3

Summary for Policymakers

1

Drafting Authors: 

Ottmar Edenhofer (Germany), Ramón Pichs-Madruga (Cuba), Youba Sokona (Mali), Shardul 

Agrawala (France), Igor Alexeyevich Bashmakov (Russia), Gabriel Blanco (Argentina), 

John Broome (UK), Thomas Bruckner (Germany), Steffen Brunner (Germany), Mercedes 

Bustamante (Brazil), Leon Clarke (USA), Felix Creutzig (Germany), Shobhakar Dhakal 

(Nepal / Thailand), Navroz K. Dubash (India), Patrick Eickemeier (Germany), Ellie Farahani 

(Canada), Manfred Fischedick (Germany), Marc Fleurbaey (France), Reyer Gerlagh 

(Netherlands), Luis Gómez-Echeverri (Colombia / Austria), Sujata Gupta (India / Philippines), 

Jochen Harnisch (Germany), Kejun Jiang (China), Susanne Kadner (Germany), Sivan Kartha 

(USA), Stephan Klasen (Germany), Charles Kolstad (USA), Volker Krey (Austria / Germany), 

Howard Kunreuther (USA), Oswaldo Lucon (Brazil), Omar Masera (México), Jan Minx 

(Germany), Yacob Mulugetta (UK / Ethiopia), Anthony Patt (Austria / Switzerland), Nijavalli 

H. Ravindranath (India), Keywan Riahi (Austria), Joyashree Roy (India), Roberto Schaeffer 

(Brazil), Steffen Schlömer (Germany), Karen Seto (USA), Kristin Seyboth (USA), Ralph Sims 

(New Zealand), Jim Skea (UK), Pete Smith (UK), Eswaran Somanathan (India), Robert Stavins 

(USA), Christoph von Stechow (Germany), Thomas Sterner (Sweden), Taishi Sugiyama 

(Japan), Sangwon Suh (Republic of Korea / USA), Kevin Chika Urama (Nigeria / UK), Diana 

Ürge-Vorsatz (Hungary), David Victor (USA), Dadi Zhou (China), Ji Zou (China), Timm Zwickel 

(Germany)

Draft Contributing Authors 

Giovanni Baiocchi (UK / Italy), Helena Chum (USA / Brazil), Jan Fuglestvedt (Norway), Helmut 

Haberl (Austria), Edgar Hertwich (Norway / Austria), Elmar Kriegler (Germany), Joeri Rogelj 

(Switzerland / Belgium), H.-Holger Rogner (Germany), Michiel Schaeffer (Netherlands), 

Steven J. Smith (USA), Detlef van Vuuren (Netherlands), Ryan Wiser (USA)

This Summary for Policymakers should be cited as:

IPCC, 2014: Summary for Policymakers, In: Climate Change 2014, Mitigation of Climate Change. Contribution of 

Working Group III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Edenhofer, 

O., R. Pichs-Madruga, Y. Sokona, E. Farahani, S. Kadner, K. Seyboth, A. Adler, I. Baum, S. Brunner, P. Eickemeier, B. 

Kriemann, J. Savolainen, S. Schlömer, C. von Stechow, T. Zwickel and J.C. Minx (eds.)]. Cambridge University Press, 

Cambridge, United Kingdom and New York, NY, USA.

Summary SPM for Policymakers

3

S

Table of Contents

SPM.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

SPM.2 Approaches to climate change mitigation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

SPM.3 Trends in stocks and flows of greenhouse gases and their drivers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

SPM.4 Mitigation pathways and measures in the context of sustainable development. . . . . . . . . . . . . . . . . . .10

SPM.4.1 Long-term mitigation pathways. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .10

SPM.4.2 Sectoral and cross-sectoral mitigation pathways and measures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .18

SPM.4.2.1 Cross-sectoral mitigation pathways and measures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .18

SPM.4.2.2 Energy supply . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .21

SPM.4.2.3 Energy end-use sectors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .22

SPM.4.2.4 Agriculture, Forestry and Other Land Use (AFOLU) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .25

SPM.4.2.5 Human settlements, infrastructure and spatial planning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .26

SPM.5 Mitigation policies and institutions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .27

SPM.5.1 Sectoral and national policies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .27

SPM.5.2 International cooperation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .30
4

SPM

Summary for Policymakers

Introduction

The Working Group III contribution to the IPCC’s Fifth Assessment Report (AR5) assesses literature on the scientific, 

technological, environmental, economic and social aspects of mitigation of climate change. It builds upon the Working 

Group III contribution to the IPCC’s Fourth Assessment Report (AR4), the Special Report on Renewable Energy Sources 

and Climate Change Mitigation (SRREN) and previous reports and incorporates subsequent new findings and research. 

The report also assesses mitigation options at different levels of governance and in different economic sectors, and the 

societal implications of different mitigation policies, but does not recommend any particular option for mitigation.

This Summary for Policymakers (SPM) follows the structure of the Working Group III report. The narrative is supported 

by a series of highlighted conclusions which, taken together, provide a concise summary. The basis for the SPM can be 

found in the chapter sections of the underlying report and in the Technical Summary (TS). References to these are given in 

square brackets.

The degree of certainty in findings in this assessment, as in the reports of all three Working Groups, is based on the 

author teams’ evaluations of underlying scientific understanding and is expressed as a qualitative level of confidence 

(from very low to very high) and, when possible, probabilistically with a quantified likelihood (from exceptionally unlikely 

to virtually certain). Confidence in the validity of a finding is based on the type, amount, quality, and consistency of 

evidence (e.g., data, mechanistic understanding, theory, models, expert judgment) and the degree of agreement.1

 Probabilistic estimates of quantified measures of uncertainty in a finding are based on statistical analysis of observations or 

model results, or both, and expert judgment.2

 Where appropriate, findings are also formulated as statements of fact 

without using uncertainty qualifiers. Within paragraphs of this summary, the confidence, evidence, and agreement terms 

given for a bolded finding apply to subsequent statements in the paragraph, unless additional terms are provided.

Approaches to climate change mitigation

Mitigation is a human intervention to reduce the sources or enhance the sinks of greenhouse gases. Mitigation, together with adaptation to climate change, contributes to the objective expressed in Article 2 of the United 

Nations Framework Convention on Climate Change (UNFCCC):

The ultimate objective of this Convention and any related legal instruments that the Conference of the Parties 

may adopt is to achieve, in accordance with the relevant provisions of the Convention, stabilization of greenhouse gas concentrations in the atmosphere at a level that would prevent dangerous anthropogenic interference 

with the climate system. Such a level should be achieved within a time frame sufficient to allow ecosystems to 

adapt naturally to climate change, to ensure that food production is not threatened and to enable economic 

development to proceed in a sustainable manner.

Climate policies can be informed by the findings of science, and systematic methods from other disciplines. [1.2, 2.4, 2.5, 

Box 3.1]

1 The following summary terms are used to describe the available evidence: limited, medium, or robust; and for the degree of agreement: low, 

medium, or high. A level of confidence is expressed using five qualifiers: very low, low, medium, high, and very high, and typeset in italics, e.g., 

medium confidence. For a given evidence and agreement statement, different confidence levels can be assigned, but increasing levels of evidence and degrees of agreement are correlated with increasing confidence. For more details, please refer to the guidance note for Lead Authors 

of the IPCC Fifth Assessment Report on consistent treatment of uncertainties. 2 The following terms have been used to indicate the assessed likelihood of an outcome or a result: virtually certain 99–100% probability, very 

likely 90–100%, likely 66–100%, about as likely as not 33–66%, unlikely 0–33%, very unlikely 0–10%, exceptionally unlikely 0–1%. Additional terms (more likely than not >50–100%, and more unlikely than likely 0–<50%) may also be used when appropriate. Assessed likelihood 

is typeset in italics, e.g., very likely.

SPM.1

SPM.2
5

S

Summary for Policymakers

Sustainable development and equity provide a basis for assessing climate policies and highlight the need for 

addressing the risks of climate change.3

 Limiting the effects of climate change is necessary to achieve sustainable 

development and equity, including poverty eradication. At the same time, some mitigation efforts could undermine action 

on the right to promote sustainable development, and on the achievement of poverty eradication and equity. Consequently, a comprehensive assessment of climate policies involves going beyond a focus on mitigation and adaptation 

policies alone to examine development pathways more broadly, along with their determinants. [4.2, 4.3, 4.4, 4.5, 4.6, 4.8]

Effective mitigation will not be achieved if individual agents advance their own interests independently. 

Climate change has the characteristics of a collective action problem at the global scale, because most greenhouse 

gases (GHGs) accumulate over time and mix globally, and emissions by any agent (e.g., individual, community, company, 

country) affect other agents.4

 International cooperation is therefore required to effectively mitigate GHG emissions and 

address other climate change issues [1.2.4, 2.6.4, 3.2, 4.2, 13.2, 13.3]. Furthermore, research and development in support 

of mitigation creates knowledge spillovers. International cooperation can play a constructive role in the development, diffusion and transfer of knowledge and environmentally sound technologies [1.4.4, 3.11.6, 11.8, 13.9, 14.4.3].

Issues of equity, justice, and fairness arise with respect to mitigation and adaptation.5 Countries’ past and future 

contributions to the accumulation of GHGs in the atmosphere are different, and countries also face varying challenges 

and circumstances, and have different capacities to address mitigation and adaptation. The evidence suggests that outcomes seen as equitable can lead to more effective cooperation. [3.10, 4.2.2, 4.6.2]

Many areas of climate policy-making involve value judgements and ethical considerations. These areas range 

from the question of how much mitigation is needed to prevent dangerous interference with the climate system to 

choices among specific policies for mitigation or adaptation [3.1, 3.2]. Social, economic and ethical analyses may be used 

to inform value judgements and may take into account values of various sorts, including human wellbeing, cultural values 

and non-human values [3.4, 3.10].

Among other methods, economic evaluation is commonly used to inform climate policy design. Practical tools 

for economic assessment include cost-benefit analysis, cost-effectiveness analysis, multi-criteria analysis and expected 

utility theory [2.5]. The limitations of these tools are well-documented [3.5]. Ethical theories based on social welfare 

functions imply that distributional weights, which take account of the different value of money to different people, should 

be applied to monetary measures of benefits and harms [3.6.1, Box TS.2]. Whereas distributional weighting has not 

frequently been applied for comparing the effects of climate policies on different people at a single time, it is standard 

practice, in the form of discounting, for comparing the effects at different times [3.6.2].

Climate policy intersects with other societal goals creating the possibility of co-benefits or adverse sideeffects. These intersections, if well-managed, can strengthen the basis for undertaking climate action. 

Mitigation and adaptation can positively or negatively influence the achievement of other societal goals, such as those 

related to human health, food security, biodiversity, local environmental quality, energy access, livelihoods, and equitable 

sustainable development; and vice versa, policies toward other societal goals can influence the achievement of mitigation 

and adaptation objectives [4.2, 4.3, 4.4, 4.5, 4.6, 4.8]. These influences can be substantial, although sometimes difficult 

to quantify, especially in welfare terms [3.6.3]. This multi-objective perspective is important in part because it helps to 

identify areas where support for policies that advance multiple goals will be robust [1.2.1, 4.2, 4.8, 6.6.1].

3 See WGII AR5 SPM. 4 In the social sciences this is referred to as a ‘global commons problem‘. As this expression is used in the social sciences, it has no specific implications for legal arrangements or for particular criteria regarding effort-sharing. 5 See FAQ 3.2 for clarification of these concepts. The philosophical literature on justice and other literature can illuminate these issues [3.2, 3.3, 

4.6.2].

S
6

SPM

Summary for Policymakers

Climate policy may be informed by a consideration of a diverse array of risks and uncertainties, some of 

which are difficult to measure, notably events that are of low probability but which would have a significant 

impact if they occur. Since AR4, the scientific literature has examined risks related to climate change, adaptation, 

and mitigation strategies. Accurately estimating the benefits of mitigation takes into account the full range of possible 

impacts of climate change, including those with high consequences but a low probability of occurrence. The benefits of 

mitigation may otherwise be underestimated (high confidence) [2.5, 2.6, Box 3.9]. The choice of mitigation actions is 

also influenced by uncertainties in many socio-economic variables, including the rate of economic growth and the evolution of technology (high confidence) [2.6, 6.3].

The design of climate policy is influenced by how individuals and organizations perceive risks and uncertainties and take them into account. People often utilize simplified decision rules such as a preference for the status quo. 

Individuals and organizations differ in their degree of risk aversion and the relative importance placed on near-term 

versus long-term ramifications of specific actions [2.4]. With the help of formal methods, policy design can be improved 

by taking into account risks and uncertainties in natural, socio-economic, and technological systems as well as decision 

processes, perceptions, values and wealth [2.5].

