## U.S. Department of the Interior **U.S. Geological Survey** 

# Prepared by the USGS Office of Water Quality, National Water Quality Laboratory 

# Determination of Elements in Natural-Water, Biota, Sediment, and **Soil Samples Using Collision/Reaction Cell Inductively Coupled Plasma–Mass Spectrometry**  **Chapter 1 Section B, Methods of the National Water Quality Laboratory**  **Book 5, Laboratory Analysis**

**Techniques and Methods Book 5–B1**

# Determination of Elements in Natural-Water, **Biota, Sediment, and Soil Samples Using Collision/Reaction Cell Inductively Coupled**  **Plasma–Mass Spectrometry**

By John R. Garbarino, Leslie K. Kanagy, and Mark E. Cree

Chapter 1 Section B, Methods of the National Water Quality Laboratory Book 5, Laboratory Analysis



# Techniques and Methods 5–B1

**U.S. Department of the Interior U.S. Geological Survey** 

# U.S. Department of the Interior Gale A. Norton, Secretary **U.S. Geological Survey** P. Patrick Leahy, Acting Director

U.S. Geological Survey, Reston, Virginia: 2006

For sale by U.S. Geological Survey, Information Services Box 25286, Denver Federal Center Denver, CO 80225 For more information about the USGS and its products: Telephone: 1-888-ASK-USGS World Wide Web: http://www.usgs.gov/

Any use of trade, product, or firm names in this publication is for descriptive purposes only and does not imply endorsement by the U.S. Government. Although this report is in the public domain, permission must be secured from the individual copyright owners to reproduce any copyrighted materials contained within this report.

Suggested citation: Garbarino, J.R., Kanagy, L.K., and Cree, M.E., 2006, Determination of elements in natural-water, biota, sediment, and soil samples using collision/reaction cell inductively coupled plasma–mass spectrometry: U.S. Geological Survey Techniques and Methods, book 5, sec. B, chap. 1, 88 p.

### iii



# Contents

Abstract

........................................................................................................................................................... 1 Introduction

..................................................................................................................................................... 1 Purpose and Scope

.............................................................................................................................. 2 Analytical Method

.......................................................................................................................................... 2 Application and Method Detection Limits

........................................................................................ 3 Interferences

......................................................................................................................................... 4 Instrumentation

................................................................................................................................... 1 0 Sample Collection, Preservation, Shipment, and Holding Times

................................................ 1 0 Calibration Standards and Other Solutions

.................................................................................... 1 3 Quantitation

.......................................................................................................................................... 1 3 Reporting of Analytical Data

............................................................................................................. 1 4 Laboratory Quality Assurance/Quality Control

.............................................................................. 1 4 Results and Discussion of Method Validation Data

............................................................................... 1 4 Summary and Conclusions

......................................................................................................................... 24 References Cited

.......................................................................................................................................... 2 5 Appendix — Linear Regression Analyses of Elemental Results

.......................................................... 27 Glossary

......................................................................................................................................................... 87 

# Figures

1. The effect of increasing concentrations of chloride from two sources on the determination of arsenic at mass-to-charge ratio 75

............................................................. 6 2. The effect of increasing concentrations of chloride from two sources on the determination of vanadium at mass-to-charge ratio 51

......................................................... 6 3. The effect of increasing concentrations of dissolved organic carbon from two natural-water sources on the determination of chromium at mass-to-charge ratio 52

............................................................................................................................................ 7 4. The variability in percentage recovery for selected elements extending the operational mass range as a function of increasing specific conductance

...................... 7 5. Sample-flow paths used with new collision/reaction cell inductively coupled plasma–mass spectrometric methods

.................................................................................... 11 6. Linear regression analysis of experimental concentrations for all elements in biological standard reference material digestates analyzed by collision/reaction cell inductively coupled plasma–mass spectrometry in relation to the certified concentrations

............................................................................................................................ 2 4

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# Appendix Figures

A1. Linear regression analysis of silver results from filtered water samples analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS)

.................................................................................................................................... 29 A2. Linear regression analysis of silver results from whole-water recoverable digestates analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS)

........................................................................................................... 30 A3. Linear regression analysis of aluminum results from filtered water samples analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS)

.................................................................................................................................... 31 A4. Linear regression analysis of aluminum results from whole-water recoverable digestates analyzed by inductively coupled plasma–mass spectrometry (ICP-MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS)

........................................................................................................... 32 A5. Linear regression analysis of arsenic results from filtered water samples analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS

..................................................................................................................................... 33 A6. Linear regression analysis of arsenic results from whole-water recoverable digestates analyzed by graphite furnace–atomic absorption spectrometry (GF–AAS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS)

........................................................................................................... 34 A7. Linear regression analysis of boron results from filtered water samples analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS)

.................................................................................................................................... 35 A8. Linear regression analysis of boron results from whole-water recoverable digestates analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS)

........................................................................................................... 36 A9. Linear regression analysis of barium results from filtered water samples analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS)

.................................................................................................................................... 37 A10. Linear regression analysis of barium results from whole-water recoverable digestates analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS)

........................................................................................................... 38 A11. Linear regression analysis of beryllium results from filtered water samples analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS)

.................................................................................................................................... 39

### A12. Linear regression analysis of beryllium results from whole-water recoverable digestates analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS)

........................................................................................................... 40 A13. Linear regression analysis of calcium results from filtered water samples analyzed by inductively coupled plasma–atomic emission spectrometry (ICP–AES) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS)

........................................................................................................... 41 A14. Linear regression analysis of calcium results from whole-water recoverable digestates analyzed by inductively coupled plasma–atomic emission spectrometry (ICP–AES) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS)

................................................................................. 42 A15. Linear regression analysis of cadmium results from filtered water samples analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS)

.................................................................................................................................... 43 A16. Linear regression analysis of cadmium results from whole-water recoverable digestates analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS)

........................................................................................................... 44 A17. Linear regression analysis of cobalt results from filtered water samples analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS)

.................................................................................................................................... 45 A18. Linear regression analysis of cobalt results from whole-water recoverable digestates analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS)

........................................................................................................... 46 A19. Linear regression analysis of chromium results from filtered water samples analyzed by graphite furnace–atomic absorption spectrometry (GF–AAS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS)

.................................................................................................................................... 47 A20. Linear regression analysis of chromium results from whole-water recoverable digestates analyzed by graphite furnace–atomic absorption spectrometry (GF–AAS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS)

........................................................................................................... 48 A21. Linear regression analysis of copper results from filtered water samples analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS)

.................................................................................................................................... 49 A22. Linear regression analysis of copper results from whole-water recoverable digestates analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS)

........................................................................................................... 50

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A23. Linear regression analysis of iron results from filtered water samples analyzed by inductively coupled plasma–atomic emission spectrometry (ICP–AES) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS)

........................................................................................................... 51 A24. Linear regression analysis of iron results from whole-water recoverable digestates analyzed by inductively coupled plasma–atomic emission spectrometry (ICP–AES) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS)

................................................................................. 52 A25. Linear regression analysis of potassium results from filtered water samples analyzed by inductively coupled plasma–atomic emission spectrometry (ICP–AES) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS)

........................................................................................................... 53 A26. Linear regression analysis of potassium results from whole-water recoverable digestates analyzed by inductively coupled plasma–atomic emission spectrometry (ICP–AES) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS)

................................................................................. 54 A27. Linear regression analysis of lithium results from filtered water samples analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS)

.................................................................................................................................... 55 A28. Linear regression analysis of lithium results from whole-water recoverable digestates analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS)

........................................................................................................... 56 A29. Linear regression analysis of magnesium results from filtered water samples analyzed by inductively coupled plasma–mass spectrometry (ICP–AES) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS)

.................................................................................................................................... 57 A30. Linear regression analysis of magnesium results from whole-water recoverable digestates analyzed by inductively coupled plasma–atomic emission spectrometry (ICP–AES) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS)

.................................................................. 58 A31. Linear regression analysis of manganese results from filtered water samples analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS)

........................................................................................................... 59 A32. Linear regression analysis of manganese results from whole-water recoverable digestates analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS)

................................................................................. 60 A33. Linear regression analysis of molybdenum results from filtered water samples analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS)

........................................................................................................... 61 A34. Linear regression analysis of molybdenum results from whole-water recoverable digestates analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS)

................................................................................. 62

### vii

A35. Linear regression analysis of sodium results from filtered water samples analyzed by inductively coupled plasma–atomic emission spectrometry (ICP–AES) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS)

........................................................................................................... 63 A36. Linear regression analysis of sodium results from whole-water recoverable digestates analyzed by inductively coupled plasma–atomic emission spectrometry (ICP–AES) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS)

.................................................................. 64 A37. Linear regression analysis of nickel results from filtered water samples analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS)

........................................................................................................... 65 A38. Linear regression analysis of nickel results from whole-water recoverable digestates analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS)

........................................................................................................... 66 A39. Linear regression analysis of lead results from filtered water samples analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS)

........................................................................................................... 67 A40. Linear regression analysis of lead results from whole-water recoverable digestates analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS)

........................................................................................................... 68 A41. Linear regression analysis of antimony results from filtered water samples analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS)

........................................................................................................... 69 A42. Linear regression analysis of antimony results from whole-water recoverable digestates analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS)

................................................................................. 70 A43. Linear regression analysis of selenium results from filtered water samples analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS)

........................................................................................................... 71 A44. Linear regression analysis of selenium results from whole-water recoverable digestates analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS)

................................................................................. 72 A45. Linear regression analysis of silicon (as SiO 2 

### ) results from filtered water samples analyzed by inductively coupled plasma–atomic emission spectrometry (ICP–AES) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS)

................................................................................. 73 A46. Linear regression analysis of silicon (as SiO 2 

### ) results from whole-water recoverable digestates analyzed by inductively coupled plasma–atomic emission spectrometry (ICP–AES) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS)

.................................................................. 74

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A47. Linear regression analysis of strontium results from filtered water samples analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS)

........................................................................................................... 75 A48. Linear regression analysis of strontium results from whole-water recoverable digestates analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS)

........................................................................................................... 76 A49. Linear regression analysis of thallium results from filtered water samples analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS)

........................................................................................................... 77 A50. Linear regression analysis of thallium results from whole-water recoverable digestates analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS)

........................................................................................................... 78 A51. Linear regression analysis of uranium results from filtered water samples analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS)

........................................................................................................... 79 A52. Linear regression analysis of uranium results from whole-water recoverable digestates analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS)

........................................................................................................... 80 A53. Linear regression analysis of vanadium results from filtered water samples analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS)

........................................................................................................... 81 A54. Linear regression analysis of vanadium results from whole-water recoverable digestates analyzed by inductively coupled plasma–atomic emission spectrometry (ICP–AES) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS)

.................................................................. 82 A55. Linear regression analysis of tungsten results from filtered water samples analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS)

........................................................................................................... 83 A56. Linear regression analysis of tungsten results from whole-water recoverable digestates analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS)

........................................................................................................... 84 A57. Linear regression analysis of zinc results from filtered water samples analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS)

........................................................................................................... 8 5 A58. Linear regression analysis of zinc results from whole-water recoverable digestates analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS)

........................................................................................................... 8 6

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# Tables

1. Codes for elements in water, biota, and sediment and for arsenic species in water samples determined by collision/reaction cell inductively coupled plasma–mass spectrometry.

....................................................................................... 3 2. Method detection limits for elements and species determined using collision/reaction cell inductively coupled plasma–mass spectrometry.

........................... 4 3. Potential molecular ion interferences for elements determined using collision/reaction cell inductively coupled plasma–mass spectrometry.

........................... 8 4. Effectiveness of using a collision/reaction cell gas for the elimination of molecular ion interferences.

....................................................................................................... 9 5. Typical operating characteristics for collision/reaction cell inductively coupled plasma–mass spectrometry

...................................................................................... 12 6. Long-term bias and variability of results from aqueous standard reference materials using collision/reaction cell inductively coupled plasma–mass spectrometry.

..................................................................................................... 15 7. Long-term bias and variability for the analysis of reagent water spiked with analyte concentrations in the lower one-third of the normal calibration range using collision/reaction cell inductively coupled plasma–mass spectrometry.

..................................................................................................... 17 8. Long-term bias and variability for the analysis of reagent water spiked with analyte concentrations at one-third and two-thirds of the normal calibration range using collision/reaction cell inductively coupled plasma–mass spectrometry.

..................................................................................................... 18 9. Long-term bias and variability for the analysis of surface water spiked with analyte concentrations at one-third and two-thirds of the normal calibration range using collision/reaction cell inductively coupled plasma–mass spectrometry.

..................................................................................................... 19 10. Long-term bias and variability for the analysis of ground water spiked with analyte concentrations at one-third and two-thirds of the normal calibration range using collision/reaction cell inductively coupled plasma–mass spectrometry.

..................................................................................................... 20 11. Linear regression results for filtered natural-water samples analyzed using collision/reaction cell inductively coupled plasma–mass spectrometry and other spectrometric methods.

.......................................................................................... 21 12. Linear regression results for unfiltered natural-water digestates analyzed using collision/reaction cell inductively coupled plasma–mass spectrometry and other spectrometric methods.

.......................................................................................... 22 13. Bias and variability of results for digested biological standard reference materials analyzed by collision/reaction cell inductively coupled plasma–mass spectrometry.

..................................................................................................... 23

## CONVERSION FACTORS, ABBREVIATED WATER-QUALITY UNITS, **ADDITIONAL ABBREVIATIONS, AND DEFINITIONS**

**Multiply By**  **To obtain** centimeter (cm) 3.94 x 10 -1 inch millimeter (mm) 3.94 x 10 -2 inch micrometer ( μ m) 3.94 x 10 -5 inc h **Mass** gram (g) 3.53 x 10 -2 ounce, avoirdupois milligram (mg) 3.53 x 10 -5 ounce, avoirdupois microgram (μg) 3.53 x 10 -8 ounce, avoirdupois **Volume** liter (L) 2.64 x 10 -1 gallon milliliter (mL) 2.64 x 10 -4 gallon microliter (μL) 2.64 x 10 -7 gallon
Degree Celsius (°C) may be converted to degree Fahrenheit (°F) by using the following equation: °F = 9/5 (°C) + 32 

### Abbreviated water-quality units used in this report:

μg/g micrograms per gram μg/L micrograms per liter μL/min microliters per minute μS/cm microsiemens per centimeter at 25oC mg/g milligrams per gram mg/L milligrams per liter mL/min milliliters per minute


### Other abbreviations used in this report:
ASTM American Society for Testing and Materials cICP–MS collision/reaction cell inductively coupled plasma–mass spectrometry GF–AAS graphite furnace–atomic absorption spectrometry HPLC high-performance liquid chromatography ICP–MS inductively coupled plasma–mass spectrometry ICP–AES inductively coupled plasma–atomic emission spectrometry LT–MDL long-term method detection level MDL(s) method detection limit(s) m/z mass-to-charge ratio NIST National Institute of Standards and Technology

### xi

**Other abbreviations used in this report (Continued):**
NWQL National Water Quality Laboratory OctP octapole P/A pulse/analog factor QP quadrupole SRM standard reference material SRWS(s) U.S. Geological Survey standard reference water sample(s) USGS U.S. Geological Survey % Bias percent error between the expected concentration and the experimental mean concentration % RSD percent relative standard deviation ≥ greater than or equal to % percent


### ± plus or minus



### Concentrations of chemical constituents in water are given either in milligrams per liter (mg/L) or micrograms per liter ( μ g/L). Concentrations of chemical constituents in solid digestates are given either in milligrams per gram (mg/g) or micrograms per gram ( μ g/g), dry weight.

# DETERMINATION OF ELEMENTS IN NATURAL-WATER, **BIOTA, SEDIMENT, AND SOIL SAMPLES USING COLLISION/REACTION CELL INDUCTIVELY COUPLED**  **PLASMA–MASS SPECTROMETRY**

By John R. Garbarino, Leslie K. Kanagy, and Mark E. Cree


# Abstract
A new analytical method for the determination of ele

ments in filtered aqueous matrices using inductively coupled plasma–mass spectrometry (ICP–MS) has been implemented at the U.S. Geological Survey National Water Quality Labo

ratory that uses collision/reaction cell technology to reduce molecular ion interferences. The updated method can be used to determine elements in filtered natural-water and other filtered aqueous matrices, including whole-water, biota, sediment, and soil digestates. Helium or hydrogen is used as the collision or reaction gas, respectively, to eliminate or substantially reduce interferences commonly resulting from sample-matrix composition. Helium is used for molecular ion interferences associated with the determination of As, Co, Cr, Cu, K, Mg, Na, Ni, V, W and Zn, whereas hydrogen is used for Ca, Fe, Se, and Si. Other elements that are not affected by molecular ion interference also can be determined simply by not introducing a collision/reaction gas into the cell. Analy

sis time is increased by about a factor of 2 over the previous method because of the additional data acquisition time in the hydrogen and helium modes. Method detection limits for As, Ca, Co, Cr, Cu, Fe, K, Mg, Na, Ni, Se, Si (as SiO 2 

### ), V, W, and Zn, all of which use a collision/reaction gas, are 0.06 microgram per liter ( μ g/L) As, 0.04 milligram per liter (mg/L) Ca, 0.02 μ g/L Co, 0.02 μ g/L Cr, 0.04 μ g/L Cu, 1 μ g/L Fe, 0.007 mg/L K, 0.009 mg/L Mg, 0.09 mg/L Na, 0.05 μ g/L Ni, 0.04 μ g/L Se, 0.03 mg/L SiO 2 

### , 0.05 μ g/L V, 0.03 μ g/L W, and 0.04 μ g/L Zn. Most method detection limits are lower or relatively unchanged compared to earlier methods except for Co, K, Mg, Ni, SiO 2 

### , and Tl, which are less than a factor of 2 higher. Percentage bias for samples spiked at about one-third and two-thirds of the concentration of the highest calibration standard ranged from –8.1 to 7.9 percent for reagent water, –14 to 21 percent for surface water, and –16 to 16 percent for ground water. The percentage bias for reagent water spiked at trace-element concentrations of 0.5 to 3 μ g/L averaged 4.4 percent with a range of –6 to 16 percent, whereas the average percentage bias for Ca, K, Mg, Na, and SiO 2 

### was 1.4 percent with a range of –4 to 10 percent for spikes of 0.5 to 3 mg/L. Elemental results for aqueous standard reference materials compared closely to the certified concentrations; all ele

ments were within 1.5 F-pseudosigma of the most probableconcentration. In addition, results from 25 filtered naturalwater samples and 25 unfiltered natural-water digestates were compared with results from previously used methods using linear regression analysis. Slopes from the regression analy

ses averaged 0.98 and ranged from 0.87 to 1.29 for filtered natural-water samples; for unfiltered natural-water digestates, the average slope was 1.0 and ranged from 0.83 to 1.22. Tests showed that accurate measurements can be made for samples having specific conductance less than 7,500 microsiemens per centimeter ( μ S/cm) without dilution; earlier ICP–MS meth

ods required dilution for samples with specific conductance greater than 2,500 μ S/cm.


# Introduction
Inductively coupled plasma–mass spectrometry (ICP– MS) has been used to determine elements in natural-water samples at the U.S. Geological Survey National Water Quality Laboratory since the early 1990s (Faires, 1993; Garbarino and Taylor, 1994; Garbarino and Struzeski, 1998; Garbarino, 1999; Garbarino, 2000; Garbarino and others, 2002). Methods have been updated over the years to document changes in data acquisition modes, to expand the number of elements deter

mined, and to expand the types of matrices analyzed. This new ICP–MS method was implemented to use recent advances in collision/reaction cell technology that reduce molecular ion interference resulting in improved accuracy and in expanded scope. A molecular ion interferes when its mass cannot be resolved from the mass of the element of interest because of limitations on the resolution of the quadrupole mass

### spectrometer. The most prominent molecular-ion interfer

ences are associated with oxide and hydroxide species arising from matrix elements in the sample (for details, see Horlick and Montaser, 1998). One example of such interference is 35 

### Cl 16 

### O + 

### on the determination of 51 

### V + 

### . Other molecular-ion interferences, such as 40 

### Ar 35 

### Cl + 

### on 75 

### As + 

### and 40 

### Ar 23 

### Na + 

### on 63 

### Cu + 

### , are associated with elements in the plasma and sample matrix. Before the introduction of collision/reaction cell tech

nology, such interference corrections were commonly made by measuring the signal at an associated interference-free iso

tope and subtracting the fraction corresponding to the interfer

ence from the signal of the quantifying isotope. Although this approach was fairly successful, analyte concentrations in the micrograms-per-liter range likely were to become more negatively biased with increasing concentrations of matrix interferents. Alternatively, the formation of oxide species could be reduced by using cold plasma conditions or by using a different elemental isotope whenever possible. However, either approach usually compromised the sensitivity of the analysis. Using a collision/reaction cell system with an ICP–MS reduces molecular ion interferences through either collisional or reactional processes. Helium is used as the cell gas to promote collisional dissociation and energy discrimination of molecular ions that cause interference. A molecular ion at the same nominal mass-to-charge ratio (m/z) and kinetic energy as an analyte ion experiences more collisions because of its larger cross-sectional area. As a result of these colli

sions, the kinetic energy of the molecular ion is reduced, and it is rejected by the cell, whereas the analyte ion is transmit

ted through the quadrupole to the detector. When hydrogen is used as the cell gas, simple reactions with argon-basedmolecular ions take place through charge-, proton-, or atomtransfer processes. Analyte ions generally do not react with hydrogen; therefore, there is no loss in analyte signal. Reac

tion processes can produce new molecular ions, principally hydrides of the original molecular-ion interference. However, such species have low kinetic energies and usually do not interfere. 

