03 - Relatório geral de mobilidade urbana 2006

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03 - Relatório geral de mobilidade urbana 2006

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Relatório 2008 - Sumário Executivo

Relatório Geral 2008

Comparativo 03/08

2006 English Summary Report

Dados atuais sobre:

Maiores cidades - Dados de 2008

Custos para usar ônibus, moto e automóvel (dados de 03/10)

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Tarifas de transporte - histórico

Metodologia

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Fórum geral

Análise de dados sobre transporte e trânsito brasileiros coletados em 2006

. English Summary

1. Characteristics of the cities included in the MDS (1)

(1) Prepared by Eduardo A Vasconcellos

ANTP’s mobility data system (MDS) encompasses 438 cities over 60,000 inhabitants which existed in Brazil in 2003. Table 1 summarizes some data for these cities. It may be seen that together they represent 60% of the country’s urban population, 70% of the vehicle fleet and 72% of the GNP, which means the system covers the majority of urban trips in Brazil and is a synthesis of the most pressing and relevant urban transport problems in the country.

Indicator	Value	% of all cities
No. of cities	438	9
Population (million)	115	61
Vehicle fleet¹ (million)	21	66
GRP² (trillion R$³)	1.5	72

Table 1 - Main social and economic characteristics of MDS cities (over 60,000 inhabitants)

1 – Automobiles, buses, trucks and motorcycles;

2 – Gross local economic product.

3 – The exchange rate of the US Dollar to the Brazilian Real in December 2005 was 1: 2.3.

2. Mobility

Data on trips made on MDS cities are summarized on Table 2 and Figures 1 and 2. All data are classified according to the prevailing transport modes – from subway and railway as being the "heaviest" to walking as being the "lightest". This means that a combined bus-subway trip is classified as a subway trip and a combined walking-bus trip is classified as a bus trip.

Table 2 shows that 53 billion trips are made per year. Figure 1 shows that non-motorized trips are the dominant form of travel, with 42% of total trips. The share of public transport trips is equal to that of trips on motorized private means.

Trips	Motorized transport		Non-motorized transport		Total	NNT/MT
Trips	Public	Private	Bycicle	Walking	Total	NNT/MT
Billion trips/year	15.6	15.8	1.4	20.6	53.5	0.70
% of total	29.1	29.6	2.7	38.6	100

Table 2 - Modal split per major transport mode, 2006

Figure 1 - Brazil, modal share in cities with more than 60,000 people, 2006

Figure 2 - Modal share, all modes, 2006

Figure 2 shows that within the public transport domain, buses (local and regional) are the dominant technology, with about 90% of all public transport trips.

Non-motorized trips prevail in cities of up to 250,000 inhabitants, while public transport gets the higher share only in cities over 1 million inhabitants. Private transport is the dominant mode in cities between 500,000 and 1 million inhabitants.

2.1. Public transport

Public transport is provided by local buses, metropolitan buses and rail systems. Local buses operate in all cities, while metropolitan services are provided in 20 areas and railway/subway services in 11 areas. Together, the three systems serve 15.57 billion passengers per year (about 52 million per workable day). Local buses are dominant, serving 74% of total demand (Table 3).

Type of service	Pass/year (billion)		Fleet
Type of service	Quantity	% of total	Fleet
Local buses	11.48	73.7	72,721
Metropolitan buses¹	2.45	15.7	21,822
Railway and subways	1.65	10.6	2,681 ²
Total	15.57	100.0	97,224 ³

Table 3 - Public transport demand and fleet, 2006

1 – Buses linking cities within metropolitan areas;

2 – Railway or subway cars;

3 – Considers railway and subway cars as equivalent to 3.5 standard, 45-seat diesel bus.

3. Costs, consumption and externalities

3.1. Infrastructure and vehicle assets

MDS cities have an estimated road length of 314,000 km, which is used by a fleet of 21.2 million vehicles. Considering the cost to build new roads (without depropriation) and the cost of new vehicles, the total asset value dedicated to urban mobility in these cities goes up to R$ 1.3 trillion, approximately 80% of the GRP (Table 4).

Transport mode	Value (new equipments) R$ billion
Transport mode	Vehicles	Road infrastructure³	Total
Public¹	41.7	145.9	187.5
Private²	630.0	521.7	1,151.7
Total	671.7	667.5	1,339,2

Table 4 - Mobility asset values, 2006

1 – Buses, subway and railway cars;

2 – Automobiles and motorcycles;

3 – Freeways, expressways, arterial roads, collector and local roads.

