Insufficient information about program
                                       4
Arkansas, Georgia, Texas, Wyoming

No information found[2]
                                      13
Connecticut, Delaware, Florida, Hawaii, Kansas, Kentucky, Mississippi, Missouri, Nebraska, North Carolina, South Dakota, West Virginia, Wisconsin

Notes:
1 Aside from having a one-time testing program, South Carolina's program also does not qualify for a CWS waiver because the testing was limited to certain economic zones.
[2] From 2018 through 2020, EPA collected data and conducted internet searches for each state to determine the extent of state-level lead testing programs at schools and eligibility for waivers. No information was found for 13 states based on these efforts.
To identify states with programs at least as stringent as the LCRR for child cares, EPA used the following criteria:
Programs must include testing for all licensed child cares. Those that included a targeted subset were not considered to have equivalent programs and thus would not qualify for a mandatory waiver. EPA also did not consider programs that targeted child cares constructed prior to the construction date of January 1, 2014 or the date the state adopted the lead ban.
Testing must meet the minimum testing requirements of two samples per child care and testing frequency unless the state includes a more stringent requirement of remediation in response to a high lead sample. EPA also assumed that regulations and state resources that referenced the 3Ts would be consistent with those required under the final LCRR.
States that received and used a WIIN grant in the past would continue to use it in the future and CWSs would qualify for a mandatory testing waiver assuming the conditions described in the bullets above were met.
Based on these assumptions, seven states and the District of Columbia would qualify for CWS waivers from mandatory child care testing, as shown in Exhibit 4-55.
Exhibit 4-55: States Where CWSs Meet the Requirements for Mandatory Program Waivers at Child Cares
                                  Waiver Type
                               Number of States
                                    States
                                     Notes
Mandatory
(p_grandfather_mand_child)
                                       8
California, Connecticut, District of Columbia, New Hampshire, New Jersey, North Carolina, Oregon, Vermont
CWSs in these states are assumed to incur no burden for the lead in drinking water testing program at child cares

Exhibit 4-56 provides the number of states where CWSs that would qualify for an on request testing program waiver at child cares that could be issued after the first 5-year cycle of testing is completed. CWSs in an additional six states would qualify for an on request program waiver.
Exhibit 4-56: States Where CWSs Meet the Requirements for On Request Waivers at Child Cares
                                  Waiver Type
                               Number of States
                                    States
                                     Notes
On Request
(p_grandfather_opt_child)
                                      14
 California, Connecticut, District of Columbia, New Hampshire, New Jersey, North Carolina, Oregon, Vermont
 New Mexico, Oklahoma, Rhode Island, Utah, Virginia, Washington
 Also meet mandatory program requirements.

 Only meet on request requirements.*

* Note: Systems in these states are assumed to incur no burden for the lead in drinking water testing program at child cares in year 9.

Exhibit 4-57 provides the number of states that do not have CWSs that qualify for a mandatory or on request testing program waiver for child cares. A total of 3 states had some testing requirements but did not met the criteria previously discussed in this section. The remaining 34 states had insufficient or no information on which to determine if CWSs in the state would qualify for a waiver.
Exhibit 4-57: States Where CWSs Do Not Meet the Requirements for Waivers at Child Cares
                                  Waiver Type
                               Number of States
                                    States
                                     Notes
No waiver: Testing targets subset of child care
                                       2
Illinois, South Carolina
Includes states that:
 Exclude some facilities based on construction date (IL)
 Limit WIIN grant to certain economic areas (SC)
No waiver: some testing requirements but do not satisfy all LCRR requirements
                                       1
Maine
Includes states that require < 5 samples (ME)
Insufficient information about program
                                      12
Alaska, Arizona, Colorado, Georgia, Idaho, Indiana, Iowa, Massachusetts, Michigan, Montana, New York, North Dakota,
Includes states that:
 Received WIIN Grant but no additional information (AK, GA, ID, IN, IA, MT, NY, ND) or pre-existing program (CO)
 Sampling protocol is unknown or other insufficient information (AZ, MA, MI)
No information found[1]
                                      22
Alabama, Arkansas, Delaware, Florida, Hawaii, Kansas, Kentucky, Louisiana, Maryland, Minnesota, Mississippi, Missouri, Nebraska, Nevada, Ohio, Pennsylvania, South Dakota, Tennessee, Texas, West Virginia, Wisconsin, Wyoming

[1] From 2018 through 2020, EPA collected data and conducted internet searches for each state to determine the extent of state-level lead testing programs at schools and eligibility for waivers. No information was found for 13 states based on these efforts.

Discussion of Data Limitations and Uncertainty
EPA assumed that when the school type (public vs. private) was not specifically referenced in the state program that the program covered both and met the requirements of the final LCRR program. The Agency also assumed that when the number of samples was not specified but instead referenced EPA's 3Ts (USEPA, 2018) the state program met the requirements of the final LCRR. This may lead to an overestimate of the number of systems already operating under the requirements of the final rule and underestimating costs of the program.
On the other hand, there are several reasons that the estimated number of systems that already meet the final LCRR requirements for school and child care PE and testing as presented in Exhibit 4-50 and Exhibit 4-51 for schools and Exhibit 4-53 and Exhibit 4-54 for child cares may be an underestimate:
The analysis does not consider programs at the county or local level and does not recognize situations where water systems have implemented their own sampling programs in response to customer requests or to gain additional data on their system. Testing programs were only reviewed at the state level.
The eight states that target a subset of schools and two states that target a subset of child cares as identified in Exhibit 4-52 and Exhibit 4-55, respectively, were not considered to have CWSs that qualify for a mandatory or on request waiver. Similarly, the analysis did not consider states that had some testing requirements but did not satisfy all LCRR requirements that are also identified in these two exhibits. CWSs in these states are already conducting some of the activities required under the LCRR. However, due to the variation in these state programs, it would have been difficult to capture this partial compliance in the analysis. As a result, this may lead to an underestimation of CWSs that already meet the final LCRR requirements for school and child care testing.
Additional testing that is already happening at schools and child cares may reduce the incremental estimated costs and burden related to school and child care testing under the final LCRR if states waive requirements in these situations.
Labor Rates
This section is divided into three subsections:
 <IP_ADDRESS>: presents PWS labor rates,
 <IP_ADDRESS>: presents Primacy Agency labor rates, and
 <IP_ADDRESS>: provides a discussion of data limitations and uncertainty associated with the labor rates.
Public Water System Labor Rates
EPA recognizes that there may be variation in labor rates across all systems. However, for purposes of this EA, EPA used national-level estimates from Labor Costs for National Drinking Water Rules (USEPA, 2011) with a few modifications, as described below.
The 2011 document evaluated three data sources for labor rates:
 The Occupational Employment Survey (OES), a semi-annual Bureau of Labor Statistics (BLS) survey that provides hourly wage estimates by occupation and industry.
 The Water Utility Compensation Survey, an annual AWWA survey that provides hourly wage estimates for the water and wastewater industry by occupation. Data are in 2008 dollars.
 The 2006 CWSS, a periodic EPA survey that obtains employment information from a sample of CWSs.
In 2011, EPA evaluated these data sources against suitability criteria (see Exhibit 4-58) (USEPA, 2011). EPA determined that the 2006 CWSS was the most suitable source for labor rates associated with national drinking water rules particularly because: the data are specific to drinking water; the survey responses can be extrapolated to national estimates since the survey has a known sampling framework; and the data can be organized by system size, source, and ownership (USEPA, 2011).
Exhibit 4-58: Comparison of Wage Rate Surveys
Suitability Criteria
OES (BLS)
AWWA (2008)
2006 CWSS
National average wage rates
Yes
Annual updates available
No
Sample of systems serving <10,000 people may not be representative of all small systems
Annual updates available
Yes
Updates are periodic
Data quality
High
Statistically precise wage estimates
Unknown
Sampling procedures unknown; no information on statistical precision of wage estimates
Moderate
Low item response rates among small systems lead to large confidence intervals
Drinking water industry data
No[1]
Yes
Yes
Management, Technical, and Administrative occupations
Yes
No administrative occupation to match WBS needs
Administrative occupation may differ from WBS needs
System size differentiation
No
Yes
Yes
Source water differentiation
No
No
Yes
Estimates are not statistically significantly different across source waters
Ownership differentiation
No
No
Yes
Estimates are not statistically significantly different across private and public ownership
Acronyms: AWWA = American Water Works Association; CWSS = Community Water System Survey; BLS = Bureau of Labor Statistics; OES = Occupational Employment Survey; WBS = work breakdown structure.
Source: From Exhibit ES-1 (USEPA, 2011).
Notes:
1 OES data are available for two North American Industry Classification System (NAICS) categories that are likely to contain drinking water systems: 221300 (Water, Sewage, and Other Systems) for private water systems and 999300 (Local Government) for PWSs.
Exhibit 4-59 presents the labor rate estimates used in USEPA (2011) in 2007 dollars. Labor rates were calculated for four occupation categories: manager, treatment plant operator, administrative personnel, and distribution system operator. The rates include benefits. EPA considered benefit multipliers from BLS and the 2006 CWSS. Benefit multipliers from BLS ranged from 1.3 to 1.5, and benefit multipliers from the 2006 CWSS ranged from 1.2 to 1.4. The BLS estimates are more precise than the 2006 CWSS estimates, but information was not available at the industry level. The CWSS estimates are related to the drinking water industry but have large confidence intervals and low precision. As a result, EPA used a benefit multiplier of 1.4 because: ranges from both sources overlapped at 1.4; the CWSS data do not indicate consistent variations by occupation, water source, or ownership; and the large confidence intervals in the CWSS data tend to overlap between adjacent size categories, indicating that differences in the multiplier among size categories are not statistically significant (USEPA, 2011).
Exhibit 4-59: Hourly Labor Costs Including Wages Plus Benefits (2007$)
                        System Size (Population Served)
                        Hourly Labor Cost by Occupation

                                    Manager
                           Treatment plant operator
                           Administrative personnel
                         Distribution system operator
<=500
                                                                        $33.68
                                                                        $23.76
                                                                        $22.69
                                                                        $22.51
501-3,300
                                                                        $33.68
                                                                        $23.76
                                                                        $22.69
                                                                        $22.51
3,301-10,000
                                                                        $38.52
                                                                        $25.35
                                                                        $22.69
                                                                        $23.90
10,001-50,000
                                                                        $42.91
                                                                        $26.76
                                                                        $29.30
                                                                        $26.05
50,001-100,000
                                                                        $50.07
                                                                        $27.93
                                                                        $29.30
                                                                        $26.74
100,001-500,000
                                                                        $53.49
                                                                        $32.64
                                                                        $29.30
                                                                        $29.62
>500,000
                                                                        $56.71
                                                                        $33.93
                                                                        $29.30
                                                                        $32.14
Source: From Exhibit ES-3 (USEPA, 2011). Based on 2006 CWSS (USEPA, 2009).
The general employment cost index (ECI) from BLS for civilian workers in June 2007 (105.1) and 2016 (126.7) was used to adjust the rates from USEPA 2011 to 2016 dollars that yielded a multiplier of 126.7/105.1, or 1.206.
To account for the general composition of staff at systems of smaller sizes, (i.e., those serving 3,300 or fewer people), EPA used only the technical rate (i.e., treatment plant operator rate). For systems serving more than 3,300 people, EPA used proportions of 80 percent technical labor and 20 percent managerial labor (i.e., manager rate) to arrive at a labor cost, or weighted labor rate. The actual proportions between technical and managerial rates employed may vary by PWS and among the different compliance activities under the final LCRR. However, for simplicity, EPA used the 80/20 proportions as a general assumption to develop system labor costs for this EA. This approach for developing system labor rates is consistent with that used for other economic analyses, such as the Revised Total Coliform Rule (USEPA, 2012).
EPA applied the same system labor rates to both CWSs and NTNCWSs. The final labor rates used in this EA are in column D in Exhibit 4-60 below.
Exhibit 4-60: Weighted Labor Rates for CWSs and NTNCWSs (2016$)
                        System Size (Population Served)
                       Technical Labor Rate (2007$/hour)
                      Managerial Labor Rate (2007$/hour)
                      Weighted System Labor (2007$/hour)
             Weighted System Labor Adjusted to 2016$ (2016$/hour)

