Spatiotemporal Characteristics and Factors Influencing Value of Forest Carbon Sequestration in Henan Province

Abstract

[Objective] The spatiotemporal characteristics and factors influencing the value of forest carbon sequestration in Henan Province were analyzed in order to provide a reference for promoting the realization of “carbon peak and carbon neutrality”. [Methods] The value of forest carbon sequestration in Henan Province from 2010 to 2020 was evaluated through the stock expansion method and the afforestation cost method, and the temporal variation characteristics of forest carbon sequestration value were analyzed. The Moran index was used to explore the spatial aggregation characteristics, and an extended STIRPAT model was constructed to analyze the factors affecting the value of forest carbon sequestration. [Results] ① The value of forest carbon sequestration in Henan Province showed a continuous rising trend which increased from 4.18 billion yuan in 2010 to 6.71 billion yuan in 2020. Carbon sequestration values exhibited a pattern of “higher in the west and south, lower in the east and north” in Henan Province, and there was a significant positive spatial aggregation effect. The areas with significant high carbon sequestration values were located in Western and Southern Henan Province, while there were only two areas with significant low carbon sequestration values. ② In addition to the negative impact of carbon sink intensity on the value of forest carbon sequestration in Henan Province, the proportion of forest area, urbanization ratio, forestry industry ratio, and per capita GDP all showed positive impacts. The proportion of forest area was the most important factor promoting the growth of forest carbon sequestration values. [Conclusion] There is great potential for forest carbon sequestration in Henan Province, and the realization of forest carbon sequestration should be promoted regionally in the future.

Keywords

• forest carbon sequestration
• carbon sequestration value
• moran index
• stirpat model
• influencing factors
• henan province