&EPA
United States
Environmental Protection
Agency
Technical Analysis for Determination of Technology-Based
Permit Limits for the Guaynabo Drinking Water Treatment
Facility NPDES No. PR0022438
Prepared for:
U.S. Environmental Protection Agency Region 2
Division of Environmental Planning and Protection
290 Broadway
New York, NY 10007-1866
Prepared by:
U.S. Environmental Protection Agency
Engineering and Analysis Division
Office of Water
1200 Pennsylvania Avenue, NW
Washington, D.C. 20460
March 23, 2009
EPA 821 -R-11-006
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TABLE OF CONTENTS
Page
1.0 OVERVIEW 1-1
2.0 LEGAL AUTHORITY 2-1
3.0 FACILITY INFORMATION 3-1
4.0 WASTEWATER CHARACTERISTICS 4-1
4.1 Treatment Chemical Addition 4-1
4.2 Wastewater Characteristics 4-2
4.3 Pollutants of Concern 4-5
4.4 Baseline Pollutant Loadings 4-6
4.4.1 Baseline Pollutant Loadings Using DMR Data 4-7
4.4.2 Baseline Pollutant Loadings Using Empirical Formulas 4-8
4.4.3 Calculation of Toxic-Weighted Pound Equivalents 4-10
4.4.4 Baseline Pollutant Loadings Results 4-10
5.0 TREATMENT TECHNOLOGY OPTIONS FOR THE GUAYNABO WTP 5-1
5.1 Treatment Technology Options 5-1
5.2 Technology 1: Optimization of Residuals Management + Dechlorination 5-2
5.2.1 Technology 1 Costs 5-3
5.2.2 Technology 1 Pollutant Removals 5-5
5.2.3 Environmental Benefits 5-8
5.2.4 Non-water Quality Environmental Impacts 5-12
5.3 Technology 2: Optimization of Residuals Management + Zero Discharge Via
Complete Recycle 5-13
5.3.1 Technology 2 Costs 5-14
5.3.2 Technology 2 Pollutant Removals 5-20
5.3.3 Environmental Impacts 5-20
5.3.4 Non-water Quality Environmental Impacts 5-20
6.0 COMPARISON OF TECHNOLOGY OPTIONS 6-1
6.1 Best Practicable Control Technology Currently Available (BPT) 6-1
6.1.1 Assessment of Economic Achievability 6-2
6.1.2 Recommended Permit Limitations for Technology 1 6-21
6.2 Best Conventional Pollutant Control Technology (BCT) 6-25
6.3 Best Available Technology Economically Achievable (BAT) 6-26
7.0 SUMMARY 7-1
8.0 REFERENCES 8-1
Appendix A: LIST OF POLLUTANTS "BELIEVED ABSENT" FROM DECEMBER 14,
2005 PERMIT APPLICATION
Appendix B: CALCULATION OF POLLUTANT LOADINGS USING DMR DATA
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TABLE OF CONTENTS (Continued)
Page
Appendix C: CALCULATION OF POLLUTANT LOADINGS USING EMPIRICAL
CHEMICAL FORMULAS
Appendix D: OPTIMIZATION OF RESIDUALS COST MODULE
Appendix E: DRAFT DECHLORINATION COST MODULE
Appendix F: COST ESTIMATE FOR ADDITIONAL DISINFECTION AS PART OF ZERO
DISCHARGE VIA COMPLETE RECYCLE
11
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LIST OF TABLES
Page
1-1 Puerto Rico Water Treatment Plants Requiring NPDES Permit Renewals 1-1
4-1 Guaynabo WTP Treatment Chemicals Identified During 2006 Site Visit 4-1
4-2 Chemicals Detected in Polyaluminum Chloride 4-1
4-3 Parameters Reported in Guaynabo WTP DMRs 4-3
4-4 Additional Potential Guaynabo WTP Wastewater Pollutants 4-5
4-5 Recommended Pollutants of Concern and Load Data Availability for the Guaynabo
WTP 4-6
4-6 Baseline Pollutant Loadings for POCs with DMR Data 4-8
4-7 Aluminum Chiorohydrate Properties 4-9
4-8 Baseline Pollutant Loadings for POCs with Treatment Chemical Information 4-9
4-9 Estimated Baseline Loadings for POCs 4-11
5-1 Summary of CWA Technology Levels of Control 5-1
5-2 Technology Options Considered 5-2
5-3 Costs to Implement Optimization of Residuals Management 5-3
5-4 Cost Estimate Components of Dechlorination 5-4
5-5 Cost Estimate Components of Technology 1: Optimization of Residuals Management
+ Dechlorination 5-5
5-6 Estimated Solids Removals for Optimization of Residuals Management 5-5
5-7 Pollutant Removals for Optimization of Residuals Management 5-7
5-8 Metals Concentrations in the Guaynabo WTP Effluent, from DMR Data 5-8
5-9 Analytical Monitoring Costs for the Guaynabo WTP for Recycling of Wastewater
Back to the Raw Water Treatment System, in 2005 Dollars 5-17
5-10 Cost Estimate Components of Technology 2: Optimization of Residuals Management
+ Zero Discharge Via Complete Recycle 5-18
6-1 Summary of Factors for Technologies 1 and 2 6-1
6-2 Summary of Compliance Costs (2005$) 6-4
iii
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LIST OF TABLES (Continued)
Page
6-3 Summary of PRASA's Capital Financing Terms 6-6
6-4 Total Annual Water Revenue Increase Based on BPJ Costs for Guaynabo WTP
($000s,2005$) 6-7
6-5 Total Annual Water Revenue Increase Based on BPJ Costs for PRASA Utility
($000s,2005$) 6-8
6-6 Summary of PRASA's Water Utility Operations 6-8
6-7 Total Annual Rate Increase per Unit of Consumption Based on BPJ Costs for
Guaynabo WTP (2005$ per 1,000 gal) 6-9
6-8 Total Annual Rate Increase per Unit of Consumption Based on BPJ Costs for PRASA
Utility (2005$ per 1,000 gal) 6-10
6-9 Annual Increase in Water Cost per Household Based on BPJ Costs for Guaynabo
WTP (2005$/yr) 6-11
6-10 Annual Increase in Water Cost per Household Based on BPJ Costs for PRASA Utility
(2005$/yr) 6-11
6-11 Puerto Rico Income Distribution (2005$) 6-13
6-12 Threshold Household Income Level Based on BPJ Costs for Guaynabo WTP ($2005)6-17
6-13 Threshold Household Annual Income Level Based on BPJ Costs for PRASA Utility
(2005$) 6-18
6-14 Households with Income Below Affordability Thresholds Based on BPJ Costs for
Guaynabo WTP (2005$) 6-18
6-15 Households with Income Below Affordability Thresholds Based on BPJ Costs for
PRASA Utility (2005$) 6-19
6-16 Target Level and Recommended Limitation for TSS 6-21
6-17 Turbidity Values Excluded from LTA Calculations 6-22
6-18 TSS Variability Factors in Recent Regulations 6-23
6-19 Summary of Current Permit Limits and Monitoring Data 6-24
6-20 Conventional Pollutant Concentrations 6-25
7-1 Long-Term Averages Based on Technology 1 7-1
IV
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LIST OF FIGURES
Page
3-1 Guaynabo WTP Intake and Rapid Mix Tank 3-1
3-2 Guaynabo WTP Flocculation Basins During Mixing (Left) and Settling (Right) 3-2
3-3 Guaynabo WTP Sedimentation Tanks 3-2
3-4 Guaynabo WTP Filters 3-3
3-5 Guaynabo WTP Equalization Basin (Left) and Sludge Drying Beds (Right) 3-4
3-6 Guaynabo WTP Process Flow Diagram 3-5
6-1 Cumulative Distribution of Income in Puerto Rico: Log-Normal Distribution Model .6-14
6-2 Cumulative Distribution of Income in Puerto Rico: Exponential Distribution Model ..6-15
6-3 Log-Normal vs. Exponential Representation of the Lower Income Range in Puerto
Rico 6-16
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1.0
OVERVIEW
The purpose of this document is to assist U.S. Environmental Protection Agency
(EPA) Region 2 in the development of site-specific, technology-based National Pollutant
Discharge Elimination System (NPDES) permit limits for drinking water treatment plants in
Puerto Rico. This document focuses on the residuals wastewater discharge from the Guaynabo,
Puerto Rico Water Treatment Plant (Guaynabo WTP). The Guaynabo WTP operates a
conventional filtration drinking water treatment plant (i.e., treats raw water using coagulation,
flocculation, sedimentation, and filtration). The plant discharges wastewater to the Bayamon
River via a stormwater sewer. EPA Region 2 is the NPDES permitting authority for this facility
and requested assistance in deriving recommended permit limits.
EPA Region 2 received NPDES permit renewal applications for 17 water
treatment plants in Puerto Rico in 2006 and 2007. They requested assistance from EPA's
Engineering and Analysis Division, Office of Water (referred to as "EPA" in this document), for
the plants listed in Table 1-1.
Table 1-1. Puerto Rico Water Treatment Plants Requiring NPDES Permit Renewals
NPDES
Permit
Number
PR0022420
PR0022616
PR0022918
PR0022411
PR0022438
PR0024210
PR0026182
PR0022845
PR0022586
PR0022543
PR0022900
PR0024015
PR0023990
PR0024651
PR0022888
PR0022756
PR0026085
Facility Name
PRASA WTP Canovanas
PRASA WTP Enrique Ortega
PRASA Aquadilla WTP
PRASA WTP Sergio Cuevas
PRASA WTP Guaynabo
PRASA WTP Arecibo
PRASA Santa Isabel WTP
PRASA Rio Blanco WTP
PRASA WTP Guamana Filter
Plant
PRASA WTP Cidra Filtration
Plant
PRASA WTP Mayaguez Filter
Plant
PRASA WTP Ramey Plant
PRASA Miradero WTP
PRASA Guaraguao WTP
PRASA Caguas WTP
PRASA Ponce Nueva WTP
Superacueducto Filtration
Plant
Mean
Wastewater
Effluent
Flow
(MGD)a
NA (zero
discharge)
1.30
0.416
2.09
1.47
0.0152
0.167
0.109
0.00587
0.328
0.0380
0.119
0.338
0.00278
0.180
0.433
4.75
Mean
Turbidity
(NTU)a
NA (zero
discharge)
733
632
414
240
232
194
125
112
100
99
84
84
79
64
35
33
Residuals Treatment In Place a
Zero Discharge: STS, supernatant
recycled to DWT plant headworks.
STS
STS not in operation due to
mechanical problems.
STS
STS
None. STS construction is planned.
None.
In 2000, STS was constructed but no
gravity thickener.
None. In 2002, plant was to be
eliminated and replaced.
None. In 2001, STS was under
construction.
None. STS planned for construction.
STS + dechlorination
STS
None
None. Application says STS would
be constructed by 2003.
STS
Series of polishing lagoons for
sludge removal.
a - Data obtained from the facilities' discharge monitoring reports and permit applications provided by EPA
Region 2. DCN EPA-HQ-OW-2004-0035-DW03621.
STS - Sludge treatment system composed of a holding tank, gravity thickener, and sludge drying beds.
1-1
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In setting best professional judgment (BPJ) limitations, the permit writer must
consider the following factors for best practicable control technology currently available (BPT)
requirements:
Total cost of application of technology in relation to the effluent reduction
benefits to be achieved from such application;
The age of equipment and facilities involved;
The process employed;
The engineering aspects of the application of various types of control
techniques;
Process changes; and
Non-water quality environmental impacts (including energy
requirements).
These requirements are specified in 40 CFR 125.3(d) and are sometimes referred
to as the "Section 304(b) factors." In particular, Section 304(b)(l)(B) of the CWA directs EPA to
consider the "total cost of application of technology in relation to the effluent reduction benefits
to be achieved from such application." This inquiry does not limit EPA's broad discretion to
adopt BPT limitations based on available technology unless the required additional effluent
reduction benefits are wholly out of proportion to the costs of achieving these benefits.
EPA completed the BPJ analysis of technology-based NPDES permit limits for
the Guaynabo WTP by comparing the treatment-in-place to two technology options. The analysis
focuses on the process residuals and wastewater discharges from the water treatment plant
(sedimentation sludge and filter backwash water). This analysis does not evaluate other
discharges from the plant (e.g., stormwater).
For each technology option, EPA compared the potential incremental annualized
compliance costs and the related effluent reduction benefits, economic impacts, non-water
quality environmental impacts, and other factors consistent with the Clean Water Act.
The Guaynabo WTP currently treats process residuals through a sludge treatment
system, consisting of an equalization basin, gravity thickener, and sludge drying beds.
Supernatant from the thickener discharges to the Bayamon River.
To determine the permit limits for the supernatant discharge to the Bayamon
River, EPA considered the following two technology options: (1) Technology 1: Optimized
Residuals Management plus Wastewater Dechlorination; and (2) Technology 2: Optimized
Residuals Management plus Zero Discharge of Wastewaters achieved via complete recycle. The
first technology option provides for additional equalization capacity, to offset surges in solids
loads from sedimentation tank drainage, and also provides for conversion of free chlorine to
chloride using sodium metabisulfite. The second technology option also provides for additional
1-2
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equalization capacity and eliminates pollutant discharges into waters of the U.S. by recycling the
supernatant from the gravity thickener back to the WTP headworks.
The general economic acceptance test this is applied to the NPDES permit limits
for residuals wastewater discharge from the Guaynabo WTP is that they are "economically
achievable" - a concept that has been generally applied to the businesses and other entities that
must achieve the discharge reductions needed to comply with effluent discharge regulations.
However, because the water system is expected to pass all of the compliance cost burden to
system customers through rate increases, the economic achievability analysis for the potential
NPDES permit requirements rests primarily on the affordability of the requirements to PRASA's
customers, and, in particular, on the system's household customers that will incur costs to meet
the NPDES requirements. Under this framework, the technology options would be economically
achievable if they were found to be "affordable" by the water system customers who bear the
costs through water rate increases.
This report has been produced with information specific to the Guaynabo WTP.
The methodologies in this report may be used to develop analyses, such as treatment technology
costs and performance, for other WTPs in the PRASA system with comparable existing
treatment technologies, service populations, source water quality, and operating characteristics. It
is important to note, however, that the same type of data as those presented in this report would
be needed to develop independent analyses for other WTPs similar to Guaynabo.
1-3
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2.0 LEGAL AUTHORITY
Congress enacted the Clean Water Act (CWA) "to restore and maintain the
chemical, physical and biological integrity of the Nation's waters" CWA Section 101(a), 33
U.S.C. §1251(a). To meet this objective, Congress declared a national goal of eliminating the
discharge of pollutants into the nation's waters, id. §1251(a)(l), and prohibit the "discharge of
any pollutant" except in compliance with the CWA's provisions. One of these provisions is
CWA Section 402, under which discharges can be authorized by a NPDES permit.
One of the CWA's major strategies in making "reasonable further progress
toward the national goal of eliminating the discharge of all pollutants" requires discharge
limitations, based not solely on the impact of the discharge on receiving waters, but also on the
capabilities of the technologies available to control those discharges. The technology-based
limits aim to prevent pollution by requiring polluters to install and implement various forms of
technology designed to reduce the pollution discharged into the nation's waters. Where
technology-based limitations alone are insufficient to attain or maintain applicable water quality
standards, NPDES permits also include water quality-based limitations. The CWA also gives
EPA the authority to consider process changes in order to evaluate technology-based controls of
industrial pollutant discharges.
EPA largely establishes technology-based controls in regulations known as
effluent limitations guidelines (effluent guidelines). EPA establishes these regulations for
specific industrial sectors after considering an in-depth analysis of each industrial sector.
However, EPA has not promulgated national, technology-based effluent guidelines for the
Drinking Water Treatment and Supply (DWT) industrial sector.
In the absence of applicable effluent guidelines for the discharge or pollutant,
technology-based limitations are determined by the permit writer on a case-by-case basis, in
accordance with the statutory factors specified in CWA Sections 301(b)(2) and 304(b), 33 U.S.C.
§§1311(b)(2), (3), 1314(b), 1342(a)(l). These site-specific, technology-based effluent limitations
reflect the best professional judgment (BPJ) of the permit writer, taking into account the same
statutory factors EPA would use in promulgating a national categorical rule, but applied to the
applicant's particular circumstances.
NPDES permit writers can develop BPJ controls using one of two methods: (1)
transferring limits from an existing source (e.g., from other existing effluent guidelines or a
similar NPDES permit); or (2) deriving new limits (U.S. EPA, 1996). EPA did not identify
transferable limits from an existing effluent guideline or other permit. This BPJ analysis for the
Guaynabo WTP relies on the second approach (i.e., deriving new limits on a case-by-case basis),
because new data collected as part of the Drinking Water Treatment effluent guidelines
rulemaking development process provided new insight into residuals wastewater treatment.
The NPDES regulations at 40 CFR 125.3 provide that permits developed on a
case-by-case basis must consider: (1) the appropriate technology for the category of point
sources for which the applicant is a member, based on all available information; and (2) any
unique factors related to the applicant. The analysis in this document uses facility-specific
information. The major references used for the analysis include the NPDES permit application
and discharge monitoring report (DMR) data provided by EPA Region 2. In addition, EPA
2-1
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obtained facility-specific information from a report of an August 2006 EPA site visit, which was
completed as part of EPA's review of the DWT industrial sector (ERG, 2006).
Finally, technology-based limits in NPDES permits are performance-based
measures. EPA incorporates technology-based controls in NPDES permits that correspond to the
application of an identified technology (including process changes), but do not require
dischargers to install the identified technology. Therefore, EPA leaves to each facility, including
the Guaynabo WTP, the discretion to select the technology design and process changes necessary
to meet the discharge limitations ultimately specified in the NPDES permit.
2-2
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3.0
FACILITY INFORMATION
The Guaynabo WTP is located on Road PR-833, kilometer 14.8, Los Filtros
sector at Frailes Ward, in Guaynabo, Puerto Rico (Latitude 18.38, Longitude -66.12). Because
Puerto Rico has not been granted NPDES permitting authority and is in EPA Region 2, EPA
Region 2 is the NPDES permit authority for this facility.
The Guaynabo WTP treats water from the Guaynabo and Bayamon Rivers. Its
design capacity is 26 million gallons per day (MGD), but it typically produces 30 MGD of
finished water for a service population of 204,000 people.l The plant began operations in 1924
and staffs a total of 19 personnel, including two operators per shift for 24 hours per day. The
steps in the water treatment process are illustrated in the flow diagram in Figure 3-6 and are
described below (PRASA, 2005; ERG, 2006).2
Intake. Upon intake, the water first enters a rapid mix chamber where the
primary coagulant, GC-850 (polyaluminum chloride as aluminum
chlorohydrate), is added at an average rate of 8,500 pounds per day
(Ibs/day) and a secondary coagulant, C-591 (poly-diallyl, dimethyl
ammonium chloride), is added at an average rate of 330 Ibs/day (PRASA,
2007; ERG, 2006). The facility also adds lime at a rate of 20 Ibs/day
(PRASA, 2007). Figure 3-1 shows the intake and rapid mix tank, as
viewed during the August 2006 site visit.
Figure 3-1. Guaynabo WTP Intake and Rapid Mix Tank
1 The Guaynabo WTP produces drinking water above capacity. Thus, the Guaynabo WTP is using equipment
designed for lower flows, including residuals management equipment. As a result, retention times are less than they
would be at lower flows, and sludge accumulates more quickly in the sedimentation basins (ERG, 2006).
2 As part of its review of the DWT industrial sector, EPA visited seven facilities in Puerto Rico, including the
Guaynabo WTP. EPA obtained facility specific information from a site visit completed in August 2006 (ERG,
2006). The photographs and some process information were obtained during the site visit.
3-1
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Flocculation. After coagulant addition, the water moves to flocculation
basins (PRASA, 2005). Here, the facility adds a polymer to assist with
flocculation. Figure 3-2 shows the flocculation basins during mixing (left)
and settling (right).
Figure 3-2. Guaynabo WTP Flocculation Basins During Mixing (Left) and Settling (Right)
Sedimentation. After flocculation, the water moves to sedimentation tanks,
where the floe settles from the water. Five sedimentation tanks operate in
parallel and chlorine is added as a pre-chlorination step. The
sedimentation tanks are equipped with continuous sludge removal, and the
plant also drains the tanks quarterly (at the manufacturer's
recommendations). Tank drainage is limited to one tank each day, and
sedimentation tank drainage is treated at the facility's sludge treatment
system (STS). Figure 3-3 shows the sedimentation tanks.
Figure 3-3. Guaynabo WTP Sedimentation Tanks
$-2
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Filtration. Settled water is piped from the sedimentation tanks to dual-
media filters. The filters consist of sand and anthracite with a base layer of
gravel. Filters are backwashed a minimum of once every 24 hours. Filter
backwash is treated at the facility's sludge treatment system. Figure 3-4
shows the dual-media filters.
Figure 3-4. Guaynabo WTP Filters
Post-Chlorination. Filtered water is disinfected with chlorine gas in a post-
chlorination step, and chlorine is added both before and after the
distribution tank. The finished water is collected in a 10 million gallon,
covered distribution tank before entering the distribution system.
Sludge treatment. The sludge treatment system handles two waste streams
(or residuals) from the Guaynabo WTP: water and sludge from
sedimentation tank drainage and water from filter backwash. In addition to
the continuous sludge removal, the plant drains the sedimentation tanks
quarterly, one tank at a time, sending 1.5 million gallons to the
3-~
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equalization basin each drainage day. The plant pumps the filter
backwash water (1.616 million gallons) to the equalization basin after
each backwash cycle (at least once per day). From the equalization basin,
the residuals are pumped to two gravity thickeners operated in parallel.
Thickener sludge is pumped to six covered, vacuum-assisted sludge drying
beds operated in parallel. Figure 3-5 shows the equalization basin (left)
and sludge drying beds (right) (PRASA, 2005).
Figure 3-5. Guaynabo WTP Equalization Basin (Left) and Sludge Drying Beds (Right)
The supernatant from the thickener is discharged to the Bayamon River. The
NPDES permit application lists the maximum discharge to the river as 3.116 MGD (PRASA,
2007). The Guaynabo WTP contracts with BFI Waste Services for disposal of the dried solids
removed from the sludge drying beds. The solids are trucked to the Ponce landfill, which is
approximately 60 miles from the plant, at a cost of $625 per 20 cubic yards (yd3). On average, 60
to 80 yd3 (3 to 4 containers at 20 yd3 each) of solids are transported to the landfill once per
month (ERG, 2006).
Figure 3-6 is a flow diagram of the Guaynabo WTP as inspected in August 2006
(ERG, 2006). The diagram includes the raw water treatment system and sludge treatment system.
Flow rates in the diagram are based on the day of expected maximum discharge flow (i.e., day
that the WTP drains its largest sedimentation tank, Sedimentation Tank #5).
3 In their NPDES permit renewal application Section II.C, the facility reported that the two residuals streams totaled
3.116 MGD at a maximum (PRASA, 2005). However, in Part V of the permit application, the facility reports actual
monitored residuals flow values: maximum flows of 4.3 MGD and a long-term average flow of 3.05 MGD (PRASA,
2005). The facility is producing drinking water above design capacity (30 MGD distributed vs. 24 MGD designed),
which results in greater sludge volumes (ERG, 2006).
3-4
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(San Jut
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f 30.0 MGD fc M... ^ J. k p . fc T , fc Filters t ^ Distribution
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n a maximum flow of 1.5 MGD. T an jcii
Flow rates based on the day
expected maximum flow.
If recirculatio
of
n occurs
tion
Figure 3-6. Guaynabo WTP Process Flow Diagram
Source: December 14,2005 NPDES Permit Application
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4.0
WASTEWATER CHARACTERISTICS
This section discusses the treatment chemicals added by the Guaynabo WTP
process (Section 4.1). It also presents data on the facility's wastewater characteristics (Section
4.2) and EPA's selection of pollutants of concern (POCs) (Section 4.3). Finally, Section 4.4
presents the estimated baseline pollutant loadings for the POCs.
4.1
Treatment Chemical Addition
At the Guaynabo WTP, the process of purifying river water for human
consumption includes addition of chemicals to assist in flocculation and settling, and further
addition of chemicals for disinfection. The Guaynabo WTP generates residuals wastewater from
filter backwash and sedimentation tank drain. The wastewater is treated through its sludge
treatment system, and effluent wastewater discharges to the Bayamon River. EPA obtained data
on treatment chemical addition and effluent water quality. Table 4-1 lists the chemicals added at
the Guaynabo WTP.
Table 4-1. Guaynabo WTP Treatment Chemicals Identified During 2006 Site Visit
Chemical
Gaseous chlorine - Primary Chlorination Only
Hydrated Lime (Ca(OH)2)
Polymer GC-850 (Polyaluminum chloride as Aluminum
Chlorohydrate)
Polymer C-591 (Polydiallyl dimethyl ammonium chloride)
Purpose
Primary Disinfection
Coagulant/pH Adjustment
Coagulant Aid
Coagulant Aid
Dosage
330 Ib/day
20 Ib/day
8,500 Ibs/day
100 Ibs/day
Sources: The Safe Drinking Water Information System (SDWIS), the Community Water Systems Survey (CWSS),
the Information Collection Rule (ICR) Auxiliary 1 Database, and EPA's site visits to Puerto Rico DWT plants. See
also the memorandum entitled, "Chemicals Added as Part of Drinking Water Treatment at Puerto Rico Facilities,"
dated February 21, 2007, DCN EPA-HQ-OW-2004-0035-DW03620.
The treatment chemicals listed in Table 4-1 contain active ingredients such as
aluminum, calcium, and ammonia compounds, but they also contain impurities. From the
American Water Works Association (AWWA) publication, Trace Contaminants in Drinking
Water Chemicals, drinking water treatment chemicals contain impurities that can concentrate
into detectable levels in residuals and recycle streams over time (AWWA, 2002). Table 4-2 lists
the chemical impurities detected in polyaluminum chloride, as identified by AWWA. Appendix
C contains a complete listing of the AWWA chemical data for polyaluminum chloride, including
those chemicals that were not detected.
Table 4-2. Chemicals Detected in Polyaluminum Chloride
Pollutant
Aluminum
Barium
Calcium
Chromium
Copper
Iron
Mean Concentration (mg/kg dry)
140,000
0.553
105
0.41
0.497
46.7
4-1
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Table 4-2. Chemicals Detected in Polyaluminum Chloride
Pollutant
Magnesium
Manganese
Mercury
Molybdenum
Nickel
Phosphorus
Potassium
Silicon
Sodium
Strontium
Titanium
Vanadium
Zinc
Zirconium
Mean Concentration (mg/kg dry)
19.3
2.30
0.978
1.10
1.20
263
8.33
30.9
728
0.41
1.9
2.0
21.8
0.683
Source: AWWA, 2002.
As a result of disinfection, chlorine by-products may form in drinking water and
drinking water treatment residuals (AWWA, 2002). By-products from disinfection include
dihaloacetonitriles, haloacetic acids, and trihalomethanes.
4.2
Wastewater Characteristics
The Guaynabo WTP wastewater contains pollutants from the raw water (the
Guaynabo and Bayamon Rivers), from treatment chemical addition, and from disinfection by-
products. EPA Region 2 provided discharge monitoring report (DMR) data for the Guaynabo
WTP, for 2003 to 2005. Table 4-3 lists the pollutant parameters from the DMR data, their
possible source, and the pollutant concentration ranges reported in the DMRs.
4-2
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Table 4-3. Parameters Reported in Guaynabo WTP DMRs
Pollutant Name in DMR
Ammonia (Total Ammonia and
Ammonium)
Biochemical Oxygen Demand
(BOD, 5-Day)
Color
Dissolved Oxygen
Dissolved Sulfide
Fecal Coliform
Oil & Grease
pH
Surfactants
Temperature
Total Arsenic
Total Coliform
Total Copper
Total Dissolved Solids (TDS)
Total Fluoride
Total Lead
Total Manganese
Possible Pollutant Source a
Treatment chemical addition (C-591). Also occurs naturally in some
surface water.
Occurs in surface water both naturally and from animal and human
sources (including treated sewage and industrial discharges).
Treatment chemical addition (polymers) and naturally occurring in raw
water.
Not applicable.
Occurs naturally in some surface water.
Occurs in surface water from animal and human sources (including
animal feeding operations).
Water quality -based parameter. Does not result from drinking water
treatment process. b
Treatment chemical addition (lime, alum, and calcium hydroxide).
Water quality -based parameter. Does not result from drinking water
treatment process based on the identified chemical additions at
Guaynabo WTP. b
Altered during retention time in sedimentation basin and thickener.
Occurs naturally in some surface water. Not present in treatment
chemicals added by Guaynabo WTP.
Occurs in surface water from animal and human sources (including
animal feeding operations).
Occurs naturally in some surface water. Also treatment chemical
addition (treatment chemical impurities).
Occurs naturally in some surface water and is concentrated in residuals
during water purification.
Occurs naturally in some surface water.
Occurs naturally in some surface water. Not present in treatment
chemicals added by Guaynabo WTP.
Occurs naturally in some surface water. Also treatment chemical
addition (treatment chemical impurities).
Concentration (mg/L), Unless Otherwise Noted
Minimum
Non-detect
(ND)
ND
ND
2.8
ND
ND
Maximum
1.56
17
20
11.1
0.011
1,600
Average
0.262
2.23
5.65
4.725
0.000633
102
No valid data points included in DMR data.
7.5
ND
23.3
ND
ND
ND
0.26
0.025
ND
0.0039
8.7
0.029
29.3
0.043
1,600
0.759
230
0.19
0.0843
11.7
7.97
0.00324
26.3
0.00354
202
0.0602
175
0.0886
0.00729
0.794
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Table 4-3. Parameters Reported in Guaynabo WTP DMRs
Pollutant Name in DMR
Total Mercury
Total Phosphorus
Total Recoverable Phenolics
Total Residual Chlorine
Total Settleable Solids
Total Zinc
Turbidity
Possible Pollutant Source a
Occurs naturally in some surface water. Also treatment chemical
addition (treatment chemical impurities).
Occurs naturally in some surface water. Also treatment chemical
addition (treatment chemical impurities).
Water quality -based parameter. Does not result from drinking water
treatment process. b
Treatment chemical addition (chlorine)
Occurs naturally in some surface water and is concentrated in residuals
during water purification.
Treatment chemical addition (treatment chemical impurities).
Occurs naturally in some surface water and is concentrated in residuals
during water purification.
Concentration (mg/L), Unless Otherwise Noted
Minimum
ND
ND
0.001
0.2
ND
ND
0.55
Maximum
0.000168
12.8
0.303
2.8
ND
0.664
2,800
Average
0.0000301
0.935
0.0399
1.45
ND
0.0543
260
a - Table 4-3 does not consider whether pollutants (such as metals) are present in raw water. Also, in the 2005 NPDES Permit Application, the Guaynabo WTP
listed many pollutants as "believed absent," including some of those in Table 4-3. Appendix A contains the list of pollutants listed as "believed absent."
b - Source: U.S. EPA Region 2, 2002. Statement of Basis Draft NPDES Permit to Discharge into the Waters of the United States, DCNDW01039.
c - Source: Guaynabo WTP DMRs, 2003 to 2005.
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Table 4-4 lists pollutants in addition to those in Table 4-3 that are likely
discharged in Guaynabo WTP wastewater. These pollutants are components or impurities of
treatment chemicals, or they are disinfection by-products. The NPDES permit for the Guaynabo
WTP does not regulate these pollutants, and no DMR data are available for them, which is why
they do not appear in Table 4-3.
Table 4-4. Additional Potential Guaynabo WTP Wastewater Pollutants
Parameter
Dihaloacetonitriles
Haloacetic acids b
Total Aluminum
Total Barium
Total Calcium
Total Chromium
Total Iron
Total Magnesium
Total Molybdenum
Total Nickel
Total Potassium
Total Silicon
Total Sodium
Total Strontium
Total Titanium
Total Trihalomethanes a
Total Vanadium
Total Zirconium
Basis for Assumed Presence
Disinfection by-product.
Disinfection by-product.
Treatment chemical component.
Treatment chemical impurity.
Treatment chemical impurity.
Treatment chemical impurity.
Treatment chemical impurity.
Treatment chemical impurity.
Treatment chemical impurity.
Treatment chemical impurity.
Treatment chemical impurity.
Treatment chemical impurity.
Treatment chemical impurity.
Treatment chemical impurity.
Treatment chemical impurity.
Disinfection by-product.
Treatment chemical impurity.
Treatment chemical impurity.
a - The parameter Total Trihalomethanes includes chloroform, dichlorobromomethane, dibromochloromethane,
bromoform, and trihalomethanes.
b - The parameter Total Haloacetic Acids includes monochloroacetic acid, dichloroacetic acid, trichloroacetic acid,
monobromoacetic acid, bromochloracetic acid, and dalapon.
4.3
Pollutants of Concern
For the Guaynabo WTP BPJ analysis, EPA's analysis focused on the parameters
and pollutants in Tables 4-3 and 4-4 that result from treatment chemical addition or disinfection.
Table 4-5 lists EPA's recommended pollutants of concern (POCs) for the Guaynabo WTP and
indicates if pollutant loads can be estimated using available data. EPA excluded those pollutants
that only occur naturally in surface water, because the Guaynabo WTP does not generate these
pollutants through chemical addition. EPA also excluded disinfection by-products because no
data were available to estimate pollutant loads.
4-5
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Table 4-5. Recommended Pollutants of Concern and Load Data
Availability for the Guaynabo WTP a
Pollutant
Ammonia (Total Ammonia
and Ammonium)
Color
Settleable Solids
Silicon
Sodium
Total Aluminum
Total Barium
Total Calcium
Total Chromium
Total Copper
TDS
Total Iron
Total Magnesium
Total Manganese
Total Mercury
Total Molybdenum
Total Nickel
Total Phosphorus
Total Potassium
Total Residual Chlorine
Total Strontium
Total Titanium
Total Vanadium
Total Zinc
Total Zirconium
Turbidity
DWT Source
Polymer C-591 ingredient
Treatment Chemical
Addition
Treatment chemical addition
Polymer GC-850 impurity
Polymer GC-850 impurity
Polymer GC-850 ingredient
Polymer GC-850 impurity
Polymer GC-850 impurity
Polymer GC-850 impurity
Polymer GC-850 impurity
Treatment chemical addition
Polymer GC-850 impurity
Polymer GC-850 impurity
Polymer GC-850 impurity
Polymer GC-850 impurity
Polymer GC-850 impurity
Polymer GC-850 impurity
Polymer GC-850 impurity
Polymer GC-850 impurity
Chlorination
Polymer GC-850 impurity
Polymer GC-850 impurity
Polymer GC-850 impurity
Polymer GC-850 impurity
Polymer GC-850 impurity
Treatment chemical addition
Sufficient Data to Calculate Pollutant Loads?
