EPA 600/R-14/376 I October 2014 I www.epa.gov/research
United States
Environmental Protection
Agency
                Environmental and Cost Life Cycle
                Assessment of Disinfection Options
                for Municipal  Drinking Water
                Treatment
Office of Research and Development
National Homeland Security Research Center

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            ENVIRONMENTAL AND COST LIFE CYCLE
       ASSESSMENT OF DISINFECTION OPTIONS FOR
         MUNICIPAL DRINKING WATER TREATMENT
      Sarah Cashman2, Anthony Gaglione2, Janet Mosley2, Lori Weiss2, Troy R.
  Hawkins1, Nick J. Ashbolt3, Jennifer Cashdollar3, Xiaobo Xue4, Cissy Ma1, and
                                                        Sam Arden5
National Risk Management Research Laboratory, U.S. Environmental Protection
                             Agency Office of Research and Development
                                    2Eastern Research Group, Inc. (ERG)
3National Exposure Research Laboratory, U.S. Environmental Protection Agency,
                                    Office of Research and Development
  4Oak Ridge Institute for Science and Education (ORISE) Postdoctoral Research
                                                         Participant
      5 University of Florida Engineering School of Sustainable Infrastructure &
                                                       Environment
                                               Date: October 13, 2014

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ABSTRACT

EPA is evaluating water disinfection technologies in coordination with the Confluence Water
Technology Innovation  Cluster  (WTIC) and EPA's National  Risk Management  Research
Laboratory (NRMRL). EPA developed an environmental life cycle assessment (LCA) and cost
analysis  to evaluate  the  environmental  outcomes and costs associated  with innovative
disinfection water treatment technologies. EPA is also interested in establishing an LCA and cost
model  framework that could be used to study other technologies or  changes to  drinking water
and municipal  wastewater treatment systems  in the future.  For each technology,  there are
associated differences in pathogen removal, disinfection by-product formation, treatment facility
energy use and operating costs, input chemical requirements, and supply chain impacts.

This document summarizes the data collection, analysis,  and results for a  base case drinking
water treatment (DWT) plant reference model and alternative disinfection technologies. The base
case is modeled after the Greater Cincinnati Water  Works (GCWW) Richard Miller Treatment
Plant. The infrastructure and operational datasets collected through iterative  inquires and onsite
visit were used to develop the baseline life cycle model for the drinking water treatment system.
Results of the base  case  analysis  show global warming, energy  demand, fossil depletion,
acidification, human health cancer, human health criteria, and ecotoxicity impacts are largely
driven  by electricity consumption at the drinking water treatment plant and during distribution to
the consumer. Labor and energy costs are the largest contributions to DWT plant  costs. Disposal
of sedimentation waste is the greatest contributor to eutrophication.  Source water acquisition
accounts for the majority of blue water use, with 1.2 m3 of source water from the river required
to deliver 1 m3  of water to the consumer. Metal depletion impacts are primarily  governed by
chemical  usage in  the  pre-disinfection  and  fluoridation stages  as  well as infrastructure
requirements at the DWT plant and distribution network. Overall, the primary disinfection with
gaseous chlorine life cycle stage only contributes  zero to five percent to  the total  life cycle
impacts of DWT for the results  categories  examined. LCA and cost results decrease slightly
when excluding the adsorption step (0-15 percent).

EPA compared the base  case results to four in-plant disinfection alternatives. The disinfection
alternatives considered are in  different  stages of  development. In-plant alternatives include
disinfection by ultraviolet (UV) light (conventional  mercury-vapor bulb system, LED UV, and
plasma-bead UV) and oxidation/disinfection using ferrate  ions. The in-plant alternatives would
reduce the amount  of chlorine required by the drinking  water  treatment  plant among other
benefits. The datasets  for compiling the life cycle inventory of disinfection technologies were
based on  available  industrial specifics and  literature sources.  Utilization of ferrate  results in
environmental,  human health, and cost benefits for combined use in the pre-disinfection and
primary disinfection stages, since  ferrate acts as both a coagulant and disinfectant and only small
dosages are required for treatment. Application  of UV technology  increases impacts during
disinfection through increased electricity consumption and through new capital investment, but
eliminates  the formation of disinfection by-products and greatly reduces  hazardous chlorine
usage.  LED UV is more energy efficient compared to conventional mercury-vapor UV; however,
it  is currently  developed  only for point-of-use applications, and  not large-scale  treatment
facilities.
                                            11

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In addition, EPA considered point-of-use disinfection alternatives such as disposable membrane
tap filters and small scale LED UV disinfection, which may be used in hospitals and other health
care  facilities to further reduce exposure to pathogens for immune-compromised individuals.
Point-of-use  disinfection alternatives for use at home were not considered. The point-of-use
technologies  are add-on technologies and are not compared to the base case results. For hospital
point-of-use disinfection, the LED UV technology has the greater impacts  overall compared to
the disposable membrane tap filter.  The LED UV system requires 0.0039 kWh per m3 water
treated for operation; whereas, the disposable membrane tap filter does not require electricity for
generation.

In general, this analysis is provided to understand the potential impacts and trade-offs between
different drinking water disinfection technologies  within the framework of the entire drinking
water supply system,  and it is not intended to provide  a recommendation on whether  any
technology is superior to other technologies. The open-source and process based models built in
this  study are  flexible to incorporate future  development  of disinfection  technologies  and
associated datasets.
                                            in

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Although the information in this document has been funded by the United States Environmental
Protection Agency under Contract EP-C-12-021 to Eastern Research Group, Inc., it does not
necessarily reflect the views of the Agency and no official endorsement should be inferred.
                                            IV

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TABLE OF CONTENTS

1.    INTRODUCTION AND STUDY GOAL	1
2.    SCOPE	3
  2.1  Functional Unit	3
  2.2  System Boundaries	3
  2.3  Impacts and Flows Tracked	5
    2.3.1   Normalized and Weighted Results	7
3.    LCA METHODOLOGY	8
  3.1  Data Collection and Model	8
  3.2  Unit Processes	9
  3.3  Base Case Data Sources	10
  3.4  Infrastructure Modeling	15
  3.5  LCA Limitations	21
4.    BASE CASE COST ANALYSIS	22
  4.1  Base Case Data Sources	22
    4.1.1   Annual Operating Costs	22
    4.1.2   Capital Costs	23
  4.2  Base Case Cost Method	24
  4.3  Cost Data Quality, Assumptions, and Limitations	25
5.    BASE CASE RESULTS	25
  5.1  Base Case Normalized Results	31
  5.2  Infrastructure Contribution to Base Case Results	31
6.    BASELINE SENSITIVITY ANALYSES	34
7.    IN-PLANT ALTERNATIVE DISINFECTION TECHNOLOGIES	42
  7.1  System Boundaries	43
  7.2  Aquionics Conventional UV Disinfection System	44
    7.2.1   LCA Model	45
    7.2.2   Cost Analysis	47
    7.2.3   Results	48
  7.3  Aquionics LED UV Disinfection System	53
    7.3.1   LCA Model	53
    7.3.2   Unit Processes	54
    7.3.3   Results	55
  7.4  Ferrate Technology	60
    7.4.1   Data Collection and System Boundaries	60
    7.4.2   LCA Model	62
    7.4.3   Cost Analysis	64
    7.4.4   Results	66
  7.5  Imaging Systems Technology	74
  7.6  Comparative Results	74
8.    POINT-OF-USE ALTERNATIVE DISINFECTION TECHNOLOGIES	78
  8.1  System Boundaries	78
  8.2  Pall Point-of-Use Filter	79
    8.2.1   LCA Model	79
    8.2.2   Unit Processes	80
    8.2.3   Results	81
  8.3  LED UV Point-of-Use Filter	84
    8.3.1   LCA Model	84
    8.3.2   Unit Processes	85
    8.3.3   Results	86
  8.4  Comparative Results	88

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9.  OVERALL RESULTS SUMMARY	91
10. REFERENCES	91
                                VI

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List of Tables

Table 1. Primary unit process matrix for the two base case models	5
Table 2. Impact and flow results categories	7
Table 3. Data sources	11
Table 4. Incoming and outgoing water quality metrics for GCWW Richard Miller
Treatment Plant (per m3water)	12
Table 5. Base case DWT LCI model-input and output operational data (per m3 drinking
water delivered to consumer)	13
Table 6. Infrastructure requirements for drinking water treatment plant buildings and
features (perm3 water delivered to consumer)	17
Table 7. Infrastructure requirements for drinking water treatment plant on-site piping (per
m3 water delivered to consumer)	18
Table 8. Infrastructure requirements for drinking water treatment distribution system
piping (perm3 water delivered to consumer)	19
Table 9. Infrastructure requirements for drinking water treatment distribution system
water storage, motors, pumps, and valves (per m3 water delivered to consumer)	20
Table 10. Annual Costs collected from GCWW	23
Table 11. GCWW Capital Improvement Projects Spending for Facilities and Water
Mains from 2000 to 2011	24
Table 12. Base Case 1 and Base Case 2 results per m3 drinking water delivered to the
consumer	30
Table 13. Contribution of infrastructure to Base Case 1 results per m3 drinking water
delivered to the consumer	33
Table 14. Sensitivity analyses for base  case model runs	34
Table 15. U.S. electrical grid fuel profiles	35
Table 16. Unit process matrix for alternative disinfection technologies	43
Table 17. Conventional UV data sources	47
Table 18. Cost data provided by Aquionics.a	48
Table 19. Conventional UV results per m3 drinking water delivered to the consumer	49
Table 20. LED UV data sources	55
Table 21. LED UV results perm3 drinking water delivered to the consumer	56
Table 22. Ferrate data sources	64
Table 23. Cost data provided by FTT	64
Table 24. Ferrate results per m  drinking water delivered to the consumer	69
Table 25. Point-of-Use hospital filter data sources	81
Table 26. Base case and Base case plus point-of-use hospital filter results per m3 drinking
water delivered to the consumer	82
Table 27. Point-of-Use LED UV data sources	86
Table 28. Base case and Base case plus point-of-use hospital LED UV disinfection results
perm3 drinking water delivered to the consumer	87
                                           vn

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List of Figures

Figure 1. System boundaries of drinking water treatment base case options	4
Figure 2. System boundaries of drinking water treatment base case showing infrastructure
input	16
Figure 3. Base Case 1 contribution analysis results	27
Figure 4. Base Case 1 contribution analysis results with unit process detail	28
Figure 5. Base Case 1 and Base Case 2 comparative summary results	29
Figure 6. Percent change in impacts if adsorption is excluded	30
Figure 7. Base case normalized results	31
Figure 8. Infrastructure contribution analysis	32
Figure 9. Significance of electricity mix: RFC West versus U.S. average baseline	37
Figure 10. Tornado chart of the sensitivity results for the relative changes  in total costs
for Base Case 1	37
Figure 11. Base Case 1 DWTP electricity usage sensitivity analysis	38
Figure 12. Base case 1 distribution system electricity usage sensitivity analysis	38
Figure 13. Base Case 1 chlorine usage sensitivity analysis	39
Figure 14. Base Case 1 DWTP infrastructure lifetime sensitivity analysis	39
Figure 15. Base Case 1 distribution system infrastructure lifetime sensitivity analysis	40
Figure 16. Base Case 1 alum coagulant usage sensitivity analysis	40
Figure 17. Base Case 1 lime usage sensitivity analysis	41
Figure 18. Base Case 1 distribution sodium hypochlorite usage  sensitivity analysis	41
Figure 19. Base Case 1 natural gas for GAC reactivation sensitivity analysis	42
Figure 20. System boundaries of drinking water treatment base  case and in-plant
disinfection alternatives	44
Figure 21. Base Case 1 and conventional UV comparative summary results	50
Figure 22. Percent change in impacts if using conventional UV rather than gaseous
chlorine for disinfection	51
Figure 23. Conventional UV electricity usage sensitivity analysis	52
Figure 24. Tornado chart of the sensitivity results for the relative changes  in total costs
for the conventional UV scenario	53
Figure 25. Base Case 1 and LED UV comparative summary results	57
Figure 26. Percent change in impacts if using LED UV rather than gaseous chlorine for
disinfection	58
Figure 27. LED UV electricity usage sensitivity analysis	59
Figure 28. System boundaries of ferrate drinking water treatment	62
Figure 29. Base Case 1, Base Case 2, and ferrate comparative results by life cycle stage	70
Figure 30. Percent reduction when switching from Base Case 1  to ferrate DWT  system	71
Figure 31. Ferrate dosage sensitivity analysis	73
Figure 32. Tornado chart of the sensitivity results for the relative changes  in total costs
for the ferrate scenario	74
Figure 33. Summary comparative results of alternative disinfection technologies	76
Figure 34. Normalized comparative results for different drinking water treatment
disinfection technologies	77
Figure 3 5. System boundaries for hospital  point-of-use drinking water treatment	79
                                           Vlll

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Figure 36. Base Case 1 plus point-of-use hospital filter contribution analysis results	83
Figure 37. Base case percent change with point-of-use filter	84
Figure 38. Base Case 1 plus point-of-use hospital LED UV disinfection contribution
analysis results	88
Figure 39. Comparative results for different hospital point-of-use disinfection
technologies	90
                                             IX

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 1.     INTRODUCTION AND STUDY GOAL

 This  study investigates disinfection technologies that  are currently under development in the
 Cincinnati Region in coordination with the Confluence Water Technology Innovation Cluster1
 and EPA's National Risk Management  Research  Laboratory.  Each technology  provides an
 alternative  means  of disinfecting drinking water and  may address  goals related to reducing
 disinfection by-products,  improving microorganism and virus  reduction,  reducing life-cycle
 impacts, or reducing disinfection costs.

 EPA collected data from  the  Greater Cincinnati  Water  Works  (GCWW) Richard Miller
 Treatment Plant to develop a base case drinking water treatment (DWT) plant LCA model and
 cost analysis. The base case GCWW plant is a 106  million gallon per day (MGD)  plant, which
 uses  gaseous chlorine  as the primary disinfectant. GCWW uses a  granular activated carbon
 (GAC) system for removal of organics prior to chlorine addition. Additional details on the base
 case plant are provided in Sections  2.2 and 3.2. This study evaluated base case models with and
 without GAC. The goal for the base case LCA model and cost analysis is to:

    1. Evaluate the base case environmental outcomes and costs to  provide a  baseline for
       comparison to alternative disinfection technologies.
    2. Establish  an LCA and  cost model  framework that could be  used to  study other
       technologies or  changes to DWT systems.
 	                                                  9
 This study addresses the following research questions :

    1. What are the net life cycle impacts associated with drinking water treatment from source
       water acquisition through distribution?
    2. What are the contributions  of each life  cycle  stage  to  the net result for  each impact
       category?
    3. How do the two  different base-case drinking water treatment options compare to one
       another for each impact category?
    4. How do the impacts and costs change as parameters associated with disinfection, energy
       use,  and  disinfection by-products (DBF)  vary?  What  parameters  associated  with
       electricity use have the greatest effect on impacts and costs?

 This study compared the results of the base case analysis to four in-plant disinfection alternatives
 and examined  the additional impact of applying two point-of-use disinfection technologies for
 hospitals:
Confluence is a network of water technology researchers, businesses, utilities, and others in the southwest Ohio,
northern Kentucky, and southeast Indiana region. The group was formed in 2011 with help from EPA and the U.S.
Small Business Administration. See http://www.watercluster.org and http://www2.epa.gov/clusters-program for
more information.
2 This project requires the collection and use of existing data. EPA developed a Quality Assurance Project Plan
(QAPP) which outlines the quality objectives for this project. The plan is entitled Quality Assurance Project Plan
for Systems-Based Sustainability and Emerging Risks Performance Assessment of Cincinnati Regional Water
Technology Innovations:  Comparative Life Cycle Assessment and Cost Analysis of Water Treatment Options, and
was prepared by Eastern Research Group, Inc. for U.S. EPA Sustainable Technology Division, National Risk
Management  Research Laboratory. The plan was approved February 2013.

                                              1

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    •   Conventional ultraviolet (UV) disinfection - UV radiation can effectively treat drinking
       water for viruses and bacteria. This study evaluated replacing chlorine disinfection with a
       conventional UV system. EPA worked with Aquionics to develop the conventional UV
       disinfection model. Recently GCWW installed a UV system to use in conjunction with
       traditional chlorine disinfection to improve removal of pathogens.
    •   LED  UV disinfection -  Use  of a large-scale  LED UV  system.  EPA worked with
       Aquionics to develop the LED UV disinfection model.
    •   Plasma-bead UV disinfection - Use of a new technology developed by Imaging Systems,
       which generates UV light for disinfection.
                                               r\
    •   Ferrate disinfection - Use of ferrate (FeC>4 "), a strong oxidizer, for disinfection. Ferrate
       Treatment Technologies, LLC (FTT) has developed an on-site, skid-mounted method of
       producing ferrate  for disinfection. Ferrate can also be used  during  pre-treatment as a
       coagulant.
    •   Point-of-use disinfection using disposable membrane tap filters and small scale LED UV
       disinfection.

Each  technology  has differences  in  pathogen  removal, disinfection  by-product formation,
chemical and energy requirements, costs, and environmental benefits. EPA intends to answer the
following research questions through the disinfection alternative analysis:

    1.  What are the net life cycle impacts associated with each disinfection alternative (in-plant
       and point-of-use add-on)?
    2.  For which life cycle stages do the results for the in-plant alternatives differ from the base
       case?
    3.  How do the overall plant costs change for each of the in-plant alternatives?
    4.  What are the costs and environmental impacts  of additional reductions in pathogens for
       point-of-use add-ons in a health care facility?

The remainder of the  report provides details on the analysis and is organized into the following
sections:

    •   Section 2 defines the study scope.
    •   Section  3 provides details on the LCA methodology including a description of the unit
       processes included in the base case model.
    •   Section 4 describes the cost analysis.
    •   Section 5 presents  base case  results.
    •   Section 6 presents  base case  sensitivity results.
    •   Section 7 describes the in-plant alternative disinfection technologies, modifications to the
       LCA model and cost analysis, and results for each technology.
    •   Section 8 describes the point-of-use alternatives and compares costs of the alternative to
       additional pathogen reduction.
    •   Section 9 summarizes the study results.
    •   Section 10 provides the references for the study.

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2.     SCOPE

The base  case DWT  model includes  source  water  acquisition,  pre-disinfection,  primary
disinfection, and distribution.  This study examined environmental impacts and changes in costs
for different disinfection technologies; therefore, the base case established the reference case for
comparison to alternative drinking water disinfection technologies.

2.1    Functional Unit

The functional unit, which provides the basis for comparison, used in this study is the delivery to
the consumer of one cubic meter of water that  meets or exceeds National Primary  Drinking
Water Regulations  for microorganisms,  disinfectants, disinfectant by-products,  inorganics,
organics,  and  radionuclides.3 For  the  point-of-use  technology  analysis, the drinking water
delivered to the consumer has  a greater reduction in pathogens compared to the base case and in-
plant  disinfection technology alternatives analysis. Results for the  point-of-use analysis are,
therefore,  not compared directly to results for the base case or in-plant alternative technologies as
the end product delivered by these different pathways are not functionally equivalent.

2.2    System Boundaries

   Figure  1 illustrates the system for the DWT base case model. The system boundaries start at
acquisition of source water from  a river and end at delivery of the treated drinking water to the
consumer. Transportation requirements for all inputs to the processes within supply chains,  such
as transporting alum coagulant  to the  treatment  plant, are  also included as are all capital
equipment and infrastructure requirements for the drinking water treatment plant and distribution
network. Impacts for the following two base case model runs were evaluated:

    •   Base  Case 1: Representative moderate-sized water treatment facility, including  GAC
       adsorption.
    •   Base Case 2: Variation of the base case excluding GAC adsorption.
3 U.S. EPA (2013) "National Primary Drinking Water Regulations"
http ://water. epa.gov/drink/contaniinants/index. cfm

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                                       Source Water, River j
                                      V	.	^y
Source Water
Acquisition


                                   Flocculation
 Sand Production
Lime Production




Sedimentation

5
Filtration
1 	
« 	
	 1


Iron Sulfate
Production

Disposal of
Sedimentation
Waste
                                       w/
                                    adsorption
                                                   w/o
                                                 adsorption
                                                                 Sodium
                                                             Hexametaphosphate
                                                                Production
              Transport, Treated
             Drinking Water, Water
                Supply Pipeline
                                                               LEGEND
                                                                             Primary Input/
                                                                             Final Demand
                                                                             Primary Process
Reference
Supply Chain

Or gate (multiple
outputs)

Or gate (multiple
inputs)
              Figure I. System boundaries of drinking water treatment base case options.
            Drinking water treatment operations along with infrastructure raw material extraction and
            construction are  within the  system boundaries. End-of-life of infrastructure is excluded
            due to lack of available data.
The GCWW Richard Miller Treatment Plant serves customers in Cincinnati and the surrounding
towns in Ohio and Kentucky. The plant has 241,000 customers, of which 230,000 are residential
customers. The remaining are either businesses or other non-residential customers.  In terms of

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volume of water supplied, 16 percent of the treated water volume goes to wholesale customers,
48 percent of the treated water volume goes to residential  customers,  and 36 percent of the
treated water volume goes to non-residential customers.  GCWW was the first major municipal
water provider to utilize granular activated  carbon for adsorption of toxins.4 While this
adsorption process offers health benefits for consumers of GCWW water, it is not used in other
areas and is not necessary for some other water sources. While GCWW was used as a reference
for this study to allow the results to be based on actual operating conditions, the intent is that the
results can be extrapolated to provide input to decisions made for other systems as well. For this
reason, a second set of base case results without the GAC  adsorption process are provided.
Table 1
shows the primary life cycle stages and unit processes included in Base Case 1 and 2
Table 1. Primary unit process matrix for the two base case models.
Life Cycle Stage
Reported
Source Water Acquisition
Drinking Water Treatment
Plant, Energy and
Infrastructure
Pre-Disinfection
Primary Disinfection
Distribution
Use
Unit Processes Covered
Source Water Acquisition
Drinking Water Treatment Plant,
Energy Usage
Flocculation
Alum Coagulant
Sedimentation
Disposal, Sedimentation Waste
Filtration
Adsorption
GAC Production
GAC Regeneration
Primary Disinfection, Gaseous
Chlorine
Fluoridation
Transport, Treated Drinking
Water, Water Supply Pipeline
Distribution Infrastructure,
Drinking Water
Drinking Water Consumption
ctf
O
ctf
pq
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
(N
ctf
O
ctf
pq
X
X
X
X
X
X
X



X
X
X
X
X

2.3    Impacts and Flows Tracked

The full inventory of emissions generated in  an LCA study is lengthy and diverse, making it
difficult to interpret  emissions profiles in a concise and meaningful manner. Life Cycle Impact
 Activated Carbon: Solutions for Improving Water Quality, Zaid K. Chowdhury, Garret P. Westerhoff, R. Scott
Summers, Brian Leto, Kirk Nowack, American Water Works Association, 2012.