Trends in stocks and flows of greenhouse gases 

and their drivers

Total anthropogenic GHG emissions have continued to increase over 1970 to 2010 with larger absolute decadal 

increases toward the end of this period (high confidence). Despite a growing number of climate change mitigation 

policies, annual GHG emissions grew on average by 1.0 gigatonne carbon dioxide equivalent (GtCO2eq) (2.2%) per year 

from 2000 to 2010 compared to 0.4 GtCO2eq (1.3%) per year from 1970 to 2000 (Figure SPM.1).6,7 Total anthropogenic 

GHG emissions were the highest in human history from 2000 to 2010 and reached 49 (±4.5) GtCO2eq/yr in 2010. The 

global economic crisis 2007/2008 only temporarily reduced emissions. [1.3, 5.2, 13.3, 15.2.2, Box TS.5, Figure 15.1]

CO2 emissions from fossil fuel combustion and industrial processes contributed about 78% of the total GHG 

emission increase from 1970 to 2010, with a similar percentage contribution for the period 2000–2010 

(high confidence). Fossil fuel-related CO2 emissions reached 32 (±2.7) GtCO2/yr, in 2010, and grew further by about 

3% between 2010 and 2011 and by about 1–2% between 2011 and 2012. Of the 49 (±4.5) GtCO2eq/yr in total 

anthropogenic GHG emissions in 2010, CO2 remains the major anthropogenic GHG accounting for 76% (38±3.8 

GtCO2eq/yr) of total anthropogenic GHG emissions in 2010. 16% (7.8±1.6 GtCO2eq/yr) come from methane (CH4), 

6.2% (3.1±1.9 GtCO2eq/yr) from nitrous oxide (N2O), and 2.0% (1.0±0.2 GtCO2eq/yr) from fluorinated gases 

(Figure SPM.1). Annually, since 1970, about 25% of anthropogenic GHG emissions have been in the form of non-CO2

gases.8

 [1.2, 5.2]

6 Throughout the SPM, emissions of GHGs are weighed by Global Warming Potentials with a 100-year time horizon (GWP100) from the IPCC 

Second Assessment Report. All metrics have limitations and uncertainties in assessing consequences of different emissions. [3.9.6, Box TS.5, 

Annex II.2.9, WGI SPM] 7 In this SPM, uncertainty in historic GHG emission data is reported using 90% uncertainty intervals unless otherwise stated. GHG emission levels 

are rounded to two significant digits throughout this document; as a consequence, small differences in sums due to rounding may occur. 8 In this report, data on non-CO2 GHGs, including fluorinated gases, are taken from the EDGAR database (Annex II.9), which covers substances 

included in the Kyoto Protocol in its first commitment period.

SPM.3
7

S

Summary for Policymakers

Figure SPM.1 | Total annual anthropogenic GHG emissions (GtCO2eq / yr) by groups of gases 1970 – 2010: CO2 from fossil fuel combustion and industrial processes; CO2 from 

Forestry and Other Land Use (FOLU); methane (CH4); nitrous oxide (N2O); fl uorinated gases8 covered under the Kyoto Protocol (F-gases). At the right side of the fi gure GHG emissions in 2010 are shown again broken down into these components with the associated uncertainties (90 % confi dence interval) indicated by the error bars. Total anthropogenic 

GHG emissions uncertainties are derived from the individual gas estimates as described in Chapter 5 [5.2.3.6]. Global CO2 emissions from fossil fuel combustion are known within 

8 % uncertainty (90 % confi dence interval). CO2 emissions from FOLU have very large uncertainties attached in the order of ± 50 %. Uncertainty for global emissions of CH4, N2O 

and the F-gases has been estimated as 20 %, 60 % and 20 %, respectively. 2010 was the most recent year for which emission statistics on all gases as well as assessment of 

uncertainties were essentially complete at the time of data cut-off for this report. Emissions are converted into CO2-equivalents based on GWP1006 from the IPCC Second Assessment 

Report. The emission data from FOLU represents land-based CO2 emissions from forest fi res, peat fi res and peat decay that approximate to net CO2 fl ux from the FOLU as described 

in chapter 11 of this report. Average annual growth rate over different periods is highlighted with the brackets. [Figure 1.3, Figure TS.1] 

27 Gt

33 Gt

55%

17%

19%

7.9%

0.44%

58%

15%

18%

7.9%

0.67%

62%

13%

16%

6.9%

38 Gt 1.3%

40 Gt

59%

16%

18%

7.4%

0.81%

49 Gt

65%

11%

16%

6.2%

2.0%

2005

Gas

CO2 Fossil Fuel and 

Industrial Processes

CO2 FOLU

CH4

N2O

F-Gases

GHG Emissions [GtCO2eq/yr]

0

10

20

30

40

50

1970 1975 1980 1985 1990 1995 2000 2005 2010

+2.2%/yr

2000 – 2010

+1.3%/yr

1970 – 2000

2010

Total Annual Anthropogenic GHG Emissions by Groups of Gases 1970 – 2010

About half of cumulative anthropogenic CO2 emissions between 1750 and 2010 have occurred in the last 40 

years (high confi dence). In 1970, cumulative CO2 emissions from fossil fuel combustion, cement production and fl aring 

since 1750 were 420 ± 35 GtCO2; in 2010, that cumulative total had tripled to 1300 ± 110 GtCO2 (Figure SPM.2). Cumulative CO2 emissions from Forestry and Other Land Use (FOLU)9

 since 1750 increased from 490 ± 180 GtCO2 in 1970 to 

680 ± 300 GtCO2 in 2010. [5.2]

9

 Forestry and Other Land Use (FOLU)—also referred to as LULUCF (Land Use, Land-Use Change, and Forestry)—is the subset of Agriculture, 

Forestry and Other Land Use (AFOLU) emissions and removals of GHGs related to direct human-induced land use, land-use change and forestry 

activities excluding agricultural emissions and removals (see WGIII AR5 Glossary).
8

SPM

Summary for Policymakers

Annual anthropogenic GHG emissions have increased by 10 GtCO2eq between 2000 and 2010, with this 

increase directly coming from energy supply (47 %), industry (30 %), transport (11 %) and buildings (3 %) 

sectors (medium confi dence). Accounting for indirect emissions raises the contributions of the buildings and 

industry sectors (high confi dence). Since 2000, GHG emissions have been growing in all sectors, except AFOLU. Of the 

49 (±4.5) GtCO2eq emissions in 2010, 35 % (17 GtCO2eq) of GHG emissions were released in the energy supply sector, 

24 % (12 GtCO2eq, net emissions) in AFOLU, 21 % (10 GtCO2eq) in industry, 14 % (7.0 GtCO2eq) in transport and 6.4 % 

(3.2 GtCO2eq) in buildings. When emissions from electricity and heat production are attributed to the sectors that use 

the fi nal energy (i. e. indirect emissions), the shares of the industry and buildings sectors in global GHG emissions are 

increased to 31 % and 19 %7

, respectively (Figure SPM.2). [7.3, 8.2, 9.2, 10.3, 11.2]

Globally, economic and population growth continue to be the most important drivers of increases in CO2

emissions from fossil fuel combustion. The contribution of population growth between 2000 and 2010 

remained roughly identical to the previous three decades, while the contribution of economic growth has 

risen sharply (high confi dence). Between 2000 and 2010, both drivers outpaced emission reductions from improvements in energy intensity (Figure SPM.3). Increased use of coal relative to other energy sources has reversed the longstanding trend of gradual decarbonization of the world’s energy supply. [1.3, 5.3, 7.2, 14.3, TS.2.2]

Figure SPM.2 | Total anthropogenic GHG emissions (GtCO2eq / yr) by economic sectors. Inner circle shows direct GHG emission shares (in % of total 

anthropogenic GHG emissions) of fi ve economic sectors in 2010. Pull-out shows how indirect CO2 emission shares (in % of total anthropogenic GHG 

emissions) from electricity and heat production are attributed to sectors of fi nal energy use. ‘Other Energy’ refers to all GHG emission sources in the 

energy sector as defi ned in Annex II other than electricity and heat production [A.II.9.1]. The emissions data from Agriculture, Forestry and Other Land 

Use (AFOLU) includes land-based CO2 emissions from forest fi res, peat fi res and peat decay that approximate to net CO2 fl ux from the Forestry and 

Other Land Use (FOLU) sub-sector as described in Chapter 11 of this report. Emissions are converted into CO2-equivalents based on GWP1006 from the 

IPCC Second Assessment Report. Sector defi nitions are provided in Annex II.9. [Figure 1.3a, Figure TS.3 a / b]

Greenhouse Gas Emissions by Economic Sectors

Indirect CO2 Direct Emissions Emissions

Buildings

6.4%

Transport

14%

Industry 

21%

Other 

Energy 

9.6%

Electricity 

and Heat Production

25%

49 Gt CO2eq

(2010)

AFOLU

24%

Buildings

12%

Transport

0.3%

Industry 

11%

Energy

1.4%

AFOLU

0.87%
9

S

Summary for Policymakers

Figure SPM.3 | Decomposition of the decadal change in total global CO2 emissions from fossil fuel combustion by four driving factors: population, 

income (GDP) per capita, energy intensity of GDP and carbon intensity of energy. The bar segments show the changes associated with each factor alone, 

holding the respective other factors constant. Total decadal changes are indicated by a triangle. Changes are measured in gigatonnes (Gt) of CO2 emissions per decade; income is converted into common units using purchasing power parities. [Figure 1.7] 

Without additional efforts to reduce GHG emissions beyond those in place today, emissions growth is expected 

to persist driven by growth in global population and economic activities. Baseline scenarios, those without 

additional mitigation, result in global mean surface temperature increases in 2100 from 3.7 °C to 4.8 °C compared to pre-industrial levels10 (median values; the range is 2.5 °C to 7.8 °C when including climate uncertainty, 

see Table SPM.1)11 (high confi dence). The emission scenarios collected for this assessment represent full radiative forcing 

including GHGs, tropospheric ozone, aerosols and albedo change. Baseline scenarios (scenarios without explicit additional 

efforts to constrain emissions) exceed 450 parts per million (ppm) CO2eq by 2030 and reach CO2eq concentration levels 

between 750 and more than 1300 ppm CO2eq by 2100. This is similar to the range in atmospheric concentration levels 

between the RCP 6.0 and RCP 8.5 pathways in 2100.12 For comparison, the CO2eq concentration in 2011 is estimated to be 

430 ppm (uncertainty range 340 – 520 ppm)13. [6.3, Box TS.6; WGI Figure SPM.5, WGI 8.5, WGI 12.3]

10 Based on the longest global surface temperature dataset available, the observed change between the average of the period 1850 – 1900 and of 

the AR5 reference period (1986 – 2005) is 0.61 °C (5 – 95 % confi dence interval: 0.55 – 0.67 °C) [WGI SPM.E], which is used here as an approximation of the change in global mean surface temperature since pre-industrial times, referred to as the period before 1750. 11 The climate uncertainty refl ects the 5th to 95th percentile of climate model calculations described in Table SPM.1.

12 For the purpose of this assessment, roughly 300 baseline scenarios and 900 mitigation scenarios were collected through an open call from 

integrated modelling teams around the world. These scenarios are complementary to the Representative Concentration Pathways (RCPs, see 

WGIII AR5 Glossary). The RCPs are identifi ed by their approximate total radiative forcing in year 2100 relative to 1750: 2.6 Watts per square meter 

(W m−2) for RCP2.6, 4.5 W m− 2 for RCP4.5, 6.0 W m− 2 for RCP6.0, and 8.5 W m− 2 for RCP8.5. The scenarios collected for this assessment span a 

slightly broader range of concentrations in the year 2100 than the four RCPs. 13 This is based on the assessment of total anthropogenic radiative forcing for 2011 relative to 1750 in WGI, i. e. 2.3 W m− 2, uncertainty range 1.1 to 

3.3 W m− 2. [WGI Figure SPM.5, WGI 8.5, WGI 12.3]

1971 – 1980 1981 – 1990 1991 – 2000 2001 – 2010

-6

-4

-2

0

2

4

6

8

10

]

2

12

Population

6.8

2.5 2.9

4.0

Decomposition of the Change in Total Global CO2 Emissions from 

Fossil Fuel Combustion
10

SPM

Summary for Policymakers

Mitigation pathways and measures in the context 

of sustainable development

Long-term mitigation pathways

There are multiple scenarios with a range of technological and behavioral options, with different characteristics and implications for sustainable development, that are consistent with different levels of mitigation. 

