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Article

Environmental Assessment and Monitoring of Heavy Metals in New York City Potable Water Systems: Case Study at Medgar Evers College, Correlation Analysis, and Public Health Impacts

1
Department of Chemistry and Environmental Science, Medgar Evers College, City University of New York, Brooklyn, NY 11225, USA
2
Graduate Center, Earth and Environmental Science and Chemistry Divisions, City University of New York, Manhattan, NY 10016, USA
3
Department of Geosciences, Institute of Computational and Data Sciences, Earth and Environmental Science Institute, PSU EnvironMentors, Penn State University, State College, PA 16803, USA
4
Department of Earth, Environment and Equity, Howard University, Washington, DC 20059, USA
5
Department of Geography, Penn State University, State College, PA 16803, USA
6
Institute for Energy and the Environment (IEE), Penn State University, State College, PA 168036, USA
7
Kingsborough Community College, City University of New York, Brooklyn, NY 11235, USA
8
Environmental Engineering Department, Central State University, Wilberforce, OH 45384, USA
9
Learning, Design and Technology Program, Department of Learning and Performance Systems, College of Education, Penn State University, State College, PA 16803, USA
10
Department of Chemistry, Earth Sciences and Environmental Sciences, Bronx Community College, City University of New York, Bronx, NY 10453, USA
*
Author to whom correspondence should be addressed.
Water 2023, 15(24), 4233; https://doi.org/10.3390/w15244233
Submission received: 12 October 2023 / Revised: 27 November 2023 / Accepted: 27 November 2023 / Published: 8 December 2023
(This article belongs to the Section Water Quality and Contamination)

Abstract

:
Reinforced by this study, New York City has one of the cleanest water systems in the world. Medgar Evers College (MEC) serves 7000 students/1050 faculty/staff. Given that: (1) students/faculty/staff spend 20–30% of their daily time there; (2) potable water sources must abide by the EPA’s maximum contamination levels (MCLs); and (3) a detrimental impact on human health arises from violations to EPA’s water quality mandates, we quantified the abundance of 27 heavy metals (96 samples, N = 3) using MEC as a case study. Water was collected from all potable water sources, following EPA protocols for sample-matrix preparation, collection, and wet-chemical analysis. Linear polyethylene containers/caps were used to prevent sample contamination while the water samples were spiked with HNO3 (aq) for preservation. Heavy metal concentrations were quantified using New Jersey’s Meadowlands Environmental Research Institute’s Inductively Coupled Plasma-Mass Spectrometer (ICP-MS, Agilent 7700X) in no gas, and He flow modes. Ninety-five percent of sample concentration relative standard deviations (RSDs) reveal four distinct regions: (1) where one mode is more precise than the other, and sample data exhibit very good to excellent precision, RSD ≤ 15%; (2) despite being at low concentrations, measurements exhibit good to excellent precision, RSD ≤ 20%; (3) species concentrations ≥0.1 ppb very good to excellent precision is shown, RSD ≤ 15%; and (4) species at concentrations ≤ 10−3 ppb display fair to very poor precision, RSD ≥ 30%. All heavy metals complied with their respective EPA MCLs (except Fe). Over 90% of Fe sample concentrations were enhanced by up to about 30×. Two samples exhibited [Pb] = 13.7 (No gas mode, RSD = 3.32%) and 14.8 ppb (He mode, RSD = 0.75%), which is close to the EPA Primary MCL, 15 ppb. Based on EPA/WHO end-member equations, we estimate a 1/103 to 1/108 chance of cancer attainment from long-term exposure to the range of concentrations of heavy metals measured in this study.

