the ecological footprint as a key indicator of sustainable tourism

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Tourism Management 28 (2007) 46–57

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Research article

The ecological footprint as a key indicator of sustainable tourism

Colin Hunter�, Jon Shaw

Department of Geography & Environment, University of Aberdeen, Elphinstone Road, Aberdeen, AB24 3UF, UK

Received 31 December 2004; accepted 26 July 2005

Abstract

This paper argues for ecological footprint (EF) analysis to become widely adopted as a key environmental indicator of sustainable

tourism (ST). It is suggested that EF analysis provides a unique, global perspective on sustainability that is absent with the use of locally

derived and contextualised ST indicators. A simple methodology to estimate indicative, minimum EF values for international tourism

activities involving air travel is presented. Critically, the methodology accounts for the EF that would have been used by a tourist at

home during the tourist trip, providing an estimate of the net, as well as the gross, tourism-related EF. Illustrations of the application of

the methodology are provided, including the evaluation and comparison of specific tourism products. It is suggested that some

(eco)tourism products may, potentially, make a positive contribution to resource conservation at the global scale. Areas for further

research in applying EF analysis to tourism are outlined.

r 2005 Elsevier Ltd. All rights reserved.

Keywords: Sustainable tourism; Indicator; Ecological footprint

1. Introduction

The importance of learning from related fields anddisciplines is increasingly being recognised in the sustain-able tourism (ST) literature, both as a means of advancingknowledge and understanding of ST, and as a means ofavoiding ‘re-inventing the wheel’ in ST practice (e.g. Farrell& Twining-Ward, 2003; Hunter, 2002a; Ko, 2001).Potentially, one area where a great deal may be learnedfrom the broader sustainable development (SD) andenvironmental management literature is in the develop-ment and use of suitable indicators of ST. This is explicitlyrecognised by Twining-Ward and Butler (2002), in one ofthe very few works to date specifically designed toformulate indicators of ST. Despite the undoubted demandfor appropriate indicators of ST, these authors argue (p.365) that research in this area is ‘‘still in its incipientstages’’, a view echoed by others (e.g. Li, 2004; Miller,2001; Rebollo & Baidal, 2003).

It is, perhaps, whilst the art/science of ST indicatorresearch is still in its infancy that arguments for the

e front matter r 2005 Elsevier Ltd. All rights reserved.

urman.2005.07.016

ing author. Tel.: +441224 272328; fax: +44 1224 272331.

ess: [email protected] (C. Hunter).

adoption of a particular approach or type of indicator arebest made. This paper argues for the widespread use of the‘ecological footprint’ (EF) as a key environmental indica-tor of ST. The very act of proposing such adoption of theEF (or any single indicator) runs counter to someperceptions of progressive thinking in ST and SD research,where sustainability is regarded as an adaptive conceptrequiring that indicators of ST ‘‘reflect the space and timespecific context of the locality under study’’ (Twining-Ward & Butler, 2002, p. 367). Other studies, however,appear to assume that the development and use of a genericset of ST indicators is appropriate (Manning, Clifford,Dougherty, & Ernst, 1996; Miller, 2001). In proposing thewidespread use of the EF technique in ST analyses, weacknowledge the importance of using indicators that reflectlocal circumstances, as suggested by Twining-Ward andButler (2002), but do not take this position to mean thatsuitable indicators ought to be wholly determined by localconditions and attitudes.Indeed, it could be argued that, to date, ST indicators

and indicators adopted to measure environmental condi-tions in tourism planning and management frameworkshave been designed almost exclusively with the localisedmonitoring of destination-based impacts and resource

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ARTICLE IN PRESSC. Hunter, J. Shaw / Tourism Management 28 (2007) 46–57 47

demands in mind (e.g. Hughes, 2002; Li, 2004; Manning etal., 1996; Moore, Smith, & Newsome, 2003; Rebollo &Baidal, 2003; Smith & Newsome, 2002; Ward, Hughey, &Urlich, 2002). This parochialism may detract from theappreciation of tourism as an agent of global environ-mental change, and ignores the consequences of impactsgenerated in the transit region (Gossling, 2002; Hunter,1995). Uniquely, the EF is specifically designed to expressaggregate environmental impact in terms of pressure on theglobal biosphere, and can account for travel-related impactcomponents. The use of EF analysis in the context of STremains almost completely unexplored with very limitedwork carried out to date. The aims of this paper are,therefore, to: provide an overview of the EF concept,including its use in tourism research; present a simplemethodology for the rapid estimation of indicative nettourism EF values using existing secondary data sources;and, illustrate different applications of the net EF as a keyenvironmental indicator of ST.

With reference to the second of these aims, it will beargued that the notion of a net EF in the tourism context isparticularly significant, as tourists when away from homeare not generating the footprint that they normally wouldin the source country. The need to consider the EF of aninternational ecotourist in the context of the EF generatedby her or him at home is explicitly recognised by Fennell(2002). Also, a desirable attribute of any potential indicatorof SD or ST is that the necessary data be relatively easilyavailable from existing, secondary sources (e.g. Bell &Morse, 2003), and this is reflected in the nature of themethodology developed in this paper. Finally, it isimportant to state that we recognise that the EF couldonly ever be one of a suite of indicators necessary for theholistic appraisal of ST. Locally based and derivedindicators that also encompass economic and socialactivities and impacts would clearly also be required.

