Carbon Emission Scenarios
Introduction
Lesson 6
Now that we have explored the underlying workings of the climate system,
experimented with actual climate models and validated their predictions, we are in a position to use climate models to make projections of future climate change.
Before we can project human-caused climate changes, however, we must consider the various plausible scenarios for future human behavior, and resulting
greenhouse gas emissions pathways.
What will we learn in Lesson 6?
By the end of Lesson 6, you should be able to:
● Discuss the range of hypotheticaI pathways of future greenhouse gas emissions;
● Distinguish between the concepts of and equivalent emissions;
● ExpIain the Kaya Identity;
● ExpIain the concept of stabilization of greenhouse gas concentrations; and
● Discuss the wedges concept for controIIing greenhouse gas emissions.
What will be due for Lesson 6?
Please refer to the Syllabus for specific time frames and due dates.
The following is an overview of the required activities for Lesson 6. Detailed directions and submission instructions are located within this lesson.
● Read
o IPCC Fifth Assessment Report, Working Group 1
■ E Future GIobaI and RegionaI CIimate Change: p. 19-20
■ E.8 CIimate StabiIization, CIimate Change Commitment and IrreversibiIity: p. 27-29
■ Box SPM.1 Representative Concentration Pathways: p. 29
o Dire Predictions, v.2: p. 92-93
● Begin Project #1: Design your own fossil fuel emissions scenario that would limit future warming by 2100 to 2.5°C relative to pre-industrial levels.
● Participate in Lesson 6 discussion: Carbon Emission Scenarios
Questions?
If you have any questions, please post them to our Questions? discussion forum (not e-mail), located under the Home tab in Canvas. The instructor will check that discussion forum daily to respond. Also, please feel free to post your own
responses if you can help with any of the posted questions.
‘SRES’ Scenarios and ‘RCP’ Pathways
Scientists attempt to create scenarios of future human activity that represent
plausible future greenhouse emissions pathways. Ideally, these scenarios span the range of possible future emissions pathways, so that they can be used as a basis for exploring a realistic set of future projections of climate change.
In previous IPCC assessments, the most widely used and referred-to family of
emissions scenarios were the so-called SRES scenarios (for Special Report on
Emissions Scenarios) that helped form the basis for the IPCC Fourth Assessment Report. These scenarios made varying assumptions (‘storylines’) regarding future global population growth, technological development, globalization, and societal values. One (the A1 ‘one global family’ storyline chosen by Michael Mann and Lee Kump in version 1 of Dire Predictions) assumed a future of globalization and rapid economic and technological growth, including fossil fuel intensive (A1FI), non-
fossil fuel intensive (A1T), and balanced (A1B) versions. Another (A2, ‘a divided world’) assumed a greater emphasis on national identities. The B1 and B2 scenarios assumed more sustainable practices (‘utopia’), with more global-focus and regional- focus, respectively.
Let us now directly compare the various SRES scenarios both in terms of their
annual rates of carbon emissions, measured in gigatons (Gt) of carbon (1Gt =
1012 tons), and the resulting trajectories of atmospheric concentrations. Getting the concentrations actually requires an intermediate step involving the use of simple model of ocean carbon uptake, to account for the effect of oceanic absorption of atmospheric .
Figure 6.1: Estimated concentrations (top) and Annual Carbon Emissions (bottom) for the Various IPCC SRES Scenarios.
Credit: Robert A. Rohde /
We can see from the above comparison how various trajectories of our future
carbon emissions translate to atmospheric concentration trajectories. From the
point of view of controlling future concentrations, these graphics can be quite
daunting. Depending on the path chosen by society, we could plausibly
approach concentrations that are quadruple pre-industrial levels by 2100. Even in the best case of the SRES scenarios, B1, we will likely reach twice pre-industrial levels (i.e., around 550 ppm) by 2100. And to keep concentrations below this level, we can see that we have to bring emissions to a peak by 2040, and ramp them
down to less than half current levels by 2100.
You might wonder, what scenario do we actually appear to be following? Over the first ten years of these scenarios, observed emissions actually were close to the
most carbon intensive of the SRES scenarios—A1FI. This gives you an idea of how challenging the problem of stabilizing carbon emissions at levels lower than twice pre-industrial actually is.
Figure 6.2: Observed Historic Emissions Compares with the Various IPCC SRES Scenarios.
Credit: The Copenhagen Diagnosis
One problem with the SRES scenarios—indeed, a fair criticism of them—is that
they do not explicitly incorporate carbon emissions controls. While some of the
scenarios involve storylines that embrace generic notions of sustainability and
environmental protection, the scenarios do not envision explicit attempts to
stabilize concentrations at any particular level. For the Fifth Assessment Report, a new set of scenarios, called Representative Concentration Pathways (RCPs), was developed. They are referred to as pathways to emphasize that they are not
definitive, but are instead internally consistent time-dependent forcing projections that could potentially be realized with multiple socioeconomic scenarios. In
particular, they can take into account climate change mitigation policies to limit
emissions. The scenarios are named after the approximate radiative forcing relative to the pre-industrial period achieved either in the year 2100, or at stabilization after
2100. They were created with ‘integrated assessment models’ that include climate, economic, land use, demographic, and energy-usage effects, whose greenhouse gas concentrations were then converted to an emissions trajectory using carbon cycle models.
