&EPA United States Environmental Protection Agency EPA 600/R-22/067 1 September 2022 1 www.epa.gov/research Summary of Detection and Response Data from Source Water Contamination Incidents ------- EPA 600/R-22/067 I September 2022 I www.epa.gov/research This page is intentionally left blank ------- EPA/600/R-22/067 Summary of detection and response data from source water contamination incidents by John Hall and Jeff Szabo U.S. Environmental Protection Agency Cincinnati, OH 45268 Sue Witt, Nicole Sojda, Brindha Murugesan and Don Schupp Aptim Cincinnati, OH 45204 Contract 68HERC19D0009, Task Order 68HERC20F390 Office of Research and Development Homeland Security Research Program Cincinnati, OH 45268 Page 1 of 18 ------- Disclaimer The U.S. Environmental Protection Agency (EPA) through its Office of Research and Development funded and managed the research described herein under Contract 68HERC19D0009, Task Order 68HERC20F0390 with Aptim. It has been subjected to the Agency's review and has been approved for publication. Note that approval does not signify that the contents necessarily reflect the views of the Agency. Any mention of trade names, products, or services does not imply an endorsement by the U.S. Government or EPA. The EPA does not endorse any commercial products, services, or enterprises. Page 2 of 18 ------- Foreword The U.S. Environmental Protection Agency (EPA) is charged by Congress with protecting the Nation's land, air, and water resources. Under a mandate of national environmental laws, the Agency strives to formulate and implement actions leading to a compatible balance between human activities and the ability of natural systems to support and nurture life. To meet this mandate, EPA's research program is providing data and technical support for solving environmental problems today and building a science knowledge base necessary to manage our ecological resources wisely, understand how pollutants affect our health, and prevent or reduce environmental risks in the future. The Center for Environmental Solutions and Emergency Response (CESER) within the Office of Research and Development (ORD) conducts applied, stakeholder-driven research and provides responsive technical support to help solve the Nation's environmental challenges. The Center's research focuses on innovative approaches to address environmental challenges associated with the built environment. We develop technologies and decision-support tools to help safeguard public water systems and groundwater, guide sustainable materials management, remediate sites from traditional contamination sources and emerging environmental stressors, and address potential threats from terrorism and natural disasters. CESER collaborates with both public- and private-sector partners to foster technologies that improve the effectiveness and reduce the cost of compliance, while anticipating emerging problems. We provide technical support to EPA regions and programs, states, tribal nations, and federal partners, and serve as the interagency liaison for EPA in homeland security research and technology. The Center is a leader in providing scientific solutions to protect human health and the environment. This report summarizes a research study on detection of contamination in source waters using on-line water quality sensors. In this study, source water is untreated water from lakes or rivers. This water will be treated to make potable drinking water. Should an event like an accidental spill take place in source water, on-line sensor can provide early warning that a spill occurred and the location of the spill as it travels through the water body. However, little data exists on whether on-line sensor parameter change in the presence of contamination. This study provides sensor response data from two common source waters which have been contaminated with chemicals and other species which could affect source water quality. Gregory Sayles, Director Center for