metadata: authors: 0: author: Timilsina, Govinda R.
1: author: Shrestha, Ashish
count: Latin America,Caribbean
docna: 0: docna: The growth of transport cector CO2 emissions
            and underlying factors in Latin America and the Caribbean
docty: Policy Research Working Paper
theme: Climate change
majtheme: Environment and natural resource management
subtopic: Economic Theory & Research,Industrial Economics,Airports and Air Services,Energy Policies & Economics,Economic Growth,Energy Demand,Energy and Environment,Energy and Mining,Transport Services
teratopic: Energy,Industry,Environment,Transport
abstracts: cdata!: This study examines the factors
            responsible for the growth of transport sector carbon
            dioxide emissions in 20 Latin American and Caribbean
            countries during 1980-2005 by decomposing the emissions
            growth into components associated with changes in fuel mix,
            modal shift, and economic growth, as well as changes in
            emission coefficients and transportation energy intensity.
            The key finding of the study is that economic growth and the
            changes in transportation energy intensity are the main
            factors driving transport sector carbon dioxide emissions
            growth in the countries considered. The results imply that
            fiscal policy instruments - such as subsidies to clean fuels
            and clean vehicles - would be more effective in reducing
            emissions in countries where the economic activity effect is
            the primary driver for transport sector carbon dioxide
            emissions growth. By contrast, regulatory policy instruments
            - such as vehicle efficiency standards and vehicle occupancy
            standards - would be more effective in countries where the
            transportation energy intensity effect is the main driver of
            carbon dioxide emissions growth. Both fiscal and regulatory
            policy instruments would be useful in countries where both
            economic activity and transportation energy intensity
            effects are responsible for driving transport sector carbon
            dioxide emissions growth.
repnme: repnme: The growth of transport cector CO2
            emissions and underlying factors in Latin America and the Caribbean
display_title: The growth of transport cector CO2
            emissions and underlying factors in Latin America and the Caribbean
listing_relative_url: /research/2008/09/9892230/growth-transport-cector-co2-emissions-underlying-factors-latin-america-caribbean
topicv3: Air Transport m1326010 165,Economic Growth m1326241 471,Energy and Extractives m1326595 507,Transport m1326661 135,Power and Electricity Sector m1327094 515
publishtoextweb_dt: 2010-07-01T00:00:00Z
historic_topic: Energy,Industry,Environment,Transport
no_of_pages: 56
model_extractions: WPS4734 Policy ReseaRch WoRking PaPeR 4734 The Growth of Transport Sector CO2 Emissions and Underlying Factors in Latin America and the Caribbean _Govinda R. Timilsina Ashish Shrestha_ The World Bank Development Research Group Sustainable Rural and Urban Development Team September 2008
Policy ReseaRch WoRking PaPeR 4734

# **Abstract**

This study examines the factors responsible for the growth of transport sector carbon dioxide emissions in 20 Latin American and Caribbean countries during 1980–2005 by decomposing the emissions growth into components associated with changes in fuel mix, modal shift, and economic growth, as well as changes in emission coefficients and transportation energy intensity. The key finding of the study is that economic growth and the changes in transportation energy intensity are the main factors driving transport sector carbon dioxide emissions growth in the countries considered. The results imply that fiscal policy instruments—such as subsidies to clean fuels and clean vehicles —would be more effective in reducing emissions in countries where the economic activity effect is the primary driver for transport sector carbon dioxide emissions growth. By contrast, regulatory policy instruments—such as vehicle efficiency standards and vehicle occupancy standards—would be more effective in countries where the transportation energy intensity effect is the main driver of carbon dioxide emissions growth. Both fiscal and regulatory policy instruments would be useful in countries where both economic activity and transportation energy intensity effects are responsible for driving transport sector carbon dioxide emissions growth.

This paper—a product of the Sustainable Rural and Urban Development Team, Development Research Group—is part of a larger effort in the department to study climate change and clean energy issues. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The author may be contacted at gtimilsina@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
# **The Growth of Transport Sector CO2 Emissions and Underlying Factors in**

**Latin America and the Caribbean**<sup>**†**</sup>

Govinda R. Timilsina<sup>*</sup> and Ashish Shrestha Development Research Group, The World Bank, 1818 H Street, NW, Washington, DC 20433, USA

**Key Words** : Transport sector CO2 emissions, Decomposition analysis, Latin American and Caribbean countries

> † We sincerely thank Ram M Shrestha, Soma Bhattacharya, John Nash, Laura Tlaiye, Gershon Feder, Walter Vergara and LAC Transport Cluster for their valuable comments and suggestions. The views expressed in this paper are those of the authors only, and do not necessarily represent the World Bank and its affiliated organizations.

> *Fax: 1 202 522 1151; e-mail: <u>gtimilsina@worldbank.org</u>
# **1. Introduction**

Carbon dioxide (CO2) emissions released from fossil fuel consumption<sup>1</sup> increased from 760 million tons in 1980 to 1,327 million tons in 2005 in the Latin America and Caribbean (hereafter ‘LAC’) region, with an average growth rate of 2.3% per year (IEA, 2007). The transport sector is one of the main contributors to CO2 emissions in the region, where its share increased from 33.1% in 1980 to 34.1% in 2005. Therefore, any attempt to address climate change in the LAC region must pay attention to transport sector emissions. The identification of key factors driving CO2 emissions is essential for the formulation of effective climate change mitigation policies and strategies. One approach to accomplish this objective is the decomposition of the growth of emissions into the possible affecting factors.

The growth of emissions is often decomposed into the potential driving factors using different methods, such as the Laspeyres or Divisia methods. While studies, such as Lin et al (2007), Diakoulaki and Mandaraka (2007) and Diakoulaki et al (2006), Ebohon and Ikeme (2006) use the refined Laspeyres techniques, studies such as Liu et al (2007), Hatzigeorgiou et al (2007), Wang et al (2005) use the Arithmetic Mean Divisia Index (AMDI) and the Logarithmic Mean Divisia Index (LMDI) techniques.

Most existing studies concentrate on the decomposition of national CO2 emissions and emission intensities or emissions and emission intensities of the industrial and power sectors. Examples of national CO2 emissions (or emission intensities) decomposition studies include Wu et al (2005) and Wang et al (2005) for China, Kawase et al (2006) for Japan, Rhee and Chung (2006) for Japan and South Korea; Lise (2006) for Turkey, Diakoulaki et al (2006) for Greece, Saikku et al (2008) for 27 EU member States, Lee and Oh (2006) for APEC countries, Luukkanen and Kaivo-oja (2002) for ASEAN countries; Luukkanen and Kaivo-oja (2002) for Scandinavian countries, Ebohon and Ikeme (2006) for sub-Saharan African countries, and Han and Chatterjee (1997) for nine developing countries (Brazil, Chile, Colombia, India, Korea, Mexico, Philippines, Thailand and Zambia).

