Geochemistry of Loess and 

Carbonate Residuum 

GEOLOGICAL SURVEY PROFESSIONAL PAPER 954-G 

Geochemistry of Loess and 

Carbonate Residuum 

By RICHARD J. EBENS and JON J. CONNOR 

GEOCHEMICAL SURVEY OF MISSOURI 

GEOLOGICAL SURVEY PROFESSIONAL PAPER 954-G 

An examination of geochemical 

variability of two suificial 

geologic units in Missouri 

UNITED STATES GOVERNMENT PRINTING OFFICE, WASHING TON: 1980 
UNITED STATES DEPARTMENT OF THE INTERIOR 

CECIL D. ANDRUS, Secretary 

GEOLOGICAL SURVEY 

H. William Menard, Director 

Library of Congress Cataloging in Publication Data 

Ebens, Richard J. 

Geochemistry of loess and carbonate residuum. 

(Geochemical survey of Missouri) 

(Geological Survey Professional Paper 954-G) 

Bibliography: p. 29 

Supt. of Docs. no.: I 19.16:954-G 

1. Loess-Missouri-Analysis. 2. Sediments (Geology)-Missouri-Analysis. I. Connor, Jon J., joint author. 

II. Title. III. Series IV. Series: United States Geological Survey Professional Paper 954-G. 

QE499.E23 553.6 80-607796 

For sale by the Superintendent of Documents, U.S. Government Printing Office 

Washington, D.C. 20402 
CONTENTS 

Page Page 

Abstract -------------------------------------------------------------------

1 ntroduction -------------------------------------------------------------

G1 

1 

2 

2 

3 

3 

5 

9 

Geochemical variability-Continued 

Loess -Continued 

Acknowledgments ----------------------------------------------------------

Geologic setting -----------------------------------------------------------------

Sampling designs -------------------------------------------------------

Transect study --------------------------------------------------- I G 13 

Residuum ------------------------------------------------------------------- 15 

Highway study ------------------------------------------------------- 17 Loess -------------------------------------------------------------------

Residuum ------------------------------------------------------------------ Final study -------------------------------------------------------------- 20 

Analytical methods and data evaluation ---------------------------------

Geochemical variability --------------------------------------------------- 11 

11 

12 

Barite ore ----------------------------------------------------------- 23 

The relation of residuum to bedrock ------------------------------ 24 

Loess --------------------------------------------------------------- Discussion ----------------------------------------------------------------------- 27 

Bluff study --------------------------------------------------- References cited ------------------------------------------------------------------- 29 

ILLUSTRATIONS 

Page 

FIGURE 1. Map showing distribution of surficial geologic units in Missouri and sampling localities of loess and residuum--------------------- G4 

2-13. Graphs showing: 

2. Variation of Si02 and Al20 3 in loess samples and distribution of Fe20 3 and CaO in loess samples ------------------------------------ 11 

3. Variation of CaO and MgO in loess-------------------------------------------------------------------------------------------------------------------------- 12 

4. V_ariation of Al20 3 and K20 in loess--------------------------------------------------------------------------------------------------------------------------------- 13 

5. Chemical concentrations in loess that decrease as a function of distance east of the Missouri River floodplain----------------- 16 

6. Chemical concentrations in loess that increase as a function of distance east of the Missouri River floodplain --------------- 17 

7. Variation of Si02 and Al20 3 and the distribution of Fe20 3 in residuum-------------------------------------------------------------------------------- 19 

8. Variation of Al20 3 and K20 in residuum ------------------------------------------------------------------------------------------------------------------------- 19 

9. Variation of CaO and MgO in residuum------------------------------------------------------------------------------------------------------------------------------ 20 

10. Barium, copper, lead, and zinc content in residuum------------------------------------------------------------------------------------------------------ 24 

11. Concentrations of barium, manganese, titanium, copper, and zinc in residuum and underlying carbonate bedrock--------- 27 

12. Concentrations of silicon and aluminum in residuum and underlying carbonate bedrock--------------------------------------------- 28 

13. Trace element concentrations in loess and residuum in Missouri------------------------------------------------------------------------------- 30 

TABLES 

Page 

TABLE 1. Sampling localities of loess in Missouri --------------------------------------------------------------------------------------------------------------------------------- G6 

2. Sampling localities of residuum in Missouri and Arkansas --------------------------------------------------------------------------------------------------- 7 

3. Analytical methods for elements determined in loess and residuum------------------------------------------------------------------------ 10 

4. Comparison of variance components for loess in bluffs along the Mississippi and Missouri Rivers---------------------------------- 14 

5. Regression of loess chemistry with distance east of the Missouri River floodplain----------------------------------------------------- 15 

6. Geochemical summary of loess in Missouri ------------------------------------------------------------------------------------------------------ 18 

7. Comparison of variance components for residuum of the highway study ------------------------------------------------------------------ 21 

8. Parameters used to assess sampling requirements in residuum ------------------------------------------------------------------------- 22 

9. Comparison of variance components for residuum of the final study------------------------------------------------------------------- 23 

10. Parameters used to assess stability in averages based on the final study-----------------------------------,------------------------ 25 

11. Geochemical summaries of carbonate residuum, undifferentiated by bedrock area, Missouri and northern Arkansas --------- 25 

12. Geochemical summaries of carbonate residuum, by bedrock area, in Missouri and northern Arkansas ----------------------- 26 

13. Chemical analyses of barite ore from Missouri --------------------------------------------------------------------------------------------------- 26 

III 

GEOCHEMICAL SURVEY OF MISSOURI 

GEOCHEMISTRY OF LOESS AND CARBONATE RESIDUUM 

By RICHARD J. EBENS and jON J. CONNOR 

ABSTRACT 

Alluvium, loess, glacial till, and carbonate residuum are the four 

most prominent surficial geologic materials in the landscape of 

Missouri. Of these, loess and residuum are the most widespread and 

constitute the "parent" upon which most of the State's soils are 

developed. Geochemically, loess is one of the most uniform geologic 

materials in the State, and residuum one of the most heterogeneous. 

Regional geochemical variation of loess consists principally of 

weak, but statistically significant, changes in concentration with 

distance away from- the Missouri River drainage, which is the 

presumed source of much of the loess in the northern half of the 

State. Elements observed to increase away from the source are 

aluminum, arsenic, cobalt, copper, fluorine, gallium, iron, lithium, 

scandium, strontium, vanadium, and ytterbium; elements observed 

to decrease are barium, calcium, carbon, magnesium, manganese, 

silicon, sodium, phosphorus, potassium, and zirconium. The first 

element suite reflects an increasing clay content away from source, 

and the second indicates a decreasing dolomite, feldspar, zircon, 

apatite, and quartz content away from source. The concentration 

trends increase or decrease exponentially with distance. 

Regional geochemical variation of residuum reflects concentration changes from one major area of bedrock to another. This variation is statistically significant for aluminum, beryllium, chromium, 

copper, iron, gallium, lithium, manganese, scandium, selenium, 

silicon, vanadium, yttrium, ytterbium, and zinc and to a large extent reflects a greater clay content in residuum over areas of 

Mississippian bedrock (rocks of Osagean and Meramecian age) than 

in residuum over areas of pre-Mississippian bedrock (including the 

Bonneterre, Potosi, Gasconade, Roubidoux, and Jefferson City Formations). The more aluminous residuum also appears to be higher in 

the rare-earth elements cerium, dysprosium, gadolinium, holmium, 

praseodymium, and samarium. This bedrock-related variability suggests that the residuum is at least in part truly residual, although 

the predictive power of residuum geochemistry as a guide to the 

immediately underlying rock geochemistry is low. On average, it 

appears that six thicknesses of parent carbonate are required to 

produce a unit thickness of residuum. 

Samples of residuum collected in the State's lead districts were 

not unusually high in base metals, but many samples from the 

Washington County barite district were anomalously high in copper, lead, mercury, neodymium, and zinc, as well as barium; some 

appeared to be anomalously-low in cadmium. The barite ore mined 

from residuum in the district is generally low in accessory elements 

except for a percent or so of aluminum and about half a percent of 

strontium. 

The geochemical differences between loess and residuum and the 

differences among residua overlying areas of different bedrock in 

southern Missouri impart a complex regional geochemical pattern 

to the surficial geologic deposits of the State. These patterns are difficult to show on maps, however, because of insufficient knowledge 

of the detailed distributions of the geologic deposits themselves. 

Nevertheless, the geochemical summaries in this report constitute 

"first-order" estimates of the local geochemical background in these 

materials, which should prove useful in judging unusual or 

"anomalous" samples. 

INTRODUCTION 

The role of trace elements in health and disease has 

been of interest to medical researchers for a long time, 

and an increasing public awareness of trace-element 

hazards in the environment has focused attention on 

the need for data concerning the expected ranges of element concentration in ordinary near-surface environmental materials under natural conditions. A reconnaissance geochemical survey of the State of Missouri 

was undertaken during the years 1969-73; the object 

of the survey was to examine the geochemical variability of the major components of the State's landscape. The survey was undertaken in cooperation with 

personnel of the Environmental Health Surveillance 

Unit at the University of Missouri in support of their 

studies on the role of the geochemical environment in 

health and disease. 

This report is one of a series describing the results of 

that survey and focuses on the geochemical variation 

observed in two widespread surficial geologic units. 

Previous reports have described the geochemistry of 

selected soils, plants, waters, and rocks (Tidball, 1976; 

Erdman and others, 1976a, 1976b; Feder, 1979; Connor 

and Ebens, 1980). Miesch (1976) gave a general statement of goals and methods of the survey. Much of the 

work on which the present report is based appeared in 

seven progress reports issued at six-month intervals 

during the life of the survey (U.S. Geological Survey, 

1972a-f, 1973). 

Gl 
G2 GEOCHEMISTRY OF LOESS AND CARBONATE RESIDUUM 

ACKNOWLEDGMENTS 

We express our appreciation to many U.S. 

Geological Survey colleagues for their assistance in 

this study. A. T. Miesch conceived, initiated, and gave 

direction to the Missouri geochemical investigations 

as a whole. Josephine G. Boerngen assisted in computer processing of the geochemical data. Hundreds of 

samples of loess and residuum were analyzed in 

laboratories of the U.S. Geological Survey for nearly 

60 elements. The analysts who performed this work are 

A. J. Bartel, L.A. Bradley, F. W. Brown, Mike Brown, 

J. W. Budinsky, C. L. Burton, J.P. Cahill, J. I. Dinnin, 

E. J. Fennely, W. H. Ficklin, L. D. Forshey, I. C. Frost, 

Johnnie Gardner, Herbert Kirschenbaum, L. M. Lee, 

V. M. Merritt, Leung Mei, H. T. Millard, Jr., Roosevelt 

Moore, Wayne Mountjoy, H. G. Neiman, D. R. Norton, 

R. L. Rahill, V. E. Shaw, G. D. Shipley, M. W. Solt. 

J. A. Thomas, J. H. Turner, R. L. Turner, J. S. 

Wahlberg, and T. L. Yager. Samples were prepared for 

analysis by John Moreland, Jr. 

We acknowledge with thanks the services and facilities provided by Dr. Carl J. Marienfeld and his associates of the Environmental Health Surveillance Unit at 

the University of Missouri. Personnel of the Missouri 

Division of Geology and Land Survey assisted us in 

many ways; specifically, we wish to thank W. B. Howe, 

State Geologist, and Larry Fellows, Assistant State 

Geologist. 1 Particular thanks are due Tom Boyer of 

National Lead Co., Steve Sitkich of Dresser Industries, Joe Rosier of Milchem, Inc., and Robert Griffey 

of Pfizer, Inc., for aid in sampling the barite ores of 

Washington County. 

GEOLOGIC SETTING 

Extensive deposits of unconsolidated sand, silt, and 

clay overlie the geologic bedrock units and underlie the 

soil units nearly everywhere in Missouri. In northern 

Missouri these deposits are heterogeneous accumulations of glacially derived sand, silt, and clay. Glaciation and deposition associated with glaciation in this 

region were both complex (Wickham and Lineback, 

1978; Aber, 1977; Bayne and others, 1971), and temporal and spatial relations among the constituent 

deposits, particularly the older ones, are only poorly 

understood (Boellstorff, 1978; Dreeszen, 1970). Even 

so, these deposits are of enormous importance to the 

general economy of the region, because they influence 

the character of the agricultural soils and host a plentiful supply of potable ground water in some areas 

(Bayne and others, 1971). 

'Now State Geologist at Arizona Bureau of Geology and Mineral Technology. 

In southern Missouri the surficial deposits consist 

largely of locally thick accumulations of red, cherty 

clay called carbonate residuum. This material is generally viewed as the residue of prolonged weathering of 

the carbonate bedrock. Soils developed on these clays 

are generally acid and of low fertility; as a conse- · 

quence, they are commonly used for pasturage (Wisconsin University, 1960, p. 101-102). Also, extensive 

deposits of alluvial sand, silt, and clay lie along floodplains of the major rivers. The most prominent of these 

deposits occurs in the Mississippi River floodplain of 

southeasternmost Missouri, where the alluvium locally 

thickens to as much as 70 m (Fuller, 1977). Soils developed on these materials tend to be young with little 

profile development (Wisconsin University, 1960, p. 

22-23). Minor areas in southeastern Missouri and a 

major area in western Missouri are underlain by noncarbonate bedrock. Weathering of bedrock in these 

areas gives rise to a silt-clay residuum which tends to 

be geochemically similar to the underlying bedrock. 

A highly generalized map showing the distribution 

of these surficial geologic materials is given in figure 1. 

Of these materials, loess and residuum form the most 

visible part of the Missouri landscape. Thick accumulations of loess along the Missouri and Mississippi 

Rivers weather to vertical cliffs, and residuum colors 

roadcuts and excavations a deep red or red-brown 

throughout southern Missouri. 

Loess in Missouri consists of wind-laid deposits of 

silt and clay accumulated during the latter half of the 

Pleistocene Epoch. It is thickest on bluffs above the 

Missouri and Mississippi Rivers, whose floodplains 

constitute the sources of the loess, but it occurs in lesser thicknesses over large parts of the State. The loess 

r -..,osits have been assigned to the Bignell and Peoria 

_ ~sses and the Roxana(?) Silt of Wisconsin age and to 

the Loveland Loess of Illinoian age. The thickest accumulations, in northwesternmost Missouri (fig. 1), 

consist largely of the Peoria Loess (Bayne and others, 

1971, p. 7-8). In Iowa, Wisconsin loess has been dated 

at 29,000 to 14,000 years old with the older deposits 

being closer to the source (Rube, 1969, p. 29). In contrast, residuum tends to be much older, as it occurs in 

i areas that have been subjected to subaerial weathering 

· for tens of millions of years. 

In sampling loess and residuum in this study, a conscious effort was made to exclude the A and B soil 

horizons, if recognizable, of the present-day soil profile. 

In general, loess in deposits less than a meter or so 

thick tended to be severely weathered. Where more 

than a few meters thick, residuum commonly displayed in its upper parts the color mottling and clay 

accumulation typical of soil development. Below this 

weathered cap, however, it tended to be uniformly red 
SAMPLING DESIGNS G3 

or red-brown and, in places, distinctly stratified, which 

likely reflects relict bedding. Neither alluvium nor till 

were sampled in this work. Alluvium is a quantitatively minor part of the surficial geologic cover in the 

State, and till is in general poorly exposed. 

SAMPLING DESIGNS 

Geochemical variability in loess and residuum was 

examined in part through the use of hierarchical 

sampling plans designed to estimate the proportions of 

the total geochemical variance occurring over selected 

ranges of scale (Miesch, 1976). Such designs are exploratory and are based on a system of hierachically 

arranged sampling units such that' each hierarchy includes paired sampling units separated by a given 

distance or a selected range of distances. 

The general statistical model used in all phases of 

the geochemical survey of Missouri is (Miesch, 1976) 

log Xijklmn = J-1. + CXi + f3ij + 'Yijk 

+ Dijkl + 1Jijklm + Eijklmn• (1) 

where Xijklmn represents an analytical value for a given 

element reported on a sample of some landscape 

material by the laboratory; p. represents the grand 

average logarithmic concentration for that material; a, 

(3, ')', and 1J (with subscripts) are deviations reflecting 

geochemical variation arising at decreasing geographic 

scales; and Eijklmn represents the difference between 

the logarithm of the reported concentration and the 

true logarithmic concentration in the analyzed sample. 

Logarithms of concentration are commonly employed 

in trace-element work to help meet some of the 

assumptions underlying the statistical procedures 

used in data analysis (Miesch, 1976, p. 27). The model 

in equation (1) is discussed in mathematical detail in 

the context of a geochemical field problem by Krumbein and Slack (1956). 

The target population in this study is the aggregate 

of all potential samples of loess and residuum in the 

study area. A sample is defined as a few kilograms of 

material cut or dug from a homogeneous part (generally a single stratum) of the unit. Because the only collecting tools used were geologic pick or shovel, the 

sampled population was confined to areas of natural or 

artificial exposure, largely roadcuts. In order to 

minimize personal bias in estimating the statistical 

properties of the units, an attempt was made to collect 

samples for the hierarchical designs at randomly 

selected locations in outcrop. This selection depended 

on outcrop distribution, but was considered effectively 

random because the outcrop distribution is controlled 

by a large number of geologic and human factors. In 

order to minimize analytical bias, all samples and 

analytical splits were submitted to the laboratory in a 

randomized sequence. 

LOESS 

Two independent studies of loess geochemistry were 

undertaken. Samples for the first study (termed the 

bluff study) were collected in the fall of 1970 from thick 

loess deposits cropping out in the bluffs above the 

Missouri and Mississippi Rivers. Sampling localities 

for this study are shown in figure 1 and specific locations are listed in table 1. 

For this study, the bluffs along the two rivers were 

divided into six segments (areas), each approximately 

150 km long. Within each of these segments, two subsegments, each a few kilometers long, were selected 

randomly, and two samples were taken randomly from 

the best exposed section in the subsegment. The 

statistical model used in this study was modified from 

equation ( 1 ), as follows 

log Xijkl = p. + f3i + 'Yij + bijk + EijkZ. (2) 

where f3i represents the difference between p. and the 

average logarithmic concentration of the ith blui'f segment; 'Yij represents the difference between the average 

of the jth stratigraphic section and the average of the 

ith segment; and Dijk represents the difference between 

the averages of the kth sample and the jth section. 

