1. Predicting Hotspots for Heavy Metal Contamination in Bumpus Cove, TN Melissa A. Magno, Arpita Nandi, and Ingrid Luffman, Department of Geosciences, East Tennessee State University
Introduction
Abandoned mines release heavy metals into the soil which become mobile and give rise to public and environmental health concerns (Alloway, 1995).
Pollution severity varies with toxicity, mobility, and bioavailability potential of the metals on site (Roberts and Johnson, 1978).
Heavy metal pollution may vary greatly within a site due to
Mine location and processing practices,
Duration since mine abandonment,
Routes of metal transport,
Density and types of vegetation, and
Soil physio-chemical properties.
In particular, the parent material, local topography, grain size, pH moisture content, soil mineralogy, total organic content (TOC), cation exchange capacity (CEC), and porosity are related to heavy metal mobility and persistence (Forstner, 1980; Harter, 1983; Li and Shuman, 1996; Ersoy et al., 2004; Tom-Peterson et al., 2004).
ABSTRACT
Anthropogenic activities, such as mining, release heavy metals into the soil and potentially present environmental health concerns. Soil physical and chemical properties play a key role in understanding the mobilization of heavy metals in soils, with finer fractions showing higher heavy metal concentrations. This study quantified texture, permeability, and pH in 53 soil samples collected in a 0.67 km2 study area containing 7 known abandoned Pb, Zn, and Mn mines in Bumpass Cove. The results of this analysis were interpolated using kriging and examined to predict hotspots for heavy metal contamination. This analysis of soil properties will lay the foundation to understand heavy metal concentration and transport in Bumpass Cove, TN.
Sand
Clay pH
Moisture Content
Methods
Bumpus Cove, TN
Once one of the richest mineralized districts of eastern TN, Bumpass Cove (Figure 1) is home to at least 47 inactive iron (Fe), zinc (Zn), lead (Pb), and manganese (Mn) ore mines all of which were permanently closed in the 1950s (Burdick, 1993). This 0.67 km2 study area was chosen because it encompasses 7 abandoned Zn, Pb, and Mn mines at the top of the Bumpus Cove watershed.
Raster Math
To develop prediction surface
Soil Samples Collected
(n=53)
Using a semi-random sampling strategy
Physical Tests
Grain Size Distribution (GSD)
Moisture Content
Chemical Tests
Soil pH
Geospatial Modeling
Kriging interpolation for each variable
Study Area
Bumpus Cove Watershed
Figure 2. Flow chart illustrating the methods performed to evaluate levels of heavy metals within the Bumpus Cove study area
Figure 3. Raster math calculated with four variables to produce a predictive surface, which was then applied to the topography
Results and Discussion
The higher values (red) in the predictive surface indicated hotspots for heavy metal accumulation combining four variables and their relationship to heavy metal deposition:
Sand  - heavy metal concentrations should decrease with increasing sand concentrations (Forstner, 1980)
Clay  - heavy metal concentrations should increase with increasing clay concentrations (Forstner, 1980)
Moisture Content  - heavy metal concentrations should increase with moisture content (Tom-Peterson et al., 2004)
pH  - heavy metal concentrations should increase with increasing (basic) pH values (Harter, 1983)
Factors positively related to heavy metal transport were added, and those negatively related were subtracted in the final equation, with each factor having equal weight
Due to the drainage of the study area, heavy metal attenuation is more likely around and northeast of the abandoned mine locations
Heavy metal accumulation is not expected to occur along the ridges or uphill of the abandoned mines. The largest hotspot in the predictive surface is affected by the increased clay and decreased sand content in the westernmost ridge.
Figure 1. Bumpus Cove study area (0.67 km2) in northeast TN, showing mine and sample locations.
Conclusions
A predictive surface was created via raster math in ArcGIS 10.1 to determine hotspots for heavy metal deposition in the vicinity of an abandoned mine complex in Bumpus Cove, TN.
Elevated levels of heavy metals are expected around and downstream of the mine locations within the red and orange areas of the predictive surface.
In the future, the predictive surface will be validated and refined by Inductively-Coupled Plasma Mass Spectrometry (ICP-MS) comparison with heavy metal concentrations at the sampling sites.
Also, additional soil physio-chemical properties (such as total organic content [TOC], Porosity, Bulk Density, Soil mineralogy, cation exchange capacity [CEC]) will assist in refining the predictive surface.
Acknowledgements
Special thanks to Jamie Kincheloe, Dr. Mick Whitelaw, Alex McClain, Macon Magno, and Samuel Hauser for assistance in data collection and processing, as well as the ETSU Honors College and ETSU Department of Geosciences for their support.