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WORLD BANK
TRANSPORT
2011
Coordination
Wagner Colombini Martins, LOGIT
Paul Procee, The Work Bank
Christophe de Gouvello, The World Bank
Jennifer Meihuy Chang, The World Bank
Technical Team
Fuad Jorge Alves José (Principal contributor),
Wagner Colombini Martins,
Fernando Howat Rodrigues,
Arthur C. Szasz, and
Sérgio H. Demarchi, LOGIT
Ronaldo Ballassiano, COPPE-UFRJ
Brazil Low Carbon
Case Study
Technical Synthesis Report
Public Disclosure AuthorizedPublic Disclosure AuthorizedPublic Disclosure AuthorizedPublic Disclosure Authorized
69859
TRANSPORT
2011
Coordination
Wagner Colombini Martins, LOGIT
Paul Procee, The Work Bank
Christophe de Gouvello, The World Bank
Jennifer Meihuy Chang, The World Bank
Technical Team
Fuad Jorge Alves José (Principal contributor),
Wagner Colombini Martins,
Fernando Howat Rodrigues,
Arthur C. Szasz, and
Sérgio H. Demarchi, LOGIT
Ronaldo Ballassiano, COPPE-UFRJ
Brazil Low Carbon
Case Study
Technical Synthesis Report
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TECHNICAL SYNTHESIS REPORT
BRAZIL LOW CARBON CASE STUDY
Coordenação
Wagner Colombini Martins, LOGIT
Paul Procee, The World Bank
Christophe de Gouvello, The World Bank
Jennifer Meihuy Chang, The World Bank
Equipe Técnica
Fuad Jorge Alves José (Principal contribuidor),
Wagner Colombini Martins,
Fernando Howat Rodrigues, Arthur C.
Szasz e Sérgio H. Demarchi, LOGIT
Ronaldo Ballassiano, COPPE-UFRJ
Technical Synthesis Report | TRANSPORT
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Table of Contents
1. INTRODUCTION ---------------------------------------------------------------------------------------------16
1.1. Historical overview of transport in Brazil ---------------------------------------------------19
1.2. Transport and the productive sectors --------------------------------------------------------22
1.3. Impacts generated by the transport sector --------------------------------------------------23
1.4. Transport and carbon emissions --------------------------------------------------------------25
1.5. General considerations for urban transport ------------------------------------------------28
1.6. General considerations for regional transport --------------------------------------------34
1.7. Institutional overview ---------------------------------------------------------------------------38
1.8. Regulatory overview ----------------------------------------------------------------------------40
1.9. Initial prospective analysis ---------------------------------------------------------------------40
2. METHODOLOGICAL APPROACH -------------------------------------------------------------------------42
2.1. Scenario building - general considerations -------------------------------------------------42
2.2. Future carbon dioxide (CO2) emission scenarios ------------------------------------------43
2.3. Regional transport assumptions --------------------------------------------------------------44
2.4. Urban transport assumptions -----------------------------------------------------------------45
2.4.1. Urban-center categories ------------------------------------------------------------------ 46
2.4.2. Assumptions for modeling urban mobility -------------------------------------------- 50
2.4.3. Investment assumptions for the Reference Scenario -------------------------------- 54
2.5. Aspects of transport modeling -----------------------------------------------------------------55
2.5.1. Transport planning and modeling ------------------------------------------------------ 56
2.5.2. The “Four-Stages” model ------------------------------------------------------------------ 57
2.5.3. Macroeconomic scenarios ---------------------------------------------------------------- 59
2.5.4. Emission modeling in the transport sector -------------------------------------------- 59
--------------------------------------------------------61
2.6.1. Parameters and general criteria --------------------------------------------------------- 61
2.6.2. Net investments curve --------------------------------------------------------------------- 62
2.6.3. Other indicators selected as analysis parameters ------------------------------------ 63
--------------------------------------- 63
---------------- 66
2.6.3.3. Final net investment curve ------------------------------------------------------ 68
2.6.4. Parameters and criteria for evaluating fuel economies ------------------------------ 71
2.6.5. Criteria and sources for urban passenger modeling --------------------------------- 72
2.6.5.1. Evaluation of operating gains in the “T5 Corridor” -------------------------- 73
2.6.5.2. Investment, operation and maintenance costs and operating gains
based on the study of the “T5 Corridor” --------------------------------------- 76
2.6.5.3. Investments, operation and maintenance costs and operating gains
for BRT in the present study ----------------------------------------------------- 77
----------------------------81
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----------------------------------83
---------------85
2.6.6. Criteria and sources for regional modeling --------------------------------------------88
------------------------------------------------------------89
-----------------------------------------------------------------90
2.7. Conclusions ----------------------------------------------------------------------------------------91
3. REFERENCE SCENARIO -----------------------------------------------------------------------------------93
3.1. Building the Reference Scenario --------------------------------------------------------------94
3.2. Reference Scenario projections ---------------------------------------------------------------95
4. MITIGATION OPTIONS ------------------------------------------------------------------------------------100
4.1. Mitigation options for regional transport -------------------------------------------------- 100
4.1.1. Modal shift - freight -------------------------------------------------------------------------100
4.1.2. Modal shift - passengers -------------------------------------------------------------------108
---------------------------------------------------------------------------112
4.1.4. Measures for overcoming barriers ------------------------------------------------------112
4.2. Mitigation options for urban transport -----------------------------------------------------113
4.2.1. Use of high-occupancy public transport ------------------------------------------------113
4.2.2. Description of policies for the BRT and Metro -----------------------------------------123
4.2.3. Travel demand management -------------------------------------------------------------124
-------------------------------------------------------------------130
4.2.3.2. Political economy scenario -----------------------------------------------------131
4.2.4. Implementation of bikeways -------------------------------------------------------------132
------------------------------------------------------------------136
4.2.4.2. Description of policies -----------------------------------------------------------137
4.2.4.3. Political economy scenario -----------------------------------------------------137
4.3. Low carbon scenario for ethanol - increasing proportion of ethanol
consumption by “Flex-Fuel” vehicles ---------------------------------------------------------137
4.3.1. Parameters for the low-carbon scenario ---------------------------------------------------------139
-------------------------------------139
-------140
4.3.2. Gains in terms of emissions reductions -------------------------------------------------141
4.3.3. “Investments required” abatement curve ----------------------------------------------144
4.3.4. Barriers and measures to overcome them ---------------------------------------------145
4.3.4.1. Establishment of a National Fuels Policy --------------------------------------146
4.4. Consolidated results ---------------------------------------------------------------------------148
5. GENERAL CONCLUSIONS----------------------------------------------------------------------------------158
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LIST OF TABLES
Table 1: Vehicle Production 1999 – 2008 ------------------------------------------------------------------------20
Table 2: Daily travel by motorized transport in Brazilian cities /
Metropolitan Regions (2005) -------------------------------------------------------------------------------------29
Table 3: Total number of trips in RJMR (per day) ---------------------------------------------------------------33
Table 4: Percentage of Population and Urban Location -
Brazil and cities with over 20,000 inhabitants -----------------------------------------------------------------39
Table 5: Investment in Regional Transport Infrastructure ---------------------------------------------------45
Table 6: Major urban regions and municipalities by similarity cluster -------------------------------------47
Table 7: Selected socioeconomic and demographic indicators for urban similarity cluster -----------48
Table 8: Households by income (minimum wages) by urban cluster – 2007 ------------------------------49
Table 9: Urban Mobility Plans Available -------------------------------------------------------------------------50
Table 10: Trip-Generating Factors by Similarity Clusters ----------------------------------------------------52
Table 11: Investments in Public and Mass Transport Systems-----------------------------------------------55
Table 12: Entry Data: COPERT-------------------------------------------------------------------------------------60
Table 13: Fuel Production costs -----------------------------------------------------------------------------------72
Table 14: Economic Operating Costs of the Public Transport System in Rio de Janeiro,
considered this study (US$ per km) ------------------------------------------------------------------------------74
Table 15: Investment, Operation and Maintenance Costs and Operating Gains calculated
on the basis of the “T5 Corridor” study (US$ per km) ---------------------------------------------------------76
Table 16: Km of BRT to be Implemented in the Reference and Low Carbon Scenarios ------------------77
Table 17: Values of Investments and Costs of O & M Operations and Gains in the
Reference and Low-Carbon Scenarios ---------------------------------------------------------------------------78
Table 18: Values of Investments and Costs of O & M Operations and Gains in the
Reference and the Low Carbon Scenarios for BRT Implementation ---------------------------------------80
on the study of the T5 Corridor Study (in US$ per km) --------------------------------------------------------83
in the Reference and Low-Carbon Scenarios -------------------------------------------------------------------84
----------------------------------------------- 86
------- 87
Table 23A: Projections of Consumption by Type of Fuel in the Reference Scenario ---------------------- 93
----------- 94
Table 24: Load and GHG Emissions for the Reference Scenario, 2007–30 --------------------------------- 96
Table 25: Comparison of Projected Emissions Reduction for Regional Transport
in 2030: Modal Shift Scenario ------------------------------------------------------------------------------------- 101
Table 26: Avoided Emissions - New Modal Shift ---------------------------------------------------------------- 102
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Table 27: Regional Freight Transport: Comparison of Investments
in the Reference and Low-carbon Scenarios, 2010–30 ------------------------------------------------------- 103
Table 28: Average cost of avoided CO 2 --------------------------------------------------------------------------- 107
----------- 108
Table 30: High Speed Train (TAV): Emissions Avoided -------------------------------------------------------- 109
Table 31: Average costs of CO 2 avoided ------------------------------------------------------------------------- 111
-------------------------------------------- 115
Table 33: Emissions avoided – BRT ------------------------------------------------------------------------------- 115
------------------- 119
Table 35: Avoided Emissions – Metro ---------------------------------------------------------------------------- 119
Table 35A: Emissions avoided - Metro + BRT ------------------------------------------------------------------- 120
Table 36: Average costs of avoided CO 2 e – BRT ---------------------------------------------------------------- 123
Table 38: Gains from Demand Management in Brazil´s large cities ----------------------------------------- 126
Table 39A: Loads and emissions - Demand Management of Urban Transport -
--------------------------------------------------------------------------------- 127
Table 39B: Emissions avoided - Demand Management of Urban Transport -
--------------------------------------------------------------------------------- 127
Table 40: Average cost of avoided CO 2 and t -------------------------------------------------------------------- 129
Table 41 Bikeway Loads and Gains in Avoided Emissions, 2010–30 --------------------------------------- 133
Table 41A: Loads and Emissions - Implementation of Bikeways -
--------------------------------------------------------------------------------- 134
Table 41B: Avoided Emissions - Implementation of Bikeways ---------------------------------------------- 134
Table 42: Average Cost of Tons of CO 2 Avoided ---------------------------------------------------------------- 136
Table 43 - Light Passenger Vehicle Fleet ( by Type of Fuel ) --------------------------------------------------- 139
Table 44 - States were Alcohol Prices were Competitive with Gasoline Prices (April 2009) ----------- 140
Table 45: Avoided Emissions - Low Carbon Ethanol ----------------------------------------------------------- 142
-------------------------------------- 143
Table 47: Investments and Costs of Avoided Tons of CO2 ----------------------------------------------------- 145
Table 48: Fuel Consumption Trends in the Reference and Low-Carbon Scenarios ---------------------- 148
Table 49: Evolution of Direct Emissions (in MtCO2) in the Reference and Low Carbon Scenarios ----- 149
Table 50: Transport-sector Load and GHG Emissions in the
Reference and Low-carbon Scenario ---------------------------------------------------------------------------- 156
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LIST OF FIGURES
Figure 1: Evolution of the road and rail networks (1996-2006) --------------------------------------------- 19
Figure 2: Production and numbers of light vehicles in circulation ------------------------------------------ 20
Figure 3: Production and numbers of heavy vehicles in circulation ---------------------------------------- 20
------------------------------------------------------------------------ 21
Figure 4A: Percentage Evolution of the Fleet in Circulation, GDP and Population in Brazil ------------- 21
Figure 5: Fossil-fuel Consumption, by Sector ------------------------------------------------------------------- 22
Figure 6: Relative contribution of air pollutant emissions (by source)
in the São Paulo Metropolitan Region ---------------------------------------------------------------------------- 24
Figure 7: Liquid fuels consumption in Brazil, by sector ------------------------------------------------------- 26
Figure 8: Emissions in Brazil´s Transport Sector (2007) ----------------------------------------------------- 27
Figure 9: Evolution of the Urban and Rural Population in Brazil -------------------------------------------- 28
Figure 10: Daily Motorized Trips: Public V Individual Transport Modes ---------------------------------- 29
Figure 11: Percentage Changes in Trips made by Public and Individual
Transport in the São Paulo Metropolitan Region -------------------------------------------------------------- 30
Figure 12: Daily Motorized Trips, by mode,
in the São Paulo Metropolitan Region (1997 and 2007) ------------------------------------------------------ 31
Figure 13: Changes in Incomes in the São Paulo
Metropolitan Region (November 2007 values) ---------------------------------------------------------------- 32
Figure 14: Modal Split of Regional Freight Transport in Brazil ---------------------------------------------- 34
Figure 15: Geo-referenced Multimodal Network -------------------------------------------------------------- 35
Figure 16: Investments in Regional Transport Infrastructure outlined in the PAC and PNLT ---------- 38
Figure 17: Emissions by the Transport System, by segment (2007) ---------------------------------------- 41
Figure 18: Households by income (minimum wages) by urban cluster (2007) -------------------------- 49
Figure 19: Public Transport and Individual Trip-Generation Factors, by Urban Cluster Similarity --- 53
Figure 20: Household Trip-Generation Factors according to Income Levels,
by Urban Cluster Similarity ---------------------------------------------------------------------------------------- 53
Figure 21: Analytical model for transport planning ----------------------------------------------------------- 56
Figure 22: Sequencing of the “Four-Stage” Transport Model ------------------------------------------------ 57
Figure 23: The “Net Investments” Curve ------------------------------------------------------------------------ 62
---------------------------------------------------- 64
-------------------------------- 67
Figure 26: The “Final Net Investments” Curve ------------------------------------------------------------------ 70
Figure 27: Linking Regional and Urban Transport to Fuel Consumption ---------------------------------- 92
Figure 28: Evolution of Transport Sector Emissions in the Reference Scenario -------------------------- 97
Figure 29: Fuel Consumption Trends (in TEP) by 2030,
by type of vehicle in the Reference Scenario -------------------------------------------------------------------- 97
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Figure 30: Comparison of the Evolution of Emissions by Vehicle Type in the
------------------------------- 98
Figure 31: Evolution of Regional Transport Emissions to 2030 (by vehicle type)
in the Reference Scenario ------------------------------------------------------------------------------------------ 99
Figure 32: Evolution of Urban Transport Emissions to 2030 (by type of vehicle)
in the Reference Scenario ------------------------------------------------------------------------------------------ 99
Figure 33: Comparison of Modal Distribution of Freight Load:
Reference v Low Carbon Scenario -------------------------------------------------------------------------------- 102
--------------------- 104
------------------ 104
Figure 33C: Soybean Freight Loads in Bahia - Reference Scenario ------------------------------------------ 105
Figure 33D: Soybean Freight Loads in Bahia - Reference Scenario ----------------------------------------- 105
Figure 34: Evolution of Emissions: Reference versus Low Carbon Scenario ------------------------------ 106
Figure 35: Curves of cost reduction (nominal) ----------------------------------------------------------------- 106
Figure 36: Abatement Cost Curves (present value) ----------------------------------------------------------- 107
--------------- 109
------------------------------------- 110
Figure 39: Cost Reduction Curves (Nominal) ------------------------------------------------------------------- 110
Figure 40: Abatement Cost Curves (Present Value) ----------------------------------------------------------- 111
Figure 40A: Belo Horizonte: with and without Investments in BRT
(2030 Reference and Low Carbon Scenarios) - Public Transport Passenger Loads --------------------- 116
Figure 40B: Belo Horizonte: with and without Investments in BRT
(2030 Reference and Low Carbon Scenarios) - Private Vehicle Users -------------------------------------- 116
------------ 117
Figure 42: Fuel Consumption Trends (TEP) up to 2030, by Vehicle Type - BRT-
---------------------------------------------------------------------------------- 117
--------------------------------------- 118
Figure 44: Modal Distribution of loads - BRT + Metro --------------------------------------------------------- 120
Figure 45: Fuel consumption (TEP) - BRT + Metro ------------------------------------------------------------ 121
Figure 46: Evolution of emissions: BRT + Metro --------------------------------------------------------------- 121
Figure 47: Cost Abatement Curves for BRT + Subway (nominalNominal) --------------------------------- 122
Figure 48: Cost Abatement Curves for BRT + Subway (present value) ------------------------------------- 123
Figure 49: Evolution of Emissions - Demand Management of Urban Transport:
---------------------------------------------------------------------------------- 128
Figure 50: Cost Reduction Curves (nominal) ------------------------------------------------------------------- 128
Figure 51: Abatement Cost Curves (present value) ----------------------------------------------------------- 129
Figure 52: Cost per Ton Avoided X Investments Required by Urban Demand
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Management (per annum up to 2030) --------------------------------------------------------------------------- 130
Figure 53: Evolution of Emissions - Implementation of Bikeways:
---------------------------------------------------------------------------------- 135
Figure 54: Cost Abatement Curves ( nominal) ------------------------------------------------------------------ 135
Figure 55: Cost Abatement Curves (present value) ----------------------------------------------------------- 136
Figure 56 - Evolution of Light Vehicle Sales by Fuel Type (1979-2007) ------------------------------------ 138
--------------------------------------------------------------------------------------------- 141
----------------------------- 143
----------------------- 144
Figure 60: Emission and Mitigation of Urban and Regional Transport 2010 through 2030 ------------ 150
Figure 61: Growth in Transport Fleet, 2007 to 2030 ---------------------------------------------------------- 151
Figure 62: Changes in Passenger Load --------------------------------------------------------------------------- 152
Figure 63: Comparison of Modal Distribution of Freight Load, 2008–30 ---------------------------------- 153
Figure 64: Comparison of Modal Distribution of Passenger Load, 2008–30 ------------------------------ 154
Figure 65: Emissions-reduction Potential in the Transport Sector, 2008–30 ----------------------------- 155
Figure 66: Comparison of Emissions in Reference, Low-carbon, and “Fossil-fuel”
Scenarios, 2008–30 ------------------------------------------------------------------------------------------------- 157
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Acronyms
ABRACICLO: Associação Brasileira dos Fabricantes de Motocicletas, Ciclomotores,
Motonetas, Bicicletas e Similares (Brazilian Association of Motorcycle, Moped, and Bi-
cycle Manufacturers)
ANAC: Agência Nacional de Aviação Civil (National Civil Aviation Agency)
ANP: Agência Nacional de Petróleo (National Petroleum Agency)
ANTAQ: Agência Nacional de Transportes Aquaviários (National Agency for Water
Transport)
ANTP: Agência Nacional de Transportes Públicos (National Agency for Public Trans-
portation)
ANTT: Agência Nacional de Transportes Terrestres (National Land Transport Agen-
cy)
BRT: Bus Rapid Transit
CETESB: Companhia de Tecnologia de Saneamento Ambiental (Environmental Sanita-
tion Technology Company)
DENATRAN: Departamento Nacional de Transportes (Transportation National De-
partment)
DUTO: Pipelines
EMBRAPA: Empresa Brasileira de Pesquisa Agropecuária (Brazilian Enterprise for
Agricultural Research)
EMME: modeling software for transport
FERRO: Railroads
FIFA: International Federation of Football Association.
FIPE: Fundação e Instituto de Pesquisas Econômicas (Foundation and Institute for
Economic Research)
GDP: Gross Domestic Product
GEIPOT: Empresa Brasileira de Planejamento de Transportes (Brazilian Company for
Transportation Planning)
GHG: Greenhouse Gases
HIDRO: Waterways
and Statistics)
INFRAERO: Empresa Brasileira de Infra-Estrutura Aeroportuária (Brazilian Company
for Airport Infrastructure)
IPEA: Instituto de Pesquisa Econômica Aplicada (Institute for Applied Economic Re-
search)
MANTRA: modeling software for transport
O&M: operation and maintenance of infrastructure for transport
PAC: Plano de Aceleração do Crescimento (Growth Acceleration Program)
PDTU: Plano de Desenvolvimento do Transporte Urbano (Plan for Urban Transporta-
tion Development)
PNE: Plano Nacional de Energia (Energy National Plan)
-
port)
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PNMC: Plano Nacional Sobre Mudança do Clima (National Plan for Climate Change)
POP: Population
RM: Metropolitan Regions
RODO: Roadways
SM: Minimum wage
TransCAD: Geographic processing and modeling software for transport
VLP: Light commercial vehicles
VLP: Light passenger vehicles
VPC: Heavy truck vehicles
VPO: Heavy bus vehicles
Units
MtCO2e: Millions tons of CO2 equivalent
Passengers x Km: loading of passengers or volume of passengers transported,
expresses the total passengers carried multiplied by the number of miles trav-
eled.
TEP’s: Tons of Equivalent Petroleum
Tons x Km: loading cargo or cargo volume transported, expresses the total cargo
carried multiplied by the number of miles traveled.
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ACKNOWLEDGEMENTS
This report summarizes the results for the transportation sector from a larger study,
the Low Carbon Study for Brazil, developed by the World Bank as part of its initiative to
consultation and research process to identify the best available knowledge, scientists,
Environment, and Science and Technology. Several seminars were organized, enabling
consultation with representatives of Ministries of Finance, Planning, Agriculture,
Transport, Mines and Energy, Industry and Commerce. Public agencies and research
center also participated during the consultation sessions, including EMBRAPA, INT,
EPE, CETESB, INPE, COPPE, UFMG, UNICAMP and USP.
The study covers four key areas with potential low carbon options: (i) land use, land
use change and forestry (LULUCF), including deforestation, (ii) transport systems,
(iii) production and use of energy, particularly electricity, oil, gas and biofuels, and (iv)
municipal waste, solids and liquids. This document has received support from more
than 15 technical reports and four summary reports for the four main areas. Also, the
study has received support from the World Bank, through resources provided by the
Sustainable Development Network for activities related to climate change and regional
support through the Energy Sector Management Assistance Program (ESMAP).
This synthesis report was prepared by a team led by Wagner Colombini Martins,
LOGIT, Christophe de Gouvello and Paul Procee, Bank World. The main contributors
were Fuad Jorge Alves José, Wagner Colombini Martins, Fernando Howat Rodrigues,
Arthur C. Szasz, and Sérgio H. Demarchi, LOGIT. The World Bank supervision team for
the Low Carbon Study for Brazil was composed by Christophe de Gouvello, Jennifer
Meihuy Chang, Govinda Timilsina, Paul Procee, Mark Lundell, Garo Batmanian, Adriana
Moreira, Fowzia Hassan, Barbara Farinelli, Augusto Jucá, Rogério Pinto, Francisco
Fernanda Pacheco, Sebastien Pascual, and Megan Hansen.
The supervision team would like to thank also Helena Jansen and John Penney for
their support in editing and translating the report, respectively.
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INTRODUCTION1
emissions of greenhouse gases (GHGs)1 arising from all areas of human activity. More
sector. These alternatives could contribute positively to the world’s climate, as well
potential carbon emissions reduction will be submitted to the Brazilian government
to assist it in the design and deployment of joint planning strategies in key sectors,
including transport.
To ensure that the study targets the most important areas, it adopts an overarching
approach. This means that it made full use of available specialist knowledge (thereby
CO2 results from the combustion of any material containing carbon, including fossil
fuels such as oil, coal and natural gas, which consist of long chains of hydrocarbons and
are widely used for electricity generation and transport purposes. Industrial activities
such as metallurgy, steel and cement manufacturing also produce large amounts of CO2.
are also responsible for CO2 emissions, since the loss of forest cover releases some of
the carbon stored in the soil and dead vegetation.
Brazil’s contribution to global CO2 emissions is substantial due to forest burning,
and halting biomass burning should certainly be a national priority. On the other
hand, the country´s contribution to global GHGs by burning fossil fuels is very small,
amounting to around 1.2% of total global emissions in 2006, according to data from the
emission rate per capita in 2006 was 0.51Mt CO 2, well below the world average of 1.25
Mt per capita.
However, this current situation could change over the years if nothing is done to
reverse certain trends emerging against a backdrop of sustained economic growth.
the Brazilian coast could result in increased fossil-fuel use. Furthermore, although the
country has low rates of GHG emissions, this is not the case for local pollutants which
are highly hazardous to human health. In large Brazilian cities air pollution levels are
fuels in motor vehicles, reducing them can lead to an overall reduction of GHGs - an
gases related to human life, with CO2e the most prominent.
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Following the general guidelines for the transport sector study, we decided to adopt
a methodological approach based on four steps:
policies of the Brazilian government;
development goals;
identifying the main obstacles to their adoption and suggesting possible measures for
overcoming them; and
macroeconomic impact of shifting from the “Reference Scenario” to a “Low-Carbon
To quantify and evaluate the potential for reducing carbon emissions in
the transport sector, this study developed special models (consistent with the
macroeconomic scenario adopted for the study) to determine the requirements for
scenarios analyzed (reference and low-carbon). The modeling involved constructing
separate simulations for urban and regional transport, based upon the traditional
groupings used in transport sector studies:
o Urban Transport: travel in the urban-metropolitan area; and
o Regional Transport: travel in rural areas, in the air and in places where
highways, waterways, railways and pipelines pass through large urban centers.
o Passengers
o Freight
of vehicles and/or modes of travel. The transport simulation processes used the
volume indicator known as “loading” (the values represented by demand for freight or
passenger transport on each stretch of a route - urban, regional, overland, waterborne
or air), as the “standard unit of measurement”, customarily applied to freight and
passenger movements and convertible into “units of GHG emissions”.
kilometers, the passenger and freight demand indicators were converted into
kilometers traveled by each mode of transport: cars, buses, trucks, trains, metro
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The reference and low-carbon scenarios were structured on the basis of
bibliographic research, consultations with specialists and analysis of metropolitan
area master plans and government plans and programs. The probable emissions for
the reference scenario were calculated and a set of options for mitigation measures
that might feasibly be deployed by 2030 was selected. The details of these measures,
The results for the transport sector, calculated using the methodological approach
and criteria outlined in the introductory paragraphs, are presented in this report as
follows:
reducing GHGs in the transport sector;
and strategies for Brazil to pursue.
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Historical Overview of Transport in Brazil1.1
the British railway industry through the 1930s. Over 30,000 km of railways were
Following the 1929 crisis and the advent of WWII, the industrialization of Brazil
proceeded apace, leading to increased demand for goods and services in the domestic
market. This brought about the need to build roads for distributing goods produced
in the Southeast - mainly in São Paulo, which had fast become Brazil´s preeminent
roads became the primary means of transport. Between the 1940s and 70s the
around 1.5 million km. At the same time, the railway network declined from 38,000 km
More recently, as shown in Figure 1, the paved-road network has continued to
30,000 km, notwithstanding the upgrading resulting from the gradual privatization of
much of the network for freight operations.
Figure 1: Evolution of the road and rail networks (1996-2006)
Source: ANTT / GEIPOT / Logit
the importance of the roads sector. The number of motor vehicles produced in Brazil
virtually tripling. Table 1 shows the evolution of production by type of vehicle.
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Table 1: Vehicle Production 1999 – 2008
Vehicle Type 2008 1999 Growth (%)
Cars 2,425,68 1,109,509 118
Light Commercial 426,874 176, 994 131
Trucks 163,681 55, 277 196
Buses 38,202 14, 934 155
Total 3,054,725 1,356,714 125
Source: ANFAVEA (2009)
Figures 2 and 3
light-duty commercial vehicles, buses and trucks. Note that the categories of light
vehicles increased overall by 300% and trucks by 200%.
Figure 2: Production and numbers of light vehicles in circulation
Source: DENATRAN / ANFAVEA / Logit
Figure 3: Production and numbers of heavy vehicles in circulation
Source: DENATRAN / ANFAVEA Processing / Logit
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It is worth noting the recent upsurge in the number of motor vehicles in circulation
(i.e. increased motorization) between 2002 and 2007, as can be seen in Figure 4.
