FIFA World Cup 2014 Journey Carbon Footprint Calculator: Summary
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Environmental
Resources
Management
FIFA World Cup 2014
Journey Carbon Footprint Calculator:
Summary
BP Target Neutral has committed to offset the carbon emissions associated with spectator travel to
and from Brazil, as well as within Brazil during the FIFA World Cup in 2014 for those who participate
in the scheme. This paper sets out the approach taken in order to calculate the scale of these
emissions, and so inform the volume of carbon emissions to be offset.
The carbon emissions to be offset from spectator travel from a country are calculated by multiplying
the carbon emission estimate for a spectator travelling from that country by the number of
spectators from that country who register for a carbon offset when they purchase their tickets. The
total to be offset is the sum of all national calculations. The emissions per spectator depend on their
country of origin and their mode of transport.
For spectators living in Brazil, average travel-related emissions per spectator have been calculated
based on work undertaken by the consultancy MGM Innova for FIFA. The calculation of average
emissions per spectator living in Brazil takes into account travel by spectators from across Brazil to
and from matches in the 12 host cities. Weighted averages are applied to travel distances and
assumptions made about the likely mode of travel (e.g. air, rail, car, bus, metro) to calculate the
average travel-related emissions per spectator.
For spectators travelling from outside Brazil, ERM has applied a series of simplified, conservative
assumptions to calculate a realistic estimate of the carbon emissions per spectator that errs on the
side of over-estimating rather than under-estimating the emissions that need to be offset. For
example, the calculations assume that all international spectators will travel by air from their country
of origin, arriving into one of two transport hubs - Recife or São Paulo.
FIFA provided a list of the top ten countries where international spectators are expected to travel
from based on ticket sales. The estimates for air travel emissions were based on the distance from
the capital city airport in each country of origin to the Recife and São Paulo international airports,
with 30% of spectators arriving at Recife, and 70% landing in São Paulo. For a small number of large
countries, such as Australia and the USA, a weighted average distance from the four most populated
cities in the country was used.
An estimate of emissions from ground travel was determined based on the assumption that
spectators would drive to the airport in their country of origin, and that the majority of travellers live
within 1-2 hours, or 150km, from their departure airport. Emissions related to transport within Brazil
to attend matches were also included and based on assumptions made in the MGM Innova report -
2014 FIFA World Cup Brazil Carbon Footprint.
To capture the emissions associated with travel from those countries not in the ‘top 10’ described
above, a series of regional emission factors was developed. These regional emission factors were
determined either by using an average from the relevant countries within the ‘top 10’ or, where a
region was not represented within the ‘top 10’, by referring to the distance from the capital city of
the furthest mainland country within the region. All remaining countries of origin were then
assigned to one of these regions, based on UN categorisations.Environmental
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FIFA World Cup 2014
Journey Carbon Footprint Calculator:
Method Statement
The following sets out the method used to calculate the emissions associated with spectator travel
to/from Brazil during the 2014 FIFA World Cup. Key aspects of the method are outlined in the
following sections:
1.1 – Geographical Scope;
1.2 – Emissions from Brazil Spectator Travel;
1.3 – Spectators from Outside Brazil: Ground Travel Distance;
1.4 – Spectators from Outside Brazil: Air Travel Distance;
1.5 – Countries not Represented in the Geographical Scope; and
1.6 – Emission Factors.
In order to deliver a practical solution to the challenge of assessing global travel patterns, a simplified
approach was taken to generating a realistic estimate of emissions. The underlying principle behind
the methodological choices made was one of conservatism, to avoid underestimating the emissions.
Following this principle, a core assumption applied was that all spectators travelling from outside
Brazil would travel by air from their country of origin, arriving into Recife or São Paulo. They would
then use various travel modes to travel between and within host cities.
