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Use of Household Survey Data as a Tool to Assess the Carbon Footprint of Rural Tourist Accommodation and Related Services in China: A Case Study of Mount Qingcheng

Author

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  • Jun Liu

    (Tourism School, Sichuan University, 24 South Section 1 Ring Road No. 1, Chengdu 610065, Sichuan, China)

  • Chu Lin

    (Tourism School, Sichuan University, 24 South Section 1 Ring Road No. 1, Chengdu 610065, Sichuan, China)

  • Li Huang

    (Tourism School, Sichuan University, 24 South Section 1 Ring Road No. 1, Chengdu 610065, Sichuan, China)

  • Jianghuan Zhu

    (Tourism School, Sichuan University, 24 South Section 1 Ring Road No. 1, Chengdu 610065, Sichuan, China)

  • Lijun Wu

    (Tourism School, Sichuan University, 24 South Section 1 Ring Road No. 1, Chengdu 610065, Sichuan, China)

  • Yunyun Li

    (Tourism School, Sichuan University, 24 South Section 1 Ring Road No. 1, Chengdu 610065, Sichuan, China)

Abstract

The need to improve the accuracy of carbon emission measurements is a major issue which the tourism industry must resolve in order to reduce adverse impacts on climate change and the environment. This study established a detailed consumption list based on household survey data and calculated the carbon emissions of accommodation and services of the rural tourism industry of Mount Qingcheng using the input–output and lifecycle methods. Further, it analysed the key factors affecting carbon emissions. The results indicate that within the surveyed area, carbon emissions from accommodation and services amounted to 30.27 kg CO 2 /per person per day; these emissions were primarily from indirect sources, which accounted for 74.99% of the total emissions. Emissions from construction and production of durable goods accounted for 13.08% and 21.58% of the total emissions. The omission of these sources of carbon emissions was the primary reason for the carbon emission levels of the tourism industry being underestimated previously. For each additional 10,000 yuan in revenue, accommodation and related services of the rural tourism industry emit an additional 1412.08 kg of CO 2 . This is higher than the level of carbon emissions of the agriculture industry, but lower than those of the processing and manufacturing industries. Tourist consumption behaviours and types of tourism operations are important factors affecting carbon emissions. Effective emission reduction strategies include guiding tourist consumption behavioural changes, optimizing tourism operation portfolios, and extending the service life of constructions and durable goods.

Suggested Citation

  • Jun Liu & Chu Lin & Li Huang & Jianghuan Zhu & Lijun Wu & Yunyun Li, 2017. "Use of Household Survey Data as a Tool to Assess the Carbon Footprint of Rural Tourist Accommodation and Related Services in China: A Case Study of Mount Qingcheng," Sustainability, MDPI, vol. 9(10), pages 1-17, September.
    • Handle: RePEc:gam:jsusta:v:9:y:2017:i:10:p:1680-:d:112758
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    References listed on IDEAS

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    1. Camillo De Camillis & Paul Peeters & Luigia Petti & Andrea Raggi, 2012. "Tourism Life Cycle Assessment (LCA): Proposal of a New Methodological Framework for Sustainable Consumption and Production," Chapters, in: Murat Kasimoglu (ed.), Visions for Global Tourism Industry - Creating and Sustaining Competitive Strategies, IntechOpen.
    2. Assumpcio Anton & Juan I. Montero & Pere Munoz & Francesc Castells, 2005. "LCA and tomato production in Mediterranean greenhouses," International Journal of Agricultural Resources, Governance and Ecology, Inderscience Enterprises Ltd, vol. 4(2), pages 102-112.
    3. Aste, Niccolò & Adhikari, R.S. & Buzzetti, Michela, 2010. "Beyond the EPBD: The low energy residential settlement Borgo Solare," Applied Energy, Elsevier, vol. 87(2), pages 629-642, February.
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    Cited by:

    1. Duoxun Ba & Jing Zhang & Suocheng Dong & Bing Xia & Lin Mu, 2022. "Spatial-Temporal Characteristics and Driving Factors of the Eco-Efficiency of Tourist Hotels in China," IJERPH, MDPI, vol. 19(18), pages 1-24, September.
    2. Jing Zhang & Bing Xia, 2024. "Carbon Emissions and Its Efficiency of Tourist Hotels in China from the Supply Chain Based on the Input–Output Method and Super-SBM Model," Sustainability, MDPI, vol. 16(21), pages 1-27, October.
    3. Geneidy Sami El & Baumeister Stefan, 2019. "The Carbon Footprint of Volunteer Tourism," European Journal of Tourism, Hospitality and Recreation, Sciendo, vol. 9(2), pages 15-25, December.

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