Yes (DMRs).
No. Do not calculate loads for color.
No. Solids data represented by other parameters
(TSS).
Yes. Estimate based on dose and percent impurity.
Yes. Estimate based on dose and percent impurity.
Yes. Estimate based on dose and chemical
composition.
Yes. Estimate based on dose and percent impurity.
Yes. Estimate based on dose and percent impurity.
Yes. Estimate based on dose and percent impurity.
Yes (DMRs).
Yes (DMRs).
Yes. Estimate based on dose and percent impurity.
Yes. Estimate based on dose and percent impurity.
Yes (DMRs).
Yes (DMRs).
Yes. Estimate based on dose and percent impurity.
Yes. Estimate based on dose and percent impurity.
Yes (DMRs).
Yes. Estimate based on dose and percent impurity.
Yes (DMRs).
Yes. Estimate based on dose and percent impurity.
Yes. Estimate based on dose and percent impurity.
Yes. Estimate based on dose and percent impurity.
Yes (DMRs).
Yes. Estimate based on dose and percent impurity.
Yes (DMRs, correlate to TSS concentration; see
Section 4.4).
a - This analysis is limited to the Guaynabo WTP. Additional POCs may apply for other drinking water treatment
facilities.
TDS - Total dissolved solids
TSS - Total suspended solids.
4.4
Baseline Pollutant Loadings
Baseline pollutant loadings represent the quantity (in Ibs and toxic-weighted Ibs)
of pollutants currently discharged to the receiving stream. For the Guaynabo WTP, baseline
pollutant loads are estimated from the supernatant discharge from the thickeners to the Bayamon
River. These loads are estimated from either DMR data (see Appendix B for detailed
4-6
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calculations) or from empirical formulas for added chemicals when DMR data are not available
(see Appendix C for detailed calculations).
Because DMRs present the results of wastewater measurements, EPA is confident
they accurately reflect wastewater concentrations. However, loads calculated using DMR data do
not account for the pounds of pollutants in the raw water. Therefore, where possible, EPA
calculated pollutant loads: 1) using DMR data and 2) using empirical formulas and compared
results. Ultimately, EPA used the loads calculated using DMR data for pollutant removal
estimates.
4.4.1
Baseline Pollutant Loadings Using DMR Data
If DMR data were available for a POC, EPA calculated the pollutant load for
2003, 2004, and 2005, using the following equation:
Annual Load
'January
Cone
Monthly Ave
Flow
Monthly Ave
(UGal] 3.785 xlOE-06L
< x :
2.205 Ib
I Day I
MGal
Days
10E-06mg Month
where:
ConCMonthlyAve ~
FloWMonthlyAve =
Days =
Month
Monthly average concentration for a given pollutant;
Monthly average flow reported for the month; and
Number of days for the month.
In some cases, flow and/or concentration data for a pollutant were missing for a
month. If flow data were missing for a month, EPA used the average flow for that year to
estimate the missing flow. If concentration data were missing for a month, EPA used the average
concentration for that year.
In some cases, pollutant concentrations were reported as "non-detect," or below
detection limits. For the purpose of this analysis, EPA used a "hybrid" approach:
1. If the pollutant concentration was non-detect, and if that pollutant was
reported as non-detect for that whole calendar year, then the pollutant
concentration was assumed to be zero.
2. If the pollutant was reported as non-detect, but it was detected at least
once for that calendar year, then the pollutant concentration was assumed
to be one-half of the detection limit value. For example, in 2005,
Guaynabo detected mercury in 9 of the 12 months. For the three months
where mercury was not detected, EPA assumed the concentration was
one-half of the sample detection limit.
The Guaynabo WTP reports monitoring data for turbidity, expressed as
Nephelometric Turbidity Units (NTUs). For pollutant loadings purposes, turbidity was correlated
4-7
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to total suspended solids (TSS) by assuming that 1 NTU Turbidity = 1.5 mg/L TSS (ASCE,
1996).4
Appendix B contains the spreadsheets that EPA used to estimate baseline loads
using DMR data. Table 4-6 lists the average annual pollutant load estimated for pollutants with
DMR data.
Table 4-6. Baseline Pollutant Loadings for POCs with DMR Data
Pollutant
Ammonia (Total Ammonia and Ammonium)
Total Residual Chlorine
Total Copper
Total Manganese
Total Mercury
Total Phosphorus
TDS
TSS
Total Zinc
Baseline Load (Ibs/yr)
1,170
6,873
232
2,649
0.146
5,351
822,667
1,418,300
197.5
Source: See Appendix B.
4.4.2
Baseline Pollutant Loadings Using Empirical Formulas
For 15 POCs, no DMR data were available and EPA estimated the pollutant loads
based on the Guaynabo WTP chemical addition. Specifically, EPA estimated the pollutant loads
for these 15 pollutants using information on the daily WTP dose of Gulbrandsen GC-850, its
empirical formula, and its estimated impurities. The Guaynabo WTP adds approximately 8,500
Ibs/day of GC-850 to its raw water daily to assist with coagulation and flocculation (PRASA,
2007). GC-850, manufactured by Gulbrandsen as aluminum chlorohydrate (Al2(OH)5Cl), has the
chemical properties listed in Table 4-7.
4 EPA did not have data from the Guaynabo WTP to correlate TSS to turbidity and relied on the midpoint of the rule
of thumb given in Drinking Water Treatment Plant Residuals: "Most water treatment facilities record solids
loadings in terms of turbidity (NTU) rather than suspended solids. Methods of converting turbidity values to
suspended solids are available. Generally the ratio of suspended solids to NTU is 1 to 2." (ASCE, 1996) EPA
selected the mid range of the ratio 1.5 mg/L TSS to 1 NTU Turbidity.
4-8
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Table 4-7. Aluminum Chlorohydrate Properties
Chemical Name and
Formula
Aluminum chlorohydrate
A12(OH)5C1
Gulbrandsen GC-850 a
1.330-1.350 SG
75-90% basicity
7.9-8.7% Cl
23% A12O3
12.2-12.7% Al
25 -50% Aluminum chlorohydrate (12042-91-0)
50-75% Water
Typical Analysis b
SG1.33
83 -84% basicity
8.5% w/w Chlorine
23-24% A12O3 or 40-41% w/w
a - Gulbrandsen, 2000.
b - Gebbie, 2005.
SG - specific gravity.
w/w - weight of element/weight of compound.
Once the aluminum chlorohydrate mixes with the Guaynabo WTP raw water, it
forms flocculent and settles in the sedimentation tank bottoms as aluminum hydroxide solids,
according to the following reaction (AWWA, 2002):
A12(OH)5C1 x 2H2O + 12.5 H2O <-» 2[A1(OH)3 x 3H2O] + H+
7.5 H2O
For simplicity, EPA assumed that 100 percent of the aluminum chlorohydrate
enters the Guaynabo WTP residuals management system as aluminum hydroxide solids. Based
on a 1 percent solids content in the sedimentation tank drainage and an average 390 mg/L TSS in
final effluent, the existing STS removes 96 percent of the solids.5
EPA used the percent of chemicals, by weight, found in polyaluminum chloride to
estimate the baseline discharge of 20 pollutants. For five of these 20 pollutants, EPA also has
DMR data and can compare the estimated pollutant loadings using treatment chemical
information to those calculated using DMR data. The loads estimates using DMR data were
greater than loads estimated using treatment chemical information, except for mercury. Table 4-8
lists the impurities and estimated pounds of pollutant added from GC-850. Table 4-9 compares
the loads estimates. Appendix C contains the detailed calculations.
Table 4-8. Baseline Pollutant Loadings for POCs with Treatment Chemical Information
Pollutant
Potassium
Silicon
Sodium
Total Aluminum
Total Barium
Total Calcium
Weight Ratio
(dry, lbs/1,000,000 Ibs) a
8.33
30.9
728
140,085
0.553
105
Mass Impurity (Ib/yr) b
25.9
96.0
2,260
434,613
1.72
326
Baseline Load (Ib/yr) c
1.03
3.84
90.4
17,385
0.0687
13.0
1 Appendix C contains calculations and basis for assumptions.
4-9
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Table 4-8. Baseline Pollutant Loadings for POCs with Treatment Chemical Information
Pollutant
Total Chromium
Total Copper
Total Iron
Total Magnesium
Total Manganese
Total Mercury
Total Molybdenum
Total Nickel
Total Phosphorus
Total Strontium
Total Titanium
Total Vanadium
Total Zinc
Total Zirconium
Weight Ratio
(dry, lbs/1,000,000 Ibs) a
0.41
0.497
46.7
19.3
2.3
0.978
1.1
1.20
263
0.41
1.9
2.0
21.8
0.683
Mass Impurity (Ib/yr) b
1.28
1.54
145
60.0
7.14
3.03
3.41
3.73
817
1.27
5.75
6.17
67.6
2.12
Baseline Load (Ib/yr) c
0.0511
0.0616
5.79
2.40
0.2854
0.121
0.137
0.149
32.7
0.0509
0.230
0.247
2.70
0.0848
Source: See Appendix C.
a-AWWA, 2002.
b - Pounds per year of chemical = lb/1,000,000 Ib (dry) x 8,500 Ibs/day polyaluminum chloride x 365 days/year.
c - Assume 96 percent removal at Guaynabo WTP STS.
4.4.3
Calculation of Toxic-Weighted Pound Equivalents
EPA weighted the annual pollutant discharges from the Guaynabo WTP using
toxic-weighting factor (TWFs) to calculate toxic-weighted pound equivalents (TWPE) for each
pollutant (U.S. EPA, 2006). EPA followed an established methodology of its Engineering and
Analysis Division (EAD) and summed the estimated TWPE to understand the relative toxicity of
the Guaynabo WTP discharges.
EPA calculates TWPE to rank pollutant discharges by their relative toxicity. EPA
uses a TWF, multiplied by the annual (Ibs) discharged by a pollutant, to calculate annual TWPE
(i.e., TWPE (Ib-eq/yr) = (Ibs/yr) x TWF).
EAD calculates TWFs using a Toxics Data Base containing toxicity data on
aquatic life and human health, as well as data on physical/chemical property, for more than 1,900
pollutants compiled from over 100 references (U.S. EPA, 2006). TWFs account for differences
in toxicity among the pollutants of concern and provide the means to compare mass loadings of
different pollutants on the basis of their toxic potential. TWFs are derived from chronic aquatic
life criteria (or toxic effect levels) and human health criteria (or toxic effect levels) established
for the consumption offish.
4.4.4
Baseline Pollutant Loadings Results
Table 4-9 summarizes the pollutant loads estimated for the Guaynabo WTP
POCs, in both Ibs/year and TWPE/yr.
4-10
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Table 4-9. Estimated Baseline Loadings for POCs
Pollutant
Ammonia (Total Ammonia and Ammonium)
Potassium
Silicon
Sodium
TDS
Total Aluminum
Total Barium
Total Calcium
Total Chromium
Total Copper
Total Iron
Total Magnesium
Total Manganese
Total Mercury
Total Molybdenum
Total Nickel
Total Phosphorus
Total Residual Chlorine
Total Strontium
Total Titanium
Total Vanadium
Total Zinc, Total (As Zn)
Total Zirconium
TSS
Total
Baseline Load (Ib/yr)
1,170
1.03
3.84
90.4
823,000
17,400
0.0687
13
0.051
232 (DMR)
0.0616 (Empirical)
5.79
2.40
2,650 (DMR)
0.2854 (Empirical)
0.146 (DMR)
0.121 (Empirical)
0.137
0.149
5,350 (DMR)
32.7 (Empirical)
6,870
0.051
0.230
0.247
198 (DMR)
2.70 (Empirical)
0.085
1.42 million
2.28 million0
TWF
0.00135
0.00105
a
5.49E-06
b
0.0647
0.00199
0.000028
0.0756
0.635
0.0056
0.000866
0.0704
117
0.201
0.109
a
0.509
2.22E-05
0.029
0.035
0.0469
0.544
b
Baseline Load (TWPE/yr)
1.58
0.00108
a
0.000496
b
1,130
0.000137
0.000364
0.00386
147 (DMR)
0.0324
0.00208
187 (DMR)
17.1 (DMR)
0.0275
0.0162
a
3,500
0.00000113
0.00667
0.00865
9.29 (DMR)
0.0462
b
4992 c
a - EPA has not yet calculated TWFs for Silicon and Total Phosphorus.
b - TWFs do not apply to conventional pollutants or bulk parameters, including TSS and TDS.
c - Totals are calculated using DMR estimates.
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5.0
TREATMENT TECHNOLOGY OPTIONS FOR THE GUAYNABO WTP
This section describes the technology options for the Guaynabo WTP. EPA
evaluated technology options for the following technology-based controls under the CWA: Best
Practicable Control Technology Currently Available, Best Conventional Pollutant Control
Technology, and Best Available Technology Economically Achievable. These controls are
described below and listed in Table 5-1.
Best Practicable Control Technology Currently Available (BPT) - The
first level of technology-based standards generally based on the average of
the best existing performance facilities within an industrial category or
sub category.
Best Conventional Pollutant Control Technology (BCT) - Technology-
based standard for the discharge from existing industrial point sources of
conventional pollutants including biochemical oxygen demand (BOD),
TSS, fecal coliform, pH, and oil & grease.
Best Available Technology Economically Achievable (BAT) - The most
appropriate means available on a national basis for controlling the direct
discharge of toxic and nonconventional pollutants to navigable waters.
BAT effluent limits represent the best existing performance of treatment
technologies that are economically achievable within an industrial point
source category or subcategory.
New Source Performance Standards (NSPS) - Technology-based
standards for facilities that qualify as new sources under 40 CFR §122.2
and 40 CFR §122.29. Because the Guaynabo WTP is an existing facility,
NSPS does not apply.
Table 5-1. Summary of CWA Technology Levels of Control
Type of Site Regulated
Existing Source Direct Dischargers
New Source Direct Dischargers
Priority Toxic Pollutants
Nonconventional Pollutants
Conventional Pollutants
BPT
X
X
X
X
BCT
X
X
BAT
X
X
X
NSPS
X
X
X
X
5.1
Treatment Technology Options
In the DWT industry, EPA collected data on residuals treatment technologies by
completing site visits to water treatment plants and conducting literature reviews. Based on these
data, residuals management in the DWT industry focuses on solids removal, dechlorination, and
zero discharge of residuals achieved through recirculation of residuals supernatant.
The current Guaynabo WTP residuals management consists of equalization,
gravity thickening of sludge, discharge of supernatant, and vacuum-assisted sludge bed drying,
5-1
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as discussed in Section 3. Although the Guaynabo WTP manages its residuals, DMR data and
permit application data suggest that the facility experiences spikes in residuals discharge during
sedimentation tank drainage. The spikes in turbidity in DMR data and permit application data
suggest that the facility's residuals management capacity is not sufficient to handle the days of
maximum residuals discharge.
As further support of the need for additional residuals management capacity, the
Guaynabo WTP produces more drinking water than its original design capacity. The Guaynabo
WTP reported its design capacity as 26 MGD; however, the facility produces 30 MGD of
drinking water (PRASA, 2005; PRASA, 2007).
As a result, the technologies considered are Optimization of Residuals
Management with Dechlorination (Technology 1), and Optimization of Residuals Management
with Zero Discharge (Technology 2). Table 5-2 lists the technology options considered for the
two applicable levels of control. The remainder of Section 5 describes the technology options in
greater detail.
Table 5-2. Technology Options Considered
Technology Description
Technology 1: Optimization of Residuals Management + Dechlorination
Technology 2: Optimization of Residuals Management + Zero Discharge Via Complete
Recycle
Regulatory Level
of Control
BPT
BPT
5.2 Technology 1: Optimization of Residuals Management + Dechlorination
Technology 1 provides for additional equalization capacity for the Guaynabo
WTP sludge treatment system to optimize residuals management. Currently, the Guaynabo WTP
peak residuals flow is 3.116 MGD (ERG, 2006; PRASA, 2007). The daily backwash is 1.616
MGD. There are five sedimentation tanks in operation: three at 750,000 gallons, one at 800,000
gallons, and one at 1.5 million gallons capacity (Sedimentation Tank #5). The capacity of the
current equalization tank is 228,960 gallons (25ft x 25ft x 49ft).
Technology 1 optimizes residuals management and increases solids removal. The
Guaynabo WTP operates continuous sludge removal from the sedimentation tanks; however, the
manufacturer of the continuous removal system recommends tank cleaning every three to six
months. Spikes in solids and other pollutant concentration (effluent outliers) correspond to
sedimentation tank cleaning (particularly cleaning of the largest tankSedimentation Tank #5)
(PRASA, 2007).
Dechlorination provides for removal of chlorine using chemical addition. In the
water treatment industry, dechlorination is often accomplished through addition of sulfur
chemicals, including sulfur dioxide, sodium sulfite, sodium bisulfite, sodium metabisulfite, and
sodium thiosulfite. For dechlorination of Guaynabo WTP effluent, Technology 1 uses sodium
metabisulfite to reduce free chlorine to chloride (U.S. EPA, 2000).
5-2
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5.2.1
Technology 1 Costs
Technology 1 includes costs from both Optimization of Residuals Management
and Dechlorination.
The Optimization of Residuals Management portion of Technology 1 assumes
sedimentation tank cleanings are staggered over each quarter, as is currently practiced.
Additional equalization capacity of 1.5 million gallons and metering the largest cleaning residual
(sedimentation tank #5) over 15 days to the thickener will prevent overloading and eliminate
effluent outliers.
To provide for the additional 1.5 million gallons of equalization capacity needed,
EPA developed costs for an equalization basin, a pump house, and a pumping system. Each cost
component is provided in detail in Appendix D. Based on site information documented in EPA's
August 2006 site visit (ERG, 2006), EPA made assumptions regarding concrete construction for
the equalization tank and available land (e.g., excavation in clay-type soil and possible hill-side
construction). Costs include the following:
Indirect costs, including permits, scheduling, performance bonds,
insurance, contractor markup, and overhead and profit;
Labor (periodic equalization tank cleaning); and
Electricity.
Table 5-3 summarizes the costs to implement Optimization of Residuals
Management, both capital and annual operations and maintenance (O&M).
Table 5-3. Costs to Implement Optimization of Residuals Management
Technology Components
Equalization Tank
Pump House
Pumping System
Labor
Electricity
Additional Sludge Removal
Type of Cost
Capital
Capital
Capital
Annual
Annual
Annual
Total Capital Cost
Total Annual Cost
Total Annualized Costs
Costs ($2005)
$1,020,000
$17,500
$104,000
$537
$1,840
$171,000 b
$1,140,000
$173,380
$307,000 a
a - U.S. EPA, 1993. Total annualized costs are equal to the sum of annual O&M costs plus the annualized capital
costs. Annualized capital costs are calculated based on a 20-year operating life and an interest rate of 10 percent.
The capital recovery factor for a 20-year operation life and 10 percent interest rate is 0.1175. Total annualized costs
are thus $1,140,000 x 0.1175 + $173,380, or $307,000.
b - See Section 5.2.4 for additional sludge removal costs.
Dechlorination using sodium metabisulfite is well established in the drinking
water treatment industry. Standard references dictate that 1.34 pounds of sodium metabisulfite
5-3
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are required to reduce 1 pound of free chlorine, and the reaction is complete within 1 to 5
minutes (U.S. EPA, 2000). As a result, EPA estimated costs for the following:
An oxidation reduction potential (ORP) detector: a high-end controller
that minimizes the use of chemicals, prevents overdosing, and keeps
chlorine concentrations near zero;
A chemical feed system: chemical storage tanks, pumps, an injector, a
mixer, and plumbing;
Chemical supply (sodium metabisulfite);
Operating and maintenance labor; and
Electricity.
Table 5-4 lists the components considered in estimating costs for this technology.
Appendix E contains the details of the dechlorination costing module.
Table 5-4. Cost Estimate Components of Dechlorination
Technology
Dechlorination
Item(s)
ORP Detector and Chemical Feed System
Electricity
Chemical Costs
Operating Labor
Maintenance Labor
Waste Disposal
Type of Cost
Capital
Annual
Annual
Annual
Annual
Annual
Total Capital
Total Annual
Total Annualized
Cost ($2005)
$57,600
$930
$16,400
$12,300
$1,230
$0
$57,600
$30,860
$37,600a
a - U.S. EPA, 1993. Total annualized costs are equal to the sum of annual costs plus the annualized capital costs.
Annualized capital costs are calculated based on a 20-year operating life and an interest rate of 10 percent. The
capital recovery factor for a 20-year operation life and 10 percent interest rate is 0.1175. Total annualized costs are
thus $57,600 x 0.1175 + $30,860, or $37,600.
Table 5-5 summarizes the Technology 1 costs and provides a total annualized
cost.
5-4
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Table 5-5. Cost Estimate Components of Technology 1:
Optimization of Residuals Management + Dechlorination
Technology
Optimization of
Residuals
Management
Dechlorination
Type of Cost
Total Capital
Total Annual
Total Annualized
Total Capital
Total Annual
Total Annualized
Technology 1 (Optimization of Residuals Management + Dechlorination) Total
Annualized
Cost ($2005)
$1,140,000
$173,380
$307,000
$57,600
$30,860
$37,600
$345,000
5.2.2
Technology 1 Pollutant Removals
By allowing for increased equalization, Optimization of Residuals Management is
expected to eliminate spikes of high solids content in effluent wastewater. EPA used monthly
monitoring data available from DMRs to evaluate spikes in solids content; however, daily
monitoring data would provide a more accurate estimate of baseline solids loads and removals.
Table 5-6 shows the 2003 to 2005 monthly turbidity data for the Guaynabo WTP,
correlated to TSS. On four occasions, the monitoring data show effluent concentrations of TSS
of more than 2,000 mg/L. The mean TSS concentration, including the spikes in effluent quality,
is 390 mg/L. Without the spikes in effluent quality, the mean TSS concentration is 14.46 mg/L.
Using these data, EPA estimates that Optimization of Residuals Management would lower the
mean effluent solids concentration by an additional 96 percent. In terms of removals, EPA
estimates that Optimization of Residuals Management would remove 96 percent of the solids
load, and that the annual TSS load would decrease from 1.42 million Ibs/yr to 60,000 Ibs/yr. This
would result in a pollutant load reduction of approximately 1.36 million Ibs/yr of TSS.
Table 5-6. Estimated Solids Removals for Optimization of Residuals Management
Year
2003
2003
2003
2003
2003
2003
2003
2003
2003
2003
2003
2004
2004
Month
1
2
o
J
4
5
6
7
9
10
11
12
1
2
Turbidity Level
(NTU)
1,900
22
11
11
1,600
3.2
0.6
o o
J.J
2,800
0.9
4.8
2.6
1.1
Baseline TSS Concentration a
(mg/L)
2,850
33
17
17
2,400
5
1
5
4,200
1
7
4
2
5-5
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Table 5-6. Estimated Solids Removals for Optimization of Residuals Management
Year
2004
2004
2004
2004
2004
2004
2004
2004
2004
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
Month
3
4
5
6
7
9
10
11
12
1
2
3
4
5
6
7
8
9
10
11
12
Turbidity Level
(NTU)
0.55
1.4
3.4
3.3
2.1
b
b
b
2.8
11
12
0.7
4.8
1.1
2.4
4
1.6
16
1,500
2.6
130
Mean TSS Concentration
Mean TSS Concentration, Excluding TSS > 1,500 mg/L
% Difference
Baseline TSS Concentration a
(mg/L)
1
2
5
5
3
b
b
b
4
17
18
1
7
2
4
6
2
24
2,250
4
195
390
14.46
96%
Source: Guaynabo WTP DMRs, 2003 to 2005.
a - TSS concentration (mg/L) is assumed to be 1.5 x Turbidity (NTU) (ASCE, 1996).
b - The facility did not report this analyte for the month.
Also, Optimization of Residuals Management would improve the removal of
pollutants that sorb to solids. For this analysis, EPA assumed that the 96 percent reduction in
TSS will also result in a 96 percent removal of metals that sorb to solids. Due to a lack of
available data, EPA did not estimate incidental removals from pollutants that are not expected to
significantly sorb to solids. Table 5-7 lists estimates of pollutant loadings and removals from
Optimization of Residuals Management. In addition to the 1.36 million Ibs of TSS, EPA
estimates that Optimization of Residuals Management would remove 19,720 pounds of metals
(1,556 toxic-weighted pound equivalents) each year.
5-6
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Table 5-7. Pollutant Removals for Optimization of Residuals Management
Pollutant
Ammonia (Total Ammonia
And Ammonium)
Potassium
Silicon
Sodium
TDS
Total Aluminum
Total Arsenic °
Total Barium
Total Calcium
Total Chromium
Total Copper
Total Iron
Total Lead c
Total Magnesium
Total Manganese
Total Mercury
Total Molybdenum
Total Nickel
Total Phosphorus
Total Residual Chlorine
Total Strontium
Total Titanium
Total Vanadium
Total Zinc, Total (As Zn)
Total Zirconium
TSS
Removed by
Technology
1?
a
a
a
a
a
/
s
/
/
s
/
s
/
s
/
s
s
/
a
a
s
/
s
/
s
s
TWF
0.00135
0.00105
b
5.49E-06
b
0.0647
4.04
0.00199
0.000028
0.0756
0.635
0.0056
2.24
0.000866
0.0704
117
0.201
0.109
b
0.509
2.22E-05
0.029
0.035
0.0469
0.544
b
Total
Baseline Pollutant
Loads
Lbs/Yr
1,170
1.03
3.84
90.4
823,000
17,400
16.1
0.0687
13
0.051
232
5.79
31.8
2.4
2,650
0.146
0.137
0.149
5,350
6,870
0.051
0.23
0.247
198
0.085
1,420,000
2,280,000
TWPE/Yr
1.58
0.00108
0.000496
1,130
65.0
0.000137
0.000364
0.00386
147
0.0324
71.23
0.00208
187
17.1
0.0275
0.0162
3,500
1.13E-06
0.00667
0.00865
9.29
0.0462
b
5,130
Pollutant Removals
Lbs/Yr
a
a
a
a
a
16,700
15.5
0.0066
12.5
0.049
223
5.60
30.5
2.30
2,540
0.140
0.132
0.143
a
a
0.0490
0.221
0.237
190
0.0816
1,360,000
1,380,000
TWPE/Yr
a
a
a
a
a
1080
62.4
0.000132
0.00035
0.00370
141
0.0311
68.4
0.00200
179
16.4
0.026
0.0156
a
a
0.00000109
0.00640
0.00830
8.91
0.0444
b
1,560
a - With the exception of TDS, EPA expects some removals of these pollutants; however, no data are available to
quantify removals. EPA did not estimate removals for these pollutants.
b - TWFs are calculated for nonconventional and toxic pollutants, not for TSS or TDS. At the time of this BPJ
analysis, EPA had not yet developed TWFs for silicon or phosphorus.
c - Incidental pollutant removals (not an impurity in GC-850). Baseline pollutant loads calculated using DMR data
(see Appendix B).
Technology 1 also includes dechlorination. By using the Siemens ORP detector,
the facility would be able to remove chlorine concentrations to levels below detection limits.
EPA expects the dechlorination portion of Technology 1 to remove chlorine at 6,870 Ibs/yr
(3,500 Ib-eq/yr). The total TWPE removed by Technology 1 is 5,060 Ib-eq/yr.
5-7
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5.2.3
Environmental Benefits
This section discusses the possible benefits achieved by Technology 1 in reducing
pollutant discharges from the Guaynabo WTP to the environment. Technology 1 is expected to
reduce metals, solids, and chlorine discharges.
5.2.3.1
Metals
There are benefits to removing metals due to their potential to cause adverse
impacts on the aquatic environment. The potential impacts of the discharged metals are diverse.
Metals can bioaccumulate in sediments, plants, and animal tissues. The effects of metals can
include reduced survivability, growth, and reproductive success in some animal species and plant
growth inhibition. Even when the concentrations of metals are not high enough for acute toxicity,
the cumulative effect of the concentration of these metals over time and the buildup in sediment
and animal tissue may be of concern, although the specific effects of these concentrations on
submerged aquatic vegetation and other biota are not well understood.
From the Guaynabo WTP DMR data, EPA can estimate the current
concentrations of metals being discharged to the Bayamon River. Table 5-8 lists concentrations
of metals in the Guaynabo WTP effluent, where DMR data are available. Some of the metals
listed in Table 5-8 are not pollutants of concern, because they result from natural sources, not
from chemical addition at the Guaynabo WTP. However, Technology 1 would still reduce the
concentration of these metals in the effluent.
Table 5-8. Metals Concentrations in the Guaynabo WTP Effluent, from DMR Data
Pollutant Name
in DMR
Total Arsenic
Total Copper
Total Fluoride
Total Lead
Total Manganese
Total Mercury
Total Phosphorus
Pollutant of Concern?
No. Occurs naturally in some surface water. Not
present in treatment chemicals added by Guaynabo
WTP.
Yes. Occurs naturally in some surface water. Also
treatment chemical addition (treatment chemical
impurities).
No. Occurs naturally in some surface water.
No. Occurs naturally in some surface water. Not
present in treatment chemicals added by Guaynabo
WTP.
Yes. Occurs naturally in some surface water. Also
treatment chemical addition (treatment chemical
impurities).
Yes. Occurs naturally in some surface water. Also
treatment chemical addition (treatment chemical
impurities).
Yes. Occurs naturally in some surface water. Also
treatment chemical addition (treatment chemical
impurities).
Concentration (mg/L)
Minimum
ND
ND
0.025
ND
0.0039
ND
ND
Maximum
0.043
0.759
0.19
0.0843
11.7
0.000168
12.8
Average
0.00354
0.0602
0.0886
0.00729
0.794
0.0000301
0.935
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Table 5-8. Metals Concentrations in the Guaynabo WTP Effluent, from DMR Data
Pollutant Name
in DMR
Total Zinc
Pollutant of Concern?
Yes. Treatment chemical addition (treatment chemical
impurities).
Concentration (mg/L)
Minimum
ND
Maximum
0.664
Average
0.0543
Source: Guaynabo WTP DMR data (Guaynabo WTP, 2003 to 2005).
For some of the metals listed in Table 5-8, EPA collected the following data on
environmental impacts:
Copper. Copper is a naturally-occurring element that is usually present in
freshwaters. Both plants and animals depend upon copper in its role as a
micronutrient, however, it can be toxic at high concentrations to fish,
amphibians, invertebrates, birds, and mammals. Copper can
bioconcentrate in the organs offish and mollusks. It can cause death in
amphibians as well as other adverse effects in tadpoles and embryos. Even
at very low concentrations, copper can cause death and reduce
photosynthesis and growth in algae and cyanobacteria.
Copper toxicity in birds can cause reductions in reproductive success (due
to lower egg production), reductions in growth, and developmental
defects. Toxic effects in mammals include fetal mortality and effects on
organs, including the brain, liver, and kidneys.
Copper can bioaccumulate in plants, though it does not biomagnify. The
toxicity of copper increases with decreasing water hardness and dissolved
oxygen concentrations, and decreases with high levels of dissolved
organic compounds and suspended solids. Copper can adsorb to organic
matter, clay, and carbonates, which reduces its bioavailability.
Mercury. Mercury is toxic to organisms and can cause mutations, cancers,
and other serious effects. It bioaccumulates and biomagnifies in
organisms. Upper trophic level mammals, birds, and fish are especially
vulnerable to mercury because of the degree to which it can biomagnify.
Mercury has been shown to biomagnify in fish to concentrations up to
100,000 times ambient water concentrations.
There is a wide range of effects caused by mercury. Acute exposures can
target the central nervous systems and kidneys in mammals, birds, and
fish. Even at low concentrations (well below 1 ppb), mercury can cause
brain lesions, changes in feeding habits and motor coordination, and other
behavioral abnormalities in fish. The Guaynabo WTP effluent contains
mercury ranging from levels below detection to 0.0301 ppb. Fish also
experience reduced reproduction and growth at relatively low mercury
concentrations. Mercury can also affect metamorphosis in frogs. Toxic
effects to birds include reduced fertility, reduced survivability and growth
5-9
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in young, and changes in mating behavior. Mammals can experience a
variety of neurological and reproductive effects.
Zinc. Zinc can be toxic to organisms, with elevated zinc concentrations
reducing growth, survival, and reproduction in aquatic plants and animals
and terrestrial invertebrates. Toxic effects to birds include mortality,
reduced growth, and pancreatic degradation. In mammals, elevated
concentrations of zinc can cause reductions in reproduction as well as
cardiovascular, neurological, and developmental problems. Zinc can
bioaccumulate in fish.
The toxicity of zinc is affected by water hardness and pH, with high
toxicity related to lower hardness and higher pH.
In addition to those chemicals listed in Table 5-8 above, Technology 1 is expected
to remove metals that may be present in the Guaynabo WTP effluent, but have not been recorded
in DMR data. The specific effects of some additional metals are described in greater detail
below.
Aluminum. In high concentrations, aluminum is toxic to aquatic
freshwater organisms, including fish and invertebrates. It can cause
osmoregulatory failure in both fish and invertebrates. Fish appear to be
more sensitive to aluminum than invertebrates, and are particularly
affected by aluminum in acidic waters. Plants can accumulate aluminum,
which can adversely affect root systems. The aluminum in plants and
macroinvertebrates can be taken up by and cause detrimental effects in
animals. For example, the consumption of these plants and invertebrates
may limit reproductive success in birds.
Barium. The effects of barium on animals can include gastrointestinal
distress, reproductive impairment, muscular paralysis, and cardiovascular
effects. Fish and aquatic organisms can accumulate barium.
Calcium. Calcium is a dietary requirement for most organisms. Since it
partially determines the hardness of water, it can affect the toxicity of
some metals, including copper, lead, and zinc. Water hardness has also
been shown to affect copper toxicity in studies conducted on aquatic
freshwater species. Calcium can be toxic to fish and amphibians. Elevated
concentrations of calcium have been shown to cause reductions in
reproductive success in some species.
