U.S. Department of the Interior

U.S. Geological Survey

Scientific Investigations Report 2012–5139

Prepared in cooperation with the California State Water Resources Control Board

A product of the California Groundwater Ambient Monitoring and Assessment (GAMA) Program

Evaluation of Volatile Organic Compound (VOC) Blank Data 

and Application of Study Reporting Levels to Groundwater 

Data Collected for the California GAMA Priority Basin 

Project, May 2004 through September 2010
Cover: 

Left: Field crew member collecting VOC samples inside a mobile laboratory using 

long sampling lines. (Photograph by Cathy M. Munday, U.S. Geological Survey.)

Right: Field crew members collecting VOC samples at a well site using short 

sampling lines. (Photograph by Michael T. Land, U.S. Geological Survey.)
Evaluation of Volatile Organic Compound (VOC) 

Blank Data and Application of Study Reporting 

Levels to Groundwater Data Collected for the 

California GAMA Priority Basin Project, 

May 2004 through September 2010

By Miranda S. Fram, Lisa D. Olsen, and Kenneth Belitz

A product of the California Groundwater Ambient Monitoring and Assessment 

(GAMA) Program 

Prepared in cooperation with the California State Water Resources Control Board

Scientific Investigations Report 2012–5139

U.S. Department of the Interior

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

KEN SALAZAR, Secretary

U.S. Geological Survey

Marcia K. McNutt, Director

U.S. Geological Survey, Reston, Virginia: 2012

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reproduce any copyrighted materials contained within this report.

Suggested citation:

Fram, M.S., Olsen, L.D., and Belitz, Kenneth, 2012, Evaluation of volatile organic compound (VOC) blank data and 

application of study reporting levels to groundwater data collected for the California GAMA Priority Basin Project, 

May 2004 through September 2010: U.S. Geological Survey Scientific Investigations Report 2012–5139, 94 p.
iii

Contents

Abstract...........................................................................................................................................................1

Introduction ....................................................................................................................................................2

Use of Study Reporting Levels............................................................................................................4

Philosophy of Quality-Control Evaluation of Blanks........................................................................5

Purpose and Scope .............................................................................................................................6

Methods Used to Collect and Evaluate VOC Data....................................................................................7

Field Methods........................................................................................................................................7

Groundwater Samples ................................................................................................................7

Blanks .........................................................................................................................................10

Laboratory Methods...........................................................................................................................11

Data Analysis Methods......................................................................................................................14

Identification of Representative Field Blanks .......................................................................15

Definition of Study Reporting Levels (SRLs)..........................................................................16

Binomial Probability Approach.......................................................................................16

Maximum Concentration Approach ..............................................................................18

Maximum LT-MDL Approach ..........................................................................................18

Evaluation of Potential Sources of Contamination to Blanks and Groundwater

Samples and Selection of Appropriate SRLs....................................................................18

Statistical Tests Used in Identification of Representative Field Blanks and Evaluation

to Infer Potential Sources of Contamination ....................................................................19

Quality-Control Assessment Results ........................................................................................................20

Identification of VOCs for Which the SRL Approach Can be Applied and of

Representative Quality-Control Field Blanks (QCFBs) for Use in Calculation 

of SRLs ....................................................................................................................................20

Minimal Contamination from the Certified Blank Water .....................................................20

Acetone, 2-Butanone, and Tetrahydrofuran Contamination Associated with

Methanol........................................................................................................................20

Inadvertent Field Test of Contamination by Methanol................................................20

Acetone, 2-Butanone, and Tetrahydrofuran Contamination in Field Blanks...........26

Acetone, 2-Butanone, and Tetrahydrofuran Contamination in Groundwater

Samples ................................................................................................................26

SRLs for Acetone, 2-Butanone, and Tetrahydrofuran.................................................31

Differences Between Sample-Collection Equipment Configurations...............................31

Quality-Control Field Blanks (QCFBs) .....................................................................................32
iv

Contents—Continued

Quality-Control Assessment Results—Continued

Evaluation of Potential Sources of Contamination, Selection of SRLs, and Application

of SRLs to Groundwater Data for VOCs Detected in Blanks..........................................32

Hydrocarbons.............................................................................................................................32

Ethylbenzene, m- and p-Xylenes, o-Xylene, Benzene, and Styrene ........................32

Inferred Mechanisms of Contamination .............................................................38

SRLs for Ethylbenzene, m- and p-Xylenes, o-Xylene, Benzene, and

Styrene.........................................................................................................40

Toluene ...............................................................................................................................45

Inferred Mechanisms of Contamination ..............................................................45

SRL for Toluene ........................................................................................................48

1,2,4-Trimethylbenzene ....................................................................................................48

Inferred Mechanisms of Contamination ..............................................................50

SRL for 1,2,4-Trimethylbenzene .............................................................................53

Chlorinated Organic Solvents..................................................................................................54

Dichloromethane, 1,1-Dichloroethene, and Trichloroethene....................................54

Tetrachloroethene ............................................................................................................54

Other VOCs..................................................................................................................................54

Bromodichloromethane and Trichlorofluoromethane................................................54

Carbon Disulfide................................................................................................................61

Inferred Source of Contamination ........................................................................61

SRL for Carbon Disulfide.........................................................................................61

Chloroform .........................................................................................................................63

Inferred Source of Contamination ........................................................................63

SRL for Chloroform ..................................................................................................63

Application of SRLs and Maximum LT-MDLS..........................................................................................65

Effect of LT-MDL Changes on VOC Detection Frequencies.........................................................65

LT-MDLs and Probabilities of False-Positive Detections .............................................................67

Assessment of Methods Used for Determining Study Reporting Levels ...........................................67

Summary and Conclusions.........................................................................................................................69

Acknowledgments.......................................................................................................................................71

References Cited..........................................................................................................................................71

Appendix........................................................................................................................................................74
v

Figures

Figure 1. Map of the 32 study units sampled for the California GAMA Priority Basin 

Project, May 2004 through September 2010 ............................................. 3

Figure 2. Graphs showing number of groundwater samples and field and source-solution

blanks collected per month by the California GAMA Priority Basin Project, and

number of laboratory instrument blanks analyzed per month for volatile organic

compounds by the USGS National Water Quality Laboratory, May 2004 through

September 2010.............................................................................. 8

Figure 3. Graphs comparing detection frequencies in field blanks collected at production

wells by the National Water-Quality Assessment (NAWQA) Program and

detection frequencies in all field blanks collected with long and short sampling

lines by the GAMA Priority Basin Project, and quality-control field blanks

collected with long and short sampling lines and inferred to be without

contamination by the methanol used to clean field equipment ........................ 22

Figure 4. Chromatograms for three vials of a field blank affected by methanol, 

California GAMA Priority Basin Project, June 25, 2007 ................................. 25

Figure 5. Time-series graph for concentrations of acetone detected in field blanks,

source-solution blanks, laboratory instrument blanks, and groundwater 

samples, California GAMA Priority Basin Project, May 2004 through 

September 2010.............................................................................. 27

Figure 6. Time-series graph for concentrations of 2-butanone detected in field blanks,

source-solution blanks, laboratory instrument blanks, and groundwater 

samples, California GAMA Priority Basin Project, May 2004 through 

September 2010.............................................................................. 28

Figure 7. Time-series graph for concentrations of tetrahydrofuran detected in field blanks,

source-solution blanks, laboratory instrument blanks, and groundwater 

samples, California GAMA Priority Basin Project, May 2004 through 

September 2010.............................................................................. 29

Figure 8. Time-series graph for concentrations of ethylbenzene detected in field blanks,

source-solution blanks, laboratory blanks, and groundwater samples, California

GAMA Priority Basin Project, May 2004 through September 2010 .................. 33

Figure 9. Time-series graph for concentrations of m- and p-xylenes detected in field

blanks, source-solution blanks, laboratory blanks, and groundwater samples,

California GAMA Priority Basin Project, May 2004 through September 2010 ...... 34

Figure 10. Time-series graph for concentrations of o-xylene detected in field blanks,

source-solution blanks, laboratory blanks, and groundwater samples, California

GAMA Priority Basin Project, May 2004 through September 2010 .................. 35

Figure 11. Time-series graph for concentrations of benzene detected in field blanks,

source-solution blanks, laboratory blanks, and groundwater samples, California

GAMA Priority Basin Project, May 2004 through September 2010 .................. 36

Figure 12. Time-series graph for concentrations of styrene detected in field blanks,

source-solution blanks, laboratory blanks, and groundwater samples, California

GAMA Priority Basin Project, May 2004 through September 2010 .................. 37

Figure 13. Relations between m- and p-xylenes and ethylbenzene, o-xylene, styrene, 

benzene, toluene, and 1,2,4-trimethylbenzene detected in field blanks,

source-solution blanks, and groundwater samples, California GAMA Priority

Basin Project, May 2004 through September 2010 .................................... 39
vi

Figure 14. Graph showing concentrations of study reporting levels (SRLs) established 

from field blanks collected for the California GAMA Priority Basin Project, 

May 2004 through September 2010, and SRLs established from field blanks 

collected at production wells for the National Water-Quality Assessment 

(NAWQA) Program ........................................................................ 46

Figure 15. Time-series graph for concentrations of toluene detected in field blanks, 

source-solution blanks, laboratory blanks, and groundwater samples, 

California GAMA Priority Basin Project, May 2004 through September 2010 ...... 47

Figure 16. Time-series graph for concentrations of 1,2,4-trimethylbenzene detected in 

field blanks, source-solution blanks, laboratory blanks, and groundwater 

samples, California GAMA Priority Basin Project, May 2004 through 

September 2010.............................................................................. 49

Figure 17. Bar charts showing relations between detection frequencies of 

1,2,4-trimethylbenzene in groundwater samples and blanks and whether or not 

samples for analysis of radon-222 were collected at the same site or previous 

site, and which GAMA field vehicle visited the site, California GAMA Priority 

Basin Project, May 2004 through September 2010 .................................... 51

Figure 18. Time-series graph for concentrations of dichloromethane detected in field 

blanks, source-solution blanks, laboratory blanks, and groundwater samples, 

California GAMA Priority Basin Project, May 2004 through September 2010 ...... 55

Figure 19. Time-series graph for concentrations of 1,1-dichloroethene detected in field 

blanks, source-solution blanks, laboratory blanks, and groundwater samples, 

California GAMA Priority Basin Project, May 2004 through September 2010 ...... 56

Figure 20. Time-series graph for concentrations of tetrachloroethene detected in field 

blanks, source-solution blanks, laboratory blanks, and groundwater samples, 

California GAMA Priority Basin Project, May 2004 through September 2010 ...... 57

Figure 21. Time-series graph for concentrations of trichloroethene detected in field 

blanks, source-solution blanks, laboratory blanks, and groundwater samples, 

California GAMA Priority Basin Project, May 2004 through September 2010 ...... 58

Figure 22. Time-series graph for concentrations of bromodichloromethane detected in 

field blanks, source-solution blanks, laboratory blanks, and groundwater 

samples, California GAMA Priority Basin Project, May 2004 through 

September 2010.............................................................................. 59

Figure 23. Time-series graph for concentrations of trichlorofluoromethane detected in 

field blanks, source-solution blanks, laboratory blanks, and groundwater 

samples, California GAMA Priority Basin Project, May 2004 through 

September 2010.............................................................................. 60

Figure 24. Time-series graph for concentrations of carbon disulfide detected in field 

blanks, source-solution blanks, laboratory blanks, and groundwater samples, 

California GAMA Priority Basin Project, May 2004 through September 2010 ...... 62

Figure 25. Time-series graph for concentrations of chloroform detected in field blanks, 

source-solution blanks, laboratory blanks, and groundwater samples, California 

GAMA Priority Basin Project, May 2004 through September 2010 .................. 64

Figure 26. Bar charts showing percentages of groundwater samples in concentration 

range categories for different long-term method detection levels (LT-MDLs) for 

chloroform and tetrachloroethene ...................................................... 66

Figures—Continued
vii

Tables

Table 1. Study unit names, sampling dates, Data Series Reports, and sampling 

schedules, California GAMA Priority Basin Project, May 2004 through 

September 2010.............................................................................. 4

Table 2. Long-term method detection levels (LT-MDLs) used by the U.S. Geological 

Survey National Water Quality Laboratory for volatile organic compounds 

(VOCs), and VOCs detected in groundwater samples and source-solution or 

field blanks, California GAMA Priority Basin Project, May 2004 through 

September 2010.............................................................................. 12

Table 3. Identification of steps in collection, handling, and analysis of blanks and

groundwater samples during which contamination may occur, California 

GAMA Priority Basin Project............................................................... 16

Table 4. Detection frequencies in field, source-solution, and laboratory blanks and in

groundwater samples for the 18 volatile organic compounds (VOCs) and

tentatively identified compounds (TICs) detected in field or source-solution

blanks, California GAMA Program, Priority Basin Project, May 2004 through

September 2010.............................................................................. 21

Table 5. Volatile organic compounds (VOCs) detected in a field blank analyzed in 

triplicate and determined to be affected by residual methanol from equipment 

cleaning, California GAMA Priority Basin Project, May 2004 through 

September 2010.............................................................................. 24

Table 6. Detection frequencies for the 17 VOCs and the TICs detected in field blanks and

results of statistical tests for differences between subsets of the field blanks,

California GAMA Priority Basin Project, May 2005 through September 2010 ...... 30

Table 7. Values of study reporting levels (SRLs) for the 18 VOCs detected in field blanks or

source-solution blanks determined from the set of 167 quality-control field 

blanks using four methods, and changes in detection frequencies in the set 

of 2,026 groundwater samples with application of the different SRLs, California 

GAMA Priority Basin Project, May 2004 through September 2010 .................. 41

Table 8. Study reporting levels (SRLs) and number of data censored by application

 of the SRLs, California GAMA Priority Basin Project, May 2004 through 

September 2010.............................................................................. 42

Table 9. Raw detection frequencies by study unit of volatile organic compounds (VOCs)

before and after application of study reporting units (SRLs), California GAMA

Priority Basin Project, May 2004 through September 2010 ........................... 43

Table 10. Probability of false-positive detections at fractions of the long-term method

detection level (LT-MDL), and numbers of detections with concentrations below

the threshold, California GAMA Priority Basin Project, May 2004 through

September 2010.............................................................................. 67
viii

Conversion Factors and Abbreviations and Acronyms

Conversion Factors

Inch/foot to International System of Units (SI)

Multiply By To obtain

Length

inch (in.) 2.54 centimeter (cm)

foot (ft) 0.3048 meter (m)

International System of Units (SI) to ounce/quart units

Multiply By To obtain

Length

meter (m) 3.281 feet (ft)

Volume

liter (L) 1.05669 quart (qt)

milliliter (mL) 0.033814 ounce (oz)

Mass

gram (g) 0.035274 ounce (oz)

Temperature in degrees Celsius (°C) may be converted to degrees Fahrenheit (°F) as follows:

°F=(1.8×°C)+32

Concentrations of chemical constituents in water are given either in milligrams per liter (mg/L) 

or micrograms per liter (μg/L). One milligram per liter is equivalent to 1 part per million (ppm); 

1 microgram per liter is equivalent to 1 part per billion (ppb).

Abbreviations and Acronyms

CDF cumulative distribution function

CDPH California Department of Public Health

BD binomial distribution

GAMA Groundwater Ambient Monitoring and Assessment Program

LRL laboratory reporting level

LT-MDL long-term method detection level

MDL method detection level

na no data available

NAWQA National Water-Quality Assessment (a USGS program)

NWQL National Water Quality Laboratory (a USGS laboratory)

PBP Priority Basin Project

PVC polyvinyl chloride

QC quality control

QCFB quality-control field blanks

SRL study reporting level

TIC tentatively identified compound

TU tritium unit

USEPA U.S. Environmental Protection Agency

USGS U.S. Geological Survey

VOC volatile organic compound
Evaluation of Volatile Organic Compound (VOC) Blank Data 

and Application of Study Reporting Levels to Groundwater 

Data Collected for the California GAMA Priority Basin 

Project, May 2004 through September 2010

By Miranda S. Fram, Lisa D. Olsen, and Kenneth Belitz

Abstract

Volatile organic compounds (VOCs) were analyzed 

in quality-control samples collected for the California 

Groundwater Ambient Monitoring and Assessment (GAMA) 

Program Priority Basin Project. From May 2004 through 

September 2010, a total of 2,026 groundwater samples, 211 

field blanks, and 109 source-solution blanks were collected 

and analyzed for concentrations of 85 VOCs. Results from 

analyses of these field and source-solution blanks and of 

2,411 laboratory instrument blanks during the same time 

period were used to assess the quality of data for the 2,026 

groundwater samples. Eighteen VOCs were detected in 

field blanks or source-solution blanks: acetone, benzene, 

bromodichloromethane, 2-butanone, carbon disulfide, 

chloroform, 1,1-dichloroethene, dichloromethane, ethylbenzene, 

tetrachloroethene, styrene, tetrahydrofuran, toluene, 

trichloroethene, trichlorofluoromethane, 1,2,4-trimethylbenzene, 

m- and p-xylenes, and o-xylene. 

The objective of the evaluation of the VOC-blank data 

was to determine if study reporting levels (SRLs) were needed 

for any of the VOCs detected in blanks to ensure the quality of 

the data from groundwater samples. An SRL is equivalent to a 

raised reporting level that is used in place of the reporting level 

used by the analyzing laboratory [long-term method detection 

level (LT-MDL) or laboratory reporting level (LRL)] to reduce 

the probability of reporting false-positive detections. Evaluation 

of VOC-blank data was done in three stages: (1) identification 

of a set of representative quality‐control field blanks (QCFBs) 

to be used for calculation of SRLs and identification of VOCs 

amenable to the SRL approach, (2) evaluation of potential 

sources of contamination to blanks and groundwater samples by 

VOCs detected in field blanks, and (3) selection of appropriate 

SRLs from among four potential SRLs for VOCs detected in 

field blanks and application of those SRLs to the groundwater 

data. An important conclusion from this study is that to ensure 

the quality of the data from groundwater samples, it was 

necessary to apply different methods of determining SRLs from 

field blank data to different VOCs, rather than use the same 

method for all VOCs.

Four potential SRL values were defined by using three 

approaches: two values were defined by using a binomial 

probability method based on one-sided, nonparametric 

upper confidence limits, one was defined as equal to the 

maximum concentration detected in the field blanks, and one 

was defined as equal to the maximum laboratory method 

detection level used during the period when samples were 

collected for the project. The differences in detection 

frequencies and concentrations among different types of 

blanks (laboratory instrument blanks, source-solution blanks, 

and field blanks collected with three different sampling 

equipment configurations) and groundwater samples were 

used to infer the sources and mechanisms of contamination 

for each VOC detection in field blanks. Other chemical data 

for the groundwater samples (oxidation-reduction state, 

co-occurrence of VOCs, groundwater age) and ancillary 

information about the well sites (land use, presence of known 

sources of contamination) were used to evaluate whether the 

patterns of detections of VOCs in groundwater samples before 

and after application of potential SRLs were plausible. On this 

basis, the appropriate SRL was selected for each VOC that 

was determined to require an SRL. 

The SRLs for ethylbenzene [0.06 microgram per liter 

(μg/L)], m- and p-xylenes (0.33 μg/L), o-xylene (0.12 μg/L), 

toluene (0.69 μg/L), and 1,2,4-trimethylbenzene (0.56 μg/L) 

corresponded to the highest concentrations detected in the 

QCFBs and were selected because they resulted in the most 

censoring of groundwater data. Comparisons of hydrocarbon 

ratios in groundwater samples and blanks and comparisons 

between detection frequencies of the five hydrocarbons in 

groundwater samples and different types of blanks suggested 

three dominant sources of contamination that affected 

groundwater samples and blanks: (1) ethylbenzene, m- and 

p-xylenes, o-xylene, and toluene from fuel or exhaust 

components sorbed onto sampling lines, (2) toluene from vials 

and the source blank water, and (3) 1,2,4-trimethylbenzene 

from materials used for collection of samples for 

radon-222 analysis. 
2 VOC Blank Data and Study Reporting Levels, California GAMA PBP, 2004–2010

The SRL for carbon disulfide (0.03 μg/L) corresponded 

to the maximum LT-MDL. The most probable source of 

carbon disulfide contamination is the gloves worn by field 

and laboratory personnel. Most carbon disulfide detections 

in groundwater samples occurred in anoxic samples, which 

is consistent with predicted occurrence of carbon disulfide 

formed naturally under sulfate-reducing conditions. 

No SRL was needed for chloroform for groundwater 

samples collected at production wells; the detection frequency 

of chloroform in the QCFBs was less than 3 percent. The 

maximum LT-MDL (0.02 μg/L) was established as the 

SRL for chloroform for groundwater samples collected 

at monitoring wells. No SRLs were established for 

benzene, bromodichloromethane, 1,1-dichloroethene, 

dichloromethane, styrene, tetrachloroethene, trichloroethene, 

or trichlorofluoromethane; the detection frequencies of these 

VOCs in the QCFBs were less than 3 percent.

The SRL approach could not be applied to acetone, 

2-butanone, or tetrahydrofuran because it was not possible 

to define threshold concentrations above which one could 

be reasonably certain that detections in groundwater 

samples were not the result of contamination. The 

highest concentrations of these three VOCs occurred in 

groundwater samples and field blanks collected at sites where 

contamination with the methanol used to clean field equipment 

or the cement used to join polyvinyl chloride (PVC) piping 

was documented.

The 2,026 groundwater samples had a total 

of 2,580 detections of 60 different VOCs. Of those 

2,580 detections, 489 were censored by application of the 

SRLs determined in this report. Of the remaining detections, 

231 had concentrations below the highest LT-MDL used 

during the study period. LT-MDLs changed by less than a 

factor of 2 between May 2004 and September 2010 for most 

VOCs, and the changes did not significantly alter reporting of 

detections with low concentrations. Therefore, censoring at 

the highest LT-MDL for VOCs that do not have SRLs does not 

appear to be necessary to ensure comparability between study 

units sampled at different times during that period.

Introduction 

The California State Water Resources Control Board, in 

collaboration with the U.S. Geological Survey (USGS) and 

the Lawrence Livermore National Laboratory, initiated the 

Groundwater Ambient Monitoring and Assessment (GAMA) 

Program (http://www.swrcb.ca.gov/gama) to assess the 

quality of groundwater in aquifers used for drinking‐water 

supply and to establish a baseline groundwater-quality 

monitoring program. The GAMA Program currently consists 

of four projects: the GAMA Priority Basin Project (PBP), 

conducted by the USGS (http://ca.water.usgs.gov/gama), 

the GAMA Domestic Well Project and GeoTracker GAMA, 

both conducted by the State Water Resources Control 

Board, and GAMA Special Studies, conducted by Lawrence 

Livermore National Laboratory. The USGS, in collaboration 

with the State Water Resources Control Board, developed 

the project design for the PBP (Belitz and others, 2003; 

California State Water Resources Control Board, 2003). For 

the PBP, California’s groundwater basins were prioritized 

primarily on the basis of the number of municipal and 

community drinking‐water supply wells. The 116 priority 

basins, representing 95 percent of the wells in basins, as 

well as selected areas outside of defined groundwater basins, 

were grouped into 35 study units to be sampled between 

2004 and 2012. Groundwater samples were collected from 

2,026 sites in the first 32 study units from May 2004 through 

September 2010 (fig. 1; tables 1, A1). 

Volatile organic compounds (VOCs) were analyzed in 

samples collected from all 2,026 sites. VOC analyses were 

conducted at the USGS National Water Quality Laboratory 

(NWQL). The NWQL uses methods that detect concentrations 

much lower than the detection limits required for analyses 

made for regulatory purposes (California Department of Public 

Health, 2011). Detections of VOCs (and other anthropogenic 

organic compounds) at these low concentrations may be used 

to trace water from the landscape, where it may have been 

affected by anthropogenic contaminants, to aquifer systems. 

Before interpretations of environmental processes 

are made using VOC data from groundwater samples, the 

potential presence of confounding VOC detections that 

are the result of contamination during sample collection, 

handling, or analysis must be evaluated. Contamination 

during sample collection, handling, or analysis (also known 

as “extrinsic” contamination) may be the result of contact 

between groundwater samples and surfaces, liquids, or 

vapors encountered during any of these steps. Detections 

in groundwater samples that are the result of extrinsic 

contamination do not reflect the occurrence of VOCs in the 

aquifer from which the groundwater sample was collected. 

These must be carefully isolated from VOC detections 

in a groundwater sample that are representative of VOC 

contamination of the aquifer (that is, intrinsic contamination). 

All VOC contamination discussed in this report is extrinsic.

In this study, field blanks were collected at 211 of the 

sites at which groundwater samples were collected. VOC data 

from the field blanks, associated source-solution blanks, and 

laboratory instrument blanks analyzed during the same time 

period were used to evaluate extrinsic contamination.
Introduction 3

Bakersfield

San Francisco

OREGON

NEVADA

MEXICO

ARIZONA

Redding

Los Angeles

San Diego

Pacific Ocean

0 200 MILES

0 200 KILOMETERS

40

42 124 122 120 118 116 114

38

36

34

Shaded relief derived from U.S. Geological Survey 

National Elevation Dataset, 2006, 

Albers Equal Area Conic Projection

Sacramento

IP031454_Figure 01. Location in California

N1

N2

N3

N4

N5

N6

N7

M1

M2

M3

M4

M5

M6

V1

V2

V3

V4

V5

V6

V7

V8

V9

D1

D2

D3 D4

D5

S1

S2

S3 S4

S6

S5

N5

N5

Figure 1. The 32 study units sampled for the California GAMA Priority Basin Project, May 2004 through 

September 2010. See table 1 for study unit names.
4 VOC Blank Data and Study Reporting Levels, California GAMA PBP, 2004–2010

Use of Study Reporting Levels

Contamination of a sample during sample collection, 

handling, or analysis may result in addition of constituents 

that are being analyzed—in this case, VOCs. Such addition 

may increase the concentration of a constituent already present 

at detectable levels in the sample, or result in detection of a 

constituent that would not otherwise be reported as detected.

Comparison of concentrations in environmental samples 

to the concentrations in benchmarks established for drinking 

water provides a context for the concentrations detected in 

groundwater samples (for example, Belitz and others, 2010; 

Landon and others, 2010; Toccalino and others, 2010). For the 

GAMA-PBP, the benchmarks used for comparison were those 

from the U.S. Environmental Protection Agency (USEPA) 

and the California Department of Public Health (CDPH), 

and included regulatory (USEPA and CDPH maximum 

contaminant levels) and non-regulatory benchmarks (CDPH 

notification levels, and USEPA lifetime health advisory levels 

and risk-specific doses) (California Department of Public 

Health, 2006, 2008, 2010; U.S. Environmental Protection 

Agency, 2009a,b). For most VOCs, contamination generally 

does not affect use of the data to assess whether concentrations 

in environmental samples are above or below benchmarks; 

however, data for VOCs often are reported as detection 

frequencies at any concentration, and the presence of low 

concentrations of VOCs can be used as a tracer indicating the 

presence of a component of modern groundwater. Therefore, 

Table 1. Study unit names, sampling dates, Data Series Reports, and sampling schedules, 

California GAMA Priority Basin Project, May 2004 through September 2010.

[USGS, U.S. Geological Survey. Map codes (figure 1): D, Desert study units; M, Mountain study units; N, 

North and Central Coast study units; S, South Coast study units; V, Central Valley study units]

Study unit Map

code Sampling dates

Data Series 

Report 

number

San Diego Drainages S5 May–July 2004 129

North San Francisco Bay N3 August–November 2004 167

Northern San Joaquin V4 December 2004–February 2005 196

Southern Sacramento Valley V3 March–June 2005 285

San Gabriel–San Fernando S3 May–July 2005 356

Monterey-Salinas N6 July–September 2005 258

Southeast San Joaquin V7 October–December 2005 351

Kern Basin V8 January–March 2006 337

Central Eastside V5 March–May 2006 325

Central Sierra Nevada M4 May 2006 335

Southern Sierra Nevada M3 June 2006 301

Middle Sacramento Valley V2 June–August 2006 385

Southern California Coastal Plain S2 August–November 2006 387

Owens-Indian Wells M2 September–December 2006 427

Santa Ana–San Jacinto S4 November 2006–February 2007 404

Coachella Valley D3 February–March 2007 373

Santa Clarita-Ventura S1 April–May 2007 408

San Francisco Bay N4 April–June 2007 396

Tahoe-Martis M5 June–September 2007 432

Colorado River D4 October–December 2007 474

Northern Sacramento Valley V1 October 2007–January 2008 452

Antelope Valley D1 January–April 2008 479

Mojave D2 February–April 2008 440

Madera-Chowchilla V6 April–May 2008 455

Santa Maria-Lompoc N7 May–November 2008 504

Sierra Nevada Regional M1 June–October 2008 534

Livermore-Gilroy-Cuyama N5 August–November 2008 463

Central Desert-Borrego D5 December 2008–March 2010 659

Ukiah-Clear Lake N2 June–July 2009 609

Eureka-Crescent City N1 July–October 2009 609

Western San Joaquin Valley V9 March–June 2010 706

Cascades-Modoc Plateau M6 July–October 2010 688
Introduction 5

extrinsic contamination that results in detection of a VOC 

that would otherwise not be reported as detected may have a 

significant effect on interpretation of the environmental data.

 A detection is confirmation of a compound’s presence in 

a sample relative to specified reporting criteria. One typical 

practice is to use the data as reported by the laboratory. The 

USGS NWQL’s reporting conventions for VOCs are discussed 

in the section “Laboratory Methods.” The GAMA Program 

uses study reporting levels (SRLs) to limit the effects of 

potential extrinsic contamination indicated by detections 

in blanks. SRLs are defined at a higher concentration than 

the reporting levels used by the laboratory. By raising the 

reporting level, samples with low concentrations of VOCs that 

may be the result of extrinsic contamination are re-defined 

as having non-detections. This avoids over-estimating 

the prevalence of the VOC in the aquifer system. An SRL 

may also be defined to provide a uniform reporting level if 

laboratory reporting levels have changed over the lifetime 

of the project. Finally, an SRL may be defined to match 

the project’s data-quality objectives for constraints on the 

probabilities of false positives and false negatives.

Detections in environmental samples with concentrations 

less than or equal to the SRL are then considered to have an 

unacceptably high probability of resulting from contamination 

by the processes that affected the field blanks. A remark code 

is added to these results, and the detections reported by the 

laboratory are not counted as detections in the environmental 

data. Environmental samples having concentrations greater 

than the SRL may also have been contaminated, but the 

probability that the amount of contamination would have 

been sufficient to result in a reported detection, when the true 

concentration was a non-detection, is acceptably low.

Philosophy of Quality-Control Evaluation 

of Blanks

There are three philosophical issues to consider when 

designing methods for quality-control evaluation of blanks 

to determine SRLs. The first issue is whether contamination 

is a process that results in contamination of samples with 

up to a certain amount of a constituent (characteristic 

concentration), or a process that affects a certain percentage 

of samples (characteristic frequency), or a process that results 

in addition of an unpredictable amount of a constituent to an 

unpredictable percentage of samples. Methods based on the 

premise that contamination has a characteristic concentration 

generally work by ranking the concentrations in the field 

blanks and selecting a threshold rank whose concentration 

is defined as the SRL. Methods based on the premise that 

contamination has a characteristic frequency assume that the 

detection frequency in the field-blank dataset is the frequency 

with which environmental samples are contaminated by the 

process that affects field blanks. The SRL is then defined by 

the concentration in environmental samples below which the 

detection frequency in the environmental samples is equal 

to the detection frequency at any concentration in the field 

blanks. Such a method implicitly assumes that contamination 

is responsible for the detections with the lowest concentrations 

within the distribution observed in the environmental 

samples. It is also possible that the amount and frequency of 

contamination of environmental samples are not predictable 

from the field-blank data. In this case, the field blanks cannot 

be used to define an SRL, and the quality of the data for 

environmental samples cannot be assessed.

The second philosophical issue is that field blanks, 

source-solution blanks, and groundwater samples may be 

treated either as independent populations (statistical approach) 

or as paired samples (deterministic approach). In deterministic 

approaches, information about the sequence of collection of 

blanks and environmental samples is used in the evaluation; in 

statistical approaches, the blanks and environmental samples 

are treated as independent populations. In a deterministic 

method, paired field blank and environmental samples and 

paired field blank and source-solution blank samples are 

examined. A deterministic method is often believed to be 

appropriate when looking for evidence of carryover between 

sequential samples (field blank/environmental sample pairs) 

or for evidence of prior contamination of source blank water 

(field blank/source-solution blank pairs) (for example, Bender 

and others, 2011). However, there is a universal drawback 

of this approach. If field blanks, source-solution blanks, and 

environmental samples are not assumed to be independent 

populations, then quality-control assessment requires 

collecting a field blank and a source-solution blank with every 

environmental sample. 

In statistical approaches, a field blank collected at a 

particular site is assumed to be statistically representative of 

conditions under which environmental samples are collected 

at all sites. Field blanks are not directly compared to the 

“paired” environmental sample collected at the same site. 

Similarly, a source-solution blank collected at a particular 

site is considered representative of source-solution blanks 

that could be collected at any site. Methods that determine 

the SRL by identifying a threshold rank and defining the 

concentration in the field blank with that rank as the SRL, and 

methods that involve comparison of cumulative frequency 

distributions (CDF), are based on the assumption that blanks 

and environmental samples are independent populations. 

Statistical approaches were used for this study.

The third philosophical issue is that different methods for 

determining SRLs may be used for different constituents, or 

the same method may be used for all constituents. In general, 

analyses of blanks to assess the quality of environmental 

data have been based on a single method being applied to all 

constituents (for example, Martin and others, 1999; Olsen and 

others, 2010; Bender and others, 2011). However, in a large 

group of constituents like the VOCs, there will be multiple 
6 VOC Blank Data and Study Reporting Levels, California GAMA PBP, 2004–2010

mechanisms by which contamination may be introduced 

during sample collection, handling, and analysis. VOCs with 

different sources and physical and chemical properties will be 

affected by different contamination mechanisms, thus, it may 

be necessary to use different methods for determining SRLs 

for different VOCs. This approach requires the ability to make 

accurate inferences both from patterns of detections in blanks 

and environmental samples and about likely mechanisms of 

contamination for different VOCs. 

In addition to the philosophical issues, it is important 

to consider the robustness of the results when selecting 

an approach to determine SRLs from field-blank data. In 

this context, robustness refers to how sensitive a particular 

screening method is to small changes in the field-blank dataset. 

For example, use of a threshold, such as the concentration 

in a field blank with a specified rank, would not be robust 

if picking one rank up or down produced radically different 

results in terms of the percentage of the environmental data 

that were then below the SRL. In this context, ‘rank’ refers 

to ordinal number of a particular field blank in a set of field 

blanks organized in sequence by concentration.

Computed detection frequencies of VOCs in groundwater 

also are sensitive to data reporting conventions. Reporting 

conventions commonly are defined to ensure that the data 

meet criteria of acceptable probability for differentiating 

between true detections and false-positive detections. The 

primary metric used by the USGS NWQL for defining 

detections is the long-term method detection level (LT-MDL); 

however, for the VOCs, the NWQL also reports concentrations 

below the LT-MDL (Connor and others, 1998). Detections 

below the LT-MDL have a greater than 1-percent probability 

of being false-positive detections (Childress and others, 1999). 

Reporting data below the LT-MDL is not in itself a problem; 

however, the probabilities of false-positive detections should 

be evaluated in comparison to project data-quality objectives. 

In addition, LT-MDLs may change over time, potentially 

resulting in a variably censored dataset. To compare detection 

frequencies across the period of study, a dataset may need 

to be re-censored to a common reporting level (for example, 

Zogorski and others, 2006).

Purpose and Scope 

The purpose of evaluating VOC-blank data is to 

characterize potential contamination of environmental 

samples during sample collection, handling, and analysis 

(extrinsic contamination). This characterization is necessary 

to distinguish between VOC detections that may be due 

to extrinsic contamination and VOC detections that are 

representative of VOC concentrations in the aquifer from 

which the sample was collected. SRLs that are higher than 

the reporting levels used by the laboratory may be defined for 

VOCs having evidence for extrinsic contamination. Detections 

with concentrations below the SRLs are considered to have an 

unacceptably high probability of resulting from contamination, 

and therefore should not be considered detections for the 

purpose of interpreting the environmental data. 

The purposes of this report are as follows:

• To present multiple methods for evaluating blanks and 

establishing SRLs, and to describe the processes used 

to select the appropriate SRL for each compound.

• To evaluate which field blanks are representative 

of processes likely to affect environmental 

samples, and if there are differences between field 

blanks collected with different sample-collection 

equipment configurations.

• To present results of a field experiment conducted 

to demonstrate the effect of contamination of 

field blanks with the methanol used to clean 

sample-collection equipment.

• To infer likely sources of VOC contamination 

during sample collection, handling, and analysis on 

the basis of comparison of detection frequencies 

and concentrations in field blanks, sourcesolution blanks, laboratory instrument blanks, and 

environmental samples.

• To put SRLs in context by comparing them to 

LT-MDLs and by comparing the effects of application 

of different SRLs on the environmental dataset.

