Uncertainty and sensitivity analysis of revised leachate pollution index

Area of Science:

• Environmental Science
• Environmental Monitoring
• Composite Indicators

Background:

• Composite indicators (CIs) are increasingly used for environmental system assessment.
• The revised leachate pollution index (r-LPI) quantifies landfill leachate pollution potential (5-100).
• Methodological choices in CI development can impact result reliability.

Purpose of the Study:

• To investigate techniques for developing the r-LPI.
• To examine decisions in parameter selection, normalization, weighting, and aggregation.
• To quantify uncertainty in r-LPI development stages.

Main Methods:

• Utilized Monte Carlo-based uncertainty analysis.
• Employed sensitivity analysis to determine input parameter impact.
• Investigated decisions in parameter selection, normalization, weighting, and aggregation.

Main Results:

• Quantified uncertainty in various stages of r-LPI development.
• Identified dependable model sections through uncertainty analysis.
• Determined the impact of input parameters on r-LPI values via sensitivity analysis.

Conclusions:

• The combined use of sensitivity and uncertainty analysis enhances r-LPI transparency.
• These analyses affirm the credibility and accuracy of the r-LPI.
• This approach strengthens the reliability of environmental monitoring indices.