For this assessment, about 900 mitigation scenarios have been collected in a database based on published integrated 

models.14 This range spans atmospheric concentration levels in 2100 from 430 ppm CO2eq to above 720 ppm CO2eq, which 

is comparable to the 2100 forcing levels between RCP 2.6 and RCP 6.0. Scenarios outside this range were also assessed 

including some scenarios with concentrations in 2100 below 430 ppm CO2eq (for a discussion of these scenarios see 

below). The mitigation scenarios involve a wide range of technological, socioeconomic, and institutional trajectories, but 

uncertainties and model limitations exist and developments outside this range are possible (Figure SPM.4, top panel). 

[6.1, 6.2, 6.3, TS.3.1, Box TS.6]

Mitigation scenarios in which it is likely that the temperature change caused by anthropogenic GHG emissions can be kept to less than 2°C relative to pre-industrial levels are characterized by atmospheric concentrations in 2100 of about 450ppm CO2eq (high confidence). Mitigation scenarios reaching concentration levels 

of about 500 ppm CO2eq by 2100 are more likely than not to limit temperature change to less than 2 °C relative to 

pre-industrial levels, unless they temporarily ‘overshoot’ concentration levels of roughly 530 ppm CO2eq before 2100, in 

which case they are about as likely as not to achieve that goal.15 Scenarios that reach 530 to 650 ppm CO2eq concentrations by 2100 are more unlikely than likely to keep temperature change below 2 °C relative to pre-industrial levels. 

Scenarios that exceed about 650 ppm CO2eq by 2100 are unlikely to limit temperature change to below 2 °C relative to 

pre-industrial levels. Mitigation scenarios in which temperature increase is more likely than not to be less than 1.5 °C 

relative to pre-industrial levels by 2100 are characterized by concentrations in 2100 of below 430 ppm CO2eq. Temperature peaks during the century and then declines in these scenarios. Probability statements regarding other levels of 

temperature change can be made with reference to Table SPM.1. [6.3, Box TS.6]

14 The long-term scenarios assessed in WGIII were generated primarily by large-scale, integrated models that project many key characteristics of 

mitigation pathways to mid-century and beyond. These models link many important human systems (e.g., energy, agriculture and land use, 

economy) with physical processes associated with climate change (e.g., the carbon cycle). The models approximate cost-effective solutions that 

minimize the aggregate economic costs of achieving mitigation outcomes, unless they are specifically constrained to behave otherwise. They are 

simplified, stylized representations of highly-complex, real-world processes, and the scenarios they produce are based on uncertain projections 

about key events and drivers over often century-long timescales. Simplifications and differences in assumptions are the reason why output 

generated from different models, or versions of the same model, can differ, and projections from all models can differ considerably from the 

reality that unfolds. [Box TS.7, 6.2] 15 Mitigation scenarios, including those reaching 2100 concentrations as high as or higher than 550 ppm CO2eq, can temporarily ‘overshoot’ 

atmospheric CO2eq concentration levels before descending to lower levels later. Such concentration overshoot involves less mitigation in the near 

term with more rapid and deeper emissions reductions in the long run. Overshoot increases the probability of exceeding any given temperature 

goal. [6.3, Table SPM.1]

SPM.4

SPM.4.1
11

S

Summary for Policymakers

Figure SPM.4 | Pathways of global GHG emissions (GtCO2eq / yr) in baseline and mitigation scenarios for different long-term concentration levels (upper panel) and associated 

upscaling requirements of low-carbon energy (% of primary energy) for 2030, 2050 and 2100 compared to 2010 levels in mitigation scenarios (lower panel). The lower panel 

excludes scenarios with limited technology availability and exogenous carbon price trajectories. For defi nitions of CO2-equivalent emissions and CO2-equivalent concentrations see 

the WGIII AR5 Glossary. [Figure 6.7, Figure 7.16] 

2000 2020 2040 2060 2080 2100 2100

-20 

0 

20 

40 

60 

80 

100 

120 

140 

Baseline

RCP8.5 

RCP6.0 

RCP4.5 

RCP2.6 

Associated Upscaling of Low-Carbon Energy Supply

0

20

40

60

80

100

2030 2050 2100 2030 2050 2100 2030 2050 2100 2030 2050 2100

Low-Carbon Energy Share of Primary Energy [%] Annual GHG Emissions [GtCO2eq/yr]

> 1000

720 – 1000

580 – 720

530 – 580

480 – 530

430 – 480

Full AR5 Database Range

ppm CO2

eq

ppm CO2

eq

ppm CO2

eq

ppm CO2

eq

ppm CO2

eq

ppm CO2

eq

GHG Emission Pathways 2000 – 2100: All AR5 Scenarios

90th percentile

Median

10th percentile

580 – 720

530 – 580

480 – 530

430 – 480

ppm CO2

eq

ppm CO2

eq

ppm CO2

eq

ppm CO2

eq

Min 

75%

Max 

Median

25%

+190%

+185%

+275%

+310%

+105%

+135%

+135%

+145%

2010
12

SPM

Summary for Policymakers

Table SPM.1| Key characteristics of the scenarios collected and assessed for WGIII AR5. For all parameters, the 10th to 90th percentile of the scenarios is shown.1, 2 [Table 6.3] 

CO2eq 

Concentrations 

in 2100 (CO2eq) 

Category label 

(concentration 

range)9

Subcategories

Relative 

position of 

the RCPs5

Cumulative CO2 

emissions3

 (GtCO2)

Change in CO2eq emissions 

compared to 2010 in (%)4 Temperature change (relative to 1850–1900)5, 6

2011–2050 2011–2100 2050 2100

2100 

Temperature 

change (°C)7

Likelihood of staying below temperature 

level over the 21st century8

1.5°C 2.0°C 3.0°C 4.0°C

< 430 Only a limited number of individual model studies have explored levels below 430 ppm CO2eq

450 

(430–480) Total range1, 10 RCP2.6 550–1300 630–1180 −72 to −41 −118 to −78 1.5–1.7 

(1.0–2.8)

More unlikely 

than likely

Likely Likely

Likely

500 

(480–530)

No overshoot of 

530 ppm CO2eq 860–1180 960–1430 −57 to −42 −107 to −73 1.7–1.9 

(1.2–2.9)

Unlikely

More likely 

than not

Overshoot of 

530 ppm CO2eq 1130–1530 990–1550 −55 to −25 −114 to −90 1.8–2.0 

(1.2–3.3)

About as 

likely as not

550 

(530–580)

No overshoot of 

580 ppm CO2eq 1070–1460 1240–2240 −47 to −19 −81 to −59 2.0–2.2 

(1.4–3.6) More unlikely 

than likely Overshoot of 12

580 ppm CO2eq 1420–1750 1170–2100 −16 to 7 −183 to −86 2.1–2.3 (1.4–3.6)

(580–650) Total range

RCP4.5

1260–1640 1870–2440 −38 to 24 −134 to −50 2.3–2.6 

(1.5–4.2)

(650–720) Total range 1310–1750 2570–3340 −11 to 17 −54 to −21 2.6–2.9 

(1.8–4.5) Unlikely

More likely 

than not

(720–1000) Total range RCP6.0 1570–1940 3620–4990 18 to 54 −7 to 72 3.1–3.7 

(2.1–5.8) Unlikely11 More unlikely 

than likely

>1000 Total range RCP8.5 1840–2310 5350–7010 52 to 95 74 to 178 4.1–4.8 

(2.8–7.8) Unlikely26 Unlikely More unlikely 

than likely

1 The ‘total range’ for the 430–480 ppm CO2eq scenarios corresponds to the range of the 10–90th percentile of the subcategory of these scenarios shown in table 6.3. 2

 Baseline scenarios (see SPM.3) fall into the >1000 and 720–1000 ppm CO2eq categories. The latter category also includes mitigation scenarios. The baseline scenarios in the 

latter category reach a temperature change of 2.5–5.8 °C above preindustrial in 2100. Together with the baseline scenarios in the >1000 ppm CO2eq category, this leads to 

an overall 2100 temperature range of 2.5–7.8 °C (median: 3.7–4.8 °C) for baseline scenarios across both concentration categories. 3

 For comparison of the cumulative CO2 emissions estimates assessed here with those presented in WGI, an amount of 515 [445–585] GtC (1890 [1630–2150] GtCO2), was 

already emitted by 2011 since 1870 [Section WGI 12.5]. Note that cumulative emissions are presented here for different periods of time (2011–2050 and 2011–2100) while 

cumulative emissions in WGI are presented as total compatible emissions for the RCPs (2012–2100) or for total compatible emissions for remaining below a given temperature target with a given likelihood. [WGI Table SPM.3, WGI SPM.E.8] 4

 The global 2010 emissions are 31% above the 1990 emissions (consistent with the historic GHG emission estimates presented in this report). CO2eq emissions include the 

basket of Kyoto gases (CO2, CH4, N2O as well as F-gases). 5

 The assessment in WGIII involves a large number of scenarios published in the scientific literature and is thus not limited to the RCPs. To evaluate the GHG concentration and 

climate implications of these scenarios, the MAGICC model was used in a probabilistic mode (see Annex II). For a comparison between MAGICC model results and the outcomes of the models used in WGI, see Section WGI 12.4.1.2 and WGI 12.4.8 and 6.3.2.6. Reasons for differences with WGI SPM Table.2 include the difference in reference 

year (1986–2005 vs. 1850–1900 here), difference in reporting year (2081–2100 vs 2100 here), set-up of simulation (CMIP5 concentration driven versus MAGICC emissiondriven here), and the wider set of scenarios (RCPs versus the full set of scenarios in the WGIII AR5 scenario database here). 6

 Temperature change is reported for the year 2100, which is not directly comparable to the equilibrium warming reported in WGIII AR4 (Table 3.5, Chapter 3). For the 2100 

temperature estimates, the transient climate response (TCR) is the most relevant system property. The assumed 90th percentile uncertainty range of the TCR for MAGICC 

is 1.2–2.6 °C (median 1.8 °C). This compares to the 90th percentile range of TCR between 1.2–2.4 °C for CMIP5 (WGI 9.7) and an assessed likely range of 1–2.5 °C from 

multiple lines of evidence reported in the IPCC AR5 WGI report (Box 12.2 in chapter 12.5). 7

 Temperature change in 2100 is provided for a median estimate of the MAGICC calculations, which illustrates differences between the emissions pathways of the scenarios 

in each category. The range of temperature change in the parentheses includes in addition the carbon cycle and climate system uncertainties as represented by the MAGICC 

model (see 6.3.2.6 for further details). The temperature data compared to the 1850–1900 reference year was calculated by taking all projected warming relative to 

1986–2005, and adding 0.61 °C for 1986–2005 compared to 1850–1900, based on HadCRUT4 (see WGI Table SPM.2). 8

 The assessment in this table is based on the probabilities calculated for the full ensemble of scenarios in WGIII using MAGICC and the assessment in WGI of the uncertainty 

of the temperature projections not covered by climate models. The statements are therefore consistent with the statements in WGI, which are based on the CMIP5 runs of the 

RCPs and the assessed uncertainties. Hence, the likelihood statements reflect different lines of evidence from both WGs. This WGI method was also applied for scenarios with 

intermediate concentration levels where no CMIP5 runs are available. The likelihood statements are indicative only (6.3), and follow broadly the terms used by the WGI SPM 

for temperature projections: likely 66–100%, more likely than not >50–100%, about as likely as not 33–66%, and unlikely 0–33%. In addition the term more unlikely 

than likely 0–<50% is used. 9

 The CO2-equivalent concentration includes the forcing of all GHGs including halogenated gases and tropospheric ozone, aerosols and albedo change (calculated on the basis 

of the total forcing from a simple carbon cycle/climate model MAGICC). 10 The vast majority of scenarios in this category overshoot the category boundary of 480 ppm CO2eq concentrations. 11 For scenarios in this category no CMIP5 run (WGI Chapter 12, Table 12.3) as well as no MAGICC realization (6.3) stays below the respective temperature level. Still, an 

‘unlikely’ assignment is given to reflect uncertainties that might not be reflected by the current climate models. 12 Scenarios in the 580–650 ppm CO2eq category include both overshoot scenarios and scenarios that do not exceed the concentration level at the high end of the category 

(like RCP4.5). The latter type of scenarios, in general, have an assessed probability of more unlikely than likely to exceed the 2 °C temperature level, while the former are 

mostly assessed to have an unlikely probability of exceeding this level. 
13

S

Summary for Policymakers

Scenarios reaching atmospheric concentration levels of about 450ppm CO2eq by 2100 (consistent with a 

likely chance to keep temperature change below 2°C relative to pre-industrial levels) include substantial 

cuts in anthropogenic GHG emissions by mid-century through large-scale changes in energy systems and 

potentially land use (high confidence). Scenarios reaching these concentrations by 2100 are characterized by lower 

global GHG emissions in 2050 than in 2010, 40% to 70% lower globally16, and emissions levels near zero GtCO2eq or 

below in 2100. In scenarios reaching 500 ppm CO2eq by 2100, 2050 emissions levels are 25% to 55% lower than in 2010 

globally. In scenarios reaching 550 ppm CO2eq, emissions in 2050 are from 5% above 2010 levels to 45% below 2010 

levels globally (Table SPM.1). At the global level, scenarios reaching 450 ppm CO2eq are also characterized by more rapid 

improvements of energy efficiency, a tripling to nearly a quadrupling of the share of zero- and low-carbon energy supply 

from renewables, nuclear energy and fossil energy with carbon dioxide capture and storage (CCS), or bioenergy with CCS 