The work presented here is based on 2,026 groundwater 

samples, 211 field blanks, and 109 source-solution blanks 

collected from May 2004 through September 2010 for 

the first 32 study units of the California GAMA-PBP, and 

2,411 laboratory instrument blanks analyzed during the 

same period. The groundwater samples were collected from 

production wells by using two different sampling equipment 

configurations (long sampling lines and short sampling 

lines) and from monitoring wells with monitoring-well 

sampling equipment.

An evaluation of blanks is presented for each of the 

18 VOCs that were detected in field or source-solution 

blanks (acetone, benzene, bromodichloromethane, 

carbon disulfide, chloroform, 1,1-dichloroethene, 

dichloromethane, ethylbenzene, 2-butanone, styrene, 

tetrachloroethene, tetrahydrofuran, toluene, trichloroethene, 

trichlorofluoromethane, 1,2,4-trimethylbenzene, m- and 

p-xylenes, and o-xylene).

The methods presented for evaluation of blanks and for 

selection of SRLs are widely applicable and can be used by 

USGS and non-USGS scientists who work with large datasets 

of water-quality measurements from blanks and environmental 

samples. This report makes inferences about the sources of 

VOC contamination on the basis of comparisons between 
Methods Used to Collect and Evaluate VOC Data 7

detection frequencies in different types of blanks and our 

understanding of field and laboratory practices. Targeted 

studies to evaluate these inferences were not undertaken as 

part of this project. 

The SRLs established in this report can be used 

for data reporting and interpretive data analysis for all 

USGS-GAMA projects. The SRLs also can be used by other 

USGS groundwater studies, such as National Water-Quality 

Assessment (NAWQA) Program studies, that used sampling 

methods similar to those used by the GAMA-PBP. The 

SRLs established in this report may be particularly useful 

for projects that have smaller quality-control (QC) datasets 

than those used for GAMA projects. These smaller QC 

datasets limit researchers’ ability to make comprehensive QC 

assessments and develop their own SRLs. 

Methods Used to Collect and Evaluate 

VOC Data

Methods used to collect and evaluate VOC data 

for this study include (1) field methods for collecting 

groundwater samples and blanks; (2) laboratory methods 

for analysis of all samples; (3) data analysis methods for 

identifying representative field blanks and calculating 

SRLs; (4) evaluation methods for inferring potential 

sources of contamination and selecting appropriate SRLs; 

and (5) statistical methods for testing the significance of 

differences between subsets of samples.

Field Methods

Because the purpose of this evaluation of VOC 

field‐blank data is to characterize potential contamination 

of environmental samples, the data collection process will 

be described for the groundwater samples as well as for 

the field and source-solution blanks. Groundwater samples 

were collected for VOC analysis from May 2004 through 

September 2010 from 2,026 sites in 32 study units distributed 

throughout California (fig. 1). Field blanks were collected 

at 211 of the sites (10.4 percent). Groundwater sample data, 

along with assessments of the corresponding QC data on 

a study unit basis, are given in USGS Data Series Reports 

for each study unit (table 1). Of the 2,026 sites, 167 were 

monitoring wells, 34 were developed springs, and 1,825 were 

production wells.

Groundwater Samples

Groundwater samples to be used for VOC analysis were 

collected in accordance with the protocols established by 

the USGS National Field Manual (U.S. Geological Survey, 

variously dated). These protocols ensure that a sample that is 

representative of the groundwater in the aquifer is collected 

from each site and that samples are handled in a consistent 

way that minimizes the potential for contamination of the 

samples. Three protocols were used (fig. 2A): 

• monitoring-well pumps for the 167 

monitoring wells; 

• short sampling lines for the 34 developed springs 

and 1,199 of the production wells; and

• long sampling lines for the other 626 

production wells. 

“Short” and “long” refer to the length of the Teflon® tubing 

used to route the water from the well to the sample bottles. For 

sites sampled with short sampling lines, the Teflon® tubing 

attached to the sampling point was approximately 18 inches 

(in.) long, and samples were collected outdoors at the 

sampling point. For sites sampled with long sampling lines, a 

25-foot (ft) or 32-ft length of Teflon® tubing was attached to 

the sampling point and routed inside a mobile laboratory. On 

rare occasions, the two lengths of tubing were connected to 

each other (making 57 ft). 

The GAMA-PBP used a tiered sampling strategy in 

many study units. Samples for a core suite of analytes were 

collected at all wells, and samples for a larger suite of analytes 

were collected at a subset of the wells. Short sampling lines 

generally were used at sites where samples for the core suite 

of analytes were being collected, and long sampling lines 

generally were used at sites where samples for the larger suite 

of analytes were being collected. Both the long and short 

sampling line configurations were used in 24 study units; only 

the long sampling line configuration was used in 6 study units. 

For two study units where vehicular access to many of the 

sites was limited, only the short sampling line configuration 

was used. 

Many of the wells sampled by GAMA were production 

wells that were in continuous use; therefore, no additional 

purging of the wells was required. Sampling lines were 

attached to the well, and water was routed through a 

flow-through chamber with a multi-parameter probe for 

measurement of field parameters (water temperature, specific 

conductance, pH, and dissolved oxygen). Field parameter 

readings were recorded every 5 minutes, and sample collection 

commenced after at least four consecutive readings with the 

same values. For wells that were not in continuous use, wells 

were pumped to purge at least three casing-volumes of water 

from the well before measurement of field parameters began. 
8 VOC Blank Data and Study Reporting Levels, California GAMA PBP, 2004–2010

IP031454_Figure 02ab. sample collection and blanks Number of blanks analyzed per month

0

2

4

6

8

10

12

14 Source-solution blanks

Long and short sampling lines

Monitoring-well pump

Affected by methanol

2004 2005 2006 2007

Year

2008 2009 2010

Field blanks

A

Number of samples collected per month

0

20

40

60

80

Long sampling lines

Short sampling lines

Monitoring-well pump

2004 2005 2006 2007 2008 2009 2010

Sample-collection equipment Groundwater samples

B

Blanks

Figure 2. Number of (A) groundwater samples and (B) field and source-solution blanks collected 

per month by the California GAMA Priority Basin Project, and (C) number of laboratory instrument 

blanks analyzed per month for volatile organic compounds by the USGS National Water Quality 

Laboratory, May 2004 through September 2010.
Methods Used to Collect and Evaluate VOC Data 9

Figure 2.—Continued

IP031454_Figure 02c. lab blanks

C

2004 2005 2006 2007

Year

2008 2009 2010

Laboratory

instrument

blanks

0

20

10

30

40

60

50

70

Number of laboratory blanks analyzed per month

Groundwater samples and field blanks were collected with three types of sampling equipment. 

Short or long sampling lines were used at production wells, where short (18 inches) and long 

(25 feet) refer to the length of Teflon® line used to route the water from the source to the sample 

bottles. Monitoring wells were sampled with monitoring-well pumps and long sampling lines.
10 VOC Blank Data and Study Reporting Levels, California GAMA PBP, 2004–2010

Production wells (and developed springs) were sampled 

by using Teflon® tubing (short or long sampling lines) with 

stainless-steel fittings attached to the sampling point (hose bib) 

on the well discharge pipe as close to the wellhead as possible. 

At some wells, additional fittings made of brass, steel, or 

stainless steel had to be used to construct a sampling point 

with a hose bib. The sampling point was located upstream of 

any wellhead treatment system or water storage tank, except 

for infrequent cases in which this was not possible. For sites 

sampled with short sampling lines, samples were collected 

outdoors at the sampling point. For sites sampled with 

long sampling lines, the tubing was connected to a Teflon®

flow‐control manifold with stainless-steel fittings, and samples 

were collected inside an enclosed chamber inside the mobile 

laboratory. Monitoring wells usually were sampled by using 

a stainless-steel Grundfos submersible pump with a 300-ft 

Teflon® discharge line. The discharge line was connected to 

the flow-control manifold inside the mobile lab with a long 

(25 ft) Teflon® sampling line. 

All fittings and lengths of tubing were cleaned thoroughly 

between collection of each sample. For the monitoring-well 

pump and the long sampling line configurations, a peristaltic 

pump was used to pump the following sequence of cleaning 

solutions through the fittings and lines: tap water, dilute 

solution of non-phosphate laboratory detergent (Liquinox®), 

deionized water, methanol, deionized water, and finally 

certified blank water (Wilde, 2004). For the short sampling 

line configuration, the same cleaning solutions were poured 

through the fittings and lines in the same order. The short 

sampling lines generally were cleaned in the laboratory, and 

clean lines wrapped in plastic wrap and aluminum foil were 

transported to the field site. The long sampling lines and 

monitoring-well pump generally were cleaned at the field site 

immediately following sample collection, although on rare 

occasions, the lines were cleaned immediately prior to sample 

collection at the next field site. Fittings used to attach a hose 

bib to the well discharge pipe (if needed) were cleaned at the 

field site immediately prior to use during the early years of the 

GAMA-PBP, and were cleaned in the laboratory during the 

later years of the project. The full sampling line configuration 

(short, long, or monitoring well) was attached before well 

purging and measurement of field parameters began, thus 

the lines generally were rinsed with a large volume of 

groundwater before sample collection.

Groundwater samples to be analyzed for VOCs were 

collected in pre-baked 40-milliliter (mL) amber glass vials 

with Teflon-septa caps. The VOC vials were the first set of 

sample containers filled during sample collection. The vials 

were bottom-filled and purged with at least three vial volumes 

of sample water before being filled to the top to eliminate 

entrainment of ambient air. Three to five drops of 6 N certified 

hydrochloric acid were added as a preservative, and the vials 

were sealed with no headspace or bubbles. The hydrochloric 

acid was certified by the USGS NWQL and was dispensed 

from a Teflon® dropper bottle. The dropper bottle of acid 

was kept sealed in a plastic container provided by the USGS 

NWQL in a cooler with ice between uses and was replaced 

approximately every 2 months. Three VOC vials were 

collected for each sample. Vials were packed in protective 

foam sleeves, sealed in ziplock bags, and placed in a cooler 

with ice inside the mobile lab until they were shipped to the 

laboratory. Samples were shipped in coolers packed with ice 

by overnight carrier to the USGS NWQL within a day or two 

of collection.

Blanks

Field blanks were collected at 10.4 percent of the sites 

(211 of 2,026 sites) to determine if equipment, procedures, 

or conditions in the field, during transit, or in the laboratory 

introduced contamination to the samples. Field blanks 

and source-solution blanks to be analyzed for VOCs were 

collected using certified blank water purchased from the 

USGS Field Supply Service (One Stop). The certified blank 

water is contracted in large lots, and each lot is tested by the 

NWQL. Lots are for sale for approximately 6 to 12 months. 

Certified blank water is purchased in 4-liter amber glass 

bottles and is used within 1 week of delivery. 

For the long and short line configurations, field blanks 

were collected by pumping the certified blank water through 

the sampling equipment using a portable peristaltic pump. 

In some cases, field blanks for the short line configuration 

were collected by pouring blank water through the sampling 

equipment. For the monitoring-well configuration, field blanks 

were collected by immersing the monitoring-well pump in 

a dedicated Teflon standpipe containing the certified blank 

water. During the early years of the GAMA-PBP, the portable 

peristaltic pump used for collection of field blanks also was 

used for pumping cleaning solutions through lines between 

samples. During the later years of the project, a dedicated 

pump was used for collection of field blanks, and the pump 

commonly was cleaned in the laboratory prior to transport to 

the field site. Of the 211 field blanks, 22 were collected with 

monitoring-well equipment, 112 with short sampling lines, and 

77 with long sampling lines (fig. 2B). 

Source-solution blanks were collected at 109 of the 

211 sites at which field blanks were collected (fig. 2B). 

Source‐solution blanks were collected by pouring blank water 

directly into the sample vials, which were then preserved, 

stored, shipped, and analyzed in the same manner as the 

field blanks. Source-solution blanks are subject to the same 

potential sources of contamination as the field blanks, with 

the exception of contact with field equipment used to collect 

samples. A trip blank was collected for 1 of the 211 sites; this 

blank was treated as a source-solution blank for the purposes 

of this report.
Methods Used to Collect and Evaluate VOC Data 11

Laboratory Methods

Samples were analyzed for VOCs at the USGS NWQL 

in Denver, Colorado, by purge & trap gas chromatography 

with quadrupole mass-spectrometric detection (Connor and 

others, 1998; NWQL Laboratory Schedule 2020). Samples 

are stored in the dark at 4°C and analyzed within 14 days of 

field collection. The quality-assurance program followed by 

the NWQL is described by Maloney (2005) and Pirkey and 

Glodt (1998). Laboratory QC samples, including laboratory 

method blanks, continuing calibration verification checks, 

reagent spikes, certified standard reference materials, and 

external blind proficiency samples, are analyzed regularly. The 

NWQL maintains certification by the National Environmental 

Laboratory Accreditation Program (NELAP) and other 

certifications (http://nwql.usgs.gov/Public/lab_cert.shtml). 

The NWQL analyzes laboratory instrument blanks 

(and other quality-control samples) as part of every batch of 

environmental and field quality-control samples analyzed 

for VOCs. The purpose of the laboratory instrument blanks 

is to evaluate the occurrence of potential carry-over between 

samples during analysis, and to evaluate the presence of 

potential systemic contamination in the analytical equipment. 

From May 2004 through September 2010, 2,411 laboratory 

instrument blanks were analyzed for VOCs (fig. 2C). Results 

for the VOCs detected in laboratory instrument blanks were 

obtained from the NWQL (http://nwqlqc.cr.usgs.gov/).

The USGS NWQL uses two thresholds for reporting 

VOC data: the long-term method detection level (LT-MDL) 

and the laboratory reporting level (LRL). The LT-MDL is 

determined by using a method (Childress and others, 1999) 

modified from a procedure reported by the U.S. Environmental 

Protection Agency for determining the method detection 

limit (USEPA MDL). The USEPA MDL is the minimum 

concentration of a substance that can be measured and 

reported with 99-percent confidence that the concentration is 

greater than zero; at the MDL, there is less than a 1-percent 

chance of a false positive (U.S. Environmental Protection 

Agency, 1997). The USEPA MDL is determined by analyzing 

at least seven low-level spikes over a relatively short period 

(“low-level” means less than 5 times the expected MDL 

concentration). The LT-MDL is designed to capture more of 

the long-term method variability present in routine laboratory 

analyses because it is derived from at least 20 measurements 

of low-level spikes made over an extended period of time (6 to 

12 months) by multiple analysts and multiple instruments 

(Childress and others, 1999). Low-level spikes and blanks 

are monitored throughout each year, and LT-MDLs are 

reevaluated at least annually and are updated accordingly. 

At the LT-MDL, the probability of a false-positive detection 

(Type I error) is statistically less than or equal to 1 percent. 

 

( 1, 1 )

where

is number of replicate low-level spike

determinations (in this case, = 24),

is standard deviation of measured concentrations

of low-level spike determination,

is level of si

n

n

n

LTMDL s

s

t

n

= × − −α

α gnificance (in this case, 1 percent,

and

is Student's t-value for 1 degrees of freedom

and 1 confidence level (in this case, = 2.50).

t n

t

α =

−

− α 

(1)

The LRL is used to control false-negative (Type II) 

error and is usually set at two times the LT-MDL for each 

constituent. The probability of reporting a false negative 

for a sample that contains a concentration of a constituent 

greater than or equal to the LRL is predicted to be less than 

or equal to 1 percent (Childress and others, 1999). The 

probability of reporting a false negative for a sample that 

contains a concentration equal to the LT-MDL is 50 percent. 

Nondetections are reported as <LRL to indicate that the true 

concentration may be as large as the LRL. 

Values below the LRL are reported as “estimated” 

concentrations, designated with an “E” code. E-coded values 

have a high likelihood of being greater than zero (detections), 

but can have a high degree of uncertainty in the precise 

concentration. For “information-rich” methods, such as the 

VOC analytical method, the NWQL may report detections 

with concentrations below the LT-MDL. The VOC method 

is considered “information-rich” because analyte identity 

is confirmed by two independent means: chromatographic 

retention time and mass spectra (Childress and others, 

1999). However, detections with concentrations less than 

the LT-MDL have a greater than 1-percent chance of being 

false-positive detections. 

There are two issues to consider about LT-MDLs 

and LRLs and interpretation of groundwater-quality data: 

(1) changes in reporting levels during the period that the 

samples were analyzed, and (2) definition of acceptable 

probabilities of false positives and false negatives. Samples 

discussed in this report were collected from May 2004 through 

September 2010. During that period, 83 of the 85 VOCs 

analyzed as part of NWQL Schedule 2020 had at least two 

different LT-MDLs. For 34 VOCs, the concentration of the 

maximum LT-MDL was at least twice the concentration of 

the minimum LT-MDL (table 2). Most notably, the maximum 

and minimum LT-MDLs for the two most frequently detected 

VOCs, chloroform and tetrachloroethene, differed by 

factors of 2 and 2.3, respectively. It is possible that detection 

frequencies for these VOCs in study units sampled during 

periods of maximum LT-MDL may not be comparable to those 

in study units sampled during periods of minimum LT-MDL. 
12 VOC Blank Data and Study Reporting Levels, California GAMA PBP, 2004–2010

Table 2. Long-term method detection levels (LT-MDLs) used by the U.S. Geological Survey National Water Quality Laboratory for 

volatile organic compounds (VOCs), and VOCs detected in groundwater samples and source-solution or field blanks, California GAMA 

Priority Basin Project, May 2004 through September 2010.

[The five-digit USGS parameter code is used to uniquely identify a specific constituent or property in USGS databases and reports. Abbreviations: μg/L, 

micrograms per liter; D, detected; –, not detected]

Constituent

USGS 

parameter 

code

CAS number1

LT-MDL values (μg/L) Detected 

Minimum Median Maximum Groundwater Blanks

Hydrocarbons

Benzene 34030 71–43–2 0.008 0.01 0.013 D D

n-Butylbenzene 77342 104–51–8 0.04 0.06 0.07 – –

sec-Butylbenzene 77350 135–98–8 0.01 0.02 0.03 D –

tert-Butylbenzene 77353 98–06–6 0.03 0.03 0.04 D –

Ethylbenzene 34371 100–41–4 0.01 0.015 0.02 D D

2-Ethyltoluene 77220 611–14–3 0.01 0.02 0.03 D –

Isopropylbenzene 77223 98–82–8 0.019 0.02 0.021 D –

4-Isopropyltoluene 77356 99–87–6 0.03 0.04 0.04 D –

Naphthalene 34696 91–20–3 0.09 0.13 0.2 D –

n-Propylbenzene 77224 103–65–1 0.018 0.02 0.021 D –

Styrene 77128 100–42–5 0.015 0.02 0.021 D D

1,2,3,4-Tetramethylbenzene 49999 488–23–3 0.04 0.07 0.07 D –

1,2,3,5-Tetramethylbenzene 50000 527–53–7 0.04 0.06 0.09 D –

1,2,3-Trimethylbenzene 77221 526–73–8 0.03 0.04 0.05 D –

1,2,4-Trimethylbenzene 77222 95–63–6 0.016 0.02 0.028 D D

1,3,5-Trimethylbenzene 77226 108–67–8 0.016 0.02 0.022 D –

Toluene 34010 108–88–3 0.009 0.009 0.03 D D

m- and p-Xylenes 85795 m:108–38–3

p:106-42-3

0.03 0.04 0.04 D D

o-Xylene 77135 95–47–6 0.016 0.019 0.02 D D

Solvents and organic synthesis

Acetone 81552 67–64–1 1.7 3 3 D D

Acrylonitrile 34215 107–13–1 0.2 0.4 0.6 – –

Bromobenzene 81555 108–86–1 0.01 0.011 0.014 – –

2-Butanone (methyl ethyl ketone, MEK) 81595 78–93–3 0.8 0.8 1 D D

Chlorobenzene 34301 108–90–7 0.008 0.01 0.014 D –

Chloroethane 34311 75–00–3 0.03 0.05 0.06 D –

3-Chloropropene 78109 107–05–1 0.04 0.04 0.25 – –

2-Chlorotoluene 77275 95–49–8 0.01 0.02 0.02 – –

4-Chlorotoluene 77277 106–43–4 0.01 0.021 0.03 – –

Dibromomethane 30217 74–95–3 0.02 0.025 0.025 D –

1,2-Dichlorobenzene 34536 95–50–1 0.01 0.02 0.024 D –

1,3-Dichlorobenzene 34566 541–73–1 0.01 0.015 0.02 D –

trans-1,4-Dichloro-2-butene 73547 110–57–6 0.18 0.3 0.35 – –

1,1-Dichloroethane 34496 75–34–3 0.018 0.02 0.03 D –

1,2-Dichloroethane 32103 107–06–2 0.03 0.05 0.07 D –

1,1-Dichloroethene 34501 75–35–4 0.01 0.011 0.012 D D

cis-1,2-Dichloroethene 77093 156–59–2 0.01 0.011 0.012 D –

trans-1,2-Dichloroethene 34546 156–60–5 0.009 0.009 0.016 D –

Dichloromethane 34423 75–09–2 0.019 0.02 0.03 D D

Ethyl methacrylate 73570 97–63–2 0.07 0.07 0.09 – –

Hexachlorobutadiene 39702 87–68–3 0.03 0.05 0.07 – –

Hexachloroethane 34396 67–72–1 0.07 0.07 0.07 – –

2-Hexanone (n-Butyl methyl ketone) 77103 591–78–6 0.2 0.23 0.4 – –

Iodomethane (Methyl iodide) 77424 74–88–4 0.13 0.225 0.4 – –

1,1-Dichloropropene 77168 563–58–6 0.013 0.015 0.02 – –
Methods Used to Collect and Evaluate VOC Data 13

Table 2. Long-term method detection levels (LT-MDLs) used by the U.S. Geological Survey National Water Quality Laboratory for 

volatile organic compounds (VOCs), and VOCs detected in groundwater samples and source-solution or field blanks, California GAMA 

Priority Basin Project, May 2004 through September 2010.—Continued

[The five-digit USGS parameter code is used to uniquely identify a specific constituent or property in USGS databases and reports. Abbreviations: μg/L, 

micrograms per liter; D, detected; –, not detected]

Constituent

USGS 

parameter 

code

CAS number1

LT-MDL values (μg/L) Detected 

Minimum Median Maximum Groundwater Blanks

Solvents and organic synthesis—Continued

Isobutyl methyl ketone 78133 108–10–1 0.1 0.18 0.2 D –

Methyl acrylate 49991 96–33–3 0.2 0.3 0.5 – –

Methyl acrylonitrile 81593 126–98–7 0.1 0.19 0.2 – –

Methyl methacrylate 81597 80–62–6 0.1 0.1 0.18 – –

1,1,1,2-Tetrachloroethane 77562 630–20–6 0.015 0.02 0.02 D –

Tetrachloroethene (perchloroethene, PCE) 34475 127–18–4 0.013 0.02 0.03 D D

1,2,3-Trichlorobenzene 77613 87–61–6 0.03 0.06 0.14 – –

1,2,4-Trichlorobenzene 34551 120–82–1 0.02 0.06 0.06 – –

1,1,1-Trichloroethane 34506 71–55–6 0.01 0.016 0.02 D –

1,1,2-Trichloroethane 34511 79–00–5 0.02 0.023 0.032 D –

1,1,2,2-Tetrachloroethane 34516 79–34–5 0.04 0.05 0.07 – –

Tetrachloromethane 32102 56–23–5 0.026 0.03 0.04 D –

Tetrahydrofuran 81607 109–99–9 0.5 0.7 1.1 D D

Trichloroethene 39180 79–01–6 0.01 0.011 0.019 D D

Vinyl chloride 39175 75–01–4 0.03 0.04 0.04 D –

Trihalomethanes

Bromodichloromethane 32101 75–27–4 0.014 0.017 0.02 D D

Bromoform 32104 75–25–2 0.04 0.05 0.05 D –

Chloroform 32106 67–66–3 0.01 0.012 0.02 D D

Dibromochloromethane 32105 124–48–1 0.05 0.06 0.06 D –

Fumigants

Bromomethane 34413 74–83–9 0.1 0.18 0.2 D –

1,2-Dibromo-3-chloropropane 2 82625 96–12–8 0.17 0.17 0.5 D –

1,2-Dibromoethane2 77651 106–93–4 0.018 0.02 0.025 D –

1,4-Dichlorobenzene 34571 106–46–7 0.01 0.017 0.02 D –

1,2-Dichloropropane 34541 78–87–5 0.01 0.013 0.015 D –

1,3-Dichloropropane 77173 142–28–9 0.03 0.03 0.03 – –

2,2-Dichloropropane 77170 594–20–7 0.02 0.03 0.03 – –

cis-1,3-Dichloropropene 34704 10061–01–5 0.02 0.03 0.05 – –

trans-1,3-Dichloropropene 34699 10061–02–6 0.04 0.05 0.07 – –

1,2,3-Trichloropropane 77443 96–18–4 0.06 0.06 0.09 D –

Gasoline oxygenates

Diethyl ether 81576 60–29–7 0.04 0.04 0.06 D –

Diisopropyl ether 81577 108–20–3 0.03 0.03 0.05 D –

Ethyl tert-butyl ether (ETBE) 50004 637–92–3 0.015 0.02 0.03 – –

Methyl tert-butyl ether (MTBE) 78032 1634–04–4 0.05 0.05 0.08 D –

Methyl tert-pentyl ether 50005 994–05–8 0.02 0.03 0.04 D –

Naturally occurring

Carbon disulfide 77041 75–15–0 0.019 0.02 0.03 D D

Fire retardants

Bromochloromethane 77297 74–97–5 0.03 0.03 0.06 D –

Bromoethane 50002 593–60–2 0.05 0.06 0.06 – –
14 VOC Blank Data and Study Reporting Levels, California GAMA PBP, 2004–2010

Because the GAMA-PBP generally interprets patterns in 

water quality from the perspective of an overall dataset—for 

example, detection frequency is a property of a dataset—rather 

than by considering individual samples, it is not necessary 

to censor data based on avoidance of false negatives (Helsel, 

2005). For any result, there is a 50-percent probability that 

the true concentration will be greater than or equal to the 

measured concentration and a 50-percent probability that 

it will be less than or equal to the measured concentration. 

In the absence of sources of contamination bias, at the 

reporting limit, wherever it is set, the number of samples 

with measured concentration less than the reporting limit 

when the true concentration is greater than the reporting 

limit (false negatives) is expected to be balanced by the 

number of samples with measured concentration greater than 

the reporting limit when the true concentration is less than 

the reporting limit (false positives). Contamination would 

impart a positive bias, further decreasing the probability of 

false negatives. In contrast, it may be necessary to censor 

data based on avoidance of false-positive detections because 

contamination of groundwater samples during sample 

collection, handling, or analysis results in positive bias in 

concentrations and detection frequencies.

The issue of variability in LRLs for VOCs may be 

addressed in different ways. Moran and others (2006) and 

Zogorski and others (2006) censored VOC data collected for 

the NAWQA Program by using a uniform assessment level 

of 0.02 microgram per liter (μg/L). That concentration was 

selected because most VOC detections in environmental 

samples had concentrations greater than 0.02 μg/L, and many 

of the LT-MDLs were less than 0.02 μg/L. The approach of 

Moran and others (2006) and Zogorski and others (2006) has 

the advantages of being simple to implement and leads to a 

straightforward presentation of results. A second approach is 

to censor data for each VOC constituent individually, selecting 

the highest LT-MDL used for that VOC during the study 

period and applying that LT-MDL as the SRL for that VOC if 

no higher SRL is warranted. This approach has the advantages 

of conforming to common statistical practices for dealing with 

multiply censored datasets (Helsel, 2005), and preserving a 

consistent threshold for an acceptable level of false-positive 

detections for all constituents. This second approach is 

evaluated in this report. 

Data Analysis Methods

Groundwater samples were collected during 2004–2010 

from the 32 GAMA-PBP study units by field personnel of the 

USGS California Water Science Center. These field personnel 

were a relatively constant group of people, and considerable 

attention was given to oversight of field activities and use 

of consistent field methods. Thus, systematic differences 

among study units in patterns of contamination due to field 

activities were unlikely. The blanks from the 32 study units 

were evaluated as if they were collected for one large study. 

The Data Series Reports for the 32 individual study units 

(table 1) include evaluation of VOC-blank data for the 

individual study units. VOC data for groundwater samples 

in a study unit may be censored on the basis of detections 

in the field blanks collected in that study unit. Because the 

number of field blanks collected in each study unit was 

relatively small (3 to 12), censoring was generally based on 

the highest concentration measured in the field blanks. As a 

result, censoring concentrations were different for different 

study units, which may affect comparison of VOC detection 

frequencies among study units. The data for all study units 

were re-evaluated using the SRLs established in this report to 

have uniform censoring levels for comparison among study 

units. This re-evaluation was done during preparation of the 

Scientific Investigations Reports that present the interpretation 

of the status and understanding of groundwater quality in 

individual study units or groups of study units.

Evaluation of VOC-blank data was done in three stages: 

(1) identification of a set of representative quality-control 

field blanks (QCFBs) to be used for calculation of SRLs, 

Table 2. Long-term method detection levels (LT-MDLs) used by the U.S. Geological Survey National Water Quality Laboratory for 

volatile organic compounds (VOCs), and VOCs detected in groundwater samples and source-solution or field blanks, California GAMA 

Priority Basin Project, May 2004 through September 2010.—Continued

[The five-digit USGS parameter code is used to uniquely identify a specific constituent or property in USGS databases and reports. Abbreviations: μg/L, 

micrograms per liter; D, detected; –, not detected]

Constituent

USGS 

parameter 

code

CAS number1

LT-MDL values (μg/L) Detected 

Minimum Median Maximum Groundwater Blanks

Refrigerants

Chloromethane 34418 74–87–3 0.05 0.07 0.09 D –

Dichlorodifluoromethane 34668 75–71–8 0.05 0.07 0.09 D –

Trichlorofluoromethane 34488 75–69–4 0.04 0.04 0.08 D D

1,1,2-Trichloro-1,2,2-trifluoroethane 77652 76–13–1 0.017 0.019 0.02 D –

1

 1,2-Dibromo-3-chloropropane (DBCP) and 1,2-dibromoethane (EDB) also were analyzed using NWQL Schedule 1306, Low-Level Fumigants, in some 

study units. The LT-MDLs listed here are for Schedule 2020.
Methods Used to Collect and Evaluate VOC Data 15

(2) evaluation of potential sources of extrinsic contamination 

to blanks and groundwater samples, and (3) selection of 

appropriate SRLs for VOCs detected in field blanks, and 

application of those SRLs to the groundwater data. 

Identification of Representative Field Blanks

Field blanks are collected by using procedures designed 

to mimic those used to collect the groundwater samples, 

and thus are expected to be representative of the potential 

sources of contamination to the groundwater samples. Small 

differences between the collection methods for field blanks 

and groundwater samples, however, may result in exposure 

of field blanks to sources and processes of contamination that 

are different from those of the groundwater samples (table 3). 

Field blanks contaminated by sources and processes not likely 

to affect groundwater samples might not be representative 

of the conditions under which groundwater samples were 

collected; therefore those blanks should not be used in 

determination of SRLs. To identify a set of representative 

QCFBs to be used for calculation of SRLs, several questions 

needed to be answered to determine if field blanks were 

representative of conditions under which groundwater samples 

were collected: 

• Can the source of contamination be isolated to 

the certified blank water itself? Compounds with 

detections reported in the certificates of analysis 

provided by the NWQL may have a source of 

contamination that is not representative of sources 

of contamination to groundwater samples. Many 

previous QC assessments have assumed that detections 

of compounds in source-solution blanks indicate 

contamination by processes not representative 

of groundwater samples. However, this may be 

an incorrect assumption because source-solution 

blanks are processed with several of the same 

steps as groundwater samples: contact with vials, 

transportation from the field site to the laboratory, and 

laboratory analytical processes (table 3). In this study, 

contamination of the certified blank water itself is 

assessed with the certificates of analysis. Field blanks 

with detections of compounds that could be attributed 

to contamination of the certified blank water itself are 

not considered representative of groundwater sample 

collection conditions for those compounds.

• Is the contamination of field blanks the result of a 

mechanism that is unlikely to affect groundwater 

samples? The differences in sample collection 

and handling methods between field blanks and 

environmental samples (for example, the use of the 

peristaltic pump; table 3) may result in field blanks 

being exposed to potential sources of contamination 

that environmental samples do not encounter. In these 

cases, the field blanks may not be representative.

• Can the SRL approach be used to address extrinsic 

contamination for the constituent? There are two 

general patterns of extrinsic contamination. For many 

constituents, contamination results in environmental 

samples and field blanks being contaminated with a 

small amount of the constituent. The mechanism of 

contamination may be equally likely to affect field 

blanks and environmental samples, or it may be more 

likely to affect field blanks (higher detection frequency 

in field blanks). In both cases, the concentrations of the 

constituent imparted to the samples by contamination 

are relatively low and similar in both sample types. 

The SRL approach can effectively be applied in these 

cases because a threshold concentration can be defined; 

above that threshold, the probability that detections 

in environmental samples are due to extrinsic 

contamination is acceptably low. In contrast, for other 

constituents, contamination results in environmental 

samples and field blanks being contaminated with 

either large or small amounts of the constituent. 

Contaminated environmental samples and field blanks 

may have higher concentrations of the constituent than 

present in uncontaminated environmental samples. 

In this case, the SRL approach cannot be effectively 

applied because there is no threshold concentration 

above which concentrations in environmental samples 

can be considered representative of environmental 

conditions; the probability of extrinsic contamination 

in those samples is not acceptably low.

• Are field blanks collected with one sampling equipment 

configuration representative of conditions under which 

groundwater samples are collected with a different 

sampling equipment configuration? Contamination 

of field blanks and groundwater samples may occur 

at many steps in the sequence of sample collection, 

handling, and analysis (table 3). Many of these steps 

are the same for samples collected with different 

sampling equipment configurations: for example, 

all samples come into contact with sample vials, are 

transported from the field site to the laboratory, and 

are analyzed in the laboratory. If contamination is 

related to contact with sample-collection equipment, 

it is possible that samples collected with different 

sample-collection equipment configurations may be 

subject to contamination by the same process, but 

to different degrees. Because contamination with 

different VOCs may occur by different mechanisms, 

field blanks collected with one sampling equipment 

configuration may be representative of conditions 

under which groundwater samples were collected 

with different sampling equipment configurations 

for some VOCs, but not for others. Statistical tests 

were used to determine significances of differences 

between field blanks collected with different 

equipment configurations.
16 VOC Blank Data and Study Reporting Levels, California GAMA PBP, 2004–2010

Definition of Study Reporting Levels (SRLs)

Four potential SRL values were defined for each VOC 

using three approaches for making quantitative estimates of 

contamination using the QCFBs: two potential SRL values 

were defined using a binomial probability method based on 

one-sided, nonparametric upper confidence limits (Hahn and 

Meeker, 1991), one was defined as equal to the maximum 

concentration detected in the field blanks, and one was defined 

as the maximum laboratory method detection level used 

during the period samples were analyzed for the project. These 

four SRL values were compared, and one value was selected 

for each VOC as the SRL for use with GAMA groundwater 

data. The SRL is equivalent to a raised reporting limit that 

can be used in place of the LRL or LT-MDL to reduce the 

probability of reporting false positives. 

Binomial Probability Approach

The first approach for quantitative assessment of blank 

data is based on binomial probabilities and rank‐order 

statistics. A desired probability of reporting results for 

groundwater samples without false-positive detections and 

a confidence level in that probability are defined, then the 

binomial distribution is used to calculate the number of field 

blanks in a set of field blanks that must be uncontaminated 

in order to meet the criteria of the desired probability and 

confidence level (Martin and others, 1999; Olsen and others, 

2010; Bender and others, 2011). If more than the allowed 

number of field blanks in the set show contamination, then 

an SRL can be defined by using the ranked concentrations of 

the field blanks. This approach assumes that contamination 

has a characteristic concentration, which is generally a range 

of concentrations that is lower than those observed in the 

majority of the groundwater samples.

Table 3. Identification of steps in collection, handling, and analysis of blanks and groundwater samples during which contamination 

may occur, California GAMA Priority Basin Project.