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Assessment (LCIA) helps with interpretation of the emissions inventory. In the LCIA phase, the
inventory of emissions is first classified into categories in which the emissions may contribute to
impacts on human health or the environment. Within each impact category, the  emissions are
then normalized to a common  reporting basis, using characterization factors that express the
impact of each substance relative to a reference substance.

Table 2 shows the complete list of impacts examined for the base case model runs. This study
addresses global, regional, and local impact categories. The LCIA method provided by the Tool
for the Reduction  and Assessment of Chemical and Environmental Impacts (TRACI), version
2.0, developed by  the U.S. EPA specifically to model environmental and human health impacts
in the U.S.,  is the  primary LCIA method applied in this  work.5 Additionally, the ReCiPe LCIA
method is used to characterize fossil  fuel, blue water use  (i.e. water  depletion), and metal
depletion.6 Energy is tracked based on point of extraction using the cumulative energy demand
method developed by Ecoinvent.7 The blue water use impact category represents freshwater use
from  surface  water  or groundwater sources.  The  blue water use category includes indirect
consumption  of water from upstream  processes,  such  as water withdrawals for electricity
generation (e.g., evaporative water losses from coal power cooling water and establishment of
                   o
hydroelectric dams).  Some flows specific to drinking water treatment,  and not typically reported
in LCA studies, are included in the results reported in the analysis:

    •   Cryptosporidium (Crypto) Exposure
    •   Total Trihalomethanes (TTHM) Exposure
    •   Chlorine Usage

These unique  flows are tracked based on data reported by GCWW for specific life cycle stages,
and do not cover all potential upstream exposure to cryptosporidium and TTHM or upstream use
of chlorine.  The purpose of tracking and displaying these aspects is to  provide a more balanced,
albeit cursory, analysis  of other benefits associated with  the disinfection technologies addressed
by  this  study. These results are intended to be supplemented by  additional  studies focused on
providing better resolution of these aspects for decision-making purposes within the context of a
specific system. They are provided here for context.
5 EPA's Tool for the Reduction and Assessment of Chemical and Other Environmental Impacts (TRACI), see:
http://www.epa.gov/nrmrl/std/sab/traci/.
6 Goedkoop M.J., Heijungs R, Huijbregts M, De Schryver A.; Struijs I, Van Zelm R, ReCiPe 2008, A life cycle
impact assessment method which comprises harmonised category indicators at the midpoint and the endpoint level;
First edition Report I: Characterisation; 6 January 2009, http://www.lcia-recipe.net
7 Ecoinvent Cumulative Energy Demand (CED) Method implemented in ecoinvent data v2.2. 2010. Swiss Centre
for Life Cycle Inventories.
8Pfister, S., Saner, D., Koehler, A. 2011. The environmental relevance of freshwater consumption in global power
production. International Journal of Life Cycle Assessment, 16 (6): 580-591.

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                         Table 2. Impact and flow results categories.
Category
Cost
Crypto Exposure
TTHM Exposure
Chlorine Usage
Global Warming
Energy Demand
Fossil Depletion
Acidification
Eutrophication
Blue Water Use
Smog
Ozone Depletion
Metal Depletion
Human Health,
Cancer, Total
Human Health,
NonCancer, Total
Human Health,
Criteria
Ecotoxicity, Total
Methodology
Cost Analysis
Individual Flow
Individual Flow
Individual Flow
TRACI 2.0
ecoinvent
ReCiPe
TRACI 2.0
TRACI 2.0
Custom
TRACI 2.0
TRACI 2.0
ReCiPe
TRACI 2.0
TRACI 2.0
TRACI 2.0
TRACI 2.0
Unit
$
oocyst
kg TTHM
kgd2
kg CO2 eq
MJeq
kg oil eq
H+ moles eq
kgNeq
m3
kg O3 eq
kgCFC-lleq
kg Fe eq
CTU
CTU
kg PM10 eq
CTU
Description
Measures total cost in U.S. dollars.
Measures exposure of consumer to cryptosporidium in
delivered drinking water. Cryptosporidum levels reported
in Distribution life cycle stage.
Measures exposure of consumer to TTHM in delivered
drinking water. TTHM levels reported in Distribution life
cycle stage.
Measures gaseous chlorine usage for primary
disinfection, which indicates on-site storage of this
hazardous chemical.
Represents the potential heat trapping capacity of
greenhouse gases.
Measures the total energy use from point of extraction.
Assesses the potential reduction of fossil fuel energy
resources.
Quantifies the potential acidifying effect of substances on
their environment.
Assesses potential impacts from excessive load of macro-
nutrients to the environment.
Calculates consumptive use of fresh surface or
groundwater.
Determines the potential formation of reactive substances
(e.g. tropospheric ozone) that cause harm to human health
and vegetation.
Measures potential stratospheric ozone depletion.
Assesses the potential reduction of metal resources.
A comparative toxic unit (CTU) for cancer characterizes
the probable increase in cancer related morbidity (from
inhalation or ingestion) for the total human population
per unit mass of a chemical emitted.
A CTU for noncancer characterizes the probable increase
in noncancer related morbidity (from inhalation or
ingestion) for the total human population per unit mass of
a chemical emitted.
Assesses human exposure to elevated paniculate matter
less than 10 um.
Assesses potential fate, exposure, and effect of chemicals
on the environment.
2.3.1   Normalized and Weighted Results

Normalization is an optional  step in LCA that aids in understanding the significance of the
impact assessment results. Normalization is conducted by dividing the impact category results by
a normalized value. The normalized value is typically the environmental burdens of the region of
interest either on an absolute  or per capita basis. The results presented here are normalized to
reflect person equivalents in the  U.S. using TRACI v2.1 normalization factors.9 Only  impacts
with TRACI normalization factors are shown. Some categories like blue water use and energy
demand are excluded due to lack of available normalization factors.
 Ryberg, M., Vieira, M.D.M., Zgola, M., Bare, I, and Rosenbaum, R.K., 2014. Updated US and Canadian
normalization factors for TRACI 2.1. Clean Techn Environ Policy, 16: 329-339.
                                            7

-------
Weighting is an additional optional step in LCA that provides a link between the quantitative
results and subjective choices of decision makers. This study applies weights to the normalized
results described above. The weights utilized here were developed by the National Institute of
Standards and Technology (NIST) for the BEES  (Building for Environmental and Economic
Sustainability) software.10 This weighting set was created specifically for the buildings  sector
context, which may not be completely compatible with the water treatment sector. However, due
to lack of a weighting set specific to the water treatment sector, this NIST weighting set has been
utilized.

3.     LCA METHODOLOGY

Development of a life cycle  assessment requires significant input data,  an LCA modeling
platform, and impact assessment methods. This section provides background on the development
of the LCA model.  Section 3.1 discusses the data collection method and model,  Section 3.2
describes  the unit  processes,  Section 3.3 lists the data sources,  and Section 3.4 describes
limitations of the LCA model.

In this study, GCWW provided much of the LCA input data for the unit processes listed in Table
1. This study also used publicly accessible and private databases to provide underlying data sets
describing the supply chains of inputs to the processes modeled here. For example, in addition to
the unit processes described in Section 3.2, an LCA also includes impacts from the production of
any materials required in the process.

3.1    Data Collection and Model

The accuracy of the study is directly related to the quality  of input data. Data were collected
electronically using Excel templates designed by the project team to be completed by GCWW.
Data collection was an iterative process whereby the project team asked GCWW multiple rounds
of questions to ensure  all necessary life cycle  and cost information was  being reported and
properly  interpreted in  the  assessment.  The quality and objectivity of results were  ensured
through carefully adhering to the data collection protocols and quality procedures laid out in the
Quality Assurance Project Plan prior to beginning work on the project.

Each  unit process in the life cycle inventory was constructed independently of all other unit
processes. This allows objective review of individual data sets before their contribution  to the
overall  life cycle  results  has  been  determined. Also, because  these  data  are reviewed
individually, EPA reviewed assumptions based on their relevance to the process rather than their
effect on the overall outcome of the study.

The model was constructed  in OpenLCA, an open-source LCA software package  provided by
GreenDelta.
10 Gloria, T.P., Lippiatt, B.C., and Cooper, J. 2007. Life cycle impact assessment weights to support environmentally
preferable purchasing in the United States. Environ. Sci. Technol, 41, 7551-7557.

-------
3.2    Unit Processes

EPA developed new unit processes for the specific DWT processes listed below (categorized by
the overall life cycle stage). As shown in    Figure 1, the DWT base case unit processes start
with source water acquisition  and end with drinking water use. Unit processes from background
LCI database (e.g.,  ecoinvent v2.2  and U.S. LCI) that  have not been modified are identified in
Section 3.3, Table 3 (Data Sources). On-site DWT plant infrastructure is included for each unit
where applicable. Section 3.4 covers the details of the infrastructure modeling.

Drinking water acquisition
    1.  Source Water Acquisition. The GCWW Miller Plant used for the base case model uses
       surface water from a river for the raw water source.

Drinking Water Treatment Plant, Energy Usage
    2.  Drinking Water Treatment Plant, Energy Usage. Covers all electricity required to
       pump in raw water, and pumping energy throughout the drinking water treatment plant.

Pre-Disinfection
    3.  Flocculation. Aggregates suspended solids by  adding coagulant and coagulant aid  and
       mixing to increase the particle size to allow settling. Alum is modeled as the coagulant.
    4.  Alum Coagulant. Production of average  alum derived from industrial aluminum sulfate.
    5.  Sedimentation.  Removes  suspended  solids  from  water by  gravity  settling.  In an
       intermediate step "lime addition", lime is added  in clarification basins prior to filtration.
    6.  Disposal, Sedimentation Waste. Disposal of settled solids to surface water.
    7.  Filtration. Removes   remaining  solids from  water using  a sand  filter.  Includes
       replacement  of filter materials during normal operation life of the filter.
    8.  Adsorption. Removes organics by a granular activated carbon (GAC) system. As noted
       in Table 1, adsorption is not included in Base Case 2.
    9.  Granular Activated Carbon Production. Production of average U.S. granular activated
       carbon from  bituminous coal. GAC production is not included in Base Case 2.
    10. Granular  Activated  Carbon   Regeneration.  Regenerates  activated  carbon  by
       conventional thermal regeneration  method with natural gas as the required energy source.
       Also includes  carbon loss and replacement. GAC regeneration is not included in Base
       Case 2.
    11. Conditioning. Adjust  pH using   sodium hydroxide and  addition  of  a polyphosphate,
       sodium hexametaphosphate.
    12. Pre-Disinfection. This unit  process  aggregates the upstream pre-disinfection unit
       processes from flocculation through conditioning.

Disinfection
    13. Primary Disinfection, Gaseous  Chlorine. Representative of a conventional  DWT
       system using gaseous chlorine for primary disinfection.

Distribution
    14. Fluoridation. Hydrofluorosilicic acid addition prior to distribution.
    15. Transport,  Treated Drinking Water,  Water Supply Pipeline.  Transporting treated
       drinking water to end users.  Accounts for pumping energy.

-------
    16. Valves for Distribution System. Steel required for production of valves for distribution
       system.
    17. Pumps  for Distribution System. Cast iron and  steel for production of pumps  for
       distribution system.
    18. Motors for Distribution System. Steel, copper, aluminum, and cast iron for production
       of motors for distribution system.
    19. Water Storage Infrastructure.  Concrete and steel  for construction  of water storage
       tanks, earthworks associated with reservoir construction.
    20. Distribution Pipe Network. Production and installation of concrete and iron pipes for
       distribution system.
    21. Distribution. This unit process aggregates upstream distribution unit processes including
       fluoridation,  pipeline  transport  of  the  treated  drinking  water,  and  infrastructure
       components of the distribution system. Sodium hypochlorite is also added as an input to
       the distribution life cycle stage as it is used in small amounts to boost the chlorine levels
       in certain sections of the distribution system.

Use
    22. Drinking Water Consumption.  Final delivery of water to an average consumer. This
       unit process aggregates the  other main life cycle stages and is  used to build the final
       product  system.  There  are no  actual  impacts  associated  with  the drinking water
       consumption life cycle stage itself.

3.3    Base Case Data Sources

Table 3  displays the  data sources used  for the  DWT base case  model. In general, data from
GCWW  were used where available. GCWW provided data for their Richard  Miller Treatment
Plant, which  produces approximately 106 MGD of finished drinking water. The incoming and
outgoing water quality metrics for the Richard Miler Treatment Plant reported for this study are
shown in Table 4. For upstream  processes that would  not be known  by  GCWW such as
information on  chemical production,  EPA  used information from the  National Renewable
Energy Laboratory's U.S. Life Cycle Inventory Database (U.S. LCI), a publically available life
cycle inventory source.11 Where data were not available from GWCC or the U.S. LCI, EPA used
ecoinvent v2.2,  a private Swiss  LCI database with  data for many unit processes.12 Table 5
presents the complete DWT base case LCI data used in the model on the basis of one cubic meter
of drinking water delivered to the consumer.
11 National Renewable Energy Lab. US LCI Database. See: http://www.nrel.gov/lci/database/default.asp.
12 Ecoinvent Centre (2010), ecoinvent data v2.2. ecoinvent reports No. 1-25, Swiss Centre for Life Cycle
Inventories.

                                            10

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                              Table 3. Data sources.
Process
Source Water Acquisition
Incoming Transport of Chemicals to DWTP
Gaseous Chlorine Production
Sodium Chloride Production
Flocculation
Aluminum Sulfate Production (Powder)
Sulfuric Acid Production
Aluminum Hydroxide Production
Iron Sulfate
Sedimentation (Operation)
Disposal  of Sedimentation Waste
Filtration (Operation)
Sand Production (for Use in Filter)
Adsorption
GAC Production
GAC Regeneration
Bituminous Coal Production
Conditioning
Sodium Hydroxide Production
Sodium Hexametaphosphatea
Lime Production
Primary Disinfection
Gaseous Chlorine Production
Sodium Hypochlorite Production
Fluoridation
Hydrofluorosilicic Acid Production11
Distribution (Operation)
Background Fuels and Energy
Infrastructure at the DWT Plant
Infrastructure in the Distribution System
Background Transportation Processes	
Data Source
Data Collection
Data Collection
ecoinvent v2.2
ecoinvent v2.2
Data Collection
ecoinvent v2.2
ecoinvent v2.2
ecoinvent v2.2
ecoinvent v2.2
Data Collection
Data Collection
Data Collection
ecoinvent v2.2
Data Collection
Data Collection
Data Collection
U.S. LCI
Data Collection
ecoinvent v2.2
ecoinvent v2.2
U.S. LCI
Data Collection
ecoinvent v2.2
ecoinvent v2.2
Data Collection
ecoinvent v2.2
Data Collection
U.S. LCI
Data Collection
Data Collection
U.S. LCI
•GCWW
•GCWW
-GCWW
•GCWW
•GCWW
•GCWW

•GCWW
•GCWW
•GCWW

-GCWW
-GCWW


•GCWW

•GCWW

•GCWW
•GCWW
a Using sodium tripolyphosphate as surrogate, since no available LCI data exists for sodium
hexametaphosphate.
b Using hydrogen fluoride (HF) as surrogate, since fluorosilicic acid is a by-product of HF production, and no
available LCA data exists for hydrofluorosilicic acid production.	
                                       11

-------
Table 4. Incoming and outgoing water quality metrics for GCWW Richard Miller Treatment Plant
                                       (per m3water).

Water Metrics
Ammonia
Arsenic
Chromium
Dissolved
organic carbon
Dissolved solids
Iron
Manganese
Nitrate
pH
Phosphorus
Suspended
solids
Temperature
Total organic
carbon
Turbidity
TTHM
Chlorine
Cryptosporidium
Giardia
E. coli
Heterotrophic
plate count
Incoming Water
Minimum
0.010
O.001
<5.0E-04
2.50
158
0.30
0.053
0.63
7.50
0.030
1.90
5.10
2.10
2.40
<5.0E-04
0
<20.0
<20.0
0
0
Maximum
0.19
0.0016
0.0029
3.30
299
0.30
0.053
1.14
8.40
0.11
225
33.0
4.80
307
<5.0E-04
0
<91.0
200
6,030,000
14,000,000,000
Average
0.050
O.001
0.0010
2.99
229
0.30
0.053
0.89
7.80
0.060
43.1
18.0
3.05
46.0
<5.0E-04
0
<51.0
20.0
1,340,000
2,250,000,000
Outgoing Water
Minimum
0
O.001
O.010
0.61
132
O.020
0.010
0.62
8.20
0.15
0
4.70
0.40
0.050
0.0078
1.13
0.80
O.80
0
0
Maximum
0
O.001
O.010
1.01
317
O.020
0.010
1.06
8.80
0.20
0
29.0
1.43
0.13
0.020
1.66
<1.10
<1.10
0
0
Average
0
O.001
O.010
0.94
228
O.020
0.010
0.86
8.80
0.17
0
17.0
0.85
0.070
0.016
1.37
<1.00
<1.00
0
0

Unit (per
m3 water)
g
g
g
g
g
g
g
g
pH
g
g
°C
g
NTU
g
g
oocysts
oocysts
counts
counts
 Source: GCWW primary data collection for the year 2011.
                                             12

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Table 5. Base case DWT LCI model-input and output operational data (per m3 drinking water delivered to consumer).

Unit
TOTAL
Quantity
Quantity by Life Cycle Stage
Source Water
Acquisition
Energy for
Pumping
Flocculation
Sedimentation
Disposal,
Sedimentation
Waste
Lime Addition
Filtration
Adsorption
GAC
Reactivation
Conditioning
d
|1§1
C ft 
-------


Combination truck transport,
sodium hypochlorite
Combination truck transport,
sodium hydroxide
Barge transport, sodium hydroxide
Combination truck transport
sodium hexametaphosphate
Combination truck transport
polymer (polyDADMAC)
Combination truck transport GAC
Unit
tkm
tkm
tkm
tkm
tkm
tkm
TOTAL
Quantity
2.7E-05
2.7E-05
6.0E-04
1.3E-04
9.8E-04
6.5E-04
Quantity by Life Cycle Stage
Source Water
Acquisition






Energy for
Pumping






Flocculation




9.8E-04

Sedimentation






Disposal,
Sedimentation
Waste






Lime Addition






Filtration






Adsorption





6.5E-04
GAC
Reactivation






Conditioning

2.7E-05
6.0E-04
1.3E-04


£
|lll
e .5 w °
fl 5 o 0






Fluoridation






Distribution
2.7E-05





3
bfL =
% « s - g-^
s oj .S es ft q
5 H Q > £ '£.






Drinking
Water
Consumption






Outputs
Waste &
Loss
Water
Emissions
Air
Emissions
Final
Product
Disposal of sedimentation waste
Water loss
Aluminum (water emissions)
Ammonia (water emission)
Biological oxygen demand (water
emission)
Chemical oxygen demand (water
emission)
Suspended solids (water emission)
Carbon monoxide (air emission)
Nitrogen oxides (air emission)
Particulates, <10 um (air emission)
Particulates, <2.5 um (air
emission)
Sulfur oxides (air emission)
Volatile organic compounds (air
emission)
Drinking water delivered to
consumer
liters
m3
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
kg
m3
0.048
0.19
0.0016
3.6E-06
3.9E-04
0.0081
0.016
2.7E-05
9.2E-05
1.5E-05
1.5E-05
2.9E-04
1.3E-05
1.00

0.0036








































0.048















0.0016
3.6E-06
3.9E-04
0.0081
0.016
























































2.7E-05
9.2E-05
1.5E-05
1.5E-05
2.9E-04
1.3E-05












































0.19







































1.00
Source: GCWW primary data collection from the year 2011.
                                                                                              14

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3.4    Infrastructure Modeling

Infrastructure at the drinking water treatment plant and for the distribution system was included
in the model based on primary data collected from GCWW. In the Figure 2 system boundaries,
infrastructure  components  modeled  are  shown in red.  Each  infrastructure component  was
normalized to a cubic meter  of  water delivered to a consumer.  It was assumed,  based on
discussion  with engineers  at  GCWW regarding replacement  rates, that the lifetime of the
buildings, features, and pipes is 100 years. A shorter lifetime of 25 years was estimated for the
pumps and motors. Infrastructure  was normalized by dividing the total infrastructure impact by
the total lifetime of the component, and then by the water delivered per year. It is assumed that
the water delivered per year (for every year during the  infrastructure component lifetime)  is
123,560,247 cubic meters,  which is  the volume of drinking  water delivered to consumers  in
2011. The infrastructure requirements for plant buildings and features (e.g., reservoirs, tanks),  at
plant piping,  distribution system  piping, water storage in  distribution system, and distribution
pumps and motors are  shown in Table 6 through Table 9.  To simplify the  model for the
distribution system  piping, only  pipe types that represent more than 0.5  percent  of the total
length  were included. Pipe types  greater than 0.5 percent of the length were then scaled up  to
represent 100  percent of the total distribution system pipe length. Construction burdens were
determined based on the volume of earthworks required per infrastructure component.
                                           15

-------
        GCWW RICHARD MILLER TREATMENT PLANT
                                   Source Water. Ri
                                           ", River

lntakeSl&S2

Pump Station
S1&S2


	
X


I
Source Water
Acquisition

                                                                           \  Primary Input/
                                                                           //  Final Demand
Figure 2. System boundaries of drinking water treatment base case showing infrastructure input.
                                               16

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  Table 6. Infrastructure requirements for drinking water treatment plant buildings and features (per m3 water delivered to consumer).

