摘要
针对区域旅游碳排放问题,从旅游所涉及的各行业着手,引入"旅游消费剥离系数",对区域旅游业的碳排放进行具体测算。由于旅游业相关统计的不完善及统计口径的变化性,文章构建了相应的灰色GM(1,1)模型,以广东为例,根据所测算的碳排放,对区域未来5年的旅游碳排放的走势进行预测分析。结果表明旅游收入与碳排放二者之间呈高度正相关,若不改变旅游发展模式,旅游经济的高速发展必然会带来旅游碳排放的快速增长,2017年广东旅游碳排放比2014年将增加70%。从环境税视角并结合旅游业特点,就低碳旅游的可持续发展提出了政策建议,为各区域开展绿色旅游经济提供参考。
Aiming at the problem of regional tourism carbon emissions,proceed from various industries involved in tourism.In order to calculate the carbon emissions of regional tourism industry,"tourism consumption stripping factor" is introduced.Because of the related statistics of tourism is not perfect and the variability of statistical caliber,the paper use Grey GM(1,1) Model to predict the next 5 years of carbon emissions-take Guangdong Province as an example.The result shows that there is a high positive correlation between Guangdong Province tourism income and carbon emissions.If we do not change the tourism development mode,high speed economic development of tourism will inevitably bring the rapid growth of tourism carbon emissions.The tourism carbon emissions of Guangdong Province will increase by 70% in 2017 than that of 2014.Finally,from the perspective of environmental tax and combined with the characteristics of tourism,sustainable development of low-carbon tourism policy built on,provide a reference for regional super giant green tourism.
出处
《生态经济》
CSSCI
北大核心
2016年第5期74-78,共5页
Ecological Economy
基金
国家社会科学基金重大攻关项目"应对国际资源环境变化挑战与加快我国经济发展方式转变研究--基于政府规制视角"(09&ZD021)
暨南大学科研培育与创新基金项目"区域旅游产业生态网络与城镇生态化发展的融合性研究"
关键词
旅游碳排放
旅游消费剥离系数
灰色预测模型
tourism carbon emissions
grey Prediction Model
tourism consumption stripping factor