Chromium. Chromium can cause many adverse effects in freshwater
aquatic organisms, including cancers and mutations. Most impacts are
caused by direct exposure. The effects of chromium on fish include
morphological changes, reduced resistance to disease, chromosomal
abnormalities, and reduced growth. Benthic macroinvertebrates can
experience reductions in growth, reproductive success, and survival, as
5-10
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well as irregular movement patterns. Chromium can also cause reduced
growth in duckweed and algae.
Chromium bioaccumulates in invertebrates, algae, and other aquatic
vegetation, however, it does not biomagnify in aquatic food webs. Most
chromium in water sorbs to settleable dirt particles, and very little
chromium dissolves in water.
Nickel. Nickel in very small concentrations is essential to growth and
reproduction in some species. At high concentrations, however, it is a
carcinogen and mutagen and can have acute and chronic toxic effects on
aquatic organisms. Toxic effects of nickel include reductions in
survivorship and growth and tissue damage. Mollusks and crustaceans
appear to be more sensitive to nickel than other organisms. Nickel toxicity
is impacted by water hardness, with softer water leading to higher toxicity.
Nickel does not appear to bioaccumulate.
5.2.3.2 TSS/Turbidity
Turbidity and total suspended solids (TSS) are present in the Guaynabo WTP
effluent. The Guaynabo WTP DMR data provide turbidity measurements, and EPA estimated
TSS concentrations from turbidity. Solids indicate the amount of mineral and organic solids that
are suspended in water. Turbidity measures the ability of light to penetrate the water, as more
suspended solids lead to reduced light penetration, while TSS measures the actual weight of the
suspended solids. From DMR data, turbidity ranged from 0.55 to 2,800 NTUs; TSS was
estimated to range from 0.80 to 4,200 mg/L.
The impacts of TSS and turbidity are numerous. Turbidity can impact water
quality, habitat, and temperature. Suspended solids can smother habitat that is essential to
organisms, such as the interstitial spaces in which some animals live, and suffocate larvae, fish
eggs, clams, mussels, as well as other invertebrates. The effects of turbidity and the associated
fine paniculate material on fish include damage to gills by abrasion and clogging, which reduces
the ability to breathe dissolved oxygen, decreased resistance to disease, reduced egg
development, and reduced foraging success.
Since turbidity scatters light, an increase in turbidity can reduce light penetration
and thus the ability of submerged aquatic vegetation to receive light. In turn, photosynthesis is
reduced. This can result in reduced growth of submerged plants, which are a food source for
aquatic animals. Decreased photosynthesis can result in lowered releases of oxygen to the water,
which reduces the amount of available oxygen for fish and other organisms.
Increased suspended solids and the resulting increases in turbidity can cause
surface water temperatures to increase, since the particles reflect radiant energy and absorb heat
from sunlight. This increase in temperature can reduce oxygen in water, since oxygen dissolves
more readily in colder water, and can lead to thermal stratification.
5-11
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5.2.3.3 Total Residual Chlorine
There are benefits to removing total residual chlorine (TRC) due to its adverse
effects on the aquatic environment. From Guaynabo WTP DMR data, TRC ranged from 0.2 to
1.45 mg/L. Even at low concentrations, residual chlorine is toxic to many kinds of aquatic life.
Studies have demonstrated a variety of lethal and sub lethal effects in fish at low concentrations.
Toxic effects on fish include mortality, reproductive and hatching problems, damages to the
structure of the gills and to the nervous system, a reduction in the ability of blood to transport
oxygen, and increased gill permeability, which may result in increased accumulation of other
toxins. Abnormalities in larval oyster shell development have been shown to occur even at low
chlorine concentrations. Total residual chlorine has also been shown to reduce the colonization
of certain species of aquatic macroinvertebrates.
Effects on mammals and reptiles include reduced reproductive success, which has
been shown to occur in minks and otters, and embryo abnormalities and death in snapping
turtles. Aquatic plants are affected by TRC in a number of ways, including reduced growth and
survival and repressed physiological processes.
The toxicity of chlorine increases as pH decreases and when it is combined by
high concentrations of ammonia, metals, surfactants and other compounds, and high biological
oxygen demand.
5.2.4 Non-water Quality Environmental Impacts
Technology 1 would require additional electricityapproximately 80,000 kW-
hours annually, from Optimization of Residuals Management6 and Dechlorination7. EPA does
not expect a change in air emissions from implementation of Technology 1. The improved solids
removal associated with this technology would result in increased sludge volume.
EPA estimated the amount of sludge removed and the cost for sludge removal,
based on the removal of approximately 1.36 million Ibs of TSS annually. EPA assumed:
14% solids content as hauled;
Resulting density of 1,830 lb/yd3; and
$625 per additional container of sludge hauled.
EPA applied these assumptions in the following equations:
[1.4(106) Ibs TSS/yr] - [14% solids] - [1,830 lb/yd3] = 5,460 yd3 of Additional Sludge/yr
[5,460 yd3 additional sludge] + [20 yd3/container] = 274 Containers/yr
[$625/additional containers hauled] x [274 additional containers] = $171,000/yr ($2005)
6 kW = 6 HP x 745.6 watts/hp x lkW/1,000 watts x 24 hr/day x 15 days/sedimentation tank cleaning per quarter x 5
sedimentation tanks x 4 quarters/yr= 32,000 kW.
7 Approximately 48,200 kW-hours annually, see Appendix E for additional electricity for dechlorination and Section
5.2.1 for additional electricity for Optimization of Residuals Management.
5-12
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EPA estimates that Optimization of Residuals Management will generate an
additional 5,460 yd3 of sludge annually. The Guaynabo WTP will incur an additional cost of
$171,000 annually ($2005) for sludge disposal. These disposal costs are included in the
incremental compliance cost of Optimization of Residuals Management (see Section 5.2.1).
5.3 Technology 2: Optimization of Residuals Management + Zero Discharge Via
Complete Recycle
In the drinking water treatment industry, plants can achieve zero discharge by
recycling wastewater to the head of the raw water treatment system. In addition, plants may
identify additional (non-potable) uses for the wastewater at their facilities or customer facilities.
Non-potable uses for the wastewater include industrial purposes (e.g., cooling water),
agricultural purposes (e.g., land irrigation), and groundwater recharge. This discussion focuses
on the recirculation of wastewater; however, if recirculation is not possible at the facility, it may
identify non-potable uses for wastewater as an alternative pollution prevention practice.
In its permit application diagram, the Guaynabo WTP shows the possibility of
recirculation (or recycling) of gravity thickener supernatant to the head of the raw water
treatment system (raw water mixing chamber). However, recycling does not currently occur at
the plant. Based on the recycling piping shown in the permit application diagram, EPA assumed
the facility had necessary piping and pumps in place for recirculation. EPA also assumed the
Guaynabo WTP would incur the costs estimated for Optimization of Residuals Management in
addition to costs that would be required to achieve zero discharge.
DWT plants must meet EPA and state (or territory) requirements before recycling
wastewater through the raw water treatment system. EPA issued the Filter Backwash Recycling
Rule (FBRR) to reduce or prevent adverse impacts on the performance of DWT plants and to
prevent microbes (e.g., Cryptosporidium) from passing through the raw treatment system and
into the finished drinking water. Although the rule includes "filter backwash" in the title, any
recycled stream must meet the rule requirements. To minimize the risk of process upsets due to
large recycle volumes and pass through of microbes (contained in high concentration in the
waste streams), FBRR requires all recycle streams to be returned at a point where the stream will
be treated through all of the plant's existing conventional or direct filtration processes (i.e.,
o
coagulation, flocculation, and filtration) . See 40 CFR 141.2 for complete definition of
conventional and direct filtration systems. These types of treatment systems can achieve 99
percent removal of Cryptosporidium (U.S. EPA, 2002).
In addition to meeting EPA requirements, facilities in Puerto Rico that intend to
recycle must also notify and meet requirements of the Puerto Rico Department of Health
(PRDOH). In addition to notification and recordkeeping (similar to the FBRR), PRDOH also
requires the following to receive an operation endorsement (PRDOH, 2004):
The WTP must disinfect the wastewater stream prior to entering the
sludge thickener.
! Or state-approved location in the process.
5-13
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The WTP must operate sludge treatment that includes a dewatering
process, holding tank with enough capacity to contain water sludge and
prevent process upsets at the sludge treatment system, sampling location
for the recycle stream, and flow meter on the recycle stream.
The recycling stream cannot be more than 20 percent of the design flow
capacity.
The WTP must perform additional analytical monitoring of the recycle
stream and combined entry-to-point of distribution stream for 15 days.
After 15-day sampling, the PRDOH determines whether recycling will be
permitted.
The WTP must perform additional routine analytical monitoring of the
recycle stream.
The WTP must develop a contingency plan to dispose of the wastewater
due to negative quality effects on the finished drinking water, malfunction
of the sludge treatment system, or operational and maintenance deficiency
found at the sludge treatment process during owner/operator or PRDOH
inspection.
Annual compliance monitoring specified by PRDOH (plant by plant basis)
to renew operation endorsement.
As listed above, PRDOH requires plants to perform an initial, consecutive 15-day
sample event before granting permission to allow recycling. Monitoring requirements of the
recycle stream and entry-to-point of distribution streams include the following:
Perform bacteriology analysis (coliform) once daily;
Monitor for organics and inorganics on the 15* day of operation (single
analysis); and
Monitor daily (or as frequently as performed at the raw water treatment
system) for turbidity, pH, daily flow rate, and free chlorine.
Once PRDOH approves the recycling of wastewater, plants must continue to
monitor the recycle stream daily (or as frequently as performed at the raw water treatment
system) for turbidity, pH, daily flow rate, and free chlorine.
5.3.1 Technology 2 Costs
The costs to recycle wastewater at Puerto Rico drinking water treatment plants
include the following:
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Capital cost to design and build recycle system (assumed already in place
at the Guaynabo WTP);
Capital and operating costs to design, build, and maintain sludge treatment
system. (Guaynabo WTP currently has sludge treatment in place. Costs for
the BPJ analysis include additional equalization capacity represented by
Optimization of Residuals Management);
Reporting and recordkeeping costs (to comply with EPA and state
requirements);
Additional disinfection required by PRDOH;
Additional chemical and microbiological monitoring; and
Development of a contingency plan.
5.3.1.1 Reporting and Recordkeeping Costs
EPA's Economic Analysis for the FBRR estimates the reporting and
recordkeeping costs per system range from $125 to $273 (2005 dollars) (U.S. EPA, 2000).9 For
this analysis, EPA assumed approximately $200 per year (for the Guaynabo WTP to maintain
additional, recycling-related records for both EPA and PRDOH.
The facility may save (1) discharge monitoring and record-keeping costs, (2)
NPDES compliance assessment reporting costs, and (3) NPDES permit application costs. The
annual savings from discharge monitoring and record-keeping costs is approximately $203; the
savings associated with compliance assessment reported would be approximately $1,142; and,
the NPDES permit application savings would be approximately $181 per year. These savings
total $1,527 per year. However, the facility may need to maintain an emergency discharge outfall
and NPDES permit.
5.3.1.2 Additional Disinfection Costs
The Guaynabo WTP would incur additional disinfection costs. The facility does
not currently add chlorine to its wastewater stream prior to the gravity thickener, which is a
requirement of the PRDOH for recirculation. To estimate the additional disinfection costs, EPA
made the following assumptions:
The average flow rate requiring disinfection prior to entering the gravity
thickener would be 1.76 MGD, based on the 2005 average DMR flow (see
Appendix B).
The Guaynabo WTP would use gaseous chlorine for the required
additional disinfection. Although other forms of disinfection are available,
9 In the Filter Backwash Recycling Rule, recordkeeping costs were provided in 1999 dollars ($102 to $222). Using
Construction Cost Index values, costs in 2005 dollars are: ($102 to $222) x 7446 (2005 Index)/6059 (2006 Index),
or $125 to $273 (ENR, 2006).
5-15
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the facility already uses gaseous chlorine and has already implemented
safety, reporting, and storage requirements.
To disinfect the wastewater stream, the Guaynabo WTP will need to add
approximately 5,300 Ibs of gaseous chlorine annually to maintain a 1
mg/L free chlorine concentration.
The cost for additional disinfection would include a $3,300 capital cost for
a pump and chlorinator and annual costs of $5,000 for chlorine.10
5.3.1.3 Chemical and Microbiological Monitoring Costs
PRDOH requires additional monitoring of two streams: 1) the recycle stream, and
2) entry-to-point of distribution stream. EPA estimated additional analytical monitoring costs for
the Guaynabo WTP including initial 15-day monitoring of both streams, daily monitoring
requirements of the recycle stream, and annual compliance monitoring (assumed to be the same
as the 15-day monitoring for both streams).
The PRDOH requires a one-day chemical analysis of "organics/inorganics." EPA
assumed the organic/inorganic parameters required would include those currently monitored by
the facility, Cryptosporidium/Giardia (due to health concerns), and suggested water quality
parameters for the recycle stream as listed in Management of'Water Plant Residuals (ASCE,
1996). Table 5-9 lists these parameters and includes the estimated analytical monitoring costs.
In some cases, the Guaynabo WTP already monitored for a parameter, and the
parameter was measured using equipment on site. The Guaynabo WTP could use flow meters,
pH meters, chlorine meters and/or colorimetric chlorine papers, Imhoff cones (for settleable
solids), turbidimeters (for turbidity), and particle counters, instead of paying for off-site
laboratory analysis. For these parameters, EPA assumed no additional analytical costs; however,
EPA assumed additional costs for labor were incurred. For the 15-day monitoring, EPA assumed
an additional two hours of labor were required daily, for a one-time need for 30 hours additional
labor ($500).u For the daily monitoring, EPA assumed one additional hour per week, for a total
of 52 hours additional labor annually ($850).u
10 See Appendix F.
11 Labor rate of $16.79 determined from Bureau of Labor Statistics, 2005.
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Table 5-9. Analytical Monitoring Costs for the Guaynabo WTP for Recycling of
Wastewater Back to the Raw Water Treatment System, in 2005 Dollars
Analyte
Method Number
Number of
Samples
Cost per
Sample
(dollars, $)
Cost for
Analyte
(dollars, $)
15-day Monitoring (Initial and Annual Compliance Costs) - Two Streams
Flow rate b
Free chlorine
PHb
Turbidity b
Flow monitor
SM 4500-C1~
Daily grab sample
EPA180.1(et. al.)
15 x 2
streams
NA
NA
NA
NA
NA
NA
NA
NA
Microbiological Analysis
Conform b
Cryptosporidium/giardia a
922 1 A, B, C (total)
EPA 1693
15 x 2
streams
50.50
550.00
1,515.00
1,100.00
Organics
Volatile organic s
Semivolatile organics
EPA 1624C
EPA 1625C
1x2 streams
637.00
1,239.00
1,274.00
2,478.00
Classicals
Ammonia as Nitrogen b
Biochemical Oxygen Demand
(BOD5)b
Total Dissolved Solids (TDS)b
Total Organic Carbon (TOC)C
Total Phosphorus b
EPASM4500-NH3BorF
EPASM5210B
EPA 160.1
EPASM5310C
EPA 365.2, 365.4
1x2 streams
23.00
21.00
12.00
22.00
28.00
46.00
42.00
24.00
44.00
56.00
Inorganics - Metals
Arsenic (total inorganic) b
Copper (total) b
Lead (total) b
Manganese (total) b
Mercury (total) b
Zinc (total) b
Fluoride (total) b
EPA 200.7, 200.8, 200.9
(analysis for 27 metals)
EPA 300.0 (et. al.)
1x2 streams
307.00
23.00
614.00
46.00
Other Analytes
Color bAd
Dissolved Oxygenb
Haloacetic Acids °
Oil & Grease b
Phenolics, total recoverable b
Settleable Solids b
Sulfide, Dissolved13
Surfactants (MB AS) b
Temperature b'c'd
Total Residual Chlorine (TRC) b
Total trihalomethanes °
EPA110.1(et. al.)
EPA360.1(et. al.)
EPA 552.1
EPA 1664 (et. al.)
420.1
SM 2540 F
EPA 376.2 SM 4500-S2
EPA425.1(et. al.)
Daily grab sample
EPA330.1(et. al.)
EPA 502.2 (et al.)
1x2 streams
12.00
10.50
155.00
38.50
80
NA
26
29.00
NA
NA
80.00
24.00
21.00
310.00
77.00
160
NA
52
58.00
NA
NA
160.00
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Table 5-9. Analytical Monitoring Costs for the Guaynabo WTP for Recycling of
Wastewater Back to the Raw Water Treatment System, in 2005 Dollars
Analyte
Method Number
Number of
Samples
Cost per
Sample
(dollars, $)
Cost for
Analyte
(dollars, $)
Daily Monitoring of Recycle Stream
Flow rate b
Free chlorine
pHb,c,d
Turbidity v'd
Flow monitor
SM-4500 Cl"
Daily grab sample
EPA180.1(et. al.), SM
2130B
365
365
365
365
NA
NA
NA
NA
NA
NA
NA
NA
Daily Monitoring of Finished Water
Particle counts °
Turbidity c
Particle counter
EPA180.1(et. al.)
365
365
NA
NA
Total Annual Analytical Monitoring Costs for Technology 2 f
NA
NA
$8,100
Source: Costs estimated using EPA/EAD Laboratory costs.
a - EPA recommends sampling for this parameter more often than once per year.
b - Guaynabo WTP currently monitors for this parameter (or similar parameter) as part of its NPDES permit.
c - Suggested water quality parameters for recycle evaluation (ASCE, 1996).
d - Monitoring suggested more frequently (ASCE, 1996).
e - Labor rate of $16.79 determined from Bureau of Labor Statistics, 2005.
f- In the initial permit year, EPA assumed the 15-day sampling event occurs in lieu of the annual analytical
monitoring event (i.e., only a single sampling event each year).
NA - Not applicable. This analyte is measured on site using specific equipment, such as flow meters, pH meters,
chlorine meters and/or colorimetric papers, Imhoff cones (settleable solids), turbidimeters, and particle counters. The
facility already monitors for these parameters. EPA assumed additional costs for labor are incurred: 30 hours for the
15-day monitoring and 52 hours for daily monitoring.
5.3.1.4
Summary of Additional Costs Incurred for Technology 2
Table 5-10 lists the additional costs that EPA estimated for the Guaynabo WTP to
apply Technology 2. EPA assumed that the Zero Discharge costs would be in addition to those
estimated for the Optimization of Residuals Management portion of Technology 1, resulting in a
total annualized cost of $323,900 (in 2005 dollars).
Table 5-10. Cost Estimate Components of Technology 2: Optimization of Residuals
Management + Zero Discharge Via Complete Recycle
Item(s)
Additional disinfection: pump for chlorination prior to gravity thickener
Additional disinfection: chlorine costs for chlorination prior to gravity
thickener
Report and recordkeeping costs
Additional analytical monitoring costs
Labor costs for additional daily monitoring
Labor costs for one-time 15-day monitoring
Contingency plan a
Type of Cost
Capital
Annual
Annual
Annual
Annual
Capital
Capital
Cost ($2005)
$3,300
$5,000
$200
$8,100
$850
$500
$20,000
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Table 5-10. Cost Estimate Components of Technology 2: Optimization of Residuals
Management + Zero Discharge Via Complete Recycle
Item(s) Type of Cost
Total Capital Costs for Zero Discharge Via Complete Recycle
Total Annual Costs for Zero Discharge Via Complete Recycle
Total Annualized Costs for Zero Discharge Via Complete Recycle
Total Annualized Costs for Optimization of Residuals Management
Total Annualized Costs for Technology 2 (Optimization of Residuals Management +
Zero Discharge Via Complete Recycle)
Cost ($2005)
$23,800
$14,100
$16,900 a'b
$307,000
$323,900
a-U.S. EPA, 1993.
b - Total annual costs are equal to the sum of operation and maintenance costs plus the annualized capital costs.
Annualized capital costs are calculated based on a 20-year operating life and an interest rate of 10 percent. The
capital recovery factor for a 20-year operation life and 10 percent interest rate is 0.1175. Total annualized costs are
thus $23,800 x 0.1175 + $14,100, or $16,900 (U.S. EPA, 1993).
5.3.1.5 Feasibility of Technology 2 and Cost Estimate Limitations
The Technology 2 cost estimate includes the following limitations:
PRDOH may not allow recirculation based on concerns for the quality of
the finished drinking water as a result of recycling; and
PRDOH may require advanced treatment to ensure the quality of finished
water if the Guaynabo WTP recycles the thickener supernatant to the plant
headworks. This would result in costs not included in this cost estimate.
As addressed by EPA in the FBRR and PRDOH in its State Administrative
Order12, there are concerns with recycling wastewater back through the raw water treatment
system. The FBRR indicates that process upsets can occur due to the introduction of the
recycling stream. The Guaynabo WTP operates 18 filters, which should be able to handle
additional loadings. Water Treatment Residuals Engineering notes that operating less than 10
filters can result in significant hydraulic surges when recycling wastewater (ASCE, 1996).
However, process upsets are a concern at the Guaynabo WTP due to hydraulic
overloading from draining Sedimentation Tank #5. If the plant exceeds the maximum
contaminant level (MCL) in its drinking water, the plant may be required to discontinue recycle
practices (PRDOH, 2004).
The Guaynabo WTP has not currently received a recycling operation endorsement
from PRDOH. PRDOH has approved wastewater recycling at the Canovanas, Puerto Rico
treatment plant. However, PRDOH has also denied the operation endorsement at other Puerto
Rico facilities, such as the Superacueducto treatment plant.
12 The PRDOH State Administrative Order 2004-403-04 establishes requirements and procedures for endorsement
of public water system plans to return specific recycle flows back to the finished drinking water treatment process.
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5.3.2 Technology 2 Pollutant Removals
EPA assumed that the Technology 2 would result in a removal of all Guaynabo
pollutant loadings from the Bayamon River, with a minimum estimated annualized cost of
$323,900:
Approximately 2.27 million pounds pollutants (1.42 million Ibs TSS and
1.15 million Ibs of metals and other pollutants), and
Approximately 5,130 Ib-eq/yr (chlorine and metals).
5.3.3 Environmental Impacts
Technology 2 would remove all pollutant loadings, which would mean no
pollutants of concern would enter the Bayamon River. There is, however, a potential for
accumulation of disinfection by-products in the finished water, because with zero discharge and
constant recycling, some pollutants may accumulate in the finished water if there is no advanced
treatment in place.
5.3.4 Non-water Quality Environmental Impacts
Technology 2 would require additional power for pumping the water back to the
head of the raw water treatment system. Technology 2 would also generate additional sludge,
from the Optimization of Residuals Management portion of the technology (see Section 5.2.4).
The additional power costs for pumping the water back to the head of the raw water treatment
system are not included as part of this cost estimate. This cost estimate does include the costs to
handle the additional sludge from the Optimization of Residuals Management portion of the
technology (both power and sludge). EPA does not expect that Technology 2 would affect the
amount of air emissions generated.
5-20
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6.0
COMPARISON OF TECHNOLOGY OPTIONS
This section summarizes the technology option costs and pollutant removals and
identifies potential options for BPJ permit limits. EPA starts with the BPT technology control as
the first level of control for all pollutants. After identifying the BPT technology option, EPA
examines potential BCT and BAT technology options for controlling conventional and toxic and
nonconventional pollutants, respectively. This section starts with the potential BPT technology
options and then examines the BCT and BAT technology levels of control.
6.1
Best Practicable Control Technology Currently Available (BPT)
One measure of BPT BPJ factor is the cost and removal comparison ratio, which
is the average cost per pound of pollutant removed by a BPT technology option.13 EPA measures
the cost component as pre-tax total annualized costs. EPA used the cost and removal comparison
ratio in this BPJ analysis. Table 6-1 presents EPA's findings on these factors. The incremental
costs of compliance with these technology options in relation to the effluent reduction benefits
are within the range of other BPT technologies in promulgated effluent limitations guidelines.
Residuals disposal will not be limited when the facility has better solids control and produces
more residuals. That is, there will be enough disposal capacity for the incremental residuals
production.
Table 6-1. Summary of Factors for Technologies 1 and 2
Technology 1
Technology 2
1. The total cost of application of technology in relation to the effluent reduction benefits to be achieved
from such application [40 CFR 125.3(d)(l)(i)]
Technology Description
Total Annualized Compliance Costs
Annual Conventional Pollutant
Removals
Annual Pollutant Removals from
Nonconventional Pollutants
$/lb pollutant removed (2005)
Percent of Households with an
Affordability Impact
Optimization of Residuals
Treatment + Dechlorination
$345,000 ($2005)
1.36 Million IbsTSS
5,060 Ib-eqs metals and
chlorine
$0.25/lb removed
<0.29%
Optimization of Residuals Treatment +
Zero Discharge
$323,900 ($2005)
1.42 Million IbsTSS
5,130 Ib-eqs metals, chlorine, and other
nonconventional pollutants
$0.23/lb removed
<0.27%
Summary: The effluent reduction benefits for Technology 1 and Technology 2 are commensurate with the total
costs.
2. The age of equipment and facilities involved [40 CFR 125.3(d)(l)(ii)]
Summary: Age does not preclude facility from implementing Technologies 1 or 2.
3. The process employed [40 CFR 125.3(d)(l)(iii)]
Considered in technology selection and treatment technology costs.
13 See the following recent effluent guidelines rulemakings: Meat and Poultry Products (8 September 2004; 69 FR
54525), Concentrated Aquatic Animal Production (23 August 2004; 69 FR 51919), Metal Products and Machinery
(13 May 2003; 68 FR 25717), Transportation Equipment Cleaning (14 August 2000; 65 FR 49665), Waste
Combustors (27 January 2000; 65 FR 4370), Landfills (19 January 2000; 65 FR 3028).
6-1
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Table 6-1. Summary of Factors for Technologies 1 and 2
Technology 1
Technology 2
4. The engineering aspects of the application of various types of control techniques [40 CFR 125.3(d)(l)(iv)]
Considered in technology selection and treatment technology costs.
5. Process changes [40 CFR 125.3(d)(l)(v)]
Other than Technology 2, EPA did not identify a process change as a viable option for reducing wastewater
pollutant discharges. Technology 2 represents a possible process change; however, the feasibility of this option
depends on PRDOH requirements and Guaynabo WTP wastewater characteristics.
6. Non-water quality environment impact including energy requirements [40 CFR 125.3(d)(l)(vi)]
Sludge
Electricity
Air emissions
Increased sludge from
additional residuals
treatment. a
Increased power requirements
for additional sludge handling
and dechlorination. a
From the additional residuals treatment
portion of the technology: increased
sludge. b
In addition to power required for
Option 1, increased power for pumping
recycled water to the head of the raw
water treatment system. b
The treatment technologies are not expected to affect air emissions.
7. Assessment of Economic Achievability
The number and percentage of households with income below the affordability threshold values indicate that
meeting the requirements of Technology 1 and Technology 2 for the Guaynabo WTP is not likely to have a
significant impact on PRASA's household customers. Even under the most conservative set of affordability
assumptions, the costs incurred for the Guaynabo WTP are expected to present an affordability challenge to less
than 1% of PRASA's household customers.
a - The costs to dispose of increased sludge and additional power are accounted for in the Total Annualized
Compliance Costs for Option 1.
b - The costs for increased sludge and increased power costs for the Option 1 are included; however, the increased
costs for power for recycling water are not included in the cost estimates. The recycling power costs are not
expected to affect the availability or affordability of the technology option.
6.1.1 Assessment of Economic Achievability
Puerto Rico's drinking water utility (Autoridad de Acueductos y Alcantarillados
de Puerto Rico or Puerto Rico Aqueduct and Sewer Authority (PRASA)) is expected to incur
costs to comply with the technology-based NPDES permit limits for the residuals wastewater
discharge from the Guaynabo WTP. However, because the water system is expected to pass all
of the compliance cost burden to system customers through rate increases, these costs are not
expected to impose material economic burdens on the water system per se.14 Accordingly, the
economic achievability analysis for the potential NPDES permit requirements is expected to rest
primarily on the affordability of the requirements to PRASA's customers that will incur costs to
meet the NPDES requirements. The economic achievability assessment that follows is organized
around four key elements:
Estimating the impact of compliance outlays on drinking water rates;
Estimating the impact on annual household water service costs, based on
estimated household water consumption and the change in drinking water rates;
14 Except for the possibility that the system might face difficulty in financing the capital outlays for technology-
based system improvements.
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Assessing the affordability of the increase on annual household water service cost
by comparing it to household incomes in the water utility service territory, and
estimating the fraction of households for which the water service cost increase
would exceed an affordability threshold; and,
Assessing the potential to moderate impacts using rate structure-based methods
that shift the rate increase away from households for which the increase may be
unaffordable.
Compliance costs were estimated for meeting the requirements of Technology 1
and Technology 2 for the Guaynabo WTP, a facility with design treatment capacity of 26 million
gallons per day (MGD) and typical operating level of 30 MGD. These costs provide the basis for
one economic achievability case.
To estimate the impacts of additional residuals treatment costs on consumers,
EPA extrapolated the Guaynabo WTP treatment costs to other WTPs in the PRASA system.
EPA assumed the other WTPs would incur similar compliance costs, which would be passed
through to water system customers. To account for this possibility in the economic achievability
analysis, EPA constructed a second economic achievability case in which the compliance costs
estimated for Technology 1 for the Guaynabo WTP were extrapolated to the level of the total
PRASA utility, based on the ratio of flow capacity for the total utility, 94,967 MGY (PRASA,
2007), to the flow capacity at the Guaynabo WTP. Key assumptions in this approach are that the
Guaynabo WTP conditions and the resulting compliance costs for Technology 1 are
representative of other treatment facilities in Puerto Rico, and that costs can be extrapolated on
the basis of flow capacity to other WTPs. EPA recognizes that these assumptions involve
considerable uncertainty. In constructing this second economic achievability case, EPA did not
extrapolate the additional of costs of Technology 2 to the entirety of the PRASA system because
of substantial technical feasibility uncertainties concerning whether the Technology 2 "add-ons"
could be reasonably applied to other WTPs (i.e., whether complete recycle is feasible at all
plants, see Section 5.3).
Accordingly, for the assessment of economic achievability, EPA considered two
cost cases:
1. Assessment of costs and economic impacts for Technology 1 and
Technology 2 based on costs estimated for only the Guaynabo WTP
(Guaynabo WTP-only}. This case provides a much lower potential cost
and affordability impact than the following case since, in this case, costs
are assumed to be incurred only for the Guaynabo WTP but these costs
are spread to the entire PRASA system in terms of potential rate impact.
This assessment assumes that PRASA would not allocate Guaynabo WTP-
only costs to only the local water consumers from the Guaynabo WTP but
would spread the costs over all of PRASA's consumers, regardless of
location. This assumption is consistent with PRASA's current system wide
pricing structure.
6-3
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2. Assessment of costs and economic impacts for Technology 1 based on the
cost estimated for all PRASA WTPs (TotalPRASA System). This case
provides a considerably higher potential cost and affordability impact than
the prior case and may be judged a more realistic assessment of potential
affordability effects if BPJ compliance requirements and costs are likely
to extend beyond the Guaynabo WTP to the rest of the PRASA system
WTPs.
In Puerto Rico, large distribution systems (i.e., those serving more than 10,000
people) operate 99 drinking water facilities. Between 60 and 78 facilities are direct dischargers15
(up to 79 percent of all facilities), and 21 facilities have no residuals generation (U.S. EPA,
2006b). The PRASA-level extrapolated costs represent the aggregate compliance costs for
PRASA's 78 direct discharge water treatment facilities.
Compliance cost estimates for the Guaynabo WTP were developed by comparing
the treatment-in-place to the technologies under consideration. The analysis focused on process
residuals and wastewater discharges from the WTP. The analysis did not evaluate other
discharges from the plant (e.g., stormwater). The technologies under consideration include:
Technology 1 - Optimized Residuals Management plus Wastewater
Dechlorination (see Section 5.2).
Technology 2 - Optimized Residuals Management plus Zero Discharge
via Complete Recycle (see Section 5.3).
Table 6-2 presents a summary of total costs for each technology for the Guaynabo
WTP and the total PRASA utility.
Table 6-2. Summary of Compliance Costs (2005$)
Technology
Component
Technology 1
Guaynabo WTP-
only
Total PRASA
System
Technology 2
Guaynabo WTP-
only
Total PRASA
System
Optimization of Residuals Management
Capital Cost
Annual Cost
$1,140,000
$173,380
$82,615,764
$5,581,518
$1,140,000
$173,380
Dechlorination
Capital Cost
Annual Cost
$57,600
$30,860
$28,224,000
$7,051,974
Zero Discharge
Capital Cost
Annual Cost
Total Capital Cost
Total Annual Cost
$1,197,600
$204,240
$110,839,764
$12,633,492
$23,800
$14,100
$1,163,800
$187,480
PRASA system
total cost case not
analyzed for
Technology 2
15 EPA identified NPDES permits for 60 of the 78 facilities expected to generate residuals. The discharge status of
the remaining 18 facilities is unknown; however, EPA assumed the plants discharged directly for this analysis.
6-4
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6.1.1.1 Impact on Water Rates to Household Customers
The affordability analysis of cost estimates begins with estimating the technology-
based increase in total water cost to households in PRASA's water utility service territory. This
estimate is based on the change in water rates to household customers and the estimated quantity
of water consumed by households. Estimating the change in water rates involves the sub-steps
summarized below.
Estimate Total Near-Term Rate Effect of Compliance Outlays
The estimated change in water rates and resulting costs to households should
reflect how the cost of compliance outlays would actually be brought into the water utility's
rates. Calculating the change in water rates begins with estimating the change in the utility's
near-term revenue requirements. For annually recurring costs, this analysis is straightforward:
those compliance costs that recur annually are simply added to the utility's total revenue
requirements.16 However, for capital or other non-annually recurring outlays, the analysis is a bit
less straightforward and requires assumptions about the financing terms for the outlays, and how
those costs would translate into a near-term rate increase.
For the financing terms of the capital outlays, EPA used the information provided
in Question 13.B. of the Water Treatment Plant Questionnaire (Questionnaire) (PRASA 2007).
This information includes the sources and cost (for borrowed capital) of funds for projects
undertaken by PRASA over the past five years. 7 To be conservative (i.e., in the sense of
increasing the likelihood of finding an affordability impact) and correct in theory,18 EPA
assumed that all of the capital outlays for compliance will come from borrowed funds, which
incur a cost of capital.
