly, if the
technology is not the last technology in the treatment train, then the default value should be 0
feet. As a default, these assumptions are set to zero.

D.6.3 Thrust Blocks

Yard piping costs include concrete thrust blocks to hold small pipe elbows and other fittings in
place. The basis of the thrust block volume calculation is thrust force in pounds. The models
derive thrust force using a lookup table based on pipe diameter. Users can modify the thrust
force assumptions by editing the engineering lookup table extracted from the WBS cost database.
The values in the lookup table assume a pipe test pressure of 150 pounds per square inch and a
pipe elbow angle of 90 degrees and account for block weight. Although both vertical and
horizontal elbows are expected in every pipe-laying job, the thrust block calculations assume
horizontal thrust blocks.

Using the data from the thrust force lookup table, the models calculate bearing surface area based
on a conservative approach found in U.S. Army Corps of Engineers guidance (U.S. ACOE,
1992). The calculation is:

Area = 1.5*T/(Soil Density*Kp*Depth*R)

where:

1.5 is a safety factor, which is typical for thrust block design
T is the thrust force required, derived as discussed above

Soil Density is the minimum soil bulk density, which the models assume is 1.55 grams
per cubic centimeter (97 pounds per cubic foot) consistent with loamy sand, which is also
on the lower end of the range for sandy soils (1.5-1.8) and the upper end of the range for
silty clay (1.4-1.5) (MNNRSC, 2003)

Kp is the coefficient of passive pressure, which the models assume to be 3, based on an
internal angle of friction of the soil (phi) of 30 degrees

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Depth is the depth to bottom of the block, which the models calculate based on trench
depth and pipe diameter

R is a reduction factor of 0.467, based on phi of 30 degrees and a vertical bearing surface
(CADOT, 2001, Figure 8).

Users can adjust soil density, Kp and R on the indirect assumption sheet of each model. Note that
this approach is conservative in that it considers only the bearing force of the vertical surface,
which is perpendicular to the thrust force, and ignores the frictional force exerted on the bottom
surface of the block. Use of deeper trench depths will result in lower thrust block costs.

D.7 Geotechnical Investigation

Construction cost estimates generally include a geotechnical allowance to provide for
investigation of subsurface conditions. Subsurface conditions can affect the foundation design
and construction technique. For example, a high groundwater table or soft substrate may require
special construction techniques such as piles and dewatering. Thus, the actual costs of addressing
subsurface conditions are site specific and can vary considerably. In addition, where a system is
adding treatment technology to a site with existing structures and, therefore, the site already has
an existing geotechnical investigation, additional geotechnical investigation may not be required.
To account for these variations, the models include assumptions that allow the user to select
whether geotechnical investigation costs should be included for low, medium and high cost
estimates. The default values for these assumptions include geotechnical costs only for high-cost
systems. However, the models always include geotechnical costs (regardless of the value
selected for these assumptions) when certain components are included in the technology design,
such as septic systems, evaporation ponds or below-grade structures like basins.

Geotechnical investigations can be as simple as digging trenches or test pits to determine the soil
conditions underlying small, lightweight structures. For larger, heavier structures, site
investigations generally involve drilling boreholes to extract samples of rock or soil for further
study. Cost estimates in the WBS models reflect either test pit costs or borehole costs, depending
on the building footprint size. For footprints of 2,000 ft2 or smaller, the WBS models have costs
based on hand digging test pits. All larger structures have costs based on the costs of drilling
boreholes. The following sections describe the method for estimating costs for each approach.

D.7.1 Borehole Cost Analysis

The cost analysis for drilling boreholes includes preparation activities (e.g., staking the field) and
actual drilling. Thus, a key cost driver is the number of boreholes needed. An additional factor is
the required drilling depth.

For a large industrial building, a borehole should be drilled at the expected location for each
column foundation and at locations where concentrated loads are expected to occur such as under
tanks and heavy equipment. The models assume four boreholes is reasonable for structures in the
range of 2,000 to 4,000 ft2. For larger structures, the models assume an additional borehole for
every 1,000 ft2 in additional space. Thus, the requirement for structures in the range of 4,001 to
5,000 ft2 is five boreholes. This approach is based on the assumption that column footings are
spaced approximately 32 feet apart.

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Drilling depth depends on a structure's weight and existing knowledge of subsurface conditions.
Nevertheless, a rough criterion used to develop WBS cost estimates is that boreholes should
penetrate at least 1.5 times the width of the footings below the lowest portion of the footing
(Krynine and Judd, 1957). The lowest portion of the footing must be below the frost line, which
ranges from almost 0 feet to more than 5 feet in the continental United States. The WBS models
assume a frost line depth of 38 inches, an additional safety depth of 22 inches and a footing
width of 3 feet to obtain a minimum borehole depth of approximately 10 feet (5 feet + 1.5 x 3
feet).

EPA selected three different boring depths to represent a range of geologic conditions and
building bearing loads. A boring depth of 10 feet applies to relatively light structures in areas
where the soil conditions are predictable without any expectation of deeper strata that exhibit
poor shear strength. A boring depth of 25 feet applies to moderately heavy structures in areas
where subsurface conditions are less well defined, but no severe conditions are expected and
where underground structures, such as basins, as deep as 20 feet need to be constructed.

Similarly, a boring depth of 50 feet deep applies to heavy structures in areas where extreme or
unknown subsurface conditions (such as strata with poor shear strength) may exist.

EPA developed cost estimates based on cost data for drilling activities that use a truck-mounted,
2.5-inch auger with casing and sampling from RSMeans (2013). Exhibit D-3 identifies the cost
elements included in borehole drilling. The WBS cost database automatically updates the unit
costs for these elements to current year dollars using the ENR Construction Cost Index (see
Chapter 2). Costs are applied based on the selected borehole depth and total structure area
rounded up to the nearest thousand ft2.

Exhibit D-3. Cost Elements Included in Borehole Drilling

Item

•	Borings, initial field stake out and determination of elevations

•	Borings, drawings showing boring details

•	Borings, report and recommendations from professional engineer

•	Borings, mobilization and demobilization, minimum

•	Borings, drill rig and crew with truck mounted auger (output 55 feet/day)

•	Borings, cased borings in earth, with samples, 2.5-inch diameter.

Source: RSMeans, 2013, 02 32 13.10-0200.

D.7.2 Test Pit Cost Analysis

For smaller, less expensive buildings, boreholes are less cost effective compared to test pits or
trenches that can be dug by hand or by using earth moving equipment if it is already available at
the site. Because geotechnical investigations may precede site work, excavating equipment may
be available to dig test pits. Therefore, for small buildings, the models use hand-dug test pits as
the basis for costs. The models assume one pit for buildings up to 1,000 ft2 and two pits for
buildings of 1,001 to 2,000 ft2.

Pit widths range from 4 feet by 4 feet to 6 feet by 8 feet (Krynine and Judd, 1957). Because this
test method is limited to small buildings, the models assume pits that are 4 feet by 4 feet wide.
Pit depth of 7 feet is based on a footing width of 2 feet and a frost depth of 5 feet (5 feet + 1.5x2

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feet). The unit excavation and backfill costs are based on data from RSMeans (2013) for hand
dug pits in heavy soil. The cost of surveying and the soil sample evaluation report and
recommendation from a Professional Engineer are assumed to be the same as for borings.

D.8 Standby Power

A new treatment facility sometimes requires a standby power source that can produce enough
energy to operate the facility in the event of an electricity outage. Thus, the power rating or
capacity of the standby generator should be sufficient to power critical operating components at
the rated maximum flow capacity of the equipment (i.e., the design flow). Critical components in
a treatment plant include pumps, lighting and ventilation. In addition, standby power can be
required to provide space heating (if an electrical resistance heater or heat pump is used) and/or
cooling in the event of a power outage. As a default, the WBS models do not include heating or
cooling in their estimate of standby power requirements. The user can change the assumptions
about inclusion of heating and/or cooling in standby power on the indirect assumptions sheet of
each model.12

Also as a default, the models do not include standby power at all for small systems with a design
flow of less than 1 MGD. These small systems typically operate for only a few hours each day,
placing water in storage for use during the rest of the day. This operating procedure means small
systems can handle short term power outages simply by postponing their operating hours,
without the need for standby power systems. The user can change the assumption about
including standby power for small systems on the indirect assumptions sheet of each model.