(BECCS) by the year 2050 (Figure SPM.4, lower panel). These scenarios describe a wide range of changes in land use, 

reflecting different assumptions about the scale of bioenergy production, afforestation, and reduced deforestation. All of 

these emissions, energy, and land-use changes vary across regions.17 Scenarios reaching higher concentrations include 

similar changes, but on a slower timescale. On the other hand, scenarios reaching lower concentrations require these 

changes on a faster timescale. [6.3, 7.11]

Mitigation scenarios reaching about 450ppm CO2eq in 2100 typically involve temporary overshoot of atmospheric concentrations, as do many scenarios reaching about 500ppm to 550ppm CO2eq in 2100. Depending 

on the level of the overshoot, overshoot scenarios typically rely on the availability and widespread deployment of BECCS and afforestation in the second half of the century. The availability and scale of these and 

other Carbon Dioxide Removal (CDR) technologies and methods are uncertain and CDR technologies and 

methods are, to varying degrees, associated with challenges and risks (high confidence) (see Section SPM.4.2).18

CDR is also prevalent in many scenarios without overshoot to compensate for residual emissions from sectors where mitigation is more expensive. There is only limited evidence on the potential for large-scale deployment of BECCS, large-scale 

afforestation, and other CDR technologies and methods. [2.6, 6.3, 6.9.1, Figure 6.7, 7.11, 11.13]

Estimated global GHG emissions levels in 2020 based on the Cancún Pledges are not consistent with costeffective long-term mitigation trajectories that are at least as likely as not to limit temperature change to 

2°C relative to pre-industrial levels (2100 concentrations of about 450 and about 500ppm CO2eq), but they 

do not preclude the option to meet that goal (high confidence). Meeting this goal would require further substantial 

reductions beyond 2020. The Cancún Pledges are broadly consistent with cost-effective scenarios that are likely to keep 

temperature change below 3 °C relative to preindustrial levels. [6.4, 13.13, Figure TS.11]

Delaying mitigation efforts beyond those in place today through 2030 is estimated to substantially increase 

the difficulty of the transition to low longer-term emissions levels and narrow the range of options consistent with maintaining temperature change below 2°C relative to pre-industrial levels (high confidence). 

Cost-effective mitigation scenarios that make it at least as likely as not that temperature change will remain below 2 °C 

relative to pre-industrial levels (2100 concentrations between about 450 and 500 ppm CO2eq) are typically characterized 

by annual GHG emissions in 2030 of roughly between 30 GtCO2eq and 50 GtCO2eq (Figure SPM.5, left panel). Scenarios 

with annual GHG emissions above 55 GtCO2eq in 2030 are characterized by substantially higher rates of emissions reductions from 2030 to 2050 (Figure SPM.5, middle panel); much more rapid scale-up of low-carbon energy over this period 

16 This range differs from the range provided for a similar concentration category in AR4 (50%–85% lower than 2000 for CO2 only). Reasons for 

this difference include that this report has assessed a substantially larger number of scenarios than in AR4 and looks at all GHGs. In addition, a 

large proportion of the new scenarios include net negative emissions technologies (see below). Other factors include the use of 2100 concentration levels instead of stabilization levels and the shift in reference year from 2000 to 2010. Scenarios with higher emissions in 2050 are characterized by a greater reliance on Carbon Dioxide Removal (CDR) technologies beyond mid-century. 17 At the national level, change is considered most effective when it reflects country and local visions and approaches to achieving sustainable 

development according to national circumstances and priorities [6.4, 11.8.4, WGII SPM]. 18 According to WGI, CDR methods have biogeochemical and technological limitations to their potential on the global scale. There is insufficient 

knowledge to quantify how much CO2 emissions could be partially offset by CDR on a century timescale. CDR methods carry side-effects and longterm consequences on a global scale. [WGI SPM.E.8]
14

SPM

Summary for Policymakers

(Figure SPM.5, right panel); a larger reliance on CDR technologies in the long-term (Figure SPM.4, top panel); and higher 

transitional and long-term economic impacts (Table SPM.2). Due to these increased mitigation challenges, many models 

with annual 2030 GHG emissions higher than 55 GtCO2eq could not produce scenarios reaching atmospheric concentration levels that make it as likely as not that temperature change will remain below 2 °C relative to pre-industrial levels. 

[6.4, 7.11, Figures TS.11, TS.13]

Figure SPM.5 | The implications of different 2030 GHG emissions levels (left panel) for the rate of CO2 emissions reductions (middle panel) and low-carbon energy upscaling 

from 2030 to 2050 (right panel) in mitigation scenarios reaching about 450 to 500 (430 – 530) ppm CO2eq concentrations by 2100. The scenarios are grouped according to different emissions levels by 2030 (coloured in different shades of green). The left panel shows the pathways of GHG emissions (GtCO2eq / yr) leading to these 2030 levels. The black 

bar shows the estimated uncertainty range of GHG emissions implied by the Cancún Pledges. The middle panel denotes the average annual CO2 emissions reduction rates for the 

period 2030 – 2050. It compares the median and interquartile range across scenarios from recent intermodel comparisons with explicit 2030 interim goals to the range of scenarios 

in the Scenario Database for WGIII AR5. Annual rates of historical emissions change (sustained over a period of 20 years) are shown in grey. The arrows in the right panel show 

the magnitude of zero and low-carbon energy supply up-scaling from 2030 to 2050 subject to different 2030 GHG emissions levels. Zero- and low-carbon energy supply includes 

renewables, nuclear energy, fossil energy with carbon dioxide capture and storage (CCS), and bioenergy with CCS (BECCS). Note: Only scenarios that apply the full, unconstrained 

mitigation technology portfolio of the underlying models (default technology assumption) are shown. Scenarios with large net negative global emissions (> 20 GtCO2 / yr), scenarios 

with exogenous carbon price assumptions, and scenarios with 2010 emissions signifi cantly outside the historical range are excluded. The right-hand panel includes only 68 scenarios, because three of the 71 scenarios shown in the fi gure do not report some subcategories for primary energy that are required to calculate the share of zero- and low-carbon 

energy. [Figure 6.32, 7.16, 13.13.1.3] 

+90%

+160%

+240%

2010

0

20

40

60

80

100

2030 2050 2100 2030 2050 2100 2030 2050 2100

Implications of Different 2030 GHG 

Emissions Levels for Low-Carbon Energy 

Upscaling

Zero- and Lo

w-Carbon Energy Share of Primary Energy [

%]

GHG Emissions Pathways to 2030 Implications of Different 2030 GHG Emissions

Levels for the Rate of Annual Average CO2

Emissions Reductions from 2030 to 2050

Annual Rate of Change in CO2 Emissions (2030 – 2050) [%/yr] -12

-9

-6

-3

0

3

6

History

1900 – 2010

2000 – 2010

AR5 Scenario Range

Interquartile Range 

and Median of Model 

Comparisons with 

2030 Targets

Annual GHG Emissions [GtCO2eq/yr]

<50 GtCO2eq

Annual GHG Emissions in 2030

50 – 55GtCO2eq >55 GtCO2

eq

n=71 n=68

Cancún

Pledges

<50 GtCO2eq

Annual 

GHG Emissions 

in 2030

50 – 55 GtCO2eq

>55 GtCO2

eq

2005 2010 2015 2020 2025 2030 

20

25

30

35

40

45

50

55

70

75

60

65

n=71 
15

S

Summary for Policymakers

Estimates of the aggregate economic costs of mitigation vary widely and are highly sensitive to model design 

and assumptions as well as the specification of scenarios, including the characterization of technologies and 

the timing of mitigation (high confidence). Scenarios in which all countries of the world begin mitigation immediately, 

there is a single global carbon price, and all key technologies are available, have been used as a cost-effective benchmark 

for estimating macroeconomic mitigation costs (Table SPM.2, grey segments). Under these assumptions, mitigation scenarios that reach atmospheric concentrations of about 450 ppm CO2eq by 2100 entail losses in global consumption—not 

including benefits of reduced climate change as well as co-benefits and adverse side-effects of mitigation19—of 1% to 

4% (median: 1.7%) in 2030, 2% to 6% (median: 3.4%) in 2050, and 3% to 11% (median: 4.8%) in 2100 relative to 

consumption in baseline scenarios that grows anywhere from 300% to more than 900% over the century. These numbers 

correspond to an annualized reduction of consumption growth by 0.04 to 0.14 (median: 0.06) percentage points over the 

century relative to annualized consumption growth in the baseline that is between 1.6% and 3% per year. Estimates at 

the high end of these cost ranges are from models that are relatively inflexible to achieve the deep emissions reductions 

required in the long run to meet these goals and/or include assumptions about market imperfections that would raise 

costs. Under the absence or limited availability of technologies, mitigation costs can increase substantially depending on 

the technology considered (Table SPM.2, orange segment). Delaying additional mitigation further increases mitigation 

costs in the medium- to long-term (Table SPM.2, blue segment). Many models could not achieve atmospheric concentration levels of about 450 ppm CO2eq by 2100 if additional mitigation is considerably delayed or under limited availability of 

key technologies, such as bioenergy, CCS, and their combination (BECCS). [6.3]

19 The total economic effects at different temperature levels would include mitigation costs, co-benefits of mitigation, adverse side-effects of mitigation, adaptation costs and climate damages. Mitigation cost and climate damage estimates at any given temperature level cannot be compared to 

evaluate the costs and benefits of mitigation. Rather, the consideration of economic costs and benefits of mitigation should include the reduction 

of climate damages relative to the case of unabated climate change.
16

SPM

Summary for Policymakers

Table SPM.2| Global mitigation costs in cost-effective scenarios1 and estimated cost increases due to assumed limited availability of specific technologies and delayed additional 

mitigation. Cost estimates shown in this table do not consider the benefits of reduced climate change as well as co-benefits and adverse side-effects of mitigation. The grey columns 

show consumption losses in the years 2030, 2050, and 2100 (light grey) and annualized consumption growth reductions (grey) over the century in cost-effective scenarios relative 

to a baseline development without climate policy. The orange columns show the percentage increase in discounted costs2 over the century, relative to cost-effective scenarios, in 

scenarios in which technology is constrained relative to default technology assumptions.3 The blue columns show the increase in mitigation costs over the periods 2030–2050 and 

2050–2100, relative to scenarios with immediate mitigation, due to delayed additional mitigation through 2030.4 These scenarios with delayed additional mitigation are grouped 

by emission levels of less or more than 55 GtCO2eq in 2030, and two concentration ranges in 2100 (430–530 ppm CO2eq and 530–650 CO2eq). In all figures, the median of the 

scenario set is shown without parentheses, the range between the 16th and 84th percentile of the scenario set is shown in the parentheses, and the number of scenarios in the set 

is shown in square brackets.5 [Figures TS.12, TS.13, 6.21, 6.24, 6.25, Annex II.10] 

Consumption losses in cost-effective scenarios1 Increase in total discounted mitigation costs in 

scenarios with limited availability of technologies

Increase in medium- and long-term mitigation costs 

due to delayed additional mitigation until 2030 

[% reduction in consumption 

relative to baseline]

[percentage 

point 

reduction in 

annualized 

consumption 

growth rate]

[% increase in total discounted mitigation costs 

(2015–2100) relative to default technology assumptions]

[% increase in mitigation costs relative 

to immediate mitigation]

2100 

Concentration 

(ppm CO2eq)

2030 2050 2100 2010–2100 No CCS Nuclear 

phase out

Limited 

Solar /Wind

Limited 

Bioenergy

≤55 GtCO2eq >55 GtCO2eq

2030–2050 2050–2100 2030–2050 2050–2100

450 (430–480) 1.7 (1.0–3.7)

[N: 14] 3.4 (2.1–6.2) 4.8 (2.9–11.4)

0.06 

(0.04–0.14)

138 (29–297)

[N: 4]

7 (4–18)

[N: 8]

6 (2–29)

[N: 8]

64 (44–78)

[N: 8] 28 (14–50)

[N: 34]

15 (5–59) 44 (2–78)

[N: 29]

37 (16–82)

500 (480–530) 1.7 (0.6–2.1)

[N: 32] 2.7 (1.5–4.2) 4.7 (2.4–10.6)

0.06 

(0.03–0.13)

550 (530–580) 0.6 (0.2–1.3)