Source: DENATRAN / ANFAVEA / Logit
In the light vehicle category, the number of cars increased by 21.4% and while light-
duty commercial vehicles increased by 19.4% during this period. As for heavy-duty
vehicles, the number of buses and trucks increased by 16.4% and 17.0% respectively.
with issues related to atmospheric emissions, including CO2, in the transport sector.
Figure 4A: Percentage Evolution of the Fleet in Circulation, GDP and Population in Brazil
Source: DENATRAN / ANFAVEA / Logit
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population. This development, particularly noticeable over the past 10 years,
highlights the continuing upsurge in current growth levels and points to the prospect of
even higher future motorization rates.
Transport and the Productive Sectors1.2
regional transport, the privatization and concessionary outsourcing of the country´s
main transport systems (roads, railways, ports) was responsible for the emergence
of new market mechanisms. These are still undergoing a process of adaptation,
restructuring and evaluation. Competition with international operators, spurred
by easier access to the Brazilian market, is a challenge now faced by practitioners
in this sector. Meanwhile, the general transport infrastructure - a determining
factor for promoting and generating economic and regional development - has been
costs of many goods and services), have risen steeply (PLANET, 2006). The so-called
other, particularly Asian, “emerging” countries.
The transport sector is the biggest consumer of fossil fuels, accounting for 50.5% of
Brazil´s total. Figure 5
the economy.
Figure 5: Fossil-fuel Consumption, by Sector
Source: BEN (2008) National Energy Balance
In the urban transport sector in Brazil some of services that have larger capacities,
customers as a result of increased availability. In addition, low-capacity vehicles
(mini-buses and vans) have begun operating in many cities. Frequently operating with
Technical Synthesis Report | TRANSPORT
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little or no supervision by the responsible regulatory bodies, these compete directly
with larger- capacity systems such as buses. While the smaller passenger-carrying
(unregulated routes and informal stopping points), contributing to increased
congestion and negative environmental impacts. This situation is particularly bad
in the large metropolitan areas, which face acute problems of balancing supply and
demand for public transport, particularly at peak rush-hour times, when the road and
Impacts Generated by the Transport Sector1.3
The transport sector is vital to economic and social development. While it can
accelerate worldwide, growth in the developing and emerging countries will be
especially rapid due to increasing prosperity. This may well be accompanied by serious
environmental impacts, particularly degraded air quality in the urban areas where
et al., 2004).
In addition to the problems caused by vehicle emissions, other impacts (less studied
but no less important) are generated by transport systems, including noise pollution,
Urban transport in Brazil predominantly concerns road transport, given that
in urban areas most trips are made by car or bus (e.g. around 55% in the city of Rio
2007).
The gases and particles emitted daily by millions of vehicles in the cities
and on intercity highways tend to accumulate in the atmosphere at different
concentrations. They are dispersed by wind, trapped by thermal inversion, diluted
and washed away by rain, or they may react with one another or with naturally-
occurring elements to form secondary pollutants. The more stable gases remain
in the atmosphere for longer, sometimes for months or years2, reaching the higher
layers of the atmosphere and causing problems of a global magnitude such as the
the Metropolitan Region of São Paulo (MRSP), motor vehicles are major sources of
contribute to emissions of particulate matter (PM), responsible for increasing rates of
respiratory disease, especially during colder periods when pollutant concentrations
are highest.
the transport sector accounts for the largest percentage
. CO
2 CO 2 remains in the atmosphere, on average, for 140 years
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for those with cardiovascular
CO
Hydrocarbons (HC) contain various pollutants known as volatile organic
system and evaporation. The
anthropogenic emissions of HC, 35% of them in the industrialized world. In the MRSP
vehicles contribute over 97% of the total emissions of this pollutant (CETESB, 2005).
HCs are precursors to the formation of tropospheric ozone,
carcinogenic. The transport sector accounts for 50-75% of the HC types in the world
considered to be carcinogenic. They can also cause neurological and respiratory
problems as well as limit reproduction and children’s growth.
industrialized countries has virtually cancelled out the gains created by more stringent
from and high compression rates, as in diesel engines. In the MRSP the
emissions, as shown in Figure 6 below.
Figure 6: Relative contribution of air pollutant emissions (by source) in the São Paulo
Metropolitan Region
Source: Report of Air Quality - 2005 CETESB
2), damage can be caused to the respiratory
diseases in children, in addition to causing damage to the ecosystems of lakes, estuaries
and forests.
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Ozone (O3) is a secondary pollutant (formed by photochemical reactions in the
the formation of tropospheric O3. In the stratosphere, ozone occurs naturally, forming
a protective layer against ultraviolet radiation. At ground level, however, ozone is a
dangerous pollutant and the primary component of photochemical smog.3 Evidence
O3.3
2), originate
have forced a marked reduction in the sulfur content of fuels permitted for use in
transport. In the United States, Europe and Japan, the levels of sulfur in vehicle fuels
are currently very low, at around 10-15 ppm. In Brazil, these are 500 ppm in the
metropolitan areas and 2,000 ppm in the
areas and 500 ppm
aerosol sulfate is a major particulate-forming agent. Furthermore, it is estimated that
over 12% of the SO2 emitted in urban areas turns into sulfate MP when released into the
acid, together with HNO3 , causes major damage to the ecosystem.
Particulate Matter (PM) is composed of solid or liquid particles suspended in the
air. MP includes acids and heavy hydrocarbons, carbonaceous material with soluble
fractions absorbed even by dust grains. PM10 includes all particles with a diameter
particles in the atmosphere is less than twenty four hours. MP2.5 includes all particles
of a diameter of less than 2.5 micrometers. Particles of this size can be emitted as
primary pollutants such as soot, or formed by incomplete combustion, or as acid
micrometers) in urban areas. In the MRSP, CETESB estimated in 2005 that about 30%
smaller particles are easily inhaled and can settle deep in the lungs, creating more
serious health hazards than those caused by larger particles, which would most
Transport and Carbon Emissions1.4
The alarm regarding increased concentrations of CO2 in the earth’s atmosphere
taking daily measurements of the atmosphere on the top of Mauna Loa, Hawaii’s tallest
mountain (Gore, 2006). But it was not until the 1980s and 90s that this message was
taken seriously around the world, especially following the Rio Conference on Climate
3 Photochemical smog results from chemical reactions between hydrocarbons (HC) and other gases in
the atmosphere, particularly ozone (O3) , and nitrogen oxides (NOx) when they combine in presence of
sunlight.
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According to May (2003), climate change was incorporated into the global political
agenda in the mid-1980s and began to assume a central role as concern grew about
possible changes in the world´s climate system. May also argues that, in addition to the
many uncertainties surrounding the issue, a political undertone hangs over the issue:
given the speed of the economic growth process, the consequences of global warming
could be negative for some countries and positive for others - resulting in an additional
source of inequality between North and South.
The UN Framework Convention on Climate Change, adopted in May 1992 in New
York and later signed by over 150 countries at Rio-92, divides countries into two
groups: the major CO2
2
commitment to reduce emissions, given that Article 3 of the Convention enshrines the
According to Brazil´s National Energy Plan, PNE (2007), the transport sector
demand for liquid fuels is the highest among all the country´s productive sectors.
Figure 7: Liquid fuels consumption in Brazil, by sector
Source: POE 2030 / Logit
As can be seen in Figure 7, Brazil´s transport sector consumed in 2005
TOE (million tons of oil equivalent) of liquid fuels, amounting
to around 75% of the total amount consumed in the country. Projections for 2030
estimate that this percentage will remain at the same level (just over 73%), indicating
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that if nothing is done, the transport sector will continue to be responsible for the
majority of CO2 emissions from the combustion of liquid fuels. The increased absolute
consumption level will produce a higher amount of CO2 emissions. A pressing need
set of strategies and mitigation options that could, over
time, lead to reduced consumption in the sector, thereby helping to reduce the impacts
of GHG emissions overall.
90% of GHG emissions originate from road transport (CTS, 2008). The transport sector
as a whole accounted for the second largest source of emissions of greenhouse gases
(18% of total GHG emissions).
Figure 8.
Figure 8: Emissions in Brazil´s Transport Sector (2007)
Source: Logit / 2009
According to estimates made in the course of our study, CO2 emissions in the
million tons (91%
metropolitan areas (urban transport) and 33% in rural areas and at places where roads
crossed urban-metropolitan areas (regional transport).
From the above it is clear that measures to mitigate greenhouse gas emissions need
to concentrate on increasing the use of alternative modes to road transport at the
regional level, and to promote the rational use of modes in the case of urban transport.
Furthermore, developing and encouraging the use of vehicles of all types capable of
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burning cleaner fuels could have a large impact.
General Considerations on Urban Transport1.5
According to the Demographic Census 2000, some 80% of all Brazilians now live in
cities (compared with 56% in 1970). This increase in the number of city-dwellers was
not accompanied by a proportional increase in investments in transport, education and
housing (See Figure 9).
Figure 9: Evolution of the Urban and Rural Population in Brazil
Source: IBGE Census / Logit
The lack of investment resources and the slow response of government agencies
responsible for major development programs (e.g. health, education and transport)
have contributed to burgeoning social problems in the cities. As a result of the
precarious urban infrastructure, quality of life in Brazil’s major cities has gradually
declined. Travel by public transport remains one of the main problems faced by the
population.
Population growth in the cities has generated a substantial increase in daily trips,
especially those involving people going to and from work. This involves large numbers
of vehicles vying for limited space and, given the chronically bad state of much of the
at peak times (morning and late afternoon rush-hours). In addition to generating
economic losses, bottlenecks and delays undermine the quality of life of the travelling
public and city-dwellers in general, and increase emissions of GHG and other
pollutants.
According to ANTP (2007), an estimated 90 million motorized trips are made every
day in Brazil´s cities with populations of over 60,000. City buses account for 44.1% of
urban trips, while suburban commuter trains and the metro are key components of the
urban transport system in the metropolitan regions, accounting for an estimated 18%
of trips in urban areas with populations of over 1 million.
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Table 2: Daily travel by motorized transport in Brazilian cities /
Metropolitan Regions (2005)
Mode
Daily trips (thousands)
Cities by population (thousands) Total
> 1 million 500-1000 250 - 500 100-250l 60 - 100
Absolute %
Bus 23,394 5,483 5,139 3,986 1,958 39,961 44.1
Rail 5,008 17 0 0 0 5,025 5.5
Public transport 28,403 5,500 5,139 3,986 1,958 44,986 49.7
Car 22,053 7,256 5,911 4,667 1,842 41,728 46.1
Motorcycle 1,208 447 761 903 564 3,883 4.3
Individual 23,261 7,703 6,672 5,569 2,406 45,611 50.3
Total Abs 51,664 13,203 11,811 9,556 4,364 90,597 100.0
% 57.0 14.6 13.0 10.5 4.8 100.0 -
Source: ANTP (2007)
In cities with over 1 million inhabitants, 55% of daily trips are on public transport
and 45% using individual modes (ANTP, 2007). In the remaining cities individual
modes of transport predominate, as illustrated in Figure 10.
Figure 10: Daily Motorized Trips: Public V Individual Transport Modes
Source: ANTP (2007)
trips are made by regular bus (PDTU, 2005), representing 35% of total trips. In the São
Paulo Metropolitan Region the percentage is around 33%, representing around 8.3
million daily trips (Metro-OD survey, 2007).
mini-buses). In Rio de Janeiro these account for about 1.7 million trips daily or 8%
of the total (PDTU, 2005), while in the SPMR the number is lower: 0.7 million trips,
amounting to 2.8% of total motorized trips (Metro-OD survey, 2007).
Figure 11 below illustrates the changes (in %) that have occurred in the SPMR
in trips made by public and individual transport over the past 40 years. Figure 12
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indicates the total numbers of trips, by mode, made in the same area in the ten-year
period 1997-2007. This data was assembled from the Origin and Destination surveys
carried out every ten years (and more recently every 5 years) by the São Paulo public
transport authorities, coordinated by the São Paulo Metro Company.
Figure 11 clearly shows the rapid growth of individual motorized trips in São Paulo
compared with travel by public transport: 70% and 30% in 1967 and 51% and 49% in
1997 respectively.
Figure 11: Percentage Changes in Trips made by Public and Individual Transport in the
São Paulo Metropolitan Region
Source: OD - Metro / Logit
municipalities within the São Paulo Metropolitan Region surpassed the number of
trips made by public transport, which declined from 52% to 48%. In 2002, however,
individual trips fell back to 45%, after peaking in 2002.
Figure 12
from 1997 to 2007 – about 4.6 million trips, with 3.5 million on public transportation
(75%) and 1.1 million by individual means (25%). In the public transport sector, the
building and upgrading of a number of suburban train and metro lines during this
on the suburban commuter train system. At the same time, the absolute numbers
of passengers carried by the regular bus services increased at a slightly higher rate:
1,022,000 by bus, compared to 996,000 by rail.
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Figure 12: Daily Motorized Trips, by mode,
in the São Paulo Metropolitan Region (1997 and 2007)
Source: OD- Metro / Logit
The three-fold increase in the number of trips by public transport compared to
individual motorized trips in São Paulo is due mainly to the increased use of light-duty
commercial vehicles for school transport: 1.06 million trips, which increased the
proportion of this mode of transport vis-à-vis the total of daily motorized trips from
1.3% in 1997 to 5.2% in 2007.
Growing public concern over crime and safety (especially concerning
The increase in trips by chartered bus (4.7% a year) most likely also relates to the
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security question, although factors such as commuter preferences to travel by public
considered.
Among the “individual” modes of transport, travel by motorcycle has increased by
over 10% per year, mainly due to the growing need for document and small package
improvements in the public transport infrastructure (which is gradually adapting to
the needs of the population) and may also be the result of a dip in consumer purchasing
power between 1997 and 2007 in the MRSP.
Figure 13 shows that from 1997-2007, average monthly individual incomes in real
terms (November 2007 values), decreased by 3.6% a year in the MRSP.
Figure 13: Changes in Incomes in the São Paulo
Metropolitan Region (November 2007 values)
Source: OD-Metro / Logit
The Rio de Janeiro Urban Transport Master Plan (PDTU), completed in 2005,
provides a breakdown of daily motorized trips in the city, including trips made by
regular bus service.
Table 3 shows the modal split of these
motorized, with bus trips accounting for over half.
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Table 3: Total number of trips in RJMR (per day)
Mode Number of trips Percentage of
total
Motorized and
Non-Motorized (%)
Bus 6.5 million 32.5 51.8
Other public transport 2.5 million 12.5 19.9
Cars 3 million 15.0 23.9
Motorcycle 100, 000 0.5 0.8
Other motorized (*) 450, 000 2.2 3.6
Sub-Total Motorized 12,550,000 62.7 100.0
On foot 6.8 million 34.0 91.3
Cycles 650, 000 3.3 8.7
Sub-Total Non-Motorized 7.45 million 37.3 100.0
Total 20 million 100.0 -
(*) Includes school buses, taxis, chartered buses and trucks.
Source: PDTU (2005) / Logit
Interestingly, the total number of trips by public transport in Rio de Janeiro
represents around 72% of all motorized trips, which is well above the 55% estimated
by the MRSP Metro Origin and Destination Survey (2007). This is most likely due to
the fact that trip lengths in Rio (Brazil´s second most highly-populated urban area
after São Paulo) are longer, due to the different geophysical characteristics of the
regular urban bus systems in Brazil. Currently, virtually all Brazilian cities depend on
buses for transporting their populations.
cost of deployment, maintenance and operation of this mode. Notwithstanding the
the lack of consistent and integrated planning of urban transport networks, such as
and budgetary constraints in the majority of Brazilian cities will continue to impact the
Upgrading bus services requires careful consideration of the costs, quality of
A regular and
communities in terms of increased
mobility and accessibility (e.g. to places with good employment opportunities), as well
as to reducing public subsidies needed to operate them (i.e. through higher passenger
loads).
suburban train services should also be considered as major components of the urban
larger passenger capacity and low impact on the local environment.
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General Considerations on Regional Transport1.6
the transport network. This is especially true in the case of surface transport, e.g. the
avoiding hills, steep gradients, rivers and lakes. Sidestep such barriers was frequently
Road transport, on the other hand, evolved quickly during the 20th century
population densities and the type of economic activities (agriculture and livestock
following the growth of the auto industry in Brazil, which was accompanied by heavy
investments in road infrastructure.
Given the naturally-navigable waterways, water transport was developed in the
North and South of the country, making it possible to link the interior to the Atlantic
Ocean. Water transport was also developed intensively in the Southeast region,
although the overcoming natural barriers involved substantial investment.
Commercial air transport developed mainly to satisfy the demand for long-distance
trips and served inter alia to integrate isolated areas into the national territory. Major
air transport hubs took root in the larger, more densely-populated, and wealthier urban
Pipeline networks began developing in Brazil to transport oil, oil products
construction of gas pipelines linking Brazil to Bolivia and Argentina.
terms of tons per kilometer, are illustrated in Figure 14.
Figure 14: Modal Split of Regional Freight Transport in Brazil
Source: Ministry of Transport (2000)
The share of the total volume of freight transported often fails to mirror the relative
economic importance of each of the transport modalities. Some modes, despite
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moving relatively small freight volumes, are responsible for transporting high-value
time contributin a greater proportion in terms of monetary value. This is due to the fact
that the vast majority of merchandise transported by plane possesses a high value-to-
weight ratio, including computer equipment, jewels, and precious stones.
public investment over recent years in infrastructure improvements for other modes,
and the greater operational autonomy of road transporters. Additionally, the ease of
The usage of rail and waterway modes is currently increasing following massive
investment by private operators in port and railway installations and operations.
contributes to less than 1% of the total volume of freight carried.
above-mentioned transport modes. These are illustrated in Figure 10 by a map geo-
referenced in TransCAD software, which shows the major transport routes radiating
from Brazil’s state capitals and large metropolitan regions.
Figure 15: Geo-referenced Multimodal Network
Source: Network 2009 Logit
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social development is essential for ensuring that investment policies and strategies for
improving the regional transport infrastructure are capable of producing the desired
socio-economic impacts. From the economic point of view, the transport sector can be
considered the most dynamic of all the sectors given that it involves a wide variety of
infrastructural components such as roads, highways, ports, airports, and railways.
The impacts and implications that investments in transport infrastructure can have
on development, especially at national and regional levels, continue to be researched
by planners and specialists on the subject. Agreement has been reached on a few issues
but many uncertainties and questions remain unanswered.
Investments in transport infrastructure certainly have short and long-term impacts
on regional economies. However, the scale and sustainability of production growth and
transport infrastructure based on modal integration, inter-modal transfer, lower
operational costs, shorter trip times, and better access to producer regions (PLANET,
2006).
The relationship between transport infrastructure and regional development is
is considered. These include:
•
•
•
•
•
regional or local).
The temporal dimension of investments is also important. The impact varies
according to the types of transport infrastructure project, but it is generally accepted
that most investments in transport infrastructure, regardless of mode, are likely to
produce at least three types of development-related impacts:
The most immediate impact is on the number of new jobs generated (mostly •
production chains in the goods and services sectors;
The second impact (apparent when the new transport infrastructure is in •
new prospects and activities in the region;
•
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establishment of new alternative routes and modal combinations for
transporting goods and people.
synchronized in time and space - an uneven phenomenon commonly known as the
“development process”.
and problems, evidence appears to show a structural link between transport
infrastructure and regional development. The role of transport cannot be separated
from development questions. No analysis of overall regional development would be
complete without highlighting the fundamental role played by transport infrastructure
in this process.
the question of national or regional development is closely linked with decisions
about transport infrastructure investments at countrywide or regional levels. It is vital
appropriate instruments and action priorities.
The instruments often consist of models or programs used to identify and analyze
the impacts and consequences of the action alternatives.
The Federal Government, through its Growth Acceleration Plan (PAC), aims to
undertake a set of interventions in the country’s infrastructure, including transport
network and port terminals, to the construction of new, essential transport facilities.
In addition to the PAC, the development and deployment of the National Logistics
and Transport Plan (PNLT), revisited in 2007 by the Ministry of Transport, aims to
pursue a number of transport infrastructure projects. Before 2001 the Brazilian
Transport Planning Company (GEIPOT) developed a structure and methodology for
implementing a process for the regional planning of freight and passenger transport.
This was discontinued after the transport sector was restructured, triggered by a
number of privatizations and concessions. The GEIPOT was disbanded and surface-
transport regulatory agencies were created.
The structure of the information bank on freight and passenger transport used in
Reports (AETs) published by GEIPOT. This information bank was updated with
information obtained from national freight and passenger OD surveys conducted
under the aegis of the PNLT in 2007.
However, the most substantial contribution made to the above-mentioned
information bank was the incorporation of a portfolio of transport infrastructure
investment projects analyzed and ranked according to the results of logistics
simulations and national socio-economic priorities. In this way, the PNLT is not only a
Government logistics plan but also a major State Plan designed to ensure a permanent
and environmental concerns, and (ii) to be integrated with relevant government
agencies, operators and other stakeholders in the transport area.
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Figure 16: Investments in Regional Transport Infrastructure outlined in the PAC and PNLT
Source: CAP / PNLT (2007) / Logit
Figure 16 shows that the total investment projected in the PNLT are distributed
more evenly between the three modes than is the case in the PAC. This is likely due to
PNLT, in addition to including virtually all the projects included in the PAC, contains
a set of clear goals, including environmental sustainability targets, to be achieved
two plans will be considered as baselines for projections of future emissions in the
reference and low-carbon scenarios, to be presented in later chapters.
Institutional Overview1.7
with the transport sector. Regional transport matters are linked to the Ministry
of Transport, the Ministry of Defense (Air Transport) and the Special Secretariat
for Ports, while urban transport is governed by guidelines issued by the Ministry
of Cities. A further complicating factor is that the Federal Constitution awards
makes it increasingly complicated to harmonize policies and plans in Brazil’s 5564
municipalities.
CO2),
need to be taken in the transport sector.
The recent National Action Plan on Climate Change (NMCP), based on the PNLT,
modal division through the time horizon of 2030, with a goal
of reducing CO2 emissions. While the Plan refers
nevertheless indicates that transport issues, especially in the metropolitan regions,
merit close attention, given that densely-populated areas are responsible for high CO2
emissions from increased motor vehicle usage.
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In addition to the various ministries involved in the sector, the authorities of the
metropolitan regions and municipalities need to work together to optimize and
implement actions to achieve the low-carbon scenario. Coherent policies and strategic
actions by all stakeholders will hopefully create the synergy needed to reach the stated
goals for reducing environmental impacts.
The City Statute provides the appropriate legal instruments for Brazilian city
managers to transform the good intentions contained in their Master Plans into
concrete proposals for improved city administration. The constitutional provision that
all cities over 20,000 inhabitants are enjoined to produce their own Master Plans will
require a proper assessment of the between transport and urban
development (Ceneviva, 2007).
While only 1,560 of Brazil´s 5,564 municipalities fall into the above category,
together they accounted for 82% of the urban population in 2007 (Institute of
55% of the population resided in predominantly urban areas (metropolitan and core
Table 4.
Table 4: Percentage of Population and Urban Location -
Brazil and cities with over 20,000 inhabitants
Urban
location
Brazil Municipalities > 20 000 inhabs
Number of
Municipalities
Population in 2007 %
Urban
Area
in
2000
Number of
Municipalities
Population in 2007 %
Urban
Area
in
2000
% Brazil
(popula-
tion 2007)
Absolute %
Total
Absolute %
Total
Outside
MR (*)
5048 84,555,446 46.0 69.9 1241 67,810,819 45.1 77.5 80.2
In MR
(*)
516 99,431,845 54.0 95.2 319 82,660,109 54.9 95.9 83.1
Total 5564 183, 987, 291 100.0 81.2 1560 150, 470, 928 100.0 87.5 81.8
Source: Census 2000 and 2007 Count - IBGE / Logit
heavily urbanized municipalities of different sizes and density levels .
In the municipalities with over 20,000 inhabitants, the problems of transport and
be
mitigated in order to ensure better quality of life for the population.
The City Statute (Federal Law 10.257 of 10 July 2001), regulates Articles 182 and
183 of the Federal Constitution. According to Ceneviva (2007) the Statute fails to
needs’ of the population in this respect. Nevertheless, it asserts that (i) urban transport
is essential for the proper functioning of cities and is a major engine of development
and (ii) access to transport is one of the rights to be enjoyed by present and future
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generations, together with the right to sustainable cities, housing, sanitation, urban
infrastructure, public services, employment and leisure. The same author argues that
people’s right to transportation must also take into account the need for long-term
sustainability of the city and the environment to ensure that the present generation
does not leave a negative legacy for the future.
Regulatory Overview1.8
regulate and harmonize transport sector operations in Brazil.
The National Land Transport Agency (ANTT) regulates all types of surface transport
of the country.
Water transport is the responsibility of the National Agency for Water Transport
(ANTAQ) charged with regulating the use and development of ports and inland
waterways.
The National Civil Aviation Agency (ANAC) is responsible for regulating safety and
security matters related to civil aircraft, personnel licensing and airports. The Brazilian
Company for Airport Infrastructure (INFRAERO) is responsible for day-to-day airport-
related operations.
In addition to regulation at the regional level the situation is further complicated
applying local rules and regulations to freight and passenger transport.
or actions aimed at reducing CO 2
will be required to coordinate actions, raise the awareness of the need for emission
which will regulatory environment.
Initial Prospective Analysis 1.9
Road transport at both the regional and urban level is the largest consumer of fossil
fuels (50.5%). The predicted surge in vehicle ownership in emerging economies,
including Brazil, makes it necessary to adopt measures to rationalize private car use
and introduce modal transfer from roads to rail and waterways for regional freight
transport.
Measures to discourage private car usage, such as reducing the number of parking
spaces in congested areas and/or increasing parking costs, may be necessary. Such
measures could be accompanied by strategies aimed at upgrading public transport as a
real alternative modal shift.
Some authors consider that passenger and freight movement in more heavily-
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density. A study by Stone et al. (2009) on a group of American cities, estimates that if
population density were to double in a medium-sized city, a reduction of about 30%
of CO 2 per household could be achieved. This urban consolidation approach, known
as “Transport Oriented Development” (TOD) maintains that in areas with denser and
non-motorized transport, such as bicycles, to cover shorter distances is a practical
public transport system (Cervero & Day, 2009; Cervero, 1998)
With the aim of encouraging municipal authorities to design urban transport plans
in accordance with City Statute guidelines, the Council of Cities issued Resolution
ConCidades No. 34 (1 July 2005), specifying that each municipal integrated urban
transport plan, known as the “Transport and Mobility Master Plan”, should (Ceneviva,
2007):
•
of the city, prioritizing public transport over individual transport, and
encouraging non-motorized transport and walking;
ensure that urban mobility management is incorporated into the Municipal •
Master Plan;
•
city, improving environmental quality and mitigating the impacts of spatial
Given that the main goal of this study is to analyze the scope for reductions in
GHG emissions, each transport sector will be addressed separately, according to the
Figure
17),
while the other 42% occurred in the air, rural areas, and near roads, waterways,
railways and pipelines passing through large urban centers.
Figure 17: Emissions by the Transport System, by segment (2007)
Source: Low Carbon Stydy for Brazil – Logit (2009)
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METHODOLOGICAL APPROACH2
the success of each depends on the unique infrastructure characteristics. Trips are
The operating characteristics of each mode of transport, the variety of freight
sector. This situation is further complicated by the volumes and types of freight
transported (perishable goods, high-value merchandise, products requiring special
comfort, safety, and cost.
A study aimed at estimating future carbon emission levels in the transport sector,
and identifying ways of mitigating such emissions, necessarily involves a varied and
of each
trip. Furthermore, it is important to note that the transport sector is directly linked
estimates of the impacts on the environment, especially of carbon emissions.
