Raising the Quality of Human Life —
A Least Cost Route to Reducing Carbon Emissions
Insights from a System Dynamics Model
Karan Khosla (EarthSafe Enterprises) and
Ashok Khosla (Development Alternatives, Club of Rome and IUCN)
Abstract
As the Kyoto Protocol approaches the end of its validity and as the international
community prepares for designing its successor, the pressure to act, for both
developed and developing countries, is inexorably building up. Developing
countries emphasize that their total emissions may be significant and growing,
but their per capita emissions are still very low -- far below those of the
developed world. On the other hand, the industrialised countries claim that
without some reduction in future emissions from emerging economies, global
change cannot be contained within the limits that are considered safe.
This paper looks at how rapid improvements in quality of life among the world’s
poorest, and specific, carefully designed interventions, through their impact may
provide the one common platform that would attract and bring together almost all
parties. These interventions would identify leverage points in societies which
have the greatest impact for the least cost and disruption. This paper presents a
possible win-win strategy that can bring the competitors in the current game to
play to agreed, logic-based and consistent rules. These rules would be derived
from a systems analysis that attempts to overcome the northern consumption vs
southern population related stand-offs that exist today.
The Problem
The changes occurring today in our climate systems may well pose the
greatest threat that life on our planet has ever faced. The United Nations
Framework Convention on Climate Change (UNFCCC), signed at Rio de J aneiro
in 1992 already recognized that such a threat could be addressed only through
concerted, large-scale action by the entire international community. Subsequent
findings by the International Panel on Climate Change (IPCC) and others have
alerted us to the alarming acceleration taking place in climate change processes
and have highlighted the need to address them with the highest priority and with
an urgency measured in time scales that are now down to years, not decades.
Yet, the current state of negotiations among nations to deal with climate
change is still stuck in an endless game of passing the buck from one to another.
Among industrialised countries, the disagreements largely relate to issues of
establishing somewhat superficial and temporary advantages, such as choice of
baselines and reference dates, acceptable CO2 emission targets, time horizons,
etc. Between the rich countries and the poor, the disagreements are slightly
more fundamental such as historical responsibility, fairness, per capita rights,
acceptable tradeoffs between economic “growth” and emissions, etc.
Given the entrenched positions and the strength of vested interests, there
appears to be little incentive for opposing parties to come to the negotiating table
with a common basis for agreement on even minor issues — other than the need
to keep the discussion going. At stake are heavy economic, political and security
issues underpinned by the deep commitments of nations and societies to
maintaining their respective “way of life” — defined primarily by their lifestyles,
consumption patterns and production systems. Supporting these commitments
is the firmly held conviction of their political and corporate leaders that changes in
this way of life are not acceptable to their electorates or customers, and should
such changes become necessary, they ought at best to be the responsibility of
others, elsewhere, or at worst introduced at the domestic level gradually and very
slowly.
These views led, in the mid-1990s, to the adoption of the Kyoto Protocol,
the agreement among nations to cut their respective energy consumption (and
thus greenhouse gas emissions) progressively down until they reached an
acceptable level. Low-income countries were temporarily exempted from these
cuts. Given the gross disparities in energy use that exist among countries, and
the accumulated emissions that different countries had been responsible for over
the past couple of centuries, a fairer and more equitable agreement would
presumably have been based on what has since come to be called “contraction
and convergence”, aiming to bring, over a reasonable time period, the per capita
emissions of all countries to a common level that is below the threshold that
could cause unacceptable climate change.
However, given the asymmetries in negotiating strength in international
fora, the agreement actually adopted at Kyoto specified each party’s obligation in
terms of how much it must reduce its carbon dioxide emissions in comparison
with the levels that existed in that country in the year 1990. The Kyoto Protocol
is an unusual instrument of international law, operating on a principle — requiring
each party to make a percentage-based reduction in existing consumption levels
— that actually perpetuates the gross inequalities of energy consumption among
nations. The logic of this approach leads to the need to define “baselines”,
“additionality” and other concepts all of which introduce large amounts of
ambiguity, room for interpretation and ad hoc reasoning, usually biased in the
direction of short-term self-interest.
' Contraction and Convergence, Global Commons Institute
2 Boyd, E. et al (October 2007). "The Clean Development Mechanism: An assessment of current practice
and future approaches for policy".
As the Kyoto Protocol approaches the end of its validity and as the
international community prepares for designing its successor, the pressure on
the poorer nations to make commitments for cutting down on their carbon dioxide
emissions (i.e., fossil energy use) is inexorably building up. This pressure is
particularly heavy on China, India, Brazil, Russia, South Africa and other large
“emerging economies”. Again, as at Kyoto in 1995, there appears to be little
meeting ground for the different players. The developing countries emphasize
that they are the victims, not the perpetrators of the huge historical emissions
whose residues form the stock of greenhouse gases in the earth’s atmosphere;
that their emissions may be significant and growing, but so are their populations
— which means that per capita they are still below the industrialised countries by
orders of magnitude; and by any standard of fairness it is the developed
countries that have to take the primary responsibility for cutting down on global
carbon dioxide emissions. The industrialised countries claim that without some
reduction in the emissions from emerging economies, global change cannot be
contained within the desired limits.