Four components of variance were estimated: 

Sfog x = s~ + s~ + s~ + s~. (3) 

These components reflect variation among segments 

(S~. representing geochemical variation at scales 

greater than about 150 km), variation between 

stratigraphic sections within segments (S~, representing geochemical variability at scales less than about 

150 km), variation between samples within sections 

(S~). and analytical variation (S~). The analytical 

variance was estimated in a very approximate way 

from replicate analyses of three samples of loess. 

The sample design used in the bluff study was a 

Stage 2a design, as described by Connor and others 

(1972), and was designed to examine scale-related 

variation in the thick (better developed) parts of the 

loess blanket of Missouri. A second study, undertaken 

in 1972, was aimed at examination of the geochemistry 

of the thinner (less well-developed) deposits blanketing 

regions away from the major drainage as well. Because 

the Missouri River valley is the apparent source for 

much of the loess deposited in northern Missouri, three 
G4 GEOCHEMISTRY OF LOESS AND CARBONATE RESIDUUM 

IOWA ( 

40° 

ILLINOIS 

39° 

KANSAS 

38° 

36° 

0 100 200 KILOMETERS 

FIGURE I.-Distribution of surficial geologic units in Missouri and sampling localities of loess and residuum. The four sampling localities 

within the Washington County barite district are all on the Potosi bedrock unit. (Adapted from Oetking and others, 1966; McCracken, 

1961; and Stout and Hoffman,l973.) 

east-west transects were sampled east of this river to 

measure downwind changes in composition (fig. 2). 

The longest transect was the middle one (transect 2), 

which followed U.S. Route 36 eastward from St. 

Joseph, Mo. The southernmost transect (transect 1) 

followed State Route 124 east of Lisbon, Mo., and the 

northernmost (transect 3) followed U.S. Route 136 east 

of Rockport. Along each tr~sect, sampling localities 

were spaced at approximate geometric intervals of 

0.75, 1.5, 3, 6 ... km from the edge of the Missouri 

River floodplain as far eastward as recognizable loess 

could be found. In each locality, three samples of loess 

were collected randomly from the best exposed vertical 

section of loess. 

These samples were tested for the presence of downwind geochemical trends by regression analysis: 
SAMPLING DESIGNS G5 

EXPLANATION 

G22J ALLUVIUM 

0 

0 

GLACIAL DEPOSITS (Present north of limit of 

glaciation; dotted area contains deposits locally 

greater than 30 m thick) 

m 

0 

j 

u u 

r 

(' 

g 

p 

b 

CARBONATE RESIDUUM 

(Distributions approximate; shown only south 

of limit of glaciation) 

On the Maramec bedrock unit 

On the Osage bedrock unit 

On the Jefferson City bedrock unit 

On the Roubidoux bedrock unit 

On the Gasconade bedrock unit 

On the Potosi bedrock unit 

On the Bonneterre bedrock unit 

D SILT-CLAY RESIDUUM 

~ WASHINGTON COUNTY BARITE DISTRICT 

..J..._--'-- ..J... SOUTHERN LIMIT OF GLACIATION 

-5- APPROXIMATE MAXIMUM THICKNESS 

OF LOESS IN METERS 

SAMPLING LOCALITIES 

A Loess-Bluff study 

6 Loess-Highway study 

• Residuum-Highway study 

0 Residuum-Final study 

log X = a + b•log (km) + r. (4) 

Here, X is the concentration of an element in a sample 

as reported by the laboratory, a. is the estimated 

logarithmic concentration at a distance of 1 km (estimated from the regression), and b is the slope of the 

geochemical trend away from presumed source. The 

last term, r, represents the difference between the estimated logarithmic concentration in the sample and the 

actual logarithmic concentration. 

The total variation (Sfog x) observed along a transect 

may be subdivided into two components: 

SfogX = S~ + S~, (5) 

where ~ is that part of the total observed variance accounted for by the trend and S~ is the remainder. The 

first component (S~) is similar in meaning to Sb and S~ 

combined of equation (3); s~ is not equal to s~ in equa· 

tion (3), because it contains variation attributable to 

more than just analytical error. S~. however, does contains~ within it. Although neither s~ nor s~ have been 

computed here, S~ may be computed from 

(6) 

where b is as defined in equation (4) and cis equal to 

0.2719 for transect 1, 0.4833 for transect 2, and 0.3700 

for transect 3. The values of S~ can be computed from 

S~ = SfogX- S~. (7) 

RESIDUUM 

Two studies of residuum were undertaken also: a 

preliminary (highway) study in 1970 and a final study 

in 1972. Sampling localities for both studies are shown 

in figure 1; specific sample localities are listed in table 

2. In both studies, residuum was classified according 

to the major bedrock unit over which it lay. The bed· 

rock units were those appearing on the State geologic 

map published by the State of Missouri (McCracken, 

1961). The residuum units used in the highway study 

were areas overlying (1) the Bonneterre Formation and 

the Elvins Group; (2) the Potosi and Eminence Forma· 

tions; (3) the Roubidoux Formation; (4) the Jefferson 

City, Cotter, Powell, and Smithville Formations; (5) 

the rocks of the Osage Series; and (6) the rocks of the 

Meramec Series. A seventh residuum unit, the area 

overlying the Gasconade Formation, was added to the 

final study (1972). For convenience, these residuum 

units will be referred to in this report as the Bonneterre, Potosi, Roubidoux, Jefferson City, Osage, 

Meramec, and Gasconade residuum units, respectively 

(fig. 1). 

In the highway study, six samples each were collected from the Bonneterre, Potosi, Roubidoux, J ef· 

ferson City, Osage, and Meramec residuum units. 

Because one object of this particular study was to ex· 

amine the geochemical relation of residuum to the 

underlying bedrock (in addition· to estimating scalerelated components of variance), sampling localities 

were restricted to exposures where bedrock could be 

sampled along with the overlying residuum. As a consequence, all sampling was done along a few major 

highways where the probability of finding such ex· 

posures seemed greatest; thus, the use of the term 

"highway study" in this report. 
G6 GEOCHEMISTRY OF LOESS AND CARBONATE RESIDUUM 

TABLE I.-Sampling localities of loess in Missouri 

[Localities shown in figure 1) 

Locality Field No. County Site description1 Thickness Cormnents 

No. (m) 

REOL-01, 02 Stoddard------- In quarry 2.3 km NE. jet. u.s. 60 State-- 1.8 Rootlets. 

Rt. 25. 

2 03, 04 Scott---------- On u.s. 61, 3.2 km s. of Kelso----------- 4.6 

3 OS, 06 Perry---------- On County Rt. A, E. edge of Altenburg---- 7.6 

4 07, 08 Ste. Genevieve- On u.s. 61, 0.8 km s. of Aux Vase R------ 9.1 

5 09, 10 Lincoln-------- At jet. of State Rts. 79 and 47---------- 1.8 Weathered. 

6 11, 12 Pike----------- On County Rt. W. 3.2 km s. of Paynesville .9 B-horizon? 

7 13, 14 Warren--------- In quarry 2.3 km NE. of Marthasville----- 4.6 

8 15, 16 ----do--------- On State Rt. 94, 6.4 km E. of McKittrick- 3.1 

9 17, 18 Boone---------- On County Rt. K, 1.6 km E. of McRaine---- 4.6 

10 19, 20 Howard--------- On County Rt. J, 1.6 km E. of Petersburg- 6.1 

11 21, 22 Platte--------- On State Rt. 45, 3.2 km w. of State Rt. 9 4.6 

12 23, 24 Atchison------- On u.s. 136, 3.2 km E. of Rock Port------ 9.1 

13 E2L-111, 112, 113 Howard--------- On County Rt. K, 0.7 km E. of Lisbon----- 6.1 

121, 122, 123 ---do---------- On County Rt. K, 1.5 km E. of Lisbon----- 3.1 Soil(?). 

131, 132, 133 ---do---------- On County Rt. K, 3 km E. of Lisbon------- 1.8 Do. 

14 141, 142, 143 ---do---------- On State Rt. 87, 6 km NE. of Lisbon------ 3.7 

15 151, 152, 153 ---do---------- On County Rt. J, 5 km w. of Fayette------ 1.5 Soil(?). 

16 161' 162, 163 ---do---------- On State Rt. 124, 6.5 km E. of Fayette--- 1.8 no. 

17 171, 172, 173 Boone---------- At jet. of n.s. 63 and State Rt. 124----- 1.8 Do. 

18 211, 212, 213 Buchanan------- On u.s. 36, 1 km E. of Missouri R-------- 7.6 

221, 222, 223 ---do---------- On u.s. 36, 1.5 km E. of Missouri R------ 4.6 

231, 232, 233 ---do---------- On u.s. 36, 3 km E. of Missouri R-------- 6.1 

19 241, 242, 243 ---do---------- On u.s. 36, 0.5 km E. of I-29------------ 3.1 

20 251, 252, 253 ---do---------- At _ict. of u.s. 36 and County Rt. c------ 1.8 

21 261, 262, 263 DeKalb--------- On u.s. 36, 4 km w. of Stewartsville----- 1.2 Soil(?). 

22 271, 272, 273 ---do---------- On u.s. 36, 4 km E. of Osburn------------ .2 

23 281, 282, 283 Caldwell------- On u.s. 36, 3 km s. of Breckenridge------ .9 Soi 1(?). 

24 291, 292, 293 Macon---------- On u.s. 36, 2 km SE. of New Cambria------ .9 Do. 

25 311, 312, 313 Atchison------- On u.s. 136, 0.5 km E. of Missouri R----- 6.1 

floodplain. 

321, 322, 323 ---do---------- On u.s. 136, 1.5 km E. of Missouri R----- 9.1 

floodplain. 

331, 332, 333 ---do---------- On u.s. 136, w. edge of Rock Port-------- 4.6 

26 341, 342, 343 ---do---------- On u.s. 136, at _ict. with County Rt. Y--- 6.7 

27 351, 352, 353 ---do---------- On u.s. 136, 4 km SW. of Tarkio---------- 4.6 

28 361, 362, 363 ---do---------- On County Rt. M, 1 km N. of u.s. 136----- 1.5 Weathered. 

29 371, 372, 373 Nodaway-------- 2.5 km NE. of Wilcox--------------------- 1.5 Do. 

30 381, 382, 383 Worth---------- 3.5 km NW. of Denver--------------------- .9 no. 

l Abbreviations: ict., iunction; Rt., Route; R.' River. 

In this study, two localities of the required kind were 

selected, randomly if possible, from each residuum unit 

along the chosen highway. Within each locality, two 

sections of residuum were selected randomly; in one of 

these sections, two random samples were collected; in 

the other, one sample was taken randomly, for a total 

of 36 samples. 

The pairing- of sampled sections in each locality required that in s~ in equation (3) be redefined as two 

components, so the statistical model used in this study 

was modified from equation (1) as follows: 

tween the average (in logs) of the jth locality and the 

average of the ith unit; Kijk represents the difference 

between the average (in logs) of the kth stratigraphic 

section and the average of the jth locality; and Oijkl 

represents the difference between the average (in logs) 

of the lth sample and the average of the kth section. 

The term 'Yij in equation (2) is here represented by 

(()ij + Kijk ). 

The five components of variance were estimated as 

(9) 

log Xijklm = Jl + f3i + ()ij + Kijk + Oijkl + Eijklm• (8) 

where f3i represents the difference between Jl and the 

average logarithmic concentration in the ith residuum 

unit (area of bedrock); ()ij represents the difference bewhere S~ reflects variation among the six residuum 

units, S~ represents variation between localities within 

units, s~ represents variation between sections within 

localities, s~ represents variation between samples 
SAMPLING DESIGNS 07 

TABLE 2.-Sampling localities of residuum in Missouri and Arkansas 

[All localities in Missouri except 37, 41, 42, and 46; localities shown in fig. 1. A sample of bedrock was collected at both residuum sites in each of the first 12 localities) 

Locality 

No. 

2 

3 

4 

5 

6 

7 

8 

9 

10 

11 

12 

13 

14 

15 

16 

17 

18 

19 

20 

21 

22 

23 

24 

25 

Field No. 

REOR-ROl 

R02, R02D 

R03 

R04, R04D 

R05, R05D 

R06 

R07 

R08, R08D 

R09 

RlO, RlOD 

Rll, RllD 

Rl2 

Rl3 

Rl4, Rl4D 

Rl5, Rl5D 

Rl6 

County 

St. Francais----

----do----------

Madison---------

----do----------

Washington------

----do----------

----do----------

----do----------

Phelps----------

----do----------

Texas-----------

P~elps----------

Laclede---------

----do----------

----do----------

----do----------

Rl7 Greene----------

Rl8, Rl8D ----do----------

Rl9 ----do----------

R20, R20D ----do----------

R29, R29D, Jasper----------

R30. 

R31 

R32, R32D 

E2R-B0ll, B012 

B013, B014 

B021, B022 

B023, B024 

B032 

B033, B034 

B041, B042 

B043, B044 

B051, B052 

B053, B054 

----do----------

----do----------

St. Francais----

----do----------

Wayne-----------

----do----------

Washington------

----do----------

----do----------

----do----------

Iron------------

----do----------

B071, B072 Madison---------

B073, B074 ----do----------

POll, P012 Crawford--------

P013, P014. ----do----------

P021, P022 Washington------

P023, P024 

P031, P032 

P033, P034 

P041, P042 

P043, P044 

----do----------

----do----------

----do----------

Carter----------

----do----------

P051, P052, Washington------

P053, P054. 

P061, P062 Shannon---------

P063, P064 ----do----------

GOll, G012 Washington------

G013, G014 ----do----------

G021, G022 Dent------------

G023, G024 ----do----------

G041, G042 ----do----------

G043, G044 ----do----------

Site description 1 

On U.S. 67, 5.6 km S. of Flat R. exit-----

On U.S. 67, 1 km S. of Flat R. exit-------

On U.S. 67, 1.1 km S. of Fredericktown----

exit. 

On U.S. 67 at Fredericktown exit----------

On State Rt. 21, 1.1 km S. of County Rt. E 

On State Rt. 21, 3.7 km S. of State Rt. 8-

0n State Rt. 47, 2.4 km N. of State Rt. 21 

On State Rt. 47, 0. 3 km N. of State Rt. 21 

On U.S. 63, 4.7 km S. of Yancy Mills------

On U.S. 63, 1.8 km s. of Yancy Mins------

On U.S. 63, 0.2 km N. of County Rt. CC----

On U.S. 63 at Phelps-Texas County line----

On U.S. 66, 6 km W. of County Rt. T-------

On U.S. 66, 6.6 km W. of County Rt. T-----

On U.S. 66, 1.8 ~ NE. of County Rt. A----

On U.S. 66, 0.5 km NE. of County Rt. A----

On I-44, 2.4 km E. of County Rt. N--------

On I-44 at County Rt. MM exit-------------

On I-44, 3.1 km E. of County Rt. PP-------

On I-44, 3.7 km E. of County Rt. PP-------

On U.S. 71, 2.4 km S. of County Rt. M-----

On U.S. 66, 0.4 km E. of State Rt. 96-----

In quarry 1.5 km NW. of Spring R. and-----

U.S. 71. 

On U.S. 67, 0.5 km S. of County Rt. DD----

On U.S. 67, 2 km S. of County Rt. T-------

On U.S. 67, 1 km S. of Coldwater----------

On U.S. 67, 3 km S. of Coldwater----------

On County Rt. M, 3.5 km E. of State Rt. 21 

On County Rt. M, 2 km E. of State Rt. 21--

0n County Rt. JJ, 0.2 km S. of Belgrade---

On County Rt. JJ, 2.1 km S. of Belgrade---

On County Rt. JJ. 0.5 km S. of State Rt. 72 

On County Rt. JJ, 4 km S. of State Rt. 72-

On U.S. 67, 1.8 km N. of County Rt. JJ----

On U.S, 67, 3.5 km N. of County Rt. JJ----

On County Rt. N, 1.8 km E. of Meramac R---

On County Rt. N at Washington County lineOn road 7.5 km NW. of Old Mines-----------

On road 7.3 km NW. of Old Mines-----------

On County Rt. E, 0.6 km S. of State Rt. 47 

OQ County Rt. E, 1.2 km S. of State Rt. 47 

On County Rt. D, 11 km N. of Van Buren----

On County Rt. D, 9 km N. of Van Buren-----

On County Rt. F, 5.5 km NW. of Potosi-----

On County Rt. A, 5.5 km E. of State Rt. 19 

On County Rt. A, 5.3 km E. of State Rt. 19 

On road 1.2 km S. of State Rt. 8, about---

4 km E. of county line. 

On State Rt. 8, 3 km E. of county line----

On State Rt. 19, 1.8 km SW. of Meramac R--

On State Rt. 19, 1.6 km SW. of Meramac R--

On road 3 km E. of jet. of State Rt. 19---

and County Rt. WW. 

On road 3.7 km NE. of jet. of State Rt. 19 

and County Rt. WW. 

Thickness 

(m) 

3.1 

1.2 

1.5 

4.6 

4.6 

.6 

1.5 

1.2 

23 

6.1 

3.1 

3.1 

3.1 

3.1 

1.5 

6.1 

1.5 

3.1 

3.2 

4.6 

3.1 

1.5 

3.1 

2.1 

1.5 

7.6 

3.1 

1.8 

1.5 

3.1 

. 9 

1.5 

2.1 

9.1 

6.1 

.9 

2.4 

1.2 

. 6 

.6 

. 6 

9.1 

3.1 

3.1 

6.1 

.9 

3.7 

1.2 

2.4 

7.6 

1.2 

.9 

Underlying 

bedrock unit 2 

Bonneterre. 

Do. 

Do. 

Do. 

Potosi. 

Do. 

Do. 

Do. 

Roubidoux. 

Do. 

Do. 

Do. 

Jefferson City 

Do. 

Do. 

Do. 

Osage. 

Do. 

Do. 

Do. 

Meramec. 

Do. 

Do. 

Bonneterre. 

Do. 

Do. 

Do. 

Do. 

Do. 

Do . 

Do. 

Do. 

Do. 

Do. 

Do. 

Potosi. 

Do. 

Do . 

Do. 

Do • 

Do. 

Do. 

Do. 

Do. 

Do. 

Do. 

Gasconade. 

Do. 

Do. 

Do. 

Do. 

Do. 
GB GEOCHEMISTRY OF LOESS AND CARBONATE RESIDUUM 

TABLE 2.-Sampling localities of residuum in Missouri and Arkansas-Continued 

Locality 

No. 

26 

27 

28 

29 

30 

31 

32 

33 

34 

35 

36 

37 

38 

39 

40 

41 

42 

43 

44 

45 

46 

47 

48 

49 

50 

51 

52 

Field No. 