## Purpose and Scope This report describes a new method for the determination of As, Co, Cr, Cu, Ni, Se, V, and Zn in filtered water, unfil

tered water digestates, biota digestates, sediment digestates, and soil digestates using collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS). In addition, other elements, such as Ca, Fe, K, Mg, Na, Si, and W that were not determined routinely by earlier ICP–MS methods, have been added to the method. Furthermore, the method can be used to determine arsenic species using high-performance liquid chromatography (HPLC) for separation and cICP–MS for detection. Elements that were determined in earlier ICP–MS methods and that are not affected by molecular ion interference also are determined by cICP–MS by simply not introducing hydrogen or helium into the gas cell. New labora

tory codes and parameter codes are not needed for Ag, Al, B, Ba, Be, Cd, Li, Mn, Mo, Pb, Sb, Sr, Tl, and U because the plasma conditions, acquisition characteristics, and analytical performance for such elements are not drastically different from earlier ICP–MS methods that did not use reaction/colli

sion cell technology. Information is provided in this report to:

Establish the method detection limits (MDLs) for all elements determined using the cICP–MS method. Evaluate the capability of collision/reaction cell tech

nology to reduce molecular ion interferences on the determination of Ag, Al, As, Ca, Cd, Co, Cr, Cu, Fe, K, Mg, Mn, Na, Ni, Se, Si, V, W, and Zn. Review sample dilution guidelines using spiked field samples having specific conductance ≥ 2,000 μ S/cm. Determine the analytical variability of measurements in laboratory reagent water as a function of analyte concentration. Determine the bias and variability of the cICP–MS method using results from standard reference materials. Validate the cICP–MS method for the determination of elements in ground-water, surface-water, and laboratory reagent-water matrices. Compare the bias and variability of cICP–MS with results from other analytical methods for 25 filtered natural-water samples and 25 whole-water digestates. The method described was developed by the U.S. Geological Survey (USGS) for use at the National Water Quality Laboratory (NWQL). This method replaces ICP–MS method I-2477-92 for the determination of dissolved As, Co, Cr, Cu, Ni, Se, V, and Zn (Faires, 1993; Garbarino, 1999), methods I-4471-97 and I-4472-97 for the determination of whole-water recoverable As, Co, Cr, Cu, Ni, Se, V, and Zn (Garbarino, 2000; Garbarino and Struzeski, 1998), methods I-1190-02, I-2191-02, I-2193-02, and I-2192-02 for arsenic speciation (Garbarino and others, 2002). The new method was implemented at the NWQL in October 2005. 

# Analytical Method
New laboratory codes, parameter codes, and method codes for collision/reaction cell inductively coupled plasma– mass spectrometry (cICP–MS) are listed in table 1 for As (speciated and unspeciated), Co, Cr, Cu, Ni, Se, V, and Zn in different sample matrices. New codes also were established for Ca, Mg, Fe, K, Na, Si (as silica), and W for filtered and unfiltered water matrices. Laboratory codes, parameter codes, and method codes for Ag, Al, B, Ba, Be, Cd, Li, Mn, Mo, Pb, •

•

•

•

•

•

• ** Determination of Elements Using Collision/Reaction Cell ICP–MS** 

### Sb, Sr, Tl, and U, elements not affected by molecular ion interference, remain unchanged for each type of sample matrix. 

## Application and Method Detection Limits The method described in this report can be used to determine a wide range of elements in filtered water, unfiltered water digestates, biological digestates, sediment digestates, and soil digestates. The collision/reaction gas is used when determining As (speciated and unspeciated), Ca, Co, Cr, Cu, Fe, K, Mg, Na, Ni, Se, Si, V, W, and Zn. Method detection limits are 0.06 microgram per liter ( μ g/L) As, 0.04 milligram per liter (mg/L) Ca, 0.02 μ g/L Co, 0.02 μ g/L Cr, 0.04 μ g/L Cu, 1 μ g/L Fe, 0.007 mg/L K, 0.009 mg/L Mg, 0.09 mg/L Na, 0.05 μ g/L Ni, 0.04 μ g/L Se, 0.03 mg/L SiO 2 

### , 0.05 μ g/L V, 0.03 μ g/L W, and 0.04 μ g/L Zn (see table 2). Most method detection limits are lower or relatively unchanged compared to earlier methods except for Co, K, Mg, Ni, SiO 2 

### , and Tl, which are less than a factor of 2 higher. Other elements (Ag, Al, B, Ba, Be, Cd, Li, Mn, Mo, Pb, Sb, Sr, Tl, and U) that have been determined using previous ICP–MS methods can be

**Element Lab code**  **P code Lab code**  **P code** Elements, water, filtered,

cICP–MS, I-2020-05 Elements, water, unfiltered, cICP–MS, I-4020-05 As, μ g/L 3122 01000 H 3123 01002 H Ca, mg/L 2916 00915 I 2917 00916 D Co, μ g/L 3124 01035 I 3125 01037 I Cr, μ g/L 3126 01030 J 3127 01034 I Cu, μ g/L 3128 01040 I 3129 01042 I Fe, μ g/L 2974 01046 I 2975 01045 D K, mg/L 3014 00935 E 3015 00937 D Mg, mg/L 2984 00925 I 2985 00927 D Na, mg/L 3048 00930 I 3049 00929 D Ni, μ g/L 3130 01065 I 3131 01067 J Se, μ g/L 3132 01145 G 3133 01147 H SiO 2 , mg/L 3046 00955 J 3047 00956 B V, μ g/L 3134 01085 G 3135 01087 D W, μ g/L 3136 01155 A 3137 01154 A Zn, μ g/L 3138 01090 I 3139 01092 E Elements, biota,

cICP–MS, I-9020-05 Elements, sediment or soil, recoverabe, cICP-MS, I-5020-05 As, μ g/g 6055 49247 C 3144 64847 A Co, μ g/g 6056 49250 D 3145 01038 E Cr, μ g/g 6057 49240 C 3146 01029 E Cu, μ g/g 6058 49241 C 3147 01043 E Ni, μ g/g 6059 49253 D 3148 01068 D Se, μ g/g 6060 49254 C 3149 64848 A V, μ g/g 6061 49465 C 3150 64849 A Zn, μ g/g 6062 49245 C 3151 01093 C **Species Lab code**  **P code** Arsenic species, water, filtered, field

separation, cICP–MS, I-2197-05 Arsenite [As(III)], H 3 AsO 3 3140 62452 E Arsenate [As(V)], H 2 AsO 4 - 3140 62453 E
Arsenic species, water, filtered, laboratory separation, malonate/acetate mobile phase, cICP–MS, I-2196-05 Arsenite [As(III)], H 3 AsO 3 3141 62452F Arsenate [As(V)], H 2 AsO 4 - 3141 62453 F
Arsenic species, water, filtered, laboratory separation, phosphate mobile phase with arsine generation, cICP–MS, I-2195-05 Arsenite [As(III)], H 3 AsO 3 3142 62452 G Arsenate [As(V)], H 2 AsO 4 - 3142 62453 G Monomethylarsonate (MMA),

(CH 3 )HAsO 3 - 3142 62454 E
Dimethylarsinate (DMA),

(CH 3 ) 2 HAsO 2 3142 62455 E
Arsenic species, water, filtered, laboratory separation, nitric acid mobile phase, cICP–MS, I-2193-05 Arsenite [As(III)], H 3 AsO 3 3143 62452 H Arsenate [As(V)], H 2 AsO 4 - 3143 62453 H Monomethylarsonate (MMA),

(CH 3 )HAsO 3 - 3143 62454 F
Dimethylarsinate (DMA),

(CH 3 )HAsO 2 3143 62455 F 

### Analytical Method ****

**Table 1.** Codes for elements in water, biota, and sediment and for arsenic species in water samples determined by collision/reaction cell inductively coupled plasma-mass spectrometry. [cICP-MS, collision/reaction cell inductively coupled plasma-mass spectrometry; I-xxxx-xx, method number; Lab code, laboratory code; P code, parameter code and method code; μ g/L, micrograms per liter; mg/L, milligrams per liter; μ g/g, micrograms per gram dry weight]

### determined with similar performance using this method. The typical linear calibration range extends from the method detection limit (MDL) to 100 μg/L for each trace element or species. Selected elements like Al, Ba, Mn, Sr, and Zn are calibrated up to 2,500 μg/L. Elements such as Ca, K, Mg, and Na normally are calibrated up to 100 mg/L, whereas Si and Fe are calibrated up to 50 mg/L and 1,000 μg/L, respectively. The method detection limits for all elements and species determined in filtered-water matrices using cICP–MS and long-term method detection levels (LT–MDL) from earlier methods are listed in table 2. These limits were calculated using guidelines of the U.S. Environmental Protection Agency (2000). Most method detection limits are lower or relatively unchanged compared to earlier methods except for Co, K, Mg, Ni, SiO 2 

### , and Tl, which are less than a factor of 2 higher. Method detection limits for unfiltered water digestates are similar to those listed in table 2 except for vanadium and arse

nic, which are about a factor of 10 lower than earlier methods. Method detection limits (in micrograms per gram, dry weight) for elements determined in biota, sediment, and soil digestates can be estimated by multiplying the limits in table 2 by the digestate volume (typically 0.100 L) and dividing it by the sample dry weight (typically 0.5 g). The linear calibration range can be extended when the analog stage of the detector is calibrated, otherwise samples that have elemental concen

trations that exceed the upper calibration standard must be diluted or, in the case of arsenic speciation, a smaller sample volume can be injected. In addition, samples with specific conductance greater than 7,500 μ S/cm need to be diluted prior to analysis. 

## Interferences Spectral interferences associated with isobaric ions and molecular ions can affect the accuracy of elemental analysis using ICP–MS. Such interferences have been documented in the literature (Tan and Horlick, 1986; Horlick and Mon

taser, 1998). Molecular ion interferences evolve from the argon plasma and elements composing the sample matrix. Molecular ions that are potential isobaric interferences for the elements determined are listed in table 3. Such interferences are greatly reduced or eliminated for ICP–MS instruments that use a collision/reaction cell without using correction equations. By introducing a gas into the cell, either He or H 2 

### in this method, an interfering molecular ion is isolated from the analyte ion through collisional or reactional interac

tions, thereby improving the accuracy of the determination of selected elements. Test solutions containing analytes and elements associated with molecular ion interferences were analyzed **Table 2** 

**.** Method detection limits for elements and species determined using collision/reaction cell inductively coupled plasma–mass spectrometry. [Analyte, concentrations are in micrograms per liter unless otherwise noted; m/z, mass-to-charge ratio; Mode, either normal (none), He (helium), or H 2 (hydrogen) cell gas; MDL, method detection limit; LT–MDL, long-term method detection level as of 2005; mg/L, milligrams per liter; cICP–MS, col

lision/reaction cell inductively coupled plasma–mass spectrometry; ICP–MS, inductively coupled plasma–mass spectrometry; ICP–AES, inductively coupled plasma–atomic emission spectrometry; GF–AAS, graphite furnace– atomic absorption spectrometry; SiO 2 , determined as silicon (Si) but reported as silica (SiO 2 ); na, not applicable]


### Analyte **m/z cICP–MS**  **Previous method Mode**  **MDL LT–MDL**  **Technique** Ag 107 Normal 0.07 0.1 ICP–MS Al 27 Normal 0.4 0.8 ICP–MS As 75 He 0.06 0.1 ICP–MS B 11 Normal 2 4 ICP–MS Ba 137 Normal 0.06 0.1 ICP–MS Be 9 Normal 0.02 0.03 ICP–MS Ca, mg/L 40 H 2 0.04 0.02 ICP–AES Cd 111 Normal 0.02 0.02 ICP–MS Co 59 He 0.02 0.008 ICP–MS Cr 52 He 0.02 0.4 GF–AAS Cu 63 He 0.04 0.2 ICP–MS Fe 56 H 2 1 3 ICP–AES K, mg/L 39 He 0.007 0.005 ICP–AES Li 7 Normal 0.1 0.3 ICP–MS Mg, mg/L 24 He 0.009 0.004 ICP–AES Mn 55 Normal 0.07 0.1 ICP–MS Mo 95 Normal 0.06 0.2 ICP–MS Na, mg/L 23 He 0.09 0.1 ICP–AES Ni 60 He 0.05 0.03 ICP–MS Pb 206, 207, 208 , Normal 0.01 0.04 ICP–MS

Sb 121 Normal 0.02 0.1 ICP–MS Se 78 H 2 0.04 0.2 ICP–MS SiO 2 ,

mg/L 28 H 2 0.03 0.02 ICP–AES

Sr 88 Normal 0.08 0.2 ICP–MS Tl 205 Normal 0.03 0.02 ICP–MS U 238 Normal 0.002 0.02 ICP–MS V 51 He 0.05 0.07 ICP–MS W 182 He 0.03 na na Zn 66 He 0.04 0.3 ICP–MS 

###  **Determination of Elements Using Collision/Reaction Cell ICP–MS**

### Analytical Method **** tions was eliminated for the two types of dissolved organic carbon tested. The average chromium concentrations mea

sured in the Suwannee River and Big Soda Lake solutions were 22.8±0.2 and 22.6±0.5 μ g/L, respectively. Other potential molecular ion interferences that are listed in table 3 also were evaluated. The percentage spike recovery for each analyte in the presence of elements that are associ

ated with molecular ion interference was determined. Spike concentrations ranged from 5 to 30 μ g/L for trace elements and 0.5 mg/L for Ca, K, Mg, Na, and Si. Concentrations ranged from 2 mg/L for interfering trace elements like Mo to 500 mg/L for major elements like Ca. Based on the percent

age spike recovery results, only Co, Fe, Ni, and Zn required the use of a cell gas to eliminate molecular ion interference (see table 4). For example, if a cell gas was not used, 3 μ g/L of Co would be measured in the presence of 500 mg/L Ca because of the 43 

### Ca 16 

### O + 

### interference. Molecular ions 29 

### Si 27 

### Al + 

### and 40 

### Ca 16 

### O + 

### severely affected the determination of Fe when hydrogen was not used making it difficult to estimate the degree of interference. All the other interference solutions indicated negligible bias for the interferent concentration range tested. For some elements where negligible bias was indicated, no cell gas is used during routine analyses (table 2) because the interferent concentration tested is rarely exceeded (for example, the interferences on Ag and Cd, see table 3), or the element being measured is normally present at concen

trations higher than trace levels (for example, Al and Mn). Nevertheless, the use of a cell gas might be required when interferent concentrations are greater than those tested. Interferences also may be associated with aqueous sample introduction and ionization processes. Dissolved-solid concentrations affect nebulization efficiency and suppress ion

ization. Typical limitations for dissolved-solid concentration for most pneumatic nebulizers range from 0.1 to 0.3 percent; some high dissolved-solid nebulizers do not have this limita

tion but also have higher sample flow rates. High dissolvedsolid concentrations associated with easily ionized cations like sodium affect the ionization of analyte ions. Dissolved-solid concentrations of 0.1 to 0.3 percent translate into estimated specific conductances of between 4,000 and 6,000 μ S/cm in natural water (Hem, 1986). Percentage recoveries in sample matrices with increasing specific conductance were used to establish the effect of specific conductance on cICP–MS analyses for various elements extending the mass range (see figure 4). The variability for elements heavier than 51 

### V aver

aged less than 3 percent over the duration of the experiment (about 17 hours); the variability for lighter elements ranged from 5 to 8 percent. These test-sample results suggest that samples having specific conductances less than 7,500 μ S/cm can be analyzed directly with acceptable bias and variability. In previous ICP–MS methods, samples with specific conduc

tances greater than 2,500 μ S/cm required dilution (Faires, 1993; Garbarino and Taylor, 1994; Garbarino and Struzeski,1998; Garbarino, 1999, 2000). The median specific conductance for samples submitted to NWQL in 2004 was **Table 2** 

**.** Method detection limits for elements and species determined using collision/reaction cell inductively coupled plasma–mass spectrometry.—Continued [HPLC/cICP–MS; high-performance liquid chromatography/collision/reac

tion cell inductively coupled plasma–mass spectrometry using a phosphate mobile phase and hydride generation; Analyte, concentrations are in micro

grams per liter; m/z, mass-to-charge ratio; Mode, He (helium), cell gas; MDL, estimated method detection limit based on non-chromatographic determina

tion; LT–MDL, long-term method detection level as of 2005; HPLC/ICP–MS, high-performance liquid chromatography/inductively coupled plasma–mass spectrometry]


### Analyte **m/z HPLC/cICP–MS**  **Previous method Mode**  **MDL LT–MDL**  **Technique** As(III) 75 He 0.09 0.3 HPLC/ ICP–MS As(V) 75 He 0.1 0.4 HPLC/ ICP–MS MMA 75 He 0.2 0.6 HPLC/ ICP–MS DMA 75 He 0.09 0.3 HPLC/ ICP–MS 

### to evaluate the performance of cICP–MS. The effects of increasing concentrations of chloride on the recovery of 5 μ g/ L arsenic and vanadium are shown in figures 1 and 2, respec

tively. Two different sources of chloride, calcium chloride (CaCl 2 

### ), and hydrochloric acid (HCl) were investigated. The data corresponding to measurements made without using the He cell gas shows an apparent increase in 75 

### As + 

### concentration as a result of 40 

### Ar 35 

### Cl + 

### . Previous ICP–MS methods cor

rected for such interference by using equations based on other measurements, whereas no correction equations are needed with the new method when He is used. The advantage of this approach is the elimination of errors resulting from measuring low analyte concentration in the presence of high interferent concentration. The average arsenic concentrations measured by the new method in the CaCl 2 

### and HCl solutions having up to 5,000 mg/L chloride were 5.38±0.09 and 5.38±0.08 μ g/L, respectively. Similar results are shown for vanadium (see fig. 2). When He is used, the 35 

### Cl 16 

### O + 

### ion is eliminated and does not contribute to the vanadium signal. The average vanadium concentration measured in the CaCl 2 

### solution was 5.06±0.08 μ g/L, whereas the concentration in the HCl was 5.2±0.4 μ g/L. The median chloride concentration for samples submitted to NWQL in 2004 was 16 mg/L; 95 percent of the samples had chloride concentration less than 370 mg/L. The effect of increasing concentrations of carbon on the recovery of about 20 μ g/L chromium is shown in figure 3. Solutions containing dissolved organic carbon from the Suwannee River (Florida) and Big Soda Lake (Nevada) were used to test the effectiveness of cICP–MS in eliminating the 40 

### Ar 12 

### C + 

### interference on 52 

### Cr + 

### . The dissolved organic car

bon concentration ranged from 0 to about 20 mg/L; the maxi

mum concentration tested is at least a factor of 10 greater than most samples submitted to NWQL. The results show that carbon molecular ion interference on chromium determina-0 1 , 0 0 0 2 , 0 0 0 3 , 0 0 0 4 , 0 0 0 5 , 0 0 0 0 5 1 0 1 5 2 0 2 5 3 0

0 5 1 0 1 5 2 0 2 5 3 0

F r o m H C lARSENICCONCENTRATION,in****g/L

C H L O R I D E C O N C E N T R A T I O N , i n m g / L W i t h c e l l g a s W i t h o u t c e l l g a s F r o m C a C l 2 W i t h c e l l g a s W i t h o u t c e l l g a s 

### Figure 1. The effect of increasing concentrations of chloride from two sources on the determination of arsenic at mass-to-charge ratio 75. The graphs show that by using helium as the cell gas the molecular ion interference from chloride [ 40 

### Ar 35 

### Cl + 

### ] is minimized. The chloride concentration was about equal in each source. Error bars correspond to the standard deviation for three replicate determinations. Arsenic and chloride concentrations are in micrograms per liter (μg/L) and milligrams per liter (mg/L), respectively.