2. The EF concept

The EF provides an aggregate estimate of demands uponthe biophysical productivity and waste assimilation capa-city of nature imposed by human lifestyles. Although aunique form of SD indicator, the EF technique draws uponolder environmental impact appraisal approaches includ-ing net primary productivity accounting, energy and‘Emergy’ accounting, carrying capacity assessment, andlife-cycle analysis (Wackernagel & Yount, 2000). Publisheddescriptions of EF analysis were first provided in the earlyto mid-1990s (Rees, 1992; Rees & Wackernagel, 1994),and their authors subsequently defined the EF as ‘‘anaccounting tool that enables us to estimate the resourceconsumption and waste assimilation requirements of adefined human population or economy in terms of acorresponding productive land area’’ (Wackernagel &Rees, 1996, p. 9).

The EF conceptualises a population or economy ashaving an ‘industrial metabolism’, consuming resources

and producing wastes in order to sustain itself, therebyappropriating a portion of the planetary biosphere in theprocess (Wackernagel & Rees, 1996). EF analysis portraysthese demands on natural resources in terms of anestimated hypothetical equivalent land/sea (biosphere)area, with the size of the footprint (sometimes also referredto as ‘appropriated carrying capacity’) for a givenpopulation and for a specified time period (normally ayear) determined by the lifestyle of the population inquestion. The EF itself does not exist in real space, butrather can be viewed as the aggregation of myriad actualland and sea areas around the world appropriated by agiven population relying on the global movement of rawmaterials and products. The unique attribute of EFanalysis is the expression of demands upon naturalresources in terms of an equivalent land/sea area (globalhectares, or gha), thereby (it is claimed) facilitatingcomprehension of environmental impact and providing apowerful educational tool (e.g. Chambers, Simmons, &Wackernagel, 2000; Wackernagel & Yount, 2000).Detailed descriptions of the procedures involved in EF

calculations are found elsewhere (e.g. Chambers et al.,2000; Wackernagel, Lewan, & Hansson, 1999), but,broadly speaking, they can be accomplished either byusing the more traditional compound (‘top down’)approach, or with the component-based (‘bottom-up’)approach. The former takes the nation state as its primaryunit of analysis, employing national trade flow and energydata to estimate the average per capita footprint, while thelatter approach seeks to account for most consumption(e.g. for a region) by summing available life-cycle dataacross individual footprint components. Typically, EFcalculations account for, and then combine, the use ofenergy, foodstuffs, raw materials and water, and alsocapture transport-related impacts, the production of wastes(including carbon dioxide from the burning of fossil fuels),and the loss of productive land associated with buildings,roads and other aspects of the built environment. Which-ever way the EF is actually calculated, it is effectively anaggregate indicator of environmental impact or environ-mental sustainability that uses gha as the common currencyto express impact magnitude across all components.Although it is relatively easy to conceive of an equivalentEF land area required to, for example, produce ‘x’ tonnesof a particular crop, or the equivalent sea space required toproduce ‘y’ tonnes of a fish species, it is less easy toappreciate how other EF components, particularly thegeneration of carbon dioxide, can be converted into ghaspace. This is achieved in EF calculations by translatingenergy use/carbon dioxide emissions into an equivalentland (forest) area required to sequester carbon dioxideloading estimates. It is also important to appreciate thatmost advocates of the EF technique stress that EFcalculations provide conservative estimates of globalenvironmental impact, and the tradition in EF analysis isto consciously err on the side of caution when makingestimates of resource use and waste production for use in

ARTICLE IN PRESSC. Hunter, J. Shaw / Tourism Management 28 (2007) 46–5748

calculations (e.g. Monfreda, Wackernagel, & Deumling,2004; Wackernagel & Rees, 1996).

Many applications of EF analysis have focused on nationsand cities or groups of cities (e.g. Folke, Jansson, Larsson, &Costanza, 1997; Fricker, 1998; Parker, 1998; Wackernagel,1998a; Wackernagel & Rees, 1996; Wackernagel, Lewanet al., 1999; Wackernagel, Onisto et al., 1999). A recent reportprovides details of the EF of 134 countries using thecompound approach (Venetoulis, Chazan, & Gaudet,2004). The per capita EF for the year 2000 ranged from0.50 gha for Bangladesh to 9.57 gha for the USA. NorthAmerica and Western Europe are the world regions withthe highest average per capita footprints, followed by Centraland Eastern Europe, the Middle East and Central Asia, theAsia–Pacific region, Latin America and the Caribbean, andAfrica. Taking Western Europe in more detail, for example,national per capita EFs ranged from 3.26 gha for Italy, to8.17 gha for Norway. A much used benchmark for compar-ison in EF studies is the so-called ‘fair earthshare’ value; i.e.the global average area of productive land/sea space availableannually on a per capita basis. One recent estimate of this,which excludes land set aside for non-human species, is1.8 gha/year (World Wildlife Fund, 2004). Other cited valuesare slightly higher (e.g. Chambers et al., 2000; Chambers,Griffiths, Lewis, & Jenkin, 2004), with some 2gha/yearregarded as a reasonable estimate (Venetoulis et al., 2004).