This paper suggests that one common platform that would attract and
bring together almost all parties is the growing recognition that the global
economy, particularly in terms of its consumption patterns and production
systems, and the global population, in terms of its numbers and growth trends
are now out of balance with the limits of the global resource base. There are, of
course, a few states today, mainly in Europe and East Asia, whose economic
and demographic situation encourages them to promote pro-natalist policies —
but very few people hold the view that the world as a whole can support more
people at standards of living that everyone now aspires to. The global economy,
with an ecological footprint approaching 1.4°, is already using 40% more
resources than the Earth produces and it is difficult to see how this can be
sustained for long.
People, Resources and the Environment
Starting with Paul Ehrlich’s simple Identity, which relates environmental
impact (I) to Technological efficiency (T), per capita use of resources (Affluence)
and population (P), and relating impact with people and their lifestyles’, (which
has evolved tol =P xA xT). Subsequent variants have included the King
identity, the Kaya Identity and the Schellnhuber Identity, as quoted in
Schellnhuber 2008. To focus more closely on the impacts of factors that have
been largely neglected in past analyses such as population and sequestration of
greenhouse gases, the Identity would now need to be expanded to:
3 Global Footprint Network
* Ehrlich, P. R. & Ehrlich, A. H. 1990 “The Population Explosion”
EarthSafe Identity
TOTAL - Carbon Energy Service
x x Population - S
x Py ry
Carbon Energy Service Population
Carbon Energy Service Service
or Intensity Intensity Intensity VOLUME
| | J L\
Carbon =(I, x I x I, x P)-S
Substitution Efficiency Sufficiency/ POPULATION/
Lifestyle FORESTS,
ALGAE, ETC
Strategic Options
Much of the research, literature, policy studies and international dialogue
thus far have addressed Carbon Intensity and Energy Intensity issues, which
largely lend themselves to technological solutions and market-based action.
Governments, business and academia have focused primarily on these kinds of
initiatives. Carbon intensity is amenable to substitution by “cleaner” energy
sources, such as solar, wind, biomass and many other renewable fuels, as well
as conservation and demand side management. Lowering energy intensity is
achievable primarily by increasing the efficiency of our technologies and
production systems, primarily by miniaturisation, time-sharing and various other
measures to reduce bottlenecks and waste and to raise performance.
Lowering the Service Intensity, which requires changes in lifestyles and
consumption patterns, has been flagged primarily by civil society and individuals
with a social philosophy orientation, for whom today’s way of life is out of balance
with the limits of nature. Lacking quantitative analysis or enthusiastic support
from the dominant sectors of society such as government, business or the media,
these issues have not yet penetrated deeply into the official international
dialogue on climate change.
While the role of carbon sequestration, by forests, algae, soils and other
natural agents, is widely understood and accepted as a desirable goal, it too has
not yet become a legitimised instrument for mitigating climate change. Despite
strong campaigns for including REDD and REDD + initiatives in any post-K yoto
regime, the likelihood of such options being adopted is still somewhat remote.
The one factor that does not seem to be on the table at all is Population.
Virtually none of the literature or negotiations mentions the role of population as
relevant to global efforts to reduce carbon emissions or to mitigate climate
change in any way. The taboo on this subject seems to be deep and close to
complete. The only mention of population in mainstream discussions is the
assumption that the number of people on Earth in 2050 — or 2100 — will be “X
Billion” where X is a large number usually taken from the medium population
projections of the United Nations Population Fund. The general assumption
appears to be that the population in 2050 will be about 10 Billion and so the
carbon emissions will be commensurately high.
Hypothesis and Caveats
There appear to be considerable opportunities for reduction of carbon
emissions through accelerated development, which generally leads to the
reduction of desired human fertility; and, moreover, there are a variety of very low
cost interventions that can speed up both processes. Since birth rates in the
developed countries are already low, and in some cases even below
replacement levels, this approach applies primarily to the developing countries,
where the future impact on resources and climate due to population growth
would be severe.
The advantage of this is that the poor countries can, by adopting the
measures described here, take their rightful place in the climate change
negotiations as contributors of effective solutions rather than simply as deniers of
current of future responsibility. Moreover, they can legitimately demand financial
and other compensation for future emissions saved.
For the rich countries, the value of slowing down global population growth
is extremely high, since it is the only way they can hope that future global
emissions will be limited by all and thus lead to permissible limits on greenhouse
gas concentrations in the atmosphere in the long run.
But it should be clear that these solutions based on lowering population
growth cannot, at best, reduce carbon emissions by more than 25 to 30% of the
reduction that needs to be achieved if the global climate is to be stabilized ata
reasonable level. In the language of “wedges”, it can only account for one or at
most two of the seven wedges needed.
5 Stabilization Wedges: Solving the Climate Problem for the Next 50 Y ears with Current Technologies
S. Pacala and R. Socolow
Wedges ’
¢
¢
¢
14 1 Billion of Tons of Carbon , a Gtc/y
Emitted per Year
Majority of Wedges for
Action by the Rich
Historical
emissions amet
Flat path
1955 2005 2055
2105
iy
( )
The bulk of the carbon emission reduction will have to be achieved by and
within the global North on account of historical responsibility, resilience to climate
change built up through prior use of fossil fuels and existing financial capability.
There is no viable substitute on the horizon for the action that industrialised
countries must take to reduce their greenhouse gas emissions.
