江苏省区域旅游业碳排放测度及其因素分解

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陶玉国, 黄震方, 吴丽敏, 余凤龙, 王坤. 江苏省区域旅游业碳排放测度及其因素分解. 69(10): 1438-1448
TAO Yuguo, HUANG Zhenfang, WU Limin, YU Fenglong, WANG Kun. Measuring carbon dioxide emissions for regional tourism and its factor decomposition:A case study of Jiangsu province. Acte Geographica Sinica, 69(10): 1438-1448 复制到剪切板

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江苏省区域旅游业碳排放测度及其因素分解

陶玉国^1,², 黄震方¹, 吴丽敏¹, 余凤龙¹, 王坤¹

1. 南京师范大学地理科学学院, 南京 210023

2. 江苏师范大学历史文化与旅游学院, 徐州 221116

黄震方 (1963-), 江苏扬中人, 教授, 博士生导师, 中国地理学会会员 (S110002383M), 主要从事文化旅游、生态旅游研究。E-mail: zhfh@263.net

作者简介：陶玉国 (1976-), 湖南耒阳人, 副教授, 博士生, 硕士生导师, 主要从事低碳旅游、旅游地理研究。E-mail: taoyuguo123@163.com

基金:国家自然科学基金项目 (41271149); 教育部人文社会科学研究青年基金项目 (12YJC790175); 江苏高校优势学科建设工程项目

摘要

区域旅游业碳排放测度是分解旅游业减碳任务的需要。依托1997年、2002年和2007年的投入产出表和旅游终端收入,以江苏省为案例地,测度了旅游业各部门包括直接和间接碳排放的旅游业碳排放总量,并利用LMDI分解了影响因素的作用机理。结果显示,旅游业碳排放总量增长较快,较均衡分布于各部门,绝大多数来自间接层面;国内游客的碳排放总量显著高于入境游客,但前者的每人次碳排放远低于后者,也远低于发达国家,还低于发展中国家;省内各地区的碳排放总量和每人次碳排放均存在着显著差异;游客规模不断扩大和旅游消费水平持续提高是碳排放增长的主要驱动力,能源强度下降和能源结构调整则对碳排放具有一定的抑制作用,收入结构变动作用具有一定的阶段波动性特征。结果表明,旅游业减碳不仅需各部门共同分担,更依赖向其提供中间产品的关联产业的大力联动;国内游客是主要碳源,需要大量排放空间;游客每人次碳排放高的地区应承担较大的减排责任;降低能源利用强度和引导旅游消费低碳发展,是旅游业碳减排的主要方向。

关键词: 旅游业碳排放; 因素分解; 投入产出; LMDI; 江苏

Measuring carbon dioxide emissions for regional tourism and its factor decomposition:A case study of Jiangsu province

TAO Yuguo^1,², HUANG Zhenfang¹, WU Limin¹, YU Fenglong¹, WANG Kun¹

1. College of Geographical Science, Nanjing Normal University, Nanjing 210023, China

2. School of History Culture and Tourism, Jiangsu Normal University, Xuzhou 221116, Jiangsu, China

Fund:National Natural Science Foundation of China, No.41271149; The Youth Foundation of Humanities and Social Sciences of Ministry of Education of China, No.12YJC790175; A Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions

Abstract

Carbon dioxide emissions of tourism, as an important study issue in tourism industry in the 21st century, is a vital index reflecting its effects on environment change. It is difficult to measure the emissions of regional tourism. The article, taking Jiangsu province as a case, based on the input-output tables and tourism expenditures of 1997, 2002 and 2007, makes an analysis of the direct emissions and indirect emissions of tourism from food, accommodation, transportation, sightseeing, shopping, entertainment and postal services, and then explores the mechanism of influencing factors by Logarithmic Mean Divisia Index. The results are as follows: The total emissions of tourism industry in Jiangsu province in 1997, 2002 and 2007 were 22.57267 Mt, 33.90042 Mt and 62.43800 Mt, respectively, and the annual rate of growth was 10.71%. The indirect emissions account for about 73% of the total emissions. These percentages of food, accommodation, transportation, sightseeing, shopping and entertainment of total emissions in Jiangsu province are comparatively balanced, which, to some extent, reflects the character that the percentage of emissions from tourism sightseeing in China is higher than that of global level and national levels. The total emissions of domestic tourists are evidently higher than those of inbound tourists; however, the per-trip emissions of the inbound tourists are 4-7 times more than those of domestic tourists. There are significant differences of total emissions and per capita emissions among the cities within the province. Among the five factors affecting emissions of tourism industry, the increase of industry size and expenditure size are generally found to be principal drivers of emission growth, whereas the main factors restricting emissions are the decrease of energy intensity and the change of energy share. In addition, the effect of consumption structure shows fluctuation in different stages. These results imply the emission reduction of tourism industry not only needs the share responsibility from all tourism sectors but also strongly relies on the cooperation with related industries, which offer the intermediate goods for the consuming of tourism. Domestic tourists are the main carbon source, but still require more emission space due to low per capita emissions. The cities with higher per capita emissions should bear more obligation of emission reduction. Finally, it should be the main direction of emission reduction to reduce energy use intensity and develop low-carbon tourism behavior.

Keyword: carbon dioxide emissions of tourism; factor decomposition; input-output; LMDI; Jiangsu province

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1 引言

自工业革命以来, 环境问题一直为研究者所广泛关注^[1]。当前和未来一段时间, 该问题集中体现为全球气候变化, 而旅游业是全球气候变化的一个重要驱动因素。1986年, 关于二者关系的成果首次面世^[2]。从全球气候变化角度看, 如果旅游业碳排放仍保持较快的增长态势, 旅游业难以持续发展^{[3, 4]}。旅游业碳排放是衡量旅游业影响环境质量的一个重要指标, 也是21世纪旅游业人地关系研究的焦点问题之一。其包含旅游业直接碳排放和旅游业间接碳排放两种类型, 前者是指旅游系统直接消耗的能源所排放的二氧化碳, 后者是指旅游系统消费的关联产业中间产品的隐含碳排放。2000年, Gö ssling率先提出了系统测度旅游业碳排放的方法^[5]。随后, 这一论题逐渐被学术界所重视^{[6, 7, 8, 9, 10]}。到2008年, UNWTO等发布了研究报告《气候变化与旅游业：应对全球气候挑战》^[11], 将旅游业碳排放研究推向了高潮。

虽然对旅游业碳排放进行测度非常艰难^[11], 但近10多年来旅游业直接碳排放测度在多个空间尺度上已取得了可喜的进展。旅游业碳排放约占全球碳排放的5%^{[6, 11, 12]}。Nielsen等和石培华等分别探讨了瑞士和中国的旅游业碳排放^{[13, 14]}, 但二者测度口径相差较大, 难以进行国别间比较。夏威夷州22%的温室气体来自旅游业^[15], 但惠斯特镇高达65%^[10]。达沃斯镇的碳排放虽超过国内其他地方25%, 但旅游业对此并不负主要责任^[16]。旅游航空交通、星级饭店和水上摩托车分别是澎湖岛旅游交通、住宿和游览温室气体的主要承担者^[17]。与UNWTO等得出的旅游业碳源主要来自交通、住宿和游览结论的测度范畴相一致^[11], 已有主流研究的核算范围也集中于这三个部门, 而对旅游业的餐饮、购物、娱乐等其他部门则关注不够。中国国家或区域层面上的碳排放是否也集中于此三个部门?

