The Yellowstone Plateau Volcanic field consists of lavas from the last two million years. The most recent volcanic units are the Central Plateau Member and the older Upper Basin Member rhyolites (Christiansen, 2001). Investigations into the elemental and isotopic composition of these lavas can provide insight into the recent volcanic history of the different eruptive episodes and provide constraints on the hydrothermal fluid compositions that result from water-rock interactions occurring at depth within the hydrothermal system. In this Data Release, twenty-one samples of Yellowstone rhyolite samples from Upper Basin Member and Central Plateau Member lava flows were analyzed for major and trace element concentrations and strontium isotopic composition. Analyzed samples include recently collected samples along with samples from the rock collection of Robert L. Christiansen (Robinson and others, 2021). This data was collected to constrain models of fluid-rock interaction of Yellowsto ...

Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) analyses of apatite provide trace element concentrations that support indicator mineral studies near the Taurus porphyry Cu-Mo deposit in the eastern Tanacross quadrangle, Alaska. The Taurus deposit and others in the region are mostly concealed, and traditional stream sediment samples typically show subdued geochemical signatures. The indicator mineral studies include collection of stream sediment samples and analysis using automated SEM mineralogical techniques. The presence of select minerals in the stream sediments may indicate mineralization. In addition, the chemistry of specific minerals may be used to distinguish a hydrothermal origin as opposed to others. The LA-ICP-MS data for apatite were collected by personnel of the Geology, Geophysics, and Geochemistry Science Center in Denver, Colorado, for the U.S. Geological Survey (USGS) Mineral Resources Program (MRP). Additional data were obtained at Queens University and Colorado School of Mines. Appreciable differences in chemistry were noted for apatite in mineralized rock and stream sediment samples draining these rocks compared to barren rocks or sediment samples away from mineralization.

Sediment cores were collected using a piston corer at three sites in the eastern Mediterranean Sea. Piston cores MS21 (32°20.7'N, 31°39.0'E; 1022 m water depth; 751.5 cm in length) and MS66 (33°1.9'N, 31°47.9'E; 1630 m water depth; 630 cm in length) were recovered during the MIMES cruise with the R/V Pelagia in 2004. Piston core 64PE406E1 (33°18.1'N, 33°23.7'E; 1760 m water depth; 920.5 cm in length) was recovered during the Eastern Mediterranean part of the 64PE406 (NESSC) cruise with the R/V Pelagia in 2016. The cores were opened and then prepared for X-Ray Fluorescence (XRF) core scanning by carefully flattening the sediment and covering it with a 4-μm SPEXCerti Ultralene foil. Subsequently, the sediments were XRF-scanned with a 1-mm resolution using four settings (10 kV-no filter, 20 kV-Al filter, 30 kV-Pd-thick filter, and 50 kV-Cu filter). The produced XRF-core-scanner data were calibrated using a subset of the discrete samples taken from the same core material. These samples were digested with an acid mixture and partially measured by inductively coupled plasma mass spectrometry (ICP-MS) and partially measured by ICP-optical emission spectroscopy (ICP-OES). The main purpose of our data collection was to reconstruct in detail (~10-50 yr resolution) the deoxygenation and anoxia in the eastern Mediterranean Sea during the last 300 ka BP; we focused on elements and elemental ratios of Al, Ba, Mo, Ti, and U.

This child page contains: (a) qualitative compositional data for 3 elements (chromium, manganese, and iron) as determined by X-ray fluorescence spectrometry using a portable instrument (“pXRF”) mounted in a test stand in the laboratory and (b) quantitative compositional data for up to 60 elements (some not reported quantitatively) determined by chemical digestion (sodium peroxide fusion) followed by inductively-coupled plasma-optical emission or inductively-coupled plasma-mass spectrometry, and (c) quantitative total organic carbon data. The pXRF data collected after July 22, 2019 presented here is subject to secondary data review as required by the Energy and Minerals Mission Area Quality Management System (EMMA QMS). Data collected by the contract lab AGAT is not subject to the EMMA QMS. As this process is not yet complete, data collected after July 22, 2019 must be considered preliminary or provisional (subject to revision). They are being provided to meet the need for timely best science. The data have not received final approval by the U.S. Geological Survey (USGS) and are provided on the condition that neither the USGS or the U.S. Government shall be held liable for any damages resulting from the authorized or unauthorized use of the data. When secondary data review is completed, this provisional statement will be removed.

