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THE DECC GLOBAL CALCULATOR AND THE ROLE OF THE TRANSPORT
SECTOR IN TACKLING CLIMATE CHANGE
Jo Baker
David Viner
Andrei Bettinson
Simon Harrison
Mott MacDonald
1. INTRODUCTION
The Global Calculator was developed by the UK Department of Energy and Climate
Change (DECC) to assess the role of different sectors in contributing to climate
change at 2100. The tool enables different experts to contribute scenarios which
might help to restrict temperature rises and is freely available to anyone wishing to
explore their own scenarios.
The Global Calculator was released as a call for evidence by the DECC, IEA and the
Climate-KIC consortium to enable experts to comment on the data, assumptions,
findings and presentation of results. The purpose of the exercise was to source a
range of perspectives from different groups of experts in order to construct potential
scenarios which might limit climate change to a 2C rise in global temperature above
pre-industrial levels. It is also designed to give confidence to users that limiting
climate change to 2C is achievable.
The tool is available as a resource for use by all interested practitioners, policy
makers and wider stakeholders, and this paper is intended to encourage ETC
participants to use the model and to provide their own inputs and ideas. The paper
provides an introduction to the tool and feedback on the experience of preparing a
scenario for the calculator as a part of a multi-disciplinary team.
It introduces and discusses the various parameters the Calculator uses to assess
transport impacts, and the scenarios assumed within the tool. Because of the multidisciplinary nature of the tool the range of transport levers is limited, and of course
the impact of transport becomes only one facet of a larger challenge.
The paper discusses the challenges of predicting changes in transport trends, not for
the UK, or the EU, but on a global basis, and the risks inherent in such an approach.
In many cases there may be a difference between our expectations of potential
outcomes, and the outcomes we might be able to achieve with optimal governance.
The paper also considers how, as professionals, we need to encourage the adoption
of targets which are both challenging but also potentially achievable.
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On the basis of the tool’s assumptions the paper considers the degree to which
transport practitioners can tackle climate change in isolation, and the importance of
integration across disciplines to understand the interaction of transport with food,
housing etc. At present the tool considers each level in isolation and this paper also
considers the ways in which a system dynamic modelling approach might offer value
to any future similar tool by providing a mechanism to assess changes in different
sectors in a consistent manner.
2. BACKGROUND
2.1. Development of the model
The Global Calculator has been developed progressively since 2009 and is rather a
product of evolution of calculators developed on country by country bases. One of
the first such calculators was the 2050 UK Pathways Calculator. DECC was tasked
with coming up with a plan to meet the world's first legally binding emissions target
(an 80% reduction by 2050 based on a 1990 baseline). Because there was so much
uncertainty about what technologies would be available in the future, the team
decided to build a new tool to explore all the options available, rather than using
existing models that determine an optimum pathway.
A number of "key messages" from the Calculator were published - lessons learnt
from all pathways that meet the 2050 target. These were then used to develop the
Carbon Plan, the government's overall emission reduction strategy, in 2011. A
simplified version of the Calculator called My2050 was developed aimed at the
general public. Over 17,000 people have submitted pathways using this site, giving a
unique insight into public opinion on the energy transition.
Since then, around 20 countries, regions and territories have adopted a similar
approach and have built or are building their own calculators to help inform policy
and increase public understanding of energy issues. This began with the Belgian
region of Wallonia, and was quickly followed by China. In 2012 DECC received
funding from the International Climate Fund to support 10 developing countries to
build calculators using locally based teams, as well as to build the Global Calculator.
2.2
Using the model
The model is available as an on-line tool but also as a freely downloadable Excel
model for which the source code is also available. As such the model is available to
be used and adapted at will. The only restriction is on exploitation for commercial
purposes. The model, supporting material, and information on its development and
application are available from the following website:
http://www.globalcalculator.org
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3.
WHAT IS THE GLOBAL CALCULATOR?
The Global Calculator is a model which enables anyone interested in policy
formulation and carbon emissions and climate change to test alternative scenarios
up to the year 2050 and simulate the Green House Gas emissions in 2100. The
model is open source and built in Excel to ensure that it is freely available for use
and adaptation by interested practitioners.
It runs through a web-based interface for ease of use. It requires the user to set circa
40 policy “levers” grouped into 15 themes under 4 main headings. These are show in
Table 1.
