Filtered and unfiltered water samples were collected from the upper Ottawa River at 3 ... me collect data, working with GIS, and adobe illustrator. I could not have ...
TRANSPORTATION OF TRACE METALS AND MAJOR ELEMENTS IN THE OTTAWA RIVER, NORTHWEST OHIO
Corrina Bissell
A Thesis Submitted to the Graduate College of Bowling Green State University in partial fulfillment of the requirements for the degree of
MASTER OF SCIENCE August 2012 Committee: Sheila J. Roberts, Advisor James E. Evans Enrique Gomezdelcampo
© 2012 Corrina Bissell All Rights Reserved
ii ABSTRACT
Shelia J. Roberts, Advisor
Sediments in the lower parts of Ottawa River in Toledo, Ohio have a known history of contamination. Upstream studies have not shown a significant amount of contamination in sediments, but have found some metals present within the fine grained and/or organic material. This contaminated material is easily transported in the suspended load down the Ottawa River. This study addressed transport mechanisms of dissolved and solid phase to determine which was dominate for trace metal and major element concentrations. Filtered and unfiltered water samples were collected from the upper Ottawa River at 3 sites in the Wildwood Preserve Metropark (WW1, WW2, and WW3) and at 2 sites in Secor Metropark (SC2 and SC3). Samples were also collected to determine the total amount of suspended material in the river. Total Suspended Solids (TSS) was analyzed by filtering water samples through coarse, medium, and fine filter paper. Unfiltered water samples were digested following the procedure in EPA method 3105a. All water samples were analyzed for selected major and trace elements using the Inductively Coupled Plasma-Optical Emission Spectrometer (ICP-OES) at Bowling Green State University. Unfiltered sample concentrations were subtracted from filtered sample concentrations to evaluate the solid phase in the suspended load. A Mann-Whitey test of the filtered and unfiltered samples showed there was a significant difference between the two sample types. Discharge was shown as the most significant factor controlling the elemental concentrations through the Principal Component Analysis (PCA) in both the unfiltered and filtered samples. The negative correlations of discharge vs. elemental
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concentrations indicate the influence of groundwater and the positive show the influence of surface water runoff. Discharge was also found to contribute to positive correlations in both the filtered and unfiltered samples for Zn and Sr. The most significant major elements contributing to the variation were Na and Ca found by unfiltered and filtered PCA. The most significant trace metals were Fe and Sr. TSS was found as not a significant factor influencing the elemental concentrations in the PCA. This result is due to the filtering process missing the grain size of 2.5µm to .45µm and grain sizes smaller than 0.45 m. Sources of the elemental concentrations can be anthropological and/or natural. Anthropological sources of overflow from adjacent storm drains could contribute to the concentrations. Natural sources of local soil and bedrock compositions within the watershed and near the metroparks can account for the elemental concentrations.
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ACKNOWLEDGEMENTS I would like to thank the people who have helped guide me through my graduate career at Bowling Green State University. First I would like to thank my advisor, Dr. Roberts, for assisting me on my research and advising me. I also want to thank Dr. Evans and Dr. Gomezdelcampo for answering my questions and guiding me through my thesis. Thanks to those whom have helped me in the geochemistry lab, Dr. Farver and Neal Cropper. Thank you Katybeth Coode for helping me collect data, working with GIS, and adobe illustrator. I could not have completed my thesis without you. Thank you Brian Renshaw for encouraging me and supporting me throughout my graduate career. For my family, who was always there to give me confidence and love.