Sediment cores were collected using a piston corer at three sites in the eastern Mediterranean Sea. Piston cores MS21 (32°20.7'N, 31°39.0'E; 1022 m water depth; 751.5 cm in length) and MS66 (33°1.9'N, 31°47.9'E; 1630 m water depth; 630 cm in length) were recovered during the MIMES cruise with the R/V Pelagia in 2004. Piston core 64PE406E1 (33°18.1'N, 33°23.7'E; 1760 m water depth; 920.5 cm in length) was recovered during the Eastern Mediterranean part of the 64PE406 (NESSC) cruise with the R/V Pelagia in 2016. The cores were opened and then prepared for X-Ray Fluorescence (XRF) core scanning by carefully flattening the sediment and covering it with a 4-μm SPEXCerti Ultralene foil. Subsequently, the sediments were XRF-scanned with a 1-mm resolution using four settings (10 kV-no filter, 20 kV-Al filter, 30 kV-Pd-thick filter, and 50 kV-Cu filter). The produced XRF-core-scanner data were calibrated using a subset of the discrete samples taken from the same core material. These samples were digested with an acid mixture and partially measured by inductively coupled plasma mass spectrometry (ICP-MS) and partially measured by ICP-optical emission spectroscopy (ICP-OES). The main purpose of our data collection was to reconstruct in detail (~10-50 yr resolution) the deoxygenation and anoxia in the eastern Mediterranean Sea during the last 300 ka BP; we focused on elements and elemental ratios of Al, Ba, Mo, Ti, and U.

data chart of all data collected for the research of laparoscopic managementpatient demographics , clinical scenario , surgical management and outcomes

The dataset contains supplementary information to a PLOS One article entitled, "Spatial and temporal trends in the fate of silver nanoparticles in a whole-lake addition study". These data are the raw data of environmental data collected and raw counts from sp-icp-ms output used in PLS regressions and other statistical analysis.

This record describes the sediment data collected from the Marine National Facility RV Investigator Event Voyage IN2015_E02, departing Hobart on the 7th April and returning to Hobart on the 14th April, 2015. The primary voyage objective was to deploy a specific sub-set of sampling equipment related to benthic biology, to establish processes, procedures and work flows in places such as the rear deck and sample processing laboratories. The primary equipment trialled was the MNF Deep Tow Camera, MNF Beam trawl, MNF Benthic (Sherman) Sled, and MNF Smith-McIntyre Grab, and the CSIRO-supplied Integrated Corer Platform (ICP), DeepBRUVs lander, and fishing dropline. The Integrated Coring Platform ( ICP) combines a number of technologies to maximise sampling in a single deployment. The ICP is built around a 6 barrel corer (KC, Denmark) and together with its central electronics module integrates cameras (cable, seafloor and corer views), CTD (SBE37IDO), altimeter, 120KHz scientific echo-sounders, Niskin bottles and hydrocarbon sensor suite. Sensor data is delivered in real time to the surface via fibre optic deployment cable. Video data from the ICP cameras includes imagery of seafloor types and mid-water biota during the up/down casts, refer to related marlin record for video data access. This metadata record describes the sediment collection using the grab and ICP taken inside the Huon Commonwealth Marine Reserve at 5 depth strata (100m, 200m, 500m, 1000m and 2000m) and on Patience seamount. Sediment samples were collected for chemical (CSIRO Energy), grainsize and composition (SARDI) analyses; surface water was also collected for PAH (polycyclic aromatic hydrocarbons ) analysis by NMI (National Measurements Institute). Bulk samples of sediments were elutriated for macrofauna analysis (University of Adelaide).

This is a data table of in situ Lu-Hf data collected from a single garnet sample obtained from a Li-bearing pegmatite in Finland. The data was collected from Adelaide Microscopy, University of Adelaide, Australia in March, 2023. The data table includes data for the unknown sample as well as standard data from the same analytical session. The purpose of data collection was to test the utility of the in situ garnet Lu-Hf dating method for obtaining ages of Li-pegmatites.

