Chapter II . Impacts of Climate Change on Human and Natural Systems
Professor Planck, of Berlin, the famous originator of the
Quantum Theory, once remarked to me that in early life he had
thought of studying economics, but had found it too difficult!
Professor Planck could easily master the whole corpus of
mathematical economics in a few days. He did not mean that!
But the amalgam of logic and intuition and the wide knowledge
of facts, most of which are not precise, which is required for
economic interpretation in its highest form is, quite truly,
overwhelmingly difficult. – J. M. Keynes (1933)
The first act of our drama has recounted how scientists have uncovered the fact
that we are changing our global climate – that the unintended actions of our daily lives
as we drive our cars and heat our homes and watch our favorite TV shows have vast
and long-lasting impacts on the world around us. We now turn to the second act, which
is to map out the impacts upon human and non-human societies of those changes.
We say that predicting future climate changes is a truly monumental task
because of the complexity of the interactions among the different parts of the
atmosphere-ocean-biosphere system. We now turn from the hard sciences to what
might be called the “very hard sciences,” understanding and predicting how human
activities as well as natural systems will respond to climate change over the coming
decades and beyond. Of all the issues involved in global warming, this is the most
difficult one and subject to the greatest uncertainty.
Figure II-1 uses our little flow diagram to indicate where we are in the circular
flow of global warming science, economics, and politics. Having described the climate
system in the first chapter, we now discuss the impacts of global warming on different
systems – both natural and human.
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Chapter 2’s coverage
Rising CO2 concentrations
along with other
greenhouse gases lead to
climate change
(temperature, precipitation,
sea-level rise, …)
Economic activity and
fossil-fuel use leads to CO2
emissions (driving, air
conditioning,
construction,…)
Climate-change policies
adopted to reduce
emissions and adapt to
warmer world (carbon
taxes, cap-and-trade,
regulations,…)
Climate change imposes
ecological and economic
impacts (farming, coastal
structures, species loss,…)
Figure II-1. Schematic of coverage of Chapter 2
This chapter discusses how climate change will affect different earth and human
systems.
______________________________________________
Impacts for our grandchildren
It is good to begin by thinking about how the current analysis might look to you,
our grandchildren, looking back on this period from several years in the future. You
have read our assessment of the science in the last chapter. You might first start by
asking whether we correctly understood the science – both the natural and the social
science aspects. Did we miss something really important?
Then, after you read this chapter on impacts, you might ask, Did we
overestimate the vulnerability of ecosystems and the resilience of economic systems?
You might then consider whether historical forces simply overwhelmed our efforts.
Technological change may have made global warming much worse (say because
someone invented a personal airplane that drinks fuel) or much better (perhaps because
of some fundamental breakthrough in non-fossil energy technologies). Perhaps the
horsemen of the apocalypse of famine, war, and pestilence made global warming a
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minor issue in the survival of humans. Or perhaps our projections proved reasonably
accurate.
Then, as you reach the final chapter, you can ask whether we were able to meet
the challenge. Did the world’s richest country, the United States, take the first steps to
slow its CO2 emissions? Or was it continually locked in partisan wrangling between
warring schools of doomsters and deniers, and caught in the vice of well-funded lobbies
who prevented even the smallest steps? Did China and India join the effort, or were
serious policies limited to a few rich countries of northwest Europe?
These are the questions that you might ask yourself as you read this assessment
made in 2010. As you judge our efforts, remember that we, like people in every
generation, are prisoners of our times, our cultures, our received wisdom, and even our
interests. We try desperately to escape from these prisons. Did we?
An Overview of Impacts Analysis
Four central issues for impacts
Before beginning our assessment of the impacts of climate change, we need to
frame the issues. The first and central point is that concerns about climate change are all
about impacts. The average mean surface temperature of the earth per se is of no
intrinsic concern any more than is the temperature on the moon or Pluto. We are
concerned about the effects of warming and other physical changes on physical,
biological, and human systems. This central point implies that sensible policies will
depend upon our assessment of the many costs, benefits, thresholds, and plateaus in the
many areas that are affected by climate change.
The second point is that reducing impacts of climate change will impose costs.
The costs of climate-change policy reflect the fact (at least today) that reducing CO2
emissions will require using costlier technologies and therefore reduce real incomes. For
example, a low carbon economy might require much more fuel-efficient cars. We can
indeed improve fuel efficiency, but we will need to spend more on the car. For example,
a hybrid gas-electric car might improve fuel efficiency by 10 percent, but the costs of the
batteries and other systems might cost $3000. We will examine the costs in more detail
in the next chapter, but the basic point is that (at least after some point) reducing
emissions will require sacrificing goods and services in other areas.
The third point – which is more controversial – is that sensible global warming
policies will require some balancing of costs and benefits. This point is actually quite
intuitive. We could stop global warming in its tracks by banning all fossil fuels today. I
know of no one what advocates such a policy – both because it shares a level of
wackiness with advocating shooting down UFOs, but primarily because it would be
extraordinarily expensive. At the other pole, we could do nothing at all forever. Some
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people actually do appear to take this position, but that proposal appears to me to
extremely myopic or disingenuous. So policies must lie somewhere between wrecking
the economy and wrecking the world. I will discuss some ideas about how to balance
the objectives of economics and the environment in the next chapter, but the basic point
is that some kind of balancing is required.
The final question is whether, after a careful weighing of objectives, a firm target
for policy emerges. I call this a “focal policy” because it is a policy that is obvious or
consensual. Most people would agree on focal policies such as no AIDS, no smallpox,
no financial collapses, no nuclear meltdowns, and no nuclear wars. For climate change,
there is a great temptation to create focal policy targets as well because that
tremendously simplifies analysis and policy. Setting a firm target would be sensible if
there is a threshold beyond which all sort of dangerous effects appear. Indeed, our
review of tipping points in the last chapter suggested that the many serious tipping
points would potentially be encountered when global temperature passes 3 °C. As we
will see in the next section, there has been a serious attempt to establish a focal policy
for global warming at 2 °C. The next chapter will examine whether such focal policies
have a good analytical basis.
Current approaches to targets
Scientists and nations have been struggling to understand the dangers of
unchecked climate change for several years. Where do we stand as of 2010? Here is a
very brief summary.
The framework for all climate change deliberations is the United Nations
Framework Convention on Climate Change, ratified in 1994. The objective was stated as
follows: “The ultimate objective … is to achieve … stabilization of greenhouse gas
concentrations in the atmosphere at a level that would prevent dangerous
anthropogenic interference with the climate system.” This lofty goal is unfortunately
extremely vague, because there is no definition or way to determine what would be a
“dangerous anthropogenic interference.”
Over recent years, scientists have refined this concept. In the first set of
international agreements, in Kyoto in 1997, countries agreed on climate policies but not
on any recognizable objectives. They agreed to cut emissions but had no target for
climate change or even for long-run goal for emissions reductions in the agreement.
Take a time ship forward for 13 years to the meeting in Copenhagen in December
2009. This meeting failed to agree upon policies extending the Kyoto Protocol. But it did
adopt a target for climate policy. In the Copenhagen Accord, countries recognized “the
scientific view that the increase in global temperature should be below 2 degrees
Celsius.” [1] This was the first time that any policy target had been established at an
international level, and in this respect it is a major advance. Was the 2 °C target based
on a strong body of evidence that suggests that there is a threshold at 2 °C? Is there
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strong evidence that there would be “dangerous” or at least serious consequences if the
earth’s climate system passes this threshold? Was there an attempt to balance the
dangers with the costs? These will be among the important question addressed in the
chapters that follow.
The Economic Fundamentals
Global Warming as an Externality
Before plunging into a discussion of different impacts, I begin with some
fundamentals of the economics of climate change. The economics of climate change is
straightforward. Virtually everything we do directly or indirectly involves the
combustion of fossil fuels, producing emissions of CO2 into the atmosphere. The carbon
dioxide accumulates over many decades and leads to many potentially harmful
impacts. But those who produce the emissions do not pay for the privilege, and those
who are harmed are not compensated. Unlike the pain and benefits of a market activity
like producing and enjoying a slice of pizza, the costs and benefits are external to the
market. They are therefore called “externalities”—i. e., interactions whose values are
not reflected in market transactions.
Economic life is full of externalities. Some are harmful, such as when someone
dumps garbage on your lawn; others are beneficial, such as when a researcher discovers
a polio vaccine. But global warming is the monster of all externalities because it
involves so many activities, affects the entire globe, and does so for so many decades
and even potentially centuries.
Economics teaches one major lesson about externalities: Markets generally
operate inefficiently in the presence of externalities. In the case of harmful externalities
like pollution, markets will produce too much. There is no invisible hand that will
correct these market failures. Governments must step in and regulate or tax the activity.
(Recall the dashed arrow in Figure II-1, which represents a non-market or non-natural
intervention.) Global warming is no different from other externalities; it requires
affirmative governmental actions to prevent the harmful spillovers.
However, there is one respect in which global warming differs from externalities
like water pollution or toxic wastes or drunk driving. It is a long-lived (or stock) global
externality, one whose impacts are indivisibly spread around the entire globe for long
periods of time. These features of global warming will occupy us in the next chapter
when we consider the politics of dealing with global warming.
The ABCs of impact studies
The central question we need to deal with in thinking about policies to deal with
global warming is, What damaging consequences might occur if global warming
continues unchecked? It will be useful to describe how scientists undertake impact
studies. The methodology of impact studies is straightforward and comes in three steps:
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A) First, we draw upon the modeling projections from the climate scientists to
calculate the impact of global warming for a particular time, place, and sector
on variables such as temperature, precipitation, sea level, and so forth.
B) Second, we estimate an “impact multiplier” that indicates how much that
sector-time-place would be affected for every unit of climate change.
C) Finally, we need to estimate the size of the sector in the target year.
The total impact is then the product of A x B x C. We then take the product of the
change in the climate times the impact multiplier times the size of the sector, and that
yields the total impact for a given time-place-sector.
ABCs for agriculture in Africa
We can illustrate the ABC methodology using one of the most carefully studied
sectors, agriculture. For this example, we rely on a compilation of studies by the IPCC.
Studies tend to concentrate on a scenario with 4 °C local temperature change. We take
this scenario and apply it to low-latitude regions such as sub-Saharan Africa and use
wheat as the crop. Let’s go through the ABCs of this example.
A’) Start with a set of climate models that has a good track record and have
detailed regional resolution. According to climate model calculations, the mean
temperature increase for low-latitudes (which we use for sub-Saharan Africa) is
very close to that for the world as a whole. The 4 °C increase is estimated to occur
around 2120 in the Yale-RICE model.
B’) According to the IPCC compilation, the yield for wheat in low latitudes is
nonlinear, but is estimated to decline by 18 percent when the local temperature
increase is 4 °C. (You can look at the graph from which this is drawn discussed
later in the chapter as Figure II-9.)
C’) We then finally need to estimate the output of wheat in 2120. The requires
estimates of African GDP, the share of agriculture in GDP, and the share of
wheat in agriculture. A rough estimate yields total production of wheat of $260
billion in 2120 in 2005 U.S. dollars.
Applying the ABC methodology, we estimate that global warming with cause a
decline in African wheat production of $47 billion in 2120. [2] Using historical trends,
this would imply a loss of about 0.07 percent of GDP for Africa from wheat yield
declines at a 4 °C warming. This represents an infinitesimal decrease in the average
growth rate for Africa over this period – a decline of 0.0007 percent per year in the
average growth rate. This would compare with an assumed growth in per capita
consumption of 3.5 percent per year over the period. [3]
Your first reaction to this example is probably that this is an absurd exercise.
How can we possibly know the growth of African GDP, the share of agriculture, the
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share of wheat in agriculture in 110 years? Should we not also note that the studies
predict anything from a yield decline of 60 percent to a yield increase of 30 percent?
Perhaps you might ask, Why not focus on something a little closer at hand,
perhaps 2030 or 2050? Fair enough. If we take 2050, models suggest that unchecked
emissions will lead to about 2 °C warming. If we consult our studies shown in Figure II9, we see that the average of the studies suggests that African wheat yields including
the CO2 effect will actually improve by about 5 percent.
This example is useful for a number of points. First, it illustrates the ABC model
of impacts. Second, it also shows the long chain of reasoning that is involved in
calculating impacts. Third, it illustrates how uncertain impacts can be and that we may
not even know whether impacts are positive or negative for some sectors. [4]
You might be tempted to throw up your hands at this stage and simply say,
“Let’s stop here. Just stipulate that the impacts are terrible and figure out a way to stop
all this madness. With all the uncertainties and tipping points and potential problems,
we don’t need any of these dubious economist’s exercises. Just say no.”
There are two problems with this reaction. First, someone might say, “I think you
are being hysterical. These problems are way in the future. We can handle them the way
we have handled other problems such as polio and horse manure and the ozone hole.
Just wait a few years and technologies will solve the problem.” Without some serious
rebuttal to this argument, it is like two people arguing about whether aliens are a risk to
our life style. Second, and more serious, is that we still have to choose how much to slow
global warming. As we noted above, there is a long distance between the pole of doing
nothing and the pole of abolishing fossil fuel use immediately. As long as we need to
balance costs and benefits, we need to have a rough idea of what the benefits of slower
warming are. And that is the point of impact studies.
Three Central Issues for Impacts Analysis
The ABC model is a useful template for studying the impacts of climate change.
However, before investigating the overall results of impact studies, we should step back
and consider the landscape. In doing this analysis, three overarching issues emerge. The
first is that climate damages are closely linked to economic growth. But this point then
raises a deeper issue: If the different economies do indeed evolve and grow rapidly over
the coming decades, how can we possibly forecast the economic structures a century or
more from now? As a third point, I propose a strategy for thinking about long-term
impacts, which is the distinction between managed systems (such as the economy) and
unmanaged systems (such as natural ecosystems). I will conclude that our major longterm focus should be on those impacts that are intrinsically unmanaged or
unmanageable.
