trace and minor metals analysis of four streams in central texas

Trace and minor metals analysis of four streams in central Texas

Jessica Garcia

Nick Kelley

Nathan Roddy

Matt Webb

Geochemistry of Natural Waters

Dr. Franco Marcantonio

December 03, 2012

Metals analysis of four Texas streams 2

Procedure

Water samples were collected directly from the streams using sterile polypropylene

centrifuge tubes. Teams 2-4’s samples were put on ice after being collected and then frozen for

approximately two days. The samples were then allowed to thaw at room temperature before

being filtered and acidified. This most likely affected the results due to the samples being

exposed to freeze-thaw activities and acidified much later than recommended affecting the

chemistry. The samples were filtered using a vacuum filtration system. Team 1’s samples were

run through a 0.4 micron polymer filter and Teams 2-4’s samples were run through 1 micron

cellulose filters. All of the samples were then acidified with a 2% HNO3 solution. HNO3 was

used to decompose ion pairs and prevent post-precipitation of magnesium and calcium salts, as

well as prevent the growth of molds and algae. Four to five dilution standards were prepared

from a known stock solution which included all of the elements of interest in known ratios. For

an internal standard, Indium-115 was added at a concentration of 10 ppb to the water samples

and dilution standards. The dilution standards are bracket concentrations of all the elements in

the sample and the dilution percentage is changed by roughly an order of magnitude for each

dilution. The indium corrects for temporal variability, resulting in a more precise working curve.

A working curve is a plot of the analytical signal (the instrument or detector response) as a

function of analyte concentration. These working curves are obtained by measuring the signal

from the series of standards of known concentration. The working curves are then used to

determine the concentration of an unknown sample, or to calibrate the linearity of an analytical

instrument. If all the working curves are precise and straight with very high R^2 values, the

samples can then be analyzed. The resulting counts can then be converted to concentrations

using the working curves.


Hydrological Considerations

We decided to consider the hydrological aspects of the four streams included in this

analysis. These four stream bodies can generally be classified in three categories based on size.

The Brazos River is a large statewide river; at 840 miles long it is the longest river contained

wholly within the state. It has numerous large reservoirs along its length and is used extensively

for water supply, hydropower, and irrigation. The Navasota River is a regional river of 125

miles, much shorter than the Brazos, it is moderately dammed. The result is that flow regimes in

these two systems are a function of precipitation (event flows), groundwater interaction (base

flows), and reservoir releases. Flow rates for these two systems are also gaged by USGS making

water chemistry vs. flow rate comparisons possible. By comparison, Lick Creek and White

Creek are much smaller systems and are likely to be dominated by local precipitation events.

For this portion of our analysis, we used Alex’s data. This was due to the fact that we were

considering the impact of flow and precipitation events and were too tightly bunched temporally

in the group versus group data. Alex’s data can generally be categorized as being taken from the

February and August timeframes. Source data originated from the National Weather Service

(precipitation) and from USGS (flows) and are shown in Figure 1 and Table 1 below.


Figure 1: Study Area Temperature and Precipitation

Source: National Weather Service

The relationship being studied was the effect of precipitation, evaporation, and flow rate

on chemical concentration. Bicarbonate was chosen as the element of study due to its high

concentration and high variability. Inspection of all data in Alex’s data set reveals that almost all

cations and anions follow the behaviors noted in the bicarbonate study.

Our theory was that water systems would become more highly concentrated with

dissolved solids during times of reduced rainfall. The potential for this effect was first analyzed

on Lick and White Creeks. Quite fortunately, the precipitation and evaporation regimes were

very different across the two sampling timeframes. Evaporation is a strong function of

temperature and the approximated mean during the first sampling at each site as taken visually

from Figure 1 was 60 F while the second sampling was about 20 degrees higher with afternoon


highs around 100 F. The precipitation amounts (Table 1 below) were much higher during the

first sampling versus the second, 12 inches to 4 inches respectively. The lower precipitation and

higher evaporation (as proxied by temperature) should lead to high dissolved concentrations of

bicarbonate. That’s exactly what was found, concentrations were three times the concentration

of the first samplings.

