江西县域土地利用变化碳排放时空演变及其影响因素

查明县域尺度下土地利用变化碳排放,对于推进县域低碳发展和土地资源的可持续利用与管理具有重要意义。以江西省为例,基于2000-2020年江西省土地利用数据、社会经济数据等,利用空间自相关模型和对数平均迪氏指数分解法(LMDI) 法,对其县域土地利用碳排放时空演变及影响因素进行分析。结果表明:①2000-2020年间,区县土地利用碳排放均呈上升趋势,碳排放量增速和平均碳排放强度均有下降,但部分区县碳排放增速在2015年后出现提高的变化特征。建设用地是碳排放量增长的首要碳源,林地则具有重要的碳汇作用。②空间上,土地利用变化碳排放呈现出明显的空间差异,表现为北高南低的分布特征和较为稳定的聚类模式,即轻度和重度及以上排放区空间分布上较为集中。经济发达区县成为碳排放量增长"核心",欠发达区县则是碳排放量增长"外围",且这种"核心-外围"格局在不断强化。③总体上,抑制碳排放量增长的主要因素为碳排放强度及土地利用效率;驱动因素则有经济发展水平和建设用地规模。但部分区县碳排放强度可能表现为"前期驱动后期抑制"作用,且抑制作用小于驱动作用,故这类区县土地利用碳排放量仍显著增长。因此,江西省各区县应积极调整产业结构和继续降低碳排放强度及通过优化土地资源配置,提高土地利用效率,如用适度集约模式提高建设用地利用效率以免盲目性扩张浪费。另外,欠发达地区和发达地区需加强在资金、技术等领域的交流与合作,不同区县还应因地制宜,各自明确发展目标,走具有各自县域特色的低碳高质量发展道路。

Spatiotemporal pattern evolution and influencing factors of land-use carbon emissions in counties, Jiangxi Province

Identifying carbon emissions from land-use change at the county scale is important for promoting low-carbon development and sustainable use and management of land resources in counties. Thus, here, taking Jiangxi province as an example, we use the spatial autocorrelation model and Logarithmic Mean Divisia Index (LMDI) method to analyze the spatiotemporal pattern evolution and the influencing factors of land-use carbon emissions in the counties, based on land-use data and socio-economic data of Jiangxi Province from 2000-2020. The results show that: (1) the carbon emissions from land use in different districts showed an increasing trend, but the growth rate of carbon emissions and the average carbon emission intensity decreased in 2000-2020. However, some districts showed a change in the growth rate of carbon emissions that increased after 2015. Construction land is the primary source of carbon emission growth, while forest land has an important role as a carbon sink. (2) Spatially, the distribution of carbon emissions from land-use change shows obviously spatial differences, with a high north to low south distribution and a relatively stable clustering pattern, and the spatial distribution of light and heavy emission areas and above is more concentrated. With economically developed regions and counties being the "core" and undeveloped regions and counties being the "periphery" of carbon emissions growth. And this "core-periphery" pattern is continuously strengthening. (3) In general, the main factors inhibiting the growth of carbon emissions are carbon emission intensity and land-use efficiency; the driving factors are the level of economic development and the scale of construction land. However, the carbon emission intensity of some districts and counties show the effect of "early driving and later suppressing", and the suppressing effect is smaller than the driving effect, so the carbon emission of land use in these districts and counties is still growing significantly. Therefore, Jiangxi counties should actively adjust their industrial structure and continue to reduce their carbon emissions intensity and improve land use efficiency by optimizing the allocation of land resources. For example, people should use an appropriately intensive model to improve the efficiency of construction land use for avoiding blind expansion and waste. Moreover, the undeveloped and developed regions need to strengthen exchanges and cooperation in the areas of capital and technology. In addition, different regions and counties in Jiangxi province should also take into account their own local conditions, define their own development goals and follow a low-carbon, high-quality development path with their own county characteristics.