Secondly, in proposing the approach below, it is not the intention of the
authors to suggest that improvements in the lives of the poor, the women and the
marginalized in the developing countries is needed only for what they can do to
mitigate climate change. The poor, the women and the marginalized have an
intrinsic right to live better, longer and more fulfilling lives. This is a moral
imperative, as well as an ecological one. While education of boys is certainly
important, the emphasis here on girls’ education is simply in recognition of the
imbalances that exist between the genders and of the need to empower and
build the confidence and capability of those, often girls, who have little say in the
choices that most affect their lives. Rapid social change needs rapid
improvement in the ability of all to exercise their rights and entitlements.
The case made in this paper is that international development efforts can
and must be reoriented so as to solve both issues at the same time: bringing
about an equitable, fair and widely shared improvement in the lives of people and
by doing so, to achieve demographic outcomes that also serve to mitigate
climate change.
It is also our view that any opportunity that creates a “positive sum”, win-
win situation, however small, can act as an effective common ground to enable
the different sides to enter constructive dialogues that can take them beyond the
initial impasse.
New Versions of Old Insights
As far back as 1965, Professor Roger Revelle, who incidentally in an
earlier career as an eminent oceanographer first commissioned the studies that
discovered the rising levels of CO2 in the atmosphere®, had recognized that
population growth is not an exogenous parameter, but that it is heavily influenced
by social and economic factors; policy decisions can have deep impacts on
fertility, mortality, migration and other demographic variables’. It was his firm
understanding of the demographic transition process, as itis for the authors of
this paper, that population growth is no less a result of per capita GDP than itis a
determinant of it. Birth rates, in a particular society, are highly correlated with the
general wellbeing people feel in that society, with their aspirations and
expectations for the future and with the position of women in it.
An equitable, widely shared improvement in the lives of the people is a
sure route to smaller families. One way to accelerate or short-circuit this process
is to make direct investments in interventions that improve the quality of life of the
poor. As the UN Conference on Population in Cairo, 1995 clearly concluded,
such interventions include education for girls, livelihoods and jobs for women,
effective and access to female reproductive health services and similar gender
empowerment measures. Other strong determinants of human fertility have long
been known to include measures to reduce infant mortality and policies for old
age security. Itis also widely agreed that availability of electricity, light and
sources of domestic or community entertainment such as television provide
inexpensive distractions that can help occupy the time families spend together.
© Revelle, R., and H. Suess, "Carbon dioxide exchange between atmosphere and ocean and the question of
an increase of atmospheric CO2 during the past decades." Tellus 9, 18-27 (1957).
t Revelle, R, “Can Man Domesticate Himself?”, Bulletin of the Atomic Scientists Vol.XXII, No.2 ,
February 1966.
Though there may or may not be a direct causal link between improving quality of
life and reducing desired total fertility, itis possible to show that with an increase
in income (or energy, or any co-variant of per capita quality of life) the poor will
be able to make better use of existing resources and of their time®. For
example, an increase in income means that a poor family would be able to send
its children to school and provide lights at home for them to study by. Similarly,
they would be able to make use of more efficient technologies at home or in the
field and would also be able to gain better access to health services.
It should therefore be possible for developing economies to reduce birth rates,
and thus population growth rates by any number of means — accelerating the
delivery of services associated with development so that everyone is better off to
an extent that they wish to have small families. In the case of Sri Lanka, the
southern state of Kerala in India, and more recently Thailand, Korea, and the
other states of Southern India (Tamil Nadu, Andhra Pradesh and Karnataka),
various welfare measures enabled the respective States to simulate some of the
conditions that exist in a developed country and thus engendered the feeling of
wellbeing and hope for the future that leads to a desire for smaller families. In
the brief period of a decade or two, these economies were able to make it
through the democratic transition to a condition of almost replacement level
5 Over the past 27 years, Development A ltematives has created millions of livelihoods in impoverished
areas across India, most of these initiatives have focused on women — the quality of life and subsequent
drop in fertility of these regions has been drastic. Data on fertility, quality of life indicators is available on
request.
fertility - and as a result to accelerate real and sustained development for their
people as well.
Regions such as Sri Lanka, or parts of South India, which have successfully
lowered the rates of their population growth by focusing on improving quality of
life, should be able to claim credit for the significant contribution they are making
to reduction of greenhouse gas emissions.
The Model
The correlation between fertility and various parameters that represent
human wellbeing is starkly apparent from both the historical trajectory of fertility
in countries that have traversed the demographic transition and comparison of
the current data of all countries. Figure A shows the relationship between fertility
and per capita GDP.
Actual Fertility Vs GDP/cap
+ + Ae
g
$9 38s ohh % SEY: wee
8
7
76 y =-1.1572Ln(x} + 13.122
z. R2~ 0.75
8,
>4 ‘
= r
i, pe
4
0
0 5000 10000 15000 20000 25000 30000 35000 40000 45000
GDPicap ($/person)
Figure A: A plot of fertility (No. of Children per Woman) vs per capita Income for
all countries except OPEC members. Data from the UNDP Human Development
Report (http://www.hdr.undp.org)
The maps in Figure B show similar relationships for fertility with other social
welfare indicators such as enrolment of girls in schools, women’s employment,
etc.
Girls not at Primary School Girls not at Secondary School
Figure B: Parametric maps showing various gender imbalances worldwide. (©
Copyright 2006 SASI Group (University of Sheffield) and Mark Newman
(University of Michigan).)
Figure C shows that the demographic conditions in a country such as Viet Nam
(Fertility: 5 children per woman and Energy use: 500 Kg of Oil Equivalent per
person per year) can easily be changed to a fertility of 2 children per woman with
the addition of 1,000 KgOE/yr — bringing its family size close to that of Thailand
today. An even simpler and less expensive method would be to provide the
gender empowerment facilities identified by the Cairo Conference.
