Rock-Bound Arsenic Influences Ground Water and 

Sediment Chemistry Throughout New England 

By Gilpin R. Robinson, Jr., and Joseph D. Ayotte 

Open-File Report 2007–1119 

U.S. Department of the Interior 

U.S. Geological Survey 


 
U.S. Department of the Interior 

DIRK KEMPTHORNE, Secretary 

U.S. Geological Survey 

Mark D. Myers, Director 

U.S. Geological Survey, Reston, Virginia 2007 

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Robinson, G.R., Jr. and Ayotte, J. D., 2007, Rock-Bound Arsenic Influences Ground Water and Sediment 


Chemistry Throughout New England: U. S. Geological Survey Open-File Report 2007-1119, 16 p. 


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2
 
Contents 

Abstract................................................................................................................................................................................5
 

Introduction .........................................................................................................................................................................5
 

Geochemical Pathways.................................................................................................................................................5
 

Data and Discussion..........................................................................................................................................................6
 

Arsenic Sources in New England................................................................................................................................6
 

Geochemistry and Geology Datasets .........................................................................................................................8
 

Arsenic Statistics..........................................................................................................................................................10
 

Data Analysis Methods and Results .............................................................................................................................10
 

Contingency Table Data Analysis..............................................................................................................................10
 

Correlation Measures and Statistics ........................................................................................................................11
 

Correlation Results .......................................................................................................................................................14
 

Correlation of wells, split into high and low categories, relative to stream sediment data........................14
 

Spatial Model of Arsenic Variability in Bedrock Ground Water..........................................................................15
 

Conclusions .......................................................................................................................................................................16
 

Stream Sediment Chemistry .......................................................................................................................................17
 

Bedrock Ground Water Chemistry ............................................................................................................................17
 

References Cited ..............................................................................................................................................................17
 

Figures 

Figure 1. Geochemical pathways involve source factors, process factors that act on sources, and 


transport factors that collectively influence chemical concentrations in sediment, water, and biological 


receptors..............................................................................................................................................................................6 


Figure 2. Agricultural lands that used arsenical pesticides and herbicides in New England............................7
 

Figure 3. Arsenic geochemistry datasets for rock, stream sediment and bedrock well water samples.. .......8
 

Figure 4. Generalized lithology of bedrock geologic units in New England. ..........................................................9 


Figure 5. Box plots and summary statistics for arsenic concentrations in rock, stream sediment (Sseds), 


Figure 7. Plot of log-transformed Odds ratio defined by high-As and low-As classified well variables, on 


Figure 8. Predicted probability of arsenic concentrations > 5 μg/L in ground water wells in bedrock 


and well water samples. .......................................................................................................................................... .....10
 

Figure 6. Box plots and summary statistics for rock arsenic data grouped by lithology....................................11
 

an area basis, versus classes of increasing stream sediment chemistry.............................................................15
 

aquifers (Ayotte and others, 2006).................................................................................................................................16 


Tables 

Table 1. Contingency table for an example testing association between well classification based on 


arsenic chemistry and an area classification based on an independent variable. .............................................12
 

3
 
Table 2. Summary of ranked Cochran-Mantel-Haenszel statistics for rock (Rocks), stream sediment 

(Sseds), and groundwater well (wells) sample populations evaluated relative to grouped geologic 

bedrock map unit (Geology), agricultural index (AGI), stream sediment arsenic interpolation grid (SSgrid), 

and groundwater well arsenic interpolation grid (Wells) variables. ......................................................................13 

4
 
Rock-Bound Arsenic Influences Ground Water and Sediment Chemistry 

Throughout New England 

By Gilpin R. Robinson, Jr., and Joseph D. Ayotte 

Abstract 

The information in this report was presented at the Northeastern Region Geological Society of 

America meeting held March 11-14, 2007, in Durham, New Hampshire. 