[Field blanks and groundwater samples were collected with three equipment configurations: short lines (18-inch Teflon sampling line, collection at well head), 

long lines (25-foot sampling line routed inside mobile lab), monitoring-well equipment (monitoring-well pump plus 25-foot sampling line routed inside mobile 

lab). Abbreviations: all, process applies to all samples of that type; some, process applies to some samples of that type; –, process applies to no samples of that 

type]

Process

Laboratory 

instrument 

blanks

Sourcesolution 

blanks

Field blanks Groundwater samples

Short 

lines

Long 

lines

Monitoring 

well

Short 

lines

Long 

lines

Monitoring 

well

Certified blank water

Laboratory production all all all all all – – –

Bottling – all all all all – – –

Transit from laboratory to field site – all all all all – – –

Vials

Manufacture and packaging all all all all all all all all

Storage and bottle set preparation – all all all all all all all

Transit to field site – all all all all all all all

Field collection

Peristaltic pump – – some all – – – –

Monitoring-well pump and fittings – – – – all – – all

Extra fittings between lines and well – – – – – some some –

Contact with long lines and manifold – – – all all – all all

Contact with short lines – – all – – all – –

Transit of equipment to field site – – all all all all all all

Conditions at field site – all all all all all all all

Conditions in field vehicle – all all all all all all all

Post-collection

Packing and storage – all all all all all all all

Transit from field site to laboratory – all all all all all all all

Laboratory handling and analysis all all all all all all all all
Methods Used to Collect and Evaluate VOC Data 17

The binomial distribution assigns a probability to 

achieving a given number of successes in a given number 

of trials: 

( ) ( ) ( )

where

is the number of trials (the total number of 

field blanks collected),

is the number of successes (the number of

uncontaminated f

!

i

; , 

eld blanks collected),

is the probability

1

! !

k n k

n

k

p

n bkn p p p knk

− = − −

 of success in each trial 

(the probability of collecting any one

groundwater sample or field blank without

contamination), and

is the probability of achieving successes in 

 trials (the probability of

b k

n collecting 

uncontaminated field blanks in a total of 

 field blanks collected).

k

n

(2)

The probability that there will be at least k uncontaminated 

field blanks among the n field blanks collected is the 

cumulative probability:

( ) ( ) ( )

k

k 0

! ; , 1 ! ! . n k n k bkn p p p knk

−

=

= − ∑ ∑ − (3)

Hahn and Meeker (1991) describe a method for 

determining which ranked field blank corresponds most 

closely to the upper confidence limit for a given percentile of 

a set of observations at a given percent of confidence. In the 

terminology used in this report, the “given percentile of a set 

of observations” corresponds to p, and the “upper confidence

limit” corresponds to ∑b . The 90th, 95th, and 99th percentiles 

and 90- and 95-percent confidence limits are commonly 

used in QC assessments. Note that the method used by Hahn 

and Meeker (1991) for calculating the confidence interval 

is one of many methods, and a more appropriate confidence 

interval to use may be the Jeffreys interval (Agresti and Coull, 

1998; Brown and others, 2001; Belitz and others, 2010). 

For a small number of samples, the difference between the 

Jeffreys interval and the interval used by Hahn and Meeker 

is significant. Using the Jeffreys interval to select the ranked 

field blank corresponding to the upper confidence limit may 

result in selection of a lower rank than would the interval used 

by Hahn and Meeker; thus, the Jeffreys interval may yield an 

SRL with a lower concentration. For the number of blanks 

used in this report, the difference is not significant.

Martin and others (1999), Olsen and others (2010), 

and Bender and others (2011) apply Hahn and Meeker’s 

method to determine the rank of the field blank corresponding 

to, for example, the 90th percentile with at least 90-percent 

confidence. There is at least a 90-percent confidence that 

the contamination in at least 90 percent of all samples is 

less than the concentration in the field blank with this rank. 

For ease of discussion, this concentration is referred to as 

the “BD-percentile/confidence” concentration, where BD 

means binomial distribution, the first number is the percentile 

of interest, and the second number is the percentage of 

confidence (Olsen and others, 2010). Because ranks are 

discrete quantities, for a given percentage of confidence, the 

percentile depends on the number of samples. For example, 

for datasets of 10, 100, and 1,000 field blanks, the BD-90/90 

corresponds to the 98.2, 94.1, and 91.5 percentiles of the 

datasets, respectively.

BD-95/90 and BD-90/90 concentrations were calculated 

for the sets of representative field blanks and source-solution 

blanks, and BD-99/90 concentrations were calculated for the 

set of laboratory blanks. For the dataset of 167 field blanks 

used to define SRLs in this study, the BD-90/90 would be the 

156th ranked blank, corresponding to the 92.8 percentile of the 

dataset, and the BD-95/90 would be the 163rd ranked blank, 

corresponding to the 97.0 percentile of the dataset.

Calculations were made using the BINOM.DIST function in 

Microsoft Excel 2007, which takes the form: 

. ( _, ,

_, )

where

is the confidence limit (90 percent);

_ is the number of successes in trials, in

this case, the specified rank minus 1,

where blanks ar

CL BINOM DIST number s trials

probability s cumulative

CL

number s

=

e ranked from highest

to lowest concentration with the highest

 concentration assigned a rank equal to 

the total number of blanks;

is the number of trials, in this case, the

total number of blanks;

trials

p _ is the percentile of interest (0.90, 0.95,

or 0.99); and

is a logical value that determines the form

 of the function, in this case TRUE, such

that BINOM.DIST returns the cumulative

d

robability s

cumulative

istribution function, which is the

probability that there are _ or

fewer successes.

number s

(4)
18 VOC Blank Data and Study Reporting Levels, California GAMA PBP, 2004–2010

Maximum Concentration Approach

The next quantitative approach we consider is defining 

the maximum concentration measured in field blanks as 

the SRL. This type of method commonly is used in studies 

for which the number of blanks collected is too small for 

meaningful statistically-based assessments. For example, 

the number of field blanks collected in each GAMA study 

unit ranged from 3 to 12, which is an insufficient number 

to define a BD-95/90 or even a BD-90/90 concentration for 

an individual study unit. Twenty-two field blanks would be 

needed for the highest concentration blank to correspond to 

the BD-90/90 concentration; a minimum of 45 field blanks 

would be needed to define a BD-95/90 concentration. In 

the absence of other ways of defining an SRL, the highest 

concentration measured in the field blanks was considered 

representative of the amount of extrinsic contamination likely 

to occur in environmental samples. One could make a more 

conservative estimate by defining the SRL at 5 to 10 times the 

highest concentration measured in field blanks (for example, 

Nowell and others, 2011).

The probability that the maximum concentration 

measured in a set of field blanks is the maximum 

concentration in the theoretical population of all field blanks 

may be estimated based on binomial probabilities (Hahn 

and Meeker, 1991; Helsel, 2005). The estimate used in this 

report is the Jeffreys interval (Belitz and others, 2010). If 

10 field blanks are collected, the probability that the maximum 

measured concentration is the true maximum concentration 

is between 72 and 100 percent, at a 90-percent confidence 

level. If 100 field blanks are collected, then the probability 

is between 96.9 and 100 percent, and if 1,000 field blanks 

are collected, then the probability is between 99.7 and 

100 percent. The larger the number of field blanks collected, 

the greater the probability that the highest concentration 

measured in the field blanks is representative of the highest 

concentration in the theoretical population of all field blanks. 

Maximum LT-MDL Approach

The last approach considered is defining the highest 

LT-MDL used during the period samples were analyzed for 

the project (May 2004 through September 2010) as the SRL. 

As discussed in the section “Laboratory Methods,” using 

the highest LT-MDL as a censoring threshold is common 

statistical practice for dealing with multiple censored datasets 

(Helsel, 2005) and may preserve a consistent threshold 

for acceptable level of false-positive detections for all 

constituents. For VOCs detected in field blanks, using the 

highest LT-MDL as the SRL may provide sufficient protection 

against false positives if the positive bias associated with 

extrinsic contamination is small.

Evaluation of Potential Sources of 

Contamination to Blanks and Groundwater 

Samples and Selection of Appropriate SRLs

Potential sources of contamination to blanks and 

groundwater samples primarily were evaluated by comparing 

detection frequencies of individual VOCs in various groups 

of blanks and samples. Contamination may occur at many 

points in the collection, handling, and analysis of blanks 

and groundwater samples (table 3). Laboratory instrument 

blanks, source-solution blanks, field blanks collected with 

different equipment configurations, and groundwater samples 

collected with different equipment configurations are 

exposed to different combinations of these potential points 

of contamination. These points may be divided into four 

categories: the certified blank water, the vials, field collection 

processes, and post-collection handling and analysis (table 3). 

Inferences of contamination mechanisms at each point were 

based on knowledge of physio-chemical properties of VOCs 

and knowledge of field and laboratory practices. 

Laboratory instrument, source-solution, and field blanks 

all use the same certified blank water, but the water used for 

the source-solution and field blanks may have been exposed 

to sources of contamination associated with bottling the water 

or with shipping and storing the bottles between the bottling 

site at the laboratory and the field site. All three types of 

blanks and the groundwater samples are collected in the same 

type of vials. The water for laboratory instrument blanks and 

source-solution blanks is poured directly into the vials. Vials 

for field blanks and groundwater samples are filled by putting 

the sampling line down to the bottom of the vial and allowing 

at least three vial volumes to overflow before withdrawing 

the sampling line. The vials used for source-solution and 

field blanks or groundwater samples also may be subject 

to contamination during storage, packing of bottle sets in 

preparation for sampling, or transit to the field site.

Source-solution blanks, field blanks, and groundwater 

samples all are exposed to the ambient conditions in the field 

vehicle and at the field site, although the degree of potential 

influence by the ambient conditions may vary depending on 

whether the sample is collected inside the vehicle or at the 

well head, and on which sampling vehicle is used. The same 

equipment is used to collect field blanks and groundwater 

samples—with the exception of the peristaltic pump that is 

only used for field blanks and specialized fittings that may 

be used to fabricate a sampling point on the well head—and 

all the equipment travels to the field site. Sample-collection 

equipment is cleaned using the same methods before 

collection of field blanks and groundwater samples, but there 

may be differences between equipment configurations because 

short sampling lines generally are cleaned in the laboratory 

and the long sampling lines and monitoring-well equipment 

generally are cleaned at field sites. Samples collected with 

the three equipment configurations have different amounts 
Methods Used to Collect and Evaluate VOC Data 19

of contact with sampling lines (less contact with short 

sampling lines and more contact with long sampling lines and 

monitoring-well equipment), and the amount of water flushed 

through the lines prior to sample collection generally is greater 

for groundwater samples than for field blanks. Source‐solution 

blanks, field blanks, and groundwater samples are packed, 

stored, and shipped together from the field site to the 

laboratory. All three types of blanks and groundwater samples 

are analyzed with the same equipment in the laboratory.

The points of possible contamination of blanks and 

groundwater samples are inferred by comparing detections in 

different types of samples by using nonparametric statistical 

tests. For example, if the detection frequency of a VOC in 

source-solution blanks is greater than in field blanks, one 

of the sources of contamination to source-solution blanks 

must be something that is less likely to affect field blanks. 

Both use the same certified blank water and experience 

the same post-collection handling and analysis, but field 

blanks have more contact with sample-collection equipment 

than do source‐solution blanks. That leaves the vials as the 

likely explanation for higher detection frequency in the 

source‐solution blanks, which is plausible, given the difference 

in how vials are filled for source-solution blanks and field 

blanks. Note that the inference that source-solution blanks may 

be contaminated by the vials does not imply that field blanks 

do not get contaminated by the vials; both types of blanks may 

be contaminated by this mechanism, but contamination of the 

source-solution blanks is more likely.

Potential points of contamination are evaluated separately 

for the 18 VOCs detected in source-solution blanks and field 

blanks. Comparison of inferred points of contamination for 

different VOCs aids in inference of contamination mechanism, 

which in turn, aids in selection of appropriate SRLs. For 

example, if the detection frequency of a VOC is greater in 

field blanks than in source-solution blanks, and greater in 

field blanks collected with long sampling lines compared 

to short sampling lines, one might infer that the point of 

contamination is contact with sampling lines. If concentrations 

in field blanks and groundwater samples are similar, one might 

further infer that the field blanks and groundwater samples 

both may be contaminated with similar amounts of the VOC 

by contact with sampling lines, and therefore, selection of 

an SRL yielding extensive censoring of the groundwater 

data may be most appropriate. In contrast, if no plausible 

point of contamination can be inferred from the data, and 

concentrations detected in field blanks are low compared to 

concentrations detected in groundwater samples, selection of 

an SRL yielding little or no censoring of the groundwater data 

may be most appropriate.

The binomial probability approach, BD-95/90, was 

considered the default approach for determining SRLs in this 

study. The SRL derived from the BD-95/90 was used unless 

evaluation of the potential sources of extrinsic contamination 

indicated that an SRL resulting in more or less censoring of 

the groundwater data than the BD-95/90 SRL was appropriate. 

The BD-95/90, rather than the BD-90/90, was chosen in 

order to restrict the acceptable probability of false-positive 

detections. Selecting the BD-95/90 as the SRL is equivalent to 

defining an acceptable probability of false-positive detections 

in field blanks of approximately 3 percent, whereas selecting 

the BD-90/90 as the SRL would be equivalent to defining 

an acceptable probability of false-positive detections in field 

blanks of approximately 7 percent. 

Statistical Tests Used in Identification of 

Representative Field Blanks and Evaluation to 

Infer Potential Sources of Contamination

Nonparametric statistical methods were used to test 

the significance of differences in detection frequencies or 

concentrations of a VOC between groups of samples, and 

of correlations between concentrations of different VOCs. 

Nonparametric statistics are robust techniques that generally 

are not affected by outliers and do not require that the data 

follow any particular distribution (Helsel and Hirsch, 2002). 

The significance level (p) used for hypothesis testing for this 

report was compared to a threshold value (α) of 5 percent 

(α=0.05) to evaluate whether the relation was statistically 

significant (p<α). Correlation between concentrations 

of different compounds was evaluated using Spearman’s 

method to calculate the rank-order coefficient (ρ, rho) and the 

significance level of the correlation (p).

Significance of differences between concentrations of a 

single compound between two sample groups was evaluated 

by using the Wilcoxon rank-sum test. The null hypothesis 

for the test is that median values of concentration in the 

two groups are not significantly different from one another. 

Significance of differences between three or more sample 

groups was evaluated in two stages: the Kruskal‐Wallis 

test, followed by Tukey’s multiple comparison test if the 

Kruskal‐Wallis test yielded a result of significance (Helsel 

and Hirsch, 2002). The Kruskal-Wallis test evaluates whether 

any of the groups has a significantly different median 

concentration than the others, but does not indicate which 

group is different. The Tukey’s multiple comparison test is 

performed on the rank-transformed concentration data.

Significance of differences between detection frequencies 

of a single VOC between two sample groups was evaluated 

by using contingency tables. For a contingency table 

analysis, the data are recorded as a matrix of counts. One 

variable is assigned to the columns and the other to the rows, 

and the entries in the cells of the matrix are the number of 

observations, Oij, which fall into the ith row and jth column 

of the matrix. A test statistic is computed by comparing 

the observed counts (Oij) to the counts expected if the two 

variables were independent, and significance is determined 

by comparing the test statistic to the (1–α) quantile of a 

chi-squared distribution. 
20 VOC Blank Data and Study Reporting Levels, California GAMA PBP, 2004–2010

Quality-Control Assessment Results

Of the 85 VOCs analyzed, 18 were detected in field 

blanks or source-solution blanks, and 67 were not detected 

(table 2). The VOCs detected in blanks may be divided into 

three groups:

Hydrocarbons Solvents Other VOCs

Benzene acetone bromodichloromethane

Ethylbenzene 2-butanone carbon disulfide

Styrene 1,1-dichloroethene chloroform

Toluene dichloromethane trichlorofluoromethane

1,2,4-trimethylbenzene tetrachloroethene

m- and p-xylenes tetrahydrofuran

o-xylene trichloroethene

Field blanks collected for the GAMA Program contained 

a similar set of VOC contaminants as field blanks collected 

at groundwater sites by the USGS NAWQA Program, which 

uses similar field collection, sample handling, and laboratory 

methods. Eleven VOCs were detected with frequencies 

greater than 5 percent in NAWQA field blanks collected at 

production wells: the hydrocarbons benzene, ethylbenzene, 

toluene, 1,2,4-trimethylbenzene, styrene, m- and p-xylenes, 

and o-xylene; the solvents acetone and dichloromethane; 

and the other VOCs carbon disulfide and chloroform (fig. 3; 

Bender and others, 2011). VOCs detected at greater than 

5-percent detection frequency in NAWQA field blanks 

collected at monitoring wells included the 11 detected in 

field blanks from production wells, plus tetrahydrofuran, 

2-butanone (methyl ethyl ketone, MEK), 1,4-dichlorobenzene, 

chlorobenzene, 1,2-dichloropropane, tetrachloroethene, 

bromodichloromethane, and chloromethane. Of these 

19 VOCs, 15 were detected in GAMA field blanks, but only 

7 (ethylbenzene, toluene, 1,2,4-trimethylbenzene, m- and 

p-xylenes, o-xylene, acetone, and 2-butanone) had detection 

frequencies greater than 5 percent (table 4; fig. 3). Thiros and 

others (2011) suggested that the high detection frequencies 

of VOCs in field blanks collected for the NAWQA Program 

may have been due to field crews inconsistently following 

protocols, particularly failure to use the recommended volume 

of blank water to rinse sample-collection equipment prior to 

collection of field blanks.

Identification of VOCs for Which the SRL 

Approach Can be Applied and of Representative 

Quality-Control Field Blanks (QCFBs) for Use in 

Calculation of SRLs 

The process of identifying a set of representative QCFBs 

to be used for calculation of SRLs yielded three results: 

(1) the certified blank water itself contributed minimally to 

contamination of field blanks, (2) the SRL approach cannot 

be applied to contamination by acetone, 2-butanone, or 

tetrahydrofuran, and (3) field blanks collected with long and 

short sampling lines can be combined for the purposes of 

generating the set of QCFBs for use in calculation of SRLs. 

Minimal Contamination from the Certified 

Blank Water

Between May 2004 and September 2010, 12 lots of 

certified blank water were available for purchase from the 

NWQL (universal blank water, lot numbers 80301, 80401, and 

80501; organic blank water, lot numbers 80601, 80606, 80702, 

80801, 80803, 80804, 80901, 81002, and 81004). Certificates 

of analysis for these lots of certified blank water are available 

from the USGS NWQL (http://wwwnwql.cr.usgs.gov/qas.

shtml?obw). Eleven of the 12 lots had certificates of analysis 

indicating that no VOCs were detected. Lot 80301 was the 

only lot with two certificates of analysis—one produced at the 

beginning and one produced at the end of the time period it 

was available for purchase (all other lots only had certificates 

produced at the beginning). The second certificate for lot 

80301 (February 2004) reported acetone at a concentration 

of 2.2 μg/L; the LT-MDL in effect during February 2004 

was 3 μg/L.

On the basis of the certificates of analysis, certified blank 

water may have been a potential source of contamination of 

field blanks or source-solution blanks by acetone, but not for 

any of the other VOCs. For the other 17 VOCs detected in 

field blanks or source-solution blanks, processes or conditions 

encountered at the field site, during shipping or storage of 

blank water or vials or samples, or at the laboratory must have 

been responsible for introducing the VOCs into the blanks.

Acetone, 2-Butanone, and Tetrahydrofuran 

Contamination Associated with Methanol

The VOCs associated with the methanol used to clean 

field equipment provide an example of contamination to which 

the SRL approach cannot effectively be applied. Moreover, 

some of the inferred mechanisms by which field blanks 

may be contaminated by methanol are unlikely to affect 

groundwater samples.

Inadvertent Field Test of Contamination by Methanol

The pattern of VOC detections observed in the field blank 

collected on June 25, 2007, led to an unusual opportunity to 

demonstrate the importance of the rigorous procedures for 

cleaning equipment after samples are collected (Fram and 

others, 2009). During sampling, three vials are filled in the 

field for each VOC sample or blank, and the laboratory (the 

NWQL) randomly selects one to be analyzed for VOCs and 

reserves the other two for reruns that may be necessary if there 

are problems with the analysis of the first vial or if the project 
Quality-Control Assessment Results 21

Table 4. Detection frequencies in field, source-solution, and laboratory blanks and in groundwater samples for the 18 volatile organic 

compounds (VOCs) and tentatively identified compounds (TICs) detected in field or source-solution blanks, California GAMA Program, 

Priority Basin Project, May 2004 through September 2010.

[Quality-control field blanks (QCFBs) are a subset of all field blanks and consist of the field blanks collected at production wells and inferred not to be 

contaminated with the methanol used to clean equipment. Abbreviations: n, number]

Detection frequency (percent)

Field blanks Sourcesolution 

blanks 

(n=109)

Laboratory 

blanks 

(n =2,411)

Groundwater samples

All

(n= 211)

Production 

well 

(n= 189)

Monitoring 

well

(n= 22)

QCFB

(n =167)

All

(n=2,026)

Production 

well 

(n= 1,859)

Monitoring 

well

(n= 167)

Hydrocarbons

Benzene 1.4 1.1 4.5 0 0 1.6 1.6 1.2 6.0

Ethylbenzene 10 10 14 6.0 1.8 0.1 0.9 0.6 4.2

Styrene 2.4 2.6 0 0 0 0.2 0.1 0.2 0

Toluene 36 33 59 28 41 4.2 7.7 6.0 26

1,2,4-Trimethylbenzene 7.1 5.8 18 6.0 6.4 0.1 11 11 8.4

m- and p-Xylenes 15 14 27 9.0 6.4 0.04 1.9 1.2 9.6

o-Xylene 9.5 9.0 14 5.4 1.8 0.04 0.7 0.4 4.2

Solvents

Acetone 9.5 7.9 23 1.2 5.5 2.1 0.4 0.3 1.8

2-Butanone 9.5 9.0 14 0 0.9 0.04 0.4 0.3 2.4

1,1-Dichloroethene 0 0 0 0 0.9 0 3.4 3.6 0.6

Dichloromethane 1.9 2.1 0 0.6 0.9 0.7 1.5 1.5 1.2

Tetrachloroethene 1.9 1.6 4.5 1.8 0 0.1 13 13 6.6

Tetrahydrofuran 0.9 0.5 4.5 0 0 0.04 1.2 0.8 5.4

Trichloroethene 1.4 1.1 4.5 0.6 0 0.7 6.2 6.7 1.2

Other VOCs

Bromodichloromethane 0.5 0.5 0 0 0 0 6.3 6.7 2.4

Carbon disulfide 2.8 3.2 0 3.0 3.7 1.6 4.3 3.8 9.6

Chloroform 4.7 2.6 23 1.8 0.9 0.2 27 27 18

Trichlorofluoromethane 0.5 0.5 0 0.6 0.9 0 2.0 2.2 0

TICs 17 11 73 6.0 19 0.7 14 13 31

(GAMA) requests a rerun to verify a result. Under normal 

circumstances, the three vials collected for a sample or a blank 

would yield comparable results. Highly unusual conditions 

occurred when the June 25, 2007, field blank was collected 

and resulted in the three vials having markedly different 

VOC results.

In the field notes for the site at which the unusual field 

blank was collected, the field crew recorded that they thought 

they might not have rinsed the peristaltic pump used to pump 

the blank water from the source bottles through the sampling 

equipment and into the sample vials for the field blank after 

the cleaning steps, which usually involve a methanol wash 

(which was done) and blank-water rinse (which was likely 

omitted). The three VOC vials for the field blank were the 

first sample containers to be filled during sample collection; 

therefore, the VOC results from the first of these vials would 

be the most affected by any contaminants from residual 

methanol in the lines or pump. The collection order was not 

marked on the three vials. 

The NWQL notified GAMA project staff upon noticing a 

high number of VOC detections and an unusual chromatogram 

for this field blank. Information in the field notes led to a 

hypothesis that residual methanol may have been the source, 

and the remaining two vials were analyzed to test this 

hypothesis. Methanol is a polar organic solvent and would be 

expected to readily dissolve other polar organic compounds 

(if present), as well as (to a lesser degree) less polar and 

nonpolar organic compounds. Although the methanol used for 

cleaning is labeled as 99.9 percent pure, this level of purity 

does not preclude the presence of other organic constituents at 

microgram-per-liter concentrations. In addition, methanol may 

be exposed to airborne contaminants while being transferred 

into the containers used to transport and store it safely in 

field vehicles and mobile laboratories, and while being used 

for cleaning. Thus, the methanol likely had opportunities to 

accumulate organic contaminants. 
22 VOC Blank Data and Study Reporting Levels, California GAMA PBP, 2004–2010

IP031454_Figure 03a. compare GAMA production well field blanks, detection frequency, in percent

0

5

10

15

20

25

40

0 5 10 15 20 25 40

1:1 line

toluene

m- and p-xylenes

1,2,4-trimethylbenzene

ethylbenzene

o-xylene

acetone

2-butanone

*VOCs in descending order of detection frequency in 

NAWQA production well field blanks: 1,4-dichlorobenzene, 

1,2-dichloropropane, methyl isobutyl ketone, 

1,2-dichloroethane, trichlorotrifluoromethane, dichlorodifluoromethane, 1,1,1-trichloroethane, methyl tert-butyl 

ether, napthalene, 1,2,3-trimethylbenzene, 2-ethyltoluene.

0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

0 2 4 6 8 10 12

1:1 line

chloroform

dichloromethane

carbon disulfide

benzene

tetrachloroethene

styrene

trichloroethene

tetrahydrofuran

bromodichloromethane

trichlorofluoromethane

* chloromethane

GAMA: 189 field blanks collected with long or short 

sampling lines (includes 22 field blanks having 

evidence for contamination with methanol during 

collection)

NAWQA: 278 field blanks collected at domestic and 

public-supply wells (Bender and others, 2011)

A

NAWQA production well field blanks,

detection frequency, in percent

GAMA production well field blanks, 

detection frequency, in percent

EXPLANATION

Hydrocarbons

Solvents

Other VOCs

NAWQA production well field blanks,

detection frequency, in percent

Figure 3. Detection frequencies in field blanks collected at production wells by the National Water-Quality Assessment 

(NAWQA) Program and detection frequencies in (A) all field blanks collected with long and short sampling lines by the 

GAMA Priority Basin Project, and (B) quality-control field blanks (QCFBs) collected with long and short sampling lines and 

inferred to be without contamination by the methanol used to clean field equipment. 
Quality-Control Assessment Results 23

IP031454_Figure 03b. compare QCFB

*VOCs in descending order of detection frequency 

in NAWQA production well field blanks: 

tetrahydrofuran, 2-butanone,1,4-dichlorobenzene, 

1,2-dichloropropane, methyl isobutyl ketone, 

1,2-dichloroethane, trichlorotrifluoromethane, 

dichlorodifluoromethane, 1,1,1-trichloroethane, 

methyl tert-butyl ether, napthalene, 

1,2,3-trimethylbenzene, 2-ethyltoluene.

GAMA: 167 field blanks collected with long or 

short sampling lines and having no evidence of 

contamination by methanol (QCFBs)

NAWQA: 278 field blanks collected at domestic 

and public-supply wells (Bender and others, 2011)

EXPLANATION

GAMA production well field blanks, 

detection frequency, in percent

0

5

10

15

20

25

40

0 5 10 15 20 25 40

1:1 line

0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

0 2 4 6 8 10 12

1:1 line

B

NAWQA production well field blanks,

detection frequency, in percent

GAMA production well field blanks, 

detection frequency, in percent

Hydrocarbons

Solvents

Other VOCs

NAWQA production well field blanks,

detection frequency, in percent

chloroform

dichloromethane

carbon disulfide

benzene

tetrachloroethene

styrene

acetone

chloromethane

trichloroethene

bromodichloromethane

trichlorofluoromethane

*

toluene

m- and p-xylenes

1,2,4-trimethylbenzene ethylbenzene

o-xylene

Figure 3.—Continued
24 VOC Blank Data and Study Reporting Levels, California GAMA PBP, 2004–2010

Analyses of the three vials yielded different results. 

For the purposes of discussion, the vials were numbered 

based on the size of an unusually broad peak present on 

the chromatograms for all three vials from this field blank 

(fig. 4); this peak generally is not present on chromatograms 

for groundwater or surface-water samples (Donna Rose, 

U.S. Geological Survey National Water Quality Laboratory, 

written commun., 2007). On the basis of comparison between 

retention times for identified VOCs on the chromatogram and 

retention times for a larger suite of VOCs (J&W Scientific, 

1998), this large, broad peak was inferred to correspond to 

methanol. This inferred methanol peak was not identified 

on the basis of the mass spectra because of the masses of 

the primary ions that would be produced from methanol are 

below the range of masses scanned by the mass spectrometer 

(Connor and others, 1998). 

Results for the first, second, and third vials showed a 

progressive decrease in the number and concentration of 

VOCs detected (table 5). Three solvents (2-butanone, acetone, 

and tetrahydrofuran) were detected in the first and second 

vials, and only 2-butanone was detected in the third vial 

(table 5). These three solvents are polar organic compounds 

with high solubility in methanol and relatively high vapor 

pressures. The methanol purchased for cleaning is certified 

99.9 percent pure methanol, with a maximum of 0.001 percent 

carbonyl compounds, which means that the methanol 

could have as much as a total of 10,000 μg/L of carbonyl 

compounds, such as acetone and 2-butanone. In addition, 

2-butanone, acetone, and tetrahydrofuran are components of 

common products, including PVC cement, varnishes, and 

cleaners, that may be encountered in the field. Thus, it is not 

unexpected to find these constituents as contaminants in the 

methanol carried by the mobile laboratories. 

In addition, the NWQL reported an unusually high 

number of tentatively identified compounds (TIC) in the 

chromatogram of the first vial, and fewer TICs in the 

chromatograms for the second and third vials (table 5). TICs 

are constituents not included in the 85 VOCs analyzed on 

NWQL schedule 2020. TICs are tentatively identified on the 

basis on their retention times and their mass spectra. The 

presence of a large number of TICs suggests some VOCs in 

the sample may have come from a source that usually does not 

contribute VOCs to groundwater or surface-water samples. 

NWQL schedule 2020 was designed to include most VOCs 

encountered in groundwater or surface-water samples (Connor 

and others, 1998).

Thiros and others (2011) report similar results for VOC 

contamination in blanks collected after insufficient rinsing of 

field sample-collection equipment. Field and equipment blanks 

contaminated with methanol contained high concentrations of 

acetone, 2-butanone, and tetrahydrofuran (8–800 μg/L), low 

concentrations of hydrocarbons (less than 1 μg/L), and a high 

number of TICs. 

On the basis of these results, residual methanol from 

cleaning of equipment was inferred to be the source of the 

VOC detections in the three vials of the June 25, 2007, field 

blank. The progressive changes in the size of the inferred 

methanol peak, the number of TICs, and the number and 

concentration of VOCs detected from the first to the second 

to the third vial are inferred to reflect the progressive 

decrease in the amount of methanol in the blank water as 

the pump was flushed with more blank water. (Results from 

the third vial were used to represent the field blank and 

are included in table A2.) The association of 2-butanone, 

acetone, tetrahydrofuran, and TICs appears to be indicative of 

contamination of field blanks with residual methanol used for 

cleaning of equipment. 

Rinsing of field equipment during collection of a field 

blank appears sufficient to prevent methanol contamination 

of a groundwater sample collected immediately following 

collection of a field blank contaminated with methanol. The 

volume of blank water passing through the pump during 

collection of the three VOC vials was less than 1 liter; thus, 

the progressive decrease in the amount of methanol in the 

three vials suggests that the methanol was being rinsed out 

of the pump rapidly. Sample bottles filled after collection 

of the VOC vials would be expected to have little or no 

contamination from methanol. The groundwater sample 

collected immediately following the inadvertent methanol 

contamination test described in this report had no detections 

of VOCs (Fram and others, 2009; sample TMART-01). 

The groundwater sample collected immediately following 

collection of the field blank contaminated with methanol 

described by Thiros and others (2011) had no detections of 

VOCs that were detected in the contaminated field blank. 

Table 5. Volatile organic compounds (VOCs) detected in a field 

blank analyzed in triplicate and determined to be affected by 

residual methanol from equipment cleaning, California GAMA 

Priority Basin Project, May 2004 through September 2010.

[The three vials were collected sequentially. TICs, tentatively identified 

compounds; E, estimated because of a higher degree of uncertainty than 

higher concentrations reported for the same compound; μg/L, micrograms per 

liter; –, not detected]

Constituent

Concentration 

(μg/L)

Vial #1 Vial #2 Vial #3

Solvents

Acetone 30.3 E3.4 –

2-Butanone 155 16.4 E4.1

Tetrahydrofuran 4.36 E0.64 –

Hydrocarbons

Toluene 0.12 E0.02 E0.02

Ethylbenzene E0.07 E0.01 –

m- and p-Xylenes E0.20 E0.06 –

o-Xylene E0.08 E0.02 –

Styrene E0.05 – –

1,2,4-Trimethylbenzene E0.02 – –

Other VOCs Number

TICs 13 0 1
Quality-Control Assessment Results 25

Relative retention time (adjusted)

Voltage (relative)

methanol (inferred)

acetone

methyl ethyl ketone

tetrahydrofuran

toluene

ethylbenzene m- and p-xylenes

o-xylene

fluorobenzene

1,2-dichloroethane-d4

toluene-d8

1,2,4-trimethylbenzene

bromofluorobenzene

1,2-dichlorobenzene-d4

1st Vial

2nd Vial

3rd Vial

EXPLANATION

Surrogate compounds

Identified VOCs

Chromatograms were adjusted slightly so that the relative retention times for the surrogate compounds and the 

relative voltage for the toluene-d8 peak were the same for all three vials. Only peaks for surrogate compounds 

and identified volatile organic compounds (VOCs) are shown. Peaks for unidentified VOCs are not shown.

IP031454_Figure 04. chromatographs Figure 4. Three vials of a field blank affected by methanol, California GAMA Priority Basin Project, June 25, 2007.
26 VOC Blank Data and Study Reporting Levels, California GAMA PBP, 2004–2010

Acetone, 2-Butanone, and Tetrahydrofuran Contamination 

in Field Blanks

Occurrences of acetone, 2-butanone, tetrahydrofuran, 

and TICs in the full set of 211 field blanks suggest that 26 

(12 percent) may have been affected by contamination from 

the methanol used to clean equipment. Fifteen (7.1 percent) 

had detections of acetone with concentrations greater than 

2 μg/L (maximum 29 μg/L) (fig. 5), and 20 (9.5 percent) had 

detections of 2-butanone with concentrations ranging from 

0.5 to 124 μg/L (fig. 6). A threshold of greater than 2 μg/L of 

acetone was used to indicate potential contamination from 

methanol because the highest concentrations measured in 

the source blank water, laboratory instrument blanks, and 

source-solution blanks were approximately 2 μg/L. The only 

two detections of tetrahydrofuran in field blanks occurred 

in field blanks that also had detections of 2-butanone and 

acetone (fig. 7; table A2). The 26 field blanks inferred 

to be contaminated with methanol had significantly 

higher numbers of TICs than the 185 field blanks without 

2-butanone or acetone detections (table 6). The number of 

TICs was significantly positively correlated with 2-butanone 

concentration (Spearman’s rho=0.63, p=0.001) and with 

acetone concentration (Spearman’s rho=0.53, p=0.005). 

The frequency of this inferred contamination with 

methanol was significantly greater in field blanks collected 

with monitoring-well equipment or long sampling lines 

compared to field blanks collected with short sampling lines 

(Kruskal-Wallis test, p =0.004). Eighteen percent (4 of 22) of 

the field blanks collected with monitoring-well equipment, 

19 percent (15 of 77) of the field blanks collected with long 

sampling lines, and 6.2 percent (7 of 112) of field blanks 

collected with short sampling lines were inferred to have 

methanol contamination. The differences in frequency of 

contamination with methanol may be explained by differences 

between methods used to collect field blanks with the three 

configurations of sampling lines and by the differences in 

efficiency of rinsing the three configurations.

The USGS National Field Manual for the Collection of 

Water-Quality Data (http://water.usgs.gov/owq/FieldManual/) 

recommends that sampling equipment be rinsed with 8 liters of 

certified blank water after the methanol wash step, and that an 

additional 6 liters of certified blank water be pumped through 

the equipment prior to collecting a field blank. In a test of field 

methods for collection of VOCs, Thiros and others (2011) 

verified that this protocol was sufficient for removing residual 

methanol from sampling equipment: none of the field blanks 

collected for their study contained quantifiable concentrations 

of 2-butanone, acetone, or tetrahydrofuran. Thiros and others 

(2011) concluded that high detection frequencies of VOCs 

in field blanks collected for the NAWQA Program likely 

indicated that field crews did not always use the recommended 

amount of certified blank water to rinse sample-collection 

equipment before collecting field blanks. Field blanks 

collected for the GAMA Program had lower detection 

frequencies of VOCs than those collected by the NAWQA 

Program, suggesting that GAMA field crews followed the 

recommended rinsing protocols more consistently than did 

NAWQA field crews. Nevertheless, it is possible that some 

field blanks were collected after rinsing with less than 14 liters 

of certified blank water. 

The portable peristaltic pump used to pump blank water 

through the equipment in order to collect the field blank is not 

used for collection of groundwater samples. The peristaltic 

pump is also used for pumping the series of cleaning solutions 

through sampling equipment after collection of groundwater 

samples, and does come in contact with methanol. Use 

of a dedicated peristaltic pump for collection of blanks 

may reduce the chance of contamination (although even a 

dedicated pump would be cleaned between uses with the same 

procedure). The second possibility is insufficient rinsing of 

the sample-collection equipment with blank water after the 

methanol wash step and prior to collection of field blanks. 

In contrast, hundreds of liters of groundwater pass through 

the sampling equipment prior to sample collection because 

of the time required to purge a well and wait for the field 

parameter readings to stabilize prior to commencement of 

sample collection. These differences result in a much greater 

likelihood that the field blanks come in contact with the 

methanol used to clean field equipment.

