Persistence factors for mobile source (roadway) carbon monoxide modeling

C. Cooper
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引用次数: 6

Abstract

A critical step in the modeling of the carbon monoxide (CO) impacts of mobile sources is predicting an 8-hour CO concentration given a modeled "worst-case" 1-hour concentration. Often, this is done by a multiplicative persistence factor. A meteorological persistence factor (MPF) accounts for the variability over 8 hours of wind speed, wind direction, stability class, and temperature. A vehicular persistence factor (VPF) reflects the lower traffic volumes during the off-peak hours. Hourly meteorological data for ten years for four cities in Florida were obtained from the National Climatic Data Center. The CALINE3 model was used to obtain hourly CO concentrations, which were combined to derive MPFs for each city. Similarly, VPFs were derived from hourly vehicle counts from one busy roadway in each city. The mean VPF multiplied by the second highest MPF was defined as the worst-case total persistence factor (TPF). These worst-case TPFs increased significantly as more hours of nighttime were included in the 8...
移动源(巷道)一氧化碳模型的持续因子
模拟移动源的一氧化碳(CO)影响的一个关键步骤是在模拟的“最坏情况”1小时浓度的情况下预测8小时的CO浓度。通常,这是通过增加持久性因子来实现的。气象持续度因子(MPF)是指风速、风向、稳定等级和温度在8小时内的变率。车辆滞留系数(VPF)反映非高峰时段交通量较低的情况。佛罗里达四个城市十年来的每小时气象数据来自国家气候数据中心。CALINE3模型用于获得每小时的CO浓度,并将其组合得出每个城市的mpf。同样,vpf是根据每个城市一条繁忙道路的每小时车辆数量得出的。平均VPF乘以第二高的强积金被定义为最坏情况总持续因子(TPF)。这些最坏情况下的TPFs显著增加,因为在8小时的睡眠中包含了更多的夜间时间。
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