The aim of this chapter is to describe the methodological approach adopted for
estimating emissions in the reference and low-carbon scenarios for 2030. The energy
sector reference scenario was developed by the Energy Planning Company (EPE) and
forms part of the National Energy Plan (PNE 2030). The methodology we used for
transport sector estimates was adjusted to ensure consistency with the PNE scenario.
A series of meetings and contacts with other institutions and groups involved in
estimates in the transport sector.
Scenario Building - General Considerations2.1
The “scenario development” technique has been widely used over the years by
instrument employed in prospective analysis, are particularly useful for forecasting
processes involving a large number of variables and increasing outcome uncertainty.
The scenarios seek to incorporate qualitative elements into traditional trend and
model analyses and are particularly useful for decision-makers when considering
future developments and options.
Transport planning frequently employs forecasting models which, although
practice. Scenarios therefore continue to be used in transport planning in the hope of
longer term (Balassiano, 1998).
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The different components of scenarios, each with a specific but unknown
can increase the chance that long-term decisions result in successful outcomes.
In short, this technique seeks to address the possibility of different outcomes
within an uncertain future. Consistent assumptions at the outset tend to lead to better
structured scenarios, which in turn should enhance planners´ capacities to address
future uncertainties.
should occur in the transport sector, it is essential that consistent policies are adopted,
changes in the transport sector. The latter, in turn, needs to be in a position to respond
Future Carbon Dioxide Emissions Scenarios2.2
We studied two different scenarios related to future transport sector GHG
scenario involving few technical or operational innovations.
The second scenario studied was an alternative, low-carbon scenario, involving a set
of mitigation options considered and assessed in terms of:
Potential for deployment; •
•
Policies required to implement the options; •
Cost estimates for each option, and •
•
regional freight and passenger transport. All non-urban trips taken outside the urban
limits of Brazil´s 5,564 Brazilian municipalities were counted as “regional trips”.
The same concept was applied to the urban transport sector, where freight and
passenger trips were considered separately.
Emissions linked to the transport sector both in the reference and low-carbon
scenarios were analyzed through 2030.
The study used a bottom-up approach to estimate passenger and load movements,
fuel consumption, number, length, and type of trip, and energy content of the fuels
consumed, in order to determine the amount of CO2 emissions. Load values were
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calculated in terms of number of passengers times kilometers and tons of freight time
kilometer in both the reference and low-carbon scenarios. The loads were estimated
for each transport mode (road, waterways, rail and air) for each subsector - urban
transport (passengers and freight) and inter-urban/regional transport (passengers
and freight).
The structuring of the reference and low emission scenarios for regional and urban
Regional Transport Assumptions2.3
To model regional freight transport, this study uses the basic matrices employed
in the PNLT 2007 studies. These matrices were revised and updated (incorporating
new modeling data as appropriate) in line with the reference scenario adopted by
consensus with the other Project teams.
For modeling and projecting regional passenger transport a methodology was
developed based on several assumptions regarding the different transport modes
(buses, cars and air):
In the case of private car travel, data on passenger movements included in •
the PNLT 2007 matrices were used, together with recent statistics based on
volumetric counts undertaken at toll booths;
For projections of bus passenger movements, we secured data from the •
ANTT and ANTP on passenger numbers, vehicle movements (origin and
destination);
Information on passenger travel by air (origin, destination and trip numbers) •
was supplied by INFRAERO and ANAC;
The socioeconomic and demographic assumptions used to construct the •
trend or reference scenario drew upon regional demographic and economic
data contained in the PNLT 2007 and PNE 2030. This data was also used to
model regional freight transport and urban freight/passenger transport.
To ensure that the modeling assumptions for freight and passenger projections
were consistent with those of the other sectors studied in the Project, the methodology
for the transport sector estimates also adopted the macroeconomic scenario contained
in the National Energy Plan (PNE 2030) prepared by the Energy Planning Company
(EPE).
The PNE 2030 projections are based on the values of infrastructure investment
Based on suggestions from a series of technical meetings with transport industry
reference scenario includes investments planned under the government´s Growth
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Acceleration Plan (PAC). In the light of the current global economic crisis, and assuming
that no other unforeseen political/institutional or other major event occurs, the study
includes the adoption of the PAC projects in the 2030 reference scenario. The PNLT-
2007 includes a series of environmental targets, together with
lower investment (50.5%) projected for highways when compared to the PAC (72.7%)
(see Figure 16). The low-emissions scenario includes some of the projects detailed in
the PNLT, as including all of them would reach a total estimated cost of around US$51
billion.
to political/institutional pressure, the portfolio contained many projects with limited
economic viability. This study therefore assumes that by 2030, only a portion of the
projects outlined in the PNLT will in fact be implemented. In short, only projects with
the total value of PNLT investments, as seen in Table 5 below.
Table 5: Investment in Regional Transport Infrastructure
Mode Reference Scenario Low Carbon
US$ billion % Total % PAC US$ billion % Total % PNLT
Roads 15.11 76.97 125.6 13.27 45.4 51.6
Rail +
Waterway +
Pipeline
4.52 23.03 100.0 15.98 54.6 63.3
Total 19.63 100.00 118.6 29.25 100.0 57.4
Source: CAP / PNLT (2007) / Logit
Based on this assumption, and given the values indicated in Table 5, the low-carbon
scenario for regional transport is based upon an analysis of the additional mitigation
options contained (or not) in the PNLT.
Urban Transport Assumptions2.4
In addition to the overlapping management and regulatory systems at regional level,
are regulated by a variety of municipal government bodies. The bodies frequently
act independently of one another and often work with divergent and sometimes
contradictory mandates.
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In the metropolitan or similar large urban areas, many daily trips are undertaken
across municipal boundaries. It is obvious that the transport requirements of
thousands, if not millions, of citizens would be better met if a single centralized
and a single transport budget independent of the present multiplicity of political and
institutional interests.
In this scenario an accurate assessment of the need for transport infrastructure-
upgrading projects in Brazil’s cities is urgently called for. This should take the form
of an up-to-date road and mobility inventory prepared by the transport managers of
the 516 municipalities in the 36 most heavily-urbanized regions (IBGE, 2008). Given
report uses aggregate numbers for urban mobility to evaluate GHG emissions in our
metropolitan areas and cities.
Urban Center Categories (Clusters)2.4.1
on demographic and socio-economic indicators.
Indicators for the municipalities in the 36 most highly-urbanized areas were
aggregated. The clusters were formulated on the basis of social economic and
demographic indicators derived from a wide variety of secondary sources, as follows:
Number of municipalities (IBGE); •
Population and households by income in minimum wages (IBGE Censuses •
and Population Counts/ Logit);
GDP and GDP per capita data (IBGE / IPEA / FIPE / PNLT-2007 •
projections);
•
commercial vehicles (LCV), light passenger vehicles (LPV), heavy-duty trucks
(VPC), heavy-duty buses (VPO) and motorcycles (ANFAVEA/DENATRAN/
ABRACICLO / Logit);
Fuel sales at urban gas stations (in million TOE): Bio-ethanol, diesel and •
gasoline (ANP / PNE 2030 projections);
Total and % urban area (EMBRAPA). •
Table 6 below presents the main municipalities and the main most densely-
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Table 6: Major urban regions and municipalities by similarity cluster
Cluster Densely-Populated Urban Municipalities
and Metropolitan Regions
Selection of Municipalities
1 RM São Paulo and Rio de Janeiro MR -
2 MR Belo Horizonte, Federal District and sur-
rounding areas, Fortaleza MR, Curitiba MR,
MR Recife, Porto Alegre MR and MR Salvador
-
3 MR Belem, MR Santos, MR Goiania, Campinas
MR, MR Manaus MR and Vitoria MR
-
4 Aglomeração Urbana do Sul (RS), Urban
Aglomeração Urbana do Nordeste (RS), RIDE
– Petrolina/PE and Juazeiro/ BA, Aglomera-
çao Cuiabá/Várzea Grande, MR Aracaju, RIDE
Greater Teresina, MR Greater São Luis, MR
Florianópolis, MR Londrina, MR João Pessoa,
MR Maringá, MR Maceió, MR North-Northe-
ast Santa Catarina, MR Natal, MR Vale do Ita-
jai, and MR Vale do Aço
Campo Grande-MS, Uberlandia, Minas Ge-
rais, São Jose dos Campos-SP, Feira de Santa-
na-BA, Sorocaba-SP, Ribeirão Preto, and Juiz
de Fora-MG
5
-
ral Norte –RS.
Campos dos Goytacazes, São Jose do Rio
Preto, Porto Velho-RO, Campina Grande-PB,
Piracicaba-SP, Bauru, SP, Montes Claros-MG,
Franca, Brazil, Vitoria da Conquista, Bahia,
Petrópolis-RJ, Ponta Grossa, Paraná, Rio
Branco-AC, Caruaru-PE, Uberaba-MG, Casca-
vel-PR, Santarém-PA, Limeira-SP, Taubaté-SP,
Buena Vista-RR, Santa Maria-RS and Volta
Redonda-RJ
6 - Maraba-PA, Araraquara-SP, Itapemirim-ES,
Rio Claro-SP, Passo Fundo-RS, Dourados, MS,
Araçatuba-SP, Palmas-TO, Nova Friburgo-RJ,
Sobral-CE, Barra Mansa-RJ, Rondonopolis-
MT, Macaé, Chapecó-SC, Guarapuava-PR,
Cabo Frio-RJ, Lages-SC, Castanhal-PA, Tere-
sópolis-RJ, Rio Verde-GO and Angra dos Reis-
RJ
7 - Votorantim-SP, Ourinhos-SP, Araruama-
RJ,Patos-PB, Açailândia-MA, PR Arapongas-
Bacabal-MA, Breves-PA, Ubá-MG, Eunápo-
lis- BA, Assis-SP,- Erechim-RS, Itaperuna-RJ
Ituiutaba-MG and Iguatu-EC
8 - Vacaria-RS, Escada-PE, Itaberaba-BA, Len-
-
nedo-AL, Camocim-CE, Carazinho-RS, Santo
Amaro-BA, São Gabriel RS, Araranguá –SC,
Rio do Sul-SC, Penápolis-SP, Palmares-PE,
Bezerros-PE, Euclides da Cunha-BA, Floria-
no-PI, Cajazeiras-PB, Ponte Nova-MG, Limo-
Sources: IBGE / Logit
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Table 7 below presents the average percentages and indicators of the socio-
during the process to determine the eight urban similarity clusters:
Table 7: Selected socioeconomic and demographic indicators for urban similarity cluster
Variables Percentages of total Brazil and Indicators by similarity cluster Brazil
(Total /
Abs)
1 2 3 4 5 6 7 8
Type of urban area MR MR MR MR
and
munici-
pality
MR
and
munic-
ipality
Munici-
palities
Munici-
palities
Munici-
palities
-
Total Municipalities 1.01% 2.98% 1.10% 3.27% 1.71% 1.44% 3.00% 85.50% 5564
Number of Inhabitants
(Band)
Over 6
million
Over
3 to 6
million
1.5 to 3
million
500
000
to 1.5
million
200 to
500
000
100 to
200
000
60 to
100 000
Up to 60
000
-
Population (2007) in
000s
16.61% 14.60% 6.45% 9.66% 6.57% 5.76% 6.78% 33.57% 183 988
GDP (2006) in US$
million
26.79% 17.64% 8.33% 9.46% 7.14% 5.94% 5.67% 19.03% 2458190
GDP per capita in US$
000s
21.55 16.15 17.26 13.09 14.53 13.76 11.16 7.57 13.36
Current
Fleet
(2007)
in
thousand
units
VLC 17.36% 15.62% 8.69% 11.75% 8.15% 6.88% 6.90% 24.67% 3349
VLP 23.70% 18.82% 8.54% 12.20% 7.90% 6.13% 5.55% 17.14% 18 377
VPC 12.15% 13.43% 7.34% 10.80% 8.15% 7.84% 8.25% 32.05% 980
POV 20.36% 17.04% 9.03% 10.24% 6.28% 6.03% 6.09% 24.93% 240
Motorcycle 8.99% 9.56% 7.31% 11.61% 9.72% 9.08% 10.47% 33.26% 9227
Total 18.45% 15.65% 8.17% 11.93% 8.45% 7.11% 7.19% 23.06% 32 173
Fuel Con-
sumption
2007 (in
million
TOE)
Ethanol 25.95% 9.79% 9.59% 10.76% 9.97% 7.02% 6.11% 20.82% 3166
Diesel 6.24% 10.83% 5.02% 10.14% 8.69% 7.77% 8.95% 42.35% 19 061
Gasoline 18.68% 18.62% 8.30% 12.43% 8.50% 6.36% 6.41% 20.71% 17 765
Total 13.32% 14.21% 6.84% 11.21% 8.71% 7.08% 7.60% 31.03% 39 992
Total Area 0.15% 1.26% 1.42% 1.44% 1.62% 2.71% 8.16% 83.24% 8,530,611
Urban Area 14.19% 16.02% 8.72% 12.39% 6.67% 5.77% 6.21% 30.05% 21 295
23.79% 3.18% 1.53% 2.15% 1.03% 0.53% 0.19% 0.09% 0.25%
Sources: IBGE / IPEA / ANFAVEA / DENATRAN / ABRACICLO / ANP / EMBRAPA / Logit
While the large metropolitan areas (Classes 1, 2 and 3) contain only 5% of Brazil’s
municipalities and occupy less than 3% of the country’s territory, their demographic
(42%), fuel consumption (34%) and proportion of occupied urban area (39%). These
substantial numbers indicate that the vast majority of urban trips are concentrated in
these areas.
Of the variables selected for determining cluster similarity, GDP was the main
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indicator for assessing trip-generation in view of the wealth produced in these
presented the lowest standard deviation of all the component units of each cluster.
The number of households by income band underpins the two other main indicators
(population and GDP) for calculating similarity clusters. This key socio-economic and
demographic indicator shows the amount and distribution of wealth in the various
areas and is an appropriate parameter for estimating mobility. The trip-generation
thus used as the main parameter for urban-metropolitan transport modeling in this
study. Table 8
similarity clusters:
Table 8: Households by income (minimum wages) by urban cluster – 2007
Clusters Household Incomes in Minimum Wages (thousand units)
Up to 2 MWs 2 to 5 MWs 5 to 10 MWs 10 to 20 MWs Over 20 MWs Total
Abs % Abs % Abs % Abs % Abs %
1 2,518 24.8 3,972 39.2 2,093 20.6 1,063 10.5 494 4.9 10, 140
2 2,699 32.6 3,106 37.5 1,439 17.4 682 8.2 359 4.3 8,285
3 886 25.9 1,371 40.1 705 20.6 331 9.7 124 3.6 3,418
4 1,445 28.8 1,921 38.2 1,010 20.1 455 9.1 191 3.8 5,023
5 1,020 28.5 1,439 40.2 710 19.8 305 8.5 103 2.9 3,577
6 989 31.3 1,284 40.7 575 18.2 230 7.3 76 2.4 3,155
7 1,463 38.5 1,496 39.4 566 14.9 206 5.4 66 1.7 3,797
8 9,519 49.9 6,806 35.7 1,938 10.2 616 3.2 180 0.9 19, 060
Total 20, 540 36.4 21, 396 37.9 9,035 16.0 3,888 6.9 1,595 2.8 56, 454
Sources: Census Counts and Population - IBGE / Logit
Figure 18
Figure 18: Households by income (minimum wages) by urban cluster (2007)
Sources: Census Counts and Population - IBGE / Logit
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The middle range (households with 2-10 minimum wages) has roughly the same
comprises the 4,757 Brazilian municipalities with under 60,000 inhabitants, whose
share is in the region of 45%. The stark differences should be noted between the
families with incomes at either end of the spectrum: while the share of the top band
(households with incomes of over ten MWs) gradually decreases (see Table 7), the
share of people in the lowest income band (households with up to two minimum
wages) gradually increases.
This phenomenon can be observed in the metropolitan areas of São Paulo and Rio
de Janeiro, which form cluster 1 (over 6 million inhabitants). In these cities, on average
1.6 households receive incomes of up to two minimum wages compared to households
with an income of above ten times the minimum wage. By contrast, in the cluster 8
municipalities (up to 60,000 inhabitants), households with incomes of up to 2 MWs
outnumber those with incomes above 10 MWs by a factor of 12 to 1.
Assumptions for Modeling Urban Mobility2.4.2
Mobility and emissions estimates in urban areas were based on origin-destination
surveys and urban Master Plans for certain heavily-populated municipalities and dense
urban areas in similarity clusters 1-5:
Table 9: Urban Mobility Plans Available
Cluster Densely-Populated Urban Areas Municipalities
1 MR São Paulo and MR Rio de Janeiro -
2 MR Belo Horizonte, MR Curitiba, MR Recife,
MR Porto Alegre
-
3 MR Santos and MR Vitória -
4 Aglomeraçao Cuiabá/Várzea Grande, MR
Florianópolis, MR Londrina, MR Maringa
and MR Maceio
Campo Grande-MS, Vitoria da Conquista-BA,
Ribeirão Preto-SP and Juiz de Fora-MG
5 - Petrópolis-RJ, Piracicaba-SP, Campina Gran-
de-PB, Rio Branco-AC and Santa Maria-RS
Source: Logit (2009)
The nature and quality of information available on urban mobility plans listed in
Table 9
series of this information was outdated and discontinuous. Therefore, the OD Survey,
conducted under the supervision of the São Paulo Metro Company (2007), for the São
Paulo metropolitan region, and the Urban Transport Master Plan - PDTU (2005) for the
Rio de Janeiro region and the Belo Horizonte Mobility Plan (2009) for Belo Horizonte,
the similarity clusters. This information (up-to-date, using similar methodological
approaches and producing a trip-generation factor by household according to income
in MWs) served as an ideal starting-point for calculations for each of the eight similarity
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Socioeconomic and demographic indicators used in the clustering • process:
(i) GDP, population and households, by income bands in minimum o
wages for calculating trip-generation intensity;
o dense’ urban area to adjust average trip
lengths; and
o
for adjusting the modal split.
Indicators of urban mobility from other plans used in the study for adjusting •
upgraded trip-generation and modal split factors; and
Information obtained from ANTP (2005-2007 on urban mobility and the •
(by categories), for overall modal split adjustments.
income bands for 2007.
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Table 10: Trip-Generating Factors by Similarity Clusters
Mode Household
Incomes
Cluster
1
Cluster
2
Cluster
3
Cluster
4
Cluster
5
Cluster
6
Cluster
7
Cluster
8
Brazil
VPO + VLC
(bus + light
commercial)
Up to 2 MWs 1.680 1.626 1.402 1.086 0.912 0.937 0.899 0.959 1.155
2 to 5 MWs 2.081 2.012 1.734 1.339 1.122 1.155 1.109 1.185 1.509
5 to 10 MWs 2.025 1.957 1.685 1.299 1.088 1.121 1.076 1.152 1.529
10 to 20 MWs 1.144 1.103 0.949 0.729 0.608 0.629 0.604 0.648 0.892
Over 20 MWs 0.566 0.547 0.470 0.362 0.302 0.312 0.300 0.321 0.462
TOTAL 1.798 1.738 1.516 1.165 0.988 1.022 0.982 1.043 1.312
Metro +
Train
Up to 2 MWs 0.364 0.042 0.000 0.008 0.000 0.000 0.000 0.000 0.051
2 to 5 MWs 0.587 0.067 0.000 0.013 0.000 0.000 0.000 0.000 0.120
5 to 10 MWs 0.594 0.068 0.000 0.013 0.000 0.000 0.000 0.000 0.150
10 to 20 MWs 0.513 0.059 0.000 0.012 0.000 0.000 0.000 0.000 0.152
Over 20 MWs 0.398 0.046 0.000 0.009 0.000 0.000 0.000 0.000 0.134
TOTAL 0.516 0.057 0.000 0.012 0.000 0.000 0.000 0.000 0.102
Total Trips
on Public
Transport
Up to 2 MWs 2.044 1.668 1.402 1.094 0.912 0.937 0.899 0.959 1.206
2 to 5 MWs 2.668 2.080 1.734 1.352 1.122 1.155 1.109 1.185 1.629
5 to 10 MWs 2.620 2.025 1.685 1.312 1.088 1.121 1.076 1.152 1.679
10 to 20 MWs 1.657 1.162 0.949 0.740 0.608 0.629 0.604 0.648 1.044
Over 20 MWs 0.964 0.592 0.470 0.371 0.302 0.312 0.300 0.321 0.596
TOTAL 2.314 1.796 1.516 1.177 0.988 1.022 0.982 1.043 1.414
Individual
Trips - VLP +
Moto + (cars
+ motorcy-
cles)
Up to 2 MWs 0.693 0.879 0.882 0.958 0.941 1.001 1.035 1.096 0.982
2 to 5 MWs 0.703 0.892 0.898 0.976 0.961 1.024 1.060 1.123 0.963
5 to 10 MWs 1.881 2.347 2.263 2.431 2.324 2.418 2.420 2.553 2.293
10 to 20 MWs 3.550 4.391 4.145 4.430 4.170 4.284 4.203 4.423 4.116
Over 20 MWs 5.114 6.286 5.838 6.211 5.775 5.867 5.661 5.945 5.762
TOTAL 1.457 1.662 1.670 1.776 1.638 1.626 1.504 1.407 1.536
Total Up to 2 MWs 2.737 2.547 2.284 2.052 1.853 1.938 1.934 2.055 2.189
2 to 5 MWs 3.371 2.972 2.632 2.328 2.083 2.179 2.169 2.309 2.592
5 to 10 MWs 4.501 4.372 3.948 3.744 3.412 3.540 3.496 3.705 3.972
10 to 20 MWs 5.206 5.553 5.094 5.170 4.779 4.912 4.807 5.072 5.160
Over 20 MWs 6.078 6.879 6.309 6.582 6.077 6.179 5.960 6.266 6.358
TOTAL 3.771 3.458 3.186 2.953 2.626 2.648 2.485 2.451 2.949
Source: Logit (2009)
passenger transport indicate that trip-generation factors are higher in the
metropolitan areas and larger cities than in smaller towns. Moreover, according to
ANTP estimates, trip-generation factors for public transport trips in the large cities are
higher than for individual trips.
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Figure 19: Public Transport and Individual Trip-Generation Factors, by Urban Cluster
Similarity
Source: Logit (2009)
factors calculated by household income bands are higher for higher-income
households than for lower-income groups, as indicated in Figure 20.
Figure 20: Household Trip-Generation Factors according to Income Levels, by Urban
Cluster Similarity
Source: Logit (2009)
Figure 20 also illustrates that the trip-generation factors for households receiving
over ten minimum wages are similar for all similarity clusters, while for households
with incomes of under 10 MWs, the trip-generation factors are higher in the larger
cities than in smaller and medium-sized ones.
modes (bus, light commercial vehicles, trains, metro, cars, motorcycles, bicycles and
on foot) for the eight urban similarity clusters, formed the basis for our calculations of
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passenger and freight movement in urban-metropolitan areas throughout Brazil, using
scenarios.
produced in the alternative scenarios.
Investment Assumptions for the Reference Scenario2.4.3
In the calculations of probable investments in urban transport infrastructure in the
reference scenario, the fact that Brazil will host the FIFA World Cup in 2014 was taken
into account, as this will call for upgrading the public transport network. Considering
that the majority of the host cities for the World Cup are situated in metropolitan areas,
it can be assumed that investments will be forthcoming to improve some of the metro
systems by 2014 in order to meet the commitments established at the time Brazil was
media and on the internet.
Although the above aspirations (and others) were taken into account when
building the reference scenario, it was concluded that Bus Rapid Transit (BRT)
systems were the most feasible option, incurring lower infrastructure investments
transport rather than by car. On this basis, all the investment types and values were
of urban similarity. A list of the investment probabilities in public urban transport
infrastructure, for the reference and low-carbon scenarios, can be seen in the table
below.
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Table 11: Investments in Public and Mass Transport Systems
Category
(no.)*
Densely populated urban municipalities and metropoli-
tan regions
System
type
No. km to be
constructed
Reference
scenario
Low- car-
bon sce-
nario
MR with
investments (1)
São Paulo and Rio de Janeiro
BRT 180 1.263
Metro 30 405
RM with
investments (2)
Belo Horizonte, Federal District and Environs (RIDE),
Fortaleza, Curitiba, Recife, Porto Alegre, and Salvador
BRT 289 670
Metro 25 280
MR with probable
investments (3)
Manaus, and Greater Vitória
BRT 60 300
Metro 0 100
MR/municipali-
ties with probable
investments (4)
Cuiabá-Várzea Grande, Aracaju, Grande Teresina
João Pessoa, Maringá, Maceió, Natal, São José dos
Campos, Ribeirão Preto, and Juiz de Fora
BRT 80 240
Metro 0 0
Municipalities
with probable
investments (5)
São José do Rio Preto, Campina Grande, Piracicaba,
-
çu, Franca, Rio Branco, Uberaba, Cascavel, and Volta
Redonda
BRT 40 120
Metro 0 0
* MR = metropolitan region; RM = regional municipality.
Source: Logit (2009)
While the majority of Brazil’s municipalities need some kind of interventions to
improve the operations and services of their public transport systems, only the larger
municipalities have been addressed in this prospective analysis for deploying high-
capacity passenger transport systems. Building new bus systems obviously involves
systems. In the case of the metropolitan regions some major transport corridors are
Aspects of Transport Modeling2.5
The study based its evaluation of the potential for reducing vehicle carbon
assessments and projections of both urban and regional passenger and freight
movements were considered.
could be measured in terms of carbon emissions. In this way it was possible to assess
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the emission impacts of different types of vehicles which might, or might not, be
capable of using alternative low-emission engine technology. This approach enabled
modeling and planning concepts, we developed a set of steps to obtain a picture of both
urban-metropolitan and regional freight and passenger movements.
Transport Planning and Modeling2.5.1
problems and solutions in line with sustainable development goals, forecast and
control possible future scenarios, and present the results of planning studies to
relevant decision-makers. In this respect, any decisions on transport planning need
to be based on wide-ranging analytical models capable of evaluating various sets of
alternatives through multiple interactions, as illustrated in Figure 21.
Figure 21: Analytical model for transport planning
Source: Logit (2009)
the transport planning process, analytical models serve as a feedback system to ensure
constant re-evaluation of the established goals and objectives.
Using the traditional “Four-Stages” transport model in the transport planning
process allows physical, economic and social changes to be incorporated at the regional
through multiple interactions and calibrations are ensured with the use of transport
planning models such as TransCAD, EMME and MANTRA.
Figure 22 illustrates the basic inputs and procedures using the “Four-Stages”
model for obtaining a volume indicator, which in transport simulation processes is
known as “loading”. This is the “standard unit of measurement” applied to freight and
passenger movements, convertible into “carbon emission units”. The sequence of the
various procedures is detailed below.
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Figure 22: Sequencing of the “Four-Stage” Transport Model
Source: Logit (2009)
The “Four-Stages” Model2.5.2
Over the past 50 years a methodology has been developed and consolidated for
modeling transport supply and demand. Conceptual improvements were introduced
at various stages of the methodological process. However, the basic structure adopted
for addressing the problem has been maintained, while improvements arising from
transport research have been gradually introduced and used in practical applications.
As illustrated in Figure 22, the traditional modeling process is usually handled in
four distinct stages:
Trip generation or demand; •
Trip distribution; •
Modal choice •;
Route assignment. •
socio-economic and demographic information or economic activities performed in
the study area. In addition data on use, occupation or the productive capacity of land
periods, are the result.
interaction between supply, represented by transport mode, and demand, summarized
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in the trip matrices converted into passenger movements or numbers of vehicles
transporting people and/or freight.
The results obtained were fed into a process for evaluating the alternatives. This
objective of each stage was to simulate demand behaviour by using a set of models.
The link between the various stages (involving the possible removal of some, or their
substitution by alternative procedures) aimed to produce the same results, depending
inter alia on the goals of each study, the methodology adopted, and the information
available. In this study, some procedures are adapted in view of the global nature
technologies for reducing carbon emissions.