16 Annually recurring costs are assumed to increase due to inflation by 2.5% per year.
17 The information provided in response to question 13.B. indicates to what extent these projects were funded by
non-borrowed funds (e.g., current revenue, reserves, equity, or grants) and therefore appear to not have a "cost" for
funds from these sources.
18 Even though these non-borrowed funds appear not to have a cost (at least as would be reported on a conventional
accounting statement), any of these "no-cost" funds in fact do impose an opportunity cost. For funds that are taken
from current revenue or reserves, these represent funds that are provided by ratepayers and would be appropriately
charged at the cost of consumption deferral and/or opportunity cost of capital of their providers. Funds provided by
equity, if appropriate for the entity in question, would be charged at the cost of equity, which, because of its lower
standing than debt in the hierarchy of payments to capital, would generally carry a higher cost than the interest cost
of debt.
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Table 6-3. Summary of PRASA's Capital Financing Terms
Funded Capital Expenditures
Equity or other funds from private investor
Other Government Grants
Drinking Water State Revolving Fund
Other borrowing from public sector
sources
Borrowing from private sector sources
Federal Funds (SRF & FEMA)
Rural Development
Percent of Total
Funded Capital
Expenses
2%
5%
6%
67%
3%
5%
12%
Average Interest
Rate for Capital
Expenses
N/A
N/A
2%
6%
5%
2%
5%
Average Length of
Loan Period
(years)
N/A
N/A
20
40
40
20
40
EPA calculated the weighted average of reported interest rates and repayment
periods to establish the capital financing terms. The weighted average of the reported interest
rates and loan durations from Question 13.B. of the Questionnaire - reported in Table 6-3 -
yields average terms of 5% and 35 years. These financing terms, however, may not be a good
indicator of financing available today for this water utility, depending on their current debt
rating. A review of publicly available credit ratings data indicates that PRASA was rated BBB-
by S&P as of May 22, 2007. S&P data indicates that the representative municipal bond yield for
20-year BBB rated general obligation (G.O.) bonds is currently about 4.67%, while 20-year
AAA rated G.O. bonds currently yield 4.35% (SIFMA, 2007). This data, however, does not
indicate the yield for a 20-year BBB rated revenue bond. Revenue bonds are generally issued by
governments for specific needs, such as construction, that generally have the power to levy fees
for their services, such as the operation of water and sewers. The interest rate for triple-A rated,
tax-exempt, insured municipal revenue bonds with 20-year duration is currently 4.68%,
according to Bloomberg (Bloomberg, 2007). To approximate the interest rate for a triple-B rated
municipal revenue bond, EPA applies the triple-A - triple-B differential (i.e., 32 basis points) for
G.O. bonds, as reported by S&P, to the triple-A rated revenue bond yield from Bloomberg. EPA,
therefore, estimated the interest rate for a triple-B rated, tax-exempt municipal revenue bond to
be approximately 5.0%. For this analysis, EPA established a range of impacts on household
water rates by using two interest rates: 4.7% and 5.0%. EPA assumed the capital cost is
recovered over the 20 year expected operating life of the capital.
The second question - how capital-related costs would be brought into the
utility's annual revenue requirement and thus total rates - requires an assumption about
PRASA's cost recovery and rate-making practices. The principal issue here is whether the cost
recovery for capital outlays is fixed to a constant annual value over the cost recovery period, or is
based on a framework of depreciating rate base with allowed rate of return.
The constant annual payment framework option is relatively straightforward. The
annual charge for compliance capital outlays is calculated as a constant annual payment, based
on an interest rate (i.e., 4.7% or 5.0%) and repayment term (i.e., 20 years) of the amount to be
financed (i.e., the capital cost for the technology).
In the depreciating rate base framework option, which follows the conventional
regulated utility ratemaking framework, the cost analysis is a bit more complicated. Under this
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framework, the annual charge is based on the amount of capital outlay that is placed into "rate
base," the depreciation period for the capital outlay, and the allowed rate of return on rate base.
Because it is not clear that one of these methods is more appropriate than the other for recovering
the PRASA costs to meet BPJ limitations, EPA performed the analysis using both approaches,
which allows EPA to understand the degree of difference in estimated total revenue requirement
values.
In implementing these approaches, EPA focused the analysis of household water
rate impacts on the first five years of the rate effect since the rate effect under the depreciating
rate base approach would be typically higher in the first few years of the recovery period than
under the constant payment approach. Thus, this approach provides the most conservative
analysis period in terms of the potential for compliance costs to cause an affordability impact. In
addition, even under the constant payment framework, the rate effect is typically larger relative
to household income in the initial years of its application, since household incomes might
reasonably be expected to increase over time with inflation while the capital recovery charge
remains constant. Accordingly, focusing this analysis on the early years of the potential rate
impact also provides a conservative assessment in increasing the likelihood of observing
potential affordability impacts.
The sum of the annually recurring costs and the annual charge for compliance
capital outlays yields the total increase in the annual water revenue requirement, which is
summarized for each case in Tables 6-4 and 6-5.
As shown in Table 6-4 and Table 6-5, the Technology 1 total annual revenue
recovery value for the total PRASA system case increases over time under the depreciating rate
base framework option. The same trend in the recovery value under the depreciating rate base
option is present for both technologies in the Guaynabo WTP-only analysis. The reason for this
time trend of revenue recovery for the PRASA utility and Guaynabo WTP analyses results from
differences in the relative contribution of capital outlays and annually recurring costs to total
costs for the PRASA utility and Guaynabo WTP. Although the depreciating rate base framework
provides a declining charge over time for the capital outlay, the annually recurring cost
component of total costs increases over time due to the assumed effect of inflation (i.e., 2.5% per
year) on these outlays. Because the increasing recurring cost component is larger in magnitude
than the decreasing depreciated capital, the overall effect is an increasing revenue recovery
value.
Table 6-4. Total Annual Water Revenue Increase Based on BPJ Costs for Guaynabo WTP
a (SOOOs, 2005$)
Technology
Yearl
Year 2
Year3
Year 4
Year 5
5-Year
Average
Depreciating rate base framework for recovery of capital and other non-annual recurring outlays
Technology 1
Technology 2
$320.4-324.0
$300.4-303.9
$322.7-326.1
$302.3 -305.7
$325.1 -328.4
$304.4 - 307.5
$327.7-330.7
$306.6-309.5
$330.4-333.2
$308.9-311.7
$325.3-328.5
$304.5 - 307.7
Constant payment framework for recovery of capital and other non-annual recurring outlays
Technology 1
Technology 2
$293.7-295.8
$274.4 - 276.4
$298.8-300.9
$279.1 -281.1
$304.0-306.1
$283.9-285.9
$309.4-311.5
$288.8-290.8
$314.9-317.0
$293.8-295.9
$304.2 - 306.3
$284.0 - 286.0
a - Ranges are defined, on the lower end, by a 4.7% cost of capital, and on the upper end, by a 5.0% cost of capital.
6-7
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Table 6-5. Total Annual Water Revenue Increase Based on BPJ Costs for PRASA Utility
(SOOOs, 2005$)
Technology
Yearl
Year 2
Year3
Year 4
YearS
5-Year
Average
Depreciating rate base framework for recovery of capital and other non-annual recurring outlays
Technology 1
$23,385-23,717
$23,440-23,756
$23,504-23,803
$23,575-23,858
$23,655-23,921
$23,512-23,811
Constant payment framework for recovery of capital and other non-annual recurring outlays
Technology 1
$20,914-21,104
$21,229-21,420
$21,553 -21,744
$21,885-22,075
$22,225-22,416
$21,561 -21,758
a - Ranges are defined, on the lower end, by a 4.7% cost of capital, and on the upper end, by a 5.0% cost of capital.
Estimate Rate Effect per Unit of Water Consumed
After calculating the total annual water utility revenue requirement increase for
each technology, EPA then allocated this increase over the customer classes served by the water
utility to calculate an approximate increase in rates per unit of water consumption. EPA then
used the rate effect per unit of water, by customer class, to estimate an annual rate impact per
household, based on estimated annual water consumption per household. As above, this analysis
requires different treatments for the recurring and capital cost components of the total rate
increase.
For the recurring cost component, EPA assumed that this cost is not allocated
differentially by customer class, and so, EPA calculated the per-unit-consumed rate effect by
simply dividing the total annual recurring costs charge by the total volume of finished water sold
annually by PRASA (from Question 5. A. of the Questionnaire, and reported in Table 6-6 as
94,946 MGY). This rate framework assumes that recurring cost can be treated as directly
allocable on the basis of total water volume sold and would be appropriately charged on the basis
of water volume consumed.19
Table 6-6. Summary of PRASA's Water Utility Operations
Total annual water volume delivered (MGY)
Total water volume residential (MGY)
Fraction water volume, residential
Total annual water sales ($ 000/yr)
Total water sales residential ($ 000/yr)
Fraction sales, residential
94,946
70,199
73.9%
660,000
448,800
68.0%
As in the previous discussion, the capital charge component presents a potentially
more challenging case because the capital charge may be more likely to be allocated
19 An alternative approach would be to assume that recovery of the recurring cost component of the rate increase is
split in some proportion between volumetric and fixed charges on residential bills. Under this assumption, low
income households may experience increased burden if the fixed charge component is allocated on the basis of
household connections instead of water volume consumed and lower income households consume less water than
households generally. In addition, lower income households would be less able to avoid the overall adverse rate
impact by reducing water consumption if a part of the rate increase does not vary with consumption.
6-8
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differentially by customer class than the recurring cost component of the water rate change. To
be conservative in the analysis (i.e., in the sense of increasing the likelihood of finding an
affordability impact), EPA allocated the capital charge to the household rate class based on the
greater of (I) the percentage of total water consumed by residential customers, or (2) the
percentage of total water sales revenue from residential customers.
The Questionnaire indicates that the percentage of total water consumed by
residential customers is about 74 percent, whereas the percentage of water sales revenues from
residential customers is about 68 percent. Since the quantity-based allocation is greater than the
revenue-based allocation, EPA allocated 74 percent of the capital charge component to
residential customers. Based on this allocation of capital charges, EPA then calculated the
average rate impact based on the total water volume sold to residential customers (from Question
5. A. of the Questionnaire, and reported in Table 6-6 as 70,199 MGY).
Summing the recurring cost and capital charge rate components yields the total
per-unit-consumed rate increase to residential customers. The unit cost results are summarized in
Tables 6-7 and 6-8. Table 6-7 presents the rate increase based on the total rate recovery value for
the Guaynabo WTP-only case and the total volume of water sold to residential customers of the
utility. Table 6-8 presents the rate increase based on the total rate recovery value for the total
PRASA system case and the total volume of water sold to residential customers of the utility.
20
Table 6-7. Total Annual Rate Increase per Unit of Consumption Based on BPJ Costs for
Guaynabo WTP a (2005$ per 1,000 gal)
Technology
Yearl
Year 2
Year 3
Year 4
YearS
5-Year
Average
Depreciating rate base framework for recovery of capital and other non-annual recurring outlays
Technology 1
Technology 2
0.003 - 0.003
0.003 - 0.003
0.003 - 0.003
0.003 - 0.003
0.003 - 0.003
0.003 - 0.003
0.003 - 0.003
0.003 - 0.003
0.003-0.004
0.003-0.003
0.003 - 0.003
0.003 - 0.003
Constant payment framework for recovery of capital and other non-annual recurring outlays
Technology 1
Technology 2
0.003 - 0.003
0.003 - 0.003
0.003 - 0.003
0.003 - 0.003
0.003 - 0.003
0.003 - 0.003
0.003 - 0.003
0.003 - 0.003
0.003-0.003
0.003-0.003
0.003 - 0.003
0.003 - 0.003
a - Ranges are defined, on the lower end, by a 4.7% cost of capital, and on the upper end, by a 5.0% cost of capital.
20 Note that costs for the total PRASA utility and the costs for the Guaynabo WTP are both evaluated against the
total number of households in Puerto Rico, although the Guaynabo facility only serves a portion of Puerto Rico' s
population. Because EPA is interested in the financial impact to the entire water utility, facility-specific Guaynabo
costs are assumed to be allocated across the entirety of PRASA's customer base rather than only the portion served
by the Guaynabo WTP.
6-9
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Table 6-8. Total Annual Rate Increase per Unit of Consumption Based on BPJ Costs for
PRASA Utility a (2005$ per 1,000 gal)
Technology
Yearl
Year 2
Year3
Year 4
YearS
5-Year
Average
Depreciating rate base framework for recovery of capital and other non-annual recurring outlays
Technology 1
0.246 - 0.250
0.247 - 0.250
0.248-0.251
0.248-0.251
0.249-0.252
0.248-0.251
Constant payment framework for recovery of capital and other non-annual recurring outlays
Technology 1
0.220 - 0.222
0.224 - 0.226
0.227 - 0.229
0.230-0.233
0.234-0.236
0.227 - 0.229
a - Ranges are defined, on the lower end, by a 4.7% cost of capital, and on the upper end, by a 5.0% cost of capital.
6.1.1.2
Impact on Annual Water Service Cost per Household
As the next step in the analysis, EPA calculated the increase in annual water
service cost per household for PRASA's residential customers. The increase in water service cost
is calculated by multiplying the unit rate increase, from the preceding step, by an estimated
average annual household water consumption quantity.
Estimate Average Annual Household Water Consumption
To calculate average annual household water consumption, EPA divided the total
water quantity supplied by PRASA to residential customers by the total number of households
served. Question 5. A. of the Questionnaire provides the total quantity of water provided to
residential customers. EPA used the Census 2005 American Community Survey estimate of the
total number of households in Puerto Rico (approximately 1.25 million) because PRASA's
facilities serve the entire island of Puerto Rico.
21
Dividing total residential deliveries from Table 6-6 (70,199 MGY) by the total
number of households served, yields an average annual household consumption value of 55,966
gallons per year.
Tables 6-9 and 6-10 summarize the average annual increase in water service costs
per household from NPDES permit compliance costs - based on the estimated unit rate increase
and average consumption per household - for the Guaynabo WTP-only and total PRASA system,
respectively.22
The analysis did not consider the presence of private wells in Puerto Rico and instead assumed that all households
are served by PRASA. The analysis may therefore understate the estimated impacts because accounting for private
wells would decrease the number of households over which the rate increase is allocated. The 1990 U.S. Census was
the last Census inquiry into the household water sources; however, this data is not available for Puerto Rico.
Nationally, the percentage of households receiving drinking water from private wells has stayed basically constant
since 1970 at about 15%.
22 As in Table 6-7, the Guaynabo-only analysis assumes that the Guaynabo WTP is the only PRASA plant incurring
compliance costs and that these costs are nevertheless spread across the entirety of PRASA's customer base since
PRASA's does not differentiate rates for customers according to differences in the cost of operating the specific
plants that serve those customers.
6-10
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Table 6-9. Annual Increase in Water Cost per Household Based on BPJ Costs for
Guaynabo WTP a (2005$/yr)
Technology
Yearl
Year 2
Year3
Year 4
YearS
5-Year
Average
Depreciating rate base framework for recovery of capital and other non-annual recurring outlays
Technology 1
Technology 2
0.19-0.19
0.18-0.18
0.19-0.19
0.18-0.18
0.19-0.19
0.18-0.18
0.19-0.19
0.18-0.18
0.19-0.20
0.18-0.18
0.19-0.19
0.18-0.18
Constant payment framework for recovery of capital and other non-annual recurring outlays
Technology 1
Technology 2
0.17-0.17
0.16-0.16
0.17-0.18
0.16-0.17
0.17-0.18
0.16-0.17
0.17-0.18
0.16-0.17
0.17-0.19
0.16-0.17
0.17-0.18
0.16-0.17
a - Ranges are defined, on the lower end, by a 4.7% cost of capital, and on the upper end, by a 5.0% cost of capital.
Table 6-10. Annual Increase in Water Cost per Household Based on BPJ Costs for
PRASA Utility a (2005$/yr)
Technology
Yearl
Year 2
Year 3
Year 4
YearS
5-Year
Average
Depreciating rate base framework for recovery of capital and other non-annual recurring outlays
Technology 1
13.78-13.98
13.82-14.00
13.85-14.03
13.90-14.06
13.94-14.10
13.86-14.04
Constant payment framework for recovery of capital and other non-annual recurring outlays
Technology 1
12.33 - 12.44
12.51-12.63
12.70-12.82
12.90-13.01
13.10-13.21
12.71-12.82
a - Ranges are defined, on the lower end, by a 4.7% cost of capital, and on the upper end, by a 5.0% cost of capital.
Whether to Adjust Estimated Household Water Consumption by Income Level
The increase in water service cost reported above is based on water consumption
for the average household and thus applies to the so-called average income household served by
the PRASA drinking water utility. However, it will be necessary to analyze the impact of
changes in water rates not only for the average or other central tendency measure (i.e., median)
of household income, but also for households at other income levels. Such an analysis requires a
way of adjusting the water consumption quantity for the average income household to other
income levels or, alternatively, EPA needs a basis for assuming that household water
consumption should not vary by income level in this analysis.
In a previous methodology memorandum, Affordability Analysis Approach for the
Drinking Water Effluent Limitation Guideline (Abt Associates, Inc., 2007), a literature review
was performed to explore this issue. An appropriate method to adjust the water consumption
quantity from the average income household to other income levels would be based on the
income elasticity of residential water consumption. A search of literature on residential water
consumption found a number of studies addressing residential water consumption and how it
varies with water price and household income. One particularly useful study compiled results
from 64 studies containing 162 estimates of the income elasticity of residential water
consumption as the basis for a meta-analysis of factors determining price and income elasticity
of water consumption (Dalhuisen et al., 2003).
6-11
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Given the review of findings from Dalhuisen et a/., and the desire to be
conservative in the analysis in terms of increasing potential impact on lower income households,
EPA proposed, as a primary analysis case, not to vary the estimated water consumption quantity
and the resulting increase in annual water service cost to household customers, over income
9^
levels. As a result, the calculated annual increase in water service cost - reported in Tables 6-9
and 6-10 - is constant over all income levels. However, for testing the potential impact of this
increase in water service cost over different household income levels, the household income
would vary and this variation in income, against which the cost increase is compared, will
become the basis for assessing differential effect of water rate increases by household income
level in the next subsection.24
6.1.1.3 Affordability Assessment of Household Water Service Cost Impacts
EPA used the analysis framework currently being revised for use in Safe Drinking
Water Act (SDWA) affordability analyses for assessing the potential affordability impact of
PRASA BPJ-based requirements. Note that the SDWA affordability determination is applied
nationally in assessing the affordability of National Primary Drinking Water Regulations,
whereas this analysis is at the plant or system level.
As the primary affordability test, EPA compared the estimated increase in
household water service cost to income by household. Households for which the estimated
percentage increase exceeds an affordability criterion are assessed as potentially finding the
water cost increase unaffordable. Three adverse impact thresholds are currently under
consideration for the revised SDWA affordability test:
0.25% of household income;
0.50% of household income; and
0.75% of household income.25
To apply this test, EPA used information on household counts by income range
for Puerto Rico from the 2005 Census American Community Survey (ACS). The ACS reports
household counts within the income ranges listed in Table 6-11.
23 Another possible source of error that should be accounted for in this analysis is the extent to which annual
household water consumption might vary by household size, and simultaneously, how household size might vary
with income. This adjustment, which would account for the joint effect of income and household size on household
water consumption, could be made using joint household size and income distribution information and a measure of
household-size elasticity of water consumption in combination with Dalhuisen's household-income elasticity of
water consumption.
24 Alternate analyses could test an assumption in which household water consumption would be assumed to decline
with income level based on the median elasticity value of 0.24, as reported over the 162 estimates of income
elasticity on which Dalhuisen et al is based.
Additional information on the current EPA effort to revise the SDWA small system variance affordability test
criterion can be found in: U.S. Environmental Protection Agency. 2006. Small Drinking Water Systems Variances -
Revision of Existing National-Level Affordability Methodology and Methodology To Identify Variance
Technologies That Are Protective of Public Health. Federal Register, Vol. 71, No. 41, Page 10671. March 2, 2006.
6-12
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Table 6-11. Puerto Rico Income Distribution (2005$)
Household Income (2005$)
Less than $10,000
$10,000 to $14,999
$15,000 to $19,999
$20,000 to $24,999
$25,000 to $29,999
$30,000 to $34,999
$35,000 to $39,999
$40,000 to $44,999
$45,000 to $49,999
$50,000 to $59,999
$60,000 to $74,999
$75,000 to $99,999
$100,000 to $124,999
$125,000 to $149,999
$150,000 to $199,999
$200,000 or more
Number of Households
408,690
163,240
119,540
101,762
81,744
69,499
55,547
42,396
36,213
51,630
48,239
38,934
16,586
7,588
6,624
6,086
Accounting for the Distribution of Household Income within Census Ranges
The Census provides the number of households by income ranges, as described
above. In this analysis, EPA calculates the number of households for which the estimated
increase in water service cost exceeds a threshold percentage of household income.
The analysis is performed by determining the household income at which the
estimated increase in water service cost equals a threshold percentage (the " threshold impact
income value "), and then estimating the number of households served by the water utility with
household income less than the threshold impact income value.
In all likelihood, the threshold impact income value(s) will fall within, and not at
the edge of, a Census income range. Accordingly, it is necessary to estimate the fraction of
households within a Census income range that fall below a threshold impact income value. To
account for the lack of information within the Census income ranges, EPA used two approaches
for fitting a model distribution to the Census income data: (1) a log-normal distribution, and (2)
an exponential distribution. The log-normal and exponential distributions are widely used to fit
income distributions, particularly the portion of income distributions that comprise the low-
middle income portion (e.g., up to 97-99 percent of the population) (Banerjee et al., 2006;
Clementi and Gallegati, 2005; Dorving, 1973).
EPA fit a two-parameter log-normal distribution model to the Census income
distribution for Puerto Rico. The log-normal distribution is a skewed distribution defined by a
mean and standard deviation. EPA estimated the mean and standard deviation for the log-normal
distribution through a transformation of midpoints of each income range, where the mean is
estimated as the weighted average of the log transformed midpoints of the income ranges. The
6-13
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cumulative distribution function of the log-normal distribution, presented below in Figure 6-1,
deviates on average by 1.1 percent from the known Census data points along that distribution,
thus providing a reasonable fit.26
1,400,000
1,200,000 - -
01 1,000,000 --
o 800,000
I
E
z 600,000
400,000 --
200,000 --
] Census Data
-Log-Normal Model
Upper-Bound of Income Range
Figure 6-1. Cumulative Distribution of Income in Puerto Rico: Log-Normal Distribution
Model
EPA also fit an exponential distribution to the Census income data, where the
mean is defined by the weighted average of the midpoints of the income ranges. The cumulative
distribution function of the exponential distribution, presented below in Figure 6-2, deviates on
average by -2.2 percent from the Census data points along that distribution, thus also providing a
reasonable fit.
26 The apparent kink in the curve in Figure 6-1 and Figure 6-2 at the $50K bar is because the bars are evenly spaced
on the figure, yet represent progressively larger income ranges beyond $50K.
6-14
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1,400,000
1,200,000 --
] Census Data
-Exponentiall Model
Upper-Bound of Income Range
Figure 6-2. Cumulative Distribution of Income in Puerto Rico: Exponential Distribution
Model
The cumulative distribution functions allow EPA to calculate, for each threshold
income value, the number of households at or below that income level, even if the threshold
value falls within one of the Census income ranges. In applying these distributions, EPA is most
concerned about the potential for error in representing the distribution of income within the
lowest income range - less than $10,000 - since these are the households most sensitive to
increasing water rates, and the threshold income levels for adverse impacts are likely to fall
within this lowest income range.
Each of these distributions offers certain strengths and weaknesses for estimating
the numbers of households with income below an affordability threshold. Specifically, because
of the shape of these distributions at very low income levels, the exponential distribution may
overstate the number of households as income levels approach $0, while the log-normal
distribution may understate the number of households as income levels approach $0.
Since the actual income-by-household data within the "less than $10,000" range is
not available, EPA cannot know which distribution better represents the Puerto Rico households
and the extent of error in using these distributions to estimate the number of households
potentially facing an affordability challenge from the compliance cost-based rate increases.
6-15
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35.0%
30.0%
25.0%
20.0%
15.0%
10.0%
o
I 5.0%
co
0.0%
LogNormal CDF
Exponential CDF
Income
Figure 6-3. Log-Normal vs. Exponential Representation of the Lower Income Range in
Puerto Rico
In this analysis, EPA performed the affordability assessment using both
distribution models to establish a range of the number of households for which the increase in
water service costs may be determined to be "unaffordable."
Determine the Threshold Household Income Levels
The analysis determines the number of households for which the technologies
might be "unaffordable" by first determining the household income level at which the estimated
increase in water service cost equals a threshold percentage. The increase in household water
service cost for each case is reported in Tables 6-9 and 6-10. Since EPA is using three possible
threshold percentages of income - 0.25%, 0.5%, and 0.75% - there are three different threshold
income levels for each technology27. As before, estimates are carried through for two capital
recovery frameworks - depreciating rate base and constant payment - as well as two possible
costs of capital - 4.7% and 5.0% - and multiple time periods - years 1 through 5 and a 5-year
average. As outlined below, EPA collapsed these alternative variable specifications into simple
high and low estimates of household counts for each of the BPT technology options.
For each technology and percentage threshold, EPA selected a single threshold
income level for estimating the number of households for which the increase in water service
costs may be "unaffordable." To be conservative in terms of increasing the number of potentially
impacted households, the final threshold income level is selected as the maximum of the
threshold income levels across each capital recovery, interest rate option, and time period. For
27 EPA analyses three possible threshold percentages of income in this case because the Office of Ground Water and
Drinking Water is currently revising their Safe Drinking Water Act affordability test criteria for small drinking
water system variances. They have put forth 0.25, 0.5, and 0.75% as possible threshold values but as of this reports
completion date not final criteria have been set. For additional information see page 6-12 and footnote 25.
6-16
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the PRASA utility and Guaynabo WTP analysis, the maximum threshold income level for each
technology comes from the 5-year average rate increase estimated using the depreciated rate base
framework and a 5% interest rate. As noted previously in reference to Tables 6-4 and 6-5, the
annual rate recovery value for the PRASA utility and the Guaynabo WTP increases over time
under the depreciating rate base framework due to the relative size of the annually recurring
costs to the capital outlays for this facility, and the impact of inflation on the annually recurring
costs. As a result, the 5-year average threshold value is greater than the year-1 threshold value
for both entities and technologies.
Tables 6-12 and 6-13 present the estimated threshold income levels for the first
year and 5-year average of each analysis case, along with the maximum income threshold used to
estimate the number of households that may experience significant burden due to the increased
9R
water service cost. These income thresholds are interpreted as the household income at which
the estimated increase in water service cost equals the threshold percentage of income. Because
the increase in water service cost per household is constant, the threshold income level in dollars
declines as the threshold income level in percentage terms increases.
For example, the maximum income threshold for Technology 1 and 0.25% in
Table 6-13, $5,614, can be interpreted as the household income level at which the annual
increase in water service costs for Technology 1 equals 0.25% of household income. Similarly,
$2,807 is interpreted as the household income level at which the Technology 1 compliance costs
equal 0.5% of household income.
Table 6-12. Threshold Household Income Level Based on BPJ Costs for Guaynabo WTP a
($2005)
Impact Criterion for
Estimated Increase in
Water Service Cost
Depreciating Rate Base
Analysis Framework
Yearl
5-Year Avg.
Constant Payment Analysis
Framework
Yearl
5-Year Avg.
Maximum Threshold
Household Income
Level
Technology 1
0.25%
0.50%
0.75%
76-76
38-38
25-25
77-77
38-39
26-26
69-70
35-35
23-23
72-72
36-36
24-24
77
39
26
Technology 2
0.25%
0.50%
0.75%
71-72
35-36
24-24
72-73
36-36
24-24
65-65
32-33
22-22
67-67
33-34
22-22
73
36
24
a - Ranges are defined, on the lower end, by a 4.7% cost of capital, and on the upper end, by a 5.0% cost of capital.
28 Again, please note that the Guaynabo analysis assumes that the residential rate effect from compliance costs at the
Guaynabo WTP is allocated all of PRASA's residential customers, not only those customers served by the
Guaynabo WTP.
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Table 6-13. Threshold Household Annual Income Level Based on BPJ Costs for PRASA
Utility a (2005$)
Impact Criterion for
Estimated Increase in
Water Service Cost
Depreciating Rate Base
Analysis Framework
Yearl
5-Year Avg.
Constant Payment Analysis
Framework
Yearl
5-Year Avg.
Maximum Threshold
Household Income
Level
Technology 1
0.25%
0.50%
0.75%
5,514-5,592
2,757 - 2,796
1,838-1,864
5,544-5,614
2,772 - 2,807
1,848-1,871
4,931-4,976
2,465 - 2,488
1,644 - 1,659
5,084-5,129
2,542-2,564
1,695-1,710
5,614
2,807
1,817
a - Ranges are defined, on the left, by a 4.7% cost of capital, and on the right, by a 5.0% cost of capital.
Estimate the Number of Households for Which Increased Water Service Costs
Exceed Affordability Thresholds
The final step of the analysis is to estimate the number and percentage of
households for which the estimated increase in water service costs exceed the percentage of
income affordability thresholds of 0.25 percent, 0.5 percent, and 0.75 percent. As outlined above,
EPA performed this calculation using both the log-normal distribution and exponential
distribution approximations of the continuous distributions of household income for Puerto Rico.
Table 6-14 and 6-15 report the estimated number and percentage of households with income
below the income threshold values.29
Table 6-14. Households with Income Below Affordability Thresholds Based on BPJ Costs
for Guaynabo WTP (2005$)
Impact Criterion (%
of household income)
Threshold Income
Level
Exponential Income Distribution a
% Households < Threshold
Households < Threshold
Technology 1
0.25%
0.50%
0.75%
$77
$39
$26
0.29%
0.14%
0.10%
3,595
1,799
1,199
Technology 2
0.25%
0.50%
0.75%
$73
$36
$24
0.27%
0.13%
0.09%
3,367
1,685
1,123
a - The log-normal results are excluded from this table. At incomes levels between $24 - $77 the log-normal
distribution of households is effectively equal to zero (see Figure 6-2 for illustration) and may no longer be a reliable
model of the Puerto Rico household income distribution.
29 Again, note that the Guaynabo analysis assumes that the residential rate effect from compliance costs at the
Guaynabo WTP is allocated all of PRASA's residential customers, not only those customers served by the
Guaynabo WTP.
6-18
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Table 6-15. Households with Income Below Affordability Thresholds Based on BPJ Costs
for PRASA Utility (2005$)
Impact Criterion (%
of household income)
Threshold
Income Level
Log-Normal Income Distribution
% Households
< Threshold
Households
< Threshold
Exponential Income Distribution
% Households
< Threshold
Households
< Threshold
Technology 1
0.25%
0.50%
0.75%
$5,614
$2,807
$1,871
14.0%
3.7%
1.4%
175,151
47,036
17,931
18.8%
9.9%
6.7%
235,584
123,912
84,032
The number and percentage of households with income below the affordability
threshold values are very small when the BPJ limits compliance costs for the Guaynabo WTP are
30
allocated across PRASA's entire residential customer class (e.g., Table 6-14). However, the
values are higher, and potentially significant in terms of overall affordability impact, based on
the BPJ limits compliance costs for the total PRASA utility.
6.1.1.4
Mitigating Impacts through PRASA's Low-Income Rate Subsidy Program
PRASA's low-income rate subsidy program may shield some of the households
with income below the threshold levels from the compliance cost-based rate increase. At this
time, EPA has relatively limited understanding of how this program would work in conjunction
with the compliance cost-based rate increase. Information provided by PRASA in their response
to Question 11 of the Questionnaire indicates that about 40,000 households in Puerto Rico
currently receive lower, alternative rates on the basis of their income (i.e., less than $10,000) and
other factors that determine qualification for the program (e.g., minimum age of 55).
To assess the potential effect of this program in reducing the affordability impact,
EPA assumed that any customers in the program would be shielded entirely from the compliance
cost -based rate increase. EPA further assumed that the rate subsidy program begins its
applicability at the very lowest of household incomes and applies without loss to all households
as income increases until the number of participating households (i.e., 40,000) is used up. These
assumptions mean that EPA can simply subtract the 40,000 participating households from the
number of households otherwise estimated to have income below a threshold level, to calculate
the number of households with income below a threshold level after consideration of the rate
subsidy program. For example, if the affordability analysis finds that 47,036 households would
incur an adverse affordability impact (see Table 6-15, Technology 1), and PRASA's current rate
reduction mechanism applies to 40,000 households, then the rate subsidy program would reduce
the number of affordability impact households by 40,000 - i.e., from 47,036 to 7,036.
Based on these assumptions, and using compliance costs for the total PRASA
utility, the rate subsidy program may eliminate the affordability impact in one of the
Technology-Threshold cases outlined above. This case (i.e., Technology 1 for the 0.75 percent
threshold) occurs under the log-normal simulation of the low end of Puerto Rico's income
30 In fact, at incomes levels this low ($24 - $77) the log-normal distribution of households is effectively equal to zero
(see Figure 6-2 for illustration) and may no longer be a reliable model of the Puerto Rico household income
distribution. For this reason, the log-normal results are excluded from this table.
6-19
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distribution. The number of adverse impact households for other cases could likewise be reduced
by about 17 percent - 85 percent, depending on the technology, affordability threshold, and
income distribution model.
Using BPJ limits compliance costs for only the Guaynabo WTP, PRASA's rate
subsidy program could similarly offset increased costs for all potentially impacted households,
regardless of the technology or affordability threshold, since all options are estimated to present
an affordability challenge to fewer than 40,000 Puerto Rican households.
Done correctly, this analysis should account for the shift in water service cost
increase to the water utility's remaining customers and whether the number of adverse
affordability impact households might increase. To examine this case, EPA assumed that all the
residential rate protection for the 40,000 participating households would be shifted to other
residential households. Of course, this assumption may not be valid: all, or a portion, of these
shifted costs could be recovered from other customer classes or otherwise supported by the
Government of the Commonwealth of Puerto Rico.
If, however, EPA does accept the assumption that the increase in costs from
PRASA compliance for these 40,000 households is shifted entirely to the remaining residential
customers, EPA finds:
Shifting the cost that would otherwise fall on the 40,000 program
participants results in a potential increase in the total number of impacted
households of 0.7 percent or less, depending on the technology,
affordability threshold, and income distribution model.