近年来, 旅游业碳排放呈现出由考虑少数部门的直接测度转向从全部要素出发的直接与间接测度的趋势。依托自上而下法和自下而上法^[9]、生产法和支出法^[18]、投入产出法^[19]、延伸式旅游卫星记事方法^{[20, 21]}等计量手段, 以Becken为代表的研究者测算了新西兰^[9]、澳大利亚^[18]、罗马尼亚^[19]和威尔士^{[20, 21]}旅游业的直接和间接碳排放。国内学者仅刘洪涛等进行了类似研究^[22]。可见, 该领域研究虽取得了一定的进展, 但总体仍较薄弱, 不利于从整个产业及其相关产业的纵横视角来审视包含直接和间接碳排放的旅游业碳排放总量。

当前, 旅游业碳排放研究主要停留在测算阶段, 对其影响因素予以定量分析的成果尚不多见。Balež entis等探讨了空间布局、能源强度等因素对立陶宛乡村旅游业碳排放的作用^[23]。1997-2005年, 游客消费水平和能源结构对成都旅游业碳排放分别具有正负效应^[22], 但2010年二者对南岳作用截然相反^[24], 个中缘由可能在于地域与时间的不同。因此, 丰富研究案例和延长核算年限有助于探寻碳排放影响因素作用的普遍规律。减排责任的区域分解需要科学评价各地区的排放责任^[25], 国家战略层面上的旅游业节能减排任务也需要落实到地方场域。区域旅游业碳排放研究已成一个新的热点^[26]。因此, 研究包含所有部门的区域旅游业碳排放总量并分析其影响因素的作用机理, 是一个值得探究的命题, 以期丰富该领域研究的视角和方法, 为制定针对性较强的旅游业节能减排措施提供科学依据。

2 研究方法与数据来源

2.1 研究方法

2.1.1 旅游业直接碳排放和间接碳排放一个部门的直接能源强度可表示为该部门能源消费实物量和总投入的比值, 计算公式如下^[27]：

$\begin{matrix} e_{i}^{direct} = \frac{\sum_{j}^{=} E_{ij}}{X_{i}} \end{matrix}$ (1)

式中： $\begin{matrix} e_{i}^{direct} \end{matrix}$ 为i部门的直接能源强度 (吨标准煤/万元); E_ij为i部门对j种能源的实物消费量 (标准煤); X_i为i部门的总投入; m为能源种类。

旅游经济收入主要来自住宿、餐饮、交通、购物、娱乐、邮电通信和游览等7个部门 (其他旅游收入部分划归娱乐)。这些部门对应投入产出表中的住宿和餐饮业、交通运输及仓储业、批发和零售业、文化、体育和娱乐业、邮政业和其他服务业等部门。由于相同部门的经济活动所创造的收入, 需要使用的成本大致相同, 故可利用公式 (2) 测算旅游业i部门直接消耗的标准煤 ( $\begin{matrix} E_{i}^{ce} \end{matrix}$ )：

$\begin{matrix} E_{i}^{ce} = e_{i}^{direct} \times s_{i} \end{matrix}$ (2)

式中：s_i为旅游业i部门的终端总收入。

旅游业i部门直接消耗的j种能源 (E_ij) 可通过公式 (3) 测算：

$\begin{matrix} E_{ij} = \frac{(E_{i}^{ce} \times W_{ij})}{E_{j}^{cont}} \end{matrix}$ (3)

式中： $\begin{matrix} E_{i}^{ce} \end{matrix}$ 为旅游业i部门的标准煤; W_ij为能源平衡表中的i部门终端能源消费的j种能源折算的标准煤占i部门总标准煤的比例; $\begin{matrix} E_{j}^{cont} \end{matrix}$ 为j种能源的标准煤折算系数, 来自中国能源统计年鉴。

旅游业直接消耗的j种能源的碳排放可通过下式计算：

$\begin{matrix} C_{j}^{direct} = E_{j} \times C_{j}^{_{cont}} \end{matrix}$ (4)

式中：C^direct为旅游业直接碳排放; E_j为旅游业直接消耗的j种能源; $\begin{matrix} C_{j}^{_{cont}} \end{matrix}$ 为j种能源的碳排放系数 (转换因子), 来自IPCC。

旅游业直接碳排放 ( $\begin{matrix} C_{tot}^{direct} \end{matrix}$ ) 计算公式为：

$\begin{matrix} C_{tot}^{direct} = \sum_{i}^{=} \sum_{j}^{=} E_{ij} \times C_{j}^{_{cont}} \end{matrix}$ (5)

式中：E_ij为旅游业i部门直接消耗的j种能源。

完全能源强度 (e^tot) 是指生产单位最终产品或服务而导致的全部能源消费量, 即该单位产品或服务中所蕴含的能源量, 是直接能源强度与列昂惕夫逆矩阵的乘积。计算式为：

$\begin{matrix} e^{tot} = e^{direct} \times {(I - A)}^{- 1} \end{matrix}$ (6)

式中：A为投入产出直耗系数矩阵。(I - A)^-1为列昂惕夫逆矩阵。利用完全能源强度可测算旅游业碳排放总量 (C^tot), 而旅游业间接碳排放 (C^indirect) 是旅游业碳排放总量与直接碳排放的差, 计算公式如下：

$\begin{matrix} C^{indirect} = C_{}^{tot} - C_{}^{direct} \end{matrix}$ (7)

2.1.2 Kaya恒等式与碳排放影响因素LMDI分解 Kaya恒等式为日本能源经济学家Kaya于1989提出, 目的是为了判断人类活动对二氧化碳的影响水平^[28]。通过扩展, 该恒等式可用来分解旅游业碳排放的影响因素。公式如下：

$\begin{matrix} C^{tot} = \sum^{} \sum^{} (\frac{C_{ij}}{E_{ij}} ∙ \frac{E_{ij}}{E_{i}} ∙ \frac{E_{i}}{Y_{i}} ∙ \frac{Y_{i}}{Y} ∙ \frac{Y}{P} ∙ P) \end{matrix}$ (8)

式中：C^tot为旅游业碳排放总量; C_ij为旅游业i部门j种能源的碳排放总量; E_ij为旅游业i部门消耗的j种能源; E_i为旅游业i部门的能耗; Y_i为旅游业i部门的收入; Y为旅游总收入; P为游客总人次。

令 $\begin{matrix} f_{ij} = \frac{C_{ij}}{E_{ij}} \end{matrix}$ , $\begin{matrix} n_{ij} = \frac{E_{ij}}{E_{i}} \end{matrix}$ , $\begin{matrix} q_{i} = \frac{E_{i}}{Y_{i}} \end{matrix}$ , $\begin{matrix} r_{i} = \frac{Y {}_{i}}{Y} \end{matrix}$ , $\begin{matrix} g = \frac{Y}{P} \end{matrix}$ , $\begin{matrix} k = P \end{matrix}$ , (9)

则f_ij、n_ij、q_i、r_i、g和k分别表示碳排放系数效应、旅游能源结构效应、旅游能源强度效应、旅游收入结构效应、旅游消费水平效应和游客规模效应。本文运用迪氏对数指标分解法 (Logarithmic Mean Disivia Index, LMDI) 对碳排放影响因子进行分解。LMDI是一种完全的、不产生残差的分解方法, 是一种很好的研究碳排放变化机理的方法。

设基期旅游业碳排放总量为C⁰, T期总量为C^t, 可将旅游业碳排放总量变化量分解为：

$\begin{matrix} Δ C^{tot} = C^{T} - C^{0} = Δ C_{f_{ij}} + Δ C_{n_{ij}} + Δ C_{q_{i}} + Δ C_{r_{i}} + Δ C_{g} + Δ C_{k} \end{matrix}$ (10)

根据LMDI, 各分解因素贡献值的表达式分别为：

$\begin{matrix} Δ C_{f_{ij}} = \sum^{} \sum^{} (\frac{C_{ij}^{T} - C_{ij}^{0}}{In C_{ij}^{T} - In C_{ij}^{0}} \times In \frac{f_{ij}^{T}}{f_{ij}^{0}}) \end{matrix}$ (11)

$\begin{matrix} Δ C_{n_{ij}} = \sum^{} \sum^{} (\frac{C_{ij}^{T} - C_{ij}^{0}}{In C_{ij}^{T} - In C_{ij}^{0}} \times In \frac{n_{ij}^{T}}{n_{ij}^{0}}) \end{matrix}$ (12)

$\begin{matrix} Δ C_{t_{i}} = \sum^{} \sum^{} (\frac{C_{ij}^{T} - C_{ij}^{0}}{In C_{ij}^{T} - In C_{ij}^{0}} \times In \frac{q_{i}^{T}}{q_{i}^{0}}) \end{matrix}$ (13)

$\begin{matrix} Δ C_{r_{j}} = \sum^{} \sum^{} (\frac{C_{ij}^{T} - C_{ij}^{0}}{In C_{ij}^{T} - In C_{ij}^{0}} \times In \frac{r_{i}^{T}}{r_{i}^{0}}) \end{matrix}$ (14)