GOSl, G052 

G053, G054 

G061 

G063, G064 

G071, G072 

G073, G074 

County 

Carter----------

----do----------

Crawford--------

----do----------

Camden----------

----do----------

E2R-R011, R012, Camden----------

R013, R014. 

R022 

R023, R024 

R041, R042 

R043, R044 

R051, R052 

R053, R054 

R061, R062 

R063, R064 

R071, R072 

R073, R074 

JOll, J012 

J013, J014 

Miller----------

----do----------

Dent------------

----do----------

----do----------

Phelps----------

Oregon----------

----do----------

Douglas---------

----do----------

Stone-----------

----do----------

J021, 

J023, 

J041, 

J043, 

J051, 

J053, 

J061, 

J063, 

J071, 

J073, 

0011, 

0013, 

0021, 

J022 Laclede----------

J024 Wright----------

J042 Marion (Ark.)---

J044 ----do----------

J052, Barry-----------

J054. 

J062, 

J064. 

J072 

J074 

0012 

0014 

0022 

0023, 0024 

0031, 0032 

0033, 0034 

0041' 0042 

0043, 0044 

0051, 0052 

0053, 0054 

0061, 0062 

0063, 0064 

MOll, M012 

M013, M014 

M021, M022 

Texas-----------

Polk------------

----do----------

Searcy (Ark.)---

----do----------

Washington (Ark) 

Benton (Ark.)---

Lawrence--------

----do----------

Newton----------

----do----------

Webster---------

----do----------

Searcy (Ark.)---

----do----------

Jasper----------

----do----------

----do----------

M023, M024 ----do----------

M031, M032 Newton----------

M033, M034 ----do----------

M061, M062 Jasper----------

M063, M064 ----do----------

M071, M072 Dade------------

M073, M074 ----do----------

M081, M082 Jasper----------

M083, M084 ----do----------

Site description1 

On County Rt. M, 2.5 km NW. of Van Buren--

On County Rt. M, 5 km NE. of Van Buren----

On County Rt. M, 2.5 km N. of Cook Station 

On County Rt. YY, 1.5 km NW. of Cook------

Station. 

On U.S. 54, 3 km NE. of Camdenton---------

On County Rt. V, 1 km S. of Linn Creek----

On State Rt. 7, 2 km E. of jet. with------

County Rt. T. 

On State Rt. 17, 2. 5 km SE. of State R. 52 

On State Rt. 17, 3 km SE. of State Rt. 52-

0n County Rt. JJ, 5 km N. of State Rt. 19-

0n County Rt. JJ, 3.5 km NE. of State Rt.-

19. 

On State Rt. 72, 0.8 km N. of Lake SpringOn State Rt. 72, 2.1 km N. of Lake SpringOn U.S. 160, 2.1 km S. of State Rt. 99----

0n U.S. 160, 1.9 km S. of State Rt. 99----

On State Rt. 76, 4 km W. of State Rt. 181-

0n State Rt. 76, 1.2 km W. of State Rt. 181 

On County Rt. H, 2 km E. of State Rt. 39--

0n County Rt. H, 0.8 km E. of State Rt. 39 

On County Rt. 0, 0.8 km W. of County Rt. AD 

On County Rt. AF, 0.6 km S. of county line 

On State Rt. 101, 3 km SE. of U.S. 62-----

0n State Rt. 101, 0.9 km SE. of U.S. 62---

0n State Rt. 86, 2 km W. of State Rt. 39--

On County Rt. M, 2.3 km W. of State Rt. 17 

On State Rt. 64, 2.2 km E. of County Rt. D 

On State Rt. 64, 1.3 km E. of County Rt. D 

On State Rt. 14, 4 km N. of Harriet-------

On State Rt. 14, 1.5 km N. of Harriet-----

On State Rt. 16, 1 km E. of Benton Countyline. 

On State Rt. 16, 1.2 km SE. of Osage Creek 

On U.S. 60, 2 km S. of Verona-------------

On U.S. 60 at Barry County line-----------

On County Rt. D, 2.5 km W. of Boulder City 

On County Rt. D, 1.5 km W. of Boulder City 

On road 3.5 km SW. of jet. of County Rt. C 

and County Rt. P. 

On road 3 km NW. of jet. of County Rt. C--

and County Rt. V. 

On State Rt. 74, 2.9 km W. of Dongola-----

On State Rt. 74, 2.1 km W. of Dongola-----

On State Rt. 37, 2.5 km N. of County Rt. F 

On State Rt. 37, 1.2 km N. of County Rt. F 

On U.S. Alt. 71, 2 km N. of I-44----------

On U.S. Alt. 71, 3.8 km N. of I-44--------

0n U.S. 60, 5.5 km W. of U.S. 71----------

0n U.S. 60, 3.5 km W. of U.S. 71----------

0n U.S. 66, 2.5 km NE. of Carterville-----

On road 3.2 km E. of Carterville----------

On U.S. 160, 0.4 km E. of Lockwood--------

On U.S. 160, 1.2 km E. of Lockwood--------

On County Rt. F, 3.8 km W. of State Rt. 37 

On County Rt. F, 6.9 km W. of State Rt. 37 

1Abbreviations: jet., junction; Rt., Route; R, River; Alt., Alternate. 

2McCracken (1961). 

Thickness 

(m) 

1.5 

1.8 

.9 

.6 

1.5 

1.5 

.9 

1.8 

1.5 

.9 

1.2 

.9 

.9 

1.5 

3.1 

1.5 

4.6 

1.5 

1.2 

1.2 

.9 

1.8 

3.1 

1.2 

1.2 

1.5 

.9 

3.1 

.6 

.9 

.9 

4.6 

7.6 

7.6 

3.1 

. 9 

.6 

2.4 

2.1 

4.6 

4.6 

6.1 

3.7 

1.5 

. 6 

1.8 

1.2 

1.5 

1.2 

. 9 

1.2 

Underlying 

bedrock unit2 

Do. 

Do. 

Do. 

Do. 

Do. 

Do. 

Roubidoux. 

Do. 

Do. 

Do. 

Do. 

Do. 

Do. 

Do. 

Do. 

Do. 

Jefferson City. 

Do. 

Do. 

Do. 

Do. 

Do. 

Do. 

Do. 

Do. 

Do. 

Osage. 

Do. 

Do. 

Do. 

Do. 

Do. 

Do. 

Do . 

Do. 

Do. 

Do. 

Do. 

Meramec. 

Do. 

Do. 

Do. 

Do . 

Do. 

Do. 

Do. 

Do. 

Do . 

Do. 

Do. 
ANALYTICALMETHODSANDDATAEVALUATION G9 

within sections, and S~ represents analytical variation. 

Geographic scales represented by these components 

are similar to the distances represented in the study of 

loess, except that S~ reflects variation arising at scales 

of about 3-150 km, and S~ reflects variation arising at 

scales less than about 3 km (the approximate dimension of a sampling locality). 

The highway study was employed (not wholly successfully) as a Stage 2a sampling scheme to design the 

final study (a Stage 2b scheme, Connor and others, 

1972). The final study was then used to estimate averages for each residuum unit. In the final study, 24 

samples of residuum were collected from each of seven 

units-the six units of the highway study plus the 

Gasconade residuum unit. In addition, the study areas 

for the Jefferson City and Osage residuum units were 

expanded to include areas of occurrence in northern 

Arkansas. The 24 samples in each unit were collected 

from six localities (each about 3 km across). These 

localities· were located randomly in each unit, two 

sampling sites were randomly located in a section of 

exposed residuum at each locality, and two samples 

were taken randomly from each section. The same statistical model was used in the final study as was used 

in the highway study (equation 8). Of the total of 168 

samples collected in the final study, 25 were split prior 

to analysis for estimation of analytical error. After 

chemical analysis, three samples-one each from localities 15, 27, and 30 (fig. 1)-were discarded because they 

contained too much carbonate for estimation of a proper geochemical background for residuum. Thus, the 

final study was based on the geochemistry of 165 

samples. 

The only important chemical resource in the surficial 

materials of Missouri is barite. Commercial quantities 

are mined from residuum in Washington County in 

southeastern Missouri (fig. 1). Accordingly, eight 

samples of barite ore that had been prepared for grinding were collected for trace element analysis from four 

milling sites and analyzed. No formal sampling design 

was used in this part of the study. 

ANALYTICAL METHODS AND DATA 

EVALUATION 

All analyses were performed in laboratories of the 

U.S. Geological Survey. The analytical data on which 

this report is based are given in Boerngen, Van Trump, 

and Ebens (1975), except for the data on barite, which 

are given below (table 13). The samples collected during the course of this work were analyzed for a variety 

of elements (table 3). Much of the trace element analysis was based on a semiquantitative emission spectrographic technique that was slightly revised from that 

described in Myers, Havens, and Dunton (1961). This 

technique was supplemented by methods based on 

X-ray fluorescence, atomic absorption, neutron activation analysis, and specialized techniques for determining fluorine and arsenic concentrations. Details of the 

analytical procedures are given in Miesch (1976). 

In the laboratory, each sample was ground in a ceramic mill to 150-J.tm (minus-1 00-mesh) particle size. 

Before being ground, a randomly selected subset of 

each material was divided into two parts with a splitter, so that analytical variance could be estimated. The 

samples of each material in each study were analyzed 

in a randomized batch. Each sample was routinely 

analyzed for 55 elements, one of these being carbon, 

which was measured in both its organic and inorganic 

(carbonate) forms. Then, depending on composition, 

some samples were checked for 15 additional elements, 

most of them rare-earth elements. Of this total, about 

30 elements were consistently detected. 

The frequency distributions of trace element determinations commonly exhibit a marked positive skewness-that is, low concentrations tend to be much more 

frequently observed than high concentrations. As a 

consequence, the average value in such a distribution 

may substantially exceed the most common, or expected, value (the mode), and the standard deviation 

may give rise to an unrealistic range in probable concentration. In order to circumvent such difficulties, 

summary statistics of most of the distributions in this 

study are based on logarithms of the data. The geometric mean (GM); defined as the antilog of the average of 

the logarithmic concentrations, is generally a less 

biased estimate of the median than the arithmetic 

mean. The geometric deviation (GD), defined as the antilog of the standard deviation of the logarithmic concentrations, is a factor useful in computing probable 

expected ranges in concentration. For example, if a 

distribution is lognormal, about 68 percent of the 

determinations in a randomly selected suite should fall 

within the range GMIGD to GM x GD. About 95 percent should fall within the range GM/(GD)2 to 

GMx (GD)2, and more than 99 percent should be 

- within the range GM/(GD)3 to GMx (GD)3

• 

Commonly, a suite of samples may contain one or 

more elements in concentrations too low to be 

measured by the analytical method used. In these 

cases the element distribution is said to be censored, 

and a problem arises as to how to estimate the mean 

and variance (or their logarithmic counterparts) in an 

unbiased manner. Miesch (1967, 1976) described procedures based on a method of Cohen (1959) which constitute an adjustment of the mean and variance computed for the uncensored part of the data. The same 

adjustment can be made if censoring occurs at the 

higher end of the distribution. 

Analysis of variance procedures, however, require 
GlO GEOCHEMISTRY OF LOESS AND CARBONATE RESIDUUM 

TABLE 3.-Analytical methods, with approximate lower limits of 

determination, for elements determined in the geochemical study of 

loess and residuum 

Element 

Ag-------

Al-------

As-------

B--------

Ba-------

Be-------

e (Tot)--

c (co3 )--

C (Org)--

Ca-------

Ca-------

Cd-------

Ce-------

Co-------

Cr-------

Cu-------

Dy-------

F--------

Fe-------

Fe-------

Ga-------

Gd-------

Hg-------

Ho-------

1--------

K--------

La-------

Li-------

Mg-------

Mn-------

Mo-------

Na-------

Nb-------

Nd-------

Ni-------

Analytical method 

Spectrographic---------------

X-ray fluorescence-----------

Colorimetric-----------------

Spectrographic---------------

----do-----------------------

----do-----------------------

r.asometric-------------------

----do-----------------------

Calculated-------------------

Spectrographic---------------

X-ray fluorescence-----------

Atomic absorption------------

Spectrographic---------------

----do-----------------------

----do-----------------------

----do-----------------------

----do-----------------------

F-selective ion electrode----

Spectrographic---------------

X-ray fluorescence-----------

Spectrographic---------------

----do-----------------------

Flameless atomic absorption--

Spectrographic---------------

Neutron activation-----------

X-ray fluorescence-----------

Soectrograohic---------------

Atomic absorption------------

----do-----------------------

Spectrographic---------------

----do-----------------------

Atomic absorption------------

Spectrographic---------------

----do-----------------------

----do-----------------------

P-------- X-ray fluorescence-----------

Ph------- Spectrographic---------------

Pr------- ----do-----------------------

Se------- ----do-----------------------

Se------- X-ray fluorescence-----------

Si------- Spectrographic---------------

Si------- X-ray fluorescence-----------

Sm------- Spectrographic---------------

Sr------- ----do-----------------------

Ti------- ----do-----------------------

Lower limit 

of determination (ppm) 

0.5 

5300 

1 

20 

1.5 

1 

400 

500 

1000 

20 

710 

1 

150 

2 

1 

1 

50 

10 

10 

700 

5 

70 

.01 

70 

830 

30 

5 

60 

1 

3 

74 

10 

70 

5 

130 

10 

150 

.2 

5 

.1 

20 

4700 

100 

5 

2 

v-------- ----do----------------------- 7 Y-------- ----do----------------------- 10 

Yb------- ----do----------------------- 1 

Zn------- Atomic absorption------------ 10 

Zr------- Spectrographic--------------- 10 

completely uncensored data, and the following arbitrary practice was used where necessary to circumvent 

problems of censoring. If less than a third of the frequency distribution of any element subjected to 

analysis of variance was censored, a value equal to 

approximately seven-tenths of the lower limit of determination was used in place of the censored values. The 

only justification for such a replacement is that 

substitution of any reasonable value below the 

analytical limit would not substantially alter 

geochemical conclusions drawn from the statistical 

analysis. 

Finally, the problem arises as to whether the area 

means (represented by one or more pairs of sampled 

stratigraphic sections of surficial material) are sufficiently different to form the basis of a geochemical 

map. If not sufficiently different, any resulting map 

may be unstable-that is, not generally reproducible 

by repetition of the field sampling and laboratory 

analysis. Thus, it is useful to identify those situations 

where the area means are sufficiently different to meet 

the criteria for geochemical mapping. Where these 

criteria are met, the means and associated statistics 

for the areas are given separately on tables and graphs 

summarizing the geochemical data. 

A basic criterion for the sufficiency of differences 

among area means is the conventional F-statistic, 

which is based on measures of variance between and 

within areas. If the F-statistic is found to be 

statistically significant, one can have a prescribed confidence that at least one of the areas is different from 

some other. However, this does not seem to be an adequate criterion for predicting whether the general configuration of a geochemical map would be reproducible. 

Several more stringent empirical criteria were described by Miesch (1976, p. A9-A10). The one used 

here requires that the variance of the area means, Es, 

be smaller than a critical value, Er. Er is the maximum 

permissible variance (at a given probability level) for 

an area mean where the F-statistic is defined as 

F = 1 + nrv, (10) 

where v for loess is defined as 

(11) 

and where v for residuum is defined as 

(12) 

In equation (10), F uses 1 and 2nr- 2 degrees of 

freedom for a test of significance at the 0.05 probability level. The term nr is the minimum number of randomly collected· samples needed from each area (if random sampling were employed) and can be read from a 

graph in Miesch (1976, p. A9). Es for loess is computed 

·as 
GEOCHEMICAL VARIABILITY Gil 

(13) 

and E s for residuum is computed as 

(14) 

The subscripted n's in equations (13) and (14) represent 

the number of sampling units at each level of the 

hierarchical design. In practice, nf in both equations is 

set to 1 because of incomplete duplication of sample 

splits. Further, in the highway study (residuum, equation 14), n0 was also set to 1 because of incomplete 

duplication of samples within each stratigraphic section. Finally, Er for loess is computed as 

(15) 

and Er for residuum is computed as 

(16) 

Where Er is larger than E 5 , the number of samples collected within each area (based on the hierarchy) is effectively less than the critical number, nr. required by 

the variance ratio, v (equations 11 and 12). 

GEOCHEMICAL VARIABILITY 

LOESS 

Loess consists principally of quartz and clay and 

contains minor amounts of dolomite, potassium-feldspar and plagioclase. X -ray diffraction traces of many 

samples show distinct peaks at the three common clay 

wavelengths (14, 10 and 7 angstroms), which likely 

represent mostly illitic and mixed-layer clay. The normative mineralogy is consistent with a composition of 

about 45-60 percent quartz (fig. 2), as much as 20 percent dolomite (fig. 3), and perhaps 25-40 percent illite 

(fig. 4). 

Samples with less than 90 percent normative quartz 

and illite combined tend to be rich in calcium or iron, 

but not both (fig. 2). The distribution of calcium in 

loess is distinctly bimodal; figure 3 demonstrates that 

the peak at about 3.5 percent CaO represents dolomite. 

The quartz-rich samples (L252, L143, L11, L12, L01, 

L113, and L13) and the dolomite-rich samples (L321, 

L09, L322, and LOS) were all collected from within a 

few kilometers of the Missouri or Mississippi floodplains, whereas many of the iron-rich (and clay-rich) 

samples (L381, L171, L292, and L291) were collected 

more than 50 km from floodplains. 

Iz 

w 

u 

a: 

w 

a. 

I-.. 

z 

w 

Iz 

0 

u 

85~----~--~~--~----~-----.-----. 

80 

L143x 

75 

EXPLANATION 

Ca-AND 

2:1 Fe-POOR Ca-RICH Fe-RICH 

SAMPLES SAMPLES SAMPLES 

Bluff 0 • 11 study 

L1 1o x 

L12 0 \ 00 

~ Y4J L01o xo 

L113x 6 b ::K 

L13 0 \ 

\~06 01 

.~ ::K ~ \ 

X 

6 

0 

<t. 

~ ? 

• • 

·-e 

1:1 % 

~ ~ 0 

N 70 •• DO 

0 

U5 ··~ ::K ~ 

LL. 

