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Estimating the carbon footprint and energy consumption of Taiwan tourism Dr. Ya Yen Sun Assistant Professor, Department of Kinesiology, Health and Leisure Studies National University of Kaohsiung, Taiwan 2011.10.17 Michigan State University

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Estimating the carbon footprint and energy consumption of Taiwan tourism

  • Dr. Ya‐Yen Sun

Assistant Professor, Department of Kinesiology, Health and Leisure Studies National University of Kaohsiung, Taiwan 2011.10.17 Michigan State University

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Contents

  • 1. Introduction
  • 2. Environmental Extended Input‐Output Model
  • 3. Literature review
  • 4. Case study‐ electricity usages and its associated CO2

emission of visitors in Taiwan

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Introduction

The tourism sector has an important place in that (Kyoto Protocol) framework, given its global economic and social value, its role in sustainable development and its strong relationship with climate.

2003 Djerba Declaration by World Tourism Organization (WTO) and United Nationals Environment Programme (UNEP)

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Kyoto Protocol (KP)

> Annex I countries agreed to reduce their collective GHG emissions by 5.2% of their 1990 levels by the end of 2012.

Greenhouse gas (GHG) – CO2, O3, CH4, N2O, CFCs, PFCs, FCs, HCFCs, and SF6 KP only controls CO2, CH4, N2O, HFCs, PFCs, SF6

> Carbon footprint ‐ the amount of GHG emissions associated with the production and consumption of goods and services at the level of an individual firm, industry or entire economy

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WTO‐UNEP CO2 estimates with global tourism

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The accurate information on the carbon footprint of each of the various sectors that comprise “the tourism industry” is essential for

The mitigation and regulation of GHG emission, The securing of financial resources to assist regions and businesses

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Contents

  • 1. Introduction
  • 2. Environmental Extended Input‐Output Model
  • 3. Literature review
  • 4. Case study‐ electricity usages in Taiwan
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Environmentally Extended Input‐Output Model (EEIO)

The basic idea of EEIO models

> Augmenting the technical coefficients matrix with additional rows and / or columns to reflect energy consumption or pollution production.

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Generalized IO model

R = resource input coefficient = resource intensity per dollar of output Q= pollution output coefficient = pollution intensity per dollar of output

Direct impact coefficient Industry A Industry B Direct impact per $ of output Energy Oil 0.2 0.3 BTUs (British thermal unit ) Coal 0.1 0.4 BTUs Pollution CO2 0.5 1.1 tonnes SOx 0.7 0.7 tonnes

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Calculation formula ‐ type I multipliers

Type I resource and pollution multipliers R* = R(I‐A)‐1 = M (X)‐1(I‐A)‐1 Q* =Q (I‐A)‐1 = N (X )‐1(I‐A)‐1

Where X = Total output A = Technical input coefficients M = Flow‐in resource matrix N = Flow‐out commodity matrix R* = The total amount of resource required, directly and indirectly, per dollar’s worth of output by industry Q* = The total amount of ecological commodity emitted, directly and indirectly, per dollar’s worth of output by industry

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Total effects

Total amount of resources required: R* (I‐A)‐1Y Total amount of pollution produced: Q* (I‐A)‐1Y > Production driven:

Total amount of ecological resources = R* [(I‐A)‐1Y] Total amount of ecological emission = Q* [(I‐A)‐1Y]

> Consumption driven:

Total amount of ecological resources = [R(I‐A)‐1]* Y Total amount of ecological emission= [Q(I‐A)‐1]* Y

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Contents

  • 1. Introduction
  • 2. Environmental Extended Input‐Output Model
  • 3. Literature review
  • 4. Case study‐ electricity usages in Taiwan
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Literature Review

EEIO studies on tourism ‐ a relative new research topic

Articles

Becken & Patterson (2006) Jones & Munday (2007) Kelly & Williams (2007) Dwyer, Forsyth, Spurr, & Hoque (2010) Konan & Chan (2010)

