Calculation and peak forecasting of power carbon emission factors in Zhejiang Province

To reveal the evolution patterns and driving mechanisms of the average power carbon emission factor in Zhejiang Province and predict its changing trend at the end of the 15th Five-Year Plan period, this paper calculates the annual power carbon emission factor of Zhejiang Province from 2020 to 2025 based on the accounting method specified by the Ministry of Ecology and Environment. The logarithmic mean Divisia index (LMDI) method is employed to decompose the variation of emission factor into four effects: in-province thermal share effect, in-province intensity effect, imported power structure effect and imported power intensity effect. Combined with the targets specified in the Outline of the 15th Five-Year Plan for National Economic and Social Development of Zhejiang Province, the baseline scenario and accelerated-transition scenario are set up to forecast the emission factor for 2030. The results show that from 2020 to 2025, the power carbon emission factor exhibits a trend of rising first and then dropping. It rises from 0.4954 kgCO₂/(kW·h) in 2020 to the peak value of 0.5308 kgCO₂/(kW·h) in 2022, and then falls to 0.4718 kgCO₂/(kW·h) in 2025. The average absolute deviation from officially released values is 4.54%. The LMDI decomposition results indicate that in terms of cumulative contribution, the imported power structure effect serves as the dominant factor for the decline of emission factor, with a cumulative contribution of −0.0336 kgCO₂/(kW·h), accounting for 142% of the total reduction. In terms of annual contribution, the in-province thermal power share effect acts as the largest driving factor for the reduction of carbon emission factor in certain years (e.g., 2022). Nevertheless, its positive and negative contributions offset each other over the five-year period, yielding a tiny cumulative contribution of only 0.0015 kgCO₂/(kW·h). In 2030, the emission factor is projected to drop to 0.39 kgCO₂/(kW·h) under the baseline scenario and 0.36 kgCO₂/(kW·h) under the accelerated-transition scenario. This study can provide a quantitative reference for the dynamic assessment and path optimization of the dual-control targets of carbon emissions in Zhejiang’s power sector.