> 1 This study considers only fossil fuel consumption related CO2 emissions as our analysis is for the transport sector which emits CO2 through energy use.

2
Most of the studies decompose national CO2 emissions growth into economic growth, fuel switching and changes in emission intensity. At the sectoral level, more studies are focused on the industrial sector than any other sector. Liu et al (2007) decompose CO2 emissions growth in 36 industrial sectors in China over the period 1998-2005 to changes in emission coefficients and energy intensity, shifts in industrial structural, activity and fuel use. Yabe (2004) decomposes Japanese industrial CO2 emissions growth between 1985 and 1995 to changes in environmental and production technologies. Liaskas et al (2000) and Schipper et al (2001) attribute changes in industrial sector CO2 emissions during the 1973-1993 period to variations in output level, energy intensity, fuel mix and industrial structural in 13 EU countries. Similarly, Lin (1998) decomposes industrial CO2 emission changes in Taiwan during 1981-1991; Bhattacharyya and Ussanarassamee (2004) do the same for Thai industrial CO2 intensities during 1981-2000. Some studies concentrate on a particular industry instead of the industry sector as whole for the decomposition analysis. For example, Murtishaw et al. (2001) decompose changes in CO2 emissions from the petroleum refining, agriculture, mining and construction sectors of eight IEA countries; Kim and Worrell (2002) for the iron and steel industry in Brazil, China, India, Mexico, South Korea and the United States; Ozawa et al (2002) for the Mexican iron and steel industry, and Lee and Lin (2001) for the petrochemical industry in Taiwan.

The changes in CO2 emission intensities of the power sector, another key contributor to national CO2 emissions in many countries, have also been decomposed into various factors such as shifts in electricity generation technologies and changes in fuel intensity. Shrestha and Timilsina (1996) explore the evolution of the CO2 intensity of the electricity sector in 12 selected Asian countries during the period 1980-1990 using the Divisia index decomposition approach. Nag and Kulshrestha (2000) employ Divisia decomposition to break down sectoral carbon emission intensity of power consumption in India for the period 1974-1994 to emission coefficient of power, electricity intensity, and structural shift. Furthermore, they quantify the relative influences of fuel mix, fuel intensity, and generation mix on the emission coefficient for power consumption, and therefore carbon intensity. Shrestha and Marpuang (2006) develop a decomposition framework to analyze the total economy-wide changes in CO2, SO2 and NOx emissions when power sector development follows the integrated resource planning approach instead of traditional supply-based electricity planning, and then apply it to the case of the power 3
sector in Indonesia. Limmeechokchai and Suksuntornsiri (2007) assess reductions in economywide CO2 emissions in Thailand from the hypothetical selection of several cleaner power generation options, including biomass power generation, hydroelectricity and integrated gasification combined cycle (IGCC), over pulverized coal-thermal technology for the undecided capacity.

Note that power, industry and transport are the three major sectors responsible for fossil fuel related CO2 emissions in each country in the world. While the factors affecting CO2 emissions and emission intensities of the industry and power sectors have been analyzed in many countries, transport sector emissions and emission intensities have not been examined except in a few developed countries. Lakshmanan and Han (1997) attribute the change in transport sector CO2 emissions in the US between 1970 and 1991 to growth in people’s propensity to travel, population, and GDP. Lu et al (2007) decompose changes in CO2 emissions from highway vehicles in Germany, Japan, South Korea and Taiwan during 1990-2002 into changes in emission coefficient, vehicle fuel intensity, vehicle ownership, population intensity and economic growth.

Understanding the factors affecting the growth of CO2 emissions from the transport sector is critical because of its increasing prominence as a source of emissions and its relevance to the preparation of climate change mitigation strategies. Moreover, the existing literature ignores most LAC countries when analyzing the factors affecting CO2 emissions or emission intensities. This study aims to address this gap by executing a Divisia decomposition analysis of CO2 emissions from the transport sector in 20 LAC countries during the 1980-2005 period. The study attributes the growth of transport sector CO2 emissions during the period to five factors. These are: (i) fuel switching, (ii) modal shifting, (iii) change in emission coefficients, (iv) sectoral energy intensity change and (v) economic growth. Our study finds that among these five factors, two factors, namely, sectoral energy intensity change and economic growth are primarily responsible for driving transport sector CO2 emissions in most LAC countries over the last 25 years.

This paper is organized as follows: Section 2 briefly highlights transport sector CO2 emissions in LAC over the last 25 years as well as changes in fuel mix, modal mix and 4
transportation energy intensity. This is followed by a discussion on methodology and data in Section 3. The main results of the study are presented in Section 4, followed by key conclusions.

# **2. Transport Sector CO2 Emissions**

# **2.1 CO2 Emissions**

The transport sector has been one of the largest consumers of energy as well as one of the primary sources of CO2 emissions in LAC countries. At the regional level, the transport sector accounted for 29.3% of total energy consumption in 1980. This share exceeded 31.7% by 2005. The relatively high share of the transport sector in total energy consumption led this sector to be one of the primary sources of CO2 emissions. Table 1 presents CO2 emissions from the transport sector in LAC countries in 1980 and 2005. In 1980, the transport sector accounted for more than 40% of the total national emissions in 6 out of the 20 countries considered here. By 2005, the number of countries with transport sector emissions greater than 40% increased to 8, and the share of the transport sector in total regional CO2 emissions grew to 34.1% in 2005 from 33.1% in 1980. The transport sector in some LAC countries, such as Paraguay, Bolivia, Brazil, El Salvador, Nicaragua, Costa Rica and Ecuador exhibit very high shares (greater than 80% in Paraguay) in total national emissions. This is because most fossil fuel consumption in these countries occur in the transport sector and CO2 emissions from the power sector are very small (see Figure 1) due to pre-dominantly hydro-based electricity systems.

Transport sector shares of total national CO2 emissions have increased in Costa Rica, Ecuador, Guatemala, Panama, Paraguay, Peru, Uruguay and Other Latin American countries. On the other hand, the shares have decreased in Argentina, Bolivia, Cuba, Honduras and Nicaragua. The shares of the transport sector remain almost unchanged in Brazil, Caribbean, Chile, Columbia, El Salvador, Mexico and Venezuela. Because the transport, power and industry sectors are the main contributors to national CO2 emissions, changes in the magnitude of the emissions from the other two sectors, particularly the power sector, have a considerable impact on the transport sector’s share of national CO2 emissions (see Figure 1). For example, in Bolivia and Nicaragua, transport sector shares in 2005 are significantly smaller than those in 1980 as the 5
power sector shares of total national emissions increased due to the reduction of these countries’ reliance on hydropower. The reverse is the case for Ecuador and Paraguay, and currently, Paraguay is reliant exclusively on hydropower for its electricity generation.