The RCP2.6 scenario peaks at 3.0 W / m2 before declining to 2.6 W / m2 in 2100, and requires strong mitigation of greenhouse gas concentrations in the 21st century. The RCP4.5 and RCP6.0 scenarios stabilize after 2100 at 4.2 W / m2 and 6.0 W / m2, respectively. The RCP4.5 and SRES B1 scenarios are comparable; RCP6.0 lies between the SRES B1 and A1B scenarios. The RCP8.5 scenario is the closest to a ‘business as usual’ scenario of fossil fuel use, and has comparable forcing to SRES A2 by 2100.
In all RCPs global population levels off or starts to decline by 2100, with a peak value of 12 billion in RCP8.5. Gross domestic product (GDP) increases in all
cases; of note, the RCP2.6 pathway has the highest GDP, though it has the least dependence on fossil fuel sources. Carbon dioxide emissions for all RCPs except the RCP8.5 scenario peak by 2100.
Even the RCPs have encountered a fair bit of criticism. For the next IPCC
Assessment Report (due in 2021-2022), scientists and modelers are using Shared
Socioeconomic Pathways (SSPs), which link specific policy decisions with
projected emissions outcomes. The readings this week include a about the issue of RCPs and the path forward with SSPs.
Figure 6.3a: RCP Global Population Scenarios Click here for text description of Figure 6.3a
Global Population
In all pathways, global population levels off or starts to decline by 2100; the highest world population (12 billion) is achieved by 2100 in RCP 8.5
Gross Domestic Product
Gross Domestic product (GDP) increases in all cases, and interestingly, the highest GDP is realized in the RCP 2.6 scenario. Energy consumption increases in all
scenarios, with non-fossil-carbon-based energy sources most important in RCP 2.6; RCP 8.5 relies heavily on coal
Carbon Dioxide Emissions
Future emissions differ quite dramatically among the scenarios. The largest growth and cumulative release of CO2 is associated with the RCAP 8.5 fossil-fuel-
intensive scenario, while the smallest is associated with the RCP 2.6 scenario
Credit: Mann & Kump, Dire Predictions: Understanding Climate Change, 2nd Edition
© 2015 Dorling Kindersley Limited.
Figure 6.3b: RCP Global Population Scenarios
Credit: Mann & Kump, Dire Predictions: Understanding Climate Change, 2nd Edition
© 2015 Dorling Kindersley Limited.
Figure 6.4: RCP Gross Domestic Product Scenarios.
Credit: Mann & Kump, Dire Predictions: Understanding Climate Change, 2nd Edition
© 2015 Dorling Kindersley Limited.
Figure 6.5: RCP Carbon Dioxide Emission Scenarios.
With all of these scenarios, stabilizing CO2 concentrations requires not just
preventing the increase of emissions, but reducing emissions. This leads naturally to our next topic—the topic of stabilization scenarios.
Stabilizing CO2 Concentrations
Before we proceed, it is useful to cover a few more important details. You that the radiative forcing due to a given increase in
atmospheric concentration, , can be approximated as:
where is the initial concentration and is the final concentration. This gives a forcing for doubling of from pre-industrial values (i.e., = 280 ppm and = 560 ppm) of just under . Given the typical estimate of climate sensitivity we discussed during the
past two lessons, we know that this forcing translates to about 3°C warming. That means, we get about 0.75°C warming for each of radiative forcing.
Think About It!
Thus far, has increased from pre-industrial levels of 280 ppm to current levels of around 410 ppm. Based on the relationships above, what radiative forcing and
global mean temperature increase would you expect in response to our behavior so far?
Click for answer.
Using the formula above, we get a radiative forcing of ΔF = 2.04 W/m2.
Given that we get roughly 0.75°C warming for each W/m2 forcing, this gives slightly more than 1.5°C warming.
If you successfully answered the question above, you know that the increases so
far should have given rise to 1.5°C warming of the globe. Yet we have only seen
about 0.8°C warming. Are the theoretical formulas wrong? Did we make a
mistake? Actually, it is neither. First of all, we know that it takes decades for the
climate system to equilibrate to a rise in atmospheric , so we have not yet realized the expected equilibrium warming indicated by the equilibrium climate
sensitivity. Models indicate that there is as much as another 0.5°C of warming still in the pipeline, due to the increases that have taken place already. That alone would almost explain the 0.7°C discrepancy between the warming we expect, and the
lesser warming we’ve observed.