**Figure 2** 

**.** The effect of increasing concentrations of chloride from two sources on the determination of vanadium at mass-to-charge ratio 51. The graphs show that by using helium as the cell gas the molecular ion interference from chloride [ 35 

### Cl 16 

### O + 

### ] is minimized. The chloride concentration was about equal in each source. Error bars correspond to the standard deviation for three replicate determinations. Vanadium and chloride concentrations are in micrograms per liter (μg/L) and milligrams per liter (mg/L), respectively. 0 5 1 0 1 5 2 0 2 5 3 0

0 1 , 0 0 0 2 , 0 0 0 3 , 0 0 0 4 , 0 0 0 5 , 0 0 0

0 5 1 0 1 5 2 0 2 5 3 0



### C H L O R I D E C O N C E N T R A T I O N , i n m g / L W i t h c e l l g a s W i t h o u t c e l l g a sVANADIUMCONCENTRATION,in****g/L 

### F r o m C a C l 2



### F r o m H C l W i t h c e l l g a s W i t h o u t c e l l g a s 

###  **Determination of Elements Using Collision/Reaction Cell ICP–MS**

### Analytical Method ****

**Figure 4** 

**.** The variability in percentage recovery for selected elements extending the operational mass range as a function of increasing specific conductance. Specific conductances are in microsiemens per centimeter (μS/cm) at 25 degrees Celsius. The variability for elements heavier than vanadium averaged less than 3 percent over the range of specific conductance; the variability for lighter elements ranged from 5 to 8 percent. The data points representthe average for spiked naturalwater samples analyzed in triplicate over a 17-hour period; the average standard deviation was 2.6 percent for elements with masses greater than vanadium and 16 percent for lighter elements. **Figure 3** 

**.** The effect of increasing concentrations of dissolved organic carbon from two natural-water sources on the determination of chromium at mass-to-charge ratio 52. The graphs show that by using helium as the cell gas the molecular ion interference from carbon [ 40 

### Ar 12 

### C + 

### ] is minimized. Error bars correspond to the standard deviation for three replicate determinations. Chromium and dissolved organic carbon concentrations are in micrograms per liter (μg/L) and milligrams per liter (mg/L), respectively.

0 5 1 0 1 5 2 0 1 5 1 8 2 1 2 4 2 7 3 0 1 5 1 8 2 1 2 4 2 7 3 0



### S u w a n n e e R i v e rCHROMIUMCONCENTRATION,inμg/L



### D I S S O L V E D O R G A N I C C A R B O N , i n m g / L B i g S o d a L a k e

2 , 0 0 0 3 , 0 0 0 4 , 0 0 0 5 , 0 0 0 6 , 0 0 0 7 , 0 0 0 8 , 0 0 0VARIABILITYINELEMENTALPERCENTAGERECOVERY,INARBITRARYUNITS



## S P E C I F I C C O N D U C T A N C E , i n **** 

## S / c m U
P b

B a S b C d M o A s C u V
B e

### Table **3**

**.** Potential molecular ion interferences for elements determined using collision/reaction cell inductively coupled plasma–mass spectrometry. [All superscripted numbers are nominal mass-to-charge ratios]


### Ion **Molecular ion Ion**  **Molecular ion Ion**  **Molecular ion**

23 

### Na + 7 

### Li 16 

### O + 52 

### Cr + 40 

### Ar 12 

### C + 35 

### Cl 16 

### OH + 36 

### Ar 16 

### O +

51 

### VH + 75 

### As + 40 

### Ar 35 

### Cl + 48 

### Ti 27 

### Al + 63 

### Cu 12 

### C +

24 

### Mg + 12 

### C 2 + 23 

### NaH + 55 

### Mn + 40 

### Ar 14 

### NH + 28 

### Si 27 

### Al + 39 

### K 16 

### O + 54 

### FeH + 54 

### CrH + 78 

### Se + 77 

### SeH + 40 

### Ar 38 

### Ar + 66 

### Zn 12 

### C +

27 

### Al + 12 

### C 14 

### NH + 26 

### MgH + 11 

### B 16 

### O + 13 

### C 14 

### N + 12 

### C 15 

### N + 56 

### Fe + 40 

### Ar 16 

### O + 55 

### MnH + 40 

### Ca 16 

### O + 29 

### Si 27 

### Al + 44 

### Ca 12 

### C + 40 

### K 16 

### O + 107 

### Ag + 91 

### Zr 16 

### O +

28 

### Si + 14 

### N 2 + 27 

### AlH + 12 

### C 16 

### O + 59 

### Co + 58 

### FeH + 43 

### Ca 16 

### O + 41 

### K 18 

### O + 111 

### Cd + 95 

### Mo 16 

### O +

39 

### K + 38 

### ArH + 27 

### Al 12 

### C + 23 

### Na 16 

### O + 60 

### Ni + 44 

### Ca 16 

### O + 48 

### Ca 12 

### C + 23 

### Na 37 

### Cl + 43 

### Ca 16 

### OH + 182 

### W + 166 

### Er 16 

### O +

40 

### Ca + 40 

### Ar + 28 

### Si 12 

### C + 24 

### Mg 16 

### O +

40 

### K + 63 

### Cu + 40 

### Ar 23 

### Na + 31 

### P 16 

### O 2 + 51 

### V 12 

### C + 47 

### V 16 

### O +

51 

### V + 35 

### Cl 16 

### O + 39 

### K 12 

### C + 66 

### Zn + 34 

### S 16 

### O 2 + 33 

### S 2 + 54 

### Fe 12 

### C + 50 

### Cr 16 

### O + 50 

### Ti 16 

### O + 54 

### Cr 12 

### C + 

###  **Determination of Elements Using Collision/Reaction Cell ICP–MS**

### Analytical Method ****
**Table 4** 

**.** Effectiveness of using a collision/reaction cell gas for the elimination of molecular ion interferences. [Analyte, nominal elemental concentration; Interferent(s), elements associated with molecular ions that interfere with the analyte and the nominal concentration tested; Cell gas, N identifies an analyte that does not require the use of a cell gas for the interferent concentration tested and X identifies an analyte that requires a cell gas for accurate quantitation followed in parentheses by either the apparent analyte concentration, in micrograms per liter, associated with interferent concentration listed or an s indicating that the apparent analyte concentration could not be estimated because of severe molecular ion interference; mg/L, milligrams per liter; &, and] 

### Analyte **Interferent(s) Cell gas**  **Analyte Interferent(s)**  **Cell gas**

Ag Zr, 2 mg/L N Mg Na, 500 mg/L C, 50 mg/L N N Al Mg, 200 mg/L C & N, 50 mg/L N N Mn K, 200 mg/L Fe, 500 mg/L N N Ca Mg, 200 mg/L K, 200 mg/L C & Si, 50 mg/L N N N Ni Ca, 500 mg/L Ca & C, 100 mg/L Na, 500 mg/L Na & Cl, 500 mg/L X(14) X(13)

N N Cd Mo, 2 mg/L N
Se C & Zn, 50 mg/L N Co Ca, 500 mg/L Fe, 500 mg/L K, 200 mg/L X(3) N X( s ) Si Al, 200 mg/L C, 50 mg/L N N Cu Na, 500 mg/L P, 200 mg/L N N V K & C, 100 mg/L C & K, 50 mg/L N N Cr C, 50 mg/L N
Fe Al & Si, 200 mg/L Ca, 500 mg/L Ca & C, 100 mg/L K, 200 mg/L C & Ca, 50 mg/L X( s ) X( s ) X(8) X( s )

N W Er, 2 mg/L N

Zn Fe & C, 100 mg/L S, 200 mg/L C & Fe, 50 mg/L Ti, 2 mg/L N N N X(2)

K Al & C, 100 mg/L Na, 500 mg/L N N

### 398 μ S/cm; 95 percent of the samples had specific conduc

tances of less than 3,000 μ S/cm. 

## Instrumentation The instrumental operating conditions for the cICP–MS method are listed in table 5. The inductively coupled plasma operating characteristics are typical of those used in earlier methods. However, there are substantial differences in the sample introduction and ion optics in conjunction with the use of the collision/reaction cell. A pneumatic concentric nebulizer is used to introduce samples at a flow rate of 0.2 to 0.3 mL/min into a thermostatically controlled spray chamber. This introduction system minimizes sample volume require

ments, increases sample introduction efficiency, reduces instrumental drift, and reduces oxide and hydroxide molecular ions. The internal standards are introduced automatically through a junction tee (see fig. 5A). Most of the lens poten

tials and pole biases are similar regardless of whether a colli

sion gas is introduced; notable differences are the cell entrance and exit potentials and the quadrupole (QP) and octapole (OctP) biases (see table 5). Nominal hydrogen and helium flow rate in the gas cell is about 4 mL/min. Previous ICP–MS methods used substantially different sample-introduction sys

tems (nebulizer and spray chamber) and ion optics (see Faires, 1993; Garbarino and Taylor, 1994; Garbarino and Struzeski, 1998; Garbarino, 1999 and 2000; Garbarino and others, 2002). Minor changes were required for determining the dis

tribution of arsenic species using high-performance liquid chromatography (HPLC) in combination with cICP–MS instrumentation. An Agilent 1100 HPLC was used to separate the arsenic species with various anion exchange columns and mobile phases as described in the original methods (Garba

rino and others, 2002). No changes were needed for arsenic speciation methods that use hydride generation for sample introduction. However, there was a mismatch in flow rates between the HPLC (about 1 mL/min) and the microflow nebu

lizer (about 0.3 mL/min) for other arsenic speciation methods. The mismatch required using the junction tee that is usually used for introducing the internal standard to reduce flow into the nebulizer (see fig. 5B). Differences in data-acquisition characteristics, nebulizer flow rate, spray-chamber volume, and transfer-line lengths had negligible effects on the chro

matographic resolution and retention times. Refer to Agilent Technologies (2001, 2004a, 2004b) and NWQL Standard Operating Procedures INCM0458.0 (M.E. Cree, U.S. Geological Survey, written commun., 2005) and ID0359.1 (J.R. Garbarino, U.S. Geological Survey, written commun., 2005) for details of the operation and maintenance of the instrumentation used in this report. 

## Sample Collection, Preservation, Shipment, and **Holding Times** Samples must be collected and preserved using the protocols outlined in the USGS National Field Manual for the Collection of Water-Quality Data (U.S. Geological Survey, variously dated). Samples used for the determination of dis

solved elements in natural-water samples need to be filtered using either a 0.45-μm membrane capsule filter or in-line fil

ter, and the filtrate must be preserved using contaminant-free nitric acid. Samples used for the determination of recover

able elements in unfiltered water also must be preserved with contaminant-free nitric acid and digested using the in-bottle procedure (Hoffman and others, 1996). The prescribed hold

ing times for acid-preserved filtered and unfiltered samples stored in tightly capped polyethylene bottles for elemental determinations in this method is 6 months (U.S. Environmen

tal Protection Agency, 2005). Biota samples, including mollusks, fish, aquatic insects, crayfish, and aquatic plants, need to be collected and pro

cessed as outlined by Crawford and Luoma (1993). Samples are stored frozen in glass or polyethylene containers at –20°C. Frozen samples need to be shipped overnight on dry ice to the laboratory. The holding time for frozen samples analyzed for the elements determined in this method is 6 months from the time of collection (Crawford and Luoma, 1993). Biota samples are digested with nitric acid using a closed-vessel microwave digestion procedure (U.S. Environ

mental Protection Agency, 1996). The holding time for biota digestates has not been established but is expected to be the same as acid-preserved aqueous samples or sediment and soil digestates (6 months). Sediment and soil samples are collected using coring or other suitable techniques, stored in glass or polyethylene con

tainers, and shipped overnight on ice to the laboratory (U.S. Geological Survey, variously dated). In the laboratory, the samples are air-dried and sieved using a 2-mm plastic sieve (Fishman and Friedman, 1989). Sieved samples are stored in glass or polyethylene containers. The holding times for unprocessed and processed sediment and soil samples have not been established because total elemental concentrations will most likely not change. Various subsampling techniques, such as cone-and-quartering or riffle splitting, are used to obtain a representative subsample of the sieved material prior to digestion. Samples are digested with nitric acid using a closed-vessel microwave digestion procedure (U.S. Environ

mental Protection Agency, 1998); the digestion is typically not a total dissolution, therefore the results represent recov

erable concentrations. The recommended holding time for sediment and soil digestates is 6 months (U.S. Environmental Protection Agency, 2005). **10 Determination of Elements Using Collision/Reaction Cell ICP–MS** 

### Analytical Method **11**

**Figure 5** 

**.** Sample-flow paths used with new collision/reaction cell inductively coupled plasma–mass spectrometric methods. Panel A represents the sample-flow path used for the introduction of internal standard solution with filtered samples and filtered biota, sediment, and soil digestates. Panel B represents the sample-flow path used for arsenic speciation that reduces the flow rate from the high-performance liquid chromatograph (HPLC) to the level that is required by the microflow nebulizer. The pump speed is increased over that used in panel A so that the flow rate at the nebulizer is reduced from 1 milliliter per minute (mL/min) to about 0.3 mL/min. 

## To microflow ne bulizer Internal standard Orange/red tubing From autosampler White/white tubing To microflow nebulizer

Peristaltic pump

To waste white/white tubing ~1 mL/min from HPLC

Peristaltic pump 

# A

B Junction tee

Junction tee

### Table **5**

**.** Typical operating characteristics for collision/reaction cell inductively coupled plasma–mass spectrometry. [cICP–MS, collision/reaction cell inductively coupled plasma–mass spectrometer; Pa, pascal; ° C, degrees Celsius; %, percent; L/min, liters per minute; kPa, kilopascal; W, watts; mL/min, milliliters per minute; rpm, revolutions per minute; mm, millimeters; id, inside diameter; V, volts; <, less than; OctP, octapole; QP, quadrupole; RF, radio frequency]

**cICP–MS Typical setting (range)** 
Instrument Agilent 7500ce Forward power 1550 W (700–1600) Reflected power 4 W (<20) Analyzer pressure 3.33 x 10 -3 Pa (3 x 10 -4 to 2 x 10 -3 ) Carrier argon 1.00 L/min (0.8 to 1.3) Makeup argon None (0 to 1.0 L/min) Plasma argon 15 L/min (about 15) Auxiliary argon 0.9 L/min (0 to 1.0) Sampling depth 8 mm (7 to 10) Sample introduction Concentric nebulizer 0.3 mL/min (0.2 to 0.3) Quartz spray chamber 2°C Peristaltic pump 0.1 rpm, during data acquisition Sample tube white/white, 1.02 mm id Internal standard tube orange/red, 0.19 mm id Waste tube yellow/blue, 1.52 mm id Ion optics and collision/reaction cell Extract 1 0 V Extract 2 –133 V (–120 to –150) Omega bias –16 V (–15 to –40) OctP RF 161 V (160 to 200) Normal mode He mode H 2 mode Cell gas 0 mL/min 4.0 (2.5 to 5.5) 4.0 (3 to 6) Cell entrance –30 V (–30 to –10) –25 –25 QP focus 3 V (1 to 5) –8 –8 Cell exit –30 V (–30 to –8) –45 –45 OctP bias –6 V (–10 to –3) –18 –18 QP bias –3 V (–7 to 0.5) –13 –5 

### 1 **2 Determination of Elements Using Collision/Reaction Cell ICP–MS** 

### Analytical Method **1 3**  Filtered arsenic speciation samples are collected using the procedures outlined in the USGS National Field Manual for the Collection of Water-Quality Data (U.S. Geological Survey, variously dated). Samples are preserved with ethyl

enediaminetetraacetic acid and stored in opaque polyethylene bottles (U.S. Geological Survey, variously dated, specifically chap. A5.6.4). Samples that are submitted for speciation in the laboratory need to be shipped on ice and analyzed within 90 days of collection to ensure the accuracy of the results. The solid phase extraction cartridge and eluate for samples that are speciated in the field need to be shipped on ice to the laboratory within 30 days of collection. The cartridge needs to be extracted in the laboratory within 49 days of sample collection. The extract and eluate need to be analyzed within 6 months. 

## Calibration Standards and Other Solutions ASTM Type I reagent water (American Society for Test

ing and Materials, 2000, p. 10), acids, and reagents used in this method must be verified to have analyte concentrations less than the method detection limits. Calibration standards for elemental determinations are prepared from either com

mercially available single-element stock solutions or multi

element stock solutions. The concentrations in all solutions used need to be verified by using National Institute of Stan

dards and Technology (NIST) standards or standards that are traceable to NIST as a reference. Multielement calibration standards containing Ag, Al, As, B, Ba, Be, Ca, Cd, Co, Cr, Cu, Fe, K, Li, Mg, Mn, Mo, Na, Ni, Pb, Sb, Se, Si, Sr, Tl, U, V, W, and Zn are prepared by making appropriate dilutions of commercial stock solutions with reagent water acidified with nitric acid (0.4 percent by volume). Calibration standards for whole-water digestates are prepared in 0.4 percent nitric acid and 2 percent hydrochloric acid. The multielement standard containing Sb also must contain 0.1 percent hydrofluoric acid by volume as a preservative. Calibration concentrations are typically 10 and 100 μ g/L for all trace elements, whereas Al, Ba, Mn, Sr, and Zn use an additional standard at 2,500 μ g/L to extend the calibration range. Multielement calibration standards for Ca and Fe were prepared at 25 and 250 mg/L and 100 and 1,000 μ g/L, respectively, whereas K, Mg, Na, and SiO 2 

### were prepared at 10 and 100 mg/L. Several internal standard elements are introduced auto

matically into the sample stream to minimize sample matrix effects and instrumental drift (see fig. 5A). A multielement internal standard solution containing Li (highly enriched in lithium-6), Bi, Ce, Cs, Ge, In, Rh, Sc, Th, and Y at 1 mg/L is prepared by making appropriate dilutions of each stock solu

tion with reagent water acidified with nitric acid (0.4 percent by volume). The cICP–MS operating conditions are optimized daily by using a tuning solution composed of Ce, Co, Li, Mg, Th, and Y at 10 μ g/L each. The tuning solution was prepared by making appropriate dilutions of each stock solution with reagent water and acidifying with nitric and hydrochloric acid at 0.4 and 2 percent (by volume), respectively. The electron multiplier of the cICP–MS is operated in the pulse-counting mode whenever an elemental concentra

tion produces less than about 2 million counts per second. Higher count rates saturate the multiplier, thereby requiring that the multiplier be used in the analog mode. The linear transition between the two modes requires that a pulse/analog (P/A) calibration factor be established daily for each element determined. A solution containing all the elements is prepared by making the appropriate dilution of the stock solutions with reagent water acidified with nitric acid (0.4 percent by vol

ume). Elemental concentrations range from 5 to 25 μ g/L. The performance of cICP–MS in interference reduction is tested periodically by analyzing solutions containing major interfering constituents and affected analytes. A solution having interfering constituents contains 1,000 mg/L Cl (from HCl); 100 mg/L each of Al, K, Mg, Mn, P, S, and Zn; 50 mg/L Si; 250 mg/L each of C (from potassium hydrogen phthalate), Ca, Fe, and Na; and 2 mg/L each of Mo, Ti, and Er. Another solution that also contains selected analytes is prepared as above with the addition of Ag, As, Cd, Co, Cr, Cu, Ni, Se, V, and W, each at 20 μ g/L. Potential interferences associated with these elements are listed in table 3. The solutions are prepared by making suitable dilutions of contaminant-free commercial solutions (except for C and Cl) with reagent water acidified to 1 percent by volume with nitric acid. 