$\begin{matrix} Δ C_{g} = \sum^{} \sum^{} (\frac{C_{ij}^{T} - C_{ij}^{0}}{In C_{ij}^{T} - In C_{ij}^{0}} \times In \frac{g_{}^{T}}{g_{}^{0}}) \end{matrix}$ (15)

$\begin{matrix} Δ C_{k} = \sum^{} \sum^{} (\frac{C_{ij}^{T} - C_{ij}^{0}}{In C_{ij}^{T} - In C_{ij}^{0}} \times In \frac{k_{}^{T}}{k_{}^{0}}) \end{matrix}$ (16)

由于在实际应用中各类能源的碳排放系数通常取常量, 因此, $\begin{matrix} Δ C_{f_{j}} \end{matrix}$ 始终等于0, 可以不作为考量因素。公式 (10) 可简化为：

$\begin{matrix} Δ C_{tot} = C^{T} - C^{0} = Δ C_{n_{ij}} + Δ C_{q_{i}} + Δ C_{r_{i}} + Δ C_{g} + Δ C_{k} \end{matrix}$ (17)

2.2 数据来源

由于旅游业能耗没有纳入传统的国家统计体系, 因此, 各国无法提供关于旅游业能耗或碳排放的全面统计数据^{[9, 11]}。国家统计局基于大规模调查数据编制了1992年124部门、1997年124部门、2002年124部门、2007年135部门的投入产出表, 为确定旅游能源强度系数提供了基础数据。受江苏省旅游统计数据的限制, 本文测度时间选取1997、2002和2007年。2007年的强度系数来自陆旸^[29], 在此基础上, 根据刘洪涛等^{[27, 30]}推算前两年。江苏省及其地级市的旅游经济收入和游客人次来自江苏统计年鉴及新中国55年统计资料汇编, 而入境游客和国内游客的旅游花费构成来自江苏旅游统计年度报告。旅游业各部门每种能源的消耗比例, 通过中国能源统计年鉴中的江苏能源平衡表中的各相关部门终端能源消费进行推算。旅游者低碳旅游消费意愿和行为方面的数据, 来自项目组于2012年9月-2013年5月对江苏省911户居民出游的实地调研。

3 江苏省旅游业碳排放测度及其内部差异

3.1 旅游业直接碳排放

1997年、2002年和2007年, 江苏省旅游业直接碳排放分别为5.53568 Mt、9.46032 Mt和18.18489 Mt (表1), 增长较快, 其中, 2002年比1997年增长1.71倍, 2007年比2002年增长1.92倍, 2007年比1997年增长3.29倍。随时间推移, 餐饮、住宿和旅游交通所占比重均有所下降, 而游览、购物和娱乐的比例则有所上升, 旅游消费的转型升级在旅游业直接排放结构的演变上得到了一定的体现。在3个年份的旅游业吃、住、行、游、购、娱六大部门的排放比例均值中, 最高者为交通, 最低者为娱乐, 交通、购物和住宿是三个主要部门, 分别占58.66%、12.21%和10.47%, 合占81.34%。这与UNWOT等得出的全球旅游业直接碳排放主要来自交通 (71%)、住宿 (24%) 和游览 (5%) 的结论^[11]基本一致, 但又有一定的差异, 表现如下：首先, 主要部门并不完全相同, 购物取代了游览, 游客对购物的偏好在碳排放上得以体现。其次, 将三个主要部门的碳排放作为一个整体, 交通分摊的责任基本不变, 住宿责任则有所降低。第三, 三大核心部门之外的其余4个部门合占19.66%的比例, 这些部门也是旅游业节能减排不容忽视的要素。

表1 1997年、2002年和2007年江苏省旅游业直接碳排放 Tab. 1 The direct CO₂ emissions of tourism in Jiangsu province in 1997, 2002 and 2007 (Mt)

鉴于国内外代表性成果的旅游业直接碳排放核算口径主要涉及交通、住宿和游览3部门^{[6, 7, 8, 9, 11, 12, 13, 14, 15, 16, 19, 22]} (图1; Peeters等^[12]不包括一日游), 以此推算, 与图1中多数年份较为靠近的2007年江苏三者比例分别为77%、13%和10%。可见, 相对其他国家和地区, 江苏旅游交通碳排放所占比重总体上适中, 但住宿和游览则分别偏低和偏高, 其中, 交通略高于国内研究^{[14, 17, 22]}, 住宿与澎湖岛^[17]较为相似, 而游览与澎湖岛^[17]、成都^[22]相接近。差异产生的背后原因既与测度方法可能不同有所关联 (如Nielsen等得出自下而上法的测度结果比自上而下法结果低14%^[13]), 也与对象的旅游发展态势不无关系, 还与其能源结构密不可分。补充一点, 因全球^{[6, 11, 12]}与中国^[14]的游览碳排放测度均采用新西兰的较低的系数 (70%为水电)^[9], 故其比重可能偏低。

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	图1 部分国家和地区旅游业直接碳排放比例Fig. 1 The percentage of carbon dioxide emissions of tourism sections in some countries and regions

3.2 旅游业间接碳排放和碳排放总量

1997年、2002年和2007年, 江苏省旅游业间接碳排放分别为17.03698 Mt、24.44011 Mt和44.25312 Mt (表2), 类似直接碳排放其增长较快, 其中, 2002年比1997年增长1.43倍, 2007年比2002年增长1.81倍, 2007年比1997年增长2.60倍。旅游消费的转型升级在旅游业间接排放结构的演变规律上也得到了一定的体现。餐饮、住宿、交通、游览、购物、娱乐和其他部门的3年比例均值分别为15.23%、16.43%、18.60%、13.96%、18.76%、9.34%和7.69%, 分配相对比较均衡, 购物最高, 交通紧随其后, 其他部门最低, 间接部门排放结构与直接结构差异显著。

表2 1997年、2002年和2007年江苏省旅游业间接碳排放 Tab. 2 The indirect CO₂ emissions of tourism in Jiangsu province in 1997, 2002 and 2007 (Mt)

3个年份碳排放总量分别为22.57267 Mt、33.90042 Mt和62.43800 Mt (表3), 2007年比1997年增长2.77倍。部门排放由高到低依次为交通 (29.42%)、购物 (16.98%)、住宿 (14.85%)、餐饮 (13.77%)、游览 (11.26%)、娱乐 (7.54%) 和其他 (6.18%)。旅游业碳源并不集中于少数几个部门, 各部门对碳排放均负有较大的责任, 因此, 旅游业节能减排不仅需考虑交通、住宿和游览等3个公认部门, 更需从全局视角考虑各部门的共同分担。间接排放占碳排放总量的均值为72.82%, 这一般要显著高于国外, 如威尔士^{[20, 21]}、新西兰^[9]和澳大利亚^[18]分别为42%、64%、46%和52%。其原因与中国许多重要行业对煤炭和火电的依赖程度依然很高^[31]关联很大。进一步的解释是, 基于火电、水电等能源形成的电力碳排放系数具有很强的国别性和区域性, 如根据美国能源部的温室气体研究报告和中国省级温室气体清单编制指南, 消耗等量电力所排放的二氧化碳, 中国是欧洲OECD的2.2倍, 江苏分别是新西兰和瑞士的5.8倍和42.2倍, 这必将拉升间接碳排放的比例。有鉴于此, 旅游业碳减排不仅需关注产业自身, 更依赖向其提供中间产品的关联部门的大力联动。

表3 1997年、2002年和2007年江苏省旅游业碳排放总量 Tab. 3 The total CO₂ emissions of tourism in Jiangsu province in 1997, 2002 and 2007 (Mt)

3.3 入境和国内游客群体碳排放

1997年、2002年和2007年, 国内游客和入境游客的碳排放及比值见表4。国内游客是旅游业碳源的主要载体, 3个年份国内游客碳排放总量占全体游客总量的均值为89.93%。比值符合旅游业碳排放大多来自国内游客的结论^[11], 但由于中国国土面积广大、国内游客众多等原因, 该比值一般高于其他国家, 如新西兰为72%^[9]。

表4 1997年、2002年和2007年江苏省国内和入境游客碳排放 Tab. 4 The CO₂ emissions of domestic and inbound tourists in Jiangsu province in 1997, 2002 and 2007 (Mt)