**Table 1: Contribution of the Transport Sector in National CO2 Emissions**

||198<br>TlCO|0|200<br>TlCO|5|
|---|---|---|---|---|
|Country|ota2<br>emissions from<br>fossil fuel<br>consumption<br>(MtCO2)|Share of the<br>transport<br>sector in the<br>total (%)|ota2<br>emissions from<br>fossil fuel<br>consumption<br>(MtCO2)|Share of the<br>transport<br>sector in the<br>total (%)|
|Argentina|95.9|32.7|140.9|28.0|
|Bolivia|4.3|49.1|11.9|30.3|
|Brazil|178.0|41.1|329.3|42.1|
|Caribbean<sup>a</sup>|30.2|19.5|55.3|19.2|
|Chile|21.2|28.8|58.6|29.2|
|Colombia|33.8|34.5|59.9|33.2|
|Costa Rica|2.2|61.2|5.4|75.2|
|Cuba|28.5|21.8|23.8|8.1|
|Ecuador|10.6|37.6|23.4|45.5|
|El Salvador|1.7|50.9|5.9|49.3|
|Guatemala|4.2|31.9|10.5|46.1|
|Honduras|1.7|36.7|6.4|32.5|
|Mexico|212.8|32.1|389.4|33.7|
|Nicaragua|1.8|49.4|4.1|35.1|
|Panama|2.9|34.9|5.7|41.2|
|Paraguay|1.4|79.8|3.4|87.3|
|Peru|20.6|28.7|28.4|34.0|
|Uruguay|5.6|30.0|5.3|43.2|
|Venezuela|92.4|29.2|142.3|29.3|
|Other Latin America<sup>b</sup>|10.0|9.9|17.2|30.9|
|Total|759.7|33.1|1,327.1|34.1|
|Source: IEA (2007)|||||

a Caribbean includes Dominican Republic, Haiti, Jamaica, Netherland Antilles, and Trinidad and Tobago. b Other Latin America includes Antigua and Barbuda, Aruba, Bahamas, Barbados, Belize, Bermuda, Dominica, French Guyana, Grenada, Guadeloupe, Guyana, Martinique, St. Kitts and Nevis, Anguilla, Saint Lucia, St. Vincent and Grenadines, and Surinam.

Source: IEA (2007) At the regional level, total CO2 emissions from the transport sector more than doubled from 251 million tons to 453 million tons in 1980-2005 with an average annual growth rate of 2.4%. Given the size of Brazil’s economy and population, it comes as no surprise that its transport sector has been the largest CO2 emitter, and also the largest consumer of energy, 6
compared to the transport sectors of other LAC countries. However, during 1989-1994, Mexico exceeded Brazil for the transport sector CO2 emissions even though its transport sector energy consumption remained below than that of Brazil’s (see Figure 2). Four large economies in the region – Argentina, Brazil, Mexico and Venezuela – alone have accounted for between 76-79% of the region’s CO2 emissions from transportation since 1980.

**Figure 1: CO2 Emission Mix by Sector**

<!-- Start of picture text --> Power Industry Transport Other Sectors<br>100%<br>80%<br>60%<br>40%<br>20%<br>0%<br>Argentina Bolivia Brazil Caribbean Chile Colombia Costa Rica Cuba Ecuador El Salvador<br>100%<br>80%<br>60%<br>40%<br>20%<br>0%<br>Guatemala Honduras Mexico Nicaragua Panama Paraguay Peru Uruguay Venezuela Other Latin<br>America<br>1980 1990 2005 1980 1990 2005 1980 1990 2005 1980 1990 2005 1980 1990 2005 1980 1990 2005 1980 1990 2005 1980 1990 2005 1980 1990 2005 1980 1990 2005<br>1980 1990 2005 1980 1990 2005 1980 1990 2005 1980 1990 2005 1980 1990 2005 1980 1990 2005 1980 1990 2005 1980 1990 2005 1980 1990 2005 1980 1990 2005<br><!-- End of picture text --> Source: IEA (2007)
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gasoline as the source of most of the emissions from transportation in most countries by 2005. Still, Costa Rica and Panama exhibited almost complete reliance on motor gasoline in 1980. Thus, virtually all of their transport sector CO2 emissions were from motor gasoline. However, while Costa Rica had diversified its transport sector fuel mix by 2005, Panama was still reliant exclusively on motor gasoline.

The combustion of aviation fuels represented another notable source of emissions from transportation in 1980, but only in a few countries such as Bolivia, Other Latin America, Argentina and Brazil. However, the share of aviation fuel in total transport sector fuel consumption as well as in emissions declined in all countries except Argentina. Utilization of electricity for transportation was negligible in 1980 and the share of electricity has not increased significantly in any LAC countries with exception of Cuba. Even in Cuba, the increased share of electricity has not helped reduce CO2 emissions because of the high CO2 emission coefficient for electricity in that country. Although liquefied petroleum gas (LPG) was not used at all for transportation in 1980, except in Mexico, where it represented less than 1% of the fuel mix, LPG use in Mexico and Peru has increased by 2005. Similarly, natural gas was not a source of fuel for transportation in LAC countries in 1980, but several countries had incorporated it into their fuel mix by 2005, particularly in Argentina, where 19.5% of fuel for transportation is derived from natural gas, resulting in 15.8% of CO2 emissions from the transport sector in the country originating from natural gas. Finally, Brazil and Cuba, the two countries that used biofuels for transportation in 1980, were joined by Paraguay in increasing their usage of biofuels by 2005.