The generation capacity requirement for critical systems is based on the maximum daily load,
which is the potential energy demand to meet production at the design flow rate. Since the
energy requirements calculated in the models are based on continuous operation (24 hours/day
and 365 days/year), the maximum power requirement in kilowatts (KW) can be estimated using
the following equation:

Power requirement for critical operating components (KW) =

[annual power use by critical operating components (MWh/yr) / 365 (day/yr) / 24 (hr/day)] *

1,000 (KW/MW)

where:

hr = hours
MW = megawatt

MWh/yr = megawatt hours per year
yr = years

Standby power costs primarily comprise equipment purchase (e.g., a generator) and installation.
Additional costs include fuel purchase and storage. Annual fuel costs for standby power
generation are hard to estimate or predict, given the unpredictable nature of using the standby
power generator. Typical standby generators consist of diesel engine powered generators

12 Note that if the assumption about including heating in standby power is changed, heating requirements will only
be included in standby power if an electrical resistance heater or heat pump is used, because the other heating
options (e.g., natural gas heat) do not use electricity.

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(NREL, 2003). Installation costs include provisions for a foundation, fuel storage and louvered
housings for larger systems. For the diesel generators typically used for standby power, EPA
used installed unit costs from RSMeans (2009a). The WBS cost database automatically updates
these unit costs to current year dollars using the Producer Price Index from the Bureau of Labor
Statistics for motors, generators and motor generator sets (see Chapter 2). The models multiply
the appropriate unit cost, which users can change by modifying the data extracted from the WBS
cost database, by the calculated standby power requirement in KW, after applying a minimum
requirement of 1.5 KW (based on the smallest available standby power generator).

D-9 Electrical

The electrical cost allowance in a construction cost estimate will primarily account for electric
wiring inside structures, such as wiring for motors, duct banks, motor control centers, relays and
lighting. The unit costs for buildings in the WBS models (see Appendix B) already incorporate
general building electrical, such as building wiring and lighting fixtures and electrical
engineering associated with those components. In addition, certain electrical costs (motor/drive
controllers, variable frequency drives and switches) are included in direct costs for system
controls and pumps. Technologies with significant process equipment located outside include an
electrical enclosure as an explicit line item. Thus, the indirect cost electrical allowance only
accounts for additional electrical equipment associated with the treatment facility, including
outdoor lighting, yard wiring, switchgear, transformers and miscellaneous wiring. Yard wiring
consists primarily of the infrastructure that connects a new treatment facility to the power grid
and, if necessary, converts voltage.

Typical electrical percentages include:

•	Building electrical as a percentage of building cost = 7.7 to 13.0 percent, depending on
building size and quality (Association for the Advancement of Cost Engineering
International [AACEI] building cost model results)

•	Seymour, Indiana electrical costs as a percentage of non-electrical process costs = 12.1
percent (AWWC, 2001a)

•	St. Joseph, Missouri electrical costs as a percentage of non-electrical process costs = 8.7
percent (AWWC, 2001b).

Based on these data, the electrical percentage in the WBS models is 10 percent as a default.
Users can change this assumption on the indirect assumptions sheet of each model.

D-10 Instrumentation and Control

Instrumentation and control (I&C) costs include a facility control system and software to operate
the system. The WBS models include detailed process cost estimates for instrumentation and
control, as described in Appendix A. Therefore, the default value for I&C on the indirect
assumptions sheet is 0 percent. This line item remains among the indirect costs on the output
sheet of each model, however, to allow the user to incorporate any site-specific or technology-
specific data that cannot be accommodated by altering the I&C design assumptions in the WBS
models.

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D.11 Process Engineering

Process engineering costs include treatment process engineering, unit operation construction
supervision, travel, system start-up engineering, operating and maintenance manual development
and production of record drawings. Process engineering as a percent of installed process capital
cost ranges from 5 to 20 percent. For example, Brayton Point Power Plant Water Works process
engineering costs were estimated at 8 percent of installed capital costs (Stone and Webster,

2001).

The ratio of process engineering to installed process capital cost varies based on system size and
the complexity of the treatment process. In particular, engineering cost as a percentage of process
cost tends to decrease as the size of the treatment plant increases. The default values in the WBS
models reflect this pattern: 8, 12 and 20 percent for large, medium and small systems,
respectively. The WBS models apply these percentages to installed process costs, but not
building costs, because structural, mechanical and electrical engineering fees are included in the
architectural fee (Section D.3).

The process engineering percentages at 13 EPA demonstration sites for low-flow packaged
systems ranged from 20 to 80 percent, with a mean of 36 percent (U.S. EPA, 2004). These
percentages, however, also include permitting and administrative costs. Because these costs are
separate line items in the WBS models, these percentages overstate stand-alone process
engineering costs. Furthermore, engineering costs can be higher for technologies in the
demonstration phase than for those in wide use. Therefore, EPA retained its assumption of 20
percent process engineering cost for small systems.

D.12 Contingency Cost

Contingency cost reflects the degree of risk that management assigns to a project. This cost
should reflect the statistical probability of additional project costs because of uncertainties and
unlikely or unforeseen events (AACEI, 1996). These unforeseeable additional costs to the project
occur because of changes in design, materials, construction methods and/or project schedule.
Contingency reflects a judgment by project management or bidders to account for unforeseeable
costs, thereby avoiding cost overruns. Contingency costs are included as part of a construction
contract allowing the contractor to be paid extra upon authorization of design and construction
changes by the project engineer (AACEI, 1996).

The risk of additional unforeseen costs associated with construction projects tends to vary with
project size and complexity. Therefore, EPA developed contingency factors using both project
size (i.e., total direct cost) and complexity (i.e., the technology being modeled) as input
variables. Ideally, a contingency cost estimate is based on statistical data or experience from
similar projects. By their nature, however, contingency costs are site specific and difficult to
predict; two estimators may recommend different contingency budgets for the same project
(Burger, 2003). EPA examined recommended contingency values, tabulated by project size,
from an economic analysis of water services (GeoEconomics Associates Inc., 2002). The
recommendations are presented in Exhibit D-4. These contingency rates, which range from 2 to
10 percent, are applied to the base costs (i.e., direct costs) to derive contingency cost. These rates
apply to projects of low to average complexity. Water treatment construction projects typically
fall into this category, depending on the technology being installed.

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Exhibit D-4. Recommended Contingency Rates from an Economic Analysis of

Water Services

Project Base (Direct) Cost

Contingency as a Percent of Base Costs

Up to $100,000

10%

$100,000 to $500,000

8%

$500,000 to $1,500,000

6%

$1,500,000 to $3,000,000

4%

Over $3,000,000

2%

Source: GeoEconomics Associates Inc. (2002)

The WBS models would ideally include only the part of a contingency budget that is actually
spent, rather than the total amount budgeted. EPA therefore considered a Construction Industry
Institute (2001) study, which included both budget estimates and actual spending for contingency
in a series of heavy construction projects. Exhibit D-5 presents the relevant results. The factors
are expressed as a percentage of the total budget, rather than direct costs. These projects are not
limited to water treatment systems and include a variety of heavy construction projects. The data
in Exhibit D-5 show that, with the exception of very large projects (those with total project costs
of over $100 million), the contingency cost tends to decrease as project size increased. The
average contingency factor decreases from 6 to 4 percent before increasing to 7 percent for very
large projects. Such very large projects are generally beyond the size of projects that can be
modeled using the WBS models. Exhibit D-5 also shows that unforeseen problems during
construction tend to account for a higher share of contingency cost than design or procurement
problems.