Environmental Solutions and Emergency Response Page 3 of 18 ------- Table of Contents Disclaimer 2 Foreword 3 List of Tables 4 Abbreviations and Acronyms 5 Acknowledgments 6 Executive Summary 7 Introduction 8 Testing Methodology 8 Quality Assurance 9 Results 10 Ohio River Water Testing 10 Lake Mead Water Testing 13 Conclusions 16 List of Tables Table 1: Source Water Contaminants 8 Table 2: Calibration checks for water quality sensors and UV-Vis devices 9 Table 3: Ohio River Water Test Results 11 Table 4: Lake Mead Water Test Results 14 Table 5: Sensor Detection for Source Water Contaminants 17 Page 4 of 18 ------- Abbreviations and Acronyms AFFF Aqueous Film Forming Foam °C Celsius CFU Colony Forming Unit Cm centimeter cso Combined Sewer Overflow HAB Harmful Algal Bloom L Liter mg milligram jiS micro Siemens mV millivolt nm nanometers ORD Oxidation Reduction Potential PFAS Per- and Polyfluoroalkyl Substances PFOA Perfluorooctanoic Acid T&E Test and Evaluation UAN Urea Ammonia Nitrogen uv Ultraviolet Vis Visible YSI Yellow Springs Instruments Page 5 of 18 ------- Acknowledgments Contributions are acknowledged from various staff at the Las Vegas Valley Water District for their help providing source water for this study. Steve Allgeier and Matt Umber from EPA's Office of Water also provided technical direction to the study. Page 6 of 18 ------- Executive Summary This report summarizes a research study on detection of contamination in source waters using on-line water quality sensors. In this study, source water is untreated water from lakes or rivers. This water will be treated to make potable drinking water. Should an event like an accidental spill take place in source water, on-line sensors can provide early warning that a spill occurred and the location of the spill as it travels through the water body. However, little data exists on whether on-line sensor parameters change in the presence of contamination. The purpose of this study is to provide sensor response data from two common source waters which have been spiked with chemical and biological contaminants which could affect source water quality. Two source waters were used. One water sample was collected from the Ohio River near Cincinnati, OH. The other water sample came from Lake Mead near Las Vegas, NV. Contaminants used in this study included unleaded gasoline, glyphosate (a common pesticide), coal ash slurry, crude oil, methanol, urea ammonium nitrate (fertilizer), algae associated with harmful algal blooms, aqueous film forming foam (used to fight fires), effluent from a combined sewer overflow, and barium chloride. Contaminants were introduced at concentrations between 1 and 10 mg/L. On-line water quality sensors included a common multi-parameter sonde measuring temperature, specific conductivity, pH, and oxidation reduction potential; and a spectrophotometer that measured light absorbance in the 200-800 nm range. The two waters were spiked with the contaminants and the sensor response recorded. The data has been compiled into tables for easy visualization. The data suggests that the on-line sondes were only marginally effective at detecting significant changes in water quality parameters in response to contaminants in the concentration ranges used in this study. The spectrophotometer detected uv-absorbance changes in response to all contaminants in the Lake Mead water, but the uv-absorbance only responded to contaminants introduced at higher concentrations in the Ohio River water. This result was attributed to higher levels of turbidity and other background contamination in the Ohio River. Page 7 of 18 ------- Introduction Little data exists on the detection of contamination in above-ground source water (e.g., lakes, rivers, etc.) used to make potable water. This data is important to a variety of stakeholders since it can help determine which sensor water quality parameters are capable of responding to contamination events, as well as providing