## Quantitation Analyte concentrations are calculated automatically from the linear regression equations by the operating system. The operating system monitors results for quality-control and quality-assurance samples in real-time and updates calibra

tion whenever acceptance criteria fail. Furthermore, sample carryover is minimized by automatically increasing the length of the rinse-cycle period until an analyte signal reaches an acceptable level. Such automatic quantitation and control fea

tures are not unlike those provided by older ICP–MS instru

ments in methods for routine elemental analyses. However, He or H 2 

### must be introduced into the cell during data acquisi

tion for elements that are affected by molecular ion interfer

ences and purged from the cell for other elements. There is also a notable difference in the procedures used to calculate arsenic speciation results when using the cICP–MS. Previous arsenic speciation methods were unable to calculate results in real time. The chromatographic peaks were integrated and the regression equations were calculated offline and required substantial manual data processing. The new operating system software makes it possible to process the results and calculate concentrations in real time.

## Reporting of Analytical Data Elemental concentrations presented in USGS data reports are reported so that the rightmost digit (called the least sig

nificant digit) represents the uncertainty in the result (Novak, 1985; Hansen, 1991; U.S. Geological Survey, 2002). The least significant digit is determined using guidance outlined by the American Society for Testing and Materials (1999). NWQL reports results in the national database to the least significant digit plus one additional digit. Results for water samples will be reported in either micrograms per liter or milligrams per liter, depending on the element (see table 1). Elemental results for biota, sediment, and soil digestates will be reported in micrograms per gram or milligrams per gram, dry weight, depending on the element. All arsenic species are reported in micrograms–arsenic per liter. 

## Laboratory Quality Assurance/Quality Control Laboratory samples are prepared in sample sets consist

ing of the calibration standards, the interference check solu

tion, laboratory reagent blanks (LRB), and laboratory control samples (LCS); the required frequency of analyzing LRB and LCS samples is outlined below. Furthermore, standard reference materials, laboratory reagent spike samples, and laboratory duplicate samples can be included to meet specific data-quality objectives. The NWQL uses the Quality Manage

ment System Document for essential Quality-Assurance/Qual

ity-Control requirements (Maloney, 2005). The LRB is prepared to match the matrix of the samples and calibration standards. A minimum of one LRB is ana

lyzed for every 10 analytical samples. The LRB cannot have any detectable levels of contaminants. The control limits for the LRB are plus or minus the LT–MDL for each element. For LRB that have a detectable concentration of a certain element, the source of contamination must be determined and either eliminated or minimized before the environmental samples are reanalyzed. In cases where the source of contamination cannot be identified, the element is assigned a data-qualifying code. The concentration of the element in the environmental sample, however, can be reported without a qualifying code if it is 10 times greater than the concentration in the LRB. Conversely, if concentrations are less than the LT–MDL, the samples need to be reanalyzed. The LCS is prepared from either a solution having a dif

ferent lot number than the calibration standards or a solution from a different vendor than the calibration standards. In either case, the solution used to prepare the LCS needs to be traceable to NIST. A minimum of one LCS is analyzed for every 10 analytical samples. The control limits for the LCS are plus or minus two standard deviations of the expected concentration of the element of interest. Any elemental results that fall outside of the control limits are not reported. All environmental samples associated with the failed LCS must be reanalyzed until the specified acceptance criterion is met. All material used to make calibration standards need to be NIST traceable. Calibration standards are verified by using a NIST traceable LCS. Determined concentrations need to be within two standard deviations of the specified concentration.


# Results and Discussion of Method **Validation Data**
The analytical bias and variability across the normal calibration range of the analytes were determined by using results for two USGS standard reference water samples (SRWS), and results for reagent-water, ground-water, and surface-water samples spiked at several concentrations. The SRWSs are based on spiked natural-water matrices whose most probable elemental concentrations have been established through interlaboratory analyses using multiple analytical methods. SRWS T145 was made with water collected from the Yampa River near Steamboat Springs, Colorado (Farrar and Long, 1997), and SRWS T169 was made with water col

lected from the South Platte River west of Bailey, Colorado (Woodworth and Conner, 2002); water samples from both sources were subsequently filtered, spiked, and preserved with nitric acid. SRWS T145 and T169 were analyzed between 21 and 68 times over several days and multiple instrument calibrations. A statistical summary of these results is listed in table 6. The average results for T145 are within one F-pseu

dosigma of the most probable concentration except for Na and Mg. Nevertheless, the averages for Na and Mg are within 1.5 F-pseudosigma of the most probable concentration, which is considered to be acceptable. The average results for T169 are within one F-pseudosigma of the most probable concentration except for Ba, Ni, and U, which are within 1.5 F-pseudosigma. The concentration of W in the SRWSs was not established; therefore, a NIST W standard was used to prepare solutions in reagent water. The resulting experimental W concentrations were within 4 and 18 percent of the expected concentrations of 1 and 50 μ g/L, respectively. The corresponding variability ranged from 3 to 7 percent for 30 measurements. Results for reagent blank samples analyzed with the SRWSs showed acceptably low concentration levels with slight variability (see table 6). The new cICP–MS method was validated by determining the percentage bias and variability at 2 to 4 spike-concentra

tion levels in reagent-water, ground-water, and surface-water matrices. Reagent water was spiked at 4 concentrations; 2 levels were in the lower one-third of the normal calibration range, 1 at roughly one-third and 1 at roughly two-thirds of the normal calibration range. Ground-water and surface-water matrices were spiked at roughly one-third and two-thirds of the normal calibration range. The number of measurements at each concentration was between 16 and 33 for each matrix determined over several days. **1 4**  **Determination of Elements Using Collision/Reaction Cell ICP–MS**

### Results and Discussion of Method Validation Data **1 5** 
**Table 6** 

**.** Long-term bias and variability of results from aqueous standard reference materials using collision/ reaction cell inductively coupled plasma–mass spectrometry. [Analyte, concentrations are in micrograms per liter unless otherwise noted; SRWS, U.S. Geological Survey standard reference water sample; Exp, mean concentration plus or minus one standard deviation for experimental results based on the number of measurements, in italics, measured over several days for SRWS T145 and T169; MPV, most probable mean value plus or minus one F-pseudosigma for interlaboratory results using multiple methods except for tungsten (W), which are nominal concentrations from a diluted National Institute of Standards and Technology reference standard; Blank, mean concentration plus or minus one standard deviation for 35 reagent blank measurements taken over several days; mg/L, milligrams per liter]
**Analyte SRWS T1**  **45 SRWS T1**  **69 Blank**  **Exp MPV**  **Exp MPV**  Ag 7.8±0.3, 68 7.6±0.9 3.9±0.1, 49 3.9±0.2 –0.01±0.01 Al 64±6, 52 68±11 32.9±0.6, 21 34±4 –0.3±0.2 As 10.4±0.6, 52 10±1 8.6±0.7, 49 8.6±0.7 –0.02±0.03 B 46±2, 40 45±6 25±1, 49 24±2 0.3±0.6 Ba 36±2, 68 37±2 41±1, 49 43±2 0.05±0.1 Be 9.0±0.3, 40 9.0±0.7 9.4±0.4, 49 9.6±0.6 –0.009±0.01 Ca, mg/L 30±2, 28 31±1 37±1, 21 37.9±0.9 –0.02±0.02 Cd 9.8±0.3, 68 9.3±0.8 3.60±0.08, 49 3.4±0.2 –0.007±0.01 Co 10.0±0.6, 68 10.0±0.9 1.91±0.05, 49 1.9±0.2 –0.002±0.04 Cr 13.9±0.5, 48 15±1 7.8±0.3, 49 8.2±0.4 –0.024±0.02 Cu 11.6±0.6, 68 11±1 14±1, 49 14.3±0.8 0.008±0.1 Fe 94±4, 38 101±8 12.1±0.5, 21 11±4 –0.03±0.2 K, mg/L 2.0±0.1, 28 2.1±0.2 2.50±0.07, 21 2.6±0.1 –0.014±0.02 Li 26.6±0.9, 40 27±2 9.1±0.3, 49 9.6±0.6 0.003±0.04 Mg, mg/L 8.1±0.5, 28 8.7±0.4 4.2±0.1, 21 4.3±0.1 –0.02±0.03 Mn 20±1, 68 21±2 27±1, 49 27.0±0.9 0.02±0.08 Mo 8.6±0.4, 68 9±1 71.8±0.6, 25 71±2 –0.005±0.02 Na, mg/L 39±2, 21 41±2 10.3±0.4, 21 10.6±0.3 –0.02±0.02 Ni 11±1, 68 11±1 11.1±0.6, 49 10.3±0.7 –0.11±0.03 Pb 12.4±0.6, 68 13±1 10.7±0.3, 49 11.4±0.7 –0.01±0.02 Sb 8.3±0.4, 68 8.8±0.9 2.92±0.09, 49 3.3±0.4 –0.008±0.01 SiO 2 , mg/L 11.5±0.8, 28 11.3±0.7 6.2±0.2, 21 6.0±0.2 –0.03±0.05 Se 10.7±0.8, 52 10±1 2.7±0.2, 49 2.9±0.4 –0.07±0.08 Sr 208±7, 68 203±19 176±6, 49 174±6 0.2±0.2 Tl 15.1±0.8, 68 15±3 4.3±0.1, 49 4.8±0.5 –0.04±0.02 U 1.02±0.06, 68 1.1±0.1 1.55±0.02, 25 1.7±0.1 –0.008±0.009 V 11.2±0.7, 68 12±2 7.4±0.3, 49 7.4±0.4 –0.03±0.02 W 0.96±0.07, 30 1 59±2, 30 50 –0.1±0.3 Zn 9.6±0.8, 68 10±2 18±1, 49 19±1 –0.2±0.4

### The bias and variability for reagent water spiked with analyte concentrations in the lower one-third of the normal calibration range are listed in table 7. The percentage bias for reagent water spiked at trace-element concentrations of 0.5 to 3 μ g/L (column 3 of table 7) averaged 4.4 percent with a range of –6 to 16 percent, whereas the average percentage bias for Ca, K, Mg, Na, and SiO 2 

### was 1.4 percent with a range of –4 to 10 percent for spikes of 0.5 to 3 mg/L. For the other 3 spike levels (column 6 of table 7 and columns 3 and 6 of table 8), the average bias for trace elements was 0.9 percent with percentages ranging from –8.1 to 13 percent, whereas for Ca, K, Mg, Na, and SiO 2 

### , the average bias was 1.0 percent with percentages ranging from –7.7 to 10 percent. The correspond

ing variability ranged from 0.7 to 10 percent relative standard deviation (percent RSD) for trace elements and from 1.0 to 10 percent RSD for Ca, K, Mg, Na, and SiO 2 

### . Validation data for surface-water and ground-water matri

ces are listed in tables 9 and 10, respectively. Surface water was spiked with between 17 and 1,754 μ g/L for trace elements and 8 and 95 mg/L for Ca, K, Mg, Na, and SiO 2 

### . The aver

age bias for trace elements was 1.8 percent with percentages ranging from –14 to 21 percent; for Ca, K, Mg, Na, and SiO 2 

### , the average bias was 0.96 percent with a range of

– 

### 4.2 to 7.8percent. The associated variability ranged from 2.6 to 22 percent RSD for trace elements and from 1.0 to 5.8 percent RSD for Ca, K, Mg, Na, and SiO 2 

### . Ground water was spiked with between 17 and 1,769 μ g/L for trace elements and 9 and 95 mg/L for Ca, K, Mg, Na, and SiO 2 

### . The average bias for trace elements was –0.59 percent with percentages ranging from –16 to 16 percent; for Ca, K, Mg, Na, and SiO 2 

### , the average bias was 1.5 percent with a range of –7.5 to 11 percent. The associated variability ranged from 1 to 18 percent RSD for trace elements and from 0.8 to 5.0 percent RSD for Ca, K, Mg, Na, and SiO 2 

### . Linear regression analysis was used to evaluate whether cICP–MS results for 25 filtered natural-water samples and 25 unfiltered natural-water digestates were notably different than results from established analytical methods. The elemental concentration range for the test samples typically extended 3 to 4 orders of magnitude (see column 6 in tables 11 and 12, in addition, see graphs of regression analyses in the Appendix). The slopes of the regression equations were used to identify systematic or random errors in the analytical results; a slope of unity indicates there is no difference between instrumen

tal methods. A nonzero y -intercept indicates possible faulty background correction for one of the methods. Eighty-three percent (24 of 29) of the elements had slopes within ±10 percent of unity in the 95 percent confidence inter

val for filtered natural-water samples. Four of the remaining five elements were within ±15 to 30 percent; cICP–MS results for Li tended to be lower than the previous method and Tl and W tended to be higher. The slope for B was about 30 percent greater than unity possibly from carryover from samples with high B concentrations. The slope for Be was notably different than unity because of the low concentrations present in the test samples. For unfiltered digestate samples, 79 percent (23 of 29) of the elements had slopes within ±10 percent of unity in the 95 percent confidence interval. Four of the remaining six elements were within ±15 to 20 percent; cICP–MS results for Al, Cu, and W tended to be lower than the other methods and Mo tended to be higher. Slopes for Ag and Sb were substan

tially different than unity because of the low concentrations present in the test samples. The median y -intercept for trace elements corresponding to the linear regression analysis of filtered results was 0.01 μ g/L with a range from –1.7 to 69 μ g/L; the median for Ca, K, Mg, Na, and SiO 2 

### was 0.05 mg/L with a range of –0.8 to 0.3 mg/L. B, Ba, Li, and Sr had the largest y -intercepts rang

ing from –2 to 69 μ g/L and corresponded to sample results extending from 100 to 1,000 μ g/L. For trace elements in whole-water digestates, the median y -intercept was 0.04 μ g/L with a range from –26 to 1.7 μ g/L; the medium for Ca, K, Mg, Na, and SiO 2 

### was –0.2 mg/L with a range of –0.6 to 1.1 mg/L. The y -intercepts for Al and Fe were –22 and –26 μ g/L, respectively, most likely an effect of sample concentrations extending to 10,000 μ g/L. The bias and variability associated with the analysis of biological standard reference materials also was determined. The analysis of sediment or soil standard reference material was not tested because the microwave digestion procedure used by NWQL does not completely solubilize such solids, thereby making the comparison of results to certified concen

trations problematic. The results of the analysis of National Research Council Canada Dolt-2 and Dorm-2 standard refer

ence materials (SRM) and NIST SRM 1577b using cICP–MS are listed in table 13. Linear regression analysis comparing the experimental elemental concentrations from cICP–MS to the certified concentrations in the standard reference materials is shown in figure 6. The regression coefficients indicate an acceptable linear relation. Nevertheless, on the average, the experimental results were about 17 percent higher for elemen

tal concentrations ranging five orders of magnitude. **1 6**  **Determination of Elements Using Collision/Reaction Cell ICP–MS**

### Results and Discussion of Method Validation Data **1 7** 

**Table 7** 

**.** Long-term bias and variability for the analysis of reagent water spiked with analyte concentrations in the lower one-third of the normal calibration range using collision/reaction cell inductively coupled plasma–mass spectrometry. [Spiked reagent-water samples were analyzed randomly with spiked surface- and ground-water samples over several days; Analyte, concentrations are in micrograms per liter unless otherwise noted; Exp, mean concentration plus or minus standard deviation for experimental results based on 16 to 22 replicate determinations at each spike concentration; Percent bias, percent

age error between the expected concentration and the mean experimental concentration; Percent RSD, percent relative standard deviation; mg/L, milligrams per liter]
**Analyte Exp**  **Percent bias**  **Percent RSD**  **Exp Percent**  **bias Percent**  **RSD** Ag 1.05±0.03 5.0 2.9 5.17±0.04 3.4 0.8 Al 2.91±0.09 16 3.1 13.9±0.6 11 4.2 As 1.04±0.05 4.0 4.8 5.21±0.09 4.2 1.7 B 2.4±0.6 2.8 25 12.1±0.9 –3.0 7.5 Ba 2.6±0.2 4.8 5.7 13.2±0.3 5.6 2.3 Be 0.50±0.01 0 2.0 2.51±0.04 0.4 1.6 Ca, mg/L 2.19±0.09 9.5 4.0 16.6±0.2 10 1.0 Cd 1.05±0.02 5.0 1.9 5.20±0.08 4.0 1.5 Co 1.06±0.03 6.0 2.8 5.26±0.04 5.2 0.8 Cr 1.00±0.02 0 2.2 4.7±0.3 –5.8 6.2 Cu 2.7±0.3 7.2 9.7 13.0±0.3 4.2 2.0 Fe 2.4±0.3 9.1 11 11.5±0.1 0 0.7 K, mg/L 0.54±0.01 8.0 2.2 2.20±0.08 10 3.5 Li 2.53±0.08 1.2 3.2 12.6±0.3 0.4 2.3 Mg, mg/L 0.48±0.01 –4.0 2.7 2.09±0.07 4.5 3.2 Mn 2.68±0.07 7.2 2.6 13.4±0.2 7.2 1.6 Mo 1.00±0.02 0 2.0 4.90±0.05 –2.0 1.0 Na, mg/L 0.48±0.01 –4.0 2.7 5.1±0.2 1.8 4.5 Ni 1.07±0.05 7.0 4.7 5.2±0.1 3.0 2.1 Pb 1.05±0.05 5.0 4.8 5.1±0.2 2.8 3.7 Sb 1.00±0.03 0 3.0 4.86±0.04 –2.9 0.8 Se 1.12±0.06 12 5.4 5.6±0.2 12 3.0 SiO 2 , mg/L 2.9±0.2 –2.3 6.5 16.0±0.3 6.7 1.8 Sr 1.89±0.07 –5.5 3.7 13.0±0.7 3.8 5.2 Tl 0.51±0.02 2.0 3.9 2.65±0.07 6.0 2.6 U 1.05±0.04 5.0 3.8 5.2±0.2 4.6 4.0 V 1.01±0.04 1.0 4.0 5.1±0.1 1.2 2.0 W 0.79±0.02 –1.3 2.7 8.9±0.1 11 1.0 Zn 2.87±0.09 13 3.1 14.1±0.3 13 2.3

### Table **8**

**.** Long-term bias and variability for the analysis of reagent water spiked with analyte concentrations at onethird and two-thirds of the normal calibration range using collision/reaction cell inductively coupled plasma–mass spectrometry. [Spiked reagent-water samples were analyzed randomly with spiked surface- and ground-water samples over several days; Analyte, con

centrations are in micrograms per liter unless otherwise noted; Exp, mean concentration plus or minus standard deviation for experimental results based on 20 to 33 replicate determinations at each spike concentration; Percent bias, percentage error between the expected concen

tration and the experimental mean concentration; Percent RSD, percent relative standard deviation; mg/L, milligrams per liter]
**Analyte Exp**  **Percent bias Percent RSD**  **Exp Percent bias**  **Percent RSD** Ag 34±2 0.6 4.8 72±4 7.7 6.1 Al 310±20 –7.3 5.6 640±20 –4.0 2.6 As 35±3 5.7 7.6 66±3 –1.5 4.8 B 82±8 –1.8 10 160±20 –4.3 10 Ba 86±3 3.0 3.0 173±4 3.7 2.3 Be 16.5±0.8 –1.2 4.8 35±1 5.1 3.6 Ca, mg/L 48.6±0.9 –2.9 1.8 83±2 –2.6 3.1 Cd 33.8±0.8 1.2 2.4 65±1 –2.1 2.2 Co 34±1 1.5 3.2 66±2 –0.6 2.5 Cr 182±2 5.8 1.2 340±30 2.2 8.8 Cu 85±7 2.2 8.7 170±10 1.2 7.1 Fe 371±3 3.1 0.7 717±7 –0.4 1.0 K, mg/L 17.6±0.2 –2.0 1.2 35±2 –2.0 5.2 Li 80±3 –4.2 3.9 170±5 1.9 2.7 Mg, mg/L 19.4±0.6 2.0 3.3 38±2 0.7 5.5 Mn 320±10 –3.2 3.1 640±20 –3.5 2.9 Mo 31±1 –6.3 3.5 62±2 –7.5 3.8 Na, mg/L 20±1 1.8 6.5 39±3 –3.0 7.8 Ni 33±2 –0.9 5.4 66±3 –0.9 4.2 Pb 34±2 2.3 4.4 65±2 –1.8 2.8 Sb 32±2 –3.4 7.7 61±2 –8.1 3.2 Se 35±1 5.6 4.0 69±2 3.2 2.6 SiO 2 , mg/L 22±2 –1.7 10 37±3 –7.7 7.3 Sr 800±40 –4.1 4.3 1,620±80 –3.2 4.7 Tl 17.3±0.7 3.5 4.0 34±1 2.1 2.8 U 32±2 –2.8 5.5 63±3 –5.7 5.3 V 32±2 –5.0 7.2 63±1 –4.8 2.3 W 41±2 7.9 6.0 73±5 –4.0 6.3 Zn 340±20 2.9 5.0 660±30 –1.2 4.7 