1. Introduction

Maintaining optimally adequate, accessible, and high-quality water is pivotal for all societies around the world, as potable water is essential for life and good health [1,2]. As defined by the World Health Organization (WHO), safe drinking water should not cause any significant adverse health impacts during one’s lifetime. All domestic purposes (e.g., personal hygiene, food preparation, and drinking) require safe drinking water. Despite significant technological advances in providing safe water [3,4,5,6,7], there is still a great need to improve the efforts to provide sufficient, manageable, and good-quality water; globally, this issue is an ongoing problem [7,8,9,10,11]. This ongoing struggle to ensure access to safe water for all highlights the complex and multifaceted nature of the issue. It involves technological and scientific advancements and economic, social, and political dimensions. Meeting this global need for safe and accessible water remains a critical challenge that requires continued dedication and collaboration among governments, organizations, researchers, and communities worldwide.
Approximately 63 million Americans may have been exposed to contaminated water since 2006. The Environmental Protection Agency (EPA) reported that 680,000 water quality and monitoring breaches occurred in the last ten years. News21 investigated these violations and came to the same conclusion (https://troubledwater.news21.com/millions-consumed-potentially-unsafe-water-in-the-last-10-years/ (accessed on 5 September 2023)). The EPA’s Safe Drinking Water Information System (SDWIS) contains information on such violations for public water systems (i.e., the Community Water System (CWS), the Non-Transient Non-Community Water System (NTNCWS), and the Transient Non-Community Water System (TNCWS)). Since 1993, thirteen years prior, the number of people across America who could have been potentially exposed to unsafe drinking water was undoubtedly much higher (https://ofmpub.epa.gov/apex/sfdw/f?p=108:200:::NO::: (accessed on 5 September 2023)). Moreover, the Louisiana Department of Health (LDOH) confirmed the presence of the brain-eating amoeba, Naegleria fowleri, to Schriever Water System and town officials (https://nypost.com/2017/06/30/potentially-deadly-amoeba-found-in-louisiana-water-system/ (accessed on 10 October 2022)). For two months, the Schriever Water System treated their water with elevated chlorine concentrations to eliminate all amoeba bacteria and their biofilm. The Schriever Water System and the Centers for Disease Control and Prevention issued recommendations to homeowners, emphasizing the importance of preventing water exposure to the nasal passages. Additionally, they advised flushing water faucets and hoses for an extended duration prior to usage, pending confirmation of the absence of the amoeba through rigorous testing. The initiation of the Flint Water Crisis on 25 April 2014, marked by the transition from the Detroit Water and Sewerage Department to the Flint River as the city’s water source, was exacerbated by inadequacies in transition management. The 100,000-resident community was exposed to exorbitantly high levels of toxins, especially lead (up to 13,200 ppb in many cases, as compared to the EPA Federal limit of 15 ppb) and potentially Legionella; this crisis may be linked to the deaths of 10 people from Legionnaire’s Disease, which affected an additional 77 persons. This tragic event will undoubtedly have longstanding health impacts due to the widespread exposure to contaminated water. The Flint Water Crisis was quickly addressed due to the help of pioneering work led by Dr. Mona Hanna-Attisha at the Hurley Medical Center [12,13,14,15,16,17,18,19,20]. The latest round of Department of Education (DOE) water testing revealed that 83% of city schools have at least one fixture with lead levels exceeding the EPA lead (Pb) concentration limit of 15 ppb (https://nypost.com/2017/04/28/over-80-percent-of-city-schools-have-high-lead-levels-in-water/ (accessed on 12 June 2022)). One source cited Pb levels reaching 15,000 ppb. The National Resource Defense Council’s 2017 Report (https://www.nrdc.org/resources/threats-tap-widespread-violations-water-infrastructure (accessed on 12 January 2023), https://www.nrdc.org/sites/default/files/threats-on-tap-water-infrastructure-protections-report.pdf (accessed on 25 October 2023), https://www.nrdc.org/sites/default/files/whats-in-your-water-flint-beyond-report.pdf (accessed on 6 July 2023)) found that toxins potentially harmful to human health were found in tap water in every state in the US. The report revealed that 80,000 reported violations (e.g., exceeding health-based standards, failing to properly test water for contaminants, and failing to report contamination to state authorities or the public) of the Safe Drinking Water Act by community water systems. Eighteen thousand of these systems served 77 million people in 2015. Moreover, 12,000 infractions were health-based violations from 5000 community water systems that serve over 27 million persons. These violations are primarily caused by the need to repair and expand America’s drinking water infrastructure, whereby the EPA and the American Water Works Association (AWWA) estimate the associated cost to be about 400 billion to 1 trillion USD, respectively (https://www.epa.gov/sites/production/files/2015-07/documents/epa816r13006.pdf (accessed on 10 October 2023); https://www.awwa.org/Portals/0/files/legreg/documents/BuriedNoLonger.pdf (accessed on 10 October 2023)). Water contamination issues persist despite increasing improvements in US water quality (https://scholar.google.com/scholar?hl=en&as_sdt=0%2C47&q=us+water+contamination+&btnG= (accessed on 10 October 2023); https://scholar.google.com/scholar?hl=en&as_sdt=0%2C47&q=us+water+contamination+2023&btnG= (accessed on 10 October 2023); https://scholar.google.com/scholar?hl=en&as_sdt=0%2C47&q=improvements+in+us+water+quality+&btnG= (accessed on 10 October 2023)).
“New York City is fortunate to have some of the cleanest and best-tasting drinking water of any city in the world”, (NYC 2015 Drinking Water Supply and Quality Report). “New York City has world-class drinking water”, (NYC 2016/2017/2018/2019/2020/2021 Drinking Water Supply and Quality Report). This extraordinary feat would not be possible without consistent and ample monetary investments toward NYC’s water infrastructure. The most recent projects include: (1) the Croton Water Filtration Plant, (2) City Water Tunnel No. 3, (3) Water Main Replacements, (4) the Delaware Bypass Tunnel, (5) Gilboa Dam, (6) the Catskill-Delaware Interconnection, (7) the Rehabilitation of Shaft 3—City Water Tunnel No. 1, (8) the Staten Island Siphon, and (9) an Aqueduct bypass tunnel under the Hudson River—all totaling over 3 billion USD. The NYC 2021 Water Quality Report provided updates on these projects and shows that New York City’s drinking water continued to be of excellent quality in 2021. This commitment to providing exceptional drinking water enhances New York City residents’ daily lives. It sets an inspiring example for other cities striving to achieve similar water quality and reliability levels. It underscores the importance of proactive investment in water infrastructure to ensure the well-being and health of urban populations while promoting sustainability and resilience in the face of evolving challenges.
The Water Supply System for New York City (NYC) provides 1.1 billion gallons of safe drinking water to nine million residents every day. This drinking water is sourced from a surface supply of 19 different reservoirs and three controlled lakes spanning about 2000 square miles. Each plant has its own treatment modus operandi. The high-quality surface water coming from the Catskills/Delaware region operates under a Filtration Avoidance Determination (FAD). Water from this supply is first treated with chlorine and then ultraviolet (UV) radiation to kill germs, prevent bacterial growth on pipes, and inactivate potentially harmful microorganisms. This treatment plant is designed to treat two billion gallons of water per day. The Croton Water Filtration Plant can treat up to 290 million gallons per day. At this plant, the water is treated via coagulation, dissolved air floatation, filtration, and disinfection. Before water is distributed in NYC, the Department of Environmental Protection (DEP) adds food-grade phosphoric acid, sodium hydroxide, and low-level fluoride. Fluoride is added to water to prevent cavities, sodium hydroxide regulates water pH and decreases pipe corrosion, and food-grade phosphoric acid reduces metal release by forming a layer on the pipes. The New York State Department of Health (NYSDOH) and the United States Environmental Protection Agency (EPA) prescribe regulations that limit contaminant (e.g., microbial contaminants, inorganic contaminants, organic chemicals, radioactive substances, pesticides, and herbicides) levels in public water systems. While the NYSDOH and EPA enforce regulations, the DEP is responsible for testing and monitoring water in the distribution system, the reservoir and feeder systems, and wells. The DEP has 1000 water quality sampling stations located throughout NYC, where the water is regularly tested. In 2016, the DEP conducted over 407,500 analyses on more than 36,300 samples from the distribution system. To support filtration avoidance determination (FAD) and optimal water quality, the DEP conducted over 231,700 analyses on about 15,200 samples and took approximately 1.5 million robotic monitoring measurements from the surface supply reservoirs. In 2021, scientists from the Department of Environmental Protection (DEP) conducted a massive sampling effort that included 44,300 samples from New York City’s watershed and reservoir systems, as well as samples from approximately 1000 street-side monitoring stations strategically placed throughout the city. These samples were subjected to a thorough evaluation, totaling 556,000 exams, at the DEP’s four water quality facilities. Furthermore, state-of-the-art robotic monitoring stations deployed in New York City reservoirs performed an additional 2.9 million tests, demonstrating the DEP’s commitment to reliably supplying water of high quality to the city. During the same year, approximately 88% of the water supply came from the Catskill/Delaware region, with the remaining 12% sourced from Croton [21].
Within the context of the exemplary work done by the EPA and its nationwide agencies, there is still a need for additional water quality monitoring and assessment analyses, especially when tap water is received from sources that can be tens to hundreds of miles away (e.g., the Queens, Croton, and Catskill/Delaware supplies, Figure 1). We conducted a water audit of 27 heavy metals from Medgar Evers College’s potable water sources and select sites throughout NYC at New Jersey’s Meadowlands Environmental Research Institute’s Earth and Environmental Science Department, using Inductively Coupled Plasma-Mass Spectrometer (ICP-MS) analysis.

2. Experimental Methodology

2.1. Water Sample Preparation and Storage

Water samples were prepared, collected, and preserved using Eaton et al. (2005)’s standard methods for examining potable water and wastewater [22]. Samples were collected using linear polyethylene bottles and polyethylene caps from potable water sources (e.g., faucets and fountains) at Medgar Evers College’s Bedford Building, Carroll Building, S-Building, and AB1-Building (Table S1a,b in Supplementary Materials). For the determination of trace metals, contamination and loss are of prime concern. Dust in the laboratory environment, impurities in reagents, and impurities on laboratory apparatus, which samples may encounter, are all sources of potential contamination. For liquid samples, containers can introduce either positive or negative errors in the measurement of trace metals by (a) contributing contaminants through leaching or surface desorption and (b) by depleting concentrations through adsorption. Thus, the collection and treatment of the sample before analysis requires particular attention. Therefore, the linear polyethylene sample bottles were thoroughly washed with detergent and tap water; rinsed with 1:1 nitric acid, tap water, and 1:1 nitric acid; and finally washed twice with deionized water. The samples were preserved immediately after sampling via acidification with concentrated nitric acid to pH < 2. We used 2.0 mL of a concentrated high-purity HNO3/L sample. Acidified samples were stored in a refrigerator at approximately 4 °C to prevent changes in volume due to evaporation. Under these conditions, samples with metal concentrations of several mg/L (e.g., surface water) are stable for up to 6 months. For mg/L metal levels (like tap water), we analyzed all samples within 72 h.

2.2. ICP-MS Analysis

The heavy metal concentrations of the water samples were determined using ICP-MS (Agilent 7700X, Palo Alto, CA, USA). The 27 selected major and trace elements measured in this study are Be, Na, Mg, Al, K, Ca, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Se, Sr, Mo, Ag, Cd, Sb, Ba, Hg, Pb, Th, and U. Helium collision mode with kinetic energy discrimination (KED) effectively removed the multiple polyatomic interferences in the ICP-MS. Li, Sc, Ge, Y, In, Tb, and Bi were used as internal standards for calibration. These elements were carefully selected for their known properties and lack of interference with the analytes of interest. By measuring the internal standards alongside the sample, any variations in the analytical process such as instrument drift or sample matrix effects could be corrected, thus enhancing the accuracy and reliability of the results. The recovery rates of the quality control (QC) samples were 90–110%. Measurements were performed both with and without He carrier gas. These QC samples checked the entire analytical process, from sample preparation to instrument analysis, ensuring that no significant errors or biases were introduced. The QC samples were prepared from SCP Science stock standard solutions, ranging from 5 to 500 µg/mL initial concentrations (Catalog #s: AQ0-090-411, AQ0-090-421, 140-051-341, 600-144-303, 600-144-305). The EPA’s 200.8 method recommends no gas mode for the drinking water and gas (He or H2) mode for the surface or wastewater analysis. In general, recent ICP-MS models simultaneously run two modes for increased accuracy, independent of the sample matrix. Gas mode generally provides simple, consistent, and reliable analysis of unknown samples, with no new interferences and no reactive signal loss for analytes. This meticulous approach to heavy metal analysis is crucial for environmental monitoring and ensuring the safety of water resources.