a warning to water treatment managers at a downstream water utility. This data can help state, local, and utility personnel determine if it is worth investing in the deployment of a sensor to a source water location for the purpose of detecting spills or other methods of contaminant introduction. A significant change in UV- VIS values should trigger additional verification sampling and possible intake closure. This would be the most straightforward response to detecting a water quality parameter abnormality in a flowing source water. There are several river spill models for the Ohio River which can provide fate and transport information in response to an upstream contamination event and inform the timing of contaminant arrival at the intake. In order to collect this data, bench-scale experiments were conducted to observe the response of in situ water quality sensors to a selected set of contaminants at concentrations that are potential threats to the source water supply in two different test waters. The information obtained was then used to develop tabular summaries for each combination of water source, contaminant, and water quality sensors. Data contained in these tables can be used as part of the decision-making process for deploying a sensor to a source water environment for detection of contamination. Testing Methodology Two different source waters were tested: Ohio River and Lake Mead. The Ohio River represents a river-based source water, and water was collected in Cincinnati, OH. Lake Mead is a lake- based source water, and water was collected in Nevada and shipped to the Test and Evaluation (T&E) Facility. Ten different contaminants were tested with each source water. Table 1 lists the contaminants that were tested. These contaminants were chosen due to their potential to be found in source water from spills, releases, or overland drainage. Table 1: Source Water Contaminants Contaminant Unleaded Gasoline Glyphosate (pesticide) Coal Ash Slurry (fly ash) Bakken Crude Oil Methanol Urea Ammonium Nitrate (UAN, fertilizer) Harmful Algal Blooms (HABs) or their precursors Aqueous Fire Fighting Foam (AFFF) Non PFAS/PFOA Barium Chloride Dihydrate (metal) Combined Sewer Overflow (CSO) (biological - E. coli) Page 8 of 18 ------- Measurements were recorded with two different sensors during the source water testing: 1. Hach Yellow Springs Instrument (YSI) 556, a water quality multiprobe parameter system, which was used for measuring temperature, specific conductivity, pH, and oxidation reduction potential (ORP). 2. Hach DR6000 spectrophotometer, which was used to measure the ultraviolet (UV)/visible (Vis) absorbance integral value by taking a UV-Vis measurement every 5 nm in the 200-800 nm spectrum on the Wavelength Scan setting. Testing was conducted by adding 2 liters (L) of source water into a 4-L aspirator bottle with a tubing outlet. A stir bar was used to agitate the water. The Hach DR6000 sipper pump tubing was connected to the 4-L aspirator bottle, and the flow valve was then put into the open position. The switch on the sipper pump was activated to pump water through the Hach DR6000 flow- through sample cell. The YSI 556 probe was inserted into the water in the 4-L aspirator bottle. Prior to each test, the instruments were zeroed using deionized water. Once the YSI 556 readings were stable, the initial, baseline values of the source water were recorded. Approximately 1 milligram (mg)/L of a single chemical contaminant, or 1% of a biological contaminant, was added to the source water and mixed in the bottle on the stir plate. The source water parameters were then measured with each of the two sensors after the 5-minute mixing time, then measured again after another 5 minutes of mixing. This process was repeated for each of the available contaminants in each of the two source waters. Once each source water was tested with 1 mg/L of each individual chemical contaminant and 1% of the volume for the biological