Exhibit D-5. Average Contingency Costs in Budgets for Heavy Industrial Projects

Project
Size

Total
Cost
Budget

Contingency
Budget
Estimate

Contingency
(% of
budget)

Final
Project
Cost

Contingency Costs
Incurred by Project Phase
(Design / Procurement /
Construction)

Contingency
Incurred /
Budgeted

<$15

8.09

0.46

6%

$7.76

0.34 (0.04/0.10/0.20)

74%

$15—$50

30.22

1.55

5%

$29.51

1.15 (0.20/0.30/0.65)

74%

$50-$100

70.70

3.09

4%

$68.19

2.24 (0.25/0.83/ 1.16)

72%

>$100

214.02

15.56

7%

$206.50

13.63 (2.00/4.24/7.39)

87%

All costs are in millions of dollars. Incurred contingency costs exclude excludes three phases: Project Planning Phase,
Demolition and Start Up.

Source: Cll (2001)

The contingency factors in Exhibit D-5 are higher than the recommended values in Exhibit D-4.
Because Exhibit D-5 data is empirical and the basis for the estimates in Exhibit D-4 is not clear,
EPA based its contingency factors in the WBS models primarily on the values in Exhibit D-5,
but incorporated additional price categories below $15 million with contingency factors above 6
percent. To create the contingency factors, EPA first converted the figures in Exhibit D-5, which
are expressed as percentages of a total budget, to markups. For instance, if the contingency
budget is 7 percent of a total budget, it represents a markup of 7 / (100 - 7) percent = 7.5 percent.
EPA modified the markups by a factor of 0.77, which is the average ratio of incurred to budgeted

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contingency costs in Exhibit D-5. Exhibit D-6 presents the resulting base contingency factors.
These represent the contingency or risk prior to consideration of technology complexity.

Exhibit D-6. WBS Model Contingency Factors Prior to Consideration of

Technology Complexity

Project Direct Cost Range

Base Contingency Factor

<$500,000

6.7%

$500,000 to $3,000,000

5.8%

$3,000,000 to $15,000,000

4.9%*

$15,000,000 to $50,000,000

4.1%*

$50,000,000 to $100,000,000

3.2%*

>$100,000,000

5.8%*

* Percentages based on Cll-Benchmarking & Metrics Analysis Results (CM, 2001).

While there are techniques and computer programs designed to estimate contingency factors for
large projects based on construction activity risk simulation, the engineering costing literature
and the example projects EPA reviewed do not provide specific quantitative guidance regarding
the effect of project complexity on contingency costs. Nevertheless, the anecdotal evidence
suggests that risks (and, therefore, contingency costs) increase when project complexity
increases.

Among the WBS technologies, project complexity depends on the type of technology employed
and the general degree of experience with the technology as it will be applied. Well-established
technologies, which have a depth of construction and technology installation and operational
history under a variety of conditions, are expected to have low risk with respect to unforeseen
problems during construction and installation. Recently developed technologies or ones that have
had limited application to a variety of water quality conditions and project sizes (or to the
conditions at the project in question) are expected to have a higher degree of risk.

To account for differences in contingency values associated with technology type and project
complexity, EPA identified four categories of project complexity and assigned multipliers that
the models use to adjust the contingency factors (up or down) from Exhibit D-6:

•	Low complexity = base contingency factor x 0.5

•	Average complexity = base contingency factor x 1.0

•	High complexity = base contingency factor x 1.5

•	Very high complexity = base contingency factor x 2.0.

Thus, for each technology, the applied contingency factor combines the effects of project size
and technology complexity to obtain the project specific contingency factor. EPA assigned a
project complexity category to each WBS technology based on general knowledge and the
application history of the technology to drinking water treatment. Exhibit D-7 shows this default
complexity category assignment. The user can change these values on the indirect assumptions

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sheet of each model if specific knowledge of the technology and its expected performance under
the site-specific conditions warrant such a change.

The WBS models assume that contingency costs are incurred only in high cost scenarios (see
Section 2.3). For low and medium cost estimates, the models assume construction is completed
with a minimum of unforeseen site-specific costs and, therefore, that none of the contingency
budget is incurred. Users can change this assumption on the indirect assumptions sheet of each
model.

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Exhibit D-7. WBS Default Complexity Factors by Technology

Technology

Risk Level Assigned to
Technology

Default Complexity
Factor

Acid Feed

Low

0.5

Cation Exchange

Low

0.5

Caustic Feed

Low

0.5

Chloramine

Low

0.5

Nontreatment Options

Low

0.5

Phosphate Feed

Low

0.5

Permanganate Addition

Low

0.5

Granular Activated Carbon

Average

1

Chlorine Gas

Average

1

Diffuse Aeration

Average

1

Packed Tower Aeration

Average

1

Adsorptive Media

High

1.5

Anion Exchange

High

1.5

Biological Treatment

High

1.5

Biologically Active Filtration

High

1.5

Chlorine Dioxide

High

1.5

Low-pressure Membranes (MicrofiItration/UItrafiItration)

High

1.5

Greensand Filtration

High

1.5

Hypochlorite

High

1.5

Multi-stage Bubble Aeration

High

1.5

Ozone

High

1.5

Reverse Osmosis/Nanofiltration

High

1.5

Tray Aeration

High

1.5

Ultraviolet Advanced Oxidation Processes

Very high

2

Ultraviolet Disinfection

Very high

2

D.13 Miscellaneous Allowance

In a cost estimate for a construction project, an allowance may be included for conditions or
events that the estimator can anticipate, but whose cost is not known with any degree of
certainty. If, for example, the site is expected to have contaminated soil that may require
remediation, the allowance will incorporate the resulting costs. An allowance differs from a
contingency cost, which provides contract coverage for unpredictable conditions. The allowance
funds account for anticipated additional costs that should become apparent at a later stage of the
project (for example, upon completion of the site investigation activities and the detailed
engineering design). Much of this cost is associated with knowledge of site-related conditions.

In a national average cost estimate such as the one that the WBS models generate, it is not
possible to allow for the specific conditions associated with any given site. However, the models

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include an allowance line item to simulate an average effect due to such conditions. The line also
accounts for the level of detail in the WBS design, since the models do not include all minor
process components.

The WBS models assume a miscellaneous allowance of 10 percent as a default. Since the
allowance addresses a modeling uncertainty, there is little guidance available from the cost
estimation literature. Instead, the assumption must be validated by comparing WBS output to
actual water treatment facility construction costs. Users can change the miscellaneous allowance
on the indirect assumptions sheet of each model.

D.14 Legal, Fiscal and Administrative

This category includes project management, accounting and administrative activities related to
the project, excluding permitting. The cost can range from 2 to 5 percent of the process cost. In
the WBS models, this category is considered to account for administrative costs that the
purchaser incurs in the course of procurement. These costs are distinct from the construction
management fee, which is included as a separate indirect cost (Section D.17). The WBS models
use a default value of 2 percent. Users can change this assumption on the indirect assumptions
sheet of each model.

D.15 Sales Tax

Water treatment plant projects may be exempt from the sales tax, particularly those constructed
with public funds. The default value in the WBS models is 0 percent, which reflects the status of
taxes in social cost analysis. Taxes are considered a transfer payment and not an actual social
cost, which is based on the concept of opportunity cost. Transfer payments are not included in
social cost analysis, so a default value of 0 percent is appropriate for social cost analysis. The
WBS models include a sales tax line item among indirect costs because the models can also be
used for private cost analysis (e.g., for a specific utility), which includes transfer payments.

Users can enter a sales tax percentage on the indirect assumptions sheet of each model in cases
where consideration of transfer payments is appropriate.

D.16 Financing During Construction

Engineering cost estimates include interest for financing of the project. Drinking water systems
can obtain financing through various sources including Drinking Water State Revolving Funds
(DWSRF), public-sector financing, private-sector borrowing or equity instruments. Exhibit D-8
shows interest rates for drinking water treatment projects derived from the EPA 2006
Community Water Systems Survey. The default value in the WBS models is 5 percent, which is
toward the higher end of the range of financing costs for public and private systems, and
implicitly assumes 1 year of financing during construction. For small systems with design flow
less than 1 MGD, the models assume 0 percent financing during construction, implicitly
accounting for the very short construction time required for these systems. Users can change the
assumptions for both large and small systems on the indirect assumptions sheet of each model.