2.3. Sample Quality Control

In analytical chemistry, the precise measurement of heavy metal concentrations using techniques like ICP-MS, calibration, and quality control are paramount for ensuring the accuracy and reliability of results. The calibration standards, verified initially by the Quality Control (QC) samples, were prepared from the dilution of the standard stock solutions representing each element. The CAL solutions were used to calibrate the instrument response concerning the analyte concentration. The QC samples/Internal Standards were made by adding a pure analyte to a sample, extract, or standard solution in known amount(s), which was then used to measure the relative responses of the additional method analytes that were components of the same sample or solution. The internal standard was required to be an analyte that was not a sample component. A Quality Control Sample (QCS) is a solution of method analytes of known concentrations, which is used to fortify an aliquot of LRB or sample matrix. The QCS is obtained from a source external to the laboratory and different from the source of calibration standards. It is used to check either laboratory or instrument performance. The calibration blank is a zero-standard volume of reagent water acidified with the same acid matrix as in the calibration standards and which calibrates the ICP instrument. Negative heavy metal concentrations expressed in the ICP-MS measurements were based on a calibration curve, which correlates to N/A RSD values. The N/A RSD values, typically associated with these measurements, were used to gauge the precision and reliability of the analytical method, with lower RSD values indicating higher precision. Seven replicate samples were measured for each sample taken at a given location.

3. Results and Discussion

Medgar Evers College (MEC), located in Crown Heights, Brooklyn, New York, is a senior/4-year undergraduate, non-residential, predominantly Black Minority-serving institution within the City University of New York (CUNY) system. It was founded in 1969 and named after Medgar Wiley Evers, an African American leader assassinated on 12 June 1963 for his courageous role during the Civil Rights Movement. The student population is ~6500, and the total number of employees is ~1035. MEC offers classes year-round, including during winter (the period during the 6-week interim between the fall and spring semesters) and summer.
As high heavy-metal concentrations in potable water have adverse effects on human health [1,2,23], water samples were collected from potable water sources (faucets and fountains) at MEC’s Bedford Building, Carroll Building, S-Building, and AB1-Building (Table S1a,b). Heavy metal concentrations of 27 elements (Be, Na, Mg, Al, K, Ca, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Se, Sr, Mo, Ag, Cd, Sb, Ba, Hg, Pb, Th, and U) were determined by New Jersey’s Meadowlands Research Institute’s Earth and Environmental Science Department via ICP-MS.
Maximum contamination Levels (MCLs) define the maximum contamination concentration in drinking water. These limits are set near Maximum Contaminant Level Goals (MCLGs) whenever possible, using cutting-edge treatment technology and factoring for cost factors. MCLGs, on the other hand, represent the pollutants in drinking water concentrations below which there is no visible or foreseeable health harm. MCLGs are non-enforceable public health objectives that provide a threshold for contaminants in drinking water that can be present without harmful impacts on human health. Importantly, MCLGs are not legally binding and so are not subject to enforcement procedures. MCLs, which are set as close as possible to MCLGs (limited by technological capabilities, such as detection limit sensitivity or lack of available Treatment Technologies (TT)), are legal threshold limits empirically derived from the United States Environmental Protection (EPA) and represent the maximum amount of a substance allowed in public water systems that do not adversely affect human health—all of which comply with the Safe Water Drinking Act. MCLs may be higher than MCLGs due to technological limitations and whether the EPA determines that the costs of treatment would outweigh the public benefits of lower MCLs. For some contaminants (e.g., As, Ba, Cd, Cr, Cl, Cu, F, Pb, Hg, Se, and Be), the EPA established National Primary Drinking Water Regulations (NPDWRs) or primary standards (https://www.epa.gov/ground-water-and-drinking-water (accessed on 29 August 2023)) by requiring an enforceable EPA-mandated treatment technique (TT) procedure that drinking water systems must follow when treating their drinking water for a contaminant (https://www.epa.gov/ground-water-and-drinking-water (accessed on 14 October 2023)). Primary MCLs, therefore, refer to health-related effects, while secondary MCLs refer to cosmetic (skin or tooth discoloration) or aesthetic (taste, odor, and color) effects. The EPA also established secondary standards/NSDWRs (National Secondary Drinking Water Regulations)/MCLs for 15 contaminants (e.g., Al, Cl, Cu, F, Fe, Mn, Ag, Zn); these MCLs are not legally enforceable. Medgar Evers College complies with all heavy metals that have an associated primary standard (Figure 2a–d).
Heavy metal primary and secondary MCLs are provided in the Supplementary File via Tables for reference. Figure 2a,b exemplifies the mean elemental concentrations with and without He flow, respectively, while Figure 2c,d exemplifies the median elemental concentrations without and with He flow, respectively. The corresponding primary MCLGs and MCLs for elements pertinent to this study are: As (0 ppbv and 10 ppbv), Ba (2000 ppbv and 2000 ppbv), Be (4 ppbv and 4 ppbv), Cd (5 ppbv and 5 ppbv), Cr (100 ppbv and 100 ppbv), Cl (250,000 ppbv and 250,000 ppbv), Cu (1300 ppbv and 1300 ppbv), F (4000 ppbv and 4000 ppbv), Pb (0 ppbv and 15 ppbv), Hg (2 ppbv and 2 ppbv), and Se (50 ppbv and 50 ppbv). Figure 2a–d shows that Medgar Evers College’s potable water sources are in accordance with the EPA’s MCLs and require no legally enforceable action for compliance. Arsenic, barium, cadmium, calcium, chromium, chloride, lead, magnesium, mercury, selenium, and sodium do not have secondary MCLs, while calcium, iron, magnesium, manganese, silver, sodium, and zinc do not have primary MCLs. All heavy metals comply w/EPA MCLs, except Fe, which exhibits mean and median concentrations of two to four times iron’s secondary MCL of 300 ppbv.