As with other indicators of sustainable development and,indeed, environmental impact appraisal tools more gen-erally, EF analysis has been closely scrutinised and subjectto criticism. Debate on the utility of ecological footprintingencompasses a range of issues, including its application inpolicy-making (e.g. Hanley, Moffatt, Faichney, & Wilson,1999; Moffatt, 2000; Opschoor, 2000), and its analyticalsoundness (e.g. van den Bergh & Verbruggen, 1999;Costanza, 2000; Ferguson, 1999, 2001; Levett, 1998; Rees,2000; van Vuuren & Smeets, 2000; Wackernagel, 1998b,1999; Wackernagel & Silverstein, 2000). It is clear,however, that EF calculations are becoming more frequentand better understood (e.g. Nijkamp, Rossi, & Vindigni,2004), with many new applications proposed (Wackernagel& Yount, 2000). Recently, for example, EF analysis hasbeen applied to situations as diverse as the examination ofexternal debt relief (Torras, 2003), and passenger transportin Merseyside, England (Barrett & Scott, 2003). Moreover,the technique has now been widely used by many privatesector organisations, NGOs, local authorities and educa-tional establishments in order to ‘‘illustrate and informmany different audiences about sustainable development’’(World Wildlife Fund-UK, 2002, p. 1).

3. EF applications in tourism

Notwithstanding the obvious potential relevance of EFanalysis to ST research and practice, very little attempt hasbeen made to examine ecological footprinting in thiscontext. In considering the ‘touristic EF’, Hunter (2002b,

p. 12) connects perceptions of ST with EF analysis, andargues that:

ythe fundamental contribution of ecological footprint-ing, currently absent from the great majority of tourismimpact studies, would be the ability to couch actual orpotential tourism activities in terms of widely scopedecological demand beyond the physical confines of anyparticular geographical setting (e.g. a destination area).

Despite the fact that travel, for example, is an inherentpart of the tourism industry, relatively little work hasaddressed the environmental impacts of tourist travel in thecontext of ST (Becken, 2002; Gossling, 2000; Gossling,2002; Hoyer, 2000; Simmons & Becken, 2004), and widerdemands upon natural resources, such as the implicationsof supplying energy, food and water to destination areas,are often excluded from studies of the sustainability oftourism products and destinations (e.g. Hunter, 2002a).Although purely theoretical in nature, Hunter’s (2002b)advocacy of the touristic EF as an important, globalenvironmental indicator of ST would appear to be borneout by the (albeit very limited) available evidence whereattempts have been made to calculate a tourism-related EF.As far as we are aware, only two such studies exist(Gossling, Borgstrom Hansson, Horstmeier, & Saggel,2002; World Wildlife Fund-UK, 2002).Gossling et al. (2002) provide a component-based

framework for the calculation of a leisure tourism EF forthe Seychelles, using secondary data sources. These authorsfound that the per tourist EF to be some 1.9 gha/year(similar to the fair earthshare value of some 2 gha/capita/year), with an average holiday in the Seychelles equivalentto 17–37% of the annual EF of a citizen of anindustrialised country. Well over 90% of the total leisuretourism footprint was found to be due to air travel to andfrom the destination. Critically, the authors conclude that,in part, the Seychelles maintains a high quality localenvironment for tourists at the expense of a much largerhinterland, and that traditional approaches used to assesssustainability, such as limits of acceptable change orenvironmental impact assessment, would fail to providethe required global perspective on the sustainability oftourism activity in the Seychelles. Indeed, focusing on theair travel component, the authors argue (p. 210) that‘‘[t]aking these results seriously, air travel should, from anecological perspective, be actively discouraged.’’ The keypoint here, echoing that made by Gossling et al. (2002), isthat locally derived and based indicators of ST are not, bytheir very nature, capable of providing a global perspectiveon tourism’s resource demands and impacts.Using a mix of primary and secondary data, the World

Wildlife Fund-UK (2002) study presents component-basedEF analyses of two typical, 2-week UK package holidayproducts (flying from Gatwick airport) to the popularMediterranean destinations of Majorca and Cyprus. TheEF per bed night for Majorca was found to be 0.03 gha,giving a total EF per guest over the 2-week holiday of


0.37 gha, while the corresponding values for Cyprus were0.07 gha and 0.93 gha, respectively. Accounting for ap-proximately 50% of the total EF in both cases, air travelwas found to be by far the largest single component of theholiday EF, although a much smaller proportion than thatreported by Gossling et al. (2002) for the Seychelles, giventhe relatively short flights involved to the Mediterraneanarea. It should also be noted that the work of Gosslinget al. (2002) included an additional radiative forcingallowance for aircraft emissions other than carbon dioxide,an approach apparently not adopted in the World WildlifeFund-UK (2002) study. Nevertheless, World WildlifeFund-UK (2002) conclude that the Majorca and Cyprusholidays account for around 20% and 50%, respectively,of the annual fair earthshare value, analogous to people‘‘spending 20 –50 % of their annual income in a 2-weekperiod!’’ (World Wildlife Fund-UK, 2002, p. v). Althoughthe report notes that judging the overall sustainability ofspecific holidays would require additional information onthe state of the local environment at the destination areaand the effects of tourism on the local community and onthe local and national economy, the conclusion is drawnthat whilst holidays involving air travel can be made more‘responsible’, it is unlikely that such holidays will be whollysustainable. Indeed, it is argued that:

In certain respects, holidays abroad typify the unsus-tainable nature of current developed country consump-tion patterns. If everyone in the world took an annualholiday similar to the Cyprus break, an extra half-planetwould be required to support the additional consump-tion involved in holidaying alone! (World WildlifeFund-UK, 2002, p. 13).