Table 1: The Global Calculator Levers
Heading
Lifestyle
Theme
TRAVEL
Homes
Diet
TRANSPORT
Buildings
Manufacturing
Carbon Capture and Storage
Bioenergy
Fossil Fuel
Nuclear
Renewables
Food
Land Use
Demographics
Emissions after 2050
Technology and Fuels
Land and Food
Demographics and Long Term
The levers relating to Travel and Transport are of most relevance to this paper and
are discussed in depth below. The relative significance of these levers compared to
the other levers is, however, also significant and merits discussion. Finally, there is
some degree of inter-relationship between the levers which also merits
consideration.
For each lever the model has a scale from 1 to 4 representing a range of
interventions from minimal to ambitious, very ambitious and extremely ambitious.
Across these levers the model has a number of controlling cross-cutting themes
relating to energy supply (electricity as well as raw resource) and land-take. These
act as boundary conditions to the choices made. We suggest that there should be
other boundary conditions such as the supply of clean water.
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3.1
The Travel and Transport Levers
There are five distinct levers in the Lifestyle (Travel) category. These are intended to
identify energy consumption associated with peoples’ energy-consuming habits, and
the influence of them of historical factors and governments’ policies. These are as
follows:
 Passenger Distance
 Freight Distance
 Mode
 Occupancy and Load
 Car Own or Hire
Under Technology and Fuels (Transport), which reflect more direct choices of
transport mode, there are two further levers as follows:
 Transport Efficiency
 Electric and Hydrogen
Each of these is discussed in turn below.
Passenger Distance
This lever combines estimate levels of urban travel, rural travel and international
long-distance travel by air and rail. Ideally there would be 3 different levers, but the
combined lever provides an indication of the degree to which these will change.
Considering this lever raises a number of interesting questions. Many global megacities are badly planned with population living in informal unplanned settlements a
long way from work: improved planning will bring work and home closer but new
Metro facilities might make long-distance commuting easier. Another trend to
consider is the ageing of the world’s population and the likelihood that in developed
countries the level of commuting may reduce, for instance in response to the
increased use of remote working technologies.
The inclusion of urban, rural and international travel as a single lever is a concern.
These cannot be assumed to change in a comparable manner. The concept of
Marginal Social Cost Pricing recommends that all travellers meet the full societal
marginal cost of their travel choice. This might lead to firm fiscal intervention to deter
urban car trips and flights, but not intervene in rural areas where benefits (or
necessity) outweigh costs.
All levels of this lever assume a significant increase in distance travelled
commensurate with population growth: the variation between these is comparatively
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modest. The potential for technological solutions to radically change travel behaviour
has not been considered.
Freight Distance
This lever looks at total freight movement and consumption per individual.
In the developed world, significant reductions in freight kilometres have been
achieved through smarter logistics. In part, this reflects the rising cost of vehicles,
fuel and personnel. There is scope to increase the ability for economic growth in the
developing world without necessarily increasing the freight kilometre value pro-rata
through the wider roll-out of logistic planning and load consolidation.
Moreover, if development levels in the world become more comparable then the
current emphasis on transhipment of high value foodstuffs from the developing to the
developed countries may reduce. Additionally, the tendency for manufacturing
processes of the developed economies to be exported overseas may reduce as
labour rates become more equitable and transport costs start to outweigh potential
labour savings. As such there may be scope to significantly control increases in
freight distance.
That said, the International Transport Forum at the OECD1 is pessimistic on this and
expects to see a fourfold growth in international freight transport by 2050, if action is
not taken.
In reality, there is a significant potential interaction between freight and food
production which would merit discussion in the future.
Mode
Mode is another complex lever which conflates the percentage of urban and rural car
usage with the percentage of travel demand diverted from international air travel.
Setting aside the validity of bringing these factors into a single lever, this raises some
interesting questions. At present, car usage is high in rural areas and in medium
sized developed cities. In major cities it is already often suppressed by congestion
and offset by public transport provisions. There is a presumption that developing
countries look to the West for inspiration, but, in reality, transit-dominated cities such
as Singapore or Tokyo may be the role models to which decision-makers aspire.
Moreover, in the developing world there is already recognition that the scope for
significant further increases in car usage is limited and that public transport
1
Global trade: International freight transport to quadruple by 2050, International Transport Forum at the
OECD”, Paris 2015
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investment is an urgency. As indicated before, the role of Information Technology as
a potential disruptive force in travel demand is significant, if not well understood.