Life Cycle Stage
Source Water
Acquisition
Flocculation
Sedimentation
Filtration
Adsorption
Conditioning
Primary Disinfection
Fluoridation
Infrastructure Component
Intake 1 (to Pump Station 1)
Intake 2 (to Pump Station 2)
Pump Station 1 (Near River)
Pump Station 2 (Farther from River)
Pretreatment Complex
Settling Reservoir #1 (Closer to
Pump Station)
Settling Reservoir #2 (Farther from
Pump Station)
Chemical House (East)
Clarification Basins
Filter Building
GAC Facility
Caustic Soda Facility
Chlorine Injector Facility
Clearwell #1
Clearwell #2
Material Type
Earthworks
(m3)
1.2E-05
1.2E-05
8.9E-07
3.3E-06
7.4E-06
4.8E-05
5.3E-05
9.3E-07
6.4E-06
5.2E-06
1.4E-05
4.1E-06
2.6E-07
9.9E-06
2.4E-06
Reinforcing
Steel (kg)
0
0
0
5.1E-05
1.1E-04
0
0
1.4E-05
0
8.0E-05
2.1E-04
6.4E-05
4.1E-06
0
0
6.5' Concrete
piping (m)
0
0
0
6.9E-08
1.5E-07
0
0
1.9E-08
0
1.1E-07
2.9E-07
8.6E-08
5.5E-09
0
0
Concrete
(m3)
0
0
0
6.0E-07
1.3E-06
0
0
1.7E-07
4.1E-07
9.3E-07
2.5E-06
7.4E-07
4.8E-08
4.7E-07
1.8E-07
Bricks
(kg)
9.4E-04
9.4E-04
0
0
0
1.8E-04
1.9E-04
0
0
0
0
0
0
0
0
Limestone
(kg)
0.0012
0.0012
0.0024
0
0
0
0
0
0
0
0
0
0
0
0
Source: GCWWprimary data collection with estimations made with facility map.
                                                                 17

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Table 7. Infrastructure requirements for drinking water treatment plant on-site piping (per m3 water delivered to consumer).

Life Cycle
Stage
Source Water
Acquisition
Flocculation
Sedimentation
Filtration
Adsorption
Conditioning
Fluoridation
Diameter
7'
36"
50"
54"
72"
60"
72"
36"
54"
60"
72"
60"
36"
36"
36"
36"
Pipe Type
Gray Iron
Pipe (m)
0
2.7E-09
3.8E-08
1.9E-09
1.2E-09
6.5E-09
7.4E-08
2.3E-09
2.7E-09
7.3E-08
1.8E-08
3.7E-08
1.2E-08
6.9E-09
3.1E-09
1.5E-08
Ductile Iron
Pipe (m)
0
1.6E-09
2.3E-08
1.2E-09
7.0E-10
4.0E-09
4.5E-08
1.4E-09
1.6E-09
4.4E-08
LIE-OS
2.2E-08
7.4E-09
4.2E-09
1.9E-09
9.3E-09
Concrete
Pipe (m)
9.8E-08
2.4E-10
3.4E-09
1.7E-10
l.OE-10
5.9E-10
6.7E-09
2.1E-10
2.4E-10
6.6E-09
1.7E-09
3.3E-09
1.1E-09
6.2E-10
2.8E-10
1.4E-09

Total
Length
(m)
9.8E-08
4.6E-09
6.4E-08
3.3E-09
2.0E-09
LIE-OS
1.3E-07
3.9E-09
4.6E-09
1.2E-07
3.1E-08
6.3E-08
2.1E-08
1.2E-08
5.2E-09
2.6E-08
Earthworks
(m3)
l.OE-06
1.8E-08
3.5E-07
2.0E-08
1.7E-08
7.6E-08
1.1E-06
1.5E-08
2.8E-08
8.4E-07
2.7E-07
4.3E-07
7.0E-08
4.6E-08
2.1E-08
l.OE-07
              Source: GCWW primary data collection with estimations made with facility map.
                                                          18

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  Table 8. Infrastructure requirements for drinking water treatment distribution system piping (per m3 water delivered to consumer).

Life Cycle
Stage
Distribution
Diameter
0.75"
1"
1.5"
2"
2.5"
3"
4"
6"
8"
10"
12"
16"
20"
24"
30"
35"
36"
42"
44"
46"
48"
54"
60"
Pipe Type
Gray Iron
(m)
2.30E-09
6.76E-09
1.06E-08
2.90E-07
O.OOE+00
1.88E-08
1.52E-06
7.52E-05
9.28E-05
4.05E-06
3.21E-05
3.85E-06
8.10E-06
4.71E-06
9.96E-07
3.98E-06
4.55E-06
9.26E-07
2.95E-06
3.57E-07
1.29E-06
2.73E-07
3.06E-07
Ductile
Iron (m)
1.39E-09
4.10E-09
6.41E-09
1.76E-07
O.OOE+00
1.14E-08
9.19E-07
4.55E-05
5.62E-05
2.45E-06
1.94E-05
2.33E-06
4.91E-06
2.85E-06
6.03E-07
2.41E-06
2.76E-06
5.61E-07
1.79E-06
2.16E-07
7.82E-07
1.66E-07
1.85E-07
Concrete
(m)
2.07E-10
6.09E-10
9.52E-10
2.61E-08
O.OOE+00
1.69E-09
1.37E-07
6.77E-06
8.36E-06
3.65E-07
2.89E-06
3.47E-07
7.29E-07
4.24E-07
8.97E-08
3.58E-07
4.10E-07
8.34E-08
2.66E-07
3.22E-08
1.16E-07
2.46E-08
2.76E-08
Steel (m)
1.81E-11
5.32E-11
8.33E-11
2.28E-09
O.OOE+00
1.48E-10
1.19E-08
5.92E-07
7.31E-07
3.19E-08
2.53E-07
3.03E-08
6.38E-08
3.71E-08
7.84E-09
3.13E-08
3.58E-08
7.29E-09
2.32E-08
2.81E-09
1.02E-08
2.15E-09
2.41E-09
Copper
(m)
4.78E-12
1.41E-11
2.20E-11
6.03E-10
O.OOE+00
3.90E-11
3.15E-09
1.56E-07
1.93E-07
8.41E-09
6.67E-08
8.00E-09
1.68E-08
9.78E-09
2.07E-09
8.26E-09
9.45E-09
1.92E-09
6.13E-09
7.42E-10
2.68E-09
5.68E-10
6.36E-10
PVC (m)
1.26E-12
3.70E-12
5.78E-12
1.59E-10
O.OOE+00
1.03E-11
8.30E-10
4.11E-08
5.07E-08
2.21E-09
1.76E-08
2.11E-09
4.43E-09
2.57E-09
5.45E-10
2.17E-09
2.49E-09
5.06E-10
1.61E-09
1.95E-10
7.06E-10
1.49E-10
1.67E-10
HOPE
(m)
5.41E-12
1.59E-11
2.49E-11
6.82E-10
O.OOE+00
4.41E-11
3.57E-09
1.77E-07
2.18E-07
9.52E-09
7.55E-08
9.06E-09
1.90E-08
1.11E-08
2.34E-09
9.35E-09
1.07E-08
2.18E-09
6.94E-09
8.40E-10
3.04E-09
6.42E-10
7.19E-10
Transite
(m)
1.27E-11
3.73E-11
5.84E-11
1.60E-09
O.OOE+00
1.04E-10
8.38E-09
4.15E-07
5.12E-07
2.24E-08
1.77E-07
2.13E-08
4.47E-08
2.60E-08
5.50E-09
2.20E-08
2.51E-08
5.11E-09
1.63E-08
1.97E-09
7.13E-09
1.51E-09
1.69E-09

Total
Length
(m)
3.95E-09
1.16E-08
1.81E-08
4.97E-07
O.OOE+00
3.22E-08
2.60E-06
1.29E-04
1.59E-04
6.94E-06
5.50E-05
6.60E-06
1.39E-05
8.07E-06
1.71E-06
6.82E-06
7.80E-06
1.59E-06
5.06E-06
6.13E-07
2.21E-06
4.68E-07
5.25E-07
Earthworks
(m3)
4.21E-09
1.25E-08
2.01E-08
5.67E-07
O.OOE+00
3.87E-08
3.29E-06
1.80E-04
2.43E-04
1.16E-05
9.97E-05
1.40E-05
3.39E-05
2.25E-05
5.71E-06
2.62E-05
3.08E-05
7.30E-06
2.44E-05
3.10E-06
1.17E-05
2.83E-06
3.58E-06
Source: GCWW Primary data collection from 2011 water main inventory.
                                                               19

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Table 9. Infrastructure requirements for drinking water treatment distribution system water storage, motors, pumps, and valves (per m3
                                                 water delivered to consumer).

Life Cycle
Stage
Distribution
Infrastructure
Water Storage Tanks
Reservoirs
Motors
Pumps
Valves
Material Type
Concrete
(m3)
3.2E-08
0
0
0
0
Steel
(kg)
6.4E-05
0
8.8E-06
0
0.0021
Earthworks
(m3)
0
2.9E-05
0
0
0
Electrical
steel (kg)
0
0
4.1E-05
0
0
Stainless
18/8 coil
(kg)
0
0
0
4.5E-06
0
Cast
Iron
(kg)
0
0
3.9E-05
6.0E-05
0
Aluminum
(kg)
0
0
2.4E-06
0
0
Copper
(kg)
0
0
7.1E-
06
0
0
     Source: GCWWprimary data collection.
                                                              20

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3.5    LCA Limitations

While limitations of this study are discussed throughout this paper, some of the main limitations
that readers should understand when interpreting the data and findings are as follows:

   •   Water Quality Metrics. A unique aspect to this study is that detailed water metrics were
       collected for source water quality, disinfection by-products, and pathogens. The majority
       of metrics under these categories are not included in standard LCIA methods; therefore,
       these metrics are excluded from the OpenLCA model and are not linked to changes in the
       model. However, TTHM and cryptosporidium exposure are reported as results categories
       under the distribution life cycle stage. They are reported under the distribution life cycle
       stage as this is where human  exposure to these pathogens and DBFs occurs.
   •   Infrastructure and  Capital  Equipment. While primary data were collected  for
       infrastructure at the drinking  water plant, only material  and installation burdens  are
       included. Assembly of the actual components (e.g., pumps, motors, tanks) and end-of-life
       of the infrastructure are excluded due to lack of available data. Exclusion of assembly is
       not the case for the piping  (at plant and  in distribution  system), which does includes
       impacts from assembly. Additionally, the infrastructure burdens are normalized over each
       component's total lifetime assuming that the water delivered every year is 123,560,247
       cubic meters, which was the volume of delivered to consumers in 2011. In actuality, there
       would  be differences in water delivered per year over time. The lifetimes assumed for
       each component are estimates based on historical information of the GCWW facility;
       however, the study does include a sensitivity analysis to look at a wider range of potential
       lifetimes  of infrastructure components.
   •   DWT  Plant Electricity Consumption. Electricity consumption at the drinking water
       treatment plant could not be  split out by life cycle stages within the plant. Therefore, this
       electricity consumption is reported as a separate life cycle stage in the results ("Pumping
       Energy, at Drinking Water  Treatment Plant"), when in  reality  it should be allocated
       among DWT unit processes.
   •   Support  Personnel Requirements. Support personnel requirements are included in the
       cost analysis, but excluded from the LCA model. The energy and wastes associated with
       research and development, sales, and administrative personnel or related activities  are not
       included.
   •   Transferability of Results. While this study is intended to inform decision-making for a
       wide range of stakeholders,  the data presented here relate to one representative facility.
       Further work is recommended to understand the variability of  key  parameters  across
       specific situations.
   •   Representativeness  of Background Data. Background processes  are representative of
       either U.S.  average data (in the case of data from U.S. LCI) or European average  (in the
       case  of ecoinvent)  data.  In some cases European ecoinvent processes were used to
       represent U.S. inputs to the  model  (e.g., for chemical inputs) due to lack of available
       representative U.S.  processes for these inputs. The background data, however, met the
       criteria listed in the project  QAPP for completeness,  representativeness, accuracy, and
       reliability.
                                           21

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   •   Representativeness of supply chains for sodium hexametaphosphate and sodium
       fluorosilicate. LCI data for sodium hexametaphosphate or sodium fluorosilicate were not
       available for use in this study. Therefore, surrogate processes of sodium tripolyphosphate
       and hydrogen fluoride were used to model sodium  hexametaphosphate  and sodium
       fluorosilicate respectively. These surrogates were chosen as the production processes for
       these chemicals were closest to the actual chemicals used.
   •   Data Accuracy and Uncertainty. In a complex study with literally thousands of numeric
       entries, the accuracy of the data and how it affects conclusions is truly a difficult subject,
       and one that does not lend itself to standard error analysis techniques. The reader should
       keep in mind the uncertainty associated with LCA models when interpreting the results.
       Comparative  conclusions  should  not be drawn  based  on small differences in  impact
       results.

4.     BASE CASE COST ANALYSIS

The focus of the cost analysis is to understand the contribution of life cycle stages to the overall
cost of water delivered  and, moving forward, to determine how different disinfection alternatives
impact the final cost of water to the consumer. The remainder of this section provides additional
details on the cost analysis data, methodology, and assumptions.13

4.1    Base Case Data Sources

The costs analysis used actual cost data provided by GCWW. GCWW provided annual operating
costs for the Richard Miller Treatment Plant from 2011 and capital improvement project costs
from 2000 to 2011. GCWW provided the treatment plant operating costs detailed by treatment
unit process.

4.1.1   Annual Operating Costs

Table 10 shows the costs included in each DWT stage.  GCWW does not track maintenance for
the acquisition  system separately. Therefore, costs were not  allocated to  the drinking water
acquisition process.  In addition,  many costs, such as  operating and  maintenance  labor, are
incurred  on a plant-wide basis.  Therefore, a separate line item for overhead is included in the
costs. Table 10 also shows the total plant costs for both Base 1 and Base Case 2.

In addition to the cost  data elements listed  in Table 10, GCWW also provided information on
revenues and the price of drinking  water to  the  consumer. EPA used these  data elements to
evaluate how changes to the disinfection technology may change revenues and  consumer prices.
These data were not used in the base case model.
13 All supporting data used in the cost analysis are included in a separate Excel file.

                                           22

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                         Table 10. Annual Costs collected from GCWW.
Stage
Drinking Water
Acquisition
Drinking Water Treatment
Plant, Energy and
Infrastructure
Pre-Disinfection
Primary Disinfection
Distribution
Overhead
Unit Processes
Included in Base
Cases 1 and 2
Acquisition

Flocculation
Sedimentation
Filtration (sand)
GAC adsorption
Conditioning
Gaseous chlorine
Fluoridation
Distribution
Plant overhead for
all processes other
than primary
disinfection
Cost Elements
None
• Electricity for pumping3
• Chemicals (alum, polymer)
• Lime
• Sludge removal
• Sand replacement
• Sand disposal
• GAC replacement
• GAC regeneration (natural
gas, permit costs)b
• Chemicals (caustic soda,
sodium
hexametaphosphate)
• Chemicals (gaseous
chlorine)
• Maintenance0
• Chemicals
(hydrofluorosilicic acid)
• Chemicals (sodium
hypochlorite)
• Electricity"1
• Labor
• Maintenance
Total Base Case 1
Total Base Case 2 (no GAC)
Cost ($/year)
Included in overhead
$1,283,000
$983,000
$69,000
$30,000
$1,515,000
$898,000
$128,000
$365,000
$2,508,000
$2,212,000
$9,992,000
$8,477,000
a GCWW provided an annual amount of purchased electricity at the plant of 39,125,286 kWh and a unit cost of
electricity of $0.0328/kWh. EPA calculated the annual cost of electricity.
b GCWW estimated that 42,000 ccf of natural gas are required per regeneration of GAC and 18 regenerations occur
per year. GCWW provided a unit cost of natural gas of $0.0057/scf (1 ccf =100 scf). EPA calculated the annual cost
of natural gas.
0 Maintenance costs for the disinfection unit process are broken out  separately from the overall maintenance costs to
evaluate potential changes for the alternative disinfection technology.
d GCWW provided an annual amount of electricity for distribution of 76,137,689 kWh and a unit cost of electricity
of $0.0328/kWh. EPA calculated the annual cost of electricity.

4.1.2  Capital Costs

GCWW provided data on capital improvement project (CIP) expenditures from 2000 to 2011 for
all of their operations (not limited to the Richard Miller Treatment Plant). GCWW provided the
capital spending data in two categories:
    •  Facilities,  including  water  treatment   plants,  distribution  pump   stations,  backup
       generators, reservoirs, and storage tanks; and
    •  Water mains, including  replacements and expansions.
                                               23

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Table 11  summarizes the CIP  spending  from 2000 to 2011. As can be seen,  yearly capital
spending can vary significantly depending on the extent  and nature of capital improvement
projects. For example, the $14,855,000 CIP spending on facilities in 2011 covered 29 projects,
including: beginning construction of the UV treatment facility and replacing a portion of the
filter  house roof at  the  Richard Miller  Treatment Plant; repairing  secondary  clarifiers and
building a new sewer line at the Bolton Treatment Plant; and construction of a  pump station,
backup generator, reservoir, and elevated storage tank along the distribution system.

From 2000 to 2011, the  average annual  facility  CIP spending is $9,076,083  with a standard
deviation of $4,023,380, or about 44% of the average. This standard deviation reflects the large
variation from year to year.

GCWW has a goal of replacing 1% of water mains each year. In 2011, the 34.4 miles of water
main work encompassed 4.8 miles of new main extensions and 29.6 miles (or about 0.94%) of
water main replacement. The running average of water main replacement from 2000 to 2011 is
0.98% per year. From 2000 to 2011, the average annual water main CIP spending is $32,511,458
with an average of 44 miles of water  main work per year. The standard deviation  of spending is
$6,545,454, or about 20% of the average.  The average spending per mile of water main work is
approximately $739,180 per mile.

  Table 11. GCWW Capital Improvement Projects Spending for Facilities and Water Mains from
                                      2000 to 2011
Year
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
Facilities Capital
Improvement Projects
CIP Spending
$ 14,855,000
$ 12,157,000
$ 5,889,000
$ 4,833,000
$ 3,985,000
$ 8,061,000
$ 7,936,000
$ 9,773,000
$ 13,197,000
$ 14,693,000
$ 9,856,000
$ 3,678,000
Water Main Installations Capital Improvement
Projects
Miles Completed
34.4
36.2
32.3
46.3
35.1
44.9
52.3
61.1
61.0
48.4
30.3
45.5
Water Main Design
Estimated Value
$ 33,207,825
$ 40,169,576
$ 40,997,569
$ 27,779,798
$ 35,469,183
$ 32,067,642
$ 22,707,669
$ 28,039,881
$ 35,999,391
$ 42,008,784
$ 26,693,046
$ 24,997,132
       Source: GCWW Engineering Division Report to the Director.

4.2    Base Case Cost Method

EPA calculated the Base Case 1 and 2 costs directly from input provided by GCWW using the
steps below.

    1.   Match provided costs to the unit processes shown in Table 1.  Note that GCWW did not
       provide  costs for ferric sulfate, which was only used 100 days in 2011. Costs for this
       chemical are not included.
                                           24

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   2.  Calculate the unit costs for items using the total annual costs and the quantities provided
       (e.g., compute costs in $/pound chemical). Where GCWW provided average, minimum,
       and maximum quantities,  EPA calculated the unit cost using the average value. These
       unit costs were not needed to compute total costs because GCWW provided the total
       annual costs. However, EPA used  unit costs in the sensitivity  analyses  and in the
       evaluation of alternative disinfection technologies.

   3.  Calculate Base Case 1 and 2 totals using the costs provided. Base Case 2 does not include
       GAC; therefore, EPA did not include the GAC replacement or regeneration costs in Base
       Case 2.

   4.  Normalize the total costs to a cubic meter of drinking water delivered.

4.3    Cost Data Quality, Assumptions, and Limitations

As stated previously, all data used in the cost analysis were provided by GCWW  and are for
calendar year 2011. The plant size and  characteristics should be  considered when translating
these costs to other DWT plants.

Because GCWW was not able to provide a breakout of labor by unit process, EPA used the total
labor costs for workers involved in all plant operations. These labor  costs exclude personnel
involved in administration. However, administration costs and similar overhead that  are not tied
directly to operations (e.g., administration personnel and expenses, office building utility  bills,
insurance) are less likely to  change  in response to implementing new technologies in the DWT
plant. Therefore, all of the alternate technologies  studied  here are assumed to have  similar
administration and overhead costs as the base case.

An important note is that plant labor is a significant component of the total plant costs and may
have the most variability between  drinking water plants  due to size and age differences.

5.     BASE CASE RESULTS

Figure 3 displays the Base Case 1 contribution analysis results, Figure  4 displays more detailed
Base Case 1 results on the unit process level, Figure 5 presents comparative summary results by
life cycle  stage for Base Case 1 versus Base  Case 2, Figure 6 presents the percent change across
the impact results when adsorption  is excluded, and Table 12 provides Base Case  1 and  Base
Case 2 results per functional unit.14 This study was not  able to collect data to determine whether
the use of GAC influences the  effluent quality such as cryptosporidium and TTHM; therefore,
these categories are excluded from the Base Case 2 results' figures and tables.

Base case findings of note include:
14 The results for the life cycle assessment and cost analysis are presented in a separate Excel file.