This record describes the biological data collected from the Marine National Facility RV Investigator Event Voyage IN2015_E02, departing Hobart on the 7th April and returning to Hobart on the 14th April, 2015. The primary voyage objective was to deploy a specific sub-set of sampling equipment related to benthic biology, and to establish processes, procedures and work flows in places such as the rear deck and sample processing laboratories. The primary equipment trialled was the MNF Deep Tow Camera, MNF Beam trawl, MNF Benthic (Sherman) Sled, and MNF Smith-McIntyre Grab, and the CSIRO-supplied Instrumented Corer Platform (ICP), DeepBRUVs lander, and fishing dropline. This metadata record describes the biological catches of benthic fauna collected using the beam trawl, sled, grab and ICP. The dropline failed to yield fish catches; however, the data also includes catches from invertebrate traps deployed on the dropline and in the deepBRUVs landers. Catches of epibenthic fauna were taken inside the Huon Commonwealth Marine Reserve at 5 depth strata (100m, 200m, 500m, 1000m and 2000m) and on Patience seamount. The catches were sorted into field identifications of operational taxonomic units (OTUs), documented and where deemed appropriate, photographed and data-based before preservation for lodgment in Australian Museums. The specimen collections will be curated at the museums for future taxonomic work. Plans for upgrading these data are subject to funding.

LA-MC-ICP-MS mapping data of Lophelia Pertusa specimen from Norway collected in September 2011 during POSEIDON cruise POS420 from a living colony at outer Trondheim-Fjord near the Norwegian island Nord-Leksa (63◦36.4′N, 09◦22.7′E) from 145-220m water depth .

In response to widespread concern that air pollution could affect forest condition, the International Co-operative Programme on the Assessment and Monitoring of Air Pollution Effects on Forests (ICP forests) was established under the UN/ECE Convention on Long-range Transboundary Air Pollution (CLRTAP) in 1985. ICP Forests was mandated to monitor air pollution effects on forests and to contribute to a better understanding of cause-effect relationships. Within the complex of anthropogenic and natural stresses, air pollution continues to be regards as an important stress factor. Air pollution and its effects on forest ecosystems are complex and difficult to isolate and quantify. A large number of other stress factors also have an influence on forest condition and must therefore be taken into consideration. The objective of the Level II network was therefore: to contribute to a better understanding of the relationships between the condition of the forest ecosystems and anthropogenic factors (in particular air pollution) as well as natural stress factors through intensive monitoring on a number of selected permanent observation plots spread over Europe and to study the development of important forest ecosystems in Europe. Data collection in the Level II/(Later FutMon) was modular in nature, in that it each assessment type was independent of the others. Included here are the daily meteorological data from various Level II sites - sites which have not been reported separately. Attribution statement:

This record describes the sediment data collected from the Marine National Facility RV Investigator Event Voyage IN2015_E02, departing Hobart on the 7th April and returning to Hobart on the 14th April, 2015.

The primary voyage objective was to deploy a specific sub-set of sampling equipment related to benthic biology, to establish processes, procedures and work flows in places such as the rear deck and sample processing laboratories. The primary equipment trialled was the MNF Deep Tow Camera, MNF Beam trawl, MNF Benthic (Sherman) Sled, and MNF Smith-McIntyre Grab, and the CSIRO-supplied Integrated Corer Platform (ICP), DeepBRUVs lander, and fishing dropline.

The Integrated Coring Platform ( ICP) combines a number of technologies to maximise sampling in a single deployment. The ICP is built around a 6 barrel corer (KC, Denmark) and together with its central electronics module integrates cameras (cable, seafloor and corer views), CTD (SBE37IDO), altimeter, 120KHz scientific echo-sounders, Niskin bottles and hydrocarbon sensor suite. Sensor data is delivered in real time to the surface via fibre optic deployment cable. Video data from the ICP cameras includes imagery of seafloor types and mid-water biota during the up/down casts, refer to related marlin record for video data access.

This metadata record describes the sediment collection using the grab and ICP taken inside the Huon Commonwealth Marine Reserve at 5 depth strata (100m, 200m, 500m, 1000m and 2000m) and on Patience seamount. Sediment samples were collected for chemical (CSIRO Energy), grainsize and composition (SARDI) analyses; surface water was also collected for PAH (polycyclic aromatic hydrocarbons ) analysis by NMI (National Measurements Institute). Bulk samples of sediments were elutriated for macrofauna analysis (University of Adelaide).

This is the complete compositional dataset for glass beads and pendants analyzed in the project. The data are in an Excel spreadsheet which may be sorted and edited. If you are using these data for comparative purposed, please be sure to cite the dissertation. Major elements are reported in weight percent of oxides, minor elements in parts per million.