In the New England crystalline bedrock aquifer, concentrations of arsenic that exceed the 

drinking water standard of 10 μg/L occur most frequently in ground water from wells sited in specific 

metamorphic and igneous rock units. Geochemical investigations indicate that these geologic units 

typically have moderately elevated whole-rock concentrations of arsenic compared to other rocks in the 

region. The distribution of ground water wells with As > 5 μg/L has a strong spatial correlation with 

specific bedrock units where average whole-rock concentrations of arsenic exceed 1.1 mg/kg and where 

geologic and geochemical factors produce high pH ground water. Arsenic concentrations in stream 

sediments collected from small drainages reflect the regional distribution of this natural arsenic source 

and have a strong correlation with both rock chemistry and the distribution of bedrock units with 

elevated arsenic chemistry. The distribution of ground water wells with As > 5 μg/L has a strong spatial 

correlation with the distribution of stream sediments where concentrations of arsenic exceed 6 mg/kg. 

Stream sediment chemistry also has a weak correlation with the distribution of agricultural lands where 

arsenical pesticides were used on apple, blueberry, and potato crops. Elevated arsenic concentrations in 

bedrock wells, however, do not correlate with agricultural areas where arsenical pesticides were used. 

These results indicate that both stream sediment chemistry and the solubility and mobility of arsenic in 

ground water in bedrock are influenced by host-rock arsenic concentrations. Stream sediment chemistry 

and the distribution of geologic units have been found to be useful parameters to predict the areas of 

greatest concern for elevated arsenic in ground water and to estimate the likely levels of human 

exposure to elevated arsenic in drinking water in New England. However, the extreme local variability 

of arsenic concentrations in ground water from these rock sources indicate that arsenic concentrations in 

ground water are affected by other factors in addition to arsenic concentrations in rock. 

Introduction 

Geochemical Pathways 

Geochemical pathways involve source factors, process factors that act on sources, and transport 

factors that collectively influence concentrations in soils, sediments, and waters (Figure 1). 

The solubility and mobility of arsenic in ground water are influenced by a variety of processes 

that often vary locally in bedrock aquifers. Important processes influencing As hydrogeochemistry 

include 1) oxidation-reduction of sulfides or organic matter that may contain arsenic, 2) desorption or 

dissolution of ferromanganese hydroxyoxide fracture and grain coatings that may sorb arsenic, and 3) 

biological transformations involving arsenic (Welch and others, 2000). 

5
 
Source Process Fate

Weathering 

Dissolution 

Sorption 

Redox 

Anthropogenic ---------------------- 

Natural Water 

Sediment 

Air 

Rocks / Minerals Eh , pH 

Mineral Deposits Complexing Agents 

Pesticides / Herbicides Mineral Hosts / Buffers 

Sediment / Dust Ion Competition 

Transport Biology 

Water 

Sediment 

Figure 1. Geochemical pathways involve source factors, process factors that act on sources, and 

transport factors that collectively influence chemical concentrations in sediment, water, and biological 

receptors.

 This study uses data on ground water chemistry and arsenic sources to evaluate the regional 

influence of these sources on arsenic concentrations in ground water in crystalline bedrock and in 

stream sediments. The relative influence of arsenic source factors on arsenic concentrations in ground 

water is uncertain. We address this uncertainty by measuring the probability that ground water As 

concentrations > 5 μg/L vary as a function of As source concentrations while controlling for other 

source and landscape factors. If the correlation measures are positive and significant, we conclude that 

source type concentrations have influence; if not, process and transport factors likely dominate source 

factors. Comparison of the correlation measures indicate which sources have the strongest influence on 

water and sediment chemistry and whether the source variable effects are independent of each other. 

Data and Discussion 

Arsenic Sources in New England 

Sources of arsenic that might influence water chemistry in New England aquifers include 1) 

rocks and mineral deposits, 2) soils and sediments derived from weathering of rocks and 3) 

anthropogenic sources related to past arsenical pesticide use, industrial contamination, and/or 

atmospheric deposition of high-As ash from coal combustion. 

Robinson and Ayotte (2006) concluded that the most significant anthropogenic source of arsenic 

in the region is from cumulative applications of arsenical pesticides and herbicides that were used in 

New England from about 1900 to 1970. 

Widespread use of arsenical agricultural compounds occurred during the 1920s to 1950s on 

agricultural lands containing apple, blueberry, and potato crops. Lead arsenate was the most extensively 

used arsenical pesticide (Peryea, 1998), particularly in apple orchards. Other metal-bearing pesticides 

and herbicides, such as copper acetoarsenite (Paris Green), calcium arsenate and sodium arsenate, were 

used to a lesser degree. 