                                           25

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Base Case 1  shows slightly increased environmental impacts compared to Base Case 2
due to the addition of adsorption. Smog and human health criteria impacts are the most
sensitive to the difference.
Labor and energy costs are the largest contributions to DWT plant costs (18% and 38%,
respectively, for Base Case 1; and 21% and 45%, respectively, for Base Case 2; including
both plant and distribution costs).
Eliminating adsorption (including GAC production and regeneration) reduces total costs
by approximately 15  percent.
Disposal  of sedimentation waste is the  largest contributor to eutrophication potential
impacts (Figure 4).  This  is a result of the waterborne emissions of BOD,  COD, and
ammonia leaching from the sedimentation waste (Table 4).
1.2 m3 of blue water are required to deliver 1 m3 of treated drinking  water to the
consumer. A majority of the water loss occurs during the distribution stage. Based on
data collected from GCWW, 0.19 m3 of water is lost per m3 of drinking water delivered
during the distribution stage.
Global warming, energy demand, fossil  depletion, acidification, human health cancer,
human  health criteria  and  ecotoxicity  impacts  are  largely driven  by  electricity
consumption   at the  drinking water treatment plant and during distribution  to the
consumer.
Distribution is the largest contributor to metal depletion, accounting for 78 percent of
impacts.  The distribution metal depletion  is due primarily  to the metal used in the iron
pipes throughout the distribution network infrastructure. Infrastructure at the DWT plant
and pre-disinfection  account for  19 percent of metal depletion impacts, which is largely
attributable steel  used for construction of the DWT plant and upstream infrastructure
required  for production of the chemicals used during pre-disinfection processes (e.g.,
alum coagulant, sodium hexametaphosphate, sodium hydroxide, iron sulfate).
Overall, the primary disinfection with gaseous chlorine life cycle stage only contributes
zero to five percent to the  total  life cycle impacts  of DWT  for the results categories
examined.
                                     26

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                       0%

                   Cost

         Cryptosporidium

                 TTHM

          Chlorine Usage

         Global Wanning

         Energy Demand

         Fossil Depletion

            Acidification

          Eutrophication

         Blue Water Use

                  Smog

        Ozone Depletion

         Metal Depletion  |

    Human Health, Cancer

Human Health, NonCancer

   Human Health, Criteria

             Ecotoxicity
     Percent Contribution by Life Cycle Stage

20%          40%          60%          80%
100%
                             • Source Water Acquisition
                             • Drinking Water Treatment Plant Energy Usage
                             n Pre-Disinfection
                             • Primary Disinfection
                             D Distribution
                               Overhead*
        * Overhead is only considered as stage for cost results category.
                       Figure 3. Base Case 1 contribution analysis results.
                                              27

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                                   Percent Contribution by Unit Process
                                      20%           40%          60%
                      80%
                    Cost
         Cryptosporidium
                 TTHM
          Chlorine Usage
         Global Wanning
          Energy Demand
         Fossil Depletion
            Acidification
           Eutrophication
          Blue Water Use
                  Smog
         Ozone Depletion
          Metal Depletion
    Human Health, Cancer
Human Health, NonCancer
    Human Health, Criteria
              Ecotoxicity
100%
              • Source Water Acquisition
              • Flocculation
              • Filtration
              • Conditioning
                Fluoridation
                Overhead*
l Drinking Water Treatment Plant Energy Usage
I Sedimentation
 Adsorption
 Primary Disinfection
 Distribution (Excluding Fluoridation)
* Overhead is only considered as stage for cost results category.
           Figure 4. Base Case 1 contribution analysis results with unit process detail.
                                              28

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I Source Water Acquisition
 Distribution
 Pre-Disinfection
            l Drinking Water Treatment Plant Energy Usage
             Overhead
            I Primary Disinfection
                       20%
Percent of Maximum
40%             60%
80%
100%
    Figure 5. Base Case 1 and Base Case 2 comparative summary results.
                                        29

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   -16%   -14%   -12%
   Percent Change
-10%    -8%     -6%
-4%
                                                                    Cost
                                                                    Smog
                                                                    Human Health, Criteria
                                                                    Fossil Depletion
                                                                    Energy Demand
                                                                    Acidification
                                                                    Eutrophication
                                                                    Global Warming
                                                                    Metal Depletion
                                                                    Human Health, Cancer
                                                                    Ozone Depletion
                                                                    Human Health, NonCancer
                                                                    Blue Water Use
                                                                    Chlorine Usage
                                                                    Ecotoxicity
                Figure 6. Percent change in impacts if adsorption is excluded.
Table 12. Base Case 1 and Base Case 2 results per m3 drinking water delivered to the consumer.
Results Category
Cost
Cryptosporidium
TTHM
Chlorine Usage
Global Warming
Energy Demand
Fossil Depletion
Acidification
Eutrophication
Blue Water Use
Smog
Ozone Depletion
Metal Depletion
Human Health, Cancer, Total
Human Health, NonCancer, Total
Human Health, Criteria
Ecotoxicity, Total
Unit
$
oocyst
kg TTHM
kgCl2
kg C02 eq
MJ
kg oil eq
kg H+ mole eq
kgN eq
m3
kg O3 eq
kgCFC-lleq
kg Fe eq
CTU
CTU
kgPMWeq
CTU
Base Case 1
0.081
1.00
1.6E-05
0.0018
1.04
19.8
0.36
0.48
9.7E-04
1.20
0.067
2.8E-08
0.036
2.9E-11
3.2E-11
0.0015
4.4E-04
Base Case 2
0.069


0.0018
1.03
19.5
0.35
0.47
9.6E-04
1.20
0.063
2.8E-08
0.035
2.9E-11
3.2E-11
0.0014
4.4E-04
                                            30

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5.1    Base Case Normalized Results

Figure 7 displays the Base Case 1 normalized results. Larger sections of the chart indicate those
impacts where DWT makes relatively larger contributions to national per capita impacts. Impacts
related to fossil fuel combustion from electricity such as acidification potential, smog formation
potential, global warming potential, and human health criteria are relatively high. Eutrophication
impacts are also relatively high, primarily due to the disposal of the sedimentation waste. Other
metrics such as  ozone depletion potential, ecotoxicity, human health cancer and noncancer are
relatively low.
          HHNC: 0.01%,
           HHCa: 0.4
        OOP: 0.1%^^  HHCr
                        ETP: 0.002%
I Global Warming (GWP)

I Acidification (AP)

lEutrophication (EP)

I Smog (SFP)

1 Ozone Depletion (OOP)

] Human Health, Cancer (HHCa)

 Human Health, NonCancer (HHNC)

 Human Health, Criteria (HHCr)

 Ecotoxicity (ETP)
                           Figure 7. Base case normalized results.
5.2    Infrastructure Contribution to Base Case Results

Table 13 and Figure 8 display the contribution of infrastructure at the drinking water treatment
plant and in the distribution system  to the Base Case 1 results. For the majority of impact
categories, the  distribution pipe  network  is the infrastructure component  with the highest
impacts.  For the majority of impact categories, excluding metal  depletion and ecotoxicity,
infrastructure contributes 5% or less to the total impacts. Metal depletion, however, is largely
driven by infrastructure, with  infrastructure  from the  drinking  water  treatment plant and
distribution system accounting  for approximately 68%  of all metal  depletion impacts. The
remaining metal depletion impacts are also primarily due to upstream infrastructure impacts, for
instance from the construction of plants which produce chemicals used for water treatment.

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                                    i Operational Impacts
                         I Infrastructure Impacts
                       0%
20%
40%
60%
80%
100%
         Global Warming



         Energy Demand



         Fossil Depletion



            Acidification



          Eutrophication



         Blue Water Use



                  Smog



        Ozone Depletion



         Metal Depletion



    Human Health, Cancer



Human Health, NonCancer



   Human Health, Criteria



             Ecotoxicity
                         Figure 8. Infrastructure contribution analysis.
                                               32

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Table 13. Contribution of infrastructure to Base Case 1 results per m3 drinking water delivered to the consumer.

Life Cycle Stage
Source Water
Acquisition
Pre-Disinfection
Primary
Disinfection
Distribution
Total


Subprocess
Source water acquisition
infrastructure
Conditioning
infrastructure
Adsorption
infrastructure
Filtration infrastructure
Lime addition
infrastructure
Sedimentation
infrastructure
Flocculation
infrastructure
Primary disinfection
infrastructure
Pipe Network
Water Storage
Valves
Pumps
Motors
All
% of total impact
Impact Category
Global
Warming
kg CO 2
eq
8.4E-04
3.6E-04
0.0012
4.5E-04
2.3E-04
2.0E-04
6.9E-04
2.3E-05
0.011
1.6E-04
0.0043
1.3E-04
1.5E-04
0.020
1.9%
Energy
Demand
MJ
0.010
0.0033
0.011
0.0041
0.0019
0.0033
0.0069
2.1E-04
0.26
0.0025
0.069
0.0022
0.0026
0.37
1.9%
Fossil
Depletion
kg oil eq
2.0E-04
6.4E-05
2.2E-04
8.1E-05
3.7E-05
7.1E-05
1.4E-04
4.1E-06
0.0057
5.0E-05
0.0014
4.4E-05
4.8E-05
0.0081
2.3%
Acidification
kg H+ mole
eq
1.4E-04
5.2E-05
1.7E-04
6.5E-05
3.2E-05
6.2E-05
1.1E-04
3.3E-06
0.0036
3.9E-05
9.1E-04
2.9E-05
8.3E-05
0.0053
1.1%
Eutrophication
kgN eq
1.5E-07
5.2E-08
1.7E-07
6.5E-08
3.4E-08
8.3E-08
l.OE-07
3.3E-09
2.9E-06
4.1E-08
7.4E-07
2.3E-08
4.6E-08
4.4E-06
0.5%
Blue
Water
Use
m3
4.8E-06
4.6E-06
1.6E-05
5.8E-06
2.9E-06
4.3E-07
8.4E-06
2.9E-07
3.2E-05
1.6E-06
4.6E-05
9.7E-07
1.4E-06
1.2E-04
0.0%
Smog
kg O3 eq
5.1E-05
1.9E-05
6.3E-05
2.4E-05
1.3E-05
2.8E-05
3.9E-05
1.2E-06
0.0015
1.3E-05
2.3E-04
7.4E-06
1.2E-05
0.0020
3.0%
Ozone
Depletion
kgCFCll
eq
6.5E-11
1.6E-11
5.5E-11
2.0E-11
l.OE-11
2.0E-11
3.0E-11
l.OE-12
1.7E-10
l.OE-11
2.2E-10
6.1E-12
9.6E-12
6.3E-10
2.3%
Metal
Depletion
kg Fe eq
7.2E-05
7.3E-05
2.5E-04
9.1E-05
1.9E-05
5.5E-06
1.3E-04
4.7E-06
0.015
2.3E-04
0.0076
1.4E-04
3.5E-04
0.024
67.3%
Human
Health,
Cancer,
Total
CTU
7.6E-14
2.4E-14
8.1E-14
3.0E-14
l.OE-14
1.3E-14
4.4E-14
1.5E-15
1.1E-13
1.8E-14
5.6E-13
2.4E-14
3.0E-14
l.OE-12
3.5%
Human
Health,
NonCancer,
Total
CTU
3.0E-14
1.4E-14
4.8E-14
1.8E-14
9.0E-15
4.4E-15
2.6E-14
9.0E-16
3.3E-14
3.3E-14
1.1E-12
4.9E-15
1.6E-12
2.9E-12
9.0%
Human
Health,
Criteria
kgPMW
eq
7.0E-07
4.4E-07
1.5E-06
5.5E-07
1.7E-07
2.4E-07
8.2E-07
2.8E-08
7.8E-06
5.4E-07
1.6E-05
5.0E-07
7.7E-07
3.0E-05
2.0%
Ecotoxicity,
total
CTU
1.7E-06
3.3E-07
1.1E-06
4.1E-07
1.6E-07
4.3E-07
6.6E-07
2.1E-08
1.7E-05
3.0E-07
8.8E-06
3.9E-07
2.5E-06
3.4E-05
7.7%
                                                  33

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6.
BASELINE SENSITIVITY ANALYSES
To see  the influence of the assumptions made in an LCA model,  it is important to conduct
sensitivity analyses. To carry out such an analysis, the assumption of interest is changed and the
entire LCA is recalculated.  In this study, EPA conducted sensitivity  analyses for key base case
assumptions. Table 14 shows the sensitivity analyses for the base case, the values  used, and
whether LCA or cost results were generated for the sensitivity. Costs results were generated if
changes to the LCA parameter  could impact the costs. For example, changing the quantity of
chlorine used at the plant would change the costs. On the other hand, varying the quantity of
cryptosporidium in the final drinking water would not result in cost changes if no changes to the
plant were made. Table 15 provides the electricity grid fuel mix used in both the baseline and the
sensitivity analysis.

                    Table 14. Sensitivity analyses for base case model runs.
Parameter
Chlorine usage
Lime consumption
Alum coagulant usage
Sodium hypochlorite usage
during distribution
Natural gas for GAC
reactivation
DBF exposure
Cryptosporidium exposure
Electricity usage at plant a
Electricity usage during
distribution a
Electricity unit cost (plant
and distribution)
Electricity grid
Lifetime of DWTP
infrastructure components
Lifetime of DWT
distribution system
infrastructure components
Values
Minimum, maximum, and average
values obtained from GCWW
Minimum, maximum, and average
values obtained from GCWW
Minimum, maximum, and average
values obtained from GCWW
Minimum, maximum, and average
values obtained from GCWW
Minimum, maximum, and average
values obtained from GCWW
Minimum, maximum, and average
values obtained from GCWW
Minimum, maximum, and average
values obtained from GCWW
±10% of value obtained from
GCWW
±10% of value obtained from
GCWW
±20% of value obtained from
GCWW
Average U.S. grid, RFCW NERC
regional grid
±25 years for buildings, pipes, and
other features (baseline =100 years)
±25 years for buildings, pipes, and
other features (baseline =100
years); ±10 years for pumps and
motors (baseline = 25 years)
LCA
Results
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
Yes
Yes
Yes
Cost
Results
Yes
Yes
Yes
Yes
Yes
No
No
Yes
Yes
Yes
No
No
No
         a Varying the electricity usage by ± 10% also provides an indication of the effects of varying
         the total cost of electricity by ±10%. EPA also varied total electricity costs by ±20% (plant
         and distribution) as shown on the cost results worksheet.
                                            34

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Table 15. U.S. electrical grid fuel i
Electricity source
Bituminous coal
Lignite coal
Natural gas
Distillate oil
Residual oil
Biomass
Nuclear
Hydro
Wind
Solar
Geothermal
MSW, non-biogenic
Petroleum coke
Petroleum waste oil
Tire derived fuel
Other fuels
Other gases
U.S. Average
46.24%
1.96%
21.43%
0.18%
0.57%
1.33%
19.57%
6.03%
1.34%
0.021%
0.36%
0.15%
0.35%
0.022%
0.030%
0.072%
0.28%
profiles15
RFCW NERC
Region
77.06%
0%
2.41%
0.14%
0.0024%
0.48%
18.24%
0.62%
0.20%
0%
0%
0.028%
0.20%
0.0014%
0.0083%
0.060%
0.54%
Sensitivity analyses findings of note include:

   •   As displayed in Figure 9,  the use of the U.S. average grid electricity mix resulted in
       considerably lower global warming, smog, and acidification impacts compared to use of
       the ReliabilityFirst Corporation  West  (RFCW) grid,  which  is  the  North  American
       Electrical Reliability Corporation (NERC) region the GCWW Richard Miller Treatment
       Plant is located. This is largely due to the higher use of coal in the RFCW grid compared
       to the U.S. average grid. However, use of the RFCW grid  electricity mix  significantly
       reduced Human health cancer and ecotoxicity impacts, which is due to the lower natural
       gas usage in the RFCW grid mix compared to the U.S. average grid mix.
   •   Figure 10  shows the results of eight cost sensitivity analyses in terms of percent change
       from the baseline. Labor and energy are the highest contributors  to the overall plant costs,
       so changes in chemical quantities and costs generally do not  have a significant impact on
       the overall costs. Cost results  are, however, sensitive to the electricity unit cost.
   •   Increases/decreases in plant electricity usage had the most effect on impacts associated
       with fossil fuel production and combustion such as  global  warming potential, human
       health  criteria,  smog, acidification, fossil  depletion,  human health cancer and energy
       demand (Figure 11).
   •   Impact results vary +/- zero to six percent when varying the distribution electricity  usage
       +/- 10 percent (Figure  12). Impacts  related  to  fossil fuel combustion  (e.g., global
       warming, energy demand, fossil depletion, acidification) are  most affected. These results
       clearly show the DWT model is sensitive to the electricity usage during distribution,  and
  eGRID 2008 (Emissions and Generation Resource Integrated Database). U.S. EPA.
(www.epa.gov/cleanenergy/egrid).
                                            35

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that electricity usage during distribution is an impactful process in the overall DWT life
cycle.  The  model  is more sensitive  to  varying electricity  usage during distribution
compared to varying electricity usage  at the DWTP since distribution  requires almost
twice as much electricity compared to treatment at the plant.
Crypto sensitivity results show that exposure results vary on average approximately -15
percent/+10% from Base Case 1.
TTHM sensitivity results indicate that exposure results vary on average approximately -
50 percent/+32 percent from Base Case  1.
Chlorine usage results vary on average approximately -27 percent/+46 percent from Base
Case 1 (Figure 13).  No other impact categories are sensitive to the chlorine usage range.
Results of the infrastructure sensitivity analysis are displayed in Figure 14 (infrastructure
at DWTP) and Figure  15 (infrastructure for distribution  system). The lifetimes assumed
for each infrastructure component are estimates based  on historical information  of the
GCWW  facility (100 years for buildings, pipes, other features, and 25 years  for pumps
and motors); however, the study does include a sensitivity analysis to look  at a wider
range of potential lifetimes of infrastructure components.  For building,  pipes and other
features  (e.g., tanks and reservoirs) the lifetime is varied +/- 25  years, while for the
pumps and motors,  the lifetime is varied +/- 10 years. Overall life cycle impacts increase
with  a  decrease in the infrastructure lifetime, since  the  infrastructure burdens are
normalized over less total water delivered. The infrastructure lifetime is only sensitive to
the metal depletion  category,  since  this  is the only impact  category  in  which
infrastructure is a significant  component.  All other impact categories vary less than 5
percent  from the  base  case  for this  sensitivity  analysis. The distribution  system
infrastructure has the  greatest impact on  metal depletion results as approximately  95
percent of the 3,135 miles of distribution system piping is iron.
Figure 16, Figure 17, Figure 18,  and Figure 19 show the sensitivity analysis  results for
alum  coagulant  usage during  flocculation,  lime usage during  sedimentation, sodium
hypochlorite usage during  distribution,  and  natural  gas  consumption  for   GAC
reactivation respectively. The LCA model is not sensitive to these parameters within the
potential operational range supplied by  GCWW. Cost results vary the most for the input
quantity of alum coagulant.
                                     36

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                                                  Percent Change
                       -60%  -50%   -40%   -30%   -20%  -10%   0%
                                            10%    20%
         Global Warming
          Energy Demand
          Fossil Depletion
            Acidification
           Eutrophication
                   Smog
         Ozone Depletion
          Metal Depletion
    Human Health, Cancer
Human Health, NonCancer
   Human Health, Criteria
              Ecotoxicity
• Acquisition & treatment
d Distribution
        L
40%
         Figure 9. Significance of electricity mix: RFC West versus U.S. average baseline.
                                                  Relative Change in Total Costs for Base Case (%)
                                              -8.00  -6.00  -4.00  -2.00  0.00   2.00   4.00   6.00  8.00
                     Electricity Unit Cost ($/kWh)
         Electricity (distribution) (purchased) (kWh)
                        Alum Usage (lb/1,000 ft3)
 Natural Gas for GAC Regeneration Unit Cost ($/scf)
            Electricity (at plant) (purchased) (kWh)
                        Lime Usage (lb/1,000 ft3)
             Gaseous Chlorine Usage (lb/1,000 ft3)
          Sodium Hypochlorite Usage (lb/1,000 ft3)
Figure 10. Tornado chart of the sensitivity analysis results for the relative changes in total costs for
                                           Base Case 1.
                                                 37

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                       -4%
                   Percent Change
-3%     -2%     -1%     0%      1%      2%      3%      4%
                  Cost
         Cryptosporidium
                 TTHM
          Chlorine Usage
         Global Wanning
         Energy Demand
         Fossil Depletion
            Acidification
          Eutrophication
         Blue Water Use
                  Smog
         Ozone Depletion
         Metal Depletion
    Human Health, Cancer
Human Health, NonCancer
   Human Health, Criteria
             Ecotoxicity
                                      I Minimum DWTP Electricity Usage (-10%)
                                      I Maximum DWTP Electricity Usage (+10%)
               Figure 11. Base Case 1 DWTP electricity usage sensitivity analysis.
                                             Percent Change
                       -8%   -6%   -4%   -2%   0%    2%    4%
                  Cost
         Cryptosporidium
                 TTHM
          Chlorine Usage
         Global Warming
         Energy Demand
         Fossil Depletion
            Acidification
          Eutrophication
         Blue Water Use
                  Smog
         Ozone Depletion
         Metal Depletion
    Human Health, Cancer
Human Health, NonCancer
   Human Health, Criteria
             Ecotoxicity
                                   6%   8%   10%
                                        D Minimum Distribution
                                          Electricity Usage (-10%)

                                        • Maximum Distribution
                                          Electricity Usage (+10%)
          Figure 12. Base case 1 distribution system electricity usage sensitivity analysis.
                                               38

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                                 Percent Change
                      -40%   -30%   -20%  -10%   0%
                   Cost
          Chlorine Usage
         Global Wanning
         Energy Demand
         Fossil Depletion
            Acidification
          Eutrophication
         Blue Water Use
                  Smog
         Ozone Depletion
         Metal Depletion
    Human Health, Cancer
Human Health, NonCancer
   Human Health, Criteria
             Ecotoxicity
                                                  t
 10%   20%   30%   40%   50%   60%
—I	1	1	
   I Minimum Chlorine Usage
   I Maximum Chlorine Usage
                    Figure 13. Base Case 1 chlorine usage sensitivity analysis.
                                                   Percent Change
                        -0.6%     -0.4%    -0.2%    0.0%     0.2%     0.4%
                       0.6%
                                     0.8%
          Global Warming
           Energy Demand
           Fossil Depletion
             Acidification
            Eutrophication
           Blue Water Use
                   Smog
          Ozone Depletion
           Metal Depletion
     Human Health, Cancer
  Human Health, NonCancer
     Human Health, Criteria
               Ecotoxicity
T
        • Minimum DWTP Lifetime

        • Maximum DWTP Lifetime
            Figure 14. Base Case 1 DWTP infrastructure lifetime sensitivity analysis.
                                              39

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                                               Percent Change
                      -15%    -10%
                                       -5%
      0%
5%
10%
15%
20%
25%
                                                              1 Minimum Distribution System
                                                              Lifetime
                                                              • Maximum Distribution System
                                                              Lifetime
         Global Warming
         Energy Demand
         Fossil Depletion
            Acidification
          Eutrophication
         Blue Water Use
                 Smog
        Ozone Depletion
         Metal Depletion
    Human Health, Cancer
Human Health, NonCancer
   Human Health, Criteria
             Ecotoxicity
       Figure 15. Base Case 1 distribution system infrastructure lifetime sensitivity analysis.
                       -3%
                  Cost
          Chlorine Usage
         Global Warming
         Energy Demand
         Fossil Depletion
            Acidification
          Eutrophication
         Blue Water Use
                  Smog
         Ozone Depletion
         Metal Depletion
    Human Health, Cancer
Human Health, NonCancer
   Human Health, Criteria
             Ecotoxicity
                                -2%
       Percent Change
-1%       0%       1%
                                           L
                                            i
           j
               2%
                 3%
                  4%
                                                                         I Minimum Alum
                                                                          Usage
                                                                         I Maximum Alum
                                                                          Usage
                Figure 16. Base Case 1 alum coagulant usage sensitivity analysis.
                                              40

-------
                      -0.5%
                                                 Percent Change
                                                      0.0%
                      0.5%
                  Cost
          Chlorine Usage
         Global Wanning
         Energy Demand
         Fossil Depletion
            Acidification
          Eutrophication
         Blue Water Use
                  Smog
         Ozone Depletion
         Metal Depletion
    Human Health, Cancer
Human Health, NonCancer
   Human Health, Criteria
             Ecotoxicity
                                                                          1 Minimum Lime Usage

                                                                          1 Maximum Lime
                                                                           Usage	
                                                        J
                      Figure 17. Base Case 1 lime usage sensitivity analysis.
                      -0.5%
                                           Percent Change
                                           0.0%
0.5%
1.0%
                                                                  I Minimum Sodium
                                                                  Hypochlorite Usage
                                                                  I Maximum Sodium
                                                                  Hypochlorite Usage
                  Cost
          Chlorine Usage
         Global Warming
         Energy Demand
         Fossil Depletion
            Acidification
          Eutrophication
         Blue Water Use
                  Smog
         Ozone Depletion
         Metal Depletion
    Human Health, Cancer
Human Health, NonCancer
   Human Health, Criteria
             Ecotoxicity
        Figure 18. Base Case 1 distribution sodium hypochlorite usage sensitivity analysis.
                                              41

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                    -1.0%
                            -0.5%
Percent Change
    0.0%
0.5%
1.0%
                 Cost
        Cryptosporidium
                TTHM
         Chlorine Usage
        Global Wanning
         Energy Demand
         Fossil Depletion
           Acidification
          Eutrophication
         Blue Water Use
                 Smog
        Ozone Depletion
         Metal Depletion
    Human Health, Cancer
 Human Health, NonCancer
   Human Health, Criteria
             Ecotoxicity
                                           T
                      I Minimum Natural Gas
                      Usage
                      I Maximum Natural Gas
                      Usage	
7.
          Figure 19. Base Case 1 natural gas for GAC reactivation sensitivity analysis.
IN-PLANT ALTERNATIVE DISINFECTION TECHNOLOGIES
EPA investigated the use of the following in-plant disinfection alternatives by collecting data
from the EPA partners noted.