### 1 **8 Determination of Elements Using Collision/Reaction Cell ICP–MS** 

### Results and Discussion of Method Validation Data **1 9** 
**Table 9** 

**.** Long-term bias and variability for the analysis of surface water spiked with analyte concentrations at one-third and two-thirds of the normal calibration range using collision/reaction cell inductively coupled plasma–mass spectrometry. [Spiked surface-water samples were analyzed randomly with spiked reagent- and ground-water samples over several days; Analyte, concentra

tions are in micrograms per liter unless otherwise noted; Exp, mean concentration plus or minus standard deviation for experimental results based on 20 to 30 replicate determinations at each spike concentration; Percent bias, percentage error between the expected concentration and the experimental mean concentration; Percent RSD, percent relative standard deviation; mg/L, milligrams per liter
**Analyte Exp**  **Percent bias Percent RSD**  **Exp Percent bias**  **Percent RSD** Ag 34±2 3.0 6.5 57±2 –14 3.7 Al 350±60 4.7 18 770±170 16 22 As 33±2 –1.4 6.5 66±4 –0.8 6.4 B 130±10 21 7.8 230±20 19 9.9 Ba 122±6 8.8 4.6 201±8 3.1 4.0 Be 18±2 8.4 11 34±4 3.5 11 Ca, mg/L 59±2 7.5 4.0 91±5 –3.9 5.8 Cd 33±2 –1.5 6.0 66±4 0 5.9 Co 34±2 0.7 5.3 66±4 –0.3 5.6 Cr 160±10 –5.1 6.6 310±20 –6.9 7.9 Cu 93±8 8.5 8.9 170±20 –0.6 11 Fe 440±12 8.0 2.6 640±20 –3.4 3.4 K, mg/L 18.3±0.8 –3.8 4.3 36±1 7.8 3.7 Li 90±9 5.2 9.5 170±20 –0.9 9.8 Mg, mg/L 20.2±0.8 –4.0 4.2 38.8±0.7 2.1 1.8 Mn 320±20 –2.5 5.3 630±30 –6.0 4.1 Mo 34±2 1.7 7.2 73±5 9.5 7.5 Na, mg/L 14.5±0.7 3.6 5.0 32.3±0.3 –3.0 1.0 Ni 33±2 –0.1 6.3 67±4 0.1 5.9 Pb 33±2 –1.0 6.4 67±4 0.6 6.4 Sb 32±2 –3.0 5.1 63±4 –5.3 5.7 Se 36±2 9.2 5.3 66±4 –1.2 5.4 SiO 2 , mg/L 8.6±0.2 7.5 2.8 32±1 –4.2 4.1 Sr 940±50 2.1 5.4 1,680±80 –4.4 4.9 Tl 16±1 –4.2 6.4 34±2 0.6 6.6 U 38±2 –9.4 4.7 68±3 2.2 4.4 V 33±2 0 5.9 69±4 3.6 5.8 W 43±1 14 3.3 76±3 1.2 3.5 Zn 320±20 –5.8 5.0 640±30 –6.1 4.9

### Table 10. Long-term bias and variability for the analysis of ground water spiked with analyte concentrations at one-third and two-thirds of the normal calibration range using collision/reaction cell inductively coupled plasma– mass spectrometry. [Spiked ground-water samples were analyzed randomly with spiked reagent- and surface-water samples over several days; Analyte, concentrations are in micrograms per liter unless otherwise noted; Exp, mean concentration plus or minus standard deviation for experimental results based on 20 to 32 replicate determinations at each spike concentration; Percent bias, percentage error between the expected concentration and the experimental mean concentration; Percent RSD, percent relative standard deviation; mg/L, milligrams per liter]
**Analyte Exp**  **Percent bias Percent RSD**  **Exp Percent bias**  **Percent RSD** Ag 33±2 –0.9 5.7 64±4 –4.1 6.3 Al 320±60 –5.7 18 700±100 9.1 18 As 32±2 –5.1 7.0 66±5 –1.5 7.0 B 106±8 16 7.8 200±20 14 7.6 Ba 134±6 5.3 4.4 214±9 1.6 4.4 Be 17±2 1.2 9.2 33±3 –1.5 8.8 Ca, mg/L 57±2 3.2 3.2 88±4 –7.5 5.0 Cd 32±2 –4.2 5.6 66±4 –1.2 5.5 Co 32±2 –3.1 5.3 65±4 –1.8 5.4 Cr 162±2 –3.3 1.0 300±20 –8.7 8.1 Cu 93±7 2.7 7.7 170±10 –4.0 8.5 Fe 420±40 7.7 8.8 550±30 –16 4.8 K, mg/L 18.9±0.8 –0.5 4.2 35±1 5.7 3.1 Li 85±7 2.0 8.2 160±10 –2.8 7.7 Mg, mg/L 15.3±0.4 2.0 2.4 37±1 11.0 3.5 Mn 310±20 –6.7 4.8 630±30 –5.2 5.1 Mo 34±2 1.2 6.8 74±5 10 7.2 Na, mg/L 17.5±0.6 2.9 3.3 32.6±0.3 –2.4 1.0 Ni 32±2 –3.1 7.3 66±4 –0.8 6.5 Pb 32±2 –4.2 6.0 66±4 –0.9 6.0 Sb 32±2 –3.1 5.1 63±4 –5.5 5.7 Se 34±1 3.2 4.3 63±3 –5.0 4.6 SiO 2 , mg/L 9.40±0.08 4.3 0.8 32.0±0.5 –3.9 1.6 Sr 920±50 –1.7 5.3 1,800±100 1.9 5.8 Tl 16±1 –4.2 6.4 34±2 0.6 6.6 U 44±2 7.0 4.8 75±1 –0.1 1.6 V 33±2 0 5.9 69±4 3.5 5.8 W 39.9±0.8 5.0 2.0 64±2 –3.9 3.2 Zn 320±20 –5.8 5.0 640±30 –6.1 4.9 

### 2 **0 Determination of Elements Using Collision/Reaction Cell ICP–MS** 

### Results and Discussion of Method Validation Data **2 1** 
**Table 11.** Linear regression results for filtered natural-water samples analyzed using collision/reaction cell inductively coupled plasma–mass spectrometry and other spectrometric methods. [Natural-water samples filtered using a 0.45-micrometer pore-size membrane and acidified to a pH of less than 2; Analyte, concentrations are in micrograms per liter unless otherwise noted; Slope, see Appendix for other spectrometric method used in comparison; 95% CI, 95-percent confidence interval for the slope or y -intercept; y -inter, y intercept; Conc. range, concentration range of the 25 samples tested; MDL, method detection limit (see table 2); mg/L, milligrams per liter]
**Analyte Slope**  **95 % CI**  **for slope** y **-inter 95**  **% CI for**  y **-inter Conc. range**  Ag 0.933 0.929 to 0.936 –0.006 –0.022 to 0.009 MDL to 19 Al 0.965 0.961 to 0.970 –0.090 –0.153 to –0.026 MDL to 40 As 0.954 0.935 to 0.972 0.107 –0.091 to 0.305 0.3 to 45 B 1.294 1.287 to 1.301 –1.735 –6.905 to 3.434 3 to 2,000 Ba 0.891 0.832 to 0.949 –1.117 –5.782 to 3.548 31 to 203 Be 0.138 –0.102 to 0.378 –0.005 0.001 to 0.008 MDL to 0.06 Ca, mg/L 0.915 0.878 to 0.952 0.052 –2.047 to 2.151 13 to 150 Cd 0.926 0.924 to 0.928 0.002 –0.020 to 0.023 MDL to 47 Co 0.986 0.981 to 0.990 0.018 –0.049 to 0.085 MDL to 50 Cr 1.050 1.029 to 1.071 –0.003 –0.489 to 0.482 0.09 to 7,400 Cu 0.964 0.953 to 0.975 0.299 0.098 to 0.499 0.06 to 60 Fe 0.934 0.913 to 0.955 –0.035 –0.549 to 0.480 MDL to 110 K, mg/L 1.048 1.025 to 1.070 –0.112 –0.183 to –0.040 0.7 to 8.0 Li 1.208 1.160 to 1.255 5.659 1.708 to 9.610 0.2 to 230 Mg, mg/L 0.982 0.967 to 0.997 –0.779 –1.299 to –0.260 1.6 to 110 Mn 1.026 0.983 to 1.069 0.082 –1.256 to 1.420 MDL to 600 Mo 1.045 1.038 to 1.053 –0.112 –0.239 to 0.016 0.3 to 57 Na, mg/L 0.906 0.898 to 0.915 0.273 –0.263 to 0.810 1.6 to 220 Ni 1.045 1.035 to 1.056 0.494 0.285 to 0.704 0.1 to 70 Pb 0.922 0.917 to 0.928 0.024 –0.047 to 0.095 MDL to 42 Sb 0.950 0.949 to 0.952 0.016 0.006 to 0.026 MDL to 44 Se 0.929 0.913 to 0.944 0.134 –0.035 to 0.303 MDL to 52 SiO 2 , mg/L 0.971 0.937 to 1.005 0.339 –0.890 to 1.567 3.9 to 74 Sr 0.870 0.829 to 0.911 68.799 9.040 to 128.559 30 to 5,000 Tl 0.873 0.870 to 0.875 0.011 –0.035 to 0.057 MDL to 58 U 0.920 0.905 to 0.935 0.246 0.089 to 0.403 0.08 to 45 V 1.010 1.005 to 1.014 –0.162 –0.803 to 0.478 0.2 to 750 W 0.874 0.873 to 0.876 0.031 –0.013 to 0.076 MDL to 132 Zn 1.020 1.013 to 1.028 –0.052 –0.692 to 0.587 0.4 to 280

### Table 1 **2**

**.** Linear regression results for unfiltered natural-water digestates analyzed using collision/reaction cell inductively coupled plasma–mass spectrometry and other spectrometric methods. [Unfiltered natural-water digestates prepared using in-bottle digestion procedure (Hoffman and others, 1996) and filtered using 20- micrometer pore-size membrane; Analyte, concentrations are in micrograms per liter unless otherwise noted; Slope, see Appendix for other spectrometric method used in comparison; 95% CI, 95-percent confidence interval for the slope or y -intercept; y -inter, y intercept; Conc. range, concentration range of the 25 samples tested; MDL, method detection limit (see table 2); mg/L, milligrams per liter]
**Analyte Slope**  **95 % CI**  **for slope** y **-inter 95**  **% CI for**  y **-inter Conc. range**  Ag 1.854 1.615 to 2.092 –0.011 –0.020 to –0.001 MDL to 0.12 Al 1.167 1.153 to 1.181 –21.799 –52.662 to 9.064 1.7 to 8,200 As 1.021 0.956 to 1.085 –0.413 –0.95 to 0.125 1.4 to 28 B 1.071 1.047 to 1.094 0.076 –1.160 to 1.312 3.8 to 140 Ba 0.970 0.951 to 0.990 –1.493 –3.517 to 0.531 4.6 to 365 Be 0.918 0.897 to 0.939 0.035 –0.009 to 0.080 MDL to 10 Ca, mg/L 1.000 0.954 to 1.046 1.193 –1.097 to 3.483 12 to 140 Cd 0.925 0.904 to 0.946 –0.002 –0.036 to 0.032 MDL to 7.9 Co 1.137 1.065 to 1.208 –0.127 –0.382 to 0.127 0.06 to 10 Cr 0.921 0.874 to 0.969 0.232 –0.274 to 0.738 0.4 to 44 Cu 1.220 1.147 to 1.294 –0.034 –0.463 to 0.396 0.2 to 15 Fe 1.078 1.069 to 1.087 –26.485 –44.006 to –8.963 5.6 to 10,000 K, mg/L 1.026 1.005 to 1.047 –0.210 –0.276 to –0.145 0.7 to 7.7 Li 0.863 0.821 to 0.906 1.472 0.018 to 2.926 MDL to 110 Mg, mg/L 0.993 0.975 to 1.011 –0.594 –1.206 to 0.019 1.5 to 104 Mn 0.938 0.907 to 0.969 1.682 –0.026 to 3.39 1.1 to 200 Mo 0.847 0.815 to 0.879 0.202 0.119 to 0.286 0.2 to 8.9 Na, mg/L 0.942 0.932 to 0.953 0.213 –0.382 to 0.807 1.6 to 196 Ni 1.128 1.080 to 1.176 0.188 0.016 to 0.360 0.3 to 17 Pb 1.089 1.043 to 1.135 0.039 –0.167 to 0.244 0.04 to 17 Sb 1.846 1.484 to 2.207 –0.161 –0.249 to –0.073 0.06 to 0.63 Se 0.831 0.695 to 0.967 0.255 0.133 to 0.378 0.08 to 2.1 SiO 2 , mg/L 1.136 1.014 to 1.259 0.238 –1.999 to 2.475 3.3 to 37 Sr 1.004 0.987 to 1.020 –2.933 –6.698 to 0.831 27 to 720 Tl 0.942 0.874 to 1.009 0.072 0.031 to 0.113 MDL to 3.0 U 1.024 0.951 to 1.097 0.046 –0.313 to 0.405 0.2 to 14 V 0.900 0.862 to 0.939 0.716 –0.035 to 1.466 1.4 to 75 W 1.122 0.654 to 1.589 –0.016 –0.039 to 0.008 MDL to 0.13 Zn 0.995 0.983 to 1.008 0.538 –0.560 to 1.637 0.7 to 340 

### 22 **Determination of Elements Using Collision/Reaction Cell ICP–MS**

### Results and Discussion of Method Validation Data **23**

**Analyte Dolt-**  **2 Dorm-**  **2 Bovine**  **Exp Target**  **Exp Target**  **Exp Target**  Ag 0.655±0.005 0.608±0.032 0.035±0.007 0.041±0.013 0.043±0.009 0.039 Al 36±1 25.2±2.4 12.4±0.5 10.9±1.7 1.06±0.05 (3) As 18.31±0.06 16.6±1.1 20.7±0.1 18.0±1.1 0.071±0.008 (0.05) Ca, mg/g na na na na 0.13±0.01 0.116 Cd 24.4±0.3 20.8±0.5 0.07±0.2 0.043±0.008 0.6±0.2 0.50 Co 0.24±0.02 0.24±0.05 0.22±0.02 0.182±0.031 0.27±0.02 (0.25) Cr 0.30±0.01 0.37±0.08 37.4±0.6 34.7±5.5 na na Cu 29±2 25.8±1.1 2.1±0.1 2.34±0.16 160±10 160 Fe 1,290±5 1,103±47 183.6±0.8 142±10 217±2 184 K, mg/g na na na na 10.54±0.04 9.94 Mg, mg/g na na na na 0.67±0.01 0.601 Mn 7.2±0.3 6.88±0.56 4.3±0.2 3.66±0.34 11.7±0.5 10.5 Mo na na na na 4.1±0.2 3.5 Na, mg/g na na na na 2.49±0.09 2.42 Ni 0.17±0.02 0.20±0.02 19.6±0.4 19.4±3.1 na na Pb 0.25±0.02 0.22±0.02 0.045±0.004 0.065±0.007 0.124±0.008 0.129 Se 7.7±0.1 6.06±0.49 1.77±0.06 1.4±0.09 0.940±0.009 0.73 Sr na na na na 0.143±0.003 0.136 V na na na na 0.109±0.001 (0.123) Zn 104±3 85.8±2.5 26.7±0.6 25.6±2.3 140±4 127 

### Table 1 **3**

**.** Bias and variability of results for digested biological standard reference materials analyzed by collision/ reaction cell inductively coupled plasma–mass spectrometry. [Analyte, concentrations are in micrograms per gram unless otherwise noted; Dolt-2, National Research Council Canada (NRC) dogfish liver standard reference material; Dorm-2, NRC dogfish muscle standard reference material; Bovine, National Institute of Standards and Technol

ogy bovine liver standard reference material 1577b; Exp, mean concentration plus or minus one standard deviation for experimental results based on three replicate measurements; Target, certified concentration (plus or minus one standard deviation when available), numbers in parentheses are uncertified; mg/g, milligrams per gram; na, concentration not available]

### Figure **6**

**.** Linear regression analysis of experimental concentrations for all elements in biological standard reference material digestates analyzed by collision/reaction cell inductively coupled plasma–mass spectrometry in relation to the certified concentrations. Error bars in each axis represent one standard deviation. The regression coefficients are the slope (m), y -intercept (b), correlation coefficient (R), and the number of data points (N). Concentrations are in micrograms per gram or milligrams per gram, dry weight. The dataset is listed in table 13.



# Summary and Conclusions
A new analytical method using collision/reaction cell inductively coupled plasma mass spectrometry (cICP–MS) has been shown to eliminate molecular ion interferences asso

ciated with selected elements. Helium or hydrogen was used to eliminate or substantially reduce such interferences. The scope of the updated method was expanded by including ele

ments that were not determined by earlier inductively coupled plasma–mass spectrometric (ICP–MS) methods. The updated method can be used to determine elements in filtered natu

ral water and in a wide variety of filtered aqueous matrices including whole water, biota, sediment, and soil digestates. Elements that are not affected by molecular ion interference also can be determined with bias and variability comparable to earlier ICP–MS methods. The findings of this report are summarized as follows to address previously cited objectives: Method detection limits were established for all elements determined using the new method. Most method detection limits are lower or unchanged compared to earlier methods except for Co, K, Mg, Ni, SiO 2 

### , and Tl, which are less than a factor of 2 higher. The results presented have shown that As, Ca, Co, Cr,Cu, Fe, K, Mg, Na, Ni, Se, Si, V, W, and Zn can be determined accurately when using a collision/reaction gas without mathematical corrections in the presence of interferent concentrations substantially greater than those found in routinely submitted samples. A colli

sion/reaction gas was not needed when determining Ag, Al, Cd, and Mn because the interferences were insignificant at the interferent concentrations tested. •

• 0
. 0 1 0
. 1 1 1 0 1 0 0 1 , 0 0 0 0
. 0 1

0
. 1

1 1 0 1 0 0 1 , 0 0 0 

## L i n e a r r e g r e s s i o n l i n eEXPERIMENTALCONCENTRATION



## C E R T I F I E D C O N C E N T R A T I O N R e g r e s s i o n c o e f f

i c i e n t s m = 1
. 1 7 b = 0
. 4 5 R = 0
. 9 9 9 9 N = 2 6 **24 Determination of Elements Using Collision/Reaction Cell ICP–MS** 

### References Cited **25** Samples having specific conductances less than 7,500 μ S/cm can be analyzed directly by cICP–MS with acceptable bias and variability. Previous ICP–MS methods required that samples with specific conduc

tances greater than 2,500 μ S/cm be diluted. Ninetyfive percent of the samples submitted to NWQL in 2004 had specific conductances less than 3,000 μ S/cm. The bias and variability of the cICP–MS method were determined using results from aqueous standard reference materials. The average results for the two standard reference materials tested were within one F-pseudosigma of the most probable concentration except for Ba, Na, Mg, Ni, and U. Nevertheless, the averages for these elements were within an acceptable1.5 F-pseudosigma of the most probable concentration. Elemental results for biological standard refer

ence materials also compared closely to the certified concentrations. The new cICP–MS method was validated by using analytical results from reagent-water, ground-water, and surface-water matrices that were spiked at 2 to 4 concentration levels. The percentage biases for reagent water, ground water, and surface water ranged from –14 to 21 percent for trace elements and –7.7 to 10 percent for Ca, K, Mg, Na, and SiO 2 

### . The cICP–MS results from 25 filtered natural-water samples and 25 whole-water digestates were compared with results from previously used methods. Further

more, experimental results for three biological stan

dard reference material digestates were compared to certified concentrations. Linear regression analysis of these results indicated that the bias and variability of cICP–MS is acceptable for a wide variety of sample matrices.