However, if one accounts for the fact that 40,000 households now incur
zero cost increase, overall there may be a net decrease in the number of
households for which the rate increase may be unaffordable, regardless of
technology, affordability threshold, and income distribution model.
A better understanding of this potential consideration would require specific
information about PRASA's rate subsidy program and whether and how it would shield some
households from the compliance cost-based rate increase.
6.1.1.5 Summary of the Economic Achievability Assessment
The general economic acceptance test applying to the NPDES permit limits for
residuals wastewater discharge from the Guaynabo WTP is that they are "economically
achievable" - a concept that has been generally applied to the businesses and other entities that
must achieve the discharge reductions needed to comply with effluent discharge regulations.
Because the PRASA utility is expected to pass on 100 percent of the costs incurred to meet the
requirement to water system customers, this economic achievability assessment focuses on the
impact of potential water rate increases on the system's customers, and, in particular, on the
system's household customers. Under this framework of thinking, the requirements would be
economically achievable if they were found to be "affordable" by the water system customers
who bear the costs through water rate increases.
6-20
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EPA believes that strong conclusions cannot be drawn from the affordability
analysis detailed in this section and that additional analyses would provide a clearer assessment
of potential affordability impacts based on compliance costs. A more definitive conclusion
regarding affordability requires judgments about (1) the specific affordability criterion (among
the options presented) that should be used to determine whether a rate increase is "unaffordable"
at the level of the individual household, and (2) the number and percentage of households for
which a finding of "unaffordability" constitutes an adverse finding for the water utility, as a
whole.
6.1.2 Recommended Permit Limitations for Technology 1
This section describes the development of the recommended permit limitations for
Technology 1, which includes both Optimization of Residuals Management and Dechlorination.
(Technology 2 is zero discharge, and thus, the plant would not have any pollutant-specific
limitations.) The previous permit specifies all numeric limitations as daily maximum limitations
and does not specify any monthly average limitations. The limits proposed for this permit also
specify only daily maximum limitations. In establishing daily maximum limitations, EPA's
objective is to restrict the discharges on a daily basis to a level that is achievable for a facility
that targets its treatment at the long-term average (LTA). A facility that discharges consistently
at a level near the daily maximum limitation would not be operating its treatment system to
achieve the LTA. That is, targeting treatment to achieve the limitations may result in frequent
values exceeding the limitations due to routine variability in treated effluent. Thus, EPA
establishes limitations at values greater than the LTA to allow for normal variability. The
following sections describe the limitations for TSS and the other pollutants in the permit.
TSS Limitations
EPA recommends TSS limitations instead of turbidity limitations. Although
turbidity measurements are relatively easy, quick, and inexpensive to collect, TSS measurements
provide a more accurate reflection of treatment system performance. In addition, controlling TSS
often leads to lower concentrations of metals. If the facility targets its average performance level
for the treatment system to the long-term average for TSS, EPA expects that the facility will be
better able to comply with its permit limitations. Table 6-16 presents the LTA, the allowance for
variability, the daily maximum limitation, and the monitoring frequency. The following
paragraphs discuss each aspect in further detail.
Table 6-16. Target Level and Recommended Limitation for TSS
TSS
Target Level: Long-term Average (mg/L)
Variability Factor
Daily Maximum Limitation (mg/L)
Monitoring Frequency
Values
10
4
40
Daily
In calculating the LTA basis for the TSS limitation, EPA used turbidity data
because TSS data were not available for the Guaynabo WTP. EPA evaluated the turbidity data
reported for January 2003 to April 2007. Table 6-17 identifies the months for which data are
missing or the values were in violation of the current permit limitation. The Guaynabo WTP
6-21
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effluent experienced spikes in turbidity, likely due to operating at greater capacity than originally
designed. EPA determined that the spikes in turbidity demonstrated an inadequate residuals
treatment system. By using the technology costed in Technology 1, the spikes in turbidity in the
effluent would be eliminated, and thus, EPA excluded the spikes in turbidity values from the
LTA calculations. That is, the BPT technology is demonstrated by the Guaynabo WTP effluent
quality if the residuals treatment system had adequate capacity.
The remaining turbidity data had corresponding TSS values ranging from 0.05
mg/L to 31 mg/L. EPA then converted the turbidity data to TSS using a conversion factor of 1.5.
For example, the current limitation for turbidity is 50 nephelometric turbidity units (NTU),
which converts to a limitation of 75 milligrams per liter (mg/L) for TSS. EPA selected the
conversion value of 1.5 because it is the midpoint of the generally accepted range of 1 to 2 for
turbidity to TSS conversions (ASCE, 1996). Assuming that the converted data are log-normally
distributed, the expected value (mean) is 9.5 mg/L. EPA rounded this value upward to a value of
10 mg/L for the LTA.
Table 6-17. Turbidity Values Excluded from LTA Calculations
Year
2003
2004
2005
2006
2007
Month
January
May
August
October
August
September
October
November
October
December
September
January
Excluded Values (NTU)
1900
1600
Not provided a
2800
Not provided a
Not reported b
Not reported b
Not reported b
2500
130
1900
3200
Date of Non-Compliance
Notification
February 24
June 24
November 26
November 16
None
None
February 21
a - PRASA did not provide the discharge monitoring report for this month.
b - PRASA did not report a value for turbidity in the monthly monitoring report.
In determining an appropriate allowance for variability, EPA first reviewed the
turbidity data used for the LTA calculations. Because the turbidity data were highly variable with
a variability factor (VF) of 9.6, EPA needed a typical VF for treatment systems that have
demonstrated appropriate control of TSS. Thus, EPA examined TSS limitations promulgated
during the last 10 years. Although the regulations were based upon different treatment
technologies, wastewater professionals generally agree that TSS can be adequately controlled by
many different types of treatment systems. Furthermore, each regulation used data from well
operated and controlled treatment processes in determining the variability of TSS. As shown in
Table 6-18, the values are relatively close in value, ranging from 2.9 to 5.4, with an arithmetic
average of 4.1 and median (midpoint) of 3.9. For purposes of the Guaynabo WTP permit, EPA
selected the value of 4 as the variability allowance for the TSS limitation.
6-22
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Table 6-18. TSS Variability Factors in Recent Regulations
Category
Centralized Waste Treatment
Waste Combustors
Iron and Steel
Landfills
Pulp, Paper, and Paperboard,
Cluster Rule
Transportation Equipment
Cleaning
Subcategory
Organic s
Oils
Metals
Commercial Hazardous Waste
Combustor
Coke By -Products
Other
1) Hazardous and
2) Non-Hazardous a
Bleached papergrade kraft and soda
Barge/Chemical and Petroleum
Food Direct
Option
4
9
3
4
BAT1
DRI_BPT
FORGING
1
2
Value
4.8
2.9
3.2
3.6
4.2
4.6
3.5
4.4
4.4
3.11
4.7
5.4
a - The VFs for both subcategories were based upon the same data.
In determining the limitation, EPA multiplied LTA and VF values above to obtain
a value of 40 mg/L (i.e., limitation=LTA x VF). By operating, controlling, and maintaining its
system to achieve the target of 10 mg/L (i.e., the LTA), the Guaynabo WTP will be capable of
complying with the limitation.
Because TSS should be monitored continuously to ensure proper operation and
control, the plant should monitor TSS on a daily basis. (Previously, the plant reported turbidity
on a monthly basis.) Furthermore, if the plant wishes to verify that conversion factor of 1.5 is
appropriate in converting turbidity to TSS, then it should monitor turbidity at the same times and
frequency as TSS for at least one year. At the end of the monitoring period, the facility should
evaluate the relationship between the two parameters and determine if the ratio is statistically
significantly different than 1.5.
Other Pollutants
For BPT Option Technology 1, EPA had LTA data for only turbidity. Therefore,
EPA recommends retaining limitations from the existing permit for the pollutants in Table 6-19.
This table identifies the pollutant parameters with numeric limitations and also summarizes the
values observed in the monitoring data from 2003 through 2005, excluding the months
associated with turbidity permit violations (because the adverse conditions also would affect
other pollutants). The following paragraphs provide additional comments about intake
allowances and residual chlorine.
6-23
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Table 6-19. Summary of Current Permit Limits and Monitoring Data
Pollutant
Parameter
Ammonia and
Ammonium
Arsenic
BODS
Color
Copper
Dissolved
Oxygen
Fecal Coliform
Flow
Fluoride
Lead
Manganese
Mercury
Phenolic
Substances
Phosphorus
Residual
Chlorine
Settleable Solids
Sulfide
Surfactants as
MB AS
Temperature
Total Dissolved
Solids (TDS)b
Zinc
pH
Units
mg/L
ug/L
mg/L
Pt/Co Units
ug/L
mg/L
colonies/
100ml
nrVday
ug/L
ug/L
ug/L
ug/L
ug/L
mg/L
mg/L
ml/L
ug/L
ug/L
°C
mg/L
ug/L
su
Daily
Maximum
Limitation
1.0 c
0.18
5.0
15
11
Not less than
5.0
a
2.37
700
2.9
50.0
0.012
1.0
1.0
0.50
[2]
2
100
32.2
50.00
6.0-9.0
Number of
Observations
26
23
39
Not evaluated
26
910
Not evaluated
910
24
24
26
26
Not evaluated
26
910
49
Not evaluated
Not evaluated
910
12
25
910
Minimum d
0.1
0.14
2.0
2.8
3.5
0.24
33.0
0.7
3.9
0.001
0.006
0
Maximum d
0.71
13.0
8.7
91.0
10.76
4.22
190
11.3
844
0.2
1.59
2.2
Arithmetic
Average d
0.20
1.99
1.95
29.0
6.4
1.74
91.21
2.68
89.73
0.028
0.1
0.363
All values are <0. 1
19.9
140
3.7
6.3
28.3
260
113
8.9
24.8
187.5
17.9
7.77
a - The coliform geometric mean of a series of representative samples (at least five samples), of the waters taken
sequential shall not exceed 2,000 colonies/100 ml. Not more than 20 percent of the samples shall exceed 4,000
colonies/100 ml.
b - Solids from wastewater sources shall not cause deposition in, or be deleterious to existing or designated uses of
the waters.
c - The value of the Daily Maximum Limitation for Ammonia and Ammonium was taken from the value reported in
NPDES Permit for Total Ammonia.
d - These values differ from those in Table 4-3 because EPA omitted data points observed on days with spikes in
turbidity levels.
PRASA's letters of non-compliance explain that parameters such as phosphorus,
arsenic, copper, lead, manganese, zinc, phenolic substances, total residual chlorine, and ammonia
are part of the natural constituents of raw water received at the plant. The plant states that the
substances are residual products from the filtering process, but are not added by the operational
phase. Consequently, the plant may be eligible to take credit for the pollutants in the intake water
6-24
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as described in 40 CFR 122.45(g). For example, control of arsenic appears to provide
considerable difficulties because the plant reported only one value in 27 months that was less
than the permit limitation. By providing an intake allowance for arsenic and controlling for TSS,
EPA is confident that the plant will be able to comply with its limitations. Similarly, permit
limitations for other native constituents could be adjusted for intake concentrations.
EPA recommends lowering the limitation for total residual chlorine, because BPT
Option Technology 1 would remove chlorine to levels below detection. For residual chlorine, the
daily maximum limitation of 0.50 mg/L can easily be achieved by proper operation of
Technology 1, which eliminates residual chlorine in the filter backwash through dechlorination
(see Section 5.2). The dechlorination treatment of the filter backwash is conducted prior to
discharge. Technology 1 allows for sufficient reaction time for dechlorination and the residual
chlorine concentration in the discharge should be at or below the analytic detection level, which
can be as low as 0.1 mg/L.
6.2
Best Conventional Pollutant Control Technology (BCT)
The Guaynabo WTP process adds mainly solids, metals, and chlorine to
wastewater. To determine if solids are the only conventional pollutant requiring control, EPA
evaluated baseline discharges of conventional pollutants using the Guaynabo WTP permit
application and DMR data from 2003 to 2005. Table 6-20 summarizes concentration data for
conventional pollutants. Appendix B contains the detailed DMR data.
Table 6-20. Conventional Pollutant Concentrations
Parameter
Range
Median
Average Annual Concentration (2003 to 2005)
Fecal
Coliform
(#/100 mL)
<2 - 1,600
<2
NC
TSS (mg/L)a
1 - 4,200
5
390
Oil and
Grease
(mg/L)
1.4
1.4
NC
BOD, 5-Day
(mg/L)
<2-17
<2
NC
Source: PRASA, 2005 and DMR data for 2003 to 2005.
a - See Appendix C.
NC - Not calculated because parameter was measured at concentrations below detection limits the majority of the
time.
For both oil and grease and BODs, concentrations are low or below detection
limits. For fecal coliform, the majority of the time, levels were below detection, with occasional
spikes. Of the conventional pollutants with monitoring data, TSS and fecal coliform are the
pollutants requiring control.
The Optimization of Residuals Management portion of Technology 1 would
control the spikes in effluent TSS and fecal coliform concentrations that result from draining
sedimentation tanks. EPA did not identify another conventional pollutant control technology for
this facility that would exceed the performance of Technology 1 and be a potential candidate as
the basis for BCT effluent limits. Consequently, EPA did not identify more stringent BCT
effluent limits for conventional pollutant discharges beyond those in Section 6.1.
6-25
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6.3 Best Available Technology Economically Achievable (BAT)
EPA did not identify BAT options that would exceed the performance of
Technologies 1 or 2 for this facility. Consequently, EPA did not identify more stringent BAT
effluent limits for pollutant discharges beyond those in Section 6.1.
6-26
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7.0
SUMMARY
To determine the permit limits for the supernatant discharge from the
Guaynabo WTP to the Bayamon River, EPA considered two technology
options: (1) Technology 1: Optimized Residuals Management plus
wastewater Dechlorination; and (2) Technology 2: Optimized Residuals
Management plus Zero Discharge of wastewaters achieved via complete
recycle.
Technology 1 would result in $345,000 ($2005) total annualized costs,
remove 1.36 million Ibs of total suspended solids (TSS), and remove 5,060
Ib-eqs of metals and chlorine. Table 7-1 presents the long-term averages
for TSS and total residual chlorine (TRC), based on the Technology
Option 1 technology.
Table 7-1. Long-Term Averages Based on Technology 1
Pollutant
Total Suspended Solids
Total Residual Chlorine
Monthly Average (mg/L)
10
0.1
Daily Maximum (mg/L)
40
0.5
Basis
Technology Option 1
Technology Option 1
For all remaining parameters, permitting authorities can retain existing
permit limits.
Technology 2 would result in $323,900 ($2005) total annualized costs,
remove 1.42 million Ibs of TSS, and remove 5,130 Ib-eqs of metals,
chlorine, and other nonconventional pollutants. However, Technology 2
may not be feasiblePRDOH may not give permission for the facility to
completely recycle residuals, because of health concerns. Furthermore, the
Guaynabo WTP may need to install additional treatment systems that are
not included in EPA's cost estimates.
EPA determined that the costs for Technology 1 and Technology 2 are
generally economically achievable. The number and percentage of
households with income below the affordability threshold values indicate
that meeting the requirements of Technology 1 and Technology 2 for the
Guaynabo WTP is not likely to have a significant impact on PRASA's
household customers.
31
EPA collected data showing the environmental benefits gained from the
reduction of metals, solids, and chlorine, as expected from installation of
Technology 1.
31 However, EPA believes that strong conclusions cannot be drawn from the affordability analysis detailed in section
6.1. land that additional analyses would provide a clearer assessment of potential affordability impacts based on
compliance costs. A more definitive conclusion regarding affordability requires judgments about (1) the specific
affordability criterion that should be used to determine whether a rate increase is "unaffordable" at the level of the
individual household, and (2) the number and percentage of households for which a finding of "unaffordability"
constitutes an adverse finding for the water utility, as a whole.
7-1
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8.0 REFERENCES
Abt Associates, Inc. 2007. Affordability Analysis Approach for the Drinking Water Effluent
Limitation Guideline. Abt Associates Inc. Memorandum to EPA. May 25, 2007.
ASCE, 1996. Management of Water Treatment Plant Residuals. American Society of Civil
Engineers and the American Water Works Association. ASCE ISBN: 0-7884-0181-0; AWWA
ISBN: 0-89867-86-5. 1996.
AWWA, 2002. Trace Contaminants in Drinking Water Treatment Chemicals. American Water
Works Association. AWWA ISBN: 1-58321-247-7. 2002.
Banerjee, A., Yakovenko, V., and Matteo, T. 2006. "A Study of the Personal Income
Distribution in Australia." Physica A, vol. 370, 54-59.
Bloomberg National Municipal Bond Yields: Triple-A Rated, Tax-Exempt Insured Revenue
Bonds, http://www.bloomberg.com/markets/rates/index.html, accessed 7/23/2007.
Clementi, F., and Gallegati, M. 2005. "Power Law Tails in the Italian Personal Income
Distribution." Physical A, vol. 350, 427-438.
Dalhuisen, Jasper M., Raymond J. G. M. Florax, Henri L. F. de Groot, and Peter Nijamp. 2003.
"Price and Income Elasticities of Residential Water Demand: A Meta-Analysis." Land
Economics 79(2): 292-308.
Dorving, F. 1973. "Distribution of Farm Size and Income: Analysis by Exponential Functions."
Land Economics, vol. 49, 143-147.
Engineering News-Record (ENR), 2006. Construction Cost Index History (1908 - 2005).
Available at http://enr.ecnext.com.
ERG, 2006. DRAFT Drinking Water Treatment Plant Site Visit Report: Puerto Rico,
November 27, 2006.
Gebbie, Peter. Commonly Available Coagulants and Details.
http://www.wioa.org.au/conf_papers/05/paperl0.htm. Conference date 2005.
Guaynabo WTP DMRs, 2003 to 2005. Discharge Monitoring Reports provided by U.S. EPA
Region 2 for NPDES Permit Number PR0022438. DCN EPA-HQ-OW-2004-0035-DW03621.
Gulbrandsen Technologies, Inc. Aluminum Chlorohydrate Solution Product Specifications;
Product Description; MSDS. http://www.gulbrandsen.com/pdf/ACHspec.pdf 2000.
Puerto Rico Aqueduct and Sewer Authority (PRASA), 2005. NPDES Permit Renewal
Application: Guaynabo Water Treatment Plant (NPDES # PR0022438), December 14, 2005.
DCN EPA-HQ-OW-2004-0035-01017.
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PRASA, 2007. Response from Guaynabo Water Treatment Plant PWSID PR0002591 in
Response to the U.S. EPA Drinking Water Treatment Questionnaire. March 29, 2007. DCN
EPA-HQ-OW-2004-0035-DW03622.
Puerto Rico Department of Health (PRDOH), 2004. State Administrative Order 2004-403-04.
Order to establish requirements and procedures to endorse new or existing public water systems
that projects to return specific recycle flows within the system's treatment process. San Juan, PR.
June 8, 2004.
Securities Industry and Financial Markets Association (SIFMA). Data: Representative Municipal
Bond Yields, http://www.investinginbonds.com/marketatagl ance.asp?catid=32, accessed
7/23/2007.
U.S. EPA, 1993. Large Water System Byproducts Treatment and Disposal Cost Document.
EPA-811/D-93-002. 1993.
U.S. EPA, 1996. NPDES Permit Writer's Manual, EPA-833-B-96-003. December.
http://cfpub.epa.gov/npdes/writermanual.cfm?program id=45.
U.S. Environmental Protection Agency. 2000. Wastewater Technology Fact Sheet:
Dechlorination. EPA 832-F-00-022.
U.S. EPA, 2002. Filter Backwash Recycling Rule: A Rule Summary for Systems (EPA 816-R-
02-013), Office of Water, August 2002.
U.S. Environmental Protection Agency. 2006. Small Drinking Water Systems Variances -
Revision of Existing National-Level Affordability Methodology and Methodology To Identify
Variance Technologies That Are Protective of Public Health. Federal Register, Vol. 71, No. 41,
Page 1067 I.March 2, 2006.
U.S. EPA, 2006. Toxic Weighting Factor Development in Support of the CWA 304(m) Planning
Process. Washington, DC. (June).
U.S. EPA, 2006b. Drinking Water Treatment Questionnaire Survey Sample Frame. December
2006.
U.S. EPA, 2007. Development Document for the Final Effluent Limitations Guidelines and New
Source Performance Standards for the Concentrated Aquatic Animal Production Point Source
Category (Revised August 2004). EPA-821-R-04-012. Retrieved on October 5, 2007 from
http://www.epa.gov/guide/aquaculture/add/appendixe 508.pdf Appendix E.
U.S. EPA Region 2, 2002. Statement of Basis Draft NPDES Permit to Discharge into the Waters
of the United States, DCN DW01039.
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Appendix A
LIST OF POLLUTANTS "BELIEVED ABSENT" FROM DECEMBER 14, 2005 PERMIT
APPLICATION
-------
Appendix A: List of Pollutants "Believed Absent" from December 14, 2005 Permit
Application
All GC/MS Semivolatile Compounds
All GC/MS Volatile Compounds
All Pesticides
Aluminum
Antimony
Barium
Beryllium
Boron
Bromide
Cadmium
Chromium
Cobalt
Cyanide
Dioxin
Fecal Coliform
Magnesium
Molybdenum
Nickel
Nitrate-Nitrite
Phenols
Radioactivity (all types)
Radium
Selenium
Silver
Sulfate
Sulfite
Thallium
Tin
Titanium
Total Organic Nitrogen
A-l
-------
Appendix B
CALCULATION OF POLLUTANT LOADINGS USING DMR DATA
-------
Appendix B: Calculation Of Pollutant Loadings Using DMR Data
I. EPA received DMR data for 2003, 2004, and 2005 for the Guaynabo, PR Drinking Water
Treatment Facility (Guaynabo WTP). EPA entered the DMR data into a Microsoft Access
database. EPA cut and pasted information from this database to calculate loads in Excel. The
worksheet named "DMR Data" contains the data cut and pasted from the DMR database.
II. EPA determined a list of pollutants of concern. See Section 3.
III. EPA calculated loads for pollutants of concern in the worksheet "POC Load Calcs" in
columns labeled A - K. The text below describes assumptions and calculation steps.
Column A: First calculated value.
1. Non-detect (ND) values. Using the hybrid approach, if a value is ND, then assume it = 1/2 x
DL if the pollutant is detected at all during that calendar year. Use 0 if pollutant is not detected at
all during that calendar year.
For any POCs, were all values non-detect for an entire calendar year? Yes: SETTLEABLE
SOLIDS ONLY. Set ND values = 0 for appropriate years of SETTLABLE SOLIDS.
Otherwise, ND values = 1/2 x DL.
2. Negative values. -2 indicates that sampling results were not received. For calculation
purposes, the concentration field is temporarily set to "ave," which will be changed in Column C.
3. Missing months. For calculation purposes, the concentration field is temporarily set to "ave,"
which will be changed in Column C.
Column B: Calculate annual average for each pollutant.
Column C: Insert calculated average for missing months and months with negative
concentration values.
For TDS: Missing data for all of 2005. Use 2004 average for all of 2005 because it is more
current than 2003 data and better reflects current practices.
Column D: Convert units. If units are ug/L, set = to 10A-3 mg/L. For Turbidity, set TSS
Cone (mg/L) = 1.5 x NTU Turbidity.
Column E: Flow from the "Flow Data" sheet.
Column F: # Days/Month = the number of days in each month of the year (omitting leap
year, because looking to represent a typical year).
Column G: Calculate Ibs/month
Ibs/yr = [Flow (Mgal/Day)] x [Cone (mg/L)] x [3.785 x 10A6 L/Mgal] x [days per month] x
[2.205 x 10A(-6)lbs/mg]
Ibs/yr =[Column D] x [Column E] x [3.785] x [Column F] x [2.205]
Column H: Calculate Ibs/year = Sum the Ibs/month for the 12 months.
Column I: 3 Sig Figs = round to nearest 3 significant figures = LBS/YR w/ sig figs = Final
Annual Load
Column J: TWFs, data entered from the 304m Project's PCSLoads2004 v2.mdb.
B-l
-------
Column K: Calculated Annual TWPE
Calculated Annual TWPE = TWF x lbs/yr
Calculated Annual TWPE = [J] x [I]
B-2
-------
From DMR
PCSID
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
From DMR
Pollutant Name (Same
as Pram Except TSS)c
Ammonia &
Ammonium - Total
Ammonia &
Ammonium - Total
Ammonia &
Ammonium - Total
Ammonia &
Ammonium - Total
Ammonia &
Ammonium - Total
Ammonia &
Ammonium - Total
Ammonia &
Ammonium - Total
Ammonia &
Ammonium - Total
Ammonia &
Ammonium - Total
Ammonia &
Ammonium - Total
Ammonia &
Ammonium - Total
Ammonia &
Ammonium - Total
Total
Ammonia &
Ammonium - Total
Ammonia &
Ammonium - Total
Ammonia &
Ammonium - Total
Ammonia &
Ammonium - Total
Ammonia &
Ammonium - Total
Ammonia &
Ammonium - Total
From
DMR
Year
2003
2003
2003
2003
2003
2003
2003
2003
2003
2003
2003
2003 Total
2004
2004
2004
2004
2004
2004
From
DMR
Month
1
2
3
4
5
6
7
8
9
10
11
12
1
2
3
4
5
6
From
DMR
Max Cone
1.24
0.24
0.18
0.14
1.56
0.1
0.32
0.16
0.08
0.129
0.1
0.14
0.1
0.107
0.251
0.187
0.446
FROM
DMR
ND?
FALSE
FALSE
FALSE
FALSE
FALSE
TRUE
FALSE
FALSE
TRUE
FALSE
TRUE
FALSE
TRUE
FALSE
FALSE
FALSE
FALSE
From
DMR
Cone
Units
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
Logic Test"
Frequency
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Logic
Test"
Sample
type
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Logic Test"
Data
Comment
Logic
Test"
Tempor
Cone
1.24
0.24
0.18
0.14
1.56
0.05
0.32
ave
0.16
0.04
0.129
0.05
0.14
0.05
0.107
0.251
0.187
0.446
Calculate
Avg
Annual
Cone
Tempor
Cone
0.374
0.374
0.374
0.374
0.374
0.374
0.374
0.374
0.374
0.374
0.374
0.374
0.177
0.177
0.177
0.177
0.177
0.177
Logic
Test"
Tempor
Cone
1.240
0.240
0.180
0.140
1.560
0.050
0.320
0.374
0.160
0.040
0.129
0.050
0.140
0.050
0.107
0.251
0.187
0.446
Fill in
Blanks
Cone for
Calc
(mg/L)
1.240
0.240
0.180
0.140
1.560
0.050
0.320
0.374
0.160
0.040
0.129
0.050
0.140
0.050
0.107
0.251
0.187
0.446
Pasted
from
DMR
AveQ
(MGD)
0.88
0.93
0.87
1.03
1.21
0.65
1.52
1.12
1.15
1.3
1.1
1.69
13.45
13.45
1.47
1.54
1.64
1.72
0.9
1.77
Data
Entered
Days Per
Month
31
28
31
30
31
30
31
31
30
31
30
31
31
28
31
30
31
30
Calculated
Monthly
Load
(Ibs/yr)
282
52
41
36
488
8
126
108
46
13
36
22
1,259
1,259
53
18
45
108
44
198
Calculated
Annual Load
(Ibs/yr)
1,259
3 Sig Figs
Annual Load
(Ibs/yr)
1,260
1,260
1,260
Data Entered
TWF
0.00135
0.00135
0.00135
0.00135
0.00135
0.00135
0.00135
0.00135
0.00135
0.00135
0.00135
0.00135
0.00135
0.00135
0.00135
0.00135
0.00135
0.00135
Calculated
TWPE
(Ib-eq/yr)
1.70
1.70
1.70
-------
From DMR
PCSID
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
From DMR
Pollutant Name (Same
as Pram Except TSS)c
Ammonia &
Ammonium - Total
Ammonia &
Ammonium - Total
Ammonia &
Ammonium - Total
Ammonia &
Ammonium - Total
Ammonia &
Ammonium - Total
Ammonia &
Ammonium - Total
Total
Ammonia &
Ammonium - Total
Ammonia &
Ammonium - Total
Ammonia &
Ammonium - Total
Ammonia &
Ammonium - Total
Ammonia &
Ammonium - Total
Ammonia &
Ammonium - Total
Ammonia &
Ammonium - Total
Ammonia &
Ammonium - Total
Ammonia &
Ammonium - Total
Ammonia &
Ammonium - Total
Ammonia &
Ammonium - Total
Ammonia &
Ammonium - Total
From
DMR
Year
2004
2004
2004
2004
2004
2004 Total
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005 Total
From
DMR
Month
7
8
9
10
11
12
1
2
3
4
5
6
7
8
9
10
11
12
From
DMR
Max Cone
0.137
-2
-2
-2
0.1
0.32
0.71
0.12
0.65
0.1
0.1
0.38
0.1
0.1
0.25
0.22
0.13
0.265
FROM
DMR
ND?
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
TRUE
TRUE
FALSE
TRUE
TRUE
FALSE
FALSE
FALSE
From
DMR
Cone
Units
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
Logic Test"
Frequency
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Logic
Test"
Sample
type
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Logic Test"
Data
Comment
Not Reported:
CODES
Not Reported:
CODES
Not Reported:
CODES
Logic
Test"
Tempor
Cone
0.137
ave
ave
ave
ave
0.1
0.32
0.71
0.12
0.65
0.05
0.05
0.38
0.05
0.05
0.25
0.22
0.13
Calculate
Avg
Annual
Cone
Tempor
Cone
0.177
0.177
0.177
0.177
0.177
0.177
0.248
0.248
0.248
0.248
0.248
0.248
0.248
0.248
0.248
0.248
0.248
0.248
Logic
Test"
Tempor
Cone
0.137
0.177
0.177
0.177
0.177
0.100
0.320
0.710
0.120
0.650
0.050
0.050
0.380
0.050
0.050
0.250
0.220
0.130
Fill in
Blanks
Cone for
Calc
(mg/L)
0.137
0.177
0.177
0.177
0.177
0.100
0.320
0.710
0.120
0.650
0.050
0.050
0.380
0.050
0.050
0.250
0.220
0.130
Pasted
from
DMR
AveQ
(MGD)
1.42
1.54
1.56
1.62
1.42
1.85
18.45
18.45
1.75
2.29
1.66
1.78
1.51
1.89
1.65
1.27
1.3
1.72
2.13
2.17
21.12
Data
Entered
Days Per
Month
31
31
30
31
30
31
31
28
31
30
31
30
31
31
30
31
30
31
Calculated
Monthly
Load
(Ibs/yr)
50
71
69
74
63
48
841
841
145
380
52
290
20
24
162
16
16
111
117
73
1,406
Calculated
Annual Load
(Ibs/yr)
841
1,406
3 Sig Figs
Annual Load
(Ibs/yr)
841
841
841
1,410
1,410
Data Entered
TWF
0.00135
0.00135
0.00135
0.00135
0.00135
0.00135
0.00135
0.00135
0.00135
0.00135
0.00135
0.00135
0.00135
0.00135
0.00135
0.00135
0.00135
0.00135
Calculated
TWPE
(Ib-eq/yr)
1.13
1.13
1.13
1.90
1.90
-------
From DMR
PCSID
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
From DMR
Pollutant Name (Same
as Pram Except TSS)c
Ammonia &
Ammonium - Total
Total
Arsenic, Total (as As)
Arsenic, Total (as As)
Arsenic, Total (as As)
Arsenic, Total (as As)
Arsenic, Total (as As)
Arsenic, Total (as As)
Arsenic, Total (as As)
Arsenic, Total (as As)
Arsenic, Total (as As)
Arsenic, Total (as As)
Arsenic, Total (as As)
Arsenic, Total (as As)
Total
Arsenic, Total (as As)
Arsenic, Total (as As)
Arsenic, Total (as As)
Arsenic, Total (as As)
Arsenic, Total (as As)
From
DMR
Year
2003
2003
2003
2003
2003
2003
2003
2003
2003
2003
2003
2003 Total
2004
2004
2004
2004
2004
From
DMR
Month
1
2
3
4
5
6
7
8
9
10
11
12
1
2
3
4
5
From
DMR
Max Cone
43
1.1
0.6
0.68
7.4
0.4
0.4
0.4
17.1
0.14
0.7
-2
0.4
0.4
0.4
0.4
FROM
DMR
ND?
FALSE
FALSE
FALSE
FALSE
FALSE
TRUE
TRUE
FALSE
FALSE
TRUE
FALSE
FALSE
TRUE
TRUE
TRUE
TRUE
From
DMR
Cone
Units
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
Logic Test"
Frequency
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Logic
Test"
Sample
type
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Logic Test"
Data
Comment
Not Reported:
CODES
Logic
Test"
Tempor
Cone
43
1.1
0.6
0.68
7.4
0.2
0.2
ave
0.4
17.1
0.07
0.7
ave
0.2
0.2
0.2
0.2
Calculate
Avg
Annual
Cone
Tempor
Cone
6.50
6.50
6.50
6.50
6.50
6.50
6.50
6.50
6.50
6.50
6.50
6.50
1.54
1.54
1.54
1.54
1.54
Logic
Test"
Tempor
Cone
43.000
1.100
0.600
0.680
7.400
0.200
0.200
6.495
0.400
17.100
0.070
0.700
1.543
0.200
0.200
0.200
0.200
Fill in
Blanks
Cone for
Calc
(mg/L)
0.043
0.001
0.001
0.001
0.007
0.000
0.000
0.006
0.000
0.017
0.000
0.001
0.002
0.000
0.000
0.000
0.000
Pasted
from
DMR
AveQ
(MGD)
21.12
0.88
0.93
0.87
1.03
1.21
0.65
1.52
1.12
1.15
1.3
1.1
1.69
13.45
13.45
1.47
1.54
1.64
1.72
0.9
Data
Entered
Days Per
Month
31
28
31
30
31
30
31
31
30
31
30
31
31
28
31
30
31
Calculated
Monthly
Load
(Ibs/yr)
1,406
10
0
0
0
2
0
0
9
0
6
0
0
21
21
1
0
0
0
0
Calculated
Annual Load
(Ibs/yr)
20.8
3 Sig Figs
Annual Load
(Ibs/yr)
1,410
20.8
20.8
20.8
Data Entered
TWF
4.04133
4.04133
4.04133
4.04133
4.04133
4.04133
4.04133
4.04133
4.04133
4.04133
4.04133
4.04133
4.04133
4.04133
4.04133
4.04133
4.04133
Calculated
TWPE
(Ib-eq/yr)
1.90
84.06
84.06
84.06
-------
From DMR
PCSID
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
From DMR
Pollutant Name (Same
as Pram Except TSS)c
Arsenic, Total (as As)
Arsenic, Total (as As)
Arsenic, Total (as As)
Arsenic, Total (as As)
Arsenic, Total (as As)
Arsenic, Total (as As)
Arsenic, Total (as As)
Total
Arsenic, Total (as As)
Arsenic, Total (as As)
Arsenic, Total (as As)
Arsenic, Total (as As)
Arsenic, Total (as As)
Arsenic, Total (as As)
Arsenic, Total (as As)
Arsenic, Total (as As)
Arsenic, Total (as As)
Arsenic, Total (as As)
Arsenic, Total (as As)
Arsenic, Total (as As)
From
DMR
Year
2004
2004
2004
2004
2004
2004
2004 Total
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
From
DMR
Month
6
7
8
9
10
11
12
1
2
3
4
5
6
7
8
9
10
11
12
From
DMR
Max Cone
5
5
-2
-2
-2
5
6
13
5
5
5
5
0.48
-2
-2
-2
3
3
FROM
DMR
ND?