   •   Conventional mercury-vapor ultraviolet (UV) disinfection (Aquionics)
   •   LED UV disinfection (Aquionics)
   •   Ferrate disinfection (Ferrate Treatment Technologies, LLC (FTT))

EPA had intended to include plasma-bead UV disinfection from Imaging Systems Technology
(1ST) in this  study. While EPA investigated plasma-bead  UV technologies  and  collected
information from 1ST, it was determined that this technology is still too early in development to
model quantitatively.

Table 16 shows  where  each technology is implemented in the drinking water model plant. The
following subsections describe each technology,  EPA's data collection  for the technology, the
methodology used to compare impacts and costs for the alternative technology,  and the final
results.
                                           42

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             Table 16. Unit process matrix for alternative disinfection technologies.
Life Cycle Stage Reported
Source Water Acquisition
Drinking Water Treatment
Plant, Energy and Infrastructure
Pre-Disinfection
Primary Disinfection
Distribution
Use
Unit Processes Covered
Source Water Acquisition
Drinking Water Treatment Plant, Energy and
Infrastructure
Flocculation
Alum Coagulant
Sedimentation
Ferrate oxidation
Disposal, Sedimentation Waste
Filtration
Adsorption
GAC Production
GAC Regeneration
Primary Disinfection, Gaseous Chlorine
Alternate UV Disinfection (conventional,
LED)
Ferrate disinfection
Fluoridation
Transport, Treated Drinking Water, Water
Supply Pipeline
Distribution Infrastructure, Drinking Water
Drinking Water Consumption

-------
                                         Sedimentation










Disposal of
Waste
LE
GEND
C )




L>
Primary Input/
Final Demand
Primary Process
Reference
Supply Chain
Or gate (multiple
outputs)
Or gate (multiple
inputs)
>


Primary
Disinfection,
Gaseous Chlorine


Conditioning U-
£

*
Primary
Disinfection,
Conventional UV
-x





~~V
Primary
Disinfection, LED
UV

i

Primary
Disinfection,
Ferrate


i
Fluoridation
   Figure 20. System boundaries of drinking water treatment base case and in-plant disinfection
                                      alternatives.

7.2    Aquionics Conventional UV Disinfection System

Aquionics provides UV  disinfection equipment  for drinking water and  municipal  treatment
plants. EPA has partnered with Aquionics to provide data on conventional and LED UV for this
study. Conventional UV uses mercury-vapor lamps to provide the UV light which de-activates
microorganisms. UV can also breakdown unwanted chemicals such as  organic compounds.
According to Aquionics product  information, Aquionics UV systems use  low wavelength UV
                                          44

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light, which can breakdown total organic carbon (TOC) molecules into smaller compounds that
can then be removed by other unit processes.16 Potential benefits of UV include:

    •  Removes chlorine-resistant pathogens;
    •  Reduces chlorine quantities required on site; and
    •  Reduces generation of DBFs.

EPA collected data on conventional UV directly  from Aquionics.

7.2.1  LCA Model

For the conventional UV LCA model, only the primary disinfection stage is changed from the
base case DWT model. Aquionics  provided electricity and infrastructure  data to assist  in
developing the LCA  model. EPA made the following  assumptions for  the  conventional UV
model based on the data provided by Aquionics:

       •      For primary disinfection, a 3.6 MOD UV unit was modeled. Therefore, 30 active
              units and one backup unit would be required  for disinfection  at the 106 MOD
              GCWW base case facility.
       •      Conventional mercury-vapor UV disinfection requires 0.042 kWh electricity per
              cubic meter of water treated. This value was calculated using Aquionics' estimate
              that 210,240 kWh/yr of electricity are required to treat 3.6 MOD of water at a
              dose of 40 ml/cm2.
       •      Each 3.6 million gallon per day (568 m3 per hour) UV disinfection unit consists of
              six mercury-vapor bulbs. The lamp lifetime is approximately 8,000 hours.
       •      The weight of each disinfection unit is 288 Ib. The unit consists of a stainless steel
              vessel,  quartz sleeves for the lamps,  electronics for control units, synthetic rubber
              for wiper rings,  and the mercury vapor lamps. Aquionics estimated a lifetime for
              each part (see Table 18). With the exception  of the lamps, EPA used the  average
              lifetime of the  disinfection  components of  five years  for the LCA model  for
              simplicity. The conventional UV unit infrastructure has a negligible impact on the
              LCA results; therefore, the results are not sensitive  to this assumption.
       •      Disinfection with conventional UV does not result in any formation of DBFs.
       •      Disinfection with conventional UV can lead to the same levels of cryptosporidium
              reduction as disinfection with gaseous chlorine.

EPA made some additional assumptions to complete the conventional UV LCA model:

       •      No chlorine is required for primary disinfection, but some gaseous chlorine is still
              required to maintain a chlorine residual in the  distribution  system. This is based
              on information  from  FTT  (see  Section 7.4).  The  sodium hypochlorite added
              during  distribution is still added in the same amount as this is  required to  boost
              chlorine residual  in  certain parts  of the  distribution  system. This  sodium
              hypochlorite boost may not be applicable for other drinking water systems.
16 Aquionics website (www.aquionics.com)
                                           45

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       •      EPA assumed there was 400 mg mercury per lamp.17
       •      Other components of the UV lamp were modeled based on an amalgam lamp: 7.5
              mm3 argon/lamp, 200 mg indium/lamp, 200 mg molybdenum/lamp, 4 g soldering
              materials/lamp, 20 g  ceramics/lamp,  and  300  g glass (assumed to be quartz
              sleeve)/lamp. 8 The total weight of  one  lamp was  therefore assumed to  be
              321.1305 grams.
       •      Besides the weight of the lamp, no data were available on the weight breakdown
              of components of the 288 Ib UV unit; therefore, the following assumptions were
              made:  the  stainless  steel vessel accounts for  85%  of the unit weight,  the
              electronics  account for  13% of the weight, the synthetic rubber wiper rings
              account for 0.5% of the total unit weight, and the remainder of the unit weight
              (1.47%) is from the lamps.

Because the conventional UV lamps include mercury, which is considered a hazardous material,
the "chlorine  usage" category from the base  case  analysis is expanded here  to "hazardous
materials" to account for this mercury. This unique flow, which is not a typical category in LCA
studies, is only tracked based on data reported by data providers for specific life cycle stages, and
does not  cover  all  potential  upstream  hazardous materials. However, this category aids  in
understanding the hazardous materials at the drinking water treatment plant that workers may be
exposed to.

       7.2.1.1    Unit Processes

The specific unit processes added for the conventional UV LCA model are identified below.

Disinfection
    1.  Primary Disinfection, Conventional  UV.  Primary  disinfection  with conventional
       (mercury-vapor)  UV.  The inputs to this unit process include operation and infrastructure
       requirements for the UV units.
    2.  Conventional UV Drinking Water Treatment,  Operation.  This process  covers
       electricity usage  associated with operation of the UV units.
    3.  Conventional UV Drinking Water Treatment,  Infrastructure.  Infrastructure inputs
       for the UV units  are aggregated in this unit process.
    4.  Conventional UV Lamp. Represents  infrastructure requirements  for the mercury-UV
       lamp and quartz  sleeve encompassing the lamp.
    5.  Stainless Steel UV Vessel. Production of the stainless steel UV vessel.
    6.  Wiper Ring. Covers infrastructure requirements for synthetic rubber wiper rings.
    7.  Conventional UV Electronic Control Unit. Production requirements for an electronics
       control unit.
17 Malley, J.P., Jr. 2006. Development of Standard Operating Plans for Mercury Release from UV Technologies.
Used in Drinking Water Treatment Plants. Course Lecture Materials University of New Hampshire, Durham, NH
18 Ekwall, Cecilia. 2004. LCA of tap water disinfection - a comparison of chlorine and UV-light. Department of
Biometry and Engineering, Swedish University of Agricultural Sciences. http://ex-
epsilon.slu.se/archive/00000280/01/cecilia ekwall 0402.pdf

                                           46

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Use
   8.  Drinking Water Consumption, Conventional UV. Final  delivery of water, which is
       disinfected with conventional UV, to an average consumer. This unit process aggregates
       the other main life cycle stages and is used to build the final product system. There are no
       actual impacts associated with the drinking water consumption life cycle stage itself.

Table 17 displays the data sources used for the conventional UV model in addition to the data
sources used in the base case model (See Table  3). In general, data from Aquionics were used
where  available. For upstream processes that would  not be known  by Aquionics, such as
information on production of UV lamp materials (e.g., mercury, molybdenum, glass), EPA used
information from ecoinvent v2.2. Data sets from ecoinvent v2.2 have not been adapted for this
project.

                          Table 17. Conventional  UV data sources.
   Process                                   Data Source
   Conventional UV disinfection operation      Data Collection-Aquionics
   Infrastructure for UV unit                   Data Collection-Aquionics, and
                                                                               1718
                                             assumptions from secondary sources '
   Stainless steel for UV vessel                 ecoinvent v2.2
   Mercury for UV lamp                      ecoinvent v2.2
   Molybdenum for UV lamp                  ecoinvent v2.2
   Ceramics for UV lamp                      ecoinvent v2.2
   Glass (i.e., quartz sleeve) for UV lamp       ecoinvent v2.2
   Argon for UV lamp                        ecoinvent v2.2
   Indium for UV lamp                        ecoinvent v2.2
   Electronics module                         ecoinvent v2.2
   Synthetic rubber for wiper rings	ecoinvent v2.2	
7.2.2   Cost A nalysis

Table 18 lists information Aquionics provided for use in the cost analysis.19 After adding in the
conventional UV system (including electricity usage, parts replacement, and amortized capital
investment) and reducing the gaseous chlorine usage, the total annual cost is $10,666,000, an
increase of $674,000 from Base Case 1.
19 Input data, calculations, and results for the UV cost analysis are included in the supporting Excel file.

                                           47

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                         Table 18. Cost data provided by Aquionics.
Cost Element
UV unit6
PLC and Control Cabinet
Online UVT Monitor
Lamps0
Quartz Sleeves
Wiper Rings
UV Sensors
Lifetime (years)
20
20
20
0.9
5
2
8
Cost
$45,050/unit
$90,100/unit
$7,500/unit
$450/1 amp
$70/sleeve
$18/ring
$500/sensor
         a See Excel worksheets for detailed cost calculations.
         b Costs are for one unit, which can treat 3.6 MOD. EPA scaled the 3.6 MOD system to the
         base case plant size and included one back-up unit.
         0 8,000 hours equals approximately 0.9 years.

In addition, EPA included the following information and assumptions  based on information
provided by Aquionics:

    1.  The Aquionics system is for a 3.6 MGD small-scale system. As described Section 7.2.1,
       the Aquionics  system was scaled up  to  30 active units plus  one  backup  unit for
       disinfection at the 106 MGD GCWW base case  facility. This scale-up factor of 31 was
       applied to the capital  costs of the UV unit and the PLC and control cabinet. Only one
       UVT monitor is required. The resulting total capital equipment cost is $4,200,000.

    2.  Costs include replacement  parts (lamps,  quartz  sleeves, wiper rings,  and UV sensors).
       Aquionics provided the cost and lifetime of each part and noted each UV unit uses six
       lamps. EPA assumed each lamp requires  one quartz sleeve, one wiper ring, and one UV
       sensor.

    3.  Cost multipliers are often applied to  equipment costs to  account for other direct costs
       such  as  installation, site work,  and  ancillary equipment and indirect costs  such as
       permitting, monitoring, and training. This study assumes Aquionics would provide piping
       and electrical equipment required for the UV system. A contingency of 25% of total
       capital equipment  costs  was included. The  resulting  total  capital  investment is
       $5,250,000.

    4.  EPA amortized the total capital costs over the 20-year expected lifetime of a UV system
       using a bond rate of 6 percent. The resulting annual, amortized cost is $457,000.

    5.  EPA did  not include cost credits for any equipment that is  no longer required with use of
       the UV system. Plants may be able to reduce equipment  required for chlorine  addition
       because less chlorine is required.

7.2.3   Results

Table 19 displays results of the conventional UV analysis on the basis of 1 m3 water delivered to
the consumer. Figure 21 presents comparative summary results by life cycle stage for Base Case
                                           48

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1 versus conventional UV disinfection. Figure 22 presents the percent change across the impact
results when using  conventional UV disinfection rather than  gaseous chlorine  disinfection.
Section 7.6 presents results comparisons between the three alternative disinfection  technologies
and the base case. Some findings to note for the conventional UV results as compared to the base
case:

       •      Application of conventional UV technology increases impacts during disinfection
              through increased electricity  consumption and through new  capital investment,
              but eliminates the formation of disinfection by-products and  greatly reduces
              hazardous chlorine usage.
       •      With the exception of hazardous materials and DBF formation (i.e., TTHM results
              category), the choice of disinfection technology does not significantly impact
              overall life cycle results, since most impacts  are  driven by energy  consumption
              for pumping  at the DWT plant and  during  distribution.  This  pumping energy
              consumption is not affected by choice of disinfection technology.
       •      For the hazardous materials category, the quantity of mercury from the bulbs is
              negligible compared to the quantity of chlorine used to maintain a residual in the
              distribution network. This study does not distinguish  between different hazard
              levels of chlorine versus mercury in the "hazardous materials"  results category.

       Table 19. Conventional UV results per m3 drinking water delivered to the consumer.
Results Category
Cost
Cryptosporidium
TTHM
Hazardous Materials
Global Warming
Energy Demand
Fossil Depletion
Acidification
Eutrophication
Blue Water Use
Smog
Ozone Depletion
Metal Depletion
Human Health, Cancer, Total
Human Health, NonCancer, Total
Human Health, Criteria
Ecotoxicity, Total
Unit
$
oocyst
kg TTHM
kg C12 & HZ
kg CO2 eq
MJ
kg oil eq
kg H+ mole eq
kgN eq
m3
kg O3 eq
kgCFC-lleq
kg Fe eq
CTU
CTU
kgPMWeq
CTU
Conventional UV
$0.086
1.00
0
4.4E-04
1.07
20.4
0.37
0.49
9. 7E-04
1.20
0.069
2.8E-08
0.036
3.0E-11
3. IE- 11
0.0015
4.5E-04
                                           49

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I Source Water Acquisition
 Distribution
 Pre-Disinfection
                 I Drinking Water Treatment Plant Energy Usage
                  Overhead
                 l Primary Disinfection
                       20%
Percent of Maximum
        40%
60%
80%
100%
 Figure 21. Base Case 1 and conventional UV comparative summary results.
                                        50

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                     -80%   -70%  -60%  -50%
 Percent Change
-40%  -30%   -20%
-10%   0%   10%  20%
          Chlorine Usage
 Human Health, NonCancer
         Metal Depletion
         Blue Water Use
          Eutrophication
             Ecotoxicity
    Human Health, Cancer
         Ozone Depletion
    Human Health, Criteria
                 Smog
           Acidification
         Energy Demand
         Global Warming
         Fossil Depletion
                  Cost
  Figure 22. Percent change in impacts if using conventional UV rather than gaseous chlorine for
                                        disinfection.

For most impacts examined, the increase seen for utilization of conventional UV versus gaseous
chlorine for primary disinfection is due to increased electricity usage. Therefore,  a  sensitivity
analysis is run here varying the electricity usage for conventional UV disinfection  +/- 25 percent.
Figure 23 presents the results  of this  analysis.  Overall, the total life cycle impacts for DWT
disinfection with conventional UV do not vary more than +/- 0.9% when varying the electricity
usage for conventional UV operation  +/- 25 percent.  This is  primarily a result of the overall
small impact of the primary disinfection life cycle stage as compared to other life cycle stages
that are larger consumers of energy (e.g., pumping at the DWT plant, distribution of the treated
water to the consumer).

Figure 24 presents a tornado chart that displays the results of the total cost sensitivity analysis.
The cost sensitivity analysis performed a Monte Carlo simulation, varying the following:

       •       Amount of electricity required by the conventional UV system by ±25% (same as
              was performed for the LCA sensitivity analysis).
       •       Cost of a conventional UV unit by ±10% ($45,050/unit).
       •       Bond rate from four to eight percent (a ±33% change from the baseline value of
              six percent).
                                            51

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The sensitivity results show that the total costs are most sensitive to the bond rate and closely
followed by the amount of electricity required by the conventional UV system. However, the
total cost changes are within approximately ±0.6%. Therefore, although the total costs are more
sensitive to the bond rate  and electricity required by the UV unit than they  are to the  capital
equipment cost, the total costs are negligibly changed by the parameter values studied.  This
result is expected as the disinfection costs are less than 8% of the total costs. Therefore, changes
to disinfection costs have a smaller impact  on the total costs compared to the larger costs: pre-
disinfection (33%); distribution (27%); overhead (21%); and plant energy (12%).
        • Primary Disinfection
                                                   Percent Change
                   -1.0%   -0.8%  -0.6%  -0.4%   -0.2%   0.0%   0.2%
0.4%   0.6%   0.8%    1.0%
                Figure 23. Conventional UV electricity usage sensitivity analysis.

                                            52

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                                  Relative Change in Total Costs for Conventional UV Scenario (%)

                                        -0.80  -0.60 -0.40 -0.20  0.00  0.20  0.40   0.60  0.80
                             Bond Rate (%)
   UV Electricity Usage to treat 3.6 MOD (kWh/yr)
 UV System Cost per Units needed to treat 3.6 MOD
                    ($)
   Figure 24. Tornado chart of the sensitivity results for the relative changes in total costs for the
                                conventional UV scenario.
7.3    Aquionics LED UV Disinfection System

Aquionics offers a line of UV-LED disinfection equipment, which provides the same benefits of
conventional UV but uses an LED light source rather than a mercury lamp. The LED UV system
Aquionics has developed is for point-of-use applications (e.g., for laboratory equipment, health
care equipment, stand-alone point-of-use). EPA made some assumptions to scale this technology
to the 106 MGD system from the base case, but it is important to note that such large-scale LED
UV disinfection technology does not currently exist. Utilization of LED for small-scale point-of-
use applications is examined in Section 8. Cost data were not available for LED UV disinfection
and are not included in this analysis.

