Consumer Behavior in Tourism Symposium ESTIMATING THE CARBON FOOTPRINT OF TOURISM IN SOUTH TYROL Mattia Cai

Transcription

1 Consumer Behavior in Tourism Symposium 2013 ESTIMATING THE CARBON FOOTPRINT OF TOURISM IN SOUTH TYROL Mattia Cai

2 Overview Aim: Quantify the greenhouse gas (GHG) emissions associated with tourism in South Tyrol (ST) Methodological approach: Input-Output (IO) analysis Multi-regional model 1

3 South Tyrol and tourism Population 505,000 Origin Visitors (mln, 2008) Nights (mln, 2008) South Tyrol Other Total

4 The contribution of tourism to South Tyrol s economy Value added (% of total) Direct 1,731 mln (11.2%) Direct and indirect 1,903 mln (12.4%) Employment (% of total) 41,300 FTE (15.3%) Source of data: ASTAT (2012). Impatto economico del turismo. Astat Info nr

5 The carbon footprint of tourism Unfortunately, there has been little attempt to measure CO 2 emissions associated with individual tourism destinations (Dwyer et al. 2010) Some notable exceptions: Jones and Munday (2007), Wales Dwyer et al. (2010), Australia Whittlesea and Owen (2012), South West England 4

6 Carbon footprints and IO models The use of IO models to analyze carbon footprints is well established Hendrickson et al. (2006) Minx et al. (2009) Applications to tourism using multiregional IO at a very local level? 5

7 Main practical difficulties No tourism industry in official statistics. Very limited data availability at the subnational level. 6

8 Outline of presentation Model structure and data requirements Preliminary results the estimated carbon footprint of tourism in ST Concluding remarks (Current) limitations, ongoing work, potential extensions 7

9 STRUCTURE AND DATA REQUIREMENTS OF THE MODEL

10 IO modeling and carbon footprints Money spent by tourists on different products in ST Multi-regional IO model Estimates of GHG emission (direct and indirect) 59 industries (NACE rev. 1.1) 5 regions Why multiple regions? 9

11 Emission factors of agriculture V. d'aosta Lombardia Piemonte Sardegna Friuli V.G. Molise Umbria Veneto Basilicata Marche Emilia R. Abruzzo Lazio Bozen Campania Toscana Puglia Sicilia Trento Calabria Liguria in Italy, (direct) tons of CO2 equivalent per mln EUR of value added Source of data: ISTAT (2009) NAMEA: emissioni atmosferiche regionali 10

12 Emission factors of energy Liguria Puglia Sicilia Friuli V.G. Sardegna Umbria Veneto Lazio Calabria Toscana Emilia R. Lombardia Piemonte Abruzzo Marche Campania Molise Basilicata Trento Bozen V. d'aosta production in Italy, (direct) kt of CO2 equivalent per mln EUR of value added Source of data: ISTAT (2009) NAMEA: emissioni atmosferiche regionali 11

13 Regions of the model South Tyrol Northwest Northeast Rest of country + REST OF WORLD 12

14 Data requirements of the model 1. Final demand by tourists by industry 2. Interregional matrix of input coefficients 3. Regional emission factors by industry 4. Rest of the world region 13

15 1. Tourism demand by industry, 2010 Agriculture 2% Other 14% Transport and storage 5% Food, beverages and tobacco 6% 3,460 mln Hotels and restaurants 62% Trade 11% Source of data: ASTAT (2013), Tavola Input-Output per lalto Adige Astat info nr

16 2. Interregional input coefficients Input coefficients estimated as: Product i from region r needed to produce one unit of product j in region s i needed per unit of j in Italy (from national IO table) Share of all i used in s that comes from r (Laboriously estimated from Bank of Italy industry survey data) 15

17 3. Emission factors 2005 emission data at regional level from ISTAT carbon dioxide (CO 2 ) methane (CH 4 ) nitrous oxide (N 2 O). Updated to 2008 (base year of the model) 16

18 4. The rest of the world Assumed German technology and emission factors (WIOD data) Working on improved representation more foreign regions in the model 17

19 PRELIMINARY RESULTS

20 Direct emissions of ST s tourism Direct emissions (kt CO 2 e) Tourism (2010, modeled) All productive activities (2005, ISTAT) 169 1,892 19

21 Direct emissions by industry Other 10% Hotels and restaurants 29% Agriculture 23% 169 kt CO 2 e Transport and storage 22% Trade 10% Food, beverages and tobacco 6% 20

22 Direct and indirect emissions of ST s tourism Total emissions (% direct) Tourism (2010, modeled) 1,262 kt CO 2 e (13.4%) Carbon intensity 372 t CO 2 e/mln of output Emissions per visitor* kg/visitor Emissions per night* 38.7 kg/night 21

23 Carbon intensity of ST s industries Non metal mineral prod. Agriculture Food, bev & tob. Other mining Electricity, gas, water Chemicals Petroleum prod. Other services Plastics and rubber Metal prod. Transport equipment Wood Leather Transport and storage Tourism Pulp and paper Textiles Machinery Other manufacturing Hotels and restaurants Construction Electrical equipment Fishing Trade Business activities Health Public adminstration Finance Education Real estate, renting (direct + indirect) t of CO2e per mln EUR output

24 Carbon emissions of ST s tourism by industry and region Agriculture Energy, gas, water Mining and quarr ying Hotels and restaurants Transport and storage Food, beverage, tob. Comm., soc., pers. serv. Other manufacturing Other South Tyrol North east North west Rest of the country Rest of the world Carbon emission from tour ism in ST (kt CO2e)

25 CONCLUDING REMARKS

26 Some issues with the current version of the model Overestimating import dependence of South Tyrol? Results sensitive to choice of rest of the world technology Treatment of emissions from transport 25

27 Potential extensions (subject to data availability) Include other environmental externalities Carbon footprint of more narrowly defined products or types of tourism Easy to replicate in other parts of the countrys 26

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29 Familiar limitations of IO models Linearity Fixed interregional trade patterns Underlying data quality issues 28

30 Emission factors of hotels and V. d'aosta Umbria Calabria Basilicata Molise Abruzzo Puglia Trento Campania Marche Emilia R. Piemonte Veneto Toscana Liguria Friuli V.G. Bozen Lombardia Sicilia Lazio Sardegna restaurants in Italy, tons of CO2 equivalent per mln EUR of value added Source of data: ISTAT (2009) NAMEA: emissioni atmosferiche regionali 29