Department of Civil Engineering, the University of Toledo, 43606, Toledo, Ohio, USA.
Environ Monit Assess. 1994 Oct;33(1):19-32. doi: 10.1007/BF00546658.
The original Industrial Source Complex Model (ISCST, 90346) and its latest version, the ISCST2 (92090), are evaluated for the 1- and 24-hour averaging periods, using six statistical parameters. The confidence limits on two parameters were obtained using the bootstrap, jacknife, seductive, and robust resampling techniques. Evaluation is conducted in a multiple point source environment and in all the different stability categories, using a year of meteorological data, emission inventory of the Lucas County, in Toledo, Ohio, and monitoring data from two nearby stations for the year 1987. This was representative of a real time situation in which the ISCST is generally applied for regulatory work. The sensitivity analysis shows that the ISC is a poor performing model in the 1-h and 24-h averaging period, neutral and stable categories, and modifications to it are necessary in order to improve its performance. Its performance changes depending on the chosen paired values. A better relative performance is observed in the unstable category relative to the neutral and stable categories. Improved model performance may be achieved by applying modifications to the physics on which the model is based.
原始工业源综合模型（ISCST，90346）及其最新版本 ISCST2（92090），在 1 小时和 24 小时平均时段，使用六个统计参数进行评估。置信限的两个参数使用自举、刀叉、诱人的和稳健的重抽样技术获得。在多点源环境和所有不同的稳定类别中进行评估，使用俄亥俄州托莱多卢卡斯县的一年气象数据、排放清单和 1987 年两个附近站点的监测数据。这代表了一个实时情况，在这种情况下，通常将 ISCST 应用于监管工作。敏感性分析表明，ISC 在 1 小时和 24 小时平均时段、中性和稳定类别中表现不佳，需要对其进行修改，以提高其性能。它的性能取决于所选择的配对值。在不稳定类别中，相对于中性和稳定类别，相对性能更好。通过对模型所基于的物理原理进行修改，可以提高模型的性能。