# References Cited
Agilent Technologies, 2001, Agilent 1100 series reference manuals for micro autosampler, quaternary pump, thermo

statted column compartment, and thermostatted autosam

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Station operator’s manual: Part number G3270-90110010, Rev. A 2004/04, Tokyo, Japan. Agilent Technologies, 2004b, Agilent 7500 ICP–MS hard

ware manual: Part number G3270-90100, Rev. A 2004/04, Tokyo, Japan. •

•

•

• American Society for Testing and Materials, 1999, E29-93a Standard practice for using significant digits in test data to determine conformance to specifications: Annual book of ASTM standards, Reporting test results, section 7.4, v. 14.02. American Society for Testing and Materials, 2000, Annual

book of ASTM standards, Section 11, Water: Philadelphia, American Society for Testing and Materials, v. 11.01, D1193, p. 10. Childress, C.J.O., Foreman, W.T., Connor, B.F., and

Maloney, T.J., 1999, New reporting procedures based on long-term method detection levels and some considerations for interpretations of water-quality data provided by the U.S. Geological Survey National Water Quality Laboratory: U.S. Geological Survey Open-File Report 99-193, 19 p. Crawford, J.K., and Luoma, S.N., 1993, Guidelines for studiesof contaminants in biological tissues for the National WaterQuality Assessment Program: U.S. Geological Survey Open-File Report 92-494, 69 p. Faires, L.M., 1993, Methods of analysis by the U.S. Geological Survey National Water Quality Laboratory— Determination of metals in water by inductively coupledplasma–mass spectrometry: U.S. Geological Survey OpenFile Report 92-634, 28 p. Farrar, J.W., and Long, H.K., 1997, Report on the U.S. Geological Survey’s evaluation program for standard refer

ence samples distributed in September 1996: U.S. Geological Survey Open-File Report 97-20, 145 p. Fishman, M.J., and Friedman, L.C., eds., 1989, Methods of determination of inorganic substances in water and fluvialsediments: U.S. Geological Survey Techniques of WaterResources Investigations, book 5, chap. A1, 545 p. Garbarino, J.R., and Taylor, H.E., 1994, Inductively coupled

plasma–mass spectrometric method for the determination of dissolved trace elements in natural water: U.S. Geological Survey Open-File Report 94-358, 28 p. Garbarino, J.R., and Struzeski, T.M., 1998, Methods of analy

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tory—Determination of dissolved arsenic, boron, lithium, selenium, strontium, thallium, and vanadium using induc

tively coupled plasma–mass spectrometry: U.S. Geological Survey Open-File Report 99-093, 31 p.

### Garbarino, J.R., 2000, Methods of analysis by the U.S. Geological Survey National Water Quality Laboratory— Determination of whole-water recoverable arsenic, boron, and vanadium using inductively coupled plasma–mass spectrometry: U.S. Geological Survey Open-File Report 99-464, 15 p. Garbarino, J.R., Bednar, A.J., and Burkhardt, M.R., 2002,

Methods of analysis by the U.S. Geological Survey NationalWater Quality Laboratory—Arsenic speciation in naturalwater samples using laboratory and field methods: U.S. Geological Survey Water-Resources Investigations Report 02-4144, 40 p. Hansen, W.R., 1991, Suggestions to authors of the reports of

the United States Geological Survey (7th ed.): U.S. Govern

ment Printing Office, p. 119–121. Hem, J.D., 1986, Study and interpretation of the chemical characteristics of natural water: U.S. Geological Survey Water-Supply Paper 2254, p. 67. Hoaglin, D.C., 1983, Letter values: A set of selected order statistics, in Hoaglin, D.C., Mosteller, Frederick, and Tukey, J.W., eds., Understanding robust and exploratory data analy

sis: New York, John Wiley & Sons, Inc., chap. 2, p. 35–55. Hoffman, G.L., Fishman, M.J., and Garbarino, J.R., 1996,

Methods of analysis by the U.S. Geological Survey National Water Quality Laboratory—In-bottle acid digestion of whole-water samples: U.S. Geological Survey Open-File Report 96-225, 28 p. Horlick, Gary, and Montaser, Akbar, 1998, Analytical characteristics of ICPMS, in Montaser, Akbar, ed., Induc

tively coupled plasma mass spectrometry: New York, Wiley-VCH, p. 503–613. Maloney, T.J., 2005, Quality management system, U.S. Geological Survey National Water Quality Laboratory: U.S. Geological Survey Open-File Report 2005-1263, version 1.3, November 9, 2005, accessed January 25, 2006, at http:// pubs.water.usgs.gov/ofr2005-1263/ National Environmental Laboratory Accreditation Confer

ence, 2003, Glossary for NELAC: 2003 NELAC Standard, EPA/600/R-04/003, accessed September 8, 2005, at URL http://www.epa.gov/nelac/2003standards.html. Novak, C.E., 1985, Preparation of water-resources data

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ing significant figures for chemical data: Office of Water Quality Technical Memorandum No. 2002.11, accessed September 6, 2005, at URL http://water.usgs.gov/admin/ memo/QW/qw02.11.html. U.S. Geological Survey, variously dated, National field manual for the collection of water-quality data: U.S. Geological Survey Techniques of Water-Resources Investigations, book 9, chaps. A1 (Rev. 1/2005), A2 (Rev. 3/2003), A3 (Rev. 4/2004), A4 (Rev. 9/1999), A5 (Rev. 4/2004), and A5.6.4 (Rev. 1/2005), accessed September 6, 2005, at URL http:// water.usgs.gov/owq/FieldManual/. Woodworth, M.T., and Conner, B.F., 2002, Results of the U.S. Geological Survey’s analytical evaluation program for standard reference samples distributed in March 2002: U.S. Geological Survey Open-File Report 02-243, 113 p. **26 Determination of Elements Using Collision/Reaction Cell ICP–MS** 

# Appendix

Linear Regression Analyses of Elemental Results

### Figure A1. Linear regression analysis of silver results from filtered water samples analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma– mass spectrometry (cICP–MS). R^2 is the coefficient of determination. In the confidence intervals table, the Intercept and Ag cICP–MS coefficients are the y -intercept and slope, respectively. Results are in micrograms per liter ( μ g/L). -4 0 4 8 12 16 20Ag ICP-MS, in μg/L

-4 0 4 8 12 16 20 Ag cICP-MS, in μg/L

Ag ICP-MS, in μg/L = -.006 + .933 * Ag cICP-MS, in μg/L; R^2 = 1

-.006 -.022 .009 .933 .929 .936 Coefficient 95% Lower 95% Upper Intercept Ag cICP-MS, in μg/L Confidence Intervals Ag ICP-MS, in μg/L vs. Ag cICP-MS, in μg/L LINEAR REGRESSION EQUATION 

### Appendix **29**

### 3 **0 Determination of Elements Using Collision/Reaction Cell ICP–MS** 

-.1

0 .1 .2 .3 .4 .5Ag ICP-MS, in μg/L

-.1 0 .1 .2 .3 .4 .5 Ag cICP-MS, in μg/L

Ag ICP-MS, in μg/L = -.011 + 1.854 * Ag cICP-MS, in μg/L; R^2 = .918

-.011 -.020 -.001 1.854 1.615 2.092 Coefficient 95% Lower 95% Upper Intercept Ag cICP-MS, in μg/L Confidence Intervals Ag ICP-MS, in μg/L vs. Ag cICP-MS, in μg/L LINEAR REGRESSION EQUATION



### Figure A **2**

**.** Linear regression analysis of silver results from whole-water recoverable digestates analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS). R^2 is the coefficient of determination. In the confidence intervals table, the Intercept and Ag cICP–MS coefficients are the y -intercept and slope, respectively. Results are in micrograms per liter ( μ g/L **).**

### Appendix **3 1** 

-5 0 5 10 15 20 25 30 35 40 45Al ICP-MS, in μg/L

-5 0 5 10 15 20 25 30 35 40 45 Al cICP-MS, in μg/L

Al ICP-MS, in μg/L = -.09 + .965 * Al cICP-MS, in μg/L; R^2 = 1

-.090 -.153 -.026 .965 .961 .970 Coefficient 95% Lower 95% Upper Intercept Al cICP-MS, in μg/L Confidence Intervals Al ICP-MS, in μg/L vs. Al cICP-MS, in μg/L LINEAR REGRESSION EQUATION



### Figure A **3**

**.** Linear regression analysis of aluminum results from filtered water samples analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS). R^2 is the coefficient of determination. In the confidence intervals table, the Intercept and Al cICP–MS coefficients are the y -intercept and slope, respectively. Results are in micrograms per liter ( μ g/L)

**.**

### 32 **Determination of Elements Using Collision/Reaction Cell ICP–MS**

1 1E1 1E2 1E3 1E4 1E5Al ICP-MS, in μg/L

1 1E1 1E2 1E3 1E4 1E5 Al cICP-MS, in μg/L

Al ICP-MS, in μg/L = -21.799 + 1.167 * Al cICP-MS, in μg/L; R^2 = .999

-21.799 -52.662 9.064

1.167 1.153 1.181 Coefficient 95% Lower 95% Upper Intercept Al cICP-MS, in μg/L Confidence Intervals Al ICP-MS, in μg/L vs. Al cICP-MS, in μg/L LINEAR REGRESSION EQUATION



### Figure A **4**

**.** Linear regression analysis of aluminum results from whole-water recoverable digestates analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS). R^2 is the coefficient of determination. In the confidence intervals table, the Intercept and Al cICP–MS coefficients are the y -intercept and slope, respectively. Results are in micrograms per liter ( μ g/L **).**

### Appendix **33**

**Figure A 5** 

**.** Linear regression analysis of arsenic results from filtered water samples analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS). R^2 is the coefficient of determination. In the confidence intervals table, the Intercept and As cICP–MS coefficients are the y-intercept and slope, respectively. Results are in micrograms per liter ( μ g/L). -10

0 10 20 30 40 50As ICP-MS, in μg/L

-10 0 10 20 30 40 50 As cICP-MS, in μg/L

As ICP-MS, in μg/L = .107 + .954 * As cICP-MS, in μg/L; R^2 = .998

.107 -.091 .305 .954 .935 .972 Coefficient 95% Lower 95% Upper Intercept As cICP-MS, in μg/L Confidence Intervals As ICP-MS, in μg/L vs. As cICP-MS, in μg/L LINEAR REGRESSION EQUATION

### 34 **Determination of Elements Using Collision/Reaction Cell ICP–MS**

0 5 10 15 20 25 30As GF-AAS in μg/L

0 5 10 15 20 25 30 As cICP-MS, in μg/L

As GF-AAS in μg/L = -.413 + 1.021 * As cICP-MS, in μg/L; R^2 = .979

-.413 -.950 .125 1.021 .956 1.085 Coefficient 95% Lower 95% Upper Intercept As cICP-MS, in μg/L Confidence Intervals As GF-AAS in μg/L vs. As cICP-MS, in μg/L LINEAR REGRESSION EQUATION



### Figure A **6**

**.** Linear regression analysis of arsenic results from whole-water recoverable digestates analyzed by graphite furnace–atomic absorption spectrometry (GF–AAS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS). R^2 is the coefficient of determination. In the confidence intervals table, the Intercept and As cICP–MS coefficients are the y -intercept and slope, respectively. Results are in micrograms per liter ( μ g/L).

### Appendix **35**

1 1E1 1E2 1E3 1E4B ICP-MS, in μg/L

1 1E1 1E2 1E3 1E4 B cICP-MS, in μg/L

B ICP-MS, in μg/L = -1.735 + 1.294 * B cICP-MS, in μg/L; R^2 = 1

-1.735 -6.905 3.434 1.294 1.287 1.301 Coefficient 95% Lower 95% Upper Intercept B cICP-MS, in μg/L Confidence Intervals B ICP-MS, in μg/L vs. B cICP-MS, in μg/L LINEAR REGRESSION EQUATION



### Figure A **7**

**.** Linear regression analysis of boron results from filtered water samples analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS). R^2 is the coefficient of determination. In the confidence intervals table, the Intercept and B cICP–MS coefficients are the y -intercept and slope, respectively. Results are in micrograms per liter ( μ g/L).

### 36 **Determination of Elements Using Collision/Reaction Cell ICP–MS**

**Figure A 8** 

**.** Linear regression analysis of boron results from whole-water recoverable digestates analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS). R^2 is the coefficient of determination. In the confidence intervals table, the Intercept and B cICP–MS coefficients are the y -intercept and slope, respectively. Results are in micrograms per liter ( μ g/L).

-20

0 20 40 60 80 100 120 140 160B ICP-MS, in μg/L

-20 0 20 40 60 80 100 120 140 160 B cICP-MS, in μg/L

B ICP-MS, in μg/L = .076 + 1.071 * B cICP-MS, in μg/L; R^2 = .997

.076 -1.160 1.312 1.071 1.047 1.094 Coefficient 95% Lower 95% Upper Intercept B cICP-MS, in μg/L Confidence Intervals B ICP-MS, in μg/L vs. B cICP-MS, in μg/L LINEAR REGRESSION EQUATION

### Appendix **37**

0 50 100 150 200Ba ICP-MS, in μg/L

0 50 100 150 200 Ba cICP-MS μg/L

Ba ICP-MS, in μg/L = -1.117 + .891 * Ba cICP-MS μg/L; R^2 = .977

-1.117 -5.782 3.548

.891 .832 .949 Coefficient 95% Lower 95% Upper Intercept Ba cICP-MS μg/L Confidence Intervals Ba ICP-MS, in μg/L vs. Ba cICP-MS μg/L LINEAR REGRESSION EQUATION



### Figure A **9**

**.** Linear regression analysis of barium results from filtered water samples analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS). R^2 is the coefficient of determination. In the confidence intervals table, the Intercept and Ba cICP–MS coefficients are the y -intercept and slope, respectively. Results are in micrograms per liter ( μ g/L).

### 38 **Determination of Elements Using Collision/Reaction Cell ICP–MS**

-50

0 50 100 150 200 250 300 350 400Ba ICP-MS, in μg/L

-50 0 50 100 150 200 250 300 350 400 Ba cICP-MS μg/L

Ba ICP-MS, in μg/L = -1.493 + .97 * Ba cICP-MS μg/L; R^2 = .998

-1.493 -3.517 .531

.970 .951 .990 Coefficient 95% Lower 95% Upper Intercept Ba cICP-MS μg/L Confidence Intervals Ba ICP-MS, in μg/L vs. Ba cICP-MS μg/L LINEAR REGRESSION EQUATION



### Figure A10. Linear regression analysis of barium results from whole-water recoverable digestates analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS). R^2 is the coefficient of determination. In the confidence intervals table, the Intercept and Ba cICP–MS coefficients are the y -intercept and slope, respectively. Results are in micrograms per liter ( μ g/L).

### Appendix **39**

**Figure A11.** Linear regression analysis of beryllium results from filtered water samples analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS). R^2 is the coefficient of determination. In the confidence intervals table, the Intercept and Be cICP–MS coefficients are the y -intercept and slope, respectively. Results are in micrograms per liter ( μ g/L). -.02

0 .02 .04 .06 .08 .1Be ICP-MS, in μg/L

-.02 0 .02 .04 .06 .08 .1 Be cICP-MS, in μg/L

Be ICP-MS, in μg/L = .005 + .138 * Be cICP-MS, in μg/L; R^2 = .058

.005 .001 .008 .138 -.102 .378 Coefficient 95% Lower 95% Upper Intercept Be cICP-MS, in μg/L Confidence Intervals Be ICP-MS, in μg/L vs. Be cICP-MS, in μg/L LINEAR REGRESSION EQUATION

### 4 **0 Determination of Elements Using Collision/Reaction Cell ICP–MS** 

-2 0 2 4 6 8 10Be ICP-MS, in μg/L

-2 0 2 4 6 8 10 Be cICP-MS, in μg/L

Be ICP-MS, in μg/L = .035 + .918 * Be cICP-MS, in μg/L; R^2 = .997

.035 -.009 .080 .918 .897 .939 Coefficient 95% Lower 95% Upper Intercept Be cICP-MS, in μg/L Confidence Intervals Be ICP-MS, in μg/L vs. Be cICP-MS, in μg/L LINEAR REGRESSION EQUATION



### Figure A1 **2**

**.** Linear regression analysis of beryllium results from whole-water recoverable digestates analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS). R^2 is the coefficient of determination. In the confidence intervals table, the Intercept and Be cICP–MS coefficients are the y -intercept and slope, respectively. Results are in micrograms per liter ( μ g/L).

### Appendix **4 1** 

0 10 20 30 40 50 60 70 80 90 100Ca ICP-AES, in mg/L

0 10 20 30 40 50 60 70 80 90 100 Ca cICPMS, in mg/L

Ca ICP-AES, in mg/L = .052 + .915 * Ca cICPMS, in mg/L; R^2 = .991

.052 -2.047 2.151 .915 .878 .952 Coefficient 95% Lower 95% Upper Intercept Ca cICPMS, in mg/L Confidence Intervals Ca ICP-AES, in mg/L vs. Ca cICPMS, in mg/L LINEAR REGRESSION EQUATION



### Figure A1 **3**

**.** Linear regression analysis of calcium results from filtered water samples analyzed by inductively coupled plasma–atomic emission spectrometry (ICP–AES) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS). R^2 is the coefficient of determination. In the confidence intervals table, the Intercept and Ca cICP–MS coefficients are the y -intercept and slope, respectively. Results are in milligrams per liter (mg/L).

### 42 **Determination of Elements Using Collision/Reaction Cell ICP–MS**

10 20 30 40 50 60 70 80 90Ca ICP-AES, in mg/L

10 20 30 40 50 60 70 80 90 Ca cICP-MS, in mg/L

Ca ICP-AES, in mg/L = 1.193 + 1 * Ca cICP-MS, in mg/L; R^2 = .989

1.193 -1.097 3.483 1.000 .954 1.046 Coefficient 95% Lower 95% Upper Intercept Ca cICP-MS, in mg/L Confidence Intervals Ca ICP-AES, in mg/L vs. Ca cICP-MS, in mg/L LINEAR REGRESSION EQUATION



### Figure A1 **4**

**.** Linear regression analysis of calcium results from whole-water recoverable digestates analyzed by inductively coupled plasma–atomic emission spectrometry (ICP–AES) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS). R^2 is the coefficient of determination. In the confidence intervals table, the Intercept and Ca cICP–MS coefficients are the y -intercept and slope, respectively. Results are in milligrams per liter (mg/L)

**.**

### Appendix **43**

-10

0 10 20 30 40 50Cd ICP-MS, in μg/L

-10 0 10 20 30 40 50 Cd cICP-MS, in μg/L

Cd ICP-MS, in μg/L = .002 + .926 * Cd cICP-MS, in μg/L; R^2 = 1

.002 -.020 .023 .926 .924 .928 Coefficient 95% Lower 95% Upper Intercept Cd cICP-MS, in μg/L Confidence Intervals Cd ICP-MS, in μg/L vs. Cd cICP-MS, in μg/L LINEAR REGRESSION EQUATION



### Figure A1 **5**

**.** Linear regression analysis of cadmium results from filtered water samples analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS). R^2 is the coefficient of determination. In the confidence intervals table, the Intercept and Cd cICP–MS coefficients are the y -intercept and slope, respectively. Results are in micrograms per liter ( μ g/L). 

### e

### 44 **Determination of Elements Using Collision/Reaction Cell ICP–MS**

-2 0 2 4 6 8 10Cd ICP-MS, in μg/L

-2 0 2 4 6 8 10 Cd cICP-MS, in μg/L

Cd ICP-MS, in μg/L = -.002 + .925 * Cd cICP-MS, in μg/L; R^2 = .997

-.002 -.036 .032 .925 .904 .946 Coefficient 95% Lower 95% Upper Intercept Cd cICP-MS, in μg/L Confidence Intervals Cd ICP-MS, in μg/L vs. Cd cICP-MS, in μg/L LINEAR REGRESSION EQUATION



### Figure A1 **6**

**.** Linear regression analysis of cadmium results from whole-water recoverable digestates analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS). R^2 is the coefficient of determination. In the confidence intervals table, the Intercept and Cd cICP–MS coefficients are the y -intercept and slope, respectively. Results are in micrograms per liter ( μ g/L).

