School of Automobile, Chang'an University, Shangyuan Road, Xi'an, 710016, Shaanxi, PR China.
Chemosphere. 2024 Oct;365:143348. doi: 10.1016/j.chemosphere.2024.143348. Epub 2024 Sep 14.
Urban Black Carbon (BC) emissions from light-duty gasoline vehicles (LDGVs) are challenging to quantify in real-world settings. This study employed a Portable Emission Measurement System (PEMS) to assess BC emissions from five LDGVs on urban roads. We also developed five machine learning (ML) models based on On-Board Diagnostics (OBD) data to predict BC emissions. Among these, the Random Forest (RF) model consistently demonstrates the best ability to predict BC emissions across all tested LDGVs, with R values exceeding 0.6. Integrating OBD-based ML models within vehicles could enable real-time BC monitoring and aid emission reduction strategies. We observed a strong correlation between BC emissions and engine parameters, such as engine speed and load (R values between 0.5 and 0.9). Furthermore, China VI standard-compliant LDGVs showed minor differences in BC emissions across urban road types. Vehicles equipped with gasoline direct injection (GDI) engines registered BC emission factors (EFs) of 0.141 ± 0.038 mg/km, an increase of 23.7% compared to their port fuel injection (PFI) counterparts, which averaged 0.114 ± 0.049 mg/km.
城市道路轻型汽油车（LDGV）的黑碳（BC）排放难以在实际环境中进行量化。本研究采用便携式排放测量系统（PEMS）评估了城市道路上五辆 LDGV 的 BC 排放。我们还开发了五个基于车载诊断（OBD）数据的机器学习（ML）模型来预测 BC 排放。在这些模型中，随机森林（RF）模型在所有测试的 LDGV 中始终表现出最佳的 BC 排放预测能力，R 值均超过 0.6。在车辆中集成基于 OBD 的 ML 模型可以实现实时的 BC 监测并有助于减排策略的制定。我们观察到 BC 排放与发动机参数之间存在很强的相关性，例如发动机转速和负荷（R 值在 0.5 到 0.9 之间）。此外，符合中国 VI 标准的 LDGV 在不同类型的城市道路上的 BC 排放差异较小。配备汽油直喷（GDI）发动机的车辆的 BC 排放因子（EF）为 0.141±0.038mg/km，比其燃油喷射（PFI）发动机的平均 EF（0.114±0.049mg/km）高 23.7%。
