Motor vehicles emit particles and other gaseous pollutants that adversely affect human health and the climate. This study investigates the impact of traffic characteristics on vehicular emissions under real-world inter-city highway driving conditions by examining vehicles that release disproportionately high level of air pollutants (super-emitters). Real-time pollutant concentrations from a heterogenous traffic fleet were measured at the entry and exit of Kamshet-I roadway tunnel, located on Mumbai-Pune Expressway. Vehicles with visible plume of smoke and overloaded vehicles (grouped as super-emitters) were visually identified. The average hourly traffic of 1560 (±410) vehicles at an average speed of 78 (±4) km.hr, composed of ∼80% light duty vehicles (LDVs) and ∼20% heavy duty vehicles (HDVs). Concentrations of all the measured gaseous and particulate pollutants at the exit were up to 2.5 times higher (p < 0.05) at the entry. Super-emitters accounted for one-fifth of the total fleet and were significantly associated with fine particles (R = 0.71). Developed statistical prediction model for super-emitters showed the influence of vehicle age for LDVs, and both vehicle age and overloading for HDVs. These findings can inform future vehicle regulation policies to systematically reduce emissions from super-emitters, by targeted vehicle inspection programs and retrofit initiatives toward reducing air pollution in Indian cities.

中文翻译：

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印度马哈拉施特拉邦城际驾驶条件下现实交通和超级排放源对车辆排放的影响

机动车辆排放颗粒物和其他气态污染物，对人类健康和气候产生不利影响。本研究通过检查释放过高水平空气污染物（超级排放者）的车辆，调查了现实城际高速公路驾驶条件下交通特征对车辆排放的影响。在位于孟买-浦那高速公路的 Kamshet-I 公路隧道的入口和出口处测量了来自异质交通车队的实时污染物浓度。通过目视识别出现明显烟雾的车辆和超载车辆（归类为超级排放者）。每小时平均交通量为 1560 (±410) 辆汽车，平均速度为 78 (±4) km.hr，其中约 80% 为轻型车辆 (LDV)，约 20% 为重型车辆 (HDV)。出口处测得的所有气态和颗粒污染物的浓度比入口处高出 2.5 倍 (p < 0.05)。超级排放者占总排放量的五分之一，并且与细颗粒物显着相关（R = 0.71）。开发的超级排放统计预测模型显示了车龄对 LDV 的影响，以及车龄和超载对 HDV 的影响。这些发现可以为未来的车辆监管政策提供信息，通过有针对性的车辆检查计划和改造举措，系统地减少超级排放者的排放，以减少印度城市的空气污染。