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A Multi-layer Computational Framework for Environmental and Resilient Chemical Process Design
Citation:
Li, S., S. Agbleze, G. Ruiz-Mercado, AND F. Lima. A Multi-layer Computational Framework for Environmental and Resilient Chemical Process Design. AIChE Enterprise & Infrastructure Resilience Conference, Cincinnati, OH, August 12 - 13, 2019.
Impact/Purpose:
Computational tools for evaluating chemical process emissions, pollution treatment simulation, and environmental impact performance are yet to be developed. This presentation describes current developments on estimating releases of chemicals and their environmental impact evaluation when including the modeling and simulation of pollution control systems. Chemical releases may present unanticipated health risks that EPA and its Office of Pollution Prevention and Toxics must evaluate, as described in the Toxic Substances Control Act. The overall evaluation may involve risk assessment, including evaluations of chemical releases, exposures, and hazards. This work is to support risk evaluation utilizing rapid estimation of industrial chemical releases and management scenarios.
Description:
Advances in research and engineering practices have resulted in the improved efficiency of industrial processes. Although these advances have led to enhancements in resource and energy utilization, these have been linked to extreme climate change and other natural events affecting such industrial processes. These facts raise the need for characterizing the ability of both natural and artificial systems (e.g., ecosystems and process systems) to recover from both unforeseen and forecasted events. This characterization would help to keep continuous process operation despite the presence of disruptions. In addition to the potential to recover, the rate at which these systems transition back to the nominal condition, and the possibility for disruptions to propagate through interconnected industrial systems are critical information for decision making and avoid extended and irreversible consequences. In this work, a framework is proposed that relies on GREENSCOPE indicators to quantify chemical process environmental impact and industrial resilience. GREENSCOPE has many indicators that can be linked to industrial resilience so that both natural and artificial systems can be analyzed in terms of the accumulation of these indicators in the boundaries of interest and the cost of retrofitting a system to be resilient against an event. The effectiveness of the proposed framework is illustrated with an acetic acid manufacturing example by quantifying selected resilience-related indicators in specific GREENSCOPE categories. This set of indicators will then be used to assist in process decision making and compare process performance considering different scenarios for improving system resilience when subject to disturbances.