基于替代式自下而上法的区域旅游交通碳排放测度

区域旅游交通碳排放测度是分解旅游业减碳任务的一个难题。在剖析替代式自下而上法机理的基础上,以长三角为例,依托归纳法和变异系数法,尝试从人均GDP、人均消费水平和人均运输线路长度三方面测算出游距离,采取以实地调研数据为主、辅之以Mus TT模型法拟定各旅游交通方式的距离比例,立足区情确定碳排放系数,并以区域输入和输出的双向旅游流的人次比值法则对替代结果进行还原调整。研究表明:(1)2011年,长三角旅游交通碳排放总量为8.32 Mt,其中江苏省、浙江省和上海市分别为3.23、2.98 Mt和2.11 Mt;(2)飞机和自驾车共占排放量的71.64%,较明显低于世界平均比例,二者是降低旅游交通碳排放的关键;旅游公共交通的碳排放比例具有远高于发达国家甚至全球平均水平的"中国式"烙印;由高碳排放系数的旅游交通方式向低碳排放系数甚至零碳排放系数的转变,是旅游交通减排的基本方向。

Carbon dioxide emissions from regional tourism transport: a substitutional bottom-up analysis

Global climate change is one of the most pressing issues in today''s world and all countries are concerned with reducing carbon dioxide emissions. The tourism industry is highly sensitive to the impacts of climate change and global warming, as good weather is a high priority for tourists. Carbon dioxide emissions from tourism transport have to be monitored to enable sustainable tourism development in the 21st century, particularly as fossil-fuel energy sources are becoming scarce. Assessing carbon dioxide emissions from regional tourism transport is difficult but these data are needed to implement effective protocols to reduce emissions. We use the substitutional bottom-up analysis method to calculate the carbon dioxide emissions from tourism transport in the the Yangtze River Delta area. This analysis method is used for the first time. Based on a region''s per capita GDP, per capita income and transport route distance per vehicle, we calculated that the daily tourism distances per person in Jiangsu Province, Zhejaing Province, and Shanghai were 3.43, 3.61 and 5.12 km in 2011, respectively. Based on on-the-spot data questionnaires and public transport data as well as tourism data (MusTT model), we calculated that the major tourism transport modes in the Yangtze River Delta area in 2011 were air (12.98%), train (14.60%), coach (49.88%), and car (16.84%). The transport coefficients of carbon dioxide emissions resulting from air, train, coach, and car travel were 121, 9, 28 and 76 g/pkm, respectively. Our results were adjusted to account for tourists that came from other provinces to the destination province vs destination province tourists who traveled to other provinces. We conclude that: (1) Carbon dioxide emissions related to tourism transport were 8.32 Mt (Jiangsu Province, Zhejiang Province and Shanghai were 46.15, 32.29 and 21.56%, respectively). The CO₂ emissions per trip in these three areas were 7.85, 8.69 and 9.14 kg, respectively. (2) The CO₂ emissions from air, train, coach, and car travel were 3.29, 0.28, 1.97, and 2.67 Mt, respectively. The total emissions from air and car travel were 5.96 Mt (71.64%). This percentage, which is lower than the world''s average value, indicates that emissions from air and car transport in the tourism sector are the main contributions to carbon dioxide emissions in China. The percentage of tourists using public transport (train and coach) was higher than the world''s average. Our results indicate that Chinese tourists prefer to travel by train and coach. We surmise that the overall transition of energy saving and carbon dioxide emission reduction resulting from tourism transport has to be reduced from high coefficients to low or even zero coefficients. Considering that the numbers of inbound tourists from neighboring provinces are similar, the results may converge. Our results indicate that tourism catchment area is an important factor and this needs to be balanced with convenient transport links, residents'' tourism preferences, and the distribution of tourism destinations in each province.