Some aquatic plants and animals have traditional and sacred cultural significance to tribes. For example, the Ojibwe and Dakota tribes in Minnesota have significant cultural ties to wild rice (MPCA, 2017). Wild rice has been gathered by Ojibwe peoples for generations, and its use by the tribe can be traced back to the time its ancestors migrated to the area. Pollution from ions, such as sulfate, is of significant concern to the tribes because of the effects on wild rice.
Numerous fish species are culturally significant as both a food and cultural resource for tribes throughout North America. For example, in the Pacific Northwest, salmon play very important roles in traditional meals and ceremonies. Tribal people pass on expert knowledge of ecosystems and the history of preceding generations; this expert cultural exchange of information about fish and water preserves the rich cultural traditions of many tribes (NEJAC, 2002). In addition, water itself is also a part of cultural ceremonies where it is used to purify the body before eating and is then consumed to purify foods that are eaten (NEJAC, 2002).
These examples illustrate important cultural benefits that tribal members value from water resources. These cultural benefits have generational traditions and a rich history that serve a significant basis for many tribal beliefs and values.
Recreational Benefits
Under federal law, Indian lands are private trust assets which cannot be used by non-tribal members without a permit or license to fish, boat, hunt, camp, or otherwise use natural resources. However, many tribes sell licenses for a wide variety of recreational activities on Indian reservations, including camping, boating, fishing, and hunting. Recreational activities that may be enhanced by improved water quality in Indian reservation waters include:
   Outings. Activities that take place near water such as hiking, jogging, picnicking, and wildlife viewing may be adversely affected by pollutant discharges that lead to a decrease in the aesthetic qualities of a waterbody or that negatively impact populations of fish, wildlife, and local flora.
   Recreational Fishing. Degraded water can reduce fish populations by inhibiting reproduction and survival of an aquatic species, leading to fewer and smaller fish and a reduction of the game fish population. Pollutants may also reduce the aesthetics of the water body, which may reduce anglers' enjoyment of their fishing experience. Also, turbidity caused by pollutant discharges may affect recreational anglers by reducing the distance over which fish can see lures, resulting in lower catch rates (Clark et al., 1985).
   Boating. Polluted water reduces the aesthetic appeal of recreational boating activities and can affect the safety of boating. For example, turbidity may obscure underwater obstacles, making collisions more likely. Increased sediment concentrations may also create sandbars, increasing the chances of running aground.
   Swimming. Pollution of water by toxic chemicals or by fecal indicator bacteria may cause closure of water bodies for swimming. Eutrophication caused by nutrients and turbidity caused by sediment and other pollutants also may greatly reduce a swimmer's aesthetic enjoyment of a water body. Additionally, turbidity may create safety hazards for the swimmer by reducing the ability to see underwater hazards or increasing diving accidents by impairing the ability to gauge water depth.
   Hunting. Similar to the effect on outings, discharged pollutants may greatly detract from the hunters' aesthetic enjoyment of a water resource. Damage to flora and fauna may also affect the game population, reducing the number and quality of the game available.
Conversely, improved water quality may translate into two components of recreational benefits: an increase in the value of a recreational trip resulting from a more enjoyable experience and an increase in recreational participation.
Nonuse Benefits
Use benefits are values individuals hold for an environmental improvement that can be inferred through a change in demand for one or more market goods (i.e., purchases of complementary goods such as equipment and travel). Thus, nonuse benefits are values individuals hold for an environmental improvement that are independent of purchases of market goods and services. The total benefits of an environmental improvement are the combination of use and nonuse benefits (Freeman III, 1993, 2003). Recent economic literature provides substantial empirical support that nonuse values, such as option and existence values, are greater than zero. In fact, small per capita nonuse values held by a substantial fraction of the population can be very large in the aggregate. Consequently, both EPA's own Guidelines for Preparing Economic Analysis and the Office of Management and Budget's (OMB) Circular A-4 governing regulatory analysis support the need to assess nonuse values (EPA, 2010b; USOMB, 2003). Excluding nonuse values from consideration is likely to substantially understate total social values.
Nonuse values may be more difficult to assess than use values for several reasons. First, nonuse values are not associated with easily observable behavior. Second, nonuse values may be held by both users and nonusers of a resource. Because nonusers may be less familiar with particular services provided by a resource, they may value the resource differently compared to users of the same resource. Third, the development of a defensible stated preference survey (the generally accepted technique for estimating nonuse values (EPA, 2010b; USOMB, 2003))is often a time- and resource-intensive process.
Although EPA is not always able to estimate changes in nonuse values as part of regulatory development, an extensive body of environmental economics literature demonstrates that the public holds significant value for services flowing from natural resources well beyond those associated with direct uses (Boyd et al., 2001; Fischman, 2001; Heal et al., 2001; Herman et al., 2001; Ruhl and Gregg, 2001; Salzman et al., 2001; Wainger et al., 2001). Studies have documented public values for the services provided by a variety of natural resources potentially affected by environmental impacts, including fish and wildlife (Loomis et al., 2000; Stevens et al., 1991); wetlands (Woodward and Wui, 2001); wilderness (Walsh et al., 1984); critical habitat for T&E species (Hagen et al., 1992; Loomis and Ekstrand, 1997; Whitehead and Blomquist, 1991); shoreline quality (Grigalunas et al., 1988); and beaches, shorebirds, and marine mammals (Rowe et al., 1992), among others.
Many ecosystems provide goods and services that contribute to societal well-being, but may be generally unrecognized because of the indirect nature of the effect. As such, valuations based solely on the analysis of markets are unlikely to capture the full economic value of the affected ecosystem services (Costanza and Folke, 1997).
Summary of Benefits
Exhibit 4-2 summarizes potential benefits from promulgating potential baseline WQS for certain Indian reservation waters, including environmental services affected by pollutant reductions and entities affected by environmental changes.
Exhibit 4-2 Summary of Benefits from Promulgating WQS for Indian Reservation Waters
Activity
Environmental Services Potentially Affected by Tribal WQS
Entities Affected by Environmental Improvements

Private Sector*
Government**
Tribal Members***
Others**** (downstream)
Fish and Shellfish Consumption
Food safety (reduced exposure to carcinogens and human health toxicants)

Commercial Fishing and Shellfishing
Fish and shellfish populations

Subsistence Fishing
Fish and shellfish populations

                            Use & Nonuse Values
                            Use & Nonuse Values
Property Values
Aesthetics, property value, turbidity

Water Supply and Use (Drinking)
Water safety, turbidity

Cultural and Traditional Uses
Food and water safety, cultural resources

Recreation
  Fishing
  Near-water
  Boating
  Swimming
  Hunting
Water safety (reduced risk of gastrointestinal illness), aesthetics, water clarity, degree of sedimentation, eutrophication, fish and shellfish populations

Nonuse
  Bequest
  Existence
  Altruistic
Environmental health, ecosystem and habitat protection

Notes:
* Fishing-related industries potentially benefit from larger fish populations and fewer fish consumption advisories. Any firms that use water from affected waterbodies could benefit from water quality improvements. Businesses located near affected waterbodies may benefit from higher property values. Recreation-based businesses (e.g., sightseeing tours, equipment rentals) potentially benefit from improved recreational experiences.
** Governments may benefit if water quality improvements reduce treatment costs for drinking water and other water supplies. They could also benefit from increased property tax revenues if water quality improvements enhance property values.
*** Tribal members potentially benefit from all affected services, with the possible exception of enhanced property values. Indian reservation land is typically not sold in open markets. However, it is reasonable to assume that the owners would benefit from water quality improvements.
**** Assuming water quality improvements downstream from Indian reservation lands are significant, downstream residents potentially benefit from all affected services.
Method for Estimating Potential Costs: Point Sources
This section describes the method EPA used for estimating the potential costs to point sources associated with the proposed baseline WQS, specifically the economic analysis criteria described in Section 3.3. Control costs for municipal and industrial point sources may result from changes to individual NPDES permit requirements.
Identification of Potentially Affected Permittees
EPA's Integrated Compliance Information System (ICIS) database identifies 220 NPDES individual permits as discharging in Indian country, some of which are discharging to Indian reservation waters outside the scope of this analysis (e.g., Indian reservation waters with CWA-effective WQS). To select only the facilities within the scope of this analysis, EPA reviewed and mapped the ICIS Indian country data, and mapped the Indian reservations with waters that may be subject to the proposed baseline WQS. In addition, EPA mapped all individual NPDES dischargers in the United States to identify additional dischargers to Indian reservation waters that may not be labeled as discharging to Indian country in the ICIS database.
The above analysis identified a total of 164 individual NPDES permits for facilities with discharges in Indian reservation waters subject to this analysis (7 majors and 157 minors). EPA uses the designation of "major" for municipal wastewater treatment plants (WWTPs) of 1 million gallons per day (MGD) or more, or serving a population of 10,000 or more, and industrial discharges with a major rating code over a specified value based on the presence of toxics and size of discharge flow (EPA, 2010a).
The proposed baseline WQS may also affect facilities upstream from Indian reservation waters, so EPA identified facilities within five miles of Indian reservation boundaries and upstream from Indian reservation waters. To identify those facilities, EPA conducted an initial nationwide ICIS query followed by geographic information system (GIS) mapping of latitude/longitude coordinates for the individual NPDES permittees, which identified 999 facilities (193 major and 806 minor). EPA then used surface water (i.e., streams and catchment areas/watersheds to those streams) GIS data from the United States Geological Survey (USGS) National Hydrography Dataset (NHD) to identify facilities upstream from Indian reservation waters. EPA relied on the following assumptions for the GIS upstream analysis:
Facilities are upstream if they discharge to a catchment, or within the catchment (as defined by NHD) to a stream that either flows through Indian reservations or borders the tribal boundary.
Facilities discharging upstream from, or in a non-flowing water body abutting Indian reservations are considered upstream from the reservation.
Tidal influence into rivers was ignored at this time.
The steps above narrowed the number of individual permit facilities upstream from Indian reservation waters to 274 (50 majors, 221 minors, and 3 without designation).
For purposes of this analysis, facilities discharging to Indian reservation waters are referred to as "tribal" facilities, while those discharging upstream from Indian reservations are identified as "upstream" facilities. Exhibit 5-1 shows the categories of individual NPDES permit facilities discharging to Indian reservation waters and upstream from those waters. Most of these facilities are sewerage systems, defined as those facilities both public and private that collect and treat primarily domestic wastewaters. Sewerage systems are also referred to as POTWs, wastewater treatment facilities (WWTFs), or WWTPs.
Exhibit 5-1 NPDES Facilities that May be Affected by the Proposed Baseline WQS