江苏省全体、入境和国内游客的每人次碳排放见表5。可看出, 游客每人次碳排放总体上呈现出随时间推移而下降的态势。下降的一个可能的原因是期间游客人数增长速度大于旅游收入增长速度。3个年份入境游客每人次碳排放总量分别是国内总量的6.89倍、4.86倍和5.40倍, 即前者是后者的4~7倍, 二者呈现一种趋同态势, 这在某种程度上也是同期国内外经济发展形态的一个表征。

从表5还可看出, 江苏省全体游客每人次碳排放总量均远高于2003年威尔士的0.02 t^[21], 这反映了该值在不同地区可能相差悬殊, 因此, 将其与全球平均值进行比较更具一般意义。以交通、住宿和游览三个部门作为直接测度的口径, UNWTO等的报告显示, 2005年, 全球游客每人次碳排放为0.250 t, 其中, 发达国家入境游客为0.678 t, 国内游客为0.258 t, 而发展中国家国内游客为0.074 t^[11]。采用相同口径, 时间距离较近的2007年的江苏全体游客每人次碳排放为0.053 t, 其中, 入境游客为0.387 t, 国内游客为0.046 t。对比发现, 江苏全体游客每人次碳排放约为全球的21.26%, 其中, 入境游客约为发达国家的57.14%, 国内游客仅为发达国家的17.73%, 甚至只达发展中国家的61.83%。国内游客每人次碳排放较低的事实, 说明了该群体尚需要大量的排放空间, 以保障其享受旅游福利。这正如有关研究^[32]所指出：高收入国家对碳排放的需求增量较为有限, 而低收入国家尚需要大量的排放空间, 来实现其人文发展的潜力。

表5 1997年、2002年和2007年江苏省不同游客群体每人次碳排放 Tab. 5 The per capita CO₂ emissions of different tourists in Jiangsu province in 1997, 2002 and 2007 (t)

3.4 地级市旅游业碳排放

通过对比中国、江苏及部分省区的旅游业各部门的花费构成发现, 其在同一时期不同地方虽有所出入, 但相对较小。在假设各地级市花费结构相同的前提下, 可估算各地级市的旅游业碳排放。2002年13个地级市旅游业碳排放总量由高到低依次为南京、苏州、无锡、常州、镇江、扬州、南通、徐州、连云港、盐城、泰州、淮安和宿迁 (图2; 因1997年各市的相关旅游统计数据不完全, 该年不予考虑), 其中, 前三市合占61.06%, 苏南、苏中和苏北分别占73.52%、13.07%和13.41%; 2007年总量由高到低依次为苏州、南京、无锡、常州、镇江、扬州、徐州、南通、连云港、泰州、淮安、盐城和宿迁, 其中, 前三市合占60.29%, 苏南、苏中和苏北分别占73.99%、12.62%和13.39%。各地级市碳排放的次序和所占比例, 随时间推移变化不大, 但排放省内分异显著, 主要集中于苏南或苏州、南京和无锡三市。

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	图2 2002年和2007年江苏省各地级市旅游业碳排放总量Fig. 2 The total CO₂ emissions of tourism of cities in Jiangsu province in 2002 and 2007 (Mt)

在游客每人次碳排放总量方面, 2002年南京、无锡、苏州、南通、常州、镇江、泰州、扬州、连云港、徐州、盐城、宿迁和淮安依次为0.37、0.36、0.35、0.33、0.33、0.31、0.30、0.30、0.29、0.28、0.27、0.21和0.20 (单位：t), 南京是淮安的1.86倍, 全组数据变异系数为0.17; 2007年无锡、苏州、南京、常州、镇江、南通、连云港、扬州、泰州、徐州、淮安、盐城和宿迁依次为0.29、0.29、0.29、0.25、0.25、0.25、0.24、0.24、0.22、0.22、0.19、0.19和0.15, 无锡是宿迁的1.96倍, 全组数据变异系数为0.18。随时间推移, 地级市游客每人次碳排放有所降低, 省内分异比较显著且有所扩大。

4 影响因素分解

根据公式 (8)~(15) 可计算不同时段各分解因素对碳排放总量的变化值及贡献值。从图3可看出, 游客规模和游客消费水平对碳排放增长表现为正效应, 能源强度与能源结构表现为负效应, 而收入结构效应则表现为阶段性波动。1997-2002年和2002-2007年正效应对负效应的数值比分别为2.90和4.53, 说明碳排放的增长作用明显大于抑制作用, 如果不采取切实可行的措施, 未来碳排放仍将继续增长。

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	图3 1997年、2002年和2007年江苏省旅游业碳排放总量变化LMDI分解结果Fig. 3 The factor decomposition of total CO₂ emissions of tourism in Jiangsu province in 1997, 2002 and 2007

4.1 游客规模效应

游客规模不断扩大是江苏省旅游业碳排放较快增长的主要驱动力。两个时间段中, 游客规模对碳排放增长的贡献值分别为70.86% (12.26 Mt) 和72.95% (26.72 Mt)。来苏游客人数由1997年的5682.71万人次增长到2007年的23711.1万人次, 增长了4.17倍, 年均增长率达15.36%。游客绝对数量的快速增长需要与之相对应的能源消费的增长, 成为满足游客旅游需求的必要条件, 同期碳排放的持续增长由此可以得到部分解释。如果寄希望于通过减少游客数量来实现碳减排, 这将以牺牲旅游机会为代价, 并不是理想的解决之道。

4.2 消费水平效应

旅游消费水平持续提高对碳排放增长表现出较大的驱动作用。这与相关研究成果比较吻合^{[22, 24]}。两个时段中, 消费水平对碳排放总量累积增量分别有29.14%和23.38%的驱动贡献。人均旅游花费由1997年的700元增长到2007年的1169元, 年均增长率为5.25%, 期间虽受到了亚洲金融危机等突发事件的影响, 但总体仍增长较快。旅游业碳锁定是由技术与制度共同演进造成的递增报酬所引起的, 但在没有制度约束或激励的前提下, 旅游者、供应商等并不愿意减少这种报酬, 碳解锁难以推进。这种“ 高碳” 的旅游消费方式产生了大量碳排放。

4.3 能源强度效应

旅游能源强度下降是促使碳排放降低的主要因素。旅游能源强度是单位旅游收入所消耗的能源总量, 反映了能源经济活动的整体效率。1997年、2002年和2007年江苏旅游能源强度分别为0.68、0.53和0.26 (单位：t标准煤/万元)。两个时段中, 能源强度对碳排放减缓的贡献值分别为88.26%和92.11%。相对于工业而言, 旅游业是一个低污染、低能耗的产业, 单位旅游收入产生的碳排放量也较小, 能源使用效率提升的空间较大。国内外一些研究也证实了能源强度对碳减排的重要性, 如在2004-2008年期间, 其每年都对立陶宛乡村旅游业碳排放的增长起很大促进作用, 但2009-2010年则是碳排放降低的关键因素^[23]。

4.4 能源结构效应

相对于能源强度, 旅游能源结构调整对碳排放的负效应大幅减小。两个时段中, 其贡献值分别为9.58%和7.89%。虽然旅游能源结构在不同阶段有所变动, 如2002年煤折算成标准煤后的比例比1997年减少了27%, 但受其他因素效应的影响, 其对碳排放的影响作用仍较小。旅游业主要碳源来自间接层面, 而中国许多重要行业对煤炭和火电的依赖程度依然很高^[31], 这也印证了现阶段旅游业通过改变能源结构减排的空间不大的结论。

4.5 旅游收入结构效应

旅游收入结构变动对碳排放的影响作用微弱。两个时段结构变动分别累积引发了2.16%的碳排放降量和3.66%的碳排放增量, 表现出阶段波动效应特征。旅游收入结构随时间推移变动较小, 以江苏国内游客为例, 2002年餐饮、住宿、交通、游览、购物、娱乐、邮电通讯和其他所占百分比分别为18.47、19.52、16.3、9.4、24.2、5.25、1.28和5.58, 到2007年对应为18.01、17.13、17.01、10.61、25.8、6.8、1.11和3.53。相对于其他因素, 收入结构变动引发的碳排放变动较少, 但如果大力推动旅游消费向低碳转型, 提高负效应, 对旅游业碳解锁的顺利实现也具有一定的积极作用。