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Climate change damages from economic growth
Economic studies indicate that the severity of damages will depend critically on
economic growth over the next century and beyond. The following table will illustrate
the point. [5] This shows two alternative future trajectories calculated from the YaleRICE model with no climate change policies. The “standard” scenario is the one used to
make the central calculations of climate change and the one we will focus on in this
chapter. For the standard run, we see that per capita consumption grows sharply over
the coming decades. The average annual per capita growth rate is 1.7 percent per year
for the 21st century and 0.9 percent per year for the 22nd century. By the end of this
period, global per capita consumption is almost three times the current level for the
United States. The rapid growth with no climate-change policies lead to rapid changes in
global temperatures. These growth projections are standard to integrated economicclimate models. [6]
Now compare the standard trajectory with the “no-growth” trajectory. In this
case, we assume that there is no further improvement in overall productivity – no
growth in “total factor productivity,” to use the economist’s technical language. This
means in effect that there would be no improvements in computers, in
telecommunications, in Internet speed, in health care, or in other areas where we have
witnessed rapid growth in recent decades. The future in the no-growth projection is
dramatically different. There is virtually no growth in average consumption – it
averages 0.07 percent per year over the entire period. But climate change is also very
small. Global mean temperature rises to between 2 and 2 ½ degrees. Most climate
specialists would probably be comfortable with the trajectory of the no-growth scenario.
Finally, examine the damages shown in the last three rows of Table II-1. These
damage estimates are drawn from different impact studies that we will review later. For
the moment, take these as illustrative for this discussion. In the standard run, with both
high output and a large temperature change, the damages are very substantial. By
contrast, in the no-growth scenario, the damages are very small.
So a first important point is that the climate problem arises largely in association
with rapid economic growth. But this also means that we will on average be richer in
the future and will be better able to afford steps to slow climate change. And while the
climate damages may be a substantial percent of output, consumption-with-growthwith-damages in 2100 or 2200 will be much larger than consumption-without-growthwith-damages in 2100 or 2200. The fact that our living standards are likely to be much
higher is no excuse for doing nothing today, but it is also a reminder that we are
bequeathing a much more productive economy along with a degraded climate. If you
compare the per capita consumption in 2100 or 2200 in the two economic scenarios, it
would take an enormous amount of climate damage to offset the fruits of technological
change.
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Economic scenario
Per capita consumption (2005 $)
2005
2100
2200
Standard
No-growth
7,000
36,200
90,300
7,000
7,500
8,100
0.73
3.27
5.32
0.73
2.19
2.45
-0.6
17.2
193.4
-0.6
0.2
0.8
Global mean temperature (°C)
2005
2100
2200
Damages from climate change
(trillions of 2005 $)
2005
2100
2200
Table II-1. Economic growth and climate damages
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Should we conclude from this example that our problem is too much economic
growth? That we should aim for zero economic growth? Few people today draw this
conclusion. [7] It is like tossing out a bag of groceries because the milk is sour. The
appropriate conclusion, economists suggest, is to fix the market failure by repairing the
flawed economic externality involved in climate change. Throw out the sour milk and
fix the faulty refrigerator. Exactly how we will do this is discussed in the third chapter.
Managed versus unmanaged systems
The central distinction we should focus on in analyzing the impacts of climate
change is the difference between managed and unmanaged systems. The idea of
“management” originates in the science of ecology but can be more generally applied. A
managed system is one that can adapt to shocks through interventions. On a geological
scale, the management might be migration, selection, or other kinds of changes that
reduce or mitigate the impact of the shock. On the time scale that we are considering,
most management occurs through human interventions. For example, a farmer may
introduce an irrigation system to optimize the soil moisture for wheat production.
By contract, an unmanaged system is one that is largely free from human
intervention. It might be unmanaged because humans choose to leave it alone (as with a
wildlife reserve) or because it is unmanageable because the process is too large for
humans to control (as with the tides or violent storms).
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If we move to the subject of this discussion, we can see the role of management
in the impact of climate change. Indoor living is an example of a managed system. With
the use of well-designed and engineered structures, equipment, and monitoring
devices, humans have modified their indoor structures so that they can live in virtually
every environment from Antarctica to the tropics to outer space. By contrast, walking
outside without any clothing is a good example of an unmanaged system. The fact is
that humans could not long survive in most parts of the globe if they were forced to live
outdoors without the management of clothes or shelter.
Another example – particularly important for the impacts of global warming – is
the distinction between managed and unmanaged ecosystems. An ecosystem is a
system of living plants and animals along with the physical environment in which they
interact. One of the most important ecosystems for humans is agriculture. Some parts of
agriculture are heavily managed. For example, hydroponics is a method of growing
plants using water and nutrients without soil. Some hydroponic establishments are
essentially food factories. They can easily survive heat, drought, and hail.
At the other extreme is the food system of hunting and gathering cultures, such
as were practiced by virtually all humans until about 10,000 years ago. These techniques
are highly dependent upon climatic patterns. The main way that management entered
the picture was through mismanagement from deforestation or overfishing and
overhunting. Human history is full of civilizations that declined or disappeared because
they depended upon unmanaged food supplies that dried up with drought or cold
periods.
A particularly thrilling account of how past societies declined is in Jared
Diamond’s Collapse. [8] He recounts the perils of deforestation, soil erosion, water
mismanagement, overhunting, and overfishing by Greenland Norse, Easter Islanders,
the Polynesians of Pitcairn Island, the Anasazi of southwestern North America, and the
Maya of Central America. He emphasizes the role of mismanagement, but we might
also understand the decline as coming from narrowly based economic structures
heavily dependent on unmanaged systems. In other words, when most economic
activity is involved in hunting and gathering food, and the food supply dries up
because of the interaction of climate change and human activities, there is little
resilience and the society must migrate, decline, or perish.
There are multiple strategies by which living organisms or societies can manage
themselves to increase their resilience in the face of environmental shocks. One
mechanism is migration, by which birds and mobile animals can follow food supplies.
Another mechanism, of which humans are particularly fond, is building structures to
warm or cool themselves, shelter themselves against storms, and make devices to
further increase management of their environment. Most species have not survived all
the shocks during the 4 billion years of life on Earth, but it is remarkable how adaptive
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strategies have allowed so many species to survive periods from hothouse periods to
snowball earth.
We need to be careful to distinguish unmanaged systems from unmanageable
ones. Hurricanes are currently unmanaged in part because they are unmanageable, but
in the future, as technologies improve, countries might attempt to weaken hurricanes or
throw them off a deadly track. Indeed, Microsoft chief Bill Gates actually filed a patent
application in 2008 for a technique to reduce hurricane intensity. Similarly, sea level
rise, which appears to be one of the most secure results of climate change, might be
managed by cloud seeding or even by some fantastic device that pumps water back
onto the top of Antarctica. In the extreme, some have proposed “geoengineering”
approaches that would offset the warming by increasing the reflectivity of the earth. We
will examine the potential of such approaches in the next part.
In the long span of economic history, the trend for human societies has evolved
from depending on largely unmanaged ecosystems to a highly managed economy. This
point is seen in the declining share over time and with economic development of
agriculture, which is probably the least managed major sector of the economy (we turn
to this point below). Even within agriculture, forestry, and fisheries, economies have
increasingly moved to manage these sectors with the use of fertilizers and irrigation in
food production, fish farming for fisheries, forest management techniques in forestry,
and recycling for wood and other products. Many people resist farmed fish, nonrecycled paper, and genetically modified organisms, but these technologies are in part a
reaction to the vicissitudes of unmanaged systems.
From the point of view of human welfare, perhaps the most important example
of managing human affairs is the rise of modern medicine. Even as late as two centuries
ago, illness and death were often thought to be visited upon people by evil spirits or the
gods, and if a child died at an early age, there were several more waiting to sit at the
table. Today, health care is the largest single sector of the economy, comprising 16
percent of total output. While most of our bodies are “natural” in the sense that they are
driven by complex biological mechanisms, in a century we may find that even our
bodies are increasingly made up of manufactured parts. All this sounds like some
horrible science fiction story, but if you imagine how the modern world would look to a
time traveler from 5,000 years ago, you can get an intuitive feel of how foreign managed
human societies may appear in a century or more.
Why is the distinction between managed and unmanaged systems important for
our topic? The reason is that it helps identify those areas where climate change is of
greatest concern and those areas where adaptive forces are likely to work to mitigate
climate-change damages.
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Heavily managed systems
Most economic sectors
Manufacturing
Services
Health care
Energy production
Most of human activities
Watching TV
Surfing the Internet
Having a baby
Partly managed systems
Vulnerable economic sectors
Agriculture
Construction
Transportation
Forestry
Non-market activities
Beaches and coastal ecosystems
Wildfires
Water systems
Unmanaged or unmanageable systems
Hurricanes
Sea-level rise
Wildlife
Ocean acidification
Table II-2. Selection of managed and unmanaged systems
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Table II-3 provides a list of major activities and sectors, dividing them into
heavily managed, lightly managed, and unmanaged or unmanageable. [9] We see that
most of the economy is in the heavily managed sector; these activities are likely to be
relatively little directly affected by climate change. At the other end of the spectrum are
activities that are with current technologies and practices unmanaged or unmanageable.
These are the areas where we need to focus our attention in considering the harmful
impacts of climate change.
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Other times, other places, other customs
The last section, with its closing reflections on the science fictional nature of
human futures, is a warning about the most profound difficulty in undertaking impacts
analysis. This difficulty is the need to project (or to imagine) the social, economic, and
ecological structures in the distant future. Recall that scenarios with the largest climatic
changes also involve rapid economic growth. This means that to estimate the impact of
a 3 °C warming requires imposing our estimated impacts upon a society that has
evolved for almost a century.
To grasp the difficulty of this task, we can recall the changes that have taken
place over the last century. Go back to 1910. In that year, Europe was under the thumb
of three defunct empires, the Ottoman, Czarist, and Austrian empires. The United
States had no central bank, no income tax, and no votes for women or blacks. The
nuclear model of the atom had not yet been discovered, and people had no idea of how
traits were transmitted from parents to children. The most advanced computational
device was the Monroe Calculator, which could operate about 3 operations per second
as compared to a current workstation which can operate around 1 trillion times faster.
Our economic statistics suggest that output per hour worked has grown by factor of 10
over the last century, but that undoubtedly underestimates the changes because of the
introduction of new and improved products and unmeasured health improvements.
Now perform the experiment of trying to project the impact of global warming
on the world in 2110. In some areas, where we are relying primarily on fundamental
physical laws, we can be reasonably confident about our estimates. For example, if we
are confident about our temperature projection, then the sea-level rise due to thermal
expansion of the oceans is relatively (emphasis on the world relatively) straightforward.
And in fact we see good agreement among physical models about this impact. [10]
At the other end of the spectrum are potential impacts that are so contingent of
future economic and social structures that projections are necessarily extremely
tenuous. One example, which features prominently in many gloomy scenarios, is
“environmental migration.” One report projects that “unless strong preventative action
is taken, between now and 2050 climate change will push the number of displaced
people globally to at least 1 billion.” [11] A report on national security and climate
change quotes a high military strategist, “More poverty, more forced migrations, higher
unemployment. Those conditions are ripe for extremists and terrorists.” [12]
In reality, there has been almost no research on the impact of global warming on
human migrations. Consider some of the issues if we were doing such a projection for
2100. We would need to have a reasonable description of national boundaries,
populations, and per capita incomes of major countries. What would be the boundary
of the European Union? Would there even be a European Union? Would people be
more or less inclined to migrate? Are they more or less attached to their families,
communities, and cultures? Would transportation costs be much lower, perhaps with
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personal aircraft that could zip across borders in a flash? In addition, we would need to
understand immigration policies along with the technologies for enforcing these
policies. Would the southern borders of the US and the future EU be more or less
porous than today? What kind of personal identification systems would be available?
Would electronic detection and monitoring be so advanced, with advanced hybrid
road-air-water robots patrolling the borders, that even a coyote would hesitate to cross?
Perhaps we could take a stab at answering these questions and making
projections of migration (although I doubt it would be accurate). But our job would be
only half-done. We would then need to measure the impact of global warming on the
incomes of countries, and measure the impact of the income changes on migration
changes. To be realistic, we could probably make an estimate of the impact of global
warming on today’s world, incomes, borders, and technologies. But these are likely to
change so dramatically over the coming century that it would be foolish to suppose that
we could make an accurate projection of global warming on migration for more than a
few years.
The point about environmental migration is an example of the more general
point about the role of impacts to climate change in managed systems. Human societies
and economies are heavily managed systems. If climate change increases air pollution
or exposure to heat waves or migration, we would expect that societies would take
steps to reduce vulnerabilities through tighter pollution regulations and air
conditioning and immigration policies. Moreover, if countries continue to improve
technologies and living standards, we would expect that poor countries (who can today
barely afford such investments) will increasingly be able to protect themselves and
become “climate-proofed” the way Minneapolis or Phoenix are today. While there is no
law of nature or economics that proves that historical trends will continue, it seems
likely that the poorer countries will follow the paths of protecting their peoples and
societies from environmental extremes in the way rich countries have. Not exactly the
same way, with better technologies, with local customs and traditions, and perhaps
with fewer mistakes.
The lesson is that we are likely to overestimate the economic impacts of climate
change if we simply take our estimated changes and impose them on current societies,
particularly for the heavily managed parts of our societies.
I-14
Perspectives on Vulnerability
Vulnerability by economic sector
It will be useful to examine the extent of vulnerability for different sectors of the
economy. For this purpose, we can examine the national economic accounts by detailed
industry for the United States for the period 1948-2007. The industrial composition of
the U.S. is representative of high-income countries today. It is likely to be representative
of the structure of middle-income countries in the middle or end of this century.
For this purpose, we classify industries into three groups: heavily impacted
sectors, moderately impacted sectors, and lightly or negligibly impacted sectors.
Detailed studies on impacts indicate that the heavily affected or vulnerable sectors are
likely to be agriculture and forestry. These are sectors where productivity might be
affected by more than 20 percent in extreme scenarios. A second group of industries are
ones that are affected by weather and climate, but can adapt at modest costs. An
example here is the transportation industry. Extreme weather (such as snow or heat)
can cause delays and impose costs, but the costs are likely to be relatively small, less
than 10 percent for most climate scenarios.
A third group of industries are ones that are likely to be directly affected little or
not at all by climate change. An example of an industry that is negligibly affected is
neurosurgery. Consultations and operations take place in highly controlled
environments, in all climates, and variations of the kind envisioned are unlikely to have
a measurable effect on this activity.
Table II-4 shows an estimate of the vulnerability of the U.S. economy over the
last six decades. [13] The results are striking. To begin with, the share of the heavily
impacted sectors today is very small – roughly 1 percent of the economy. The
moderately impacted sectors constitute about one-tenth of the economy, with the major
affected sectors being coastal real estate, transportation, construction, and utilities.
These estimates are probably exaggerated because some parts of the heavily or
moderately affected sectors are likely to be insensitive to climate change. The group of
lightly affected sectors comprises most of the economy, rising from 79 to 89 percent of
the total market economy.