The dataset includes .csv spreadsheets which provide whole rock geochemical data for the alkaline silicate and carbonatite samples from which apatite and monazite were analyzed, as well as geochemical data collected via electron microprobe and laser ablation ICP-MS for the apatite and monazite mineral grains. Whole rock geochemical data were collected by SGS Labs, except carbonatite samples 84-6-125, 85-1-162, 85-9-157, 85-12-304, and 85-12-317, which were collected by AGAT Labs. The .csv files containing geochemical data are associated with individual data dictionaries that define the columns in each file. Additional .csv files are included summarizing reference material analyses, detection limits, and analytical error for electron microprobe and laser ablation ICP-MS analysis. This data release also includes back-scattered electron (BSE) images of apatite mineral separates in epoxy grain mounts from samples collected in outcrop from alkaline silicate rocks of the Mountain Pass Intrusive Suite, as well as apatite and monazite in thin section in samples of drill core from the Mountain Pass carbonatite (the Sulphide Queen orebody). The zip file Phosphate_Mineral_Images contains all BSE images, organized into separate folders for apatite and monazite with subfolders for each sample. The file name of each photograph correlates to the date the image was taken, the mineral imaged, and the sample, mineral grain, and spot identification. The zip file CL_Images contains all mixed RGB hyperspectral cathodoluminescence images and element maps for Sr, Na, and Ce (apatite) and Ca, Si, and Th (monazite). The file name correlates to the sample number, grain number (as in Phosphate_Mineral_Images), and type of data displayed. Acquisition parameters for element map data are displayed on element map images.

Sediment particles can strongly bind metals, effectively repartitioning them from solution to a solid phase. As a result, sediments may accumulate and retain metals released to an aquatic environment. Sediment cores provide a historical record of metal inputs that can reveal anthropogenic influences (Förstner and Wittmann, 1979). Specifically, studies of sediment cores in San Francisco Bay chronicled metal inputs and suggested that legacy contamination can remain a chronic source of metals to the system owing to sediment mixing and redistribution (Hornberger and others, 1999; Van Geen and Luoma, 1999). Metals in sediments also indicate exposure levels to benthic animals through contact with, and ingestion of, bottom sediments and suspended particulate materials. However, physical and geochemical conditions of the sediment affect the biological availability of the bound metals. Assimilation of bioavailable sediment-bound metal by digestive processes and the contribution of this source of metals relative to metals in the aqueous phase are difficult to predict from sediment concentrations alone. Thus, in order to better estimate bioavailable metal exposures, the tissues of organisms may be analyzed for trace metals (Phillips and Rainbow, 1993). Different species concentrate metals to different degrees. However, if one species is analyzed consistently, the results can be used to track temporal changes in trace-element exposures at a specified location. This data release includes the sediment and tissue metal data starting in January 2019 and is presented in 13 tables as comma-separated values (.CSV) files as follows: T1_Sediment_Summary as a summary of the fine sediment, silver, aluminum, chromium, copper, iron, mercury, nickel, selenium, zinc and total organic carbon in the sediment. T2_Sediment_Metals_ICPOES provides detailed silver, aluminum, chromium, copper, iron, mercury, nickel, selenium and zinc data collected by inductively coupled plasma-optical emission spectrophotometry (ICP-OES) T3_Sediment_Hg_Se reports detailed mercury and selenium data T4_TOC reports detailed total organic carbon data from the sediment T5_Tissue_Metals reports the silver, chromium, copper, nickel, and zinc data collected from clams with the size and mass of the collected clam tissue for each sample date. T6_Tissue_Hg_Se reports the mercury and selenium data collected from clam tissue collected by size fraction and collection date. T7_QA_ICPOES_Sediment_SRM reports the standard reference material run data for certified reference standards for sediment analyzed on the ICP-OES. T8_QA_ICPOES_Tissue_SRM reports the standard reference material run data collected for certified standards for biological tissues analyzed on the ICP-OES. T9_QA_Hg_ Se reports the standard reference materials run for mercury and selenium data T10_QA_Spike_Recovery reports the spike recovery runs for the ICP-OES T11_QA_ICPOES_Blanks reports the procedural blanks run on the ICP-OES T12_QA_MDL_MRL reports the annual method detection limits and method reporting limits for the listed analyte T13_QA_SRM_reference_values reports the reference values for each of the reported standard reference material included in this data release

This dataset contains primarily the raw data collected during Michael Bensaid's thesis (https://doi.org/10.15126/thesis.901090), which was used to create all graphs, figures, and tables in the thesis.

