The rapid development of the tourism industry has been accompanied by an increase in CO2 emissions and has a certain degree of impact on climate change. This study adopted the bottom-up approach to estimate the spatiotemporal change of CO2 emissions of the tourism industry in China and its 31 provinces over the period 2000–2015. In addition, the decoupling index was applied to analyze the decoupling effects between tourism-related CO2 emissions and tourism economy from 2000 to 2015. The results showed that the total CO2 emissions of the tourism industry rose from 37.95 Mt in 2000 to 100.98 Mt in 2015 with an average annual growth rate of 7.1%. The highest CO2 emissions from the tourism industry occurred in eastern coastal China, whereas the least CO2 emissions were in the west of China. Additionally, the decoupling of CO2 emissions from economic growth in China’s tourism industry had mainly gone through the alternations of negative decoupling and weak decoupling. The decoupling states in most of the Chinese provinces were desirable during the study period. This study may serve as a scientific reference regarding decision-making in the sustainable development of the tourism industry in China.
As one of the largest economic sectors in the world, the tourism industry plays an important role in creating jobs, driving exports, and generating prosperity across the world. According to the WTTC’s report, the total contribution of travel and tourism to the global economy was USD7.61 trillion in 2016, rising to a total of 10.2% of the world’s GDP. The travel and tourism sector supported 284 million people in employment, equivalent to 1 in 11 jobs on the planet [
In China, the tourism industry has gained high-speed and unprecedented development since the reform and opening up. Through thirty years of development, China’s tourism revenue has jumped to the second place in the world in 2015. China has become the world’s largest consumer of outbound tourism for many years and contributes more than 13% to the global tourism revenue. The statistics from China Tourism Academy indicated that, during the year 2016, the number of domestic and inbound tourists in China reached 4.58 billion person-times, and the total domestic and international income from the tourism industry approached CNY4.69 trillion, accounting for 6.3% of the country’s GDP [
Accordingly, Chinese scholars have paid more attention to CO2 emissions from the tourism industry. Recent research methods to estimate tourism-related CO2 emissions include life cycle assessment [
In China, the development level of the tourism industry varies from region to region. It is necessary to clarify the current situation and regional differences of tourism-related CO2 emissions, which plays an important role not only in promoting energy saving and emission reduction in the whole tourism industry, but also in improving the pertinence and operability of carbon reduction policies and measures. In view of the importance of estimating spatiotemporal changes of CO2 emission of the tourism industry and its decoupling effects as well as the shortage of related research in China, this study served as a preliminary attempt to address this gap in such studies. This paper revealed spatiotemporal dynamics of CO2 emissions of the tourism industry from 2000 to 2015 and examined the occurrence of decoupling between the growth rates in CO2 emissions and economic growth in the tourism industry in China and its 31 provinces during 2000–2015 and proposed some suggestions for the tourism industry to mitigate climate change and low-carbon development. The purpose of this paper was to provide reference for the formulation of CO2 emission reduction strategies that will help the tourism industry adapt to climate change. The remainder of this paper was organized as follows. Section
Previous studies have shown that CO2 emissions of the tourism industry were mainly from tourism transport, tourism accommodation, and tourist activities [
Originally derived from physics, decoupling presents the separation and independent operation of two previously linked factors [
In order to distinguish the decoupling state, Tapio defined eight logical possibilities [ Strong decoupling: it represents the case when the change rate of tourism-related CO2 emissions is negative and that of the tourism economy is positive, and the relationship is optimal. Weak decoupling: it represents the case when the growth rate of tourism-related CO2 emissions is less than that of the tourism economy, and the relationship is desirable. Negative decoupling: it represents the case when the growth rate of tourism-related CO2 emissions is greater than that of the tourism economy. Recessive decoupling: it represents the case when the decline rate of tourism-related CO2 emissions is greater than that of the tourism economy. Weak negative decoupling: it represents the case when the decline rate of tourism-related CO2 emissions is less than that of the tourism economy. Strong negative decoupling: it represents the case when the growth rate of tourism-related CO2 emissions is positive and that of the tourism economy is negative, and the relationship is the most unfavorable.
Decoupling states on CO2 emission from economic growth in the tourism industry.
Decoupling state | Relationship between tourism-related CO2 emissions and tourism economy | |
---|---|---|
| Strong decoupling | |
Weak decoupling | | |
Negative decoupling | | |
Recessive decoupling | | |
Weak negative decoupling | | |
Strong negative decoupling | |
The research period in this study ranged from 2000 to 2015. All statistical data were collected from China Statistical Yearbook series for the period 2001–2016, the Yearbook of China Tourism Statistics series for the period 2001–2016, Tourism Sample Survey Information series for the period 2001–2016, and the relevant statistical yearbooks of the 31 Chinese provinces (autonomous regions and municipalities) [
Some parameters were obtained based on a full reference of the previous empirical studies. For tourism transportation, according to the
Figure
Total CO2 emission and its shares of the tourism industry in China during 2000–2015.
