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This project will employ multi-region input-output analysis (Isard 1951; Leontief 1953) and a comprehensive global database (Lenzen et al. 2012; Lenzen et al. 2013; Lenzen et al. 2017) to assess the carbon footprint of global tourism (Lenzen et al. 2018). The particular focus of this project is on rebound effects, or additionality.

An unexplored aspect in carbon footprints of tourism is additionality, or systemic or rebound effects, meaning that if visitors had not embarked on their journey, they would have eaten and travelled at home. These effects can be assessed by drawing up alternative scenarios (travel or stay-at-home), resulting in carbon footprints of tourism that are net of carbon emissions associated with such alternative activities, or in other words, comprise only additional emissions (in the sense of the Clean Development Mechanism; Shrestha and Timilsina 2002). Such carbon footprints would more realistically describe the additional impacts that tourism has on global climate change. For example, if only additional emissions were counted with reference to a stay-home scenario, air travel may well come out as the dominant emissions component.

The PhD will be supervised by Prof. Manfred, Dr Ya-Yen Sun and Dr Arunima Malik. The applicant will join the ISA Research Group at the School of Physics – The University of Sydney. ISA develops leading-edge research and applications for environmental and broader sustainability issues, bringing together expertise in environmental science, economics, technology, and social science.


Professor Manfred Lenzen, Dr Arunima Malik.

Research location

School of Physics

Program type



On the back of a growth in tourist expenditure from 2.5 $tr in 2009 to 4.7 $tr in 2013, the carbon footprint of global tourism increased rapidly from 3.9 Gt CO2-e to 4.4 Gt CO2-e during the same period. More than half of this carbon footprint was caused in high-income country destinations, and by visitors from high-income countries.

One interesting aspect in carbon footprints not only of tourism is what can be described as additionality, or systemic or rebound effects, meaning for example that the carbon footprint of a wind turbine could include a credit for displaced coal or gas, and an addition for the increased need of grid balancing and back-up (Pehnt 2006); or the carbon footprint of a recommended diet could include the carbon footprint of those commodities that are purchased with the money saved (since the recommended diet is generally cheaper; Lenzen and Dey 2002) or the carbon footprint of defense spending could be offset against the carbon footprint of the portfolio that the government funds would alternatively be spent on (Heyes and Liston-Heyes 1993). In the context of the tourism carbon footprint: if visitors had not embarked on their journey, they would have eaten and travelled at home, giving rise to the question of whether the carbon footprint of tourism should be net of carbon emissions associated with such alternative activities, or in other words, should only comprise additional emissions (in the sense of the Clean Development Mechanism; Shrestha and Timilsina 2002).

In prior work, authors did not attempt to quantify additionality, systemics and rebounds, because of a number of reasons. First, footprint or consequential LCA studies that include such rebounds or systemic changes are rare at the national level (Heyes and Liston-Heyes 1993; Lenzen and Dey 2002; Pehnt 2006), and virtually absent at the global level, because of the inherent difficulty in specifying and estimating the often complex, alternative scenarios that would have occurred in the absence of the activities under investigation. Offsetting food consumption, shopping and travel behavior of tourists against their practices at home, for all individual countries and five years, requires constructing alternative scenarios.

The majority of existing footprint and LCA studies generally view the so-called functional unit as a clear-cut, distinct entity, including every activity that fell within the scope of the study (Minx et al. 2009), and without the requirement of capturing wider systemic effects (Wiedmann and Minx 2008). In the context of tourism this means accepting as a fact that tourists do not eat at home but at their destination, and that the food consumed must be considered as one necessary component for realising – in LCA parlance – the functional unit “visit”. However, the consumption patterns of tourists are found to be different from their lifestyle at home: Visitors tend to use more private transportation than public transportation (Le-Klähn and Hall 2014), consume more water (Gössling et al. 2012), and eat more processed food (especially alcoholic drinks and meat products; Collins et al. 2007). Thus, evaluating alternative travel and stay-at-home scenarios is important task, to which this PhD project will contribute.

Additional information

Quantitative methods
The project will utilize multi-region input-output (MRIO) analysis (Isard 1951; Leontief 1953) and a comprehensive global database (Lenzen et al. 2012; Lenzen et al. 2013; Lenzen et al. 2017). Environmental and social footprint analyses have recently been carried out using a hybrid method (Suh and Nakamura 2007), guaranteeing complete coverage of upstream supply-chain contributions. Here, “complete coverage” means that all upstream supply-chain contributions such as emissions embodied in anything that a “tourist” as per UNWTO definition consumes – food, accommodation, transport, fuel, and shopping – are included in the footprint measure. Input-output-assisted footprinting is supported by a long history of numerous applications (see for example Hoekstra 2010).

Interest and prior engagement in broader sustainability will be beneficial. Please consult Lenzen et al. 2018 prior to applying. Applications should be sent by email to Prof. Manfred Lenzen:

Heyes, A.G. and C. Liston-Heyes (1993) US demilitarization and global warming. Energy Policy 21, 1217-1224.
Hoekstra, R. (2010) (Towards) a complete database of peer-reviewed articles on environmentally extended input-output analysis. In: J.M. Rueda-Cantuche and K. Hubacek (eds.) 18th International Input-Output Conference, Sydney, Australia.
Isard, W. (1951) Interregional and regional input–output analysis: a model of a space economy. Rev Econ Stat 33.
Lenzen, M. and C.J. Dey (2002) Economic, energy and emissions impacts of some environmentally motivated consumer, technology and government spending options. Energy Economics 24, 377-403.
Lenzen, M., A. Geschke, M.D. Abd Rahman, Y. Xiao, J. Fry, R. Reyes, E. Dietzenbacher, S. Inomata, K. Kanemoto, B. Los, D. Moran, H. Schulte in den Bäumen, A. Tukker, T. Walmsley, T. Wiedmann, R. Wood and N. Yamano (2017) The Global MRIO Lab - charting the world economy. Economic Systems Research 29, 158-186.
Lenzen, M., K. Kanemoto, D. Moran and A. Geschke (2012) Mapping the structure of the world economy. Environmental Science & Technology 46, 8374–8381,
Lenzen, M., D. Moran, K. Kanemoto and A. Geschke (2013) Building Eora: a global multi-region input–output database at high country and sector resolution. Economic Systems Research 25, 20-49.
Lenzen, M., Y.-Y. Sun, F. Faturay, Y.-P. Ting, A. Geschke and A. Malik (2018) The carbon footprint of global tourism. Nature Climate Change.
Leontief, W. (1953) Interregional theory. In: W. Leontief, H.B. Chenery, P.G. Clark, J.S. Duesenberry, A.R. Ferguson, A.P. Grosse, R.N. Grosse, M. Holzman, W. Isard and H. Kistin (eds.) Studies in the Structure of the American Economy. New York, NY, USA, Oxford University Press, 93-115.
Pehnt, M. (2006) Dynamic life cycle assessment (LCA) of renewable energy technologies. Renewable Energy 31, 55-71.
Shrestha, R.M. and G.R. Timilsina (2002) The additionality criterion for identifying clean development mechanism projects under the Kyoto Protocol. Energy Policy 30, 73-79.
Suh, S. and S. Nakamura (2007) Five years in the area of input-output and Hybrid LCA. International Journal of Life Cycle Assessment 12, 351-352.
Wiedmann, T. and J. Minx (2008) A Definition of 'Carbon Footprint'. In: C.C. Pertsova (ed.) Ecological Economics Research Trends. Hauppauge NY, USA, Nova Science Publishers, Inc.

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Opportunity ID

The opportunity ID for this research opportunity is 2390

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