TRUE
TRUE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
TRUE
TRUE
TRUE
TRUE
FALSE
FALSE
FALSE
FALSE
TRUE
TRUE
From
DMR
Cone
Units
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
Logic Test"
Frequency
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Logic
Test"
Sample
type
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Logic Test"
Data
Comment
Not Reported:
CODES
Not Reported:
CODES
Not Reported:
CODES
Not Reported:
CODES
Not Reported:
CODES
Not Reported:
CODES
Logic
Test"
Tempor
Cone
2.5
2.5
ave
ave
ave
ave
5
6
13
2.5
2.5
2.5
2.5
0.48
ave
ave
ave
1.5
1.5
Calculate
Avg
Annual
Cone
Tempor
Cone
1.54
1.54
1.54
1.54
1.54
1.54
1.54
3.61
3.61
3.61
3.61
3.61
3.61
3.61
3.61
3.61
3.61
3.61
3.61
Logic
Test"
Tempor
Cone
2.500
2.500
1.543
1.543
1.543
1.543
5.000
6.000
13.000
2.500
2.500
2.500
2.500
0.480
3.609
3.609
3.609
1.500
1.500
Fill in
Blanks
Cone for
Calc
(mg/L)
0.003
0.003
0.002
0.002
0.002
0.002
0.005
0.006
0.013
0.003
0.003
0.003
0.003
0.000
0.004
0.004
0.004
0.002
0.002
Pasted
from
DMR
AveQ
(MGD)
1.77
1.42
1.54
1.56
1.62
1.42
1.85
18.45
18.45
1.75
2.29
1.66
1.78
1.51
1.89
1.65
1.27
1.3
1.72
2.13
2.17
Data
Entered
Days Per
Month
30
31
31
30
31
30
31
31
28
31
30
31
30
31
31
30
31
30
31
Calculated
Monthly
Load
(Ibs/yr)
1
1
1
1
1
1
2
8
8
3
7
1
1
1
1
0
1
1
9
1
1
Calculated
Annual Load
(Ibs/yr)
7.71
19.8
3 Sig Figs
Annual Load
(Ibs/yr)
7.71
7.71
7.71
19.8
Data Entered
TWF
4.04133
4.04133
4.04133
4.04133
4.04133
4.04133
4.04133
4.04133
4.04133
4.04133
4.04133
4.04133
4.04133
4.04133
4.04133
4.04133
4.04133
4.04133
4.04133
Calculated
TWPE
(Ib-eq/yr)
31.16
31.16
31.16
80.02
-------
From DMR
PCSID
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
From DMR
Pollutant Name (Same
as Pram Except TSS)c
Arsenic, Total (as As)
Total
BOD, 5-day (20 Deg.
C)
BOD, 5-day (20 Deg.
C)
BOD, 5-day (20 Deg.
C)
BOD, 5-day (20 Deg.
C)
BOD, 5-day (20 Deg.
C)
BOD, 5-day (20 Deg.
C)
BOD, 5-day (20 Deg.
C)
BOD, 5-day (20 Deg.
C)
BOD, 5-day (20 Deg.
C)
BOD, 5-day (20 Deg.
C)
BOD, 5-day (20 Deg.
C)
BOD, 5-day (20 Deg.
C) Total
BOD, 5-day (20 Deg.
C)
BOD, 5-day (20 Deg.
C)
BOD, 5-day (20 Deg.
C)
BOD, 5-day (20 Deg.
C)
BOD, 5-day (20 Deg.
C)
From
DMR
Year
2005 Total
2003
2003
2003
2003
2003
2003
2003
2003
2003
2003
2003
2003 Total
2004
2004
2004
2004
2004
From
DMR
Month
1
2
3
4
5
6
7
8
9
10
11
12
1
2
3
4
5
From
DMR
Max Cone
5.3
2
3.3
2
17
2
2
2
2.8
6.8
2
3.4
7.8
2
2
2
FROM
DMR
ND?
FALSE
TRUE
FALSE
TRUE
FALSE
TRUE
TRUE
TRUE
FALSE
FALSE
TRUE
FALSE
FALSE
TRUE
TRUE
TRUE
From
DMR
Cone
Units
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
Logic Test"
Frequency
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Twice/mont
h
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Logic
Test"
Sample
type
Grab
Grab
Grab
Composit
e
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Logic Test"
Data
Comment
Logic
Test"
Tempor
Cone
5.3
1
3.3
1
17
1
1
ave
1
2.8
6.8
1
3.4
7.8
1
1
1
Calculate
Avg
Annual
Cone
Tempor
Cone
3.75
3.75
3.75
3.75
3.75
3.75
3.75
3.75
3.75
3.75
3.75
3.75
2.40
2.40
2.40
2.40
2.40
Logic
Test"
Tempor
Cone
5.300
1.000
3.300
1.000
17.000
1.000
1.000
3.745
1.000
2.800
6.800
1.000
3.400
7.800
1.000
1.000
1.000
Fill in
Blanks
Cone for
Calc
(mg/L)
5.300
1.000
3.300
1.000
17.000
1.000
1.000
3.745
1.000
2.800
6.800
1.000
3.400
7.800
1.000
1.000
1.000
Pasted
from
DMR
AveQ
(MGD)
21.12
21.12
0.88
0.93
0.87
1.03
1.21
0.65
1.52
1.12
1.15
1.3
1.1
1.69
13.45
13.45
1.47
1.54
1.64
1.72
0.9
Data
Entered
Days Per
Month
31
28
31
30
31
30
31
31
30
31
30
31
31
28
31
30
31
Calculated
Monthly
Load
(Ibs/yr)
20
20
1,207
217
743
258
5,322
163
393
1,085
288
942
1,873
437
12,928
12,928
1,293
2,807
424
431
233
Calculated
Annual Load
(Ibs/yr)
12,928
3 Sig Figs
Annual Load
(Ibs/yr)
19.8
19.8
12,900
12,900
12,900
Data Entered
TWF
Calculated
TWPE
(Ib-eq/yr)
80.02
80.02
-
-
-------
From DMR
PCSID
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
From DMR
Pollutant Name (Same
as Pram Except TSS)c
BOD, 5-day (20 Deg.
C)
BOD, 5-day (20 Deg.
C)
BOD, 5-day (20 Deg.
C)
BOD, 5-day (20 Deg.
C)
BOD, 5-day (20 Deg.
C)
BOD, 5-day (20 Deg.
C)
BOD, 5-day (20 Deg.
C) Total
BOD, 5-day (20 Deg.
C)
BOD, 5-day (20 Deg.
C)
BOD, 5-day (20 Deg.
C)
BOD, 5-day (20 Deg.
C)
BOD, 5-day (20 Deg.
C)
BOD, 5-day (20 Deg.
C)
BOD, 5-day (20 Deg.
C)
BOD, 5-day (20 Deg.
C)
BOD, 5-day (20 Deg.
C)
BOD, 5-day (20 Deg.
C)
BOD, 5-day (20 Deg.
C)
BOD, 5-day (20 Deg.
C)
From
DMR
Year
2004
2004
2004
2004
2004
2004
2004 Total
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
From
DMR
Month
6
7
8
9
10
11
12
1
2
3
4
5
6
7
8
9
10
11
12
From
DMR
Max Cone
2
2
-2
-2
-2
3
2
8.7
2
4
2
2
2
2.4
2
4.5
2
2
FROM
DMR
ND?
TRUE
TRUE
FALSE
FALSE
FALSE
FALSE
TRUE
FALSE
TRUE
FALSE
TRUE
TRUE
TRUE
FALSE
TRUE
FALSE
TRUE
TRUE
From
DMR
Cone
Units
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
Logic Test"
Frequency
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Logic
Test"
Sample
type
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Logic Test"
Data
Comment
Not Reported:
CODES
Not Reported:
CODES
Not Reported:
CODES
Logic
Test"
Tempor
Cone
1
1
ave
ave
ave
ave
3
1
8.7
1
4
1
1
1
2.4
1
4.5
1
1
Calculate
Avg
Annual
Cone
Tempor
Cone
2.40
2.40
2.40
2.40
2.40
2.40
2.40
2.30
2.30
2.30
2.30
2.30
2.30
2.30
2.30
2.30
2.30
2.30
2.30
Logic
Test"
Tempor
Cone
1.000
1.000
2.400
2.400
2.400
2.400
3.000
1.000
8.700
1.000
4.000
1.000
1.000
1.000
2.400
1.000
4.500
1.000
1.000
Fill in
Blanks
Cone for
Calc
(mg/L)
1.000
1.000
2.400
2.400
2.400
2.400
3.000
1.000
8.700
1.000
4.000
1.000
1.000
1.000
2.400
1.000
4.500
1.000
1.000
Pasted
from
DMR
AveQ
(MGD)
1.77
1.42
1.54
1.56
1.62
1.42
1.85
18.45
18.45
1.75
2.29
1.66
1.78
1.51
1.89
1.65
1.27
1.3
1.72
2.13
2.17
Data
Entered
Days Per
Month
30
31
31
30
31
30
31
31
28
31
30
31
30
31
31
30
31
30
31
Calculated
Monthly
Load
(Ibs/yr)
443
367
956
937
1,006
853
1,436
11,187
11,187
453
4,656
429
1,783
391
473
427
789
325
2,003
533
561
Calculated
Annual Load
(Ibs/yr)
11,187
12,823
3 Sig Figs
Annual Load
(Ibs/yr)
11,200
11,200
11,200
12,800
Data Entered
TWF
Calculated
TWPE
(Ib-eq/yr)
-
-
-------
From DMR
PCSID
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
From DMR
Pollutant Name (Same
as Pram Except TSS)c
BOD, 5-day (20 Deg.
C) Total
Chlorine, Total
Residual
Chlorine, Total
Residual
Chlorine, Total
Residual
Chlorine, Total
Residual
Chlorine, Total
Residual
Chlorine, Total
Residual
Chlorine, Total
Residual
Chlorine, Total
Residual
Chlorine, Total
Residual
Chlorine, Total
Residual
Chlorine, Total
Residual
Chlorine, Total
Residual Total
Chlorine, Total
Residual
Chlorine, Total
Residual
Chlorine, Total
Residual
Chlorine, Total
Residual
Chlorine, Total
Residual
From
DMR
Year
2005 Total
2003
2003
2003
2003
2003
2003
2003
2003
2003
2003
2003
2003 Total
2004
2004
2004
2004
2004
From
DMR
Month
1
2
3
4
5
6
7
8
9
10
11
12
1
2
3
4
5
From
DMR
Max Cone
0.9
0.2
0.4
0.2
0.3
0.4
2.2
2.2
2.2
2.2
2.2
1.218182
0.5
1.1
2.2
2.2
2.4
FROM
DMR
ND?
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
From
DMR
Cone
Units
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
Logic Test"
Frequency
Daily
Once/
Month
Daily
Once/
Month
Daily
Twice/mont
h
Daily
Daily
Daily
Daily
Daily
Daily
Daily
Daily
Daily
Daily
Logic
Test"
Sample
type
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Logic Test"
Data
Comment
Logic
Test"
Tempor
Cone
0.9
0.2
0.4
0.2
0.3
0.4
2.2
ave
2.2
2.2
2.2
2.2
0.5
1.1
2.2
2.2
2.4
Calculate
Avg
Annual
Cone
Tempor
Cone
1.22
1.22
1.22
1.22
1.22
1.22
1.22
1.22
1.22
1.22
1.22
1.22
1.70
1.70
1.70
1.70
1.70
Logic
Test"
Tempor
Cone
0.900
0.200
0.400
0.200
0.300
0.400
2.200
1.218
2.200
2.200
2.200
2.200
0.500
1.100
2.200
2.200
2.400
Fill in
Blanks
Cone for
Calc
(mg/L)
0.900
0.200
0.400
0.200
0.300
0.400
2.200
1.218
2.200
2.200
2.200
2.200
0.500
1.100
2.200
2.200
2.400
Pasted
from
DMR
AveQ
(MGD)
21.12
21.12
0.88
0.93
0.87
1.03
1.21
0.65
1.52
1.12
1.15
1.3
1.1
1.69
13.45
13.45
1.47
1.54
1.64
1.72
0.9
Data
Entered
Days Per
Month
31
28
31
30
31
30
31
31
30
31
30
31
31
28
31
30
31
Calculated
Monthly
Load
(Ibs/yr)
12,823
12,823
205
43
90
52
94
65
865
353
633
740
606
962
4,708
4,708
190
396
933
947
559
Calculated
Annual Load
(Ibs/yr)
4,708
3 Sig Figs
Annual Load
(Ibs/yr)
12,800
12,800
4,710
4,710
4,710
Data Entered
TWF
0.509
0.509
0.509
0.509
0.509
0.509
0.509
0.509
0.509
0.509
0.509
0.509
0.509
0.509
0.509
0.509
0.509
Calculated
TWPE
(Ib-eq/yr)
-
-
2,398.15
2,398.15
2,398.15
-------
From DMR
PCSID
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
From DMR
Pollutant Name (Same
as Pram Except TSS)c
Chlorine, Total
Residual
Chlorine, Total
Residual
Chlorine, Total
Residual
Chlorine, Total
Residual
Chlorine, Total
Residual
Chlorine, Total
Residual
Chlorine, Total
Residual Total
Chlorine, Total
Residual
Chlorine, Total
Residual
Chlorine, Total
Residual
Chlorine, Total
Residual
Chlorine, Total
Residual
Chlorine, Total
Residual
Chlorine, Total
Residual
Chlorine, Total
Residual
Chlorine, Total
Residual
Chlorine, Total
Residual
Chlorine, Total
Residual
Chlorine, Total
Residual
From
DMR
Year
2004
2004
2004
2004
2004
2004
2004 Total
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
From
DMR
Month
6
7
8
9
10
11
12
1
2
3
4
5
6
7
8
9
10
11
12
From
DMR
Max Cone
2.2
0.4
2.2
2.2
2.8
0.54
1.703636
2.2
2.2
0.9
2.1
1
1.2
0.6
0.6
0.9
2.2
1.2
2.2
FROM
DMR
ND?
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
From
DMR
Cone
Units
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
Logic Test"
Frequency
Daily
Daily
Daily
Daily
Daily
Daily
Daily
Daily
Daily
Daily
Daily
Daily
Daily
Daily
Daily
Daily
Daily
Daily
Logic
Test"
Sample
type
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Logic Test"
Data
Comment
Logic
Test"
Tempor
Cone
2.2
0.4
ave
2.2
2.2
2.8
0.54
2.2
2.2
0.9
2.1
1
1.2
0.6
0.6
0.9
2.2
1.2
2.2
Calculate
Avg
Annual
Cone
Tempor
Cone
1.70
1.70
1.70
1.70
1.70
1.70
1.70
1.44
1.44
1.44
1.44
1.44
1.44
1.44
1.44
1.44
1.44
1.44
1.44
Logic
Test"
Tempor
Cone
2.200
0.400
1.704
2.200
2.200
2.800
0.540
2.200
2.200
0.900
2.100
1.000
1.200
0.600
0.600
0.900
2.200
1.200
2.200
Fill in
Blanks
Cone for
Calc
(mg/L)
2.200
0.400
1.704
2.200
2.200
2.800
0.540
2.200
2.200
0.900
2.100
1.000
1.200
0.600
0.600
0.900
2.200
1.200
2.200
Pasted
from
DMR
AveQ
(MGD)
1.77
1.42
1.54
1.56
1.62
1.42
1.85
18.45
18.45
1.75
2.29
1.66
1.78
1.51
1.89
1.65
1.27
1.3
1.72
2.13
2.17
Data
Entered
Days Per
Month
30
31
31
30
31
30
31
31
28
31
30
31
30
31
31
30
31
30
31
Calculated
Monthly
Load
(Ibs/yr)
975
147
679
859
922
996
258
7,862
7,862
996
1,177
387
936
391
568
256
197
293
979
640
1,235
Calculated
Annual Load
(Ibs/yr)
7,862
8,055
3 Sig Figs
Annual Load
(Ibs/yr)
7,860
7,860
7,860
8,050
Data Entered
TWF
0.509
0.509
0.509
0.509
0.509
0.509
0.509
0.509
0.509
0.509
0.509
0.509
0.509
0.509
0.509
0.509
0.509
0.509
0.509
Calculated
TWPE
(Ib-eq/yr)
4,002.01
4,002.01
4,002.01
4,098.76
-------
From DMR
PCSID
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
From DMR
Pollutant Name (Same
as Pram Except TSS)c
Chlorine, Total
Residual Total
Copper, Total (as Cu)
Copper, Total (as Cu)
Copper, Total (as Cu)
Copper, Total (as Cu)
Copper, Total (as Cu)
Copper, Total (as Cu)
Copper, Total (as Cu)
Copper, Total (as Cu)
Copper, Total (as Cu)
Copper, Total (as Cu)
Copper, Total (as Cu)
Copper, Total (as Cu)
Total
Copper, Total (as Cu)
Copper, Total (as Cu)
Copper, Total (as Cu)
Copper, Total (as Cu)
Copper, Total (as Cu)
From
DMR
Year
2005 Total
2003
2003
2003
2003
2003
2003
2003
2003
2003
2003
2003
2003 Total
2004
2004
2004
2004
2004
From
DMR
Month
1
2
3
4
5
6
7
8
9
10
11
12
1
2
3
4
5
From
DMR
Max Cone
1.441667
148
22
34
2.8
759
18
44
48
123
10.3
20
14
57
29
35
33
FROM
DMR
ND?
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
From
DMR
Cone
Units
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
Logic Test"
Frequency
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Logic
Test"
Sample
type
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Logic Test"
Data
Comment
Logic
Test"
Tempor
Cone
148
22
34
2.8
759
18
44
ave
48
123
10.3
20
14
57
29
35
33
Calculate
Avg
Annual
Cone
Tempor
Cone
111.74
111.74
111.74
111.74
111.74
111.74
111.74
111.74
111.74
111.74
111.74
111.74
22.63
22.63
22.63
22.63
22.63
Logic
Test"
Tempor
Cone
148.000
22.000
34.000
2.800
759.000
18.000
44.000
111.736
48.000
123.000
10.300
20.000
14.000
57.000
29.000
35.000
33.000
Fill in
Blanks
Cone for
Calc
(mg/L)
0.148
0.022
0.034
0.003
0.759
0.018
0.044
0.112
0.048
0.123
0.010
0.020
0.014
0.057
0.029
0.035
0.033
Pasted
from
DMR
AveQ
(MGD)
21.12
21.12
0.88
0.93
0.87
1.03
1.21
0.65
1.52
1.12
1.15
1.3
1.1
1.69
13.45
13.45
1.47
1.54
1.64
1.72
0.9
Data
Entered
Days Per
Month
31
28
31
30
31
30
31
31
30
31
30
31
31
28
31
30
31
Calculated
Monthly
Load
(Ibs/yr)
8,055
8,055
34
5
8
1
238
3
17
32
14
41
3
9
404
404
5
21
12
15
8
Calculated
Annual Load
(Ibs/yr)
404
3 Sig Figs
Annual Load
(Ibs/yr)
8,050
8,050
404
404
404
Data Entered
TWF
0.635
0.635
0.635
0.635
0.635
0.635
0.635
0.635
0.635
0.635
0.635
0.635
0.635
0.635
0.635
0.635
0.635
Calculated
TWPE
(Ib-eq/yr)
4,098.76
4,098.76
256.47
256.47
256.47
-------
From DMR
PCSID
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
From DMR
Pollutant Name (Same
as Pram Except TSS)c
Copper, Total (as Cu)
Copper, Total (as Cu)
Copper, Total (as Cu)
Copper, Total (as Cu)
Copper, Total (as Cu)
Copper, Total (as Cu)
Copper, Total (as Cu)
Total
Copper, Total (as Cu)
Copper, Total (as Cu)
Copper, Total (as Cu)
Copper, Total (as Cu)
Copper, Total (as Cu)
Copper, Total (as Cu)
Copper, Total (as Cu)
Copper, Total (as Cu)
Copper, Total (as Cu)
Copper, Total (as Cu)
Copper, Total (as Cu)
Copper, Total (as Cu)
From
DMR
Year
2004
2004
2004
2004
2004
2004
2004 Total
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
From
DMR
Month
6
7
8
9
10
11
12
1
2
3
4
5
6
7
8
9
10
11
12
From
DMR
Max Cone
5
5
-2
-2
-2
8
5
27
5
91
18
60
63.2
68
40.2
-2
3
32
FROM
DMR
ND?
TRUE
TRUE
FALSE
FALSE
FALSE
FALSE
TRUE
FALSE
TRUE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
TRUE
FALSE
From
DMR
Cone
Units
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
Logic Test"
Frequency
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Logic
Test"
Sample
type
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Logic Test"
Data
Comment
Not Reported:
CODES
Not Reported:
CODES
Not Reported:
CODES
Not Reported:
CODES
Logic
Test"
Tempor
Cone
2.5
2.5
ave
ave
ave
ave
8
2.5
27
2.5
91
18
60
63.2
68
40.2
ave
1.5
32
Calculate
Avg
Annual
Cone
Tempor
Cone
22.63
22.63
22.63
22.63
22.63
22.63
22.63
36.90
36.90
36.90
36.90
36.90
36.90
36.90
36.90
36.90
36.90
36.90
36.90
Logic
Test"
Tempor
Cone
2.500
2.500
22.625
22.625
22.625
22.625
8.000
2.500
27.000
2.500
91.000
18.000
60.000
63.200
68.000
40.200
36.900
1.500
32.000
Fill in
Blanks
Cone for
Calc
(mg/L)
0.003
0.003
0.023
0.023
0.023
0.023
0.008
0.003
0.027
0.003
0.091
0.018
0.060
0.063
0.068
0.040
0.037
0.002
0.032
Pasted
from
DMR
AveQ
(MGD)
1.77
1.42
1.54
1.56
1.62
1.42
1.85
18.45
18.45
1.75
2.29
1.66
1.78
1.51
1.89
1.65
1.27
1.3
1.72
2.13
2.17
Data
Entered
Days Per
Month
30
31
31
30
31
30
31
31
28
31
30
31
30
31
31
30
31
30
31
Calculated
Monthly
Load
(Ibs/yr)
1
1
9
9
9
8
4
102
102
1
14
1
41
7
28
27
22
13
16
1
18
Calculated
Annual Load
(Ibs/yr)
102
190
3 Sig Figs
Annual Load
(Ibs/yr)
102
102
102
190
Data Entered
TWF
0.635
0.635
0.635
0.635
0.635
0.635
0.635
0.635
0.635
0.635
0.635
0.635
0.635
0.635
0.635
0.635
0.635
0.635
0.635
Calculated
TWPE
(Ib-eq/yr)
64.75
64.75
64.75
120.62
-------
From DMR
PCSID
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
From DMR
Pollutant Name (Same
as Pram Except TSS)c
Copper, Total (as Cu)
Total
Lead, Total (as Pb)
Lead, Total (as Pb)
Lead, Total (as Pb)
Lead, Total (as Pb)
Lead, Total (as Pb)
Lead, Total (as Pb)
Lead, Total (as Pb)
Lead, Total (as Pb)
Lead, Total (as Pb)
Lead, Total (as Pb)
Lead, Total (as Pb)
Lead, Total (as Pb)
Total
Lead, Total (as Pb)
Lead, Total (as Pb)
Lead, Total (as Pb)
Lead, Total (as Pb)
Lead, Total (as Pb)
From
DMR
Year
2005 Total
2003
2003
2003
2003
2003
2003
2003
2003
2003
2003
2003
2003 Total
2004
2004
2004
2004
2004
From
DMR
Month
1
2
3
4
5
6
7
8
9
10
11
12
1
2
3
4
5
From
DMR
Max Cone
24.4
-2
3.4
1.3
84.3
1.2
-2
0.7
45.3
11.3
1.4
0.7
0.7
0.7
0.8
0.7
FROM
DMR
ND?
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
TRUE
FALSE
FALSE
FALSE
TRUE
TRUE
TRUE
FALSE
TRUE
From
DMR
Cone
Units
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
Logic Test"
Frequency
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Logic
Test"
Sample
type
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Logic Test"
Data
Comment
Not Reported:
CODES
Not Reported:
CODES
Logic
Test"
Tempor
Cone
24.4
ave
3.4
1.3
84.3
1.2
ave
ave
0.35
45.3
11.3
1.4
0.35
0.35
0.35
0.8
0.35
Calculate
Avg
Annual
Cone
Tempor
Cone
19.22
19.22
19.22
19.22
19.22
19.22
19.22
19.22
19.22
19.22
19.22
19.22
1.53
1.53
1.53
1.53
1.53
Logic
Test"
Tempor
Cone
24.400
19.217
3.400
1.300
84.300
1.200
19.217
19.217
0.350
45.300
11.300
1.400
0.350
0.350
0.350
0.800
0.350
Fill in
Blanks
Cone for
Calc
(mg/L)
0.024
0.019
0.003
0.001
0.084
0.001
0.019
0.019
0.000
0.045
0.011
0.001
0.000
0.000
0.000
0.001
0.000
Pasted
from
DMR
AveQ
(MGD)
21.12
21.12
0.88
0.93
0.87
1.03
1.21
0.65
1.52
1.12
1.15
1.3
1.1
1.69
13.45
13.45
1.47
1.54
1.64
1.72
0.9
Data
Entered
Days Per
Month
31
28
31
30
31
30
31
31
30
31
30
31
31
28
31
30
31
Calculated
Monthly
Load
(Ibs/yr)
190
190
6
4
1
0
26
0
8
6
0
15
3
1
70
70
0
0
0
0
0
Calculated
Annual Load
(Ibs/yr)
69.6
3 Sig Figs
Annual Load
(Ibs/yr)
190
190
69.6
69.6
69.6
Data Entered
TWF
2.24
2.24
224
224
224
2.24
2.24
2.24
224
2.24
2.24
2.24
2.24
2.24
224
2.24
224
Calculated
TWPE
(Ib-eq/yr)
120.62
120.62
155.90
155.90
155.90
-------
From DMR
PCSID
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
From DMR
Pollutant Name (Same
as Pram Except TSS)c
Lead, Total (as Pb)
Lead, Total (as Pb)
Lead, Total (as Pb)
Lead, Total (as Pb)
Lead, Total (as Pb)
Lead, Total (as Pb)
Lead, Total (as Pb)
Total
Lead, Total (as Pb)
Lead, Total (as Pb)
Lead, Total (as Pb)
Lead, Total (as Pb)
Lead, Total (as Pb)
Lead, Total (as Pb)
Lead, Total (as Pb)
Lead, Total (as Pb)
Lead, Total (as Pb)
Lead, Total (as Pb)
Lead, Total (as Pb)
Lead, Total (as Pb)
From
DMR
Year
2004
2004
2004
2004
2004
2004
2004 Total
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
From
DMR
Month
6
7
8
9
10
11
12
1
2
3
4
5
6
7
8
9
10
11
12
From
DMR
Max Cone
5
5
-2
-2
-2
5
5
5
5
11
5
6
2.6
2.4
0.97
-2
1.5
3.8
FROM
DMR
ND?
TRUE
TRUE
FALSE
FALSE
FALSE
FALSE
TRUE
TRUE
TRUE
FALSE
TRUE
FALSE
FALSE
FALSE
TRUE
FALSE
TRUE
FALSE
From
DMR
Cone
Units
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
Logic Test"
Frequency
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Logic
Test"
Sample
type
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Logic Test"
Data
Comment
Not Reported:
CODES
Not Reported:
CODES
Not Reported:
CODES
Not Reported:
CODES
Logic
Test"
Tempor
Cone
2.5
2.5
ave
ave
ave
ave
5
2.5
2.5
2.5
11
2.5
6
2.6
2.4
0.485
ave
0.75
3.8
Calculate
Avg
Annual
Cone
Tempor
Cone
1.53
1.53
1.53
1.53
1.53
1.53
1.53
3.37
3.37
3.37
3.37
3.37
3.37
3.37
3.37
3.37
3.37
3.37
3.37
Logic
Test"
Tempor
Cone
2.500
2.500
1.525
1.525
1.525
1.525
5.000
2.500
2.500
2.500
11.000
2.500
6.000
2.600
2.400
0.485
3.367
0.750
3.800
Fill in
Blanks
Cone for
Calc
(mg/L)
0.003
0.003
0.002
0.002
0.002
0.002
0.005
0.003
0.003
0.003
0.011
0.003
0.006
0.003
0.002
0.000
0.003
0.001
0.004
Pasted
from
DMR
AveQ
(MGD)
1.77
1.42
1.54
1.56
1.62
1.42
1.85
18.45
18.45
1.75
2.29
1.66
1.78
1.51
1.89
1.65
1.27
1.3
1.72
2.13
2.17
Data
Entered
Days Per
Month
30
31
31
30
31
30
31
31
28
31
30
31
30
31
31
30
31
30
31
Calculated
Monthly
Load
(Ibs/yr)
1
1
1
1
1
1
2
8
8
1
1
1
5
1
3
1
1
0
1
0
2
Calculated
Annual Load
(Ibs/yr)
7.64
18.3
3 Sig Figs
Annual Load
(Ibs/yr)
7.64
7.64
7.64
18.3
Data Entered
TWF
2.24
2.24
224
224
2.24
2.24
2.24
2.24
2.24
224
224
224
2.24
2.24
224
224
224
2.24
2.24
Calculated
TWPE
(Ib-eq/yr)
17.11
17.11
17.11
40.99
-------
From DMR
PCSID
From DMR
Pollutant Name (Same
as Pram Except TSS)c
Lead, Total (as Pb)
Total
Manganese, Total (as
Mn)
Manganese, Total (as
Mn)
Manganese, Total (as
Mn)
Manganese, Total (as
Mn)
Manganese, Total (as
Mn)
Manganese, Total (as
Mn)
Manganese, Total (as
Mn)
Manganese, Total (as
Mn)
Manganese, Total (as
Mn)
Manganese, Total (as
Mn)
Manganese, Total (as
Mn)
Manganese, Total (as
Mn) Total
Manganese, Total (as
Mn)
Manganese, Total (as
Mn)
Manganese, Total (as
Mn)
Manganese, Total (as
Mn)
Manganese, Total (as
Mn)
From
DMR
Year
2005 Total
2003
2003
2003
2003
2003
2003
2003
2003
2003
2003
2003
2003 Total
2004
2004
2004
2004
2004
From
DMR
Month
1
2
3
4
5
6
7
8
9
10
11
12
1
2
3
4
5
From
DMR
Max Cone
6430
195
203
242
11700
99
11
36
2790
3.9
51
14
43
8
10
75
FROM
DMR
ND?
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
From
DMR
Cone
Units
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
Logic Test"
Frequency
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Logic
Test"
Sample
type
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Logic Test"
Data
Comment
Logic
Test"
Tempor
Cone
6430
195
203
242
11700
99
11
ave
36
2790
3.9
51
14
43
8
10
75
Calculate
Avg
Annual
Cone
Tempor
Cone
1973.97
1973.97
1973.97
1973.97
1973.97
1973.97
1973.97
1973.97
1973.97
1973.97
1973.97
1978.26
28.50
28.50
28.50
28.50
28.50
Logic
Test"
Tempor
Cone
6,430.000
195.000
203.000
242.000
11,700.00
0
99.000
11.000
1,973.973
36.000
2,790.000
3.900
51.000
14.000
43.000
8.000
10.000
75.000
Fill in
Blanks
Cone for
Calc
(mg/L)
6.430
0.195
0.203
0.242
11.700
0.099
0.011
1.974
0.036
2.790
0.004
0.051
0.014
0.043
0.008
0.010
0.075
Pasted
from
DMR
AveQ
(MGD)
21.12
21.12
0.88
0.93
0.87
1.03
1.21
0.65
1.52
1.12
1.15
1.3
1.1
1.69
13.45
13.45
1.47
1.54
1.64
1.72
0.9
Data
Entered
Days Per
Month
31
28
31
30
31
30
31
31
30
31
30
31
31
28
31
30
31
Calculated
Monthly
Load
(Ibs/yr)
18
18
1,464
42
46
62
3,663
16
4
572
10
938
1
22
6,842
6,842
5
15
3
4
17
Calculated
Annual Load
(Ibs/yr)
6,842
3 Sig Figs
Annual Load
(Ibs/yr)
18.3
18.3
6,840
6,840
6,840
Data Entered
TWF
0.0704
0.0704
0.0704
0.0704
0.0704
0.0704
0.0704
0.0704
0.0704
0.0704
0.0704
0.0704
0.0704
0.0704
0.0704
0.0704
0.0704
Calculated
TWPE
(Ib-eq/yr)
40.99
40.99
481.76
481.76
481.76
-------
From DMR
PCSID
From DMR
Pollutant Name (Same
as Pram Except TSS)c
Manganese, Total (as
Mn)
Manganese, Total (as
Mn)
Manganese, Total (as
Mn)
Manganese, Total (as
Mn)
Manganese, Total (as
Mn)
Manganese, Total (as
Mn)
Manganese, Total (as
Mn) Total
Manganese, Total (as
Mn)
Manganese, Total (as
Mn)
Manganese, Total (as
Mn)
Manganese, Total (as
Mn)
Manganese, Total (as
Mn)
Manganese, Total (as
Mn)
Manganese, Total (as
Mn)
Manganese, Total (as
Mn)
Manganese, Total (as
Mn)
Manganese, Total (as
Mn)
Manganese, Total (as
Mn)
Manganese, Total (as
Mn)
From
DMR
Year
2004
2004
2004
2004
2004
2004
2004 Total
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
From
DMR
Month
6
7
8
9
10
11
12
1
2
3
4
5
6
7
8
9
10
11
12
From
DMR
Max Cone
48
16
-2
-2
-2
14
72
234
23
844
13
18
7.7
4.7
25.6
-2
22
580
FROM
DMR
ND?