The two tourism-related calculations of the EF sum-marised above illustrate the potential benefits of adoptingthe EF as a key environmental indicator of ST: the EFprovides a means of identifying and understanding globallyexpressed demands on the biosphere brought about bytourism activity. Although very valuable, however, theseare isolated examples focusing on forms of mass tourism,and they did not set out to provide explicit guidance onhow EF analysis might be rapidly and routinely adopted inST assessments using existing, secondary data sources, andused in different contexts (e.g. to estimate the impact ofdifferent types of tourism product, or to examine thenational implications of tourism policy). Moreover, bothstudies appear to focus on and highlight the gross holidayEF. As illustrated by the above quotation, the WorldWildlife Fund-UK (2002) study uses the gross estimate of aholiday footprint to extrapolate impact in terms ofadditional, absolute, planetary space required. In otherwords, the holiday EF appears to be interpreted andpresented as a wholly additional ‘burden’ on the globalbiosphere. In reality, however, whilst on holiday (and asrecognised by World Wildlife Fund-UK (2002) in theirstudy), the tourist is clearly not producing at home thefootprint that would normally be created over the same

period. The key indicator for any tourism product ordestination area should therefore be the net, rather than thegross, EF generated. This distinction may appear ratherobvious, and in some scenarios the EF that would havebeen generated at home will be small compared to the grossholiday EF, making the difference between gross and netEF values similarly small. Yet as we seek to demonstratebelow, other, very different, outcomes for the apparentsustainability of tourism products are possible, and for thisreason it is critical to distinguish between gross and nettourism EF values. Moreover, as the net estimate providesthe more conservative basis for tourism EF accounting, it ismore in keeping with the tradition in EF analysis of erringon the side of caution when calculating the magnitude ofimpact of a particular activity or group (e.g. Monfreda etal., 2004).As with the calculations summarised above, the context

used for the methodology and examples provided in theremainder of this paper is international, holiday tourism.Secondary data, particularly for arrivals by air, arerelatively easily available for international tourism, andthe environmental costs of air travel are attractingincreasing attention and concern in the literature (e.g.Simmons & Becken, 2004).

4. The rapid calculation of an indicative net EF for

international tourism by air

The gross tourism EF can be seen as having two broadcomponents: that generated in the transit zone and that atthe destination area. The net tourism EF is simply the sumof the transit and destination area components, less thesource country EF for the period away from home.Potentially, there is the complication that a very smallfootprint will actually be generated by a tourist in thesource country even when the tourist is away from home;for example, by leaving on some home heating or securitylighting. The normal, major footprint components asso-ciated with energy use, transportation, food consumptionand the consumption of other raw materials, etc. will beabsent, however, so it would appear reasonable to assumethe home-based footprint to be negligible during theinternational tourist trip.The overall procedure for obtaining indicative estimates

of the annual equivalent net per capita EF for internationaltourism involving air travel is summarised below. Steps1–5, relating to the air travel EF, draw from a number ofsources, as indicated.

Transit zone:

(1)
Determine the total, round trip flight distance (km). (2) Obtain energy use per tourist (megaJoules, MJ) by
multiplying flight distance by an energy intensityconversion factor of 1.75–2.75MJ/km (see below).

(3)
Obtain the equivalent land area (ha of forest) pertourist (per year), by dividing energy use per tourist by73GJ/ha (i.e. the number of gigaJoules that 1 ha of

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forest will sequester, in carbon dioxide equivalent, peryear when liquid fossil fuel is combusted) (WorldWildlife Fund, 2000).

(4)
Allow for the additional radiative forcing of aircraftemissions other than carbon dioxide emitted at altitude(IPCC, 1999; Schumann, 1994) by multiplying by afactor of 2.7 (Gossling et al., 2002), giving a newestimate of required forest land (ha) (see below).
(5)
Multiply by the appropriate ‘equivalence factor’ (in2001 this was 1.38) to correct for forest land being moreproductive than average world space (World WildlifeFund, 2004), giving a final estimate of the transit zoneper tourist footprint in gha/year (see below).Destination area:
(6)
Use either the host or source country average per capitaEF as a proxy for the destination area EF of the tourist,reduced pro rata from an annualised value according tothe length of stay (see below).Net EF:
(7)
Use the average per capita EF of the source countryand the length of stay away from home to calculate theper tourist EF that would have been generated at homefor the period away (again reduced pro rata from anannualised value), and subtract this from the gross pertourist EF (the sum of steps 1–6).
Additional explanation is required for some of thesesteps. With reference to step 2, energy intensity is theenergy use per passenger km, accounting for average loadfactors and an average freight-to-passenger ratio (Becken,2002). Different conversion factors are suggested bydifferent sources and vary according to trip length. Forlong haul flights, Lenzen (1999) estimates 1.75MJ/km;1

Gossling et al. (2002), drawing on a range of sources,suggest 2.0MJ/km; and British Airways and Lufthansa citeoverall energy intensities of 2.03 and 1.86MJ/km, respec-tively (Green Globe, 2000, cited in Becken, 2002). Forshort haul flights, the Energy Efficiency ConservationAuthority (1999) calculates a figure of 2.75MJ/km in thecontext of New Zealand. The choice of figure to be appliedwill therefore depend upon the nature of the flight underconsideration. Except where noted, EF calculations thatappear later in this paper adopt an energy intensity value of2.0MJ/km, since this falls between the extremes notedabove and would seem most appropriate to the mediumand long haul flight scenarios presented.

