[Carbon Emission Probability Density Forecasting and Carbon Peaking Potential Analysis： A Case of Anhui Province]

China has committed to achieving carbon peaking before 2030， which calls for overcoming the limitations of traditional point prediction methods in addressing the uncertainties of carbon emissions. A more comprehensive forecasting model is essential to support scientific decision-making and policy design. As a key part of the Yangtze River Delta integration and the Central China Rise strategy， Anhui Province plays a critical role in promoting high-quality development and low-carbon transition. Therefore， Anhui Province is selected as the study area to develop a carbon emission probability density forecasting model based on the quantile regression neural network （QRNN）. It evaluates the actual emission reduction progress in 2022 and conducts carbon emission forecasts and peaking potential analysis under four scenarios for the period 2023-2035. The main findings are as follows： ① The proposed model not only achieved high-accuracy point prediction but also effectively captured the uncertainty of carbon emissions. ② In 2022， Anhui's carbon reduction performance was unsatisfactory， with a 79.01% probability that total emissions will continue to increase， and relative reduction targets were not achieved. ③ The energy revolution scenario was identified as the optimal development pathway， under which Anhui is expected to reach its carbon peak in 2028， with a peak value of 456.78 Mt. This study provides theoretical support and decision-making references for Anhui Province in formulating precise carbon peaking strategies and promoting green， sustainable regional development.