School for Environment and Sustainability, University of Michigan , Ann Arbor, Michigan 48109-1041, United States.
State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Beijing Normal University , Beijing, 100875, People's Republic of China.
Environ Sci Technol. 2017 Sep 19;51(18):10893-10902. doi: 10.1021/acs.est.7b01814. Epub 2017 Aug 25.
Existing studies on the evaluation of CO emissions due to electricity consumption in China are inaccurate and incomplete. This study uses a network approach to calculate CO emissions of purchased electricity in Chinese provinces. The CO emission factors of purchased electricity range from 265 g/kWh in Sichuan to 947 g/kWh in Inner Mongolia. We find that emission factors of purchased electricity in many provinces are quite different from the emission factors of electricity generation. This indicates the importance of the network approach in accurately reflecting embodied emissions. We also observe substantial variations of emissions factors of purchased electricity within subnational grids: the provincial emission factors deviate from the corresponding subnational-grid averages from -58% to 44%. This implies that using subnational-grid averages as required by Chinese government agencies can be quite inaccurate for reporting indirect CO emissions of enterprises' purchased electricity. The network approach can improve the accuracy of the quantification of embodied emissions in purchased electricity and emission flows embodied in electricity transmission.
现有关于中国电力消费二氧化碳排放评估的研究不够准确和完整。本研究采用网络方法计算中国各省购买电力的二氧化碳排放量。购买电力的二氧化碳排放系数范围从四川的 265 克/千瓦时到内蒙古的 947 克/千瓦时。我们发现,许多省份购买电力的排放系数与发电排放系数有很大差异。这表明网络方法在准确反映隐含排放方面的重要性。我们还观察到,省级电网内的购买电力排放系数存在很大差异:省级排放系数偏离相应的省级电网平均值,范围从-58%到 44%。这意味着,中国政府机构要求使用省级电网平均值来报告企业购买电力的间接二氧化碳排放量可能会非常不准确。网络方法可以提高购买电力隐含排放和输电隐含排放流量化的准确性。