Clearly, accounting as above for the transit EF solely interms of fuel/energy use by aircraft excludes othercontributions to the transit EF such as land travel to andfrom the airport, a contribution to airport infrastructureand energy use, and in-flight food and beverage consump-tion by tourists. The size of these components relative tothe fuel consumption footprint component of even theshortest of international flights is likely to be extremely

enzen’s conversion factor refers to secondary energy and thus

des energy used in extracting, refining and transporting fuels.

small (e.g. Gossling et al., 2002), and as such they are notconsidered further as part of the rapid EF estimationmethodology presented here.Step 4 recognises the emission or formation of sub-

stances other than carbon dioxide, such as nitrogen oxides,methane, ozone and water vapour, at high altitude whichcontribute to radiative forcing (global climate changepotential) by aircraft (IPCC, 1999). We have, therefore,adopted the approach of Gossling (2002) and Gosslinget al. (2002) whereby the contribution to radiative forcingby other substances effectively increases the forest arearequired, in EF terms, to combat global climate change.The IPCC (1999) has estimated, from a range of values,that aviation’s carbon dioxide emission is only some 37%of its total radiative forcing effect, and the use of a 2.7multiplier is therefore suggested in step 4 (100%/37% ¼ 2.7).With reference to step 5, it should be noted that

equivalence factors are specific to each year for whichnational per capita EFs are produced. The latest nationalper capita EF estimates although produced in 2004 (WorldWildlife Fund, 2004) were actually for the year 2001, andfor this year the equivalence factor was determined to be1.38. This highlights the broader point that care should betaken to ensure that a consistent reference year is used forall aspects of a tourism EF estimate, where applicable; i.e.if combining a per tourist EF estimate with actualinternational tourist arrival numbers and length of stayinformation in order to estimate the total EF of interna-tional tourism from a particular source country.With this important caveat in mind, the destination area

per tourist footprint (step 6) can be estimated usingcompound national footprint data (e.g. Venetoulis et al.,2004; World Wildlife Fund, 2004) in one of two ways. Itcan be assumed either that, on average, tourists consumeresources at the destination in approximately the samemanner and extent as they would at home, or in the samemanner and at the same rate as the average resident of thehost country. In situations where the holiday product is ofan up-market, luxury type but is situated in a compara-tively poor country where the per capita EF is small, theformer approach may be the most appropriate (Gosslinget al., 2002). However, in the first instance, we adopt thelatter alternative (Hunter, 2002b), as this provides moreconservative net EF estimates, in keeping with the generaltradition of erring on the side of caution when undertakingEF analysis. This said, net EF estimates that follow wouldbest be viewed as potential minimum values, and we returnto the implications of assuming higher resource consump-tion by the tourist at the destination later in the paper.Whichever alternative is used, the average annual percapita footprint of source or host nation is reduced fromthe annualised value on a pro rata basis according to thelength of stay. Data on average length of stay (bed nights)are commonly available from national tourism organisa-tions, or are advertised as a matter of course for individualholiday products.


As a partial check, it is interesting and informative tocompare EF values obtained using the above methodologywith those obtained in an actual study. In the case of theWorld Wildlife Fund-UK (2002) work, a quite detailed,component-based approach was employed in calculatingthe EF whilst at the destination area, using, for example,data obtained from hotels on the use of various naturalresources. Whilst the precise basis of the air travel EFcalculation is unclear, a check against the destination areaEF is still possible. Majorca is used as an illustration sinceno national EF values are available for Cyprus. Given thatthe annual average per capita footprint of a Spanish citizenwas some 4.80 gha in 2001 (World Wildlife Fund, 2004),Step 6 of our methodology suggests that the destinationarea per tourist EF for a two-week holiday in Majorca canbe estimated as 0.18 gha (14/365 days � 4.80 gha).2 Thiscompares well to the World Wildlife Fund-UK (2002)destination area EF of 0.16 gha.

5. Examples of the application of the net tourism EF

methodology

There are very many potential illustrations of the EFapplied to tourism. With per capita national EF data, flightdata and length of stay information, it is possible toestimate—albeit crudely at this stage—a credible minimumvalue for the net tourism EF of an international tourist onany given holiday product. With enough additionalinformation on the number and source of internationaltourist arrivals by air, the EF of a destination area (evenhost country) can be estimated. Additional primary data,not to mention the refinement and development of themethodology presented in this paper, will permit thegeneration of increasingly sophisticated EF estimates. Inthe meantime, the intention of the following paragraphs ismerely to direct the reader to a range of possible uses of thetourism EF.

5.1. Calculating the net EF

A useful starting point is to re-visit an existing tourismEF study and consider the importance of using the net,rather than the gross, EF as the more appropriate,conservative indicator of environmental sustainability. Ofthe two existing studies outlined above, the World WildlifeFund-UK’s (2002) work provides the simpler basis forconsideration as its focus is the individual product,involving one source country (the UK), rather than thedestination as a whole. The gross per tourist EFs for a 2-week holiday to Majorca and Cyprus were found to be0.37 gha and 0.93 gha, respectively. Since the annualaverage per capita footprint of a UK citizen in 2001 was5.40 gha (World Wildlife Fund, 2004), the average tourist

2It is unclear from the World Wildlife Fund-UK (2002) report for which

year data was collected. It seems reasonable to assume that EF data for

the year 2001 is suitable.

over a 2-week period at home would normally generate anEF of some 0.21 gha (14/365 days � 5.40 gha). The net pertourist EFs over the 2-week holiday are thus 0.16 gha forMajorca and 0.72 gha for Cyprus. This reveals the net EFvalues as a percentage of gross values to be 43% forMajorca and 77% for Cyprus. In the case of Majorca,therefore, the additional impact of the holiday maypotentially have been under half of that reported usingthe gross EF value.