1.1 GEOGRAPHICAL SCOPE
For Brazilian spectator emissions, a single value for average per spectator emissions was calculated
based on data provided in the MGM Innova 2014 FIFA World Cup Brazil Carbon Footprint completed
for FIFA in 2013. An overview of the approach taken is provided in Section 1.2.
For the following ten countries, individual emission factors were calculated for spectator travel. FIFA
estimates that these, after Brazil, have the highest spectator numbers (1).
1. United States of America
2. England
3. Germany
4. Australia
5. Canada
6. France
7. Colombia
8. Switzerland
9. Japan
10. Argentina
For all remaining countries not included here, the calculator assumes a conservative emission factor
(see Section 1.5).
(1) Article: rd
889,305 tickets allocated during the random selection draw for the 2014 FIFA World Cup; retrieved on 23
January 2014; http://www.fifa.com/worldcup/organisation/ticketing/news/newsid=2218428/index.html
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1.2 EMISSIONS FROM BRAZIL SPECTATOR TRAVEL
The total emissions associated with all spectator travel were assessed by MGM Innova for FIFA. The
following data from the MGM Innova report were used to calculate the average emissions per
Brazilian spectator in this study:
• modal split for transportation methods for both intra-city (1) and inter-city (2) travel within
Brazil;
• average air and road distance between all venue cities;
• average intra-city distances travelled to and from the venue (50km) and to and from
temporary accommodation in the city (50 km for inter-city travellers), and
• the total number of inter-city travellers (41% of all Brazilian spectators) and total number of
intra-city travellers (59% of all Brazilian spectators).
Full details of the modal split used and average distances for air and road travel between host cities
are set out in the MGM Innova report and a summary of these data is provided in Annex A. Further
to this, all domestic fans were assumed to attend two matches. This is based on assumptions used in
MGM Innova report and the Feasibility study for a carbon neutral 2010 FIFA World Cup in South
Africa produced in 2009 (3).
The average emissions per Brazilian spectator were calculated as the weighted average of intra-city
travellers and inter-city travellers.
1.2.1 Intra-city travel
For the 59% of Brazilian spectators assumed to travel within their own city only, a round trip of 50km
was assumed. A weighted average modal split of transportation methods was calculated from the
modal split supplied by MGM Innova for each city and further weighted by the number of matches in
each city. The average distance travelled per spectator for each mode of transport was calculated
and multiplied by the relevant emission factor.
1.2.2 Inter-city travel
For the 41% of Brazilian spectators who will travel between cities, a single average value for the
distance travelled by air and road (car or bus) was calculated to represent the journey to each match.
This was a weighted average distance, assuming all spectators are travelling from a host city, and
calculated using the average distance between each host city and the other 11 host cities weighted
by the number of games played in each. The average distance travelled per spectator for each mode
of transport (air, car and bus) was calculated and multiplied by the relevant emission factor.
The weighted average distance between host cities assumes that all inter-city travellers are travelling
from one host city to another. While this may not strictly be true, the host cities are spread around
Brazil and represent the majority of the major population centres and so these figures are likely to
represent a reasonable average distance travelled to matches.
(1) Car,Taxi, Bus, Bus Rapid Transit, Subway, Train and Non-motor (walking or cycling)
(2) Plane (50%), Car (25%) and Bus (25%)
(3) Feasibility study for a carbon neutral 2010 FIFA World Cup in South Africa, Econ Poyry (2009)
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1.2.3 Emission factors
Emission factors (including both direct and embodied emissions for fuel use) for all public transport
were sourced from Defra/DECC GHG Conversion factors for company reporting for 2013. However,
as ethanol, produced from sugar cane, is added to all petrol in Brazil and many cars (known as
flexible fuel vehicles) in Brazil are able to run on 100% ethanol the Defra emission factors were not
suitable for assessing car/taxi journeys within Brazil.
Brazilian regulations require that all petrol sold should include 25% ethanol. However in practice this
can vary depending on the success of the sugar cane harvest in that year. The following assumptions
were used to calculate an average emission factor for car and taxi transport in Brazil:
• All petrol contains 25% ethanol.