9
# **Table 2: Transport Sector Fuel Mix**

||Total|Aviation<br>Fuel|Electricity|1<br>Diesel|980<br>LPG|Biofuels|Motor<br>Gasoline|Natural<br>Gas|Residual<br>Fuel Oil|Total|Aviation<br>Fuel|Electricity|Diesel|2005<br>LPG|Biofuels|Motor<br>Gasoline|Natural<br>Gas|Residual<br>Fuel Oil|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|Country|(ktoe)|%|%|%|%|%|%|%|%|(ktoe)|%|%|%|%|%|%|%|%|
|Argentina|10,475|8.0|0.2|38.3|0.0|0.0|52.6|0.0|0.9|13,599|9.1|0.4|50.0|0.0|0.0|20.8|19.5|0.2|
|<br>Bolivia|712|14.8|0.0|28.1|0.0|0.0|57.1|0.0|0.0|1,219|10.9|0.0|43.0|0.0|0.0|36.9|9.1|0.0|
|Brazil|25,654|6.8|0.3|49.5|0.0|5.5|34.3|0.0|<br>3.7|52,998|5.0|0.2|50.9|0.0|13.0|26.3|3.1|1.5|
|Caribbean|1,975|2.9|0.0|39.5|0.0|0.0|57.6|0.0|0.0|3,579|2.5|0.0|30.9|0.0|0.0|66.7|0.0|0.0|
|Chile|2,040|n.a.|0.8|42.5|0.0|0.0|56.6|0.0|0.0|5,653|n.a|0.4|59.7|0.0|0.0|39.4|0.5|0.0|
|Colombia|3,975|n.a.|0.0|14.5|0.0|0.0|85.5|0.0|0.0|6,707|0.3|0.1|40.9|0.0|0.0|55.1|3.6|0.0|
|Costa Rica|440|n.a.|0.2|68.0|0.0|0.0|31.9|0.0|0.0|1,356|n.a|0.0|51.7|0.0|0.0|48.3|0.0|0.0|
|Cuba|2,172|n.a.|0.0|20.2|0.0|5.0|56.5|0.0|18.3|682|n.a|1.2|29.6|0.0|7.7|61.5|0.0|0.0|
|Ecuador|1,341|n.a.|0.0|16.1|0.0|0.0|71.2|0.0|12.3|3,537|0.1|0.0|53.7|0.0|0.0|46.2|0.0|0.0|
|El Salvador|285|n.a.|0.0|49.7|0.0|0.0|50.3|0.0|0.0|971|n.a|0.0|51.8|0.0|0.0|48.2|0.0|0.0|
|Guatemala|454|n.a.|0.0|38.7|0.0|0.0|61.3|0.0|0.0|1,614|n.a|0.0|45.5|0.0|0.0|54.5|0.0|0.0|
|Honduras|205|n.a.|0.0|49.4|0.0|0.0|50.6|0.0|0.0|694|n.a|0.0|50.7|0.0|0.0|49.3|0.0|0.0|
|Mexico|22,935|n.a.|0.2|34.5|0.7|0.0|64.6|0.0|0.0|44,296|n.a|0.2|29.2|3.5|0.0|66.9|0.0|0.2|
|Nicaragua|295|3.3|0.0|47.4|0.0|0.0|49.3|0.0|0.0|475|n.a|0.0|59.8|0.0|0.0|40.2|0.0|0.0|
|Panama|342|n.a|0.0|30.3|0.0|0.0|69.7|0.0|0.0|780|n.a|0.0|45.1|0.0|0.0|54.9|0.0|0.0|
|Paraguay|357|n.a|0.0|69.1|0.0|0.0|30.9|0.0|0.0|995|n.a|0.0|82.5|0.0|1.7|15.8|0.0|0.0|
|Peru|1,959|0.5|0.0|31.9|0.0|0.0|56.1|0.0|11.5|3,170|n.a|0.0|72.1|0.9|0.0|26.0|0.0|0.9|
|Uruguay|551|6.6|0.0|46.1|0.0|0.0|40.8|0.0|6.4|744|0.4|0.0|70.8|0.0|0.0|28.8|0.0|0.0|
|<br>Venezuela|9,182|n.a.|0.0|14.7|0.0|0.0|82.7|0.0|2.5|14,201|n.a|0.2|15.6|0.0|0.0|84.1|0.0|0.1|
|Other L.A.|335|11.2|0.0|18.5|0.0|0.0|70.3|0.0|0.0|1,791|6.0|0.0|35.5|0.0|0.0|58.6|0.0|0.0|

Source: IEA (2007) 10
# **Table 3: CO2 Emission Mix by Fuel Type in the Transport Sector**

||Total|Aviation<br>Fuel|Electricity|19<br>Diesel|80<br>LPG|Biofuels|Motor<br>Gasoline|Natural<br>Gas|Residual<br>Fuel Oil|Total|Aviation<br>Fuel|Electricity|Diesel|2005<br>LPG|Biofuels|Motor<br>Gasoline|Natural<br>Gas|Residual<br>Fuel Oil|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
||('000|||||||||('000|||||||||
|Country|tCO2)|%|%|%|%|%|%|%|%|tCO2)|%|%|%|%|%|%|%|%|
|Argentina|31,391|8.0|0.5|39.7|0.0|0.0|50.9|0.0|<br>1.0|39,516|9.3|0.5|53.4|0.0|0.0|20.8|15.8|0.2|
|<br>Bolivia|2,115|14.9|0.0|29.3|0.0|0.0|55.8|0.0|<br>0.0|3,594|11.1|0.0|45.3|0.0|0.0|<br>36.4|7.3|0.0|
|Brazil|73,186|7.1|0.1|53.8|0.0|0.0|34.8|0.0|<br>4.2|138,596|5.7|0.1|60.4|0.0|0.0|<br>29.2|2.7|1.9|
|Caribbean|5,893|2.9|0.0|41.1|0.0|0.0|56.0|0.0|<br>0.0|10,614|2.5|0.0|32.3|0.0|0.0|65.2|0.0|0.0|
|Chile|6,108|n.a.|1.0|44.1|0.0|0.0|54.9|0.0|<br>0.0|17,091|n.a.|0.5|61.2|0.0|0.0|<br>37.8|0.4|0.0|
|Colombia|11,650|n.a.|0.0|15.3|0.0|0.0|84.6|0.0|<br>0.0|19,880|n.a.|0.0|42.8|0.0|0.0|54.0|2.8|0.0|
|Costa Rica|1,335|n.a.|0.0|69.5|0.0|0.0|30.5|0.0|<br>0.0|4,074|n.a.|0.0|53.4|0.0|0.0|46.6|0.0|0.0|
|Cuba|6,210|n.a.|0.0|21.9|0.0|0.0|57.3|0.0|<br>20.7|1,935|n.a.|4.7|32.4|0.0|0.0|62.9|0.0|0.0|
|Ecuador|3,991|n.a.|0.0|16.7|0.0|0.0|69.5|0.0|<br>13.4|10,645|n.a.|0.0|55.3|0.0|0.0|44.6|0.0|0.0|
|El Salvador|856|n.a.|0.0|51.4|0.0|0.0|48.6|0.0|<br>0.0|2,917|n.a.|0.0|53.5|0.0|0.0|46.5|0.0|0.0|
|Guatemala|1,353|n.a.|0.0|40.3|0.0|0.0|59.7|0.0|<br>0.0|4,832|n.a.|0.0|47.2|0.0|0.0|52.8|0.0|0.0|
|Honduras|616|n.a.|0.0|51.1|0.0|0.0|48.9|0.0|<br>0.0|2,085|n.a.|0.0|52.4|0.0|0.0|47.6|0.0|0.0|
|Mexico|68,232|n.a.|0.4|36.0|0.6|0.0|63.0|0.0|<br>0.0|131,057|n.a.|0.5|30.6|3.1|0.0|65.6|0.0|0.2|
|Nicaragua|885|3.3|0.0|49.0|0.0|0.0|47.7|0.0|<br>0.0|1,434|n.a.|0.0|61.4|0.0|0.0|38.6|0.0|0.0|
|<br>Panama|1,013|n.a.|0.0|31.7|0.0|0.0|68.3|0.0|<br>0.0|2,334|n.a.|0.0|46.8|0.0|0.0|53.2|0.0|0.0|
|Paraguay|1,085|n.a.|0.0|70.5|0.0|0.0|29.5|0.0|<br>0.0|3,004|n.a.|0.0|84.8|0.0|0.0|15.2|0.0|0.0|
|<br>Peru|5,888|0.5|0.0|32.9|0.0|0.0|54.2|0.0|<br>12.4|9,661|n.a.|0.0|73.4|0.8|0.0|24.8|0.0|1.0|
|Uruguay|1,665|6.6|0.0|47.4|0.0|0.0|39.1|0.0|<br>6.9|2,265|0.4|0.0|72.1|0.0|0.0|<br>27.5|0.0|0.0|
|<br>Venezuela|26,991|n.a.|0.0|15.5|0.0|0.0|81.7|0.0|<br>2.8|41,649|n.a.|0.2|16.6|0.0|0.0|<br>83.2|0.0|0.1|
|Other L.A.|987|11.3|0.0|19.5|0.0|0.0|69.2|0.0|0.0|5,334|6.0|0.0|37.0|0.0|0.0|57.0|0.0|0.0|