5.2. Extending existing studies

Another opportunity to apply the EF concept to tourismis to extend existing studies to encompass a tourism EFcalculation. Becken (2002), for example, provides a veryuseful and detailed examination of the energy use andcarbon dioxide emissions associated with international airtourist travel to New Zealand in 1999. Her data can beused to estimate in gross EF terms the impacts of NewZealand’s international tourism trade (Table 1). Becken’scalculation of energy used in the transit zone from eachmajor source country can be taken in conjunction withtotal air arrivals data to estimate average per tourist energyuse in transit, some 34.9GJ. This translates to an averagetransit EF of around 1.76 gha per tourist, using theequivalence factor of 1.35 for 1999 (World Wildlife Fund,2002). An estimate of the average per capita EF of a NewZealand citizen for the year 1999 is 8.68 gha (WorldWildlife Fund, 2002). Using this value, and an averagelength of stay for all international tourists to New Zealandof 18 bed nights (Tourism Research Council New Zealand,2004), it can be estimated that the average gross EFper international tourist to New Zealand around theturn of the century was 2.19 gha, higher than the fairearthshare value of some 2 gha/year. Approximately 80%of the gross per tourist EF can be attributed in this caseto the flight component, reflecting New Zealand’s rela-tive geographic isolation from many major internationaltourist markets.Extending this analysis to individual source countries

also allows the calculation of net tourist EFs becausenational EF data can be used. Table 2 presents an estimateof the average net EF per UK tourist for a stay of 28 nights(Tourism Research Council New Zealand, 2004) in 1999.In this case, an estimated gross EF per tourist trip of4.15 gha is obtained, with some 84% of this (3.48 gha)accounted for by the transit component. At home, a UKresident in 1999 would on average have generated an EFover the same time period of approximately 0.41 gha(World Wildlife Fund, 2002), producing a net per touristEF of 3.74 gha. This value represents around 70% of theannual average per capita footprint of a UK resident at thetime. From an environmental perspective, even allowingfor widely differing interpretations of the meaning ofsustainable tourism, it is difficult to see this outcome asanything other than indicative of a highly unsustainableaspect of New Zealand’s tourism industry.

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Table 1

Average gross EF per international tourist per year to New Zealand in 1999 for a stay of 18 nights, using the source study’s original energy intensity

conversion factor of 1.75MJ/km

Step

Transit zone

2 Energy use per tourist (55.6 PJ/1,591,650 visitors) 34.9GJ

3 Required forest land 0.48 ha

4 Air transport EF on forest land 1.30 ha

5 Air transport EF in world average space 1.76 gha

Destination area

6 Host country per capita EF for average length of stay (18 nights) 0.43 gha

Gross EF

Sum of (5) and (6) above 2.19 gha

Sources: Becken (2002), World Wildlife Fund (2000), and authors’ calculations.

Table 2

Average net EF per UK tourist per year to New Zealand in 1999 for a stay of 28 nights, using the source study’s original energy intensity conversion factor

of 1.75MJ/km

Step

Transit zone

1 Round trip flight distance 39,910km

2 Energy use per tourist (167,202 visitors) 69,843MJ (69.8GJ)

3 Required forest land 0.96 ha

4 Air transport EF on forest land 2.58 ha

5 Air transport EF in world average space 3.48 gha

Destination area

6 Host country per capita EF for average length of stay (28 nights) 0.67 gha

Gross per tourist EF 4.15 gha

Net EF

7 Deducting home country per capita EF for average length of stay (0.41 gha) 3.74 gha

Sources: Becken (2002), World Wildlife Fund (2000), and authors’ calculations.

C. Hunter, J. Shaw / Tourism Management 28 (2007) 46–5752

Building on the claim that the EF is a useful educationaltool (e.g. Chambers et al., 2000), there is also scopethrough the net tourist ecological footprint for policymakers to better understand the environmental implica-tions of their decisions. To illustrate, it is not uncommonfor national tourism organisations and governments totarget key overseas markets in their promotion anddevelopment strategies (see Scottish Executive (2000)targets relating to encouraging visitors from the USA,Germany and France). In the New Zealand context, the EFimplications of encouraging a (for the sake of argument)10% increase in the number of UK tourists over a giventime period can be estimated very quickly.3 UK touristarrivals to New Zealand in 1999 were 167,202 (Becken,2002), resulting in a total tourism EF for UK tourists ofsome 625, 335 gha (167,202 � 3.74 gha). The suggestedincrease in tourist numbers would thus generate an

3Assuming roughly static parameters used in the methodology presented

here, although changes in parameters could be built in to EF forecasts.

additional footprint of around 62,500 gha, although someallowance needs to be made for ‘opportunity cost’ tripswhich otherwise would have been taken by the extravisitors.This can be compared with, for example, the effects of

aiming for a 10% increase over the same time period inAustralian tourists. The 521,912 Australian tourists visitingNew Zealand in 1999 (Becken, 2002), each of whoseaverage stay of 12 nights (Tourism Research Council NewZealand, 2004) generated a net EF of around 0.66 gha(Table 3), were responsible for a total footprint ofapproximately 344,462 gha. The suggested increase in thiscase would result in an additional footprint (againexcluding trips which otherwise would have been taken)of around 34,500 gha being generated. Such increases infootprint magnitude can easily be compared by interestedparties seeking to evaluate the impacts of internationaltourism, and used to inform their marketing or lobbyingactivities. In this very simple example, it appears that,notwithstanding the longer average length of stay of UK


visitors, achieving a 10% increase in Australian rather thanBritish visitors would result in both economic benefit (moreadditional bed nights—626,292 as opposed to 468,160) andless additional global ecological impact (a smaller overallfootprint).