6
 
The application of arsenical pesticides in New England predates systematic record-keeping and 

the exact locations and amounts of pesticide applications are unknown. However, it is estimated, based 

on cultivation practices and history, that cumulative application rates of arsenic could have been 200 lbs 

of elemental arsenic per acre of cultivation (as reported by D’Angelo et al, 1996), equivalent to 22 g/m2 

As. On an area basis, the cumulate application rates for arsenic pesticides applied to apple, blueberry, 

and potato crops are estimated to be comparable (D’Angelo et al., 1996). 

Cultivation data for these crops during this time period (U.S. Department of Agriculture, 1935­

1997) indicate where arsenical pesticides and herbicides were used most extensively in the region. 

The cultivation data for crops receiving arsenical pesticide applications from the 1930s to 1970s 

has been generalized at census tract level to develop an Agricultural Index (AGI; Figure 2) related to 

arsenical pesticide use. The AGI is used as a proxy for the intensity of arsenical pesticide application in 

the region. 

Figure 2. Agricultural lands that used arsenical pesticides and herbicides in New England. The 

agricultural index value (AGI) portrays the average cultivation rate of apples, blueberries, and potatoes, 

in units of acres of cultivation per square mile of census tract area, based on agricultural census data 

from 1935 to 1977 (US Department of Agriculture). 

7
 
Geochemistry and Geology Datasets 

Rock chemistry data were restricted to representative rock samples taken from outcrop settings 

where the rock type is identified. The distribution of rock samples cluster along southwest-northeasttrending transects from 1) southern Connecticut to northern Vermont near the Vermont-New Hampshire 

border and 2) eastern Connecticut to coastal Maine. Other rock samples are scattered across Connecticut 

and Maine (Figure 3A). 

We analyzed 1,597 stream sediment samples collected from 1977 to 1980 by the National 

Uranium Resource Evaluation (NURE) Program for As (Figure 3B). The NURE program did not 

sample drainages in Maine north of 45o latitude. 

Arsenic data for 1,572 bedrock ground-water wells in New England were obtained from state 

records on public-water supply wells collected for compliance with the Safe Drinking Water Act during 

the years 1992 to 1999 (Figure 3C). The laboratory reporting level (detection limit) for As in the ground 

water samples used in this study was variable but no higher than 5 μg/L. 

The chemical data for stream sediments, rocks, and ground waters have been interpolated into 1 

km2

 cells so that spatial comparisons could be made. 

Figure 3. Arsenic geochemistry datasets for rock, stream sediment and bedrock well water samples. 

The symbol legend for the arsenic concentration data for each sample media is based on percentiles for 

the ranked arsenic concentrations. A: Rock chemistry sample locations in New England, showing 

arsenic concentration ranges. Symbol transitions occur at 0.5 (1.1 mg/Kg), 0.8 (6.5 mg/Kg), and 0.95 (25 

mg/Kg) percentile values. B: Stream sediment chemistry sample locations in New England, showing 

arsenic concentration ranges. Symbol transitions occur at 0.5 (2.8 mg/Kg) and 0.8 (7.3 mg/Kg) percentile 

values. C: Water chemistry sample locations from public-supply bedrock wells in New England. Symbol 

transitions occur at 0.5 (0.005 mg/L), 0.8 (0.01 mg/L), and 0.95 (0.02 mg/L) percentile values. 

8
 
Geologic data on dominant lithology and map unit characteristics were compiled from statewide 

maps of bedrock geology for the New England states. Over 1,200 individual map units are named and 

portrayed in these state bedrock geology maps. For analysis of differences in arsenic distributions, the 

bedrock map units were grouped into lithology and tectonostratigraphic setting categories using map 

unit descriptions and other geologic information provided with the geologic maps. Generalized lithology 

groups are in Figure 4. 

Figure 4. Generalized lithology of bedrock geologic units in New England. The rock types have been 

grouped into seven general categories based on map unit descriptions and depositional setting 

information summarized in Robinson and Kapo (2003). 