Source: IEA (2007) 11
# **2.3. Modal Mix**<sup>**3**</sup> **in the Transport Sector**

Road was the predominant mode of transportation in LAC countries in 1980, especially in El Salvador, Guatemala, Honduras and Panama, where it was the only mode of transportation (see Tables 4 and 5). Because every country, except Argentina, Chile and Columbia, has increased their reliance on road transportation since then, this distribution was even more prominent in 2005. Road transport accounted for more than 90% of transport sector fuel consumption and CO2 emissions in 18 out of the 20 countries in 2005. A few countries utilized domestic air transport, e.g., Uruguay, Brazil, Argentina, Other Latin America, and especially Bolivia (where it accounted for about 15% of the fuel consumption and CO2 emissions in 1980), but the share of air transport in total transport sector fuel consumption and CO2 emissions declined in all LAC countries by 2005 with the exception of Argentina.

Rail has not been an important mode of transportation in any of the countries since 1980, but Cuba experienced a dramatic increase in the share of CO2 emissions from rail transport despite rail only accounting for 1.2% of fuel consumption for transportation in 2005 due to its use of electricity for rail transport and its high emission coefficient for electricity production. Inland waterways represented a significant mode of transportation in a few LAC countries in 1980 (Cuba, Ecuador and Peru). However, there has been a decline in fuel consumption and CO2 emissions from inland waterways transportation in these countries, particularly Cuba and Peru, where inland waterways went from being responsible for, respectively, 22.6% and 11.5% of CO2 emissions in 1980 to almost none in 2005. The general shift towards road transportation in LAC was accompanied by reduced reliance on domestic air and inland waterways.

> 3 Ideally modal mix should be measured in terms of transport services (e.g., passenger kilometers, ton kilometers or any other equivalent unit) generated by each type of transportation mode. However, due to the lack of data, the study uses total fuel consumption by mode as a surrogate to illustrate modal mix. In energy literature, this is a common practice to measure modal mix in the transportation sector (see e.g., EIA, 2007; IEA, 2004)

12
**Table 4: Modal Mix for Fuel Consumption in Transport Sector**

||||1980|||||2005|||
|---|---|---|---|---|---|---|---|---|---|---|
|||Domestic|Inland||||Domestic|Inland|||
||Total|Air|Waterways|Rail|Road|Total|Air|Waterways|Rail|Road|
|Country|(ktoe)|%|%|%|%|(ktoe)|%|%|%|%|
|Argentina|10,475|8.0|0.9|0.2|90.9|13,599|9.1|0.2|0.4|90.3|
|Bolivia|712|14.8|0.0|1.7|83.4|1,219|10.9|1.1|0.4|87.6|
|Brazil|25,654|6.8|6.4|2.6|84.2|52,998|5.0|2.1|1.3|91.6|
|Caribbean|1,975|2.9|0.0|0.0|97.1|3,579|2.5|0.0|0.0|97.5|
|Chile|2,040|0.0|5.3|1.3|93.3|5,653|0.0|6.2|0.4|93.4|
|Colombia|3,975|0.0|0.8|0.5|98.6|6,707|0.6|3.0|0.5|95.9|
|Costa Rica|440|0.0|2.6|0.2|97.3|1,356|0.0|0.2|0.0|99.8|
|Cuba|2,172|0.0|23.3|2.9|73.8|682|0.0|0.0|1.2|98.8|
|Ecuador|1,341|0.0|16.3|0.4|83.3|3,537|0.0|10.1|0.0|89.9|
|El Salvador|285|0.0|0.0|0.0|100.0|971|0.0|0.0|0.0|100.0|
|Guatemala|454|0.0|0.0|0.0|100.0|1,614|0.0|0.0|0.0|100.0|
|Honduras|205|0.0|0.0|0.0|100.0|694|0.0|0.0|0.0|100.0|
|Mexico|22,935|0.0|0.0|2.9|97.1|44,296|0.0|1.9|1.6|96.4|
|Nicaragua|295|3.3|2.8|0.0|93.9|475|0.0|3.0|0.0|97.0|
|Panama|342|0.0|0.0|0.0|100.0|780|0.0|0.0|0.0|100.0|
|Paraguay|357|0.0|0.9|0.0|99.1|995|0.0|0.0|0.0|100.0|
|<br>Peru|1,959|0.5|11.5|0.0|88.0|3,170|0.0|0.9|0.0|99.0|
|Uruguay|551|6.6|6.4|0.0|86.9|744|0.4|0.0|0.0|99.6|
|<br>Venezuela|9,182|0.0|0.0|2.5|97.5|14,201|0.0|0.0|0.3|99.7|
|Other Latin America|335|11.2|2.2|0.0|86.6|1,791|6.0|0.0|0.0|94.0|

Based on the available data and following normal practices in energy accounting systems, the study considers four modes of transportation: road, rail, water and air. If data is available, road transportation, which is the primary mode for providing transportation services as well as energy consumption and associated emissions, can be disaggregated further into auto, bus etc.

