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About Gas-CAP

Gas-CAP is a tool to evaluate the global emissions impact of national or sectoral emissions decisions. The user can set a global greenhouse emission target and then develop scenarios consistent with that emissions limit. The analysis can be conducted at the national level or based on industrial sectors.

The Gas-CAP tool is designed to push the boundaries of thinking in terms of emissions goals and feasibility. In the interests of sparking lively discussion, we encourage you to take the Gas-CAP Challenge.

Contents

The Gas-CAP Challenge

Using Gas-CAP, set a global CO2 emissions target and define a CO2 emissions trajectory by nation and sector that:

  • Is feasible based on your expert judgment
  • Stabilizes at the CO2 ppm that you believe we need to achieve

About Gas-CAP

Using publicly available data and a user-friendly interface, Gas-CAP provides a non-prescriptive, common, transparent framework to facilitate exploration and debate regarding emission trajectories and trade-offs.

Gas-CAP was introduced in beta v1 format on June 18, 2008, at the CITRIS-Copenhagen Research Conference on Climate & Energy. Feedback on this evolving product is welcome and encouraged.

We are particularly interested in feedback on your experience with Gas-CAP – including examples of analyses in which you’ve found it useful and any issues you have with the tool. If this tool has furthered your work or understanding, please drop a brief email - your positive feedback will energize our efforts as we continue the development!

Value Proposition

Gas-CAP is a tool to evaluate the global emissions impact of national or sectoral emissions decisions. The user can set a global CO2 emission target and then develop trajectories consistent with that emissions limit. The analysis can be conducted at the national level or based on industrial sectors.

Gas-CAP and the Climate Bottom Line

Gas-CAP is the simplest and one of the few publicly available tools that focuses solely on the climate bottom line: CO2 emissions and atmospheric concentration.

Gas-CAP addresses the Impact ("I") of the oft-referenced I=PAT equation:

Impact (Emissions) = Population * Affluence (GDP per capita) * Technology (Emissions/GDP) Many existing climate & energy tools address the Technology (emissions/GDP) component of IPAT, and Gas-CAP does not attempt to replicate this work. Gas-CAP assumes that users have a familiarity with the population growth, GDP growth, and Technology dimensions of the climate challenge. The tool allows the user to summarize their knowledge into country- & sector-level emissions trajectories, thus focusing discussion on the focus of international target-setting: the climate bottom line of emissions & atmospheric concentration.

Gas-CAP versus Other Emissions Models

Only a handful of publicly available tools focus on the climate bottom line of emissions & atmospheric concentration. These existing tools are in some cases more sophisticated, but offer a limited set of scenarios and involve more complicated user interfaces. Existing tools include the FAIR model by the Netherlands Environmental Assessment Agency and the Contraction & Convergence model by the Global Commons Institute.

Gas-CAP is designed to be a non-prescriptive, flexible sandbox with an immediately understandable interface. It offers experts and non-experts alike the opportunity to create emissions trajectories to fit any political perspective, and focuses discussion clearly on the climate bottom line.

Current Features

The beta v1 version of Gas-CAP includes the following features:

  • Global, national, and sectoral targeting
  • Sector-level targeting within nations
  • Nation-level targeting within sectors
  • Atmospheric concentration calculations
  • Ability to set the peak emissions year, pre-peak growth rate, stabilization level, and stabilization year
  • Choice of emission curve shapes
  • Top-15 emitting nations, 6 sectors
  • Emissions including all anthropogenic CO2 sources
  • Updated land use data from Houghton 2008

Future Features

  • Ability to show only selected countries or sectors plus “other” on the graph
  • Refined ppm sensitivity at extremes of emissions values
  • Improved Save functionality
  • Format improvements

We’re considering the following features for v2 of Gas-CAP. Feedback on these or other useful features is more than welcome:

  • Ability to group countries into regional or other combinations
  • Comparative analytics – emissions per capita (user-defined population), emissions vs. business-as-usual baseline (user-defined baseline), emissions per GDP (user-defined GDP)
  • Ability to overlay multiple regions, countries, or sectors on the same graph for comparison
  • Ability to download final emissions trajectory data into spreadsheet

We are also considering a complementary tool that bridges technology-specific emissions tools and Gas-CAP, should this feature prove important to users. If you have suggestions for future features or opinions about which ones are critical, email Stacy Jackson at jackson@citris-uc.org.