[N: 46] 1.7 (1.2–3.3) 3.8 (1.2–7.3) 0.04 (0.01–0.09)

39 (18–78)

[N: 11]

13 (2–23)

[N: 10]

8 (5–15)

[N: 10]

18 (4–66)

[N: 12] 3 (−5–16)

[N: 14]

4 (−4–11) 15 (3–32)

[N: 10]

16 (5–24)

580–650 0.3 (0–0.9)

[N: 16] 1.3 (0.5–2.0) 2.3 (1.2–4.4) 0.03 (0.01–0.05)

1 Cost-effective scenarios assume immediate mitigation in all countries and a single global carbon price, and impose no additional limitations on technology relative to the 

models’ default technology assumptions. 2 Percentage increase of net present value of consumption losses in percent of baseline consumption (for scenarios from general equilibrium 

models) and abatement costs in percent of baseline GDP (for scenarios from partial equilibrium models) for the period 2015–2100, discounted at 5% per year. 3 No CCS: CCS is not included in these scenarios. Nuclear phase out: No addition of nuclear power plants beyond those under construction, and operation of existing plants 

until the end of their lifetime. Limited Solar/Wind: a maximum of 20% global electricity generation from solar and wind power in any year of these scenarios. Limited Bioenergy: a maximum of 100 EJ/yr modern bioenergy supply globally (modern bioenergy used for heat, power, combinations, and industry was around 18 EJ/yr in 2008 [11.13.5]). 4 Percentage increase of total undiscounted mitigation costs for the periods 2030–2050 and 2050–2100. 5 The range is determined by the central scenarios encompassing the 16th and 84th percentile of the scenario set. Only scenarios with a time 

horizon until 2100 are included. Some models that are included in the cost ranges for concentration levels above 530 ppm CO2eq in 2100 could not produce associated 

scenarios for concentration levels below 530 ppm CO2eq in 2100 with assumptions about limited availability of technologies and/or delayed additional mitigation. 
17

S

Summary for Policymakers

Only a limited number of studies have explored scenarios that are more likely than not to bring temperature 

change back to below 1.5 °C by 2100 relative to pre-industrial levels; these scenarios bring atmospheric 

concentrations to below 430 ppm CO2eq by 2100 (high confi dence). Assessing this goal is currently diffi cult because 

no multi-model studies have explored these scenarios. The limited number of published studies consistent with this goal 

produces scenarios that are characterized by (1) immediate mitigation action; (2) the rapid upscaling of the full portfolio 

of mitigation technologies; and (3) development along a low-energy demand trajectory.20 [6.3, 7.11] 

Mitigation scenarios reaching about 450 or 500 ppm CO2eq by 2100 show reduced costs for achieving air 

quality and energy security objectives, with signifi cant co-benefi ts for human health, ecosystem impacts, 

and suffi ciency of resources and resilience of the energy system; these scenarios did not quantify other cobenefi ts or adverse side-effects (medium confi dence). These mitigation scenarios show improvements in terms of the 

suffi ciency of resources to meet national energy demand as well as the resilience of energy supply, resulting in energy 

systems that are less vulnerable to price volatility and supply disruptions. The benefi ts from reduced impacts to health 

and ecosystems associated with major cuts in air pollutant emissions (Figure SPM.6) are particularly high where currently 

legislated and planned air pollution controls are weak. There is a wide range of co-benefi ts and adverse side-effects for 

additional objectives other than air quality and energy security. Overall, the potential for co-benefi ts for energy end-use 

measures outweigh the potential for adverse side-effects, whereas the evidence suggests this may not be the case for all 

energy supply and AFOLU measures. [WGIII 4.8, 5.7, 6.3.6, 6.6, 7.9, 8.7, 9.7, 10.8, 11.7, 11.13.6, 12.8, Figure TS.14, 

Table 6.7, Tables TS.3–TS.7; WGII 11.9]

Figure SPM.6 | Air pollutant emission levels for black carbon (BC) and sulfur dioxide (SO2) in 2050 relative to 2005 (0=2005 levels). Baseline scenarios 

without additional efforts to reduce GHG emissions beyond those in place today are compared to scenarios with stringent mitigation policies, which are 

consistent with reaching about 450 to 500 (430– 530) ppm CO2eq concentrations by 2100. [Figure 6.33]

20 In these scenarios, the cumulative CO2 emissions range between 655 and 815 GtCO2 for the period 2011 – 2050 and between 90 and 350 GtCO2

for the period 2011 – 2100. Global CO2eq emissions in 2050 are between 70 and 95 % below 2010 emissions, and they are between 110 and 

120 % below 2010 emissions in 2100.

Individual 

Scenarios

Min 

75%

Max 

Median

25%

Stringent

Climate Policy

Stringent

Climate Policy

Baseline Baseline

] %[ 5002 morf egnahC

Co-Benefits of Climate Change Mitigation for Air Quality

Impact of Stringent Climate Policy on Air Pollutant Emissions

(Global, 2005 – 2050)

Increased 

Pollution

Decreased

Pollution

-100

-50

0

50

Black Carbon Sulfur Dioxide
18

SPM

Summary for Policymakers

There is a wide range of possible adverse side-effects as well as co-benefits and spillovers from climate 

policy that have not been well-quantified (high confidence). Whether or not side-effects materialize, and to what 

extent side-effects materialize, will be case- and site-specific, as they will depend on local circumstances and the scale, 

scope, and pace of implementation. Important examples include biodiversity conservation, water availability, food security, income distribution, efficiency of the taxation system, labour supply and employment, urban sprawl, and the sustainability of the growth of developing countries. [Box TS.11]

Mitigation efforts and associated costs vary between countries in mitigation scenarios. The distribution of 

costs across countries can differ from the distribution of the actions themselves (high confidence). In globally 

cost-effective scenarios, the majority of mitigation efforts takes place in countries with the highest future emissions in 

baseline scenarios. Some studies exploring particular effort-sharing frameworks, under the assumption of a global carbon market, have estimated substantial global financial flows associated with mitigation for scenarios leading to 2100 

atmospheric concentrations of about 450 to 550 ppm CO2eq. [Box 3.5, 4.6, 6.3.6, Table 6.4, Figure 6.9, Figure 6.27, Figure 

6.28, Figure 6.29, 13.4.2.4]

Mitigation policy could devalue fossil fuel assets and reduce revenues for fossil fuel exporters, but differences between regions and fuels exist (high confidence). Most mitigation scenarios are associated with reduced 

revenues from coal and oil trade for major exporters (high confidence). The effect of mitigation on natural gas export 

revenues is more uncertain, with some studies showing possible benefits for export revenues in the medium term until 

about 2050 (medium confidence). The availability of CCS would reduce the adverse effect of mitigation on the value of 

fossil fuel assets (medium confidence). [6.3.6, 6.6, 14.4.2]

Sectoral and cross-sectoral mitigation pathways and measures 

Cross-sectoral mitigation pathways and measures

In baseline scenarios, GHG emissions are projected to grow in all sectors, except for net CO2 emissions in 

the AFOLU sector21 (robust evidence, medium agreement). Energy supply sector emissions are expected to continue 

to be the major source of GHG emissions, ultimately accounting for the significant increases in indirect emissions from 

electricity use in the buildings and industry sectors. In baseline scenarios, while non-CO2 GHG agricultural emissions are 

projected to increase, net CO2 emissions from the AFOLU sector decline over time, with some models projecting a net 

sink towards the end of the century (Figure SPM.7).22 [6.3.1.4, 6.8, Figure TS.15]

Infrastructure developments and long-lived products that lock societies into GHG-intensive emissions 

pathways may be difficult or very costly to change, reinforcing the importance of early action for ambitious 

mitigation (robust evidence, high agreement). This lock-in risk is compounded by the lifetime of the infrastructure, by 

the difference in emissions associated with alternatives, and the magnitude of the investment cost. As a result, lock-in 

related to infrastructure and spatial planning is the most difficult to reduce. However, materials, products and infrastructure with long lifetimes and low lifecycle emissions can facilitate a transition to low-emission pathways while also 

reducing emissions through lower levels of material use. [5.6.3, 6.3.6.4, 9.4, 10.4, 12.3, 12.4]

21 Net AFOLU CO2 emissions include emissions and removals of CO2 from the AFOLU sector, including land under forestry and, in some assessments, CO2 sinks in agricultural soils. 22 A majority of the Earth System Models assessed in WGI project a continued land carbon uptake under all RCPs through to 2100, but some 

models simulate a land carbon loss due to the combined effect of climate change and land-use change. [WGI SPM.E.7, WGI 6.4]

SPM.4.2

SPM.4.2.1
19

S

Summary for Policymakers

Figure SPM.7 | Direct emissions of CO2 by sector and total non-CO2 GHGs (Kyoto gases) across sectors in baseline (left panel) and mitigation scenarios that reach around 450 

(430 – 480) ppm CO2eq with CCS (middle panel) and without CCS (right panel). The numbers at the bottom of the graphs refer to the number of scenarios included in the range 

which differs across sectors and time due to different sectoral resolution and time horizon of models. Note that many models cannot reach 450 ppm CO2eq concentration by 2100 

in the absence of CCS, resulting in a low number of scenarios for the right panel [Figures 6.34 and 6.35]. 

CO2 Transport 

CO2

 Buildings

CO2

 Industry 

CO2

 Electricity

CO2

 Net AFOLU

Non−CO2

 (All Sectors)

Actual 2010 Level Individual 

Scenarios

Min 

75%

Max 

Median

25%

Direct Sectoral CO2 and Non-CO2 GHG Emissions in Baseline and Mitigation Scenarios with and without CCS

939378808065808065

147147127

131131

118

121121

107

2030

2050

2100

292929222222222222363636323232363636

2030

2050

2100

Transport Buildings Industry Electricity Net

AFOLU

Non−CO2 Transport Buildings Industry Electricity Net

AFOLU

Non−CO2 Transport Buildings Industry Electricity Net

AFOLU

Non−CO2

555333333555666666

2030

2050

2100

30

20

-20

10

-10

0

40

50

30

20

-20

10

-10

0

40

50

30

20

-20

10

-10

0

40

50

Direct Emissions [GtCO2eq/yr] n=

80 GtCO2

/yr

450 ppm CO2 Baselines eq with CCS 450 ppm CO2

eq without CCS

There are strong interdependencies in mitigation scenarios between the pace of introducing mitigation 

measures in energy supply and energy end-use and developments in the AFOLU sector (high confi dence). The 

distribution of the mitigation effort across sectors is strongly infl uenced by the availability and performance of BECCS and 

large scale afforestation (Figure SPM.7). This is particularly the case in scenarios reaching CO2eq concentrations of about 

450 ppm by 2100. Well-designed systemic and cross-sectoral mitigation strategies are more cost-effective in cutting emissions than a focus on individual technologies and sectors. At the energy system level these include reductions in the GHG 

emission intensity of the energy supply sector, a switch to low-carbon energy carriers (including low-carbon electricity) 

and reductions in energy demand in the end-use sectors without compromising development (Figure SPM.8). [6.3.5, 6.4, 

6.8, 7.11, Table TS.2]

Mitigation scenarios reaching around 450 ppm CO2eq concentrations by 2100 show large-scale global changes 

in the energy supply sector (robust evidence, high agreement). In these selected scenarios, global CO2 emissions from 

the energy supply sector are projected to decline over the next decades and are characterized by reductions of 90 % or 

more below 2010 levels between 2040 and 2070. Emissions in many of these scenarios are projected to decline to below 

zero thereafter. [6.3.4, 6.8, 7.1, 7.11]
20

SPM

Summary for Policymakers

Figure SPM.8 | Final energy demand reduction relative to baseline (upper row) and low-carbon energy carrier shares in fi nal energy (lower row) in the transport, buildings, and 

industry sectors by 2030 and 2050 in scenarios from two different CO2eq concentration categories compared to sectoral studies assessed in Chapters 8 – 10. The demand reductions 

shown by these scenarios do not compromise development. Low-carbon energy carriers include electricity, hydrogen and liquid biofuels in transport, electricity in buildings and 

electricity, heat, hydrogen and bioenergy in industry. The numbers at the bottom of the graphs refer to the number of scenarios included in the ranges which differ across sectors 

and time due to different sectoral resolution and time horizon of models. [Figures 6.37 and 6.38] 

Min 

75%

Max 

Median

25%

Final Energy Demand Reduction and Low-Carbon Energy Carrier Shares in Energy End-Use Sectors

N= 161 225 161 225 126 189 126 189 126 189 126 189

2030 2050

Transport

Final Energy Demand Reduction Relative to Baseline [%]

2030 2050

Buildings

Final Energy Demand Reduction Relative to Baseline [%]