contaminant, the contaminant concentration was increased to 10 mg/L for each individual chemical contaminant and 10% of the volume for the biological contaminant, and the test was then repeated. Quality Assurance The quality metrics for this study are summarized below and shown in Table 2. Table 2: Calibration checks for water quality sensors and UV-Vis devices Measurement QA/QC Check Frequency Acceptance Criteria PH Calibration Check Daily prior to sample analysis ±0.1 pH units ±0.1 pH units ORP Calibration Check Daily prior to sample analysis ±1 mV ±1 mV Specific Conductance Calibration Check Daily prior to sample analysis ±1 mS ±1 mS Temperature Calibration Check Annually 1+ 1+ o o n n UV-Vis 200-800 nm absorbance Calibration Check Initially and quarterly ±0.1 nm Reagent Blank Daily prior to sample analysis ±0.1 nm Page 9 of 18 ------- This study relied exclusively on readings from water quality sensors and a UV-Vis spectrophotometer. Turbidity data for this experiment was not collected because previous studies have not shown a strong correlation between changes in turbidity and contaminant injections. Turbidity levels in the Ohio River have typically been in the 1 to 10 NTU range on previous experiments while Lake Meade turbidity has often been reported around 0.15 NTU. The acceptable ranges limit the error introduced into the experimental work. All analytical methods operated within the QC requirements for calibration checks unless otherwise noted, and all data quality objectives in Table 2 were met. At least 10% of the data acquired during the evaluation were audited. The data were traced from the initial acquisition, through analysis, to final reporting, to ensure the integrity of the reported results. All calculations performed on the data undergoing the audit were checked. No significant adverse findings were noted in this audit. Results Ohio River Water Testing Four 5 5-gal Ion drums of Ohio River Water were collected from the Gil day Riverside Park boat ramp in Cincinnati, Ohio, in November 2019. The following measurements were recorded for each test: • Initial Ohio River water quality parameter readings • Water quality parameter readings at two time intervals after the contaminant was added (5 and 10 minutes) • The average water quality parameter reading of the two time intervals • The percent change between the initial Ohio River water and the average of the two time intervals after the contaminant was added Preliminary tests were performed using 10 mg/L of the chemical contaminants and 10% by volume of the biological contaminant (HAB or CSO effluent) shown in Table 3. To determine if a difference between the baseline water and the contaminated water was significant, a minimum of 10%) difference between the initial water quality parameters and the average of the 5- and 10- minute readings of the contaminated water quality parameters had to be observed. The initial water quality reading is also referred to as the "baseline". A 10 % difference was chosen as a simple target to minimize noise or background changes such that the sensor data change could be more directly attributed to the contaminant added. Other percentage ranges, methods of event detection (e.g., algorithms) or standard deviation manipulation could be used. If there were no changes in water quality parameters at the 10 mg/1 and 10%> levels, then the 1 mg/1 and 1 % contaminant injection was not performed. If a response was observed from the 10 mg/L and 10%> preliminary test, the test was repeated using lmg/L of each of the chemical contaminants and 1%> by volume of the biological contaminant. For the Ohio River water a 50%> by volume of CSO water was injected. There was not enough water sample volume from Lake Meade to perform the 50%> CSO test. Table 3 shows the results of the Ohio River water tests. Changes greater than 10%> are highlighted in yellow. Page 10 of 18 ------- Table 3: Ohio River Water Test Results Ohio River