Identifying the Full Carbon Sink of Forest Vegetation: A Case Study in the Three Northeast Provinces of China

Bing Wang, Xiang Niu () and Tingyu Xu ()
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Bing Wang: Ecology and Nature Conservation Institute, Chinese Academy of Forestry, Beijing 100091, China
Xiang Niu: Ecology and Nature Conservation Institute, Chinese Academy of Forestry, Beijing 100091, China
Tingyu Xu: Ecology and Nature Conservation Institute, Chinese Academy of Forestry, Beijing 100091, China

Sustainability, 2023, vol. 15, issue 13, 1-13

Abstract: Accurate analysis of the carbon sink capacity of forest vegetation is particularly important for achieving China’s carbon neutral strategy. In this study, we put forward the concept of the full carbon sink, which includes the sink capacity of forest components carbon sink tree arbors and bushes, sparse forest land, unclosed forest land, other shrubs, nursery, barren mountain shrubs, urban and rural green areas surrounding trees and scattered forests, and forest soil. The plot measurement method was used based on the forest resource inventory data and the plot data of the China Forest Ecosystem Research Network to accurately estimate the full carbon sequestration of forest vegetation in the Three Northeastern Provinces. The results showed that the full carbon sink is 69.45 TgC yr −1 , which is equivalent to neutralizing 22% of carbon emissions from energy consumption. Among the three provinces, the vegetation of Heilongjiang Province was the largest carbon sink, accounting for 63% of the total. Regarding the contribution of each component to the full carbon sink, tree arbors accounted for 78%, followed by other forest vegetation at 13%, then soil at 9%. Crop output was the main factor influencing the spatial pattern of the full carbon sink. The full carbon sink of forest vegetation can objectively reflect the important role of forestry in achieving the carbon neutrality strategy.

Keywords: three provinces in Northeast China; spatial pattern; full carbon neutral ability; impact factors (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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