Trip generation and distribution:
of its potential as a producer or attractor for trips. Once the global demand levels for
distribution can be calculated. This produces an estimate of the degree of interchange
is represented by a set of distribution-demand or trip matrices. The latter are square
j (destination zone, attraction or consumption j) contains an estimate of transport
trips, vehicles or tonnage over a given period (hour, day, year etc.).
Mode choice:
transport mode the probable portion of demand that it will absorb. At this stage a
alternative modes.
Once the choice of modes simulation is done, the transport demand estimate is
concluded. The resulting information can be represented in a set of demand or trip
Route assignment: These matrices must then be loaded onto the transport supply
on each stretch of the transport system, as well as performance levels based on the
estimated loading.
Loading, the result of simulations for urban and regional freight and passenger
transport, can be used for evaluating the socio-economic importance of projects and
for assessing the operational quality of the modes via a feedback process. In this study,
it will serve as a basis for assessing the impacts of vehicle carbon emissions.
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Macroeconomic Scenarios2.5.3
The stages employed in a model targeted at simulating transport demand behavior
require an input of socio-economic and demographic data and the deployment of
a procedure for determining the parameters of this set of information within the
proposed time horizon. This procedure consists of elaborating reference scenarios to
The projection of future demand is framed on the basis of a reference scenario
comprising a set of assumptions regarding the behavior of macroeconomic aggregates,
technological change, consumer preferences, demographic projections, changes in
the international scenario and trend data on regional and sectoral investments. These
assumptions form the basis for projecting economic variables that impact demand for
Based on a reference scenario, the trajectory of economic variables over a pre-
of economic growth on the levels of sectoral activity in states and key micro-
regions and on the spatial aggregations of results related to areas of interest to
the municipalities. The demand scenarios are also constructed by forecasting the
possibilities for
projections of product supply and demand.
Emissions Modeling in the Transport Sector2.5.4
After determining trip allocations to the transport infrastructure and to vehicle
types (network loading), it is possible to calculate the associated GHG emissions. To do
this, this study drew on the concepts contained in the COPERT model, used by member
countries of the European Union. This highly-detailed model allows emission estimates
the accuracy of the estimates.
Copert 4 is a software designed to calculate transport sector emissions. Developed
initially by the Thessaloniki Aristotle University in Greece for use in European countries,
enables it to be applied in large areas (countries, states and cities) as well as in smaller
areas (a minimum of one km2) without loss of reliability.
This
and “hot” emissions (calculated when the engine reaches its stability level). It also
accounts for vehicle deterioration resulting from age or high mileage.
Emissions calculated by Copert 4 include the main transport-generated pollutants:
2, CH4, N2O),
(NH3, SO2 ), particulate matter, carcinogens, polycyclic aromatic hydrocarbons (PAHs),
furans). The model also calculates fuel consumption based on operating conditions.
The entry data are presented in Table 12.
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Table 12: Entry Data: COPERT
Variable Description
Fleet categorized by class of vehicle-engine tech-
nology for each year of study (urban, regional and
road)
Total mileage by class of vehicle-engine technol-
ogy for each year of study
Average trip mileage of trips per year and class of
vehicle-engine technology
Average speeds by class of vehicle-engine tech-
nology, by year and category (urban, regional and
road)
Size of fuel tank, by class of vehicle-engine technol-
ogy
Canister size of each class of vehicle-engine tech-
nology
Percentage of fuel injection Percentage control of fuel evaporation of fuel per
engine type and category (urban, regional and
road)
month and year
Atmospheric pressure recorded by month and
year and the Beta distribution parameter
Chemical composition of each fuel type Record of improvements in emissions of each
type of pollutant per year
Annual fuel consumption -
nology
Source: COPERT 4 Manuals / Logit (2009)
Emission parameters established for the São Paulo Metropolitan Region by CETESB,
emissions, were used to put the COPERT model to practical use. The emission curves
based on vehicle speeds according to the COPERT model were initially adapted to
with the other subjects addressed by the Brazil Low Carbon Study, mainly Ethanol &
Cogeneration.
CETESB is a technical body mandated by the Brazilian Institute of Environment
and Renewable Natural Resources (IBAMA) as the agency responsible for
implementing PROCONVE (Program for Controlling Air Pollution Produced by Motor
Vehicles). CETESB has adapted international methodologies to Brazilian requirements
and developed the technical means to combat motor vehicle-generated pollution.
These served as the basis for the establishment of the aforementioned program in 1986
by CONAMA (the National Environment Council). This program has led to a reduction
in pollutants from new vehicles by around 97%, by progressively restricting emissions
through the introduction of technologies such as electronic fuel injection, catalysers
and fuel improvements.
As already mentioned, eight urban similarity clusters were established, based on the
demographic indicators from the 5564 Brazilian municipalities. The similarity clusters
higher than the clusters of small and medium-size cities. In other words, the larger
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model, was applied in the present study to the eight urban clusters.
Models for Evaluating Economic Results 2.6
The evaluation of the economic results of mitigation options proposed in a study
an analysis parameter framed on indicators which merely assess the proportion of
emissions savings produced by investments in emissions-saving measures. Mitigation
measures, principally in the transport sector, can also trigger other social economic
of the economic outcomes of the various alternatives. In the economic evaluations
used as a comparative benchmark.
used in the economic evaluation models adopted for the transport sector. It also
provides details on how each of the indicators selected as analysis parameters for each
of the low-carbon scenario mitigation measures for the transport sector was obtained.
Parameters and General Criteria2.6.1
generated by institutional actions. In this study we will refer to these investments as
“investment required”.
The majority of measures involving investments in infrastructure will also require
during their useful lifetimes outlays on operation and maintenance (O&M costs).
to the infrastructure investments considered in the reference scenario. Some
investments will be avoided, while in other cases required investment will increase.
infrastructure investments within the timeframe of the study (up to 2030), these values
of 8% per annum.
The approach adopted for the individual economic evaluation of each of the
measures, would occur in the reference scenario.
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Net Investments Curve2.6.2
Not all the mitigation measures will require investments to or avoided
time, will constitute the “Net Investments Curve” as illustrated in Figure 23 below.
Figure 23: The “Net Investments” Curve
Figure 23
will amount to US$891 million, “O&M Costs” to US$264 million, and “Investment
Avoided” to US$623 million, resulting in a total “Net Investment” of US$531 million,
calculated according to the following formula:
where:
IL (tot) = total “Net Investment”;
IRPMT 8% per annum);
IE- PMT 8% per annum).
The emissions avoided in the reference scenario, compared with the total “Net
each measure - the “Financial Cost of Ton of CO2 avoided”, according to the following
formula:
CF Ton CO 2e2e Ev
where:
CF Ton CO 2e Ev = “Financial Cost of Ton of CO 2 equivalent avoided;
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= Sum of total “net investment” accumulated on a year-on-year basis up
to year “n”;
Ton CO 2e Ev = Sum of the value of year-on-year emission savings within the study
period, with respect to the reference scenario, in tons of CO 2 equivalent avoided.
Figure 23, it can be seen that if the accumulated
emissions avoided during the study period amount to 50 million tons of CO2e and the
indicator of “Financial Cost of Ton of CO 2 equivalent avoided” is US$150.44 per ton of
CO 2e the result would be the following:
The values of total “net investment” accumulated year-by-year by the end-year of
the project are, in increasing order (US$ million), 30, 87, 138, 84, 226, 263, 297, 327,
355, 379, 401, 421, 439, 455, 470, 483, 494, 505, 514, 523 and 531.
The sum of these values of accumulated “net investment” amounts to US$7,522
million. Divided by the hypothetical 50 million tons of CO2
US$150.44 per ton of CO2e.
Other Indicators Selected as Analysis Parameters2.6.3
avoided in this study of the transport sector, the economic analysis of all the mitigation
into the “Financial Cost per Ton of CO2e avoided”, under three headings: fuel economy,
sectors of the economy were considered in the economic assessments for the transport
sector by applying a production or opportunity costs approach, in line with the
parameters adopted in other areas of the study.
2.6.3.1 Net Investments Curve with “Fuel” effect
The vast majority of mitigation measures concern the increased operational
transport modes for low-emission modes. Both will involve fuel savings either by a
reduction in load factors
i.e. involving the same load factors, but with a new modal shift leading to lower fuel
emissions (which frequently involves improved fuel economies).
(e.g. “Urban Demand Management for Individual Transport”, “Urban Planning Focused
on Transport”, etc).
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public transport operators (conventional buses, BRT, metro, passenger trains and air
travel).
were the freight transporters (trucks, freight trains, waterways, coastal shipping and
pipelines).
of production adopted for evaluating the total fuels production and consumption.
Figure 24.
Figure 24: The “Net Investments with Fuel Effect” Curve
Figure 24
Figure 23. Thus in 2030, the cumulative “Net Investment” amounts to US$ 531 million,
from which was subtracted the US$164 million relating to fuel economies. The result,
US$367 million, comprises the “net investment with fuel effect curve”, calculated
according to the following formula:
where:
ILEfC (tot)
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IL (tot) = total “net investment”, and
EcoComb
The emissions avoided in the reference scenario, compared to total “net investment
with fuel effect”, at present and nominal values, constitutes the second indicator
calculated for each measure - the “Financial Cost of Ton of CO2e avoided with Fuel
CFEfC Ton CO 2e CO2e Ev
where:
CFEfC Ton CO 2e Ev = “Financial Cost of Ton of CO2
year-by-year basis up to year “n”;
Ton CO2e Ev = The sum of the value of emission reductions annually within the
2 equivalent avoided compared to the reference
scenario.
Figures 23 and 24, the indicator of
the “Financial Cost of a Ton of CO2
US$123.16 per ton of CO2e and therefore:
•
by-year through the end year of the project are, in incremental order (US$
million): 30, 86, 134, 177, 214, 246, 273, 296, 316, 332 , 345, 356, 364, 370,
374, 377, 377, 377, 375, 372 and 367.
•
to US$6,158 million. Divided by the hypothetical 50 million tons of CO2e
avoided, the result is US$123.16 per ton of CO2e.
fuel consumption with the introduction of these mitigation measures has a positive
impact on the entire sector. However, for the economy as a whole, it is necessary to
verify the forecast production and consumption of fuels, and especially to determine
the destination of fuel consumed at lower levels than originally anticipated.
The effects of the mitigation measures presented in this study were evaluated
options, using the production costs of fuels used in the Brazil Low Carbon Study as a
parameter, but without considering other possible macroeconomic outcomes. The
overall macroeconomic effect was evaluated on the basis of “Increased Ethanol
(calculated on the basis of bio-ethanol production costs) and avoided by lower gasoline
fuel consumption in the reference scenario were aligned with the data on ethanol and
gasoline production in the rest of the Brazil Low Carbon Project.
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2.6.3.2 Curve of Net Investment with “fuel” and “operation” effects
In general terms a transport system can be seen as a production process which
consumes resources in order to generate useful products for society. Products of the
transport system can generate both advantages and disadvantages. However, a key
Early transport studies undertook results evaluations purely in engineering terms,
concentrating on the safest and cheapest way of installing and running a transport
system. Later studies established monetary values for all the factors considered
relevant, in order to make it possible to calculate rates of return on capital costs or
present net values as a means of comparing alternative projects.
for infrastructure and vehicles. Thus the so-called “operational gains” derived from
the planned interventions an
with the new developments.
The methodology of economic evaluation follows the general concepts adopted
by the World Bank for economic feasibility studies of transport projects, where the
•
gains achieved by comparing operating costs with infrastructure and/or
vehicle maintenance costs with the alternatives considered (cost of rolling
•
gains achieved, by comparing the administrative costs needed for operation
of the infrastructure and/or vehicles with the alternatives considered
(personnel costs, equipment costs etc);
Accident Reduction: measuring the gains by comparing the number of •
costs with the alternatives
considered (replacement cost of rolling stock, cost of lost workdays by
drivers etc).
In the case of regional freight and passenger transport, the operational gains
correspond to the net variation of the revenues of each operator arising from the
deployment of the mitigation measure under consideration (reference scenario vs.
low-carbon scenario).
In line with the proposed methodology, the initial stage of the evaluation process
consisted of identifying the production costs of the transport services on a “present
costs” basis. The following stage consisted of incorporating the demand to be
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captured in each of the simulated alternatives for the time-horizons of the study. The
methodology adopted used the measurements generated by the transport planning
alternatives studied.
Figure 25: The “Net Investments with Fuel and Operation Effects Curve:”
a value of US$367 million accumulated by 2030 for the “net
was subtracted. The result, US$5 million, constitutes the curve of “net investment with
where:
ILEfCO (tot)
ILEfC (tot)
GOper = operation revenue gains.
The avoided emissions in the reference scenario, compared with the total “net
investment with fuel and operation effect” at face and present values, constitute
the third indicator calculated for each measure - the “Financial Cost of a Ton of CO2e
CFEfCO Ton CO 2e2e Ev
where:
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CFEfCO Ton CO 2e Ev = “Financial Cost of a Ton of CO 2e avoided with the Fuel and
= The sum of “net investment with fuel and operation effects,”
accumulated year-on-year up to year “n”;
Ton CO 2e Ev = the value of emission reductions for each year within the study period
compared to the reference scenario in tons of CO2e avoided.
Figures 23, 24 and 25, the indicator of
“Financial Cost of a Ton of CO2
US$62.50 per ton of CO2e. Therefore:
•
accumulated on a year-by-year basis up to the project horizon year, will be
(in US$ million) in ascending order: 30, 83, 126, 160, 187, 206, 220, 227, 230,
227, 221, 211, 198, 182, 163, 141, 117, 92, 64, 35 and 5;
The sum of these values of “net investment with fuel and operation •
hypothetical 50 million tons of avoided CO2e avoided, this results in US$62.50
per ton of CO2e.
2.6.3.3 Final Net Investment Curve
In the methodological approach of the economic evaluation model adopted, the
the alternatives.
•
for transport users and operators;
•
by comparing the costs of alternative systems, were then incorporated
gains have a positive impact on the decisions made by logistics operators.
Positive evaluations indicate that the mitigation options analyzed could be
successful;
To complete the economic assessment of mitigation options leading to •
Some of these effects will directly benefit passenger-transport users and were
transport and individual means. The interdependence of many of the variables in the
transport systems means that actions focused on a small part of the system which can
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users of public transport and those using individual modes. Thus, in addition to the
groups:
Lower costs of pollution (CO •2 is harmless to humans in the lower atmosphere,
from CO2);
Reduced cost of accidents. •
Diseconomies
through Improvement of Urban Public Transport”, coordinated by IPEA and ANTP
(August 1998).4
parameters were adapted according to the emission levels of each of the transport
modes.
The reductions in terms of vehicles times kilometers, multiplied by the unit costs
generated by reduced air pollution.
and without the deployment of the mitigation measures. The parameters of unit costs
of accidents for transport systems derived from studies conducted by the World Bank in
Brazil, particularly the CBTU programs for the decentralization of urban rail transport
in Rio de Janeiro, São Paulo, Belo Horizonte and Recife.
formed the
diagram below:
4 The values that appear in the ANTP study refer to the costs of local pollution and not to CO2 and GHGs
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Figure 26: The “Final Net Investments” Curve
was accumulated by 2030 in the “net investment with fuel and operation” curve. From
a negative result: US$(395) million. This indicates that in 2030 the direct and indirect
required for implementing the hypothetical measure. This amount, which will
formula:
where:
ILFinal (tot)
ILEfCO (tot)
BenSoc
The emissions avoided, compared to the reference scenario, and compared with
indicator calculated for each of the measures, the “Final Cost of tons of CO2e avoided”,
CFFinal Ton CO 22 and Ev
where:
CFFinal Ton CO 2 and Ev = “Final Cost of some of Avoided CO 2”;
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year “n”;
Ton CO2 and Ev = the value of emission reductions for each year within the study
period, compared to the reference scenario in tons of CO2 avoided.
Figures 23, 24, 25 and 26, the indicator of
the “Final Cost of a Ton of CO2e Avoided” will be negative: US$ (4.28) per ton of CO2e. In
other words, with the inclusion of all the direct and indirect economic and social
measure will be fully compensated for, producing a credit of US$ 4.28 for each ton
of CO2
aforementioned investments required:
The values of the total “Final Cost of tons of CO •2 Avoided” accumulated on a
year-by-year basis up to the horizon year of the project will be, in ascending
order (in US$ million) 30, 79, 116, 142, 157, 163, 161, 151 , 135, 112, 85, 52,
15, (26), (70), (118) (169) (222) (277) (335) and (395);
The sum of these total accumulated values of “net investment with fuel and •
US$ (214) million. Divided by the
hypothetical 50 million tons of CO2e avoided, this results in a “Final Cost of a
Ton of CO2 avoided”, if negative US$(4.28) per ton of CO2e. In other words, a
credit of US$4.28 for every ton of CO2e avoided.
Parameters and Criteria for Evaluating Fuel Economy2.6.4
the mitigation measures was based on the results of the transport and GHG emissions
modeling undertaken as part of this study. These results were evaluated incrementally
and cumulatively, employing the production costs of fuel as a parameter for assessing
on the economy, since it could force the government to adopt unforeseen fuel supply
Study, using them as a parameter for evaluating the resulting fuel economies. Table
13 below contains the parameters used in the evaluations of all the mitigation
measures.
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Table 13: Fuel Production costs
Fuel Type => Ethanol
(m 3)
Petrol
(m 3)
Diesel
(m 3)
Aviation Fuel
(m3)
Elec-(MW)
% Considered in economic evaluation 30% 30% 50% 85% 100%
Production costs in US$
(Project parameters)
2009 276.46 281.76 188.68 281.76 56.89
2010 276.46 281.76 188.68 281.76 56.89
2011 273.96 314.15 189.62 314.15 56.89
2012 269.77 321.13 193.84 321.13 56.89
2013 264.54 328.11 198.05 328.11 56.89
2014 258.75 335.09 202.26 335.09 56.89
2015 252.44 342.08 206.48 342.08 56.89
2016 249.52 349.06 210.69 349.06 56.65
2017 245.48 349.06 210.69 349.06 56.65
2018 241.24 349.06 210.69 349.06 56.65
2019 236.50 349.06 210.69 349.06 56.65
2020 231.42 314.15 189.62 314.15 56.40
2021 226.84 314.15 189.62 314.15 56.40
2022 221.87 314.15 189.62 314.15 56.40
2023 216.72 314.15 189.62 314.15 56.40
2024 211.47 314.15 189.62 314.15 56.40
2025 206.19 314.15 189.62 314.15 56.17
2026 203.22 314.15 189.62 314.15 56.17
2027 200.23 314.15 189.62 314.15 56.17
2028 197.22 314.15 189.62 314.15 56.17
2029 194.19 314.15 189.62 314.15 56.17
2030 191.18 314.15 189.62 314.15 55.94
Criteria and Sources for Urban Passenger Modeling 2.6.5
from all the mitigation measures for the urban areas, this study adopted as parameters
the values used in the feasibility study for the implementation of the BRT in Rio de
Janeiro´s “T5 Corridor” under the 2005 Urban Transport Master Plan (PDTU). This
study also drew from the same study of BRT-related mitigation criteria for calculating
the “investment required” costs, as well as the maintenance and operational costs of
the system.
deploying the T5 Corridor and streamlining public transport in the project’s area of
The approach adopted in the economic feasibility study of the T5 Corridor was
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the interventions. This was presented in a pro-forma chart on a year-on-year basis,
year time span.
production costs based on the methodology adapted by the Rio de Janeiro City Hall,
and developed using the approach proposed by GEIPOT, the former government body
responsible for study and research in transport planning.
The methodology used in the study of the T5 Corridor employed measures
associated with each of the alternatives studied.
The principal measures used were the total passenger times kilometers, passenger
times kilometer hours and vehicles times kilometers, relating to the basic and
alternative situations for baseline and horizon years. Other measures for quantifying
In the economic feasibility study data on transport movements during the morning
2.6.5.1 Evaluation of Operational Gains in the T5 Corridor
Reducing Operating Costs
The basic source for determining the economic costs of operating the transport
system in the city of Rio de Janeiro was the for December 2004. This made
it possible to analyze the individual components of the cost of transport services. It
was particularly useful for estimating the operating costs of the T5 Corridor, including
characteristics of the proposed technology.
To determine the economic costs of public and individual transport, the input costs
Table 14 illustrates the unit costs for the separate items dealt with in the
aforementioned study, and variable components of the operating
costs of the conventional and articulated bus systems:
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Table 14: Economic Operating Costs of the Public Transport System in Rio de Janeiro,
considered this study (US$ per km)
Cost Items Conventional Buses Articulated buses
Lubricants 0.0494 0.0494
Running-in 0.0511 0.0769
Parts & Accessories 0.0547 0.1099
Variable Cost Considered 0.1552 0.2362
Depreciation 0.1044 0.4998
Remuneration 0.0727 0.4600
Administrative costs 0.1025 0.3190
0.7934 0.4911
1.0730 1.7699
Economic Cost 1.2282 2.0061
Source: Studies for Implementation of T5 Corridor T5 / Logit
The total operating costs were determined by using the methodology proposed
components of the costs in situations with and without the implementation of the new
T5 Corridor, for each of the modeling horizons.
system with and without the deployment of the alternative considered i.e. conventional
vs. articulated bus services (Table 14). Based on this data, the model allowed
operating costs of the system for each modeling horizon and alternative considered.
Corridor studies were underway.
Multiplying the number of vehicles by kilometers by the unit cost of operation
and the number of days in the year produces the annual operating cost for each type
of vehicle for each time-horizon, and for situations with and without the project. The
annual gain can thus be determined as the result of reduced operating costs. The
RCO = (
where:
RCO = Reduced Operating Cost
project
FP - Supply Factor = Peak factor related to supply
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Cop = unit costs of bus system operation determined according to the methodology
described previously
Days / Year = Total number of days in year
Although the unit costs of the articulated bus used in the BRT system are higher
Table 14), their
passenger load capacity per unit is at least double- an important point to consider when
determining cost reductions.
Reduction of Cost Management Systems
in the cost of bus system management involved determining a percentage reduction in
operating costs.
Based on recent data on public passenger transport in several Brazilian cities,
management costs amount to around 3-5% of the costs of the entire bus operation.
management costs.
Reducing the Cost of Accidents
The data on unit costs of accidents in bus systems were obtained from studies
conducted by the World Bank in Brazil, particularly the programs for the CBTU
decentralization of urban rail transport in Rio de Janeiro, São Paulo, Belo Horizonte and
Recife.
times kilometers in the situations with and without the project, for each transport
mode and each modeling horizon.
The general mathematical formulation for each mode of transport is given by:
where:
RCAcid = Reduced Cost of Accidents
period, without project
FP - Supply Factor = Peak Demand Factor
studies
Days / Year = Total number of days in the year
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2.6.5.2 Investment, Operation and Maintenance Costs and Operating
Gains calculated on the basis of the “ T5 Corridor” study
The data from the Corridor T5 study provided a good basis for determining the
values of the investments required, operation and maintenance costs and operating
gains for the year of implementation and over the 25-year lifespan of the entire
system. These values are presented in the following table.
Table 15: Investment, Operation and Maintenance Costs and Operating Gains calculated
on the basis of the “T5 Corridor” study (US$ per km)
Year of Operation Investment Operation and Maintenance Costs Operating Gain
0 5,32,5361 0 0
1 1,266,511 53,403 513,519
2 0 54, 472 546, 608
3 55, 329 55,561 581, 032
4 0 56,672 613, 145
5 0 57,806 646, 272
6 0 58,962 680, 443
7 0 60,141 715, 685
8 97, 463 61,344 752, 029
9 0 62,571 773, 876
10 0 63,822 795, 563
11 0 65,099 817, 077
12 0 66,400 838, 408
13 1,112,300 67,729 859, 543
14 0 69, 083 881, 165
15 43, 802 70, 465 902, 687
16 0 71, 874 924, 105
17 0 73, 312 945, 414
18 48, 731 74, 778 966, 608
19 0 76, 273 985, 332
20 77, 158 77,799 1,003,841
21 0 79, 355 1,022,126
22 0 80, 942 1,040,180
23 12, 183 82, 561 1,057,995
24 0 84, 212 1,080,037
25 -398, 058 85, 896 1,102,078
The values indicated above for operating gains served as a parameter for calculating
.
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2.6.5.3 Evaluation of Investments, Operation and Maintenance Costs
and Operating Gains for BRT
deployment, the data presented in Table 15
(year of deployment + 25 year lifespan) for each year within the project study period,
with the
reference and low-carbon scenarios.
The following table presents a year-by-year forecast of the launching of new
scenarios:
Table 16: Km of BRT to be Implemented in the Reference and Low Carbon Scenarios
Year of Commencement of Operations Low-carbon Scenario Reference Scenario
2010 123 49
2011 123 49
2012 123 49
2013 120 46
2014 120 46
2015 105 33
2016 102 30
2017 120 30
2018 118 28
2019 115 26
2020 115 26
2021 115 26
2022 113 24
2023 113 24
2024 135 24
2025 135 24
2026 134 23
2027 134 23
2028 143 23
2029 143 23
2030 143 23
As can be seen in the above table, the forecast applies to the two scenarios for the 21-
considered up to year 2054.
amounts (real disbursement values), total operation and maintenance costs and the
schedule shown in Table 16:
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Table 17: Values of Investments and Costs of O & M Operations and Gains in the Reference
and Low-Carbon Scenarios
Year Reference Scenario Low-carbon Scenario
Investment Operation and
Maintenance
Costs
Operating
Gains
Investment Operation and
Maintenance
Costs
Operating
Gains
2009 259 0 0 679 0 0
2010 320 3 25 841 8 33
2011 320 5 52 841 17 71
2012 310 8 80 833 25 112
2013 307 11 108 829 34 157
2014 236 13 138 745 42 205
2015 206 15 163 710 50 254
2016 203 17 188 808 58 306
2017 194 19 214 828 67 367
2018 178 21 239 809 76 430
2019 175 23 263 807 85 496
2020 174 25 288 806 95 565
2021 168 26 312 799 104 637
2022 219 28 337 937 114 712
2023 219 30 362 1059 124 790
2024 221 32 387 1095 135 877
2025 211 34 413 1084 147 968
2026 210 36 438 1083 159 1062
2027 197 38 464 1122 171 1160
2028 194 40 490 1131 184 1264
2029 197 42 517 1161 198 1372
2030 71 44 544 365 211 1484
2031 39 45 559 176 215 1560
2032 39 46 574 177 220 1635
2033 37 47 589 168 224 1710
2034 16 48 603 115 228 1784
2035 15 44 563 116 220 1736
2036 15 41 522 143 211 1683
2037 16 37 479 143 201 1626
2038 12 34 437 128 192 1566
2039 17 31 395 134 183 1503
2040 18 29 366 146 175 1452
2041 18 26 340 139 167 1400
2042 19 24 313 141 158 1328
2043 -6 22 288 -22 148 1255
2044 -6 21 265 -22 138 1181
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2045 -7 19 242 -28 128 1105
2046 -6 17 218 -27 118 1025
2047 -6 15 195 -27 108 943
2048 -8 13 171 -43 98 858
2049 -8 11 147 -43 85 748
2050 -9 10 122 -54 72 635
2051 -9 8 99 -54 59 521
2052 -9 6 75 -57 45 403
2053 -9 4 50 -59 30 272
2054 -9 2 25 -59 15 138
Given that the last year considered within the study is 2030, and in order to balance
and for commencing investment
operations in accordance with the time-spreads indicated in the economic evaluations,
the values were annualized by a discount rate of 8% per annum for a period of 25 years
(useful lifetime adopted for the system).
and operating gains in the economic evaluation of the mitigation measure associated
with the BRT deployment throughout the country:
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Table 18: Values of Investments and Costs of O & M Operations and Gains in the Reference
and the Low Carbon Scenarios for BRT Implementation
Year Genesis of Values Considered in Economic Evaluation (in US$ million)
Required Investment and Investment Avoided Operation and Maintenance
Costs
Curve of
Net
Invest-
ment
(A-B +
E)
“Operating
Gains”
Low-carbon Scenario values Reference Scenario values
Investment Investment
Required
(A) =
Accum.