Unbiased Philosophy

Gas-CAP is designed as a common platform for parties of all political perspectives to explore potential climate mitigation policies. Care has been taken to ensure that Gas-CAP is as free as possible from biases regarding the “right” way to approach mitigation; the user is free to set targets and allocate emissions across nations, sectors, and time in any way the user considers appropriate.

Because the tool is unbiased, we expect it to be particularly useful as a discussion tool for parties with differing perspectives on the best approach to mitigation, and broadly useful as a tool to explore which scenarios have the potential for reaching a desired target.

Target Audience

Gas-CAP is intended to be highly user-friendly, and is intended to be useful to anyone who wishes to gain better intuition regarding the range of global emissions options and the global impact of national & sectoral emissions over time.

We particularly encourage conference & workshop organizers to use Gas-CAP in small group breakout sessions to generate data-based insights on emissions scenarios and to stimulate lively debate among participants regarding the feasibility and desirability of different policy choices.

Users include:

  • Legislators & their staff members
  • Government agency leaders
  • Business leaders
  • NGO leaders
  • Professors & graduate students
  • Journalists covering climate mitigation
  • Teachers & students of climate change
  • Citizens seeking better understanding of climate policy

Sample Applications

  1. Application 1: International policymakers are interested in understanding the cumulative global effect of each country’s independent greenhouse gas emissions policy. Using the calculator, policymakers can enter each country’s policy details and compare the total with the global emissions goal. Given its user-friendly interface, the calculator can be used “live” during policy discussions to ensure that national commitments add up to a globally desired result.
  2. Application 2: Electricity industry leaders are interested in understanding the likely future emissions requirements for their sector. Using the calculator, these leaders can explore the emissions requirements for their sector based upon varying scenarios for emissions in the other sectors and global emissions targets. Based upon the results of their scenario analysis, these leaders can establish criteria for selecting and developing technologies for their portfolios.
  3. Application 3: Government agencies and corporations are interested in funding research on technologies that will meet greenhouse emission reduction goals. Using the calculator, experts can interactively explore and discuss plausible sector-level emissions scenarios and the relative ease of achieving emissions reductions in one sector vs. another. These discussions can lead to emissions targets for different sectors and steer funding to technologies that show promise for achieving those targets.

Questions Gas-CAP Can and Can't Answer

Gas-CAP is designed as a tool to explore whether sector- and national-level emissions policies “add up” to desired global totals. It is a sandbox in which the user can play with different future scenarios for certain nations or sectors (e.g., “what if we dropped the emissions in sector X to zero?) and understand the increased or decreased pressure on other nations or sectors. It is a tool designed to encourage “what if” exploration at the macro-level of emissions.

Gas-CAP is not designed to answer questions regarding whether the user’s chosen scenarios are technically, economically, or politically feasible, nor is it designed to answer questions regarding “how” the emissions reductions are accomplished. It is expected that the tool will generate vigorous dialogue among users regarding feasibility & implementation.

Sample Questions

For each question, the answer is “it depends” on the user’s assumptions. The power of Gas-CAP is in helping the user understand the range of scenarios in which a certain answer will hold true.

  1. Sample National Question: “How many countries need to participate in order to achieve a certain global climate mitigation goal?”
    • Using the national calculator, the user can explore the outcomes of emissions reductions in a limited number of countries and reach a conclusion on the desired scope of an international agreement.
  2. Sample Sector Question: “Do we need zero-emission electricity?”
    • Using the sector calculator, the user can explore “what would you have to believe” about global targets and other sectors to support or reject the zero-emission requirement.
  3. Sample National Question: “How much can developing countries increase their emissions while still achieving a certain global climate mitigation goal?”
    • Using the national calculator, the user can explore the limits of developing country emissions growth vis-à-vis scenarios regarding global and developed country emissions.
  4. Sample Sector Question: “Can we limit the scope of discussion to sectors X & Y, or do we need to find reductions in all sectors?”
    • Using the sector calculator, the user can explore the reduction scenarios for sectors X & Y and reach an opinion re. the appropriate scope of policy discussions.

