Input:
	Background

This section provides information on (1) the known health effects of lead  in drinking water; (2) how water systems deliver drinking water to the  public and where lead may be present; (3) the requirements of the LCR;  (4) LCR data that states report to EPA; and (5) the roles of federal, state,  and local entities in implementing the LCR.

		Health Effects of Lead in Drinking Water

EPA, the Centers for Disease Control and Prevention (CDC), and others  have indicated that the rates of lead contamination in the U.S. population  have decreased over the years. However, lead remains a significant  concern to public health because lead is persistent and can accumulate in  the body over time with long-lasting effects, particularly for children and  pregnant women. According to EPA documents, low levels of lead  exposure in children are linked to hyperactivity, anemia, lower intelligence  quotient (IQ), physical and learning disabilities, and slowed growth. In  pregnant women, lead can store in bones and be released as maternal  calcium used to form the bones of the fetus, reduce fetal growth, and  increase risk of miscarriage and stillbirth. For adults, lead can have  detrimental effects on cardiovascular, renal, and reproductive systems;  and, it can prompt memory loss. The presence of lead in the bloodstream  can disappear relatively quickly, but bones can retain the toxin for  decades.
According to the National Institutes of Health and CDC documents,  medications can remove some lead from the body but cannot undo the  damage lead causes, although additional services may mitigate some of  the damage. Recognizing that vigilance and collaboration are necessary  to ensure that children negatively affected by lead exposure receive  services designed to compensate for lead’s effect on the brain, and  behavior of children, some medical experts promote early-childhood  intervention, education, and other programs. According to CDC  documents, early intervention for children can help improve IQ scores,  academic readiness, and language development as well as decrease  placement in special education classes. For these reasons, EPA and  others recommend the prevention of lead exposure before it occurs.

		How Water Systems Deliver Drinking Water

Water systems depend on distribution systems, both simple and complex,  composed of interconnected components to deliver drinking water from a  source to their customers. Source water can be either surface (streams,  rivers, and lakes) or ground (aquifers). As figure 1 illustrates, the  distribution system used to deliver water from the source can include a  network of pipes and other components. A distribution system comprises  water towers, pipes, pumps, and other components to deliver treated  water from treatment systems to consumers. Particularly among larger  water systems, distribution systems may contain thousands of miles of  pipes, including water mains.
There are 1 million miles of drinking water mains in the country, according  to a 2017 American Society of Civil Engineers study. Service lines are  the smaller pipes that connect the water mains to homes and buildings  and can also include smaller pipes used for connecting a service line to  the water mains (e.g., called pigtail and gooseneck pipes). In contrast to  most other drinking water contaminants, lead is rarely found in the source  water. More commonly, lead enters drinking water after the water comes  into contact with water mains; service lines; smaller pipes that connect  the two; and other plumbing materials that contain lead, such as faucets  and water coolers. Schools and day care centers with their own water  supplies generally rely on well-water systems using groundwater to  deliver drinking water.
According to the 2017 American Society of Civil Engineers study and  EPA documents, communities, both urban and rural, have aging and  deteriorating drinking water infrastructure, which, according to EPA  documents, can contribute to lead hazards in drinking water. Since the  early 1970s, when several medical studies confirmed that lead exposure  negatively impacts health, measures have been taken to reduce the  public’s exposure to lead in drinking water, including the enactment of  amendments to the SDWA in 1986 and 1996, the enactment of the Lead  Contamination Control Act in 1988, the issuance of the LCR in 1991, and  amendments to state building codes prohibiting the use of lead pipes.

		The Lead and Copper Rule

The LCR generally requires water systems to minimize lead in drinking  water by controlling the corrosion of metals in the infrastructure they use  to deliver water and in household plumbing. EPA has stated that the  LCR is one of the most complicated drinking water regulations for states  to implement because of the need to control the corrosion of pipes and  plumbing fixtures as water is delivered to consumers. The corrosion of  pipes results from a chemical interaction between water and pipes that  wears the metal away and allows particles of metal to flake away over time. All large water systems (serving populations larger than 50,000) are  generally required to install corrosion control treatment. While the majority  of the U.S. population receives its drinking water from medium and large  water systems, most water systems are small.
Characteristics of water can affect the occurrence and rate of corrosion.  For example, corrosion occurs more frequently in soft water—water with  low concentrations of calcium and magnesium—and also in acidic water,  or water with low pH. Water systems control corrosion by adjusting the  pH and alkalinity of water or by adding corrosion inhibitors. The LCR  establishes corrosion control as the required treatment technique for large  water systems and, for medium and small systems, the required  treatment technique when the federal lead action level is exceeded (also  known as an action level exceedance). Lead concentrations exceeding  an action level of 15 parts per billion, or 0.015 milligrams per liter (mg/L),  in over 10 percent of tap water samples (i.e., the 90th percentile level) are  an indicator that corrosion control is needed or is not working correctly.  A water system’s 90th percentile sample result does not exceed the lead  action level if it is equal to or less than 15 parts per billion. As figure 2  illustrates, the LCR also requires water systems to identify locations  where lead may be present and periodically obtain tap water samples  from those locations (of which single-family homes are the highest  priority).
Under the LCR, an action level exceedance requires the water system  and state to take a number of additional steps. Those additional steps  require that small and medium water systems install or modify corrosion  control treatment, and water systems of all sizes provide information  (known as public education) about the harmful effects of lead to  consumers and vulnerable populations (e.g., schools, if the water system  serves a school, and public health departments). Water systems are  also required to test and, if necessary, treat the source water. If, after  installing corrosion control and treating source water, a system continues  to have 90th percentile sample results that exceed the lead action level,  the LCR requires the water system to begin replacing lead service lines, if  they exist. In most communities, lead service lines are partially owned by  the water system and partially owned by the homeowner. The LCR allows  for a partial replacement when an owner of a home or building is unable  or unwilling to pay for replacement of the portion of the service line not  owned by the water system.
In an October 2016 study, EPA noted that sample requirements under the  LCR are complex for many reasons, one reason being that it is the only  drinking water regulation in which homeowners or consumers collect the  drinking water samples. Water systems are in compliance with the LCR  when they follow the various federal requirements for collecting samples,  reporting, installing treatments, providing public education, and replacing  lead service lines; as well as when they follow any state requirements that  are more stringent than the federal requirements. States and EPA can  take several different types of enforcement actions when water systems  fail to complete requirements in these areas. Sample results that exceed  the lead action level do not by themselves constitute violations of the  LCR.
The SDWA, as amended in 1996, requires EPA to review and revise, as  appropriate, each national primary drinking water regulation, including the  LCR, at least once every 6 years. The 1991 LCR was revised in 2000 and  2007. EPA initiated an extensive review of the LCR in 2004 after  widespread increases in lead levels were detected in the District of  Columbia’s water following a water treatment change. EPA promulgated  short-term revisions and clarifications in 2007 and has continued working  on comprehensive revisions. In 2016, the agency announced that it would  revise the LCR and issue proposed revisions in 2017 and a final revised  rule in 2019. EPA also released a Lead and Copper Rule Revisions White  Paper in 2016 that outlined potential elements of the rule under  consideration for revision such as use of corrosion control practices,  requirements for collecting samples, and lead service line replacement.

		LCR Data That States Report to EPA

The LCR generally requires that water systems submit data to states to  demonstrate their compliance with the treatment technique required by  the rule. The LCR also requires states to submit some of these data to  EPA’s SDWIS/Fed database on a quarterly basis. Specifically, states are  required to submit the following data to EPA:  for large and medium water systems, all 90th percentile sample  results (i.e., sample results that meet, fall below, and exceed the lead  action level);  for small water systems, 90th percentile sample results that exceed  the lead action level; on water systems that have been designated as having achieved  corrosion control because the state has determined that the source  water is minimally corrosive; on water systems that were required to install corrosion control  treatment, source water treatment, and lead service line replacement  and have completed the applicable requirements as a result of having  sample results exceed the lead action level; on water systems that have begun the process of replacing lead on water systems that have new violations of the LCR; and on enforcement actions taken in response to violations of the LCR.
For corrosion control, the LCR requires the states to report what EPA  refers to as “milestone” data to the SDWIS/Fed database: data on the status of required actions, such as installing corrosion  control treatment, as required, after reporting sample results that  exceed the lead action level; and data on those water systems deemed to have corrosion already under  control, such as when the water is minimally corrosive.
The states collect and manage relevant data (including violations and  enforcement information) in either a database provided by EPA—known  as the Safe Drinking Water Information System/State—or in a data  system of their own design. States must then transfer the data from one  of those databases into SDWIS/Fed. In 2010, EPA announced that it  would redesign SDWIS/Fed. We reported in June 2011 that EPA officials  expected this redesign of SDWIS/Fed to expand the amount of data that  EPA receives electronically from states. The name of the redesigned  database is SDWIS Prime, which according to EPA officials, is expected  to be complete by 2018.

		Roles of Federal, State, and Local Entities in Implementing the LCR

Generally, the responsibility for reducing lead in drinking water and  ensuring safe drinking water overall, is shared by EPA, states, and, local  water systems. As shown in figure 3, EPA is responsible for national  implementation of the LCR and setting standards; overseeing states’  implementation of the LCR; providing infrastructure funding, training, and  technical assistance to states and water systems; and conducting some  enforcement activities. However, the primary responsibility for ensuring  that drinking water is free of lead resides with states and local water  systems.
Generally, states with primary enforcement responsibility initiate  enforcement actions against water systems that do not comply with the  LCR and other drinking water regulations. However, EPA can also issue  orders necessary to protect human health where a contaminant in a  public water system presents an imminent and substantial  endangerment. According to a 2013 EPA drinking water compliance  report, states generally implement and enforce the LCR, and other  drinking water regulations, in the following ways: provide technical assistance through such actions as offering training,  holding public information meetings, and lending monitoring  equipment;  take informal actions such as field visits, reminder letters, telephone  calls, and notices of violation; and  take formal actions such as issuing citations, administrative orders  with or without penalties, civil and criminal cases, and emergency  orders.
Since 2009, according to an EPA document, the agency’s enforcement  strategy, in collaboration with states, has focused on identifying water  systems with a history of violations across multiple drinking water rules for  enforcement actions in states, territories, and tribal regions. To facilitate  this strategy, EPA’s headquarters staff are to review data on violations in  EPA’s SDWIS/Fed using an Enforcement Targeting Tool to identify  systems that merit action by states based on the seriousness of their  violations. EPA staff also are to use these data to determine whether water systems are achieving the agency’s national targets for compliance.  According to the EPA FY 2014-2018 Strategic Plan, the agency’s goal is  for 92 percent of water systems that provide drinking water year-round to  meet all applicable health-based drinking water standards by 2018.

	Available EPA Data Show Sample Results, Use of Corrosion Control, Violations, and Enforcement Actions Taken, but Data Are Not Complete

The available EPA data show sample results, use of corrosion control,  violations, and enforcement actions taken for the 68,000 water systems  from July 2011 to December 2016, but data are not complete. The  available data reported by states in EPA’s SDWIS/Fed database show at  least 2 percent of drinking water systems with sample results exceeding  the lead action level (from 2014 to 2016), and at least 10 percent of water  systems being out of compliance with the LCR (i.e., having at least one  reported violation) as of December 31, 2016. In addition, the state- reported data in SDWIS/Fed show 99 percent of enforcement actions  were taken by states, as expected because states generally have primary  responsibility for monitoring and enforcement of the SDWA requirements,  including the LCR. According to recent EPA assessments, the EPA OIG  report, and our January 2006 and June 2011 reports, some of the data in  the SDWIS/Fed database are not complete. Specifically, the data are  underreported, and therefore, data available in SDWIS/Fed likely  understate the number of sample results, violations, and enforcement  actions that actually occurred. In addition, the available EPA data on  water systems’ use of corrosion control are not complete. We also found  that because the LCR does not require states to submit certain data to  EPA, EPA’s SDWIS/Fed database does not contain data on key parts of  the rule, such as the presence or location of lead pipes—information that  water systems use to identify the locations from which they will draw tap  samples—or complete sample results for small water systems.

		Available EPA Data Show Sample Results, Violations, and Enforcement Actions Taken, but Data on Water Systems’ Use of Corrosion Control Are Not Complete

EPA’s SDWIS/Fed database contains descriptive data on, for example,  drinking water sample results, corrosion control, violations, and  enforcement actions, as required by the LCR.