The Navasota and Brazos Rivers have the extra complication of receiving discharge from

upstream reservoirs (Limestone and Whitney, respectively). The first sampling of the Navasota

had high precipitation and high discharge. One would expect the river to have concentrations

slightly lower than Limestone due to dilution and that is exactly what the data indicates: 89 ppm

at Limestone and 83 ppm in the Navasota. During the second sampling with low flows and low

precipitation, significant increases in concentration might be expected and that is what the data

indicates as well, with concentrations increasing to 378 ppm.

We felt very good until we looked at the Brazos. It showed a very consistent bicarbonate

concentration moderately higher than Lake Whitney despite large changes in precipitation,

evaporation, and flow rate. This behavior indicates the complicated nature of natural processes

and would require further study. As such, we lack an explanation for this behavior. It should be

noted that had we substituted Na for bicarbonate as our representative compound, this confused

behavior would not have been exhibited. We decided on bicarbonate specifically because it

showed that small studies often result in insufficient conclusions.


Source Sample Date

(2012)

Preceding

Precip

(Monthly inches)

Discharge

(cfs)

Concentration

HCO3

(ppm)

Lick2/14 12 NA 128

7/23 4 408

White2/18 12 NA 122

7/26 4 376

Navasota2/20 12 1100 83

9/10 3 8 378

Brazos3/21 6 2500 211

8/16 0 500 203

Limestone 8/3 NA NA 89

Whitney 8/3 NA NA ~180

Table 1: Concentration Comparison

Mineral SI

In order to see what minerals would precipitate from the various concentrations of all the

ions from the samples that we collected as well as those provided from Alex’s personal

collection, we used Visual MINTEQ to see which combinations of ions would produce minerals.

The program takes into account the temperature, pH, alkalinity, and concentration of each

dissolved ion in the water sample and produces an extensive table describing the molality and

activity of every conceivable ion as well as certain molecules. The main purpose of using the

MINTEQ program is to identify what minerals are present and to see how saturated the water is

relative to each mineral.


Visual MINTEQ provided a very extensive list of possible mineral combinations from the

inputted data derived from the ICPMS. Many of the species it provided are very abstract and

uncommon, whether it is from the scarcity of the element or the state that the ion has to be in

order for a mineral to precipitate. The vast majority of the ions tested showed most

combinations of minerals from the dissolved ions had a slightly negative SI number on the order

of -0.1 to relatively high negative SI numbers around -70 for a particular lead carbonate hydroxyl

mineral. Most SI numbers however were much less extreme and were on the range of around -1

to -20. For example, Table 2 shows all four streams are under-saturated with the common

evaporite mineral gypsum, and calcite/aragonite is also slightly under-saturated.

There were of course some mineral combinations that were supersaturated. Many of the

supersaturated minerals are the ones that are much more common and less obscure than many of

the under-saturated minerals. The range of SI numbers for the supersaturated minerals is

actually larger than the range that corresponds to the under-saturated minerals. This is not

because of extremely supersaturated minerals that might precipitate out of the water; it is because

many minerals are so close to equilibrium that their SI numbers are quite low. An example of a

low saturation index number is demonstrated in Table 2, Team 1’s Brazos data showed that

gibbsite has a SI of 0.03 meaning that it is closer to being in equilibrium and most any other

mineral. In fact, gibbsite is so close to being in equilibrium when Team 1 collected their sample,

that when the remainder of the teams collected samples gibbsite was under-saturated. Low

positive SI numbers are expected to be lower and closer to equilibrium than minerals that are

under-saturated. This is only true when the sampling site is not close to a major point source area

of erosion or tributary nearby that would add excess amounts of dissolved ions to the water.