I-15
Share of total national income in sector
Sector by impact
1948
1973
2007
Heavily impacted sectors
9.3
3.9
1.1
Farming
Forestry, fishing
8.2
3.4
0.8
1.1
0.6
0.2
Moderately impacted sectors
11.7
11.1
9.7
Real estate (coastal)
Transportation
Construction
Utilities
0.2
0.2
0.3
6.0
3.9
2.9
4.2
5.0
4.4
1.4
2.0
2.0
79.1
85.0
89.3
4.9
6.9
8.5
2.8
1.4
2.0
13.3
13.4
6.7
12.7
8.5
5.0
6.4
6.7
5.8
9.0
7.8
6.5
0.1
0.2
0.3
2.6
3.4
4.2
2.4
4.0
7.9
0.6
0.8
1.0
18.1
24.2
37.2
11.1
14.6
12.6
100.0
100.0
100.0
Lightly or negligibly impacted sectors
Real estate (non-coastal)
Mining
Manufacturing
Durable goods
Nondurable goods
Wholesale trade
Retail trade
Warehousing and storage
Information
Finance and insurance
Rental and leasing services
Services and residual
Government
TOTAL
Table II-3. Vulnerability of the U.S. Economy by sector, 1948-2007
―――――――――――――――――――――――――――――――――――――――
The second striking feature of the sectoral data is the sharp decline in the most
vulnerable sectors. The share of the heavily impacted sectors has declined from around
9 percent of the economy in 1948 to around 1 percent today. This trend is largely due to
the declining share of agriculture. The share of the workforce in agriculture is similarly
declining, with the share of workers in farming being only 1 percent in 2008.
I-16
The declining share of agriculture is seen around the world, not just in the
United States. Figure II-4 shows trends in the share of agriculture for major countries
since 1965. [14] The downward trend is most striking in Asia, which shows how rapid
economic growth drives people off the farm and into industrial cities. The five countries
with the largest share of their output in agriculture in 1970 had declines in that share by
almost half in the next 35 years.
50
45
High income
East Asia
Latin America
South Asia
Sub-Saharan Africa
Share of agriculture in GDP (%)
40
35
30
25
20
15
10
5
0
1965
1970
1975
1980
1985
1990
1995
2000
2005
Figure II-2. Share of agriculture in major groupings of countries, 1965-2008
―――――――――――――――――――――――――――――――――――――――
What is the point here? If countries do show the rapid growth in output and
emissions found in the standard projections, then market economies will generally
become increasingly less vulnerable to climate change. This pattern is not inevitable, but
the pattern is so pervasive and striking across time and space that it seems one of the
central findings of the economics of climate change.
I-17
Evidence from time-use surveys
The results on the sectoral distribution of national output is deficient because it
omits non-market activities. These include environmental services, pollution, health
status, home production, leisure time, and many other valuable human activities. While
the need to supplement the standard economic accounts with non-market sectors has
been discussed for decades, little progress has been made in developing comprehensive
accounts.
One interesting approach that provides a perspective on non-market activity is
the way a population uses its time. Time is the ultimate resource, forever limited to 24
hours per day. We will consider the case of the United States, which has very detailed
time-use data. We can use the time metric as another way of examining the climatesensitivity of human activities.
The basic idea is the following. Suppose that a person spends a great deal of
leisure time in outdoor recreational activities – perhaps skiing in the winter, birdwatching in the spring, and scuba diving in the summer. With a changing climate, these
activities might well be disrupted because the snow line changes, bird migration
patterns are disrupted, and coral reefs dissolve. If this were the case, we would observe
a great deal of the time spend in activities that are climate sensitive, and these hours
would be greatly disrupted by climate change.
To examine this question, I looked at the American Time Use Survey for the year
2007. This covers all civilian adults, whether or not they are in the labor force. I then
classified time use into three categories, similar to those in Table 2. For example, I
assume that spiritual activities and writing emails are unaffected by climate; that travel
and attending meetings are moderately affected; and that working in agriculture,
gardening, and engaged in outdoor sports potentially significantly affected. The
categorization is subject to alternative judgments but the results are so striking that they
are unlikely to be significantly changed by alternative assumptions.
Table II-5 shows the results of this exercise. The life style of the statistically
average American appears to be at the other extreme from the skier-birdwatcher-scuba
diver example. The numbers are very similar to the sectoral breakdown of economic
activity in the last Table. A little more than 1 percent of time use is significantly affected
by climate (for example, outdoor sports), while another 8 percent is potentially
moderately affected. However, most activities take place indoors and are unlikely to be
severely stressed by climate change – examples here are sleeping, answering emails,
and watching TV. Most of our time use and daily life is largely unaffected by climate.
With the exception of a few outdoor activities – such as golfing, skiing, and farming –
our lives are spent indoors in our houses or in malls or in businesses that are largely
climate controlled environments. [15]
I-18
Perhaps Americans will change their ways and start sleeping under the stars,
eating their meals in the park, praying on the mountain-top, and surfing the web at the
beach. Until that point, human activities appear be relatively insensitive to climatic
influences.
Activity
Average hours per day,
civilian population
Heavily impacted sectors
0.35
Lawn and garden care
0.21
Exterior maintenance, repair, and decoration
0.06
1.90
Moderately impacted sectors
Work in moderately affected sector
0.35
Travel related to purchasing goods and services
0.28
Recreation in outdoor activity
0.18
Lightly or negligibly impacted sectors
21.76
Sleeping
8.57
Watching TV
2.62
Religious and spiritual activities
0.15
24.00
TOTAL
Table II-4. Distribution of time use of Americans, 2007,
with illustrative examples of each category.
―――――――――――――――――――――――――――――――――――――――
Four major areas of concern
We described above a useful way to separate areas of major concern in terms of
whether the systems under consideration were managed or unmanaged. We listed four
areas that were ones that appeared on the unmanaged end of the spectrum, and we
discuss each of those briefly in this section. The four are sea-level rise and coastal
systems, wildlife and species preservation, hurricanes, and ocean acidification. These
are not the only important areas, but they illustrate some of the areas where global
warming may prove particularly damaging and where and potential adaptations may
be difficult to achieve.
I-19
Sea-level rise and coastal systems
One of the major concerns over coming decades and centuries is the impact of
sea-level rise on coastal systems and human settlements near the coast. We begin with
the scientific background and projections and then discuss the potential impacts.
Sea-level rise (SLR) has two major components: thermal expansion and melting
of terrestrial icecaps. Water density is a function of temperature, salinity, and pressure,
but the relationships are highly non-linear. On average, as the oceans warm, they will
expand, thereby raising sea level. This part of SLR is well-understood and can be
carefully modeled. Current estimates indicate that for the A1B scenario (which is closest
to the estimates of integrated assessment models discussed in the last chapter [16]),
thermal expansion will raise the oceans by about 0.20 meters (8 inches) by 2100. This is
only slightly more rapid than the rate of SLR over the last century. [17]
The other major component of SLR is melting ice from glaciers and icecaps. What
frightens scientists here is the vast quantity of water locked up in icecaps. There are
three major areas that scientists have examined. The first is the Greenland Ice Sheet, or
GIS, which has about 7 meters of SLR-equivalent of ice. (This means that if the GIS were
to melt completely, sea level would rise about 7 meters, or 22 feet.) A second area of
concern is the West Antarctic Ice Sheet (WAIS), which has ice with a SLR-equivalent of
about 5 meters. The balance of the Antarctic Ice Sheet has a much larger quantity of ice,
but this area is so cold that there seems little risk of melting for at least 1000 years.
Modeling icecaps is extremely complex, and most models do not make
projections beyond 2100. The last round of estimates projected a range of SLR from
melting glaciers and icecaps between 0.04 and 0.20 meters by 2100. So at the outside,
land ice might contribute as much as thermal expansion. It must be emphasized,
however, that this is a very active area of scientific research, and we must be prepared
for “inevitable surprises” in the future. [18]
We have used the Yale-RICE model to make very rough projections of climate
change for different scenarios over the coming centuries. The model includes all sources
of SLR, not just thermal expansion, although the dynamics of the icecaps are very
uncertain. The projections are consistent with standard ocean-climate models but
additionally are linked to the economic and emissions models. For this exercise, we
have compared two different emissions trajectories. One is unconstrained emissions, in
which countries take no policies to reduce emissions, and most fossil resources are
used. We also showed the results of this scenario in the last chapter. The second
represents a very ambitious target such as the one set in the Copenhagen Accord
mentioned at the beginning of this chapter. This second scenario limits global mean
temperature to 2 °C over 1900 averages.
Figure II-5 shows the SLR projections for the two scenarios. [?? Mislabeled. need
to redo fig.] The top half shows the two scenarios along with the comparable estimates
I-20
from the IPCC report. Note that the Yale-RICE model has significantly higher estimates
of SLR than the last round of IPCC projections. This result arises because the Yale-RICE
model uses parameter estimates that suggest more rapid responses of ice sheets. A
second point seen in the top graph is that the difference between an aggressive and an
uncontrolled path is relatively small over the first few decades. This closeness of the
control and no-control lines shows the tremendous inertia in the earth system, which is
one of the recurrent themes of climate change.
The bottom half of the figure shows projections for 1000 years. It should be
emphasized that these are highly uncertain because of difficulties of modeling the
response of the icecaps, but they are consistent with current model estimates. [19] These
projections are very sobering. They indicate that even with extremely ambitious climate
policies there will be substantial SLR over the coming centuries. The model suggests that
limiting climate change to 2 °C will still lead to around 2 meters (6+ feet) of eventual
SLR.
However, the model suggests that an uncontrolled climate system will lead to
SLR of more than 10 meters over the next millennium. This upper-end result is
produced by a combination of more thermal expansion and substantial melting of the
Greenland Ice Sheet and discharge from the West Antarctic Ice Sheet. While these
projections are not part of the scientific consensus, they are consistent with some of the
gloomy projections of several climate scientists. [20]
I-21
0.80
Unconstrained
Limit T < 2 °C
0.70
IPCC: B2
Sea-level rise (meters)
0.60
0.50
0.40
0.30
0.20
0.10
0.00
2000
2020
2040
2060
2080
2100
14
Unconstrained
12
Sea-level rise (meters)
Limit T < 2 °C
10
8
6
4
2
0
2000
2100
2200
2300
2400
2500
2600
2700
2800
2900
3000
Figure II-3. Projected sea-level rise for uncontrolled and temperature-limit scenarios
Figure at top compares our sea-level rise projections with those of IPCC models of
roughly the same temperature trajectory over the next century. Bottom panel shows
much more speculative projection over the coming millennium. Note that even in the
case of strong climate-change policies, there will be substantial rise. [21]
―――――――――――――――――――――――――――――――――――――――
I-22
What are the potential impacts of SLR over the coming century (perhaps ½
meter) or over the longer term (up to 10 meters)? On a geological time scale, sea level
has risen and fallen by even more than this. At the height of the last ice age, the ocean
was approximately 130 meters lower than today. This was the (very cold!) time when
humans migrated across a land bridge between Asia and the Americas. In earlier
periods, when glaciers were largely absent, sea level was much higher, perhaps 200
meters higher in the age of the dinosaurs.
However, the pace of SLR over the coming century and beyond is unprecedented
during the period of human civilizations. Ecologists are particularly concerned about
the impact of the rising ocean as it interacts with human settlements. I will concentrate
here, however, on the economic dimensions.
We can first examine the total population, output, and land area of the globe at
risk from sea-level rise. Figure II-6 shows the cumulative total for these three important
magnitudes. This indicates that approximately 4 percent of 2005 population and output
are in regions that have elevation at or below 10 meters. This is significantly more than
the land area at risk, which is about 1 percent, because people and economic activity
tend to cluster near coastlines. [22]
.05
Population
Share of global total
.04
Output
.03
.02
.01
Area
.00
0
2
4
6
8
10
Less than elevation of (meters)
Figure II-4. Share of global totals at or below different elevations
―――――――――――――――――――――――――――――――――――――――
We might care about the global total if people, output, nations, and ecosystems
could migrate freely around the world. However, most people are relatively immobile
I-23
in the short run, although there is much mobility in the longer run. We should also
examine, therefore, the distribution of human settlements in the “red zone” below 10
meters. Table II-6 shows countries at risk. For this tabulation, we rely on the Yale GEcon data base, which has developed a data set on area, population, and output for the
entire globe. [23]This metric considers the fraction of the 2005 population that is at or
below 10 meters of elevation. The top part of the table shows the 10 countries that are
most at risk for sea-level rise. These countries have more than half of population and
output at risk. The most at-risk countries are relatively small, but there are two
populous countries on the list, the Netherlands and Bangladesh. The bottom part shows
the 10 most populous countries and data on the fraction of population, output, and area
at risk. Aside from Bangladesh, most countries have less than 10 percent of population
and output at risk. However, the three most populous countries have between 5 and 10
percent of populations living in the long-run red zone.
Sea-level rise is one of the most worrisome impacts of climate change because it
has such important effects and because it is difficult to stop once it is underway. While
the loss of land may be small, often the land is among the most precious parts of our
natural and human heritage.
However, we must also caution that there are steps that societies can take to
reduce the damages. A good example is whether to “retreat or defend” against the
rising seas. Defending often takes the form of building dikes and sea walls to protect
existing structures and towns. This is the strategy that the Netherlands has taken for
centuries.
In some cases, a strategy of retreat is a sensible long-run strategy. It is prudent
and not defeatist. This is in fact the strategy that nature has adapted to the long-run
changes in sea level over geological time. It is easy to overlook the fact that waterfront
properties do not disappear with sea-level rise; the location just moves. [24] Alas, this is
little comfort for property owners who find their property values destroyed and their
inland neighbor getting a windfall. But over a period of decades and more, allowing
natural processes to shift sand, beaches, ponds, and dunes is likely to protect the overall
value of land and ecosystems much better than the propensity to adopt a Maginot Line
mentality and protect every parcel. This is yet another example of the great value of
migration – of people, capital, and in this case sand and ecosystems – in reducing the
long-run costs of climate change.
