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Related Experiment Videos

Factors affecting alkalinity generation by successive alkalinity-producing systems: regression analysis.

C R Jage1, C E Zipper, R Noble

  • 1Regional Land Trust Representative, New Jersey Conservation Foundation, Far Hills 07931, USA.

Journal of Environmental Quality
|June 13, 2001
PubMed
Summary

Successive alkalinity-producing systems (SAPS) effectively treat acidic mine drainage (AMD). Key factors influencing performance include limestone contact time, iron concentration, and acidity, explaining 68% of variability.

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Area of Science:

  • Environmental Engineering
  • Water Treatment Technologies
  • Acidic Mine Drainage Remediation

Background:

  • Successive alkalinity-producing systems (SAPS) are increasingly used for acidic mine drainage (AMD) treatment.
  • Inconsistent performance has limited widespread adoption of SAPS technology.

Purpose of the Study:

  • To investigate the impact of system design and influent AMD chemistry on net alkalinity generation in SAPS.
  • To develop a predictive model for SAPS performance.

Main Methods:

  • Monthly data collection from eight SAPS cells in West Virginia and Virginia.
  • Statistical analysis to identify correlations between net alkalinity generation and system/influent parameters.
  • Model calibration and adjustment using an additional dataset from Pennsylvania.

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Main Results:

  • Net alkalinity generation showed strong positive correlations with the natural log of limestone residence time, influent dissolved iron (Fe) concentration, and influent non-manganese (Mn) acidity.
  • Limestone residence time had a logarithmic relationship, with most alkalinity generated early in contact.
  • Influent Fe and non-Mn acidity exhibited linear relationships with alkalinity generation.
  • The identified factors accounted for 68% of the variability in SAPS performance across combined datasets.

Conclusions:

  • System design (limestone residence time) and influent AMD chemistry (Fe and non-Mn acidity) are critical determinants of SAPS performance.
  • Optimizing these factors can improve the reliability and effectiveness of SAPS for AMD treatment.
  • The developed statistical model provides a valuable tool for predicting and enhancing SAPS efficiency.