The cost of interventions such as creating schools for educating girls and
enterprises for employing women has been estimated from actual field data. Our
estimate for educating a girl to a level where she has options other than bearing
children is approximately $ 2,000.
Energy Consumption and the Demographic Transition
1000 2000 3000 4000 5000 6000 7000
Per Capita Energy (KgoE)
Figure C: A typical fertility transition curve.
Results
Running the model under different assumptions shows that it is possible to
end up with a world population by the target dates (2050 or 2100) that would be
well below the numbers that would exist if business were to continue as usual.
Using plausible assumptions on redirecting investments towards gender
empowerment and other interventions in the poorer regions of the world, itis
possible to imagine a world in 2100 that would have several billion fewer people
than is generally assumed today. By 2050, itis possible to redirect global
development efforts to save as many as 2 Billion births.
Total Population:
BAU vs 1000 Kg OE Transfer
Population (billions)
2008 aos mz 2038 20a 20s 2085
Time (years)
Today’s average emission of CO2 stands at roughly 2 tonnes per capita.
Assuming that each of the persons not born would have been responsible for 1
tonne of CO2 emission per year, and that he or she would have lived to an
average age of 60 years, the total saving per person would be 120 tonnes of
CO2. Ata value of $ 15 per tonne, this is close to $ 2,000 — more or less equal
to the investment made in her education.
If we include the savings due to averting the births of her children and
grandchildren up to the end of the target date, the investment actually yields very
high returns indeed.
In comparison with many of the other solutions currently under
consideration, this is an extremely low cost method to reduce carbon emissions.
In a 50-year simulation, the model puts the cost at around $ 10 to 20 per tonne of
C02 emission saved. With a 100 year time horizon, the costs actually come
down to well below $ 10. The latest estimates for Carbon Capture and Storage
come out to over $ 100 per tonne’.
° MOHAMMED AL-JUAIED, ADAM WHITMORE, "Realistic Costs of Carbon Capture", Discussion
Paper 2009-08, Energy Technology Innovation Policy Belfer Center for Science and International A ffairs
Harvard Kennedy School, Harvard University
The savings in CO2 emission from this kind of approach could reach as
much as 2 or more billion tonnes per year.
Relevance to Climate Mitigation
Activities that lead to reduced population growth, and as a consequence to
lower emission of CO2 should be just as eligible for recognition of their
contribution directly to mitigation or indirectly as carbon-offsets as are normal
engineering works that try to achieve the same results through improved
efficiency. Measurement of demographic parameters is a well-known science
and the number of births averted can be estimated quite accurately by measuring
the difference between what would have been the population had business-as-
usual trends continued and what was actually the case after the interventions.
The carbon savings achieved in this manner since, say, 1990 could be
allotted to the account of the country as part of its direct contribution to mitigation;
the carbon saving yet to come could be the source of CDM or other carbon offset
money to be used directly for the kinds of activities described here.
Conventionally, carbon offset money is paid after the offsetting activity has been
completed, verified and approved. This convention could be changed to provide
front-end capital for setting up schools, enterprises, etc — or alternatively the
future expected revenue streams could be securitized into a bank loan, which
would be repaid from the carbon offset earnings when they materialize.
To be eligible for carbon offset or mitigation benefits, projects have to pass
the “additionality” test, which shows that the reduction in greenhouse gases it
results in would not have taken place without the incentives provided by those
benefits. Given the time it takes for societies to move through the demographic
transition and the well-known barriers they normally face in this process, fertility
reduction resulting from female empowerment certainly meets the additionality
requirements. In fact, given its inherent grounding in the behaviour of the family
and community, it should be taken as an archetypal gold standard mitigation
action.
Conclusion
The model, based on System Dynamics methods, shows that there is a
strong prima facie case for redirecting international development efforts towards
eradicating poverty and particularly at improving the lives of women in developing
countries. Preliminary calculations show that $ 1 spent on such programmes
would yield more carbon emission reduction than $ 10 spent of engineering
solutions such as Carbon Capture and Storage.
Needless to say, improving the lives of the poor, and particularly the
women and children living in extreme poverty, is an imperative in its own right,
and from many viewpoints — the moral, the ethical, the social, the ecological and
the practical. It is also one of the least cost ways of achieving goals that currently
can capture the support of global decision-makers. The argument presented in
this paper, based on a quantitative analysis of the relationship between human
fertility and specific development interventions that emphasize gender
empowerment, shows that rapid, equitable development is also crucial to reduce
carbon emissions, stabilize the climate, reduce the pressures of humankind on
nature and its resources, and save life on Earth.
The systemic analysis summarized above shows that there exists a possible win-win
strategy that can bring the competitors in the current game to play to agreed, logic-
based and consistent rules. These rules would be designed to overcome the
consumption-population related stand-offs that exist today.
The analysis shows conclusively that, counterintuitive and paradoxical though it
might appear, accelerating the removal of poverty throughout the world, involving
access by the poor to higher energy services, not lower, provides the surest and
least cost transition path to mitigating climate change. Depriving the poor of a
better life can only be severely counterproductive for achieving climate mitigation
goals.
Annex: The Model
Introduction
In a world of growing complexity, often neither the lessons of history nor
“common sense” is adequate to help us understand the causes and effects that
determine the outcomes of human interventions. Systems Thinking is a scientific
art that facilitates rational analysis and clarity of understanding that permits us to
make better decisions.