                                       A
                                       B
                          C = A for PWSs <= 3,300);
                  C = (0.8*A) + (0.2*B) for PWSs > 3,300
                              D = C*(126.7/105.1)
<=3,300
                                                                        $23.76
                                                                        $33.68
                                                                        $23.76
                                                                        $28.64
3,301-10,000
                                                                        $25.35
                                                                        $38.52
                                                                        $27.98
                                                                        $33.74
10,001-50,000
                                                                        $26.76
                                                                        $42.91
                                                                        $29.99
                                                                        $36.15
50,001-100,000
                                                                        $27.93
                                                                        $50.07
                                                                        $32.36
                                                                        $39.01
>100,000
                                                                        $32.64
                                                                        $53.49
                                                                        $36.81
                                                                        $44.38
Sources: A, B: Labor Costs for National Drinking Water Rules (USEPA, 2011). Hourly labor costs include wages and benefits. Technical labor wage rates are based on wage rates for treatment plant operators.
Notes:
General: Labor rates for each size category are assumed to be the same regardless of system type (CWSs or NTNCWSs). In general, information in Chapter 4 is presented by the nine size categories used in the SafeWater LCR model. In this exhibit for the final EA, EPA merged size categories with the same hourly rate.
C: EPA estimates that systems serving 3,300 people or fewer use 100 percent technical labor, whereas systems serving more than 3,300 use 80 percent technical (operator) labor and 20 percent managerial (engineer) labor.
D: The weighted system hourly rate was adjusted to 2016 dollars using the general ECI seasonally adjusted (June) for 2007 (105.1) and 2016 (126.7): http://www.bls.gov/web/eci/echistrynaics.pdf.
Primacy Agency Labor Rates
EPA used the hourly mean state employee labor rate from the BLS from the category "State Government - Environmental Scientists and Specialists, Including Health" as an approximation for the Primacy Agency labor rate. This approximation is a reasonable estimate because the majority of Primacy Agencies are states. The base hourly state labor rate is $36.23 in 2016 dollars. The labor rate is further adjusted using a 1.58 loading factor that reflect additional employee benefits from the BLS Employer Costs for Employee Compensation report, Table 3, September 2016. Percent of total compensation - Wages and Salaries - All Workers - State and Local Government Workers. See worksheet BLS Table 3 in the file, "General Cost Model Input_Final Rule.xlsx." The final "loaded" hourly rate of $57.24 is used for the Primacy Agency labor rate in the SafeWater LCR and is designated with the data variable name of rate_js. Calculations and the loaded labor rate are shown in the Exhibit 4-61.
Exhibit 4-61: Loaded Labor Rate for Primacy Agency Staff (2016$)
                            Base Hourly Labor Cost
                                Loading Factor
                       Loaded Hourly Labor Rate (2016$)