As shown in Figure
Figure
CO2 emissions and average growth rates of the tourism industry for the 31 Chinese provinces in 2000 and 2015.
The average growth rates of the 31 provinces varied from one another even though the emissions of all provinces in 2015 are higher than those in 2000 (Figure
Table
The decoupling state in China for the period 2000–2015.
| | | Decoupling state | |
---|---|---|---|---|
2000-2001 | 11.03 | 8.34 | 1.32 | Negative decoupling |
2001-2002 | 10.09 | 9.13 | 1.11 | Negative decoupling |
2002-2003 | 1.28 | 10.04 | 0.13 | Weak decoupling |
2003-2004 | 18.52 | 10.11 | 1.83 | Negative decoupling |
2004-2005 | 8.22 | 11.40 | 0.72 | Weak decoupling |
2005-2006 | 10.47 | 12.72 | 0.82 | Weak decoupling |
2006-2007 | 13.08 | 14.23 | 0.92 | Weak decoupling |
2007-2008 | 5.58 | 9.65 | 0.58 | Weak decoupling |
2008-2009 | 8.96 | 9.40 | 0.95 | Weak decoupling |
2009-2010 | 10.28 | 10.64 | 0.97 | Weak decoupling |
2010-2011 | 11.23 | 9.54 | 1.18 | Negative decoupling |
2011-2012 | 8.88 | 7.86 | 1.13 | Negative decoupling |
2012-2013 | −19.95 | 7.76 | −2.57 | Strong decoupling |
2013-2014 | 3.81 | 7.30 | 0.52 | Weak decoupling |
2014-2015 | 5.04 | 6.91 | 0.73 | Weak decoupling |
The decoupling state for the tourism industry of the 31 provinces of China from 2000 to 2015 is shown in Figure
The decoupling index of the 31 provinces of China from 2000 to 2015.
Because the tourism industry rapidly expands and has high relevance with other industries, there are huge amounts of CO2 emissions from the tourism industry. Therefore, the negative influence of the tourism development on climate change and ecological environment cannot be ignored. Since the adoption of a strategy of reform and opening up in China, the tourism industry has experienced a remarkable growth and has become an important sector of the Chinese economy. Economic growth in tourism industry was accompanied by increasing CO2 emission levels. In China, the number of tourists increased from 0.79 billion in 2000 to 4.13 billion in 2015. In addition, the total tourism revenue reached CNY4.13 trillion in 2015, which was further improved from CNY0.45 trillion in 2000. The rapid increase of tourists brought about a large amount of carbon dioxide in the process of travel by choosing different types of transportation, accommodations, and activities. At the provincial level, the highest CO2 emissions from the tourism industry occurred in eastern coastal China such as Guangdong, Beijing, Shanghai, Shandong, Zhejiang, and Jiangsu. Abounding in tourism resources, these regions’ tourism industry was highly developed, which attracted a large number of domestic and foreign tourists. The least carbon dioxide emissions were in the west of China, consisting of Tibet, Qinghai, and Ningxia. In these areas, the tourism industry was on the rise along with the improvement of transport facilities and enhancement of reception capacity. Especially in Tibet, the opening of Qinghai-Tibet railway has attracted many tourists from around the world since 2006, which caused the highest average growth rates of CO2 emissions from tourism industry among all provinces.
This study primarily showed an understanding of spatiotemporal change of CO2 emissions from the tourism industry in China. More importantly, as an exploratory study, the findings discovered dynamic change in the relationship between CO2 emissions and economic growth of the tourism industry. At the national level, the trend of weak decoupling occurred for 9 years, and negative decoupling appeared for 5 years during the period 2000–2015. Furthermore, the average value of decoupling index was 0.69 over the study period, which indicated that tourism economy presented weak decoupling as a whole. In addition, viewed from the decoupling index of various provinces, negative decoupling mainly occurred in the most developed tourism areas and quickly developing tourism regions. The reason for negative decoupling may be attributed to the percentage change of tourism-related CO2 emission which was higher than that of tourism economy. Hence, these provinces should take steps to curb tourism-related CO2 emissions while ensuring the long-term stable growth of tourism economy in the future development.