Tribal
Upstream

Category*
Major
Minor
N/A
Major
Minor
N/A
Total
Sewerage Systems
                                                                              7
                                                                             90
                                                                              0
                                                                             41
                                                                             98
                                                                              1
                                                                            237
N/A**
                                                                              0
                                                                             19
                                                                              0
                                                                              0
                                                                             49
                                                                              1
                                                                             69
Water Supply
                                                                              0
                                                                             13
                                                                              0
                                                                              0
                                                                              8
                                                                              0
                                                                             21
Crude Petroleum And Natural Gas
                                                                              0
                                                                             11
                                                                              0
                                                                              0
                                                                              5
                                                                              0
                                                                             16
Construction Sand And Gravel
                                                                              0
                                                                              4
                                                                              0
                                                                              0
                                                                              4
                                                                              0
                                                                              8
Hotels And Motels
                                                                              0
                                                                              4
                                                                              0
                                                                              0
                                                                              3
                                                                              0
                                                                              7
Poultry Slaughtering And Processing
                                                                              0
                                                                              0
                                                                              0
                                                                              1
                                                                              4
                                                                              0
                                                                              5
Fish Hatcheries And Preserves
                                                                              0
                                                                              1
                                                                              0
                                                                              0
                                                                              4
                                                                              0
                                                                              5
Dairy Farms
                                                                              0
                                                                              0
                                                                              0
                                                                              0
                                                                              5
                                                                              0
                                                                              5
Electric Services
                                                                              0
                                                                              0
                                                                              0
                                                                              2
                                                                              2
                                                                              0
                                                                              4
Elementary And Secondary Schools
                                                                              0
                                                                              1
                                                                              0
                                                                              0
                                                                              3
                                                                              0
                                                                              4
Refuse Systems
                                                                              0
                                                                              1
                                                                              0
                                                                              0
                                                                              3
                                                                              0
                                                                              4
Copper Ores
                                                                              0
                                                                              2
                                                                              0
                                                                              0
                                                                              1
                                                                              0
                                                                              3
Pulp Mills
                                                                              0
                                                                              0
                                                                              0
                                                                              1
                                                                              1
                                                                              0
                                                                              2
Beef Cattle Feedlots
                                                                              0
                                                                              1
                                                                              0
                                                                              0
                                                                              1
                                                                              0
                                                                              2
Sporting And Recreational Camps
                                                                              0
                                                                              0
                                                                              0
                                                                              0
                                                                              2
                                                                              0
                                                                              2
Nitrogenous Fertilizers
                                                                              0
                                                                              0
                                                                              0
                                                                              1
                                                                              0
                                                                              0
                                                                              1
Crude Petroleum Pipelines
                                                                              0
                                                                              0
                                                                              0
                                                                              1
                                                                              0
                                                                              0
                                                                              1
Petroleum Refining
                                                                              0
                                                                              0
                                                                              0
                                                                              1
                                                                              0
                                                                              0
                                                                              1
Finishing Plants
                                                                              0
                                                                              0
                                                                              0
                                                                              1
                                                                              0
                                                                              0
                                                                              1
Paper Mills
                                                                              0
                                                                              0
                                                                              0
                                                                              1
                                                                              0
                                                                              0
                                                                              1
All Others***
                                                                              0
                                                                             10
                                                                              0
                                                                              0
                                                                             28
                                                                              1
                                                                             39
Total
                                                                              7
                                                                            157
                                                                              0
                                                                             50
                                                                            221
                                                                              3
                                                                            438
Notes:
* Based on standard industrial classification code. Source: EPA Enforcement and Compliance History Online (ECHO) and ICIS databases; Accessed February 2021 and some information from facility permits and fact sheets.
** Facility type was not specified in the ICIS-NPDES system.
*** Includes industrial categories with only one minor discharger and no major dischargers.
Methodology for Sampling
As shown in Exhibit 5-1, there are 57 major (7 tribal and 50 upstream), and 378 minor (157 tribal and 221 upstream) individually permitted dischargers to waters for which the proposed baseline WQS would apply. Factors that may affect the potential magnitude of control costs include flow and facility type. Larger flows are typically associated with the largest treatment costs, although per-unit costs may decrease due to economies of scale. While POTWs are typically designed to treat domestic wastewater using biological treatment, industrial facilities have a wide range of process wastewaters with different characteristics and types of treatment technologies. Therefore, the costs for treating industrial wastewater are often different than those identified for POTWs.
Minor dischargers typically do not have monitoring requirements for toxic pollutants so data to evaluate reasonable potential and the need for WQBELs for these facilities is limited. In addition, these facilities may not contribute significantly to instream loads even if such pollutants were present in their effluent. Thus, the potential for minor facilities to incur costs as a result of criteria translations is low, and minor facilities were not included in the selected sample.
Stormwater discharges are generated by precipitation and runoff from land, pavement, building rooftops, and other surfaces. During rainfall events, stormwater washes over the loose soil on construction sites, along with various materials and products being stored outside, and can pick up pollutants like sediment, debris, and chemicals. Also, road and parking lot run-off can contain a variety of pollutants such as copper from worn out brake pads, oil and grease, and polycyclic aromatic hydrocarbons (PAHs). Metal rooftops and atmospheric deposition onto roofs can contribute to metals and PAHs in stormwater, while birds and other animals leave fecal matter on rooftops and in gutters, which can contribute bacteria to run-off. Roofs with wooden or asphalt shingles can increase concentrations of chemicals used for waterproofing or weathering treatment (DeBusk et al., 2009). Although stormwater from municipal and industrial areas and from construction projects may contribute pollutants to Indian reservation waters, most stormwater discharges are regulated through general permits and most NPDES permits for stormwater discharges, whether individual or general, require permittees to develop and implement programs and plans to reduce pollutant discharges. Implementing the proposed baseline WQS may lead to increased or additional nonstructural best management practices (BMPs) (e.g., institutional, educational, or pollution prevention (P2) practices designed to limit generation of runoff or reduce the pollutant load in runoff) and structural controls (e.g., engineered and constructed systems designed to provide water quantity or quality control) for stormwater dischargers. However, for the most part, stormwater permits do not include numeric WQBELs to control pollutant discharges. Consequently, EPA was unable to estimate incremental costs to permittees with stormwater permits that may result from implementation of the proposed baseline WQS.
To incorporate facilities with the highest potential for cost, EPA included all tribal major dischargers (7 facilities) and all upstream major industrial dischargers (9 facilities). In addition, EPA selected a sample of 10 upstream major sewerage systems (out of 41) to analyze as a basis for extrapolation of costs for remaining upstream facilities as described in Section 0 below. To select the sample of sewerage systems, EPA downloaded available flow data from ICIS-NPDES for all the upstream majors for the past five years and identified facilities with a broad geographic distribution and the most available and relevant pollutant monitoring data. EPA selected ten of the sewerage systems with sufficient data to conduct reasonable potential analyses based on geographic distribution of those facilities.
Exhibit 5-2 provides a list of the 26 facilities included in the sample for reasonable potential analyses, with the tribal facilities listed first, followed by upstream facilities, sorted alphabetically by NPDES identifier number.
Exhibit 5-2 Sample NPDES Dischargers for Reasonable Potential Analyses
NPDES ID
Facility Name
Location
Region
Type
AZ0021415
Colorado River Sewage Joint Venture*
Tribal
                                       9
                                     WWTP
AZ0024627
Mesa Northwest Water Reclamation Plant (WRP)*
Tribal
                                       9
                                     WWTP
MI0023655
Mt. Pleasant WWTP*
Tribal
                                       5
                                     WWTP
MI0055808
Union Township WWTP*
Tribal
                                       5
                                     WWTP
MS0053503
Pearl River WWTP*
Tribal
                                       4
                                     WWTP
MT0030759
City of Hardin Water Treatment Plant (WTP)*
Tribal
                                       8
                                     WWTP
NY0020508
Salamanca WWTP*
Tribal
                                       2
                                     WWTP
AZ0020524
City of Phoenix 91[st] Avenue WWTP
Upstream
                                       9
                                     WWTP
AZ0024121
Pima County WRC Arva Valley Wastewater Reclamation Facility (WRF)
Upstream
                                       9
                                     WWTP
AZ0025208
Town of Florence WWTP
Upstream
                                       9
                                     WWTP
CA0104973
Coachella Valley Mid-Valley WRP
Upstream
                                       9
                                     WWTP
CO0031755
Pagosa Area Vista WWTP
Upstream
                                       8
                                     WWTP
IA0004014
CF Industries Nitrogen
Upstream
                                       7
                                  Industrial
IA0004103
MidAmerican-Neal North Energy Center
Upstream
                                       7
                                  Industrial
IA0061859
MidAmerican-Neal South Energy Center
Upstream
                                       7
                                  Industrial
ID0021784
City of Pocatello Water Pollution Control Facility (WPCF)
Upstream
                                      10
                                     WWTP
ND0020681
City of Devils Lake WWTF
Upstream
                                       8
                                     WWTP
NE0113735
MG Waldbaum Company
Upstream
                                       7
                                  Industrial
NM0020141
Los Alamos County WWTF
Upstream
                                       6
                                     WWTP
NM0028355
Los Alamos National Laboratory
Upstream
                                       6
                                  Industrial
OK0000256
Phillips 66 Ponco City Refinery
Upstream
                                       6
                                  Industrial
RI0000191
Kenyon Industries, Inc.
Upstream
                                       1
                                  Industrial
TX0101605
Roberto R. Bustamante WWTP
Upstream
                                       6
                                     WWTP
WA0002925
McKinley Paper Company
Upstream
                                      10
                                  Industrial
WI0003620
Domtar A.W., LLC Water Reclamation Center (WRC)
Upstream
                                       5
                                  Industrial
WI0020605
City of Baraboo WWTP
Upstream
                                       5
                                     WWTP
Note:
* Identifies a facility discharging to Indian reservation waters.
Extrapolation Process
EPA selected all major industrials and all tribal facilities for reasonable potential analyses, so no extrapolation of industrial or tribal facility costs is required for this analysis. As discussed in Section 7, EPA also evaluated reasonable potential for 10 upstream sewerage systems, which were used to extrapolate costs to the remaining upstream sewerage systems that were not included as part of the facility sample. EPA extrapolated costs on a design flow basis (or actual flow where design flow was not available). The total costs for the relevant sewerage systems were divided by their total flow to obtain a unit cost per MGD. EPA then derived the cost for the facilities outside of the sample by multiplying their design flow (or actual flow where design flow was not available) by the unit cost derived from the sample.
Determining Reasonable Potential
EPA conducted an analysis to determine whether dischargers have the reasonable potential (RP) to cause or contribute to an exceedance of the proposed baseline WQS. The analysis followed the approach outlined in the EPA Technical Support Document for Water Quality-based Toxics Control (EPA, 1991). Reasonable potential analysis (RPA) and WQBEL tools from EPA Region 10 were used to assess the effluent quality of the selected dischargers to determine whether criteria values would be exceeded and WQBELs would need to be established.
For all facilities evaluated, EPA used approved regulatory mixing zone (RMZ) dilution factors if authorized and detailed in the NPDES permit fact sheet. If dilution factors were not provided and critical flow data were available, those flows were used in the analysis to derive approximate dilution factors. If neither dilution factors nor critical flows were available for facilities discharging to flowing waters, or if the permit prohibited any mixing zones or dilution factors, an effluent analysis was performed (i.e., EPA made the conservative assumption of no dilution). For lake or marine discharges without available dilution factors, a 10:1 dilution factor was assumed.
Discharge data for the facilities were obtained through ICIS-NPDES and used in the RPA process. For the RPA projections, EPA calculated the maximum effluent concentration of each pollutant analyzed for each facility and applied multipliers to the maximum observed effluent concentration to determine a statistical maximum expected concentration of the pollutant (EPA, 1991). EPA made the following assumptions to determine the maximum expected effluent concentration.
For aquatic life economic analysis criteria, EPA used available effluent data to statistically project the 99[th] percentile effluent concentration with 99% confidence and used this concentration in the RPA analysis.
For human health economic analysis criteria, EPA used available effluent data to calculate the 50[th] percentile effluent concentration if the data set included 10 or more data points or to statistically project the 50[th] percentile with 99% confidence from a smaller data set.
The fewer the number of data points available for the analysis, the larger the multiplying factor used to statistically project a maximum expected concentration of the pollutant.
For purposes of effluent characterization in this analysis, if a result was reported as not detected because the result was below the DL, EPA assumed a result of zero. If the result was reported as less than a specific concentration or as not quantifiable, EPA assumed a result equal to one-half of the DL.
If ambient data for a particular pollutant were not available, EPA used a value equal to one-half the DL for that pollutant as receiving water pollutant concentration in the analysis. However, if one-half of the DL exceeds the most stringent criteria, the RPA tool would calculate negative effluent limitations; to avoid this situation, EPA used a value of zero for receiving water pollutant concentration in such cases.
When the projected concentration at the boundary of the RMZ or at the point of discharge (whichever is appropriate) is less than both the acute and chronic criteria for aquatic life and human health criteria (where applicable), there is no reasonable potential and a WQBEL is not necessary. If the concentration is greater than any applicable criterion, there is reasonable potential and the permit writer develops WQBELs for that pollutant. Exhibit 5-3 summarizes the RPAs for the potentially affected facilities. Appendix A provides the details of the analyses.
Exhibit 5-3 Pollutants Triggering RP for Sample NPDES Dischargers
NPDES ID
Facility Name
Pollutants Triggering RP
(None if blank)
AZ0021415
Colorado River Sewage Joint Venture*
Zinc
AZ0024627
Mesa Northwest WRP*
Bacteria, Ammonia
MI0023655
Mt. Pleasant WWTP*
Bacteria
MI0055808
Union Township WWTP*

