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Updated: Jan 6, 2026
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Design and Use of a Full Flow Sampling System FFS for the Quantification of Methane Emissions
Published on: June 12, 2016
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Regional carbon emission reduction potential estimation based on scenario analysis under emission standards
Xuwei Xia1, Zhibin Yan2, Shuang Zhang1
1State Grid Ningxia Electric Power Co., Ltd., Technical Research Institute, Yinchuan, 750002, Ningxia, China.
Carbon Balance and Management
|October 1, 2025
Summary
This study estimates carbon emission reduction potential using scenario analysis and a novel index model, addressing data gaps. Results show improved efficiency and minimal industrial carbon emission contribution under strict standards.
Area of Science:
- Environmental Science
- Economics
- Industrial Engineering
Background:
- Estimating carbon emission reduction potential is hindered by missing data in many regions.
- Scenario analysis offers a viable approach to overcome data limitations in emission reduction assessments.
Purpose of the Study:
- To develop and apply a carbon emission reduction potential index model using scenario analysis.
- To estimate carbon emission rights considering industrial output value from 2018 to 2030.
Main Methods:
- Constructed a carbon emission reduction potential index model based on the Slack-Based Model (SBM).
- Employed a full factor carbon emission efficiency measurement method.
- Defined three emission limit scenarios: maintaining, ultra-low, and tightening.
Main Results:
- Carbon emission performance was found to be less than 0.05, indicating improved efficiency.
- Allocation weights were calculated, with a significant finding of industrial carbon emissions contributing nearly zero.
- The model estimated carbon emission rights from 2018 to 2030.
Conclusions:
- The developed model effectively estimates carbon emission reduction potential despite data limitations.
- Improved carbon emission efficiency is achievable through scenario-based analysis and defined emission standards.
- The study highlights a near-zero contribution of industrial carbon emissions under the analyzed conditions.
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