I-24
Fraction at risk:
Country
Most at-risk countries
Bahamas
Maldives
Bahrain
Kiribati
Netherlands
Tonga
Gambia
Bangladesh
Kuwait
Guinea Bissau
Most populous countries
China
India
United States
Indonesia
Brazil
Pakistan
Bangladesh
Russia
Nigeria
Japan
Mexico
Population,
2005
Output,
2005
Total population,
Area
2005 (000)
100.0
100.0
91.9
91.8
74.9
69.0
63.2
60.1
48.8
48.2
100.0
100.0
60.3
91.2
76.9
58.1
62.9
58.0
9.5
48.2
100.0
100.0
65.9
9.0
76.3
17.5
30.5
50.6
7.8
29.2
323
295
725
99
16,320
99
1,617
153,281
2,535
1,597
9.0
7.3
6.1
2.8
2.9
6.8
60.1
1.8
3.7
0.0
3.2
14.4
7.2
5.9
3.6
1.7
3.5
58.0
1.0
12.9
0.0
2.9
1.8
2.8
2.9
7.5
1.4
2.4
50.6
2.4
2.3
0.0
3.3
1,304,500
1,094,583
296,507
220,558
186,849
155,772
153,281
143,150
141,356
127,773
103,089
Table II-5. Countries at risk from sea-level rise
Table shows the fraction of 2005 population and output as well as area that is at or
below 10 meters.
―――――――――――――――――――――――――――――――――――――――
Ocean Acidification
Another particularly troubling issue associated with rising CO2 concentrations is
carbonization and acidification of the oceans. This is an interesting issue because the
problem here does not result primarily from warming but from the carbon itself. Rising
CO2 concentrations in the atmosphere are quickly mixed into the upper layer of the
I-25
oceans. While this reduces atmospheric concentrations, it also causes changes in ocean
chemistry.
The chemistry is relatively straightforward. When CO2 dissolves in the oceans, it
makes the oceans more acidic and lowers the concentrations of calcium carbonate. [25]
Several marine organisms form shells from calcium carbonate, including corals,
mollusks, crustaceans, and many plankton. Because climate change and ocean
acidification are both caused by increasing atmospheric CO2, acidification is sometimes
referred to as “the other CO2 problem.” I will refer to it as ocean acidification.
There are several important features of ocean acidification. First, it is dependent
primarily on the carbon cycle and does not have the uncertainties associated with
climate modeling. While there are over 1 million Google hits on “global warming hoax,”
as of summer 2010 Google does not record a single instance of “ocean carbonization
hoax.” Second, the entire phenomenon was only recently recognized, with the first
major publications appearing in over the last decade. Indeed, the biological problems
were not even recognized in the IPCC Third Assessment Report of 2001. This is a
sobering exhibit in the category of “inevitable surprises.” Third, the major predictions
of the ocean acidification hypothesis have been confirmed by measurements in the
world’s oceans.
Marine scientists are just beginning to reckon with the consequences of
acidification on ocean organisms and ecosystems. Field experiments indicate a complex
set of responses. In many of the organisms studies (particularly corals and mollusks),
the rate of calcification and reproduction slows with higher CO2 concentrations, and
this is especially pronounced at high latitudes. This will lead to a major redistribution of
species, with those depending upon calcification declining and their predators and the
non-calcifiers increasing. We have evidence of a sharp increase in ocean CO2 during an
episode known as the Paleocene-Eocene thermal maximum (PETM), 55 million years
ago. Based on earlier episodes of spikes of atmospheric CO2 like the PETM, it appears
that most species survived, but we should expect extinction of some species.
Ocean acidification is one of the most troubling features of CO2 accumulation. It
is a polar example of an unmanaged and probably unmanageable system. The
quantities of CO2 involved are massive – in the order of 4 trillion tons of CO2 in the
upper oceans by 2100. Moreover, the geoengineering solutions to the climate change
issue that have been discussed and will be considered in the next chapter will do almost
nothing to solve the ocean acidification problem: a technology that reduces incoming
radiation and cools the early to offset the warming from accumulating CO2 will not
undo the CO2 accumulations in the atmosphere and oceans. Moreover, while it is
somewhat reassuring that the earth has experiences similar episodes of spikes in CO2
concentrations similar to that which humans are causing, the distribution of species in
earlier periods was different, and we do not have the entire record of how different
I-26
species fared in those periods. Because the system is so complex, even with the most
talented and diligent scientists trying to understand its consequences, we are unlikely to
have a full account of the impacts of ocean acidification until it is upon us.
Hurricanes
Hurricanes are another example of an unmanaged system that is clearly affected
by global warming. Hurricanes differ from sea-level rise and ocean acidification in
being extremely local and highly differentiated in impact. Hurricanes are the name
given to the North Atlantic versions of a spectacular natural phenomenon known as
“tropical cyclones.” If sustained winds reach 74 miles per hour, they are called
“hurricanes” in the North Atlantic Ocean. [26]
Tropical cyclones are giant heat engines fueled by condensation of warm
water, with a positive feedback loop whereby stronger winds lead to lower pressure,
increased evaporation and condensation, and yet stronger winds. The genesis of
hurricanes is incompletely understood, but one important necessary condition is seasurface water temperature of at least 26.5 ˚C (80 ˚F). Moreover, there are
thermodynamic upper limits on the strength of hurricanes, determined primarily by
ocean temperature.
Begin with the historical trend of hurricane damage. The data for the U.S. are the
most complete, and we have gathered data on the storm characteristics and economic
damages for 233 hurricanes that have made landfall in the United States between 1900
and 2008. These include all storms since 1933 and 30 storms before 1933. Figure II-7
shows the trend in normalized hurricane damages since 1900 (normalized damages are
hurricane damages divided by GDP). Hurricanes caused an average damage of 0.05
percent of GDP over this period, with the maximum being slightly less than 1 percent of
GDP in 2005.
One interesting feature is that, unlike many other sectors such as agriculture,
environmental damages from hurricanes appear to have an upward trend. The impact
of Hurricane Katrina is also clearly shown as a spike in 2005. Statistical analysis
indicates that, after correcting for the number of storms and their intensity, damages
have risen around 2½ percent per year faster than GDP. The reason for this increased
vulnerability is a puzzle. It is pretty clearly not primarily due to global warming, but
may be due to the fondness people have for being near the coast. [27]
I-27
Damage/GDP (percent)
1.0
0.8
0.6
0.4
0.2
0.0
00
10
20
30
40
50
60
70
80
90
00
10
Figure II-5. Normalized costs of hurricanes, 1900-2008
This figure shows the ratio of damages to GDP for all hurricanes for the given year.
The effect of global warming on tropical cyclones has been studied intensively;
the basic physics is clear if complex. Global warming might affect hurricanes in several
dimensions, including the frequency, size, intensity, lifetime, and geographic
distribution of tropical cyclones. Of the five, the only clear link from basic physics is
between global warming and cyclonic intensity. As sea-surface temperature rises, the
“potential intensity” or upper limit of cyclonic wind speed increases (holding other
factors constant).
Early calculations by MIT hurricane expert Kerry Emanuel indicated that each
degree C of warming of sea-surface temperature (SST) would lead to an increase of 5.5
percent in potential intensity (maximum wind speed). Using several global circulation
models (GCMs), Knutson and Tuleya found a slightly lower impact of 3.5 percent
increase in maximum wind speed per degree C. Statistical analysis by Emanuel
indicates that the distribution of actual hurricane intensity would increase with the
increase in potential intensity.
There have been several assessments of the impact of global warming on
hurricanes. The impact is similar to that of rising sea levels in that the physical effects can
be estimated using models, but the socioeconomic impacts will depend upon how humans
adapt to increased storm intensity and rising sea levels. We have estimated that the
I-28
impact of warming over the 21st century will lead to a doubling of hurricane damages in
the U.S. if no measures are taken to reduce vulnerability. This would lead to increased
damages of around ½ percent of GDP, or about $75 billion per year at current levels of
output. While the is not a substantial fraction of GDP over the next century, it could be
devastating to individual communities, as was seen in the case of New Orleans in 2005.
Societies can take many steps to reduce vulnerability to more intense hurricanes.
Better hurricane forecasting, as an example, has dramatically reduced the fatalities from
hurricanes over the last half century. This would not protect immobile structures,
however. In the longer run, vulnerable immobile structures depreciate, and incentives
should be in place so that they will migrate to higher and safer ground.
It does not take much migration to offset the impacts of higher hurricane
intensity. The following will illustrate the order of magnitude estimates. About 3
percent of the U.S. capital stock is below 10 meters of altitude and lies in the path of
hurricanes. Assuming that the major vulnerable items are structures, this amounts to
about $600 billion of capital. The average lifetime of structures is less than 50 years, but
we will take this number for simplicity. Assume as a polar case that all of the vulnerably
capital is replaced with houses, roads, and hospitals in safer locations as it depreciated.
The only cost would be the relocation costs. If these relocation costs were half of the
replacement capital costs, the cost of securing the nation’s capital from hurricanes
would cost about 0.03 percent of GDP per year. [28]
This example illustrates how farsighted planning for the impacts of climate
change can reduce the damages significantly. But we must again emphasize that the
patterns of winners and losers makes orderly planning extremely difficult. Inlanders
may feel little sympathy for rich people in fancy houses whose vulnerable coastal
properties are threatened; highlanders may not wish to contributed tax dollars to
protect vital structures such as dikes and levees for those threatened by flooding;
thriving towns will be disinclined to transfer resources to towns whose tax bases are
declining. Moving all the facilities in a coastal town to a more secure location may
reduce vulnerability, but that will provide little solace to those who are attached to their
homes and communities. So in reality the process of adaptation to more intense storms
is likely to be contentious and messy at best, and may lead to counterproductive
measures and fiscal or violent conflicts at worst.
Wildlife and species loss
A final example of a vulnerable sector is wildlife, and more generally species and
ecosystems around the globe. The history of speciation and extinction shows distinct
periods of surges and extinctions. Major extinctions have occurred during abrupt
climatic changes caused by asteroid collisions, volcanic eruptions, glaciations, or sealevel rise. In the worst case, the Permian-Triassic extinction about 250 million years ago
wiped out about 90 percent of all species. In the last 10,000 years, many of the most
dramatic extinctions were due to human interventions. For example, more than half of
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the large mammal species of the Americas disappeared in a short period around the
time of humans first arrived approximately 13,000 years ago. There is evidence that
humans have had a similarly disastrous effect on species on other continents. For most
of human history, as with the dodo bird, the disappearance of species was not mourned
or sometimes even unremarked. So, history does not lend comfort on the adaptability of
ecosystems and species to further economic expansion accompanied by rapid climate
change.
Scientists who have studied this question project very dire consequences of the
warming if no policies are taken. The most recent summary by the IPCC concludes that
about 25 percent of species on a global scale will be at increasingly high risk of
extinction as global mean temperatures exceed 2 to 3 °C above pre-industrial levels. Our
projections indicate that this temperature range will occur in the second half of the 21st
century. We should add to this outlook the dangers to marine organisms of ocean
acidification discussed above.
A few comments about the dangers to species and ecosystems are in order. To
begin with, many people feel there are strong ethical issues involved in extinguishing
life. For some this is a religious issue. I would view it as a neglect of our responsibilities
as stewards of planet Earth if we, even inadvertently through the indirect impact of our
energy use, were to cause further widespread species losses. The evolution of polar
bears, Monarch butterflies, cutthroat trout, South African protea – and, yes even those
ingenious but irritating mosquitoes – is the greatest wonder of the world. To undo a
substantial part of that heritage in a century is a terrible step. As Schopenhauer wrote,
“The assumption that animals are without rights and the illusion that our treatment of
them has no moral significance is a positively outrageous example of Western crudity
and barbarity.” [29]
Major difficulties arise when we attempt to translate the immorality of
destroying life into action. The heart of the difficult is to determine how much we
would be willing to sacrifice to prevent the loss of wildlife and species. Some may object
that even asking this question invokes a crude materialism and that the balancing of life
and money is itself an immoral act. But preventing loss of ecosystems and species is not
a simple matter. It involves, as we will see in the next part, taking costly steps to change
energy systems at very large costs. Moreover, there is inevitably a tradeoff between the
stringency of our emissions reductions and the risk of ecosystem and species losses.
Unfortunately, the natural and social sciences have been unable to make
plausible estimates of the value of preserving ecosystems and species. In other words,
we cannot make reliable estimates of the damages from climate change in this area. The
first difficulty comes from the difficulty in making reliable projections of the species
losses over time.
We will illustrate the difficulties by examining an influential study by Thomas et
al. This study concludes that between 18 and 35 percent of species are committed to
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extinction. The technique is to begin with the climatic range of an existing species
(mammal, bird, frog, etc.) in a particular region, such as Mexico. Then, the team
estimated how the size of the climate range would change under a particular scenario,
such as a 3 °C increase for South Africa. They then apply a technique known as the
species-area relationship, which states that the number of species is positively
associated with area of the habitat. In general, for the regions considered, the climate
range shrinks, which implies that the number of species will also shrink. For example,
under the assumed 3 °C increase for South Africa, they conclude that 38 percent of the
Proteaceae species will become extinct. [30] Perhaps the best documented examples of
potential extinctions are the reef-building corals. Estimates of extinction rates are based
on classification systems of how threatened the different systems are, but there are no
reliable long-term population measures. [31]
While these are impressive studies, they have severe limitations. For example,
some of the species can be preserved, so the extinctions often refer to in situ survival.
Secondly, the techniques are quite controversial and may not apply to a situation in
which species have adapted to human habitations. And in other cases, the damage is
being done by habitat destruction, overuse, overfishing, overhunting, and pollution that
would occur even in the absence of climate change.
A second difficulty arises because economists have not developed a reliable
technique for valuing ecosystem and species losses. The difficulty can be described by
comparing this issue with the economic impacts of damage to wheat production
discussed above. When the production of wheat declines by 10 percent, economists
typically value that at the market price of wheat. If climate change leads wheat
production to decline by 100 million bushels and the price of wheat is unchanged at $5
per bushel, then the social cost is $500 million.
It has been tempting for scientists worried about ecosystem and species losses to
point to the economic damage that might occur with major losses. One common but
unsubstantiated claim is that one-quarter of Western pharmaceuticals are derived from
rainforest ingredients. [32] A caricature of these analyses is that when species disappear
we are foregoing the miracle cure to AIDS that lurks in the Brazilian forest hidden in
some undiscovered fungus. While such a tale is not impossible, the direct economic
value of many of the species is likely to be next to nothing. Innovations in agriculture,
forestry, fisheries, and pharmacology occur primarily in industrial and laboratory
settings, not in the rain forest. As we noted above, economic output around the world is
becoming increasingly less dependent on unmanaged systems. It is hard to conceive
that a 10 percent loss in frog species will have a measurable effect on market economic
activity. The point is not that these should be ignored. Rather, it is the moral imperative
to preserve the natural world that we have inherited, rather than some hypothetical
return on investment, that should drive our actions.
