The inspiration for this tool is a chapter by Jørgen Nørgård in a recent book "Rethinking Climate and the Energy Policies".
The equation I=P*A*T which combines population (P), affluence (A) and technological eco-intensity factor (T), has been known since Ehrlich and Holdren presented it in 1971. This equation aims to show that reducing climate change by means of only reducing T may be incredibly difficult if no measures are taken in the other two factors, i.e. P and A.
In our version we have extrated diet (D) as a seperate impact and therefore the equation I=PAT(D). The ecological impact is represented by CO2 emissions and the global concentration level is translated into mean global temperature increase until 2100. The impacts are tracked on 16 different regions of the world and equality within population growth and affluence can therefore be investigated.
The ecological footprint is also tracked based on data from www.footprintnetwork.org and illustrates how much area is needed to maintain a sustainable production of food and energy to cover the global demand. The result is how many earths are needed with a given level of consumption.
Acknowledgement
We would like to thank the GLOBAL FOOTPRINT NETWORK for providing us with data that made the estimation of the footprint possible.
“© Global Footprint Network 2016. National Footprint Accounts, 2016 Edition. Licensed and provided solely for informational purposes. Contact Global Footprint Network at www.footprintnetwork.org to obtain more information.”
Input scenarios
included in the IPAT(D) model
The IPAT(D) model includes a database with the
scenarios listed below for population, affluence, technological development,
GHG emissions and diet. All combinations of these parameters can be tested in
the model.
Population and Affluence Scenarios
The population and affluence scenarios are based on
the Shared Socio-economic Pathways (SSPs) data (Moss et al 2010, Kriegler et al
2012, O’Neill et al 2014) illustrating possible pathways for change in
population and economic development.
Each SSP consists of quantitative projections of GDP,
Population and Urbanisation along with resource and technology constraints
consistent with the underlying qualitative narrative. SSP1
“Sustainability – taking the green road” is a scenario in which the world
shifts gradually, but pervasively towards a more sustainable path, with a focus
on inclusive development within environmental limits. SSP2, “Middle of the
Road” is a world in which social, economic and technological trends do not
significantly change from historical rates of change. SSP3, “Regional Rivalry –
A Rocky Road” is characterised by resurgent nationalism, competitiveness,
fragmentation and little cooperation on environmental policy with a focus on
energy and food security within nation development goals. SSP4, “Inequality – A
Road Divided”, is a scenario in which there is increasingly inequality in
economic opportunity and political power, leading to social stratification
across the world and within countries. Social cohesion degrades and conflict
becomes common. SSP5, “Fossil-fuelled Development – Taking the Highway”, relies
heavily on the open market and innovation to drive rapid technological change
and development of human capital towards sustainable development.
Population
scenarios
SSP1
|
Low fertility in current low and medium income
countries, medium fertility in current rich OECD countries
|
SSP2
|
Medium fertility in all countries
|
SSP3
|
High fertility in current low and medium income
countries, low fertility in current rich OECD countries
|
SSP4
|
High fertility in current low income countries, low
fertility in current medium income and rich countries and medium fertility in
rich OECD countries
|
SSP5
|
Low fertility in current low and medium income
countries, high fertility in current rich OECD countries
|
Low fertility
|
Low fertility, immediately fall to < 1.5 birth
per woman in all countries
|
No change
|
No change in population from 2015 and forward
|
Affluence
scenarios
SSP1
|
High growth in current low and medium income
countries, medium growth in current high income countries
|
SSP2
|
Medium uneven economic growth in all countries
|
SSP3
|
Low economic growth in all countries
|
SSP4
|
Low economic growth in current low income countries,
medium growth in other
|
SSP5
|
High economic growth in all countries
|
No change in affluence
|
No change from 2015, constant in each region on the
level of 2015
|
Economic crisis
|
Crisis until 2050, stronger in high income
countries, and then slow recovery
|
Equality
|
All regions reach by 2100 the level of USA in 2015
|
Catching up
|
Continuing historic growth rates until 2050, after
2050 the current low income countries catch up with current high income
countries
|
Shifting
power
|
Low economic growth in current high income countries
and high growth in current low income countries
|
Diet scenarios
Dietary impacts can be altered for each region in the
model, but for simplicity sake, only three alternatives are used in this model.
The diets from different countries and regions are based on FAOSTAT (2017) and
change in environmental impact from Ranganathan J et al (2016).
Diet scenarios
IND Diet
|
India’s diet in all countries, transition over 20
years
|
USA Diet
|
USA or EU diet in all countries, transition over 20
years
|
No Change
|
No change from today
|
Technology scenarios and associated GHG share
Three scenarios are chosen from a large number of
technology scenarios from TIAM-World driven by the different SSP scenarios, to
represent the potential technological development. The TIMES Integrated
Assessment Model (TIAM) is a multi-regional and inter-temporal partial
equilibrium model of the entire energy/emission system of the world, based on
the TIMES paradigm (Loulou and Labriet 2008; Loulou 2008). Several variants of
the model exist that differ with regard to, e.g. regional aggregation, sectoral
details, etc. TIAM-World is the model variant used in the IPAT(D) model.
From each scenario in TIAM-World, CO2 emissions per
GDP has been calculated by year and region, and is used in the IPAT(D) model to
scale the GHG emissions with change of regional GDP, which is further scaled
with the change in regional population.
Technology
scenarios
Business As Usual
|
No policies or targets implemented, competitive
markets secure global cost minimized solution
|
Strong Technology Development
|
90% non-fossil power, 50% non-fossil primary energy
in 2050. More than 90% non-fossil primary energy in 2100
|
Radical Technology Development
|
100% non-fossil power, 85% non-fossil primary energy
in 2050. 95% non-fossil primary energy in 2100
|
References
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growth, Science (New Science), 171(3977), 1212-1217
FAOSTAT (2017) Food and Agriculture Organization of
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Jespersen and Chick (2016) John Maynard Keynes
(1883-1946). I. G. Faccarello & HD Kurz (red), Handbook on the History of
Economic Analysis: Great Economists since Petty and Boisguilbert. vol. 1,
Edward Elgar Publishing, Incorporated, Cheltenham, UK, s. 468-483.
Kanors-EMR (2017) TIAM-WORLD. Available at: http://www.kanors-emr.org/models/tiam-w
Kriegler E et al (2012) The need for and use of
socio-economic scenarios for climate change analysis: A new approach based on
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Moss RH et al (2010) The next generation of
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(2017) Data. Available at: http://climate.nasa.gov/vital-signs/global-temperature/
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Ranganathan J et al (2016) Shifting diets for a
sustainable food future. Available at: http://www.wri.org/sites/default/files/Shifting_Diets_for_a_Sustainable_Food_Future_1.pdf
Rees W and Wackernagel M (1996) Our
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Gabriola Island, BC
Shrinkthatfootprint (2017) Life Cycle Assessment Data.
Available at: http://shrinkthatfootprint.com/food-carbon-footprint-diet
Wackernagel M et al (2014) Ecological footprint
accounts, Handbook of Sustainable Development (second revised edition), Edward
Elgar Publishing, Cheltenham, Glos, UK.
Disclaimer: Data might be subject to copyright or related rights. Please consult the primary data owner.