However, we have forgotten two other things that—as it happens—roughly cancel out! First of all, is not the only greenhouse gas whose concentrations we have been increasing through industrial and other human activities. There are other
greenhouse gases—methane, nitrous oxide, and others—whose concentrations we have increased, and whose concentrations are projected to continue to rise in the various SRES and RCP scenarios we have examined.
Figure 6.6: Greenhouse Gas Levels Resulting from Various Emissions Scenarios.
Credit: Mann & Kump, Dire Predictions: Understanding Climate Change, 2nd Edition
© 2015 Dorling Kindersley Limited.
We need to account for the effect of all of these other greenhouse gases. We can do this using the concept of equivalent ( _eq). _eq is the concentration of that would be equivalent, in terms of the total radiative forcing, to a combination of all the
other greenhouse gases. If we take into account the rises in methane and other
anthropogenic greenhouse gases, then the net radiative forcing is equivalent to
having increased to a substantially higher, roughly 485 ppm! In other words, the
current value of _eq is 485 ppm. This fact has caused quite a bit of confusion,
leading some commentators (see this ) to incorrectly sound the alarm that it is already too late to stabilize concentrations at 450 ppm and, hence, to avoid breaching the targets that have been set by some as constituting dangerous
anthropogenic interference with the climate ( for a discussion of these considerations).
Nonetheless, if _eq has reached 485ppm, does that mean that we are committed to the net warming that can be expected from a concentration of 485 ppm ? Well, yes and no. The other thing we have left out is that greenhouse gases are not the only significant anthropogenic impact on the climate. We know that the production of sulphate and other aerosols has played an important role, cooling substantial
regions of the Northern Hemisphere continents, in particular, during the past
century. The best estimate of the impact of this anthropogenc forcing, while quite uncertain, is roughly -0.8 of forcing, which is equivalent—in this context—to the contribution of negative 60 ppm of . If we add -60 ppm to 485 ppm we get 425
ppm—which is closer to the current actual concentration of 408 ppm. So, in other words, if we take into account not only the effect of all other greenhouse gases, but also the offsetting cooling effect of anthropogenic aerosols, we end up roughly
where we started off, considering only the effect of increasing atmospheric concentration through fossil fuel burning.
It is, therefore, a useful simplification to simply look at atmospheric alone as a proxy for the total anthropogenic forcing of the climate, but there are some
important caveats to keep in mind:
(1) the various scenarios assume that the sulphate aerosol burden remains unchanged. If we instead choose to clean up the atmosphere to the point of scrubbing all current sulphate aerosols from industrial emissions, we are left with the faustian bargain of experiencing the additional climate change impacts of a sudden effective increase of atmospheric of 60 ppm;
(2) not all greenhouse gases are created the same—some, such as
methane, have far shorter residence times in the atmosphere (timescale of years) than does , which persists for centuries.
That means that there is a far greater future climate change commitment embodied in a scenario of pure emissions than the same equivalent emissions consisting
largely of methane. This has implications for the abatement strategies we will discuss later in the course.
These limitations notwithstanding, let us now consider the impact of various
pure scenarios. Let us focus specifically on scenarios that will stabilize
atmospheric at some particular level, i.e., so-called stabilization scenarios.
Invariably, these scenarios involve bringing annual emissions to a peak at some
point during the 21st century, and decreasing them subsequently. Obviously, the
higher we allow the concentrations to increase and the later the peak, the higher the ultimate concentration is going to be. The various possible such scenarios are
shown below in increments of 50 ppm. If we are to stabilize concentrations at 550 ppm, we can see that emissions should be brought to a peak of no more than 8.7
gigatons of carbon per year, by around 2050, and reduced below 1990 levels (i.e., 6 gigatons carbon per year) by 2100. For comparison, as we saw earlier that current emissions are at roughly 8.5 gigatons per year and rising at the rate of the carbon- intensive A1FI SRES emissions scenario, so we are already “behind the curve” so to speak, even for 550 ppm stabilization.
For 450 ppm stabilization, the challenge is far greater. According to the figure
below, we would have had to bring emissions to a peak before 2010 at roughly 7.5 gigatons per year, and lower them to roughly 4 gigatons per year (i.e., 33% below 1990 levels) by 2050. Obviously, that train has already left the station.
Alternatively, the RCP2.6 pathway is an example of a 450 ppm stabilization
scenario consistent with where we are now, that involves bringing emissions to a peak within the next decade below 10 gigatons per year, and reducing them far
more dramatically, to near zero 80% by 2100 through various mitigation policies. With every year we continue with business-as-usual carbon emissions, achieving a 450 ppm stabilization target becomes that much more difficult, and involves far
greater reduction of emissions in future decades. It is for this reason that the
problem of greenhouse gas stabilization has been referred to by some scientists as a problem with a very large .
Figure 6.7: Annual emissions and Resulting concentrations for Various Stablization Scenarios.