3.2. Mobility costs

Mobility costs were estimated as individual and public costs. Individual costs are operating costs (automobiles and motorcycles) and fares (public transport). Public costs are those incurred by the government to maintain road infrastructure and signing (assumed as 2% a year of the infrastructure value). Costs were also split between public and private means of transport.

Figure 3 - Mobility costs per public and private transport, 2006

Figure 3 shows that people expend R$ 95.6 billion a year (91% of total) to use motorized transport means, while government expenses are estimated at R$ 9.5 billion (9% of total). Total value adds up to 6.6 % of the cities´gross product. The use of individual modes is much more expensive for people - R$ 75.2 billion, as compared to R$ 20.4 billion for public transport users. This yields an average cost per trip on individual means of R$ 4.75, as compared to the cost of the average public transport trip of R$ 1.31. When public expenses are compared according to public or private means, it may be concluded that they correspond to R$ 0.04 per public transport trip and R$ 0.56 per private transport trip.

3.3. Energy consumption

A total of 11.4 million TEP were consumed by public and private modes in 2006, with private transport being responsible for 75% of all consumption. Figure 4 reveals that private means consume more energy in cities of any size.

Figure 4 - Transport energy consumption per population range, 2006

The average energy spent per trip was 181 GEP for public transport means and 545 GEP for private means (rate of 1:3.0).

3.4. Air pollution

Emissions were estimated for local pollutants – CO, NOx, HC, PM - and for CO2 for public and private vehicles (table 5).

Transport mode	Million tons/year
Transport mode	Local pollutants	CO2	total	%
Public	0.22	9.28	9.50	36
Private	1.32	15.92	17.24	64
Total	1.54	25.20	26.74	100

Table 5 - Pollutant emissions in 2006

Table 5 shows that total yearly emissions were 1.54 million tons for local pollutants and 25.20 million tons for CO2. Private transport means were responsible for 64% of all emissions. The average emission of local pollutants per trip was 14 grams for public means and 84 grams for private means (1:6 ratio).

3.5. Accidents

Few MDS cities have sound statistics on traffic accidents and there is a large number of unreported events. The number of accidents was estimated by using rates derived from a special study conducted in 2002 in large Brazilian metropolitan areas by IPEA/ANTP. This home survey was designed to examine rates of accidents with household vehicles. Using the parameters of this study in the MDS cities, it was estimated that 1,563,000 vehicles were involved in about 829,000 traffic accidents in 2006 (from minor to fatal) (Table 6).

Event	Number
Vehicles involved in traffic accidents	1,562,544
Accidents	828,622
Victims (fatal and non-fatal)	355,124

Table 6 - Traffic accidents, 2006

3.6. Methodology remarks

The new ANTP urban mobility data system (MDS) was designed to generate transport-related data on Brazilian cities with higher traffic levels – those above 60,000 inhabitants (438 cities among a total of 5,600 in 2003). With the purpose of supporting the implementation of public transport policies the system was designed to provide reliable information at an aggregate level – national, regional and by group of cities – and not at the city level alone.

Collected information encompasses supply, demand, costs and revenues of public transport means, road and sign infrastructure and human and material resources used in traffic management and public transportation activities. Additional data on population, income, school enrolment, employment and daily trips were collected in several reliable external primary sources. The system integrates these data and summarizes them into specific areas, such as mobility and transport use, resource consumption, productivity, sustainability and environmental aspects. The final result is a comprehensive understanding of urban mobility and transport use in the cities surveyed.

Local authorities did not provide all the information required for the survey, either because data were not available or because city agencies do not usually have qualified staff to gather the necessary data. Therefore, statistical tools were developed to estimate the unavailable data. With the purpose of identifying the best approach, rather than classifying cities into population categories, they were classified into city "clusters", according to their social and economic characteristics such as population distribution, bus and vehicle supply per inhabitant, traffic signal supply, gross local economic product, etc. Five groups of cities were formed through the application of this methodology.

For each cluster, key indicators were defined e.g. passenger trips per inhabitant and bus, which allowed us to estimate values not provided by transport authorities and arrive at a final database structure.

Since most cities do not generally have adequate data for modal share, our estimates utilized information on public transport trips (available in most cases) and trip-generation equations derived from reliable origin-destination surveys, which have been conducted mostly within the São Paulo metropolitan area every 10 years since 1967. Such surveys represent a wide array of social, economic and travel conditions and are representative of the variety of transport options found in other large Brazilian cities. Once the final database was built, standard parameters for asset values, transport operational costs, pollutant emissions, accident rates and energy consumption were applied, therefore yielding final values for policy analysis.