Investigating the impact of high-altitude on vehicle carbon emissions: A comprehensive on-road driving study

被引:11
|
作者
Jiang, Zhiwen [1 ]
Wu, Lin [1 ]
Niu, Haomiao [1 ]
Jia, Zhenyu [1 ]
Qi, Zhaoyu [2 ]
Liu, Yan [1 ]
Zhang, Qijun [1 ]
Wang, Ting [1 ]
Peng, Jianfei [1 ]
Mao, Hongjun [1 ]
机构
[1] Nankai Univ, Coll Environm Sci & Engn, Tianjin Key Lab Urban Transport Emiss Res, Tianjin 300071, Peoples R China
[2] Minist Transport, Tianjin Res Inst Water Transport Engn, Key Lab Environm Protect Water Transport Engn Mini, 2618 Xingang Erhao Rd, Tianjin 300456, Peoples R China
关键词
High altitude; Vehicle carbon emission; PEMS; Machine learning; DUTY DIESEL VEHICLE; FUEL CONSUMPTION;
D O I
10.1016/j.scitotenv.2024.170671
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
This study addresses the literature gap concerning accurately identifying vehicle carbon emission characteristics in high -altitude areas. Utilizing a portable emission measurement system (PEMS) for real -world testing, we quantified the influence of altitude on carbon emissions from light -duty gasoline (LDGV) and diesel vehicles (LDDV). The Random Forest (RF) algorithm was employed to analyze the complex nonlinear relationships between altitude, meteorological conditions, driving patterns, and carbon dioxide (CO2) emissions, enabling predictions across different altitudes. The results showed that CO2 emissions progressively increase with elevation. Furthermore, as altitude increases, combustion efficiency declines, and the overall impact of driving conditions on emission rates diminishes. Altitude and meteorological factors significantly contributed to CO2 emissions, whereas driving conditions and road grades contributed less. Compared with the COPERT model, the RF model demonstrates strong accuracy in predicting carbon emissions at different altitudes. Specifically, the CO2 emission rate nearly triples as altitude increases from 2.0 km to 4.5 km. This research bridges a critical gap in the understanding carbon emissions from high -altitude vehicles, offering insights into policy development for emission reduction strategies in such regions. Future studies should integrate diverse testing methodologies and comprehensive surveys to validate and extend the findings.
引用
收藏
页数:12
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