MS0053503
Pearl River WWTP*
Bacteria, Ammonia, Copper
MT0030759
City of Hardin WTP*
Bacteria, Copper, Zinc
NY0020508
Salamanca WWTP*
Bacteria, Chlorine
AZ0020524
City of Phoenix 91[st] Avenue WWTP
Bacteria, Ammonia, Chlorine
Cyanide, Manganese
AZ0024121
Pima County WRC Arva Valley WRF

AZ0025208
Town of Florence WWTP
Bacteria, Ammonia, Cyanide
Chlorodibromomethane, Selenium
CA0104973
Coachella Valley Mid-Valley WRP
Bacteria, 4-4'-DDT, alpha-BHC
Ammonia, Chloride, Chlorodibromomethane, Copper
Dichlorobromomethane, Selenium
Silver ,Solids, Dissolved and Salinity, Zinc
CO0031755
Pagosa Area Vista WWTP
Bacteria, Arsenic, Cadmium
Chromium (VI), Copper, Cyanide, Lead, Manganese, Nonylphenol, Selenium, Zinc
IA0004014
CF Industries Nitrogen
Ammonia
IA0004103
MidAmerican-Neal North Energy Center

IA0061859
MidAmerican-Neal South Energy Center
Chlorine
ID0021784
City of Pocatello WPCF
Bacteria, Ammonia, Copper, Selenium
ND0020681
City of Devils Lake WWTF
Ammonia
NE0113735
MG Waldbaum Company
Ammonia, Chlorine, Copper
NM0020141
Los Alamos County WWTF
Bacteria, Aluminum
NM0028355
Los Alamos National Laboratory
Copper, PCBs
OK0000256
Phillips 66 Ponco City Refinery
Ammonia, Chromium (VI), Selenium
RI0000191
Kenyon Industries, Inc.
Aluminum, Ammonia, Chlorine, Copper
TX0101605
Roberto R. Bustamante WWTP
Ammonia, Chlorine
WA0002925
McKinley Paper Company

WI0003620
Domtar A.W., LLC WRC

WI0020605
City of Baraboo WWTP
Ammonia, Chloride
Note:
* Identifies a facility discharging to Indian reservation waters.
Projecting Effluent Limits
For each facility and parameter with RP, EPA calculated average monthly and maximum daily effluent limits using the methodology consistent with EPA's 1991 Technical Support Document for Water Quality-based Toxics Control (TSD). Specifically, EPA calculated wasteload allocations (WLAs) and WQBELs to be protective of aquatic life and human health economic analysis criteria in the receiving water. The methodology accounts for the allowable dilution, ambient concentration, effluent variability, and sampling frequency.
For aquatic life economic analysis criteria, EPA calculated the WLAs (chronic and acute, respectively) using the following equations:
WLAchronic= Dmzx x (WQCchronic  -  Cb) + Cb
and
WLAacute= Dmzx x (WQCacute  -  Cb) + Cb
where,
WLA	= Wasteload allocation
Dmzx	= Dilution factor (Qeff + Qrecevingwater)/Qeff
WQC	= Water quality criterion
Cb	= Ambient background concentration.
A corresponding long-term average (LTA) is calculated from each WLA assuming that the WLA is set at the 99[th] percentile concentration using the following equations:
LTAa = WLAacute x e[[0.5σ2  -  zσ]]
LTAc = WLAchronic x e[[][0.5σ]42  -  [zσ]4[]]
LTAc = WLAchronic x e[[][0.5σ]302  -  [zσ]30[]] (ammonia and selenium only)
where:
σ2 = ln(CV[2] +1) where CV is the coefficient of variation
σ4[2] = ln(CV[2] /4 +1)
σ30[2] = ln(CV[2] /30 +1)
Z= 2.2326 for 99[th] percentile probability basis.
As recommended in the TSD (EPA, 1991), EPA selected the lowest LTA for each facility to calculate the maximum daily limit (MDL) set at the 99[th] percentile concentration and average monthly limit (AML), set at the 95[th] percentile concentration. The AML calculation also depends on an assumed monthly monitoring frequency. The TSD recommends assuming a minimum of four samples per month. The analysis follows this recommendation with the exception of calculating AMLs for aluminum and selenium where the analysis assumes 30 samples per month. As stated in the TSD, assuming a number of samples per month that matches the averaging period of the chronic criteria (4 days for most chronic criteria and 30 days for ammonia and selenium) avoids calculating an AML that exceeds the chronic WLA.
Developing WQBELs for toxic pollutants affecting human health is somewhat different from calculating WQBELs for aquatic life. The exposure period of concern is generally longer (e.g., often a lifetime exposure) and the average exposure, rather than the maximum exposure, is of concern. This analysis followed EPA's recommended approach for setting WQBELs for toxic pollutants for human health protection. The AML is equal to the WLA calculated from the human health toxic pollutant economic analysis criterion and the MDL is calculated from the AML based on expected monitoring frequency and assuming that the MDL is set at a 99[th] percentile concentration and that the AML is set at a 95[th] percentile concentration.
For those facilities demonstrating RP, EPA calculated the potential WQBELs, including the AML and the MDL, shown in Exhibit 5-4. If both effluent limitations were calculated based on aquatic life and human health, they were compared and the more stringent effluent limitation selected. Exhibit 5-4 also provides DLs for each pollutant. All values in Exhibit 5-4 are provided in ug/L unless specified otherwise.
Exhibit 5-4 Summary of WQBELs for Sampled Facilities (ug/L unless specified otherwise)
NPDES ID
Facility Name
Pollutant
DL
AML
MDL
AZ0021415
Colorado River Sewage Joint Venture*
Zinc
                                                                           0.05
                                                                             61
                                                                            120
AZ0024627
Mesa Northwest WRP*
Bacteria (cfu/100 mL)
                                                                            -
                                                                            100
                                                                              -