Water 12/16/2019-12/19/2019 YSI 556 Water Quality Parameter Readings Hach DR6000 Readings Contaminant Concentration Sample Interval Specific Conductivity (US/cm) PH ORP (mV) Temp (°C) UV-Vis 200-800 nm (Area) Methanol 10 mg/L Initial 410 7.76 381.1 23.58 46.092 5-min 410 7.77 377.6 23.62 46.993 10-min 410 7.80 376.4 23.64 46.259 Avg of 5-10 min 410 7.785 377 46.626 % Change 0.00% -0.32% 1.08% -1.16% Barium (BaCl2*2H20) 1 mg/L Initial 427 7.74 348.7 22.36 39.908 5-min 431 7.76 352.0 22.34 43.647 10-min 431 7.76 352.0 22.36 44.066 Avg of 5-10 min 431 7.76 352 43.8565 % Change -0.94% -0.26% -0.95% -9.89% 10 mg/L Initial 407 7.79 384.3 23.32 44.996 5-min 421 7.79 383.0 23.04 57.846 10-min 420 7.80 381.2 23.09 59.824 Avg of 5-10 min 420.5 7.795 382.1 58.835 % Change -3.32% -0.06% 0.57% -30.76% Urea Ammonium Nitrate 10 mg/L Initial 410 7.65 455.2 23.61 47.436 5-min 418 7.67 426.8 23.61 48.113 10-min 418 7.69 410.1 23.61 49.138 Avg of 5-10 min 418 7.68 418.45 48.6255 % Change -1.95% -0.39% 8.07% -2.51% Glyphosate 10 mg/L Initial 409 7.79 384.7 23.25 44.615 5-min 411 7.68 374.5 23.26 47.427 10-min 411 7.70 368.8 23.31 48.161 Avg of 5-10 min 411 7.69 371.65 47.794 % Change -0.49% 1.28% 3.39% -7.13% Non- PFAS/PFOA AFFF 1 mg/L Initial 427 7.78 348.3 22.11 44.023 5-min 428 7.77 351.4 22.12 44.968 10-min 428 7.78 352.2 22.16 44.668 Avg of 5-10 min 428 7.775 351.8 44.818 % Change -0.23% 0.06% -1.00% -1.81% 10 mg/L Initial 409 7.77 370.4 23.29 39.860 5-min 410 7.80 366.5 23.32 47.624 10-min 410 7.79 366.9 23.38 48.180 Avg of 5-10 min 410 7.795 366.7 47.902 % Change -0.24% -0.32% 1.00% -20.18% Page 11 of 18 ------- Table 3: Ohio River Water Test Results (continued) Ohio River Water 12/16/2019-12/19/2019 YSI 556 Water Quality Parameter Readings Hach DR6000 Readings Contaminant Concentration Sample Interval Specific Conductivity (US/cm) PH ORP (mV) Temp (°C) UV-Vis 200-800 nm (Area) Initial 411 7.82 313.6 22.70 45.726 Coal Ash Slurry 5-min 411 7.91 315.7 23.55 50.129 10 mg/L 10-min 411 7.94 328.3 23.57 49.708 Avg of 5-10 min 411 7.925 322 49.9185 % Change 0.00% -1.34% -2.68% -9.17% Initial 427 7.77 355.9 22.10 42.696 5-min 427 7.78 356.1 22.15 46.780 1 mg/L 10-min 427 7.78 356.5 22.21 46.629 Avg of 5-10 min 427 7.78 356.3 46.7045 HABs % Change 0.00% -0.13% -0.11% -9.39% Initial 410 7.80 338.2 23.34 43.815 5-min 410 7.81 325.0 23.35 48.391 10 mg/L 10-min 410 7.82 318.5 23.38 47.144 Avg of 5-10 min 410 7.815 321.75 47.7675 % Change 0.00% -0.19% 4.86% -9.02% Initial 409 7.81 327.0 23.25 46.198 Unleaded Gasoline 5-min 410 7.82 322.7 23.26 50.305 10 mg/L 10-min 410 7.82 321.1 23.30 50.023 Avg of 5-10 min 410 7.82 321.9 50.164 % Change -0.24% -0.13% 1.56% -8.58% Initial 410 7.81 324.8 23.27 46.291 Bakken Crude Oil 5-min 410 7.82 322.5 23.28 48.875 10 mg/L 10-min 410 7.82 322.2 23.32 49.572 Avg of 5-10 min 410 7.82 322.35 49.2235 % Change 0.00% -0.13% 0.75% -6.33% Initial 413 7.73 392.1 23.14 45.112 5-min 412 7.76 383.0 23.00 48.300 1% 10-min 412 7.77 377.7 23.04 48.781 Avg of 5-10 min 412 7.765 380.35 48.5405 % Change 0.24% -0.45% 3.00% -7.60% Initial 411 7.77 348.4 22.34 45.739 5-min 404 7.85 346.1 21.27 56.638 CSO 10% 10-min 404 7.86 344.2 21.34 58.140 Avg of 5-10 min 404 7.855 345.15 57.389 % Change 1.70% -1.09% 0.93% -25.47% Initial 413 7.75 361.2 22.83 42.731 5-min 380 7.43 389.5 17.77 88.900 50% 10-min 380 7.73 364.2 17.98 92.373 Avg of 5-10 min 380 7.58 376.85 90.6365 % Change 7.99% 2.19% -4.33% -112.11% There were three contaminants that showed a 10% or greater change between the initial baseline water and the contaminated water: Page 12 of 18 ------- • Barium Chloride Dihydrate • Non PFAS/PFOA AFFF • CSO Of the sensor water quality parameters examined, only the UV-Vis Absorbance showed greater than 10% difference. The tests were then repeated with 1 mg/L of barium and AFFF, but neither contaminant showed greater than 10% difference for UV-Vis Absorbance (Table 3). The CSO tests were conducted using 1%, 10%, and 50% by