Destination

New Zealand Wales, UK Whistler, Canada Australia Hawaii

Reference Year

1997/98 2000 2000 2003‐2004 1997

Environment al variables

Carbon dioxide; energy consumption Carbon dioxide, waste

  • utputs

Carbon‐dioxide equivalent GHG emission for energy and the disposal of solid waste Green House Gas (GHG) Seven fuel types and three GHG gases (CO2, Methane and NOx)

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Differences across the previous studies

  • 1. Analysis method

Top‐down approach Bottom‐up approach

  • 2. Research scope
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The bottom‐up analysis

> The bottom‐up analysis computes energy use and GHG emission based on information on energy end‐ uses of typical tourism industry and tourist behavior.

1. Sample transportation, accommodation and attraction business to calibrate the average energy efficiency and coefficients with respect to per dollar sales (industry analysis) 2. Combine with tourist travel behavior and visitor volume (tourist analysis) to estimate total energy use in the tourism sector.

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The top‐down analysis

> The second approach, referred as Integrated Economic‐Environmental Accounting, allows the assessment of tourism as a sector within a comprehensive national economic platform.

1. Adopt Tourism Satellite Accounts and national EEIO table 2. Allocate the proportional sales, energy use and GHG emission to the the tourism industry by the TSA tourism ratio.

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Advantages of the bottom‐up approach

> Detailed energy information can be gathered using business surveys to reflect the regional characteristics in production

  • function. For example, the transportation category can be

differentiated by domestic air, private air, rental car, coach, train, motorcycle, scheduled bus, or ferry, depending on the transportation modes that are best utilized in the area. > The linkages of recreational behaviors and GHG emission can be established. It helps to trace the GHG emission due to behavior changes overtime.

Whistler, British Columbia, Canada (Kelly & Williams, 2007) 2004 World Rally Championship (Jones, 2008) Hawaii (Konan & Chan, 2010)

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Advantage of the top‐down method

> The top‐down analysis is best suited for comparing the tourism’s eco‐efficiency with other sectors, or formulating the macroeconomic instruments such as carbon charges on the tourism industry at the national level.

GHG estimation for New Zealand (Becken & Patterson, 2006) Wales, UK (Jones & Munday, 2007) Australia (Dwyer, et al., 2010)

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Differences across previous studies

1. Analysis method 2. Research scope

  • tourism‐characteristic industries
  • tourism‐characteristic industries & tourism‐related industries
  • Whether to include air transportation, especially international aviation
  • Residents vs. tourists
  • Internal destination energy consumption vs. employee commuting to

and from the destination vs. visitor travel to and from the destination.

  • Direct effects
  • Direct + indirect effects
  • Direct + indirect + induced effects
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Contents

  • 1. Introduction
  • 2. Environmental Extended Input‐Output Model
  • 3. Literature review
  • 4. Case study‐ electricity usages & CO2 emission for

tourists in Taiwan

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Study purposes of the Taiwan project

1. To construct the Environmental Extended Input‐Output Model (EEIO) as a life‐cycle assessment tool for Taiwan.

  • 10 energy types
  • GHG emission

2. To evaluate the amount of carbon emission based on different visitor segments per capita including

  • Inbound tourist vs. domestic tourist
  • Visitor segments based on nationality and travel purposes
  • Per dollar tourist spending vs. per dollar output of the non‐tourism

injection

  • Per tourist in Taiwan vs. a global average tourist journey

3. To estimate total carbon emission associated with tourism in 2006

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Data sources

  • 1. 2006 National Taiwan IO table
  • 2. 2006 Taiwan Tourism Satellite Account
  • 3. 2006 Energy consumption data
  • Coal
  • Crude oil and petroleum products (7 types)
  • Natural gas
  • Electricity
  • 4. 2006 Energy converting coefficients
  • Parameters that can covert each energy use to the emission of

GHG

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Analytical framework

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An example‐ The tourism electricity consumption in Taiwan

Party-trip consumption in Taiwan (NT$)