Value PMT
Investment Investment
Avoided
(B) =
Accum.
Value PMT
Low
C a r b o n
Scenario
V a l u e s
(c)
Reference
Scenario
Values
(D)
Final
Values
(E =
C-D)
Real Va-
lue
Annualized
Cost (PMT
- lifetime =
25 years)
R e a l
Value
Annualized
Cost (PMT
- lifetime =
25 years)
2009 816.6 76.5 76.5 258.9 24.3 24.3 0.0 0.0 0.0 52.2 0.0
2010 1010.8 94.7 171.2 320.5 30.0 54.3 8.2 2.6 5.6 122.5 33.3
2011 1010.8 94.7 265.9 320.5 30.0 84.3 16.5 5.2 11.3 192.9 70.6
2012 1001.0 93.8 359.7 310.2 29.1 113.4 25.1 7.9 17.1 263.4 111.9
2013 996.7 93.4 453.0 307.1 28.8 142.1 33.6 10.6 23.0 333.9 156.6
2014 896.1 83.9 537.0 235.9 22.1 164.2 42.2 13.2 29.0 401.8 205.3
2015 853.7 80.0 617.0 205.9 19.3 183.5 50.1 15.3 34.8 468.3 254.1
2016 971.3 91.0 707.9 202.8 19.0 202.5 57.9 17.2 40.7 546.1 306.1
2017 995.9 93.3 801.2 193.9 18.2 220.7 67.1 19.2 47.9 628.5 366.9
2018 973.1 91.2 892.4 177.7 16.7 237.3 76.3 21.0 55.3 710.3 430.3
2019 970.0 90.9 983.3 174.7 16.4 253.7 85.5 22.8 62.7 792.2 496.2
2020 969.5 90.8 1074.1 174.3 16.3 270.0 94.9 24.6 70.2 874.3 565.2
2021 960.1 89.9 1164.0 167.7 15.7 285.7 104.4 26.5 77.9 956.2 637.2
2022 1126.7 105.5 1269.6 218.9 20.5 306.2 114.1 28.3 85.8 1049.1 711.9
2023 1272.6 119.2 1388.8 218.7 20.5 326.7 124.0 30.2 93.8 1155.8 789.8
2024 1316.2 123.3 1512.1 220.7 20.7 347.4 135.5 32.1 103.4 1268.1 876.9
2025 1303.0 122.1 1634.2 211.3 19.8 367.2 147.2 34.0 113.2 1380.2 967.8
2026 1302.0 122.0 1756.1 209.5 19.6 386.8 159.1 35.9 123.2 1492.5 1062.1
2027 1349.2 126.4 1882.5 196.9 18.4 405.3 171.3 37.9 133.4 1610.6 1160.1
2028 1359.8w 127.4 2009.9 194.2 18.2 423.5 184.3 39.9 144.4 1730.8 1264.1
2029 1396.1 130.8 2140.7 197.2 18.5 441.9 197.5 41.9 155.6 1854.3 1371.9
2030 438.9 41.1 2181.8 71.3 6.7 448.6 211.0 44.0 167.0 1900.2 1483.5
Total 23290.1 - 23,878.8 4788.9 - 5689.7 2105.8 510.5 1595.3 19784.4 13321.8
In order to obtain the curve of “net investment values”, an initial calculation was
made of the values of the “investments required “ and “avoided investments” by
analyzing and aggregating the real values considered for the low carbon and reference
scenarios respectively. Subsequently, the value for operating and maintenance costs
was calculated and the reference scenario numbers were subtracted from those of the
low-carbon scenario. To conclude calculation of the “net investment values curve”, the
“avoided investments” value was subtracted from the “required investments” and the
calculated values were added to the operating and maintenance costs.
The “operating gains” shown at Table 18 served as a basis for calculating the
“operating gains” of all the urban mitigation measures.
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Some of the “social benefits” directly affect all passenger transport users.
monetary savings involved in shorter trip times of public and individual transport. The
interdependency of the many variables in the transport systems means that actions
related to a small part of this particular system leading to reduced trip times triggers a
chain reaction, which impacts users of public and private transport.
of the variation between total passengers per hour in the “with and without the project”
situations, based upon the time-value calculated in the Declared Preference Survey
conducted in Rio de Janeiro at the time of the T5 Corridor studies. The values obtained
for “Value of User Travel Time” were R$1.08 per passenger-hour for travel on public
transport, and R$12.07 per passenger-hour for individual transport users. The general
mathematical formula adopted for the calculation is as follows:
where:
RTV = Reduced Travel Time
the situation
without project
project
VT = Value of Time
FP - Dem = Peak Demand Factor
Days / Year = Total number of days in the year
The model adopted in the economic evaluation, in the T5 Corridor studies, assessed
and increases in total passengers-hours at each modeling horizon for all the transport
modes considered.
In addition to the direct effects on users, society as a whole will also indirectly
into account savings on healthcare spending arising from the alternatives analyzed,
separated into two groups as follows:
Reducing Pollution costs •
Reducing Costs of Accidents •
from “lower costs of pollution” were obtained from the “Study of Urban Diseconomies
Reduction through the Improvement of Public Transport”, coordinated by IPEA and
ANTP.
The reductions in terms of vehicles times kilometers, multiplied by the unit costs
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generated by reduced air pollution.
with and without the deployment of the projects. The parameters of transport accident
unit costs derived from studies conducted by the World Bank in Brazil, particularly the
CBTU programs for the decentralization of urban rail transport in Rio de Janeiro, São
Paulo, Belo Horizonte and Recife.
The T5 Corridor studies contained an evaluation of the direct and indirect social
together with the other transport modeling data, are presented in the following table
(in US$ per kilometer of operation):
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the study of the T5 Corridor Study (in US$ per km)
Year of
Operation
Investment Operation
and Mainte-
nance Costs
Operating Gains
0 5,325,361 0 0 0
1 1,266,511 53, 403 513,519 228, 311
2 0 54, 472 546, 608 230, 320
3 55, 329 55, 561 581, 032 232,392
4 0 56, 672 613 145 237, 784
5 0 57, 806 646, 272 239, 968
6 0 58, 962 680, 443 259, 862
7 0 60, 141 715, 685 265, 427
8 97, 463 61, 344 752, 029 286, 864
9 0 62, 571 773, 876 293, 275
10 0 63, 822 795, 563 299, 059
11 0 65, 099 817, 077 303, 794
12 0 66,400 838, 408 307, 425
13 1,112,300 67, 729 859, 543 311, 609
14 0 69, 083 881, 165 315, 329
15 43, 802 70, 465 902, 687 340, 829
16 0 71, 874 924, 105 344, 261
17 0 73, 312 945, 414 349, 163
18 48, 731 74, 778 966, 608 352, 555
19 0 76, 273 985, 332 366, 730
20 77, 158 77, 799 1,003,841 370, 072
21 0 79, 355 1,022,126 373, 638
22 0 80, 942 1,040,180 378, 340
23 12, 183 82, 561 1,057,995 383, 104
24 0 84, 212 1,080,037 385, 392
25 -398, 058 85, 896 1,102,078 387, 679
Table 19
(25 years of useful lifetime) on a year-on-year basis over the study period, assuming
the foreshadowed launching of the new BRT lines in the reference and low-carbon
scenarios (see section 2.6.5.3 for background on the year-on-year calculation of the
values involved in mitigation through BRT deployment).
Table
16. In Table 20
deployment are presented for the two scenarios, together with other transport modeling data.
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the Reference and Low-Carbon Scenarios
Year Reference Scenario Low-carbon Scenario
Investment
Costs
Operating
Gains
Social
Investment
Costs
Operating
Gains
Social
2009 259 0 0 0 679 0 0 0
2010 320 3 25 9 841 8 33 35
2011 320 5 52 19 841 17 71 70
2012 310 8 80 28 833 25 112 106
2013 307 11 108 38 829 34 157 142
2014 236 13 138 47 745 42 205 178
2015 206 15 163 55 710 50 254 212
2016 203 17 188 62 808 58 306 247
2017 194 19 214 71 828 67 367 290
2018 178 21 239 78 809 76 430 334
2019 175 23 263 86 807 85 496 377
2020 174 25 288 94 806 95 565 421
2021 168 26 312 101 799 104 637 465
2022 219 28 337 108 937 114 712 509
2023 219 30 362 116 1059 124 790 554
2024 221 32 387 124 1095 135 877 609
2025 211 34 413 132 1084 147 968 665
2026 210 36 431 140 1083 159 1062 721
2027 197 38 464 147 1122 171 1160 777
2028 194 40 490 156 1131 184 1264 839
2029 197 42 517 164 1161 198 1372 901
2030 71 44 544 172 365 211 1484 963
2031 39 45 559 176 176 215 1560 987
2032 39 46 574 180 177 220 1635 1010
2033 37 47 589 183 168 224 1710 1034
2034 16 48 603 187 115 228 1784 1058
2035 15 44 563 174 116 220 1736 1022
2036 15 41 522 161 143 211 1683 982
2037 16 37 479 148 143 201 1626 942
2038 12 34 437 135 128 192 1566 900
2039 17 31 395 122 134 183 1503 856
2040 18 29 366 113 146 175 1452 820
2041 18 26 340 105 139 167 1400 784
2042 19 24 313 96 141 158 1328 739
2043 -6 22 288 89 -22 148 1255 694
2044 -6 21 265 82 -22 138 1181 651
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2045 -7 19 242 74 -28 128 1105 603
2046 -6 17 218 67 -27 118 1025 555
2047 -6 15 195 60 -27 108 943 506
2048 -8 13 171 52 -43 98 858 457
2049 -8 11 147 45 -43 85 748 395
2050 -9 10 122 37 -54 72 635 333
2051 -9 8 99 30 -54 59 521 270
2052 -9 6 75 22 -57 45 403 207
2053 -9 4 50 15 -59 30 272 138
2054 -9 2 25 7 -59 15 138 69
were levelized throughout the study period at a discount rate 8% annum for a 25-
year period (the useful lifetime adopted for the system). The portions relating to the
Table 20 were not annualized, since these were
already considered in the “useful lifetime” of the BRT. The values considered served as
of the BRT System
Using the methodology for the economic evaluation of urban mitigation measures
data was calculated on a consolidated basis, taking into account both the direct and
Table 20). The criteria and parameters used for calculating these
transport users. Regarded as “reduced trip times”, these were calculated by measuring
the monetary savings involved in shorter trip times in public and individual transport
users.
arising from the alternatives analyzed, separated into two groups:
Costs of Pollution: the T5 corridor models used the basic parameters adopted •
by the “ Study of Reduction of Diseconomies through the Improvement of
Urban Public Transport “ (note that this does not deal with CO2 but only with
low atmosphere local pollutants);
Costs of Accidents: the T5 Corridor models used parameters related to •
the unit costs of accidents in the transport systems obtained from studies
undertaken by the World Bank in Brazil (cited above).
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covered in each of the alternative scenarios. The fewer kilometers travelled, the lower
the possibility of accidents and GHGs and other emissions, regardless of the type of
an intensity parameter the lower number of kilometers that would be covered in the
low-carbon scenario advocated by the BRT as against the reference scenario.
Based on the studies which formed the basis of the T5 Corridor models, we
Table 21 below presents, on a
year-on-year basis, the number of fewer kilometers covered in the low-carbon scenario
Year Number of miles (millions) Indirect Social
Reference Scenario Low-carbon scenario Low-carbon
scenario savings
2009 333,441.2 333,441.2 0.0 0
2010 342,837.1 341,111.6 1725.5 6902086
2011 352,494.1 348,966.0 3528.1 14,112,375
2012 362,419.4 357,009.3 5410.1 21,640,276
2013 372,615.8 365,283.2 7332.6 29,330,209
2014 383,095.4 373,757.9 9337.5 37,349,857
2015 393,839.7 382,649.9 11189.8 44,759,399
2016 404,877.4 391,802.4 13075.0 52,299,884
2017 416,254.6 400,916.7 15338.0 61,351,874
2018 427,943.1 410,295.5 17647.6 70,590,474
2019 439,951.4 419,947.9 20003.6 80,014,319
2020 452,293.7 429,840.1 22453.6 89,814,480
2021 464,979.5 439,979.0 25000.5 100 001 853
2022 478,015.7 450,394.0 27621.7 110 486 987
2023 491,415.1 461,070.7 30344.4 121 377 507
2024 505,234.3 471,642.8 33591.5 134 365 976
2025 519,439.6 482,475.4 36964.2 147 856 644
2026 534,039.2 493,600.7 40438.5 161 754 084
2027 549,047.4 505,003.0 44044.5 176 177 845
2028 564,497.0 516,520.4 47976.6 191 906 246
2029 580,380.0 528,323.9 52056.0 208 224 059
2030 596,709.0 540,422.1 56286.9 225 147 785
Total 9,965,819.8 9,444,453.7 521,366.1 2085464219
Table 22
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the transport modeling parameters used in the study.
Calculated for BRT Deployment
Year
Total (A)
Indirect Social
Direct Social
(C = AB)
Increase in lo-
ading in pass
x million km
by BRT in the
low-carbon
scenario (D)
Indirect
Social Be-
/ loading
in pass
million x
km (B / D)
Direct social
/ loading in pass
x million km by
BRT(C / D)
2009 0 0 0 0 - -
2010 35,010,428 6,902,086 28,108,342 10, 695 645.38 2628.25
2011 70,329,060 14,112,375 56,216,684 22, 018 640.96 2553.26
2012 105, 965, 302 21,640,276 84,325,027 33, 997 636.54 2480.40
2013 141, 643, 929 29,330,209 112,313,720 46, 399 632.13 2420.60
2014 177,652,270 37,349,857 140, 302, 413 59, 501 627.72 2357.99
2015 212, 392, 434 44,759,399 167, 633, 035 71, 810 623.30 2334.39
2016 247, 143, 893 52,299,884 194,844, 009 84, 506 618.89 2305.67
2017 290, 356, 954 61,351,874 229, 005, 080 99, 841 614.49 2293.69
2018 333, 636, 975 70,590,474 263, 046, 501 115, 702 610.10 2273.47
2019 376, 982, 592 80,014,319 296, 968, 273 132, 098 605.72 2248.08
2020 420, 704, 525 89,814,480 330, 890, 046 149, 358 601.34 2215.42
2021 464, 813, 671 100, 001, 853 364, 811, 818 167, 517 596.97 2177.76
2022 509, 160, 753 110, 486, 987 398, 673, 766 186, 444 592.60 2138.30
2023 553, 913, 221 121, 377, 507 432, 535, 714 206, 339 588.24 2096.23
2024 609, 103, 754 134, 365, 976 474,737,778 230, 115 583.91 2063.05
2025 664, 796, 486 147, 856, 644 516, 939, 842 255, 109 579.58 2026.35
2026 720, 836, 166 161, 754, 084 559, 082, 082 281, 182 575.26 1988.33
2027 777, 402, 167 176, 177, 845 601, 224 ,321 308, 567 570.95 1948.44
2028 838, 747, 856 191, 906, 246 646, 841, 610 338, 662 566.66 1909.99
2029 900, 682, 957 208, 224, 059 692, 458, 898 370, 259 562.37 1870.20
2030 963, 223, 971 225, 147, 785 738, 076, 186 403, 419 558.10 1829.55
Total 9,414,499,364 2,085,464,219 7,329,035,145 3,573,540 583.58 2050.92
the gains obtained from direct/indirect
carbon scenario as compared with the reference scenario (Table 22
and emissions models used..
The parameters indicated for the BRT in Table 22 were used for calculating the
measures.
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2.6.6 Criteria and Sources for Regional Modeling
measures for regional freight and passenger transport, “MANTRA” was used: economic
evaluation methodology andemploying the same inputs and results of the regional
transport modeling process of the present study:
for modeling regional freight transport the basic matrices formulated by the •
PNLT 2007 studies were used. These matrices were revised and brought up-
Project work groups and also taking into account new relevant information
to the modeling process;
•
of institutional sources: PNLT 2007 and data supplied by transport sector
agencies - ANTT, ANTP, ANAC and INFRAERO.
The economic evaluation procedure for regional transport enabled an assessment
of the economic performance of each alternative based on comparisons with a baseline
situation (or alternative). Any consistent set of changes proposed for a transport
system must be considered as an alternative. In this way, complete overhauling of the
rail network, the addition of a new stretch of a strategically important road or even the
considered as alternatives which can be compared to a baseline situation.
Scenarios generally evolve in ways that are not directly controllable by transport
planners. It is therefore necessary to estimate their “possible” evolution. On the other
for regional transport which comprise the low-carbon scenario: (i) one for the freight
sector (modal shift - freight) which involves fewer emissions to the detriment of road
investments and (ii) one for the passenger sector (modal shift -passengers) which
presupposes the deployment of a high-speed train between Rio de Janeiro and São
Paulo. The baseline scenario to be compared is referred to in this study as the “reference
scenario”
To undertake the economic evaluation of the mitigation measures proposed for
regional transport using “MANTRA”, the distributive criteria was used to present
concepts, applied to urban and regional modeling. (In this respect see e.g., Flowerdew,
A. - Evaluation Models for City and Regional Planning, Proceedings of the Australian Road
Research Board. In: 9th Conference (1978). This criterion makes it possible to evaluate
separately the economic impacts of each transport alternative on the two main groups
of stakeholders involved:
•
•
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sections 2.6.1, 2.6.2 and 2.6.3.
the revenues received by each operator due to the deployment of alternatives or the
the alternative can be
formula:
operating costs
Ben. (Operator) = [RT (Alt / Oper) - CT (Alt / Oper)] - [RT (Baseline / Oper) - CT
(Baseline / Oper)]
Ben. (Operators) = [RT (Alt) - CT (Alt)] - [RT (Baseline)]
where
pairs of zones in the baseline situation (reference scenario);
TT (Alt): total costs (money and time) transport
of zones in the alternative or mitigation measure under analysis (low-carbon scenario).
Note that the total monetary costs of transport users correspond to the total revenue
TT = RT + GT
where:
by the totality of operators with the alternative or mitigation measure under analysis
(low-carbon scenario);
the totality of operators in the baseline situation (reference scenario);
CT (Alt): operating costs incurred by all the operators with the alternative or
mitigation measure under analysis (low-carbon scenario);
CT (Baseline): operating costs incurred by all the operators with the baseline
situation (reference scenario).
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sensitivity of the economic evaluation against these assumptions.
mitigation measure is needed that can reduce the overall cost of transport to the user
across a given pair of zones. The overall cost of transport to the user corresponds to the
carry the user or product from origin to destination by the various forms of transport
available.
Assuming that, due to the reduced overall cost of transport from T to T1 the demand
increases between D and D1
parts:(i) related to the reduction of costs as compared to those incurred by former
1
corresponds to the increased demand for transport between that pair of zones due to
reduced transport costs. It can be assumed (for reasons of clarity) that in this interval
the demand curve can be represented by a straight line.
called “consumer surplus”.
across each pair of origin-destination zones:
where:
deployment of the alternative or mitigation measure under consideration.
It is often argued that demand between pairs of zones is inelastic over the short
term. This presupposes that changes (in time and costs) in transport supplied for a
time has elapsed.
corresponding to the consumer surplus produced by demand variation. The economic
public transport.
where:
TT (Baseline):
pairs of zones in the baseline situation (reference scenario);
TT (Alt): total costs (money and time) on transport
pairs of zones, in the alternative or mitigation measure under analysis (low-carbon
scenario).
Note is that total user-spending on transport corresponds to the total revenue
accruing to the totality of system operators. The value TT can also be written as:
TT = RT + GT
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where:
GT: time spent by users (or their products) on transport.
where:
zones in the baseline situation (reference scenario);
in the alternative or mitigation measure in the analysis (low-carbon scenario).
GT (Baseline): time spent by users (or their products) on
(reference scenario);
GT (Alt): time spent by users (or their products) on transport, converted into
mitigation measure in the analysis (low-carbon scenario).
economic evaluation of regional transport mitigation measures as being direct “social
referred to in 2.6.3.3 above.
Conclusions2.7
The methodology used and consolidated throughout this study resulted from the
information was also needed to facilitate building the scenarios. The work revealed
consistent data and information; and (ii) the lack of coordination among the various
stakeholders in the sector.
Notwithstanding the above problems, the work team succeeded in producing robust
and consistent estimates which matched those developed by other groups working on
and hopefully contribute to reducing carbon emissions for the different transport
modes. Meanwhile, it is obvious that the behavior patterns of transport-users
throughout Brazil need to be future. Streamlining of both freight and
passenger transport regionally and in urban areas will introduce more balance into the
Figure 26 shows the modeling structure used for linking regional and urban
transport to fuel consumption, as well as the related parameters and information
sources used in our work. It is important to highlight the diversity of factors considered
as representing the transport system and energy consumption by the sector in Brazil. A
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number of features of the model are worth highlighting:
•
diesel;
•
dependent on diesel;
in the cities, diesel continues to be the main fuel used for freight transport; •
diesel also plays a major role in passenger transport in the urban areas, •
although vehicle energy sources are more diverse.
Figure 27: Linking Regional and Urban Transport to Fuel Consumption
Source: Logit
Finally, it is important to note that in the course of formulating the methodology
for the study’s work, a number of partnerships were established in order to take best
Ministries of Transport, Cities, Environment, together with CETESB - São Paulo, and
FIPE were particularly helpful in this respect.
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REFERENCE SCENARIO3
The Reference Scenario considered for the transport sector is the same as
that designed for the PNE 2030 (ranked as the “most likely”). To estimate future
consumption and emissions, the PNE adopted a type of top-down methodology. The
main parameters for the PNE projections were (i) the volume of fuel sold in the country
2007.
It is important to emphasize that the fuel consumption volumes resulting from
the transport sector modeling were reconciled and adjusted in line with the trend
based on a bottom-up methodology.
The projections considered in the 2030 PNE assume that the investments
foreshadowed in the PAC for transport infrastructure work would be implemented by
the end of the study’s timescale (2030).
Table 16 shows perfect harmony between the fuel consumption projections
estimated by the PNE 2030 using the top-down methodology with the bottom-up
method considered in the transport modeling.
Table 23A: Projections of Consumption by Type of Fuel in the Reference Scenario
Fuel PNE 2030 (1000 m3) Transport Modeling
(1000 m3)
Gasoline 42,190 42,376
Diesel 74,760 74,767
Ethanol 53,304 52,611
Source: NAP 2030 / Logit
which uses bio-ethanol widely as a fuel for light vehicles, the reference scenario can
already be regarded as a “low emissions” scenario, compared to other countries with
the same problems caused by rapid increases in the number of motorized vehicles.
In the light of the above, particularly in the case of urban transport, the future low-
2
emissions by private vehicles. Meanwhile, prioritizing the public transport system at
this alternative targets reductions in the number of private cars in circulation.
Table 23-A presents estimates of CO 2, emissions calculated for the Brazilian
Direct Emissions: CO •2 emissions resulting from direct combustion by all
types of vehicles used in transporting freight and passengers. This was the
criterion adopted in this project for calculating emissions from the transport
sector in the two scenarios studied,
Total Emissions: direct emissions, plus emissions from the processes needed •
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Total emissions without the addition of bio-fuels: total emissions considering •
gasoline with no alcohol added (G0), and diesel without the addition of
biodiesel (B0).
Table 23B: Estimates of Emissions in 2007 by Type of Fuel, According to Different Criteria
Fuel type
Direct Emissions
(In MtCO 2 e)
Total Emissions
(in MtCO 2 e)
Total Emissions - Gasoline E0 and
Diesel B0 -
(in MtCO 2 e)
Ethanol 0.00 4.48 4.48
Gasoline 40.76 51.14 64.12
Diesel 94.86 115.76 119.34
Aviation Fuel 8.44 10.25 10.25
Electricity 0.00 0.13 0.13
Total 144.06 181.76 198.33
Source: Logit (2009)
Table 23A indicates that if biofuels had not been added to diesel and gasoline,
emissions for 2007 would have been around 39% higher: 144.06 MtCO 2
MtCO 2 e. Furthermore, in this hypothetical scenario, if ethanol had not been used
as engine fuel in Brazil, at least another 35.0 MtCO2 (caused by burning gasoline
as an alternative to ethanol) would be added to the 181.76 MtCO 2 e , totaling
transport sector in Brazil as an already low-carbon scenario.
Structuring the Reference Scenario 3.1
In the National Logistics and Transport Plan (PNLT 2007), the reference scenario
forecasts a probable situation for 110 sectors of the Brazilian economy (557
micro-regions), considering the constraints under which they operate and framing
assumptions about some of their basic structural aspects. The “probable” scenario was
the relatively- recent development of the economy.
Assuming a reference scenario for the period 2007-2031 (with 2007 as the baseline
year), the results were generated from projections based on the projections of the
EFES model developed by FIPE-USP, which provides inputs for a module containing
sub-sector variables. Formulating these scenarios made it possible to project inputs for
calculating the transport matrices for the future PNLT horizons.
The assumptions of future scenarios needed for formulating the projections of
relevance to this project were initially the same as those utilized in the 2007 PNLT. As
our work developed, these assumptions were adjusted in order to reconcile and/or
align them with possible alternative scenarios structured by other groups or study
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teams participating in the project. In this way they were totally integrated into the
parameters and assumptions postulated in the PNE 2030.
This approach sought to ensure that the assumptions used for the projections of
freight and passenger movements were consistent with the other premises adopted
in the modeling of other study areas. In addition to ensuring the consistency of
assumptions, the work also the possibility of producing sensitivity analyses by using
regional growth, with direct impacts on the results of the projections.
As mentioned in sections 1.6 and 2.3 of this report, in order to build a “most likely”
scenario (provided that unforeseen political-institutional or other unpredictable
events do not intervene), it was decided that for the purposes of this study the transport
infrastructure projects and interventions planned by the PAC were to be implemented
by 2030. These investments, also dealt with in the PNLT-2007, were regarded as the
“reference scenario” investments, thereby enabling an evaluation of emissions in the
Reference Scenario Projections3.2
The present study is based on bottom-up methodology which estimates future
consumption and emissions on the basis of freight volumes, numbers of passengers
transported and the distances covered by each mode of transport. The fuel
consumption assumptions’growth rates are the same as those adopted in the PNE
2030.
The set of models enabled us to project the relevant variables on an annualized basis,
taking into account the impact of PAC investments on regional transport infrastructure
and the Urban Mobility Plans “balance sheets” for urban transport infrastructure. In
this way it was possible to estimate
for all the regional and urban transport modes, in the reference scenario.
Table 24 presents the projected values for loads and the resulting direct
CO 2 emissions in the reference scenario for regional and urban transport. Emissions
from the transport sector in this scenario would increase by 72% during the period
between 2007 and 2030, from 144 MtCO 2 to 247 MtCO 2,
4.8 billion tons of CO 2 between 2010 and 2030.