About Us

The Greenhouse Emissions Targeting Calculator is a collaborative effort of CITRIS and UC Berkeley’s Energy and Resources Group. The project is led by Stacy Jackson, with web development by Tao Starbow, advising by Prof. Dan Kammen and Prof. Alex Farrell (in memoriam), and terrific support from the entire C-GRACE team.

Contact: Stacy Jackson: jackson@citris-uc.org CITRIS (Gary Baldwin): (510) 643-8489

Methodology

Gas-CAP is a user-defined emissions scenario tool, and as such includes very few pre-defined assumptions. Different sets of equations with user-defined parameters define the pre-peak and post-peak stages of each emissions curve.

Nations and Sectors

Gas-CAP covers the top-15 emitting nations plus "Rest of World" as of year 2000. Sector emissions are divided into 6 sectors.

Sectors

Sector definitions are based on the IPCC Common Reporting Framework used by the UNFCCC (IPCC 1996b[1]), with large segments grouped together as follows:

  1. Electricity & Heat, including:
    • Public Plants (electricity, heat, CHP) (IPCC category 1A1a)
    • Autoproducers (electricity, heat, CHP) (IPCC category 1A)
    • Other Energy Industries (fossil fuels (IPCC category 1A1b,c)
  2. Manufacturing & Construction (IPCC category 1A2)
  3. Transportation, including:
    • Domestic Transportation (IPCC category 1A3)
    • International Bunkers (IPCC category 1A3ai, 1A3di)
  4. Other Combustion (IPCC category 1A4)
  5. Land Use Change & Forestry (IPCC category 5)
  6. Other, including:
    • Fugitive Emissions from natural gas flaring/venting (IPCC category 1B2c)
    • Industrial Processes: cement (IPCC category 2A1)

The IPCC categories not listed above apply to the non-CO2 gases, and hence are not included in the Gas-CAP data.

For more detailed definitions of the above categories, see pp.15-20 of WRI CAIT: Greenhouse Gas Sources & Methods, Feb. 2008.

Top 15 Nations

  1. United States
  2. China
  3. EU-25
  4. Indonesia
  5. Brazil
  6. Russian Federation
  7. Japan
  8. India
  9. Canada
  10. Malaysia
  11. South Korea
  12. Mexico
  13. Iran
  14. Australia
  15. South Africa

Together, these countries accounted for 73% of global CO2 emissions. See #Data Sources (emissions) for more information.

Data Sources (emissions)

Historical emissions are provided for the top-15 CO2 emitters as of 2004. Historical emissions data, 1990-2004, come from two sources:

Non-land-use emissions: Climate Analysis Indicators Tool (CAIT) version 5.0. (Washington, DC: World Resources Institute, 2008). Available at [7]. Note, for the Russian Federation, 1990 data at the sector level are unavailable. In this case, we assume that 1990 sectoral emissions were proportional to 1995 emissions.

Land use emissions: Houghton, R.A. 2008. Carbon Flux to the Atmosphere from Land-Use Changes: 1850-2005. In TRENDS: A Compendium of Data on Global Change. Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tenn., U.S.A

The Houghton 2008 land use analysis provides more recent and more accurate emissions figures than CAIT, which uses the figures from Houghton’s previous 2003 analysis. In his 2008 analysis, Richard Houghton extended the time period of coverage through 2005 and also revised his previous land use emissions estimates downward. He describes the change as follows:

“These estimates differ from those provided in the previous versions…because they include revised rates of land-use change for the period of 1960-2000. For example, in the 1990s the annual rate of loss of natural forests in the tropics averaged 16.7 million ha in the 2000 Forest Resources Assessment (FRA) (FAO 2001) and 11.6 million ha in the 2005 Assessment (FAO 2006). The lower estimates of tropical deforestation lowered the average net flux over the period 1990-2000 from ~2.2 PgC/yr (Houghton 2003) to ~1.5 PgC/yr.”