Credit: Robert A. Rohde /
The “Kaya Identity”
We can actually play around with greenhouse gas emissions scenarios ourselves.
To do so, we will take advantage of something known as the
. Technically, the identity is just a definition, relating the quantity of annual carbon emissions to a factor of terms that reflect (1) population, (2) relative (i.e., per capita) economic production, measured by annual GDP in dollars/person,
(3) energy intensity, measured in terawatts of energy consumed per dollar added to GDP, and (4) carbon efficiency, measured in gigatons of carbon emitted per
terawatt of energy used. Multiply these out, and you get gigatons of carbon
emitted. If the other quantities are expressed as a percentage change per year, then the carbon emissions, too, are expressed as a percentage change per year, which, in turn, defines a future trajectory of carbon emissions and concentrations.
Mathematically, the Kaya identity is expressed in the form:
where
is global emissions from human sources
is global population
is world GDP
is global energy consumption
By projecting the future changes in population (P), economic production , energy intensity , and carbon efficiency , it is possible to make an informed projection of future carbon emissions . Obviously, population is important as, in the absence of anything else, more people means more energy use. Moreover, economic
production measured by GDP per capita plays an important role, as a bigger
economy means greater use of energy. The energy intensity term is where
technology comes in. As we develop new energy technologies or improve the
efficiency of existing energy technology, we expect that it will take less energy to increase our GDP by and additional dollar, i.e., we should see a decline in energy intensity. Last, but certainly not least, is the carbon efficiency. As we develop and increasingly switch over to renewable energy sources and non-fossil fuel based energy alternatives and improve the carbon efficiency of existing fossil fuel
sources (e.g., by finding a way to extract and sequester ), we can expect a decline in this quantity as well, i.e., less carbon emitted per unit of energy production.
Fortunately, we do not have to start from scratch. There is a convenient here, provided courtesy of David Archer of the University of Chicago
(and a blogger ). Below a brief demonstration of how the tool can be used. After you watch the demonstration, use the link provided above to play
around with the calculator yourself.
Video: Kaya Demo – Part 1 (4:59)
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Kaya Demo (part 1)
Click here for transcript of Kaya Demo (part 1).
PRESENTER: OK, we’re now going to play around with this online calculator that uses that Kaya identity to project future CO2 emissions. And this identity, as we
now know, uses the fact that CO2 emissions are going to be a product of various
terms that contribute to emissions growth, population, GDP per person, relative
economic growth, energy intensity, the amount of energy we can get for a dollar– a given amount of money, and carbon efficiency, how efficient we are at producing energy in a non-carbon intensive manner.
So the idea is that population, we can use demographic projections that, for
example, have global population leveling out somewhere around 11 billion later
this century. Projections of relative– that is per capita economic growth, that as the world becomes more industrialized as developing nations develop more industrial economies, that we’re likely to see an increase in relative economic expansion per person. Energy intensity, in principle, should decrease over time. As we develop
more efficient means of obtaining energy, we will decrease the cost in dollars for a given watt of power.
And finally, carbon efficiency. As we switch over to less carbon intensive sources of energy, we will decrease over time, the amount of carbon that we emit for each unit of power, say, a terawatt of power. So we can calculate CO2 emissions
trajectories as a product of these various terms. Now, let’s use the default values that are set in the calculator and do the calculation.
And here we go. This red curve is the projected future carbon emissions, given the values that we’ve chosen for the various terms. And the blue pluses here show
historical values of carbon emissions. And so we can sort of see how our projection ties into the past historical trends. We can use a carbon cycle model that involves some assumptions about both the oceans and the terrestrial biosphere that
calculates the changes in CO2 concentrations over time, given this carbon emission scenario.
And the red curve is what we’re projecting for future CO2. By 2100, we reach
about 700 parts per million. And you can compare that trajectory to various
stabilization scenarios. The green curve shows what the CO2 concentrations would be if we were to stabilize CO2 concentrations at 350 parts per million. The blue is 450 parts per million and so on. The yellow is 750 parts per million. Eventually,
CO2 concentration stabilizes at 750 parts per million in that stabilization scenario.
So we can see how our projected emissions are comparing with various
stabilization scenarios. And if we take this as sort of business as usual, these
various assumptions about population, GDP, energy intensity, and carbon
efficiency, then we see that, in fact, we’ll be well over the 750 stabilization
scenario. We’ll already be at 700 parts per million at 2,100 with CO2 continuing to rise.
We can calculate accordingly the amount of carbon free energy we would need,
given the assumptions of population, energy intensity. We can calculate how much carbon free energy we would need to produce to meet our energy demands if we are to keep CO2 to the specified level. And so we see the amount of carbon free energy that would be required in the various CO2 stabilization scenarios. And the red curve is the amount of carbon free energy that we would need to–
Credit:
Video: Kaya Demo – Part 2 (3:55)
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Kaya Demo (part 2)
Click here for transcript of Kaya Demo (part 2).
