Abating Carbon Dioxide Emissions from Electric Power Generation: Model Uncertainty and Regulatory Epistemology
本文以美国环保署用数值模型制定电厂二氧化碳减排法规为例，探讨能源环境监管中模型验证、不确定性分析及其对决策的意义。
Computational modeling of natural, economic, and technological systems is a primary analytical methodology in US energy and environmental regulation. Validating or otherwise evaluating such models and analyzing the uncertainties involved in their regulatory applications have become both more important and more challenging. This paper reviews these issues in the context of an important recent example involving energy, the US Environmental Protection Agency’s (EPA’s) development of regulations to reduce carbon dioxide emissions from electric power plants using a numerical model of the US electric power system. Following a summary of background information about greenhouse gas abatement policy, the paper discusses the agency’s general computational model evaluation philosophy; the history of, and current practices in, energy model evaluation; the specific model used by the EPA and its application to carbon dioxide regulation; and the concept of fundamental model uncertainty and its significance for this modeling domain.