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Ecosystem and species losses are different from wheat or medicine because we
have no market metric to use to value these losses. Some of the impacts will be market
or near-market goods and services (such as the losses from harvesting timber or from
the value of the catch as food). But the gains from species preservation are “public
goods.” Public goods are commodities for which the cost of extending the service to an
additional person is zero and for which it is impossible or expensive to exclude
individuals from enjoying. Take global positioning systems as an example. These are
used for hiking, missile guidance, and determining the distance of a golf ball from a
hole. These are public goods because people who find their location are not reducing
the value of signals for others. Similarly, the gain from preserving polar bears is
primarily from the non-market gain and satisfaction of having such a beautiful animal
on earth, as well as the moral gain from not destroying it.
The difficulty comes in attempting to estimate the value of public goods. Since
there is no market for moral gain or remote appreciation, we have no reliable measuring
rod to calculate the gain from protecting species. Statisticians have devised measures
known as “contingent valuation” to estimate the value. These are essentially highly
structured surveys in which people are asked, in effect, “What would you pay to
protect polar bears?” But these instruments are highly controversial, have proven
unreliable, are subject to huge biases in use, and have no behavioral counterparts.
As a result of both these shortcomings – incomplete scientific assessment of the
risk and inadequate economic tools for valuation – it seems fair to conclude that we do
not have even an order-of-magnitude estimate of the economic impact of ecosystem and
species losses from global warming.
But again, this does not mean we should simply throw up our hands and walk
away from the problem. At the least, we need a better way of sorting out the urgent
ecosystem and species preservation from those with a lower priority. Some biologists
suggest that number of species is an impoverished measure of biological importance.
Other metrics would emphasize such qualities as functional or behavioral diversity and
the ability to rebound after an environmental shock that extinguishes many species or
genera. This point was emphasized in an important finding of biologists Sean Nee and
Robert May, who studied how much of the evolutionary history – the “tree of life” – is
lost during extinctions. Their work had the surprising finding that approximately 80
percent of the underlying tree of life can survive even when approximately 95 percent
of species are lost. [33] One of the major tasks of modern biology will be to develop
better metrics of evolutionary importance to guide our conservation decisions.
Impacts on Lake Wobegon
One of the difficulties most people have with assessing the dangers of climate
change is what might be called the Lake Wobegon syndrome. Remember that in Lake
Wobegon, all the men are good looking, and all the children are above average. In this
context, we must ask if everything is at risk with global warming. Clearly, all problems
I-32
cannot be above average concern. We need to separate major from less major. If we are
told to worry about everything, we end of worrying about nothing.
The last section analyzed four problems that seemed indeed to be both genuine
and relatively difficult to manage. In this section, therefore, I will discuss problems
sometimes associated with climate change that may in fact be of lesser concern. This is
not to imply that they are of no concern because assessment is so difficult. Rather, they
are areas that would seem to be relatively low on the list of priorities that require the
closest scrutiny and major investments.
The three areas discussed here are agriculture, national security, and health. Each
of these is discussed because they have featured prominently in discussions about the
potential impacts of climate change. They all share a common feature as we look out a
century or more in a world of continued rapid technological advance, however, because
each is a heavily managed sector. That is, each of them has features in which climate
plays a diminishing role over time and in which human decisions and technologies
dominate the action. Unlike coastal properties, hurricanes, concerns about species
preservation, and ocean acidification, the three areas discussed here are ones where
technology will increasingly be in the laboratories rather than in the fields.
Human health
Among the frightening impacts of global warming is the potential for major
increases in the burden of disease. Recent research reviewed by the IPCC concludes that
climate change will have harmful effects on health through two mechanisms. The first is
the direct effect of increasing the stress from environmental conditions due to heat
waves, pollution, and floods; the second is the indirect effect that occurs because global
warming may lower living standards, thereby increasing the range of some infectious
diseases such as malaria and increasing malnutrition and diarrheal disorders.
The most detailed assessment of health impacts of climate change has been
undertaken by a team of health and climate scientists for the World Health
Organization. They employ the useful concept of “DALY,” or disability-adjusted lifeyear. The DALY concept measures the loss in healthy years of life from different
diseases. For example, if someone dies in an automobile accident at age 40, this would
be about 40 DALYs lost. If a girl in Tanzania contracts malaria, her life expectancy
would be reduced by about 33 years, so that would have a loss of 33 DALYs. [34] (Some
scholars prefer “QALYs,” which are quality-adjusted life years, but public health
specialists have generally focused on DALYs.)
The researchers examine epidemiological evidence on the relationship between
different diseases and climatic conditions. They then estimate the increased risk of
disease from the changing climate. By combining these estimates, they estimated the
total health risk from climate change. [35] Table II-7 shows estimates of the health losses
from climate change in the mid-21st century using relative risk estimates of the WHO
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team. The team identified three major areas as concerns: malnutrition (from inadequate
incomes), diarrheal diseases (from poor sanitation and health systems), and malaria
(from a spread of malarial regions). We have taken the estimates using low adaptation
and for unrestrained emissions. The temperature assumptions underlying the estimates
in the WHO study correspond to the emissions and temperature projections for around
2050 in the Yale-RICE model, so we will generally identify these with impact for 2050.
The top part of the figure shows the estimated disability adjusted life-years lost
from each of the three sources for six major regions. According to the estimates, the
major vulnerable regions are Africa and South East Asia (primarily India). Diarrheal
diseases consist of about half the health risks, with malaria and malnutrition each being
about a quarter. Note that these estimates exclude a number of major but quantitatively
less significant risks such as flooding, other tropical diseases, and heat stress.
The bottom part shows the increase as a percent of total losses and losses for that
specific set of diseases. The total estimated losses from climate change consists of about
1.3 percent of all losses. This estimate is based on 2004 population and mortality rates.
The increased health risk arises primarily for Africa and Southeast Asia. For the
developed regions of North America and Western Europe, the increased health risks are
minimal. [36]
I-34
Increased risk from
climate change
Diarrhoeal
diseases
Total
Malaria
Nutritional
deficiencies
[Disability adjusted life years lost per 1000 persons]
14.91
6.99
7.13
0.80
Eastern Mediterranean
1.06
0.61
0.06
0.39
Latin American
0.26
0.24
0.03
0.00
South East Asia
4.53
2.34
0.02
2.18
Western Pacific
North America and Western
Europe
World Total
0.35
0.27
0.08
0.00
0.02
0.02
0.00
0.00
3.09
1.56
0.85
0.69
Total
Diarrhoeal
diseases
Malaria
Nutritional
deficiencies
Africa
Increased risk as
percent of baseline
mortality
[Losses from climate change as % of all losses]
Africa
2.92
1.37
1.40
0.16
Eastern Mediterranean
0.61
0.35
0.04
0.22
Latin American
0.16
0.14
0.02
0.00
South East Asia
1.71
0.88
0.01
0.82
Western Pacific
0.23
0.18
0.05
0.00
North America and Western
Europe
0.01
0.01
0.00
0.00
1.31
0.66
0.36
0.29
World Total
Table II-6. Estimated health impact of global warming to 2000
Table shows the disability-adjusted life years lost in different regions and from different
sources as a percent of the total lost life years from all sources.
____________________________
We remarked at the beginning of this chapter that impacts analysis is a kind of
house-to-house combat between analysts, messy data, and murky future trends.
Nowhere is the terrain more treacherous than in mapping out future health impacts.
Health is of great importance to people’s well-being and to economic performance.
Health care is a large and growing part of the economy. The technology of health care is
I-35
changing rapidly as new knowledge, drugs, equipment, and information technology
transform the sector enormously.
Moreover, the health status of poor countries has improved rapidly in recent
years. Consider for example the 60 countries with per capita income less than $2000 in
1980. In these countries, life expectancy rose by 14 years in the last 3 decades. Moreover,
the rise in health status is clearly associated with higher incomes. Economic studies
indicate that a rise of 10 percent in per capita income is associated with life expectancy
that is higher by 0.3 years. The major threat to the health in poor countries has not been
climate change, but the AIDS epidemic. Health improvements in other areas have been
offset in countries such as Zimbabwe, Botswana, Zambia, and South Africa, where the
AIDS epidemic has lowered life expectancies by more than 10 years and perhaps as
much as 20 years in the worst cases. [37]
We can put the health risks in Table II-7 in the context of the overall health
improvements in developing countries. For poor countries, life expectancy has
increased 3½ years per decade over the last half century. The losses from climate change
shown in Table II-7 amount to about one-third of a year of life expectancy (1/3 of a lifeyear per person) on a global basis. For Africa, they amount to about one year of life
expectancy. This is approximately three years lost over the next half century using the
pessimistic assumptions in Table II-7.
Given the race between technology and income growth on the one hand and
climate change on the other, there are two major problems with projections of health
impacts. First, they assume minimal adaptations to the rising temperatures and health
burden. For example, we might expect, particularly with rising incomes, that people
would adapt their structures and life styles to the higher temperatures through such
means as air conditioning; the models assumed no adaptation at all to heat stress.
Similarly, there were no adaptations taken to the potential spread of malaria with
warming, even with the higher incomes.
Second, the modeling does not account for the sharp improvements in health
care and life expectancies that have taken place and can be expected to take place with
higher incomes. Note that by the end of the next century, the low-income regions are
expected to have incomes close to those of today’s high income regions; moreover, this
rapid growth is a central part of the scenarios that are producing warming in the first
place. But modeling of the vulnerability to warming overlooks the likely improvements
in public and private health that are likely to occur with rising incomes and
urbanization.
We can take the example of diarrheal diseases as an example. Diarrheal diseases
are assumed to produce about half the health impacts of climate change by mid-21st
century. The methodologies used in the projections assume that higher incomes reduce
diarrheal diseases, and that countries with a per capita income of greater than $6000
have no diarrheal diseases. Yet the studies that produce rapid emissions growth assume
I-36
rapid economic growth. For example, the Yale-RICE model used to develop the
estimates used here project output per capita in sub-Saharan Africa to grow to $9500 by
2050. So the estimates of growing malnutrition and related diseases in the climatehealth scenarios are inconsistent with the estimates of growing incomes that produce
the emissions that lead to the rapid warming.
Another example of questionable assumptions is the incidence of malaria. The
IPCC Fourth Assessment states that by 2100, there will be a 16 to 28 percent increase in
exposure to malaria in Africa. [38] These are slightly higher than the numbers used in
our estimates in Table II-7. However, these estimates assume that there are no
socioeconomic adapatations in the coming years. Such adaptations would include available
technologies such as avoidance of mosquitoes, use of repellants or mosquito nets,
preventive medicines, and treatment with infection. More important, the projections
would be completely wrong if technological improvements over the next century were to
produce an economical malaria vaccine. We might not take seriously Bill Gates’s patent
on hurricane intensity described above, but surely we should take seriously the Gates
Foundation’s program on malaria.
The points about diarrheal diseases, malnutrition, and malaria are example of the
more general point about the role of impacts to climate change in managed systems that
we have emphasized. Health care is one of the most intensively managed of all human
systems. In the case of malaria or other diseases that are worsened by climate change,
we would expect that governments would take steps to reduce vulnerabilities through
health research, preventive measures, and alleviative care. We have also seen that
human societies have, at least from the point of view of climate change, become
increasingly managed and climate-proofed. While there is no law of nature that proves
this trend will continue, it seems likely that the poorer countries will follow the path of
climate-proofing over the next century – in housing, medical care, storm warning
systems, and the like.
National security
One of the new concerns about climate change has been as a threat to national
security. This has been voiced particularly in the United States. These concerns became
public in 2007 with a report by the military research organization, the Center for Naval
Analyses, and prepared by several former military officers. While not an official
military document, this has been influential in defense circles. The report concluded,
“The nature and pace of climate changes being observed today and the consequences
projected by the consensus scientific opinion are grave and pose equally grave
implications for our national security.” [39]
The most recent National Security Strategy (NSS) of the U.S. issued in 2010
discussed climate change as an integral part of national security. However, it lists
climate change as one of the elements of “International Order” rather than “Security.” It
states, “The danger from climate change is real, urgent, and severe. The change
I-37
wrought by a warming planet will lead to new conflicts over refugees and resources;
new suffering from drought and famine; catastrophic natural disasters; and the
degradation of land across the globe.” [40]
Given this and other reports, these concerns warrant close scrutiny. To begin
with, it is important to define carefully what is meant by a “national-security concern.”
In this discussion, I will concentrate on the “hard” aspects of national security. In the
NSS, the hard security concerns include “Disrupt, Dismantle, and Defeat Al-Qa’ida and
its Violent Extremist Affiliates in Afghanistan, Pakistan, and Around the World,”
“Reverse the Spread of Nuclear and Biological Weapons and Secure Nuclear Materials,”
and “Secure Cyberspace.” That is, these are threats to the survival, viability, and
welfare of the nation-state and its allies.
Often, discussions of national security include other “soft” threats. In the NSS,
for example, the discussion includes measure to strengthen education and human
capital, enhance science, technology, and innovation, spend taxpayers’ dollars wisely,
and sustain broad cooperation on key global challenges. These are a combination of
foreign policy and even traditional domestic policy. I do not dismiss these important
objectives. Rather, I would divide the problems into ones that are properly military in
nature – which is discussed in this section – and those that are economic or
humanitarian in nature – discussed elsewhere.
One further warning is particularly important in examining the impact of climate
change on military policy: We must be careful not to assume a static technological and
political environment. In considering the impact on security in the late 21st century, we
must allow for at least two major trends. The first is that, under the standard scenario
that produces climate change, most countries will be much richer than they are today.
We should not assume that African countries have incomes comparable to the West
today and at the same time assume that large numbers of their populations are leading
a nomadic existence herding starving cattle across the desert. Second, it seems highly
likely that 21st century warfare will be increasingly dominated by information systems,
remote control, and artificial intelligence. Just as the crossbow and the battleship have
passed into the graveyard of military technologies, we should be wary of assuming that
today’s technologies will continue to dominate future warfare.
With these caveats, turn first to the question of whether climate change is
thought to pose direct effects on American national security (I concentrate on American
security because this is where the thinking is most developed). A review of the studies
cited above find relatively few major direct impacts of climate change on national
security. Some U.S. bases may be affected, particularly if they are vulnerable to sea-level
rise. An ice-free Arctic ocean will change naval planning and submarine operations.
