数据驱动的方法用于估计挖掘机多重污染物的排放因子,基于便携式排放测量系统和在线驾驶特征识别
Yongqi Wang1, Hao Cai1, Xiaowei Hu1
1School of Energy and Power Engineering, Shandong University, Jinan 250061, China.
The Science of the total environment
|December 24, 2023
概括
这项研究揭示了非公路移动机械 (NRMM) 挖掘机运行如何影响污染物排放. 计算排放因子的新数据驱动方法提供了比传统方法更准确的结果.
科学领域:
- 环境科学 环境科学
- 机械工程 机械工程
- 汽车工程 汽车工程
背景情况:
- 非公路移动机械 (NRMM) 对空气污染作出了重大贡献.
- 准确的排放因子对于有效的环境监管和排放清单开发至关重要.
- 传统的排放因子计算方法可能无法完全捕捉现实世界的操作复杂性.
研究的目的:
- 在现实条件下调查影响NRMM挖掘机污染物排放的因素.
- 开发和验证一个数据驱动的方法来计算准确的排放因子.
- 将拟议的数据驱动方法与传统方法进行比较.
主要方法:
- 分析了108台NRMM挖掘机的368,000小时运行数据,使用自主开发的测试系统.
- 使用便携式排放测试系统 (PEMS) 来研究10台EC210挖掘机的瞬间排放.
- 开发基于实际驾驶数据的基于数据的排放因子计算方法.
主要成果:
- 挖掘机运行模式:21%的空,66%的工作,13%的移动.
- 由于驾驶风格和模式,瞬间排放率的显著变化.
- 数据驱动的排放因子 (EFfs和EFps) 与传统方法有显著差异,一些指标明显高或低.
结论:
- 驾驶风格和模式通过液压功率和发动机负载等因素对NRMM污染物排放产生重大影响.
- 数据驱动方法为排放因子计算提供了更科学支持的方法.
- 建议强调采用数据驱动方法来准确开发排放清单.
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