PRESENTER: OK. So we were just looking at the carbon-free energy
requirements. And the red curve tells us how much carbon-free energy we would need to produce, given the assumptions that we’ve made here and given the
scenarios shown for both carbon emissions and CO2 concentrations.
We can also see how our assumptions regarding each of these terms compare to historical numbers, population growth in the past versus our projected population growth under this assumption that we’ve made of stabilizing global population at 11 billion later this century or early next century, the assumption of a GDP per
person relative economic expansion of 1.6% per year– these are the historical values, the pluses. And the curve shows what we’re projecting for the future.
Energy intensity– our curve sort of follows the past couple decades of data, as far as energy intensity is concerned. And so we might imagine that there have been some developments in technology that have led to a trend in recent decades that may be more representative of the trend we would expect in the future than, say, the numbers from the early 20th century. So our projected energy intensity over time sort of matches the past few decades of energy intensity information.
And finally, carbon efficiency– this is the decline we’re projecting as we become more carbon efficient in our energy usage, fewer gigatons of carbon produced per terawatt. We are extrapolating the past trend. And we project increasing carbon efficiency, increasingly less reliance on carbon-based energy as time goes on.
So these are the underlying assumptions in our default projection here. And as we’ve seen, in that default projection, which corresponds to business as usual, we’re going to be upwards of 700 parts per million by the end of the century.
If we’re looking to stabilize CO2 concentrations at, say, 550 parts per million–
down in here, the purple curve– then clearly, we are going to need to change our behavior. We’re going to need to change these various terms, some combination of these terms, in such a way that we lower CO2 increase.
And accordingly, as the purple curve shows, we would need to produce less carbon-free energy in that stabilization scenario, in the 550 parts per million stabilization scenario.
So we can play around with these numbers and try to figure out how we would
actually go about achieving a particular stabilization, what terms we might be able to change through technology and through future policy changes, and how those
changes would translate to a CO2 emission scenario and our ability to stabilize CO2 concentrations at some particular level.
So the next thing we’ll do is to play around a little bit with these numbers and see if we might be able to lower our projected CO2 increase from the current trajectory, the business-as-usual trajectory that has us at 700 parts per million, well over twice pre-Industrial by the end of the century.
Credit:
Video: Kaya Demo – Part 3 (4:59)
<
Kaya Demo (part 3)
Click here for transcript of Kaya Demo (part 3).
PRESENTER: OK. So first of all, imagine that we found a way to stabilize a population at a significantly lower level. Through appropriate governmental
policies, we found a way to limit global population to 10 billion, rather than 11 billion. Well, how does that change things?
Well, we can see we’ve lowered our carbon emissions, our projected carbon
emissions. The CO2 concentration at 2,100 is now a little bit above 650 parts per million. So we’ve knocked off about 50 parts per million of our projected CO2 increase by 2,100.
It would be very difficult to decrease the projected global population much more than that. But let’s say we go for 9 billion. Then we’ve now lowered the 2,100 CO2 concentration to below 650 parts per million. So we’re slowly working our way
towards a 550 stabilization.
Let’s imagine that we were able to increase energy efficiency more than is
currently projected, through new technologies that have not yet been incorporated or implemented, perhaps large-scale use of fusion energy. So let’s imagine that the energy intensity, that we can get a better improvement in energy intensity,
something closer to 1.5% decline, versus a 1% decline in the amount of energy that we need per unit dollar.
Well, now we have lowered CO2 concentrations even more. We’re a little bit above 550 parts per million. Now, of course, if we were to establish policies that favored non-carbon-based forms of energy, renewable energy, technology, then we can, of course, further improve our carbon efficiency.
And so we might imagine changing this number from minus 0.3% to maybe minus 0.6% or so through the introduction of appropriate policies. And now we have
come very close to 550 PPM stabilization.
So we would have to go in and look in more detail at the assumptions that go into assuming that we can change our carbon efficiency by the amount that we’ve
changed it or that we can change energy intensity by the amount we’ve changed it. If we, for example, look at how we now are comparing with the historical
trajectories, we can see that our energy intensity curve is far more optimistic than would be suggested by even the past two decades, which we originally used to extrapolate the future trend somewhat optimistically.
If we look at carbon efficiency, then to decrease our reliance on our carbon-based energy by the amount assumed in the carbon efficiency number we’ve used, again, we would need to start doing significantly better in terms of that decline in use of carbon-based energy than we have done in even the past decade or two.
So clearly, changes in policy, changes in behavior– somewhat dramatic changes in policy and behavior– would be necessary to put us on the trajectories that are, in essence, dependent on these optimistic numbers we’ve now used to replace the so- called “business as usual” settings in our attempt to lower future CO2 emissions and future CO2 concentrations.