Acetone, 2-Butanone, and Tetrahydrofuran Contamination 

in Groundwater Samples

The detection frequencies of 2-butanone and acetone in 

the 2,026 groundwater samples were 0.4 percent each, which 

are much lower than the detection frequencies in the field 

blanks (table 4). Fifteen of the 2,026 groundwater samples 

had detections of 2-butanone and (or) acetone, and 7 of these 

15 also had detections of tetrahydrofuran. An additional 

17 groundwater samples had a detection of tetrahydrofuran 

without detections of 2-butanone or acetone. Of these 

32 groundwater samples, 28 had no detections of solvents 

other than acetone or 2-butanone or tetrahydrofuran. Of the 

32 groundwater samples, 11 (34 percent) were collected with 

monitoring-well equipment, which is significantly higher 

than the percentage of all groundwater samples collected 

with monitoring-well equipment (8.2 percent) (contingency 

table test, p<0.001). The association between 2-butanone 

and acetone detections and the significantly greater detection 

frequency in samples collected with monitoring-well 

equipment in the groundwater samples and the field blanks 

suggests that contamination with methanol may have affected 

a small number of groundwater samples. The overall detection 

frequency in groundwater samples was less than in field blanks 

because the peristaltic pump was not used for groundwater 

samples and because of the additional amount of rinsing that 

generally occurs during collection of groundwater samples.
Quality-Control Assessment Results 27

IP031454_Figure 05. acetone Acetone concentration, in micrograms per liter

Date of sample collection

Quality-control field blank (QCFB, n=167)

Monitoring-well field blank (n=18)

Field blank contaminated by methanol (n=26)

Source-solution blank (n=109)

Laboratory instrument blank (n=2,411)

Groundwater—long or short lines (n=1,859)

Groundwater—monitoring well (n=167)

EXPLANATION

Sample type (only detections are shown)

Threshold

Long-term method detection level (LT-MDL)

The study reporting level (SRL) approach was not applied to acetone because there

is no threshold concentration above which concentrations in groundwater can be

distinguished from concentrations in field blanks. All detections in groundwater

are rejected, and the samples are considered "not analyzed" for acetone.

0

2

4

6

8

10

12

14

20

40

60

80

100

2004 2005 2006 2007 2008 2009 2010

Figure 5. Concentrations of acetone detected in field blanks, source-solution blanks, laboratory 

instrument blanks, and groundwater samples, California GAMA Priority Basin Project, May 2004 

through September 2010. Non-detections are not shown.
28 VOC Blank Data and Study Reporting Levels, California GAMA PBP, 2004–2010

IP031454_Figure 06. 2-butanone 2-Butanone concentration, in micrograms per liter

Date of sample collection

Quality-control field blank (QCFB, n=167)

Monitoring-well field blank (n=18)

Field blank contaminated by methanol (n=26)

Source-solution blank (n=109)

Laboratory instrument blank (n=2,411)

Groundwater—long or short lines (n=1,859)

Groundwater—monitoring well (n=167)

EXPLANATION

Sample type (only detections are shown)

Threshold

Long-term method detection level (LT-MDL)

0

5

10

15

20

25

30

35

50

100

150

200

2004 2005 2006 2007 2008 2009 2010

The study reporting level (SRL) approach was not applied to 2-butanone because there

is no threshold concentration above which concentrations in groundwater can be

distinguished from concentrations in field blanks. All detections in groundwater

are rejected, and the samples are considered "not analyzed" for 2-butanone.

Figure 6. Concentrations of 2-butanone detected in field blanks, source-solution blanks, laboratory 

instrument blanks, and groundwater samples, California GAMA Priority Basin Project, May 2004 through 

September 2010. Non-detections are not shown.
Quality-Control Assessment Results 29

IP031454_Figure 07. thf Tetrahydrofuran concentration, in micrograms per liter

Date of sample collection

0

5

10

15

50

100

150

200

250

300

350

400

450

500

550

2004 2005 2006 2007 2008 2009 2010

Quality-control field blank (QCFB, n=167)

Monitoring-well field blank (n=18)

Field blank contaminated by methanol (n=26)

Source-solution blank (n=109)

Laboratory instrument blank (n=2,411)

Groundwater—long or short lines (n=1,859)

Groundwater—monitoring well (n=167)

EXPLANATION

Sample type (only detections are shown)

Threshold

Long-term method detection level (LT-MDL)

The study reporting level (SRL) approach was not applied to tetrahydrofuran because there

is no threshold concentration above which concentrations in groundwater can be

distinguished from concentrations in field blanks. All detections in groundwater

are rejected, and the samples are considered "not analyzed" for tetrahydrofuran.

Figure 7. Concentrations of tetrahydrofuran detected in field blanks, source-solution blanks, laboratory 

instrument blanks, and groundwater samples, California GAMA Priority Basin Project, May 2004 through 

September 2010. Non-detections are not shown.
30 VOC Blank Data and Study Reporting Levels, California GAMA PBP, 2004–2010 Table 6. Detection frequencies for the 17 VOCs and the TICs detected in field blanks and results of statistical tests for differences between subsets of the field blanks, California GAMA Priority Basin Project, May 2005 through September 2010. [A result of significant difference on a statistical test is as a p-value less than the threshold value (α) of 0.05. For cases with a result of significance on the Kruskal-Wallis test, Tukey’s multiple comparison test was applied to determine which sample groups were significantly different. Sampling equipment configurations: M, monitoring-well equipment; L, long sampling lines; S, short sampling lines. Other abbreviations: VOCs, volatile organic compounds; TICs, tentatively identified compounds; n, number; <, less than; >, greater than; ns, not significant] Detection frequency (percent) p-value (Wilcoxon test, methanol-affected to unaffected) Three configurations of unaffected field blanks, detection frequency (percent) p-value (Kruskal- Wallis test, three configurations) Configurations with significant differences Methanol- affected field blanks (n= 26) Unaffected field blanks (n= 185) Monitoring-well equipment (M) (n =18) Long sampling lines (L) (n=62) Short sampling lines (S) (n = 105) Hydrocarbons Benzene 12 0 <0.001 0 0 0 ns ns Ethylbenzene 42 5.9 <0.001 5.6 15 1.0 0.002 L > S Styrene 19 0 <0.001 0 0 0 ns ns Toluene 77 30 <0.001 50 31 27 ns ns 1,2,4-Trimethylbenzene 7.7 7.0 ns 17 11 2.9 0.036 M > S, L > S

m- and 

p-Xylene 50 10 <0.001 22 18 3.8 0.002 M > S, L > S

o-Xylene 38 5.4 <0.001 5.6 13 1.0 0.004 L > S

SolventsAcetone 65 1.6 <0.001 5.6 1.6 1.0 ns ns

2-Butanone 77 0 <0.001 0 0 0 ns ns

Dichloromethane 12 0.5 <0.001 0 0 1.0 ns ns

Tetrachloroethene 3.8 1.6 ns 0 3.2 1.0 ns ns

Tetrahydrofuran 7.7 0 <0.001 0 0 0 ns ns

Trichloroethene 7.7 0.5 0.004 0 1.6 0 ns ns

Other VOCsBromodichloromethane 3.8 0 0.007 0 0 0 ns ns

Carbon disulfide 3.8 2.7 ns 0 3.2 2.9 ns ns

Chloroform 15 3.2 0.006 17 3.2 1.0 0.002 M > L, M > S

Trichlorofluoromethane 0 0.5 ns 0 0 1.0 ns ns

TICs 46 12 <0.001 72 8.1 4.8 <0.001 M > L, M > S
Quality-Control Assessment Results 31

In addition, 2-butanone, acetone, and tetrahydrofuran are 

the primary ingredients in the cements used to join polyvinyl 

chloride (PVC) piping, and PVC piping may be used in the 

distribution system connected to the well. The groundwater 

sample with the highest concentrations (80 μg/L of acetone, 

154 μg/L of 2-butanone, and 495 μg/L of tetrahydrofuran) 

was collected from a well where the owner had just connected 

a PVC line to the wellhead to create a sampling port, and a 

strong odor of PVC cement was recorded in the field notes 

for the site (Ferrari and others, 2008). It is highly probable 

that the detections were the result of contamination from 

PVC cement and were not representative of the groundwater 

in the aquifer. The presence of PVC piping with relatively 

fresh connections was noted at a few other sites from which 

the groundwater samples had detections of 2-butanone, 

acetone, and (or) tetrahydrofuran (Fram and others, 2009). 

However, the presence or absence of these conditions is not 

routinely recorded in the field notes, thus, it is not possible 

to assess how many of the detections of these compounds in 

groundwater could be due to contamination from PVC cement 

contacting the groundwater during sample collection. 

The relative concentrations of the three solvents imparted 

by contamination from the two known sources (methanol and 

PVC cement) do not appear to follow a characteristic pattern. 

The groundwater sample with the highest concentrations 

of all three solvents does not lie at the end of a trend in the 

concentration data for other samples and blanks containing 

the solvents. Two other groundwater samples from sites with 

documented presence of new PVC cement contained only 

tetrahydrofuran (Fram and others, 2009; study unit M5). 

The order of the three solvents in the list of ingredients in 

different brands of PVC cement varies, suggesting that the 

relative amounts of the three solvents vary. Field blanks 

containing methanol generally were characterized by the 

presence of 2-butanone and acetone, with lesser amounts of 

tetrahydrofuran (table 5), although the data do not fall on a 

smooth trend. The concentrations of the acetone, 2-butanone, 

and tetrahydrofuran contaminants in the methanol may 

be variable, which makes sense, as different containers of 

methanol may have different histories of exposure to sources 

of contamination.

SRLs for Acetone, 2-Butanone, and Tetrahydrofuran

The contamination patterns of acetone, 2-butanone, and 

tetrahydrofuran are not amenable to the SRL approach. The 

highest concentrations of all three VOCs in groundwater 

samples (greater than 100 μg/L) and in field blanks occurred 

in samples collected at sites having confirmed presence 

of known sources of extrinsic contamination—fresh PVC 

cement at well sites and methanol in field blanks. Seven field 

blanks contained greater than 10 μg/L of one or more of the 

three VOCs. In contrast, the maximum concentration for 

all other VOCs detected in field blanks was 0.69 μg/L. The 

observations that field blanks can contain high concentrations 

of acetone, 2-butanone, and tetrahydrofuran, and that 

contamination from PVC cement at well sites can produce 

high concentrations of these three VOCs in groundwater 

samples, indicate that it is not possible to define a threshold 

concentration above which detections in groundwater have 

an acceptable probability of being representative of aquifer 

conditions rather than due to contamination. Therefore, SRLs 

cannot be defined for these three VOCs.

Because SRLs cannot be defined and no quantitative QC 

assessment can be made, it is not possible to evaluate whether 

detections of 2-butanone, acetone, and tetrahydrofuran in 

groundwater samples represent aquifer conditions or extrinsic 

contamination. For the GAMA Program, groundwater samples 

with reported detections of these three VOCs are defined 

as having no data available for these three VOCs. This is 

achieved by changing the data-quality-indicator code (DQI) 

in NWIS to “Q,” for “reviewed and rejected” and by adding 

the following result-level remark: “Upon careful review, 

these data have been rejected per Fram and others, 2012, 

USGS SIR 2012-5139.” Data for groundwater samples having 

non-detections of 2-butanone, acetone, and tetrahydrofuran 

are not similarly rejected. Extrinsic contamination produces 

a positive bias; therefore, a non-detection indicates both 

the absence of contamination and the absence of detectable 

concentrations of the VOC in groundwater. Note that “not 

analyzed” is not the same as “not detected.” Rejecting all 

reported detections of these three VOCs means that detection 

frequencies for these VOCs in groundwater cannot be defined.

Differences Between Sample-Collection 

Equipment Configurations

Because the frequency of contamination attributable to 

methanol was significantly different in field blanks collected 

with different sampling equipment configurations, it was 

prudent to assess whether there were significant differences for 

other constituents. Of the 185 field blanks without methanol 

contamination, 18 were collected with monitoring-well 

equipment, 62 were collected with long sampling lines, and 

105 were collected with short sampling lines. Significant 

differences between the field blanks collected using the three 

equipment configurations were found for hydrocarbons, 

chloroform, and TICs (table 6).

Field blanks collected with long sampling lines had 

significantly greater concentrations of m- and p-xylenes, 

o-xylene, ethylbenzene, and 1,2,4-trimethylbenzene than 

field blanks collected with short sampling lines, and field 

blanks collected with monitoring-well equipment had 

significantly greater concentrations of m- and p-xylenes and 

1,2,4-trimethylbenzene than field blanks collected with short 

sampling lines (table 6). However, detection frequencies 

of ethylbenzene, m- and p-xylenes, and o-xylene were 

much greater in blanks (of any configuration) than in the 

groundwater samples (table 4); thus these differences between 

sample-collection equipment configurations are not considered 

relevant for the quality-control assessment of the groundwater 

VOC data. 
32 VOC Blank Data and Study Reporting Levels, California GAMA PBP, 2004–2010

Chloroform was the most frequently detected VOC 

in groundwater samples (27 percent; table 4), thus the 

quality-control assessment for chloroform is vitally important 

and could have a noticeable effect on the interpretation of 

the groundwater-quality data. Chloroform concentrations 

were significantly greater in field blanks collected with 

monitoring‐well equipment than in field blanks collected 

with either long or short sampling lines, and there was no 

significant difference between field blanks collected with the 

long and with the short sampling lines (table 6). 

TICs usually are not used in the interpretation of the 

groundwater-quality data; however, they may be an indicator 

of the presence of contamination by VOCs not generally 

present in groundwater. The occurrence of TICs in field blanks 

collected with monitoring-well equipment was significantly 

more frequent than the occurrence in field blanks collected 

with either long or short sampling lines. 

Quality-Control Field Blanks (QCFBs)

Of the 211 field blanks, 167 were included in the set of 

QCFBs that was used to calculate SRLs. The 26 field blanks 

with evidence of contamination by methanol and 18 other 

field blanks collected with monitoring-well equipment were 

excluded from the set of QCFBs.

Field blanks collected with monitoring-well equipment 

had significantly more detections of chloroform, toluene, 

1,2,4-trimethylbenzene, and m- and p-xylenes than field blanks 

collected with long or short sampling lines (table 6). However, 

with only 18 field blanks collected with monitoring-well 

equipment, SRLs can be established with far less confidence 

than for the set of 167 QCFBs: The 18th-ranked monitoringwell field blank corresponds to the BD-95/56. In the absence 

of more quantitative estimates, the SRLs determined from 

the QCFBs were also applied to groundwater samples 

collected with monitoring-well sampling equipment, except 

in the case of chloroform where detections of chloroform in 

monitoring‐well field blanks suggested that an SRL with a 

higher concentration was warranted.

Evaluation of Potential Sources of 

Contamination, Selection of SRLs, and 

Application of SRLs to Groundwater Data for 

VOCs Detected in Blanks

The 15 VOCs that were detected in field or sourcesolution blanks and considered to be amenable to the SRL 

approach were divided into groups on the basis of chemical 

class and inferred mechanism of contamination. For each 

group, the following topics are discussed: (1) inferred 

mechanism(s) of contamination, (2) comparison of SRLs 

determined by the different methods, (3) selection of an 

appropriate SRL (if any) and results of application of that 

SRL to the groundwater data, and (4) comparison to SRLs 

determined from NAWQA VOC field-blank data by Bender 

and others (2011). 

SRLs were implemented in NWIS by changing the 

reported value to “<SRL,” where “SRL” is the value of the 

SRL for that VOC, and by adding the following result-level 

remark: “Upon careful review, these data have been censored 

per Fram and others, 2012, USGS SIR 2012-5139. Bench 

chemist values can be obtained from NWQL.”

Hydrocarbons

Chemically, the seven hydrocarbons detected in blanks 

all are benzene rings with 0 to 3 aliphatic hydrocarbon 

substituents. All are components of gasoline and other 

petroleum-based fuels, materials, and combustion products. 

They are divided into three groups for discussion based on 

similarities in inferred mechanisms of contamination.

Ethylbenzene, m- and p-Xylenes, o-Xylene, Benzene, and 

Styrene

Ethylbenzene, m- and p-xylenes, and o-xylene had 

higher detection frequencies in QCFBs and source-solution 

blanks than in groundwater samples, whereas the detection 

frequencies of benzene and styrene were lower in the QCFBs 

and source-solution blanks than in groundwater samples 

(table 4; figs. 8–12). These five hydrocarbons are present in 

fuels used in and exhaust produced by operation of vehicles 

and generators, and emissions from fuel combustion generally 

are the dominant source of these hydrocarbons in ambient air 

(for example, Daisey and others, 1994; Monod and others, 

2001). Although it is also possible that these compounds could 

enter the blanks and the groundwater samples through entirely 

different avenues, this is unlikely to be the case. Correlations 

among the five hydrocarbons and the ratios of hydrocarbon 

species in blanks and groundwater samples were examined to 

evaluate the hypothesis that fuel vapors or exhaust were the 

source of contamination.
Quality-Control Assessment Results 33

IP031454_Figure 08. ethylb Ethylbenzene concentration, in micrograms per liter

Date of sample collection

0

0.02

0.04

0.06

0.08

0.10

0.12

0.20

0.40

0.60

0.80

1.00

2004 2005 2006 2007 2008 2009 2010

Quality-control field blank (QCFB, n=167)

Monitoring-well field blank (n=18)

Field blank contaminated by methanol (n=26)

Source-solution blank (n=109)

Laboratory instrument blank (n=2,411)

Groundwater—long or short lines (n=1,859)

Groundwater—monitoring well (n=167)

Sample type (only detections are shown)

Thresholds

Long-term method detection level (LT-MDL)

Study reporting level (SRL)

EXPLANATION

Figure 8. Concentrations of ethylbenzene detected in field blanks, source-solution blanks, 

laboratory blanks, and groundwater samples, California GAMA Priority Basin Project, May 2004 

through September 2010. Non-detections are not shown.
34 VOC Blank Data and Study Reporting Levels, California GAMA PBP, 2004–2010

IP031454_Figure 09. m-&p-xylenes

Quality-control field blank (QCFB, n=167)

Monitoring-well field blank (n=18)

Field blank contaminated by methanol (n=26)

Source-solution blank (n=109)

Laboratory instrument blank (n=2,411)

Groundwater—long or short lines (n=1,859)

Groundwater—monitoring well (n=167)

Sample type (only detections are shown)

Thresholds

Long-term method detection level (LT-MDL)

Study reporting level (SRL)

m- and 

p-Xylene concentration, in micrograms per liter

Date of sample collection

0

0.1

0.2

0.3

0.4

0.8

1.2

1.6

2004 2005 2006 2007 2008 2009 2010

EXPLANATION

Figure 9. Concentrations of m- and p-xylenes detected in field blanks, source-solution blanks, 

laboratory blanks, and groundwater samples, California GAMA Priority Basin Project, May 2004 

through September 2010. Non-detections are not shown.
Quality-Control Assessment Results 35

IP031454_Figure 10. o-xylenes

Quality-control field blank (QCFB, n=167)

Monitoring-well field blank (n=18)

Field blank contaminated by methanol (n=26)

Source-solution blank (n=109)

Laboratory instrument blank (n=2,411)

Groundwater—long or short lines (n=1,859)

Groundwater—monitoring well (n=167)

Sample type (only detections are shown)

Thresholds

Long-term method detection level (LT-MDL)

Study reporting level (SRL)

o-Xylene concentration, in micrograms per liter

Date of sample collection

0

0.02

0.04

0.06

0.08

0.10

0.12

0.14

0.16

0.18

0.20

0.40

0.60

2004 2005 2006 2007 2008 2009 2010

EXPLANATION

Figure 10. Concentrations of o-xylene detected in field blanks, source-solution blanks, 

laboratory blanks, and groundwater samples, California GAMA Priority Basin Project, 

May 2004 through September 2010. Non-detections are not shown.
36 VOC Blank Data and Study Reporting Levels, California GAMA PBP, 2004–2010

IP031454_Figure 11. benzene

Quality-control field blank (QCFB, n=167)

Monitoring-well field blank (n=18)

Field blank contaminated by methanol (n=26)

Source-solution blank (n=109)

Laboratory instrument blank (n=2,411)

Groundwater—long or short lines (n=1,859)

Groundwater—monitoring well (n=167)

EXPLANATION

Sample type (only detections are shown)

Threshold

Long-term method detection level (LT-MDL)

Benzene concentration, in micrograms per liter

Date of sample collection

0

1

2

3

4

5

6

7

8

50

100

150

200

2004 2005 2006 2007 2008 2009 2010

A study reporting level (SRL) was not needed for benzene.

Figure 11. Concentrations of benzene detected in field blanks, source-solution blanks, 

laboratory blanks, and groundwater samples, California GAMA Priority Basin Project, 

May 2004 through September 2010. Non-detections are not shown.
Quality-Control Assessment Results 37

IP031454_Figure 12. styrene

Quality-control field blank (QCFB, n=167)

Monitoring-well field blank (n=18)

Field blank contaminated by methanol (n=26)

Source-solution blank (n=109)

Laboratory instrument blank (n=2,411)

Groundwater—long or short lines (n=1,859)

Groundwater—monitoring well (n=167)

EXPLANATION

Sample type (only detections are shown)

Threshold

Long-term method detection level (LT-MDL)

0

0.02

0.04

0.06

0.08

0.10

Styrene concentration, in micrograms per liter

Date of sample collection

2004 2005 2006 2007 2008 2009 2010

A study reporting level (SRL) was not needed for styrene.

Figure 12. Concentrations of styrene detected in field blanks, source-solution blanks, laboratory 

blanks, and groundwater samples, California GAMA Priority Basin Project, May 2004 through 

September 2010. Non-detections are not shown.
38 VOC Blank Data and Study Reporting Levels, California GAMA PBP, 2004–2010

Inferred Mechanisms of Contamination 

Concentrations of ethylbenzene, m- and p-xylenes, 

and o-xylene in the blanks are significantly correlated with 

one another (p<0.001 for Spearman’s rho tests between 

each pair). Concentrations of the three compounds in the 

QCFBs, source-solution blanks, field blanks from monitoring 

wells, and field blanks affected by methanol contamination 

all lie on the same linear correlations that correspond 

to ethylbenzene/m- and p-xylenes and o-xylene/m- and 

p-xylenes ratios of approximately 0.2 and 0.4, respectively 

(fig. 13A,B). These ratios are similar to those found in vehicle 

exhaust and ambient urban air (Daisey and others, 1994; 

Monod and others, 2001). These relations suggest that the 

QCFBs, source‐solution blanks, field blanks from monitoring 

wells, and field blanks affected by methanol contamination 

are all subject to contamination from the same source of 

hydrocarbons, which is likely vehicle exhaust fumes. 

Most groundwater samples containing ethylbenzene, 

o-xylene, and m- and p-xylenes had ratios of hydrocarbons 

similar to those observed in field and source-solution blanks 

(fig. 13A,B), suggesting that the groundwater samples may 

have been contaminated with the same source of hydrocarbons 

as the blanks—vehicle exhaust fumes. VOCs from vehicle 

exhaust fumes also could have been present in the aquifer due 

to recharge of recent precipitation; however, other information 

about the groundwater samples suggests that the ethylbenzene, 

o-xylene, and m- and p-xylenes were unlikely to have been the 

result of aquifer conditions. Of the groundwater samples with 

hydrocarbon ratios similar to those in the blanks or detection 

of low concentration of m- and p-xylenes without detections 

of ethylbenzene or o-xylene, 45 percent had tritium activities 

less than 1 TU, suggesting absence of significant amounts of 

modern recharge. Of those with tritium activities greater than 

1 TU, 60 percent were from sites with less than 20 percent 

urban land use in the area within 500 meters of the well site, 

suggesting absence of significant sources of vehicle exhaust 

fumes. In the dataset as a whole, percentage of urban land 

use around the well site was not correlated with detection of 

ethylbenzene, o-xylene, or m- and p-xylenes in groundwater 

samples (Wilcoxon rank-sum test, p>0.05).

Five groundwater samples had ethylbenzene/m- and 

p-xylenes and (or) o-xylene/m- and p-xylenes ratios greater 

than 1, which suggests a different source of hydrocarbons. 

The two samples with the highest ratios were collected from 

the same site (TLR-07) in 2005 and 2010 in study unit V7 

(southeast San Joaquin Valley; Burton and Belitz, 2008), 

and also contained greater than 75 μg/L of benzene. That 

area of the southeast San Joaquin Valley has extensive oil 

and gas production, thus the source of the hydrocarbons in 

groundwater may be the petroleum deposits. Hydrocarbons 

in natural petroleum deposits or anthropogenic sources of 

petroleum products (such as spills and leaks) will dissolve in 

groundwater. The dissolved hydrocarbons are then subject to 

biodegradation under aquifer conditions, and they biodegrade 

at different rates; thus, hydrocarbon ratios in groundwater may 

differ from those in petroleum.

Concentrations of benzene and styrene in the blanks 

were correlated with concentrations of ethylbenzene, m- and 

p-xylenes, and o-xylene (p<0.001 for styrene and p<0.001 

to 0.003 for benzene, Spearman’s rho test), and the ratios of 

benzene and styrene to m- and p-xylenes in field blanks were 

similar to the ratios in ambient air (fig. 13C,D). The detection 

frequencies of benzene and styrene in blanks, however, were 

much lower than those of the other hydrocarbons (table 4). 

The median detected concentrations of benzene and styrene in 

field blanks were less than or equal to the maximum LT-MDL; 

the median detected concentrations of ethylbenzene, m- and 

p-xylenes, and o-xylene in field blanks were greater than the 

maximum LT-MDL. This suggests that although the ambient 

air with vehicle exhaust may contaminate sampling equipment 

(or the methanol) with all five hydrocarbons, the resulting 

concentrations of benzene and styrene commonly may be 

below detection levels. All six field blanks containing benzene 

and styrene were contaminated with methanol, and five of the 

six blanks (83 percent) also had detections of ethylbenzene, mand p-xylenes, and o-xylene (table A2). 

Among groundwater samples with detections of benzene 

or styrene, the detection frequency of ethylbenzene, mand p-xylenes, or o-xylene (33 percent) was significantly 

lower than in the blanks (contingency table test, p=0.021). 

Furthermore, the ratios between benzene or styrene and m- and 

p-xylenes in groundwater samples were not the same as the 

ratios in blanks (fig. 13C,D). These ratios suggest that the 

detections of styrene and benzene in groundwater likely were 

not caused by contamination.

The relative detection frequencies of ethylbenzene, 

m- and p-xylenes, and o-xylene hydrocarbons in laboratory 

instrument blanks, source-solution blanks, the various 

subsets of field blanks, and groundwater samples (tables 4, 

6) provided data for developing a hypothesis about the 

mechanism of contamination from vehicle exhaust. The 

presence of hydrocarbons in source-solution blanks indicates 

that potential sources of contamination are the source 

blank water, laboratory processes, the vials, or something 

encountered during travel, either before or after sample 

collection. The absence of detections on the certificates of 

analysis for the source blank water suggests that the source 

blank water itself is not the source of contamination, and the 

much lower detection frequencies in laboratory instrument 

blanks suggest that laboratory processes are not the source. 
Quality-Control Assessment Results 39

IP031454_Figure 13. correlations

0

0.4

0.8

1.2

1.6

2.0

4.0

6.0

Toluene, in micrograms per liter

0

0.2

0.4

0.6

0.8

Ethylbenzene, in micrograms per liter

0

0.1

0.2

0.3

0.4

0.5

0.6

o-Xylene, in micrograms per liter

0

0.2

0.4

0.6

0.8

1.0

1.5

2.0

1,2,4-trimethylbenzene, in micrograms per liter

0

0 0.2 0.4 0.6 0.8 1.0 1.2

0.02

0.04

0.06

0.08

0.10

Styrene, in micrograms per liter

m- and p-Xylenes, in micrograms per liter

0 0.2 0.4 0.6 0.8 1.0 1.2

m- and p-Xylenes, in micrograms per liter

0

2

4

6

8

50

100

150

200

Benzene, in micrograms per liter

EXPLANATION

Field blank—short

 lines (n=105)

Field blank—long

 lines (n=62)

Field blank—moni-

 toring well (n=18)

Field blank contam-

 inated by methanol

 (n=26)

Source-solution

 blank (n=109)

Groundwater—long

 or short lines

 (n=1,859)

Ratio of compounds

 in California

 ambient urban air

 (Daisey and

 others, 1994) 

A

B

C

D

E

F

Figure 13. Relations between m- and p-xylenes and (A) ethylbenzene, (B) o-xylene, (C) styrene, 

(D) benzene, (E) toluene, and (F) 1,2,4-trimethylbenzene detected in field blanks, source-solution blanks, 

and groundwater samples, California GAMA Priority Basin Project, May 2004 through September 2010.
40 VOC Blank Data and Study Reporting Levels, California GAMA PBP, 2004–2010

The fact that the detection frequencies in groundwater samples 

are less than in source-solution blanks suggests that processes 

occurring during travel after sample collection are not the 

source. That leaves the vials and processes occurring during 

transit of the source blank water to the field site as potential 

sources of contamination to the source-solution blanks. Both 

the vials and the source blank water may be exposed to fuel 

exhaust or vapors from fuel used in vehicles during transit or 

storage. The bottles of source blank water tend to be tightly 

sealed, and caps on the unused VOC vials generally are 

loosely attached. This difference in capping may point to the 

vials as the problem, but there is no way to be certain with 

this dataset.

The potential sources of contamination to field blanks 

are the same as those for source-solution blanks, with the 

addition of contact with sample-collection equipment. 

Detection frequencies of ethylbenzene, m- and p-xylenes, 

and o-xylene were significantly higher in field blanks than in 

source-solution blanks (table 4), indicating that contact with 

sample-collection equipment was a source of contamination. 

Detection frequencies of the three hydrocarbons were 

significantly higher in QCFBs collected with long sampling 

lines compared to those collected with short sampling lines 

(table 6), indicating that more contact with field equipment 

yields more contamination. Detection frequencies of the three 

hydrocarbons were significantly higher in field blanks affected 

by methanol compared to those not affected by methanol 

(table 6); however, the concentrations of hydrocarbons in 

the inadvertent field test of methanol contamination (table 5) 

were similar to the concentrations in QCFBs (figs. 8–10). This 

suggests that the methanol itself was not the source of the 

hydrocarbons. The purpose of the methanol rinse is to wash 

organic compounds off of the sample-collection equipment; 

many organic compounds, including hydrocarbons, are more 

soluble in methanol than they are in water. 

If the methanol is effective for removing hydrocarbons 

from the field collection equipment, then why did field 

blanks with no evidence for contamination with methanol 

still have relatively high frequencies of contamination with 

hydrocarbons (table 6)? This observation may be explained 

by the timing of the methanol rinse. To reduce the use of 

methanol by field crews, sample-collection equipment was 

cleaned in the laboratory (where fume hoods are available 

to limit exposure) whenever possible. Sets of clean samplecollection equipment may be exposed to fuel exhaust or vapor 

from fuel used in vehicles during travel in the field vehicles. 

According to protocols, sample-collection equipment and 

peristaltic pumps that were last cleaned in the laboratory 

would require rinsing with 6 liters of certified blank water in 

the field before collection of a field blank. It is possible that 

rinsing with 6 liters of blank water may not be sufficient to 

remove hydrocarbons that sorbed onto the clean equipment 

during transit to the field site. The lower detection frequencies 

in the groundwater samples compared to the field blanks 

suggest that the additional amount of rinsing of equipment and 

vials that occurs during collection of groundwater samples was 

more effective for removing the hydrocarbons.

SRLs for Ethylbenzene, m- and p-Xylenes, o-Xylene, Benzene, 

and Styrene

The different methods for calculating SRLs yield 

SRLs for ethylbenzene, m- and p-xylenes, and o-xylene 

that would result in vastly different amounts of censoring 

to the groundwater data (table 7). On the basis of the 

inferred mechanisms of contamination for field blanks and 

groundwater samples, a large portion of the detections in 

groundwater samples may be the result of contamination, 

suggesting that SRLs that result in censoring of a large portion 

of the groundwater data may be more appropriate. However, 

the hydrocarbon ratios suggest that hydrocarbons in a few of 

the groundwater samples are derived from a distinct source; 

thus, some detections of hydrocarbons in groundwater samples 

likely do reflect hydrocarbon occurrence in the aquifer rather 

than contamination, and these data should not be censored.

The SRLs derived from the maximum concentration 

in the QCFBs, 0.06 μg/L, 0.33 μg/L, and 0.12 μg/L, were 

selected for ethylbenzene, m- and p-xylenes, and o-xylene, 

respectively (table 8). These SRLs result in censoring nearly 

all of the groundwater data for ethylbenzene and o-xylene 

and all of the groundwater data for m- and p-xylenes (table 8; 

figs. 8–10). Detections of ethylbenzene, m- and p-xylenes, 

and o-xylene occurred in 11 of the 32 study units (N3, N6, 

S1, S2, S3, V1, V3, V4, V5, V7, and V9; table 9), and of the 

71 total detections, 66 were censored by application of the 

SRLs (table 8).

Four groundwater samples contained concentrations 

of ethylbenzene greater than the SRL. Ethylbenzene/m- and 

p-xylenes and o-xylene/m- and p-xylenes ratios in these 

samples were considerably higher than the ratios calculated 

for field blanks (fig. 13A,B). Three of these four samples had 

additional characteristics suggesting geogenic sources of 

hydrocarbons: benzene and hydrocarbons were the only VOCs 

detected, groundwater samples had tritium < 1 TU, and the 

wells were relatively deep (Landon and Belitz, 2012).

In contrast, if the BD-95/90, BD-90/90, or maximum 

LT-MDL SRLs had been selected, many detections in 

groundwater samples with concentrations and ratios of 

hydrocarbons indistinguishable from those in the field blanks 

would have been retained as detections representative of 

aquifer conditions. Thirty groundwater samples had detections 

of ethylbenzene, m- and p-xylenes, or o-xylene censored 

by application of SRLs equal to the highest concentration 

measured in QCFBs; these detections would not have been 

censored had the BD-90/90 values been selected as the SRLs. 
Quality-Control Assessment Results 41

Table 7. Values of study reporting levels (SRLs) for the 18 VOCs detected in field blanks or source-solution blanks determined from the set of 167 quality-control field blanks using four methods, and changes in detection frequencies in the set of 2,026 groundwater samples with application of the different SRLs, California GAMA Priority Basin Project, May 2004 through September 2010.[LT-MDL, long-term method detection level; BD-95/90, 90-percent upper confidence limit of the 95th percentile; BD-90/90, 90-percent upper confidence limit of the 90th percentile; QCFB, quality-control field blanks; μg/L, micrograms per liter; %, percent; –, not detected; NA, not applicable]

Detection 

frequency 

in 2,026 

groundwater 

samples

(percent)

BD-90/90 BD-95/90 Maximum QCFB Maximum LT-MDL

90th 

percentile 

(μg/L)

SRL

BD-90/90 

(μg/L)

Detection 

frequency 

after 

application 

of SRL

(percent)

95th 

percentile 

(μg/L)

SRL

BD-95/90 

(μg/L)

Detection 

frequency 

after 

application 

of SRL

(percent)

SRL

maximum 

QCFB (μg/L)

Detection 

frequency 

after 

application 

of SRL

(percent)

SRL

maximum 

LT-MDL 

(μg/L)

Detection 

frequency 

after 

application 

of SRL

(percent)

HydrocarbonsBenzene 1.6 – – no change – – no change – no change 0.013 1.4

Ethylbenzene 0.9 – – no change 0.022 0.022 0.7 0.060 0.2 0.02 0.7

Styrene 0.1 – – no change – – no change – no change 0.021 no change

Toluene 7.7 0.036 0.048 1.6 0.060 0.104 0.8 0.686 0.2 0.03 2.6

1,2,4-Trimethylbenzene 11 – – no change 0.035 0.069 3.9 0.556 0.2 0.028 8.4

m- and p-Xylenes 1.9 – 0.033 1.5 0.083 0.118 0.3 0.328 0 0.04 1.1

o-Xylene 0.7 – – no change 0.020 0.040 0.4 0.120 0.05 0.02 0.6

SolventsAcetone1 0.4 – – NA1 – – NA1 2 1.938 NA1 3 0.2

2-Butanone1 0.4 – – NA1 – – NA1 – NA1 1 0.41,1-Dichloroethene 3.4 – – no change – – no change – no change 0.012 no change

Dichloromethane 1.5 – – no change – – no change 0.028 1.1 0.03 1.0

Tetrachloroethene 13 – – no change – – no change 0.148 5.1 0.03 9.6

Tetrahydrofuran1 1.2 – – NA1 – – NA1 – NA1 1.1 1.0

Trichloroethene 6.2 – – no change – – no change 0.093 3.8 0.019 6.0

Other VOCsBromodichloromethane 6.3 – – no change – – no change – no change 0.02 6.2

Carbon disulfide 4.3 – – no change – 0.056 1.7 3 0.092 1.2 0.03 3.3

Chloroform 27 – – no change – – no change 0.127 9.3 0.02 23

Trichlorofluoromethane 2.0 – – no change – – no change 0.100 1.2 0.08 1.4

1 The SRL approach cannot be applied to acetone, 2-butanone, and tetrahydrofuran. Detections in groundwater samples reported by the laboratory were reviewed and rejected.2 Maximum concentrations of acetone in the source-solution blanks and laboratory blanks were 2.842 μg/L and 1.957 μg/L, respectively.3 Maximum concentrations of carbon disulfide in the source-solution blanks and laboratory blanks were 0.089 μg/L and 0.490 μg/L, respectively.
42 VOC Blank Data and Study Reporting Levels, California GAMA PBP, 2004–2010

Table 8. Study reporting levels (SRLs) and number of data censored by application of the SRLs, California GAMA Priority Basin Project, 

May 2004 through September 2010.