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Exhibit D-8. Average Interest Rates for Capital Funds

System Ownership Type

Lender

Average Interest Rate
(All System Sizes)

Range of Average Interest
Rates

Public

DWSRF

2.3

LO
CO
I

O

Public

Other Public Sector

3.5

"st

I

LO
O

Public

Private Sector

4.6

o
LO
I

CsJ
"st

Public

Other

3.9

O
O

I



Private

DWSRF

5.6

0.8-6.2

Private

Other Public Sector

4.4

LO
LO
I

CO

Private

Private Sector

6.5

4.3-7.7

Private

Other

5.9

O
o

I

o
o

All Systems

DWSRF

2.6

CO

"st

I

o

All Systems

Other Public Sector

3.8

1.9-4.5

All Systems

Private Sector

5.2

LO
LO
I

CO

"st

All Systems

Other

4.3

O
o

I

o
o

All Systems

All Lenders

Data not available

0.0-10.0

DWSRF = Drinking Water State Revolving Funds

D.17 Construction Management and General Contractor Overhead

As discussed in Section D.4.2, the component costs in the WBS cost database include the cost of
installation, including O&P for the installing contractor. However, the installation cost does not
cover the cost of insurance, performance bonds, job supervision or other costs associated with
the general contractor. The WBS models account for these costs by combining costs and fees for
the following items:

•	Builder's risk insurance

•	Performance bonds

•	Construction management.

Builder's risk insurance is casualty insurance for the project during construction and may cover
various risks, such as vandalism, fire, theft or natural disasters. According to RSMeans (2009c),
a national average rate is 0.34 percent of the project cost. EPA adopted this assumption for the
WBS models. Users can adjust this rate on the indirect assumptions sheet of each model.

Performance bonds compensate the owner for losses due to contractor failure to complete work
according to specifications. RSMeans (2006) estimates the costs based on the total direct cost of
the project, as described in Exhibit D-9.

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Exhibit D-9. Cost of Performance Bonds

Project Direct Cost Range

Performance Bond Cost

<$100,000

2.5%

$100,000 to $500,000

$2,500 plus 1.5% of the amount over $100,000

$500,000 to $2,500,000

$8,500 plus 1.0% of the amount over $500,000

$2,500,000 to $5,000,000

$28,500 plus 0.75% of the amount over $2,500,000

$5,000,000 to $7,500,000

$47,250 plus 0.70% of the amount over $5,000,000

>$7,500,000

$64,750 plus 0.60% of the amount over $7,500,000

Source: RSMeans (2006), reference table R013113-80.

The construction management fee covers the cost of job supervision, an on-site office, main
office overhead and profit. Various sources provide individual estimates for these items, but the
WBS models roll them into a construction management fee to reflect a cost structure that the
owner might see. RSMeans (2009c) provides a table of typical construction management rates
for jobs of various sizes. EPA adapted those rates to develop those shown in Exhibit D-10.

Exhibit D-10. Construction Management Fees

Project Direct Cost Range

Construction Management Fee

<$100,000

10%

$100,000 to $250,000

9%

$250,000 to $1,000,000

6%

$1,000,000 to $5,000,000

5%

$5,000,000 to $10,000,000

4%

>$10,000,000

3.2%a

a. The reference quotes a fee range of 2.5% to 4% for a $50 million project. The WBS models assume an intermediate rate for
projects over $10 million.

Source: RSMeans (2009c), division 01 11 31.20.

The indirect line item for construction management and general contractor overhead sums all of
these costs. The costs can be omitted individually on the indirect assumptions sheet of each
model, either by an assumption that directly controls inclusion or exclusion or by setting the
appropriate percentage to zero. For example, in the case of small systems that use pre-engineered
package treatment plants, the models exclude the construction management fee portion by
default and include only the performance bond and builder's risk insurance. Because package
plants typically are skid-mounted and assembled offsite, they typically do not require a general
contractor to supervise their installation. Instead, their installation is managed by a single entity,
often the vendor that supplied the package.

D.18 City Index

This indirect cost accounts for city-specific and regional variability in materials and construction
costs. The city index factor included in the WBS models is expressed as a decimal number,
assuming a national average of 1.0. The default value in the WBS models is set to the national
average of 1.0, which is appropriate for estimating national compliance costs. Users wishing to

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adjust estimated costs to be more reflective of potential costs in specific geographic locations can
change the city index value on the output sheet. For example, to estimate costs for a city where
construction costs are 90 percent of the national average, the user would change the city index to
0.9. One source for region- or location-specific adjustment factors is RSMeans (2013), which
publishes average construction cost indices for various three-digit zip code locations.

D.19 List of Abbreviations and Symbols in this Appendix

DWSRF

Drinking Water State Revolving Funds

EPA

U.S. Environmental Protection Agency

ENR

Engineering News-Record

ft2

square feet

I&C

instrumentation and control

KW

kilowatt

LTL

less than a load

MGD

million gallons per day

O&P

overhead and profit

WBS

work breakdown structure

D.20 References

Association for the Advancement of Cost Engineering International (AACEI). 1996.

Certification Study Guide. Morgantown, West Virginia.

Allis, William A. 2005. Personal communication with L. Petruzzi, SAIC. April.

Air Force Combat Climatology Center (AFCCC). 2000. Engineering Weather Data: 2000
International Edition. Published by the National Climatic Data Center.

American Water Works Corporation (AWWC). 1999. Preliminary Cost Estimate Summary:
Alton Water Treatment Plant, H&S no. 1862. 7 January.

AWWC. 2001a. Seymour, Indiana Process Cost Estimate.

AWWC. 2001b. St. Joseph, Missouri Cost Estimate.

Burger, Riaan. 2003. "Contingency, Quantifying the Uncertainty." Cost Engineering 45, no. 8. 8
August.

California Department of Transportation (CADOT). 2001. Earth Pressure Theory and
Application.

Construction Industry Institute (CII). 2001. Benchmarking & Metrics Analysis Results. Austin,
Texas. May.

Fairfax Water Authority (FWA). 2003. New Construction Works Brochures. Virginia.

GeoEconomics Associates Incorporated. 2002. An Economic Analysis of Water Services. Chapter
5.

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Krynine, D.P. and W.R. Judd. 1957. Principles of Engineering Geology and Geotechnics.
McGraw-Hill. New York.

Minnesota Natural Resources Conservation Services (MNNRSC). 2003. General Guide for
Estimating Moist Soil Density. 10 May.

National Renewable Energy Laboratory (NREL). 2003. Gas-Fired Distributed Energy Resource
Technology Characterizations. U.S. Department of Energy.

RSMeans. 2006. Facilities Construction Cost Data. 21st Annual Edition. Kingston,
Massachusetts: RSMeans Company.

RSMeans. 2009a. Assemblies Cost Data. 34th Annual Edition. Kingston, Massachusetts:
RSMeans Company.

RSMeans. 2009b. Building Construction Cost Data. 67th Annual Edition. Kingston,
Massachusetts: RSMeans Company.

RSMeans. 2009c. Facilities Construction Cost Data. 24th Annual Edition. Kingston,
Massachusetts: RSMeans Company.

RSMeans. 2013. Facilities Construction Cost Data 2014. 29th Annual Edition. Norwell,
Massachusetts: Reed Construction Data LLC.

Scoutten, Inc. 2009. Opinion of Probable Cost for Town Of Buckeye Water And Wastewater
Infrastructure and Water Resources Improvements Associated with 2009 Development Fees.
Revised 11 May. Retrieved from http://www.buckeyeaz.gov/DocumentView.aspx?DID=640

Stone and Webster. 2001. Brayton Point Station Permit Renewal Application. Five Volumes.