The relative contribution of urban transport in terms of direct emissions declines
marginally, from 52.2% in 2007 to 51.9% in 2030 (52.1% of total emissions in 2010-
2030). The impact of urban transport on the total direct transport sector emissions can
up to 2030. The introduction of vehicles forms part of Brazil’s energy policy
to encourage the use of alcohol in motor transport. According to ANFAVEA, around
90% of all the light vehicles in circulation will be by 2030. If ethanol’s price is
competitive with gasoline’s, there is little doubt that all the PNE 2030 projections will
In the case of private vehicles for regional and urban transport, the projected
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passenger loads for gasoline-powered cars between 2007 and 2030 will increase 1.2
Table 24: Load and GHG Emissions for the Reference Scenario, 2007–30
Load Global direct
(Mt * km or pax * km/
year)
CO2 emissions*
(Mt CO2)
Load type
Transport
mode
Vehicle
type
Fuel
type
2007 2030 2007 2030 2010 - 2030
Urban
Freight
Road Truck Diesel 32,436 49,151 4.9 7.6 131.1
Total urban freight 32,436 49,151 4.85 7.58 131.1
Urban
passenger
Road
Bus
Diesel
730,799 32.9 43.1 827.3
BRT 0 102,332 0.0 2.1 19.6
Car Ethanol 96,399 364,894 0.0 0.0 0.0
Car and
motorbike Gasoline 272,570 347,346 36.6 66.2 1,087.0
Rail
Metro
Electricity
28,412 55,385 0.021 0.039 0.63
Train 35,370 50,699 0.022 0.029 0.55
Total urban passenger 864,078 1,651,46 69.5 111.4 1,933.9
GHG emissions from urban transport - - 74.4 119.0 2,065.0
Regional
freight
Rail Train
Diesel
321,240 552,364 4.4 6.6 114.8
Waterway Boat 26,984 81,349 0.2 0.5 8.1
Pipeline Pipeline 15,732 24,727 0.1 0.1 1.5
Road Truck 689,057 1,274,440 48.0 77.3 1,323.5
Total regional freight 1,053,013 1,932,880 52.7 84.5 1,447.9
Regional
passenger
Road
Car Ethanol 21,905 176,485 0.0 0.0 0.0
Car and
motorbike
Gasoline 83,166 97,031 4.2 5.2 94.8
Bus Diesel 154,845 276,915 4.5 7.3 124.0
Air Plane Aviation
kerosene
45,259 127,569 10.5 28.7 400.8
Rail High-
speed train
Electricity - - 0.0 0.0 0.0
Total regional passenger 305,175 678,001 19.1 41.2 619.6
GHG emissions from regional transport - - 71.7 125.7 2,067.5
TOTAL TRANSPORT-SECTOR EMISSIONS 146.2 244.7 4,132.5
(*) in order to avoid double counting with emissions already accounted for in the agriculture and energy
sectors, only direct emissions are included in this table.
Source: Logit Modeling and Processing - 2009
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2 emissions and fuel consumption
by TEPs (tons of oil equivalent) in the baseline scenario for all types of vehicles,
regardless of geographical location (urban or regional) or type of transport (freight or
passenger). Figure 28 shows that most emissions in the transport sector in Brazil are
produced by cars, trucks and buses - around 3.6 billion tons of CO2 - 88% of the total in
2010-2030.
Figure 28: Evolution of Transport Sector Emissions in the Reference Scenario
Source: Logit (2009)
Figure 29
that fuel consumption and emissions are directly correlated. However, increasing
ethanol production in Brazil means that between 2007 and 2030 fuel consumption
will increase faster than emissions - 3.4% a year for fuels, compared with 2.4% for
emissions.
Figure 29: Fuel Consumption Trends (in TEP) by 2030,
by type of vehicle in the Reference Scenario
Source: Logit (2009)
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The growing consumption of ethanol compared to gasoline in private vehicles (the
main users) is clear from a comparison between the two graphs in Figure 30. Note
biofuel consumption by 2030 (Biodiesel and Bio-H).
Figure 30 below compares the growth of emissions in the baseline scenario with a
scenario without “clean fuels” is substantial: in 2030, an additional 165 MtCO 2 would
be emitted between 2010 and 2030, amounting in absolute terms to around 2.3 billion
tons of CO 2, representing an increase of 57% compared to the baseline scenario.
Figure 30: Comparison of the Evolution of Emissions by Vehicle Type in the Reference
Scenario x Hypothetical Scenario involving gasoline and diesel
Source: Logit (2009)
Figures 31 and 32
regional level, trucks are the mainly cause for emissions, accounting for around 66% in
2010-2030, followed by aircrafts, which account for only 17.5%. Note however that the
emissions curve for the aircraft sector grows steeply (4.6% a year, compared to 2.0%
for trucks).
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Figure 31: Evolution of Regional Transport Emissions to 2030 (by vehicle type) in the
Reference Scenario
Source: Logit (2009)
Cars and motorcycles are responsible for around 51% of emissions in urban areas
for the transport sector between 2010 and 2030, followed by conventional buses which
fast growing emissions curve: 1.8% a year for conventional buses and 2.6% for cars and
motorbikes.
Figure 32: Evolution of Urban Transport Emissions to 2030 (by type of vehicle) in the
Reference Scenario
Source: Logit (2009)
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MITIGATION OPTIONS4
Master Plans for the metropolitan regions, and government plans and programs, a set
of mitigation options was selected which could feasibly be deployed by year 2030 in the
reductions of CO2 emissions, are presented separately for regional transport and urban
transport respectively.
Mitigation Options for Regional Transport4.1
The set of public policies for regional transport addresses the modal supply and
transporting merchandise (around 60% of the total volume) and passengers. A more
(e.g. soybeans) or bulk liquids (oil products, ethanol, alcohol etc) would be by rail and
to a substantial reduction of CO2 emissions at the regional level.
The majority of regional passenger trips are also made by road, either by bus or
private cars (and a small number by air). The latter produces emission levels per
mitigation measures being considered in this respect is the possibility of a special “fast
train” link between Brazil’s two major economic centers, Rio de Janeiro and São Paulo.
resources for undertaking the works. Given that the idea is to have the new service in
full operation during the World Cup in 2014 the project has been included in the low
counterpart sums to be made available for this project. Thus the Federal Government
is hoping to introduce a high “percentage waiver” to help establish the fast train service
to link the cities of Campinas, São Paulo, São José dos Campos and Rio de Janeiro. The
(“state counterpart”) may be restricted to a small portion of the resource requirements,
completed.
Modal Shift - Freight4.1.1
in Brazil. Both the PNLT and PNMC have highlighted the importance of reducing the
volume of freight carried by trucks and a corresponding increase in carriage by more
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shift aimed at shifting freight away from road transport to railways, waterways and
pipelines). Tables 25 and 26 present the main transport indicators, as well as the CO2
emissions, for each mode/segment in the low-carbon scenario and their respective
“modal shift” related to the mitigation option for regional freight transport. While this
measure is aimed at freight transport it could also have an impact on regional passenger
transport on the roads.
Table 25: Comparison of Projected Emissions Reduction for Regional Transport
in 2030: Modal Shift Scenario
Segment
Trans-
port
mode
Vehicle
type
Fuel
type
Load
(Mt * km or pax * km/year)
GHG
direct emissions*
(Mt CO2e/year)
Avoided emis-
sions
2010 – 2030
Reference
scenario
Low-
carbon
scenario
Reference
scenario
Low-
carbon
scenario
MtCO2e
Freight
Rail Train
Diesel
552,364 703,854 6.5 8.3 -25.4
Water Ship 81,349 133,503 0.5 0.9 -4.5
Pipeline Pipe 24,727 26,621 0.08 0.09 -0.1
Road Truck 1,274,440 1,113,926 77.3 65.5 115.1
Total freight (regional) 1,932.880 1,977.904 84.5 74.9 85.1
Passenger
Road
Car Ethanol 176,490 165,460 0 0 0
Car and
motor-
bike
Gasoline
97,030 90,970
5.2 4.9 4.5
Bus Diesel 276,915 276,915 7.3 7.1 -0.6
Air Plane Aviation
kerosene
127,569 127,569 28.7 28.7 0
Total passengers (regional) 678,010 660,920 41.2 40.7 3.9
TOTAL EMISSIONS: load and passenger (regional) 125.7 115.6 88.9
(*) in order to avoid double counting with emissions already accounted for in the agriculture and energy
sectors, only direct emissions are included in this table.
Source: Logit (2009)
for promoting a
modal shift, particularly in the freight transport area, with the aim of reducing total CO2
emissions in a low-carbon scenario.
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Table 26: Avoided Emissions - New Modal Shift
Segment Mode Vehicle
Type
Fuel Gains as result of measure Accumulated gains in
low-carbon scenario
Absolute % Baseline Absolute % Reference
Scenario
2030 2010-
2030
2030 2010-
2030
2030 2010-
2030
2030 2010-
2030
Regional
Freight
Road Trucks Diesel 9054 84 137 12.0 6.5 9054 84 137 12.0 6.5
Rail Train -2033 -28 239 -31.6 -25.1 -2033 -28 239 -31.6 -25.1
Waterways Vessels -363 -4766 -69.5 -59.8 -363 -4766 -69.5 -59.8
Pipeline Pipelines -9 -145 -11.2 -10.1 -9 -145 -11.2 -10.1
Regional
Total Charges
6650 50 987 8.0 3.6 6650 50 987 8.0 3.6
Regional
Passenger
Road Cars Ethanol 0 0 0.0 0.0 0 0 0.0 0.0
Cars +
Motorcycles
Gasoline 327 4499 6.2 4.7 327 4499 6.2 4.7
Bus Diesel 837 7174 11.1 5.7 837 7174 11.1 5.7
Regional Passenger Total 1164 11 673 3.2 2.1 1164 11 673 3.2 2.1
Avoided Emissions Totals for
Regional Transport
7813 62 660 6.6 3.2 7813 62 660 6.6 3.2
Total Avoided Emissions for Transport Sector 7813 62 660 3.2 1.5 7813 62 660 3.2 1.5
Source: Logit (2009)
In terms of absolute values, it can be seen that in the 2030 low-carbon scenario
the total quantity of CO2 emitted is reduced by around 9% compared to the reference
scenario. This value stems mainly from the reduction in the relative share of freight
transport by road – from 66% to 56%.
Figure 33: Comparison of Modal Distribution of Freight Load:
Reference v Low Carbon Scenario
Source: Logit (2009)
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hidrovias) in
the North and Center-West of Brazil, although at present the demand in these regions
number of logistical solutions have already been deployed for transporting these
products by water, competition from other transport modes is severe.
As mentioned previously, the projects involving switching from road investments to
other transport modes which are potentially lower CO2 emitters are also those with the
Table 27 below is a summary of the investments planned for the mitigation option
which considers a modal shift for freight transport in Brazil in 2030. The projections
for the reference and low-carbon scenario are presented. It is clear that the low-carbon
scenario will involve substantial investments: US $ 42 billion.
Table 27: Regional Freight Transport: Comparison of Investments
in the Reference and Low-carbon Scenarios, 2010–30
Year
Reference scenario (million US$) Low-carbon scenario (million US$)
Rail and waterway Road Total Rail and waterway Road Total
2010 0.396 - 0.396 0.396 - 0.396
2011 0.793 - 0.793 0.793 - 0.793
2012 1.189 - 1.189 1.189 - 1.189
2013 - - - - -
2014 0.356 2.788 3.144 0.356 2.548 2.905
2015 0.712 5.575 6.288 0.712 5.097 5.809
2016 1.069 8.363 9.432 1.069 7.645 8.714
2017 - - - - - -
2018 - 0.554 0.554 1.331 0.554 1.885
2019 - 1.108 1.108 2.661 1.108 3.769
2020 - 1.662 1.662 3.992 1.662 5.654
2021 - - - - - -
2022 - - - 0.581 - 0.581
2023 - - - 1.162 - 1.162
2024 - - - 1.742 - 1.742
2025 - - - - - -
2026 - 1.251 1.251 - 1.185 1.185
2027 - 2.503 2.503 - 2.369 2.369
2028 - 3.754 3.754 - 3.554 3.554
2029 - - - - - -
2030 - - - - - -
Total 4.516 27.559 32.074 15.984 25.722 41.707
Source: PAC / PNLT / Logit
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Among the investments selected in the low-carbon scenario and linked to the modal
Hidrovia (waterway), as can be seen in Figures 33A and 33B:
Figure 33A: Freight carried on Teles Pires Hidrovia x BR-163 - Reference Scenario
]
Source: Logit (2009)
Figure 33B: Freight carried on Teles Pires Hidrovia x BR-163 - Low-carbon Scenario
Source: Logit (2009)
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Of the 6,150,000 tons of soya transported on the BR-163 highway in the reference
scenario, 4,500,000 tons would be transferred to the Teles Pires Hidrovia in the low-
carbon scenario.
will absorb the majority of the agricultural and liquid bulk products at present carried
Figure 33C: Soybean Freight Loads in Bahia - Reference Scenario
Source: Logit (2009)
Figure 33D: Soybean Freight Loads in Bahia - Reference Scenario
Source: Logit (2009)
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be transported by road in the baseline scenario. In the low-carbon scenario this will use
the “West Bahia Railway”.
The additional resources required in the PNLT low carbon scenario compared to the
reference scenario (PAC) will amount to around US$10 billion –mainly consisting of
investment in railways and waterways. This policy would generate saving reduction of
2 between 2010 and 2030 (see Figure 34):
Figure 34: Evolution of Emissions: Reference versus Low Carbon Scenario
Source: Logit (2009)
structure an appropriate and realistic allocation of resources. In order to ensure the
costs of the appropriate infrastructure. The investments required to implement this
low carbon policy and the related abatement costs are presented in the graphs below
Figure 35: Curves of cost reduction (nominal)
Source: Logit (2009)
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Figure 36: Abatement Cost Curves (present value)
Source: Logit (2009)
Table 28: Average cost of avoided CO 2
Abatement Curves US$ per tCO 2 e
Nominal Present Value in 2009
Low Carbon Investment 827.80 289.04
Avoided Investment 157.13 45.22
Fuel Savings 111.31 29.01
Operating Gains -18.21 -9.72
-151.14 -49.09
Source: Logit (2009)
The “additional investment required” curve was provided by the MANTRA model,
programs for 2030 with the new investments projected for a low carbon scenario.
The O & M costs of the projects in the event of modal shift were also determined, with
priority given to the alternatives to road transport.
The curve of “avoided infrastructure investments” (and O&M) was modeled,
targeting the projects which will not be deployed in a low-carbon scenario. Energy-
saving and emissions-reducing projects were awarded priority. The costs (including
operation and maintenance) of the non-implemented projects were calculated, with
the resulting values considered to be “gains” or “avoided” costs in the low-carbon
scenario.
The modeling also indicated the amount and costs of the fuel not used in these
projects. These values were also calculated as “avoided” costs in the low-carbon
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Modal Shift - Passengers4.1.2
In the case of passenger transport, the mitigation option considers that a change
is necessary in the present passenger transport structure at the regional level. With
network, travel is done virtually 100% by road. A small higher-income segment of the
population tends to use air travel over the same routes. The mitigation option aims to
being studied at present to provide a link between Rio and São Paulo. If this proves to be
other train links between large metropolitan regions could enter service by 2030. The
main idea is to reduce the number of people currently using road transport.
Tables 29 and 30 present the projections for loads and direct emissions, by type
of vehicle, in the baseline and low-carbon scenarios, together with the inclusion of the
mitigation measure which considers the introduction of the above-mentioned TVA.
Table 29: High Speed Train (TAV), Loads and Emissions: Baseline x Low Carbon Scenarios
Segment Mode Vehicle
Type
Fuel Loading in 2030
(millions pax * km)
CO 2
(thousand tons)
Baseline Low
Carbon
Baseline Low Carbon
2030 2010-
2030
2030 2010-
2030
Regional
Passenger
Road Cars Ethanol 165, 457 162, 280 0 0 0 0
Cars &
Motorcycles
Gasoline 90, 968 89, 221 4901 90, 308 4807 89, 066
Bus Diesel 276, 915 266, 675 6704 118, 478 6425 114, 822
Rail TAV Electricity 0 21, 092 0 0 0 0
Air Airplanes Aviation
fuel
127, 569 121, 641 23 740 324, 010 23, 128 317, 259
Regional Passenger Total 660, 909 660, 909 35, 344 532, 796 34, 359 521, 148
Total Emissions Regional Transport - - 111, 348 1,900,591 110, 363 1,888,943
Total Emissions from Transport Sector - - 239, 675 4,038,079 238, 690 402,6431
Source: Logit (2009)
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Table 30: High Speed Train (TAV): Emissions Avoided
Segment Mode Vehicle
Type
Fuel Gains from measure Gains from deployment of
low-carbon scenario
Absolute
% Baseline
Absolute
% Reference
Scenario
2030 2010-
2030
2030 2010-
2030
2030 2010-
2030
2030 2010-
2030
Regional
Passenger
Road Cars Ethanol 0 0 0.0 0.0 0 0 0.0 0.0
Cars &
Motorcycles
Gasoline 94 1,242 1.9 1.4 421 5,741 8.0 6.1
Bus Diesel 279 3,656 4.2 3.1 1,116 10, 829 14.8 8.6
Rail TAV Electricity 0 0 0.0 0.0 0 0 0.0 0.0
Airway Airplanes A v i a t i o n
fuel
612 6,751 2.6 2.1 612 6,751 2.6 2.1
Regional Passenger Total 985 11, 648 2.8 2.2 2,149 23, 321 5.9 4.3
Avoided Emissions Totals
Regional Transport
985 11, 648 0.9 0.6 8,798 74, 308 7.4 3.8
Total Avoided Emissions by Transport Sector 985 11, 648 0.4 0.3 8,798 74, 308 3.6 1.8
Source: Logit (2009)
While the quantity of emissions avoided in 2030 is probably not particularly
substantial (1.0 MtCO 2 , or around 2.8% lower than the reference scenario),
nevertheless the reduction of 1.9 g CO 22 at the
baseline less 52.0 g of CO 2 in the low-carbon scenario) shows that the savings could
increase and be sustained.
be restricted to the Rio-São Paulo corridor, the service has the capacity to attract a
Figure 37: High Speed Train (TAV): Modal Load Shift - Baseline x Low Carbon Scenario
Source: Logit (2009)
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An overall reduction of 11.6 MtCO 2 in net emissions between 2014 and 2030 alone,
may not justify the US$16 billion projected investments for the Rio de Janeiro-São Paulo
high-speed rail link. Nevertheless, in addition to the possibility of increased gains, civil
Figure 38: Evolution of emissions: Reference x Low Carbon Scenario
Source: Logit (2009)
In the baseline scenario, emissions from aircraft used for regional passenger transport
Figure 38 the evolution curve in the
low-carbon scenario shows a slight shift from 2014 - the year planned for launching
and social/economic impacts (positive and negative) arising from this project could
be considerable. There remains no doubt that the Brazilian civil aviation sector will
need to radically change its modus operandi in the Rio-SP corridor.
The investments required for implementing this particular emissions mitigation op-
tion in regional transport and its respective abatement costs are shown in the follow-
Figure 39: Cost Reduction Curves (Nominal)
Source: Logit (2009)
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Figure 40: Abatement Cost Curves (Present Value)
Source: Logit (2009)
Table 31: Average costs of tCO 2 avoided
Abatement Curves US$ per tCO 2 e
Nominal Present Value (2009)
Low Carbon Investment 2187.49 862.73
Avoided Investment 1093.75 431.37
Fuel Savings 1005.84 400.34
Operating Gains 807.91 327.63
584.27 248.41
Source: Logit (2009)
As in the case of freight transport, the required additional investments concern new
projects in a low-carbon scenario. The additional operation and maintenance costs
through PPPs was considered to be “avoided” investments.
The “avoided investments” curve is the result of the modeling based upon projects
that will be substituted after the high-speed train is launched. The maintenance and
operation costs of such projects are also calculated.
The fuel economy curve (“fuel consumption avoided”) is based upon the volumes of
jet fuel, diesel and gasoline that will be saved (i.e. not spent) on roads and air transport
due to the modal shift of some of the trips from road and air to rail.
Government.
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Existing Barriers4.1.3
The Ministry of Transport, using the National Plan for Transport Logistics (PNLT)
feasibility of fully implementing the plan during this time period. The study assumed
that it would be more feasible to envisage the implementation of all(or most of)the
projects contained in the PNLT by 2030.
also include Federal Government interventions under the Growth Acceleration Plan
(PAC). The projections resulting from the modeling developed for regional transport
assume that the PAC projects are completed by 2030 - forming a kind of “Legality
deployment of the PNLT projects.
High infrastructure investment costs ; •
Need for centralized coordination of the new Infrastructure implementation •
program;
Need for more integration among transport •concessionaires;
•
cargoes;
•
Relatively lower volume of freight in the North and Northeast, where potential •
Measures for Overcoming Barriers 4.1.4
It is obvious that operators using alternatives to road transport, particularly for
freight, stand to gain most from this set of policies. The current competition between
road transport and other modes for transporting large amounts of freight contributes
with regard to modal integration and using a transport infrastructure in need of
modernization.
in 2030 would generate negative impacts for independent operators faced with fewer
options to transport freight. A possible strategy for reducing these future impacts
would be to establish integrated transport routes where the distances would be
shorter, but where frequency would be enhanced. An operational balance could thus be
achieved with a more streamlined system.
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carbon scenario would be the introduction of the high-speed train (TVA). It is entirely
train service. If as a result of this switch, the number of road and air passengers were
to be reduced, the economic viability of a number of air and bus companies could be
undermined. A prospective analysis of the possible impacts on this particular market
is recommended in order to avoid possibly serious economic and social problems in
these sectors.
Alternatives for overcoming barriers:
Financing model that facilitates the raising of resources for new transport •
infrastructure investment;
Ministry of Transport to coordinate the deployment of new infrastructure; •
•
network;
Incentives to increase the volume of cabotage; •
To monitor deployment of PAC and PNLT projects. •
Mitigation Options for Urban Transport4.2
concentration of vehicles operating in densely-populated areas, and the need to ensure
pedestrian safety in such areas. The close interaction between various modes of
transport and the links between transport, land use, local economic development, and
urban areas.
Three groups of emissions mitigation options were considered in the urban
transport facilities in the metropolitan regions. The second focused on interventions
in travel demand management, where the priority is to reduce trip length and demand
and promote a shift from private cars to high-occupancy transport. The third focuses on
developing zero-carbon, non-motorized transport.
Use of High -Occupancy Public Transport 4.2.1
in metropolitan areas using modes such as the BRT (Bus Rapid Transit) and the
Metro. Urban transport in Brazilian cities is primarily by bus, which at present accounts
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for around 85% of all trips. The carbon emissions of buses are a function of speed, since
lower velocities imply lower fuel consumption. BRT systems can operate in higher
average speeds, because they can travel in dedicated lanes. This more constant and
higher average speed, when compared to the operation of conventional buses results in
a fewer emissions
In addition, compared to conventional bus systems, BRT can transport many
more passengers, thereby reducing fuel consumption per passenger kilometer. BRT
vehicles require less frequent maintenance due to its more regular operation. Policies
supply of public transport services must be encouraged in order to reduce the number
of vehicules on the road and the level of CO2e emissions.
cities such
as In Rio
Tijuca neighborhood via a private concession is likely to become operational. Plans
of the low-carbon scenario.
metro underway and Belo Horizonte´s Master Plan, issued in 2009, anticipates
building metro lines which could be in operation by 2030.
Loads and global emissions for all urban passenger transport modes were projected
transport infrastructure. This was done initially for a low-carbon scenario which
investments could add to the low-carbon scenario. The BRT usesdiesel, both in the
reference and low-carbon scenarios.
Table 32 below presents the results projected for loads and direct emissions by type
of vehicle in the baseline and low-carbon scenarios, including the deployment of diesel
-fueled BRTs. Table 33 details the absolute and total emissions avoided. Note that the
total value of overall emissions in the low-carbon scenario for 2030 is considerably
less than those for the baseline: 112 MtCO 22,
around 8%. This saving is due to the introduction of the BRTs for passenger transport
in the low-carbon scenario, compared to the base scenario – which, in 2030, will be
considerably higher: 30% versus 6%. In the reference scenario, of the new passengers
using the BRTs, 69% would be previous users of conventional buses (from 44% to 27%)
and 17% would be potential car users (private car use would decline from 43% to 38%.
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Table 32: Loading and emissions - BRT - Baseline x Low Carbon
Segment Mode Vehicle
Type Fuel
Loading in 2030
(millions pax x km)
CO 2 emissions
(thousand tons)
Baseline Low
Carbon
Baseline Low Carbon
2030 2010-
2030 2030 2010-
2030
Urban
Passengers
Road Bus Diesel 730, 799 453, 337 51 310 887, 697 39 398 732, 048
BRT 102, 332 505, 751 3360 32,370 13 349 155, 713
Cars Ethanol 364, 894 329, 657 0 0 0 0
Cars +
motorcycles
Gasoline 347, 346 313, 804 66 160 1,087,014 59 227 1,016,901
Metro
+ rail
Metro Electricity 55, 385 39, 256 0 0 0 0
Trains 50, 699 33, 594 0 0 0 0
Total Urban Passenger 1,651,455 1,675,399 120 829 2,007,082 111 974 1,904,662
Total Urban Transport Emissions - - 128 327 2,137,488 119 472 2,035,068
Total Emissions from Transport Sector - - 238 690 4,026,431 229 835 3,924,011
Source: Logit (2009)
Table 33: Emissions avoided – BRT
Segment Mode Vehicle
Type Fuel
Gains from measure Accumulated gains from
deployment of low-carbon scenario
Absolute
% Baseline Absolute % Reference
Scenario
2030 2010-
2030 2030 2010-
2030 2030 2010-
2030 2030 2010-
2030
Urban
Freight
Road Trucks Diesel 0 0 0.0 0.0 0 0 0.0 0.0
Total Urban Loads 0 0 0.0 0.0 0 0 0.0 0.0
Urban
Passengers
Road Bus Diesel 11, 911 155, 649 30.2 21.3 11, 911 155, 649 23.2 17.5
BRT -9,989 -123, 342 -74.8 -79.2 -9,989 -123, 342 -297.3 -381.0
Cars Ethanol 0 0 0.0 0.0 0 0 0.0 0.0
Cars +
motorcycles
Gasoline 6,933 70, 114 11.7 6.9 6,933 70, 114 10.5 6.5
Metro-rail Metro trains Electricity 0 0 0.0 0.0 0 0 0.0 0.0
Trains 0 0 0.0 0.0 0 0 0.0 0.0
Total Urban Passenger 8855 102 420 7.9 5.4 8855 102 420 7.3 5.1
Total Urban Transport Emissions 8855 102 420 7.4 5.0 8855 102 420 6.9 4.8
Source: Logit (2009)
The studies for the Belo Horizonte Urban Mobility Plan, completed in 2009, served
as a basis for the simulations undertaken in the present paper. Figures 40 and 40A
below illustrate the results in 2030, based on simulations made under the above
mentioned plan, with respect to the locomotion of passengers in collective trips and
private trips, respectively, by vehicule, compared a scenario without investments with
a scenario with more than 100km of BRT investments.
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Figure 40A: Belo Horizonte: with and without Investments in BRT (2030 Reference and
Low Carbon Scenarios) - Public Transport Passenger Loads
Source: Belo Horizonte Transport Plan / Logit (2009)
Figure 40B: Belo Horizonte: with and without Investments in BRT (2030 Reference and
Low Carbon Scenarios) - Private Vehicle Users
Source: Belo Horizonte Transport Plan / Logit (2009)
In 2030, the Belo Horizonte BRT will absorb virtually all the passengers from
conventional buses in the reference scenario. Ordinary buses (in the BRT investment
scenario) will continue to be used in parallel wherever necessary.
Travel by light vehicles and motorbikes will diminish slightly by 2030 in the scenario
with investments compared to the scenario without investments.
results of the simulations for the low-carbon scenario proposed in the present paper.
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In the low-carbon scenario for diesel-fueled BRT, compared with the baseline
scenario, much of the passenger loads of conventional buses and a small segment of
passengers shifting from cars and motorbikes will be absorbed by the BRTs, as seen in
Figure 41.
Figure 41: Modal Distribution of Passenger Load - BRT - Baseline Scenario x Low Carbon
Source: Logit (2009)
buses. As a result the new modal distribution in the low-carbon scenario will mean
that lower volumes of CO2 will be produced. The migration of car and motorbike users
to the BRT will not be as substantial as passengers shifting from ordinary buses to BRT,
but any shift, even by a minority of individuals, will contribute to emissions and fuel
savings, as indicated in Figure 42:
Figure 42: Fuel Consumption Trends (TEP) up to 2030, by Vehicle Type - BRT - Baseline x
Low Carbon Scenario
Source: Logit (2009)
The investment required to build the 649km of BRT lanes considered in the
reference scenario would total about US$6.5 billion. The modeling indicates that it
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carbon scenario, requiring an additional US$26 billion. This would require public-
margins involved).