volume CSO in Ohio River water. The CSO tests were planned to be conducted at 105 Colony Forming Units (CFU)/100mL; however, the concentration of the CSO sample collected was determined to be 2.44 x 104 CFU/lOOmL before mixing with the source water. The UV-Vis Absorbance showed greater than 10%) difference for the 10% and 50% by volume CSO concentrations. Lake Mead Water Testing Two 20-L cubitainers of source water were collected from Lake Mead in Nevada in March 2020, and shipped to the T&E Facility. Lake Mead is formed by the Hoover Dam on the Colorado River. The source water sample was collected from a relatively undisturbed area of Lake Mead (away from intakes or outfalls and mixing zones) in an attempt to grab a representative sample of the Colorado River water. Nine contaminants were tested in the Lake Mead source water. All the source water contaminants are listed in Table 4 with the exception of HABs. The following measurements were recorded for each test: • Initial Lake Mead water quality parameter readings • Water quality parameter readings at two time intervals after the contaminant was added (5 and 10 minutes) • The average water quality parameter reading of the two time intervals • The percent change between the initial Lake Mead water and the average of the two time intervals after the contaminate was added The test was run using 1 mg/L of the chemical contaminant and 1% by volume of the biological contaminant. To determine if a difference between the baseline water and the contaminated water was significant, a minimum of 10% difference between the initial water quality parameters and the average between the 5- and 10-minute readings of the contaminated water quality parameters had to be observed. Table 4 shows the results of the Lake Mead water tests. The following contaminants showed a minimum of 10% difference between the initial baseline water and the contaminated water: • Methanol • Barium Chloride Dihydrate • Glyphosate • Coal Ash Slurry Page 13 of 18 ------- Table 4: Lake Mead Water Test Results Lake Mead Water 03/11/2020-03/12/2020 YSI 556 Water Quality Parameter Readings Hach DR6000 Readings Contaminant Concentration Sample Interval Specific Conductivity (US/cm) PH ORP (mV) Temp (°C) UV-Vis 200-800 nm Integral Methanol 1 mg/L Initial 838 7.92 387.5 20.90 3.1741 5-min 839 7.97 386.5 21.29 2.2570 10-min 839 8.01 389.0 21.40 2.2263 Avg of 5-10 min 839 7.99 387.75 2.2417 % Change 0.12% 0.88% 0.06% -29.38% 10 mg/L Initial 915 8.14 338.8 26.33 3.6060 5-min 914 8.13 335.8 26.31 4.4531 10-min 914 8.12 337.1 26.33 3.6086 Avg of 5-10 min 914 8.125 336.45 4.0309 % Change -0.11% -0.18% -0.69% 11.78% Barium (BaCl2*2H20) 1 mg/L Initial 838 8.10 380.2 21.78 2.7646 5-min 841 8.14 384.3 22.14 4.6171 10-min 840 8.14 382.9 22.28 5.3734 Avg of 5-10 min 840.5 8.14 383.6 4.9953 % Change 0.30% 0.49% 0.89% 80.69% 10 mg/L Initial 914 8.17 360.5 26.84 1.6873 5-min 918 8.12 374.4 26.54 23.0410 10-min 913 8.11 381.9 26.58 24.8020 Avg of 5-10 min 915.5 8.115 378.15 23.9215 % Change 0.16% -0.67% 4.90% 1317.74% Urea Ammonium Nitrate 1 mg/L Initial 841 8.02 382.6 22.25 3.1644 5-min 842 8.14 374.4 22.47 2.9889 10-min 842 8.18 370.9 22.62 3.3340 Avg of 5-10 min 842 8.16 372.65 3.1615 % Change 0.12% 1.75% -2.60% -0.09% 10 mg/L Initial 914 8.15 358.1 26.58 2.9582 5-min 921 8.12 346.0 26.53 3.8450 10-min 918 8.11 341.4 26.56 3.5792 Avg of 5-10 min 919.5 8.115 343.7 3.7121 % Change 0.60% -0.43% -4.02% 25.49% Glyphosate 1 mg/L Initial 841 8.06 365.4 22.38 2.3216 5-min 842 8.11 348.2 22.56 3.6860 10-min 839 8.13 340.4 22.75 2.5771 Avg of 5-10 min 840.5 8.12 344.3 3.1316 % Change -0.06% 0.74% -5.77% 34.89% 10 mg/L Initial 914 8.14 340.8 26.60 2.8946 5-min 915 8.07 321.8 26.59 3.2087 10-min 915 8.07 313.0 26.63 3.5444 Avg of 5-10 min 915 8.07 317.4 3.3766 % Change 0.11% -0.86% -6.87% 16.65% Page 14 of 18 ------- Table 4: Lake Mead Water Test Results (continued) Lake Mead Water 03/11/2020-03/12/2020 YSI 556 Water Quality Parameter