9
 
Box Plot 

Arsenic Concentration, ppm 

1000 

100 

10 

1 

.1 

.01 

Rock Stream Sediment 

Arsenic Statistics 

Concentrations of arsenic in rocks, stream sediments, and ground-water wells in bedrock vary by 

more than two orders of magnitude (Figure 5). The arsenic concentrations show a positively skewed 

distribution (note the log-transformed Y axis in Figure 5) with median values of 1.1 ppm (mg/Kg), 2.8 

ppm, <5 μg/L (ppb) for rocks, stream sediments, and ground water, respectively (Table 1). 

Arsenic 

Statistics 

Rocks 

(ppm) 

Sseds 

(ppm) 

Wells 

(μg/L) 

N 1279 1597 1572 

Mean 7.7 5.0 -----­

Median 1.1 2.8 <5.0 

80% 6.7 7.2 5.0 

90% 16.0 11.7 9.0 

Figure 5. Box plots and summary statistics for arsenic concentrations in rock, stream sediment (Sseds), 

and well water samples. N is the number of samples for each sample type. 

The distribution of arsenic concentrations in rocks, sorted by lithology, shows higher median and 

mean arsenic concentrations in felsic volcanics relative to granitic rocks and in calcareous 

metasedimentary and sulfide-rich metamorphic rocks relative to the other lithologic groups in the study 

area (Figure 6). 

Data Analysis Methods and Results 

Contingency Table Data Analysis 

Contingency tables are used to record and analyze the relationship between two or more 

variables. The table elements, Tij, are the counts of wells in each table category. (Table 1). 

10
 
1000 

100 

10 

1 

.1 

Rock As (ppm) 

275 

418 298 

124 29 

125 

Box Plot 

Split By: Lithology Group 

Felsic Volcanics 

Granite 

Mafic Rocks 

Metased-Calcareous 

Metased-Sulfidic 

Metased-Undivided 

Number of samples in 

group 

Units 

Lithology Felsic 

Volcanics 

Granite Mafic Rocks Metacalcareous Meta-sulfidic Metaundivided 

Mean 9.0 2.4 1.8 24.9 21.7 16.0 

Median 6.0 0.6 0.9 5.9 5.0 0.5 

Figure 6. Box plots and summary statistics for rock arsenic data grouped by lithology. Concentration 

units are in ppm. 

The odds ratio measures the discrimination of the relationship. It is the correct classification 

product divided by the incorrect classification product. 

Balanced accuracy measures the performance efficiency of a classification model based on the 

independent variable classes. It is an average of the correct classification fractions by classification 

categories. A balanced accuracy of 0.5 is no better than the accuracy expected by random selection. 

Correlation Measures and Statistics 

A stratified cross-tabulation contingency-table analysis approach is used to measure strength of 

the spatial associations between arsenic in rocks, sediments, and ground waters while controlling for the 

influence and covariance of geologic and agricultural As-pesticide variables. 

11
 
Table 1. Contingency table for an example testing association between well classification based on 

arsenic chemistry and an area classification based on an independent variable.[The table elements, Tij are 

the counts of wells in each table category.] 

Well Classification 

Row Totals 

>5 μg/L <=5 μg/L 

Area

Classification

High area T11 T12 T1* 

Low area T21 T22 T2* 

Column Totals T*1 T*2 T** 

The magnitude of the Mantel-Haenszel Case-control odds ratio, ORMH ,is a measure of the 

strength of association between the dependent Y and independent X variables, as adjusted for the 

influence of the control variables. An odds ratio of 1 indicates no effect, while a ratio greater than 1 

indicates that the independent variable category increases the odds of occurrence of high concentrations 

in the sample media. Odds ratios not significantly different from 1 at 95% confidence are shown in red. 

The data in Table 2 are grouped by dependent variable (Y var) and are listed in order of 

decreasing association strength (decreasing ORMH ) for each dependent variable group. 

The Breslow-Day statistic, p(BD), measures the probability that the odds ratio of the groups 

defined by the control variables are not homogeneous. A p(BD) probability < 0.05 (95% confidence) 

means that it is possible to summarize the conditional association between the dependent and 

explanatory variable by a single odds ratio. Situations where the odds ratio categories differ at 95% 

confidence are shown in red. This situation occurs when the explanatory and control variables are 

influenced by each other but have differing associations with the dependent variable. 