2030 2050

100

80

60

40

20

0

100

80

60

40

20

0

100

80

60

40

20

0

Industry

Final Energy Demand Reduction Relative to Baseline [%]

Sectoral Studies (Base)

Sectoral Studies (Policy)

Actual 2010 Level

Baselines

530 – 650 ppm CO2

eq

430 – 530 ppm CO2

eq

Sectoral Studies (Partial)

Sectoral Studies (Full)

N= 154 130 182 154 130 182 124 103 110 124 103 110 107 86 95 107 86 95

 2030 2050

0

20

40

60

100 100 100

80

Transport

Low-Carbon Energy Carrier Share in Final Energy [%]

 2030 2050

0

20

40

60

80

Buildings

Low-Carbon Energy Carrier Share in Final Energy [%]

 2030 2050

0

20

40

60

80

Industry

Low-Carbon Energy Carrier Share in Final Energy [%]
21

S

Summary for Policymakers

Efficiency enhancements and behavioural changes, in order to reduce energy demand compared to baseline 

scenarios without compromising development, are a key mitigation strategy in scenarios reaching atmospheric CO2eq concentrations of about 450 or 500ppm by 2100 (robust evidence, high agreement). Near-term 

reductions in energy demand are an important element of cost-effective mitigation strategies, provide more flexibility for 

reducing carbon intensity in the energy supply sector, hedge against related supply-side risks, avoid lock-in to carbonintensive infrastructures, and are associated with important co-benefits. Both integrated and sectoral studies provide 

similar estimates for energy demand reductions in the transport, buildings and industry sectors for 2030 and 2050 

(Figure SPM.8). [6.3.4, 6.6, 6.8, 7.11, 8.9, 9.8, 10.10]

Behaviour, lifestyle and culture have a considerable influence on energy use and associated emissions, with 

high mitigation potential in some sectors, in particular when complementing technological and structural 

change23 (medium evidence, medium agreement). Emissions can be substantially lowered through changes in consumption patterns (e.g., mobility demand and mode, energy use in households, choice of longer-lasting products) and dietary 

change and reduction in food wastes. A number of options including monetary and non-monetary incentives as well as 

information measures may facilitate behavioural changes. [6.8, 7.9, 8.3.5, 8.9, 9.2, 9.3, 9.10, Box 10.2, 10.4, 11.4, 12.4, 

12.6, 12.7, 15.3, 15.5, Table TS.2]

Energy supply

In the baseline scenarios assessed in AR5, direct CO2 emissions from the energy supply sector are projected 

to almost double or even triple by 2050 compared to the level of 14.4 GtCO2/year in 2010, unless energy 

intensity improvements can be significantly accelerated beyond the historical development (medium evidence, 

medium agreement). In the last decade, the main contributors to emission growth were a growing energy demand and 

an increase of the share of coal in the global fuel mix. The availability of fossil fuels alone will not be sufficient to limit 

CO2eq concentration to levels such as 450 ppm, 550 ppm, or 650 ppm. [6.3.4, 7.2, 7.3, Figures 6.15, TS.15, SPM.7]

Decarbonizing (i.e. reducing the carbon intensity of) electricity generation is a key component of costeffective mitigation strategies in achieving low-stabilization levels (430–530ppm CO2eq); in most integrated 

modelling scenarios, decarbonization happens more rapidly in electricity generation than in the industry, 

buildings, and transport sectors (medium evidence, high agreement) (Figure SPM.7). In the majority of low-stabilization scenarios, the share of low-carbon electricity supply (comprising renewable energy (RE), nuclear and CCS) increases 

from the current share of approximately 30% to more than 80% by 2050, and fossil fuel power generation without CCS 

is phased out almost entirely by 2100 (Figure SPM. 7). [6.8, 7.11, Figures 7.14, TS.18]

Since AR4, many RE technologies have demonstrated substantial performance improvements and cost reductions, and a growing number of RE technologies have achieved a level of maturity to enable deployment at 

significant scale (robust evidence, high agreement). Regarding electricity generation alone, RE accounted for just over 

half of the new electricity-generating capacity added globally in 2012, led by growth in wind, hydro and solar power. 

However, many RE technologies still need direct and/or indirect support, if their market shares are to be significantly 

increased; RE technology policies have been successful in driving recent growth of RE. Challenges for integrating RE into 

energy systems and the associated costs vary by RE technology, regional circumstances, and the characteristics of the 

existing background energy system (medium evidence, medium agreement). [7.5.3, 7.6.1, 7.8.2, 7.12, Table 7.1]

Nuclear energy is a mature low-GHG emission source of baseload power, but its share of global electricity 

generation has been declining (since 1993). Nuclear energy could make an increasing contribution to lowcarbon energy supply, but a variety of barriers and risks exist (robust evidence, high agreement). Those include: 

23 Structural changes refer to systems transformations whereby some components are either replaced or potentially substituted by other components (see WGIII AR5 Glossary).

SPM.4.2.2
22

SPM

Summary for Policymakers

operational risks, and the associated concerns, uranium mining risks, financial and regulatory risks, unresolved waste 

management issues, nuclear weapon proliferation concerns, and adverse public opinion (robust evidence, high agreement). New fuel cycles and reactor technologies addressing some of these issues are being investigated and progress in 

research and development has been made concerning safety and waste disposal. [7.5.4, 7.8, 7.9, 7.12, Figure TS.19]

GHG emissions from energy supply can be reduced significantly by replacing current world average coalfired power plants with modern, highly efficient natural gas combined-cycle power plants or combined heat 

and power plants, provided that natural gas is available and the fugitive emissions associated with extraction and supply are low or mitigated (robust evidence, high agreement). In mitigation scenarios reaching about 

450 ppm CO2eq concentrations by 2100, natural gas power generation without CCS acts as a bridge technology, with 

deployment increasing before peaking and falling to below current levels by 2050 and declining further in the second 

half of the century (robust evidence, high agreement). [7.5.1, 7.8, 7.9, 7.11, 7.12]

Carbon dioxide capture and storage (CCS) technologies could reduce the lifecycle GHG emissions of fossil fuel power plants (medium evidence, medium agreement). While all components of integrated CCS systems exist 

and are in use today by the fossil fuel extraction and refining industry, CCS has not yet been applied at scale to a large, 

operational commercial fossil fuel power plant. CCS power plants could be seen in the market if this is incentivized by 

regulation and/or if they become competitive with their unabated counterparts, for instance, if the additional investment 

and operational costs, caused in part by efficiency reductions, are compensated by sufficiently high carbon prices (or 

direct financial support). For the large-scale future deployment of CCS, well-defined regulations concerning short- and 

long-term responsibilities for storage are needed as well as economic incentives. Barriers to large-scale deployment of 

CCS technologies include concerns about the operational safety and long-term integrity of CO2 storage as well as transport risks. There is, however, a growing body of literature on how to ensure the integrity of CO2 wells, on the potential 

consequences of a pressure build-up within a geologic formation caused by CO2 storage (such as induced seismicity), 

and on the potential human health and environmental impacts from CO2 that migrates out of the primary injection zone 

(limited evidence, medium agreement). [7.5.5., 7.8, 7.9, 7.11, 7.12, 11.13]

Combining bioenergy with CCS (BECCS) offers the prospect of energy supply with large-scale net negative 

emissions which plays an important role in many low-stabilization scenarios, while it entails challenges and 

risks (limited evidence, medium agreement). These challenges and risks include those associated with the upstream 

large-scale provision of the biomass that is used in the CCS facility as well as those associated with the CCS technology 

itself. [7.5.5, 7.9, 11.13]

Energy end-use sectors

Transport

The transport sector accounted for 27% of final energy use and 6.7 GtCO2 direct emissions in 2010, with 

baseline CO2 emissions projected to approximately double by 2050 (medium evidence, medium agreement). This 

growth in CO2 emissions from increasing global passenger and freight activity could partly offset future mitigation measures that include fuel carbon and energy intensity improvements, infrastructure development, behavioural change and 

comprehensive policy implementation (high confidence). Overall, reductions in total transport CO2 emissions of 15–40% 

compared to baseline growth could be achieved in 2050 (medium evidence, medium agreement). (Figure SPM.7) [6.8, 

8.1, 8.2, 8.9, 8.10]

Technical and behavioural mitigation measures for all transport modes, plus new infrastructure and urban 

redevelopment investments, could reduce final energy demand in 2050 by around 40% below the baseline, 

with the mitigation potential assessed to be higher than reported in the AR4 (robust evidence, medium agreement). Projected energy efficiency and vehicle performance improvements range from 30–50% in 2030 relative to 2010 

depending on transport mode and vehicle type (medium evidence, medium agreement). Integrated urban planning, 

SPM.4.2.3
23

S

Summary for Policymakers

transit-oriented development, more compact urban form that supports cycling and walking, can all lead to modal shifts 

as can, in the longer term, urban redevelopment and investments in new infrastructure such as high-speed rail systems 

that reduce short-haul air travel demand (medium evidence, medium agreement). Such mitigation measures are challenging, have uncertain outcomes, and could reduce transport GHG emissions by 20–50% in 2050 compared to baseline 

(limited evidence, low agreement). (Figure SPM.8 top panel) [8.2, 8.3, 8.4, 8.5, 8.6, 8.7, 8.8, 8.9, 12.4, 12.5]

Strategies to reduce the carbon intensities of fuel and the rate of reducing carbon intensity are constrained 

by challenges associated with energy storage and the relatively low energy density of low-carbon transport 

fuels (medium confidence). Integrated and sectoral studies broadly agree that opportunities for switching to low-carbon 

fuels exist in the near term and will grow over time. Methane-based fuels are already increasing their share for road 

vehicles and waterborne craft. Electricity produced from low-carbon sources has near-term potential for electric rail and 

short-to medium-term potential as electric buses, light-duty and 2-wheel road vehicles are deployed. Hydrogen fuels from 

low-carbon sources constitute longer-term options. Commercially available liquid and gaseous biofuels already provide 

co-benefits together with mitigation options that can be increased by technology advances. Reducing transport emissions 

of particulate matter (including black carbon), tropospheric ozone and aerosol precursors (including NOx) can have human 

health and mitigation co-benefits in the short term (medium evidence, medium agreement). [8.2, 8.3, 11.13, Figure TS.20, 

right panel]

The cost-effectiveness of different carbon reduction measures in the transport sector varies significantly 

with vehicle type and transport mode (high confidence). The levelized costs of conserved carbon can be very low or 

negative for many short-term behavioural measures and efficiency improvements for light- and heavy-duty road vehicles 

and waterborne craft. In 2030, for some electric vehicles, aircraft and possibly high-speed rail, levelized costs could be 

more than USD100/tCO2 avoided (limited evidence, medium agreement). [8.6, 8.8, 8.9, Figures TS.21, TS.22]

Regional differences influence the choice of transport mitigation options (high confidence). Institutional, legal, 

financial and cultural barriers constrain low-carbon technology uptake and behavioural change. Established infrastructure 

may limit the options for modal shift and lead to a greater reliance on advanced vehicle technologies; a slowing of growth 

in light-duty vehicle demand is already evident in some OECD countries. For all economies, especially those with high 

rates of urban growth, investment in public transport systems and low-carbon infrastructure can avoid lock-in to carbonintensive modes. Prioritizing infrastructure for pedestrians and integrating non-motorized and transit services can create 

economic and social co-benefits in all regions (medium evidence, medium agreement). [8.4, 8.8, 8.9, 14.3, Table 8.3]

Mitigation strategies, when associated with non-climate policies at all government levels, can help decouple 

transport GHG emissions from economic growth in all regions (medium confidence). These strategies can help 

reduce travel demand, incentivise freight businesses to reduce the carbon intensity of their logistical systems and induce 

modal shifts, as well as provide co-benefits including improved access and mobility, better health and safety, greater 

energy security, and cost and time savings (medium evidence, high agreement). [8.7, 8.10]

Buildings 

In 2010, the buildings sector24 accounted for around 32% final energy use and 8.8 GtCO2 emissions, including 

direct and indirect emissions, with energy demand projected to approximately double and CO2 emissions to 

increase by 50–150% by mid-century in baseline scenarios (medium evidence, medium agreement). This energy 

demand growth results from improvements in wealth, lifestyle change, access to modern energy services and adequate 

housing, and urbanisation. There are significant lock-in risks associated with the long lifespans of buildings and related 

infrastructure, and these are especially important in regions with high construction rates (robust evidence, high agreement). [9.4, Figure SPM.7]

24 The buildings sector covers the residential, commercial, public and services sectors; emissions from construction are accounted for in the industry 

sector.
24

SPM

Summary for Policymakers

Recent advances in technologies, know-how and policies provide opportunities to stabilize or reduce global 

buildings sector energy use by mid-century (robust evidence, high agreement). For new buildings, the adoption of 

very low energy building codes is important and has progressed substantially since AR4. Retrofits form a key part of 

the mitigation strategy in countries with established building stocks, and reductions of heating/cooling energy use by 