Tampa Bay Water. 2006. West Pasco Infrastructure Project, Maytum WTP Modifications,
Project No. 05903. Memorandum from Kenneth R. Herd, Director of Operations and Facilities,
to Jerry L. Maxwell, General Manager. 1 December.

United States Army Corp of Engineers (U.S. ACOE). 1992. Revision of Thrust Block Criteria in
TM5-813-5/AFM88-10 VOL. 5 Appendix C. Publication Number: ETL 1110-3-446. 20 August.

U.S. Environmental Protection Agency (U.S. EPA). 2004. Capital Costs of Arsenic Removal
Technologies, U.S. EPA Arsenic Removal Demonstration Project, Round 1. EPA-600-R-04-201.
Cincinnati, OH: U.S. EPA, National Risk Management Research Laboratory.

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Appendix E. General Assumptions for Operating and

Maintenance Costs

E.1 Introduction

The work breakdown structure (WBS) models calculate operating and maintenance (O&M) costs
independently for each treatment technology. Nevertheless, there are several general assumptions
and estimation functions that are common to the O&M estimates across the treatment models.
This appendix describes those assumptions and functions. Any O&M cost element that is
technology-specific is included in the chapter describing that technology in the main document.

The O&M costs estimated in the WBS models primarily include annual expenses for:

•	Labor to operate and maintain the new treatment equipment

•	Chemicals required by the treatment

•	Materials needed to carry out maintenance (including small tools)

•	Energy.

Costs for commercial liability insurance, inspection fees, domestic waste disposal, property
insurance and other miscellaneous expenditures that are not directly related to the operation of
the technology are included in the WBS models by applying a miscellaneous allowance to the
total annual O&M costs. This calculation uses the same miscellaneous allowance percentage that
is applied to capital costs as an indirect line item (see Appendix D). Users can change this
percentage on the indirect assumptions sheet of each model.

The WBS models calculate O&M costs based on the inputs provided by the user on the input
sheet and values specified on the O&M assumptions sheet. These inputs include system size, raw
and finished water quality parameters and other factors that affect operation requirements such as
an option in the activated alumina model to regenerate media or operate on a throw away basis.
The design equations and assumptions incorporated in the O&M sheets are described below.

Despite provisions for user inputs, there are several factors that can affect site-specific O&M
costs in ways that are not readily reflected in the WBS outputs. These include:

•	Operator expertise

•	Equipment quality, design, installation and degree of automation

•	Environmental conditions (e.g., changes in raw water quality over time).

Some O&M costs components, such as energy for pumping water or chemicals for treatment, are
well defined and readily estimated using an engineering cost approach. Other O&M cost drivers,
however, depend on multiple factors that are difficult to quantify and, therefore, represent a
challenge for estimating costs. For example, the required level of effort to operate or maintain a
technology depends on the level of complexity and sophistication of the installed technology, the
size of the treatment system, the professional level or education and training of the operator and
state and local regulations for process staffing.

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To complicate matters further, there are trade-offs between system capital costs and O&M costs.
Higher cost equipment may require less intensive maintenance or less hands-on operation. For
example, using mixers and tanks to prepare brine solution for regenerating an anion exchanger
might reduce equipment costs compared to using salt saturators. However, salt saturators require
less labor to use and potentially reduce the need for a salt storage facility. Also high quality,
highly automated systems can significantly reduce labor requirements, but increase capital costs.
The U.S. Environmental Protection Agency (EPA) included some adjustments to O&M costs in
the WBS models to account for some types of savings, which are described below.

E.2 Labor Costs

The WBS models calculate the annual hours of O&M labor in the following categories:

•	Operator labor for operation and maintenance of process equipment

•	Operator labor for building maintenance

•	Managerial and clerical labor.

The WBS model labor hour estimates are intended to be incremental. That is, they only include
labor associated with the new treatment system components.

E.2.1 Operator Labor for Operation and Maintenance of Process Equipment

System operation includes the following primary tasks:

•	Collecting data from process instruments and recording system operating parameters

•	Preventative maintenance and calibration of process instruments

•	Verifying the proper operation of pumps, valves and other equipment and controlling the
treatment process by adjusting this equipment

•	Preventative maintenance of pumps, valves and other equipment

•	Inspection and maintenance of chemical supplies

•	Visual inspection of the treatment facility and system components

•	Other, technology-specific tasks (e.g., managing regeneration, backwash or media
replacement).

Labor required for these tasks is sensitive to the level of system automation. As discussed in
Section 2.3 and Appendix A, the user has the option to choose from three levels of automation:
manual, semi-automated and fully automated. The assumptions about labor required for each
task vary depending on the level of automation selected, as shown in Exhibit E-l and discussed
below. Users can change these assumptions, if desired, on the O&M assumptions sheet of each
model.

EPA compared model results using these assumptions with annual labor hours reported for 12
different water treatment facilities. Most of the resulting model estimates were within +50
percent to -30 percent of the annual labor hours reported for the sample facilities.

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Exhibit E-1. Operator Labor Assumptions for Three Levels of Automation

Task

Manual

Semi-automated

Automated

Record system operating parameters from process
instruments (includes routine sampling)

5 minutes per day
per instrument

5 minutes per day

5 minutes per day

Preventative maintenance and calibration of process
instruments

10 minutes per
month per
instrument

10 minutes per
month per
instrument

10 minutes per month
per instrument

Verify and adjust pump operating parameters

5 minutes per day
per pump

5 minutes per day
per pump

None

Preventative maintenance of pumps

30.25 hours per
year per pump

30.25 hours per
year per pump

30.25 hours per year
per pump

Verify and adjust valve positions

5 minutes per
week per valve

5 minutes per
week per valve

None

Preventative maintenance and inspection of valves

5 minutes per year
per valve

5 minutes per year
per valve

5 minutes per year per
valve

Visual inspection of facility

1 minute per day
per 100 square
feet of facility

1 minute per day
per 100 square
feet of facility

1 minute per day per
100 square feet of
facility

Inspect and maintain chemical supplies

120 minutes per

month per
chemical supply
tank

120 minutes per

month per
chemical supply
tank

120 minutes per month
per chemical supply
tank

Collecting Data from Process Instruments and Recording System Operating
Parameters

For manual systems, the models assume 5 minutes per day per instrument associated with day-
to-day operation of the treatment process (e.g., flow meter, head loss sensor). Instruments
associated with intermittent processes (e.g., backwash flow meters) are not included in this
estimate, because observation of these instruments is included the operator labor associated with
managing the intermittent process. In semi-automated and automated systems, the control system
handles the task of collecting information from the various process instruments, so operator labor
is reduced to 5 minutes per day to keep a record of operating parameters.

Preventative Maintenance and Calibration of Process Instruments

Regardless of the level of automation, the models assume 5 minutes per month for each
instrument, including those associated with intermittent processes. While some instruments (e.g.,
chlorine residual analyzers) may require calibration more frequently than monthly, others (e.g.,
head loss sensors) will require limited, less frequent maintenance. Therefore, the models use 10
minutes per month as an average across the various types of instruments.

Verify and Adjust Pump Operating Parameters

For manual and semi-automated systems, the models assume 5 minutes per day per pump,
including metering pumps associated with continuous chemical feed processes. Pumps
associated with intermittent processes (e.g., backwash pumps) are not included in this estimate,

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because operation of these pumps is included the operator labor associated with managing the
intermittent process. In automated systems, the control system handles this task, so no additional
operator labor is required.

Preventative Maintenance of Pumps

Regardless of level of automation, the models assume 30.25 hours per year for large, frequently
operated pumps (e.g., booster pumps). This estimate does not include small chemical metering
pumps, but does include backwash pumps when these are operated more frequently than weekly.
The estimate of 30.25 hours per year is based on a list of recommended pump maintenance
activities from a vendor, combined with an independent engineering estimate of hours required
for each activity, as shown in Exhibit E-2.

