使用Plume Chasing识别高排放重型车辆:欧洲执法案例研究
Christina Schmidt1, Denis Pöhler1, Markus Knoll2
1Institute of Environmental Physics, Heidelberg University, INF 229, Heidelberg, 69120, Germany; Airyx GmbH, Hans-Bunte-Str. 4, Heidelberg, 69123, Germany.
The Science of the total environment
|July 16, 2025
概括
现实世界重型车辆 (HDV) 的排放量因国家和执法而异. 一小部分高排放汽车不成比例地增加了总体的氧化 (NOx),黑碳 (BC) 和颗粒数 (PN) 污染.
科学领域:
- 环境科学 环境科学
- 汽车工程 汽车工程
- 空气质量监测 空气质量监测
背景情况:
- 重型车辆 (HDV) 的实际排放往往超过了规定的限值.
- 有效的监测方法对于识别高排放者和确保遵守欧元排放标准至关重要.
研究的目的:
- 通过使用羽毛追逐方法,为欧洲近5000辆重型车提供现实世界的排放数据.
- 评估实时软件在识别可疑和高排放者的有效性.
- 分析高排放者对整体车队排放的影响以及国家执法的有效性.
主要方法:
- 采用羽毛追逐方法来测量各种欧洲国家的重型车的真实世界排放 (NOx,PN,BC) (2016-2023).
- 使用实时处理软件,根据欧元标准将车辆分类为可疑或高排放的车辆.
- 与国家执法水平和检查结果相关联的排放数据.
主要成果:
- 平均排放量因国家,执法严格性和测量年而异.
- 在2023年,斯洛伐克和捷克显示出高比例 (34%,41%) 的疑似/高排放者,而德国有8%.
- 高排放者负责平均NOx排放量增加一倍以上,并显著增加颗粒物 (PM) 排放量; 4-14%的最脏车辆占BC和PN排放量的50%.
结论:
- 羽毛追逐方法对于预先识别重型车的排放系统故障是有效的.
- 国家法规和执法对高排放汽车的流行有很大影响.
- 针对一小部分高排放者的目标对于大幅减少HV空气污染至关重要.
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