                                    rate_js
                                       A
                                       B
                                    C = A*B
                                                                        $36.23
                                                                           1.58
                                                                         $57.24
Sources:
A: State employee wage rates from National Occupational Employment and Wage Estimates, United States, BLS SOC Code 19-2041, "State Government - Environmental Scientists and Specialists, Including Health," hourly mean wage rate. May 2016 data (published in March 2017): https://stats.bls.gov/oes/2016/May/oes192041.htm. See worksheet OES in the file, "General Cost Model Input_Final Rule.xlsx."
B: Wages are loaded using a factor from the BLS Employer Costs for Employee Compensation report, Table 3, September 2016. Percent of total compensation - Wages and Salaries - All Workers - State and Local Government Workers (https://www.bls.gov/news.release/archives/ecec_12082016.pdf). See worksheet BLS Table 3 in the file, "General Cost Model Input_Final Rule.xlsx."
Discussion of Data Limitations and Uncertainty
There is uncertainty in the derivation of water system labor rates that could result in an over or underestimate of national costs of the final LCRR. The mean labor rate is based on findings of the 2006 CWSS  -  see Section 4.2.2 for discussion of the 2006 CWSS as a data source. The labor rate mix may have changed since the time of the survey. Moreover, the labor rate used is a national average and does not capture differences across regions or between urban and rural areas. EPA accounted for general changes in cost of labor by adjusting 2007 values to 2016 using the employment cost index.
There is also uncertainty in assuming a 1.4 benefits multiplier and that a labor mix of 80/20 technical/managerial staff will apply to activities conducted by CWSs and NTNCWSs serving more than 3,300 people. There may be situations where an activity is performed just by technical staff, e.g., sample analysis, or just by managerial staff. This may cause an under or overestimation of cost of the final LCRR.
Similarly, there is uncertainty in the derivation of the state labor rate that could result in an over or underestimation of national cost. The base hourly labor rate is an average rate that is based on the labor category of an environmental scientists and specialist category. Some of the activities undertaken by the Primacy Agency may include support staff, more technical staff, or management staff that have a lower or higher base rate. There is also uncertainty in assuming an average state employee hourly labor rate includes a loading factor of 1.58. This factor, provided by BLS, is an average across all state and local governments and job categories. This assumption could result in an under or overestimation of the state labor costs estimated for the LCRR.
Uncertainties in the Baseline and Compliance Characteristics of Systems
Uncertainties in the baseline and compliance characteristics of PWSs, which can apply to systems under both the previous rule and LCRR analysis, are due to the limits of available information. The largest sources of uncertainty include the following five variables: 1) the baseline number of systems with LSLs and the percent of connections in those system that are LSLs, 2) the number of PWSs that will exceed the AL and/or TL under the revised tap sampling requirements, 3) the cost of LSL replacement, 4) the cost of CCT treatment, and 5) the effectiveness of CCT in PWSs with LSLs. EPA is using low and high cost scenarios defined by the assignment of low and high values for the set of uncertain cost drivers listed above to assess the potential impact of these uncertain variables on the costs and benefits of the final LCRR. Detailed descriptions of these five uncertain variables and the derivation of their values under the low and high cost scenarios can be found in Chapter 5, Section <IP_ADDRESS>.
In addition to the uncertainty, which is represented in the cost range, EPA acknowledges that there are other uncertainties associated with the input to the cost-benefit model. EPA has described these uncertainties throughout the text in Chapter 4 and Exhibit 4-62 provides a summary of these uncertainties.
Exhibit 4-62: Summary of Uncertainties in the Baseline and Compliance Characteristics of Drinking Water Systems
Uncertainty Description
Effect on Costs
Effect on Benefits
Relevant Section(s)
System and CCT Characterization
For PWSs with unknown source type, uncertainty in assigning source type based on the ratio of systems with known primary ground water or surface water sources.
                                      +/-
                                      +/-
                                     4.3.1
Uncertainty in using 2010 census data on average persons per household to estimate number of households served by CWSs.
                                      +/-
                                      +/-
                                     4.3.2
Uncertainty in using retail population to predict average daily flow per PWS in situations where the PWS is a wholesale system that sells water to a consecutive PWS.
                                       +
                                     None
                                     4.3.2
Uncertainty in assuming that all PWSs serving 50,000 or more except "b3" systems[1] have CCT. For those serving 50,000 or fewer, uncertainty in using SDWIS/Fed treatment data to estimate percent with CCT.
                                      +/-
                                      +/-
                                     4.3.3
Uncertainty in assuming that flow is proportioned equally among all entry points in a given system.
                                      +/-
                                      +/-
                                     4.3.6
Uncertainty in using historical CWSS data as analyzed in the Geometries document (USEPA, 2000) to predict population/flow relationships given water efficiency trends over the last 20 years.
                                       +
                                     None
                                    4.2.3
                                     4.3.6
Uncertainty in estimated percent of PWSs with pH adjustment only, orthophosphate only, or both based on SDWIS/Fed historical data. Uncertainty in using SYR3 ICR dataset to estimate baseline pH and orthophosphate concentration.
                                      +/-
                                      +/-
                                     4.3.6
Lead Service Line Characterization
For CWSs, uncertainty in using survey data to estimate 1) percent with LSLs, and 2) percent of service connections that are lead within CWSs that are known to have LSLs.
                                      +/-
                                      +/-
                                     4.2.4
                                     4.2.5
                                     4.3.4
For CWSs, uncertainty in adjustments to LSL estimates from the 1991 RIA to account for LSL infrastructure replacement and system consolidation.
                                      +/-
                                      +/-
                                     4.3.4
For NTNCWS, uncertainty in using data from 2 states to estimate percent of systems with LSLs. Uncertainty in assumptions related to percent of connections that are lead within NTNCWSs that are known to have LSLs.
                                      +/-
                                      +/-
                                    <IP_ADDRESS>
For CWSs and NTNCWSs, uncertainty in using LSL survey data that did not explicitly ask systems to consider galvanized service lines that were ever downstream of LSL.
                                       -
                                       `
                                     4.3.4
Uncertainty in using LSLR milestone data and 90[th] percentile levels from SDWIS/Fed to estimate the length of time CWSs and NTNCWSs would replace LSLs under the previous rule.
                                      +/-
                                      +/-
                                    <IP_ADDRESS>
Lead and Copper Tap Sample 90[th] Percentile Levels
Uncertainty in using historical SDWIS/Fed 90[th] percentile lead data from 2007  -  2015 to predict future 90[th] percentile lead levels and percent of systems that would have no TLE, a TLE but no ALE, and an ALE under previous rule conditions.
                                      +/-
                                      +/-
                                     4.2.1
                                    <IP_ADDRESS>
Uncertainty in using historical SDWIS/Fed 90[th] percentile data from 2007  -  2015 to predict future 90[th] percentile lead levels and percent of systems with no TLE, a TLE but no ALE, and an ALE under final LCRR conditions. Includes adjustments for final LCRR requirement for LSL systems to collect all samples from locations served by an LSL (as opposed to 50 percent under the previous rule).
                                      +/-
                                      +/-
                                     4.2.1
                                    <IP_ADDRESS>
Uncertainty in using a subset of CWSs with known LSL status to predict future 90[th] percentile values.
                                      +/-
                                      +/-
                                    <IP_ADDRESS>
Uncertainty in using data from a single state (Michigan) to estimate the impact on the lead 90[th] percentile levels that will be based on fifth liter vs. first liter samples under the final LCRR for LSL systems.
                                      +/-
                                      +/-
                                     4.2.7
                                    <IP_ADDRESS>
Uncertainty in basing the likelihood of a sample exceeding 15 ug/L based on data from a single state (Michigan).
                                      +/-
                                      +/-
                                     4.2.7
                                       0
Uncertainty in basing the likelihood a system has a copper ALE based on historical Cu90 data reported for 2012  -  2015.
                                      +/-
                                      +/-
                                    <IP_ADDRESS>
Lead and WQP Monitoring Schedules
Uncertainty in using historical P90, Cu90, milestone, treatment, and violation data from SDWIS/Fed to estimate the tap sampling schedules for systems under previous rule conditions.
                                      +/-
                                      +/-
                                    <IP_ADDRESS>
Uncertainty in using schedule based on historical P90, Cu90, milestone, treatment, and violation data from SDWIS/Fed to estimate initial WQP schedules under the previous and final rule.
                                      +/-
                                      +/-
                                    <IP_ADDRESS>
Change in Source or Treatment
Uncertainty in using historical information on source water type from SDWIS/Fed to estimate the percent of systems that will change source each year. May underestimate costs by not counting when the same type of source was added and removed at a system in a given year.
                                       -
                                      +/-
                                    4.2.1
                                    <IP_ADDRESS>
Uncertainty in using historical treatment code data from SDWIS/Fed to estimate the percent of systems making a treatment change each year.
                                      +/-
                                      +/-
                                    4.2.1
                                    <IP_ADDRESS>
Schools, Child Cares, Local Health Departments, and Targeted Medical Providers
Uncertainty in number of schools based on NCES data for 2016  -  2017 (NCES, 2018a) due to population growth.
                                       -
                                     None
                                       0
                                    <IP_ADDRESS>
Uncertainty in number of child cares based on 2017 industry statistics (CED, 2019) due to potential inclusion of unlicensed at-home facilities.
                                       +
                                     None
                                       0
                                    <IP_ADDRESS>
Uncertainty in identification of local health agencies number based on 2016 statistics (NACCHO, 2017).
No effect on incremental costs. Requirement to deliver to this group is the same under the previous and final rules.
                                     None
                                       0
                                    <IP_ADDRESS>
Possible underestimation of states that may grant waivers to CWSs for sampling in schools and child cares because it does not consider states that target a subset of these facilities or require one round of testing.
                                       +
                                     None
                                    <IP_ADDRESS>
Labor Rates
Uncertainty in using 2006 CWSS data for PWS labor rates, 1.4 benefits multiplier, and 80/20 technical/managerial staffing mix for PWSs serving more than 3,300 people.
                                      +/-
                                     None
                                   <IP_ADDRESS>
Uncertainty in basing the State labor rate on the wage rate category for Environmental Scientists and Specialists (activities may be done by staff with higher or lower rates) and uncertainty in using a single benefits loading factor of 1.58 for employee compensation.
                                      +/-
                                     None
                                   <IP_ADDRESS>
Acronyms: ALE = action level exceedance; CED = Committee for Economic Development; Cu90 = copper 90[th] percentile value; CCT = corrosion control treatment; CWS = community water system; CWSS = Community Water System Survey; LCRR = Lead and Copper Rule revisions; LSL = lead service line; LSLR = lead service line replacement; NACCHO = National Association of County and City Health Officials; NCES = National Center for Education Statistics; NTNCWS = non-transient non-community water system; P90 = lead 90[th] percentile value; PWS = public water system; RIA = regulatory impact assessment; SDWIS/Fed = Safe Drinking Water Information System  -  Federal version; SYR3 ICR = Six-Year Review 3 Information Collection Request; TLE = trigger level exceedance.
Notes:
General: This exhibit indicates whether each uncertainty factor contributes to understating (-), overstating (+), or either understating or overstating (+/-) the overall economic impact results.
[1] Excluded 11 CWSs serving 50,000 that were assumed to meet the b3 criteria, i.e., have naturally non-corrosive water, and under the previous rule are not required to install CCT. See Section 4.3.3 for additional information.
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National Child Care Information and Technical Assistance Center (NCCIC) and the National Association for Regulatory Administration (NARA). 2010. The 2008 Child Care Licensing Study. https://www.naralicensing.org/2008-child-care-licensing-study.
Rayburn, W.F., J.C. Klagholz, C. Murray-Krezan, L.E. Dowell, and A.L. Strunk. 2012. Distribution of American Congress of Obstetricians and Gynecologists Fellows and Junior Fellows in Practice in the United States. Obstetrics and Gynecology 119(5):1017-22. https://www.ncbi.nlm.nih.gov/pubmed/22525913.
Rockaway, T.D., P.A. Coomes, J. Rivard, and B. Kornstein. 2011. Residential water use trends in North America. JAWWA 103(2):76-89.
Sandvig, A., P. Kwan, P.E., G. Kirmeyer, P.E., Dr. B. Maynard, Dr. D. Mast, Dr. R. R. Trussell, P.E., Dr. S. Trussell, P.E., A. Cantor, P.E., MCSD, and A. Prescott. 2008. Contribution of Service Line and Plumbing Fixtures to Lead and Copper Rule Compliance Issues. Denver, CO: AWWA Research Foundation.
Slabaugh, R.M., R.B. Arnold, S. Chaparro, and C.P. Hill. 2015. National cost implications of potential long‐term LCR requirements. Journal AWWA. 107(8):E389-E400.
United States Census Bureau. 2010. Table AVG1. Average Number of People Per Household, By Race And Hispanic Origin, Marital Status, Age, And Education Of Householder: 2010. http://www.census.gov/hhes/families/data/cps2010.html.
United States Environmental Protection Agency (USEPA). 1987. Amendments to the Safe Drinking Water Act. Federal Register 52(105):20674. June 2, 1987. Washington, D.C.: Government Printing Office. https://www.govinfo.gov/content/pkg/FR-1987-06-02/pdf/FR-1987-06-02.pdf.
USEPA. 1991. Final Regulatory Impact Analysis of National Primary Drinking Water Regulations for Lead and Copper. April 1991. Office of Water.
USEPA. 2000. Geometries and Characteristics of Public Water Systems. December 2000. EPA 815-R-00-24.
USEPA. 2003. Drinking Water Baseline Handbook, Fourth Edition.
USEPA. 2007. Office Ground Water and Drinking Water's Error Code Tracking Tool [for SDWIS/Fed]. Developed 2007.
USEPA. 2009. Community Water System Survey Volume II: Detailed Tables and Survey Methodology. May 2009. Office of Water. EPA 815-R-09-002.
USEPA. 2011. Labor Costs for National Drinking Water Rules. Submitted to Rajiv Khera, Office of Ground Water and Drinking Water, USEPA. June 2011. EPA Contract No. GSA GS-10F-0076J.
USEPA. 2012. Economic Analysis for the Final Revised Total Coliform Rule. September 2012. Office of Water. EPA 815-R-12-004. https://nepis.epa.gov/Exe/ZyPDF.cgi/P100PIVO.PDF?Dockey=P100PIVO.PDF.
USEPA. 2014. Guidelines for Preparing and Economic Analyses. Office of Policy. December 17, 2010 (updated May 2014).
USEPA. 2016a. Safe Drinking Water Information System Federal Version (SDWIS/Fed) Data Reporting Requirements, v1.2. March 2016. Office of Ground Water and Drinking Water.
USEPA. 2016b. The Analysis of Regulated Contaminant Occurrence Data from Public Water Systems in Support of the Third Six-Year Review of National Primary Drinking Water Regulations: Chemical Phase Rules and Radionuclides Rules. December 2016. Office of Water. EPA 810-R-16-014.
USEPA. 2016c. The Data Management and Quality Assurance/Quality Control Process for the Third Six-Year Review Information Collection Rule Dataset. December 2016. Office of Water. EPA 810-R-16-015.
USEPA. 2018. 3Ts for Reducing Lead in Drinking Water in Schools and Child Care Facilities: A Training, Testing, and Taking Action Approach (Revised Manual). October 2018. Office of Water. EPA 815-B-18-007. https://www.epa.gov/ground-water-and-drinking-water/3ts-reducing-lead-drinking-water-toolkit.
Water Research Foundation (WaterRF). 2016. Residential End Uses of Water, Volume II. Available online at https://www.circleofblue.org/wp-content/uploads/2016/04/WRF_REU2016.pdf.
Weston, R.F. and Economic and Engineering Services, Inc (EES). 1990. Final Report: Lead Service Line Replacement A Benefit-to-Cost Analysis. Denver, CO: American Water Works Association.
Economic Impact and Cost Analysis of the Final Lead and Copper Rule Revisions
Introduction
In this chapter the United States Environmental Protection Agency (EPA) presents its estimates of, and approach to estimate, the national cost of the final Lead and Copper Rule revisions (LCRR). To determine the national cost of the final LCRR, EPA estimated the additional costs public water systems (PWSs), households, and Primacy Agencies will incur in response to the final LCRR, above the cost they would face under the previous Lead and Copper Rule (LCR) if no revisions were enacted. To determine the incremental cost of the final LCRR, the Agency first calculated the costs that would be incurred in continuing to comply with the previous LCR. Next, the Agency estimated the cost PWSs, households, and Primacy Agencies would incur in response to the final LCRR if no rule were currently in place. The national cost of the final LCRR, or incremental cost, is the difference between the cost of compliance with the final LCRR and the cost of compliance with the previous LCR.
Summary of Rule Costs
The annualized costs, discounted at 3 percent and 7 percent, that PWSs, households, and Primacy Agencies will incur in complying with the previous LCR and the final LCRR are summarized Exhibit 5-1 and Exhibit 5-2, respectively.  EPA used these discount rates as prescribed by the Office of Management and Budget (OMB Circular A-4, 2003). See Section <IP_ADDRESS> below for additional information on discounting. EPA estimated costs of the final LCRR under both low cost and high cost scenarios to reflect uncertainty in the cost estimates. The low cost scenario and high cost scenario differ in their assumptions made about: 1) the existing number of lead service lines (LSLs) in PWSs; 2) the number of PWSs above the action level (AL) or trigger level (TL) under the previous and final monitoring requirements; 3) the cost of installing and optimizing corrosion control treatment (CCT); 4) the effectiveness of CCT in mitigating lead concentrations; and 5) the cost of lead service line replacement (LSLR). EPA discusses these assumptions in more detail below and in Section <IP_ADDRESS>.
The incremental annualized cost of the final LCRR ranges from $161 to $335 million at a 3 percent discount rate, and from $167 to $372 million at a 7 percent discount rate in 2016 dollars. The exhibits also detail the proportion of the annualized costs attributable to each rule component.
Exhibit 5-1: National Annualized Rule Costs - All PWSs at 3 Percent Discount Rate (2016$)

                               Low Cost Estimate
                               High Cost Estimate

                                Previous LCR[1]
                                   Final LCRR
                                  Incremental
                                Previous LCR[1]
                                   Final LCRR
                                  Incremental
 PWS Annual Costs

 Sampling
                                                                    $41,962,000
                                                                    $67,744,000
                                                                    $25,782,000
                                                                    $45,099,000
                                                                    $78,739,000
                                                                    $33,641,000
 PWS LSLR
                                                                       $628,000
                                                                    $44,372,000
                                                                    $43,744,000
                                                                    $27,277,000
                                                                   $140,242,000
                                                                   $112,965,000
 Corrosion Control Technology
                                                                   $344,483,000
                                                                   $363,894,000
                                                                    $19,412,000
                                                                   $385,681,000
                                                                   $471,087,000
                                                                    $85,407,000
 Point-of Use Installation and Maintenance
                                                                             $0
                                                                     $3,418,000
                                                                     $3,418,000
                                                                             $0
                                                                    $20,238,000
                                                                    $20,238,000
 Public Education and Outreach
                                                                       $345,000
                                                                    $37,207,000
                                                                    $36,861,000
                                                                     $1,467,000
                                                                    $45,461,000
                                                                    $43,994,000
 Rule Implementation and Administration
                                                                             $0
                                                                     $2,576,000
                                                                     $2,576,000
                                                                             $0
                                                                     $2,576,000
                                                                     $2,576,000
 Total Annual PWS Costs
                                                                   $387,417,000
                                                                   $519,210,000
                                                                   $131,792,000
                                                                   $459,523,000
                                                                   $758,343,000
                                                                   $298,820,000
 State Rule Implementation and Administration
                                                                     $6,145,000
                                                                    $25,852,000
                                                                    $19,707,000
                                                                     $7,137,000
                                                                    $27,893,000
                                                                    $20,756,000
 Household LSLR
                                                                       $182,000
                                                                     $8,100,000
                                                                     $7,918,000
                                                                     $5,466,000
                                                                    $19,542,000
                                                                    $14,076,000
 Wastewater Treatment Plant Costs
                                                                       $161,000
                                                                     $1,313,000
                                                                     $1,152,000
                                                                       $695,000
                                                                     $2,523,000
                                                                     $1,828,000
 Total Annual Rule Costs
                                                                   $393,904,000
                                                                   $554,475,000
                                                                   $160,571,000
                                                                   $472,821,000
                                                                   $808,301,000
                                                                   $335,481,000
  Previous LCR costs are projected over the 35-year period of analysis and are affected by EPA's assumptions on five uncertain variables which vary between the low and high cost scenarios. The low/high variable assignments for the number of LSLs, CCT cost and effectiveness, LSLR costs, and the 90[th] percentile tap sample assignments for non-LSL systems are consistent across the previous rule and final LCRR projections. The 90[th] percentile tap sample assignments for LSL systems varies between the previous rule and final LCRR. Details may not add exactly to total due to independent rounding.