Source: IEA (2007) 13
**Table 5: Modal Mix for CO2Emissions from Transportation**

|||Domestic|1980<br>Inland||||Domestic|2005<br>Inland|||
|---|---|---|---|---|---|---|---|---|---|---|
||Total|Air|Waterways|Rail|Road|Total|Air|Waterways|Rail|Road|
||('000|||||('000|||||
|Country|tCO2)|%|%|%|%|tCO2)|%|%|%|%|
|Argentina|31,391|8.0|1.0|0.5|90.6|39,516|9.3|0.2|0.5|90.0|
|Bolivia|2,115|14.9|0.0|1.8|83.2|3,594|11.1|1.2|0.4|87.3|
|Brazil|73,186|7.1|7.1|2.6|83.2|138,596|5.7|2.6|1.3|90.3|
|Caribbean|5,893|2.9|0.0|0.0|97.1|10,614|2.5|0.0|0.0|97.5|
|Chile|6,108|0.0|5.5|1.5|93.0|17,091|0.0|6.4|0.5|93.1|
|Colombia|11,650|0.0|0.9|0.6|98.5|19,880|0.6|3.1|0.5|95.9|
|Costa Rica|1,335|0.0|2.6|0.0|97.4|4,074|0.0|0.2|0.0|99.8|
|Cuba|6,210|0.0|26.2|3.2|70.7|1,935|0.0|0.0|4.7|95.3|
|Ecuador|3,991|0.0|17.6|0.4|82.0|10,645|0.0|10.4|0.0|89.6|
|El Salvador|856|0.0|0.0|0.0|100.0|2,917|0.0|0.0|0.0|100.0|
|Guatemala|1,353|0.0|0.0|0.0|100.0|4,832|0.0|0.0|0.0|100.0|
|Honduras|616|0.0|0.0|0.0|100.0|2,085|0.0|0.0|0.0|100.0|
|Mexico|68,232|0.0|0.0|3.2|96.8|131,057|0.0|2.0|1.9|96.0|
|Nicaragua|885|3.3|2.9|0.0|93.8|1,434|0.0|3.1|0.0|96.9|
|Panama|1,013|0.0|0.0|0.0|100.0|2,334|0.0|0.0|0.0|100.0|
|Paraguay|1,085|0.0|0.9|0.0|99.1|3,004|0.0|0.0|0.0|100.0|
|<br>Peru|5,888|0.5|12.4|0.0|87.1|9,661|0.0|1.0|0.0|99.0|
|Uruguay|1,665|6.6|6.9|0.0|86.5|2,265|0.4|0.0|0.0|99.6|
|<br>Venezuela|26,991|0.0|0.0|2.8|97.2|41,649|0.0|0.0|0.3|99.7|
|Other Latin America|987|11.3|2.2|0.0|86.5|5,334|6.0|0.0|0.0|94.0|

Source: IEA (2007) .

14
# **3. Methodology and Data**

# **3.1 Methodology**

Total CO2 emission from the transport sector in a country in year t (CO2t) is the summation of CO2 emissions from all fuels used in all transport modes in that year, i.e., where, CO2ijt = CO2 emissions from fuel i in transportation mode j in year t In order to decompose the emission to the potential factors affecting it, Equation (1) can be expressed as: where, FCijt = consumption of fuel i (e.g., gasoline, diesel, fuel oil, natural gas, electricity) in transportation mode j (e.g., road, rail, domestic air and inland water) in year t FCjt = total fuel consumption in transportation mode j in year t FCt = total fuel consumption in the transportation sector in year t GDPt = Gross domestic product in year t Ideally Equation (2) should be replaced with the following equation, where, TSjt = transport services (e.g., passenger kilometers, tons kilometers or any equivalent measurement representing transport services<sup>4</sup> ) provided by transport mode j in year t

> 4 Includes transport services provided to all sectors (e.g., households, industry, government).

15
TSt = total transport services in year t Since transportation service data needed for the study (i.e., 20 LAC countries for 25 years between 1980 and 2005) are not available, the study uses Equation (2) instead of Equation (3). Note that Equation (3) can be expanded further to differentiate passenger and freight transportation, this would, however, complicates further in obtaining the necessary data.

Equation (2) can also be rewritten as: where, ECijt = emission coefficient of fuel i used in transportation mode j in year t (= CO2ijt/FCijt) FMijt = share of fuel i in transportation mode j (fuel mix) in year t (= FCijt/FCjt) MMjt = share of mode j in total transport sector fuel consumption (modal mix) in year t (= FCjt/FCt) EIt = transportation energy intensity in year t (= FCt/GDPt) EAt = economic activity in year t (= GDPt) Note that Equation (4) implicitly assumes the same energy intensity (e.g., kj per passenger kilometer or kj per ton kilometer) across the different modes of transport. This is a strong assumption. This does however, not affect the results of this particular study as modal shifting is insignificant in all countries considered over the study horizon.

Following Shrestha and Timilsina (1996) and Boyd et al. (1987), the change in transport sector CO2 emission between year t and t-1 can be decomposed using the general Divisia index approach as: 16
where This study uses the logarithmic mean Divisia index (LMDI) approach (Ang et al. 1998; Ang and Liu, 2001) instead of the general Divisia index approach. The preference of LMDI approach to the general Divisia index approach is based on the fact that the former provides a residual-free decomposition. Moreover, the LMDI can accommodate the occurrence of zero values in the data set<sup>5</sup> . Using LMDI, the change in the transport sector CO2 emissions from year t-1 to t is expressed as: In Equation (8) w<sup>~</sup> ijt is defined differently from that in Equation (6); following Ang (2005) w<sup>~</sup> ijt is now given as: The first term in the right hand side of Equation (8) represents the emission coefficient (EC) effect. Note that only the coefficient of electricity is changing due to variations in electricity generation mix over time. Emission coefficients (i.e., carbon contents) for other fuels are assumed to be constant over time. The second and third terms represent the fuel mix (FM) or fuel

> 5 In this approach zero values are replaced with a small positive constant. Wood and Lenzen (2006) contend that this strategy is not necessarily robust if applied to a data set containing a large number or zeros and small values and recommend the use of analytical limits proposed in Ang et al (1998). However, while Ang and Liu (2007) concur that the use of analytical limits is superior on theoretical grounds, they demonstrate that the small value strategy is generally robust for index decomposition analyses when a sufficiently small value is utilized.

17
switching and the modal mix (MM) or modal shift effects, respectively. Finally, the fourth and fifth terms represent the transportation energy intensity (EI) effect and the economic activity (EA) effect, respectively. The study carries out decomposition analysis on an annual basis over the twenty five years period between 1980 and 2005.

# **3.2 Data**

This paper uses transport sector energy consumption data by fuel type and mode from the International Energy Agency (IEA). Fuels included are biofuel (i.e., ethanol), natural gas, liquefied petroleum gases (LPG), motor gasoline, aviation fuels (i.e., aviation gasoline, kerosene and jet fuel), diesel oil, residual fuel oil, and electricity. The use of coal for transportation is negligible in LAC countries, and so the study excludes it. The modes of transportation considered are domestic aviation, road, rail and domestic water transport<sup>6</sup> . The study excludes energy consumption in oil and gas pipeline transport.

