Article: Marginal emission reduction costs of regional energy system transformation enabled by digital economy from the perspective of supply chain Journal: International Journal of Environment and Pollution (IJEP) 2026 Vol.76 No.8 pp.1 - 26 Abstract: The existing supply chain management model cannot effectively control unit-level marginal emission-reduction costs. This paper constructs a multi-level, integrated framework based on the extreme gradient boosting (XGBoost) algorithm to capture the nonlinear relationships among electricity prices, weather, industrial activities, and historical loads, and to output node loads and carbon-emission boundaries dynamically. The prediction results are transmitted to the mixed-integer linear programming (MILP) model in real time, which optimises the carbon-emission path using piecewise linear control and global constraints to minimise the unit marginal emission-reduction cost. The node carbon emission data is written to the Hyperledger Fabric blockchain after encryption, enabling full-link, end-to-end encrypted evidence storage and traceability. Experiments show that when the carbon quota is set to 50% of the system's baseline emissions, the unit marginal emission-reduction cost is reduced from 278 yuan/ton to 245 yuan/ton. Inderscience Publishers - linking academia, business and industry through research

Title: Marginal emission reduction costs of regional energy system transformation enabled by digital economy from the perspective of supply chain

Authors: Wenjuan Liu; Wenbo Ma

Addresses: College of Economics and Management, Henan Polytechnic, Zhengzhou, 450046, Henan, China ' College of Business Administration, Zhejiang University of Finance and Economics Dongfang College, Haining, 314408, Zhejiang, China

Abstract: The existing supply chain management model cannot effectively control unit-level marginal emission-reduction costs. This paper constructs a multi-level, integrated framework based on the extreme gradient boosting (XGBoost) algorithm to capture the nonlinear relationships among electricity prices, weather, industrial activities, and historical loads, and to output node loads and carbon-emission boundaries dynamically. The prediction results are transmitted to the mixed-integer linear programming (MILP) model in real time, which optimises the carbon-emission path using piecewise linear control and global constraints to minimise the unit marginal emission-reduction cost. The node carbon emission data is written to the Hyperledger Fabric blockchain after encryption, enabling full-link, end-to-end encrypted evidence storage and traceability. Experiments show that when the carbon quota is set to 50% of the system's baseline emissions, the unit marginal emission-reduction cost is reduced from 278 yuan/ton to 245 yuan/ton.

Keywords: digital economy integration; marginal abatement cost; regional energy system; supply chain coordination; carbon information governance.

DOI: 10.1504/IJEP.2026.156117

International Journal of Environment and Pollution, 2026 Vol.76 No.8, pp.1 - 26

Received: 05 Sep 2025
Accepted: 01 Apr 2026
Published online: 04 Sep 2026 *

Title: Marginal emission reduction costs of regional energy system transformation enabled by digital economy from the perspective of supply chain

Keep up-to-date