			Sample Results

The available state-reported data in EPA’s SDWIS/Fed database show  that of the approximately 68,000 drinking water systems subject to the  LCR, at least 1,430 water systems (2 percent) had 90th percentile sample  results that exceeded the lead action level of 15 parts per billion from  2014 to 2016. EPA officials told us that they analyze these sample data  over a 3-year period rather than yearly to ensure that the majority of water  systems will have submitted sample results. These 1,430 systems serve  a population of approximately 3 million people. Of the 1,430 systems with  sample results exceeding the lead action level, 258 (18 percent) were  schools and day care centers with their own water supplies. As we  reported in January 2006, the LCR sample data in SDWIS/Fed were  underreported; recent EPA file reviews in selected states found that  sample data were not always reported to SDWIS/Fed; and a 2017 EPA  Office of Inspector General report indicated that sample data, specifically,  are potentially underreported. Appendix II provides additional  information about the available EPA data on sample results, reported  violations, and enforcement. In addition, some state regulators with whom  we interviewed in 2016 told us that homeowners and water systems may  take LCR samples improperly as we discuss later in this report. See  appendix III for these state regulators’ views on challenges associated  with waters systems’ implementation of the sample requirements under  the LCR.

			Use of Corrosion Control

The 2015 Report of the Lead and Copper Working Group to the National  Drinking Water Advisory Council noted the importance of corrosion  control because it is intended to achieve a water quality that minimizes  lead in water. Our analysis of the available state-reported data in EPA’s  SDWIS/Fed database on corrosion control from July 2011 to December  2016, shows that the database contained milestone data for 904 water  systems on the status of required actions about corrosion control  treatment after a sample result exceeded the lead action level, and 1,479  water systems were deemed to have corrosion already under control. In  addition, 34 water systems had milestone data in SDWIS/Fed for lead  service line replacement. For the approximately 68,000 water systems  subject to the LCR, 1,665 systems, had milestone data in SDWIS/Fed, or  about 2 percent of all water systems from July 2011 to December 2016.  According to EPA officials, when including milestone data available prior  to July 1, 2011, almost half of these systems have submitted the required  information regarding corrosion control milestones. Each water system  can have up to three types of milestone data (i.e., status of required  actions about corrosion control, systems deemed to have corrosion  already under control, and lead service line replacement) in SDWIS/Fed.  In June 2017, EPA officials said that all water systems subject to the LCR  are expected to have data on corrosion control in SDWIS/Fed.  However, these officials also said that states may not report the data to  SDWIS/Fed because of technical limitations with some state databases  and confusion among some state officials about how to report the data to  SDWIS/Fed.
Of the 983 large systems in the SDWIS/Fed database, milestone data  were available for 13 from July 2011 to December 2016, and 5 of those  systems had sample results exceeding the lead action level at some point  over that time period. Of the small and medium water systems for this  period that installed corrosion control treatment because their sample  results exceeded the lead action level, milestone data were available for  884 water systems.
We reported in January 2006 that EPA did not have complete milestone  data, including data on corrosion control. Specifically, we reported that  EPA had, at that time, collected milestone data for about 28 percent of  water systems. At the time of our 2006 report, EPA officials told us that in  most instances water systems should have data on corrosion control  treatment and that it was more likely the case that states were not  reporting the data rather than a case of noncompliance by water systems.  We recommended that EPA ensure that data on water systems’ test  results, corrective action milestones, and violations were current,  accurate, and complete. EPA generally agreed with our recommendation,  but has not fully implemented it. In 2016, EPA highlighted its response to  our January 2006 recommendation through such efforts as having staff  review SDWIS/Fed data for accuracy and timeliness and promoting  electronic reporting of the drinking water data states submit to  SDWIS/Fed.
In addition, EPA headquarters officials said in June 2017 that the agency  also worked with the states on reporting corrosion control data by  conducting webinars and in-person training that included information  about reporting data to SDWIS/Fed. For example, EPA conducted a  three-part series of LCR 101 webinars. EPA officials said that the  webinars in this series reached over 1,600 attendees with individual  webinars ranging from 227 to 551 viewers. EPA’s efforts regarding  training sound promising, but it may be too early to see the impact of  these efforts to work with states on reporting milestone data on corrosion  control to SDWIS/Fed. We continue to believe that EPA should take steps  to ensure that data, including those on milestones, are current, accurate,  and complete.

			Violations

The available data reported by states in EPA’s SDWIS/Fed database  show that of the approximately 68,000 drinking water systems subject to  the LCR, states reported that at least 6,567 water systems (about 10  percent) had at least one reported open violation of the LCR as of  December 2016. In total, these 6,567 water systems had a total of at  least 12,884 open violations as of December 2016. As we reported in  January 2006 and June 2011, the violations data in SDWIS/Fed were  underreported. Recent EPA file reviews in selected states found that  some violations data were not reported to SDWIS/Fed.
LCR violations fall into two categories: (1) monitoring and reporting and  (2) treatment technique. Monitoring and reporting violations generally  refer to a water system  failing to collect samples of drinking water from the tap, within the  distribution system, and from source water and  failing to report sample results to the states.
Treatment technique violations, which EPA considers to be health-based  violations, generally refer to a water system failing to take actions as  required after water samples exceed the federal lead action level.
The two most frequent violations were for not following requirements for  (1) monitoring and reporting routine follow-up and (2) initial tap  sampling. Taking samples from homes is the only way that water  systems, states, and ultimately EPA can obtain the indicators needed to  determine whether corrosion control treatment is needed or if corrosion  control treatments already installed are working, in addition to other  treatment technique requirements. The third most frequent violation was  lead consumer notification, which states or water systems are to do in  writing, about the results of the samples taken from homes or buildings  they occupy regardless of the presence of lead in the samples taken,  known as lead consumer notice violations. These notifications are to  provide consumers with information about their drinking water sample  results so that they can determine what actions to take to reduce their  exposure to lead if lead is present.
Of the approximately 68,000 water systems subject to the LCR,  approximately 7,000 schools and daycare centers make up about 10  percent. As their missions would indicate, these schools and daycare  centers provide drinking water to children, one of the populations most at- risk for adverse health effects from even small amounts of lead. Most of  the schools and daycare centers in the EPA data we analyzed were  classified as small water systems. EPA data show that schools and  daycare centers comprise about 10 percent (664 water systems) of the  6,567 water systems with at least one open violation of the LCR as of  December 31, 2016. Much like the overall group of water systems,  schools and daycare centers were most frequently violating the LCR  requirements for not (1) monitoring and reporting routine follow-up (2)  initial tap sampling, and (3) lead consumer notification.

			Enforcement

The available data reported by states in the SDWIS/Fed database show  reported information on the enforcement actions taken by states and EPA  against water systems that have violated requirements of the LCR. States  reported taking 98 percent of the enforcement actions from July 1, 2011,  to December 31, 2016, as would be expected given that states generally  have primary responsibility for enforcement of the LCR. In our January  2006 report, we found that because sample results, milestones, and  violations data for the LCR in SDWIS/Fed were underreported, it was  difficult to assess the adequacy of enforcement. We then found in June  2011 that the enforcement data, generally, in SDWIS/Fed were  incomplete. States and EPA can take a range of enforcement actions  both formal and informal. Formal enforcement actions include issuing  state administrative orders with or without penalties, filing state or federal  civil and criminal cases, and issuing emergency orders. Informal  enforcement actions include reminder notices of a violation, formal  notices of violation, public notification requests, and state referrals of  cases to EPA. According to a 2013 EPA compliance report, the number of  enforcement actions in a year does not necessarily correlate with the  number of violations that are reported in the same year. The two most  frequently reported enforcement actions taken were informalstate  violation/reminder notice, which inform water systems that the system has  open violations, and state public notification requested, in which the state  requests a copy of the information water systems sent to homeowners.  Most of the EPA officials we interviewed in the 10 regional offices told us that states primarily rely on informal actions and technical assistance and  training because they are the most effective means of getting water  systems to comply with regulations.

		EPA’s SDWIS/Fed Database Does Not Contain Data on the Presence of Lead Pipes and Complete Sample Results for Small Systems

The LCR does not require states to submit data to EPA’s SDWIS/Fed  database on (1) location of lead pipes or (2) all sample results for small  water systems. As a result, EPA does not have available data on either  the location of lead pipes or complete sample results for small water  systems. Water systems were required to collect information on the  presence of lead pipes when the LCR was promulgated in 1991, but there  is currently no requirement that this information be reported to EPA.  States are to submit to SDWIS/Fed on a quarterly basis all 90th percentile  sample results for large and medium water systems (including those that  exceed the lead action level). However, for small water systems, states  are required to submit data to SDWIS/Fed only for those 90th percentile  sample results that exceed the lead action level. As a result, sample  results for small water systems are not complete in SDWIS/Fed.

			Collection of Data on the Presence of Lead Pipes Was a 1991 LCR Requirement

When the LCR was promulgated in 1991, all drinking water systems were  required to collect information about the infrastructure that delivered water  to customers, including any known lead pipes and lead service lines. The  purpose of this effort, referred to as a materials evaluation, was to identify  locations that may have been particularly susceptible to high lead or  copper concentrations, which would become the pool of targeted sample  sites. Water systems that must replace their lead service lines under the  LCR also must report their materials evaluations to their respective  states. In addition, a 1980 EPA regulation required community water  systems to identify, among other things, whether lead from piping, solder,  caulking, interior lining of distribution mains, alloys, and home plumbing  was present in their distribution system and report this information to the  state. However, the LCR does not require states to report information on  known lead pipes and service lines to EPA’s SDWIS/Fed database. As  a result, the agency may not have information at the national level about  the lead infrastructure in the country.
In February 2016, in light of the events in Flint, Michigan, and other U.S.  cities, EPA asked states to collect information about the locations of lead  service lines and publish the information on local or state websites to  better inform the public. In a July 2016 letter to the Environmental Council  of States and the Association of State and Territorial Health Officials, EPA  noted that some states had successfully taken action to fulfill the request,  citing (1) water systems with online searchable databases that provide  information on lead service lines and (2) several states that were  requiring water systems to update their inventories of lead service lines.  In the letter, EPA also noted that many states identified challenges in  identifying lead service lines but that improving knowledge of lead service  lines is important to ensure that water systems are (1) collecting drinking  water samples from valid high-risk locations, as required under the LCR,  (2) managing the risks associated with disruption of lead service lines,  and (3) providing information to customers on how to assess and mitigate  risks posed by lead.
In written responses to EPA’s letter, most (37) of the 50 states (or  primacy agencies) indicated that they had fulfilled or intended to fulfill  EPA’s request to work with water systems to collect and make public  information about lead pipes. Four states indicated that they were  considering EPA’s request. However, 9 states indicated that they would  not or did not intend to fulfill EPA’s request because of challenges in  finding the historical documentation about lead pipes used to create  original sample plans or dedicating staff resources to do so. In addition, in  their responses to EPA’s letter, 13 states noted that the LCR does not  require states to maintain information about water systems’ lead pipes or  to provide the information to the public. EPA stated in its 2016 Lead and  Copper Rule Revisions White Paper that it was considering a proposal in  the upcoming revision to the LCR for water systems to update their  information on lead service lines and share the results of their “materials  evaluation.” In June 2017, EPA headquarters officials said that the  agency was evaluating all options outlined in its 2016 white paper as well  as recommendations related to lead pipes by other stakeholders.
According to EPA technical guidance on corrosion control, knowledge  about lead service lines is needed for studies of corrosion control  treatments. In addition, the National Drinking Water Advisory Council  stated in its 2015 final report that knowledge about the location of lead  service lines is essential to ensuring replacement and outreach to  customers who are most likely to have a lead service line. We reported in  March 2013 that, as the nation faces limited budgets and funding for  federal programs, the importance of targeting federal funds to  communities with the greatest need and spending funds efficiently  increases. For example, the Water Infrastructure Improvements for the  Nation Act, enacted in December 2016, directs EPA to establish a grant  program for reducing the lead in drinking water by, among other things,  replacing publicly owned lead service lines and assisting homeowners  with replacing the lead service lines on their property. In addition, EPA’s  2016 action plan identifies the reduction of lead risks as a priority area. By  requiring, in the upcoming revision of the LCR, that states report the  available information about lead pipes in its SDWIS/Fed (or in future  redesigns, such as SDWIS Prime) database, EPA and congressional  decision makers would have important information at the national level on  what is known about lead infrastructure in the country, thereby facilitating  the agency in its oversight role.