Figure 43: Evolution of Emissions: Baseline Scenario x Low Carbon
Source: Logit (2009)
The investments in BRT in the low-carbon scenario proposed here should lead to
a reduction in net emissions in the urban passenger transport sector of 102 MtCO 2
between 2010 and 2030.
The total emissions in the low-carbon scenario for 2030 will reduce further with
the inclusion of investment in the metro system. Table 34 below shows loads and
emissions in the reference and low-carbon scenarios, with investments in high-
occupancy public transport, the introduction of diesel-fueled BRTs and improvements
to the metro networks.
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Table 34: Passenger Loads and Emissions - Metro - Baseline Scenario x Low Carbon
Segment Mode Type
Vehicle Fuel
Loading in 2030
(millions pax x km)
CO 2
(thousand tons)
Baseline Low Carbon
Baseline Low Carbon
2030 2010-
2030 2030 2010-
2030
Urban
Passengers
Road Bus Diesel 453, 337 346 281 39, 398 732, 048 29, 696 670, 044
BRT 505, 751 470, 621 13, 349 155, 713 12, 430 143, 544
Cars Ethanol 329, 657 320, 239 0 0 0 0
Cars +
Motorcycles
Gasoline 313, 804 304, 838 59, 227 1,016,901 57, 540 1,019,654
Metro-
rail
Metro Electricity 39, 256 212, 844 0 0 0 0
Trains 33, 594 26, 577 0 0 0 0
Total Urban Passenger 1,675,399 1,681,400 111, 974 1,904,662 99, 667 1,833,243
Total Urban Transport Emissions - - 119, 472 2,035,068 107, 164 1,963,649
Total Emissions from Transport Sector - - 229, 835 3,924,011 217, 527 3,852,592
Source: Logit (2009)
Table 35
investments targeted at improving the metro system.
Table 35: Avoided Emissions – Metro
Segment Mode Vehicle
Type Fuel
Gains from measure Accumulated gains from deployment
of low-carbon scenario
Absolute
% Baseline Absolute % Reference
Scenario
2030 2010-
2030 2030 2010-
2030 2030 2010-
2030 2030 2010-
2030
Urban
Passengers
Road Bus Diesel 9,702 62, 004 24.6 8.5 21, 613 217, 652 42.1 24.5
BRT 919 12, 168 6.9 7.8 -9070 -111, 174 -270.0 -343.4
Cars Ethanol 0 0 0.0 0.0 0 0 0.0 0.0
Cars +
Motorcycles
Gasoline 1,686 -2754 2.8 -0.3 8619 67, 360 13.0 6.2
Metro-
rail
Metro Electricity 0 0 0.0 0.0 0 0 0.0 0.0
Trains 0 0 0.0 0.0 0 0 0.0 0.0
Total Urban Passenger 12, 308 71, 418 11.0 3.7 21, 163 173, 838 17.5 8.7
Total Urban Transport Emissions 12, 308 71, 418 10.3 3.5 21, 163 173, 838 16.5 8.1
Source: Logit (2009)
Table 35A shows that joint introduction of BRT and metro would result in a total
annual CO2 emissions reduction between 2010 and 2030 from about 173 MtCO 2 e to
102 MtCO 2e, for the BRT and 71 MtCO 2e for the metro.
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Table 35A: Emissions avoided - Metro + BRT
Segment Mode Type
Vehicle Fuel
Gains Metro Gains BRT Total Gains
2030 2010-
2030 2030 2010-
2030 2030 2010-
2030
Urban
Passenger
Road Bus Diesel 9,702 62, 004 21, 613 155, 649 31, 315 217, 652
BRT 919 12, 168 -9,070 -123, 342 -8,151 -111, 174
Cars Ethanol 0 0 0 0 0 0
Cars +
Motorcycles
Gasoline 1,686 -2754 8,619 70, 114 10, 306 67, 360
Metro-
rail
Metro Electricity 0 0 0 0 0 0
Trains 0 0 0 0 0 0
Total Urban Passenger 12, 308 71, 418 21, 163 102, 420 33, 470 173, 838
Avoided Emissions Total Urban Transport 12, 308 71, 418 21, 163 102, 420 33, 470 173, 838
Source: Logit (2009)
With the addition of the metro in the low-carbon scenario, the passenger load in
conventional buses would decline further (from 44% to 21%), and the number of
passengers using private motor vehicles would also decline (from 43% to 37%). The
addition of BRTs alone would result in a marginally-reduced passenger load factor for
this transport mode: 30% to 28%, as illustrated in Figure 44:
Figure 44: Modal Distribution of loads - BRT + Metro
Source: Logit (2009)
The fuel economy resulting from the implementation of the BRT alone will be 28
million tons of oil equivalent by 2030, compared to the
Figure 45.
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Figure 45: Fuel consumption (TEP) - BRT + Metro
Source: Logit (2009)
Figure 46 shows the evolution of net emissions up to 2030 for the two low-carbon
scenario alternatives - investments in high-capacity public transport, with and
(representing a reduction of over 71 MtCO2e by 2030), resulting in increasing and
sustainable emissions reduction.
Figure 46: Evolution of emissions: BRT + Metro
Source: Logit (2009)
The net emissions reduction of 173 MtCO 2, between 2010 and 2030, was calculated
on the basis of a “full” low-carbon scenario (GMT + Metro). The modeling indicates that
it would be possible to build an additional 785 km of metro lines. This would require
following a similar Private Public Partnership (PPP) model adopted for the “Yellow
Line” in São Paulo.
As in the case of the abatement cost curves for regional transport, the urban
transport curves compare the additional investments needed for implementing a BRT/
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Metro network in a low-carbon scenario. The additional investments also include
the operation and maintenance costs of the new systems planned. The “avoided
investments” take into account the costs that would be incurred in the implementation
their substantial O&M costs.
As for “fuel consumption avoided”, we considered the amounts avoided by the
non-implementation of conventional bus systems. Furthermore, we estimated the
implementation of new mass transit systems congestion would be reduced. Private per
lower congestion.
operating costs, reduced trip times, reduced bus management costs, reduced pollution
and fewer accidents. As for pollution and accident reduction, the modeling was based
on values similar to those considered in the BRT projects scheduled for deployment in
Rio de Janeiro and Belo Horizonte.
The abatement costs for the combined BRT and Metro are presented below. In the
in mind the very high costs of implementing this particular option. The modeling also
took account of the possibility of introducing BRTs in a larger number of cities.
Figure 47: Cost Abatement Curves for BRT + Subway (nominalNominal)
Source: Logit (2009)
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Figure 48: Cost Abatement Curves for BRT + Subway (present value)
Source: Logit (2009)
Table 36: Average costs of avoided tCO 2 e – BRT
Abatement Curves US$ per tCO 2 e
Nominal Present Value in 2009
Low Carbon Investment 426.54 141.32
Avoided Investment 384.23 124.55
Fuel Economies 334.39 106.47
Operating Gains 155.23 54.81
0.24 10.20
Description of Policies for the BRT and Metro4.2.2
Various transport-related interventions are underway in the metropolitan regions
and municipalities. Since municipalities have autonomous control over their transport
The National Mobility Plan (PlanMob), under the aegis of the Ministry of Cities,
aims to encourage Brazilian municipal authorities to implement their Transport
Master Plans and to help them adopt appropriate policies and strategies in line with
their development programs, taking into account municipality size, social, economic,
cultural and environmental characteristics, as well as resource availability. The Master
Plans are considered mandatory for municipalities with over 500 inhabitants, and
essential for those with over 100,000.
Given that each municipality posseses autonomous control over the management of
of coordinating these policies at the central level. Incentives are needed to encourage
large- capacity passenger transport systems.
The policies outlined here are of an incremental nature, aimed at increasing
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the supply of good-quality public transport in the municipalities, and especially in
Brazil’s metropolitan regions, which contain the largest numbers of private vehicles in
circulation. Policies designed to enhance the supply of quality public transport can lead
to reduced private car use in the large cities.
Consideration could be given to establishing the new BRT-type systems (similar
circulation and as an alternative to private car transport. A key advantage is that BRT
involves lower investment costs in infrastructure and quicker deployment times.
and good quality public transport increases the prospects for increased demand and
modal shift (from private cars to rapid high-capacity public transport). The cities stand
given the smaller number of private vehicles in operation.
life of transport- users.
Municipal governments. Given the very substantial investments required, coordination
stock) etc. in the anticipation of successfully implementing new mass transit systems
Travel Demand Management4.2.3
The second group of mitigation measures proposed for the urban transport low-
carbon scenario aims at discouraging the use of private cars, while at the same time
encouraging the use of public transport systems. The main measures are to:
Prioritize bus systems in high-demand corridors; •
•
with timetables etc issued by operating bodies;
Design strategies to restrict the use of private cars; •
Integrate the various transport modes; •
Introduce tolls for private vehicles where good quality public transport •
Increase parking costs to reduce the number of cars in saturated areas; •
Integrate land-use and transport policies (to reduce trip-numbers and •
lengths).
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operation must be fully integrated with those that promote and enhance the quality of
public and mass transport systems and the rational use of motor cars.
situation in general in the metropolitan regions where, according to the Belo Horizonte
hour. It is well-known that fuel consumption and CO2 emissions are greatly reduced at
bring about substantial emissions reductions.
section 4.2.1, introducing high-performance public transport leads
demand. Thus, demand management strategies must ensure a balance between the
development of transport supply and demand in order to prevent emissions reverting
to former levels.
The set of mitigation strategies based on travel demand management must, in
addition to improving public transport systems, restricting private car use and
use and occupation. Curitiba, Bogotá, and other Latin American cities illustrate the
2 emissions that can result from integrated planning. But
and regulatory structures, as well as marketing and public outreach policies, must be in
place.
for managing the policies recommended for urban transport. The resources needed
will largely depend on where and how the policies will be implemented and the special
characteristics of each municipality involved. It was considered that the policies should
target only the densely-populated urban areas forming part of Brazil´s metropolitan
regions (similarity clusters 1-5). To apply the measures described, we assumed that
urban planning
agencies of the municipalities considered would be a reasonable amount for deploying
US$50 million.
We estimated emissions reductions and fuel economies by assuming that the
number and length of trips projected in the reference scenario would gradually reduce
year over year by about 3% up to 2030.
Table 38 presents possible emissions reductions on a year by year basis up to 2030,
as the result of urban transport demand management, assuming the implementation of
criteria described in this section. It can be seen that the gains arising from shorter and
2).
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Table 38: Gains from Demand Management in Brazil´s large cities
Year
Reference Scenario Savings
Loads
(million
pass x km)
Emissions
(thousand
tons CO 2 e)
% decrease in
number of trips
Loads
(million
pass x km)
Emissions
(thousand tons CO 2 e)
Number Length Year Accumulated
2010 940 337 70508.1 0.14 0.14 1706 141.4 141.4
2011 967 350 72307.6 0.28 0.28 3498 288.9 430.3
2012 995 186 74254.9 0.42 0.42 5381 442.4 872.7
2013 1023878 76258.7 0.56 0.56 7354 602.4 1475.2
2014 1053642 77522.3 0.70 0.71 9400 773.2 2248.4
2015 1084212 79279.9 0.84 0.85 11 552 949.9 3198.2
2016 1115712 81142.6 0.98 0.99 13,805 1134.0 4332.2
2017 1148250 83005.1 1.12 1.13 16 158 1327.2 5659.4
2018 1181816 84864.3 1.26 1.27 18 616 1529.8 7189.2
2019 1216444 86712.4 1.41 1.42 21 181 1742.9 8932.1
2020 1252180 88536.0 1.55 1.56 23 859 1966.4 10898.5
2021 1289063 90153.5 1.69 1.70 26 654 2198.6 13097.1
2022 1327128 91716.9 1.84 1.85 29 570 2438.6 15535.7
2023 1366421 93213.6 1.98 1.99 32 614 2691.6 18227.3
2024 1407112 94620.9 2.12 2.13 35 784 2959.0 21186.3
2025 1449143 95925.1 2.27 2.28 39 094 3238.6 24424.9
2026 1492556 97090.7 2.41 2.42 42 552 3535.2 27960.2
2027 1537409 98111.1 2.56 2.57 46 169 3842.6 31802.7
2028 1583827 98913.4 2.71 2.71 49 953 4171.2 35974.0
2029 1631805 99439.3 2.85 2.86 53 925 4522.3 40496.3
2030 1681400 99666.5 3.00 3.00 58 107 4888.4 45384.6
Source: Logit (2009)
Table 39A presents loads and direct emissions by type of vehicle in the baseline and
the low-carbon scenarios, with the inclusion of the mitigation measure “investments in
urban transport demand management”.
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Table 39A: Loads and emissions - Demand Management of Urban Transport - Baseline x
Low Carbon Scenarios
Segment Mode Type
Vehicle Fuel
Loads in 2030
(millions pax x km)
Emissions of CO 2
(thousand tons)
Baseline
in 2030
Low
Carbon
Baseline Low Carbon
2030 2010-
2030 2030 2010-
2030
Urban
Passenger
Road Bus Diesel 346, 281 331, 054 29, 696 670, 044 28, 390 658, 407
BRT 470,621 468, 454 12, 430 143,544 12,373 143, 082
Cars Ethanol 320, 239 301, 232 0 0 0 0
Cars+
Motorcycles
Gasoline 304, 838 286, 162 57, 540 1,019,654 54, 015 986, 369
Metro-
rail
Metro Electricity 212, 844 211, 262 0 0 0 0
Trains 26, 577 25, 129 0 0 0 0
Total Urban Passenger 1,681,400 1,623,293 99, 667 1,833,243 94, 778 178,7858
Total Urban Transport Emissions - - 107, 164 1,963,649 102, 276 1,918,264
Source: Logit (2009)
Table 39B shows the values of absolute and total emissions avoided.
Table 39B: Emissions avoided - Demand Management of Urban Transport - Baseline x
Low Carbon Scenarios
Segment Mode Vehicle
Type Fuel
Gains from measure Accumulated gains from deployment of
low-carbon scenario
Absolute
% Baseline Absolute % Reference
Scenario
2030 2010-
2030 2030 2010-
2030 2030 2010-
2030 2030 2010-
2030
Urban
Passengers
Road Bus Diesel 1,306 11, 637 4.4 1.7 22, 919 229, 290 44.7 25.8
BRT 57 462 0.5 0.3 -9,013 - 1 1 0 ,
712
-268.3 -342.0
Cars
Ethanol
0 0 0.0 0.0 0 0 0.0 0.0
Cars+
Motorcycles
Gasoline 3,525 33, 286 6.1 3.3 12, 145 100, 646 18.4 9.3
Total Urban Passenger 4,888 45, 385 4.9 2.5 26, 051 219, 223 21.6 10.9
Avoided Emissions Total Urban Transport 4,888 45, 385 4.6 2.3 26, 051 219, 223 20.3 10.3
Total Avoided Emissions from Transport Sector 4,888 45, 385 2.2 1.2 34, 849 293, 531 14.1 7.2
Source: Logit (2009)
The values established for the mitigation measures are incremental. Figure 49
for urban transport with the inclusion of the mitigation measure to encourage
implementation of the urban transport demand management measure, where the
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volume of emissions avoided between 2010 and 2030 will increase by 45.4 MtCO 2 e,
representing an overall increase of 2.5% in comparison with the baseline scenario.
Figure 49: Evolution of Emissions - Demand Management of Urban Transport: Baseline x
Low Carbon Scenario
Source: Logit (2009)
The following are the abatement cost curves relating to the demand management
strategies considered in this mitigation option. From these it can be seen that, although
the mitigation options presented.
Figure 50: Cost Reduction Curves (nominal)
Source: Logit (2009)
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Figure 51: Abatement Cost Curves (present value)
Source: Logit (2009)
Table 40 shows that the average cost per ton of CO2 indicators arising from this
mitigation measure are among the lowest. The indicator “Financial Cost of Tons of
CO2 Avoided”, which is based on the ratio between avoided emissions and the values
of investments required by the low-carbon scenario, less the avoided investment as
a result of the measure, is relatively low at US$23.14 per ton of CO2 avoided. Since no
investment is avoided, the “Financial Cost of Tons of CO2 Avoided” indicator is linked
directly to the curve of “investments required” by the low-carbon scenario. The
indicator of the “Final Cost of Tons of CO 2
abatement curve is negative, atUS$ (163.52) per ton of CO 2 e. This negative cost
result, the required investments are fully compensated - showing a credit of US$163.52
per ton of CO 2
amount of investment required.
Table 40: Average cost of avoided CO 2 and t
Abatement Curves US$ per tCO 2 e
Nominal Present Value in 2009
Low Carbon Investment 23.14 11.04
Fuel Economy -15.93 -1.85
Operating Gains -113.59 -34.06
-163.52 -50.53
Source: Logit (2009)
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The chart at Figure 52 shows the evolution on a year-on-year basis between the
accumulated investment values in US$ and the accumulated cost per ton of CO 2 avoided
as a result of the implementation of the mitigation measure. Note that the gains are
likely to be continuous and sustainable.
Figure 52: Cost per Ton Avoided X Investments Required by Urban Demand Management
(per annum up to 2030)
Source: Logit (2009)
with a reduction of operational costs, trip-times, pollution and accidents. For pollution
and accident reduction, the values of passenger loads proportionate to the mitigation
option were used in the modeling, involving the introduction of high-capacity public
transport systems.
4.2.3.1 Existing Policies
The operational and management streamlining of public transport should
contribute to reducing congestion, fuel consumption and pollutant emissions.
Given that each municipality has independent power to manage its own transport
and related systems the Ministry of Cities will need to coordinate adoption of the
strategies centrally. Incentives are required to encourage municipal authorities to
adopt policies aimed at improving operational and managerial performance in the
public transport sector in accordance with the PlanMob recommendations.
Brazil’s metropolitan areas concentrate the largest numbers private cars in
circulation. Policies that enhance the provision of good public transport should be
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encouraged and the use of private cars discouraged.
this second group are in line with the PlanMob. The measures suggested serve to
underpin future actions that could be implemented in a coordinated manner by the
The metropolitan regions would need special treatment, since transport problems
are most severe in these areas. Congestion is heavy during much of the day, causing
substantial waste of fossil fuels and increasing levels of local pollutants and GHGs.
supervision of their implementation is vital for achieving the hoped-for results within
The interventions presented individually in Group 2 call for coordination actions
which prioritize public transport and discourage the use of private motor vehicles. The
introduction of BRTs and the Metro (Group 1) needs to be coordinated by programs
designed to improve urban mobility and ensure a better quality of life for people living
in densely-populated cities.
Restrictions on the use of private transport, by increasing parking costs in
downtown areas can also be considered. Establishing parking lots on the outskirts of
cities, integrated into public transport corridors, is also recommended for reducing the
number of private cars in the most congested areas.
4.2.3.2 Political Economy Scenario
The proposals presented in this group of policies, considered to be more of a
structural nature, will depend on their acceptance by the community. Acceptance of
and maintenance costs generated by systems better able to satisfy present and
potential customer demand.
if the main goal of reducing
the number of vehicles in circulation in the cities, especially at peak times, is achieved,
possiblesolution would be for car manufacturers and their agents to encourage more
rapid vehicle sales turnover.
Thus, even if the use of private cars in terms of km operated per year is limited,
Union countries, where similar demand management strategies have been deployed
over the past twenty years.
This policy group, where managing demand for travel is prioritized as a means
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of reducing GHG emissions, also requires a coordinated approach by the different
institutional stakeholders involved.
In general, government policies need to be incorporated into the action agendas
of the state and city administrations. The need for greater public policy coordination
at the different levels of government is of particular importance in the transport
be fully addressed at all levels of government to ensure satisfactory results. At the same
time, it is vital to strengthen the appropriate administrative skills to ensure timely
deployment of policies and actions.
recommended.
arrangements.
Implementation of Bikeways4.2.4
environmental impacts and ensure more rational use of public spaces.
Encouraging bicycle use involves ensuring safe conditions. The construction of
interlinked bikeways in busy areas, integrating them with motorized public transport
facilities, can produce satisfactory results.
The cost of establishing bikeways in Brazil varies from US$25,000 to US $50,000
per kilometer depending on the type of lane. In cases where special bikeways are
per kilometer of construction was adopted, for bikeways and US$400 per year for
maintenance.
The concept of cycling and establishing bikeways
appeal in terms of swift and economical transport, preserving health, reducing
sponsors to underwrite a greater part of the investments required for establishing a
8400 km of bikeways throughout Brazil. We calculate that 400 km of bikeways could be
installed annually between 2010 and 2030.
We estimated the gains from cycling based on the potential for shifting loads from
motorized vehicles (cars, motorbikes, BRTs and conventional buses) to bicycles, based
on studies on the implementation of 400 km of bikeways in the city of Porto Alegre.
Table 41 shows the gains resulting from this measure, with the cost of an
avoided ton of CO2 evaluated in terms of nominal accumulated values, considering
the investments required and their respective operational and maintenance costs
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from motor vehicles increases, the cost indicator of an avoided ton of CO2 reduces
2 avoided in 2010,
decreasing to zero in 2030 (minus US$0.11 per ton of CO2 avoided). This means that
the investment required for establishing bikeways, plus the costs of operation and
maintenance, would be totally compensated by the fuel consumption savings. Between
2010 and 2030 a credit of US$ 0.11 for each ton of CO2 avoided would result.
Table 41 Bikeway Loads and Gains in
Avoided Emissions, 2010–30
Year
Load transfer
to bicycle (mil-
lions of pass
x km)
Avoided emis-
sions
(thousand tons
CO2/ year)
Cumulative value
(thousands of US$)
Costs of tons
of cumula-
tive avoided
CO2e per year
(US$/tCO2e)
Investment +
O&M Fuel savings
2010 88 6 14,160 136 2,229.91
2011 273 26 28,480 555 1,085.45
2012 563 66 42,960 1,418 630.88
2013 968 135 57,600 2,899 405.50
2014 1.497 242 72,400 5,187 277.56
2015 2.162 398 87,360 8,486 198.29
2016 2.973 613 102,480 13,014 145.98
2017 3.942 900 117,760 19,006 109.73
2018 5.083 1,273 133,200 26,714 83.66
2019 6.408 1,748 148,800 36,408 64.31
2020 7.932 2,341 164,560 48,375 49.62
2021 9.670 3,071 180,480 62,924 38.28
2022 11.501 3,941 196,560 80,188 29.53
2023 13.431 4,964 212,800 100,304 22.66
2024 15.464 6,151 229,200 123,402 17.20
2025 17.605 7,510 245,760 149,625 12.80
2026 19.857 9,059 262,480 179,119 9.20
2027 22.225 10,801 279,360 212,033 6.23
2028 24.715 12,756 296,400 248,513 3.75
2029 27.332 14,940 313,600 288,710 1.67
2030 30.080 17,360 330,960 332,784 -0.11
Note: This potential scenario includes the construction of 8,400 km of bikeways and related facilities.
Source: Logit (2009)
Table 41A below presents the results of the loads and direct emissions by type
of vehicle in the baseline and in the low-carbon scenario with the inclusion of the
mitigation measure for implementation of bikeways throughout Brazil.
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Table 41A: Loads and Emissions - Implementation of Bikeways - Baseline x Low Carbon
Scenarios
Segment Mode Type
Vehicle Fuel
Loads in 2030
(millions pax x km)
Emissions of CO 2
(thousand tons)
Baseline
in 2030
Low
Carbon
Baseline Low Carbon
2030 2010 –
2030 2030 2010 -
2030
Urban
Passengers
Road Bus Diesel 331, 054 308, 538 28, 390 658, 407 26, 460 644, 640
BRT 468, 454 465, 301 12, 373 143, 082 12, 289 142, 525
Cars Ethanol 301, 232 298, 973 0 0 0 0
Cars+
Motorcycles
Gasoline 286, 162 284, 011 54, 015 986, 369 53, 609 983, 332
Total Urban Passenger 1,623,293 1,593,213 94, 778 1,787,858 92, 358 1,770,498
Total Urban Transport Emissions - - 102, 276 1,918,264 99, 856 1,900,904
Total Emissions from Transport Sector - - 212, 639 3,807,208 210, 218 3,789,847
Source: Logit (2009)
Table 41B shows the values of absolute emissions avoided and their respective
percentage variations for the measure.
Table 41B: Avoided Emissions - Implementation of Bikeways
Segment Mode Vehicle
type Fuel
Gains from the Measure Accumulated gains from deployment
of low-carbon scenario
Absolute
% baseline Absolute % reference
scenario
2030 2010-
2030 2030 2010-
2030 2030 2010-
2030 2030 2010-
2030
Urban
Passengers
Road Bus Diesel 1,931 13, 767 6.8 2.1 24, 850 243, 056 48.4 27.4
BRT 83 557 0.7 0.4 -8,929 -110, 155 -265.8 -340.3
Cars Ethanol 0 0 0.0 0.0 0 0 0.0 0.0
Cars+
Motorcycles
Gasoline 406 3,036 0.8 0.3 12, 551 103, 682 19.0 9.5
Total Urban Passenger 2,420 1 7 ,
360
2.6 1.0 28, 471 236, 584 23.6 11.8
Total Urban Transport Emissions 2,420 17,360 2.4 0.9 28, 471 236, 584 22.2 11.1
Source: Logit (2009)
The values of the mitigation measures are incremental. Figure 53 illustrates in
aggregated low-carbon scenario emissions for urban
transport with the inclusion of the bikeway mitigation measure. The avoided emissions
between 2010 and 2030 would increase by 17.4 MtCO 2 e, representing a 2.6% increase
from the baseline.
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Figure 53: Evolution of Emissions - Implementation of Bikeways: Baseline x Low Carbon
Scenario
Source: Logit (2009)
The following are the abatement cost curves related to the implementation of
parallel with the cost curves for the demand management
abatement mitigation measure (Figures 50 and 51) . In this case it is clear that the
compared with the other mitigation options presented.
Figure 54: Cost Abatement Curves ( nominal)
Source: Logit (2009)
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Figure 55: Cost Abatement Curves (present value)
Source: Logit (2009)
Table 42: Average Cost of Tons of CO 2 Avoided
Abatement Curves US $ per tCO 2 e
Nominal Present Value in 2009
Low Carbon Investment 19.58 7.04
Fuel Economy 0.41 1.21
Operating Gains -47.51 -13.36
-70.66 -20.30
Source: Logit (2009)
4.2.4.1 Existing Policies
The Ministry of Cities, through Secretariat of Mobility (SeMob), has issued a reference
Bicicleta Brasil’) which underscores
the Ministry’s philosophy of “Sustainable Urban Mobility”. Although this policy is not
attempt to encourage more frequent bicycle use.
The general thrust of this document is that bicycles should be integrated with other
forms of public transport to generate fewer environmental impacts and make more rational
use of public spaces.
In addition to the recommendations for bikeways, the PlanMob booklet contains a set
of proposals for upgrading pedestrian safety in urban areas, emphasizing the need for local
authorities to include pedestrian concerns in their transport and urban-planning agendas.
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4.2.4.2 Description of Policies
Encouraging bicycle use involves ensuring safe conditions. Integrating a safe
transport policies and systems can enhance the overall urban landscape and avoid
2 emissions.
These policies can be applied incrementally. Brazil´s largest cities in general do
not possess a cycling culture. Some cities have however begun to establish bikeways
without reference to the municipal Master Plans. Some are isolated initiatives which
(in general those with under 50,000 inhabitants), bicycle use is more frequent. Given
that the distances travelled are normally less than 5 km, cycling is part of local culture
and contributes to environmental conservation.
4.2.4.3 Political Economy Scenario
This scenario is basically one of gains, since the use of non-motorized transport
contributes to local sustainability and encourages revitalization of urban areas, in
sidewalks, street furniture (shelters, benches etc) and other amenities. All of these
initiatives serve to encourage enhanced use of cycling and walking, as well as reducing
atmospheric emissions.
The increased use of non-motorized transport in urban areas requires a coordinated
approach by the three government levels.