The more specific science of System Dynamics offers a powerful method to
characterize the functions and behaviour of real world structures. The work of
J ay Forrester, father of System Dynamics?° demonstrated the value of this
method in applications as varied as complex urban communities, multi-faceted
industries and global societies. World3, the original global dynamics model,
(further refined by Meadows et al.!!) shows the growth of economy and
population in a world constrained by resources and pollution. The methodology
has since been refined through several generations of elaboration, testing and
application.
The world today is beset by many successive socio-economic structural failures
and concurrent crises. Of these, perhaps the most pressing one is that of climate
change, recognized widely to be the result of increased levels of greenhouse
gases in the atmosphere, which in turn result from anthropogenic emissions of
these gases, primarily from the burning of fossil fuels. The final result is that
these changes in the climate now threaten to destroy our life support systems.
The solutions discussed thus far have been largely limited to technological
improvements and lifestyle changes. Very little attention has been given to the
effects of population growth.
The EarthSafe Model, Ver 1.3
Objective: CO2 emissions are an indicator of our planet's poor health. This
model seeks to quantify the effect of population dynamics on the amount of CO2
released annually into the atmosphere and improve the quality of life of those
living in its poorest regions. .
Version 1.3 of the EarthSafe model represents a world comprising 4 Regions
defined economically rather than geographically (Very Poor, Poor, Medium and
Rich countries). Each region is further divided into 3 classes: those who live in
the poorest (L Class), middle (M Class) and rich (U class) income groups, as
determined by data.
»° Jay Wright Forrester, “Industrial Dynamics” (1961) “Principles of Systems” (1968)
™ Dennis L. Meadows, Donella H. Meadows, | orgen Randers, William W. Behrens, ‘The Limits to growth: A report for the
Club of Rome's Project on the Predicament of Mankind” (1972)
Regions of the World
Each Region of World
Population Living in Lowest
income Class of Society *L
fas"
Population Living in
Medium Income
WA Class “M Class’
A income Class, "U Class
Figure 1
+ Population
oO
a Births/Y ear
a Fertility
QOL (or GDP/cap)
Figure 2 Causal relationship between quality of life and population growth
For a first approximation, as in most standard Economics texts, and without loss
of relevance to real world behaviour where environmental carrying capacity
poses no constraints parameters such as food, water, land or pollution have
been omitted. Resource consumption, however, is fundamental to our model as
is the relationship between population growth and quality of life — factors that are
introduced in later versions of the EarthSafe model.
What Determines Population Dynamics?
Data from the UNDP Human Development Report and the World Bank
Database, showed clear relationships between population growth and various
indicators of quality of life; Figure 2 demonstrates, for example, the strong
correlation between total fertility (number of children per woman) and per capita
GDP.
Actual Fertility Vs GDP/cap
8
7
a6 y = -1.1572Ln(x) + 13.122
°
z. R2~ 0.75
a
2 4
= 3 —
uw 24 + tags +
4 ry ey 2) .
0
ie} 5000 10000 15000 20000 25000 30000 35000 40000
GDP/cap ($/person)
Figure 3 (representation of best fit trend line)
Data from UNDP/HDR and WDR. All countries included, except OPEC
Historically, under normal economic circumstances, the drop in total fertility has
invariably followed the rise in per capita GDP. Itis not unreasonable, therefore,
to infer that the changes in per capita GDP are driving the changes in fertility.
Moreover, the data show that the curve of total fertility vs GDP is very steep at
low per capita GDP and flat at high per capita GDP. This means that even small
changes in GDP at the lower end can lead to very high changes in fertility.
The model incorporates the normal growth expected in per capita GDP, which
generally leads to a gradually declining fertility, as has been observed in all
regions of the world in the recent past.
To accelerate the fall in total fertility directly, itis possible to further increase the
GDP growth, either through policies designed to prioritize expenditures on
industrialisation, agriculture, etc, or with external funds mobilized for this
purpose.
45000
Fertility (medium)
: “a +
Population Population
“L” Class @ “M" Class
‘ +
# of girls who can go to next level Y
Saving in CO2
Fertility (very high) Sans from births
Cost to Educate Girls / averted
Employment of women /
Televisions / Lights /
Family Planning
Services
Funds from Global taxation of CO2 Excess
Emissions
Figure 4 Interaction between lower and medium income classes in a region
Low Cost Intervention
Analysis of data shows that population growth is significantly higher in regions of
low economic development. Accelerated population growth is the result of
contributing factors such as the effect of perceived mortality on total fertility; for
example, if a family believes that two out every four children born will die as
infants, the family will have more children to compensate”.
Verion 1.3 of the EarthS afe model will focus on the interaction between two
classes of each region; Figure 4 represents the “L class” and “M Class” of each
region; M Class, has higher per capita GDP and lower total fertility relative to L
Class.
Itis also possible to achieve the goal of fertility reduction indirectly by enabling
young women in the L Class to achieve a better quality of life through, for
example,
Schools for education and vocational training of girls
e Enterprises for employment of young women
e Improved reproductive and health care facilities
°
e
Electricity for domestic lighting and television
Etc
Such interventions can, at very low cost, help the movement of people from the L
(high fertility) class to the M (lower fertility) class (Figure 4).
