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Updated: Jan 15, 2026

Design and Use of a Full Flow Sampling System FFS for the Quantification of Methane Emissions
Published on: June 12, 2016
[Accounting and Driving Factor Analysis of Carbon Emissions in Heilongjiang Province]
Hao-Dong Liu1, Si-Tao Li2, Xiang Zhang1
1School of Environment, Harbin Institute of Technology, Harbin 150090, China.
Abstract:
Based on the greenhouse gas inventory guidelines proposed by the Intergovernmental Panel on Climate Change of the United Nations, the carbon emissions of Heilongjiang Province were calculated from aspects such as energy, industrial production processes, and land use. The correlation between different factors and carbon emissions was analyzed using grey relational theory and Tapio decoupling theory, and the STIRPAT model was used to explore the differences in the impact of various factors on carbon emissions. Future carbon emissions in Heilongjiang Province were predicted using scenario analysis. The results showed that: ① The total carbon emissions in Heilongjiang Province grew rapidly from 2005 to 2012, then showed a fluctuating downward trend from 2012 to 2020, with the decline gradually slowing. ② Energy carbon emissions dominated the carbon emissions in Heilongjiang Province, accounting for approximately 90%, far exceeding the other three categories of carbon emissions. ③ The order of influence of different factors on carbon emissions was as follows: land area > population > energy structure > wealth level > energy intensity. ④ During the study period, carbon emissions in Heilongjiang Province reached the peak in 2012 according to the STIRPAT model, effectively achieving the goal of "carbon peak." ⑤ In the scenario simulation, the optimal scenario was Scenario IV. In this scenario, the rate of change for each factor was based on the more optimal values between the recent actual data from Heilongjiang Province and the "14th Five-Year Plan."
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