Houghton’s published data are available for a subset of the Top-15 countries/regions (US, Canada, Europe, China, former USSR), and is otherwise only available at a regional level. For those countries in our data set that do not have specific Houghton numbers, we have made an proportional estimate based on the former and revised Houghton figures. If, for example, Brazil represented X% of South & Central America’s land use-related emissions in the Houghton 2003 analysis (as shown in the CAIT database), we assume that Brazil accounts for the same fraction of South & Central America in the revised regional numbers.

Equations (pre-peak emissions)

The user has the choice of two curve shapes for the pre-peak curve, defined as follows:

  1. Accelerating increase: Emissions continue to grow at the user-defined growth rate (g) until the user-defined peak year. The equation is: Emissions (t) = Emissions (t-1) *(1+g), where t is the year, and g is the growth rate
  2. Slowing increase: Growth in emissions slows from the user-defined rate (g) in the current year to 0 in the user-defined peak year. The equation is: Emissions (t) = Emissions (current)*(1+g*(peak year – t)/peak year – current year), where t is the year and g is the initial growth rate.

Note, “current” year is defined as the latest year for which emissions data is available.

Equations (post-peak emissions)

The user has the choice of post-peak emissions curves, ranging from a slow start to a quick start. The equation is defined as follows:

Emissions (t) = Emissions (peak) + (S*((t-peakyr)*T)^R)/1000, where t =the year, S = 1 if the stabilization value is above the peak value (rising curve), = -1 otherwise, T = a user-defined level ranging from 1 to 1e7 (low numbers correspond to a slow start, high to a quick start) R = LN(ABS(Emissions (peak) – Emissions (stabilization))*1000)/LN((stab yr – peak yr)*T)

Data Sources (ppm)

The atmospheric concentration of CO2 in parts-per-million (ppm) is sourced from the U.S. National Oceanic & Atmospheric Administration (NOAA) Earth System Research Laboratory (ESRL)’s Global Monitoring Division (GMD):

Dr. Pieter Tans, NOAA/ESRL (www.esrl.noaa.gov/gmd/ccgg/trends)

The globally averaged marine surface annual mean data provided by ESRL are plotted in the atmospheric concentration (aka, “ppm”) graph for 1990-2007. The annual data have an uncertainty of +/- 0.10ppm, which reflects the mean of the standard deviations for each annual average estimated using a Monte Carlo technique.

Equations (ppm)

To calculate the annual impact of emissions on the atmospheric concentration of CO2 , the emissions are converted into parts-per-million by volume and multiplied by the “airborne fraction of total emissions”, the amount of emitted CO2 that stays in the atmosphere.

The airborne fraction is calculated by dividing CO2 emissions by the change in atmospheric CO2 concentration. This fraction averaged 0.43 from 1980-2004 and 0.46 from 1995-2004. See Data Sources (emissions) and Data Source (ppm). The future projections of CO2 concentrations in Gas-CAP assume an airborne fraction of 0.46.

Note, there is interannual variability in the historical data, and continued variability can be expected going forward. Interannual variability of the past decades can be explained by El Nino & La Nina cycles, volcanic eruptions (Mt. Pinatubo in 1991), and wildfires. For more information on interannual variability, see pp. 517 and 523-525 of IPCC Working Group I chapter 7.

Additionally, assuming continued trends, the airborne fraction is expected to increase over the next century due to reduced uptake of CO2 by land & ocean sinks. Model results vary widely, with an expected value of approximately 0.56 over the period to 2100 (ranging from 0.46 to 0.72). For more information, see pp. 533-539, "Coupling between the Carbon Cycle & Climate" in IPCC Working Group I chapter 7.

Conversely, the airborne fraction may decrease slightly if emissions drop substantially (to a level at which current year emissions fall below land & ocean uptake of prior year emissions).

GasCAP does not currently account for either of these factors that might drive increases or decreases in the airborne fraction, and thus presents a somewhat narrower range of ppm results than more refined projections. (more refined projections will look worse than Gas-CAP at high emission rates and better than Gas-CAP at very low emission rates)

For additional discussion of the physical atmospheric response to changes in emissions, see pp.824-25 of IPCC Working Group I chapter 10.