OCil 

w a:-l 

wa. 

m~ 

~<( 

::JCil 

z 

~ o,o 

LOB• ~ • • ·:~ ~ :t;i ll: t> 

0 ~L291 

eL322 L 171 ::K L

292 

65 L381t) 

eL321 

0

o 1 2 3 4 5 6 

PERCENT Fe20 3 

~ 

~PERCENT 

QUARTZ 

+ILLITE 

COMBINED 

A 

FIGURE 2.-Variation of Si02 and Al20 3 in loess samples having 

various contents of Fe20 3 and CaO (A), and the distributions of 

Fe20a (B) and CaO (C) in loess samples. Iron-rich samples Qave 

Fe20 3_2_4.5 percent; calcium-rich samples have CaO _2_2 percent; 

calcium- and iron-poor samples have lesser amounts of both contituents. Compositions of normative quartz and illite shown. The illite composition is that of Weaver and Pollard (1973, p. 9)'and contains 26 percent Al20 3 and 50 percent Si02• 
G12 GEOCHEMISTRY OF LOESS AND CARBONATE RESIDUUM 

1-

z 

w 

u 

a: 

w 

CL 

~ a1 0.7 

1-

z 

0 

u 0.5 

0 

C) 

~ 

0 l::l 

X 

• 

. {. ,<:),~··· .,,7, .. 

•• • • • 

EXPLANATION 

Ca- AND 

Fe- POOR Ca-RICH Fe- RICH 

SAMPLES SAMPLES SAMPLES 

Bluff study 0 • I] 

Transects 

No. 1 X ::K 

No. 2 l::l • ~ 

No. 3 0 • () 

1.5 2 3 5 7 10 

PERCENT 

FIGURE 3.-Variation of CaO and MgO in loess. Samples grouped as iron-rich, calcium-rich, and iron- and calcium-poor, as defined in figure 2. 

Composition of normative dolomite shown. 

X-ray work suggested the presence of potassiumpoor clay phases (such as kaolinite and montmorillonite), and the relation of potassium to aluminum (fig. 4) 

supports this suggestion in that the clay appears to be 

poorer in potassium than common illite (Weaver and 

Pollard, 1973, p. 9). Because the feldspar in the 

loess also requires potassium in its composition, the 

aluminum-potassium ratios in figure 4 reflect a complex of potassium- and aluminum-bearing minerals. 

The dashed line represents a mixture of illite, kaolinite, 

and potassium feldspar that appears to be reasonable 

for average loess, particularly if the loess is dolomitic 

(high CaO). Permissible percentages of these three normative minerals are shown in boxes around the boundaries of the plotted points. 

BLUFF STUDY 

The loess capping the bluffs along the Mississippi 

and Missouri Rivers was sampled to assess the magnitude of geochemical change occurring in these deposits 

along the river. The analysis of variance (table 4) suggests that in the main there is little such variation. 

: Only barium, phosphorus and strontium exhibit statistically significant components of regional geochemical 

variance (S~). Area (segment) averages for these 

elementcS were examined for stability as described 

above. Es was computed by 

(17) 
GEOCHEMICAL VARIABILITY G13 

I- 2.5 

z 

w 

u 

a: 

w 

a.. 