More intense storms may occasionally interfere with naval operations. It is hard to see,
however, why any of these would cause a major change in the strategic balance among
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countries; one exception world considering is how an ice-free Arctic would affect
Canada and Russia. [41]
There is an extensive literature on conflict and the environment. In his study of
climate change and security, Rymn Parsons observed that “environmental problems do
not themselves cause wars, but do exacerbate other problems and conflicts that can lead
to war.” [42] In a survey of the literature on conflict and resources, Halvard Buhaug,
Nils Petter Gleditsch, and Ole Magnus Theisen concluded, “No tested link between
resource scarcity and civil conflict remains robust across various data
operationalizations and model specifications. Tellingly, two recent reports from the
Political Instability Task Force have abandoned the issue of environmental scarcity
altogether.” [43]
Another way of approaching the issue is to look at the indirect link between
climate change and conflict. Most studies of national security emphasize that climate
change may destabilize countries. The reasoning takes two steps. First, climate change
will have damaging effects on sectors such as water, agriculture, public health, flooding,
and loss of land. From an economic vantage point, these impacts will reduce the living
standards of the affected populations – presumably sharply. The second step in the
logic is that a sharp decline in living standards will increase the likelihood of mass
migrations, political unrest, societal collapse, and failed states.
Each of these steps needs to be examined carefully. We have discussed all of the
damaging impacts elsewhere. Some appear to be significant, while others seem less
central. The central question is whether these impacts are large and pervasive against
the background of rising trend of economic growth and the relatively small calculated
impacts of climate change. It would take much larger impacts of climate change than
those now estimated to have the sudden and large impacts on incomes that appear to be
assumed in the security studies.
The second point – that the income shocks will lead to political disturbances –
also needs careful attention. The impact of economic distress on military conflict and
other disturbances is unclear. The literature on the determinants of military conflicts has
looked intensively into the different sources but has not determined whether prior
economic stress leads to war. In work by John Oneal, Bruce Russett, and myself, we
examined several theories and variables, including democracy, per capita income,
geographical variables, and the threat environment. I have extended that study by
adding another set of variables that include whether one of the countries experienced a
sharp economic decline in prior years. For this test, I defined economic stress as a
period in which real GDP declined by at least 5 percent per year for two prior years,
looking at the period since World War II. These periods of distress include about 3
percent of the observations. The presence of economic distress was associated with a
lower probability of military disputes than other years, but the variable was statistically
insignificant. While this exercise is hardly the last word, it does suggest that the causal
I-39
linkage from climate change through economic distress to military conflict is not a tight
or universal one. [44]
In the end, concerns about national security turn out to be primarily concerns
that the world of the late 21st century will be poorer and more unstable – that climate
change will harm food production, water availability, and living standards so greatly
that political structures will not be able to cope. This picture is not supported by
economic studies of the impacts, but much remains highly unpredictable.
Agriculture
We close our discussion of specific sectors – the last house in our house-to-house
combat with impact studies – with agriculture. We have seen that many of the gloomy
predictions about the impacts of climate change actually lead back to agriculture. Two
of the major health impacts – malnourishment and diarrheal diseases – suggest poor
diets and poverty. The national security concerns arise in part because of potential
conflicts from drought, bad harvests, poverty, water shortages, and international
migration. Almost daily we read about global famine, decadal droughts, and major
areas at risk. For example, the well-known Stern Review writes, “Declining crop yields
are likely to leave hundreds of millions without the ability to produce or purchase
sufficient food, particularly in the poorest parts of the world…. Once temperatures
increase by 3 °C, 250 - 550 million additional people may be at risk – over half in Africa
and Western Asia, where (1) the declines in yield are greatest, (2) dependence on
agriculture highest, and (3) purchasing power most limited.” [45]
The basic reasoning behind the gloomy forecasts for food production relies on
two major negative factors. First, climate change is likely to lead to warmer climates
with lower soil moisture in many regions of the world where climates are already
warmer than would be optimal for food production. Work of my colleague Robert
Mendelsohn suggests that current climates in many parts of Latin America, Africa, and
Asia are already warmer than is optimal for food production, and further warming
would disadvantage those regions even more. A second concern is that climate change
may lead to declines in mountain snowpack and river runoff. This would reduce water
availability for irrigation and harm agricultural productivity. These two factors have
been extensively investigated with the use of climate projections and crop models.
The crystal ball of future impacts for agriculture is just as cloudy as in other
areas, but there are several factors that mitigate the potentially harmful impacts of
climate change. These are carbon fertilization, adaptation, and trade.
One important mitigation in agriculture is “carbon fertilization.” Carbon dioxide
is an important fertilizer in many plants. The fertilization effect has been tested in the
field in several experiments. Crop yields for wheat, cotton, and clover – particularly
when combined with appropriate adjustments of other fertilizers – have increased
sharply in field experiments. One review of multiple studies in the field found that
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doubling atmospheric concentrations of CO2 would increase yields of rice, wheat, and
soybeans between 10 and 15 percent. Certain plants (the C4 variety like corn) are
expected to show relatively small increases in yield. There are many questions about
how fertilization will interact with other stresses, but the general view is that this is a
significant offset to the warmer and drier climates that might occur in many regions.
A second important factor is what is called “adaptation.” Adaptation refers to
the adjustments that human or natural systems take in response to changes in
environmental conditions. These take place on multiple levels. We can use the example
of agriculture to illustrate how adaptation occurs. Some adaptation takes place even in
unmanaged systems, such as when a species migrates to a more friendly climatic zone
after climate change. In agriculture, we usually consider the most important
adaptations to be those undertaken by farmers. Among the important adaptations in the
short run are changes in sowing and harvesting dates, changing seeds and crops,
modifying water supply through irrigation systems, changing techniques of production
such as fertilizer, tillage methods, grain drying, and other field operations. In the
longer run, farmers can move into new areas and abandon infertile ones, develop new
varieties of seeds that are drought and heat resistant, and move land into other uses.
One of the most important adaptations is the use of more water-efficient irrigation
systems. [46]
Figure II-8 illustrates the both the way that adaptation works and the biases that
can occur when adaptation is not taken into account. The graph shows land value in
different uses. Land value is used by economists to reflect the inherent productivity of
land as determined by climate, location, and other variables. The horizontal axis
measures temperature, while the vertical axis measures the economic value of an
activity. We show four activities – wheat production, corn production, grazing, and
retirement homes. For each of these, the illustrated shape of the curve is dome-shaped
or concave, with a rising segment, a maximum, and a sharp decline when the
temperature deviates too far from the optimum. [47]
For this example, we consider only adaptations that involve changing the crop or
land use. Studies of wheat yield without adaptation would do experiments and find
that the yield or value followed the ABCF line; those for corn would follow the CD corn
line; and so on. A study that examined the effect of warming without adaptation would
assume that the value of the land at high temperature would fall from point C to point
F. It would therefore find a very sharp decline in food production with climate change.
In reality, as yields fall, farmers look around and find the best possible use for
their land. In the example shown in Figure II-8, farmers would change to corn
production. Then, as temperatures rose further, they would switch to grazing cattle.
Finally, when the land becomes completely unsuitable for agriculture, they might sell to
a developer who would build a retirement community and golf course. The value of the
land with adapatation is shown as the upper “envelope” joined by points ABCDE of the
I-41
values for the different activities. Clearly, with adaptations, the economic value of land
is much higher than without adaptations.
Figure II-6. Illustration of the value of land with and without adaptation
_____________________
Studies of agriculture have looked extensively at impacts with and without
adaptation, and it will be useful to examine a specific example. Figure II-9 shows a
compilation of studies of the effect of climate change on the yields of wheat in low
latitude regions. [48] The plot shows the results of 69 published studies at multiple
simulation sites as a function of mean local temperature change. The red dots show the
response without adaptations, while the dark green dots show with a limited set of
adaptations. The green and red lines show the best statistical fit to the points.
I-42
Figure II-7. Estimated impact of climate change on wheat yields for low-latitude
regions
The central results shown in Figure II-9 are that with adaptation the yields of
wheat would be positive for climate change scenarios up to 3 °C. This is the change that
would be expected around 2100 for low-latitude regions. They would begin to turn
significantly negative after than increase, and would reach around minus 30 percent at a
5 °C temperature increase. Note that these estimates include projected impacts on
precipitation and soil moisture. The same survey found that the break-even
temperature change for rice is estimated to be around 4 °C.
The adaptations varied among studies, but typically included changes in
fertilizer treatments, planting dates, and shifts from rain-fed to irrigated conditions.
They usually did not consider changing crops or new genetic varieties. They almost
never considered the value of the land in non-agricultural activities. From an economic
point of view, it would be very surprising to have a situation where no adaptations took
place over a period of several years, and indeed the adaptations assumed in most
studies are on the lean side of what is realistic.
The third mitigating factor for agriculture is national and international trade.
Increasingly, farming is a market activity not a subsistence activity. This means that a
shock to agricultural productivity in one region is buffered by markets so that the
impact on food prices is very small. To a first approximation, if wheat yields in Kansas
decline by 10 percent because of climate change, there will be virtually no impact on
food prices or on consumers. [49]
I-43
Real farm prices, U.S. (1948=100)
100
80
70
60
50
40
30
20
10
50
55
60
65
70
75
80
85
90
95
00
05
Figure II-8. Trends in the prices of farm products, United States 1948 – 2009
Moreover, if this change takes place over a decade or more, the impact on the
market will be lost in the noise. It is useful to recall that agricultural markets are
constantly subject to supply and demand shocks. But the major shocks have been to
lower food prices in most regions. Figure II-10 shows the trend in U.S. raw food prices
relative to wages over the last half century. The downward trend in prices – not
warming – is the major fact that American farmers are worried about. [50]
The symptoms of a climate-induced food crisis would be a reversal of the trend
shown in Figure II-9. What do studies show? A review of world food models by the
IPCC showed a range of results. Those models with adaptation and highly developed
trade models generally showed a decline in food prices relative to a baseline out to at
least a temperature increase of 3 °C. These results are consistent with studies that find
increasing agricultural yields up to 3 °C temperature increase, as shown in Figure II-9.
[51]
This concludes our discussion of Lake Wobegon effects. Our review of health,
national security, and agriculture indicate that for the next few years climate change is
likely to add noise to the background shocks in these sectors. Shocks are usually
I-44
unwelcome, so few people would advocate increasing the variability that doctors and
generals and farmers have to contend with. But relative to the background trends in
these sectors, climate change would appear to be a concern that is … below average.
Aggregate Assessments of the Damages from Climate Change
Central estimates of overall damages
We have taken a long excursion to examine the techniques used for assessing
impacts and presented some of the major results. Having gone house to house, we can
stand back and look at the village. We are clearly interested in much more than wheat
in Kansas or sea-level rise in the Netherlands. What are the overall impacts as best as
can be judged?
Economists have struggled to estimate the aggregate damages from climate
change for several years. The aggregate studies pull together studies for all the relevant
sectors for different countries and where estimates are available. But be warned: There
is no social science analog to the global climate models. We cannot look to some grand
economic “model of everything” to estimate the impacts of climate change. Rather,
estimating damages is like house-to-house combat, looking at each of the countries’
economic and social structures, geography, climate, and industry composition.
However, many sectors in many countries have not been studied, so the aggregate
estimates involve a great deal of guesswork and extrapolation. Additionally, some
impacts are extremely difficult to value, particularly impacts on natural processes like
ecosystems or species extinctions. But just as national accountants attempt to put
together the “gross domestic product” to measure the entire output of an economy,
similarly do environmental economists attempt to combine measures from different
Damages as percent of output
6
5
4
3
2
1
0
-1
0.0
0.5
1.0
1.5
2.0
2.5
3.0
-2
-3
I-45
Global mean temperature increase (°C)
3.5
areas to estimate the total impacts or damages from climate change.
Figure II-11 shows the results of studies over the last two decades compiled by
the leading scholar in this area, Richard Tol. [52] Several interesting findings emerge
from these results. The first and major surprise is that, for the range of changes that
have been calculated, the estimated impacts of climate change are relatively small. The
largest damage estimate is around 5 percent of output. The most carefully studied
scenario is one with a 2.5 °C warming (which we estimate to occur around 2070). For
this amount of warming, the central estimate is around 1½ percent of global output.
Additionally, impacts are estimated to be non-linear. This means that an additional
degree is estimated to be increasingly costly with more warming. Another surprise
(foreshadowed by our discussion of agriculture above) is that there may be a modest
net benefit from the first degree or so of warming.
Cautionary reservations about the estimates
These results must be used with great caution, however. They include only the
quantifiable impacts and are largely concentrated on the market or near-market sectors
such as agriculture, real estate, land, forestry, sea-level rise, and human health. Since we
have found that much of the economy is relative invulnerable to climate, it is not
surprising that the market component of damages, particularly in high income
countries, is relative modest.
It is important to understand what these studies exclude. To begin with, they
exclude several negative and positive items that are unlikely to add up to much in the
aggregate, even for individual countries. Here are some examples of impacts that have
been examined but are generally ambiguous or small. Generally excluded are the
impact on energy expenditures (less space heating, more space cooling); lower
expenditures on winter coats; the costs of cooling plants for electricity generation;
increased accessibility of arctic harbors; greater cost of snowmaking for skiing;
decreased amenities from winter recreation and greater amenities from warm-weather
recreation; loss of income from fisheries; and so on. There is always the possibility that
the list is a very large number of small numbers, which could add up to a large number,
as in death with 1000 cuts. Given all the sectors in all the regions for all the possible
scenarios, the aggregate impact of these “minor” impacts is hard to judge.
Additionally, there are a few potentially very large impacts that are either too
uncertain or too difficult to estimate reliably. We discussed above the difficulty of
calculating the economic impacts of loss of biodiversity. This analysis is doubly cursed
because the impacts are too complex to estimate and economists have no reliable
methodology for estimate the value of biodiversity losses. Also, we might consider
whether these figures should be increased because of risk aversion because the impacts
are so uncertain. [53] Finally, there are the global scale singularities and abrupt events,
which I discuss in the next section.
I-46
Singularities and abrupt changes
Background on abrupt changes
Perhaps the major concerns, particularly among earth scientists, are the
possibility that continued warming might lead to discontinuous, abrupt, or catastrophic
climate changes and consequences. We have discussed these above, but they are worth
further discussion. These concerns are variously called tipping points, singularities,
mathematical catastrophes, and abrupt events. Such outcomes can occur in non-linear
dynamic systems when a system crosses a threshold, and a sharply discontinuous
behavior ensues. Look back at Figure I-14 on p. I-25. This shows how a tiny change in
an influence can send a system into a completely new, different, and locally stable
equilibrium.
