A Guide to Surface Features Related to Underground Coal Mining

The purpose of this guide is to assist investigators conducting geologic hazard assessments with the understanding, detection, and characterization of surface features related to subsidence from underground coal mining. Subsidence related to underground coal mining can present serious problems to new and/or existing infrastructure, utilities, and facilities. For example, heavy equipment driving over the ground surface during construction processes may punch into voids created by sinkholes or cracks, resulting in injury to persons and property. Abandoned underground mines also may be full of water, and if punctured, can flood nearby areas. Furthermore, the integrity of rigid structures such as buildings, dams and bridges may be compromised if mining subsidence results in differential movement at the ground surface. Subsidence of the ground surface is a phenomenon associated with the removal of material at depth, and may occur coincident with mining, gradually over time, or sometimes suddenly, long after mining operations have ceased (Gray and Bruhn, 1984). The spatial limits of underground coal mines may extend for great distances beyond the surface operations of a mine, in some cases more than 10 miles for an individual mine. When conducting geologic hazard assessments, several remote investigation methods can be used to observe surface features related to underground mining subsidence. LiDAR-derived DEMs are generally the most useful method available for identifying these features because the bare earth surface can be viewed. However, due to limitations in the availability of LiDAR data, other methods often need to be considered when investigating surface features related to underground coal mining subsidence, such as Google Earth and aerial imagery. Mine maps, when available, can be viewed in tandem with these datasets, potentially improving the confidence of any possible mining subsidence-related features observed remotely. However, maps for both active and abandoned mines may be incomplete or unavailable. Therefore, it is important to be able to recognize possible surface features related to underground mining subsidence. This guide provides examples of surface subsidence features related to the two principal underground coal mining methods used in the United States: longwall mining and room and pillar mining. The depth and type of mining, geologic conditions, hydrologic conditions, and time are all factors that may influence the type of features that manifest at the surface. This guide provides investigators a basic understanding about the size, character and conditions of various surface features that occur as a result of underground mining subsidence.

An investigation of contaminant distribution in subsurface marine wood waste at Mill-A South Terminal, Port of Everett, Washington

This project investigates the correlation between contaminants and the wood waste present in marine sediments off the shore of the Port of Everett in the former Weyerhaeuser Mill-A pulp mill site. The investigation includes the results of two field studies, which tested contaminant levels in 22 boreholes as well as several surface samples. The contaminants include heavy metals and wood waste byproducts. These results, along with 14 other bore logs, provide the framework for a three-dimensional site model, interpolating the full extent of the depositional units and organic and inorganic chemicals found at Mill-A. The sediments of interest are divided into five depositional units defined by the percent wood content and type of wood: native material (<5% wood), intermediate (<30% wood), sawdust (<30% wood), woodchips (<30% wood), and poorly sorted sands with silt (SM-SP) (0% wood). The contaminants include arsenic, 2,4-dimethylphenol, and total organic carbon. Three-dimensional modeling software, RockWorks, interpolated the discrete borehole data of sediment and contaminants assuming horizontal continuity between sampling locations. The sediment distribution was calculated within concentration ranges for each contaminant of concern. The lowest detection limits, the screening levels, and the cleanup levels defined these ranges. Total organic carbon served as a proxy to estimate the quantity of wood waste in the sediment. As a known byproduct of wood decomposition, 2,4-dimethylphenol was expected to be more prevalent in the depositional units with more wood waste. Finally, arsenic was a proxy for other contaminants to determine if contaminants at Mill-A are dominant in sediments with high percentages of wood waste. The volumetric distribution established that high levels of total organic carbon are present in the sediment with higher percentages of wood waste. This correlation was stronger in the decomposing sawdust-rich sediment than the woodchip-rich sediment. The 2,4-dimethylphenol concentrations above cleanup standards were dominant in the sawdust-rich, intermediate and native sediments. Concentrations of 2,4-dimethylphenol below cleanup levels characterized the native sediment. The distribution of arsenic showed no statistically significant correlation to wood content in sediment. These results do not support the hypothesis of contaminant-rich wood waste, as many of the high concentrations of contaminants were not in the wood-rich sediments. This suggests that the contaminants are more distributed among all depositional units at Mill-A rather than focused within sediments with a high percent of wood waste. Understanding the distribution of potentially toxic compounds with wood waste is important for restoring the Puget Sound waterways to a more habitable environment. Future studies should include new data to validate these results and to limit the uncertainty of the extent of contaminants. Future studies may also find motive in looking for a correlation between contaminants and grain size based on previous studies linking these characteristics. These investigations will benefit the current cleanup effort as well as future cleanup efforts at similarly contaminated waterways.