Objective Based on the existing survey data from the 8th Landscape Plant Census of Forest Resources Type Ⅱ survey data, the forest carbon sink capacity of Beijing was assessed to provide a theoretical basis for the scientific management of forest resources in the city.

Method In this study, we adopted the forest stock expansion method to calculate the overall carbon stock, carbon density and changes in Beijing’s forests, and use the afforestation cost method and carbon tax method to assess the economic value of their carbon stocks.

Result (1) The total carbon stock of the total forest in Beijing was 1 934.59 ×10⁴ t, and the carbon density was 32.35 t/ha, among the regions, Miyun District, Yanqing District and Shunyi District had larger carbon stocks, accounting for 13.79%, 12.73% and 11.40%, respectively, while those with higher carbon density were Shunyi District, Daxing District and Tongzhou District; the carbon density of both plains and mountains showed broadleaf forests > mixed forests > coniferous forests, and the carbon density of forests in plains was about 3.3 times higher than that in mountains; the carbon stocks in both mountains and plains were dominated by broadleaf trees; protection forests were the main contributors to the forest carbon stock. The carbon stock of protection forest was the main contributor to forest stock, among which soil and water conservation forest had the largest carbon stock of 414.15 ×10⁴ t, while the carbon density of farmland protection forest was the largest at 175.23 t/ha; the carbon stock of dominant species was ranked as follows: other Populus spp. > Quercus spp. > Pinus tabuliformis > broadleaf tree > Platycladus orientalis > Robinia pseudoacacia > Betula spp. > Larix principis-rupprechtii > Populus davidiana, the carbon density was ranked as follows: other Populus spp. > Betula spp. > Larix principis-rupprechtii > Populus davidiana > Pinus tabuliformis > Robinia pseudoacacia > Quercus spp. > broadleaf tree > Platycladus orientalis; the carbon stock and carbon density in different origins were: planted forests > flycasting forests > natural forests; the carbon stock size in age group: middle-aged forest > young forest > mature forest > near-mature forest > over-mature forest, and the overall pattern of carbon density increased with the increase of age class. (2) From the first to the eighth forest resource survey, forest carbon stock and carbon density continued to increase; among the forest species, special-purpose forest had the highest growth rate and the highest carbon density; carbon stock of larch and aspen increased and then decreased, while acacia and birch showed a trend of decreasing and then increasing, and all other tree species showed an increasing trend, while carbon density of oleander, larch and aspen increased and then decreased, side cypress, Quercus spp. and birch decreased and then increased, acacia and broadleaf tree continued to decrease, and poplar continued to increase; both natural and planted forests showed an increasing trend. (3) Based on different carbon prices estimated by the afforestation cost method and the carbon tax method, the economic value of forest carbon stocks in Beijing ranged from 5.414 billion to 23.215 billion RMB, and the economic value of forest carbon stocks under the carbon tax method was higher. The economic value of carbon stock in each region of Beijing under the two calculation methods varied greatly, with Miyun, Yanqing, and Shunyi districts having the largest economic value of carbon stock; among all dominant tree species, poplar had the highest economic value of carbon stock; and among age groups, middle-aged forests had the largest contribution to Beijing.

Conclusion Beijing’s forests have obvious carbon sequestration potential, but the overall carbon sink is relatively low. In the future, we should pay attention to the matching of forest structure, strengthen the management of forest land cultivation, enhance the function of Beijing’s forest carbon sink, improve the value of carbon sink, and stimulate the vitality of forestry management.