50–90% in individual buildings have been achieved. Recent large improvements in performance and costs make very low 

energy construction and retrofits economically attractive, sometimes even at net negative costs. [9.3]

Lifestyle, culture and behaviour significantly influence energy consumption in buildings (limited evidence, high 

agreement). A three-to five-fold difference in energy use has been shown for provision of similar building-related energy 

service levels in buildings. For developed countries, scenarios indicate that lifestyle and behavioural changes could reduce 

energy demand by up to 20% in the short term and by up to 50% of present levels by mid-century. In developing countries, integrating elements of traditional lifestyles into building practices and architecture could facilitate the provision of 

high levels of energy services with much lower energy inputs than baseline. [9.3]

Most mitigation options for buildings have considerable and diverse co-benefits in addition to energy cost 

savings (robust evidence, high agreement). These include improvements in energy security, health (such as from cleaner 

wood-burning cookstoves), environmental outcomes, workplace productivity, fuel poverty reductions and net employment 

gains. Studies which have monetized co-benefits often find that these exceed energy cost savings and possibly climate 

benefits (medium evidence, medium agreement). [9.6, 9.7, 3.6.3]

Strong barriers, such as split incentives (e.g., tenants and builders), fragmented markets and inadequate 

access to information and financing, hinder the market-based uptake of cost-effective opportunities. Barriers 

can be overcome by policy interventions addressing all stages of the building and appliance lifecycles (robust evidence, 

high agreement). [9.8, 9.10, 16, Box 3.10]

The development of portfolios of energy efficiency policies and their implementation has advanced considerably since AR4. Building codes and appliance standards, if well designed and implemented, have been among 

the most environmentally and cost-effective instruments for emission reductions (robust evidence, high agreement). In some developed countries they have contributed to a stabilization of, or reduction in, total energy demand for 

buildings. Substantially strengthening these codes, adopting them in further jurisdictions, and extending them to more 

building and appliance types, will be a key factor in reaching ambitious climate goals. [9.10, 2.6.5.3]

Industry 

In 2010, the industry sector accounted for around 28% of final energy use, and 13 GtCO2 emissions, including 

direct and indirect emissions as well as process emissions, with emissions projected to increase by 50–150% 

by 2050 in the baseline scenarios assessed in AR5, unless energy efficiency improvements are accelerated 

significantly (medium evidence, medium agreement). Emissions from industry accounted for just over 30% of global 

GHG emissions in 2010 and are currently greater than emissions from either the buildings or transport end-use sectors. 

(Figures SPM.2, SPM.7) [10.3]

The energy intensity of the industry sector could be directly reduced by about 25% compared to the current level through the wide-scale upgrading, replacement and deployment of best available technologies, 

particularly in countries where these are not in use and in non-energy intensive industries (high agreement, 

robust evidence). Additional energy intensity reductions of about 20% may potentially be realized through innovation

(limited evidence, medium agreement). Barriers to implementing energy efficiency relate largely to initial investment costs 

and lack of information. Information programmes are a prevalent approach for promoting energy efficiency, followed by 

economic instruments, regulatory approaches and voluntary actions. [10.7, 10.9, 10.11]
25

S

Summary for Policymakers

Improvements in GHG emission efficiency and in the efficiency of material use, recycling and re-use of 

materials and products, and overall reductions in product demand (e.g., through a more intensive use of 

products) and service demand could, in addition to energy efficiency, help reduce GHG emissions below the 

baseline level in the industry sector (medium evidence, high agreement). Many emission-reducing options are costeffective, profitable and associated with multiple co-benefits (better environmental compliance, health benefits etc.). In 

the long term, a shift to low-carbon electricity, new industrial processes, radical product innovations (e.g., alternatives 

to cement), or CCS (e.g., to mitigate process emissions) could contribute to significant GHG emission reductions. Lack of 

policy and experiences in material and product service efficiency are major barriers. [10.4, 10.7, 10.8, 10.11]

CO2 emissions dominate GHG emissions from industry, but there are also substantial mitigation opportunities 

for non-CO2 gases (robust evidence, high agreement). CH4, N2O and fluorinated gases from industry accounted for emissions of 0.9 GtCO2eq in 2010. Key mitigation opportunities include, e.g., the reduction of hydrofluorocarbon emissions by 

process optimization and refrigerant recovery, recycling and substitution, although there are barriers. [Tables 10.2, 10.7]

Systemic approaches and collaborative activities across companies and sectors can reduce energy and material consumption and thus GHG emissions (robust evidence, high agreement). The application of cross-cutting technologies (e.g., efficient motors) and measures (e.g., reducing air or steam leaks) in both large energy intensive industries 

and small and medium enterprises can improve process performance and plant efficiency cost-effectively. Cooperation 

across companies (e.g., in industrial parks) and sectors could include the sharing of infrastructure, information, and 

waste heat utilization. [10.4, 10.5]

Important options for mitigation in waste management are waste reduction, followed by re-use, recycling 

and energy recovery (robust evidence, high agreement). Waste and wastewater accounted for 1.5 GtCO2eq in 2010. 

As the share of recycled or reused material is still low (e.g., globally, around 20% of municipal solid waste is recycled), 

waste treatment technologies and recovering energy to reduce demand for fossil fuels can result in significant direct 

emission reductions from waste disposal. [10.4, 10.14]

Agriculture, Forestry and Other Land Use (AFOLU) 

The AFOLU sector accounts for about a quarter (~10–12GtCO2eq/yr) of net anthropogenic GHG emissions 

mainly from deforestation, agricultural emissions from soil and nutrient management and livestock (medium 

evidence, high agreement). Most recent estimates indicate a decline in AFOLU CO2 fluxes, largely due to decreasing 

deforestation rates and increased afforestation. However, the uncertainty in historical net AFOLU emissions is larger 

than for other sectors, and additional uncertainties in projected baseline net AFOLU emissions exist. Nonetheless, in the 

future, net annual baseline CO2 emissions from AFOLU are projected to decline, with net emissions potentially less than 

half the 2010 level by 2050 and the possibility of the AFOLU sectors becoming a net CO2 sink before the end of century 

(medium evidence, high agreement). (Figure SPM. 7) [6.3.1.4, 11.2, Figure 6.5]

AFOLU plays a central role for food security and sustainable development. The most cost-effective mitigation options in forestry are afforestation, sustainable forest management and reducing deforestation, with 

large differences in their relative importance across regions. In agriculture, the most cost-effective mitigation options are cropland management, grazing land management, and restoration of organic soils (medium 

evidence, high agreement). The economic mitigation potential of supply-side measures is estimated to be 7.2 to 11 

GtCO2eq/year25 in 2030 for mitigation efforts consistent with carbon prices26 up to 100 USD/tCO2eq, about a third of 

which can be achieved at a <20 USD/tCO2eq (medium evidence, medium agreement). There are potential barriers to 

25 Full range of all studies: 0.49–11 GtCO2eq/year 26 In many models that are used to assess the economic costs of mitigation, carbon price is often used as a proxy to represent the level of effort in 

mitigation policies (see WGIII AR5 Glossary).

SPM.4.2.4
26

SPM

Summary for Policymakers

implementation of available mitigation options [11.7, 11.8]. Demand-side measures, such as changes in diet and reductions of losses in the food supply chain, have a significant, but uncertain, potential to reduce GHG emissions from food 

production (medium evidence, medium agreement). Estimates vary from roughly 0.76–8.6 GtCO2eq/yr by 2050 (limited 

evidence, medium agreement). [11.4, 11.6, Figure 11.14]

Policies governing agricultural practices and forest conservation and management are more effective when 

involving both mitigation and adaptation. Some mitigation options in the AFOLU sector (such as soil and forest 

carbon stocks) may be vulnerable to climate change (medium evidence, high agreement). When implemented sustainably, 

activities to reduce emissions from deforestation and forest degradation (REDD+27 is an example designed to be sustainable) are cost-effective policy options for mitigating climate change, with potential economic, social and other environmental and adaptation co-benefits (e.g., conservation of biodiversity and water resources, and reducing soil erosion) 

(limited evidence, medium agreement). [11.3.2, 11.10]

Bioenergy can play a critical role for mitigation, but there are issues to consider, such as the sustainability of 

practices and the efficiency of bioenergy systems (robust evidence, medium agreement) [11.4.4, Box 11.5, 11.13.6, 

11.13.7]. Barriers to large-scale deployment of bioenergy include concerns about GHG emissions from land, food security, 

water resources, biodiversity conservation and livelihoods. The scientific debate about the overall climate impact related 

to land-use competition effects of specific bioenergy pathways remains unresolved (robust evidence, high agreement). 

[11.4.4, 11.13] Bioenergy technologies are diverse and span a wide range of options and technology pathways. Evidence 

suggests that options with low lifecycle emissions (e.g., sugar cane, Miscanthus, fast growing tree species, and sustainable use of biomass residues), some already available, can reduce GHG emissions; outcomes are site-specific and rely 

on efficient integrated ‘biomass-to-bioenergy systems’, and sustainable land-use management and governance. In some 

regions, specific bioenergy options, such as improved cookstoves, and small-scale biogas and biopower production, could 

reduce GHG emissions and improve livelihoods and health in the context of sustainable development (medium evidence, 

medium agreement). [11.13]

Human settlements, infrastructure and spatial planning 

Urbanization is a global trend and is associated with increases in income, and higher urban incomes are correlated with higher consumption of energy and GHG emissions (medium evidence, high agreement). As of 2011, 

more than 52% of the global population lives in urban areas. In 2006, urban areas accounted for 67–76% of energy use 

and 71–76% of energy-related CO2 emissions. By 2050, the urban population is expected to increase to 5.6–7.1 billion, 

or 64–69% of world population. Cities in non-Annex I countries generally have higher levels of energy use compared to 

the national average, whereas cities in Annex I countries generally have lower energy use per capita than national averages (medium evidence, medium agreement). [12.2, 12.3]

The next two decades present a window of opportunity for mitigation in urban areas, as a large portion of 

the world’s urban areas will be developed during this period (limited evidence, high agreement). Accounting for 

trends in declining population densities, and continued economic and population growth, urban land cover is projected to 

expand by 56–310% between 2000 and 2030. [12.2, 12.3, 12.4, 12.8]

Mitigation options in urban areas vary by urbanization trajectories and are expected to be most effective 

when policy instruments are bundled (robust evidence, high agreement). Infrastructure and urban form are strongly 

interlinked, and lock-in patterns of land use, transport choice, housing, and behaviour. Effective mitigation strategies 

involve packages of mutually reinforcing policies, including co-locating high residential with high employment densities, 

achieving high diversity and integration of land uses, increasing accessibility and investing in public transport and other 

demand management measures. [8.4, 12.3, 12.4, 12.5, 12.6]

27 See WGIII AR5 Glossary.

SPM.4.2.5
27

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Summary for Policymakers

The largest mitigation opportunities with respect to human settlements are in rapidly urbanizing areas 

where urban form and infrastructure are not locked in, but where there are often limited governance, technical, financial, and institutional capacities (robust evidence, high agreement). The bulk of urban growth is expected 

in small- to medium-size cities in developing countries. The feasibility of spatial planning instruments for climate change 

mitigation is highly dependent on a city’s financial and governance capability. [12.6, 12.7]

Thousands of cities are undertaking climate action plans, but their aggregate impact on urban emissions 

is uncertain (robust evidence, high agreement). There has been little systematic assessment on their implementation, 

the extent to which emission reduction targets are being achieved, or emissions reduced. Current climate action plans 

focus largely on energy efficiency. Fewer climate action plans consider land-use planning strategies and cross-sectoral 

measures to reduce sprawl and promote transit-oriented development28. [12.6, 12.7, 12.9]

Successful implementation of urban-scale climate change mitigation strategies can provide co-benefits 

(robust evidence, high agreement). Urban areas throughout the world continue to struggle with challenges, including 

ensuring access to energy, limiting air and water pollution, and maintaining employment opportunities and competitiveness. Action on urban-scale mitigation often depends on the ability to relate climate change mitigation efforts to local 

co-benefits (robust evidence, high agreement). [12.5, 12.6, 12.7, 12.8]

Mitigation policies and institutions 

Sectoral and national policies

Substantial reductions in emissions would require large changes in investment patterns. Mitigation scenarios 

in which policies stabilize atmospheric concentrations (without overshoot) in the range from 430 to 530 ppm CO2eq by 

2100 lead to substantial shifts in annual investment flows during the period 2010–2029 compared to baseline scenarios 