v TABLE OF CONTENTS
Page INTRODUCTION………………………………………………………………………… 1 METHODS ……………………………………………………………………………….. 11 Study Area………………………………………………………………………… 11 Field Work………………………………………………………………………… 24 Laboratory Work………………………………………………………………….. 31 Daily Flux …………………………………………………………………………. 33 Influence of Discharge…………………………………………………………….. 34 Statistically Analysis………………………………………………………………. 35 RESULTS…………………………………………………………………………………. 37 Total Suspended Solids Characterization………………….………………………. 39 Sediment Flux and Concentrations………………………………………………... 45 Discharge………………………………………………………………………….. 49 Filtered vs. Unfiltered……………………………………………………………… 51 Principle Component Analysis……………………………………………………. 53 Covariance Relationships of Elements and Discharge……….………………….. 65 DISCUSSION……………………………………………………………………………... 78 Total Suspended Solids and Sediment Flux……………………………………… 78 Impact of Discharge………………………………………………………………. 79 Transportation of the Elemental Concentrations………………………………… 82 Sources……………………………………………………………………………. 85
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CONCLUSION……………………………………………………………………………. 87 REFERENCES……………………………………………………………………………. 89 APPENDICES…………………………………………………………………………….. 95 APPENDIX A SOIL DESCRIPTIONS…………………………………………………… 96 APPENDIX B UNFILTERED AND FILETERED CONCENTRATIONS……………… 102 APPENDIX C DAILY FLUX MEANS………………………………………………….. 115
vi LIST OF FIGURES/TABLES
Figure/Table 1
Page
Cation Exchange Capacity Results Modified from Malcom and Kennedy (1970) for Differing Particle Size ...........................................................................................
5
2
Water Discharge vs. Zn Concentrations for Unfiltered, Filtered, and Total ............
7
1
Previous Studies in the Ottawa River Showing Contamination above the PEL .......
12
3
Study Area Location in Lucas County, Ohio ..........................................................
13
4
Bedrock Map of Study Area in Lucas County, Ohio ..............................................
15
2
Stratigraphic Section of the Study Area .................................................................
16
5
Wildwood Metropark Soil Map Located in Lucas County, Ohio ............................
18
6
Secor Metropark Soil Map Located in Lucas County, Ohio ...................................
19
7
Land Use Map of Study Area.................................................................................
21
8
Wildwood Metropark Sample Locations in Lucas County, Ohio ............................
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9
Secor Metropark Sample Locations in Lucas County, Ohio ...................................
26
10
Mean Daily Discharge Values During Sample Period May19th to November 15th
28
3
List of Sampling Dates in Each Location and Number of Filtered, Unfiltered, and TSS
samples taken 4
......................................................................................................
29
Standard Statistics of Major Elements and Trace Metals in Differing Phases of Solid and
Dissolved in Concentrations of ppm ...............................................................................
38
11
TSS in g/L on Sample locations WW1, WW2, WW3, SC2, and SC3 .....................
40
12
Correlation of TSS to the Discharge in Sample Locations WW1, WW2, WW3, SC2, and
SC3
......................................................................................................
42
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Slope and R Squared Value of Discharge Plotted Against TSS ..............................
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13
Daily Sediment Flux for each Sample Location during the Sample Period .............
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6
Sample Locations and Highest Average Mean for Daily Elemental Flux and Rank of
Daily Sediment Flux ......................................................................................................
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14
Daily Elemental Flux for each Sample Location during the Sample Period ............
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15
Discharge vs. Total Metal Concentration in Filtered, Unfiltered, and Sum of Both
Samples for Zn and Sr .................................................................................................... 7
Mann-Whitney Test Results and P-Value for Major Elements and Trace Metals in the
two phases 8
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.......................................................................................................
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Principal Components from PCA of Discharge, Trace Metals, and Major Elements in
Unfiltered Samples .......................................................................................................
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9
PCA of Discharge, Trace Metals, and Major Elements in Unfiltered Samples ........
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10
Principal Components from PCA of Discharge, Trace Metals, and Major Elements in
Filtered Samples
11
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.......................................................................................................
58
PC1 vs. PC2 for Filtered Samples Including Discharge, Major Elements, and Trace
Metals 12
.......................................................................................................
PC1 vs. PC2 for Unfiltered Samples Including Discharge, Major Elements, and Trace
Metals 17
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Loadings from the PCA of Discharge, Trace Metals, Major Elements in the Filtered
Samples 16
.......................................................................................................
.......................................................................................................