Readings Hach DR6000 Readings Contaminant Concentration Sample Interval Specific Conductivity (US/cm) PH ORP (mV) Temp (°C) UV-Vis 200-800 nm Integral Initial 841 8.04 349.1 22.66 2.7707 5-min 841 8.14 344.0 22.86 3.1405 1 mg/L 10-min 842 8.15 344.8 23.00 2.8373 Non- PFAS/PFOA (AFFF) Avg of 5-10 min 841.5 8.145 344.4 2.9889 % Change 0.06% 1.31% -1.35% 7.88% Initial 914 8.13 301.9 26.52 3.9469 5-min 913 8.12 305.3 26.49 3.6269 10 mg/L 10-min 913 8.12 314.5 26.51 4.1007 Avg of 5-10 min 913 8.12 309.9 3.8638 % Change -0.11% -0.12% 2.65% -2.11% Initial 837 8.00 358.9 22.96 2.1423 5-min 841 8.15 348.4 22.94 2.9502 1 mg/L 10-min 838 8.17 344.2 23.11 3.2384 Avg of 5-10 min 839.5 8.16 346.3 3.0943 Coal Ash % Change 0.30% 2.00% -3.51% 44.44% Slurry Initial 913 8.13 312.9 26.52 2.0279 5-min 913 8.17 394.5 26.36 3.5411 10 mg/L 10-min 913 8.17 394.6 26.39 3.2275 Avg of 5-10 min 913 8.17 394.55 3.3843 % Change 0.00% 0.45% 26.09% 66.89% Initial 841 8.10 350.0 24.49 2.5840 5-min 842 8.17 345.1 24.60 2.5542 1 mg/L 10-min 842 8.18 344.8 24.67 2.0816 Avg of 5-10 min 842 8.175 344.95 2.3179 Unleaded % Change 0.12% 0.93% -1.44% -10.30% Gasoline Initial 913 8.13 311.2 26.41 2.9374 5-min 913 8.13 322.5 26.42 3.4800 10 mg/L 10-min 913 8.16 326.4 26.47 3.0489 Avg of 5-10 min 913 8.145 324.45 3.2645 % Change 0.00% 0.18% 4.26% 11.13% Initial 843 8.16 342.3 24.19 2.5855 5-min 843 8.17 343.3 24.29 2.5966 1 mg/L 10-min 843 8.17 345.4 24.37 2.9287 Bakken Crude Oil (Shale) Avg of 5-10 min 843 8.17 344.35 2.7627 % Change 0.00% 0.12% 0.60% 6.85% Initial 913 8.13 332.8 26.15 2.8838 5-min 913 8.12 322.4 26.09 3.6851 10 mg/L 10-min 913 8.11 322.9 26.10 3.2602 Avg of 5-10 min 913 8.115 322.65 3.4727 % Change 0.00% -0.18% -3.05% 20.42% Page 15 of 18 ------- Table 4: Lake Mead Water Test Results (continued) Lake Mead Water 03/11/2020-03/12/2020 YSI 556 Water Quality Parameter Readings Hach DR6000 Readings Contaminant Concentration Sample Interval Specific Conductivity (US/cm) PH ORP (mV) Temp (°C) UV-Vis 200-800 nm Integral CSO 1% Initial 916 8.09 366.2 26.79 3.6858 5-min 910 8.13 349.8 26.75 3.8741 10-min 911 8.13 345.2 26.75 4.6693 Avg of 5-10 min % Change 910.5 -0.60% 8.13 0.49% 347.5 -5.11% 4.2717 15.90% 10% Initial 915 8.16 342.9 26.33 3.6063 5-min 857 8.11 332.2 25.50 9.3633 10-min 853 8.11 328.0 25.54 10.2470 Avg of 5-10 min 855 8.11 330.1 9.8052 % Change -6.56% -0.61% -3.73% 171.89% The test was then repeated using 10 mg/L of the chemical contaminant and 10% by volume of the biological contaminant (Table 4). There were three contaminants that had a 10% or greater change between the initial baseline water and the contaminated water. Those contaminants include the following (in addition to methanol, barium, glyphosate and coal ash in the 1 mg/L test): • Urea Ammonium Nitrate • Unleaded Gasoline • Bakken Crude Oil Of the sensor water quality parameters examined, only the UV-Vis Absorbance showed greater than 10% difference. The only contaminant that did not show a difference at either 1 mg/L or 10 mg/L was AFFF. The CSO test was conducted using 1% and 10% by volume CSO in Lake Mead water. The CSO tests were planned to be conducted at 105 CFU/lOOmL; however, the concentration of the CSO sample collected was determined to be 2.09 x 104 CFU/lOOmL before mixing with the source water. The UV-Vis Absorbance showed greater than 10% difference for the 1% and 10% CSO concentrations. The 50% CSO concentration by volume was not performed due to the lack of Lake Meade sample volume. Conclusions Based on the results of this study, the water quality parameters associated with the YSI 556 unit do not appear capable of detecting contaminants that are potential threats to the source water supply (Table 5). There was one change in the ORP that was greater than 10% (Lake Mead, 10 mg/L of Coal Ash Slurry); however, this ORP reading was qualified because the water in the beaker test was circulating due to the stir bar (not flowing). Flowing water is preferred