A limited suite of samples for the 2020–2023 Kīlauea eruptions within Kaluapele (the summit caldera) were collected by the U.S. Geological Survey’s Hawaiian Volcano Observatory (HVO) field teams from within a publicly closed area of Hawai‘i Volcanoes National Park in cooperation with the National Park Service. This data release presents sample metadata, whole rock ED-XRF, whole rock WD-XRF, whole rock LA-ICP-MS, glass EPMA, glass LA-ICP-MS, leachate, and isotope data for these samples.

This data publication contains analytical data from direct analysis in real time time-of-flight mass spectrometry (DART TOFMS), inductively coupled plasma mass spectrometry (ICP-MS), and handheld laser-induced breakdown spectroscopy (LIBS) collected from five populations of Pinus ponderosa located 14 to 72 kilometers apart in Oregon between October 2021 and February 2025. These data were generated to assess the effectiveness of these techniques paired with machine learning models in determining the geographical provenance of timber. The data support research into forensic wood identification and environmental forensics by providing mass spectral and elemental composition data for comparative analysis. These data can be used to explore classification models, develop geographic reference databases, and evaluate alternative approaches for timber provenance determination. This data publication includes tabular digital data including: 1) the geographic coordinates and final ash mass for 107 Pinus ponderosa core samples, 2) ICP-MS data for 107 Pinus ponderosa wood core samples (normalized), 3) recorded DART TOFMS spectra data including the mass-to-charge ratio and corresponding relative intensity, and 4) recorded LIBS spectra data including wavelength and corresponding intensity.These data were collected to evaluate how data collected via DART TOFMS, LIBS, and ICP-MS could be used to classify different populations of Pinus ponderosa timber.For more information about this study and these data, see Price et al. (2025).

