Carbon stock is an important indicator of cumulative ecosystem productivity. Using this indicator, and based on field sampling data, this paper compared the long-term difference in carbon stocks between aerial seeding (AS) and natural regeneration (NR) forests of Pinus massoniana in sub-tropic forests, China, in order to assess the effectiveness of AS in a highly degraded forest landscape. The results showed that the carbon stocks of stems, branches, roots, and trees (including stems, branches, leaves, and roots) were 140%, 85%, 110%, and 110%, significantly higher (p < 0.05) in the NR forests than those in the AS forests at the ages of 11–20 years, respectively. In addition, the carbon stocks of understory, litter and soil were also 176%, 151%, and 77%, significantly higher (p < 0.05) in the NR forests than those in the AS forests at the same age range, respectively. However, with increasing age (i.e., >21 years), those differences became statistically insignificant (p > 0.05). The total carbon stocks of the two forest types also showed a similar pattern. Those results clearly demonstrate that AS was an effective mean for restoring carbon stocks in highly degraded areas, even though their early growth was lower than the NR forests, and thus can be applied in the regions where the areas with limited seed sources and road accessibility.

Carbon density is an important indicator of carbon sequestration capacity in forest ecosystems. We investigated the vegetation carbon density of Pinus massoniana Lamb. forest in the Jiangxi Province. Based on plots investigation and measurement of the carbon content of the samples, the influencing factors and spatial variation of vegetation carbon density (including the tree layer, understory vegetation layer and litter layer) were analysed. The results showed that the average vegetation carbon density value of P. massoniana forest was 52 Mg·ha⁻¹. The vegetation carbon density was significantly (p < 0.01) and positively correlated with the stand age, mean annual precipitation, elevation and stand density and negatively correlated with the slope and mean annual temperature. Forest management had a significant impact on vegetation carbon density. To manage P. massoniana forest for carbon sequestration as the primary objective, near-natural forest management theory should be followed, e.g., replanting broadleaf trees. These measures would promote positive succession and improve the vegetation carbon sequestration capacity of forests. The results from the global Moran’s I showed that the vegetation carbon density of P. massoniana forest had significant positive spatial autocorrelation. The results of local Moran’s I showed that the high-high spatial clusters were mainly distributed in the southern, western and eastern parts of the province. The low-low spatial clusters were distributed in the Yushan Mountains and in the northern part of the province. The fitting results of the semivariogram models showed that the spherical model was the best fitting model for vegetation carbon density. The ratio of nugget to sill was 0.45, indicating a moderate spatial correlation of carbon density. The vegetation carbon density based on kriging spatial interpolation was mainly concentrated in the range of 32.5–69.8 Mg·ha⁻¹. The spatial distribution of vegetation carbon density regularity was generally low in the middle region and high in the peripheral region, which was consistent with the terrain characteristics of the study area.

The Chinese government has set ambitious carbon peak and carbon neutrality goals for 2030 and 2060. To achieve these targets, China will need to adopt stricter carbon emission policies in the future. Due to China’s vast territory, there are significant disparities in economic development levels and carbon dioxide emissions (CEs) among its provinces. Therefore, equitable carbon reduction policies are crucial for regional economic development. This study calculates CEs from energy consumption in 30 Chinese provinces using energy balance tables and CEs factors. Based on this, the Dagum decomposition Gini index is used to quantitatively assess CEs inequality between the primary, secondary, and tertiary industries in China’s central, eastern, and western regions. The results show that over the past 25 years, China’s CEs have increased from 3.17 billion tons to 13.32 billion tons, with an average annual growth rate of 6.17%. Additionally, CEs inequality in China has decreased by 3.96%. Moreover, CEs inequality in the eastern provinces has decreased the most (57.65%), followed by the central and western regions. Furthermore, CEs inequality in the secondary industry has expanded in all three regions, while inequality in the tertiary industry remained smaller due to technological and geographical constraints.