Saturation

Indices

Hematite

(Fe2O3)

Cupric Ferrite

(CuFe2O4)

Calcite

(CaCO3)

Gibbsite

(AlOH3)

Gypsum

(CaSO42)

Team1

Brazos 13.01 11.70 0.60 0.03 -1.64

Navasota 14.91 13.14 -0.52 0.73 -2.37

White 9.42 14.67 0.31 0.49 -1.37

Lick 15.26 13.46 -0.17 2.18 -2.19

Team 2

Brazos 13.96 13.23 1.07 -0.29 -1.22

Navasota 15.93 14.98 0.39 0.73 -2.40

White 15.73 15.50 1.00 0.49 -1.38

Lick 15.99 15.01 0.24 1.16 -2.02

Table 2: Common Mineral SI Indices from Visual MINTEQ

The minerals in Table 2 were chosen due to their abundance, familiarity, and ability to

track the effects of precipitation events upstream. Each mineral is composed of important ion,

both cation and anions, found in natural waters. Iron is an important minor ion to test for in

natural waters because iron is a good indicator of pollution rates from acid mine drainage and

certain ecosystems, and of course erosion from other iron bearing minerals such as magnetite and

pyrite and any mafic rocks that is a drainage basin. In our case, there are not any mafic rocks

present on the surface or large mining operations upstream, thus shrinking the sources that could

introduce iron into the streams affecting the SI values. Generally speaking, hematite and cupric

ferrite to an extent are usually found in most natural waters, and in this particular case, they are


both clearly fully supersaturated and consistent probably resulting from oxide minerals in the soil

or industrial pollution.

As mentioned earlier, the Brazos has the furthest reach and the highest flow rate and

discharge of the four streams that were tested, with the headwaters originating to the northwest

portion of Texas where evaporite deposits such as gypsum and clay soils are very prevalent.

With that said, the Brazos is exposed to a greater variety of rock types over it course and is likely

to have a greater variety of minerals and dissolved ions as well. It is also true that, due to its

size, the concentrations of ions are not likely to change as much as either White or Lick would

between and after precipitation events. For example, the result of a large precipitation event that

occurs around the headwaters, where large amounts of gypsum/anhydrite and fine gain clay soils

are eroded, would not readily be noticed at our testing site in College Station due to the dilution

effects of tributaries and springs adding their own blend of ions as well as other precipitation

events causing more runoff and erosion. As a result, the high quantity of gypsum that is

inevitably eroded to the northwest is diluted to the point the point of having similar SI values as

all the other streams. The Navasota River is about an eighth as along as the Brazos, and White

and Lick are relatively very small and only have local reaches equates that the SI values for the

mineral will have a greater percentage of change after a precipitation event and during periods of

drought. The SI values are dictated directly by the local strata a rather than by the geology

hundreds of miles away.

While these differences and similarities discussed are some of the more important and

recognizable minerals, they were not the only connections that could be made. There were many

other examples of less common minerals that would require much more research than the scope

of this paper allows.


Quality

Contaminates and trace elements find their way into water sources both naturally and

through human activities. At certain amounts these elements can become harmful when

consumed by humans and as a preventative measure the Environmental Protection Agency

(EPA) and the World Health Organization (WHO) have created guidelines and regulations for

drinking water quality. In the United States the EPA has created National Primary Drinking

Water Regulations. These regulations are legally enforceable standards that apply to public water

systems. Primary standards protect the health of the public by limiting the levels of contaminants

in drinking water. There is a set Maximum Contaminant Level (MCL) which is the highest level

of a contaminant that is allowed in drinking water. Globally, WHO has created a set of

provisional guideline values for safe drinking-water at which there are no significant risk to

health over a lifetime of consumption.