t-=' ~ 5 

0 

z 

w 

Iz 

0 

u 

0 N 

~ 1.5 Ca- AND 

Fe-POOR Ca-RICH Fe-RICH 

1-··' SAMPLES SAMPLES SAMPLES 

~~~ Bluff study o • ll 

oV~\ Transects 

.~ No. 1 X )I( 

~~. No. 2 6 A 1::, 

\\..0 No. 3 0 e () 1·0s'--_,.£_ __ ----~.8 ____ ___J_10 _____ 1_L2 ___ :..___J14 

AI203 CONTENT, PERCENT 

FIGURE 4.-Variation of Al20 3 and K20 in loess. Samples grouped as 

iron-rich, calcium-rich, and iron- and calcium-poor as defined in 

figure 2. The boxed numbers are permissible percentages of normative illite (top), kaolinite (middle), and potassium feldspar (bottom). The dashed line represents a ratio of illite:kaolinite:feldspar of 

10:2:1. 

The pertinent parameters for this estimation are listed 

below: 

Ele~ent v nr Er Es 

Ba 1.21 5 0.0012 0.0015 

p .57 7 .0033 .0071 

Sr .84 6 .0011 .0016 

Area averages based on the data collected from the 

river bluffs are not sufficiently stable according to the 

criterion used (E5 >Er), and additional data are required 

if area averages are to be computed for these three 

elements. 

Between-locality variance (S~) is significant for 

calcium and magnesium, which reflects variation of 

dolomite, and for chromium, potassium, lithium, 

sodium, nickel, titanium, and zirconium. Variation in 

potassium and sodium may reflect variation of feldspar, and variation of nickel, chromium, titanium, and 

zirconium could reflect variation of clay or heavy 

mineral content or both. Overall, however, loess in the! 

river bluffs in Missouri is rather uniform in chemical 

composition. Only 11 of the 35 constituents listed in 

table 4 exhibit more than half of their total variation as 

variation between localities (S~ + S~ ). They are 

barium, calcium, chromium, potassium, lithium, 

magnesium, sodium, nickel, phosphorus, titanium, and 

zirconium. 

TRANSECT STUDY 

Geochemical variation transverse to major drainage 

was examined by regression analysis of data collected 

along three transects (fig. 1). The parameters for each 

fitted trend (equation 4) are given in table 5 along with 

the correlation of geochemical variation with distance. 

Each equation predicts the concentration for that constituent in loess at various distances from the Missouri 

River drainage. Most of the statistically significant 

trends are plotted in figures 5 and 6. 

As noted above, calcium decreases (fig. 5) and iron 

increases (fig. 6) away from the source (the floodplain). 

Trends in magnesium and carbon (not shown). parallel 

those in calcium (fig. 5) because all three are major 

components of dolomite, whose occurrence largely con-, 

trois their distributions. Concentrations of phosphorus, barium, manganese, and strontium (fig. 5) also 

decrease with distance in one or more of the transects. 

The trend in manganese is so weak that suppression of 

either the first or the last sampling locality would 

result in a nonsignificant trend. Variation in phosphol"l.JS may reflect variation of apatite. The trends in 

barium and strontium are similar to those in potassium and sodium (fig. 5), and all four elements largely 

reflect a decrease in feldspar with distance. These 

trends, along with decreases in silicon (quartz) and zirconium (zircon), indicate that small but apparently real 

decreases in the common rock-forming minerals .dolomite, apatite, feldspar, quartz, and zircon occur downwind of the source. 

In contrast, a number of clay-related elements increase downwind of the source (fig. 6). These trends are 

about as weak as most of the decreasing trends arid 

many (specifically copper, selenium, aluminum, and 

iron along transect 1; arsenic and vanadium along 

transect 2; and arsenic along transect 3) would be nonsignificant if the first or the last sampling locality 

were suppressed. Nevertheless, the overall pattern in 

figure 6 seems real and is antithetic to the pattern in 

figure 5. The pattern in figure 6 reflects an increase in 

clay content with distance, probably at the expense of 

quartz (mostly) and dolomite. 

Two obvious causes of the geochemical change with 

distance seen here are (1) more thorough weathering of 

the thinner loess deposits, and (2) elutriation of the 

original windborne material by wind fractionation. 

Hall (1977) found in southwest Indiana that soil 

development in Wisconsin loess tended to increase as 

the loess thinned away from source, and Rieger and 

Juve (1961) in Alaska found soil development during 
G14 GEOCHEMISTRY OF LOESS AND CARBONATE RESIDUUM 

TABLE 4.-Comparison of estimated logarithmic variance components for loess in bluffs along the Mississippi and Missouri Rivers in Missouri 

[Asterisk (*), significantly different from zero at the 0.05 probability level] 

Total log10 Between segments Between localities 

Element 

Al-------

As-------

B--------

Ba-------

Be-------

C (co3)--

C (Org)--

Ca-------

Co-------

Cr-------

Cu--------

F---------

Fe--------

Ga--------

Hg--------

1--------- K---------

La--------

Li--------

Mg--------

Mn--------

Na--------

Ni--------

P---------

Pb--------

variance 

<siogx) 

0.0019 

.0193 

.0273 

.0128 

.0074 

.5826 

.0443 

.1203 

.0123 

.0041 

.0136 

.0276 

.0020 

.0039 

.0635 

.0174 

.0028 

.0152 

.0088 

.0693 

.0518 

.0068 

.0149 

.0360 

.0128 

Se-------- .0935 

Sc-------- .0052 1 Si-------- 13.13 

Sr-------- .0118 

Ti-------- .0187 

v--------- Y---------

Yb--------

Zn--------

Zr--------

.0074 

.0223 

.0192 

.OllO 

.0143 

Component Percent 

2 

s6 of total 

0.0004 

.0030 

.0028 

.0070* 

<.0001 

<.0001 

.0045 

<.0001 

<.0001 

.0003 

<.0001 

<.0001 

<.0001 

<.0001 

.0133 

.0123 

.0008 

<.0001 

<.0001 

<.0001 

.0015 

.0001 

<.0001 

.0130* 

.0019 

<.0001 

.0002 

<.01 

.0054* 

.0017 

<.0001 

<.0001 

<.0001 

<.0001 

<.0001 

21 

15 

10 

55 

<1 

<1 

10 

<1 

<1 

7 

<1 

<1 

<1 

<1 

21 

17 

29 

<1 

<1 

<1 

3 

1 

<1 

36 

15 

<1 

4 

<1 

46 

9 

<1 

<1 

<1 

<1 

<1 

Component Percent 

2 

sy of total 

(0.0001 

<.0001 

<.0001 

<.0001 

.0001 

.0942 

<.0001 

.0804* 

.0009 

.0020* 

.0040 

.Oll3 

.0007 

.0007 

<.0001 

.0190 

.0013* 

.0055 

.0060* 

.0467* 

<.0001 

.0041* 

.0079* 

.0055 

<.0001 

<.0001 

<.0001 

4.92 

<.0001 

.0087* 

.0001 

.0042 

<.0001 

.0039 

.0085* 

<1 

<1 

<1 

<1 

1 

16 

<1 

67 

7 

49 

29 

41 

35 

18 

<1 

27 

46 

36 

68 

67 

<1 

60 

53 

15 

<1 

<1 

<1 

37 

<1 

47 

1 

19 

<1 

35 

59 

Between samples 

Component Percent 

2 

s~ of total 

O.OOll 

.0015 

.omn 

<.0001 

<.0001 

.4104 

<.0001 

.0383 

.0022 

.0018 

.0044 

<.0001 

.0013 

.0006 

<.0001 

.0387 

.0006 

<.0001 

.0023 

.0220 

.0432 

.0013 

.0070 

.0001 

<.0001 

<.0001 

.0010 

7.21 

.0012 

.0083 

.0073 

.0047 

.OllO 

.0062 

<.0001 

58 

8 

30 

<1 

<1 

70 

<1 

32 

18 

44 

32 

<1 

65 

15 

<1 

54 

21 

<1 

26 

32 

83 

19 

47 

<1 

<1 

<1 

19 

55 

10 

44 

99 

21 

57 

56 

<1 

1variance calculated on nontransformed data rather than log data. 

Between replicates 

Component Percent 

2 

se: of total 

0.0004 

.0148 

.0164 

.0058 

.0073 

.0780 

.0398 

.0016 

.0092 

<.0001 

.0052 

.0163 

<.0001 

.0026 

.0502 

.0014 

.0001 

.0097 

.0005 

.0006 

.0071 

.0013 

<.0001 

.0174 

.0109 

.0935 

.0040 

1.0 

.0052 

<.0001 

<.0001 

.0134 

.0082 

.0009 

.0058 

21 

77 

60 

60 

99 

13 

90 

1 

75 

<1 

38 

59 

<1 

67 

79 

2 

4 

64 

6 

1 

14 

19 

<1 

48 

85 

100 

77 

8 

44 

<1 

<1 

60 

43 

8 

41 

active loess deposition to be fastest in those places 

where deposition was slowest. Similar processes 

almost certainly operated in northwest Missouri during loess deposition there. However, the prevalence of 

element concentrations that follow conventional exponential decay-type curves (fig. 5) strongly suggests 

elutriation by wind as the major cause. The apparent 

decrease with distance in quartz, dolomite, apatite, 

feldspar, and zircon indicates mineral sorting. The 

mineral sorting in loess noted by Ruhe (1969) 

underscores the importance of this mechanism. 

geochemical character of loess is different in deposits 

far from the source than it is in deposits near the 

source (bluff loess). In order to take such differences 

into account in defining the geochemical background 

for loess in Missouri, a selected subset of the transect 

samples was used to geochemically characterize the deposits away from the bluffs (table 6). The samples selected for this subset were from deposits that appeared 

to be thin (commonly less than 6 m), heavy textured 

(clay-rich), and locally mottled red, yellow, or white. 

Some of this loess may contain weathered till. 

The patterns in figures 5 and 6 demonstrate that the Finally, for purposes of comparison, summary data 
GEOCHEMICAL VARIABILITY G15 

TABLE 5.-Regression of loess chemistry with distance east of the Missouri River floodplain 

(a. b, defined in equation (41; r, correlation of geochemical property and distance; asterisk(*), r significantly different from zero at the 0.05 probability level; Ratio, number of samples in 

which constituent was detected to total number of samples analyzed; data in parts per million except where noted as percent (pcU. Leaders (-I indicate insufficient data for computation) 

Geochemical Transect 

Property 

a b r Ratio a 

Log Al 2o3, pet--- 1.01 0.035 0.41* 21:21 0.99 

As----------- 1.07 .028 .15 21:21 1.05 

B------------ 1.41 -.007 -.05 21:21 1.38 

Ba----------- 3.01 -.020 -.20 21:21 3.02 

Total c, pet- -.57 .049 .17 21:21 -.17 

CaO, pet----- -.08 -.109 -.53* 21:21 .36 

Co----------- .89 .076 .34 21:21 .86 

Cr----------- 1. 78 .017 .15 21:21 1. 73 

Cu----------- 1.20 .062 .39* 21:21 1.21 

F------------ 2.62 .019 .12 21:21 2.65 

Fe2o3, pet--- .58 .056 .44* 21:21 .56 

Ga----------- 1.10 .028 .20 21:21 1.11 

Hg----------- -1.60 .049 .13 20:21 -1.50 

K2o, pet----- .39 -.017 -.33 21:21 .39 

La----------- 1.60 .044 .26 15:21 

Li----------- 1.35 .053 . 72* 21:21 1.33 

MgO, pet----- -.02 .030 .20 21:21 .24 

Mn----------- 2. 72 -.083 -.21 21:21 2.68 

Na2o, pet---- .09 -.048 -.42* 21:21 .12 

Ni----------- 1.32 -.011 -.04 21:21 1.30 

P2os--------- 3.23 -.108 -.46* 21:21 3.28 

Pb----------- 1.19 -.010 -.22 21:21 1.18 

Sc----------- .90 .064 .43* 21 :21 .86 

Se----------- -.99 .258 .50* 14:21 -.93 

Sio2, pet-------- 73.1 -2.4 -.43* 21:21 70.1 

Log Sr----------- 2.28 -.035 -.34 21:21 2.30 

v------------ 1.95 .032 .20 21:21 1.90 

Y------------ 1.42 -.021 -.14 21:21 1. 29 

Yb----------- .47 -.007 -.11 21 :21 .36 

Zn----------- 1.84 .015 .12 21:21 1.85 

Zr----------- 2.24 -.064 -.40* 21:21 2.14 

for dolomite-bearing loess are given in the middle 

column of table 6. Most of the dolomite-bearing 

samples were collected from the region in northwesternmost Missouri where the maximum thickness 

of capping loess is 10 m or· more (fig. 1 ). Thus,' these 

data should prove most useful in that particular area of 

the State, although carbonate-bearing loess locally occurs in bluffs all along the Missouri River in the State. 

Ray (1967, p. D224) suggested that loess in western 

Kentucky originally had a uniform carbonate content, 

and that the present variation in the carbonate of those 

deposits reflects a variable degree of leaching during 

deposition (the slower the deposition, the greater the 

leaching). In general, calcite is leached before dolomite, 

and the smaller carbonate grains are leached before the 

larger. A similar history of carbonate in loess along the 

Missouri River would account for the erratic distribution of dolomite noted in those deposits. 

Transect 2 Transect 3 

b r Ratio a b r Ratio 

0.035 0.53* 27:27 0.99 0.054 0.78* 24:24 

.024 .36* 27:27 .93 .054 .35* 24:24 

-.020 -.17 26:27 1.35 .023 .18 24:24 

-.083 -.53* 27:27 3.01 -.025 -.40* 24:24 

-.196 -.54* 27:27 -.13 -.217 -.48* 24:24 

-.332 -.80* 27:27 .46 -.326 -.77* 24:24 

.056 .37* 27:27 .90 .032 .21 24:24 

.030 .32 27:27 1.77 .019 .18 24:24 

.004 .03 27:27 1.19 .048 .53* 24:24 

.002 .01 27:27 2.66 .047 .38* 24:24 

.050 .56* 27:27 .53 .070 .79* 24:24 

-.003 -.03 27:27 1.07 .070 .63* 24:24 

-.014 -.04 26:27 -1.67 .099 .29 22:24 

-.038 -.51* 27:27 .39 -.013 -.21 24:24 

12:27 8:24 

.079 .82* 27:27 1.34 .075 .82* 24:24 

-.164 -.68* 27:27 .30 -.160 -.68* 24:24 

-.156 -.50* 27:27 2.50 .016 .05 24:24 

-.073 -.57* 27:27 .14 -.051 -.57* 24:24 

-.026 -~15 27:27 1.25 .038 .25 24:24 

-.248 -.64* 22:27 3.19 -.110 -.28 21:24 

.009 .18 27:27 1.17 .005 .07 24:24 

.063 .63* 27:27 .84 .088 .79* 24:24 

.163 .47* 21:27 16:24 

.3 .06 27:27 69.4 .2 .OS 24:24 

-.073 .58* 27:27 2.30 -.016 -.24 24:24 

.041 .36* 27:27 1.88 .100 .74* 24:24 

.029 .24 27:27 1. 30 .034 .22 24:24 

.045 .42* 27:27 .35 .056 .44* 24:24 

-.011 -.09 27:27 1.82 .033 .30 24:24 

.077 .OS 27:24 2.12 .002 .01 24:24 

In spite of these geochemical distinctions, differences between bluff loess, non-bluff loess, and dolo-

·mite-bearing loess are minimal, the exception being 

that carbon, calcium, and magnesium occur in the 

dolomite-bearing loess in concentrations twice as high 

as in the other types. Other observed differences are 

very minor and may not be significant; these include 

higher boron, iodine, and yttrium and lower fluorine in 

bluff loess; lower selenium and ytterbium in dolomitebearing loess; and higher arsenic and selenium and 

lower phosphorus in loess away from the river bluffs. 

RESIDUUM 

Like loess, residuum is composed principally of 

quartz and clay. However, the residuum is everywhere 

much more iron rich than loess, and the quartz in 
G16 GEOCHEMISTRY OF LOESS AND CARBONATE RESIDUUM 

80 

75 

70 

65 

7 

5 

1-

z 3 w 

u 

a: 2 w 

a.. 

~ 1 

0 .......... 6 

................................................ 0 g ............................................. ---c.... ..................... 

........................................ -.................... 

( i~j---:_- ~-:-l. X X .j. X ~--

1.5L......l.----L------'---L-----'-------1.--L..---....L----L.J 

:~-~-~-~-i-~-~--[~o~ 

0.5L....l----'---'-----'------l...-----'--.l,__-_J,_ 

:·;r:~~=ra2~ _ ___u 

z 

0 3 500 

EXPLANATION 

Sample 

X 

6 

0 

Trend 

~ 300~-~--.1,__--L----L------1.--~-~-~ 

; :~[--~=~=~t=~~~~i~~ 

z 

0 

~ a: 

1-

z 

w 

u 

z 

0 

u 

--

6 ~--6---6.-_A, 6 

6 ~ --;;:---

~ ~ ~ ; ~ ; : il ~ ~~r-~-~--~-~--~-~-;~~-j 0.03 ~ 0.02 

0.015 

0.01 

0.75 1.5 3 6 12 24 48 96 192 0.75 1.5 3 6 12 24 48 96 192 

DISTANCE EAST OF FLOODPLAIN, IN KILOMETERS 

FIGURE 5.-Chemical concentrations in loess that decrease as a function of distance east of the Missouri River floodplain. 

residuum occurs mostly as large fragments rather than 

as sand or silt. Compositions of residuum samples are 

plotted in figure 7, in the same type of plot used for the 

loess samples (fig. 2). The approximate outline of variation of loess is noted, showing clearly that residuum is 

much more variable than loess. The iron-rich nature of 

residuum is indicated by the fact that 28 samples contain more than 10 percent Fe20 3• Sample ROl (from the 

Bonneterre residuum unit) contained more than 20 percent Fe20 3, and samples P023 and P024R (from the 

Potosi unit) each contained more than 30 percent 

Fe20s. 

Most samples lie within a normative composition 

based on a simple mixture of quartz and common illite. 

The samples richest in aluminum have compositions 

equivalent to mixtures of normative quartz and 

kaolinite or of quartz, illite, and kaolinite. (See dashed 

line, fig. 7 .) Samples poorest in aluminum (including 

RIO, R052, RlOD and RllD, all from the arenaceous 

Roubidoux unit) consisted of more than 90 percent normative quartz. 

Residuum is distinctly poorer in potassium than 

loess (fig. 8), although a few samples from the Bonneterre, Roubidoux, and Jefferson City units (R062, 

. R02D, J042, J054R, B052, B054, ROl, and R02) are so 

potassium-rich as to suggest the presence of minor 

amounts of muscovite or potassium feldspar. The 

boxed numbers in figure 8 show permissible percentages of normative illite and kaolinite in residuum. On 

average, residuum consists of about 50 percent total 

clay, slightly more than that estimated for loess. 

Although three samples containing visible dolomite 

were excluded from the geochemical evaluation of 

residuum, more than 10 percent normative carbonate 

appeared in the norms of 11 other samples (fig. 9). Sample R07 (from the Potosi unit in the highway study) 

contained nearly 30 percent normative dolomite. 

Samples Rl7, R18D, and R31 (from the Osage and 

, Meramec units) contained more than 10 percent normative calcite. The carbonate in these samples is probably interspersed through chert fragments. CaO and 

MgO concentrations in the calcium-poor samples from 
GEOCHEMICAL VARIABILITY G17 

FIGURE 6.-Chemical concentrations in loess that increase as a function of distance east of the Missouri Ri~er floodplain. 

the Bonneterre, Potosi, Gasconade, Roubidoux, and 

Jefferson City units (circles) are positively correlated 

(in logarithms, r = 0.64), suggesting that these 

samples may contain small amounts of dolomite (1-5 

percent). The regression line fitted to these points 

demonstrates that the excess of MgO over that needed 

for the dolomite is about 0.7-1 percent, which could occur in 30-50 percent illitic or montmorillonitic clay. 

HIGHWAY STUDY 

Statistical tests of scale-related geochemical variation in residuum of the highway study are summarized 

in table 7. All but five elements (carbon, mercury, 

phosphorus, selenium, and zirconium) exhibit 

statistically significant variation (S~) among the six 

residuum units. In particular, three elements of 

economic interest-lead, copper, and zinc-exhibit approximately half or more of their total observed varia-

, tion at this scale of the design. This high percentage 

reflects the fact that six samples of the Potosi unit, collected in or near the Washington County barite 

district, an area of known anomalous lead, copper, and 

zinc in residuum (Ebens and Connor, 1977), were 

unusually high in these elements. Maximum concentrations measured in these six samples were 0.27 percent zinc (in sample R08D), 0.3 percent lead (sample 

' R05), and 10 percent barium (sample R08). 

The general lack of variability between sampling 

localities within units (S~) is more apparent than real 

and, as will be seen below in the section describing 

results of the final study, residuum within each unit 

does in fact vary in a geochemically significant 

fashion. The failure of the highway study to show that 

variation is due to the sampling bias arising from the 

restriction of sampling to a few major highways. 

Variation at local scales is large for many elements. 
GIS GEOCHEMISTRY OF LOESS AND CARBONATE RESIDUUM 

TABLE 6.-Geochemical summary of loess .in Missouri 

(GM, geometric mean; GD, geometric deviation; GE, geometric error; Ratio, number of samples in which element was determined to total number of samples analyzed. Leaders(···' indicate 

insufficient data for computation. Geometric means are in parts per million except where noted as percent (pet' or parts per billion (ppbH 