CO2 versus all GHGs

Gas-CAP uses CO2 only as the basis for emissions and atmospheric concentrations calculations. Other greenhouse gases (CH4, N2O, HFCs, PFCs, SF6) are excluded from the calculations. The reasons for CO2-only inclusion in Gas-CAP are as follows:

    • Data availability:
    • Emissions data for the non-CO2 GHGs is available only through year 2000; CO2 data is available through 2005 for land use (Houghton 2008) and through 2004 for non-land-use (WRI 2008).
    • Dynamics of the greenhouse gases:
  2. CO2 is the dominant contributor to global warming.
    • Between 1997-2007, CO2 accounted for 87% of the increase in global radiative forcing (W/m2) caused by greenhouse gases. Nitrous oxide accounted for 8%, methane accounted for 3%, and all other GHGs accounted for 2%. (NOAA Annual Greenhouse Gas Index, table 2)
  3. The atmospheric concentration of CO2 provides a good proxy for total global radiative forcing:
    • There are anthropogenic pollutants such as aerosols that provide negative radiative forcing, effectively offsetting the non-CO2 GHG effect.
    • As of 2005, the mean estimate of cumulative radiative forcing caused by anthropogenic CO2 was 1.66 W/m2 and the mean estimate of cumulative radiative forcing caused by net anthropogenic contributions was 1.6 W/m2 (see Figure SPM.2 in IPCC[2]) – nearly the same as the CO2 contribution.
    • Calculator simplicity:
    • A comprehensive calculator would be complex:
    • It would need to include all non-CO2 gases and anthropogenic impacts that generate both positive and negative radiative forcing impacts.
    • Such a calculator would require the user to make estimates for each gas separately, and would consequently require more expertise to use.
    • A CO2-only targeting calculator focuses the user and the policy debate on the most important greenhouse gas and allows us to maintain the design principles of accessibility, simplicity, ease of use, and transparency.

Note, some nations have higher proportions of non-CO2 greenhouse emissions than others (see below).

CO2 vs Non CO2 GHGs by Nation

Non-CO2 emissions range from 7-36% of individual nations’ CO2-equivalent greenhouse emissions. For countries with large non-CO2 emissions, a CO2-only analysis may understate the country’s greenhouse impact. See here for a chart.

Climate and Target Settting

In Gas-CAP, the user can define a global emissions curve to meet his/her desired stabilization level for ppm. Emissions target-setting involves acceptance of the underlying variability and uncertainty in the climate response, which are described by the IPCC in terms of ranges and probabilities of potential responses.

An increase in the ppm of CO2 leads to changes in global surface temperature and changes in ocean acidity. These changes have impacts on global freshwater supplies, sea level, survival of species, agricultural productivity, human disease vectors, wildfires, and other complex environmental phenomena.

The emissions of CO2 lead to an increase in the atmospheric concentration of CO2, commonly stated in parts-per-million (ppm(v)). 1 ppm means there is 1 molecule of CO2 per million molecules of dry air.

The following sections summarize the linkage between emissions, ppm, temperature, and impacts, providing background for the user to set emissions targets, and also provide information on policies currently under discussion in national and international political bodies.

For information on how ppm is calculated in Gas-CAP, see #Equations (ppm)

PPM Targets

PPM targets can be set based upon what is possible (technically, politically, economically), what is desirable (environmentally, socially), or some combination of the two. In line with the principles of Gas-CAP, we do not presuppose what is possible technically, politically, or economically, and we are not providing links to opinions about the feasibility of various approaches.

The links that follow reflect the best in scientific understanding of the consequences of various levels of ppm. It is up to the user to decide what outcomes and risk levels are acceptable when weighed against the requisite emission reductions.

Finally, it must be pointed out that changes in atmospheric concentrations are determined not only by emissions, but also by complex environmental feedback loops that may have large nonlinear effects. These feedback effects are not reflected in the ppm graph in Gas-CAP and should thus be considered an added risk. More information on feedback loops and abrupt climate change can be found in the links below.

