Multi-scenario Simulation on Carbon Storage of Green Space in Harbin City - Li Xue; Li Wen; Shi Song; Qu Chen (Shuitu baochi tongbao)
[Objective] The carbon storage of the future green space patterns was predicted, and the impact of green space changes on carbon storage was analyzed in order to provide a basis for green space planning in Harbin City, Heilongjiang Province under the dual-carbon policy. [Methods] Based on the green space land cover data of Harbin City in 2010 and 2020, the dual-carbon industry driving factors were introduced into the FLUS model, and the changes in green space land cover under different scenarios in 2030 were predicted. The carbon storage values in 2010, 2020, and 2030 were calculated using the InVEST model. The spatial-temporal variation of carbon storage was compared and analyzed, and the influence of green space on carbon storage was discussed. [Results] ① After the dual-carbon industry factors were introduced into the FLUS model, the kappa coefficient increased by 1.30%, and the root mean square error decreased by 0.21% compared with the original model, indicating increased simulation accuracy of the improved model. ② From 2010 to 2020, carbon storage decreased by 5.14×106 t, primarily as result of decreased cultivated land. Carbon was primarily stored in the aboveground biomass carbon pool and the soil carbon pool, accounting for 88.52% of the total carbon reserves. ③ Carbon storage under natural development, ecological protection, and economic development scenarios in 2030 were 2.58×109, 2.58×109, and 2.58×109 t, respectively, showing a downward trend from 2020. The decline rate in the ecological protection scenario was the slowest of the three scenarios, and was 0.12 times the rate observed for the natural development scenario. [Conclusion] In the future, ecological protection and restoration measures should be strengthened to reduce the loss of cultivated land and forest land, and the expansion of non-green space should be controlled in order to improve carbon storage in Harbin City.