综上所述, 考虑到短期内游客规模不可能大幅降低, 降低能源利用强度和引导旅游消费向低碳发展, 是旅游业节能减排的两种主要手段。减排需能耗供求双方的利益相关者共同努力。降低能源利用强度的主要驱动力来自技术进步, 有效的技术减排措施是供应商采取清洁生产等技术, 提高能源利用效率。遗憾的是低碳技术被旅游商使用有限^[33]。虽然国家旅游局发布的《关于进一步推进旅游行业节能减排工作的指导意见》指明了各省区旅游业的节能减排目标和时间表, 减排刻不容缓, 但旅游消费现状与低碳要求仍有较大差距。项目组通过对江苏省911户居民的出游调查发现, 虽然87.16%的游客认为“ 非常应该” 或“ 应该” 减少旅游业的碳排放, 但仅32.16%的“ 非常自觉” 或“ 较自觉” 践行节能节水; 仅6.15%的“ 非常愿意” 通过减少旅游机会以减排, 41.60%的犹豫不决。因此, 建立制度性约束机制, 促使游客在吃、住、行、游、购、娱等环节低碳消费, 对整个产业节能减排意义重大。

5 结论与启示

(1) 江苏旅游业碳排放总量增长较快, 主要来自间接碳排放。2007年碳排放总量为62.43800 Mt, 比1997年增长2.8倍, 在各部门分配相对比较均衡。旅游业碳排放沿袭了旅游业关联性强的特征, 间接碳排放约占总量的73%, 该比例一般要显著高于国外。直接碳排放主要来自交通、购物和住宿三个部门, 与国外主流研究得出的结论基本一致但又有所不同。后续研究需进一步总结区域、区际间、国家的旅游业碳排放在直间接分配、部门分配等方面的一般性规律, 也有助于完善和修正本文的不足之处。

(2) 国内游客群体碳排放总量远高于入境游客, 但每人次碳排放截然相反。国内游客碳排放总量约占全体游客的90%, 是主要碳源。在游客每人次碳排放方面, 入境游客和国内游客总体上均呈随时间推移缓慢降低的态势, 但前者是后者的4~7倍; 与国外相比, 入境游客略高于发达国家的一半, 国内游客远低于发达国家也低于发展中国家。国外部分研究还探索了具有不同收入^[6]、旅游形式^[21]的游客群体碳排放, 国内研究在此方面亟需加强。

(3) 省内各地区的碳排放总量和游客每人次碳排放分异非常显著。旅游收入高的苏南是碳排放的主要来源区, 苏中和苏北基本持平, 苏州、南京和无锡三市约占全省的六成, 各地区游客每人次碳排放存在着显著的差异且在缓慢扩大。估算的地区碳排放结论基本可靠, 通过实地调查确定各地区的旅游花费结构有助于提高研究的准确性, 但实际操作难度很大。

(4) 游客规模不断扩大和消费水平持续提高分别是旅游业碳排放较快增长的主要和次要驱动力, 能源强度的负效应大于能源结构, 收入结构作用表现出一定的阶段波动性特征。这为探寻样区甚至全国旅游业碳排放影响因素作用的一般规律积累了一定的经验。丰富研究案例, 延长测算年限, 可更明晰区域间影响因素作用机理的异同性。

结果表明, 旅游业碳排放的增长作用明显大于抑制作用, 如果不采取切实可行的措施, 未来旅游业碳排放仍将继续较快增长; 旅游业的减碳不仅需要自身吃、住、行、游、购、娱等各部门共同分担, 更依赖向其提供中间产品的相关产业的大力联动; 国内游客每人次碳排放低, 需要大量排放空间, 以保障旅游福利的惠及; 游客每人次碳排放高的地区应承担较大的减排责任; 建立倡导低碳旅游消费的制度性约束机制, 是旅游业实现碳减排的重要保障, 而通过低碳技术以降低能源利用强度和优化能源结构, 是旅游业根本的碳解锁之道。

The authors have declared that no competing interests exist.

参考文献

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2002

38.597

0.0

... 1 引言自工业革命以来,环境问题一直为研究者所广泛关注^[1] ...

2013

0.0

... 1986年,关于二者关系的成果首次面世^[2] ...

2010

0.0

... 从全球气候变化角度看,如果旅游业碳排放仍保持较快的增长态势,旅游业难以持续发展^[3,4] ...

2011

0.0

... 从全球气候变化角度看,如果旅游业碳排放仍保持较快的增长态势,旅游业难以持续发展^[3,4] ...

2000

0.0

... ssling率先提出了系统测度旅游业碳排放的方法^[5] ...

2002

5.236

0.0

Gössling

Global environmental consequences of tourism.

Global Environmental Change, 2002, 12(4): 283-302.

Abstract In 2000, almost 700 million international tourist arrivals were counted worldwide. Even though a global activity of this scale can be assumed to have a substantial impact on the environment, its consequences have never been assessed and quantified. In this contribution, five major aspects of the leisure-related alteration of the environment are investigated: (1) the change of land cover and land use, (2) the use of energy and its associated impacts, (3) the exchange of biota over geographical barriers and the extinction of wild species, (4) the exchange and dispersion of diseases, and (5), a psychological consequence of travel, the changes in the perception and the understanding of the environment initiated by travel.

... 随后,这一论题逐渐被学术界所重视^[6,7,8,9,10] ...

... 旅游业碳排放约占全球碳排放的5%^{[6, 11,12]} ...

... 鉴于国内外代表性成果的旅游业直接碳排放核算口径主要涉及交通、住宿和游览3部门^{[6,7,8,9, 11,12,13,14,15,16, 19, 22]} (图1 ...

... 补充一点,因全球^{[6, 11,12]}与中国^[14]的游览碳排放测度均采用新西兰的较低的系数 (70%为水电)^[9],故其比重可能偏低 ...

... 国外部分研究还探索了具有不同收入^[6]、旅游形式^[21]的游客群体碳排放,国内研究在此方面亟需加强 ...

2002

2.855

0.0

... 随后,这一论题逐渐被学术界所重视^[6,7,8,9,10] ...

... 鉴于国内外代表性成果的旅游业直接碳排放核算口径主要涉及交通、住宿和游览3部门^{[6,7,8,9, 11,12,13,14,15,16, 19, 22]} (图1 ...

2005

2.855

0.0

... 随后,这一论题逐渐被学术界所重视^[6,7,8,9,10] ...

... 鉴于国内外代表性成果的旅游业直接碳排放核算口径主要涉及交通、住宿和游览3部门^{[6,7,8,9, 11,12,13,14,15,16, 19, 22]} (图1 ...

2006

0.0

... 随后,这一论题逐渐被学术界所重视^[6,7,8,9,10] ...

... 依托自上而下法和自下而上法^[9]、生产法和支出法^[18]、投入产出法^[19]、延伸式旅游卫星记事方法^[20,21]等计量手段,以Becken为代表的研究者测算了新西兰^[9]、澳大利亚^[18]、罗马尼亚^[19]和威尔士^[20,21]旅游业的直接和间接碳排放 ...

... 2 数据来源由于旅游业能耗没有纳入传统的国家统计体系,因此,各国无法提供关于旅游业能耗或碳排放的全面统计数据^[9,11] ...

... 鉴于国内外代表性成果的旅游业直接碳排放核算口径主要涉及交通、住宿和游览3部门^{[6,7,8,9, 11,12,13,14,15,16, 19, 22]} (图1 ...

... 补充一点,因全球^{[6, 11,12]}与中国^[14]的游览碳排放测度均采用新西兰的较低的系数 (70%为水电)^[9],故其比重可能偏低 ...

... 82%,这一般要显著高于国外,如威尔士^[20,21]、新西兰^[9]和澳大利亚^[18]分别为42%、64%、46%和52% ...

... 比值符合旅游业碳排放大多来自国内游客的结论^[11],但由于中国国土面积广大、国内游客众多等原因,该比值一般高于其他国家,如新西兰为72%^[9] ...

2007

0.0

... 随后,这一论题逐渐被学术界所重视^[6,7,8,9,10] ...

... 夏威夷州22%的温室气体来自旅游业^[15],但惠斯特镇高达65%^[10] ...

2008

0.0

... 到2008年,UNWTO等发布了研究报告《气候变化与旅游业：应对全球气候挑战》^[11],将旅游业碳排放研究推向了高潮 ...

