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Title: Prediction of Coal ash leaching behavior in acid mine water, comparison of laboratory and field studies

Abstract

Strongly alkaline fluidized bed combustion ash is commonly used to control acid mine drainage in West Virginia coal mines. Objectives include acid neutralization and immobilization of the primary AMD pollutants: iron, aluminum and manganese. The process has been successful in controlling AMD though doubts remain regarding mobilization of other toxic elements present in the ash. In addition, AMD contains many toxic elements in low concentrations. And, each mine produces AMD of widely varying quality. So, predicting the effect of a particular ash on a given coal mine's drainage quality is of particular interest. In this chapter we compare the results of a site-specific ash leaching procedure with two large-scale field applications of FBC ash. The results suggested a high degree of predictability for roughly half of the 25 chemical parameters and poor predictability for the remainder. Of these, seven parameters were successfully predicted on both sites: acidity, Al, B, Ba, Fe, Ni and Zn while electrical conductivity, Ca, Cd, SO4, Pb and Sb were not successfully predicted on either site. Trends for the remaining elements: As, Ag, Be, Cu, Cr, Hg, Mg, Mn, pH, Se Tl and V were successfully predicted on one but not both mine sites.

Authors:
Publication Date:
Research Org.:
Savannah River Site (SRS), Aiken, SC (United States)
Sponsoring Org.:
US Department of Energy (US)
OSTI Identifier:
838804
Report Number(s):
WSRC-TR-2005-00018
TRN: US200508%%510
DOE Contract Number:  
AC09-96SR18500
Resource Type:
Technical Report
Resource Relation:
Other Information: PBD: 10 Jan 2005
Country of Publication:
United States
Language:
English
Subject:
01 COAL, LIGNITE, AND PEAT; 42 ENGINEERING; ACID MINE DRAINAGE; ALUMINIUM; COAL; COAL MINES; DRAINAGE; ELECTRIC CONDUCTIVITY; FLUIDIZED-BED COMBUSTION; FORECASTING; IRON; LEACHING; MANGANESE; PH VALUE; POLLUTANTS; WATER

Citation Formats

ANNA, KNOX. Prediction of Coal ash leaching behavior in acid mine water, comparison of laboratory and field studies. United States: N. p., 2005. Web. doi:10.2172/838804.
ANNA, KNOX. Prediction of Coal ash leaching behavior in acid mine water, comparison of laboratory and field studies. United States. https://doi.org/10.2172/838804
ANNA, KNOX. 2005. "Prediction of Coal ash leaching behavior in acid mine water, comparison of laboratory and field studies". United States. https://doi.org/10.2172/838804. https://www.osti.gov/servlets/purl/838804.
@article{osti_838804,
title = {Prediction of Coal ash leaching behavior in acid mine water, comparison of laboratory and field studies},
author = {ANNA, KNOX},
abstractNote = {Strongly alkaline fluidized bed combustion ash is commonly used to control acid mine drainage in West Virginia coal mines. Objectives include acid neutralization and immobilization of the primary AMD pollutants: iron, aluminum and manganese. The process has been successful in controlling AMD though doubts remain regarding mobilization of other toxic elements present in the ash. In addition, AMD contains many toxic elements in low concentrations. And, each mine produces AMD of widely varying quality. So, predicting the effect of a particular ash on a given coal mine's drainage quality is of particular interest. In this chapter we compare the results of a site-specific ash leaching procedure with two large-scale field applications of FBC ash. The results suggested a high degree of predictability for roughly half of the 25 chemical parameters and poor predictability for the remainder. Of these, seven parameters were successfully predicted on both sites: acidity, Al, B, Ba, Fe, Ni and Zn while electrical conductivity, Ca, Cd, SO4, Pb and Sb were not successfully predicted on either site. Trends for the remaining elements: As, Ag, Be, Cu, Cr, Hg, Mg, Mn, pH, Se Tl and V were successfully predicted on one but not both mine sites.},
doi = {10.2172/838804},
url = {https://www.osti.gov/biblio/838804}, journal = {},
number = ,
volume = ,
place = {United States},
year = {Mon Jan 10 00:00:00 EST 2005},
month = {Mon Jan 10 00:00:00 EST 2005}
}