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
From
DMR
Cone
Units
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
Logic Test"
Frequency
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Logic
Test"
Sample
type
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Logic Test"
Data
Comment
Not Reported:
CODES
Not Reported:
CODES
Not Reported:
CODES
Not Reported:
CODES
Logic
Test"
Tempor
Cone
48
16
ave
ave
ave
ave
14
72
234
23
844
13
18
7.7
4.7
25.6
ave
22
580
Calculate
Avg
Annual
Cone
Tempor
Cone
28.50
28.50
28.50
28.50
28.50
28.50
28.50
167.64
167.64
167.64
167.64
167.64
167.64
167.64
167.64
167.64
167.64
167.64
167.64
Logic
Test"
Tempor
Cone
48.000
16.000
28.500
28.500
28.500
28.500
14.000
72.000
234.000
23.000
844.000
13.000
18.000
7.700
4.700
25.600
167.636
22.000
580.000
Fill in
Blanks
Cone for
Calc
(mg/L)
0.048
0.016
0.029
0.029
0.029
0.029
0.014
0.072
0.234
0.023
0.844
0.013
0.018
0.008
0.005
0.026
0.168
0.022
0.580
Pasted
from
DMR
AveQ
(MGD)
1.77
1.42
1.54
1.56
1.62
1.42
1.85
18.45
18.45
1.75
2.29
1.66
1.78
1.51
1.89
1.65
1.27
1.3
1.72
2.13
2.17
Data
Entered
Days Per
Month
30
31
31
30
31
30
31
31
28
31
30
31
30
31
31
30
31
30
31
Calculated
Monthly
Load
(Ibs/yr)
21
6
11
11
12
10
7
124
124
33
125
10
376
5.08
8.52
3.29
1.54
8.33
75
12
326
Calculated
Annual Load
(Ibs/yr)
124
983
3 Sig Figs
Annual Load
(Ibs/yr)
124
124
124
983
Data Entered
TWF
0.0704
0.0704
0.0704
0.0704
0.0704
0.0704
0.0704
0.0704
0.0704
0.0704
0.0704
0.0704
0.0704
0.0704
0.0704
0.0704
0.0704
0.0704
0.0704
Calculated
TWPE
(Ib-eq/yr)
8.73
8.73
8.73
69.24
-------
From DMR
PCSID
From DMR
Pollutant Name (Same
as Pram Except TSS)c
Manganese, Total (as
Mn) Total
Mercury, Total (as Hg)
Mercury, Total (as Hg)
Mercury, Total (as Hg)
Mercury, Total (as Hg)
Mercury, Total (as Hg)
Mercury, Total (as Hg)
Mercury, Total (as Hg)
Mercury, Total (as Hg)
Mercury, Total (as Hg)
Mercury, Total (as Hg)
Mercury, Total (as Hg)
Mercury, Total (as Hg)
Total
Mercury, Total (as Hg)
Mercury, Total (as Hg)
Mercury, Total (as Hg)
Mercury, Total (as Hg)
Mercury, Total (as Hg)
From
DMR
Year
2005 Total
2003
2003
2003
2003
2003
2003
2003
2003
2003
2003
2003
2003 Total
2004
2004
2004
2004
2004
From
DMR
Month
1
2
3
4
5
6
7
8
9
10
11
12
1
2
3
4
5
From
DMR
Max Cone
0.2
0.2
0.0287
0.0176
0.0014
0.0942
0.0223
0.0132
0.0352
0.0058
0.011
0.0062
0.0101
0.0064
0.0054
0.049
FROM
DMR
ND?
TRUE
TRUE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
From
DMR
Cone
Units
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
Logic Test"
Frequency
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Logic
Test"
Sample
type
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Logic Test"
Data
Comment
Logic
Test"
Tempor
Cone
0.1
0.1
0.0287
0.0176
0.0014
0.0942
0.0223
ave
0.0132
0.0352
0.0058
0.011
0.0062
0.0101
0.0064
0.0054
0.049
Calculate
Avg
Annual
Cone
Tempor
Cone
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.01
0.01
0.01
0.01
0.01
Logic
Test"
Tempor
Cone
0.100
0.100
0.029
0.018
0.001
0.094
0.022
0.039
0.013
0.035
0.006
0.011
0.006
0.010
0.006
0.005
0.049
Fill in
Blanks
Cone for
Calc
(mg/L)
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
Pasted
from
DMR
AveQ
(MGD)
21.12
21.12
0.88
0.93
0.87
1.03
1.21
0.65
1.52
1.12
1.15
1.3
1.1
1.69
13.45
13.45
1.47
1.54
1.64
1.72
0.9
Data
Entered
Days Per
Month
31
28
31
30
31
30
31
31
30
31
30
31
31
28
31
30
31
Calculated
Monthly
Load
(Ibs/yr)
983
983
0.0228
0.0217
0.0065
0.0045
0.0004
0.0153
0.0088
0.0113
0.0038
0.0118
0.0016
0.0048
0.1134
0.1134
0.0024
0.0036
0.0027
0.0023
0.0114
Calculated
Annual Load
(Ibs/yr)
0.113
3 Sig Figs
Annual Load
(Ibs/yr)
983
983
0.110
0.110
0.110
Data Entered
TWF
117
117
117
117
117
117
117
117
117
117
117
117
117
117
117
117
117
Calculated
TWPE
(Ib-eq/yr)
69.24
69.24
12.88
12.88
12.88
-------
From DMR
PCSID
From DMR
Pollutant Name (Same
as Pram Except TSS)c
Mercury, Total (as Hg)
Mercury, Total (as Hg)
Mercury, Total (as Hg)
Mercury, Total (as Hg)
Mercury, Total (as Hg)
Mercury, Total (as Hg)
Mercury, Total (as Hg)
Total
Mercury, Total (as Hg)
Mercury, Total (as Hg)
Mercury, Total (as Hg)
Mercury, Total (as Hg)
Mercury, Total (as Hg)
Mercury, Total (as Hg)
Mercury, Total (as Hg)
Mercury, Total (as Hg)
Mercury, Total (as Hg)
Mercury, Total (as Hg)
Mercury, Total (as Hg)
Mercury, Total (as Hg)
From
DMR
Year
2004
2004
2004
2004
2004
2004
2004 Total
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
From
DMR
Month
6
7
8
9
10
11
12
1
2
3
4
5
6
7
8
9
10
11
12
From
DMR
Max Cone
0.0126
0.0055
-2
-2
-2
0.0083
0.0005
0.0133
0.0182
0.1278
0.0036
0.0005
0.1418
0.0005
0.0253
0.1679
0.0046
0.0985
FROM
DMR
ND?
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
TRUE
FALSE
FALSE
FALSE
FALSE
TRUE
FALSE
TRUE
FALSE
FALSE
FALSE
FALSE
From
DMR
Cone
Units
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
Logic Test"
Frequency
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Logic
Test"
Sample
type
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Logic Test"
Data
Comment
Not Reported:
CODES
Not Reported:
CODES
Not Reported:
CODES
Logic
Test"
Tempor
Cone
0.0126
0.0055
ave
ave
ave
ave
0.0083
0.00025
0.0133
0.0182
0.1278
0.0036
0.00025
0.1418
0.00025
0.0253
0.1679
0.0046
0.0985
Calculate
Avg
Annual
Cone
Tempor
Cone
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.05
0.05
0.05
0.05
0.05
0.05
0.05
0.05
0.05
0.05
0.05
0.05
Logic
Test"
Tempor
Cone
0.013
0.006
0.013
0.013
0.013
0.013
0.008
0.000
0.013
0.018
0.128
0.004
0.000
0.142
0.000
0.025
0.168
0.005
0.099
Fill in
Blanks
Cone for
Calc
(mg/L)
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
Pasted
from
DMR
AveQ
(MGD)
1.77
1.42
1.54
1.56
1.62
1.42
1.85
18.45
18.45
1.75
2.29
1.66
1.78
1.51
1.89
1.65
1.27
1.3
1.72
2.13
2.17
Data
Entered
Days Per
Month
30
31
31
30
31
30
31
31
28
31
30
31
30
31
31
30
31
30
31
Calculated
Monthly
Load
(Ibs/yr)
0.0056
0.0020
0.0052
0.0051
0.0054
0.0046
0.0040
0.0543
0.0543
0.0001
0.0071
0.0078
0.0570
0.0014
0.0001
0.0605
0.0001
0.0082
0.0747
0.0025
0.0553
Calculated
Annual Load
(Ibs/yr)
0.0543
0.275
3 Sig Figs
Annual Load
(Ibs/yr)
0.0543
0.0543
0.0543
0.275
Data Entered
TWF
117
117
117
117
117
117
117
117
117
117
117
117
117
117
117
117
117
117
117
Calculated
TWPE
(Ib-eq/yr)
6.35
6.35
6.35
32.19
-------
From DMR
PCSID
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
From DMR
Pollutant Name (Same
as Pram Except TSS)c
Mercury, Total (as Hg)
Total
Phosphorus, Total (As
P)
Phosphorus, Total (As
P)
Phosphorus, Total (As
P)
Phosphorus, Total (As
P)
Phosphorus, Total (As
P)
Phosphorus, Total (As
P)
Phosphorus, Total (As
P)
Phosphorus, Total (As
P)
Phosphorus, Total (As
P)
Phosphorus, Total (As
P)
Phosphorus, Total (As
P)
Phosphorus, Total (As
P)
Phosphorus, Total (As
P)
Phosphorus, Total (As
P)
Phosphorus, Total (As
P)
Phosphorus, Total (As
P)
Phosphorus, Total (As
P)
Phosphorus, Total (As
P)
From
DMR
Year
2005 Total
2003
2003
2003
2003
2003
2003
2003
2003
2003
2003
2003
2004
2004
2004
2004
2004
2004
2004
From
DMR
Month
1
2
3
4
5
6
7
9
10
11
12
1
2
3
4
5
6
7
From
DMR
Max Cone
12.8
0.08
0.077
0.085
10.055
0.016
0.01
0.01
0.435
0.01
0.014
0.049
0.047
0.032
0.016
0.021
0.065
0.1
FROM
DMR
ND?
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
TRUE
TRUE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
From
DMR
Cone
Units
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
Logic Test"
Frequency
Logic
Test"
Sample
type
Logic Test"
Data
Comment
Logic
Test"
Tempor
Cone
12.8
0.08
0.077
0.085
10.055
0.016
0.005
ave
0.005
0.435
0.01
0.014
0.049
0.047
0.032
0.016
0.021
0.065
0.1
Calculate
Avg
Annual
Cone
Tempor
Cone
2.144
2.144
2.144
2.144
2.144
2.144
2.144
2.144
2.144
2.144
2.144
2.144
0.043
0.043
0.043
0.043
0.043
0.043
0.043
Logic
Test"
Tempor
Cone
12.800
0.080
0.077
0.085
10.055
0.016
0.005
2.144
0.005
0.435
0.010
0.014
0.049
0.047
0.032
0.016
0.021
0.065
0.100
Fill in
Blanks
Cone for
Calc
(mg/L)
12.800
0.080
0.077
0.085
10.055
0.016
0.005
2.144
0.005
0.435
0.010
0.014
0.049
0.047
0.032
0.016
0.021
0.065
0.100
Pasted
from
DMR
AveQ
(MGD)
21.12
21.12
0.88
0.93
0.87
1.03
1.21
0.65
1.52
1.12
1.15
1.3
1.1
1.69
13.45
13.45
1.47
1.54
1.64
1.72
0.9
Data
Entered
Days Per
Month
31
28
31
30
31
30
31
31
30
31
30
31
31
28
31
30
31
30
31
Calculated
Monthly
Load
(Ibs/yr)
0.2748
0.2748
2,914
17
17
22
3,148
3
9
621
1
146
3
6
171
148
12
6
9
28
23
Calculated
Annual Load
(Ibs/yr)
6,901
3 Sig Figs
Annual Load
(Ibs/yr)
0.275
0.275
6,900
Data Entered
TWF
Calculated
TWPE
(Ib-eq/yr)
32.19
32.19
-------
From DMR
PCSID
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
PR0022438
From DMR
Pollutant Name (Same
as Pram Except TSS)c
Phosphorus, Total (As
P)
Phosphorus, Total (As
P)
Phosphorus, Total (As
P)
Phosphorus, Total (As
P)
Phosphorus, Total (As
P)
Phosphorus, Total (As
P)
Phosphorus, Total (As
P)
Phosphorus, Total (As
P)
Phosphorus, Total (As
P)
Phosphorus, Total (As
P)
Phosphorus, Total (As
P)
Phosphorus, Total (As
P)
Phosphorus, Total (As
P)
Phosphorus, Total (As
P)
Phosphorus, Total (As
P)
Phosphorus, Total (As
P)
Solids, Total Dissolved
-180Deg. C
Solids, Total Dissolved
-180Deg. C
From
DMR
Year
2004
2004
2004
2004
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2003
2003
From
DMR
Month
9
10
11
12
1
2
3
4
5
6
7
8
9
10
11
12
1
2
From
DMR
Max Cone
-2
-2
-2
0.01
0.09
0.015
0.01
1.588
0.01
0.08
0.006
0.096
0.055
2.558
0.032
0.557
230
230
FROM
DMR
ND?
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
TRUE
FALSE
TRUE
FALSE
TRUE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
From
DMR
Cone
Units
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
Logic Test"
Frequency
Once/
Month
Once/
Month
Logic
Test"
Sample
type
Grab
Grab
Logic Test"
Data
Comment
Logic
Test"
Tempor
Cone
ave
ave
ave
ave
0.01
0.09
0.015
0.005
1.588
0.005
0.08
0.003
0.096
0.055
2.558
0.032
0.557
230
230
Calculate
Avg
Annual
Cone
Tempor
Cone
0.043
0.043
0.043
0.043
0.043
0.424
0.195
0.195
0.195
0.195
0.195
0.195
0.195
0.195
0.195
0.195
0.195
196.67
196.67
Logic
Test"
Tempor
Cone
0.043
0.043
0.043
0.043
0.010
0.090
0.015
0.005
1.588
0.005
0.080
0.003
0.096
0.055
2.558
0.032
0.557
230.000
230.000
Fill in
Blanks
Cone for
Calc
(mg/L)
0.043
0.043
0.043
0.043
0.010
0.090
0.015
0.005
1.588
0.005
0.080
0.003
0.096
0.055
2.558
0.032
0.557
230.000
230.000
Pasted
from
DMR
AveQ
(MGD)
1.77
1.42
1.54
1.56
1.62
1.42
1.85
18.45
18.45
1.75
2.29
1.66
1.78
1.51
1.89
1.65
1.27
0.88
0.93
Data
Entered
Days Per
Month
31
30
31
30
31
31
28
31
30
31
30
31
31
30
31
30
31
31
28
Calculated
Monthly
Load
(Ibs/yr)
19
15
17
17
4
33
6
24
7,336
9
46
1
44
21
1,251
13
183
Average
52,366
49,985
Calculated
Annual Load
(Ibs/yr)
190
8,961
5,351
3 Sig Figs
Annual Load
(Ibs/yr)
190
8,960
5,350
Data Entered
TWF
Calculated
TWPE
(Ib-eq/yr)
-------
From DMR
PCSID
From DMR
Pollutant Name (Same
as Pram Except TSS)c
Solids, Total Dissolved
-180Deg. C
Solids, Total Dissolved
-180Deg. C
Solids, Total Dissolved
-180Deg. C
Solids, Total Dissolved
-180Deg. C
Solids, Total Dissolved
- 180 Deg. C
Solids, Total Dissolved
-180Deg. C
Solids, Total Dissolved
- 180 Deg. C
Solids, Total Dissolved
-180Deg. C
Solids, Total Dissolved
- 180 Deg. C
Solids, Total Dissolved
- 1 80 Deg. C Total
Solids, Total Dissolved
- 180 Deg. C
Solids, Total Dissolved
- 180 Deg. C
Solids, Total Dissolved
- 180 Deg. C
Solids, Total Dissolved
- 180 Deg. C
Solids, Total Dissolved
- 180 Deg. C
Solids, Total Dissolved
- 180 Deg. C
Solids, Total Dissolved
- 180 Deg. C
Solids, Total Dissolved
- 180 Deg. C
From
DMR
Year
2003
2003
2003
2003
2003
2003
2003
2003
2003
2003 Total
2004
2004
2004
2004
2004
2004
2004
2004
From
DMR
Month
3
4
5
6
7
8
9
10
11
12
1
2
3
4
5
6
7
8
9
From
DMR
Max Cone
150
260
210
150
140
200
200
-2
-2
180
190
160
180
220
190
-2
-2
FROM
DMR
ND?
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
From
DMR
Cone
Units
MG/L
UG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
Logic Test"
Frequency
Annual
Once/
Month
Annual
Once/
Month
Annual
Annual
Annual
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Logic
Test"
Sample
type
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Logic Test"
Data
Comment
Not Reported:
CODES
Not Reported:
CODE 9
Not Reported:
CODE 9
Not Reported:
CODE 9
Logic
Test"
Tempor
Cone
150
260
210
150
140
ave
200
200
ave
ave
180
190
160
180
220
190
ave
ave
ave
Calculate
Avg
Annual
Cone
Tempor
Cone
196.67
196.67
196.67
196.67
196.67
196.67
196.67
196.67
196.67
196.67
186.67
186.67
186.67
186.67
186.67
186.67
186.67
186.67
186.67
Logic
Test"
Tempor
Cone
150.000
260.000
210.000
150.000
140.000
196.667
200.000
200.000
196.667
196.667
180.000
190.000
160.000
180.000
220.000
190.000
186.667
186.667
186.667
Fill in
Blanks
Cone for
Calc
(mg/L)
150.000
0.260
210.000
150.000
140.000
196.667
200.000
200.000
196.667
196.667
180.000
190.000
160.000
180.000
220.000
190.000
186.667
186.667
186.667
Pasted
from
DMR
AveQ
(MGD)
0.87
1.03
1.21
0.65
1.52
1.12
1.15
1.3
1.1
1.69
13.45
13.45
1.47
1.54
1.64
1.72
0.9
1.77
1.42
1.54
1.56
Data
Entered
Days Per
Month
31
30
31
30
31
31
30
31
30
31
31
28
31
30
31
30
31
31
30
Calculated
Monthly
Load
(Ibs/yr)
33,763
67
65,742
24,412
55,056
56,988
57,587
67,268
54,165
85,991
603,391
603,391
68,458
68,376
67,889
77,517
51,227
84,202
68,579
74,374
72,910
Calculated
Annual Load
(Ibs/yr)
603,391
3 Sig Figs
Annual Load
(Ibs/yr)
603,000
603,000
603,000
Data Entered
TWF
Calculated
TWPE
(Ib-eq/yr)
-
-
-------
From DMR
PCSID
From DMR
Pollutant Name (Same
as Pram Except TSS)c
Solids, Total Dissolved
-180Deg. C
Solids, Total Dissolved
-180Deg. C
Solids, Total Dissolved
-180Deg. C
Solids, Total Dissolved
- 1 80 Deg. C Total
Solids, Total Dissolved
- 180 Deg. C
Solids, Total Dissolved
- 180 Deg. C
Solids, Total Dissolved
- 180 Deg. C
Solids, Total Dissolved
- 180 Deg. C
Solids, Total Dissolved
- 180 Deg. C
Solids, Total Dissolved
- 180 Deg. C
Solids, Total Dissolved
- 180 Deg. C
Solids, Total Dissolved
- 180 Deg. C
Solids, Total Dissolved
- 180 Deg. C
Solids, Total Dissolved
- 180 Deg. C
Solids, Total Dissolved
- 180 Deg. C
Solids, Total Dissolved
- 180 Deg. C
Solids, Total Dissolved
- 1 80 Deg. C Total
TSS (assumed that TSS
mg/l= 1.5 Turbidity
(Ntu)
From
DMR
Year
2004
2004
2004
2004 Total
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005 Total
2003
From
DMR
Month
10
11
12
1
2
3
4
5
6
7
8
9
10
11
12
1
From
DMR
Max Cone
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
-2
1900
FROM
DMR
ND?
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
From
DMR
Cone
Units
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
MG/L
NTU
Logic Test"
Frequency
Once/
Month
Logic
Test"
Sample
type
Grab
Logic Test"
Data
Comment
Not Reported:
CODE 9
Not Reported:
CODE 9
Not Reported:
CODE 9
Not Reported:
CODE 9
Not Reported:
CODE 9
Not Reported:
CODE 9
Not Reported:
CODE 9
Not Reported:
CODE 9
Not Reported:
CODE 9
Not Reported:
CODE 9
Not Reported:
CODE 9
Not Reported:
CODE 9
Not Reported:
CODE 9
Not Reported:
CODE 9
Not Reported:
CODE 9
Logic
Test"
Tempor
Cone
ave
ave
ave
ave
ave
ave
ave
ave
ave
ave
ave
ave
ave
ave
ave
1900
Calculate
Avg
Annual
Cone
Tempor
Cone
186.67
186.67
186.67
186.67
186.67
186.67
186.67
186.67
186.67
186.67
186.67
186.67
186.67
186.67
186.67
577.89
Logic
Test"
Tempor
Cone
186.667
186.667
186.667
186.667
186.667
186.667
186.667
186.667
186.667
186.667
186.667
186.667
186.667
186.667
186.667
1,900.000
Fill in
Blanks
Cone for
Calc
(mg/L)
186.667
186.667
186.667
186.667
186.667
186.667
186.667
186.667
186.667
186.667
186.667
186.667
186.667
186.667
186.667
2,850.00
0
Pasted
from
DMR
AveQ
(MGD)
1.62
1.42
1.85
18.45
18.45
1.75
2.29
1.66
1.78
1.51
1.89
1.65
1.27
1.3
1.72
2.13
2.17
21.12
21.12
0.88
Data
Entered
Days Per
Month
31
30
31
31
28
31
30
31
30
31
31
30
31
30
31
31
Calculated
Monthly
Load
(Ibs/yr)
78,238
66,367
89,346
867,484
867,484
84,516
99,893
80,170
83,192
72,926
88,333
79,687
61,335
60,758
83,068
99,550
104,800
998,228
998,228
648,879
Calculated
Annual Load
(Ibs/yr)
867,484
998,228
3 Sig Figs
Annual Load
(Ibs/yr)
867,000
867,000
867,000
998,000
998,000
998,000
Data Entered
TWF
Calculated
TWPE
(Ib-eq/yr)
-
-
-
-
-------
From DMR
PCSID
From DMR
Pollutant Name (Same
as Pram Except TSS)c
TSS (assumed that TSS
mg/l= 1.5 Turbidity
(Ntu)
TSS (assumed that TSS
mg/l= 1.5 Turbidity
(Ntu)
TSS (assumed that TSS
mg/l= 1.5 Turbidity
(Ntu)
TSS (assumed that TSS
mg/l= 1.5 Turbidity
(Ntu)
TSS (assumed that TSS
mg/l= 1.5 Turbidity
(Ntu)
TSS (assumed that TSS
mg/l= 1.5 Turbidity
(Ntu)
TSS (assumed that TSS
mg/l= 1.5 Turbidity
(Ntu)
TSS (assumed that TSS
mg/l= 1.5 Turbidity
(Ntu)
TSS (assumed that TSS
mg/l= 1.5 Turbidity
(Ntu)
TSS (assumed that TSS
mg/l= 1.5 Turbidity
(Ntu)
TSS (assumed that TSS
mg/l= 1.5 Turbidity
(Ntu)
TSS Total
TSS (assumed that TSS
mg/l= 1.5 Turbidity
(Ntu)
TSS (assumed that TSS
mg/1 =1.5 Turbidity
(Ntu)
From
DMR
Year
2003
2003
2003
2003
2003
2003
2003
2003
2003
2003
2003 Total
2004
2004
From
DMR
Month
2
3
4
5
6
7
8
9
10
11
12
1
2
From
DMR
Max Cone
22
11
11
1600
3.2
0.6
3.3
2800
0.9
4.8
2.6
1.1
FROM
DMR
ND?
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
From
DMR
Cone
Units
NTU
NTU
NTU
NTU
NTU
NTU
NTU
NTU
NTU
NTU
NTU
NTU
NTU
Logic Test"
Frequency
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Twice/mont
h
Once/
Month
Logic
Test"
Sample
type
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Logic Test"
Data
Comment
Logic
Test"
Tempor
Cone
22
11
11
1600
3.2
0.6
ave
3.3
2800
0.9
4.8
2.6
1.1
Calculate
Avg
Annual
Cone
Tempor
Cone
577.89
577.89
577.89
577.89
577.89
577.89
577.89
577.89
577.89
577.89
577.89
2.16
2.16
Logic
Test"
Tempor
Cone
22.000
11.000
11.000
1,600.000
3.200
0.600
577.891
3.300
2,800.000
0.900
4.800
2.600
1.100
Fill in
Blanks
Cone for
Calc
(mg/L)
33.000
16.500
16.500
2,400.00
0
4.800
0.900
866.836
4.950
4,200.00
0
1.350
7.200
3.900
1.650
Pasted
from
DMR
AveQ
(MGD)
0.93
0.87
1.03
1.21
0.65
1.52
1.12
1.15
1.3
1.1
1.69
13.45
13.45
1.47
1.54
Data
Entered
Days Per
Month
28
31
30
31
30
31
31
30
31
30
31
31
28
Calculated
Monthly
Load
(Ibs/yr)
7,172
3,714
4,255
751,334
781
354
251,184
1,425
1,412,631
372
3,148
3,085,249
3,085,249
1,483
594
Calculated
Annual Load
(Ibs/yr)
3,085,249
3 Sig Figs
Annual Load
(Ibs/yr)
3,090,000
3,090,000
3,090,000
Data Entered
TWF
Calculated
TWPE
(Ib-eq/yr)
-
-
-------
From DMR
PCSID
From DMR
Pollutant Name (Same
as Pram Except TSS)c
TSS (assumed that TSS
mg/l= 1.5 Turbidity
(Ntu)
TSS (assumed that TSS
mg/1 =1.5 Turbidity
(Ntu)
TSS (assumed that TSS
mg/l= 1.5 Turbidity
(Ntu)
TSS (assumed that TSS
mg/l= 1.5 Turbidity
(Ntu)
TSS (assumed that TSS
mg/l= 1.5 Turbidity
(Ntu)
TSS (assumed that TSS
mg/l= 1.5 Turbidity
(Ntu)
TSS (assumed that TSS
mg/l= 1.5 Turbidity
(Ntu)
TSS (assumed that TSS
mg/l= 1.5 Turbidity
(Ntu)
TSS (assumed that TSS
mg/l= 1.5 Turbidity
(Ntu)
TSS (assumed that TSS
mg/l= 1.5 Turbidity
(Ntu)
TSS Total
TSS (assumed that TSS
mg/1 =1.5 Turbidity
(Ntu)
TSS (assumed that TSS
mg/l= 1.5 Turbidity
(Ntu)
TSS (assumed that TSS
mg/l= 1.5 Turbidity
(Ntu)
From
DMR
Year
2004
2004
2004
2004
2004
2004
2004
2004
2004
2004 Total
2005
2005
2005
From
DMR
Month
3
4
5
6
7
8
9
10
11
12
1
2
3
From
DMR
Max Cone
0.55
1.4
3.4
3.3
2.1
-2
-2
-2
2.8
11
12
0.7
FROM
DMR
ND?
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
From
DMR
Cone
Units
NTU
NTU
NTU
NTU
NTU
NTU
NTU
NTU
NTU
NTU
NTU
NTU
NTU
Logic Test"
Frequency
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Logic
Test"
Sample
type
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Logic Test"
Data
Comment
Not Reported:
CODES
Not Reported:
CODE 8
Not Reported:
CODES
Logic
Test"
Tempor
Cone
0.55
1.4
3.4
3.3
2.1
ave
ave
ave
ave
2.8
11
12
0.7
Calculate
Avg
Annual
Cone
Tempor
Cone
2.16
2.16
2.16
2.16
2.16
2.16
2.16
2.16
2.16
2.16
140.52
140.52
140.52
Logic
Test"
Tempor
Cone
0.550
1.400
3.400
3.300
2.100
2.156
2.156
2.156
2.156
2.800
11.000
12.000
0.700
Fill in
Blanks
Cone for
Calc
(mg/L)
0.825
2.100
5.100
4.950
3.150
3.234
3.234
3.234
3.234
4.200
16.500
18.000
1.050
Pasted
from
DMR
AveQ
(MGD)
1.64
1.72
0.9
1.77
1.42
1.54
1.56
1.62
1.42
1.85
18.45
18.45
1.75
2.29
1.66
Data
Entered
Days Per
Month
31
30
31
30
31
31
30
31
30
31
31
28
31
Calculated
Monthly
Load
(Ibs/yr)
350
904
1,188
2,194
1,157
1,289
1,263
1,356
1,150
2,010
14,938
14,938
7,471
9,633
451
Calculated
Annual Load
(Ibs/yr)
14,938
3 Sig Figs
Annual Load
(Ibs/yr)
14,900
14,900
14,900
Data Entered
TWF
Calculated
TWPE
(Ib-eq/yr)
-
-
-------
From DMR
PCSID
From DMR
Pollutant Name (Same
as Pram Except TSS)c
TSS (assumed that TSS
mg/l= 1.5 Turbidity
(Ntu)
TSS (assumed that TSS
mg/l= 1.5 Turbidity
(Ntu)
TSS (assumed that TSS
mg/l= 1.5 Turbidity
(Ntu)
TSS (assumed that TSS
mg/l= 1.5 Turbidity
(Ntu)
TSS (assumed that TSS
mg/l= 1.5 Turbidity
(Ntu)
TSS (assumed that TSS
mg/l= 1.5 Turbidity
(Ntu)
TSS (assumed that TSS
mg/l= 1.5 Turbidity
(Ntu)
TSS (assumed that TSS
mg/l= 1.5 Turbidity
(Ntu)
TSS (assumed that TSS
mg/l= 1.5 Turbidity
(Ntu)
TSS Total
Zinc, Total (as Zn)
Zinc, Total (as Zn)
Zinc, Total (as Zn)
Zinc, Total (as Zn)
Zinc, Total (as Zn)
Zinc, Total (as Zn)
From
DMR
Year
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005 Total
2003
2003
2003
2003
2003
2003
From
DMR
Month
4
5
6
7
8
9
10
11
12
1
2
3
4
5
6
From
DMR
Max Cone
4.8
1.1
2.4
4
1.6
16
1500
2.6
130
276
5
50
3.7
664
15
FROM
DMR
ND?
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
TRUE
FALSE
TRUE
FALSE
FALSE
From
DMR
Cone
Units
NTU
NTU
NTU
NTU
NTU
NTU
NTU
NTU
NTU
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
Logic Test"
Frequency
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Logic
Test"
Sample
type
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Logic Test"
Data
Comment
Logic
Test"
Tempor
Cone
4.8
1.1
2.4
4
1.6
16
1500
2.6
130
276
2.5
50
1.85
664
15
Calculate
Avg
Annual
Cone
Tempor
Cone
140.52
140.52
140.52
140.52
140.52
140.52
140.52
140.52
140.52
113.98
113.98
113.98
113.98
113.98
113.98
Logic
Test"
Tempor
Cone
4.800
1.100
2.400
4.000
1.600
16.000
1,500.000
2.600
130.000
276.000
2.500
50.000
1.850
664.000
15.000
Fill in
Blanks
Cone for
Calc
(mg/L)
7.200
1.650
3.600
6.000
2.400
24.000
2,250.00
0
3.900
195.000
0.276
0.003
0.050
0.002
0.664
0.015
Pasted
from
DMR
AveQ
(MGD)
1.78
1.51
1.89
1.65
1.27
1.3
1.72
2.13
2.17
21.12
21.12
0.88
0.93
0.87
1.03
1.21
0.65
Data
Entered
Days Per
Month
30
31
30
31
31
30
31
30
31
31
28
31
30
31
30
Calculated
Monthly
Load
(Ibs/yr)
3,209
645
1,704
2,561
789
7,812
1,001,261
2,080
109,479
1,147,092
1,147,092
63
1
11
0
208
9
Calculated
Annual Load
(Ibs/yr)
1,147,092
3 Sig Figs
Annual Load
(Ibs/yr)
1,150,000
1,150,000
1,150,000
Data Entered
TWF
0.0469
0.0469
0.0469
0.0469
0.0469
0.0469
Calculated
TWPE
(Ib-eq/yr)
-
-
-------
From DMR
PCSID
From DMR
Pollutant Name (Same
as Pram Except TSS)c
Zinc, Total (as Zn)
Zinc, Total (as Zn)
Zinc, Total (as Zn)
Zinc, Total (as Zn)
Zinc, Total (as Zn)
Zinc, Total (as Zn)
Total
Zinc, Total (as Zn)
Zinc, Total (as Zn)
Zinc, Total (as Zn)
Zinc, Total (as Zn)
Zinc, Total (as Zn)
Zinc, Total (as Zn)
Zinc, Total (as Zn)
Zinc, Total (as Zn)
Zinc, Total (as Zn)
Zinc, Total (as Zn)
Zinc, Total (as Zn)
Zinc, Total (as Zn)
Total
From
DMR
Year
2003
2003
2003
2003
2003
2003 Total
2004
2004
2004
2004
2004
2004
2004
2004
2004
2004
2004
2004 Total
From
DMR
Month
7
8
9
10
11
12
1
2
3
4
5
6
7
8
9
10
11
12
From
DMR
Max Cone
5
30
192
7.9
12
114.6
22
113
26
15
20
5
5
-2
-2
-2
5
18.63636
FROM
DMR
ND?