Ammonia
                                                                             10
                                                                          1,400
                                                                          5,500
MI0023655
Mt. Pleasant WWTP*
Bacteria (cfu/100 mL)
                                                                             -
                                                                            100
                                                                              -
MI00555808
Union Township WWTP
-
                                                                              -
                                                                              -
                                                                              -
MS0053503
Pearl River WWTP*
Bacteria (cfu/100 mL)
                                                                             -
                                                                            100
                                                                              -

Ammonia
                                                                             10
                                                                          1,400
                                                                          5,000

Copper
                                                                            0.5
                                                                            2.0
                                                                            4.4
MT0030759
City of Hardin WTP*
Bacteria (cfu/100 mL)
                                                                            -
                                                                            100
                                                                              -

Copper
                                                                            0.5
                                                                            2.2
                                                                            4.4

Zinc
                                                                           0.05
                                                                             61
                                                                            120
NY0020508
Salamanca WWTP*
Bacteria (cfu/100 mL)
                                                                            -
                                                                            100
                                                                              -

Chlorine
                                                                             10
                                                                             33
                                                                             42
AZ0020524
City of Phoenix 91[st] Avenue WWTP
Bacteria (cfu/100mL)
                                                                             -
                                                                            100
                                                                              -

Ammonia
                                                                             10
                                                                          1,400
                                                                          2,500

Chlorine**
                                                                             10
                                                                            4.0
                                                                             14

Cyanide**
                                                                              5
                                                                            4.5
                                                                            7.9

Manganese
                                                                            0.1
                                                                             30
                                                                             64
AZ0024121
Pima County WRC Arva Valley WRF

                                                                              -
                                                                              -
                                                                              -
AZ0025208
Town of Florence WWTP
Bacteria (cfu/100mL)
                                                                             -
                                                                            100
                                                                              -

Ammonia
                                                                             10
                                                                          1,400
                                                                          5,500

Cyanide**
                                                                              5
                                                                            3.3
                                                                            9.6

Chlorodibromomethane
                                                                          0.003
                                                                           0.66
                                                                            1.3

Selenium
                                                                            0.6
                                                                            1.5
                                                                            5.9

Zinc
                                                                           0.05
                                                                             61
                                                                            120
CA0104973
Coachella Valley Mid-Valley WRP
Bacteria (cfu/100mL)
                                                                            -
                                                                            100
                                                                              -

4,4'-DDT**
                                                                          0.012
                                                                      0.0000040
                                                                      0.0000080

alpha-BHC
                                                                              -
                                                                       0.000058
                                                                        0.00012

Ammonia
                                                                             10
                                                                          1,400
                                                                          4,800

Chloride
                                                                              4
                                                                        190,000
                                                                        380,000

Chlorodibromomethane
                                                                          0.003
                                                                           0.66
                                                                            1.3

Copper
                                                                            0.5
                                                                            2.2
                                                                            4.4

Dichlorobromomethane
                                                                          0.003
                                                                           0.79
                                                                            1.6

Selenium
                                                                            0.6
                                                                            1.5
                                                                            2.0

Silver
                                                                            0.1
                                                                            1.9
                                                                            3.8

Solids, Dissolved and Salinity
                                                                              -
                                                                        250,000
                                                                        270,000

Zinc
                                                                           0.05
                                                                             61
                                                                            120
CO0031755
Pagosa Area Vista WWTP
Bacteria (cfu/100mL)
                                                                             -
                                                                            100
                                                                              -

Ammonia
                                                                             10
                                                                          1,400
                                                                          5,200

Cadmium
                                                                           0.05
                                                                            0.5
                                                                            1.4

Chromium (VI)
                                                                            0.3
                                                                             11
                                                                             12

Copper
                                                                            0.5
                                                                            1.4
                                                                            4.4

Cyanide**
                                                                              5
                                                                            4.0
                                                                            4.0

Lead
                                                                            0.6
                                                                            1.4
                                                                            4.7

Manganese
                                                                            0.1
                                                                             50
                                                                             91

Nonylphenol

                                                                            4.9
                                                                             12

Selenium
                                                                            0.6
                                                                            1.5
                                                                            2.7

Zinc
                                                                           0.05
                                                                             61
                                                                            120
IA0004014
CF Industries Nitrogen
Ammonia
                                                                             10
                                                                         77,000
                                                                        200,000
IA0004103
MidAmerican-Neal North Energy Center
-
                                                                              -
                                                                              -
                                                                              -
IA0061859
MidAmerican-Neal South Energy Center: Outfall 001
Chlorine
                                                                             10
                                                                             13
                                                                             24

MidAmerican-Neal South Energy Center: Outfall 007
Chlorine
                                                                             10
                                                                             13
                                                                             27
ID0021784
City of Pocatello WPCF
Bacteria (cfu/100mL)
                                                                             -
                                                                            100
                                                                              -

Ammonia
                                                                             10
                                                                         2,6600
                                                                         12,000

Copper
                                                                            0.5
                                                                            5.0
                                                                            7.9

Selenium
                                                                            0.6
                                                                            3.0
                                                                            8.7
ND0020681
City of Devils Lake
Ammonia
                                                                             10
                                                                          2,600
                                                                         25,000
NE0113735
MG Waldbaum Company
Ammonia
                                                                             10
                                                                          1,400
                                                                          5,400

Chlorine**
                                                                             10
                                                                            8.1
                                                                             19

Copper
                                                                            0.5
                                                                            2.2
                                                                            4.4
NM0020141
Los Alamos County WWTF
Bacteria (cfu/100mL)
                                                                             -
                                                                            100
                                                                              -

Aluminum
                                                                              -
                                                                             67
                                                                            150
NM0028355
Los Alamos National Laboratory
Copper
                                                                           0.5
                                                                            2.2
                                                                            4.4

PCBs**
                                                                           0.03
                                                                      0.0000090
                                                                       0.000018
OK0000256
Phillips 66 Ponco City Refinery
Ammonia
                                                                             10
                                                                          1,400
                                                                          5,300

Chromium (VI)
                                                                            0.3
                                                                            5.0
                                                                             16

Selenium
                                                                            0.6
                                                                            1.5
                                                                            2.4
RI0000191
Kenyon Industries, Inc.
Aluminum

                                                                          1,200
                                                                          3,700

Ammonia
                                                                             10
                                                                         32,000
                                                                        104,000

Chlorine
                                                                             10
                                                                            190
                                                                            480

Copper
                                                                            0.5
                                                                             57
                                                                             82
TX0101605
Roberto R. Bustamante WWTP
Ammonia
                                                                             10
                                                                          1,400
                                                                          2,600

Chlorine
                                                                             10
                                                                             11
                                                                             12
WA0002925
McKinley Paper Co.
-
                                                                              -
                                                                              -
                                                                              -
WI0003620
Domtar A.W., LLC WRC
-
                                                                              -
                                                                              -
                                                                              -
WI0020605
City of Baraboo
Ammonia
                                                                             10
                                                                          1,400
                                                                          4,200