[SRL method: BD-95/90, field blank having rank corresponding to the upper 90-percent confidence interval of the 95th percentile determined using the binomial 

distribution; max QCFB, maximum concentration in the set of quality-control field blanks; max LT-MDL, maximum long-term method detection level used 

during period samples were analyzed. Other abbreviations: NA, not applicable; n, number; μg/L, micrograms per liter]

Constituent SRL SRL method

Detection frequency

(percent)

Long and short sampling 

lines (n =1,859)

Monitoring-well 

equipment (n= 167)

Original SRL applied Original SRL applied

Hydrocarbons

Benzene No SRL BD-95/90 1.2 1.2 6.0 6.0

Ethylbenzene SRL = 0.06 μg/L max QCFB 0.6 0.2 4.2 0

Styrene No SRL BD-95/90 0.2 0.2 0 0

Toluene SRL = 0.69 ug/L max QCFB 6.0 0.2 26 0.6

1,2,4-Trimethylbenzene SRL = 0.56 μg/L max QCFB 11 0.2 8.4 0.6

m- and p-Xylenes SRL = 0.33 μg/L max QCFB 1.2 0 9.6 0

o-Xylene SRL = 0.12 μg/L max QCFB 0.4 0.1 4.2 0

Solvents

Acetone Report all detections as “not analyzed” NA1 0.3 0 1.8 0

2-Butanone Report all detections as “not analyzed” NA1 0.3 0 2.4 0

1,1-Dichloroethene No SRL BD-95/90 3.6 3.6 0.6 0.6

Dichloromethane No SRL BD-95/90 1.5 1.5 1.2 1.2

Tetrachloroethene No SRL BD-95/90 13 13 6.6 6.6

Tetrahydrofuran Report all detections as “not analyzed” NA1 0.8 0 5.4 0

Trichloroethene No SRL BD-95/90 6.7 6.7 1.2 1.2

Other VOCs

Bromodichloromethane No SRL BD-95/90 6.7 6.7 2.4 2.4

Carbon disulfide SRL = 0.03 LT-MDL 3.8 3.0 9.6 6.6

Chloroform No SRL for long or short lines;

SRL = 0.02 μg/L for monitoring wells

BD-95/90

LT-MDL

27 27 18 14.4

Trichlorofluoromethane No SRL BD-95/90 2.2 2.2 0 0

1

The SRL approach was not applied to acetone, 2-butanone, or tetrahydrofuran because there is no threshold concentration above which concentrations in 

groundwater samples can be considered representative of environmental conditions (see text for discussion). 

Of these 30 samples, 8 (27 percent) had detections of benzene 

and at least two of the other four characteristics suggestive of 

geogenic sources of hydrocarbons (elevated ethylbenzene/

m-and p-xylenes or o-xylene/m- and p-xylenes ratios, no 

VOCs other than hydrocarbons and carbon disulfide detected, 

tritium <1 TU, and deep wells). However, concentrations 

of ethylbenzene, m- and p-xylenes, and o-xylene in these 

8 samples were indistinguishable from concentrations in the 

other 22 samples that showed no relations between detections 

of ethylbenzene, m- and p-xylenes, and o-xylene and presence 

or absence of detections of other VOCs, groundwater age, well 

depth, or land use.

SRLs defined on the basis of the maximum concentration 

in the QCFBs may not be robust because collection of 

additional field blanks may result in an increase in the 

maximum concentration. Because of the relatively large 

number of QCFBs, however, the probability that additional 

field blanks collected under the same conditions would yield a 

higher concentration is relatively small. For 167 field blanks, 

the probability that the maximum measured concentration is 

the true maximum concentration is 98.6 to 100 percent, at a 

90-percent confidence level.
Quality-Control Assessment Results 43

Table 9. Raw detection frequencies by study unit of volatile organic compounds (VOCs) before and after application of study reporting limits (SRLs), California GAMA Priority Basin Project, May 2004 through September 2010.[Detection frequencies are not area-weighted; they are raw detection frequencies indicating the percentage of detections among the total number of groundwater samples. Thus, original detection frequencies may not be the same as those reported for grid well networks in the Data Series Reports for individual study units. Study unit names given in table 1. Detection frequencies of zero are indicated by the – symbol]

Study 

unit

Number 

of 

samples

Ethylbenzene

1,2,4-

Trimethylbenzene Toluene m- and p- Xylenes o-Xylene Acetone 2-Butanone Tetrahy- drofuran Carbon disulfide Chloroform

Initial Final Initial Final Initial Final Initial Final Initial Final Initial Final Initial Final Initial Final Initial Final Initial Final

Desert study unitsD1 57 – – 3.5 – 40 – – – – – – – – – – – – – 37 37

D2 59 – – 12 – 5.1 1.7 – – – – – – – – 3.4 – – – 29 29

D3 35 – – – – 29 – – – – – – – – – – – – – 23 23D4 28 – – 14 – – – – – – – – – – – – – – – 14 14

D5 52 – – 23 5.8 5.8 – – – – – 1.9 – – – – – – – 27 27

Mountain study unitsM1 83 – – 4.8 – 3.6 – – – – – – – – – 1.2 – 1.2 – 22 22M2 75 – – 6.7 – 8.0 – – – – – – – – – 2.7 – 5.3 2.7 12 12

M3 50 – – – – 4.0 – – – – – – – – – – – – – 14 14

M4 30 – – – – 6.7 – – – – – 3.3 – 3.3 – 3.3 – 3.3 3.3 17 17

M5 53 – – 40 – 3.8 – – – – – – – – – 3.8 – 1.9 1.9 30 30

M6 1 72 – – 61 – 1.4 – – – – – 1.4 – – – – – 4.2 4.2 13 13

North and Central Coast study unitsN1 30 – – 30 – 3.3 – – – – – – – – – – – 3.3 3.3 27 27

N2 28 – – 36 – – – – – – – – – – – – – 7.1 7.1 25 25

N3 108 0.9 – 17 – 5.6 – 3.7 – 1.9 – 0.9 – 1.9 – 1.9 – 7.4 6.5 17 17

N4 79 – – – – 7.6 – – – – – 2.5 – 1.3 – 3.8 – 5.1 3.8 27 27

N5 54 – – – – 1.9 – – – – – – – 1.9 – 1.9 – 1.9 – 19 19N6 97 1.0 1.0 7.2 – 4.1 – 1.0 – – – – – 1.0 – 2.1 – 6.2 5.2 22 22

N7 70 – – 26 – 5.7 – – – – – – – – – 1.4 – – – 16 16

South Coast study unitsS1 53 – – – – 13 1.9 1.9 – – – – – – – 1.9 – 3.8 3.8 17 15

S2 69 1.4 – 2.9 – 5.8 1.4 1.4 – – – – – – – 1.4 – 7.2 5.8 45 45

S3 52 – – 1.9 – 5.8 – 1.9 – – – – – – – – – 17 15 79 79

S4 99 – – 19 – 5.1 – – – – – – – – – – – – – 72 72

S5 58 – – – – 6.9 – – – – – – – – – – – 1.7 1.7 31 31
44 VOC Blank Data and Study Reporting Levels, California GAMA PBP, 2004–2010 Table 9. Raw detection frequencies by study unit of volatile organic compounds (VOCs) before and after application of study reporting units (SRLs), California GAMA Priority Basin Project, May 2004 through September 2010.—Continued [Detection frequencies are not area-weighted; they are raw detection frequencies indicating the percentage of detections among the total number of groundwater samples. Thus, original detection frequencies may not be the same as those reported for grid well networks in the Data Series Reports for individual study units. Study unit names given in table 1. Detection frequencies of zero are indicated by the – symbol] Study unit Number of samples Ethylbenzene 1,2,4- Trimethyl- benzene Toluene

m- and 

pXylenes o-Xylene Acetone 2-Butanone Tetrahy- drofuran Carbon disulfide Chloroform

Initial Final Initial Final Initial Final Initial Final Initial Final Initial Final Initial Final Initial Final Initial Final Initial Final

Central Valley study unitsV1 66 4.5 – 6.1 – 7.6 – 6.1 – 6.1 – – – 1.5 – 1.5 – 1.5 1.5 12 12

V2 87 – – 10 – 1.1 – – – – – 1.1 – 1.1 – – – 4.6 3.5 16 16

V3 87 1.1 – 1.1 – 14 – 5.7 – – – 1.1 – – – 1.1 – 14 6.9 33 33

V4 75 6.7 – 9.3 1.3 35 – 11 – 5.3 – – – – – 2.7 – 2.7 1.3 29 27

V5 78 1.3 1.3 2.6 – 3.8 1.3 1.3 – – – – – – – – – 3.8 2.6 26 24

V6 35 – – 5.7 – 2.9 – – – – – – – – – – – – – 17 17

V7 101 3.0 2.0 5.0 – 5.0 – 13 – 3.0 1.0 1.0 – 1.0 – 1.0 – 7.9 6.9 28 28

V8 50 2.0 – 4.0 – 4.0 – – – – – – – – – – – 4.0 4.0 28 26V9 56 1.8 – 1.8 – 1.8 – – – 1.8 – – – – – – – 11 8.9 7.1 5.4

All 2,026 0.9 0.2 11 0.2 7.7 0.2 1.9 – 0.7 0.05 0.4 – 0.4 – 1.2 – 4.3 3.3 27 26

1An additional 18 samples were collected for study unit M6 in October 2010.
Quality-Control Assessment Results 45

Bender and others (2011) also reported detection 

frequencies of ethylbenzene, m- and p-xylenes, and o-xylene 

in field blanks collected at production wells and at monitoring 

wells greater than detection frequencies in groundwater 

samples collected at those site types. Field blanks collected 

at production wells by the GAMA Program (this study) and 

by the NAWQA Program (Bender and others, 2011) had 

similar detection frequencies for each of these three VOCs 

(fig. 3). However, the SRLs calculated by Bender and others 

(2011) have much lower concentrations (fig. 14) because 

they used the BD-90/90 method to calculate SRLs. For the 

278 production well field blanks used by Bender and others 

(2011), the BD-90/90 corresponds to the 258th-ranked field 

blank, which yielded SRLs of 0.008 μg/L for ethylbenzene 

and 0.02 μg/L for m- and p-xylenes (the method yielded no 

SRL for o-xylene because the 258th-ranked field blank was 

a non-detection). These SRLs result in little censoring of 

groundwater data. Application of the BD-90/90 method to the 

167 QCFBs in this study would have resulted in (1) no SRLs 

for ethylbenzene or o-xylene (table 7) because the 156thranked field blank was a non-detection, and (2) an SRL of 

0.033 μg/L for m- and p-xylenes. The BD-90/90 method does 

not yield an SRL if the detection frequency in the field blanks 

is less than approximately 7 percent. 

Benzene and styrene were detected in laboratory 

instrument blanks and in field blanks affected by methanol 

(tables 4, 6; figs. 11, 12). Neither was detected in the QCFBs; 

therefore, none of the four methods for determining SRLs 

yielded concentrations. The BD-99/90 for benzene in 

laboratory instrument blanks was 0.006 μg/L, which was 

lower than all of the concentrations detected in groundwater 

samples (fig. 11). No SRLs are recommended for benzene or 

styrene on the basis of detections in the blanks (table 8). 

Toluene

Toluene, like ethylbenzene, m- and p-xylenes, and 

o-xylene, was detected more frequently in blanks than in 

groundwater samples; it is discussed separately, however, 

because the patterns of toluene detections differed from those 

of the other hydrocarbons. Toluene was the most frequently 

detected VOC in laboratory instrument blanks, source-solution 

blanks, and field blanks (table 4; fig. 15).

Inferred Mechanisms of Contamination

The relations between toluene and other hydrocarbons 

and of the relative detection frequencies of toluene in 

laboratory instrument blanks, source-solution blanks, the 

various subsets of field blanks, and groundwater samples 

suggest that there are multiple sources of contamination for 

toluene. Although toluene concentrations in blanks were 

significantly correlated to concentrations of ethylbenzene, 

m- and p-xylenes, and o-xylene in blanks (p<0.001 for 

Spearman’s rho tests), the relations were not dominated by 

single linear correlations as they were among ethylbenzene 

and the xylenes (fig. 13E). Contamination of equipment 

and vials by vehicle exhaust of fuel fumes may result in 

contamination of blanks and groundwater samples by toluene 

along with ethylbenzene and the xylenes; however, additional 

significant sources of toluene contamination are required to 

account for the relative detection frequencies.

Unlike ethylbenzene and the xylenes, toluene was 

detected less frequently in QCFBs (28 percent) than in 

source-solution blanks (41 percent) (table 4), and there was 

no significant difference in toluene occurrence between 

QCFBs collected with long and short sampling lines (table 6). 

This suggests that contact with field equipment was not the 

dominant source of contamination by toluene. The presence 

of toluene in laboratory instrument blanks (4.2 percent) 

indicates that there was a source of contamination in 

laboratory processes. The detection frequency of toluene 

in source‐solution blanks was significantly higher than in 

laboratory instrument blanks, suggesting that either the vials 

or processes occurring during transit to the field site also 

are sources of contamination. The detection frequency in 

groundwater samples (7.7 percent) was significantly lower 

than in source-solution blanks or field blanks, indicating that 

processes occurring during transit after sample collection 

could not have been a large source of contamination. These 

observations suggest that the primary sources of contamination 

were toluene that enters the bottles of source blank water after 

the initial certificates of analysis are produced and toluene that 

was present in the vials at the time of purchase and (or) that 

entered the vials during transit to the field.

Contamination of blanks by toluene derived from 

contact with field equipment is discernible when the blank 

data are divided into different concentration ranges. Of the 

320 total field blanks and source-solution blanks, 121 have 

detections of toluene (tables A2, A3). Two-thirds of the 

toluene detections had concentrations less than 0.03 μg/L (a 

value equal to the maximum LT-MDL, table 7), and one-third 

had concentrations between 0.03 μg/L and 0.69 μg/L. 

The group of field and source-solution blanks with higher 

toluene concentrations had hydrocarbon ratios and relations 

between detection frequencies and sample-collection 

equipment configurations similar to those observed for field 

blanks contaminated with ethylbenzene, o-xylene, and m-and 

p-xylenes. The group with higher toluene concentrations had 

a significantly higher detection frequency of m- and p-xylenes 

(68 percent) compared to the group with lower toluene 

concentrations (12 percent detection frequency of m- and 

p-xylenes; contingency table tests, p<0.001). Toluene and 

m- and p-xylene concentrations had a strong linear correlation 

in the group with higher toluene concentrations (fig. 13D). 
46 VOC Blank Data and Study Reporting Levels, California GAMA PBP, 2004–2010

IP031454_Figure 14. compare

NAWQA study reporting level, in micrograms per liter

0 0.01 0.02 0.03 0.04 0.05 0.06

GAMA study reporting level, in micrograms per liter

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

toluene

1,2,4-trimethylbenzene

m- and p-xylenes

o-xylene

dichloromethane

chloroform carbon disulfide

ethylbenzene

styrene

1:1 line

2-butanone*

tetrahydrofuran*

acetone*

Hydrocarbons

Solvents

Other VOCs

EXPLANATION

*For GAMA, all detections of acetone, 2-butanone, and 

tetrahydrofuran in groundwater samples are censored. For 

NAWQA, acetone’s SRL is 1 microgram per liter, and 

2-butanone and tetrahydrofuran have no SRLs. [NAWQA 

SRLs are the SRLs determined for public-supply and 

domestic wells by Bender and others (2011).]

Figure 14. Concentrations of study reporting levels (SRLs) established from field blanks 

collected for the California GAMA Priority Basin Project, May 2004 through September 2010, and 

SRLs established from field blanks collected at production wells for the National Water-Quality 

Assessment (NAWQA) Program (Bender and others, 2011).
Quality-Control Assessment Results 47

IP031454_Figure 15. toluene

2004 2005 2006 2007 2008 2009 2010

0

0.02

0.04

0.06

0.08

0.10

Toluene concentration, in micrograms per liter

Date of sample collection

Quality-control field blank (QCFB, n=167)

Monitoring-well field blank (n=18)

Field blank contaminated by methanol (n=26)

Source-solution blank (n=109)

Laboratory instrument blank (n=2,411)

Groundwater—Long or short lines (n=1,859)

Groundwater—Monitoring well (n=167)

EXPLANATION

Sample type (only detections are shown)

Thresholds

Long-term method detection level (LT-MDL)

Study reporting level (SRL)

0

0.2

0.4

0.6

0.8

1.2

2

4

6

8

1.0

Toluene concentration, in micrograms per liter

Figure 15. Concentrations of toluene detected in field blanks, source-solution blanks, laboratory 

blanks, and groundwater samples, California GAMA Priority Basin Project, May 2004 through 

September 2010. Non-detections are not shown.
48 VOC Blank Data and Study Reporting Levels, California GAMA PBP, 2004–2010

The ratio was slightly higher than observed in ambient urban 

air (fig. 13E), suggesting that there may be a systematic 

fractionation. The group with higher toluene concentrations 

also had a significantly higher proportion of field blanks 

(80 percent field blanks, 20 percent source-solution blanks) 

compared to the group with the lower toluene concentrations 

(54 percent field blanks) (contingency test, p=0.006), 

suggesting that contact with field equipment increased 

contamination with toluene over the contamination present 

in source-solution blanks. The detection frequency of toluene 

with a concentration greater than 0.03 μg/L was significantly 

greater in QCFBs collected with long sampling lines compared 

to short sampling lines, and in field blanks contaminated 

with methanol compared to QCFBs (contingency table tests, 

p=0.013 and p<0.001, respectively). This is similar to the 

pattern observed for ethylbenzene, o-xylene, and m- and 

p-xylenes (table 6), suggesting that higher concentrations of 

toluene contamination in field blanks likely have the same 

origin as contamination with ethylbenzene, o-xylene, and 

m- and p-xylenes—exposure of the water or sampling 

equipment to fuel exhaust vapors.

In contrast, the group of blanks with lower concentrations 

of toluene appeared to be contaminated by toluene from a 

different source(s). There were no significant differences 

in detection frequency of toluene with concentrations less 

than 0.03 μg/L between methanol-contaminated field blanks 

compared to QCFBs (contingency table test, p=0.42), or 

between QCFBs collected with long sampling lines compared 

to short sampling lines (contingency table test, p=0.78).

These patterns are consistent with the source of contamination 

being the vials and the source-blank water, as inferred 

from comparison of detection frequencies in laboratory 

instrument blanks, source-solution blanks, field blanks, and 

groundwater samples.

SRL for Toluene

The detection frequency of toluene in groundwater 

without censoring is 7.7 percent. On the basis of the 

inferred mechanisms of contamination for field blanks 

and groundwater samples, a large portion of the detections 

in groundwater samples may be the result of extrinsic 

contamination, suggesting that an SRL that results in 

censoring of a large portion of the groundwater data may 

be most appropriate. However, the highest concentration 

measured in groundwater samples was 10 times higher than 

the highest concentration measured in field blanks, suggesting 

that at least some of the detections in groundwater are likely to 

represent intrinsic, rather than extrinsic contamination. 

SRLs derived from the four methods all result in 

substantial reduction in the detection frequency of toluene 

in groundwater samples (table 7). If an SRL were calculated 

using the maximum QCFB method, detection frequency in 

groundwater samples would decrease from 7.7 to 0.2 percent, 

and if the maximum LT-MDL method were used, the detection 

frequency would be 2.6 percent. The detection frequencies 

that resulted by using SRLs computed from the BD-95/90 and 

BD-90/90 were 0.8 and 1.6 percent, respectively. Given the 

multiple potential sources of extrinsic toluene contamination 

and the likelihood that some of the detections in groundwater 

are indicative of intrinsic contamination, the SRL based on 

the QCFB method—0.69 μg/L—was selected (table 8). Of 

the 156 toluene detections in groundwater samples, 152 were 

censored by application of the SRL.

Bender and others (2011) also reported detection 

frequencies of toluene in field blanks collected at production 

wells and at monitoring wells greater than detection 

frequencies in groundwater samples collected at those site 

types. The detection frequency in field blanks collected at 

production wells was 34 percent, which is similar to the 

detection frequency observed in field blanks collected for 

GAMA (fig. 3); however, the SRL calculated by Bender and 

others (2011) had a much lower concentration than the SRL 

selected during this study (fig. 14). Bender and others (2011) 

used the BD-90/90 method to calculate the SRL of 0.05 μg/L 

for data from production wells; the BD-90/90 method applied 

to the QCFBs in this study would have yielded an SRL with 

nearly the same concentration (table 7).

1,2,4-Trimethylbenzene

The occurrence patterns of 1,2,4-trimethylbenzene in 

blanks and groundwater samples were quite different from 

the patterns observed for any of the other hydrocarbons. The 

1,2,4-trimethylbenzene concentration was not significantly 

correlated with concentrations of toluene or m- and p-xylenes 

(p>0.05, Spearman’s rho tests; fig. 13F). Fifty-nine percent 

of blanks and 49 percent of groundwater samples containing 

1,2,4-trimethylbenzene had no other detections of VOCs. 

Detections of 1,2,4-trimethylbenzene commonly occurred in 

clusters in time (fig. 16). Detection frequency in groundwater 

samples (11 percent) was greater than in QCFBs (6.0 percent) 

or source-solution blanks (6.4 percent) (table 4), and the 

ranges of concentrations measured in the groundwater samples 

and blanks were similar (fig. 13F).
Quality-Control Assessment Results 49

IP031454_Figure 16. 1,2,4-tmb 1,2,4-Trimethylbenzene concentration, in micrograms per liter

Date of sample collection

2004 2005 2006 2007 2008 2009 2010

0

0.05

0.10

0.15

0.20

0.25

0.5

1.0

1.5

2.0

Quality-control field blank (QCFB, n=167)

Monitoring-well field blank (n=18)

Field blank contaminated by methanol (n=26)

Source-solution blank (n=109)

Laboratory instrument blank (n=2,411)

Groundwater—Long or short lines (n=1,859)

Groundwater—Monitoring well (n=167)

EXPLANATION

Sample type (only detections are shown)

Thresholds

Long-term method detection level (LT-MDL)

Study reporting level (SRL)

Figure 16. Concentrations of 1,2,4-trimethylbenzene detected in field blanks, source-solution blanks, 

laboratory blanks, and groundwater samples, California GAMA Priority Basin Project, May 2004 through 

September 2010. Non-detections are not shown.
50 VOC Blank Data and Study Reporting Levels, California GAMA PBP, 2004–2010

Inferred Mechanisms of Contamination

An understanding of the probable source of 

contamination was useful for selecting an appropriate 

recommended SRL for 1,2,4-trimethylbenzene. As with the 

other hydrocarbons, the relative detection frequencies in 

laboratory instrument blanks, source-solution blanks, the 

various subsets of field blanks, and groundwater samples 

provided data as to the likely source of contamination 

with 1,2,4-trimethylbenzene. The detection frequencies 

of 1,2,4-trimethylbenzene in source-solution blanks and 

QCFBs were not significantly different (table 4), suggesting 

that contact with field sample-collection equipment was 

not a source of contamination. However, QCFBs collected 

with monitoring-well equipment and QCFBs collected with 

long sampling lines had significantly greater occurrence of 

1,2,4-trimethylbenzene than QCFBs collected with short 

sampling lines (table 6), suggesting that contact with field 

sample-collection equipment was a source of contamination. 

1,2,4-Trimethylbenzene was the only hydrocarbon that 

did not have significantly greater occurrence in field 

blanks contaminated with methanol (table 6), suggesting 

that unlike the other hydrocarbons, the occurrence of 

1,2,4-trimethylbenzene in field blanks was not related to 

the amount of rinsing of sampling equipment that occurred 

during collection of the field blanks. These seemingly 

contradictory observations suggest that contamination with 

1,2,4-trimethylbenzene was caused by a difference between 

sample collection with short sampling lines and sample 

collection with long sampling lines or monitoring-well 

equipment that was not related to increased contact 

with equipment.

One difference between sites sampled with short 

sampling lines and sites sampled with long sampling lines 

or monitoring-well equipment is that samples for radon-222 

analysis were more likely to be collected with the latter two 

equipment types. The scintillation media in the vials used 

to collect radon-222 samples is a mixture of mineral oil and 

1,2,4-trimethylbenzene (Horton, 1983; Whittaker and others, 

1989; Vitz and Martin, 1991). Therefore, samples collected 

with long sampling lines or monitoring-well equipment were 

more likely to be collected under conditions where a potential 

source of 1,2,4-trimethylbenzene was present than were 

samples collected with short sampling lines.

Radon-222 samples were not collected at all sites 

sampled for the GAMA-PBP. Radon-222 samples were 

collected at 616 (30 percent) of the 2,026 sites sampled (see 

references in table A1 for data). In most study units for which 

radon-222 samples were collected, they were only collected 

at sites where samples for the larger suite of analytes were 

collected. Samples for radon-222 were not collected at sites 

sampled for only the core suite of analytes. Most sites at which 

the larger suite of analytes were collected were sampled with 

long sampling lines or monitoring-well equipment, and most 

sites at which only the core suite of analytes were collected 

were sampled with short sampling lines. Long sampling lines 

or monitoring-well equipment were used at 82 percent of the 

sites at which a sample for radon-222 was collected. Samples 

for radon-222 were collected at 37 percent of the sites at which 

field blanks were collected These data indicate that a potential 

source of contamination of 1,2,4-trimethylbenzene—the vials 

used to collect radon-222 samples—were more likely to be 

present at sites where long sampling lines or monitoring-well 

equipment was used, which may account for the higher 

occurrence of 1,2,4-trimethylbenzene in field blanks collected 

with long sampling lines compared to short sampling lines.

Further examination of the correlations between 

collection of radon-222 samples and occurrence of 

1,2,4-trimethylbenzene provided additional evidence 

that collection of radon-222 samples is responsible for 

contamination of groundwater samples and blanks by 

1,2,4-trimethylbenzene. The detection frequency of 

1,2,4-trimethylbenzene in groundwater samples from sites 

where a sample for radon-222 was collected (29 percent) 

was significantly greater than the detection frequency 

in groundwater samples from sites where a sample for 

radon-222 was not collected (4.1 percent) (contingency 

table test, p<0.001) (fig. 17A). The detection frequency 

of 1,2,4-trimethylbenzene in field and source-solution 

blanks collected at sites where radon-222 samples were 

collected (16 and 13 percent, respectively) also were 

significantly greater than the detection frequency in field 

and source‐solution blanks from sites where radon-222 

samples were not collected (2.4 and 1.6 percent, respectively) 

(contingency table tests, p<0.001 and p=0.019) (fig. 17A). 

There were no significant differences in detection frequencies 

between field blanks and source-solution blanks. 
Quality-Control Assessment Results 51

IP031454_Figure 17a. 1,2,4-tmb

A

1,2,4-Trimethylbenzene detection frequency, in percent

0

5

10

15

20

25

30

35

EXPLANATION

Radon collected at site

Radon collected at previous site

Groundwater samples Field blanks Source-solution blanks

YES

YES NO

NO

n = 813 n = 1,525 n = 576 n = 1,026

Radon collected at same site or at previous site

Yes No Yes No

Same Previous

n = 87 n = 129 n = 52 n = 98

Yes No Yes No

Same Previous

n = 47 n = 60 n = 21 n = 43

Yes No Yes No

Same Previous

The number of sites in each category at which groundwater 

samples, field blanks, or source-solution blanks were 

collected is given below the bar.

Figure 17. Relations between detection frequencies of 1,2,4-trimethylbenzene in groundwater samples and 

blanks and (A) whether or not samples for analysis of radon-222 were collected at the same site or previous 

site, and (B) which GAMA field vehicle visited the site, California GAMA Priority Basin Project, May 2004 

through September 2010.
52 VOC Blank Data and Study Reporting Levels, California GAMA PBP, 2004–2010 Percentage of sites

0

10

20

30

40

50

70

60

W

n = 501

X

n = 289

G

n = 318

B

n = 112

V

n = 282

W

n = 56

X

n = 34

G

n = 34

B

n = 2

V

n = 21

W

n = 24

X

n = 14

G

n = 13

B

n = 3

V

n = 9

Groundwater samples Field blanks Source-solution blanks

Vehicle visiting site

EXPLANATION

USGS-GAMA vehicles

 W = White lab

 X = X-Lab

 G = Green Lab

 B = Blue Lab

 V = Van

 Sample for radon 

 collected

 1,2,4-Trimethylbenzene 

 detected

Five field vehicles were used to visit sites and collect samples for the California GAMA Priority Basin Project 

between May 2004 and September 2010. The number of sites visited by each vehicle for collection of 

groundwater samples, field blanks, or source-solution blanks is given below the vehicle letter code.

Percentage of sites

IP031454_Figure 17b. 1,2,4-tmb

B

Figure 17.—Continued
Quality-Control Assessment Results 53

The detection of 1,2,4-trimethylbenzene in groundwater 

samples and in blanks also had similar relations to whether or 

not radon-222 samples had been collected at a previous site 

visited by a particular sampling vehicle. The GAMA-PBP uses 

five different sampling vehicles, and the identity of the vehicle 

was recorded for nearly all sites visited between October 2005 

and September 2010. Nearly all of the detections of 

1,2,4-trimethylbenzene in groundwater samples and all of the 

detections in field blanks and source-solution blanks occurred 

at sites visited by three of the vehicles, the X-Lab, the White 

Lab, or the Green Lab (fig. 17B). The other two vehicles 

(the Blue Lab and the Van Lab) were never used at sites 

where samples were collected for radon-222, and although 

24 percent of the groundwater samples were collected in these 

two vehicles, only 2.9 percent of the 1,2,4-trimethylbenzene 

detections in groundwater samples occurred in samples 

collected using these two vehicles. The six detections of 

1,2,4-trimethylbenzene in groundwater samples that were 

collected in the Blue Lab were collected during two different 

weeks (one week in study unit V2, one week in study unit 

V7), and in both cases, groundwater samples collected in the 

White Lab in the same study unit during the same week had 

detections of 1,2,4-trimethylbenzene.

How and when does the 1,2,4-trimethylbenzene from 

the radon-222 vials reach the VOC vials? The VOC sample 

is collected and vials are sealed at the beginning of the 

sample collection sequence, and the radon-222 sample is 

collected near the end of the sample collection sequence. At 

sites sampled with long sampling lines or monitoring-well 

equipment, VOCs are collected inside the field vehicle, and 

radon is collected outside at the well head. Furthermore, field 

blanks and source-solution blanks are not collected for radon222. Thus, direct exposure of VOC samples at the field site to 

the 1,2,4-trimethylbenzene in the radon-222 sample vial used 

at the same field site is unlikely. 

The correlation between 1,2,4-trimethylbenzene 

occurrence and sampling vehicle (fig. 17B) and whether or 

not a sample for radon-222 was collected at the previous 

site (fig. 17A) suggest that radon-222 sampling can cause 

contamination of field vehicles with 1,2,4-trimethylbenzene. 

1,2,4-Trimethylbenzene is highly soluble in the mineral oil 

and would be expected to volatilize gradually, potentially 

contaminating the vehicle over time. The fact that detection 

frequencies of 1,2,4-trimethylbenzene were not significantly 

different between field blanks and source-solution blanks 

may suggest that the 1,2,4-trimethylbenzene was present in 

the atmosphere in the vehicle and entered the blank water 

by partial equilibration between the blank water and the 

atmosphere. The kits used for radon sampling are stored in 

the vehicle, and gloves that may have come in contact with 

the scintillation fluid during collection of the radon samples 

generally are disposed of inside the vehicle. Field personnel 

had not been told that the scintillation fluid may present a 

contamination problem. 

SRL for 1,2,4-Trimethylbenzene

The methods for calculating SRLs yield SRLs for 

1,2,4-trimethylbenzene that would result in vastly different 

amounts of censoring to the groundwater data (table 7). 

Application of the BD-90/90 method would result in no 

censoring of the groundwater data, and at the other extreme, 

use of the maximum concentration measured in the QCFBs 

as the SRL would result in reducing the detection frequency 

in groundwater samples from 11 to 0.2 percent. Because 

of the strong association between 1,2,4-trimethylbenzene 

contamination in blanks and groundwater samples and 

presence of materials connected with collection of samples 

for radon-222, it is likely that a large portion of the detections 

in groundwater samples may be the result of contamination. 

This suggests that an SRL that results in censoring of a large 

portion of the groundwater data may be most appropriate. 

The SRL derived from the maximum concentration 

in the QCFBs, 0.556 μg/L, was selected (table 8) and 

results in censoring nearly all of the groundwater data 

for 1,2,4-trimethylbenzene (table 8; fig. 16). Uncensored 

detections of 1,2,4-trimethylbenzene occurred in 216 

groundwater samples distributed across 25 of the 32 study 

units (table 9). After application of the SRL, there are only 

four detections in two study units. 

Other information about the four groundwater samples 

having detections of 1,2,4-trimethylbenzene after application 

of the SRL suggests that these four detections also may be 

the result of extrinsic contamination and not representative 

of aquifer conditions. Three of the samples were collected in 

the Green Lab (during study unit D5 data collection). All 52 

sites for study unit D5 were sampled by using the Green Lab 

or the X-Lab, and samples for radon-222 were collected at 

46 percent of the sites. In addition to the three samples with 

detections of 1,2,4-trimethylbenzene in groundwater with 

concentrations above the SRL, eight samples had detections 

with concentrations below the SRL that were censored by 

application of the SRL. The vehicle used for one sample was 

not recorded (study unit V4). Among the four groundwater 

samples with 1,2,4-trimethylbenzene concentrations greater 

than the SRL, one had no other VOCs detected, two had 

detections of toluene at concentrations less than the SRL, and 

two had detections of low concentrations of chloroform. This 

suggests that the detections of 1,2,4-trimethylbenzene with 

concentrations greater than the SRL likely also are the result 

of extrinsic contamination. Even though these four detections 

would not be censored by application of the SRL, it may 

be appropriate to censor the detections on the basis of the 

additional information about the samples. 
54 VOC Blank Data and Study Reporting Levels, California GAMA PBP, 2004–2010

Bender and others (2011) also reported detection 

frequencies of 1,2,4-trimethylbenzene in field blanks 

collected at production wells and at monitoring wells 

greater than detection frequencies in groundwater samples 

collected at those site types. The detection frequency in 

field blanks collected at production wells was 17 percent, 

which is considerably higher than the detection frequency 

observed in field blanks collected for the GAMA-PBP 

(fig. 3); however, the SRL calculated by Bender and others 

(2011) had a much lower concentration than the SRL selected 

in this study (fig. 14). Bender and others (2011) used the 

BD-90/90 method to calculate the SRL of 0.03 μg/L for data 

from production wells; the BD-90/90 method applied to the 

QCFBs in this study would have yielded no SRL because the 

detection frequency of 1,2,4-trimethylbenzene in the QCFBs 

was less than 7 percent. Approximately 54 percent of the 

9,000 groundwater sites sampled by the NAWQA Program 

have data for radon-222 (U.S. Geological Survey, 2012). 

Information concerning relations between field vehicles 

used at sites at which samples for radon-222 were collected 

and occurrence of 1,2,4-trimethylbenzene in blanks and 

groundwater samples is not available.

Chlorinated Organic Solvents

Dichloromethane and 1,1-dichloroethene were 

detected in source-solution blanks, and dichloromethane, 

tetrachloroethene, and trichloroethene were detected in 

QCFBs (table 4; figs. 18–21). The detection frequencies of all 

four solvents in groundwater samples were greater than the 

detection frequencies in QCFBs (table 4). 

Dichloromethane, 1,1-Dichloroethene, and 

Trichloroethene

The detection frequencies of dichloromethane and 

trichloroethene in the QCFBs were similar to the detection 

frequencies in the laboratory instrument blanks (table 4), and 

the concentrations detected in the QCFBs were within the 

range of concentrations detected in the laboratory instrument 

blanks (figs. 18, 21). These similarities suggest that laboratory 

sources of these two VOCs are sufficient to account for 

the observed detections in the QCFBs. Concentrations of 

dichloromethane and trichloroethene in field blanks affected 

by methanol were significantly greater than concentrations 

in field blanks not affected by methanol (table 6). 

Dichloromethane and trichloroethene are both highly soluble 

in methanol; thus their presence in field blanks contaminated 

by methanol is not surprising.

Because the detection frequencies of dichloromethane 

and trichloroethene in the QCFBs are less than 1 percent and 

the detected concentrations are low compared to most of the 

concentrations detected in groundwater samples, it is not 

necessary to censor the dichloromethane and trichloroethene 

data on the basis of detections in blanks. Application of the 

BD-95/90 method yields the result of no SRL for either VOC 

(table 7) because the detection frequencies of the two VOCs 

in the QCFBs are less than 3 percent. For the 167 QCFBs, the 

BD-95/90 method selects the 163rd-ranked blank as the SRL; 

if the detection frequency in the QCFBs is less than 3 percent, 

the 163rd-ranked blank is a non-detection. 