			Data on Drinking Water Sample Results for Small Systems

In a 2016 report on how science and technology can address drinking  water challenges, the President’s Council of Advisors on Science and  Technology stated that, sample data are essential for evaluating the  performance of a drinking water system. While the LCR requires small  water systems to report all 90th percentile sample results (i.e., results that  meet, fall below, and exceed the lead action level) to the states, it does  not require the states to report all of this information to EPA through the  SDWIS/Fed database. EPA headquarters officials said that the agency had not required states to submit the results for all small systems due to  the reporting burden on states. According to EPA’s reporting guidance for  states, however, reporting all sample results to the SDWIS/Fed database  for small water systems that do not exceed the lead action level is  encouraged and will be accepted. EPA officials told us that SDWIS/Fed  contained complete sample results for about 20,000 of the approximately  58,000 small water systems, or about 30 percent, of the 68,000 water  systems.
Officials we interviewed in 1 of EPA’s 10 regional offices said that the lack  of all 90th percentile sample results for small systems prevents the  agency from observing such systems in SDWIS/Fed. In June 2017, EPA  headquarters officials said that having all 90th percentile sample results  for small systems would give the agency a more complete national picture  of lead in drinking water. According to information on EPA’s website,  small water systems can face unique managerial, financial and  operational challenges in consistently providing drinking water that meets  EPA standards and requirements. In 2016, EPA’s Office of Inspector  General reported that small water systems are less likely to have the  technical, managerial, and financial capacity to conduct actions that  would ensure safe drinking water. The SDWA requires that EPA assist  states in ensuring that water systems acquire and maintain technical,  managerial, and financial capacity. In addition, the SDWA also authorizes  EPA to provide technical assistance to small public water systems to  enable such systems to achieve and maintain compliance with applicable  national primary drinking water regulations, including the LCR.
Because it does not have complete 90th percentile sample results on  small water systems, EPA does not have information on how such  systems are managing the reduction of lead in their drinking water. Small  systems represent the majority of water systems reporting samples that  have exceeded the lead action level, but states are not required to submit  all 90th percentile sample results for small systems in the SDWIS/Fed  database; this would require a revision to EPA’s regulations. By requiring,  in the upcoming LCR revision, that states report all 90th percentile  sample results for small systems in the SDWIS/Fed database, EPA would  have data to track the changes in lead levels over time among small  systems and would be better positioned to assist states in early  intervention for small water systems that are near the lead action level  where appropriate. In June 2017, EPA officials said that as states move  toward more modernized data flows using electronic reporting and  SDWIS Prime, the burden for reporting should be significantly lowered.

	EPA Uses Available Data to Monitor Compliance with the LCR, and Officials Said That They Have Increased the Use of Data in the Last Year

EPA officials said that they analyze data in their SDWIS/Fed database  and meet quarterly with state regulators to monitor compliance across all  drinking water rules and that, in the last year, in response to the events in  Flint, Michigan, they have increased their use of these data to monitor  compliance and address implementation of the LCR.
EPA applies its Enforcement Targeting Tool to the violations data  associated with the more than 90 drinking water contaminants regulated  under SDWA for the purpose of identifying systems that merit action by  states based on the seriousness of their violations. Specifically, the  Enforcement Targeting Tool assigns a score to each water system based  on, among other criteria, the types of violations and number of unresolved  violations over the previous 5-year period. The Enforcement Targeting  Tool assigns higher scores to health-based violations, such as treatment  technique violations. Water systems whose scores meet or exceed a  certain threshold are given higher enforcement priority for states (and  EPA, if necessary). EPA officials we interviewed in all 10 of the regional  offices said that they meet quarterly with state regulators to discuss the  results generated by the Enforcement Targeting Tool and generally  considered it to be a success. EPA headquarters officials agreed that the  Enforcement Targeting Tool was a success, even with the agency’s  challenges with the SDWIS/Fed data, including using data that are not  always complete and accurate. However, these officials also told us that  the Enforcement Targeting Tool was not designed for and therefore would  not be appropriate for monitoring compliance with any single regulation,  including the LCR. In April 2017, EPA headquarters officials told us that  as of January 2017, the Enforcement Targeting Tool includes information  on water systems’ most recent 90th percentile sample result and the  number of 90th percentile sample results exceeding the lead action level  over the previous 5-year time period.
EPA officials told us that they also conduct on-site file reviews of one to  two states each year. File reviews involve regional staff comparing  information on a sample of water systems in states’ databases with that in  SDWIS/Fed to identify any discrepancies and to assess states’  compliance decisions. EPA headquarters officials told us that the agency  developed a protocol for conducting file reviews and provided training on  this protocol for the regions. Staff have discretion on how to prioritize the  states in their regions. These file reviews cover all of the drinking water  regulations, which allows them to also periodically assess how well states  were implementing the LCR. According to EPA officials, in 2011, these  file reviews replaced the data verification audits, which were discontinued  in 2010; were designed to be generalizable to all water systems; and  involved contractors comprehensively reviewing states’ water system  inventories and violations and enforcement data and comparing them  against the information in SDWIS/Fed. Agency officials said that the  agency can no longer conduct these audits due to a lack of resources.
EPA headquarters officials told us that the agency had begun using  SDWIS/Fed data, in the last year, in response to the discovery of drinking  water contaminated with elevated levels of lead in Flint, Michigan, as part  of a two-pronged approach for reviewing states’ and water systems’  implementation of the LCR.
The first part of EPA’s approach was to identify all of the water  systems that reported sample results exceeding the federal action  level from 2013 to 2016. EPA officials said that they requested that  state officials provide updates on the status of each of the  approximately 2,400 water systems identified as reporting such  results. The purpose of this approach, according to EPA officials, was  to determine whether the states and water systems were properly  following the LCR’s requirements after a water system’s sample  results exceeded the federal lead action level. In addition, the  approach would allow, if necessary, states and EPA to have an  opportunity for early intervention. EPA officials said that previously  they had not systematically and uniformly analyzed all of the water  systems in their database with sample results that exceed the federal  lead action level or asked states, at any one time, to provide updates  on all of the water systems with sample results exceeding the action  level. Instead, EPA headquarters officials said that staff in the regional  offices generally had worked with individual states on individual cases  of water systems with sample results exceeding the action level as a  part of the agency’s routine oversight efforts. EPA headquarters  officials said that one outcome of their effort since the discovery in  Flint, Michigan, was “lessons learned” about the importance of  knowing where lead service lines are located and the need for states  to focus more attention on small water systems and schools with their  own water supplies. EPA officials we interviewed in some of the 10  regional offices said that meetings with state officials to discuss the  water systems that had exceeded the lead action level had been  beneficial because agency officials gained a better understanding of  how states understood and implemented the requirements of the  LCR. However, officials in 3 of the 10 regional offices said that they  would ask states to provide these updates less frequently because of  limited staff resources. EPA headquarters officials told us that an  additional outcome of this approach was insight, for EPA staff, into the  types of training state regulators may need about the implementation  of LCR requirements.
The second part of EPA’s approach, according to headquarters  officials, was to review state protocols and practices against all of the  requirements of the LCR to ensure that states were implementing the  rule, including protocols and procedures for using corrosion control  treatments. After reviewing state protocols and practices, EPA  requested that states take such actions as providing information on  their websites and documenting protocols and practices for greater  transparency. In addition, EPA staff in the 10 regional offices  conducted meetings with the state officials in their regions. Some of  these EPA officials also told us that the agency determined that  generally states were implementing the LCR appropriately. However,  EPA identified weaknesses among states and water systems with  identifying lead pipes and understanding the requirements for  installing and maintaining corrosion control. In response, EPA officials  told us that they updated guidance to states and water systems and  offered training and written technical guidance on implementing  corrosion control. Specifically, EPA officials said, they offered in- person training for state regulators in each of the 10 EPA regions on  implementing the corrosion control requirements of the LCR.

	Certain Factors May Contribute to Water Systems’ Noncompliance with the LCR

Through discussions with state regulators, we identified multiple factors  that may contribute to water systems’ noncompliance with the LCR. To  determine whether such factors were associated with a higher likelihood  of having a reported violation of the LCR, we conducted a statistical  analysis that calculated a system’s likelihood of a violation using selected  factors, such as the size of the population served and source water, and  currently available EPA data and found that incorporating multiple factors  in the analysis may help identify water systems at a higher likelihood of  violating the LCR.

		Certain Factors May Contribute to Water Systems’ Noncompliance with the LCR

Based on our analysis of transcripts of discussion groups, state regulators  representing 41 states and 1 territory identified 29 factors that may  contribute to water systems’ noncompliance with the LCR. We also  reviewed 31 studies and summarized the factors the authors identified.  Table 1 identifies the 10 factors state regulators most frequently  identified.
During our discussion groups, state regulators provided examples of how  these factors contributed to noncompliance with the rule. For example,  regulators in 37 states said that the size of the population served by water  systems may influence noncompliance with the LCR. Regulators in 28 of  the 37 states said that small systems are more likely to have drinking  water sample results that exceed the federal action level, to be in  noncompliance, or to face challenges that may contribute to  noncompliance. Regulators in 5 states explained that this may be  because small systems are generally less likely to have operators with  the knowledge to properly collect samples or manage corrosion control  treatment. Regulators in 28 states said that the required LCR process for  collecting drinking water samples to test for lead levels may contribute to  noncompliance. Regulators in 19 of these 28 states said that collecting  the required number of samples is a challenge for water systems that can  lead to noncompliance, because homeowners are frequently not willing to  collect samples or, if they agree to collect samples, often collect them  improperly. For example, homeowners may sample from an infrequently  used faucet (e.g., outside spigot) instead of the required drinking water  tap. Regulators in 20 states also described how the type of water system  can lead to noncompliance. For example, they said that water systems for  which water management and treatment are not the primary missions,  such as schools, mobile home parks, and other entities, have challenges  complying with the LCR.
These regulators also told us that the presence of multiple factors could,  together, contribute to violations of the LCR. For example, a regulator in  one state said that the presence of lead in the pipes, combined with  corrosive water, could lead to sample results that exceed the federal lead  action level for a water system. A 90th percentile sample result that  exceeds the lead action level is not by itself a violation. However, if the  same water system did not conduct the required corrosion control  treatment study for any reason, including because it lacked the financial  capacity to pay for the study, the system would be in violation of the  LCR.  Appendix III provides information on all of the factors that state  regulators in the 41 states and 1 territory identified in our discussions as  well as examples of how those factors, individually and together, may  contribute to violations of the LCR.
The 31 academic studies we reviewed associated certain factors with  elevated concentrations of lead in public drinking water, human exposure  to lead in drinking water, or violations of drinking water laws and  regulations. These studies identified the potential effects of, among other  factors,  the presence of lead in pipes or lead solder, within the water system’s  pipes; natural disturbances within drinking water pipes, such as stagnant or  soft water; operator actions to address lead in drinking water, such as the use of  corrosion control to decrease the presence of lead and the use of  chemical treatments to decrease the presence of other contaminants  that may increase the presence of lead; a water system’s capacity to address existing lead challenges, such  as the size of the population it serves and whether the system is  publically or privately owned; and  state and local policies designed to reduce drinking water violations or  human exposure to lead in water.

		Use of a Statistical Analysis Could Help Identify Systems at Higher Likelihood of LCR Violations