3.1. Iron (Fe)

Fe is one of the most abundant elements on Earth and makes up about 5% of its crust. Iron plays a pivotal and diverse role in maintaining optimal human health, constituting 65 to 80% of the body’s total iron reserves. This elemental contribution is integral to the formation of proteins hemoglobin and myoglobin, facilitating the transportation of oxygen to body cells and supporting cellular metabolism, with an approximate requirement of 400 mg of iron. The Environmental Protection Agency (EPA) has established a secondary standard for iron at 300 parts per billion by volume (ppbv), equivalent to 0.30 milligrams per liter (mg/L) or 30 micrograms per deciliter (µg/dL). The recommended dietary allowance for Fe ranges from 0.25 to 50 mg/day, depending on factors like age, gender, and individual health needs (see references via https://ods.od.nih.gov/factsheets/Iron-HealthProfessional/#en5 (accessed on 28 March 2023), https://cdn.who.int/media/docs/default-source/wash-documents/wash-chemicals/iron-bd.pdf?sfvrsn=8bde1f09_4 (accessed on 1 December 2023), and https://ods.od.nih.gov/factsheets/Iron-HealthProfessional/ (accessed on 19 July 2023)). Meeting these dietary guidelines is essential for maintaining optimal health. Most well-nourished/healthy persons in industrial countries have 4 to 5 g Fe in their bodies (https://en.wikipedia.org/wiki/Human_iron_metabolism (accessed on 17 March 2023)). Approximately 2.5 g are contained in the hemoglobin, while the rest is contained in ferritin complexes present in the cells, bone marrow, liver, and spleen. As there is no physiological regulatory mechanism for excreting iron, the vast majority of Fe in the human body is recycled by the reticuloendothelial system and stored as ferritin complex in the liver. A minor amount of Fe (1 to 2 mg) is excreted through urine, vaginal fluid, sweat, feces, and tears; therefore, regulating Fe uptake is key to optimal human health. Long-term deviations from adequate daily Fe uptakes may result in sideropaenia (iron deficiency) or hemochromatosis (iron overload). Damage to one’s intestinal lining may amplify the absorption of Fe across the mucosa; iron toxicity then results when the amount of circulating iron exceeds the amount of transferrin available to bind it. This is usually the result of extreme cases which are usually caused by an individual over-consuming Fe supplements/tablets, rather than through variations in an individual’s diet. Iron overload causes severe mucosa damage in the gastrointestinal tract, among other adverse issues such as fatigue/weakness as well as joint and abdominal pain. Iron deficiency may be caused by nutrient deficiency, inability to absorb Fe, damage to the intestinal lining, increased loss of iron due to excessive blood loss, and inflammation.
It has been reported that rivers have a median iron concentration of 0.7 mg. L. Anaerobic groundwater has iron in the form of iron (II); and the concentrations are around 0.5–10 mg/L, there can be instances where this value can reach 50 mg/L (6). The iron concentration in drinking water is usually less than 0.3 mg/L. This value for drinking water varies from country to country; some regions use various iron salts as coagulating agents in water-treatment plants as well as cast-iron, steel, and galvanized iron pipes for water distribution (http://www.who.int/water_sanitation_health/dwq/chemicals/iron.pdf (accessed on 19 September 2023)). Despite the instances in which humans add iron to water intentionally or unintentionally, iron occurs as a natural constituent in plants and animals. Some common foods containing iron are animal livers and kidneys, fish, and green vegetables; their iron concentrations range between 20 and 150 mg/kg. Other foods like red meats and egg yolk contain 10–20 mg/kg, while rice and many fruits and vegetables have low iron contents (1–10 mg/kg). On average, the reported daily intake of iron from food is about 10–14 mg (7.8); from drinking water, the reported daily intake is around 0.6 mg, and air contributes about 25 µg/day in urban areas. Concentrations above 0.3 mg/L, which exceed Fe’s secondary MCL, may contribute to bad water taste, pipe clogging, and the staining of clothes, teeth, tubs, and sinks. High Fe concentrations in drinking water are often due to the corrosion of underground iron pipes (for water distribution) and groundwater soil content.
A comprehensive analysis of samples gathered from MEC revealed that 89% surpassed the Environmental Protection Agency’s (EPA) secondary standard for iron. The observed elevations ranged from a factor of 1.5 (0.5 mg/L) to 28 (8.5 mg/L) when compared to the corresponding EPA standard of 300 parts per billion by volume (ppbv), as illustrated in Figure 3a. This range of enhanced Fe represents 84% of the samples collected from water fountains throughout all four primary buildings (Bedford, AB1, S-Building, and Carroll Buildings) on campus. Accordingly, 11% of samples complied with the respective EPA secondary standard, and 45% of those samples were from select water fountains in the AB1, Beford, and Carroll Buildings (Figure 3a). 97 and 90% of samples exhibit RSD < 10% and 5%, correspondingly (Figure 3b,c). Note the monotonic increase in precision, especially at [Fe] > 10−1 ppb, RSD < 10% (only He gas mode). Medgar Evers College is therefore in full compliance with the EPA’s primary MCL for Fe, because the EPA’s MCL is not legally enforceable due to it being a secondary standard. Here, the RSD is defined as: where s = 1 n 1 i = 1 n ( x i x ¯ ) 2 and x ¯ are sample standard deviation and sample mean, correspondingly. In essence, this quantitatively represents an instrument’s precision as a function of concentration.