1,1-Dichloroethene was not detected in the QCFBs 

(table 4; fig. 19). Therefore, no SRL was defined.

Tetrachloroethene

The detection frequency of tetrachloroethene in the 

QCFBs was significantly greater than in the laboratory 

instrument blanks (table 4; contingency table test, p<0.001; 

fig. 20), indicating that there is a source of contamination 

beyond processes occurring during laboratory analysis. 

However, detection frequencies in the QCFBs and sourcesolution blanks were not significantly different (table 4; 

contingency table test, p=0.16), suggesting that contact with 

field sample-collection equipment is not a major source of 

extrinsic contamination. Given the low detection frequency 

of tetrachloroethene in the QCFBs (1.8 percent), and the 

lack of definitive pattern of detection frequencies pointing 

to a likely source of contamination, no censoring of the data 

for tetrachloroethene in groundwater samples appears to be 

needed. Application of the BD-95/90 method yields the result 

of no SRL for tetrachloroethene (table 7).

Other VOCs

The remaining four VOCs detected in blanks belong to 

three classes of VOCs and have been lumped together as the 

group “other VOCs” for convenience. Trichlorofluoromethane 

is a refrigerant, bromodichloromethane and chloroform are 

trihalomethanes, and carbon disulfide is naturally occurring 

and is used in industrial organic syntheses. The four VOCs 

are divided into three groups for discussion on the basis of 

patterns of detection in blanks.

Bromodichloromethane and Trichlorofluoromethane

Bromodichloromethane was detected in one 

field blank contaminated with methanol (fig. 22), and 

trichlorofluoromethane was detected in one QCFB and one 

source-solution blank collected at the same site (fig. 23). The 

detection frequencies in groundwater samples were greater 

than in blanks (table 4). Given the low detection frequencies in 

QCFBs for bromodichloromethane and trichlorofluoromethane 

(0 and 0.6 percent, respectively), no SRLs are needed 

for bromodichloromethane or trichlorofluoromethane. 

Application of the BD-95/90 method yields no SRLs for either 

VOC (table 7).
Quality-Control Assessment Results 55

IP031454_Figure 18. ch2cl2

Quality-control field blank (QCFB, n=167)

Monitoring-well field blank (n=18)

Field blank contaminated by methanol (n=26)

Source-solution blank (n=109)

Laboratory instrument blank (n=2,411)

Groundwater—Long or short lines (n=1,859)

Groundwater—Monitoring well (n=167)

EXPLANATION

Sample type (only detections are shown)

Threshold

Long-term method detection level (LT-MDL)

Dichloromethane concentration, in micrograms per liter

Date of sample collection

0

0.05

0.10

0.15

0.20

0.25

1

2

2004 2005 2006 2007 2008 2009 2010

A study reporting level (SRL) was not needed for dichloromethane.

Figure 18. Concentrations of dichloromethane detected in field blanks, source-solution blanks, 

laboratory blanks, and groundwater samples, California GAMA Priority Basin Project, May 2004 

through September 2010. Non-detections are not shown.
56 VOC Blank Data and Study Reporting Levels, California GAMA PBP, 2004–2010

IP031454_Figure 19. 1,1dce

Quality-control field blank (QCFB, n=167)

Monitoring-well field blank (n=18)

Field blank contaminated by methanol (n=26)

Source-solution blank (n=109)

Laboratory instrument blank (n=2,411)

Groundwater—Long or short lines (n=1,859)

Groundwater—Monitoring well (n=167)

EXPLANATION

Sample type (only detections are shown)

Threshold

Long-term method detection level (LT-MDL)

A study reporting level (SRL) was not needed for 1,1-dichloroethene.

1,1-Dichloroethene concentration, in micrograms per liter

Date of sample collection

0

1

2

3

4

5

6

7

2004 2005 2006 2007 2008 2009 2010

Figure 19. Concentrations of 1,1-dichloroethene detected in field blanks, source-solution blanks, 

laboratory blanks, and groundwater samples, California GAMA Priority Basin Project, May 2004 through 

September 2010. Non-detections are not shown.
Quality-Control Assessment Results 57

IP031454_Figure 20. pce

Quality-control field blank (QCFB, n=167)

Monitoring-well field blank (n=18)

Field blank contaminated by methanol (n=26)

Source-solution blank (n=109)

Laboratory instrument blank (n=2,411)

Groundwater—Long or short lines (n=1,859)

Groundwater—Monitoring well (n=167)

EXPLANATION

Sample type (only detections are shown)

Threshold

Long-term method detection level (LT-MDL)

A study reporting level (SRL) was not needed

for tetrachloroethene.

0

0.05

0.10

0.15

0.20

Tetrachloroethene concentration, in micrograms per liter

0

5

10

15

20

25

30

35

40

100

200

300

Tetrachloroethene concentration, in micrograms per liter

2004 2005 2006 2007 2008 2009 2010

Date of sample collection

Figure 20. Concentrations of tetrachloroethene detected in field blanks, source-solution blanks, 

laboratory blanks, and groundwater samples, California GAMA Priority Basin Project, May 2004 

through September 2010. Non-detections are not shown.
58 VOC Blank Data and Study Reporting Levels, California GAMA PBP, 2004–2010

IP031454_Figure 21. tce

Quality-control field blank (QCFB, n=167)

Monitoring-well field blank (n=18)

Field blank contaminated by methanol (n=26)

Source-solution blank (n=109)

Laboratory instrument blank (n=2,411)

Groundwater—Long or short lines (n=1,859)

Groundwater—Monitoring well (n=167)

EXPLANATION

Sample type (only detections are shown)

Threshold

Long-term method detection level (LT-MDL)

A study reporting level (SRL) was not needed

for trichloroethene.

0

0.10

0.20

0.30

0.40

Trichloroethene concentration, in micrograms per liter

0

10

20

30

40

50

60

70

80

Trichloroethene concentration, in micrograms per liter

2004 2005 2006 2007 2008 2009 2010

Date of sample collection

Figure 21. Concentrations of trichloroethene detected in field blanks, source-solution blanks, 

laboratory blanks, and groundwater samples, California GAMA Priority Basin Project, May 2004 

through September 2010. Non-detections are not shown.
Quality-Control Assessment Results 59

IP031454_Figure 22. bdcm

Quality-control field blank (QCFB, n=167)

Monitoring-well field blank (n=18)

Field blank contaminated by methanol (n=26)

Source-solution blank (n=109)

Laboratory instrument blank (n=2,411)

Groundwater—Long or short lines (n=1,859)

Groundwater—Monitoring well (n=167)

EXPLANATION

Sample type (only detections are shown)

Threshold

Long-term method detection level (LT-MDL)

A study reporting level (SRL) was not needed for bromodichloromethane.

Date of sample collection

0

0.2

0.6

0.4

0.8

2.0

1.0

3.0

5.0

4.0

7.0

6.0

2004 2005 2006 2007 2008 2009 2010

Bromodichloromethane concentration, in micrograms per liter

Figure 22. Concentrations of bromodichloromethane detected in field blanks, source-solution 

blanks, laboratory blanks, and groundwater samples, California GAMA Priority Basin Project, 

May 2004 through September 2010. Non-detections are not shown.
60 VOC Blank Data and Study Reporting Levels, California GAMA PBP, 2004–2010

IP031454_Figure 23. chcl3f

Quality-control field blank (QCFB, n=167)

Monitoring-well field blank (n=18)

Field blank contaminated by methanol (n=26)

Source-solution blank (n=109)

Laboratory instrument blank (n=2,411)

Groundwater—Long or short lines (n=1,859)

Groundwater—Monitoring well (n=167)

EXPLANATION

Sample type (only detections are shown)

Threshold

Long-term method detection level (LT-MDL)

A study reporting level (SRL) was not needed for trichlorofluoromethane.

Trichlorofluoromethane concentration, in micrograms per liter

Date of sample collection

0

0.5

1.0

1.5

2.0

2.5

10

30

20

2004 2005 2006 2007 2008 2009 2010

Figure 23. Concentrations of trichlorofluoromethane detected in field blanks, source-solution blanks, 

laboratory blanks, and groundwater samples, California GAMA Priority Basin Project, May 2004 

through September 2010. Non-detections are not shown.
Quality-Control Assessment Results 61

Carbon Disulfide

 Carbon disulfide has anthropogenic and natural 

sources. It has been an important industrial chemical since 

the 1800s, primarily because of its ability to solubilize fats, 

rubber, phosphorous, and other substances (Agency for Toxic 

Substances and Disease Registry, 1996). The most important 

current industrial uses are in the manufacturing of rayon, 

cellophane, and carbon tetrachloride. Carbon disulfide was 

used as a fumigant, primarily for insect control in stored grain, 

until registration was cancelled in 1985 (U.S. Environmental 

Protection Agency, 1985). Natural microbial reduction of 

sulfate produces carbon disulfide in soils, marshes, stratified 

lakes, and other anaerobic environments, and carbon disulfide 

is emitted to the atmosphere from the oceans and from 

volcanic eruptions (for example, Chin and Davis, 1993; Devai 

and DeLaune, 1995; Agency for Toxic Substances and Disease 

Registry, 1996).

Inferred Source of Contamination

Comparisons of detection frequencies and concentrations 

of carbon disulfide in laboratory instrument blanks, sourcesolution blanks, and field blanks suggest that there are sources 

of contamination during analysis of samples in the laboratory 

and in sample collection or handling in the field. The detection 

frequency in laboratory instrument blanks (1.6 percent) was 

lower than in other types of blanks (table 4); however, the 

differences were not statistically significant (contingency table 

tests, p>0.05), and the concentrations detected in all three 

types of blanks were similar (fig. 24).

There were no significant differences in detection 

frequencies of carbon disulfide between source-solution 

blanks (3.7 percent), methanol-affected field blanks 

(3.8 percent), field blanks collected with long sampling lines 

(3.2 percent), or field blanks collected with short sampling 

lines (2.9 percent) (tables 4, 6), indicating that contact 

with field sampling equipment likely was not the source of 

contamination during sample collection and handling. 

On the basis of results from two sets of laboratory 

experiments, the likely source of contamination by carbon 

disulfide is the nitrile gloves used by both laboratory and 

field personnel. Soaking a nitrile glove in 1,000 mL of blank 

water for 20 minutes yielded 38 μg/L carbon disulfide in 

the water (Worthington and others, 2007). In a separate 

experiment, soaking four types of nitrile gloves used by field 

or laboratory personnel in blank water for 24 hours leached 

800 to 11,600 micrograms per gram (μg/g) of carbon disulfide 

from the gloves (Lisa Olsen and Donna Rose, U.S. Geological 

Survey, written commun., 2011). One glove (approximately 

10 grams) soaked in 1,000 mL of water would yield 80 to 

1,160 μg/L carbon disulfide in the water. The carbon disulfide 

leached from gloves in these experiments may be sufficient 

to account for the low concentrations observed in field and 

source-solution blanks (0.01 μg/L to 0.09 μg/L). If blank 

water dripping off a glove contained 100 μg/L of carbon 

disulfide, then the median detected concentration observed 

in field blanks and source-solution blanks (0.056 μg/L) 

would correspond to a mixture of 0.056 percent drip water 

and 99.944 percent source-blank water. This is equivalent to 

approximately 1⁄2 drop of drip water in a 40-mL VOC vial. 

SRL for Carbon Disulfide

The occurrence pattern of carbon disulfide in 

groundwater samples is largely consistent with the pattern 

expected for the occurrence of carbon disulfide from natural 

sources; therefore, selection of an SRL that results in little 

censoring of the data may be most appropriate. Carbon 

disulfide can form naturally under anoxic conditions by 

reaction between organic matter and dissolved sulfide 

(for example, Devai and DeLaune, 1995). The detection 

frequency of carbon disulfide in groundwater samples 

considered anoxic (10 percent) was significantly greater than 

the detection frequency in groundwater samples considered 

oxic (1.5 percent) (contingency table test, p<0.001). [For 

the purposes of this report, samples are considered anoxic if 

dissolved oxygen concentration was less than 1 milligram 

per liter (mg/L) or if iron concentration was greater than 

100 μg/L or if manganese concentration was greater than 

50 μg/L. Anoxic samples were not further classified because 

of insufficient data: of the 2,026 groundwater samples, 1,783 

had dissolved oxygen data, 1,315 had iron and manganese 

data, and 1,243 had data for dissolved oxygen and for iron 

and manganese.] 

The methods for determining SRLs yield SRLs that result 

in censoring of vastly different amounts of the groundwater 

data. The BD-90/90 method does not yield an SRL because 

the detection frequency of carbon disulfide in the QCFBs is 

less than 7 percent, and therefore would result in no censoring 

of the groundwater data. The other methods yield SRLs 

ranging from 0.056 μg/L (BD-95/90) to 0.092 μg/L (maximum 

QCFB) (table 7). 

Application of the BD-95/90 as the SRL would reduce 

the detection frequency to 5.0 percent in anoxic samples 

and 0.08 percent in oxic samples. However, many of the 

detections censored by application of this SRL appear to 

be representative of aquifer conditions. Of the 18 oxic 

groundwater samples having carbon disulfide less than 

0.056 μg/L, 11 samples (61 percent) had detections of 

chlorinated solvents and 11 samples were from wells 

surrounded by more than 50 percent urban land use, which are 

factors that are correlated with industrial sources of carbon 

disulfide to groundwater. Many detections in groundwater 

samples appear to be representative of aquifer conditions; 

however, these detections would be censored by the 

application of an SRL as high as 0.056 μg/L.
62 VOC Blank Data and Study Reporting Levels, California GAMA PBP, 2004–2010

IP031454_Figure 24. cs2

Quality-control field blank (QCFB, n=167)

Monitoring-well field blank (n=18)

Field blank contaminated by methanol (n=26)

Source-solution blank (n=109)

Laboratory instrument blank (n=2,411)

Groundwater—Long or short lines (n=1,859)

Groundwater—Monitoring well (n=167)

EXPLANATION

Sample type (only detections are shown)

Thresholds

Long-term method detection level (LT-MDL)

Study reporting level (SRL)

0

0.02

0.04

0.08

0.06

0.10

0

0.1

0.2

0.3

0.4

0.5

0.6

0.6

1.2

2004 2005 2006 2007 2008 2009 2010

Date of sample collection

Carbon disulfide concentration, in micrograms per liter

Carbon disulfide concentration, in micrograms per liter

Figure 24. Concentrations of carbon disulfide detected in field blanks, source-solution blanks, 

laboratory blanks, and groundwater samples, California GAMA Priority Basin Project, May 2004 

through September 2010. Non-detections are not shown.
Quality-Control Assessment Results 63

The results for the laboratory instrument blanks indicate 

that an SRL is needed for carbon disulfide. The BD-99/90 

for carbon disulfide in the laboratory instrument blanks was 

0.022 μg/L, which is higher than the LT-MDL for some 

periods of time between May 2004 and September 2010 

(fig. 24). A BD-99/90 concentration greater than the LT-MDL 

may indicate that the set of samples used to establish the 

LT-MDL was not representative of the true variability, 

which would result in the LT-MDL having been too low a 

concentration. The SRL for carbon disulfide (0.03 μg/L) was 

defined as the highest concentration LT-MDL used for carbon 

disulfide between May 2004 and September 2010. Application 

of this SRL reduced the overall detection frequency in 

groundwater samples from 4.3 percent to 3.3 percent (tables 7, 

8). Detection frequencies in anoxic and oxic samples 

decreased to 8.4 percent and 0.9 percent, respectively. 

The detection frequencies of carbon disulfide in field 

blanks (7.2 percent) and groundwater samples (approximately 

8 percent) collected at production wells by the NAWQA 

Program (Bender and others, 2011) were greater than 

the detection frequencies observed in this study (3.2 and 

3.8 percent, respectively; table 4; fig. 3). The SRL calculated 

by Bender and others (2011) had a lower concentration than 

the SRL selected in this study (fig. 14). Bender and others 

(2011) used the BD-90/90 method to calculate the SRL of 

0.01 μg/L for data from production wells; the BD-90/90 

method applied to the QCFBs in this study would have yielded 

no SRL because the detection frequency of carbon disulfide in 

the QCFBs was less than 7 percent.

Chloroform

The trihalomethane chloroform was the most frequently 

detected VOC in groundwater samples (27 percent; table 4). 

Chloroform was detected in 1.8 percent of the QCFBs 

(table 4), and the patterns of detection of chloroform 

in field blanks, source-solution blanks, and laboratory 

instrument blanks are consistent with the primary source 

of contamination being the tap water used to rinse field 

equipment. Most tap water has been disinfected with chlorine 

solutions during the drinking-water treatment process. 

Chlorine solutions can react with organic matter present in 

the water, forming trihalomethanes and other halogenated 

disinfection byproducts. 

Inferred Source of Contamination

The occurrence of chloroform was significantly higher in 

field blanks contaminated with methanol (15 percent) than in 

ones not contaminated with methanol (3.2 percent) (table 6). 

Among the field blanks not contaminated with methanol, the 

occurrence of chloroform was significantly greater in field 

blanks collected at monitoring wells (17 percent) compared to 

field blanks collected with long sampling lines (3.2 percent) 

or short sampling lines (1.0 percent). The lines used for the 

monitoring-well sampling equipment are longer and more 

complex than those used for the long and short sampling lines 

sampling configurations. There may be higher probability that 

a small amount of tap water would remain in the equipment 

even after rinsing with a sufficient amount of blank water to 

remove the methanol. The median detected concentration of 

chloroform in field blanks was 0.038 μg/L (fig. 25; table A2). 

If the concentration of chloroform in tap water were 32 μg/L 

[the average concentration of trihalomethanes in Sacramento, 

California, tap water in 2010 (City of Sacramento, 2010)], 

then the median detected concentrations observed in the field 

blanks would correspond to a mixture of 0.12 percent tap 

water and 99.88 percent source-blank water. This is equivalent 

to approximately one drop of tap water in a 40-mL VOC vial. 

SRL for Chloroform

The methods for determining SRLs yield SRLs that result 

in censoring of vastly different amounts of the groundwater 

data. The BD-90/90 and BD-95/90 methods do not yield SRLs 

and therefore would result in no censoring of the groundwater 

data. Use of the maximum LT-MDL method would yield an 

SRL of 0.02 μg/L and result in a slight decrease in detection 

frequency in groundwater from 27 percent to 23 percent 

(table 7). At the other extreme, application of the maximum 

concentration detected in the QCFBs (0.127 μg/L) as the 

SRL would result in reducing the detection frequency of 

chloroform in groundwater to 9.3 percent. The fact that the 

detection frequency in the QCFBs (1.8 percent) is so much 

lower than the detection frequency in groundwater samples 

suggests that contamination has a negligible effect on 

chloroform detections; therefore, an SRL that results in little 

or no censoring of the groundwater data is warranted. On this 

basis, either the BD-95/90 method (no SRL) or maximum 

LT-MDL method would yield appropriate values for the SRL 

for chloroform (table 7). The BD-95/90 method was selected 

for consistency with other VOCs.

The occurrence of chloroform in field blanks collected 

with monitoring-well equipment (17 percent) was significantly 

greater than the occurrence in field blanks collected with long 

(3.2 percent) or short sampling lines (1.0 percent) (table 6), 

suggesting that an SRL may be warranted for groundwater 

samples collected with monitoring-well equipment. There 

were 18 field blanks collected at monitoring wells that were 

not affected by methanol, which is an insufficient number to 

define a BD-95/90. The maximum LT-MDL for chloroform, 

0.02 μg/L, was used as the SRL for groundwater samples 

collected with monitoring-well equipment. Application of 

this SRL decreases the detection frequency of chloroform 

in groundwater samples collected with monitoring-well 

equipment from 18 percent to 14 percent (table 8). Bender and 

others (2011) also reported that the detection frequency in field 

blanks collected at monitoring wells by the NAWQA Program 

(28 percent) was significantly greater than the frequency in 

field blanks collected at production wells (11 percent).
64 VOC Blank Data and Study Reporting Levels, California GAMA PBP, 2004–2010

IP031454_Figure 25. chcl3

Quality-control field blank (QCFB, n=167)

Monitoring-well field blank (n=18)

Field blank contaminated by methanol (n=26)

Source-solution blank (n=109)

Laboratory instrument blank (n=2,411)

Groundwater—Long or short lines (n=1,859)

Groundwater—Monitoring well (n=167)

EXPLANATION

Sample type (only detections are shown)

Threshold

Long-term method detection level (LT-MDL)

0

0.05

0.10

0.15

0.20

0

5

10

15

20

25

50

2004 2005 2006 2007 2008 2009 2010

Date of sample collection

Chloroform concentration, in micrograms per liter

Chloroform concentration, in micrograms per liter

A study reporting level (SRL) was not needed 

for chloroform for samples collected with long 

or short sampling lines. An SRL equal to the 

highest LT-MDL (0.02 microgram per liter) was 

needed for samples collected with monitoringwell equipment.

Figure 25. Concentrations of chloroform detected in field blanks, source-solution blanks, 

laboratory blanks, and groundwater samples, California GAMA Priority Basin Project, May 2004 

through September 2010. Non-detections are not shown.
Application of SRLs and Maximum LT-MDLS 65

The detection frequency of chloroform in field blanks 

collected at production wells (11 percent) by the NAWQA 

Program (Bender and others, 2011) was significantly greater 

than the detection frequency observed in this study (fig. 3). 

Bender and others (2011) used the BD-90/90 method to 

calculate the SRL of 0.02 μg/L for data from production wells; 

the BD-90/90 method applied to the QCFBs in this study 

would have yielded no SRL because the detection frequency 

of chloroform in the QCFBs was only 1.8 percent.

Application of SRLs and 

Maximum LT-MDLS

The GAMA-PBP uses 10-percent detection frequency 

in a study unit as a threshold for identifying organic 

constituents that may be of concern (for example, Landon 

and others, 2010). There are three primary issues associated 

with comparing detection frequencies at low concentrations: 

(1) discerning between VOC detections that are the result 

of extrinsic contamination and those that are representative 

of aquifer conditions; (2) comparing data collected at 

different times if laboratory reporting levels have changed 

over time; and (3) defining an acceptable probability of 

false-positive detections. The first issue is addressed by 

censoring water-quality data by using SRLs, and the latter 

two issues require examining the reporting of detections with 

concentrations near the LT-MDLs.

Application of SRLs had a noticeable effect on the 

identification of organic constituents that may be of concern. 

Initially, 20 VOCs had raw detection frequencies greater 

than 10 percent in at least 1 of the 32 study units. Of these 

20 VOCs, 5 have SRLs that were determined in this report: 

m- and p-xylenes, toluene, 1,2,4-trimethylbenzene, carbon 

disulfide, and chloroform. Application of the SRLs for 

the hydrocarbons resulted in large changes in detection 

frequencies: initial raw detection frequencies for m- and 

p-xylenes, toluene, and 1,2,4-trimethylbenzene were greater 

than or equal to 10 percent in 2, 5, and 11 of the 32 study 

units, respectively, and after application of the SRLs, there 

were no study units with raw detection frequencies greater 

than 10 percent (table 9). Initial raw detection frequency for 

carbon disulfide was greater than 10 percent in three GAMA 

study units; after application of the SRL it was greater than 

10 percent in one study unit (study unit S3). Application of 

the SRL for chloroform caused no change in the number 

of study units with raw detection frequency greater than 

10 percent (table 9). 

There were a total of 2,580 detections of 60 different 

VOCs in the 2,026 groundwater samples. Of those 

2,580 detections, 489 were censored by application 

of the recommended SRLs (table 8). Toluene and 

1,2,4-trimethylbenzene account for 74 percent of the 

detections censored. Of the remaining 2,091 detections in 

groundwater samples, 231 had concentrations below the 

highest LT-MDL used during the study period. Nearly half of 

the detections with concentrations below the highest LT-MDL 

were of three VOCs: tetrachloroethene (49 of 259 detections 

had concentrations below 0.03 μg/L, fig. 20), chloroform (35 

of 539 detections had concentrations below 0.02 μg/L, fig. 25), 

and methyl tert-butyl ether (29 of the 113 detections had 

concentrations below 0.08 μg/L, not shown). All detections 

of four other VOCs had concentrations below the highest 

LT-MDL: 4-isopropyltoluene (3), bromomethane (1), methyl 

tert-pentyl ether (1), and sec-butylbenzene (1).

Effect of LT-MDL Changes on VOC 

Detection Frequencies

After application of SRLs, chloroform and 

tetrachloroethene were the two most commonly detected 

VOCs in GAMA groundwater samples collected between 

May 2004 and September 2010 (table 7). Comparisons were 

made between the detection frequencies of chloroform and 

tetrachloroethene in the 32 study units sampled during that 

period. Therefore, it was important to evaluate whether 

changes in LT-MDLs affected reporting of detections with low 

concentrations. This was evaluated by comparing data from 

periods with different LT-MDLs.

Of the 2,026 groundwater samples, 1,357 were 

analyzed during periods when the LT-MDL for chloroform 

was 0.01 μg/L, and 699 were analyzed when the LT-MDL 

was 0.015 μg/L or 0.02 μg/L. Samples in the two groups 

were divided into seven categories by concentration 

(non-detections, detections with concentrations less than 

0.02 μg/L, and detections with concentrations in five different 

ranges between 0.02 μg/L and 40 μg/L), and the frequencies 

in each category were compared (fig. 26A). There were no 

significant differences in frequencies in any category between 

samples analyzed during periods with the higher and lower 

LT-MDLs. During periods when the LT-MDL was 0.01 μg/L, 

74 percent of samples had a non-detection of chloroform, 

and 3.8 percent had a detection with concentration less than 

0.02 μg/L. During periods that the LT-MDL was 0.015 μg/L 

or 0.02 μg/L, 71 percent of samples had a non-detection of 

chloroform, and 3.6 percent had a detection with concentration 

less than 0.02 μg/L. These results suggest that changes in 

LT-MDL may not have affected reporting of detections 

with concentrations less than the maximum LT-MDL. 

Therefore, detection frequencies of chloroform in study units 

sampled during periods having different LT-MDLs should 

be able to be compared without re-censoring the data to the 

maximum LT-MDL.
66 VOC Blank Data and Study Reporting Levels, California GAMA PBP, 2004–2010

IP031454_Figure 26. ranges Percentage of groundwater samples

0

2

4

6

8

20

40

60

80

100

Not 0.01 0.02 0.03 0.04 0.05 0.15 40 0.01 0.02 0.03 0.04 0.05 220

detected

Not

detected

Chloroform concentration, in micrograms per liter Tetrachloroethene concentration, in micrograms per liter

LT-MDL = 0.01 microgram per liter (n=1,357)

LT-MDL = 0.015 or 0.02 microgram per liter (n=669)

LT-MDL = 0.015 microgram per liter (n=999)

LT-MDL = 0.02 or 0.03 microgram per liter (n=1,027)

A B

Figure 26. Percentages of groundwater samples in concentration range categories for different long-term method 

detection levels (LT-MDLs) for (A) chloroform and (B) tetrachloroethene.

A similar analysis for tetrachloroethene was also 

conducted, with statistically significant differences in two 

of the seven categories and no significant differences in 

five of the categories. Of the 2,026 groundwater samples, 

999 were analyzed during periods when the LT-MDL was 

0.015 μg/L, and 1,027 were analyzed during periods when 

the LT-MDL was 0.02 μg/L or 0.03 μg/L. The percentage of 

samples having a non-detection for tetrachloroethene was 

significantly greater during the period with higher LT-MDL 

(89 percent) than during the period with lower LT-MDL 

(85 percent) (contingency table test, p=0.003; fig. 26B). 

However, the types of study units sampled during the two 

periods were not the same. Periods with the higher LT-MDLs 

had a significantly higher percentage of samples from Desert 

or Mountain study units (28 percent) than did periods with the 

lower LT-MDL (20 percent) (contingency table test, p<0.001). 

These study units generally have lower population densities 

and therefore may have fewer sources of tetrachloroethene 

to groundwater. There were no significant differences in the 

percentages of samples having detections with concentrations 

in the four categories with concentrations between 0.01 and 

0.05 μg/L. The percentage of samples having detections with 

concentrations greater than 0.05 μg/L was significantly lower 

during periods with the higher LT-MDL than during periods 

with the lower LT-MDL (contingency table test, p=0.002) 

(fig. 26B); this difference is consistent with the difference in 

the population densities of study units sampled during the 

two periods. These observations—no significant difference 

in five of the seven categories and plausible explanation for 

significant differences in the other two categories—suggest 

that the lower detection frequency of tetrachloroethene in 

samples analyzed during periods when the LT-MDL was 

0.02 μg/L or 0.03 μg/L compared to periods when the 

LT-MDL was 0.015 μg/L may reflect true differences in the 

samples rather than being an artifact of differences in reporting 

of detections with low concentrations between the periods.

These results suggest that changes in LT-MDLs 

between May 2004 and September 2010 did not significantly 

affect the reporting of detections with low concentrations. 

Therefore, differences in detection frequencies of VOCs in 

GAMA study units sampled at different times likely reflect 

differences between the aquifers and are not artifacts of the 

LT-MDL changes.
Assessment of Methods Used for Determining Study Reporting Levels 67

Table 10. Probability of false-positive detections 

at fractions of the long-term method detection level 

(LT-MDL), and numbers of detections with concentrations 

below the threshold, California GAMA Priority Basin 

Project, May 2004 through September 2010.

[Probability calculated assuming that the standard deviation(s) and 

number of samples (n=24) used in the calculation of the original 

LT-MDL remain constant]

Threshold 

concentration

Probability of 

false-positive 

detection

(percent)

Number of detections 

with concentrations 

less than threshold

LT-MDL 1.0 231

3/4 LT-MDL 3.7 169

1/2 LT-MDL 11 35

1/4 LT-MDL 27 3

1/10 LT-MDL 40 0

LT-MDLs and Probabilities of 

False-Positive Detections

Depending on project objectives and how the data will be 

used, it may be appropriate to include detections with greater 

than a 1-percent probability of being false-positive detections 

(concentrations below the LT-MDL) in the dataset. However, 

if concentrations below the LT-MDL are included, the level of 

confidence in these detections should be stated in the report. 

The probability (α) of false-positive detection for a detection 

with concentration less than the LT-MDL can be estimated 

from the equation for the LT-MDL:

23,0.01 (revision of Equation 1) and LTMDL

LTMDL

t t

s = = (5)

23,1

where

is the fraction of the LT-MDL, and

is the probability.

f LTMDL

f LTMDL t t

s

f

× −α

× = =

α

(6)

The probabilities were calculated by assuming that the 

number of samples used to determine the LT-MDL (n=24) 

and the standard deviation of the values for those samples 

(s) remained the same as in the original determination of the 

LT-MDL. The probability of false-positive detection increases 

from 1 percent at the LT-MDL to 40 percent at one-tenth of the 

LT-MDL (table 10). 

After application of the SRLs, a total of 231 detections 

of VOCs had concentrations less than the maximum LT-MDL. 

Most had concentrations between the LT-MDL and one-half 

of the LT-MDL. The difference between the minimum and 

maximum LT-MDL was less than a factor of 2 for most VOCs 

(table 2); therefore, many of these detections may have had 

concentrations greater than the LT-MDL in effect at the time 

the samples were analyzed. Thirty-five detections of VOCs 

had concentrations below one-half of the LT-MDL (table 10). 

The probability of false-positive detection at concentrations 

less than one-half of the LT-MDL is greater than 11 percent. 

Of these 35 detections, 12 were of tetrachloroethene. 

Assessment of Methods Used for 

Determining Study Reporting Levels

Three philosophical issues relevant to analysis of 

field-blank data were introduced earlier in this report: use of 

statistical or deterministic methods for analysis of field‐blank 

data, use of methods based on contamination having a 

characteristic pattern of concentrations or a characteristic 

detection frequency, and use of different methods for 

different VOCs.

In this report we have followed a statistical approach 

in that blanks and environmental samples are treated as 

independent populations. In other words, a field blank 

collected at a particular site is considered representative of 

conditions under which environmental samples are collected 

at all sites, and field blanks are not directly compared to 

the “paired” environmental sample collected at the same 

site. Even in the evaluations of hypotheses about specific 

sources of contamination, a statistical approach was 

followed. Contamination, even from known sources, is a 

probabilistic process. 
68 VOC Blank Data and Study Reporting Levels, California GAMA PBP, 2004–2010

The case of 1,2,4-trimethylbenzene provides an example 

of the probabilistic nature of contamination. The detection 

frequencies of 1,2,4-trimethylbenzene at concentrations 

less than the SRL were 11 percent in field blanks collected 

with long sampling lines and 17 percent in groundwater 

samples collected with long sampling lines. The field blanks 

likely were contaminated by a mechanism that also would 

affect groundwater samples, namely airborne contact with 

1,2,4-trimethylbenzene that had contaminated field vehicles 

from storage of radon sampling kits or materials that had 

come in contact with radon sampling vials. However, of the 

seven field blanks collected with long sampling lines that 

had detection of 1,2,4-trimethylbenzene, only one was paired 

with an environmental sample that also had a detection of 

1,2,4-trimethylbenzene. The association between radon 

sampling and 1,2,4-trimethylbenzene likely would not have 

been apparent from only comparing the paired field blank and 

environmental sample data.

The reason for this apparent discrepancy is that not all of 

the field blanks or environmental samples were contaminated. 

There was an 11-percent probability that a field blank 

collected with long sampling lines would be contaminated 

with 1,2,4-trimethylbenzene and a 17-percent probability that 

an environmental sample collected with long sampling lines 

would be contaminated. Thus, if no other factors caused a 

greater or lesser tendency toward co-occurrence at the same 

site, there was a 1.8-percent probability that a field blank and 

environmental sample collected at the same site would both 

be contaminated, which is in agreement with the observed 

detection frequency in the data collected with long sampling 

lines (1 co-occurrence in 62 instances, which is a frequency of 

1.6 percent). 

After examining the different methods of determining 

SRLs for a range of VOCs, we reached the conclusion that 

selection of the most appropriate method for determining 

SRLs depended on the hypothesized or inferred mechanisms 

and frequencies of contamination of field blanks and 

environmental samples. We found that using different methods 

for different VOCs yielded SRLs that resulted in more rational 

censoring of groundwater data than attempting to apply a 

single approach for all compounds. 

For most VOCs having significantly lower detection 

frequencies in field blanks than in groundwater samples, 

the method selected for determining SRLs was the binomial 

probability method, using the BD-95/90 concentration as the 

SRL. For dichloromethane, tetrachloroethene, trichloroethene, 

chloroform, and trichlorofluoromethane, application of 

this method resulted in no SRL because the BD-95/90 was 

a non-detection (detection frequency in QCFBs was less 

than 3 percent). Maximum LT-MDLs could also have been 

selected as SRLs for these VOCs; however, censoring was 

not considered necessary on the basis of detections in blanks 

because detection frequencies in the QCFBs (0.6 percent for 

dichloromethane, trichloroethene, and trichlorofluoromethane; 

1.8 percent for chloroform and tetrachloroethene) were so 

low. Selection of the maximum QCFBs as SRLs would have 

resulted in unwarranted, high degrees of censoring of the 

groundwater data. Comparison of detection frequencies in 

source-solution blanks, groundwater samples, and different 

types of field blanks did not result in well-defined hypotheses 

for the sources and mechanisms of contamination to field 

blanks or groundwater samples. 

In contrast, for VOCs having higher detection frequencies 

in field blanks than in groundwater samples, application 

of the binomial probability method would have resulted in 

insufficient censoring. Ethylbenzene, m- and p-xylenes, and 

o-xylene had higher detection frequencies in field blanks 

than in groundwater samples, and the concentrations detected 

in blanks were similar to most concentrations detected in 

groundwater samples. Hydrocarbon ratios indicated that 

the likely source of contamination to field blanks and most 

groundwater samples was fuel exhaust or fumes. Comparison 

among detection frequencies in different types of field blanks 

suggested that the primary mechanism of contamination was 

contact with field sampling equipment, and differences in the 

amount of rinsing of field equipment plausibly accounted for 

the higher detection frequencies in field blanks compared to 

groundwater samples. The hydrocarbon ratios also indicated 

that the ethylbenzene and o-xylene in the groundwater samples 

with the highest concentrations (which were much higher 

than all of the concentrations in blanks) were likely from a 

different source. Selection of the maximum concentrations 

detected in the QCFBs as SRLs resulted in censoring of nearly 

all detections in groundwater. If the BD-95/90 values had been 

selected as the SRLs, many detections in groundwater with 

hydrocarbon ratios and concentrations indistinguishable from 

those in field blanks would have been retained. 