Temperature and Impacts

Impacts to earth systems and human systems increase as temperature increases. The European Union has identified 2 degrees C above pre-industrial levels as the threshold for “dangerous climate change”. The charts below will help the user assess the 2oC threshold and come to his or her own conclusion.

Note, the temperature increase from pre-industrial to 2005 was 0.76 degrees C +/- 0.19[3], so 2 degrees C versus pre-industrial corresponds to ~1.25oC increase versus today.

Figure SPM.7 from the IPCC Final Summary for Policymakers[4] illustrates the high-level impacts:

Table 19.1 from the IPCC Working Group II report[5] summarizes the more nuanced effects for social systems, regional systems, biological systems, geophysical systems, and extreme events.

PPM and Temperature

There is no precise formula for the temperature that corresponds to a certain ppm, nor is there a complete instantaneous response of temperature to ppm. Instead, a change in ppm causes a gradual temperature change over time and this change is expected to fall within a certain range with a certain degree of probability. The lag in response is due to the time required for feedback effects to occur.

The two terms used to describe short-term and long-term temperature changes are: “transient climate response” and “equilibrium climate response”. Reaching equilibrium can take several centuries, especially at higher levels of ppm. The term “climate sensitivity” refers to the temperature response to a doubling of CO2 versus pre-industrial levels (to 560ppm).

The IPCC Final Summary for Policymakers[6] reports the transient climate sensitivity to be 1-3 degrees C and the equilibrium climate sensitivity to be 2-4.5 degrees C (most likely 3 degrees C). This range reflects 66% confidence that the climate sensitivity is above the low end of the range and below the high end of the range. These figures are used to calculate temperatures that correspond to ppm levels in the links below.

Some recent research papers (Harte & Torn 2006[7], Hansen 2008) suggest that the temperature range for equilibrium climate sensitivity is higher, due to slow feedback processes. The IPCC models include only fast feedback processes. When slow feedback processes are taken into account, Harte & Torn estimate the equilibrium climate sensitivity between 1.6-6.0 degrees C and Hansen estimates the most likely equilibrium climate sensitivity at 6 degrees C (twice the most likely level of the IPCC models).

The chart in the equilibrium link reflects only the IPCC estimate for temperature response.

IPCC Equilibrium Temperatures

The Figure SPM.11 from the IPCC Final Summary for Policymakers[8] illustrates the range of equilibrium temperatures corresponding to different atmospheric concentrations of CO2. The lower curve reflects a climate sensitivity of 2 degrees C, the upper curve reflects a climate sensitivity of 4.5 degrees C, and the middle curve reflects a climate sensitivity of 3 degrees C. The roman numerals reflect different stabilization scenarios considered by the IPCC.

The equilibrium IPCC estimate includes feedbacks from the reduction in ice albedo (reflectivity), an increase in water vapor in the air at higher temperatures (water vapor is also a greenhouse gas), and changes in clouds (can have positive or negative effects).

IPCC Transient Temperature

The IPCC modeling uses several scenarios (SRES) for future emissions in the absence of climate policies. Figure SPM.5 from the IPCC Final Summary for Policymakers[9] illustrates the transient temperature changes that can be expected over the next century for these different emissions scenarios. The bars on the right reflect the range of 1-3 degrees C per doubling of CO2 concentration.

Feedback Effects and PPM

Feedback effects/loops are chains of causation in which a change in a given variable leads to changes in other variables that ultimately result in changes to the original variable. A positive feedback is one in which a change in one direction leads to additional change in the same direction. A negative feedback is one in which a change in one direction leads to an offsetting change.

For example, an increase in temperature leads to increased decomposition, leads to increased release of soil carbon, leads to higher atmospheric CO2 concentration, leads to higher temperature. This is a positive feedback loop.