5.3. Rethinking the impact of ecotourism?

In the case of New Zealand, international tourismgenerally involves long flights and also occurs in thecontext of a country with a high per capita nationalfootprint, resulting in large net and gross tourism EFs. Yetvery different findings and sustainability implications occurin other situations. Table 4 considers international tourismfrom a developed (high footprint) country, the USA, to adeveloping (low footprint) country, Costa Rica, involving arelatively short flight from Florida, and using the latestnational EF data for 2001. According to World WildlifeFund, (2004), the USA has one of the highest per capitaEFs in the world, 9.5 gha/year, whereas Costa Rica’s, at

Table 3

Average net EF per Australian tourist per year to New Zealand in 1999 for a sta

factor of 1.75MJ/km

Step

Transit zone

1 Round trip flight distance

2 Energy use per tourist (521,912 visitors)

3 Required forest land

4 Air transport EF on forest land

5 Air transport EF in world average space

Destination area

6 Host country per capita EF for average len

Gross per tourist EF

Net EF

7 Deducting home country per capita EF for

Sources: Becken (2002), World Wildlife Fund (2000), and authors’ calculation

Table 4

Average net EF per American ‘eco-tourist’ per year travelling from Miami to

Step

Transit zone

1 Distance

2 Energy use per tourist




Destination area

6 Host country per capita EF for average l


Net EF

7 Deducting home country per capita EF f

Source: authors’ calculations using national EF data for 2001 from World W

2.1 gha/year, is around the fair earthshare value. In thisillustration, it is assumed (initially) that the touristconsumes resources at a similar rate to the averagedestination country resident, a not unreasonable scenariogiven that Costa Rica is a well-known eco-tourismdestination (e.g. Weaver, 1999) and that low impact/consumption eco-tourism products exist there (Buckley,2003).For a stay of 14 nights, the average gross per tourist EF

would equate to around 0.45 gha (Table 4) but, interest-ingly, the net value is potentially as low as 0.09 gha, areduction of some 80%. If the holiday period is stretched to3 weeks, the net per tourist EF potentially becomesnegative (�0.06 gha) suggesting, rather surprisingly, thatthis particular holiday scenario might actually reduce theconsumption of global biological resources compared withthat of an average USA citizen for the same time period athome. Arguably, this would in fact be the case for shorterlengths of stay if the tourists were more affluent and hadgenerally higher individual EFs than the USA average.

y of 12 nights, using the source study’s original energy intensity conversion

6892km

12061 MJ (12.06 GJ)

0.17 ha

0.46 ha

0.62 gha

gth of stay (12 nights) 0.29 gha

0.91 gha

average length of stay (0.25 gha) 0.66 gha

s.

Costa Rica for a stay of 14 nights

3604 km

7208 MJ (7.2 GJ)

0.1 ha

0.27 ha

0.37 gha

ength of stay (14 nights) 0.08 gha

0.45 gha

or average length of stay (0.36 gha) 0.09 gha

ildlife Fund (2004).


Evidence suggests that eco-tourists are often bettereducated and more affluent than other tourist types (e.g.Page & Dowling, 2002).

Clearly it is important not to overplay the significance ofthese illustrations because the transit zone EF—principallydetermined by the length of flight between the origin anddestination countries—is critical to the overall net touristEF. Recent critiques of eco-tourism (e.g. Mowforth &Munt, 2003; Simmons & Becken, 2004) have built uponearlier attacks focusing on the impacts of its frequentreliance on long haul air travel. Hall and Kinnaird (1994,cited in Mowforth & Munt, 2003) argue that ‘‘travel to eco-tourism destinations undertaken in fuel-hungry aeroplanesis in itself incompatible with ecological sentimentsy. Theextolling of eco-tourism developments in faraway lands...may be thus viewed as paradoxical.’’ Eco-tourists travellingfrom, say, London to the interior of Brazil would create asizeable EF—broadly equivalent to the fair earthsharevalue—even if their activities within the host countrycreated a negligible footprint (see, for example, Wolfe,2004) and the length of their stay was a month or more(Table 5).

Furthermore, it has so far been assumed that resourceuse by the eco-tourist at the destination is relativelyresource-conservative, reflecting that of the host country.Yet, eco-tourism activities may also occur in much moreup-market, resource-demanding contexts with touristsliving much more luxurious lifestyles than locals (e.g.Kontogeorgopoulos, 2004), and tourists in general oftenexhibit rather hedonistic behaviour. It could be argued,therefore, that in many circumstances—particularly invol-ving ‘popular’ or ‘soft’ (Page & Dowling, 2002) forms ofeco-tourism—it would be more appropriate to adopt theaverage per capita EF of the source country as a proxy forthe EF generated at the destination (Gossling et al., 2002).Thus, the source country per capita EF would be used inboth steps 6 and 7 of the above procedure, and the nettourism EF becomes the same as the transit zone EF

Table 5

Average net EF per UK ‘eco-tourist’ per year travelling from London to Man

Step

Transit zone

1 Distance

2 Energy use per tourist




Destination area

6 Host country per capita EF for average le


Net EF

7 Deducting home country per capita EF fo

Source: authors’ calculations using national EF data for 2001 from World Wi

Wolfe (2004).