### Appendix **45**

-10

0 10 20 30 40 50Co ICP-MS, in μg/L

-10 0 10 20 30 40 50 Co cICP-MS, in μg/L

Co ICP-MS, in μg/L = .018 + .986 * Co cICP-MS, in μg/L; R^2 = 1

.018 -.049 .085 .986 .981 .990 Coefficient 95% Lower 95% Upper Intercept Co cICP-MS, in μg/L Confidence Intervals Co ICP-MS, in μg/L vs. Co cICP-MS, in μg/L LINEAR REGRESSION EQUATION



### Figure A1 **7**

**.** Linear regression analysis of cobalt results from filtered water samples analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS). R^2 is the coefficient of determination. In the confidence intervals table, the Intercept and Co cICP–MS coefficients are the y -intercept and slope, respectively. Results are in micrograms per liter ( μ g/L)

**.**

### 46 **Determination of Elements Using Collision/Reaction Cell ICP–MS**

-2 0 2 4 6 8 10 12Co ICP-MS, in μg/L

-2 0 2 4 6 8 10 12 Co cICP-MS, in μg/L

Co ICP-MS, in μg/L = -.127 + 1.137 * Co cICP-MS, in μg/L; R^2 = .979

-.127 -.382 .127 1.137 1.065 1.208 Coefficient 95% Lower 95% Upper Intercept Co cICP-MS, in μg/L Confidence Intervals Co ICP-MS, in μg/L vs. Co cICP-MS, in μg/L LINEAR REGRESSION EQUATION



### Figure A1 **8**

**.** Linear regression analysis of cobalt results from whole-water recoverable digestates analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS). R^2 is the coefficient of determination. In the confidence intervals table, the Intercept and Co cICP–MS coefficients are the y -intercept and slope, respectively. Results are in micrograms per liter ( μ g/L)

**.**

### Appendix **47**

-20

0 20 40 60 80 100Cr GF-AAS, in μg/L

-20 0 20 40 60 80 100 Cr cICP-MS, in μg/L

Cr GF-AAS, in μg/L = -.003 + 1.05 * Cr cICP-MS, in μg/L; R^2 = .998

-.003 -.489 .482 1.050 1.029 1.071 Coefficient 95% Lower 95% Upper Intercept Cr cICP-MS, in μg/L Confidence Intervals Cr GF-AAS, in μg/L vs. Cr cICP-MS, in μg/L LINEAR REGRESSION EQUATION



### Figure A1 **9**

**.** Linear regression analysis of chromium results from filtered water samples analyzed by graphite furnace–atomic absorption spectrometry (GF–AAS) and collision/reaction cell inductively coupled plasma– mass spectrometry (cICP–MS). R^2 is the coefficient of determination. In the confidence intervals table, the Intercept and Cr cICP–MS coefficients are the y -intercept and slope, respectively. Results are in micrograms per liter ( μ g/L)

**.**

### 48 **Determination of Elements Using Collision/Reaction Cell ICP–MS**

-5 0 5 10 15 20 25 30 35 40 45Cr GF-AAS, in μg/L

-5 0 5 10 15 20 25 30 35 40 45 Cr cICP-MS, in μg/L

Cr GF-AAS, in μg/L = .232 + .921 * Cr cICP-MS, in μg/L; R^2 = .986

.232 -.274 .738 .921 .874 .969 Coefficient 95% Lower 95% Upper Intercept Cr cICP-MS, in μg/L Confidence Intervals Cr GF-AAS, in μg/L vs. Cr cICP-MS, in μg/L LINEAR REGRESSION EQUATION



### Figure A **2 0.**  Linear regression analysis of chromium results from whole-water recoverable digestates analyzed by graphite furnace–atomic absorption spectrometry (GF–AAS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS). R^2 is the coefficient of determination. In the confidence intervals table, the Intercept and Cr cICP–MS coefficients are the y -intercept and slope, respectively. Results are in micrograms per liter ( μ g/L)

**.**

### Appendix **49**

-20

0 20 40 60 80 100Cu ICP-MS, in μg/L

-20 0 20 40 60 80 100 Cu cICP-MS, in μg/L

Cu ICP-MS, in μg/L = .299 + .964 * Cu cICP-MS, in μg/L; R^2 = .999

.299 .098 .499 .964 .953 .975 Coefficient 95% Lower 95% Upper Intercept Cu cICP-MS, in μg/L Confidence Intervals Cu ICP-MS, in μg/L vs. Cu cICP-MS, in μg/L LINEAR REGRESSION EQUATION



### Figure A **2 1.**  Linear regression analysis of copper results from filtered water samples analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS). R^2 is the coefficient of determination. In the confidence intervals table, the Intercept and Cu cICP–MS coefficients are the y -intercept and slope, respectively. Results are in micrograms per liter ( μ g/L).

### 5 **0 Determination of Elements Using Collision/Reaction Cell ICP–MS** 

-5 0 5 10 15 20 25Cu ICP-MS, in μg/L

-5 0 5 10 15 20 25 Cu cICP-MS, in μg/L

Cu ICP-MS, in μg/L = -.034 + 1.22 * Cu cICP-MS, in μg/L; R^2 = .981

-.034 -.463 .396 1.220 1.147 1.294 Coefficient 95% Lower 95% Upper Intercept Cu cICP-MS, in μg/L Confidence Intervals Cu ICP-MS, in μg/L vs. Cu cICP-MS, in μg/L LINEAR REGRESSION EQUATION



### Figure A **22**

**.** Linear regression analysis of copper results from whole-water recoverable digestates analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS). R^2 is the coefficient of determination. In the confidence intervals table, the Intercept and Cu cICP–MS coefficients are the y -intercept and slope, respectively. Results are in micrograms per liter ( μ g/L).

### Appendix **5 1** 

-20

0 20 40 60 80 100 120Fe ICP-AES, in μg/L

-20 0 20 40 60 80 100 120 Fe cICP-MS, in μg/L

Fe ICP-AES, in μg/L = -.035 + .934 * Fe cICP-MS, in μg/L; R^2 = .997

-.035 -.549 .480 .934 .913 .955 Coefficient 95% Lower 95% Upper Intercept Fe cICP-MS, in μg/L Confidence Intervals Fe ICP-AES, in μg/L vs. Fe cICP-MS, in μg/L LINEAR REGRESSION EQUATION



### Figure A **23**

**.** Linear regression analysis of iron results from filtered water samples analyzed by inductively coupled plasma–atomic emission spectrometry (ICP–AES) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS). R^2 is the coefficient of determination. In the confidence intervals table, the Intercept and Fe cICP–MS coefficients are the y -intercept and slope, respectively. Results are in micrograms per liter ( μ g/L)

**.**1 1E1 1E2 1E3 1E4 1E5Fe ICP-AES, in μg/L

1 1E1 1E2 1E3 1E4 1E5 Fe cICP-MS, in μg/L

Fe ICP-AES, in μg/L = -26.485 + 1.078 * Fe cICP-MS, in μg/L; R^2 = 1

-26.485 -44.006 -8.963

1.078 1.069 1.087 Coefficient 95% Lower 95% Upper Intercept Fe cICP-MS, in μg/L Confidence Intervals Fe ICP-AES, in μg/L vs. Fe cICP-MS, in μg/L LINEAR REGRESSION EQUATION



### Figure A **24**

**.** Linear regression analysis of iron results from whole-water recoverable digestates analyzed by inductively coupled plasma–atomic emission spectrometry (ICP–AES) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS). R^2 is the coefficient of determination. In the confidence intervals table, the Intercept and Fe cICP–MS coefficients are the y-intercept and slope, respectively. Results are in micrograms per liter ( μ g/L). 

### 52 **Determination of Elements Using Collision/Reaction Cell ICP–MS**-2 0 2 4 6 8 10K ICP-AES, in mg/L

-2 0 2 4 6 8 10 K cICP-MS, in mg/L

K ICP-AES, in mg/L = -.112 + 1.048 * K cICP-MS, in mg/L; R^2 = .998

-.112 -.183 -.040 1.048 1.025 1.070 Coefficient 95% Lower 95% Upper Intercept K cICP-MS, in mg/L Confidence Intervals K ICP-AES, in mg/L vs. K cICP-MS, in mg/L LINEAR REGRESSION EQUATION



### Figure A **25**

**.** Linear regression analysis of potassium results from filtered water samples analyzed by inductively coupled plasma–atomic emission spectrometry (ICP–AES) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS). R^2 is the coefficient of determination. In the confidence intervals table, the Intercept and K cICP–MS coefficients are the y -intercept and slope, respectively. Results are in milligrams per liter (mg/L)

**.** 

### Appendix **53**

### 54 **Determination of Elements Using Collision/Reaction Cell ICP–MS**

0 1 2 3 4 5 6 7 8K ICP-AES, in mg/L

0 1 2 3 4 5 6 7 8 K cICP-MS, in mg/L

K ICP-AES, in mg/L = -.21 + 1.026 * K cICP-MS, in mg/L; R^2 = .998

-.210 -.276 -.145 1.026 1.005 1.047 Coefficient 95% Lower 95% Upper Intercept K cICP-MS, in mg/L Confidence Intervals K ICP-AES, in mg/L vs. K cICP-MS, in mg/L LINEAR REGRESSION EQUATION



### Figure A **26**

**.** Linear regression analysis of potassium results from whole-water recoverable digestates analyzed by inductively coupled plasma–atomic emission spectrometry (ICP–AES) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS). R^2 is the coefficient of determination. In the confidence intervals table, the Intercept and K cICP–MS coefficients are the y -intercept and slope, respectively. Results are in milligrams per liter (mg/L).

### Appendix **55**

-50

0 50 100 150 200 250 300Li ICP-MS, in μg/L

-50 0 50 100 150 200 250 300 Li cICP-MS, in μg/L

Li ICP-MS, in μg/L = 5.659 + 1.208 * Li cICP-MS, in μg/L; R^2 = .992

5.659 1.708 9.610 1.208 1.160 1.255 Coefficient 95% Lower 95% Upper Intercept Li cICP-MS, in μg/L Confidence Intervals Li ICP-MS, in μg/L vs. Li cICP-MS, in μg/L LINEAR REGRESSION EQUATION



### Figure A **27**

**.** Linear regression analysis of lithium results from filtered water samples analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS). R^2 is the coefficient of determination. In the confidence intervals table, the Intercept and Li cICP–MS coefficients are the y -intercept and slope, respectively. Results are in micrograms per liter ( μ g/L).

### 56 **Determination of Elements Using Collision/Reaction Cell ICP–MS**

**Figure A 28** 

**.** Linear regression analysis of lithium results from whole-water recoverable digestates analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS). R^2 is the coefficient of determination. In the confidence intervals table, the Intercept and Li cICP–MS coefficients are the y -intercept and slope, respectively. Results are in micrograms per liter ( μ g/L).

-20

0 20 40 60 80 100 120Li ICP-MS, in μg/L

-20 0 20 40 60 80 100 120 Li cICP-MS, in μg/L

Li ICP-MS, in μg/L = 1.472 + .863 * Li cICP-MS, in μg/L; R^2 = .987

1.472 .018 2.926

.863 .821 .906 Coefficient 95% Lower 95% Upper Intercept Li cICP-MS, in μg/L Confidence Intervals Li ICP-MS, in μg/L vs. Li cICP-MS, in μg/L LINEAR REGRESSION EQUATION

### Appendix **57**

-20

0 20 40 60 80 100 120Mg ICP-AES, in mg/L

-20 0 20 40 60 80 100 120 Mg cICP-MS, in mg/L

Mg ICP-AES, in mg/L = -.779 + .982 * Mg cICP-MS, in mg/L; R^2 = .999

-.779 -1.299 -.260 .982 .967 .997 Coefficient 95% Lower 95% Upper Intercept Mg cICP-MS, in mg/L Confidence Intervals Mg ICP-AES, in mg/L vs. Mg cICP-MS, in mg/L LINEAR REGRESSION EQUATION



### Figure A **29**

**.** Linear regression analysis of magnesium results from filtered water samples analyzed by inductively coupled plasma–atomic emission spectrometry (ICP–AES) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS). R^2 is the coefficient of determination. In the confidence intervals table, the Intercept and Mg cICP–MS coefficients are the y -intercept and slope, respectively. Results are in milligrams per liter (mg/L).

### 58 **Determination of Elements Using Collision/Reaction Cell ICP–MS**

-20

0 20 40 60 80 100 120Mg ICP-AES, in mg/L

-20 0 20 40 60 80 100 120 Mg cICP-MS, in mg/L

Mg ICP-AES, in mg/L = -.594 + .993 * Mg cICP-MS, in mg/L; R^2 = .998

-.594 -1.206 .019 .993 .975 1.011 Coefficient 95% Lower 95% Upper Intercept Mg cICP-MS, in mg/L Confidence Intervals Mg ICP-AES, in mg/L vs. Mg cICP-MS, in mg/L LINEAR REGRESSION EQUATION



### Figure A **3 0.**  Linear regression analysis of magnesium results from whole-water recoverable digestates analyzed by inductively coupled plasma–atomic emission spectrometry (ICP–AES) and collision/ reaction cell inductively coupled plasma–mass spectrometry (cICP–MS). R^2 is the coefficient of determination. In the confidence intervals table, the Intercept and Mg cICP–MS coefficients are the y -intercept and slope, respectively. Results are in milligrams per liter (mg/L).

### Appendix **59**

-25 25 75 125 175Mn ICP-MS, in μg/L

-25 25 75 125 175 Mn cICP-MS, in μg/L

Mn ICP-MS, in μg/L = .082 + 1.026 * Mn cICP-MS, in μg/L; R^2 = .991

.082 -1.256 1.420 1.026 .983 1.069 Coefficient 95% Lower 95% Upper Intercept Mn cICP-MS, in μg/L Confidence Intervals Mn ICP-MS, in μg/L vs. Mn cICP-MS, in μg/L LINEAR REGRESSION EQUATION



### Figure A **3 1.**  Linear regression analysis of manganese results from filtered water samples analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS). R^2 is the coefficient of determination. In the confidence intervals table, the Intercept and Mn cICP–MS coefficients are the y -intercept and slope, respectively. Results are in micrograms per liter ( μ g/L).

### 6 **0 Determination of Elements Using Collision/Reaction Cell ICP–MS** 

-25

0 25 50 75 100 125 150 175 200 225Mn ICP-MS, in μg/L

-25 0 25 50 75 100 125 150 175 200 225 Mn cICP-MS, in μg/L

Mn ICP-MS, in μg/L = 1.682 + .938 * Mn cICP-MS, in μg/L; R^2 = .994

1.682 -.026 3.390

.938 .907 .969 Coefficient 95% Lower 95% Upper Intercept Mn cICP-MS, in μg/L Confidence Intervals Mn ICP-MS, in μg/L vs. Mn cICP-MS, in μg/L LINEAR REGRESSION EQUATION



### Figure A **32**

**.** Linear regression analysis of manganese results from whole-water recoverable digestates analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS). R^2 is the coefficient of determination. In the confidence intervals table, the Intercept and Mn cICP–MS coefficients are the y -intercept and slope, respectively. Results are in micrograms per liter ( μ g/L).

### Appendix **6 1** 

-20

0 20 40 60 80 100Mo ICP-MS, in μg/L

-20 0 20 40 60 80 100 Mo cICP-MS, in μg/L

Mo ICP-MS, in μg/L = -.112 + 1.045 * Mo cICP-MS, in μg/L; R^2 = 1

-.112 -.239 .016 1.045 1.038 1.053 Coefficient 95% Lower 95% Upper Intercept Mo cICP-MS, in μg/L Confidence Intervals Mo ICP-MS, in μg/L vs. Mo cICP-MS, in μg/L LINEAR REGRESSION EQUATION



### Figure A **33**

**.** Linear regression analysis of molybdenum results from filtered water samples analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS). R^2 is the coefficient of determination. In the confidence intervals table, the Intercept and Mo cICP–MS coefficients are the y -intercept and slope, respectively. Results are in micrograms per liter ( μ g/L).

### 62 **Determination of Elements Using Collision/Reaction Cell ICP–MS**

-2 0 2 4 6 8 10Mo ICP-MS, in μg/L

-2 0 2 4 6 8 10 Mo cICP-MS, in μg/L

Mo ICP-MS, in μg/L = .202 + .847 * Mo cICP-MS, in μg/L; R^2 = .993

.202 .119 .286 .847 .815 .879 Coefficient 95% Lower 95% Upper Intercept Mo cICP-MS, in μg/L Confidence Intervals Mo ICP-MS, in μg/L vs. Mo cICP-MS, in μg/L LINEAR REGRESSION EQUATION



### Figure A **34**

**.** Linear regression analysis of molybdenum results from whole-water recoverable digestates analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS). R^2 is the coefficient of determination. In the confidence intervals table, the Intercept and Mo cICP–MS coefficients are the y -intercept and slope, respectively. Results are in micrograms per liter ( μ g/L).

### Appendix **63**

1 1E1 1E2 1E3Na ICP-AES, in mg/L

1 1E1 1E2 1E3 Na cICP-MS, in mg/L

Na ICP-AES, in mg/L = .273 + .906 * Na cICP-MS, in mg/L; R^2 = 1

.273 -.263 .810 .906 .898 .915 Coefficient 95% Lower 95% Upper Intercept Na cICP-MS, in mg/L Confidence Intervals Na ICP-AES, in mg/L vs. Na cICP-MS, in mg/L LINEAR REGRESSION EQUATION



### Figure A **35**

**.** Linear regression analysis of sodium results from filtered water samples analyzed by inductively coupled plasma–atomic emission spectrometry (ICP–AES) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS). R^2 is the coefficient of determination. In the confidence intervals table, the Intercept and Na cICP–MS coefficients are the y -intercept and slope, respectively. Results are in milligrams per liter (mg/L).

### 64 **Determination of Elements Using Collision/Reaction Cell ICP–MS**

1 1E1 1E2 1E3Na ICP-AES, in mg/L

1 1E1 1E2 1E3 Na cICP-MS, in mg/L

Na ICP-AES, in mg/L = .213 + .942 * Na cICP-MS, in mg/L; R^2 = .999

.213 -.382 .807 .942 .932 .953 Coefficient 95% Lower 95% Upper Intercept Na cICP-MS, in mg/L Confidence Intervals Na ICP-AES, in mg/L vs. Na cICP-MS, in mg/L LINEAR REGRESSION EQUATION



### Figure A **36**

**.** Linear regression analysis of sodium results from whole-water recoverable digestates analyzed by inductively coupled plasma–atomic emission spectrometry (ICP–AES) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS). R^2 is the coefficient of determination. In the confidence intervals table, the Intercept and Na cICP–MS coefficients are the y -intercept and slope, respectively. Results are in milligrams per liter (mg/L).

### Appendix **65**

-20

0 20 40 60 80 100Ni ICP-MS, in μg/L

-20 0 20 40 60 80 100 Ni cICP-MS, in μg/L

Ni ICP-MS, in μg/L = .494 + 1.045 * Ni cICP-MS, in μg/L; R^2 = .999

.494 .285 .704 1.045 1.035 1.056 Coefficient 95% Lower 95% Upper Intercept Ni cICP-MS, in μg/L Confidence Intervals Ni ICP-MS, in μg/L vs. Ni cICP-MS, in μg/L LINEAR REGRESSION EQUATION



### Figure A **37**

**.** Linear regression analysis of nickel results from filtered water samples analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS). R^2 is the coefficient of determination. In the confidence intervals table, the Intercept and Ni cICP–MS coefficients are the y -intercept and slope, respectively. Results are in micrograms per liter ( μ g/L).

### 66 **Determination of Elements Using Collision/Reaction Cell ICP–MS**

-2 0 2 4 6 8 10 12 14 16 18 20Ni ICP-MS, in μg/L

-2 0 2 4 6 8 10 12 14 16 18 20 Ni cICP-MS, in μg/L

Ni ICP-MS, in μg/L = .188 + 1.128 * Ni cICP-MS, in μg/L; R^2 = .99

.188 .016 .360 1.128 1.080 1.176 Coefficient 95% Lower 95% Upper Intercept Ni cICP-MS, in μg/L Confidence Intervals Ni ICP-MS, in μg/L vs. Ni cICP-MS, in μg/L LINEAR REGRESSION EQUATION



### Figure A **38**

**.** Linear regression analysis of nickel results from whole-water recoverable digestates analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS). R^2 is the coefficient of determination. In the confidence intervals table, the Intercept and Ni cICP–MS coefficients are the y -intercept and slope, respectively. Results are in micrograms per liter ( μ g/L).

### Appendix **67**

-10

0 10 20 30 40 50Pb ICP-MS, in μg/L

-10 0 10 20 30 40 50 Pb cICP-MS, in μg/L

Pb ICP-MS, in μg/L = .024 + .922 * Pb cICP-MS, in μg/L; R^2 = 1

.024 -.047 .095 .922 .917 .928 Coefficient 95% Lower 95% Upper Intercept Pb cICP-MS, in μg/L Confidence Intervals Pb ICP-MS, in μg/L vs. Pb cICP-MS, in μg/L LINEAR REGRESSION EQUATION



### Figure A **39**

**.** Linear regression analysis of lead results from filtered water samples analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS). R^2 is the coefficient of determination. In the confidence intervals table, the Intercept and Pb cICP–MS coefficients are the y -intercept and slope, respectively. Results are in micrograms per liter ( μ g/L).

