Hierarchical partial order ranking.

Area of Science:

• Environmental Science and Risk Assessment
• Chemical Safety and Toxicology
• Socio-Environmental Studies

Background:

• Assessing chemical production/use impacts on health and environment requires multi-criteria evaluation.
• Numerous parameters (production, release, site factors, substance properties, socio-economics) complicate model development.
• Existing methods struggle with the high number of variables in risk assessment.

Purpose of the Study:

• To introduce a novel method, hierarchical partial order ranking (HPOR), for simplifying complex environmental and human health impact assessments.
• To address the challenge of integrating a large number of parameters in risk prioritization models.
• To provide a framework for ranking polluted sites and chemical risks more effectively.

Main Methods:

• Hierarchical Partial Order Ranking (HPOR) groups initial parameters by interconnections.
• Meta-descriptors are derived from these groups to represent intermediate rankings.
• A second ranking is performed on meta-descriptors, with final results based on average ranks.

Main Results:

• HPOR successfully reduces the complexity of multi-criteria evaluation schemes.
• The method allows for a sensible model development despite a large number of input parameters.
• An illustrative example demonstrates the effective prioritization of polluted sites using HPOR.

Conclusions:

• Hierarchical Partial Order Ranking (HPOR) offers a robust solution for environmental and health risk assessment.
• The methodology simplifies the integration of diverse parameters, enabling more effective prioritization.
• HPOR provides a valuable tool for environmental management and public health protection strategies.