Bayesian Statistics in Environmental Engineering Planning

Abstract

Bayesian inference can provide a rigorous assessment of risk based on the information available. Today's environmental engineer faces many uncertainties in designing systems to address environmental concerns. Uncertainties arising from a lack of information may range from population forecasts to the projected benefits of technologies designed to reduce global warming impacts to remedial levels for hazardous waste posing the least amount of risk. Variabilities include such parameters as wastewater flows and concentrations. Quantitative assessments of uncertainty and variability using such methods as Bayesian statistics are more convincing that those using rules of thumb and other, less-formal arguments.