The cost of any of these interventions and the funds available for them determine
the number of girls who can participate in any region. Experience shows that
12 “Dynamics of Growth in a Finite World”, by Dennis L. Meadows (Author), William W., III Behrens (Contributor) discusses, in
detail, the principle of compensatory births and the effects of perceived mortality.
such costs can be quite low, enabling large numbers of people to cross the
demographic transition in a short period of time.
+, a
# Births/Y ear Fonulation
Fertility
Current CO2/cap Emissions of Class +
Limit CO2/cap for = _|_
Kegon # regions
Funds invested by Se
State, Pvt. Sector
Fraction of funds from taxation
invested in region VPC, PC
CO2/cap Emissions in Excess
2050
Unit
tax
+
Funds, e.g. from taxing
QOL/cap or covariant for VPC, PC Excess CO2/cap from al
Figure 5 Overall feedback structure of model
Financing Fertility-Reducing Interventions
One possible policy by which funds can be raised for low cost intervention
methods would involve taxing regions whose per capita CO2 emissions (metric
tons per person per year) are above the critical threshold level and then
redistribute these funds to poorer regions (Figure 5).
UNIT TAX PER MTON CO2 EXCESS
20
15
10
USD/CozTons
0
2005 2011 2017 2023 2029 2035
Time (Y ear)
2041
2047
UNITTAX PER MTON C02 EXCESS: COZTAXUSD20
UNITTAX PER MTON C02 EXCESS: COZTAXUSD10
UNITTAX PER MTON C02 EXCESS: CO2TAXUSDS
UNITTAX PER MTON C02 EXCESS: COZTAXUSD1
UNITTAX PER MTON CO2 EXCESS: BASE CASE
Figure 6
The critical per capita CO2 emissions for 2050 are calculated by examining the
relationship between these emissions and the concentration of CO2 that remains
in the atmosphere, and relating this concentration to the desired atmospheric
temperature rise in 2050.
Contraction and Convergence
PRPS SSE
SERRE RSB ESS Sree
2005 2011 2017 2023 2029 2035 2041 2047
Time (Y ear)
w
~
a
Co2Tons/(people*Y¥ ear)
=
SG wp
a wo
"CO2/cap EM ISSIONS L CLA SS"[VPC] : BAU
"CO2/cap EMISSION M CLASS'[VPC]: BAU
"CO2/cap EMISSION U CLASS'[VPC]: BAU
Figure 7 Per Capita CO2 Emissions for the three classes in the very poor region
Contraction and Convergence: Due to historical responsibilities and technological capacities,
classes with high per capita CO2 emissions will reduce their levels of pollution, whereas classes
with low emissions will, over time and with access to newer technologies, asymptotically increase
their emissions to the level that is acceptable. The model achieves this phenomenon through a
first order goal-seeking adjustment.
To calculate total CO2 savings, an analytical method has been developed to
estimate future births averted from such interventions. For each girl who makes
the transition from L Class to M Class, itis possible to calculate the number of
births that did not take place because of the reduction in her desired total fertility,
which resulted from the intervention. This figure allows us to calculate the
cumulative CO2 emissions averted; the ratio of the cumulative costs of this
policy, to the CO2 emissions averted, gives us the cost of abatement per ton of
cO2.
In this version of the model, the key determinant for fund raising is the unit
penalty (tax) charged per excess CO2 ton of emissions. Other assumptions are:
TABLE 1: Initial Conditions?
[Class CO2/cap (metric
tons) Emissions
M Class CO2/cap
Emissions
U Class COZ/cap
Emissions
L_GDP/cap (USD/person)
M_GDP/cap (USD/person)
'S Death Fraction
(people/people/year)
M Class Death Fraction
(people/people/year
U Class Death Fraction
(people/people/year
Initial Global P opulation, ~ 6 Billion People
cost per girl
« — Cost of educating for a girl, USD 2000/person
* Time to complete education, 5 Years
Per Capita GDP growth rate 1% forL Class, 3% for U Class
~ 30% of population is female of reproductive age for each class, each region
Funds distributed: 67% to VPC Region, 33% to PC Region
Reasonable values for Unit tax, from USD 1/MtonCO2 to USD 20/MtonCO2
Number of girls who can benefit from the program is limited by the minimum time needed to educate girls and
Table 2 Sample of results (Taxation Policy in effect from 2010-1030):
Variable Base Case | Tax (lower Tax: USD5/per | Tax: USD10/ per
(No tax) limit): USD1/ capita excess capita excess
per capita Mtons CO2 Mtons CO2
excess Mtons
co2
Global Population at 2050 12.48 12.09 11.6 10.84
(Billion people) Figure 13
Global Anthropogenic Co2 29.70 29.70 29.70 29.70
Emissions at start of model
(Billion Mtons of CO2/Y ear)
Figure 9
Global Anthropogenic Co2 35.96 35.68 35.14 35.13
Emissions at end of model
(Billion Mtons of CO2/Y ear)
Figure 9
Approx. Number of girl births 0 0.45 1.31 1.34
averted at end of model
(vPC]
(Billion people) Figure 8
13 Estimated from various data sets: UNDP HDR, World Bank, IEA
Cumulative Funds Raised 0 1.15 5.9 10*
for region [VPC] over entire
run
(Trillion USD)
Cumulative Funds Spent on {i} 1.03 1.90 2”
Educating Girls over entire
run of model [VPC] (Trillion
USD)
Cumulative Funds available 0 0.12 4 chad
for other intervention
methods over entire run of
model [VPC] (Trillion USD)
* Average Funds Available 0 3 100 200
per Year (Billions of
USD/Year)
* Cost of Abatement at 0 14.27 14.27 14.27
