基于空间聚类分析的中国旅游业碳排放效率

旅游业碳排放效率是考量旅游经济增长与生态环境关系的重要指标，对旅游业碳排放效率的有效测度和分析是实现旅游业节能减排与可持续发展的基础支撑.采用“自下而上”法核算2001—2015年我国旅游业能源消耗量与碳排放量（不含港澳台及西藏自治区数据，下同）；继而运用非期望产出SBM模型对旅游业碳排放效率进行测度，并通过空间自相关分析揭示其空间特征；最后采用Malmquist指数（MI）评估旅游业碳排放效率的动态趋势.结果表明:①研究期内我国旅游业总体碳排放效率较低，平均水平为60%；各年度达到最佳生产前沿面（旅游业碳排放效率值为1）的省(市、自治区)(简称“省区”)数量较少，绝大多数省区的碳排放效率具有较大改善空间；旅游业碳排放效率水平存在明显的省际差异；东、中、西部地区的效率存在梯度差，形成“东高西低”的空间格局.②Moran's I指数和LISA聚类图显示，各省区旅游业碳排放效率存在明显的正向空间相关性，在空间分布上呈现出显著的地理聚集特征，形成“高—高”型与“低—低”型聚集区，空间联动格局尚未形成.③2001—2015年MI均在1以上（2004年除外），且总体平均值高达1.195，体现出持续改善的态势；各省区碳排放效率的提升来源于技术进步与技术效率双重贡献，其中，技术进步是促进旅游业碳排放效率提升的主要贡献因素.研究显示，我国旅游业碳排放效率的空间分布不均衡，但整体呈现持续上升的态势，各省区在依赖技术进步提高碳排放效率的同时，要注重全局空间联动格局的形成，最终实现低碳旅游业的协调发展. 

Carbon Emission Efficiency in China's Tourism Industry by Spatial Clustering Analysis

Carbon emission efficiency of tourism industry is an important index to evaluate the link between economic growth of tourism and ecological environment. The measurement and analysis of carbon emission efficiency is the basic support for energy saving and sustainable development of tourism industry. By using the 'bottom-up' approach, the energy consumption and carbon emission of tourism industry and its subsectors in China were estimated from 2001 to 2015 (the data do not include Hong Kong, Macao, Taiwan and Tibet Autonomous Region). Based on the panel data about provincial input-output of tourism industry, the carbon emission efficiency of China's tourism is measured by the SBM model considering the unexpected output. In addition, the spatial autocorrelation is applied to analyze the spatial distribution characteristics of carbon emission efficiency of tourism. At last, the Malmquist index is used to evaluate the dynamic trend of carbon emission efficiency of tourism industry. The results show that carbon emission efficiency of China's tourism industry is low, with an average of 60%, during the study period. In each year, the number of provinces with the best production frontier (carbon emission efficiency of tourism is 1) is less, there are only 2 to 4 provinces per year and efficiency of most provinces needs to be improved. There are obvious provincial differences in the carbon emission efficiency of tourism industry. The efficiency of the East, Middle and West of China has gradient difference, forming the spatial pattern of 'high in eastern China and low in western China'. The Moran's I index and the LISA clustering show carbon emission efficiency of tourism industry has significant characteristics in spatial correlation which are still strengthening constantly, and forming 'high-high' type and 'low-low' type gathering area. The spatial linkage pattern of carbon emission efficiency of tourism has not formed. Except for 2004, the Malmquist index is greater than 1 from 2001 to 2015. The average of Malmquist index is 1.195, as a result, the overall efficiency of carbon emission of tourism continues to improve. The promotion of carbon emission efficiency of tourism industry comes from technological progress and technical efficiency. Technological progress is the main contribution factor to promote the efficiency of carbon emission of tourism industry. It is expected that the above conclusions can provide valuable reference for the improvement carbon emission efficiency of China's tourism industry, and provide a theoretical basis for energy saving, emission reduction and sustainable coordinated development of tourism economy.