The Kappa coefficient (K) measures the correlation agreement between variables and corrects 

for the amount of correlation expected by random distribution. K varies from –1 for perfect negative 

correlation to 0 for random correlation to +1 for perfect correlation. Kappa measures not significantly 

different from random correlation at 95% confidence are shown in red. 

The non-parametric Spearman’s Rho coefficient measures the degree of monotonic correlation 

between continuous ordered variables. Rho coefficients have been calculated for the continuous 

dependent and independent data variables when the statistics indicate significant group differences, i.e. 

when the ORMH odds ratios differ from a value of 1.0 at 95% confidence. 

12
 
Table 2. Summary of ranked Cochran-Mantel-Haenszel statistics for rock (Rocks), stream sediment 

(Sseds), and groundwater well (wells) sample populations evaluated relative to grouped geologic 

bedrock map unit (Geology), agricultural index (AGI), stream sediment arsenic interpolation grid 

(SSgrid), and groundwater well arsenic interpolation grid (Wells) variables. 

[The threshold values used to group the samples and independent variables into binary categories are identified. The MantelHaenszel Case-control odds ratio, ORMH, measures the strength of the relationship between the two variables, when adjusted 

for the control variable. An odds ratio of 1 indicates no effect while a ratio greater than 1 indicates that the independent 

variable category increases the odds of occurrence of high concentrations in the sample media. Odds ratios not significantly 

different from 1 at 95% confidence are shown in red. The data are grouped by dependent variable and listed in order of 

decreasing ORMH. The Breslow-Day statistic, p(BD), measures the probability that the odds ratio of the groups defined by the 

control variables are homogeneous. Acceptance of the null hypothesis means that it is possible to summarize the conditional 

association between the dependent and explanatory variable by a single odds ratio. Situations where the odds ratio categories 

differ at 95% confidence are shown in red. Kappa (K) measures correlation corrected for randomness. Kappa measures not 

significantly different from random correlation at 95% confidence are shown in red. Spearman’s Rho correlation coefficients 

have been calculated for the continuous dependent and independent data variables when the CMH statistic indicates 

significant group differences. All tests use a 95-percent confidence level.] 

Y var Threshold X var Control ORMH p(BD) K Rho 

Wells 5 μg/L Geology AGI 8.755 0.5369 0.403 

Wells 5 μg/L Rocks AGI 7.453 0.1783 0.325 0.454 

Wells 5 μg/L SSgrid AGI 3.899 0.1577 0.237 0.283 

Wells 5 μg/L Rocks Geo+AGI 3.050 0.0012 0.135 

Wells 5 μg/L SSgrid Geo+AGI 1.918 0.0003 0.078 

Wells 5 μg/L AGI Geology 0.819 0.5387 -0.021 

Sseds 6.0 ppm Rocks AGI 4.253 0.9404 0.233 0.438 

Sseds 6.0 ppm Geology AGI 3.294 0.1930 0.248 

Sseds 6.0 ppm AGI Geology 1.630 0.1932 0.087 0.192 

Sseds 6.0 ppm Rocks Geo+AGI 1.518 0.0002 0.053 

Rocks 1.1 ppm SSgrid AGI 7.022 0.6451 0.204 0.438 

AGI 6.5 acres/mi2 Geology 1.930 

Correlation Results 

Bedrock well arsenic distributions, adjusted for the Agr-index variable (AGI), correlate strongly 

with the following explanatory variables (in decreasing strength of correlation as indicated by the MH 

Odds Ratio): 1) geology , 2) rock chemistry, and 3) stream sediment As (SSgrid) variables (Table 2). 