• Direct emissions per litre of fuel used for petrol use were taken from Defra/DECC GHG
Conversion factors.
• 50% of cars are flexible-fuel vehicles (1).
• 50% of all flexible fuel vehicles run on 100% ethanol (2).
• Fuel efficiencies for flexible-fuel vehicles and petrol cars were taken from Brazilian
government data for 2009 (3).
• Assumed that car/taxi occupancy was 1.6 passengers per journey.
• Embodied emissions per litre of petrol were taken from Defra/DECC GHG Conversion factors.
• Embodied emissions per litre of ethanol were taken from the ecoinvent database V2.2 (4).
No embodied emissions from direct land use change associated with sugar cane production were
included in the embodied emissions for ethanol as research has shown that where sugar cane
expansion has occurred this has typically been in areas of existing farmland. However, it is possible
that indirect land use change may have occurred as a result of the expansion in sugar cane
production areas but this complex issue is considered outside the scope of this calculator.
Buses in Brazil were assumed to run on primarily on diesel. While biodiesel is routinely mixed with
diesel in Brazil, this is typically only in the region of 5% of the total volume.
It should be noted that using a single average value for the travel emissions from all Brazilian fans is
likely to overestimate emissions from individual fans making only intra-city journeys and
underestimate the emissions from individual fans making inter-city journeys but overall will provide a
realistic estimate.
(1) Inventario Nacional de Fontes Moveis, MMA (2011). 2009 data shows that 43% of cars were flex or ethanol assumed that
this will increased to 50% by 2014
(2) Inventario Nacional de Fontes Moveis, MMA (2011). Average 2004-2009.
(3) Inventario Nacional de Fontes Moveis, MMA (2011). Efficiencies based on manufacturers data and so 15% decrease in
efficiency applied to account for inefficient cars and driving style as recommended under Defra GHG guidance.
(4) Ecoinvent V2.2 ethanol, 99.7% in H2O, from biomass, production BR, at service station/kg/CH
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1.3 SPECTATORS FROM OUTSIDE BRAZIL: GROUND TRAVEL DISTANCE
No literature reference, applicable to the range of geographies considered, could be found to
support an ‘average journey distance’ travelled to an airport. As a result, the following assumptions
were made with regard to spectator travel from their home to an airport:
• spectators would drive to the airport, with an average car occupancy of 1.6 passengers per
journey, as opposed to taking any form of public transport;
• the majority of travellers will live within 1-2 hours ground transport of a major airport; and
• on this basis, a distance of 150 km travel by car to an airport was included in the emissions
estimate for all countries (i.e. 300 km return). We consider that this is likely to be a conservative
estimate since a significant proportion of ground travel will be by alternative modes (e.g. coach
or rail).
Emissions related to travel within Brazil by international spectators were calculated using the same
method as outlined above in Section 1.2 for inter-city travel by Brazilian spectators.
However, each international fan was assumed to attend an average of four matches and were
assumed to travel from /return to either Sao Palo (70% of fans) or Recife (30% of fans) for the first
and last games attended.
1.4 SPECTATORS FROM OUTSIDE BRAZIL: AIR TRAVEL DISTANCE
There are two key challenges in determining a representative estimate of the flight distance for
spectators originating from different countries: 1) there are multiple airports within each country;
and 2) flight paths are not always direct.
In order to simplify the calculations, yet retain a realistic estimate overall, the following approach
was taken:
• the air travel distance was calculated from the capital city airport within each country of origin
to Recife (assumed 30% of all visitors) and São Paulo international airports (assumed 70% of all
visitors); and
• the distance between airports was assessed using the coordinates of each airport, and using the
Great Circle Flight methodology, which accounts for the curvature of the earth.
