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Updated: May 28, 2026

Design and Use of a Full Flow Sampling System (FFS) for the Quantification of Methane Emissions
Published on: June 12, 2016
[Multi-source Carbon Emissions Evolution and Mitigation Pathways in China]
Meng-Lin Liu1, Qing-Hua Zhao1, Yu-Xiang Ma1
1Key Laboratory of Thermo-Fluid Science and Engineering, Ministry of Education, School of Energy and Power Engineering, Xi'an Jiaotong University, Xi'an 710049, China.
Abstract:
To investigate the evolutionary patterns of multi-source carbon emissions and formulate scientific reduction pathways in China, this study constructed an integrated "accounting-decomposition-prediction" analytical framework. Utilizing China's energy consumption, land use, and waste management data from 2000 to 2022, multi-source carbon emissions were calculated through the IPCC coefficient method, with key driving factors decoupled using the logarithmic man divisia index (LMDI) model. The system dynamics (SD) model combined with scenario analysis was employed to simulate carbon emission trends from 2023 to 2050. The results demonstrate that: ① Total carbon emissions exhibited phased characteristics of "rapid growth followed by decelerated increase," projected to peak at 12.193 billion t (in terms of CO2, the same as below) in 2030 before declining to 8.224 billion t by 2050. ② Carbon emission intensity achieved leapfrog reduction, decreasing from 3.177 4 t·(104 RMB)-1 in 2 000 to 0.355 8 t·(104 RMB)-1 in 2050, with a cumulative reduction of 88.80%. ③ Driver decomposition revealed that energy intensity significantly inhibited emissions (cumulative reduction of 1 973.90 Mt from 2001 to 2022), while per capita GDP demonstrated the strongest positive contribution (cumulative increase of 5 516.83 Mt). ④ The coordinated development scenario verified the time-sensitive compensation mechanism of policy interventions, establishing quantitative targets for key parameters including GDP, energy structure, and industrial composition. This study establishes a multi-source carbon analytical system, identifies the optimal emission reduction path through multi-policy coordination, and provides quantitative tools and decision-making support for constructing low-carbon oriented regional sustainable development systems.
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