Roth Philip M, Reynolds Steven D, Tesche Thomas W
Envair, San Anselmo, CA. USA.
J Air Waste Manag Assoc. 2005 Oct;55(10):1558-73. doi: 10.1080/10473289.2005.10464751.
Despite the widespread application of photochemical air quality models (AQMs) in U.S. state implementation planning (SIP) for attainment of the ambient ozone standard, documentation for the reliability of projections has remained highly subjective. An "idealized" evaluation framework is proposed that provides a means for assessing reliability. Applied to 18 cases of regulatory modeling in the early 1990s in North America, a comparative review of these applications is reported. The intercomparisons suggest that more than two thirds of these AQM applications suffered from having inadequate air quality and meteorological databases. Emissions representations often were unreliable; uncertainties were too high. More than two thirds of the performance evaluation efforts were judged to be substandard compared with idealized goals. Meteorological conditions chosen according regulatory guidelines were limited to one or two cases and tended to be similar, thus limiting the extent to which public policy makers could be confident that the emission controls adopted would yield attainment for a broad range of adverse atmospheric conditions. More than half of the studies reviewed did not give sufficient attention to addressing the potential for compensating errors. Corroborative analyses were conducted in only one of the 18 studies reviewed. Insufficient attention was given to the estimation of model and/or input database errors, uncertainties, or variability in all of the cases examined. However, recent SIP and policy-related regional modeling provides evidence of substantial improvements in the underlying science and available modeling systems used for regulatory decision making. Nevertheless, the availability of suitable databases to support increasingly sophisticated modeling continues to be a concern for many locations. Thus, AQM results may still be subject to significant uncertainties. The evaluative process used here provides a framework for modelers and public policy makers to assess the adequacy of contemporary and future modeling work.
尽管光化学空气质量模型（AQM）在美国各州实施规划（SIP）中广泛应用以实现环境臭氧标准，但有关预测可靠性的文档仍高度主观。本文提出了一个“理想化”的评估框架，为评估可靠性提供了一种方法。本文报告了对20世纪90年代初北美18个监管建模案例应用该框架的比较性综述。相互比较表明，这些AQM应用中超过三分之二存在空气质量和气象数据库不足的问题。排放表征往往不可靠，不确定性过高。与理想化目标相比，超过三分之二的性能评估工作被判定为不合格。根据监管指南选择的气象条件仅限于一两个案例且往往相似，因此限制了公共政策制定者确信所采用的排放控制措施能在广泛的不利大气条件下实现达标目标的程度。超过一半的综述研究没有充分关注解决误差补偿的可能性。在所综述的18项研究中只有一项进行了确证分析。在所审查的所有案例中，对模型和/或输入数据库误差、不确定性或变异性的估计都未给予足够关注。然而，近期的SIP和与政策相关的区域建模表明，用于监管决策的基础科学和现有建模系统有了显著改进。尽管如此，许多地区获取合适数据库以支持日益复杂建模的问题仍然令人担忧。因此，AQM结果可能仍存在重大不确定性。本文所采用的评估过程为建模人员和公共政策制定者评估当代及未来建模工作的充分性提供了一个框架。