For VOCs with similar detection frequencies in field 

blanks and groundwater, the choice of the most appropriate 

method for determining an SRL was more complicated. In 

the case of 1,2,4-trimethylbenzene, the highest concentration 

detected in the QCFBs was deemed the most appropriate 

because it resulted in censoring of the most data; nearly all 

occurrences of 1,2,4-trimethylbenzene in groundwater samples 

could be accounted for by the same source and mechanism as 

were inferred for contamination of the field blanks. The likely 

source of the 1,2,4-trimethylbenzene was the scintillation 

fluid in the vials used for collection of radon samples, and 

the likely mechanism was pervasive contamination of field 

vehicles due to presence of materials (kits, used gloves, 

etc.) associated with sampling for radon. Selection of the 

SRL from the binomial probability method (BD-95/90 or 

BD-90/90) would have resulted in insufficient censoring of the 

groundwater data, although for different reasons than for the 

other hydrocarbons. 
Summary and Conclusions 69

In the case of carbon disulfide, the BD-95/90 and 

maximum concentration in the QCFBs methods both would 

have resulted in over-censoring of the groundwater data. The 

inferred source and mechanism of contamination—contact 

with the gloves worn by field and laboratory personnel—does 

affect field blanks and groundwater samples. However, the 

occurrence pattern of carbon disulfide in groundwater samples 

was broadly consistent with geochemical predictions (higher 

frequency of detection in anoxic groundwater), suggesting that 

extrinsic contamination was not the dominant source of carbon 

disulfide to the samples; therefore, the data were largely 

representative of aquifer conditions. The highest LT-MDL was 

selected as the SRL because it resulted in censoring of fewer 

data than the BD-95/90 SRL would have caused.

Summary and Conclusions

Volatile organic compounds (VOCs) were analyzed 

in quality-control samples collected for the California 

Groundwater Ambient Monitoring and Assessment (GAMA) 

Program Priority Basin Project (PBP). The project is being 

conducted by the U.S. Geological Survey (USGS) in 

cooperation with the California State Water Resources Control 

Board to assess and monitor the quality of groundwater 

resources used for drinking-water supply and to improve 

public knowledge of groundwater quality in California. 

From May 2004 through September 2010, a total of 2,026 

groundwater samples, 211 field blanks, and 109 sourcesolution blanks were collected and analyzed for concentrations 

of 85 VOCs. Results from these field and source-solution 

blanks, and from 2,411 laboratory instrument blanks analyzed 

during the same time period were used to assess the quality of 

data for the 2,026 groundwater samples. 

Of the 85 VOCs analyzed, 18 were detected in field 

blanks or source-solution blanks, and 67 were not detected. 

The VOCs detected in blanks can be divided into three groups:

Hydrocarbons Solvents Other VOCs

benzene acetone bromodichloromethane

ethylbenzene 2-butanone carbon disulfide

styrene 1,1-dichloroethene chloroform

toluene dichloromethane trichlorofluoromethane

1,2,4-trimethylbenzene tetrachloroethene

m- and p-xylenes tetrahydrofuran

o-xylene trichloroethene

The objective of the evaluation of the VOC-blank data 

was to determine if study reporting levels (SRLs) were needed 

for any of the VOCs detected in blanks to ensure the quality 

of the data from groundwater samples. An SRL is equivalent 

to a raised reporting limit that is used in place of the reporting 

limit used by the analyzing laboratory [laboratory reporting 

level (LRL) or long-term method detection level (LT-MDL)] 

to reduce the probability of reporting false positives. 

Evaluation of VOC-blank data was done in three stages: 

(1) identification of a set of representative quality-control 

field blanks (QCFBs) to be used for calculation of SRLs 

and identification of VOCs amenable to the SRL approach, 

(2) evaluation of potential sources of contamination to blanks 

and groundwater samples by VOCs detected in field blanks, 

and (3) selection of appropriate SRLs from among the SRLs 

defined using different approaches for determining SRLs for 

VOCs detected in field blanks and application of those SRLs 

to the groundwater data. 

An important conclusion from this study is that to 

ensure the quality of the data from groundwater samples, it 

was necessary to apply different approaches of determining 

SRLs from field-blank data to different VOCs, rather than 

use the same approach for all VOCs. There are multiple 

potential sources and mechanisms of extrinsic contamination 

of blanks and groundwater samples; these mechanisms do not 

have equal probabilities of affecting blanks and groundwater 

samples. The differences in detection frequencies and 

concentrations among different types of blanks (laboratory 

instrument blanks, source-solution blanks, and field 

blanks collected with three different sampling equipment 

configurations) and groundwater samples were used to infer 

the sources and mechanisms of contamination for each 

VOC detection in field blanks. Other chemical data for the 

groundwater samples (oxidation-reduction state, co-occurrence 

of VOCs, groundwater age) and ancillary information 

about the well sites (land use, presence of known sources of 

contamination) were used to evaluate whether the patterns of 

detections of VOCs in groundwater samples, before and after 

application of potential SRLs, were plausible. 

The SRL approach assumes that extrinsic contamination 

adds relatively low concentrations of VOCs to samples, 

and that there is a threshold concentration above which 

detections in groundwater samples have an acceptably 

small probability of being false positives. Contamination 

with acetone, 2-butanone, and tetrahydrofuran did not 

follow this pattern; therefore, these three VOCs were not 

amenable to the SRL approach. An inadvertent field test 

indicated that contamination with methanol can introduce 

2-butanone, acetone, and tetrahydrofuran into field blanks, 

and observations from field sites indicated that the presence 

of fresh PVC-cement can also contaminate groundwater 

samples and field blanks with these VOCs. In both cases, there 

was no threshold concentration above which detections in 

groundwater samples could be assumed to represent aquifer 

conditions rather than extrinsic contamination. Reported 

detections of 2-butanone, acetone, and tetrahydrofuran 

in groundwater samples were coded as “reviewed and 

rejected” in NWIS, which is interpreted to be the same 

as if the groundwater sample was not analyzed for those 

VOCs. Detection frequencies for acetone, 2-butanone, and 

tetrahydrofuran in groundwater samples therefore cannot 

be defined.
70 VOC Blank Data and Study Reporting Levels, California GAMA PBP, 2004–2010

Of the 211 field blanks, 167 constituted the set of 

QCFBs that was used to assess the quality of the groundwater 

data for VOCs. The 26 field blanks containing evidence of 

contamination with methanol [presence of acetone and (or) 

2-butanone] were not included in the QCFBs. Contamination 

with methanol primarily was related to steps in the sample 

collection process at which there are small differences in 

sample collection procedures between field blanks and 

groundwater samples; thus, field blanks contaminated with 

methanol were not considered representative of conditions 

under which groundwater samples were collected. The 18 field 

blanks collected with monitoring-well equipment and not 

contaminated with methanol also were not included in the 

QCFBs because they had significantly higher concentrations 

and detection frequencies of chloroform than field blanks 

collected with other sampling equipment configurations. There 

were no significant differences between field blanks collected 

with long sampling lines (62 field blanks) and short sampling 

lines (105 field blanks); these were grouped together as the 

QCFBs. Because the small number of field blanks collected 

with monitoring-well equipment precluded robust calculation 

of separate SRLs for groundwater samples collected with 

monitoring-well equipment, the SRLs determined from the 

QCFBs were applied to groundwater samples collected with 

all three sampling equipment configurations. 

Four potential SRL values were defined for each VOC 

using three approaches: two potential SRL values were defined 

using a binomial probability method based on one-sided, 

nonparametric upper confidence limits, one was defined as 

equal to the maximum concentration detected in the field 

blanks, and one was defined as the maximum LT-MDL used 

during the period samples were collected for the project. 

These four SRL values were compared, and one value was 

selected for each VOC as the SRL for use with GAMA 

groundwater data.

Ethylbenzene, m- and p-xylenes, and o-xylene had 

higher detection frequencies in QCFBs than in groundwater. 

All blanks and most groundwater samples had the same 

ratios of ethylbenzene and o-xylene to m- and p-xylenes, 

and concentrations in groundwater samples and field blanks 

were similar, implying a common source of contamination. 

Hydrocarbon ratios and comparisons between detection 

frequencies in different types of blanks suggest that the likely 

source is fuel or exhaust components sorbed onto sampling 

lines. The highest concentrations detected in the QCFBs 

[ethylbenzene, 0.06 microgram per liter (μg/L); m- and 

p-xylenes, 0.33 μg/L; and o-xylene, 0.12 μg/L] were selected 

as the SRLs because they resulted in the most censoring of 

groundwater data. Application of these SRLs resulted in 

censoring of 14 of 18 ethylbenzene detections, all 49 m- and 

p-xylenes detections, and 13 of 14 o-xylene detections in the 

2,026 groundwater samples.

Toluene was the most frequently detected VOC in 

QCFBs, source-solution blanks, and laboratory instrument 

blanks, and detection frequencies in blanks were greater 

than in groundwater. Comparisons between detection 

frequencies in different types of blanks suggest two sources 

of toluene contamination: the source of contamination with 

low concentrations may be the vials used for VOC samples 

and (or) contamination of the source-blank water during 

transit to field sites or storage in bottles, and the source 

of contamination with high concentrations may be fuel 

or exhaust components sorbed onto sampling lines. The 

highest concentration detected in the QCFBs, 0.69 μg/L, 

was selected as the SRL because it resulted in the most 

censoring of groundwater data. Application of this SRL 

resulted in censoring of 152 of the 156 detections of toluene in 

groundwater samples.

1,2,4-Trimethylbenzene detections in blanks and 

groundwater samples were not correlated with detections 

of other hydrocarbons. Three of the five field mobile labs 

used during the GAMA-PBP were used at sites where 

samples for radon were collected (approximately 30 percent 

of the 2,026 groundwater sampling sites), and detections 

of 1,2,4-trimethylbenzene in groundwater and blanks were 

confined to samples collected at sites visited by those mobile 

labs. Radon samples are collected in vials containing a 

scintillation cocktail composed of 1,2,4-trimethylbenzene 

and mineral oil. Although radon samples are collected at the 

wellhead, not in the mobile lab, the mobile labs apparently 

are subject to contamination from 1,2,4-trimethylbenzene, 

likely from storage of the kits used for radon sample 

collection and (or) disposal of gloves and other materials 

that may have come in contact with the radon sample 

vials. The highest concentration detected in the QCFBs, 

0.56 μg/L, was selected as the SRL because it resulted in 

the most censoring of groundwater data. Application of this 

SRL resulted in censoring of 212 of the 216 detections of 

1,2,4-trimethylbenzene in groundwater samples. 

Carbon disulfide was detected at similar concentrations 

and detection frequencies in QCFBs and source-solution 

blanks and at slightly lower frequency in laboratory instrument 

blanks. Most carbon disulfide detections in groundwater 

samples occurred in anoxic samples, which is consistent with 

predicted occurrence of carbon disulfide formed naturally 

under sulfate-reducing conditions. The most probable source 

of carbon disulfide contamination is the gloves worn by field 

and laboratory personnel. The recommended SRL for carbon 

disulfide is the maximum LT-MDL, 0.03 μg/L. Application 

of this SRL resulted in censoring of 20 of the 87 detections of 

carbon disulfide.

Chloroform was the most frequently detected VOC in 

groundwater samples. The detection frequency of chloroform 

in field blanks collected at monitoring wells was significantly 

greater than in QCFBs; chloroform was the only VOC for 

which different SRLs were recommended for groundwater 

samples collected at production wells and at monitoring wells. 

The SRL recommended for groundwater samples collected 

at monitoring wells was the highest LT-MDL, 0.02 μg/L. 

Application of this SRL resulted in censoring of 6 of the 

30 detections of chloroform in samples collected at monitoring 

wells. No SRL was recommended for groundwater samples 

collected with long or short sampling lines. 
References Cited 71

No SRLs were established for the remaining eight VOCs 

detected in field blanks. Benzene, styrene, 1,1-dichloroethene, 

and bromodichloromethane were not detected in QCFBs, 

and the detection frequencies of dichloromethane, 

tetrachloroethene, trichloroethene, and trichlorofluoromethane 

in QCFBs were less than 3 percent; thus the BD-95/90s of the 

QCFBs were non-detections. 

The 2,026 groundwater samples had a total of 

2,580 detections of 60 different VOCs. Of those 2,580 

detections, 489 were censored by application of the SRLs 

determined in this report. Of the remaining detections, 231 

had concentrations below the highest LT-MDL used during 

the study period. LT-MDLs changed by less than a factor of 2 

between May 2004 and September 2010 for most VOCs, and 

the changes did not significantly alter reporting of detections 

with low concentrations. Therefore, censoring at the highest 

LT-MDLs for VOCs that do not have SRLs does not appear 

to be necessary to ensure comparability between study units 

sampled at different times during that period.

Acknowledgments

We thank the members of the U.S. Geological Survey 

(USGS) Groundwater Ambient Monitoring Assessment 

(GAMA) Program Team who did all the field work, tracked 

all of the data, and wrote the data-series reports for individual 

study units. We especially thank the many well owners and 

water purveyors who allowed the USGS to collect samples 

from their wells. The GAMA Priority Basin Project is funded 

by State of California bonds authorized by Proposition 50 

and administered by the California State Water Resources 

Control Board. 

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Geological Survey Circular 1292, 101 p. (Also available at 

http://pubs.usgs.gov/circ/circ1292/.)
74 VOC Blank Data and Study Reporting Levels, California GAMA PBP, 2004–2010 Table A1. Study unit names and Data Series Reports, California GAMA Priority Basin Project, May 2004 through September 2010. [USGS, U.S. Geological Survey; DS, Data Series] Study unit Map code Data Series Report Online Desert study units Antelope Valley D1 Schmitt, S.J., Dawson, B.J., Belitz, K., 2009, Groundwater-quality data in the Antelope Valley study unit, 2008: Results from the California GAMA Program: USGS DS 479, 79 p. http://pubs.usgs.gov/ds/479/ Mojave D2 Mathany, T.M., Belitz, K., 2009, Ground-water quality data in the Mojave study unit, 2008: Results from the California GAMA Program: USGS DS 440, 80 p. http://pubs.usgs.gov/ds/440/ Coachella Valley D3 Goldrath, D.A., Wright, M.T., Belitz, K., 2009, Ground-water quality data in the Coachella Valley study unit, 2007: Results from the California GAMA Program: USGS DS 373, 70 p. http://pubs.usgs.gov/ds/373/ Colorado River D4 Goldrath, D.A., Wright, M.T., Belitz, K., 2010, Groundwater-quality data in the Colorado River study unit, 2007: Results from the California GAMA Program: USGS DS 474, 66 p. http://pubs.usgs.gov/ds/474/ Central Desert-Borrego D5 Mathany, T.M., Wright, M.T., Beuttel, B.S., Belitz, K., 2012, Groundwater-quality data in the Borrego Valley, Central Desert, and Low-Use Basins of the Mojave and Sonoran Deserts, 2008–2010: USGS DS 659, 100 p. http://pubs.usgs.gov/ds/659/ Mountain study units Sierra Nevada Regional M1 Shelton, J.L., Fram, M.S., Munday, C.M., Belitz, K., 2010, Groundwater-quality data for the Sierra 

Nevada study unit, 2008: Results from the California GAMA Program: USGS DS 534, 106 p.

http://pubs.usgs.gov/ds/534/

Owens-Indian Wells M2 Densmore, J.N., Fram, M.S., Belitz, K., 2009, Ground-water quality data in the Owens and Indian 

Wells Valleys study unit, 2006: Results from the California GAMA Program: USGS DS 427, 86 p. 

http://pubs.usgs.gov/ds/427/

Southern Sierra Nevada M3 Fram, M.S., Belitz, K., 2007, Ground-water quality data in the Southern Sierra study unit, 2006—

Results from the California GAMA Program: USGS DS 301, 78 p.

http://pubs.usgs.gov/ds/301/

Central Sierra Nevada M4 Ferrari, M.J., Fram, M.S., Belitz, K., 2008, Ground-water quality in the Central Sierra study unit, 

California, 2006: Results from the California GAMA Program: USGS DS 335, 60 p.

http://pubs.usgs.gov/ds/335/

Tahoe–Martis M5 Fram, M.S., Munday, C.M., Belitz, K., 2009, Groundwater quality data for the Tahoe–Martis study 

unit, 2007: Results from the California GAMA Program: USGS DS 432, 88 p. 

http://pubs.usgs.gov/ds/432/

Cascades-Modoc Plateau M6 Shelton, J.L., Fram, M.S., Belitz, K., 2012, Groundwater-quality data for the Cascades-Modoc Plateau 

study unit, 2010: Results from the California GAMA Program: USGS DS 688, 126 p.

Appendix

References for the Data Series Reports for GAMA study units sampled between May 2004 and September 2010 are listed in table A1. Concentrations of the 

17 VOCs detected in field or source-solution blanks are listed in table A2 for the 211 field blanks, and in table A3 for the 109 source-solution blanks. 
Appendix 75

Table A1. Study unit names and Data Series Reports, California GAMA Priority Basin Project, May 2004 through September 2010.—Continued[USGS, U.S. Geological Survey; DS, Data Series]

Study unit Map code Data Series Report Online

North and Central Coast study unitsEureka-Crescent City N1 Mathany, T.M., Dawson, B.J., Shelton, J.L., Belitz, K., 2011, Groundwater quality data in the 

Northern Coast Ranges study unit, 2009: Results from the California GAMA Program: USGS 

DS 609, 92 p.

http://pubs.usgs.gov/ds/609/

Ukiah-Clear Lake N2North San Francisco Bay N3 Kulongoski, J.T., Belitz, K., Dawson, B.J., 2006, Ground-water quality data in the North San 

Francisco Bay hydrologic provinces, California, 2004: Results from the California Ground-Water Ambient Monitoring Assessment (GAMA) Program: USGS DS 167, 100 p. 

http://pubs.usgs.gov/ds/ds167/

San Francisco Bay N4 Ray, M.C., Kulongoski, J.T., Belitz, K., 2009, Ground-water quality data in the San Francisco Bay 

study unit, 2007: Results from the California GAMA Program: USGS DS 396, 92 p. 

http://pubs.usgs.gov/ds/396/

Livermore-Gilroy-Cuyama N5 Mathany, T.M., Kulongski, J.T., Ray, M.C., Belitz, K., 2009, Groundwater quality data in the South 

Coast Interior Basins study unit, 2008: Results from the California GAMA Program: USGS DS 463, 82 p. 

http://pubs.usgs.gov/ds/463/

Monterey-Salinas N6 Kulongoski, J. T., Belitz, K., 2007, Ground-water quality data in the Monterey Bay and Salinas Valley 

Basins, California, 2005—Results from the California GAMA Program: USGS DS 258, 84 p. 

http://pubs.usgs.gov/ds/2007/258/

Santa Maria-Lompoc N7 Mathany, T.M., Burton, C.A., Land, M.T., Belitz, K., 2010, Groundwater-quality data in the South 

Coast Range–Coastal study unit, 2008: Results from the California GAMA Program: USGS 

DS 504, 106 p.

http://pubs.usgs.gov/ds/504/

South Coast study unitsSanta Clarita-Ventura S1 Montrella, J., Belitz, K., 2009, Ground-water quality data in the Santa Clara River Valley study unit, 

2007: Results from the California GAMA Program: USGS DS 408, 84 p. 

http://pubs.usgs.gov/ds/408/

Southern California Coastal 

Plain

S2 Mathany, T.M., Land, M.T., Belitz, K., 2008, Ground-water quality data in the coastal Los Angeles 

Basin Study Unit, 2006: Results from the California GAMA Program: USGS DS 387, 98 p. 

http://pubs.usgs.gov/ds/387/

San Gabriel–San Fernando S3 Land, M.T., Belitz, K., 2008, Ground-water quality data in the San Fernando–San Gabriel study unit, 

2005—Results from the California GAMA Program: USGS DS 356, 84 p. 

http://pubs.usgs.gov/ds/356/

Santa Ana–San Jacinto S4 Kent, R.H., Belitz, K., 2009, Ground-water quality data in the Upper Santa Ana Watershed Study 

Unit, November 2006 to March 2007: Results from the California GAMA Program: USGS DS 404, 

116 p. 

http://pubs.usgs.gov/ds/404/

San Diego area S5 Wright, M.T., Belitz, K., Burton, C.A., 2005, California GAMA Program—Ground-water quality in 

the San Diego Drainages hydrogeologic province, California, 2004: USGS DS 129, 91 p. 

http://pubs.usgs.gov/ds/2005/129/
76 VOC Blank Data and Study Reporting Levels, California GAMA PBP, 2004–2010 Study unit Map code Data Series Report Online Central Valley study units Northern Sacramento Valley V1 Bennett, P.A., Bennett, G.L., V, Belitz, K., 2009, Groundwater quality data in the northern Sacramento Valley, 2007: Results from the California GAMA Program: USGS DS 452, 90 p. http://pubs.usgs.gov/ds/452/ Middle Sacramento Valley V2 Schmitt, S.J., Fram, M.S., Dawson, B.J., Belitz, K., 2008, Ground-water quality data in the middle Sacramento Valley study unit, 2006—Results from the California GAMA Program: USGS DS 385, 100 p. http://pubs.usgs.gov/ds/385/ Southern Sacramento Valley V3 Dawson, B.J., Bennett, G.L., V, Belitz, K., 2008, Ground-water quality data in the Southern Sacramento Valley, California, 2005—Results from the California GAMA Program: USGS DS 285, 93 p. http://pubs.usgs.gov/ds/285/ Northern San Joaquin V4 Bennett, G.L., V, Belitz, K., Dawson, B.J., 2006, California GAMA Program—Ground-water quality data in the northern San Joaquin basin study unit, 2005: USGS DS 196, 122 p. http://pubs.usgs.gov/ds/2006/196/ Central Eastside V5 Landon, M.K., Belitz, K., 2008, Ground-water quality data in the Central Eastside San Joaquin Basin 2006: Results from the California GAMA Program: USGS DS 325, 88 p. http://pubs.usgs.gov/ds/325/ Madera-Chowchilla V6 Shelton, J.L., Fram, M.S., Belitz, K., 2009, Groundwater-quality data for the Madera–Chowchilla study unit, 2008: Results from the California GAMA Program: USGS DS 455, 80 p. http://pubs.usgs.gov/ds/455/ Southeast San Joaquin V7 Burton, C.A., Belitz, K., 2008, Ground-water quality data in the southeast San Joaquin Valley, 2005–2006—Results from the California GAMA Program: USGS DS 351, 103 p. http://pubs.usgs.gov/ds/351/ Kern Basin V8 Shelton, J.L., Pimentel, I., Fram, M.S., Belitz, K., 2008, Ground-water quality data in the Kern County subbasin study unit, 2006—Results from the California GAMA Program: USGS DS 337, 75 p. http://pubs.usgs.gov/ds/337/

Western San Joaquin Valley V9 Mathany, T.M., Landon, M.L., Belitz, K., 2012, Ground-water quality data in the Western San Joaquin 

Valley Study Unit, 2010: Results from the California GAMA Program: USGS DS 706 (in press)

Table A1. Study unit names, and Data Series Reports, California GAMA Priority Basin Project, May 2004 through September 2010.—Continued[USGS, U.S. Geological Survey; DS, Data Series]
Appendix 77

Table A2. Volatile organic compounds (VOCs) detected in field blanks, California GAMA Priority Basin Project, May 2004 through September 2010.[See table 1 for study unit names. Concentrations are reported here as unrounded values; data for these samples are reported as rounded values in the Data Series reports. Abbreviations: SSB, source-solution blank; μg/L, micrograms per liter; –, not detected]

Collection

date

Collection 

time

Paired

SSB

analyzed

Study

unit

Sampling line 

configuration

Inferred 

contamination with methanol

Hydrocarbons

Benzene 

(μg/L)

Ethylbenzene 

(μg/L)

Styrene

(μg/L)

1,2,4-Trimethylbenzene

(μg/L)

Toluene 

(μg/L)

m- and 

p-Xylenes 

(μg/L)

o-Xylene 

(μg/L)

05/24/2004 1158 Yes S5 Short Yes – – – – – – –06/17/2004 1348 No S5 Short No – – – – – – –

07/01/2004 1008 Yes S5 Long No – – – – – – –

07/12/2004 1628 Yes S5 Short No – – – – – – –

08/31/2004 0908 No N3 Short No – – – – – – –

09/13/2004 0948 No N3 Long No – 0.021 – – 0.060 0.105 0.039

09/14/2004 0838 No N3 Short No – – – – – – –

09/20/2004 1008 Yes N3 Short No – – – – 0.008 – –

09/30/2004 1528 No N3 Short No – – – – – – –

10/04/2004 1048 Yes N3 Long Yes – 0.039 – – 0.106 0.211 0.064

10/07/2004 0938 No N3 Short No – – – – – – –

10/18/2004 1148 No N3 Short No – – – – – – –

10/26/2004 1108 No N3 Short No – – – – – – –

11/02/2004 1038 Yes N3 Long No – 0.053 – – 0.104 0.321 0.105

12/13/2004 1348 No V4 Short No – – – – – – –

01/04/2005 1228 Yes V4 Short No – – – – 0.016 – –

01/04/2005 1308 Yes V4 Long No – 0.031 – – 0.057 0.198 0.068

01/10/2005 1008 Yes V4 Long Yes – 0.115 – – 0.302 0.522 0.232

01/12/2005 0938 No V4 Short No – – – – – – –

01/13/2005 0938 No V4 Short No – – – – – – –

02/08/2005 1208 No V4 Short No – – – – – – –

02/09/2005 1328 No V4 Short No – – – – – – –

03/22/2005 0938 Yes V3 Long Yes – 0.237 0.079 0.104 0.453 1.153 0.51103/23/2005 0938 Yes V3 Short No – – – – 0.015 0.028 –

03/29/2005 1108 Yes V3 Monitor Yes 0.009 0.044 – 0.039 0.154 0.304 0.083

03/31/2005 0938 Yes V3 Short No – 0.022 – – 0.686 0.083 0.037

04/20/2005 1108 No V3 Short No – – – – – – –

05/11/2005 1328 No V3 Short No – – – – – – –

05/19/2005 1258 No V3 Short No – – – – – – –

05/26/2005 1238 Yes V3 Short No – – – – 0.018 0.026 –

06/08/2005 1008 Yes S3 Long No – 0.022 – – 0.034 0.110 0.039

06/09/2005 0938 Yes S3 Short No – – – – – – –

06/13/2005 1238 Yes V3 Monitor No – 0.020 – 0.049 0.385 0.091 0.046

06/14/2005 1408 No S3 Short No – – – – – – –
78 VOC Blank Data and Study Reporting Levels, California GAMA PBP, 2004–2010 Table A2.

Volatile organic compounds (VOCs) detected in field blanks, California GAMA Priority Basin Project, May 2004 through September 2010.—Continued

[See table 1 for study unit names. Concentrations are reported here as unrounded values; data for these samples are reported as rounded values in the Data Series reports. Abbreviations: SSB, source-solution blank; μg/L, micrograms per liter; –, not detected]

Collection

date

Collection 

time

Paired

SSB

analyzed

Study

unit

Sampling line 

configuration

Inferred 

contamination with methanol

Hydrocarbons

Benzene 

(μg/L)

Ethylbenzene 

(μg/L)

Styrene

(μg/L)

1,2,4-Trimethylbenzene

(μg/L)

Toluene 

(μg/L)

m- and 

p-Xylenes 

(μg/L)

o-Xylene 

(μg/L)

06/22/2005 0948 Yes S3 Long No – 0.060 – – 0.077 0.328 0.120

07/11/2005 1438 Yes S3 Short No – – – – 0.009 – –

07/19/2005 0908 Yes N6 Long No – 0.028 – – 0.051 0.118 0.047

07/25/2005 1128 Yes N6 Short No – – – – – – –

08/02/2005 1218 Yes N6 Long No – – – – 0.012 – –

08/03/2005 0908 Yes N6 Long No – – – 0.556 0.036 0.065 –

08/09/2005 1008 Yes N6 Long No – 0.011 – – 0.048 0.057 0.020

08/10/2005 1208 Yes N6 Short No – – – – 0.194 – –

08/30/2005 1138 Yes N6 Short No – – – – 0.049 – –

09/01/2005 1008 Yes N6 Long Yes – – – – 0.022 – –

09/15/2005 0848 No N6 Short No – – – – – – –

09/19/2005 1148 No N6 Short No – – – – – – –

09/21/2005 1108 Yes N6 Monitor Yes – – – – 0.020 – –

10/17/2005 1338 Yes V7 Short No – – – – 0.065 – –

10/18/2005 0808 Yes V7 Long No – 0.022 – – 0.047 0.126 –

10/25/2005 0928 No V7 Short No – – – – – – –

10/26/2005 1308 Yes V7 Short No – – – – 0.017 – –

10/31/2005 1038 Yes V7 Monitor Yes – 0.055 – – 0.232 0.372 0.118

11/15/2005 1108 No V7 Monitor No – – – – – – –

11/16/2005 1038 Yes V7 Short No – – – – 0.016 – –

11/30/2005 0928 No V7 Long No – – – – – – –

11/30/2005 1208 No V7 Short No – – – – – – –

12/07/2005 1128 No V7 Short No – – – – – – –

12/13/2006 0908 Yes V7 Short Yes – 0.015 – – 0.053 0.066 0.02901/10/2006 1008 Yes V8 Long Yes – 0.046 – – 0.121 0.236 0.104

01/11/2006 1408 Yes V8 Short Yes – – – – 0.015 – –

01/24/2006 1248 Yes V8 Short No – – – – 0.012 – –

02/08 /2006 1208 Yes V8 Long No – – – – 0.026 – –

02/09/2006 0908 Yes V8 Short No – – – – 0.015 – –

03/14/2006 0908 Yes V5 Monitor No – – – – – – –

03/14 /2006 9038 Yes V5 Long Yes – 0.016 – – – 0.068 0.043

03/29/2006 0938 Yes V5 Long Yes – – – – – – –04/04/2006 1028 Yes V5 Short No – – – – 0.011 – –

04/20/2006 0938 No V5 Short No – – – – – – –
Appendix 79

Table A2. Volatile organic compounds (VOCs) detected in field blanks, California GAMA Priority Basin Project, May 2004 through September 2010.—Continued[See table 1 for study unit names. Concentrations are reported here as unrounded values; data for these samples are reported as rounded values in the Data Series reports. Abbreviations: SSB, source-solution blank; μg/L, micrograms per liter; –, not detected]

Collection

date

Collection 

time

Paired

SSB

analyzed

Study

unit

Sampling line 

configuration

Inferred 

contamination with methanol

Hydrocarbons

Benzene 

(μg/L)

Ethylbenzene 

(μg/L)

Styrene

(μg/L)

1,2,4-Trimethylbenzene

(μg/L)

Toluene 

(μg/L)

m- and 

p-Xylenes 

(μg/L)

o-Xylene 

(μg/L)

05/01/2006 1228 No V5 Short No – – – – – – –

05/09/2006 0608 Yes M4 Long Yes – 0.018 0.025 – 0.042 0.079 0.03705/10/2006 1008 No M4 Long No – – – – – – –

05/24/2006 1208 Yes M4 Long No – – – – 0.023 – –

05/25/2006 1208 Yes M4 Long No – – – – 0.011 – –

06/06/2006 0808 Yes M3 Long No – – – – – – –

06/06/2006 0928 Yes M3 Short No – – – – – – –

06/14/2006 0848 Yes M3 Short No – – – – 0.019 – –

06/15/2006 1008 No M3 Short No – – – – – – –

06/19/2006 0928 No M3 Short No – – – – – – –

06/22/2006 0958 No M3 Short No – – – – – – –

07/10/2006 1038 No V2 Short No – – – – – – –

07/11/2006 0938 No V2 Long No – – – – – – –

07/17/2006 1308 Yes V2 Monitor No – – – – 0.018 0.030 –

07/17/2006 1528 No V2 Short No – – – – – – –

07/20/2006 0908 Yes V2 Short Yes 0.013 0.013 0.010 – 0.076 0.044 0.027

07/24/2006 1158 No V2 Short No – – – – – – –

07/25/2006 1538 Yes V2 Monitor No – – – 0.019 0.069 0.074 –

08/03/2006 0938 Yes V2 Short Yes – 0.017 0.015 – 0.102 0.057 –08/07/2006 1008 Yes S2 Long No – – – – – – –

08/08/2006 0848 Yes V2 Short Yes – – 0.017 – 0.156 0.057 –08/14/2006 1258 Yes V2 Monitor No – – – – 0.017 – –

08/15/2006 0948 Yes V2 Monitor No – – – – – – –

08/21/2006 0958 No S2 Short No – – – – – – –

08/21/2006 1038 No V2 Monitor No – – – – – – –

08/28/2006 0958 Yes S2 Short Yes – – – – 0.060 – –

09/11/2006 1248 Yes S2 Short No – – – – – – –

09/13/2006 0828 No M2 Long No – – – – – – –

09/21/2006 0948 Yes M2 Short No – – – – 0.016 – –

10/03/2006 1248 No M2 Short No – – – – – – –

10/05/2006 1008 No M2 Short No – – – – – – –

10/24/2006 1008 Yes M2 Monitor No – – – – 0.024 – –

11/13/2006 1328 Yes S2 Short No – – – – 0.015 – –

11/15/2006 0938 Yes S2 Long No – – – – – – –
80 VOC Blank Data and Study Reporting Levels, California GAMA PBP, 2004–2010 Table A2.

Volatile organic compounds (VOCs) detected in field blanks, California GAMA Priority Basin Project, May 2004 through September 2010.—Continued

[See table 1 for study unit names. Concentrations are reported here as unrounded values; data for these samples are reported as rounded values in the Data Series reports. Abbreviations: SSB, source-solution blank; μg/L, micrograms per liter; –, not detected]

Collection

date

Collection 

time

Paired

SSB

analyzed

Study

unit

Sampling line 

configuration

Inferred 

contamination with methanol

Hydrocarbons

Benzene 

(μg/L)

Ethylbenzene 

(μg/L)

Styrene

(μg/L)

1,2,4-Trimethylbenzene

(μg/L)

Toluene 

(μg/L)

m- and 

p-Xylenes 

(μg/L)

o-Xylene 

(μg/L)

11/28/2006 1428 Yes S4 Short No – – – – 0.008 – –

11/29/2006 0908 Yes S4 Long No – – – 0.035 0.010 – –

12/05/2006 0938 Yes S4 Long Yes – – – – – 0.021 –

01/23/2007 1218 No S4 Short No – – – – – – –

01/30/2007 1328 Yes S4 Short No – – – – 0.016 – –

02/07/2007 0848 Yes S4 Long No – – – – – – –

02/08/2007 1208 No S4 Short No – – – – – – –

02/14/2007 1218 No S4 Short No – – – – – – –

02/28/2007 0938 Yes D3 Long No – 0.009 – – 0.019 0.033 0.010

03/05/2007 1208 Yes D3 Short No – – – – 0.011 0.020 –

03/22/2007 1008 Yes D3 Short No – – – – 0.126 – –

04/02/2007 0938 No S1 Short No – – – – – – –

04/02/2007 0948 Yes S1 Long Yes – – – – – – –

04/16/2007 0938 Yes S1 Short No – – – – – – –

04/17/2007 0858 Yes S1 Short No – – – – – – –

04/23/2007 0938 No N4 Short No – – – – – – –

04/23/2007 1038 Yes N4 Long No – – – – 0.017 0.053 –

04/30/2007 1258 No N4 Short No – – – – – – –

05/07/2007 1458 Yes S1 Monitor No – – – – 0.040 – –

05/08/2007 0928 Yes N4 Monitor No – – – – 0.017 – –

05/21/2007 0908 No N4 Short No – – – – – – –

05/21/2007 1058 Yes N4 Monitor No – – – – 0.012 0.032 –

06/13/2007 0918 Yes N4 Long Yes – – – – – – –

06/19/2007 0908 Yes N4 Monitor No – – – – 0.012 – –

06/20/2007 1338 No N4 Short No – – – – – – –

06/25/2007 1018 Yes M5 Long Yes – – – – 0.018 – –07/12/2007 0958 No M5 Long No – – – – – – –

07/25/2007 0838 No M5 Long No – – – – – – –

08/01/2007 0858 Yes M5 Long No – – – 0.121 0.015 – –

08/01/2007 0908 No M5 Long No – – – – – – –

08/27/2007 1008 Yes M5 Monitor No – – – 0.048 – – –08/27/2007 1038 No N3 Long No – – – – – – –

09/13/2007 0738 Yes M5 Long No – – – 0.050 – – –

10/02/2007 0848 No V1 Long No – – – – – – –

10/03/2007 1038 No D4 Long No – – – – – – –
Appendix 81

Table A2. Volatile organic compounds (VOCs) detected in field blanks, California GAMA Priority Basin Project, May 2004 through September 2010.—Continued[See table 1 for study unit names. Concentrations are reported here as unrounded values; data for these samples are reported as rounded values in the Data Series reports. Abbreviations: SSB, source-solution blank; μg/L, micrograms per liter; –, not detected]

Collection

date

Collection 

time

Paired

SSB

analyzed

Study

unit

Sampling line 

configuration

Inferred 

contamination with methanol

Hydrocarbons

Benzene 

(μg/L)

Ethylbenzene 

(μg/L)

Styrene

(μg/L)

1,2,4-Trimethylbenzene

(μg/L)

Toluene 

(μg/L)

m- and 

p-Xylenes 

(μg/L)

o-Xylene 

(μg/L)

10/29/2007 0928 No V1 Long No – – – – – – –

11/16/2007 1038 Yes N3 Short No – – – – 0.021 – –

11/28/2007 1008 No D4 Long No – – – – – – –

11/29/2007 1228 No V1 Long No – – – – – – –

12/10/2007 1028 No D4 Long No – – – – – – –

12/11/2007 0858 No V1 Long No – – – – – – –

01/09/2008 0908 Yes V1 Long No – – – – – – –

01/09/2008 1008 Yes V1 Monitor No – – – – – – –

01/16/2008 0858 Yes V1 Monitor Yes – – – – 0.019 – –

01/28/2008 0848 Yes D1 Long Yes – – – – 0.009 – –

01/28/2008 1418 Yes D1 Short No – – – – 0.015 – –

02/05/2008 0938 No D2 Short No – – – – – – –

02/07/2008 0918 Yes D1 Long Yes – – – – 0.014 – –

02/12/2008 1228 No D2 Long No – – – – – – –

02/13/2008 1148 Yes D1 Short No – – – – 0.023 – –

02/26/2008 1018 Yes D1 Short No – – – – – – –

03/04/2008 0958 No D2 Long No – – – – – – –

03/05/2008 0908 No D1 Long No – – – – – – –

03/18/2008 1318 No D2 Short No – – – – – – –

03/31/2008 1008 No V4 Long No – – – – – – –

04/03/2008 1028 No M5 Long No – – – – – – –

04/10/2008 1038 Yes D1 Short No – – – – 0.019 – –

04/16/2008 1028 No V6 Long No – – – – – – –

04/21/2008 1108 No V6 Long No – – – – – – –

04/28/2008 1308 No V6 Long No – – – – – – –

05/05/2008 0908 No V6 Long No – – – – – – –

05/21/2008 1438 No N7 Short No – – – – – – –

06/05/2008 0928 No N7 Long No – – – – – – –

06/11/2008 0908 Yes N7 Long No – – – – 0.175 – –

06/18/2008 1338 Yes N7 Short No – – – 0.085 – – –

06/23/2008 1138 No M1 Short No – – – – – – –

06/23/2008 1318 No N7 Short No – – – – – – –

07/10/2008 0948 Yes N7 Long Yes 0.019 – – – 0.026 – –07/16/2008 0938 Yes N7 Long No – – – – – – –

07/23/2008 1028 No M1 Short No – – – – – – –
82 VOC Blank Data and Study Reporting Levels, California GAMA PBP, 2004–2010 Table A2.