Element Loess in bluffs Dolomite-bearing loess 1 Loess away from bluffs 2 

GM GD GE Ratio GM GD Ratio GM GD GE Ratio 

Al2o3, pet---

As-----------

B------------

Ba-----------

Be-----------

C, pet: 

Total------

Carbonate--

Organic----

CaD, pct-----

Cd-----------

9.8 

8.3 

39 

840 

.95 

.30 3 .05 

.13 

1.2 

<1 

Ce----------- <100 

Co----------- 9.8 

Cr----------- 70 

Cu----------- 18 

F------------ 290 

Fe2o3 , pct---

Ga-----------

Hg, ppb------

1------------

K2o, pet-----

La-----------

Li-----------

MgO, pct-----

Mn-----------

Mo-----------

Na2o, pct----

Nb-----------

Ni-----------

P2o5, pct----

Pb-----------

Se-----------

Se-----------

"Sio2, pct----

Sr-----------

v------------

Y------------ Yb----------- Zn----------- Zr-----------

3.4 

16 

35 

1.2 

2.3 

42 

23 

1.1 

510 

<3 

1.3 

(10 

22 

.14 

15 

9.0 

.18 

73 

220 

93 

32 

3.5 

61 

230 

1.09 

1.33 

1.36 

1.26 

1.17 

2.43 

1.53 

1.96 

1.05 

1. 32 

1.34 

1.19 

1.22 

1.90 

1.58 

1.10 

1.28 1.25 

1.16 (1.03 

1.30 1.18 

1.42 1.34 

1.10 (1.03 

1.14 1.12 

1.62 1.68 

1.83 1.09 

1.13 (1.03 

1.31 

1.20 

1.66 

1.54 

1.25 

1.05 

1.06 

1. 21 

1.21 1.09 

1. 29 (1.03 

1.53 1.35 

1.27 1.27 

1.18 

2.00 

3.2 

1.26 

1.21 

1. 36 

1.34 

1.25 

1.29 

1.16 

2.02 

1.0 

1.18 

<1.03 

1. 31 

1.23 

1.07 

1.19 

24:24 

24:24 

24:24 

24:24 

18:24 

24:24 

22:24 

24:24 

24:24 

0:24 

2:24 

24:24 

24:24 

24:24 

24:24 

24:24 

24:24 

23:24 

24:24 

24:24 

24:24 

24:24 

24:24 

24:24 

0:24 

24:24 

4:24 

24:24 

24:24 

24:24 

24:24 

19:24 

24:24 

24:24 

24:24 

24:24 

24:24 

24:24 

24:24 

9.6 

9.2 

26 

940 

<1 

,97 

.59 

.18 

3.1 

<1 

(100 

8.1 

61 

17 

420 

3.4 

13 

28 

.76 

2.4 

34 

21 

2.2 

380 

<3 

1.3 

(10 

19 

.15 

15 

7.4 

.14 

68 

210 

83 

22 

2.5 

68 

140 

1.09 

1.37 

1.37 

1.23 

1.50 

3.20 

1.99 

1.34 

1.27 

1.22 

1.24 

1.28 

1.07 

1.22 

1.48 

1.84 

1.05 

1.37 

1.10 

1.21 

1.65 

1.06' 

1.28 

1.52 

1.16 

1.15 

1.80 

2.4 

1.12 

1.24 

1.31 

1.29 

1.16 

1.28 

23:23 

23:23 

23:23 

23:23 

5:23 

23:23 

22:23 

23:23 

23:23 

4:23 

0:23 

23:23 

23:23 

23:23 

23:23 

23:23 

23:23 

23:23 

7:7 

23:23 

10:23 

23:23 

23:23 

23:23 

2:23 

23:23 

0:23 

23:23 

22:23 

23:23 

23:23 

18:23 

23:23 

23:23 

23:23 

23:23 

23:23 

23:23 

23:23 

11.3 

12 

24 

900 

1.2 

.32 

<.01 

.67 

<1 

(100 

9.4 

63 

18 

470 

4.4 

14 

29 

2.3 

45 

27 

.99 

370 

<3 

1.1 

7.1 

20 

.11 

15 

9.4 

.21 

71 

170 

100 

23 

2.8 

72 

140 

1.12 

1.28 

1.24 

1.26 

1.27 

<1.03 

1.14 

1.23 

1.14 

1. 52 1.19 

1.31 (1.03 

1.34 

1.17 

1.23 

1.27 

1.29 

1.20 

1.27 

1.18 

1.17 <1. 03 

1.19 1.16 

1. 80 1.40 

1.13 <1. 03 

1.19 1.26 

1.14 (1.03 

1.26 (1.03 

1.88 1. 30 

1.22 

1.29 

1.42 

1. 74 

1.12 

1.18 

1.88 

3.2 

1.21 

1.23 

1.27 

1.15 

1.23 

1.31 

1.05 

1.34 

1.25 

1.08 

1.16 

1.52 

.83 

1.08 

(1.03 

1.16 

1.16 

1.11 

1.28 

1 Twenty-three samples of loess were used in computing these statistics. Bluff loess 

samples were REOL-07, 08, 09, 15, 17, 23, and 24. Transect loess samples were E2L-211, 212, 

213, 221, 222, 223, 311, 312, 321, 322, 323, 331, 332, 333, 342, and 343. 2 0nly samples from localities 13 (excepting samples E2L-111, 112, and 113), 21, 22, 

23, 24, 28, 29, and 30 were used in computing these statistics. 

'This average is a median. 

"Summary statistics given as arithmetic means, standard deviations, and standard errors. 

39:39 

39:39 

38:39 

39:39 

15:39 

39:39 

1:7 

7:7 

39:39 

5:39 

0:39 

39:39 

39:39 

39:39 

39:39 

39:39 

39:39 

36:39 

0:0 

39:39 

27:39 

39:39 

39:39 

39:39 

1:39 

39:39 

10:39 

39:39 

33:39 

39:39 

39:39 

33:39 

83:83 

39:39 

39:39 

39:39 

39:39 

39:39 

39:39 

Fourteen elements differ in a significant way between 

sections (S~) spaced as much as 3 km apart. The 

presence of a clay-related suite of elements (aluminum, 

lithium, scandium, vanadium, yttrium, and ytterbium) 

and a carbonate-related suite (calcium, magnesium, 

and strontium) suggests that differences among these 

closely spaced sections reflect simple variation in carl bonate content and perhaps also in chert content, in-
GEOCHEMICAL VARIABILITY G19 

100.----------r----------r---------~--------~ 

1-

z 

w 

u 

a: 

w 

a.. 

t-' 

~ 60 

1-

z 

0 

u 

0 

u; 50 

40 

30 

0 

Fe- POOR 

0 

0 

EXPLANATION 

Fe- RICH 

• 

UNDERLYING ROCKS 1 

Bonneterre unit, 

Potosi-Eminence unit, 

Gasconade unit, 

Jefferson City unit 

Roubidoux unit 

Osage unit, 

Meramec unit 

1 McCracken (1961) 

A 

2~~--------~170--------~~--------~--------~40 

en 

w 

~ 

a.. 

~ 

<( 

en 

LL 

0 

a: 

w 

a:l 

~ 

::> 

z 

Al 20 3 

80.--=~~--~--------~ 

Fe- RICH 

8 

10 20 30 40 

PERCENT Fe20 3 

FIGURE 7.-Variation of Si02 and Al20 3 (A) and the distribution of 

Fe20a (B) in residuum. Samples grouped as iron-rich ( ) 10 percent 

Fe20aJ and iron-poor (_llO percent Fe20 3). Composit~ns of normative quartz (0), illite (I), and kaolinite (K) shown. 

I-

.z 

w 

u 5 a: 

w 

Q.. 

~--- 4 z 

w 

Iz 

0 

u 

0 N 

~ 

~ 

8 12 16 20 24 

Al20 3 CONTENT, PERCENT 

EXPLANATION 

Fe- POOR Fe- RICH UNDERLYING ROCKS 1 

0 

0 

6 

• Bonneterre unit, 

Potosi-Eminence unit, 

Gasconade unit, 

Jefferson City unit 

Roubidoux unit 

Osage unit, 

Meramec unit 

1 McCracken ( 1961) 

32 

FIGURE B.-Variation of Al20 3 and K20 in residuum. Samples 

grouped as iron-rich and iron-poor, as defined in figure 7. The boxed 

numbers are permissible percentages of normative illite (top) and 

kaolinite (bottom). 

asmucli as silicon shows significant variation also. 

Variation between sections and between samples combined (S! + Sh) exceeds 50 percent of the total observed variation for 19 elements and indicates a high 

degree of geochemical heterogeneity in residuum at 

local scales. 

The strong geochemical differences among the 

residuum units prompted a second sampling effort 

aimed at quantifying these differences. An attempt 

was made to collect enough samples from each unit to 

produce realistic geochemical averages. Based on the 

variance components in table 7, a final sampling 

design was set up using six localities within each unit, 

two sections in each locality, and two samples from 

each section. Thus, the final sampling involved 24 

samples from each unit (in contrast to the six samples 

per unit of the highway design). Table 8 gives the 

parameters used to assess sampling requirements in 

residuum. E 5 is the basic criterion used in this assessment; E 5 (1) is computed for the highway sampling and 

E 5 (2) is estimated for the final sampling. 
G20 GEOCHEMISTRY OF LOESS AND CARBONATE RESIDUUM 

1-

z 

w 

u 

a: 

w 

a.. 

1--

z 1 w 

!z 0 0.7 

u 

0 0.5 Cl 

~ 

(S~) is much less in . this study and the variance 

estimated between localities (S0) is correspondingly 

enhanced. These changes reflect the fact that the 

localities used within each unit of the highway study 

were spaced less than 50 km apart on the average 

(fig. 1 ), but the localities in the final study were spaced 

150 km apart on the average. Thus, the between-unit 

component (S~) in the highway study includes variance 

at scales which in the final study are part of the between-localities component (S~). 

For many elements, the total observed variance in 

the highway study (table 7) is nearly 2-3 times that 

estimated in the final study (table 9). Part of this contrast reflects the fact that 23 samples from Washington County were excluded from the analysis of 

variance in table 9 because they were anomalously 

o.~':-.1 ~=--=-':---'--_._--~....----.~.._..J...._..J....___J_ _ ___j___J__L_____j_____j____J high in barium, lead, copper, and zinc (fig. 10). Thus, 0.5 0.7 1 1.5 2 3 5 10 15 20 30 fl d . . h al . h 

cao CONTENT, PERCENT the in ate variances seen 1n t ese met s 1n t e 

Fe- POOR 

0 

EXPLANATION 

Fe-RICH UNDERLYING ROCKS1 

• Bonneterre unit, 

Potosi-Eminence unit, 

Gasconade unit, 

Jefferson City unit 

Roubidoux unit 

Osage unit, 

Maramec unit 1 McCracken ( 1961) 

FIGURE 9.-Variation of CaO and MgO in residuum. Samples 

grouped as iron-rich and iron-poor, as defined in figure 7. Compositions of normative calcite and dolomite shown. The dashed line is 

the regression of CaO on MgO for low-CaO residuum samples collected over pre-Mississippian bedrock. 

S2 S!+Sb+S! E 8 (1) =~+ (18) 2 4 

s2 s2 sb + s~ E 8 (2) =~+-K-+ (19) 6 12 24 

Even though the geochemical differences among the 

six units (as indicated by the analysis of variance, 

table 7) are large, the data of the highway study are 

judged to be too few for computation of satisfactory 

averages for each residuum unit (E8 (1) ) Er). The sampling load of the final design, however, should be sufficiently large (E8 (2) ~Er). In fact, for some geochemical 

constituents, the sampling bias in the highway study 

(noted above) resulted in an underestimation of therequired sampling load. 

FINAL STUDY 

The analysis of variance of residuum collected in 

the final study is given in table 9. The results of 

this analysis differ from those of the highway study 

(table 7) in that the variance estimated between units 

I 

highway study (table 7) have been reduced in the final 

study to values more commensurate with the other 

trace elements listed in table 8. Overall, though, the inflated estimates of total variance in the highway study 

may be related to the bias in the selection of localities. 

Nevertheless, the analysis of variance in the final 

study (table 9) confirmed that a number of geochemical 

differences in fact exist among the seven residuum 

units studied. A clay-related suite of elements (aluminum, beryllium, chromium, gallium, lithium, scandium, 

vanadium, yttrium, and ytterbium) exhibits significant between-unit variance, as do two ore metals (copper and zinc) and iron and manganese. The lower 

percentages attributed to the between-areas component (S~) in the final study resulted in E 8 (2) values 

much greater than those estimated from the highway 

study. Consequently the sampling load of the final 

study turned out to be inadequate for computing unit 

averages of some elements. The parameters used to 

assess stability in averages based on the final study 

are given in table 10. 

Six elements (aluminum, chromium, iron, scandium, 

yttrium, and ytterbium) display a sufficiently low 

E 8 (2) to permit computation of realistic averages of the 

data from each unit. The remaining elements require 

still further sampling if useful averages are to be computed, although averages for copper, gallium, silicon, 

vanadium and zinc would require only a little more 

sampling. 

Geochemical summaries based on residuum from the 

final study are given in tables 11 and 12. Grand 

averages for residuum regardless of unit are given in 

table 11. Taole 12 lists averages of 16 selected constituents for each bedrock area: the first six constituents 

have E 8 (2){E,.; the 10 remaining constituents have 

E 8 (2)>Er but also have between-unit components (Sb) 
GEOCHEMICAL VARIABILITY G21 

TABLE 7.-Comparison of estimated logarithmic variance components for residuum of the highway study in Missouri 

[Asterisk (*l, significantly diff~rent from zero at the 0.05 probability level) 

Elements Total loglO 

Between units Between localities Between sections Between samples Between replicates 

variance Comp~nent Percent Comp~nent Percent Comp~nent Percent Comp~nent Percent Component Percent 2 

(SlogX) ss of total se of total SK of total S s~ of total 0 of total 

Al--------- 0.0803 0.0257* 32 <0.0001 <1 0.0385* 48 0.0157 20 0.0005 1 

As--------- .1147 .0614* 54 <.0001 <1 .0180 16 <.0001 <1 .0350 31 

B---------- .0653 .0172* 26 <.0001 <1 .0255 39 <.0001 <1 .0226 34 

Ba--------- .4778 .3063* 64 .0026 1 .1325* 28 .0265 6 .0099 2 

Be--------- .0664 .0261* 40 <.0001 <1 .0065 10 .0284 35 .0104 16 

Total C---- .2274 <.0001 <1 .0879* 39 <.0001 <1 .1277 56 .0117 5 

Carbonate C .3952 <.0001 <1 .0382 10 .1490 38 .1857 47 .0224 6 

Organic C-- .1540 <.0001 <1 .0450 29 <.0001 <1 .0548 36 .0544 35 

Ca--------- .4133 .1677* 41 .0824 20 .1005* 24 .0602 15 .0005 <1 

Co--------- .0887 .0447* 50 <.0001 <1 .0146 16 .0182 21 .0102 11 

c---------- .0716 .0288* 40 <.0001 <1 .0183 25 .0197 28 .0049 7 

Cu--------- .1551 .0752* 48 <.0001 <1 .0570*· 37 .0148 10 .0082 5 

F---------- .1638 .0306* 19 <.0001 <1 .0571 35 .0597 36 .0164 10 

Fe--------- .0957 .0397* 41 <.0001 <1 .0349* 36 .0211 22 .0001 <1 

Ga--------- .0717 .0142* 20 <.0001 <1 .0269 37 .0275 38 .0032 4 

Hg--------- .1468 .0162 11 .0084 6 .0196 13 .0777 53 .0250 17 

1---------- .2257 .1043* 46 <.0001 <1 .0982 21 .0720 32 .0011 <1 

K---------- .1403 .0661* 47 .0019 1 .0205 15 .0518 37 .0001 <1 

Li--------- .0781 .0287* 37 <.0001 <1 .0384* 49 .0108 14 .0002 <1 

Mg--------- .1118 .0375* 34 <.0001 <1 .0557* 50 .0113 10 .0074 7 

Mn-------- .4346 .2290* 53 <.0001 <1 .0805 19 .1210 28 .0051 1 

Na--------- .0569 .0145* 26 .0051 9 <.0001 <1 .0022 4 .0350 62 

Ni--------- .1037 .0337* 33 <.0001 <1 .0313 30 .0315 30 .0072 7 

P---------- .0855 .0062 7 .0100 12 <.0001 <1 .0507 59 .0187 22 

Pb--------- .4388 .2956* 67 <.0001 <1 .0228 5 .1026 24 .0158 4 

1si-------- 248.8 103.2* 41 <.1 <1 114.9* 46 29.7 12 1.0 <1 

Se-------- .0908 .0051 6 <.0001 <1 .0179 20 .0108 12 .0569 63 

Sc-------- .0669 .0216* 32 <.0001 <1 .0455* 51 .0084 13 .0069 10 

Sr-------- .1896 .0671* 35 <.0001 <1 .0826* 44 .0350 18 .0049 3 

Ti-------- .0412 .0141* 34 .0021 5 .0133 32 .0070 17 .0048 12 

v--------- .0728 .0236* 32 <.0001 <1 .0318* 44 .0143 20 .0032 4 

Y---------. .2298 .1154* 50 <.0001 <1 .0953* 40 .0267 12 .0059 2 

z-------- .1316 .0503* 32 <.0001 <1 .0452* 47 .0136 10 .0140 11 

Zn-------- .3187 .2433* 76 <.0001 <1 .0452* 14 .0290 9 .0012 <1 

Zr-------- .0381 .0052 14 .0095* 25 .0109 29 <.0001 <1 .0125 33 

1variance calculated on nontransformed data rather than log data. 

that were found to be significant (table 9). For these 

last 10 constituents, only those two units showing the 

highest and lowest averages are tabulated. (The 

analysis of variance results in table 9 indicate that the 

highest and lowest averages are distinct even if Es(2) 

indicates that any two randomly selected averages are 

not necessarily distinct.) 

The data collected in Washington County were averaged independently of the rest (table 11 ). A comparison 

of these averages with those for undifferentiated 

- residuum suggests that not only is Washington County residuum anomalous in the ore metals-barium, 

copper, lead, and zinc (see Ebens and Connor, 

1977)-but it also tends to be high in arsenic, mercury, 

and neodymium and low in cadmium. In addition, the 

only sample in which silver was detected (sample 

P031R, 0.5 ppm silver) was taken from the Potosi unit 

in Washington County. 

Among the seven residuum units (table 12) there is a 

tendency for the Osage and Meramec units (over 

Mis·sissippian bedrock) to be distinctly high in 

aluminum, chromium, iron, scandium, yttrium, and 

ytterbium. These same two units are also higher in zinc 

and lower in copper and silicon than residuum of the 

Bonneterre, Potosi, Gasconade, Roubidoux, and J efferson City units. Other comparisons suggest that 

residuum of the Bonneterre unit is high in manganese 

and zirconium and low in lithium; residuum of the 

Potosi unit tends to be high in beryllium and silicon 

and low in zirconium; residuum of the Gasconade unit 

tends to be high in copper and low in selenium; 

residuum of the Roubidoux unit tends to be low in 

beryllium, gallium, manganese, and vanadium; 

residuum of the Jefferson City unit tends to be high in 

lithium and low in zinc; residuum of the Osage unit 

tends to be high in gallium and vanadium; and 

residuum of the Meramec unit tends to be high in 

gallium, selenium, and vanadium. 
G22 GEOCHEMISTRY OF LOESS AND CARBONATE RESIDUUM 

TABLE B.-Parameters used to assess sampling requirements i'!- · 

residuum 

(u, variance ratio (defined in equation 12); n,.. minimum number of randomly collected 

samples needed to represent each area: Er. maximum permissible variance; E5 (1), · 

variance computed for the highway sampling (by equation 18): E 5 (2), variance estimated 

for the final study (by equation 19)) 

Element v 

Al----- 0.47 

As--.-~- 1 .15 

B------ .36 

Ba----- 1 . 79 

Be----- .65 

Ca----- .69 

Co----- .98 

Cr----- .67 

Cu----- ,q4 

F------ .23 

Fe----- .71 

Ga----- .25 

1------ .86 

K------ .89 

Li----- .58 

Mg----- .50 

Mn----- 1.11 

Na----- .34 

Ni----- .48 

Pb----- 2.06 

Si----- .71 

Sc----- .48 

Sr----- .55 

Ti----- .52 

v------ .48 

Y------- 1.01 

Yb------ .62 

Zn------ 3.23 

8 0.007 

5 .Oll 

10 .005 

4 .043 

7 .006 

6 .041 

5 .009 

6 .007 

5 .016 

14 .010 

6 .009 

13 .004 

6 .020 

5 .015 

7 .007 

8 .009 

5 .041 

ll .004 

8 .ooq 

4 .036 

6 24.3 

8 .008 

7 .018 

8 .003 

8 .006 

5 .026 

7 .010 

3 .025 

0.014 

.013 

.012 

.044 

.010 

.082 

.Oll 

.Oll 

.020 

.033 

.014 

.014 

.030 

.019 

.012 

.019 

.051 

.012 

.018 

.036 

36.4 

.015 

.031 

.007 

.012 

.032 

.018 

.019 

0.004 

.003 

.003 

.013 

.002 

.025 

.002 

.003 

.006 

.008 

.004 

.004 

.007 

.004 

.004 

.005 

.012 

.002 

.004 

.007 

10.9 

.004 

.009 

.002 

.003 

.009 

.005 

.005 

Other elements, determined in too few samples to 

permit a quantitative test of regional variation, also 

appear to differ between residuum overlying the 

Mississippian and pre-Mississippian bedrock areas. 

Boron, for example, was determined in a substantially 

lower percentage of samples in residuum over Mississippian bedrock (7 of 48; 15 percent) than in samples of 

residuum over pre-Mississippian bedrock (57 of 94; 61 

percent). Cadmium, cerium, and lanthanum, on the 

other hand, were determined in a higher percentage of 

residuum samples collected over Mississippian bedrock (21 percent for cadmium, 13 percent for cerium, 

and 57 percent for lanthanum) compared to residuum 

samples over pre-Mississippian bedrock (5 percent for 

cadmium and cerium and 15 percent for lanthanum). 

These comparisons suggest that residuum over bedrock of Mississippian age is relatively rich in rare-earth 

elements compared to residuum over bedrock of preMississippian age. In addition to cerium and lanthanum, praseodymium and samarium were detected in 

two samples of the final study collected over Mississippian bedrock and in none taken over pre-Mississippian 

bedrock. Sample 0063 (Searcy County, Ark.) contained 

200 ppm cerium, 150 ppm praseodymium, 700 ppm 

neodymium, 150 ppm samarium, and 100 ppm dysprosium; sample M022 (Jasper County, Mo.) contained 

200, 150, 700, 150, and 70 ppm of these same elements, 

respectively; and sample R17 in the highway study 

(from the Osage unit, Greene County, Mo.) contained 

300 ppm each of lanthanum and neodymium, 100 ppm 

each of samarium and gadolinium, and 70 ppm each of 

dysprosium and holmium. Residuum over Mississippian bedrock is relatively rich in aluminum (table 12), 

and the distribution of rare-earth elements probably 