We are all familiar with examples of singularities in daily life. For example, if
you lean to the side of a canoe, you will eventually pass the tipping point, the canoe tips
over, and you are in the water. Tipping points are found in economics in the
phenomenon known as “bank runs,” which were endemic in earlier days. If too many
people lose confidence in a bank, they rush to the bank and attempt to withdraw their
funds. Because banks typically have only a small fraction of their deposits on hand, they
could not satisfy all depositors. Once people judge that there is likely to be a bank run,
it is a self-fulfilling expectation because they run to the bank to get there before other
people, who in turn are trying to get there before they do, and the bank is quickly out of
cash. Lest this seems too archaic a notion, it is worth noting that exactly this
phenomenon was responsible for the demise of investment banks Bear, Sterns in March
2003 and Lehman Bros in September 2003. In both cases, large investors smelled trouble
and withdrew funds, but in the second case the government did not come to the rescue.
The fleet and well-connected got their money out, while the laggards lost billions of
dollars.
Tipping points have many interesting features. One is that they often have
multiple equilibria. For example, in the case of bank runs and the tippy canoes, there
are “good equilibria” (sitting in the canoe and or with your money in solvent banks)
and “bad equilibria” (swimming in the water or left with some worthless deposits). A
second feature is that singular events can occur very quickly. Indeed, abrupt climate
change is sometimes defined as changes in the climate that occur much more quickly
than the change in the precipitating event. [54] In financial markets, the brilliant
economist Rudy Dornbusch remarked that financial crises take much, much longer to
come than you think, and then they happen much faster than you could imagine. [55]
One of the more frightening aspects of tipping points and abrupt events is their
inherent unpredictability. [56]
I-47
Worrisome singularities
What are the singularities in climate change? We must emphasize that, like
financial crises or the tippy canoe, the exact timing of these is essentially impossible to
predict. They can occur rapidly and unexpectedly, or perhaps they will never happen.
With that said, three global-scale singularities have received considerable attention. The
first, which we discussed above, is sea-level rise from abrupt melting or collapse of the
major ice sheets of Greenland and West Antarctica. This would have major
consequences for the entire globe, but particularly for coastal communities and many
large agglomerations. The estimates of sea-level rise that I showed in Figure II-5 shows
how the process might proceed without any abrupt events. But many specialists believe
that the current estimates may not capture the processes correctly, and that they may
occur much more rapidly. Scientists are hard at work in modeling these changes, and it
seem likely that the pace and scope of deglaciation will be better understood in the
coming years. [57]
A second important singularity is change in ocean currents, particularly the
Atlantic Thermohaline Circulation (THC), popularly known as the Gulf Stream. In the
present era, ocean currents bring warm surface water to the North Atlantic. As a result,
the North Atlantic community is much warmer, indeed habitable, than it would
otherwise be. For example, Scotland is the same latitude at the peninsula of Kamchatka
in eastern Russia, but its average temperature is about 12 °C warmer in Scotland than in
Kamchatka. Although the THC has been stable for several thousand years, it appears
that there were large and rapid shifts in the system during ice ages. A weakening or
reversal of the THC would lead to a sharp cooling of the North Atlantic region.
Climate models project increases in both temperature and precipitation in the
higher latitudes. These changes make surface water less dense and thereby reduce the
speed of the thermohaline circulation. Warm water now moves north, warms the North
Atlantic, and then dives to return south. In a warmer world, that process would slow or
even stop. This would tend to cool the North Atlantic relative to the rest of the world
and actually warm other regions.
The most recent review of the evidence on changes in the THC shows less
dramatic changes than earlier modeling results. This is one of the few pieces of good
news on impacts that has been recorded in recent years. For temperature projections
that are roughly the same as the economic models discussed earlier, the North Atlantic
circulation is projected to weaken by about 50 percent over the 21st century. None of the
19 models contained in the IPCC Fourth Report shows a complete shutdown of the
circulation in the 21st century. In the models where the circulation weakens, Europe
continues to warm because the cooling effect of the slowdown is smaller than the
warming effects of the reduced circulation. [58]
A third set of major global concerns is the long-term interaction between climate,
the biosphere, and the carbon cycle. Some background on climate models will be
I-48
helpful here. Most climate models begin with a given path of emissions of CO2 and
other greenhouse gases. The CO2 gradually is distributed through different reservoirs,
including the atmosphere, the oceans, and the biosphere in trees, crops, and soils. In the
short run of a century or so, however, the only added CO2 comes from human additions
such as burning fossil fuels.
With a warmer climate and higher CO2 concentrations, there are many important
feedback effects that may increase or decrease climate change. One set of feedbacks
takes place in the oceans through reduced circulation and decreased chemical buffering,
which will lower the uptake of CO2 in the oceans. This by itself is estimated to increase
atmospheric concentrations of CO2 over the 21st century by about 20 percent. [59]
Another set of feedbacks is the impact of warming on release of carbon dioxide
(CO2) and methane (CH4). Begin with the methane question. Methane is a powerful
greenhouse gas, and it gradually is transformed to the stable chemical compound of
CO2. There are vast quantities of methane stored frozen in the form of methane
hydrates, which are methane molecules trapped in ice crystals. Most of the methane
hydrates are stored in sediments in the oceans, while a vast quantity is frozen in the
ground in cold regions. The concern is that if either of these sources released methane
into the atmosphere, this could add a sharp further warming to that already in train.
A final concern involves the difference between the short-run and the long-run
response of climate to human changes. Today’s climate models are basically designed to
calculate the “fast feedback processes” – those involving the direct effects of increasing
concentrations of greenhouse gases and the rapid feedbacks such as changes of water
vapor, clouds and sea ice. (These are not very fast by economists’ standards as they
occur over a few hundred years, but they are fast by geoscientists’ standards.) There
may be “slow feedback processes” that amplify these effects. The slow processes
involve ice-sheet disintegration, vegetation migration, and releases of greenhouse gases
(such as the methane just discussed) from soils, tundra, and ocean sediments. For
example, as glaciers and ice sheets melt, the earth becomes darker. This leads to a lower
albedo (reflectivity), which in turn further warms the earth. Additionally, a warmer
earth may lead to releases of CO2 and other greenhouse gases from the oceans and the
biota, as described above.
Preliminary calculation suggest that, when the slow feedback processes are
included, the climate sensitivity may be twice as large as is calculated by the current
suite of climate models. That is, the long-run sensitivity to CO2 doubling might be as
high as 6 °C, instead of the standard 3 °C found in most models today. [60] While this is
a very frightening prospect, it must be recognized that it has not been validated by
multiple models. Furthermore, it applies when CO2 has been airborne for time periods
of centuries to millennia. We might wonder whether it is appropriate to assume that we
cannot devise technologies to control atmospheric concentrations of CO2 sometime in
the next 1000 years, so this may be less alarming than would appear at first blush.
I-49
Careful modeling of the economic, emissions, and longer-term climate models will be
necessary to determine how central these slow feedback processes are to decisions
about climate policy.
Final Thoughts on Impacts
At the end of this review of the impacts of future climate change, what should
we conclude? The first point is to emphasize how difficult impact analyses are. They
combine the uncertainties of emissions projections and climate models. Even if we
overlook the uncertainties about future climate change, the reactions of human and
natural systems to these changes are very poorly understood. In part, reactions of social
systems are hard to forecast because they are so complex. Additionally, human can
manage the environment, so that in many sectors a small investment in adaptation can
offset the climatic changes. Moreover, the climate changes are almost certain to take
place in a vastly different set of technologies and economic structures.
However, we must look through the fog as best we can. One second set of
findings, which many find surprising, is that managed systems are surprisingly resilient
to climate changes over the coming decades. This finding applies particularly to highincome market economies with small agricultural sectors. While some might worry that
this dooms poor countries to be highly vulnerable to climatic shocks, this overlooks the
economic growth that underlies the projections of major climate changes. The two most
populous countries of the world, with 2½ billion people, have seen their per capita
incomes rise by a factor of almost 10 over the last half century. [61] Another half century
of similar growth will raise the per capita incomes in India and China to around
$50,000, with most people working in services and few left in agriculture. The
vulnerability of poor countries to climate change in the late 21st century is likely to look
completely different from today.
A third major conclusion is that the most damaging impacts of climate change
are likely to be in the unmanaged and unmanageable human and natural systems. We
identified four areas important areas of concern – sea-level rise, tropical cyclones, ocean
acidification, and loss of biodiversity. For each of these, the scale of the changes are (at
least at the present time) beyond the capability of human efforts to stop. To put this in
perspective, the total volume of ice in the endangered ice caps is around about
1,584,000,000,000,000,000 gallons. This is far beyond what we can easily store in some
convenient location. The implications of sea-level rise and more intense hurricanes are
easily comprehended, and in reality human societies can adapt to them without
catastrophic losses. But the implications of ocean acidification and the potential loss of
large numbers of species and of the tree of life is difficult to comprehend and
impossible to value reliably. We cannot rule out the possibility that future technologies
– the analogs of Bill Gates’s patent on hurricane modification – will change the outlook
I-50
for these four areas. But the hurdles here are much higher than for areas which are
managed systems such as health, agriculture, and security.
Finally, given what we know about impacts, we want to know if there is a limit
for which we can say, up to this point but no further. Scientists and policy makers at
Copenhagen in 2009 determined that a temperature increase of 2 °C over pre-industrial
levels was the maximum that was within the safety margin for Earth systems. What
does our study of impact suggest about the Copenhagen target? My view is that the
target is both too low and too high. It is too low given the identifiable damages and the
high costs of attaining such an objective. But it is surely too high if we put a large
weight on preventing the big four of intense hurricanes, ocean acidification, sea-level
rise, and species loss – and if we believe along with many earth scientists that we have
already passed the safe lower boundary for preventing these dangerous effects.
I conclude, then, that the Copenhagen target is somewhere between too low and
too high. So, like some murder mystery where the butler and the rich niece are both
implicated in the poisoning of the rich dowager, the story is not over. The next chapter
continues the drama by considering the costs of slowing climate change. We can then
put together costs and benefits and propose a solution going forward to balance the
twin objectives of preserving our environment for the future while economizing on
losses in living standards today.
I-51
Endnotes: These notes are for the curious or specialists who would like to know where
the statements in the text are from or their statistical support.
The Accord is found at
http://unfccc.int/files/meetings/cop_15/application/pdf/cop15_cph_auv.pdf .
1
Here is a first problem with impact studies. Most studies focus on the grains such as
wheat, maize, and rice. However, these represent only 15 percent of the value of
production for the 20 major commodities in Africa. (See data from the Food and
Agriculture Organization at http://faostat.fao.org.) So we do not really have a good
sample of this very important sector.
2
Details are the following. For this example, we use the UKMO-HadGEM1 model,
which is a highly resolved model. We downloaded the regional projections for 20802099 and then averaged those for the grid cells of sub-Saharan Africa. The area
weighted average temperature increases were 3.40 °C for Africa and 3.43 °C for the
globe. Because models tend to scale with mean temperature, we took the period for the
4 °C increase for the Yale-RICE model to be the period under consideration, which is
2120. The decline in wheat yield is estimated to be 18 percent at that temperature
increase. (The compilation is provided in IPCC, Climate Change Impacts, p. 286.) African
GDP is estimated to be $63.6 trillion; agriculture’s share is estimated to be 8.2 percent of
GDP; wheat is estimated to be 5 percent of agriculture. [Source:
wheat_africa_example.xlsx]
3
If you go through the many steps in the ABC methodology, you will suspect – quite
correctly – that these results are very insecure. They do not take into account the
uncertainties in the studies, or the substitution into different crops, or how much
elevated levels of CO2 will fertilize different crops, or that new technologies might
make wheat adaptable to the new climate. Moreover, the effect is highly non-linear, and
if the temperature change is 3 °C rather than 4 °C, the estimated multiplier is zero and
not negative. If you go back and look at the results, you will notice that, for every other
crop and every other region, the impact multiplier is less damaging than for lowlatitude wheat. Above all, this technique cannot capture that in a world that is assumed
to have dramatic technological changes, where African countries have per capita
consumption equal to that in the high-income countries today, that the economy of
Africa may have a completely different foundation and one in which wheat-as-weknow-it-today simply no longer is used. So while the methodology of ABC is simple in
principle, impact analysis has turned out to be the most difficult area in all of climate
change science.
4
I-52
The estimates were constructed as follows. The “standard run” follows the Yale-RICE
model’s estimates of output growth in different countries with the associated CO2
emissions and temperature path. For the no-growth run, we assumed that population
growth continues but total factor productivity remains at the 2005 level. The damage
function uses the consensus estimates presented later in this chapter in Figure ?. We
have fit a quadratic function to the data in the Tol survey and used that function to
estimate damages. The quadratic function is that the damage/output ratio = -2.18T +
1.046 T2.
5
The conclusions about economic growth and climate change is a unanimous part of
integrated assessment models and is not a peculiarity of the Yale-RICE model. Two
other examples will illustrate the point. In the well-known Stern Review, which was
generally thought to be very pessimistic, average output growth over the first two
centuries was even more rapid than in the Yale-RICE model. Even with the damages
estimated by the Stern Review, average living standards would still growth by at least a
factor of more than 11. [Source: chap2_tab_nogrowth.xlsx]
6
Another example is the group of models used in the EMF-22 model comparison
study (see Weyant, ???). These average of the assumed growth rates of GDP per capita
over the period 2000-2100 was 1.74 percent per year. The lowest growth rate of any
model for any region was 0.74 percent per year (for the U.S. by the MESSAGE model).
For low-income countries, the average growth rate was assumed to be 2.3 percent per
year. [Source: EMFpop gdp growth.xls]
One analyst who does take this path is Herman Daly, author of The Steady State
Economy.
7
8
Collapse: How Societies Choose to Fail or Survive, Viking Press, New York, 2005
This list is primarily drawn from IPCC, Impacts 2007, with particular attention to the
Summary for Policymakers and the chapter on ecosystems. The emphasis here is
slightly different, however, because some of the major issues identified in that report
are ones that are in fact heavily managed and seem less likely to be of long-run concern.
For example, much of the work on impacts concerns agriculture, which, as noted
elsewhere in this part, is increasingly managed and a declining share of economic and
human activities. Similarly, the emphasis on health consequences has a very static view
of the health-care system; see the discussion of health effects later in this part. Several
reports also emphasize the harmful impacts of migration, whereas migration is an
important safety valve to relieve regions that are harmed by income or environmental
shocks.