China ferry passenger Kaohsiung day visitors Domestic visitors International visitors World Games participant Accommodation 4,000 1,276 13,659 3,208 Food & beverage 2,764 771 1,395 6,565 2,399 Transportation 1,635 288 944 4,568 599 Entertainment 1,207 90 427 2,399 476 Shopping 25,703 570 1,728 10,509 4,502 Travel agency 2,330 157 1,760 185 Total 37,640 1,720 5,928 39,460 11,370

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Economic & environmental effects

Per 1000 party trips Sales ($ million's) Jobs Electricity (000 kwh) CO2 emission (000 kg) Multipliers (kwh per dollar direct sales) Direct effects China ferry passenger $34.3 22.5 217.8 139.0 0.00635 KHH domestic visitors $1.6 1.2 6.4 4.1 0.00400 Domestic visitors $5.7 4.2 43.2 27.6 0.00758 International visitors $38.1 28.0 369.2 235.6 0.00969 World Games participatns $10.8 7.4 96.0 61.3 0.00889 Direct + Indirect effects China ferry passenger $57.8 32.4 326.2 208.1 0.00951 KHH domestic visitors $2.8 1.8 11.6 7.4 0.00725 Domestic visitors $9.6 5.8 60.6 38.7 0.01063 International visitors $63.8 38.5 487.5 311.0 0.01280 World Games participatns $18.4 10.7 131.8 84.1 0.01220

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Direct & Indirect Effects

Aggregate I‐O sectors

Sales ($ million's) Jobs Personal Income ($ million's) Electricity (1000 Kwh) CO2 emission (000 kg)

Services Lodging

22.2 15 6.3 440 281

Food & beverage

14.2 13 4.5 43 28

Transportation

9.9 7 5.4 31 20

Leisure services

4.8 4 1.8 30 19

Travel agency service

4.5 7 1.4 5 3

Retailing

22.1 16 7.7 37 23

Financial services

6.3 1 1.2 3 2

Other services

10.5 6 3.5 34 22

Manufacturing Manufactured food

7.9 2 0.7 49 31

Clothing

1.2 1 0.3 9 6

Recreation equipment

2.0 1 0.4 5 3

Handicraft products

9.5 4 0.5 85 55

Rest manufacturing sectors

28.2 6 3.1 201 128

Farming, foresting, finishing

4.0 5 1.0 16 10

Utility

4.3 0.2 29 19

Construction

1.0 0.2

Total

152.5 89 38.3 1,018 649

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Challenges in implementation

  • 1. The incompatibility across data sources

Energy data – 50 sectors IO table – 166 sectors Electricity data – 200 sectors

  • 2. Visitor expenditure data cannot directly link with IO

sectors, which produce errors in estimation and cannot reflect visitor travel pattern and its associated GHG emission.

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Recommendations for future visitor expenditure surveys

Break down transportation and shopping expenses into detailed categories.

Shopping:

(1) Clothes or accessories (2) Jewelry or jade (3) Souvenirs or handicraft products (4) Cosmetics or perfumes (5) Local special products (6) Tobacco or alcohol (7) Chinese herbal medicine or health food (8) 3C or electric appliances (9) Tea (10) Others

Transportation

  • Domestic air
  • Rail
  • Water transportation
  • Road transportation
  • Private car / Gasoline
  • Distance travelled
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Re‐visit Kyoto Protocol

> Individual countries do not assume responsibility for the carbon footprint from goods produced outside of their jurisdiction. ⇒ Carbon emission of International aviation

services does not include or be regulated by the KP framework. ⇒ Imported products, as intermediate inputs or final products, are not included either.

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Reduce GHG emission from tourism

Factors in influencing recreational GHG emission 1. Final demand

Reduce visitor numbers, reduce length of stay, switching to environmental –friendly recreational activities

2. Energy requirement per dollars of final demand changes

Energy‐saving equipment or technological changes in the production process

3. The relative composition of different energy

Adopt clean energy

4. The energy converting ratio with respect to GHG emission

Technological changes or innovation in producing energy

5. Carbon Neutral

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Thank you for your listening. Any questions or comments?