Exhibit 5-2: National Annualized Rule Costs - All PWSs at 7 Percent Discount Rate (2016$)

                               Low Cost Estimate
                               High Cost Estimate

                                Previous LCR[1]
                                   Final LCRR
                                  Incremental
                                Previous LCR[1]
                                   Final LCRR
                                  Incremental
 PWS Annual Costs

 Sampling
                                                                    $40,890,000
                                                                    $70,197,000
                                                                    $29,307,000
                                                                    $45,164,000
                                                                    $84,407,000
                                                                    $39,243,000
 PWS LSLR
                                                                       $667,000
                                                                    $46,803,000
                                                                    $46,136,000
                                                                    $38,327,000
                                                                   $169,562,000
                                                                   $131,235,000
 Corrosion Control Technology
                                                                   $322,684,000
                                                                   $340,307,000
                                                                    $17,623,000
                                                                   $364,809,000
                                                                   $457,554,000
                                                                    $92,745,000
 Point-of Use Installation and Maintenance
                                                                             $0
                                                                     $3,308,000
                                                                     $3,308,000
                                                                             $0
                                                                    $19,928,000
                                                                    $19,928,000
 Public Education and Outreach
                                                                       $471,000
                                                                    $36,555,000
                                                                    $36,084,000
                                                                     $2,016,000
                                                                    $45,628,000
                                                                    $43,612,000
 Rule Implementation and Administration
                                                                             $0
                                                                     $4,147,000
                                                                     $4,147,000
                                                                             $0
                                                                     $4,147,000
                                                                     $4,147,000
 Total Annual PWS Costs
                                                                   $364,711,000
                                                                   $501,316,000
                                                                   $136,605,000
                                                                   $450,316,000
                                                                   $781,224,000
                                                                   $330,908,000
 State Rule Implementation and Administration
                                                                     $6,073,000
                                                                    $26,949,000
                                                                    $20,876,000
                                                                     $7,429,000
                                                                    $29,645,000
                                                                    $22,216,000
 Household LSLR
                                                                       $193,000
                                                                     $8,587,000
                                                                     $8,393,000
                                                                     $7,681,000
                                                                    $24,409,000
                                                                    $16,728,000
 Wastewater Treatment Plant Costs
                                                                       $211,000
                                                                     $1,669,000
                                                                     $1,458,000
                                                                     $1,097,000
                                                                     $3,705,000
                                                                     $2,607,000
 Total Annual Rule Costs
                                                                   $371,188,000
                                                                   $538,521,000
                                                                   $167,333,000
                                                                   $466,523,000
                                                                   $838,983,000
                                                                   $372,460,000
  Previous LCR costs are projected over the 35-year period of analysis and are affected by EPA's assumptions on five uncertain variables which vary between the low and high cost scenarios. The low/high variable assignments for the number of LSLs, CCT cost and effectiveness, LSLR costs, and the 90[th] percentile tap sample assignments for non-LSL systems are consistent across the previous rule and final LCRR projections. The 90[th] percentile tap sample assignments for LSL systems varies between the previous rule and final LCRR. Details may not add exactly to total due to independent rounding.

Overview of the Chapter
In Section 0, EPA provides an overview of its approach to estimate the cost of the final LCRR. In Section 5, EPA provides the data and algorithms used to calculate the cost of each activity PWSs will undertake to comply with the final rule. In addition, Section 5 provides EPA's estimates of these costs. In Section 5.4, EPA provides the data and algorithms used to calculate the cost of each activity Primacy Agencies will undertake to implement and administer the final rule, as well as EPA's estimates of these costs. While this chapter includes EPA's national cost estimates for both the previous LCR and final LCRR, only details on the approach, data, and algorithms used to calculate the costs of the final LCRR are provided in this chapter. The details on the approach, data, and algorithms used to calculate the costs of the previous LCR are provided in Appendix B.
An important compliance option for PWSs is to add additional phosphate for corrosion control. Some of this phosphate may eventually enter wastewater treatment plants (WWTPs). In Section 5.5, EPA estimates the costs and impacts associated with increased phosphorous loadings.
Cost Modeling Method
Section 0 begins with an overview of the SafeWater Lead and Copper Rule (LCR) model that EPA used to estimate the costs, as well as the benefits, of the final LCRR (Section 5.2.1). EPA next describes the development of the SafeWater CBX model (Section 5.2.2 and Section 5.2.3). In Section 5.2.4, a number of topics are discussed in subsections: the modification of the SafeWater CBX model for use with the treatment technique LCR; the development of the low and high cost scenarios that characterize uncertainty for the regulatory cost estimates; the assignment of low and high variable values for the scenarios; the use of model PWSs; how data was developed for very large systems; the period of analysis; annualization discount rates; the compliance schedule for the final rule; and simulating compliance activities in the SafeWater LCR model.
Overview of the SafeWater LCR Model
In order to estimate the compliance costs (and benefits) of the final LCRR, EPA developed a new variant of its existing SafeWater CBX model, which is designed to estimate the impacts of a maximum contaminant level (MCL) based rulemaking. This new model, called the SafeWater LCR model, is designed to estimate the costs and benefits of a treatment technique rule, and focuses on water contamination in the distribution system.
Like previous versions of the model, this new model improves the accuracy of estimated cost values by incorporating the large degree of variability across water system baseline characteristics that influence compliance and costs. For example, under the final LCRR, PWSs will face different compliance scenarios and costs depending on their size, primary source water type, number of entry points to the distribution system, number of LSLs in their distribution system, and existing corrosion controls in place. The SafeWater LCR model also includes variability in compliance characteristics like different labor rates and number of tap and water quality parameter (WQP) samples required by system size.
Compared to the SafeWater CBX MCL model, this new treatment technique model is more complex incorporating multiple compliance triggers (e.g., AL exceedance, TL exceedance, single sample exceedance/find-and-fix) that require multiple and varying compliance actions (LSLR, CCT installation or re-optimization, find-and-fix, public education). The complexity of the final LCRR treatment technique means there are significantly more required inputs for the estimation of total compliance costs. Many of these inputs, which are specific to the assessment of the cost impacts of the final LCRR, are uncertain. EPA only has limited data, including midpoint and/or high and low estimates available and does not have robust information on the relative likelihood of the available estimates for these inputs. The inability to fully assess the level or distribution of model variables affects the following major final LCRR compliance cost drivers: the number of PWSs that will exceed the AL and TL under the final tap sampling requirements; the baseline number and geographic distribution of LSLs; the cost of LSL replacement; the cost of CCT treatment; and the effectiveness of CCT in PWSs with LSLs. EPA determined it does not have enough information to perform a Monte-Carlo based uncertainty analysis as part of the SafeWater LCR model. Instead, in order to capture uncertainty, EPA estimated compliance costs (and benefits) using the SafeWater LCR model under high and low bracketing scenarios.
In Section 5.2.2, the development history of the SafeWater modeling platform is discussed, including the first version of the model used in the estimation of cost for the 2001 final Arsenic Rule, the inclusion of uncertainty assessment and benefits valuation in the SafeWater CBX model, and the external peer review of the model and relevant changes as a result of the peer review. Section 5.2.4 details the development of the SafeWater LCR model, the lack of information to describe the uncertainty in major LCR cost drivers, and the high and low cost bracketing scenarios ultimately used to capture a broad understanding of uncertainty in the costs of the final LCRR.
History of SafeWater Model Development
The first version of the SafeWater model platform, known as SafeWater XL, was developed to estimate costs for the 1997 proposal for the Arsenic Rule. The model platform has been under continual development to improve its function since that time. Prior to 1997, EPA used mean unit cost inputs when calculating the national costs of drinking water regulations. Mean values were typically assigned to all PWSs within a category. Each category was defined by system attributes, including population served, source water type, and ownership type (e.g., publicly owned ground water systems serving 100-500 people). In other words, all PWSs in a given category were assumed to be identical and face identical compliance costs.
The SafeWater model was developed in response to the recognition that PWSs have a great deal of inherent variability even within each category and that ignoring this variability can result in inaccurate compliance cost estimates. These inaccuracies often result from cost functions being non-linear in their inputs.
The model allows input values to vary across and within PWS types, which makes it possible to output not only the mean estimate of costs, but also distributions that show how costs vary across PWSs.
Based on a better understanding of the level of variability among PWSs, and the importance of modeling variability among PWSs, EPA changed its cost modeling approach during the development of the National Primary Drinking Water Regulations (NPDWR) for Arsenic. To estimate the national costs of the Arsenic Rule, EPA developed an Excel based model that incorporated the large variability among systems within each system size and source water category. This avoided the prior problem of treating all PWSs in a category as if they are identical and equal to the "average" system.
This model was subjected to extensive review by the National Drinking Water Advisory Council (NDWAC). Concurrent with the NDWAC's review of the Arsenic Rule cost analysis, EPA's Science Advisory Board (SAB) made a series of recommendations to improve the estimation of the health benefits of the Arsenic Rule.
Development of SafeWater CBX
The second phase of the development of the SafeWater platform began in 2002. The goal being to have a single, customizable model that with the appropriate user inputs and data, could estimate both the costs and benefits of any new or revised MCL based drinking water standard while employing a consistent and standard modeling approach across rules. This next generation of the model was called SafeWater CBX. The model was designed to incorporate not only the PWS variability and compliance data on costs but also variability on the exposure and risk impacts when computing benefits estimates at the same time. As suggested by the NDWAC Arsenic Rule peer reviewers, the model also incorporated the uncertainty in input values in order to estimate the confidence in the cost and benefit estimates.
Modeling PWS Variability in SafeWater CBX
As discussed above, the costs incurred by a PWS depend on particular water system characteristics. The values for some of these characteristics for the PWS are reported in the federal version of the Safe Drinking Water Information System (SDWIS/Fed). The SDWIS/Fed data provide information on the PWS characteristics that typically define PWS categories, or strata, for which EPA develops costs in rulemakings:
 System type (community water system (CWS), non-transient non-community water system (NTNCWS))
 Number of people served by the PWS
 PWS's primary raw water source (ground water or surface water)
 PWS's ownership type (public or private)
 Location
 Number of service connections
Since EPA does not have complete PWS specific data across the 50,067 CWSs and 17,589 NTNCWS in SDWIS/Fed for many of the baseline and compliance characteristics necessary to estimate costs and benefits, such as average and daily flow rates, water quality characteristics, treatment in-place, and labor rates, EPA adopted a "model PWS" approach. SafeWater CBX creates model PWSs by combining the PWS-specific data available in SDWIS/Fed with data on baseline and compliance characteristics available at the PWS category level. In some cases, the categorical data are simple point estimates. In this case, every model PWS in a category is assigned the same value. In other cases, where more robust data representing system variability are available the category-level data includes a distribution of potential values. In the case of distributional information, SafeWater CBX assigns each model PWS a value sampled from the distribution.
Because of this model PWS approach, SafeWater CBX does not output any results at the PWS level, but rather, outputs cost and benefit estimates for 36 PWS categories, or strata. Each PWS category is defined by the system type (CWS and NTNCWS), primary water source (ground or surface), and size category (there are nine). In order to ensure stability in results, each PWS category must have a large enough number of the model PWSs to capture the full range of potential variability in the data.
Exhibit 5-3: Model PWS Approach Utilized by SafeWater CBX to Model PWS Variability