The 'capital city' approach will lead to the under-estimation of air travel emissions from some
countries, where the capital is relatively close to Brazil, and an over-estimation for others where the
opposite is true.
In the majority of instances, it is reasonable to assume that these under- /over-estimations will, on
balance, yield a net estimate that is realistic. There are some countries for which the capital city
approach is unlikely to be representative, however. A screening step was therefore undertaken to
identify countries with a surface area > 1 million km2 – considered to be those at greatest risk for
potential under-estimation of flight distance.
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The countries emerging from this screening step were: the USA; Canada; Australia; Argentina; Russia;
China; and Brazil. For these countries further consideration was given to the positioning of the
capital city, to determine whether the capital city approach was justified to calculate a reasonable
emissions estimate. This was found to be the case for Russia, Brazil, Argentina and China, where
either:
• the position of the capital city results in a likely conservative emission factor (e.g. Beijing,
being positioned in the far east part of China); or
• a large proportion of the population lives in a relatively small area, in relatively close
proximity to the capital (e.g. Argentina, Russia).
For the USA, Canada and Australia it was determined that a more detailed approach was needed, in
light of the fact that major population hubs are spread around the country. For these countries, the
weighted average distance from the four most populated cities in each country was used. The cities
selected for each country are shown in Table 1.
Table 1 Countries and major population hubs
Country Top 4 Cities by Population
USA New York
Los Angeles
Chicago
Houston
Australia Sydney
Melbourne
Brisbane
Perth
Canada Toronto
Montreal
Vancouver
Ottawa
1.5 COUNTRIES NOT REPRESENTED IN THE GEOGRAPHICAL SCOPE
The ten countries provided by FIFA, besides Brazil, included within the scope of the assessment are
those from which the greatest number of visitors are expected but are not all the countries from
which spectators will travel. To capture the emissions associated with travel from other countries, a
series of regional emission factors were developed, using the following approach.
• Where the region (as categorised by the United Nations) was already represented by a country or
a set of countries within the top ten outlined in Section 1.1, the average emissions for this
country or this set of countries was taken.
• Where the region was not represented within the geographical scope of those countries in the
FIFA list, the furthest mainland country in each region, where applicable, was taken and the
capital city approach was used to determine an air travel distance. A list of these regions and
country representations is shown in Table 2 below.
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Table 2 Regions and country representation1
Region Corresponding country
Eastern Africa Djibouti
Middle Africa Chad
Northern Africa Egypt
Southern Africa Swaziland
Western Africa Niger
Caribbean Bahamas
Central America Guatemala
Central Asia Kyrgyzstan
Southern Asia Bangladesh
South Eastern Asia Philippines
Western Asia Oman
Eastern Europe Russia
Southern Europe Serbia
Melanesia Papua New Guinea
Micronesia Palau
Polynesia Tuvalu
1. World sub-regions categories and country listings were extracted from United Nations documentation
(link: http://unstats.un.org/unsd/methods/m49/m49regin.htm)
1.6 EMISSION FACTORS
Having defined the distance travelled by car and by aircraft for each country and region, emission
factors ‘per km’ were sourced from the 2013 UK Government Conversion Factors for Company
Reporting in order to translate distances into CO2e emissions.
⇒ For car transport, the emission factor for ‘average passenger car’ was used. This reports
emissions per vehicle km and so an average figure for car occupancy (1.6 (1)) was sourced from
the UK Department for Transport in order to convert to emissions per passenger km.
⇒ For air transport, the emission factors within the UK Government Conversion Factors for
Company Reporting are categorised into average domestic, short haul, and long haul flight types.
Long haul flights are classed as those greater than 3700 km, and so this cut-off was also applied
in the calculations.
(1)
Data based on UK National Travel Survey; Car occupancy by trip purpose: Great Britain, 2012. Retrieved from the GOV.UK
th
website on 6 January 2014, https://www.gov.uk/government/statistical-data-sets/nts09-vehicle-mileage-and-occupancy
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