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Principal Components from PCA of Discharge, Trace Metals, Major Elements in the
Solid Phase
.......................................................................................................
61
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Loadings in PCA of Discharge, Trace Metals, Major Elements in the Calculated Solid
Phase
.......................................................................................................
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14
Principal Components from PCA of TSS, Trace Metals, and Major Elements ........
63
15
Loadings from PCA of TSS, Trace Metals, and Major Elements in Solid Phase .....
64
16
Linear Correlation Matrix of Calculated Solid Phase with Major Elements, Trace Metals,
and Discharge 18
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Linear correlation matrix for the unfiltered sample with trace metals, major elements and
Discharge 17
.......................................................................................................
.. .....................................................................................................
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Linear Correlation Matrix of Dissolved Phase with Major Elements, Trace Metals, and
Discharge
.......................................................................................................
69
18
Correlation Graphs to Fe........................................................................................
70
19
Correlation Graphs to Ca Concentrations ..............................................................
72
20
Correlation Graphs to Discharge ............................................................................
75
21
Unfiltered Samples, Filtered Samples, and Total Zn to an Increasing Discharge with
Sample from WW3 Missing from May 19th ...................................................................
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INTRODUCTION Freshwater from river systems makes up a total of 0.003% in Earth’s water supply. This amount is important for municipal water supplies, recreational use, agricultural irrigation, transportation of materials, and industries (Miller and Miller, 2007). Contamination of a river can impact these economical usages, and have negative impacts on ecological systems and human health. Contamination can be recognized through biological impairment, nutrient criteria, and contaminated sediments. Biological impairment is caused from six major factors outlined by the OEPA which include habitat alterations, organic enrichment, siltation, metals, flow alteration and nutrients (nitrogen and phosphorous),(Rankin et al., 1998). High amounts of nutrients can lead to algae blooms that deplete the amount of oxygen in the water affecting the bioactivity. Human health is also affected from cyano bacteria which produces a toxin that can be ingested from recreational activities (Dubrovsky et al., 2010). Sediments become contaminated from industry release, municipal waste discharges, runoff, or atmospheric transportation. Sediment monitoring is important since contaminated particles can affect bioactivity, recreational use, and human health. These factors are recognized by regulations and monitoring through state and federal agencies (EPA 1998). Sediments do not always remain deposited in a river. They can collect at the bottom of a stream and be resuspended from human activates, bioturbation, or flooding events. The mobility of contaminated sediments is essential to understand since downstream transport of increased sediment load can cause further problems. Rivers can transport material in the bed load, suspended load, and dissolved load. Chemicals dissolved in the liquid phase are defined as the dissolved load. Several studies define
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the dissolved load as any material less than 0.45μm; (Cortecci et al, 2009, Horowitz, 1996, Frӧhlich et al., 2008). The dissolved includes dissolved organic matter and colloids transported in solution. The suspended and bed loads are composed of the solid material in the stream. The suspended load is classified as fine sediment retained in the 0.45μm filter that is transported in suspension (Horowitz, 1991). The bed load is defined as larger particles sizes of coarse sands to cobbles near the stream bed that move by rolling and saltation (Miller and Miller, 2007). Contaminants can be transported via any of the mechanisms described above. Generally, the dissolved phase is the primary focus in contamination studies since it is considered to be more bioavailable. However, the suspended load is an important since the suspended sediment is a primary sink for trace metals and may have concentrations orders of magnitude higher than in the dissolved phase (Miller and Miller, 2007). Most fluvial environments have a strong correlation of total trace metal concentrations in the suspended load rather than in the dissolved (Zonta,2005; LeBlanc, 2001; Blake et al., 2003). Generally, concentrations of As, Cd, Hg, Pb, and Zn are highest in particulates and bottom sediments (Horowitz, 1991). Bed load transportation is excluded from the dominate transportation due to the low metal concentrations relative to the larger grain size. The dynamics of contaminant transport in fluvial environments depend on sediment size, sediment texture, mineralogy, hydrology, climate, and geomorphology (e.g. Horowitz, 1996). Sediment size, mineralogy, and texture have a relationship to the cation exchange capacity. The size of the sediment relates to the ability to absorb contaminants; the smaller the sediment size, the greater the amount specific surface area (Hiemenz and Rajagopalan, 1997). Larger particle sizes such as sand and gravel have a significantly lower specific surface area, resulting in a low
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cation exchange capacity. This relationship demonstrates bed load transportation as not as important since it contains larger particle sizes (Literathy et al., 1994, Nelson and Lamothe, 1993, and Che et al., 2003). These values and the specific area relationship to cation exchange are expressed in Figure 1 from Malcolm and Kennedy (1970). Their study focused on the importance of cation exchange in different particle sizes including clay, silt, sand, and gravel. Their results show that clays have higher cation exchange than sand and gravel size particles. The composition of the suspended load affects the trace metal absorption. Clay minerals will vary on their exchange capacitates for absorption. Fine grained, montomorillonite (0.001, statistically significant p>0.001, statistically significant p>0.001, statistically significant p>0.001, statistically significant p0.001, statistically significant p>0.001, statistically significant p>0.001, statistically significant p0.001, statistically significant p>0.001, statistically significant p0.001, statistically significant
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Principal Component Analysis
This study conducted PCAs on both unfiltered and filtered samples comparing trace metals, major elements and discharge. For the unfiltered samples, PC1 had a 77.6% of variance (Table 8). Discharge had the highest eigenvalue, and therefore was most heavily loaded (0.989) followed by Na (-0.135) (Table 9). PC2 accounts for15.2% of variance; Na, (0.943) and Ca (0.280) were heavily loaded in PC2 (Table 9). Results for the filtered samples are similar. PC1 accounts for of 91.8% of the variance (Table 10). Again discharge had the highest eigenvalue (0.987) and was most heavily loaded followed by Na (-0.156) (Table 11). PC2 accounted for 5.16% of variance with Na (0.962), Ca (0.195), and discharge (0.159) most heavily loaded (Table 11). According to the loadings for both filtered and unfiltered samples, discharge controlled much of the variation in the samples followed by the major elements Na, and Ca. Sr and Fe were the most important trace elements. Figure 16 and 17 show plots of PC1 vs. PC2 for the unfiltered and filtered samples. The PC1 axis shows the influence of discharge. The PC2 axis represents the influence of Na, following Ca. Samples from November 3rd move from a greater value of the PC2 axis in the unfiltered sample to a smaller PC2 axis values in the filtered samples. Secor samples from September 10th are separated in Figure 13 but grouped in close proximity in Figure 14. November 15th samples and May19th samples have the highest values on the PC1 axis in both the unfiltered and filtered diagrams. Samples from June 28th and August 7th both have higher PC2 values in both diagrams. Samples from May 24th, August 24th, June 8th, July 12th, and September 5th increase from the unfiltered to filtered PC2 values.
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Table 8: Principal components from the PCA of discharge, trace metals, and major elements in the unfiltered samples.
PC 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
Eigenvalue %Variance 143×103 77.6 1 282×10 15.2 1 127×10 6.84 26.2 0.142 16.4 0.885×10-1 7.82 0.422×10-1 1.55 0.839×10-2 0.101×10-1 5.45×10-5 0.367×10-2 1.9×10-5 0.131×10-2 7.09×10-6 -3 0.551×10 2.97×10-6 0.473×10-3 2.55×10-6 0.207×10-3 1.12×10-6 7.34×10-5 3.96×10-7 3.95×10-5 2.13×10-7 1.62×10-5 8.75×10-8 2.07×10-29 1.12×10-31 7.19×10-35 3.88×10-37
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Table 9: PCA of discharge, trace metals and major elements in the unfiltered samples. The loadings correspond to Table 8. The bolded numbers show significance.
Loadings Ba Cd Co Cr Cu Fe Mn Mo Ni Pb Sr Zn As Ca K Mg Na Discharge
Axis 1 Axis 2 Axis 3 0.237×10-3 0.392×10-3 0.74×10-3