The nonsignificant p(BD) test scores for the geology, rock, and SSgrid variables relative the AGI 

variable indicate that they are not independent in influence. The strong spatial correlation of the AGI 

variable with the geology variable (ORMH = 1.93) is a likely cause of this effect. The well-rock and wellSSgrid correlations are both positive and significant when the data are adjusted for the influence of both 

the geology and AGI variables. These correlations have moderate Spearman’s Rho measures (0.454 and 

13
 
0.283, respectively). These data collectively indicate that elevated groundwater arsenic concentrations 

correlate most strongly with areas of elevated arsenic concentrations in rocks, the geologic units that 

host these rocks, and with stream sediments dominated by rock-derived arsenic sources. The correlation 

of well arsenic distributions with the AGI variable, when adjusted for the geology variable, was not 

significant. The significance of the p(BD) test score for the wells-AGI correlation indicate that the 

nonsignificant ORMH statistic is likely the result of no association rather than an inconsistent pattern of 

association that does not have enough strength or consistency to dominate any other pattern in the 

controlled strata groups. The stream sediment arsenic distributions, adjusted for the AGI or Geology 

variables, indicate significant correlation with the following explanatory variables, in decreasing 

strength of correlation as indicated by the MH Odds Ratio: 1) geology, and 2) AGI. The high values of 

the p(BD) test scores indicate that the odds ratios estimated for the stream sediment-wellgrid and stream 

sediment-geology associations are independent of the controlled AGI variable, and the stream sedimentAGI association is independent of the controlled geology variable. Although the stream sediment 

arsenic chemistry correlations with the geology and Agr-index variables are both positive and 

significant, the strength of the stream sediment correlation with the AGI variable is significantly weaker 

than the correlations with the geology variable. 

Correlation of wells, split into high and low categories, relative to stream sediment data 

For ordered variable relationships, the variation in Odds ratio as a function of the classification 

groups of the independent variable defines the properties of the relationship between dependent and 

independent variables (Figure 7). The “log of the Odds Ratio” (shown in the Y axis) is the variable fit 

during logistic regression. This plot shows the high-As and low-As classified well variables, on an area 

basis, versus classes of increasing stream sediment chemistry. The difference between the high and lowAs well trends is the Odds ratio of the high wells to low wells. For relationships, such as the above, 

where the log-transformed Odds ratio is linear with increasing independent variable value, the 

relationship between variables is well described by a continuous variable. The high-As wells increase in 

odds of occurrence with increasing stream sediment arsenic concentration. 

In contrast, the distribution of low-As wells appears to be independent of stream sediment 

arsenic concentration. The most accurate binary classification based on the independent variable occurs 

where the two Odds Ratio trends cross at approximately 6 ppm As in stream sediments. Binary 

classification of the independent variables is needed for the multiple comparison tests between 

dependent and independent variables that follows. The multiple comparison tests between dependent 

and independent variables used similar variable classifications for each comparison. 

14
 
4 

io

3 

taR

2 

s d

1 

d O

0 

ln

-1 

-2 

Well As >5 ug/L 

Well As <5 ug/L 

2 3 4 5 7 8 9 

0 

0-2-3-4-5-7-8-

11 13 16 19 23 28 34 40 

9-

>4

11-13-16-19-23-28-34-

Stream Sediment As range (ppm) 

Figure 7. Plot of log-transformed odds ratio defined by high-As and low-As classified well variables, on 

an area basis, versus classes of stream sediment chemistry defined by arsenic concentration range. The 

stream sediment arsenic data are discretized into bins with nearly equal log-transformed intervals. One 

sigma uncertainty intervals for the odds ratio values are shown by tic marks. The solid color lines are 

linear regression fits to the point data of similar color. The difference between the high and low-As well 

trends is the odds ratio of the high wells to low wells. The log-transformed odds ratio is the variable fit 

during logistic regression. 

Spatial Model of Arsenic Variability in Bedrock Ground Water 

A statistical model (Ayotte and others, 2006) has been developed to predict the probability of 

arsenic concentrations exceeding 5 μg/L in bedrock drinking-water wells by geographic area in New 

England (Figure 8). 

Multivariate logistic regression was used to estimate the probability of occurrence of elevated 

arsenic concentrations in ground water, based on the evaluation of more than 30 geologic, hydrologic, 

and landscape variables. 

Stream sediment chemistry and the distribution of geologic units have been found to be 

important parameters to predict the areas of greatest concern for elevated arsenic in ground water and to 

estimate the likely levels of human exposure to elevated arsenic in drinking water in New England 

(Ayotte and others, 2006). 

