Mapping and Prediction of Coal Workers' Pneumoconiosis with Bioavailable Iron Content in the Bituminous Coals
Based on the first National Study of Coal Workers' Pneumoconiosis (CWP) and the U.S. Geological Survey database of coal quality, we show that the prevalence of CWP in seven coal mine regions correlates with levels of bioavailable iron (BAI) in the coals from that particular region (correlation...
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Published in: | Environmental health perspectives Vol. 113; no. 8; pp. 964 - 968 |
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Main Authors: | , , , , , |
Format: | Journal Article |
Language: | English |
Published: |
United States
National Institute of Environmental Health Sciences. National Institutes of Health. Department of Health, Education and Welfare
01-08-2005
National Institute of Environmental Health Sciences |
Subjects: | |
Online Access: | Get full text |
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Summary: | Based on the first National Study of Coal Workers' Pneumoconiosis (CWP) and the U.S. Geological Survey database of coal quality, we show that the prevalence of CWP in seven coal mine regions correlates with levels of bioavailable iron (BAI) in the coals from that particular region (correlation coefficient r = 0.94, p < 0.0015). CWP prevalence is also correlated with contents of pyritic sulfur (r = 0.91, p < 0.0048) or total iron (r = 0.85, p < 0.016) but not with coal rank (r = 0.59, p < 0.16) or silica (r = 0.28, p < 0.54). BAI was calculated using our model, taking into account chemical interactions of pyrite, sulfuric acid, calcite, and total iron. That is, iron present in coals can become bioavailable by pyrite oxidation, which produces ferrous sulfate and sulfuric acid. Calcite is the major component in coals that neutralizes the available acid and inhibits iron's bioavailability. Therefore, levels of BAI in the coals are determined by the available amounts of acid after neutralization of calcite and the amount of total iron in the coals. Using the linear fit of CWP prevalence and the calculated BAI in the seven coal mine regions, we have derived and mapped the pneumoconiotic potencies of 7,000 coal samples. Our studies indicate that levels of BAI in the coals may be used to predict coal's toxicity, even before large-scale mining. |
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Bibliography: | ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 23 ObjectType-Article-1 ObjectType-Feature-2 The authors declare they have no competing financial interests. |
ISSN: | 0091-6765 1552-9924 |
DOI: | 10.1289/ehp.7679 |