(Figure SPM.9). Over the next two decades (2010 to 2029), annual investment in conventional fossil fuel technologies 

associated with the electricity supply sector is projected to decline by about USD 30 (2–166) billion (median: −20% 

compared to 2010) while annual investment in low-carbon electricity supply (i.e., renewables, nuclear and electricity generation with CCS) is projected to rise by about USD 147 (31–360) billion (median: +100% compared to 2010) 

(limited evidence, medium agreement). For comparison, global total annual investment in the energy system is presently 

about USD 1200 billion. In addition, annual incremental energy efficiency investments in transport, buildings and industry is projected to increase by about USD 336 (1–641) billion (limited evidence, medium agreement), frequently involving 

modernization of existing equipment. [13.11, 16.2.2]

There is no widely agreed definition of what constitutes climate finance, but estimates of the financial flows 

associated with climate change mitigation and adaptation are available. Published assessments of all current 

annual financial flows whose expected effect is to reduce net GHG emissions and/or to enhance resilience to climate 

change and climate variability show USD 343 to 385 billion per year globally (medium confidence) [Box TS.14]. Most of 

this goes to mitigation. Out of this, total public climate finance that flowed to developing countries is estimated to be 

between USD 35 and 49 billion/yr in 2011 and 2012 (medium confidence). Estimates of international private climate 

finance flowing to developing countries range from USD 10 to 72 billion/yr including foreign direct investment as equity 

and loans in the range of USD 10 to 37 billion/yr over the period of 2008–2011 (medium confidence). [16.2.2]

28 See WGIII AR5 Glossary.

SPM.5

SPM.5.1
28

SPM

Summary for Policymakers

Figure SPM.9 | Change in annual investment fl ows from the average baseline level over the next two decades (2010 – 2029) for mitigation scenarios that stabilize concentrations 

within the range of approximately 430 – 530 ppm CO2eq by 2100. Investment changes are based on a limited number of model studies and model comparisons. Total electricity generation (leftmost column) is the sum of renewables, nuclear, power plants with CCS and fossil fuel power plants without CCS. The vertical bars indicate the range between minimum 

and maximum estimate; the horizontal bar indicates the median. Proximity to this median value does not imply higher likelihood because of the different degree of aggregation of 

model results, the low number of studies available and different assumptions in the different studies considered. The numbers in the bottom row show the total number of studies in the literature used for the assessment. This underscores that investment needs are still an evolving area of research that relatively few studies have examined. [Figure 16.3] 

-400

-300

-200

-100

0

100

200

300

400

500

600

700

800

Power Plants

with CCS

Renewables Energy Efficiency

Across Sectors

Extraction of 

Fossil Fuels

Fossil Fuel

Power Plants

without CCS

Total Electricity Nuclear

Generation

# of Studies: 4 4 5 4 4 5 4 4 5 4 4 5 4 4 5 4 4 5 3 3 4 Changes in Annual Investment Flows 2010 – 2029 [Billion USD2010/yr]

Max 

Median

Mean

Min 

OECD non-OECD World

There has been a considerable increase in national and sub-national mitigation plans and strategies since AR4. 

In 2012, 67 % of global GHG emissions were subject to national legislation or strategies versus 45 % in 2007. However, 

there has not yet been a substantial deviation in global emissions from the past trend [Figure 1.3c]. These plans and 

strategies are in their early stages of development and implementation in many countries, making it diffi cult to assess their 

aggregate impact on future global emissions (medium evidence, high agreement). [14.3.4, 14.3.5, 15.1, 15.2]

Since AR4, there has been an increased focus on policies designed to integrate multiple objectives, increase 

co-benefi ts and reduce adverse side-effects (high confi dence). Governments often explicitly reference co-benefi ts in 

climate and sectoral plans and strategies. The scientifi c literature has sought to assess the size of co-benefi ts (see Section 

SPM.4.1) and the greater political feasibility and durability of policies that have large co-benefi ts and small adverse sideeffects. [4.8, 5.7, 6.6, 13.2, 15.2] Despite the growing attention in policymaking and the scientifi c literature since AR4, the 

analytical and empirical underpinnings for understanding many of the interactive effects are under-developed [1.2, 3.6.3, 

4.2, 4.8, 5.7, 6.6].
29

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Summary for Policymakers

Sector-specific policies have been more widely used than economy-wide policies (medium evidence, high agreement). Although most economic theory suggests that economy-wide policies for the singular objective of mitigation 

would be more cost-effective than sector-specific policies, since AR4 a growing number of studies has demonstrated that 

administrative and political barriers may make economy-wide policies harder to design and implement than sectorspecific policies. The latter may be better suited to address barriers or market failures specific to certain sectors, and may 

be bundled in packages of complementary policies. [6.3.6.5, 8.10, 9.10, 10.10, 15.2, 15.5, 15.8, 15.9]

Regulatory approaches and information measures are widely used, and are often environmentally effective (medium evidence, medium agreement). Examples of regulatory approaches include energy efficiency standards; 

examples of information programmes include labelling programmes that can help consumers make better-informed decisions. While such approaches have often been found to have a net social benefit, the scientific literature is divided on the 

extent to which such policies can be implemented with negative private costs to firms and individuals. [Box 3.10, 15.5.5, 

15.5.6] There is general agreement that rebound effects exist, whereby higher efficiency can lead to lower energy prices 

and greater consumption, but there is low agreement in the literature on the magnitude [3.9.5, 5.7.2, 14.4.2, 15.5.4].

Since AR4, cap and trade systems for GHGs have been established in a number of countries and regions. 

Their short-run environmental effect has been limited as a result of loose caps or caps that have not proved 

to be constraining (limited evidence, medium agreement). This was related to factors such as the financial and economic crisis that reduced energy demand, new energy sources, interactions with other policies, and regulatory uncertainty. In principle, a cap and trade system can achieve mitigation in a cost-effective way; its implementation depends 

on national circumstances. Though earlier programmes relied almost exclusively on grandfathering (free allocation of 

permits), auctioning permits is increasingly applied. If allowances are auctioned, revenues can be used to address other 

investments with a high social return, and/or reduce the tax and debt burden. [14.4.2, 15.5.3]

In some countries, tax-based policies specifically aimed at reducing GHG emissions—alongside technology 

and other policies—have helped to weaken the link between GHG emissions and GDP (high confidence). In 

a large group of countries, fuel taxes (although not necessarily designed for the purpose of mitigation) have effects 

that are akin to sectoral carbon taxes [Table 15.2]. The demand reduction in transport fuel associated with a 1% price 

increase is 0.6% to 0.8% in the long run, although the short-run response is much smaller [15.5.2]. In some countries 

revenues are used to reduce other taxes and/or to provide transfers to low-income groups. This illustrates the general 

principle that mitigation policies that raise government revenue generally have lower social costs than approaches 

which do not. While it has previously been assumed that fuel taxes in the transport sector are regressive, there have 

been a number of other studies since AR4 that have shown them to be progressive, particularly in developing countries 

(medium evidence, medium agreement). [3.6.3, 14.4.2, 15.5.2]

The reduction of subsidies for GHG-related activities in various sectors can achieve emission reductions, 

depending on the social and economic context (high confidence). While subsidies can affect emissions in many sectors, most of the recent literature has focused on subsidies for fossil fuels. Since AR4 a small but growing literature based 

on economy-wide models has projected that complete removal of subsidies for fossil fuels in all countries could result in 

reductions in global aggregate emissions by mid-century (medium evidence, medium agreement) [7.12, 13.13, 14.3.2, 

15.5.2]. Studies vary in methodology, the type and definition of subsidies and the time frame for phase out considered. 

In particular, the studies assess the impacts of complete removal of all fossil fuel subsidies without seeking to assess 

which subsidies are wasteful and inefficient, keeping in mind national circumstances. Although political economy barriers are substantial, some countries have reformed their tax and budget systems to reduce fuel subsidies. To help reduce 

possible adverse effects on lower-income groups who often spend a large fraction of their income on energy services, 

many governments have utilized lump-sum cash transfers or other mechanisms targeted on the poor. [15.5.2]

Interactions between or among mitigation policies may be synergistic or may have no additive effect on 

reducing emissions (medium evidence, high agreement). For instance, a carbon tax can have an additive environmental effect to policies such as subsidies for the supply of RE. By contrast, if a cap and trade system has a binding cap 
30

SPM

Summary for Policymakers

(sufficiently stringent to affect emission-related decisions), then other policies such as RE subsidies have no further impact 

on reducing emissions within the time period that the cap applies (although they may affect costs and possibly the viability of more stringent future targets) (medium evidence, high agreement). In either case, additional policies may be needed 

to address market failures relating to innovation and technology diffusion. [15.7]

Some mitigation policies raise the prices for some energy services and could hamper the ability of societies to expand access to modern energy services to underserved populations (low confidence). These potential 

adverse side-effects can be avoided with the adoption of complementary policies (medium confidence). Most 

notably, about 1.3 billion people worldwide do not have access to electricity and about 3 billion are dependent on traditional solid fuels for cooking and heating with severe adverse effects on health, ecosystems and development. Providing 

access to modern energy services is an important sustainable development objective. The costs of achieving nearly universal access to electricity and clean fuels for cooking and heating are projected to be between USD 72 and 95 billion per 

year until 2030 with minimal effects on GHG emissions (limited evidence, medium agreement). A transition away from the 

use of traditional biomass29 and the more efficient combustion of solid fuels reduce air pollutant emissions, such as sulfur 

dioxide (SO2), nitrogen oxides (NOx), carbon monoxide (CO), and black carbon (BC), and thus yield large health benefits 

(high confidence). [4.3, 6.6, 7.9, 9.3, 9.7, 11.13.6, 16.8]

Technology policy complements other mitigation policies (high confidence). Technology policy includes technologypush (e.g., publicly funded R&D) and demand-pull (e.g., governmental procurement programmes). Such policies address 

market failures related to innovation and technology diffusion. [3.11, 15.6] Technology support policies have promoted 

substantial innovation and diffusion of new technologies, but the cost-effectiveness of such policies is often difficult to 

assess [2.6.5, 7.12, 9.10]. Nevertheless, program evaluation data can provide empirical evidence on the relative effectiveness of different policies and can assist with policy design [15.6.5].

In many countries, the private sector plays central roles in the processes that lead to emissions as well as to 

mitigation. Within appropriate enabling environments, the private sector, along with the public sector, can 

play an important role in financing mitigation (medium evidence, high agreement). The share of total mitigation 

finance from the private sector, acknowledging data limitations, is estimated to be on average between two-thirds and 

three-fourths on the global level (2010–2012) (limited evidence, medium agreement). In many countries, public finance 

interventions by governments and national and international development banks encourage climate investments by the 

private sector [16.2.1] and provide finance where private sector investment is limited. The quality of a country’s enabling 

environment includes the effectiveness of its institutions, regulations and guidelines regarding the private sector, security 

of property rights, credibility of policies and other factors that have a substantial impact on whether private firms invest in 

new technologies and infrastructures [16.3]. Dedicated policy instruments, for example, credit insurance, power purchase 

agreements and feed-in tariffs, concessional finance or rebates, provide an incentive for investment by lowering risks for 

private actors [16.4].

International cooperation

The United Nations Framework Convention on Climate Change (UNFCCC) is the main multilateral forum 

focused on addressing climate change, with nearly universal participation. Other institutions organized at different levels of governance have resulted in diversifying international climate change cooperation. [13.3.1, 13.4.1.4, 13.5]

Existing and proposed international climate change cooperation arrangements vary in their focus and degree 

of centralization and coordination. They span: multilateral agreements, harmonized national policies and decentralized but coordinated national policies, as well as regional and regionally-coordinated policies. [Figure TS.38, 13.4.1, 

13.13.2, 14.4]

29 See WGIII AR5 Glossary.

SPM.5.2
31

S

Summary for Policymakers

The Kyoto Protocol offers lessons towards achieving the ultimate objective of the UNFCCC, particularly with 

respect to participation, implementation, flexibility mechanisms, and environmental effectiveness (medium 

evidence, low agreement). [5.3.3, 13.3.4, 13.7.2, 13.13.1.1, 13.13.1.2, 14.3.7.1, Table TS.9]

UNFCCC activities since 2007 have led to an increasing number of institutions and other arrangements for 

international climate change cooperation. [13.5.1.1, 13.13.1.3, 16.2.1]

Policy linkages among regional, national, and sub-national climate policies offer potential climate change 

mitigation and adaptation benefits (medium evidence, medium agreement). Linkages can be established between 

national policies, various instruments, and through regional cooperation. [13.3.1, 13.5.3, 13.6, 13.7, 13.13.2.3, 14.4, 

Figure 13.4]

Various regional initiatives between the national and global scales are either being developed or implemented, but their impact on global mitigation has been limited to date (medium confidence). Many climate 

policies can be more effective if implemented across geographical regions. [13.13, 13.6, 14.4, 14.5]