Using a probabilistic approach in an ecological risk assessment simulation tool: test case for depleted uranium (DU)

Area of Science:

• Environmental toxicology
• Probabilistic ecological risk assessment
• Environmental science

Background:

• Ecological risk assessment (ERA) traditionally faces challenges in quantifying uncertainty.
• Probabilistic methods offer a robust framework for addressing variability in ecological risk.
• Depleted uranium (DU) contamination poses potential ecological threats at military testing sites.

Purpose of the Study:

• To develop and apply a probabilistic ecological risk assessment model.
• To characterize ecological risks associated with depleted uranium exposure.
• To evaluate the efficacy of Monte Carlo simulations in ecological risk assessment.

Main Methods:

• Utilized Monte Carlo simulations to generate probabilistic distributions for risk parameters.
• Developed a simulation tool (ERA) with a graphical user interface and database management system.
• Assessed exposure pathways and food web dynamics at trophic levels.
• Applied the model to assess DU risks at US Army Yuma Proving Ground (YPG) and Aberdeen Proving Ground (APG).

Main Results:

• At YPG, DU exposure is likely to reduce plant root weight (98% probability) and cause adverse reproductive effects in terrestrial animals (0.1%–44%).
• The lesser long-nosed bat faces a >99% likelihood of adverse effects, including reduced offspring size and weight.
• At APG, DU uptake is unlikely to affect aquatic plant and animal survival (<0.1% probability).
• Observed body burdens in various species at YPG and APG align with simulated distributions.

Conclusions:

• Probabilistic ERA effectively characterizes ecological risks and quantifies uncertainty associated with contaminants like DU.
• The developed simulation tool provides a valuable framework for assessing complex ecological systems.
• Specific ecological receptors, such as the lesser long-nosed bat, may be highly vulnerable to DU contamination.