7.3.1   LCA Model

EPA made the following assumptions for the in-plant LED UV analysis:

       •       For the LED UV LCA model, only the primary disinfection stage is changed from
              the base case DWT model.
       •       Water treated per disinfection unit is assumed equivalent to that treated under the
              conventional UV scenario (since no large-scale LED UV system exists, primary
              data on water treated for large-scale LED UV systems was not available).
       •       It is also assumed that the LED UV lamps are housed in the same stainless steel
              vessel with electronic controls as the conventional UV, and that the lifetime of
              these components is five years.
       •       Based on equipment specifications  from Aquionics, 0.0039 kWh of electricity are
              required per m3 water treated via LED UV.
       •       LED  lamp infrastructure requirements were  modeled based on a U.S. Department
              of Energy  (DOE)  LCA on energy and environmental impacts of LED lighting
                                           53

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                      90 	
              products.   This  study  identified  the background  ecoinvent data  sets  and
              associated  quantities  utilized in  the  life  cycle  inventory model,  and  EPA
              replicated this LCI model (See Table 5-3, 5-6, and 5-8 of DOE study). The DOE
              study (and therefore this study) assumes the LEDs are produced in China.
       •      Disinfection with LED UV does not result in any formation of DBFs.
       •      Disinfection with  LED  UV can lead to the  same levels of cryptosporidium
              reduction as disinfection with gaseous chlorine.
       •      No chlorine is required for primary disinfection, but some gaseous chlorine is still
              required to maintain a chlorine residual in the distribution system.  This is based
              on information from  FTT (see  Section  7.4).  The sodium hypochlorite added
              during  distribution is  still added in the same amount as this is required to boost
              chlorine  residual  in  certain  parts  of the  distribution system.  This sodium
              hypochlorite boost may not be applicable for other drinking water systems.

7.3.2   Unit Processes

The specific unit processes added for the LED UV LCA model are identified below.

Disinfection
   1.  Primary Disinfection, LED  UV. Primary disinfection with LED UV. The inputs to this
       unit process include operation and infrastructure requirements for the UV units.
   2.  LED UV Drinking Water Treatment, Operation.  This process covers electricity usage
       associated with operation of the UV units.
   3.  LED UV Drinking Water Treatment, Infrastructure. Infrastructure inputs for the UV
       units are aggregated in this unit process. Infrastructure processes included are the LED
       die fabrication,  LED  packaging  assembly, three-inch  sapphire wafer  manufacture,
       production of the stainless steel UV vessel,  and production  of the LED UV electronics
       control unit.
   4.  Three-Inch Sapphire Wafer Manufacture. Preparation  of sapphire wafers to use for
       LED die fabrication.
   5.  LED Die Fabrication. LED semiconductor device fabrication.
   6.  LED Packaging Assembly. Packaging and assembly of the LED devices.
   7.  Stainless Steel UV Vessel. Production of the stainless steel UV vessel.
   8.  LED UV Electronics Control Unit. Production requirements for an electronics control
       unit.

Use
   9.  Drinking Water Consumption, LED UV. Final delivery of water, which is disinfected
       with LED UV, to an average  consumer. This unit process aggregates the other main life
       cycle stages and is used to build the final product system. There are no actual impacts
       associated with the drinking water consumption life cycle stage itself.
20 U.S. Department of Energy: Buildings Technology Program. June 2012. Life Cycle Assessment of Energy and
Environmental Impacts of LED Lighting Impacts. Accessed at:
http ://apps 1. eere. energy .gov/buildings/publications/pdfs/ssl/2012_led_lca-pt2 .pdf

                                            54

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Table 20 displays the data sources used for the LED UV model in addition to the data sources
used in the base case model (See Table 3). Aquionics' equipment specifications were used to
determine operational energy requirements. Upstream infrastructure was modeled based on a
DOE LCA of LEDs.20 This study identified the background ecoinvent data sets and associated
quantities utilized in the LCI and EPA replicated this LCI model.

                             Table 20. LED UV data sources.
Process
LED UV disinfection operation
Infrastructure for UV lamp
Infrastructure for UV vessel and electronics
Three-Inch Sapphire Wafer Manufacture
LED Die Fabrication
LED Packaging Assembly
Materials for LED production
Energy for LED production
Data Source
Aquionics' equipment
specifications
DOE LED LCA2U
Equivalent to conventional UV analysis
DOE LED LCA/U
DOE LED LCA2U
DOE LED LCA2U
ecoinvent v2.2
ecoinvent v2.2
7.3.3   Results

Table 21 provides results of the LED UV analysis on the basis of 1 m3 water delivered to the
consumer. Figure 25 presents comparative summary results by life cycle stage for Base Case 1
versus LED UV disinfection. As previously mentioned, no cost data was available for LED UV
disinfection, so this is excluded from the figure. Figure 26 presents the percent change across the
impact results when using LED  UV disinfection rather than gaseous  chlorine disinfection.
Section 7.6 presents results comparisons between the  three alternative disinfection technologies
and the base case. Overall LED UV results are similar to conventional UV results, but LED UV
is more energy  efficient compared to conventional UV. With the exception of the decrease in
hazardous material usage, decrease in human health noncancer impacts, and the  elimination of
the  formation of DBFs under the  LED UV scenario,  the LCA results for the gaseous chlorine
base case and primary disinfection with LED UV  are essentially equivalent. Human health
noncancer results decrease  because of the elimination of gaseous chlorine with the LED UV
disinfection system.  The primary emission leading to human health noncancer impacts during the
production of gaseous chlorine is CFC-10.
                                           55

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Table 21. LED UV results per m3 drinking water delivered to the consumer.
Results Category
Cryptosporidium
TTHM
Hazardous Materials
Global Warming
Energy Demand
Fossil Depletion
Acidification
Eutrophication
Blue Water Use
Smog
Ozone Depletion
Metal Depletion
Human Health, Cancer, Total
Human Health, NonCancer, Total
Human Health, Criteria
Ecotoxicity, Total
Unit
oocyst
kg TTHM
kgCl2
kg CO2 eq
MJ
kg oil eq
kg H+ mole eq
kgN eq
m3
kg O3 eq
kgCFC-lleq
kg Fe eq
CTU
CTU
kgPMWeq
CTU
LEDUV
1.00
0
4.4E-04
1.04
19.8
.36
0.48
9. 7E-04
1.20
0.067
2.8E-08
0.036
2.9E-11
3.0E-11
0.0015
4.5E-04
                                56

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      I Source Water Acquisition
      Distribution
      l Primary Disinfection
I Drinking Water Treatment Plant Energy Usage
 Pre-Disinfection
                               Percent of Maximum
                                                                                      100%
Figure 25. Base Case 1 and LED UV comparative summary results.
                                   57

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                     -80%   -70%   -60%    -50%
Percent Change

 -40%   -30%   -20%
-10%
10%
      Hazardous Materials

 Human Health, NonCancer

    Human Health, Cancer

         Ozone Depletion

          Blue Water Use

          Eutrophication

         Energy Demand

         Global Warming

         Fossil Depletion

    Human Health, Criteria

                 Smog

           Acidification

         Metal Depletion

             Ecotoxicity
      Figure 26. Percent change in impacts if using LED UV rather than gaseous chlorine for
                                        disinfection.

Similar to the conventional UV analysis, for most impacts examined (excluding the formation of
DBFs), the change seen  for utilization of LED UV  versus gaseous  chlorine for  primary
disinfection is due to increased electricity usage with LED UV. Therefore, a sensitivity  analysis
is  run here varying the electricity usage for LED UV disinfection +/- 25 percent.  Figure 27
presents the results of this analysis. Overall, the total life cycle impacts  for DWT disinfection
with LED UV do not vary more than +/-  0.1% when varying the electricity usage for LED UV
operation  +/- 25 percent.  This is primarily a result of the overall small impact of the  primary
disinfection life cycle stage as compared  to other life  cycle stages that are larger consumers of
energy (e.g., pumping at the DWT plant, distribution of the treated water  to the consumer).  The
change for the +/- 25 percent electricity usage for LED UV operation is less than that seen in the
same sensitivity analysis conducted for the  conventional  UV technology, as LED UV  requires
less electricity overall for disinfection compared to the conventional mercury-vapor UV.
                                            58

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       Primary Disinfection
               -0.10%
  •g .g   Min (-25%)
  ^ g  	


  5 |  Max (+25%)
        Min (-25%)
  t9 Q  Max (+25%)
        Min (-25%)
  o ~

  fe ,§" Max (+25%)
  « c
  ^3 o
        Min (-25%)
  •Jj    Max (+25%)
        Min (-25%)
  S "
       Max (+25%)
        Min (-25%)
       Max (+25%)
  
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7.4    Ferrate Technology

FTT patented  an on-site reactor for municipal and industrial water treatment applications (the
Ferrator®).  The Ferrator®  generates  ferrate  ions  (FeC>42~)  on-site from caustic,  sodium
hypochlorite, and ferric  chloride and delivers it continuously to the process. Ferrate can be used
as an oxidant,  coagulant, and disinfectant. When used at the beginning of a treatment train,
ferrate will oxidize organics and sulfides, eliminate taste and  odor issues, and eliminate the need
for GAC to remove disinfection byproducts. According to FTT, ferrate has the following benefits
over chlorine disinfection:

   •   Reduces the chlorine dose required to maintain an adequate  residual;
   •   Eliminates the need for alum coagulation;
   •   Reduces the amount of sludge generated; and
   •   Eliminates the generation of DBFs.

According to FTT, one  of the key benefits is the reduction of DBFs.  In conventional drinking
water plants, DBFs form when chlorine reacts with the organics present in the raw water. Using
ferrate at the  pre-disinfection stage  can remove solids and organics. The Ferrator® reactor
controls  the generation  of ferrate ions such that the  chlorine in the chemical feedstocks is
consumed in the reaction to form sodium chloride, which will not combine with organics to form
DBFs. Ferrate also provides disinfection by inactivating microorganisms. Chlorine will still need
to be added to maintain a chlorine residual in the distribution system;  however, the quantity of
chlorine required for the residual is reduced and the chlorine is added after all organics have been
removed, eliminating the formation of DBFs.

7.4.1   Data Collection and System Boundaries

EPA obtained information on the Ferrator® technology directly from FTT. Based on discussions
with FTT, EPA made the following changes to the base case model to represent use of the
Ferrator® technology:

   •   Added 3 ppm ferrate at the pre-disinfection stage as an oxidant/coagulant and eliminated
       the addition of alum and polymer as coagulants.

   •   Added ferric chloride  for pH adjustment after addition of ferrate because ferrate will
       increase  the  pH  (0.075 ppm  of 40%  concentration ferric chloride  used at  the
       sedimentation  stage and 0.05  ppm of 40% concentration ferric chloride  used  at  the
       conditioning  stage).  Eliminated the  addition  of lime and  sodium hydroxide for  pH
       control.

   •   Removed GAC. EPA assumed that ferrate would oxidize any organics present in the raw
       water and eliminate any taste and odor concerns; therefore, GAC is not required.

   •   Reduced volume of sludge generated (see details below).

   •   Added 2 ppm ferrate for primary disinfection.

                                           60

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    •   Reduced amount of chlorine required by 75 percent. This chlorine dose is required to
       maintain a chlorine residual in the distribution system.

    •   Increased electricity consumption to power the Ferrators®.

    •   Added infrastructure  requirements  for production of the Ferrator® (amortized over the
       useful life of the system).

EPA compared  data provided by  FTT to the base case model assumptions and made some
adjustments to the data inputs as described below:

    1.  Ferrator chemical feedstocks - The chemical composition of Ferrate is confidential. For
       purposes of this analysis, EPA assumed ferrate is produced on-site at the DWT plant in a
       Ferrator® using sodium hydroxide  (50%  concentration),  sodium hypochlorite (15%
       concentration, estimated based on available data), and ferric chloride (40% concentration)
       at a mass ratio of 3:1:0.5.

    2.  Sludge generation - GCWW does not dewater sludge from the sedimentation basin and
       returns a watery sludge stream to the river. EPA computed an estimated mass of sludge
       generated given the TSS concentration of raw river water and GCWW's dosage of alum,
       polymer, and  lime,  which all contribute  to the  sludge  generated. EPA  calculated
       approximately  3.6 Ib  dry sludge is generated per 1,000 ft3 of water produced in the base
       case given  a  raw water  TSS  concentration of 43 mg/L.21 EPA performed similar
       calculations  to determine the amount of sludge generated from ferrate (3.0 Ib dry sludge/
       1,000 ft3 of water).

Additional assumptions specific to the LCA model  and  cost analysis  are  described in the
subsections below. Because use of ferrate impacts or eliminates the need for many unit processes
in the  base case, the  system  boundaries  for the ferrate drinking water treatment  model are
provided in Figure 28.
21 Calculations based on equations from Appendix E Sludge Production from Coagulants and Other Treatment
Chemicals, AWWA Research Foundation, "Trace Contaminants in Drinking Water Chemicals", 2002.

                                           61

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LEGEND

^~ ~""\
i




0
Primary Input/
Final Demand
Primary Process
Reference
Supply Chain
Or gate (multiple
outputs)
\ "x Or gate (multiple
/ -S inputs)
                                                                                Sodium
                                                                           Hexametaphosphate
                                                                               Production
                                    Sodium
                                   Hypochlorite
                                   Production
1
Distribution
1


Transport, Treated
Drinking Water, Water
Supply Pipeline
 *Gaseous chlorine is not used as primary disinfectant, and is added to
 maintain a chlorine residual in the distribution system.
/ Drinking Water  \
\   Consumption   I
V	    ^
                Figure 28. System boundaries of ferrate drinking water treatment.

7.4.2  LCA Model

This section provides information on the unit processes developed and data sources used for the
ferrate DWT LCA model.

       7.4.2.1     Unit Processes

EPA developed  new unit  processes  for the  specific  ferrate DWT processes listed below
(categorized by the overall life cycle stage or material). As shown in Figure 28, the ferrate DWT
unit processes start with source water  acquisition and end with drinking water use. Unaffected
                                               62

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unit processes from the base case are not listed here. Additional ferrate unit processes from
background LCI database (e.g., ecoinvent v2.2 and U.S. LCI) that have not been modified are
identified in Section 7.4.2.2, Table 22 (Ferrate Data Sources).

Ferrate Solution
    1.  Ferrate Solution. Ferrate solution is produced on-site at the DWT plant in a Ferrator®
       using sodium hydroxide (50%), sodium hypochlorite (15%, estimated based on available
       data), and ferric chloride (40%) at a mass ratio of 3:1:0.5. Some electricity is required for
       operating the Ferrator® to produce the ferrate solution at the DWT plant. The Ferrator®
       infrastructure, amortized over lifetime production of ferrate, is an input to the ferrate
       solution unit process.
    2.  Ferrator® (FeSOO) Production. This unit process includes production  of one Fe300
       Ferrator®. The Ferrator® has a lifetime of 15 years, weighs 14,000 Ibs, and is composed
       primarily of steel (for the frame and skid) and PVC (for piping valves and fittings). EPA
       assumed the Ferrator® is, by weight, 90% steel and 10% PVC. This unit process  only
       includes material production for the Ferrator®, no assembly information was available,
       and is therefore excluded.

P re-Disinfection
    3.  Pre-Treatment, Ferrate. Ferrate solution is used at 3 ppm during pre-treatment to act as
       an oxidant/coagulant.
    4.  Sedimentation, Ferrate. Ferric chloride is added during sedimentation to adjust pH (as
       opposed to lime addition in the base case). The sedimentation  unit process has been
       otherwise unchanged from the base case.
    5.  Disposal, Sedimentation Waste, Ferrate. Use of ferrate decreases the suspended solids
       and  total  sludge  amount since  alum is  no longer used  as a coagulant.  Waterborne
       emissions of aluminum from the base case are  also  removed with the elimination of
       flocculation in the ferrate model. The overall waterborne emissions of ammonia, BOD,
       and COD remain unchanged from the base case, since it is assumed ferrate removes these
       emissions at the same rate as the base case model.
    6.  Conditioning, Ferrate. Ferric chloride is  used for pH adjustment, and the use of sodium
       hydroxide is eliminated.
    7.  Pre-Disinfection,  Ferrate.  This unit process aggregates  the  upstream  ferrate  pre-
       disinfection unit processes from ferrate pre-treatment through conditioning.

Disinfection
    8.  Primary Disinfection, Ferrate. Representative of a DWT system using ferrate solution
       for primary disinfection. Ferrate is used at a 2 ppm dosage for primary disinfection. Some
       gaseous chlorine  (reduced  75% from base  case) is still  included to have a  chlorine
       residual in the distribution system.

Use
    9.  Drinking  Water  Consumption, Ferrate. Final  delivery  of  water to  an  average
       consumer. This unit process aggregates the other main ferrate life cycle stages and is used
       to build the final product system. There are no  actual  impacts associated with the
       drinking water consumption life cycle stage itself.


                                           63

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       7.4.2.2    Data Sources
Table 22 displays the data sources used for the ferrate model in addition to the data sources used
in the base case model (See Table 3). In general, data from FTT were used where available.  For
upstream processes that would not be known by FTT such as information on chemical feedstock
production  (e.g., ferric  chloride,  sodium  hydroxide, and sodium hypochlorite),  EPA used
information from either the U.S. LCI Database or  ecoinvent v2.2. Data sets from U.S. LCI
Database and ecoinvent v2.2 have not been adapted for this project.

                                Table 22. Ferrate data sources.
          Process
          Ferrate Solution
          Sodium Hypochlorite
          Ferric Chloride
          Sodium Hydroxide
          Ferrator® Infrastructure
          Polyvinyl Chloride Resin
          Steel, Low-Alloyed
          Pre-Treatment, Ferrate
          Primary Disinfection, Ferrate
Data Source
Data Collection-FTT
ecoinvent v2.2
ecoinvent v2.2
ecoinvent v2.2
Data Collection-FTT
U.S. LCI
ecoinvent v2.2
Data Collection-FTT
Data Collection-FTT
7.4.3   Cost Analysis
	                           „,„,                                      99
Table 23  lists  information FTT provided for use in the cost analysis.   After adding in the
Ferrator® system (including electricity usage, chemical inputs, incidental repairs, and amortized
capital investment); reducing the gaseous chlorine usage; eliminating GAC, alum, polymer, lime,
and caustic soda; and  reducing the sludge produced, the total  annual cost is $8,333,000,  a
decrease of $1,659,000 from Base Case 1.

                            Table 23. Cost data provided by FTT.
Cost Element
Ferrator®
Ferrator® monitor
Ferrator® lifetime
Electricity requirement
Incidental repairs
Value
$810,000a
$20,000
15
15,208b
2%c
Unit
$/unit
$/unit
years
kWh/unit
% of capital cost
Ferrator® units





of
    aFTT noted that quantity discounts Ferrator® costs.
    bFTT estimated 91,250 kWh of electricity would be required to operate six Ferrators®, which is
    approximately 15,208 kWh per Ferrator®.
    0 FTT estimated that incidental repairs would cost approximately 2% of the total cost of Ferrator® units
    installed, which is approximately $97,200 for six Ferrators®.
 : Input data, calculations, and results for the FTT cost analysis are included in the supporting Excel file.
                                            64

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In addition, EPA included the following information and assumptions based on discussions with
FIT:

    1.  The number of Ferrators® required depends on the ferrate dose needed to achieve the
       treatment objectives. EPA assumed ferrate would be added at the pre-disinfection stage
       as an oxidant/coagulant at a dose of 3 ppm and as the primary disinfectant at a dose of 2
       ppm. FIT estimated that this dose would require 5 Ferrators® for pre-treatment and 4 for
       disinfection  based on a  DWT plant capacity  of 100 MGD. FTT also  recommended
       including an additional Ferrator® and an additional Ferrator® monitor as back-ups. EPA
       scaled-up the estimates provided by FTT to match the  actual volume of water treated by
       GCWW used in the base case model. EPA estimated that 10 active Ferrators® and one
       active monitor would be required with an additional Ferrator® and monitor as back-ups.
       The resulting total capital equipment cost is $8,950,000.

    2.  Costs include two Ferrate monitors (primary and backup). The required dose of Ferrate is
       generated on site. The monitors adjust the ferrate dose to match demand automatically.
       The monitor continuously measures and records the concentration of ferrate in the stream
       being treated after the ferrate is mixed.

    3.  Cost multipliers are  often applied to equipment costs to account  for other direct costs
       such as installation, site work,  and ancillary equipment and indirect  costs such  as
       permitting, monitoring,   and  training.  Ferrators® are  a pre-assembled skid-mounted
       system that  can be set up on a  pad. FTT noted that values less than standard costs
       multipliers would be appropriate for estimates of other direct costs and indirect costs. A
       2008 AWWA drinking water report used the following  multipliers to develop costs for
       drinking water residuals processes:

       •  Piping and fittings - 10% of equipment
       •  Electrical - 15% of equipment, piping
       •  Instrumentation - 15% of equipment, piping, electrical
       •  Contingency, bonding, and mobilization - 25% of total equipment, piping, electrical,
          and instrumentation.2

       FTT noted there is little ancillary equipment required other than feedstock storage tanks
       and transfer pumps. Ferrators® are also self-contained on their own skid and only require
       connections to utilities and feedstock tanks. FTT usually connects  piping as part of their
       contract,  so  only power  connections are required. Because  FTT  provides the required
       instrumentation and controls, EPA only added a 25% cost factor to the capital costs of the
       Ferrators® to  account for  any contingencies.  The resulting total  capital investment is
       $11,177,500.

    4.  EPA amortized the total capital costs over the 15-year expected lifetime of a Ferrator®
       using a bond rate of 6 percent. The resulting annual, amortized cost is $1,151,000.
23 AWWA, 2008. Costing Analysis to Support National Drinking Water Treatment Plant Residuals
Management Regulatory Options. Submitted by Environmental Engineering & Technology, Inc.
Newport News, VA.

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    5.  EPA did not include cost credits for any equipment that is no longer required with use of
       the Ferrators®. Plants would no longer need GAC equipment and may be able to reduce
       equipment  required for chlorine  addition because less chlorine is required. EPA did
       include the annual operating cost reduction from the reduced chlorine use and elimination
       of GAC.

7.4.4   Results

Table 24  provides results of the ferrate  analysis on the basis of 1 m3 water delivered to the
consumer. Figure  29  displays the ferrate results compared  to Base Case 1 and Base Case 2
results by life cycle stage. As can be seen in the figure, only the impacts associated with pre-
disinfection  and primary disinfection (green and purple bars) change when switching from Base
Case 1 to the ferrate DWT system. Figure 30  shows the percent change by impact when using
ferrate for pre-treatment and primary disinfection instead of the  Base Case 1 scenario. Results
are sorted in this figure to visually display which impact categories are most affected by use of
ferrate.

