A carbon emission allowance bargaining model for energy transactions among prosumers is proposed to enable cost-effective decarbonization in energy networks. The model is based on a nodal carbon pricing approach, incorporating the sharing and integration of intraregional carbon emission allowances. Game theory is used to construct a multi-agent carbon emission allowance bargaining model, which is solved using the alternating direction multiplier method (ADMM) to address competitive burden and privacy preservation. Numerical results show that the model significantly reduces regional carbon emissions and improves the economic benefits of prosumers. The model is structured in two levels: the upper level formulates a carbon flow-led nodal carbon price based on the carbon emission flow (CEF) technique, while the lower level involves carbon emission allowance (CEA) bargaining among prosumers. This is converted into two subproblems: cooperative alliance maximization and benefit distribution. The upper-level model considers the joint clearing of regional energy systems and the optimal operation of prosumers, while the lower-level model involves prosumers negotiating CEA/Chinese Certified Emission Reduction (CCER) to obtain the best trading strategy and return energy demand to the upper level. The upper-level formulation includes the prosumers' unit set and market set, with the carbon flow-led nodal carbon pricing model using the node carbon emission intensity (NCI) to determine the nodal carbon price. The lower-level formulation involves minimizing the prosumers' overall costs, including operation and carbon trading costs. The model is solved using ADMM, leading to optimal CEA trading volumes and prices among prosumers. Case studies demonstrate the effectiveness of the model, showing that prosumers can achieve more stable and credible transaction prices through CEA bargaining. The model also reduces the total operation cost of prosumers and improves their profits. The model is scalable and feasible, with the calculation time and number of iterations increasing only slightly with the number of prosumers. The results indicate that the proposed model can effectively reduce regional carbon emissions and assist prosumers in making optimal carbon trading decisions.A carbon emission allowance bargaining model for energy transactions among prosumers is proposed to enable cost-effective decarbonization in energy networks. The model is based on a nodal carbon pricing approach, incorporating the sharing and integration of intraregional carbon emission allowances. Game theory is used to construct a multi-agent carbon emission allowance bargaining model, which is solved using the alternating direction multiplier method (ADMM) to address competitive burden and privacy preservation. Numerical results show that the model significantly reduces regional carbon emissions and improves the economic benefits of prosumers. The model is structured in two levels: the upper level formulates a carbon flow-led nodal carbon price based on the carbon emission flow (CEF) technique, while the lower level involves carbon emission allowance (CEA) bargaining among prosumers. This is converted into two subproblems: cooperative alliance maximization and benefit distribution. The upper-level model considers the joint clearing of regional energy systems and the optimal operation of prosumers, while the lower-level model involves prosumers negotiating CEA/Chinese Certified Emission Reduction (CCER) to obtain the best trading strategy and return energy demand to the upper level. The upper-level formulation includes the prosumers' unit set and market set, with the carbon flow-led nodal carbon pricing model using the node carbon emission intensity (NCI) to determine the nodal carbon price. The lower-level formulation involves minimizing the prosumers' overall costs, including operation and carbon trading costs. The model is solved using ADMM, leading to optimal CEA trading volumes and prices among prosumers. Case studies demonstrate the effectiveness of the model, showing that prosumers can achieve more stable and credible transaction prices through CEA bargaining. The model also reduces the total operation cost of prosumers and improves their profits. The model is scalable and feasible, with the calculation time and number of iterations increasing only slightly with the number of prosumers. The results indicate that the proposed model can effectively reduce regional carbon emissions and assist prosumers in making optimal carbon trading decisions.