The data collected, specifically for Team 1 and Teams 2-4 (avg.) were compared to the

MCL’s designated by the EPA and the guidelines created by the WHO. The elements examined

were primarily trace metals, including Mg, Al, Ba, Fe, Mn, Cu, Cd, Pb, and U. Neither the EPA

nor WHO designated a value for magnesium because of the uncertainties surrounding mineral

nutrition from drinking-water. There is insufficient scientific information on the benefits or

hazards of long-term consumption of very low mineral waters to allow any recommendations to

be made. The WHO also did not set a guideline for aluminum based on the fact that a health-

based value of 0.9 mg/l could be derived from the Joint FAO/WHO Expert Committee on Food

Additives provisional tolerable weekly intake (PTWI), but this value exceeds practicable levels

based on optimization of the coagulation process in drinking-water plants using aluminium-

based coagulants: 0.1 mg/l or less in large water treatment facilities and 0.2 mg/l or less in small


facilities. Also guideline values for iron and manganese were not established due to levels of

manganese and iron not bringing health concern at levels found in drinking-water. Natural fresh

waters contain iron at levels ranging from 0.5 to 50 mg/l. At levels above 0.3 mg/l, iron stains

laundry and plumbing fixtures. There is usually no noticeable taste at concentrations below 0.3

mg/l, although turbidity and color may develop at concentrations higher than 0.1 mg/l,

manganese causes an undesirable taste in beverages and stains sanitary ware and laundry but

does not pose a health concern at the levels found in drinking water. Both the EPA and WHO

have designated guideline and MCL values for barium, copper, cadmium, lead, and uranium

noted in Tables 3 and 4.

Mg Al Ba Fe Mn Cu Cd Pb U

ICP

MS

Res

ult

s (p

pb

) Brazos 5662.79 1.58 62.89 0.87 0.64 0.83 0.05 0.05 0.68

Navasota 1489.70 18.90 20.90 30.43 2.36 3.94 0.16 0.28 0.18

White 1548.29 10.89 24.40 25.24 3.94 6.51 0.08 0.24 0.99

Lick 1786.60 26.18 23.66 40.06 3.97 3.87 0.12 0.34 0.25

WHO (ppb) -- -- 700 -- -- 2000 3 10 30

EPA (ppb) -- 50-200 2000 300 50 1300 5 15 30

Table 3: Team 1’s ICPMS results compared to WHP and EPA drinking water MCL’s


Mg Al Ba Fe Mn Cu Cd Pb UIC

PM

S R

esu

lts

(pp

b) Brazos 6568.13 3.16 61.06 1.43 0.20 0.76 0.06 0.04 0.62

Navasota 1885.42 12.38 26.36 14.93 0.21 2.24 0.11 0.09 0.27

White 2231.56 12.22 34.86 10.39 0.66 7.47 0.06 0.07 2.46

Lick 1551.87 20.07 21.86 25.91 0.23 3.72 0.19 0.12 0.15

WHO (ppb) -- -- 700 -- -- 2000 3 10 30

EPA (ppb) -- 50-200 2000 300 50 1300 5 15 30

Table 4: Teams 2-4’s (avg.) ICPMS results compared to WHO and EPA drinking water MCL’s

When Team 1’s data is compared to the values stated by the WHO and the EPA,

all of the elements concentrations fall into a safe range as observed in Table 3. Magnesium levels

were highest in the Brazos and increasingly less in Lick Creek, White Creek, and Navasota

respectively ranging from 5662.79 ppb to 1489.70 ppb. Team 2-4’s (avg.) values of elements are

well within a healthy range when compared to the WHO and EPA’s standards as well as seen in

Table 4. The levels of magnesium are highest in the Brazos and increasing less so in White

Creek, Navasota, and Lick Creek, respectively ranging from 6568.13 ppb to 1551.87 ppb. In all

of our data aluminum is highest in Lick Creek perhaps due to the feldspar and clay content in the

area. Barium has the highest concentration in the area of the Brazos River. Major sources of

barium in drinking water come from discharge of drilling wastes, discharge from metal

refineries, and erosion of natural deposits. The highest amount of iron is found in Lick Creek

with a value of 40.06 ppb for Team 1 and 25.91 ppb for Team 2-4 (avg.). This iron concentration

is most likely due to oxide minerals being dissolved into the groundwater. As for cadmium the

highest amounts for all groups was detected in White Creek in all likelihood due from erosion of


natural deposits, discharge from metal refineries, or runoff from waste batteries and paints.