Exhibit E-2. Pump Maintenance Activities

Task

Interval

Estimated
Minutes/Task

Estimated Hours/Year

Check bearing temperature

Monthly

5

1

Changing lubricant/ adjusting power level

Monthly

30

6

Disassemble for inspection, reassemble

Monthly

60

12

Check oil

Quarterly

10

0.67

Check lubricated bearings for saponification

Quarterly

10

0.67

Removal of bearings and replace, reassemble

Quarterly

60

4

Check packing and replace if necessary, reassemble

6 months

60

2

Vibration readings

6 months

10

0.33

Remove casing and inspect pump

Annual

120

2

If parts are worn, replace

Annual

varies

covered by pump materials
percentage and pump
useful life

Clean deposits and/ or scaling

Annual

60

1

Clean out stuffing box piping

Annual

30

0.5

Measure and record suction and discharge pipe head

Annual

5

0.08

Total All Tasks

Annual

1,815

30.25

Verify and Adjust Valve Positions

For manual and semi-automated systems, the models assume 5 minutes per week per valve on
the main process line. In automated systems, the control system handles this task, so no
additional operator labor is required.

Preventative Maintenance and Inspection of Valves

Regardless of level of automation, the models assume 5 minutes per year per valve on the main
process line.

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Visual Inspection of Facility

Regardless of level of automation, the models assume 1 minute per week per 100 square feet (ft2)
of treatment system floor plan to conduct visual inspection of the overall process. This daily
inspection is in addition to inspection conducted as part of routine operation and maintenance of
major operational components (instruments, pumps and valves), as discussed above.

Inspect and Maintain Chemical Supplies

The models assume that chemical supplies, whether they are associated with continuous addition
or intermittent use, require additional attention beyond that included in daily visual inspection. In
particular, they also require labor associated with receiving chemical shipments. Regardless of
level of automation, the models assume 120 minutes per month for each chemical storage tank.
Although counted on the basis of the number of tanks, this estimate is intended to cover all
components associated with the chemical supply system (e.g., checking pipes and valves for
leaks and inspecting and maintaining small metering pumps).

Technology-Specific Tasks

Many of the technologies include activities in addition to day-to-day operation that may require
operator attention, depending on the level of automation (e.g., intermittent regeneration,
backwash or media replacement). Where this is the case, the technology chapters in the main
document describe the specific assumptions required to calculate operator labor.

E.2.2 Labor for Building Maintenance

The WBS models include a building maintenance cost based on the building area (i.e., using a
unit cost in dollars per square foot per year). EPA developed this cost based on two sources:
Whitestone Research (2009) and RSMeans (2013). Specifically, EPA selected a list of
appropriate building maintenance repair and repair tasks from those listed in the two sources.
The selected tasks include those associated with preventative maintenance, small repairs and
major repairs. EPA estimated a frequency for each task by averaging the frequency
recommended in each of the two sources. Exhibit E-3 identifies the tasks included in the
maintenance and repair buildup. The models include maintenance and repair tasks for heating
and cooling systems only for buildings with the relevant systems. To avoid double-counting, the
task list does not include tasks in the following categories:

•	Maintenance of treatment system components that are already explicitly considered in the
models' maintenance labor and materials costs (e.g., pumps, valves, instruments)

•	Full replacement of items that are explicitly given a useful life in the models (e.g., piping,
heating and cooling systems)

•	Repair tasks with a lower frequency than the useful life assumed in the models for the
related WBS line item (e.g., skylight replacement has a recommended frequency of 40
years, whereas the models assume a useful life for the entire building of 37 to 40 years).

For the buildup, EPA assumed a baseline building area of 4,000 ft2 and building components
corresponding to a medium-quality building (see the assumptions in Appendix B). EPA
estimated costs for each task using data from RSMeans (2013) and assuming that preventative
maintenance and minor repairs would be conducted using in-house labor, while major repairs

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would be conducted using outside contractors. These costs include both labor and materials.
Because repair needs do not follow a strict schedule, EPA annualized costs with no discount
rate—that is, a $100 task with a typical frequency of 5 years is assigned an annual cost of $20.

Labor accounts for most of the cost for the maintenance and repair tasks. Further, the Building
Cost Index and Construction Cost Index, the only two cost indices in the WBS cost database that
combine labor and material costs, do not include the costs of materials that are likely to be used
in building maintenance. The WBS cost database therefore uses the Employment Cost Index to
escalate the building maintenance costs to current year dollars.

Exhibit E-3. Building Maintenance and Repair Tasks

•	Minor repairs and refinishing for concrete floors

•	Repairs and waterproofing for exterior concrete block walls

•	Repairs and refinishing for doors

•	Roofing debris removal and inspections

•	Minor repairs and replacement for roofing membranes and flashing

•	Repairs to skylights

•	Repairs and refinishing for interior concrete block walls

•	Repairs and refinishing for drywall

•	Office painting

•	Vinyl tile flooring replacement

•	Repairs, refinishing and replacement for acoustic tile ceilings

•	Preventive maintenance, repairs and replacement for lavatories and lavatory fixtures

•	Water heater preventive maintenance, cleaning and servicing, overhauls and replacement

•	Repairs to pipe joints and fittings

•	Cleaning of drains

•	Maintenance, repair and replacement of gutters

•	Repai r and replacement of fans

•	Inspection and replacement of sprinkler systems

•	Maintenance, inspection, repair and replacement of electrical systems including switchgear, receptacles, wiring devices,
voice/data outlets and structure ground

•	Replacement of lamps, ballasts and lighting fixtures

•	Standby generator maintenance and inspection

•	Preventive maintenance of computers

E.2.3 Managerial and Administrative Labor

The models contain an assumption that managerial and administrative support levels for a new
treatment plant are equal to 10 percent of the total operator hours for system operation and
maintenance. This estimate is not intended to represent total administrative and managerial time
at a drinking water system, because total time includes many tasks unrelated to operating a new
treatment train. It only represents incremental time needed to provide administrative support for
the new treatment plant, e.g., processing supply orders. It also does not include labor time
associated with recordkeeping and reporting burden estimates that EPA must estimate and report
independently to comply with Paperwork Reduction Act requirements. Users can change the 10

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percent assumption for either or both of managerial and administrative labor on the O&M
assumptions sheet of each model.

E.2.4 Labor Unit Costs

To estimate the cost of the labor calculated in each of the categories above, the models multiply
labor hours by unit costs from the WBS cost database. These unit costs reflect average loaded
wage rates for applicable labor categories (i.e. technical, managerial and administrative) and vary
across system size. The WBS cost database uses the Employment Cost Index to escalate the rates
to current year dollars. Users can change the wage rates, if desired, in the data extracted from the
WBS cost database.

E.3 Chemicals

Each of the WBS models calculates annual chemical usage (in pounds or gallons per year) on a
technology-specific basis. The technology chapters in the main document describe these
calculations. In some models, these calculations also reflect the selected option for regeneration
or disposal of spent chemicals. Annual chemical costs equal the product of the annual chemical
requirements and the unit chemical costs in the WBS cost database.

E.4 Materials

The WBS models calculate the annual cost of materials in the following categories:

•	Materials for maintenance of booster or influent pumps

•	Materials for maintenance and operation of other, technology-specific equipment

•	Replacement of technology-specific equipment that occurs on an annual basis

•	Materials for building maintenance.

Pumps are operated continuously (or nearly continuously) and require preventive and routine
maintenance. Pumps are common to all the technologies. Each of the models assumes the annual
cost of materials for pumps is equal to 1 percent of their pre-installation capital cost to account
for consumable supplies and small parts requiring frequent replacement. This assumption is
based on input from the technology experts who reviewed the WBS models and commented that
the initial assumption of 5 percent was too high. Users can change this assumption on the O&M
assumptions sheet of each model. Although accidents or improper operation can result in a need
for major repairs that increase maintenance materials costs beyond 1 percent, the models do not
include these types of costs.

Some of the technologies include other equipment that may require significant maintenance (e.g.,
the blowers in the packed tower aeration and multi-stage bubble aeration technologies). The
models for these technologies include annual costs for maintenance materials. The technology
chapters in this document describe the specific calculations. In general, these calculations are
based a percentage of the pre-installation capital cost of the equipment.