3.2. Lead (Pb)

Used to produce plastic stabilizers, rust inhibitors, pigments, cable sheathing, solder alloys, and lead acid batteries, lead is one of the most common heavy metals found in the Earth’s crust (13 mg/kg) [1,2]. Tetramethyl and tetraethyl lead were extensively used in North America and western Europe as antiknock agents in petrol but have been almost completed phased out in these areas. Lead pipes were used in older water distribution and plumbing systems and are widely used in plumbing fittings and solder in such systems [1,2]. Addressing lead-related issues is imperative due to the detrimental effects of lead exposure, particularly on cognitive development in children, effects which necessitate comprehensive efforts to safeguard public health.
Since the introduction of legislation restricting the use of lead in fuels, there has been a decline in atmospheric emissions of lead, making water the largest controllable source of lead exposure in the USA [24]. Lead can be found in tap water, primarily due to its presence in household plumbing systems such as pipes, solder, fittings, or connections to homes. A small contribution to the lead in tap water could be caused by dissolution from natural resources. Lead compounds can leach out of polyvinyl chloride (PVC) pipes and result in high lead levels in drinking water. The amount of lead that dissolves from plumbing systems depends on various factors such as the presence of chloride and dissolved oxygen, pH, temperature, water softness, and the duration of time the water has been standing. Water that is soft and acidic is particularly effective at dissolving lead from plumbing systems [25,26]. Lead can continue to be released from pipes indefinitely; however, the release of lead from soldered joints and brass facets seems to decrease over time [24]. In newly constructed homes with copper pipes, soldered connections can release a significant amount of lead (between 210–390 μg/L), which can be harmful to children [27]. Note: the EPA’s primary standard for Pb = 15 ppbv = 0.015 mg/L = 1.5 µg/dL. To reduce the amount of lead in drinking water, corrosion control measures can be implemented such as increasing the pH from <7 to a range of 8–9 in the distribution system by adding lime [28,29]. Additionally, lead may also be released from flaking lead carbonate deposits on lead pipes or from iron sediment from older galvanized plumbing that has accumulated lead from various sources even when the water is no longer plumbosolvent.
In 1998, it was estimated that in the USA, only 1.1% of public water distribution systems had a lead level higher than 5 μg/L [16]. A more recent study found the average lead level in drinking water in the USA to be 2.8 μg/L [10]. In Canada, the median lead level in drinking water samples collected from five cities was 2.0 μg/L [30]. A study in Ontario, Canada found that the average concentration of lead in water consumed over the period of a week was between 1.1–30.7 μg/L, with a median level of 4.8 μg/L [31]. In the United Kingdom, from 1975–1976, about two-thirds of households had no lead in their drinking water, but the levels were about 50 μg/L in 10% of homes in England and 33% in Scotland (2). In Glasgow, Scotland, where water was known to be plumbosolvent, the lead concentration in about 40% of samples exceeded 100 μg/L [29]. These regional variations and historical lead-level trends underscore the importance of ongoing monitoring and regulatory efforts to ensure safe drinking water for all populations. It is evident that, while progress has been made in mitigating lead exposure, there remain areas and instances in which led contamination continues to pose a significant concern for public health.
Estimating the lead intake from various sources, including drinking water and prepared food, provides insights into potential exposure levels. Assuming a lead concentration of 5 μg/L in drinking water, the total intake of lead from this source can range from 3.8 μg/day for an infant to 10 μg/day for an adult. Prepared food also contains small but significant amounts of lead. Lead content increases when the water used for cooking or the cooking utensils contain lead, or when food, especially acidic food, is stored in lead-ceramic pottery or lead-soldered cans. However, the intake of lead from lead-soldered cans is decreasing as the use of lead-free solders becomes more widespread in the food processing industry [32,33].
Soils and household dust can be significant sources of lead exposure for young children, but the levels of lead can vary from less than 5 μg/g to tens of milligrams per gram in contaminated areas [34,35,36]. Because lead is immobile, contaminated soil levels will remain unchanged unless action is taken to decontaminate them (CDC, 1985). The highest lead concentrations are typically found in surface soil at depths of 1–5 cm. More than 80% of the daily intake of lead comes from food, dirt, and dust.
With a concentration of 5 micrograms per liter (μg/L), this average daily intake represents a substantial ingestion level for both children and adults, particularly noteworthy for bottle-fed infants. These estimates have a wide margin of error. It is not known to what extent the general public flushes the system before using tap water, and the duration of the time the water has been standing (and hence the lead levels) can vary greatly [24]. The contribution of ingested dust and dirt to total lead intake is known to vary with age, peaking around two years [37]. Lead is a cumulative poison, with infants, children under six years of age, fetuses, and pregnant women being most susceptible to adverse health effects. Its effects on the central nervous system can be severe.
Lead poisoning can manifest via a range of symptoms, with acute and chronic forms presenting distinct sets of issues. Symptoms of acute lead poisoning include dullness, restlessness, irritability, poor attention span, headaches, muscle tremors, abdominal cramps, kidney damage, hallucinations, memory loss, and brain dysfunction. These symptoms may occur when blood lead levels reach between 100–120 μg/dL in adults and 80–100 μg/dL in children. Chronic lead toxicity can manifest as fatigue, insomnia, irritability, headaches, joint pain, and gastrointestinal issues, and may appear in adults with blood lead levels between 50–80 μg/dL. After 1–2 years of exposure, occupationally exposed populations have been observed to have muscle weakness, gastrointestinal symptoms, lower scores on cognitive tests, mood disturbances, and symptoms of nerve damage at blood lead levels between 40–60 μg/dL [34].
Lead poisoning has long been linked to kidney disease, but in adults and children, chronic kidney damage has not been found at blood lead levels below 40 μg/dL [38]. Damage to the kidneys can also include acute dysfunction of the proximal tubules, which is characterized by the presence of lead-protein complexes in the cells of the proximal tubules at blood lead concentrations of 40–80 μg/dL [39]. There are indications that blood lead levels above 37 μg/dL may be associated with an increased risk of hypertension [40]. Studies using data from the second United States National Health and Nutrition Examination Survey (NHANES II) have found a significant association, without a clear threshold, between blood lead levels in the range of 7–34 μg/dL and high diastolic blood pressure in people aged 21–55 [41]. However, the validity of these results has been questioned [42].
Lead can disrupt the activity of several enzymes responsible to produce hemoglobin [34]. The only clearly defined symptom associated with the disruption of hemoglobin production is anemia [43], which only occurs when blood lead levels are above 40 μg/dL in children and 50 μg/dL in adults [44]. Amenia caused by lead exposure is the result of two processes: the inhibition of hemoglobin synthesis and the increased destruction of red blood cells [43]. Enzymes involved in the production of hemoglobin include d-aminolevulinic synthetase, the activity of which is indirectly blocked by feedback inhibition, leading to the accumulation of the neurotoxin d-aminolevulinic. Enzymes that are inhibited by lead include d-aminolevulinic acid dehydratase (d-ALAD), coproporphyrinogen oxidase, and ferrochelatse [43,44]. The activity of d-ALAD can be a good indicator of exposure to lead at both environmental and industrial levels. In children, inhibition of d-ALAD has been observed at blood lead levels as low as 5 μg/dL [45], but there are no known health impacts associated with this level of inhibition.
Lead can inhibit the enzyme ferrochelatase, which results in an accumulation of erythrocyte protoporphyrin (EP), indicating damage to the mitochondria [46]. No observed adverse effect levels (NOAELs) for increases in EP levels in infants and children have been established at around 15–17 μg/dL [47,48,49]. For adults, the NOAEL for increases in EP levels ranges from 25 to 30 μg/dL [50], while for females alone, the NOAEL ranges from 20 to 25 μg/dL, which is similar to that observed for children [48,51]. Infants under 42 months of age may experience changes in growth patterns as a result of increased levels of EP. Persistent increases in EP levels may initially lead to a rapid weight gain but later result in slowed growth [52]. A study of data from the NHANES II found a strong negative correlation between the height of children under the age of 7 years and blood lead levels between 5–35 μg/dL [53].
Lead can also interfere with calcium metabolism, both directly and by disrupting the production of the vitamin D precursor 1,25-dihydroxycholecalciferol by hemoglobin. Studies have shown that children with blood lead levels between 12–120 μg/dL have significantly lower levels of circulating 1,25-dihydroxycholecalciferol, with no clear threshold [54]. Lead is also known to accumulate in tissues of individuals who are calcium-deficient, which is especially concerning when considering the increased sensitivity to lead exposure that pregnant women with calcium deficiency may have. Research has shown that the interactions between calcium and lead can significantly contribute to the variance in cognitive scores, and that calcium can influence the negative effects of lead [55]. The enzyme brain protein kinase C, which regulates neural function, can be activated by lead concentrations as low as pm/L in laboratory tests, an effect similar to that caused by µmoles/L of calcium. These levels of lead can be found in the environment through exposure [56].
Multiple lines of evidence show that both the central and peripheral nervous systems are primarily affected by lead toxicity. The effects of lead toxicity can include brain damage and behavioral changes in adults; in children, electrophysiological evidence of nervous system effects has been found at blood lead levels as low as 30 μg/dL. Studies have also shown that abnormal brain wave readings are significantly correlated with blood lead levels as low as 15 μg/dL [57,58]. In children aged 5–9 years living near smelter, significant reductions in the maximal motor nerve conduction velocity (MNCV) have been observed, with a threshold occurring at a blood lead level of around 20 μg/dL; a 2% decrease in the MNCV was seen for every 10 μg/dL increase in the blood lead level [59]. Lead toxicity may also affect the auditory nerve, as some children have reported reduced hearing acuity [60]. The NHANES II survey in the USA found a significant association between blood lead levels and hearing threshold in children between the ages of 4–19 years, with a 10–20% increased likelihood of an elevated hearing threshold for those with a blood lead level of 20 μg/dL compared to those with blood lead levels of 4 μg/dL [61]. The data from the NHANES II survey also showed that there is a significant correlation between blood lead levels and the age at which infants first sit up, walk, and start to speak. Although no threshold level was found for when a child first walked, thresholds existed at the 29th and 28th percentile of lead rank for when a child first sat up and spoke, respectively [61].
Lead exposure in men has been linked to decreased sperm count at blood lead levels of 40–50 μg/dL [62,63,64,65]. Women who are occupationally exposed to lead may also experience reproductive dysfunction [34,66]. Studies have also shown that pregnant women exposed to lead have an increased risk of preterm delivery. A study of 774 pregnant women in Port Pirie found that the risk of preterm delivery was more than four times higher among women with blood lead levels above 14 μg/dL as compared to those with 8 μg/dL or less [67]. Approximately 10% of babies with elevated cord blood lead levels were found to have minor physical defects, such as angiomas, syndactylism, and hydrocele. The risk of malformations doubled at blood lead levels of around 7–10 μg/dL, and the incidence of any defects increased with increasing cord blood lead levels in the range of 0.7–35.1 μg/dL [68].
Research on the effects of lead exposure on human chromosomes (blood lead levels greater than 40 μg/dL) has yielded mixed results; some studies have found chromatid and chromosomal aberrations, breaks, and gaps, while others have not [64,69]. Studies on the link between lead exposure and cancer have also been inconclusive; some studies have shown small increases in cancer deaths, while others have not. Many of these studies did not consider other possible carcinogenic exposures or confounding factors such as smoking [64,67]. One study of 700 smelter workers (mean blood level 79.7 μg/dL) and battery factory workers (mean blood level 62.7 μg/dL) found an excess of deaths from cancers of the digestive and respiratory systems [70], but the significance of this is debated [71,72]. There was not a significant increase in urinary tract tumors in the production workers; however, the lead smelter workers in Australia had a substantial number of deaths caused by chronic renal disease [73]. The International Agency for Research on Cancer (IARC) states that the overall evidence for the carcinogenicity of lead in humans is inadequate [69]. However, inorganic lead compounds are considered probably carcinogenic to humans by the IARC (International Agency for Research on Cancer, Inorganic and Organic Lead Compounds, 1980).
Numerous epidemiological studies have been conducted to examine the potential negative effects of lead exposure on young children’s cognitive abilities and behavior, with a focus on “low” levels of lead exposure (blood lead levels less than 40 μg/dL) where overt clinical symptoms are absent. The conclusions drawn from these studies can be affected by several factors [74], including the study’s statistical power, potential biases in selecting study and control populations, the choice of parameter used to evaluate lead exposure, the timing of exposure measurement and psychological evaluations, the ability to quantify neurological and behavioral tests accurately and reproducibly, and the influence of nutritional and dietary factors such as iron and calcium intake. Recognizing and accounting for these complexities is crucial for interpreting the findings of such studies accurately and drawing meaningful conclusions about the effects of low-level lead exposure on the cognitive abilities and behavior of children.
Exposure to lead has been linked to a variety of health effects, including neurological and behavioral changes, increased risk of death from cardiovascular disease, impaired kidney function, high blood pressure, reduced fertility, poor pregnancy outcomes, delayed sexual development, and dental health issues. The IARC has determined that there is enough evidence in animals, but only limited evidence in humans, to classify inorganic lead as probably carcinogenic to humans (group 2A). Recent research does not suggest that these conclusions need to be revised.
The evidence suggests that exposure to lead in children is primarily linked to a decrease in IQ. This is particularly true for lower levels of lead exposure, and the impact on the IQ is significant when looking at the population as a whole. For an individual child, the IQ may be lowered by about 6.9 points over the range of 2.4–30 μg/dL. Although the individual decrease in IQ may be small per microgram of lead per deciliter of blood, when viewed at the population level it can have a significant impact. If the average IQ were to decrease by three points from 100 to 97, the number of individuals with a score below 100 would increase by 8%. Additionally, the number of individuals with an IQ score below 70, which is typically considered the threshold for intellectual disability, would increase by 57%. Conversely, there would be a 40% decrease in the number of individuals with an IQ score above 130, which is the cutoff for identifying individuals with “very superior” IQs. Additionally, the committee highlighted the fact that decreases in IQ linked to lead exposure can indicate the presence of other neurodevelopmental issues, even though the evidence for these effects is not as strong. These issues, such as attention deficit hyperactivity disorder, reading problems, difficulties with executive function, and fine motor impairments, have been observed in children with similar blood lead levels.
For adults, the adverse effect with the most significant and consistent evidence is the association between lead exposure and increased blood pressure. Although the increase in blood pressure may be small when viewed individually, it can have a significant impact on the distribution of blood pressure within a population. Increased blood pressure is linked to a higher risk of cardiovascular mortality. A meta-analysis of 61 studies involving over 1 million adults found that increased blood pressure is associated with higher mortality rates for ischemic heart disease and stroke across all blood pressure levels above 115 mmHg (15 kPa) systolic or 75 mmHg (10 kPa) diastolic.
The most commonly used methods for measuring lead levels in environmental and biological samples are atomic absorption spectrometry and anodic stripping voltammetry. Atomic absorption spectrometry can detect lead levels lower than 1 μg/L (International Organization for Standardization, 1986: water quality—determination of cobalt, nickel, copper, zinc, cadmium, and lead). When assessing human exposure to lead in drinking water, it is important to measure lead levels at the tap, rather than at the water source, as corrosion in plumbing systems can contribute to elevated lead levels.
None of the samples exceeded the EPA’s primary standard for Pb (15 ppbv = 0.015 mg/L = 1.5 µg/dL) (Figure 4a). The MCL for lead in drinking water was established by the collaboration of the EPA, the Food and Agricultural Organization of the United Nations (FAO), and the WHO. It was set based on the assumption that infants, who are considered the most valuable group, consume 50% of their provisional tolerable weekly intake (PTWI) from drinking water. The guideline value was determined by considering the daily water consumption of a 5-kg-bottle-fed infant, which is 0.75 L. It was also considered protective for all other age groups. At MEC, only two samples from the Carroll Building’s men’s faucets exhibited [Pb] = 13.7 and 14.8 ppb. A total of 92, or 80% of the samples, exhibited RSD < 10% and 5%, correspondingly (Figure 4b–d). Note the monotonic increase in precision in both the no gas and He gas modes, especially at Fe concentrations > 10−2 ppb (RSD < 10%) and 0.5 × 10−1 ppb (at RSD < 10%) for the He gas mode and the no gas mode, respectively. The He gas mode contributes, at most, a 23% reduction in the background Pb in 25% of all the samples. Medgar Evers College is in full compliance with the EPA’s primary MCL for lead.
It is also important to note that Fuller et al. (2022)’s “Pollution and health: a progress update” reinforces the fact that Pb pollution accounts for 900,000 premature deaths globally as of 2019. Pb ranks fourth among pollution-related deaths globally. Therefore, further work is needed to mitigate Pb lead pollution around the world, despite the significant efforts that have already been made to abate its public health impact.