end of 45 Year model
[VPC] (USD/MtonsCo2)
Figure 10
Cumulative CO2 Averted by 0 ¥ 45,28 131.19 134.48
end model (Billion
MtonsCo2 over 35 years)
Percent of people living in L =60 =60 =60 =60
Class at start of model
(VPC](DMNL) Figure 14
Percent of people in L Class 78 64 29 28
at end of model [VPC]
(DMNL) Figure 14
Cumulative # of Girl Beneficiaries
1B
750M
2005 =. 2011 2017 2023 2029 2035 = 2041 2047
Time (Y ear)
“Cumulative #of girls who have benefited till date'[VPC] : USDTA X20
“"1: Average funds available per year (Trillion USD/Year) =
{Cumulative Funds Raised for region [VPC] over entire run (Trillion USD) - Cumulative Funds Spent on Educating Girls at over entire run of model [VPC] {Trilion USD}
{Final Time — Start Time of Policy Years}
The difference between the “cumulative funds raised” and the “cumulative costs” involved in implementing low cost programmes gives as an idea of the amount of funds
available for other intervention programmes to reduce CO2 emissions. Divide this figure by the time between the end of the model and the start of the intervention to get
the average funds available per year for other programmes
*2: In the 95 Year simulation, the cost of abatementiis one fith ( ~USD 3) that of the 45 year run ( ~USD 14); the number births averted is almost five times as much
*3: 72.15 Billion MtonsCO2 Averted is equivalent to an average of 3.36 Billion MtonsCo2 Averted per Year (for the 20 years that the policy is in effect)
* Cumulative funds raised from taxing excess per capita CO2 emissions (over entire run), cannot reasonably exceed 10 trilion dollars, which is defined as the upper limit.
Coupled with a maximum number of girls that can benefit from intervention, the upper limit for annual funds available for other methods cannot exceed 8 trilion dollars.
+k Please note that the figures in the table above represent exponential growth with no effect of feedback of capacity constraints
Figure 8
The figure above demonstrates the effect of various values of penalty tax on the
number of possible girl births averted in Very Poor Countries. The policy is
introduced in 2010 and lasts till 2030; after that there are no more girls to benefit.
The interplay of declining fertility rates (due to increasing per capita GDP and
proportionally adapting goals for desired fertility) reduces the cumulative number
of girl births averted towards the end of the model run.
Note that girl births averted results in diminishing returns for penalties greater
than USD 5/ Excess Mton CO2; if the total number of beneficiaries is greater
than the maximum number of girls that can be educated by the system, the rate
of outflow from one class to the next will be that of the maximum capacity of the
system.
The analytical method for calculating approximate total number of girl births
averted and CO2 savings: PLease NOTETHE MESSAGE OF THIS PAPER IS TO IMPROVE QUALITY OF
LIFE AND THUS REDUCE A POOR COMMUNITY'S DESIRE TO HAVE MORE CHILDREN
First Generation of Births Averted = (Girl going to M Class) * (Current Difference in Fertility b/w both Classes) * (Average Number
of girls born per woman) {people}
Current Difference in Fertility = (Current Fertility of L Class) — (Current Fertility of M Class) {births/)woman}
Successive Births Averted = (First Generation of Girl Births Averted) * (Current Fertility of L Class) * (Average Number of girls born
per woman) {people}
“N” Number of generations of births averted = (Time of Model Simulation) / (Average time for each generation to reproduce)
{damn}
Average time for each generation to reproduce = 25 Years {years}
Total Number of Girl Births Averted by One Person= [First Generation Births Averted + (Successive Births Averted)“"» ] *
(Probability of Survival of Child) {people}
Cumulative Number of Births Averted = | [(total beneficiaries each year) * (total births averted by one girl that year)] dt {people}
Integrated over model lifetime
Total Co2 Savings = Average Co2/cap Emissions * Cumulative Number of Births Averted
{Co2Tons} = {Co2Tons/person} * {people}
ANNUAL ANTHROPOGENIC ADDITION OF CO2
37.258
CozToney ear
25.58
2005 08 Di De iT 20 DB Bay DE DH DS 2038 Evy Err aT 50
Time (¥ ean)
‘cumulative anthropogenic rate of addin of CO2 :BAU
‘cumulative anthropogenic rate of addon of CO2 : USDTAX1
‘cumulative anthropogenic rate of addon of CO2 : USDTAXS
‘cumulative anthropogenic: rate of addon of CO2 : USDTAX 10
‘cumulative anthropogenic rate of addition of CO2 : USDTAX20
Figure 9
The behaviour of annual anthropogenic CO2 emissions over time is somewhat
counter-intuitive (Figure 9); as the amount of the penalty increases, emissions
initially increase relative to the base, but then start to decrease and eventually
end up lower than BAU over the course of the simulation. The reason for the
initial increase in emissions is that intervention takes people from a low income
class (which has low CO2/cap emissions) to one which is higher (with higher
CO2/cap emissions); however, simultaneously, per capita CO2 emissions for
high income classes also approach the critical limit due to efficiencies — the net
result is that cumulative CO2 emissions eventually drop below the business as
usual case.