Ferrate findings of note include:

    •   Cost results decrease 18 percent when  switching from Base  Case  1 to the ferrate DWT
       system.  While primary disinfection costs  increase due to the ferrate infrastructure, these
       costs are offset and savings are realized by cost reductions in the pre-disinfection stage.
       Ferrate  cost  savings  are  dominated  by: 1)  elimination  of GAC  replacement,  2)
       elimination of alum coagulant for flocculation, 3) elimination of sodium hydroxide for
       pH adjustment, and 4) elimination of natural gas combustion for regeneration of the
       GAC.

    •   Usage of gaseous  chlorine for primary disinfection decreases 75 percent when using
       ferrate to maintain a chlorine residual in the distribution system. The sodium hypochlorite
       added during distribution is still added in the  same amount  as this is required to boost
       chlorine residual in certain parts  of the distribution  system.  This sodium hypochlorite
       boost may not be applicable for other drinking water systems. As discussed previously,
       using ferrate at the pre-disinfection stage can remove solids and organics. Since chlorine
       is only added after the organics have been removed, DBFs are not expected to form from
       using ferrate as applied in this model.

    •   There is no expected change in human exposure to cryptosporidium when switching to a
       ferrate treatment system.

    •   Global warming potential decreases seven percent when  using ferrate  compared to the
       base  case.  This reduction is largely attributable to the removal of sodium hydroxide and
       lime  for pH adjustment in the  sedimentation and conditioning processes (ferric chloride is
       used for pH adjustment in ferrate model) and the elimination of the GAC adsorption step.
       Overall, electricity  consumption  at  the  plant and  during  distribution  is the largest
       contributor to  the GWP.  Use of ferrate does  not significantly impact electricity usage,
       with  exception of a small amount of electricity required to operate the Ferrators®. The

                                            66

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   additional electricity required to operate the Ferrators® has a negligible effect on  all
   impact results.

•  Overall,  the additional infrastructure required to produce  the  Ferrator® units has a
   negligible effect on all impact results with the exception of cost.

•  Blue water use does not change between Base Case 1 and the ferrate DWT system. Blue
   water use is dominated by the actual source water acquired to produce the drinking water
   and the water losses during distribution, with neither of these factors being influenced by
   the type of disinfection technology.

•  Smog formation decreases 10 percent when switching from Base Case 1  to the ferrate
   DWT system. This is primarily due to the elimination of the GAC adsorption step, which
   includes production of GAC from coal and regeneration of GAC with natural gas, as well
   as the elimination of the need for alum coagulant for flocculation since ferrate acts as a
   flocculant. Exclusion of the sodium hydroxide and lime for pH adjustment also contribute
   to the lower smog results for ferrate. However, a significant  decrease in smog formation
   is not seen because most of the  smog impacts are due to electricity consumption at the
   plant and during distribution, which are unaffected by switching to ferrate.

•  Similarly, energy  demand decreases eight percent and fossil depletion decreases  four
   percent when  switching from Base Case  1 to the  ferrate DWT system due to the
   elimination  of sodium hydroxide, lime, alum coagulant, and GAC  adsorption.

•  Eutrophication,  which is dominated by  disposal of the  sedimentation  sludge,  only
   decreases one percent  under the ferrate  DWT  system. While elimination of alum
   decreases the overall sludge at the DWT plant,  it is expected that the same amount of
   BOD, COD and ammonia (primary emissions leading to eutrophication) will be removed
   from  the raw water under the ferrate system;  therefore,  the final flows  of these
   waterborne emissions from sedimentation sludge do not vary from the base case.

•  Acidification results decrease five  percent when  switching from Base Case 1 to the
   ferrate DWT system due to the elimination of sodium hydroxide  (for pH adjustment),
   lime, alum coagulant, and GAC adsorption. Acidification impacts in the DWT model are
   dominated by sulfur dioxide and nitrogen oxide emissions from fossil fuel combustion for
   electricity generation. Again, because ferrate does  not influence  electricity consumption
   significantly at the plant or during distribution, a large overall decrease in acidification
   impacts is not realized with the use of ferrate.

•  Human health criteria  impacts decreases nine percent under the ferrate DWT system.
   This is largely due to the reduction in sulfur dioxide  emissions  with the elimination of
   GAC production and regeneration as well as the elimination of the alum coagulant and
   sodium hydroxide for pH adjustment.

•  Ozone depletion,  metal  depletion, human  health  cancer and human health noncancer
   results have a higher uncertainty associated with them in the comparative results due to

                                       67

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   data alignment issues between the unmodified European ecoinvent datasets and the U.S.
   datasets  (U.S.  LCI Database  and EPA processes developed  for  this work).  While
   reductions in impacts are expected in these categories when switching to ferrate, it is
   emphasized that these reductions are likely overstated in the results figures presented.

•  Ozone depletion impacts decrease 15  percent under  the  ferrate DWT system in this
   model. This is  primarily due to the elimination of sodium  hydroxide for pH adjustment
   and alum  coagulant for flocculation.  These materials are modeled  using  European
   ecoinvent datasets. The background European electricity  data for production of these
   materials uses  an electricity grid with higher ozone  depletion  than the U.S. average
   electricity grid  modeled for plant operations and drinking water distribution. The average
   European electricity  grid ozone  depletion impacts are primarily influenced  by  Halon
   1301 emissions from crude oil production and Halon  1211 emissions from natural gas
   production. These  emissions are  not incorporated  into the U.S.  electricity  grid fuel
   profiles.  Therefore, it is expected that the actual reduction  in ozone  depletion  under the
   ferrate system is lower than stated here, and the notable reduction is primarily influenced
   by data alignment issues. The uncertainty associated with the ozone  depletion  results is,
   therefore, considered high.

•  Metal depletion results also decrease 15 percent when switching from Base Case 1 to the
   ferrate DWT   system.  Ecoinvent processes,  specifically  sodium  hydroxide, that are
   eliminated with use of ferrate do include background infrastructure for capital equipment.
   This  metal infrastructure leads  to depletion  of metals  such  as  nickel, copper and
   chromium.  So, some reduction  in metal  depletion is expected when using ferrate;
   however, it is  likely that the metal depletion reduction value is overstated  here. The
   ecoinvent data  sets and the ferrate production do include background infrastructure, but
   background infrastructure is  not included for any of the primary DWT processes, U.S.
   electricity generation, or background U.S. LCI processes. The uncertainty associated with
   metal depletion results  is considered high due to these infrastructure data  alignment
   concerns.

•  Human health noncancer results decrease 36 percent under the ferrate DWT system. This
   decrease is due to elimination of the sodium hydroxide for pH adjustment, relating to the
   background carbon disulfide emissions from ecoinvent European electricity.

•  Human health cancer decrease 11  percent when switching from Base Case 1  to the ferrate
   DWT system, largely from the elimination of sodium  hydroxide  for pH adjustment and
   alum coagulant for flocculation. This is primarily due to fewer dioxin and formaldehyde
   emissions in the background European ecoinvent electricity required  to produce these
   material.

•  Ecotoxicity results  decrease 12 percent when switching from Base Case 1 to the ferrate
   DWT system.  This reduction  is due to the elimination of sodium hydroxide for pH
   adjustment and alum coagulant for flocculation. The main emissions associated with the
   supply chain of  these materials  that lead to ecotoxicity are cyanide,  carbofuran, and
   phenol.

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Table 24. Ferrate results per m3 drinking water delivered to the consumer.
Results Category
Cost
Cryptosporidium
TTHM
Hazardous Materials
Global Warming
Energy Demand
Fossil Depletion
Acidification
Eutrophication
Blue Water Use
Smog
Ozone Depletion
Metal Depletion
Human Health, Cancer, Total
Human Health, NonCancer, Total
Human Health, Criteria
Ecotoxicity, Total
Unit
$
oocyst
kg TTHM
kgCl2
kg CO2 eq
MJ
kg oil eq
kg H+ mole eq
kgN eq
m3
kg O3 eq
kgCFC-lleq
kg Fe eq
CTU
CTU
kgPMWeq
CTU
Ferrate
$0.067
LOO
0
4.4E-04
0.97
18.3
0.33
0.45
9.4E-04
1.20
0.060
2.3E-08
0.03 1
2.6E-11
2.0E-11
0.0013
3.9E-04
                                69

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                 I Source Water Acquisition
                  Distribution
                  Pre-Disinfection
                     I Drinking Water Treatment Plant Energy Usage
                      Overhead
                     l Primary Disinfection	
                      0%
20%
Percent of Maximum
40%             60%
80%
100%
         +-  Base Case 1
o
o .3
I1S
0 o,
1
a 
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                            Percent Change

 -100%  -90%   -80%  -70%   -60%  -50%  -40%  -30%  -20%   -10%   0%
                                                                      TTHM
                                                                      Chlorine Usage
                                                                      Human Health, NonCancer
                                                                      Cost
                                                                      Ozone Depletion
                                                                      Metal Depletion
                                                                      Ecotoxicity
                                                                      Human Health, Criteria
                                                                      Smog
                                                                      Human Health, Cancer
                                                                      Energy Demand
                                                                      Global Warming
                                                                      Fossil Depletion
                                                                      Acidification
                                                                      Eutrophication
                                                                      Blue Water Use
                                                                      Cryptosporidium

   *Higher uncertainty associated with results for these impact categories. Reductions likely
   overstated due to data alignment concerns.

   Figure 30. Percent reduction when switching from Base Case 1 to ferrate DWT system.

The ferrate base case assumes that 3 ppm of ferrate is added at the pre-disinfection life cycle
stage and 2 ppm of ferrate is added during the primary disinfection life cycle stage.  The actual
ferrate dosage may vary depending  on the specific plant  conditions  and the quality  of the
incoming water.  A sensitivity analysis is conducted here varying the ferrate dosage  during the
pre-disinfection and  primary disinfection stages. A minimum  dosage  of 1  ppm during pre-
disinfection and 1 ppm during primary disinfection and a maximum dosage of 5 ppm during pre-
disinfection and 3 ppm during primary disinfection are investigated.

Figure 31 presents the results of this sensitivity analysis. Impact assessment results do  not vary
more than +/- 0.80 percent in this sensitivity analysis; therefore, the ferrate LCA model is not
sensitive to the ferrate dosage requirements.

Figure 32 presents a tornado chart that displays the results of the total cost sensitivity analysis.
The cost sensitivity analysis performed a Monte Carlo simulation, varying the following:

    •  Pre-disinfection ferrate dose from 1 ppm to 5 ppm (same as was performed for  the LCA
       sensitivity analysis).
    •  Disinfection ferrate dose from 1 ppm to 3  ppm (same as was performed for the  LCA
       sensitivity analysis).
    •  Cost of a Ferrator® unit by ±10% (baseline value of $810,000/unit).
                                             71

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    •   Bond rate from four to eight percent (a ±33% change from the baseline value of six
       percent).

The sensitivity results  show that the total costs are most sensitive to the bond rate and followed
by the Ferrator® cost  per unit, pre-disinfection ferrate dose, and  the disinfection ferrate dose.
However, the total cost changes are within approximately ±1.70%. Therefore, although the total
costs  are more sensitive to the bond rate than they are to the  capital equipment cost and the
ferrate doses, the total cost sensitivities are  mitigated over the parameter values studied. This
result is expected as the Ferrator®  system only impacts the pre-disinfection  and disinfection
stages, which constitute 5% and 18% of the total costs, respectively (the use of ferrate increases
the disinfection costs but decreases the pre-disinfection costs for an overall cost savings). The
total costs are dominated by the distribution costs (35%) and overhead costs (27%). The plant
energy costs constitute the remaining 15% of the total costs.

It is important to note that FTT has reported to be  continuing the optimization of its ferrate
manufacturing equipment,  thus reducing the associated equipment  costs.  Compared with the
estimated costs in this study, a significantly lower cost may occur in the present and future,
especially for large water treatment plants.
                                            72

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Percent Change
-0.80% -0.60% -0.40% -0.20% 0.00% 0.20% 0.40% 0.60% 0.80%
•a .s Min
•^ c
^ ^ Max
>^13 Min
£? §
W Q Max
— .2 Min
It 	
^ Q Max
o
3 Min
o
•5 Max
.§ Min
•S a
5 Max
w
a Min
5 Max
m
BO Min
O
1X1 Max

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                                    Relative Change in Total Costs for Ferrator Scenario (%)

                           -2.00   -1.50    -1.00    -0.50    0.00    0.50    1.00    1.50    2.00
                Bond Rate (%)
        Ferrator Cost per Unit ($)
 Pre-Treatment Ferrate Dose (ppm)
   Disinfection Ferrate Dose (ppm)
   Figure 32. Tornado chart of the sensitivity results for the relative changes in total costs for the
                                     ferrate scenario.
7.5    Imaging Systems Technology

1ST is an electronics and materials firm that manufactures a hollow gas encapsulating shell called
a plasma-bead. When a voltage is applied across the shell, the gas ionizes into plasma to generate
UV light which can be used for disinfection. Multiple plasma-beads  can be configured  in an
array  to disinfect  different quantities  of drinking water. 1ST is at the  design  phase of
implementing their plasma-bead technology for drinking water disinfection and is looking to
partner  with UV  vendors  such as Aquionics to  develop pilot-  and full-scale  plasma-bead
disinfection technologies. As such, 1ST is not able to provide detailed unit process and cost data
to use to develop a model to compare to the base case. EPA is working with 1ST to develop
general  assumptions  regarding  the  manufacturing  and  composition  of their  plasma-bead
technology to use in the analysis. According to 1ST, potential benefits of the technology include:

   •   Low manufacturing cost;
   •   Low operating cost;
   •   UV light source is in direct contact with water and the light output is very bright;
   •   Technology can scale to large sizes;  and
   •   Plasma-bead are composed primarily of alumina oxide  gas  and do  not  contain
       environmentally hazardous materials such as mercury.

7.6    Comparative Results

Figure 33 presents  the summary comparative results of the base case DWT  model versus the
alternative disinfection technology models (ferrate, conventional UV, and LED UV). Utilization
of ferrate results in environmental, human health,  and cost benefits for  combined use in the pre-
disinfection  and primary  disinfection  stages, since ferrate  acts  as  both  a  coagulant and
disinfectant and only small dosages are  required for treatment.  Application of UV technology
increases impacts during disinfection through increased electricity consumption and through new
capital investment,  but eliminates the formation of disinfection by-products and greatly reduces
                                            74

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hazardous chlorine usage. LED UV is more energy efficient compared to conventional mercury-
vapor UV; however, it is currently  developed only for point-of-use applications, and not large-
scale treatment facilities.

Figure 34 presents the comparative normalized results for the different disinfection technology
life cycles. The following results are shown on this figure:

    •  Cost: this category displays cost by life cycle stage.  The costs are shown as a percentage
       of the highest cost system (in this case conventional UV).
    •  Normalized by impact: this  category presents the normalized impact assessment results
       by  impact category. Impact categories  have  been  normalized using  TRACT v2.1
       normalization factors.24  The results are shown as a percentage of the highest normalized
       impact system (in this case conventional UV).
    •  Normalized & weighted by  impact: this category presents the normalized and weighted
       impact assessment results by impact category. Impact categories have been normalized
       using TRACT v2.1 normalization factors and  have been weighted using NIST weighting
       factors.24, 25 The results are shown  as a  percentage  of the highest normalized impact
       system (in this case conventional UV).
    •  Normalized by stage: this category presents the normalized impact assessment results by
       life cycle stage. Life  cycle stages have been normalized using TRACT v2.1 normalization
       factors.24 The results are shown as  a percentage of the highest normalized impact system
       (in this case conventional UV).

Only impacts with TRACT normalization factors are  shown in Figure  34. Blue water use, metal
depletion, cumulative energy demand, and fossil depletion are excluded due to lack of available
normalization factors. Additional water  treatment  metrics  included (TTHM and  hazardous
materials) are not shown since they also do not have associated normalization factors. Cost
results for LED UV are also not shown in Figure 34 due to lack of available  cost data for this
technology. Some findings of note from Figure 34:

    •  Weighting increases the relative importance of global warming potential.
    •  In all cases, conventional UV has the highest  overall normalized impact, normalized and
       weighted impact, and cost.
    •  Impact assessment results' correlate with cost  results.
24 Ryberg, M, Vieira, M.D.M., Zgola, M, Bare, I, and Rosenbaum, R.K., 2014. Updated US and Canadian
normalization factors for TRACI 2.1. Clean Techn Environ Policy, 16: 329-339.
25 Gloria, T.P., Lippiatt, B.C., and Cooper, J. 2007. Life cycle impact assessment weights to support environmentally
preferable purchasing in the United States. Environ. Sci. Technol, 41, 7551-7557.

                                           75

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                     i Base Case 1
Ferrate
I Conventional UV
ILEDUV
                                   20%
          Percent of Maximum
            40%         60%
            ±
                           80%
                   100%
                  Cost*

         Cryptosporidium

                 TTHM

     Hazardous Materials

         Global Warming

         Energy Demand

         Fossil Depletion

            Acidification

          Eutrophication

         Blue Water Use

                 Smog

        Ozone Depletion

         Metal Depletion

    Human Health, Cancer

Human Health, NonCancer

   Human Health, Criteria

             Ecotoxicity

    *No cost data available for LED UV
       Figure 33. Summary comparative results of alternative disinfection technologies.
                                             76

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                                            20%
                                                    Percent Contribution
                                                       40%       60%
80%
100%
                             Cost
&


                             Cost
              Normalized by Impact
O
U
    Normalized & Weighted by Impact

               Normalized by Stage
• Global Warming
• Eutrophication
Human Health. Criteria
Drinking Water Treatment Plant Energy Usage
• Primary Disinfection
• Overhead
• Acidification
• Smog •<•
Other Inroads**
• Pre-Disinfection
Distribution ^
                                                                      Impact Categories


                                                                      Life Cycle Stage
  *No cost data available for LED UV
  **"Other Impacts" includes human health noncancer, human health cancer, ozone depletion, and
  ecotoxicity

  Figure 34. Normalized comparative results for different drinking water treatment disinfection
                                        technologies.
                                             77

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8.     PoiNT-OF-UsE ALTERNATIVE DISINFECTION TECHNOLOGIES

EPA investigated the impacts and costs associated with point-of-use drinking water technologies.
EPA focused this analysis on point-of-use technologies that may be used by hospitals to reduce
pathogen exposure for immune-compromised individuals. EPA did not investigate point-of-use
alternatives for home use. Because point-of-use technologies will not change unit processes at
the drinking water plant, EPA did not compare point-of-use LCA results to the base case model.
Instead, EPA reported the life cycle impacts of each point-of-use technology and compared the
impacts to the additional pathogen removal provided by the technology.

Hospitals draw water from  the municipal water supply.  Although water is disinfected at the
treatment  plant  and chlorine  is added to  maintain  an  appropriate residual  throughout the
distribution system,  microorganisms can be present in water at the tap due to residual bacteria in
the distribution systems. Hospitals may  use  additional technologies to  prevent pathogen
exposure. Typically, Legionella and Pseudomonas bacteria are of greatest concern to hospitals.
Hospitals may use technologies that are implemented for the water system as a whole at the point
water enters the building from the municipality and prior to distribution throughout the facility.
However, EPA's analysis focused on point-of-use filters  that could be  installed at or near the
faucet.

EPA  investigated  use  of Pall-Aquasafe™  31-day  point-of-use  filters  for waterborne
microorganisms. According  to Pall's website, filters can be used for up to 31  days  and use a
double-layer sterilizing grade membrane to reduce Legionella and Pseudomonas and other gram-
negative bacteria.26  The cost per filter ranges from $39 to $79, depending  on the volume
purchased by each customer. Since the point-of-use filter is an additional level of drinking water
treatment and does not replace any processes in the base case water treatment scenario, the filter
cost does not change any of the costs associated with water treatment in the base case.

An additional point-of-use technology  examined was LED UV.  As discussed in Section 7.3,
Aquionics'  current LED UV system is for  point-of-use applications. Aquionics notes that this
system  may be used for stand-alone point  of use,  healthcare  equipment, laboratory research
equipment, and autocalves among other uses. This system is not installed directly on the faucet,
but rather more likely installed in the pipe system right before the faucet.

8.1    System Boundaries

The system boundaries for the point-of-use disinfection technologies are displayed in  Figure 35.
Prior to point-of-use disinfection, all processes are equivalent to base case 1.  The drinking water
at the hospital then undergoes further disinfection via either the point-of use faucet filter (Pall) or
the LED UV technology (Aquionics). The system boundaries end at consumption of the water by
an immune-compromised adult.
26 Pall Corporation Aquasafe Medical Filters. See: http://www.pall.com/main/medical/product.page?id=45154#

                                           78

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                              f   Drinking Water
                               Consumption by Immune-
         Figure 35. System boundaries for hospital point-of-use drinking water treatment.

8.2    Pall Point-of-Use Filter


8.2.1   LCA Model

EPA made the following assumptions for the point-of-use filter analysis:

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       •      For the point-of-use LCA model, only the primary disinfection stage is changed
              from the base case DWT model.
       •      Water treated per filter unit is highly dependent upon the water use patterns in a
              given hospital. Thus, it is assumed that an individual faucet and filter are used on
              average 12 hours per day for one month. The faucet and filter is assumed to flow
              at a rate of 8.33  liters of treated water per minute, which is based  on the standard
              maximum flow for faucets in the U.S. set by the U.S. Department of Energy and
              is within the rate of disinfection for the Pall Aquasafe 31-day filter as reported on
                           97 9R
              their website.  '
       •      Point-of-use filter infrastructure requirements were modeled based on the publicly
              available Declaration of Compliance for the Aquasafe 31-day filter, specifications
              for the QPoint™ filter published on the Pall Corporation website, and personal
              communication with Pall representatives.29'30'31 This study identified the
              background ecoinvent datasets and associated quantities utilized in the life cycle
              inventory model, which were replicated in this LCI model.
       •      Disinfection  with   point-of-use  filters  removes  100%   of Legionella  and
              Pseudomonas present in drinking water delivered to the hospital. This is based on
              field evaluation reports on the Pall Aquasafe 31-day filter.32

8.2.2  Unit Processes

The specific unit processes added for the point-of-use filter LCA model are identified below.