Our interviews with state regulators and review of academic studies  suggest that certain factors could indicate whether water systems are at a  higher likelihood for having a reported violation of the LCR. We selected  four system characteristics that were consistent with the factors reported  by state regulators in discussion groups and were available in  SDWIS/Fed to conduct a statistical analysis:  the population served by (or size of) the drinking water system, whether the drinking water system was publicly- or privately-owned, whether the drinking water system used groundwater or surface water whether the drinking water system was classified as a community  water system or a non-transient non-community water system.
We also included the factor of whether a system had sample results that  exceeded the lead action level. SDWIS/Fed does not include data on  such factors as the presence of lead service lines or technical,  managerial, and financial capacity.
We were unable to develop a nationwide statistical model referred to as a  logistic regression analysis. A logistic regression analysis can identify  factors that are associated with a violation and can estimate a drinking  water system’s likelihood of a violation based on these factors. We have  previously found that regression analysis can identify entities, regulated  by a federal program, that pose a higher likelihood for a particular  outcome. However, during our review of the reliability of EPA’s data on  violations, we could not verify that the limitations in the completeness of  the data identified in our June 2011 report had been sufficiently  addressed, nationwide. Specifically, in June 2011, we found that EPA  had not been able, among other things, to resume the comprehensive  and routine data verification audits that would provide it with current  information on the completeness of the data states provide to  SDWIS/Fed. As a result, in June 2011, we recommended that EPA  resume data verification audits to routinely evaluate the quality of  selected drinking water data on health-based and monitoring violations  that the states provide to EPA. These audits should also evaluate the  quality of data on the enforcement actions that states and other primacy  agencies have taken to correct violations. EPA partially agreed with our  recommendation and stated that it has found that data verification audits  provide valuable information on data completeness but did not commit to  conducting such audits beyond 2011. Instead, EPA said that until the next  generation of SDWIS (SDWIS Prime) is deployed, thus enabling the  agency to view compliance monitoring data and compliance  determinations directly, it will consider using data verification audits to  evaluate data quality. As of October 2016, EPA reported that it has not  conducted another data verification audit.
Because of the limitations of using SDWIS/Fed data to conduct a  nationwide analysis, we sought to use such data to conduct an analysis  for individual states to determine whether factors could predict the  likelihood that a water system would violate the LCR. As such, we used data from Ohio and Texas to examine the potential for developing a  statistical analysis to identify drinking water systems at higher likelihood  of having a reported violation. EPA found few or no discrepancies  between the LCR data in these state systems and in SDWIS/Fed for the  time period of our statistical analysis, 2013 to 2016. The results of our  analysis are not generalizable to other states.
To conduct an analysis for the two states, we developed a series of  logistic regression models for these states using (1) LCR violations data  for Ohio and Texas in SDWIS/Fed for 2013 and 2014 and (2) the four  factors for which data were available in SDWIS/Fed (size of the  population served, ownership, source water, and water system type). Our  models estimated the likelihood that a water system in those two states  would have a reported violation of the LCR based on these factors. We  found that water systems with certain factors had a higher likelihood of  having a reported violation of the LCR than water systems without those  factors. For example, in both states, a water system serving 100 people  was more likely to have a reported violation of the LCR than a water  system serving 1,000 people. In addition, systems with a previous sample  result that exceeded the lead action level were more likely to have a  reported violation of the LCR than systems without a previous sample  result that exceeded the lead action level.
We then tested the ability of our models to predict subsequent rates of  having reported violations. Specifically, we compared the estimates from  our models to violations that were actually reported in SDWIS/Fed in  2015 and 2016. We found that water systems that we identified as having  higher likelihoods of having a reported violation, based on our models,  had significantly higher rates of reported violations in 2015 and 2016. The  results of our analysis indicate that multiple factors, in addition to whether  a system had sample results that exceeded the lead action level, could be  used to predict water systems with a higher likelihood of having a  reported violation of the LCR.
Our analysis suggests that a statistical analysis of EPA data could be  used to identify water systems with a higher likelihood of having a  reported violation of the LCR. However, we identified two key limitations,  among others, based on the state of the data in SDWIS/Fed as of  December 2016. The first was the quality of the data for the purposes of  conducting an analysis. We could not be confident in the specific results  of a nationwide or, for some states, a state-specific analysis, because we  did not have the necessary assurances of the accuracy and  completeness of the SDWIS/Fed data, issues about which we previously  reported in January 2006 and June 2011. EPA headquarters officials  told us in June 2011 and April 2016 that their upcoming SDWIS/Fed  upgrade, SDWIS Prime, could give the agency direct access to state  data. Having complete and accurate data for all states or a nationally  representative sample of states would allow for a nationwide analysis.
The second limitation was that data are not available for many of the  factors identified by state regulators that may contribute to water systems’  noncompliance with the LCR. Our analysis was limited to those four  factors for which states submit data to EPA’s SDWIS/Fed. Because data  were unavailable for all potentially relevant factors, we were unable to  include information on the presence of lead pipes, lack of financial  capacity, and lack of technical capacity. EPA headquarters officials told  us that they were considering the development of indicators of capacity.  For example, these officials said that potential indicators suggesting a  drinking water system is challenged by capacity are the drinking water  system (1) not having raised rates in 20 years; (2) not having recently  used asset management; or (3) having experienced difficulty in retaining  trained operators. Data on the presence of lead pipes, financial capacity,  technical capacity, and other factors may allow for stronger logistic  regression models that more accurately identify water systems with a  higher likelihood for violations. Appendix V provides a technical  description of the statistical analysis we conducted.
According to EPA, the agency promulgated the LCR to protect public  health by minimizing the levels of lead in the drinking water supply.  EPA’s current approach for oversight of the LCR targets water systems  with sample results that exceed the lead action level. This approach is  reasonable because water systems that exceed the action level have a  known and documented lead exposure risk and are required under the  LCR to take actions that are considered health-based. This approach,  however, primarily incorporates one factorsample results that exceed the lead action leveland does not include the potential of having  reported violations across all of the requirements of the LCR. In addition,  EPA officials we interviewed in 3 of the 10 regional offices said that they  do not have the resources to sustain the agency’s current approach.  Under federal standards for internal control, management should identify,  analyze, and respond to risks related to achieving the defined objectives.  Although EPA may not have the resources to continue the use of its  current approach of following up on all sample results that exceed the  lead action level, our analysis illustrates that EPA collects data that,  where complete and accurate, could be incorporated into a risk-based  analysis. For example, such an analysis could be used in individual states  or geographical areas, while EPA is taking steps to improve its data and  implement SDWIS Prime. A statistical, risk-based analysis, whether it is  used for individual states or nationwide, may provide EPA with an  additional tool by which it may be able to efficiently target its limited  resources for oversight of water systems and meet its goal of reducing  the risk of lead exposure. By developing a statistical analysis that  incorporates multiple factors—including those currently in SDWIS/Fed  and others such as the presence of lead pipes and the use of corrosion  control—to identify water systems that might pose a higher likelihood for  violating the LCR once complete violations data are obtained such as  through SDWIS Prime, EPA could supplement its current efforts to better  target its oversight to the water systems that present a higher risk of  violating the LCR.

	Conclusions

EPA has taken several actions to increase transparency about lead  hazards, focus on water systems’ sample results over the federal lead  action level, and ensure a better understanding of how states and water  systems interpret and implement the LCR. However, most states are not  submitting data to the SDWIS/Fed database on water systems’ use of  corrosion control as required by the LCR. We continue to believe that  EPA should take actions to address our 2006 recommendation. Further,  by requiring that states report the available information about lead pipes  in EPA’s SDWIS/Fed database nationally, EPA and congressional  decision makers would have important information at the national level  about lead infrastructure, thereby facilitating the agency in its oversight  role.
The LCR does not require states to submit data to EPA’s SDWIS/Fed  database on all 90th percentile sample results for small water systems,  only to provide sample results that exceed the lead action level. EPA has  long acknowledged the challenges experienced by small water systems,  as evidenced in the data for samples that exceed the lead action level  and violations for taking samples as required and reporting sample  results. The upcoming revision of the LCR provides an opportunity for  EPA to require states to report all 90th percentile sample results for small  systems. By doing so, EPA would have data to track the changes in lead  levels over time among small systems and would be better positioned to  assist states in early intervention for small water systems that are near  the lead action level where appropriate. EPA also has an opportunity to  enhance its oversight of the LCR by using statistical analyses to analyze  those data that it currently collects and has determined to be complete.  With the LCR applying to about 68,000 water systems across the country  (or approximately 45 percent of all drinking water systems), it is important  to target limited resources to those water systems that pose the highest  likelihood of a violation. By developing a statistical analysis that  incorporates multiple factors—including those currently in SDWIS/Fed  and others such as the presence of lead pipes and the use of corrosion  control—to identify water systems that might pose a higher likelihood for  violating the LCR, EPA could supplement its current efforts and better  target its oversight to the water systems that present a higher likelihood of  violating the LCR, particularly when complete violations data are more  readily available through upgrades, such as SDWIS Prime.

	Recommendations for Executive Action

We are making the following three recommendations to EPA:
The Assistant Administrator for Water of EPA’s Office of Water should  require states to report available information about lead pipes to  EPA’s SDWIS/Fed (or a future redesign such as SDWIS Prime)  database, in its upcoming revision of the LCR; (Recommendation 1)
The Assistant Administrator for Water of EPA’s Office of Water should  require states to report all 90th percentile sample results for small  water systems to EPA’s SDWIS/Fed (or a future redesign such as  SDWIS Prime) database, in its upcoming revision of the LCR;  (Recommendation 2) and
The Assistant Administrator for Water of EPA’s Office of Water and  the Assistant Administrator of EPA’s Office of Enforcement and  Compliance Assurance should develop a statistical analysis that  incorporates multiple factors—including those currently in SDWIS/Fed  and others such as the presence of lead pipes and the use of  corrosion control—to identify water systems that might pose a higher  likelihood for violating the LCR once complete violations data are  obtained, such as through SDWIS Prime. (Recommendation 3)

	Agency Comments

We provided a draft of this report to EPA for review and comment. In its  written comments, reproduced in appendix VII, EPA stated that it  generally agreed with all three of our recommendations and the  importance of ensuring that the agency has the information needed to  ensure effective oversight of the drinking water programs. EPA also  provided technical comments which we incorporated, as appropriate.
EPA stated that our first two recommendations relate to the LCR  revisions: (1) report available information about lead pipes to EPA’s  database and (2) report all 90th percentile sample results for small water  systems to EPA’s SDWIS/Fed (or a future design such as SDWIS Prime).  As a result, EPA said that it would consider our recommendations along  with those of other stakeholders as the agency continues to support the  development of the proposed LCR for publication in the Federal Register  and follows the public review and comment process in 2018. In addition,  EPA said that the agency would continue to work with states to develop  SDWIS Prime and another electronic reporting tool, which will facilitate  electronic reporting, which in turn will increase data accuracy and  completeness.
In response to our third recommendation, EPA stated that it agrees with  the concept of our third recommendation to develop a national statistical  analysis that could identify water systems with a higher likelihood of  violating the LCR and that the agency previously tried to build a similar  tool but faced challenges due to variations between selected factors and  violations between states. EPA also said that while developing a national  tool would be a challenge, it would be beneficial to both the agency and  state primacy agencies.
As agreed with your offices, unless you publicly announce the contents of  this report earlier, we plan no further distribution until 30 days from the  report date. At that time, we will send copies of this report to the  appropriate congressional committees; the Administrator of the  Environmental Protection Agency, and other interested parties. In  addition, this report will be available at no charge on the GAO website at  http://www.gao.gov.
If you or your staff members have any questions about this report, please  contact me at (202) 512-3841 or gomezj@gao.gov. Contact points for our  Offices of Congressional Relations and Public Affairs may be found on  the last page of this report. Key contributors to this report are listed in  appendix VIII.

