中国省域旅游业碳中和时空分异与模拟

旅游业碳中和的实现对于旅游业的绿色高质量发展和可持续发展至关重要。基于全国尺度以30个省份为分析单元,在承接团队前期关于旅游业碳达峰研究成果的基础上,借助土地利用数据、碳吸收系数和灰色预测模型分别测算与模拟了近20年和未来40年各省旅游业碳汇,通过旅游业碳中和指数反映旅游业碳排放和旅游业碳汇之间的动态变化,并利用空间自相关探索旅游业碳中和指数的时空差异。结果表明：（1）未来40年,我国省域旅游业碳汇总体呈现出"南北高,中间低"的空间分布特征,大多数省份的旅游业碳汇不断增长。东北部地区和长江流域以南各地区的旅游业碳汇较为富余,华东地区的山东、江苏和上海等省份的旅游业碳汇则相对匮乏。（2）不同情景中,低碳情景下的旅游业碳中和实现情况最好,有云南、四川和青海等7个省份在2060年之前实现了旅游业碳中和,而中等情景和基准情景下均仅有黑龙江和云南2个省份能够如期或提前实现。其中,西部和北部沿边省份的旅游业碳中和实现情况都要优于其它地区。（3）各省旅游业碳中和指数在未来40年的等级分区大致呈现出从Ⅰ级区逐步向Ⅴ级区转变的趋势,我国总体旅游业碳赤字率由2030年的96.67%逐渐降至2060年的76.67%。（4）未来40年,我国省域旅游业碳中和指数在空间上总体处于集聚态势,热点和冷点的空间分布特征较为明显,且演化趋势较为稳定。其中,热点区和次热点区主要分布在西北、西南、华南和东北地区,冷点区和次冷点区集中分布在华北、华中和华东地区。研究有效探讨了旅游业碳中和研究的理论与范式,并为中国旅游业碳中和的实现提供了一定的现实参考。

Spatio-temporal differentiation and simulation of provincial tourism carbon neutrality in China

Achievement of tourism carbon neutrality is crucial to the green and high-quality development and sustainability of tourism. This paper takes 30 provinces as the unit of analysis at the national scale. We measure and simulate the tourism carbon sinks of each province in the last 20 years and the next 40 years with the land use data, carbon absorption coefficients and gray prediction models. The dynamic changes between tourism carbon emissions and tourism carbon sinks are analyzed through the tourism carbon neutrality index, and the spatial and temporal differences of the tourism carbon neutrality index are explored by using spatial autocorrelation. The results show that:(1) in the next 40 years, the Chinese provincial tourism carbon sinks show a spatial distribution characteristic of high in the north and low in the middle, and most provincial tourism carbon sinks will be growing. The tourism carbon sinks in the northeastern region and the south regions of the Yangtze River Basin are relatively abundant, while those in Shandong, Jiangsu and Shanghai in eastern China are relatively scarce. (2) Among different scenarios, the low-carbon scenario has the best achievement of tourism carbon neutrality, with seven provinces, including Yunnan, Sichuan and Qinghai, before 2060. Only two provinces, Heilongjiang and Yunnan, achieve tourism carbon neutrality on time or ahead of schedule in both the medium and baseline scenarios. In all scenarios, the western and northern border provinces achieve tourism carbon neutrality better than other regions. (3) The tourism carbon neutrality index of each province in the next 40 years roughly shows a gradual shift from Class I to Class V zones, and the overall tourism carbon deficit rate of China will gradually decrease from 96.67% in 2030 to 76.67% in 2060. (4) In the next 40 years, the provincial tourism carbon neutrality index is generally in a spatial clustering situation, and the spatial distribution characteristics of hot spots and cold spots are more obvious, and the evolution trend is more stable. Among them, hot spots and sub-hot spots are mainly distributed in Northwest, Southwest, South, and Northeast China, while cold spots and sub-cold spots are concentrated in North China, Central China and East China. This paper effectively explores the theory and paradigm of tourism carbon neutrality research, and provides some realistic references for achieving China''s tourism carbon neutrality.