for accurate ORP readings. Therefore, this data point was flagged. None of the other water quality Page 16 of 18 ------- parameters (pH, temperature, or specific conductivity) had differences above 10% for any of the contaminants in either Ohio River water or Lake Mead water. The Hach DR6000 does seem to have the potential to be useful in detecting contaminants that are potential threats to the source water supply (Table 5). The Hach DR6000 was able to detect eight of the nine contaminants in the Lake Mead water and three of the ten in the Ohio River water. Table 5: Sensor Detection for Source Water Contaminants Contaminant YSI 556 Hach DR6000 Spectrophotometer Ohio River* Lake Mead* Unleaded Gasoline NMR NMR 1 mg/L Glyphosate (pesticide) NMR NMR 1 mg/L Coal Ash Slurry (fly ash) NMR NMR 1 mg/L Bakken Crude Oil NMR NMR 10 mg/L Methanol NMR NMR 1 mg/L UAN (fertilizer) NMR NMR 10 mg/L HABs or their precursors NMR NMR NT AFFF NMR 10 mg/L NMR Barium Chloride Dihydrate (metal) NMR 10 mg/L 1 mg/L CSO (biological - E. coli) NMR 10% 1% *Lowest concentration contaminant was detected NT= not tested; NMR = no measurable response (change < 10%) While turbidity readings were not taken as a part of this study, the Lake Meade water used for this study had a visibly lower turbidity than the Ohio river. The clearer water allowed the light- based Hach DR6000 sensor to perform better than it did in the muddier Ohio river water. Any difference in the water quality is easier to detect; therefore, the Hach DR6000 had more contaminants detected at lower concentrations in Lake Mead water than in the Ohio River water. There were percent changes greater than 10% between the initial baseline water and the contaminated water with five contaminants at a concentration of 1 mg/L (unleaded gasoline, glyphosate, coal ash slurry, methanol, and barium chloride dihydrate) and two contaminants at a concentration of 10 mg/L (Bakken crude oil and urea ammonium nitrate). The CSO showed a greater than 10% change between the initial baseline water and the contaminated water at the 1% by volume concentration. The Hach DR6000 provided fewer response changes in water quality parameters on the Ohio River water than the Lake Mead water and they responded at higher concentrations. This is likely due to the increased turbidity and potential pollutants already present in the Ohio River water. The Ohio River water also had a much lower overall specific conductivity than the Lake Mead water. There were percent changes greater than 10% between the initial baseline water and the contaminated water with two contaminants at a concentration of 10 mg/L (AFFF and barium chloride dihydrate). The CSO had a greater than 10% change between the initial baseline water and the contaminated water at the 10% by volume concentration. Data summarized in this report demonstrates that standard source water quality parameters such as conductivity, ORP, pH, and temperature were not able to provide consistent and reliable responses to common source water contaminants at 1 and 10 mg/ 1 concentrations. The Page 17 of 18 ------- spectrometer measuring absorbance in the 200 to 800 nm range was able to provide more consistent and reliable responses to 1 and 10 mg concentrations of contaminants, especially in less turbid waters. Future research should gradually increase turbidity from Lake Meade levels up to Ohio River turbidity levels to determine optimal turbidity levels. The effect of filtering samples to lower turbidities for better spectrometry detections should also be studied. Page 18 of 18 ------- A EPA United States Environmental Protection Agency EPA 600/R-22/067 I September 2022 I Office of Research and Development (8101R)Washington, DC 20460 PRESORTED STANDARD POSTAGE & FEES PAID EPA PERMIT NO. G-35 Official Business Penalty for Private Use $300 Recycled/Recyclable Printed on paper that contains a minimum of 50% postconsumer fiber content processed chlorine free ------- |