Infrastructure
    1.  Point-of-Use Hospital  Filter, Infrastructure.  Infrastructure inputs for the point-of-use
       hospital filter are aggregated in this unit process. Infrastructure processes included are the
       production of the filter  itself,  production of a tap  adapter, and corrugated packaging for
       distribution of the filters to hospitals.
    2.  Point-of-Use Hospital  Filter, Production. Filters are manufactured from a  variety of
       plastic resins.
    3  Tap Adapter for Point-of-Use Hospital Filter. The faucet adapter, made  of nickel-
       plated brass connects the point-of-use filter to a standard faucet for use in a hospital.
    4.  Packaging  for  Point-of-Use  Hospital  Filter.  Filters are  shipped  to hospitals in
       corrugated boxes with 12 filers per box.
27 U.S. Department of Energy: Buildings Technology Program. Oct 2013. Faucets. Accessed at:
http://wwwl.eere.energy.go^uildings/appliance_standards/product.aspx/productid/64
28 Pall Corporation. Pall-Aquasafe™ AQ3 IF IS and AQ31F1R Filters for Waterborne Microorganisms. Accessed at:
http://www.pall.com/main/medical/product.page?id=45154
29 Pall Corporation. March 2013. Declaration of Compliance: Pall-Aquasafe™ Disposable Water Filter 31 Day Use
- Tap Application. Accessed at: http://www.pall.com/pdfs/Medical/AQ31FlR-Declaration-of-Compliance.pdf
30 Pall Corporation. Nov 2012. QPoint™ Tap Water Filter - USA. Accessed at:
http://www.pall.com/main/consumer-water/product. page?lid=h8pw!57j
31 Pall Medical North American Sales Representatives Personal Communication. February 24, 2014.
32Pall Corporation. Feb 2009. Pall-Aquasafe™ Disposable Water Filter - Tap (AQ31F1S and AQ31F1R) Field
Evaluation Report.

                                             80

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Use
    5.  Drinking Water Consumption, Base Case, at Hospital with Point-of-Use Filter. The
       point-of-use filter removes Legionella and Pseudomonas and other gram-negative
       bacteria from drinking water at the tap.

Table 25 displays the data sources used for the point-of-use hospital filter in addition to the data
sources used in the base case model  (See Table 3). Some data on components and weight of the
filter were gathered from Pall. For upstream  processes that would not be known by Pall such  as
information on resin  production, EPA used  information from the National Renewable Energy
Laboratory's U.S. Life Cycle Inventory Database (U.S. LCI), a publically available life cycle
inventory source.33 Where data were not available from Pall or the U.S. LCI, ecoinvent v2.2,
EPA used a private Swiss LCI database with data for many unit processes.34
                       Table 25. Point-of-Use hospital filter data sources.
Process
Point-of-use hospital filter production
Corrugated for filter packaging
Nickel-plated brass tap adapter
Polycarbonate for filter
High-density polyethylene resin for filter
Synthetic rubber for filter
Polypropylene for filter
Injection molding of plastic components of
filter
Data Source
Information from Pall
ecoinvent v2.2
ecoinvent v2.2
ecoinvent v2.2
U.S. LCI
ecoinvent v2.2
U.S. LCI
ecoinvent v2.2
8.2.3   Results

Table 26 displays results for the base case and base case plus the point-of-use hospital filter per
cubic meter of drinking water delivered to the immune-compromised person. Figure 36 presents
summary results by life cycle stage for Base Case with the additional point-of-use  disinfection
with the Pall Aquasafe 31-day filter. As previously mentioned, no cost data was available for
point-of-use filtration, so this is excluded from the figure. Overall point-of-use filter results show
minimal increases in impacts compared to the base case results.
  National Renewable Energy Lab. US LCI Database. See: http://www.nrel.gov/lci/database/default.asp.
34 Ecoinvent Centre (2010), ecoinvent data v2.2. ecoinvent reports No. 1-25, Swiss Centre for Life Cycle
Inventories.
                                            81

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Table 26. Base case and Base case plus point-of-use hospital filter results per m3 drinking water
                               delivered to the consumer.
Results Category
Hazardous Materials
Global Warming
Energy Demand
Fossil Depletion
Acidification
Eutrophication
Blue Water Use
Smog
Ozone Depletion
Metal Depletion
Human Health, Cancer, Total
Human Health, NonCancer, Total
Human Health, Criteria
Ecotoxicity, Total
Unit
kgCl2
kg CO2 eq
MJ
kg oil eq
kg H+ mole eq
kg N eq
m3
kg O3 eq
kg CFC-11 eq
kg Fe eq
CTU
CTU
kgPMWeq
CTU
Base Case 1
0.0018
1.04
19.8
0.36
0.48
9. 7E-04
1.20
0.067
2.8E-08
0.036
2.9E-11
3.2E-11
0.0015
4.4E-04
Base Case 1 plus
Point-of-Use
Hospital Filter
0.0018
1.04
19.9
0.36
0.48
9. 7E-04
1.20
0.067
2.8E-08
0.036
2.9E-11
3.2E-11
0.0015
5.9E-04
                                          82

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                       I Source Water Acquisition
                       ] Pre-Disinfection
                       I Distribution
                        Point-of-Use Disinfection
             I Drinking Water Treatment Plant Energy Usage
             I Primary Disinfection
              Overhead
               0%

  Chlorine Usage

 Global Warming

 Energy Demand  |

 Fossil Depletion  |

    Acidification  |

  Eutrophication

 Blue Water Use

         Smog

Ozone Depletion

 Metal Depletion
                                 20%
Percent Contribution
40%           60%
80%
100%
      Human Health,
         Cancer
      Human Health,
       NonCancer
      Human Health,
         Criteria
                                          =
         Ecotoxicity
        Figure 36. Base Case 1 plus point-of-use hospital filter contribution analysis results.

Because the point-of-use filter results are dependent on the assumption regarding water use per
day (base case assumed 12 hours per day), additional analyses were conducted assuming 1 hour
use per day and 24 hour use per day. The percent change in impacts for the base case plus the
point-of-use hospital filter compared to the base case without the point-of-use hospital filter was
calculated for the three  different use scenarios. The results of this analysis are displayed in
Figure 37. Ecotoxicity is excluded, since it has a comparatively  large increase and makes it
difficult to interpret other impact changes graphically. Ecotoxicity impacts are largely driven by
upstream fungicide  and pesticide  use  during potato farming  for  the potato  starch  in the
corrugated boxes used to distribute  the filters. Overall, impacts increase with less water treated
per day,  since this means more filters are required per volume of water.
                                              83

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              I Increase with 1 hr day use    • Increase with 12 hr day use    • Increase with 24 hr day use
                        0%
                            5%
      Percent Change
10%        15%        20%
25%
30%
Global Warming
Energy Demand
Fossil Depletion 1
Acidification 1
Eutrophication 1
Blue Water Use
.
Smog
Ozone Depletion
Metal Depletion 1
Human Health, Cancer 1
Human Health, NonCancer
Human Health, Criteria

1











































8.3
            Figure 37. Base case percent change with point-of-use filter.

LED UV Point-of-Use Filter
8.3.1   LCA Model

EPA made the following assumptions for the point-of-use LED UV analysis:

    •   The LED UV  system modeled  is identical  to that  modeled in Section 7.3, with the
       following exceptions.
           o  Instead of being housed in a stainless steel vessel with electronic controls, it is
              assumed the LED lamp is within a 6  pound unit that is primarily polypropylene
              with stainless steel pipe attachments.35
  The unit is 6 Ib per Aquionics website: http://www.aquionics.com/main/pearl-brand2/pearlaqua/. EPA assumed
the plastic housing was polypropylene due to lack of specific composition data.

                                              84

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          o   Based on Aquionics' website, it is assumed that 1 LED lamp treats 60,000 gallons
              of water over its lifetime.36

8.3.2   Unit Processes

The specific unit processes added for the point-of-use LED UV unit LCA model are identified
below.

Disinfection
   1.  Disinfection, Point-of-Use LED UV. Primary disinfection with LED UV. The inputs to
       this unit process include operation and infrastructure requirements for the UV units.
   2.  Point-of-Use LED  UV Drinking Water Treatment, Operation. This process covers
       electricity usage associated with operation of the point-of-use UV units.
   3.  Point-of-Use LED  UV  Drinking Water  Treatment, Infrastructure. Infrastructure
       inputs  for the UV  units  are aggregated  in this unit process. Infrastructure  processes
       included are  the LED die fabrication, LED packaging assembly, three-inch sapphire
       wafer manufacture, and the point-of-use UV vessel.
   4.  Point-of-Use UV Vessel. Production of the plastic and steel vessel used to  house  the
       LED UV lamps.

Use
   5.  Drinking Water Consumption, Base Case, at Hospital with Point-of-Use LED UV.
       Final delivery of water, which is disinfected with LED UV, to an immune-compromised
       adult. This unit process aggregates the other main life cycle  stages and is used to build
       the final product system.  There  are no actual impacts associated with the drinking water
       consumption life cycle stage itself.

Table 27 displays the data  sources used for the point-of-use LED UV model in addition to  the
data sources used in the base case  model (See Table 3). Aquionics'  equipment specifications
were used to determine operational energy requirements. Upstream infrastructure was primarily
modeled based on a DOE LCA of LEDs.20 This study identified the  background ecoinvent data
sets and associated quantities utilized  in the DOE LCI  and EPA replicated this LCI model.
Aquionics' equipment  specifications were also used to determine the  materials  and weights of
the UV vessel.
36 Aquionics. PearlAqua™. Accessed at: http://www.aquionics.com/main/pearl-brand2/pearlaqua/ (February 10.
2014).

                                           85

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                        Table 27. Point-of-Use LED UV data sources.
Process
Point-of-Use LED UV disinfection
operation
Infrastructure for UV lamp
Infrastructure for Point-of-Use UV vessel
Three-Inch Sapphire Wafer Manufacture
LED Die Fabrication
LED Packaging Assembly
Materials for LED production
Energy for LED production
Data Source
Aquionics' equipment specifications
DOE LED LCA2U
Aquionics' equipment specifications
DOE LED LCA2U
DOE LED LCA/U
DOE LED LCA2U
ecoinvent v2.2
ecoinvent v2.2
8.3.3   Results

Table 28 presents results for the base case and base case plus the point-of-use hospital LED UV
system per cubic meter of drinking water delivered to the immune-compromised person. Figure
38 shows summary results by life cycle stage for Base Case with the additional point-of-use
disinfection with  the LED UV unit. As previously mentioned, no cost data was available for
LED UV, so this is excluded from the figure. A notable increase in overall impacts is seen for the
addition of point-of-use LED UV disinfection. While some of this increase is due to electricity
requirements for  LED  UV  disinfection,  the majority  of increased impacts  are  driven by
production of the LED UV  lamps. The LED  UV lamp  infrastructure (e.g.,  sapphire  wafer
manufacture, die fabrication)  is complex, and the lamps  are assumed to be produced in China,
which generates much of its electricity from coal,  a relatively high impact energy source. The
electricity mix in  China is modeled based on ecoinvent v2.2 data specific to China, with 78.6%
of the electricity sourced from hard coal, followed by 15.9% sourced from hydropower, 2.9%
sourced from oil, and 2.1% sourced from nuclear12 Such LED UV infrastructure burdens are not
seen for the large-scale LED UV analysis, as that analysis assumes 200 million gallons of water
is able to be treated per lamp compared to the 60,000 gallons of water treated per lamp in this
point-of-use analysis.
                                           86

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Table 28. Base case and Base case plus point-of-use hospital LED UV disinfection results per m3
                        drinking water delivered to the consumer.
Results Category
Hazardous Materials
Global Warming
Energy Demand
Fossil Depletion
Acidification
Eutrophication
Blue Water Use
Smog
Ozone Depletion
Metal Depletion
Human Health, Cancer, Total
Human Health, NonCancer, Total
Human Health, Criteria
Ecotoxicity, Total
Unit
kgCl2
kg C02 eq
MJ
kg oil eq
kg H+ mole eq
kgN eq
m3
kg O3 eq
kg CFC-11 eq
kg Fe eq
CTU
CTU
kgPMWeq
CTU
Base Case 1
0.0018
1.04
19.8
0.36
0.48
9. 7E-04
1.20
0.067
2.8E-08
0.036
2.9E-11
3.2E-11
0.0015
4.4E-04
Base Case 1 plus
Point-of-Use
Hospital LED UV
Disinfection
0.0018
1.47
25.6
0.48
0.67
1.4E-03
1.21
0.101
4.0E-08
0.075
4.6E-11
5.0E-11
0.0023
1.8E-03
                                          87

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I Source Water Acquisition
] Pre-Disinfection
I Distribution
            I Drinking Water Treatment Plant Energy Usage
            I Primary Disinfection
            IPoint-of-Use LED UV Disinfection
         20%
Percent Contribution
40%           60%
                  0%

     Chlorine Usage

    Global Warming

     Energy Demand

    Fossil Depletion

       Acidification

      Eutrophication

     Blue Water Use

             Smog

    Ozone Depletion

     Metal Depletion  |

     Human Health,.. |

     Human Health,..

     Human Health,..

         Ecotoxicity

Figure 38. Base Case 1 plus point-of-use hospital LED UV disinfection contribution analysis results.


8.4    Comparative Results

Figure 39 illustrates the comparative results for the different hospital point-of-use disinfection
technologies. Both  point-of-use  technologies are examined as an  addition  to  Base  Case  1
(disinfection with gaseous  chlorine). In this figure,  results are  normalized to the point of use
technology with the highest impact in the category under examination. In all cases, the LED UV
point-of-use  technology has the greater impacts compared to the Pall point-of-use tap filter. The
LED UV system requires  some  electricity for operation;  whereas, the filter  does not require
electricity for generation. The production of the LED UV lamp  in  China is relatively more
burdensome  for the impacts examined compared to the infrastructure production requirements of
the Pall filter.

While  a direct  comparison  is  made  here  between these  two  point-of-use  disinfection
technologies, there  are some  key distinctions  between them.  The Pall  filter is  designed for
100%
                     88

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application to the faucet; whereas, the LED UV system is designed for application prior to the
faucet. Any pathogens formed near the faucet may not be treated by the LED UV system.
Additionally, the Pall filter is  designed specifically for hospital use; whereas, Aquionics notes
that healthcare  is just one of many applications  for the point-of-use  LED  UV system.  This
analysis is  provided to begin to understand the potential impact differences between these two
systems, and it is not intended to provide a recommendation on use of either of the technologies.
                                           89

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                l Source Water Acquisition
                 Pre-Disinfection
                 Distribution
                                                               l Drinking Water Treatment Plant Energy Usage
                                                               l Primary Disinfection
                                                               Point-of-Use Disinfection
                                            20%
                                                        Percent Contribution
                                                            40%             60%
80%
100%
  5
           Point-of-Use Filter
        Point-of-Use LED UV
           Point-of-Use Filter
        Point-of-Use LED UV
  gjj "B     Point-of-Use Filter
  S3  g
  W Q  Point-of-Use LED UV
  -.2     Point-of-Use Filter
  $ "S
  r9 "3-
        Point-of-Use LED UV
  '^3
i  fe
o
<	
           Point-of-Use Filter
        Point-of-Use LED UV
tro
tio
           Point-of-Use Filter
        Point-of-Use LED UV
           Point-of-Use Filter
U
  5     Point-of-Use LED UV
  03	
     OD     Point-of-Use Filter
        Point-of-Use LED UV
  •o .o     Point-of-Use Filter
        Point-of-Use LED UV
           Point-of-Use Filter
        Point-of-Use LED UV
  j=  3
  ~
           Point-of-Use Filter
    O  Point-of-Use LED UV
        Point-of-Use LED UV
           Point-of-Use Filter
S "3 £
  ^ 3  Point-of-Use LED UV
    1
           Point-of-Use Filter
        Point-of-Use LED UV
    Figure 39. Comparative results for different hospital point-of-use disinfection technologies.
                                                          90

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9.     OVERALL RESULTS SUMMARY

Results of the base case drinking water analysis with disinfection via gaseous chlorine show
impacts are largely driven by electricity consumption at the drinking water treatment plant and
during distribution to the  consumer.  Overall, primary disinfection with gaseous chlorine only
contributes zero to five percent to the total life cycle impacts of drinking water treatment for the
results categories examined.  Utilization of ferrate results in environmental, human health, and
cost benefits for combined use in the pre-disinfection and primary disinfection  stages, since
ferrate acts  as  both a coagulant and  disinfectant and only  small  dosages are  required for
treatment. Application of UV technology increases impacts during disinfection through increased
electricity consumption and  through  new capital investment,  but eliminates the  formation of
disinfection by-products and greatly reduces hazardous chlorine usage. LED UV is more energy
efficient compared to conventional mercury-vapor UV; however, it is currently developed only
for point-of-use applications,  and not large-scale treatment facilities.  For  hospital point-of-use
disinfection, the LED UV technology has the greater impacts overall compared to the Pall filter.
The LED UV system requires some electricity for operation; whereas, the filter does not require
electricity for generation and the production of the LED UV lamp in China is relatively more
burdensome for the impacts examined compared to the infrastructure production requirements of
the Pall filter. In general, this  analysis is provided to understand the potential impacts and trade-
offs between different drinking water disinfection  technologies within the framework of the
entire drinking water supply  system, and it is not intended to  provide a recommendation on
whether any technology is superior to other technologies. The LCA model and cost analysis built
here can serve  as the  basis  for future assessments  of water-related  technologies and can be
incorporated into broader, sustainable systems analyses of water technologies.

10.    REFERENCES

1.     Aquionics. Pearl Aqua™, http://www.aquionics.com/main/pearl-brand2/pearlaqua/
       (Accessed February 10. 2014).

2.     AWWA Research Foundation. 2002.  Trace Contaminants in Drinking Water Chemicals.

3.     AWWA. 2008. Costing Analysis to Support National Drinking Water Treatment Plant
       Residuals Management Regulatory Options. Submitted by Environmental Engineering &
       Technology, Inc. Newport News, VA.

4.     Chowdhury, Zaid K.; Westerhoff, Garret P; Summers, R. Scott; Leto, Brian;  Nowack,
       Kirk. 2012. Activated Carbon: Solutions for Improving Water Quality. American Water
       Works Association.

5.     Ecoinvent Centre (2010), ecoinvent data v2.2. ecoinvent reports No.  1-25, Swiss Centre
       for Life Cycle Inventories.

6.     Ecoinvent Cumulative Energy Demand (CED) Method implemented in ecoinvent data
       v2.2. 2010. Swiss Centre for Life Cycle Inventories.
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7.      eGRID 2008 (Emissions and Generation Resource Integrated Database). U.S. EPA.
       (www.epa.gov/cleanenergy/egrid).

8.      Ekwall, Cecilia. 2004. LCA of tap water disinfection - a comparison of chlorine and UV-
       light. Department of Biometry and Engineering, Swedish University of Agricultural
       Sciences. http://ex-epsilon.slu.se/archive/00000280/01/cecilia_ekwall_0402.pdf

9.      Goedkoop. M.J., Heijungs. R, Huijbregts. M., De Schryver. A., Struijs. J., Van Zelm. R.
       ReCiPe 2008. A life cycle impact assessment method which comprises harmonised
       category indicators at the midpoint and the endpoint level; First edition Report I:
       Characterisation; 6 January 2009. See http://www.lcia-recipe.net.

10.     Gloria, T.P., Lippiatt, B.C., and Cooper, J. 2007. Life cycle impact assessment weights to
       support environmentally preferable purchasing in the United States. Environ. Sci.
       Technol, 41,7551-7557.

11.     Malley, J.P., Jr. 2006. Development of Standard Operating Plans for Mercury Release
       from UV Technologies. Used in Drinking Water Treatment Plants. Course Lecture
       Materials University of New Hampshire, Durham, NH

12.     National Renewable Energy Lab. US LCI Database. See:
       http://www.nrel.gov/lci/database/default.asp.

13.     Pall Corporation. Pall-Aquasafe™ AQ3 IF 1S and AQ3 IF 1R Filters for Waterborne
       Microorganisms. Accessed at:
       http://www.pall. com/main/medical/product.page?id=45154

14.     Pall Corporation. March 2013. Declaration of Compliance: Pall-Aquasafe™ Disposable
       Water Filter 31 Day Use - Tap Application. Accessed at:
       http://www.pall.com/pdfs/Medical/A031FlR-Declaration-of-Compliance.pdf

15.     Pall Corporation. Nov 2012.  QPoint™ Tap Water Filter - USA. Accessed at:
       http://www.pall.com/main/consumer-water/product.page71idHi8pwl57i

16.     Pall Corporation. Feb 2009. Pall-Aquasafe™ Disposable Water Filter - Tap (AQ31F1S
       and AQ31F1R) Field Evaluation Report.

17.     Pall Corporation Aquasafe Medical Filters. See:
       http://www.pall. com/main/medical/product.page?id=45154#

18.     Pall Medical North American Sales Representatives Personal Communication. February
       24, 2014.

19.     Pfister ,S., Saner, D., Koehler, A. 2011. The environmental relevance of freshwater
       consumption in global power production. International Journal of Life Cycle Assessment,
       16(6): 580-591.


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20.    U.S. Department of Energy: Buildings Technology Program. June 2012. Life Cycle
       Assessment of Energy and Environmental Impacts of LED Lighting Impacts. Accessed
       at: http://appsl.eere.energy.gov/buildings/publications/pdfs/ssl/2012_led_lca-pt2.pdf

21.    U.S. Department of Energy: Buildings Technology Program. Oct 2013. Faucets.
       Accessed at:
       http://wwwl.eere.energy.gov/buildings/appliance_standards/product.aspx/productid/64

22.    U.S. EPA. 2013. National Primary Drinking Water Regulations. See:
       http ://water. epa. gov/drink/contaminants/index. cfm

23.    U.S. EPA's Tool for the Reduction and Assessment of Chemical and Other
       Environmental Impacts (TRACI). See: http://www.epa.gov/nrmrl/std/sab/traci/.

24.    U.S. EPA. February 2013 .Quality Assurance Project Plan for Systems-Based
       Sustainability and Emerging Risks Performance Assessment of Cincinnati Regional
       Water Technology Innovations: Comparative Life Cycle Assessment and Cost Analysis of
       Water Treatment Options. Prepared by Eastern Research Group, Inc. for U.S. EPA
       Sustainable Technology Division, National  Risk Management Research Laboratory.
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Environmental Protection
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