Some of the technologies also include equipment components (e.g., membrane filter cartridges)
that require frequent replacement. Rather than treat these components as frequently replaced
capital items, the models handle the replacement costs in the O&M sheet. The replacement cost
calculations are based on assumptions about replacement frequency and unit costs from the WBS

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component cost database. The specific calculations are in the technology sections of the main
document.

The WBS models compute a cost for building maintenance that combines labor and materials.
The cost is discussed in Section E.2.2.

E.5 Energy

All of the WBS models calculate the annual cost of energy in the following categories:

•	Energy for operation of booster or influent pumps

•	Energy for operation of other, technology-specific items of equipment

•	Energy for lighting

•	Energy for ventilation

•	Energy for cooling

•	Energy for heating.

E.5.1 Energy for Pumps and Other Equipment

Booster or influent pumps are equipment common to all the technologies. Because these pumps
are operated continuously (or nearly continuously), they can represent significant energy
consumption. Therefore, each of the WBS models calculates pump operating horsepower based
on average flow, pump head and pump efficiency. The models then convert this operating
horsepower to megawatt-hours/year assuming continuous operation. To calculate annual cost, the
models then multiply the annual power requirement by the unit cost for electricity contained in
the WBS component cost database.

Some of the technologies include other equipment that consumes significant quantities of energy
(e.g., blowers, backwash pumps, mixers). For those technologies, the model also calculates the
energy for such equipment explicitly. The technology chapters in the main document describe
the specific energy calculations. In general, those calculations are similar to the energy
calculation for pumps.

E.5.2 Energy for Lighting

The models calculate annual lighting requirements based on the building square footage estimate
and the quality level of the building (see Appendix B). The building capital costs in the WBS
cost database include the cost of light fixtures for the following light requirements:

•	Sheds and low quality buildings, 0.3 watts/hour/ft2 of building area

•	Mid quality buildings, 0.6 watts/hour/ft2 of building area

•	High quality buildings, 1.2 watts/hour/ft2 of building area.

Multiplying the appropriate light requirement by 8.8 results in an energy usage rate in kilowatt
hours per ft2 per year. This conversion is based on operation of the lights 24 hours per day, 365
days per year. EPA evaluated these assumptions by calculating the granular activated carbon
contactor, pipe gallery and furnace area lighting requirements at the Richard Miller Water
Treatment Plant in Cincinnati, Ohio. For this facility, the lighting requirements are 1.5, 1.0 and
0.8 watts per hour per ft2 for the contactor, pipe gallery and regeneration areas, respectively, with

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a weighted average of 1.0 watt per hour per ft2, which is between the mid and high quality values
that EPA uses in the models. Users can change the lighting requirement for each level of
building quality on the O&M assumptions sheet of each model.

Because many systems are not lit during times an operator is not present, the models reduce
lighting energy requirements when a full-time operator presence is not required (possible for
small systems for many technologies) using the following factor (with a maximum of 1 to
account for large systems that might require more than one full-time operator):

Operator hours per year/ (24*365).

E.5.3 Energy for Ventilation

The models calculate ventilation requirements based on the assumptions shown in Exhibit E-4.
The technology experts who reviewed the assumptions for the WBS models confirmed the
reasonableness of these assumptions, although one expert commented that the air change rate for
pumps could be lower for systems in a northern climate. The WBS models continue to use the
value shown, however, because it is believed to be more reasonable for a national average
estimate and results in a more conservative (i.e., higher) estimate of ventilation energy
consumption. All of the models use these same assumptions with the exception of chlorination,
which has special ventilation requirements as described in that technology section. Users can
change the ventilation assumptions, if desired, on the O&M assumptions sheet of each WBS
technology model.

Exhibit E-4. Assumptions for Calculating Ventilation Requirements

Variable

Value used

Ventilation air change rate for contactor areas

3 air changes/hour

Ventilation air change rate for pump areas

20 air changes/hour

Ventilation air change rate for chemical storage areas

2 air changes/hour

Ventilation air change rate for offices

2 air changes/hour

Pressure drop across ventilation fans

0.25 pounds/ft2

Number of days with mechanical ventilation for small systems (less than 1 MGD)

90 days/year

Number of days with mechanical ventilation for medium systems (1 to 10 MGD)

120 days/year

Number of days with mechanical ventilation for large systems (greater than 10 MGD)

185 days/year

MGD = million gallons per day

The models first use the air change rate assumptions to calculate an overall weighted average air
change rate for each building based on the equipment present in that building. The models then
use this weighted average air change rate for each building in the following formula:

Ventilation energy (kWh/yr) = DAYS x 24 x 0.746 x Pdrop x FP x H x Achanges / 33,000
where:

DAYS = days per year with mechanical ventilation
Pdrop = pressure drop across ventilation fans (pounds/ft2)

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FP = building footprint (ft2)

H = building height (feet)

Achanges = weighted average air change rate for the building (air changes/hour)
E.5.4 Energy for Heating and Cooling

The models calculate heating and cooling requirements based on the assumptions shown in
Exhibit E-5. Users can change these assumptions, if desired, on the O&M assumptions sheet of
each WBS technology model. These assumptions are described in greater detail below.

R-values are a measure of the effective resistance to heat flow of an insulating barrier such as a
building envelope. The R-values assumed in the models (20 for walls, 49 for ceilings) are based
on minimum requirements from the 2021 International Energy Conservation Code for
commercial buildings in the majority of climate zones, assuming construction materials
consistent with those used to develop the unit building costs (see Appendix B) (ICC, 2021). The
user can change these values to reflect higher efficiency construction materials. In doing so,
however, the user should also examine the unit building costs extracted from the WBS cost
database to determine if they are consistent with the use of such construction materials.

Exhibit E-5. Assumptions for Calculating Heating and Cooling Requirements

Variable

Value used

R-value for walls

20 hour -ft?-°F /BTU

R-value for ceilings

49 hour -ft?-°F /BTU

Annual heating degree days

4,260 degree days

Annual cooling degree days

1,415 degree days

Heating ventilation/infiltration load

168,679 BTU/cfm

Cooling ventilation/infiltration load

51,771 BTU/cfm

Electric resistance heating efficiency

98%

Heat pump heating coefficient of performance

3.3

Natural gas non-condensing furnace efficiency

85%

Natural gas condensing furnace efficiency

90%

Standard oil furnace efficiency

82%

Mid-efficiency oil furnace efficiency

90%

Air conditioning energy efficiency ratio

11.8 BTU/Whr

Heat pump cooling energy efficiency ratio

11.8 BTU/Whr

BTU = British thermal unit; cfm = cubic feet per minute; Whr = watt hour

Annual heating and cooling degree days are based on data from the U.S. Energy Information
Administration (U.S. EIA, 2021). Specifically, the values used in the models (4,260 heating
degree days and 1,415 cooling degree days) are the national average of regional, population-
weighted data. EPA derived the heating and cooling ventilation/infiltration load values from data
in the Air Force Combat Climatology Center Engineering Weather Data Version 1.0 (U.S. Air
Force, 2000). Specifically, EPA selected climate data for 21 cities distributed geographically

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throughout the United States and calculated total annual heating and cooling losses. The values
used in the WBS models (168,679 BTU/cfm heating load and 51,771 BTU/cfm cooling load) are
those for the city (St. Louis) that represents the median total annual heating and cooling loss
from among the 21 cities. In combination, the degree day and ventilation/infiltration load values
used in the models are intended to represent a climate that produces a nationally representative
total heating and cooling requirement. The user can change these values to represent a specific
different climate. In doing so, however, the user should select values for the heating and cooling
measures, respectively, that are consistent with one another (i.e., reflective of a realistic climate).

