Carbon sinks are of great significance for mitigating the greenhouse effect and climate change. However, only a few carbon sink measurement methods are suitable for small-scale research, such as at the city-region scale. Methods that can accurately distinguish the high–low gradients of forest carbon sinks within small-scale areas have not yet been established. To fill this gap, we used a tree allometric growth model—the i-Tree Eco model—and applied it to Tai’an, which is a National Forest City in China. By using indicator conversion methods, we innovatively combined the China Forest Resources Inventory Geographic Information Database with i-Tree Eco. The results showed that i-Tree Eco successfully estimated the carbon sinks provided by urban–rural forests (in 2019)—the total carbon storage in Tai’an forest was 5,828,165.90 t; the average carbon storage per hectare was 37.19 tC·ha−1; the total carbon sequestration was 936,789.03 tC·yr−1; and the annual carbon sequestration was, on average, 5.97 tC·ha−1·yr−1. Our method improved the spatial resolution of carbon sequestration and storage compared to the commonly used InVEST model, from about 350 m × 350 m to 195 m × 195 m. Compared to the traditional IPCC method, the i-Tree Eco model provided greater accuracy and timeliness in small-scale carbon sequestration measurements, eliminating the need to wait for the next forest inventory to be published. Our method yielded results that covered the entire city region and better reflected the spatial heterogeneity of carbon sinks. We conclude that the innovative application of the i-Tree Eco model to urban–rural-scale carbon sink measurements provides stronger technical support for urban green space planning, as well as data guidance, in relation to local carbon mitigation strategies.
Li et al. (Fri,) studied this question.