As illustrated in Exhibit 5-3, once all the model PWSs are created and assigned baseline and compliance characteristics, SafeWater CBX estimates the cost and benefits of compliance for each model PWS under the final rule. For each PWS category, the model then calculates summary statistics that describe the costs and benefits associated with final LCRR compliance. These summary statistics include total costs and benefits, total costs per final regulatory requirement, total benefits per final regulatory requirement, the variability in PWS-level costs (i.e., 10[th], 25[th], 75[th], and 90[th] percentile system costs), and the variability in household-level costs.
Modeling Uncertainty in SafeWater CBX
Many of the input values used to calculate the costs of drinking water regulations are not known with certainty. For example, technology unit costs, population served to drinking water treatment plant flow relationships, and contaminant occurrence are all uncertain. Prior to the development of SafeWater CBX, past modeling approaches have used "best estimates" or mean values for these inputs when calculating the benefits and costs of drinking water regulations. SafeWater CBX instead allows input parameters to be treated as uncertain when data are available to characterize the underlying distribution of these parameters.
Incorporating input uncertainty into the calculation of costs and benefits is important for the same reasons it is important to incorporate input variability. First, calculating costs and benefits at the mean values will lead to inaccurate estimates if costs and/or benefits are not linear in these input parameters. Second, by incorporating input uncertainty it is possible to output not only estimates of costs, but also distributions that show how confident EPA is in these estimates, when the underlying data are sufficiently robust to characterize input uncertainty.
SafeWater CBX allows analysts to use a standard Monte-Carlo approach for modeling uncertainty when sufficient data are available to characterize the full distribution. When using the Monte-Carlo approach, for each iteration of the model, SafeWater CBX randomly pulls a value for each uncertain input. Using these input values, SafeWater CBX calculates the costs for all model PWSs and calculates the costs at each PWS category. It then randomly pulls new values for each uncertain input and repeats the process. This process is repeated many times until the results become stable (i.e., additional iterations do not significantly change the output).
External Peer Review of SafeWater CBX
SafeWater CBX's Beta version was completed in 2010. In that same year, EPA conducted an external letter peer review of the model by three economists (IntelliTech Systems, Inc., 2010). As a result of some of the comments, EPA added a number of additional pre-programmed outputs to the model code including: scalable contaminant occurrence graphs, the calculation of net benefits, and graphical representations of marginal costs and benefits. Two computational improvements were also made. SafeWater CBX was modified to allow for regional differences in contaminant occurrence and a water loss percentage was included to account for the treatment costs of water associated with firefighting and leakages.
Overview of SafeWater LCR
SafeWater CBX was designed to calculate the costs and benefits associated with setting a new or revised MCL. Since the final LCRR is a treatment technique rule, and focuses on water contamination in the distribution system, significant changes needed to be made to the existing model framework. This next version of the model is the SafeWater LCR model. The changes in the new model were driven by the need to model multiple compliance triggers (e.g., AL exceedance, TL exceedance, individual tap sample AL exceedance/find-and-fix) that require multiple compliance actions (LSLR, CCT installation or re-optimization, find-and-fix, public education). The complexity of this treatment technique also means there are many more required inputs for the estimation of total compliance costs than is the case for an MCL based rulemaking.
Modeling PWS Variability in the SafeWater LCR Model
To reflect variability across PWS categories in modeling the final LCRR, the SafeWater LCR model applies the same "model PWS" approach developed in SafeWater CBX. From a set of system baseline characteristic data including system type, system size, and primary water source, EPA defined PWS categories in the SafeWater LCR model. The SafeWater LCR model creates model PWSs representing systems in each category by combining the PWS-specific data available in SDWIS/Fed with data on baseline and compliance characteristics available at the PWS category level. When categorical data are point estimates, every model PWS in a category is assigned the same value. When EPA has robust data representing system variability, the category-level data includes the categorical data as a distribution of potential values. In the case of distributional information, the SafeWater LCR model assigns each model PWS a value sampled from the distribution. Examples of the distributional data inputs that characterize variability in the SafeWater LCR model include the number of distribution system entry points, and the burden for PWS and Primacy Agency staff to conduct tasks like sampling and compliance documentation and review. For additional detail on the development of model-PWSs in the SafeWater LCR model, see Appendix B, Section B.2.1.
Modeling Uncertainty in the SafeWater LCR Model
The available LCR data limit EPA's ability to quantify uncertainty in the SafeWater LCR model. During the development of the SafeWater LCR model, it became clear that not only were many of the inputs uncertain, but for many LCR specific inputs, EPA only has limited midpoint, high, and low estimates available and does not have information on the relative likelihood of the available estimates. This included major drivers of the cost of compliance, including:
 Baseline number of LSLs
Likelihood a model PWS will exceed the AL and/or TL under the previous rule and the final LCRR
The effectiveness of CCT installation or re-optimization
LSLR unit costs
CCT unit Costs
Therefore, EPA determined it does not have enough information about the level or distribution of uncertainty to conduct a Monte-Carlo based uncertainty analysis as part of the SafeWater LCR model. Instead, EPA estimated final LCRR compliance costs under two scenarios, one for low cost and one for high cost, defined by these five uncertain cost drivers. Descriptions of these uncertain variables and the derivation of their values under the low and high cost scenarios follows.
Baseline Number of Lead Service Lines
The number of LSLs in the United States is a key input to calculating costs of the LCRR. Systems with LSLs have unique requirements and different burden and costs compared to non-LSL systems under the previous rule and LCRR. EPA recognizes that the characterization of the national LSL inventory is uncertain and has a significant impact on estimated costs and benefits of the LCRR. In order to capture the uncertainty associated with this variable, EPA developed low and high model inputs that correspond to two key parameters related to the LSL inventory: 1) the percent of systems with LSLs, and 2) the percent of service connections that are lead within systems that are known to have LSLs. The derivation of these input variables for the low cost scenario, which assumed 6,286,963 LSLs distributed nationwide, is described in detail in Chapter 4, Section <IP_ADDRESS> based on data from Cornwell et al. (2016). EPA used data the 1991 Regulatory Impact Assessment (RIA) (USEPA, 1991) to generate the high cost scenario estimate of these LSL inventory parameters. The RIA assumed that 10,274,845 LSLs existed nationwide in 1988. Based on this initial number, EPA adjusted the value to 9,239,141 for the year 2024. This adjustment is also described in Chapter 4, Section <IP_ADDRESS>. Exhibit 5-4 summarizes the LSL inventory information used in the estimation of the LCRR. EPA assumed that a significant majority of systems serving 50,000 persons or fewer that have installed CCT under the previous LCR have done so because the presence of LSLs in their system has caused the system to exceed the lead AL.
Exhibit 5-4: Percent of CWSs with CCT that have LSLs, Percent of CWSs without CCT that Have LSLs, and Percent of Connections that Are Lead in CWSs with LSLs under Low and High Cost Scenarios [1]
                               CWS Size Category
                              High Cost Scenario
                               Low Cost Scenario

               Percent CWSs with LSLs by CCT Status (p_lsl)[3]
       Percent of Connections that are Lead in CWSs with LSLs (perc_lsl)
                Percent CWSs with LSLs by CCT Status (p_lsl)[3]
       Percent of Connections that are Lead in CWSs with LSLs (perc_lsl)

                                   Have CCT
                                    No CCT

                                   Have CCT
                                    No CCT

<=100
                                                                           100%
                                                                           3.6%
                                                                          86.9%
                                                                           100%
                                                                           9.9%
                                                                          14.5%
101-500
                                                                           100%
                                                                           1.6%
                                                                          89.2%
                                                                           100%
                                                                           2.2%
                                                                          16.6%
501-1,000
                                                                           100%
                                                                          13.0%
                                                                          88.8%
                                                                            75%
                                                                           0.0%
                                                                          17.7%
1,001-3,300
                                                                           100%
                                                                           0.6%
                                                                          29.4%
                                                                            56%
                                                                           0.0%
                                                                          17.1%
3,301-10,000
                                                                            84%
                                                                           0.0%
                                                                          21.0%
                                                                            42%
                                                                           0.0%
                                                                          17.6%
10,001-50,000
                                                                            69%
                                                                           0.0%
                                                                          14.2%
                                                                            60%
                                                                           0.0%
                                                                          27.1%
50,001-100,000
                                                                            45%
                                                                           0.0%
                                                                          10.0%
                                                                            53%
                                                                           0.0%
                                                                          11.0%
100,001-1,000,000
                                                                            63%
                                                                           0.0%
                                                                          12.5%
                                                                            49%
                                                                           0.0%
                                                                           9.2%
> 1,000,000[2]
                                                                            65%
                                                                           0.0%
                                                                          24.2%
                                                                            57%
                                                                           0.0%
                                                                           9.4%
 [1] Low cost scenario data are replicated from Exhibit 4-13 and Exhibit 4-14. High cost scenario data are replicated from Exhibit 4-10 and Exhibit 4-11.
 [2] Values presented for systems serving > 1 million people are only used when EPA does not have specific data collected from individual systems.
 [3] The percentages of systems with LSLs are within each category of CCT status and do not need to sum to 100 percent. They represent the percent of systems with LSLs of the systems within the given "Have CCT" or "No CCT" category of systems.