Appendix I: Objectives, Scope, and Methodology

This report examines the issue of elevated lead in drinking water and the  Environmental Protection Agency’s (EPA) use of compliance data for  oversight of the Lead and Copper Rule (LCR). Our objectives were to  examine (1) what the available EPA data show about compliance with  and enforcement of the LCR among water systems, including schools; (2)  how EPA uses these data to monitor compliance; and (3) factors, if any,  that may contribute to water systems’ noncompliance with the LCR. We  compared our evidence on EPA’s a use of these data for oversight of the  LCR to Standards for Internal Control in the Federal Government.  According to these standards, internal control is a process by an entity’s  oversight body, management, and other personnel that provides  reasonable assurance that the objectives of an entity will be achieved. An  effective internal control system increases the likelihood that an entity will  achieve its objectives. For this review, we used the standard for one of  the five components of internal controlrisk assessmentas criteria.
To examine what the EPA data show about reported compliance and  enforcement, we reviewed LCR data in EPA’s Safe Drinking Water  Information System (SDWIS/Fed) for the time period July 1, 2011, to  December 31, 2016. We chose this time period because it provided the  most recent history of available compliance data without a change in the  regulations at the time of our analysis. The LCR data contained  information on 67,581 active community water systems and non-transient  non-community water systems, including those that were schools or  daycare centers with their own water supply. Table 2 provides the water  systems, by type and size, included in our analysis. The LCR divides  water systems into three broad categories: small, medium, and large.  Size is a factor in determining the number of samples that must be  collected as well as the applicability and timing of some of the LCR  requirements.
We reviewed the available data on corrosion control, drinking water  sample results, violations of the requirements of the LCR, and state and  EPA enforcement actions. We also described the data by population  served/size, whether the water system was a school or daycare center,  and whether the water system was a community water system or a non- transient non-community water system, among other factors. We  analyzed data on sample results for a 3-year time period (from January  2014 to December 2016) and for a 5 1/2-year period (from July 2011 to  December 2016). EPA officials told us that they analyze sample data over  a 3-year period rather than yearly to ensure that the majority of water  systems will have submitted sample results. When presenting a  comparison of the sample data and the milestone data on corrosion  control, we used the 5 1/2-year period for both sets of data. For violations  data, we presented open violations as of December 2016. Violations are  considered open when the state has not determined that a water system  is in compliance with the specific requirement for which it received the  violation. Finally, we presented data on enforcement actions for a 5 1/2- year period (July 2011 through December 2016) to ensure that we  provided the most complete picture of the range of state and federal  actions taken and to avoid comparisons with the violations data.  According to a 2013 EPA compliance report, enforcement data, in any  one year, do not necessarily correlate with violations data. In addition,  the compliance report states that enforcement actions can be initiated  against violations that occurred in a previous year, one enforcement  action may address numerous violations at the same system; and it can  take several years for a system to return to compliance.
We reviewed the data available in the SDWIS/Fed database and the  compliance requirements in the LCR to evaluate those aspects of the  LCR for which implementation data were available. We interviewed  officials from EPA’s Office of Water and Office of Enforcement and  Compliance Assurance on the reliability, completeness and accuracy of  LCR data in SDWIS/Fed. In addition, we reviewed EPA data reliability  assessments, recent file reviews for selected states, a 2017 EPA OIG  report on the reliability of SDWIS/Fed sample data, data verification  reports and past GAO reports on the reliability of the data in SDWIS/Fed.  For example, EPA’s file reviews in some states found that not all  violations data were reported to SDWIS/Fed, which could lead to  undercounting. In addition, some state regulators told us that samples  may be collected incorrectly by some homeowners, which could lead to  inaccurate sample results. EPA has stated on its website that the agency  acknowledges challenges related to the data in SDWIS/Fed, specifically  underreporting of some data by states. GAO has also reported on EPA’s  challenges with SDWIS/Fed. Based on this, the compliance data in  SDWIS/Fed likely underreport the actual number of sample results that  exceed the lead action level, milestones, violations, and enforcement  actions, which we note in this report. Because of the incompleteness of  reported data on sample results, violations, and enforcement actions, and  because of concerns raised by state officials about sample data, we  found the data to be of undetermined reliability. For this review, we  describe the data about water systems’ compliance with the LCR  compliance and EPA’s enforcement actions as they are reported in  SDWIS/Fed for the purpose of providing a current assessment of EPA’s  use of the data.
To examine how EPA uses LCR data to monitor compliance we  conducted semistructured interviews with EPA officials. We used a  standard set of questions to interview officials in EPA’s headquarters and  in each of the 10 regional offices. Our standard set of open-ended  questions for EPA’s 10 regional offices asked about state actions  responding to EPA’s requests about, among other things, implementation  of the LCR, the use of SDWIS/Fed data, enforcement tools, and  compliance with the LCR among water systems and schools. We  conducted in-person interviews with officials responsible for monitoring  compliance in states within EPA regions 1, 2, 3, 4, 5, and 7. We identified  these regions based on a 2016 survey that estimated that these regions  have the highest number of lead service lines. We spoke with officials in  EPA regions 6, 8, 9, and 10 on the telephone. Table 3 provides a list of  the EPA regions and the states under the regulatory jurisdiction of those  regions. Our in-person interviews with officials in EPA regions 1through 5  and 7 were in offices located in Boston, Massachusetts; New York, New  York; Philadelphia, Pennsylvania; Atlanta, Georgia; Chicago, Illinois; and  Lenexa, Kansas, respectively. In these cities, we also met with state  primacy agencies and local water systems and other local officials, when  possible, to obtain examples of compliance and enforcement practices  and implementation challenges. Specifically, we met with state drinking  water officials in Massachusetts and Georgia. We met with officials  representing local water systems in Atlanta, Boston, New York, Chicago,  and Kansas City, Missouri. In total, we held 10 interviews with EPA staff  in the regional offices and seven interviews with state and local officials in  the cities we visited. We also reviewed EPA policy documents that  outlined the agency’s enforcement approach and documents related to  EPA’s request that states take certain actions following the events in Flint,  Michigan. Finally, we reviewed federal regulations; EPA guidance to  states and water systems on how to implement the LCR; the 2016 action  plan; information on what constitutes a violation of the LCR, action plans,  and other relevant documents.
To identify the factors that may influence water systems’ risk of  noncompliance with the LCR, we conducted a content analysis of  information provided by state regulators in discussion groups. To assess  whether selected factors available in SDWIS/Fed could be used to predict  reported violations, we conducted a statistical analysis of EPA data to  develop an illustrative model. We conducted a literature review to identify  factors associated with elevated concentrations of lead in public drinking  water, human exposure to lead in drinking water, or violations of drinking  water laws and regulations.
Discussion groups with state regulators. We conducted discussion  groups with a nonprobability sample of state drinking water regulators to  contribute to our understanding of the potential factors that may influence  noncompliance with the LCR. We invited regulators from all states and  territories to participate via email. In total, we conducted eight, 1-hour  discussion groups over the telephone in September and October 2016.  Regulators representing 41 states and 1 territory participated in these  discussion groups. Each discussion group had from 2 to 8 states or  territory, and each state or territory had a primary designated  spokesperson. During each discussion group, the GAO moderator asked  participants to list one or two factors that, in their experience, most  strongly influence a water system’s ability to comply with the LCR. Each  state provided a list of factors. The moderator then asked participants to  elaborate on how the factors reported could influence compliance. When  necessary, the moderator asked probing questions to further clarify  participants’ comments. Two or three analysts transcribed each session  and combined and reconciled notes to develop transcripts for each of the  discussion groups. We conducted a content analysis of the transcripts  from the eight discussion groups to identify the factors most frequently  reported by the participants in the groups. Two GAO analysts  independently classified each comment using qualitative analysis  software. The findings from these discussion groups may not be  generalizable to all state regulators. We provide a narrative description of  the results of our discussions with the state regulators in appendix III and  a technical description of the content analysis we conducted in appendix  IV.
Statistical analysis. We conducted a statistical analysis to illustrate  whether predictive modeling could be used to identify water systems with  a higher likelihood of a reported violation of the LCR. To conduct our  analysis, we used the same data from EPA’s SDWIS/Fed for systems  listed as active as of December 31, 2016 as mentioned above. We  selected two statesOhio and Texasbecause EPA’s file reviews  indicated that there were not significant discrepancies during the scope  and time period of our analysis, which focused on 2013 to 2016, in the  LCR data reported by these states to SDWIS/Fed. We reviewed EPA’s  2016 file reviews of data the states provide to SDWIS/Fed and  interviewed EPA and state officials for Texas and received written  responses to our questions from Ohio. For each of the sampled systems,  EPA reviewed state records to determine whether the state was correctly  identifying violations and reporting those violations to SDWIS/Fed.  Although, unlike EPA’s previous reviews, EPA’s 2016 file reviews are not  based on generalizable samples, they were conducted for a broad range  of drinking water systems in each of the states. Based on the results of  EPA’s reviews, we determined that these two states had sufficiently  reliable data for our purposes of illustrating a statistical approach. The  results of our analysis for these two states are not generalizable to other  states. Our analysis included three steps. We first conducted a bivariate  analysis to determine whether the following four factors correspond to  violations of the LCR for 2013 to 2014: (1) size of the population served;  (2) water source (groundwater or surface water); (3) ownership (public or  private); and (4) whether the system is a community water system or non- transient, non-community water system. We also included the factor of  whether sample results exceeded the lead action level. We then  developed a series of multivariate logistic regression models. Specifically,  multivariate logistic regression modeling is statistical method for analyzing  the potential influence of each individual factor on the likelihood of a  binary outcome (e.g., a violation) while simultaneously accounting for the  potential influence of the other factors. We selected this type of model  because it could account for the factors simultaneously. Lastly, to test  whether our models could be used to identify systems with a higher  likelihood of a future violation, we compared the values generated by our  models to actual violations reported in the SDWIS/Fed data in 2015 to  2016. We provide a technical description of the statistical analysis we  conducted, including determinations about the reliability of the data and  the limitations of the analysis, in appendix V.
Literature review. We reviewed studies concerning detection of lead in  drinking water and violation of drinking water regulations. These studies  were identified through searches by GAO research librarians for peer- reviewed materials in such databases as ProQuest, Scopus, Academic  One-File, and Web of Science. Librarians conducted searches using such  terms and phrases as lead and copper, water supply, drinking water, lead  exposure and lead poisoning alone and in combination with one another.  We also identified and reviewed relevant publications by trade groups,  think tanks, and other nongovernmental organization. We narrowed a  preliminary selection of results by reviewing abstracts and introductions,  where applicable. Based on that preliminary review, we determined that  31 sources fit within the scope of our engagement objectives. We then  reviewed the data and key findings of each of these 31 sources to  formulate and refine some hypotheses concerning violations of the LCR  and detection of lead in drinking water. The hypotheses were reviewed by  a GAO technical expert to ensure that they were sufficiently supported by  the cited corresponding research.

Appendix II: Additional Analysis of Available EPA Data on Reported Sample Results, Violations, and Enforcement for the Lead and Copper Rule

Environmental Protection Agency (EPA) data from July 1, 2011, to  December 31, 2016, can provide information on compliance by water  systems and enforcement by states and EPA regarding the Lead and  Copper Rule (LCR). This appendix provides additional information from  our analysis of what the EPA data in the agency’s Safe Drinking Water  Information System (SDWIS/Fed) show about compliance with and  enforcement of the LCR. The LCR requires water systems to monitor  drinking water at customer taps, and if lead levels are elevated, take  additional actions to control corrosion, inform the public, and in some  circumstances replace lead service lines under the systems’ control.  States generally have primary responsibility for monitoring and  enforcement of Safe Drinking Water Act requirements, including the  LCR. In this appendix, we provide additional results of our analysis of the  LCR data for (1) sample results, (2) violations, and (3) enforcement. We  reported in January 2006, that the LCR data, and in June 2011, the data  in SDWIS/Fed generally, were not accurate or complete. According to  EPA, some of the violations data are underreported. In addition, a 2017  EPA Office of Inspector General report indicated that sample data,  specifically, are potentially underreported. In addition, some state  regulators with whom we interviewed in 2016 told us that homeowners  and water systems may take LCR samples improperly as we discuss in  this report. See, also, appendix III for these state regulators’ views on  waters systems’ challenges with implementing the sample requirements  under the LCR. We present the data that were available in the  SDWIS/Fed database at the time of our review.

	Sample Results

The LCR requires that all water systems periodically obtain tap water  samples and for sample results that exceed an action level of 15 parts per  billion (ppb) to determine if corrosion control treatments are working  properly. EPA requires states to report (1) sample results for any water  system whose 90th percentile sample results exceed the federal action  level of 15 parts per billion; and, (2) sample results for large and medium  water systems even if the sample results do not exceed the lead action  level. From January 1, 2014, to December 31, 2016, there were  approximately 1,430 water systems reporting sample results over the lead  action level (see table 4), the majority of which were small water systems.  EPA officials told us that they analyze these sample data over a 3-year  period rather than yearly to ensure that the majority of water systems will  have submitted 90th percentile sample results.
The available EPA data show that almost all of the water systems (1,364,  or 95 percent) reporting sample results that exceeded the lead action  level from 2014 to 2016 were small and, together, served a population of  about 505,000. In contrast, the remaining 66 large and medium water  systems (5 percent) reporting sample results that exceeded the lead  action level from 2014 to 2016, together, served a population of 2.7  million. In addition, as shown in table 5, states within EPA’s regions 1 and  3 had the highest number of water systems that reported sample results  exceeding the lead action level. EPA headquarters officials we  interviewed provided possible explanations for why 90th percentile  sample results would be higher in these states. They said that there are  more lead service lines in the northeastern states, such as those within  regions 1 and 3. See table 5.
Table 6 provides information on the EPA data available for those water  systems that have results under the federal action level in 2016. As  previously mentioned, states are to report all 90th percentile sample  results for large and medium water systems to EPAthose that exceed  and fall below the federal action level.

	Violations

The 6,567 water systems (or 10 percent of all water systems) with  reported open violations as of December 2016, had at least one open  violation, based on our analysis of the available EPA data. Violations are  considered open when the state has not determined that a water system  is in compliance with the specific requirement for which it received the  violation. Table 7 provides an overview of the number of water systems  (including schools and day care centers) with violations of the LCR, by  size.
Table 8 provides a summary of the available EPA data on the violations  of the LCR among schools and daycare centers.

	Enforcement Actions and Outcomes

The available EPA data show that from July 1, 2011 to December 31,  2016, 99 percent of the 589,827enforcement actions and outcomes were  taken by states, as would be expected given that states generally have  primary responsibility for enforcement of the LCR . Enforcement actions  in SDWIS/Fed include actions taken and what we considered in our  analysis as outcomes, such as the receipt of information or a water  system having achieved compliance. The enforcement codes in  SDWIS/Fed that we defined as outcomes were: federal civil case  concluded, federal bilateral compliance agreement signed, federal public  notification received, federal no longer subject to rule, federal compliance  achieved, federal variance/exemption issued, state civil case concluded,  state bilateral compliance agreement signed, state public notification  received, state no longer subject to rule, state compliance achieved, and  state variance/exemption issued. Collectively, outcomes represented 43  percent (256,107) of the enforcement data in the database. Table 9  provides the number of enforcement actions and outcomes reported from  July 1, 2011, to December 31, 2016, at the federal and state levels. The  data show that states in regions 6 and 4 had the highest numbers of  enforcement actions and outcomes.
Table 10 shows the five most frequently reported enforcement actions  taken by states for LCR violations as they were reported in SDWIS/Fed  as of December 31, 2016.
In a 2009 document outlining its enforcement policy, EPA stated that the  policy would focus on “return to compliance.” According to this  document, “return to compliance” is intended to show the effectiveness of  the agency’s protection of public health. The available EPA data show  that from July 1, 2011, to December 31, 2016, 10,702 water systems had  at least one violation of some type and were returned to compliance (see  table 11). As table 11 illustrates, small systems were most frequently  designated as returned to compliance for monitoring and reporting  violations.

