The use of Monte Carlo simulation to quantify the uncertainty in modeled estimates of toxic, radiation and overpressure impacts resulting from accidents in large chemical plants

Abstract

Current Risk Assessment procedures for the estimation of the acute health impacts resulting from the accidental release of toxic chemicals into the atmosphere involve the definition or construction of a representative accidental release scenario and the use of one or other air quality or dispersion model to estimate ambient air concentrations and exposure durations in the vicinity of the source. Legislation such as the South African Occupational Health and Safety Act, 1993, Major Hazard Installation Regulations, United States Risk Management Plan Rule and the European Union Seveso n, to prevent and or minimize impacts of such events require owners of installations to perform a Risk Assessment if they handle hazardous substances above specified threshold quantities. Mathematical modeling has been widely used to assist with the Exposure Assessment to perform off-site worst-case release analysis. Governmental departments, agencies and local authorities increasingly (but not exclusively) rely on air pollution models for making decisions related to air quality, traffic management, urban planning, and public health. As a result, the model users' community is becoming larger and more diverse. Most of the air quality modeling work has so far been based on the "deterministic" approach of using only set input parameters and specific applications. The selected model provides estimates of averaged concentrations using specific meteorological and emission data sets.