The remaining values in the exhibit are related to the efficiency and performance of heating and
air conditioning equipment. Electric resistance heating efficiency is based on information from
the U.S. Department of Energy (U.S. DOE, 1997) in combination with guidance from Rosen
(2021). The heat pump heating coefficient of performance is based on requirements from the
Federal Energy Management Program, assuming a heat pump that is air-cooled and in the
135,000 to less than 240,000 BTU per hour category (U.S. DOE, 2021). The four furnace
efficiency assumptions consider minimum efficiencies as outlined in Title 42 of the U.S. Code
Chapter 77, Subchapter III: Improving Energy Efficiency, as well as trends and definitions from
the Appliance Standards Awareness Project (ASAP, 2021). EPA derived the air conditioning and
heat pump cooling energy efficiency ratios by converting the minimum Seasonal Energy
Efficiency Ratios for single-package units outlined in 10 CFR 430.32 to approximate energy
efficiency ratios using the formula outlined in Engebrecht and Hendron (2010). The user can
modify these values, as desired, to reflect the use of more or less efficient equipment.

The WBS models use the assumptions in Exhibit E-5, along with estimated building
dimensions, to calculate total annual heating and cooling losses. The models consider both
conductance losses and ventilation/infiltration losses. The models calculate conductance losses
for each building using the following formulae:

Conductance heating loss = 4 x S x H x Hdd x 24 / Rwaii + FP x Hdd x 24 / Rceiiing
Conductance cooling loss = 4 x S x H x Cdd x 24 / Rwaii + FP x Cdd x 24 / Rceiiing

where:

S = length of building side in feet (assumed to equal the square root of the building

footprint)

H = building height (feet)

Hdd = annual heating degree-days
Cdd = annual cooling degree-days
FP = building footprint (ft2)

Rwaii = R-value for walls
Rceiiing = R-value for ceiling.

The equations above represent the total heat transfer in British thermal units (BTU)/year through
all four walls and the ceiling of each building. The models assume heat transfer through the
building floor is negligible.

To calculate ventilation and infiltration losses, the models first calculate the air exchange rate in
cubic feet per minute (cfm) for each building using the following formula:

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Air exchange rate (cfm) = FP x H x Achanges / 60

where:

H = building height (feet)

FP = building footprint (ft2)

Achanges = weighted average air change rate for the building (air changes/hour, as
described above in the section on ventilation)

Note that, unlike the calculation for ventilation energy use, this calculation does not incorporate
assumptions about the frequency of mechanical ventilation. This is because heating and cooling
losses occur regardless of whether ventilation is achieved by mechanical or natural means.

The models then apply the air exchange rate calculated above to determine ventilation and
infiltration losses (in BTU/year) for each building using the following formulae:

Heating ventilation and infiltration heat loss = CFM x Hviioad
Cooling ventilation and infiltration heat loss = CFM x Cviioad

where:

CFM = air exchange rate (cfm, as calculated above)

Hviioad = heating ventilation/infiltration load (in BTU/cfm)

Cviioad = cooling ventilation/infiltration load (in BTU/cfm)

The models then sum conductance losses and ventilation/infiltration losses to determine total
annual heating and cooling requirements for each building. For cooling, the models add cooling
required to compensate for the waste heat generated by pumps (and other technology-specific
mechanical equipment).

The models then calculate heating and cooling energy consumption for each of several options
using these requirements, BTU values for the appropriate fuel (i.e., electricity, natural gas or oil)
and the efficiency factors shown in Exhibit E-5. For heating, the options are electric resistance
heating, electric heat pump, natural gas condensing or non-condensing furnace and standard or
mid-efficiency oil furnace. For cooling, the options are conventional air conditioning and electric
heat pump.

The models determine whether to include heating and cooling costs (both capital and O&M)
based on building size, system design flow and user input for component level (see Section 2.3),
as shown in Exhibit E-6. Users can change these assumptions on the indirect assumptions sheet
of each model. When heating and/or cooling are included, the models choose among the heating
and cooling system options based on the total annualized cost of each option (annual energy cost,
plus capital cost of the system annualized as discussed in Section 2.4). The models select the
option with the lowest annualized cost for inclusion in the system capital costs and add the
corresponding annual energy cost to O&M costs.

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Exhibit E-6. WBS Model Assumptions Regarding Inclusion of Heating and Cooling

Building Square
Footage

Component Cost
Level Selected

System Design Flow:
Less than 1 MGD

System Design Flow:
1 to 10 MGD

System Design Flow:
10 MGD or greater

500 or greater

Low

Neither

Heating Only

Heating and Cooling

500 or greater

Medium

Heating Only

Heating and Cooling

Heating and Cooling

500 or greater

High

Heating and Cooling

Heating and Cooling

Heating and Cooling

Less than 500

Low or Medium

Neither

Neither

Heating Only

Less than 500

High

Heating Only

Heating Only

Heating Only

MGD = million gallons per day

E.5.5 Energy Unit Costs

To estimate the cost of the energy consumption calculated in each of the categories above, the
models use unit costs from the WBS component cost database. These unit costs represent
national averages for each fuel (electricity, natural gas and diesel) obtained from the U.S.
Department of Energy's Energy Information Administration. Because energy costs are highly
variable, users can change these energy unit costs, if desired, in the data extracted from the WBS
cost database.

E.6 List of Abbreviations and Symbols in this Appendix

BTU	British thermal unit

cfm	cubic feet per minute

EPA	U.S. Environmental Protection Agency

ft2	square feet

kWh	kilowatt hour

MGD	million gallons per day

O&M	operating and maintenance

U.S. DOE	U.S. Department of Energy

WBS	work breakdown structure

Whr	watt hour

E.7 References

Appliance Standards Awareness Project. 2021. Furnaces. Retrieved from: https://appliance-
standards. org / product/furnace s

Code of Federal Regulations. Title 10. Part 430.32 Energy and water conservation standards and
their compliance dates. Retrieved from: https://www.ecfr.gov/current/title-10/chapter-
II/subchapter-D/part-43 0/subpart-C/section-43 0.32

Engebrecht, C. and Hendron, R. 2010. Building America House Simulation Protocols. Building
Technologies Program. Retrieved from: https://www.nrel.gov/docs/fyllosti/49246.pdf

International Code Council (ICC). 2021. 2021 International Energy Conservation Code: Chapter
4 [CEJ Commerical Energy Efficiency. Retrieved from:

https://codes.iccsafe.org/content/IECC2021P2/chapter-4-ce-commercial-energy-efficiency

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Rosen, M. A. 2021. Chapter 4 - Exergy analysis. In El Haj Assad, M. and Rosen, M.A. (Eds.),
Design and Performance Optimization of Renewable Energy Systems (pp. 43-60). Academic
Press. https://doi.org/10.1016/C2019-0-Q3733-8

RSMeans. 2013. Facilities Maintenance and Repair Cost Data 2014. 21st Annual Edition.
Norwell, Massachusetts: Reed Construction Data.

U.S. Air Force. 2000. Air Force Combat Climatology Center Engineering Weather Data.

Version 1.0.

U.S. Code. Chapter 77, Subchapter III: IMPROVING ENERGY EFFICIENCY. From Title 42—
THE PUBLIC HEALTH AND WELFARE. Retrieved from:

https://uscode. house. gov/view.xhtml?path=/prelim@title42/chapter77/subchapter3&edition=prel
im

U.S. Department of Energy (DOE). 1997. Saving Energy with Electric Resistance Heating.
DOE/GO-10097-381. FS 230. Retrieved from: https://www.nrel.gov/docs/legosti/fy97/6987.pdf

U. S. DOE. 2021. Incorporate Minimum Efficiency Requirements for Heating and Cooling
Products into Federal Acquisition Documents. Office of Energy Efficiency and Renewable
Energy, Federal Energy Management Program. Retrieved from:

https://www.energv.gov/eere/femp/incorporate-minimum-efficiencv-requirements-heating-and-
cooling-products-federal

U.S. Energy Information Administration. 2021. Monthly Energy Review. Table 1.9. Retrieved
from: https://www.eia.gov/energyexplained/units-and-calculators/degree-davs.php

Whitestone Research. 2009. The Whitestone Facility Maintenance and Repair Cost Reference
2009-2010. Fourteenth Annual Edition. October.

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