15
 
Probability of As > 5 

High: 0.905029 

Low: 0.000479 

0 50 100 

KILOMETERS 

72° W 

70° W 

68° W 

42° N 

44° N 

46° N 

CANADA 

C

A

N

A

DA 

Vermont 

Massachusetts 

New 

Hampshire 

Connecticut 

Rhode 

Island 

Maine 

Figure 8. Predicted probability of arsenic concentrations > 5 μg/L in ground water wells in bedrock 

aquifers (Ayotte and others, 2006). Truncation at 45 degrees north latitude reflects absence of stream 

sediment data. 

16 
Conclusions 

Stream Sediment Chemistry 

Elevated concentrations of arsenic in stream sediments correlate with elevated rock arsenic 

concentrations, the geologic units that have elevated rock arsenic concentrations, and areas where 

arsenical pesticide were used. Calcpelite, felsic volcanic, and sulfidic schist rock types have the highest 

baseline arsenic concentrations for rocks in the region. Stream sediments integrate arsenic from both 

rock and arsenical pesticide sources, although the relative influence of rock sources is stronger than 

arsenical pesticide sources. Mean stream sediment arsenic concentrations grouped by geology and 

lithology units are typically higher than the corresponding mean rock arsenic concentrations. 

Weathering appears to concentrate arsenic in soil, and derived sediments, relative to source rock 

materials. 

Bedrock Ground Water Chemistry 

The probability of ground water wells having arsenic concentrations greater than 5 μg/L varies 

by geology features. The highest ground water probability values correlate with lithology groups and 

geologic map units mostly occurring in the Coastal Maine and the Central Maine - New Hampshire 

lithotectonic belts. The well statistics correlate with variation in rock chemistry when the rocks are 

classified at a threshold of 1.1 ppm As. The well statistics correlate with variation in stream sediment 

chemistry when the sediments are classified at a threshold of 6.0 ppm. The well statistics do not 

correlate with variation in the intensity of past use of arsenical pesticides. These results indicate that the 

solubility and mobility of arsenic in ground water in bedrock are influenced by host-rock arsenic 

concentrations. However, the extreme local variability of arsenic concentrations in ground water from 

these rock sources indicate that arsenic concentrations in ground water are affected by other factors in 

addition to arsenic concentrations in rock. 

References Cited 

Ayotte, J.D., Nolan, B.T., Nuckols, J.R., Cantor, K.P., Robinson, G.R., Jr., Baris, Dalsu, Hayes, Laura, 

Silverman, D.T., and Lubin, Jay, 2006, Modeling the probability of arsenic in ground water in New 

England as a tool for exposure assessment: Environmental Science and Technology, v. 40, no. 11, p. 

3578-3585. 

D’Angelo, D., Norton, S.A., Loiselle, M.C., 1996. Historical Uses and Fate of Arsenic in Maine. Water 

Research Institute Completion Report 1986. University of Maine. Orono, Maine. 

Peryea, F.J., 1998. Historical use of lead arsenate insecticides, resulting soil contamination and 

implications for soil remediation. In: Proc. 16th World Congress of Soil Science. Montpellier, France. 

Science Reg. No. 274. Symposium 25. 

Robinson, G. R., Jr. and Ayotte, J.D., 2006, The influence of geology and land use on arsenic in stream 

sediments and ground waters in New England, USA: Applied Geochemistry, v. 21, p. 1482–1497. 

17
 
Robinson, G.R., Jr. and Kapo, K.E., 2003. Generalized lithology and lithogeochemical character of 

near-surface bedrock in the New England region. U.S. Geological Survey Open-File Report 03-225 . 

http://pubs.usgs.gov/of/2003/of03-225/ 

U.S. Department of Agriculture. 1935-1997. Census of Agriculture. Volume 1, Geographic Area Series. 

Table 1, County Summary Highlights. National Agriculture Statistics Service, Washington, D.C. 

Welch, A.H., Westjohn, D.B., Helsel, D.R., and Wanty, R.B., 2000, Arsenic in ground water of the 

United States: Occurrence and geochemistry: Ground Water, v. 38, no. 4, p. 589-604. 

18