reflects the fact that this residuum is simply more 

clay-rich than residuum over pre-Mississippian 

bedrock. 

In general, those elements for which the regional 

component of variance in the final study (Sb) was nonsignificant displayed significant components between 

localities within units (S~). These include two alkali 

elements (potassium and sodium), a carbonate-related 

suite (carbon, calcium, magnesium, and strontium), an 

ore-element suite (barium, copper, lead, and zinc), and a 

miscellaneous trace-element suite of arsenic, cobalt, 

chromium, fluorine, nickel, yttrium, and zirconium. 

The differences in the carbonate suite result from 

minor variations of calcite or dolomite in the samples. 

Potassium is high in localities 16, 37, and 38 (as high as 

6.4 percent K20 in sample B052), and sodium is high in 

locality 19 (as high as 0.28 percent Na20 in sample 

POll). These high values may reflect in part an arkosic 

heritage for the residuum in those localities. 

The greatest concentrations of ore elements outside 

of Washington County were reported for the following 

localities: Barium (as high as 500 ppm) in localities 16, 

17, and 18; copper (as high as 150 ppm) in 25, 27, and 

34; lead (as high as 150 ppm) in 16, 28, 30, and 43; and 

zinc (as high as 1040 ppm) in 30, 44, and 51. Other 

trace elements were highest at these localities (still excluding Washington County): Arsenic (as high as 

61 ppm) in locality 37; cobalt (as high as 100 ppm) in 

18; chromium (as high as 200 ppm) in 42; fluorine (as 

high as 5900 ppm) in 28; nickel (as high as 100 ppm) in 

48 and 51; yttrium (as high as 500 ppm) in 46; and zirconium (as high as 200 ppm) in 14 and 17. In addition 

to these elements, boron appears to be high in locality 

16 (as much as 70 ppm), molybdenum appears to be 

high in locality 37 (as much as 7 ppm), cadmium appears to be high in locality 51 (as much as 6 ppm), and 
GEOCHEMICAL VARIABILITY 023 

TABLE 9.-Comparison of estimated logarithmic variance components for residuum of the final study in Missouri 

[Asterisk(*), significantly different from zero at the 0.05 probability level. Note: 23 samples collected from Washington County were excluded from this analysis because they were judged 

to be geochemically anomalous] 

Between units Between localities 

Element Total loglO 

variance Component Percent Component Percent 

2 2 

(SlogX) SB of total s~ of total 

Al----- 0.0253 0.0051* 20 0.0017 7 

As----- .0503 <.0001 <1 .0202* 40 

Ba----- .0243 <.0001 <1 .0098* 40 

Be---'-- .0222 .0018* 8 .0035 16 

c (Tot) .0665 .0071 11 .0154* 23 

1ca----- .2673 .0185 7 .0999* 37 

Co----- .0886 <.0001 <1 .0292* 33 

Cr----- .0407 .0148* 36 .0067* 16 

Cu----- .0596 .0117* 20 .0128* 21 

F------ .0660 .0003 <1 .0195* 30 

Fe----- .0312 .0065* 21 <.0001 <1 

Ga----- .0397 .0074* 19 .0020 5 

Hg----- .1241 .0024 2 .0155 12 

K------ .0696 <.0001 <1 .0405* 58 

Li----- .0347 .0031* 9 .0072 21 

Mg----- .0427 .0027 6 .0165* 39 

Mn----- .1498 .0200* 13 .0239 16 

Na----- .0419 <.0001 <1 .0139* 33 

Ni----- .0556 .0020 4 .0186* 33 

Pb----- .0636 <.0001 <1 .0365* 57 

Sc----- .0328 .0093* 28 .0031 9 

Se----- .1482 .0167* 11 <.0001 <1 

2si----- 124.4 22.9* 18 15.9 13 

Sr----- .0635 .0019 3 .0208* 33 

Ti----- .0087 <.0001 <2 .0008 9 

v------ .0301 .0050* 17 .0022 7 

Y------ .1249 .0350* 28 .0237* 19 

Yb----- .0790 .0168* 21 .0013 2 

Zn----- .0738 .0142* 19 .0150* 20 

Zr----- .0178 .0002 <2 .0059* 33 

1Determined by semiquantitative emission spectrography. 2Variance calculated on nontransformed data rather than 

lanthanum appears to be high in locality 46 (as much 

as 1000 ppm). 

The geochemical heterogeneity noted at local scales 

in the highway study (S~ + S~, table 7) is confirmed in 

the final study. In table 9, 21 of 30 entries exhibit half 

or more of their total observed variances at scales less 

than a few kilometers. If the laboratory variance (S:) is 

added to this, 27 of the 30 listed elements exhibit over 

half of the total variance at these three levels of design, 

and 16 exhibit over two-thirds. For the most part, 

these three combined variances estimate the basic 

geochemical imprecision which would be encountered 

in representing a residuum locality by a single sample, 

if that sample were analyzed by the methods listed in 

table 3 or by methods with similar precision. 

BARITE ORE 

The State of Missouri is a leading producer of barite, 

which is mined from residuum in the Washington 

County barite district. It is used principally as a comBetween sections Between samples Between replicates 

Compo~ent Percent Compo~ent Percent Compo~ent .Percent 

SK of total so of total SE of total 

0.0118* 47 0.0065 26 0.0002 <1 

.0197* 39 .0050 10 .0054 11 

.0047* 19 .0058 24 .0040 16 

.0094* 42 .0044 20 .0031 14 

.0111* 17 .0235 35 .0094 14 

.0530* 20 .0707 27 .0252 9 

.0280* 32 .0286 32 .0028 3 

.0102* 25 .0045 11 .0045 11 

.0194* 33 .0118 20 .0039 7 

.0246* 37 .0075 11 .0141 21 

.0173* 55 .0073 23 .0001 <1 

.0185* 47 .0087 22 .0031 8 

.0546* 44 .0394 32 .0122 10 

.0189* 27 .0101 15 .0001 <1 

.0161* 46 .0075 22 .0008 2 

.0152* 36 .0080 19 .0003 <1 

.0532* 36 .0444 30 .0083 6 

.0130* 31 .0126 30 .0024 6 

.0137* 25 .0099 18 .0114 21 

.0127* 20 .0045 7 .0099 16 

.0106* 32 .0086 26 .0012 4 

.0596* 40 <.0001 <1 .0719 49 

44.2* 36 38.8 31 2.6 2 

.0237* 37 .0119 19 .0052 8 

.0036* 41 .0027 31 .0016 18 

.0130* 43 .0050 17 .0049 16 

.0261* 21 .0385 31 .0016 1 

.0271* 34 .0287 36 .0051 6 

.0296* 40 .0146 20 .0004 <1 

.0014 8 .0074 42 .0029 16 

log data. 

ponent of oil-well drilling fluids and secondarily in 

paint, rubber, and glass manufacturing (Stout and 

Hoffman, 1973, p. 22; Wharton and others, 1969, 

p. 227). Minor amounts of lead are recovered from the 

barite operations (Kisvarsanyi and Searight, 1965 ). 

Results of chemical analyses of eight samples of 

washed but unground barite ore are given in table 13. 

Two samples were collected in 1971 from each of four 

operating companies in the barite district. The traceelement content in barite is one of the lowest among 

geologic materials in the State. Apart from about 1 

2 percent alumina and about 0.5 percent strontium, 

' few elements occur in amounts much above a tenth of a 

·percent. Of the constituents listed in table 13, only 

· lead occurs in barite ore in quantities substantially 

greater than in the host residuum (compare table 11 ). 

Calcium, copper, and mercury occur in the barite in 

about the same amount that they occur in residuum; 

all other elements tend to occur in very low amounts in 

barite. Many elements commonly determined in more 

typical geologic materials at low levels (see table 3) 

were not detected in barite. 
024 GEOCHEMISTRY OF LOESS AND CARBONATE RESIDUUM 

40 

20 

Barium 

0 0 0 0 It) 0 ~ ~ N 

0 0 0 0 

" 0 ~ 

ELEMENT CONTENT, IN PARTS PER MILLION 

FIGURE 10.-Barium, copper, lead, and zinc content in residuum. Diagonal line pattern represents samples from Washington County, 

Missouri. 

The aluminum-silicon ratio in the barite ore is about 

10 times too high to account for these two elements in 

any common clay. It is probable that the alumina oc- . 

curs instead as a hydrated oxide. The strontium prob- ' 

ably substitutes for the barium in barite. 

THE RELATION OF RESIDUUM TO BEDROCK 

In the highway study, a sample of bedrock, assumed 

to be the parent material, was collected underneath 

each sampled section of residuum. Correlations between logarithms of element concentration in these 

two materials are given here for those elements that 

were represented by sufficient data from both materials. (Many trace elements occur in carbonate rock in 

concentrations too low to be determined.) Data for the 

Roubidoux unit and overlying residuum have been excluded from these calculations because the bedrock 

sampled was quartzite, the distinguishing component 

of the Roubidoux unit. The correlations are: 

Element Correlation Element Correlation 

Al -0.19 Mn 0.51 

Ba .52 Na -.16 

Cr .32 Si .61 

Cu .67 Sr -.17 

F .37 Ti .55 

Fe .29 Zn .79 

Hg -.48 
GEOCHEMICAL VARIABILITY 025 

TABLE 10.-Parameters used to assess stability in averages based 

on the final study 

[v, variance ratio (defined in equation 12); n,.. minimum number of randomly collected 

samples needed to represent each area; E,.. maximum permissible variance; E 8(2), actual 

variance computed in the final study) 

Element----- v nr Er 1': 8 (2) 

Al---------- 0.25 13 0.0016 0.0016 

Be---------- .09 <so <.0004 .0017 

Cr---------- .57 7 .0037 .0023 

Cu---------- .24 14 .0034 .0044 

Fe---------- .26 13 .0019 .0018 

Ga---------- .23 14 .0023 .0024 

Li---------- .10 30 .0011 .0029 

Mn---------- .15 20 .0065 .0106 

Sc---------- .40 9 .0026 .0018 

Se---------- .13 23 .0057 .0080 

Si---------- .23 14 7.3 8.1 

v----------- .20 16 .0016 .0019 

Y----------- .39 9 .0100 .0082 

Yb---------- .27 13 .0048 .0039 

Zn---------- .24 14 .0043 .0056 

Those elements having a correlation greater than 0.5 

are shown on the graph in figure 11, except for silicon 

and aluminum, which are shown in figure 12. A correlation of 0.5 indicates that 25 percent of the variance in 

one of the materials can be related to variation in the 

other material. Clearly, the positive relation seen in 

barium is controlled by a single point, sample R08 

(which was collected from the Potosi unit in the 

Washington County barite district). The relations in 

copper, manganese, silicon, titanium, and zinc seem to 

be real, although the strength of some of these relations depends on the presence of subpopulations. The 

positive relations in manganese and zinc are greatly 

enhanced by the presence of samples from the Bonneterre (R01, R03, R04) and Potosi (R05, R06, R07, R08) 

units, respectively. The high zinc samples, like the 

high barium sample, come from the Washington County barite district. 

These relations indic;;t.te that the concentrations of at 

least ·some elements in residuum appear to directly 

reflect the geochemistry of the immediately underlying 

bedrock. Olsen and Ruhe (1978) concluded that terra 

rosa (residuum) in southern Indiana is probably more 

of a transported deposit than a residual one, and it's 

likely that major parts of the residuum in southern 

Missouri are also exotic, reflecting deposition of 

alluvial, colluvial, or eolian materials. However, 

because the carbonate bedrock underlying the residuum is everywhere highly soluble, at least part of the 

residuum represents the insoluble residue of the 

bedrock. 

Residuum is rich in aluminum and silicon and, if it is -, 

TABLE 11.-Geochemical summaries of carbonate residuum, undifferentiated by bedrock area, Missouri and northern Arkansas 

[GM, geometric mean; GD, geometric deviation; GE, geometric error; Ratio, number of 

samples in which element was determined to total number of samples analyzed. Leaders 

(-) indicate insufficient data for computation. Geometric means are in parts per million 

except where noted as percent (pet) or parts per billion (ppb)] 

Element 

GM 

Ag-------- <o.5 

A1 2o3, pet 16 

As-------- 19 

B--------- 16 Ba-------- 170 

All residuum Washington Countv, 

Missouri 

GD Ratio GE GM 

0:142 <0.5 

1.40 142:142 1.03 17 

1.63 142:142 1.18 30 

1.36 54:142 1.05 12 

1.41 142:142 1.16 400 

GD Ratio 

1:23 

1.36 23:23 

1. 76 23:23 

1.52 4:23 

4.99 23:23 

Be-------- 1.3 1.72 103:142 1.14 1.4 1.85 17:23 

Total C, 

pct-----

CaO, pct--

.20 1.81 142:142 1.25 .34 1.70 23:23 

.82 4.18 77:142 1.07 .34 2.34 22:23 

Cd--------

Ce--------

1.5 1.75 15:142 1.15 .92 2.10 11:23 

26 2.96 11:142 ---- <150 0:23 

Co-------- 5.8 

Cr-------- 69 

Cu-------- 23 

Dy-------- 31 F--------- 790 

Fe2o3, pet 6.5 

Ga-------- 21 

Gd-------- <70 

Hg, ppb--- 57 

K2o, pet-- 1.4 

2.44 110:142 1.13 7.9 

1.54 142:142 1.17 65 

1.72 142:142 1.15 50 

2.03 4:11 <so 

1.74 142:142 1.31 750 

1.46 142:142 1.02 

1.54 141:142 1.14 

0:11 

2.90 139:142 1.29 

1.78 142:142 1.02 

9.7 

21 

<70 

85 

1.0 

1.50 23:23 

1.29 23:23 

1.80 23:23 

1:2 

1.55 23:23 

1.76 23:23 

1.40 23:23 

1:2 

3.39 22:23 

1.38 23:23 

La-------- 26 2.73 50:142 1.11 30 1. 96 8:23 

1.36 23:23 

1.49 23:23 

2.66 23:23 

Li-------- 39 1.50 142:142 1.07 50 

MgO, pet-- .73 1.57 142:142 1.04 .96 

Mn-------- 110 2.43 142:142 1.23 120 

Mo-------- .78 2.73 16:142 <3 0:23 

Na2o, pet- 500 

Nb-------- 3.8 

Nd-------- 23 

Ni-------- 22 

Pb-------- 24 

1.57 142:142 1.12 570 

1.54 5:142 5.1 

3.62 16:62 45 

1.71 142:142 1.28 27 

1.78 140:142 1.26 99 

1.55 23:23 

1.43 2:23 

2.31 4:10 

1.60 23:23 

2.59 23:23 

P2o5, pet- .97 1.23 64:142 1.43 .78 1.24 11:23 

Pr-------- 49 1.63 2:62 ---- <150 0:10 

Sc-------- 10 1.50 140:142 1.08 9.4 1.35 23:23 

Se-------- .39 2.04 126:142 1.85 .46 2.05 21:23 1 Sio2, pet- 62 12 142:142 1.6 53 13 23:23 

Sm-------- 49 

Sr-------- 46 

Ti, pet--- .15 

v--------- 100 Y--------- 13 

Yb-------- 1.7 

Zn-------- 80 

Zr-------- 69 

1.63 2:62 ---- <150 0:10 

1.77 142:142 1.18 51 1.55 23:23 

1.24 142:142 1.09 .14 1.40 23:23 

1.46 142:142 1.18 130 1.45 23:23 

2.76 112:142 1.09 12 3.14 17:23 

2.11 126:142 1.18 2.0 

1.83 142:142 1.54 470 

1.36 142:142 1.13 57 

2.00 20:21 

4.08 23:23 

1.63 23:23 

1 Summary statistics given as arithmetic means, 

standard deviations, and standard error. 

assumed that only negligible amounts of these elements were removed during weathering, the relative 

amount of parent carbonate required to produce a unit 

amount of daughter residuum may be estimated 

(fig. 12). These estimates, given as concentration factors by weight, range from about 5 (sample R04, collected from the Bonneterre unit) to about 500 (sample 

R17, collected from the Osage unit). A comparison of 

the average abundance in residuum (from the final 
TABLE I2.-Geochemical summaries of carbonate residuum, by bedrock area, in Missouri and northern Arkansas 

(GM, geometric mean; GD, geometric deviation; Ratio, number of samples in which element was determined to total number of samples analyzed. Leaders(---) indicate insufficient data for computation. Geometric means are in parts per million except where noted as percent (pet). Bedrock units from McCracken (1961)( 

Element Bonneterre Potosi Gasconade Roubidoux Jefferson City Osage Meramac 

GM GD Ratio GM GD Ratio GM GD Ratio GM GD Ratio GM GD Ratio GM GD Ratio GM GD Ratio 

Al 2o3, pet- 16.0 1.52 

Be---------

Cr--------- 55 1.47 

Cu---------

Fe2o3, pet- 7.6 1.64 

16:16 

16:16 

16:16 

13.0 

2.0 

47 

5.3 

1.32 

2.04 

1.65 

1.30 

12:12 

11:12 

12:12 

12:12 

16.0 

59 

39 

6.4 

1.29 

1.33 

1.84 

1.28 

19:19 

19:19 

19:19 

19:19 

12.0 

.95 

52 

5.0 

1.57 

1.84 

1.52 

1.60 

23 23 

12 23 

23 23 

23:23 

15.0 

71 

5.6 

1.24 

1.27 

1.25 

24:24 19.0 

24:24 100 

24:24 7.6 

1.21 24:24 

1.44 24:24 

1.31 24:24 

20.0 

93 

17 

8.2 

1.26 

1.30 

1.36 

1.33 

24:24 

24 24 

24 24 

24 24 

Ga--------- 15 1.79 22:23 26 1. 33 24:24 26 1. 39 24:24 

Li--------- 28 

Mn--------- 280 

Sc--------- 10 

Se---------

lsio2, pctv---------

Y---------

Yb--------

Zn--------

13 

1.8 

Zr-------- 87 

1.37 

2.89 

1.57 

1.59 

1.66 

16 16 

16 16 

16 16 

14:16 

15:16 

9.5 

69 

15 

1.9 

1.43 16:16 64 

1.31 

8.5 

2.22 

2.25 

12:12 

12:12 

11:12 

11:12 

1.44 12:12 

9.3 1.27 

.31 1.62 

9.0 

1.4 

1.61 

1.65 

19:19 

19:19 

14:19 

17:19 

73 

7.6 

83 

7.2 

1.1 

1.98 23:23 

1.64 21:23 

1. 67 

2.25 

2.04 

23:23 

13:23 

17:23 

45 

9.2 

6.4 

1.1 

50 

1.39 

1.34 

2.48 

2.02 

1.35 

1Summary statistics given as arithmetic means, standard deviations, and standard error. 

TABLE I3.-Chemical analyses of barite ore from Missouri 

24:24 

24:24 

13:24 

18:24 

24:24 

15 1.29 24:24 

.54 1.96 22:24 

130 

28 

2.6 

1.30 

2.58 

2.01 

24:24 

24:24 

24:24 

12 

54 

130 

27 

2.6 

120 

1.40 

10 

1.33 

2.64 

1.89 

1.97 

(Field samples BOI. B02 from Baroid Division, National Lead Co.; B03, B04 from Dresser Minerals Division of Dresser Industries, Inc.; B05, B06 from Pfi..:er, Inc.; and B07, B08 from Milchem, 

Inc. All data in parts per million except where noted as percent (pet); GM, geometric mean; GD, geometric deviation, Leaders(---) indicate insufficient data for computation. Analysts: Violet 

Merritt, I. C. Frost, R. L. Rahill, J. A. Thomas, R. L.Turner, Mike Brown, J. W. Budinsky, Leung Mei, and L. C. Bradley( 

Sample No. 

Lab Field 

DI53- REI788W 

794W 

792W 

793W 

790W 

787W 

786 

789W 

BOI 

B02 

B03 

'B04 

B05 

B06 

B07 

B08 

Summary 

GM 

GD 

AI 203 

(pet) 

l.I 

1.8 

2.0 

2.3 

2.2 

2.8 

1.9 

.3 

1.9 

1.36 

As 

<I 

1.2 

<1 

2.5 

1.4 

<1 

<1 

1 

<1 

Total C 

(pet) 

<0.05 

<.05 

<.os 

<.os 

<.05 

<.05 

<.06 

.20 

<.05 

Ca1 

200 

200 

200 

200 

300 

200 

500 

1000 

290 

1.82 

Cr 

<1 

<1 

Cu 

50 

70 

1 20 

3 20 

<1 15 

3 150 

2 70 

<1 30 

Fe 1 

(pet) 

0.2 

.15 

Hg 

0.08 

.02 

Mg 

50 

<so 

Mn 

7 

7 

.3 <.o1 <so s 

.2 .o6 <so 1 

.15 .03 150 5 

.1 .08 50 7 

.5 <.01 150 15 

.15 .03 50 15 

Na2o 

(pet) 

Pb 

0.01 70 

<.01 200 

.03 100 

.01 200 

<.01 70 

<.01 150 

<.01 200 

<.01 150 

<1 40 .19 .03 

2.77 

<so 7.8 <.01 

1.53 

I30 

2.82 1.64 1.57 

1 Determined by semiquantitative emission spectrography. 2 Ana1yses of acid-soluble fractions. 

P205 

(pet) 

<0.05 

<.05 

<.05 

.06 

<.05 

<.05 

<.05 

<.05 

<.05 

Se 

<O.I 

<.1 

Si 1 

500 

700 

<.1 2000 

<.1 2000 

<.1 700 

<.1 700 

.2 500 

.1 800 

< .1 840 

1. 75 

Sr 

5000 

2000 

3000 

3000 

7000 

3000 

3000 

3000 

3600 

1. 39 

Ti 

2 

2 

7 

15 

2 

<2 

10 

10 

4.1 

2.74 

24:24 

24:24 

24 24 

23 24 

24 24 

24 24 

Zn2 

I8 

27 

28 

77 

15 

33 

155 

17 

33 

2.25 

0 

~ 

0') 

0 

tri 

0 

(1 

:I: 

t'l:j 

s: 

~ ~ 

-< 

0 

"%j 

t'"' 

0 

tri 

00 

00 

> z 

t::l 

(1 

> 

~ 

l:l:l 

0 

z 

> t-3 

t'l:j 

~ 

t'l:j 

00 

a 

c 

c 

== 
DISCUSSION G27 

20 

z 

0 

:::::i 10 ...J 

~ 5 0:: 

w 

Q.. 

en 2 I0:: 

<( 

Q.. 

'::2 60 u 

o o.s~~--~-........_--~--~---'----'---1---~ 

~ 100 200 500 1000 2000 5000 10,000 20,000 50,000 100,000 

w soo~~----~--~-~-~--~ Ill 

~ 

z 200 

0 

~ 0:: 

1-

z 

w 50 u 

z 

0 

u 20 

10 

5 

Titanium 

0 

1000 

500 

200 

Manganese 

20 50 100 200 500 1000 2000 5000 10,000 

EXPLANATION 

Samples of residuum overlying rocks of: 

0 Pre-Mississippian age 

6 Mississippian age 

Copper 

0.2 5 ....._ _ __._ _ _.__.....__ _ ___._ _ __._ _ __._ _ ___. 

500 1000 2000 5000 10,000" 10 20 50 100 200 500 20 50 100 200 5000 

CONCENTRATION IN RESIDUUM, PARTS PER MILLION 

FIGURE H.-Concentrations of barium, manganese, titanium, copper, and zinc in residuum (R) and underlying carbonate bedrock (B). 

study, table 11) to the average abundance in bedrock of 

both Mississippian and pre-Mississippian age (from 

Connor and Ebens, 1980) indicates that the average 

concentration factor is probably in the range of 10-20. 

Because the specific g~;avity of residuum is substantially less than that of carbonate rock, concentration 

factors on a volume basis are less than those shown in 

figure 12. If the specific gravity of residuum is taken 