Occupancy and Load
This lever combines car occupancy and freight load factors for light trucks. Clearly,
car-pooling and lift-sharing are still emerging opportunities, which may increase as
social media becomes more sophisticated and motoring costs rise.
The freight lever is less clear as light trucks are often used for final mile delivery
which may be the least optimised element in the supply chain.
Car Own or Hire
The model then looks at vehicle ownership compared to the use of hired and other
vehicles. This is expressed in terms of the kilometres travelled by a vehicle annually
and is driven by the assumption that an increase reflects increased car sharing and
is, as such, a positive. This is, perhaps, a curious choice of indicator as a hired
vehicle is not, per se, cleaner than an owned vehicle. A move towards collective
ownership may be associated with lower personal usage as the marginal cost
becomes more explicit, whilst the converse argument is that those that do not own
cars may use cars more if there is an opportunity to drive.
Either effect could be covered by levers dealing with personal distance travelled and
mode choice or a lever which considered total vehicle kilometres rather than
distance travelled per vehicle. The model suggests that this might be associated with
the use of self-driving vehicles but the implications of that are not explicit.
Transport Efficiency
This lever looks at fuel consumption and, in general, appears to be pessimistic when
it considers private cars, light trucks and freight planes.
Given the improvements seen in the last 35 years it would seem likely that by 2050,
in the face of rising fuel costs, further step-changes should be attained for private
cars: the target of 4.3 l/100km (corresponds to “very ambitious” level for 2050) is
already beaten by vehicles on the market in 2014 and as such is potentially “soft”. It
is harder, however, to assume parallel enhancements for other types of vehicle.
In recent years, the emphasis within the EU has been on driving down health-related
emissions for heavy vehicles. This has been achieved through a series of European
standards but the impact has been that fuel consumption has not significantly
reduced. The implications of the recent debate over emission-testing of diesel
vehicles may lead to a pushback on diesel vehicles which could lead to a modest
increase in CO2 emissions. The level of improvement in fuel consumption that has
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been achieved for private cars is unlikely to be achieved for commercial vehicles.
The weight of a commercial vehicle is predicated on its load and is unlikely to be
greatly reduced, whilst the biggest savings may be on measures to improve logistical
efficiency through load consolidation thus increasing weight and fuel consumption.
At a global level, the challenge has been the disposal of second-hand vehicle fleets
to developing countries. This has meant that the average emission levels lag
significantly behind the “best in class”. That said, over 35 years the fleet will be
replenished a number of times and the vehicles operating in developing countries
are likely to be equivalent to, or better than, those operating in the developed world
today.
Electric and Hydrogen
This is a complex indicator which considers the shift to hydrogen and electric urban
passenger and light freight vehicles.
It is assumed that more challenging targets will see take-up of hydrogen technology.
At present this seems unclear, particularly for private vehicles, and as such it may be
that more innovative charging techniques for pure electric or plug-in hybrid vehicles
will be more likely to see adoption.
As an observation, the reference in the Calculator to “zero-emission” is unhelpful. All
vehicles will emit pollutants associated with wear and tear on brakes, tyres etc.,
whilst hydrogen and electric vehicles can, at best, be considered “zero-emission”
only at point of use: the lifecycle for electric vehicles may be low whilst even
renewable energy has a tangible infrastructure-related carbon footprint.
4. DEVELOPING A PATHWAY
At the request of DECC, Mott MacDonald reviewed the emerging model and
developed a pathway which reflects, from our perspective, what we need to do to
stay below the 2 degree rise that is necessary to prevent dangerous climate change.
Mott MacDonald’s view was that:



This would be achieved through technological development that will maintain
economic growth, societal choice and climate resiliency.
We use less carbon intensive technologies and fuels with more efficient
supply chains. Buildings are heated and cooled more efficiently, our
appliances are efficient in both water and energy usage.
Gas, nuclear, renewables and CCS drive down emissions, however,
decarbonisation of energy is not the sole driver: through awareness raising
and cultural shifts we will use land more efficiently and produce less food
waste.
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When developing the pathway, we were even more optimistic of the possibilities for
the low carbon generation, however, in order to balance the electricity supply and
demand, we had to constrain those levers.
