Literature DB >> 26053694

Complex contaminant mixtures in multistressor Appalachian riverscapes.

Eric R Merriam1, J Todd Petty1, Michael P Strager2, Aaron E Maxwell3, Paul F Ziemkiewicz4.   

Abstract

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.
© 2015 SETAC.

Entities:  

Keywords:  Cumulative effects; Mountaintop mining; Water chemistry types; Water quality

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Year:  2015        PMID: 26053694     DOI: 10.1002/etc.3101

Source DB:  PubMed          Journal:  Environ Toxicol Chem        ISSN: 0730-7268            Impact factor:   3.742


  2 in total

1.  Variation in stream network relationships and geospatial predictions of watershed conductivity.

Authors:  Michael G McManus; Ellen D'Amico; Elizabeth M Smith; Robyn Polinsky; Jerry Ackerman; Kip Tyler
Journal:  Freshw Sci       Date:  2020-12-01       Impact factor: 2.034

2.  Watershed Planning within a Quantitative Scenario Analysis Framework.

Authors:  Eric R Merriam; J Todd Petty; Michael P Strager
Journal:  J Vis Exp       Date:  2016-07-24       Impact factor: 1.355

  2 in total

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