provided by steps 1–5, irrespective of the length of stay.Consequently, the net EF can never be negative, and issimply a function of distance travelled by air. Changing theassumption about the nature of resource demand by(eco)tourists at the destination in this way would obviouslyproduce higher net EF estimates. The Miami to Costa Ricascenario, for example, would now give a net EF estimate of0.37 gha, rather than 0.09 gha as previously (Table 4). Withthe longer flight, the difference for London to Manaus(2.46 gha, as compared to 2.05 gha; Table 5) is less marked.Potential differences associated with different assump-

tions about tourist consumption at the destinationdemonstrate the need for care in understanding the natureof the tourism product and in applying the EF methodol-ogy. Nevertheless, it is important to recognise that forsome types of ‘adventure/hard’ eco-tourism product (e.g.Page & Dowling, 2002) resource use at the destination isakin to that of the host population and, in contrast to theearlier illustrations provided above, these may have thepotential to offer a positive contribution to environmentalsustainability in terms of global resource use. We wouldstress again, however, that EF estimates obtained using theprocedure reported here are best regarded as providingpotential minimum values, particularly if host country EFdata are used to approximate resource use by tourists at thedestination. Certainly, and despite the tradition in EFanalysis to provide conservative estimates, there arecircumstances where the use of the source country EF asa proxy for consumption at the destination provides themore realistic alternative. On the other hand, it may berather too easily assumed that hedonistic behaviour bytourists will have a significant effect: host country nationalEF values, and therefore proxy consumption by tourists atthe destination, reflect the nature of consumption as well asthe magnitude of consumption. Eating and drinking morelocally/nationally produced food and beverage thanresidents, for example, is likely to have a proportionatelysmall impact on the destination EF. Where food and drink

aus, via Rio de Janeiro, for 28 nights

24,179km

48,358 MJ (48.4 GJ)

0.66 ha

1.78 ha

2.46 gha

ngth of stay (28 nights) Negligible

2.46 gha

r average length of stay (0.41 gha) 2.05 gha

ldlife Fund (2004), and indicative resource consumption information from


are imported for tourists, however, and the energyembodied in these products is therefore high, tourismmight generate a large additional EF at the destination.

6. Conclusions

It is likely that the use of ST indicators that are whollyderived from a local perspective and through localprocesses of participation will underplay the recognitionof tourism activity as a user of natural resources at theglobal scale. Furthermore, different sets of locally derivedand contextualised indicators make it less easy to comparedifferent areas or products in terms of environmentalimpact and sustainability. At the very least, therefore, itwould appear appropriate to recognise the potentialbenefits of the widespread adoption of a unique indicatorcapable of providing a global perspective on tourism’senvironmental impact. The use of EF analysis as anindicator of environmental sustainability allows quantita-tive comparison between different impact components (e.g.the transit zone and destination area footprints), and canprovide an indication of the overall ecological impact oftourism products on global biological resources. Thesimple methodology outlined in this paper could be widelyadopted for the environmental appraisal of internationaltourism products and destination areas. It should bestressed again, however, that the methodology is as yetrather crude, providing indicative estimates of the likelyminimum potential tourism EF.

This said, it would appear critical in any tourism EFanalysis to determine the net tourism EF; i.e. to account forthe EF that a tourist would normally produce at homewhilst s/he is abroad. Otherwise, the additional burden onthe planet’s resources created by the tourist trip/productmay be greatly over-estimated, in contravention of thetradition in EF analysis work. Furthermore, as we soughtto demonstrate above, it may be that some tourismproducts could actually alleviate the consumption of theworld’s biological resources. The potential for this rathersurprising outcome is greatest for some products to low EFcountries, but involving tourists from high EF (generallydeveloped) countries, and where short to medium haulflights are involved if the length of stay is of sufficientduration. By way of defining one avenue for futureresearch, some types of ‘hard’ (Page & Dowling, 2002)eco-tourism product, at least on the face of it, exhibit thenecessary characteristics for a ‘zero’ or ‘negative net EF’outcome. However indicative it may be at this stage, EFanalysis offers the prospect of more ‘rounded’ evaluationsof eco-tourism (and other tourism) products, and suggeststhat any automatic dismissal of eco-tourism on environ-mental grounds—certainly if short to medium haul flightsare involved—may be rather premature. Furthermore, it isby no means clear that even eco-tourism productsinvolving long haul flights will, in net EF terms, tend tobe more environmentally demanding than many masstourism products. What is clear, however, is the danger of

assessing the sustainability of tourism products withoutconsidering the transit zone.Avenues for further research in the application of EF

analysis to tourism are many and varied. Many moresimple estimates of the EF of different tourism productscould be made using, for example, the methodologyoutlined in this paper. These might also attempt toincorporate different modes of transport to the destination.Ways of estimating the EF of domestic tourism activitiescould also be explored. Perhaps the greatest need, however,is to collect ‘real world’ primary data for the resourcesconsumed during the life-cycle of a range of differenttourism products, including low-impact, ‘genuine’ eco-tourism holidays of various kinds, and very up-market,luxury hotel-type holiday resorts.

Acknowledgements

We would like to thank Martin Mowforth for comment-ing on an earlier draft of this paper, and Tristan Wolfe forhis insights into adventure- and eco-tourism in SouthAmerica. Thanks also to Pam Wight for a useful discussionof the ecological footprint applied to tourism, and to DanMoran, Mathis Wackernagel and Thomas Wiedmann fortheir insights into air travel footprinting and carbonsequestration rates. Of course the usual disclaimer applies.

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