The dominant source of drinking water in rural Nevada, United States, is privately-owned domestic wells. Because the water from these wells is unregulated with respect to government guidelines, it is the owner’s responsibility to test their groundwater for heavy metals and other contaminants. Arsenic, lead, cadmium, and uranium have been previously measured at concentrations above Environmental Protection Agency (EPA) guidelines in Nevada groundwater. This is a public health concern because elevated levels of these metals are known to have negative health effects. We recruited individuals through a population health study, the Healthy Nevada Project, to submit drinking water samples from domestic wells for testing. Water samples were returned from 174 households with private wells. We found 22% had arsenic concentrations exceeding the EPA maximum contaminant level (MCL) of 10 mg/L. Additionally, federal, state, or health-based guidelines were exceeded for 8% of the households for uranium and iron, 6% for lithium and manganese, 4% for molybdenum, and 1% for lead. The maximum observed concentrations of arsenic, uranium, and lead were ~80, ~5, and ~1.5 times the EPA guideline values, respectively. 41% of households had a treatment system and submitted both pre- and post-treatment water samples from their well. The household treatments were shown to reduce metal concentrations, but concentrations above guideline values were still observed. Many treatment systems cannot reduce the concentration below guideline values because of water chemistry, treatment failure, or improper treatment techniques. These results show the pressing need for continued education and outreach on regular testing of domestic well waters, proper treatment types, and health effects of metal contamination. These findings are potentially applicable to other arid areas where groundwater contamination of naturally occurring heavy metals occurs. Methods Recruitment and survey of participants Participants of the Healthy Nevada Project (HNP) were recruited for this research. The HNP is a large (>50,000 participants) all-comers population health study in Nevada that includes cross-referenced electronic health records, socio-demographic data, whole-exome sequences, and social health determinant data. Details about the HNP were previously published (Grzymski et al., 2020; Read et al., 2021; Schlauch et al., 2022, 2020). Specifically, HNP participants who consented to be contacted for future studies were invited via email to complete the HNP private well survey. The HNP private well survey contained 11 questions regarding their well, water treatment, and drinking water habits (Supplementary Material). The private well survey was created and disseminated on the Survey Monkey platform (www.SurveyMonkey.com). Sampling Survey respondents who had a private well and wanted to submit a well water sample were emailed an informed consent document for water sampling. Consented individuals were mailed an at-home sampling kit. The kit included sampling instructions, a data collection sheet, pre-cleaned (1% nitric acid washed) sample bottle(s), and a return-shipment box. Sampling protocols (Supplementary Material) requested participants to purge their well casing of stagnant water by allowing the water to run for 2 to 4 hours prior to sampling, which is similar to state well water sampling guidelines (Donaldson et al., 2012). After purging, participants were asked to sample from the tap they used for drinking, cooking, and other household activities (referred to as “household water” herein). Households without a water treatment system were instructed to sample from the tap they most commonly used for household activities (referred to as “households without treatment”). Homeowners with a water treatment system in their home were instructed to sample after the treatment system from the tap they most commonly used for household activities (referred to as “households with treatment”). For the purpose of this study, any method, media, etc. that is used to treat, purify, or filter well water is considered a “treatment.” To study the effectiveness of water treatment, households with treatment were asked to submit an additional pre-treatment sample. The pre-treatment sample represents the groundwater geochemistry and the households do not use the pre-treatment water for drinking, cooking, and other household activities. The post-treatment sample represents the water after undergoing water treatment. Additional metadata requested of all participants were sample location, date, time, treatment method prior to sampling, color and smell of the well water, duration of well purging, and any other relevant information pertaining to the participant’s water and sampling experience. Geochemical analysis Participant sampling kits were mailed back to the Desert Research Institute (DRI) in Reno, Nevada. Samples were accessioned and de-identified. Related data were manually entered in an electronic database. Using ultra-high purity nitric acid (Aristar Ultra, VWR Chemicals BDH), the water samples were then preserved in 1% nitric acid and analyzed following EPA Method 200.8. All but one sample were received within the sample hold times outlined in EPA Method 200.8. The one sample received outside of the sample hold time was discarded. Sample geochemical analysis was conducted at the University of Nevada Core Analytical Laboratory using a Shimadzu 2030 Inductively Coupled Plasma Mass Spectrometry (Shimadzu Corporation, Columbia, Maryland, US) instrument. Settings for the ICP-MS are provided in Table S1. The targeted elements include As, copper (Cu), Fe, lithium (Li), Mn, Mo, Pb, and U. Calibration standards (Inorganic Ventures, Christiansburg, Virginia, US) for the ICP-MS instrument captured the concentration range of the samples. Quality assurance (QA) and quality control (QC) steps were taken at DRI and during ICP-MS analysis. DRI laboratory blanks and internal standards were submitted with the samples for analysis. DRI internal standards were made using a standard of known elemental concentration (Inorganic Ventures, Christiansburg, Virginia, US) with the elemental concentration targeting expected concentrations. QC included comparing the calculated internal standard concentrations to measured values as well as ensuring the DRI laboratory blank elemental concentrations were below sample concentrations or below detection limits. The average offset of a ~10 mg/L internal DRI standard (n=6) was <5% for As and Pb and <11% for Cu, Mn, Mo, and U. The average offset of a ~50 mg/L internal DRI standard (n=4) was <5% for Fe, Mo, and Pb and <16% for As, Cu and Mn. Additionally, during ICP-MS analysis precision recovery check standards (Agilent, Santa Clara, California, US) were measured every 10 to 15 samples (depending on sample analysis duration) to ensure the ICP-MS instrument response did not drift > 5% during analysis. Also during ICP-MS analysis, internal standards (Inorganic Ventures, Christiansburg, Virginia, US) were added to further monitor ICP-MS instrument drift. The detection limit for all analyzed metals was 0.05 mg/L. The detection limits were determined by a signal-to-noise ratio of >3, where the noise is the instrument response to the matrix. In some cases, the measured detection limit was below 0.05 mg/L, but 0.05 mg/L was used in this study as it is the reported detection limit for the element by the instrument manufacturer. The results were then reported to the homeowners including remediation options, as necessary. Statistical analysis Non-detects complicate subsequent data analysis. Discarding values <0.05 mg/L (i.e., below detection limit) or replacing them with zero may introduce a bias (Palarea-Albaladejo and Martín-Fernández, 2015) when computing summary statistics (i.e., mean median, and standard deviation), testing differences among groups, and correlation coefficients and regression equations (Helsel, 2011). Therefore, we chose to impute values <0.05 mg/L using R package (R Core Team, 2021) zCompositions (Palarea-Albaladejo and Martín-Fernández, 2015). We used the robust regression on order statistics (ROS) multiplicative lognormal replacement approach via the R package NADA for the imputation. This approach uses the measured values and assumes a distribution for the imputation of the censored portion (Helsel, 2005; Lee, 2020). To assess differences in metal concentrations in household water between homes without treatment and those with treatment as well as differences between pre- and post-treatment concentrations, we used the cendiff function in R, which is part of the NADA package. This function tests if there is a difference between two empirical cumulative distribution functions. The cendiff function is the Peto and Peto modification of the Gehan-Wilcoxon test (Helsel, 2005). This approach is appropriate for left-censored log-normal data, as is commonly observed in geochemical studies (Helsel, 2005), and was observed in this study.