Percent of Model PWSs that are Expected to Exceed the AL and/or TL under the Previous Rule and the Final LCRR
As described in Chapter 4, Section <IP_ADDRESS>, the likelihood a model PWS would have an initial lead 90[th] percentile value (P90) not greater than the TL, greater than the TL but not greater than the AL, or greater than the AL is based on SDWIS/Fed historical 90[th] percentile lead data from 2007 to 2015. EPA recognizes that there are uncertainties in predicting the future percent of systems having 90[th] percentile values that fall within the set of three ranges (not greater than the TL, greater than the TL but not greater than the AL, or greater than the AL) from historical SDWIS data. Also, the Agency recognizes that these uncertainties could have a significant impact on estimated costs and benefits of the final LCRR. Therefore, EPA developed two sets of expected percentages for placement of model PWSs into one of the three possible 90[th] percentile -ranges. Because the implementation of a number of final rule requirements are driven by TL and AL exceedances, the greater the estimated percent of systems above those levels the greater the total final rule costs. Therefore, the low cost scenario uses data derived from the lowest 90[th] percentile value each PWS reported in SDWIS/Fed between 2007 to 2015. The data used in the high cost scenario is derived by using the highest 90[th] percentile value each PWS reported in SDWIS/Fed between 2007 to 2015. Exhibit 5-5 provides the likelihood a model PWS, with or without LSLs, would be assigned a 90[th] percentile in each of the 90[th] percentile-ranges by the SafeWater LCR model under the previous rule in the low and high cost scenarios.
Exhibit 5-5: Likelihood of Initial Model PWS 90[th] Percentile Placement under Previous LCR
                                  Category
                                   No LSLs
                                  Has LSLs
                                Low Estimate
 No TLE/ALE (P90 <=10 ug/L)
                                                                          97%
                                                                          99%
 TLE (10 ug/L < P90 <=15 ug/L)
                                                                           0%
                                                                           1%
 ALE (P90 > 15 ug/L)
                                                                           2%
                                                                           0%
                               High Estimate
  No TLE/ALE (P90 <=10 ug/L)
                                                                          87%
                                                                          79%
 TLE (10 ug/L < P90 <=15 ug/L)
                                                                           7%
                                                                          12%
 ALE (P90 > 15 ug/L)
                                                                           6%
                                                                           9%
    Acronyms: ALE = action level exceedance; PWS = Public water system; LSL = lead service line; P90 = lead 90[th] percentile level; TLE = trigger level exceedance.
    Note: Data in this exhibit replicates data provided in Chapter 4, Exhibit 4-19.

As discussed in Chapter 4, Section <IP_ADDRESS>, under the final LCRR, EPA estimated the percent of CWSs with no TLE or ALE, a TLE, or an ALE using historical SDWIS/Fed 90[th] percentile tap sample data (as done for the previous rule) with two important adjustments:

 An adjustment to reflect the new requirement for LSL systems to collect all samples from LSL sites where possible, as opposed to the previous rule minimum of 50 percent of samples being collected from LSL sites.
 An adjustment to reflect new requirements for LSL systems to collect fifth liter samples from LSL sites instead of first liter samples (as required under the previous rule).

Exhibit 5-6 provides the likelihood a model PWS, with or without LSLs, would be assigned a 90[th] percentile in each of the 90[th] percentile -ranges by the SafeWater LCR model under the final rule in the low and high cost scenarios.
Exhibit 5-6: Likelihood of Initial Model PWS 90[th] Percentile Placement under Final LCRR
                                  Category
                                   No LSLs
                                  Has LSLs
                                Low Estimate
 No TLE/ALE (P90 <=10 ug/L)
                                                                          97%
                                                                          89%
 TLE (10 ug/L < P90 <=15 ug/L)
                                                                           0%
                                                                           5%
 ALE (P90 > 15 ug/L)
                                                                           2%
                                                                           6%
                               High Estimate
 No TLE/ALE (P90 <=10 ug/L)
                                                                          87%
                                                                          58%
 TLE (10 ug/L < P90 <=15 ug/L)
                                                                           7%
                                                                          12%
 ALE (P90 > 15 ug/L)
                                                                           6%
                                                                          30%
      Acronyms: ALE = action level exceedance; PWS = public water system; LCRR = Lead and Copper Rule revisions; LSL = lead service line; P90 = lead 90[th] percentile level; TLE = trigger level exceedance
      Note: Data in this exhibit replicates data provided in Chapter 4, Exhibit 4-20.
Effectiveness of CCT Installation or Re-optimization
The effectiveness of CCT installation or re-optimization is uncertain, given variability in system specific water quality, the flow rate of water through the distribution system, and the possibility that other competing treatment requirements may exist for individual systems because of other NPDWRs that may limit the full effectiveness of CCT. This uncertainty can have an impact on the estimated cost of all modeled systems required to install or re-optimize CCT under both the previous and final LCRR. This impact on cost follows from the rule structure with systems that continue to exceed the TL and AL being required to take additional actions (e.g., increase frequency of sampling, LSLR, and public education). In determining the likely ranges of effectiveness among PWSs under the low and high cost scenarios, EPA made the following assumptions:
 There is no difference between the effectiveness of a new installation of CCT or the re-optimization of existing CCT under the final LCRR as systems are assumed to get to the same endpoint of orthophosphate dose or pH adjustment through either process.
 For PWSs with no LSLs, CCT is always effective enough to ensure the model PWS's post installation or re-optimization 90[th] percentile is always lower than or equal to the TL.
 Under the low cost scenario, CCT is highly effective in lowering lead levels in model PWSs with LSLs. Ninety percent of PWSs that begin with a 90[th] percentile greater than the AL will reach a 90[th] percentile lower than or equal to the TL after CCT installation or re-optimization. The remaining 10 percent will have a 90[th] percentile greater than the TL but not greater than the AL after installing or re-optimizing CCT. All PWSs that begin with a 90[th] percentile greater than the TL but not greater than the AL will have a 90[th] percentile below or equal to the TL after CCT installation or re-optimization.
 Under the high cost scenario, CCT is somewhat less effective in lowering lead levels in model PWSs with LSLs. Seventy-five percent of PWSs that begin with a 90[th] percentile greater than the AL will reach a 90[th] percentile lower than or equal to the TL after CCT installation or re-optimization. The remaining 25 percent will have a 90[th] percentile greater than the TL but not greater than the AL after installing or re-optimizing CCT. Ninety percent of PWSs that begin with a 90[th] percentile greater than the TL but not greater than the AL will have a 90[th] percentile below or equal to the TL after CCT installation or re-optimization. The remaining 10 percent will not be able to lower their 90[th] percentile to the TL or below.
The assumptions about CCT effectiveness under the low and high cost scenarios are summarized in Exhibit 5-7 and Exhibit 5-8.
Exhibit 5-7: Low Cost Scenario Assumptions for CCT Effectiveness
Likelihood of Change in Post CCT Installation or Re-optimization P90y+1 Range
                      P90y+1-Range Prior to Change in CCT
Likelihood P90y+1 greater than the TL and not greater than the AL after change in CCT
         Likelihood P90y+1 not greater than the TL after change in CCT

                                     LSLs
                                    No LSL
                                     LSLs
                                    No LSLs
Greater than the AL
                                      10%
                                      0%
                                      90%
                                     100%
Greater than the TL but not greater than the AL
                                      0%
                                      0%
                                     100%
                                     100%
Note: In SafeWater LCR, P90y+1 is the 90[th] percentile tap sample level for the PWS in the next year to be modeled.  PWS decisions about CCT installation are made in year y based on P90y+1  as changes in treatment technology or source water in year y could change P90y+1. In other words, EPA assumes that before a treatment change, or source water change, is made, Primacy Agencies would require adequate CCT to be in place that ensures the PWS does not have an ALE.
Exhibit 5-8: High Cost Scenario Assumptions for CCT Effectiveness
Likelihood of Change in Post CCT Installation or Re-optimization P90y+1 Range
                      P90y+1-Range Prior to Change in CCT
Likelihood P90y+1 greater than the TL and not greater than the AL after change in CCT
         Likelihood P90y+1 not greater than the TL after change in CCT

                                     LSLs
                                    No LSL
                                     LSLs
                                    No LSLs
Greater than the AL
                                      25%
                                      0%
                                      75%
                                     100%
Greater than the TL but not greater than the AL
                                      10%
                                      0%
                                      90%
                                     100%
Note: In SafeWater LCR, P90y+1 is the 90[th] percentile tap sample level for the PWS in the next year to be modeled.  PWS decisions about CCT installation are made in year y based on P90y+1  as changes in treatment technology or source water in year y could change P90y+1. In other words, EPA assumes that before a treatment change, or source water change, is made, Primacy Agencies would require adequate CCT to be in place that ensures the PWS does not have an ALE.
LSLR Unit Costs
EPA collected LSLR estimates available from the web in the form of news reports, press releases, and utility websites, primarily representing costs and practices from 2016 to 2020. The compiled dataset provides costs estimates across full, customer-side, and system-side replacements from 38 systems that have reported actual replacement costs from pilot studies and recent or on-going LSLR projects. Additional information on the unit cost data sources is described in Appendix A, Section A.2.1. Utilizing the utility data EPA collected on the average unit cost of full, utility-side, and customer-side LSLR to represent the potential universe of LSLR costs facing PWSs is also uncertain given the small number of observations. Because of this uncertainty in the LSLR cost estimate and the potentially large impact this unit cost may have on the overall national cost estimates, EPA chose to develop low and high LSLR unit cost estimates that will be used as inputs for the SafeWater LCR model in the development of cost ranges that potentially bracket the overall uncertainty in EPA's estimated average LSLR unit costs.
Based on a review of the data from all sources and experience with LSLR in high-profile systems including Flint, Michigan, EPA developed a low and high LSLR unit cost estimate as follows:

 Low estimate: 25[th] percentile of utility estimates for each type of replacement: utility-side, customer-side, and full, as well as planned full and planned utility-side.
 High estimate: 75[th] percentile of utility estimates for each type of replacement: utility-side, customer-side, and full, as well as planned full and planned utility-side.
EPA did not use the minimum and maximum values for this bounding exercise given that applying these figures to 100 percent of LSLRs seemed unreasonably extreme. Moreover, a key cost driver is the length of the LSL to be replaced, and the minimum and maximum would represent an extremely short or long line and not a typical length. Using minimum and maximum values would have produced a national estimate range greater than what is warranted given the uncertainty in the distribution of LSLR unit costs.

The low and high estimates used in this economic analysis (EA) are presented in Exhibit 5-9. They are expected to provide a range of national costs for the final LCRR that reflects the degree of uncertainty in the average LSLR unit costs.

