Building consensus in environmental impact assessment through multicriteria modeling and sensitivity analysis

Area of Science:

• Environmental Science
• Decision Science
• Operations Research

Background:

• Multicriteria decision analysis (MCDA) is increasingly utilized in environmental impact assessment (EIA).
• Selecting sites for major infrastructure projects, like new airports, often involves complex environmental considerations and stakeholder disagreements.

Purpose of the Study:

• To apply and combine two MCDA techniques: stochastic analytic hierarchy process and compromise programming.
• To rank two alternative sites for Mexico City's new airport based on environmental impacts.
• To assess the role of sensitivity analysis in MCDA for controversial projects.

Main Methods:

• Combined stochastic analytic hierarchy process and compromise programming for MCDA.
• Conducted extensive sensitivity analyses to evaluate rank ordering under uncertainty.
• Investigated uncertainty in hierarchy structure, criteria weights, and performance values.

Main Results:

• The study successfully ranked two alternative airport sites using the combined MCDA approach.
• Sensitivity analysis revealed its fundamental role in achieving consensus among interdisciplinary teams.
• Demonstrated the impact of uncertainty in decision criteria on the final site rankings.

Conclusions:

• Sensitivity analysis is critical for transparent and technically defensible MCDA implementation in environmental impact assessment.
• The findings support the use of MCDA with sensitivity analysis for resolving debates in controversial infrastructure projects.
• Effective use of sensitivity analysis can lead to greater agreement in complex decision-making processes.