Ao Li
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Ao Li has a total of 3 co-authors. Here are the top co-authors by number of shared publications:
- Fei Ma
Huadian Coal Industry Group Digital Intelligence Technology Co., Ltd., Beijing 102400, China
1 shared publication - Xingyu Sun
Inner Mongolia Mengtai Buliangou Coal Industry Co., Ltd., Ordos 017000, China
1 shared publication - Zhen Wang
College of Environmental Science and Engineering, Beijing Forestry University, Beijing 100083, China
1 shared publication
Latest Publications
- Open Access
Accounting Factors and Spatio-Temporal Differences of the Carbon Footprint Factor in China’s Power System
The carbon footprint factor of a power system is a crucial basis for calculating carbon emissions from electricity consumption. However, the current carbon footprint factor of China’s power system faces several issues, such as a limited spatial range, outdated updates, an incomplete accounting scope, and unclear accounting methods. To make the power system’s carbon footprint accounting method and its temporal and spatial scope more comprehensive, this study reconstructs the accounting method based on the emission factor method, adding factors such as transmission losses, power transmission across spatial ranges, and Sulfur hexafluoride (SF6) gas leakage. This study’s analysis reveals that these three accounting factors have a significant impact on the power system’s carbon footprint factor. In terms of the time dimension, the carbon footprint factor has decreased by more than 20% over the past 18 years, and when the time interval is refined to a monthly scale, the carbon footprint factor exhibits significant seasonal fluctuations. In the spatial dimension, the coefficient of variation (CV) for regional and provincial power system carbon footprint factors reached 27.38% and 29.98%, respectively, in 2022. For the same geographic location, the difference in carbon footprint factors between provincial and regional levels ranged from −73.98% to 119.95%. This study shows that the current carbon footprint factor of the power system has limitations, and there is an urgent need to improve the accounting factors, establish multi-level spatial division standards for provincial and regional scales, and shorten the update intervals while ensuring data timeliness. This will enhance the temporal and spatial accuracy of the carbon footprint factor, providing scientific support for precise carbon emission management.
Open AccessAccounting Factors and Spatio-Temporal Differences of the Carbon Footprint Factor in China’s Power System
The carbon footprint factor of a power system is a crucial basis for calculating carbon emissions from electricity consumption. However, the current carbon footprint factor of China’s power system faces several issues, such as a limited spatial range, outdated updates, an incomplete accounting scope, and unclear accounting methods. To make the power system’s carbon footprint accounting method and its temporal and spatial scope more comprehensive, this study reconstructs the accounting method based on the emission factor method, adding factors such as transmission losses, power transmission across spatial ranges, and Sulfur hexafluoride (SF6) gas leakage. This study’s analysis reveals that these three accounting factors have a significant impact on the power system’s carbon footprint factor. In terms of the time dimension, the carbon footprint factor has decreased by more than 20% over the past 18 years, and when the time interval is refined to a monthly scale, the carbon footprint factor exhibits significant seasonal fluctuations. In the spatial dimension, the coefficient of variation (CV) for regional and provincial power system carbon footprint factors reached 27.38% and 29.98%, respectively, in 2022. For the same geographic location, the difference in carbon footprint factors between provincial and regional levels ranged from −73.98% to 119.95%. This study shows that the current carbon footprint factor of the power system has limitations, and there is an urgent need to improve the accounting factors, establish multi-level spatial division standards for provincial and regional scales, and shorten the update intervals while ensuring data timeliness. This will enhance the temporal and spatial accuracy of the carbon footprint factor, providing scientific support for precise carbon emission management.