Volatile organic compounds (VOCs) detected in field blanks, California GAMA Priority Basin Project, May 2004 through September 2010.—Continued

[See table 1 for study unit names. Concentrations are reported here as unrounded values; data for these samples are reported as rounded values in the Data Series reports. Abbreviations: SSB, source-solution blank; μg/L, micrograms per liter; –, not detected]

Collection

date

Collection 

time

Paired

SSB

analyzed

Study

unit

Sampling line 

configuration

Inferred 

contamination with methanol

Hydrocarbons

Benzene 

(μg/L)

Ethylbenzene 

(μg/L)

Styrene

(μg/L)

1,2,4-Trimethylbenzene

(μg/L)

Toluene 

(μg/L)

m- and 

p-Xylenes 

(μg/L)

o-Xylene 

(μg/L)

07/29/2008 1038 No M1 Short No – – – – – – –

08/06/2008 0928 No M1 Short No – – – – – – –

08/07/2008 0848 No N7 Long No – – – – – – –

08/11/2008 0838 No N5 Short No – – – – – – –

08/18/2008 0848 No N5 Long No – – – – – – –

08/25/2008 0918 No M1 Short No – – – – – – –

08/26/2008 1128 No N5 Short No – – – – – – –

09/15/2008 1048 No M1 Short No – – – – – – –

09/17/2008 1008 No N5 Long No – – – – – – –

09/22/2008 0948 No N5 Short No – – – – – – –

10/09/2008 1048 No M1 Short No – – – – – – –

10/22/2008 1448 No M1 Short No – – – – – – –

10/29/2008 1108 No N5 Monitor No – – – – – – –

12/02/2008 0908 No D5 Short No – – – – – – –

12/11/2008 1018 No D5 Short No – – – – – – –

12/16/2008 0908 No D5 Short No – – – – – – –

06/01/2009 1048 Yes N2 Long No – – – 0.024 – – –

06/24/2009 0938 Yes N2 Long No – – – – – – –

07/14/2009 0948 Yes N2 Long No – – – 0.042 – – –

07/29/2009 1108 Yes N1 Long No – – – – – – –

08/17/2009 1008 Yes N1 Long No – – – – – – –

10/05/2009 1058 Yes N1 Long No – – – 0.020 – – –

10/20/2009 1218 No D5 Short No – – – – – – –

12/08/2009 1418 No D5 Short No – – – – 0.023 – –

03/03/2010 1028 Yes V9 Long No – – – – 0.041 – –

03/17/2010 1208 Yes V9 Short No – – – – 0.029 – –

04/06/2010 1048 No V9 Monitor No – – – – – – –

04/14/2010 0808 No V9 Long No – – – – – – –

05/18/2010 1208 No V9 Monitor No – – – – – – –

06/07/2010 0908 No V9 Short No – – – – – – –

06/15/2010 1008 No V9 Short No – – – – – – –
Appendix 83

Table A2. Volatile organic compounds (VOCs) detected in field blanks, California GAMA Priority Basin Project, May 2004 through September 2010.—Continued[See table 1 for study unit names. Concentrations are reported here as unrounded values; data for these samples are reported as rounded values in the Data Series reports. Abbreviations: SSB, source-solution blank; μg/L, micrograms per liter; –, not detected]

Collection

date

Collection 

time

Paired

SSB

analyzed

Study

unit

Sampling line 

configuration

Inferred 

contamination with methanol

Hydrocarbons

Benzene 

(μg/L)

Ethylbenzene 

(μg/L)

Styrene

(μg/L)

1,2,4-Trimethylbenzene

(μg/L)

Toluene 

(μg/L)

m- and 

p-Xylenes 

(μg/L)

o-Xylene 

(μg/L)

06/22/2010 1538 Yes V9 Short No – – – – 0.043 – –

07/14/2010 0908 Yes M6 Short No – – – – – – –

07/21/2010 0908 No M6 Short No – – – – – – –

07/28/2010 0908 No M6 Short No – – – – – – –

08/05/2010 1548 No M6 Short No – – – 0.069 – – –

08/10/2010 1028 No M6 Short No – – – – – – –

08/24/2010 0918 No M6 Short No – – – – – – –

08/31/2010 0928 No M6 Short No – – – 0.079 – – –
84 VOC Blank Data and Study Reporting Levels, California GAMA PBP, 2004–2010 Table A2.

Volatile organic compounds (VOCs) detected in field blanks, California GAMA Priority Basin Project, May 2004 through September 2010.—Continued

[See table 1 for study unit names. Concentrations are reported here as unrounded values; data for these samples are reported as rounded values in the Data Series reports. Abbreviations: SSB, source-solution blank; μg/L, micrograms per liter; –, not detected]

Collection 

date

Collection 

time

Solvents Other VOCs

Acetone 

(μg/L)

2-Butanone 

(μg/L)

1,1-Dichloroethene

(μg/L)

Dichloromethane

(μg/L)

Tetrachloroethene

(μg/L)

Tetrahydrofuran

(μg/L)

Trichloroethene

(μg/L)

Bromodichloromethane

(μg/L)

Carbon 

disulfide 

(μg/L)

Chloroform 

(μg/L)

Trichlorofluoromethane

(μg/L)

05/24/2004 1158 2.732 – – – – – – – – – –

06/17/2004 1348 – – – – – – – – – – –

07/01/2004 1008 – – – – – – – – – 0.127 –

07/12/2004 1628 – – – – – – – – – – –

08/31/2004 0908 – – – – – – – – – – –

09/13/2004 0948 – – – – – – – – – – –

09/14/2004 0838 – – – – – – – – – – –

09/20/2004 1008 – – – – – – – – – – –

09/30/2004 1528 – – – – – – – – – – –

10/04/2004 1048 2.91 – – – – – – – – – –

10/07/2004 0938 – – – – – – – – – – –

10/18/2004 1148 – – – – – – – – – – –

10/26/2004 1108 – – – – – – – – – – –

11/02/2004 1038 – – – – – – – – 0.073 – –

12/13/2004 1348 – – – – – – – – – – –

01/04/2005 1228 – – – – – – – – – – –

01/04/2005 1308 – – – – – – – – – – –

01/10/2005 1008 4.236 0.630 – – – – – – – – –

01/12/2005 0938 – – – – – – – – – – –

01/13/2005 0938 – – – – – – – – – – –

02/08/2005 1208 – – – – – – – – – – –

02/09/2005 1328 – – – – – – – – – – –

03/22/2005 0938 7.247 1.723 – – – – – – – – –

03/23/2005 0938 – – – – – – – – – – –

03/29/2005 1108 6.632 28.38 – – – 1.084 – – – – –

03/31/2005 0938 – – – – – – – – – – –

04/20/2005 1108 – – – – – – – – – – –

05/11/2005 1328 – – – – – – – – – – –

05/19/2005 1258 – – – – – – – – – – –

05/26/2005 1238 – – – – – – – – – – –

06/08/2005 1008 – – – – 0.148 – 0.090 – – – –

06/09/2005 0938 – – – – – – – – – – –

06/13/2005 1238 – – – – – – – – – – –

06/14/2005 1408 – – – – – – – – – – –
Appendix 85

Table A2. Volatile organic compounds (VOCs) detected in field blanks, California GAMA Priority Basin Project, May 2004 through September 2010.—Continued[See table 1 for study unit names. Concentrations are reported here as unrounded values; data for these samples are reported as rounded values in the Data Series reports. Abbreviations: SSB, source-solution blank; μg/L, micrograms per liter; –, not detected]

Collection 

date

Collection 

time

Solvents Other VOCs

Acetone 

(μg/L)

2-Butanone 

(μg/L)

1,1-Dichloroethene

(μg/L)

Dichloromethane

(μg/L)

Tetrachloroethene

(μg/L)

Tetrahydrofuran

(μg/L)

Trichloroethene

(μg/L)

Bromodichloromethane

(μg/L)

Carbon 

disulfide 

(μg/L)

Chloroform 

(μg/L)

Trichlorofluoromethane

(μg/L)

06/22/2005 0948 – – – – – – – – – – –

07/11/2005 1438 – – – – – – – – – – –

07/19/2005 0908 – – – – – – – – – – –

07/25/2005 1128 – – – – – – – – – – –

08/02/2005 1218 – – – – – – – – – – –

08/03/2005 0908 – – – – – – – – – – –

08/09/2005 1008 – – – – 0.027 – – – – – –

08/10/2005 1208 – – – – – – – – – – –

08/30/2005 1138 – – – – – – – – – – 0.100

09/01/2005 1008 – 1.342 – – – – – – – – –

09/15/2005 0848 – – – – – – – – – – –

09/19/2005 1148 – – – – – – – – – – –

09/21/2005 1108 11.59 30.79 – – – – – – – 0.104 –

10/17/2005 1338 – – – – – – – – – 0.038 –

10/18/2005 0808 – – – – – – – – – – –

10/25/2005 0928 – – – – – – – – – – –

10/26/2005 1308 – – – – – – – – – – –

10/31/2005 1038 26.68 3.327 – – 0.026 – 0.021 – – 0.014 –

11/15/2005 1108 – – – – – – – – – – –

11/16/2005 1038 – – – – – – – – – – –

11/30/2005 0928 – – – – – – – – – – –

11/30/2005 1208 – – – – – – – – – – –

12/07/2005 1128 – – – – – – – – – – –

12/13/2006 0908 – 1.405 – – – – – – – – –

01/10/2006 1008 10.8 – – – – – 0.011 – – – –

01/11/2006 1408 – 3.488 – – – – – – – – –

01/24/2006 1248 – – – – – – – – – – –

02/08/2006 1208 – – – – – – – – – – –

02/09/2006 0908 – – – 0.028 – – – – – – –

03/14/2006 0908 – – – – – – – – – 0.054 –

03/14/2006 9038 29.1 123.7 – – – 3.006 – – – – –

03/29/2006 0938 – 4.029 – – – – – – – – –

04/04/2006 1028 – – – – – – – – – – –

04/20/2006 0938 – – – – – – – – – – –
86 VOC Blank Data and Study Reporting Levels, California GAMA PBP, 2004–2010 Table A2.

Volatile organic compounds (VOCs) detected in field blanks, California GAMA Priority Basin Project, May 2004 through September 2010.—Continued

[See table 1 for study unit names. Concentrations are reported here as unrounded values; data for these samples are reported as rounded values in the Data Series reports. Abbreviations: SSB, source-solution blank; μg/L, micrograms per liter; –, not detected]

Collection 

date

Collection 

time

Solvents Other VOCs

Acetone 

(μg/L)

2-Butanone 

(μg/L)

1,1-Dichloroethene

(μg/L)

Dichloromethane

(μg/L)

Tetrachloroethene

(μg/L)

Tetrahydrofuran

(μg/L)

Trichloroethene

(μg/L)

Bromodichloromethane

(μg/L)

Carbon 

disulfide 

(μg/L)

Chloroform 

(μg/L)

Trichlorofluoromethane

(μg/L)

05/01/2006 1228 – – – – – – – – – – –

05/09/2006 0608 – 2.402 – 0.157 – – – – – – –

05/10/2006 1008 – – – – – – – – – – –

05/24/2006 1208 – – – – – – – – – – –

05/25/2006 1208 – – – – – – – – – – –

06/06/2006 0808 – – – – – – – – – – –

06/06/2006 0928 – – – – – – – – – – –

06/14/2006 0848 – – – – – – – – – – –

06/15/2006 1008 – – – – – – – – – – –

06/19/2006 0928 – – – – – – – – – – –

06/22/2006 0958 – – – – – – – – – – –

07/10/2006 1038 – – – – – – – – – – –

07/11/2006 0938 – – – – – – – – – – –

07/17/2006 1308 – – – – – – – – – – –

07/17/2006 1528 – – – – – – – – – – –

07/20/2006 0908 10.58 1.363 – – – – – – – – –

07/24/2006 1158 – – – – – – – – – – –

07/25/2006 1538 – – – – – – – – – – –

08/03/2006 0938 3.045 – – 0.062 – – – – – 0.035 –

08/07/2006 1008 – – – – – – – – – – –

08/08/2006 0848 7.544 5.862 – – – – – – – – –

08/14/2006 1258 – – – – – – – – – – –

08/15/2006 0948 – – – – – – – – – – –

08/21/2006 0958 – – – – – – – – – – –

08/21/2006 1038 – – – – – – – – – – –

08/28/2006 0958 2.911 – – 0.049 – – – 0.106 – 0.194 –

09/11/2006 1248 – – – – – – – – – – –

09/13/2006 0828 – – – – – – – – – – –

09/21/2006 0948 – – – – – – – – – – –

10/03/2006 1248 – – – – – – – – – – –

10/05/2006 1008 – – – – – – – – – – –

10/24/2006 1008 – – – – – – – – – 0.051 –

11/13/2006 1328 – – – – – – – – – – –

11/15/2006 0938 – – – – – – – – – – –
Appendix 87

Table A2. Volatile organic compounds (VOCs) detected in field blanks, California GAMA Priority Basin Project, May 2004 through September 2010.—Continued[See table 1 for study unit names. Concentrations are reported here as unrounded values; data for these samples are reported as rounded values in the Data Series reports. Abbreviations: SSB, source-solution blank; μg/L, micrograms per liter; –, not detected]

Collection 

date

Collection 

time

Solvents Other VOCs

Acetone 

(μg/L)

2-Butanone 

(μg/L)

1,1-Dichloroethene

(μg/L)

Dichloromethane

(μg/L)

Tetrachloroethene

(μg/L)

Tetrahydrofuran

(μg/L)

Trichloroethene

(μg/L)

Bromodichloromethane

(μg/L)

Carbon 

disulfide 

(μg/L)

Chloroform 

(μg/L)

Trichlorofluoromethane

(μg/L)

11/28/2006 1428 – – – – – – – – – – –

11/29/2006 0908 – – – – – – – – – – –

12/05/2006 0938 3.696 12.61 – – – – – – – – –

01/23/2007 1218 – – – – – – – – – – –

01/30/2007 1328 – – – – – – – – – – –

02/07/2007 0848 – – – – – – – – – – –

02/08/2007 1208 – – – – – – – – – – –

02/14/2007 1218 – – – – – – – – – – –

02/28/2007 0938 – – – – – – – – – – –

03/05/2007 1208 – – – – – – – – – – –

03/22/2007 1008 – – – – – – – – – – –

04/02/2007 0938 – – – – – – – – – – –

04/02/2007 0948 – 0.922 – – – – – – – – –

04/16/2007 0938 – – – – – – – – – – –

04/17/2007 0858 – – – – – – – – – – –

04/23/2007 0938 – – – – – – – – – – –

04/23/2007 1038 – – – – – – – – – – –

04/30/2007 1258 – – – – – – – – – – –

05/07/2007 1458 – – – – – – – – – – –

05/08/2007 0928 – – – – – – – – – – –

05/21/2007 0908 – – – – – – – – – – –

05/21/2007 1058 – – – – – – – – – – –

06/13/2007 0918 – 8.581 – – – – – – 0.043 – –

06/19/2007 0908 – – – – – – – – – – –

06/20/2007 1338 – – – – – – – – – – –

06/25/2007 1018 – 4.099 – – – – – – – – –

07/12/2007 0958 – – – – – – – – – – –

07/25/2007 0838 – – – – – – – – – – –

08/01/2007 0858 – – – – – – – – – – –

08/01/2007 0908 – – – – – – – – – – –

08/27/2007 1008 – – – – – – – – – – –

08/27/2007 1038 – – – – – – – – – – –

09/13/2007 0738 – – – – – – – – – – –

10/02/2007 0848 – – – – – – – – – – –

10/03/2007 1038 – – – – – – – – – – –
88 VOC Blank Data and Study Reporting Levels, California GAMA PBP, 2004–2010 Table A2.

Volatile organic compounds (VOCs) detected in field blanks, California GAMA Priority Basin Project, May 2004 through September 2010.—Continued

[See table 1 for study unit names. Concentrations are reported here as unrounded values; data for these samples are reported as rounded values in the Data Series reports. Abbreviations: SSB, source-solution blank; μg/L, micrograms per liter; –, not detected]

Collection 

date

Collection 

time

Solvents Other VOCs

Acetone 

(μg/L)

2-Butanone 

(μg/L)

1,1-Dichloroethene

(μg/L)

Dichloromethane

(μg/L)

Tetrachloroethene

(μg/L)

Tetrahydrofuran

(μg/L)

Trichloroethene

(μg/L)

Bromodichloromethane

(μg/L)

Carbon 

disulfide 

(μg/L)

Chloroform 

(μg/L)

Trichlorofluoromethane

(μg/L)

10/29/2007 0928 – – – – – – – – – – –

11/16/2007 1038 – – – – – – – – – – –

11/28/2007 1008 – – – – – – – – – – –

11/29/2007 1228 – – – – – – – – – – –

12/10/2007 1028 – – – – – – – – – – –

12/11/2007 0858 – – – – – – – – – – –

01/09/2008 0908 1.938 – – – – – – – – – –

01/09/2008 1008 – – – – – – – – – – –

01/16/2008 0858 3.744 – – – – – – – – – –

01/28/2008 0848 1.319 0.471 – – – – – – – – –

01/28/2008 1418 1.003 – – – – – – – – – –

02/05/2008 0938 – – – – – – – – – – –

02/07/2008 0918 0.999 0.612 – – – – – – – – –

02/12/2008 1228 – – – – – – – – – – –

02/13/2008 1148 – – – – – – – – – – –

02/26/2008 1018 – – – – – – – – – – –

03/04/2008 0958 – – – – – – – – – – –

03/05/2008 0908 – – – – – – – – – – –

03/18/2008 1318 – – – – – – – – – – –

03/31/2008 1008 – – – – – – – – – – –

04/03/2008 1028 – – – – – – – – – – –

04/10/2008 1038 – – – – – – – – – – –

04/16/2008 1028 – – – – – – – – – – –

04/21/2008 1108 – – – – – – – – – – –

04/28/2008 1308 – – – – – – – – – – –

05/05/2008 0908 – – – – – – – – – – –

05/21/2008 1438 – – – – – – – – – – –

06/05/2008 0928 – – – – – – – – – – –

06/11/2008 0908 – – – – – – – – – – –

06/18/2008 1338 – – – – – – – – – – –

06/23/2008 1138 – – – – – – – – – – –

06/23/2008 1318 – – – – – – – – – – –

07/10/2008 0948 – 0.827 – – – – – – – – –

07/16/2008 0938 – – – – – – – – – – –

07/23/2008 1028 – – – – – – – – – – –
Appendix 89

Table A2. Volatile organic compounds (VOCs) detected in field blanks, California GAMA Priority Basin Project, May 2004 through September 2010.—Continued[See table 1 for study unit names. Concentrations are reported here as unrounded values; data for these samples are reported as rounded values in the Data Series reports. Abbreviations: SSB, source-solution blank; μg/L, micrograms per liter; –, not detected]

Collection 

date

Collection 

time

Solvents Other VOCs

Acetone 

(μg/L)

2-Butanone 

(μg/L)

1,1-Dichloroethene

(μg/L)

Dichloromethane

(μg/L)

Tetrachloroethene

(μg/L)

Tetrahydrofuran

(μg/L)

Trichloroethene

(μg/L)

Bromodichloromethane

(μg/L)

Carbon 

disulfide 

(μg/L)

Chloroform 

(μg/L)

Trichlorofluoromethane

(μg/L)

07/29/2008 1038 – – – – – – – – – – –

08/06/2008 0928 – – – – – – – – – – –

08/07/2008 0848 – – – – – – – – – – –

08/11/2008 0838 – – – – – – – – – – –

08/18/2008 0848 – – – – – – – – – – –

08/25/2008 0918 – – – – – – – – – – –

08/26/2008 1128 – – – – – – – – – – –

09/15/2008 1048 – – – – – – – – – – –

09/17/2008 1008 – – – – – – – – – – –

09/22/2008 0948 – – – – – – – – – – –

10/09/2008 1048 – – – – – – – – – – –

10/22/2008 1448 – – – – – – – – – – –

10/29/2008 1108 – – – – – – – – – 0.024 –

12/02/2008 0908 – – – – – – – – – – –

12/11/2008 1018 – – – – – – – – – – –

12/16/2008 0908 – – – – – – – – – – –

06/01/2009 1048 – – – – – – – – – – –

06/24/2009 0938 – – – – – – – – – – –

07/14/2009 0948 – – – – – – – – – 0.016 –

07/29/2009 1108 – – – – – – – – – – –

08/17/2009 1008 – – – – – – – – 0.056 – –

10/05/2009 1058 – – – – – – – – – – –

10/20 /2009 1218 – – – – 0.021 – – – – – –

12/08/2009 1418 – – – – – – – – – – –

03/03/2010 1028 – – – – – – – – – – –

03/17/2010 1208 – – – – – – – – – – –

04/06/2010 1048 – – – – – – – – – – –

04/14/2010 0808 – – – – – – – – – – –

05/18/2010 1208 0.327 – – – – – – – – – –

06/07/2010 0908 – – – – – – – – – – –

06/15/2010 1008 – – – – – – – – 0.056 – –
90 VOC Blank Data and Study Reporting Levels, California GAMA PBP, 2004–2010 Table A2.

Volatile organic compounds (VOCs) detected in field blanks, California GAMA Priority Basin Project, May 2004 through September 2010.—Continued

[See table 1 for study unit names. Concentrations are reported here as unrounded values; data for these samples are reported as rounded values in the Data Series reports. Abbreviations: SSB, source-solution blank; μg/L, micrograms per liter; –, not detected]

Collection 

date

Collection 

time

Solvents Other VOCs

Acetone 

(μg/L)

2-Butanone 

(μg/L)

1,1-Dichloroethene

(μg/L)

Dichloromethane

(μg/L)

Tetrachloroethene

(μg/L)

Tetrahydrofuran

(μg/L)

Trichloroethene

(μg/L)

Bromodichloromethane

(μg/L)

Carbon 

disulfide 

(μg/L)

Chloroform 

(μg/L)

Trichlorofluoromethane

(μg/L)

06/22/2010 1538 – – – – – – – – – – –

07/14/2010 0908 – – – – – – – – – – –

07/21/2010 0908 – – – – – – – – – – –

07/28/2010 0908 – – – – – – – – – – –

08/05/2010 1548 – – – – – – – – 0.092 – –

08/10/2010 1028 – – – – – – – – – – –

08/24/2010 0918 – – – – – – – – – – –

08/31/2010 0928 – – – – – – – – 0.060 – –
Appendix 91

Table A3. Volatile organic compounds (VOCs) detected in source-solution blanks, California GAMA Priority Basin Project, May 2004 through September 2010.[Unrounded data are reported. Abbreviations: μg/L microgram per liter. See table 1 for study unit names; –, not detected]

Collection 

date

Collection 

time

Study 

unit

Hydrocarbons Solvents Other VOCs

Benzene 

(μg/L)

Ethylbenzene

(μg/L)

Styrene 

(μg/L)

1,2,4-

Trimethylbenzene 

(μg/L)

Toluene 

(μg/L)

m- and 

p-Xylenes 

(μg/L)

o-Xylene 

(μg/L)

Acetone 

(μg/L)

2-Butanone 

(μg/L)

1,1-Dichloroethene 

(μg/L)

Dichloromethane 

(μg/L)

Tetrachloroethene 

(μg/L)

Tetrahydrofuran 

(μg/L)

Trichloroethene 

(μg/L)

Bromodichloromethane 

(μg/L)

Carbon 

disulfide 

(μg/L)

Chloroform 

(μg/L)

Trichlorofluoromethane

(μg/L)

05/20/2004 1049 S5 – – – – 0.011 – – – – – – – – – – – – –

05/24/2004 1159 S5 – – – – 0.024 – – 2.842 – – – – – – – – – –

07/01/2004 1007 S5 – – – – 0.025 – – – – – – – – – – – 0.121 –

07/01/2004 1009 S5 – – – – – – – – – – – – – – – – – –

07/12/2004 1629 S5 – – – – – – – – – – – – – – – – – –

09/20/2004 1007 N3 – – – – 0.010 – – – – – – – – – – – – –

10/04/2004 1047 N3 – – – 0.086 0.020 – – 2.744 – – – – – – – – – –

11/02/2004 1037 N3 – – – – 0.033 0.038 – – – – – – – – – 0.044 – –

01/04/2004 1227 V4 – – – – 0.016 – – – – – – – – – – – – –

01/04/2004 1307 V4 – – – – 0.022 0.020 – – – – – – – – – – – –

01/10/2004 1007 V4 – – – – 0.026 – – – – – – – – – – – – –

03/22/2004 0937 V3 – 0.023 – 0.059 0.047 0.085 0.037 – – – – – – – – – – –

03/23/2004 0937 V3 – – – – 0.011 – – – – – – – – – – – – –

03/29/2004 1107 V3 – – – 0.029 – – – – – – – – – – – – – –

03/31/2004 0937 V3 – – – – – – – – – – – – – – – – – –

05/26/2005 1237 V3 – – – – 0.024 0.027 – 1.216 – – – – – – – – – –

06/08/2005 1007 S3 – 0.039 – – 0.041 0.176 0.080 – – – – – – – – – – –06/09/2005 0937 S3 – – – – 0.012 – – – – – – – – – – – – –06/13/2005 1237 V3 – – – – – – – – – – – – – – – – – –06/22/2005 0947 S3 – – – – – – – – – – – – – – – – – –

07/11/2005 1437 S3 – – – – 0.013 – – – – – – – – – – 0.033 – –

07/19/2005 0907 N6 – – – – 0.012 – – – – – – – – – – – – –

07/25/2005 1127 N6 – – – – – – – – – – – – – – – – – –

08/02/2005 1217 N6 – – – – – – – – – – – – – – – – – –

08/03/2005 0907 N6 – – – – 0.026 – – – – – – – – – – – – –

08/09/2005 1007 N6 – – – – 0.026 – – – – – – – – – – – – –

08/10/2005 1207 N6 – – – – 0.018 – – – – – – – – – – 0.089 – –

08/30/2005 1137 N6 – – – – – – – – – – – – – – – – – 0.112

09/01/2005 1007 N6 – – – – 0.012 – – – – – – – – – – 0.014 – –

09/21/2005 1107 N6 – – – – – – – – – – – – – – – – – –

10/17/2005 1337 V7 – – – – – – – – – – – – – – – – – –10/18/2005 0807 V7 – – – – – – – – – – – – – – – – – –10/26/2005 1307 V7 – – – – – – – – – – – – – – – – – –10/31/2005 1037 V7 – – – – – – – – – – – – – – – – – –

11/16/2005 1037 V7 – – – – – – – – – – – – – – – – – –

12/13/2005 0907 V7 – – – – 0.022 – – – – – – – – – – – – –
92 VOC Blank Data and Study Reporting Levels, California GAMA PBP, 2004–2010 Table A3.

Volatile organic compounds (VOCs) detected in source/solution blanks, California GAMA Priority Basin Project, May 2004 through September 2010.—Continued

[Unrounded data are reported. Abbreviations: μg/L microgram per liter. See table 1 for study unit names; –, not detected]

Collection 

date

Collection 

time

Study 

unit

Hydrocarbons Solvents Other VOCs

Benzene 

(μg/L)

Ethylbenzene

(μg/L)

Styrene 

(μg/L)

1,2,4-

Trimethylbenzene 

(μg/L)

Toluene 

(μg/L)

m- and 

p-Xylenes 

(μg/L)

o-Xylene 

(μg/L)

Acetone 

(μg/L)

2-Butanone 

(μg/L)

1,1-Dichloroethene 

(μg/L)

Dichloromethane 

(μg/L)

Tetrachloroethene 

(μg/L)

Tetrahydrofuran 

(μg/L)

Trichloroethene 

(μg/L)

Bromodichloromethane 

(μg/L)

Carbon 

disulfide 

(μg/L)

Chloroform 

(μg/L)

Trichlorofluoromethane

(μg/L)

01/10/2006 1007 V8 – – – – – – – – – – – – – – – – – –

01/11/2006 1407 V8 – – – – – – – – – – – – – – – – – –

01/24/2006 1247 V8 – – – – 0.011 – – – – – – – – – – – – –

02/08/2006 1207 V8 – – – – 0.038 – – – – – – – – – – – – –

02/09/2006 0907 V8 – – – – – – – – – – – – – – – – – –

03/14/2006 0907 V5 – – – – 0.01 – – – – – – – – – – – – –

03/14/2006 0937 V5 – – – – 0.015 – – – – – – – – – – – – –

03/29/2006 0937 V5 – – – – – – – – – – – – – – – – – –

04/04/2006 1027 V5 – – – – – – – – – – – – – – – – – –

05/09/2006 0607 M4 – – – – – – – – – – – – – – – – – –

05/24/2006 1207 M4 – – – – – – – – – – – – – – – – – –

05/25/2006 1207 M4 – – – – 0.018 – – – – – – – – – – – – –

06/06/2006 0807 M3 – – – – – – – – – – – – – – – – – –

06/06/2006 0927 M3 – – – – – – – – – – – – – – – – – –

06/14/2006 0847 M3 – – – – – – – – – – – – – – – – – –

07/17/2006 1307 V2 – – – – – – – – – – – – – – – – – –07/20/2006 0907 V2 – – – – 0.014 – – – – – – – – – – – – –07/25/2006 1537 V2 – – – – – – – – – – – – – – – – – –08/03/2006 0937 V2 – – – – 0.018 – – – – – – – – – – – – –08/07/2006 1007 S2 – – – – 0.014 – – – – – – – – – – – – –08/08/2006 0847 V2 – – – – 0.011 – – – – – – – – – – – – –

08/14/2006 1247 V2 – – – 0.040 – – – – – – – – – – – – – –

08/15/2006 0947 V2 – – – – – – – – – – – – – – – – – –

08/28/2006 0957 S2 – – – – – – – – – – – – – – – – – –

09/11/2006 1247 S2 – – – – – – – – – – – – – – – – – –

09/21/2006 0947 M2 – – – – – – – – – – – – – – – – – –

10/24/2006 1007 M2 – – – – – – – – – – – – – – – – – –

11/13/2006 1327 S2 – – – – 0.017 – – – – – – – – – – – – –

11/15/2006 0937 S2 – – – – – – – – – – – – – – – – – –11/28/2006 1427 S4 – – – – 0.034 – – – – – – – – – – – – –11/29/2006 0907 S4 – – – – – – – – – – – – – – – – – –

12/05/2006 0937 S4 – – – – – – – – – – – – – – – – – –

01/30/2007 1327 S4 – – – – – – – – – – – – – – – – – –02/07/2007 0847 S4 – – – – 0.019 – – – – – – – – – – – – –

02/28/2007 0937 D3 – – – – 0.010 0.009 – – – – – – – – – – – –03/05/2007 1207 D3 – – – – 0.012 – – – – – – – – – – – – –
Appendix 93

Table A3. Volatile organic compounds (VOCs) detected in source/solution blanks, California GAMA Priority Basin Project, May 2004 through September 2010.—Continued[Unrounded data are reported. Abbreviations: μg/L microgram per liter. See table 1 for study unit names; –, not detected]

Collection 

date

Collection 

time

Study 

unit

Hydrocarbons Solvents Other VOCs

Benzene 

(μg/L)

Ethylbenzene

(μg/L)

Styrene 

(μg/L)

1,2,4-

Trimethylbenzene 

(μg/L)

Toluene 

(μg/L)

m- and 

p-Xylenes 

(μg/L)

o-Xylene 

(μg/L)

Acetone 

(μg/L)

2-Butanone 

(μg/L)

1,1-Dichloroethene 

(μg/L)

Dichloromethane 

(μg/L)

Tetrachloroethene 

(μg/L)

Tetrahydrofuran 

(μg/L)

Trichloroethene 

(μg/L)

Bromodichloromethane 

(μg/L)

Carbon 

disulfide 

(μg/L)

Chloroform 

(μg/L)

Trichlorofluoromethane

(μg/L)

03/22/2007 1007 D3 – – – – 0.330 0.022 – – – – – – – – – – – –

04/02/2007 0947 S1 – – – – – – – – – – – – – – – – – –

04/16/2007 0937 S1 – – – – – – – – – – – – – – – – – –

04/17/2007 0857 S1 – – – – – – – – – – – – – – – – – –

04/23/2007 1037 N4 – – – – 0.018 – – – – – – – – – – – – –

05/07/2007 1457 S1 – – – – 0.025 – – – – – – – – – – – – –

05/08/2007 0927 N4 – – – – – – – – – – – – – – – – – –

05/21/2007 1057 N4 – – – – – – – – – – – – – – – – – –

06/13/2007 0917 N4 – – – – – – – – – – – – – – – – – –

06/19/2007 0907 N4 – – – – – – – – – – – – – – – – – –

06/25/2007 1017 M5 – – – – – – – – – – – – – – – – – –

08/27/2007 1007 M5 – – – – – – – – – – – – – – – – – –

09/13/2007 0737 M5 – – – 0.030 – – – – – – – – – – – – – –

11/16/2007 1037 N3 – – – – – – – – – – – – – – – – – –

01/09/2008 0907 V1 – – – – – – – 1.458 – – – – – – – – – –

01/09/2008 1007 V1 – – – – – – – – – – – – – – – – – –01/16/2008 0857 V1 – – – – – – – – – – – – – – – – – –01/28/2008 0847 D1 – – – – 0.017 – – 1.34 0.536 – – – – – – – – –01/28/2008 1417 D1 – – – – 0.022 – – 1.216 – – – – – – – – – –

02/07/2008 0917 D1 – – – – 0.038 – – – – – 0.182 – – – – – – –02/13/2008 1147 D1 – – – – 0.016 – – – – – – – – – – – – –

02/26/2008 1017 D1 – – – – 0.018 – – – – – – – – – – – – –

04/10/2008 1037 D1 – – – – 0.068 – – – – – – – – – – – – –

06/11/2008 0907 N7 – – – – – – – – – – – – – – – – – –

06/18/2008 1337 N7 – – – – – – – – – – – – – – – – – –

07/10/2008 0947 N7 – – – – – – – – – – – – – – – – – –

07/16/2008 0937 N7 – – – – – – – – – 0.026 – – – – – – – –

06/01/2009 1047 N2 – – – – – – – – – – – – – – – – – –

06/24/2009 0937 N2 – – – – – – – – – – – – – – – – – –07/14/2009 0947 N2 – – – 0.047 – – – – – – – – – – – – – –07/29/2009 1107 N1 – – – – – – – – – – – – – – – – – –

08/17/2009 1007 N1 – – – – – – – – – – – – – – – – – –

10/05/2009 1057 N1 – – – 0.016 – – – – – – – – – – – – – –

03/03/2010 1027 V9 – – – – 0.015 – – – – – – – – – – – – –

03/17 2010 1207 V9 – – – – – – – – – – – – – – – – – –06/22 2010 1537 V9 – – – – – – – – – – – – – – – – – –07/14 2010 0907 M6 – – – – – – – – – – – – – – – – – –
94 VOC Blank Data and Study Reporting Levels, California GAMA PBP, 2004–2010

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