### 68 **Determination of Elements Using Collision/Reaction Cell ICP–MS**

-2 0 2 4 6 8 10 12 14 16 18 20Pb ICP-MS, in μg/L

-2 0 2 4 6 8 10 12 14 16 18 20 Pb cICP-MS, in μg/L

Pb ICP-MS, in μg/L = .039 + 1.089 * Pb cICP-MS, in μg/L; R^2 = .99

.039 -.167 .244 1.089 1.043 1.135 Coefficient 95% Lower 95% Upper Intercept Pb cICP-MS, in μg/L Confidence Intervals Pb ICP-MS, in μg/L vs. Pb cICP-MS, in μg/L LINEAR REGRESSION EQUATION



### Figure A **4 0.**  Linear regression analysis of lead results from whole-water recoverable digestates analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS). R^2 is the coefficient of determination. In the confidence intervals table, the Intercept and Pb cICP–MS coefficients are the y -intercept and slope, respectively. Results are in micrograms per liter ( μ g/L).

### Appendix **69**

-10

0 10 20 30 40 50Sb ICP-MS, in μg/L

-10 0 10 20 30 40 50 Sb cICP-MS, in μg/L

Sb ICP-MS, in μg/L = .016 + .95 * Sb cICP-MS, in μg/L; R^2 = 1

.016 .006 .026 .950 .949 .952 Coefficient 95% Lower 95% Upper Intercept Sb cICP-MS, in μg/L Confidence Intervals Sb ICP-MS, in μg/L vs. Sb cICP-MS, in μg/L LINEAR REGRESSION EQUATION



### Figure A **4 1.**  Linear regression analysis of antimony results from filtered water samples analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS). R^2 is the coefficient of determination. In the confidence intervals table, the Intercept and Sb cICP–MS coefficients are the y -intercept and slope, respectively. Results are in micrograms per liter ( μ g/L).

### 7 **0 Determination of Elements Using Collision/Reaction Cell ICP–MS** 

-.2

0 .2 .4 .6 .8 1 1.2Sb ICP-MS, in μg/L

-.2 0 .2 .4 .6 .8 1 1.2 Sb cICP-MS, in μg/L

Sb ICP-MS, in μg/L = -.161 + 1.846 * Sb cICP-MS, in μg/L; R^2 = .829

-.161 -.249 -.073 1.846 1.484 2.207 Coefficient 95% Lower 95% Upper Intercept Sb cICP-MS, in μg/L Confidence Intervals Sb ICP-MS, in μg/L vs. Sb cICP-MS, in μg/L LINEAR REGRESSION EQUATION



### Figure A **42**

**.** Linear regression analysis of antimony results from whole-water recoverable digestates analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS). R^2 is the coefficient of determination. In the confidence intervals table, the Intercept and Sb cICP–MS coefficients are the y -intercept and slope, respectively. Results are in micrograms per liter ( μ g/L).

### Appendix **7 1** 

-10

0 10 20 30 40 50Se ICP-MS, in μg/L

-10 0 10 20 30 40 50 Se cICP-MS, in μg/L

Se ICP-MS, in μg/L = .134 + .929 * Se cICP-MS, in μg/L; R^2 = .998

.134 -.035 .303 .929 .913 .944 Coefficient 95% Lower 95% Upper Intercept Se cICP-MS, in μg/L Confidence Intervals Se ICP-MS, in μg/L vs. Se cICP-MS, in μg/L LINEAR REGRESSION EQUATION



### Figure A **43**

**.** Linear regression analysis of selenium results from filtered water samples analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS). R^2 is the coefficient of determination. In the confidence intervals table, the Intercept and Se cICP–MS coefficients are the y -intercept and slope, respectively. Results are in micrograms per liter ( μ g/L)

**.**

### 72 **Determination of Elements Using Collision/Reaction Cell ICP–MS**

-.5

0 .5 1 1.5

2 2.5

3Se ICP-MS, in μg/L

-.5 0 .5 1 1.5 2 2.5 3 Se cICP-MS, in μg/L

Se ICP-MS, in μg/L = .255 + .831 * Se cICP-MS, in μg/L; R^2 = .875

.255 .133 .378 .831 .695 .967 Coefficient 95% Lower 95% Upper Intercept Se cICP-MS, in μg/L Confidence Intervals Se ICP-MS, in μg/L vs. Se cICP-MS, in μg/L LINEAR REGRESSION EQUATION



### Figure A **44**

**.** Linear regression analysis of selenium results from whole-water recoverable digestates analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS). R^2 is the coefficient of determination. In the confidence intervals table, the Intercept and Se cICP–MS coefficients are the y -intercept and slope, respectively. Results are in micrograms per liter ( μ g/L).

### Appendix **73**

-20

0 20 40 60 80Si ICP-AES, in mg/L

-20 0 20 40 60 80 Si cICP-MS, in mg/L

Si ICP-AES, in mg/L = .339 + .971 * Si cICP-MS, in mg/L; R^2 = .993

.339 -.890 1.567 .971 .937 1.005 Coefficient 95% Lower 95% Upper Intercept Si cICP-MS, in mg/L Confidence Intervals Si ICP-AES, in mg/L vs. Si cICP-MS, in mg/L LINEAR REGRESSION EQUATION



### Figure A **45**

**.** Linear regression analysis of silicon (as SiO 2 

### ) results from filtered water samples analyzed by inductively coupled plasma–atomic emission spectrometry (ICP–AES) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS). R^2 is the coefficient of determination. In the confidence intervals table, the Intercept and Si cICP–MS coefficients are the y -intercept and slope, respectively. Results are in milligrams per liter (mg/L).

### 74 **Determination of Elements Using Collision/Reaction Cell ICP–MS**

0 5 10 15 20 25 30 35 40Si ICP-AES, in mg/L

0 5 10 15 20 25 30 35 40 Si cICP-MS, in mg/L

Si ICP-AES, in mg/L = .238 + 1.136 * Si cICP-MS, in mg/L; R^2 = .946

.238 -1.999 2.475 1.136 1.014 1.259 Coefficient 95% Lower 95% Upper Intercept Si cICP-MS, in mg/L Confidence Intervals Si ICP-AES, in mg/L vs. Si cICP-MS, in mg/L LINEAR REGRESSION EQUATION



### Figure A **46**

**.** Linear regression analysis of silicon (as SiO 2 

### ) results from whole-water recoverable digestates analyzed by inductively coupled plasma–atomic emission spectrometry (ICP–AES) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS). R^2 is the coefficient of determination. In the confidence intervals table, the Intercept and Si cICP–MS coefficients are the y -intercept and slope, respectively. Results are in milligrams per liter (mg/L).

### Appendix **75**

-1000 0 1000 2000 3000 4000 5000 6000Sr ICP-MS, in μg/L

-1000 0 1000 2000 3000 4000 5000 6000 Sr cICP-MS, in μg/L

Sr ICP-MS, in μg/L = 68.799 + .87 * Sr cICP-MS, in μg/L; R^2 = .988

68.799 9.040 128.559

.870 .829 .911 Coefficient 95% Lower 95% Upper Intercept Sr cICP-MS, in μg/L Confidence Intervals Sr ICP-MS, in μg/L vs. Sr cICP-MS, in μg/L LINEAR REGRESSION EQUATION



### Figure A **47**

**.** Linear regression analysis of strontium results from filtered water samples analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS). R^2 is the coefficient of determination. In the confidence intervals table, the Intercept and Sr cICP–MS coefficients are the y -intercept and slope, respectively. Results are in micrograms per liter ( μ g/L).

### 76 **Determination of Elements Using Collision/Reaction Cell ICP–MS**

20 200 2000Sr ICP-MS, in μg/L

20 200 2000 Sr cICP-MS, in μg/L

Sr ICP-MS, in μg/L = -2.933 + 1.004 * Sr cICP-MS, in μg/L; R^2 = .999

-2.933 -6.698 .831 1.004 .987 1.020 Coefficient 95% Lower 95% Upper Intercept Sr cICP-MS, in μg/L Confidence Intervals Sr ICP-MS, in μg/L vs. Sr cICP-MS, in μg/L LINEAR REGRESSION EQUATION



### Figure A **48**

**.** Linear regression analysis of strontium results from whole-water recoverable digestates analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS). R^2 is the coefficient of determination. In the confidence intervals table, the Intercept and Sr cICP–MS coefficients are the y -intercept and slope, respectively. Results are in micrograms per liter ( μ g/L).

### Appendix **77**

-10

0 10 20 30 40 50 60Tl ICP-MS, in μg/L

-10 0 10 20 30 40 50 60 Tl cICP-MS, in μg/L

Tl ICP-MS, in μg/L = .011 + .873 * Tl cICP-MS, in μg/L; R^2 = 1

.011 -.035 .057 .873 .870 .875 Coefficient 95% Lower 95% Upper Intercept Tl cICP-MS, in μg/L Confidence Intervals Tl ICP-MS, in μg/L vs. Tl cICP-MS, in μg/L LINEAR REGRESSION EQUATION



### Figure A **49**

**.** Linear regression analysis of thallium results from filtered water samples analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS). R^2 is the coefficient of determination. In the confidence intervals table, the Intercept and Tl cICP–MS coefficients are the y -intercept and slope, respectively. Results are in micrograms per liter ( μ g/L)

**.**

### 78 **Determination of Elements Using Collision/Reaction Cell ICP–MS**

**Figure A 5**  **0.** Linear regression analysis of thallium results from whole-water recoverable digestates analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS). R^2 is the coefficient of determination. In the confidence intervals table, the Intercept and Tl cICP–MS coefficients are the y -intercept and slope, respectively. Results are in micrograms per liter ( μ g/L)

**.** -.5

0 .5 1 1.5

2 2.5

3 3.5Tl ICP-MS, in μg/L

-.5 0 .5 1 1.5 2 2.5 3 3.5 Tl cICP-MS, in μg/L

Tl ICP-MS, in μg/L = .072 + .942 * Tl cICP-MS, in μg/L; R^2 = .973

.072 .031 .113 .942 .874 1.009 Coefficient 95% Lower 95% Upper Intercept Tl cICP-MS, in μg/L Confidence Intervals Tl ICP-MS, in μg/L vs. Tl cICP-MS, in μg/L LINEAR REGRESSION EQUATION

### Appendix **79**

-10

0 10 20 30 40 50U ICPMS, in μg/L

-10 0 10 20 30 40 50 U cICP-MS, in μg/L

U ICPMS, in μg/L = .246 + .92 * U cICP-MS, in μg/L; R^2 = .999

.246 .089 .403 .920 .905 .935 Coefficient 95% Lower 95% Upper Intercept U cICP-MS, in μg/L Confidence Intervals U ICPMS, in μg/L vs. U cICP-MS, in μg/L LINEAR REGRESSION EQUATION



### Figure A **5 1.**  Linear regression analysis of uranium results from filtered water samples analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS). R^2 is the coefficient of determination. In the confidence intervals table, the Intercept and U cICP–MS coefficients are the y -intercept and slope, respectively. Results are in micrograms per liter ( μ g/L).

### 8 **0 Determination of Elements Using Collision/Reaction Cell ICP–MS** 

-2 0 2 4 6 8 10 12 14 16 18 20U ICP-MS, in μg/L

-2 0 2 4 6 8 10 12 14 16 18 20 U cICP-MS, in μg/L

U ICP-MS, in μg/L = .046 + 1.024 * U cICP-MS, in μg/L; R^2 = .973

.046 -.313 .405 1.024 .951 1.097 Coefficient 95% Lower 95% Upper Intercept U cICP-MS, in μg/L Confidence Intervals U ICP-MS, in μg/L vs. U cICP-MS, in μg/L LINEAR REGRESSION EQUATION



### Figure A **52**

**.** Linear regression analysis of uranium results from whole-water recoverable digestates analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS). R^2 is the coefficient of determination. In the confidence intervals table, the Intercept and U cICP–MS coefficients are the y -intercept and slope, respectively. Results are in micrograms per liter (μg/L).

### Appendix **8 1** 

1E-2 1E-1 1 1E1 1E2 1E3V ICP-MS, in μg/L

1E-2 1E-1 1 1E1 1E2 1E3 V cICP-MS, in μg/L

V ICP-MS, in μg/L = -.162 + 1.01 * V cICP-MS, in μg/L; R^2 = 1

-.162 -.803 .478 1.010 1.005 1.014 Coefficient 95% Lower 95% Upper Intercept V cICP-MS, in μg/L Confidence Intervals V ICP-MS, in μg/L vs. V cICP-MS, in μg/L LINEAR REGRESSION EQUATION



### Figure A **53**

**.** Linear regression analysis of vanadium results from filtered water samples analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS). R^2 is the coefficient of determination. In the confidence intervals table, the Intercept and V cICP–MS coefficients are the y -intercept and slope, respectively. Results are in micrograms per liter ( μ g/L).

### 82 **Determination of Elements Using Collision/Reaction Cell ICP–MS**

-10

0 10 20 30 40 50 60 70 80V ICP-AES, in μg/L

-10 0 10 20 30 40 50 60 70 80 V cICP-MS, in μg/L

V ICP-AES, in μg/L = .716 + .9 * V cICP-MS, in μg/L; R^2 = .99

.716 -.035 1.466 .900 .862 .939 Coefficient 95% Lower 95% Upper Intercept V cICP-MS, in μg/L Confidence Intervals V ICP-AES, in μg/L vs. V cICP-MS, in μg/L LINEAR REGRESSION EQUATION



### Figure A **54 . L**  inear regression analysis of vanadium results from whole-water recoverable digestates analyzed by inductively coupled plasma–atomic emission spectrometry (ICP–AES) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS). R^2 is the coefficient of determination. In the confidence intervals table, the Intercept and V cICP–MS coefficients are the y -intercept and slope, respectively. Results are in micrograms per liter ( μ g/L).

### Appendix **83**

1E-1 1 1E1 1E2W ICP-MS, in μg/L

1E-1 1 1E1 1E2 W cICP-MS, in μg/L

W ICP-MS, in μg/L = .031 + .874 * W cICP-MS, in μg/L; R^2 = 1

.031 -.013 .076 .874 .873 .876 Coefficient 95% Lower 95% Upper Intercept W cICP-MS, in μg/L Confidence Intervals W ICP-MS, in μg/L vs. W cICP-MS, in μg/L LINEAR REGRESSION EQUATION



### Figure A **55**

**.** Linear regression analysis of tungsten results from filtered water samples analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS). R^2 is the coefficient of determination. In the confidence intervals table, the Intercept and W cICP–MS coefficients are the y -intercept and slope, respectively. Results are in micrograms per liter ( μ g/L)

**.**

### 84 **Determination of Elements Using Collision/Reaction Cell ICP–MS**

-.05

0 .05 .1 .15 .2W ICP-MS, in μg/L

-.05 0 .05 .1 .15 .2 W cICP-MS, in μg/L

W ICP-MS, in μg/L = -.016 + 1.122 * W cICP-MS, in μg/L; R^2 = .617

-.016 -.039 .008 1.122 .654 1.589 Coefficient 95% Lower 95% Upper Intercept W cICP-MS, in μg/L Confidence Intervals W ICP-MS, in μg/L vs. W cICP-MS, in μg/L LINEAR REGRESSION EQUATION



### Figure A **56**

**.** Linear regression analysis of tungsten results from whole-water recoverable digestates analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS). R^2 is the coefficient of determination. In the confidence intervals table, the Intercept and W cICP–MS coefficients are the y -intercept and slope, respectively. Results are in micrograms per liter ( μ g/L)

**.**

### Appendix **85**

1E-2 1E-1 1 1E1 1E2Zn ICP-MS, in μg/L

1E-2 1E-1 1 1E1 1E2 Zn cICP-MS, in μg/L

Zn ICP-MS, in μg/L = -.052 + 1.02 * Zn cICP-MS, in μg/L; R^2 = 1

-.052 -.692 .587 1.020 1.013 1.028 Coefficient 95% Lower 95% Upper Intercept Zn cICP-MS, in μg/L Confidence Intervals Zn ICP-MS, in μg/L vs. Zn cICP-MS, in μg/L LINEAR REGRESSION EQUATION



### Figure A **57**

**.** Linear regression analysis of zinc results from filtered water samples analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma– mass spectrometry (cICP–MS). R^2 is the coefficient of determination. In the confidence intervals table, the Intercept and Zn cICP–MS coefficients are the y -intercept and slope, respectively. Results are in micrograms per liter ( μ g/L).

### 86 **Determination of Elements Using Collision/Reaction Cell ICP–MS**

-50

0 50 100 150 200 250 300 350 400Zn ICP-MS, in μg/L

-50 0 50 100 150 200 250 300 350 400 Zn cICP-MS, in μg/L

Zn ICP-MS, in μg/L = .538 + .995 * Zn cICP-MS, in μg/L; R^2 = .999

.538 -.560 1.637 .995 .983 1.008 Coefficient 95% Lower 95% Upper Intercept Zn cICP-MS, in μg/L Confidence Intervals Zn ICP-MS, in μg/L vs. Zn cICP-MS, in μg/L LINEAR REGRESSION EQUATION



### Figure A **58**

**.** Linear regression analysis of zinc results from whole-water recoverable digestates analyzed by inductively coupled plasma–mass spectrometry (ICP–MS) and collision/reaction cell inductively coupled plasma–mass spectrometry (cICP–MS). R^2 is the coefficient of determination. In the confidence intervals table, the Intercept and Zn cICP–MS coefficients are the y -intercept and slope, respectively. Results are in micrograms per liter ( μ g/L).

### Glossary **87**



# Glossary

**Bias** Systematic error that is manifested as a consistent positive or negative deviation from the known or true value (Taylor, 1990). The error can be positive or negative. Positive error can result from sample contamination or spectral interference, whereas negative error can result from analyte loss or signal suppression. Bias differs from random error which shows no such consistent or systematic deviation. **F-pseudosigma** A nonparametric, resistant measure of data spread defined as the inter

quartile range of the data divided by 1.349 (Hoaglin and others, 1983). F-pseudosigma and the standard deviation of the data will benearly equivalent if the data have a nearnormal distribution. **Long-term method detection level (LT–MDL)** The minimum concentration of an element that can be measured and reported with 99- percent confidence that the elemental concen

tration is greater than zero. The LT–MDL is calculated from replicate analyses of samples fortified with all the method elements, and includes variability introduced by multiple instruments, multiple analysts, and multiple calibrations over 6 to 12 months (Childress and others, 1999).
**Matrix** The substrate of a test sample (National Environmental Laboratory Accredi

tation Conference, 2003). **Matrix spike** A sample prepared by adding a known mass of target analyte to a speci

fied amount of matrix sample for which an independent estimate of target analyte concentration is available. Matrix spike is used to determine the effect of the matrix on a method’s recovery efficiency (National Envi

ronmental Laboratory Accreditation Confer

ence, 2003). **Method detection limit (MDL)** The minimum concentration of an element that can be mea

sured and reported with 99-percent confidence that the elemental concentration is greater than zero and is determined from analysis of a sample in a given matrix containing the ele

ment of interest (U.S. Environmental Protec

tion Agency, 2000). **Spike** A known mass of target analyte added to a blank sample or subsample; used to deter

mine the recovery efficiency or for other qual

ity-control purposes (National Environmental Laboratory Accreditation Conference, 2003). **Variability** Random error in independent measurements as the result of repeated appli

cation of the process under specific condi

tions. Precision is a measure of variability in experimental data that can be statistically characterized by the standard deviation (Taylor, 1990).Manuscript approved for publication, November 18, 2005 Prepared by the Publishing Group, U.S. Geological Survey,

National Water Quality Laboratory, Denver, Colorado USGS Publishing Staff Editorial Assistance by Jon W. Raese and Keith L. Lucey Cover Designed by Suzanne C. Roberts Report Preparation by Barbara L. Kemp Technical Reviews Anthony Bednar, U.S. Army Corps of Engineers David A. Roth, USGS, National Research Program Jeffrey W. Pritt, USGS, National Water Quality Laboratory Alfred J. Driscoll, USGS, National Water Quality Laboratory Peter F. Rogerson, USGS, Office of Water Quality For more information concerning the research in this report, contact the National Water Quality Laboratory, Laboratory Chief U.S. Geological Survey, P.O. Box 25046, MS 407 Denver Federal Center Denver, Colorado 80225-0046 http://nwql.cr.usgs.govGarbarino and others**—Determination of Elements Using Collision/Reaction Cell ICP–MS —** Techniques and Methods Book 5–B1

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