We can see, for example, that to follow this 550 PPM, we’ve come pretty close now to 550 PPM stabilization. We’re a little bit above the 550 PPM stabilization, but not too far above–
Credit:
Video: Kaya Demo – Part 4 (2:57)
<
Kaya Demo (part 4)
Click here for transcript of Kaya Demo (part 4).
PRESENTER: OK. So continuing where I left off, so with these settings, with
these assumptions, we’ve come pretty close to 550 PPM stabilization. If we look at the carbon emissions, we can see that, in fact, to achieve that CO2 trajectory, that roughly 550 PPM CO2 stabilization trajectory, we would need to bring emissions to a peak of less than eight gigatons per year by the next decade or so. And we
would need to begin bringing them down.
And in fact, if we had sought to stabilize CO2 concentrations at an even lower
level, say, 450 parts per million– now, that’s the blue curve here, which we’re well
above– to stabilize CO2 concentrations at 450 parts per million, we would need to bring emissions to a peak even sooner. And we would need to start bringing them down far more quickly in future decades.
And so for your first course project described later on in this lesson, you are going to be playing around with the settings, the various assumptions for per capita
economic growth, energy intensity, and carbon efficiency projections for the future and perhaps population assumptions about population growth and population
stabilization and see if you can come up with a realistic scenario, a justifiable
scenario, of assumptions for these various terms that allow us to stabilize CO2
concentrations at a level that would minimize the risk of exceeding what we might define as dangerous human interference with our climate.
So your first project will involve integrating what we’ve learned about climate
models, using simple climate models to look at projected temperature increases,
and then looking at the distribution, the probability of future temperature increases, and what changes we could make in policy and behavior that would allow us to
stabilize CO2 concentrations at a level that gives us a fairly high probability of avoiding breaching some temperature, some warming limit, that we might define as dangerous interference with the climate.
So you’ll have lots of time to play around with this and get used to using this tool yourself and combining it with projections that we make from our simple energy balance model to address these issues in your first project.
Credit:
The “Wedges” Concept
An increasingly widespread approach to characterizing greenhouse gas emissions reductions is the so-called Wedges concept introduced by Princeton researchers a few years ago. The concept is relatively straightforward. First, one defines the
current path of business-as-usual emissions. We can think of that ramp-like path as defining a stabilization triangle, as shown below.
Figure 6.8: Schematic of “Wedges” Approach to Defining Carbon Emissions Reduction Strategies.
Credit:
Based on the past one to two decades, the business-as-usual pathway corresponds to an increase of about 1.5 gigatons per decade—which, if we extrapolate linearly, amounts to about 7 gigatons of carbon emissions over the next 50 years. The
stabilization triangle can thus be split into 7 “wedges” that each represent 1 gigaton of carbon over the next 50 years. The first step to stabilizing greenhouse gas
concentrations is to freeze annual emissions so that they do not rise any further. To accomplish this, we would need to replace 7 gigaton wedges of projected
greenhouse gas emissions that would be required to meet the forecasted business- as-usual global energy requirements over the next 50 years. The individual wedges could be derived from greater energy efficiency, decreased reliance on fossil fuels, new technologies aimed at sequestration of , etc.
Of course, as we have seen from our discussion of, simply freezing greenhouse emissions at current levels is not adequate to stabilize
concentrations. The emissions must be decreased, eventually to zero, or at least
close enough to zero so that they are balanced by the natural rates of uptake of
carbon from the ocean and biosphere. So, the wedge approach must be
supplemented by an actual decrease in emission rates. In one idealization of the
approach, the wedges are used to freeze greenhouse annual emissions for 50 years, after which technological innovations that have been developed over the
intervening half century presumably make the problem of fully phasing out fossil fuel-based energy more tractable, and emissions can be reduced over the
subsequent 50 years as necessary to avoid breaching, e.g., twice pre-
industrial levels. Alternatively, more additional wedges, beyond the original 7, can be used, to not only freeze annual emissions at current levels during the next 50 years, but instead, bring them down.
Figure 6.9: Diagram Showing the Individual “Wedges” in the Wedge Strategy.
Credit: EPA
The wedge concept can be generalized beyond the global stabilization problem. For example, the U.S. EPA has introduced wedge-based plan for reducing
emissions in the U.S. transportation sector as a means of mitigating this important current contribution to U.S. greenhouse gas emissions.
Figure 6.10: Application of Wedge Concept to Greenhouse Emission Reductions in the U.S. Transportation Sector.
Credit: EPA
The Wedge Concept is an increasingly popular way to go about achieving the
required greenhouse gas emissions in the decades ahead, by thinking about each of the individual mitigation approaches that might buy us a wedge, or some fraction of a wedge, of reductions. It is a way to think about how to take a seemingly
intractable problem and break it up into many smaller, potentially tractable
problems which collectively can help civilization achieve the daunting emissions reductions necessary for avoiding potentially dangerous climate change.