Exhibit 5-9: LSLR Unit Costs for Low and High Cost Scenarios ($2016)
Replacement Type
                               Low Cost Scenario
                              High Cost Scenario
Utility-Side
                                                                    $2,449
                                  $5,689
Customer-Side
                                                                    $2,514
                                  $3,929
Full Replacement
                                                                    $3,953
                                  $6,024
Utility-Side, Planned
                                                                    $1,959
                                  $4,551
Full Replacement, Planned
                                                                    $3,163
                                  $4,819
     Note: Data in this exhibit replicated data provided in Appendix A, Exhibit A-3.
The unit costs estimates used in the SafeWater LCR model do not include certain indirect and non-market costs such as traffic congestion costs, inconvenience to homeowners and neighbors at LSLR sites, potential short term impact to the aesthetic appeal of the property, and additional impacts to landscaping and cost of replacement beyond lawn repair, which is covered in the unit cost estimates above.
CCT Unit Costs
EPA developed the cost estimates for CCT scenarios using outputs from the caustic feed and phosphate feed Work Breakdown Structure (WBS) models. Outputs from these models are point estimates of total capital and operation and maintenance (O&M) cost that correspond to a given set of inputs that include treatment plant design flow (DF) and average flow in million gallons per day (MGD). To estimate costs for CCT, EPA fit cost curves to the WBS outputs for up to 49 different flow rates. Specifically, for each scenario modeled and separately for total capital and for O&M costs, EPA fit three curves: one covering small systems (less than 1 MGD DF), one covering medium systems (1 MGD to less than 10 MGD DF), and one covering large systems (10 MGD DF and greater).
For each CCT scenario modeled, EPA also estimated separate equations for low, mid, and high costs (see Technologies and Costs for Corrosion Control to Reduce Lead in Drinking Water (USEPA, 2020)). EPA developed the low, mid, and high cost equations by varying the component level input in the WBS models. This input drives the selection of materials for items of equipment that can be constructed of different materials. For example, a low cost system might include fiberglass storage tanks and polyvinyl chloride (PVC) piping. A high cost system might include stainless steel storage tanks and stainless steel piping. The component level input also drives other WBS model assumptions that can affect the total cost, such as building quality and heating and cooling. Because of uncertainty in the component level materials selection a PWSs would choose for real world installation or re-optimization of CCT technology, EPA chose to use the low CCT cost equations in the SafeWater LCR model for the low cost scenario and, for the high cost scenario, the SafeWater LCR model uses the high CCT cost equations.
Model PWSs, Large Systems, Discounting, Compliance Schedule, and Simulating Compliance Activities
As discussed above in Sections <IP_ADDRESS> and <IP_ADDRESS>, under the regulatory provisions of the final rule, PWSs will face different compliance scenarios depending on the size, the type of water system, the presence of LSLs, and existing corrosion controls. In addition, PWSs will also face different unit costs based on water system size, type, and number of entry points (e.g., labor rates and CCT capital, and O&M unit costs). PWSs have a great deal of inherent variability across the water system characteristics that dictate both compliance activities and cost.
Because of this variability, to accurately estimate the national level compliance costs (and benefits) of the final LCRR, as well as describe how compliance costs are expected to vary across types of PWSs, the SafeWater LCR model creates a sample of representative "model PWSs" by combining the PWS-specific data available in SDWIS/Fed with data on baseline and compliance characteristics available at the PWS category level. The SafeWater LCR model follows each model PWS in the sample through each year of analysis  -  determining how the PWS will comply with each requirement of the final rule, estimating the yearly compliance cost, and tracking the impact of the compliance actions on drinking water lead concentrations. It also tracks how other events, such as changing a water source or treatment, affect the water system's compliance requirements for the next year.
In constructing the initial model PWS sample for the cost-benefit analysis, EPA began with the 50,067 CWSs and 17,589 NTNCWSs in SDWIS/Fed. Also, from SDWIS/Fed, EPA knows each water system's type (CWS or NTNCWS); primary water source (surface water or groundwater); population served; CCT status (yes/no); ownership (public or private); and number of connections. The available limited data on major LCR compliance cost drivers including: the baseline number of systems with LSLs and the percent of connections in those system that are LSLs; the number of PWSs that will exceed the AL and/or TL under the final revised tap sampling requirements; the cost of LSL replacement; the cost of CCT; and the effectiveness of CCT in PWSs with LSLs constrained EPA's ability to develop accurate point cost estimates for the previous rule and final LCRR or quantify uncertainty around the point estimates in the SafeWater LCR model. Therefore, EPA estimated previous rule and final LCRR compliance costs under low and high bracketing scenarios. These low and high cost scenarios are defined by the assignment of low and high values for the set of uncertain cost drivers. Detailed descriptions of these five uncertain variables and the derivation of their values under the low and high cost scenarios can be found in Section <IP_ADDRESS>, above. With the exception of the five uncertain variables, which define the difference between the low and high cost scenarios, the remaining baseline water system and compliance characteristics are assigned to model PWSs, as described in Section <IP_ADDRESS> above and Appendix B section B.2.1, and remain constant across the scenarios. This allows EPA to define the uncertainty characterized in the cost range provided by the low and high scenarios and maintains consistency between the estimation of costs for the previous and final rules (e.g., percentage of lead tap water samples that will be invalidated).
Because PWS baseline characteristics are being assigned from distributional source data to capture the variability across PWS characteristics, EPA needed to ensure that its sample size was large enough that the results of the cost-benefit model were stable for each of the 36 PWS categories. To ensure stability in modeled results, EPA oversampled the SDWIS/Fed inventory to increase the number of water systems in each PWS category. For every PWS category, EPA set the target minimum number of model-PWSs to 5,000. To calculate the total estimated costs for each PWS category, the SafeWater LCR model weights the estimated per water system costs so that, when summed, the total cost is appropriate for the actual number of water systems known to be in the category. See Appendix B Section B.2.1 for more detail.
The exception to the assignment of water system characteristics discussed in Sections <IP_ADDRESS>, and Appendix B.2.1 are the 21 very large water systems serving more than one million people. Because of the small number of water systems in this size category, the uniqueness of their system characteristics, and the potential large cost for these systems to comply with the final regulatory requirements, using the methods described above to assign system attributes could result in substantial error in the estimation of the national costs. Therefore, EPA attempted to collect information on very large water systems' CCT practices and chemical doses, pH measurements and pH adjustment practices, number of LSLs, service populations, and average annual flow rates for each entry point to the distribution system. EPA gathered this information from publicly available data such as SDWIS/Fed facility-level data, Consumer Confidence Reports, and water system websites. In addition, the American Water Works Association (AWWA) provided additional data from member water systems to fill in gaps. When facility-specific data was available, EPA used it to estimate compliance costs for the very large water systems. If data were not available, EPA assigned baseline characteristics using the same process as previously described. See Appendix B, Section B.2.1.1 for a summary of the data EPA collected on these very large systems.
The SafeWater LCR model estimates the incremental cost of the final LCRR over a 35-year period. In accordance with EPA's policy, and based on guidance from OMB, when calculating social costs and benefits, EPA discounted future costs (and benefits) under two alternative social discount rates, 3 percent and 7 percent.
When evaluating the economic impacts on PWSs and households, EPA uses the estimated PWS cost of capital to discount future costs, as this best represents the actual costs of compliance that water systems would incur over time. EPA used data from the 2006 Community Water System Survey (CWSS) to estimate the PWS cost of capital (USEPA, 2009). EPA calculated the overall weighted average cost of capital (across all funding sources and loan periods) for each size/ownership category, weighted by the percentage of funding from each source. The cost of capital for each CWS size category and ownership type is shown in Exhibit B-3 in Appendix B.2.2. Since similar cost of capital information is not available for NTNCWSs, EPA used the CWS cost of capital when calculating the annualized cost per NTNCWS. Total estimated cost of capital may be greater than actual costs water systems bear when complying with future regulatory revisions because financing support for lead reduction efforts may be available from state and local governments, EPA programs (e.g., the Drinking Water State Revolving Fund (DWSRF), the Water Infrastructure Finance and Innovations Act (WIFIA) Program, and the Water Infrastructure Improvements for the Nation Act of 2016 (WIIN Act) grant programs), and other federal agencies (e.g., the United States Department of Housing and Urban Development's (HUD's) Community Development Block Grants). The availability of funds from government sources, while potentially reducing the cost to individual PWSs, does not reduce the social cost of capital to society.
EPA projects that rule implementation activities will begin immediately after rule promulgation. These activities will include one-time PWS and Primacy Agency costs for staff to read the rule, become familiar with its provisions, and develop training materials and train employees on the new rule. Primacy Agencies will also incur burden hours associated with adopting the rule into State requirements, updating their LCR program policies and practices, and modifying data record keeping systems. PWSs will incur costs to comply with the service line materials inventory requirements and develop an initial LSLR plan in years one through three of the analysis. EPA expects that water systems will begin complying with all other final rule requirements three years after promulgation, or in year four of the analysis.
Some requirements of the final rule must be implemented by water systems regardless of their water quality and tap sampling results (e.g., CWS school and child care sampling programs); however, most of the major cost drivers are a function of a water systems 90[th] percentile lead tap sample value. The 90[th] percentile value, and if it exceeds the lead TL or AL, dictates:
 the tap water sampling and WQP monitoring schedules,
 the installation/re-optimization of CCT, "find-and-fix" adjustments to CCT (triggered by single lead tap sample exceedances of the 15 μg/L AL, which has an increasing likelihood in the model as 90[th] percentile tap sample results increase),
 the installation of point-of-use (POU) filters at water systems selecting this treatment option as part of the small water system flexibilities of the final rule,
 the goal-based or mandatory removal of LSLs, and water system and Primacy Agency administrative costs.
Because of uncertainty in the estimation of the 90[th] percentile values, the Agency developed low and high estimates for this cost driving variable affecting both the estimation of costs for the previous rule and the final LCRR. EPA used both the minimum and maximum 90[th] percentile tap sample values from SDWIS/Fed over the period from 2007 to 2015, to assign a percentage of PWSs by LSL status to each of three groups, those at the TL or below, those above the lead trigger but at or below AL, and those above the lead AL. These assignments represent the status of systems under the previous rule. Because the tap sampling requirements under the final LCRR call for 100 percent of compliance tap samples to be taken from sites with LSLs, for water systems with LSLs, and for sampling the fifth liter instead of the first liter (as required under the previous rule) at LSL sites, EPA's estimate of the likelihood that a PWS would have a lead 90[th] percentile greater than the TL or AL is higher under the final rule compared to under the previous LCR. See Section <IP_ADDRESS>.2 for additional information on the estimation of the low and high 90[th] percentile values for the previous rule assessment and the further adjustments made to project 90[th] percentile values for the final LCRR.
Once water systems are assigned to the groupings based on their LSL status, individual 90[th] percentile lead tap sample values are assigned from the distribution of 90[t][h] percentile values within each grouping.
Several regulatory compliance activities are assumed to not affect a water system's 90[th] percentile value. These include, for example, developing an inventory of LSLs, CWS sampling at schools and child cares, and public education. In the SafeWater LCR model, the only compliance activities that will change a water system's 90[th] percentile lead tap sample are: installation of CCT; re-optimization of existing CCT; removal of LSLs; and a water system-wide "find-and-fix" activity (assumed to be a system-wide increase in pH). In addition to these final rule compliance activities, changing a water source or treatment technology can also result in a change in a water system's 90[th] percentile tap sample value.
Because a water system's lead 90[th] percentile value is so important to determining regulatory requirements and cost under the final rule, the SafeWater LCR model, under both the low and high cost scenarios, tracks each water system's 90[th] percentile value over each annual time step in the model. Based on the initial 90[th] percentile values, a number of final rule compliance actions are triggered. With the implementation of CCT, LSLR, and "find-and-fix" corrections, 90[th] percentile tap sample values are expected to decrease. The SafeWater LCR model allows for future increases in 90[th] percentile values as a result of changes in source water and treatment. The likelihood of these events occurring have been derived from SDWIS/Fed data (see Chapter 4). When a change in source or treatment occurs in a modeled year, a new 90[th] percentile value is assigned to the water system. This value may be higher or lower than the current value thus potentially triggering new corrective actions. In the SafeWater LCR model, if a water system already has "optimized" CCT in place, it is assumed that no additional action is needed and that the current treatment is adequate; therefore, the 90[th] percentile will not change.
Estimating Public Water System Costs
This section details how EPA estimated the cost of water system compliance for each major rule component of the LCRR, including:
 5.3.1: PWS Implementation and Administrative Costs
 5.3.2: PWS Sampling Costs
 5.3.3: PWS Corrosion Control Costs
 5.3.4: PWS Lead Service Line Inventory and Replacement Costs
 5.3.5: PWS POU-Related Costs
 5.3.6: PWS Lead Public Education and Outreach Costs
Section 5.3.7 provides a summary of PWS costs including PWSs counts and population affected by each major requirement, as well as costs by system and source water type and size category for low and high cost scenarios at a 3 percent and 7 percent discount rate. In addition, the cost per household is also presented.
For most activities, water systems will incur costs in the form of burden (i.e., hours). The burden is multiplied by the labor rate ($/hr), as presented in Chapter 4, Section <IP_ADDRESS>, to estimate labor unit costs. Systems will also incur capital and O&M costs for some activities. Exhibit 5-10 provides an overview of the rule components, subcomponents, and activities for which EPA estimates water system costs for the LCRR. The derivation of unit burden and/or cost is provided in each referenced subsection.
At the end of each subsection, EPA provides a summary exhibit showing the SafeWater LCR modeling approach for each water system activity (e.g., Exhibit 5-12, Exhibit 5-20). The exhibits are organized as follows:
 The first and second columns show how unit burden and labor rate information is combined to estimate a CWS and NTNCWS cost per activity, respectively.
 The third and fourth columns indicate the conditions under which the water system activity occurs. The columns indicate if the system activity is dependent on:
 The system's 90[th] percentile range. See Appendix B, Section B.3 for a detailed discussion of how the SafeWater LCR model tracks a water system's 90[th] percentile level and accounts for changes in the 90[th] percentile level over the 35-year analysis period.
 Other characteristics of the system such as presence or absence of LSLs and/or CCT, and frequency of monitoring.
 The fifth column indicates the frequency of the activity (e.g., one-time, annually, every 3 years).
The SafeWater LCR model uses the information from these exhibits to calculate total annualized water system cost for each activity. See Section 5.2.4 for detail on the cost modeling methodology.
As noted in Section 5.1, costs for water systems presented in this section are LCRR costs if no previous rule were in place. The national costs of the LCRR, or incremental costs, are the difference between the cost of compliance with the LCRR and the cost of compliance with the previous LCR. These incremental national costs are presented in Section 5.1.
For the purpose of the SafeWater LCR modeling, all cost model inputs are assigned a unique data variable name, usually in the form of abbreviations, or shorthand, separated by underlined spaces (e.g., rate_op, hrs_read_rule_op). The SafeWater LCR model uses these data variables to model LCRR scenarios for different system sizes and types.
Exhibit 5-10: PWS Cost Components, Subcomponents, and Activities Organized by Section1
                                   Component
                                 Subcomponents
                                 Activities[2]
5.3.1: PWS Implementation and Administration Costs
<IP_ADDRESS>: One-time Costs
 Read and understand the rule
 Assign personnel and resources for rule implementation
Participate in training and technical assistance from Primacy Agency during rule implementation
Provide small system flexibility option recommendation to Primacy Agency
5.3.2: PWS Sampling-Related Costs
<IP_ADDRESS>: Lead Tap Sampling Costs
 Update sampling instruction for lead tap sampling and submit to Primacy Agency
Contact homes to establish new 100 percent LSL tap sampling pool
Report any changes in sampling location to the Primacy Agency
Confer with Primacy Agency on initial lead sampling data and status under the LCRR
Obtain households for each round of lead tap sampling
Offer incentives to households to encourage participation in lead tap sampling program
Ship tap sampling material and instructions to participating households
Collect lead tap samples
Determine if sample should be rejected and not analyzed
Analyze lead tap samples in-house or commercially
Prepare and submit sample invalidation request to Primacy Agency
Inform customers of lead tap sample results
Certify to Primacy Agency that results were reported to customers
Submit request to renew 9-year monitoring waiver to Primacy Agency
Submit sampling results and 90[th] percentile calculation to Primacy Agency