Appendix III: Key Factors State Regulators Identified That May Contribute to Noncompliance with the Lead and Copper Rule

State drinking water regulators who participated in discussion groups we  conducted identified 29 factors that may contribute to noncompliance with  the Lead and Copper Rule (LCR). Of these factors, the state regulators  most frequently mentioned size, technical capacity, and sample  collection, among other factors. State regulators mentioned other factors  less frequently, including requirements to comply with multiple drinking  water regulations and the number of water samples required to be  collected by the LCR as also contributing to noncompliance. Regulators in  12 states identified factors that they thought specifically helped water  systems comply with the LCR. We obtained this information from drinking  water state regulators representing 41 states and 1 territory through eight  discussion groups held in September and October 2016. The purpose of  the discussion groups was to develop an understanding of the factors that  may influence noncompliance with the LCR. We analyzed the transcripts  of those discussion groups using a content analysis software package.  For a detailed description of the methodology we used to conduct these  groups and analyze the content of these discussions, see appendix I and  appendix IV.

	State Regulators Identified 29 Factors That May Contribute to Noncompliance with the LCR

State regulators who participated in our discussion groups identified 29  factors that may contribute to water systems’ noncompliance with the  LCR. The LCR requires water systems to identify locations where lead  may be present and periodically obtain tap water samples from those  locations (of which single-family homes are the highest priority). When a  water system’s 90th percentile sample result for lead exceeds 15 parts  per billion, the system has exceeded the federal action level (also known  as an action level exceedance). Sample results that exceed the lead  action level do not by themselves constitute violations of the LCR.
Under the LCR, an action level exceedance requires the water system  and state to take additional steps. Those additional steps require that  small and medium water systems install or modify corrosion control  treatment and water systems of all sizes provide information (known as  public education) about the harmful effects of lead to consumers and  vulnerable populations (such as schools if the water system serves a  school and public health departments). Water systems are also required  to test and, if necessary, treat the source water. If, after installing  corrosion control and treating source water, a system continues to have  90th percentile sample results that exceed the lead action level, the LCR  requires the water system to begin replacing its lead service lines, if they  exist.
As part of our analysis, we grouped the 29 factors into seven broad  groups: (1) water system characteristics, (2) water system operations, (3)  characteristics of water, (4) sample procedures required to comply with  the LCR, (5) actions that states take to ensure water systems comply with  the LCR, (6) actions that the Environmental Protection Agency (EPA) can  take to assist with compliance, and (7) features of the LCR regulation.  Figure 4 provides these seven groups and the factors that fell into each  one.

	State Regulators Most Frequently Identified 10 Factors That May Contribute to Noncompliance with the LCR

State regulators we interviewed most frequently identified 10 factors that  may contribute to noncompliance of the LCR. Among those were size,  technical capacity of operators, and the collection of drinking water  samples. The 10 factors fell into the following broad groups: (1) water  system characteristics, (2) water system operations, (3) characteristics of  water, and (4) sample procedures. To identify the factors most frequently  identified by the state regulators as contributing to noncompliance, we  focused on those factors that were mentioned by regulators in at least 13  of the 41 states participating in the discussion groups (30 percent). Table  12 provides a description of each factor, the definition we used for our  analysis and the number of states in which officials mentioned the factor.
State regulators who participated in the discussion groups explained how  each of these factors may contribute to noncompliance. In most  instances, regulators also described what they observed as relationships  between factors and how, together, multiple factors could contribute to  noncompliance.
Size. Regulators in 37 states said that the size of the population  served by water systems may influence noncompliance with the LCR.  Regulators in 28 of the 37 states said that small systems (serving  populations of 3,300 and fewer) are more likely to have drinking water  sample results that exceed the federal action level, to be in  noncompliance, or face challenges that may lead to noncompliance.  Most of these regulators mentioned the size of a system and the  technical, managerial, or financial capacity of the system as factors  that, together, may influence noncompliance. For example,  regulators in 10 states said that small systems are more likely to  receive a violation because they are generally less likely to have  operators with the knowledge to properly collect samples (sample  collection) or manage corrosion control treatment (technical capacity)  or have the financial resources to pay for corrosion control treatment  or to hire professional help to do so (financial capacity). A regulator  from 1 state provided an example of a small water system in  noncompliance because it has a part-time operator with little training  on the rule and with other professional responsibilities, such as snow  removal and animal control, which prevent this operator from  providing drinking water test results to homeowners whose water was  tested within the required timeframe.
Technical capacity. Regulators in 33 states said that the technical  capacity of water systems may influence noncompliance with the  LCR. Regulators in 18 of the 33 states said that water systems that do  not have personnel with the knowledge to adequately operate a  system or who understand the LCR are less likely to have the skill set  to interpret and implement the LCR appropriately.
Sample collection. Regulators in 28 states said if systems fail to  collect drinking water samples, improperly collect samples, or have  other problems with collecting samples they may be out of compliance  with the LCR. For example, regulators in 9 of these 28 states said that  some water systems struggle to find enough homeowners willing to  collect water samples for testing and regulators in 3 states said that  this may cause the systems to collect samples from taps that are not  used for drinking water, contrary to the LCR. In addition, regulators in  14 states said that even when systems are able to find homeowners  willing to collect drinking water samples, the homeowners themselves  may collect the samples improperly. A regulator from 1 state provided  an example of a homeowner who was out of town for the weekend  and upon return collected a water sample from tap water that sat  stagnant for 4 days, which is problematic because the sample taken  should be representative of everyday use. Sample results that exceed  the lead action level do not by themselves constitute violations of the  LCR.
Financial capacity. Regulators in 28 states said that water systems  that do not have sufficient financial resources will experience  challenges complying with the LCR, including paying for chemicals  and professional help needed to install corrosion control treatment.  For example, a regulator in 1 state said that a system without  adequate financial resources may not be able to pay for the required,  and often costly, corrosion control study.
Presence of lead. Regulators in 23 states said that the presence of  lead in the pipes may influence noncompliance with the LCR.  Regulators in 9 of the 23 states said that the presence of lead in pipes  increases the likelihood that drinking water samples will exceed the  federal action level; and require a system to perform additional  actions. Regulators in 11 of the 23 states specifically said that a water  system with old infrastructure is more likely have lead service lines.  Regulators in 9 states identified the presence of lead service lines and  managerial capacity as factors that may work together. These  regulators said that water systems that maintain good records of the  materials in their distribution systems know about the presence of  lead service lines and may be better able to collect drinking water  samples from the appropriate locations.
Managerial capacity. Regulators in 24 states said that the  managerial capacity of water systems may influence noncompliance  with the LCR. Regulators in 16 of the 24 states said that water  systems that do not have effective management structures and  practices will have problems keeping up with the rule requirements  and deadlines. Regulators in 6 states explained that proper data and  records management help systems comply with the LCR.
Water chemistry. Regulators in 23 states said that the chemistry of  the water may influence noncompliance with the LCR. Regulators in  20 of the 23 states said that having corrosive water increases the  likelihood of samples that exceed the action level—which is not a  violation—and will require a system to perform additional actions. For  example, if these systems do not install corrosion control or manage it  properly—for example, because the operator does not understand  water chemistry—the system will get a violation, according to  regulators in 6 states.
Corrosion control. Regulators in 16 states said that the corrosion  control may influence noncompliance with the LCR. Specifically,  regulators in 15 of the 16 states said that water systems that have  installed corrosion control treatment are more likely to be in  compliance with the LCR because corrosion control is the primary  method used to prevent lead from entering drinking water. A regulator  from 1 state said that despite the corrosive water that exists in that  state, water systems are not getting samples that exceed the action  level and are staying in compliance because they have corrosion  control installed. Regulators also discussed how the size of the  system and corrosion control, together, can influence compliance.  Regulators in 5 states said that large water systems are generally in  compliance with the LCR because the rule requires them to install  corrosion control treatment.
Type. Regulators in 18 states said that the type of water system may  influence noncompliance with the LCR. Regulators in 14 of the 18  states said schools and daycare facilities with their own water  supplies experience challenges in complying with the LCR, and  regulators in 6 states explained that it is because their primary  mission is not water delivery and management. A regulator in 1 state  said that they had a school submit improper samples because school  officials collected samples after the summer break during which the  faucets had not been used for 6 weeks, thus not being representative  of normal drinking water use. Sample results that exceed the lead  action level do not by themselves constitute violations of the LCR.
Source. Regulators in 14 states said that the source of drinking water  may influence noncompliance and offered a range of opinions as to  how corrosive or non-corrosive groundwater may influence actions.  State regulators frequently discussed source water, water chemistry,  and corrosion control as factors that presented themselves together.  State regulators in 4 states said that systems using ground water can  more easily comply with the LCR because ground water is non- corrosive compared to surface water. In contrast, regulators in 4  states said that the ground water in other parts of the country is more  corrosive. However, regulators in 5 states said that systems with  corrosive water sources are still able to comply when they properly  install and manage corrosion control treatment.

	State Regulators Identified Additional Factors That May Influence Noncompliance

State regulators who participated in our discussion groups identified  additional factors that may contribute to water systems’ noncompliance  with the LCR, though less frequently. These regulators cited factors such  as compliance with multiple drinking water rules, the number of samples  that systems are required to collect under the LCR, and the complexity of  the LCR. Table 13 describes each factor less frequently mentioned as  contributing to noncompliance, the definition of the factor, and the number  of states in which officials mentioned the factor. Some of these factors are  more specific attributes that may impact of some the 10 factors that were  most frequently identified by state regulators. For example, regulators told  us about several aspects of water (age, stability, and flow) that may  impact water chemistry.
The regulators participating in our discussion groups provided examples  of these less frequently mentioned factors, below:
Simultaneous compliance. Regulators in nine states said that  systems that have to simultaneously comply with multiple drinking  water regulations can lead to noncompliance with the LCR and  regulators in three of the nine states explained that this is because  changes to water treatment to address one problem can create  additional problems. For example, regulators in five states said that  systems that have to comply with a rule aimed at reducing drinking  water exposure to disinfection byproducts may require a reduction in  the pH level of their water, and this, in turn, may affect the  effectiveness of their control corrosion treatment. Much like other  factors, this causes samples results to exceed the federal action level  which subjects the water system to additional rule requirements.
Lead and Copper Rule. Regulators in seven states said that aspects  of the LCR may influence noncompliance. Regulators in two of the  seven states said that the LCR does not require states to routinely  approve material surveys or for systems to update these surveys  periodically, which can prevent water systems from knowing if they  are collecting samples from high-risk sites. In addition, regulators in  four states said that the LCR allows too much time for systems to  complete requirements, such as the installation of corrosion control  treatment and the issuance of public education notices to consumers.  For example, a regulator in one state provided an example of a  system that started the process of installing corrosion control.  However, the system stopped the treatment installment because, as  allowed by the LCR, the system sampled the water again and did not  exceed the action level. Regulators in three of the states also said that  the LCR does not allow state regulators to invalidate samples that  they know were taken using poor practices at the sample site.,
EPA guidance. Regulators in seven states said that EPA’s guidance  may contribute to noncompliance, and according to regulators in four  states, this is because the guidance may not be clear which may  cause states and water systems to incorrectly implement the LCR. For  example, regulators in three states said that EPA guidance on sample  procedures and public education was confusing for states and water  systems because it is not clear about the timeframes that systems  should adhere to when repeating the collection of water samples or  providing public education to ensure that they conduct these actions  properly and in accordance with the LCR.
Regulators also identified several additional factors that could lead to  noncompliance or to 90th percentile sample results over the action level  and thus additional requirements for water systems to implement, which  could increase the chances of a violation. For example, regulators  mentioned that the ownership of a water system could be a factor and  provided the example of privately-owned, small water systems with less  knowledgeable or available operators. Regulators also said that the age  of the water can interfere with corrosion control and that some systems  buying treated water are not doing any treatment themselves. Finally,  regulators in two states said that water systems that are geographically  isolated may not be able to access alternative water sources if their  existing source water is corrosive or to attract operators with the skills to  implement the LCR.

