Evaluating the real-world emissions of diesel passenger Car in Indian heterogeneous traffic

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作者
Chowdaiah Chandrashekar
Rohan Singh Rawat
Pritha Chatterjee
Digvijay Sampatrao Pawar
机构
[1] Indian Institute of Technology Hyderabad,Department of Civil Engineering
[2] Indian Institute of Technology Hyderabad,Department of Climate Change
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关键词
Tailpipe emissions; Aggressive driving modes; Normal driving modes; Passenger cars; Urban roads; Rural roads;
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摘要
A 30 portable emission measurement system (PEMS) test was conducted in this study to examine the effect of driving modes (aggressive and normal) and road type (urban and rural) on tailpipe emissions. Driving modes were assessed using relative positive acceleration and velocity × positive acceleration factors. The findings revealed that aggressive and normal driving modes differed significantly on urban and rural roads, as evident from paired sample t-test (p < 0.05). Furthermore, aggressive driving exhibited more prominent speed and acceleration on rural roads, while normal driving modes showed consistent acceleration or speed patterns regardless of road conditions as observed from kernel density estimation and box plot analysis. Emission rates (CO, CO2, HC, and NOx) significantly varied between aggressive and normal driving modes on urban and rural roads, as indicated by paired sample t-test analysis (p < 0.05). Aggressive driving increased CO2, CO, and HC emission rates for acceleration and deceleration modes by 18% to 40% compared to normal driving. Aggressive driving modes increased the emission factors (CO, HC, and CO2) by 5% to 25% compared to the normal driving mode on both urban and rural roads. Moreover, the NOx emission factors were also found significant during normal driving conditions on urban roads. This study provides real-world emission factors of diesel cars considering the impact of route, vehicle familiarity, and driving behavior induced by varying traffic conditions, which will contribute to improve the current emissions inventory on both a local and global level.
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