Emission coefficients are based on the carbon contents of fuels and are obtained from Intergovernmental Panel on Climate Change (IPCC) Guidelines for National Greenhouse Gas Inventories (IPCC, 2006) for all fuels except electricity. Emission coefficients for electricity are derived using IEA data on electricity output and CO2 emissions from electricity production (IEA, 2007a, 2007b, 2007c). While CO2 emission factors for other transportation fuels (e.g., gasoline, diesel etc.) remain the same throughout the study period, CO2 emission factors for electricity vary with time. This is because, the carbon content of a fossil fuel is not expected to change over time, but CO2 emission coefficients of an electricity grid change over time as the electricity generation mix and thereby the input fuel mix for electricity generation changes every year. Moreover, the CO2 emission coefficient of a particular fossil fuel is the same for all countries, whereas the coefficient for electricity varies across the countries depending on their electricity generation mix. CO2 emissions are estimated by type of fuel and mode, using the corresponding fuel consumption and associated emission factors. Data on gross domestic product (GDP),

> 6 In energy statistics, energy consumption by international aviation and maritime transportation are not considered part of national energy consumption. These are treated separately under their international conventions (i.e., International Civil Aviation Organization and International Maritime Organization).

18
expressed at 2000 constant dollar measured in purchasing power parity, are also taken from the IEA (IEA, 2007f, 2007g).

Data for “Other Latin America” are taken directly from the IEA at the aggregate level. Caribbean data are either the summation of the data for the constituent countries (e.g., GDP, fuel consumption) or their weighted average (e.g., CO2 coefficients of electricity).

# **4. Results and Discussion**

All countries in LAC, with the exception of Cuba, experienced significant growth in transportation sector CO2 emissions during the 1980-2005 period. However, there remain significant differences in the magnitude of emissions growth and the factors driving it. Figure 3 summarizes the results of the decomposition of transport sector CO2 emissions growth into fuel switching, modal shifting and changes in emission coefficients<sup>7</sup> , transportation energy intensity, and economic activity (or GDP). Detailed results for each country considered are presented in the Appendix.

> 7 Only the emission coefficients of electricity changes due to different electricity generation mix over time; emission coefficients of other fuels remain constant throughout the study period.

19
# **Figure 3: Factors Affecting CO2 Emissions Growth in LAC Countries**

|Country|1981 1982|1983 1984 1985|1986 198|7 1988 1989 1990|1991 1|99|2 1993 1994 199|5 1996 1997 199|8 1999 2000 2001|2002 2003 2004 2005|<br>Overall|
|---|---|---|---|---|---|---|---|---|---|---|---|
|Argentina|||||||||||EA|
|Bolivia|||||||||||EI|
|Brazil|||||||||||EA|
|Caribbean|||||||||||EI|
|Chile|||||||||||EI & EA|
|Colombia|||||||||||EI & EA|
|Costa Rica|||||||||||EA|
|Cuba|||||||||||EI|
|Ecuador|||||||||||EI|
|El Salvado|r||||||||||EI & EA|
|Guatemala|||||||||||EI|
|Honduras|||||||||||EI|
|Mexico|||||||||||EI & EA|
|Nicaragua|||||||||||EI & EA|
|Other L.A.|||||||||||EI|
|Panama|||||||||||EI|
|Paraguay|||||||||||EI|
|Peru|||||||||||EA|
|Uruguay|||||||||||EA|
|Venezuela|||||||||||EI & EA|
||EI|EA||EI-EA|FM-E|A|FM-EI|||||

Note: Overall factor selected if it is a main factor in at least 40% (10 out of 25 years) of the study period.

The modal mix effect, as defined in this study, considers only four modes: road, rail, water and air, and does not appear to influence emission growth. If necessary data is available to further disaggregate road transportation into auto, bus etc., modal mix might be found to influence CO2 emission growth.

20
As illustrated in Figure 3, the energy intensity effect is found to be pre-dominant in influencing the growth of transportation sector CO2 during the 1980-1990 period. Conversely, the economic activity effect is the primary factor driving transportation sector CO2 emissions during the 1991-1998 period. Both energy intensity and economic activity effects are responsible for CO2 emission growth in the transport sector during the 1999-2005 period.

The economic activity effect (i.e., change in GDP) is the primary factor in the growth of transportation sector CO2 emissions in Argentina, Brazil, Costa Rica, Peru and Uruguay. On the other hand, the transportation energy intensity effect is found to be the main driver of transport sector CO2 emissions change in Bolivia, the Caribbean, Cuba, Ecuador, Guatemala, Honduras, Other Latin America, Panama and Paraguay. In the remaining LAC countries (i.e., Chile, Colombia, El Salvador, Mexico, Nicaragua, and Venezuela), both the economic activity effect and transportation energy intensity effect are found responsible for their transport sector CO2 emission growth.

Although fuel switching is a common phenomenon in many LAC countries during the 1980-2005 period (see Table 2), interestingly, the fuel switching effect is not found to play a role in driving transport sector CO2 emissions in these countries. This is because the substitution occurred between diesel and gasoline, but their CO2 emission coefficients are not significantly different Figures 4 (a) – (e) present indexed time-series charts of the decomposition results for Argentina, Brazil, Costa Rica, Peru and Uruguay, where the economic activity effect is found to be the principal driver of transport sector CO2 emission growth. In all five of these countries, the pattern of CO2 emission growth looks similar: almost stagnant until 1990, sharp increase between 1990 and 1998, drop thereafter until 2002 and increase again after 2002. This pattern is consistent with the economic performance of these countries during the period as economic growth was stagnant during the 1980s, gradually increased in the 1990s until the economic crisis of the late 1990s, and then recovered after 2002.

21
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although the fuel mix effect is also found to contribute slightly to the change in CO2 emissions in some years in Brazil. These countries are not expected to slow down their economic growth to control their CO2 emissions because they have neither mandatory nor voluntary commitments to reduce CO2 emissions under the Kyoto Protocol. Thus, the main strategy to limit the growth of CO2 emissions in the transport sector in these countries in the future would likely be the decoupling (or weakening) of the growth of CO2 emissions from economic growth, which has not been the case historically. Rapid switching to clean fuels and shifting over to public transportation, including rail and water transportation, could help achieve this objective. Policy instruments such as subsidies to public transportation, clean fuels and clean vehicles would be helpful in triggering the fuel switching and modal shifting activities. Although regulatory instruments such as fuel economy standards could also help reduce CO2 emissions, such instruments, however, act only indirectly (e.g., through the improvement of transportation energy intensity, which is not found to be the main factor for driving CO2 emission growth in these countries).

