The promulgation of the probabilistic and stringent 1-hour standards in 2010 has triggered the need for a reassessment in the model characterization of certain source types. Specifically, sources with periodic but random emissions (e.g., the maintenance and testing of emergency engines at data centers or natural gas transmission station compressor engines) pose unique challenges using standard and simplified assumptions in AERMOD. This webinar will explore the scientific and regulatory challenges of using Monte Carlo sampling techniques to better characterize the potential air quality impacts of intermittent sources. The use of Monte Carlo has extensive scientific precedent in related fields, but is relatively new when used to demonstrate compliance with air quality standards under the Clean Air Act. This Webinar will provide: an overview of Monte Carlo sampling; examples of its implementation; factors to consider during implementation and use; and case studies such as the Pipeline Researach Council International (PCRI) Balko natural gas compressor station study.