<IP_ADDRESS>: Lead WQP Monitoring Costs
Collect lead WQP samples in the distribution system
Analyze distribution system lead WQP samples
Collect lead WQP samples from entry points
Analyze entry point lead WQP samples
Report lead WQP sampling data and compliance with OWQPs to Primacy Agency
5.3.2: PWS Sampling-Related Costs (continued)
<IP_ADDRESS>: Copper WQP Monitoring Costs
Collect copper WQP samples in the distribution system
Analyze distribution system copper WQP samples
Collect copper WQP samples from entry points
Analyze entry point copper WQP samples
Report copper WQP sampling data and compliance with OWQPs to Primacy Agency

<IP_ADDRESS>: Source Water Monitoring Costs
Collect source water sample
Analyze source water sample
Report source water monitoring results to Primacy Agency

<IP_ADDRESS>.1: School and Child Care Lead Sampling Costs - Mandatory
Create a contact list of schools and child cares served by CWS and submit to Primacy Agency
Develop lead outreach materials for schools and child cares
Prepare and distribute initial letter explaining the sampling program and the 3Ts Toolkit
Contact school or child care to determine and finalize its sampling schedule
Contact school or child care to coordinate sample collection logistics
Conduct walkthrough at school or child care before the start of sampling
Travel to collect samples
Collect samples
Analyze samples
Provide sampling results to tested facilities
Discuss sampling results with school or child care
Conduct detailed discussion of high sampling results with school and child cares
Prepare and provide annual report on school and child care sampling program to the Primacy Agency

<IP_ADDRESS>.2: School and Child Care Lead Sampling Costs  -  On Request
Contact school and child cares to offer sampling
Contact school or child care to coordinate sample collection logistics
Conduct walkthrough at school or child care before the start of sampling
Travel to collect samples
Collect samples
Analyze samples
Provide sampling results to tested facilities
Discuss sampling results with school and child care
Conduct detailed discussion of high sampling results with school and child cares
Prepare and provide annual report on school and child care sampling program to the Primacy Agency
5.3.3: PWS CCT-Related Costs

<IP_ADDRESS>: CCT Installation Costs
 Conduct a CCT study
Install CCT Treatment (PO4, PO4 with post treatment, pH adjustment, or modify pH)

<IP_ADDRESS>: Re-optimization of Existing Corrosion Control Treatment
Revise CCT study
Reoptimize existing CCT

<IP_ADDRESS>: Find-and-Fix Costs
Contact customers and collect follow-up tap sample
Analyze follow-up lead tap sample
Collect distribution system WQP sample
Analyze distribution system WQP sample
Review incidents of system-wide event and other system conditions
Consult with Primacy Agency prior to making CCT changes
Report to Primacy Agency follow-up sample results and overall "find-and-fix" responses

<IP_ADDRESS> System Lead CCT Routine Costs
Review CCT guidance
Provide water quality data to Primacy Agency and discuss during sanitary survey
Notify and consult with Primacy Agency on required actions in response to source water change
Notify and consult with Primacy Agency on required actions in response to treatment change
5.3.4: PWS LSL Inventory and Replacement Costs
<IP_ADDRESS>: LSL Inventory Costs
 Create initial LSL inventory and submit to Primacy Agency
 Submit documentation of no LSLs to Primacy Agency
Develop general LSL outreach materials and submit to Primacy Agency for review
Distribute general LSL outreach materials
Submit annual or triennial LSL inventory update to Primacy Agency

<IP_ADDRESS>: LSLR Plan
Develop LSLR plan and submit to Primacy Agency for review

<IP_ADDRESS>: LSL Replacement Costs
Systems replace LSLs
Households replace privately-owned portion of LSLs if goal-based or customer-initiated program

<IP_ADDRESS>: Ancillary LSL Replacement Activities
Conduct planning and identify financial options for LSLRs and submit to Primacy Agency
Consult with Primacy Agency and develop targeted LSLR program outreach materials
Distribute targeted LSLR program outreach materials
Contact customers and conduct site visits prior to LSLR
Inspect and test lines to confirm they are not lead
Deliver filters and cartridges at time of LSLR and maintain them for 6 months
Collect tap sample post-LSLR
Analyze post-LSLR tap sample
Inform customers of tap sample result
Submit annual report on LSLR program to Primacy Agency

<IP_ADDRESS>: PWS Failure to Meet Goal-Based Replacement Rate Costs
Consult with Primacy Agency on activities to satisfy additional goal-based LSLR program outreach requirements
Conduct activities in response to the first failure to meet LSLR goal
Conduct activities in response to each additional failure to meet LSLR goal
5.3.5: PWS POU-Related Costs
<IP_ADDRESS>: POU Installation and Maintenance
 Provide, monitor, and maintain POU devices

<IP_ADDRESS>: POU Ancillary Costs
Develop POU plan and submit to Primacy Agency
Develop PE materials and submit to Primacy Agency
Print POU education materials
Obtain households for POU monitoring
Deliver POU monitoring materials and instructions to participating households
Collect tap samples after POU installation
Determine if sample should be rejected and not analyzed
Analyze POU tap samples
Prepare and submit sample invalidation request to Primacy Agency
Inform customers of POU tap sample results
Certify to Primacy Agency that POU tap results were reported to customers
Prepare and submit annual report on POU program to Primacy Agency
5.3.6: PWS PE and Outreach Costs
<IP_ADDRESS>: Consumer Notice in Response to Lead Sample > 15 ug/L
 Provide notice to customers with lead tap sample > 15 ug/L within 3 calendar days
 Provide a copy of the 3 calendar day notice to the Primacy Agency

<IP_ADDRESS>: Activities Regardless of 90[th] Percentile Level
Update CCR language
Develop new customer outreach plan
Develop approach for improved public access to lead health-related information and tap sample results
Establish a process for public access to information on LSL locations
Maintain a process for public access to lead health information, LSL locations, and tap sample results
Respond to customer request for LSL information
Respond to requests from realtors, home inspectors, and potential home buyers for LSL information
Develop list of state and local health agencies
Develop lead outreach materials for state and local health agencies
Deliver lead outreach materials for state and local health agencies
Develop PE materials for disturbances of service lines and submit to Primacy Agency
Deliver PE during disturbances of service lines
Deliver filters and cartridges during disturbances of service lines and maintain them for 6 months

<IP_ADDRESS>: Activities in Response to Lead ALE
Update mandatory language for lead ALE PE and submit to Primacy Agency for review
Deliver lead ALE PE materials to all customers
Contact public health agencies to obtain additional organizations and update recipient list
Notify public health agencies and other organizations
Post notice to website
Consult with Primacy Agency on other PE activities
Implement other PE activities
Prepare press release
Certify to Primacy Agency that lead outreach was completed[3]
Acronyms: 3Ts = "3Ts for Reducing Lead in Drinking Water in Schools and Child Care Facilities Toolkit: A Training, Testing, and Taking Action Approach (Revised Manual)"; AL = action level; ALE = action level exceedance; CCR = consumer confidence report; CCT = corrosion control treatment; CWS = community water system; LCRR = Lead and Copper Rule revisions; LSL = lead service line; LSLR = lead service line replacement; OWQPs = optimal water quality parameters; PE = public education; PO4 = orthophosphate; POU = point-of-use; PWS = public water system; WQP = water quality parameter.
Notes:
1 Systems will also incur burden for recordkeeping activities under the LCRR, such as retaining records of decisions, supporting documentation, technical basis for decisions, and documentation submitted by the system. EPA has included burden for recordkeeping with each activity when applicable and opposed to providing separate burden estimates.
[2] EPA assigned a unique letter identification (ID) for each activity under a given rule component. Activities are generally organized with upfront, one-time activities first followed by ongoing activities.
[3] This certification is inclusive of outreach activities in Sections <IP_ADDRESS> through <IP_ADDRESS>.
PWS Implementation and Administrative Costs
PWSs will incur one-time burden to implement new requirements. These activities and associated SafeWater LCR model cost inputs are described in Section <IP_ADDRESS>. Section <IP_ADDRESS> provides the estimated annualized national PWS implementation and administrative costs for the LCRR at 3 percent and 7 percent discount rates.
PWS One-Time Implementation and Administrative Costs