	Regulators in 12 States Identified Operator Engagement, State Assistance and Local Support as Factors Helping Water Systems Comply with the LCR

Regulators in 12 states specifically identified factors that they thought  helped water systems comply with the LCR (see table 14). Regulators in  7 states said that assistance from the states helps water systems comply  with the LCR by providing systems with information about the  requirements of the rule, training or technical assistance including using  state rural water associations. Regulators in 4 different states said that  the engagement of the water system with the state regulatory office—for  example, through training—places the system in a better position to  implement the LCR because they are gaining an understanding of the  requirements. Further, regulators in 1 state said that support from state  and local decision makers provides water system managers with the tools  they need to implement the rule appropriately.

Appendix IV: Content Analysis of the Transcripts of Discussion Groups on Factors That May Contribute to Noncompliance with the Lead and Copper Rule

We conducted eight discussion groups with drinking water regulators  representing 41 states and 1 territory to develop an understanding of the  potential factors that may influence noncompliance with the Lead and  Copper Rule (LCR). These were hour-long discussions conducted over  the telephone. We held these discussion groups in September and  October 2016. From two to eight states participated in each discussion  group and each state had a primary designated spokesperson. For more  information about our overall methodology, see appendix I.

	Discussion Groups

In each discussion group, the moderator asked two questions. First, the  moderator asked participants to list one or two factors that most influence  a water system’s ability to comply with the LCR. Each state provided a list  of factors. After all of the states responded, the moderator noted the  factors provided by the group participants and asked for consensus on  the list of factors reported. Second, the moderator asked participants to  elaborate on how the factors reported could influence compliance. When  necessary, the moderator asked probing questions to further clarify  participants’ comments. Two or three analysts transcribed each session  and combined and reconciled notes to develop transcripts for each of the  discussion groups.

	Identifying and Defining Factors

Using the factors that participants mentioned in each discussion group,  we compiled an initial aggregate list of factors. We reviewed the initial list  to determine if certain factors were closely related and could be  combined. To check for completeness, we reviewed the transcripts and  noted factors that participants repeatedly mentioned throughout the  discussion groups but that were missing from the current list, and we  added them to the list. This allowed us to delete some factors and  incorporate them into other factors under which we determined they could  reasonably fit. For example, we determined that “water chemistry” and  “water corrosivity” were too closely related to be separate factors, so we  combined them. Our goal was to develop a list of complete, distinct and  mutually exclusive factors based on the information that participants  shared in the discussion groups.
We took additional steps to ensure that we identified significant factors by  conducting a word frequency count in all of the discussion group  transcripts using a content analysis software package. We grouped  similar wordsfor example, “system,” “systems and systems’” so that  they were counted together. We determined that the top 11 words  identified by the frequency count—which were mentioned 100 times or  more—represented factors that we already had in our list. We also  determined that the top 50 words identified by the frequency count — which were mentioned 32 times or more—represented factors that were  already on our list.
To have a clear and consistent understanding of each factor for  classification purposes, we defined each factor using information from the  LCR, other federal regulations, Environmental Protection Agency  guidance to states and water systems, and published GAO reports. Using  the factors and their definitions, we developed a guide to use in the  classification process.
To identify broad themes when classifying comments in the transcripts,  we developed groups under which the factors could reasonably fit. We  took steps to make every group distinct and mutually exclusive and to  ensure that every factor fell into its associated category. For example, we  determined the factors “system size,” “system type,” and “financial  capacity of system,” could naturally be grouped under “water system  characteristics”. Over the course of several meetings, four analysts  reviewed and finalized the factors and their associated groups. We  agreed on a final list of 29 factors, which included issues like “system  size,” “corrosion control,” and “water source.” The 29 factors were placed  under seven groups, including “water system characteristics,” “water  system operations,” and “characteristics of water.” For a detailed  discussion of these factors, see appendix III.

	Analysis

To analyze the content of the discussion groups, using a content analysis  software package, two analysts independently classified each comment in  the transcripts into the factors we defined, and one analyst analyzed the  classification to identify the factors that were most frequently reported.  During the classification process, the analysts classified each participant’s  individual statements in the transcripts separately. For the purposes of  analysis, we defined an individual comment to be a statement made by a  single individual. Across the eight discussion groups, there were a total of  225 such comments. Some comments were brief and covered a single  issue while others were extensive and covered multiple issues. The  analysts applied multiple classifications if statements covered a range of  factors. For example, a statement made by a specific drinking water  regulator could have been classified as relating to the source of the water  and the size of the system. The analysts only coded statements made in  response to the moderators’ questions. The analysts did not code  statements that did not discuss factors or directly answer the moderators’  questions. After independently coding the transcripts, we used software to  run an intercoder reliability report. The two analysts met on three  occasions to compare and discuss the coding results. In instances where  the analysts applied different codes to the same statement, they  discussed their reasoning and reached agreement on which codes were  the most appropriate. Each analyst then updated the database to reflect  the agreements reached.
We also used software to identify the factors most frequently reported by  the participants. We determined these by identifying the number of states  that reported each factor (regardless of how many times a factor was  mentioned) because this approach presented the number of states that  agreed on the validity of each factor as contributing to noncompliance. To  do this, we used software to cross-tabulate the factors that were classified  with the states that participated in the discussion groups. During the  classification process, we classified each participant’s statements as (1)  the state the participant represented and (2) the factors that the statement  covered. For example, an individual statement could have been classified  as “Texas” and “water source.” Thus, for each factor, the cross tabulation  showed which states made statements that were classified into that  factor. We also ran a cross tabulation of the seven broad groups (under  which the factors were grouped) and the states that reported each group.  We identified the factors that were most frequently reported by focusing  on those that were reported by at least 30 percent of the states, and  reported this information in the report.

Appendix V: Statistical Analysis to Identify Water Systems with a Higher Likelihood for LCR Violations

To identify any factors that may contribute to noncompliance with the  Lead and Copper Rule (LCR), we conducted discussion groups with a  nonprobability sample of state drinking water regulators representing 41  states and 1 territory. We conducted a literature review of 31 academic  studies about the detection of lead in drinking water and violations of  drinking water regulations to corroborate our findings from the discussion  groups. Our discussion groups with state regulators and review of  academic studies suggested that certain factors could indicate whether  water systems are at a higher likelihood for violating the LCR. To  determine whether data on these factors could be used to predict LCR  violations, we developed a series of statistical models, specifically  multivariate logistic regression models. To conduct our analysis, we used  the available data from the Environmental Protection Agency’s (EPA)  Safe Drinking Water Information System (SDWIS/Fed) database for  community water systems and non-transient non-community water  systems active as of December 31, 2016, in 2 states, Ohio and Texas.  We selected these states because recent EPA file reviews did not find  significant discrepancies in the LCR violations data reported to  SDWIS/Fed. In both states, we found that water systems with some  factors were significantly more likely to violate the LCR than systems  without those factors. Furthermore, we found that our models, which were  based on data for 2013 and 2014, could predict systems with a higher  likelihood of a violation in 2015 and 2016 significantly better than chance.  Our analysis is limited because it is based on 2 states and thus, not  generalizable to other states. It is also based on a subset of the relevant  factors that might predict LCR violations and therefore is illustrative of the  potential for statistical models to predict violations rather than the  definitive model of violations.

	Analytical Approach

In a review of previous GAO reports and peer-reviewed literature, we  found that statistical models have been used to predict the risk of a  violation for regulated entities. For example, in October 2016, we reported  on the potential for statistical models to identify motor carriers that posed  a high risk of a highway crash. In addition, several peer-reviewed studies  have developed statistical models to predict the likelihood of drinking  water systems violating Safe Drinking Water Act requirements. Based on  this prior research, we considered predictive modeling as a potential  approach to identify drinking water systems with a higher likelihood of  violating the LCR. The specific steps we took to conduct this analysis are  described below.

	Available Data

To conduct our analysis, we used the available data on community water  systems and non-transient non-community water systems active in  SDWIS/Fed as of December 31, 2016. We analyzed data for drinking  water systems that serve more than 25 people, which is EPA’s size  threshold for a public drinking water system. EPA’s SDWIS/Fed database  contains descriptive data on water systems (e.g., size, location, and water  source), drinking water sample results, violations, and enforcement  actions, as required by the LCR. Generally, states with primary  enforcement responsibility initiate enforcement actions against water  systems that do not comply with the LCR and other drinking water  regulations. The LCR requires states to submit certain data to EPA’s  SDWIS/Fed database on a quarterly basis.

	Selected Factors

In our discussion groups with state regulators and review of academic  studies and peer-reviewed literature, we identified 29 factors that may  influence a drinking water system’s noncompliance with the LCR (see  apps. I and III). We examined the SDWIS/Fed database to identify data  elements that might represent these factors. Of the factors that were  consistent with findings reported in the literature we reviewed and  reported by state regulators in discussion groups, we selected four that  were available in SDWIS/Fed to conduct a statistical analysis:  the population served by (or size of) the drinking water system, whether the drinking water system was publicly or privately owned, whether the drinking water system used groundwater or surface water  as a source, and whether the drinking water system was classified as a community  water system or a non-transient non-community water system.
In addition, EPA’s current approach for targeting oversight of the LCR is  to identify water systems with sample results that exceed the lead action  level. Therefore, we also included the factor of whether the system had  sample results exceeding the lead action level.

	Data Reliability

We conducted steps to assess the reliability, completeness, and accuracy  of the LCR compliance data in SDWIS/Fed for the purpose of conducting  this analysis. We determined that data in SDWIS/Fed were not sufficiently  reliable to conduct a nationwide statistical model of LCR violations. We  could not verify that the limitations in the completeness of the data  identified in our June 2011 report had been sufficiently addressed  nationwide. Thus, we could not be assured that the LCR violations data  submitted to SDWIS/Fed were sufficiently complete, accurate, or  comparable across the states. Instead, we used the data in SDWIS/Fed  to conduct an illustrative analysis for two statesOhio and Texas. We  selected these states because EPA’s recent reviews of the completeness  and accuracy of LCR data reported by these states did not find significant  discrepancies in LCR violations data. We examined EPA’s reviews and  either obtained written responses to questions or interviewed EPA and  state officials to determine that these two states had sufficiently reliable  data for this purpose. EPA’s reviews were not based on statistically  representative samples of drinking water systems in these states.  Therefore, we cannot conclude definitively that the agency has addressed  problems with the completeness and accuracy of violations data.  However, we found that these states had sufficiently reliable data for the  purpose of testing the feasibility of statistical modeling to predict drinking  water systems with a higher likelihood of violating the LCR.

	Bivariate Analysis

Before developing the logistic regression model, we analyzed whether or  not each water system in the two states violated the LCR from January 1,  2013, to December 31, 2014, with respect to each of the four selected  factors. We conducted this analysis with cross tabulations and graphical  analysis. In cross tabulations, each of the factors we examined was  significantly associated with LCR violations, although the nature of these  relationships varied between the states. In general, in both states,  privately owned systems were more likely to violate the LCR than  publically-owned systems, community water systems were less likely to  violate the LCR than non-community non-transient water systems; and  systems that had sample results exceeding the lead action level were  more likely to violate the LCR than those that had not. In Ohio, water  systems that used groundwater were more likely to violate the LCR than  surface water systems, whereas, in Texas, water systems that used  purchased groundwater were less likely to violate the LCR.
In graphical analysis, we found that the likelihood of a violation was  related to the size of the population served by the water system. For  example, in Ohio, grouped data plots displayed a negative, linear  relationship between the likelihood of a violation and the number of  people served by a system. In Texas, these plots displayed a negative,  linear relationship for systems serving 3,300 people or fewer and a  positive linear relationship for systems serving larger populations. The  threshold of 3,300 people is the threshold that the LCR uses to  distinguish small systems.
The results of these cross tabulations were illustrative of factors  influencing violations, but they provided only a partial assessment of the  relationship between LCR violations and the factors. This is because the  cross tabulations compared LCR violations with each factor individually  without accounting for the influence of the other factors. For example, we  found in our analysis that while systems that had exceeded the lead  action level were more likely to have a violation than systems that had not  exceeded this level, such systems are also more likely to serve smaller  populations. Because these factors are related, bivariate cross  tabulations cannot distinguish between their respective influences on the  likelihood that a system violated the LCR. To account for multiple factors  simultaneously, we developed logistic regression models.