Project #1: Fossil Fuel Emissions
Scenario for Limiting Future Warming
Climate Change mitigation is an example of the need for decision making in the
face of uncertainty. We must take steps today to stabilize greenhouse gas
concentrations if we are to prevent future warming of the globe, despite the fact
that we do not know precisely how much warming to expect. Furthermore, it is a problem of risk management. We do not know precisely what potential impacts
loom in our future, and where the threshold for dangerous anthropogenic impacts on the climate lies. Just like in nearly all walks of life, we must make choices in the face of uncertainty, and we must decide precisely how risk averse we are. Most
homeowners have fire insurance, yet they don’t expect their homes to burn down. They simply want to hedge against the catastrophe if it does happen. We can, in an analogous manner, think of climate change mitigation as hedging against
dangerous potential impacts down the road. This project aims to integrate a number of themes we have already explored—energy balance and climate modeling, and our current lesson on carbon emissions scenarios—to quantify how to go about
answering critical questions like, “How do we go about setting emissions limits that will allow us to hedge against the possibility of dangerous anthropogenic impacts (DAI) on our climate?”
Activity
Note:
For this assignment, you will need to record your work on a word processing document. Your work must be submitted in Word (.doc or .docx), or PDF (.pdf) format so the instructor can open it.
For this project, you will design your own fossil fuel emissions scenario that would limit future warming by the year 2100 to 2.0°C relative to the pre- industrial level.
Directions
1. Defining the threshold for DAI with the climate is a value judgment, as
much as a scientific one. The European Union has defined 2°C warming
relative to pre-industrial conditions to be the threshold of DAI (and this has been adopted in the recent Paris agreement). Use the with the standard, i.e., mid-range values of the gray body
parameters (and default settings for solar constant and albedo) to estimate the concentration for which we would achieve such warming when
equilibrium is reached. [Hint: you already did this particular calculation in Problem Set #3]
2. As discussed above, where we choose to set our emissions limits is also a matter of risk management. How risk averse are we? Let us assume that we want to limit the chance of exceeding DAI to only 5%, which is a typical
threshold used in risk abatement strategies. Let us also assume that
the low end and high end IPCC sensitivities define our best estimate of the 90% confidence interval for climate sensitivity, that is, there is a 5% chance that the true sensitivity is lower than the low end value, and a 5% chance
that the true sensitivity is higher than the high end value. Now, revisit the calculation that you did in Step 1, and use high-end setting of the gray body parameters to calculate the highest concentration that we can reach and
still keep the chance of exceeding DAI below 5%.
3. That was the easy part! Now is where things really get interesting. You have to come up with your own emissions scenario to stabilize concentrations
below the dangerous threshold that you calculated in Step 1 (i.e., using the mid-range values). Recall that based on Step 2 we are not being
particularly risk-averse under this assumption. By stabilizing, we will mean that by the year 2100 the concentration curve should be flat or nearly flat, indicating that any peak in concentrations has been reached before 2100 – and that the value of that peak should not exceed the threshold found in Step 1. You should make use of the on-line Kaya calculator that we
examined earlier in this lesson. Begin with the default settings in the Kaya calculator to figure out what baseline emissions scenario you are starting with and how much you need to do to achieve the required reduction in emissions to stabilize the concentration (given by the ‘pCO2’ curve when you choose ‘ISAM pCO2’ in the selector for the display on the right). You
then have several knobs you can tune to achieve an alternative emissions scenario; specifically, you can do the following. Through some combination of tuning these knobs within the indicated ranges, it should be possible to stabilize concentrations at the necessary threshold level. (The
concentration time-evolution curves corresponding to different specific stabilization scenarios are shown in the ‘ISAM pCO2’ plot.)
1. You can take measures to control global population growth, which are consistent with the spread of the population trajectories of the various SRES scenarios (e.g., A1, A2, B1, B2); though note that you cannot set the limit below the current global population of
7.8 billion.
2. You can change the rate of economic expansion (measured by GDP per capita) by up to 75% from the default value of 1.6% per year; that is, you can choose a value within the range of 0.4 to 2.8 % per
year.
3. You may change the rate of decline in energy intensity (measured in Watts per dollar) through new technology and/or the improvement of existing technology. You are permitted to change this value by
100% from its default setting of -1% per year, that is you can choose a value within the range of 0 to -2 % per year.
4. You may change the decline in carbon intensity by 100% from the
default value of -0.3 % per year, that is you can choose a value within the range of 0 to -0.6 % per year. This would reflect efforts to shift
from the current reliance on fossil fuel sources, or the improved carbon efficiency of fossil fuel energy sources, e.g., through
sequestration of , etc.