3.3. Remaining Heavy Metals

All remaining heavy metal concentrations in the samples taken from MEC were below their designated EPA primary and secondary MCLs (Figure 5a, Figure 6a, Figure 7a, Figure 8a, Figure 9a, Figure 10a, Figure 11a, Figure 12a, Figure 13a,b and Figure 14a,b). Figure 5a shows that MEC’s potable water [Ag]s are all three orders of magnitude less than its respective EPA’s secondary MCL; overall, the He gas mode reduces the background concentrations of Ag. Similarly, all other heavy metals exhibited concentrations several factors to several orders of magnitude less than the respective EPA primary and secondary MCLs. With the exceptions of cadmium and chromium, all other heavy metals exhibited concentrations that were comparable with and without the He flow or were less with the He flow. Heavy metals that exhibited lower measured concentrations with the He flow, compared to no gas, was primarily due to the dilution of respective heavy metal concentrations with He gas. With no gas, Cd and Cr exhibit undetected values due to mitigated dynamic flow, while gas flow with He increases dynamic flow such that non-negligible amounts can be measured. All heavy metal RSDs decrease with increasing heavy metal concentration, and 80 to 90% of all sample RSDs are below 15 to 10% (Figure 3b,c, Figure 4b–d, Figure 5b–d, Figure 6b,c, Figure 7b–d, Figure 8b–d, Figure 9b–d, Figure 10b–d, Figure 11b–d, Figure 12b,c, Figure 13c,d and Figure 14c–e).
We utilized Tableau Public (https://public.tableau.com/app/discover (accessed on 10 December 2022)), a free platform used to explore, create, and publicly share data visualizations online, to construct multidimensional data visualization products that related heavy metal concentrations to sample locations and displayed cancer estimates to heavy metal exposure. Figure 15a,b showcases the dominance of [Fe]s at all buildings at Medgar Evers College, where Fe exist at concentrations several factors to several orders of magnitude greater than all other heavy metals. Analogously high concentrations were found in select sites across all boroughs except Staten Island; similarly, [Fe]s were much higher than other heavy metals measured via ICP-MS (Figure 16a,b). Figure 17 gives a scaling of the amount samples taken per sample area/site; we attained most water samples in Brooklyn.

3.4. Public Health Implications toward Cancer Attainment

We utilized the WHO’s non-carcinogenic and carcinogenic endpoint estimation to quantify first-order cancer attainment tendencies for heavy metal exposures via measurements performed at Medgar Evers College. Table S2 exemplifies the cancer risk with respect to non-carcinogenic and carcinogenic public health protection concentration estimations for Pb. Similarly, we used non-carcinogenic and carcinogenic public health protection concentration estimations for all other heavy metals that have WHO-established formulations. Table S3 + Figure 18 illustrate the cancer risk estimates for select heavy metals and the relative cancer risks with respect to select heavy metals, respectively. In the first three rows, Table S3 shows the EPA MCL, the OEHHA MCL (and respective cancer risks), and the OEHHA PHG (and respective cancer risks) for Pb, U, Cr, Hg, As, and Fe for all sample locations at Medgar Evers College. Table S3 also shows their mean heavy metal concentrations and respective cancer risks, using available non-carcinogenic and carcinogenic end-point cancer risk formulations from the WHO. This cancer risk formulation is not available for Fe, as it is only governed by the EPA’s secondary MCL guidelines and there is no significant quantitative causal correlation between Fe and cancer attainment for humans. For Pb, U, Cr, and As, there is a 10−7 to 10−8, 10−8, 10−5 to 10−6, and 10−4 to 10−5, chance for cancer attainment, respectively. This estimation shows that the measured arsenic levels can impart a one in 10,000 chance of developing cancer, while the measured Pb, U, and Cr levels impart at least a one in 100,000 chance of developing cancer. Figure 18 exemplifies a relative cancer risk data visualization for arsenic, lead, and chromium. Figure 19 provides clarity regarding the estimation of cancer attainment frequency as governed by the WHO’s non-carcinogenic and carcinogenic endpoint equations.