Chloride
                                                                              4
                                                                        220,000
                                                                        250,000
Notes:
* Identifies a facility discharging to Indian reservation waters.
** DL is greater than AML, MDL, or both. Compliance cost estimates for this facility and pollutant are based on the DL.
Identifying Control Scenarios
Analysis of the available data for the sampled facilities indicates that implementing the economic analysis criteria would likely result in exceedances of projected effluent limits for bacteria, ammonia, chlorine, cyanide, and various metals and organic compounds. Potential alternatives for compliance with effluent limits for these pollutants include:
Optimizing treatment processes (e.g., adding chemicals to increase flocculation or filtration efficiency) to increase pollutant removal efficiencies;
Source control (e.g., P2 programs);
Installing effluent treatment technology (e.g., chemical precipitation and filtration, ion exchange granular activated carbon (GAC)); and,
Alternative compliance mechanisms such as WQS variances, dilution credits (e.g., new or revised mixing zones), or criteria based on site-specific conditions.
Dischargers will likely pursue the lowest cost means of compliance with effluent limits first and may pursue multiple compliance mechanisms (e.g., P2 and treatment). The following section describes the various options for compliance considered in this analysis.
Process Optimization
The lowest cost option to comply with effluent limits is likely the adjustment of existing treatment (i.e., process optimization). This option would be most feasible where relatively low pollutant reductions are needed or monitoring data indicate that pollutant loads increase throughout the treatment process as a result of chemical additions or treatment techniques.
Process optimization usually involves process analysis and process modifications. Process analysis is an investigation of the performance-limiting factors of the treatment process and is a key factor in achieving optimum treatment efficiency. Performance-limiting factors for common wastewater treatment processes (e.g., sedimentation, activated sludge, filtration) may include operator training, response to changes in wastewater quality, maintenance activities, automation, and process control testing. The cost of process analysis includes the cost of additional or continuous monitoring throughout the treatment process, and a treatment performance evaluation. These costs vary based on the number of treatment processes to be analyzed and the magnitude of the reductions needed.
Process modifications include activities short of adding new treatment technology units (conventional or unconventional) to the treatment train. For increasing pollutant removal efficiencies, process modifications could include adjusting coagulant doses to increase settling, equalizing flow if pollutant concentrations change during wet weather events, increasing filter maintenance activities or backwash cycles, training operators, and installing automation equipment including necessary hardware and software. Several months of adjustments may be needed to achieve a desired level of process optimization. In practice, the process modifications necessary would be determined by the process analysis study.
The effectiveness of process optimization largely depends on the efficiency of current operations, the existing treatment processes, and the fate and transport of the pollutant through the treatment train. For example, if a facility is already well maintained and operated, implementing process optimization may not result in additional pollutant reductions because the existing treatment processes are already performing at their feasible limits. Also, because most conventional treatment technologies are designed to maximize removal of suspended solids, process optimization aimed at increasing those removal efficiencies may not result in significant reductions for pollutants existing primarily in dissolved form. Given the available information for the sample facilities, it is generally not possible to estimate the reductions achievable with process optimization; rather, a detailed, site-specific study would be necessary. However, it is expected that process optimization may address compliance with effluent limits on ammonia and bacteria (see Appendix C for information on process optimization).
Source Controls (Pollution Prevention Programs)
If adjusting existing operations is not feasible or not sufficient to achieve the necessary reductions, source controls would likely be the next most cost-effective control option. Source control could be used alone, or in conjunction with process optimization. The feasibility of source control efforts depends on the makeup of the influent and potential sources of the pollutant. For example, certain toxic pollutants are primarily used in industrial processes. Thus, for a municipal facility with a pre-treatment program, a feasible source control option would be regulating indirect industrial dischargers through pretreatment permits. Municipal facilities without a pre-treatment program may seek to implement one targeting the toxic pollutants of concern. Facilities that primarily treat commercial and residential wastewater (e.g., POTWs with no indirect industrial discharger) would likely have to concentrate efforts on public outreach and education or a sewer use ordinance.
Costs for source control activities depend on the pollutant and the measures or controls implemented. For this analysis, EPA estimated that, where pollutant reductions were needed, most of the sample facilities would pursue P2 programs for targeted pollutants. However, as contributing sources are identified and controlled, the cost-effectiveness and efficacy of a P2 program will diminish, and a discharger may need to pursue additional compliance mechanisms.
Successful P2 programs will likely include at least some of the following steps:
Identify sources  -  particularly sources that contribute the greatest load to the influent;
Form a workgroup  -  preferably composed of representatives from government, industry, community, and environmental organizations that are either familiar with P2 strategies or familiar with the pollutant(s);
Define program goals  -  including a statement of how the municipality intends to reduce pollutant levels in its effluent, the purpose for doing so, and a timeline for completion;
Develop an approach  -  including selecting sectors for P2 efforts, the criteria for targeting efforts (e.g., size of the source loading, authority available to control the source, time required to produce desired results), whether efforts will be voluntary or regulatory, and who will execute each program effort;
Estimate program costs  -  develop estimates and identify entities that will bear the costs;
Implement program  -  starting with the most cost-effective measures and modifying activities and approach based on measured results;
Assess progress  -  including both successes and failures (i.e., lessons learned) throughout the duration of the program;
Provide follow-up  -  necessary to ensure P2 measures continue to be implemented; and
Develop a contingency plan  -  including a description of actions to be taken if plan efforts are unsuccessful.
The focus and approach of the program will be different for each community and sector targeted. As such, plans vary in complexity and in the resources necessary to achieve the goals set forth.
The reductions in pollutants achievable through P2, and thus the ability to achieve compliance with numeric effluent limits using P2 alone, will vary based on existing treatment processes, complexity of the facility (for industrial discharges), the makeup and size of the service area of a WWTP (e.g., number of potential pollutant sources), and the level of P2 already being implemented. For example, large municipal facilities with numerous potential pollutant sources may see significant reductions after implementation of a measure that targets a major influent copper source, such as: requiring a pre-treatment permit from a sheet metal manufacturer or encouraging the main drinking water utilities in the service area to adjust pH levels in drinking water to the extent feasible. However, facilities with much smaller service areas may not be able to achieve the same reductions in their effluent with P2 due to a lower percent of easily identifiable and controllable sources contributing to the influent pollutant load. For example, sources from the residential sector are not as easy to identify as those from industrial and commercial sectors because they may originate from a wide range of products, as well as residential water pipes. Smaller municipalities are likely to receive most of their inflow from the residential sector.
Little information is available on the cost of P2 programs for individual pollutants. For municipal dischargers, community size is likely to be a factor affecting P2 program costs. For example, it is unlikely that a minor POTW would need the same resources for program development and outreach efforts as a large major municipal facility because the minor facility's service area is smaller and contains fewer households and commercial/industrial dischargers to target. Smaller facilities may also pool their resources and develop a joint P2 program to save time and money on program development and outreach materials. Likewise, smaller industrial facilities engaging in a limited number of manufacturing processes should need to expend less resources on a P2 program than a large, complex industrial facility with multiple operations processing a variety of raw materials. P2 programs and program costs are discussed further in Appendix B.
Effluent Treatment
If process optimization or source control is not sufficient for compliance with the economic analysis criteria, alternative discharge options or effluent treatment technologies may be necessary. For some facilities and pollutants of concern, EPA assumed that the control options implemented would include both effluent treatment and a P2 program.
For metals such as copper and cadmium, technologies that primarily target the dissolved fraction of the pollutant are most likely to achieve low effluent levels because most of the particulate fraction will already be removed with existing treatment controls designed to remove solids (see discussion of Process Optimization). For organic pollutants such as 4,4-DDT and alpha-BHC, similar treatment technologies can be used, although operating parameters may have to be adjusted to achieve optimal removal rates. An effective way to reduce disinfection by-products (e.g., trihalomethanes such as chlorobromomethane and dichlorobromomethane) may be to remove precursors in the effluent prior to disinfection, or to change the disinfection process.
Exhibit 5-5 summarizes selected effluent treatment technologies that could be used to remove the pollutants of concern. Note that although these technologies theoretically should be able to achieve the levels needed to meet the baseline and revised criteria, it is likely pilot studies would be required at each facility to confirm technology performance prior to full-scale effluent implementation at that facility. It should also be noted that local water quality information (e.g., hardness, DOC) for some of these facilities could significantly change the numeric translation of the baseline narrative criteria (e.g., copper and other dissolved metals).
Exhibit 5-5 Summary of Potential Effluent Treatment Technologies
Technology
Pollutants Removed
Comments
Chemical Precipitation
Metals (e.g., copper and cadmium)
Pre-oxidation likely necessary to achieve low effluent levels; removal rates may be highly dependent on pH and other wastewater characteristics.
Nitrification
Ammonia
Requires sufficient oxygen and alkalinity
Chlorination
Cyanide
Requires addition of dechlorination
Dechlorination
Chlorine
Use of sulfur dioxide gas for dechlorination requires numerous safety precautions
Ion Exchange
Metals (e.g., copper and cadmium), nitrate, and radionuclides
System would have to be optimized for removal of a specific pollutant to achieve low effluent levels.
Granular Activated Carbon
Refractory organics (e.g., DDT, BHC), cyanide, PCBs, and some dissolved metal ions
Pretreatment to remove solids and prevent fouling; disposal of spent media could be costly.
Reverse Osmosis
Inorganics (e.g., copper, cyanide), pesticides, and microbial pollutants
Pretreatment (e.g., microfiltration) to prevent fouling; may need multiple units in series to achieve low effluent levels.