A further point is that cycling in particular has won the support of private-sector
tune with environmental causes. A number of projects have been sponsored in Brazil
similar to those in other countries, where bicycles can be hired at strategic points. By
sponsoring these initiatives, investors have perceived good opportunities for pursuing
Low-carbon Scenario for Ethanol - Increasing Proportion 4.3
of Ethanol Consumption by “Flex-Fuel” vehicles
Energy issues are considered as strategic concerns for the majority of countries,
particularly since the Industrial Revolution - when manufacturing, economic
development and a good supply of energy (coal and wood) were crucially interlinked.
Over the years, oil products and oil-powered machines have played an increasing
role in technological development. The demand for oil and derivatives has grown
dependent on them, with oil production highly concentrated in the Middle East.
Serious economic problems were caused in the main oil consuming countries by
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to lessen vulnerability to energy shortages, the Brazilian government established the
National Alcohol Program (Proálcool) in 1975.
Fuel distribution problems led to a shift in Brazilian energy policy which created a
fall in ethanol production. One problem was that attractive prices for sugar in the
international market meant that much of the sugarcane produced in Brazil began to
was undermined, followed by a substantial decline in the production of ethanol-fueled
vehicles.
alcohol and gasoline (E85).
Meanwhile in Brazil, the automotive industry chose to invest in the creation of
engines which could use either hydrated alcohol ( E100) or gasoline (E22) or any
combination of both, automatically adapting to either or both fuels with no need for
driver adjustments.
mitigating supply and price risks for customers.
around 89% of total car sales.
Figure 56 - Evolution of Light Vehicle Sales by Fuel Type (1979-2007)
Source: ANFAVEA / Logit (2009)
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Parameters for the Low-carbon Scenario4.3.1
determines the level of pollutant emissions reductions in the low-carbon scenario for
bio-ethanol. Two main parameters determine the substitution of gasoline by ethanol as
4.3.1.1 Assessing the Size of the Flex- Fuel Fleet
For both the reference and low-carbon scenarios, projections were made of the sales
of light vehicles according to type of fuel used, based on ANFAVEA statistics, correlated
with GDP and population growth (as estimated in the PNE-2030).
We also applied the Winfrey-3 Curve (for phasing out older vehicles) for the current
Table 43 - Light Passenger Vehicle Fleet ( by Type of Fuel )
Reference Year
Flex Ethanol Gasoline
2010 29% 6% 65%
2011 32% 6% 62%
2012 35% 6% 60%
2013 37% 5% 58%
2014 40% 5% 55%
2015 43% 5% 53%
2016 46% 4% 50%
2017 48% 4% 48%
2018 51% 4% 45%
2019 54% 4% 42%
2020 57% 3% 39%
2021 61% 3% 37%
2022 64% 3% 34%
2023 67% 2% 31%
2024 70% 2% 28%
2025 74% 2% 25%
2026 77% 2% 21%
2027 81% 1% 18%
2028 84% 1% 15%
2029 88% 1% 11%
2030 92% 1% 8%
Source: ANFAVEA / PNE-2030 / Logit (2009)
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4.3.1.2 Proportion of Consumption Ethanol / Gasoline by “Flex-fuel” Fleet
consumption of bio-ethanol and gasoline in the transport sector (oil equivalent), which
for ethanol and 47% for gasoline by 2030. Given that gasoline will be gradually replaced
by ethanol, substantial CO2 emissions savings will result even in the reference scenario.
the main fuel.
According to Brazil’s National Petroleum,
Natural Gas and Bio-fuels Agency (ANP), ethanol was more attractive (in 2009) than
gasoline for customers in 17 states, less attractive in 5 states, and equivalent in another
5. The main advantage of gasoline over ethanol is the higher per liter energy content of
gasoline (70%).
Table 44
taking account of the fact that this fuel is more attractive to customers when its price is
less than 70% of that of gasoline.
Table 44 - States were Alcohol Prices were Competitive with Gasoline Prices (April 2009)
State Ethanol price versus
Gasoline price
São Paulo 53.47%
Mato Grosso 56.35%
Paraná 56.81%
Bahia 60.59%
61.78%
Mato Grosso do Sul 62.62%
Alagoas 62.73%
Source: ANP / Logit (2009)
Gasoline prices were more attractive mainly in the states of Roraima (where the
fuels were equivalent.
The distribution cost of alcohol is a key factor, given that large amounts of sugarcane
are required for the process, and that alcohol-processing plants normally need to be
installed near plantations for logistical reasons. Without doubt the price of ethanol for
price of gasoline than in other areas of the country. The seven most “competitive” states
(Table 44 above) account for 70% of all alcohol consumption in the country (ANP
(CONAB-2008 ).
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from region to region, depending on a range of factors. In order to ensure that ethanol
is competitive compared to gasoline, the price of which is also subject to many
uncertainties, a sensible national fuel-pricing policy needs to be established, targeted
at encouraging ethanol consumption to replace gasoline.
envisaged that the ratio of alcohol to gasoline consumption
be on average 60% - 40%. This parameter, which we believe is credible and observable
in practice, produces numbers which are consistent with the forecast contained in the
PNE 2030.
For the low-carbon scenario proposed here (the outcome of the above-mentioned
“sensible national policy on fuel prices”), this fuel consumption ratio over the years will
by 2030 – resulting in considerable emissions reductions.
Figure 57: Consumption Ethanol x Gasoline for Vehicle Fleet
(Total and “Flex-Fuel”)
Source: Logit (2009)
In the low-carbon scenario the increased domestic consumption of ethanol will
for this fuel. We considered in our analysis of abatement costs (“avoided investments”)
that the required investments for implementing the ethanol mitigation measure will
Gains in terms of emissions reductions4.3.2
Table 45 presents data on avoided emissions: total avoided emissions in the
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policy. Note that the cumulative emissions avoided using the “Low Carbon Ethanol”
measure in the 2010-2030 period over the total emissions avoided in the transport
Table 45: Avoided Emissions - Low Carbon Ethanol
Transport /
Segment Vehicle Type
Gains from applying the measure Gains by applying low-carbon scenario
Absolute % Baseline Absolute % Reference Scenario
2030 2010-
2030
2030 2010-
2030
2030 2010-
2030
2030 2010-
2030
Cars and
motorcycles
26, 350 161, 718 49.2 16.4 38, 901 265, 400 58.8 24.4
Total Urban
Passenger
26, 350 161, 718 28.5 9.1 54, 821 398, 302 45.4 19.8
Total Urban
Transport
26, 350 161, 718 26.4 8.5 54, 821 398, 302 42.7 18.6
Cars and
Motorcycles
2,363 14, 148 49.2 15.9 2,783 19, 888 53.2 21
Regional
Passenger Total
2363 14, 148 6.9 2.7 4,511 37, 469 12.4 6.9
Total Regional
Transport
2,363 14, 148 2.1 0.7 11, 161 88, 456 9.4 4.5
Total Transport
Sector
28, 712 175, 866 13.7 4.6 65, 982 486, 757 26.7 11.9
Source: Logit (2009)
Figure 58 illustrates the evolution of emissions by vehicle-type in the reference
scenario, the low-carbon scenario without
carbon scenario for the transport sector, which incorporates the low-carbon ethanol
substantial and, regardless of the fact that it is included in the “cars and motorbikes”
category, it promises the highest potential for emissions reduction of all the low-carbon
measures proposed in the present study: a 13.7% gain in comparison with its baseline.
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Figure 58: Emissions: With and Without the Effects of the Ethanol Measure
Source: Logit (2009)
The comparison for cars and motorcycles of this
Table 46 below, gives
pricing policy recommended for encouraging the use of ethanol: in urban areas, in
the baseline scenario, the proportion of the ethanol passenger load will be 51% (299
the low-carbon scenario, this would be a
regional
Table 46: Charging and Emissions, Ethanol - Baseline x Low Carbon
Segment Mode Vehicle
Type Fuel
Loading million
passengers x km
CO 2
thousand tons
Baseline Low-
Carbon
Baseline Low Carbon
2030 2010-
2030 2030 2010-
2030
Urban
Passenger
Road Cars Ethanol 298, 973 446, 579 0 0 0 0
Cars +
Motorcycles
Gasoline 284, 011 136, 404 53, 609 983, 332 27, 259 821, 614
Total Urban
Passenger
1,593,213 1,593,213 92 ,358 1,770,498 66, 008 1,608,780
Total Urban
Transport Emissions
- - 99, 856 1,900,904 73, 506 1,739,186
Regional
Passenger
Road Cars Ethanol 162,280 213, 720 0 0 0 0
Cars + Mo-
torcycles
Gasoline 89, 221 37, 781 4,807 89, 066 2,444 74, 919
Regional
Passenger Total
660, 909 660, 909 34, 359 521, 148 31, 997 507, 000
Total Emissions Regional Transport - - 110, 363 1,888,943 108, 000 1,874,795
Total Emissions from Transport Sector - - 210, 218 3,789,847 181, 506 3,613,981
Source: Logit (2009)
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Figure 59 compares the evolution of regional and urban aggregated passenger
loads with and without the ethanol low-carbon measure. Note the effects of this
measure on the modal split between private vehicles by fuel-type.
Figure 59: Loading With and Without the Effect of Low Carbon Ethanol Measure
Source: Logit (2009)
“Investments Required” Abatement Curve4.3.3
The required investments for implementing this measure will be the cost of the non-
the “ avoided investments” in the abatement cost analysis.
The production costs of ethanol and gasoline used for the economic were the
same as those calculated in the sub-themes “Ethanol” and “Cogeneration”, where the
values are similar in the baseline year, and where the cost of a barrel of ethanol (for
equivalency purposes) will gradually fall until it reaches around 61% of the cost of a
barrel of gasoline in 2030.
Table 47
and avoided” investments, and the values of tCO2 avoided. Note that the present value of
the total cost of a tCO2
for the mitigation measures presented here.
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Table 47: Investments and Costs of Avoided Tons of CO2
Year
000 barrels
Avoided
Emissions
in tons
of CO 2
Investments in US$ millions Cost per ton
of CO 2 avoided
(US $ / tCO 2 e)
Ethanol
not
Gasoline
Required Avoided Net
Nominal
Present
value
(2009)
Nominal
Present
value
(2009)
Nominal
Present
value
(2009)
Nominal
Present
value
(2009)
2010 1,612 1,100 293 71 66 49 46 22 20 73.68 68.22
2011 2,789 1,903 507 121 165 95 124 26 41 52.16 81.23
2012 4,914 3,353 893 211 320 171 250 40 70 44.33 77.87
2013 7,324 4,997 1,331 308 523 261 424 47 99 35.58 74.53
2014 6,348 4,332 1,153 261 662 231 549 30 113 26.34 97.54
2015 8,138 5,553 1,479 327 819 302 699 25 120 16.65 80.94
2016 10, 825 7,387 1,967 429 1,009 410 886 20 122 9.92 62.13
2017 14, 149 9,654 2,571 552 1,232 536 1,110 16 122 6.39 47.47
2018 18, 028 12, 301 3,276 692 1,487 683 1,369 9 117 2.68 35.84
2019 22, 473 15, 334 4,083 845 1,768 851 1,662 -6 106 -1.47 25.94
2020 27, 655 18, 870 5,025 1,018 2,074 943 1,943 75 130 14.93 25.92
2021 33, 588 22, 919 6,103 1,211 2,401 1,145 2,254 67 147 10.93 24.10
2022 40, 427 27, 585 7,345 1,426 2,748 1,378 2,594 48 154 6.58 20.96
2023 48, 201 32, 890 8,758 1,661 3,110 1,643 2,961 18 149 2.07 16.98
2024 57, 391 39, 160 10, 428 1,930 3,488 1,956 3,358 -26 129 -2.53 12.41
2025 69, 848 47, 660 12, 691 2,290 3,898 2,381 3,804 -91 93 -7.15 7.35
2026 83, 764 57,155 15, 220 2,707 4,340 2,855 4,294 -148 46 -9.74 3.04
2027 99, 313 67, 765 18, 045 3,162 4,810 3,385 4,823 -223 -13 -12.36 -0.72
2028 116, 800 79, 697 21, 222 3,663 5303 3,981 5,388 -318 -86 -15.00 -4.04
2029 136, 299 93, 002 24, 765 4,208 5813 4,645 5,986 -437 -173 -17.65 -6.99
2030 158, 023 107, 825 28, 712 4,804 6336 5,386 6,612 -582 -276 -20.28 -9.61
Total 967, 908 660, 441 175, 866 31, 896 52, 368 33, 285 51, 137 -1,389 1,231 -7.90 7.00
Barriers and measures to overcome them4.3.4
portray the various fuel-substitution processes:
Stage 1 -
shock, the government readjusted the price of diesel downward (to less than gasoline).
Between 1973 and 1977 the price of the latter increased 107% and that of diesel 34%,
resulting in a shift to diesel.
Stage 2 - Gasoline versus alcohol: after the second oil shock, priority was given to
reducing dependence on oil and substituting it for alcohol - development of which had
already commenced with the establishment of the government´s Pro-Alcohol program
85% of all vehicles produced in Brazil were dependent on alcohol. However, when oil
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In this scenario alcohol production failed to keep up with demand, resulting in a serious
shortage by 1989/1990.
Stage 3 - Alcohol versus gasoline: attractive prices in the international sugar
market, plus the low alcohol prices at the pumps caused much of the cane producers to
concentrate on sugar production, leading to a shortage of cane for alcohol production.
With the decline in alcohol production, gasoline recovered its position in the fuels
market.
Stage 4 - Gasoline versus alcohol versus GNV (natural gas for vehicles): in the period
1998-2004, the GNV
Sales of GNV increased by 61% per annum, amounting by 2004 to 4.3 million m3/day
In the main markets for •GNVGNV was lower than
that on other fuels;
•
vehicules) on GNV were less than for alcohol;
In São Paulo, ICMS and IPVA were identical (since 2003) for •GNV and
alcohol.
Given the current problems of natural gas supply in Brazil the GNV market has
alcohol.
4.3.4.1 Establishment of a Fuels Policy
In order to ensure the success of the ethanol mitigation measure proposed here,
economy needs to be established. It is important that this policy guarantees a stable
environment for investment and provides assurance to fuel consumers.
shown that four policy instruments can be used to sustain the attractiveness of ethanol
for car end-users:
Financial incentives •
purchase;
Regulatory standards •: mandatory minimum level of renewable fuels to be
Taxation •
R&D •
This policy should be framed on the basis of the following requirements:
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to avoid programs requiring either •ad hoc or permanent subsidies;
•
to ensure program sustainability; •
to provide support for R&D with a view to ensuring a competitive environment •
for renewable fuels, to enhance the comparative advantages of Brazil and to
to ensure transparency in the Derivatives Pricing Policy: e.g. to avoid •
to ensure integrated planning by creating a National Automotive Fuels Plan, •
with achievable targets and clear supply-and-demand fuel scenarios in order
to minimize incompatibilities and resource wastage.
A National Fuels Policy should be based on the following principles (in line with
Art. 1 of Petroleum Law 9.478/97):
to preserve the national interest; •
•
resources;
to protect consumer interests with regard to prices, quality and availability •
of automotive fuels;
to protect the environment and promote energy conservation; •
to ensure supplies of petroleum products throughout the national territory; •
to increase the use of natural gas on an economic basis; •
to identify the most appropriate solutions for supplying automotive fuel in •
the various regions of the country;
to use alternative energy sources by the economic use of available inputs and •
applicable technologies,
to promote free competition; •
to attract investment in fuels production ; •
•
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Consolidated Results4.4
Tables 48 and 49 contain the main emissions indicators for the reference and the
Two measures for regional transport: •deployment of investments to promote
a new modal distribution for freight transport, by increasing the share of
lower-emission transport modes and introduce a high-speed train service in
the Rio de Janeiro-São Paulo corridor ;
Three measures for urban transport: deployment of high-capacity public •
systems, establishment of an urban transport demand management system
and the establishment of bikeways; and
One measure to impact regional and urban passenger transport: the •
vehicles.
Table 48: Fuel Consumption Trends in the Reference and Low-Carbon Scenarios
Scenario
Fuel Type
2010-
2015
2016-
2020
2021-
2025
2026-
2030
Total
Reference
Scenario
Ethanol (million m 3) 89.14 120.91 188.90 295.13 694.07
Gasoline (million m 3) 158.52 137.79 132.66 106.36 535.32
Diesel (million m 3) 245.45 228.83 249.21 270.25 993.74
Aviation fuel (million m 3) 26.14 26.98 33.59 42.25 128.97
Electricity (GWh) 11.30 14.18 18.77 25.13 69.38
Low-carbon
scenario
Ethanol l (million m 3) 88.97 114.54 166.62 232.79 602.92
Gasoline (million m 3) 166.54 158.25 178.36 202.52 705.67
Diesel (million m 3) 249.43 240.31 273.52 312.24 1075.51
Aviation fuel (million m 3) 26.29 27.59 34.46 43.37 131.71
Electricity (GWh) 9.45 8.78 9.71 10.75 38.70
% Change Scenario:
Reference Scenario
Ethanol 0.18 5.56 13.37 26.78 15.12
Gasoline -4.82 -12.93 -25.62 -47.48 -24.14
Diesel -1.60 -4.78 -8.89 -13.45 -7.60
Aviation Fuel -0.56 -2.22 -2.52 -2.58 -2.08
Electricity 19.51 61.47 93.30 133.81 79.30
Source: Logit (2009)
The consumption patterns of the various types of fuels in the low-carbon scenario
compared to the reference scenario, illustrated in Table 48
mitigation measures proposed:
the gradual increase in ethanol consumption, compared to a gradual •
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decreased diesel consumption due to the mitigation measures covering •
the modal shift recommended for regional freight transport and the
implementation of high-capacity transport systems in Brazilian cities;
the reduction in aviation fuel consumption will be due to passengers •
transferring from planes to the high-speed train (TAV) in the Rio de Janeiro-
São Paulo corridor; and
•
shift for regional freight transport, the implementation of high-capacity
public transport systems in the cities and the introduction the TAV.
Table 49: Evolution of Direct Emissions (in MtCO2) in the Reference and Low Carbon
Scenarios
Scenario Period
Urban Transport Regional Transport Grand
Total
Road Rail Total Road Rail Water Pipeline Air Total
Reference
Scenario
2010-2015 496.64 0.00 496.6 367.76 28.02 1.56 0.37 64.68 462.4 959.0
2016-2020 481.07 0.00 481.1 345.55 25.79 1.74 0.33 67.87 441.3 922.4
2021-2025 546.11 0.00 546.1 380.89 27.87 2.18 0.35 84.77 496.1 1,042.2
2026-2030 613.67 0.00 613.7 423.17 30.77 2.50 0.38 106.69 563.5 1,177.2
Total 2,137.5 0.0 2,137.5 1,517.4 112.5 8.0 1.4 324.0 1,963.3 4,100.7
Low-Carbon
Scenario
2010-2015 472.89 0.00 472.9 364.44 31.32 2.05 0.39 64.32 462.5 935.4
2016-2020 428.89 0.00 428.9 328.37 31.73 2.71 0.36 66.36 429.5 858.4
2021-2025 438.12 0.00 438.1 343.29 36.85 3.72 0.39 82.64 466.9 905.0
2026-2030 399.29 0.00 399.3 366.42 40.80 4.27 0.43 103.94 515.8 915.1
Total 1,739.2 0.0 1,739.2 1,402.5 140.7 12.7 1.6 317.3 1,874.8 3,614.0
Avoided
emissions
2010-2015 23.75 0.00 23.7 3.32 -3.30 -0.50 -0.02 0.36 -0.1 23.6
2016-2020 52.18 0.00 52.2 17.18 -5.94 -0.97 -0.03 1.51 11.7 63.9
2021-2025 107.99 0.00 108.0 37.61 -8.98 -1.53 -0.04 2.13 29.2 137.2
2026-2030 214.38 0.00 214.4 56.75 -10.02 -1.77 -0.05 2.75 47.7 262.0
Total 398.3 0.0 398.3 114.9 -28.2 -4.8 -0.1 6.8 88.5 486.8
Source: Logit (2009)
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Figure 60: Emission and Mitigation of Urban and Regional Transport 2010 through 2030.
Table 49 presents the emissions by mode and geographical situation in both the
Reference and Low Carbon Scenarios. Figure 60 presents these same emission values
by state.
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Figure 61: Growth in Transport Fleet, 2007 to 2030
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Figure 62: Changes in Passenger Load
The low-carbon scenario for the transport sector is built by combining the
mitigation options proposed for regional and urban transport. Emission reductions are
achieved by shifting part of the freight load and passenger trips from carbon-intensive
to low- or zero-carbon transport modes (Figures 61 and 62
modal shifts are from truck to rail (freight transport) and from use of private vehicles
to BRT and Metro, along with measures for travel demand management (passenger
transport).
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Figure 63: Comparison of Modal Distribution of Freight Load, 2008–30
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Figure 64: Comparison of Modal Distribution of Passenger Load, 2008–30
percent over the study period or 302 Mt CO2
potential of around 4.3 percent could be harvested over the same period by increasing
the use of ethanol, and another 1.5 percent by managing the demand for trips (Figure
65). In this way, emissions would be reduced more than 13 percent.
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Figure 65: Emissions-reduction Potential in the Transport Sector, 2008–30
As result, the increase in sector emissions would be reduced from 60 percent in
the reference scenario to only 18% in the low-carbon scenario. That is, from 247 in
the reference scenario to 182 Mt CO2 per year in the low-carbon scenario in 2030,
compared to 154 Mt CO2 in 2010, thereby avoiding a total of 487Mt CO2e, or 23 Mt CO2e
per year on average (Table 49).
The potential for emissions reduction appears limited, given that biofuels, which
are low carbon, play a large role in the reference scenario. For this reason, the study
simulated the sector emissions that would result if biofuels were substituted by fossil
50 percent in 2030 (45 percent in cumulative terms over the 2010–30 period), growing
from 143 Mt CO2 in 2008 to 371 Mt CO2 per year in 2030. By comparison, emissions in
the low-carbon scenario would be 51 percent lower in 2030 than in the “fossil-fuel”
scenario (26% lower versus the reference scenario) (Figure 66) and 39 percent in
cumulative terms over the 2010-30 period, that is 1.65 Gt CO2e less over the study
period.
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Table 50: Transport-sector Load and GHG Emissions in the Reference
and Low-carbon Scenario
Load (Mt CO2e)
(Mt * km or pass * km/year)
Load type Transport mode Vehicle type Fuel type Reference scenario
2030 Low- carbon
scenario 2030
Reference
scenario
2030
Low- carbon
scenario 2030 Avoided emissions
2010–2030
Urban
freight
Road Truck Diesel 49,151 49,151 7.6 7.6 0.0
Total urban freight 49,151 49,151 7.6 7.6 0.0
Urban
passengers
Road
Bus
Diesel
730,799 308,538 43.1 17.5 215.5
BRT 102,332 465,301 2.1 9.6 -72.3
Car Ethanol 364,894 446,579 - - 0
Car and
motorbike Gasoline 347,346 136,404 66.16 27.26 265.4
Rail
Metro
Electricity
55,385 211,262 0.0 0.0 0.0
Train 50,699 25,129 0.0 0.0 0.0
Total urban passengers 1,651,455 1,593,213 111.42 54.59 408.6
GHG emissions from urban transport - 119.01 62.18 408.6
Regional
reight
Rail Train Diesel 552,364 703,854 6.6 8.3 -25.4
Waterway Boat 81,349 133,503 0.5 0.9 -4.5
Pipeline Pipeline 24,727 26,621 0.1 0.1 -0.1
Road Truck 1,274,440 1,113,926 77.3 65.6 115.1
Total freight 1,932,880 1,977,904 84.5 74.9 85.1
Regional
passengers
Road
Car Ethanol 176,485 213,72 0.0 0.0 0
Car and motorbike Gasoline 97,031 37,781 5.23 2.44 19.9
Bus Diesel 276,915 266,675 7.3 6.8 2.9
Air Plane Aviation
kerosene 127,569 121,641 28.7 28.0 8.3
Train TAV Eletricity - 21,092 0.0 0.0 0
Total regional passenger 678,001 660,909 41.23 37.25 31.0
GHG Emissions from regional transport - 125.76 112.12 116.0
TOTAL TRANSPORT-SECTOR EMISSIONS 244.77 174.29 524.6
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Figure 66: Comparison of Emissions in Reference, Low-carbon, and “Fossil-fuel”
Scenarios, 2008–30
Implementing the proposed low-carbon scenario triggers two main challenges:
spectrum of public and private actors involved, harmonization of the many diverse
initiatives represented requires federal government coordination. Furthermore,
infrastructure.
Improved coordination is needed for both urban and regional transport. For
transport systems, incentives to adhere to broader mass-transport plans under the
National Mobility Plan (PlanMob). For regional transport, the Ministry of Transport
(MT), under the PNLT, could facilitate the integrated development of new infrastructure
and transport-services concessions.
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General Conclusions5
freight and passengers, fuel consumption and emissions.
This approach requires a set of data and information that is often unavailable.
estimates when performed in a consistent manner.
With regard to institutional issues, there is an urgent and real need for greater
integration between Federal, State and Municipal agencies. Notwithstanding
integration, the formal structure of the transport sector complicates coordinated
modes.
greater detail each mode of transport to avoid possible distortions in projections.
much larger volume of vehicles in cities generates substantially more localized
assess regional transport conditions. The need for modal integration in the regional
freight sector is crucial. Measures to ensure adequate logistics, and operational and
technological up-scaling will undoubtedly contribute to reducing energy consumption
and emissions in this sector.
The high infrastructure-building costs at both the urban and regional levels add
Federal, State and Municipal budgets make it necessary to seek international and
private-sector funding. In this respect, the introduction of PPPs and concessions
awarded to private highway-operators have contributed to increasing the volume of
investments in the sector.
agencies, management agencies and operators involved, highlight the pressing need to
component inherent in this sector. A rationally-organized functioning transport
system can contribute much to the economic and social development of the country,
promoting citizenship and ensuring a better quality of life for all, whilte at the same
time preserving and enhancing the regional and urban environment.
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Bibliography:
Cervero, R. (1998) The Transit Metropolis. Island Press, Washington, D.C..
Cervero, R. (2005) Accessible Cities and Regions: A Framework for Sustainable
Transport and Urbanism in the 21st Century. Working Paper UCB-ITS–VWP–
2005-3, UC Berkeley Center for Future Urban Transport.
Cherry, C. (2005) China’s Urban Transportation System: Issues and Policies Facing
Cities. Working Paper UCB-ITS–VWP– 2005-4, UC Berkeley Center for Future
Urban Transport.
IPCC (1996) Greenhouse Gas Inventory Reporting Instructions – IPCC Guidelines for
National Greenhouse Gas Inventories. Vol 1, 2, 3. Intergovernmental Panel on
Climate Change, United Nations Environment Program, The OECD and the
International Energy Agency, London.
MCT (1999) Relatório das Emissões de Carbono Derivadas do Sistema Energético:
MME (2005) Balanço Energético Nacional - 2005. Ministério das Minas e Energia,
de Transportes, Ministério dos Transportes.
Ribeiro, S.K., Kobayashi, S., Beuthe, M., Gasca, J., Greene, D., Lee, D.S., Muromachi,
Y.,Newton, P.J., Plotkin, S., Sperling, D., Wit, R., Zhou, P.J. (2007) Transport and its
infrastructure. In Climate change 2007: Mitigation, Contribution of Working Group III
to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change [B.
Metz, O.R. Davidson, P.R. Bosch, R. Dave, L.A. Meyer (eds)],
Cambridge University Press, Cambridge, United Kingdom and New York, NY,
USA.
Ribeiro, S.K., Balassiano, R. (1997) CO2 Emissions from Passenger Transport in Rio
de Janeiro. Transport Policy, Vol. 4, No. 2, April, pp.135-139.
Wilson, D., Purushothaman, R. (2003) Dreaming with BRICs: the Path to 2050.
Global
Economics Paper No: 99, Goldman Sachs.
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