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黄河流域旅游业碳排放量持续增长且分布格局复杂，厘清其时空特征并预测峰值，成为制定科学合理、绿色低碳发展路径的迫切需求。首先通过测算黄河流域2000—2023年旅游业碳排放量剖析该区域时空分异特征，然后借助扩展STIRPAT模型厘清该区域各影响因素，最后结合旅游业碳排放预测模型和情景分析法预测该区域旅游业碳达峰时间与峰值。结果表明：(1)黄河流域旅游业碳排放量呈先增长后断崖式下降再波动上升的变化态势，空间呈“东南多，西北少”的分布格局，重心整体由东南向西北方向迁移，轨迹呈现小“w”字型；(2)碳排放总体差异的主要原因来自区域内差异，而区域内差异主要源于上游地区的差异；(3)五大影响因素均对黄河流域旅游业碳排放产生作用，且不同区域各因素的作用强度存在显著差异；(4)不同发展情景下，该区域旅游业碳排放经历了“先上升后下降”的演变过程，各情景的达峰时间和峰值存在差异，其中绿色发展情景为最佳选择。
Abstract：The carbon emissions from tourism in the Yellow River Basin have been continuously increasing, with a complex distribution pattern.Understanding the spatio-temporal characteristics and predicting the peak emissions are urgent needs for formulating scientifically sound and green low-carbon development paths.This paper first calculated the carbon emissions from tourism in the Yellow River Basin from 2000 to 2023 to analyze the spatiotemporal differentiation characteristics of the region.Next, the extended STIRPAT model was used to clarify the influencing factors in the region.Finally, a tourism carbon emission prediction model, along with scenario analysis, was applied to predict the peak time and value of tourism carbon emissions in the region.The results showed that:(1) The carbon emissions from tourism in the Yellow River Basin initially increased, followed by a sharp declined and then fluctuating rose.The spatial distribution showed a pattern of “more in the southeast, less in the northwest",with the center of gravity shifting from southeast to northwest, forming a small “w" shape.(2) The main reason for the overall carbon emission differences came from the regional disparities, which were mainly driven by differences in the upstream areas.(3) The five major influencing factors all affected tourism carbon emissions in the Yellow River Basin, with significant differences in the strength of their impacts across different regions.(4) Under different development scenarios, the region′s tourism carbon emissions followed a “rise first, then fall" evolution, with differences in peak times and values across scenarios, where the green development scenario is the best choice.
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基本信息:
中图分类号:F592.7;X322
引用信息:
[1]陶春艳,时朋飞,李星明.黄河流域旅游业碳排放时空分异及峰值预测研究[J].资源开发与市场,2026,42(01):33-43.
基金信息:
重庆人文科技学院乡村旅游可持续发展研究中心
2024-11-05
2024
2025-02-08
2025
2
2025-11-14
2025-11-14
2025-11-14