Monitoring the enterprise carbon emissions using electricity big data: A case study of Beijing

H Chen, R Wang, X Liu, Y Du, Y Yang - Journal of Cleaner Production, 2023 - Elsevier
Enterprises are major sources of anthropogenic carbon emissions, and high-quality data on
enterprise carbon emissions are prerequisites for climate abatement policies and actions …

Prediction of cold start emissions for hybrid electric vehicles based on genetic algorithms and neural networks

D Tang, Z Zhang, L Hua, J Pan, Y Xiao - Journal of Cleaner Production, 2023 - Elsevier
The emission of hybrid electric vehicles deteriorates during cold start, and it is a cost-
effective method to reduce pollutant emissions during cold start of hybrid electric vehicles …

Monitoring high-carbon industry enterprise emission in carbon market: a multi-trusted approach using externally available big data

B Gao, X Kong, G Liu, T Xiang, Y Gao, S Luo… - Journal of Cleaner …, 2024 - Elsevier
Carbon markets are widely recognized as effective strategies for regulating carbon
emissions from the enterprises of the high-carbon industry. Accurate monitoring of emissions …

Integrated MOVES model and machine learning method for prediction of CO2 and NO from light-duty gasoline vehicle

R Liu, Z Zhang, C Wu, J Yang, X Zhu, Z Peng - Journal of Cleaner …, 2023 - Elsevier
With rapid urbanization and industrialization, the number of light-duty gasoline vehicles
(LDGVs) in China has continued to grow rapidly, leading to a significant increase in traffic …

Real-world emissions and fuel consumption of gasoline and hybrid light duty vehicles under local and regulatory drive cycles

R Tu, J Xu, A Wang, M Zhang, Z Zhai… - Science of The Total …, 2022 - Elsevier
In this study, driving trajectory data from private vehicles were collected in Toronto, Canada
to construct representative local drive cycles. In addition, real-driving emission testing for …

[HTML][HTML] Embodied carbon determination in the transportation stage of prefabricated constructions: A micro-level model using the bin-packing algorithm and modal …

Y Xiang, K Ma, AM Mahamadu, L Florez-Perez… - Energy and …, 2023 - Elsevier
The prefabricated construction generates considerable embodied carbon emissions during
the manufacture, transportation, and construction stages. However, the contribution from the …

Which factor contributes more to the fuel consumption gap between in-laboratory vs. real-world driving conditions? An independent component analysis

P Fan, H Yin, H Lu, Y Wu, Z Zhai, L Yu, G Song - Energy Policy, 2023 - Elsevier
A widening vehicle fuel consumption gap has been found between in-laboratory and real-
world driving conditions, which can undermine policy-making concerning energy saving and …

Modeling energy consumption for battery electric vehicles based on in-use vehicle trajectories

Z Zhai, L Zhang, G Song, X Li, L Yu - Transportation Research Part D …, 2024 - Elsevier
The development of battery electric vehicles (BEVs) raises a demand to develop a tool to
estimate and predict their energy consumption accurately and efficiently. This study …

Fuel consumption estimation in heavy-duty trucks: Integrating vehicle weight into deep-learning frameworks

P Fan, G Song, Z Zhai, Y Wu, L Yu - Transportation Research Part D …, 2024 - Elsevier
Insufficient consideration of vehicle weight dynamics during real-world driving could lead to
inaccurate fuel consumption estimates. This study examined the impact of vehicle weight on …

A novel method for real driving emission prediction utilizing an artificial neural network

A Baghani, I Chitsaz, MM Teymoori - Engineering Applications of Artificial …, 2024 - Elsevier
The present study introduces a novel method based on the experimental emission data of
standard Real driving emission measurement is a challenging issue for future emission …