9
I-53
[manage v unmanage.xlsx]
See IPCC, Science, p. 812, Figure 10.31. The range of estimates of thermal expansion
for scenario A1B is 14 to 38 cm by 2100. I suspect that a substantial part of the difference
is due to differences in the temperature trajectories.
10
11
Human tide: the real migration crisis, A Christian Aid report, May 2007.
Center for Naval Analyses, National Security and the Threat of Climate Change, Alexandria, VA:
The CNA Corporation, 2007, available online at
http://www.cna.org/nationalsecurity/climate/ (hereafter the “CNA Report”).
12
The underlying data are provided by the U.S. Bureau of Economic Analysis at www.bea.gov,
in the industry tables at http://www.bea.gov/industry/gpotables/gpo_action.cfm. The only
major decision is how to partition real estate between moderately and lightly vulnerable sectors.
We assume that low-lying real estate is susceptible to storms and flooding. From our GEcon
data, we estimate that 3 percent of U.S. output and population lies below 10 meters of elevation,
so that is our estimate of the moderately affected share of real estate. [Source: gdp by
sector.xlsx]
13
Data are from the World Bank, World Development Indicators at
http://www.worldbank.org. [Source: share_ag_diff_countries.xlsx]
14
The underlying data are from the American Time Use Survey conducted by the
Bureau of Labor Statistics, available at atus.bls.gov. Two areas required some
supplementation. The time at work is taken from the hours engaged, from the Bureau of
Economic Analysis, and uses the same industrial breakdown as in Table 1. For sports
and recreation, we draw upon a Australian survey that shows participation for detailed
sports, available at
http://www.ausport.gov.au/__data/assets/pdf_file/0004/304384/ERASS_Report_200
8.pdf . [Source: timeuse.xlsx]
15
16
The comparison of RICE and IPCC scenarios is contained in temperature history.xlsx.
These estimates are drawn from IPCC, Science 2007, Chapters 5 and 10. The estimate
for the 21st century is for SRES scenario A1, Table 10.7, ibid., p. 820. Similar results are
found for scenario B2. The range of models is from 0.12 to 0.32 meters over the century.
17
This is the striking title of a report by a committee of the National Academy of
Sciences, Abrupt Climate Change: Inevitable Surprises, Washington, D.C., National
Academy Press, 2002.
18
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A description of the SLR module of the Yale-RICE model is available at
http://nordhaus.econ.yale.edu/RICEmodels.htm.
19
See particularly James Hansen et al., “Target Atmospheric CO2: Where Should
Humanity Aim?” The Open Atmospheric Science Journal, 2008, pp. 217- 231.
20
21
?? A reference is missing here??
[Source: elev_gecon31_120109.wf1 for the data; program is cum_pop_gcp.prg; figure
is fig_cum_alt]
22
For more information on the G-Econ data set, see gecon.yale.edu . [Source:
slr_area_pop.xlsx for the tabulation; elev_gecon31_120109.wf1 for the data; programs
are elev_sort.prg and country_id_dums_v3.prg]
23
This important point was uncovered in a series of pioneering studies by Gary Yohe
and colleagues. See for example Gary Yohe, et al., “The economic cost of greenhouseinduced sea-level rise for developed property in the United States,” Climatic Change,
1996, pp. 1573-1480.
24
The study of ocean carbonization is a very new field. It was discovered almost by
accident by Ken Caldeira about a decade ago. For those interested in the chemistry, here
are the reactions: The net effect of increased CO2 is to lower the carbonate-ion (CO3 2-)
concentration, and lower the saturation state of calcium carbonate (CaCO3) minerals.
One of the first studies was Ken Caldeira and Michael E. Wickett, “Oceanography:
Anthropogenic carbon and ocean pH,” Nature, 425, 25 September 2003, p. 365.
25
The material here draws upon my study, “The Economics of Hurricanes and
Implications of Global Warming,” Climate Change Economics, vol. 1., no. 1, 2010. The
important scientific studies are Kerry A. Emanuel, “The Dependence of Hurricane
Intensity on Climate,” Nature, 326, April 8, 1987, pp. 483 – 485 and Thomas R. Knutson
and Robert E. Tuleya, “Impact Of CO2-Induced Warming On Simulated Hurricane
Intensity And Precipitation: Sensitivity To The Choice Of Climate Model And
Convective Parameterization,” Journal of Climate, Vol. 17, No. 18, September 15, 2004, p.
3477-95. Similar results, including estimates for other countries, are in ???.
26
One of the earliest studies was Richard A. Feely, et al., “Impact of Anthropogenic
CO2 on the CaCO3 System in the Oceans,” Science, 305, 2004, pp. 362-366. A recent nontechnical survey of the issue is in Scott C. Doney et al., “Ocean Acidification: The Other
CO2 Problem,” Annual Review of Marine Science, 2009, pp. 169–92.
27
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Estimates of vulnerable capital are from Nordhaus, “The Economic Impacts of
Hurricanes,” op. cit. The estimates of capital stock are from the U.S. Bureau of Economic
Analysis and are available at http://www.bea.gov/national/index.htm#fixed.
Depreciation rates are discussed in Barbara M. Fraumeni, “The Measurement of
Depreciation in the U.S. National Income and Product Accounts,” Survey of Current
Business, July 1997, pp. 7-23 available at
www.bea.gov/scb/pdf/NATIONAL/NIPAREL/1997/0797fr.pdf. The methodology of
replacement estimates is also used by Yohe et al., op. cit.
28
Arthur Schopenhauer, On the Basis of Morality, translation, E.F.J. Payne, Providence,
RI, USA, Berghahn Books, 1955.
29
See Chris D. Thomas et al., “Extinction risk from climate change,” Nature, 8 January
2004, pp. 145-148.
30
An exemplary study that shows the methodology is Kent E. Carpenter, et al., “OneThird of Reef-Building Corals Face Elevated Extinction Risk from Climate Change and
Local Impacts,” Science, 321, 2008, 560-563.
31
This is one of those statements that is widely quoted but seems to emerge from nowhere. I
have seen it widely used but cannot find the original source. Many of the cites are to www.raintree.com. A query to that site produced no answer.
32
See Chris D. Thomas et al., “Extinction risk from climate change,” Nature, 8 January 2004, pp.
145-148.
33
Guy Hutton, David Schellenberg, Fabrizio Tediosi, Eusebio Macete, Elizeus Kahigwa,
Betuel Sigauque, Xavier Mas, Marta Trapero, Marcel Tanner, Antoni Trilla, Pedro
Alonso, and Clara Menendez “Cost-effectiveness of malaria intermittent preventive
treatment in infants (IPTi) in Mozambique and the United Republic of Tanzania,”
Bulletin of the World Health Organization (BLT), Volume 87, Number 2, February 2009,
123-129. Data at malaria DALY.xlsx.
34
The sources are Christopher J. L. Murray and Alan D. Lopez, Global Health Statistics,
Harvard School of Public Health, and World Health Organization, 1996; data on DALYs
are published by the World Health Organization and can be found at
http://www.who.int/healthinfo/global_burden_disease/estimates_regional/en/index
.html. A detailed discussion of the methodology is contained in Anthony J. McMichael,
et al., Climate Change and Human Health: Risks and Responses, World Health Organization,
Geneva, 2003.
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The estimates were prepared as follows. We took the relative risk estimates from
McMichael, et al., op. cit., for each of the major sources for 2030 and applied them to the
baseline mortality risk from the WHO data cited op. cit. for 2004. We have used the
temperature estimates from the RICE-Yale baseline, which reach the same temperature
level in 2050 as the climate assumptions in McMichael et al., so we have labeled these as
“2050 impacts.” There will be some inconsistency because that study used different
assumptions about GDP growth. For each of the three diseases, we took the upper
response for the “unmitigated emissions” scenario. [Source: health_impacts_v2.xlsx,
sheet “Future impacts”]
36
The data on life expectancy are from the World Bank. [Source: le and pcy and
temp.wf1]
37
IPCC, Impacts 2007, p. 409. This is one of many statements, some of which are
inconsistent.
38
Center for Naval Analyses, National Security and the Threat of Climate Change,
Alexandria, VA: The CNA Corporation, 2007, available online at
http://www.cna.org/nationalsecurity/climate/ (hereafter the “CNA Report”).
39
The White House, National Security Strategy, May 2010, unclassified, available at
www.whitehouse.gov/sites/default/files/rss.../national_security_strategy.pdf.
40
These examples are drawn from the CNA report, op. cit., particularly the chapter on
Direct Impacts on Military Systems, Infrastructure, and Operations.
41
This is from the thoughtful analysis by Rymn J. Parsons, “Taking up the Security
Challenge of Climate Change, Strategic Studies Institute, U.S. Army War Institute,
August 2009, available at
www.strategicstudiesinstitute.army.mil/pdffiles/PUB932.pdf.
42
Halvard Buhaug, Nils Petter Gleditsch, and Ole Magnus Theisen, “Implications of
Climate Change for Armed Conflict,” paper commissioned by the World Bank Group
for the “Social Dimensions of Climate Change” workshop, The World Bank,
Washington DC, 5–6 March 2008. This quotation is slightly edited for brevity.
43
See Nordhaus, Oneal, and Russett at ??. I modified the equation estimated in this
study by adding dummy variables “ifdepa2” and “ifdepb2.” These variables takes a
value of zero in normal times and a value of 1 if real GDP growth in the prior two years
was less than -5 percent per year in each year. The specification contains growth rates
44
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for each of the two countries of conflict and has 185,015 dyadic observations. The
coefficient in a linear regression of the probability of conflict on various determinants
had coefficients of -0.00095 ( + 0.0011) and -0.00028 ( + 0.00067) on the recession dummy
variables. These coefficients are very small and statistically insignificant. On the face,
they state that a sharp economic downturn in either country lowers the probability of
military conflict by about 0.1 percent per year, but this is very poorly determined. The
estimates are similar for different definitions of economic downturns for either 2 or 3
years and for downturns of greater than 1 to 20 percent per year. [Data set is
panel3a.wf1; program is econ_distress_war.prg]
Stern Review of the Economics of Climate Change, Cambridge University Press,
Cambridge, UK, p. 84 – 86..
45
One of the best detailed studies of adaptation in agriculture is Norman Rosenberg,
“Adaptation of agriculture to climate change,“ Climatic Change, Volume 21, Number 4,
August, 1992, pp. 385-405.
46
This figure and discussion are drawn from Robert Mendelsohn, William D. Nordhaus
and Daigee Shaw, “Measuring the Impact of Global Warming on Agriculture,” American
Economics Review, 1996.
47
48
The plot is from IPCC, Impacts: 2007, p. 286.
The reasoning is the follows. World wheat production in 2008 was 680 million metric
tons, of which about 10 million tons was from Kansas. A 10 percent decline of Kansas
production with a supply elasticity of 0.2 is estimated to raise prices by about ½ percent.
This would raise the prices of products with wheat by less than 0.1 percent.
49
The figure shows the ratio of the price index of farm output to the price of all GDP.
Data are from the U.S. Bureau of Economic Analysis, Table 1.12. [Source: q011109.wf1;
Figure: fig_real_farm_p]
50
See IPCC, Impacts: 2007, p. 297. At 3 °C, 2 models showed an increase in food prices of
around 15 percent, 2 models showed a decrease of around 10 percent, and 1 model
showed no change.
51
The study is Richard Tol, “The Economic Impact of Climate Change,” Working Paper
No. 255, Economic and Social Research Institute, Dublin, Ireland, September 2008.
[source: impacts_survey.xlsx]
52
The question of risk aversion is more complicated than it would appear at first glance.
The modern theory of risk holds that we will pay a risk premium to avoid losses of
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income or consumption that occur when we are likely to be poor. This is why we buy
fire insurance on our house. If our house burns down, we are not only out of a house
but have lost a substantial fraction of our wealth. On the other hand, it would not be
sensible to buy insurance to cover the risk that we win the lottery, which is a risk that
would leave us rich. In the case of climate change, we need to consider whether the
cases where we have higher damages are also associated with higher incomes. Since on
the whole this is likely to be the case (see Table II-1), buying insurance against higher
warming may be like buying insurance against winning the lottery.
Here is an interesting definition, “Technically, an abrupt climate change occurs when
the climate system is forced to cross some threshold, triggering a transition to a new
state at a rate determined by the climate system itself and faster than the cause.” See
National Academy of Sciences, Abrupt Climate Change: Inevitable Surprises, Washington,
D.C., National Academy Press, 2002, p. 14. I am particularly grateful to Richard Alley
for explaining many of these phenomena to me.
54
The statement is a slightly alteration of the original drawn from the transcript of
Dornbusch’s Munich lectures, published posthumously. See Rudi Dornbusch and
Stanley Fischer, “International Financial Crises” CESIFO Working Paper No. 926,
Category 6: Monetary Policy And International Finance, March 2003.
55
The Dornbusch quip is actually a very deep point about catastrophic structures. We
can often predict that a situation is dangerous, but we cannot predict the timing of the
crash. This is why we often tip over a canoe. If the canoe’s exact tipping point were
easily predictable, then we would avoid it. Note that financial crises and abrupt events
are different from high tides in their intrinsic unpredictability. People often proclaim
that they predicted the crisis of 2007-2009, but if you look carefully you find that they
were regularly predicting crashes that did not occur. This point is captured in Paul
Samuelson’s remark that the stock market predicted 9 of the last 5 recessions.
56
A useful summary of evidence is contained in Jonathan T. Overpeck, Bette L. OttoBliesner, Gifford H. Miller, Daniel R. Muhs, Richard B. Alley, and Jeffrey T. Kiehl,
“Paleoclimatic Evidence for Future Ice-Sheet Instability and Rapid Sea-Level Rise,”
Science, 311, 1747, 2006, pp. 1747-1750.
57
58
See the detailed analysis in IPCC, Science: 2007, particularly in section 10.3.4.
59
See IPCC, Science: 2007, Table 7.4, p. 535 and the surrounding discussion.
This argument is presented in James Hansen et. al., “Target atmospheric CO2: Where
should humanity aim?” Open Atmospheric Science Journal, 2008, vol. 2, pp. 217-231.
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These data refer to India and China. According to the Penn World Table 6.3, the
growth of Indian per capita real income was a factor of 4.8 from 1950 to 2007, while the
growth of Chinese per capita income was a factor between 14 and 23 depending upon
the measures used. Source: pcy india china.xlsx
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