	Logistic Regression Models

We developed a series of logistic regression models for each state to  determine whether factors collectively could identify the likelihood that a  water system would violate the LCR. A logistic regression model is an  equation, which is developed through statistical procedures, that  estimates the individual association of each factor with the likelihood of a  violation, while simultaneously accounting for the association between  each of the other factors and the likelihood of a violation. It provides a  basis for combining multiple variables to predict outcomes and is more  inclusive than the bi-variate analysis described in the previous section. ) for groups of systems ranked by the size of  the population served. whether the drinking water system was classified as a community  water system or a non-transient non-community water system.
We also included whether the system had a sample result exceeding the  lead action level during the monitoring period from January 1, 2012, to  December 31, 2014. We specified different logistic regression models for  each state because of differences in the distributions of the data between  the states. For example, in Ohio, nearly all non-transient, non-community  water systems used ground water as their primary source water, which  made it difficult to disentangle the unique effects of community water  systems from those of ground water systems. Therefore, we collapsed  non-community water systems using groundwater and non-community  water systems not using ground water into a single group for analysis. In  Texas, the relationship between the likelihood of a violation and size of  the population served shifted as the number of people served by a  system reached 3,300. Therefore, we added a term to our logistic  regression equation for Texas that allowed us to account for the  difference in the relationship between size and the likelihood of a violation  or systems below the 3,300 threshold and systems above that threshold.
To test the adequacy of these models, we verified that our data contained  a sufficient number of systems with each combination of characteristics,  that it adequately fit the data based on the chi-squared goodness-of-fit  tests, and that estimated effects were generally stable across multiple  model specifications. We tested for nonlinear relationships between the  likelihood of a violation and the size of the population served by a system  and we transformed the variable accordingly. We also tested for  interaction effects between the categorical system characteristics and the  size of the population served by the system. In each state, we tested  several model specifications to identify the combinations and  transformations of variables that best met these conditions.
Among the models we tested, the best-fitting model for Ohio included  explanatory variables for whether the system had a sample result  exceeding the lead action level, whether the system was privately owned,  the size of the population served by the system, whether the system was  a non-community water system using groundwater, and whether the  system was a non-community water system not using ground water. This  model also included an interaction term between community water  systems using groundwater and the size of the population served by the  system. The data for this model included 1,849 systems, of which 137  violated the LCR in the compliance periods that began in 2013 and 2014  and 1,712 of which did not. The model had an adequate fit to the data  based on chi-squared and Hosmer-Lemeshow goodness-of-fit tests, and  it had a good accuracy in predicting LCR violations in 2013 or 2014 based  on the area under the Receiver Operator Characteristic (ROC) curve.
The best-fitting model for Texas included explanatory variables for  whether the system had a sample result exceeding the lead action level;  whether the system was privately owned; whether the system was a  community water system; whether the system used groundwater as a  source of water; the size of the population served by the system; and a  linear spline term, which accounted for a different relationship between  system size and the likelihood of a violation for systems served more than  3,300 people. Data for this model included 5,395 systems, of which 2,321  violated the LCR in the compliance periods that began in 2013 and 2014  and 3,074 of which did not. The model had an adequate fit to the data  based on the chi-squared and Hosmer-Lemeshow goodness–of-fit tests,  and a moderate accuracy in predicting violations in 2013-14 based on the  area under the ROC curve.
In each model, we found that certain factors were consistently associated  with violations. For example, in both states, water systems that had  reported a previous sample result exceeding the lead action level were  significantly more likely to violate the LCR. The size of the population  served was a statistically significant predictor of a violation in both states  but in different ways. In Ohio, water systems were less likely to violate the  LCR as their size increased. In Texas, water systems were less likely to  violate the LCR as the size of their population increased to 3,300 but  were more likely to violate the LCR as the size of the population over  3,300 increased. These patterns persisted in our models even after  accounting for whether the system was privately owned, whether the  system was a community water system and whether the system used  groundwater as a source of water. These three other factors were also  associated with the likelihood of a violation in some of our models, but the  direction, magnitude and the significance of these associations were not  consistent This could be the result of strong associations among the  factors, which would make it difficult for the models to precisely estimate  their association with violations. Because this imprecision, we do not  report the associations between these three factors and the likelihood of a  violation. Since the purpose of these models was to identify drinking  water systems with a higher likelihood of a violation, rather than to  estimate the influence of specific factors on the likelihood of a violation,  we focus on the predictive accuracy of these models as described in the  next section.

	Predictive Accuracy

To test whether our models could be used to predict water systems with a  higher likelihood of a future violation, we compared the predicted violation  results from our models to actual violations that were reported in  SDWIS/Fed for 2015 and 2016. Our models, which were based on data  from 2013 and 2014, predicted subsequent violations in 2015 and 2016  significantly better than chance. Systems with higher average predicted  probabilities of violations had higher observed rates of violations in the  subsequent year than systems with lower predicted probabilities, and this  difference was statistically significant. To make this determination, we  took three steps. First, we used our models to estimate the likelihood that  each system violated the LCR in 2013 or 2014 based on the factors  identified in the logistic regression models. Second, we divided the water  systems into five equally sized groups, referred to as quintiles, based on  their estimated likelihood of a violation. Third, we compared the  percentage of systems that violated the LCR in 2015 or 2016 across each  of these five groups.
We found that systems in the highest likelihood group, based on our  models of 2013 to 2014 data, had significantly higher violation rates in  2015 and 2016 as compared to systems in the lowest likelihood group.  This result was true for each of the two states and for each of the models  that we tested in those states. The tests of predictive accuracy in 2015  and 2016 for the best-fitting models in each state are shown in table 15.  For example, in Ohio, 7.9 percent of systems in the fifth quintilethe  group with the highest violation likelihood scoresviolated the LCR in  2015 or 2016 as compared to 2.4 percent of those in the first quintile, the  group with the lowest likelihood scores. Similarly in Texas, 43.1 percent of  systems with the highest likelihood scores violated the LCR in 2015 or  2016 as compared to 21.4 percent of those in the lowest likelihood group.

	Discussion

Based on our illustrative analysis, we found that statistical models could  be used to predict water systems with a higher likelihood of violating the  LCR. However, our analysis was subject to certain limitations. First, our  models used only data for factors available in SDWIS/Fed. They did not  include other factors that might be important to predicting violations, such  as the treatment technique used by a drinking water system; the  presence of lead pipes in a community; or the technical, financial, and  managerial capacity of a drinking water system. Second, our models were  limited to the two states for which we could obtain reasonable assurances  of data reliability, and therefore, the results are not generalizable to other  states. While we found some commonalities in the factors that may  contribute to violations between the states, we also found several  differences between them, suggesting that specific factors may influence  violations differently in different states. Finally, while we took several  steps to confirm that the data for these states were sufficiently reliable for  the purpose of developing illustrative regression models to predict  violations, we cannot be confident that the inaccuracies and  incompleteness that we and EPA identified in June 2011 have been  addressed nationwide. Reliable and sufficient data for additional states  would increase the external validity of future analysis. Additionally, data  for additional explanatory variables mentioned in the literature and by  state regulatorssuch as the presence of lead service lines and the  technical, financial, and managerial capacity of a systemwould allow for  a more fully specified model with the potential to increase the explanatory  power of those models. Taken together, reliable data for a broader  sample and a fuller range of explanatory variables could potentially  improve the usefulness of models predicting LCR violations.

Appendix VI: EPA Guidance to the Public on Addressing Lead in Drinking Water

The Environmental Protection Agency (EPA) provides information on its  website for the public on lead hazards in drinking water. EPA’s website  includes, among other documents, a February 2005 fact sheet for the  public entitled Is There Lead in My Drinking Water? (see fig. 5).

Appendix VII: Comments from the Environmental Protection Agency

Appendix VIII: GAO Contact and Staff Acknowledgments

	GAO Contact

	Staff Acknowledgments

In addition to the individual named above, Diane Raynes (Assistant  Director); Jennifer Beddor; David Blanding, Jr.; Mark Braza; Richard P.  Johnson; Tahra Nichols; Jerry Sandau, and Karen Villafana made key  contributions to this report. In addition, Sarah Gilliland, Lindsay Juarez,  Maureen Lackner, Dan Royer, and Kiki Theodoropoulos made important  contributions to this report.

Related GAO Products

Water Infrastructure: Information on Selected Midsize and Large Cities  with Declining Populations. GAO-16-785. Washington, D.C.: September  15, 2016.
Water Infrastructure: EPA and USDA Are Helping Small Water Utilities  with Asset Management; Opportunities Exist to Better Track Results.  GAO-16-237. Washington, D.C.: January, 27, 2016.
Environmental Health: EPA Has Made Substantial Progress but Could  Improve Processes for Considering Children’s Health. GAO-13-254.  Washington, D.C.: August 12, 2013.
Drinking Water: Unreliable State Data Limit EPA’s Ability to Target  Enforcement Priorities and Communicate Water Systems’ Performance.  GAO-11-381. Washington, D.C.: June 17, 2011.
Environmental Health: High-level Strategy and Leadership Needed to  Continue Progress toward Protecting Children from Environmental  Threats. GAO-10-205. Washington, D.C.: January 28, 2010.
Drinking Water: The District of Columbia and Communities Nationwide  Face Serious Challenges in Their Efforts to Safeguard Water Supplies.  GAO-08-687T. Washington, D.C.: April 15, 2008.
Drinking Water: EPA Should Strengthen Ongoing Efforts to Ensure That  Consumers Are Protected from Lead Contamination. GAO-06-148.  Washington, D.C.: January 4, 2006.
District of Columbia’s Drinking Water: Agencies Have Improved  Coordination, but Key Challenges Remain in Protecting the Public from  Elevated Lead Levels. GAO-05-344. Washington, D.C.: March 31, 2005.
Drinking Water: Safeguarding the District of Columbia’s Supplies and  Applying Lessons Learned to Other Systems. GAO-04-974T.  Washington, D.C.: July 22, 2004.

Output:
Why GAO Did This Study

Drinking water contaminated with lead in Flint, Michigan, renewed awareness of the danger lead poses to the nation's drinking water supply. Lead exposure through drinking water is caused primarily by the corrosion of plumbing materials, such as pipes, that carry water from a water system to pipes in homes. EPA set national standards to reduce lead in drinking water with the LCR, which applies to all water systems providing drinking water to most of the U.S. population, except places where people do not remain for long, such as campgrounds. States generally have primary responsibility for enforcing the LCR, and data help EPA monitor states' and systems' compliance with the LCR.
GAO was asked to review the issue of elevated lead in drinking water. Among other objectives, this report examines (1) what available EPA data show about LCR compliance among water systems and (2) factors that may contribute to LCR noncompliance. GAO analyzed EPA data on violations and enforcement of the LCR from July 1, 2011, through December 31, 2016, interviewed EPA officials in headquarters and the 10 regional offices; conducted a statistical analysis of the likelihood of reported LCR violations; and held discussion groups with a nonprobability sample of regulators representing 41 states.

What GAO Found

Available Environmental Protection Agency (EPA) data, reported by states, show that of the approximately 68,000 drinking water systems subject to the Lead and Copper Rule (LCR), at least 10 percent had at least one open violation of the rule; however these and other data are not complete. When the LCR was promulgated in 1991, all water systems were required to collect information about the infrastructure delivering water to customers, including lead pipes (see figure). However, because the LCR does not require states to submit information on known lead pipes to EPA, the agency does not have national-level information about lead infrastructure. After the events in Flint, Michigan, and other cities, EPA asked states to collect information on the locations of lead pipes, and all but nine, which had such difficulties as finding historical documentation, indicated a plan or intent to fulfill the request. According to EPA guidance, knowledge of lead pipes is needed for studies of corrosion control. GAO reported in March 2013 that with limited funding for federal programs, the need to target such funds efficiently increases. By EPA requiring states to report data on lead pipes, key decision makers would have information about the nation's lead infrastructure.
Through discussion groups, state regulators identified 29 factors that may contribute to water systems' noncompliance with the LCR. In conducting a statistical analysis using EPA data on selected factors, such as the size of the population served and type of source water, GAO found that such factors were associated with a higher likelihood of water systems having reported violations of the LCR. EPA's current approach to oversight of the LCR targets water systems with sample results that exceed the lead action level. While this approach is reasonable because such water systems have a documented lead exposure risk, EPA officials in 3 of the 10 regional offices told GAO that it is not sustainable over time because of limited resources. Under federal standards for internal control, management should identify, analyze, and respond to risks related to achieving the defined objectives. By developing a statistical analysis that incorporates multiple factors to identify water systems that might pose a higher likelihood for having reported violations of the LCR to supplement its current approach, EPA could better target its oversight to such water systems.

What GAO Recommends

GAO is making three recommendations, including for EPA to require states to report data on lead pipes and develop a statistical analysis on the likelihood of LCR violations to supplement its current oversight. EPA agreed with GAO's recommendations.