... 虽然对旅游业碳排放进行测度非常艰难^[11],但近10多年来旅游业直接碳排放测度在多个空间尺度上已取得了可喜的进展 ...

... 旅游业碳排放约占全球碳排放的5%^{[6, 11,12]} ...

... 与UNWTO等得出的旅游业碳源主要来自交通、住宿和游览结论的测度范畴相一致^[11],已有主流研究的核算范围也集中于这三个部门,而对旅游业的餐饮、购物、娱乐等其他部门则关注不够 ...

... 2 数据来源由于旅游业能耗没有纳入传统的国家统计体系,因此,各国无法提供关于旅游业能耗或碳排放的全面统计数据^[9,11] ...

... 这与UNWOT等得出的全球旅游业直接碳排放主要来自交通 (71%)、住宿 (24%) 和游览 (5%) 的结论^[11]基本一致,但又有一定的差异,表现如下：首先,主要部门并不完全相同,购物取代了游览,游客对购物的偏好在碳排放上得以体现 ...

... 鉴于国内外代表性成果的旅游业直接碳排放核算口径主要涉及交通、住宿和游览3部门^{[6,7,8,9, 11,12,13,14,15,16, 19, 22]} (图1 ...

... 补充一点,因全球^{[6, 11,12]}与中国^[14]的游览碳排放测度均采用新西兰的较低的系数 (70%为水电)^[9],故其比重可能偏低 ...

... 比值符合旅游业碳排放大多来自国内游客的结论^[11],但由于中国国土面积广大、国内游客众多等原因,该比值一般高于其他国家,如新西兰为72%^[9] ...

... 074 t^[11] ...

2010

0.0

Peeters

, Dubois

Tourism travel under climate change mitigation constraints.

Journal of Transport Geography, 2010, 18(3): 447-457.

Abstract The paper first describes an inventory for 2005 giving the tourism related CO 2 emission caused by global tourism, and presents a 30-year projection and a 45-year simulation. The study found that tourists cause 4.4% of global CO 2 emissions. Also these emissions are projected to grow at an average rate of 3.2% per year up to 2035. This increase is problematic as globally a reduction of emissions by 3–6% is required to avoid ‘dangerous’ climate change. Using contemporary scenario techniques it appeared difficult to find a future tourist travel system consistent with CO 2 emission reductions of up to 70% by 2050 with respect to 2005. Based on the model underlying the 30-year projection, 70 scenarios are presented in a ‘landscape’ graph exploring the effect of opportunities to reduce the emissions, but this attempt did not reach the large reductions envisaged. We therefore explored automated scenario generation as a way to define backcasting scenarios that both reach the emission reduction target and retain the highest possible economic value for the sector. The main contributions made by this study are (1) in comparing the value of different ways to approach a (desired) future and (2) giving insight into the kind of structural changes required within tourism and tourism transport in case very strong emission reductions are required. Finally the model showed signs of ‘complex’ behaviour.

... 旅游业碳排放约占全球碳排放的5%^{[6, 11,12]} ...

... 鉴于国内外代表性成果的旅游业直接碳排放核算口径主要涉及交通、住宿和游览3部门^{[6,7,8,9, 11,12,13,14,15,16, 19, 22]} (图1 ...

... Peeters等^[12]不包括一日游),以此推算,与图1中多数年份较为靠近的2007年江苏三者比例分别为77%、13%和10% ...

... 补充一点,因全球^{[6, 11,12]}与中国^[14]的游览碳排放测度均采用新西兰的较低的系数 (70%为水电)^[9],故其比重可能偏低 ...

2010

0.0

... Nielsen等和石培华等分别探讨了瑞士和中国的旅游业碳排放^[13,14],但二者测度口径相差较大,难以进行国别间比较 ...

... 鉴于国内外代表性成果的旅游业直接碳排放核算口径主要涉及交通、住宿和游览3部门^{[6,7,8,9, 11,12,13,14,15,16, 19, 22]} (图1 ...

... 差异产生的背后原因既与测度方法可能不同有所关联 (如Nielsen等得出自下而上法的测度结果比自上而下法结果低14%^[13]),也与对象的旅游发展态势不无关系,还与其能源结构密不可分 ...

2011

0.0

2.937

Shi

Peihua

, Wu

Pu.

A rough estimation of energy consumption and CO₂ emission in tourism sector of China.

Acta Geographica Sinica, 2011, 66(2): 235-243.

[石培华, 吴普. 中国旅游业能源消耗与CO₂排放量的初步估算. 地理学报, 2011, 66(2): 235-243. ]

In 2009, a total of nearly 900 million international tourist arrivals were counted worldwide. A global activity of this scale can be assumed to have a substantial impact on the environment. In this contribution, five major aspects such as the change of LUCC and the use of energy and its associated impacts had been recognized. Recently, the impact of tourism on environment and climate attracts the attention of international organizations and societies in pace with rapid development of tourism industry. Energy consumption and CO 2 emissions in tourism sector has become a hot topic of international tourism research in recent five years. The use of energy for tourism can be divided according to transport-related purposes (travel to, from and at the destination) and destination-related purposes excluding transports (accommodation, food, tourist activities, etc.). In addition, transports, accommodation and food are related to many other industries dependent on energy. Thus, the estimations of energy consumption and CO 2 emissions in tourism sector have become a worldwide concern. Tourism in China grows rapidly, and the number of domestic tourists was 1902 million in 2009. Energy use and its impact on the environment increase synchronously with China's tourism. It is necessary to examine the relationship between energy use and CO 2 emissions. In this article, a preliminary attempt was applied to estimate the energy consumption and CO 2 emissions from China's tourism sector in 2008. Bottom-up approach, literature research and mathematical statistics technology were also adopted. According to the calculations, Chinese tourism-related may have consumed approximately 428.30 PJ of energy in 2008, or ahout 0.51% of the total energy consumptions in China. It is estimated that CO 2 emissions from tourism sector amounted to 51.34 Mt, accounting for 0.86% of the Chinese total. The results show that tourism is the industry of low-carbon and the leading industry coping with global climate change, energy-saving and CO 2 emission reduction. Based on this, the authors hold that tourism should become an important field in low-carbon economy.

1. Beijing Jiaotong University, Beijing, 100044, China; 2. China Tourism Academy, Beijing 100005, China

随着旅游产业规模的不断壮大，旅游业对气候、环境的影响日益引起国际机构和社会各界的关注。旅游业能源利用及二氧化碳排放是旅游对环境影响的重要驱动力之一，成为近5 年来世界旅游研究的新兴热点。旅游产业特点决定了旅游业能源消耗和二氧化碳排放量的测算是个世界性的难题。本文采用“自下而上”法，通过文献研究与数理统计方法，首次系统估算中国旅游业能源消耗和二氧化碳排放量。结果表明，2008 年，中国旅游业消耗能源428.30 PJ，占中国能源总消耗量的0.51%；排放二氧化碳51.34 Mt，占全国二氧化碳总排放量的0.86%。旅游业是低耗能、低排放、低碳产业，是应对气候变化和节能减排的优势产业，应该成为低碳经济发展的重要领域。

... Nielsen等和石培华等分别探讨了瑞士和中国的旅游业碳排放^[13,14],但二者测度口径相差较大,难以进行国别间比较 ...

... 鉴于国内外代表性成果的旅游业直接碳排放核算口径主要涉及交通、住宿和游览3部门^{[6,7,8,9, 11,12,13,14,15,16, 19, 22]} (图1 ...

... 可见,相对其他国家和地区,江苏旅游交通碳排放所占比重总体上适中,但住宿和游览则分别偏低和偏高,其中,交通略高于国内研究^[14,17,22],住宿与澎湖岛^[17]较为相似,而游览与澎湖岛^[17]、成都^[22]相接近 ...

... 补充一点,因全球^{[6, 11,12]}与中国^[14]的游览碳排放测度均采用新西兰的较低的系数 (70%为水电)^[9],故其比重可能偏低 ...

2010

0.0

Konan D

, Chan H

Greenhouse gas emissions in Hawaii: Household and visitor expenditure analysis.

Energy Economics, 2010, 32(1): 210-219.