Amounts of manganese, cadmium, lead, and uranium ranges are not only much lower than the

MCLs or standards; they are not variable enough for mentioning and seen in Figures 2 and 3.

Al Ba Fe Mn Cu Cd Pb U0

10

20

30

40

50

60

70

BrazosNavasotaWhiteLick

Figure 2: Team 1 Data excluding Mg

Al Ba Fe Mn Cu Cd Pb U0

10

20

30

40

50

60

70

BrazosNavasotaWhiteLick

Figure 3: Teams 2-4 averaged data excluding Mg

Conductivity is a measure of the ability of water to pass an electrical current.

Conductivity in water is affected by the presence of inorganic dissolved solids such as chloride,


nitrate, sulfate, and phosphate anions, and sodium, magnesium, calcium, iron, and aluminum

cations. Organic compounds like oil, phenol, alcohol, and sugar do not conduct electrical current

very well and therefore have a low conductivity when in water. Conductivity is also affected by

temperature: the warmer the water, the higher the conductivity. According to the EPA, the

conductivity of rivers in the United States generally ranges from 50 to 1500 µmhos/cm. Studies

of inland fresh waters indicate that streams supporting good mixed fisheries have a range

between 150 and 500 µhos/cm. Conductivity outside this range could indicate that the water is

not suitable for certain species of fish or macro-invertebrates. Industrial waters can range as high

as 10,000 µmhos/cm. The conductivity levels found in the Brazos area are stated in Table 5 and

fall in the range of normal conductivity for the United States although all of the fluvial bodies

have a conductivity above 500 µmhos/cm and may indicate the water is not suitable for certain

aquatic life.

SourceConductivity

(Team 1)

Conductivity

(Teams 2-4)

Lick 800.00 882.00

White 533.00 782.0

Navasota 615.00 782.00

Brazos 862.00 1027.00

Table 5: Conductivity values

Conclusion


In this paper, we examined several different aspects regarding the water samples

we collected in order to better understand what process affect the concentration of the dissolved

ions, the saturation of minerals comprised of the dissolved ions, and how the quality of the water

compares to regulated standards. We have shown that our four streams are affected by dams,

precipitation events, and upstream lithology. Chemical concentration behavior was dominated

by precipitation effects, especially in the smaller stream systems of Lick and White Creeks.

Periods of low precipitation and high evaporation led to dramatically higher concentration levels.

This was also generally true of the larger, dammed systems except the chemical concentration

generally mimicked the reservoir upstream of sampling. This was surprisingly not true of

bicarbonate concentration in the Brazos.

The analysis of the results from Visual MINTEQ program gave good insight to

what minerals are likely to form from the waters, which again gives insight to the origins of the

waters as well as how the lithology and soil type changes during the span of the stream by telling

the saturation indexes of many different mineral present. Upstream lithology definitely plays a

factor in all water both surface and ground, but might not be apparent if far enough away from

the source. Such is the case with gypsum, the headwaters of the Brazos originate in the

northwest portion of the state where there are high amounts of evaporite deposits but due to high

solubility and distance, our results showed that the water was under-saturated.

Finally, we discussed both the national and international regulatory standards

provided by EPA and WHO. Upon comparing the concentrations of our ions to that of these two

agencies, we are confident that all of the rivers within this study are well within the parameters

set by each respective agency. In most cases, our results from the ICP-MS compared to


regulations are different by an order of magnitude, if not more. The conductivity of the water is

also well within the range dictated by the EPA.

trace and minor metals analysis of four streams in central texas

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