In climate science, feedback loops represent a large variable and introduce considerable uncertainty in climate projections. Feedback loops fall into several categories – fast versus slow and physical versus biogeochemical – and are typically interrelated. Examples include:

  • Ice albedo: increased temperature leads to less ice, leads to less reflectivity, leads to higher temperatures
  • Water vapor: increased temperature leads to increased water vapor (a greenhouse gas), leads to increased temperature
  • Vegetation changes: increased temperature leads to less net primary productivity, leads to a reduced terrestrial carbon sink, leads to higher atmospheric ppm, leads to increased temperature
  • Wildfire: increased temperature leads to more and larger wildfires, leads to release of more CO2, leads to higher atmospheric ppm, leads to increased temperature
  • Melting of permafrost: increased temperature leads to melting of tundra & permafrost, leads to soil decomposition, leads to release of more greenhouse gases, leads to higher atmospheric ppm, leads to increased temperature
  • Etc.

The IPCC has summarized feedback loops in the following sections:

See also #PPM and Ice for a paleoclimate perspective on slow and fast feedbacks.

Abrupt Climate Change

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."[10] Related terms include "climate surprise", "tipping point", "point of no return".

Examples of such non-linear changes may include changes in ocean circulation, melting of ice (caps, sheets, glaciers), vegetation changes (including release of CO2 and CH4 from soils & sediments), and atmospheric circulation.

Such changes become more likely at higher ppm levels, but there is no consensus on the ppm level that would trigger one of these events.

For more information, see pp.775-777 and 818-819 of IPCC Working Group I Chapter 10.

For more information on PPM & sea ice, follow the link below.

PPM and Ice

Ice has been melting more rapidly than expected in Greenland and the Arctic Circle, and much research is underway regarding the dynamics of ice melting and global warming.

A 2008 report by Jim Hansen (Director, NASA Goddard Institute for Space Studies) takes a different approach and looks at the history of ice formation. Hansen finds that large-scale glaciation of Antarctica began 50 million years ago, when CO2 fell to 350-500ppm (range reflects uncertainty). Hansen suggests that if glaciation were triggered by CO2 in this range, then irreversible melting of that same ice may also be triggered by CO2 in this range.

Note, the pre-industrial (pre-1750) atmospheric concentration of CO2 was 280ppm. The 2007 level was 383ppm. (see #Data Sources)

Emissions Policies

See the link below for current policy proposals around the world:

Policies in Key Countries (Pew Center on Global Climate Change)

  1. ↑ IPCC. 1996. Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories. Understanding the Common Reporting Framework. Available at: [1]
  2. ↑ IPCC, 2007: Summary for Policymakers. In: Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change [Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M.Tignor and H.L. Miller (eds.). Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.)
  3. ↑ IPCC, 2007: Summary for Policymakers. In: Climate Change 2007: The Physical Science Basis. Contribution of Working
  4. ↑ Climate Change 2007: Synthesis Report: Summary for Policymakers. Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, UK. [2]
  5. ↑ Schneider, S.H., S. Semenov, A. Patwardhan, I. Burton, C.H.D. Magadza, M. Oppenheimer, A.B. Pittock, A. Rahman, J.B. Smith, A. Suarez and F. Yamin, 2007: Assessing key vulnerabilities and the risk from climate change. Climate Change 2007: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, M.L. Parry, O.F. Canziani, J.P. Palutikof, P.J. van der Linden and C.E. Hanson, Eds., Cambridge University Press, Cambridge, UK, 779-810. [3]
  6. ↑ Climate Change 2007: Synthesis Report: Summary for Policymakers. Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, UK.. [4]
  7. ↑ Torn, MS and J Harte. Missing feedbacks, asymmetric uncertainties, and the underestimation of future warming. Geophysical Research Letters 33:10, 2006
  8. ↑ Climate Change 2007: Synthesis Report: Summary for Policymakers. Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, UK.. [5]
  9. ↑ Climate Change 2007: Synthesis Report: Summary for Policymakers. Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, UK. [6]
  10. ↑ Meehl, G.A., T.F. Stocker, W.D. Collins, P. Friedlingstein, A.T. Gaye, J.M. Gregory, A. Kitoh, R. Knutti, J.M. Murphy, A. Noda, S.C.B. Raper, I.G. Watterson, A.J. Weaver and Z.-C. Zhao, 2007: Global Climate Projections. In: Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change [Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M. Tignor and H.L. Miller (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.
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