4. Conclusions

We measured heavy metal concentrations at Medgar Evers College’s potable water sources as well as select residential and commercial sites in Brooklyn (other than MEC), Queens, Manhattan, and Bronx via ICP-MS. All sample sites are compliant with EPA MCLs for heavy metals despite noncompliance with the EPA’s secondary MCL for Fe at Medgar Evers College, which is non-enforceable via the EPA, as secondary MCLs are only recommendations. Utilizing WHO End-Member Equations for carcinogenic incidence estimates, we approximated a 10−3 to 10−8 chance of contracting cancer from Pb, U, Cr, Hg, and As. These short case studies provide deep data analytics and water quality testing/analysis training, which in turn increases job acquisition in the environmental science workforce sector.
Ninety-five percent of sample concentration RSDs reveal four distinct regions: (1) where one mode is more precise than the other and sample data exhibit very good to excellent precision, RSD ≤ 15%; (2) despite being at low concentrations, some elements exhibit good to excellent precision, RSD ≤ 20%; (3) species concentrations exhibit very good to excellent precision, RSD ≤ 15%; and (4) species at concentrations ≤10−3 ppb display fair to very poor precision, RSD ≥ 30%. All heavy metals complied with their respective EPA MCLs (except Fe); compliances were, at most, three orders of magnitude less than the EPA requirements. Only 11.50% of Fe samples are below the EPA’s MCL (300 ppb).
As noted in the introduction, water is essential for life and good health. It is also a harbinger of the health of communities across multiple levels, from that of the individual who consumes water to that of the local government that advocates for clean water, to that of the infrastructure that supports water consumption. Moreover, water—and one’s ability to consume it—is intimately tied to deeper, local, and often racialized histories. The water infrastructure of places like Flint, Michigan, and Jackson, Mississippi—as just two examples—are relics of the early 20th century, reminders of an era of industrialization in which the jobs were plentiful, businesses thrived, and homes were affordable. Faltering industries, White flight, and subsequent disinvestment led to increasingly contaminated water supplies in both Flint and Jackson, reaching toxic tipping points in 2014 and 2020 in each city, respectively. These are just two examples of this phenomenon.
Educating community members about their water to prevent the next Flint or the next Jackson is of critical urgency. Again, these are just a few prominent examples, given their extensive media coverage. In 2021, the US had 153,611 active Public Water Systems (PWS). A total of 75% (114,758) of those PWSs had no water quality violations, while 25% (38,853) had at least one drinking water quality standard violation. In future studies, we anticipate combining the methods and findings described in this paper with qualitative, design-based research to collectively engage youth and adults in the forms of citizen science that revolve around these issues of environmental racism and infrastructural apartheid. Who has access to clean water? Who does not? Why is this the case? Local community members need to have the tools—in terms of data collection and in terms of data representation—both to monitor and advocate for change. The environmental racism of water, however, is indicative of other forms of toxicity, from infrastructural decay to inequitable funding, redlining, and more. As such, the kinds of community-based educational experiences we envision will enable citizens to use water to trace the relationship, over time, of both systemic and environmental racism and to advocate for a more just future.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/w15244233/s1.

Author Contributions

C.S.B.-B. governed all aspects of the research project, including the experimental procedures related to the project (e.g., sample preparation and analytic analysis via ICP-MS); N.N.K. reviewed and edited the manuscript; N.G. and D.S.H., S.W., M.Y., M.R. and K.S. reduced the data and constructed select data visualization plots; P.S., K.S., T.H. and B.A.-H. constructed select data visualization products and aided in the editing, content writing, and finalizing of the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

Funding was provided through the DOE-NYC Summer Youth Employment Program, $200K (2016–2019) and the Carnegie Faculty Student Research Award, $5K (2018).