Abstract This paper focuses on petroleum use and greenhouse gas emissions associated with economic activities in Hawai‘i. Data on economic activity, petroleum consumption by type (gasoline, diesel, aviation fuel, residual, propane), and emissions factors are compiled and analyzed. In the baseline year 1997, emissions are estimated to total approximately 23.2 million metric tons of carbon, 181 thousand metric tons of nitrous oxide, and 31 thousand metric tons of methane in terms of carbon-equivalent global warming potential over a 100-year horizon. Air transportation, electricity, and other transportation are the key economic activity responsible for GHG emissions associated with fossil fuel use. More than 22% of total emissions are attributed to visitor expenditures. On a per person per annum basis, emission rates generated by visitor demand are estimated to be higher than that of residents by a factor of 4.3 for carbon, 3.2 for methane, and 4.8 for nitrous oxide.

... 夏威夷州22%的温室气体来自旅游业^[15],但惠斯特镇高达65%^[10] ...

... 鉴于国内外代表性成果的旅游业直接碳排放核算口径主要涉及交通、住宿和游览3部门^{[6,7,8,9, 11,12,13,14,15,16, 19, 22]} (图1 ...

2008

2.743

0.0

Walz

, Calonder

G. P

, Hagedorn

. et al. Regional CO₂ budget, countermeasures and reduction aims for the Alpine tourist region of Davos, Switzerland . Energy Policy, 2008, 36(2): 811-820.

Abstract In its latest report, the Intergovernmental Panel on Climate Change (IPCC) concludes that global climate change can still be slowed down if greenhouse gas emissions are rapidly and strongly reduced. We present a detailed regional CO 2 budget for the Alpine tourist region of Davos, Switzerland, including emissions and potential sinks. The aim of the study was (1) to estimate the most important CO 2 sources and sinks, (2) to identify the most efficient reduction measures and (3) to assess the feasibility of different reduction targets. The results show that the emissions due to heating contribute to a proportion of 86.3% to the total budget, which is mainly due to the harsh local climate and the tourism-focused local economy. They also show that the yearly CO 2 emissions per capita in Davos exceed the Swiss average of 6 tonnes by 25%. The augmentation of the carbon pool through the natural environment compares to 10.3% of the total emissions, and further afforestation of the community forest can contribute to an improvement of the total budget by 2.6%. The reduction aim of −15% until 2015 (compared with 2004), as set by the municipality itself, could be easily reached through better building insulation and the use of renewable energy sources. More ambitious aims, such as a 2000 W-society or CO 2 neutrality, however, will not be realised without major drawbacks in living standards.

... 达沃斯镇的碳排放虽超过国内其他地方25%,但旅游业对此并不负主要责任^[16] ...

... 鉴于国内外代表性成果的旅游业直接碳排放核算口径主要涉及交通、住宿和游览3部门^{[6,7,8,9, 11,12,13,14,15,16, 19, 22]} (图1 ...

2009

3.398

0.0

Kuo N

, Chen P

Quantifying energy use, carbon dioxide emission, and other environmental loads from island tourism based on a life cycle assessment approach.

Journal of Cleaner Production, 2009, 15(10): 1324-1330.

Abstract The main purpose of industrial ecology is to evaluate and minimize impacts from economic activities of human society. Tourism as one economic activity, results in a full range of environmental impacts, but few applications of industrial ecology to tourism management have previously been discussed. Life cycle assessment (LCA) is used in this research to explore environmental impacts of island tourism, and then the environmental loads per tourist per trip can be found. Penghu Island in Taiwan is taken as an example to examine this new approach. Various environmental loads in transportation, accommodation, and recreation activity sector are all inventoried and calculated here. In summary, per tourist per trip uses 1606 MJ of energy, 607 L of water, and emits 109,034 g of CO 2 , 2660 g of CO, 597 g of HC, 70 g of NO x . In addition, per tourist per trip also discharges 416 L of wastewater, 83.1 g of BOD, and 1.95 g of solid waste. In terms of energy use, the transportation consumes the largest energy (67%); in particular, the airplane sector. Moreover, per Penghu tourist results in more environmental loads than local people; for example, the amount of solid waste discharge per tourist is 1.95 kg per day, while that of per local people is 1.18 kg. Finally, the advantages and limitations of such LCA approach are also discussed.

... 旅游航空交通、星级饭店和水上摩托车分别是澎湖岛旅游交通、住宿和游览温室气体的主要承担者^[17] ...

2010

0.0

... 82%,这一般要显著高于国外,如威尔士^[20,21]、新西兰^[9]和澳大利亚^[18]分别为42%、64%、46%和52% ...

2012

0.0

... 鉴于国内外代表性成果的旅游业直接碳排放核算口径主要涉及交通、住宿和游览3部门^{[6,7,8,9, 11,12,13,14,15,16, 19, 22]} (图1 ...

2012

0.0

... 82%,这一般要显著高于国外,如威尔士^[20,21]、新西兰^[9]和澳大利亚^[18]分别为42%、64%、46%和52% ...

2013

0.0

... 82%,这一般要显著高于国外,如威尔士^[20,21]、新西兰^[9]和澳大利亚^[18]分别为42%、64%、46%和52% ...

... 02 t^[21],这反映了该值在不同地区可能相差悬殊,因此,将其与全球平均值进行比较更具一般意义 ...

... 国外部分研究还探索了具有不同收入^[6]、旅游形式^[21]的游客群体碳排放,国内研究在此方面亟需加强 ...

2011

5.627

0.0

Liu

Jun

, Feng

Tingting

, Yang

Xi.

The energy requirements and carbon dioxide emissions of tourism industry of Western China: A case of Chengdu city.

Renewable and Sustainable Energy Reviews, 2011, 15(6): 2887-2894.

Abstract Chengdu, the capital city of Sichuan province in western China is the gateway to Tibet. It is also the major habitat for giant panda and the principal city with the largest total tourism economic output in western China. The energy requirement of tourism industry is calculated by combining the 7 energy intensities with tourist consumption data from the Chengdu Domestic Tourist Expenditure Survey in which over 50,000 tourists were involved during 1999–2004. The carbon dioxide emissions of tourism industry are calculated based on the method introduced by IPCC report. Then, decomposition analysis was used to identify key factors causing the change of carbon emission. From 1999 to 2004, the energy consumption and carbon dioxide emission of tourism industry in Chengdu increased from 1.8 × 10 7 GJ to 2.3 × 10 7 GJ and from 1.7 × 10 6 tons to 2.1 × 10 6 tons, respectively. The indirect energy requirements and indirect CO 2 emissions dominate the total energy consumptions and total CO 2 emissions, with an overwhelming percentage of over 90%. The transportation is the major contributor for energy consumption and carbon emission of tourism industry. The relative importance of the transportation and shopping tends to increase while the food and entertainment tends to decrease. Among the five factors affecting energy consumption and carbon dioxide emission in tourism, energy intensity, expenditure size and the industry size are generally found to be principal drivers of emission growth, whereas energy share and consumption structure are not found to have a sizable influence on the growth of tourism industry emissions. In addition, the energy intensity has a negative effect on the increase of CO 2 levels while the expenditure size and the industry size have a positive effect on it.

... 国内学者仅刘洪涛等进行了类似研究^[22] ...

... 1997-2005年,游客消费水平和能源结构对成都旅游业碳排放分别具有正负效应^[22],但2010年二者对南岳作用截然相反^[24],个中缘由可能在于地域与时间的不同 ...

... 鉴于国内外代表性成果的旅游业直接碳排放核算口径主要涉及交通、住宿和游览3部门^{[6,7,8,9, 11,12,13,14,15,16, 19, 22]} (图1 ...

... 这与相关研究成果比较吻合^{[22, 24]} ...

2012

0.0

... entis等探讨了空间布局、能源强度等因素对立陶宛乡村旅游业碳排放的作用^[23] ...

... 国内外一些研究也证实了能源强度对碳减排的重要性,如在2004-2008年期间,其每年都对立陶宛乡村旅游业碳排放的增长起很大促进作用,但2009-2010年则是碳排放降低的关键因素^[23] ...

2012

0.0

2.123

Bohua

, Liu

Yunpeng

, Dou

Yindi.

Carbon footprint evaluation of tourism transportation system in tourist attractions and analysis of the influencing factors: A case study in Hengshan.

Resources Science, 2012, 67(10): 956-963.