4. As you write up your results, please discuss the reasoning that you used in arriving at the various choices for the factors in the Kaya identity, i.e.,
provide justification for why your choices reflect plausible policies that
governments could in principle implement to achieve the necessary
reductions. If your projections depart from what might be expected based on an extrapolation of past historic trends, provide some justification. Your discussion here might, for example, be guided by the plot of the required
amounts of carbon-free energy to meet the requirements of your scenario, which is provided by the Kaya calculator tool. You will probably want to do some additional background reading. A good place to start would be the
original 2001 IPCC report on SRES scenarios:
5. Save your word processing document as either a Microsoft Word or PDF file and upload to the appropriate location in Canvas.
Submitting your work
● Upload your file to the Project 1 assignment in Canvas by the due date indicated in the Syllabus.
Grading Rubric
The instructor will use the general to grade this project.
Lesson 6 Discussion
Activity
Directions
Please participate in an online discussion of the material presented in Lesson 6:
Carbon Emission Scenarios.
This discussion will take place in a threaded discussion forum in Canvas (see
the for the specific information on how to use this tool) over
approximately a week-long period of time. Since the class participants will be
posting to the discussion forum at various points in time during the week, you will need to check the forum frequently in order to fully participate. You can also
subscribe to the discussion and receive e-mail alerts each time there is a new post.
Please realize that a discussion is a group effort and make sure to participate early in order to give your classmates enough time to respond to your posts.
Post your comments addressing some aspect of the material that is of interest to
you and respond to other postings by asking for clarification, asking a follow-up
question, expanding on what has already been said, etc. For each new topic you are
posting, please try to start a new discussion thread with a descriptive title, in order to make the conversation easier to follow.
Suggested Topics
● Discuss the concept of SRES scenarios and RCP pathways. How are these scenarios used for projecting future climate change? Given what we know about the current greenhouse emissions, which scenarios and/or pathways appear to best represent the real world?
● Discuss potential reasons for the switch from SRES scenarios to RCP
pathways in the latest IPCC report. How useful do you think the change was?
● What is the difference between emissions and equivalent emissions?
● Atmospheric increases observed so far should have given rise to 1.3°C warming, but we have only seen about 0.8°C warming. Why?
● What are stabilization scenarios?
● Do you find the Wedges Concept a useful tool for characterizing greenhouse gas emissions reductions?
Submitting your work
1. Go to Canvas.
2. Go to the Home tab.
3. Click on the Lesson 6 discussion: Carbon Emission Scenarios.
4. Post your comments and responses.
Grading criteria
You will be graded on the quality of your participation. See the online discussion grading rubric for the specifics on how this assignment will be graded. Please note that you will not receive a passing grade on this assignment if you wait until the
last day of the discussion to make your first post.
Lesson 6 Summary
In this lesson, we looked at the science underlying greenhouse gas emissions scenarios. We learned that:
● Up through the Fourth Assessment Report, the IPCC employed, for the
purpose of projecting future greenhouse gas concentrations, a set of
emissions scenarios, known as the SRES scenarios. These scenarios reflect a broad range of alternative assumptions about how future technology,
economic growth, demographics, and energy policies will evolve over the
next century, and, therefore, plausibly reflect the diversity of potential future global greenhouse emissions pathways;
● The SRES scenarios embody a range of projected increases in
atmospheric by 2100 from a lower end of approximately doubling the pre- industrial levels to reach 550 ppm (B1) to a near quadrupling of pre-
industrial levels (A1FI). Current emissions place us on a pathway close to the upper-end A1FI scenario;
● In the Fifth Assessment Report, the IPCC switched to the use of
Representative Concentration Pathways, or RCPs. These pathways (RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5) were chosen to be representative scenarios named for their total radiative forcing in the year 2100 (in watts per meter squared), and reflect a range of policies, from strong mitigation (RCP 2.6) to approximately business-as-usual (RCP 8.5);
● The stabilization scenarios are designed to stabilize
atmospheric concentrations at a particular level. The lower the desired
stabilization level, the lower and sooner the peak in emissions must be. To stabilize below twice the pre-industrial levels, emissions must be brought to a peak within the next few decades and rapidly brought down by the end of the century, falling below 1990 levels by mid-century. To stabilize below 450 ppm, levels must be brought to a peak within the next decade, and brought down to 80% below 1990 levels by mid-century;
● An increasingly widely used approach to defining the required carbon
emissions reductions is the Wedge approach. This approach involves
freezing emissions at current rates by offsetting projected business-as-usual emissions over the next 50 years (roughly 7 gigatons), envisioned, e.g., as 7 strategies for 1 gigaton carbon emission reductions. After 50 years,
emission rates are brought down, but how abruptly and rapidly depends on the stabilization targets desired. Additional wedges can be used to achieve lower stabilization targets by bringing down, rather than freezing, annual carbon emission rates over the next 50 years.
Reminder – Complete all of the lesson tasks!
You have finished Lesson 6. Double-check the list of requirements on to make sure you have completed all of the activities listed there
before beginning the next lesson.
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