Indexed time-series charts of the decomposition results for Bolivia, Caribbean, Cuba, Ecuador, Guatemala, Honduras, Other Latin America, Panama and Paraguay, where transport sector CO2 emission changes were primarily driven by changes in transportation energy intensity, are presented in Figures 5(a) to 5(i). With the exception of a few years, such as 1990-1993 and 2002-2005, the energy intensity effect is increasing in all of these eight countries. The reason for this is that the growth of energy consumption in the transport sector of each of these countries is outpacing GDP growth during the study period. Table 6 shows that the magnitude of the average annual growth rate of transport sector energy consumption is greater than that of GDP in Bolivia, the Caribbean, Cuba, Ecuador, Guatemala, Honduras, Other Latin America, Panama and Paraguay. Although further studies are needed to precisely determine the causes of 23
increases in the transportation energy intensities<sup>8</sup> , possible reasons could be an increase in the non-productive usage of transport services, traffic congestion, etc.

Since transportation energy intensity is the primary factor driving transport sector CO2 emissions in these countries, policy instruments that could help reduce transportation energy intensity, such as vehicle efficiency or fuel economy standards and vehicle occupancy standards, would be more effective in slowing transport sector CO2 emission growth in these countries.

> 8 In order to determine the reasons for transportation energy intensity change, this indicator itself can be decomposed into its driving factors, such as fuel efficiency of transportation by mode and transport service intensity of the economy.

24
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**Figure 5 (continued): Transport Sector CO2 Emissions Growth and Driving Factors in Bolivia, Caribbean, Cuba, Ecuador, Guatemala, Honduras, Other Latin America, Panama and Paraguay**

<!-- Start of picture text --> h) Panama<br><!-- End of picture text --> <!-- Start of picture text --> g) Other Latin America<br><!-- End of picture text --> <!-- Start of picture text --> 5.3<br>CO2 CO2<br>4.8 Fuel Mix Fuel Mix<br>Modal Mix 2.8 Modal Mix<br>4.3 Emission Coefficient Emission Coefficient<br>3.8 Energy Intensity Energy Intensity<br>GDP 2.3 GDP<br>3.3<br>2.8 1.8<br>2.3<br>1.8 1.3<br>1.3<br>0.8 0.8<br><!-- End of picture text --> i) Paraguay <!-- Start of picture text --> 3.3<br>CO2<br>Fuel Mix<br>2.8 Modal Mix<br>Emission Coefficient<br>Energy Intensity<br>2.3 GDP<br>1.8<br>1.3<br>0.8<br><!-- End of picture text -->

**Table 6: Average Annual Growth Rate of GDP and Transport Sector Energy Consumption for the 1980-2005 Period (%)**

|Country|GDP|Energy Consumption|
|---|---|---|
|Bolivia|2.18|2.44|
|Caribbean|2.49|2.60|
|Cuba|1.53|-3.12|
|Ecuador|2.61|4.19|
|Guatemala|2.51|5.48|
|Honduras|3.03|5.27|
|Other Latin America|2.84|7.86|
|Panama|3.51|3.62|
|Paraguay|2.20|4.60|

Source: IEA (2007) 26
The study finds that both economic activity and transportation energy intensity effects are responsible for transport sector CO2 emission growth in Chile, Colombia, El Salvador, Mexico, Nicaragua, and Venezuela. The indexed time-series charts of the decomposition results for these countries are presented in Figure 6(a) to 7(f). Although both effects influence transport sector CO2 emissions most of the time during the study period, exceptions are noted in some years. For example, the energy intensity effect does not significantly affect transport sector CO2 emission after 2003 in all of these countries, with the exception of Columbia and Nicaragua. Both the economic activity and energy intensity effects are driving CO2 emissions gradually upwards between the mid-1980s to 2000 in Chile and El Salvador, while CO2 emissions remained almost unchanged during the 1980s and then increased gradually in the 1990s along with energy intensity and economic activity effects in Costa Rica, Nicaragua and Venezuela. In Mexico, the energy intensity effect is the main driving factor for CO2 emissions growth in the 1980s, but then the economic activity effect becomes the main contributor in the 1990s.

**Figure 6: Transport Sector CO2 Emissions Growth and Driving Factors in Chile, Colombia, El Salvador, Mexico, Nicaragua, and Venezuela**

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subsidies to public transportation, clean fuels and clean vehicles would be needed to induce switching over to clean fuels and shifting over to public transportation (including rail and water transportation). Moreover, policy instruments, such as vehicle efficiency standards, vehicle occupancy standards, congestion charges, investments on road maintenance and congestion reduction would be required to reduce transportation energy intensity and thereby reduce transport sector CO2 emissions in these countries.

# **5. Conclusions**

This study examines the growth of transport sector CO2 emissions and determines the underlying factors in 20 Latin American and Caribbean countries over 25 years between 1980 and 2005. To identify the driving factors, the study decomposes the emission growth to fuel switching, modal shifting, economic growth and changes in emission coefficients and transportation energy intensity using the logarithmic mean Divisia index (LMDI) approach. The study finds that economic growth and change in transportation energy intensity are the principal drivers of transport sector CO2 emission growth in Latin American and Caribbean countries, whereas fuel switching, modal shifting and change in emission coefficients are not found to have a sizeable influence on the growth of transport sector CO2 emissions in those countries. The economic activity effect (i.e., GDP growth) is found to be driving transport sector CO2 emissions in most years in the study horizon in Argentina, Brazil, Costa Rica, Peru and Uruguay. On the other hand, the transportation energy intensity effect is found to be the main driver of CO2 emissions change in Bolivia, Caribbean, Cuba, Ecuador, Guatemala, Honduras, Panama, Paraguay and “Other Latin America.” In the remaining LAC countries (i.e., Chile, Colombia, El Salvador, Mexico, Nicaragua, and Venezuela), both the economic activity effect and transportation energy intensity effect are found responsible for transport sector CO2 emissions growth.

The results also suggest some policy conclusions. In order to limit the growth of CO2 emissions, emissions growth should first be decoupled from economic growth, 29
which has not been the case historically. This can be done via rapid switching to clean fuels, shifting to public transportation (including rail and water transportation), and an increase in transportation energy efficiency through vehicles efficiency improvements, road maintenance, and the reduction of traffic congestion. Fiscal instruments such as emission taxes and subsidies for clean fuels and clean vehicles would be more effective in slowing CO2 emission growth in countries where the economic activity effect is the primary driver for transport sector CO2 emission growth. On the other hand, regulatory instruments such as fuel economy standards and vehicle occupancy standards would be more effective in countries where the transportation energy intensity effect is the main driver for CO2 emission growth. Both fiscal and regulatory policy instruments would be useful in countries where both economic activity effect and transportation energy intensity effect are responsible for driving transport sector CO2 emissions growth.

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