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

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Figure 1. New York City’s Water Supply System (New York City drinking water supply and quality report, 2021).
Figure 1. New York City’s Water Supply System (New York City drinking water supply and quality report, 2021).
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Figure 2. Mean ± population standard deviation with and without He flow (a,b) and media ± population standard deviation with and without He flow (c,d).
Figure 2. Mean ± population standard deviation with and without He flow (a,b) and media ± population standard deviation with and without He flow (c,d).
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Figure 3. Sample numbers vs. Fe [ppb], He gas (a); 56 Fe [He] vs. Concentration of RSD (b); Fe ESD vs. Fe [ppb]/(EPA/NYSDOH Primary MCL [ppb]) vs. sample numbers (c).
Figure 3. Sample numbers vs. Fe [ppb], He gas (a); 56 Fe [He] vs. Concentration of RSD (b); Fe ESD vs. Fe [ppb]/(EPA/NYSDOH Primary MCL [ppb]) vs. sample numbers (c).
Water 15 04233 g003aWater 15 04233 g003b
Figure 4. Sample numbers vs. Pb [ppb], with and without He gas (a); 208 Pb [No Gas] vs. Concentration of RSD and 208 Pb [He] vs. Col 4 (b); Pb RSD vs. Pb [ppb]/(EPA/NYSDOH Primary MCL [ppb]) vs. sample numbers with no gas mode (c); Pb RSD vs. Pb [ppb]/(EPA/NYSDOH Primary MCL [ppb]) vs. sample numbers with gas mode (d).
Figure 4. Sample numbers vs. Pb [ppb], with and without He gas (a); 208 Pb [No Gas] vs. Concentration of RSD and 208 Pb [He] vs. Col 4 (b); Pb RSD vs. Pb [ppb]/(EPA/NYSDOH Primary MCL [ppb]) vs. sample numbers with no gas mode (c); Pb RSD vs. Pb [ppb]/(EPA/NYSDOH Primary MCL [ppb]) vs. sample numbers with gas mode (d).
Water 15 04233 g004aWater 15 04233 g004b
Figure 5. Sample numbers vs. Ag [ppb], with and without He gas (a); 107 Ag [No Gas] vs. concentration of RSD and 107 Pb [He] vs. Col 4 (b); Ag RSD vs. Ag [ppb]/(EPA/NYSDOH Primary MCL [ppb]) vs. sample numbers with no gas mode (c); Ag RSD vs. Ag [ppb]/(EPA/NYSDOH Primary MCL [ppb]) vs. sample numbers with gas mode (d).
Figure 5. Sample numbers vs. Ag [ppb], with and without He gas (a); 107 Ag [No Gas] vs. concentration of RSD and 107 Pb [He] vs. Col 4 (b); Ag RSD vs. Ag [ppb]/(EPA/NYSDOH Primary MCL [ppb]) vs. sample numbers with no gas mode (c); Ag RSD vs. Ag [ppb]/(EPA/NYSDOH Primary MCL [ppb]) vs. sample numbers with gas mode (d).
Water 15 04233 g005aWater 15 04233 g005b
Figure 6. Sample numbers vs. Cr [ppb], with and without He gas (a); 52 Cr [No Gas] vs. concentration of RSD and 52 Cr [He] vs. Col 4 (b); Cr RSD vs. Cr [ppb]/(EPA/NYSDOH Primary MCL [ppb]) vs. sample numbers with no gas mode (c).
Figure 6. Sample numbers vs. Cr [ppb], with and without He gas (a); 52 Cr [No Gas] vs. concentration of RSD and 52 Cr [He] vs. Col 4 (b); Cr RSD vs. Cr [ppb]/(EPA/NYSDOH Primary MCL [ppb]) vs. sample numbers with no gas mode (c).
Water 15 04233 g006aWater 15 04233 g006b
Figure 7. Sample numbers vs. As [ppb], with and without He gas (a); 75 As [No Gas] vs. concentration of RSD and 75 As [He] vs. Col 4 (b); As RSD vs. As [ppb]/(EPA/NYSDOH Primary MCL [ppb]) vs. sample numbers with no gas mode (c); As RSD vs. As [ppb]/(EPA/NYSDOH Primary MCL [ppb]) vs. sample numbers with gas mode (d).
Figure 7. Sample numbers vs. As [ppb], with and without He gas (a); 75 As [No Gas] vs. concentration of RSD and 75 As [He] vs. Col 4 (b); As RSD vs. As [ppb]/(EPA/NYSDOH Primary MCL [ppb]) vs. sample numbers with no gas mode (c); As RSD vs. As [ppb]/(EPA/NYSDOH Primary MCL [ppb]) vs. sample numbers with gas mode (d).
Water 15 04233 g007aWater 15 04233 g007bWater 15 04233 g007c
Figure 8. Sample numbers vs. Ba [ppb], with and without He gas (a); 137 Ba [No Gas] vs. concentration of RSD and 137 Ba [He] vs. Col 4 (b); Ba RSD vs. Ba [ppb]/(EPA/NYSDOH Primary MCL [ppb]) vs. sample numbers with no gas mode (c); Ba RSD vs. Ba [ppb]/(EPA/NYSDOH Primary MCL [ppb]) vs. sample numbers with gas mode (d).
Figure 8. Sample numbers vs. Ba [ppb], with and without He gas (a); 137 Ba [No Gas] vs. concentration of RSD and 137 Ba [He] vs. Col 4 (b); Ba RSD vs. Ba [ppb]/(EPA/NYSDOH Primary MCL [ppb]) vs. sample numbers with no gas mode (c); Ba RSD vs. Ba [ppb]/(EPA/NYSDOH Primary MCL [ppb]) vs. sample numbers with gas mode (d).
Water 15 04233 g008aWater 15 04233 g008bWater 15 04233 g008c
Figure 9. Sample numbers vs. Cd [ppb], with and without He gas (a); 111 Cd [No Gas] vs. concentration of RSD and 111 Cd [He] vs. Col 4 (b); Cd RSD vs. Cd [ppb]/(EPA/NYSDOH Primary MCL [ppb]) vs. sample numbers with no gas mode (c); Cd RSD vs. Cd [ppb]/(EPA/NYSDOH Primary MCL [ppb]) vs. sample numbers with gas mode (d).
Figure 9. Sample numbers vs. Cd [ppb], with and without He gas (a); 111 Cd [No Gas] vs. concentration of RSD and 111 Cd [He] vs. Col 4 (b); Cd RSD vs. Cd [ppb]/(EPA/NYSDOH Primary MCL [ppb]) vs. sample numbers with no gas mode (c); Cd RSD vs. Cd [ppb]/(EPA/NYSDOH Primary MCL [ppb]) vs. sample numbers with gas mode (d).
Water 15 04233 g009aWater 15 04233 g009bWater 15 04233 g009c
Figure 10. Sample numbers vs. Hg [ppb], with and without He gas (a); 201 Hg [No Gas] vs. concentration of RSD and 201 Hg [He] vs. Col 4 (b); Hg RSD vs. Hg [ppb]/(EPA/NYSDOH Primary MCL [ppb]) vs. sample numbers with no gas mode (c); Hg RSD vs. Hg [ppb]/(EPA/NYSDOH Primary MCL [ppb]) vs. sample numbers with gas mode (d).
Figure 10. Sample numbers vs. Hg [ppb], with and without He gas (a); 201 Hg [No Gas] vs. concentration of RSD and 201 Hg [He] vs. Col 4 (b); Hg RSD vs. Hg [ppb]/(EPA/NYSDOH Primary MCL [ppb]) vs. sample numbers with no gas mode (c); Hg RSD vs. Hg [ppb]/(EPA/NYSDOH Primary MCL [ppb]) vs. sample numbers with gas mode (d).
Water 15 04233 g010aWater 15 04233 g010bWater 15 04233 g010c
Figure 11. Sample numbers vs. Se [ppb], with and without He gas (a); 82 Se [No Gas] vs. concentration of RSD and 82 Se [He] vs. Col 4 (b); Se RSD vs. Se [ppb]/(EPA/NYSDOH Primary MCL [ppb]) vs. sample numbers with no gas mode (c); Se RSD vs. Se [ppb]/(EPA/NYSDOH Primary MCL [ppb]) vs. sample numbers with gas mode (d).
Figure 11. Sample numbers vs. Se [ppb], with and without He gas (a); 82 Se [No Gas] vs. concentration of RSD and 82 Se [He] vs. Col 4 (b); Se RSD vs. Se [ppb]/(EPA/NYSDOH Primary MCL [ppb]) vs. sample numbers with no gas mode (c); Se RSD vs. Se [ppb]/(EPA/NYSDOH Primary MCL [ppb]) vs. sample numbers with gas mode (d).
Water 15 04233 g011aWater 15 04233 g011bWater 15 04233 g011c
Figure 12. Sample numbers vs. Zn [ppb], with and without He gas (a); 66 Zn [He] vs. concentration of RSD (b); Zn RSD vs. Zn [ppb]/(EPA/NYSDOH Primary MCL [ppb]) vs. sample numbers with gas mode (c).
Figure 12. Sample numbers vs. Zn [ppb], with and without He gas (a); 66 Zn [He] vs. concentration of RSD (b); Zn RSD vs. Zn [ppb]/(EPA/NYSDOH Primary MCL [ppb]) vs. sample numbers with gas mode (c).
Water 15 04233 g012aWater 15 04233 g012b
Figure 13. Sample numbers vs. Cu [ppb], with and without He gas (a); sample number vs. Cu [ppb], He gas (b); 63 Cu [He] vs. concentration RSD (c); Cu RSD vs. Cu [ppb]/(EPA/NYSDOH Primary MCL [ppb]) vs. sample numbers with gas mode (d).
Figure 13. Sample numbers vs. Cu [ppb], with and without He gas (a); sample number vs. Cu [ppb], He gas (b); 63 Cu [He] vs. concentration RSD (c); Cu RSD vs. Cu [ppb]/(EPA/NYSDOH Primary MCL [ppb]) vs. sample numbers with gas mode (d).
Water 15 04233 g013aWater 15 04233 g013b
Figure 14. Sample numbers vs. Mn [ppb], with and without He gas (a); sample number vs. Mn [ppb], with and without He gas (b); 55 Mn [no gas] vs. concentration RSD and 55 Mn [He] vs. Col 4 (c); Mn RSD vs. Mn [ppb]/(EPA/NYSDOH Primary MCL [ppb]) vs. sample numbers with no gas mode (d); Mn RSD vs. Mn [ppb]/(EPA/NYSDOH Primary MCL [ppb]) vs. sample numbers with gas mode (e).
Figure 14. Sample numbers vs. Mn [ppb], with and without He gas (a); sample number vs. Mn [ppb], with and without He gas (b); 55 Mn [no gas] vs. concentration RSD and 55 Mn [He] vs. Col 4 (c); Mn RSD vs. Mn [ppb]/(EPA/NYSDOH Primary MCL [ppb]) vs. sample numbers with no gas mode (d); Mn RSD vs. Mn [ppb]/(EPA/NYSDOH Primary MCL [ppb]) vs. sample numbers with gas mode (e).
Water 15 04233 g014aWater 15 04233 g014bWater 15 04233 g014c
Figure 15. Site locations (left) and measured chemical values (right) with (a) focuses on Fe (yellow) concentrations whereas (b) focuses on Cr (orange), U (green), and Pb (teal) concentrations.
Figure 15. Site locations (left) and measured chemical values (right) with (a) focuses on Fe (yellow) concentrations whereas (b) focuses on Cr (orange), U (green), and Pb (teal) concentrations.
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Figure 16. Site locations (left) and measured chemical values (right) with (a) focuses on Fe (teal) concentrations whereas (b) focuses on Co (orange), Hg (red), and Pb (brown) concentrations.
Figure 16. Site locations (left) and measured chemical values (right) with (a) focuses on Fe (teal) concentrations whereas (b) focuses on Co (orange), Hg (red), and Pb (brown) concentrations.
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Figure 17. Study site locations.
Figure 17. Study site locations.
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Figure 18. Specific study site locations.
Figure 18. Specific study site locations.
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Figure 19. PHG and cancer risk determination.
Figure 19. PHG and cancer risk determination.
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Blaszczak-Boxe, C.S.; Karle, N.N.; Wang, S.; Yu, M.; Golosov, N.; Riyad, M.; Smith, K.; Hollet, T.; Abdul-Hamid, B.; St. Hillaire, D.; et al. Environmental Assessment and Monitoring of Heavy Metals in New York City Potable Water Systems: Case Study at Medgar Evers College, Correlation Analysis, and Public Health Impacts. Water 2023, 15, 4233. https://doi.org/10.3390/w15244233

AMA Style

Blaszczak-Boxe CS, Karle NN, Wang S, Yu M, Golosov N, Riyad M, Smith K, Hollet T, Abdul-Hamid B, St. Hillaire D, et al. Environmental Assessment and Monitoring of Heavy Metals in New York City Potable Water Systems: Case Study at Medgar Evers College, Correlation Analysis, and Public Health Impacts. Water. 2023; 15(24):4233. https://doi.org/10.3390/w15244233

Chicago/Turabian Style

Blaszczak-Boxe, Christopher S., Nakul N. Karle, Shujie Wang, Manzhu Yu, Nikolay Golosov, Mohammed Riyad, Kayla Smith, Ty Hollet, Bishara Abdul-Hamid, Dickens St. Hillaire, and et al. 2023. "Environmental Assessment and Monitoring of Heavy Metals in New York City Potable Water Systems: Case Study at Medgar Evers College, Correlation Analysis, and Public Health Impacts" Water 15, no. 24: 4233. https://doi.org/10.3390/w15244233

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