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<p>Reducing carbon emissions is a basic policy long insisted on by the Chinese government, and the calculation of carbon footprint is of great application significance for reducing carbon emissions and realizing green consumption. Based on the multi-objective planning model this paper establishes a carbon footprint assessment model based on multi-objective planning from the economic, environmental, and social benefits of carbon footprint. It optimizes the particle swarm algorithm to solve the objective function of the carbon footprint multi-objective assessment model. The designed model is utilized in green consumption decision-making to forecast the carbon footprint and structure of green energy consumption in the future. The comparison shows that after the optimization of the carbon footprint assessment model based on multi-objective planning designed in this paper, the proportion of coal and oil consumption in the carbon footprint of energy consumption decreases by 1.2% and 0.5%, respectively, and the energy intensity can be optimized. The per capita carbon footprint of energy consumption of residents in eastern, central, and western China grows by 11.3%, 15.2%, and 2.7%, respectively, from 2024 to 2026. The carbon footprint of per capita energy consumption in the three regions is quite different. The results of the two projections show that the carbon footprint assessment model based on multi-objective planning designed in this paper is important for improving the energy consumption structure in different regions and realizing green consumption decisions.</p>
</abstract>

Reducing carbon emissions is a basic policy long insisted on by the Chinese government, and the calculation of carbon footprint is of great application significance for reducing carbon emissions and realizing green consumption. Based on the multi-objective planning model this paper establishes a carbon footprint assessment model based on multi-objective planning from the economic, environmental, and social benefits of carbon footprint. It optimizes the particle swarm algorithm to solve the objective function of the carbon footprint multi-objective assessment model. The designed model is utilized in green consumption decision-making to forecast the carbon footprint and structure of green energy consumption in the future. The comparison shows that after the optimization of the carbon footprint assessment model based on multi-objective planning designed in this paper, the proportion of coal and oil consumption in the carbon footprint of energy consumption decreases by 1.2% and 0.5%, respectively, and the energy intensity can be optimized. The per capita carbon footprint of energy consumption of residents in eastern, central, and western China grows by 11.3%, 15.2%, and 2.7%, respectively, from 2024 to 2026. The carbon footprint of per capita energy consumption in the three regions is quite different. The results of the two projections show that the carbon footprint assessment model based on multi-objective planning designed in this paper is important for improving the energy consumption structure in different regions and realizing green consumption decisions.

The application of carbon footprint assessment under intelligent computing in green consumption decision-making

Center of Education and Communications of Ecology and Environment of Sichuan Province

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

Reducing carbon emissions is a basic policy long insisted on by the Chinese government, and the calculation of carbon footprint is of great application...

The application of carbon footprint assessment under intelligent computing in green consumption decision-making

Online veröffentlicht: 05. Juli 2024

Seitenbereich: -

Eingereicht: 05. März 2024

Akzeptiert: 19. Mai 2024

DOI: https://doi.org/10.2478/amns-2024-1594

Schlüsselwörter
Multi-objective planning, Carbon footprint, Particle swarm algorithm, Objective function, Energy consumption

© 2024 Yu Du et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

The application of carbon footprint assessment under intelligent computing in green consumption decision-making

Online veröffentlicht: 05. Juli 2024

Seitenbereich: -

Eingereicht: 05. März 2024

Akzeptiert: 19. Mai 2024

DOI: https://doi.org/10.2478/amns-2024-1594

SchlüsselwörterMulti-objective planning, Carbon footprint, Particle swarm algorithm, Objective function, Energy consumption

© 2024 Yu Du et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
Multi-objective planning, Carbon footprint, Particle swarm algorithm, Objective function, Energy consumption