COST OF ABATEMENT
2005 2011 2017 2023 2029 2035 2041 2047
‘Time (Y ear)
cost of abatement[V PC]: BAU
cost of abatement[V PC]: USDTAX1
cost of abatement[V PC] : USDTAX5
cost of abatement[V PC] : USDTAX10
Figure 10 [50 Year Simulation]
When the policy comes into effect in 2010, the cost of abatement (in for example,
Very Poor Countries) rises briefly to a maximum but settles at a low constant
value after some time. The reason for the initial rise is that cumulative funds
raised from taxation begin to increase immediately after the policy comes into
effect, but there exists a delay due to the time it takes to educate a girl (five years
for the first lot of girls to graduate). After the fifth year of introducing the policy,
the ratio of cumulative funds to cumulative young women who have passed
through the program (or CO2 averted) is constant.
COST OF ABATEMENT
‘
me EN
Tin
cost aatenV PC]: 100° RUSDTAXS
‘ostf abatement PC]: 10 RUSDTAXIO
Figure 11 [100 Year Simulation]
As shown in figure 11, the longer the time for the simulation, the greater the number of births
averted (see analytical solution above), which results in a lower average cost of abatement.
Selected Variables
800M
= 400M
0
2005 = .2011 2017-2023) 2029 2035. 2041 2047
Time (Y ear)
Population L CLASS[RC]: BA U
[RC]: USDTAX1
L
L
Population L CLASS[RC] : USDTAXS
Population L CLASS[RC] : USDTAX10
Population L CLASS[RC] : USDTAX20
Population MCLASS[RC]: BAU
Population MCLASS[RC]: USDTAX1
Population MCLASS|
it
[Ri
Population MCLASSIR
Population MCLASSIR
\C]: USDTAX20
Figure 12
In this version of the model, the demographics of the rich regions (Figure 12,
RCs and MCs) are not sensitive to the unit tax parameter; funds raised from
taxing excess consumption are not re-invested in these regions (though in other
versions of the model this does not have to be the case). The only factor which
changes the fertility for this region is the growth of per capita GDP.
POPULATION "L CLASS"
3B
2.35 B
o
& L7B
g
1.05 B
400M
2005 = 2011 2017. = 2023, 2029) 2035) 2041 2047
Time (Y ear)
Population L CLASS[VPC] : BAU
Population L CLASS[VPC] : USDTAX1
Population L CLASS[VPC] : USDTAX5
Population L CLASS[VPC] : USDTAX 10
Population L CLASS[VPC] : USDTAX 20
POPULATION "M CLASS"
650M
BILLIONS OF PEOPLE
i
a
w
200M
2005 =. 2011 2017 = 2023-2029. 2035S 2041 2047
Time (Y ear)
Populaion M CLASS[VPC] : BAU
Populaion M CLASS[VPC] : USDTAX1
Populaion M CLASS[VPC] : USDTAX5
Populaion M CLASS[VPC] : USDTAX 10
Populaion M CLASS[VPC] : USDTAX 20
Figure 13
The populations of the poor regions (Figure 13, VPCs and PCs) on the other
hand, are very sensitive to the unit tax parameter. Depending on its value, the
population living in L Class (below an acceptable quality of life) decreases quite
dramatically during the implementation phase of the policy. As the policy comes
into effect, it opens up the flow between the lower and middle classes thereby
decreasing the number of people in the poorer segment and increasing those in
the higher segment. As the class of people with higher per capita GDP have
lower fertility, their contribution to the cumulative growth of population is far less
than that of the poorer class of the region and as a result, global population
(Figure 14) decreases relative to the base case.
Furthermore, as seen in the following graph (Figure 15), the fraction of population
living below an acceptable quality of life in the very poor region decreases quite
significantly as a result of the policy.
Total Global Population
6B
2005 = «2011-2017, 2023) 2029) 2035. 2041S 2047
TIME (YEARS)
total global population : BAU.
total global population: USDTAX 1
total global population: USDTAX 5
total global population : USDTAX 10
total global population : USDTAX 20
Figure 14
DMNL
FRACTION POPULATION LIVING IN L CLASS
0.8
0.6
0.4
0.2
0
2005 2011 2017 2023 2029 2035 2041 2047
Time (Y ear)
fraction ofpopulation living L CLA SS[VPC]: BAU
fraction ofpopulation living L CLA SS[VPC]: USDTAX1
fraction ofpopulation living L CLA SS[VPC]: USDTAX5
fraction ofpopulation living L CLA SS[ VPC]: USDTAX10
fraction ofpopulation living L CLA SS[VPC]: USDTAX20
Figure 15 Fraction of population living in L Class relative to total population of the VPC region.
Other variants of the model show what would happen if
external funding, not raised through excess per capita CO2 emissions,
were to be contributed directly to fertility control measures for the
population living below acceptable quality of life in the poorer regions.
Portions of the funding were to be redistributed back to the developed
countries as incentives to reduce consumption?
Resource constraints were applied and what would be the scenarios
under which collapse could be averted?
POPULATION STRUCTURE OF EARTHSAFE MODEL (Similar for each Region)
PECRADE OE pone
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LOOKUP OF EFFECT PERCENTAGE OF WOMEN Yn L © osu
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C02, TAXATION STRUCTURE OF EARTHSAFE MODEL
(Similar for each class in each region)
MODEL AND MODEL EQUATIONS AVAILABLE FOR
DOWNLOAD FROM THE FOLLOWING WEBSITE:
www.earthsafeonline.com/esmodel.zip