Appendix C provides detailed information on each treatment technology.
Alternative Compliance Mechanisms
If none of the control options discussed above would result in meeting the potential effluent limitations, or if the costs of available treatment would be prohibitive, dischargers would likely pursue some form of relief from the requirements. EPA estimated costs for WQS variances and dilution credits as alternative compliance mechanisms.
WQS Variances
40 CFR 131.14 describes federal WQS variances. A WQS variance is a time-limited designated use and water quality criterion for a specific pollutant(s) or water quality parameter(s) that reflect the highest attainable condition during its term.
WQS variances adopted in accordance with § 131.14 provide a flexible but defined pathway for states and authorized tribes to make incremental water quality improvements when the state or authorized tribe demonstrates that the applicable designated use and associated criteria are not immediately attainable but may be attainable in the future. Per § 131.14(b)(1)(ii), WQS variances specify the interim requirements that apply during the WQS variance term based on the highest attainable condition. Further, WQS variances, if approved by EPA, become the applicable WQS for certain purposes during the term of the WQS variance: most importantly, they serve as the basis for water quality based effluent limits in NPDES permits or when issuing certifications under section 401 of the Act, for the permittee, parameter, and water body identified in the WQS variance. (§ 131.14(a)(3)). Once the WQS variance expires, NPDES permits must be written to meet the underlying designated use and associated criterion. If dischargers are still unable to meet the WQBELs derived from the designated use and criterion once a WQS variance term is complete, the state or authorized tribe may adopt a subsequent WQS variance consistent with § 131.14.
Dischargers for whom meeting effluent limits is cost-prohibitive are most likely to pursue a WQS variance based on economic infeasibility (i.e., the sixth condition above). The analysis to support such an application likely begins with a technical feasibility analysis, costs for which are detailed in Appendix B and summarized in Section 4.4.5. EPA based unit costs for applying for WQS variances on estimates previously developed for the economic analysis for EPA's copper and cadmium rule for the State of Oregon (EPA, 2016b). To account for a nationwide potential cost, EPA updated the Oregon costs to reflect national labor rates. The WQS variance process and cost estimation are detailed in Appendix B and the costs are summarized in Section 4.4.5.
Mixing Zones and Dilution Credits
The CWA does not require that all criteria be met at the exact point where pollutants are discharged into a receiving water prior to the effluent mixing with the receiving water. Sometimes it is possible to expose aquatic organisms to a pollutant concentration above a criterion for a short duration within a limited, clearly defined area of a waterbody while still maintaining the designated use of the waterbody as a whole. Where this is the case, a state or authorized tribe may find it appropriate to allow ambient concentrations of a pollutant above the criterion in small areas near point-source outfalls, referred to as mixing zones (EPA, 2014).
Mixing zones may be established when a discharger has applied all known and reasonable controls and a dilution study has been performed. This study is the basis for calculating a potential dilution credit for a given pollutant. Dilution credits account for the assimilative capacity of the receiving water when computing the WLA applicable to a specific parameter that then becomes the basis for effluent limitations. Once approved, a dilution credit can reflect no more than the level of effluent and ambient receiving water mixing that occurs under critical conditions.
Dischargers who cannot readily comply with effluent effluent limitations based on the economic analysis criteria and who do not currently have an approved dilution credit for a pollutant of concern may elect to pursue approval of a dilution credit to achieve compliance with effluent limitations. A number of the NPDES permits from the facility sample already include dilution credits, but the permittees could still apply for a revision of these provisions.
When applying for a dilution credit a specific study is required to estimate and document the level of mixing that is present in the receiving water under applicable critical conditions. Details on the cost estimate for a dilution study are provided in Appendix B. Costs for a dilution study are also shown in Section 4.4.5.
Method for Identifying Potential Impairments and Characterization of Nonpoint Sources
This section describes the method EPA used for estimating the number of waters that may be identified as impaired based on comparison of available water quality monitoring data to the economic analysis criteria described in Section 3.3. Identification of impairments may lead to the need to further address nonpoint sources. Therefore, this sections also describes the major categories of nonpoint sources and ways to control their impact on water quality.
Available Data to Evaluate Impairments
To assess the degree to which tribal waters may be impaired, EPA evaluated available data to evaluate current conditions to the economic analysis criteria described in Section 3.3. EPA first downloaded available instream monitoring water quality data of Indian reservation waters from the EPA and USGS' Water Quality Portal (WQP) and matched each monitoring station to the nearest water body from the USGS' NHD. EPA then used this data to assess the degree to which existing conditions are in compliance with economic analysis criteria. Although not representative of all Indian reservation surface waters, the locations for which monitoring data exceed the economic analysis criteria are candidates for listings of impaired waters for the purpose of estimating impacts.
The WQP has data for over 630,000 sampling locations across the U.S. but does not identify tribal waters and/or locations. To narrow the sampling locations prior to downloading WQP data, EPA identified NHD waterbodies within two miles of Indian reservation waters and selected all sampling locations within one mile of those waterbodies (approximately 25,000 locations), and used these locations' hydrologic unit code (HUC) level 8 to download water quality data at the HUC8 level. EPA then identified the closest water body to each sampling location (e.g., stream, pond), grouped sampling locations by water body, and excluded non-tribal waters from the analysis.
EPA downloaded the WQP data from these sampling locations for all available pollutants from January 1, 2011 to December 31, 2020. This is a reasonable timeframe to potentially include all of the tribes' regularly monitored waters while still being relevant in characterizing current conditions. EPA conducted a review of the data for potential unit conversions and issues (e.g., unexpected units or lack thereof, data out of expected range  -  such as for pH, multiple names/acronyms for the same pollutant), and used the remaining data to identify exceedances of the economic analysis criteria. EPA also restricted the data to include only a single observation for each station and parameter on a single date. In most cases, EPA used the maximum concentration but used the minimum in cases where the economic analysis criteria represent a minimum concentration (e.g., dissolved oxygen).
Exhibit 6-1 provides a summary of the data used for the impairments analysis.
Exhibit 6-1 Available Water Quality Data for Tribal Waters for Parameters with Economic Analysis Criteria
Parameter
Number of Waterbodies with Observations
Number of Observations* Across Waterbodies
2,4-Dichlorophenol
                                                                              1
                                                                              1
Alkalinity
                                                                            128
                                                                          2,027
Aluminum
                                                                             50
                                                                            437
Ammonia
                                                                            175
                                                                          2,248
Anthracene
                                                                              1
                                                                              1
Antimony
                                                                             32
                                                                            352
Arsenic
                                                                            103
                                                                          1,045
Barium
                                                                             51
                                                                            647
Benzene
                                                                              1
                                                                              1
Cadmium
                                                                             30
                                                                            125
Carbaryl
                                                                              2
                                                                             38
Chloride
                                                                            184
                                                                          2,418
Chlorine
                                                                              3
                                                                             21
Chlorpyrifos
                                                                              2
                                                                             27
Chromium (III)
                                                                             34
                                                                            209
Chromium (VI)
                                                                              1
                                                                              1
Copper
                                                                             58
                                                                            423
Cyanide
                                                                              1
                                                                              1
Diazinon
                                                                              3
                                                                             26
Dieldrin
                                                                              2
                                                                              4
E. coli
                                                                            125
                                                                          2,041
Enterococci
                                                                              3
                                                                             66
Fluoranthene
                                                                              7
                                                                             18
Iron
                                                                            123
                                                                          1,106
Isophorone
                                                                              8
                                                                             44
Lead
                                                                             59
                                                                            331
Malathion
                                                                              1
                                                                              1
Manganese
                                                                            128
                                                                          1,222
Methylmercury
                                                                              4
                                                                             32
Mirex
                                                                              1
                                                                              1
Nickel
                                                                             37
                                                                            533
Nitrates
                                                                             98
                                                                          1,419
Oxygen, Dissolved
                                                                            213
                                                                          3,017
pH
                                                                            348
                                                                          4,403
Phenol
                                                                              3
                                                                              5
Pyrene
                                                                              6
                                                                             11
Selenium
                                                                             90
                                                                            774
Silver
                                                                             15
                                                                            112
Toluene
                                                                              5
                                                                              8
Zinc
                                                                             58
                                                                            327
Notes:
* Includes records with reported values for parameters with economic analysis criteria (see Section 3.3) between 2011 and 2020.
Identifying Potential Impairments
EPA used the GIS data for the USGS NHD streams and catchments to group the sampling locations by water body (i.e., NHD reach), and conduct the assessment at the reach basis (identified as feature ID in the NHD data). EPA assigned to each sampling location the feature ID of the stream catchment in which it is located, such that multiple sampling stations are assigned the same feature ID when they are located in the same catchment.
Depending on the type of pollutant, EPA identified a potential impairment for a pollutant in a particular stream reach when the following assumptions were met:
Conventional pollutants: 10 percent of all the samples in a five-year rolling window exceed the economic analysis criteria.
Toxic pollutants: two or more sample results collected on different sampling dates in a three-year rolling window exceed the economic analysis criteria.
EPA applied the conventional pollutant methodology to alkalinity, bacteria, dissolved oxygen, and total dissolved solids (TDS) and assigned the toxic methodology to all other pollutants. The analysis showed impairments of Indian reservation waters for 25 pollutants for either human health, aquatic life, or both economic analysis criteria. Exhibit 6-2 summarizes the potential impairments to Indian reservation waters by providing the number of feature IDs (reaches) potentially impaired for each pollutant and economic analysis criteria.
Exhibit 6-2 Number of Reaches on Indian Reservation Waters that are Potentially Impaired by Economic Analysis Criteria and Parameter*
Parameter
AL Acute
AL Chronic
HH
Any Criteria**
Alkalinity***

                                                                            114

                                                                            114
Aluminum
                                                                              3
                                                                             15

                                                                             15
Ammonia
                                                                              0
                                                                              2

                                                                              2
Antimony

                                                                              1
                                                                              1
Arsenic
                                                                              1
                                                                              2

                                                                              2
Barium

                                                                              1
                                                                              1
Cadmium
                                                                              1
                                                                              3

                                                                              3
Chloride
                                                                              1
                                                                              1