We found this tool valuable as a means to drive collaboration internal across our
sectors. It is apparent that Climate Change can not be addressed by a single sector
in isolation and the Calculator provides an efficient means to generate dialogue and
creates the opportunity to discuss and identify solutions. At, present and research
has shown that the public have an apparent distrust of many climate change
mitigation policies as they are perceived as either being expensive or detrimental to
living standards. Decision-makers may have to adopt certain policies which appear
unpopular in the short-term, but in such instances they need to have robust evidence
for their decisions and they need to be convinced personally that the benefits of such
decisions are justified. Mott MacDonald’s pathway (and others) have demonstrated
that 20C can be achieved through the adoption, not of strict detrimental actions, but
ones which demonstrate efficiency in the use of finite resources.
4.1
Relative sensitivity by sector and the role of the transport profession in
tackling climate change
As a matter of comparison, we simulated the implications for each lever moving from
a Level 2 to a Level 3 in terms of CO2 reduction. The results provide a helpful
indication as to the impact of different policy decisions. The move to electric and
hydrogen vehicles is less beneficial because it depends on the ability to decarbonise
the power source.
Transport clearly has a significant part to play in reducing carbon emissions but,
relatively conventional mechanisms, such as travelling less and changing mode, may
be more effective than changes to electric vehicles until there is clarity over the
availability of renewable electricity.
What is very stark, is the implication of diet in general, and the consumption of meat
specifically, as a driver of carbon emissions. Policy makers working in a city-wide
context will need to tackle a range of issues of which transport is only one in terms of
addressing climate change.
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Table 2: Sensitivity Analysis of a shift from Level “2” to Level “3”
“2→3”
Sensitivity
Analyses (relative to
2’s)
Passenger Distance
Freight Distance
Mode
Occupancy and Load
Car Ownership
Transport Efficiency
Electric
and
Hydrogen vehicles
Quantity of Meat
Type of Meat
Livestock
Intensification
Extensive Livestock
Yields
Land-use Efficiency
Global Population
CO2
-2.47%
-1.19%
-3.25%
-1.42%
-0.54%
-2.79%
4.34%
-34.25%
-11.55%
-10.45%
-18.97%
-17.27%
-30.64%
4.2
Challenges in making predictions
The analysis methodology in the Global Calculator is based on the best available
research and has been thoroughly reviewed. Of course, the estimation of likely future
scenarios is highly subjective. Working at a global level requires consideration of
how behaviour will change in both developed and developing countries, as well as
the implications of different levels of population growth, and rates of urbanisation.
The latter are reflected as levers in their own right but may also have an influence.
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Looking to the Future
5.1
System Dynamic Modelling
As things stand, the model is probably most useful for comparing the individual and
cumulative impacts of different policy levers. It doesn’t provide a robust quantified
estimate of GHG emissions at city or country level or reflect all the potential
interactions between the levers and macro-economic drivers.
Also, whilst the model does look at the total supply of land and energy, there is
absence of water resources as a key boundary condition.
As an example, the means of production of food will have a significant impact on
water consumption. At both a global and local level, this has implications for
population development and other industries. Moreover, the distribution of food
production will have implications for energy consumption, whether in terms of
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heating in temperate climates or transport from tropical to temperate zones. These
are not simple issues to resolve.
An example2 is shown below. These system dynamic models enable the linkages
between different levers to be understood better. Quantifying the linkages is a
challenge and may be difficult to achieve in the short term but might be a valid longer
term goal.
Figure 1: Ilustration of System Dynamic Model
6. CONCLUSION
The vast majority of experts (as demonstrated through the wealth of scientific
evidence) are in agreement that the observed changes in the climate system are
associated with man-made actions and specifically carbon emissions. The
forthcoming COP21 talks in Paris raise the urgency of constructive dialogue on these
issues.
2
Dynamic modeling of selected social and mobility aspects, Emberger and Mayerthaler, TUW-IVV,
2010
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The Climate Change agenda is often obscured by opinions, perceptions and
misconceptions and successful policy interventions may struggle to achieve public
acceptability.
The Global Calculator provides the experts who support policy formulation with a
robust, yet accessible tool to animate the discussion and to help to quantify the
implications of actions. Whilst the tool will benefit from further development, it is a
valuable step forward as COP21 draws near.
ETC delegates are encouraged to use the Global Calculator themselves and to
provide feedback to DECC to inform subsequent development.
Acknowledgement.
The authors are grateful for the encouragement of Laura Aylett and her colleagues at
DECC to trial and make use of the Global Calculator, and their support and advice
during the development of our response. This paper draws on discussions with them
but presents the views solely of the authors and not DECC or Mott MacDonald.
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