Complex contaminant mixtures in multistressor Appalachian riverscapes.

Runoff from watersheds altered by mountaintop mining in the Appalachian region (USA) is known to pollute headwater streams, yet regional-scale assessments of water quality have focused on salinization and selenium. The authors conducted a comprehensive survey of inorganic contaminants found in 170 stream segments distributed across a spectrum of historic and contemporary human land use. Principal component analysis identified 3 important dimensions of variation in water chemistry that were significantly correlated with contemporary surface mining (principal component 1: elevated dominant ions, sulfate, alkalinity, and selenium), coal geology and legacy mines (principal component 2: elevated trace metals), and residential development (principal component 3: elevated sodium and chloride). The combination of these 3 dominant sources of pollutants produced a complex stream-to-stream patchwork of contaminant mixtures. Seventy-five percent of headwater streams (catchments < 5 km(2) ) had water chemistries that could be classified as either reference (49%), development only (18%), or mining only (8%). Only 21% of larger streams (catchments > 5 km(2) ) were classified as having reference chemistries, and chemistries indicative of combined mining and development contaminants accounted for 47% of larger streams (compared with 26% of headwater streams). Extreme degradation of larger streams can be attributed to accumulation of contaminants from multiple human land use activities that include contemporary mountaintop mining, underground mining, abandoned mines, and untreated domestic wastewater. Consequently, water quality improvements in this region will require a multicontaminant remediation approach.

Combining a Spatial Model and Demand Forecasts to Map Future Surface Coal Mining in Appalachia.

Predicting the locations of future surface coal mining in Appalachia is challenging for a number of reasons. Economic and regulatory factors impact the coal mining industry and forecasts of future coal production do not specifically predict changes in location of future coal production. With the potential environmental impacts from surface coal mining, prediction of the location of future activity would be valuable to decision makers. The goal of this study was to provide a method for predicting future surface coal mining extents under changing economic and regulatory forecasts through the year 2035. This was accomplished by integrating a spatial model with production demand forecasts to predict (1 km2) gridded cell size land cover change. Combining these two inputs was possible with a ratio which linked coal extraction quantities to a unit area extent. The result was a spatial distribution of probabilities allocated over forecasted demand for the Appalachian region including northern, central, southern, and eastern Illinois coal regions. The results can be used to better plan for land use alterations and potential cumulative impacts.