                                                                              1
Chlorine
                                                                              3
                                                                              3

                                                                              3
Chromium (III)
                                                                              0
                                                                              1

                                                                              1
Copper
                                                                             10
                                                                             14
                                                                              1
                                                                             14
Dieldrin
                                                                              0
                                                                              0
                                                                              1
                                                                              1
E. coli***

                                                                             68
                                                                             68
Enterococci***

                                                                              3
                                                                              3
Iron

                                                                             22

                                                                             22
Lead
                                                                              1
                                                                             11

                                                                             11
Manganese

                                                                             56
                                                                             56
Methylmercury
                                                                              1
                                                                              1
                                                                              1
                                                                              1
Nickel
                                                                              0
                                                                              1
                                                                              1
                                                                              1
Nitrates

                                                                             18
                                                                             18
Oxygen, Dissolved***
                                                                             60
                                                                             60

                                                                             60
pH***

                                                                             74
                                                                             54
                                                                             74
Selenium
                                                                              0
                                                                             24
                                                                              0
                                                                             24
Silver
                                                                              2

                                                                              2
Zinc
                                                                              2
                                                                              2
                                                                              1
                                                                              2
Total
                                                                             85
                                                                            350
                                                                            206
                                                                            500
Notes:
AL = aquatic life; HH = human health
* Blanks indicate that there is no economic analysis criteria for the parameter.
**Note that the number of waterbodies with impairments under any economic analysis criteria is not the sum of the waterbodies with individual economic analysis criteria impairments, since one water body may be impaired across more than one economic analysis criteria.
***Impairments for these pollutants used the conventional pollutant methodology.
EPA's evaluation of water quality data indicates that 215 reaches on Indian reservations would be considered impaired for at least one pollutant and economic analysis criteria under the proposed WQS, with many reaches impaired for multiple pollutants. Impairments total 500 when including all waterbodies and pollutants, for an average of 2.3 pollutant impairments per reach.
Nonpoint Source Discharge Categories
Pollutants can be introduced to surface water through natural and human activities that occur over large, diffuse areas and do not discharge at single, identifiable locations. These sources are referred to as nonpoint sources and can include agriculture, forestry, mining, urban stormwater, septic systems, atmospheric deposition, and contaminated sediments (legacy sources). The following sections describe these categories of nonpoint source dischargers, including the types of pollutants they may introduce into surface waters.
Agriculture
Pesticides, fertilizers, and other chemicals applied to agricultural land can reach surface waters through irrigation return flow, stormwater runoff, and erosion of soils. Many chemicals on the human health and aquatic life pollutant lists are used as part of current and past agricultural practices, and therefore may enter surface waters on Indian reservations. For example, atrazine is an herbicide used primarily on farms to kill weeds. Guthion is an organophosphorous pesticide that was used on many crops, especially apples, pears, cherries, peaches, almonds, and cotton. Its use is being phased out by EPA due to toxicity concerns, but guthion residue may persist in the environment. Endosulfin is a pesticide used to control insects on food and non-food crops and also as a wood preservative. Nitrate and phosphorous are key components of fertilizers. Metals, such as cadmium and copper, can also be present in agricultural fertilizers or pesticides. In addition, erosion of soil on agricultural lands can increase TSS loads in surface water.
Farm animals can contribute bacteria and excess nutrients to downstream waters through fecal waste. Also, chemicals may be added to their feed or used directly on the animals for veterinary purposes. As an example, chlorpyrifos is an insecticide used to control ticks on cattle, as well as a spray to control crop pests.
Forestry
Forestry can contribute to surface water pollution through timber harvesting, thinning, road construction, fertilization, and chemical application. For example, to meet requirements for rapid reforestation after harvesting, forest landowners apply herbicides to protect tree seedlings from competing plants. Other chemicals may be used to control insects on forestry crops, such as hexachlorocyclohexane (HCH). Soil erosion is a significant concern in areas that are actively managed for forestry products because removal of trees and creation of forest roads can lead to increased TSS loads and turbidity in downstream surface water.
The processing of forestry products may also generate pollutants. For example, chlorophenols (e.g., 2,4,5-trichlorophenol, 2,4,6-trichlorophenol, and 2,4-dichlorophenol) and dioxin (2,3,7,8-TCDD) may be formed during the chlorine bleaching process at pulp and paper mills. Dioxin is known to be a human carcinogen, according to the National Toxicology Program.
Mining
Both currently active and abandoned/inactive mine sites can contribute to elevated pollutant concentrations in surface waters. Mining activities require large amounts of water to process ore, which results in discharged effluent (regulated as a point source discharge under the NPDES program), as well as seepage from tailings storage facilities, and accidental releases (both of which may be considered nonpoint source discharges). In addition to this direct contamination, exploratory activities such as road building and erosion of mineralized overburden during mine construction can also contribute to the contamination of surface water (Jennings et al., 2008). The leaching of heavy metals from excavated rock is especially problematic when mine wastes with high acid-generating potential are oxidized through exposure to surface conditions.
To gain an understanding of the types of active and inactive mines present on Indian reservations, EPA obtained geospatial data from the USGS Mineral Resources Data System (MRDS). MRDS has state-by-state geospatial data on mines and mineral resources. EPA selected five representative states that were anticipated to have numerous mines on Indian reservations: Arizona, Utah, Washington, California, and South Dakota. Mine data for Indian reservations within these states was then extracted from the MRDS layers. The mine data were then further refined based on development status: only those mine sites that were listed as "producer" or "past producer" were included in the analysis; mines whose development status was listed as "occurrence", "prospect", or "unknown" were not included.
On Indian reservations in Arizona, Utah, Washington, California, and South Dakota, MRDS listed 925 mines that were either a "producer" or "past producer" (i.e., active or inactive) with information on the type of material mined at the site. Of these 925 mine sites, 44 percent indicated their primary commodity was sand and gravel, while 44 percent indicated their primary commodity was some combination of metals, including barium, beryllium, copper, lead, iron, manganese, mercury, silver, titanium, uranium, and zinc. The remaining 11 percent of mines had varied commodities, including sulfur, asbestos, nitrate, and phosphorous. This analysis of readily-available geospatial data provides a snapshot of the types of mines that may be present on Indian reservations and therefore, the types of pollutants that may make their way into site run-off.
Other chemicals may be used in the mining process that can potentially contaminate surface waters. For example, cyanide is currently employed to separate gold and silver from ore, while liquid mercury was used in the past. According to the MRDS data, silver and gold are primary commodities for 208 and 52 past or present mine sites, respectively, on Indian reservations in Arizona, Utah, Washington, California, and South Dakota. Thus, cyanide and mercury could potentially leach from these active or inactive mines.
Septic Systems
Septic systems (also known as onsite wastewater disposal systems) are used to treat and dispose of sanitary waste and are particularly common in rural areas. When properly sited, designed, constructed, and operated, septic systems pose a relatively minor threat to water sources. However, improperly operated septic systems can be a significant nonpoint source of groundwater contamination, which can lead to surface water pollution at the groundwater-surface water interface.
Septic systems are a significant source of groundwater contamination leading to waterborne disease outbreaks and other adverse health effects. The bacteria (e.g., Escherichia coli), protozoa, and viruses found in sanitary wastewater can cause numerous diseases, including gastrointestinal illness, cholera, hepatitis A, and typhoid. In addition, septic systems can be a significant source of nitrate (e.g., from urine, feces, food waste, and cleaning compounds present in sanitary wastewater), which can contaminate groundwater over time (EPA, 2001b).
Atmospheric Deposition
Atmospheric deposition may be a potential nonpoint source of pollutants to surface waters through either direct or indirect deposition. Direct deposition occurs when pollutants are deposited directly on surface waters from the atmosphere. Indirect deposition reflects the process by which pollutants deposited on the land surface are washed off during storm events and enter surface water through stormwater run-off. Atmospheric deposition is not directly addressed through any existing regulation.
Atmospheric deposition of pollutants from industrial emissions, fossil fuel combustion, open pit mining, wind erosion, and other activities can contribute to pollution of Indian reservation surface waters. For example, chlorinated dibenzo-p-dioxins, such as dioxin, are released into the air in emissions from municipal solid waste and industrial incinerators. PAHs can be formed during incomplete burning of coal, oil and gas, garbage, or other organic substances. In addition, PCBs can exist as vapor in air and can be either directly or indirectly deposited in surface water. PCBs have been used as coolants and lubricants in transformers, capacitors, and other electrical equipment. The manufacture of PCBs was stopped in the United States in 1977 because of evidence they build up in the environment and can cause harmful health effects. Products made before 1977 that may contain PCBs include old fluorescent lighting fixtures and electrical devices containing PCB capacitors, and old microscope and hydraulic oils. PCBs are reasonably anticipated to be a human carcinogen, according to the National Toxicology Program.
Contaminated Sediments/Legacy Sources
When pollutants enter a water body through run-off, precipitation, or other means, they can accumulate in sediment at the bottom of wetlands, ponds, lakes, or rivers. Once in the sediment, these pollutants can persist for many years and are therefore often referred to as "legacy sources." These pollutants can affect the health of benthic organisms and can degrade overall water quality when the sediments are disturbed and resuspended.
There are several major migration pathways for pollutants to reach sediments. Tributaries can carry pollutants, such as nutrients and PCBs. Nutrients, pesticides, (e.g., atrazine, and chlordane), chlorinated solvents (e.g., dichloromethane, tetrachloroethene, trichloroethane, and tricholoroethene), and fuel hydrocarbons can reach sediments through the groundwater-surface water interface. Atmospheric deposition can be a source of pollutants to sediments, including dioxin, PCBs, PAHs, and mercury. In addition, agricultural runoff can add to pollutant burden in sediments with pesticides and nutrients (Adriaens et al., 2002)
Legacy sources can persist long after a chemical has been banned from use. For example, the pesticide DDT was once widely used to control insects in agriculture and insects that carry diseases such as malaria. The use of DDT in the United States was banned in 1972 because of harm to wildlife. However, studies have found evidence of DDT in river sediments decades after its use was banned (Phillips et al., 1997).
Identifying Potential Control Actions and Costs
Implementation of economic analysis criteria could result in identifying the need for additional controls on nonpoint sources of pollution, such as agriculture, forestry, mining, urban stormwater, septic systems, atmospheric deposition, and contaminated sediment. Exhibit 6-3 summarizes potential control actions required for nonpoint source dischargers.
Exhibit 6-3 Potential Control Actions Required for Nonpoint Sources of Contamination
Nonpoint Source
Potential Control Actions
Agriculture
Changes in fertilizer or pesticide use, sediment erosion controls beyond those under existing regulations
Forestry
Changes in fertilizer or pesticide use, sediment erosion controls beyond those under existing regulations
Mining
Cleanup and remediation, including excavation and onsite capping of contaminated soils, capping of onsite solid waste mining debris, re-grading of tailings to mitigate mass wasting and off-site migration, and abatement and mitigation of physical hazards
Septic Systems
Improve O&M of existing septic systems, upgrade failing septic systems, build centralized wastewater treatment facilities to replace septic systems, where feasible
Atmospheric Deposition
Reduce air pollution at industrial facilities, control actions for point source dischargers and nonpoint sources
Contaminated Sediments/Legacy Sources
Control actions for point source dischargers and nonpoint sources listed above, clean up and remediation including excavation of contaminated sediments