[李伯华, 刘云鹏, 窦银娣. 旅游风景区旅游交通系统碳足迹评估及影响因素分析: 以南岳衡山为例. 资源科学, 2012, 34(5): 956-963. ]

As climate change is receiving more and more attentions from the world, low-carbon tour is gradually becoming the practical choice of countries to develop tourism. And as a result, a new concept, carbon footprint emerges. By constructing carbon emission life-cycle model of tourism transportation system in tourist attractions and taking quantitative research on carbon footprint of the system, this article aims to provide decision-making basis for low-carbon tourism development in Hengshan scenic spots. Taking Hengshan as a case and using life-cycle evaluation theory, this article has constructed a carbon footprint calculation model of tourism transportation system in Hengshan scenic spot. The results show that: 1) In terms of total volume, different types of transportation mode have greatly different carbon footprints. The biggest threat to the environment of tourist attractions is tourist communication on highway, whose total carbon footprint is 2.6 times that of tourist traffic by cableway and 46.1 times that of tourist traffic by sidewalk; 2) In terms of influencing factors, the increasing of carbon emission is deeply affected by energy structure and population scale, which have produced 45.5% and 145.8% of carbon increment respectively. Energy intensity effect and economic scale effect are main efficiency factors of carbon emission reduction, which accumulatively achieved 73.8% and 17.6% of carbon emission reduction respectively. Therefore, we should put emphasis on low carbon propaganda and rational choice of tourism vehicles so as to establish a better transportation operation mechanism. Here are some suggestions: first, tourists' environmental consciousness-“Low-Carbon Tour”should be strengthened; second, low-carbon vehicles should be used cautiously according to the characteristics of infrastructures in Hengshan scenic spot; third, we should make operation mechanism to be more reasonable in order to quicken the steps in building low-carbon tourism transportation.

Department of Resource Environment & Tourism Management, Hengyang Normal University, Hengyang 421008, China;Department of Resource Environment & Tourism Management, Hengyang Normal University, Hengyang 421008, China;Department of Resource Environment & Tourism Management, Hengyang Normal University, Hengyang 421008, China

气候变化越来成为国际社会关注的焦点,低碳旅游战略逐步成为各国发展旅游的现实选择,碳足迹的概念也应运而生。本文以南岳衡山旅游风景区为例,运用生命周期评价理论,构建了南岳风景区旅游交通系统碳足迹计算模型。研究结果表明:从总量来看,不同类型交通方式的碳足迹情况相差甚远。公路旅游交通对旅游景区的环境威胁最大,碳足迹总量是索道旅游交通的2.6倍,是人行道旅游交通的46.1倍;从影响因素来看,能源结构效应和人口规模效应是南岳旅游景区碳排放增加的主要因素,分别累计产生了45.5%和145.8%的碳增量,而能源强度效应和经济规模效应则是抑制碳排放的有效因子,分别累计实现了73.8%和17.6%的碳减排。因此,应重视旅游景区交通工具的低碳宣传和合理选择,建立完善的交通运营机制。

... 这与相关研究成果比较吻合^{[22, 24]} ...

2012

0.0

2.937

Shi

Minjun

, Wang

Yan

, Zhang

Zhuoying.

et al.

Regional carbon footprint and interregional transfer of carbon emissions in China.

Acta Geographica Sinica, 2012, 67(10): 1327-1338.

[石敏俊, 王妍, 张卓颖等. 中国各省区碳足迹与碳排放空间转移. 地理学报, 2012, 67(10): 1327-1338. ]

Obligation assignment of carbon emission reduction needs to evaluate carbon emission charge by taking into account interregional transfer of carbon emissions. Carbon footprint, as a concept of carbon emission measurement, can evaluate life cycle carbon emissions of production and service to meet final demand. It should include direct carbon emissions caused by fossil energy as well as indirect carbon emissions induced by intermediate products production. This paper aims to estimate carbon footprint of each province and inter-provincial transfer of carbon emissions in China based on an input-output approach and China IRIO 2002 database. The results indicate there are significant differences of carbon footprint and per capita carbon footprint among provinces in China. The provinces with higher carbon footprint, mainly located in northern China, have large economic scale. The provinces with high per capita carbon footprint include developed metropolitan regions and energy-rich regions with a high proportion of energy intensive sectors. Interregional transfer of carbon emissions has emerged from energy-rich regions with a high proportion of energy intensive sectors to developed coastal regions and developing regions with incomplete industrial systems. The results imply developed coastal regions should bear more obligation of carbon emission reduction. As a significant amount of carbon emissions of energy-rich regions with a high proportion of energy intensive sectors is induced by provision of energy intensive products for developed coastal regions and developing regions with incomplete industrial systems, interregional transfer of carbon emissions should be taken into account for regional obligation assignment of carbon emission reduction. It can be considered to reduce obligation of carbon emission reduction for those energy-rich regions with a high proportion of energy intensive sectors. Otherwise, a compensation mechanism should be considered for developed coastal provinces to provide financial and technological aid to energy-rich regions with a high proportion of energy intensive sectors for improvement of energy use efficiency and reduction of carbon emissions.

1. University of Chinese Academy of Sciences, Beijing 100049, China; 2. Research Center on Fictitious Economy and Data Science, CAS, Beijing 100190, China; 3. China Communication University, Beijing 100024, China; 4. Japan Institute of Global Environmental Strategy

减排责任的区域分解需要科学评价各地区的排放责任。碳足迹可以全面客观地评价为满足消费而进行的生产的生命周期碳排放水平, 除了生产过程的直接碳排放, 也包括生产过程中所消耗的中间产品的隐含碳排放。应用2007 年各省区投入产出模型和2002 年中国省区间投入产出模型, 定量测算了各省区的碳足迹和省区间的碳排放转移。结果显示, 各省区之间碳足迹和人均碳足迹存在显著的差异。碳足迹较大的省份为经济大省, 主要分布在北方地区;人均碳足迹较高的省份主要是北京、上海等中心城市和能源富集区域及重化工基地;中国存在着从能源富集区域和重化工基地分布区域向经济发达区域和产业结构不完整的欠发达区域的碳排放空间转移。上述结果表明, 人均碳足迹高的经济发达省份应承担较大的减排责任, 能源富集区域和重化工基地分布区域有相当一部分的碳排放是为沿海发达省份和产业结构不完整的欠发达省份提供电力、原材料等高碳产品所致, 减排责任的区域分解需要考虑碳排放空间转移的因素, 适当减轻能源富集区域和重化工基地分布区域的减排责任, 或使沿海发达省份向能源富集区域和重化工区域提供资金和技术上的扶持, 帮助这些区域提高能源利用效率, 减少碳排放。

... 减排责任的区域分解需要科学评价各地区的排放责任^[25],国家战略层面上的旅游业节能减排任务也需要落实到地方场域 ...

0.0

2.139

... 区域旅游业碳排放研究已成一个新的热点^[26] ...

2010

2.743

0.0

... 1 旅游业直接碳排放和间接碳排放一个部门的直接能源强度可表示为该部门能源消费实物量和总投入的比值,计算公式如下^[27]： ...

... 2007年的强度系数来自陆旸^[29],在此基础上,根据刘洪涛等^{[27, 30]}推算前两年 ...

1989

0.0

... 2 Kaya恒等式与碳排放影响因素LMDI分解 Kaya恒等式为日本能源经济学家Kaya于1989提出,目的是为了判断人类活动对二氧化碳的影响水平^[28] ...

2011

0.0

8.619

... 2007年的强度系数来自陆旸^[29],在此基础上,根据刘洪涛等^{[27, 30]}推算前两年 ...

2011

0.0

0.0348

... 2007年的强度系数来自陆旸^[29],在此基础上,根据刘洪涛等^{[27, 30]}推算前两年 ...

2010

0.0

0.082

... 其原因与中国许多重要行业对煤炭和火电的依赖程度依然很高^[31]关联很大 ...

... 旅游业主要碳源来自间接层面,而中国许多重要行业对煤炭和火电的依赖程度依然很高^[31],这也印证了现阶段旅游业通过改变能源结构减排的空间不大的结论 ...

2010

0.0

0.082

... 这正如有关研究^[32]所指出：高收入国家对碳排放的需求增量较为有限,而低收入国家尚需要大量的排放空间,来实现其人文发展的潜力 ...

2014

0.0

... 遗憾的是低碳技术被旅游商使用有限^[33] ...