机动车比功率在高排污车辆鉴别中的应用

机动车尾气遥感监测是I/M制度的有益补充.以2004年广州市机动车尾气遥感监测实验为基础,对实验数据作了深入分析.结果表明,占全体车辆10%的高排污车辆所排放的一氧化碳(CO)、碳氢化合物(HC)和氮氧化合物(NOx)分别占当日该污染物总量的36.81%,41.80%和48.52%,证明了高排污车辆是造成机动车排放污染的最主要污染源.进一步引入机动车比功率概念研究了机动车比功率与污染物排放之间的关系,并对15次实验结果进行了对比研究.结果表明,在不同测量中,CO、HC和NOx的排放与机动车比功率区间分布具有较好的一致性.分布规律还表明,在遥感监测中,在机动车比功率区间高值部分,机动车的CO或者HC的高排放为瞬间高排放,此时,不能将其判别为高排污车辆.将此结论用于基于神经网络的高排污车辆鉴别模型中,使高排污车辆的正确判断率达到95%.

Improvement of the identification model for vehicles with high emissions by employing vehicle specific power

As a useful supplement to the inspection and maintenance (I/M) system, remote sensing is mainly for the detection of vehicles with high emissions. From experimental data in Guangzhou in 2004, we found that vehicles with high emissions, which account for 10% of the total vehicles in the city, contribute over 36.81% of the carbon monoxide (CO), 41.80% of the hydrocarbons (HC), and 48.52% of the nitrogen oxides (NOx) in the total daily emissions. This indicates that vehicles with high emissions constitute the main vehicular pollution sources. The concept of vehicle specific power is introduced and its relation with pollution emissions is analyzed. Through a comparison of 15 different measurements, vehicle emissions show great uniformity in various measurements when vehicle specific power is used as the basic metric. The distribution also indicates that the high emissions of CO or HC occur momentarily in vehicles with a high level of specific power. Thus, those vehicles should not be considered vehicles with high emissions. By applying these conclusions to improve our previously developed artificial neural network model for identifying vehicles with high emissions, the percentage of hits reached 95%.