as 1.5 and the specific gravity of rock is taken as 2.5, 

the factors in figure 12 would be reduced by about 40 

percent. Under this assumption, the concentration factors then range from about 3 to 300 for the individual 

samples and from about 6 to 12 for the averages. 

Residuum as sampled in the final study ranged in 

thickness from ( 1 to 23 m and averaged perhaps 3 m. 

Concentration factors of a 100 or more (suggesting 

that 3 m of residuum is equivalent to 300 m of parent 

rock) seem unrealistic. A factor of 6 (3 m of residuum 

equivalent to 18 m of parent rock) may be more 

realistic. 

DISCUSSION 

The data of this work were collected for the specific 

purpose of defining the regional geochemical character 

of two of the most widespread surficial deposits in the 

State of Missouri. The data summaries in tables 5, 11, 

and 12 constitute this geochemical definition. The 

primary use of the data or the data summaries is expected to be in evaluation of geochemical anomalies in 

the local landscape of Missouri, although any assessment of geochemically related disease in plants, 

animals, or humans would likely make use of these 

summaries also. 

The strongest geochemical contrast in the surficial 

deposits is that between the two units themselves. 
G28 GEOCHEMISTRY OF LOESS AND CARBONATE RESIDUUM 

1-

z 

w 

u 

a: 

w 

ll.. 

~ 

u 

0 

a: 

c 

w 

r:c 

~ 

z 

0 

~ ~ 0.1 

z 

w 

u 

z 

0 

u 0.05 

0 R04 

ALUMINUM 

• 

SILICON 

5 10 20 10 20 50 

CONCENTRATION IN RESIDUUM, PERCENT 

Residuum 

samples 

0 

6 

EXPLANATION 

Average 

abundance 

• 

.. Age of underlying 

bedrock 

Pre-Mississippian 

Mississippian 

FIGURE 12.-Concentrations of silicon and aluminum in residuum 

and underlying carbonate bedrock. Diagonal lines show concentration factors of the elements in residuum. Average abund!plces are 

based on table 11 for residuum and on Connor and Ebens (1980) for 

bedrock. The standard deviation (vertical bar) on sample R32 

represents the imprecision in the bedrock sample due to sampling 

and analytical errors. 

Although the residuum is only slightly more clay-rich 

than loess, it contains as much as twice the aluminum, 

because the clay in residuum is more. kaolinitic than 

that in loess. Fluorine and lithium are also about twice 

as high in residuum as in loess, but a variety of other 

clay-related elements, including boron, gallium, scandium, yttrium, ytterbium, and zirconium, occur in 

about the same concentration in both units or are even 

higher in loess. The illitic clay (more common in loess) 

probably offers a greater opportunity for trace-element 

substitution or surface adsorption than does the kaolinitic clay (more common in residuum). Boron, the alkali elements sodium and potassium, and the alkaline 

earth elements calcium, magnesium, strontium, and 

barium are all at least twice as high in loess as in 

residuum, reflecting in part the geologically prolonged 

leaching of these more soluble elements from residuum. Iron and manganese are about twice as high in 

residuum as in loess, as are two ore elements (lead and 

zinc) and three trace elements of particular environmental interest (arsenic, mercury, and selenium). The 

iron and manganese occur in residuum as hydrated oxides, which are capable of "scavenging" base metals 

from percolating waters. 

The geochemical summaries in tables 5, 11, and 12 

are best used in conjunction with maps showing the 

distribution of the surficial geologic deposits in the 

State. Unfortunately, few such maps are available, in 

part because of the complexities of origin of these 

deposits. (See Dean and Davis, 1973, for a detailed 

map showing the distribution of loess in a small area.) 

The map in figure 1 indicates something of the distribution of these materials, but it is only grossly approximate and must be used with caution. The surficial 

geologic deposits are almost everywhere separated by 

gradational boundaries. 

The development of soil profiles in these materials 

commonly poses problems of differentiating soil from 

unconsolidated geologic material. For residuum, particularly, the distinction between soil and geologic 

material is difficult. The distributions in figure 1 are 

means to portray the kind of geologic material that 

might be expected immediately underneath a conventional soil profile; that is, the material at a depth of 

~ 1-2 m. In large parts of the State, such material would 

likely be recognizable as alluvium, loess, till, carbonate 

residuum, or perhaps some mixture of these. 

Bar graphs for 28 trace elements are shown in figure 

13. These graphs compare the ranges of element concentration in loess and residuum over the State. The 

expected concentrations and the expected 68- and 

i 95-percent ranges in concentration are shown for those 

· units that have sufficient data in tables 5 and 12 to 

permit computation. Where such data were judged to 

be insufficient for computation, only the observed 

range in concentration is given. In general, the comparisons shown in these graphs have not been tested 

statistically, except for the individual residuum units. 

They do, however, provide the opportunity to visually 

compare both average properties and the degree of 

variability of the two materials. For example, the 

range of element concentrations in loess rarely exceeds 

threefold, but in residuum it commonly exceeds tenfold. In bedrock, variation in element concentrations 
REFERENCES CITED 029 

commonly exceeded a hundredfold (Connor and Ebens; 

1980, fig. 14). 

The purpose of these graphs is to aid the user in 

judging the ranges of element concentration to be expected in the two surficial materials in different parts 

of the State. Thus a sample of such material may be 

judged as ordinary or unusual by comparing its composition with the ranges given for the appropriate surficial unit. Use of the graph~ requires that the sample 

or samples being judged be assigned to the correct surficial unit, as the units have been classified for this 

study. To this end, the user may need geological advice, readily available from the Division of Geology 

and Land Survey of the State of Missouri or from local 

offices of the U.S. Geological Survey. 

In examining a local field area of interest, the user 

first determines what surficial unit (or units) may be 

present. In localities far from a geologic boundary, the 

unit underlying the area of interest can probably be determined from figure 1. Localities near to or straddling 

boundaries will likely require geological consultation. 

In particular, the distinction between bluff and nonbluff loess or the determination of a specific bedrock 

area of residuum may prove difficult in the field, 

especially to the inexperienced eye. Field differentiation among soil, till, and loess is difficult where the till 

or loess is thin or weathered. Once the unit is identified, however, the expected range in concentration 

for a number of trace elements can be read from 

figure 13. Also, if samples are collected and analyzed, 

the results can be compared to the graphs (fig. 13) or 

summaries (tables 5, 11, and 12) to determine whether 

the samples in question should be viewed as geochemically unusual. 

REFERENCES CITED 

Aber, J. S., 1977, Multiple advances of the Kansan glacier south of 

the Kansas River valley [abs.]: Geological Society of America 

Abstracts with Programs, v. 9, no. 5, p. 569. 

Bayne, C. K., Davis, S. N., Howe, W. B., and O'Connor, H. G., 1971, 

Regional Pleistocene stratigraphy, in Pleistocene stratigraphy 

of Missouri River valley along the Kansas-Missouri border: 

Kansas Geological Survey Special Distribution Publication 53, 

p.5-8. 

Boellstorff, John, 1978, Proposed abandonment of pre-Illinoian 

Pleistocene stage terms [abs.]: Geological Society of America 

Abstracts with Programs, v.10, no. 6, p. 247. 

Boemgen, J. G., VanTrump, George, Jr., and Ebens, R. J., 1975, 

Analytical data for geologic units in Missouri and parts of Kansas, Oklahoma and Arkansas: U.S. Geological Survey Open-File 

Report 75-137,276 p. 

Cohen, A. C., Jr., 1959, Simplified estimators for the normal 

distribution when samples are singly censored or truncated: 

Technometrics, v. 1, no. 3, p. 217-237. 

Connor, J. J., and Ebens, R. J., 1980, Geochemical survey of 

Missouri-Geochemistry of bedrock units in Missouri and parts 

of adjacent States: U.S. Geological Survey Professional Paper 

954-F, 55 p. 

Connor, J. J., Feder, G. L., Erdman, J. A., and Tidball, R. R., 1972, 

Environmental geochemistry in Missouri-A multidisciplinary 

study: International Geological Congress, 24th, Montreal, 

1972, Symposium 1, Proceedings, no. 24, p. 7-14. 

Dean, T. J., and Davis, S. N., 1973, Geology of the Platte City 

quadrangle, Platte County, Missouri, and Leavenworth County, Kansas: Missouri Division of Geological Survey and Water 

Resources, Geologic Quadrangle Map Series, no. 6. 

Dreeszen, V. H., 1970, The stratigraphic framework of Pleistocene 

glacial and periglacial deposits in the central plains, in 

Pleistocene and Recent environments of the central Great 

Plains: Kansas University Department of Geology, Special 

Publication 3, p. 9-22. 

Ebens, R. J., and Connor, J. J., 1977, Cu, Ph, Zn, and Ba in carbonate residuum of southern Missouri: American Institute of 

Mining, Metallurgical, and Petroleum Engineers, Society of 

Mining Engineers, Pre print no. 7 7-L-325, 4 p. 

Erdman,· J. A., Shacklette, H. T., and Keith, J. R., 1976a, 

Geochemical survey of Missouri-Elemental composition of 

selected native plants and associated soils from major 

vegetation-type areas in Missouri: U.S. Geological Survey Professional Paper 954-C, 87 p. 

__ 1976b, Geochemical survey of Missouri-Elemental composition of com grains, soybean seeds, pasture grasses and 

associated soils from selected areas in Missouri: U.S. Geological 

Survey Professional Paper 954-D, 23 p. 

Feder, G. L., 1979, Geochemical survey of Missouri-Geochemical 

survey of waters of Missouri: U.S. Geological Survey Professional Paper 954-E, 78 p. 

Fuller, D. L., 1977, Groundwater resources along Interstate-55, in 

Guidebook to the geology along Interstate-55 in Missouri: 

Missouri Geological Survey Report of Investigations no. 62, 

p. 91-98. 

Hall, R. D., 1977, Weathering of Wisconsinan loess and related surficial materials in southwestern Indiana [abs.]: Geological Society of America Abstracts with Programs, v. 9, no. 5, p. 602. 

Kisvarsanyi, E. B., and Searight, W. V., compilers, 1965, Mineral 

resources and industry map of Missouri: Rolla, Mo., Missouri 

Division of Geological Survey and Water Resources. 

Krumbein, W. C., and Slack, H. A., 1956, Statistical analysis of lowlevel radioactivity of Pennsylvanian black fissile shale in Illinois: Geological Society of America Bulletin, v. 67, p. 739-762. 

McCracken, M. H., compiler, 1961, Geologic map of Missouri: Rolla, 

Mo., Missouri Division of Geological Survey and Water 

I Resources. 

Miesch, A. T., 1967, Methods of computation ·for estimating 

geochemical abundance: U.S. Geological Survey Professional 

Paper 574-B, 15 p. 

__ 1976, Geochemical survey of Missouri-Methods of sampling, laboratory analysis, and statistical reduction of data, with 

sections on Laboratory methods by 11 others: U.S. Geological 

Survey Professional Paper 954-A, 39 p. 

Myers, A. T., Havens, R. G., and Dunton, P. J., 1961, A spectrochemical method for the semiquantitative analysis of rocks, 

minerals, and ores: U.S. Geological Survey Bulletin 1084-1, 

p. 207-220. 

Oetking, Philip, Feray, D. E., and Renfro, H. B., compilers, 1966, 

Geological highway map of the mid-continent region-Kansas, 

Oklahoma, Missouri, Arkansas: American Association of 

Petroleum Geologists, U.S. Geological Highway Map Series, 

no.l. 
G30 

Loess 

In bluffs 

Dolomite-bearing 

Away from bluffs 

Carbonate residuum 

Undifferentiated 

Washington County 

I I 

I I 

I I 

=0-= 

I I 0.007 0.010.0150.02 0.03 

Loess 

In bluffs 

Dolomite-bearing 

Away from bluffs 

Carbonate residuum 

Undifferentiated 

Washington County 

Loess 

In bluffs 

Dolomite-bearing 

Away from bluffs 

0.1 

Carbonate residuum 

Undifferentiated 

Washington County 

I I 

I I 

0.150.2 

I 

1 

I I 

Mo 

I I 

0..3 0.5 

I I I 

___, 

--1 

--1 

I I I 0.2 0.3 0.5 0.7 

I I I 

I I I 

0.05 0.07 0.1 

I I I 

I I I 

0.7 1 1.5 

I I I 

Cd 

I I I 1.5 2 3 

I I I I I I I I I I I I I I 

Hg =0= 

=:()::1 

Co 

==0== 

===Q==> 

I I I I I I I I I I I I I I 

0.15 0.2 0.3 0.5 0.7 1.5 2 3 5 7 10 15 20 3040 

I I I I I I I I I I I I I I 

____, c:::()::::::::l 

------1 ~ Pb 

---1 ~ 

---1 

I I I I I I I I I I I I I I 

2 3 5 7 10 15 20 30 50 70 100 150 200 300 500 700 

I I I I I I I 

=.():::= 

B --==Q=:L-

~ 

=0= 

I I I I I I I 5 7 10 15 20 30 50 70 8015 

Loess I I I I I I I I I I I I I I I I I I I I I 

Ba In bluffs 

Dolomite-bearing 

Away from bluffs 

Carbonate residuum 

Undifferentiated 

Washington County 

I 

1.5 2 

Loess 

In bluffs 

Dolomite-bearing 

Away from bluffs 

Carbonate residuum 

Undifferentiated 

Washington County 

Loess 

In bluffs 

Dolomite-bearing 

Away from bluffs 

Carbonate residuum 

Undifferentiated 

Washington County 

Loess 

In bluffs 

Dolomite-bearing 

Away from bluffs 

Carbonate residuum 

Undifferentiated 

Washington County 

7 10 

7 

3 

Nb --1 

___, r=Q---"1 

==0-= 

==0:::==:> 

I I I I 3 5 7 10 15 

c:::::(}::::::: Ni =::()::::1 

==0= 

30 50 70 

----! 

----1 

I 

20 

I I I I 

30 50 70 100 

=0= 

==e= ~ 

7 10 

La 

~ 

~ 

I I I I I I I I I I I 150 200 300 500 700 1000 1500 2000 3000 5000 7000 10,000 

As F 

30 500 700 1000 1500 2000 3000 

5000 10,000 20,000 

7000 15,000 

EXPLANATION 0 Geometric mean 

C=====::J 68-percent expected range 

---- 95-percent expected range 

- ------4 Observed range; undetermined where dashed 

----1 All data below limit of analytical determination; 

symbol plotted at limit 

CONCENTRATION IN PARTS PER MILLION 

FIGURE 13.-Trace element concentrations in loess and residuum in Missouri. Bedrock units are from McCracken (1961). 
Loess 

In bluffs 

Dolomite-bearing 

Away from bluffs 

Carbonate residuum 

Overlying specific bedrock 

Maramec 

Osage 

Jefferson City 

Roubidoux 

Gasconade 

Potosi 

Bonneterre 

Washington County 

Loess 

In bluffs 

Dolomite-bearing 

Away from bluffs 

Carbonate residuum 

Overlying specific bedrock 

Maramec 

Osage 

Jefferson City 

Roubidoux 

Gasconade 

Potosi 

Bonneterre 

Washington County 

Loess 

In bluffs 

Dolomite-bearing 

Away from bluffs 

Carbonate residuum 

Undifferentiated 

Overlying specific 

bedrock units 

identified on graph 

Washington County 

Loess 

In bluffs 

Dolomite-bearing 

Away from bluffs 

Carbonate residuum 

Undifferentiated 

Overlying specific 

bedrock units 

identified on graph 

Washington County 

Loess 

In bluffs 

Dolomite-bearing 

Away from bluffs 

Carbonate residuum 

Undifferentiated 

Overlying specific 

bedrock units 

identified on graph 

Washington County 

Loess 

In bluffs 

Dolomite-bearing 

Away from bluffs 

Carbonate residuum 

Undifferentiated 

Overlying specific 

bedrock units 

identified on graph 

Washington County 

units: 

units: 

7 

}{ 

2 

I I I I I I I I I 

=0-= 

=0==> 

c::():::::::l 

I I I I I I I I I 

1.5 2 3 5 7 10 15 20 30 

t:::::()::::::l 

==0==> 

~ 

' 

' 

I I 

Ga 

OSAGE AND MERAMEC~ ~ 

ROUBIDOUX~>,::......____.==:::O::==--

I I I I I I I 

I I 

I I 

50 70 

Yb 

I 

I I 

y 

I I 

100 150 200 2 3 

-d):::L_ 

----'=()::::::~ 

---1::()::1,... 

=0= 

c:::::()::::::: 

----.:J::::= 

I I I 

r::::O= 

I I 

---=Q:::::I- Sc .....c:::CP- -J::()::::L._ 

c=::::O::== r---T......._ 

c::::::O= 

c::::::():::::l 

=::():::::::1 

--==0==----

5 

I 

7 30 

Cr 

v 

OSAGE AND MERAMEC, c==Q=-"l 

ROUBIDOU~X~.........~:=::::C):==--

I I I I I I I 

Zn 

: tMERAMEC 

_ _....~__.,_.,_.......___.cJEFFERSON CITY 

I I I I I I I I I l I l 1 I 

G31 

300 

3 5 7 10 15 20 30 50 20 30 50 70 100 150 200 300 500 700 1000 1500 2000 3000 5000 8000 

----'==::::::X:)::::::==---<:::.!R~OUBIDOUX POTOSI 

------I.==:::O===-~tcR~O~U:!!:BIDOUX 

: 

Se 

5 

CONCENTRATION IN PARTS PER 

tBONNETERRE 

Cu 
G32 GEOCHEMISTRY OF LOESS AND CARBONATE RESIDUUM 

Olsen, C. G., and Ruhe, R. V., 1978, A mechanism for the origin of, 

terra rosa in humid karst, southern Indiana, U.S.A. [abs.]: 

Geological Society of America Abstracts with Programs, v. 10, 

no. 6, p. 280. 

Ray, L. L., 1967, An interpretation of profiles of weathering of 

the Peorian Loess of western Kentucky, in Geological Survey 

research 1967: U.S. Geological Survey Professional Paper 

575-D, p. D221-D227. 

Rieger, Samuel, and Juve, R. L., 1961, Soil development in Recent 

loess in the Matanuska Valley, Alaska: Soil Science Society of 

America Proceedings, v. 25, p. 243-248. 

Ruhe, R. V., 1969, Quaternary landscapes in Iowa: Ames, Iowa, 

Iowa State University Press, 255 p. 

Stout, L. N ., and Hoffman, David, 1973, An introduction to 

Missouri's geologic environment: Missouri Geological Survey 

Educational Series, no. 3, 44 p. 

U.S. Geological Survey, 1972a, Geochemical survey of Missouri-Plans and progress for first six-month period 

(July-December, 1969): U.S. Geological Survey open-file report, 

49p. 

__ 1972b, Geochemical survey of Missouri-Plans and progress 

for second six-month period (January-June, 1970): U.S. 

Geological Survey open-file report, 60 p. 

__ 1972c, Geochemical survey of Missouri-Plans and progress ' 

for third six-month period (July-December, 1970): U.S.· 

Geological Survey open-file report, 33 p. i __ 1972d, Geochemical survey of Missouri-Plans and progress 

for fourth six-month period (January-June, 1971): U.S. 

Geological Survey open-file report, 63 p. 

__ 1972e, Geochemical survey of Missouri-Plans and progress 

for fifth six-month period (July-December, 1971): U.S. 

Geological Survey open-file report, 145 p. 

__ 1972f, Geochemical survey of Missouri-Plans and progress 

for sixth six-month period (January-June, 1972): U.S. 

Geological Survey open-file report, 86 p. 

__ 1973, Geochemical survey of Missouri-Plans and progress 

for seventh six-month period (July-December, 1972): U.S. 

Geological Survey open-file report, 86 p. 

Weaver, C. E., and Pollard, L. D., 1973, The chemistry of clay 

minerals: Amsterdam, Elsevier Scientific Publishing Company, 

Developments in Sedimentology, no. 15, 213 p. 

Wharton, H. M., Martin, J. A., Rueff, A. W., Robertson, C. E., 

Wells, J. S., and Kisvarsanyi, E. B., 1969, Missouri 

minerals-Resources, production and forecasts: Missouri 

Division of Geological Survey and Water Resources Special 

Publication, no. 1, 303 p. 

Wickham, J. T., and Lineback, J. A., 1978, Multiple glacial 

advances of western Illinois [abs.]: Geological Society of 

America Abstracts with Programs, v. 10, no. 6, p. 287. 

Wisconsin Uiuversity, Agricultural Experiment Station, 1960, Soils 

of the north central region of the United States-Their 

characteristics, classification: Wisconsin University 

Agricultural Experiment Station Bulletin 544, 192 p. 

<r U.S. GOVERNMENT PRINTING OFFICE: 19B0--777-034f17