Many of the controls and BMPs described above can have positive cumulative effects. For example, BMPs that control the erosion of toxic-containing sediments, such as increased riparian buffers, may also reduce stream temperatures by providing shade, and reduce nutrient loads by increasing nutrient uptake by plants. Buffers also slow runoff (reducing erosion), filter pollutants, and trap sediments. Thus, it is possible that controls can be implemented to meet multiple economic analysis criteria.
Nonpoint source controls, whether required through a nonpoint source program or implemented voluntarily, may lead to nonpoint sources incurring costs as an indirect result of the proposed baseline WQS. EPA did not estimate the costs of reducing pollution from nonpoint sources to meet the proposed baseline WQS for this analysis. This type of analysis would require site-specific knowledge and modeling that are beyond the scope of this analysis. Nonpoint source discharges are difficult to quantify because they are intermittent, variable, and occur under hydrologic or climatic conditions associated with precipitation events. In addition, nonpoint sources are not subject to regulatory programs under the CWA. Thus, data are too limited to reliably estimate the extent of incremental nonpoint source controls needed to comply with the economic analysis criteria for purposes of this analysis.
Implementing nonpoint source controls may relieve a portion of the estimated indirect burden on and cost to point sources within the same watershed. Control of nonpoint sources of the pollutants of concern could reduce costs to point sources.
Potential Compliance Costs
This section summarizes the estimates of potential costs of implementing the economic analysis criteria, and discusses the limitations and uncertainties associated with the analysis. It includes a discussion of the estimated potential costs to point sources and a brief discussion of potential costs to nonpoint sources.
Potential Compliance Costs for Point Sources
For the 26 major facilities in the sample for this economic analysis, EPA estimated costs associated with actions or controls to meet the economic analysis criteria. Appendix A provides additional details on the cost estimates for each of the 26 facilities in the sample. EPA identified nitrification, chlorination/dechlorination, chemical precipitation, adsorption, and ion exchange as the most likely control options where additional treatment may be required. As noted previously, EPA assumed that the control options implemented would include both effluent treatment and a P2 program for some facilities and pollutants of concern. If none of the control options considered would result in meeting the potential effluent limitations, or if the costs of available treatment would be prohibitive, dischargers would likely pursue relief through an alternative compliance mechanism, such as a WQS variance, along with a P2 program. Appendix B provides a detailed description of the estimated costs of alternative compliance mechanisms. Some facilities may be able to use alternative compliance mechanisms other than a WQS variance and accompanying P2 program (e.g., dilution credit) at a lower cost, so assuming a WQS variance with a P2 program as the main alternative compliance mechanism may over-estimate cost. For some facilities and pollutants of concern, the available data did not clearly point to a specific effluent treatment technology or an alternative compliance mechanism as the most likely approach to compliance. In such cases, EPA estimated a range of potential costs for the facility. These costs are summarized in Exhibits 7-1 through 7-3 below.
As discussed in Section 5.4.1, RPAs were conducted for all 7 major facilities discharging directly to Indian reservation waters. Only 2 of the 7 major dischargers to Indian reservation waters (Pearl River WWTP and Salamanca STP) were projected to potentially incur costs for additional treatment. EPA estimated the capital and O&M costs for effluent treatment at both facilities, EPA annualized capital costs over 20 years using a 3 and 7 percent discount rate. In addition, the Pearl River WWTP could also potentially pursue an alternative compliance mechanism (i.e., a WQS variance with a P2 program) rather than effluent treatment. The other five facilities either (1) have no reasonable potential for any pollutant, (2) should be able to optimize their treatment systems, or (3) would likely pursue source control (P2 program) and possibly a WQS variance. For the Pearl River WWTP, the WQS variance cost is part of the low estimate because it would be in lieu of effluent treatment. For others, the WQS variance cost is part of the high estimate because it would be in addition to P2 program costs where P2 alone may be insufficient for compliance for certain pollutants. The estimated range of potential costs for the seven major facilities discharging directly of Indian reservation waters are presented in Exhibit 7-1.
The remaining 19 major facilities in the sample discharge upstream from Indian reservation waters. Of these, nine are industrial facilities. EPA estimated capital and O&M costs for effluent treatment at the facilities that would potentially incur such costs, identifying a range where alternatives were appropriate to consider. EPA annualized capital costs for installing additional treatment over 20 years using a 3 and 7 percent discount rate. EPA also estimated one time and annual costs for a P2 program in addition to effluent treatment for these facilities. The estimated range of potential costs for each of the nine major industrial facilities discharging upstream (within five miles) of Indian reservation waters are presented in Exhibit 7-2 .
As discussed in Section 5, EPA also identified 41 major sewerage treatment plants located within 5 miles of Indian reservations and discharging upstream from Indian reservation waters as potentially affected by the proposed rule. EPA analyzed a sample of these 41 facilities for this economic analysis. The sample comprises 10 facilities with the most available data. The sample of 10 sewerage treatment plants was extrapolated to represent the entire group of 41 major sewerage treatment plants discharging within 5 miles upstream from Indian reservation waters. EPA estimated potential costs for the 10 major sewerage treatment plants in the sample. As with other facilities, EPA estimated capital and O&M costs for effluent treatment for the facilities that would potentially incur such costs, identifying a range where alternatives were appropriate to consider. EPA annualized capital costs for installing additional treatment over 20 years using a 3 and 7 percent discount rate. EPA estimated one time and annual costs for a P2 program in addition to or in lieu of effluent treatment for some facilities. Finally, EPA estimated one-time cost for facilities that may pursue a WQS variance for certain pollutants either in lieu of effluent treatment, or in addition to a P2 program where P2 alone may not be sufficient for compliance. In the former case, WQS variance cost appears as part of the low estimate. In the latter case, WQS variance cost appears as part of the high estimate. The estimated range of potential costs for the sample of 10 major sewerage treatment plants discharging upstream (within five miles) of Indian reservation waters are presented in Exhibit 7-3.

Exhibit 7-1 Estimated Potential Costs (2020 dollars) for Facilities Discharging to Indian Reservation Waters
NPDES ID
Facility Name
Facility Type
Design Flow (MGD)
Effluent Treatment
P2 Program
WQS Variance One-Time Cost

Capital Cost (present value)
Annual O&M Cost
Annualized Cost
(n = 20 yr;
i = 3%)
Annualized Cost
(n = 20 yr;
i = 7%)
One-Time Cost
Annual Cost

AZ0021415
Colorado River SJV (low estimate)
WWTP
                                                                            1.2
                                                                             $0
                                                                             $0
                                                                             $0
                                                                             $0
                                                                       $16,557
                                                                        $9,934
                                                                             $0
AZ0021415
Colorado River SJV (high estimate)
WWTP
                                                                            1.2
                                                                             $0
                                                                             $0
                                                                             $0
                                                                             $0
                                                                        $16,557
                                                                         $9,934
                                                                       $173,004
AZ0024627
Mesa Northwest WRP
WWTP
                                                                             18
                                                                             $0
                                                                             $0
                                                                             $0
                                                                             $0
                                                                             $0
                                                                             $0
                                                                             $0
MI0023655
Mt. Pleasant WWTP
WWTP
                                                                           4.14
                                                                             $0
                                                                             $0
                                                                             $0
                                                                             $0
                                                                             $0
                                                                             $0
                                                                             $0
MI0055808
Union Township WWTP
WWTP
                                                                            2.4
                                                                             $0
                                                                             $0
                                                                             $0
                                                                             $0
                                                                             $0
                                                                             $0
                                                                             $0
MS0053503
Pearl River WWTP (low estimate)
WWTP
                                                                           1.50
                                                                             $0