The tourism industry is strongly related to other industries. It is very complicated to determine CO2 emissions of the tourism industry due to the lack of complete statistics. Owing to the restriction of analysis conditions, the study on the calculation of CO2 emissions of tourism transport, tourism accommodation, and tourist activities is still to be perfected. For example, some parameters were selected by referring to other scholars’ research results. An in-depth investigation of the coefficients will further improve the accuracy of the estimates. This paper is a rough relative estimate of CO2 emissions from the tourism industry in China, which can reflect the time change trend and regional differences to a certain extent. In addition, the study period is from 2000 to 2015. During this period, new energy and low-carbon technologies have been used in transport, hotels, and scenic spots, which can cause per-unit parameters of carbon emissions to decrease. But these parameters are not fast enough to deviate greatly from the total amount and the estimations [
This study calculated the spatiotemporal change of CO2 emissions of the tourism industry based on a bottom-up approach from 2000 to 2015. Then, the relationship between CO2 emission and economic growth in the tourism industry was analyzed by the decoupling index. The conclusions were as follows.
(1) At the national level, the total CO2 emissions of the tourism industry increased from 37.95 Mt in 2000 to 100.98 Mt in 2015 with an average annual growth rate of 7.1%. The results also showed that CO2 emissions of the tourism industry in China were dominated by tourism transport, which accounts for over 83% of total CO2 emissions. At the provincial level, the highest CO2 emissions from the tourism industry occurred in eastern coastal China such as Guangdong, Beijing, Shanghai, Shandong, Zhejiang, and Jiangsu. The least carbon dioxide emissions were in the west of China, consisting of Tibet, Qinghai, and Ningxia.
(2) From 2000 to 2015, the decoupling of CO2 emissions from economic growth in the tourism industry mainly experienced the alternations of negative decoupling and weak decoupling. By examining the historical evolution of decoupling analysis during 2000–2015, this study can obtain the fact that tourism economy grew faster than tourism-related CO2 emissions in China. Generally speaking, the decoupling states of CO2 emissions from economic growth in the tourism industry in the 31 Chinese provinces were desirable, except for Shanghai, Tibet, and Beijing.
(3) Future studies should pay more attention to the changes of CO2 emissions from the tourism industry accompanied by the broad application of the energy-saving technology. Some key parameters demand more accurate findings and further investigations. Furthermore, comparative studies using different estimating methods, such as life cycle assessment, carbon footprint, tourist consuming minus coefficient, and input-output method, can give more valuable information of the spatiotemporal change of tourism-related CO2 emissions in China.
According to the above results, this study puts forward some suggestions in order to slow down the impact of the tourism industry on climate change.
(1) Relevant tourism administrations should set up low-carbon tourism standards and action plans, give a systematic guarantee of policies funds and technology for low-carbon tourism development, strengthen the publicity and marketing efforts of green tourism and low-carbon tourism, expand international exchanges and cooperation, and introduce an international advanced management model of low-carbon tourism.
(2) Tourism enterprises should supply low-carbon routes and products. As the guider of low-carbon tourism, travel agencies can design low-carbon routes and methods depending on vast forests, lakes, and wetlands. Tourism attraction should build the closed-loop feedback cycle process of “resource-product-recycling-resource” in the process of tourism resources development and tourism activities. Tourism traffic should improve the energy efficiency, optimize the energy structure, demand, and supply, and actively explore the application of new clean energy [
(3) Tourists with low-carbon demand will lead to low-carbon supply in tourism. Tourists should develop strong low-carbon and environmental awareness and then shift to actual action. Green and low-carbon behaviors should run through the entire travel process, such as catering, lodging, transportation, sightseeing, shopping, and entertainment, in order to really implement the consumption patterns of low-carbon tourism [
(4) Policy measures of low-carbon tourism should be formulated considering the social and economic development degree and tourism resources endowment of different provinces. The economically developed eastern China should further promote the transformation and upgrading of the tourism industry, increase investment and R&D efforts in energy saving and emission reduction technology, and improve the energy efficiency and optimize the energy structure of the tourism industry by means of science and technology. The central and western regions of China should improve the energy efficiency of the tourism industry, reduce the carbon intensity of the tourism industry, and vigorously develop clean energy, such as wind energy, solar energy, and biomass energy. In addition, clean development mechanisms or cooperation projects, such as carbon compensation, carbon neutralization, and carbon trading, can also be carried out among different provinces.
The authors declare that they have no conflicts of interest.
This work was supported by the China Postdoctoral Science Foundation (2016M600257), Postdoctoral Program of Heilongjiang Province (LBH-Z16093), Projects of Philosophy and Social Sciences of Heilongjiang Province (16JYE03, 14E012), Doctoral and Postdoctoral Research Projects of Harbin University of Commerce (2016BS05, 2017BSH014), and Research Projects of Harbin University of Commerce (2016QN028, 17XN086).