TRUE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
TRUE
TRUE
FALSE
FALSE
FALSE
FALSE
From
DMR
Cone
Units
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
UG/L
Logic Test"
Frequency
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Once/
Month
Logic
Test"
Sample
type
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Grab
Logic Test"
Data
Comment
Not Reported:
CODES
Not Reported:
CODE 8
Not Reported:
CODES
Logic
Test"
Tempor
Cone
2.5
ave
30
192
7.9
12
22
113
26
15
20
2.5
2.5
ave
ave
ave
ave
5
Calculate
Avg
Annual
Cone
Tempor
Cone
113.98
113.98
113.98
113.98
113.98
113.98
25.75
25.75
25.75
25.75
25.75
25.75
25.75
25.75
25.75
25.75
25.75
25.75
Logic
Test"
Tempor
Cone
2.500
113.977
30.000
192.000
7.900
12.000
22.000
113.000
26.000
15.000
20.000
2.500
2.500
25.750
25.750
25.750
25.750
5.000
Fill in
Blanks
Cone for
Calc
(mg/L)
0.003
0.114
0.030
0.192
0.008
0.012
0.022
0.113
0.026
0.015
0.020
0.003
0.003
0.026
0.026
0.026
0.026
0.005
Pasted
from
DMR
AveQ
(MGD)
1.52
1.12
1.15
1.3
1.1
1.69
13.45
13.45
1.47
1.54
1.64
1.72
0.9
1.77
1.42
1.54
1.56
1.62
1.42
1.85
18.45
18.45
Data
Entered
Days Per
Month
31
31
30
31
30
31
31
28
31
30
31
30
31
31
30
31
30
31
Calculated
Monthly
Load
(Ibs/yr)
1
33
9
65
2
5
400
400
8
41
11
6
5
1
1
10
10
11
9
2
116
116
Calculated
Annual Load
(Ibs/yr)
400
116
3 Sig Figs
Annual Load
(Ibs/yr)
400
400
400
116
116
116
Data Entered
TWF
0.0469
0.0469
0.0469
0.0469
0.0469
0.0469
0.0469
0.0469
0.0469
0.0469
0.0469
0.0469
0.0469
0.0469
0.0469
0.0469
0.0469
0.0469
Calculated
TWPE
(Ib-eq/yr)
18.75
18.75
18.75
5.44
5.44
5.44
-------
From DMR
PCSID
From DMR
Pollutant Name (Same
as Pram Except TSS)c
Zinc, Total (as Zn)
Total
From
DMR
Year
2005 Total
Grand
Total
From
DMR
Month
From
DMR
Max Cone
13.11667
FROM
DMR
ND?
From
DMR
Cone
Units
Logic Test"
Frequency
Logic
Test"
Sample
type
Logic Test"
Data
Comment
Logic
Test"
Tempor
Cone
Calculate
Avg
Annual
Cone
Tempor
Cone
Logic
Test"
Tempor
Cone
Fill in
Blanks
Cone for
Calc
(mg/L)
Pasted
from
DMR
AveQ
(MGD)
21.12
21.12
583.22
Data
Entered
Days Per
Month
Calculated
Monthly
Load
(Ibs/yr)
77
77
6,786,833
Calculated
Annual Load
(Ibs/yr)
Total Lbs
2003
Total Lbs
2004
Total Lbs
2005
Average Lbs Over 2003 - 2005
3 Sig Figs
Annual Load
(Ibs/yr)
76.5
76.5
6,793,310.8
3,715,271
902,670
2,168,892
Data Entered
TWF
Total TWPE
2003
Total TWPE
2004
Total TWPE
2005
Calculated
TWPE
(Ib-eq/yr)
3.59
3.59
11,993.68
3,410
4,137
4,447
td
to
Blue highlighted cells indicate that, for that month and pollutant, DMR data were missing.
Green highlighted cells indicate that, for that the pollutant was reported as having concentrations below detection limits.
-------
Appendix C
CALCULATION OF POLLUTANT LOADINGS USING EMPIRICAL FORMULAS
-------
Appendix C: Calculation of Pollutant Loadings Using Empirical Formulas
EPA used data from the AWWA document entitled, Trace Contaminants in
Drinking Water Chemicals, dated 2002. Page 161 lists the chemical content (in mg/kg) measured
in three samples of polyaluminum chloride (PAC1). EPA used only data from the three samples
named PAC1 #1, PAC1 #2, and PAC1 #3. Table C-l lists the chemical content data for PAC1 in
the AWWA document, as well as the associated mean concentration.
Table C-l. Concentrations of Chemicals Measured in PAC1 a
Chemical Name
Aluminum
Arsenic
Barium
Cadmium
Calcium
Chromium
Cobalt
Copper
Iron
Lead
Magnesium
Manganese
Mercury
Molybdenum
Nickel
Phosphorus
Potassium
Silicon
Silver
Sodium
Strontium
Tin
Titanium
Vanadium
Yttrium
Zinc
Zirconium
PAC1 #1
114,615
< 1.03
0.1
< 0.1
62
0.41
< 0.21
< 0.1
29
17
1
< 1.03
0.21
< 0.62
< 4.12
9.5
< 0.82
660
0.41
< 1.03
1.03
0.41
< 0.21
17.94
0.41
PAC1 #2
186,659
< 4.12
1.44
< 0.21
179
< 0.41
< 0.41
0.62
29
10
4.3
< 4.12
0.62
783.51
6.6
< 1.65
1113
< 4.12
1.44
0.41
< 0.62
35.05
0.82
PAC1 #3
118,981
< 1.03
0.12
< 0.1
74
0.62
< 0.21
0.82
82
< 2.06
31
1.6
1.44
< 2.06
2.68
4.12
8.9
30.93
< 0.82
412
0.41
< 1.03
3.09
5.15
< 0.21
12.37
0.82
Concentration, lb/1,000 Ib (dry)
Mean
140,085
Not Detected In Any Sample
0.553
Not Detected In Any Sample
105
0.41
Not Detected In Any Sample
0.497
46.7
Not Detected In Any Sample
19.3
2.30
0.978
1.10
1.20
263
8.33
30.9
Not Detected In Any Sample
728
0.41
Not Detected In Any Sample
1.9
2.0
Not Detected In Any Sample
21.8
0.683
Notes:
a - The less than sign denotes that the value was below sample-specific method detection limits (MDL). The MDL
can change with instrument, analyst, and matrix, and therefore may vary for each sample. The AWWA presented the
MDL for these samples. The MDL is different from the Practical Quantitation Level (PQL). EPA sets the PQL as
the lowest concentration of an analyte that can be reliably measured within specified limits of precision and
accuracy during routine laboratory operating conditions. The PQL is always greater than the MDL.
C-l
-------
For concentrations below detection limits, EPA used the "hybrid" approach: 1) if
the chemical is not detected in any of the three samples, assume it is not present and the
concentration = 0 and 2) if the chemical is detected in any of the three samples, assume
concentrations below method detection limits = 1A> x MDL.
EPA next calculated the mass of the chemicals in Table C-l that enter the
Guaynabo WTP system using the following equation:
Mass Impurity (Ibs/yr) = PAC1 Dose (in 1,000 Ibs) x A x 365 dpy
(EQ1)
where:
8,500 Ibs/day (from Guaynabo WTP Partial Questionnaire
Response, submitted April 2007); and
Mean Ib impurity/1,000 PAC1, from Table C-l.
PAC1 Dose =
A
Table C-3 contains the results of these calculations.
EPA next calculated the mass of chemicals in the treated effluent from the
Guaynabo WTP. The facility operates a sludge treatment system (STS). EPA used estimates of
TSS concentrations in the treated effluent to assess the expected solids removal by the STS.
Appendix B contains calculations of TSS (mg/L) from the Guaynabo WTP. Table C-2 shows the
mean TSS concentration calculated for the Guaynabo WTP effluent.
Table C-2. TSS Concentrations in Guaynabo WTP Effluent
Year
2003
2003
2003
2003
2003
2003
2003
2003
2003
2003
2003
2003
2004
2004
2004
2004
2004
2004
2004
Month
1
2
3
4
5
6
7
8
9
10
11
12
1
2
3
4
5
6
7
Max Cone
1900
22
11
11
1600
3.2
0.6
3.3
2800
0.9
4.8
2.6
1.1
0.55
1.4
3.4
3.3
2.1
ND?
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
Turbidity Cone, NTU
(no negatives)
1900
22
11
11
1600
3.2
0.6
Average
3.3
2800
0.9
4.8
2.6
1.1
0.55
1.4
3.4
3.3
2.1
Baseline TSS Cone,
mg/La
2,850
33
17
17
2,400
5
1
5
4,200
1
7
4
2
1
2
5
5
3
C-2
-------
Table C-2. TSS Concentrations in Guaynabo WTP Effluent
Year
2004
2004
2004
2004
2004
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
2005
Month
8
9
10
11
12
1
2
3
4
5
6
7
8
9
10
11
12
Max Cone
-2
-2
-2
2.8
11
12
0.7
4.8
1.1
2.4
4
1.6
16
1500
2.6
130
ND?
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
FALSE
Mean Effluent Concentration
Mean Effluent Concentration Excluding
TSS > 2,000 mg/L
Turbidity Cone, NTU
(no negatives)
Average
Average
Average
Average
2.8
11
12
0.7
4.8
1.1
2.4
4
1.6
16
1500
2.6
130
260
9.64
Baseline TSS Cone,
mg/La
4
17
18
1
7
2
4
6
2
24
2,250
4
195
390
14.46
Blank cells indicate no data were provided for that month.
a - EPA estimated TSS concentration (mg/L) = 1.5 x Turbidity (NTU)
The influent to the STS will contain 1% solids, or 10,000 ppm. EPA estimates
that the STS solids removal efficiency =1-390 mg/L / 10,000 mg/L, or 96 percent.
Optimization of Residuals Management will eliminate spikes in effluent water
quality. If outliers are excluded, EPA estimates the STS removal efficiency =1-14 mg/L /
10,000 mg/L, or 99.86 percent. EPA estimates that for Optimization of Residuals Management,
99.86% of solids will be removed. EPA also estimates that metals would be present in the solids,
and 99.86% of the metals present as a result of treatment chemical addition would also be
removed.
EPA estimated the mass of pollutants in the baseline load (current discharge) and
removed load (if Optimization of Residuals Management treatment is in place) that would be
discharged using the following equations:
Baseline Load (Ib/yr) = B x 4% (because 96% is removed in STS) (EQ 2)
Optimization of Residuals Management Loads (Ib/yr) = B x 0.14% (EQ 3)
(because 99.86% is removed in STS).
C-2
-------
where:
B
Mass of Impurity Added from Equation 1.
EPA calculated pollutant loads in terms of toxic-weighted pound equivalents
(TWPE) using the following equation:
where:
Load (Ib-eq/yr) = Load (Ib/yr) x TWF
TWF = Toxic Weighting Factor.
Table C-3 shows the results of these calculations.
Table C-3. Pollutant Loadings Calculations
(EQ4)
Aluminum
Arsenic
Barium
Calcium
Chromium
Copper
Iron
Magnesium
Manganese
Mercury
Molybdenum
Nickel
Phosphorus
Potassium
Silicon
Sodium
Strontium
Tin
Titanium
Vanadium
Zirconium
A
mg/kg
(dry)
140,085
1.89
0.313
105
0.41
0.513
46.7
19.3
2.3
0.978
1.41
1.20
263
8.33
30.9
728
0.41
1.72
1.9
2.0
0.683
B
Mass
Impurity
(Ib/yr)
434,614
5.86
0.97
326
1.28
1.59
145
60
7.14
3.03
4.37
3.73
817
26
96
2,260
1.27
5.33
5.75
6.17
2.12
Total
C
Baseline
Load,
Ibs/yr
17,385
0.234
0.0389
13.0
0.0511
0.0637
5.79
2.40
0.2854
0.121
0.175
0.149
32.7
1.03
3.84
90.4
0.0509
0.213
0.230
0.247
0.0848
17,536
D
Baseline
Load,
TWPE/yr
1,125
0.947
0.0000774
0.00386
0.0404
0.0324
0.00208
0.00412
14.2
0.0352
0.0163
0.00109
0.00000113
0.0641
0.00674
0.0086
0.0461
1,140
E
Optimization
of Residuals
Management
Load, Ibs/yr
608
0.00820
0.0013610
F
Removal
(Ibs/yr)
16,776
0.226
0.0375
G
Removal
(TWPE/yr)
1,085
0.914
0.0000747
H
TWF
0.0647
4.04
0.001991
Not applicable do not expect removals.
0.00179
0.00223
0.203
0.0840
0.00999
0.0
0.00612
0.00523
0.0493
0.0615
5.59
2.32
0.2754
0.117
0.169
0.144
0.00373
0.0390
0.0313
0.00200
0.00398
13.7
0.0340
0.0157
0.0756
0.634822
0.0056
0.000866
0.014433
117
0.201
0.109
Not applicable do not expect removals.
0.0362
1.00
0.00105
0.00105
Not applicable do not expect removals.
Not applicable do not expect removals.
0.00178
0.00746
0.00805
0.00864
0.00297
609
0.0491
0.206
0.222
0.238
0.0818
16,787
0.00000109
0.0619
0.00651
0.0083
0.0445
1,100
2.22E-05
0.301
0.029
0.035
0.544
C-4
-------
Appendix D
DETERMINATION OF OPTIMIZATION OF RESIDUALS MANAGEMENT COSTS
-------
Appendix D: Determination of Optimization of Residuals Management Costs
Summary Cost Sheet ($2005)
Capital Costs
EQTank $1,019,261
Pump House $17,515
Pumping System $104,424
Total Capita! Cost $1,141,200
Annual Costs
Labor (1) $537
Electricity (2) $1,844
Total Annual Cost $2,381
Annuallzed Costs (3)
EQTank $119,763
Pump House $2,058
Pumping System $12,270
Labor $537
Electricity $1,844
Total Annualized $136,472
(1) Labor is for 8 hrs per quarter for cleaning equalization tank. $16.79/hour
Bureau of Labor Statistics, 2005. May 2005 National Occupational Employment and Wage Estimates, http://'www. bis.gov/oes/current'oes_nat.htni
(2) The total kilowatt load for this system is as follows;
kW = 6 HP * 745.6 watts/hp * 1 kW/1,000 watts = 4.47 kW
The annual energy costs for this system are determined by the following equation :
Cost (2005$/yr) = 4.47 kW * 24 hr/day * 15 days/sedimenation tank cleaning per quarter * 5 sedimenation tanks * 4 quarters/yr * $G.Q573/kWh =
$1844/yr
U.S. Department of Energy, 2006. Average Retail Price of Electricity to Ultimate Customers by End-Use Sector.
http:/Mww,eia.doe.gov/cneaf/electricity/epa/epat7p4.html
(3) Total annual costs are equal to trie sum of operation and maintenance costs plus the annualized capital costs.
Annualized capita! costs are calculated based on a 20-year operating life and an interest rate of 10 percent.
The capital recovery factor for a 20-year operation life and 10 percent interest rate is 0.1175.
U.S. Environmental Protection Agency. Large Water System Byproducts Treatment and Disposal Cost Document. EPA-811/D-93-002.1993.
D-l
-------
Drinking Water EQ Basin Costing
Design Information Value
Tank Description In-ground reinforced concrete
Concrete Wall Thickness (inches) 15
Concrete Floor Thickness (inches) 8
Spread Footings Width (ft) 4
Footings Depth (ft) 1.5
Footing Trench Volume (cubic yards) 75,2
Tank Liner Required No
Tank Cover No
Lift Equipment Required (frame/winch) Yes
Solids Scraping Equipment Required Yes
Pumps Required Yes
Tank Volume (gal) 1,500,000
Tank Sidewall Depth (ft) 25
Tank Freeboard (ft) 3
Maximum Water Depth (ft) 22
Tank Area (ft2) 9,115
Tank Diameter (ft) 108
TankCircumfrence (ft) 338
Cleared Space Surrounding Tank (ft) 16
Land Requirement (ft2) 19,527
Soil Excavation Volume (cubic yds) 18,081
Topography Hill side
Vegetation Wooded
Soil Type Clay
Slope Stablization Required Yes
Length of Stablization along 1 side (linear ft) 140
Pumping Time (days) 15
Pumping Rate (gpm) 69
Number of Pumps (including spare) 3
Pump Type Self Prime Centrifugal
Piping to/from EQ Tank to Thickeners Welded Carbon Steel
Effluent Piping Diameter (inches) 4
Influent Piping Diameter (inches) 12
Piping Distance (ft) 100
Pipe Racks Required Yes
Pipe Rack Spacing (ft) 10
Number of Pipe Racks 5
Pump House (sq. ft) 100
Pump House Height (ft) 10
Pump House Walls Length and Width (ft) 10
Pump House Pad Length and Width (ft) 12
Pump House Pad (sq. ft) 144
Pump House Construction 8" Concrete Block
Roof Construction 4/12 Pitch Wood Trusses & Asphalt Shingles
HVAC Required No
D-2
-------
EQ Tank Cost (not including pump house or liquid transfer systems)
Description
Clear and grub area for tank. Assume
cut and chip trees to 1 2" diameter.
Grub stumps and remove.
Sheet piling along slope area for
stability. Assume 25' depth, 38 psf, left
in place pilings.
Excavate an area for the concrete EQ
tank. Assume excavation in clay type
soils using a 2 cubic yard bucket.
Excavate trench for concrete footings.
Trench is 4' wide and 18" deep in clay
soils.
Forms in place for concrete footings.
Assume continuous wall plywood, 3 use.
Reinforceing in place for footings.
Assumes to 18 Ib
Reinforced concrete spread footings at
bottom of excavation to support
concrete walls.
Forms in place for tank walls. Assume
radial wll forms, plywood, 2 use.
Reinforceing in place for walls. Assume
8 to 1 8 Ib.
Concrete poured into wall forms.
Reinforceing in place for floor of tank.
Concrete poured into floor of tank for
concrete bottom. Assume 8" thick
bottom. Costs for slab on grade, trowel
finish.
Unit
Acre
Square Foot
Cubic yard
Cubic yard
SFCA
ton
Cubic yard
SFCA
ton
Cubic yard
ton
Square Foot
Quantity
0.4
3,493.5
18,081.0
75.2
1,015.2
1.0
75.2
16,921
10
392
2
9,115
Unit Cost
$6,925
$24.50
$9.30
$2.82
$4.00
$1 ,050.00
$237.00
8.35
$1,025
$325
$1,350
$2.80
Total Cost
$2,986
$85,591
$168,347
$212
$4,061
$1,050
$17,823
$141,288
$10,250
$127,297
$2,700
$25,523
Notes
1
1
1
1
1
1
1
1
1
1
1
1
D-3
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EQ Tank Cost (not including pump house or liquid transfer systems)
Description
Construct a pipe bedding system to
remove water from the tank footings
area. Assume an 8-inch diameter pipe
and a trench backfilled with bank sand.
Assume the trench will extend around
the perimeter of the tank.
Backfill area on outside of tank
excavation. Dozer or front end loader,
50' haul, clay soils.
Topsoil over backfilled area on exterior
of tank. Assume 6" deep and 300' haul.
Unit
Linear foot
Cubic yard
Cubic yard
Quantity
338
5,014
100
Unit Cost
$1.57
$0.9
$2.54
Subtotal Direct Cost (2001):
Mechanical systems
(frame/winch/cable, bridge/ladders,
metal railings, etc).
% of subtotal direct cost
35.0
Total Direct Cost (2001):
Permits
Scheduling
Performance bonds
Insurance
(risk, equipment floater, public liability)
Contractor markup (handling, procuring,
subcontracting, change orders, etc.)
Overhead and profit
% of total direct cost
% of total direct cost
% of total direct cost
% of total direct cost
% of total direct cost
% of total direct cost
2.0
0.8
2.5
2.3
10.0
10.0
Total Cost
$531
$4,713
$255
$504,049
$176,417
$680,466
$13,609
$5,444
$17,012
$15,651
$68,047
$68,047
Total Indirect Cost (2001): $187,809
Total Cost (2001): $868,274
Total Cost (2005): $1 ,01 9,261
Notes
2
1
1
1
1
1
1
1
1
1
3
Notes:
NA - Not Applicable
1. Costs and cost factors obtained from RSMeans Building Construction Cost Data, 59th Edition, 2001.
2. Costs obtained from RSMeans Site Work and Landscape Cost Data. 20th Edition, 2001.
3. ENR Construction Cost Index
D-4
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Pump House Construction Costs
(not including pumping system)
Description
Forms in place for concrete footings
and pad. Assume continuous wall
plywood, 3 use.
Reinforceing in place for concrete pad.
Assume 8 to 18 Ib
Poured concrete for pump house slaf.
Assume 8" thick bottom . Costs for slab
on grade, trowel finish.
Exterior walls. Concrete block, 8" x 1 6"
x 6" thick, including reinforcing alt
courses, tooled joints, 2 sides, foam
inserts.
Wood trusses, 10-foot span, metal
plate connected, 4 in 1 2 slope.
Plywood sheathing on roof, 1/2 inch
thick.
Asphalt felt, #15, no mopping.
Asphalt shingles. Assume shingles are
inorganic class A, 210-235 Ib/sq.
Paint interiorwalls, 2 coats, smooth
finish, roller.
Paint exteriorwalls, 2 coats, latex,
smooth finish, roller.
Commercial steel entrance door, 3 feet
wide by 7 feet high.
Unit
SFCA
ton
Square Foot
Square Foot
Square foot
Square foot
Square Foot
Square
Square foot
Square foot
Each
Quantity
108.0
1.0
144
400
100
100
100
10
400
400
1
Unit Cost
$4.00
$1,050.00
$2.80
$6.1
$2.33
$1.06
$8.45
$94
$0.50
$0.47
$227
Total Cost
$432
$1,050
$403
Notes
1
1
1
$2,420 1
$233 1
$106 1
$845 1
$940 1
$200
$188
$227
Subtotal Direct Cost (2001 ): $7,044
1
1
1
D-5
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Plumbing Systems including floor
drains, potable water for tank
wash down, etc.
Mechanical Systems including HVAC
Electrical systems
(lighting, switches, wiring, conduit,
outlets, etc.)
% of subtotal direct cost
% of subtotal direct cost
% of subtotal direct cost
32.7
17.5
15.8
Total Direct Cost:
Permits
Scheduling
Performance bonds
Insurance
(risk, equipment floater, public liability)
Contractor markup (handling,
procuring, subcontracting, change
orders, etc.)
Overhead and profit
% of total direct cost
% of total direct cost
% of total direct cost
% of total direct cost
% of total direct cost
% of total direct cost
2.0
0.8
2.5
2.3
10.0
10.0
$2,303
$1,233
$1,113
$1 1 ,693
$234
$94
$292
$269
$1,169
$1,169
Total Indirect Cost (2001): $3,227
Total Cost (2001): $14,921
2
1
1
1
1
1
1
Total Capital Cost (2005) $17,515 2
Notes:
MA - Not Applicable
1. Costs and cost factors obtained from RSMeans Building Construction Cost Data. 59th Edition, 2001.
2. ENR Construction Cost Index
D-6
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Appendix E
DRAFT DECHLORINATION COST MODULE
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Appendix E: Draft Dechlorination Cost Module
Module: Dechlorination of Filter Backwash32
Disclaimer: This is a draft module. This module was developed for EPA's Guaynabo WTP BPJ
analysis. Costs from additional vendors are needed, along with cost data over a wider flow range.
In addition, cost factors in this module could be updated based on additional costing data/input.
The costs included in this model have varying basis years and will need to standardized. The
costs in this module are assumed to be in 2005 dollars for this analysis (the most recent labor
rates are from 2005).
Module Methodology
This module estimates the costs associated with installing and operating a filter backwash
dechlorination system in drinking water treatment plants using sodium metabisulfite. The system
presented in this module consists of a dechlorination controller and a chemical feed system.
Chlorination has been used widely to disinfect wastewater prior to discharge since passage of the
1975 Federal Water Pollution Act (WPCA). Residual chlorine is toxic to many kinds of aquatic
life. The reaction of chlorine with organic materials in water forms carcinogenic trihalomethanes
and organochlorides. Dechlorination minimizes the effect of potentially toxic disinfection
byproducts by removing the free or total combined chlorine residual remaining after chlorination
(U.S. EPA, 2000).
A dechlorination controller with an oxidation reduction potential (ORP) detector was included in
this module because appropriate controllers can help minimize the use of dechlorination
chemicals and prevent overdosing while keeping chlorine concentrations in the effluent near
zero. The controller presented in this module uses an ORP detector to measure the amount of
free chlorine in wastewater. A controller will use this data to inject the appropriate amount of
sodium metabisulfite (dechlorination chemical). Constant measurement of the ORP reduces the
risk of overdosing, reduces of the amount of chemicals needed, and will adjust to meet effluent
requirements.
Controllers with residual detectors are also available to control dechlorination. These detectors
are able to detect specific ions in solution. Traditionally, ORP controllers have been less
sensitive than residual detectors. Case studies have shown that new technology using ORP
detectors can be very effective in reducing chlorine concentrations to near 0 mg/L. An ORP
controller from Siemens Water Technologies was selected for this cost module because it is less
expensive than a comparable residual detector and case studies have shown that it is able to
reduce chlorine concentrations to near 0 mg/L.
32 This module also applies to supernatant combined with filter backwash
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Process Description
The most common types of chemicals used for dechlorination are sulfur-based. The mechanism
associated with dechlorination, using sulfur based chemicals, is the reaction of a sulfite ion
(SO3~2) with free chlorine (HOC1 or OC1). This reaction neutralizes free chlorine by turning it
into chloride (Cl~). Sodium metabisulfite (^28205) can be used to remove free chlorine from
filter backwash as shown in the chemical reactions below:
Na2S2O5 + H2O -> 2 Na+ + 2 HSO3" (1)
SO3"2 + HOC1 -> SO4"2 + Cr + H+ (2)
This reaction is typically very rapid and requires about 5 minutes of mixing for the reaction to
complete (U.S. EPA, 2000). Because of the rapid reaction time and minimal mixing
requirements, no additional tank volume is assumed to be required to install this dechlorination
system.
Design Considerations
Several different sulfur-based chemicals can dechlorinate wastewater. Sulfur dioxide (862),
sodium metabisulfite (^28205), and sodium bisulfite (Na2HSO3), are some of the most
common chemicals used by treatment plants for dechlorination. This cost module uses sodium
metabisulfite because it is safer than sulfur dioxide and is more effective than sodium bisulfite.
Sulfur dioxide is considered hazardous and special precautions must be made to handle and store
sulfur dioxide that will reduce risk of exposure to the gas. Sulfur dioxide gas (in pressurized
cylinders) must be stored in well-ventilated and temperature-controlled rooms. Small treatment
plants tend not to use sulfur dioxide to avoid safety concerns associated with the gas.
Sodium bisulfite is similar to sodium metabisulfite in design, use, and handling; however, it is
less efficient than sodium metabisulfite. Approximately 1.46 parts sodium bisulfite per part of
free chlorine is required to remove free chlorine compared to 1.34 parts sodium metabisulfite per
part of free chlorine. Because less sodium metabisulfite is required to react with free chlorine, it
is more efficient (U.S. EPA, 2000).
Overdosing sodium metabisulfite must be avoided because excess sulfite can react with
dissolved oxygen to produce sulfates. Sulfates may lead to reduced dissolved oxygen
concentration and low pH levels in the finished effluent for high levels of overdose. Careful
control of a dechlorination system must be maintained to prevent overdosing (U.S. EPA, 2000).
E-2
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INSTALLED CAPITAL COSTS33
CAPITAL COST
Estimated equipment costs were provided by Siemens Water Technologies and include the ORP
controller, two-pump skid, Va" to W CPVC plumbing, mixing system, and injector. The direct
capital costs for this equipment are provided below:
Siemens Controller with ORP detector ~ $10,000
Feed system (pumps, injector, mixer, and plumbing) ~ $30,000
Note: the cost for the controller is valid for all flow ranges; the cost for the feed system applies
only to a flow range of 48,000 to 75,000 gallons per hour.
Indirect costs include engineering and administrative costs, plus the costs for secondary
containment and procurement of additional space (if necessary) typically equal 20% of the direct
capital cost. Therefore, the total plant cost is estimated to be:
$40,000 + $40,000 x 20% (for engineering, administrative, etc) = $48,000
EPA also assumed a contractor fee of 5% and a 15% contingency. Therefore, the total capital
investment is estimated to be:
$48,000 + $48,000 x 20% (contractor fee, contingency) = $57,600
ANNUAL COSTS
Electrical31
Annual electrical costs are based on individual unit horsepower for pumps and mixers, and
converting to kilowatts per the following equation:
kW = total HP x 745.6 watts/hp x lkW/1,000 watts
Two 0.75 hp pumps are required to convey filter backwash through the system. These pumps are
assumed to run continuously. A 1 hp mixer is appropriate for mixing dilute streams, such as filter
backwash, and sodium metabisulfite. The kilowatt usage for these units is calculated below:
Pumps: 2 x 0.75 hp
Mixer: 1 x 1.0 hp
Total 2.5 hp
The total kilowatt load for this system is as follows:
kW = 2.5 HP x 745.6 watts/hp x lkW/1,000 watts = 1.86 kW
33 Costs valid for flow range of 48,000 to 75,000 gallons per hour.
34 Power requirements were obtained through vendor information. Costs valid for flow range of 48,000 to 75,000
gallons per hour.
E-3
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The annual energy costs for this system are determined by the following equation35:
Cost ($/yr) = 1.86 kW x 24 hr/day x 365 day/yr x $0.0573/kWh = $930 / yr
Chemicals
The estimation of annual chemical costs assumed 1.34 parts sodium metabisulfite are mixed for
every part free chlorine. If the flow and concentration of free chlorine are known, the following
equation can be used to calculate annual chemical cost36:
Cost ($/yr) = Cone, of Chlorine (mg/L) x flow (gal/min) x 3.785 L/ gal x
[2.205 xlO'6 lb / mg] x 1440 min/day x 365 day/yr x 1.34 NaS2O5 / 1 HOC1 x
$1.65/lbofNaS2O5
The above equation is valid to calculate the cost of chemicals for all flows.
For Guaynabo WTP, chemical costs are:
Cost ($/yr) = [1.65 mg/L] x [1,023 gpm] x 3.785 x 2.205 x 10'6 x 1440 x 365 x 1.34 x $1.65
Cost ($/yr) = $16,400
OPERATING LABOR
Operating labor for a sodium metabisulfite dechlorination system includes preparation of
solution from bagged sodium metabisulfite and ensuring the system is running properly. Based
on engineering judgment, the operating labor is assumed to be 1 hour per shift a rate of
$16.79/hr37 for water and wastewater treatment operators. Assume labor over 2 shifts per day
and 365 days per year in the absence of the dewatering operating schedule. The cost equation for
the operating labor is:
Operating Labor Cost = 2 hr/day x 365 days/yr x $16.79/hr = $12,300/yr
The above equation is valid for calculating operating labor costs for all flows.
Maintenance Labor
Because many of the maintenance tasks are performed during routine operation of the system,
EPA assumed that additional maintenance labor would be 1 hour per week33. To calculate the
maintenance labor, the following equation will be used:
Maintenance Labor Cost ($/yr) = 1 hr/wk x 365 d/yr x 1 wk/5 days x $16.79/hour
Maintenance Labor Cost ($/yr) = $l,230/yr
The above calculation of maintenance labor is valid for all flows.
35 Value of $0.0573/kWh obtained from U.S. Department of Energy - Average Industrial Electrical Costs in 2005.
36 Price of NaS2O5 obtained for http://thechemistrystore.com.
37 Labor rate of $16.79 determined from Bureau of Labor Statistics, 2005.
E-4
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WASTE DISPOSAL
No waste disposal costs are associated with a sodium metabisulfite dechlorination system. The
amount of free chlorine removed per day can be calculated by using the approximation 1.34 parts
sodium metabisulfite removes 1 part free chlorine. To calculate the free chlorine removed, the
following equation will be used:
Free Chlorine Removed (Ibs/day) = Weight of Sodium Metabisulfite Used (Ibs/day) 71.34
The above equation is valid to approximate free chlorine removed for all flows.
Cost Calculation
Costs are summarized below.
Item (s)
ORP Detector and Chemical Feed System
Electricity
Chemical Costs
Operating Labor
Maintenance Labor
Waste Disposal
Type of Cost
Capital
Annual
Annual
Annual
Annual
Annual
Total Capital
Total Annual
Cost
$57,600
$930
$16,400
$12,300
$1,230
$0
$57,600
$30,860
References
Bureau of Labor Statistics, 2005. May 2005 National Occupational Employment and Wage
Estimates, http://www.bls.gov/oes/current/oes nat.htm
U.S. Department of Energy, 2006. Average Retail Price of Electricity to Ultimate Customers by
End-Use Sector, http://www.eia.doe.gov/cneaf/electricity/epa/epat7p4.html
U.S. Environmental Protection Agency. 2000. Wastewater Technology Fact Sheet:
Dechlorination. EPA 832-F-00-022.
The Chemistry Store, 2007. Sodium Metabisulfite.
http://www.chemistrystore.com/sodium_metabisulfite.htm
Brian Stofko, Siemens Water Technologies Sales Representative, and Jeff Chittim, ERG.
Personal communications discussing dechlorination systems. 15 November 2006 and 28
February 2007.
E-5
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Appendix F
ADDITIONAL DISINFECTION COST ESTIMATES FOR ZERO DISCHARGE VIA
COMPLETE RECYCLE
-------
Appendix F: Additional Disinfection Cost Estimates for Zero Discharge Via Complete
Recycle
EPA estimated the costs of additional disinfection using the following information
from Tramfloc, Inc.:
Estimated Costs to Disinfect 1 MGD Drinking Water Using Chlorine Gas
Required Equipment
1 Hydro Model 500 chlorinator
1 Booster pump
1-150 Ib chlorine cylinder
Media Quantity Required per Year: 3,030 Ibs at $0.93/lb
Initial Capital Investment
$1,870.00
Annual Costs
$2,817.90
Source: http://www.tramfloc.com/tf69.html
EPA scaled up the disinfection requirements to a flow of 1.76 MGD, the average
effluent flow from the Guaynabo WTP, resulting in the following cost estimates:
Estimated Costs to Disinfect 1.76 MGD Drinking Water Using Chlorine Gas
Required Equipment
1 Hydro Model 500 chlorinator
1 Booster pump
1-150 Ib chlorine cylinder
Media Quantity Required per Year: 5,380 Ibs at $0.93/lb
Initial Capital Investment
$3,300.00
Annual Costs
$5,000.00
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